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. 2019 Sep;40(9):1579-1592.
doi: 10.1002/humu.23826. Epub 2019 Aug 7.

Predicting pathogenicity of missense variants with weakly supervised regression

Yue Cao  1 , Yuanfei Sun  1 , Mostafa Karimi  1 , Haoran Chen  1 , Oluwaseyi Moronfoye  1 , Yang Shen  1
Affiliations

Predicting pathogenicity of missense variants with weakly supervised regression

Yue Cao et al. Hum Mutat. 2019 Sep.

Abstract

Quickly growing genetic variation data of unknown clinical significance demand computational methods that can reliably predict clinical phenotypes and deeply unravel molecular mechanisms. On the platform enabled by the Critical Assessment of Genome Interpretation (CAGI), we develop a novel "weakly supervised" regression (WSR) model that not only predicts precise clinical significance (probability of pathogenicity) from inexact training annotations (class of pathogenicity) but also infers underlying molecular mechanisms in a variant-specific manner. Compared to multiclass logistic regression, a representative multiclass classifier, our kernelized WSR improves the performance for the ENIGMA Challenge set from 0.72 to 0.97 in binary area under the receiver operating characteristic curve (AUC) and from 0.64 to 0.80 in ordinal multiclass AUC. WSR model interpretation and protein structural interpretation reach consensus in corroborating the most probable molecular mechanisms by which some pathogenic BRCA1 variants confer clinical significance, namely metal-binding disruption for p.C44F and p.C47Y, protein-binding disruption for p.M18T, and structure destabilization for p.S1715N.

Keywords: clinical significance; genetic variation; genome medicine; machine learning; model interpretability; molecular mechanism; weak supervision.

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Conflict of interest statement

4.1. CONFLICT OF INTEREST

The authors declare no conflict of interest.

Figures

Figure 1:
Figure 1:
Illustration of loss functions used in weakly supervised regressors (WSR). A. Parabola-shaped loss functions for WSR1 and B. ε-insensitive loss functions for WSR2 and WSR3.
Figure 2:
Figure 2:
Structural interpretation of pathogenicity mechanisms for several BRCA1 variations at structurallyavailable RING and BRCT domains. Pathogenic (Class 5) and benign (Class 1) variation sites are shown in red and pale cyan spheres. Zoomed-in illustrations of molecular mechanisms have been shown for individual variants in smaller side boxes, where crystal wild-type residues are in gray sticks and modeled mutant residues are in cyan sticks. A. RING domain complex of BRCA1-BARD1 in PDB structure 1JM7 where RING domain of BRCA1 is shown in gray cartoon, BARD1 wheat cartoon, and Zn2+ ions small blue sphere. B. BRCT domain of BRCA1 interacting with Bach1 helicase in PDB structure 1T29 PDB where BRCT is shown in grey cartoon and Bach1 helicase in pink sticks.
See this image and copyright information in PMC

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