Biology subjects

Oliynyk, R. T.

Publications and source records attributed to Oliynyk, R. T..

2 recordsLinked to original sources

bioRxiv2018

Could future gene therapy prevent aging diseases?

BackgroundWithin the next few decades, gene therapy techniques and genetic knowledge may sufficiently advance to support prophylactic gene therapy to prevent polygenic late-onset diseases. A combination of a large number of common low effect gene variants offers the most likely explanation for the heritability of the majority of these diseases, and their risk may be lowered by correcting the effect of a subset of such gene variants.\n\nMethodsComputer simulations quantified the correlation between the aging process, polygenic risk score, and hazard ratio change with age, using as inputs clinical incidence rates and familial heritability, and estimated the outcomes of hypothetical future prophylactic gene therapy on the lifetime risk and age of onset for eight highly prevalent late-onset diseases.\n\nResultsThe simulation results confirmed that gene therapy would be beneficial in both delaying the age of onset and lowering the lifetime risk of the analyzed lateonset diseases. Longer life expectancy is associated with a higher lifetime risk of these diseases, and this tendency, while delayed, will continue after the therapy.\n\nConclusionsWhen the gene therapy as hypothesized here becomes possible, and if the incidences of the treated diseases follow the proportional hazards model with multiplicative genetic architecture composed of a sufficient number of common small effect gene variants, then (a) late-onset diseases with the highest familial heritability will have the largest number of variants available for editing, (b) diseases that currently have the highest lifetime risk, and particularly those with the highest incidence rate continuing into older ages, will prove the most challenging cases in which to lower lifetime risk and delay the age of onset at the populational level, and (c) diseases that are characterized by the lowest lifetime risk will show the strongest and longest-lasting response to such therapy.

genomics↗

bioRxiv2018

Age-related late-onset disease heritability patterns and implications for genome-wide association studies

BackgroundGenome-wide association studies and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called \"missing heritability\" problem.\n\nMethodsComputer simulations of polygenic late-onset diseases in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimers disease, coronary artery disease, cerebral stroke, and type 2 diabetes.\n\nResultsThe incidence rate for late-onset diseases grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for genome-wide association studies overrepresent older individuals with lower polygenic risk scores, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and genome-wide association studies. It also explains the relatively constant-with-age heritability found for late-onset diseases of lower prevalence, exemplified by cancers.\n\nConclusionsFor late-onset polygenic diseases showing high cumulative incidence together with high initial heritability, rather than using relatively old age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

genetics↗