Biology subjects

Molina, A. J. A.

Publications and source records attributed to Molina, A. J. A..

5 recordsLinked to original sources

bioRxiv2026

Serum metabolomics reveals signatures associated with physical resilience trajectories from middle to older age

Lifecourse physical resilience is defined by the ability to maintain abilities across multiple domains of physical performance. While the importance of physical resilience in functional independence and mobility disability is clear, studies investigating metabolomic signatures of physical resilience are lacking. Here, we performed untargeted metabolomics on serum samples from a community-based cohort of 237 individuals followed over 28 years, and applied spectral data mining tools to map identified metabolites to health phenotypes from public repositories. We identified metabolites across multiple chemical classes, including acylcarnitines, glutamine conjugates, and phosphocholines, that were differentially associated with physical resilience status. Notably, medium-chain acylcarnitines negatively associated with physical resilience were more frequently observed in disease phenotypes than in healthy individuals. Kynurenine, a tryptophan metabolite linked to age-related functional decline, increased more steeply with age in individuals with low physical resilience. We also found that metabolites of the antihypertensive drug verapamil were associated with physical resilience in a metabolism-dependent manner, differing between oxidative and glucuronidated forms. Together, these metabolic signatures offer a resource for identifying biochemical pathways and biomarkers relevant to physical resilience for healthy aging.

bioinformatics↗

bioRxiv2026

Serum metabolic signatures of cognitive resilience in a longitudinal aging cohort

Aging is typically accompanied by a progressive decline in cognitive function, yet some individuals maintain exceptional cognitive performance, even across the transition from middle to older age, defining exceptional cognitive resilience. While existing measures of resilience primarily rely on clinical assessments, its molecular determinants and early predictive markers remain poorly understood. Here, we performed untargeted LC-MS/MS profiling of longitudinal serum samples to identify metabolic signatures associated with cognitive resilience, which was established based on cognitive tests conducted over 28 years in a cohort of 237 participants. We observed associations across multiple chemical classes, including carnitines, glutamine conjugates, phosphocholines, as well as diet-and drug-derived metabolites. Chemical class-specific analyses revealed distinct metabolic profiles, including predominantly negative associations of medium-chain acylcarnitines with cognitive resilience, increased accumulation of glucuronide conjugates in individuals with low cognitive resilience, altered metabolism of the antihypertensive drug, metoprolol, and elevated levels of dietary compounds such as piperine and lutein in individuals with high cognitive resilience. By leveraging public metabolomics data, we further contextualized the metabolic signatures with respect to their organ specificity, microbial origin, and disease associations. Collectively, these metabolic features, including several previously underexplored compounds, represent promising candidates for functional characterization in mechanisms of aging biology and provide mechanistic insights into the molecular basis of cognitive resilience. HighlightsO_LISerum metabolite MS/MS features, including acyl carnitines, phosphocholines, and hippuric acid conjugates, are associated with cognitive resilience in 237 individuals transitioning from middle to older age. C_LIO_LIDiet-derived piperine is positively associated with cognitive resilience. C_LIO_LIDifferences in {beta}-blocker drug metabolism, rather than parent drug levels, are associated with cognitive resilience. C_LIO_LIRepository-scale searches for the resilience-associated metabolites reveal organ specificity, microbial contributions, and their presence across multiple disease contexts. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=166 SRC="FIGDIR/small/715122v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1038203org.highwire.dtl.DTLVardef@14ca5f1org.highwire.dtl.DTLVardef@12275fcorg.highwire.dtl.DTLVardef@16ff70c_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

A searchable metadata network graph for microbiome metabolomics

Establishing the biological context of microbial metabolites remains a major challenge. We present microbiomeMASST, a metadata-driven network graph that maps metabolites across 467 available datasets with 144,424 mass spectrometry files from humans, animals, and microbial culture systems. MicrobiomeMASST integrates monocultures, synthetic communities, and host-associated samples across multiple body sites and plants. MS/MS spectra can be queried to trace occurrence across hosts, experimental conditions, and interventions, enabling cross-study integration. We demonstrate this framework by contextualizing microbial-conjugated bile acids and interrogating microbiome-mediated drug metabolism. Screening gut bacteria revealed deprolylation of the angiotensin-converting enzyme (ACE) inhibitor prodrug enalapril. Using microbiomeMASST, we traced this metabolite across human cohorts, microbial isolates, environmental samples, and in Gorilla gorilla. Structural modeling and enzymatic assays showed that microbial deprolylation abolishes ACE inhibition, thereby inactivating its therapeutic effect. Together, microbiomeMASST links MS/MS spectra to biological context, converting isolated observations into an interpretable microbiome map for cross-study analysis.

biochemistry↗

bioRxiv2025

The blood proteome predicts the impact of circulating factors on age-related mitochondrial health

Circulating non-cellular factors, such as plasma proteins, contribute to various features of aging. To determine the impacts of endogenous circulating factors on human age-related bioenergetic decline, we treated primary human fibroblasts with serum samples representing the adult life-course. Our results demonstrate that the maximal mitochondrial bioenergetic capacity of fibroblasts treated with serum is negatively correlated with the chronological and epigenetic age of the serum donor. Using targeted proteomics, we identified plasma proteins associated with the bioenergetic effects of serum. We then utilized elastic net, a linear regression modeling technique, to derive a novel proteomic signature of age-related mitochondrial differences. MitoAge is a 25-protein signature of age-related mitochondrial health that predicts the systemic bioenergetic effects of circulating factors and is related to differences in physical function across human aging. Signatures that report on cellular hallmarks of aging, such as mitochondrial function, represent a new generation of mechanistically-informed biomarkers of biological aging. GRAPHICAL ABSTRACTIn this study, we describe the development of a novel proteomic signature, MitoAge. This signature was developed by utilizing human primary fibroblasts treated with serum samples representing the adult human life-course and analyzing how resulting respirometry correlated with chronological age, epigenetic age, and abundance of serum proteins. Utilizing machine learning techniques, we derived a 25-protein signature which can predict bioenergetics and physical features related to aging. Application and utility of this signature may be used to identify novel drivers of health and longevity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/687483v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@905c12org.highwire.dtl.DTLVardef@18ca82forg.highwire.dtl.DTLVardef@175d397org.highwire.dtl.DTLVardef@966faa_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

Gnas ablation in CD11c+ cells prevents high-fat diet-induced obesity by elevating adipose tissue catecholamine levels and thermogenesis

CD11c+ immune cells are a potential therapeutic target for treatment of obesity-related insulin resistance and type 2 diabetes (T2D). In obesity, CD11c+ immune cells are recruited to white adipose tissue and create an inflammatory state that causes both insulin and catecholamine resistance. In this study, we found that ablation of Gnas, the gene that encodes Gas, in CD11c expressing cells protects mice from high-fat diet-induced obesity, glucose intolerance and insulin resistance. Gnas{Delta}CD11c mice (KO) had increased oxygen consumption, energy expenditure, and beigeing of white adipose tissue (WAT). Transplantation studies showed that the lean phenotype was conferred by bone marrow-derived cells and the absence of T and B cells by crossing the KO to a Rag1-/- background did not alter the phenotype. Notably, we observed elevated norepinephrine and elevated cAMP signaling in the WAT of KO mice. The KO adipose tissue also had reduced expression of catecholamine transport and degradation enzymes. Collectively, our results identified an important role of Gas in CD11c+ cells in whole body metabolism regulation by controlling norepinephrine levels in WAT, modulating catecholamine-induced lipolysis and increasing thermogenesis that together created a lean phenotype.

immunology↗