Using Population Genetics to Interrogate the Monogenic Nephrotic Syndrome Diagnosis in a Case Cohort.

Publication Type:

Journal Article

Source:

J Am Soc Nephrol, Volume 27, Issue 7, p.1970-83 (2016)

Keywords:

Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Genetics, Population, Humans, Middle Aged, Nephrotic Syndrome, Young Adult

Abstract:

To maximize clinical benefits of genetic screening of patients with nephrotic syndrome (NS) to diagnose monogenic causes, reliably distinguishing NS-causing variants from the background of rare, noncausal variants prevalent in all genomes is vital. To determine the prevalence of monogenic NS in a North American case cohort while accounting for background prevalence of genetic variation, we sequenced 21 implicated monogenic NS genes in 312 participants from the Nephrotic Syndrome Study Network and 61 putative controls from the 1000 Genomes Project (1000G). These analyses were extended to available sequence data from approximately 2500 subjects from the 1000G. A typical pathogenicity filter identified causal variants for NS in 4.2% of patients and 5.8% of subjects from the 1000G. We devised a more stringent pathogenicity filtering strategy, reducing background prevalence of causal variants to 1.5%. When applying this stringent filter to patients, prevalence of monogenic NS was 2.9%; of these patients, 67% were pediatric, and 44% had FSGS on biopsy. The rate of complete remission did not associate with monogenic classification. Thus, we identified factors contributing to inaccurate monogenic classification of NS and developed a more accurate variant filtering strategy. The prevalence and clinical correlates of monogenic NS in this sporadically affected cohort differ substantially from those reported for patients referred for genetic analysis. Particularly in unselected, population-based cases, considering putative causal variants in known NS genes from a probabilistic rather than a deterministic perspective may be more precise. We also introduce GeneVetter, a web tool for monogenic assessment of rare disease.