Next Generation Sequencing Could Dramatically Impact Life Expectancy
A Centers for Disease Control website provides a definition for life expectancy as “the average number of years that a hypothetical group of infants would live at each attained age if the group was subject, throughout its lifetime, to the age-specific death rates prevailing for the actual population in a given year” (1). It is essentially the time a person or other organism is expected to live based on a number of factors, such as date of birth, sex, and others. Life expectancy has been impacted over the years due to changes in the environment, health delivery options, and more. New information, such as that afforded by data obtained using new biomedical technologies such as next-generation sequencing (NGS), has the potential to positively impact the world population’s life expectancy.
Contributors to Longer Life Expectancy
There are many factors that impact life expectancy including race, sex, geographical location, and even income levels. How and why these factors impact life expectancy and health are rigorously studied. For instance, issues of income level affect access to health care, healthy diets, and other factors that affect an individual’s health, and thus mortality. The same applies to race and the relationship to race-based health disparities. In general, various health-changing and modifying factors greatly contribute to changes in human life expectancy.
Perhaps the most important factors in the global increase in life expectancy have been efforts affecting infectious disease incidence. One of the effects of the eradication of or provision of successful treatments for infectious disease is the increase in infant survival (2). Eliminating diseases such as smallpox, rinderpest, and polio from most parts of the world drastically increased life expectancy from that seen during the 18th through 20th centuries.
Health and safety policies developed and adopted by governments, work places, etc. affect life expectancy by providing guidelines and protocols designed to prevent accidents or unsafe exposures to toxicants, infectious organisms, and other life or health-threatening agents. However, given the knowledge regarding the leading causes of death globally (cardiovascular and respiratory diseases) (3) allows the design and implementation of disease-prevention programs and guidance. Gains in the medical arena to affect the leading causes of death will further improve human life expectancy.
Advances in Personalized Medicine
The emergence and refinement of personalized medicine approaches have and continue to demonstrate the ability to better address chronic and other diseases in ways previously difficult to attain. Better understanding of a patient’s biological makeup has been achieved with the advent of NGS and its application to clinical medicine and research. The massively-parallel sequencing technology has provided unprecedented volumes of actionable genomic information proving useful in medical diagnostics and therapeutics. The accessible costs have also been a factor in the ability to rapidly obtain comprehensive genomic and genetic information.
Healthcare providers can use analyzed NGS data to design personalized therapeutics based on a patient’s genomic profile and other information. This is demonstrated by a case of a person with acute lymphoblastic leukemia who was unresponsive to chemotherapy or bone transplant. With NGS data, overexpression of the FLT3 gene was revealed, and the person achieved remission that has remained for the past 4 years with treatment using an FLT3 inhibitor, sunitinib (4).
NGS and Longevity Research
Next-generation sequencing data helped to show that women with specific BRCA1 or BRCA2 gene mutations can have a higher chance of developing breast cancer by age 70 than the general population of women (5). Determining disease risk for individual patients provides opportunities to implement preventive measures. Women with higher risk factors can choose to undergo additional screening, chemoprevention, or prophylactic surgery.
In addition to studies addressing disease prevention and treatment to improve quality and length of life, NGS is also being applied to research the aging process. Next-generation sequencing data has provided information regarding genes related to human longevity. In a study of the genomes of super-centenarians, Sebastiani et al. identified variants that may be linked to longevity (6). A genomics technology company, Human Longevity, Inc., has embarked on a project with the objective to develop a large database of genomic data that may be used to identify risk factors and means to change age-related disease risk using the knowledge gained.
Medical advances are major factors that contribute to increased life expectancy. Next-generation sequencing plays a valuable role in searching for and identifying genomic-level factors that can be applied to medical approaches and efforts that improve health, thereby positively affecting longevity. This can lead to a lowering of mortality rates associated with disease and improvement of life expectancy that can be manifested at the global level.
- Elizabeth, A. (2016, April 20). Changes in Life Expectancy by Race and Hispanic Origin in the United States, 2013–2014. Retrieved from https://www.cdc.gov/nchs/products/databriefs/db244.htm
- Andre FE, Booy R, Bock HL, Clemens J, Datta SK, John TJ, Lee BW, Lolekha S, Peltola H, Ruff TA, Santosham M, Schmitt HJ. Vaccination greatly reduces disease, disability, death and inequity worldwide. Bull World Health Organ. 2008 Feb;86(2):140-6. Review.
- GBD 2013 Mortality and Causes of Death Collaborators.. Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study Lancet. 2015 Jan 10;385(9963):117-71.
- Griffith M, Griffith OL, Krysiak K, Skidmore ZL, Christopher MJ, Klco JM, Ramu A, Lamprecht TL, Wagner AH, Campbell KM, Lesurf R, Hundal J, Zhang J, Spies NC, Ainscough BJ, Larson DE, Heath SE, Fronick C, O’Laughlin S, Fulton RS, Magrini V, McGrath S, Smith SM, Miller CA, Maher CA, Payton JE, Walker JR, Eldred JM, Walter MJ, Link DC, Graubert TA, Westervelt P, Kulkarni S, DiPersio JF, Mardis ER, Wilson RK, Ley TJ. Comprehensive genomic analysis reveals FLT3 activation and a therapeutic strategy for a patient with relapsed adult B-lymphoblastic leukemia. Exp Hematol. 2016 Jul;44(7):603-13.
- Antoniou A, Pharoah PD, Narod S, et al. Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: A combined analysis of 22 studies. American Journal of Human Genetics 2003; 72(5):1117–1130.
- Sebastiani P, Riva A, Montano M, Pham P, Torkamani A, Scherba E et al (2011) Whole genome sequences of a male and female supercentenarian, ages greater than 114 years. Front Genet 2:90.
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