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Longevity is increasing: Can we extend our lifespan, one gene at a time?

Since the death of 116-year-old Susannah Mushatt Jones of the United States in May 2016, Italy’s Emma Morano is now the oldest living person in the world whose age can be documented. Morano is also the only living person on earth to have been born in the 1800s.

The longest human lifespan, also by a woman, is thought to be that of Jeanne Calment of France (1875–1997), who died at 122 years, 164 days.

Females generally live longer than males, but why anyone lives longer remains a genetic mystery.

Longevity and healthy aging are among the most complex traits studied in the fields of genetics and epidemiology. Longevity can be defined as individual’s ability to live longer under perfect and relatively fine environments. Lifespan varies greatly among human societies. Life expectancy ranging from 47.5, 79.8 and 87.2 years, in Sierra Leone, the United States and Monaco, respectively. The median for human population is 71.3, according to the World Health Statistics.

The good news: there has been a dramatic increase in average life expectancy over the past century and the life expectancy at birth index is increasing, meaning that our kids have a good chance of living longer than the present day parents. The bad news: understanding this extremely complex traits that are determined and shaped by environment, life style and genetics is still in infancy. Several large scale experiments measuring several variables such as effects of levels of activity, ethnicity, stress levels, and common disease status concurrently have been attempted in the recent years. Whereas there are definitely environmental factors that influence longevity such as diet, level of exercise and stress, geneticists for years were interested in solving this conundrum relying solely on information within the genome.

In a recent study conducted by researchers at University of Cambridge, Drosophila melanogaster Genetic Reference Panel was used to detect the locations within the genome that greatly influence for longevity. The objective was to measure the influence of genetic variants, alleles on lifespans in a highly controlled environment. So far, several genes susceptible to disease have been detected less so than longevity genes. Studies performed on model organisms such as flies, yeast and mice could shed light onto the natural variants that predispose longevity in humans. Furthermore they allow for controlled environments eliminating factors that might cloud results.

In this particular study several new variants within the genome have been isolated but they will have to be tested to determine their effect upon aging and longevity. This multifaceted whole genome sequencing approach to longevity is likely a step in the right direction to understanding this complex trait. More experiments are of course instrumental to validate the current findings; nevertheless whole genome sequencing, coupled with large numbers of participants and multiple generations of people will likely yield some fruitful insights. These recent technologies allow scientists to sequence DNA and RNA quicker and cheaper than ever before, and, hence, have revolutionized the study of genomics and molecular biology.

Genome wide association studies (GWAS) have been a powerful tool to identify the genetic origin of other complex outcomes with a similar heritability to that of longevity. In GWAS, the genome is searched for small variations, called single nucleotide polymorphisms, that occur more frequently in people with a particular condition than in the rest of population. In longevity studies, that condition is living to a certain age. Given the findings of all GWAS of longevity conducted to date the only consistent association emerging from the data is the APOE gene that has been already identified as a candidate gene in the study of Alzheimer’s. Although GWAS have identified genes and pathways of biological relevance, unfortunately no new variants for longevity have been conclusively proven in humans.

A reason for not finding any replicated associations for longevity could be the high number of genes influencing this trait. Interestingly though heterogeneity also underlies many other traits for which GWAS has been successful. In the age of big data science, it is highly likely that in the near future, joining large data-sets may bring to the surface new causative determinants of living longer. In model organisms it has been possible to demonstrate effects of mutations in genes that can extend lifespan nearly tenfold. As exciting as this appears, there is a bridge missing between translatable and applicable findings to extending lifespan with former making biological sense and latter allowing for detectable improvements in lifespan for individuals.

Clearly human lifespan is influenced not only by composition of longevity genes that promote healthy aging and not having disease susceptibility variants but also by the environment, gene–environment interactions, and of course chance. Non-genetic factors, particularly lifestyle, clearly affect the development of age-related diseases and health and lifespan in the general population.

To fully understand the desirable phenotypes of healthy aging and longevity all these factors have to be taken into account. Maybe instead of having genetic protection longevity is the result of not having susceptibility to some of the common disorders–these being cancer, cardiovascular disease, dementia, hypertension, osteoporosis and stroke. From a genetic standpoint the causes of the 40 percent of heritability of living to at least 100 are still unknown. Within that 40 percent lies the potential to extending lifespan.

Sandra Smieszek is a postdoctoral fellow in the Department of Epidemiology and Biostatistics at the Institute of Computational Biology. Her research focuses on translating biomedical ‘big data’ with the aim of elucidating the genetic underpinnings of complex traits and disorders with emphasis on Alzheimer’s, HIV, and autism. She is additionally conducting research in the area of Food Security. Follow her at @S108801S.

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