Leveraging Northern European population history: novel low-frequency variants for polycystic ovary syndrome Article Swipe
YOU?
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· 2021
· Open Access
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· DOI: https://doi.org/10.1093/humrep/deab250
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 (r2 = 0.95) and a missense I157T (r2 = 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.
Related Topics
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1093/humrep/deab250
- https://academic.oup.com/humrep/article-pdf/37/2/352/42324483/deab250.pdf
- OA Status
- bronze
- Cited By
- 94
- References
- 89
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3164157327
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3164157327Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/humrep/deab250Digital Object Identifier
- Title
-
Leveraging Northern European population history: novel low-frequency variants for polycystic ovary syndromeWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-10-28Full publication date if available
- Authors
-
Jaakko Tyrmi, Riikka K. Arffman, Natàlia Pujol‐Gualdo, Venla Kurra, Laure Morin‐Papunen, Eeva Sliz, Terhi Piltonen, Triin Laisk, Johannes Kettunen, Hannele LaivuoriList of authors in order
- Landing page
-
https://doi.org/10.1093/humrep/deab250Publisher landing page
- PDF URL
-
https://academic.oup.com/humrep/article-pdf/37/2/352/42324483/deab250.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://academic.oup.com/humrep/article-pdf/37/2/352/42324483/deab250.pdfDirect OA link when available
- Concepts
-
Polycystic ovary, Ovary, Population, Medicine, Gynecology, Biology, Internal medicine, Environmental health, Obesity, Insulin resistanceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
94Total citation count in OpenAlex
- Citations by year (recent)
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2025: 14, 2024: 56, 2023: 17, 2022: 7Per-year citation counts (last 5 years)
- References (count)
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89Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| citation_normalized_percentile.value | 0.99262287 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |