PMID- 32753925
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20231111
IS  - 1178-7007 (Print)
IS  - 1178-7007 (Electronic)
IS  - 1178-7007 (Linking)
VI  - 13
DP  - 2020
TI  - Integrated Datasets of Proteomic and Metabolomic Biomarkers to Predict Its 
      Impacts on Comorbidities of Type 2 Diabetes Mellitus.
PG  - 2409-2431
LID - 10.2147/DMSO.S244432 [doi]
AB  - OBJECTIVE: The objective of the current study is to accomplish a relative 
      exploration of the biological roles of differentially dysregulated genes (DRGs) 
      in type 2 diabetes mellitus (T2DM). The study aimed to determine the impact of 
      these DRGs on the biological pathways and networks that are related to the 
      associated disorders and complications in T2DM and to predict its role as 
      prospective biomarkers. METHODS: Datasets obtained from metabolomic and proteomic 
      profiling were used for investigation of the differential expression of the 
      genes. A subset of DRGs was integrated into IPA software to explore its 
      biological pathways, related diseases, and their regulation in T2DM. Upon entry 
      into the IPA, only 94 of the DRGs were recognizable, mapped, and matched within 
      the database. RESULTS: The study identified networks that explore the 
      dysregulation of several functions; cell components such as degranulation of 
      cells; molecular transport process and metabolism of cellular proteins; and 
      inflammatory responses. Top disorders associated with DRGs in T2DM are related to 
      organ injuries such as renal damage, connective tissue disorders, and acute 
      inflammatory disorders. Upstream regulator analysis predicted the role of several 
      transcription factors of interest, such as STAT3 and HIF alpha, as well as many 
      kinases such as JAK kinases, which affects the gene expression of the dataset in 
      T2DM. Interleukin 6 (IL6) is the top regulator of the DRGs, followed by leptin 
      (LEP). Monitoring the dysregulation of the coupled expression of the following 
      biomarkers (TNF, IL6, LEP, AGT, APOE, F2, SPP1, and INS) highlights that they 
      could be used as potential prognostic biomarkers. CONCLUSION: The integration of 
      data obtained by advanced metabolomic and proteomic technologies has made it 
      probable to advantage in understanding the role of these biomarkers in the 
      identification of significant biological processes, pathways, and regulators that 
      are associated with T2DM and its comorbidities.
CI  - (c) 2020 Cheema et al.
FAU - Cheema, Amrita K
AU  - Cheema AK
AD  - Department of Oncology, Lombardi Comprehensive Cancer Center at Georgetown 
      University Medical Center, Washington, DC, USA.
FAU - Kaur, Prabhjit
AU  - Kaur P
AD  - Department of Oncology, Lombardi Comprehensive Cancer Center at Georgetown 
      University Medical Center, Washington, DC, USA.
FAU - Fadel, Amina
AU  - Fadel A
AD  - Biomedical Sciences Department, College of Health Sciences and Biomedical 
      Research Center, QU Health, Qatar University, Doha, Qatar.
FAU - Younes, Noura
AU  - Younes N
AD  - Clinical Chemistry Lab, Hamad Medical Corporation, Doha, Qatar.
FAU - Zirie, Mahmoud
AU  - Zirie M
AD  - Endocrine Department, Hammad Medical Corporation, Doha, Qatar.
FAU - Rizk, Nasser M
AU  - Rizk NM
AUID- ORCID: 0000-0002-6288-3609
AD  - Biomedical Sciences Department, College of Health Sciences and Biomedical 
      Research Center, QU Health, Qatar University, Doha, Qatar.
AD  - Physiology Department, Mansoura Faculty of Medicine, Mansoura, Egypt.
LA  - eng
PT  - Journal Article
DEP - 20200707
PL  - New Zealand
TA  - Diabetes Metab Syndr Obes
JT  - Diabetes, metabolic syndrome and obesity : targets and therapy
JID - 101515585
PMC - PMC7354282
OTO - NOTNLM
OT  - bioinformatics
OT  - biomarkers
OT  - disorders
OT  - pathway analysis
OT  - regulators
OT  - type 2 diabetes mellitus
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a conflict of 
      interest.
EDAT- 2020/08/06 06:00
MHDA- 2020/08/06 06:01
PMCR- 2020/07/07
CRDT- 2020/08/06 06:00
PHST- 2020/01/01 00:00 [received]
PHST- 2020/05/29 00:00 [accepted]
PHST- 2020/08/06 06:00 [entrez]
PHST- 2020/08/06 06:00 [pubmed]
PHST- 2020/08/06 06:01 [medline]
PHST- 2020/07/07 00:00 [pmc-release]
AID - 244432 [pii]
AID - 10.2147/DMSO.S244432 [doi]
PST - epublish
SO  - Diabetes Metab Syndr Obes. 2020 Jul 7;13:2409-2431. doi: 10.2147/DMSO.S244432. 
      eCollection 2020.