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Oestereicher, M. A.

Publications and source records attributed to Oestereicher, M. A..

2 recordsLinked to original sources

Rethinking ratio-based normalization: A guide towards model-based approaches in heart weight analysis

Heart weight is a critical parameter in cardiology and mouse research, reflecting structural and functional changes linked to cardiac size or hypertrophy and pathophysiological conditions. Normalizing heart weight (HW) to body weight (BW) or tibia length (TL) is a common practice; however, the validity of these ratios has been questioned due to non-proportional relationships between parameters, and this becomes particularly problematic when comparing distinct populations based on such normalized values. Using data from over 25,000 C57BL/6N wildtype mice provided by the International Mouse Phenotyping Consortium (IMPC), we investigated the limitations of ratio-based normalization when comparing different groups, aiming to propose a robust framework for HW analysis. Our findings reveal negligible to weak correlations between HW, BW, and TL across age and sex groups, undermining the validity of ratio-based methods. A modelling study using simulated data demonstrated that ratios could produce misleading results, including reversed or false group differences, when scaling assumptions are violated. Ratios yield accurate and interpretable results only when a truly proportional relationship exists between the variables--specifically, when the regression line passes through the origin--conditions under which ratio-based normalization aligns with outcomes obtained from more robust modelling approaches. These results underscore the superiority of linear models with covariate adjustment and allometric scaling for organ weight analysis, as they more accurately capture biologically relevant scaling relationships. By leveraging the IMPCs large-scale wildtype dataset, we establish the necessity of reassessing normalization practices in quantitative biology traits and propose that ratios should be avoided when comparing normalized values across distinct populations unless key mathematical assumptions are met. This study advances the analytical rigor in phenotyping research, enabling more accurate interpretations of organ mass and function across biological contexts.

physiology↗

Deep Phenotyping and Lifetime Trajectories Reveal Limited Effects of Longevity Regulators on the Aging Process in C57BL/6J Mice

Current concepts regarding the biology of aging are based on studies aimed at identifying factors regulating natural lifespan. However, lifespan as a sole proxy measure for aging can be of limited value because it may be restricted by specific sets of pathologies, rather than by general physiological decline. Here, we employed large-scale phenotyping to analyze hundreds of phenotypes and thousands of molecular markers across tissues and organ systems in a single study of aging male C57BL/6J mice. For each phenotype, we established lifetime profiles to determine when age-dependent phenotypic change is first detectable relative to the young adult baseline. We examined central genetic and environmental lifespan regulators (putative anti-aging interventions, PAAIs; the following PAAIs were examined: mTOR loss-of-function, loss-of-function in growth hormone signaling, dietary restriction) for a possible countering of the signs and symptoms of aging. Importantly, in our study design, we included young treated groups of animals, subjected to PAAIs prior to the onset of detectable age-dependent phenotypic change. In parallel to our studies in mice, we assessed genetic variants for their effects on age-sensitive phenotypes in humans. We observed that, surprisingly, many PAAI effects influenced phenotypes long before the onset of detectable age-dependent changes, rather than altering the rate at which these phenotypes developed with age. Accordingly, this subset of PAAI effects does not reflect a targeting of age-dependent phenotypic change. Overall, our findings suggest that comprehensive phenotyping, including the controls built in our study, is critical for the investigation of PAAIs as it facilitates the proper interpretation of the mechanistic mode by which PAAIs influence biological aging. HighlightsO_LIPhenotyping at scale defines lifetime trajectories of age-dependent changes in C57BL/6J mice C_LIO_LICentral genetic and environmental lifespan regulators (putative anti-aging interventions; PAAIs) influence age-sensitive phenotypes (ASPs) often long before the appearance of age-dependent changes in these ASPs C_LIO_LICorresponding genetic variants in humans also have age-independent effects C_LIO_LIMany PAAI effects shift the baseline of ASPs rather than slowing their rate of change C_LI

physiology↗