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Pilot Study Examining the Utility of Microarray Data to Identify Genes Associated with Weight in Transplant Recipients
Author(s) -
Cashion Ann,
Driscoll Carolyn,
Conley Yvette,
Xu Lijing,
Mandrell Belinda,
Homayouni Ramin
Publication year - 2006
Publication title -
nursing and health sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.563
H-Index - 47
eISSN - 1442-2018
pISSN - 1441-0745
DOI - 10.1111/j.1442-2018.2006.00272_3.x
Subject(s) - body mass index , gene , microarray , microarray analysis techniques , gene chip analysis , obesity , gene ontology , gene expression , medicine , biology , bioinformatics , oncology , genetics
Purpose/Methods: Obesity, a complex, polygenic disorder and a growing epidemic in transplant recipients, is a risk factor for chronic diseases. This secondary data analysis identified if microarray technologies and bioinformatics could find differences in gene expression profiles between liver transplant recipients with low Body Mass Index (BMI < 29; n = 5) vs. high (BMI > 29; n = 7). Blood was hybridized on Human U133 Plus 2 GeneChip (Affymetrix) and analyzed using GeneSpring Software. Results: Groups were similar in age and race, but not gender. Expression levels of 852 genes were different between the low and high BMI groups ( P < 0.05). The majority (562) of the changes associated with high BMI were decreases in transcript levels. Among the 852 genes associated with BMI, 263 and 14 genes were affected greater than 2‐ or 5‐fold, respectively. Following functionally classification using Gene Ontology (GO), we found that 19 genes ( P < 0.00008) belonged to defense response and 15 genes ( P < 0.00006) belonged to immune response. Conclusion: These data could point the way toward therapeutic interventions and identify those at‐risk. These results demonstrate that we can (1) extract high quality RNA from immunosuppressed patients; (2) manage large datasets and perform statistical and functional analysis.