DataSheet_1_The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study.pdf
Background and aims: Obesity is a major health problem worldwide. Given the heterogeneous obesity phenotype, an optimal obesity stratification would improve clinical management. Since obesity has a strong genetic component, we aimed to develop a polygenic risk score (PRS) to stratify obesity according to the genetic background of the individuals.
Methods: A total of 231 single nucleotide polymorphisms (SNP) significantly associated to body mass index (BMI) from 21 genome-wide association studies were genotyped or imputed in 881 subjects from the Quebec Family Study (QFS). The population was randomly split into discovery (80%; n = 704) and validation (20%; n = 177) samples with similar obesity (BMI ≥ 30) prevalence (27.8% and 28.2%, respectively). Family-based associations with obesity were tested for every SNP in the discovery sample and a weighed and continuous PRS231 was constructed. Generalized linear mixed effects models were used to test the association of PRS231 with obesity in the QFS discovery sample and validated in the QFS replication sample. Furthermore, the Fatty Acid Sensor (FAS) Study (n = 141; 27.7% obesity prevalence) was used as an independent sample to replicate the results.
Results: The linear trend test demonstrated a significant association of PRS231 with obesity in the QFS discovery sample (ORtrend = 1.19 [95% CI, 1.14-1.24]; P = 2.0x10-16). We also found that the obesity prevalence was significantly greater in the higher PRS231 quintiles compared to the lowest quintile. Significant and consistent results were obtained in the QFS validation sample for both the linear trend test (ORtrend = 1.16 [95% CI, 1.07-1.26]; P = 6.7x10-4), and obesity prevalence across quintiles. These results were partially replicated in the FAS sample (ORtrend = 1.12 [95% CI, 1.02-1.24]; P = 2.2x10-2). PRS231 explained 7.5%, 3.2%, and 1.2% of BMI variance in QFS discovery, QFS validation, and FAS samples, respectively.
Conclusions: These results revealed that genetic background in the form of a 231 BMI-associated PRS has a significant impact on obesity, but a limited potential to accurately stratify it. Further studies are encouraged on larger populations.
- Gene and Molecular Therapy
- Genetically Modified Animals
- Developmental Genetics (incl. Sex Determination)
- Epigenetics (incl. Genome Methylation and Epigenomics)
- Gene Expression (incl. Microarray and other genome-wide approaches)
- Livestock Cloning
- Genome Structure and Regulation
- Genetic Engineering