Aging
Navigate
Submit an Article
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

Paolo Garagnani1,2,3, Cristina Giuliani4, Chiara Pirazzini1,2, Fabiola Olivieri5,6, Maria Giulia Bacalini1,2, Rita Ostan1,2, Daniela Mari7, Giuseppe Passarino8, Daniela Monti9, Anna Rita Bonfigli10, Massimo Boemi10, Antonio Ceriello11,12, Stefano Genovese13, Federica Sevini1,2, Donata Luiselli4, Paolo Tieri14, Miriam Capri1,2, Stefano Salvioli1,2, Jan Vijg15,17, Yousin Suh15,16,17,18, Massimo Delledonne19,20, Roberto Testa21, Claudio Franceschi1
  • 1DIMES - Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, 40126 Italy
  • 2C.I.G. Interdepartmental Center “L. Galvani”, University of Bologna, Bologna, Italy
  • 3CRBA - Applied Biomedical Research Center, S. Orsola-Malpighi Polyclinic, Bologna, 40138 Italy
  • 4Department of Biological, Geological and Environmental Sciences, Laboratory of Molecular Anthropology & Centre for Genome Biology, University of Bologna, Bologna 40126, Italy
  • 5Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy
  • 6Center of Clinical Pathology and Innovative Therapy, Italian National Research Center on Aging INRCA-IRCCS, Ancona, Italy
  • 7Geriatric Unit IRCCS Ca' Granda Foundation Maggiore Policlinico Hospital Hospital and Department of Clinical Sciences and Community Health, University of Milano, Italy
  • 8Department of Cell Biology, University of Calabria, Rende, Italy
  • 9Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, Italy
  • 10Metabolic Diseases and Diabetology Unit, IRCCS-INRCA, Ancona, Italy
  • 11Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
  • 12Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
  • 13Department of Cardiovascular and Metabolic Diseases, IRCCS Gruppo Multimedica Sesto San Giovanni (MI), Italy
  • 14IAC-CNR Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerche, Rome, Italy
  • 15Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
  • 16Department of Medicine, Albert Einstein College of Medicine, Bronx, NY 10461, USA
  • 17Institute for Aging Research, Diabetes Research and Training Center, Albert Einstein College of Medicine, Bronx, NY 10461, USA
  • 18Institute of Aging Research, Guangdong Medical College, Dongguan 523808, China
  • 19Personal Genomics SRL, Strada le Grazie 15, 37133 Verona - Italy
  • 20Functional Genomics Center, Dept. of Biotechnologies, University of Verona, Strada le Grazie 15, 37133 Verona - Italy
  • 21Experimental Models in Clinical Pathology, IRCCS-INRCA, Ancona, Italy

* * Equal contribution

Received: May 17, 2013Accepted: May 31, 2013Published: May 31, 2013
https://doi.org/10.18632/aging.100562

Copyright: © 2013 Garagnani et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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.