SNP association study in PMS2-associated Lynch syndrome

Abstract

Lynch syndrome (LS) patients are at high risk of developing colorectal cancer (CRC). Phenotypic variability might in part be explained by common susceptibility loci identified in Genome Wide Association Studies (GWAS). Previous studies focused mostly on MLH1, MSH2 and MSH6 carriers, with conflicting results. We aimed to determine the role of GWAS SNPs in PMS2 mutation carriers. A cohort study was performed in 507 PMS2 carriers (124 CRC cases), genotyped for 24 GWAS SNPs, including SNPs at 11q23.1 and 8q23.3. Hazard ratios (HRs) were calculated using a weighted Cox regression analysis to correct for ascertainment bias. Discrimination was assessed with a concordance statistic in a bootstrap cross-validation procedure. Individual SNPs only had non-significant associations with CRC occurrence with HRs lower than 2, although male carriers of allele A at rs1321311 (6p21.31) may have increased risk of CRC (HR = 2.1, 95% CI 1.2–3.0). A polygenic risk score (PRS) based on 24 HRs had an HR of 2.6 (95% CI 1.5–4.6) for the highest compared to the lowest quartile, but had no discriminative ability (c statistic 0.52). Previously suggested SNPs do not modify CRC risk in PMS2 carriers. Future large studies are needed for improved risk stratification among Lynch syndrome patients.Electronic supplementary materialThe online version of this article (10.1007/s10689-017-0061-3) contains supplementary material, which is available to authorized users.

A common genetic variation in GZMB may associate with cancer risk in patients with Lynch syndrome

“…Nevertheless, studies leveraging these results to construct polygenic risk scores in this cohort are still scarce. However, a pioneering study in individuals with germline PMS2 mutations provided a rationale to investigate this matter more thoroughly ( 49 ). In anticipation of these studies we aimed to investigate if immunogenetic factors, specifically genetic variants of GrB might associate with cancer risk in LS.…”

A new inverse probability of selection weighted Cox model to deal with outcome-dependent sampling in survival analysis

“…The weight equation for censored individuals is given by Once weights v k , w k for each age interval I k , k = 1, …, K are calculated, the regression parameter β can be estimated using the following weighted score equation: where R ( t ij ) is the set of individuals that are still at risk just before t ij , i.e. R ( t ij ) = {l : t ij ≤ t l } , and weight a ij for individual ij ( i = 1, …, n j , j = 1, …, M ) is defined as A number of conditions are required to guarantee finite and positive weights w k and v k , namely: Conditions (7) and (9) are required to get valid w k weights for the cases, while conditions (8) and (10) are required to get valid v k weights for those that are censored. Condition (7) implies the observation of events in all the considered intervals and condition (8) implies the presence of right-censored observations in all considered intervals.…”

“…R ( t ij ) = {l : t ij ≤ t l } , and weight a ij for individual ij ( i = 1, …, n j , j = 1, …, M ) is defined as A number of conditions are required to guarantee finite and positive weights w k and v k , namely: Conditions (7) and (9) are required to get valid w k weights for the cases, while conditions (8) and (10) are required to get valid v k weights for those that are censored. Condition (7) implies the observation of events in all the considered intervals and condition (8) implies the presence of right-censored observations in all considered intervals. Conditions (9) and (10) are more difficult to interpret and evaluate beforehand, but they are both related to the level of oversampling of events.…”

“…When any of the conditions (7)-(10) are not satisfied, the weighted cohort method can still be applied by merging intervals, however the method becomes then less precise and dependent on sample specific characteristics which may hamper comparability among studies using this method.…”

Progress in Polygenic Composite Scores in Alzheimer’s and Other Complex Diseases

“…The most commonly used weight is the GWAS odds ratio (OR), or the univariate linear regression coefficient. Recent studies [1][2][3][4][5][6][7][8] have introduced the Cox-derived hazard ratio (HR) as alternative weight, to account for the time to event, which is otherwise ignored when using the GWAS-OR. Step 2) weight calculation: Candidate SNPs can be assigned a weight of 1 (PRS is a simple sum of SNP alleles) or weighed using existing GWAS-derived effect sizes.…”