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Updated: Jul 8, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Quantitative thresholds for variant enrichment in 13,845 cases: improving pathogenicity classification in genetic
Sihan Liu1,2, Mingjun Zhong2, Yu Huang2
1Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, 610000, China.
Background:
The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines recommend using variant enrichment among cases as "strong" evidence for pathogenicity per the PS4 criterion. However, quantitative support for PS4 thresholds from real-world Mendelian case-control cohorts is lacking.
Methods:
To address this gap, we evaluated and established PS4 thresholds using data from the Chinese Deafness Genetics Consortium. A total of 9,050 variants from 13,845 patients with hearing loss (HL) and 6,570 ancestry-matched controls were analyzed. Positive likelihood ratio and local positive likelihood ratio values were calculated to determine the thresholds corresponding to each strength of evidence across three variant subsets.
Results:
In subset 1, consisting of variants present in both cases and controls with an allele frequency (AF) in cases ≥ 0.0005, an odds ratio (OR) ≥ 6 achieved strong evidence, while OR ≥ 3 represented moderate evidence. For subset 2, which encompassed variants present in both cases and controls with a case AF < 0.0005, and subset 3, comprising variants found only in cases and absent from controls, we defined the PS4_Supporting threshold (OR > 2.27 or allele count ≥ 3) and the PS4_Moderate threshold (allele count ≥ 6), respectively. Reanalysis applying the adjusted PS4 criteria changed the classification of 15 variants and enabled diagnosis of an additional four patients.
Conclusions:
Our study quantified evidence strength thresholds for variant enrichment in genetic HL cases, highlighting the importance of defining disease/gene-specific thresholds to improve the precision and accuracy of clinical genetic testing.
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