A genome-wide association meta-analysis identifies new childhood obesity loci

Jp, Bradfield; Hr, Taal; Timpson, Nicholas J.; Scherag, André; Lecœur, Cécile; Warrington, Nicole M.; Hyppönen, Elina; Holst, Claus; Valcárcel, Beatriz; Thiering, Elisabeth; Rm, Salem; Schumacher, Fredrick; Dl, Cousminer; Pm, Sleiman; Zhao, Jin; Ri, Berkowitz; Ks, Vimaleswaran; Jarick, Ivonne; Ce, Pennell; Dm, Evans; B, St Pourcain; Berry, DJ; Do, Mook-Kanamori; Hofman, Albert; Rivadeneira, Fernando; Ag, Uitterlinden; Duijn, van; Rj, van der Valk; Jc, de Jongste; Ds, Postma; Boomsma, D.I.; Wj, Gauderman; Mt, Hassanein; Cm, Lindgren; Mägi, Reedik; Ca, Boreham; Ce, Neville; Moreno, LA; Elliott, Paul; Pouta, A; Al, Hartikainen; M, Li; Raitakari, O; Lehtimäki, Terho; Eriksson, Johan G.; Palotie, A.; Dallongeville, Jean; Das, Sandip; Deloukas, Panagiotis; McMahon, George; Ring, SM; Kemp, John P.; Jl, Buxton; Ai, Blakemore; Guxens, Mònica; Jn, Hirschhorn; Mw, Gillman; Kreiner‐Møller, Eskil; Bisgaard, Hans; Gilliland, Frank D.; Heinrich, Joachim; Wheeler, Eleanor; Barroso, Inês; O’Rahilly, Stephen; Meirhaeghe, Aline; Ti, Sørensen; Power, Christine; Lj, Palmer; Widen, E.; Farooqi, I. Sadaf; McCarthy, Mark I.; Froguel, Philippe; Meyre, David; Järvelin, Marjo‐Riitta; Vw, Jaddoe; Gd, Smith; Hákonarson, Hákon; Grant, SF

doi:10.14341/2071-8713-5058

Cited by 63 publications

(96 citation statements)

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“…(4). Furthermore, all have been identified as being associated with obesity in children (6,15,17). Interestingly, although SNP rs1561288 showed partial dependence on the previously identified index SNP in the region, we found suggestive evidence for a secondary signal in the POMC region from the conditional analyses.…”

Section: Discussionmentioning

confidence: 45%

“…For these 13 SNPs, we observed 10 SNPs with consistent directions of effect with BMI and five SNPs that displayed Bonferroni corrected (assuming 13 tests) significant associations (P , 0.0038), including the recently identified SNP near HOX5 (rs9299) (17). The SNP near OLFM4 (rs9568856) (17) also displayed a nominally significant effect in our young adult sample.…”

Section: Resultsmentioning

confidence: 54%

“…In the past 5 years, genome-wide association studies (GWASs) have identified over 30 common genetic loci associated with body mass index (BMI, kg/m 2 ) mainly in European adult samples, with an average age often greater than 50 (4 -10). Whereas several loci identified in adults have also been found to be associated with BMI in childhood (6,(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) and two loci were recently identified in childhood obesity (17), little is known about these obesity susceptibility loci across high-risk periods for weight gain, such as adolescence and young adulthood. The influence of these loci in adolescence and young adulthood remains largely speculative from previously established association studies that illustrate the association of these loci on BMI during middle-aged adulthood and/or childhood.…”

Section: Introductionmentioning

confidence: 99%

“…The purpose of the current study was to conduct a two-stage GWAS for genetic loci influencing BMI during late adolescence and early adulthood (aged [16][17][18][19][20][21][22][23][24][25]. Furthermore, we sought to compare estimates of effect sizes on BMI for the 32 BMI loci previously identified in European middle-aged adults (4) to effect sizes observed in adolescent and young adults of European descent.…”

Section: Introductionmentioning

confidence: 99%

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Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course

Graff¹,

Ngwa

Workalemahu

et al. 2013

Human Molecular Genetics

120

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Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 3 10 28 ) near FTO (P 5 3.72 3 10 223 ), TMEM18 (P 5 3.24 3 10 217 ), MC4R (P 5 4.41 3 10 217 ), TNNI3K (P 5 4.32 3 10 211 ), SEC16B (P 5 6.24 3 10 29 ), GNPDA2 (P 5 1.11 3 10 28 ) and POMC (P 5 4.94 3 10 28 ) as well as a potential secondary signal at the POMC locus (rs2118404, P 5 2.4 3 10 25 after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18 -90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages.

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Section: Discussionmentioning

confidence: 45%

Section: Resultsmentioning

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course

Graff¹,

Ngwa

Workalemahu

et al. 2013

Human Molecular Genetics

120

View full text Add to dashboard Cite

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“…This deletion is located between the LOC647946 and KC6 genes. (LOC647946 is an uncharacterized noncoding RNA and is a predicted top target of the motif CDC5L.p2 of the cell division cycle 5-like gene (Suzuki et al, 2009), and KC6 was found to be associated with childhood obesity (Bradfield et al, 2012) and multiple blood and metabolism-related traits.) On the same cytoband (B3970 kb distance), 18q12.3, another deletion, showed suggestive evidence of a protective effect (OR ¼ 0.49 (0.33-0.73) and P(Z) ¼ 0.0005 in the combined samples; Table 2).…”

Section: Burden Analyses In Odmentioning

confidence: 99%

Genome-Wide Association Study of Copy Number Variations (CNVs) with Opioid Dependence

Zhao

Kranzler

et al. 2014

Neuropsychopharmacol

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Single-nucleotide polymorphisms that have been associated with opioid dependence (OD) altogether account for only a small proportion of the known heritability. Most of the genetic risk factors are unknown. Some of the 'missing heritability' might be explained by copy number variations (CNVs) in the human genome. We used Illumina HumanOmni1 arrays to genotype 5152 African-American and European-American OD cases and screened controls and implemented combined CNV calling methods. After quality control measures were applied, a genome-wide association study (GWAS) of CNVs with OD was performed. For common CNVs, two deletions and one duplication were significantly associated with OD genome-wide (eg, P ¼ 2 Â 10 À 8 and OR (95% CI) ¼ 0.64 (0.54-0.74) for a chromosome 18q12.3 deletion). Several rare or unique CNVs showed suggestive or marginal significance with large effect sizes. This study is the first GWAS of OD using CNVs. Some identified CNVs harbor genes newly identified here to be of biological importance in addiction, whereas others affect genes previously known to contribute to substance dependence risk. Our findings augment our specific knowledge of the importance of genomic variation in addictive disorders, and provide an addiction CNV pool for further research. These findings require replication.

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Using Phenotypic Heterogeneity to Increase the Power of Genome‐Wide Association Studies: Application to Age at Onset of Ischaemic Stroke Subphenotypes

Traylor

Bevan

Rothwell

et al. 2013

Genetic Epidemiology

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Genome-wide association studies (GWAS) have been successful in identifying common variants related to complex disorders. However, some disorders have proved resistant to this strategy with few associations confirmed, despite evidence from twin and family studies of a genetic component. Sophisticated strategies that account for phenotypic heterogeneity may be required to uncover these genetic contributions. Age at onset is an example of a potential source of this heterogeneity in ischaemic stroke. We explore the contribution of age at onset in the Wellcome Trust Case-Control Consortium 2 ischaemic stroke study. We first examine four established stroke loci in younger onset cases. We extend this to all single-nucleotide polymorphisms (SNPs) genome-wide, testing for stronger association signals in younger subsets of cases. Finally, we estimate the pseudoheritability accounted for by common SNPs present on genome-wide genotyping arrays for cases stratified by age at onset. We find evidence for stronger associations in younger onset cases for the four established stroke loci. Genome-wide, in cardioembolic and small vessel stroke subphenotypes, a significant number of SNPs show stronger association P-values when the oldest cases are removed. Finally, we show that the pseudoheritability estimated by common SNPs in cardioembolic stroke increased from 16.5% for older onset cases to 28.5% for younger onset cases. Our results indicate that age at onset is a valuable measure for case ascertainment and in analysis of GWAS in ischaemic stroke: focussing on younger cases who may have a stronger genetic predisposition increases power to detect associations.

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A genome-wide association meta-analysis identifies new childhood obesity loci

Cited by 63 publications

References 0 publications

Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course

Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course

Genome-Wide Association Study of Copy Number Variations (CNVs) with Opioid Dependence

Using Phenotypic Heterogeneity to Increase the Power of Genome‐Wide Association Studies: Application to Age at Onset of Ischaemic Stroke Subphenotypes

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