A toolkit for quantification of biological age from blood chemistry and organ function test data: BioAge

Abstract

Methods to quantify biological aging are emerging as new measurement tools for epidemiology and population science and have been proposed as surrogate measures for healthy lifespan extension in geroscience clinical trials. Publicly available software packages to compute biological aging measurements from DNA methylation data have accelerated dissemination of these measures and generated rapid gains in knowledge about how different measures perform in a range of datasets. Biological age measures derived from blood chemistry data were introduced at the same time as the DNA methylation measures and, in multiple studies, demonstrate superior performance to these measures in prediction of healthy lifespan. However, their dissemination has been slow by comparison, resulting in a significant gap in knowledge. We developed a software package to help address this knowledge gap. The BioAge R package, available for download at GitHub ( http://github.com/dayoonkwon/BioAge ), implements three published methods to quantify biological aging based on analysis of chronological age and mortality risk: Klemera-Doubal biological age, PhenoAge, and homeostatic dysregulation. The package allows users to parametrize measurement algorithms using custom sets of biomarkers, to compare the resulting measurements to published versions of the Klemera-Doubal method and PhenoAge algorithms, and to score the measurements in new datasets. We applied BioAge to safety lab data from the CALERIE™ randomized controlled trial, the first-ever human trial of long-term calorie restriction in healthy, non-obese adults, to test effects of intervention on biological aging. Results contribute evidence that CALERIE intervention slowed biological aging. BioAge is a toolkit to facilitate measurement of biological age for geroscience.

Keywords: Aging; Biological age; Biomarkers; CALERIE; Geroscience; Healthspan.

Fig. 1

Correlations of published versions of Klemera-Doubal method (KDM) biological age and PhenoAge with versions of KDM biological age, PhenoAge, and a measure computed using the homeostatic dysregulation method based on a modified set of biomarkers. The figure plots data from NHANES IV generated with the _nhanes commands within the BioAge package. All measures were developed from analysis of NHANES III and computed using data from NHANES IV. KDM biological age and PhenoAge values were differenced from chronological age for analysis. The “Levine Original” KDM algorithm was composed from chronological age and 10 biomarkers: albumin, alkaline phosphatase, blood urea nitrogen, creatinine, C-reactive protein, cytomegalovirus optical density, HbA1C, total cholesterol, systolic blood pressure, and forced expiratory volume in 1 s (FEV₁). The “Levine Original” PhenoAge was composed from chronological age and 9 biomarkers: albumin, alkaline phosphatase, creatinine, C-reactive protein, fasting glucose, white blood cell count, lymphocyte percentage, mean cell volume, and red cell distribution width. The “V2” versions of the KDM, PhenoAge, and HD algorithms included chronological age and 12 biomarkers: albumin, alkaline phosphatase, blood urea nitrogen, creatinine, C-reactive protein, HbA1C, total cholesterol, uric acid, white blood cell count, lymphocyte percentage, mean cell volume, and red cell distribution width

Fig. 2

Associations of Klemera-Doubal method (KDM) biological age, PhenoAge, and homeostatic dysregulation (HD) measures of biological age with chronological age among participants in the CALERIE trial at pre-intervention baseline. The figure plots pre-intervention baseline values of the three biological aging measures against chronological age for men (blue) and women (pink) participating in the CALERIE trial (n = 207)

Fig. 3

Change in Klemera-Doubal method (KDM) biological age, PhenoAge, and homeostatic dysregulation (HD) from baseline to 12- and 24-month follow-ups in the ad libitum (dark blue dots) and caloric restriction (light blue triangles) groups of the CALERIE trial. The figure plots predicted values and 95% confidence intervals estimated from mixed-effects growth models for participants in the ad libitum control group (dark blue circles, solid line) and caloric restriction intervention group (light blue triangles, dashed line). Values of KDM biological age and PhenoAge are denominated in years. Values of HD are denominated in log Mahalanobis distance units