Research Paper Volume 5, Issue 5 pp 373—385
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
- 1 DIMES - Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, 40126 Italy
- 2 C.I.G. Interdepartmental Center “L. Galvani”, University of Bologna, Bologna, Italy
- 3 CRBA - Applied Biomedical Research Center, S. Orsola-Malpighi Polyclinic, Bologna, 40138 Italy
- 4 Department of Biological, Geological and Environmental Sciences, Laboratory of Molecular Anthropology & Centre for Genome Biology, University of Bologna, Bologna 40126, Italy
- 5 Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy
- 6 Center of Clinical Pathology and Innovative Therapy, Italian National Research Center on Aging INRCA-IRCCS, Ancona, Italy
- 7 Geriatric Unit IRCCS Ca' Granda Foundation Maggiore Policlinico Hospital Hospital and Department of Clinical Sciences and Community Health, University of Milano, Italy
- 8 Department of Cell Biology, University of Calabria, Rende, Italy
- 9 Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, Italy
- 10 Metabolic Diseases and Diabetology Unit, IRCCS-INRCA, Ancona, Italy
- 11 Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- 12 Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
- 13 Department of Cardiovascular and Metabolic Diseases, IRCCS Gruppo Multimedica Sesto San Giovanni (MI), Italy
- 14 IAC-CNR Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerche, Rome, Italy
- 15 Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- 16 Department of Medicine, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- 17 Institute for Aging Research, Diabetes Research and Training Center, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- 18 Institute of Aging Research, Guangdong Medical College, Dongguan 523808, China
- 19 Personal Genomics SRL, Strada le Grazie 15, 37133 Verona - Italy
- 20 Functional Genomics Center, Dept. of Biotechnologies, University of Verona, Strada le Grazie 15, 37133 Verona - Italy
- 21 Experimental Models in Clinical Pathology, IRCCS-INRCA, Ancona, Italy
Received: May 17, 2013 Accepted: May 31, 2013 Published: May 31, 2013
https://doi.org/10.18632/aging.100562How to Cite
Abstract
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 allelic/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.