Identification of candidate biomarkers for the prediction of gestational diabetes mellitus in the early stages of pregnancy using iTRAQ quantitative proteomics

Zhao, Donghong; Shen, Liming; Yan, Wei; Xie, Jiaming; Chen, Shuqiang; Liang, Yi; Chen, Youjiao; H, Wu

doi:10.1002/prca.201600152

Cited by 32 publications

(61 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The iTRAQ analysis was performed according to the previous study . Plasma proteins (100 μg) were reduced, alkylated, and digested with trypsin (Promega, Madison, WI, USA) at a ratio of 1:30 at 37 °C for overnight, and then labeled with the iTRAQ reagents (AB Sciex, Foster City, CA, USA).…”

Section: Methodsmentioning

confidence: 99%

“…The dried samples were reconstituted in 100 μL double‐distilled water and injected into the Agilent HPLC (HPLC; Agilent Technologies, Santa Clara, CA, USA) with a high pH RP column (Durashell, C18, 250 mm × 4.6 mm, 5 μm; Bonna‐Agela Technologies, Inc., Wilmington, DE, USA). Peptides were eluted and combined into 10 groups and lyophilized and stored at −80 °C …”

Section: Methodsmentioning

confidence: 99%

“…An Ultra 2D Plus nanoflow HPLC (Eksigent, Inc., Dublin, CA, USA) coupled with Triple TOF 5600 system (AB Sciex) was used for analytical separation of peptides . Microfluidic traps and nanofluidic columns packed with ChromXP C18 (3 μm, 2.1 × 100 mm, Eksigent) were utilized for online trapping and desalting, while nanofluidic columns packed with ChromXP C18 (3 μm × 150 cm, Eksigent) were employed in analytical separation.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

iTRAQ‐Based Proteomic Analysis Reveals Protein Profile in Plasma from Children with Autism

Shen

Zhang

Feng

et al. 2018

Proteomics Clinical Apps

Self Cite

View full text Add to dashboard Cite

These above described proteins are found involved in different pathways that have previously been linked to the pathophysiology of autism spectrum disorders (ASDs). The results strongly support that focal adhesions, acting cytoskeleton, cell adhesion, motility and migration, synaptogenesis, and complement system are involved in the pathogenesis of autism, and highlight the important role of platelet function in the pathophysiology of autism.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

iTRAQ‐Based Proteomic Analysis Reveals Protein Profile in Plasma from Children with Autism

Shen

Zhang

Feng

et al. 2018

Proteomics Clinical Apps

Self Cite

View full text Add to dashboard Cite

show abstract

“…Samples from mothers with GDM were compared with normoglycemic pregnant controls (10 vs 10), and ELISA used for the validation of the observed differences (20 vs 20). The validated markers, APOE, F9, FGA, and IGFBP5, classified the subjects with high sensitivity and specificity …”

Section: Applications Of Isobaric Labeling For Serum and Plasma Protementioning

confidence: 99%

Analysis of the plasma proteome using iTRAQ and TMT‐based Isobaric labeling

Moulder

Bhosale

Goodlett

et al. 2017

Mass Spectrometry Reviews

126

View full text Add to dashboard Cite

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

show abstract

“…Recent advancements in gene expression profiles studies on GDM mothers reveal that cell adhesion protein fibronectin 1 interacts with inflammatory response proteins like insulin‐like growth factor 1 (IGF1R), calmodulin 1 (CALM1) and also with cytokines such as leptin (LEP) . Protein–protein interaction network based studies have identified differentially expressed inflammatory proteins as an effective diagnostic biomarker in serum of GDM‐affected mothers . Polymorphism studies on transcription factor 7 like 2 (TCF7L2) by Lin et al and Ye et al highlight its association with GDM and also enlist its eminent role in INS secretion .…”

Section: Introductionmentioning

confidence: 99%

Molecular and disease association of gestational diabetes mellitus affected mother and placental datasets reveal a strong link between insulin growth factor (IGF) genes in amino acid transport pathway: A network biology approach

Rout

2018

J of Cellular Biochemistry

View full text Add to dashboard Cite

Discerning the relationship between molecules involved in diseases based on their underlying biological mechanisms is one of the greatest challenges in therapeutic development today. Gestational diabetes mellitus (GDM) is one of the most common complications during pregnancy, which adversely affects both mothers and offspring during and after pregnancy. We have constructed two datasets of (GDM associated genes from affected mother and placenta to systematically analyze and evaluate their interactions like gene–gene, gene–protein, gene–microRNA (miRNA), gene–transcription factors, and gene‐associated diseases to enhance our current knowledge, which may lead to further advancements in disease diagnosis, prognosis, and treatment. The results identify the key genes with respect to maternal dataset as insulin receptor, insulin (INS), leptin (LEP), glucokinase, and hepatocyte nuclear factor 1 alpha, whereas from placenta include insulin‐like growth factor 1, growth hormone receptor, and breast cancer anti‐estrogen resistance protein 1, which are found to be highly enriched in pancreas, ovary, adipocyte, heart, and placental tissues. The key transcription factors include Sp1 transcription factor, pancreatic and duodenal homeobox 1, and hepatocyte nuclear factor 4 alpha, whereas miRNA includes has‐miR‐5699‐5p and has‐miR‐3158‐3p. The study also reveals that GDM has associations with diseases like type I and II diabetes mellitus, obesity, and preeclampsia. More significantly, we could trace out a significant connection between the key molecules like LEP and placental growth hormone from mother and placental dataset, which plays a critical role in INS secretion, INS signaling, and β‐cell dysfunction pathways.

show abstract

Identification of candidate biomarkers for the prediction of gestational diabetes mellitus in the early stages of pregnancy using iTRAQ quantitative proteomics

Abstract: The results highlight the roles of complement system, inflammatory and immune response, and blood coagulation in the pathogenesis of GDM. The panel of four candidate proteins could distinguish women subsequently developed with GDM from controls with high sensitivity and specificity.

Cited by 32 publications

References 48 publications

iTRAQ‐Based Proteomic Analysis Reveals Protein Profile in Plasma from Children with Autism

iTRAQ‐Based Proteomic Analysis Reveals Protein Profile in Plasma from Children with Autism

Analysis of the plasma proteome using iTRAQ and TMT‐based Isobaric labeling

Molecular and disease association of gestational diabetes mellitus affected mother and placental datasets reveal a strong link between insulin growth factor (IGF) genes in amino acid transport pathway: A network biology approach

Contact Info

Product

Resources

About