Promising biomarkers of human aging: In search of a multi-omics panel to understand the aging process from a multidimensional perspective.

The aging process has been linked to the occurrence of chronic diseases and functional impairments, including cancer, sarcopenia, frailty, metabolic, cardiovascular, and neurodegenerative diseases. Nonetheless, aging is highly variable and heterogeneous and represents a challenge for its characterization. In this sense, intrinsic capacity (IC) stands as a novel perspective by the World Health Organization, which integrates the individual wellbeing, environment, and risk factors to understand aging. However, there is a lack of quantitative and qualitative attributes to define it objectively. Therefore, in this review we attempt to summarize the most relevant and promising biomarkers described in clinical studies at date over different molecular levels, including epigenomics, transcriptomics, proteomics, metabolomics, and the microbiome. To aid gerontologists, geriatricians, and biomedical researchers to understand the aging process through the IC. Aging biomarkers reflect the physiological state of individuals and the underlying mechanisms related to homeostatic changes throughout an individual lifespan; they demonstrated that aging could be measured independently of time (that may explain its heterogeneity) and to be helpful to predict age-related syndromes and mortality. In summary, we highlight the areas of opportunity and gaps of knowledge that must be addressed to fully integrate biomedical findings into clinically useful tools and interventions.

The combination of insulin resistance and visceral adipose tissue estimation improves the performance of metabolic syndrome as a predictor of type 2 diabetes.

AIMS: To assess the performance of metabolic syndrome as a predictor of type 2 diabetes in a model that also includes both a measure of insulin resistance and a metabolic score for visceral fat, and to propose a novel metabolic syndrome definition. METHODS: In a prospective Metabolic Syndrome Cohort (n=6143), we evaluated improvements in type 2 diabetes risk prediction using International Diabetes Federation-defined and Adult Treatment Panel III-defined metabolic syndrome, after inclusion in the model of updated homeostatic model assessment of insulin resistance and a metabolic score for visceral fat. We also developed a modified metabolic syndrome construct, 'MS-METS', which used the metabolic score for visceral fat instead of waist circumference to evaluate improved predictive performance for risk of developing type 2 diabetes. RESULTS: Participants who had metabolic syndrome as defined by both the Adult Treatment Panel III and the International Diabetes Federation criteria had a higher risk of type 2 diabetes compared to participants who did not meet these criteria. Addition of updated homeostatic model assessment of insulin resistance and metabolic score for visceral fat to both metabolic syndrome definitions increased predictive performance for type 2 diabetes risk. Homeostatic model assessment of insulin resistance was the only additional predictor of type 2 diabetes in participants without metabolic syndrome. Conversely, in participants with metabolic syndrome, the use of the metabolic score for visceral fat was the stronger added predictor for type 2 diabetes. When evaluating participants using the MS-METS definition we observed the largest improvement in predictive ability for type 2 diabetes risk and a significant reduction in risk overestimation compared to evaluation using metabolic syndrome defined according to the International Diabetes Federation and Adult Treatment Panel III criteria alone. CONCLUSION: Inclusion of updated homeostatic model assessment of insulin resistance and metabolic score for visceral fat increases performance of metabolic syndrome in prediction of type 2 diabetes. Assessment of insulin resistance could be more useful than conventional metabolic syndrome and assessment of visceral adipose tissue could be more useful in people with metabolic syndrome. Metabolic syndrome as defined using our modified MS-METS construct improved the accuracy of type 2 diabetes prediction.

[Meningeal syndrome in a patient treated with a combination of immune checkpoint inhibitors for a metastatic melanoma]. / Sindrome meningeo en un paciente tratado con combinacion de inhibidores de puntos de control inmunologico para melanoma metastasico.

TITLE: Sindrome meningeo en un paciente tratado con combinacion de inhibidores de puntos de control inmunologico para melanoma metastasico.