An Evolutionary Perspective on Single-Nucleotide Polymorphism Screening in Molecular Cancer Epidemiology

Abstract

Given that there are millions of single-nucleotide polymorphisms (SNPs) in the entire human genome, a major difficulty faced by scientists in planning costly population-based genotyping is to choose target SNPs that are most likely to affect phenotypic functions and ultimately contribute to disease development. Although it is widely accepted that sequences with important functionality tend to be less variable across species because of selective pressure, to what extent evolutionary conservation is mirrored by epidemiological outcome has never been demonstrated. In this study, we surveyed odds ratios detected for 46 SNPs in 39 different cancer-related genes from 166 molecular epidemiological studies. The conservation levels of amino acid that these SNPs affected were calculated as a tolerance index by comparing sequences from different species. Our results provide evidence of a significant relationship between the detected odds ratios associated with cancer risk and the conservation levels of the SNP-affected amino acids (P ‫؍‬ 0.002; R 2 ‫؍‬ 0.06). Tolerance indices were further calculated for 355 nonsynonymous SNPs identified in 90 human DNA repair genes, of which 103 caused amino acid changes in very conserved positions. Our findings support the concept that SNPs altering the conserved amino acids are more likely to be associated with cancer susceptibility. Using such a molecular evolutionary approach may hold great promise for prioritizing SNPs to be genotyped in future molecular epidemiological studies.

Correlating observed odds ratios from lung cancer case–control studies to SNP functional scores predicted by bioinformatic tools

“…Our findings are congruent with our previous observations, which demonstrated that SNPs altering conserved amino acids assessed by the SIFT tool are more likely to be associated with cancer risk [12]. The current study expanded on the previous analysis in three important ways, resulting in more meaningful and interpretable results.…”

Polymorphisms of cytosolic serine hydroxymethyltransferase and risk of lung cancer: A case–control analysis

“…The SNPs altering the conserved amino acids, i.e., non-synonymous SNPs, are more likely to be associated with cancer susceptibility and thus often recommended for their inclusion in association studies [30][31][32][33]. However, other types of SNPs may also have an impact on gene functions at the transcription level through modulating its mRNA amount, such as those SNPs that are located in the promoter and 3′-untranslated region, i.e., the regulatory SNPs.…”

Comparative genomics analysis of human sequence variation in the UGT1A gene cluster

“…48 To increase the sensitivity of the algorithm, some have altered the threshold score for declaring functional significance from 0.05 to 0.1. 30,46,49 This choice is supported by the UGT1A1*6 (G71R) variant, which has been shown to influence serum bilirubin levels in several independent studies 9,10,50-57 although it has a SIFT score of 0.1. If the SIFT algorithm identifies functional variants and these variants have deleterious effects on the phenotype, the predicted functional variants should occur at lower frequencies compared to non-functional, neutrally evolving variants.…”