Structural Biology Helps Interpret Variants of Uncertain Significance in Genes
Causing Endocrine and Metabolic Disorders
#MMPMID30019023
Ittisoponpisan S
; David A
J Endocr Soc
2018[Aug]; 2
(8
): 842-854
PMID30019023
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CONTEXT: Variants of uncertain significance (VUSs) lack sufficient evidence, in
terms of statistical power or experimental studies, to allow unequivocal
determination of their damaging effect. VUSs are a major burden in performing
genetic analysis. Although in silico prediction tools are widely used, their
specificity is low, thus urgently calling for methods for prioritizing and
characterizing variants. OBJECTIVE: To assess the frequency of VUSs in genes
causing endocrine and metabolic disorders, the concordance rate of predictions
from different in silico methods, and the added value of three-dimensional
protein structure analysis in discerning and prioritizing damaging variants.
RESULTS: A total of 12,266 missense variants reported in 641 genes causing
endocrine and metabolic disorders were analyzed. Among these, 4123 (33.7%) were
VUSs, of which 2010 (48.8%) were predicted to be damaging and 1452 (35.2%) were
predicted to be tolerated according to in silico tools. A total of 5383 (87.7%)
of 6133 disease-causing variants and 823 (55.8%) of 1474 benign variants were
correctly predicted. In silico predictions were noninformative in 5.7%, 14.4%,
and 16% of damaging, benign, and VUSs, respectively. A damaging effect on 3D
protein structure was present in 240 (30.9%) of predicted damaging and 40 (9.7%)
of predicted tolerated VUSs (P < 0.001). An in-depth analysis of nine VUSs
occurring in TSHR, LDLR, CASR, and APOE showed that they greatly affect protein
stability and are therefore strong candidates for disease. CONCLUSIONS: In our
dataset, we confirmed the high sensitivity but low specificity of in silico
predictions tools. 3D protein structural analysis is a compelling tool for
characterizing and prioritizing VUSs and should be a part of genetic variant
analysis.
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