Polygenic markers of survival and longevity in the antioxidant genes PON1, PON2, MTHFR, MSRA, SOD1, NQO1, and CAT in a 20-year follow-up study in the population from the Volga-Ural region

BACKGROUND

Genetic background of healthy or pathological styles of aging and human lifespan is determined by joint gene interactions. Lucky combinations of antioxidant gene polymorphisms can result in a highly adaptive phenotype, providing a successful way to interact with external triggers. Our purpose was to identify the polygenic markers of survival and longevity in the antioxidant genes among elderly people with physiological and pathological aging.

METHODS

In a 20-year follow-up study of 2350 individuals aged 18-114 years residing in the Volga-Ural region of Russia, sex-adjusted association analyses of MTHFR rs1801133, MSRA rs10098474, PON1 rs662, PON2 rs7493, SOD1 rs2070424, NQO1 rs1131341 and CAT rs1001179 polymorphic loci with longevity were carried out. Survival analysis was subsequently performed using the established single genes and gene-gene combinations as cofactors.

RESULTS

The PON1 rs662*G allele was defined as the main longevity marker in women (OR = 1.44, p = 3E-04 in the log-additive model; HR = 0.77, p = 1.9E-04 in the Cox-survival model). The polymorphisms in the MTHFR, MSRA, PON2, SOD1, and CAT genes had an additive effect on longevity. A strong protective effect of combined MTHFR rs1801133*C, MSRA rs10098474*T, PON1 rs662*G, and PON2 rs7493*C alleles against mortality was obtained in women (HR = 0.81, p = 5E-03). The PON1 rs662*A allele had a meaningful impact on mortality for both long-lived men with cerebrovascular accidents (HR = 1.76, p = 0.027 for the PON1 rs662*AG genotype) and women with cardiovascular diseases (HR = 1.43, p = 0.002 for PON1 rs662*AA genotype). The MTHFR rs1801133*TT (HR = 1.91, p = 0.036), CAT rs1001179*TT (HR = 2.83, p = 0.031) and SOD1 rs2070424*AG (HR = 1.58, p = 0.018) genotypes were associated with the cancer mortality.

CONCLUSION

In our longitudinal 20-year study, we found the combinations of functional polymorphisms in antioxidant genes involved in longevity and survival in certain clinical phenotypes in the advanced age.

Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes

We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, P_FDR = 3.40 × 10^-5), CCR5 rs333 (OR = 1.99, P_FDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, P_FDR = 2.64 × 10^-4), TCF7L2 rs114758349 (OR = 1.77, P_FDR = 9.37 × 10^-5), and CCL2 rs1024611 (OR = 1.38, P_FDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10^-6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.