Giuliani Cristina, Sazzini Marco, Pirazzini Chiara, Bacalini Maria Giulia, Marasco Elena, Ruscone Guido Alberto Gnecchi, Fang Fang, Sarno Stefania, Gentilini Davide, Di Blasio Anna Maria, Crocco Paolina, Passarino Giuseppe, Mari Daniela, Monti Daniela, Nacmias Benedetta, Sorbi Sandro, Salvarani Carlo, Catanoso Mariagrazia, Pettener Davide, Luiselli Donata, Ukraintseva Svetlana, Yashin Anatoliy, Franceschi Claudio, Garagnani Paolo
Department of Biological, Geological, and Environmental Sciences (BiGeA), Laboratory of Molecular Anthropology and Centre for Genome Biology, University of Bologna, Bologna, Italy.
School of Anthropology and Museum Ethnography, University of Oxford, Oxford, UK.
Aging (Albany NY). 2018 Aug 8;10(8):1947-1963. doi: 10.18632/aging.101515.
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 ( 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.
长寿遗传学的研究主要通过全基因组关联研究(GWASs)来进行,这些研究考虑了来自不同人群的受试者以获得更高的统计效力。“付出的代价”是,在基因与环境相互作用的研究中,特定人群的进化历史和权衡被忽视了。我们提出了一种新的“历时性”方法,该方法考虑了在进化和寿命时间尺度上发生的过程。我们聚焦于一个在进化历史方面特征明确的人群(意大利人),并为来自半岛的333名百岁老人和773名地理匹配的健康个体生成了全基因组数据。获得的结果表明:(i)百岁老人的基因组富含可能由新石器时代前的迁徙塑造的祖先成分;(ii)出生在意大利北部的百岁老人意外地与来自意大利中部/南部的对照组聚集在一起,这表明新石器时代和青铜时代的基因流动对该人群的长寿没有促进作用;(iii)过去针对病原体并靶向花生四烯酸代谢的局部适应性事件对长寿变得有利;(iv)几个等位基因频率的终身变化揭示了对长寿至关重要的多效性和权衡机制。因此,我们提出,为了识别与长寿相关的基因,需要适当考虑人口统计学历史以及古代/近代的人口动态,这些基因在不同的时间/空间背景下可能会有所不同。