Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UMLS:C0036341 (schizophrenia)
 60,220 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Bipolar disorder affects about 1% of the world's population, and its estimated heritability is about 75%. Only few whole genome or whole-exome sequencing studies in bipolar disorder have been reported, and no rare coding variants have yet been robustly identified. The use of isolated populations might help finding variants with a recent origin, more likely to have drifted to higher frequency by chance. Following this approach, we investigated 28 bipolar cases and 214 controls from the Faroe Islands by whole exome sequencing, and the results were followed-up in a British sample of 2025 cases and 1358 controls. Seventeen variants in 16 genes in the single-variant analysis, and 3 genes in the gene-based statistics surpassed exome-wide significance in the discovery phase. The discovery findings were supported by enrichment analysis of common variants from genome-wide association studies (GWAS) data and interrogation of protein-protein interaction networks. The replication in the British sample confirmed the association with NOS1 (missense variant rs79487279) and NCL (gene-based test). A number of variants from the discovery set were not present in the replication sample, including a novel PITPNM2 missense variant, which is located in a highly significant schizophrenia GWAS locus. Likewise, PIK3C2A identified in the gene-based analysis is located in a combined bipolar and schizophrenia GWAS locus. Our results show support both for existing findings in the literature, as well as for new risk genes, and identify rare variants that might provide additional information on the underlying biology of bipolar disorder.
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PMID:Whole-exome sequencing of individuals from an isolated population implicates rare risk variants in bipolar disorder. 2819 73

Genome-wide association studies (GWAS) have identified abundant risk loci associated with schizophrenia (SCZ), cardiometabolic disease (CMD) including body mass index, coronary artery diseases, type 2 diabetes, low- and high-density lipoprotein, total cholesterol, and triglycerides. Although recent studies have suggested that genetic risk shared between these disorders, the pleiotropic genes and biological pathways shared between them are still vague. Here we integrated comprehensive multi-dimensional data from GWAS, expression quantitative trait loci (eQTL), and gene set database to systematically identify potential pleiotropic genes and biological pathways shared between SCZ and CMD. By integrating the results from different approaches including FUMA, Sherlock, SMR, UTMOST, FOCUS, and DEPICT, we revealed 21 pleiotropic genes that are likely to be shared between SCZ and CMD. These genes include VRK2, SLC39A8, NT5C2, AMBRA1, ARL6IP4, OGFOD2, PITPNM2, CDK2AP1, C12orf65, ABCB9, SETD8, MPHOSPH9, FES, FURIN, INO80E, YPEL3, MAPK3, SREBF1, TOM1L2, GATAD2A, and TM6SF2. In addition, we also performed the gene-set enrichment analysis using the software of GSA-SNP2 and MAGMA with GWAS summary statistics and identified three biological pathways (MAPK-TRK signaling, growth hormone signaling, and regulation of insulin secretion signaling) shared between them. Our study provides insights into the pleiotropic genes and biological pathways underlying mechanisms for the comorbidity of SCZ and CMD. However, further genetic and functional studies are required to validate the role of these potential pleiotropic genes and pathways in the etiology of the comorbidity of SCZ and CMD, which should provide potential targets for future diagnostics and therapeutics.
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PMID:Integrated Analysis of Summary Statistics to Identify Pleiotropic Genes and Pathways for the Comorbidity of Schizophrenia and Cardiometabolic Disease. 3242 17