1. Age-dependent co-dependency structure of biomarkers in the general population of the United States
- Author
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Chirag J. Patel and Alan Le Goallec
- Subjects
Adult ,Blood Glucose ,Male ,Aging ,National Health and Nutrition Examination Survey ,Population ,Age dependent ,03 medical and health sciences ,0302 clinical medicine ,Predictive Value of Tests ,Risk Factors ,correlations ,demographics ,Humans ,Medicine ,education ,Aged ,030304 developmental biology ,Aged, 80 and over ,0303 health sciences ,education.field_of_study ,Co dependency ,business.industry ,Body Weight ,Racial Groups ,biomarkers ,Mean age ,Cell Biology ,Chronological age ,Middle Aged ,Nutrition Surveys ,Biobank ,3. Good health ,Cholesterol ,machine learning ,Blood pressure ,Gene Expression Regulation ,030220 oncology & carcinogenesis ,Female ,business ,Research Paper ,Demography - Abstract
Phenotypic biomarkers (e.g. cholesterol, weight, and glucose) are important to diagnose and treat diseases associated with aging. However, while many biomarkers are co-dependent (e.g. glycohemoglobin and glucose), it is generally unknown how age influences their co-dependence. In the following, we analyzed 50 biomarkers in 27,508 National Health and Nutrition Examination Survey (NHANES) participants (age range: 20 to 80, mean age: 46.3 years old, sexes: 48.9% males, 51.1% females, ethnicities: 46.0% Whites, 27.8% Hispanics, 20.0% non-Hispanic Blacks, 6.1% others) to investigate how the co-dependency structure of common biomarkers evolves with age and whether differences exist between sexes and ethnicities. First, we associated the change in correlations between biomarkers with chronological age. We identified six trends and replicated our top finding (height vs. systolic blood pressure) in participants of the UK Biobank (N=470,895). We found that, on average, correlations tend to decrease with age. Secondly, we examined how biomarkers predict other biomarkers in participants of different age groups. We found 17 (34%) biomarkers whose predictability decreases with age and 5 (10%) biomarkers whose predictability increases with age. A limitation of this study is that it cannot distinguish between biological changes related to aging and generational effects. Our results can be interactively explored here: http://apps.chiragjpgroup.org/Aging_Biomarkers_Co-Dependencies/.
- Published
- 2019