Genetic studies of birth weight give biological insights ... · Genetic studies of birth weight...

GeneticstudiesofbirthweightgivebiologicalinsightsintolinkswithadultdiseaseMomokoHorikoshi1,2,*,RobinNBeaumont3,*,FelixRDay4,*,NicoleMWarrington5,6,*,MarjoleinNKooijman7,8,9,*,JuanFernandez-Tajes1,*,NatalieRvanZuydam1,2,KyleJGaulton1,10,NielsGrarup11,JonathanPBradfield12,DavidPStrachan13,RuifangLi-Gao14,TarunveerSAhluwalia11,15,16,EskilKreiner-Møller15,RicoRueedi17,18,Leo-PekkaLyytikäinen19,20,DianaLCousminer21,22,YingWu23,ElisabethThiering24,25,CarolAWang6,ChristianTHave11,Jouke-JanHottenga26,NataliaVilor-Tejedor27,28,29,PeterKJoshi30,BjarkeFeenstra31,EileenTaiHuiBoh32,IoannaNtalla33,34,NiinaPitkänen35,AnubhaMahajan1,ElisabethMvanLeeuwen8,RaimoJoro36,VasilikiLagou1,37,38,MichaelNodzenski39,LouiseADiver40,KrinaTZondervan1,41,MarionaBustamante27,28,29,42,PedroMMarques-Vidal43,JosepMMercader44,AmandaJBennett2,NiluferRahmioglu1,DaleRNyholt45,RonaldChingWanMa46,47,ClaudiaHaTingTam46,WingHungTam48,CHARGEConsortiumHematologyWorkingGroup,SanthiKGanesh49,FrankJAvanRooij8,SamuelEJones3,Po-RuLoh50,51,KatherineSRuth3,MarcusATuke3,JessicaTyrrell3,52,AndrewRWood3,HaniehYaghootkar3,DeniseMScholtens39,LaviniaPaternoster53,54,IngaProkopenko1,55,PeterKovacs56,MustafaAtalay36,SaraMWillems8,KalliopePanoutsopoulou57,XuWang32,LisbethCarstensen31,FrankGeller31,KatharinaESchraut30,MarioMurcia29,58,CatharinaEMvanBeijsterveldt26,GonnekeWillemsen26,EmilVRAppel11,CiliusEFonvig11,59,CaecilieTrier11,59,CarlaMTTiesler24,25,MarieStandl24,ZoltánKutalik18,60,SílviaBonas-Guarch44,DavidMHougaard61,62,FrimanSánchez44,63,DavidTorrents44,64,JohannesWaage15,MadsVHollegaard61,62,ǂ,HugolineGdeHaan14,FritsRRosendaal14,CarolinaMedina-Gomez7,8,65,SusanMRing53,54,GibranHemani53,54,GeorgeMcMahon54,NeilRRobertson1,2,ChristopherJGroves2,ClaudiaLangenberg4,Jian'anLuan4,RobertAScott4,JingHuaZhao4,FrankDMentch12,ScottMMacKenzie40,RebeccaMReynolds66,WilliamLLoweJr67,AnkeTönjes68,MichaelStumvoll56,68,VirpiLindi36,TimoALakka36,69,70,CorneliaMvanDuijn8,WielandKiess71,AntjeKörner56,71,ThorkildIASørensen53,54,72,73,HarriNiinikoski74,75,KatjaPahkala35,76,OlliTRaitakari35,77,EleftheriaZeggini57,GeorgeVDedoussis34,Yik-YingTeo32,78,79,Seang-MeiSaw32,80,MadsMelbye31,81,82,HarryCampbell30,JamesFWilson30,83,MartineVrijheid27,28,29,EcoJCNdeGeus26,84,DorretIBoomsma26,HajaNKadarmideen85,Jens-ChristianHolm11,59,TorbenHansen11,SylvainSebert86,87,AndrewTHattersley3,LawrenceJBeilin88,JohnPNewnham6,CraigEPennell6,JoachimHeinrich24,89,LindaSAdair90,JudithBBorja91,92,KarenLMohlke23,JohanGEriksson93,94,95,ElisabethEWidén21,MikaKähönen96,97,JormaSViikari98,99,TerhoLehtimäki19,20,PeterVollenweider43,KlausBønnelykke15,HansBisgaard15,DennisOMook-Kanamori14,100,101,AlbertHofman7,8,FernandoRivadeneira7,8,65,AndréGUitterlinden7,8,65,CharlottaPisinger102,OlufPedersen11,ChristinePower103,ElinaHyppönen103,104,105,NicholasJWareham4,HakonHakonarson12,22,106,EleanorDavies40,BrianRWalker66,VincentWVJaddoe7,8,9,Marjo-RiittaJarvelin86,87,107,108,StruanFAGrant12,22,106,109,AllanAVaag81,110,DebbieALawlor53,54,TimothyMFrayling3,GeorgeDaveySmith53,54,AndrewPMorris1,111,112,§,KenKOng4,113,§,JanineFFelix7,8,9,§,NicholasJTimpson53,54,§,JohnRBPerry4,§,DavidMEvans5,53,54,§,MarkIMcCarthy1,2,114,§andRachelMFreathy3,53,§fortheEarlyGrowthGenetics(EGG)Consortium1. WellcomeTrustCentreforHumanGenetics,UniversityofOxford,Oxford,UK.2. OxfordCentreforDiabetes,EndocrinologyandMetabolism,UniversityofOxford,Oxford,UK.3. InstituteofBiomedicalandClinicalScience,UniversityofExeterMedicalSchool,RoyalDevon

andExeterHospital,Exeter,UK.4. MRCEpidemiologyUnit,UniversityofCambridgeSchoolofClinicalMedicine,Cambridge,UK.5. TheUniversityofQueenslandDiamantinaInstitute,TranslationalResearchInstitute,Brisbane,

Australia.6. SchoolofWomen’sandInfants’Health,TheUniversityofWesternAustralia,Perth,Australia.

7. TheGenerationRStudyGroup,ErasmusMC,UniversityMedicalCenterRotterdam,theNetherlands.

8. DepartmentofEpidemiology,ErasmusMC,UniversityMedicalCenterRotterdam,theNetherlands.

9. DepartmentofPediatrics,ErasmusMC,UniversityMedicalCenterRotterdam,theNetherlands.

10. DepartmentofPediatrics,UniversityofCaliforniaSanDiego,LaJolla,California,USA.11. TheNovoNordiskFoundationCenterforBasicMetabolicResearch,SectionofMetabolic

Genetics,FacultyofHealthandMedicalSciences,UniversityofCopenhagen,Copenhagen,Denmark.

12. CenterforAppliedGenomics,TheChildren’sHospitalofPhiladelphia,Philadelphia,Pennsylvania,USA.

13. PopulationHealthResearchInstitute,StGeorge'sUniversityofLondon,London,CranmerTerrace,UK.

14. DepartmentofClinicalEpidemiology,LeidenUniversityMedicalCenter,Leiden,theNetherlands.

15. CopenhagenProspectiveStudiesonAsthmainChildhood,FacultyofHealthandMedicalSciences,UniversityofCopenhagenandGentofteHospital,UniversityofCopenhagen,Copenhagen,Denmark.

16. StenoDiabetesCenter,Gentofte,Denmark.17. DepartmentofMedicalGenetics,UniversityofLausanne,Lausanne,Switzerland.18. SwissInstituteofBioinformatics,Lausanne,Switzerland.19. DepartmentofClinicalChemistry,FimlabLaboratories,Tampere,Finland.20. DepartmentofClinicalChemistry,UniversityofTampereSchoolofMedicine,Tampere,

Finland.21. InstituteforMolecularMedicine,Finland(FIMM),UniversityofHelsinki,Helsinki,Finland.22. DivisionofHumanGenetics,TheChildren’sHospitalofPhiladelphia,Philadelphia,

Pennsylvania,USA.23. DepartmentofGenetics,UniversityofNorthCarolina,ChapelHill,NC,USA.24. InstituteofEpidemiologyI,HelmholtzZentrumMünchen-GermanResearchCenterfor

EnvironmentalHealth,Neuherberg,Germany.25. DivisionofMetabolicandNutritionalMedicine,Dr.vonHaunerChildren'sHospital,University

ofMunichMedicalCenter,Munich,Germany.26. NetherlandsTwinRegister,DepartmentofBiologicalPsychology,VUUniversity,Amsterdam,

theNetherlands.27. ISGlobal,CentreforResearchinEnvironmentalEpidemiology(CREAL),Barcelona,Spain.28. UniversitatPompeuFabra(UPF),Barcelona,Spain.29. CIBERdeEpidemiologíaySaludPública(CIBERESP),Spain.30. UsherInstituteforPopulationHealthSciencesandInformatics,UniversityofEdinburgh,

Edinburgh,Scotland,UK.31. DepartmentofEpidemiologyResearch,StatensSerumInstitute,Copenhagen,Denmark.32. SawSweeHockSchoolofPublicHealth,NationalUniversityofSingapore,NationalUniversity

HealthSystem,Singapore,Singapore.33. WilliamHarveyResearchInstitute,BartsandtheLondonSchoolofMedicineandDentistry,

QueenMaryUniversityofLondon,London,UK.34. DepartmentofNutritionandDietetics,SchoolofHealthScienceandEducation,Harokopio

University,Athens,Greece.35. ResearchCentreofAppliedandPreventiveCardiovascularMedicine,UniversityofTurku,

Turku,Finland.36. InstituteofBiomedicine,Physiology,UniversityofEasternFinland,Kuopio,Finland.37. KUL–UniversityofLeuven,DepartmentofNeurosciences,Leuven,Belgium.

38. TranslationalImmunologyLaboratory,VIB,Leuven,Belgium.39. DepartmentofPreventiveMedicine,DivisionofBiostatistics,FeinbergSchoolofMedicine,

NorthwesternUniversity,Chicago,USA.40. InstituteofCardiovascular&MedicalSciences,CollegeofMedical,VeterinaryandLife

Sciences,UniversityofGlasgow,Glasgow,UK.41. EndometriosisCaReCentre,NuffieldDepartmentofObstetrics&Gynaecology,Universityof

Oxford,Oxford,UK.42. CenterforGenomicRegulation(CRG),Barcelona,Spain.43. DepartmentofInternalMedicine,InternalMedicine,LausanneUniversityHospital(CHUV),

Lausanne,Switzerland.44. JointBSC-CRG-IRBResearchPrograminComputationalBiology,BarcelonaSupercomputing

Center,Barcelona,Spain.45. InstituteofHealthandBiomedicalInnovation,QueenslandUniversityofTechnology,

Queensland,Australia.46. DepartmentofMedicineandTherapeutics,TheChineseUniversityofHongKong,HongKong,

HongKong,China.47. LiKaShingInstituteofHealthSciences,TheChineseUniversityofHongKong,HongKong,

HongKong,China.48. DepartmentofObstetricsandGynaecology,TheChineseUniversityofHongKong,HongKong,

HongKong,China.49. CardiovascularMedicine,DepartmentofInternalMedicine,UniversityofMichigan,AnnArbor,

Michigan,USA.50. DepartmentofEpidemiology,HarvardT.H.ChanSchoolofPublicHealth,Boston,

Massachusetts,USA.51. PrograminMedicalandPopulationGenetics,BroadInstituteofHarvardandMIT,Cambridge,

Massachusetts,USA.52. EuropeanCentreforEnvironmentandHumanHealth,UniversityofExeter,Truro,UK.53. MedicalResearchCouncilIntegrativeEpidemiologyUnitattheUniversityofBristol,Bristol,

UK.54. SchoolofSocialandCommunityMedicine,UniversityofBristol,Bristol,UK.55. DepartmentofGenomicsofCommonDisease,SchoolofPublicHealth,ImperialCollege

London,London,UK.56. IFBAdiposityDiseases,UniversityofLeipzig,Leipzig,Germany.57. WellcomeTrustSangerInstitute,Hinxton,Cambridgeshire,UK.58. FISABIO–UniversitatJaumeI–UniversitatdeValència,JointResearchUnitofEpidemiologyand

EnvironmentalHealth,Valencia,Spain.59. TheChildren'sObesityClinic,DepartmentofPediatrics,CopenhagenUniversityHospital

Holbæk,Holbæk,Denmark.60. InstituteofSocialandPreventiveMedicine,LausanneUniversityHospital(CHUV),Lausanne,

Switzerland.61. DanishCenterforNeonatalScreening,StatensSerumInstitute,Copenhagen,Denmark.62. DepartmentforCongenitalDisorders,StatensSerumInstitute,Copenhagen,Denmark.63. ComputerSciencesDepartment,BarcelonaSupercomputingCenter,Barcelona,Spain.64. InstitucióCatalanadeRecercaiEstudisAvançats(ICREA),Barcelona,Spain.65. DepartmentofInternalMedicine,ErasmusMC,UniversityMedicalCenterRotterdam,the

Netherlands.66. BHFCentreforCardiovascularScience,UniversityofEdinburgh,Queen'sMedicalResearch

Institute,Edinburgh,Scotland,UK.67. DepartmentofMedicine,DivisionofEndocrinology,MetabolismandMolecularMedicine,

FeinbergSchoolofMedicine,NorthwesternUniversity,Chicago,USA.68. MedicalDepartment,UniversityofLeipzig,Leipzig,Germany.

69. DepartmentofClinicalPhysiologyandNuclearMedicine,KuopioUniversityHospital,Kuopio,Finland.

70. KuopioResearchInstituteofExerciseMedicine,Kuopio,Finland.71. PediatricResearchCenter,DepartmentofWomen´s&ChildHealth,UniversityofLeipzig,

Leipzig,Germany.72. NovoNordiskFoundationCenterforBasicMetabolicResearchandDepartmentofPublic

Health,FacultyofHealthandMedicalSciences,UniversityofCopenhagen,Copenhagen,Denmark.

73. InstituteofPreventiveMedicine,BispebjergandFrederiksbergHospital,TheCapitalRegion,Copenhagen,Denmark.

74. DepartmentofPediatrics,TurkuUniversityHospital,Turku,Finland.75. DepartmentofPhysiology,UniversityofTurku,Turku,Finland.76. PaavoNurmiCentre,SportsandExerciseMedicineUnit,DepartmentofPhysicalActivityand

Health,Turku,Finland.77. DepartmentofClinicalPhysiologyandNuclearMedicine,TurkuUniversityHospital,Turku,

Finland.78. DepartmentofStatisticsandAppliedProbability,NationalUniversityofSingapore,Singapore,

Singapore.79. LifeSciencesInstitute,NationalUniversityofSingapore,Singapore,Singapore.80. SingaporeEyeResearchInstitute,Singapore,Singapore.81. DepartmentofClinicalMedicine,CopenhagenUniversity,Copenhagen,Denmark.82. DepartmentofMedicine,StanfordSchoolofMedicine,Stanford,California,USA.83. MRCHumanGeneticsUnit,InstituteofGeneticsandMolecularMedicine,Universityof

Edinburgh,Edinburgh,Scotland,UK.84. EMGOInstituteforHealthandCareResearch,VUUniversityandVUUniversityMedical

Center,Amsterdam,theNetherlands.85. DepartmentofLargeAnimalSciences,FacultyofHealthandMedicalSciences,Universityof

Copenhagen,Copenhagen,Denmark.86. CenterforLifeCourseHealthResearch,FacultyofMedicine,UniversityofOulu,Oulu,Finland.87. BiocenterOulu,UniversityofOulu,Finland.88. SchoolofMedicineandPharmacology,RoyalPerthHospitalUnit,TheUniversityofWestern

Australia,Perth,Australia.89. InstituteandOutpatientClinicforOccupational,SocialandEnvironmentalMedicine,InnerCity

Clinic,UniversityHospitalMunich,LudwigMaximilianUniversityofMunich,Munich,Germany.90. DepartmentofNutrition,UniversityofNorthCarolina,ChapelHill,NC,USA.91. USC-OfficeofPopulationStudiesFoundation,Inc.,UniversityofSanCarlos,CebuCity,

Philippines.92. DepartmentofNutritionandDietetics,UniversityofSanCarlos,CebuCity,Philippines.93. NationalInstituteforHealthandWelfare,Helsinki,Finland.94. DepartmentofGeneralPracticeandPrimaryHealthCare,UniversityofHelsinkiandHelsinki

UniversityHospital,Helsinki,Finland.95. FolkhälsanResearchCenter,Helsinki,Finland.96. DepartmentofClinicalPhysiology,TampereUniversityHopital,Tampere,Finland.97. DepartmentofClinicalPhysiology,UniversityofTampereSchoolofMedicine,Tampere,

Finland.98. DivisionofMedicine,TurkuUniversityHospital,Turku,Finland.99. DepartmentofMedicine,UniversityofTurku,Turku,Finland.100. DepartmentofPublicHealthandPrimaryCare,LeidenUniversityMedicalCenter,Leiden,the

Netherlands.101. EpidemiologySection,BESCDepartment,KingFaisalSpecialistHospitalandResearchCentre,

Riyadh,SaudiArabia.

102. ResearchCenterforPreventionandHealthCapitalRegion,CenterforSundhed,Rigshospitalet–Glostrup,CopenhagenUniversity,Glostrup,Denmark.

103. Population,PolicyandPractice,UCLInstituteofChildHealth,UniversityCollegeLondon,London,UK.

104. CentreforPopulationHealthResearch,SchoolofHealthSciencesandSansomInstitute,UniversityofSouthAustralia,Adelaide,Australia.

105. SouthAustralianHealthandMedicalResearchInstitute,Adelaide,Australia.106. DepartmentofPediatrics,PerelmanSchoolofMedicine,UniversityofPennsylvania,

Philadelphia,Pennsylvania,USA.107. DepartmentofEpidemiologyandBiostatistics,MRC–PHECentreforEnvironment&Health,

SchoolofPublicHealth,ImperialCollegeLondon,London,UK.108. UnitofPrimaryCare,OuluUniversityHospital,Oulu,Finland.109. DivisionofEndocrinology,TheChildren’sHospitalofPhiladelphia,Philadelphia,Pennsylvania,

USA.110. DepartmentofEndocrinology,Rigshospitalet,Copenhagen,Denmark.111. DepartmentofBiostatistics,UniversityofLiverpool,Liverpool,UK.112. EstonianGenomeCenter,UniversityofTartu,Tartu,Estonia.113. DepartmentofPaediatrics,UniversityofCambridge,Cambridge,UK.114. OxfordNationalInstituteforHealthResearch(NIHR)BiomedicalResearchCentre,Churchill

Hospital,Oxford,UK.*Theseauthorscontributedequallytothiswork.§Theseauthorsjointlydirectedthiswork.ǂDeceased.

Birthweight(BW)isinfluencedbybothfoetalandmaternalfactorsandinobservationalstudiesis1reproduciblyassociatedwithfutureriskofadultmetabolicdiseasesincludingtype2diabetes2(T2D)andcardiovasculardisease1.Theselifecourseassociationshaveoftenbeenattributedtothe3impactofanadverseearlylifeenvironment.Weperformedamulti-ancestrygenome-wide4associationstudy(GWAS)meta-analysisofBWin153,781individuals,identifying59lociwhere5foetalgenotypewasassociatedwithBW(P<5x10-8).Overall,~15%ofvarianceinBWcouldbe6capturedbyassaysoffoetalgeneticvariation.Usinggeneticassociationalone,wefoundastrong7inversegeneticcorrelationbetweenBWandT2D(rg=-0.27,P=1.1x10-6)andestimatedthat52%of8thephenotypiccovariancebetweenthesetwotraitswasdrivenbygeneticvariation.Wealso9detectedinversegeneticcorrelationsbetweenBWandsystolicbloodpressure(rg=-0.22,P=5.5x10-1013)andcoronaryarterydisease(rg=-0.30,P=6.5x10-9).Pathwayanalysesindicatedthattheprotein11productsofgeneswithinBW-associatedregionswereenrichedfordiverseprocessesincluding12insulinsignalling,glucosehomeostasis,glycogenbiosynthesisandchromatinremodelling.There13wasalsoenrichmentofassociationswithBWinknownimprintedregions(P=1.9x10-4).Wehave14shownthatlifecourseassociationsbetweenearlygrowthphenotypesandadultcardiometabolic15diseaseareinparttheresultofsharedgeneticeffectsandwehighlightsomeofthepathways16throughwhichthesecausalgeneticeffectsaremediated.1718WecombinedGWASdataforBWin153,781individualsrepresentingseveralancestriesfrom3719studiesacrossthreecomponents(ExtendedData1,SupplementaryTable1):(i)75,891individuals20ofEuropeanancestryfrom30studies;(ii)67,786individualsofEuropeanancestryfromtheUK21Biobank;and(iii)10,104individualsofdiverseancestries(AfricanAmerican,Chinese,Filipino,22Surinamese,TurkishandMoroccan)from6studies.Withineachstudy,BWwasz-scoretransformed23separatelyinmalesandfemalesafterexcludingnon-singletonsandprematurebirthsandadjusting24forgestationalagewhereavailable.Genotypeswereimputedusingreferencepanelsfromthe100025Genomes(1000G)ProjectConsortium2or1000GandUK10KProjectConsortium3(Supplementary26Table2).WeperformedqualitycontrolassessmentstoconfirmthatthedistributionofBWwas27consistentacrossstudies,irrespectiveofthedatacollectionprotocolandconfirmedthatself-28reportedBWinUKBiobankshowedgeneticandphenotypicassociationsconsistentwiththoseseen29formeasuredBWinotherstudies4(Methods).3031Weidentified59lociassociatedwithBWatgenome-widesignificance(P<5x10-8),includingallseven32previously-reportedsignals5,ineithertheEuropeanancestryortrans-ancestrymeta-analyses(Figure331a,ExtendedData2,SupplementaryData;Methods).AtleadSNPs,weobservednoheterogeneity34inalleliceffectsbetweenthethreestudycomponents(Cochran’sQstatisticP>0.00085)35(SupplementaryTable3).Fifty-twooftheselociwerenovelinthattheleadSNPmapped>2Mb36awayfromandwasstatisticallyindependent(EURr2<0.05)ofpreviously-reportedsignals537(SupplementaryTable4).ApproximateconditioningintheEuropeanancestrymeta-analysis38identifiedthreeloci(nearZBTB7B,HMGA1andPTCH1)harbouringmultipledistinctassociation39signalsattaininggenome-widesignificance(Methods;SupplementaryTable5,ExtendedData3).4041Theleadvariantsformostsignalsmappedtonon-codingsequence,andatonlytwoloci,ADRB142(rs7076938;r2=0.99withADRB1G389R)andNRIP1(rs2229742,R448G)didtheassociationdata43pointtolikelycausalnon-synonymouscodingvariants(SupplementaryTable6;Methods).Lead44SNPsforallbuttwoofthe62signals(thosemappingnearYKT6-GCKandSUZ12P1-CRLF3)were45common(minorallelefrequency(MAF)≥5%)withindividuallymodesteffectsonBW(z=0.020-0.05346perallele,equivalentto10to26g).Thiswasdespitemuchimprovedcoverageoflow-frequency47variantsinthisstudy(comparedtoprevious)reflectingimputationfromlarger,andmorecomplete,48referencepanels(ExtendedData4).Indeed,55ofthe60commonvariantassociationsignalswere49taggedbyvariants(EURr2>0.6)intheHapMap2referencepanel(SupplementaryTables4and5),50indicatingthatmostofthenoveldiscoveryinthepresentstudywasdrivenbyincreasedsample51

size5.Fine-mappinganalysisyielded14regionswithfewerthantenvariantsina“credibleset”of52variantsaccountingfor>99%ofprobabilityofbeingcausalfortheassociationsignal(Methods;53SupplementaryTable7).ThegreatestrefinementwasatYKT6-GCK,wherethecrediblesetincluded54onlythelowfrequencyvariantrs138715366,whichmapsintronictoYKT6.5556Incombination,the62distinctgenome-widesignificantsignalsexplained2.0%(standarderror(SE)571.1%)ofvarianceinBW(SupplementaryTable8;Methods),whichissimilarinmagnitudetothe58varianceexplainedbysexormaternalBMI5.However,thevarianceinBWcapturedcollectivelybyall59autosomalgenotypedvariantsonthearraywasconsiderablylarger,estimatedat15.1%(SE=0.9)in60UKBiobank(usingREMLimplementedinBOLT-LMM6).Thesefiguresareconsistentwithalongtail61ofgeneticvariantsofsmallereffectscontributingtovariationinBW.6263AssociationsbetweenfoetalgenotypeandBWcouldresultfromindirecteffectsofthematernal64genotype(rwithfoetalgenotype≈0.5)influencingBWviatheintrauterineenvironment.To65investigatethispossibilityforeachofthelead59SNPs,wecomparedtheeffectsizeofmaternal66genotypeonBWoffirstchildin19,626women7withthatoffoetalgenotype(fromtheEuropean67ancestryGWASmeta-analysisof143,677individualsfromthepresentstudy;Methods).Wealso68undertookanalysesoffoetalgenotypeconditionalonmaternalgenotypein5,177mother-child69pairs.Thepoweroftheseanalyseswasconstrainedbythelimitedsamplesize,butonlythe70associationatMTNR1Bemergedasmorelikelytobedrivenbythematernalthanthefoetal71genotype(ExtendedData5and6,SupplementaryTable9).ThedependenceofMTNR1BBWeffect72onmaternalgenotypehasbeenreportedbyothers7.7374Theseanalysesprovidecompellingevidencethatfoetalgenotypehasasubstantialimpactonearly75growth,asmeasuredbyBW.Wesoughttousethesegeneticassociationstounderstandthecausal76relationshipsbetweentheobservedBW-diseaseassociationsandtocharacterisetheunderlying77processesresponsible.78 79ToquantifythesharedgeneticcontributiontoBWandotherhealth-relatedtraits,weestimated80theirgeneticcorrelationsusingLDScoreregression8(Methods).BW(inEuropeanancestrysamples)81showedstrongpositivegeneticcorrelationswithanthropometricandobesity-relatedtraitsincluding82birthlength(rg=0.81,P=2.0x10-44),andinadults,height(rg=0.41,P=4.8x10-52),waistcircumference83(rg=0.18,P=3.9x10-10)andbodymassindex(BMIrg=0.11,P=7.3x10-6).Incontrast,BWshowedinverse84geneticcorrelationswithindicatorsofadversemetabolicandcardiovascularhealthincluding85coronaryarterydisease(CADrg=-0.30,P=6.5x10-9),systolicbloodpressure(SBPrg=-0.22,P=5.5x10-13)86andT2D(rg=-0.27,P=1.1x10-6)(Figure2,SupplementaryTable10),whichnotablyareofsimilar87magnitude,althoughdirectionally-opposite,tothereportedgeneticcorrelationsbetweenadultBMI88andthosesamecardiometabolicoutcomes8.Thesefindingssupportobservationalassociations89betweenpaternalT2Dandlowerbirthweight4,andestablishmoregenerallythattheobserved90lifecourseassociationsbetweenearlygrowthandadultdiseaseatleastinpartreflecttheimpactof91sharedgeneticvariants.Toestimatetheextentofgeneticcontributiontotheselifecourse92associations,wefocusedondatafromUKBiobank(Methods).Weestimatedthat52%oftheBW-93T2Dcovarianceand86%oftheBW-SBPcovarianceisexplainedbysharedgeneticassociationswith94directlygenotypedSNPs(SupplementaryTable11).Theseanalysesbenefitfromthelargesample95sizeinUKBiobank,butarelimitedinthesensethattheydonotaccountformaternalgenotypic96effectsandalsoassumelinearityoftherelationships.Nevertheless,theseestimatesindicatethata97substantialproportionofthevariationinT2DriskorSBPthatcovarieswithBWcanbeattributedto98theeffectsofcommongeneticvariation.99100Toelucidatethebiologicalpathwaysandprocessesunderlyingregulationoffoetalgrowth,wefirst101performedgenesetenrichmentanalysisofourBWGWASanalysisusingMAGENTA9(Methods).102

Twelvepathwaysreachedstudy-widesignificance(FDR<0.05),includingpathwaysinvolvedin103metabolism(insulinsignalling,glycogenbiosynthesis,cholesterolbiosynthesis),growth(IGF-104signalling,growthhormonepathway)anddevelopment(chromatinremodelling)(ExtendedData7).105Weinterrogatedempiricalprotein-proteininteraction(PPI)data(collatedwithinInweb10)tofurther106characterisethesenetworks(ExtendedData8;Methods),identifying13PPInetworkmoduleswith107marked(z-score>5)enrichmentforgene-levelBW-associationscores.Theproteinswithinthese108moduleswerethemselvesalsoenrichedfordiverseprocessesrelatedtometabolism,growthand109development(ExtendedData8a,b).110111WealsoobservedenrichmentofBWassociationsignalsat77imprintedgenesdefinedbythe112Genotype-TissueExpression(GTEx)project11(P=1.9x10-4;ExtendedData7,SupplementaryTable11312).Suchenrichmentisconsistentwiththe“parentalconflict”hypothesisregardingtheallocationof114maternalresourcestothefoetus12.Althoughtheroleofimprintedgenesinfoetalgrowthis115describedinanimalmodelsandrarehumandisorders13,ourresultisthefirstlarge-scale,systematic116demonstrationoftheircontributiontonormalvariationinBW.Ofthe59genome-widesignificant117loci,two(INS-IGF2,RB1)fallwithin(ornear)imprintedregions(Figure1b),withanoteworthythird118signalatDLK1(previouslyfoetalantigen-1;P=5.6x10-8).Parent-of-originspecificanalysestofurther119investigatetheseindividuallocilackedpowerduetothelimitedavailabilityofsuitablylargefamily-120basedstudies(ExtendedData9,SupplementaryTables13and14;Methods).121122Manyofthegenome-widesignalsforBWdetectedherearealsoestablishedgenome-wide123associationsignalsacrossawidevarietyoftraits(Figure3).TheseincludetheBWsignalsnear124CDKAL1,ADCY5,HHEX/IDEandANK1(forT2D),NT5C2andADRB1(forBP/CAD/BMI).Weusedtwo125approachestounderstandwhetherthispatternofadulttraitassociationwasagenericpropertyof126BW-associatedloci,orreflectedheterogeneousmechanismscharacterisingtheunderlyingbiologyof127thoseloci.128129First,weappliedunsupervisedhierarchicalclustering(Methods)tothenon-BWtraitassociation130statisticsforthe59significantBWloci.Theresultantheatmapillustratestheappreciable131heterogeneityofbetween-locuseffect-sizeacrosstherangeofadulttraits(Figure3,Supplementary132Table15).Forexample,anassociationbetweentheBW-raisingalleleandhigheradultheightis133concentratedamongstasubsetoflociincludingHHIPandGNA12.134135Secondly,weconstructedtrait-specific“point-of-contact”(PoC)PPInetworksfromproteins136representedinboththeglobalBWPPInetworkandequivalentPPInetworksgeneratedforeachof137theadulttraits(Methods;ExtendedData8c-e):weevaluatedeachofthesewithrespectto138enrichmentforthe50pathwaysover-representedintheglobalBWPPInetwork.Thisanalysis139highlightedpathwaysthatwerespecificallyimplicatedinBW-traitoverlaps:forexampleproteinsin140theWntcanonicalsignallingpathwayareonlydetectedinthepoint-of-contactPPIforBPtraits.We141usedthesePPIoverlapstohighlightspecificcandidatetranscriptsthatarelikelytomediatethe142mechanisticlinks.Forexample,theoverlapbetweenWntsignallingpathwayandthepoint-of-143contactPPInetworkfortheintersectionofBWandBP-relatedtraitsimplicatesFZD9asthelikely144effectorgeneattheMLXIPLBWlocus.145146Wefocusedourmoredetailedinvestigationofthemechanisticlinksbetweenearlygrowthandadult147traitsontwophenotypicareas:arterialBPandT2D/glycaemia.148149AcrossboththeoverallGWASandspecificallyamongthe59significantBWloci,BW-raisingalleles150wereassociatedwithreducedBP(Figures2,3),withthestrongestinverseassociationsseenforthe151locinearNT5C2,FES,NRIP1,EBF1andPTH1R.Whenweconsideredthereciprocalrelationship,i.e.152theeffectsonBWofBP-raisingallelesat30reportedlociforSBP14,15,thereweremoreassociations153

(5/30)withlowerBWatP<0.05thanexpectedbychance(P=0.0026;ExtendedData10a).Thesemay154indicatedirectgrowth-restrictiveeffectsofbloodpressure-raisingallelesinthefoetus.Whenwe155performedequivalentanalysesusing45lociassociatedwithCAD16,theinversegeneticcorrelation156betweenCADandBWwasconcentratedamongstthe5CADlociwithprimaryBPassociations.This157suggeststhatgeneticdeterminantsofBPplayaleadingroleinmediatingthelifecourseassociations158betweenBWandCAD(ExtendedData10b,e).However,wealsoobservedlocus-specific159heterogeneityinthegeneticrelationshipsbetweenBPandBW:theSBP-raisingalleleatADRB115is160associatedwithhigher,ratherthanlower,BW(ExtendedData10a).161162TheBP-raisingallelewiththelargestBW-loweringeffectmapstotheNT5C2locus(indexvariantfor163BW,rs74233809,atr2=0.98withindexvariantforBP,rs1119154814)andisalsoassociatedwith164loweradultBMI(r2=0.99withrs1119156017).TheBW-loweringalleleatrs74233809isaproxyfora165recentlydescribedfunctionalvariantinthenearbyCYP17A1gene(r2=0.92withrs138009835)18.This166variantisknowntoaltertranscriptionalefficiencyinvitroandisassociatedwithhigherurinary167tetrahydroaldosteroneexcretion18.TheCYP17A1geneencodesthecytochromeP450c17αenzyme,168CYP1719,whichcatalyseskeystepsinsteroidogenesisthatdeterminethebalancebetween169mineralocorticoid,glucocorticoidandandrogensynthesis.Itisexpressedinfoetaladrenalglandsand170testesfromearlygestation20andintheplacenta21.ThesedataimplicatevariationinCYP17A1171expressionasacontributortotheobservationalassociationbetweenlowBWandadult172hypertension22.173174AcrosstheoverallGWAS,BW-raisingalleleswereassociatedwithreducedriskofT2D(Figure2),but175thelocusspecificheatmap(Figure3)indicatesaheterogeneouspatternacrossindividualloci.To176explorethisfurther,wetestedthe84reportedT2Dloci23forassociationwithBW.SomeT2Drisk177alleleswerestronglyassociatedwithhigherBW,whilstotherswithlower(ExtendedData10c).This178wasincontrastwiththeBWeffectsof422knownheightloci24(ExtendedData10d),whichshoweda179strongpositivecorrelationconsistentwiththeoverallgeneticcorrelationbetweenheightandBW,180suggestingthatthegrowtheffectsofmanyheightlocistartprenatallyandpersistintoadulthood.181TheeffectsofT2D-riskalleleswithrespecttolowerBW(atADCY5,CDKAL1andHHEX-IDE)exemplify182the“foetalinsulinhypothesis”25andreflectthepotentialforreducedinsulinsecretionand/or183signallingtoleadtobothreducedfoetalgrowthand,manydecadeslater,enhancedpredisposition184toT2D.Conversely,theevidencethatT2Driskallelesatsomeloci(mostnotablyatMTNR1B)are185associatedwithhigherBWisconsistentwithmaternalgenotypeeffects7,26.Whenwecategorised186T2Dlociusingaclassificationofphysiologicalfunctionderivedfromtheireffectsonrelated187glycaemicandanthropometrictraits27,wefoundthatT2D-riskallelesassociatedwithlowerBWwere188thosetypicallycharacterisedbyreducedinsulinprocessingandsecretionwithoutdetectable189changesinfastingglucose(the“BetaCell”clusterinExtendedData10f).190191TheYTK6signalatrs138715366isnotable,notonlybecausethegeneticdataindicatesthatasingle192low-frequencynon-codingriskalleleisdrivingtheassociationsignal(seeabove)butbecauseofthe193proximityofthissignaltoGCK.Rarecodingvariantsinglucokinasearecausalforaformof194monogenichyperglycaemiaandleadtolargereductionsinBWwhenparentalallelesarepassedto195theiroffspring28.Inaddition,commonnon-codingvariantsnearbyareimplicatedinT2D-riskand196fastinghyperglycaemia29,30.However,thelattervariantsareconditionallyindependentof197rs138715366(SupplementaryTable16)andshownocomparableassociationwithlowerBW.Either198rs138715366actsthrougheffectortranscriptsotherthanGCK,ortheimpactofthelow-frequency199SNPnearYKT6onGCKexpressioninvolvestissue-and/ortemporal-specificvariationinregulatory200impact.201202Wehaveidentified59geneticlociassociatedwithBWandusedthesetogaininsightsintothe203aetiologyoffoetalgrowthandintowell-established,butuntilnowpoorlyunderstood,lifecourse204

diseaseassociations.Theevidencethattherelationshipbetweenearlygrowthandlatermetabolic205diseasehasanappreciablegeneticcomponentmaylimittheextenttowhichimprovementsin206antenatalnutritionandcareconstraintheexplodingprevalenceofdiseasessuchastype2diabetes.207However,thesegeneticstudiesalsoprovidearoutetodefiningthemechanismsthatdrivethese208lifecourseassociationswhethertheyarisefromgeneticvariationorfromenvironmentaleffects.209210211212

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METHODS297298Ethicsstatement.Allhumanresearchwasapprovedbytherelevantinstitutionalreviewboardsand299conductedaccordingtotheDeclarationofHelsinki.Allparticipantsprovidedwritteninformed300consent.EthicalapprovalforthestudywasobtainedfromtheALSPACEthicsandLawCommittee301andtheLocalResearchEthicsCommittees.302303Study-levelanalyses.Withineachstudy,BWwascollectedfromavarietyofsources,including304measurementsatbirthbymedicalpractitioners,obstetricrecords,medicalregisters,interviewswith305themotherandself-reportasadults(SupplementaryTable1).BWwasz-scoretransformed,306separatelyinmalesandfemales.IndividualswithextremeBW(>5standarddeviations(SD)fromthe307sex-specificstudymean),monozygoticorpolyzygoticsiblings,orpretermbirths(gestationalage<37308weeks,wherethisinformationwasavailable)wereexcludedfromdownstreamassociationanalyses309(SupplementaryTable1).310

Withineachstudy,stringentqualitycontroloftheGWASgenotypescaffoldwasundertaken,311priortoimputation(SupplementaryTable2).Eachscaffoldwasthenpre-phasedandimputed31,32312uptoreferencepanelsfromthe1000GenomesProjectConsortium2or1000GandUK10KProject313Consortium3(SupplementaryTable2).AssociationofBWwitheachvariantpassingestablished314GWASqualitycontrolfilters33wastestedinalinearregressionframework,underanadditivemodel315forthealleliceffect,afteradjustmentforstudy-specificcovariates,includinggestationalage,where316available(SupplementaryTable2).Whereappropriate,populationstructurewasaccountedforby317adjustmentforaxesofgeneticvariationfromprincipalcomponentsanalysis34andsubsequent318genomiccontrolcorrection35,orinclusionofageneticrelationshipmatrixinamixedmodel36319(SupplementaryTable2).320321Preparation,qualitycontrolandgeneticanalysisinUKBiobanksamples.UKBiobankphenotype322datawasavailablefor502,655participants37.AllparticipantsintheUKBiobankwereaskedtorecall323theirBW,ofwhich279,971didsoateitherthebaselineorfollow-upassessmentvisit.Ofthese,3247,686participantsreportedbeingpartofmultiplebirthsandwereexcludedfromdownstream325analyses.Ancestrychecks,basedonself-reportedancestryresultedintheexclusionof8,998326additionalparticipantsreportednottobewhiteEuropean.OfthoseindividualsreportingBWinthe327baselineandfollow-upassessments,393wereexcludedbecausethetworeportedvaluesdifferedby328morethan0.5kg.Forthosereportingdifferentvalues(≤0.5kg)betweenbaselineandfollow-up,we329tookthebaselinemeasureforwardfordownstreamanalyses.Wethenexcluded36,716individuals330reportingvalues<2.5kgor>4.5kgasimplausibleforlivetermbirthsbefore1970.Intotal226,178331participantshaddatarelatingtoBWthatmatchedtheseinclusioncriteria.332

GenotypedatafromtheMay2015releasewasavailableforasubsetof152,249participants333fromUKBiobank.InadditiontothequalitycontrolmetricsperformedcentrallybyUKBiobank,we334definedasubsetof“whiteEuropean”ancestrysamplesusingaK-means(K=4)clusteringapproach335basedonthefirst4geneticallydeterminedprincipalcomponents.Amaximumof67,786individuals336(40,425femalesand27,361males)withgenotypeandvalidBWmeasureswereavailablefor337downstreamanalyses.WetestedforassociationwithBW,assuminganadditivealleliceffect,ina338linearmixedmodelimplementedinBOLT-LMM6toaccountforcrypticpopulationstructureand339relatedness.Genotypingarraywasincludedasabinarycovariateinallmodels.Totalchip340heritability(i.e.thevarianceexplainedbyallautosomalpolymorphicgenotypedSNPspassingquality341control)wascalculatedusingRestrictedMaximumLikelihood(REML)implementedinBOLT-LMM6.342WeadditionallyanalysedtheassociationbetweenBWanddirectlygenotypedSNPsontheX343chromosome:forthisanalysis,weused57,715unrelatedindividualswithBWavailableand344identifiedbyUKBiobankaswhiteBritish.WeexcludedSNPswithevidenceofdeviationfromHardy-345WeinbergEquilibrium(P<1x10-6),MAF<0.01oroverallmissingrate>0.015,resultingin19,423SNPs346

foranalysisinPlinkv1.07(http://pngu.mgh.harvard.edu/purcell/plink/)38,withthefirst5ancestry347principalcomponentsascovariates.348

InboththefullUKBiobanksampleandourrefinedsample,weobservedthatBWwas349associatedwithsex,yearofbirthandmaternalsmoking(P<0.0015,allintheexpecteddirections),350confirmingmorecomprehensivepreviousvalidationofself-reportedBW4.Weadditionallyverified351thatBWassociationswithleadSNPsatsevenestablishedloci5basedonself-reportinUKBiobank352wereconsistentwiththosepreviouslypublished.353354Europeanancestrymeta-analysis.TheEuropeanancestrymeta-analysisconsistedoftwo355components:(i)75,891individualsfrom30GWASfromEurope,USAandAustralia;and(ii)67,786356individualsofwhiteEuropeanoriginfromUKBiobank.Inthefirstcomponent,wecombinedsex-357specificBWassociationsummarystatisticsacrossstudiesinafixed-effectsmeta-analysis,358implementedinGWAMA39andappliedasecondroundofgenomiccontrol35(λGC=1.001).359Subsequently,wecombinedassociationsummarystatisticsfromthiscomponentwithUKBiobankin360aEuropeanancestryfixed-effectsmeta-analysis,implementedinGWAMA39.VariantsfailingGWAS361qualitycontrolfiltersinUKBiobankorinatleast50%ofthetotalsamplesizeinthefirstcomponent,362orwithMAF≥0.1%,wereexcludedfromtheEuropeanancestrymeta-analysis.Wemeta-analysedthe363X-ChromosomeUKBiobankresults(19,423SNPs)withcorrespondingresultsfromtheEuropean364ancestrymeta-analysisusingfixedeffectsP-valuebasedmeta-analysisinMetal40(maxN=99,152)365butfoundnoassociationsatP<5x10-8.366

Wewereconcernedthatself-reportedBWasadultsinUKBiobankwouldnotbecomparable367withthatobtainedfrommorestringentcollectionmethodsusedinotherEuropeanancestryGWAS.368Inaddition,UKBioBanklackedinformationongestationalageforadjustment,whichcouldhavean369impactondifferenceinstrengthofassociationcomparedtotheresultsobtainedfromother370EuropeanancestryGWAS.However,weobservednoevidenceofheterogeneityinBWalleliceffects371atleadSNPsbetweenthetwocomponentsofEuropeanancestrymeta-analysis,usingCochran’sQ372statistic41,implementedinGWAMA39,afterBonferronicorrection(P>0.00085)(Supplementary373Table3).374

Wewerealsoconcernedthatoverlapofindividuals(duplicatedorrelated)betweenthetwo375componentsoftheEuropeanancestrymeta-analysismightleadtofalsepositiveassociationsignals.376WeperformedbivariateLDScoreregression8usingthetwocomponentsoftheEuropeanancestry377meta-analysisandobservedageneticcovarianceinterceptof0.0156(SE0.0058),indicatinga378maximumof1,119duplicateindividuals.UnivariateLDScoreregression8oftheEuropeanancestry379meta-analysisestimatedtheinterceptas1.0426,whichmayindicatepopulationstructureor380relatednessthatisnotadequatelyaccountedforintheanalysis.Toassesstheimpactofthis381inflationontheEuropeanancestrymeta-analysis,weexpandedthestandarderrorsofBWallelic382effectsizeestimatesandre-calculatedassociationP-values.Onthebasisofthisadjustedanalysis,383theleadSNPonlyatMTNR1Bdroppedbelowgenome-widesignificance(rs10830963,P=5.5x10-8).384385Trans-ancestrymeta-analysis.Thetrans-ancestrymeta-analysiscombinedthetwoEuropean386ancestrycomponentswithanadditional10,104individualsfromsixGWASfromdiverseancestry387groups:AfricanAmerican,Chinese,Filipino,Surinamese,TurkishandMoroccan.WithineachGWAS,388wefirstcombinedsex-specificBWassociationsummarystatisticsinafixed-effectsmeta-analysis,389implementedinGWAMA39andappliedasecondroundofgenomiccontrol35.Subsequently,we390combinedassociationsummarystatisticsfromthesixnon-EuropeanGWASandthetwoEuropean391ancestrycomponentsinatrans-ancestryfixed-effectsmeta-analysis,implementedinGWAMA39.392VariantsfailingGWASqualitycontrolfiltersinUKBiobankorinatleast50%ofthetotalsamplesize393inthefirstcomponent,orwithMAF≥0.1%,wereexcludedfromthetrans-ancestrymeta-analysis.394395PrioritisingcandidategenesineachBWlocus.Wecombinedanumberofapproachestoprioritise396themostlikelycandidategene(s)ineachBWlocus.Expressionquantitativetraitloci(eQTLs)were397

obtainedfromtheGenotypeTissueExpression(GTEx)Project(Version4)42,theGEUVADISProject43398andelevenotherstudies44-54usingHaploReg55.WeinterrogatedcodingvariantsforeachBWlead399SNPanditsproxies(EURr2>0.8)usingEnsemblandHaploReg.Theirlikelyfunctionalconsequences400werepredictedbySIFT56andPolyPhen257.Biologicalcandidacywasassessedbypresencein401significantlyenrichedgenesetpathwaysfromMAGENTAanalyses(seebelowfordetails).We402extractedallgeneswithin300kbofallleadBWSNPSandsearchedforconnectivitybetweenany403genesusingSTRING58.IftwoormoregenesbetweentwoseparateBWlociwereconnected,they404weregivenanincreasedpriorforbothbeingplausiblecandidates.Wealsoappliedprotein-protein405interaction(PPI)analysis(seebelowfordetails)toallgeneswithin300kbofeachleadBWSNPsand406rankedthegenesbasedonthescoreforconnectivitywiththesurroundinggenes.407408Approximateconditionalanalysis.WesearchedformultipledistinctBWassociationsignalsineach409oftheestablishedandnovelloci,definedas1Mbup-anddown-streamoftheleadSNPfromthe410trans-ancestrymeta-analysis,throughapproximateconditionalanalysis.WeappliedGCTA59to411identify“indexSNPs”fordistinctassociationsignalsattaininggenome-widesignificance(P<5x10-8)in412theEuropeanancestrymeta-analysisusingareferencesampleof5,000individualsofwhiteBritish413origin,randomlyselectedfromUKBiobank,toapproximatepatternsoflinkagedisequilibrium(LD)414betweenvariantsintheseregions.Notethatweperformedapproximateconditioningonthebasis415ofonlytheEuropeanancestrymeta-analysisbecauseGCTAcannotaccommodateLDvariation416betweendiversepopulations.417418Fine-mappinganalyses.WesoughttoleverageLDdifferencesbetweenpopulationscontributingto419thetrans-ancestrymeta-analysisandtotakeadvantageoftheimprovedcoverageofcommonand420low-frequencyvariationofferedby1000Genomesand/orUK10Kimputationtolocalisevariants421drivingeachdistinctassociationsignalachievinglocus-widesignificance.Foreachdistinctsignal,we422usedMANTRA60toconstruct99%crediblesetsofvariants61thattogetheraccountfor99%ofthe423posteriorprobabilityofdrivingtheassociation.MANTRAincorporatesapriormodelofrelatedness424betweenstudies,basedonmeanpair-wiseallelefrequencydifferencesacrossloci,toaccountfor425heterogeneityinalleliceffects(SupplementaryTable3).MANTRAhasbeendemonstrated,by426simulation,toimprovelocalisationofcausalvariantscomparedwitheitherafixed-orrandom-427effectstrans-ancestrymeta-analysis60,62.428

Forlociwithonlyonesignalofassociation,weusedMANTRAtocombinesummarystatistics429fromthesixnon-EuropeanGWASandthetwoEuropeanancestrycomponents.However,forloci430withmultipledistinctassociationsignals,weusedMANTRAtocombinesummarystatisticsfrom431approximateconditioningforthetwoEuropeancomponents,separatelyforeachsignal.432

Foreachdistinctsignal,wecalculatedtheposteriorprobabilitythatthejthvariant,πCj,is433drivingtheassociation,givenby434435

𝜋!! =!!!!!,436

437wherethesummationisoverallvariantsmappingwithinthe(conditional)meta-analysisacrossthe438locus.Inthisexpression,ΛjistheBayes’factor(BF)infavourofassociationfromtheMANTRA439analysis.A99%credibleset61wasthenconstructedby:(i)rankingallvariantsaccordingtotheirBF,440Λj;and(ii)includingrankedvariantsuntiltheircumulativeposteriorprobabilityexceeds0.99.441442Evaluationofimputationqualityoflow-frequencyvariantattheYKT6-GCKlocus.AttheYKT6-GCK443locus,theleadSNP(rs138715366)isoflow-frequencyinEuropeanancestrypopulations444(MAF=0.92%)andevenrarerinotherancestrygroups(MAF=0.23%inAfricanAmericans,otherwise445monomorphic)andisnotpresentintheHapMapreferencepanel63.Toassesstheaccuracyof446imputationforthislow-frequentvariant,wegenotypedrs138715366inNFBC1966(Supplementary447Table1).Ofthe5,010samplesinthestudy,4,704weresuccessfullyimputedandgenotyped(or448

sequenced)forrs138715366.Theoverallconcordanceratebetweenimputedanddirectlyassayed449genotypeswas99.8%andfordirectlyassayedheterozygotecallswas75.0%.450451Estimationofgeneticvarianceexplained.VarianceexplainedwascalculatedusingtheREML452methodimplementedinGCTA64.WeconsideredthevarianceexplainedbytwosetsofSNPs:(i)lead453SNPsatsevenpreviouslyreportedBWloci(ExtendedData2);and(ii)leadSNPsofall62distinct454associationsignalsatthe59establishedandnovelBWlociidentifiedintheEuropean-specificor455trans-ancestrymeta-analyses(SupplementaryTable7).Varianceexplainedwascalculatedin456samplesofEuropeanancestryintheHyperglycemiaandAdversePregnancyOutcome(HAPO)457study65(independentofthemeta-analysis)andtwostudiesthatwerepartoftheEuropeanancestry458meta-analysis:NFBC1966andGenerationR(SupplementaryTable1).Ineachstudy,thegenetic459relationshipmatrixwasestimatedforeachsetofSNPsandwastestedindividuallyagainstBW460(malesandfemalescombined)withstudyspecificcovariates.Theseanalysesprovidedanestimate461andstandarderrorforthevarianceexplainedbyeachofthegivensetsofSNPs.462463ExaminingtherelativeeffectsonBWofmaternalandfoetalgenotypeatthe59identifiedloci.464WhereresultswereavailablewecomparedassociationswithBWofthefoetalversusmaternal465genotypeateachofthe59BWloci.ThematernalalleliceffectonoffspringBWwasobtainedfroma466maternalGWASmeta-analysisof19,626Europeanmothers7,whichwasimputeduptotheHapMap4672referencepanel66.Ofthese19,626women,9,048weremothersofindividualsincludedinthe468currentfoetalEuropeanancestryGWAS,andafurther3,729werethemselves(withtheirownBW)469includedinthefoetalGWAS.Proxieswithr2>0.6wereusediftheBWleadSNPwasnotpresentin470thereferencepanel.ThelocinearDTL,YKT6-GCK,INS-IGF2,SUZ12P1-CRLF3andPEPDdidnothave471suitableproxiesavailable.Wealsoconductedanalysesin5,177mother-childpairsintheAvon472LongitudinalStudyofParentsAndChildren(ALSPAC)study.Ateachofthe59loci,wecomparedthe473effectofthefoetalgenotypeonBWadjustedforsexandgestationalage,withandwithout474adjustmentformaternalgenotype.Wereciprocallycomparedtheassociationbetweenthe475maternalgenotypeandBWwithandwithoutadjustmentforfoetalgenotype.476477LDScoreRegression.SummarystatisticsfromtheGWASmeta-analysisfortraitsanddiseasesof478interestweredownloadedfromtherelevantconsortiumwebsite(SupplementaryTable10).The479summarystatisticsfileswerereformattedforLDScoreregressionanalysisusingthe480munge_sumstats.pypythonscriptprovidedonthedeveloper’swebsite481(https://github.com/bulik/ldsc).Foreachtrait,wefilteredthesummarystatisticstothesubsetof482HapMap3SNPs60,asadvisedbythedevelopers,toensurethatnobiaswasintroducedduetopoor483imputationquality.SummarystatisticsfromtheEuropean-specificBWmeta-analysiswereused484becauseofthevariableLDstructurebetweenancestrygroups.WherethesamplesizeforeachSNP485wasincludedintheresultsfilethiswasflaggedusing--N-col;ifnosamplesizewasavailablethenthe486maximumsamplesizereportedinthereferencefortheGWASmeta-analysiswasused.SNPswere487excludedforthefollowingreasons:MAF<0.01;ambiguousstrand;duplicatersID;reportedsample488sizelessthan60%ofthetotalavailable.Onceallfileswerereformatted,weusedtheldsc.pypython489script,alsoonthedevelopers’website,tocalculatethegeneticcorrelationbetweenBWandeachof490thetraitsanddiseases.TheEuropeanLDScorefilesthatwerecalculatedfromthe1000Genomes491referencepanelandprovidedbythedeveloperswereusedfortheanalysis.WheremultipleGWAS492meta-analyseshadbeenconductedonthesamephenotype(i.e.overaperiodofyears),thegenetic493correlationwithBWwasestimatedusingeachsetofsummarystatisticsandpresentedin494SupplementaryTable10.ThephenotypeswithmultipleGWASincludedheight,BMI,waist-hipratio495(adjustedforBMI),totalcholesterol,triglycerides,HDLandLDL.Theestimateofthegenetic496correlationbetweenthemultipleGWASmeta-analysesonthesamephenotypewerecomparable497andthelaterGWAShadasmallerstandarderrorduetotheincreasedsamplesize,soonlythe498geneticcorrelationbetweenBWandthemostrecentmeta-analyseswerepresentedinthefigure.499

InthepublishedGWASforbloodpressure14thephenotypewasadjustedforBMI.Cautionis500neededwheninterpretingthegeneticcorrelationbetweenBWandBMI-adjustedSBPduetothe501potentialforcolliderbias67.SinceBMIisassociatedwithbothbloodpressureandBW,itispossible502thattheuseofabloodpressuregeneticscoreadjustedforBMImightbiasthegeneticcorrelation503estimatetowardsamorenegativevalue.Toinvestigatethepossibilitythatthenegativegenetic504correlationbetweenBWandSBP(adjustedforBMI)wasduetocolliderbias,weperformedaGWAS505ofsystolicbloodpressure(unadjustedforBMI)intheUKBiobankdataandusedtheresulting506summarystatisticsintheLDScoreregressionanalysis,inplaceofthepublisheddata.Thesystolic507bloodpressurephenotypeinUKBiobankwaspreparedasfollows.Twobloodpressurereadings508weretakenatassessment,approximately5minutesapart.Weincludedallindividualswithan509automatedbloodpressurereading(takenusinganautomatedOmronbloodpressuremonitor).Two510validmeasurementswereavailableformostparticipants(averagedtocreateabloodpressure511variable,oralternativelyasinglereadingwasusedifonlyonewasavailable).Individualswere512excludedifthetworeadingsdifferedbymorethan4.56SD.Bloodpressuremeasurementsmore513than4.56SDawayfromthemeanwereexcluded.Weaccountedforbloodpressuremedicationuse514byadding15mmHgtothesystolicbloodpressuremeasure.Bloodpressurewasadjustedforage,515sexandcentrelocationandtheninverseranknormalised.WeperformedtheGWASon127,698516individualsofBritishdescentusingBOLT-LMM6,withgenotypingarrayascovariate.517518EstimatingtheproportionoftheBW-type2diabetes(T2D)andBW-systolicbloodpressure(SBP)519covarianceattributabletogenotypedSNPsinUKBiobankdata.Weestimatedthegeneticand520residualcovariancecomponentsinUKBiobankusingdirectlygenotypedSNPsandtheREMLmethod521implementedinBOLT-LMM6.TheUKBiobanksystolicbloodpressurephenotypewaspreparedas522describedabove.IndividualsweredefinedashavingT2Diftheyreportedbeingaffectedbythe523diseaseorgenericdiabetesatassessment.Thefollowingcaseswereexcluded:(i)thosereporting524insulinusewithinthefirstyearofdiagnosis;(ii)thosereportingdiagnosisundertheageof35(to525limitthenumberofindividualswithslow-progressingautoimmunediabetesormonogenicforms);526(iii)thosediagnosedwithdiabeteswithinthelastyear(aswewereunabletodeterminewhether527theywereusinginsulinwithinthistimeframe);and(iv)thosereportingtype1diabetes.Atotalof5284,327T2Dcasesand121,261controlswereretainedforanalysis.529530Genesetenrichmentanalysis.Meta-AnalysisGene-setEnrichmentofvariaNTAssociations531(MAGENTA)wasusedtoexplorepathway-basedassociationsusingsummarystatisticsfromthe532trans-ancestrymeta-analysis.MAGENTAimplementsagenesetenrichmentanalysis(GSEA)based533approach,aspreviouslydescribed9.Briefly,eachgeneinthegenomeismappedtoasingleindex534SNPwiththelowestP-valuewithina110kbupstreamand40kbdownstreamwindow.ThisP-value,535representingagenescore,isthencorrectedforconfoundingfactorssuchasgenesize,SNPdensity536andLD-relatedpropertiesinaregressionmodel.GeneswithintheHLA-regionwereexcludedfrom537analysisduetodifficultiesinaccountingforgenedensityandLDpatterns.Eachmappedgeneinthe538genomeisthenrankedbyitsadjustedgenescore.Atagivensignificancethreshold(95thand75th539percentilesofallgenescores),theobservednumberofgenescoresinagivenpathway,witha540rankedscoreabovethespecifiedthresholdpercentile,iscalculated.Thisobservedstatisticisthen541comparedto1,000,000randomlypermutedpathwaysofidenticalsize.Thisgeneratesanempirical542GSEAP-valueforeachpathway.Significancewasattainedwhenanindividualpathwayreacheda543falsediscoveryrate(FDR)<0.05ineitheranalysis.Intotal,3,216pre-definedbiologicalpathways544fromGeneOntology,PANTHER,KEGGandIngenuityweretestedforenrichmentofmultiplemodest545associationswithbirthweight.TheMAGENTAsoftwarewasalsousedforenrichmenttestingof546customgenesets.547548Protein-Proteininteractionnetworkanalyses.WeusedtheintegrativeProtein-Interaction-549Network-BasedPathwayAnalysis(iPINBPA)method68.Brieflywegeneratedgene-wiseP-values550

fromthetrans-ancestrymeta-analysisusingVEGAS269.Thosethatwerenominallysignificant551(P≤0.01)wereselectedas“seedgenes”toweightthenodesinthenetworkfollowingaguilt-by-552associationapproach.Inasecondstep,anetworkscorewasdefinedbythecombinationofthez-553scoresderivedfromthegene-wiseP-valueswithnodeweightsusingtheLiptak-Stouffermethod70.A554heuristicalgorithmwasthenappliedtoextensivelysearchformodulesenrichedingeneswithlowP-555values.Themoduleswerefurthernormalisedusinganulldistributionof10,000randomnetworks.556Onlythosemoduleswithz-score>5wereselected.557558Parent-of-originspecificassociations.Wefirstsearchedforevidenceofparentoforigineffectsin559theUKBiobanksamplesbycomparingvariancebetweenheterozygotesandhomozygotesusing560Quicktest71.Inthisanalysis,weusedonlyunrelatedindividualsidentifiedgeneticallyasofwhite561Britishorigin.Principalcomponentsweregeneratedusingtheseindividualsandthefirstfivewere562usedtoadjustforpopulationstructureascovariatesintheanalysis,inadditiontoabinaryindicator563forgenotypingarray.564

Wealsoexamined4,908mother-childpairsinALSPACanddeterminedtheparentaloriginof565thealleleswherepossible72.Briefly,themethodusesmother-childpairstodeterminetheparentof566originofeachallele.Forexample,ifthemother/childgenotypesareAA/Aa,thechild’s567maternal/paternalallelecombinationisA/a.Forthesituationwherebothmotherandchildare568heterozygous,thechild’smaternal/paternalallelescannotbedirectlyspecified.However,the569parentaloriginoftheallelescanbedeterminedbyphasingthegenotypedataandcomparing570maternalandchildhaplotypes.WethentestedtheseallelesforassociationwithBWadjustingfor571sexandgestationalage.572573HierarchicalclusteringofBWloci.ToexplorethedifferentpatternsofassociationbetweenBWand574otheranthropometric/metabolic/endocrinetraitsanddiseases,weperformedhierarchicalclustering575analysis.TheleadSNP(orproxy,EURr2>0.6)atthe59BWlociwasqueriedinpubliclyavailable576GWASmeta-analysisdatasetsorinGWASresultobtainedthroughcollaboration73,74.Resultswere577availablefor53ofthoselociandtheextractedz-score(alleliceffect/SE,SupplementaryTable15)578wasalignedtotheBW-raisingallele.Weperformed2Dclusteringbytraitandbylocus.We579computedtheEuclideandistanceamongstz-scoresoftheextractedtraits/lociandperformed580completehierarchicalclusteringimplementedinthepvclustpackage(http://www.sigmath.es.osaka-581u.ac.jp/shimo-lab/prog/pvclust/)inRv3.2.0(http://www.R-project.org/).Clusteringuncertaintywas582measuredbymultiscalebootstrapresamplingestimatedfrom1,000replicates.Weusedα=0.05to583definedistinctclustersand,basedonthebootstrapanalysis,calculatedtheCalinskiindextoidentify584thenumberofwell-supportedclusters(cascadeKMfunction,Veganpackage,http://CRAN.R-585project.org/package=vegan).Clusteringwasvisualisedbyconstructingdendrogramsandaheatmap.586587588ADDITIONALREFERENCESFORMETHODS58959031. MarchiniJ,HowieB.Genotypeimputationforgenome-wideassociationstudies.NatRevGenet591

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ENDNOTESSupplementaryInformationisavailableintheonlineversionofthepaper.AcknowledgementsThisstudyhasbeenconductedusingtheUKBiobankResource.FullgrantsupportsandacknowledgementscanbefoundintheSupplementaryInformation.AuthorContributionsCoreanalysesandwriting. M.H.,R.N.B.,F.R.D.,N.M.W.,M.N.K.,J.F-T.,N.R.v.Z.,K.J.G.,A.P.M.,K.K.O.,J.F.F.,N.J.T.,J.R.P.,D.M.E.,M.I.M.,R.M.F.Statisticalanalysisinindividualstudies(leadanalystsinitalics). M.H.,R.N.B.,F.R.D.,N.M.W.,M.N.K.,N.G.,J.P.B.,D.P.S.,R.L-G.,T.S.A.,E.K-M.,R.R.,L-P.L.,D.L.C.,Y.W.,E.T.,C.A.W.,C.T.H.,J-J.H.,N.V-T.,P.K.J.,B.F.,E.T.H.B.,I.N.,N.P.,A.M.,E.M.v.L.,R.J.,V.Lagou,M.N.,J.M.M.,S.E.J.,P-R.L.,K.S.R.,M.A.T.,J.T.,A.R.W.,H.Y.,D.M.S.,I.P.,K.Panoutsopoulou,X.W.,L.C.,F.G.,K.E.S.,M.Murcia,E.V.R.A.,Z.K.,S.B.-G.,F.S.,D.T.,J.W.,C.M-G.,N.R.R.,E.Z.,G.V.D.,Y-Y.T.,H.N.K.,A.P.M.,J.F.F.,N.J.T.,J.R.P.,D.M.E.,R.M.F.GWASlook-upinunpublisheddatasets. K.T.Z.,N.R.,D.R.N.,R.C.W.M.,C.H.T.T.,W.H.T.,S.K.G.,F.J.v.R.Samplecollectionanddatagenerationinindividualstudies. F.R.D.,M.N.K.,N.G.,J.P.B.,D.P.S.,R.L-G.,R.R.,L-P.L.,J-J.H.,B.F.,I.N.,E.M.v.L.,M.B.,P.M.M-V.,A.J.B.,L.P.,P.K.,M.A.,S.M.W.,F.G.,C.E.v.B.,G.W.,E.V.R.A.,C.E.F.,C.T.,C.M.T.,M.Standl,Z.K.,M.V.H.,H.G.d.H.,F.R.R.,C.M-G.,S.M.R.,G.H.,G.M.,N.R.R.,C.J.G.,C.L.,J.L.,R.A.S.,J.H.Z.,F.D.M.,W.L.L.Jr,A.T.,M.Stumvoll,V.Lindi,T.A.L.,C.M.v.D.,A.K.,T.I.S.,H.N.,K.Pahkala,O.T.R.,E.Z.,G.V.D.,S-M.S.,M.Melbye,H.C.,J.F.W.,M.V.,J-C.H.,T.H.,L.J.B.,J.P.N.,C.E.P.,L.S.A.,J.B.B.,K.L.M.,J.G.E.,E.E.W.,M.K.,J.S.V.,T.L.,P.V.,K.B.,H.B.,D.O.M-K.,F.R.,A.G.U.,C.Pisinger,O.P.,N.J.W.,H.H.,V.W.J.,S.F.G.,A.A.V.,D.A.L.,G.D.S.,K.K.O.,J.F.F.,N.J.T.,J.R.P.,M.I.M.Functionalfollow-upexperiment. L.A.D.,S.M.M.,R.M.R.,E.D.,B.R.W.Individualstudydesignandprincipalinvestigators. J.P.B.,I.N.,M.A.,F.D.M.,W.L.L.Jr,A.T.,M.Stumvoll,V.Lindi,T.A.L.,C.M.v.D.,W.K.,A.K.,T.I.S.,H.N.,K.Pahkala,O.T.R.,G.V.D.,Y-Y.T.,S-M.S.,M.Melbye,H.C.,J.F.W.,M.V.,E.J.d.G.,D.I.B.,H.N.K.,J-C.H.,T.H.,A.T.H.,L.J.B.,J.P.N.,C.E.P.,J.H.,L.S.A.,J.B.B.,K.L.M.,J.G.E.,E.E.W.,M.K.,J.S.V.,T.L.,P.V.,K.B.,H.B.,D.O.M-K.,A.H.,F.R.,A.G.U.,C.Pisinger,O.P.,C.Power,E.H.,N.J.W.,H.H.,V.W.J.,M-R.J.,S.F.G.,A.A.V.,T.M.F.,A.P.M.,K.K.O.,N.J.T.,J.R.P.,M.I.M.,R.M.F.AuthorInformationCorrespondenceandrequestsformaterialsshouldbeaddressedtomark.mccarthy@drl.ox.ac.ukandr.freathy@ex.ac.uk.Reprintsandpermissionsinformationisavailableatwww.nature.com/reprints.DisclosuresNiluferRahmiogluhasconsultancyforBayerHealthCareLtd.andScientificcollaborationwithBayerHealthCareLtd.andPopulationDiagnostics.KrinaZondervanhasascientificcollaborationwithBayerHealthCareLtd.andPopulationDiagnosticsInc.GrantsandfundingsupportsforstudiesTheAcademyofFinland[41071,1114194,117787,120315,121584,124282,126925,129287,129378,134309,206374,218029,24300796,251360,267561,276861,286284andEGEA-project];Althingi(theIcelandicParliament);theAmericanDiabetesAssociation;theArthritisResearchUK;theAugustinusFoundation;BaylorMedicalCollege[N01-HC-55016];theBecketFoundation;BiobankingandBiomolecularResourcesResearchInfrastructure(BBMRI-NL);BiocenterOulu,UniversityofOulu,

Finland;BiomedicalResearchCouncil,Singapore(BMRC06/1/21/19/466);theBritishHeartFoundation[SP/13/2/30111];theC.G.SundellFoundation;CambridgeInstituteforMedicalResearch(CIMR);theCanadianInstitutesofHealthResearch[MOP-82893];theCancerResearchUK[SP2024-0201andSP2024-0204];theCapitalRegionResearchFoundation;CenterforMedicalSystemsBiology(CMSB);theChiefScientistOfficeoftheScottishGovernment[CZB/4/276andCZB/4/710];theChildren’sHospitalofPhiladelphia[InstituteDevelopmentAward];ChineseUniversityofHongKong(CUHK)[FacultyofMedicineOutstandingFellowship];thecityofKuopio;ConselleriadeSanitatGeneralitatValenciana;theCotswoldFoundation[ResearchDevelopmentAward];DanielB.BurkeEndowedChairforDiabetesResearch;DanishCentreforHealthTechnologyAssessment;DanishCouncilforIndependentResearch;DanishInnovationFoundation[0603-00484Band0603-00457B];DanishDiabetesAssociation;DanishHeartFoundation;DanishInnovationFoundation;theDanishNationalResearchFoundation;DanishPharmaceuticalAssociation;DanishPharmacists’Fund;DanishResearchCouncil;DHFD(DiabetesHilfs-undForschungsfondsDeutschland);DiabetesandInflammationLaboratory;DiabetesResearchFoundationofFinland;EFSD/Lillyresearchfellowship;theEgmontFoundation;EmilAaltonenFoundation;ErasmusMedicalCenter,Rotterdam,theErasmusUniversityRotterdam;EuropeanCommission[ENGAGE(HEALTH-F4-2007-201413),FrameworkProgramme5(QLG2-CT-2002-01254),FrameworkProgramme6(018996,018947(LSHG-CT-2006-01947)andLSHG-CT-2006-018947),FrameworkProgramme7(FP7/2007-2013),H2020-633595DynaHEALTHaction,Beta-JUDOn°279153andDGXII];EuropeanResearchCouncil(ERCAdvanced,230374);EuropeanScienceFoundation(ESF,EU/QLRT-2001-01254);EuropeanUnion(EuropeanSocialFund-ESF);FacultyofBiologyandMedicineofLausanne;FinnishCardiacResearchFoundation;FinnishCulturalFoundation;FinnishFoundationofCardiovascularResearch,FinnishInnovationFundSitra;FinnishMinistryofEducationandCulture;FIS-FEDER[03/1615,04/1112,04/1509,04/1931,05/1052,05/1079,06/1213,07/0314,09/02647,11/00178,11/01007,11/02591,13/02032,13/1944,14/00891,14/01687,97/0588,00/0021-2,PI041436,PI061756,PI081151andPS0901958],FoundationforPaediatricResearchofFinland;FrenchMinistryofResearch;FundacióLaMaratódeTV3;Gene-dietInteractionsinObesityproject(GENDINOB);GeneralitatdeCatalunya[CIRIT1999SGR00241],GeneticAssociationInformationNetwork(GAIN);theGeneticLaboratoryoftheDepartmentofInternalMedicine,ErasmusMC;GermanDiabetesAssociation;GermanResearchCouncil[DFG-SFB1052“Obesitymechanisms”;A01,B01,B03,C01andSPP1629TO718/2-1];GermanResearchFoundationCollaborativeResearchCenter[CRC1085];GlaxoSmithKline;Greeknationalfunds:HeracleitusII;HealthFundoftheDanishHealthInsuranceSocieties;Hjartavernd(theIcelandicHeartAssociation);theIbHenriksenFoundation;theImpactofourGenomesonIndividualTreatmentResponseinObeseChildren(TARGET)theIndo-Danishbi-lateralproject,GeneticsandSystemsBiologyofChildhoodObesityinIndiaandDenmark(BioChild);InstitutodeSaludCarlosIII[RedINMAG03/176andCB06/02/0041];IntegratedResearchandTreatmentCenter(IFB)AdiposityDiseases[01EO1001];theItalianMinistryofHealth[ICS110.1RS97.71];JohnsHopkinsUniversity[N01-HC-55020];theJuhoVainioFoundation;theJuvenileDiabetesResearchFoundationInternational(JDRF);KuopioUniversityHospital[5031343];Kuopio,TampereandTurkuUniversityHospitalMedicalFunds[X51001];LeidenUniversityMedicalCenter;LeidenUniversity,ResearchProfileAreaVascularandRegenerativeMedicine;theLundbeckFoundation;theMarchofDimesBirthDefectsFoundation;MedicalResearchCouncil[G0000934,G0400874,G0500539,G0600705,G0601261,G9502233,MC_U106179471,PrevMetSynandMRCDoctoralTrainingGrantScholarship];MinistryofEducationandCultureofFinland;MinistryofEducation,CultureandScienceoftheNetherlands;MinistryofHealthofDenmark;MinistryofHealth,WelfareandSportoftheNetherlands;MinistryofInternalAffairsandHealthofDenmark;MinistryofSocialAffairsandHealthofFinland;MinistryofYouthandFamiliesoftheNetherlands;MRCIntegrativeEpidemiologyUnitattheUniversityofBristol(MC_UU_12013/1-9);MRCHumanGeneticsUnit;MunicipalityofRotterdam;NationalCenterforAdvancingTranslationalSciences[CTSIgrantUL1TR000124];NationalHeart,LungandBloodInstitute(NHLBI)[5R01HL087679,STAMPEEDprogram(1RL1MH083268-01),HHSN268201100005C,HHSN268201100006C,HHSN268201100007C,

HHSN268201100008C,HHSN268201100009C,HHSN268201100010C,HHSN268201100011CandHHSN268201100012C,HHSN268201200036C,HHSN268200800007C,N01HC55222,N01HC85079,N01HC85080,N01HC85081,N01HC85082,N01HC85083,N01HC8508,U01HL080295,R01HL087652,R01HL105756,R01HL103612,R01HL120393,N01-HC-25195andN02-HL-6-4278];NationalHealthandMedicalResearchCouncilofAustralia[003209,403981and572613];NationalHumanGenomeResearchInstitute(NHGRI)[U01HG004402];NationalInstituteofAging(NIA)[IntramuralResearchProgram,R01AG023629,N01-AG-916413,N01-AG-821336,263MD916413and263MD821336];NIA/NIH[AG000932-2];NationalInstituteofAllergyandInfectiousDiseases(NIAID);NationalInstituteofChildHealthandHumanDevelopment(NICHD);NationalInstituteofDiabetesandDigestiveandKidneyDiseases(NIDDK)[DK063491];NationalInstitutesofHealth(NIH)[1RC2MH089995-01;DK056350,DK078150,DK099820,ES10126,HD34242,HD34243,HG004415,HL085144,RR20649,R01D0042157-01A,R01DK092127-01;R01HD056465,TW05596,U01DK062418,U01HG004423,U01HG004438,U01HG004446,R01HL087641,R01HL59367,R01HL086694,UL1RR025005andN01-AG-12100];NationalInstituteforHealthResearchCambridgeBiomedicalResearchCentre;NationalInstituteofMentalHealth(NIMH)[MH081802,U24MH068457-06];NationalInstituteofNeurologicalDisordersandStroke(NINDS);NationalMedicalResearchFoundation,Singapore(NMRC/0975/2005);NBIC/BioAssist/RK(2008.024);theNetherlandsConsortiumforHealthyAging(NCHA);theNetherlandsGenomicsInitiative(NGI);theNetherlandsOrganisationforScientificResearchandtheRussianFoundationforBasicResearch[NWO-RFBR047.017.043];theNetherlandsOrganisationforScientificResearch(NWO)[NWO/ZonMw;NWOGenomics;NWO:MagW/ZonMWgrants400-05-717,480-04-004,481-08-011,451-04-034,463-06-001,904-61-090,904-61-193,912-10-020,916-76-125,985-10-002,Addiction-31160008Middelgroot-911-09-032andSpinozapremie56-464-14192,175.010.2005.011,911-03-012];NeuroscienceCampusAmsterdam(NCA);NovoNordiskFoundation;NovoNordiskInc.;thePaavoNurmiFoundation;PauloFoundation;theRegionZealandHealthandMedicalResearchFoundation;ResearchCommitteeoftheKuopioUniversityHospitalCatchmentArea;ResearchFoundationofCopenhagenCounty;ResearchGrantCouncilGeneralResearchFund[CU473408,CU471713];ResearchInstituteforDiseasesintheElderly(RIDE)[014-93-015];RobertDawsonEvansEndowment;theRoyalSociety;RutgersUniversityCellandDNARepository;theSigridJuseliusFoundation;SocialInsuranceInstitutionofFinland;SpanishGovernment[SEV-2011-00067];SpanishMinistryofScienceandInnovation[SAF2008-00357];SpanishNationalGenotypingCentre(CEGEN-Barcelona);SpecialGovernmentalGrantsforHealthSciencesResearch,TurkuUniversityHospital;SwissNationalScienceFoundation[33CSCO-122661,33CS30-139468and33CS30-148401];TampereTuberculosisFoundation;TurkuUniversityFoundation;UniversityofBristol;UniversityofCambridge;UniversityofMinnesota[N01-HC-55019];UniversityofMississippiMedicalCenter[N01-HC-55021];UniversityofNorthCarolina[N01-HC-55018];UniversityofNorthCarolinaatChapelHill[N01-HC-55015];UniversityofTexasHouston[N01-HC-55017];theVUUniversity’sInstituteforHealthandCareResearch(EMGO+);WellcomeTrust[068545/Z/02,076113/B/04/Z,079895,090532,098017,098051,098381,102215/2/13/2,GR069224];YrjöJahnssonFoundation.

FIGURELEGENDSFigure1|Manhattanandquantile-quantile(QQ)plotsofthetrans-ancestrymeta-analysisforbirthweight.a,Manhattan(mainpanel)andQQ(topright)plotsofgenome-wideassociationresultsforbirthweightfromtrans-ancestrymeta-analysisofupto153,781individuals.TheassociationPvalue(on-log10scale)foreachofupto22,185,636SNPs(yaxis)isplottedagainstthegenomicposition(NCBIBuild37;xaxis).Associationsignalsthatreachedgenome-widesignificance(P<5x10-8)areshowningreenifnovelandpinkifpreviouslyreported.IntheQQplot,theblackdotsrepresentobservedPvaluesandthegreylinerepresentsexpectedPvaluesunderthenulldistribution.ThereddotsrepresentobservedPvaluesafterexcludingthepreviouslyidentifiedsignalsdescribedinExtendedData2.b,Manhattan(mainpanel)andQQ(topright)plotsoftrans-ethnicGWASmeta-analysisforBWhighlightingthereportedimprintedregionsdescribedinSupplementaryTable12.Novelassociationsignalsthatreachedgenome-widesignificance(P<5x10-8)andmappedtoimprintedregionsareshowningreen.Genomicregionsoutsideimprintedregionsareshadedingrey.IntheQQplot,theblackdotsrepresentobservedPvaluesandthegreylinesrepresentexpectedPvaluesandtheir95%confidenceintervalsunderthenulldistributionfortheSNPswithintheimprintedregions.Figure2|Genome-widegeneticcorrelationbetweenbirthweightandarangeoftraitsanddiseasesinlaterlife.Geneticcorrelation(rg)andcorrespondingstandarderrorbetweenbirthweightandthetraitsdisplayedonthex-axisareestimatedusingLDScoreregression8.Thegeneticcorrelationestimates(rg)arecolourcodedaccordingtotheirintensityanddirection(redforpositiveandbluefornegativecorrelation).HC=headcircumference,WHR=waist-hipratio,WHR(adjBMI)=waist-hipratioadjustedforbodymassindex,BMI=bodymassindex,Pubertalgrowth=standardizeddifferenceinheightbetweenage8andadultheight,Totalgrowth=standardizeddifferenceinheightatage14andadultheight,CAD=coronaryarterydisease,DBP=diastolicbloodpressure,SBP=systolicbloodpressure*,Chol=totalcholesterol,TG=triglycerides,LDL=low-densitylipoprotein,HDL=high-densitylipoprotein,T2D=type2diabetes,HOMA-B=homeostaticmodelassessmentbeta-cellfunction,HOMA-IR=homeostaticmodelassessmentinsulinresistance,HbA1C=HemoglobinA1c,LSBMD=lumbarspinebonemineraldensity,FNBMD=femoralneckbonemineraldensity,EduAtt=educationalattainment,ADHD=attentiondeficithyperactivitydisorder,Cigarettes/Day=numberofcigarettesperday.SeeSupplementaryTable10forreferencesforeachofthetraitsanddiseasesdisplayedhere.*Thesourceofdataforbloodpressure14wasaGWASofSBPorDBPadjustedforBMI.ToverifythattheinversegeneticcorrelationwithBWwasnotduetocolliderbiascausedbytheBMIadjustmentofthephenotype,weobtainedanalternativeestimateusingUKBiobankGWASdataforSBPthatwasunadjustedforBMI(seeMethods)andobtainedasimilarresult:rg=-0.22(SE=0.03),P=5.5x10-13.Figure3|Hierarchicalclusteringofbirthweightlocibasedonsimilarityofoverlapwithadultdiseases,metabolicandanthropometrictraits.FortheleadSNPateachofthebirthweightloci(listedony-axis),thezscorealignedtothebirthweight-raisingalleleisobtainedfrompubliclyavailableGWASresultsforvariousadultdiseasesandtraits(listedonxaxis)andaredisplayedintheheatmap.Positivez-scoresinredindicatetheBW-raisingalleleincreasesthevalueofthetraitconcerned,andnegativez-scoresinblueshowthatitisassociatedwithdecreaseofthetraitvalueofinterest.Birthweightloci(onyaxis)andtraits(onxaxis)areclusteredaccordingtotheEuclideandistanceamongstz-scoreoftheloci/traits(seeMethods).ADRB1(leadBWvariantrs7076938)wasreportedasbloodpressurelocusbyJohnsonetal.15andKatoetal.75(leadBPvariantsrs1801253andrs2484294,respectively,EURr2=0.99withrs7076938)butwasnotsignificantlyassociatedwithvariousmeasurementsofbloodpressureinEhretetal.14fromwhichthez-scoreswereextracted.InEhretetal.,adifferentleadvariantrs2782980(EURr2=0.31withrs7076938)wasreported.Therefore,ADRB1doesnotshowstrongpositivecorrelationinthisheatmapdespitethefactthat

ADRB1locusissignificantlyassociatedwithbothbirthweightandbloodpressure.WhitecrosswithablackcircleinthemiddleindicatestraitlocuswithP<5x10-8inthepubliclyavailableGWASlook-up(SupplementaryTable15).Plainwhitecrossindicatestraitlocuswithestablishedgenome-wideassociationsignals.HC=headcircumference,WHRadjBMI=waist-hipratioadjustedforbodymassindex,BMI=bodymassindex,CAD=coronaryarterydisease,DBP=diastolicbloodpressure,SBP=systolicbloodpressure,Chol=totalcholesterol,TG=triglycerides,LDL=low-densitylipoprotein,HDL=high-densitylipoprotein,T2D=type2diabetes.

EXTENDEDDATALEGENDS

ExtendedData1|Flowchartofthestudydesign.ExtendedData2|Fiftyninelociassociatedwithbirthweight(P<5x10-8)inEuropeanancestrymeta-analysisofupto143,677individualsand/ortrans-ancestrymeta-analysisofupto153,781individuals.ExtendedData3|Regionalplotsformultipledistinctsignalsatthreebirthweightloci,ZBTB7B(a),HMGA1(b)andPTCH1(c).Regionalplotsforeachlocusaredisplayedfrom:theunconditionalEuropean-specificmeta-analysisofupto143,677individuals(left);theapproximateconditionalmeta-analysisfortheprimarysignalafteradjustmentfortheindexvariantforthesecondarysignal(middle);andtheapproximateconditionalmeta-analysisforthesecondarysignalafteradjustmentfortheindexvariantfortheprimarysignal(right).DirectlygenotypedorimputedSNPsareplottedwiththeirassociationPvalues(ona-log10scale)asafunctionofgenomicposition(NCBIBuild37).EstimatedrecombinationratesareplottedtoreflectthelocalLDstructurearoundtheindexSNPsandtheircorrelatedproxies.SNPsarecolouredinreferencetoLDwiththeparticularindexSNPaccordingtoabluetoredscalefromr2=0to1,basedonpairwiser2valuesestimatedfromareferenceof5,000individualsofwhiteBritishorigin,randomlyselectedfromtheUKBiobank.ExtendedData4|AbsoluteeffectsizeandminorallelefrequencyofleadSNPsat59knownandnovelbirthweightlocifromthetrans-ancestrymeta-analysisofupto153,781individuals.TheeffectofleadSNP(absolutevalueofbeta,yaxis)isgivenasafunctionofminorallelefrequency(xaxis)forknownbirthweightlociinpinkandnovellociingreen.Errorbarsareproportionaltothestandarderroroftheeffectsize.Thedashedlineindicates80%powertodetectassociationatgenome-widesignificancelevelforthesamplesizeintrans-ancestrymeta-analysis.Allbirthweightlociwerecommonexceptfortwo:attheYKT6-GCKlocus,theindexSNP(rs138715366)wasoflow-frequencyinEuropeanancestrypopulations(MAF=0.92%),andevenrarerinotherancestrygroups(MAF=0.23%inAfricanAmericans,otherwisemonomorphic).Similarly,attheSUZ12P1-CRLF3locus,theindexSNP(rs144843919)wasoflow-frequencyinEuropeanandAfricanAmericanancestrystudies(MAFof3.5%and4.0%,respectively),andabsentfromotherancestrygroups.Noneofthevariantsattaininggenome-widesignificanceinEuropeanancestryortrans-ancestrymeta-analysesatthesetwolociwaspresentinHapMap,suggestingthatthesetwoassociationsignalswouldnothavebeenidentifiedwithoutimputationuptothedenserreferencepanelsfrom1000G/UK10K,irrespectiveoftheavailablesamplesize.ExtendedData5|Comparisonoffoetaleffectsizesandmaternaleffectsizesat59knownandnovelbirthweightloci.Foreachbirthweightlocus,thefollowingsixeffectsizes(with95%CI)areshown,allalignedtothebirthweight-raisingalleleintheoveralltrans-ancestrymeta-analysis:f_GWAS=foetalalleliceffectonbirthweight(fromEuropeanancestrymeta-analysisofupton=143,677individuals);f_ALSPAC=foetalalleliceffectonbirthweight(unconditionedinn=5,177ALSPACmother-childpairs);f_ALSPAC-m=foetaleffectconditionedonmaternalgenotype(inn=5,177ALSPACmother-childpairs);m_GWAS=maternalalleliceffectonoffspringbirthweight(frommeta-analysisofupton=19,626Europeanmothers)7;m_ALSPAC=maternalalleliceffectonoffspringbirthweight(unconditionedinn=5,177ALSPACmother-childpairs);m_ALSPAC-f=maternaleffectconditionedonfoetalgenotype(inn=5,177ALSPACmother-childpairs).Ofthe59loci,fiveloci(nearDTL,YKT6-GCK,INS-IGF2,SUZ12P1-CRLF3,andPEPD)lackinformationonthematernaleffectonoffspringbirthweightfromthemeta-analysisofupton=19,626Europeanmothers(whichwasbasedonHapMap2imputation),duetotheunavailabilityoftheleadSNPoraproxy(r2=0.62to1).The59birthweightlociarearrangedintheorderofthechangeinthefoetaleffectonadjustmentformaternalgenotype(fromlargestincreasetolargestdecrease).Foran

associationtoshowconsistentevidenceofbeingdrivenbythematernalgenotype,wewouldexpect(i)theeffectsizeofthematernalGWASresulttobelargeranddirectionallyconsistentwiththefoetalGWASresult,(ii)theassociationbetweenfoetalgenotypeandBWtoresultinmajorattenuationonadjustmentformaternalgenotype,and(iii)theassociationbetweenthematernalgenotypeandBWtoresultinminorattenuationonadjustmentforfoetalgenotype.Onlyonelocus,MTNR1B(5thinthe7thcolumn)showedthispatternofresults(maternalGWASeffect=0.055SDperallele[95%CI:0.032,0.079];foetalEuropeanGWASeffect=0.022SD[95%CI:0.014,0.030]).ExtendedData6|Comparisonoffoetaleffectsizesandmaternaleffectsizesat59knownandnovelbirthweightloci.(Continued)ExtendedData7|Genesetenrichmentanalysisandprotein-proteininteractionanalysis.ExtendedData8|Protein-ProteinInteraction(PPI)Networkanalysis.a,illustratesthegloballargestcomponentbirthweight(BW)PPInetworkcontaining13modules.b,thehistogramshowsthenulldistributionofZ-scoresofBWPPInetworksbasedon10,1000randomnetworksandwheretheZ-scoresforthe13birthweightmodules(M1-13)lie.Foreachmodule,thetwomostsignificantGOtermsaredepicted.c,heatmapshowingtheenrichmentforthetop50biologicalprocessesover-representedintheglobalBWPPInetworkofthetrait-specific“pointofcontact“(PoC)PPInetworks.d-e,trait-specificPoCPPInetworkscomposedofproteinsthataresharedinboththeglobalbirthweightPPInetworkandnetworksgeneratedusingthesamepipelineforeachoftheadulttraits:d,canonicalWntsignallingpathwayenrichedforPoCPPIbetweenBWandbloodpressure(BP)-relatedphenotypes;ande,regulationofinsulinsecretionpathwayenrichedforPoCbetweenBWandtype2diabetes(T2D)/fastingglucose(FG).RednodesarethosethatarepresentinBWandPoCfortraitsofinterest;bluenodescorrespondtothepathwaynodes;purplenodesarethosepresentinboththepathwayandPoC.LargenodescorrespondtogenesinBWloci(within300kbfromtheleadSNP)andhaveablackborderiftheyhaveastrongeffect(top5ofallloci)onatleastoneofthetraits.ExtendedData9|Quantile-Quantile(QQ)plotofthevariancebetweenheterozygotesandhomozygotesanalysisin67,786UKBiobanksamples(a)andparent-of-originspecificanalysisin4,908ALSPACmother-childpairsat59identifiedbirthweightlociplusDLK1.a,QQplotfromtheQuicktest71analysistestingthebirthweightvariancebetweenheterozygotesandhomozygotesin67,786UKBiobanksamplesisshown.b,QQplotfromtheparent-of-originspecificanalysistestingthebirthweightvariancebetweenmaternallytransmittedandpaternallytransmittedallelesin4,908mother-childpairsfromtheALSPACstudyisshown(Methods,SupplementaryTables13and14).Inbothpanels,theblackdotsrepresentleadSNPsat59identifiedbirthweightlociandafurthersub-genome-widesignificantsignalforbirthweightnearDLK1(rs6575803;P=5.6x10-8).ThegreylinesrepresentexpectedPvaluesandtheir95%confidenceintervalsunderthenulldistributionforthe60SNPs.ExtendedData10|Summaryofpreviouslyreportedlociforsystolicbloodpressure(SBP,a),coronaryarterydisease(CAD,b,e),type2diabetes(T2D,c,f)andadultheight(d)andtheireffectonbirthweight.a-d,Effectsizes(leftyaxis)ofpreviouslyreported30SBPloci14,15,45CADloci16,84T2Dloci23and422adultheightloci24areplottedagainstchangesinbirthweightz-score(xaxis)pertraitraisingallele.Effectsizesarealignedtothetrait-raisingallele.ThecolourofeachdotindicatesbirthweightassociationPvalue:red,P<5×10−8;orange,5×10−8≤P<0.001;yellow,0.001≤P<0.01;white,P≥0.01.ThesuperimposedgreyfrequencyhistogramshowsthenumberofSNPs(rightyaxis)ineachcategoryofbirthweighteffectsize.e,45knownCADlociareplottedarrangedintheorderofCADeffectsizefromhighesttolowest,separatingouttheknownSBPlociandf,32knownT2Dlociareplotted,subdividedbypreviouslyreportedcategoriesderivedfromdetailedadult

physiologicaldata27.Allofthebirthweighteffectsizesplottedintheforestplotsarealignedtothetrait(orrisk)-raisingallele.

Genetic studies of birth weight give biological insights ... · Genetic studies of birth weight...

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