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[Preprint]. 2023 Apr 3:2023.04.03.23288064.
doi: 10.1101/2023.04.03.23288064.

Validation of a polygenic risk score for Frailty in the Lothian Birth Cohort and English Longitudinal Study of Ageing

J P Flint  1   2   3   4 , M Welstead  3   4 , S R Cox  2   3 , T C Russ  4   5 , A Marshall  1   6 , M Luciano  2   3
Affiliations

Validation of a polygenic risk score for Frailty in the Lothian Birth Cohort and English Longitudinal Study of Ageing

J P Flint et al. medRxiv. .

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Abstract

Frailty is a complex trait. Twin studies and a high-powered Genome Wide Association Study (GWAS) conducted in the UK Biobank have demonstrated a strong genetic basis of frailty. The present study utilized summary statistics from this GWAS to create and test the predictive power of frailty polygenic risk scores (PRS) in two independent samples - the Lothian Birth Cohort 1936 (LBC1936) and the English Longitudinal Study of Ageing (ELSA) aged 67-84 years. Multiple regression models were built to test the predictive power of frailty PRS at five time points. Frailty PRS significantly predicted frailty at all-time points in LBC1936 and ELSA, explaining 2.1% (β = 0.15, 95%CI, 0.085-0.21) and 1.6% (β = 0.14, 95%CI, 0.10-0.17) of the variance, respectively, at age ~68/~70 years (p < 0.001). This work demonstrates that frailty PRS can predict frailty in two independent cohorts, particularly at early ages (~68/~70). PRS have the potential to be valuable instruments for identifying those at risk for frailty and could be important for controlling for genetic confounders in epidemiological studies.

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Figures

Figure 1.
Figure 1.
Multiple bar plots, from the multiple regression models, showing the optimal p-value thresholds when predicting frailty using PRS at five time points the LBC1936. The x axis displays the varying different p-value threshold levels. The y axis displays the variance explained by the PGS. The values above the bar are the p-values from the regression output. The darker and taller the bar the stronger the prediction of the frailty PGS.
Figure 2.
Figure 2.
Multiple bar plots, from the multiple regression models, showing the optimal p-value thresholds when predicting frailty using PGS at five time points the ELSA. The x axis displays the varying different p-value threshold levels. The y axis displays the variance explained by the PGS. The values above the bar are the p-values from the regression output. The darker and taller the bar the stronger the prediction of the frailty PRS.
Figure 3:
Figure 3:
A bar plot comparing the standardized coefficients from the most predictive model at each time point in LBC1936 and ELSA. Error bars represent 95% confidence intervals. The darker the bar the stronger the effect size.
See this image and copyright information in PMC

References

    1. Young A. C. M., Glaser K., Spector T. D. & Steves C. J. The Identification of Hereditary and Environmental Determinants of Frailty in a Cohort of UK Twins. Twin Res Hum Genet 19, 600–609; 10.1017/thg.2016.72 (2016). - DOI - PubMed
    1. Stow D., Matthews F. E. & Hanratty B. Frailty trajectories to identify end of life: a longitudinal population-based study. BMC Med 16, 171; 10.1186/s12916-018-1148-x (2018). - DOI - PMC - PubMed
    1. Stow D., Matthews F. E. & Hanratty B. Frailty trajectories to identify end of life: a longitudinal population-based study. BMC Med 16, 171; 10.1186/sl2916-018-1148-x (2018). - DOI - PMC - PubMed
    1. Gale C. R., Cooper C. & Aihie Sayer A. Prevalence of frailty and disability: findings from the English Longitudinal Study of Ageing. Age and Ageing 44, 162–165; 10.1093/ageing/afu148 (2015). - DOI - PMC - PubMed
    1. Lazarus N. R., Izquierdo M., Higginson I. J. & Harridge S. D. R. Exercise Deficiency Diseases of Ageing: The Primacy of Exercise and Muscle Strengthening as First-Line Therapeutic Agents to Combat Frailty. Journal of the American Medical Directors Association 19, 741–743; 10.1016/j.jamda.2018.04.014 (2018). - DOI - PubMed

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