PMID- 27980621
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20200929
IS  - 1753-6561 (Print)
IS  - 1753-6561 (Electronic)
IS  - 1753-6561 (Linking)
VI  - 10
IP  - Suppl 7
DP  - 2016
TI  - Analysis of gene expression to predict dynamics of future hypertension incidence 
      in type 2 diabetic patients.
PG  - 113-117
LID - 10.1186/s12919-016-0015-z [doi]
AB  - BACKGROUND: The main focus of the Genetic Analysis Workshop 19 (GAW19) is 
      identification of genes related to the occurrence of hypertension in the cohort 
      of patients with type 2 diabetes mellitus (T2DM). The aim of our study was to 
      predict dynamics of the future hypertension incidence, based on gene expression 
      profiles, systolic and diastolic blood pressure changes in time, sex, baseline 
      age, and cigarette smoking status. We analyzed data made available to GAW19 
      participants, which included gene expression profiles of peripheral blood 
      mononuclear cells (PBMCs) from the diabetic members of 20 Mexican American 
      families. METHODS: On the basis of mid blood pressure measurements at several 
      time points, the coefficient of regression (slope) was calculated for each 
      individual. We corrected the slope value in patients treated with 
      antihypertensive medications. Feature preprocessing methods were used to remove 
      highly correlated probes and linear dependencies between them. Subsequently, 
      multiple linear regression model was used to associate gene expression with the 
      regression coefficient calculated for each T2DM patient. Tenfold cross-validation 
      was used to validate the model. We used linear mixed effects model and kinship 
      coefficients to account for the family structure. All calculations were performed 
      in R. RESULTS: This analysis allowed us to identify 6 well-annotated genes: RTP4, 
      FXYD6, GDF11, IFNAR1, NOX3, and HLA-DQ2, associated with dynamics of future 
      hypertension incidence. Two of them, IFNAR1 and NOX3 were previously implicated 
      in pathogenesis of hypertension. CONCLUSIONS: There is no obvious mechanism that 
      links all detected genes with dynamics of hypertension incidence. Identification 
      of possible connection with hypertension needs further investigation.
FAU - Radkowski, Piotr
AU  - Radkowski P
AD  - Center for Medical Genomics-OMICRON, Jagiellonian University Medical College, 
      Krakow, Poland.
FAU - Wator, Gracjan
AU  - Wator G
AD  - III Chair of Surgery, Jagiellonian University Medical College, Krakow, Poland.
FAU - Skupien, Jan
AU  - Skupien J
AD  - Department of Metabolic Diseases, Jagiellonian University Medical College, 
      Krakow, Poland.
FAU - Bogdali, Anna
AU  - Bogdali A
AD  - Department of Internal and Agricultural Medicine, Jagiellonian University Medical 
      College, Krakow, Poland.
FAU - Wolkow, Pawel
AU  - Wolkow P
AD  - Center for Medical Genomics-OMICRON, Jagiellonian University Medical College, 
      Krakow, Poland.
AD  - Department of Pharmacology, Jagiellonian University Medical College, Krakow, 
      Poland.
LA  - eng
GR  - R01 GM031575/GM/NIGMS NIH HHS/United States
PT  - Journal Article
DEP - 20161018
PL  - England
TA  - BMC Proc
JT  - BMC proceedings
JID - 101316936
PMC - PMC5133526
EDAT- 2016/12/17 06:00
MHDA- 2016/12/17 06:01
PMCR- 2016/10/18
CRDT- 2016/12/17 06:00
PHST- 2016/12/17 06:00 [entrez]
PHST- 2016/12/17 06:00 [pubmed]
PHST- 2016/12/17 06:01 [medline]
PHST- 2016/10/18 00:00 [pmc-release]
AID - 15 [pii]
AID - 10.1186/s12919-016-0015-z [doi]
PST - epublish
SO  - BMC Proc. 2016 Oct 18;10(Suppl 7):113-117. doi: 10.1186/s12919-016-0015-z. 
      eCollection 2016.