Genetic effects influencing risk for major depressive disorder in China and Europe.

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

Evidence for genetic heterogeneity between clinical subtypes of bipolar disorder.

We performed a genome-wide association study of 6447 bipolar disorder (BD) cases and 12 639 controls from the International Cohort Collection for Bipolar Disorder (ICCBD). Meta-analysis was performed with prior results from the Psychiatric Genomics Consortium Bipolar Disorder Working Group for a combined sample of 13 902 cases and 19 279 controls. We identified eight genome-wide significant, associated regions, including a novel associated region on chromosome 10 (rs10884920; P=3.28 × 10-8) that includes the brain-enriched cytoskeleton protein adducin 3 (ADD3), a non-coding RNA, and a neuropeptide-specific aminopeptidase P (XPNPEP1). Our large sample size allowed us to test the heritability and genetic correlation of BD subtypes and investigate their genetic overlap with schizophrenia and major depressive disorder. We found a significant difference in heritability of the two most common forms of BD (BD I SNP-h2=0.35; BD II SNP-h2=0.25; P=0.02). The genetic correlation between BD I and BD II was 0.78, whereas the genetic correlation was 0.97 when BD cohorts containing both types were compared. In addition, we demonstrated a significantly greater load of polygenic risk alleles for schizophrenia and BD in patients with BD I compared with patients with BD II, and a greater load of schizophrenia risk alleles in patients with the bipolar type of schizoaffective disorder compared with patients with either BD I or BD II. These results point to a partial difference in the genetic architecture of BD subtypes as currently defined.

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction.

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.

GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia.

We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed bioinformatic prioritization for all the markers with P-values ≤0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE and MGS-GAIN samples, rs4704591 was identified as the most significant marker in the gene. Linkage disequilibrium analyses indicated that these markers were in low LD (3 828 611-rs10043986, r(2)=0.008; rs10043986-rs4704591, r(2)=0.204). In addition, CMYA5 was reported to be physically interacting with the DTNBP1 gene, a promising candidate for schizophrenia, suggesting that CMYA5 may be involved in the same biological pathway and process. On the basis of this information, we performed replication studies for these three single-nucleotide polymorphisms. The rs3828611 was found to have conflicting results in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case-control samples, 11 380 cases and 15 021 controls), we found that both markers are significantly associated with schizophrenia (rs10043986, odds ratio (OR)=1.11, 95% confidence interval (CI)=1.04-1.18, P=8.2 × 10(-4) and rs4704591, OR=1.07, 95% CI=1.03-1.11, P=3.0 × 10(-4)). The results were also significant for the 22 Caucasian replication samples (rs10043986, OR=1.11, 95% CI=1.03-1.17, P=0.0026 and rs4704591, OR=1.07, 95% CI=1.02-1.11, P=0.0015). Furthermore, haplotype conditioned analyses indicated that the association signals observed at these two markers are independent. On the basis of these results, we concluded that CMYA5 is associated with schizophrenia and further investigation of the gene is warranted.

Association study of SNAP25 and schizophrenia in Irish family and case-control samples.

SNAP25 occurs on chromosome 20p12.2, which has been linked to schizophrenia in some samples, and recently linked to latent classes of psychotic illness in our sample. SNAP25 is crucial to synaptic functioning, may be involved in axonal growth and dendritic sprouting, and its expression may be decreased in schizophrenia. We genotyped 18 haplotype-tagging SNPs in SNAP25 in a sample of 270 Irish high-density families. Single marker and haplotype analyses were performed in FBAT and PDT. We adjusted for multiple testing by computing q values. Association was followed up in an independent sample of 657 cases and 411 controls. We tested for allelic effects on the clinical phenotype by using the method of sequential addition and 5 factor-derived scores of the OPCRIT. Nine of 18 SNPs had P values <0.05 in either FBAT or PDT for one or more definitions of illness. Several two-marker haplotypes were also associated. Subjects inheriting the risk alleles of the most significantly associated two-marker haplotype were likely to have higher levels of hallucinations and delusions. The most significantly associated marker, rs6039820, was observed to perturb 12 transcription-factor binding sites in in silico analyses. An attempt to replicate association findings in the case-control sample resulted in no SNPs being significantly associated. We observed robust association in both single marker and haplotype-based analyses between SNAP25 and schizophrenia in an Irish family sample. Although we failed to replicate this in an independent sample, this gene should be further tested in other samples.

Replication of association between schizophrenia and ZNF804A in the Irish Case-Control Study of Schizophrenia sample.

A recent genome-wide association study reported association between schizophrenia and the ZNF804A gene on chromosome 2q32.1. We attempted to replicate these findings in our Irish Case-Control Study of Schizophrenia (ICCSS) sample (N=1021 cases, 626 controls). Following consultation with the original investigators, we genotyped three of the most promising single-nucleotide polymorphisms (SNPs) from the Cardiff study. We replicate association with rs1344706 (trend test one-tailed P=0.0113 with the previously associated A allele) in ZNF804A. We detect no evidence of association with rs6490121 in NOS1 (one-tailed P=0.21), and only a trend with rs9922369 in RGRIP1L (one-tailed P=0.0515). On the basis of these results, we completed genotyping of 11 additional linkage disequilibrium-tagging SNPs in ZNF804A. Of 12 SNPs genotyped, 11 pass quality control criteria and 4 are nominally associated, with our most significant evidence of association at rs7597593 (P=0.0013) followed by rs1344706. We observe no evidence of differential association in ZNF804A on the basis of family history or sex of case. The associated SNP rs1344706 lies in approximately 30 bp of conserved mammalian sequence, and the associated A allele is predicted to maintain binding sites for the brain-expressed transcription factors MYT1l and POU3F1/OCT-6. In controls, expression is significantly increased from the A allele of rs1344706 compared with the C allele. Expression is increased in schizophrenic cases compared with controls, but this difference does not achieve statistical significance. This study replicates the original reported association of ZNF804A with schizophrenia and suggests that there is a consistent link between the A allele of rs1344706, increased expression of ZNF804A and risk for schizophrenia.

Significant correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy.

Prior family and adoption studies have suggested a genetic relationship between schizophrenia and schizotypy. However, this has never been verified using linkage methods. We therefore attempted to test for a correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy. The Irish study of high-density schizophrenia families comprises 270 families with at least two members with schizophrenia or poor-outcome schizoaffective disorder (n=637). Non-psychotic relatives were assessed using the structured interview for schizotypy (n=746). A 10-cM multipoint, non-parametric, autosomal genome-wide scan of schizophrenia was performed in Merlin. A scan of a quantitative trait comprising ratings of DSM-III-R criteria for schizotypal personality disorder in non-psychotic relatives was also performed. Schizotypy logarithm of the odds (LOD) scores were regressed onto schizophrenia LOD scores at all loci, with adjustment for spatial autocorrelation. To assess empirical significance, this was also carried out using 1000 null scans of schizotypy. The number of jointly linked loci in the real data was compared to distribution of jointly linked loci in the null scans. No markers were suggestively linked to schizotypy based on strict Lander-Kruglyak criteria. Schizotypy LODs predicted schizophrenia LODs above chance expectation genome wide (empirical P=0.04). Two and four loci yielded nonparametric LOD (NPLs) >1.0 and >0.75, respectively, for both schizophrenia and schizotypy (genome-wide empirical P=0.04 and 0.02, respectively). These results suggest that at least a subset of schizophrenia susceptibility genes also affects schizotypy in non-psychotic relatives. Power may therefore be increased in molecular genetic studies of schizophrenia if they incorporate measures of schizotypy in non-psychotic relatives.

Genetic heterogeneity, modifier genes, and quantitative phenotypes in psychiatric illness: searching for a framework.

Schizophrenia has long been thought to be clinically heterogeneous. A range of studies suggests that this is due to genetic heterogeneity. Some clinical features, such as negative symptoms, are associated with a greater risk of illness in relatives. Affected sibling pairs are correlated for clinical and course features as well as subforms of illness, and twin studies suggest that this is due to genetic factors. This is further supported by findings that subjects from families linked to some chromosomal regions may differ clinically from those from unlinked families. Moreover, some genes may affect clinical features without altering susceptibility (ie are modifier genes). High-risk genotypes may have quantitative, rather than categorical effects, and may influence milder or subclinical phenotypes. Another recent finding is that nonpsychotic relatives may have personality features that resemble those of their affected relatives. These findings taken together suggest that there may be several classes of gene action in schizophrenia: some genes may influence susceptibility only, others may influence clinical features only, and still others may have a mixed effect. Furthermore, subsets of these classes may affect personality and other traits in nonpsychotic relatives. Understanding these classes of gene action may help guide the design of linkage and association studies that have increased power. We describe five classes of genes and their predictions of the outcomes of family, twin, and several types of linkage studies. We go on to explore how these predictions can in turn be used to aid in the design of linkage studies.

The prediction of thoughts of death or self-harm in a population-based sample of female twins.

BACKGROUND: Although suicide is a leading cause of death, few studies have attempted to predict suicidal ideation prospectively using epidemiological samples or multivariate methods. METHOD: Discrete-time event history analysis was used to model the onset of thoughts of death or self-harm (TD/SH) in a population-based sample of female twins (N=2164) using variables from the demographic, psychopathological, childhood adversity, personality and life event domains. Univariate, multivariate-within domain and multivariate-across domain regression analyses were performed. RESULTS: Most variables predicted TD/SH in the univariate analyses. However, the only variables to predict TD/SH independently were obsessive symptoms, childhood sexual abuse, rural residence, unemployment, older age, lifetime history of cocaine misuse and low levels of education, personal religious devotion and altruism, as well as divorce/separation, loss of confidant, assault, job loss and financial problems in the previous month. This final model explained 16% of the variance in TD/SH. Lifetime histories of major depression, panic disorder and alcohol misuse had no significant independent effect. CONCLUSIONS: Many variables, from all five domains of risk factors, are associated with the risk of TD/SH, but many of these effects may be mediated by other risk factors. Proximal life events and psychopathology may have more independent effects than other domains. The overall ability of these risk factors to predict TD/SH is modest. We cannot rule out that differences between these analyses and previous reports were due to our use of TD/SH as the dependent variable instead of thoughts of committing suicide per se.

Do endogenous features in depression predict the risk of psychiatric illness in relatives?

We sought to evaluate the hypothesis that endogenous symptoms define a form of depression that is relatively distinct from a familial perspective. Cox models examined the relationship between endogenous symptoms in 88 epidemiologically ascertained cases of treated major depression and the risk for a range of psychiatric disorders in relatives. Endogenicity did not predict risk of major depression, bipolar disorder, anxiety disorders, schizophrenia, or schizophrenia spectrum illnesses in relatives. Risk in relatives of illness as an external validator of endogenous depression is not supported by our family study data.