title: Identification of novel candidate maternal serum protein markers for Down syndrome by integrated proteomic and bioinformatic analysis.
abstract: OBJECTIVE
  This study aimed to identify candidate protein biomarkers from maternal serum for Down syndrome (DS) by integrated proteomic and bioinformatics analysis.
  
  
  METHODS
  A pregnancy DS group of 18 women and a control group with the same number were prepared, and the maternal serum proteins were analyzed by isobaric tags for relative and absolute quantitation and mass spectrometry, to identify DS differentially expressed maternal serum proteins (DS-DEMSPs). Comprehensive bioinformatics analysis was then employed to analyze DS-DEMSPs both in this paper and seven related publications.
  
  
  RESULTS
  Down syndrome differentially expressed maternal serum proteins from different studies are significantly enriched with common Gene Ontology functions, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, transcription factor binding sites, and Pfam protein domains, However, the DS-DEMSPs are less functionally related to known DS-related genes. These evidences suggest that common molecular mechanisms induced by secondary effects may be present upon DS carrying. A simple scoring scheme revealed Alpha-2-macroglobulin, Apolipoprotein A1, Apolipoprotein E, Complement C1s subcomponent, Complement component 5, Complement component 8, alpha polypeptide, Complement component 8, beta polypeptide and Fibronectin as potential DS biomarkers.
  
  
  CONCLUSIONS
  The integration of proteomics and bioinformatics studies provides a novel approach to develop new prenatal screening methods for noninvasive yet accurate diagnosis of DS.
authors.affiliation: Obstetrics & Gynecology Hospital, Fudan University, Fudan, China.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Kang
authors.forename: Xinran
authors.initials: X
authors.lastname: Dong
authors.forename: Qiongjie
authors.initials: Q
authors.lastname: Zhou
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhang
authors.forename: Yan
authors.initials: Y
authors.lastname: Cheng
authors.forename: Rong
authors.initials: R
authors.lastname: Hu
authors.forename: Cuihong
authors.initials: C
authors.lastname: Su
authors.forename: Hong
authors.initials: H
authors.lastname: Jin
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Liu
authors.forename: Duan
authors.initials: D
authors.lastname: Ma
authors.forename: Weidong
authors.initials: W
authors.lastname: Tian
authors.forename: Xiaotian
authors.initials: X
authors.lastname: Li
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000032:analysis* / Q000097:blood; D001798:Blood Proteins / Q000032:analysis* / Q000302:isolation & purification; D016022:Case-Control Studies; D019295:Computational Biology / Q000379:methods*; D004314:Down Syndrome / Q000097:blood / Q000175:diagnosis*; D005260:Female; D005865:Gestational Age; D006801:Humans; D009035:Mothers; D011247:Pregnancy; D011296:Prenatal Diagnosis / Q000379:methods; D040901:Proteomics / Q000379:methods*; D018511:Systems Integration
chemical_list: D015415:Biomarkers; D001798:Blood Proteins