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Abstract Background Phenotypic age (PhenoAge), a widely used marker of biological aging, has been shown to be a robust predictor of all-cause mortality and morbidity in different populations. Existing studies on biological aging have primarily focused on individual domains, resulting in a lack of a comprehensive understanding of the multi-systemic dysregulation that occurs in aging. Methods PhenoAge was evaluated based on a linear combination of chronological age (CA) and 9 clinical biomarkers in 952 multi-ethnic Asian women of reproductive age. Phenotypic age acceleration (PhenoAgeAccel), an aging biomarker, represents PhenoAge after adjusting for CA. This study conducts an in-depth association analysis of PhenoAgeAccel with clinical, nutritional, lipidomic, gut microbiome, and genetic factors. Results Higher adiposity, glycaemia, plasma saturated fatty acids, kynurenine pathway metabolites, GlycA, riboflavin, nicotinamide, and insulin-like growth factor binding proteins were positively associated with PhenoAgeAccel. Conversely, a healthier diet and higher levels of pyridoxal phosphate, all-trans retinol, betaine, tryptophan, glutamine, histidine, apolipoprotein B, and insulin-like growth factors were inversely associated with PhenoAgeAccel. Lipidomic analysis found 132 lipid species linked to PhenoAgeAccel, with PC(O-36:0) showing the strongest positive association and CE(24:5) demonstrating the strongest inverse association. A genome-wide association study identified rs9864994 as the top genetic variant (P = 5.69E-07) from the ZDHHC19 gene. Gut microbiome analysis revealed that Erysipelotrichaceae UCG-003 and Bacteroides vulgatus were inversely associated with PhenoAgeAccel. Integrative network analysis of aging-related factors underscored the intricate links among clinical, nutritional and lipidomic variables, such as positive associations between kynurenine pathway metabolites, amino acids, adiposity, and insulin resistance. Furthermore, potential mediation effects of blood biomarkers related to inflammation, immune response, and nutritional and energy metabolism were observed in the associations of diet, adiposity, genetic variants, and gut microbial species with PhenoAgeAccel. Conclusions Our findings provide a comprehensive analysis of aging-related factors across multiple platforms, delineating their complex interconnections. This study is the first to report novel signatures in lipidomics, gut microbiome and blood biomarkers specifically associated with PhenoAgeAccel. These insights are invaluable in understanding the molecular and metabolic mechanisms underlying biological aging and shed light on potential interventions to mitigate accelerated biological aging by targeting modifiable factors.

Abstract Metabolic dysfunction‐associated steatotic liver disease (MASLD) represents an impending global health challenge. Current management strategies often face setbacks, emphasizing the need for preclinical models that faithfully mimic the human disease and its comorbidities. The liver disease progression aggravation diet (LIDPAD), a diet‐induced murine model, extensively characterized under thermoneutral conditions and refined diets is introduced to ensure reproducibility and minimize species differences. LIDPAD recapitulates key phenotypic, genetic, and metabolic hallmarks of human MASLD, including multiorgan communications, and disease progression within 4 to 16 weeks. These findings reveal gut‐liver dysregulation as an early event and compensatory pancreatic islet hyperplasia, underscoring the gut‐pancreas axis in MASLD pathogenesis. A robust computational pipeline is also detailed for transcriptomic‐guided disease staging, validated against multiple harmonized human hepatic transcriptomic datasets, thereby enabling comparative studies between human and mouse models. This approach underscores the remarkable similarity of the LIDPAD model to human MASLD. The LIDPAD model fidelity to human MASLD is further confirmed by its responsiveness to dietary interventions, with improvements in metabolic profiles, liver histopathology, hepatic transcriptomes, and gut microbial diversity. These results, alongside the closely aligned changing disease‐associated molecular signatures between the human MASLD and LIDPAD model, affirm the model's relevance and potential for driving therapeutic development.

Abstract Background Familial partial lipodystrophy (FPLD) is an inherited disorder of white adipose tissue that causes premature cardiometabolic disease. There is no clear diagnostic criteria for FPLD, and this may explain the under-detection of this condition. Aim This pilot study aimed to describe the clinical features of women with FPLD and to explore the value of adipose tissue measurements that could be useful in diagnosis. Methods In 8 women with FPLD and 4 controls, skinfold measurements, DXA and whole-body MRI were undertaken. Results Whole genome sequencing was negative for monogenic metabolic causes, but polygenic scores for partial lipodystrophy were elevated in keeping with FPLD type 1. The mean age of diagnosis of DM was 31 years in the FPLD group. Compared with controls, the FPLD group had increased HOMA-IR (10.3 vs 2.9, p = 0.028) and lower mean thigh skinfold thickness (19.5 mm vs 48.2 mm, p = 0.008). The FPLD group had lower percentage of leg fat and an increased ratio of trunk to leg fat percentage on DXA. By MRI, the FPLD group had decreased subcutaneous adipose tissue (SAT) volume in the femoral and calf regions (p