Japanese GWAS identifies variants for bust-size, dysmenorrhea, and menstrual fever that are eQTLs for relevant protein-coding or long non-coding RNAs.
Japanese GWAS identifies variants for bust-size, dysmenorrhea, and menstrual fever that are eQTLs for relevant protein-coding or long non-coding RNAs.
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DOI:
10.1038/s41598-018-25065-9
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发表时间:
2018-05-31
影响因子:
4.6
通讯作者:
Osuga Y
中科院分区:
文献类型:
--
作者:
Hirata T;Koga K;Johnson TA;Morino R;Nakazono K;Kamitsuji S;Akita M;Kawajiri M;Kami A;Hoshi Y;Tada A;Ishikawa K;Hine M;Kobayashi M;Kurume N;Fujii T;Kamatani N;Osuga Y
Traits related to primary and secondary sexual characteristics greatly impact females during puberty and day-to-day adult life. Therefore, we performed a GWAS analysis of 11,348 Japanese female volunteers and 22 gynecology-related phenotypic variables, and identified significant associations for bust-size, menstrual pain (dysmenorrhea) severity, and menstrual fever. Bust-size analysis identified significant association signals in CCDC170-ESR1 (rs6557160; P = 1.7 × 10−16) and KCNU1-ZNF703 (rs146992477; P = 6.2 × 10−9) and found that one-third of known European-ancestry associations were also present in Japanese. eQTL data points to CCDC170 and ZNF703 as those signals’ functional targets. For menstrual fever, we identified a novel association in OPRM1 (rs17181171; P = 2.0 × 10−8), for which top variants were eQTLs in multiple tissues. A known dysmenorrhea signal near NGF replicated in our data (rs12030576; P = 1.1 × 10−19) and was associated with RP4-663N10.1 expression, a putative lncRNA enhancer of NGF, while a novel dysmenorrhea signal in the IL1 locus (rs80111889; P = 1.9 × 10−16) contained SNPs previously associated with endometriosis, and GWAS SNPs were most significantly associated with IL1A expression. By combining regional imputation with colocalization analysis of GWAS/eQTL signals along with integrated annotation with epigenomic data, this study further refines the sets of candidate causal variants and target genes for these known and novel gynecology-related trait loci.
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影响因子:
32.4
作者:
Garlanda C;Dinarello CA;Mantovani A
通讯作者:
Mantovani A
影响因子:
7
作者:
Harrow J;Frankish A;Gonzalez JM;Tapanari E;Diekhans M;Kokocinski F;Aken BL;Barrell D;Zadissa A;Searle S;Barnes I;Bignell A;Boychenko V;Hunt T;Kay M;Mukherjee G;Rajan J;Despacio-Reyes G;Saunders G;Steward C;Harte R;Lin M;Howald C;Tanzer A;Derrien T;Chrast J;Walters N;Balasubramanian S;Pei B;Tress M;Rodriguez JM;Ezkurdia I;van Baren J;Brent M;Haussler D;Kellis M;Valencia A;Reymond A;Gerstein M;Guigó R;Hubbard TJ
通讯作者:
Hubbard TJ
影响因子:
3.5
作者:
Demerath, Ellen W.;Liu, Ching-Ti;Haiman, Christopher A.
通讯作者:
Haiman, Christopher A.
影响因子:
9.2
作者:
Chang CC;Chow CC;Tellier LC;Vattikuti S;Purcell SM;Lee JJ
通讯作者:
Lee JJ
影响因子:
14.9
作者:
Griffon A;Barbier Q;Dalino J;van Helden J;Spicuglia S;Ballester B
通讯作者:
Ballester B