Association of genetic disorders and congenital malformations with premature ovarian insufficiency: a nationwide register-based study

Abstract STUDY QUESTION Are genetic disorders and congenital malformations associated with premature ovarian insufficiency (POI)? SUMMARY ANSWER A wide range of genetic disorder and congenital malformation diagnoses are associated with POI, especially early onset POI. WHAT IS KNOWN ALREADY POI is kn...

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Veröffentlicht in:Human reproduction (Oxford) 2023-06, Vol.38 (6), p.1224-1230
Hauptverfasser: Silvén, H, Savukoski, S M, Pesonen, P, Pukkala, E, Ojaniemi, M, Gissler, M, Suvanto, E, Niinimäki, M
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Sprache:eng
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Zusammenfassung:Abstract STUDY QUESTION Are genetic disorders and congenital malformations associated with premature ovarian insufficiency (POI)? SUMMARY ANSWER A wide range of genetic disorder and congenital malformation diagnoses are associated with POI, especially early onset POI. WHAT IS KNOWN ALREADY POI is known to be associated with some genetic disorders, such as Turner syndrome and Fragile X premutation. Multiple genetic syndromes, such as ataxia teleangiectasia and galactosemia, have also been associated with an increased risk of POI, and many of these genetic syndromes manifest with various congenital malformations. In previous studies, a genetic aetiology has been found for 7–15% of POI cases. STUDY DESIGN, SIZE, DURATION This population-based study included 5011 women diagnosed with POI in 1988–2017. The data were collected from various national registries and covers women with POI nationwide. PARTICIPANTS/MATERIALS, SETTING, METHODS We identified 5011 women diagnosed with POI from 1988 to 2017 from the drug reimbursement registry of the Social Insurance Institution of Finland. Women with surgical POI (bilateral oophorectomy for benign indications) were not included. We selected four population controls per woman with POI matched by month and year of birth and municipality of residence. Diagnostic codes for genetic disorders and congenital malformations (GD/CM) for the cases and controls were searched from the Hospital Discharge Register. Binary logistic regression was used to compare the odds for GD/CM among cases and controls. To minimize bias, for the statistical analyses, we excluded diagnoses which were reported
ISSN:0268-1161
1460-2350
DOI:10.1093/humrep/dead066