Background: Exome sequencing is increasingly being used for clinical diagnostics, with an impetus to expand reporting of incidental findings across a wide range of disorders. Analysis of population cohorts can help reduce risk for genetic variant misclassification and resultant unnecessary referrals to subspecialists.
Objective: To examine the burden of candidate pathogenic variants for kidney and genitourinary disorders emerging from exome sequencing.
Design: Secondary analysis of genetic data.
Setting: A tertiary care academic medical center.
Patients: A convenience sample of exome sequence data from 7974 self-declared healthy adults.
Measurements: Assessment of the prevalence of candidate pathogenic variants in 625 genes associated with Mendelian kidney and genitourinary disorders.
Results: Of all participants, 23.3% carried a candidate pathogenic variant, most of which were attributable to previously reported variants that had implausibly high allele frequencies. In particular, 25 genes (discovered before the creation of the Exome Aggregation Consortium, a genetic database comprising data from a large control population) accounted for 67.7% of persons with candidate pathogenic variants. After stringent filtering based on allele frequency, 1.4% of persons still had a candidate pathogenic variant, an excessive rate given the prevalence of monogenic kidney and genitourinary disorders. Manual annotation of a subset of variants showed that the majority would be classified as nonbenign under current guidelines for clinical sequence interpretation and could prompt subspecialty referrals if returned.
Limitation: Limited access to health record data prevented comprehensive assessment of the phenotypic concordance with genetic diagnoses.
Conclusion: Widespread reporting of incidental genetic findings related to kidney and genitourinary disorders will require stringent curation of clinical variant databases and detailed case-level review to avoid genetic misdiagnosis and unnecessary referrals. These findings motivate similar analyses for genes relevant to other medical subspecialties.
Primary funding source: National Institute of Diabetes and Digestive and Kidney Diseases and National Human Genome Research Institute.