Ensemble DNA methylation clock demonstrates Immune-metabolic Aging signatures associated with Mortality

Muthukumar Yugan Gogul, Karthikeyan Vijayakumar och Gwang-Won Cho presenterar en stacked survival model baserad på DNA-methylation-data från Framingham Heart Studie. Fem complementary survival models kombinerades med en neural-network meta-learner. The model used 190 CpG loci selected with elastic-net Cox regression och was externally validated i postmenopausal kvinnor aged 50 till 79 years. The reported performance exceeded PhenoAge och was statistically comparable till GrimAge. The fetched abstract does not give sample sizes, hazard ratios, confidence intervals, or discrimination statistics. This matters because a clock can predict mortality without being a modifiable cause of aging. The studie is useful for biomarker monitoring och for understanding immune-metabolic signatures, not for proving that an intervention changes lifespan. The training och validation populations also limit transportability. Both were demographically narrower than the general population, och the abstract specifically limits interpretation till demographically similar groups of European ancestry. A stronger model is not automatiskt a better treatment endpoint. Any intervention claim would still require prospective trials showing that clock movement tracks functional health, disease events, or survival.

These performance estimates were derived i cohorts of European ancestry och externally validated i postmenopausal kvinnor aged 50-79 years, och should therefore be interpreted as applicable only till demographically similar populations.