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Comparative Abuse Liability of GHB and Ethanol in Humans REF 4.docx

Comparative Abuse Liability of GHB and Ethanol in Humans

Matthew W. Johnson and Roland R. Griffiths

Johns Hopkins University School of Medicine

Gamma-hydroxybutyric acid (GHB; sodium oxybate) is approved for narcolepsy symptom treatment, and

it is also abused. This study compared the participant-rated, observer-rated effects, motor/cognitive,

physiological, and reinforcing effects of GHB and ethanol in participants with histories of sedative

(including alcohol) abuse. Fourteen participants lived on a residential unit for

1 month. Sessions were

conducted Monday through Friday. Measures were taken before and repeatedly up to 24 hours after drug

administration. Participants were administered GHB (1, 2, 4, 6, 8, and 10g/70kg), ethanol (12, 24, 48, 72,

96, and 120g/70kg), or placebo in a double-blind, within-subjects design. For safety, GHB and ethanol

were administered in an ascending dose sequence, with placebos and both drugs intermixed across

sessions. The sequence for each drug was stopped if significant impairment or intolerable effects

occurred. Only 9 and 10 participants received the full dose range for GHB and ethanol, respectively. The

highest doses of GHB and ethanol showed onset within 30 minutes, with peak effects at 60 minutes. GHB

effects dissipated between 4 and 6 hours, whereas ethanol effects dissipated between 6 and 8 hours.

Dose-related effects were observed for both drugs on a variety of measures assessing sedative drug

effects, abuse liability, performance impairment, and physiological effects. Within-session measures of

abuse liability were similar between the two drugs. However, postsession measures of abuse liability,

including a direct preference test between the highest tolerated doses of each drug, suggested somewhat

greater abuse liability for GHB, most likely as a result of the delayed aversive ethanol effects (e.g.,

headache).

Keywords:

Gamma-hydroxybutyric acid, GHB, sodium oxybate, ethanol, alcohol

Gamma-hydroxybutyric acid (GHB; sodium oxybate) is a nat-

urally occurring, biologically active metabolite of the neurotrans-

mitter gamma-aminobutyric acid (GABA), with low affinity and

efficacy for GABA-B receptors (

Lingenhoehl et al., 1999

;

Ma-

thivet, Bernasconi, De Barry, Marescaux, & Bittiger, 1997

) and

high affinity for the GHB receptor (

Hechler, Gobaille, & Maitre,

1992

). GHB is currently marketed in the United States for the

treatment of cataplexy associated with narcolepsy and excessive

daytime sleepiness associated with narcolepsy. In addition, GHB

has been used as a recreational drug. GHB use has been associated

with emergency department visits, with over 1,000 per year for the

years 2004–2009 (

Substance Abuse & Mental Health Services

Administration, 2011

). Epidemiology and case reports show that

GHB is used as a recreational drug, with some users meeting

Diagnostic and Statistical Manual of Mental Disorders

, fourth

edition (

DSM–IV

) criteria for dependence (

Craig, Gomez, McMa-

nus, & Bania, 2000

;

Degenhardt, Darke, & Dillon, 2002

;

Galloway

et al., 1997

;

McDaniel & Miotto, 2001

).

Understanding the abuse liability relative to other drugs of abuse

is critical given the importance of its medical application and

substantial concerns over its abuse. As an example of the com-

plexity in balancing these issues, in the United States GHB is

controlled on a bifurcated schedule as a controlled substance.

Under this framework, GHB is regulated as a schedule I drug, with

the exception that the pharmaceutical product Xyrem, which con-

tains GHB as the active ingredient, is regulated as a schedule III

drug. Xyrem is approved for the treatment of cataplexy associated

with narcolepsy and excessive daytime sleepiness associated with

narcolepsy.

GHB is reportedly often consumed to increase sociability (

Mi-

otto et al., 2001

;

Stein et al., 2011

;

Sumnall, Woolfall, Edwards,

Cole, & Beynon, 2008

) with repeated administrations over the

course of an evening to maintain a desired level of effect (

Dean,

Morgenthaler, & Fowkes, 1997

). These use patterns, along with its

This article was published Online First February 18, 2013.

Matthew W. Johnson, Behavioral Pharmacology Research Unit, Depart-

ment of Psychiatry and Behavioral Sciences, Johns Hopkins University

School of Medicine; Roland R. Griffiths, Behavioral Pharmacology Re-

search Unit, Department of Psychiatry and Behavioral Sciences, and De-

partment of Neuroscience, Johns Hopkins University School of Medicine.

We thank Eric C. Strain, MD, Annie Umbricht, MD, and the medical

staff at the Behavioral Pharmacology Research Unit for medical screening

and medical coverage, Benjamin McKay and Margaret Klinedinst for

collecting and organizing the data. GHB and sodium citrate (GHB placebo)

solutions were kindly provided by Orphan Medical, Minnetonka, MN,

currently known as Jazz Pharmaceuticals, Palo Alto, CA. This work was

supported by the National Institute on Drug Abuse (NIDA) through

R01DA003889. Matthew Johnson has consulted for Eli Lilly on issues

related to drug abuse liability. During the past 3 years, on issues related to

drug abuse liability, Roland Griffiths has been a consultant to or has

received contracts or grants from the following: Alexza Pharmaceuticals,

Bristol-Myers Squibb, Hoffman-La Roche Inc., Jazz Pharmaceuticals Inc.,

Merck & Co, Sanofi-Aventis, Transcept Pharmaceuticals Inc., and Vanda

Pharmaceuticals.

Correspondence concerning this article should be addressed to Matthew

W. Johnson, Behavioral Pharmacology Research Unit, Department of

Psychiatry and Behavioral Sciences, Johns Hopkins University School of

Medicine, 5510 Nathan Shock Drive, Baltimore, MD 21224-6823. E-mail:

[email protected]

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Experimental and Clinical Psychopharmacology

© 2013 American Psychological Association

2013, Vol. 21, No. 2, 112–123

1064-1297/13/$12.00 DOI:

10.1037/a0031692

112

liquid form and corresponding mode of administration (drinking),

are remarkably similar to those of alcohol (i.e., ethanol), the most

widely nonmedically consumed sedative hypnotic in the United

States and the world. Previous research suggests that the abuse

liability of GHB may be somewhat less than barbiturates, and

somewhat greater than benzodiazepines. This conclusion is drawn

from a laboratory abuse liability study (

Carter, Richards, Mintzer,

& Griffiths, 2006

) and a cross-study multidimensional review of

sedative hypnotic abuse liability (

Griffiths & Johnson, 2005

).

Limited information is provided by previous studies comparing

GHB to ethanol due to lack of dose effect examination and use of

relatively low doses (

Abanades et al., 2007

;

Thai, Dyer, Benowitz,

& Haller, 2006

). A direct comparison of the abuse liability be-

tween GHB and ethanol is relevant because (1) the aforementioned

similarities between the use of GHB and ethanol suggest potential

drug substitutability, (

Bickel, DeGrandpre, & Higgins, 1995

;

John-

son, Bickel, & Kirshenbaum, 2004

), which may explain why some

alcohol users may also become GHB users, and also may inform

the possible efficacy of GHB in treatment of alcoholism (

Addolor-

ato, Leggio, Ferrulli, Caputo, & Gasbarrini, 2009

;

Caputo, Vignoli,

Maremmani, Bernardi, & Zoli, 2009

;

Gallimberti, Spella, Soncini,

& Gessa, 2000

); (2) the abuse potential characteristics of alcohol

are widely known to both the scientific community and general

public, making alcohol a valuable comparator for GHB; (3) GHB

and alcohol are often used concurrently, therefore comparison of

their relative abuse liabilities at a wide range of doses may inform

future work investigating their interactive effects. This laboratory

study compared the behavioral, participant-rated, and observer-

rated effects of GHB and ethanol under double-blind conditions in

participants with histories of sedative (including alcohol) abuse. In

addition, a choice procedure was used in which participants were

readministered the highest tolerated dose of both drugs, and choose

which they preferred to receive once again on a final session.

Method

Participants

Fourteen (11 male and 3 female) community volunteers partic-

ipated in this residential research study. Participants were recruited

with posted notices and newspaper advertisements. Volunteers

were screened by telephone to determine whether they met major

inclusion/exclusion criteria, and thus whether they were eligible

for an in-person screening session. Participants had a history of

recreational nonmedical use of both ethanol and other sedative-

hypnotics to the point of intoxication within the last year. Although

participants had recent histories of use of these drugs, they were

not physically dependent (i.e., showed no withdrawal signs or

symptoms) as assessed by observation by nursing staff during the

first several days of living on the residential research unit. Other

inclusion criteria included being 21–50 years old, being within

20% of their ideal body weight according to Metropolitan Life

height-weight tables, and being healthy as determined by screening

for medical problems via a personal interview, a medical ques-

tionnaire, a physical examination, an electrocardiogram (ECG),

and routine medical blood and urinalysis laboratory tests. Exclu-

sion criteria included pregnancy (determined by urinalysis at

screening and weekly throughout participation) or breastfeeding

for females, a history of hypersensitivity/allergy or other contra-

indications to alcohol or other sedatives, or a history of current

serious medical or psychiatric conditions, including heart disease,

lung disease, diabetes, seizure disorders, significant gastrointesti-

nal disturbances, narrow angle glaucoma, sleep apnea, schizophre-

nia, bipolar disorder, paranoia, or multiple personality disorder.

Participants were compensated

$2,500 (85$ per day) for com-

pleting this study requiring living on a restricted residential re-

search unit for

1 month. The study was approved by a Johns

Hopkins Medicine Institutional Review Board, and all volunteers

signed written informed consent.

Drugs

GHB (Xyrem, 500

g

/ml GHB solution; Orphan Medical; Min-

netonka, MN, currently known as Jazz Pharmaceuticals, Palo Alto,

CA), ethanol (ethyl alcohol 95% USP, Warner Graham Co., Cock-

eysville, MD), and placebo were delivered in separate sessions

using the same vehicle solution, and consumed orally. Sodium

citrate solution (389

g

/ml, providing an equimolar concentration of

sodium relative to the GHB solution; also provided by Orphan

Medical) was used to match sodium content across conditions.

GHB drinks contained a 30-ml solution consisting of a combina-

tion of GHB solution (at the volume providing the intended dose)

and sodium citrate solution, to which 370 ml deionized water and

600 ml of cranberry juice cocktail (Ocean Spray; Lakeville-

Middleboro, MA) were added, bringing the total solution volume

to 1000 ml. Ethanol drinks contained 30 ml sodium citrate solu-

tion, to which 370 ml was added consisting of a combination of

ethanol (at the volume providing the intended dose) and deionized

water. To this 600 ml of cranberry juice cocktail was added,

bringing the total solution volume to 1000 ml. Placebo drinks

contained 30 ml sodium citrate solution, 370 ml water, and 600 ml

juice cocktail. The total solution was consumed over a targeted

15-min period, although at the higher ethanol sessions some par-

ticipants took up t

o1hto

consume all of the solution because of

unpleasant taste.

Procedure

This was a double-blind study, conducted on a 14-bed residen-

tial research unit, which compared the behavioral pharmacology of

GHB and ethanol. Participants were awoken by 0700 hours and

were allowed to smoke cigarettes until drug/placebo dosing at

approximately 0930 hours. Participants were maintained on a

caffeine-free diet for the duration of the study and were not

allowed to eat or drink caloric beverages after midnight before a

session. Participants were allowed to smoke cigarettes and eat after

1215 hours or after the drug effect resolved, whichever occurred

later. The experimental room contained a hospital bed, a chair, a

desk, an Apple Macintosh computer (Apple Computer, Inc., Cu-

pertino, CA), and an automated ECG and blood pressure monitor

(Criticare Systems Inc., Waukesha, WI). A crash cart was avail-

able in the event of a medical emergency. When not performing

experimental tasks, participants were allowed to engage in recre-

ational activities (e.g., watch TV or read).

GHB and ethanol were administered in separate sessions at a

range of doses in an ascending dose design. Sessions were con-

ducted once per day and generally took place 5 days per week

(Monday through Friday, except holidays). In some cases sessions

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113

COMPARATIVE ABUSE LIABILITY OF GHB AND ETHANOL

The Effect of MDMA on Sensitivity to Reinforcement Rate REF 5.docx

The Effect of MDMA on Sensitivity to Reinforcement Rate

Celia Lie

University of Otago

Anne C. Macaskill and David N. Harper

Victoria University of Wellington

Administration of (

)3,4-methylenedioxymethamphetamine (MDMA) causes memory errors by increas-

ing proactive interference. This might occur because MDMA alters sensitivity to reinforcement. The

current 2 experiments investigated this directly by assessing the acute (Experiment 1) and chronic

(Experiment 2) effects of MDMA on sensitivity to reinforcement. We presented 5 pairs of concurrent

variable interval schedules within each session and calculated sensitivity to reinforcement for 3 acute

doses of MDMA. In contrast to the related drug,

d

-amphetamine, and in spite of producing reductions in

response rate, MDMA did not reduce sensitivity to reinforcement rate. Chronic administration of a fixed

dose of MDMA following each session reduced response rate but did not affect sensitivity to reinforce-

ment rate. In combination with previous research, these results indicate that related drugs may have

different effects on sensitivity to reinforcement and that these effects should be considered when

interpreting disruptions to operant task performance caused by drug administration.

Keywords:

MDMA, ecstasy, sensitivity to reinforcement, generalized matching law

The recreational drug (

)3,4-methylenedioxymethamphetamine

(MDMA) is used by many people worldwide (

World Health Organiza-

tion, 2014

). MDMA is an indirect monoaminergic agonist that reduces

reuptake of and increases release of serotonin, and also increases levels of

dopamine at higher doses (

Colado, O’Shea, & Green, 2004

;

Green,

Mechan, Elliott, O’Shea, & Colado, 2003

). MDMA produces a range of

memory effects in humans (

Laws & Kokkalis, 2007

). It can be difficult

to precisely identify the impacts of MDMA use on human memory as

users often also take other drugs, and people may not accurately report

when and in what quantities they have used each drug (

Meyer, 2013

).

Nonhuman animal models do not have these limitations, and thus are a

useful approach to precisely characterizing the effects of MDMA on

memory and other aspects of behavior.

MDMA impairs animals’ performance on a range of tasks that

require conditional discrimination (performing different responses

in the presence of different stimuli) and memory. For example,

Braida, Pozzi, Cavallini, and Sala (2002)

found that MDMA

impaired rats’ performance on the radial-arm maze task.

Kay,

Harper, and Hunt (2010)

used a variant of this task in which the

same four arms were baited with food at the beginning of each

session. This procedure makes it possible to separate reference

memory errors (visiting an arm that has never been baited) from

working memory errors (revisiting an arm already visited in the

current session). Kay et al. found that acute administration of

MDMA produced increases in both type of errors, but produced a

larger increase in reference-memory errors. This suggested that

MDMA reduced memory for stable task rules; that is, memory for

which behaviors were necessary to produce reinforcement in the

presence of a given stimulus.

MDMA also impairs performance in the delayed-matching-to-

sample (DMTS) task. In the DMTS task, subjects are first pre-

sented with a sample stimulus (for rats, either the left or right

lever) and then after a delay they are presented with two compar-

ison stimuli (for rats, both levers). Responding on the comparison

stimulus that was presented earlier in the trial produces reinforce-

ment.

LeSage, Clark, and Poling (1993)

found that MDMA pro-

duced an overall impairment in DMTS accuracy in pigeons.

Harper, Wisnewski, Hunt, and Schenk (2005)

characterized the

impact of MDMA on DMTS performance in rats more completely.

They found that MDMA impaired performance by increasing

proac-

tive interference

; that is, rats tended to respond on the comparison

lever they had responded on during the previous trial regardless of

whether it was correct on the current trial or not. If errors are caused

by proactive interference from the previous trial, then increasing the

intertrial interval (i.e., the time between trials) should reduce these

errors.

Harper, Hunt, and Schenk (2006)

found that it did so, again

consistent with proactive interference as a crucial driver of impair-

ment in DMTS performance caused by MDMA. In general,

stimulant-based drugs, including

d-

amphetamine (

Harper, McLean, &

Dalrymple-Alford, 1994

) and methamphetamine (

Macaskill, Harrow,

& Harper, 2015

) have been found to produce proactive interference.

The proactive interference effects of both MDMA and methamphet-

amine are reduced by administration of the D

1

receptor antagonist

SCH23390 (

Harper, 2013

;

Macaskill et al., 2015

).

This article was published Online First January 28, 2016.

Celia Lie, Department of Psychology, University of Otago; Anne C.

Macaskill and David N. Harper, School of Psychology, Victoria University

of Wellington.

Portions of this study were presented at the Australasian Winter Con-

ference on Brain Research in 2008, the New Zealand Association for

Behavior Analysis Conference in 2008, the Association for Behavior

Analysis International Conference in 2009, the second international

MDMA “ecstasy” conference in Australasia at Monash University in

Melbourne in 2010, and at the Third International Conference on Cognitive

Neurodynamics in 2011. We thank the staff and students of Victoria

University of Wellington’s animal research laboratory.

Correspondence concerning this article should be addressed to Anne C.

Macaskill, School of Psychology, Victoria University of Wellington, PO

Box 600, Wellington, New Zealand. E-mail:

[email protected]

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Behavioral Neuroscience

© 2016 American Psychological Association

2016, Vol. 130, No. 2, 243–251

0735-7044/16/$12.00

http://dx.doi.org/10.1037/bne0000125

243

When drugs impair DMTS or radial arm maze performance it is

often interpreted as direct evidence that the drug has rendered

subjects unable to recall recent task events such as presentation of

the sample. Research demonstrating that MDMA can reduce ref-

erence memory and produce proactive interference, however, sug-

gests that reductions in accuracy alone may actually be uninfor-

mative about whether the drug has impaired memory for recent

task events. Rather, reductions in accuracy might occur because of

a disruption in stimulus control. Following drug administration

subjects may be able to recall stimuli they have seen but may no

longer be able to use them to determine which behaviors will

produce reinforcement. For example, on the radial arm maze task,

they may not be able to use information about which arms are

usually baited and which they have recently visited to identify

which arms still contain reinforcers. On the delayed matching-to-

sample task, subjects may no longer be able to use information

about which sample they recently responded on to identify the

sample stimulus that will produce food. That is, some drugs may

cause reduced sensitivity to relations among recent events and

stimuli, the individual’s own behavior, and reinforcement.

To explore this further, the current study investigated the impact

of MDMA on sensitivity to reinforcement using

Davison and

Baum’s (2000)

rapidly changing concurrent choice procedure.

This procedure has been successfully used to characterize sensi-

tivity to reinforcement in both nonhuman (e.g.,

Rodewald, Hughes,

& Pitts, 2010a

) and human (e.g.,

Lie, Harper, & Hunt, 2009

;

Daly

et al., 2014

) choice. This procedure allows use of the generalized

matching law (

Baum, 1974

) to provide a quantitative description

of both sensitivity to reinforcement rate and bias to one or other

response alternative (here, left and right levers). It is useful to

consider side bias separately from sensitivity to reinforcement

because an increase in position bias caused by drug administration

might account for some of the impairment in DMTS performance

previously observed. As

Macaskill et al. (2015)

noted, proactive

interference and side-bias cannot be conclusively separated in the

standard DMTS task because proactive interference can manifest

as repeated responses on one alternative and thus resemble a side

bias. The procedure used in the current study allowed the impact

of MDMA administration on side bias to be isolated and quanti-

fied.

Using a similar procedure,

Rodewald, Hughes, and Pitts (2010a)

examined the effects of

d

-amphetamine on sensitivity and bias

using

Davison and Baum’s (2000)

rapidly changing choice proce-

dure. Acute administration of

d-

amphetamine reduced sensitivity

to relative reinforcement rate, suggesting that a reduction in sen-

sitivity to reinforcement rate might contribute to reductions in

accuracy in DMTS performance caused by

d-

amphetamine.

Rode-

wald et al. (2010a)

also conducted a more local-level analysis of

response patterns and found that

d-

amphetamine reduced prefer-

ence pulses, or the tendency for pigeons to continue to respond on

the alternative that had produced that reinforcer immediately after

that reinforcer’s delivery. Rodewald et al. did not find that

d

-amphetamine administration produced an increase in side bias.

In a related study,

Maguire, Rodewald, Hughes, and Pitts (2009)

found that

d

-methamphetamine reduced sensitivity to reinforce-

ment magnitude in a similar rapidly changing procedure.

Experiment 1: Acute Administration of MDMA

Experiment 1 explored whether MDMA reduced sensitivity to

reinforcement rate in a similar manner to

d

-amphetamine. An

understanding of the effects of MDMA on sensitivity to reinforce-

ment would contribute to a more complete characterization of the

disruptive effects of MDMA on memory and conditional discrim-

ination in other operant tasks. To this end, we examined the effects

of a range of doses of MDMA on overall response output, global

sensitivity to reinforcement rate, preference pulses, and side bias.

We hypothesized that, like the related drug,

d-

amphetamine, acute

administration of MDMA would reduce subjects’ sensitivity to

reinforcement rate.

Method

Subjects.

Seven male Norway hooded rats served as subjects.

Subjects were approximately 1 year old at the beginning of the

experiment. Subjects were kept at 85% of their free-feeding weight

with supplementary feeding following each session. Subjects’

home cages provided continuous access to water. They were

located in a housing room that was dark from 7 a.m. to 7 p.m.

(during which time sessions were conducted) and maintained at a

constant temperature of 22 °C.

Apparatus.

Standard two-lever operant chambers supplied by

Med Associates Inc. (St. Albans, Vermont) were used for all

experimental tasks. Operant chambers were in a darkened room

next to the housing room. Each operant chamber was 31 cm

long

31 cm wide

25 cm high. Levers were 5 cm above the

floor on either side of the front panel. There was an 80 mA light

above each lever. MED-PC-IV (Med Associates Inc.) was used to

arrange reinforcers and stimuli and record data. Each reinforcer

consisted of 0.01 ml of sweetened condensed milk.

Procedure.

Rats were trained to press each lever using stan-

dard auto-shaping techniques. In the final procedure, different VI

schedules of reinforcement were arranged on each lever through-

out the session. Under these VI schedules, an interval began at the

onset of each trial and the first response after the interval expired

produced a reinforcer. Five pairs of VI schedules (i.e., compo-

nents) were arranged during each session. The VI schedule param-

eter indicates the mean length of the intervals, for example, under

a VI 60-s interval one reinforcer is presented, on average, every

minute. The length of the interval for the pair of schedules pre-

sented in each component is presented in

Table 1

. Each component

was presented once in random order within each session. Changes

in reinforcement schedule were not signaled.

Table 1

The Five Concurrent Variable Interval (VI) Schedules Presented

During Each Session and the Resulting Reinforcer Ratio

Component

VI schedule

left lever (s)

VI schedule

right lever (s)

Reinforcer

ratio

1

32

480

15:1

2

36

180

5:1

3

60

60

1:1

4

180

36

1:5

5

480

32

1:15

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244

LIE, MACASKILL, AND HARPER

The overall reinforcement rate across the two levers was held

constant (two reinforcers/minute) across all five pairs of schedules.

Schedules were dependently scheduled (

Stubbs & Pliskoff, 1969

);

that is, if an interval expired and a reinforcer became available on

one alternative, a response had to be made on that alternative to

produce that reinforcer before responses on the other alternative

became effective once more. A 2-s changeover delay was in effect,

meaning that any responses made on one lever less tha

n 2 s after

a response was made on the other lever did not produce a rein-

forcer, even if the interval on that lever had expired.

Each pair of schedules was presented for 15 reinforcers (i.e., a

component) within each session. There was a 10-s blackout period

between components. During the blackout, the chamber was dark

and the levers were retracted. The session ended after all 75

reinforcers had been received or after 90 min, whichever came

first. The session-length criterion was included in anticipation that

drug administration would reduce response rates and therefore

lengthen sessions. Sessions were conducted Monday to Friday

each week. Each individual completed all sessions in the same

operant chamber.

Pharmacological procedure.

MDMA was obtained from

BDS, Porirua, New Zealand. Drugs were administered 10 to 15

min before the session began. Drugs were mixed in 0.9% saline

solution and delivered intraperitoneal at a volume of 1 ml/kg of

body weight. Drugs were administered on Tuesdays and Fridays.

Rats were still exposed to the concurrent VI procedure on inter-

vening days. Each rat received three administrations of the saline

vehicle and of 0.5, 1.0, and 2.0 mg/kg of MDMA. Subjects also

received one dose of 3.0 mg/kg. This reduced response rates to the

point that response patterns were uninterpretable (see Graph A on

Figure 1

). This dose was therefore excluded from subsequent data

analyses.

Statistical analyses.

Response rates were calculated by divid-

ing the total number of responses made on either lever during the

entire session by the session length excluding intercomponent

intervals. Mean response rates were calculated for each dose for

each rat. The generalized matching law (

Baum, 1974

;

Equation 1

)

was used to calculate an individual rat’s sensitivity to reinforce-

ment rate for each drug dose.

B

1

B

2

a

log

R

1

R

2

log

b

(1)

In

Equation 1

,B

1

is the number of responses made to one of the

response alternatives (here, the left lever), and B

2

is the number of

responses made to the other response alternative (here, the right

lever). R

1

and R

2

are the numbers of reinforcers received from

each of those levers.

a

is a free parameter corresponding to the

slope of the regression line if

Equation 1

is graphed. The

a

parameter captures the extent to which a subject’s distribution of

responses across the left and right lever changes as the distribution

of reinforcers received from those levers changes. If

a

is smaller

than 1.0 this indicates that changes in the subject’s distribution of

responses across conditions are smaller than the change in distri-

bution of reinforcers (a pattern termed

undermatching

).

Sensitivity values were calculated for each subject by summing

the total number of responses and reinforcers received in a given

component during all of the relevant drug sessions and then using

linear regression in combination with

Equation 1

above. In cases

were R

1

,R

2

,B

1,

or B

2

were zero, estimates of

a

and

log b

are

incalculable. In such cases therefore, an arbitrarily small value of

0.25 was added to that value to allow

Equation 1

to be used (see

Brown & White, 2005

for a discussion of this issue when using

quantitative models). One-way analysis of variance (ANOVA) and

follow-up paired sample

t

tests were used to assess the impact of

drug doses on

R

2

. One-sample

t

tests were used to determine

whether sensitivity values were significantly greater than zero.

Rodewald et al. found that sensitivity was higher at the end than

the beginning of the component, presumably because subjects took

time to make contact with the changed reinforcement rates on the

two alternatives and adjust their response distribution accordingly.

For this reason, we use

d a 2 (Component Half)

4 (Dose)

ANOVA to assess the effect of dose and component half on

sensitivity where the first half was defined as from after the

presentation of the first reinforcer up to the presentation of the

eighth reinforcer. Follow-up one-way ANOVA and follow-up

paired samples

t

tests were used to assess the effect of dose of

MDMA on the first and second halves of each component sepa-

rately.

In

Equation 1

, log

b

is the

y

-intercept of the regression line if

Equation 1

is graphed. Nonzero log

b

values indicate a preference

Figure 1.

Group mean response rate (top graph), and

R

2

(bottom graph)

as a function of dose of 3,4-methylenedioxy-methamphetamin (MDMA;

mg/kg). Error bars are

SEM

. Brackets with

indicate significance at the

0.05 level, and

at the 0.01 level.

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245

MDMA AND SENSITIVITY TO REINFORCEMENT RATE

for either B

1

or B

2

that is unrelated to the proportion of reinforcers

that the individual has received from that response alternative, that

is, a bias (

Baum, 1974

). We used a 2 (Component Half)

4

(Dose) ANOVA to assess the effect of component half and dose on

bias.

We used the generalized matching law to assess the effect of

MDMA on the effects of reinforcers at a global level, considering

session total numbers of responses and reinforcers. We also con-

sidered the effects of MDMA on the local effects of reinforcers.

The local effects a reinforcer are those that occur within a short

time—typically seconds—following its presentation. During the

period immediately after a reinforcer there is typically an increase

in preference for the response alternative that produced that rein-

forcer for a brief period—termed a

preference pulse

(e.g.,

Davison

& Baum, 2002

).

Rodewald et al. (2010a)

found that

d

-amphetamine reduced the size of preference pulses. In order to

investigate whether MDMA produced similar effects at the local

level, we summed all responses occurring on B

1

and all occurring

on B

2

within the firs

t 5 s following a reinforcer on all sessions for

a given dose and a given subject. We then calculated response

ratios log (B

1

/B

2

). If this number is greater than zero it indicates

preference for B

1

, and if smaller than zero preference for B

2

.A4

(Dose)

2 (Previous Reinforcer Side) ANOVA was used to

assess the impact of reinforcer location to determine whether

preference pulses were present, and whether their size was affected

by dose of MDMA.

An alpha level of

p

.05 was used as the significance criterion

for all statistical tests. Partial eta squared was used to characterize

effect sizes.

Results

We assessed mean response rate in order to evaluate the overall

impact of each dose of MDMA on overall response output. Mean

response rate is presented as a function of dose in the top graph on

Figure 1

. A repeated measures ANOVA indicated a significant

main effect of dose of MDMA on response rate,

F

(4, 24)

19.19,

p

.001,

2

0.762. This main effect remained when 3.0 mg/kg

was excluded,

F

(3, 18)

4.70,

p

.014,

2

0.439, confirming

that the doses included in subsequent analyses were in a behav-

iorally active range. Follow-up paired samples

t

tests indicated

significant differences between 3.0 mg/kg and saline, 0.5 mg/kg,

and 1.0 mg/kg and between 0.5 mg/kg and 2.0 mg/kg (all

p

s

0.05).

As the bottom graph on

Figure 1

indicates,

R

2

values were high.

A repeated measures ANOVA indicated a significant effect of

dose on

R

2

,

F

(1, 6)

3.24,

p

.047,

2

0.351. Follow-up

paired samples

t

tests indicated that

R

2

for the 2.0 mg/kg dose was

significantly smaller than

R

2

values for 1.0 mg/kg,

t

(6)

3.5,

p

.013 and 0.5 mg/kg,

t

(6)

3.6,

p

.012. No other pairs differed

significantly (all

p

s

0.05).

One-sample

t

tests indicated that sensitivity values were signif-

icantly above zero for each dose, saline:

t

(6)

10.8,

p

.01; 0.5

mg/kg:

t

(6)

13.0,

p

.01; 1.0 mg/kg:

t

(6)

8.2,

p

.01; 2.0

mg/kg:

t

(6)

5.1,

p

.002, using an alpha adjusted following a

Bonferroni correction (adjusted

.0125). Sensitivity values are

presented for the first (closed circles) and second (open circles)

halves of the component as a function of dose for each individual

in the top graph of

Figure 2

. A 2 (Component Half)

4 (Dose)

ANOVA revealed a main effect of component half,

F

(1, 6)

112.467,

2

0.949, no main effect of dose,

F

(3, 18)

6.27,

p

.607,

2

0.095, and a significant interaction between dose and

component half,

F

(3, 18)

3.709,

p

.031,

2

0.382, that

became only marginally significant once a Greenhouse–Geisser

correction to address violation of nonsphericity was applied,

F

(12.27, 1.171)

3.709,

p

.092,

2

0.382. To investigate this

further, we assessed the effect of dose for the first and second

halves of each component separately There was a significant

increase sensitivity in the second half of the components,

F

(3,

18)

4.44,

p

.017,

2

0.425, but not the first half of the

components,

F

(3, 18)

0.530,

p

.667,

2

0.081. Follow-up

paired samples

t

tests indicated that sensitivity values were signif-

icantly larger at the 2.0 mg/kg dose than the 0.5 and 1.0 mg/kg

doses.

Bias values are presented for each half of the component as a

function of dose for each individual in the bottom graph of

Figure

2

. A 2 (Half)

4 (Dose) revealed no main effect of half,

F

(1, 6)

3.485,

p

.111,

2

0.367, no main effect of dose,

F

(3, 18)

0.233,

p

.872,

2

0.037, and no significant interaction,

F

(3,

18)

0.790,

p

.515,

2

0.116. This indicates that acute

administration of MDMA did not create a bias to the same lever in

all subjects. We also calculated absolute values of log

c

to inves-

tigate whether drug doses made bias more extreme regardless of

which lever the bias was to

. A 2 (Half)

4 (Dose) revealed no

main effect of half,

F

(1, 6)

0.362,

p

.569,

2

0.057, no

main effect of dose,

F

(3, 18)

1.465,

p

.257,

2

0.196, and

no significant interaction,

F

(3, 18)

0.407,

p

.750,

2

0.063.

Figure 3

presents log response ratios as a function of dose

following reinforcers received from responses on the left (open

Figure 2.

Mean sensitivity (top graph) and bias (bottom graph) in the first

(closed circles) and second (open circles) half of the component as a

function of dose of 3,4-methylenedioxy-methamphetamin (MDMA). Error

bars are

SEM

. Brackets with

indicate significance at the 0.05 level.

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246

LIE, MACASKILL, AND HARPER

Teaching_Assignment_3_Template.docx

RLGN 330

Teaching Assignment 3 Template

In Part 1, answer the questions related to the assigned reading material. In Part 2, you will continue to develop your Bible lesson (which you began/presented in Module/Week 1).

Part 1: Answer the following questions related to the reading material from Modules/Weeks 4–6. Each answer must be at least 100 words to receive credit.

1. After reading Chapter 1 of the Wilkinson textbook, who would you say was the best teacher you ever had? What 3 main characteristics made that person your favorite? How important was his/her commitment to “cause you to learn”? What do you think would have happened if he/she had lost that commitment?

2. After reading Chapter 2 of the Wilkinson textbook, examine yourself as a teacher. On a scale of 1 to 10, rate how strong you are in each of the following areas: Scholar (subject-oriented), Friend (student-oriented), and Communicator (style-oriented). If you are to become a truly outstanding teacher, you must focus your efforts on your greatest strengths. Name at least 3 ways you can do that during the next twelve months.

3. After reading Chapter 5 of the Wilkinson textbook, how would your teaching change if you made sure each lesson filtered through you first before you shared it with others?

4. After reading Chapter 6 of the Wilkinson textbook, who has the greatest applier’s heart you know? On a scale of 1 to 10, how would you rank your applier’s heart? What could you do to move it closer to a 10?

5. After reading Chapter 8 of the Wilkinson textbook, discuss the following question. Step 2 of the Retention Method occurs when the teacher boils down the content to the minimum. Why do you think so few teachers take this step? What is the difference between content being covered and content being learned?

6. After reading Chapter 9 of the Wilkinson textbook, what percentage of teachers you have had regularly “built the need” before teaching the content? Why do you think the percentage is so low? What difference would it have made if they had built the need first?

7. After reading Chapter 12 of the Wilkinson textbook, discuss the following question. Think through the 5 steps of the Equipping Method – Instruct, Illustrate, Involve, Improve, Inspire. Which teacher modeled this process best for you? Discuss the impact you experienced.

Part 2: Answer the following questions related to your Bible lesson, which you began in Module/Week 1. Each answer must be at least 100 words to receive credit.

1. Briefly describe Wilkinson’s law of the learner, then explain in more detail how this law affects the way you prepare and present your Bible lesson.

2. Briefly describe Wilkinson’s law of expectation, then explain in more detail how this law affects the way you prepare and present your Bible lesson.

3. Briefly describe Wilkinson’s law of application, then explain in more detail how this law affects the way you prepare and present your Bible lesson.

4. Briefly describe Wilkinson’s law of retention, then explain in more detail how this law affects the way you prepare and present your Bible lesson.

5. Briefly describe Wilkinson’s law of need, then explain in more detail how this law affects the way you prepare and present your Bible lesson.

6. Briefly describe Wilkinson’s law of equipping, then explain in more detail how this law affects the way you prepare and present your Bible lesson.

Page 1 of 3

Marijuana REF 3.docx

Marijuana’s Dose-Dependent Effects in Daily Marijuana Smokers

Divya Ramesh, Margaret Haney, and Ziva D. Cooper

New York Psychiatric Institute, and College of Physicians and Surgeons of Columbia University

Active marijuana produces significant subjective, psychomotor, and physiological effects relative to

inactive marijuana, yet demonstrating that these effects are dose-dependent has proven difficult. This

within-subject, double-blind study was designed to develop a smoking procedure to obtain a marijuana

dose–response function. In four outpatient laboratory sessions, daily marijuana smokers (

N

17 males,

1 female) smoked six 5-s puffs from 3 marijuana cigarettes (2 puffs/cigarette). The number of puffs from

active (

5.5%

9

-tetrahydrocannabinol/THC) and inactive (0.0% THC) marijuana varied according to

condition (0, 2, 4, or 6 active puffs); active puffs were always smoked before inactive puffs. Subjective,

physiological, and performance effects were assessed prior to and at set time points after marijuana

administration. Active marijuana dose-dependently increased heart rate and decreased marijuana craving,

despite evidence (carbon monoxide expiration, weight of marijuana cigarettes post-smoking) that

participants inhaled less of each active marijuana cigarette than inactive cigarettes. Subjective ratings of

marijuana “strength,” “high,” “liking,” “good effect,” and “take again” were increased by active

marijuana compared with inactive marijuana, but these effects were not dose-dependent. Active mari-

juana also produced modest, non-dose-dependent deficits in attention, psychomotor function, and recall

relative to the inactive condition. In summary, although changes in inhalation patterns as a function of

marijuana strength likely minimized the difference between dose conditions, dose-dependent differences

in marijuana’s cardiovascular effects and ratings of craving were observed, whereas subjective ratings of

marijuana effects did not significantly vary as a function of dose.

Keywords:

cannabis, THC, cannabinoid

Marijuana is the most widely used illicit drug in the United

States and smoking is the most common route of administration

(

Johnston, O’Malley, Bachman, & Schulenberg, 2012

). Effects of

marijuana, including tachycardia, subjective reports of intoxica-

tion, as well as impaired memory and attention, have been well

established in a number of controlled laboratory studies (

Foltin &

Fischman, 1990

;

Foltin, Fischman, Pedroso, & Pearlson, 1987

;

Hart, van Gorp, Haney, Foltin, & Fischman, 2001

;

Nemeth-

Coslett, Henningfield, O’Keeffe, & Griffiths, 1986

). Although

marijuana’s subjective effects are primarily mediated by

9

-

tetrahydrocannabinol (THC) (

Chait, 1989

;

Heishman, Arasteh, &

Stitzer, 1997

;

Kelly, Foltin, Emurian, & Fischman, 1997

), dem-

onstrating a dose–effect relationship between marijuana strength

(THC concentration) and its elicited subjective and physiological

effects (

Azorlosa, Heishman, Stitzer, & Mahaffey, 1992

;

Chait,

1989

;

Heishman, Stitzer, & Yingling, 1989

) has proven difficult.

Possible explanations for the difficulty observing marijuana

dose dependence in early studies could be that the range of

marijuana strengths tested (0.2% to 0.8% THC) was too narrow

(

Cappell, Kuchar, & Webster, 1973

) or that marijuana administra-

tion was ad libitum as opposed to controlled (

Ashton, Golding,

Marsh, Millman, & Thompson, 1981

;

Herning, Hooker, & Jones,

1986

). Unlike drugs administered orally or intravenously, smoked

administration is reliant on inhalation strength (

Azorlosa, Green-

wald, & Stitzer, 1995

), and participants alter their smoking topog-

raphy as a function of marijuana potency. One such study tested a

range of marijuana potencies (0.0% to 4.0% THC) using a timed

smoking procedure, in which puff duration was measured and

participants held the inhaled smoke in their lungs for a fixed

amount of time. Although subjective and cardiovascular measures

were not dose-dependent, expired carbon monoxide (CO) levels,

an index of smoke inhalation, showed a significant inverse rela-

tionship to THC content, demonstrating that participants reduced

their smoke intake as strength of the marijuana increased (

Nemeth-

Coslett et al., 1986

). These observations have been replicated in

later studies showing that CO expiration, as well as puff duration,

are inversely related to marijuana strength (

Chait, Fischman, &

Schuster, 1985

;

Cooper & Haney, 2009

;

Kelly, Foltin, & Fis-

chman, 1993

). Thus, even while using controlled smoking proce-

dures, smoke inhalation decreased with increasing strengths of

marijuana. Consequently, marijuana exposure is reduced at higher

Divya Ramesh, Margaret Haney, and Ziva D. Cooper, Division on

Substance Abuse, New York Psychiatric Institute, and Department of

Psychiatry, College of Physicians and Surgeons of Columbia University.

This research was supported by the U.S. National Institute on Drug

Abuse (Margaret Haney: DA09236; Ziva D. Cooper: DA027755).

The authors acknowledge and appreciate the exceptional assistance of

Divya Lakhaney, Elyssa Berg, and Michael Harakas in data collection, and

Richard Foltin for statistical assistance. Ziva D. Cooper and Margaret

Haney designed the study and wrote the protocol. Authors Divya Ramesh

and Ziva D. Cooper managed the literature searches, summaries of previ-

ous related work, and performed statistical analysis of results. All authors

contributed and have approved the final manuscript.

Correspondence concerning this article should be addressed to Margaret

Haney, Division on Substance Abuse, New York Psychiatric Institute, and

Department of Psychiatry, College of Physicians and Surgeons of Colum-

bia University, 1051 Riverside Drive, Unit 120, New York, NY 10032.

E-mail:

[email protected]

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Experimental and Clinical Psychopharmacology

© 2013 American Psychological Association

2013, Vol. 21, No. 4, 287–293

1064-1297/13/$12.00 DOI:

10.1037/a0033661

287

strengths, which decreases the likelihood of observing dose-

dependent marijuana effects.

In an effort to account for dose-dependent titration, Heishman

and colleagues used a procedure that controlled for smoking to-

pography (

Azorlosa et al., 1992

;

Heishman et al., 1997

) as well as

THC content (1.75% to 3.55% THC). In order to deliver uniform

amounts of marijuana smoke per puff, a computer-based smoking

topography system monitored puff volume, inhalation volume,

lung exposure duration, and interpuff interval. Although this pro-

cedure produced sensitive differences in plasma THC levels as a

function of dose condition, only considerably different dose con-

ditions produced significantly different subjective effects, that is,

the lowest and highest number of puff conditions (4 vs. 16 or 25

puffs). Thus, even procedures that carefully control smoke inha-

lation and produce distinct plasma THC concentrations demon-

strate that dose-dependent marijuana effects are difficult to ob-

serve.

Yet, establishing a procedure that produces dose-dependent

marijuana effects would greatly inform drug interaction studies.

For example, assessing how medications or other drugs of abuse

shift the marijuana dose-response curve would elucidate the mech-

anism of drug interaction. Thus, the objective of this within-

subject,

double-blind, placebo-controlled study was to develop a

smoking procedure to characterize marijuana

dose-dependence

by keeping participants blind to the marijuana “dose” and thereby

minimizing the expectation of a particular drug effect. Non-

treatment-seeking marijuana smokers smoked 6 puffs of marijuana

in each session, but the number of active marijuana puffs smoked

varied from 0 to 6. Participants smoked active puffs of marijuana

prior to inactive puffs because it was hypothesized that this would

better maintain the blind regarding the different dose conditions.

The duration of inhalation and the amount of time the smoke was

held in the lungs was controlled. We measured the time course of

marijuana’s subjective, physiological (heart rate, blood pressure,

expired carbon monoxide), and performance effects, as well as the

amount of marijuana smoked from each cigarette as a function of

the number of active marijuana puffs smoked.

Methods

Participants

Volunteers, 21 to 45 years of age, were recruited through

newspaper advertisements. Those meeting inclusion/exclusion cri-

teria after an initial phone screen were invited to the laboratory for

further screening. Participants were accepted into the study if they

were healthy, as determined by a physical examination, electro-

cardiogram, and urine and blood chemistry. Marijuana use was

confirmed by urine toxicology and self-report. To be eligible for

participation, volunteers had to report smoking at least three mar-

ijuana cigarettes four times a week for the previous month before

screening. Repeated use of other drugs, with the exception of

nicotine, alcohol, or caffeine, as determined by urine toxicology

and self-report, and/or current use of over-the-counter or prescrip-

tion medication was exclusionary, as was alcohol dependence.

Those who met

Diagnostic and Statistical Manual of Mental

Disorders

(4th ed., text rev.;

American Psychiatric Association,

2000

) revised criteria for current Axis I psychopathology accord-

ing to a psychiatric examination were not eligible for participation.

Females were excluded if they were pregnant, nursing, or not using

contraception.

This study was part of an eight-session study assessing the

effects of naltrexone, a mu-opioid antagonist, on marijuana. Prior

to consent, volunteers were told that (a) the study objective was to

determine if commonly prescribed medications altered marijuana’s

effects on mood and physiology, (b) they would receive a capsule

containing placebo or one of three medications listed on the

consent form, and (c) active or inactive marijuana would be

smoked after capsule administration according to instructions from

the research staff. Participants were admitted into the study only

after written informed consent was obtained and eligibility was

verified. All study procedures were approved by the Institutional

Review Board of the New York State Psychiatric Institute and

were in accordance with the Declaration of Helsinki.

Drugs

Marijuana cigarettes (0, 5.5, or 6.2% THC; ca. 800 mg) were

provided by the National Institute on Drug Abuse. Cigarettes were

stored frozen in an airtight container and humidified at room

temperature for 24 hr prior to the session. Because of limited

supply of the highest strength of marijuana (6.2% THC), the first

13 participants smoked 6.2% THC for the active puffs, and the

final five participants smoked 5.5% THC; marijuana strength was

consistent within participants. Size 00 opaque capsules with lac-

tose filler or naltrexone (12 mg) were prepared by the New York

State Psychiatric Institute Research Pharmacy.

Study Design and Procedures

The study included eight outpatient sessions over the course of

3 to 6 weeks at the New York State Psychiatric Institute. Sessions,

which were separated by at least 48 hr to prevent medication

carryover effects, began around 9:00 a.m., and were about 6 hr in

duration. After study consent was obtained and prior to the first

session, participants were familiarized with computerized tasks

and study procedures with one to two training sessions. During the

training session, capsules and marijuana were not administered.

During each of the outpatient sessions, participants smoked a

total of 6 puffs from three marijuana cigarettes (2 puffs from each

cigarette). Marijuana administration occurred 45 min after capsule

administration. The experimenter rolled the marijuana cigarette

ends, and one end was inserted into a plastic cigarette holder so

that the participants could not distinguish active from placebo

marijuana based on visual cues. The number of active versus

inactive cigarettes smoked during each session varied according to

active puff conditions (i.e., 0 puffs

3 inactive cigarettes; 2

puffs

1 active

2 inactive cigarettes; 4 puffs

2 active

1

inactive cigarettes; 6 puffs

3 active cigarettes). Cigarettes were

smoked according to a cued smoking procedure that has been

shown to produce reliable increases in heart rate and plasma THC

levels (

Foltin et al., 1987

). During marijuana smoking, the exper-

imenter observed the participant behind a one-way mirror and used

an intercom to guide the participant as to which color-coded

cigarette to light, to “inhale” (5 s), “hold smoke in lungs” (10 s)

and “exhale,” with a 40-s interval between each inhalation. After

2 puffs, the participant was instructed to extinguish the cigarette

and light the next. Participants continued to smoke according to

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288

RAMESH, HANEY, AND COOPER

Neuropharmacology REF 1.docx

N Neuropharmacology

Volume 76, Part B, January 2014, Pages 269–275

NIDA 40th Anniversary Issue

Cover image

125461||

Invited review

The impact of exposure to addictive drugs on future generations: Physiological and behavioral effects

· F.M. Vassoler a , , , 

· E.M. Byrnes a

· R.C. Pierce b

 Show more

doi:10.1016/j.neuropharm.2013.06.016

Get rights and content

Highlights

Transgenerational consequences of exposure to drugs of abuse.

Paternal and maternal transmission to offspring prior to conception.

Alcohol,  nicotine cannabinoids opioids cocaine .

Abstract

It is clear that both genetic and environmental factors contribute to drug addiction. Recent evidence indicating trans-generational influences of drug abuse highlight potential  epigenetic  factors as well. Specifically, mounting evidence suggests that parental ingestion of abused drugs influence the physiology and behavior of future generations even in the absence of  prenatal  exposure. The goal of this review is to describe the trans-generational consequences of preconception exposure to drugs of abuse for five major classes of drugs: alcohol,  nicotine , marijuana,  opioids , and  cocaine . The potential epigenetic mechanisms underlying the transmission of these  phenotypes across generations also are detailed.

This article is part of a Special Issue entitled ‘NIDA 40th Anniversary Issue’.

Keywords

· Transgenerational; 

· Epigenetic

· Drugs of abuse; 

· Alcohol; 

· Nicotine

· Marijuana; 

· Opioids ;

· Cocaine

1. Introduction

Drug addiction is a serious medical and social issue in the United States and around the world. There is consistent evidence that  substance use disorders  run in families ( Bierut et al., 1998 Brook et al., 2002 Cloninger et al., 1981  and  Merikangas et al., 1998 ). Adoption, twin, and sibling studies implicate genetic factors in the heritability of abuse ( Cloninger et al., 1981 ). However, simple genetic mechanisms of inheritance cannot explain all results ( Cloninger et al., 1981  and  Schuckit et al., 1972 ). Societal differences in drug use and consumption patterns vary from different time periods and between countries suggesting a large environmental component ( UNODC, 2012 ). Thus, vulnerability to develop an addiction is dependent on both genetics and the environment. The sum of separate genetic and environmental contributions cannot fully explain the heritability either. Therefore, the interaction between genetics and the environment may help explain some of the discrepancies ( Cloninger et al., 1981 ).

Epigenetics  is a key mechanism by which the environment can influence and interact with genetics. In recent years, the term epigenetics has been used to describe myriad processes ( Haig, 2004 ). For example, modifications to the structure of  chromatin  or DNA without changes in the sequence that affect gene transcription even in non-dividing cells such as  DNA methylation  or  histone acetylation  are described as  epigenetic modifications ( Holliday, 1989 ). However, some definitions of epigenetics emphasize that the modifications in gene expression that do not involve alterations in the  DNA sequence must be heritable, spanning multiple generations. There has recently been an increase in studies examining the transgenerational effects of environmental toxins on offspring. The goal of the current review is to examine the available literature regarding the effects on offspring of parental drug exposure in the absence of any direct fetal exposure for five major drugs of abuse. While offspring susceptibility to drug use is of particular interest, all behavioral, molecular, and physiological changes in the offspring will be reported. The majority of the studies available on this topic focus on paternal transmission of epigenetic phenotypes , as this model eliminates any direct fetal exposure and ostensibly avoids maternal rearing effects. With regard to maternal transmission, there is certainly an extensive body of literature documenting offspring effects following  prenatal  exposure to drugs of abuse ( Malanga and Kosofsky, 2003  and  Sithisarn et al., 2012 ). Due to the possible direct effects of in utero exposure on the fetus, as well as the numerous confounds that drug use during pregnancy introduces (e.g. changes in nutritional status, renal function, vascular perfusion, etc.), prenatal substance use models will not be included in the current review. We will, however, include data from studies examining transgenerational effects of female drug use occurring prior to conception. Thus, the current review will examine the effects of parental exposure to drugs of abuse prior to conception on the development of subsequent generations.

2. Alcohol

Currently, alcohol is the most commonly abused drug in the United States. In 2011, the center for disease control estimated that 60% of males and 44% of females engage in chronic alcohol drinking ( Edward J. Sondik et al., 2012 ). While the neurobehavioral effects of fetal alcohol exposure are well described, less is known about the effects of parental exposure to alcohol prior to conception. It should be noted, however, that reports and writings as early as the 1720's, during the so-called gin epidemic, observed that both maternal and paternal alcohol use had detrimental effects on offspring ( Warner and Rosett, 1975 ). While few studies have examined maternal alcohol use prior to pregnancy (i.e. in the absence of  prenatal  use), several findings have demonstrated effects of paternal alcohol exposure on offspring development. Indeed, as early as 1913 animal studies found that offspring sired by alcohol inhaling rats demonstrated malformations, low birth weight, retarded growth and increased neonatal mortality across several generations ( Friedler, 1996 ). Clearly the concept that alcohol use by the father, and not solely his genetic composition, can affect future progeny is not novel. The interest in paternal effects, however, has been reinvigorated by the emergence of the field of  epigenetics , with a number of preclinical findings suggesting transgenerational epigenetic effects  of paternal alcohol use.

Several of the initial animal studies on paternal alcohol effects focused on basic parameters of reproductive success, such as fertility and fecundity, following exposure to alcohol in peripubertal males. These studies observed a significant reduction in the number of successful pregnancies which decreased from 92% in controls to 75% in naïve females mated with alcohol-drinking sires ( Emanuele et al., 2001 ). Litter size was also substantially reduced ( Cicero et al., 1990  and  Emanuele et al., 2001 ). It was determined that alcohol exposure during puberty modified sexual maturation and resulted in decreased testes and secondary sex organ weight, eliminated the typical pubertal surge in  testosterone , decreased  beta-endorphin  levels in the  hypothalamus , and enhanced testicular oxidative injury ( Cicero et al., 1990  and  Emanuele et al., 2001 ). Interestingly, offspring of these pubertal alcohol-exposed sires demonstrated similar alterations, including decreased serum testosterone levels, reduced  seminal vesicle weights, and lower levels of  hypothalamic  beta-endorphin ( Abel and Lee, 1988  and  Cicero et al., 1990 ).

Alcohol-sired offspring also demonstrate abnormalities in development. In an elegantly designed rodent study, Jamerson and colleagues revealed that paternal alcohol exposure that was ongoing, or that had ceased weeks prior to conception resulted in more rapid development of various reflexes, differences in  gait , and thicker  cortical layers ( Jamerson et al., 2004 ). It was also noted that timing of alcohol exposure in relation to conception impacted the neurobehavioral effects of the offspring ( Jamerson et al., 2004 ). For example, one study found that a single exposure to alcohol just prior to conception resulted in a significant increase in small for gestational age offspring as well as an increase in offspring demonstrating significant malformations ( Bielawski and Abel, 1997 ). Moreover, alcohol-exposed sires also produced offspring displaying increased adrenal cortex  and decreased  spleen  weights ( Abel, 1993b ). Finally, there is evidence that metabolic and immune functioning may be disrupted in alcohol-sired offspring, given that they display reductions in  leptin  levels ( Emanuele et al., 2001 ) and a diminished immune response ( Berk et al., 1989  and  Hazlett et al., 1989 ).

In terms of behavioral effects, both increases and decreases in activity have been noted in offspring of alcohol-consuming sires ( Abel, 1989a Abel, 1989b Abel, 1993a Abel, 1993b  and  Abel and Lee, 1988 ), with the direction of these effects mediated by a number of factors including the level of alcohol consumption, the time between exposure and conception ( Jamerson et al., 2004 ), and the age at the time of testing ( Abel, 1989a ). Alterations in behavioral activity following  amphetamine  were also noted in male offspring ( Abel, 1993a ), with some evidence suggesting that increased activity was dependent on the  cholinergic system  ( Abel, 1994 ). Potential modifications in the cholinergic system of alcohol-sired offspring are notable given that deficits in learning and memory have also been reported. For example, offspring sired by alcohol treated males demonstrated impairments in  spatial learning  ( Wozniak et al., 1991 ) and had increased latencies to reach a choice point in a  T-maze  ( Abel, 1994  and  Abel and Lee, 1988 ). In addition to deficits observed in males, alcohol-sired female offspring showed impaired performance in a two-way shock  avoidance learning  task ( Abel and Tan, 1988 ). Finally, offspring of alcohol-consuming sires demonstrated decreased grooming as well as decreased immobility in a  forced swim test , an effect that was rescued by  imipramine and  propranolol  and exacerbated by  yohimbine  and  metergoline  ( Abel, 1991a Abel, 1991b  and  Abel and Bilitzke, 1990 ). Together, these results indicate a detrimental behavioral  phenotype  of paternal alcohol consumption on both male and female offspring.

Examining  epigenetic  parental effects in human populations can be difficult. Human studies have, however, revealed correlations between parental drinking behavior and offspring initiation and drinking patterns. Thus, heavy paternal drinking or heavy-episodic drinking in both parents predicts earlier onset of offspring drinking as well as heavier drinking ( Vermeulen-Smit et al., 2012 ). Children born with characteristics associated with fetal alcohol syndrome whose mother's did not drink but fathers were alcoholics have also been observed ( Lemoine et al., 2003 ). Additionally, there is evidence that sons of early-onset (adolescent) alcoholic fathers perform more poorly on tests of verbal intelligence  and attention than late onset (adult) alcoholics ( Tarter et al., 1989 ). While this may suggest that adolescence, or periods of significant neural and  endocrine development, are particularly important in determining the effects of paternal alcohol exposure, one cannot exclude the possibility that early-onset drinking may be a marker of genetic vulnerability or additional  comorbid  pathologies. Finally, in addition to deficits in cognition, attention, and visuospatial capacity observed in children of alcoholic fathers, increased hyperactivity has also been noted ( Goodwin et al., 1975 ), although the relationship between hyperactivity and paternal alcohol consumption remains equivocal ( Knopik et al., 2009 ). Much less work has been done examining the effects of maternal preconception alcohol consumption. However, a decreased birth weight has been observed in children of alcoholic women that abstain from use during pregnancy ( Little et al., 1980 Livy et al., 2004  and  Ramsay, 2010 ). While human studies remain more difficult to interpret than preclinical research due to many aspects that are impossible to control, it is important that both lines of research continue in order to fully understand the scope of preconception alcohol use and abuse.

3. Nicotine

Nicotine  is the second most abused substance in the United States. In 2011 it was reported that 21.6% of adult men and 16.5% of adult women smoke regularly ( Agaku et al., 2011 ). It is clear from both human epidemiological and preclinical research models that exposure to tobacco smoke in utero is harmful to development and can result in low birth weight, sudden infant death syndrome, and serious behavioral issues in the offspring (  Abbott and Winzer-Serhan, 2012 ). Examining the indirect effects (i.e. non- prenatal  exposure) in humans is more challenging because it is difficult to distinguish the indirect  epigenetic effects  of paternal or maternal nicotine abuse on the offspring from potential exposure to second-hand smoke in utero or post-partum. Keeping that in mind, some studies have shown increased risk of spontaneous abortion associated with paternal smoking (  Blanco-Munoz et al., 2009  and  Venners et al., 2004 ). However, others have shown no association (  Chatenoud et al., 1998 Windham et al., 1992  and  Windham et al., 1999 ). Moreover, paternal smoking is a factor associated with anorectal malformations in humans in multiple studies ( Zwink et al., 2011 ). Human epidemiological studies also indicate that early paternal smoking (onset before age 11) is associated with greater  body mass index  in male, but not female, offspring (  Pembrey, 2010  and  Pembrey et al., 2006 ).

Aside from these few studies looking at the effect of paternal smoking on offspring, numerous studies have found evidence that male smoking affects multiple fertility factors in the male. Thus, paternal tobacco use is associated with defects in the tail of the spermatozoon ( Ozgur et al., 2005 ) and decreases in sperm density, motility, and morphology ( Sofikitis et al., 1995 ). Another study found no differences in sperm concentration or motility but decreased semen volume ( Pasqualotto et al., 2006 ). Taken together, these studies point toward decreases in male fertility and/or embryo viability which suggests potential negative effects in the offspring. To date, we found only one animal study which found that paternal nicotine smoke exposure did not affect development or any behavioral parameters measured ( Gaworski et al., 2004 ). More animal work is needed to determine if nicotine exposure and smoking has transgenerational epigenetic effects.

4. Cannabinoids

Marijuana is the most widely abused illicit substance in the United States. Of particular concern is the high percentage of adolescents that engage in marijuana use. It is estimated that almost 50% of teenagers have used marijuana and approximately 9% use marijuana heavily (>20 days out of the month) ( Metlife, 2011 ). Marijuana use by adolescents may be particularly problematic as developing systems may be more vulnerable to the impact of exogenous  cannabinoids  ( Rice and Barone, 2000 ). Abuse by adolescent females is of particular concern as the  endogenous cannabinoid system  is important for reproductive physiology, with  CB1 receptors  as well as  endogenous cannabinoids  expressed in the ovaries, uterine endometrium, and other peripheral endocrine  tissue ( Bari et al., 2011 ). Thus,  cannabinoid  exposure during this critical period could result in lasting modifications in female reproduction, and might impact future offspring. To examine the potential effects on offspring, adolescent females were exposed to cannabinoids during adolescence. They were then maintained drug-free for over 3 weeks and bred during adulthood. Using this model, it was shown that both adolescent and adult male offspring of adolescently-exposed dams exhibit greater sensitivity to  morphine -induced  conditioned place preference  than the control animals, even in the absence of any direct in utero exposure (  Byrnes et al., 2012 ). Moreover, unpublished data from the Byrnes laboratory shows that female offspring demonstrate enhanced expression of morphine-induced locomotor sensitization accompanied by increased expression of the  mu opioid receptor  in the  nucleus accumbens .

While no studies to date have examined the effect on the offspring of cannabinoid exposure in the sire prior to conception, available evidence suggests that disruptions in endocrine functioning resulting from cannabinoid exposure may cause deleterious effects in subsequent generations. For example,  tetrahydrocannabinol  ( THC ) disrupts gonadal functions by depriving testicular cells of energy reserves and stimulating androgen-binding protein  secretion which leads to oligospermia in chronic  cannabis smokers. THC also interferes with production of  prolactin luteinizing hormone  ( LH ), and follicle stimulating hormone  ( FSH ), which causes reduced  testosterone  production in the testes ( Banerjee et al., 2011 Harclerode, 1984  and  Husain and Khan, 1985 ). It has also been suggested that acute cannabinoid treatment affects the quality and quantity of spermatozoa produced by the testis ( Harclerode, 1984 ). Animal models have demonstrated that cannabinoid administration suppresses  gonadal steroids growth hormone , prolactin,  thyroid hormone  and activates the  HPA-axis  ( Banerjee et al., 2011  and  Brown and Dobs, 2002 ). These effects have been shown to be mediated by the binding of exogenous cannabinoids to the  endogenous  receptor in or near the hypothalamus  ( Brown and Dobs, 2002 ). However, the effects in humans have been inconsistent likely due to the development of tolerance ( Brown and Dobs, 2002 ). Finally, in humans, two case controlled studies found an increased risk for congenital heart defects associated with paternal marijuana use ( Ewing et al., 1997  and  Wilson et al., 1998 ). Clearly, there is a large gap in the literature examining the effects of marijuana use preconception on future generations.

5. Morphine

The significant impact of maternal  opioid  use on fetal outcomes and offspring neurodevelopment has been an area of interest for decades ( Hutchings, 1982 Malanga and Kosofsky, 1999  and  Vathy, 2002 ). In both substance abusing women and animal models of  prenatal  substance use the fetus is directly exposed to  opioids , limiting the applicability to a discussion on transgenerational  epigenetic  processes. To avoid direct fetal exposure, animal models were developed that expose both males and females to opioids preconception and then examine the effects on their offspring. Such studies have primarily examined the impact of exposure to  morphine  during adolescence. In male rats, morphine administered throughout adolescent development resulted in significant modifications in sexual maturation in the males themselves. When these males were mated to  drug naïve  females several weeks after morphine exposure, they produced smaller litters and as adults their offspring demonstrated significant modifications in endocrine  parameters, including sex specific changes in adrenal weights,  luteinizing hormone  and  hypothalamic  β-endorphin ( Cicero et al., 1991 ). As all that the male contributed in this model was sperm, such findings strongly suggest that prior exposure to opioids can induce transgenerational  epigenetic effects  even in the absence of continuing use.

Similar findings have been revealed using a female rat model. In those studies, females were exposed to an intermittent, increasing dose regimen of morphine during early-mid adolescence. All animals were then drug-free for several weeks prior to mating with drug naïve males. In these studies there were no significant differences in any postnatal parameter (i.e. litter size, weight, sex ratio). When offspring were examined as adults, however, a number of significant effects have been observed. These include sex-specific changes in social and emotional behaviors ( Byrnes et al., 2011  and  Johnson et al., 2011 ) as well as alterations in their response to morphine ( Byrnes, 2005  and  Byrnes et al., 2011 ). More recent findings using this model also observed significant changes in the functional response to  dopamine agonists  coupled with increased levels of dopamine- and opioid-related gene expression in the  nucleus accumbens . Of note, these effects were observed in both the first (F1) and second (F2) generation, suggesting multigenerational epigenetic effects triggered by adolescent exposure ( Byrnes et al., 2013 ).

The mechanisms underlying such intergenerational transmission are unknown and perhaps more complicated when considering maternal transmission. Exposure to drugs of abuse, even when experienced prior to conception, may alter the prenatal hormonal milieu, thereby modifying the developmental trajectory of offspring. Alternatively, or perhaps additionally, modifications in maternal care as a result of prior exposure to opioids, could impact the development of offspring. Indeed, morphine administered both prior to parturition or during active mothering significantly alters maternal care ( Bridges and Grimm, 1982 Mann et al., 1991 Miranda-Paiva et al., 2001  and  Slamberova et al., 2001 ). Moreover, non-genomic transmission via subtle variations in maternal care have been demonstrated repeatedly in animal models ( McLeod et al., 2007 Szyf et al., 2007 , Weaver, 2007  and  Weaver et al., 2004 ). Thus, one possible mechanism of transmission may be alterations in the pre- and/or postnatal environment.

Alternatively, exposure to opioids could directly affect epigenetic  germline cells  in the exposed male and female. Such effects could alter early embryogenesis and impact a number of developmental processes. These effects could then be passed forward via alterations in behavior/physiology of the next generation or via direct  epigenetic inheritance . Additional studies are needed to determine the mechanisms underlying transmission in both males and females exposed to opioids. Nonetheless, the nature of the observed offspring effects, including dysregulation of the  hypothalamic–pituitary–adrenal axis , increased sensitivity to opioids, and blunted response to dopamine agonists, all suggest that parental exposure to opioids prior to conception may increase the risk of substance use in their future offspring.

6. Cocaine

In terms of parental  cocaine  administration, the clinical and preclinical literatures have focused primarily on the developmental effects of  prenatal  cocaine exposure. In that regard, preclinical studies relatively consistently show disrupted cortical and hippocampal  development in the offspring as well as impaired  executive function  and memory following in utero cocaine exposure (  Dow-Edwards, 2011 Lidow, 2003  and  Malanga and Kosofsky, 2003 ).  Epigenetic  mechanisms appear to play a role in these changes in that male mice exposed to cocaine prenatally had altered patterns of DNA methylation  in hippocampal  pyramidal neurons  ( Novikova et al., 2008 ), which could underlie impaired sustained attention and  spatial working memory  observed in these offspring ( He et al., 2006b ). While interesting, studies of this sort are directly examining the effect of cocaine on development. Moreover, the dams were exposed to cocaine, which may have influenced maternal behaviors. These issues are largely obviated in experiments in which paternal cocaine exposure is examined.

It has long been known that cocaine concentrates in the testes at levels second only to the brain ( Mule et al., 1977  and  Yazigi et al., 1991 ) due primarily to specific binding sites in spermatozoa ( Yazigi et al., 1991 ). Animal studies showed that prolonged experimenter-administered cocaine (72–150 days) impaired spermatogenesis ( George et al., 1996 ) and increased the percentage of sperm with tails separated from their heads ( Abel et al., 1989 ). Although some evidence indicated that the fertility of cocaine-treated rats was substantially impaired ( George et al., 1996 ), fecundity remained sufficient to examine the effects of paternal cocaine exposure on their offspring. For example, paternal cocaine exposure decreased the weight of their progeny ( George et al., 1996  and  Killinger et al., 2012 ) but see also ( Abel et al., 1989 ). Experimenter-delivered cocaine to mouse sires also resulted in increased immobility in the  tail suspension test , a model of depression, but had no effect on locomotor activity, measures of anxiety or learning and memory ( Killinger et al., 2012 ). In contrast, the offspring of mouse sires that self-administered cocaine displayed attention and spatial working memory deficits, particularly among the female progeny ( He et al., 2006a ). Consistent with these results, the offspring of cocaine-exposed rat sires showed increased perseverance in a  T-maze learning task ( Abel et al., 1989 ). Interestingly, the expression of DNA  methyltransferase  1 (Dnmt-1) was decreased in the  seminiferous tubules  of the testis (the locus of spermatogenesis) of sires that self-administered cocaine ( He et al., 2006a ). Given that DNA  methyltransferases  play a critical role in maintaining imprinting in  germ cells , reduced Dnmt-1 in the sperm of sires that self-administered cocaine is a potential mechanism that may account for the intergenerational influence of paternal cocaine exposure ( He et al., 2006a ).

Notably, none of these studies examined cocaine reinforcement among the offspring. Therefore, two of the authors of the current paper (Vassoler and Pierce) and our colleagues examined cocaine self-administration in the offspring of sires that self-administered cocaine for 60 days. The male offspring of cocaine-experienced sires acquired cocaine self-administration more slowly and had decreased levels of cocaine intake relative to controls. Cocaine self-administration in female offspring did not differ between cocaine- and saline-exposed sires ( Vassoler et al., 2013 ). Previous work indicated that increased  brain derived neurotrophic factor  ( BDNF ) in the  medial prefrontal cortex  ( mPFC ) blunted the behavioral effects of cocaine ( Berglind et al., 2007  and  Sadri-Vakili et al., 2010 ). We showed that mPFC Bdnf mRNA and protein were increased only in the male offspring of sires that self-administered cocaine (  Vassoler et al., 2013 ). Moreover, increased association of  acetylated   histone H3  with Bdnf promoters was observed in the mPFC of male offspring, which is one mechanism that may underlie the enhanced BDNF transcription in the mPFC of cocaine-sired rats. Systemic administration of a BDNF  receptor antagonist  (the  TrkB receptor  antagonist ANA-12) normalized the decreased cocaine self-administration in male cocaine-sired rats. In addition, the association of acetylated histone H3 with Bdnf promoters was increased in the sperm of sires that self-administered cocaine (  Vassoler et al., 2013 ). Taken together, these findings indicated that voluntary paternal ingestion of cocaine reprograms the germline resulting in enhanced BDNF expression in the mPFC among male progeny, which appears to confer resistance to the reinforcing effects of cocaine. This result should be interpreted cautiously. It is as yet unknown if these male offspring have impairments in reward and motivational circuits that underlie the decreased self-administration behavior.

We examined paternal transmission in order to avoid the influence of in utero cocaine exposure and the potential influence of prior cocaine experience by dams on maternal behavior. It is possible that even the relatively brief exposure to a cocaine-experienced male during breeding might have an impact on maternal behavior. We examined licking/grooming and other maternal behaviors and found no differences between the dams bred with cocaine-experienced sires relative to controls (  Vassoler et al., 2013 ).

A critical unanswered question is whether this cocaine resistance  phenotype  is present in the F2 generation (i.e. the grandoffspring of cocaine-experienced sires). Since the sperm of the sires was exposed to cocaine, it cannot be assumed that the heritability is transgenerational. Indeed, as suggested above, it is possible that cocaine binding to the spermatozoa could allow for transport of cocaine into the fertilized ovum ( Yazigi et al., 1991 ). In order to demonstrate transgenerational heritability in these experiments, the epigenetic markers and associated  phenotypes  need to be observed in the F2 generation. It also is unclear why only the male offspring found cocaine less reinforcing. Given that  ovarian hormones  have been shown to have profound influences on the behavioral effects of cocaine ( Anker and Carroll, 2011 Hu and Becker, 2008  and  Quinones-Jenab and Jenab, 2010 ), it is possible that direct or indirect influences on  steroid hormones  may underlie the observed gender differences in the offspring of cocaine-experienced sires.

Resistance to cocaine in the offspring of sires that self-administered this drug is apparently at odds with human epidemiological data indicating that cocaine addiction is highly heritable ( Kendler et al., 2007 Merikangas et al., 1998  and  Tsuang et al., 1998 ). Of course, cocaine addiction is not completely heritable and all addictions are influenced by drug availability and many other environmental factors. In our study, environmental influences were controlled to an extent that is impossible in epidemiological experiments.

7. Conclusions

The idea that the environment of one generation can impact the  phenotype  of subsequent generations is not new. Jean-Baptiste Lamarck proposed a theory of evolution that incorporated environmental conditions as well as reproductive fitness into hereditary changes. His work was largely discredited and ignored for lack of mechanism and in favor Darwin's elegant description of “survival of the fittest” ( Burkhardt, 2009 ). However, it seems that some of his ideas had merit and can now be explained by the phenomenon of  epigenetics . The way that environmental exposures of one generation can influence and affect subsequent generations is of critical importance to the understanding of human behavior and evolution.

This review demonstrated that there are many consequences for the offspring of parents that were exposed to drugs, even in the absence of direct fetal exposure (summarized in Table 1 ). The idea that environmental toxins ingested prior to conception by either parent can have such a pronounced impact on the offspring needs further research and should garner more attention. In fact, one study found that the effects of paternal and maternal drug use had an additive effect on offspring's adolescent drug use trajectory rather than an interactive parental effect ( Walden et al., 2007 ). This suggests the need for policy change and new campaigns to spread awareness among men and women during adolescence and throughout child bearing years.

Table 1.

Preconception effects of drug exposure on subsequent generation.

Phenotype

Drug

Rodents

Humans

Decreased fecundity/fertility

Alcohol

Emanuele et al., 2001  and  Cicero et al., 1990

Tobacco

Blanco-Munoz et al., 2009 , Venners et al., 2004 Ozgur et al., 2005  and  Sofikitis et al., 1995

Cannabinoids

Banerjee et al., 2011 , Harclerode, 1984 Husain and Khan, 1985  and  Harclerode, 1984

Opioids

Cicero et al., 1991

Cocaine

George et al., 1996 Abel et al., 1989  and  Killinger et al., 2012

Developmental abnormalities

Alcohol

Jamerson et al., 2004  and  Bielawski and Abel, 1997

Lemoine et al., 2003 Little et al., 1980 Livy et al., 2004  and  Ramsay, 2010

Tobacco

Zwink et al., 2011 , Pembrey, 2010  and  Pembrey et al., 2006

Cannabinoids

Ewing et al., 1997  and  Wilson et al., 1998

Opioids

Cicero et al., 1991

Change in basal activity level

Alcohol

Abel, 1989a , 1993a;  Abel, 1989b Abel, 1993a Abel, 1993b  and  Abel and Lee, 1988

Goodwin et al., 1975

Anxiety/depression-like phenotypes

Alcohol

Abel, 1991a Abel, 1991b  and  Abel and Bilitzke, 1990

Opioids

Byrnes et al., 2011  and  Johnson et al., 2011

Cocaine

Killinger et al., 2012

Impairments in learning/memory/attention

Alcohol

Abel, 1994 Abel and Lee, 1988  and  Abel and Tan, 1988

Tarter et al., 1989

Cocaine

He et al., 2006a  and  Abel et al., 1989

Altered responsivity to drugs of abuse

Alcohol

Abel, 1993a

Cannabinoids

Byrnes et al., 2012

Opioids

Byrnes, 2005  and  Byrnes et al., 2011

Cocssaine

Vassoler et al., 2013

Table options

The results presented here suggest the intriguing, and potentially alarming, possibility that exposure to drugs of abuse produce transmissible  epigenetic  changes that result in profound alterations to the physiology and behavior of offspring. However, for an effect to be truly non-genomic  epigenetic inheritance , many of the experiments need to be carried to further generations to avoid exposure of the  germ cells  to the drug of abuse. The few studies that have looked beyond the first generation suggest that many  phenotypes persist. Regardless of the number of future generations preconception drug use influences, the impact on first generation offspring alone is sufficient to justify further research defining the extent of epigenetic heritability of phenotypes associated with parental drug abuse and the specific mechanisms underlying these effects

europharmacology

Volume 76, Part B, January 2014, Pages 269–275

NIDA 40th Anniversary Issue

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Invited review

The impact of exposure to addictive drugs on future generations: Physiological and behavioral effects

· F.M. Vassoler a, , , 

· E.M. Byrnes a

· R.C. Pierce b

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doi:10.1016/j.neuropharm.2013.06.016

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Highlights

Transgenerational consequences of exposure to drugs of abuse.

Paternal and maternal transmission to offspring prior to conception.

Alcohol, nicotinecannabinoidsopioidscocaine.

Abstract

It is clear that both genetic and environmental factors contribute to drug addiction. Recent evidence indicating trans-generational influences of drug abuse highlight potential epigenetic factors as well. Specifically, mounting evidence suggests that parental ingestion of abused drugs influence the physiology and behavior of future generations even in the absence of prenatal exposure. The goal of this review is to describe the trans-generational consequences of preconception exposure to drugs of abuse for five major classes of drugs: alcohol, nicotine, marijuana, opioids, and cocaine. The potential epigenetic mechanisms underlying the transmission of these phenotypesacross generations also are detailed.

This article is part of a Special Issue entitled ‘NIDA 40th Anniversary Issue’.

Keywords

· Transgenerational; 

· Epigenetic

· Drugs of abuse; 

· Alcohol; 

· Nicotine

· Marijuana; 

· Opioids;

· Cocaine

1. Introduction

Drug addiction is a serious medical and social issue in the United States and around the world. There is consistent evidence that substance use disorders run in families (Bierut et al., 1998Brook et al., 2002Cloninger et al., 1981 and Merikangas et al., 1998). Adoption, twin, and sibling studies implicate genetic factors in the heritability of abuse (Cloninger et al., 1981). However, simple genetic mechanisms of inheritance cannot explain all results (Cloninger et al., 1981 and Schuckit et al., 1972). Societal differences in drug use and consumption patterns vary from different time periods and between countries suggesting a large environmental component (UNODC, 2012). Thus, vulnerability to develop an addiction is dependent on both genetics and the environment. The sum of separate genetic and environmental contributions cannot fully explain the heritability either. Therefore, the interaction between genetics and the environment may help explain some of the discrepancies (Cloninger et al., 1981).

Epigenetics is a key mechanism by which the environment can influence and interact with genetics. In recent years, the term epigenetics has been used to describe myriad processes (Haig, 2004). For example, modifications to the structure of chromatin or DNA without changes in the sequence that affect gene transcription even in non-dividing cells such as DNA methylation or histone acetylation are described as epigeneticmodifications (Holliday, 1989). However, some definitions of epigenetics emphasize that the modifications in gene expression that do not involve alterations in the DNA sequencemust be heritable, spanning multiple generations. There has recently been an increase in studies examining the transgenerational effects of environmental toxins on offspring. The goal of the current review is to examine the available literature regarding the effects on offspring of parental drug exposure in the absence of any direct fetal exposure for five major drugs of abuse. While offspring susceptibility to drug use is of particular interest, all behavioral, molecular, and physiological changes in the offspring will be reported. The majority of the studies available on this topic focus on paternal transmission of epigeneticphenotypes, as this model eliminates any direct fetal exposure and ostensibly avoids maternal rearing effects. With regard to maternal transmission, there is certainly an extensive body of literature documenting offspring effects following prenatal exposure to drugs of abuse (Malanga and Kosofsky, 2003 and Sithisarn et al., 2012). Due to the possible direct effects of in utero exposure on the fetus, as well as the numerous confounds that drug use during pregnancy introduces (e.g. changes in nutritional status, renal function, vascular perfusion, etc.), prenatal substance use models will not be included in the current review. We will, however, include data from studies examining transgenerational effects of female drug use occurring prior to conception. Thus, the current review will examine the effects of parental exposure to drugs of abuse prior to conception on the development of subsequent generations.

2. Alcohol

Currently, alcohol is the most commonly abused drug in the United States. In 2011, the center for disease control estimated that 60% of males and 44% of females engage in chronic alcohol drinking (Edward J. Sondik et al., 2012). While the neurobehavioral effects of fetal alcohol exposure are well described, less is known about the effects of parental exposure to alcohol prior to conception. It should be noted, however, that reports and writings as early as the 1720's, during the so-called gin epidemic, observed that both maternal and paternal alcohol use had detrimental effects on offspring (Warner and Rosett, 1975). While few studies have examined maternal alcohol use prior to pregnancy (i.e. in the absence of prenatal use), several findings have demonstrated effects of paternal alcohol exposure on offspring development. Indeed, as early as 1913 animal studies found that offspring sired by alcohol inhaling rats demonstrated malformations, low birth weight, retarded growth and increased neonatal mortality across several generations (Friedler, 1996). Clearly the concept that alcohol use by the father, and not solely his genetic composition, can affect future progeny is not novel. The interest in paternal effects, however, has been reinvigorated by the emergence of the field of epigenetics, with a number of preclinical findings suggesting transgenerationalepigenetic effects of paternal alcohol use.

Several of the initial animal studies on paternal alcohol effects focused on basic parameters of reproductive success, such as fertility and fecundity, following exposure to alcohol in peripubertal males. These studies observed a significant reduction in the number of successful pregnancies which decreased from 92% in controls to 75% in naïve females mated with alcohol-drinking sires (Emanuele et al., 2001). Litter size was also substantially reduced (Cicero et al., 1990 and Emanuele et al., 2001). It was determined that alcohol exposure during puberty modified sexual maturation and resulted in decreased testes and secondary sex organ weight, eliminated the typical pubertal surge in testosterone, decreased beta-endorphin levels in the hypothalamus, and enhanced testicular oxidative injury (Cicero et al., 1990 and Emanuele et al., 2001). Interestingly, offspring of these pubertal alcohol-exposed sires demonstrated similar alterations, including decreased serum testosterone levels, reduced seminal vesicleweights, and lower levels of hypothalamic beta-endorphin (Abel and Lee, 1988 and Cicero et al., 1990).

Alcohol-sired offspring also demonstrate abnormalities in development. In an elegantly designed rodent study, Jamerson and colleagues revealed that paternal alcohol exposure that was ongoing, or that had ceased weeks prior to conception resulted in more rapid development of various reflexes, differences in gait, and thicker cortical layers(Jamerson et al., 2004). It was also noted that timing of alcohol exposure in relation to conception impacted the neurobehavioral effects of the offspring (Jamerson et al., 2004). For example, one study found that a single exposure to alcohol just prior to conception resulted in a significant increase in small for gestational age offspring as well as an increase in offspring demonstrating significant malformations (Bielawski and Abel, 1997). Moreover, alcohol-exposed sires also produced offspring displaying increasedadrenal cortex and decreased spleen weights (Abel, 1993b). Finally, there is evidence that metabolic and immune functioning may be disrupted in alcohol-sired offspring, given that they display reductions in leptin levels (Emanuele et al., 2001) and a diminished immune response (Berk et al., 1989 and Hazlett et al., 1989).

In terms of behavioral effects, both increases and decreases in activity have been noted in offspring of alcohol-consuming sires (Abel, 1989aAbel, 1989bAbel, 1993aAbel, 1993b and Abel and Lee, 1988), with the direction of these effects mediated by a number of factors including the level of alcohol consumption, the time between exposure and conception (Jamerson et al., 2004), and the age at the time of testing (Abel, 1989a). Alterations in behavioral activity following amphetamine were also noted in male offspring (Abel, 1993a), with some evidence suggesting that increased activity was dependent on the cholinergic system (Abel, 1994). Potential modifications in the cholinergic system of alcohol-sired offspring are notable given that deficits in learning and memory have also been reported. For example, offspring sired by alcohol treated males demonstrated impairments in spatial learning (Wozniak et al., 1991) and had increased latencies to reach a choice point in a T-maze (Abel, 1994 and Abel and Lee, 1988). In addition to deficits observed in males, alcohol-sired female offspring showed impaired performance in a two-way shock avoidance learning task (Abel and Tan, 1988). Finally, offspring of alcohol-consuming sires demonstrated decreased grooming as well as decreased immobility in a forced swim test, an effect that was rescued by imipramineand propranolol and exacerbated by yohimbine and metergoline (Abel, 1991aAbel, 1991b and Abel and Bilitzke, 1990). Together, these results indicate a detrimental behavioral phenotype of paternal alcohol consumption on both male and female offspring.

Examining epigenetic parental effects in human populations can be difficult. Human studies have, however, revealed correlations between parental drinking behavior and offspring initiation and drinking patterns. Thus, heavy paternal drinking or heavy-episodic drinking in both parents predicts earlier onset of offspring drinking as well as heavier drinking (Vermeulen-Smit et al., 2012). Children born with characteristics associated with fetal alcohol syndrome whose mother's did not drink but fathers were alcoholics have also been observed (Lemoine et al., 2003). Additionally, there is evidence that sons of early-onset (adolescent) alcoholic fathers perform more poorly on tests of verbalintelligence and attention than late onset (adult) alcoholics (Tarter et al., 1989). While this may suggest that adolescence, or periods of significant neural and endocrinedevelopment, are particularly important in determining the effects of paternal alcohol exposure, one cannot exclude the possibility that early-onset drinking may be a marker of genetic vulnerability or additional comorbid pathologies. Finally, in addition to deficits in cognition, attention, and visuospatial capacity observed in children of alcoholic fathers, increased hyperactivity has also been noted (Goodwin et al., 1975), although the relationship between hyperactivity and paternal alcohol consumption remains equivocal (Knopik et al., 2009). Much less work has been done examining the effects of maternal preconception alcohol consumption. However, a decreased birth weight has been observed in children of alcoholic women that abstain from use during pregnancy (Little et al., 1980Livy et al., 2004 and Ramsay, 2010). While human studies remain more difficult to interpret than preclinical research due to many aspects that are impossible to control, it is important that both lines of research continue in order to fully understand the scope of preconception alcohol use and abuse.

3. Nicotine

Nicotine is the second most abused substance in the United States. In 2011 it was reported that 21.6% of adult men and 16.5% of adult women smoke regularly (Agaku et al., 2011). It is clear from both human epidemiological and preclinical research models that exposure to tobacco smoke in utero is harmful to development and can result in low birth weight, sudden infant death syndrome, and serious behavioral issues in the offspring ( Abbott and Winzer-Serhan, 2012). Examining the indirect effects (i.e. non-prenatal exposure) in humans is more challenging because it is difficult to distinguish the indirect epigenetic effects of paternal or maternal nicotine abuse on the offspring from potential exposure to second-hand smoke in utero or post-partum. Keeping that in mind, some studies have shown increased risk of spontaneous abortion associated with paternal smoking ( Blanco-Munoz et al., 2009 and Venners et al., 2004). However, others have shown no association ( Chatenoud et al., 1998Windham et al., 1992 and Windham et al., 1999). Moreover, paternal smoking is a factor associated with anorectal malformations in humans in multiple studies (Zwink et al., 2011). Human epidemiological studies also indicate that early paternal smoking (onset before age 11) is associated with greater body mass index in male, but not female, offspring ( Pembrey, 2010 and Pembrey et al., 2006).

Aside from these few studies looking at the effect of paternal smoking on offspring, numerous studies have found evidence that male smoking affects multiple fertility factors in the male. Thus, paternal tobacco use is associated with defects in the tail of the spermatozoon (Ozgur et al., 2005) and decreases in sperm density, motility, and morphology (Sofikitis et al., 1995). Another study found no differences in sperm concentration or motility but decreased semen volume (Pasqualotto et al., 2006). Taken together, these studies point toward decreases in male fertility and/or embryo viability which suggests potential negative effects in the offspring. To date, we found only one animal study which found that paternal nicotine smoke exposure did not affect development or any behavioral parameters measured (Gaworski et al., 2004). More animal work is needed to determine if nicotine exposure and smoking has transgenerational epigenetic effects.

4. Cannabinoids

Marijuana is the most widely abused illicit substance in the United States. Of particular concern is the high percentage of adolescents that engage in marijuana use. It is estimated that almost 50% of teenagers have used marijuana and approximately 9% use marijuana heavily (>20 days out of the month) (Metlife, 2011). Marijuana use by adolescents may be particularly problematic as developing systems may be more vulnerable to the impact of exogenous cannabinoids (Rice and Barone, 2000). Abuse by adolescent females is of particular concern as the endogenous cannabinoid system is important for reproductive physiology, with CB1 receptors as well as endogenous cannabinoids expressed in the ovaries, uterine endometrium, and other peripheralendocrine tissue (Bari et al., 2011). Thus, cannabinoid exposure during this critical period could result in lasting modifications in female reproduction, and might impact future offspring. To examine the potential effects on offspring, adolescent females were exposed to cannabinoids during adolescence. They were then maintained drug-free for over 3 weeks and bred during adulthood. Using this model, it was shown that both adolescent and adult male offspring of adolescently-exposed dams exhibit greater sensitivity to morphine-induced conditioned place preference than the control animals, even in the absence of any direct in utero exposure ( Byrnes et al., 2012). Moreover, unpublished data from the Byrnes laboratory shows that female offspring demonstrate enhanced expression of morphine-induced locomotor sensitization accompanied by increased expression of the mu opioid receptor in the nucleus accumbens.

While no studies to date have examined the effect on the offspring of cannabinoid exposure in the sire prior to conception, available evidence suggests that disruptions in endocrine functioning resulting from cannabinoid exposure may cause deleterious effects in subsequent generations. For example, tetrahydrocannabinol (THC) disrupts gonadal functions by depriving testicular cells of energy reserves and stimulatingandrogen-binding protein secretion which leads to oligospermia in chronic cannabissmokers. THC also interferes with production of prolactinluteinizing hormone (LH), andfollicle stimulating hormone (FSH), which causes reduced testosterone production in the testes (Banerjee et al., 2011Harclerode, 1984 and Husain and Khan, 1985). It has also been suggested that acute cannabinoid treatment affects the quality and quantity of spermatozoa produced by the testis (Harclerode, 1984). Animal models have demonstrated that cannabinoid administration suppresses gonadal steroidsgrowth hormone, prolactin, thyroid hormone and activates the HPA-axis (Banerjee et al., 2011 and Brown and Dobs, 2002). These effects have been shown to be mediated by the binding of exogenous cannabinoids to the endogenous receptor in or near thehypothalamus (Brown and Dobs, 2002). However, the effects in humans have been inconsistent likely due to the development of tolerance (Brown and Dobs, 2002). Finally, in humans, two case controlled studies found an increased risk for congenital heart defects associated with paternal marijuana use (Ewing et al., 1997 and Wilson et al., 1998). Clearly, there is a large gap in the literature examining the effects of marijuana use preconception on future generations.

5. Morphine

The significant impact of maternal opioid use on fetal outcomes and offspring neurodevelopment has been an area of interest for decades (Hutchings, 1982Malanga and Kosofsky, 1999 and Vathy, 2002). In both substance abusing women and animal models of prenatal substance use the fetus is directly exposed to opioids, limiting the applicability to a discussion on transgenerational epigenetic processes. To avoid direct fetal exposure, animal models were developed that expose both males and females to opioids preconception and then examine the effects on their offspring. Such studies have primarily examined the impact of exposure to morphine during adolescence. In male rats, morphine administered throughout adolescent development resulted in significant modifications in sexual maturation in the males themselves. When these males were mated to drug naïve females several weeks after morphine exposure, they produced smaller litters and as adults their offspring demonstrated significant modifications inendocrine parameters, including sex specific changes in adrenal weights, luteinizing hormone and hypothalamic β-endorphin (Cicero et al., 1991). As all that the male contributed in this model was sperm, such findings strongly suggest that prior exposure to opioids can induce transgenerational epigenetic effects even in the absence of continuing use.

Similar findings have been revealed using a female rat model. In those studies, females were exposed to an intermittent, increasing dose regimen of morphine during early-mid adolescence. All animals were then drug-free for several weeks prior to mating with drug naïve males. In these studies there were no significant differences in any postnatal parameter (i.e. litter size, weight, sex ratio). When offspring were examined as adults, however, a number of significant effects have been observed. These include sex-specific changes in social and emotional behaviors (Byrnes et al., 2011 and Johnson et al., 2011) as well as alterations in their response to morphine (Byrnes, 2005 and Byrnes et al., 2011). More recent findings using this model also observed significant changes in the functional response to dopamine agonists coupled with increased levels of dopamine- and opioid-related gene expression in the nucleus accumbens. Of note, these effects were observed in both the first (F1) and second (F2) generation, suggesting multigenerational epigenetic effects triggered by adolescent exposure (Byrnes et al., 2013).

The mechanisms underlying such intergenerational transmission are unknown and perhaps more complicated when considering maternal transmission. Exposure to drugs of abuse, even when experienced prior to conception, may alter the prenatal hormonal milieu, thereby modifying the developmental trajectory of offspring. Alternatively, or perhaps additionally, modifications in maternal care as a result of prior exposure to opioids, could impact the development of offspring. Indeed, morphine administered both prior to parturition or during active mothering significantly alters maternal care (Bridges and Grimm, 1982Mann et al., 1991Miranda-Paiva et al., 2001 and Slamberova et al., 2001). Moreover, non-genomic transmission via subtle variations in maternal care have been demonstrated repeatedly in animal models (McLeod et al., 2007Szyf et al., 2007,Weaver, 2007 and Weaver et al., 2004). Thus, one possible mechanism of transmission may be alterations in the pre- and/or postnatal environment.

Alternatively, exposure to opioids could directly affect epigenetic germline cells in the exposed male and female. Such effects could alter early embryogenesis and impact a number of developmental processes. These effects could then be passed forward via alterations in behavior/physiology of the next generation or via direct epigenetic inheritance. Additional studies are needed to determine the mechanisms underlying transmission in both males and females exposed to opioids. Nonetheless, the nature of the observed offspring effects, including dysregulation of the hypothalamic–pituitary–adrenal axis, increased sensitivity to opioids, and blunted response to dopamine agonists, all suggest that parental exposure to opioids prior to conception may increase the risk of substance use in their future offspring.

6. Cocaine

In terms of parental cocaine administration, the clinical and preclinical literatures have focused primarily on the developmental effects of prenatal cocaine exposure. In that regard, preclinical studies relatively consistently show disrupted cortical andhippocampal development in the offspring as well as impaired executive function and memory following in utero cocaine exposure ( Dow-Edwards, 2011Lidow, 2003 and Malanga and Kosofsky, 2003). Epigenetic mechanisms appear to play a role in these changes in that male mice exposed to cocaine prenatally had altered patterns ofDNA methylation in hippocampal pyramidal neurons (Novikova et al., 2008), which could underlie impaired sustained attention and spatial working memory observed in these offspring (He et al., 2006b). While interesting, studies of this sort are directly examining the effect of cocaine on development. Moreover, the dams were exposed to cocaine, which may have influenced maternal behaviors. These issues are largely obviated in experiments in which paternal cocaine exposure is examined.

It has long been known that cocaine concentrates in the testes at levels second only to the brain (Mule et al., 1977 and Yazigi et al., 1991) due primarily to specific binding sites in spermatozoa (Yazigi et al., 1991). Animal studies showed that prolonged experimenter-administered cocaine (72–150 days) impaired spermatogenesis (George et al., 1996) and increased the percentage of sperm with tails separated from their heads (Abel et al., 1989). Although some evidence indicated that the fertility of cocaine-treated rats was substantially impaired (George et al., 1996), fecundity remained sufficient to examine the effects of paternal cocaine exposure on their offspring. For example, paternal cocaine exposure decreased the weight of their progeny (George et al., 1996 and Killinger et al., 2012) but see also (Abel et al., 1989). Experimenter-delivered cocaine to mouse sires also resulted in increased immobility in the tail suspension test, a model of depression, but had no effect on locomotor activity, measures of anxiety or learning and memory (Killinger et al., 2012). In contrast, the offspring of mouse sires that self-administered cocaine displayed attention and spatial working memory deficits, particularly among the female progeny (He et al., 2006a). Consistent with these results, the offspring of cocaine-exposed rat sires showed increased perseverance in a T-mazelearning task (Abel et al., 1989). Interestingly, the expression of DNA methyltransferase 1 (Dnmt-1) was decreased in the seminiferous tubules of the testis (the locus of spermatogenesis) of sires that self-administered cocaine (He et al., 2006a). Given that DNA methyltransferases play a critical role in maintaining imprinting in germ cells, reduced Dnmt-1 in the sperm of sires that self-administered cocaine is a potential mechanism that may account for the intergenerational influence of paternal cocaine exposure (He et al., 2006a).

Notably, none of these studies examined cocaine reinforcement among the offspring. Therefore, two of the authors of the current paper (Vassoler and Pierce) and our colleagues examined cocaine self-administration in the offspring of sires that self-administered cocaine for 60 days. The male offspring of cocaine-experienced sires acquired cocaine self-administration more slowly and had decreased levels of cocaine intake relative to controls. Cocaine self-administration in female offspring did not differ between cocaine- and saline-exposed sires (Vassoler et al., 2013). Previous work indicated that increased brain derived neurotrophic factor (BDNF) in the medial prefrontal cortex (mPFC) blunted the behavioral effects of cocaine (Berglind et al., 2007 and Sadri-Vakili et al., 2010). We showed that mPFC Bdnf mRNA and protein were increased only in the male offspring of sires that self-administered cocaine ( Vassoler et al., 2013). Moreover, increased association of acetylated histone H3 with Bdnf promoters was observed in the mPFC of male offspring, which is one mechanism that may underlie the enhanced BDNF transcription in the mPFC of cocaine-sired rats. Systemic administration of a BDNF receptor antagonist (the TrkB receptor antagonist ANA-12) normalized the decreased cocaine self-administration in male cocaine-sired rats. In addition, the association of acetylated histone H3 with Bdnf promoters was increased in the sperm of sires that self-administered cocaine ( Vassoler et al., 2013). Taken together, these findings indicated that voluntary paternal ingestion of cocaine reprograms the germline resulting in enhanced BDNF expression in the mPFC among male progeny, which appears to confer resistance to the reinforcing effects of cocaine. This result should be interpreted cautiously. It is as yet unknown if these male offspring have impairments in reward and motivational circuits that underlie the decreased self-administration behavior.

We examined paternal transmission in order to avoid the influence of in utero cocaine exposure and the potential influence of prior cocaine experience by dams on maternal behavior. It is possible that even the relatively brief exposure to a cocaine-experienced male during breeding might have an impact on maternal behavior. We examined licking/grooming and other maternal behaviors and found no differences between the dams bred with cocaine-experienced sires relative to controls ( Vassoler et al., 2013).

A critical unanswered question is whether this cocaine resistance phenotype is present in the F2 generation (i.e. the grandoffspring of cocaine-experienced sires). Since the sperm of the sires was exposed to cocaine, it cannot be assumed that the heritability is transgenerational. Indeed, as suggested above, it is possible that cocaine binding to the spermatozoa could allow for transport of cocaine into the fertilized ovum (Yazigi et al., 1991). In order to demonstrate transgenerational heritability in these experiments, the epigenetic markers and associated phenotypes need to be observed in the F2 generation. It also is unclear why only the male offspring found cocaine less reinforcing. Given that ovarian hormones have been shown to have profound influences on the behavioral effects of cocaine (Anker and Carroll, 2011Hu and Becker, 2008 and Quinones-Jenab and Jenab, 2010), it is possible that direct or indirect influences on steroid hormones may underlie the observed gender differences in the offspring of cocaine-experienced sires.

Resistance to cocaine in the offspring of sires that self-administered this drug is apparently at odds with human epidemiological data indicating that cocaine addiction is highly heritable (Kendler et al., 2007Merikangas et al., 1998 and Tsuang et al., 1998). Of course, cocaine addiction is not completely heritable and all addictions are influenced by drug availability and many other environmental factors. In our study, environmental influences were controlled to an extent that is impossible in epidemiological experiments.

7. Conclusions

The idea that the environment of one generation can impact the phenotype of subsequent generations is not new. Jean-Baptiste Lamarck proposed a theory of evolution that incorporated environmental conditions as well as reproductive fitness into hereditary changes. His work was largely discredited and ignored for lack of mechanism and in favor Darwin's elegant description of “survival of the fittest” (Burkhardt, 2009). However, it seems that some of his ideas had merit and can now be explained by the phenomenon of epigenetics. The way that environmental exposures of one generation can influence and affect subsequent generations is of critical importance to the understanding of human behavior and evolution.

This review demonstrated that there are many consequences for the offspring of parents that were exposed to drugs, even in the absence of direct fetal exposure (summarized inTable 1). The idea that environmental toxins ingested prior to conception by either parent can have such a pronounced impact on the offspring needs further research and should garner more attention. In fact, one study found that the effects of paternal and maternal drug use had an additive effect on offspring's adolescent drug use trajectory rather than an interactive parental effect (Walden et al., 2007). This suggests the need for policy change and new campaigns to spread awareness among men and women during adolescence and throughout child bearing years.

Table 1.

Preconception effects of drug exposure on subsequent generation.

Phenotype

Drug

Rodents

Humans

Decreased fecundity/fertility

Alcohol

Emanuele et al., 2001 and Cicero et al., 1990

Tobacco

Blanco-Munoz et al., 2009,Venners et al., 2004Ozgur et al., 2005 and Sofikitis et al., 1995

Cannabinoids

Banerjee et al., 2011,Harclerode, 1984Husain and Khan, 1985 and Harclerode, 1984

Opioids

Cicero et al., 1991

Cocaine

George et al., 1996Abel et al., 1989 and Killinger et al., 2012

Developmental abnormalities

Alcohol

Jamerson et al., 2004 and Bielawski and Abel, 1997

Lemoine et al., 2003Little et al., 1980Livy et al., 2004 and Ramsay, 2010

Tobacco

Zwink et al., 2011,Pembrey, 2010 and Pembrey et al., 2006

Cannabinoids

Ewing et al., 1997 and Wilson et al., 1998

Opioids

Cicero et al., 1991

Change in basal activity level

Alcohol

Abel, 1989a, 1993a; Abel, 1989bAbel, 1993aAbel, 1993b and Abel and Lee, 1988

Goodwin et al., 1975

Anxiety/depression-like phenotypes

Alcohol

Abel, 1991aAbel, 1991b and Abel and Bilitzke, 1990

Opioids

Byrnes et al., 2011 and Johnson et al., 2011

Cocaine

Killinger et al., 2012

Impairments in learning/memory/attention

Alcohol

Abel, 1994Abel and Lee, 1988 and Abel and Tan, 1988

Tarter et al., 1989

Cocaine

He et al., 2006a and Abel et al., 1989

Altered responsivity to drugs of abuse

Alcohol

Abel, 1993a

Cannabinoids

Byrnes et al., 2012

Opioids

Byrnes, 2005 and Byrnes et al., 2011

Cocssaine

Vassoler et al., 2013

Table options

The results presented here suggest the intriguing, and potentially alarming, possibility that exposure to drugs of abuse produce transmissible epigenetic changes that result in profound alterations to the physiology and behavior of offspring. However, for an effect to be truly non-genomic epigenetic inheritance, many of the experiments need to be carried to further generations to avoid exposure of the germ cells to the drug of abuse. The few studies that have looked beyond the first generation suggest that many phenotypespersist. Regardless of the number of future generations preconception drug use influences, the impact on first generation offspring alone is sufficient to justify further research defining the extent of epigenetic heritability of phenotypes associated with parental drug abuse and the specific mechanisms underlying these effects

SOBER LIVING COMMUNITY REF 2.docx

SOBER LIVING COMMUNITY

Helping People Help Themselves

HEALTH

INTENTION

SPIRITUALITY

PRUDENCE

ACCURATE THOUGHT

LOVE

SELF

-

EFFICACY

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TO MY SERENITY

1

THE TOLL ADDICTION TAKES ON THE BODY

By Andrew T. Martin, MBA, CADC II

, SAP

Most of us have heard the phrase ‘Our body is our temple’, which accurately conveys the message

that without a healthy body other aspects of our lives may suffer. Most of us have also known people

that have mistreated their body and have suffered serious health consequences.

For example, the

individual who consumes vast amounts of sugar and becomes obese with complications of

hypertension

, joint ailments, and sleep disturbance.

Most of us have also known people suffering

from a disease with symptoms that

seriously i

mpact physical health, such as arthritis.

When we

consider

the human body that has been impacted by the disease of

chemical dependency, there is a

lso

significant impact on physical health.

Before we look at the impact of addiction on the huma

n body, let’s consider the healthy behaviors in

recovery that can help nurse the body back to health.

When the individual suffering from the disease

of addiction is in remission (aka abstinence and recovery)

, there is an opportunity for the body to heal

itself in many ways. This healing requires discipline on the part of the afflicted individual, and with

time, the body can make astounding healing progress. One of the seven principles of Balanced

Center Living is entitled “Health” and does a good job of

outlining the behaviors necessary for the

body to physically mend.

SOBER LIVING COMMUNITY

Helping People Help Themselves

HEALTH

INTENTION

SPIRITUALITY

PRUDENCE

ACCURATE THOUGHT

LOVE

SELF

-

EFFICACY

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2

1.

Health

1.1.

Rest

The physical body requires rest to recover from strain and to grow. The cognitive

mind must rest, or enter into an anabolic state where simple

substances are

synthesized into complex living tissues, in order to maintain normal function. The

average adult requires 7

-8 hours of sleep each day, although some require as few as 5

hours and some as much as 10 hours each day.

1.2.

Nutrition

The best way to g

ive your body the balanced nutrition it needs to function properly is

by eating a variety of nutrient

-packed foods every day that stay within your daily

calorie needs. Just be sure to stay within your daily calorie needs.

A healthy eating

plan is one that:

Emphasizes fruits, vegetables, whole grains, and fat

-free or low

-fat milk and

milk products.

Includes lean meats, poultry, fish, beans, eggs, and nuts.

Is low in saturated fats,

trans

-fats, cholesterol, s

alt (sodium), and added

sugars.

1.3.

Exercise

Moderate

cardiovascular exercise for 20

-30 minutes each day will significantly

improve the body’s health. Moderate exercise is the equivalent of walking or jogging

at a 4

– 5 mile per hour pace. Strength training is also beneficial because muscle

tissue tends to b

reak down without use.

1.4.

Play

Play energizes us. It makes us happier, renews a natural sense of optimism and allows

our imaginations to thrive.

Play allows

us

to practice, elaborate on, and perfect skills

before they become necessary

(Ru

bin, 1982).

1.5.

Adventure

Activities for the purpose of recreation or excitement, whether potentially dangerous

or not, creates psychological and physiological arousal that is interpreted in our mind

as positive or negative. Adventurous experiences push our limits and provide

opportunities for internal growth.

1.6.

Creativity

Mental processes (e.g. art, music, abstract thought, writing, etc.), involving the

generation of new ideas or concepts, or new association between ideas or concepts.

Creativity stimulates the brain and causes intellectual growth and elevates mood.

Creative insight can evoke feelings of elation, personal awareness and spiritual

enhancement.

SOBER LIVING COMMUNITY

Helping People Help Themselves

HEALTH

INTENTION

SPIRITUALITY

PRUDENCE

ACCURATE THOUGHT

LOVE

SELF

-

EFFICACY

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When an individual is suffering from the physiological effects of addiction, their body is impacted in

several ways. Pri

mary

detrimental effects are located in the filtering organs such as the liver and

kidneys, and control organs in the body such as the brain and glands, and the cardiovascular system

such as the lungs, heart and blood vessels.

There are also detrimental effects in many other systems

and organs in the body. The extent of the damage caused by the disease is entirely dependent upon

the substance being ingested, the duration and quantity of the substance, and the capabilities of the

individual’

s physiology.

The National Institute on Drug Abuse has comp

iled the results of extensive research on the various

health effects of mood altering addictive substances on the human body.

Cannabis

(Marijuana

, Hashish,

THC, blunt, boom,

dope,

gangster,

ganja, grass, hash,

hash oil, hemp, herb, joint, bud,

Mary Jane, pot, reefer, green, trees, smoke, sinsemilla, skunk, weed)

Acute

Health Effects

Heightened sensory perception; euphoria, followed by drowsiness/relaxation; impaired

short

-term memory, attention, judgment, coord

ination and balance; increased heart rate;

increased appetite

Long

-

term

Health Effects

Addiction: About 9 percent of users; about 1 in 6 of those who started using in their teens;

25 to 50 % of daily users

Mental disorders: May be a causal factor in schizophreniform disorders (in those with a

pre-

existing vulnerability); is associated with depression and anxiety

Smoking related: Chronic cough; bronchitis; lung and upper airway cancers is

undetermined

Cocaine

(blow, bump, C, candy, Charlie, coke, cr

ack, flake, rock, snow, toot)

Acute

Health Effects

Dilated pupils; increased body temperature, heart rate, and blood pressure; nausea;

increased energy, alertness; euphoria; decreased appetite and sleep

High doses: Erratic and violent behavior, panic

attacks

Long

-

term

Health Effects

Addiction, restlessness, anxiety, irritability, paranoia, panic attacks, mood disturbances;

insomnia; nasal damage and difficulty swallowing from snorting; GI problems; HIV

Prescription Stimulants

(Amphetamine,

Methylphenidate, bennies, black beauties, crosses, hearts, LA

turnaround, speed, truck drivers, uppers)

Acute

Health Effects

Increased alertness, attention, energy; irregular heartbeat, dangerously high body

temperature, potential for cardiovascular

failure or seizures

SOBER LIVING COMMUNITY

Helping People Help Themselves

HEALTH

INTENTION

SPIRITUALITY

PRUDENCE

ACCURATE THOUGHT

LOVE

SELF

-

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Long

-

term

Health Effects

High doses, or alternate routes of administration (e.g., snorting, injecting): Anxiety,

hostility, paranoia, psychosis; addiction

Methamphetamine

(meth, ice, crank, chalk, crystal, fire, glass, go fast, speed

)

Acute

Health Effects

Enhanced mood; increased heart rate, blood pressure, body temperature, energy and

activity; decreased appetite; dry mouth; increased sexuality; jaw

-

clenching

Long

-

term

Health Effects

Addiction, memory loss; weight loss; impaired

cognition; insomnia, anxiety, irritability,

confusion, paranoia, aggression, mood disturbances, hallucinations, violent behavior; liver,

kidney, lung damage; severe dental problems; cardiac and neurological damage; HIV,

Hepatitis

Inhalants

(aerosol propellants, butane, gasoline, glues, isoamyl, isobutyl, cyclohexyl, laughing gas, nitrous oxide, paint

thinners, poppers, propane, snappers, whippets)

Acute

Health Effects

Confusion; nausea; slurred speech; lack of coordination; euphoria; dizzi

ness; drowsiness;

disinhibition, lightheadedness, hallucinations/ delusions; headaches; suffocation;

convulsions/seizures; hypoxia; heart failure; coma; sudden sniffing death (butane,

propane, and other chemicals in aerosols)

Nitrites:

Systemic vasodilati

on; increased heart rate; brief sensation of heat and

excitement; dizziness; headache

Long

-

term

Health Effects

Myelin break down leading to muscle spasms, tremors and possible permanent motor

impairment; liver/kidney damage

Addiction: A minority inhale o

n a regular basis, but among those, some report symptoms

of addiction (need to continue using, despite severe adverse consequences).

Nitrites:

HIV/AIDS and hepatitis; lipoid pneumonia

Prescription Sedatives, sleepin

g pills*, or anxiolytics

(barbiturates, benzodiazepines)

Acute

Health Effects

Drowsiness, relaxation; overdose

Long

-

term

Health Effects

Tolerance, physical dependence, addiction

Hallucinogens

(LSD, PCP, MDMA, Psilocybin, Salvia, Ketamine, acid, adam, angel dust, blotter, boat, blue heaven,

buttons, cactus, clarity, cubes, ecstacy, eve, hog, little smoke, love boat, lover’s speed, magic mushrooms, Maria Pastora,

magic mint, microdot, mesc, peac

e, peace pill, peyote, purple passion, Sally

-

D, shrooms, uppers, yellow sunshine)

LSD

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HEALTH

INTENTION

SPIRITUALITY

PRUDENCE

ACCURATE THOUGHT

LOVE

SELF

-

EFFICACY

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5

Acute

Health Effects

Elation, depression, arousal, paranoia or panic; impulsive behavior, rapid shifts in emotions;

distortions in perception. Increased body temperature, heart rate, blood pressure; nausea;

loss of appetite; jaw

-clenching; numbness; sleeplessness; dizziness, weakness, tremors

High doses: Panic, paranoia, feelings of despair, fear of insanity and death

Long

-

term

Health Effects

Frightening flas

hbacks, Hallucinogen Persisting Perception Disorder (HPPD), low addictive

potential; however, tolerance possible

PCP

Acute

Health Effects

Low Doses: Shallow, rapid breathing, increase in heart rate and blood pressure; nausea,

blurred vision, dizziness; numbness; slurred speech; confusion; loss of coordination; muscle

contractions; analgesia; altered perceptions; feelings of being separated from one’s body

High Doses: Feelings of invulnerability and exaggerated strength; seizures, coma,

hyperthermia

MDM

A (Ecstasy)

Acute

Health Effects

Euphoria; increased energy, alertness, tactile sensitivity, empathy; decreased fear, anxiety;

increased/irregular heartbeat; dehydration; chills; sweating; impaired cognition and motor

function; reduced appetite; muscle cr

amping; teeth grinding/clenching; in rare cases

hyperthermia, rhabdomyolysis, and death

Long

-

term

Health Effects

Impulsiveness; irritability; sleep disturbances; anxiety addiction

Psilocybin

Acute

Health Effects

Low doses: Relaxation; altered sensory

perception; increased energy, heart rate; decreased

appetite

High doses: Effects similar to LSD, including visual hallucinations, altered perceptions;

nervousness, confusion, panic, paranoia

Long

-

term

Health Effects

Low addictive potential, however may p

roduce tolerance

Salvia

Acute

Health Effects

Short

-

lived, but intense hallucinations, altered visual perception, mood, body sensations;

emotional swings, feelings of detachment from one’s body; highly modified perception of

external reality and self;

sweating

Long

-

term

Health Effects

Unknown addictive potential

SOBER LIVING COMMUNITY

Helping People Help Themselves

HEALTH

INTENTION

SPIRITUALITY

PRUDENCE

ACCURATE THOUGHT

LOVE

SELF

-

EFFICACY

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Unmodified duplication of this document in its entirety is permitted.

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TO MY SERENITY

6

Ketamine (similar to PCP)

Acute

Health Effects

Anxiety; agitation; insomnia; euphoria; excitement; slurred speech; blurred vision; irregular

heartbeat

Low Doses: Nausea; elevated blood pressure; sedation; analgesia; impaired attention;

memory and motor function

Higher Doses: Immobility; distortions of auditory and visual perceptions; feelings of being

separated from one’s body and environment; hallucinations; memory problems

Long

-

term

Health Effects

Cognitive impairment, including verbal and short

-

term memory; blurred vision; loss of

coordination

Street Opioids

(Heroin, Opium

, big O, black stuff, block, brown sugar, cheese,

China white, dope, gum,

H,

hop,

horse, junk, skag, skunk, smack, white horse,

)

Acute

Health Effects

Euphoria; warm flushing of skin; dry mouth; heavy feeling in extremities; clouded thinking;

alternate wakeful and drowsy states; itching; nausea; depressed respiration

Long

-

term

Health

Effects

Addiction; physical dependence; collapsed veins; abscesses; infection of heart lining and

valves; arthritis/other rheumatologic problems; HIV; Hepatitis C

Prescription Opioids

(Hydrocodone, Oxycodone, Codeine)

Acute

Health Effects

Pain relief,

drowsiness, nausea, constipation, euphoria

in some

When taken by routes other than as prescribed (e.g., snorted, injected), increased risk of

depressed respiration, leading to coma, death; CDC reports marked increases in

unintentional poisoning deaths since late the 1990s, due mainly to opioid pain reliever

overdose (often in combination with alcohol or other drugs).

Long

-

term

Health Effects

Tolerance, addiction

Androgenic Anabolic Ster

oids

(juice,

gym candy, pumpers, roids)

Acute

Health Effects

Headaches, acne; fluid retention (especially in the extremities), gastrointestinal irritation,

diarrhea, stomach pains, and an oily skin, jaundice, and hypertension; infections possible at

injection site

Long

-

term

Health Effects

Liver damage; CVD: high

blood pressure; increases in LDL (“bad” cholesterol); and decreases

in HDL (“good” cholesterol); cardiac hypertrophy, atherosclerosis