Evidence map›Paper›PMID 30318485›Full record

ArticleAging2018

A joint analysis of metabolomic profiles associated with muscle mass and strength in Caucasian women.

Qi Zhao, Hui Shen, Kuan-Jui Su, Qing Tian, Lan-Juan Zhao, Chuan Qiu, Timothy J Garrett, Jiawang Liu, David Kakhniashvili, Hong-Wen Deng

Open access · greenAbstract read
In one paragraph

Article in Aging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% of its field
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

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

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  19. Identification and Functional Characterization of Metabolites for Skeletal Muscle Mass in Early Postmenopausal Chinese Women.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022
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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

10 authors at 4 institutions in 2 countries.

Qi Zhao *Department of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
Hui Shen *Tulane Center of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.
Kuan-Jui SuTulane Center of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.
Qing TianTulane Center of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.
Lan-Juan ZhaoTulane Center of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.
Chuan QiuTulane Center of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.
Timothy J GarrettSoutheast Center for Integrated Metabolomics Core, University of Florida, Gainesville, FL 32610, USA.
Jiawang LiuMedicinal Chemistry Core, Office of Research, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
David KakhniashviliProteomics and Metabolomics Core, Office of Research, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
Hong-Wen DengTulane Center of Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.
Tulane University · USUniversity of Tennessee Health Science Center · USCentral South University · CNUniversity of Florida · US

Funding

Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Ning Liu · 2016 to 2026
$25.3M
Trans-omics Integration of Multi-omics Studies for OsteoporosisU19AG055373 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI Chuan Qiu · 2017 to 2026
$24.3M
Southeast Resource Center for Integrated Metabolomics (SECIM)U24DK097209 · NIDDK · UNIVERSITY OF FLORIDA · PI EDISON, ARTHUR S, YOST, RICHARD A. · 2013 to 2017
$9.2M
Epigenomewide DNA Methylation Study for Osteoporosis RiskR01AR059781 · NIAMS · TULANE UNIVERSITY OF LOUISIANA · PI DENG, HONG-WEN · 2012 to 2016
$3.1M
Decoding Methylation Mediated Epigenomic Contributions to Male OsteoporosisR01AR069055 · NIAMS · TULANE UNIVERSITY OF LOUISIANA · PI DENG, HONG-WEN · 2017 to 2021
$2.9M
Integration of brain imaging with genomic and epigenomic dataR01MH104680 · NIMH · TULANE UNIVERSITY OF LOUISIANA · PI CALHOUN, VINCE D, DENG, HONG-WEN · 2014 to 2017
$2.1M
NIAMS NIH HHS R01 AR059781NIAMS NIH HHS R01 AR069055NIA NIH HHS U19 AG055373NIDDK NIH HHS U24 DK097209NIGMS NIH HHS P20 GM109036NIMH NIH HHS R01 MH104680
6 · The paper itself

Abstract

Both loss of muscle mass and strength are important sarcopenia-related traits. In this study, we investigated both specific and shared serum metabolites associated with these two traits in 136 Caucasian women using a liquid chromatography-mass spectrometry method. A joint analysis of multivariate traits was used to examine the associations of individual metabolites with muscle mass measured by the body mass index-adjusted appendicular lean mass (ALM/BMI) and muscle strength measured by hand grip strength (HGS). After adjusting for multiple testing, nine metabolites including two amino acids (aspartic acid and glutamic acid) and an amino acid derive (pipecolic acid), one peptide (phenylalanyl-threonine), one carbohydrate (methyl beta-D-glucopyranoside), and four lipids (12S-HETRE, arachidonic acid, 12S-HETE, and glycerophosphocholine) were significant in the joint analysis. Of them, the two amino acids (aspartic acid and glutamic acid) and two lipids (12S-HETRE and 12S-HETE) were associated with both ALM/BMI and HGS, and the other five were only associated with ALM/BMI. The pathway analysis showed the amino acid metabolism pathways (aspartic acid and glutamic acid) might play important roles in the regulation of muscle mass and strength. In conclusion, our study identified novel metabolites associated with sarcopenia-related traits, suggesting novel metabolic pathways for muscle regulation.

Indexed as

Energy MetabolismMuscle StrengthWhite PeopleAdultBiomarkersBody CompositionChromatography, High Pressure LiquidCross-Sectional StudiesFemaleHumansMetabolomicsMuscle, SkeletalPilot ProjectsSarcopeniaSex FactorsSpectrometry, Mass, Electrospray IonizationBiomarkersgrip strengthlean massmetabolitemetabolomicsmusclesarcopenia

Identifiers

PMID30318485
PMCPMC6224264
OpenAlexW2896522016

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.