Metabolomics analysis reveals serum biomarkers in patients with diabetic sarcopenia

From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies

In the dynamic landscape of targeted therapeutics, drug discovery has pivoted towards understanding underlying disease mechanisms, placing a strong emphasis on molecular perturbations and target identification. This paradigm shift, crucial for drug discovery, is underpinned by big data, a transformative force in the current era. Omics data, characterized by its heterogeneity and enormity, has ushered biological and biomedical research into the big data domain. Acknowledging the significance of integrating diverse omics data strata, known as multi-omics studies, researchers delve into the intricate interrelationships among various omics layers. This review navigates the expansive omics landscape, showcasing tailored assays for each molecular layer through genomes to metabolomes. The sheer volume of data generated necessitates sophisticated informatics techniques, with machine-learning (ML) algorithms emerging as robust tools. These datasets not only refine disease classification but also enhance diagnostics and foster the development of targeted therapeutic strategies. Through the integration of high-throughput data, the review focuses on targeting and modeling multiple disease-regulated networks, validating interactions with multiple targets, and enhancing therapeutic potential using network pharmacology approaches. Ultimately, this exploration aims to illuminate the transformative impact of multi-omics in the big data era, shaping the future of biological research.

Causal Associations with Arterial Stiffness and Sarcopenia: A Mendelian Randomization Analysis

Observational studies and clinical trials indicate a link between arterial stiffness (AS) and sarcopenia (SAR), yet the causal relationship between these remains unclear. The study aims to investigate the causal connection from AS to SAR by Mendelian randomization (MR). We analyzed Genome-Wide Association Studies data for AS indicators: pulse wave arterial stiffness index (PWASI) and pulse wave peak-to-peak time (PPT), and SAR indicators: low hand grip strength (LHGS), usual walking pace (UWP), moderate-to-vigorous physical activity levels (MVPA), and walk or cycle unassisted for 10 minutes. The inverse variance-weighted, MR-Egger, weighted mode, and weighted median were applied to MR. There is a bidirectional causal relationship between the AS and SAR. The PWASI has a causation with UWP (odds ratio [OR] = 0.97, 95% confidence interval [CI] = 0.94-0.99). The PPT has a causal association with MVPA (OR = 1.08, 95% CI = 1.002-1.144) and UWP (OR = 1.05, 95% CI = 1.017-1.096). The LHGS is causally associated with PPT (OR = 0.95, 95% CI = 0.91-0.98) and UWP has a causal association with PWASI (OR = 0.77, 95% CI = 0.65-0.90) and PPT (OR = 1.37, 95% CI = 1.17-1.60). The increased AS could reduce the motor ability slightly and the lower upper and lower limb strength could lead to the higher AS. This bidirectional causal relationship of the two may offer novel perspectives for advancing the understanding of the underlying mechanisms related to AS and muscle pathophysiology.

Bile acid signaling in skeletal muscle homeostasis: from molecular mechanisms to clinical applications

The intricate relationship between bile acid metabolism and skeletal muscle function has emerged as a crucial area of research in metabolic health. This review synthesizes current evidence highlighting the fundamental role of bile acids as key signaling molecules in muscle homeostasis and their therapeutic potential in muscle-related disorders. Recent advances in molecular biology and metabolomics have revealed that bile acids, beyond their classical role in lipid absorption, function as essential regulators of muscle mass and function through multiple signaling pathways, particularly via the nuclear receptor FXR and membrane receptor TGR5. Clinical studies have demonstrated significant associations between altered bile acid profiles and muscle wasting conditions, while experimental evidence has elucidated the underlying mechanisms linking bile acid signaling to muscle protein synthesis, energy metabolism, and regeneration capacity. We critically examine the emerging therapeutic strategies targeting bile acid pathways, including receptor-specific agonists, microbiome modulators, and personalized interventions based on individual bile acid profiles. Additionally, we discuss novel diagnostic approaches utilizing bile acid-based biomarkers and their potential in early detection and monitoring of muscle disorders. This review also addresses current challenges in standardization and clinical translation while highlighting promising future directions in this rapidly evolving field. Understanding the bile acid-muscle axis may provide new opportunities for developing targeted therapies for age-related muscle loss and metabolic diseases.

Erythrocyte Fatty Acid Patterns Are Associated with Skeletal Muscle Mass in Chinese Children

BACKGROUND

Nutritional factors are important for skeletal muscle mass and grip strength development in children.

OBJECTIVES

This study aimed to investigate the relationship between erythrocyte membrane fatty acid patterns (FAPs) and skeletal muscle mass and grip strength in children.

METHODS

A total of 452 children aged 6-9 y were included in this study. Appendicular skeletal muscle mass (ASM) was assessed by dual-energy X-ray absorptiometry. Hand grip strength was determined by the Jamar Plus+ hand dynamometer (Sammons Preston). Appendicular skeletal muscle mass index (ASMI) was calculated, and the relative concentrations of 20 fatty acids in erythrocyte membranes were measured by gas chromatography-mass spectrometry. Factor analysis was used to explore the relationship between fatty acids and skeletal muscle mass and grip strength.

RESULTS

Five FAPs were identified by factor analysis, and after adjusting for covariates, a multiple linear regression model showed that FAP2 (high C17:0, C20:5 n-3, C22:6 n-3) showed a negative correlation with ASM (β = -0.214; P < 0.001), ASMI (β = -0.085; P < 0.001), and left-hand grip strength (β = -0.235; P = 0.012). FAP3 (high C14:0, C15:0, C16:0, C16:1 n-7, low C20:4 n-6) scores were positively correlated with ASM (β = 0.134, P = 0.017). No other associations between FAPs and skeletal muscle mass were found.

CONCLUSIONS

The relationship between different FAPs and skeletal muscle health in children aged 6-9 y may be different. The pattern characterized by higher concentrations of C17:0, C20:5 n-3, and C22:6 n-3 in erythrocyte membranes may be associated with lower skeletal muscle mass. The pattern featuring higher concentrations of C14:0, C15:0, C16:0, and C16:1 n-7 and lower concentrations of C20:4 n-6 may be protective factors for muscle mass.

GNLY as A Novel Cis-eQTL and Cis-pQTL Mediated Susceptibility Gene in Suppressing Prostatitis. Mendelian Randomization Study

BACKGROUND

Prostatitis is characterized by high prevalence, low cure rates, and frequent recurrences, and remains one of the most clinically challenging problems. Hence, in this article, we first integrated Mendelian randomization (MR) with expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) data to identify novel therapeutic targets and their potential metabolic mechanisms for prostatitis.

METHODS

Prostatitis-related genetic data, eQTLs, pQTLs, and 1400 metabolites were downloaded from online databases. MR, or summary data-based MR (SMR) analyses were applied to assess the potential causal relationships between exposures and predicted outcomes. Sensitivity analysis was conducted using pleiotropy, heterogeneity, and leave-one-out analysis to evaluate the robustness of our results.

RESULTS

Based on our results, we first identified and validated GNLY as a novel cis-eQTL and cis-pQTL-mediated susceptibility gene for reducing prostatitis risk in five independent datasets (one discovery dataset and four validation datasets) (all p <0.05). Meanwhile, we also found that the GNLY eQTL could increase the metabolite of sphingomyelin level (d18:0/20:0, d16:0/22:0) risks (p <0.05), and the metabolite of sphingomyelin level (d18:0/20:0, d16:0/22:0) could reduce the risk of prostatitis (p <0.05). According to the above-mentioned relationships, we finally revealed the potential metabolic mechanism of GNLY eQTL in suppressing prostatitis via regulating the metabolite of sphingomyelin level (d18:0/20:0, d16:0/22:0).

CONCLUSIONS

We successfully identified GNLY as a novel cis-eQTL and cis-pQTL-mediated susceptibility gene in suppressing prostatitis and its potential metabolic mechanism via regulating sphingomyelin (d18:0/20:0, d16:0/22:0) levels, providing a novel therapeutic target and paving the way for future GNLY-related studies in prostatitis.

Sarcopenia: recent advances for detection, progression, and metabolic alterations along with therapeutic targets

Sarcopenia, a disorder marked by muscle loss and dysfunction, is a global health concern, particularly in aging populations. Sarcopenia is intricately related to various health conditions, including obesity, dysphagia, and frailty, which underscores the complexity. Despite recent advances in metabolomics and other omics data for early detection and treatment, the precise characterization and diagnosis of sarcopenia remains challenging. In the present review we provide an overview of the complex metabolic mechanisms that underlie sarcopenia, with particular emphasis on protein, lipid, carbohydrate, and bone metabolism. The review highlights the importance of leucine and other amino acids in promoting muscle protein synthesis and clarifies the critical role played by amino acid metabolism in preserving muscular health. In addition, the review provides insights regarding lipid metabolism on sarcopenia, with an emphasis on the effects of inflammation and insulin resistance. The development of sarcopenia is largely influenced by insulin resistance, especially with regard to glucose metabolism. Overall, the review emphasizes the complex relationship between bone and muscle health by highlighting the interaction between sarcopenia and bone metabolism. Furthermore, the review outlines various therapeutic approaches and potential biomarkers for diagnosing sarcopenia. These include pharmacological strategies such as hormone replacement therapy and anabolic steroids as well as lifestyle modifications such as exercise, nutrition, and dietary changes.

Genetically predicted metabolites mediate the association between immune cells and metabolic dysfunction-associated steatotic liver disease: a mendelian randomization study

BACKGROUND

Existing studies have presented limited and disparate findings on the nexus between immune cells, plasma metabolites, and metabolic dysfunction-associated steatotic liver disease (MASLD). The aim of this study was to investigate the causal relationship between immune cells and MASLD. Additionally, we aimed to identify and quantify the potential mediating role of metabolites.

METHODS

A Mendelian randomization (MR) analysis was conducted using two samples of pooled data from genome-wide association studies on MASLD that included 2568 patients and 409,613 control individuals. Additionally, a mediated MR study was employed to quantify the metabolite-mediated immune cell effects on MASLD.

RESULTS

In this study, eight immunophenotypes were linked to the risk of MASLD, and thirty-five metabolites/metabolite ratios were linked to the occurrence of MASLD. Furthermore, a total of six combinations of immunophenotypic and metabolic factors demonstrated effects on the occurrence of MASLD, although the mediating effects of metabolites were not significant.

CONCLUSION

Our study demonstrated that certain immunophenotypes and metabolite/metabolite ratios have independent causal relationships with MASLD. Furthermore, we identified specific metabolites/metabolite ratios that are associated with an increased risk of MASLD. However, their mediating role in the causal association between immunophenotypes and MASLD was not significant. It is important to consider immune and metabolic disorders among patients with MASLD in clinical practice.

d-Pinitol Improves Diabetic Sarcopenia by Regulation of the Gut Microbiome, Metabolome, and Proteome in STZ-Induced SAMP8 Mice

d-Pinitol (DP) is primarily found in Vigna sinensis, which has been shown to have hypoglycemic and protective effects on target organs. However, the mechanism of DP in treating diabetic sarcopenia (DS) is still unclear. To explore the underlying mechanism of DS and the protective targets of DP by high-throughput analysis of 16S rRNA gene, metabolome, and the proteome. Streptozotocin-induced SAMP8 mice were intragastrically administrated DP (150 mg/kg) for 8 weeks. Fecal 16S rRNA gene sequencing and gastrocnemius muscle metabolomic and proteomic analyses were completed to investigate the gut-muscle axis interactions. DP significantly alleviated the muscle atrophy in diabetic mice. Dysfunction of the gut microbiota was observed in the DS mice. DP significantly reduced the Parabacteroides, Akkermansia, and Enterobacteriaceae, while it increased Lachnospiraceae_NK4A136. Metabolome and proteome revealed that 261 metabolites and 626 proteins were significantly changed in the gastrocnemius muscle of diabetic mice. Among these, DP treatment restored 44 metabolites and 17 proteins to normal levels. Functional signaling pathways of DP-treated diabetic mice included nucleotide metabolism, β-alanine, histidine metabolism, ABC transporters, and the calcium signaling pathway. We systematically explored the molecular mechanism of DS and the protective effect of DP, providing new insights that may advance the treatment of sarcopenia.

The causal relationship of human blood metabolites with the components of Sarcopenia: a two-sample Mendelian randomization analysis

BACKGROUND

Sarcopenia is a progressive loss of muscle mass and function. Since skeletal muscle plays a critical role in metabolic homeostasis, identifying the relationship of blood metabolites with sarcopenia components would help understand the etiology of sarcopenia.

METHODS

A two-sample Mendelian randomization study was conducted to examine the causal relationship of blood metabolites with the components of sarcopenia. Summary genetic association data for 309 known metabolites were obtained from the Twins UK cohort and KORA F4 study (7824 participants). The summary statistics for sarcopenia components [hand grip strength (HGS), walking pace (WP), and appendicular lean mass (ALM)] were obtained from the IEU Open GWAS project (461,089 participants). The inverse variance weighted method was used, and the MR-Egger, weighted median, and MR-PRESSO were used for the sensitivity analyses. Metabolic pathways analysis was further performed.

RESULTS

Fifty-four metabolites associated with sarcopenia components were selected from 275 known metabolites pool. Metabolites that are causally linked to the sarcopenia components were mainly enriched in amino sugar and nucleotide sugar metabolism, galactose metabolism, fructose and mannose metabolism, carnitine synthesis, and biotin metabolism. The associations of pentadecanoate (15:0) with ALM, and 3-dehydrocarnitine and isovalerylcarnitine with HGS were significant after Bonferroni correction with a threshold of P < 1.82 × 10- 4 (0.05/275). Meanwhile, the association of hyodeoxycholate and glycine with the right HGS, and androsterone sulfate with ALM were significant in the sensitivity analyses.

CONCLUSION

Blood metabolites from different metabolism pathways were causally related to the components of sarcopenia. These findings might benefit the understanding of the biological mechanisms of sarcopenia and targeted drugs development for muscle health.

Aging-Related Sarcopenia: Metabolic Characteristics and Therapeutic Strategies

The proportion of the elderly population is gradually increasing as a result of medical care advances, leading to a subsequent surge in geriatric diseases that significantly impact quality of life and pose a substantial healthcare burden. Sarcopenia, characterized by age-related decline in skeletal muscle mass and quality, affects a considerable portion of older adults, particularly the elderly, and can result in adverse outcomes such as frailty, fractures, bedridden, hospitalization, and even mortality. Skeletal muscle aging is accompanied by underlying metabolic changes. Therefore, elucidating these metabolic profiles and specific mechanisms holds promise for informing prevention and treatment strategies for sarcopenia. This review provides a comprehensive overview of the key metabolites identified in current clinical studies on sarcopenia and their potential pathophysiological alterations in metabolic activity. Besides, we examine potential therapeutic strategies for sarcopenia from a perspective focused on metabolic regulation.

Metabolic clues to aging: exploring the role of circulating metabolites in frailty, sarcopenia and vascular aging related traits and diseases

Background: Physical weakness and cardiovascular risk increase significantly with age, but the underlying biological mechanisms remain largely unknown. This study aims to reveal the causal effect of circulating metabolites on frailty, sarcopenia and vascular aging related traits and diseases through a two-sample Mendelian Randomization (MR) analysis. Methods: Exposures were 486 metabolites analyzed in a genome-wide association study (GWAS), while outcomes included frailty, sarcopenia, arterial stiffness, atherosclerosis, peripheral vascular disease (PAD) and aortic aneurysm. Primary causal estimates were calculated using the inverse-variance weighted (IVW) method. Methods including MR Egger, weighted median, Q-test, and leave-one-out analysis were used for the sensitive analysis. Results: A total of 125 suggestive causative associations between metabolites and outcomes were identified. Seven strong causal links were ultimately identified between six metabolites (kynurenine, pentadecanoate (15:0), 1-arachidonoylglycerophosphocholine, androsterone sulfate, glycine and mannose) and three diseases (sarcopenia, PAD and atherosclerosis). Besides, metabolic pathway analysis identified 13 significant metabolic pathways in 6 age-related diseases. Furthermore, the metabolite-gene interaction networks were constructed. Conclusion: Our research suggested new evidence of the relationship between identified metabolites and 6 age-related diseases, which may hold promise as valuable biomarkers.

Integrative analysis of transcriptome and proteome in primary Sjögren syndrome

OBJECTIVE

Primary Sjögren's syndrome (pSS) is a intricate autoimmune disease mainly characterized of immune-mediated destruction of exocrine tissues, such as salivary and lacrimal glands, occurring dry mouth and eyes. Although some breakthroughs in understanding pSS have been uncovered, many questions remain about its pathogenesis, especially the internal relations between exocrine glands and secretions.

METHOD

Transcriptomic and proteomic analyses were conducted on salivary tissues and saliva in experimental Sjögren syndrome (ESS). The ESS model was established by immunization with salivary gland protein. The expression of mRNAs and proteins in salivary tissues and saliva were determined by high-throughput sequencing transcriptomic analysis and LC-MS/MS-based proteome, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to recognize dysregulated genes and proteins. The association between RNA and protein abundance was investigated to provides a comprehensive understanding of RNA-protein correlations in the pathogenesis of pSS.

RESULTS

As a result, we successfully established the ESS model. We recognized 3221 differentially expressed genes (DEGs) and 253 differentially expressed proteins (DEPs). The sample analysis showed that 61 proteins overlapped through the integrative analysis of transcriptomics and proteomics data. The enrichment pathway analysis of DEGs and DEPs in samples showed alterations in renin-angiotensin-system (RAS), lysosome, and apoptosis. Notably, we found that some genes, such as AGT, FN1, Klk1b26, Klk1, Klk1b5, Klk1b3 had a consistent trend in the regulation at the RNA and protein levels and might be potential diagnostic biomarkers of pSS.

CONCLUSION

Herein, we found critical processes and potential biomakers that may contribute to pSS pathogenesis by analyzing dysregulated genes and pathways. Additionally, the integrative multi-omics datasets provided additional insight into understanding complicated disease mechanisms.