biostudies-arrayexpressRossella De CegliMus musculushttps://www.ebi.ac.uk/biostudies/studies/E-MTAB-15944Sarcopenic obesity affects up to 40% of older adults with obesity, yet many remain protected despite comparable metabolic burden. The molecular basis for this heterogeneity remains unknown, limiting risk stratification and targeted intervention. We superimposed metabolic challenge on aging physiology by exposing seventy-two 12-month-old female mice to high-fat diet (HFD) or standard diet for 7 months, modeling the development of sarcopenic obesity during the transition from middle to old age. Multi-Omics Factor Analysis (MOFA) integrated muscle transcriptomics and metabolomics to identify latent factors explaining phenotypic variation. Total RNA was quantified using the Qubit 4.0 fluorimetric Assay (Thermo Fisher Scientific). Libraries were prepared from 125 ng of total RNA using the NEGEDIA Digital mRNA-seq research grade sequencing service v2.0 (Next Generation Diagnostic S.r.l., Pozzuoli, Italy), which included library preparation, quality assessment and sequencing on a NovaSeq 6000 sequencing system using a single-end, 100 cycle strategy (Illumina Inc.). Raw data were analyzed by Next Generation Diagnostic srl proprietary NEGEDIA Digital mRNA-seq pipeline (Next Generation Diagnostic S.r.l., Pozzuoli, Italy, v2.0), which involves a cleaning step by quality filtering and trimming, alignment to the reference genome and counting by genebiostudies-arrayexpressLibrary Construction - The raw data were analyzed by Next Generation Diagnostic srl proprietary NEGEDIA Digital mRNA-seq pipeline (v2.0) which involves a cleaning step by quality filtering and trimming, alignment to the reference genome and counting by gene. The raw expression data were normalized separately for each tissue, analyzed by NEGEDIA degsanalysis pipeline (v1.2.0) and visualized in a proprietary report (v1.0).The Performer for the 'nucleic acid sequencing protocol' was the sequencing center Next Generation Diagnostic srl (NEGEDIA), Via Campi Flegrei 34, 80078 Pozzuoli (NA), ItalyNucleic Acid Extraction - Total RNA was quantified using the Qubit 4.0 fluorimetric Assay (Thermo Fisher Scientific). Libraries were prepared from 125 ng of total RNA using the NEGEDIA Digital mRNA-seq research grade sequencing service v2.0 (Next Generation Diagnostic S.r.l., Pozzuoli, Italy), which included library preparation, quality assessment and sequencing on a NovaSeq 6000 sequencing system using a single-end, 100 cycle strategy (Illumina Inc.). Raw data were analyzed by Next Generation Diagnostic srl proprietary NEGEDIA Digital mRNA-seq pipeline (Next Generation Diagnostic S.r.l., Pozzuoli, Italy, v2.0), which involves a cleaning step by quality filtering and trimming, alignment to the reference genome and counting by gene.Sequencing - NovaSeq 6000 sequencing system using a single-end, 100 cycle strategy (Illumina Inc.).Sample Collection - Seventy-two twelve-month-old female C57BL/6N wild-type mice (Charles River Laboratories, Calco (LC), Italy) were housed in a pathogen-free facility at our institution. Mice were randomly assigned based on body weight to either SD (10% fat, D12450B, Charles River Laboratories) or HFD (35.5% fat, D12492, Charles River Laboratories) groups. Cohorts of mice were euthanized after 1, 3, and 7 months of dietary intervention (n=12/diet/timepoint). Visceral and subcutaneous adipose tissues, skeletal muscle (gastrocnemius and tibialis anterior), and liver were harvested for analysis. All procedures were approved by the institutional animal care committee (IACUC 1232023-PR) and performed in accordance with European Union guidelines. Mice were weighed weekly, and body composition was analyzed monthly using Time-Domain Nuclear Magnetic Resonance relaxometry with the MINISPEC LF50 system (Bruker, Billerica, MA, USA). Fat mass percentage was calculated as (body fat/body weight) × 100 (Matias et al., 2018), while lean mass percentage as (body lean mass/ body weight) × 100.OrganizationMINSEQE ScoreAssays and DataProcessed DataMAGE-TAB FilesData Transformation - The raw expression data were normalized and analyzed using the DESeq2 pipelineMetabolomicsUnknownTranscriptomicsGenomicsProteomicsIllumina NovaSeq 6000RNA-seq of coding RNAMus musculusRossella De CeglifalseMetabolic exhaustion underlies sarcopenic obesity susceptibility in aging mice as revealed by multi-omics factor analysisSarcopenic obesity affects up to 40% of older adults with obesity, yet many remain protected despite comparable metabolic burden. The molecular basis for this heterogeneity remains unknown, limiting risk stratification and targeted intervention. We superimposed metabolic challenge on aging physiology by exposing seventy-two 12-month-old female mice to high-fat diet (HFD) or standard diet for 7 months, modeling the development of sarcopenic obesity during the transition from middle to old age. Multi-Omics Factor Analysis (MOFA) integrated muscle transcriptomics and metabolomics to identify latent factors explaining phenotypic variation. Total RNA was quantified using the Qubit 4.0 fluorimetric Assay (Thermo Fisher Scientific). Libraries were prepared from 125 ng of total RNA using the NEGEDIA Digital mRNA-seq research grade sequencing service v2.0 (Next Generation Diagnostic S.r.l., Pozzuoli, Italy), which included library preparation, quality assessment and sequencing on a NovaSeq 6000 sequencing system using a single-end, 100 cycle strategy (Illumina Inc.). Raw data were analyzed by Next Generation Diagnostic srl proprietary NEGEDIA Digital mRNA-seq pipeline (Next Generation Diagnostic S.r.l., Pozzuoli, Italy, v2.0), which involves a cleaning step by quality filtering and trimming, alignment to the reference genome and counting by gene2026-09-22T00:00:00Z2026-09-22T10:28:00.409Z2025-10-31T15:24:17.132ZE-MTAB-15944ERP183470EFO_0002944EFO_0004170EFO_0005518EFO_0003816EFO_0003738EFO_0004184