Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

Background: Curated databases of genetic variants assist clinicians and researchers in interpreting genetic variation. Yet, these databases contain some misclassified variants. It is unclear whether variant misclassification is abating as these databases rapidly grow and implement new guidelines. Methods: Using archives of ClinVar and HGMD, we investigated how variant misclassification has changed over 6 years, across different ancestry groups. We considered inborn errors of metabolism (IEMs) screened in newborns as a model system because these disorders are often highly penetrant with neonatal phenotypes. We used samples from the 1000 Genomes Project (1KGP) to identify individuals with genotypes that were classified by the databases as pathogenic. Due to the rarity of IEMs, nearly all such classified pathogenic genotypes indicate likely variant misclassification in ClinVar or HGMD. Results: While the false-positive rates of both ClinVar and HGMD have improved over time, HGMD variants currently imply two orders of magnitude more affected individuals in 1KGP than ClinVar variants. We observed that African ancestry individuals have a significantly increased chance of being incorrectly indicated to be affected by a screened IEM when HGMD variants are used. However, this bias affecting genomes of African ancestry was no longer significant once common variants were removed in accordance with recent variant classification guidelines. We discovered that ClinVar variants classified as Pathogenic or Likely Pathogenic are reclassified sixfold more often than DM or DM? variants in HGMD, which has likely resulted in ClinVar’s lower false-positive rate. Conclusions: Considering misclassified variants that have since been reclassified reveals our increasing understanding of rare genetic variation. We found that variant classification guidelines and allele frequency databases comprising genetically diverse samples are important factors in reclassification. We also discovered that ClinVar variants common in European and South Asian individuals were more likely to be reclassified to a lower confidence category, perhaps due to an increased chance of these variants being classified by multiple submitters. We discuss features for variant classification databases that would support their continued improvement.

Short-chain acyl-CoA dehydrogenase deficiency (SCADD) is a rare autosomal recessive disorder of β-oxidation caused by pathogenic variants in the ACADS gene. Analyte testing for SCADD in blood and urine, including newborn screening (NBS) using tandem mass spectrometry (MS/MS) on dried blood spots (DBSs), is complicated by the presence of two relatively common ACADS variants (c.625G>A and c.511C>T). Individuals homozygous for these variants or compound heterozygous do not have clinical disease but do have reduced short-chain acyl-CoA dehydrogenase (SCAD) activity, resulting in elevated blood and urine metabolites. As part of a larger study of the potential role of exome sequencing in NBS in California, we reviewed ACADS sequence and MS/MS data from DBSs from a cohort of 74 patients identified to have SCADD. Of this cohort, approximately 60% had one or more of the common variants and did not have the two rare variants, and thus would need no further testing. Retrospective analysis of ethylmalonic acid, glutaric acid, 2-hydroxyglutaric acid, 3-hydroxyglutaric acid, and methylsuccinic acid demonstrated that second-tier testing applied before the release of the newborn screening result could reduce referrals by over 50% and improve the positive predictive value for SCADD to above 75%.