Genetics and Psychiatry

Basic Organization of the Human Genome

The human genome comprises the full sequence of deoxyribonucleic acid (DNA) found in the nucleus of each nucleated human cell (mature erythrocytes and platelets lack nuclei and thus do not contain a copy of the genome). The DNA sequence is distributed over 23 pairs of chromosomes, long strands of DNA that include the 22 autosomes and two sex chromosomes. One of each pair of the autosomes and the sex chromosomes is inherited from each parent. The autosomes are numbered 1 through 22 in order of size, and most consist of two arms divided by a region called the centromere ( Figure 63-1 ). The longer arm of a chromosome is denoted by the letter “q” and the short arm by the letter “p.” Thus, the long arm of chromosome 1 is referred to as 1q. Subdivisions of chromosomes, originally identified on the basis of chromosome staining, are referred to by numbers (e.g., 1q31.2). With the sequencing of the human genome, however, references to locations on chromosomes can now be made more precisely based on their base-pair positions (e.g., a single nucleotide polymorphism at base pair 27644225 on chromosome 11).

DNA encodes the instructions for making all of the proteins in the human body. Double-stranded DNA itself is composed of a linear sequence of the nucleotides adenine (A), cytosine (C), guanine (G), and thymine (T) (see Figure 63-1 ). The full genome sequence, comprising approximately 3 billion bases, was deciphered in 2001. Genes convey the instruction for protein sequence through messenger ribonucleic acid (mRNA), which is transcribed from the gene sequence and, ultimately, translated into the amino acid sequence of a given protein ( Figure 63-2 ). The human genome contains approximately 20,700 protein-coding genes. Protein-coding genes include protein-coding sequences (exons), intervening sequences (introns), and untranscribed regions (e.g., regulatory promoter sequences). These genes are often alternatively spliced, a process during which different combinations of exons of a gene are spliced together, resulting in different mRNAs that can potentially encode multiple protein variants from one gene. Each gene has, on average, approximately six alternatively spliced transcripts. Exons of protein-coding genes cover 2.9% of the genome. The protein-coding genes, from their start to their stop codon, including exons and introns, cover 33% of the genome. Genomic sequence outside of protein-coding exons contains regulatory units that control gene expression in the different cell types in the body. The large ENCODE project recently calculated that 80% of the genome has a biochemical function, including functioning as enhancers or encoding RNA species that can regulate gene expression. A significant subset of genetic mutations and variants associated with psychiatric disorders are located outside the protein-coding exons. These mutations outside of protein-coding exons may disrupt the biochemical function of that genomic locus, including the proper regulation of gene expression.

Genetic Variation and Polymorphism

Although the majority of the genomic sequence is shared identically by all humans, important variations (polymorphisms) exist across populations and individuals. Some of this variation has no effect on observable traits, while other variations influence phenotypic differences among people. A variant form of DNA sequence at a particular locus (genomic position) is referred to as an allele. Because all nucleated human cells (with the exception of the gametes) are diploid, carrying two copies of each autosome, a given allele can occur on one or both copies of a genetic locus. Variants are often described in terms of the major (more common) allele and the minor (less common) allele. Polymorphisms in which the minor allele frequency is 1% or less are referred to as mutations. Several common forms of genetic variation relevant to neuropsychiatric phenotypes are discussed below.

Microsatellites and variable number tandem repeats (VNTRs) are common forms of genetic variation involving short repeated sequences ( Figure 63-3 ). Microsatellites typically comprise repeats of two to four nucleotides (e.g., CA repeats). These repeat sequences are typically found outside of the amino acid coding sequences, but their high degree of polymorphism has made them useful as genetic markers in genetic linkage studies. In some cases, short repeats do have functional effects.

Variable numbers of repeated three base-pair sequences, known as triplet repeats, have been shown to play a role in several neurological illnesses. For example, CAG repeats (which encode the amino acid glutamine) within the Huntingtin gene on chromosome 4 cause Huntington disease when more than 40 repeats are present ( Figure 63-4 ). Alleles containing fewer than 35 repeats do not produce disease, but as repeat length increases, instability in replication can lead to expansion of the repeat sequence. This accounts for the phenomenon of anticipation in which the mutation “worsens” over successive generations, resulting in earlier-onset and more severe disease phenotypes. Other diseases associated with triplet repeat expansion include fragile X, spinocerebellar ataxias, and myotonic dystrophy.

Single nucleotide polymorphisms (SNPs), in which one of the four nucleotide bases is substituted for another, are the most common form of genetic variation, occurring approximately once per 1,000 base pairs (bp) of DNA sequence. Because they are so common (more than 10 million in the genome) and may have functional significance, SNPs have become the focus of genetic association analysis, the most widespread approach to identifying susceptibility genes for complex disorders (see below). SNPs may affect phenotypic variation through several mechanisms. One straightforward mechanism results when an SNP in the exon of a gene alters or disrupts the instructions for the normal amino acid sequence of the gene product. Such “non-synonymous” coding sequence SNPs can result in an abnormal or truncated protein product with aberrant or no function. In addition, SNPs occurring in the regulatory regions of genes (e.g., the promoter) can induce phenotypic effects through alterations in gene expression.

Recently, the widespread occurrence of copy number variation in the genome has been reported. These variations include deletions, insertions, and duplications of DNA sequence, ranging from kilobases (thousands of bases) to megabases (millions) in length, that may alter gene function or the amount of gene expression. The extent and frequency of copy number variants and their relationship to complex disease is an area of active research. Examples of copy number variation relevant to psychiatry include the 22q11 microdeletion that causes velocardiofacial/DiGeorge syndrome and is associated with psychotic illness and the duplication of15q11-13 with autism. There is a higher rate of de novo copy number variants (present in the offspring but not the parents) in autism and schizophrenia as compared to controls.

Linkage Disequilibrium and Haplotypes

The phenomenon of linkage disequilibrium (LD) is an important characteristic of the human genome. LD refers to the correlation or association of alleles at linked polymorphic markers. A key feature of the structure of the human genome is that it is organized into regions of high LD separated by regions of low LD. Markers that exhibit high levels of LD and that reside on the same chromosome (i.e., markers whose alleles are strongly correlated) are referred to as haplotypes. Put another way, a haplotype refers to a set of strongly associated alleles at markers along a chromosomal region that tend to be inherited together. LD arises when a new variant occurs on a chromosome (e.g., through mutation). The chromosome on which the variant arises is surrounded by other alleles and so it is inherited along with those alleles in the subsequent generation. Over successive generations, recombination of chromosomes and other mutations at neighboring sites dilute the degree of correlation between the new variant allele and surrounding alleles, degrading the extent of LD between them. However, human populations are relatively young so that stretches of LD have persisted. In regions of high LD, there is limited haplotype diversity—that is, only a few haplotypes exist in the population in these regions. A major advance in cataloguing genetic variation and LD across the human genome was accomplished by the International HapMap Project. A crucial dividend of the HapMap was to facilitate genome-wide association studies (described below).

Gene Expression

Gene expression refers to the process and products of gene transcription into RNA and, if applicable, translation into protein (see Figure 63-2 ). The regulation of gene expression involves both genetic and epigenetic factors. Genetic influences on expression include DNA sequences in regions around genes known as promoters and enhancers. These regulatory regions function in part by serving as binding sites for transcription factors that help determine where (in what tissues) or when (during which developmental periods) genes are activated or silenced. Sequence variations in regulatory regions provide another mechanism (beyond variations in protein-coding regions of genes) by which DNA sequence differences contribute to phenotypic differences among individuals and populations.

Another important mechanism for modulation of gene expression involves epigenetic regulation. Epigenetics refers to the study of heritable gene expression changes that are not due to variation in DNA sequence. Chromatin, the complex of DNA, histones, and associated non-histone proteins, is the primary substrate of epigenetic modulation. Histones are highly basic proteins found in the nucleus of the cell; chromatin consists primarily of DNA molecules wrapped around octomeric complexes of histones. The configuration of chromatin can vary from states in which it is inactivated and condensed (also known as heterochromatin) or activated and open (also known as euchromatin). Genes in regions of condensed chromatin are inaccessible to transcription factors and thus functionally repressed, while those in regions of open chromatin are available to transcriptional activation. Shifts in chromatin structure (chromatin re-modeling) may thus lead to important variations in gene expression with downstream effects on a variety of phenotypes. The chemical and molecular bases of chromatin re-modeling and epigenetic modification of gene expression include histone acetylation (which generally increases transcriptional activity), histone methylation (which can increase or decrease transcriptional activity), and DNA methylation (which generally reduces transcriptional activity). A variety of factors appear to influence epigenetic modification of chromatin and DNA, including aging, stress, diet, and various drugs and medications. Indeed, modification of the epigenome may be a central mechanism by which environmental influences are transduced into molecular effects on gene expression and action.

A number of neuropsychiatric disorders and phenotypes have been linked to epigenetic variations, including Rett syndrome (an autism spectrum disorder caused by mutations in the transcriptional repressor MECP2 that encodes a methylated-DNA-binding protein), depression, schizophrenia, and addiction.

Finally, gene expression can also be regulated by RNA interference (RNAi) due to non-coding RNAs, including short-interfering RNA (siRNA), microRNA (miRNA), and small hairpin RNA (shRNA). These RNAs can modulate gene expression by several mechanisms, including degrading mRNAs of target genes or interfering with translation of mRNA into proteins. The role of these factors in human disease is an area of active investigation.

The Complex Genetic Architecture of Psychiatric Disorders

The underlying genetic basis of psychiatric disorders is diverse and complex. Neuropsychiatric disorders may arise from mutation in one gene, variations in multiple genes that together lead to the disorder, or mutations in non-protein-coding regions of the genome. A subset of psychiatric disorders has mutations in a single gene that is highly penetrant (i.e., the risk of illness in those carrying the genetic liability is high). Mutations in a single gene that causes disease with high penetrance may have classical Mendelian patterns of inheritance, including dominant, recessive, or X-linked. Dominant inheritance occurs when variations in a single copy of the relevant gene are sufficient to cause disease. In recessive inheritance, mutations in both copies of a gene, on each allele, are needed to lead to disease. In X-linked inheritance, a gene on the X-chromosome is mutated. Male offspring inherit one copy of the X-chromosome, whereas female offspring inherit two copies of the X-chromosome, one of which is inactivated in cells.

Psychiatric disorders can arise from copy number variants (CNVs). CNVs include deletions, insertions, duplications, and inversions of regions of the genome. Some of these CNVs are rare mutations in the population. There is an increased number of rare CNVs in individuals with autism and schizophrenia as compared to controls.

Another subset of psychiatric disorders arise from de novo mutations. A de novo mutation is found in the individual or recent ancestry. For example, a de novo mutation can be found in the offspring but not in the parents. The mutation may have occurred in the sperm of the father. Increasing age of the father is a risk for autism, which may be due to increased number of mutations in the sperm of older fathers, leading to de novo mutations in the offspring that cause autism. Some CNVs are de novo alterations in the genome. In schizophrenia, there is an excess rate of de novo CNVs.

While some psychiatric disorders are caused by rare mutations, including rare CNVs, another subset of psychiatric disorders seem to be caused by the combination of alterations in many genes. In this scenario, each gene variation contributes a small effect that, on its own, would not lead to the disorder. Only the combination of these variations in multiple genes leads to the expression of the psychiatric disorder. This hypothesis of the genetic basis of a subset of psychiatric disorders has been called the common variant, common disease model. Genome-wide association studies (GWAS), described below, can help identify these common genetic variations that can contribute to the development of a psychiatric disorder in combination with multiple other genetic variations. These multiple common variants associated with psychiatric disorders may function in convergent molecular pathways. For instance, multiple genes associated with autism spectrum disorders encode proteins that regulate synapses, the connections between neurons.

At times, the underlying genetic basis crosses diagnostic boundaries defined from clinical experience. In a phenomenon named pleoitropy, a particular gene, or genetic loci, may increase the risk for developing multiple different psychiatric disorders. Twin and family studies have provided evidence for genetic overlap between disorders. Using data from GWAS, variations in the calcium channel, voltage-dependent, L-type, alpha 1C subunit (CACNA1C) is associated with both bipolar disorder and schizophrenia. In another example, an analysis of an extended family with a chromosomal translocation that disrupts DISC1 , this mutation is associated with multiple mood disorders and schizophrenia.

For a subset of psychiatric disorders, environmental factors may play a key factor in whether a certain composition of genetic variations led to development of a disorder. For instance, early life stress may be an important environmental factor that contributes to the development of a psychiatric disorder in the context of certain genetic variants. One mechanism by which environmental experiences are hypothesized to contribute to the development of psychiatric disorders is by regulating gene expression in the brain through alterations in the epigenome, including by modifying methylation of DNA and post-translational modifications of histones.

Approaches to the Study of Psychiatric Genetics

The goal of psychiatric genetic research is to identify and characterize the genetic basis of psychiatric disorders. This process typically involves a series of questions about familial and genetic contributions that are addressed using several study designs. In the following sections, the rationale and methodological aspects of each of these research tools will be presented, beginning with genetic epidemiological studies and then addressing molecular genetic approaches. In recent years, the advent of powerful genetic sequencing technologies has transformed the study of psychiatric genetics. These new technologies include GWAS, genome-wide studies of copy number variants, and whole-exome sequencing.

Genetic Epidemiology

Family Studies.

Family studies address the question: Does the disorder run in families? A disorder that runs in families may indicate a genetic etiology. However, a disorder may run in families for non-genetic reasons, including shared environmental factors. Alternatively, a disorder may not run in families and still have a genetic etiology; an important subset of psychiatric disorders seems to be caused by de novo genetic mutations in which genetic mutations that lead to the disorder can be found in the offspring but not the parents.

The design of a typical family study is similar to other case-control studies. Cases (affected probands) and controls (unaffected probands) are ascertained and the lifetime prevalence of the disorder is measured among their (usually first-degree) relatives. A higher prevalence among relatives of affected probands is evidence that the disorder aggregates in families. The risk to relatives of affected probands is referred to as the “recurrence risk.” One index of the strength of familiality is the “recurrence risk ratio” for first-degree relatives (λ ₁ ), defined as the ratio of the risk of the disorder in a first-degree relative of an affected individual to the prevalence in the general population. It is important to bear in mind that the size of these risk ratios depends on both the risk to relatives (numerator) and the base rate of the disorder (denominator). Even when the relative risk of a disorder is high, the absolute risk to a first-degree relative may be relatively low if the base rate of the disorder is low. For example, siblings of probands with schizophrenia have a roughly 10-fold increased risk of the disorder compared to an individual randomly drawn from the general population (λ ₁ ≈ 10). However, because the population prevalence is approximately 1%, the absolute risk of the disorder for the sibling is only about 10% (with a 90% probability of being unaffected). In contrast, the lifetime prevalence of major depression is approximately 15%, so that even a two-fold increased risk to siblings would be associated with a 30% risk of being affected. Family studies can also provide information about the etiological boundaries or relatedness of different traits or diagnoses. For example, relatives of probands with Tourette syndrome have an elevated risk of obsessive-compulsive disorder (OCD), suggesting that these conditions have overlapping familial determinants ( Table 63-1 ).

TABLE 63-1

Genetic Epidemiology of Some Psychiatric Disorders

Disorder	λ 1 *	Estimated Concordance Rates		Estimated Heritability (Approximate)	Selected Genetic Findings †
		MZ	DZ
ADHD	2–8	51%–58%	31%–33%	75%	rare CNVs, GRM1 , GRM5 , GRM7 , GRM8
Autism	50–100	40%–90%	0%–30%	60%–90%	rare CNVs de novo CNVs, NRXN1 , NLGN3 , NLGN3 , NRXN1 , SHANK2 , SHANK3 , CNTNAP2 , MECP2 , CHD8
Alzheimer's disease (late onset)	2	21%	11%	60%	Early onset: presenilin-1, presenilin-2, amyloid precursor protein Late onset: ApoE (ε4), SORL1
Schizophrenia	10	46%	14%	70%–89%	rare CNVs de novo CNVs, TCF4 , NRGN , ZNF804A , microRNA MIR137
Bipolar disorder	7–10	40%–45%	5%	60%–85%	CACNA1C, ANK3, NCAN
Major depressive disorder	3	23%–49%	16%–42%	40%	limited rigorous findings; gene–environment interactions may be key
Panic disorder	5–7	24%	11%	45%	limited rigorous findings
Phobic disorders	4	13%–26%	4%–12%	10%–39%	limited rigorous findings
Obsessive-compulsive disorder	4	Limited data	Limited data	30%–45%	SAPAP3, SLC1A1
Alcohol dependence	2–4	50%–58%	32%–50%	35%–60%	Alleles of ADH and ADLH GABRA2 ,

* λ ₁ , recurrence risk ratio for first-degree relatives: the risk of the disorder in a first-degree relative of an affected individual compared with the general population prevalence of the disorder.

† Rigorous genetic linkages and associations are beginning to be identified. Much of the genetic basis for these disorders remains not well understood.

Methodological issues can influence the interpretability of family studies. Studies using the “family history method” rely on informant reports to assign diagnoses (e.g., probands may be interviewed about their relatives). Because this method can be less sensitive than direct interview methods for detecting psychopathology in relatives, the latter are considered the gold standard. The “family study method” involves direct assessment of probands and relatives, although informant reports may be incorporated to derive “best-estimate” diagnoses using all available data.

Twin Studies.

The observation that a trait aggregates in families does not, in itself, establish that genes influence the phenotype. Traits and disorders may run in families for non-genetic reasons. For example, shared environmental experiences may produce the disorder in multiple family members. Twin and adoption studies can be used to assess, to a degree, the contribution of genetic and environmental causes of familial aggregation.

Twin studies compare concordance rates between monozygotic (MZ) twins (who are genetically identical) and dizygotic (DZ) twins (who share on average 50% of their alleles). A twin pair is concordant if both co-twins have the phenotype. If we can assume that environmental influences on MZ twins are not different from environmental influences on DZ twins (the “equal environments assumption”), then significantly higher concordance rates in MZ twins reflect the action of genes. Nevertheless, an MZ concordance rate that is less than 100% suggests that environmental factors influence the phenotype. Twin studies can provide an estimate of the heritability of the disorder, which refers to the proportion of the phenotypic differences among individuals in a population that can be attributed to genetic factors. The total variance in phenotypes ( V _P ) in a population can be decomposed to a genetic component ( V _G ) and an environmental component ( V _E ): that is, V _P = V _G + V _E . Thus, the heritability is the proportion of the total variance represented by the genetic variance: ( V _G /V _P ).

For quantitative traits, heritability can be estimated as 2( r _MZ − r _DZ ) where r _MZ refers to the co-twin phenotypic correlation for MZ twins and r _DZ refers to the correlation for DZ twins. For categorical traits (such as diagnosis), the concordance rate can be substituted for these correlations to obtain a rough estimate of heritability. Several caveats are important to note regarding the interpretation of heritability estimates.

• Heritability refers to the strength of genetic influences in a population , not a particular individual, and heritability estimates may differ depending on the population studied. A heritability of 60% says nothing about the contribution of genes to an individual's risk of a phenotype.

• Heritability refers to the additive sum of all genetic influences on a trait in a population. Thus, a heritability of 0.80 (80%) suggests that genes contribute more to trait variance in the population than does a heritability of 40%. However, heritability provides no information regarding how many genes are involved, how strong the effect of any given gene is, or how easy it will be to identify contributing genes. The number and effect of genetic influences on a trait is sometimes referred to as the “genetic architecture.”

• The magnitude of heritability is not a strong predictor of the potential impact of environmental interventions. A classic illustration is the case of phenylketonuria (PKU), a recessively-inherited disorder due to a mutation in the gene-encoding phenylalanine hydroxylase that results in a toxic accumulation of phenylalanine. Untreated, PKU can result in progressive brain damage with seizures and intellectual disability. However, these devastating outcomes can be minimized by entirely environmental interventions: avoidance of dietary phenylalanine and supplementation with tyrosine.

Adoption Studies.

Adoption studies can disentangle, to a degree, genetic and environmental influences on family resemblance by comparing rates of a disorder in biological family members with those in adoptive family members. For example, if an adopted child has a genetically-influenced disorder, the biological (genetic) parents should have a higher risk of the disorder than the adoptive (environmental) parents. Adoption studies provided the first convincing evidence that genes play an important role in the development of schizophrenia.

Linkage Analysis.

Linkage studies address the question of where in the genome (i.e., in which chromosomal region) a disease mutation or susceptibility locus may reside. Linkage analysis examines the degree to which alleles at two or more genetic loci are co-inherited (co-segregate) within families (thus deviating from Mendel's law of independent assortment of loci). The likelihood that two loci on a chromosome will co-segregate is inversely proportional to the distance between them. This principle is due to the phenomenon of recombination between homologous chromosomes that occurs during gamete formation (meiosis). During meiosis, the two members of each chromosomal pair (comprising a maternal and a paternal chromosome) align and undergo crossovers that result in an exchange of chromosomal segments (recombination). The closer two loci are on a chromosome, the less likely it is that they will be separated by a recombination event.

If individuals affected by a disorder within a family tend to inherit the same alleles at a marker locus, this implies that the marker locus is linked to (i.e., is physically close to) a gene that influences the disorder. In classical (parametric) linkage analysis, the strength of the evidence in favor of linkage is calculated as a logarithm of the odds (LOD) score. The LOD score compares the likelihood of obtaining the observed genotypes and phenotypes when linkage is present with the likelihood assuming no linkage. For classic single gene (Mendelian) disorders, a LOD score of 3 (corresponding to odds of 1,000 : 1 in favor of linkage) has been the threshold for declaring linkage; for complex disorders, such as psychiatric illnesses, higher thresholds (3.3 : 4.0) have been recommended. Traditional LOD score linkage analysis requires that a model including several parameters (mode of inheritance, disease allele frequencies, and marker allele frequencies) be specified. Thus, linkage analysis has been most successfully applied when a single major gene is involved and the mode of inheritance (e.g., dominant, recessive) is known.

The degree of genetic linkage reflects the proximity of two loci and depends on the frequency of recombination between them. The distance between two loci can be expressed as a genetic distance (in centimorgans) or a physical distance (in base pairs). Loci that are separated by recombination in 1% of meioses are 1 centimorgan (cM) apart; this corresponds roughly to a physical distance of 1 million base pairs.

Even in the case of Mendelian inheritance, linkage analysis can be complicated by several phenomena that can attenuate the direct relationship between genotype and phenotype. It may be difficult to accurately classify whether an individual is affected with the disease genotype because there may be phenocopies (individuals who have the disorder for non-genetic reasons), incomplete penetrance (individuals with the disease genotype may not manifest the phenotype), variable expression (the disease genotype may produce a spectrum of phenotypes), and genetic heterogeneity (different genes may independently produce the phenotype). All of these complicating factors are likely to apply to psychiatric phenotypes and reduce the power of linkage analysis in this setting.

Association Analysis.

Whereas linkage analysis examines the co-inheritance of alleles and phenotypes within families, association analysis examines the co-inheritance of alleles and phenotypes across families (i.e., across a population of unrelated individuals) ( Figure 63-5 ). While linkage analysis asks “where” a susceptibility gene resides, association analysis asks “which” specific genetic variants influence a phenotype. In recent years, association methods have increasingly replaced linkage methods for the study of complex diseases. This is because association methods are more powerful than linkage analysis for detecting small genetic effects. However, association between variants operates over much shorter genomic distances, so that much denser sets of genetic markers are needed.

The most common type of association study of complex traits is conceptually very similar to standard case-control epidemiological studies in which the frequency of a risk factor (e.g., smoking) is compared between cases (e.g., individuals with coronary artery disease) and unaffected controls. In the genetic context, the risk factor is an allele (or haplotype). Association is declared if the allele is significantly more common among cases than controls. However, this simple design is complicated by a number of factors.

Statistical evidence of association can result from the following: (a) direct association between a causal variant and disease; (b) indirect association between disease and a genetic variant that is in LD with the true causal variant; (c) confounded association due to population stratification (in which cases and controls differ in their population genetic backgrounds); or (d) spurious association due to chance (as often occurs due to multiple testing or the testing of variants that have low prior probability of association).

Candidate Gene Studies

Until recently, association studies have focused exclusively on candidate genes —that is, genes hypothesized to influence a phenotype of interest based on prior evidence. In general, two classes of candidates have been studied: biological candidates (selected based on prior evidence that the gene or pathway is involved in the biology or treatment of a disorder) and positional candidates (selected based on evidence from linkage or cytogenetic studies that a genomic region harbors susceptibility genes). In psychiatric genetics, common biological candidate genes have included those involved in monoaminergic neurotransmission (e.g., transporters, receptors, and enzymes involved in the metabolism of serotonin, dopamine, and norepinephrine [noradrenaline]).

While some candidate genes have shown evidence of association in multiple studies, findings have generally been inconsistent and non-replications are common. Candidate gene studies have commonly been underpowered. It is increasingly clear that very large sample sizes (on the order of thousands of cases and controls) are needed to detect the small effects that genes underlying complex traits are likely to exert. Thus, negative findings can be uninformative if power is inadequate.

Genome-Wide Association Studies

In recent years, advances in high-throughput genotyping technologies coupled with the extensive cataloguing of genetic variation, including SNPs, through the International HapMap Project and the 1000 Genomes Project have made genome-wide association analysis possible. These studies make use of the fact that there is extensive LD across the genome so that the alleles of many SNPs are strongly correlated. Such genotyping technology has been used to identify genes influencing common, complex disorders including psychiatric disorders. Unlike candidate gene studies, GWAS are “unbiased” in that they do not require a pre-specified hypothesis about which genes are important; as such, they offer the opportunity to uncover novel molecules and molecular pathways in the biology of these disorders.

Because of the large number of statistical tests involved, stringent statistical measures to control false-positive rates are needed. In addition, GWAS usually examine relatively common polymorphisms, so that effects of rare susceptibility variants may be missed. However, this approach has already provided conclusive evidence implicating specific genes for a wide range of common, complex medical disorders (including diabetes, heart disease, inflammatory bowel disease, macular degeneration, multiple sclerosis, rheumatoid arthritis, and a growing list of others). In addition, GWAS have identified genetic loci associated with autism, bipolar disorder, and schizophrenia, as described later in the chapter.

Copy Number Variants

Human genomes vary not only by SNPs but also by copy number variants (CNVs). CNVs and structural variants include deletions, duplications, insertions, and inversions of regions of the genome. There are, on average, over 1,000 CNVs in the human genome. Some CNVs are common allelles, while others are rare. Rare CNVs have received significant scientific interest in recent years and have been associated with psychiatric disorders. Cytogenetic studies have documented large chromosomal abnormalities that had association with psychiatric disorders. For instance, the deletion of 22q11.2, in velocardiofacial syndrome, has been associated with schizophrenia and the duplication of 15q11-13 with autism. Genome-wide CNV studies have provided important new insight into the genetics of psychiatric disorders. For instance, there is a higher rate of de novo CNVs (5%–10%) in individuals with autism spectrum disorders as compared to unaffected controls. Rare and large (greater than 100 kb) CNVs have been associated with schizophrenia. In addition, there is a high rate of de novo CNVs in schizophrenia (5%) as compared to controls.

Whole-Exome Sequencing

Facilitated by the rapidly declining cost of DNA sequencing, another new approach to psychiatric genetics is to sequence all the exons in a genome of an individual and compare cases and controls. Whole-exome sequencing can reveal rare single nucleotide variants (point mutations) that may be associated with a disorder, including mis-sense mutations (DNA mutations that result in one amino acid, of the encoded protein, being changed), nonsense mutations (DNA mutations that result in the premature stop of the protein product), and mutations that disrupt proper alternative splicing of proteins. These point mutations can be de novo mutations, arising in the offspring and not present in the parents. Whole-exome sequencing studies of autism have been recently published. Whole-exome sequencing studies have found that de novo single nucleotide variants, particularly nonsense mutations or mutations that disrupt alternative splicing, are associated with autism. Increasing age of the father and mother has been highly correlated with increased number of de novo single nucleotide mutations, likely from mutations in the germ cells of the parents.

Gene–Environment Interaction

Genes operate in the inextricable context of environments, and the etiology of psychiatric illness is generally believed to involve additive and interactive effects of genetic susceptibility and environmental stressors. One reason for the inconsistency in genetic association findings may be that risk alleles may only have observable effects in the context of specific environmental exposures. Thus, failure to measure and incorporate environmental factors may obscure genotype–phenotype relationships. More recently, the examination of gene–environment interaction has become a major focus of research, in part because genetic association methods are well-suited to examine additive and interactive effects of multiple risk factors. Ironically, it has become a simpler matter to measure genetic variation than environmental risk factors: the genome is finite but the environment is nearly unbounded. Identifying which candidate environmental factors are relevant and capturing their longitudinal effects can be difficult. In addition, the sample sizes required are likely to be very large to achieve adequate power to examine these interactions.

Intermediate Phenotypes and Endophenotypes

With the advent of high-throughput genotyping methods and the availability of large clinical cohorts, the rate-limiting step in identifying susceptibility genes for psychiatric disorders may be uncertainty about phenotype definition. While the constellations of symptoms used as diagnostic criteria in the Diagnostic and Statistical Manual of Mental Disorders have been useful for clinical practice, it is unlikely that they are the optimal phenotype definitions for genetic analyses. With few exceptions, these criteria are based on self-reported or observable symptoms that may be distant reflections of any underlying neurobiology that is influenced by genes. This makes the study of genetics in psychiatry even more challenging than in other areas of medicine in which direct measurements of the relevant biological phenotypes (e.g., hormone levels, histopathology) are possible. Given this, there has been great interest in identifying phenotypes related to psychiatric disorders that are closer to the genetic substrate than are clinical definitions of the disorders themselves. By more directly capturing gene effects, such “endophenotypes” or “intermediate phenotypes” could avoid the need for unfeasibly large sample sizes in genetic studies; in addition, by modeling more fundamental aspects of psychiatric illness, such phenotypes could help clarify the underlying phenotypic architecture and even inform a new nosology that would not rely exclusively on symptom checklists.

Gottesman and Gould highlighted five desirable characteristics of a putative endophenotype: it is associated with illness in the population; it is heritable; it is primarily state-independent (present even when illness is not active); it co-segregates with illness within families; and the endophenotype found in affected family members is found in non-affected relatives more frequently than in the general population.

A large number of endophenotypes and intermediate phenotypes have been proposed for psychiatric disorders, though data regarding all five criteria listed above are not available for many of these. An example of an endophenotype that appears to meet most of the criteria is inhibition of the P50 evoked response to repeated auditory stimuli, a phenotype that may underlie the abnormalities in sensory gating observed in schizophrenia. A deficit in P50 inhibition has been associated with schizophrenia and the phenotype appears to be heritable and to co-segregate with the illness in families. Linkage of impaired P50 inhibition has been linked to a locus on chromosome 15q, adjacent to the alpha-7 nicotinic receptor gene, and subsequent analyses provided evidence that variants in the promoter of this gene are associated with both P50 inhibition and schizophrenia. A recent study identifying genetic loci associated with risk of developing Alzheimer's disease performed a GWAS using the endophenotype of elevated levels of the protein tau and phosphorylated tau in the CSF, biomarkers known to be associated with Alzheimer's disease.

Neuroimaging phenotypes are attractive for genetic studies because they directly measure brain structure or function. The growing literature on imaging genetics has identified several genotype–phenotype correlations involving specific genetic variants. For example, the functional promoter polymorphism in the serotonin transporter gene ( 5HTTLPR ) has been associated with increased amygdala reactivity and reduced coupling of corticolimbic circuits, and neuroimaging phenotypes have been implicated in the biology of anxiety and depressive disorders. Other studies have implicated functional polymorphisms in catechol O -methyltransferase (COMT) and prefrontal cortical phenotypes have been thought to underlie working memory deficits and dopaminergic dysregulation in schizophrenia.

Genetic Aspects of Psychopathology

Evidence for a genetic component of many psychiatric disorders is growing, and molecular genetic studies have begun to provide evidence for variants in genes and genetic loci that lead these disorders ( Table 63-1 ). Prior to the advent of new genomic technologies, many linkage and association findings have been difficult to replicate, emphasizing the need for caution in interpreting the results of those studies. Some of these findings have undoubtedly been false positives, but non-replication can also be due to inadequate power, differences in diagnosis and phenotype definition, and genetic heterogeneity (different genes acting in different samples). In recent years, the use of new genomic technologies, with large sample sizes of sufficient statistical power, have begun to provide rigorous new insight into the genetic basis of psychiatric disorders. How variations in genes and genomic loci that have been associated with psychiatric disorders actually lead to psychopathology remains poorly understood.

Disorders of Childhood and Adolescence

Dementia