Traditionally, biomarkers of aging are classified as either pro-longevity or antilongevity. Using longitudinal data sets from the large-scale inbred mouse strain study at the Jackson Laboratory Nathan Shock Center, we describe a protocol to identify two kinds of biomarkers: those with prognostic implication for lifespan and those with longitudinal evidence. Our protocol also identifies biomarkers for which, at first sight, there is conflicting evidence. Conflict resolution is possible by postulating a role switch. In these cases, high biomarker values are, for example, antilongevity in early life and pro-longevity in later life. Role-switching biomarkers correspond to features that must, for example, be minimized early, but maximized later, for optimal longevity. The clear-cut pro-longevity biomarkers we found reflect anti-inflammatory, anti-immunosenescent or anti-anaemic mechanisms, whereas clear-cut antilongevity biomarkers reflect inflammatory mechanisms. Many highly significant blood biomarkers relate to immune system features, indicating a shift from adaptive to innate processes, whereas most role-switching biomarkers relate to blood serum features and whole-body phenotypes. Our biomarker classification approach is applicable to any combination of longitudinal studies with life expectancy data, and it provides insights beyond a simplified scheme of biomarkers for long or short lifespan.
Lifespan is a complex trait, and longitudinal data for humans are naturally scarce. We report the results of Cox regression and Pearson correlation analyses using data of the Study of Health in Pomerania (SHIP), with mortality data of 1518 participants (113 of which died), over a time span of more than 10 years. We found that in the Cox regression model based on the Bayesian information criterion, apart from chronological age of the participant, six baseline variables were considerably associated with higher mortality rates: smoking, mean attachment loss (i.e. loss of tooth supporting tissue), fibrinogen concentration, albumin/creatinine ratio, treated gastritis, and medication during the last 7 days. Except for smoking, the causative contribution of these variables to mortality was deemed inconclusive. In turn, four variables were found to be associated with decreased mortality rates: treatment of benign prostatic hypertrophy, treatment of dyslipidemia, IGF-1 and being female. Here, being female was an undisputed causative variable, the causal role of IFG-1 was deemed inconclusive, and the treatment effects were deemed protective to the degree that treated subjects feature better survival than respective controls. Using Cox modeling based on the Akaike information criterion, diabetes, mean corpuscular hemoglobin concentration, red blood cell count and serum calcium were also associated with mortality. The latter two, together with albumin and fibrinogen, aligned with an”integrated albunemia” model of aging proposed recently.
Long-term-selected DUhTP mice represent a non-inbred model for inborn physical high-performance without previous training. Abundance of hepatic mRNA in 70-day male DUhTP and control mice was analyzed using the Affymetrix mouse array 430A 2.0. Differential expression analysis with PLIER corrected data was performed using AltAnalyze. Searching for over-representation in biochemical pathways revealed cholesterol metabolism being most prominently affected in DUhTP compared to unselected control mice. Furthermore, pathway analysis by AltAnalyze plus PathVisio indicated significant induction of glycolysis, fatty acid synthesis and cholesterol biosynthesis in the liver of DUhTP mice versus unselected control mice. In contrast, gluconeogenesis was partially inactivated as judged from the analysis of hepatic mRNA transcript abundance in DUhTP mice. Analysis of mRNA transcripts related to steroid hormone metabolism inferred elevated synthesis of progesterone and reduced levels of sex steroids. Abundance of steroid delta isomerase-5 mRNA (Hsd3b5, FC 4.97) was increased and steroid 17-alpha-monooxygenase mRNA (Cyp17a1, FC -11.6) was massively diminished in the liver of DUhTP mice. Assessment of steroid profiles by LC-MS revealed increased levels of progesterone and decreased levels of sex steroids in serum from DUhTP mice versus controls. Analysis of hepatic mRNA transcript abundance indicates that sterol regulatory element-binding protein-1 (SREBP-1) may play a major role in metabolic pathway activation in the marathon mouse model DUhTP. Thus, results from bioinformatics modeling of hepatic mRNA transcript abundance correlated with direct steroid analysis by mass spectrometry and further indicated functions of SREBP-1 and steroid hormones for endurance performance in DUhTP mice.
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