2020
DOI: 10.1038/s41398-020-00902-6
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Multi-trait analysis for genome-wide association study of five psychiatric disorders

Abstract: We conducted a cross-trait meta-analysis of genome-wide association study on schizophrenia (SCZ) (n = 65,967), bipolar disorder (BD) (n = 41,653), autism spectrum disorder (ASD) (n = 46,350), attention deficit hyperactivity disorder (ADHD) (n = 55,374), and depression (DEP) (n = 688,809). After the meta-analysis, the number of genomic loci

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Cited by 165 publications
(124 citation statements)
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References 65 publications
(68 reference statements)
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“…As one of the validation criteria, relative risk estimates should have been reported with standard errors or 95% CIs. Data are then extracted from the validated articles [ 40 , 41 ]. Dosage effect and age or gender specificity should be considered when evaluating the response to NTP treatment.…”
Section: Discussionmentioning
confidence: 99%
“…As one of the validation criteria, relative risk estimates should have been reported with standard errors or 95% CIs. Data are then extracted from the validated articles [ 40 , 41 ]. Dosage effect and age or gender specificity should be considered when evaluating the response to NTP treatment.…”
Section: Discussionmentioning
confidence: 99%
“…), was used to identify cholinergic-relevant gene sets encompassing a total of 345 genes, which constituted the cholinergic activity gene set for this ontological enrichment analysis. An autism gene set containing 47 genes from a recent cross-trait genome-wide meta-analysis (Wu et al, 2020) was used because it identified more risk genes for ASD compared with another GWAS study for ASD, thus providing enhanced statistical power for the present study (Grove et al, 2019).…”
Section: Identification Of Ontologies Associated With Each Gene Set mentioning
confidence: 99%
“…Each instance of a relationship identified by NLPbased word triplet identification was graded by Pathway Studio in terms of confidence levels of 1-3, with a maximum confidence level of 3 being defined as an entity-to-entity relationship supported by at least three peer reviewed publications reflected FIGURE 1 | Gene ontology overlap between autism and cholinergic metabolism gene sets. Overlap between an autism-associated genome-wide associated studies gene set (Wu et al, 2020) and cholinergic pathways gene set (MSigDB v7.1) was identified using Venny 2.1. The two shared ontologies were (1) regulation of ion transport and (2) positive regulation of ion transport, identifying ion transport functionality as a critical area of enrichment for further analysis.…”
Section: Gene Set Pathway Intersection Analysis Of Shared Ontologiesmentioning
confidence: 99%
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