Evidence map›Paper›PMID 31652310›Full record

ArticleThe Journal of clinical endocrinology and metabolism2020

Kinome Profiling Reveals Abnormal Activity of Kinases in Skeletal Muscle From Adults With Obesity and Insulin Resistance.

Yue Qi, Xiangmin Zhang, Berhane Seyoum, Zaher Msallaty, Abdullah Mallisho, Michael Caruso, Divyasri Damacharla, Danjun Ma, Wissam Al-Janabi, Rebecca Tagett and 7 more

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of clinical endocrinology and metabolism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

10 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
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  4. Roles of naïve CD4Journal of translational medicine · 2024
    Article
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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

17 authors at 2 institutions in 3 countries.

Yue QiDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Xiangmin ZhangDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Berhane SeyoumDivision of Endocrinology, Wayne State University School of Medicine, Wayne State University, Detroit, MI.
Zaher MsallatyDivision of Endocrinology, Wayne State University School of Medicine, Wayne State University, Detroit, MI.
Abdullah MallishoDivision of Endocrinology, Wayne State University School of Medicine, Wayne State University, Detroit, MI.
Michael CarusoDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Divyasri DamacharlaDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Danjun MaDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Wissam Al-JanabiDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Rebecca TagettDepartment of Computer Science, College of Engineering, Wayne State University, Detroit, MI.
Majed AlharbiDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Griffin CalmeDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Aktham MestareehiDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Sorin DraghiciDepartment of Computer Science, College of Engineering, Wayne State University, Detroit, MI.
Abdul Abou-SamraDivision of Endocrinology, Wayne State University School of Medicine, Wayne State University, Detroit, MI.
Anjaneyulu KowluruDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Zhengping YiDepartment of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI.
Wayne State University · USKing Abdulaziz University · SA

Funding

Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Martin G Myers · 2013 to 2026
$24.3M
NADPH Oxidase, Mitochondrial Dysfunction and Diabetic RetinopathyR01EY022230 · NEI · WAYNE STATE UNIVERSITY · PI KOWLURU, ANJANEYULU, KOWLURU, RENU A. · 2012 to 2022
$3.4M
Human Skeletal Muscle Proteome and Phosphoproteome in Obesity and Type 2 DiabetesR01DK081750 · NIDDK · WAYNE STATE UNIVERSITY · PI YI, ZHENGPING · 2009 to 2017
$3.0M
Serine/threonine Protein Phosphatase 1 in Insulin resistance and Type 2 DiabetesR01DK107666 · NIDDK · WAYNE STATE UNIVERSITY · PI YI, ZHENGPING · 2015 to 2019
$2.6M
Training Program in Endocrine and Diabetes ResearchT32DK080657 · NIDDK · WAYNE STATE UNIVERSITY · PI GRANNEMAN, JAMES G · 2010 to 2014
$851k
Novel Regulators of Islet Beta-Cell Function in Health and DiabetesI01BX002801 · VA · JOHN D DINGELL VA MEDICAL CENTER · PI KOWLURU, ANJANEYULU · 2015 to 2018
–
Islet Beta-Cell Dysfunction Under Metabolic StressI01BX004663 · VA · JOHN D DINGELL VA MEDICAL CENTER · PI KOWLURU, ANJANEYULU · 2020 to 2023
–
BLRD VA I01 BX002801BLRD VA I01 BX004663NEI NIH HHS R01 EY022230NIDDK NIH HHS P30 DK020572NIDDK NIH HHS R01 DK081750NIDDK NIH HHS R01 DK107666NIDDK NIH HHS T32 DK080657
6 · The paper itself

Abstract

contextObesity-related insulin resistance (OIR) is one of the main contributors to type 2 diabetes and other metabolic diseases. Protein kinases are implicated in insulin signaling and glucose metabolism. Molecular mechanisms underlying OIR involving global kinase activities remain incompletely understood.

objectiveTo investigate abnormal kinase activity associated with OIR in human skeletal muscle.

designUtilization of stable isotopic labeling-based quantitative proteomics combined with affinity-based active enzyme probes to profile in vivo kinase activity in skeletal muscle from lean control (Lean) and OIR participants.

participantsA total of 16 nondiabetic adults, 8 Lean and 8 with OIR, underwent hyperinsulinemic-euglycemic clamp with muscle biopsy.

resultsWe identified the first active kinome, comprising 54 active protein kinases, in human skeletal muscle. The activities of 23 kinases were different in OIR muscle compared with Lean muscle (11 hyper- and 12 hypo-active), while their protein abundance was the same between the 2 groups. The activities of multiple kinases involved in adenosine monophosphate-activated protein kinase (AMPK) and p38 signaling were lower in OIR compared with Lean. On the contrary, multiple kinases in the c-Jun N-terminal kinase (JNK) signaling pathway exhibited higher activity in OIR vs Lean. The kinase-substrate-prediction based on experimental data further confirmed a potential downregulation of insulin signaling (eg, inhibited phosphorylation of insulin receptor substrate-1 and AKT1/2).

conclusionsThese findings provide a global view of the kinome activity in OIR and Lean muscle, pinpoint novel specific impairment in kinase activities in signaling pathways important for skeletal muscle insulin resistance, and may provide potential drug targets (ie, abnormal kinase activities) to prevent and/or reverse skeletal muscle insulin resistance in humans.

Indexed as

Insulin ResistanceProteomeAdultAMP-Activated Protein KinasesFemaleHumansMaleMuscle, SkeletalObesityp38 Mitogen-Activated Protein KinasesProtein KinasesSignal TransductionAMP-Activated Protein Kinasesp38 Mitogen-Activated Protein KinasesProtein KinasesProteomeactive kinomehuman skeletal muscleinsulin resistanceobesityprotein kinasequantitative proteomics

Identifiers

PMID31652310
PMCPMC6991621
OpenAlexW2982096298

What OpenQuestion holds

Textmetadata
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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.