Evidence map›Paper›PMID 26764052›Full record

ArticleAmerican journal of physiology. Regulatory, integrative and comparative physiology2016

Diminished anabolic signaling response to insulin induced by intramuscular lipid accumulation is associated with inflammation in aging but not obesity.

Donato A Rivas, Devin J McDonald, Nicholas P Rice, Prashanth H Haran, Gregory G Dolnikowski, Roger A Fielding

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in American journal of physiology. Regulatory, integrative and comparative physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed
7.4field-weighted citation impact, top 2% 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

78 citing papers in PubMed, 131 citations in OpenAlex.

  1. Trial
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  6. Rethinking Osteoporosis Drugs: Can We Simultaneously Address Sarcopenia?International journal of molecular sciences · 2025
    Review
  7. Osteosarcopenia in Chronic Kidney Disease: An Overlooked Syndrome?Journal of cachexia, sarcopenia and muscle · 2025
    Review
  8. Article
  9. Review
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  11. Article
  12. Review
  13. Article
  14. Article
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  16. Article
  17. Sarcopenic obesity in cancer.Radiology and oncology · 2024
    Review
  18. Beyond Inflammaging: The Impact of Immune System Aging on Age-Related Muscle Decline, Results From the InCHIANTI Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024
    Article
  19. Article
  20. Article

18 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 1 country.

Donato A RivasNutrition, Exercise Physiology and Sarcopenia Laboratory, Tufts University, Boston, Massachusetts; and donato.rivas@tufts.edu.
Devin J McDonaldNutrition, Exercise Physiology and Sarcopenia Laboratory, Tufts University, Boston, Massachusetts; and.
Nicholas P RiceNutrition, Exercise Physiology and Sarcopenia Laboratory, Tufts University, Boston, Massachusetts; and.
Prashanth H HaranNutrition, Exercise Physiology and Sarcopenia Laboratory, Tufts University, Boston, Massachusetts; and.
Gregory G DolnikowskiMass Spectrometry Unit; Jean Mayer U.S. Department of Agriculture, Human Nutrition Research Center on Aging, Tufts University, Boston, Massachusetts.
Roger A FieldingNutrition, Exercise Physiology and Sarcopenia Laboratory, Tufts University, Boston, Massachusetts; and.
Tufts University · USJean Mayer Human Nutrition Research Center on Aging · US

Funding

TUFTS--FIELDINGP30AG031679 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI Ravi Jasuja · 2008 to 2026
$23.9M
NIA NIH HHS 1P30AG031679NIA NIH HHS P30 AG031679
6 · The paper itself

Abstract

The loss of skeletal muscle mass is observed in many pathophysiological conditions, including aging and obesity. The loss of muscle mass and function with aging is defined as sarcopenia and is characterized by a mismatch between skeletal muscle protein synthesis and breakdown. Characteristic metabolic features of both aging and obesity are increases in intramyocellular lipid (IMCL) content in muscle. IMCL accumulation may play a mechanistic role in the development of anabolic resistance and the progression of muscle atrophy in aging and obesity. In the present study, aged and high-fat fed mice were used to determine mechanisms leading to muscle loss. We hypothesized the accumulation of bioactive lipids in skeletal muscle, such as ceramide or diacylglycerols, leads to insulin resistance with aging and obesity and the inability to activate protein synthesis, contributing to skeletal muscle loss. We report a positive association between bioactive lipid accumulation and the loss of lean mass and muscle strength. Obese and aged animals had significantly higher storage of ceramide and diacylglycerol compared with young. Furthermore, there was an attenuated insulin response in components of the mTOR anabolic signaling pathway. We also observed differential increases in the expression of inflammatory cytokines and the phosphorylation of IκBα with aging and obesity. These data challenge the accepted role of increased inflammation in obesity-induced insulin resistance in skeletal muscle. Furthermore, we have now established IκBα with a novel function in aging-associated muscle loss that may be independent of its previously understood role as an NF-κB inhibitor.

Indexed as

Insulin ResistanceAgingAnimalsInsulinLipid MetabolismLipidsMaleMetabolismMiceMice, Inbred C57BLMuscle, SkeletalMyositisObesitySarcopeniaSignal TransductionInsulinLipidsagingceramidediacylglycerolinflammationinsulinintramuscular lipidsobesitysarcopenia

Identifiers

PMID26764052
PMCPMC4867383
OpenAlexW2321444106

What OpenQuestion holds

Textmetadata
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.