Dataset Information

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

ABSTRACT: Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (r_g=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (r_g=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no r_g between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.

SUBMITTER: Venkatesh SS

PROVIDER: S-EPMC10984039 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Venkatesh Samvida S SS Wittemans Laura B L LBL Palmer Duncan S DS Baya Nikolas A NA Ferreira Teresa T Hill Barney B Lassen Frederik Heymann FH Parker Melody J MJ Reibe Saskia S Elhakeem Ahmed A Banasik Karina K Bruun Mie T MT Erikstrup Christian C Jensen Bitten A BA Juul Anders A Mikkelsen Christina C Nielsen Henriette S HS Ostrowski Sisse R SR Pedersen Ole B OB Rohde Palle D PD Sorensen Erik E Ullum Henrik H Westergaard David D Haraldsson Asgeir A Holm Hilma H Jonsdottir Ingileif I Olafsson Isleifur I Steingrimsdottir Thora T Steinthorsdottir Valgerdur V Thorleifsson Gudmar G Figueredo Jessica J Karjalainen Minna K MK Pasanen Anu A Jacobs Benjamin M BM Hubers Nikki N Lippincott Margaret M Fraser Abigail A Lawlor Deborah A DA Timpson Nicholas J NJ Nyegaard Mette M Stefansson Kari K Magi Reedik R Laivuori Hannele H van Heel David A DA Boomsma Dorret I DI Balasubramanian Ravikumar R Seminara Stephanie B SB Chan Yee-Ming YM Laisk Triin T Lindgren Cecilia M CM

medRxiv : the preprint server for health sciences 20240320

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (<i>P</i>≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (<i>r</i> <su ...[more]

PMID: 38562841

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Project description:Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, that affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (p < 5×10-8). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes (MYBPC3, BAG3), as well as regulators of lipoprotein (LPL) and glucose metabolism (GIPR, GLP1R), and are enriched in cardiac, muscle, nerve, and vascular tissues, as well as myocyte and adipocyte cell types. Gene burden studies across three biobanks (PMBB, UKB, AOU) including 27,208 individuals with HF and 349,126 without uncover exome-wide significant (p < 3.15×10-6) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN, MYBPC3, FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, and is lower than heritability attributable to common variants (4.3%, 95% CI 3.9-4.7%) which is more diffusely spread throughout the genome. Finally, we demonstrate that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. These findings suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.

Dataset Information

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Publications

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

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