IntroductionA recently published study by Keet al. utilized whole exome sequencing (WES) to screen genetic variants contributing to premature ovarian insufficiency (POI) in a large cohort of 1,030 patients from China (doi: 10.1038/s41591-022-02194-3). The authors reported that 285 likely pathogenic (LP) and pathogenic (P) variants identified in 79 genes contributed to POI in 242 study subjects, representing 23.5% of the cohort. The majority, 191 patients (∼79%), carried monoallelic (heterozygous) variants.ObjectiveWe re-analyzed the contribution of reported genotypes considering the inheritance mode of POI and other inherited conditions linked to 79 genes with reported findings by Keet al.MethodsThe disease inheritance modes linked to targeted genes were retrieved from publicly available databases (OMIM, Genomic England PanelApp, PubMed, DOMINO, gnomAD). Genotypes of 242 cases reported by Keet al.were assessed in the context of known inheritance mode(s) of disorders linked to respective genes.ResultsMost, 48 of 79 genes were classified as recessive, whereas only 13 genes were dominant. Insufficient data was available for 18 genes to conclusively determine their inheritance mode. Nearly half of 242 cases reported by Keet al., 119 women (∼49%), carried heterozygous variants in known autosomal recessive genes and therefore these variants are not contributing to their POI phenotype. Only 68 of women (6.6%) carried biallelic variants in either recessive or dominant genes or monoallelic variants in dominant genes, hence contributing to the diagnostic yield. This is ∼3.5-fold lower than 23.5% claimed in Keet al. Additional 56 women (5.4%) were reported monoallelic variants in genes with insufficient data to determine the inheritance mode or multiple heterozygous variants in >1 recessive gene, whereby oligogenic contribution to POI cannot be excluded. But when even including these cases, the maximum estimated contributing yield is ∼12%, two times lower than claimed.ConclusionUsing WES to screen monogenic causes of POI as part of the diagnostic pipeline will improve patient management strategies, but overestimated diagnostic yield in genetic research can create unrealistic expectations in the POI clinical community, typically non-specialist in genetics.