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Accurate and efficient classification of variant pathogenicity is critical for research and clinical care. Using data from three large studies, we demonstrate that population-based associations between rare variants and quantitative endophenotypes for three monogenic diseases (low-density-lipoprotein cholesterol for familial hypercholesterolemia, electrocardiographic QTc interval for long QT syndrome, and glycosylated hemoglobin for maturity-onset diabetes of the young) are proxies for variant pathogenicity. Effect sizes were associated with pathogenic ClinVar assertions (P<0.001 for each trait) and discriminated pathogenic from non-pathogenic variants (area under the curve 0.82-0.83 across endophenotypes). Large effect size thresholds provided evidence supporting pathogenicity for up to 35% of rare variants of uncertain significance or not in ClinVar in disease susceptibility genes, using an effect size threshold of [&ge;]0.5 times the endophenotype standard deviation. We propose that variant associations with quantitative endophenotypes for monogenic diseases can provide evidence supporting pathogenicity.

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