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Showing 1–4 of 4 results

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Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations

A proteomic aging clock, developed using data from the UK Biobank and validated using data from the China Kadoorie Biobank and FinnGen, predicts the incidence of 18 major chronic diseases, as well as multimorbidity and all-cause mortality.

M. Austin Argentieri
Sihao Xiao
Cornelia M. van Duijn
ResearchOpen Access08 Aug 2024
Nature Medicine

Volume: 30, P: 2450-2460
Author Correction: FinnGen provides genetic insights from a well-phenotyped isolated population

Mitja I. Kurki
Juha Karjalainen
Aarno Palotie
Amendments and CorrectionsOpen Access24 Feb 2023
Nature

Volume: 615, P: E19
FinnGen provides genetic insights from a well-phenotyped isolated population

Genome-wide association studies of individuals from an isolated population (data from the Finnish biobank study FinnGen) and consequent meta-analyses facilitate the identification of previously unknown coding variant associations for both rare and common diseases.

Mitja I. Kurki
Juha Karjalainen
Aarno Palotie
ResearchOpen Access18 Jan 2023
Nature

Volume: 613, P: 508-518
Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker

Here the authors show that deep learning accurately predicts one-year mortality using nationwide Finnish data. Despite robust performance and potential as an aging marker, fairness analyses reveal prediction disparities, urging cautious integration into public health.

Andrius Vabalas
Tuomo Hartonen
Andrea Ganna
ResearchOpen Access24 Jun 2024
Nature Aging

Volume: 4, P: 1014-1027