Most cited article - PubMed ID 27329760
Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder
Bipolar disorder is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 bipolar disorder risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci and prioritized 17 likely causal SNPs for bipolar disorder. We mapped these SNPs to genes and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci and results from rare variant exome sequencing in bipolar disorder. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment, including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, FKBP2, RASGRP1, FURIN, FES, MED24 and THRA among others in bipolar disorder. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of bipolar disorder polygenic risk scores across diverse populations and present a high-throughput fine-mapping pipeline.
- MeSH
- Bipolar Disorder * genetics MeSH
- Genome-Wide Association Study methods MeSH
- Genetic Predisposition to Disease * genetics MeSH
- Polymorphism, Single Nucleotide genetics MeSH
- Humans MeSH
- Quantitative Trait Loci genetics MeSH
- Chromosome Mapping * methods MeSH
- Multifactorial Inheritance genetics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 17 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, CRTC3, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, DPH1, GSDMB, MED24 and THRA in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of BD polygenic risk scores across diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
- Publication type
- Journal Article MeSH
- Preprint MeSH
Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
- MeSH
- Bipolar Disorder genetics MeSH
- Genome-Wide Association Study * MeSH
- Phenotype MeSH
- Genetic Predisposition to Disease MeSH
- Genome, Human MeSH
- Major Histocompatibility Complex genetics MeSH
- Humans MeSH
- Chromosomes, Human genetics MeSH
- Quantitative Trait Loci genetics MeSH
- Multifactorial Inheritance genetics MeSH
- Risk Factors MeSH
- Case-Control Studies MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Meta-Analysis MeSH
- Research Support, N.I.H., Extramural MeSH
Kleine-Levin syndrome (KLS) is a rare disorder characterized by severe episodic hypersomnia, with cognitive impairment accompanied by apathy or disinhibition. Pathophysiology is unknown, although imaging studies indicate decreased activity in hypothalamic/thalamic areas during episodes. Familial occurrence is increased, and risk is associated with reports of a difficult birth. We conducted a worldwide case-control genome-wide association study in 673 KLS cases collected over 14 y, and ethnically matched 15,341 control individuals. We found a strong genome-wide significant association (rs71947865, Odds Ratio [OR] = 1.48, P = 8.6 × 10-9) within the 3'region of TRANK1 gene locus, previously associated with bipolar disorder and schizophrenia. Strikingly, KLS cases with rs71947865 variant had significantly increased reports of a difficult birth. As perinatal outcomes have dramatically improved over the last 40 y, we further stratified our sample by birth years and found that recent cases had a significantly reduced rs71947865 association. While the rs71947865 association did not replicate in the entire follow-up sample of 171 KLS cases, rs71947865 was significantly associated with KLS in the subset follow-up sample of 59 KLS cases who reported birth difficulties (OR = 1.54, P = 0.01). Genetic liability of KLS as explained by polygenic risk scores was increased (pseudo R2 = 0.15; P < 2.0 × 10-22 at P = 0.5 threshold) in the follow-up sample. Pathway analysis of genetic associations identified enrichment of circadian regulation pathway genes in KLS cases. Our results suggest links between KLS, circadian regulation, and bipolar disorder, and indicate that the TRANK1 polymorphisms in conjunction with reported birth difficulties may predispose to KLS.
- Keywords
- GWAS, Kleine-Levin syndrome, bipolar disorder, birth difficulties, hypersomnia,
- MeSH
- Bipolar Disorder etiology MeSH
- Cytokines genetics MeSH
- Genetic Predisposition to Disease MeSH
- Genetic Variation * MeSH
- Genetic Association Studies MeSH
- Risk Assessment MeSH
- Kleine-Levin Syndrome complications epidemiology genetics MeSH
- Obstetric Labor Complications epidemiology etiology MeSH
- Humans MeSH
- Disease Susceptibility * MeSH
- Odds Ratio MeSH
- Polymorphism, Genetic MeSH
- Disorders of Excessive Somnolence etiology MeSH
- Risk Factors MeSH
- Pregnancy MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Names of Substances
- Cytokines MeSH
- TRANK1 protein, human MeSH Browser
Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
- MeSH
- Bipolar Disorder classification genetics MeSH
- Genome-Wide Association Study MeSH
- Depressive Disorder, Major genetics MeSH
- Genetic Predisposition to Disease MeSH
- Genetic Loci * MeSH
- Polymorphism, Single Nucleotide MeSH
- Humans MeSH
- Psychotic Disorders genetics MeSH
- Schizophrenia genetics MeSH
- Case-Control Studies MeSH
- Systems Biology MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Meta-Analysis MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Intramural MeSH
OBJECTIVES: Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients. METHODS: A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models. RESULTS: BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment. CONCLUSIONS: The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype.
- Keywords
- age at onset, bipolar disorder, early onset, polygenic risk score, schizophrenia,
- MeSH
- Bipolar Disorder genetics MeSH
- Child MeSH
- Adult MeSH
- Phenotype MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Multifactorial Inheritance MeSH
- Schizophrenia genetics MeSH
- Age Factors MeSH
- Check Tag
- Child MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
- Research Support, Non-U.S. Gov't MeSH
IMPORTANCE: Lithium is a first-line mood stabilizer for the treatment of bipolar affective disorder (BPAD). However, the efficacy of lithium varies widely, with a nonresponse rate of up to 30%. Biological response markers are lacking. Genetic factors are thought to mediate treatment response to lithium, and there is a previously reported genetic overlap between BPAD and schizophrenia (SCZ). OBJECTIVES: To test whether a polygenic score for SCZ is associated with treatment response to lithium in BPAD and to explore the potential molecular underpinnings of this association. DESIGN, SETTING, AND PARTICIPANTS: A total of 2586 patients with BPAD who had undergone lithium treatment were genotyped and assessed for long-term response to treatment between 2008 and 2013. Weighted SCZ polygenic scores were computed at different P value thresholds using summary statistics from an international multicenter genome-wide association study (GWAS) of 36 989 individuals with SCZ and genotype data from patients with BPAD from the Consortium on Lithium Genetics. For functional exploration, a cross-trait meta-GWAS and pathway analysis was performed, combining GWAS summary statistics on SCZ and response to treatment with lithium. Data analysis was performed from September 2016 to February 2017. MAIN OUTCOMES AND MEASURES: Treatment response to lithium was defined on both the categorical and continuous scales using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. The effect measures include odds ratios and the proportion of variance explained. RESULTS: Of the 2586 patients in the study (mean [SD] age, 47.2 [13.9] years), 1478 were women and 1108 were men. The polygenic score for SCZ was inversely associated with lithium treatment response in the categorical outcome, at a threshold P < 5 × 10-2. Patients with BPAD who had a low polygenic load for SCZ responded better to lithium, with odds ratios for lithium response ranging from 3.46 (95% CI, 1.42-8.41) at the first decile to 2.03 (95% CI, 0.86-4.81) at the ninth decile, compared with the patients in the 10th decile of SCZ risk. In the cross-trait meta-GWAS, 15 genetic loci that may have overlapping effects on lithium treatment response and susceptibility to SCZ were identified. Functional pathway and network analysis of these loci point to the HLA antigen complex and inflammatory cytokines. CONCLUSIONS AND RELEVANCE: This study provides evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPAD. These results suggest the potential for translational research aimed at personalized prescribing of lithium.
- MeSH
- Bipolar Disorder drug therapy genetics MeSH
- Genome-Wide Association Study * MeSH
- Adult MeSH
- Genetic Load MeSH
- Genotype MeSH
- HLA Antigens genetics MeSH
- Middle Aged MeSH
- Humans MeSH
- Lithium Carbonate therapeutic use MeSH
- Multifactorial Inheritance genetics MeSH
- Schizophrenic Psychology MeSH
- Schizophrenia drug therapy genetics MeSH
- Treatment Outcome MeSH
- Inflammation genetics MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Randomized Controlled Trial MeSH
- Research Support, N.I.H., Extramural MeSH
- Names of Substances
- HLA Antigens MeSH
- Lithium Carbonate MeSH