BDgene: A Genetic Database for Bipolar Disorder and Its Overlap With Schizophrenia and Major Depressive Disorder

Chang, Suhua; Gao, Lei; Zhao, Li; Zhang, Weina; Du, Yang; Wang, Jing

doi:10.1016/j.biopsych.2013.04.016

Cited by 47 publications

(35 citation statements)

References 60 publications

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“…Additionally, the contribution of potassium channels, which were enriched gene sets for Extraversion in this study, has been reported in psychiatric disorders (Judy & Zandi ; Zhang et al ). Recent studies have reported that common genetic influences are shared among psychiatric disorders including schizophrenia, bipolar and major depressive disorders (Chang et al ; Cross‐Disorder Group of the Psychiatric Genomics Consortium ; Lichtenstein et al ). Several genes that contributed to top‐ranked pathways in this study had previously been identified by GWA studies or pathway analysis in schizophrenia or other neuropsychiatric disorder phenotypes.…”

Section: Discussionmentioning

confidence: 99%

Pathway analysis of genome‐wide association datasets of personality traits

Kim

Cho

et al. 2015

Genes Brain and Behavior

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Although several genome-wide association (GWA) studies of human personality have been recently published, genetic variants that are highly associated with certain personality traits remain unknown, due to difficulty reproducing results. To further investigate these genetic variants, we assessed biological pathways using GWA datasets. Pathway analysis using GWA data was performed on 1089 Korean women whose personality traits were measured with the Revised NEO Personality Inventory for the 5-factor model of personality. A total of 1042 pathways containing 8297 genes were included in our study. Of these, 14 pathways were highly enriched with association signals that were validated in 1490 independent samples. These pathways include association of: Neuroticism with axon guidance [L1 cell adhesion molecule (L1CAM) interactions]; Extraversion with neuronal system and voltage-gated potassium channels; Agreeableness with L1CAM interaction, neurotransmitter receptor binding and downstream transmission in postsynaptic cells; and Conscientiousness with the interferon-gamma and platelet-derived growth factor receptor beta polypeptide pathways. Several genes that contribute to top-ranked pathways in this study were previously identified in GWA studies or by pathway analysis in schizophrenia or other neuropsychiatric disorders. Here we report the first pathway analysis of all five personality traits. Importantly, our analysis identified novel pathways that contribute to understanding the etiology of personality traits.

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Section: Discussionmentioning

confidence: 99%

Pathway analysis of genome‐wide association datasets of personality traits

Kim

Cho

et al. 2015

Genes Brain and Behavior

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“…2,3 In addition, several studies have reported evidence of familial co-aggregation or comorbidity between BD and SC, mainly attributable to overlapping genetic influences. 4 Over the past several years, genome-wide association studies (GWASs) have identified genetic variants that contribute to complex human disorders or physiological traits. 5 To date, over 10 000 putative single nucleotide polymorphism GWAS results reported to date are based almost exclusively on extensive cohorts of European ancestry.…”

Section: Introductionmentioning

confidence: 99%

Replication of genome‐wide association study (GWAS) susceptibility loci in a Latino bipolar disorder cohort

et al. 2016

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Objectives: Recent genome-wide association studies (GWASs) have identified numerous putative genetic polymorphisms associated with bipolar disorder (BD) and/or schizophrenia (SC). We hypothesized that a portion of these polymorphisms would also be associated with BD in the Latino American population. To identify such regions, we tested previously identified genetic variants associated with BD and/or SC and ancestral haploblocks containing these single nucleotide polymorphisms (SNPs) in a sample of Latino subjects with BD. Methods:A total of 2254 Latino individuals were genotyped for 91 SNPs identified in previous BD and/or SC GWASs, along with selected SNPs in strong linkage disequilibrium with these markers. Family-based single marker and haplotype association testing was performed using the PBAT software package. Empirical P-values were derived from 10 000 permutations.Results: Associations of eight a priori GWAS SNPs with BD were replicated with nominal (P≤.05) levels of significance. These included SNPs within nuclear factor I A (NFIA), serologically defined colon cancer antigen 8 (SDCCAG8), lysosomal associated membrane protein 3 (LAMP3), nuclear factor kappa B subunit 1 (NFKB1), major histocompatibility complex, class I, B (HLA-B) and 5′-nucleotidase, cytosolic II (NT5C2) and SNPs within intragenic regions microRNA 6828 (MIR6828)-solute carrier family 7 member 14 (SLC7A14) and sonic hedgehog (SHH)-long intergenic non-protein coding RNA 1006 (LINC01006). Of the 76 ancestral haploblocks that were tested for associations with BD, our top associated haploblock was located in LAMP3; however, the association did not meet statistical thresholds of significance following Bonferroni correction. Conclusions:These results indicate that some of the gene variants found to be associated with BD or SC in other populations are also associated with BD risk in Latinos.Variants in six genes and two intragenic regions were associated with BD in our Latino sample and provide additional evidence for overlap in genetic risk between SC and BD. K E Y W O R D Sbipolar disorder, Central American, family studies, genetics, lysosomal associated membrane protein 3 (LAMP3), Latinos, Mexican, Mexican-American, nuclear factor kappa B subunit 1 (NFKB1), serologically defined colon cancer antigen 8 (SDCCAG8)

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“…For each disease, we identify the top 10 most frequent genes. We then assess whether they are previously reported to be associated with T2D [52], CAD [59] and BD [61, 62] as well. The results of this analysis are shown in Table 3.…”

Section: Resultsmentioning

confidence: 99%

PoCos: Population Covering Locus Sets for Risk Assessment in Complex Diseases

Ayati

Koyutürk

2016

PLoS Comput Biol

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Susceptibility loci identified by GWAS generally account for a limited fraction of heritability. Predictive models based on identified loci also have modest success in risk assessment and therefore are of limited practical use. Many methods have been developed to overcome these limitations by incorporating prior biological knowledge. However, most of the information utilized by these methods is at the level of genes, limiting analyses to variants that are in or proximate to coding regions. We propose a new method that integrates protein protein interaction (PPI) as well as expression quantitative trait loci (eQTL) data to identify sets of functionally related loci that are collectively associated with a trait of interest. We call such sets of loci “population covering locus sets” (PoCos). The contributions of the proposed approach are three-fold: 1) We consider all possible genotype models for each locus, thereby enabling identification of combinatorial relationships between multiple loci. 2) We develop a framework for the integration of PPI and eQTL into a heterogenous network model, enabling efficient identification of functionally related variants that are associated with the disease. 3) We develop a novel method to integrate the genotypes of multiple loci in a PoCo into a representative genotype to be used in risk assessment. We test the proposed framework in the context of risk assessment for seven complex diseases, type 1 diabetes (T1D), type 2 diabetes (T2D), psoriasis (PS), bipolar disorder (BD), coronary artery disease (CAD), hypertension (HT), and multiple sclerosis (MS). Our results show that the proposed method significantly outperforms individual variant based risk assessment models as well as the state-of-the-art polygenic score. We also show that incorporation of eQTL data improves the performance of identified POCOs in risk assessment. We also assess the biological relevance of PoCos for three diseases that have similar biological mechanisms and identify novel candidate genes. The resulting software is publicly available at http://compbio.case.edu/pocos/.

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BDgene: A Genetic Database for Bipolar Disorder and Its Overlap With Schizophrenia and Major Depressive Disorder

Cited by 47 publications

References 60 publications

Pathway analysis of genome‐wide association datasets of personality traits

Pathway analysis of genome‐wide association datasets of personality traits

Replication of genome‐wide association study (GWAS) susceptibility loci in a Latino bipolar disorder cohort

PoCos: Population Covering Locus Sets for Risk Assessment in Complex Diseases

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