Sarcopenia (SP) is increasingly recognized as a poor prognostic factor for patients with Crohn's disease (CD). We aimed to use radiographically-measured SP to determine a disease-specific definition and measure its association with CD-related outcomes. This retrospective study included adults with CD seen at our outpatient tertiary center between 2019 and 2021 who underwent a CT scan within 3 months of visit. Using axial cross-sectional measurements at the L3 vertebral level, skeletal muscle area was indexed to height to derive skeletal muscle index (SMI). Demographics, comorbidities, CD phenotype, and outcomes, including hospitalization at 1 year, were analyzed in univariate and multivariate models. One hundred twenty-four patients with CD were included, with a mean age of 52.2±16.6 years and 53.2% (66/124) women. Overall, 33.1% (41/124) had SP based on sex-specific cutoffs with men representing 75.6% (31/41) of the sarcopenic population. In bivariate analysis, patients with SP had a higher likelihood of hospitalization (43.9% vs. 22.9% for non-SP, P=0.02) and penetrating CD phenotype (20.0% vs. 2.3% for non-SP, P<0.05). On multivariate regression, higher SMI was associated with decreased hospitalization, with each 10-unit increase in SMI conferring 0.54 lower odds (OR: 0.54 [95% CI: 0.32-0.92], P=0.02). Patients with higher SMI trended towards lower use of biologics (OR: 0.70 [95% CI: 0.45-1.09], P=0.12). Our novel SP definition derived from an IBD population performed similarly to definitions from the literature. Our study demonstrates the application of an automated algorithm for the quantification of body composition based on CT scan in patients with CD. SP and low SMI were associated with increased hospitalization at 1 year.

The interrelation between sarcopenia and obesity is both reciprocal and pathogenic. Nevertheless, the operational definitions and subsequent findings of sarcopenic obesity (SO) demonstrate variability and inconsistency. This study explored the relationships between sarcopenia and total muscle-to-fat ratio (tMFR), fat mass (FM) ratio, and all-cause mortality. This retrospective study recruited inpatients and outpatients aged 18years and older in a tertiary-hospital-based cohort study from 2018 to 2024. Sarcopenia (SP) was defined by low muscle strength (lowest 20% of handgrip strength), low physical performance (lowest 20% of 6-meter walking), and low appendicular skeletal mass index (<7.0kg/m2 for men; <5.4kg/m2 for women). Low tMFR or high FM ratio was defined as the lowest and highest quartiles, respectively, for categorizing obesity. The Cox proportional hazard model and Kaplan-Meier curves were used for the primary outcome. The mean age of the 538 patients was 67.9±14.0years, and 72.7% were female. After median (interquartile range) 0.7 (0.2-1.4) years of follow-up, 22 patients had died. Among the 32 patients with sarcopenia and low tMFR, as well as the 31 patients with sarcopenia and high FM ratio, significant characteristics included older age, male predominance, high android-to-gynoid fat ratio, and increased total fat. Older age, sarcopenia, osteoporosis, multimorbidity, serum creatinine, albumin, glycated hemoglobin, and alkaline phosphate were significantly associated with all-cause mortality. After adjusting for age and multimorbidity, SP patients with a low tMFR showed a non-significant trend toward higher all-cause mortality risk (hazard ratio [HR]=3.26; 95% confidence interval [CI]=0.92-11.48), while those with a high FM ratio had a significantly increased risk (HR=3.83; 95% CI=1.10-13.39). Given the limited number of deaths (events), the statistical power of the study may be inadequate, although true associations are likely to exist. The study underscores the significant associations between low tMFR, high FM ratio, and increased all-cause mortality in patients with sarcopenia. However, considering short follow-up time and limited mortality with a wide hazard ratio in our study, further longer follow up is necessary.

Colorectal cancer (CRC) often occurs in combination with sarcopenia (SP), which affects the prognosis of CRC, but the histopathological mechanisms underlying this process are unclear. Single-cell transcriptome technology provides a tool for resolving multi-organ pathological interactions, and previous studies have lacked direct molecular evidence of a trans-tissue microenvironment. To address this, we applied an integrated analytical approach. The integration of single-cell transcriptome data from 16 CRC tumor tissues (scRNA-seq) and 17 SP muscle tissues (snRNA-seq) was used to systematically resolve heterogeneity across tissue microenvironments using Harmony to correct for batch effects and combining cellular annotations, differential expression analyses, and CellChat communication modeling. Our analysis revealed that CRC and SP share 3 core cell types, namely, endothelial cells, fibroblasts and monocytes, but they show distinct transcriptional and functional differentiation in different tissues. CRC cells are enriched in the inflammatory, angiogenic and matrix remodeling pathways, accompanied by the upregulation of hypoxia-associated genes, whereas SP is biased toward muscle structural maintenance, metabolic regulation and repair functions. The MIF-CD74, COLLAGEN and THBS-CD47 pathways were active in CRC, whereas SDC4 and CD36-related signals were dominant in SP. VWF, PDGFRA and FCN1 were stably expressed in both groups, suggesting the existence of a conserved homeostatic regulatory network. In conclusion, this study reveals the cross-tissue functional heterogeneity of cell types shared by CRC and SP, suggests a set of potential pervasive regulators, and provides new perspectives for understanding the systemic effects of tumors and the microenvironmental mechanisms of sarcopenia.

We propose a markerless gait anomaly detection system for orthopedic screening. The framework combines MediaPipe-based joint tracking, unsupervised LSTM-autoencoder modeling, and targeted preprocessing to address clinical video noise. Trained only on normal gait, the model detects abnormal patterns in sarcopenia (SA) and Parkinson’s disease (PD) patients, achieving detection rates of 97% and 88%, respectively. Our method achieves state-of-the-art performance in sarcopenia detection, surpassing recent sensor-based approaches that require wearable devices or handcrafted features. Furthermore, to the best of our knowledge, this is the first unified markerless framework capable of identifying both sarcopenia and Parkinson’s disease using a single video-based system. To improve input quality, we address three common sources of error–frame imbalance, clothing interference, and background clutter—using YOLO-based frame filtering and semantic segmentation. This increased usable gait data by up to 38%. Joint-level analysis identified the knees as the most responsive to gait abnormalities, enabling interpretable and localized assessments. Our results highlight the potential of a scalable, non-invasive system for early detection and monitoring of musculoskeletal disorders.

Sarcopenia (SARC), a progressive degenerative disorder associated with aging, is characterized by a gradual loss of muscle mass and strength and imposes major burdens on individuals and society. Current diagnostic and therapeutic methods for SARC remain limited, highlighting the urgent need for novel biomarkers. The present research was designed to investigate the role of lactate metabolism–related differentially expressed genes (LMRDEGs) in SARC, identify key genes and pathways, and develop a diagnostic model for the disease. Differentially expressed genes (DEGs) were identified using data from the Gene Expression Omnibus database. Gene set enrichment analysis was used to determine signaling pathways associated with the DEGs. Pearson’s correlation analysis was used to quantify the strength of linear relationships between coding genes and DEGs. Protein–protein interaction networks of DEGs were constructed using the STRING database. Functional annotation of DEGs was conducted using comprehensive enrichment analyses based on Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to elucidate their biological relevance. Seventeen LMRDEGs were found to be significantly upregulated or downregulated in SARC, underscoring their pivotal roles in disease pathogenesis. GO and KEGG pathway enrichment analyses revealed that these DEGs were primarily involved in metabolic energy regulation and intracellular signal transduction, suggesting their functional importance in SARC development. Immune infiltration analysis suggested substantial variations in immune cell abundance among SARC samples, emphasizing the immune system’s potential contribution to disease progression. This study demonstrates the importance of LMRDEGs in SARC and the need for further investigation into their roles as potential therapeutic targets.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-25525-z.

The increasing prevalence of sarcopenia (SAR) has raised significant concerns in healthcare. Although mitochondrial dysfunction and immune disorders are recognized as risk factors, the interactions between them remain unclear. This study aims to identify potential diagnostic biomarkers associated with both phenotypes in the progression of SAR. Three transcriptional datasets were obtained from the GEO database. Gene set enrichment analysis (GSEA) was performed to explore the features of the training set, followed by filtering the differentially expressed genes (DEGs). Weighted gene co-expression network analysis was applied to select gene modules closely related to SAR. SAR-mitochondria-related DEGs were then determined by intersecting the DEGs, weighted gene co-expression network analysis, and mitochondrial-related genes from the MitoCarta3.0 database. Hub genes were further explored using LASSO and random forest machine learning algorithms. The regulatory molecules of these hub genes were predicted using the NetworkAnalyst database. Subsequently, receiver operating characteristic analysis was performed and the immune infiltration was analyzed using the CIBERSORT algorithm. A SAR model was established in C2C12 cells using d-galactose, and RT-qPCR experiments were performed for further validation. Gene set enrichment analysis results revealed that the training set genes are mainly enriched in mitochondrial function and energy metabolism. Through the machine learning methods, 5 hub genes were screened out from 32 SAR-Mito DEGs, namely MTRF1L, MICU1, DHTKD1, ACADM, and FHIT. A total of 42 transcription factors and 10 miRNAs strongly associated with the hub genes were detected. These hub genes demonstrated solid diagnostic potential in both training and validation sets. Furthermore, immune infiltration analysis indicated a significant reduction in neutrophil levels in SAR patients. The downregulation of the hub genes in d-galactose-induced C2C12 cells was confirmed. Collectively, our findings identified 5 potential biomarkers for the diagnosis and therapy of SAR and emphasized the interaction between mitochondrial function and the immune response in the development of this condition.

This study aimed to explore the relationship between appendicular lean mass (ALM), osteoporosis (OP), and fracture risk in postmenopausal patients with type 2 diabetes mellitus (T2DM). A total of 1418 hospitalized postmenopausal patients with T2DM were enrolled. Bone mineral density (BMD) and ALM were measured using dual-energy X-ray absorptiometry (DXA). Based on BMD T-values, patients were categorized into OP and non-OP groups. General demographic data, biochemical markers, and body composition indices were compared between groups. Logistic regression analysis, nomogram construction, and receiver operating characteristic (ROC) curve analysis were performed to identify predictors and assess model performance. The prevalence of OP was significantly higher in patients with sarcopenia (SAC) compared to those without (P < 0.05). Significant between-group differences were observed in age, heart rate, 25-hydroxyvitamin D, height, weight, BMI, systolic blood pressure, presence of peripheral neuropathy, lymphocyte count, LDL cholesterol, total cholesterol, alanine aminotransferase, albumin, uric acid, creatinine, β-CTX, ALM/Ht2, and ALM (P < 0.05). Logistic regression identified ALM [OR = 0.785, 95% CI 0.697–0.884] and BMI [OR = 0.880, 95% CI 0.839–0.923] as protective factors against OP. A nomogram prediction model was developed using multiple independent predictors. ROC analysis showed good predictive performance, with an area under the curve (AUC) of 0.80 (95% CI 0.77–0.82), sensitivity of 82.0%, specificity of 67.8%, and an optimal cut-off value of 0.466. Lower age, BMI, and ALM were significantly associated with increased risk of OP. ALM and BMI emerged as independent protective factors. The developed nomogram can assist healthcare professionals in identifying key risk factors for OP in elderly postmenopausal patients with T2DM and support early screening and intervention strategies to reduce fracture risk.

Ankylosing spondylitis (AS) and sarcopenia (SARC) often coexist, leading to impaired mobility through reduced muscle strength and altered bone metabolism. This study aimed to identify core diagnostic genes linking AS and SARC. This research analyzed 2 AS and 1 SARC dataset from the Gene Expression Omnibus database. Moreover, module genes and differentially expressed genes (DEGs) were evaluated via linear models for microarray data (Limma) and the weighted gene co-expression network analysis. Furthermore, functional enrichment analysis, various machine learning (ML) algorithms, and protein–protein interaction networks were employed for elucidating key candidate genes for the diagnosis of AS patients with SARC. The Receiver Operating Characteristic curve plots were utilized to determine the diagnostic significance of key genes. The merged AS dataset identified 1768 and 438 DEGs and module genes, respectively, in SARC. The intersection of module genes in SARC and DEGs in AS revealed 287 genes, which were predominantly enriched in oxidative phosphorylation. The protein–protein interaction network indicated 30 node genes. Furthermore, ML analysis identified 10 candidate hub genes for diagnostic value evaluation. In total, 6 candidate genes indicated high diagnostic significance key genes with the area under the curve > 0.7. The current study determined 6 hub genes (ENSA, FAM43A, MDH2, NUBP1, SAMM50, and TM2D1) for diagnosing AS patients with SARC, therefore providing a theoretical reference for potential diagnostic targets in these patients.

With the acceleration of global population aging, sarcopenia (SA) and cognitive impairment have become major public health concerns. Observational studies suggest associations between them, but such findings may be biased by confounding and reverse causation. Previous Mendelian randomization (MR) studies have yielded inconsistent results. Therefore, this study applied a bidirectional MR design to clarify their causal relationships. We obtained genetic instrumental variables for SA-related traits, including hand grip strength, lean mass, and usual walking pace, from the UK Biobank. Data on cognitive performance were derived from a large genome-wide association studies meta-analysis published in Nature Genetics in 2018 (n = 257,841), with replication performed in an independent cohort from the IEU Open genome-wide association studies database (n = 22,593). Bidirectional MR analyses were primarily conducted using the inverse variance weighted method, supplemented by MR Egger, weighted median, and weighted mode approaches to validate robustness. Heterogeneity and pleiotropy were evaluated by Cochran Q and MR Egger intercept tests, while leave-one-out and Steiger directionality tests assessed robustness. Inverse variance weighted analysis demonstrated significant positive causal effects of genetically predicted right hand grip strength (odds ratio [OR] = 1.112, 95% confidence interval [CI]: 1.032–1.198, P = .005), right arm fat-free mass (OR = 1.060, 95% CI: 1.021–1.100, P = .002), left arm fat-free mass (OR = 1.046, 95% CI: 1.008–1.085, P = .017), right leg fat-free mass (OR = 1.060, 95% CI: 1.023–1.098, P = .001), left leg fat-free mass (OR = 1.050, 95% CI: 1.014–1.087, P = .006), whole body fat-free mass (OR = 1.081, 95% CI: 1.045–1.119, P < .001), and walking pace (OR = 1.414, 95% CI: 1.172–1.705, P < .001) on cognitive performance. In the reverse MR analysis, no significant causal effects of cognitive performance on SA-related traits were observed, except for walking pace. Genetic prediction of SA-related traits may indicate that cognitive impairment is a potential pathogenic factor. Monitoring the muscle health of older adults and preventing the onset or progression of SA could potentially slow cognitive decline. Furthermore, bidirectional MR results suggest a strong causal relationship between walking pace and cognitive performance.

Sarcopenia (SP) associated with functional impairment is highly prevalent; however, therapeutic strategies addressing this condition remain limited. Inflammation and oxidative stress are the key contributors. Suitably, formononetin (FMN) offers diverse benefits, including antioxidant, anti-apoptotic, and anti-inflammatory properties. Therefore, this study used network pharmacology to identify 81 potential target genes for FMN to alleviate SP. Serine/threonine-protein kinase 1 (AKT1), epidermal growth factor receptor (EGFR), and sirtuin 1 (SIRT1) as the core targets. Kyoto Encyclopedia of Genes and Genome analysis indicated that FMN primarily affects SP via the interleukin (IL)-17, PI3K-Akt and FoxO signalling pathways. Cell studies revealed that FMN reduces IL-6 release and boosts superoxide dismutase activity, thereby enhancing C2C12 skeletal muscle cell vitality. FMN intervention also enhanced AKT1 and SIRT1 gene and protein expression, decreased muscle-specific RING finger protein-1 gene expression, and increased EGFR protein expression. This suggests its anti-inflammatory and antioxidant effects in dexamethasone-treated C2C12 cells, potentially preventing muscle atrophy by inhibiting protein breakdown. These findings highlight the promising multi-target role and molecular mechanism of FMN in the treatment of SP and suggest future clinical applications.Graphical

Cistanche deserticola extract and its active components, echinacoside, ameliorate sarcopenia by activating the IGF-1/PI3K-AKT pathway to modulate ferroptosis.

Predictive performance of the geriatric nutritional risk index for sarcopenia: A meta-analysis.

Sarcopenia (SARC) presents considerable challenges to the quality of life for the elderly and exerts a significant economic strain on healthcare systems. Contemporary therapeutic methods, such as physical activity, dietary supplementation, and medication, frequently demonstrate restricted effectiveness and significant individual variation. This study seeks to identify new therapeutic targets through the analysis of lysosomal autophagy-related differentially expressed genes (LARDEGs) associated with SARC. Differentially expressed genes(DEGs) related to SARC were identified through an extensive analysis of microarray datasets (GSE8479 and GSE1428) obtained from the Gene Expression Omnibus. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway analysis, protein-protein interaction (PPI) network analysis, and Gene Set Enrichment Analysis were used to assess the biological functions, molecular pathways, autophagy-related molecular markers, and immune microenvironment linked to SARC DEGs. Our findings identified 12 LARDEGs, including BHLHE41, HLTF, UBE2D1, UBE2D2, NPC1, NDRG1, SLC22A18, CDKN1A, CALCOCO2, SCARB2, LGALS1, and RPS27A, that were significantly correlated with energy metabolism and mitochondrial function. We constructed a PPI network that identified six crucial hub genes: BHLHE41, UBE2D1, UBE2D2, CDKN1A, SCARB2, and RPS27A. This network provides significant insights into their functional roles and their potential as therapeutic targets. Additionally, an examination of immune infiltration demonstrated significant differences in the quantities of resting natural killer (NK) cells and M2 macrophages between SARC samples and control samples. CDKN1A displayed a positive correlation with M2 macrophages and an inverse relationship with resting NK cells. The results show how important the immune microenvironment is to the spread of SARC, suggesting promising pathways for the creation of immunotherapeutic strategies. Our research elucidates the molecular pathways implicated in SARC and establishes a foundation for future therapeutic approaches. However, additional validation is crucial to translating these findings into viable clinical applications.

Sarcopenia (SP) is an age-related disorder characterized by progressive loss of muscle strength, mass, and limb dysfunction, severely compromising the quality of life and life safety in older adults. With the global aging population, the incidence of this disease has been escalating, posing a significant public health challenge. Preclinical studies have demonstrated that acupuncture effectively mitigates muscle loss in rats; however, the field currently lacks robust randomized controlled trials (RCTs), marked by limitations such as the absence of sham acupuncture controls, multicenter designs, and standardized outcome metrics. Therefore, this study integrates acupuncture with exercise therapy, incorporating the following design highlights:A multicenter approach to enhance research reliability;A control group receiving sham acupuncture combined with exercise to eliminate the placebo effect;The most comprehensive and validated set of outcome measures to ensure study rigor and expand the conceptual framework for sarcopenia assessment.This research aims to provide robust evidence for acupuncture as an effective adjuvant therapy for SP. The study has been registered with the International Traditional Medicine Clinical Trials Registry Platform (ITMCTR2024000374).

BackgroundStudies indicate an association between cardiovascular health and sarcopenia (SP). Insulin resistance is significantly linked to both cardiovascular disease and diabetes. The estimated glucose disposal rate (eGDR), a reliable marker of insulin sensitivity, has an unclear relationship with SP, yet it may hold predictive value.MethodsData from 7,769 participants in the U.S. National Health and Nutrition Examination Survey (NHANES) 2011–2018 were analyzed. All analyses incorporated appropriate NHANES sampling weights, primary sampling units (PSUs), and stratification variables to ensure national representativeness and correct variance estimation. Multivariate logistic regression, restricted cubic splines (RCS) with specified knot placement, subgroup analyses with multiple comparison corrections, and mediation analysis were employed to examine the association between LC9 and SP prevalence. Mediation analysis was conducted to evaluate the role of eGDR levels in the LC9-SP relationship.ResultsAmong the 7,769 participants, 647 had sarcopenia. In crude models, each 10-point increase in LC9 was associated with a 4.9% decrease in sarcopenia odds (OR: 0.951, p < 0.001). Similarly, each 1-unit increase in eGDR was associated with a 26.5% decrease in the odds of sarcopenia (OR: 0.735, p < 0.001). However, after adjusting for all covariates including BMI, this association became non-significant (OR: 0.994, p = 0.282). Compared to the lowest tertile, participants in the highest tertiles of LC9 and eGDR had significantly lower odds of SP, with reductions of 83.4% (p < 0.001) and 86.0% (p < 0.001), respectively. RCS and threshold effect analysis revealed a non-linear relationship between LC9 and SP risk, with an inflection point identified at LC9 = 73.33. Mediation analysis indicated that eGDR partially mediated the association between LC9 and SP, accounting for 48.5% of the total effect (p < 0.001).ConclusionIn crude models, an inverse association was observed between LC9 and sarcopenia prevalence in US adults. However, this association became non-significant after full adjustment including BMI. The estimated glucose disposal rate (eGDR) showed statistical mediation of this relationship.

BACKGROUNDEsophageal cancer is a common malignancy with high mortality. Radiotherapy is an important treatment. Sarcopenia affects patients' physical function and prognosis. However, the relationship between sarcopenia diagnosed by Chun-Hou Chen method for sarcopenia measurement and index (C3SMI) criteria and esophageal cancer prognosis after radiotherapy is unclear.AIMTo explore the correlation between sarcopenia (SA) diagnosed based on C3SMI criteria and the prognosis of patients with esophageal cancer following radiotherapy.METHODSA retrospective analysis was conducted on the general clinical data of 131 esophageal cancer patients who received radiotherapy in the Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University from March 2021 to July 2024. Based on the presence of SA, the patients were assigned into two groups - the SA group and the non-SA group. Logistic regression analysis was used for investigating the risk factors influencing SA in esophageal cancer patients. Additionally, the patients were followed up, with their prognosis recorded. As per their prognostic outcomes, the patients were allocated into a good prognosis group and a poor prognosis group. The data of the two groups were compared. Using logistic regression analysis, the risk factors that may influence the prognosis of these patients were analyzed. SPSS 26.0 statistical software was introduced for analyzing the study data. Comparisons were made between groups using t-tests or χ2 tests based on the data type.RESULTSAs revealed through logistic regression analysis, age [odds ratio (OR) = 2.898, P = 0.038], body mass index (OR = 5.983, P = 0.006), prealbumin (OR = 6.253, P = 0.003), and Karnofsky performance status score (OR = 3.854, P = 0.010) were independent risk factors impacting SA for esophageal cancer patients (P < 0.05). Logistic regression analysis also found that age (OR = 3.823, P = 0.030), differentiation degree (OR = 4.802, P = 0.028), American Joint Committee on Cancer clinical staging (OR = 3.732, P = 0.013), alpha-fetoprotein level (OR = 3.508, P = 0.018), thrombospondin-1 level (OR = 5.749, P = 0.006), carcinoembryonic antigen level (OR = 3.873, P = 0.030), and SA (OR = 3.593, P = 0.017) were independent risk factors that may influence esophageal cancer patients' prognosis (P < 0.05).CONCLUSIONThe presence of SA has a significant relation to the poor prognosis of esophageal cancer patients, which highlights the importance of assessing and intervening in SA in clinical management so as to improve patient prognosis.

Aging is associated with a progressive change of body composition characterized by muscle mass decline and accumulation of adipose tissue that can lead to sarcopenia and obesity, respectively. The prevalence of sarcopenia is poorly known given the different parameters and thresholds in proposed definitions. The combination of obesity (defined as a percentage of body fat mass of > 25% in men and > 35% in women) and sarcopenia (SO) adds complexity to the characterization of this pathology. SARA-OBS aimed to better characterize sarcopenia (including SO) and its consequences on physical function over time, in community-dwelling older adults at risk of mobility disability, and to support the design of further interventional clinical trials. This was an international, multicenter, 6-month observational study of men and women aged ≥ 65 years suffering from sarcopenia according to the Foundation for the National Institute of Health (FNIH) cut-offs for Sarcopenia and with a Short Physical Performance Battery (SPPB) ≤ 8. The primary endpoint was the change in Gait Speed (GS) in the 400-meter walking test (400MWT), reported at baseline and at Month 6/ end of the study (EOS). Secondary endpoints included changes in handgrip strength (HGS), physical performance (6-Minute Walking Distance [6MWD], SPPB), the Physical Function Domain (PF-10) sub-score and total score of the SF-36 survey and the Sarcopenia and Quality of Life (SarQoL) questionnaire. Overall, the mean (± SD) change from baseline to Month 6/EOS in 400MWT GS was - 0.027 ± 0.171m/sec (p = 0.064). Both GS and 6MWD decreased significantly in subgroup with GS ≥ 0.8m/sec at baseline (-0.047 ± 0.185m/sec; p = 0.017 and - 24.01 ± 68.24m; p = 0.001, respectively). In subgroup with SPPB = 8 at baseline, 6MWD also decreased (-36.80 ± 67.60m; p < 0.001). We observed a significant change from baseline for 6MWD in the SO subgroup (-18.30 ± 81.95m; p = 0.013). Neither HGS nor SarQoL changed significantly from baseline to Month 6/EOS. SARA-OBS results contribute to defining subgroups of older adults at risk of functional decline over 6 months, specifically subjects with SPPB = 8, affecting GS and the 6MWD. Additionally, the SO subpopulation exhibited a relevant deterioration in physical function as evaluated by the 6MWD. NCT03021798 (ClinicalTrials.gov). Date of registration 16/01/2017.

Bu-Yang decoction attenuates OVX-induced sarcopenia by upregulating CXCR4 to suppress GPX4-mediated ferroptosis.

Type 2 diabetes (T2D) and sarcopenia (SA) commonly co-occur in clinical settings. This study aims to identify overlapping biomarkers for T2D and SA, thereby advancing the understanding of shared pathophysiological mechanisms. Gene expression data from the NCBI GEO database were analyzed to detect differentially expressed genes (DEGs) in T2D and SA using the limma package. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to identify significant gene modules in each condition, followed by functional enrichment analysis. A risk assessment model was established and evaluated through Support Vector Machine (SVM) analysis. Additionally, regulatory networks, including miRNAs and transcription factors, were constructed to investigate gene regulation. qRT‒PCR and western blotting were employed to validate the expression of these biomarkers in the muscle tissues of db/db mice. A total of 330 DEGs were identified in the T2D dataset, while 1054 were found in the SA dataset, with 50 overlapping genes. Key modules in each condition highlighted 30 shared genes, which were enriched in biological processes and pathways related to metabolic and immune functions. Fourteen intersecting hub genes exhibited significant differential expression across the disease datasets, supporting the development of a robust risk classification model. This model demonstrated strong predictive performance, with AUC values of 0.944 for T2D and 0.940 for SA. BDH1, FGF9, and LDHA were identified as key biomarkers through bioinformatics analysis and experimental validation. The identification of BDH1, FGF9, and LDHA offers both diagnostic value and potential therapeutic targets for T2D and SA, thus clarifying the shared pathogenesis of these diseases.

Clinical studies reveal bidirectional links between sarcopenia (SP) and diabetic nephropathy (DN). Damage to mitochondria in DN may result in diminished energy production, which consequently triggers SP. Consequently, mitochondria seem to function as critical nodes connecting DN with SP. The objective of this research was to pinpoint biomarkers associated with mitochondrial dysfunction in DN and SP. By analyzing the Gene Expression Omnibus (GEO) repository, we identified shared differentially expressed genes (DEGs) in the DN (GSE96804, GSE30528) and SP (GSE1428, GSE136344) datasets that displayed similar expression trends in mitochondrial genes. Using Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), Extreme Gradient Boosting (XGB), and Random Forest (RF) algorithms, we identified three key mitochondrial hub genes. Diagnostic nomograms were created to predict DN and SP risk. We assessed immune infiltration using CIBERSORT and built a drug-gene network with Cytoscape. Molecular docking determined binding affinities between potential drugs and hub genes, which were validated in the datasets. Analysis of GEO datasets identified 80 shared DEGs between DN and SP, including 10 mitochondria-related genes. Utilizing four machine learning algorithms (LASSO, SVM, XGBoost, RF), we pinpointed three mitochondrial hub genes. Subsequent validation confirmed two key mitochondria-related genes - HTT and TTC19 - as shared diagnostic biomarkers for both DN and SP. These biomarkers demonstrated strong diagnostic power (AUC >0.8), leading to the construction of diagnostic nomograms. Immune infiltration analysis revealed elevated M1 macrophages in DN and increased M2 macrophages in SP, with both biomarkers showing significant correlations with various immune cells. Gene set enrichment analysis linked HTT and TTC19 to mitochondrial metabolic processes. Crucially, in silico drug prediction identified 156 potential drugs, and molecular docking confirmed a high binding affinity between acetaminophen and the HTT protein. Our study identifies HTT and TTC19 as novel mitochondria-immune related biomarkers common to both DN and SP, providing insights into their shared pathogenesis involving mitochondrial dysfunction and immune dysregulation. The computational prediction of acetaminophen interaction highlights a potential avenue for therapeutic exploration. Further clinical and mechanistic studies are warranted to validate these findings and elucidate the underlying pathways.