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Meta-Analysis
. 2020 Oct 12;16(10):e1008718.
doi: 10.1371/journal.pgen.1008718. eCollection 2020 Oct.

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

Suzanne Vogelezang  1   2   3 , Jonathan P Bradfield  4   5 , Tarunveer S Ahluwalia  6   7   8   9 , John A Curtin  10 , Timo A Lakka  11   12   13 , Niels Grarup  8 , Markus Scholz  14   15 , Peter J van der Most  16 , Claire Monnereau  1   2   3 , Evie Stergiakouli  17   18   19 , Anni Heiskala  20 , Momoko Horikoshi  21   22   23 , Iryna O Fedko  24 , Natalia Vilor-Tejedor  25   26   27   28 , Diana L Cousminer  29   30 , Marie Standl  31 , Carol A Wang  32 , Jorma Viikari  33   34 , Frank Geller  35 , Carmen Íñiguez  28   36   37 , Niina Pitkänen  38   39 , Alessandra Chesi  29 , Jonas Bacelis  40   41 , Loic Yengo  42   43 , Maties Torrent  44   45 , Ioanna Ntalla  46 , Øyvind Helgeland  47   48 , Saskia Selzam  49 , Judith M Vonk  50 , Mohammed H Zafarmand  51   52   53 , Barbara Heude  54 , Ismaa Sadaf Farooqi  55 , Akram Alyass  56 , Robin N Beaumont  57 , Christian T Have  8 , Peter Rzehak  58 , Jose Ramon Bilbao  59   60   61 , Theresia M Schnurr  8 , Inês Barroso  62   63 , Klaus Bønnelykke  6 , Lawrence J Beilin  64 , Lisbeth Carstensen  35 , Marie-Aline Charles  54 , Bo Chawes  6 , Karine Clément  65 , Ricardo Closa-Monasterolo  66 , Adnan Custovic  67 , Johan G Eriksson  68   69 , Joaquin Escribano  66 , Maria Groen-Blokhuis  24 , Veit Grote  58 , Dariusz Gruszfeld  70 , Hakon Hakonarson  5   71 , Torben Hansen  8 , Andrew T Hattersley  57   72 , Mette Hollensted  8   73 , Jouke-Jan Hottenga  24 , Elina Hyppönen  74   75   76 , Stefan Johansson  47   77 , Raimo Joro  11 , Mika Kähönen  78   79 , Ville Karhunen  80   81 , Wieland Kiess  82 , Bridget A Knight  72 , Berthold Koletzko  58 , Andreas Kühnapfel  14   15 , Kathrin Landgraf  82   83 , Jean-Paul Langhendries  84 , Terho Lehtimäki  85   86 , Jaakko T Leinonen  87 , Aihuali Li  56 , Virpi Lindi  88 , Estelle Lowry  20   89 , Mariona Bustamante  25   28   90 , Carolina Medina-Gomez  1   3   91 , Mads Melbye  35   92 , Kim F Michaelsen  93 , Camilla S Morgen  94   95 , Trevor A Mori  64 , Tenna R H Nielsen  96   97 , Harri Niinikoski  98   99 , Albertine J Oldehinkel  100 , Katja Pahkala  38   39   101 , Kalliope Panoutsopoulou  102 , Oluf Pedersen  8 , Craig E Pennell  32 , Christine Power  103 , Sijmen A Reijneveld  104 , Fernando Rivadeneira  3   91 , Angela Simpson  10 , Peter D Sly  105   106 , Jakob Stokholm  6 , Kook K Teo  107 , Elisabeth Thiering  31   58 , Nicholas J Timpson  17   18 , André G Uitterlinden  3   91   108 , Catharina E M van Beijsterveldt  24 , Barbera D C van Schaik  109 , Marc Vaudel  47   77 , Elvira Verduci  110 , Rebecca K Vinding  6 , Mandy Vogel  82   83 , Eleftheria Zeggini  102   111   112 , Sylvain Sebert  20   89   113 , Mads V Lind  93 , Christopher D Brown  114 , Loreto Santa-Marina  115   116   117 , Eva Reischl  118 , Christine Frithioff-Bøjsøe  8   97   119 , David Meyre  56 , Eleanor Wheeler  62   63 , Ken Ong  120 , Ellen A Nohr  121 , Tanja G M Vrijkotte  51 , Gerard H Koppelman  122 , Robert Plomin  49 , Pål R Njølstad  47   123   124 , George D Dedoussis  125 , Philippe Froguel  42   113 , Thorkild I A Sørensen  8   17   94 , Bo Jacobsson  40   41   48 , Rachel M Freathy  57   126 , Babette S Zemel  71   127 , Olli Raitakari  38   39   128 , Martine Vrijheid  25   28   90 , Bjarke Feenstra  35 , Leo-Pekka Lyytikäinen  85   86   129 , Harold Snieder  16 , Holger Kirsten  14   15 , Patrick G Holt  130 , Joachim Heinrich  31   131   132 , Elisabeth Widén  87 , Jordi Sunyer  25   28   90   133 , Dorret I Boomsma  24   134 , Marjo-Riitta Järvelin  20   80   81 , Antje Körner  82   83 , George Davey Smith  17   18 , Jens-Christian Holm  8   97   119 , Mustafa Atalay  11 , Clare Murray  10 , Hans Bisgaard  6 , Mark I McCarthy  21   22   135 ; Early Growth Genetics Consortium; Vincent W V Jaddoe  1   2 , Struan F A Grant  5   29   30   70   136 , Janine F Felix  1   2
Affiliations
Meta-Analysis

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

Suzanne Vogelezang et al. PLoS Genet. .

Abstract

The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.

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Conflict of interest statement

I have read the journal's policy and the authors of this manuscript have the following competing interests: MMcC: The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. He serves on advisory panels for Pfizer, NovoNordisk, Zoe Global; has received honoraria from Merck, Pfizer, NovoNordisk and Eli Lilly; has stock options in Zoe Global; has received research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier & Takeda. MS receives funding from Pfizer Inc. for a project not related to this research. IB and spouse own stock in GlaxoSmithKline and Incyte Corp. ZE and CDB currently serve on the editorial board of PLOS Genetics. AC reports personal fees from Novartis, personal fees from Thermo Fisher Scientific, personal fees from Philips, personal fees from Sanofi, personal fees from Stallergenes Greer, outside the submitted work. KC in involved in consultancy for Danone Research, LNC-therapeutic and Confo-therapeutic but no personal funding is received and this activity not linked to the present research.

Figures

Fig 1
Fig 1. Manhattan plot of results of the discovery meta-analysis of 26 single study GWAS.
On the x-axis the chromosomes are shown. On the y-axis the–log 10 of the P-value is shown. Novel SNPs are shown in green. Independent SNPs are shown in blue. Known SNPs are shown in black. The genome wide significance cutoff of 5 × 10−8 is represented by the grey dotted line.
Fig 2
Fig 2. Locus zoom plots of the 2 novel SNPs Regional association plot of the 2 novel SNPs in the 26 childhood BMI discovery studies.
SNPs are plotted with their P-values (as–log10; left y-axis) as a function of genomic position (x-axis). Estimated recombination rates (right y-axis) taken from 1000 Genomes, March 2012 release are plotted to reflect the local LD-structure around the top associated SNP (indicated with purple color) and the correlated proxies (indicated in colors). A. rs1094647 B. rs184566112.
Fig 3
Fig 3. Genome-wide genetic correlations between childhood BMI and adult traits and diseases.
On the x-axis the traits and diseases are shown. On the y-axis the genetic correlations (Rg) and corresponding standard errors, indicated by error bars, between childhood BMI and each trait were shown, estimated by LD score regression. The genetic correlation estimates (Rg) are colored according to their intensity and direction. Red indicates positive correlation, blue indicates negative correlation. References can be found in S11 Table.
Fig 4
Fig 4. Associations of the weighted risk score with childhood BMI.
Along the x-axis, categories of the risk score are shown together with the mean SDS BMI on the y-axis on the right and a line representing the regression of the mean SDS childhood BMI values for each category of the risk score. Along the y-axis on the left a histogram represents the number of individuals in each risk-score category. P-value is based on the continuous risk score. Analysis was performed in the TRAILS cohort (N = 1,169).
See this image and copyright information in PMC

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