Fig. 2: Genome-wide significant SNPs associated with SHS. | Communications Biology

Fig. 2: Genome-wide significant SNPs associated with SHS.

From: Genome-wide association analysis of composite sleep health scores in 413,904 individuals

Fig. 2

a Number of Genome-wide significant (GWS) SNPs (p < 5e-08) and risk loci (“Methods”). b Number of risk variants that colocalized for each pair of SHS (HyPrColoc; “Methods”). c Number of loci not reported by previous sleep GWASs in biobanks (GWS loci with a lead variant at least 500 kb from any of the previously published GWS sleep variants; “Methods”). d Number of loci reported by previous sleep GWASs in biobanks (lead variant within 500 kb of published GWS sleep variants; “Methods”). e Distribution of Functional consequences (FUMA18; “Methods”) of all annotated SNPs in LD with independent GWS SNPs by SHS; 3.2% of the annotated SNPs were in functional regions (exon, UTR, and splice site). f Regulome DB score distribution (FUMA; “Methods”) of all annotated SNPs in LD with independent GWS SNPs by SHS; 3.4% of the annotated SNPs were in regulatory regions with Regulome DB score < 2. g CADD score distribution (FUMA; “Methods”) of all annotated SNPs in LD with independent GWS SNPs by SHS; 6.8% of the annotated SNPs likely deleterious effect with CADD score>10. h Chromatin state distribution (FUMA; “Methods”) of all annotated SNPs in LD with independent GWS SNPs by SHS; 74% of the annotated SNPs were in open chromatin regions with a minimum chromatin state between 1 and 7. OSA obstructive sleep apnea, RLS restless leg syndrome, SHS sleep health score, UTR5 5′ untranslated region: UTR3 3′ untranslated region, ncRNA non-coding RNA.

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