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Self-ReportedFamilySocioeconomicStatus,
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AGGRESSIVE BEHAVIOR
Volume 00, pages 1–12 (2012)
Self-Reported Family Socioeconomic Status,
the 5-HTTLPR Genotype, and Delinquent Behavior
in a Community-Based Adolescent Population
Cecilia Åslund1 ∗ , Erika Comasco2 , Niklas Nordquist2 , Jerzy Leppert1 , Lars Oreland2 ,
and Kent W. Nilsson1
1
2
Centre for Clinical Research, Uppsala University, Central Hospital, Västerås, Sweden
Department of Neuroscience, Unit of Pharmacology, Uppsala University, Uppsala, Sweden
: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :
Twin and adoption studies have demonstrated a significant contribution of both genetic and environmental factors to antisocial
and delinquent behavior. Associations have been reported between the serotonin transporter (5-HTT) and aggression, and between
socioeconomic status (SES), aggression, and serotonergic functions of the brain. We aimed to investigate associations between the
5-HTTLPR genotype and family SES in relation to delinquent behavior among adolescents. A total of 1,467 17- to 18-year-old
students in the county of Västmanland, Sweden, anonymously completed a questionnaire and gave a saliva sample. Family SES
had a U-shaped relation to delinquency, where adolescents with low and high family SES were the most delinquent. There were
curvilinear interactions between the 5-HTTLPR genotype and family SES in relation to delinquency. Among individuals having high
family SES, boys with the LL (homozygous for the long allele) or LS (heterozygous) genotypes and girls with the SS (homozygous
for the short allele) or LS (heterozygous) genotypes showed the highest delinquency scores. Among individuals having low family
SES, boys with the LL (homozygous for the long allele) genotype and girls with the LS (heterozygous) genotype showed the highest
delinquency scores. The present study suggests evidence for an interaction between family SES and the 5-HTTLPR genotype in
C 2012 Wiley Periodicals, Inc.
relation to juvenile delinquency. Aggr. Behav. 00:1–12, 2012.
: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :
Keywords: adolescent; juvenile delinquency; serotonin transporter; socioeconomic status; 5-HTTLPR
INTRODUCTION
Low socioeconomic status (SES) is related to aggression, violence, and crime [Aneshensel and Sucoff, 1996; Burgess, 1916; Farrington, 1998; Marmot, 2004; Shaw and McKay, 1942; Wilkinson, 1999,
2004]. The central serotonergic system also influences
predisposition toward aggression [Popova, 2006; Reif
et al., 2007], and low brain serotonergic responsivity
has been related to low SES [Manuck et al., 2005;
Matthews et al., 2000]. Therefore, polymorphic variants of the serotonin transporter (5-HTT) gene may
interact with experiences related to SES in the development of antisocial and criminal behavior. The
present study is, to our knowledge, the first to investigate associations between the 5-HTTLPR polymorphism and SES in relation to delinquency among
adolescents.
Delinquency and conduct problems are examples of
antisocial behavior that are influenced both by hereditary and environmental factors and often have an
C 2012 Wiley Periodicals, Inc.
onset early in life. Childhood and adolescent antisocial behavior is associated with lifelong and pervasive
mental [Moffitt et al., 2002], physical [Farrington,
Contract grant sponsor: The Swedish Research Council (VR) (2006–
6072); Contract grant sponsor: The Swedish Council for Working Life
and Social Research (FAS); Contract grant sponsor: The Swedish Alcohol Monopoly Research Council (SRA); Contract grant sponsor:
The Swedish Brain Foundation; Contract grant sponsor: The Swedish
Labour Market Insurance Company (AFA); Contract grant sponsor:
The Uppsala and Örebro Regional Research Council; Contract grant
sponsor: The Fredrik and Ingrid Thurings Foundation; Contract grant
sponsor: The County Council of Västmanland; Contract grant sponsor: The König-Söderströmska Foundation; Contract grant sponsor:
The Swedish Psychiatric Foundation.
∗ Correspondence to: Cecilia Åslund, Centre for Clinical Research,
Uppsala University, Central Hospital, S-72189 Västerås, Sweden.
E-mail: [email protected]
Received 5 December 2011; Accepted 18 June 2012
Published online in Wiley Online Library (wileyonlinelibrary.com).
DOI: 10.1002/ab.21451
2 Åslund et al.
1995], interpersonal [Moffitt et al., 2002], and economic [Caspi et al., 1998; Moffitt et al., 2002] problems that create an enormous societal burden.
Antisocial and aggressive behavior is associated
with a large number of neurobiological mechanisms.
One neurotransmitter that is frequently mentioned
in relation to aggressive behavior is serotonin [Carrillo et al., 2009; Lucki, 1998]. The 5-HTT is the
key molecule in regulating the levels of serotonin in
the synaptic cleft, thus playing an important role in
serotonergic neurotransmission [Blakely et al., 1994;
Lesch and Mössner, 1998; Uhl and Johnson, 1994].
For example, mice lacking the 5-HTT show lower levels of aggression [Holmes et al., 2002]. In humans,
the serotonin transporter availability was reduced in
the anterior cingulate cortex of subjects with impulsive aggression [Frankle et al., 2005]. Moreover, serotonin releasing agent administration tests have shown
a blunted prolactin response among men with aggressive and impulsive traits [Manuck et al., 1998]. Further, cerebrospinal fluid 5-HIAA has been associated
with violent and aggressive behavioral traits in humans [Coccaro and Lee, 2010; Soderstrom et al., 2003]
and in non-human primates [Higley et al., 1996], and
5-HIAA levels are also dependent on environmental
factors [Higley and Linnoila, 1997]. Findings thus indicate that reduced serotonergic function is related to
traits of aggression and impulsiveness [Popova, 2006].
The gene expression of the 5-HTT is modulated
by a polymorphism 5-HTTLPR that is located in the
upstream regulatory promoter region of the SLC6A4
gene and consists of different lengths of a repetitive sequence containing 20- to 23-bp-long repeat elements
[Canli and Lesch, 2007; Heils et al., 1996; Lesch et al.,
1996]. Insertion or deletion of the 5-HTTLPR has at
some point in evolution resulted in a short (S) 14repeat and a long (L) 16-repeat allele where the short
variant has been associated with lower transcriptional
efficiency [Collier et al., 1996; Heils et al., 1996; Lesch,
2004; Lesch et al., 1996]. A number of less-common
alleles with 15, 18–20, or 22 repeat copies and variants with single-base insertions/deletions or substitutions within individual repeats are rare [Lesch and
Gutknecht, 2005; Nakamura et al., 2000]. Several
studies have reported an association between the Sallele of the 5-HTTLPR and aggression, impulsiveness, and conduct disorder in both children and adults
[Beitchman et al., 2006; Gerra et al., 2005; Haberstick
et al., 2006; Hohmann et al., 2009; Retz et al., 2004;
Sakai et al., 2006]. However, there have also been several nonreplications [Beitchman et al., 2003; Sakai
et al., 2007]. Moreover, it has been suggested that
the 5-HTTLPR may interact with environmental factors such as delinquent peer network [Vaughn et al.,
Aggr. Behav.
2009] to predict antisocial phenotypes and pathological criminal behavior. Therefore, other criminogenic
risk factors might be influenced by biological heredity
such as the 5-HTTLPR.
It has been suggested that the serotonergic system behaves differently in males and females [Biver
et al., 1996; Costes et al., 2005; Williams et al., 2003].
Moreover, studies of different species have found correlations between social status and serotonin levels
[Gilbert and McGuire, 1998; Kaplan et al., 2002;
Larson and Summers, 2001]. Among humans, associations have been found between low SES [Manuck
et al., 2005; Matthews et al., 2000] and low brain
serotonergic responsivity. Interactions have also been
found between SES and the short variant of the 5HTTLPR in relation to low brain serotonergic responsivity [Manuck et al., 2004].
From a psychosocial perspective, it has been suggested that violent behavior arises from an extreme
sensitivity to, and defense of, personal social status
among people who have few sources of status and
self-esteem [Gilligan, 1996; Wilkinson et al., 1998].
The importance of social rejection in interpersonal
interaction has been emphasized as a common factor behind many types of aggressive behavior [Leary
et al., 2006]. Subjective social status may be described
as a person’s belief about his or her standing in a
hierarchical community, that is, his/her subordination or superiority in relation to other people. Several
studies have shown associations between low-status
neighborhoods and a high prevalence of crime and social problems [Aneshensel and Sucoff, 1996; Burgess,
1916; Farrington, 1998; Shaw and McKay, 1942], and
the relationship between violence and inequality is
nowadays well established [Marmot, 2004; Wilkinson, 1999, 2004]. The environmental consequences
of living in a low-status neighborhood may be related to increased levels of stress, presumably altering
the function of the hypothalamic–pituitary–adrenal
(HPA) axis [Brunner and Marmot, 2006]. Subordination and experiences of humiliation in human social interactions may create similar patterns of social
stress, as shown in several animal studies where dysregulation of the HPA axis has been associated with
several health and behavioral problems. Moreover,
theories of social rank [Gilbert, 1992; Price et al.,
1994] suggest that, through evolution, humans and
other species have acquired behavioral strategies for
contesting and safeguarding resources relevant for reproduction. Consequently, hierarchical organizations
have developed where threats from a subordinate may
elicit down-hierarchy aggression to restrict resource
access, whereas threats from a superior may elicit appeasement efforts and up-hierarchy subordination in
Family SES, 5-HTTLPR, and Delinquent Behavior
order to repair cooperative alliances and reduce aggression. Such behavioral strategies have been identified among animals [Huhman, 2006] and in hierarchical relationships between humans [Fournier et al.,
2002]. Individuals with high status and those with low
status are therefore both of interest when investigating associations between social status and aggressive
behavior, although the associations may stem from
completely different psychological mechanisms in individuals with high status compared with low status. Following this, a recent investigation using the
same study population as the present study found a
U-shaped pattern of aggressive behavior in relation
to social status among adolescents, where individuals
with low or high social status who reported experiences of shaming were most inclined to physical aggression at school, whereas medium status seemed to
have a protective function [Åslund et al., 2009c].
Low SES is related to aggression, violence, and
crime, but not all individuals with low SES are delinquent. The effect of SES is highly variable across people and perhaps part of the heterogeneity in response
to SES is because of inherited genotype. According
to the differential susceptibility hypothesis, specific
genes function as plasticity factors, rendering some
individuals more susceptible than others to environmental influences [Belsky and Pluess, 2009]. The term
“orchid children” has also been introduced to describe
individuals with high biological sensitivity to context [Boyce and Ellis, 2005]. These individuals have
a higher risk of functioning poorly when challenged
with stressful conditions, but they are also more likely
to benefit from supportive environments [Beaver and
Belsky, 2012; Belsky and Pluess, 2009; Boyce and Ellis, 2005]. The short allele of the serotonin transporter
gene has been suggested as a typical plasticity allele
associated with such increased sensitivity to environmental context [Beaver and Belsky, 2012]. It seems
plausible that genotype may influence susceptibility
to environmental stress from, for example, low SES.
The present study investigates associations between
the 5-HTTLPR and self-reported family SES in relation to delinquency in a large population based sample of adolescents. Based on previous findings, we hypothesize that the S-allele of the 5-HTTLPR will be
associated with delinquency, particularly among adolescents with either high or low family SES compared
with medium family SES.
METHOD
This present study was part of the Survey of Adolescent Life in Vestmanland 2006, a survey distributed
biennially by the County Council of Västmanland,
3
Sweden, to monitor the psychosocial health of the
county’s adolescent population. Västmanland is a
medium-sized Swedish county, situated about 100 km
west of Stockholm. All students in the second year of
high school (17–18 years old) were asked to complete
a questionnaire during class hours. Questionnaires
were given to teachers for distribution to students
not attending class at the time of the study. In addition, participants were asked to provide a saliva
sample for DNA extraction by rinsing their mouth
for 30 sec with a 0.9% sodium chloride solution. Participation was anonymous and voluntary. Because of
the anonymous design of the study and the relatively
mature age of the adolescent participants, informed
written consent from participants or their parents was
not deemed necessary. A total of 2,263 students completed the questionnaire (77.4% of the target population), of whom 183 were late responders who returned
their questionnaires by mail. Saliva samples were provided by 2,131 participants. Seven participants did not
state their sex and were excluded. Because of problems with the 5-HTTLPR analyses, 586 participants
were excluded. These genotype analysis problems will
be further addressed in the Discussion. Another 71
participants were excluded because of internal questionnaire nonresponse, leaving 753 boys and 714 girls
in the final models. The study followed the Swedish
guidelines for studies of social science and humanities
according to the Declaration of Helsinki and was approved by the regional ethics review board of Uppsala
University.
Measures
5-HTTLPR polymorphism genotype analysis.
The polymerase chain reaction (PCR) based genotyping of the 5-HTTLPR polymorphism was amplified from 3–30 ng genomic DNA using the primer
sequences: forward 5 -AAC ATG CTC ATT TAA
GAA GTG GAA C-3 and reverse 5 -HEX CT AGA
GGG ACT GAG CTG GAC AAC-3 . PCR was performed in a 10 μL reaction mixture containing 30 ng
DNA, 1 mM PCR Buffer 10× with 1.5 mM MgCl2 ,
0.2 μM dNTPs, 0.8 μM of two primers, and 0.5 U
FastStart Taq DNA polymerase (Roche Diagnostics
GmbH, Mannheim, Germany). The PCR reactions
were performed on a GeneAmp 9700 (Applied Biosystems Inc., Foster City, CA) with the following profile:
starting at 94◦ C for 4 min, followed by 35 cycles of
denaturation at 94◦ C for 45 sec, annealing at 61◦ C
for 1 min, and elongation at 72◦ C for 90 sec, with
a final extension at 72◦ C for 7 min. The PCR products were analyzed by capillary electrophoresis usR
3700 DNA Analyzer (Applied
ing an ABI PRISM
Aggr. Behav.
4 Åslund et al.
Biosystems Inc.) and allele sizes were determined
R
manually on chromatograms using Gene Marker
1.5 AFLP/Genotyping software (SoftGenetics LLC,
State College, PA). As a control method in the case
of inconsistencies, the genotype analysis was carried
out a second time and the PCR products were analyzed by electrophoresis on a 2% agarose gel. The
gel was run at 120 V and visualized under UV light.
Running buffer was 0.5× Tris-EDTA buffer, and sizes
were determined by comparison with a 100-bp DNA
sequencing ladder.
For the analyses, 5-HTTLPR genotypes were divided into three groups: individuals homozygous for
the short allele (SS), heterozygous (LS), and individuals homozygous for the long allele (LL).
Demographic
data. Variables
were
dichotomized as follows: sex (boy: 0, girl: 1), whether
the parents were living together (0) or divorced/
separated (1), whether both parents were working
(0) or one or both parents were unemployed (1),
whether the participant was living in a single-family
house (0) or a multifamily house (1), whether
both parents were born in Sweden or Scandinavia
(0) or at least one parent was born outside of
Scandinavia (1).
Delinquency. This was measured by the following questions: How often have you . . .
(1) broken into a house, shop, store, kiosk, or other
building with the intention to steal things?
(2) sold or bought something you knew was
stolen?
(3) threatened or forced someone to give you money,
cigarettes, or anything else?
(4) been involved in a fight during your leisure time
(not at school)?
(5) carried a weapon (knuckle-duster, baseball bat,
knife, switch-blade, or similar) at school or during your leisure time?
(6) stolen a car?
(7) stolen a moped, motorbike, or motor scooter?
(8) hit/kicked someone so hard he/she needed medical attention?
(9) deliberately hurt someone with a knife, switchblade, knuckle-duster, or similar?
(10) been involved in threatening another person to
do something he/she did not want to?
(11) by yourself threatened another person to do
something he/she did not want to?
(12) been involved in breaking into and stealing
something from a car?
(13) by yourself broken into and stolen something
from a car?
Aggr. Behav.
(14) had sex with a person who was so drunk/high
that he/she did not really understand what was
going on?
(15) had sex with a person against his/her will?
The response alternatives were: never (0), once (1),
two to four times (2), five to ten times (3), more than
ten times (4). The internal consistency of the delinquency items measured by Cronbach’s α was .96. A
delinquency index was created as a summation of the
above questions. For the descriptive figures, we created a dichotomous variable where delinquency was
measured as having committed at least one delinquent
act during one’s lifetime. We also created a nonviolent delinquency index by summarizing items 1, 2,
6, 7, 12, and 13 (range 0–24 points, Cronbach’s α =
.90) and a violent delinquency index by summarizing items 3, 4, 5, 8, 9, 10, 11, 14, and 15 (range 0–36
points, Cronbach’s α = .87). The correlation between
the violent and nonviolent delinquency subscales was
Spearman’s rho = .494, P < .001.
The use of the delinquency measures has previously
been reported [Åslund et al., 2011], although in a
slightly different version that included several questions on vandalism and minor theft. In the present
study, we chose to exclude those questions and only
included questions on delinquent acts deemed severe
according to Swedish law.
Family SES. This was measured by using a modified version of the Goodman et al. [2001] scale of
adolescent social status. This use of the measurement
has been reported previously [Åslund et al., 2009b,
2009c, 2010].
The variable family SES was constructed from the
following two questions:
(1) Imagine society as being like a ladder. At the bottom are those with the least money, at the top
are those with the most. If you think about how
wealthy your own family is compared with the rest
of society, where would you place your family on
this scale?
(2) Imagine society as being like a ladder. At the bottom are those with the lowest standing, at the top
are those with the highest. If you think of the
standing/position of your family compared with
the rest of society, where would you place your
family on this scale?
Answers were given on a 7-point Likert
scale, where 1 represented lowest place—least
money/standing, and 7 represented highest place—
most money/standing. The two questions were summarized into an index ranging from 2 to 14 points.
Family SES, 5-HTTLPR, and Delinquent Behavior
TABLE I. Prevalence of Any Lifetime Delinquent Behavior,
Family Socioeconomic Status (SES), and 5-HTTLPR Genotype
Frequencies in the Study Population
Boys
Delinquent behavior (N = 2,169)
Yes
552 (48.1%)
No
596 (51.9%)
Family SES (N = 2,175)
Low
232 (19.7%)
Medium
766 (65.2%)
High
177 (15.1%)
5-HTTLPR (N = 1,538)
SS
156 (19.8%)
SL
392 (49.7%)
LL
240 (30.5%)
Girls
208 (20.4%)
813 (79.6%)
232 (23.2%)
651 (65.1%)
117 (11.7%)
165 (22.0%)
346 (46.1%)
239 (31.9%)
For the descriptives, we divided the family SES index
into three categories: 2–7 points were taken as low
family SES, 8–10 as medium family SES, and 11–14
as high family SES. These cutoff points were chosen
to make the groups as equal in proportion as possible,
because most people have a tendency to rank themselves as slightly above average regarding attractive
personal qualities such as intelligence, friendliness,
and status [Evans and Kelley, 2004; Marmot, 2004],
and this trend is even more common among adolescents [Goodman et al., 2001].
Nonindependent adjustment variables. The
analyses were adjusted for alcohol consumption according to the AUDIT-C [Nilsson et al., 2011]
and major depression according to the Depression
Self-Rating Scale of the DSM-IV [Åslund et al.,
2009a] because these factors are known to be associated with both SES and the 5-HTTLPR.
Statistical Analyses
Differences between groups were analyzed by ttests and ANOVA and controlled by nonparametric Kruskal–Wallis tests. Main and interaction effects were analyzed by general linear models (GLMs).
Curvilinear associations of family SES were analyzed
by including Z-score transformation (family SESz)
as well as a quadratic term (family SESz2 ). We also
validated the GLMs with a Poisson log-linear model.
The model was furthermore adjusted for other known
nonindependent confounding factors related to both
family SES and the 5-HTTLPR.
RESULTS
Descriptive statistics are presented in Table I. Frequency of delinquent behavior was higher among
boys (boys: M = 3.40, SD = 7.19; girls: M = 0.73,
5
SD = 2.39, t (1,465) = 9.44, P < .001). Boys reported
a higher family SES than girls (boys: M = 8.80, SD =
1.88; girls: M = 8.57, SD = 1.75, t (1,465) = 2.43,
P = .015). Regarding the 5-HTTLPR, the distribution of the genotype did not differ from what could
be expected according to the Hardy–Weinberg equilibrium (total population: χ2 (2) = 1.67, P = .20; boys:
χ2 (2), = 0.032, P = .86; girls χ2 (2) = 3.50, P = .062).
The demographic background factors were associated with mean values of the delinquency index (Separated parents: M = 2.63, SD = 6.03 vs. parents living
together: M = 1.74, SD = 5.11, t (1,401) = −2.94, P =
.003; Living in a multifamily house: M = 2.73, SD =
6.03 vs. living in a single-family house: M = 1.82,
SD = 5.35, t (1,463) = −2.90, P = .004; At least one
parent unemployed: M = 2.71, SD = 7.20 vs. both
parents working: M = 1.87, SD = 4.85, t (1,458) =
−2.55, P < .001; Non-Scandinavian ethnicity: M =
3.54, SD = 8.29 vs. Scandinavian ethnicity: M = 1.86,
SD = 4.95, t (1,449) = −4.08, P < .001).
Late responders reported a lower family SES than
the total population (M = 8.21, SD = 1.79 vs. M =
8.71, SD = 1.82, t (1,465) = 2.31, P = .021) but there
was no difference in delinquency (P = .465) between
late responders and the total population. There were
no differences in family SES (P = .898) between the
group of participants where DNA analyses of the 5HTTLPR failed and individuals where 5-HTTLPR
analysis succeeded. However, there was higher delinquency among individuals with 5-HTTLPR analysis
failure (M = 3.10, SD = 6.80 vs. M = 2.10, SD = 5.59,
t (2,011) = 3.37, P = .001). The 5-HTTLPR analysis
failure rate was higher for boys (30.4% vs. 24.2%, χ2
(1) = 9.60, P = .002).
There were associations between the measures of social status and delinquency. Adolescents with medium
family SES had the lowest delinquency scores and
adolescents with low family SES had the highest
delinquency scores, followed by adolescents with high
family SES. The association between family SES and
delinquency can be pictured as a U-shaped association, as presented in Figure 1.
There were no differences in delinquency depending on 5-HTTLPR genotype without adjusting for
socioeconomic factors. Because a curvilinear effect
was found for family SES in relation to delinquency,
we analyzed our GLM models accordingly.
In multivariate GLM analyses of sex, 5-HTTLPR,
and linear and quadratic family SES in relation to
delinquency, there were significant main effects of sex
(F (1, 1,449) = 41.393, P < .001), 5-HTTLPR (F (2,
1,449) = 3.625, P = .027), family SESz (F (1, 1,449) =
3.931, P = .048), and family SESz2 (F (1, 1,449) =
20.540, P < .001). Furthermore, there were significant
Aggr. Behav.
6 Åslund et al.
Fig. 1. Differences in delinquency index scores according to family socioeconomic status (SES) (M and 95% CI).
two-way interactions between sex × family SESz (F
(1, 1,449) = 4.529, P = .033), sex × family SESz2 (F (1,
1,449) = 4.910, P = .027), 5-HTTLPR × family SESz
(F (2, 1,449) = 5.788, P = .003), and 5-HTTLPR ×
family SESz2 (F (2, 1,449) = 3.662, P = .026). Finally,
significant three-way interactions were found for sex
× 5-HTTLPR × family SESz (F (2, 1,449) = 3.843,
P = .022) and sex × 5-HTTLPR × family SESz2 (F (2,
1,449) = 9.606, P < .001). No significant interaction
effect was found for sex × 5-HTTLPR. The observed
power (with an α of .05) of the main and interaction effects ranged between .57 and .99, except for the
main effect of family SESz and the sex × 5-HTTLPR
interaction, which had a power of .51 and .40, respectively. These findings remained after adjusting for
the nonindependent confounding factors of separated
parents, parental unemployment, living conditions,
ethnicity, alcohol consumption, and depression, except for the main effect of family SESz, which was
nonsignificant. Moreover, to eliminate sampling effects, we performed analyses with two random samples of 75% of the population. These analyses showed
significant results of the same magnitude for the interaction effects, except the sex × family SESz interaction (P = .048 and .084, respectively) and the sex ×
family SESz2 interaction (P = .118 and .152, respectively).
To validate our GLM models, we also performed
Poisson log-linear models. In these models, significant
main effects were found for sex (χ2 (1) = 731.229, P <
.001), 5-HTTLPR (χ2 (2) = 63.483, P < .001), family
SESz (χ2 (1) = 5.158, P = .023), and family SESz2 (χ2
(1) = 43.198, P < .001). Significant two-way interaction effects were found for sex × 5-HTTLPR (χ2 (2) =
Aggr. Behav.
8.563, P = .014), 5-HTTLPR × family SESz (χ2 (2) =
43.719, P < .001), and 5-HTTLPR × family SESz2
(χ2 (2) = 63.519, P < .001). Furthermore, three-way
interaction effects were found for sex × 5-HTTLPR
× family SESz (χ2 (2) = 22.650, P < .001) and sex
× 5-HTTLPR × family SESz2 (χ2 (2) = 57.526, P <
.001).
Because there is reason to believe that there is a difference between violent and nonviolent delinquency,
we performed another GLM analysis to test this. In
the nonviolent delinquency model, there were significant main effects of sex (F (1, 1,449) = 28.242, P <
.001), 5-HTTLPR (F (2, 1,449) = 3.891, P = .021),
family SESz (F (2, 1,449) = 4.457, P = .035), and
family SESz2 (F (1, 1,449) = 10.175, P = .001). Furthermore, there were significant two-way interactions
between sex × family SESz (F (1, 1,449) = 4.681,
P = .031), sex × family SESz2 (F (1, 1,449) = 5.370,
P = .021), and 5-HTTLPR × family SESz (F (2,
1,449) = 6.314, P = .002). Finally, three-way interactions were found for sex × 5-HTTLPR × family
SESz (F (2, 1,449) = 3.160, P = .043) and sex ×
5-HTTLPR × family SESz2 (F (2, 1,449) = 5.733,
P = .003).
In the model of violent delinquency, there were significant main effects of sex (F (1, 1,449) = 39.448,
P < .001), 5-HTTLPR (F (2, 1,449) = 3.126, P =
.044), and family SESz2 (F (1, 1,449) = 23.719, P <
.001). Furthermore, there were significant two-way interactions between 5-HTTLPR × family SESz (F (2,
1,449) = 3.828, P = .022) and 5-HTTLPR × family
SESz2 (F (2, 1,449) = 3.995, P = .019). However, the
two-way interactions with sex did not reach significance, although a borderline significance was found
for sex × family SESz2 (F (1, 1,449) = 3.708, P = .054.
Finally, a three-way interaction was found for sex ×
5-HTTLPR × family SESz2 (F (2, 1,449) = 10.400, P
< .001).
Because previous studies have shown sex differences
in the direction of gene–environment interaction effects concerning the 5-HTTLPR [Åslund et al., 2009a;
Sjoberg et al., 2006], we performed further multivariate GLM analyses divided by sex. There was a significant main effect of the 5-HTTLPR among girls,
but not among boys (Table II). Interaction effects
between the 5-HTTLPR and family SESz2 were significantly related to delinquency between both sexes
in the model (Table II, model A). The model was
then adjusted for other nonindependent demographic
factors and comorbid phenotypic factors such as alcohol consumption and depression. This adjusted
model showed similar gene–environment interaction
effects as the unadjusted model for both boys and girls
(Table II, model B).
Family SES, 5-HTTLPR, and Delinquent Behavior
7
TABLE II. Two Multivariate General Linear Models Testing the Effect of the 5-HTTLPR in Interaction with Linear and Quadratic
Family Socioeconomic Status (SESz and SESz2 ) on Delinquency; df, F, and P values, model A unadjusted and model B adjusted for
nonindependent confounding factors
Model Aa
Boys
Girls
1. 5-HTTLPR
2. Family SESz
3. Family SESz2
1×2
1×3
1. 5-HTTLPR
2. Family SESz
3. Family SESz2
1×2
1×3
Model Bb,c
df
F
P
df
F
P
2, 744
1, 744
1, 744
2, 744
2, 744
2, 705
1, 705
1, 705
2, 705
2, 705
2.596
4.946
12.440
5.797
7.124
3.757
0.052
14.174
3.614
9.706
.075
.026
<.001
.003
.001
.024
.820
<.001
.027
<.001
2, 689
1, 689
1, 689
2, 689
2, 689
2, 661
1, 661
1, 661
2, 661
2, 661
1.766
0.974
7.571
6.665
6.916
3.366
0.586
7.398
2.738
10.792
.172
.324
.006
.001
.001
.035
.444
.007
.065
<.001
R2 , Boys = .073, Girls = .059. b Adjusted R2 , Boys = .203, Girls = .106. c Adjusted for separated parents, parental unemployment, living
conditions, ethnicity, alcohol consumption, and depression.
a Adjusted
The directions of the findings regarding family
SES and the 5-HTTLPR are further illustrated in
Figure 2. Curvilinear associations between family
SES and delinquency were found among boys carrying the LL or LS genotypes, and girls carrying the SS
or LS genotypes (Fig. 2). Among individuals having
high family SES, boys with the LL or LS genotypes
and girls with the SS or LS genotypes showed the
highest delinquency scores. Among individuals having low family SES, boys with the LL genotype and
girls with the LS genotype showed the highest delinquency scores.
Fig. 2. Regression plot of predicted values (means and standard deviations) for boys and girls of 5-HTTLPR and family socioeconomic status
(SES) interaction in relation to delinquency. SS denotes individuals homozygous for the short allele, LS denotes heterozygous individuals, and
LL denotes individuals homozygous for the long allele.
DISCUSSION
The present study investigated associations between
family SES and the 5-HTTLPR genotype in relation
to delinquency in a representative adolescent population in Sweden. The main findings were as follows.
First, delinquency had a U-shaped relation to family
SES, where adolescents with medium family SES were
the least delinquent, while adolescents with low family SES were the most delinquent, closely followed by
adolescents with high family SES. Second, there was
an interaction between the 5-HTTLPR and family
SES in relation to delinquency. Curvilinear associations between family SES and delinquency were found
among boys carrying the LL and LS genotypes, and
girls carrying the SS and LS genotypes.
A possible explanation for the U-shaped results of
family SES in relation to delinquency may be cultural
differences between different socioeconomic groups.
Adolescents from different social classes may differ in
behavior because of variations in upbringing and values. The SES of the family may, for example, involve
different demands for success and consequences of
failure. Moreover, the norms of liberty may vary depending on social class. Such a view would be in agreement with results reported by Luthar and Ansary
[2005], for example. Interestingly, there was no sex
difference in this regard, although there are reports of
gender differences in risk and promotive factors associated with adolescent delinquency [Whitney et al.,
2010]. One possible explanation would be that boys
and girls may be socialized differently depending not
only on cultural gender roles [Block, 1983] but possibly also on social class. Adolescents from the lower
socioeconomic groups in society might grow up in
an environment characterized by traditional gender
Aggr. Behav.
8 Åslund et al.
role values regarding what boys and girls are allowed
to do. In contrast, higher SES and education levels are often associated with more egalitarian gender role attitudes [Bryant, 2003; Morgan and Walker,
1983]. This could suggest that boys with lower SES are
influenced by more traditional gender role attitudes,
involving higher liberty within the behavioral spectrum. Similarly, girls with high SES may have a high
degree of liberty of behavior as a result of more modern egalitarian gender role attitudes. Following this,
these two groups of male and female adolescents show
the most delinquent behavior, although the reasons
behind their behavior are socioeconomically and culturally different.
Serotonin is one of the neurotransmitters most often associated with neurobiological mechanisms behind social and aggressive behavior [Carrillo et al.,
2009; Lucki, 1998; Nordquist and Oreland, 2010].
Among various biological measures of central serotonergic function on a molecular level, the variation
in the serotonin transporter promoter of functional
importance, the 5-HTTLPR, has recently been much
studied. Thus, several studies have reported an association between the S-allele of the 5-HTTLPR and
aggression, impulsiveness, and conduct disorder in
both childhood and adulthood [Beitchman et al.,
2006; Gerra et al., 2005; Haberstick et al., 2006; Retz
et al., 2004; Sakai et al., 2006]. However, there have
also been several nonreplications [Beitchman et al.,
2003; Sakai et al., 2007]. Furthermore, SES covaries
with central serotonergic responsivity as a function
of allelic variation of the 5-HTTLPR [Manuck et al.,
2004, 2005; Matthews et al., 2000]. Carriers of the
short, low-expressing variant have an approximately
25% reduction in the volume of the perigenual anterior cingulate cortex and uncoupling of a feedback
circuit implicated in the extinction of negative affect
[Pezawas et al., 2005], which is in agreement with
findings of increased susceptibility to stress and to
emotional response in both non-human and human
primates [Barr et al., 2003; Caspi et al., 2010]. The
size of this brain region has also been shown to covary with perceived social standing [Gianaros et al.,
2007]. In the present study, we hypothesized that adolescents who were carriers of the short variant of the
5-HTTLPR (S) would be the most delinquent and
that family SES would have an impact on the expression of such behavior. This hypothesis was partly confirmed. Curvilinear associations between family SES
and delinquency were found among girls carrying the
SS or LS genotypes and boys carrying the LL or LS
genotypes. Thus, the 5-HTTLPR differed in its relation to delinquency depending on family SES. The
results are interesting in the light of previous findings
Aggr. Behav.
of an interaction between SES and the short variant of
the 5-HTTLPR in relation to low brain serotonergic
responsivity [Manuck et al., 2004]. No differences in
prevalence of delinquency in relation to 5-HTTLPR
genotype were found without adjusting for the social
status of the family, which might be explained by the
U-shape of the association.
Moreover, the results may be interpreted in relation to the differential susceptibility hypothesis,
also called the hypothesis of biological sensitivity
to context [Beaver and Belsky, 2012; Belsky and
Pluess, 2009; Boyce and Ellis, 2005]. It has been
described previously that the short 5-HTTLPR allele is associated with higher sensitivity to environmental context [Belsky and Pluess, 2009], especially among females [Åslund et al., 2009a; Sjoberg
et al., 2006]. However, in the present study, boys
with the LL and LS genotypes seemed to show
the highest plasticity of the 5-HTTLPR gene, because of the curvilinear associations between family
SES and delinquency. The same pattern was found
among girls with the SS and LS genotypes, who also
showed curvilinear associations between family SES
and delinquency. This suggests that genetic plasticity
may have a dimension beyond sensitivity to stressful or supportive environments. Individuals differ in
phenotype according to environment, but the environmental exposure might also have different stressful impacts according to genotype. The association
between SES and delinquency may thus partly depend on individual genetic differences in sensitivity
to environmental influence.
The results should be interpreted in the light of several limitations and strengths. First, the study relies on
self-reports, which involves a risk of information bias
resulting from false or inaccurate responses from the
participants. During self-reporting, individuals tend
to overestimate their positive traits such as social status [Evans and Kelley, 2004], and underestimate or
diminish their socially undesired behaviors such as
delinquency [Cillessen and Mayeux, 2004; Österman
et al., 1998]. However, an alternative method using
official records of delinquent behavior is known to
underestimate greatly the prevalence of delinquency
and suffers from biases in police and court processing
[Farrington, 1998]. Thus, many criminologists today
rely on self-reports [Hindelang et al., 1979] as a reliable and valid method for measuring delinquency
[Smith and Thornberry, 1995].
Second, we reached only 77.4% of the target population, which may have influenced the results. There
were 183 late responders, who completed the questionnaire at a later time because of their absence
from school and returned it together with their saliva
Family SES, 5-HTTLPR, and Delinquent Behavior
sample by mail. No significant differences in delinquency were found in the late responding group. According to Miller and Smith [1983], late respondents
tend to be similar to nonrespondents in survey studies. Moreover, another 664 participants were excluded
from the analyses because of problems with the 5HTTLPR genotyping or missing answers. The DNA
extraction method was not optimal and in some cases
yielded poor quality DNA. The anonymous design of
the study did not allow for collection of another DNA
sample from these individuals. There were no differences in the measures of social status among those
with available 5-HTTLPR genotype compared with
the individuals where genotyping failed. However,
individuals for whom genotyping failed had higher
delinquency scores. It is possible that individuals with
self-reported antisocial behavior might have been less
careful in applying the required procedure to give the
saliva sample. Thus, the mean delinquency might have
been somewhat higher if the individuals with genotype failure had been included in the study, especially
among boys, who had a higher 5-HTTLPR analysis
failure rate. It is not possible, however, to speculate
whether there would have been any differences in the
distribution of the 5-HTTLPR genotypes and thus
any changes in our results. Moreover, the triallelic nature of the 5-HTTLPR was not analyzed in the present
study. This triallelic nature has been described as an
A > G polymorphism at position 6 of the first of two
22-bp imperfect repeats defining the 16-repeat L allele
and has been suggested to be equivalent in expression
to the S allele [Nakamura et al., 2000]. This LG allele has a reported frequency of 9–14% in Caucasians
and 24% in African-Americans, and the three alleles
(S, LA , and LG ) appear to act differently [Hu et al.,
2005]. Another A > G substitution has been identified
in the S allele [Kraft et al., 2005]. There is, however, a
need for further functionality studies regarding these
allelic variations.
Third, the delinquency variable was skewed and neither a log- nor a log–log transformation produced
a symmetric distribution of the data. It is difficult
to choose appropriate statistical methods in a study
of gene–environment interactions where the outcome
measures are on skewed ordinal or interval scales. On
the one hand, interactions are efficiently estimated
by a GLM but the inference is not valid if the assumption of normally distributed residuals is violated. Therefore, although GLMs could be used to estimate main and interaction effects, the results should
be interpreted with caution. However, we performed
analyses of observed power, two analyses of random
samples of 75% of the population that tested for
sampling effects, and complemented our statistics
9
with a Poisson log-linear regression, which is suitable for ordinal scaled variables and the kind of distribution that was found in the present study. Procedures with complementary statistical approaches can
help to overcome shortcomings of individual statistical methods and help to eliminate scaling artifacts,
one of the ubiquitous sources of artifacts in interaction research. The GLM, the random sample analyses, and the Poisson log-linear model all showed similar results, in the same direction, which gives further support to the robustness of the findings. We
also adjusted our model for possible nonindependent
confounders. In these models, the curvilinear interaction effect between 5-HTTLPR and family SES remained significant and of equivalent magnitude, indicating a robust finding of the gene–environment
interaction. However, it should be noted that even
though the models were significant, the unadjusted
explained variance in relation to delinquency was
relatively low (6–7%) compared with, for example,
monoamine oxidase A gene–environment interaction
studies that have shown 10–60% explained variance
[Åslund et al., 2011; Caspi et al., 2002; Nilsson
et al., 2006].
An important strength of the present study is the
large population based sample of adolescents from
a county that is considered to be representative of
Sweden as a whole because of its distribution of education, income, and employment levels together with
urban and rural areas [SCB, 2009]. There is intense
debate at present about candidate gene–environment
interaction studies (G × E) on the one hand, and
genome-wide association studies (GWAS) of single
nucleotide polymorphisms (SNPs) on the other [Banaschewski et al., 2010; Duncan and Keller, 2011].
We believe that both methods of analyzing the genetic contribution to psychiatric conditions are important and complementary. Despite high heritability
in most psychiatric conditions, GWAS in psychiatry
have been particularly poor, with a low explanation
of the observed variance [Banaschewski et al., 2010].
Areas of explanation that are in favor for candidate
gene analysis are that gene–gene (G × G) and G × E
interactions may make strong contributions to the observed heritability of psychiatric conditions, and that
genetic factors other than SNPs, such as insertions,
deletions, and duplications, may play important roles
[Banaschewski et al., 2010].
In the view of previous findings regarding associations between SES, the serotonergic system, and aggression, the present study suggests evidence for an
interaction between family SES and the 5-HTTLPR
in relation to juvenile delinquency. Because of the relatively representative population sample, our results
Aggr. Behav.
10
Åslund et al.
might also be valid for other nonreferred adolescent
populations.
ACKNOWLEDGMENTS
The sponsors of the study had no role in the study
design, data collection, data analysis, data interpretation, or writing of the report.
Conflict of interest
None declared.
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