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Adolescent Drug Exposure: A Review of Evidence for the Development of Persistent Changes in Brain Function

Article in Brain Research Bulletin · January 2020

DOI: 10.1016/j.brainresbull.2020.01.007

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Brain Research Bulletin

journal homepage:www.elsevier.com/locate/brainresbull

Adolescent drug exposure: A review of evidence for the development of persistent changes in brain function

Hamed Salmanzadeh

^a,c

, S. Mohammad Ahmadi-Soleimani

^b

, Narges Pachenari

^a

, Maryam Azadi

^a

, Robert F. Halliwell

^c

, Tiziana Rubino

^d

, Hossein Azizi

^a,

*

aDepartment of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

bNeuroscience Research Center, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran

cTJ Long School of Pharmacy & Health Sciences, University of the Paciﬁc, Stockton, CA, USA

dDepartment of Biotechnology and Life Sciences, University of Insubria, Busto Arsizio, VA, Italy

A R T I C L E I N F O

Keywords:

Adolescence Brain development Nicotine Opioids Cannabinoids Alcohol Cocaine Amphetamines

A B S T R A C T

Over the past decade, many studies have indicated that adolescence is a critical period of brain development and maturation. The reﬁnement and maturation of the central nervous system over this prolonged period, however, makes the adolescent brain highly susceptible to perturbations from acute and chronic drug exposure. Here we review the preclinical literature addressing the long-term consequences of adolescent exposure to common re- creational drugs and drugs-of-abuse. These studies on adolescent exposure to alcohol, nicotine, opioids, cannabinoids and psychostimulant drugs, such as cocaine and amphetamine, reveal a variety of long-lasting behavioral and neurobiological consequences. These agents can aﬀect development of the prefrontal cortex and mesolimbic dopamine pathways and modify the reward systems, socio-emotional processing and cognition.

Other consequences include disruption in working memory, anxiety disorders and an increased risk of subsequent drug abuse in adult life. Although preventive and control policies are a valuable approach to reduce the detrimental eﬀects of drugs-of-abuse on the adolescent brain, a more profound understanding of their neurobiological impact can lead to improved strategies for the treatment and attenuation of the detrimental neu- ropsychiatric sequelae.

1. Introduction

The use of addictive substances by adolescents is a growing concern associated with complications such as intoxication and multi-drug abuse. Developmental changes in the brain, including synaptic pruning, a reduction in cortical and subcortical gray volume, maturation of axons and myelination, continue throughout the entire period of ado- lescence (Andersen, 2003; Schepis et al., 2008). Despite the dis- crepancies in overall brain complexity and the relative length of the adolescent period, similar processes occur in a variety of mammalian species, (Spear, 2000a,b,c; Spear, 2016). For instance, in rats, the period between postnatal days (PND) 28 and 42 is considered the early- mid adolescent period (∼12–17 years in humans), whereas the later interval (PND

∼43–55) may model the late adolescence/emerging

adulthood period (

∼

18

–

25 years) in humans (Spear, 2015). The conserved nature of changes in the brain during adolescence among various species therefore supports the use of animals to investigate the neurobiological impact of drug exposure and its associated consequences

(Spear, 2016).

Maladaptive behaviors can result from drug addiction (Nesse and Berridge, 1997) but studies also suggest that drugs-of-abuse might have beneﬁcial eﬀects under circumstances of controlled use (Morgan et al., 2013; Wol

ﬀ

et al., 2014). The notion of psychoactive drugs having positive eﬀects or being

instrumentalized

has an evident neuronal basis (Müller and Kornhuber, 2017; Müller and Schumann, 2011; Ahmed et al., 2018). For example, chronic nicotine administration can e

ﬀ

ec- tively reverse hypofrontality in prefrontal cortex (PFC) and improve cognitive deficits in an animal model of schizophrenia (Koukouli et al., 2017). Also, free-choice alcohol consumption has been found to restore sphingolipid and monoamine homeostasis in mice. This supports the antidepressant effect of alcohol self-medication in human subjects suf- fering depression (Müller et al., 2017). However, accumulating evidence suggests that drug administration during adolescence can induce a variety of effects different from those observed with consumption in adulthood. It can adversely influence neural, behavioral and cognitive functions even long after early life exposure. In this review, we will

https://doi.org/10.1016/j.brainresbull.2020.01.007

Received 7 November 2019; Received in revised form 28 December 2019; Accepted 6 January 2020

⁎Corresponding author.

E-mail address:[email protected](H. Azizi).

Available online 08 January 2020

T

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discuss the

ﬁ

ndings on the long-term changes induced by adolescent drug abuse during this critical time window (see Fig. 1).

2. Adolescence: deﬁnition and characteristics

Adolescence is a transitional phase from childhood to adulthood, characterized by major hormonal, physiological, behavioral and psy- chological changes. This developmental stage shares similar changes and is conserved among mammalian species. Adolescence and puberty are two terms that should not be used interchangeably: during puberty the levels of gonadal hormones increase and sexual maturation occurs.

In contrast, adolescence is a gradual change from childhood during which cognitive, emotional and social skills are acquired and the in- dividual begins to become independent from the family (Sisk and Foster, 2004; Varlinskaya et al., 2013). Deﬁning the exact onset and end of adolescence is diﬃcult although some studies consider the physiological changes of puberty as the onset of adolescence (Spear, 2000a,b,c).

Adolescence is commonly divided into early, mid and late stages. In humans, around 10

–

14 years of age is considered as early, 15

–

17 years old as mid and 18

–

25 years old as late adolescent and/or emerging adulthood (Arnett, 2000). Similar stages are found in rodents, where PNDs 28

–

42 are considered as early-mid adolescence and PNDs 42

–

55 are more related to late adolescence/emerging adulthood (Vetter- O’Hagen and Spear, 2012). Diﬀerent physiological and behavioral characteristics are associated with each of these stages. For example, in a human study, conducted on individuals within the age range of 10–30, enhanced reward seeking was observed during mid-adolescence while impulsivity steadily declines from age 10 on (Steinberg, 2010).

It is well established that during adolescence signi

ﬁ

cant transitions occur and a person attains special characteristics critical for social life and healthy living in a community. Social interaction with peers (Csikszentmihalyi et al., 1977), novelty seeking, high activity, high exploration and emotional instability, and enhanced risk taking are among the characteristics shaped during this developmental stage (Spear, 2000c). It is expected that at the end of this period a person becomes independent from parents.

It is also notable that this is the time period for the emergence of psychiatric and mental disorders like depression, schizophrenia, anxiety, eating disorders and substance abuse (Paus et al., 2008). Ado- lescents also show risky behaviors that contribute to major causes of morbidity and mortality (Merrick et al., 2004) and respond diﬀerently to stressors compared to older and younger individuals. For instance, acute stress leads to enhancement of adrenocorticotropic hormone (ACTH) and corticosterone release in adolescent rats compared to their adult counterparts (Foilb et al., 2011; Lui et al., 2012). Comparable results have been reported from human studies: Stroud et al. (2009) for example, found that upon experiencing a stressor, such as public

speaking, mental arithmetic or mirror tracing, cortisol levels are greater in adolescents compared to children (Stroud et al., 2009).

3. Adolescence: age-related alterations in brain physiology and connectivity

Behavioral alterations during adolescence occur in parallel with reﬁnement of brain circuits (Vijayakumar et al., 2016; Tamnes et al., 2017). For example, a non-linear reduction in the volume of grey matter is observed over the entire course of adolescence (Tamnes et al., 2017) and this coincides with enhanced cognitive capacity (Gogtay and Thompson, 2010). It is also noteworthy that the process of pruning, i.e.

the elimination of excessive neural connections, increases during adolescence, and this leads to a reduction of synaptic density in late childhood and adolescence (Giedd, 2004; Casey et al., 2008). In contrast, cerebral white matter increases almost linearly throughout childhood and adolescence periods along with myelination of intra- cortical structures (Mills et al., 2016; Tamnes et al., 2017). This enables the brain to bene

ﬁ

t from a more e

ﬃ

cient communication system among its various regions. Additionally, the directional organization of white matter, which can be evaluated

via

diﬀusion tensor imaging (DTI), increases in an age-related manner (Bonekamp et al., 2007; Schmithorst and Yuan, 2010). Moreover, DTI studies on adolescents have revealed that increased integrity of white matter is associated with improvement of inter-hemispheric transfer (Muetzel et al., 2008), inhibitory control (Liston et al., 2006), working memory (Nagy et al., 2006) and general intelligence (Shaw et al., 2006). All these changes are both temporally and regionally speci

ﬁ

c. Primitive brain regions undergo modi

ﬁ

cations prior to phylogenetically newer structures with the most anterior parts of the frontal and temporal lobes last to reach their

ﬁnal form of adult

organization (Gogtay et al., 2004). Structural development also occurs in sub-cortical brain regions during adolescence (Tamnes et al., 2017).

In addition to structural remodeling, significant neurochemical maturation occurs during adolescence. Specifically, the dopaminergic system undergoes dramatic reorganization which appears essential for the development of associative learning and motivated behaviors (O’Donnell, 2010; Wahlstrom et al., 2010). The expression of dopamine receptors increases maximally during adolescence in cortical and sub- cortical regions (Andersen et al., 2000). Moreover, adolescents and adults differ in the excitation-inhibition balance of neurotransmission.

For example, the inhibitory GABAergic system undergoes reﬁnement processes within the neocortex which lasts until the end of adolescence, whereas it exhibits mature characteristics prior to the onset of puberty in the hippocampus (Kilb, 2012; Zamberletti et al., 2014).

Along the same lines, neurobiological models of brain development during adolescence indicate an imbalance between controlling top- down processes and motivational bottom-up mechanisms (Ernst, 2014;

Shulman et al., 2016). Speci

ﬁ

cally, maturation of sub-cortical brain regions occurs around the onset of puberty and early adolescence, whereas cortical brain structures mature later in time and this process continues into young adulthood (Giedd, 2008). Thus, the hyperactive limbic system is only gradually controlled by higher cortical mechanisms. These diﬀerential developmental trajectories in brain region maturation may therefore subsume increased risk-taking behaviors in adolescents and their engagement in addiction behaviors.

4. Long term eﬀects of adolescent drug exposure

An unresolved question is whether adolescent drug exposure con- tributes to long-lasting alterations in brain development which subse- quently compromise adult behavior and lead to increased vulnerability to addiction (Kuhn et al., 2013). In humans, the experience of drug abuse during adolescence is clearly associated with increased risk of psychiatric disorders and addiction in adulthood (Rutherford et al., 2010; Hanson et al., 2011a; Moss et al., 2014). Additionally, other behavioral domains, such as learning and memory processes are also

Fig. 1.Schematic representation of developmental changes in brain functions

following adolescent drug exposure.

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susceptible to early life drug abuse (Palmer et al., 2009). In the fol- lowing sections, we review the impact and possible consequences of the major drugs of adolescent abuse (see Fig. 1).

4.1. Cannabinoids

Cannabis abuse is increasingly common with around 23 % of adolescents, aged 12–19, having used marijuana in their lifetime and 9 % having

‘used’

during the past month (Sherman and McRae-Clark, 2016).

Even if the majority of users do not report adverse reactions, an increasing number of epidemiological studies suggest that sustained cannabis use in adolescence may increase the risk for developing cognitive de

ﬁ

cits, psychosis, depression, and a gateway to other drugs of abuse (Radhakrishnan et al., 2014; Otten et al., 2017; Krebs et al., 2019). For example, administration of natural or synthetic cannabinoid agonists during adolescence in rats causes cognitive impairments in adulthood (Realini et al., 2011; Orr et al., 2019). Speciﬁcally, long-term exposure of adolescent rats to the cannabinoid type 1 receptor (CB1R) agonists WIN 55,212-2, delta-9 tetrahydrocannabinol (THC) or CP 55,940 impaired memory when assessed using the object recognition task in these animals tested as adults (O’Shea et al., 2006; Schneider and Koch, 2003).

Long-term de

ﬁ

cits in memory resulting from adolescent cannabinoids however are still a matter of controversy. For example, Tomas- Roig et al. (2017) reported memory impairments in adult rats in the fear conditioning and Morris water maze tests exposed to WIN 55,212-2 during adolescence (Tomas-Roig et al., 2017). Furthermore, attenuation of spatial working memory, assessed by the radial maze and object location tasks, occurs in adult rats exposed during adolescence to CB1R agonists (Rubino et al., 2009a,b; Renard et al., 2013). In contrast, several studies do not

ﬁnd persistent memory impairment in adult rats,

exposed in adolescence to THC or CP 55,940 in the water maze task (Cha et al., 2007; Higuera-Matas et al., 2009). Indeed, Kirschmann et al.

(2017b) reported that adolescent WIN 55,212-2 only causes acute impairments of short-term memory in adult rats in the object recognition test when the drug is administered by the experimenter, but this sub- sequently recovers with abstinence. Self-administration of WIN 55,212- 2 during adolescence elicits neither acute nor chronic e

ﬀ

ects on short- term memory (Kirschmann et al., 2017b). Moreover, low-dose WIN 55,212-2 during adolescence, whether self-administered or experi- menter-administered, leads to either enhancement or no change in adult working memory function in rats (Kirschmann et al., 2017a).

Thus, we conclude that the eﬀect of adolescent exposure to cannabinoids on cognition depends on the type of cannabinoid, the time course of drug exposure, dose and strain of animals used. In general, higher doses and/or earlier exposures appear necessary to impact cognition, and the type of memory impaired usually involves PFC circuits.

Researchers investigating anxiety after cannabinoids have also reported conﬂicting

ﬁndings. For example, long-term administration of

CB1R agonists in adolescent rats induced anxiolytic-like responses when assessed using the elevated plus maze (Biscaia et al., 2003), and open

ﬁ

eld test (Wegener and Koch, 2009) in adult animals. In contrast, several studies have demonstrated anxiogenic eﬀects after adolescent administration of THC, when assessed by the open-ﬁeld test (Llorente- Berzal et al., 2013), the light

–

dark box test (Renard et al., 2017) the social interaction test (O’Shea et al., 2006; Quinn et al., 2008;

Zamberletti et al., 2014) and the elevated plus maze (Higuera-Matas et al., 2009) in these adults. Similarly, rats chronically treated with high doses of WIN 55,212-2 during adolescence display anxiety-like behaviors in the elevated plus maze and open

ﬁeld tests in adulthood

(Frontera et al., 2018). Finally, there are also reports of no change in the expression of anxiety-like behavior (Rubino et al., 2008; Higuera- Matas et al., 2009; Mateos et al., 2011; Bortolato et al., 2014).

Notably, adolescent THC exposure results in increased expression of depressive-like behaviors during adulthood (Rubino et al., 2008;

Bambico et al., 2010). Interestingly, increasing concentrations of HU-

210, a CB1R agonist, in adolescence is associated with higher corti- costerone levels and potentiated responses to stress, well-known para- meters associated with depressive behaviors. Curiously, this e

ﬀ

ect is more pronounced in adult males than females (Lee et al., 2014). Can- nabinoid exposure in adolescents also results in dysfunction of hedonic processing as indicated by the palatable food consumption test and the sucrose preference test (Realini et al., 2011; Abush and Akirav, 2013).

The long-lasting eﬀ ;ects of adolescent cannabinoids on psychosis- related behaviors in adult rodents remains scarce. Impaired pre-pulse inhibition (PPI), a measure of sensorimotor gating, is commonly known as an endophenotype of schizophrenia with signiﬁcant translational validity (Bra

ﬀ

et al., 2001; Perry et al., 2001). Adolescent rats treated chronically with WIN 55,212-2, exhibit long-lasting gating dysfunction in adulthood in the PPI test (Schneider and Koch, 2003; Wegener and Koch, 2009). In a recent study the appearance of such dysfunction during adulthood, as a lasting consequence of adolescent cannabinoids, is associated with enhanced dopaminergic (DA) activity in the ventral tegmental area and dysregulation in DA-related signaling pathways which may underlie aspects of schizophrenia etiology (Renard et al., 2017). In contrast, Bortolato and colleagues did not see changes in PPI following long-term adolescent exposure to WIN 55,212-2 in rats (Bortolato et al., 2014). These disparities may be related to the period of adolescence during which cannabinoid exposure occurred and the strain of animals used.

There is evidence indicating that use of marijuana during adolescence enhances the risk of future drug intake, a phenomenon established as the

gateway hypothesis

(Kandel et al., 2006). Indeed, WIN 55,212-2 during the early adolescent period enhanced preference for alcohol consumption in these adult rodents (Frontera et al., 2018).

Moreover, THC in adolescent animals facilitates opioid, cocaine and WIN 55,212-2 self-administration in these adult rats (Ellgren et al., 2007; Scherma et al., 2016; Friedman et al., 2019). However, there are also opposing reports which do not support the gateway theory. For example, Ellgren et al. (2004) did not

ﬁnd sensitization to amphetamine

in adult rats previously exposed to THC in adolescence compared to control animals (Ellgren et al., 2004).

Mechanisms underlying the behavioral and cognitive impairments in adult individuals with experience of adolescent cannabinoids are not fully understood. Changes in morphology and neuroplasticity, including decreased total dendritic arborization (Rubino et al., 2009b), and reduced density of BrdU-immunoreactive positive cells, indicative of neurogenesis, in the dentate gyrus of adult males has been reported (Lee et al., 2014). Cognitive impairments in adult mice might also be mediated by a genetic predisposition within hippocampal astrocytes to in

ﬂ

ammatory signaling following exposure to cannabis during adolescence (Jouroukhin et al., 2019).

Adolescent THC disrupts maturation of the endocannabinoid system and impairs endocannabinoid-mediated long-term depression (LTD) in the adult PFC (Rubino et al., 2015). Adolescent WIN 55,212-2 impairs choice and reward-seeking behaviors in adults, associated with blunted responses in

reward

neurons in the PFC (Schoch et al., 2018; Jacobs- Brichford et al., 2019). Moreover, these alterations in the en- docannabinoid system also aﬀect GABAergic and glutamatergic trans- mission, mainly in PFC and profoundly change the functional role of this region (Cass et al., 2014). Accordingly, alterations of dendritic growth in the medial PFC pyramidal neurons attenuates hippocampal projection-induced synaptic plasticity and the expression of post- synaptic density protein 95 (Renard et al., 2016). Finally, recent evi- dence supports the involvement of epigenetic mechanisms in brain network functionality induced by adolescent cannabis. Accordingly, elevated levels of adult hippocampal endocannabinoids and DNA hyper-methylation at the site of intracellular regulator of G protein signaling 7 (RGS7), which is associated with reduced rates of mRNA transcription of this gene, has been described after adolescent WIN55212.2 in mice (Tomas-Roig et al., 2017).

Additionally, THC in female rats induces region- and age-speciﬁc

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alterations in histone modiﬁcations, and the adolescent brain is gen- erally more sensitive to THC than the adult brain (Prini et al., 2017).

THC-induced histone modiﬁcations in the adolescent brain are characterized by a speciﬁc kinetics (Prini et al., 2017, 2018). The

ﬁrst event,

present immediately after the end of the treatment, negatively a

ﬀ

ects gene transcription in all the analyzed brain areas (PFC, hippocampus, nucleus accumbens and amygdala). The second event, occurring later on in all the brain areas except for the amygdala, may represent a homeostatic response to counterbalance the THC-induced repressive eﬀect, since it has an opposite outcome at the transcriptional level.

Interestingly, in the PFC, the alteration in histone modiﬁcations induces a decreased expression of plasticity genes through a mechanism invol- ving histone-methyl transferase, SUV39H1 - a pathway implicated in the development of cognitive deﬁcits in adulthood (Prini et al., 2018), see Fig. 2.

4.2. Nicotine

Approximately 90 % of adult smokers experience cigarette use before the age of 18 with an average age of 13 to

ﬁ

rst use of nicotine or tobacco products; initiation of smoking prior to age 14 makes teenagers

ﬁve and a half times more likely to continue smoking later in adoles-

cence (Korpi et al., 2015). These observations give strength to the no- tion that adolescence is a critical period for the initiation of smoking and subsequent nicotine dependence (Eaton et al., 2012; Buchmann et al., 2013; Kendler et al., 2013).

Youth cigarette use is also considered a risk factor for illicit substance abuse in later life, indicating long-term changes in the reward system resulting from adolescent smoking (Lewinsohn et al., 1999;

Hanna et al., 2001). Indeed, the probability of illicit drug abuse is 5 times higher in smokers aged 12 and up in comparison to non-smokers.

Moreover, the likelihood of marijuana abuse is over three times higher in adulthood in smokers who begin using under age of 13 compared to those who have never used cigarettes (Merrill et al., 1999). Such

ﬁ

ndings support the

‘gateway’

theory that tobacco use sensitizes adoles- cents to other drugs of abuse (Kandel and Logan, 1984; Kandel et al., 1992; Yu and Williford, 1992; Zipori et al., 2017). Nicotine adminis- tration during adolescence makes acute and long-lasting changes in the developing brain which may lead to continued smoking and relapse even after long time abstinence (Lydon et al., 2014). As a matter of fact, the rate of failure in attempts to quit and/or relapse is higher in smokers who started smoking during adolescence (Khuder et al., 1999;

Abdolahinia et al., 2012). Moreover, young smokers demonstrate greater impairments of working memory and further de

ﬁ

cits in working and verbal memory during periods of abstinence, compared with non-

smokers (Jacobsen et al., 2005; Falcone et al., 2014).

Animal studies show that nicotine during adolescence can induce long-lasting changes in brain regions such as the prefrontal cortex, nucleus accumbens (NAc) and amygdala (Fig. 3) (Slotkin, 2004;

McQuown et al., 2009; Levine et al., 2011; Huang et al., 2013, 2014).

These changes can aﬀect drug sensitivity and reward-related manifestations in adulthood (Dickson et al., 2014). For instance, cigarette exposure during adolescence enhances the rewarding e

ﬀ

ect of nicotine even after a long period of abstinence (Brielmaier et al., 2007; Kota et al., 2009; Natividad et al., 2013; de la Peña et al., 2015).

Both clinical and animal studies show that use of nicotine and tobacco during adolescence results in cognitive and behavioral impairments and more severe dependence later in life (Jacobsen et al., 2005;

Fried et al., 2006; Bracken et al., 2011; Portugal et al., 2012). These impairments include de

ﬁ

cits in attentional performance (Counotte et al., 2009), impaired serial pattern learning (Fountain, 2008; Pickens et al., 2013; Renaud et al., 2015), impaired context conditioning (Spaeth et al., 2010) and increased anxiety and depressive-like beha- viors in adults (Abreu-Villaça et al., 2015; Holliday et al., 2016).

Adolescent mice, for example, exposed to nicotine for a total of 12 days (PND 38

–

50) followed by 30 days of abstinence exhibit de

ﬁ

cits in contextual but not cued fear conditioning which are hippocampus-dependent and independent, respectively (Phillips and LeDoux, 1992;

Logue et al., 1997). The same learning de

ﬁ

cits could not be observed in mice that received the same treatment during adulthood (PND 53

–

65) (Holliday and Gould, 2017). The occurrence of long-lasting learning deﬁcits that persist throughout adulthood appear to increase risk of continuing nicotine use in adulthood and may promote administration of higher doses of nicotine to compensate for learning deﬁcits (Holliday and Gould, 2017).

Other studies have shed light on the role of nicotine on normal brain development during adolescence and suggest a steady form of nicotine- induced plasticity (Smith et al., 2015). For instance, nicotine during adolescence induces plasticity in the NAc shell, an e

ﬀ

ect that appears D1 dopamine receptor dependent (Ehlinger et al., 2016). It also leads to lasting suppression of nicotine-evoked elevation of striatal dopamine and norepinephrine levels (Trauth et al., 2001). Nicotine induces persistent changes in 5-hydroxytryptamine (5 H T) synaptic function which can inﬂuence the response to other drugs of abuse (Collins et al., 2004a,b; Slotkin et al., 2014). Accordingly, nicotine in adolescence enhances the e

ﬀ

ects of nicotine administration and withdrawal in adulthood through serotonergic circuits (Slotkin et al., 2014) as well as other transmitter systems (Slotkin et al., 2007). Adolescent nicotine induces long-lasting changes in the function of central monoamine systems (Slotkin and Seidler, 2009) raising the hypothesis that the same eﬀect may also occur in the peripheral sympathetic nervous system activity (Slotkin et al., 2016). Also, altered expression of genes involved in neuroplasticity can lead to structural changes that last into adulthood and include decreases in the length of apical dendrites of the

Fig. 2.Summary of the long-term eﬀects of adolescent cannabis use on adult

brain function and behavior;↓: decrease,↑: increase,Δ: change, DA: dopamine.

Fig. 3.Summary of the long-term eﬀects of adolescent nicotine use on adult brain function and behavior;↓: decrease,↑: increase,Δ: change.

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hippocampal CA1 region (Holliday et al., 2016) and increases in total dendritic length in medium spiny neurons from the NAc shell and PFC (McDonald et al., 2007; Goriounova and Mansvelder, 2012) (see Fig. 3).

Epidemiological data suggest that nicotine intake acts as a

‘gateway’

to use of drugs like cocaine, opioids and alcohol (Lai et al., 2000; Huang et al., 2013). In a recent study, we showed that nicotine challenge during adolescence enhanced long-term vulnerability to opioid addiction associated with induction of neuroadaptations in LPGi neurons in adult rats (Torabi et al., 2019). Other studies have shown that nicotine during adolescence increases reward for cocaine in adulthood (Anker and Carroll, 2011; Dao et al., 2011; Dickson et al., 2014; Alajaji et al., 2016). Moreover, nicotine during pre-adolescence periods increases cocaine primed reinstatement (Anker and Carroll, 2011) and pretreatment of adolescent rats with nicotine results in locomotor sensitization to cocaine and increased cocaine self-administration in adulthood (Dickson et al., 2014; Reed and Izenwasser, 2017). Adolescent rats pre- treated with nicotine show locomotor sensitization to amphetamine immediately after the end of nicotine pretreatment and 30 days later.

However, adult rats pre-treated with nicotine do not show such sensitization to amphetamine at either time points (Collins et al., 2004a,b).

It is worth noting that nicotine during adolescence does not always induce signi

ﬁ

cant changes in adulthood, suggesting that its e

ﬀ

ects may depend on dosage and pretreatment regimens (Cunningham et al., 2002; Schramm-Sapyta et al., 2004; Wetzell and Riley, 2012). For instance, nicotine during adolescence does not a

ﬀ

ect cocaine-induced taste avoidance or change cocaine CPP in adulthood (Hutchison and Riley, 2008; Riley, 2011; Pomfrey et al., 2015). In summary, adolescent nicotine can trigger long-lasting alterations in neural signaling and cognitive and emotional changes in young adults (see Fig. 3).

4.3. Opioids

Opioid abuse is common in adolescents and young adults, yet little is known about its long-term eﬀects in these age groups. Our knowledge about opioid abuse and addiction comes primarily from heroin addiction in 20-40-year-old humans and research in adult animals (Koek, 2014). Notably, the rate of adolescent heroin abuse has held steady;

however, the rate of synthetic opioid abuse by adolescents is progres- sively increasing in society (Doherty and Frantz, 2013; Palmer et al., 2009).

Animal behavioral studies show that morphine during adolescence is in

ﬂ

uenced by the sex of the animal with males being the more af- fected (White et al., 2008). Adolescent morphine also induces behavioral despair after a long abstinence in mice, suggesting comorbidity between depression and opiate addiction but it also enhances socia- bility in adult mice (Lutz et al., 2013). Results from our previous study have shown that adolescent morphine treatment signiﬁcantly facilitates the development of tolerance to the analgesic e

ﬀ

ects of morphine and increases morphine withdrawal signs in these adult rats (Salmanzadeh et al., 2017), suggesting the occurrence of cellular alterations into adulthood involved in the development of morphine tolerance and dependence. Studies from our lab also determined that adolescent morphine induces lasting eﬀects on the lateral paragigantocellular (LPGi) neuronal response to morphine in these adult rats. The changes include enhanced baseline neuronal activity and potentiation of morphine-induced inhibition. However, morphine treatment during adolescence did not aﬀect the onset or peak of neuronal responses, the regularity of unit discharge or the extent of morphine excitatory e

ﬀ

ects (Salmanzadeh et al., 2018). This specific brain region has already been studied as a critical modulator of opioid effects at both the behavioral and cellular levels (Ahmadi-Soleimani et al., 2017). We also examined the effect of morphine administration on impulsive behavior, 24 h and 25 days after administration in adolescent rats, through a

ﬁve-choice

serial reaction time task (5-CSRTT) and found a profound e

ﬀ

ect on motor impulsive behavior in adulthood (Moazen et al., 2018). In another study, we demonstrated a lasting eﬀect of chronic morphine

administration during adolescence, not adulthood, with increased pain responsiveness in the formalin test in adult rats compared with controls (Ghasemi et al., 2018). Results from adolescent oxycodone exposure also show alteration in the development of the VTA and NAc reward pathway and increased sensitivity to the rewarding eﬀects of morphine in adult mice (Sanchez et al., 2016).

Adolescence appears to represent a sensitive period for morphine- induced changes in the Toll-like receptor 4 (TLR4) signaling pathway and in the function of microglial cells within the NAc. This alteration in microglial function enhances the risk of adverse consequences later in life after drug treatment, since it induces long-term changes in the neural circuitry related to morphine addiction and relapse (Schwarz and Bilbo, 2013). Based upon these studies, we suggest that adolescent morphine abuse may trigger development of psychiatric disorders later in life through a complex array of changes. Notably, these changes include alterations in microglia.

4.4. Cocaine

Cocaine is a psychostimulant drug with long-lasting behavioral and neurobiological outcomes (Nestler, 2005; Kauer and Malenka, 2007;

Marin et al., 2008). Cocaine during adolescence and the subsequent excessive activation of multiple neural circuits, like dopaminergic pathways, may lead to changes in brain structure, physiology and function and is associated with behavioral abnormalities and development of mental disorders in adulthood (Marco et al., 2011; Sillivan et al., 2011; Wheeler et al., 2013). For example, adolescent cocaine exposure induces persistent changes in stimulus-reward learning and causes de

ﬁ

ciency in hippocampal neurogenesis in rats during adulthood (García-Cabrerizo et al., 2015; García-Fuster et al., 2017). Exposure to cocaine during adolescence also leads to increased despair and anxiety- like behaviors during adulthood along with alterations in morphology of pyramidal neurons, activities of astrocytes and protein expression involved in synaptic transmission, apoptosis and inﬂammation in the hippocampus (Zhu et al., 2016). In adolescent rats, cocaine exposure modulates amygdala-mediated behaviors such as contextual fear responses and anxiety tasks are disrupted during adulthood (Sillivan et al., 2011). Remarkably, cocaine evokes transient alterations in the expression of genes involved in the regulation of dendritic structures and synapse formation within the amygdala (Sillivan et al., 2011).

Cocaine during adolescence induces enduring changes in the hypothalamic-pituitary-adrenal axis and testosterone levels. This can lead to behavioral changes in response to the evaluation of potential threats that lead to high-risk behaviors and low-beneﬁt choices (Alves et al., 2014). The increase in high-risk behaviors may also stem from enhancement of GABAergic transmission on pyramidal neurons in prelimbic cortex, and an enduring disinhibition of the medial PFC (Cass et al., 2013; Shi et al., 2019).

Cocaine self-administration elicits habit-like behavioral inflexibility and preference for cocaine during adulthood. Cocaine-induced changes in the cortex might play a role in such altered responsiveness. For example, though low doses of cocaine do not impact the density of dendritic spines in deep-layers of PFC, the size of the dendritic spine head, as a predictor of synapse formation, synapse-related proteins (synapsin I and PSD-95) and the density of synapses are decreased (Black et al., 2006; DePoy et al., 2016; Broadwater et al., 2018). Moreover, adolescent cocaine abuse causes persistent effects on dendrite structure in the orbitofrontal cortex. It has been suggested that cocaine-induced alterations in dendrite structure might be related to the behavioral effects of cocaine more than pre-existing structural abnormalities in this cell population (Gourley et al., 2012; DePoy et al., 2014). Accordingly, undermined functions of this cortical region predict the development of impulsive behavior and impaired decision-making which are also behavioral traits related with increased susceptibility for substance abuse (Kuhn et al., 2013).

In another study, the elevation of locomotor sensitization and

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cocaine-seeking behaviors have been observed in adolescent cocaine exposed rats (Badanich and Kirstein, 2012). Cocaine abuse during adolescence induces cross-sensitization to a sub-acute dose of methamphetamine during adulthood, which is an indicator of long-lasting alterations in brain and of addiction to other drugs (Marin et al., 2008;

Valzachi et al., 2013; Shanks et al., 2015). It appears that modiﬁcations in dopamine and glutamate transmission in NAc and medial PFC underlie these behavioral manifestations (Black et al., 2006; Marin et al., 2008). In this regard, adolescent cocaine self-administration increases memory impairment (Kantak et al., 2014), suggesting a role for dopamine agonists in these processes which may impair di

ﬀ

erent traits of

‘executive functions’

during adulthood (Pope et al., 2016). In summary, cocaine during adolescence results in morphological and neurochemical changes coincident with long-term behavioral alterations in adulthood (please see Fig. 4).

4.5. Amphetamines

Amphetamines are among the psychoactive drugs used more than heroin and cocaine each year (Lipari and Van Horn, 2013). Ampheta- mine and methamphetamine are psychomotor stimulants which a

ﬀ

ect the dopamine system and lead to cognitive de

ﬁ

cits in adults (McKetin and Mattick, 1998). Although the number of adolescents who use amphetamine and methamphetamine are low compared to those who use other drugs, some studies have reported an increase in adolescents who seek amphetamines in the 2000s (Rawson et al., 2007; Gonzales et al., 2008).

Animal studies have shown that amphetamine during adolescence induces deﬁcits in learning and memory, including impaired visual discrimination, reversal learning and spatial working memory in adulthood (Braren et al., 2014; Ye et al., 2014). Additionally, pre-exposure to amphetamine and methamphetamine during adolescence signiﬁcantly increases the consumption of these drugs and the likelihood to use other drugs-of-abuse in adult rats (Lacy et al., 2018).

These results show that even modest exposure to methamphetamine during adolescence may elicit extensive impairments in learning during adulthood and a long-lasting sensitivity to the eﬀects of methamphe- tamine (Ye et al., 2014). Along the same lines, sporadic exposure to amphetamine during adolescence was found to induce enduring changes in drug sensitivity and cognitive function (Sherrill et al., 2013).

In another study, adolescent amphetamine resulted in adaptations in the mesocorticolimbic dopamine system that increased the response to the drug during adulthood (Sherrill and Gulley, 2018). Studies on rodents show that methamphetamine administration during early adolescence elevates the expression of depressive-like behaviors and reduces the number of vasopressin-immunoreactive neurons in the

paraventricular nucleus of the hypothalamus (Joca et al., 2014).

Adolescent amphetamine exposure induces alterations in amphetamine-evoked motivation and causes an impaired ability for transition to other purposeful behaviors (perseveration). These eﬀects are more ro- bust and long-lasting than amphetamine induced deﬁcits in impulse control during adulthood (Hankosky and Gulley, 2013). An intriguing point is that a single methamphetamine exposure during early adolescence has been observed to attenuate anxiety-like behavioral signs later in adolescence (Buck et al., 2017). In addition, repeated adolescent amphetamine induces lasting e

ﬀ

ects on the function of the medial PFC by reduction in inhibitory transmission which persists up to 14 weeks in rats (Kang et al., 2016). Changes of dopamine-GABA interactions in the medial PFC may underlie such e

ﬀ

ects (Paul et al., 2016). Moreover, increased sensitization to amphetamine re-challenge in adulthood ap- pears to be associated with widespread neuronal activation along the PFC neuroaxis. Finally, chronic exposure to amphetamine during ado- lescence enhances

ﬁring of monoamine neurons during adulthood. This

condition has been shown to be associated with changes in locomotion and risk-taking behaviors (Labonte et al., 2012).

Collectively, adolescent exposure to amphetamines and methamphetamine, as psychostimulant drugs, can inﬂuence CNS neuronal circuits and thereby adversely a

ﬀ

ect brain function, which in turn may induce long-lasting sensitization of neurons to the activity of other drugs. All these changes may enhance the risk of adverse consequences in later life.

4.6. Alcohol

Alcohol is amongst the most commonly used psychoactive sub- stances. Excessive consumption of alcohol is the third leading cause of death worldwide (Koob and Le Moal, 2005). Among the wide range of alcohol users, the main concern is the young population within the age range of 15–24 years (Dawson et al., 2008; Kirby and Barry, 2012). In this regard, alcohol consumption is prevalent in adolescence with in- dividuals displaying binge-like drinking pattern characterized by high alcohol intake during a short period of time, often followed by an ab- stinence period (Vore et al., 2017).

Studies on adult humans with the history of alcohol consumption during adolescence have revealed smaller volumes of prefrontal white and grey matter compared to control cases (De Bellis et al., 2005; Welch et al., 2013). From a functional viewpoint, adolescent binge-like alcohol consumption reduces the baseline functional connectivity between the PFC and striatal regions, suggesting that the PFC is vulnerable to the long-term eﬀects of adolescent alcohol binge drinking. These data also indicate that alcohol during adolescence may a

ﬀ

ect PFC function in top-down inhibitory control, associated with increased vulnerability to alcohol-related disorders such as Alcohol Use Disorder in adulthood (Broadwater et al., 2018).

Growing evidence from human studies have also revealed that alcohol use during the late stages of brain maturation causes cognitive de

ﬁ

cits in attention, learning, verbal and non-verbal skills and visuos- patial function (Tapert et al., 2002; Chin et al., 2010; Hanson et al., 2011b; White et al., 2011; Koskinen et al., 2011). Consistent with these observations, studies in rats have revealed that adolescents are more vulnerable to alcohol-induced memory loss than older animals (Little et al., 1996; Markwiese et al., 1998). Two studies have reported long- lasting deﬁcits of recognition memory in adult rats exposed to chronic intermittent alcohol (CIA) during adolescence (Pascual et al., 2007;

Vetreno and Crews, 2015). Speciﬁcally, CIA administration in adoles- cent animals impairs object recognition performance and conditional discrimination (Pascual et al., 2007; Beaudet et al., 2016). It is note- worthy that prolonged impairments in object recognition are associated with changes in neuronal activity of the hippocampus (Beaudet et al., 2016).

Interestingly, it has been determined that one of the functional consequences of ethanol abuse during adolescence is that an

Fig. 4.Summary of the long-term eﬀects of adolescent cocaine use on adult

brain function and behavior;↓: decrease,↑: increase,Δ: change, DA: dopamine, Glut: glutamate.

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adolescent-like phenotype could be retained until adulthood (Vore et al., 2017). This

“locking in”

phenomenon is observed in a variety of behaviors and does not occur in rats that receive the same quantities of ethanol in adulthood. Behavioral alterations such as insensitivity to ethanol-induced anxiogenesis during withdrawal (Doremus et al., 2003), attenuated sensitivity to the sedative e

ﬀ

ects of ethanol (Matthews et al., 2008) and decreased sensitivity to the induction of conditioned taste aversion (Diaz-Granados and Graham, 2007) char- acterize this

locking in

state when monitored during adulthood. Fur- thermore, novelty seeking, and level of impulsivity have also been reported to persist into adulthood following ethanol during adolescence although control group showed decreased impulsivity with increasing age (Spear and Swartzwelder, 2014).

Alcohol binge drinking in adolescents causes short and long-term consequences including social rejection and depression and increases risky decision-making (Briones and Woods, 2013; McBride and Cheng, 2011; Miller et al., 2017). Furthermore, it is believed to serve as a

“gateway”

for using other types of drugs such as marijuana or tobacco (Kirby and Barry, 2012). Consistent with this hypothesis, cocaine addiction is strongly associated with an early experience of ethanol abuse in adolescence (Arias et al., 2013a, 2013b). Moreover, ethanol binge drinking, when induced in adolescent mice, modulates cocaine withdrawal signs and elicits short-term as well as long-term behavioral alterations such as increased anxiety, depressive symptoms, and memory impairments (Ledesma et al., 2017; Shan et al., 2019; Galaj et al., 2019). Adolescent alcohol also reduces sensitivity to nicotine-related motivational and rewarding eﬀects (Boutros et al., 2016). Studies of humans have also shown that tobacco use increases during adulthood in individuals with adolescent alcohol use experience (Paavola et al., 2004; Dierker et al., 2013). Interestingly, amphetamine-induced dopamine release decreases in rats who have received ethanol during adolescence (Granholm et al., 2015).

Several lines of evidence propose a connection between adolescent alcohol consumption and enhanced risk of alcohol binge drinking during adulthood (Alaux-Cantin et al., 2013; Amodeo et al., 2017). For example, alcohol use before 14 years of age is associated with sig- nificant enhancement of alcohol dependence risk during adulthood (DeWit et al., 2000; Dawson et al., 2008). The cellular mechanisms underlying this are still poorly understood (Spear, 2000a,b,c). Simi- larly, studies performed on animal models have shown that ethanol use during adolescence facilitates the acquisition of alcohol self-adminis- tration, increases behavioral signs of craving and strengthens the pos- sibility of relapse during adulthood (Gilpin et al., 2012; Serlin and Torregrossa, 2015; Toalston et al., 2015). In contrast, Vetter and col- leagues observed that animals that learned to voluntarily drink ethanol during adolescence exhibit no significant difference in ethanol drinking behavior in adulthood compared to the control group (Vetter et al., 2007).

Different mechanisms seem to be involved in adolescent vulnerability to alcohol. Several observations suggest that ethanol during adolescence may result in long-lasting changes in regulation of cyto- kines and sensitivity of the hypothalamic-pituitary-adrenal (HPA) axis and these effects persist into adulthood (Logrip et al., 2013; Vore et al., 2017). Excess use of alcohol during adolescence is known to damage brain regions including olfactory cortex, piriform and anterior peri- rhinal cortex (Bava and Tapert, 2010; Guerri and Pascual, 2010). Binge- like consumption of alcohol results in attenuated dopaminergic function in the prelimbic cortex of adult rats (Trantham-Davidson and Chandler, 2015). Recent evidence indicates that adolescent intermittent ethanol alters tonic inhibitory currents in pyramidal neurons of the prelimbic cortex (Centanni et al., 2017). It appears that adolescent alcohol affects development of the medial PFC suggesting that cognitive impairments mediated by this brain regions might, in part, be the consequence of disruptions in D1 receptor-mediated modulation of PFC activity and decreased excitability of GABAergic fast-spiking interneurons (Trantham-Davidson et al., 2017).

A series of studies have reported that chronic adolescent ethanol causes signiﬁcant reduction in the volume of hippocampus, PFC and corpus callosum in adult rats (Coleman et al., 2011; Ehlers et al., 2013;

Vetreno et al., 2016) and cortical thickness (Vetreno et al., 2017). Other studies have reported alterations in the myelin sheath, synaptic remodeling and activity of the PFC and NAc in both rats and mice that have chronically received ethanol during adolescence (Montesinos et al., 2015; Liu and Crews, 2015; Jury et al., 2017). Intermittent administration of ethanol during adolescence also induces neuro-adaptations that may lead to reduced dopamine release in response to future ethanol consumption in adulthood. These

ﬁndings indicate possible

mechanisms underlying addiction susceptibility in individuals who drink alcohol during adolescence and highlight the necessity of alcohol prevention programs for adolescents (Zandy et al., 2015; Shnitko et al., 2016).

Alcohol during adolescence is associated with impaired neurogen- esis in the hippocampus, NAc (Taﬀe et al., 2010; Broadwater et al., 2014; Galaj et al., 2019) and enhanced neurodegeneration (Nixon et al., 2010) in several brain regions. This impaired neurogenesis is accom- panied by increased apoptosis as well as prolonged up-regulation of TLR4, high-mobility group box 1 (HMGB1) and other signaling mole- cules (Vetreno and Crews, 2015). Although the precise mechanism underlying this impairment remains unclear, some evidence supports the hypothesis that the activation of immune genes by adolescent ethanol intake plays a role in the progressive loss of hippocampal neurogenesis. These e

ﬀ

ects might be involved in the long-lasting impairment of hippocampal-mediated novel object recognition memory and potentiate the expression of anxiety-like behaviors (Vetreno and Crews, 2015). Additionally, intermittent alcohol in adolescence is correlated with lower concentrations of brain-derived neurotrophic factor (BDNF) and alters histone H3 acetylation in BDNF gene promoters, which in turn attenuates its function within the hippocampus. This may impact neurogenesis as well as the occurrence of anxiety-like behaviors during adulthood (Scheidt et al., 2015; Sakharkar et al., 2019).

Teenage alcohol consumption impairs hippocampal function, memory and synaptic plasticity in adults (Swartzwelder et al., 2016) which may result from alcohol-induced mitochondrial damage (Tapia- Rojas et al., 2018). Additionally, chronic ethanol during adolescence elicits long-lasting changes in some astrocyte-speci

ﬁ

c signaling proteins, such as dysregulation of thrombospondin, and their neuronal receptors. Signaling cascades mediated by these factors in adulthood may serve as a compensatory mechanism by which astrocytes help sy- naptogenesis and repair lost connectivity (Risher et al., 2015).

Together, these studies reveal that adolescent alcohol can induce molecular, structural and functional alterations in brain and support the idea that adolescent alcohol abuse can signiﬁcantly diminish adult brain health, as well as increase the risk for adult alcoholism and alcohol dependence (see Fig. 5). Future studies addressing the mechanisms underlying alcohol-induced changes in the adolescent brain will provide a better understanding of the risks that contribute to the development of alcoholism and adult neuropathology.

5. Conclusions and future perspectives

The studies reviewed here provide evidence that exposure to drugs during adolescence have drug-specific neural, cognitive, affective and behavioral consequences. Indeed, drugs like nicotine, cocaine, canna- binoids, morphine, amphetamine and alcohol during adolescence can induce long-lasting effects on brain functions. Mature neural systems might undergo limited neuroadaptations after moderate consumption, whereas immature developing systems appear to incorporate these changes into a more permanent repertoire of cellular responsiveness.

The overall outcome is impaired brain function that can last into

adulthood. The brain regions particularly sensitive to adolescent drug

exposure are the ones with signi

ﬁ

cant developmental processes during

this period, and this leads to long-term perturbations in these areas.

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Although a wide variety of studies have addressed the mechanisms of adolescent vulnerability to the adverse eﬀects of drugs-of-abuse we do not yet have the full picture. We need to acquire a more profound understanding of neurodevelopmental trajectories at this critical age to fully characterize the susceptibility of diﬀerent brain regions to drugs during adolescence.

Declaration of Competing Interest

All authors approve this manuscript and declare no con

ﬂ

ict of interest related to this work.

Acknowledgements

The Cognitive Sciences and Technologies Council of Iran (CSTC, Grant No. 95P31) and the Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran supported this work. The funders had no role in study design, collection, analysis and interpretation of data, the writing of the manuscript, or the decision to submit the manuscript for publication.

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