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Research Paper|Volume 10, Issue 8|pp 1947—1963

Impact of demography and population dynamics on the genetic architecture of human longevity

Cristina Giuliani1,2,3, Marco Sazzini1, Chiara Pirazzini4, Maria Giulia Bacalini4, Elena Marasco3,5,6, Guido Alberto Gnecchi Ruscone1, Fang Fang7, Stefania Sarno1, Davide Gentilini8, Anna Maria Di Blasio8, Paolina Crocco9, Giuseppe Passarino9, Daniela Mari10,11, Daniela Monti12, Benedetta Nacmias13, Sandro Sorbi13,14, Carlo Salvarani15,16, Mariagrazia Catanoso15, Davide Pettener1, Donata Luiselli17, Svetlana Ukraintseva7, Anatoliy Yashin7, Claudio Franceschi4,21, Paolo Garagnani5,18,19,20,21
  • 1Department of Biological, Geological, and Environmental Sciences (BiGeA), Laboratory of Molecular Anthropology and Centre for Genome Biology, University of Bologna, Bologna, Italy
  • 2School of Anthropology and Museum Ethnography, University of Oxford, Oxford, UK
  • 3Interdepartmental Center "L. Galvani," (CIG), University of Bologna, Bologna, Italy
  • 4IRCCS, Institute of Neurological Sciences of Bologna, Bologna, Italy
  • 5Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
  • 6Applied Biomedical Research Center (CRBA), S. Orsola-Malpighi Polyclinic, Bologna, Italy
  • 7Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27708, USA
  • 8Istituto Auxologico Italiano IRCCS, Cusano Milanino, Milan, Italy
  • 9Department of Biology, Ecology and Earth Sciences, University of Calabria, Rende, Italy
  • 10Geriatric Unit, Department of Medical Sciences and Community Health, Milan, Italy
  • 11Fondazione Ca' Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
  • 12Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
  • 13Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
  • 14IRCCS Don Gnocchi, Florence, Italy
  • 15Azienda Ospedaliera-IRCCS, Reggio Emilia, Italy
  • 16Department of Surgical, Medical, Dental and Morphological Sciences with Interest Transplant, Oncological and Regenerative Medicine, , Italy
  • 17Department for the Cultural Heritage (DBC), University of Bologna, Ravenna, Italy
  • 18Clinical Chemistry, Department of Laboratory Medicine, Karolinska Institutet at Huddinge University Hospital, S-141 86 Stockholm, Sweden
  • 19CNR Institute of Molecular Genetics, Unit of Bologna, Bologna, Italy
  • 20Rizzoli Orthopaedic Institute, Laboratory of Cell Biology, Bologna, Italy
  • 21Co-senior authors

* * Equal contribution

Received: July 20, 2018Accepted: July 26, 2018Published: August 8, 2018
https://doi.org/10.18632/aging.101515

Copyright: © 2018 Giuliani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The study of the genetics of longevity has been mainly addressed by GWASs that considered subjects from different populations to reach higher statistical power. The "price to pay" is that population-specific evolutionary histories and trade-offs were neglected in the investigation of gene-environment interactions. We propose a new “diachronic” approach that considers processes occurred at both evolutionary and lifespan timescales. We focused on a well-characterized population in terms of evolutionary history (i.e. Italians) and we generated genome-wide data for 333 centenarians from the peninsula and 773 geographically-matched healthy individuals. Obtained results showed that: (i) centenarian genomes are enriched for an ancestral component likely shaped by pre-Neolithic migrations; (ii) centenarians born in Northern Italy unexpectedly clustered with controls from Central/Southern Italy suggesting that Neolithic and Bronze Age gene flow did not favor longevity in this population; (iii) local past adaptive events in response to pathogens and targeting arachidonic acid metabolism became favorable for longevity; (iv) lifelong changes in the frequency of several alleles revealed pleiotropy and trade-off mechanisms crucial for longevity. Therefore, we propose that demographic history and ancient/recent population dynamics need to be properly considered to identify genes involved in longevity, which can differ in different temporal/spatial settings.