Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits

Vogelezang, Suzanne; Bradfield, Jonathan P.; Ahluwalia, Tarunveer S.; Curtin, John A.; Lakka, Timo A.; Grarup, Niels; Scholz, Markus; Most, Peter J. van der; Monnereau, Claire; Stergiakouli, Evie; Heiskala, Anni; Horikoshi, Momoko; Fedko, Iryna O.; Vilor‐Tejedor, Natàlia; Cousminer, Diana L.; Standl, Marie; Wang, Carol A.; Viikari, Jorma; Geller, Frank; Íñiguez, Carmen; Pitkänen, Niina; Chesi, Alessandra; Bacelis, Jonas; Yengo, Loïc; Torrent, Maties; Ντάλλα, Ιωάννα; Helgeland, Øyvind; Selzam, Saskia; Vonk, Judith M.; Zafarmand, Mohammed H.; Heude, Barbara; Farooqi, I. Sadaf; Alyass, Akram; Beaumont, Robin N; Have, Christian Theil; Rzehak, Peter; Bilbao, José Ramón; Schnurr, Theresia M.; Barroso, Inês; Bønnelykke, Klaus; Beilin, Lawrence J.; Carstensen, Lisbeth; Munier, Charles; Chawes, Bo; Clément, Karine; Closa‐Monasterolo, Ricardo; Čustović, Adnan; Eriksson, Johan G.; Escribano, Joaquín; Groen-Blokhuis, Maria M.; Grote, Veit; Gruszfeld, Dariusz; Hákonarson, Hákon; Hansen, Torben; Hattersley, Andrew T.; Hollensted, Mette; Hottenga, Jouke‐Jan; Hyppönen, Elina; Johansson, Stefan; Joro, Raimo; Kähönen, Mika; Karhunen, Ville; Kieß, Wieland; Knight, Bridget; Koletzko, Berthold; Kühnapfel, Andreas; Landgraf, Kathrin; Langhendries, Jean‐Paul; Lehtimäki, Terho; Leinonen, Jaakko T.; Li, Aihuali; Lindi, Virpi; Lowry, Estelle; Bustamante, Mariona; Medina‐Gomez, Carolina; Melbye, Mads; Michaelsen, Kim F.; Morgen, Camilla Schmidt; Mori, Trevor A.; Nielsen, Tenna Ruest Haarmark; Niinikoski, Harri; Oldehinkel, Albertine J.; Pahkala, Katja; Panoutsopoulou, Kalliope; Pedersen, Oluf; Pennell, Craig E.; Power, Christine; Reijneveld, Sijmen A.; Rivadeneira, Fernando; Simpson, Angela; Sly, Peter D.; Stokholm, Jakob; Teo, Kook K; Thiering, Elisabeth; Timpson, Nicholas J.; Uitterlinden, André G.; Beijsterveldt, Catharina E. M. van; Schaik, Barbera D. C. van; Vaudel, Marc; Verduci, Elvira; Vinding, Rebecca K.; Vogel, Mandy; Zeggini, Eleftheria; Sebért, Sylvain; Lind, Mads Vendelbo; Brown, Christopher D.; Santa‐Marina, Loreto; Reischl, Eva; Frithioff-Bøjsøe, Christine; Meyre, David; Wheeler, Eleanor; Ong, Ken K.; Nøhr, Ellen Aagaard; Vrijkotte, Tanja G. M.; Koppelman, Gerard H.; Plomin, Robert; Njølstad, Pål R.; Dedoussis, George; Froguel, Philippe; Sørensen, Thorkild I A; Jacobsson, Bo; Freathy, Rachel M.; Zemel, Babette S.; Raitakari, Olli T.; Vrijheid, Martine; Feenstra, Bjarke; Lyytikäinen, Leo-Pekka; Snieder, Harold; Kirsten, Holger; Holt, Patrick G.; Heinrich, Joachim; Widén, Elisabeth; Sunyer, Jordi; Boomsma, Dorret I.; Järvelin, Marjo‐Riitta; Körner, Antje; Smith, George Davey; Holm, Jens-Christian; Atalay, Mustafa; Murray, Clare; Bisgaard, Hans; McCarthy, Mark; Jaddoe, Vincent W.V.; Grant, Struan F A; Felix, Janine F.

doi:10.1371/journal.pgen.1008718

Cited by 112 publications

(112 citation statements)

References 76 publications

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“…As reviewed by others, 27,28 genome-wide association studies (GWAS) have been effective in the identification of more than 1,000 genetic loci associated with adiposity-related outcomes, such as adult BMI, 29 body fat percentage, 30 and obesity as a binary trait, 31 and child BMI-standard deviation score 32 and obesity. 33 The vast majority of these loci were identified for adult BMI (N = 941 loci, explaining 6% of adult BMI variance 29 ).…”

Section: Genetic Determinants Of Physical Activity Sedentary Behaviour and Adiposity-related Traitsmentioning

confidence: 99%

Evidence for shared genetics between physical activity, sedentary behaviour and adiposity‐related traits

et al. 2020

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Summary Observational, cross‐sectional and longitudinal studies showed that physical activity and sedentary behaviour are associated with adiposity‐related traits, apparently in a bidirectional manner. Physical activity is also suggested to suppress the genetic risk of adiposity. Since phenotypic associations with genetic variants are not subject to reverse causation or confounding, they may be used as tools to shed light on cause and effect in this complex interdependency. We review the evidence for shared genetics of physical activity and adiposity‐related traits and for gene‐by‐physical activity interactions on adiposity‐related traits in human studies. We outline limitations, challenges and opportunities in studying and understanding of these relationships. In summary, physical activity and sedentary behaviour are genetically correlated with body mass index and fat percentage but may not be correlated with lean body mass. Mendelian randomisation analyses show that physical activity and sedentary behaviour have bidirectional relationships with adiposity. Several studies suggest that physical activity suppresses genetic risk of adiposity. No studies have yet tested whether adiposity enhances genetic predisposition to sedentariness. The complexity of the comprehensive causal model makes the assessment of the single or combined components challenging. Substantial progress in this field may need long‐term intervention studies.

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Section: Genetic Determinants Of Physical Activity Sedentary Behaviour and Adiposity-related Traitsmentioning

confidence: 99%

Evidence for shared genetics between physical activity, sedentary behaviour and adiposity‐related traits

et al. 2020

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“…This study was limited, in that there were far fewer childhood BMI SNPs (N = 14 and 5) than adult BMI SNPs (N = 323 and 115), decreasing the power of the MR estimation (Au Yeung et al, 2021). Our twosample MR using 25 childhood BMI SNPs (Vogelezang et al, 2020) supports a causal relationship with asthma. However, based on the previous study (Au Yeung et al, 2021) and our result, childhood BMI has a weak causal impact on asthma but not on any specific subtype.…”

Section: Discussionmentioning

confidence: 71%

“…To determine the effect of childhood BMI on asthma in our setting, we extracted 25 childhood BMI SNPs with associated statistical values from a previous study ( Vogelezang et al, 2020 ). These BMI SNPs were subject to the removal of SNPs with strand ambiguity (e.g., A/T and C/G), SNPs in the MHC region (chromosome 6:25-34M), SNPs with no proxy ( r 2 > 0.8) in UKB, and SNPs that were associated with asthma ( P < 2.17E–03, 0.05/23) leaving 21 SNPs.…”

Section: Resultsmentioning

confidence: 99%

“…Ultimately, 159 BMI SNPs were used for the MR (BMI → asthma). The results confirmed BMI as a causal factor for asthma [IVW OR = 1.16 (1.07-1.26), P = 2.89E-04; weighted median OR = 1.18 (1.07-1.32), P = 1.71E-03; GSMR OR = 1.18 (1.11-1.26), P = 4.37E-08; Figure 5C and Supplementary To determine the effect of childhood BMI on asthma in our setting, we extracted 25 childhood BMI SNPs with associated statistical values from a previous study (Vogelezang et al, 2020). These BMI SNPs were subject to the removal of SNPs with strand ambiguity (e.g., A/T and C/G), SNPs in the MHC region (chromosome 6:25-34M), SNPs with no proxy (r 2 > 0.8) in UKB, and SNPs that were associated with asthma (P < 2.17E-03, 0.05/23) leaving 21 SNPs.…”

Section: Effect Of Bmi On Asthma and Its Subtypes In Two-sample Mendelian Randomizationmentioning

confidence: 99%

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Association Between Environmental Factors and Asthma Using Mendelian Randomization: Increased Effect of Body Mass Index on Adult-Onset Moderate-to-Severe Asthma Subtypes

Jung

Kim

et al. 2021

Front. Genet.

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Although asthma is one of the most common chronic diseases throughout all age groups, its etiology remains unknown, primarily due to its heterogeneous characteristics. We examined the causal effects of various environmental factors on asthma using Mendelian randomization and determined whether the susceptibility to asthma due to the causal effect of a risk factor differs between asthma subtypes, based on age of onset, severity of asthma, and sex. We performed Mendelian randomization analyses (inverse variance weighted, weighted median, and generalized summary-data-based Mendelian randomization) using UK Biobank data to estimate the causal effects of 69 environmental factors on asthma. Additional sensitivity analyses (MR-Egger regression, Cochran’s Q test, clumping, and reverse Mendelian randomization) were performed to ensure minimal or no pleiotropy. For confirmation, two-sample setting analyses were replicated using BMI SNPs that had been reported by a meta-genome-wide association study in Japanese and European (GIANT) populations and a genome-wide association study in control individuals from the UK Biobank. We found that BMI causally affects the development of asthma and that the adult-onset moderate-to-severe asthma subtype is the most susceptible to causal inference by BMI. Further, it is likely that the female subtype is more susceptible to BMI than males among adult asthma cases. Our findings provide evidence that obesity is a considerable risk factor in asthma patients, particularly in adult-onset moderate-to-severe asthma cases, and that weight loss is beneficial for reducing the burden of asthma.

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“…Notably, a multi-ethnic GWAS in adults has found an association between rs1650505 (near EBF1 ) and pericardial adipose tissue volume 56 . Previous studies found substantial overlaps between childhood and adult obesity GWAS loci 62 . While there is relatively weak LD between the lead SNP showing pleiotropic effect in our study (rs6887211) and rs1650505 (r 2 = 0.06 in CEU), we acknowledge that the novelty of the locus in childhood BMI may be in part due to the small study power of the source GWAS used for childhood BMI.…”

Section: Discussionmentioning

confidence: 95%

Pleiotropic genetic influence on birth weight and childhood obesity

Chatterjee

Ouidir

Tekola‐Ayele

2021

Sci Rep

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Childhood obesity is a global public health problem. Understanding the molecular mechanisms that underlie early origins of childhood obesity can facilitate interventions. Consistent phenotypic and genetic correlations have been found between childhood obesity traits and birth weight (a proxy for in-utero growth), suggesting shared genetic influences (pleiotropy). We aimed to (1) investigate whether there is significant shared genetic influence between birth weight and childhood obesity traits, and (2) to identify genetic loci with shared effects. Using a statistical approach that integrates summary statistics and functional annotations for paired traits, we found strong evidence of pleiotropy (P < 3.53 × 10–127) and enrichment of functional annotations (P < 1.62 × 10–39) between birth weight and childhood body mass index (BMI)/obesity. The pleiotropic loci were enriched for regulatory features in skeletal muscle, adipose and brain tissues and in cell lines derived from blood lymphocytes. At 5% false discovery rate, 6 loci were associated with birth weight and childhood BMI and 13 loci were associated with birth weight and childhood obesity. Out of these 19 loci, one locus (EBF1) was novel to childhood obesity and one locus (LMBR1L) was novel to both birth weight and childhood BMI/obesity. These findings give evidence of substantial shared genetic effects in the regulation of both fetal growth and childhood obesity.

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Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits

Cited by 112 publications

References 76 publications

Evidence for shared genetics between physical activity, sedentary behaviour and adiposity‐related traits

Evidence for shared genetics between physical activity, sedentary behaviour and adiposity‐related traits

Association Between Environmental Factors and Asthma Using Mendelian Randomization: Increased Effect of Body Mass Index on Adult-Onset Moderate-to-Severe Asthma Subtypes

Pleiotropic genetic influence on birth weight and childhood obesity

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