Redefining meaningful age groups in the context of disease

• Published in: AGE Vol. 35; no. 6; pp. 2357 - 2366
• Main Authors: Geifman, Nophar, Cohen, Raphael, Rubin, Eitan
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.12.2013; Springer Nature B.V
• Subjects: Adolescent; Adult; Age Distribution; Age groups; Aged; Aged, 80 and over; Aging; Alzheimer's disease; Beer; Biomedical and Life Sciences; Biomedical Research - statistics & numerical data; Cell Biology; Child; Child, Preschool; Cluster Analysis; Disease; Female; Fertility; Gene expression; Geriatrics; Geriatrics/Gerontology; Gerontology; Humans; Hypotheses; Infant; Infant, Newborn; Infertility; Life Sciences; Male; Medical research; Medical Subject Headings-MeSH; Methods; Middle Aged; Models, Statistical; Molecular Medicine; Older people; Studies; Subject heading schemes; Young Adult; Disease; Clustering; Age; Age groups
• ISSN: 0161-9152; 2509-2715; 1574-4647; 1574-4647; 2509-2723
• DOI: 10.1007/s11357-013-9510-6

Age is an important factor when considering phenotypic changes in health and disease. Currently, the use of age information in medicine is somewhat simplistic, with ages commonly being grouped into a small number of crude ranges reflecting the major stages of development and aging, such as childhood or adolescence. Here, we investigate the possibility of redefining age groups using the recently developed Age-Phenome Knowledge-base (APK) that holds over 35,000 literature-derived entries describing relationships between age and phenotype. Clustering of APK data suggests 13 new, partially overlapping, age groups. The diseases that define these groups suggest that the proposed divisions are biologically meaningful. We further show that the number of different age ranges that should be considered depends on the type of disease being evaluated. This finding was further strengthened by similar results obtained from clinical blood measurement data. The grouping of diseases that share a similar pattern of disease-related reports directly mirrors, in some cases, medical knowledge of disease–age relationships. In other cases, our results may be used to generate new and reasonable hypotheses regarding links between diseases.