How Well Does the Family Longevity Selection Score Work: A Validation Test Using the Utah Population Database

Evaluation of Family Characteristics and Multiple Hospitalizations at the End of Life: Evidence from the Utah Population Database

Background: Scant research has examined the relationship between family characteristics and end-of-life (EOL) outcomes despite the importance of family at the EOL. Objectives: This study examined factors associated with the size and composition of family relationships on multiple EOL hospitalizations. Design: Retrospective analysis of the Utah Population Database, a statewide population database using linked administrative records. Setting/subjects: We identified adults who died of natural causes in Utah, United States (n = 216,913) between 1998 and 2016 and identified adult first-degree family members (n = 743,874; spouses = 13.2%; parents = 3.6%; children = 51.7%; siblings = 31.5%). Measurements: We compared demographic, socioeconomic, and death characteristics of decedents with and without first-degree family. Using logistic regression models adjusting for sex, age, race/ethnicity, marital status, comorbidity, and causes of death, we examined the association of first-degree family size and composition, on multiple hospitalizations in the last six months of life. Results: Among decedents without documented first-degree family members in Utah (16.0%), 57.7% were female and 7 in 10 were older than 70 years. Nonmarried (aOR = 0.90, 95% CI = 0.88-0.92) decedents and decedents with children (aOR = 0.97, 95% CI = 0.94-0.99) were less likely to have multiple EOL hospitalizations. Family size was not associated with multiple EOL hospitalizations. Conclusions: First-degree family characteristics vary at the EOL. EOL care utilization may be influenced by family characteristics-in particular, presence of a spouse. Future studies should explore how the quality of family networks, as well as extended family, impacts other EOL characteristics such as hospice and palliative care use to better understand the EOL care experience.

Longevity Relatives Count score identifies heritable longevity carriers and suggests case improvement in genetic studies

Loci associated with longevity are likely to harbor genes coding for key players of molecular pathways involved in a lifelong decreased mortality and decreased/compressed morbidity. However, identifying such loci is challenging. One of the most plausible reasons is the uncertainty in defining long‐lived cases with the heritable longevity trait among long‐living phenocopies. To avoid phenocopies, family selection scores have been constructed, but these have not yet been adopted as state of the art in longevity research. Here, we aim to identify individuals with the heritable longevity trait by using current insights and a novel family score based on these insights. We use a unique dataset connecting living study participants to their deceased ancestors covering 37,825 persons from 1,326 five‐generational families, living between 1788 and 2019. Our main finding suggests that longevity is transmitted for at least two subsequent generations only when at least 20% of all relatives are long‐lived. This proves the importance of family data to avoid phenocopies in genetic studies.

Genetics of physiological dysregulation: findings from the long life family study using joint models

Recently, Mahalanobis distance (D_M) was suggested as a statistical measure of physiological dysregulation in aging individuals. We constructed D_M variants using sets of biomarkers collected at the two visits of the Long Life Family Study (LLFS) and performed joint analyses of longitudinal observations of D_M and follow-up mortality in LLFS using joint models. We found that D_M is significantly associated with mortality (hazard ratio per standard deviation: 1.31 [1.16, 1.48] to 2.22 [1.84, 2.67]) after controlling for age and other covariates. GWAS of random intercepts and slopes of D_M estimated from joint models found a genome-wide significant SNP (rs12652543, p=7.2×10^-9) in the TRIO gene associated with the slope of D_M constructed from biomarkers declining in late life. Review of biological effects of genes corresponding to top SNPs from GWAS of D_M slopes revealed that these genes are broadly involved in cancer prognosis and axon guidance/synapse function. Although axon growth is mainly observed during early development, the axon guidance genes can function in adults and contribute to maintenance of neural circuits and synaptic plasticity. Our results indicate that decline in axons' ability to maintain complex regulatory networks may potentially play an important role in the increase in physiological dysregulation during aging.

Composite Measure of Physiological Dysregulation as a Predictor of Mortality: The Long Life Family Study

Biological aging results in changes in an organism that accumulate over age in a complex fashion across different regulatory systems, and their cumulative effect manifests in increased physiological dysregulation (PD) and declining robustness and resilience that increase risks of health disorders and death. Several composite measures involving multiple biomarkers that capture complex effects of aging have been proposed. We applied one such approach, the Mahalanobis distance (D_M), to baseline measurements of various biomarkers (inflammation, hematological, diabetes-associated, lipids, endocrine, renal) in 3,279 participants from the Long Life Family Study (LLFS) with complete biomarker data. We used D_M to estimate the level of PD by summarizing information about multiple deviations of biomarkers from specified “norms” in the reference population (here, LLFS participants younger than 60 years at baseline). An increase in D_M was associated with significantly higher mortality risk (hazard ratio per standard deviation of D_M: 1.42; 95% confidence interval: [1.3, 1.54]), even after adjustment for a composite measure summarizing 85 health-related deficits (disabilities, diseases, less severe symptoms), age, and other covariates. Such composite measures significantly improved mortality predictions especially in the subsample of participants from families enriched for exceptional longevity (the areas under the receiver operating characteristic curves are 0.88 vs. 0.85, in models with and without the composite measures, p = 2.9 × 10⁻⁵). Sensitivity analyses confirmed that our conclusions are not sensitive to different aspects of computational procedures. Our findings provide the first evidence of association of PD with mortality and its predictive performance in a unique sample selected for exceptional familial longevity.