Int J Gynaecol Obstet
January 2025
Objective: To study whether gynecologic or reproductive disorders show association with trisomic conceptions.
Methods: This nationwide cohort study utilized the Registry of Congenital Malformations to identify women who had a trisomic pregnancy (n = 5784), either with trisomy 13 (T13; n = 351), trisomy 18 (T18; n = 1065) or trisomy 21 (T21; n = 4369) from 1987 to 2018. We used the Finnish Maternity cohort to match the cases to population controls (n = 34 422) on the age, residence, and timing of pregnancy.
Background: Discussion about the risks and benefits of offering secondary findings as part of genome-wide diagnostics lacks real-life data. We studied the opt-in decisions of patients/families referred to whole exome study (WES) in Blueprint Genetics (BpG), a genetic testing company with customers in over 70 countries to receive secondary findings. Based on the American College of Medical Genetics (ACMG) recommendations for reporting secondary findings, BpG offered testing of specific actionable genes without additional charge for specimens submitted to WES diagnostics.
View Article and Find Full Text PDFIsolated populations have been valuable for the discovery of rare monogenic diseases and their causative genetic variants. Finnish disease heritage (FDH) is an example of a group of hereditary monogenic disorders caused by single major, usually autosomal-recessive, variants enriched in the population due to several past genetic drift events. Interestingly, distinct subpopulations have remained in Finland and have maintained their unique genetic repertoire.
View Article and Find Full Text PDFReceiving polygenic risk estimates of future disease through health care or direct-to-consumer companies is expected to become more common in the coming decades. However, only a limited number of studies have examined if such estimates might evoke an adverse psychosocial reaction in receivers. The present study utilized data from a sub-section of a personalized medicine project (the P5 study) that combines genomic and traditional health data to evaluate participants' risk for certain common diseases.
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