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      Leveraging Northern European population history: novel low-frequency variants for polycystic ovary syndrome

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          Abstract

          STUDY QUESTION

          Can we identify novel variants associated with polycystic ovary syndrome (PCOS) by leveraging the unique population history of Northern Europe?

          SUMMARY ANSWER

          We identified three novel genome-wide significant associations with PCOS, with two putative independent causal variants in the checkpoint kinase 2 ( CHEK2) gene and a third in myosin X ( MYO10).

          WHAT IS KNOWN ALREADY

          PCOS is a common, complex disorder with unknown aetiology. While previous genome-wide association studies (GWAS) have mapped several loci associated with PCOS, the analysis of populations with unique population history and genetic makeup has the potential to uncover new low-frequency variants with larger effects.

          STUDY DESIGN, SIZE, DURATION

          A population-based case–control GWAS was carried out.

          PARTICIPANTS/MATERIALS, SETTING, METHODS

          We identified PCOS cases from national registers by ICD codes (ICD-10 E28.2, ICD-9 256.4, or ICD-8 256.90), and all remaining women were considered controls. We then conducted a three-stage case–control GWAS: in the discovery phase, we had a total of 797 cases and 140 558 controls from the FinnGen study. For validation, we used an independent dataset from the Estonian Biobank, including 2812 cases and 89 230 controls. Finally, we performed a joint meta-analysis of 3609 cases and 229 788 controls from both cohorts. Additionally, we reran the association analyses including BMI as a covariate, with 2169 cases and 160 321 controls from both cohorts.

          MAIN RESULTS AND THE ROLE OF CHANCE

          Two out of the three novel genome-wide significant variants associating with PCOS, rs145598156 ( P = 3.6×10 −8, odds ratio (OR) = 3.01 [2.02–4.50] minor allele frequency (MAF) = 0.005) and rs182075939 ( P = 1.9×10 −16, OR = 1.69 [1.49–1.91], MAF = 0.04), were found to be enriched in the Finnish and Estonian populations and are tightly linked to a deletion c.1100delC ( r 2 = 0.95) and a missense I157T ( r 2 = 0.83) in CHEK2. The third novel association is a common variant near MYO10 (rs9312937, P = 1.7 × 10 −8, OR = 1.16 [1.10–1.23], MAF = 0.44). We also replicated four previous reported associations near the genes Erb-B2 Receptor Tyrosine Kinase 4 ( ERBB4), DENN Domain Containing 1A ( DENND1A), FSH Subunit Beta ( FSHB) and Zinc Finger And BTB Domain Containing 16 ( ZBTB16). When adding BMI as a covariate only one of the novel variants remained genome-wide significant in the meta-analysis (the EstBB lead signal in CHEK2 rs182075939, P = 1.9×10 −16, OR = 1.74 [1.5–2.01]) possibly owing to reduced sample size.

          LARGE SCALE DATA

          The age- and BMI-adjusted GWAS meta-analysis summary statistics are available for download from the GWAS Catalog with accession numbers GCST90044902 and GCST90044903.

          LIMITATIONS, REASONS FOR CAUTION

          The main limitation was the low prevalence of PCOS in registers; however, the ones with the diagnosis most likely represent the most severe cases. Also, BMI data were not available for all (63% for FinnGen, 76% for EstBB), and the biobank setting limited the accessibility of PCOS phenotypes and laboratory values.

          WIDER IMPLICATIONS OF THE FINDINGS

          This study encourages the use of isolated populations to perform genetic association studies for the identification of rare variants contributing to the genetic landscape of complex diseases such as PCOS.

          STUDY FUNDING/COMPETING INTEREST(S)

          This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the MATER Marie Skłodowska-Curie grant agreement No. 813707 (N.P.-G., T.L., T.P.), the Estonian Research Council grant (PRG687, T.L.), the Academy of Finland grants 315921 (T.P.), 321763 (T.P.), 297338 (J.K.), 307247 (J.K.), 344695 (H.L.), Novo Nordisk Foundation grant NNF17OC0026062 (J.K.), the Sigrid Juselius Foundation project grants (T.L., J.K., T.P.), Finska Läkaresällskapet (H.L.) and Jane and Aatos Erkko Foundation (H.L.). The funders had no role in study design, data collection and analysis, publishing or preparation of the manuscript. The authors declare no conflicts of interest.

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          Most cited references85

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          The mutational constraint spectrum quantified from variation in 141,456 humans

          Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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            METAL: fast and efficient meta-analysis of genomewide association scans

            Summary: METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats. Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/ Contact: goncalo@umich.edu
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              Functional mapping and annotation of genetic associations with FUMA

              A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.
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                Author and article information

                Contributors
                Journal
                Hum Reprod
                Hum Reprod
                humrep
                Human Reproduction (Oxford, England)
                Oxford University Press
                0268-1161
                1460-2350
                February 2022
                13 November 2021
                13 November 2021
                : 37
                : 2
                : 352-365
                Affiliations
                Computational Medicine, Faculty of Medicine, University of Oulu , Oulu, Finland
                Center for Life Course Health Research, Faculty of Medicine, University of Oulu , Oulu, Finland
                Biocenter Oulu, University of Oulu , Oulu, Finland
                Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Centre, Oulu University Hospital, University of Oulu , Oulu, Finland
                Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Centre, Oulu University Hospital, University of Oulu , Oulu, Finland
                Estonian Genome Centre, Institute of Genomics, University of Tartu , Tartu, Estonia
                Department of Clinical Genetics, Faculty of Medicine and Health Technology, Tampere University Hospital and Tampere University , Tampere, Finland
                Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Centre, Oulu University Hospital, University of Oulu , Oulu, Finland
                Computational Medicine, Faculty of Medicine, University of Oulu , Oulu, Finland
                Center for Life Course Health Research, Faculty of Medicine, University of Oulu , Oulu, Finland
                Biocenter Oulu, University of Oulu , Oulu, Finland
                Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Centre, Oulu University Hospital, University of Oulu , Oulu, Finland
                Estonian Genome Centre, Institute of Genomics, University of Tartu , Tartu, Estonia
                Computational Medicine, Faculty of Medicine, University of Oulu , Oulu, Finland
                Center for Life Course Health Research, Faculty of Medicine, University of Oulu , Oulu, Finland
                Biocenter Oulu, University of Oulu , Oulu, Finland
                Finnish Institute for Health and Welfare , Helsinki, Finland
                Department of Obstetrics and Gynecology, Faculty of Medicine and Health Technology, Tampere University Hospital and Tampere University , Tampere, Finland
                Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital , Helsinki, Finland
                Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki , Helsinki, Finland
                Author notes

                Jaakko S Tyrmi and Riikka K Arffman contributed equally to this work.

                Johannes Kettunen and Hannele Laivuori contributed equally to this work.

                Correspondence address. Center for Life Course Health Research, Faculty of Medicine, Aapistie 5A, PO Box 5000, 90014 University of Oulu, Oulu, Finland. E-mail: jaakko.tyrmi@ 123456oulu.fi
                Author information
                https://orcid.org/0000-0002-4757-6563
                https://orcid.org/0000-0003-3277-9293
                https://orcid.org/0000-0001-6428-8427
                https://orcid.org/0000-0002-3086-733X
                https://orcid.org/0000-0001-5987-7534
                https://orcid.org/0000-0002-2316-058X
                https://orcid.org/0000-0002-9921-7300
                https://orcid.org/0000-0003-1501-9030
                https://orcid.org/0000-0002-3345-491X
                https://orcid.org/0000-0003-3212-7826
                Article
                deab250
                10.1093/humrep/deab250
                8804330
                34791234
                bca07dc6-8307-4d98-9704-7a948e49af93
                © The Author(s) 2021. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 01 July 2021
                : 07 October 2021
                : 17 October 2021
                Page count
                Pages: 14
                Funding
                Funded by: European Union’s Horizon 2020 research and innovation programme;
                Award ID: 813707
                Funded by: Estonian Research Council, DOI 10.13039/501100002301;
                Award ID: PRG687
                Funded by: Academy of Finland, DOI 10.13039/501100002341;
                Award ID: 315921
                Award ID: 321763
                Award ID: 297338
                Award ID: 307247
                Award ID: 344695
                Funded by: Novo Nordisk Foundation, DOI 10.13039/501100009708;
                Award ID: NNF17OC0026062
                Funded by: Sigrid Juselius Foundation;
                Funded by: Finska Läkaresällskapet (H.L.) and Jane and Aatos Erkko Foundation (H.L.);
                Categories
                Original Articles
                Reproductive Genetics
                AcademicSubjects/MED00905

                Human biology
                genome-wide association study,rare variants,polycystic ovary syndrome,checkpoint kinase 2,myosin x

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