ur knowledge of psychiatric and substance-use
genetics comes from two key fields of research, both
dynamic areas in rapid change. First, genetic epidemiol-
ogy asks whether there is risk in excess of the population
baseline in the relatives of cases, and, if so, whether the
excess risk is attributable to the genetic factors or the
environments they share. Beyond simply estimating her-
itability, genetic epidemiology has evolved to address
more sophisticated questions, such as whether liability
genes have the same effects across the lifespan, how they
may influence multiple disorders, and how they might
interact with environmental risks.
Genetic epidemiology of psychiatric and behavioral phe-
notypes has consistently demonstrated that: i) genetic
risk factors are, in aggregate, important etiological com-
ponents; ii) they cannot completely account for observed
risk, meaning these phenotypes are multifactorial traits,
with important nongenetic (or environmental) con-
tributing factors; and iii) the risk alleles appear to be of
small effect size and to occur in a large number of genes.
Psychiatric and behavioral phenotypes are influenced by
a large number of risk factors that individually are within
the range of normal human variation and produce mod-
est individual increases in risk.
The initial goal of the second major research area, mole-
cular genetics, is to identify genes which influence these
S t a t e o f t h e a r t
Copyright © 2010 LLS SAS. All rights reserved www.dialogues-cns.org
Nature and nurture in neuropsychiatric
genetics: where do we stand?
Danielle M. Dick, PhD; Brien Riley, PhD; Kenneth S. Kendler, MD
Keywords: genetics; gene-environment interaction; alcohol dependence; twin
Author affiliations: Virginia Institute of Psychiatric and Behavioral Genetics;
Department of Psychiatry; Department of Human and Molecular Genetics,
Virginia Commonwealth University School of Medicine, Richmond, VA, USA
(Danielle M. Dick*, Brien Riley*, Kenneth S. Kendler); Department of Psychology,
Virginia Commonwealth University, Richmond, Virginia, USA (Danielle M. Dick*)
*These authors contributed equally to the review
Address for correspondence: Kenneth S. Kendler MD, Dept Psychiatry MCV, PO
Box 980126, Richmond VA 23298, USA
Both genetic and nongenetic risk factors, as well as inter-
actions and correlations between them, are thought to
contribute to the etiology of psychiatric and behavioral
phenotypes. Genetic epidemiology consistently supports
the involvement of genes in liability. Molecular genetic
studies have been less successful in identifying liability
genes, but recent progress suggests that a number of spe-
cific genes contributing to risk have been identified.
Collectively, the results are complex and inconsistent, with
a single common DNA variant in any gene influencing
risk across human populations. Few specific genetic vari-
ants influencing risk have been unambiguously identified.
Contemporary approaches, however, hold great promise
to further elucidate liability genes and variants, as well as
their potential inter-relationships with each other and
with the environment. We will review the fields of
genetic epidemiology and molecular genetics, providing
examples from the literature to illustrate the key concepts
emerging from this work.
© 2010, LLS SAS Dialogues Clin Neurosci. 2010;12:7-23.
phenotypes and to identify the specific risk variants within
them. There are substantial differences in DNA sequences
between individuals, and gene identification methods test
whether specific alleles at these variable positions are
more common in affected than in unaffected individuals,
most commonly with linkage studies (in families) and
association studies (primarily in case/controls, but also in
numerous other designs). We will discuss the underlying
causes of these two genetic phenomena, the methods for
detecting them, and the limitations of each.
The second goal of molecular genetics is to identify spe-
cific risk alleles and to use functional studies to elucidate
how a gene functions normally, how the risk allele alters
normal function, and how these alterations contribute to
disease. The aim of this work is to explain the aggregate
genetic risks observed through the effects of risk alleles
on gene expression, protein structure and function,
and/or biological processes. This area remains largely
unsuccessful to date for complex traits generally.
In this review we focus on the basic methods of genetic
epidemiology and molecular genetics, and provide exam-
ples, across a variety of psychiatric and substance use dis-
orders, of questions currently being addressed. In con-
trast to this first section on genetic epidemiology, the
sections on molecular genetics focus narrowly on schiz-
ophrenia, where there is a much longer history of mole-
cular genetic studies, because we judged that emphasiz-
ing a single disorder would provide a more coherent
example of ongoing research progress and challenges.
Basic genetic epidemiology
The most fundamental question addressed by psychiatric
genetic epidemiology is whether a particular trait or dis-
order shows evidence for genetic influence. Both twin
and adoption studies provide methods to address this
question and tease apart the degree to which genetic and
environmental influences are important on a given out-
come. Twin studies accomplish this by comparisons of
the similarity of monozygotic twins (MZs; who share
100% of their genetic variation), with dizygotic twins
(DZs; who share on average just 50% of their genetic
variation). Adoption studies compare similarity among
adopted-apart biological relatives, who share genetic
variation, but not their environments, and adoptive rel-
atives, who share their environment, but not their
genetic makeup. Through these comparisons, we can
quantify the degree to which genetic influences con-
tribute to individual differences in risk, a statistic com-
monly referred to as the heritability of the trait. These
study designs have been applied to virtually all psychi-
atric disorders and to a number of related traits, yielding
compelling evidence that genetic influences play a criti-
cal role in virtually all psychiatric outcomes. There is
considerable variability in the magnitude of genetic
influence across different disorders. On the high end are
disorders such as schizophrenia, bipolar disorder, and
autism, which yield heritability estimates of the order of
80% or higher. Alcohol and other drug dependence
shows moderate heritability, in the range of 50% to 60%.
On the lower end of the spectrum, though still showing
significant evidence of genetic influence, are anxiety and
depressive disorders, as well as eating disorders, which
yield heritability estimates of ~30% to 40%. So, while
there is variability in the magnitude of importance of
genetic effects, it is widely accepted that a significant
genetic component plays a role in virtually all psychiatric
traits. It is a sign of the paradigm shift that has taken
place in psychiatry that heritability estimates are no
longer considered controversial, since the original stud-
ies finding evidence for genetic effects represented
strong challenges to predominant views favoring envi-
ronmental theories on the causation of most psychiatric
conditions, ranging from schizophrenia to autism to alco-
hol dependence—disorders that are all now widely rec-
ognized as having genetic components.
While demonstration of heritability played an important
role in altering fundamental assumptions about the eti-
ology of psychiatric disorders, if not understood in their
proper context, heritability estimates can also have a
number of unfortunate side effects. Firstly, the heritabil-
ity statistic created a dichotomy of genetic versus envi-
ronmental influence—nature versus nurture. How much
is genetic? How much is environmental? This is, as we
hope to show, a somewhat arbitrary distinction. Genetic
predispositions by necessity are expressed in the context
of the organism’s environment, and the environment can
differentially affect individuals based on their unique
genetic makeup. Further, many environments are not
simply “imposed” on an individual; rather, individuals
play an active role in selecting and shaping their envi-
ronments. Accordingly, it is generally more informative
to elucidate pathways of risk and show how genetic and
environmental influences come together in this process,
rather than trying to divide influence into that which is
genetic and that which is environmental. Secondly,
S t a t e o f t h e a r t
demonstration of heritability led to the idea that there
were genes “for” a given disorder. More complex mod-
els that have examined genetic influences across multi-
ple different conditions suggest that the Diagnostic and
Statistical Manual of Mental Disorders (DSM) structure
of psychiatric diagnoses often does not map onto the
underlying genetic architecture of psychiatric traits.
Genetic influences appear to be shared across many psy-
chiatric conditions, and likely operate through mediat-
ing characteristics that alter risk for a number of differ-
ent outcomes. Finally, static heritability estimates fail to
capture the dynamic nature of genetic and environmen-
tal influences on psychiatric outcome. Heritability esti-
mates are specific to the population under study. Lost in
heritability estimates are potential differences across
environmental conditions, across populations or gender,
and across ages. Accordingly, genetic epidemiology has
undergone an evolution in the kinds of questions being
addressed. No longer is the question simply “Are genetic
influences important on Trait X?” or even “How impor-
tant are genetic influences on Trait X?”. Rather, the
focus has shifted to addressing the complexities raised
here, using the paradigm we have called advanced
Advanced genetic epidemiology
Moving beyond genes versus environment:
gene-environment interaction and correlation
Parsing genetic and environmental influences into sep-
arate sources represents a necessary oversimplification,
as for most traits we know about, genetic and environ-
mental influences are inexorably intertwined. Most mea-
sures of the environment show some degree of genetic
influence, illustrating the active role that individuals play
in selecting and creating their social worlds.1To the
extent that these choices are impacted upon by an indi-
vidual’s genetically influenced temperaments and behav-
ioral characteristics, an individual’s environment is not
purely exogenous, but rather, in some sense, is in part an
extension and reflection of the individual’s genotype.
This concept is called gene-environment correlation or,
perhaps more descriptively, genetic control of exposure
to the environment. It is likely an important process in
the risk associated with several psychiatric outcomes. For
example, there is considerable evidence for peer
deviance being associated with adolescent substance use.
However, individuals play an active role in selecting
their friends, and multiple genetically informative sam-
ples have now demonstrated that a genetic predisposi-
tion toward substance use is associated with the selec-
tion of other friends who use substances.2-4Interestingly,
there is evidence that genetic effects on peer-group
deviance show a strong and steady increase across devel-
opment,5suggesting that as individuals get older and
have increasing opportunities to select and create their
own social environment, genetic factors assume increas-
ing importance. Another area where gene-environment
correlation is known to play a significant role is in the
risk pathways associated with depression. Stressful life
events have been consistently associated with the man-
ifestation of depression. However, there is evidence for
genetic influence on the occurrence of stressful life
events,6,7indicating that an individual’s predisposition
plays a role in the likelihood that they will experience
difficulties that are then associated with risk for depres-
sive episodes. For example, research has shown that a
genetic liability to major depression increases the risk
for a range of stressful life events, particularly those
reflecting interpersonal and romantic difficulties.8These
represent only a couple of areas where individuals are
known to play an active role in shaping environmental
factors that are associated with subsequent risk for psy-
Another way that genetic and environmental influences
are linked is via gene-environment interaction or, as we
might prefer, genetic control of sensitivity to the envi-
ronment. In these situations, genetic influences may vary
in importance as a function of environmental conditions
and/or that the environment differs in importance as a
function of an individual’s genetic predisposition (these
two conceptualizations of gene-environment interaction
are indistinguishable statistically). Heritability estimates
essentially average across environments; accordingly, if
there is reason to believe that the importance of genetic
effects might vary as a function of the environment, this
information can be incorporated into the twin model to
test for significant differences in heritability as a func-
tion of the environment. Substance use provides one
area where gene-environment interaction effects have
been found to be particularly important. Environments
that exert more social control and present less opportu-
nity to engage in substance use consistently show
reduced evidence for the importance of genetic effects.
In this sense, the environment is essentially constraining
Nature and nurture in neuropsychiatric genetics - Dick et al Dialogues in Clinical Neuroscience - Vol 12 .No. 1 .2010
the expression of a predisposition toward substance
use/problems. This has been demonstrated with respect
to enhanced parental monitoring in adolescents,9a more
religious upbringing,10and enhanced community stabil-
ity,11among other factors. One nice example of this can
be found in an analysis of the heritability of adolescent
smoking across the United States using data from the
National Longitudinal Study of Adolescent Health.
Genetic influences on daily smoking were lower in states
with relatively high taxes on cigarettes and in those with
greater controls on vending machines and cigarette
advertising, again suggesting the importance of social
control mechanisms in moderating the importance of
genetic influences on substance use.12
Delineating phenotypic boundaries of genetic risk
The rationale of the basic twin design can be expanded
to examine the extent to which genetic and environ-
mental factors contribute to the co-occurrence of psy-
chiatric conditions. Comorbidity among psychiatric dis-
orders is common, and multivariate twin studies have
helped address the etiological mechanisms that con-
tribute to these observed epidemiological patterns. A
fascinating result to emerge from these studies is that
psychiatric conditions with distinct clinical presentations
(eg, major depression and anxiety) are not necessarily
distinct genetically. For example, a study of major
depression and generalized anxiety disorder found a
genetic correlation of 1.0, suggesting that the same
genetic influences impact depression and anxiety, but
differences in environmental experiences contribute to
the manifestation of different outcomes.13An expanded
study that examined the genetic and environmental
architecture across seven common psychiatric and sub-
stance-use disorders found that genetic influences load
broadly onto two factors that map onto internalizing dis-
orders (depression, anxiety disorders), and externalizing
disorders (alcohol and other drug dependence, child-
hood conduct problems, and adult antisocial behavior).14
These findings indicate that while distinguishing these
disorders as “separate conditions” in the DSM may be
useful for clinical purposes, these categories do not nec-
essarily reflect differences in biological etiology. These
findings, along with similar results from phenotypic
analyses (eg, refs 15,16) have led some to suggest a reor-
ganization of the “metastructure” of psychiatric disor-
ders in DSM-V.
Another area of investigation examines whether there
are differences in the importance of genetic and envi-
ronmental factors at different stages of the disorder. For
example, the development of substance dependence is
necessarily preceded by several stages, including the ini-
tiation of the substance, the progression to regular use,
and the subsequent development of problems, whether
they be psychological, social, and/or physiological. Twin
studies can investigate the degree to which each of these
steps in the pathway of risk is influenced by genetic
and/or environmental factors, and the extent to which
the same or different genetic/environmental factors
impact different stages. For example, data from two pop-
ulation-based, longitudinal Finnish twin studies found
that shared environmental factors played a large role in
initiation of alcohol use, and a more moderate role on
frequency of use, and it was largely the same influences
acting across these stages of use. However, there was no
significant evidence of shared environmental influences
on alcohol problems in early adulthood. Problems were
largely influenced by genetic factors that overlapped
with genetic influences on frequency of use.17In a study
from Virginia in male twins, similar results were found
for alcohol, cannabis, and nicotine.18In the early years of
adolescence, shared environmental influences were
responsible for nearly all twin resemblance for levels of
intake of these psychoactive substances. However, as
individuals aged, the impact of shared environment
decreased and that of genetic factors increased.
Finally, there is known to be tremendous heterogeneity
among individuals with psychiatric conditions. Twin stud-
ies can provide insight into whether clinical hetero-
geneity may reflect differences in etiological risk factors.
For example, alcohol dependence with comorbid drug
dependence has been found to be a particularly herita-
ble form of the disorder,19,20and twin studies have sug-
gested a genetic influence on typical versus atypical
forms of major depression.21
Changing genetic influence across development
Another active area of research is the clarification of
how genetic and environmental influences may change
across development. A recent meta-analysis examined
published studies with at least two heritability time
points across adolescence and young adulthood for eight
different behavioral domains. These analyses revealed
significant cross-time heritability increases for external-
S t a t e o f t h e a r t
izing behaviors, anxiety symptoms, depressive symptoms,
IQ, and social attitudes, and nonsignificant increases for
alcohol consumption and nicotine initiation. The only
domain that showed no evidence of heritability changes
across time was attention-deficit/hyperactivity disorder.22
Similarly, in a large study of >11 000 pairs of twins from
four countries, the heritability of general cognitive abil-
ity was found to increase significantly and linearly from
41% in childhood (9 years) to 55% in adolescence (12
years) and to 66% in young adulthood (17 years).23The
robust finding of increases in the importance of genetic
influences across development likely reflects, in part,
active gene-environment correlation, as individuals
increasingly select and create their own experiences
based on their genetic propensities.
In addition to changes in the relative magnitude of
importance of genetic and environmental influences,
another dynamic change is that different genes may be
acting at different time points. This is nicely illustrated
in recent analyses of alcohol use problems, as assessed
at five time points from ages 19 to 28 in the Dutch Twin
Registry (Kendler et al, in preparation). Kendler and
colleagues found strong innovation and attenuation of
genetic factors across this age range—indicating that
some genetic influences on alcohol problems that were
evident at age 19 declined in importance across time,
while new genetic influences became important starting
at ages 21 and 23. Thus, although the overall heritability
of alcohol problems remained fairly stable, it appeared
that different genetic factors were important at different
timepoints. In analyses in the TCHAD Swedish study
which followed twins from ages 9 to 20 across four waves
of assessment, large changes were seen in the genetic
risk factors for fears and phobias24and for symptoms of
anxiety and depression,25with particularly pronounced
evidence for genetic innovation at puberty. These analy-
ses suggest that genetic influences of many psychiatric
and substance use disorders are likely to be develop-
Sex differences in the prevalence of psychiatric disor-
ders, and in risk and protective factors associated with
psychiatric outcomes, are widespread in epidemiology.
Twin studies allow us to investigate the extent to which
there are differences in the relative importance of
genetic and environmental influences on outcome, and
the extent to which different genes and/or environments
may be important. Large-scale twin studies have sug-
gested, for example, that the genetic risk factors for both
depression26and alcohol dependence,27while correlated,
are not entirely the same for males and females. Results
from two large twin studies in the US and Sweden agree
that the genetic influences of major depression are mod-
estly stronger in women than in men.26,28
Do we still need twin studies in the era of
As advances in molecular genetics and statistical analy-
sis have made it possible to conduct large-scale projects
aimed at identifying the specific genes involved in sus-
ceptibility to psychiatric outcome (detailed in the next
sections), some have raised questions about the contin-
uing utility of genetic epidemiology. The argument is that
heritability has now been established, which provides the
foundation and justification for moving beyond twin
studies, on to large-scale gene identification projects.
However, as detailed in this paper, most twin studies are
no longer conducted simply to test for the presence of
genetic effects; rather, they focus on the more complex
kinds of questions summarized above. These analyses
are not only informative about the nature of etiological
pathways of risk, but they can also be used to guide gene
identification efforts and to further our understanding
of the risk associated with specific genes as they are
Currently, gene-finding efforts for psychiatric disorders
(and other common, complex medical conditions) have
met with limited success. Findings from genetic epi-
demiology can be used to inform the phenotypes used in
gene-finding studies. For example, based on the twin lit-
erature (reviewed above) suggesting that much of the
predisposition to alcohol dependence is via a broad
externalizing factor, externalizing factor scores were cre-
ated in the Collaborative Study on the Genetics of
Alcoholism (COGA) sample, comprised of symptoms of
alcohol and other drug dependence, and childhood and
adult antisocial behavior, as well as the personality traits
of novelty-seeking and sensation-seeking, which also
index general behavioral disinhibition. This latent exter-
nalizing factor score was then used in both linkage and
association analyses, with results compared with analyz-
ing separately the individual symptoms of each of the
psychiatric disorders that went into the creation of the
Nature and nurture in neuropsychiatric genetics - Dick et al Dialogues in Clinical Neuroscience - Vol 12 .No. 1 .2010
general externalizing score.29The results demonstrated
that this broader externalizing phenotype was useful in
both linkage and association analyses, suggesting that
creating phenotypes grounded in the twin literature can
aid in identifying susceptibility genes. Twin data has also
been used to aid in genetic association studies in the area
of internalizing disorders. Using data from the Virginia
Adult Twin Study of Psychiatric and Substance Use
Disorders, multivariate structural equation modeling was
used to identify common genetic risk factors for major
depression, generalized anxiety disorder, panic disorder,
agoraphobia, social phobia, and neuroticism. Cases and
controls were then identified for genetic association
studies based on scoring at the extremes of the genetic
factor extracted from the twin analysis, with the subse-
quent association analyses yielding evidence for associ-
ation with the gene GAD1.30
Another area where genetic epidemiology intersects
with gene identification efforts is in the characterization
of risk associated with identified genes. Most major
gene identification efforts for psychiatric disorders cur-
rently focus on adult psychiatric outcomes. As we iden-
tify genes that are reliably associated with these disor-
ders, one of the next interesting research challenges will
be to study how risk associated with these genes unfolds
across development and in conjunction with the envi-
ronment. Here, findings from genetic epidemiology can
again be useful in developing hypotheses to test the risk
associated with specific genes. For example, based on
the twin literature suggesting that adult alcohol depen-
dence and childhood externalizing symptoms overlap in
large part due to a shared genetic predisposition,31genes
that were originally identified as associated with adult
alcohol dependence (eg, GABRA2,32CHRM233) have
been tested for association with externalizing behavior
in younger samples of children and adolescents. These
studies suggest that children carrying the genetic vari-
ants associated with alcohol problems later in life dis-
play elevated rates of conduct problems earlier in devel-
opment, before any association with alcohol
dependence has manifested.34-36Further, based on the
twin literatures suggesting that genetic influences on
externalizing behaviors are moderated by parental
monitoring9and peer deviance,37,38further analyses
demonstrated that the associations between these genes
and externalizing behavior were stronger under condi-
tions of lower parental monitoring and higher peer
deviance. Characterizing the risk pathways associated
with identified genes will be critical in eventually trans-
lating this information into improved prevention and
Gene identification methods
The field of psychiatric genetics has used two different
methods to attempt to identify individual risk genes:
linkage and association. These are fundamentally differ-
ent approaches with different study designs applied, until
recently, to very different research questions. It is impor-
tant to understand both in order to understand why
association approaches have become the norm in follow-
up studies of linkage regions as well as the primary cur-
rent approach in genome-wide studies.
Humans are ~99.9% identical at the nucleotide level on
average. Molecular genetic studies depend critically on
the remaining 0.1% (~3 million nucleotides) where vari-
ation occurs between individuals, collectively known as
genetic polymorphisms or markers. Linkage studies gen-
erally use short tandem repeat polymorphisms (STRs).
STR alleles are differing numbers of a repeating unit of
nucleotides and have specific sequence lengths and mol-
ecular weights as a result, allowing them to be separated
and identified. STRs are very common and tend to be
extremely polymorphic (ie, to have many alleles—where
an allele is one of the possible variants that exist in a
population at a particular genetic locus) and therefore
to have high heterozygosity (the proportion of individ-
uals who have two different alleles at the marker locus).
This high heterozygosity is important for linkage analy-
ses, which require a unique allele at each position on
each homologous chromosome to be informative.
In contrast, single nucleotide polymorphisms (SNPs) are
changes of a single base or insertion/deletion variation
up to a few nucleotides in size. SNPs generally have only
two alleles, and have lower heterozygosity and lower
information content. Association studies tend to use
SNPs as the marker of choice, because alleles of these
markers evolve more slowly than those of STRs and pre-
serve more of the evolutionary relationships on which
genetic association is based. SNPs can also be used for
linkage, but about ten times as many SNPs as STRs are
required to capture the linkage information.
S t a t e o f t h e a r t
In marker genotype data from families, new combina-
tions of alleles at a series of markers on individual chro-
mosomes are observed in each generation. This recom-
bination of alleles is observed because there is at least
one physical exchange of material (or crossover)
between each homologous chromosome pair in every
meiosis (Figure 1). Recombination between loci on dif-
ferent chromosomes (because of independent assort-
ment of homologous chromosome pairs) or far apart on
the same chromosome (because of crossover at meiosis)
is observed 50% of the time. Linkage is observed
between loci in close proximity on a chromosome
because their alleles are separated by crossover less than
50% of the time.
Mendelian diseases are caused by mutations in a single
gene at a single chromosomal location, so disease phe-
notypes can be treated as marker alleles in linkage
analysis. Because these illnesses are rare, for a dominant
disorder, the rare risk allele must segregate from one
parent (often affected or with family history) into
affected offspring, or arise as an even rarer de novo
mutation. By following the segregation of marker alle-
les from the affected lineage into offspring, linkage
between markers and phenotypes can be observed when
affected offspring inherit a particular set of marker alle-
les (and thus a specific parental chromosomal segment)
compared with their unaffected relatives.
While linkage occurs in families, association is a popu-
lation-based phenomenon. Genetic association studies
test whether specific alleles at variable sites are more
common in individuals affected by a disease (cases) than
individuals not affected by the disease (controls). This
association between allele and phenotype can occur for
two reasons. Either the allele being studied directly influ-
ences risk for the disorder or, more commonly, the allele
is in linkage disequilibrium (LD) with the disease-pre-
disposing allele. Linkage disequilibrium means that spe-
cific alleles at two nearby loci tend to occur together in
an entire population. Linkage, (the cosegregation of a
chromosome region and a disease observed in families),
occurs at scales of tens of millions of base pairs because
of the limited number of recombinations observed in
each generation of a family. Association (and LD) are
seen at scales of thousands to tens of thousands of base
pairs, because the number of recombinations present in
the evolutionary history of a population is large, mean-
ing that the physical distances between loci in LD must
be correspondingly small if recombination is to occur
rarely (if ever) between them.
LD occurs because a new allele always arises on a spe-
cific background chromosome (and its existing haplo-
type of marker alleles), and will, until separated by
recombination, only exist in conjunction with the other
alleles present on that background. Over time, the orig-
inal LD (and thus the genetic association) between more
distant loci decays as a result of recombination events,
while the rarity of recombination between nearby loci
preserves the original LD and association. Association
can also be detected spuriously, eg, if observed differ-
ences in allele frequency are due to population differ-
ences rather than to true association between marker
and phenotype. Association approaches are also sub-
stantially reduced in power in the presence of allelic het-
erogeneity (the existence of more than one risk allele at
a locus), while this phenomenon has no effect on the
detection of linkage.
Challenges associated with gene identification in psy-
chiatric and substance-use disorders
A number of features of psychiatric and behavioral phe-
notypes contribute to an overall reduction in study
power. Association is more powerful, generally for
detecting genes of small effect,39but the specific features
of psychiatric and behavioral phenotypes also reduce the
power of association studies.
First, psychiatric phenotypes are almost certainly influ-
enced by multiple common alleles of small effect in many
genes. Both linkage and association study designs are
more powerful for alleles of large effect size, and are
much less powerful when examining highly polygenic
phenotypes. Replication studies are hampered by the
need for sample sizes larger than the discovery sample
(in order to maintain power) and stochastic sampling
variation, the expected variation in the extent to which
any specific risk factor is present (and association
detectable) in any particular sample.
Second, interactions between genes (GxG) or between
genes and environmental variables (GxE) seem necessary
Nature and nurture in neuropsychiatric genetics - Dick et alDialogues in Clinical Neuroscience - Vol 12 .No. 1 .2010
to account for observed risks, but we rely heavily on ana-
lytic approaches that assess single genes. In a few cases,
genes with known molecular interactions with the can-
didates have also generated replicated association.
Environmental risk factors remain largely unknown and
are difficult or very expensive to test in many samples.
Third, these phenotypes are common, so the liability alle-
les seem likely to be common, although increased rates of
rare deletions and duplications (structural or copy num-
ber variants) in cases have been observed multiple times
and suggest that rare variation may also contribute to
risk in a proportion of cases. The common risk variants
are expected to occur with relatively high frequency in
the general population, reducing contrast between
affected and unaffected individuals and reducing power.
The impact of individual rare structural variants in the
subset of cases where they are observed is harder to
assess currently, but the observation of an aggregate
increase appears robust, further increasing the apparent
Fourth, the expected frequency of risk alleles and the
clinical variability in presentation, course, and outcome
suggest that the etiology of individual cases may be het-
erogeneous, derived from different specific genes or alle-
les between individuals. Allelic heterogeneity substan-
tially reduces the power of association designs.
Fifth, diagnostic boundaries are difficult to draw, and the
best phenotype to study is a complex choice. It is criti-
cally important to consider this last point and the phe-
notypes that yield the strongest evidence in some detail.
An example: schizophrenia
Through 2004, 25 complete or nearly complete genome
scans for schizophrenia (in which about 400 individual
genetic markers are genotyped at regular intervals over
the entire human genome) were published (for review
see refs 40,41). None provided evidence for genes of
major effect. Some linkage regions were replicated in
these studies, and a number of promising genes emerged
from sequential linkage and association studies and mul-
tiple replication reports. We focus here on those regions
with the best replication record and with evidence
emerging from other contemporary studies: 22q12-q13,
8p22-p21, 6p24-p22, and 1q32-42. Two additional regions
with little support in the primary literature, 2p11.1-q21.1
and 3p25.3-p22.1, were among the most significant in a
meta-analysis of schizophrenia genome scans. A number
of other regions (including 5q22-q31 and 15q13-q14)
have less strong summary evidence but also overlap with
evidence from more recent GWAS and structural varia-
Chromosome 22q, the VCFS microdeletion,
Chromosome 22q has been widely studied using many
different designs. Primary linkage signals were observed
in a few samples but have generally been widely repli-
cated. However, the cosegregation of a known
microdeletion in the region with a phenotype in which
psychosis is a common feature added significantly to
interest in this region. Velo-cardio-facial syndrome
(VCFS) is caused by two overlapping, recurrent dele-
tions at 22q11. Historically, about 10% of VCFS patients
were thought to present with a psychotic phenotype, but
more recent studies suggest much higher rates of 25%
to 29%.42,43Conversely, preliminary results suggest that
about 2% of adult onset and 6% of childhood onset
schizophrenic patients have microdeletions in this
region, in excess of the estimated general population fre-
quency of such deletions of 0.025%.44Interest in this
region has been further increased recently by studies
assessing structural variation (see below). The gene for
catechol-O-methyl transferase (COMT), involved in the
degradation of catecholamines, maps to this region; the
enzyme is functionally polymorphic with a variable
amino acid, Val158Met, affecting activity. Although
widely studied, the results from genetic studies of
COMT are inconclusive as reviewed recently.45
Chromosome 8p22-p21, NRG1, and ERBB4
Studies of pedigrees from numerous different ethnic
backgrounds have detected linkage to schizophrenia on
8p, as did a statistically robust meta-analysis.46Although
numerous samples support a locus on 8p, comparison
between individual studies is consistent with the pres-
ence of multiple susceptibility genes, a feature of a num-
ber of linkage regions. Almost certainly the most impor-
tant result on 8p so far is the widely replicated
association with the neuregulin 1 (NRG1) gene in fami-
S t a t e o f t h e a r t
lies and case/controls from Iceland.47NRG1 is a large
gene with multiple transcripts yielding distinct protein
molecules. It is expressed at central nervous system
synapses and is involved in the expression and activation
of neurotransmitter (including glutamate) receptors.
Initial replication studies48,49detected association on hap-
lotypes identical or closely related to those identified in
the Icelandic cases; 13 additional studies in multiple pop-
ulations reported association with more variation in
associated alleles or haplotypes,50-62while nine studies did
not.63-71A meta-analysis of studies of NRG1 supported
involvement of the gene in schizophrenia liability, but
did not provide evidence supporting association of the
most prominent marker in the original studies.72In a pat-
tern observed for a number of the best supported schiz-
ophrenia genes, several studies have also shown associ-
ation between NRG1 and bipolar disorder.62,73,74
ErbB4, encoded by the ERBB4 gene, is a receptor for
NRG1 and has important roles in neurodevelopment
and the modulation of NMDA receptor functioning.
Both activation of ErbB4 and suppression of NMDA
receptor activation by NRG1 are increased in the pre-
frontal cortex in individuals with schizophrenia com-
pared with controls.75This functional relationship
prompted genetic study of ERBB4, which demonstrated
association in ERBB4 and evidence of interaction with
NRG1.59,76-78Associated alleles in ERBB4 alter splice-
variant expression79and both NRG1 and ErbB4 protein
are increased in the brain in schizophrenia. These results
may be of particular importance as there is a biologically
plausible mechanism for gene x gene interactions, and
even if the interaction is not confirmed, both genes
impact the glutamatergic system (supporting the widely
held view that part of the complexity may be explained
by effects at the level of the pathway or system).
Important tests of both interaction and system effects
unbiased by candidate selection will be undertaken in
the current GWAS datasets.
Chromosome 6p24-p22, DTNBP1, and the
Chromosome 6 has a long history in genetic studies of
schizophrenia with major shifts in the apparent impor-
tance of particular results. Early linkage studies observed
evidence of linkage in human leukocyte antigen (HLA)
genes in the major histocompatibility complex (MHC)
region on chromosome 6p21.3-22.1, but the limited
genome coverage (only ~6%) and lack of replication
reduced the apparent importance of these findings. The
first strong evidence for linkage of schizophrenia to the
6p region came from studies of Irish families with a high
density of disease.80This study was also important
because it addressed the question of diagnostic bound-
aries in some detail. Evidence for linkage was modest
under a narrow diagnostic model, increased substantially
as the diagnostic definition broadened to include psy-
chosis spectrum disorders, and fell when the definition
was broadened further to include nonspectrum disor-
ders, in keeping with observed risks in relatives for these
traits. Multiple independent studies of this region of 6p
observed evidence for linkage, as did a multicenter col-
laborative study81and a robust meta-analysis.46
The dystrobrevin binding protein 1 or dysbindin
(DTNBP1) gene was first reported to be associated in
the same Irish families.82,83Many studies support associ-
ation in DTNBP1 in samples from diverse ethnic back-
grounds although the markers, alleles and haplotypes
associated vary significantly from study to study: 13 stud-
ies of 15 independent samples reported significant pos-
itive association with schizophrenia (most consistently
with common alleles and the highest frequency common
allele haplotype),70,82-93while 14 studies of 18 independent
samples did not.61,63,85,94-104A further four studies have also
provided positive evidence for association of DTNBP1
with bipolar disorder.105-108Although the function of
DTNBP1 in brain is unknown, both RNA109and pro-
tein110expression is reduced in cases.
Chromosome 1q and DISC1
Interest in chromosome 1 in schizophrenia began with
reports of a balanced 1:11 translocation segregating with
serious mental illness in a large pedigree from
Scotland.111The chromosome 1 breakpoint lies at 1q42.1,
and the breakpoint directly disrupts a novel gene,
Disrupted in Schizophrenia 1 (DISC1).112There are now
nine positive reports of association of DISC1 with schiz-
ophrenia74,113-120and 2 of association with positive symp-
toms121,122suggesting that this gene influences schizo-
phrenia liability in the general population, as well as in
the family with the chromosomal anomaly. Other rare
variants in this gene besides the breakpoint have also
been reported to be associated with schizophrenia123,124
and association has been reported for additional psy-
chiatric diagnoses, reviewed in ref 125, and for bipolar
Nature and nurture in neuropsychiatric genetics - Dick et al Dialogues in Clinical Neuroscience - Vol 12 .No. 1 .2010
disorder.126A smaller number of negative reports have
also been published.103,127-130
Other chromosomal regions and genes
Two additional chromosome regions, 5q22-q31, where
association was recently reported in the interleukin-3
(IL3) gene131and 15q13-q14, where evidence for linkage
of an evoked potential abnormality common in
patients132was supported by five additional studies
reporting linkage of schizophrenia to the same narrow
region,133-137show some overlap with the results of cur-
rent studies discussed below. Other high-profile candi-
date genes such as PRODH2 on 22q138and PPP3CC on
8p139have not replicated well. One exception is AKT1,140
which has similar numbers of positive141-145and nega-
Genome-wide association studies
By assaying 500 000 to 1 000 000 DNA variants in a sin-
gle experiment, GWAS provide unbiased genome-wide
coverage, avoiding selection of candidate genes. They use
an association framework for analysis, avoiding the
weaknesses of linkage in complex traits. They impose
stringent criteria due to the number of tests performed
(typically around P<5 x 10-8for genome-wide signifi-
cance). They hold enormous potential to move beyond
the identification of single genes (which may show small
effects and be difficult to detect individually) toward the
simultaneous identification of multiple genes through
their interactions or involvement in systems.
Seven GWAS of schizophrenia have been published to
date, four of which were small and underpowered. The
first (320 cases, 325 controls) was of limited density as it
genotyped only 25 000 SNPs in 14 000 known genes, and
did not detect any association that reached genome-wide
significance150; nominal association was reported in the
plexin A2 (PLXNA2) gene. Only one of four samples
tested in three independent studies replicates the asso-
ciation.151-153The second (extremely underpowered with
178 cases, 144 controls) identified one genome-wide sig-
nificant association in the X/Y pseudoautosomal region
(a homologous region of the sex chromosomes where
recombination can occur), near the interleukin 3 recep-
tor (IL3R) gene.154Cytokines have been suggested as
possible candidates previously and IL3 (in the 5q link-
age region) was associated with schizophrenia in one
study.131One replication attempt supported association
in IL3R.155The third, using the CATIE156sample (738
cases, 733 controls), did not detect any genome-wide sig-
nificant results in its primary analysis.157The fourth, using
a multistage design of discovery (479 cases, 2937 con-
trols) and targeted replication (6666 cases, 9897 controls)
samples, identified one genome-wide significant SNP in
the zinc-finger protein transcription factor ZNF804A
gene,158but only in the meta-analysis including the orig-
inal sample. One independent replication attempt sup-
ported the association of ZNF804A, and showed that
expression was increased from the associated haplo-
Three substantially larger GWAS of schizophrenia were
published in 2009, in the SGENE+ sample160(multiple
European sites, 2663 cases/13498 controls), the
International Schizophrenia Consortium (ISC) sample161
(multiple European sites, 3322 cases/3587 controls) and
the Molecular Genetics of Schizophrenia (MGS) sam-
ple162(multiple US sites, European ancestry: 2681
cases/2653 controls; African ancestry: 1286 cases/973
controls), analyzed both separately and together. The
one region of the genome with significant overlap in sig-
nals from the 3 studies was the MHC region on chro-
mosome 6p21.3-p22.1, site of some of the earliest genetic
evidence in schizophrenia discussed above. The
SGENE+ sample detected significant association with
several markers spanning the MHC region, as well as
signals upstream of the neurogranin (NRGN) gene on
11q24.2 and in intron four of the transcription factor 4
(TCF4) gene on 18q21.2. The ISC sample detected asso-
ciation in ~450 SNPs spanning the MHC region and the
myosin XVIIIB (MYO18B) gene on 22q and supported
ZNF804A. The MGS sample did not detect any individ-
ual genome-wide significant signals, but detected signals
in the range of 10-5-10-7in the CENTG2 gene (reported
deleted in autism cases163) on chromosome 2q37.2 and
JARID2 (the gene adjacent to DTNBP1) in European-
ancestry subjects, and in ERBB4 and NRG1 in African-
Meta-analysis of data from all European-ancestry MGS,
ISC and SGENE samples detected genome-wide signif-
icant association signals for 7 SNPs spanning 209 Kb of
the MHC region. LD is high between the 7 SNPs and
extends over a region of 1.5 Mb on chromosome 6p22.1,
making it difficult to determine if the signal is driven by
one or many genes. The genic content of this region is not
limited to histocompatibility loci, and also includes genes
S t a t e o f t h e a r t
involved in transcriptional regulation, DNA repair, chro-
matin structure, G-protein-coupled-receptor signaling
and the nuclear pore complex.
Meta-analyses of schizophrenia linkage and
The strongest linkage meta-analysis approach ranks 30 cM
bins of the genome from most positive to least positive for
each study, and then sums the ranks for each bin.
Significance levels are calculated by simulation, and this
method can identify regions of the genome where modest
positive results occur across many studies. Results of this
approach supported linkage to chromosomes 6p and 8p
among the previously identified regions discussed above.46
The strongest evidence for a potential locus was on chro-
mosome 2p11.1-q21.1, a region suggested by only a few
studies and not widely followed up, and on 3p, the site of
an early linkage finding that could never be replicated.
A recent effort has been made to systematize the collec-
tion and archiving of association data from studies of schiz-
ophrenia, and to provide a framework for continuous
updating of both the data and the meta-analytic results164
in the SzGene database (http://www.szgene.org/). Meta-
analyses of the data contained in this resource provided
support of varying degrees for 24 SNPs in 16 previously
reported genes, including older candidate genes (eg,
dopamine receptor 2 (DRD2) gene, those resulting from
association-based follow-up of linkage data (eg, DTNBP1)
and one suggested by one of the smaller GWAS
(PLXNA2). Meta-analyses of schizophrenia GWAS data
from at least 15 000 cases and 15 000 controls are sched-
uled for completion in 2010.
Rare structural variation in schizophrenia
The epidemiological and genetic data above seems most
consistent with the common disease/common variant
hypothesis of the genetic risks for complex traits and the
results of GWAS in other complex traits like type 2 dia-
betes provided a major validation of this model.165-168The
alternative common disease/rare variant hypothesis of
genetic risks for complex traits has been proposed in
schizophrenia,169largely based on the reduction in fertil-
ity observed in cases. A key focus of research in this area
has been the deletions, duplications, and inversions of a
few thousand (Kb) to a few million (Mb) base pairs col-
lectively known as structural variants, an area of intense
research interest generally since 2004,170-172reviewed in
ref 173. As a class, these genomic rearrangements are
common: ~360 Mb or 12% of the genome is included in
structural variation.174A few such variants occur at high
frequency due to apparent selection in certain con-
texts,175,176but studies of large samples consistently show
that the majority of structural variants are rare (~50%
detected in only one individual).174
The aggregate rate of such rare structural variants is sig-
nificantly increased in individuals with schizophrenia in
all four studies that have examined this question.177-180
Critically, there is substantial overlap in the regions
where excess structural variation is observed, most
notably on chromosomes 22q11, 15q13.3 and 1q21.1,
with some evidence that neurodevelopmental genes are
overrepresented, as in181and more recently on 16p11.2.182
However, even considered in aggregate, structural vari-
ants are observed in only 15% of schizophrenia cases,
and so cannot account for a substantial fraction of the
total population risk. Because they are rare, the true
impact of individual structural variants on schizophre-
nia is difficult to validate and interpret, although the
replication of excess structural variation in cases on
chromosomes 22q11, 15q13.3, and 1q21.1 is extremely
Summary of current gene-finding studies
At both the technical/molecular and statistical/concep-
tual levels, the science of gene discovery in complex dis-
ease genetics is moving rapidly. By the time this paper is
published, new developments are sure to have arisen. As
is common in science in the state of rapid flux, the direc-
tion ahead is far from clear. How will the modest but
hard-fought advances obtained in more traditional posi-
tional cloning and candidate gene work integrate with
the new findings from GWAS? How will the common-
variant SNP-based approach inter-relate with the emerg-
ing rare-variant copy number variant findings? Will
advances in phenotypic assessment or endophenotypes
provide critical new insights? How will the burgeoning
fields of bioinformatics, expression arrays, and pro-
teomics impact on our gene-finding efforts?
One emerging consensus is that the field needs to move
from a “gene-centric” approach toward one that consid-
ers “gene networks.” For example, many of the candidate
genes discussed above are involved in glutamatergic
neurotransmission, which may be an important systemic
Nature and nurture in neuropsychiatric genetics - Dick et al Dialogues in Clinical Neuroscience - Vol 12 .No. 1 .2010
element in the etiology of schizophrenia. Although a
detailed discussion of this theory is outside the scope of
this summary, recent reviews of the genetic183and neu-
roscience184data and evidence from other studies high-
light the positions of the gene products of NRG1,
COMT, and possibly DTNBP1 among others, in the bio-
chemical and functional pathways influencing the gluta-
matergic system. Many other possible networks may be
involved in the etiology of schizophrenia that, if prop-
erly articulated, could aid in our gene-discovery efforts.
We have attempted in this article to review the rapidly
evolving field of psychiatric genetics. In the section on
genetic epidemiology, we took a conceptual approach
focusing on a range of the most interesting questions
now being confronted by the field, with the goal of giv-
ing the reader a “feel” for the issues. While examining
a wide range of disorders, we focused on substance use
and externalizing disorders because they clearly illus-
trated the points we wanted to make. In the section on
gene-finding, we decided it would be more useful to
“drill down” and illustrate our important themes by
focusing on one disorder—schizophrenia.
The major theme that cuts across these two sections is
the complexity of the pathways from genetic variation
to psychiatric and substance use disorders. Results of the
last 20 years have shown that the early prior simple
hypothesis of large effect genes that directly causes psy-
chiatric illness was seriously misplaced. We now know
that multiple gene variants (as well as—for at least some
disorders—genomic rearrangements) are involved at the
DNA level. These genetic risk factors then act and inter-
act with each other and with the environment in a com-
plex developmental “dance” to produce individuals at
high versus low risk of illness. It is this kind of complex-
ity that the field is now confronting directly.
As one might hope, progress is being made in multiple
ways. The field that is moving downward—in a reduction-
ist sense—to more detailed biological mechanisms at the
DNA, RNA, and protein levels. These efforts are being dri-
ven by rapid technological advances. However, we are
straining to develop the conceptual and analytic tools to
keep pace with the information generated by these new
generation technologies. At the same time, the field is mov-
ing out into the environment to clarify the often critical
inter-relationship between these two broad classes of risk
factors. Equally importantly, it is moving “forward” in
emphasizing the importance of time and development.
This can all be confusing and sometimes a bit overwhelm-
ing. In a desire to simplify, some, in the “glow” of the new
biological tools now available, have devalued the genetic
epidemiologic approaches. These approaches, they suggest,
focus on “statistics” but not “real genes.” However, knowl-
edge gained from genetic epidemiology, in addition to pro-
vide a guiding light for molecular approaches, also have
their own inherent validity. Studying aggregate genetic risk
factors allows us to build etiologic models that can inform
prevention efforts, aid policy makers in planning for
research programs, and provide critical input into revisions
of psychiatric nosology.
We would like to close by emphasizing that knowledge
about the role of genetic factors in the etiology of psy-
chiatric illness can be profitably understood from sev-
eral perspectives. The human mind/brain system—the
organ that instantiates psychiatric illness—is surely influ-
enced by processes occurring at the levels of basic mol-
ecular biology, neural systems and networks, and psy-
chological, social, and cultural processes.185A full
understanding of the processes whereby genetic risks
lead to the development of psychiatric disorders will
surely require considering all these perspectives, each of
which contributes a useful viewpoint with methodolo-
gies that have important (and different) strengths and
S t a t e o f t h e a r t
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use. Behav Genet. 2008;38:339-347.
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Nature and nurture in neuropsychiatric genetics - Dick et al Dialogues in Clinical Neuroscience - Vol 12 .No. 1 .2010
Lo innato y lo adquirido en la genética
neuropsiquiátrica: ¿dónde estamos?
Se piensa que los factores de riesgo tanto genéticos
como no genéticos, al igual que las interacciones y
correlaciones entre ellos contribuyen a la etiología
de los fenotipos psiquiátricos y conductuales. La
epidemiología genética confirma consistentemente
la participación de genes en estos defectos. Los
estudios de genética molecular han resultado
menos exitosos en la identificación de genes defec-
tuosos, pero el progreso reciente sugiere que se ha
identificado un número de genes específicos que
contribuyen al riesgo. En conjunto los resultados
son complejos e inconsistentes, al considerar una
sola variante común de ADN en algún gen que
influya en el riesgo en poblaciones humanas. Son
pocas las variantes genéticas específicas que influ-
yen en el riesgo que se han identificado en forma
inequívoca. Sin embargo, las aproximaciones actua-
les son prometedoras respecto a dilucidar más
genes y variantes defectuosas, como también sus
potenciales interrelaciones entre ellos y con el
ambiente. Se revisarán los campos de la genética
molecular y de la epidemiología genética, apor-
tando ejemplos de la literatura para ilustrar los con-
ceptos clave que surgen de este trabajo.
L’inné et l’acquis en génétique
neuropsychiatrique : où en sommes-nous ?
Des facteurs de risque génétiques et non géné-
tiques, et leurs interactions et leurs corrélations
mutuelles, participeraient à l’étiologie des phéno-
L’implication des gènes de susceptibilité est régu-
lièrement confirmée par l’épidémiologie génétique.
Des études de génétique moléculaire ont été moins
heureuses dans l’identification des gènes de sus-
ceptibilité, mais des progrès récents suggèrent que
plusieurs gènes spécifiques participant au risque ont
été identifiés. Pris collectivement, les résultats sont
complexes et contradictoires avec un variant ADN
unique présent dans un gène, influant sur le risque
à travers les populations humaines. Les variants
génétiques spécifiques influant sur le risque sont
peu nombreux à avoir été identifiés sans ambiguïté.
Les approches actuelles sont cependant très pro-
metteuses pour l’identification future des gènes de
susceptibilité et de leurs variants, de leurs interre-
lations éventuelles les uns avec les autres et avec
l’environnement. Dans cette revue, nous analyse-
rons les domaines de l’épidémiologie génétique et
de la génétique moléculaire, des exemples de la lit-
térature illustrant les idées phares de notre travail.
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