Parental and child genetic contributions to obesity traits in early life based on 83 loci validated in adults: the FAMILY study.

BACKGROUND: The genetic influence on child obesity has not been fully elucidated. OBJECTIVE: This study investigated the parental and child contributions of 83 adult body mass index (BMI)-associated single-nucleotide polymorphisms (SNPs) to obesity-related traits in children from birth to 5 years old. METHODS: A total of 1402 individuals were genotyped for 83 SNPs. An unweighted genetic risk score (GRS) was generated by the sum of BMI-increasing alleles. Repeated weight and length/height were measured at birth, 1, 2, 3 and 5 years of age, and age-specific and sex-specific weight and BMI Z-scores were computed. RESULTS: The GRS was significantly associated with birthweight Z-score (P = 0.03). It was also associated with weight/BMI Z-score gain between birth and 5 years old (P = 0.02 and 6.77 × 10-3 , respectively). In longitudinal analyses, the GRS was associated with weight and BMI Z-score from birth to 5 years (P = 5.91 × 10-3 and 5.08 × 10-3 , respectively). The maternal effects of rs3736485 in DMXL2 on weight and BMI variation from birth to 5 years were significantly greater compared with the paternal effects by Z test (P = 1.53 × 10-6 and 3.75 × 10-5 , respectively). CONCLUSIONS: SNPs contributing to adult BMI exert their effect at birth and in early childhood. Parent-of-origin effects may occur in a limited subset of obesity predisposing SNPs.

Expressed fusion gene landscape and its impact in multiple myeloma.

Multiple myeloma is a plasma cell malignancy characterized by recurrent IgH translocations and well described genomic heterogeneity. Although transcriptome profiles in multiple myeloma has been described, landscape of expressed fusion genes and their clinical impact remains unknown. To provide a comprehensive and detailed fusion gene cartography and suggest new mechanisms of tumorigenesis in multiple myeloma, we performed RNA sequencing in a cohort of 255 newly diagnosed and homogeneously treated multiple myeloma patients with long follow-up. Here, we report that patients have on average 5.5 expressed fusion genes. Kappa and lambda light chains and IgH genes are main partners in a third of all fusion genes. We also identify recurrent fusion genes that significantly impact both progression-free and overall survival and may act as drivers of the disease. Lastly, we find a correlation between the number of fusions, the age of patients and the clinical outcome, strongly suggesting that genomic instability drives prognosis of the disease.

Empirical evaluation of the Q-Genie tool: a protocol for assessment of effectiveness.

INTRODUCTION: Meta-analyses of genetic association studies are affected by biases and quality shortcomings of the individual studies. We previously developed and validated a risk of bias tool for use in systematic reviews of genetic association studies. The present study describes a larger empirical evaluation of the Q-Genie tool. METHODS AND ANALYSIS: MEDLINE, Embase, Global Health and the Human Genome Epidemiology Network will be searched for published meta-analyses of genetic association studies. Twelve reviewers in pairs will apply the Q-Genie tool to all studies in included meta-analyses. The Q-Genie will then be evaluated on its ability to (i) increase precision after exclusion of low quality studies, (ii) decrease heterogeneity after exclusion of low quality studies and (iii) good agreement with experts on quality rating by Q-Genie. A qualitative assessment of the tool will also be conducted using structured questionnaires. DISCUSSION: This systematic review will quantitatively and qualitatively assess the Q-Genie's ability to identify poor quality genetic association studies. This information will inform the selection of studies for inclusion in meta-analyses, conduct sensitivity analyses and perform metaregression. Results of this study will strengthen our confidence in estimates of the effect of a gene on an outcome from meta-analyses, ultimately bringing us closer to deliver on the promise of personalised medicine. ETHICS AND DISSEMINATION: An updated Q-Genie tool will be made available from the Population Genomics Program website and the results will be submitted for a peer-reviewed publication.

Contribution of 24 obesity-associated genetic variants to insulin resistance, pancreatic beta-cell function and type 2 diabetes risk in the French population.

CONTEXT: Obesity is the major determinant of type 2 diabetes (T2D), presumably through its effect on insulin resistance. Genome-wide association studies reported many single-nucleotide polymorphisms (SNPs) that increase obesity risk and body mass index (BMI), but their impact on T2D-related traits and risk is unclear. OBJECTIVE: We aimed at analyzing the effect of 24 obesity risk alleles, separately and in combination, on variation of both insulin resistance and ß-cell dysfunction, and on T2D risk. DESIGN: We genotyped 24 obesity-associated SNPs and calculated an obesity genotype score (sum of the obesity risk alleles per individual). We analyzed the contribution of each SNP and this score to the variation of four metabolic indices: homeostasis model assessment of insulin resistance (HOMA-IR), homeostasis model assessment of the pancreatic ß-cell function (HOMA-B), insulin sensitivity index (ISI) and insulinogenic index (II) (in up to 8050 nondiabetic French individuals) and to T2D risk (in 2077 T2D cases and 3085 controls). RESULTS: We found a highly significant effect of the obesity genotype score on increased insulin resistance adjusted for age and gender (ß=0.02; P-value=7.16 × 10(-9) for HOMA-IR). Individually, we identified nominal or significant association between increased insulin resistance and risk alleles in FAIM2, FTO, GNPDA2, MC4R, NPC1, PTER and SH2B1. Most signals, including the obesity genotype score and FTO SNP, were also associated with increased ß-cell function (ß=0.01; P-value=1.05 × 10(-6) and ß=0.04; P-value=3.45 × 10(-4), respectively). In our T2D case-control study, only the obesity genotype score and the well-known FTO locus significantly contributed to T2D risk (OR=1.03; P-value=9.99 × 10(-3) and OR=1.15; P-value=9.46 × 10(-4), respectively). Adjustment for BMI abolished all significant associations. CONCLUSIONS: Genetic predisposition to obesity contributes to increased insulin resistance and to its compensation through increased ß-cell function, and weakly increases the T2D risk. These associations are mediated by BMI.