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. 2023 Feb 3;18(2):e0279971.
doi: 10.1371/journal.pone.0279971. eCollection 2023.

Genetic scores for predicting longevity in the Croatian oldest-old population

Maja Šetinc  1 , Željka Celinšćak  1 , Luka Bočkor  1   2 , Tanja Ćorić  3 , Branko Kolarić  3 , Anita Stojanović Marković  1 , Matea Zajc Petranović  1 , Marijana Peričić Salihović  1 , Nina Smolej Narančić  1 , Tatjana Škarić-Jurić  1
Affiliations

Genetic scores for predicting longevity in the Croatian oldest-old population

Maja Šetinc et al. PLoS One. .

Abstract

Longevity is a hallmark of successful ageing and a complex trait with a significant genetic component. In this study, 43 single nucleotide polymorphisms (SNPs) were chosen from the literature and genotyped in a Croatian oldest-old sample (85+ years, sample size (N) = 314), in order to determine whether any of these SNPs have a significant effect on reaching the age thresholds for longevity (90+ years, N = 212) and extreme longevity (95+ years, N = 84). The best models were selected for both survival ages using multivariate logistic regression. In the model for reaching age 90, nine SNPs explained 20% of variance for survival to that age, while the 95-year model included five SNPs accounting for 9.3% of variance. The two SNPs that showed the most significant association (p ≤ 0.01) with longevity were TERC rs16847897 and GHRHR rs2267723. Unweighted and weighted Genetic Longevity Scores (uGLS and wGLS) were calculated and their predictive power was tested. All four scores showed significant correlation with age at death (p ≤ 0.01). They also passed the ROC curve test with at least 50% predictive ability, but wGLS90 stood out as the most accurate score, with a 69% chance of accurately predicting survival to the age of 90.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Forest plot of SNPs positively (O.R. > 1) associated with longevity, with multivariate model Odds Ratios (O.R.) and 95% confidence intervals (C.I.) displayed.
A) SNPs positively associated with survival to the age of 90, B) SNPs positively associated with survival to the age of 95.
Fig 2
Fig 2. Comparison of the genetic longevity score values between participants who died before and after reaching the cut-off ages of 90 and 95 years.
Box-and-whiskers plot showing the median value, quartile and extremes of A) uGLS90, B) uGLS95, C) wGLS90, D) wGLS95.
Fig 3
Fig 3. Distribution of two unweighted genetic longevity scores in three age-at-death groups.
Histograms show the distribution of A) uGLS90, and B) uGLS95 among the participants belonging to a specific age-at-death group: < 90.00 years, 90.00–94.99 years, and 95.00+ years.
Fig 4
Fig 4. Receiver operating characteristics (ROC) curves for calculated genetic longevity scores.
The ROC curve and area-under-curve (AUC) score for: A) uGLS90 (AUC = 0.662), B) uGLS95 (AUC = 0.649), C) wGLS90 (AUC = 0.690), D) wGLS95 (AUC = 0.649).
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Grants and funding

This research was funded by Croatian Science Foundation grants IP-01-2018-2497 (HECUBA project) and DOK-2018-09-8382 to Tatjana Škarić-Jurić. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.