ArticlesIdentification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis
Introduction
Psychiatric nosology arose in central Europe towards the end of the 19th century, in particular with Kraepelin's foundational distinction between dementia praecox (schizophrenia) and manic depressive insanity.1 The distinction between bipolar illness and unipolar (major) depression was first proposed in the late 1950s and became increasingly widely accepted. The major syndromes—especially schizophrenia, bipolar disorder, and major depression—were differentiated on the basis of their symptom patterns and course of illness. At the same time, clinical features such as psychosis, mood dysregulation, and cognitive impairments were known to transcend diagnostic categories. Doubt remains about the boundaries between the syndromes and the degree to which they signify entirely distinct entities, disorders that have overlapping foundations, or different variants of one underlying disease. Such debates have intensified with syndromes described subsequently, including autism spectrum disorders and attention deficit-hyperactivity disorder.
The pathogenic mechanisms of psychiatric disorders are largely unknown, so diagnostic boundaries are difficult to define. Genetic risk factors are important in the causation of all major psychiatric disorders,2 and genetic strategies are widely used to assess potential overlaps. The imminent revision of psychiatric classifications in the Diagnostic and Statistical Manual of Mental Disorders (DSM) and the International Classification of Diseases (ICD) has reinvigorated debate about the validity of diagnostic boundaries. With increasing availability of large genome-wide genotype data for several psychiatric disorders, shared cause can now be examined at a molecular level.
We formed the Psychiatric Genomics Consortium (PGC) in 2007, to undertake meta-analyses of genome-wide association studies (GWAS) for psychiatric disorders and, so far, the consortium has incorporated GWAS data from more than 19 countries for schizophrenia, bipolar disorder, major depressive disorder, attention deficit-hyperactivity disorder, and autism spectrum disorders. Previous research has suggested varying degrees of overlap in familial and genetic liability for pairs of these disorders. For example, some findings3, 4 from family and twin studies support diagnostic boundaries between schizophrenia and bipolar disorder and bipolar disorder and major depressive disorder, but also suggest correlations in familial and genetic liabilities.3, 5 Several molecular variants confer risk of both schizophrenia and bipolar disorder.6, 7, 8 Autism was once known as childhood schizophrenia and the two disorders were not clearly differentiated until the 1970s. Findings from the past few years have emphasised phenotypic and genetic overlap between autism spectrum disorders and schizophrenia,9, 10 including identification of copy number variants conferring risk of both.11 Findings from family, twin, and molecular studies12, 13, 14, 15 suggest some genetic overlap between autism spectrum disorder and attention deficit-hyperactivity disorder.
In this first report from the PGC Cross-Disorder Group, we analyse data on genome-wide single-nucleotide polymorphism (SNP) for the five PGC disorders to answer two questions. First, what information emerges when all five disorders are examined in one GWAS? When risk is correlated across disorders, pooled analyses will be better powered than individual-disorder analyses to detect risk loci. Second, what are the cross-disorder effects of variants already identified as being associated with a specific psychiatric disorder in previous PGC analyses? We aimed to examine the genetic relation between the five psychiatric disorders with the expectation that findings will ultimately inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and generate new models for prevention and treatment.
Section snippets
Samples and genotypes
The sample for these analyses consisted of cases, controls, and family-based samples assembled for previous genome-wide PGC mega-analyses of individual-level data.6, 7, 16, 17 Cases and controls were not related. For the family-based samples, we matched alleles transmitted to affected offspring (trio cases) with untransmitted alleles (pseudocontrols). We estimated the identity-by-descent relation for all pairs of individuals to identify any duplicate individuals in the component datasets. When
Results
The final dataset consisted of 33 332 cases and 27 888 controls (including pseudocontrols formed from non-transmitted alleles) distributed among the five disorder groups: autism spectrum disorders (4788 trio cases, 4788 trio pseudocontrols, 161 cases, 526 controls), attention deficit-hyperactivity disorder (1947 trio cases, 1947 trio pseudocontrols, 840 cases, 688 controls), bipolar disorder (6990 cases, 4820 controls), major depressive disorder (9227 cases, 7383 controls), and schizophrenia
Discussion
This study is the largest genome-wide analysis of psychiatric illness so far and the first to provide evidence that specific SNPs are significantly associated with a range of childhood-onset and adult-onset psychiatric disorders. For the five disorders studied, SNPs at four loci—regions on chromosomes 3p21 and 10q24, and SNPs in two L-type voltage-gated calcium-channel subunits, CACNA1C and CACNB2—exceeded the cutoff for genome-wide significance in the primary analysis. The strongest signal was
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