Centenarians as super-controls to assess the biological relevance of genetic risk factors for common age-related diseases: A proof of principle on type 2 diabetes
Author(s) -
Paolo Garagnani,
Cristina Giuliani,
Chiara Pirazzini,
Fabiola Olivieri,
Maria Giulia Bacalini,
Rita Ostan,
Daniela Mari,
Giuseppe Passarino,
Daniela Monti,
Anna Rita Bonfigli,
Massimo Boemi,
Antonio Ceriello,
Stefano Genovese,
Federica Sevini,
Donata Luiselli,
Paolo Tieri,
Miriam Capri,
Stefano Salvioli,
Jan Vijg,
Yousin Suh,
Massimo Delledonne,
Roberto Testa,
Claudio Franceschi
Publication year - 2013
Publication title -
aging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 90
ISSN - 1945-4589
DOI - 10.18632/aging.100562
Subject(s) - relevance (law) , type 2 diabetes , proof of concept , medicine , diabetes mellitus , biology , bioinformatics , gerontology , computer science , endocrinology , political science , law , operating system
Genetic association studies of age-related, chronic human diseases often suffer from a lack of power to detect modest effects. Here we propose an alternative approach of including healthy centenarians as a more homogeneous and extreme control group. As a proof of principle we focused on type 2 diabetes (T2D) and assessed /genotypic associations of 31 SNPs associated with T2D, diabetes complications and metabolic diseases and SNPs of genes relevant for telomere stability and age-related diseases. We hypothesized that the frequencies of risk variants are inversely correlated with decreasing health and longevity. We performed association analyses comparing diabetic patients and non-diabetic controls followed by association analyses with extreme phenotypic groups (T2D patients with complications and centenarians). Results drew attention to rs7903146 (TCF7L2 gene) that showed a constant increase in the frequencies of risk genotype (TT) from centenarians to diabetic patients who developed macro-complications and the strongest genotypic association was detected when diabetic patients were compared to centenarians (p_value = 9.066*10⁻⁷). We conclude that robust and biologically relevant associations can be obtained when extreme phenotypes, even with a small sample size, are compared.
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