Background Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO ( n = 12 977) and PAO ( n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample ( n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. Conclusions AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

ABSTRACT Bipolar disorder is a highly heritable psychiatric disorder that features episodes of mania and depression. We performed the largest genome-wide association study to date, including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 sentinel variants at loci with P<1×10 -4 in an independent sample of 9,412 cases and 137,760 controls. In the combined analysis, 30 loci reached genome-wide significant evidence for association, of which 20 were novel. These significant loci contain genes encoding ion channels and neurotransmitter transporters ( CACNA1C , GRIN2A , SCN2A , SLC4A1 ), synaptic components ( RIMS1 , ANK3 ), immune and energy metabolism components. Bipolar disorder type I (depressive and manic episodes; ~ 73% of our cases) is strongly genetically correlated with schizophrenia whereas bipolar disorder type II (depressive and hypomanic episodes; ~ 17% of our cases) is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for bipolar disorder.

Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 – 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 – rs2086256 – rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.

Disentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: a novel data mining procedure to identify yet undetected genotype–phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted.

Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable disorders that share a significant proportion of common risk variation. Understanding the genetic factors underlying the specific symptoms of these disorders will be crucial for improving diagnosis, intervention and treatment. In case-control data consisting of 53,555 cases (20,129 BD, 33,426 SCZ) and 54,065 controls, we identified 114 genome-wide significant loci (GWS) when comparing all cases to controls, of which 41 represented novel findings. Two genome-wide significant loci were identified when comparing SCZ to BD and a third was found when directly incorporating functional information. Regional joint association identified a genomic region of overlapping association in BD and SCZ with disease-independent causal variants indicating a fourth region contributing to differences between these disorders. Regional SNP-heritability analyses demonstrated that the estimated heritability of BD based on the SCZ GWS regions was significantly higher than that based on the average genomic region (91 regions, p = 1.2×10−6) while the inverse was not significant (19 regions, p=0.89). Using our BD and SCZ GWAS we calculated polygenic risk scores and identified several significant correlations with: 1) SCZ subphenotypes: negative symptoms (SCZ, p=3.6×10−6) and manic symptoms (BD, p=2×10−5), 2) BD subphenotypes: psychotic features (SCZ p=1.2×10−10, BD p=5.3×10−5) and age of onset (SCZ p=7.9×10−4). Finally, we show that psychotic features in BD has significant SNP-heritability (h2 snp=0.15, SE=0.06), and a significant genetic correlation with SCZ (rg=0.34) in addition there is a significant sign test result between SCZ GWAS and a GWAS of BD cases contrasting those with and without psychotic features (p=0.0038, one-side binomial test). For the first time, we have identified specific loci pointing to a potential role of 4 genes ( DARS2 , ARFGEF2 , DCAKD and GATAD2A ) that distinguish between BD and SCZ, providing an opportunity to understand the biology contributing to clinical differences of these disorders. Our results provide the best evidence so far of genomic components distinguishing between BD and SCZ that contribute directly to specific symptom dimensions.

ABSTRACTBipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324,p= 5.87×10−9; odds ratio = 1.12) and markers withinERBB2(rs2517959,p= 4.53×10−9; odds ratio = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.

We conducted a systematic study of top susceptibility variants from a genome-wide association (GWA) study of bipolar disorder to gain insight into the functional consequences of genetic variation influencing disease risk. We report here the results of experiments to explore the effects of these susceptibility variants on DNA methylation and mRNA expression in human cerebellum samples. Among the top susceptibility variants, we identified an enrichment of cis regulatory loci on mRNA expression (eQTLs), and a significant excess of quantitative trait loci for DNA CpG methylation, hereafter referred to as methylation quantitative trait loci (mQTLs). Bipolar disorder susceptibility variants that cis regulate both cerebellar expression and methylation of the same gene are a very small proportion of bipolar disorder susceptibility variants. This finding suggests that mQTLs and eQTLs provide orthogonal ways of functionally annotating genetic variation within the context of studies of pathophysiology in brain. No lymphocyte mQTL enrichment was found, suggesting that mQTL enrichment was specific to the cerebellum, in contrast to eQTLs. Separately, we found that using mQTL information to restrict the number of single-nucleotide polymorphisms studied enhances our ability to detect a significant association. With this restriction a priori informed by the observed functional enrichment, we identified a significant association (rs12618769, P(bonferroni)<0.05) from two other GWA studies (TGen+GAIN; 2191 cases and 1434 controls) of bipolar disorder, which we replicated in an independent GWA study (WTCCC). Collectively, our findings highlight the importance of integrating functional annotation of genetic variants for gene expression and DNA methylation to advance the biological understanding of bipolar disorder.

Although a highly heritable and disabling disease, bipolar disorder's (BD) genetic variants have been challenging to identify. We present new genotype data for 1,190 cases and 401 controls and perform a genome-wide association study including additional samples for a total of 2,191 cases and 1,434 controls. We do not detect genome-wide significant associations for individual loci; however, across all SNPs, we show an association between the power to detect effects calculated from a previous genome-wide association study and evidence for replication (P = 1.5×10(-7)). To demonstrate that this result is not likely to be a false positive, we analyze replication rates in a large meta-analysis of height and show that, in a large enough study, associations replicate as a function of power, approaching a linear relationship. Within BD, SNPs near exons exhibit a greater probability of replication, supporting an enrichment of reproducible associations near functional regions of genes. These results indicate that there is likely common genetic variation associated with BD near exons (±10 kb) that could be identified in larger studies and, further, provide a framework for assessing the potential for replication when combining results from multiple studies.

BACKGROUND:Recent genome-wide association studies have associated polymorphisms in the gene CACNA1C, which codes for Ca(v)1.2, with a bipolar disorder and depression diagnosis. METHODS:The behaviors of wild-type and Cacna1c heterozygous mice of both sexes were evaluated in a number of tests. Based upon sex differences in our mouse data, we assessed a gene × sex interaction for diagnosis of mood disorders in human subjects. Data from the National Institute of Mental Health Genetics Initiative Bipolar Disorder Consortium and the Genetics of Recurrent Early-Onset Major Depression Consortium were examined using a combined dataset that included 2021 mood disorder cases (1223 female cases) and 1840 control subjects (837 female subjects). RESULTS:In both male and female mice, Cacna1c haploinsufficiency was associated with lower exploratory behavior, decreased response to amphetamine, and antidepressant-like behavior in the forced swim and tail suspension tests. Female, but not male, heterozygous mice displayed decreased risk-taking behavior or increased anxiety in multiple tests, greater attenuation of amphetamine-induced hyperlocomotion, decreased development of learned helplessness, and a decreased acoustic startle response, indicating a sex-specific role of Cacna1c. In humans, sex-specific genetic association was seen for two intronic single nucleotide polymorphisms, rs2370419 and rs2470411, in CACNA1C, with effects in female subjects (odds ratio = 1.64, 1.32) but not in male subjects (odds ratio = .82, .86). The interactions by sex were significant after correction for testing 190 single nucleotide polymorphisms (p = 1.4 × 10⁻⁴, 2.1 × 10⁻⁴; p(corrected) = .03, .04) and were consistent across two large datasets. CONCLUSIONS:Our preclinical results support a role for CACNA1C in mood disorder pathophysiology, and the combination of human genetic and preclinical data support an interaction between sex and genotype.

A genome-wide association study was carried out in 1020 case subjects with recurrent early-onset major depressive disorder (MDD) (onset before age 31) and 1636 control subjects screened to exclude lifetime MDD. Subjects were genotyped with the Affymetrix 6.0 platform. After extensive quality control procedures, 671 424 autosomal single nucleotide polymorphisms (SNPs) and 25 068 X chromosome SNPs with minor allele frequency greater than 1% were available for analysis. An additional 1 892 186 HapMap II SNPs were analyzed based on imputed genotypic data. Single-SNP logistic regression trend tests were computed, with correction for ancestry-informative principal component scores. No genome-wide significant evidence for association was observed, assuming that nominal P <5 × 10 −8 approximates a 5% genome-wide significance threshold. The strongest evidence for association was observed on chromosome 18q22.1 (rs17077540, P =1.83 × 10 −7 ) in a region that has produced some evidence for linkage to bipolar-I or -II disorder in several studies, within an mRNA detected in human brain tissue (BC053410) and approximately 75 kb upstream of DSEL . Comparing these results with those of a meta-analysis of three MDD GWAS data sets reported in a companion article, we note that among the strongest signals observed in the GenRED sample, the meta-analysis provided the greatest support (although not at a genome-wide significant level) for association of MDD to SNPs within SP4 , a brain-specific transcription factor. Larger samples will be required to confirm the hypothesis of association between MDD (and particularly the recurrent early-onset subtype) and common SNPs.

We report a genome-wide association study (GWAS) of major depressive disorder (MDD) in 1221 cases from the Sequenced Treatment Alternatives to Relieve Depression (STAR * D) study and 1636 screened controls. No genome-wide evidence for association was detected. We also carried out a meta-analysis of three European-ancestry MDD GWAS data sets: STAR * D, Genetics of Recurrent Early-onset Depression and the publicly available Genetic Association Information Network–MDD data set. These data sets, totaling 3957 cases and 3428 controls, were genotyped using four different platforms (Affymetrix 6.0, 5.0 and 500 K, and Perlegen). For each of 2.4 million HapMap II single-nucleotide polymorphisms (SNPs), using genotyped data where available and imputed data otherwise, single-SNP association tests were carried out in each sample with correction for ancestry-informative principal components. The strongest evidence for association in the meta-analysis was observed for intronic SNPs in ATP6V1B2 ( P =6.78 × 10 −7 ), SP4 ( P =7.68 × 10 −7 ) and GRM7 ( P =1.11 × 10 −6 ). Additional exploratory analyses were carried out for a narrower phenotype (recurrent MDD with onset before age 31, N =2191 cases), and separately for males and females. Several of the best findings were supported primarily by evidence from narrow cases or from either males or females. On the basis of previous biological evidence, we consider GRM7 a strong MDD candidate gene. Larger samples will be required to determine whether any common SNPs are significantly associated with MDD.

To identify bipolar disorder (BD) genetic susceptibility factors, we conducted two genome-wide association (GWA) studies: one involving a sample of individuals of European ancestry (EA; n =1001 cases; n =1033 controls), and one involving a sample of individuals of African ancestry (AA; n =345 cases; n =670 controls). For the EA sample, single-nucleotide polymorphisms (SNPs) with the strongest statistical evidence for association included rs5907577 in an intergenic region at Xq27.1 ( P =1.6 × 10 −6 ) and rs10193871 in NAP5 at 2q21.2 ( P =9.8 × 10 −6 ). For the AA sample, SNPs with the strongest statistical evidence for association included rs2111504 in DPY19L3 at 19q13.11 ( P =1.5 × 10 −6 ) and rs2769605 in NTRK2 at 9q21.33 ( P =4.5 × 10 −5 ). We also investigated whether we could provide support for three regions previously associated with BD, and we showed that the ANK3 region replicates in our sample, along with some support for C15Orf53 ; other evidence implicates BD candidate genes such as SLITRK2 . We also tested the hypothesis that BD susceptibility variants exhibit genetic background-dependent effects. SNPs with the strongest statistical evidence for genetic background effects included rs11208285 in ROR1 at 1p31.3 ( P =1.4 × 10 −6 ), rs4657247 in RGS5 at 1q23.3 ( P =4.1 × 10 −6 ), and rs7078071 in BTBD16 at 10q26.13 ( P =4.5 × 10 −6 ). This study is the first to conduct GWA of BD in individuals of AA and suggests that genetic variations that contribute to BD may vary as a function of ancestry.

OBJECTIVE Family studies have suggested that postpartum mood symptoms might have a partly genetic etiology. The authors used a genome-wide linkage analysis to search for chromosomal regions that harbor genetic variants conferring susceptibility for such symptoms. The authors then fine-mapped their best linkage regions, assessing single nucleotide polymorphisms (SNPs) for genetic association with postpartum symptoms. METHOD Subjects were ascertained from two studies: the NIMH Genetics Initiative Bipolar Disorder project and the Genetics of Recurrent Early-Onset Depression. Subjects included women with a history of pregnancy, any mood disorder, and information about postpartum symptoms. In the linkage study, 1,210 women met criteria (23% with postpartum symptoms), and 417 microsatellite markers were analyzed in multipoint allele sharing analyses. For the association study, 759 women met criteria (25% with postpartum symptoms), and 16,916 SNPs in the regions of the best linkage peaks were assessed for association with postpartum symptoms. RESULTS The maximum linkage peak for postpartum symptoms occurred on chromosome 1q21.3-q32.1, with a chromosome-wide significant likelihood ratio Z score (Z(LR)) of 2.93 (permutation p=0.02). This was a significant increase over the baseline Z(LR) of 0.32 observed at this locus among all women with a mood disorder (permutation p=0.004). Suggestive linkage was also found on 9p24.3-p22.3 (Z(LR)=2.91). In the fine-mapping study, the strongest implicated gene was HMCN1 (nominal p=0.00017), containing four estrogen receptor binding sites, although this was not region-wide significant. CONCLUSIONS This is the first study to examine the genetic etiology of postpartum mood symptoms using genome-wide data. The results suggest that genetic variations on chromosomes 1q21.3-q32.1 and 9p24.3-p22.3 may increase susceptibility to postpartum mood symptoms.

We sought to determine whether premenstrual mood symptoms exhibit familial aggregation in bipolar disorder or major depression pedigrees. Two thousand eight hundred seventy-six women were interviewed with the Diagnostic Interview for Genetic Studies as part of either the NIMH Genetics Initiative Bipolar Disorder Collaborative study or the Genetics of Early Onset Major Depression (GenRED) study and asked whether they had experienced severe mood symptoms premenstrually. In families with two or more female siblings with bipolar disorder (BP) or major depressive disorder (MDD), we examined the odds of having premenstrual mood symptoms given one or more siblings with these symptoms. For the GenRED MDD sample we also assessed the impact of personality as measured by the NEO-FFI. Premenstrual mood symptoms did not exhibit familial aggregation in families with BP or MDD. We unexpectedly found an association between high NEO openness scores and premenstrual mood symptoms, but neither this factor, nor NEO neuroticism influenced evidence for familial aggregation of symptoms. Limitations include the retrospective interview, the lack of data on premenstrual dysphoric disorder, and the inability to control for factors such as medication use.

BACKGROUND:We reported genome-wide significant linkage on chromosome 15q25.3-26.2 to recurrent early-onset major depressive disorder (MDD-RE). Here we present initial linkage-disequilibrium (LD) fine mapping of this signal and sequence analysis of NTRK3 (neurotrophic receptor kinase-3), a biologically plausible candidate gene. METHODS:In 300 pedigrees informative for family-based association, 1195 individuals were genotyped for 795 single nucleotide polymorphism (SNPs). We resequenced 21 exons and 7 highly conserved NTRK3 regions in 176 MDD-RE cases to test for an excess of rare functional variants and, 176 controls for case-control analysis of common variants. RESULTS:LD mapping showed nominally significant association in NTRK3, FLJ12484, RHCG, DKFZp547K1113, VPS33B, SV2B, SLCO3A1, RGMA, and MCTP2 with MDD-RE. In NTRK3, five SNPs had nominally significant p values (.035-.001). Sequence analysis revealed 35 variants (24 novel, including 9 rare exonic); the number of rare variants did not exceed chance expectation. Case-control analysis of 13 common variants showed modest nominal association of MDD-RE with rs4887379, rs6496463, and rs3825882 (p = .008, .048, and .034), which were in partial LD with four of five associated SNPs from the family-based experiment. CONCLUSIONS:Common variants in NTRK3 or other genes identified might play a role in MDD-RE. However, much larger studies are required for full evaluation of this region.

Payne JL, MacKinnon DF, Mondimore FM, McInnis MG, Schweizer B,Zamoiski RB, McMahon FJ, Nurnberger Jr JI, Rice JP, Scheftner W,Coryell W, Berrettini WH, Kelsoe JR, Byerley W, Gershon ES,DePaulo Jr JR, Potash JB. Familial aggregation of postpartum moodsymptoms in bipolar disorder pedigrees.Bipolar Disord 2008: 10: 38–44. a Blackwell Munksgaard, 2008Objectives: We sought to determine if postpartum mood symptomsand depressive episodes exhibit familial aggregation in bipolar Ipedigrees.Methods: A total of 1,130 women were interviewed with the DiagnosticInterview for Genetic Studies as part of the National Institute of MentalHealth (NIMH) Genetics Initiative Bipolar Disorder CollaborativeStudy and were asked whether they had ever experienced moodsymptoms within four weeks postpartum. Women were also askedwhether either of two major depressive episodes described in detailoccurred postpartum. We examined the odds of postpartum moodsymptoms in female siblings, who had previously been pregnant and hada diagnosis of bipolar I, bipolar II, or schizoaffective (bipolar type)disorders (n ¼ 303), given one or more relatives with postpartum moodsymptoms.Results: The odds ratio for familial aggregation of postpartum moodsymptoms was 2.31 (p ¼ 0.011) in an Any Mood Symptoms analysis(n ¼ 304) and increased to 2.71 (p ¼ 0.005) when manic symptoms wereexcluded, though this was not significantly different from the Any MoodSymptoms analysis. We also examined familial aggregation ofpostpartum major depressive episodes; however, the number of subjectswas small.Conclusions: Limitations of the study include the retrospectiveinterview, the fact that the data were collected for other purposes and theinability to control for such factors as medication use. Taken togetherwith previous studies, these data provide support for the hypothesis thatthere may be a genetic basis for the trait of postpartum mood symptomsgenerally and postpartum depressive symptoms in particular in womenwith bipolar disorder. Genetic linkage and association studiesincorporating this trait are warranted.

Objective Brain-derived neurotrophic factor (BDNF) plays an important role in the survival, differentiation, and outgrowth of select peripheral and central neurons throughout adulthood. Growing evidence suggests that BDNF is involved in the pathophysiology of mood disorders. Methods Ten single nucleotide polymorphisms (SNPs) across the BDNF gene were genotyped in a sample of 1749 Caucasian Americans from 250 multiplex bipolar families. Family-based association analysis was used with three hierarchical bipolar disorder models to test for an association between SNPs in BDNF and the risk of bipolar disorder. In addition, an exploratory analysis was performed to test for an association of the SNPs in BDNF and the phenotypes of rapid cycling and episode frequency. Results Evidence of association (P<0.05) was found with several of the SNPs using multiple models of bipolar disorder; one of these SNPs also showed evidence of association (P<0.05) with rapid cycling. Conclusion These results provide further evidence that variation in BDNF affects the risk for bipolar disorder.