Dataset Information

The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study.

ABSTRACT: 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.

SUBMITTER: de Toro-Martin J

PROVIDER: S-EPMC6796792 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study.

de Toro-Martín Juan J Guénard Frédéric F Bouchard Claude C Tremblay Angelo A Pérusse Louis L Vohl Marie-Claude MC

Frontiers in genetics 20191010

<b>Background and aims:</b> 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. <b>Methods:</b> A total of 231 single nucleotide polymorphisms (SNP) significantly associated to body mass index (BMI) from 21 genome-wide assoc ...[more]

PMID: 31649740

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Project description:Suicidal behavior (SB) has a complex etiology of genes, environment or both. One of the genetic components in SB could be copy number variations (CNVs), since CNVs are implicated in a range of neurodevelopmental disorders. However, a recently published genome-wide and case-control study failed to observe a significant role of CNVs in SB (see E-MTAB-3519). Here we complement those initial observations by conducting a brief CNV-association study, for the first time in a family-based trio-sample with severe suicide attempt (SA) outcome in offspring (n=660 trios; the \GISS\ sample, see http://www.ncbi.nlm.nih.gov/pubmed/23422793 and refs therein). For association testing, we here used the FBAT-CNV methodology (http://www.ncbi.nlm.nih.gov/pubmed/18228561), which allows for CNV association testing directly on the raw intensity values (Illumina \log R ratio\), evaluating any type of CNVs (e.g. de novo or inherited) without reliance on CNV calling algorithms and robust to control selection biases. Here we have deposited these raw logR-values for 88,450 on-chip CNV-loci of the HumanOmni1-Quad_v1 chip, arranged in a standard pedigree format used as input for FBAT-CNV analysis in SVS software (goldenhelix.com): column 1 is the family ID, column 2 is the Subject type (1 = offspring, 2 = mother, 3 = father), column 3 is the father ID (? for missing), column 4 is the mother ID (? for missing), column 5 is the sex (1 = female, 0 = male), column 6 is the affection status (1 = suicide attempt, 0 = not affected) and columns 7 and onward are the logR-values for each CNV-loci as is listed in the header row. We observed experiment-wide significant association (P ≤ 5.6 x 10-7) of two proximal CNVs at chromosome 14 (Illumina markers cnvi0108946 and cnvi0118308, with NCBI 36.3 start positions 22794779 and 22582820). However, these CNV-associations mapped to T-cell receptor regions, and therefore most likely reflect inter-individual variation in somatic rearrangements occurring in white blood cells (as our source of DNA was blood), rather than association with SA. In conclusion, our results did not suggest any major role of CNVs in SA etiology, in line with the results of the recent case-control study (see E-MTAB-3519).

Dataset Information

The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study.

Publications

The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study.

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