Validation of Biological Age Test Metrics in a Multi-omic Dataset
Validation of the resulting biological age estimates with respect to their associations with predicted disease states and sensitivity to biobehavioral interventions was therefore performed using ISB’s inhouse multi-omic dataset where clinical laboratory tests (and, in some cases, plasma metabolomics) were available at baseline for over 3,500 individuals.
This validation focused on, first, establishing the associations between global/organ-specific estimates of ∆BA (difference between estimated biological and actual chronological age) and over 50 self-reported health and disease states (i.e., occurring at least 2.5% prevalence in the sample). Second, since some of the Biological Age Test estimates incorporate DHEA, we have examined the recovery of the DHEAspecific signal via the incorporation of samples (>1,800) whose plasma was assayed using untargeted metabolomics. We also evaluated the presence of sex-specific or sex-moderated (amplified for males or females) effects by directly testing for interactions between biological sex and disease states.
Finally, the project examined the sensitivity of Biological Age Test metrics to longitudinal change associated with the participation in a biobehavioral (lifestyle) intervention. Crucially, this independent dataset used for validation of the Biological Age Test metrics, has already been demonstrated to afford reliable estimation of BA and showed sensitivity to change due to behavioral intervention (Earls et al., 2019; Zubair et al., 2019). The remainder of the report is organized as follows. The Methods section describes relevant selection and subsetting as well as providing information on relevant quality control/transformation procedures; followed by the description of the adopted statistical framework.
The Results section presents, in a narrative summary format, the main findings from the association analysis. This section is followed by a short Summary and a List of Deliverables which describes the content of the supplemental files with the report.
- Biological Age Test estimates of biological age are sensitive to a wide range of health and disease conditions and traits, in particular components of the Metabolic Syndrome
- Imputation of DHEA enables adequate recovery of the statistical signal with respect to detecting these associations; some unique signal can be attributed to DHEA (or, in this study, DHEA-S)
- Some established associations with disease states are more pronounced in women, compared to men
- Discrepancy between estimated biological and chronological age decreases as a function of time while in a lifestyle intervention program, predicting the narrowing of the gap over time
- Kidney-specific BA estimates showed an outlying pattern with respect to change estimates as well as lack of prominent disease association signal.