Evidence map›Paper›PMID 40207397›Full record

ArticleJournal of cachexia, sarcopenia and muscle2025

Comparative Analysis of Primary Sarcopenia and End-Stage Renal Disease-Related Muscle Wasting Using Multi-Omics Approaches.

Daiki Setoyama, Dohyun Han, Jingwen Tian, Ho Yeop Lee, Hyun Suk Shin, Ha Thi Nga, Thi Linh Nguyen, Ji Sun Moon, Hyo Ju Jang, Evonne Kim and 5 more

Abstract readComparative Study
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Daiki SetoyamaDepartment of Clinical Chemistry and Laboratory Medicine, Kyushu University Hospital, Fukuoka, Japan.
Dohyun HanProteomics Core Facility, Seoul National University Hospital Biomedical Research Institute, Seoul, South Korea.
Jingwen TianLaboratory of Endocrinology and Immune System, Chungnam National University School of Medicine, Daejeon, South Korea.
Ho Yeop LeeLaboratory of Endocrinology and Immune System, Chungnam National University School of Medicine, Daejeon, South Korea.
Hyun Suk ShinProteomics Core Facility, Seoul National University Hospital Biomedical Research Institute, Seoul, South Korea.
Ha Thi NgaLaboratory of Endocrinology and Immune System, Chungnam National University School of Medicine, Daejeon, South Korea.
Thi Linh NguyenLaboratory of Endocrinology and Immune System, Chungnam National University School of Medicine, Daejeon, South Korea.
Ji Sun MoonLaboratory of Endocrinology and Immune System, Chungnam National University School of Medicine, Daejeon, South Korea.
Hyo Ju JangLaboratory of Endocrinology and Immune System, Chungnam National University School of Medicine, Daejeon, South Korea.
Evonne KimDepartment of Biomedical Sciences, BK21 FOUR Biomedical Science Program, Seoul National University College of Medicine, Seoul, South Korea.
Seong-Kyu ChoeDepartment of Medicine, Graduate School, Wonkwang University, Iksan, South Korea.
Sang Hyeon JuDepartment of Internal Medicine, Chungnam National University School of Medicine, Daejeon, South Korea.
Dae Eun ChoiDepartment of Internal Medicine, Chungnam National University School of Medicine, Daejeon, South Korea.
Obin KwonDepartment of Biomedical Sciences, BK21 FOUR Biomedical Science Program, Seoul National University College of Medicine, Seoul, South Korea.
Hyon-Seung YiLaboratory of Endocrinology and Immune System, Chungnam National University School of Medicine, Daejeon, South Korea.ORCID 0000-0002-3767-1954

Funding

Korea government (MSIT)Korea Health Industry Development Institute (KHIDI)Ministry of Health and Welfare, Republic of Korea RS-2022-KH130308Ministry of Health and Welfare, Republic of Korea RS-2024-00507183Ministry of Science, ICT, and Future Planning, KoreaNational Research Foundation of Korea (NRF) NRF-2020R1C1C1008033National Research Foundation of Korea (NRF) NRF-2021R1A5A8029876National Research Foundation of Korea (NRF) NRF-2023R1A2C3006220
6 · The paper itself

Abstract

backgroundAge-related primary sarcopenia and end-stage renal disease (ESRD)-related muscle wasting are discrete entities; however, both manifest as a decline in skeletal muscle mass and strength. The etiological pathways differ, with aging factors implicated in sarcopenia and a combination of uremic factors, including haemodialysis, contributing to ESRD-related muscle wasting. Understanding these molecular nuances is imperative for targeted interventions, and the integration of proteomic and metabolomic data elucidate these intricate processes.

methodsWe generated detailed clinical data and multi-omics data (plasma proteomics and metabolomics) for 78 participants to characterise sarcopenia (n = 28; mean age, 72.6 ± 7.0 years) or ESRD (n = 22; 61.6 ± 5.5 years) compared with controls (n = 28; 69.3 ± 5.7 years). Muscle mass was measured using bioelectrical impedance analysis and handgrip strength. Five-times sit-to-stand test performance was measured for all participants. Sarcopenia was diagnosed in accordance with the 2019 Consensus Guidelines from the Asian Working Group for Sarcopenia. An abundance of 234 metabolites and 722 protein groups was quantified in all plasma samples using liquid chromatography with tandem mass spectrometry.

resultsMuscle mass, handgrip strength and lower limb muscle function significantly lower in the sarcopenia group and the ESRD group compared with those in the control group. Metabolomics revealed altered metabolites, highlighting exclusive differences in ESRD-related muscle wasting. Metabolite set enrichment analysis revealed the involvement of numerous metabolic intermediates associated with urea cycle, amino acid metabolism and nucleic acid metabolism. Catecholamines, including epinephrine, dopamine and serotonin, are significantly elevated in the plasma of patients within the ESRD group. Proteomics data exhibited a clearer distinction among the three groups compared with the metabolomics data, particularly in distinguishing the control group from the sarcopenia group. The ciliary neurotrophic factor receptor was top-ranked in terms of the variable importance of projection scores. Plasma AHNAK protein levels was higher in the sarcopenia group but was lower in the ESRD group. Proteomic set enrichment analysis revealed enrichment of several pathways related to sarcopenia, such as hemopexin, defence response and cell differentiation, in sarcopenia group. Multi-omic integration analysis revealed associations between relevant metabolites, including catecholamines, and a group of annotated proteins in extracellular exosomes.

conclusionsWe identified distinct multi-omic signatures in individuals with ESRD or sarcopenia, providing new insights into the mechanisms underlying ESRD-related muscle wasting, which differ from primary sarcopenia. These findings may support interventions for context-dependent muscle loss and contribute to the development of targeted treatments and preventive strategies for muscle wasting.

Indexed as

Kidney Failure, ChronicMetabolomicsMuscular AtrophySarcopeniaAgedFemaleHumansMaleMiddle AgedMultiomicsMuscle, SkeletalProteomicsend‐stage renal diseasemetabolomicsmulti‐omicsproteomicssarcopenia

Identifiers

PMID40207397
PMCPMC11982700

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.