Horikoshi, M., Beaumont, R., Day, F., Warrington, N., Kooijman, M., et. al.,on behalf of the Early Growth Genetics (ECG) Consortium, ... Paternoster, L.(2016). Genome-wide associations for birth weight and correlations withadult disease. Nature, 538(7624), 248-252.https://doi.org/10.1038/nature19806

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Genome-wideassociationsforbirthweightandcorrelationswithadultdiseaseMomokoHorikoshi1,2,*,RobinNBeaumont3,*,FelixRDay4,*,NicoleMWarrington5,6,*,MarjoleinNKooijman7,8,9,*,JuanFernandez-Tajes1,*,BjarkeFeenstra10,NatalieRvanZuydam1,2,KyleJGaulton1,11,NielsGrarup12,JonathanPBradfield13,DavidPStrachan14,RuifangLi-Gao15,TarunveerSAhluwalia12,16,17,EskilKreiner16,RicoRueedi18,19,Leo-PekkaLyytikäinen20,21,DianaLCousminer22,23,24,YingWu25,ElisabethThiering26,27,CarolAWang6,ChristianTHave12,Jouke-JanHottenga28,NataliaVilor-Tejedor29,30,31,PeterKJoshi32,EileenTaiHuiBoh33,IoannaNtalla34,35,NiinaPitkänen36,AnubhaMahajan1,ElisabethMvanLeeuwen8,RaimoJoro37,VasilikiLagou1,38,39,MichaelNodzenski40,LouiseADiver41,KrinaTZondervan1,42,MarionaBustamante29,30,31,43,PedroMarques-Vidal44,JosepMMercader45,AmandaJBennett2,NiluferRahmioglu1,DaleRNyholt46,RonaldChingWanMa47,48,49,ClaudiaHaTingTam47,WingHungTam50,CHARGEConsortiumHematologyWorkingGroup,SanthiKGanesh51,FrankJAvanRooij8,SamuelEJones3,Po-RuLoh52,53,KatherineSRuth3,MarcusATuke3,JessicaTyrrell3,54,AndrewRWood3,HaniehYaghootkar3,DeniseMScholtens40,LaviniaPaternoster55,56,IngaProkopenko1,57,PeterKovacs58,MustafaAtalay37,SaraMWillems8,KalliopePanoutsopoulou59,XuWang33,LisbethCarstensen10,FrankGeller10,KatharinaESchraut32,MarioMurcia31,60,CatharinaEMvanBeijsterveldt28,GonnekeWillemsen28,EmilVRAppel12,CiliusEFonvig12,61,CaecilieTrier12,61,CarlaMTTiesler26,27,MarieStandl26,ZoltánKutalik19,62,SílviaBonas-Guarch45,DavidMHougaard63,64,FrimanSánchez45,65,DavidTorrents45,66,JohannesWaage16,MadsVHollegaard63,64,ǂ,HugolineGdeHaan15,FritsRRosendaal15,CarolinaMedina-Gomez7,8,67,SusanMRing55,56,GibranHemani55,56,GeorgeMcMahon56,NeilRRobertson1,2,ChristopherJGroves2,ClaudiaLangenberg4,Jian'anLuan4,RobertAScott4,JingHuaZhao4,FrankDMentch13,ScottMMacKenzie41,RebeccaMReynolds68,WilliamLLoweJr69,AnkeTönjes70,MichaelStumvoll58,70,VirpiLindi37,TimoALakka37,71,72,CorneliaMvanDuijn8,WielandKiess73,AntjeKörner58,73,ThorkildIASørensen55,56,74,75,HarriNiinikoski76,77,KatjaPahkala36,78,OlliTRaitakari36,79,EleftheriaZeggini59,GeorgeVDedoussis35,Yik-YingTeo33,80,81,Seang-MeiSaw33,82,MadsMelbye10,83,84,HarryCampbell32,JamesFWilson32,85,MartineVrijheid29,30,31,EcoJCNdeGeus28,86,DorretIBoomsma28,HajaNKadarmideen87,Jens-ChristianHolm12,61,TorbenHansen12,SylvainSebert88,89,AndrewTHattersley3,LawrenceJBeilin90,JohnPNewnham6,CraigEPennell6,JoachimHeinrich26,91,LindaSAdair92,JudithBBorja93,94,KarenLMohlke25,JohanGEriksson95,96,97,ElisabethEWidén22,MikaKähönen98,99,JormaSViikari100,101,TerhoLehtimäki20,21,PeterVollenweider44,KlausBønnelykke16,HansBisgaard16,DennisOMook-Kanamori15,102,103,AlbertHofman7,8,FernandoRivadeneira7,8,67,AndréGUitterlinden7,8,67,CharlottaPisinger104,OlufPedersen12,ChristinePower105,ElinaHyppönen105,106,107,NicholasJWareham4,HakonHakonarson13,23,108,EleanorDavies41,BrianRWalker68,VincentWVJaddoe7,8,9,Marjo-RiittaJarvelin88,89,109,110,StruanFAGrant13,23,108,111,AllanAVaag83,112,DebbieALawlor55,56,TimothyMFrayling3,GeorgeDaveySmith55,56,AndrewPMorris1,113,114,§,KenKOng4,115,§,JanineFFelix7,8,9,§,NicholasJTimpson55,56,§,JohnRBPerry4,§,DavidMEvans5,55,56,§,MarkIMcCarthy1,2,116,§,RachelMFreathy3,55,§,onbehalfoftheEarlyGrowthGenetics(EGG)Consortium

1. 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.

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7. TheGenerationRStudyGroup,ErasmusMC,UniversityMedicalCenterRotterdam,theNetherlands.

8. DepartmentofEpidemiology,ErasmusMC,UniversityMedicalCenterRotterdam,theNetherlands.

9. DepartmentofPediatrics,ErasmusMC,UniversityMedicalCenterRotterdam,theNetherlands.10. DepartmentofEpidemiologyResearch,StatensSerumInstitute,Copenhagen,Denmark.11. DepartmentofPediatrics,UniversityofCaliforniaSanDiego,LaJolla,California,USA.12. TheNovoNordiskFoundationCenterforBasicMetabolicResearch,SectionofMetabolic

Genetics,FacultyofHealthandMedicalSciences,UniversityofCopenhagen,Copenhagen,Denmark.

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

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

15. DepartmentofClinicalEpidemiology,LeidenUniversityMedicalCenter,Leiden,theNetherlands.

16. COPSAC,CopenhagenProspectiveStudiesonAsthmainChildhood,HerlevandGentofteHospital,UniversityofCopenhagen,Copenhagen,Denmark.

17. StenoDiabetesCenter,Gentofte,Denmark.18. DepartmentofMedicalGenetics,UniversityofLausanne,Lausanne,Switzerland.19. SwissInstituteofBioinformatics,Lausanne,Switzerland.20. DepartmentofClinicalChemistry,FimlabLaboratories,Tampere,Finland.21. DepartmentofClinicalChemistry,UniversityofTampereSchoolofMedicine,Tampere,Finland.22. InstituteforMolecularMedicine,Finland(FIMM),UniversityofHelsinki,Helsinki,Finland.23. DivisionofHumanGenetics,TheChildren’sHospitalofPhiladelphia,Philadelphia,Pennsylvania,

USA.24. DepartmentofGenetics,PerelmanSchoolofMedicine,UniversityofPennsylvania,Philadelphia,

Pennsylvania,USA.25. DepartmentofGenetics,UniversityofNorthCarolina,ChapelHill,NC,USA.26. InstituteofEpidemiologyI,HelmholtzZentrumMünchen-GermanResearchCenterfor

EnvironmentalHealth,Neuherberg,Germany.27. DivisionofMetabolicandNutritionalMedicine,Dr.vonHaunerChildren'sHospital,Universityof

MunichMedicalCenter,Munich,Germany.28. NetherlandsTwinRegister,DepartmentofBiologicalPsychology,VUUniversity,Amsterdam,

theNetherlands.29. ISGlobal,CentreforResearchinEnvironmentalEpidemiology(CREAL),Barcelona,Spain.30. UniversitatPompeuFabra(UPF),Barcelona,Spain.31. CIBERdeEpidemiologíaySaludPública(CIBERESP),Spain.32. UsherInstituteforPopulationHealthSciencesandInformatics,UniversityofEdinburgh,

Edinburgh,Scotland,UK.33. SawSweeHockSchoolofPublicHealth,NationalUniversityofSingapore,NationalUniversity

HealthSystem,Singapore,Singapore.34. WilliamHarveyResearchInstitute,BartsandtheLondonSchoolofMedicineandDentistry,

QueenMaryUniversityofLondon,London,UK.35. DepartmentofNutritionandDietetics,SchoolofHealthScienceandEducation,Harokopio

University,Athens,Greece.36. ResearchCentreofAppliedandPreventiveCardiovascularMedicine,UniversityofTurku,Turku,

Finland.37. InstituteofBiomedicine,Physiology,UniversityofEasternFinland,Kuopio,Finland.38. KUL–UniversityofLeuven,DepartmentofNeurosciences,Leuven,Belgium.39. TranslationalImmunologyLaboratory,VIB,Leuven,Belgium.

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40. DepartmentofPreventiveMedicine,DivisionofBiostatistics,FeinbergSchoolofMedicine,NorthwesternUniversity,Chicago,USA.

41. InstituteofCardiovascular&MedicalSciences,CollegeofMedical,VeterinaryandLifeSciences,UniversityofGlasgow,Glasgow,UK.

42. EndometriosisCaReCentre,NuffieldDepartmentofObstetrics&Gynaecology,UniversityofOxford,Oxford,UK.

43. CenterforGenomicRegulation(CRG),Barcelona,Spain.44. DepartmentofInternalMedicine,InternalMedicine,LausanneUniversityHospital(CHUV),

Lausanne,Switzerland.45. JointBSC-CRG-IRBResearchPrograminComputationalBiology,BarcelonaSupercomputing

Center,Barcelona,Spain.46. InstituteofHealthandBiomedicalInnovation,QueenslandUniversityofTechnology,

Queensland,Australia.47. DepartmentofMedicineandTherapeutics,TheChineseUniversityofHongKong,HongKong,

HongKong,China.48. LiKaShingInstituteofHealthSciences,TheChineseUniversityofHongKong,HongKong,Hong

Kong,China.49. HongKongInstituteofDiabetesandObesity,TheChineseUniversityofHongKong,HongKong,

China.50. DepartmentofObstetricsandGynaecology,TheChineseUniversityofHongKong,HongKong,

HongKong,China.51. CardiovascularMedicine,DepartmentofInternalMedicine,UniversityofMichigan,AnnArbor,

Michigan,USA.52. DepartmentofEpidemiology,HarvardT.H.ChanSchoolofPublicHealth,Boston,

Massachusetts,USA.53. PrograminMedicalandPopulationGenetics,BroadInstituteofHarvardandMIT,Cambridge,

Massachusetts,USA.54. EuropeanCentreforEnvironmentandHumanHealth,UniversityofExeter,Truro,UK.55. MedicalResearchCouncilIntegrativeEpidemiologyUnitattheUniversityofBristol,Bristol,UK.56. SchoolofSocialandCommunityMedicine,UniversityofBristol,Bristol,UK.57. DepartmentofGenomicsofCommonDisease,SchoolofPublicHealth,ImperialCollegeLondon,

London,UK.58. IFBAdiposityDiseases,UniversityofLeipzig,Leipzig,Germany.59. WellcomeTrustSangerInstitute,Hinxton,Cambridgeshire,UK.60. FISABIO–UniversitatJaumeI–UniversitatdeValència,JointResearchUnitofEpidemiologyand

EnvironmentalHealth,Valencia,Spain.61. TheChildren'sObesityClinic,DepartmentofPediatrics,CopenhagenUniversityHospital

Holbæk,Holbæk,Denmark.62. InstituteofSocialandPreventiveMedicine,LausanneUniversityHospital(CHUV),Lausanne,

Switzerland.63. DanishCenterforNeonatalScreening,StatensSerumInstitute,Copenhagen,Denmark.64. DepartmentforCongenitalDisorders,StatensSerumInstitute,Copenhagen,Denmark.65. ComputerSciencesDepartment,BarcelonaSupercomputingCenter,Barcelona,Spain.66. InstitucióCatalanadeRecercaiEstudisAvançats(ICREA),Barcelona,Spain.67. DepartmentofInternalMedicine,ErasmusMC,UniversityMedicalCenterRotterdam,the

Netherlands.68. BHFCentreforCardiovascularScience,UniversityofEdinburgh,Queen'sMedicalResearch

Institute,Edinburgh,Scotland,UK.69. DepartmentofMedicine,DivisionofEndocrinology,Metabolism,andMolecularMedicine,

FeinbergSchoolofMedicine,NorthwesternUniversity,Chicago,USA.70. MedicalDepartment,UniversityofLeipzig,Leipzig,Germany.

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71. DepartmentofClinicalPhysiologyandNuclearMedicine,KuopioUniversityHospital,Kuopio,Finland.

72. KuopioResearchInstituteofExerciseMedicine,Kuopio,Finland.73. PediatricResearchCenter,DepartmentofWomen´s&ChildHealth,UniversityofLeipzig,

Leipzig,Germany.74. NovoNordiskFoundationCenterforBasicMetabolicResearchandDepartmentofPublic

Health,FacultyofHealthandMedicalSciences,UniversityofCopenhagen,Copenhagen,Denmark.

75. InstituteofPreventiveMedicine,BispebjergandFrederiksbergHospital,TheCapitalRegion,Copenhagen,Denmark.

76. DepartmentofPediatrics,TurkuUniversityHospital,Turku,Finland.77. DepartmentofPhysiology,UniversityofTurku,Turku,Finland.78. PaavoNurmiCentre,SportsandExerciseMedicineUnit,DepartmentofPhysicalActivityand

Health,Turku,Finland.79. DepartmentofClinicalPhysiologyandNuclearMedicine,TurkuUniversityHospital,Turku,

Finland.80. DepartmentofStatisticsandAppliedProbability,NationalUniversityofSingapore,Singapore,

Singapore.81. LifeSciencesInstitute,NationalUniversityofSingapore,Singapore,Singapore.82. SingaporeEyeResearchInstitute,Singapore,Singapore.83. DepartmentofClinicalMedicine,CopenhagenUniversity,Copenhagen,Denmark.84. DepartmentofMedicine,StanfordSchoolofMedicine,Stanford,California,USA.85. MRCHumanGeneticsUnit,InstituteofGeneticsandMolecularMedicine,Universityof

Edinburgh,Edinburgh,Scotland,UK.86. EMGOInstituteforHealthandCareResearch,VUUniversityandVUUniversityMedicalCenter,

Amsterdam,theNetherlands.87. DepartmentofLargeAnimalSciences,FacultyofHealthandMedicalSciences,Universityof

Copenhagen,Copenhagen,Denmark.88. CenterforLifeCourseHealthResearch,FacultyofMedicine,UniversityofOulu,Oulu,Finland.89. BiocenterOulu,UniversityofOulu,Finland.90. SchoolofMedicineandPharmacology,RoyalPerthHospitalUnit,TheUniversityofWestern

Australia,Perth,Australia.91. InstituteandOutpatientClinicforOccupational,SocialandEnvironmentalMedicine,InnerCity

Clinic,UniversityHospitalMunich,LudwigMaximilianUniversityofMunich,Munich,Germany.92. DepartmentofNutrition,UniversityofNorthCarolina,ChapelHill,NC,USA.93. USC-OfficeofPopulationStudiesFoundation,Inc.,UniversityofSanCarlos,CebuCity,

Philippines.94. DepartmentofNutritionandDietetics,UniversityofSanCarlos,CebuCity,Philippines.95. NationalInstituteforHealthandWelfare,Helsinki,Finland.96. DepartmentofGeneralPracticeandPrimaryHealthCare,UniversityofHelsinkiandHelsinki

UniversityHospital,Helsinki,Finland.97. FolkhälsanResearchCenter,Helsinki,Finland.98. DepartmentofClinicalPhysiology,TampereUniversityHopital,Tampere,Finland.99. DepartmentofClinicalPhysiology,UniversityofTampereSchoolofMedicine,Tampere,Finland.100.DivisionofMedicine,TurkuUniversityHospital,Turku,Finland.101.DepartmentofMedicine,UniversityofTurku,Turku,Finland.102.DepartmentofPublicHealthandPrimaryCare,LeidenUniversityMedicalCenter,Leiden,the

Netherlands.103.EpidemiologySection,BESCDepartment,KingFaisalSpecialistHospitalandResearchCentre,

Riyadh,SaudiArabia.

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

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

106.CentreforPopulationHealthResearch,SchoolofHealthSciences,andSansomInstitute,UniversityofSouthAustralia,Adelaide,Australia.

107.SouthAustralianHealthandMedicalResearchInstitute,Adelaide,Australia.108.DepartmentofPediatrics,PerelmanSchoolofMedicine,UniversityofPennsylvania,

Philadelphia,Pennsylvania,USA.109.DepartmentofEpidemiologyandBiostatistics,MRC–PHECentreforEnvironment&Health,

SchoolofPublicHealth,ImperialCollegeLondon,London,UK.110.UnitofPrimaryCare,OuluUniversityHospital,Oulu,Finland.111.DivisionofEndocrinology,TheChildren’sHospitalofPhiladelphia,Philadelphia,Pennsylvania,

USA.112.DepartmentofEndocrinology,Rigshospitalet,Copenhagen,Denmark.113.DepartmentofBiostatistics,UniversityofLiverpool,Liverpool,UK.114.EstonianGenomeCenter,UniversityofTartu,Tartu,Estonia.115.DepartmentofPaediatrics,UniversityofCambridge,Cambridge,UK.116.OxfordNationalInstituteforHealthResearch(NIHR)BiomedicalResearchCentre,Churchill

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

6

Birthweight(BW)isinfluencedbybothfoetalandmaternalfactorsandinobservationalstudiesis1reproduciblyassociatedwithfutureriskofadultmetabolicdiseasesincludingtype2diabetes2(T2D)andcardiovasculardisease1.Theselifecourseassociationshaveoftenbeenattributedtothe3impactofanadverseearlylifeenvironment.Weperformedamulti-ancestrygenome-wide4associationstudy(GWAS)meta-analysisofBWin153,781individuals,identifying60lociwhere5foetalgenotypewasassociatedwithBW(P<5x10-8).Overall,~15%ofvarianceinBWcouldbe6capturedbyassaysoffoetalgeneticvariation.Usinggeneticassociationalone,wefoundstrong7inversegeneticcorrelationsbetweenBWandsystolicbloodpressure(rg=-0.22,P=5.5x10-13),T2D8(rg=-0.27,P=1.1x10-6)andcoronaryarterydisease(rg=-0.30,P=6.5x10-9)and,inlargecohortdata9sets,demonstratedthatgeneticfactorswerethemajorcontributortothenegativecovariance10betweenBWandfuturecardiometabolicrisk.Pathwayanalysesindicatedthattheprotein11productsofgeneswithinBW-associatedregionswereenrichedfordiverseprocessesincluding12insulinsignalling,glucosehomeostasis,glycogenbiosynthesisandchromatinremodelling.There13wasalsoenrichmentofassociationswithBWinknownimprintedregions(P=1.9x10-4).Wehave14demonstratedthatlifecourseassociationsbetweenearlygrowthphenotypesandadult15cardiometabolicdiseaseareinparttheresultofsharedgeneticeffectsandhavehighlightedsome16ofthepathwaysthroughwhichthesecausalgeneticeffectsaremediated.1718WecombinedGWASdataforBWin153,781individualsrepresentingmultipleancestriesfrom3719studiesacrossthreecomponents(ExtendedDataFig.1andSupplementaryTable1):(i)75,89120individualsofEuropeanancestryfrom30studies;(ii)67,786individualsofEuropeanancestryfrom21theUKBiobank;and(iii)10,104individualsofdiverseancestries(AfricanAmerican,Chinese,Filipino,22Surinamese,TurkishandMoroccan)fromsixstudies.Withineachstudy,BWwasz-score23transformedseparatelyinmalesandfemalesafterexcludingnon-singletonsandprematurebirths24andadjustingforgestationalagewhereavailable.Genotypeswereimputedusingreferencepanels25fromthe1000Genomes(1000G)2orcombined1000GandUK10KProject3(SupplementaryTable2).26WeperformedqualitycontrolassessmentstoconfirmthatthedistributionofBWwasconsistent27acrossstudies,irrespectiveofthedatacollectionprotocol,andconfirmedthatself-reportedBWin28UKBiobankshowedgeneticandphenotypicassociationsconsistentwiththoseseenformeasured29BWinotherstudies4(Methods).3031Weidentified60loci(59autosomal)associatedwithBWatgenome-widesignificance(P<5x10-8)in32eithertheEuropeanancestryortrans-ancestrymeta-analyses(ExtendedDataFig.2a,Extended33DataTable1aandSupplementaryData;Methods).AtleadSNPs,weobservednoheterogeneityin34alleliceffectsbetweenthethreestudycomponents(Cochran’sQstatisticP>0.00083)35(SupplementaryTable3).Fifty-threeoftheselociwerenovelinthattheleadSNPmapped>2Mb36awayfrom,andwasstatisticallyindependent(EURr2<0.05)of,thesevenpreviously-reportedBW37signals5,allofwhichwereconfirmedinthislargeranalysis(SupplementaryTable4).Approximate38conditionalanalysisintheEuropeanancestrydataindicatedthatthreeofthesenovelloci(near39ZBTB7B,HMGA1andPTCH1)harbouredmultipledistinctassociationsignalsattaininggenome-wide40significance(Methods;SupplementaryTable5andExtendedDataFig.3).4142Theleadvariantsformostsignalsmappedtonon-codingsequence,andatonlytwoloci,ADRB143(rs7076938;r2=0.99withADRB1G389R)andNRIP1(rs2229742,R448G)didtheassociationdata44pointtolikelycausalnon-synonymouscodingvariants(SupplementaryTable6;Methods).Lead45SNPsforallbuttwoloci(thosemappingnearYKT6-GCKandSUZ12P1-CRLF3)werecommon(minor46allelefrequency(MAF)≥5%)withindividuallymodesteffectsonBW(β=0.020-0.053standard47deviations(SD)perallele,equivalentto10-26g).Thiswasdespitemuchimprovedcoverageoflow-48frequencyvariantsinthisstudy(comparedtopreviousHapMap2imputedmeta-analyses5)49reflectingimputationfromlarger,andmorecomplete,referencepanels(ExtendedDataTable1b).50Indeed,allbutfiveofthecommonvariantassociationsignalsweretaggedbyvariants(EURr2>0.6)in51

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theHapMap2referencepanel(SupplementaryTables4,5),indicatingthatmostofthenovel52discoveryinthepresentstudywasdrivenbyincreasedsamplesize5.Fine-mappinganalysisyielded5314regionswithinwhichfewerthantenvariantscontributedtothelocus-specificcrediblesetthat54accountedfor>99%oftheposteriorprobabilityofassociation(Methods;SupplementaryTable7).55ThegreatestrefinementwasatYKT6-GCK,wherethecrediblesetincludedonlythelowfrequency56variantrs138715366,whichmapsintronictoYKT6.Thesecrediblesetvariantscollectivelyshowed57enrichmentforoverlapwithDNaseIhypersensitivitysites,particularlythosegenerated,byENCODE,58fromfoetal(4.2-fold,95%CI[1.8-10.7])andneonataltissues(4.9[1.8-11.0])(SupplementaryFig.159andSupplementaryTable8;Methods).6061Incombination,the62distinctgenome-widesignificantsignalsatthe59autosomallociexplained622.0%(standarderror(SE)1.1%)ofvarianceinBW(SupplementaryTable9;Methods),similarin63magnitudetothatattributabletosexormaternalbodymassindex(BMI)5.However,thevariancein64BWcapturedcollectivelybyallautosomalgenotypedvariantsonthearraywasconsiderablylarger,65estimatedat15.1%(SE=0.9)inUKBiobank(Methods).Thesefiguresareconsistentwithalongtailof66geneticvariantsofsmallereffectscontributingtovariationinBW.6768AssociationsbetweenfoetalgenotypeandBWcouldresultfromindirecteffectsofthematernal69genotypeinfluencingBWviatheintrauterineenvironmentgiventhecorrelation(r≈0.5)between70maternalandfoetalgenotype.However,twolinesofevidenceindicatedthatvariationinthefoetal71genomewasthepredominantdriveroftheBWassociations.First,ananalysisoftheglobal72contributionofmaternalvs.foetalgeneticvariation,usingamaternal-GCTAmodel6(Methods)73appliedto4,382mother-childpairs,estimatedthatthechild’sgenotype(σC

2=0.24,SE=0.11)makesa74largercontributiontoBWvariancethaneitherthemother’sgenotype(σM

2=0.04,SE=0.10),orthe75covariancebetweenthetwo(σCM=0.04,SE=0.08).Second,whenwecomparedthepointestimatesof76theBWeffectsizedependentonmaternalgenotypeateachofthe60loci(asmeasuredinupto7768,254women7)withthosedependentonfoetalgenotype(usingEuropeanancestrydatafrom78143,677individualsinthepresentstudy),foetalvariationhadgreaterimpactthanmaternalat93%79ofloci(55/60;binomialP=1x10-11)(SupplementaryTable10,ExtendedDataFigs4,5;Methods).80Powertofurtherdisentanglematernalandfoetalcontributionsusinganalysesoffoetalgenotype81conditionalonmaternalgenotypewasconstrainedbythelimitedsamplesizeavailable(n=12,90982mother-childpairs)(SupplementaryTable11).8384Collectively,theseanalysesprovidecompellingevidencethatfoetalgenotypehasasubstantial85impactonearlygrowth,asmeasuredbyBW.Wesoughttousethesegeneticassociationsto86understandthecausalrelationshipsunderlyingobservedassociationsbetweenBWanddisease,and87tocharacterisetheprocessesresponsible.88 89ToquantifythesharedgeneticcontributiontoBWandotherhealth-relatedtraits,weestimated90theirgeneticcorrelationsusingLDScoreregression8(Methods).BW(inEuropeanancestrysamples)91showedstrongpositivegeneticcorrelationswithanthropometricandobesity-relatedtraitsincluding92birthlength(rg=0.81,P=2.0x10-44),andinadults,height(rg=0.41,P=4.8x10-52),waistcircumference93(rg=0.18,P=3.9x10-10)andBMI(rg=0.11,P=7.3x10-6).Incontrast,BWshowedinversegenetic94correlationswithindicatorsofadversemetabolicandcardiovascularhealthincludingcoronaryartery95disease(CAD,rg=-0.30,P=6.5x10-9),systolicbloodpressure(SBP,rg=-0.22,P=5.5x10-13)andT2D(rg=-960.27,P=1.1x10-6)(Fig.1,SupplementaryTable12andSupplementaryFig.2).Thesecorrelations97betweenBWandadultcardiometabolicphenotypesareofsimilarmagnitude,althoughdirectionally-98opposite,tothereportedgeneticcorrelationsbetweenadultBMIandthosesamecardiometabolic99outcomes8.ThesefindingssupportobservationalassociationsbetweenahistoryofpaternalT2Dand100lowerBW4,andestablishmoregenerallythattheobservedlifecourseassociationsbetweenearly101growthandadultdisease,atleastinpart,reflecttheimpactofsharedgeneticvariantsthatinfluence102

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bothsetsofphenotypes.Inanefforttoestimatetheextentofgeneticcontributiontothese103lifecourseassociations,wefirstfocusedondatafromUKBiobank(n=57,715).Formanyofthetraits104forwhichdatawereavailable,geneticvariationcontributedsubstantiallytothelifecourse105relationshipbetweenBWandadultphenotypes,andinsomecasesappearedtobethemajorsource106ofcovariancebetweenthetraits.Forexample,weestimatedthat85%(95%CI=70%-99%)ofthe107negativecovariancebetweenBWandSBPwasexplainedbysharedgeneticassociationscapturedby108directlygenotypedSNPs(SupplementaryTable13;Methods).Forcontinuouscardiometabolic109measures,includinglipidsandfastingglycaemia,forwhichmeasuresarenotcurrentlyavailablein110UKBiobank,weturnedtotheNorthernFinlandBirthCohort(n=5,009),andobtainedsimilarresults111(SupplementaryTable13).However,theseestimatesarelimited,notonlybywideconfidence112intervals,butalsobytheassumptionofalinearrelationshipbetweenBWandeachofthe113phenotypesandbytheinabilitytoexplicitlymodelmaternalgenotypiceffects.Inotherwords,the114inversegeneticcorrelationsbetweenBWandcardiometabolictraitsmaynotexclusivelyreflect115geneticeffectsmediateddirectlythroughtheoffspring,butalsoeffectsmediatedbymaternal116genotypeactingindirectlyviaperturbationoftheinuteroenvironment.Nevertheless,these117estimatesindicatethatasubstantialproportionofthevarianceincardiometabolicriskthatcovaries118withBWcanbeattributedtotheeffectsofcommongeneticvariation.119120Toelucidatethebiologicalpathwaysandprocessesunderlyingregulationoffoetalgrowth,wefirst121performedgenesetenrichmentanalysisofourBWGWASanalysisusingMAGENTA9(Methods).122Twelvepathwaysreachedstudy-widesignificance(FDR<0.05),includingpathwaysinvolvedin123metabolism(insulinsignalling,glycogenbiosynthesis,cholesterolbiosynthesis),growth(IGF-124signalling,growthhormonepathway)anddevelopment(chromatinremodelling)(ExtendedData125Table2a).Similarpathwaysweredetectedinacomplementaryanalysiswhereweinterrogated126empiricalprotein-proteininteraction(PPI)dataidentifying13PPInetworkmoduleswithmarked(z-127score>5)enrichmentforBW-associationscores(ExtendedDataTable2bandExtendedDataFigs1286a,b;Methods).Theproteinswithinthesemoduleswerethemselvesenrichedfordiverseprocesses129relatedtometabolism,growthanddevelopment(ExtendedDataFigs6a,b).130131WealsoobservedenrichmentofBWassociationsignalsacrossthesetof77imprintedgenesdefined132bytheGenotype-TissueExpression(GTEx)project10(P=1.9x10-4;ExtendedDataTable2aand133SupplementaryTable14).Suchenrichmentisconsistentwiththe“parentalconflict”hypothesis134regardingtheallocationofmaternalresourcestothefoetus11.Althoughtheroleofimprintedgenes135infoetalgrowthisdescribedinanimalmodelsandrarehumandisorders12,ourresultisthefirst136large-scale,systematicdemonstrationoftheircontributiontonormalvariationinBW.Ofthe60137genome-widesignificantloci,two(INS-IGF2,RB1)fallwithin(ornear)imprintedregions(Extended138DataFig.2b),withanoteworthythirdsignalatDLK1(previouslyfoetalantigen-1;P=5.6x10-8).139Parent-of-originspecificanalysestofurtherinvestigatetheseindividualloci(comparing140heterozygotevs.homozygoteBWvariancein57,715unrelatedindividuals,andtestingBW141associationswithpaternalvs.maternalallelesin4,908mother-childpairs;seeMethods)proved,142despitethesesamplesizes,tobeunderpowered(ExtendedDataFig.7andSupplementaryTables14315,16).144145Manyofthegenome-widesignalsforBWdetectedherearealsoestablishedgenome-wide146associationsignalsforawidevarietyofcardiometabolictraits(Fig.2).TheseincludetheBWsignals147nearCDKAL1,ADCY5,HHEX/IDEandANK1(alsogenome-widesignificantforT2D),NT5C2(forblood148pressure(BP),CADandBMI)andADRB1(forBP).Weusedtwoapproachestounderstandwhether149thispatternofadulttraitassociationrepresentedagenericpropertyofBW-associatedloci,or150reflectedheterogeneousmechanismslinkingBWtoadultdisease.151152

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First,weappliedunsupervisedhierarchicalclustering(Methods)tothenon-BWtraitassociation153statisticsforthe60significantBWloci.Theresultantheatmapindicatestheheterogeneityoflocus-154specificeffectsizesacrosstherangeofadulttraits(Fig.2andSupplementaryTable17).For155example,itshowsthattheassociationsbetweenBW-raisingallelesandincreasedadultheightare156concentratedamongstasubsetoflociincludingHHIPandGNA12,andhighlightsparticularlystrong157associationswithlipidtraitsforvariantsattheTRIB1andMAFBloci.158159Second,weconstructedtrait-specific“point-of-contact”(PoC)PPInetworksfromproteins160representedinboththeglobalBWPPInetworkandequivalentPPInetworksgeneratedforeachof161theadulttraits(Methods;ExtendedDataFigs6c-e).WereasonedthatthesePoCPPInetworks162wouldbeenrichedforthespecificproteinsmediatingtheobservedlinksbetweenBWandadult163traits,generatinghypothesesthatareamenabletosubsequentempiricalvalidation.Tohighlight164processesimplicatedinspecificBW-traitassociations,weoverlaidthesePoCPPIwiththe50165pathwaysover-representedintheglobalBWPPInetwork.Theseanalysesrevealed,forexample,166thatproteinsintheWntcanonicalsignallingpathwaywereonlydetectedinthePoCPPInetworkfor167BPtraits.WecanusethesePPIoverlapstohighlightthespecifictranscriptswithinBWGWASloci168thatarelikelytomediatethemechanisticlinks.Forexample,theoverlapbetweentheWntsignalling169pathwayandthePoCPPInetworkfortheintersectionofBWandBP-relatedtraitsimplicatesFZD9as170thelikelyeffectorgeneattheMLXIPLBWlocus(ExtendedDataFig.6dandSupplementaryTable6).171172Wefocusedourmoredetailedinvestigationofthemechanisticlinksbetweenearlygrowthandadult173traitsontwophenotypicareas:arterialBPandT2D/glycaemia.AcrossboththeoverallGWASand174specificallyamongthe60significantBWloci,mostBW-raisingalleleswereassociatedwithreduced175BP(Figs1,2):thestrongestinverseassociationswereseenforthelocinearNT5C2,FES,NRIP1,EBF1176andPTH1R.However,wealsoobservedlocus-specificheterogeneityinthegeneticrelationships177betweenBPandBW:theSBP-raisingalleleatADRB113isassociatedwithhigher,ratherthanlower,178BW(ExtendedDataFig.8a).Whenweconsideredthereciprocalrelationship,i.e.theeffectsonBW179ofBP-raisingallelesat30reportedlociforSBP13,14,therewasanexcessofassociations(5/30with180lowerBWatP<0.05;P=0.0026;ExtendedDataFig.8a).Todissectmaternalandfoetalgenotype181effectsattheseloci,wetestedtheimpactonBWofariskscoregeneratedfromthe30SBPSNPs,182restrictedtotheuntransmittedmaternalhaplotypescore15inasetof5,201mother-childpairs.183Analysisoftheselociindicatedthatmaternalgenotypeeffectsontheintrauterineenvironmentare184likelytocontributetotheinversegeneticcorrelationbetweenSBPandBW(Methods;185SupplementaryTable18),andwasconsistentwiththeresultsofawiderstudyof>30,000women186whichdemonstratedassociationsbetweenamaternalgeneticscoreforSBP(conditionalonfoetal187genotype)andloweroffspringBW16.188189TheBP-raisingallelewiththelargestBW-loweringeffectmapstotheNT5C2locus(indexvariantfor190BW,rs74233809,r2=0.98withindexvariantforBP,rs1119154814)andisalsoassociatedwithlower191adultBMI(r2=0.99withrs1119156017).TheBW-loweringalleleatrs74233809isaproxyfora192recently-describedfunctionalvariantinthenearbyCYP17A1gene(r2=0.92withrs138009835)18.The193CYP17A1geneencodesthecytochromeP450c17αenzyme,CYP1719,whichcatalyseskeystepsin194steroidogenesisthatdeterminethebalancebetweenmineralocorticoid,glucocorticoidand195androgensynthesis.Thisvariantisknowntoaltertranscriptionalefficiencyinvitroandisassociated196withhigherurinarytetrahydroaldosteroneexcretion18.CYP17A1isexpressedinfoetaladrenalglands197andtestesfromearlygestation20aswellasintheplacenta21.Thesedataimplicatevariationin198CYP17A1expressionasacontributortotheobservationalassociationbetweenlowBWandadult199hypertension22.200201Whenweexamined45lociassociatedwithCAD23,theinversegeneticcorrelationbetweenCADand202BWwasconcentratedamongstthefiveCADlociwithprimaryBPassociations.Thissuggeststhat203

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geneticdeterminantsofBPplayaleadingroleinmediatingthelifecourseassociationsbetweenBW204andCAD(ExtendedDataFigs8b,e).205206LDscoreregressionanalysesdemonstratedoverallinversegeneticcorrelationbetweenlowerBW207andelevatedriskofT2D(Fig.1).However,thelocusspecificheatmapindicatesaheterogeneous208patternacrossindividualloci(Fig.2).Toexplorethisfurther,wetestedthe84reportedT2Dloci24for209associationwithBW.SomeT2Driskalleles(suchasatADCY5,CDKAL1andHHEX-IDE)werestrongly210associatedwithlowerBW,whilstothers(e.g.ANK1andMTNR1B)wereassociatedwithhigherBW211(ExtendedDataFig.8c).ThiswasincontrastwiththeBWeffectsof422knownheightloci25212(ExtendedDataFig.8d),whichshowedastrongpositivecorrelationconsistentwiththeoverall213geneticcorrelationbetweenheightandBW,indicatingthatthegrowtheffectsofmanyheightloci214startprenatallyandpersistintoadulthood.215216ThecontrastingassociationsofT2Drisk-alleleswithbothhigherandlowerBWarelikelytoreflect217thedifferentialimpactsacrosslociofvariationinthematernalandfoetalgenomes.Observational218datalinkpaternaldiabeteswithloweroffspringBW4indicatingthattheinheritanceofT2Drisk219allelesbythefoetustends,inlinewiththeLDscoreregressionanalysis,toreducegrowth.These220relationshipsareconsistentwiththepreceptsofthe“foetalinsulinhypothesis”26andreflectthe221potentialforreducedinsulinsecretionand/orsignallingtoleadtobothreducedfoetalgrowthand,222manydecadeslater,enhancedpredispositiontoT2D.Inlinewiththis,theinferredpaternal223transmittedhaplotypescoregeneratedfromthe84T2DriskvariantswasassociatedwithlowerBW224(P=0.045)in5,201mother-childpairs(Methods;SupplementaryTable18).Incontrast,maternal225diabetesisobservationallyassociatedwithhigheroffspringBW4,reflectingtheimpactofmaternal226hyperglycaemiatostimulatefoetalinsulinsecretion.Thecontributionofgenotype-dependent227maternalhyperglycaemiatoBWisinlinewiththeevidence,fromarecentstudy,thatmaternal228genotypescoresforfastingglucoseandT2D(conditionalonfoetalgenotype)werecausally229associatedwithhigheroffspringBW16.Itisalsoconsistentwiththeobservationthatasubsetof230glucose-raisingallelesisassociatedwithhigherBW7.Forexample,theT2D-riskvariantatMTNR1B231(whichalsohasaparticularlymarkedeffectonfastingglucoselevelsinnon-diabeticindivudals27,28)232wasamongstthesubsetofBWloci(5/60)forwhichtheBWeffectattributabletomaternalgenotype233exceededthatassociatedwiththefoetalgenotype(maternal:β=0.048,P=5.1x10-15;foetal:β=0.023,234P=2.9x10-8)(SupplementaryTable10,ExtendedDataFigs4,5).Thus,bothmaternalandfoetal235geneticeffectsconnectBWtolaterT2Drisk,albeitactinginopposingdirections.Whenwe236categorisedT2Dlociusingaclassificationofphysiologicalfunctionderivedfromtheireffectson237relatedglycaemicandanthropometrictraits27,wefoundthatT2D-riskallelesassociatedwithlower238BWwerethosetypicallycharacterisedbyreducedinsulinprocessingandsecretionwithout239detectablechangesinfastingglucose(the“BetaCell”clusterinExtendedDataFig.8f).240241TheYTK6signalatrs138715366isnotable,notonlybecausethegeneticdataindicatesthatasingle242low-frequencynon-codingvariantisdrivingtheassociationsignal(seeabove)butbecauseofthe243proximityofthissignaltoGCK.Rarecodingvariantsinglucokinasearecausalforaformof244monogenichyperglycaemiaandleadtolargereductionsinBWwhenparentalallelesarepassedto245theiroffspring29.Inaddition,commonnon-codingvariantsnearbyareimplicatedinT2D-riskand246fastinghyperglycaemia28.However,thelattervariantsareconditionallyindependentofrs138715366247(SupplementaryTable19)andshownocomparableassociationwithlowerBW.Eitherrs138715366248actsthrougheffectortranscriptsotherthanGCK,ortheimpactofthelow-frequencySNPnearYKT6249onGCKexpressioninvolvestissue-and/ortemporal-specificvariationinregulatoryimpact.250251Inconclusion,wehaveidentified60geneticlociassociatedwithBWandusedthesetogaininsights252intotheaetiologyoffoetalgrowthandintowell-established,butuntilnowpoorlyunderstood,253lifecoursediseaseassociations.Theevidencethattherelationshipbetweenearlygrowthandlater254

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metabolicdiseasehasanappreciablegeneticcomponentcontrastswith,butisnotnecessarily 255incompatiblewith,theemphasisonadverseearlyenvironmentaleventshighlightedbytheFoetal256OriginsHypothesis1.Aswehaveshown,thesegeneticeffectsreflectvariationinboththefoetaland257thematernalgenome:theimpactofthelatterontheoffspring’spredispositiontoadultdisease258couldbemediated,atleastinpart,throughperturbationoftheantenatalandearlylife259environment.Futuremechanisticandgeneticstudiesshouldsupportreconciliationbetweenthese260alternative,butcomplementary,explanationsforthefar-reachinglifecourseassociationsthatexist261betweeneventsinearlylifeandpredispositiontocardiometabolicdiseaseseveraldecadeslater.262263264265

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346347

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FIGURELEGENDS348349Figure1|Genome-widegeneticcorrelationbetweenbirthweightandarangeoftraitsand350diseasesinlaterlife.Geneticcorrelation(rg)andcorrespondingstandarderrorbetweenBWandthe351traitsdisplayedonthexaxisareestimatedusingLDScoreregression8.Thegeneticcorrelation352estimates(rg)arecolourcodedaccordingtotheirintensityanddirection(redforpositiveandblue353forinversecorrelation).WHRadjBMI=waist-hipratioadjustedforbodymassindex,HOMA-354B/IR=homeostaticmodelassessmentofbeta-cellfunction/insulinresistance,HbA1c=Hemoglobin355A1c,BMD=bonemineraldensity,ADHD=attentiondeficithyperactivitydisorder.SeeSupplementary356Table12forreferencesforeachofthetraitsanddiseasesdisplayed.357358Figure2|Hierarchicalclusteringofbirthweightlocibasedonsimilarityofoverlapwithadult359diseases,metabolicandanthropometrictraits.FortheleadSNPateachBWlocus(x-axis),z-scores360(alignedtoBW-raisingallele)wereobtainedfrompubliclyavailableGWASforvarioustraits(y-axis;361seeSupplementaryTable17).Apositivez-score(red)indicatesapositiveassociationbetweenthe362BW-raisingalleleandtheoutcometrait,whileanegativez-score(blue)indicatesaninverse363association.BWlociandtraitsareclusteredaccordingtotheEuclideandistanceamongstz-scores364(seeMethods).SquaresareoutlinedwithasolidblacklineiftheBWlocusissignificantly(P<5x10-8)365associatedwiththetraitinpubliclyavailableGWAS,orwithadashedlineifreportedsignificant366elsewhere.WHRadjBMI=waist-hipratioadjustedforbodymassindex.367368

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METHODS369370Ethicsstatement.Allhumanresearchwasapprovedbytherelevantinstitutionalreviewboardsand371conductedaccordingtotheDeclarationofHelsinki.Allparticipantsprovidedwritteninformed372consent.EthicalapprovalforthestudywasobtainedfromtheALSPACEthicsandLawCommittee373andtheLocalResearchEthicsCommittees.374375Study-levelanalyses.Withineachstudy,BWwascollectedfromavarietyofsources,including376measurementsatbirthbymedicalpractitioners,obstetricrecords,medicalregisters,interviewswith377themotherandself-reportasadults(SupplementaryTable1).BWwasz-scoretransformed,378separatelyinmalesandfemales.IndividualswithextremeBW(>5SDfromthesex-specificstudy379mean),monozygoticorpolyzygoticsiblings,orpretermbirths(gestationalage<37weeks,wherethis380informationwasavailable)wereexcludedfromdownstreamassociationanalyses(Supplementary381Table1).382

Withineachstudy,stringentqualitycontroloftheGWASgenotypescaffoldwasundertaken,383priortoimputation(SupplementaryTable2).Eachscaffoldwasthenpre-phasedandimputed30,31384uptoreferencepanelsfromthe1000G2or1000GandUK10KProject3(SupplementaryTable2).385AssociationofBWwitheachvariantpassingestablishedGWASqualitycontrolfilters32wastestedin386alinearregressionframework,underanadditivemodelforthealleliceffect,afteradjustmentfor387study-specificcovariates,includinggestationalage,whereavailable(SupplementaryTable2).388Wherenecessary,populationstructurewasaccountedforbyadjustmentforaxesofgenetic389variationfromprincipalcomponentsanalysis33andsubsequentgenomiccontrolcorrection34,or390inclusionofageneticrelationshipmatrixinamixedmodel35(SupplementaryTable2). Wecalculated391thegenomiccontrolinflationfactor(λ)ineachstudytoconfirmthatstudy-levelpopulationstructure392wasaccountedforpriortometa-analysis.393394Preparation,qualitycontrolandgeneticanalysisinUKBiobanksamples.UKBiobankphenotype395datawereavailablefor502,655participants36.AllparticipantsintheUKBiobankwereaskedtorecall396theirBW,ofwhich279,971didsoateitherthebaselineorfollow-upassessmentvisit.Ofthese,3977,686participantsreportedbeingpartofmultiplebirthsandwereexcludedfromdownstream398analyses.Ancestrychecks,basedonself-reportedancestry,resultedintheexclusionof8,998399additionalparticipantsreportednottobewhiteEuropean.OfthoseindividualsreportingBWat400baselineandfollow-upassessments,393wereexcludedbecausethetworeportedvaluesdifferedby401morethan0.5kg.Forthosereportingdifferentvalues(≤0.5kg)betweenbaselineandfollow-up,we402tookthebaselinemeasureforwardfordownstreamanalyses.Wethenexcluded36,716individuals403reportingvalues<2.5kgor>4.5kgasimplausibleforlivetermbirthsbefore1970.Intotal226,178404participantshaddatarelatingtoBWthatmatchedtheseinclusioncriteria.405

GenotypedatafromtheMay2015releasewereavailableforasubsetof152,249406participantsfromUKBiobank.InadditiontothequalitycontrolmetricsperformedcentrallybyUK407Biobank,wedefinedasubsetof“whiteEuropean”ancestrysamplesusingaK-means(K=4)408clusteringapproachbasedonthefirstfourgeneticallydeterminedprincipalcomponents.A409maximumof67,786individuals(40,425femalesand27,361males)withgenotypeandvalidBW410measureswereavailablefordownstreamanalyses.WetestedforassociationwithBW,assumingan411additivealleliceffect,inalinearmixedmodelimplementedinBOLT-LMM37toaccountforcryptic412populationstructureandrelatedness.Genotypingarraywasincludedasabinarycovariateinall413models.Totalchipheritability(i.e.thevarianceexplainedbyallautosomalpolymorphicgenotyped414SNPspassingqualitycontrol)wascalculatedusingRestrictedMaximumLikelihood(REML)415implementedinBOLT-LMM37.WeadditionallyanalysedtheassociationbetweenBWanddirectly416genotypedSNPsontheXchromosome:forthisanalysis,weused57,715unrelatedindividualswith417BWavailableandidentifiedbyUKBiobankaswhiteBritish.WeexcludedSNPswithevidenceof418deviationfromHardy-WeinbergEquilibrium(P<1x10-6),MAF<0.01oroverallmissingrate>0.015,419

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resultingin19,423SNPsforanalysisinPlinkv1.07(http://pngu.mgh.harvard.edu/purcell/plink/)38,420withthefirstfiveancestryprincipalcomponentsascovariates.421

InboththefullUKBiobanksampleandourrefinedsample,weobservedthatBWwas422associatedwithsex,yearofbirthandmaternalsmoking(P<0.0015,allintheexpecteddirections),423confirmingmorecomprehensivepreviousvalidationofself-reportedBW4.Weadditionallyverified424thatBWassociationswithleadSNPsatsevenestablishedloci5basedonself-reportinUKBiobank425wereconsistentwiththosepreviouslypublished.426427Europeanancestrymeta-analysis.TheEuropeanancestrymeta-analysisconsistedoftwo428components:(i)75,891individualsfrom30GWASfromEurope,USAandAustralia;and(ii)67,786429individualsofwhiteEuropeanoriginfromUKBiobank.Inthefirstcomponent,wecombinedsex-430specificBWassociationsummarystatisticsacrossstudiesinafixed-effectsmeta-analysis,431implementedinGWAMA39andappliedasecondroundofgenomiccontrol34(λGC=1.001).432Subsequently,wecombinedassociationsummarystatisticsfromthiscomponentwithUKBiobankin433aEuropeanancestryfixed-effectsmeta-analysis,implementedinGWAMA39.VariantsfailingGWAS434qualitycontrolfiltersinUKBiobank,reportedinlessthan50%ofthetotalsamplesizeinthefirst435component,orwithMAF<0.1%,wereexcludedfromtheEuropeanancestrymeta-analysis.We436aggregatedX-ChromosomeassociationsummarystatisticsfromUKBiobank(19,423SNPs)with437correspondingstatisticsfromtheEuropeanGWAScomponentusingfixedeffectsP-valuebased438meta-analysisinMETAL40(maxN=99,152).439

Wewereconcernedthatself-reportedBWasadultsinUKBiobankwouldnotbecomparable440withthatobtainedfrommorestringentcollectionmethodsusedinotherEuropeanancestryGWAS.441Inaddition,UKBiobanklackedinformationongestationalageforadjustment,whichcouldhavean442impactondifferenceinstrengthofassociationcomparedtotheresultsobtainedfromother443EuropeanancestryGWAS.However,weobservednoevidenceofheterogeneityinBWalleliceffects444atleadSNPsbetweenthetwocomponentsofEuropeanancestrymeta-analysis,usingCochran’sQ445statistic41,implementedinGWAMA39,afterBonferronicorrection(P>0.00083)(Supplementary446Table3).WetestedforheterogeneityinalleliceffectsbetweenstudieswithintheEuropean447componentusingCochran’sQ.Atlocidemonstratingevidenceofheterogeneity,weconfirmedthat448associationsignalswerenotbeingdrivenbyoutlyingstudies byvisualinspectionofforestplots.We449performedsensitivityanalysestoassesstheimpactofcovariateadjustment(gestationalageand450populationstructure)onheterogeneity.451

Wewerealsoconcernedthatoverlapofindividuals(duplicatedorrelated)betweenthetwo452componentsoftheEuropeanancestrymeta-analysismightleadtofalsepositiveassociationsignals.453WeperformedbivariateLDScoreregression8usingthetwocomponentsoftheEuropeanancestry454meta-analysisandobservedageneticcovarianceinterceptof0.0156(SE0.0058),indicatinga455maximumof1,119duplicateindividuals.UnivariateLDScoreregression8oftheEuropeanancestry456meta-analysisestimatedtheinterceptas1.0426,whichmayindicatepopulationstructureor457relatednessthatisnotadequatelyaccountedforintheanalysis.Toassesstheimpactofthisinflation458ontheEuropeanancestrymeta-analysis,weexpandedthestandarderrorsofBWalleliceffectsize459estimatesandre-calculatedassociationP-values.Onthebasisofthisadjustedanalysis,theleadSNP460onlyatMTNR1Bdroppedbelowgenome-widesignificance(rs10830963,P=5.5x10-8).461462Trans-ancestrymeta-analysis.Thetrans-ancestrymeta-analysiscombinedthetwoEuropean463ancestrycomponentswithanadditional10,104individualsfromsixGWASfromdiverseancestry464groups:AfricanAmerican,Chinese,Filipino,Surinamese,TurkishandMoroccan.WithineachGWAS,465wefirstcombinedsex-specificBWassociationsummarystatisticsinafixed-effectsmeta-analysis,466implementedinGWAMA39andappliedasecondroundofgenomiccontrol34.Subsequently,we467combinedassociationsummarystatisticsfromthesixnon-EuropeanGWASandthetwoEuropean468ancestrycomponentsinatrans-ancestryfixed-effectsmeta-analysis,implementedinGWAMA39.469VariantsfailingGWASqualitycontrolfiltersinUKBiobank,reportedinlessthan50%ofthetotal470

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samplesizeinthefirstcomponent,orwithMAF<0.1%,wereexcludedfromthetrans-ancestrymeta-471analysis.WetestedforheterogeneityinalleliceffectsbetweenancestriesusingCochran’sQ41.472473Approximateconditionalanalysis.WesearchedformultipledistinctBWassociationsignalsineach474oftheestablishedandnovelloci,definedas1Mbup-anddown-streamoftheleadSNPfromthe475trans-ancestrymeta-analysis,throughapproximateconditionalanalysis.WeappliedGCTA42to476identify“indexSNPs”fordistinctassociationsignalsattaininggenome-widesignificance(P<5x10-8)in477theEuropeanancestrymeta-analysisusingareferencesampleof5,000individualsofwhiteBritish478origin,randomlyselectedfromUKBiobank,toapproximatepatternsoflinkagedisequilibrium(LD)479betweenvariantsintheseregions.Notethatweperformedapproximateconditioningonthebasisof480onlytheEuropeanancestrymeta-analysisbecauseGCTAcannotaccommodateLDvariationbetween481diversepopulations.482483PrioritisingcandidategenesineachBWlocus.Wecombinedanumberofapproachestoprioritise484themostlikelycandidategene(s)ineachBWlocus.Expressionquantitativetraitloci(eQTLs)were485obtainedfromtheGenotypeTissueExpression(GTEx)Project43,theGEUVADISProject44andeleven486otherstudies45-55usingHaploRegv456.WeinterrogatedcodingvariantsforeachBWleadSNPandits487proxies(EURr2>0.8)usingEnsembl57andHaploReg.Theirlikelyfunctionalconsequenceswere488predictedbySIFT58andPolyPhen259.Biologicalcandidacywasassessedbypresenceinsignificantly489enrichedgenesetpathwaysfromMAGENTAanalyses(seebelowfordetails).Weextractedallgenes490within300kbofallleadBWSNPsandsearchedforconnectivitybetweenanygenesusingSTRING60.491IftwoormoregenesbetweentwoseparateBWlociwereconnected,theyweregivenanincreased492priorforbothbeingplausiblecandidates.Wealsoappliedprotein-proteininteraction(PPI)analysis493(seebelowfordetails)toallgeneswithin300kbofeachleadBWSNPsandrankedthegenesbased494onthescoreforconnectivitywiththesurroundinggenes.495496Evaluationofimputationqualityoflow-frequencyvariantattheYKT6-GCKlocus.AttheYKT6-GCK497locus,theleadSNP(rs138715366)isoflow-frequencyinEuropeanancestrypopulations498(MAF=0.92%)andevenrarerinotherancestrygroups(MAF=0.23%inAfricanAmericans,otherwise499monomorphic)andisnotpresentintheHapMapreferencepanel61.Toassesstheaccuracyof500imputationforthislow-frequentvariant,wegenotypedrs138715366intheNorthernFinlandBirth501Cohort(NFBC)1966(SupplementaryTable1).Ofthe5,009samplesinthestudy,4,704were502successfullyimputedandgenotyped(orsequenced)forrs138715366.Theoverallconcordancerate503betweenimputedanddirectlyassayedgenotypeswas99.8%andfordirectlyassayedheterozygote504callswas75.0%.505506Fine-mappinganalyses.WesoughttoleverageLDdifferencesbetweenpopulationscontributingto507thetrans-ancestrymeta-analysisandtotakeadvantageoftheimprovedcoverageofcommonand508low-frequencyvariationofferedby1000Gor1000GandUK10Kcombinedimputationtolocalise509variantsdrivingeachdistinctassociationsignalachievinglocus-widesignificance.Foreachdistinct510signal,weusedMANTRA62toconstruct99%crediblesetsofvariants63thattogetheraccountfor99%511oftheposteriorprobabilityofdrivingtheassociation.MANTRAincorporatesapriormodelof512relatednessbetweenstudies,basedonmeanpair-wiseallelefrequencydifferencesacrossloci,to513accountforheterogeneityinalleliceffects(SupplementaryTable3).MANTRAhasbeen514demonstrated,bysimulation,toimprovelocalisationofcausalvariantscomparedwitheithera515fixed-orrandom-effectstrans-ancestrymeta-analysis62,64.516

Forlociwithonlyonesignalofassociation,weusedMANTRAtocombinesummarystatistics517fromthesixnon-EuropeanGWASandthetwoEuropeanancestrycomponents.However,forloci518withmultipledistinctassociationsignals,weusedMANTRAtocombinesummarystatisticsfrom519approximateconditioningforthetwoEuropeancomponents,separatelyforeachsignal.520

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Foreachdistinctsignal,wecalculatedtheposteriorprobabilitythatthejthvariant,πCj,is521drivingtheassociation,givenby522523

𝜋!! =!!!!!,524

525wherethesummationisoverallvariantsmappingwithinthe(conditional)meta-analysisacrossthe526locus.Inthisexpression,ΛjistheBayes’factor(BF)infavourofassociationfromtheMANTRA527analysis.A99%credibleset63wasthenconstructedby:(i)rankingallvariantsaccordingtotheirBF,528Λj;and(ii)includingrankedvariantsuntiltheircumulativeposteriorprobabilityexceeds0.99.529530Genomicannotation.WeusedgenomicannotationsofDNaseIhypersensitivesites(DHS)fromthe531ENCODE65projectandproteincodinggenesfromGENCODE66.Wefilteredcelltypesthatarecancer532celllines(karyotype‘cancer’fromhttps://genome.ucsc.edu/ENCODE/cellTypes.html),andmerged533datafrommultiplesamplesfromthesamecelltype.Thisresultedin128DHScell-typeannotations,534aswellas4gene-basedannotations(codingexon,5UTR,3UTRand1kbupstreamofTSS).First,we535testedfortheeffectofeachcelltypeDHSandgeneannotationindividuallyusingtheBayes’factors536forallvariantsinthe62crediblesetsusingfgwas67.Second,wecategorisedtheannotationsinto537‘genic’,‘foetalDHS’,‘embryonicDHS’,‘stemcellDHS’,‘neonatalDHS’and‘adultDHS’basedonthe538descriptionfieldsfromENCODE,andtestedfortheeffectofeachcategoryindividuallyasdescribed539aboveusingfgwas.Third,wethentestedtheeffectofeachcategorybyincludingallcategoriesina540jointmodelusingfgwas.Foreachofthethreeanalyses,weobtainedtheestimatedeffectsand95%541confidenceintervals(CI)foreachannotation,andconsideredanannotationenrichedifthe95%CI542didnotoverlapzero.543544Estimationofgeneticvarianceexplained.VarianceexplainedwascalculatedusingtheREML545methodimplementedinGCTA68.WeconsideredthevarianceexplainedbytwosetsofSNPs:(i)lead546SNPsofall62distinctassociationsignalsatthe59establishedandnovelautosomalBWloci547identifiedintheEuropean-specificortrans-ancestrymeta-analyses;(ii)leadSNPsof55distinct548associationsignalsatthe52novelautosomalBWloci(ExtendedDataTable1aandSupplementary549Table7).VarianceexplainedwascalculatedinsamplesofEuropeanancestryintheHyperglycemia550andAdversePregnancyOutcome(HAPO)study69(independentofthemeta-analysis)andtwostudies551thatwerepartoftheEuropeanancestrymeta-analysis:NFBC1966andGenerationR552(SupplementaryTable1).Ineachstudy,thegeneticrelationshipmatrixwasestimatedforeachset553ofSNPsandwastestedindividuallyagainstBW(malesandfemalescombined)withstudyspecific554covariates.Theseanalysesprovidedanestimateandstandarderrorforthevarianceexplainedby555eachofthegivensetsofSNPs.556557ExaminingtherelativeeffectsonBWofmaternalandfoetalgenotypeatthe60identifiedloci.We558performedfoursetsofanalyses.559

First,weusedGWASdatafrom4,382mother-childpairsintheAvonLongitudinalStudyof560ParentsandChildren(ALSPAC)studytofita“maternal-GCTAmodel”6toestimatetheextentto561whichthematernalgenomemightinfluenceoffspringBWindependentofthefoetalgenome.The562m-GCTAmodelusesgenome-widegeneticsimilaritybetweenmothersandoffspringtopartitionthe563phenotypicvarianceinBWintocomponentsduetothematernalgenotype,thechild’sgenotype,the564covariancebetweenthetwoandenvironmentalsourcesofvariation.565

Second,wecomparedassociationswithBWofthefoetalversusmaternalgenotypeateach566ofthe60BWloci.ThematernalalleliceffectonoffspringBWwasobtainedfromamaternalGWAS567meta-analysisof68,254EuropeanmothersfromtheEGGConsortium(n=19,626)7andtheUK568Biobank(n=48,628).IntheUKBiobank,motherswereaskedtoreporttheBWoftheirfirstchild.569WomenofEuropeanancestrywithgenotypedataavailableintheMay2015datareleasewere570included,andthosewithreportedBWequivalentto<2.5kgor>4.5kgwereexcluded.No571

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informationongestationalageorgenderofchildwasavailable.BWoffirstchildwasassociatedwith572maternalfactorssuchassmokingstatus,BMIandheightintheexpecteddirections.Ofthe68,254573womenincludedinthematernalGWAS,13%weremothersofindividualsincludedinthecurrent574foetalEuropeanancestryGWAS,andafurtherapproximately45%werethemselves(withtheirown575BW)includedinthefoetalGWAS.576

Third,weadditionallyconductedanalysesin12,909mother-childpairsfromnine577contributingstudies:ateachofthe60loci,wecomparedtheeffectofthefoetalgenotypeonBW578adjustedforsexandgestationalage,withandwithoutadjustmentformaternalgenotype.We579reciprocallycomparedtheassociationbetweenthematernalgenotypeandBWwithandwithout580adjustmentforfoetalgenotype.581

Fourth,weusedthemethodofZhangetal15totestassociationsbetweenBWandthe582maternaluntransmitted,maternaltransmittedandinferredpaternaltransmittedhaplotypescoreof583422heightSNPs25,30SBPSNPs13,14and84T2DSNPs24in5,201mother-childpairsfromtheALSPAC584study.585586LDScoreRegression.TheuseofLDScoreregressiontoestimatethegeneticcorrelationbetween587twotraits/diseaseshasbeendescribedindetailelsewhere70.Briefly,“LDScore”isameasureofhow588muchgeneticvariationeachvarianttags;ifavarianthasahighLDScorethenitisinhighLDwith589manynearbypolymorphisms.VariantswithhighLDScoresaremorelikelytocontainmoretrue590signalsandhenceprovidemorechanceofoverlapwithgenuinesignalsbetweenGWAS.TheLD591scoreregressionmethodusessummarystatisticsfromtheGWASmeta-analysisofBWandtheother592traitsofinterest,calculatesthecross-productofteststatisticsateachSNP,andthenregressesthe593cross-productontheLDScore.Bulik-Sullivanetal70showthattheslopeoftheregressionisa594functionofthegeneticcovariancebetweentraits:595

596

𝐸 𝑧!!𝑧!! =𝑁!𝑁!𝜌!𝑀

𝑙! +𝜌𝑁!𝑁!𝑁!

whereNiisthesamplesizeforstudyi,ρgisthegeneticcovariance,MisthenumberofSNPsinthe597referencepanelwithMAFbetween5%and50%,ljistheLDscoreforSNPj,Nsquantifiesthenumber598ofindividualsthatoverlapbothstudies,andρisthephenotypiccorrelationamongsttheNs599overlappingsamples.Thus,ifthereissampleoverlap(orcrypticrelatednessbetweensamples),it600willonlyaffecttheinterceptfromtheregression(i.e.theterm !!!

!!!!)andnottheslope,andhence601

estimatesofthegeneticcovariancewillnotbebiasedbysampleoverlap.Likewise,population602stratificationwillaffecttheinterceptbutwillhaveminimalimpactontheslope(i.e.intuitivelysince603populationstratificationdoesnotcorrelatewithlinkagedisequilibriumbetweennearbymarkers).604

SummarystatisticsfromtheGWASmeta-analysisfortraitsanddiseasesofinterestwere605downloadedfromtherelevantconsortiumwebsite.Thesummarystatisticsfileswerereformatted606forLDScoreregressionanalysisusingthemunge_sumstats.pypythonscriptprovidedonthe607developer’swebsite(https://github.com/bulik/ldsc).Foreachtrait,wefilteredthesummary608statisticstothesubsetofHapMap3SNPs71,asadvisedbythedevelopers,toensurethatnobiaswas609introducedduetopoorimputationquality.SummarystatisticsfromtheEuropean-specificBWmeta-610analysiswereusedbecauseofthevariableLDstructurebetweenancestrygroups.Wherethesample611sizeforeachSNPwasincludedintheresultsfilethiswasflaggedusing--N-col;ifnosamplesizewas612availablethenthemaximumsamplesizereportedinthereferencefortheGWASmeta-analysiswas613used.SNPswereexcludedforthefollowingreasons:MAF<0.01;ambiguousstrand;duplicatersID;614non-autosomalSNPs;reportedsamplesizelessthan60%ofthetotalavailable.Onceallfileswere615reformatted,weusedtheldsc.pypythonscript,alsoonthedevelopers’website,tocalculatethe616geneticcorrelationbetweenBWandeachofthetraitsanddiseases.TheEuropeanLDScorefiles617

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thatwerecalculatedfromthe1000Greferencepanelandprovidedbythedeveloperswereusedfor618theanalysis.WheremultipleGWASmeta-analyseshadbeenconductedonthesamephenotype(i.e.619overaperiodofyears),thegeneticcorrelationwithBWwasestimatedusingeachsetofsummary620statisticsandpresentedinSupplementaryTable12.ThephenotypeswithmultipleGWASincluded621height,BMI,waist-hipratio(adjustedforBMI),totalcholesterol,triglycerides,highdensity622lipoprotein(HDL)andlowdensitylipoprotein(LDL).Theestimateofthegeneticcorrelationbetween623themultipleGWASmeta-analysesonthesamephenotypewerecomparableandthelaterGWAS624hadasmallerstandarderrorduetotheincreasedsamplesize,soonlythegeneticcorrelation625betweenBWandthemostrecentmeta-analyseswerepresentedinFig.2.626

InthepublishedGWASforBP14thephenotypewasadjustedforBMI.Cautionisneeded627wheninterpretingthegeneticcorrelationbetweenBWandBMI-adjustedSBPduetothepotential628forcolliderbias72.SinceBMIisassociatedwithbothBPandBW,itispossiblethattheuseofaBP629geneticscoreadjustedforBMImightbiasthegeneticcorrelationestimatetowardsamorenegative630value.ToverifythattheinversegeneticcorrelationwithBW(rg=-0.26,SE=0.05,P=6.5x10-9)wasnot631duetocolliderbiascausedbytheBMIadjustmentofthephenotype,weobtainedanalternative632estimateusingUKBiobankGWASdataforSBPthatwasunadjustedforBMIandobtainedasimilar633result(rg=-0.22,SE=0.03,P=5.5x10-13).TheSBPphenotypeinUKBiobankwaspreparedasfollows.634TwoBPreadingsweretakenatassessment,approximately5minutesapart.Weincludedall635individualswithanautomatedBPreading(takenusinganautomatedOmronBPmonitor).Twovalid636measurementswereavailableformostparticipants(averagedtocreateaBPvariable,or637alternativelyasinglereadingwasusedifonlyonewasavailable).Individualswereexcludedifthe638tworeadingsdifferedbymorethan4.56SD.BPmeasurementsmorethan4.56SDawayfromthe639meanwereexcluded.WeaccountedforBPmedicationusebyadding15mmHgtotheSBPmeasure.640BPwasadjustedforage,sexandcentrelocationandtheninverseranknormalised.Weperformed641theGWASon127,698individualsofBritishdescentusingBOLT-LMM37,withgenotypingarrayas642covariate.643644EstimatingtheproportionoftheBW-adulttraitscovarianceattributabletogenotypedSNPs.We645estimatedthephenotypic,geneticandresidualcorrelationsaswellasthegeneticandresidual646covariancebetweenBWandseveralquantitativetraits/diseaseoutcomesinUKBiobankusing647directlygenotypedSNPsandtheREMLmethodimplementedinBOLT-LMM37.Thetraitsexamined648includedT2D,SBP,diastolicBP,CAD,height,BMI,weight,waist-hipratio,hipcircumference,waist649circumference,obesity,overweight,ageatmenarche,asthma,andsmoking.Wherephenotypes650werenotavailable(e.g.serumbloodmeasuresarenotcurrentlyavailableinUKBiobank),we651obtainedestimatesusingtheNFBC1966study(forcorrelations/covariancebetweenBWand652triglycerides,totalcholesterol,HDL,LDL,fastingglucoseandfastinginsulin).IntheUKBiobank653analysis,weused57,715unrelatedindividualswithBWavailableandidentifiedbyUKBiobankas654whiteBritish.SNPswithevidenceofdeviationfromHardy-WeinbergEquilibrium(P<1x10-6),655MAF<0.05oroverallmissingrate>0.015wereexcluded,resultingin328,928SNPsforanalysis.We656includedthefirstfiveancestryprincipalcomponentsascovariates.IntheNFBC1966analysis,5,009657individualswithBWwereenrolled.GenotypedSNPsthatpassedqualitycontrol(Supplementary658Table2)wereincluded,resultingin324,895SNPsforanalysis.Thefirstthreeancestryprincipal659componentsandsexwereincludedascovariates.660661Genesetenrichmentanalysis.Meta-AnalysisGene-setEnrichmentofvariaNTAssociations662(MAGENTA)wasusedtoexplorepathway-basedassociationsusingsummarystatisticsfromthe663trans-ancestrymeta-analysis.MAGENTAimplementsagenesetenrichmentanalysis(GSEA)based664approach,aspreviouslydescribed9.Briefly,eachgeneinthegenomeismappedtoasingleindexSNP665withthelowestP-valuewithina110kbupstreamand40kbdownstreamwindow.ThisP-value,666representingagenescore,isthencorrectedforconfoundingfactorssuchasgenesize,SNPdensity667andLD-relatedpropertiesinaregressionmodel.GeneswithintheHLA-regionwereexcludedfrom668

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analysisduetodifficultiesinaccountingforgenedensityandLDpatterns.Eachmappedgeneinthe669genomeisthenrankedbyitsadjustedgenescore.Atagivensignificancethreshold(95thand75th670percentilesofallgenescores),theobservednumberofgenescoresinagivenpathway,witha671rankedscoreabovethespecifiedthresholdpercentile,iscalculated.Thisobservedstatisticisthen672comparedto1,000,000randomlypermutedpathwaysofidenticalsize.Thisgeneratesanempirical673GSEAP-valueforeachpathway.Significancewasattainedwhenanindividualpathwayreacheda674falsediscoveryrate(FDR)<0.05ineitheranalysis.Intotal,3,216pre-definedbiologicalpathways675fromGeneOntology,PANTHER,KEGGandIngenuityweretestedforenrichmentofmultiplemodest676associationswithBW.TheMAGENTAsoftwarewasalsousedforenrichmenttestingofcustomgene677sets.678679Protein-Proteininteractionnetworkanalyses.WeusedtheintegrativeProtein-Interaction-680Network-BasedPathwayAnalysis(iPINBPA)method73.Briefly,wegeneratedgene-wiseP-values681fromthetrans-ancestrymeta-analysisusingVEGAS274,whichmaptheSNPstogenesandaccountfor682possiblecofounders,suchasLDbetweenmarkers.Theempiricalgene-wiseP-valuesarecalculated683usingsimulationsfromthemultivariatenormaldistribution.Thosethatwerenominallysignificant684(P≤0.01)wereselectedas“seedgenes”,andwerecollatedwithinhighconfidenceversionof685inweb375,toweightthenodesinthenetworkfollowingaguilt-by-associationapproach.Inasecond686step,anetworkscorewasdefinedbythecombinationofthez-scoresderivedfromthegene-wiseP-687valueswithnodeweightsusingtheLiptak-Stouffermethod76.Aheuristicalgorithmwasthenapplied688toextensivelysearchformodulesenrichedingeneswithlowP-values.Themoduleswerefurther689normalisedusinganulldistributionof10,000randomnetworks.Onlythosemoduleswithz-score>5690wereselected.Finally,theunionofallmodulesconstructedaBW-overallPPInetwork.Boththe691proteinsontheindividualmodulesandontheoverallBW-PPIwereinterrogatedforenrichmentin692GeneOntologyTerms(BiologicalProcesses)usingaHypergeometrictest.Termswereconsideredas693significantwhenadjustedP-value,followingBenjamini-Hochbergprocedure,wasbelow0.05.694695Pointofcontact(PoC)analyses.Thesamemethodologydescribedabovewasappliedto16different696adulttraitsresultinginanumberofenrichedmodulespertrait.Differentmodulesforeachtrait697werecombinedinasinglecomponentandtheintersectionbetweenthesetrait-specificcomponents698andtheBWcomponentwascalculated.ThisintersectionisdefinedasthePoCnetwork.Weusedthe699resultingPoCnetworksindownstreamanalysestointerrogatewhichsetofproteinsconnectsBW700variationandadulttraitvariationviapathwaysenrichedintheoverallBWanalysis.701702Parent-of-originspecificassociations.Wefirstsearchedforevidenceofparentoforigineffectsin703theUKBiobanksamplesbycomparingvariancebetweenheterozygotesandhomozygotesusing704Quicktest77.Inthisanalysis,weusedonlyunrelatedindividualsidentifiedgeneticallyasofwhite705Britishorigin(n=57,715).Principalcomponentsweregeneratedusingtheseindividualsandthefirst706fivewereusedtoadjustforpopulationstructureascovariatesintheanalysis,inadditiontoabinary707indicatorforgenotypingarray.708

Wealsoexamined4,908mother-childpairsinALSPACanddeterminedtheparentaloriginof709thealleleswherepossible78.Briefly,themethodusesmother-childpairstodeterminetheparentof710originofeachallele.Forexample,ifthemother/childgenotypesareAA/Aa,thechild’s711maternal/paternalallelecombinationisA/a.Forthesituationwherebothmotherandchildare712heterozygous,thechild’smaternal/paternalallelescannotbedirectlyspecified.However,the713parentaloriginoftheallelescanbedeterminedbyphasingthegenotypedataandcomparing714maternalandchildhaplotypes.WethentestedtheseallelesforassociationwithBWadjustingfor715sexandgestationalage.716

Statisticalpowerinthesecurrentlyavailablesamplesizesisinsufficienttoruleout717widespreadparent-of-origineffectsacrosstheregionstested.Usingthemeanbeta(0.034SD)and718MAF(0.28)oftheidentifiedloci,weestimatethatwewouldneedatleast200,000unrelated719

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individualsor70,000mother-childpairsfor80%powertodetectparent-of-origineffectsat720P<0.00085.721722HierarchicalclusteringofBWloci.ToexplorethedifferentpatternsofassociationbetweenBWand723otheranthropometric/metabolic/endocrinetraitsanddiseases,weperformedhierarchicalclustering724analysis.TheleadSNP(orproxy,EURr2>0.6)atthe60BWlociwasqueriedinpubliclyavailable725GWASmeta-analysisdatasetsorinGWASresultobtainedthroughcollaboration79.Resultswere726availablefor53ofthoselociandtheextractedz-score(alleliceffect/SE,SupplementaryTable17)727wasalignedtotheBW-raisingallele.Weperformedtwodimensionalclusteringbytraitandbylocus.728WecomputedtheEuclideandistanceamongstz-scoresoftheextractedtraits/lociandperformed729completehierarchicalclusteringimplementedinthepvclustpackage(http://www.sigmath.es.osaka-730u.ac.jp/shimo-lab/prog/pvclust/)inRv3.2.0(http://www.R-project.org/).Clusteringuncertaintywas731measuredbymultiscalebootstrapresamplingestimatedfrom1,000replicates.Weusedα=0.05to732definedistinctclustersand,basedonthebootstrapanalysis,calculatedtheCalinskiindextoidentify733thenumberofwell-supportedclusters(cascadeKMfunction,Veganpackage,http://CRAN.R-734project.org/package=vegan).Clusteringwasvisualisedbyconstructingdendrogramsandaheatmap.735 Separatelyfromthehierarchicalclusteringanalysis,wequeriedtheleadSNPatEPAS1ina736GWASofhaematologicaltraits80becausevariationatthatlocushaspreviouslybeenimplicatedin737BWandadaptationtohypoxiaathighaltitudesinTibetans81,82(SupplementaryTable17).738

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ENDNOTESSupplementaryInformationislinkedtotheonlineversionofthepaper.AcknowledgementsFullacknowledgementsandsupportinggrantdetailscanbefoundintheSupplementaryInformation.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.,B.F.,N.G.,J.P.B.,D.P.S.,R.L-G.,T.S.A.,E.K.,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.,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.,B.F.,N.G.,J.P.B.,D.P.S.,R.L-G.,R.R.,L-P.L.,J-J.H.,I.N.,E.M.v.L.,M.B.,P.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.AuthorInformationSummarystatisticsfromthemeta-analysesareavailableathttp://egg-consortium.org/.Reprintsandpermissionsinformationisavailableatwww.nature.com/reprints.Oneoftheauthorsdisclosescompetingfinancialinterests:KrinaZondervanhasascientificcollaborationwithBayerHealthCareLtd.andPopulationDiagnosticsInc.Correspondenceandrequestsformaterialsshouldbeaddressedtomark.mccarthy@drl.ox.ac.ukandr.freathy@ex.ac.uk.

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EXTENDEDDATALEGENDS

ExtendedDataFigure1|Flowchartofthestudydesign.ExtendedDataFigure2|Manhattanandquantile-quantile(QQ)plotsofthetrans-ancestrymeta-analysisforbirthweight.a,Manhattan(mainpanel)andQQ(topright)plotsofgenome-wideassociationresultsforBWfromtrans-ancestrymeta-analysisofupto153,781individuals.TheassociationP-value(on-log10scale)foreachofupto22,434,434SNPs(yaxis)isplottedagainstthegenomicposition(NCBIBuild37;xaxis).Associationsignalsthatreachedgenome-widesignificance(P<5x10-8)areshowningreenifnovelandpinkifpreviouslyreported.IntheQQplot,theblackdotsrepresentobservedP-valuesandthegreylinerepresentsexpectedP-valuesunderthenulldistribution.ThereddotsrepresentobservedP-valuesafterexcludingthepreviouslyidentifiedsignals5.b,Manhattan(mainpanel)andQQ(topright)plotsoftrans-ethnicGWASmeta-analysisforBWhighlightingthereportedimprintedregionsdescribedinSupplementaryTable14.Novelassociationsignalsthatreachedgenome-widesignificance(P<5x10-8)andmappedtoimprintedregionsareshowningreen.Genomicregionsoutsideimprintedregionsareshadedingrey.SNPsintheimprintedregionsareshowninlightblueordarkblue,dependingonchromosomenumber(oddoreven).IntheQQplot,theblackdotsrepresentobservedPvaluesandthegreylinesrepresentexpectedP-valuesandtheir95%confidenceintervalsunderthenulldistributionfortheSNPswithintheimprintedregions.ExtendedDataFigure3|Regionalplotsformultipledistinctsignalsatthreebirthweightloci,ZBTB7B(a),HMGA1(b)andPTCH1(c).Regionalplotsforeachlocusaredisplayedfrom:theunconditionalEuropean-specificmeta-analysisofupto143,677individuals(left);theapproximateconditionalmeta-analysisfortheprimarysignalafteradjustmentfortheindexvariantforthesecondarysignal(middle);andtheapproximateconditionalmeta-analysisforthesecondarysignalafteradjustmentfortheindexvariantfortheprimarysignal(right).DirectlygenotypedorimputedSNPsareplottedwiththeirassociationP-values(ona-log10scale)asafunctionofgenomicposition(NCBIBuild37).Estimatedrecombinationrates(bluelines)areplottedtoreflectthelocalLDstructurearoundtheindexSNPsandtheircorrelatedproxies.SNPsarecolouredinreferencetoLDwiththeparticularindexSNPaccordingtoabluetoredscalefromr2=0to1,basedonpairwiser2valuesestimatedfromareferenceof5,000individualsofwhiteBritishorigin,randomlyselectedfromtheUKBiobank.ExtendedDataFigure4|Comparisonoffoetaleffectsizesandmaternaleffectsizesat60knownandnovelbirthweightloci(continuestoExtendedDataFigure5).ForeachBWlocus,thefollowingsixeffectsizes(with95%CI)areshown,allalignedtothesameBW-raisingallele:foetal_GWAS=foetalalleliceffectonBW(fromEuropeanancestrymeta-analysisofupton=143,677individuals);foetal_unadjusted=foetalalleliceffectonBW(unconditionedinn=12,909mother-childpairs);foetal_adjusted=foetaleffect(conditionedonmaternalgenotype,n=12,909);maternal_GWAS=maternalalleliceffectonoffspringBW(frommeta-analysisofupton=68,254Europeanmothers)7;maternal_unadjusted=maternalalleliceffectonoffspringBW(unconditioned,n=12,909);maternal_adjusted=maternaleffect(conditionedonfoetalgenotype,n=12,909).The60BWlociareorderedbychromosomeandposition(SupplementaryTables10,11).TheseplotsillustratethatinlargeGWASofBW,foetaleffectsizeestimatesarelargerthanthoseofmaternalat55/60identifiedloci(binomialP=1x10-11),suggestingthatmostoftheassociationsaredrivenbythefoetalgenotype.Inconditionalanalysesthatmodelledtheeffectsofbothmaternalandfoetalgenotypes(n=12,909mother-childpairs),confidenceintervalsaroundtheestimateswerewide,precludinginferenceaboutthelikelycontributionofmaternalvs.foetalgenotypeatindividualloci.

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ExtendedDataFigure5|Comparisonoffoetaleffectsizesandmaternaleffectsizesat60knownandnovelbirthweightloci.a,ContinuedfromExtendedDataFigure4.b,Thescatterplotillustratesthedifferencebetweenthefoetal(xaxis)andmaternal(yaxis)effectsizesintheoverallmaternalvs.foetalGWASresults.ExtendedDataFigure6|Protein-ProteinInteraction(PPI)Networkanalysis.a,Illustratesthelargestglobalcomponentofbirthweight(BW)PPInetworkcontaining13modules.b,Thehistogramshowsthenulldistributionofz-scoresofBWPPInetworksbasedon10,000randomnetworks,andwherethez-scoresforthe13BWmodules(M1-13)lie.Foreachmodule,thetwomostsignificantGOtermsaredepicted.c,Illustratesaheatmapwhichtakesthetop50biologicalprocessesover-representedintheglobalBWPPInetwork(listedattherightoftheplot),anddisplaysextentofenrichmentforthevarioustrait-specific“pointofcontact“(PoC)PPInetworks.d-e,Trait-specificPoCPPInetworkscomposedofproteinsthataresharedinboththeglobalBWPPInetworkandnetworksgeneratedusingthesamepipelineforeachoftheadulttraits:d,canonicalWntsignallingpathwayenrichedforPoCPPIbetweenBWandbloodpressure(BP)-relatedphenotypes;ande,regulationofinsulinsecretionpathwayenrichedforPoCbetweenBWandtype2diabetes(T2D)/fastingglucose(FG).RednodesarethosethatarepresentinPoCforBWandtraitsofinterest;bluenodescorrespondtothepathwaynodes;purplenodesarethosepresentinboththepathwayandPoC;orangenodesaregenesinBWlocithatoverlapwithboththepathwayandPoC.LargenodescorrespondtogenesinBWloci(within300kbfromtheleadSNP),andhaveblackborderifthey,amongstallBWloci,haveastronger(top5)associationwithatleastoneofthepairingadulttraits.ExtendedDataFigure7|Quantile-Quantile(QQ)plotsof(a)variancecomparisonbetweenheterozygotesandhomozygotesanalysisin57,715UKBiobanksamplesand(b)parent-of-originspecificanalysisin4,908ALSPACmother-childpairsat59autosomalbirthweightlociplusDLK1.a,QQplotfromtheQuicktest77analysiscomparingtheBWvarianceofheterozygoteswithhomozygotesin57,715UKBiobanksamples.b,QQplotfromtheparent-of-originspecificanalysistestingtheassociationbetweenBWandmaternallytransmittedvs.paternallytransmittedallelesin4,908mother-childpairsfromtheALSPACstudy(Methods,SupplementaryTables15,16).Inbothpanels,theblackdotsrepresentleadSNPsat59identifiedautosomalBWlociandafurthersub-genome-widesignificantsignalforBWnearDLK1(rs6575803;P=5.6x10-8).ThegreylinesrepresentexpectedPvaluesandtheir95%confidenceintervalsunderthenulldistributionforthe60SNPs.BothresultsshowtrendsinfavourofimprintingeffectsatBWloci:however,despitethelargesamplesize,theseanalyseswereunderpowered(seeMethods)andmuchlargersamplesizesarerequiredfordefinitiveanalysis.ExtendedDataFigure8|Summaryofpreviouslyreportedlociforsystolicbloodpressure(SBP,a),coronaryarterydisease(CAD,b,e),type2diabetes(T2D,c,f)andadultheight(d)andtheireffectonbirthweight.a-d,Effectsizes(leftyaxis)ofpreviouslyreported30SBPloci13,14,45CADloci23,84T2Dloci24and422adultheightloci25areplottedagainsteffectsonBW(xaxis).Effectsizesarealignedtotheadulttrait-raisingallele.ThecolourofeachdotindicatesBWassociationPvalue:red,P<5×10−8;orange,5×10−8≤P<0.001;yellow,0.001≤P<0.01;white,P≥0.01.ThesuperimposedgreyfrequencyhistogramshowsthenumberofSNPs(rightyaxis)ineachcategoryofBWeffectsize.e,Effectsizes(with95%CI)onBWof45knownCADlociareplottedarrangedintheorderofCADeffectsizefromhighesttolowest,separatingouttheknownSBPloci.CADlociwithalargereffectonBWconcentratedamongstlociwithprimaryBPassociation.f,Effectsizes(with95%CI)onBWof32knownT2Dlociareplotted,subdividedbypreviouslyreportedcategoriesderivedfromdetailedadultphysiologicaldata27.HeterogeneityinBWeffectsizesbetweenfiveT2Dlocigroupswithdifferentmechanisticcategorieswassubstantial(Phet=1.2x10-9).Inpairwisecomparisons,the“betacell”groupofvariantsdifferedfromtheotherfourgroups:fastinghyperglycaemia(Phet=3x10-11),

28

insulinresistance(Phet=0.002),proinsulin(Phet=0.78)andunclassified(Phet=0.02)groups.AlloftheBWeffectsizesplottedintheforestplotsarealignedtothetrait(orrisk)-raisingallele.ExtendedDataTable1|Sixtylociassociatedwithbirthweight(P<5x10-8)inEuropeanancestrymeta-analysisofupto143,677individualsand/ortrans-ancestrymeta-analysisofupto153,781individuals.a,Effects(betavalues)arealignedtotheBW-raisingallele.EAFwasobtainedfromthetrans-ancestrymeta-analysis,exceptforPLAC1,forwhichtheEAFwasobtainedfromtheEuropeanancestrymeta-analysisduetolackofXchromosomedatafromthenon-Europeanstudies.Chr.,chromosome;bp,basepair;EAF,effectallelefrequency;SE,standarderror.b,TheeffectoftheleadSNP(absolutevalueofbeta,yaxis)isgivenasafunctionofminorallelefrequency(xaxis)for60known(pink)andnovel(green)BWlocifromthetrans-ancestrymeta-analysis.Errorbarsareproportionaltothestandarderroroftheeffectsize.Thedashedlineindicates80%powertodetectassociationatgenome-widesignificancelevelforthesamplesizeintrans-ancestrymeta-analysis.ExtendedDataTable2|Genesetenrichmentanalysisandprotein-proteininteraction(PPI)analysis.TwocomplementaryanalysesoftheoverallGWASsummarydataidentifiedenrichmentofBWassociationsinbiologicalpathwaysrelatedtometabolism,growthanddevelopment.a,Thetopresults(FDR<0.05atthe95thpercentileenrichmentthreshold)fromatotalof3,216biologicalpathwaystestedforenrichmentofmultiplemodestassociationswithBW.Additionally,resultsarepresentedforcustomsetsofimprintedgenes.b,TheresultsofacomplementaryanalysisofempiricalPPIdata,displayingthetop10mostsignificantpathwaysenrichedforBW-associationscores.