A computational framework for predicting obesity risk based on optimizing and integrating genetic risk score and gene expression profiles.

Authors:
Dr. Paule V Joseph, PhD, RN, MS, FNP-BC, CTN-B
Dr. Paule V Joseph, PhD, RN, MS, FNP-BC, CTN-B
National Institute of Nursing Research
Tenure-Track Investigator (Clinical)
N/A
Bethesda , Maryland | United States
Yupeng Wang
Yupeng Wang
University of Georgia
United States
Nicolaas H Fourie
Nicolaas H Fourie
University of Cape Town
South Africa

PLoS One 2018 24;13(5):e0197843. Epub 2018 May 24.

Division of Intramural Research, National Institutes of Health, Bethesda, Maryland, United States of America.

Recent large-scale genome-wide association studies have identified tens of genetic loci robustly associated with Body Mass Index (BMI). Gene expression profiles were also found to be associated with BMI. However, accurate prediction of obesity risk utilizing genetic data remains challenging. In a cohort of 75 individuals, we integrated 27 BMI-associated SNPs and obesity-associated gene expression profiles. Genetic risk score was computed by adding BMI-increasing alleles. The genetic risk score was significantly correlated with BMI when an optimization algorithm was used that excluded some SNPs. Linear regression and support vector machine models were built to predict obesity risk using gene expression profiles and the genetic risk score. An adjusted R2 of 0.556 and accuracy of 76% was achieved for the linear regression and support vector machine models, respectively. In this paper, we report a new mathematical method to predict obesity genetic risk. We constructed obesity prediction models based on genetic information for a small cohort. Our computational framework serves as an example for using genetic information to predict obesity risk for specific cohorts.

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0197843PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993110PMC
December 2018
57 Reads
3.234 Impact Factor

Article Mentions


Provided by Crossref Event Data
twitter
Twitter: OValverde_
June 11, 2018, 11:49 am EST
twitter
Twitter: DisGeNET
June 11, 2018, 4:39 am EST
twitter
Twitter: Jytaylor007
May 26, 2018, 8:25 am EST
twitter
Twitter: Paulevj
May 26, 2018, 7:45 am EST

Publication Analysis

Top Keywords

genetic risk
20
expression profiles
16
gene expression
16
risk score
16
obesity risk
16
predict obesity
12
risk
9
genetic
9
machine models
8
vector machine
8
regression support
8
linear regression
8
support vector
8
profiles genetic
8
computational framework
8
obesity
6
obesity-associated gene
4
score computed
4
snps obesity-associated
4
obesity genetic
4

References

(Supplied by CrossRef)
The obesity epidemic: challenges, health initiatives, and implications for gastroenterologists
RT Hurt et al.
Gastroenterology & hepatology 2010
Genetic determinants of common obesity and their value in prediction
RJ Loos et al.
Best practice & research Clinical endocrinology & metabolism 2012
Genetic risk estimation in the Coriell Personalized Medicine Collaborative
CB Stack et al.
Genetics in medicine: official journal of the American College of Medical Genetics 2011
Development and evaluation of a genetic risk score for obesity
DW Belsky et al.
Biodemography and social biology 2013

Similar Publications