PMID- 32831068
OWN - NLM
STAT- MEDLINE
DCOM- 20210510
LR  - 20210510
IS  - 1755-8794 (Electronic)
IS  - 1755-8794 (Linking)
VI  - 13
IP  - 1
DP  - 2020 Aug 24
TI  - Unraveling the molecular heterogeneity in type 2 diabetes: a potential subtype 
      discovery followed by metabolic modeling.
PG  - 119
LID - 10.1186/s12920-020-00767-0 [doi]
LID - 119
AB  - BACKGROUND: Type 2 diabetes mellitus (T2DM) is a complex multifactorial disease 
      with a high prevalence worldwide. Insulin resistance and impaired insulin 
      secretion are the two major abnormalities in the pathogenesis of T2DM. Skeletal 
      muscle is responsible for over 75% of the glucose uptake and plays a critical 
      role in T2DM. Here, we sought to provide a better understanding of the 
      abnormalities in this tissue. METHODS: The muscle gene expression patterns were 
      explored in healthy and newly diagnosed T2DM individuals using supervised and 
      unsupervised classification approaches. Moreover, the potential of subtyping T2DM 
      patients was evaluated based on the gene expression patterns. RESULTS: A 
      machine-learning technique was applied to identify a set of genes whose 
      expression patterns could discriminate diabetic subjects from healthy ones. A 
      gene set comprising of 26 genes was found that was able to distinguish healthy 
      from diabetic individuals with 94% accuracy. In addition, three distinct clusters 
      of diabetic patients with different dysregulated genes and metabolic pathways 
      were identified. CONCLUSIONS: This study indicates that T2DM is triggered by 
      different cellular/molecular mechanisms, and it can be categorized into different 
      subtypes. Subtyping of T2DM patients in combination with their real clinical 
      profiles will provide a better understanding of the abnormalities in each group 
      and more effective therapeutic approaches in the future.
FAU - Khoshnejat, Maryam
AU  - Khoshnejat M
AD  - Laboratory of Complex Biological Systems and Bioinformatics (CBB), Department of 
      Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of 
      Tehran, Tehran, Iran.
AD  - The UNESCO Chair on Interdisciplinary Research in Diabetes, Institute of 
      Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran.
FAU - Kavousi, Kaveh
AU  - Kavousi K
AUID- ORCID: 0000-0002-1906-3912
AD  - Laboratory of Complex Biological Systems and Bioinformatics (CBB), Department of 
      Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of 
      Tehran, Tehran, Iran. kkavousi@ut.ac.ir.
AD  - The UNESCO Chair on Interdisciplinary Research in Diabetes, Institute of 
      Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran. 
      kkavousi@ut.ac.ir.
FAU - Banaei-Moghaddam, Ali Mohammad
AU  - Banaei-Moghaddam AM
AD  - The UNESCO Chair on Interdisciplinary Research in Diabetes, Institute of 
      Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran.
AD  - Laboratory of Genomics and Epigenomics (LGE), Department of Biochemistry, 
      Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, 
      Iran.
FAU - Moosavi-Movahedi, Ali Akbar
AU  - Moosavi-Movahedi AA
AD  - The UNESCO Chair on Interdisciplinary Research in Diabetes, Institute of 
      Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran.
AD  - Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20200824
PL  - England
TA  - BMC Med Genomics
JT  - BMC medical genomics
JID - 101319628
RN  - 0 (Biomarkers)
RN  - 0 (Insulin)
SB  - IM
MH  - Biomarkers/*analysis
MH  - Case-Control Studies
MH  - Diabetes Mellitus, Type 2/classification/genetics/metabolism/*pathology
MH  - *Gene Expression Regulation
MH  - Humans
MH  - Insulin/*metabolism
MH  - *Metabolic Networks and Pathways
MH  - Signal Transduction
MH  - *Transcriptome
PMC - PMC7444195
OTO - NOTNLM
OT  - Classification
OT  - Clustering
OT  - Flux variability analysis
OT  - Insulin resistance
OT  - Metabolic modeling
OT  - Muscle
OT  - Subtype
OT  - Type 2 diabetes
COIS- The authors declare that they have no competing interest.
EDAT- 2020/08/25 06:00
MHDA- 2021/05/11 06:00
PMCR- 2020/08/24
CRDT- 2020/08/25 06:00
PHST- 2019/12/18 00:00 [received]
PHST- 2020/08/12 00:00 [accepted]
PHST- 2020/08/25 06:00 [entrez]
PHST- 2020/08/25 06:00 [pubmed]
PHST- 2021/05/11 06:00 [medline]
PHST- 2020/08/24 00:00 [pmc-release]
AID - 10.1186/s12920-020-00767-0 [pii]
AID - 767 [pii]
AID - 10.1186/s12920-020-00767-0 [doi]
PST - epublish
SO  - BMC Med Genomics. 2020 Aug 24;13(1):119. doi: 10.1186/s12920-020-00767-0.