title: Predicting Survival from Telomere Length versus Conventional Predictors: A Multinational Population-Based Cohort Study.
abstract: Telomere length has generated substantial interest as a potential predictor of aging-related diseases and mortality. Some studies have reported significant associations, but few have tested its ability to discriminate between decedents and survivors compared with a broad range of well-established predictors that include both biomarkers and commonly collected self-reported data. Our aim here was to quantify the prognostic value of leukocyte telomere length relative to age, sex, and 19 other variables for predicting five-year mortality among older persons in three countries. We used data from nationally representative surveys in Costa Rica (N = 923, aged 61+), Taiwan (N = 976, aged 54+), and the U.S. (N = 2672, aged 60+). Our study used a prospective cohort design with all-cause mortality during five years post-exam as the outcome. We fit Cox hazards models separately by country, and assessed the discriminatory ability of each predictor. Age was, by far, the single best predictor of all-cause mortality, whereas leukocyte telomere length was only somewhat better than random chance in terms of discriminating between decedents and survivors. After adjustment for age and sex, telomere length ranked between 15th and 17th (out of 20), and its incremental contribution was small; nine self-reported variables (e.g., mobility, global self-assessed health status, limitations with activities of daily living, smoking status), a cognitive assessment, and three biological markers (C-reactive protein, serum creatinine, and glycosylated hemoglobin) were more powerful predictors of mortality in all three countries. Results were similar for cause-specific models (i.e., mortality from cardiovascular disease, cancer, and all other causes combined). Leukocyte telomere length had a statistically discernible, but weak, association with mortality, but it did not predict survival as well as age or many other self-reported variables. Although telomere length may eventually help scientists understand aging, more powerful and more easily obtained tools are available for predicting survival.
authors.affiliation: Center for Population and Health, Georgetown University, Washington, District of Columbia, United States of America.
authors.forename: Dana A
authors.initials: DA
authors.lastname: Glei
authors.affiliation: Office of Population Research, Princeton University, Princeton, New Jersey, United States of America.
authors.forename: Noreen
authors.initials: N
authors.lastname: Goldman
authors.affiliation: Department of Pathology, University of Washington, Seattle, Washington, United States of America.
authors.forename: Rosa Ana
authors.initials: RA
authors.lastname: Risques
authors.affiliation: Division of General Medical Disciplines, School of Medicine, Stanford University, Stanford, California, United States of America.
authors.forename: David H
authors.initials: DH
authors.lastname: Rehkopf
authors.affiliation: School of Public Health, University of California-Berkeley, Berkeley, California, United States of America.
authors.forename: William H
authors.initials: WH
authors.lastname: Dow
authors.affiliation: Centro Centroamericano de Población, Universidad de Costa Rica, San Jose, Costa Rica.
authors.forename: Luis
authors.initials: L
authors.lastname: Rosero-Bixby
authors.affiliation: Center for Population and Health, Georgetown University, Washington, District of Columbia, United States of America.
authors.forename: Maxine
authors.initials: M
authors.lastname: Weinstein
mesh_terms: D015331:Cohort Studies; D003364:Costa Rica; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D013624:Taiwan; D016615:Telomere; D014481:United States