Life expectancy is the time a person is expected to live based on a number of factors, including date of birth, sex, and the availability of health care services. Average life expectancy has changed over the years because of changes in the environment, health delivery options, and more.
New information afforded by advancements in next-generation sequencing has the potential to positively impact the world population’s life expectancy. In this article, we explore major contributors to increased life expectancy. We also discuss the emerging field of longevity research and how genetic information can add to that knowledge base.
Factors Increasing Life Expectancy
There are many factors that impact life expectancy. These include ethnicity, sex, geographical location, and the social determinants of health. For example, income level affects access to health care, healthy diets, vaccinations, and other factors affecting health and mortality. Life expectancy in the US has declined for the first time in a century, in large part because of the Covid-19 pandemic.
Infectious disease treatments
Perhaps the most important factor in the global increase in life expectancy is efforts affecting infectious disease incidence. Eradicating or providing treatments for infectious disease increases survival rates for vulnerable populations. Preventing infection or preparing the individuals’ immune systems to rapidly recognize and destroy the invading pathogen is highly effective at improving life expectancy. This is called vaccination.
Vaccination is a method of educating the immune system that specific proteins are “foreign” and should be destroyed. Vaccines can also target and destroy the cells that make these proteins.
In 2007, CDC researchers investigated morbidity and mortality rates before and after the widespread implementation of vaccination programs for 13 preventable diseases. Diseases like diphtheria, mumps, pertussis, and tetanus saw an over 99% decrease in mortality after vaccine program implementation. In 2022, the risk of dying from Covid-19 for vaccinated individuals was several times lower than for those who remained unvaccinated.
The supersonic development rate of SARS-CoV-2 vaccines was possible because of the adoption of mRNA-based vaccines. The 2023 Nobel Prize in Physiology or Medicine was awarded to Katalin Karikó and Drew Weissman, who jointly developed methods to stabilize RNA bases. mRNA-based vaccines have opened the gates to rapidly identify, develop, test, and apply vaccines against non-infectious diseases, including cancer.
Using next-generation sequencing technologies, including single-cell sequencing, we can identify genetic changes that contribute to tumor cell evolution and neoantigen production. Neoantigens are abnormal proteins made by tumor cells. Theoretically, they could serve as good vaccine targets since nearby healthy cells would be ignored. Since tumor cells are constantly changing, cancer vaccines would need to be identified, manufactured, and delivered to the individual patients within weeks of getting their biopsy results.
Excitingly, in a small study on head and neck cancers two patients (out of ten) showed complete responses to vaccination. Five others showed decreases in tumor size. Only NGS combined with mRNA-based vaccines can meet the rapid treatment timelines required for this unique example of precision medicine.
Advancements in precision medicine
The emergence of precision medicine demonstrates our ability to better address diseases. With the advent of NGS, clinicians can obtain a better understanding of a patient’s biological makeup. Massively-parallel sequencing technology has provided unprecedented volumes of actionable genomic information. Medical diagnostics and therapeutics benefit from these breakthrough technologies.
In the past, the cost of sequencing was a barrier to its widespread use for medical purposes. However, decreasing costs have been a factor in the ability to rapidly obtain comprehensive genomic information. Using NGS data, medical providers can design personalized therapeutics based on a patient’s genomic profile.
In this study, researchers from Washington University and St. Jude Children’s Hospital used NGS technologies on a patient with relapsed adult B-lymphoblastic leukemia (B-ALL). The team analyzed nine timepoints of data from whole genome, whole exome, and whole transcriptome assays to investigate the causes of B-ALL relapse.
With NGS data, they discovered overexpression of the FLT3 gene. The patient’s treatment was then updated to include the FLT3 inhibitor sunitinib. At the time the study was released, the patient had remained in remission for over four years.
Disease screening and risk assessment
Determining disease risk for individual patients provides opportunities to implement preventive measures. Next-generation sequencing data from over 8,000 individuals helped to show that women with specific BRCA1 or BRCA2 gene mutations have a higher chance of developing breast cancer by age 70 than the general population of women. Furthermore, women with BRCA1 mutations saw their risk of cancer decrease with age. The same is not true for women with BRCA2 mutations.
BRCA screenings are now commonly offered to women with high risk factors for breast or ovarian cancers. With this information, it’s possible to make more informed health decisions, such as chemoprevention or prophylactic surgery.
NGS and Longevity Research
In addition to its application in disease research, NGS is used to research the aging process. Scientists estimate the heritability of lifespan as falling somewhere between 12 and 25%. However, it is understood that aging is a complex interplay of factors.
Next-generation sequencing data has provided information regarding genes related to human longevity. The Human Ageing Genomic Resources (HAGR) has taken a systems biology approach to collect this massive amount of data on humans and model organisms. Using comparative genomics, we have identified genes that contribute to humans aging nearly 30 times slower than rats and mice.
Genomics technology company Human Longevity, Inc. has embarked on a project to help people “live to 100+.” The company has developed a large database of genomic data that may be used to identify disease risk factors. With the knowledge gained from this research, researchers would be able to address age-related disease risk with earlier diagnosis, improved treatments, and improved health outcomes.
Medical advancement is a major factor in increasing life expectancy. With NGS technologies, researchers have new tools to search for and identify genomic-level factors that can be applied to medical approaches. These discoveries will improve health and positively affect longevity.
Psomagen thanks Dr. Stacy Matthews Branch for her contributions to the research and writing of the original version of this article. Dr. Branch is a biomedical consultant, medical writer, and veterinary medical doctor. She owns Djehuty Biomed Consulting and has published research articles and book chapters in the areas of molecular, developmental, reproductive, forensic, and clinical toxicology. Dr. Matthews Branch received her DVM from Tuskegee University and her Ph.D. from North Carolina State University.
