Evolutionary genetic bases of longevity and senescence

Low Risk for Developing Diabetes Among the Offspring of Individuals With Exceptional Longevity and Their Spouses

Little is known about the risk of type 2 diabetes (T2D) among the offspring of individuals with exceptional longevity. We determined the incidence of and potential risk and protective factors for T2D among the offspring of probands and offspring’s spouses (mean age=60 years, range 32-88 years) in the Long Life Family Study (LLFS), a multicenter cohort study of 583 two-generation families with a clustering of healthy aging and exceptional longevity. Incident T2D was defined as fasting serum glucose ≥126 mg/dl, or HbA1c of ≥6.5%, or self-reported with doctor diagnosis of T2D, or the use of anti-diabetic medication during a mean follow-up 7.9 ± 1.1 years. Among offspring (n=1105) and spouses (n=328) aged 45-64 years without T2D at baseline visit, the annual incident rate of T2D was 3.6 and 3.0 per 1000 person-years, respectively, while among offspring (n=444) and spouses (n=153) aged 65+ years without T2D at baseline, the annual incident rate of T2D was 7.2 and 7.4 per 1000 person-years, respectively. By comparison, the annual incident rate of T2D per 1000 person-years in the U.S. general population was 9.9 among those aged 45-64, and 8.8 among those aged 65+ years (2018 National Health Interview Survey). Baseline BMI, waist circumference, and fasting serum triglycerides were positively associated with incident T2D, whereas fasting serum HDL-C, adiponectin, and sex hormone binding globulin were protective against incident T2D among the offspring (all P<0.05). Similar associations were observed among their spouses (all P<0.05, except sex hormone binding globulin). In addition, we observed that among spouses, but not offspring, fasting serum interleukin 6 and insulin-like growth factor 1 were positively associated with incident T2D (P<0.05 for both). Our study suggests that both offspring of long-living individuals and their spouses, especially middle-aged, share a similar low risk for developing T2D as compared with the general population. Our findings also raise the possibility that distinct biological risk and protective factors may contribute to T2D risk among offspring of long-lived individuals when compared with their spouses. Future studies are needed to identify the mechanisms underlying low T2D risk among the offspring of individuals with exceptional longevity, and also among their spouses.

Genetic and epigenetic Muller's ratchet as a mechanism of frailty and morbidity during aging: a demographic genetic model

Mutation accumulation has been proposed as a cause of senescence. During this process, age-related genetic and epigenetic mutations steadily accumulate. Cascading deleterious effects of mutations might initiate a steady "accumulation of deficits" in cells, despite the existence of repair mechanisms, leading to cellular senescence and functional decline of tissues and organs, which ultimately manifest as frailty and disease. Here, we investigate several of these aspects in differentiating cell populations through modeling and simulation using the Moran birth-death (demographic) process, under several scenarios of mutation accumulation. Deleterious mutations seem to rapidly accumulate particularly early in the course of life, during which the rate of cell division is high, thereby exerting a greater effect on subsequent cellular senescence. Our results are compatible with the principle of the Muller's ratchet taking place in asexually reproducing organisms. The ratchet speed in a given tissue depends on the size of the cell population, mutation rate and the impact of such mutations on cell phenotypes. It varies substantially among cells in different tissues and organs due to heterogeneity in relation to cell and organ-specific demographic features. Ratchet accelerates particularly after middle age, resulting in a synergistic fitness decay at the level of cell populations. We extend Fisher's average excess concept and rank order scale to interpret differential phenotypic effects of the increase of the mutation load among cell populations within a given tissue. We postulate that classical evolutionary genetic models can explain, at least in part, the origins of frailty, subclinical conditions, morbidity and the health consequences of senescence.

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

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.

Adaptation to temperature stress by Vibrio fischeri facilitates this microbe's symbiosis with the Hawaiian bobtail squid (Euprymna scolopes)

For microorganisms cycling between free-living and host-associated stages, where reproduction occurs in both of these lifestyles, an interesting inquiry is whether adaptation to stress during the free-living stage can impact microbial fitness in the host. To address this topic, the mutualism between the Hawaiian bobtail squid (Euprymna scolopes) and the marine bioluminescent bacterium Vibrio fischeri was utilized. Using microbial experimental evolution, V. fischeri was selected to low (8°C), high (34°C), and fluctuating temperature stress (8°C/34°C) for 2000 generations. The temperatures 8°C and 34°C were the lower and upper growth limits, respectively. V. fischeri was also selected to benign temperatures (21°C and 28°C) for 2000 generations, which served as controls. V. fischeri demonstrated significant adaptation to low, high, and fluctuating temperature stress. V. fischeri did not display significant adaptation to the benign temperatures. Adaptation to stressful temperatures facilitated V. fischeri's ability to colonize the squid host relative to the ancestral lines. Bioluminescence levels also increased. Evolution to benign temperatures did not manifest these results. In summary, microbial adaptation to stress during the free-living stage can promote coevolution between hosts and microorganisms.

Symbiont evolution during the free-living phase can improve host colonization

For micro-organisms cycling between free-living and host-associated stages, where reproduction occurs in both of these lifestyles, an interesting inquiry is whether evolution during the free-living stage can be positively pleiotropic to microbial fitness in a host environment. To address this topic, the squid host Euprymna tasmanica and the marine bioluminescent bacterium Vibrio fischeri were utilized. Microbial ecological diversification in static liquid microcosms was used to simulate symbiont evolution during the free-living stage. Thirteen genetically distinct V. fischeri strains from a broad diversity of ecological sources (e.g. squid light organs, fish light organs and seawater) were examined to see if the results were reproducible in many different genetic settings. Genetic backgrounds that are closely related can be predisposed to considerable differences in how they respond to similar selection pressures. For all strains examined, new mutations with striking and facilitating effects on host colonization arose quickly during microbial evolution in the free-living stage, regardless of the ecological context under consideration for a strain’s genetic background. Microbial evolution outside a host environment promoted host range expansion, improved host colonization for a micro-organism, and diminished the negative correlation between biofilm formation and motility.

Apolipoprotein E gene in physiological and pathological aging

INTRODUCTION

The genetic background plays a role on longevity. The distribution of the apolipoprotein E gene (APOE) variants (ε2, ε3, ε4) may differ across age groups, especially in the oldest old and despite geographical and ethnic specificities. Since the ε4 variant is associated with Alzheimer's disease (AD), it might represent an opportunity for exploring the relationship of APOE with physiological and pathological aging.

AIM

To explore the role played by APOE genotype/alleles on physiological and pathological brain aging.

MATERIALS AND METHODS

The study was conducted in a cohort of centenarians (n = 106), and two cohorts of octogenarians (without cognitive decline, n = 351 controls; and with AD, n = 294).

RESULTS

No significant differences in genotype/allele distributions were observed comparing controls to centenarians. The prevalence of ε2/ε3, ε3/ε3, ε3/ε4 and ε4/ε4 genotypes were significantly different in centenarians compared to AD. The prevalence of ε2 and ε3 alleles were significantly higher in centenarians, whereas the ε4 was less frequent. The ε4 allele was positively associated with AD, whereas a negative association was found for ε2 and ε3 alleles.

CONCLUSIONS

Our study indicates that ε4 allele is strongly associated with AD. APOE significantly affects AD risk, but apparently not longevity.

Genetic cartography of longevity in humans and mice: Current landscape and horizons

Aging is a complex and highly variable process. Heritability of longevity among humans and other species is low, and this finding has given rise to the idea that it may be futile to search for DNA variants that modulate aging. We argue that the problem in mapping longevity genes is mainly one of low power and the genetic and environmental complexity of aging. In this review we highlight progress made in mapping genes and molecular networks associated with longevity, paying special attention to work in mice and humans. We summarize 40 years of linkage studies using murine cohorts and 15 years of studies in human populations that have exploited candidate gene and genome-wide association methods. A small but growing number of gene variants contribute to known longevity mechanisms, but a much larger set have unknown functions. We outline these and other challenges and suggest some possible solutions, including more intense collaboration between research communities that use model organisms and human cohorts. Once hundreds of gene variants have been linked to differences in longevity in mammals, it will become feasible to systematically explore gene-by-environmental interactions, dissect mechanisms with more assurance, and evaluate the roles of epistasis and epigenetics in aging. A deeper understanding of complex networks-genetic, cellular, physiological, and social-should position us well to improve healthspan.

Assortative Mating by Ethnicity in Longevous Families

Recent work shows strong evidence of ancestry-based assortative mating in spouse pairs of the older generation of the Framingham Heart Study. Here, we extend this analysis to two studies of human longevity: the Long Life Family Study (LLFS), and the New England Centenarian Study (NECS). In the LLFS, we identified 890 spouse pairs spanning two generations, while in the NECS we used data from 102 spouse pairs including offspring of centenarians. We used principal components of genome-wide genotype data to demonstrate strong evidence of ancestry-based assortative mating in spouse pairs of the older generation and also confirm the decreasing trend of endogamy in more recent generations. These findings in studies of human longevity suggest that spouses marrying into longevous families may not be powerful controls for genetic association studies, and that there may be important ethnicity-specific, genetic influences and/or gene–environment interactions that influence extreme survival in old generations. In addition, the decreasing trend of genetic similarity of more recent generations might have ramifications for the incidence of homozygous rare variants necessary for survival to the most extreme ages.

Application of Smart Infrastructure Systems approach to precision medicine

All biological variation is hierarchically organized dynamic network system of genomic components, organelles, cells, tissues, organs, individuals, families, populations and metapopulations. Individuals are axial in this hierarchy, as they represent antecedent, attendant and anticipated aspects of health, disease, evolution and medical care. Humans show individual specific genetic and clinical features such as complexity, cooperation, resilience, robustness, vulnerability, self-organization, latent and emergent behavior during their development, growth and senescence. Accurate collection, measurement, organization and analyses of individual specific data, embedded at all stratified levels of biological, demographic and cultural diversity - the big data - is necessary to make informed decisions on health, disease and longevity; which is a central theme of precision medicine initiative (PMI). This initiative also calls for the development of novel analytical approaches to handle complex multidimensional data. Here we suggest the application of Smart Infrastructure Systems (SIS) approach to accomplish some of the goals set forth by the PMI on the premise that biological systems and the SIS share many common features. The latter has been successfully employed in managing complex networks of non-linear adaptive controls, commonly encountered in smart engineering systems. We highlight their concordance and discuss the utility of the SIS approach in precision medicine programs.