biostudies-literatureKodate SAMED17035https://www.ebi.ac.uk/biostudies/studies/S-EPMC12084608biostudies-literatureUnknown15(1)Advancements in large-scale analysis of metabolites in human peripheral blood samples revealed the links between metabolite concentrations and genetic variations. This field is known as metabolome-genome-wide association study (MGWAS). Although MGWAS is a powerful tool, it has some limitations, particularly in terms of the number of metabolites that can be measured. Whether the observed associations are directly due to genetic variation or indirectly due to changes in unmeasured metabolites is unclear. To address this, we used simulations of metabolic pathway models to investigate the influence of genetic variants on metabolite concentrations and enhance the interpretation of MGWAS results. By systematically adjusting the enzyme reaction rates to simulate genetic variants, we observed chanScientific reportsSimulating metabolic pathways to enhance interpretations of metabolome genome-wide association studies.PMC12084608JP23ama121019Saito SMotoike INSaito RNakagawa KSaito TTakasawa MSaito YSaito KOtsuki ATsunoda ISaito MUeki YOhisa NTomizuka MOtsuki YOtomo SYamada EBaird LWatanabe HKodate SFue RHatanaka RHirama HTamahara TWatanabe KOyamada KIrie RShinoda GInoue RTaiji NKunii YTsuchiya NYamazaki MIida CInoue MKurota SKikukawa TKumagai YSaito HAizawa HKumagai TKishi IKikuya MNobukuni TSaito AKumagai RNaganuma TSasaki KOikawa YSasaki MMiyazawa ATsuda MMinakawa SSasaki TSuga MOomachi MTakayama JSato YSatoh MMakino SKawame HKohketsu NNagase SKanno TKawagoe AOikawa MSasaki YShirota MHamaie YLi BAoki YYu ZIzumi YTakase MMomii MSato CAoki ESaitoh YOkamura YNakamichi KYageta MFunayama TOkumoto AAnzawa HSato TFukunaga WOjima YSato SSato RSato NSato MNishiyama MYagyu MSato HKuriki MChiba KMaeta KSuenaga YChiba IKoida NOtake NToki MChiba HKoyama TOgishima STamiya GNochioka KSuenaga RChiba ATakagi KYasuda JNanatani KHino KHirayama IOgasawara KKatsuoka FMaeshibu KMugikura SChiba TNakasato YUeno FYamauchi YOkuda HKishimoto TNagaie SNakamura NWada TOkuda MOta RSakurai RLi DOsanai TTakeuchi MKojima KTanaka AWada IGocho CNakamura CAbe HAbe NSuzuki AKumada KLi XAbe MToMMo Study GroupAiki KAsano YSugawara JSakurai MTateno MAbe TNakamura TSakurai KTateno KAbe YMatsubara HKambe MSugawara SNozoe KSuzuki RSuzuki TSuzuki MUeda ASuzuki NSugawara YTaguchi KMito STsumuraya TSugawara MSuzuki KSugawara NFuruhashi SNagai MOguma NMori NFushimi JMurakami KMori HTamura NSuzuki YOotomo KNunokawa RMurakami TNakaya NNakaya KKawada RKudo HNakai TKoshiba SKitaura TNemoto YNishida KOnodera MYin HOnodera KKusano HTomita HOnodera GOno ATomita EIgari NOno CKonno RSaigusa DAkiyama YSugimoto SFujishiro FOrui MOsada MNagami FZhang LShimada MHirano SOouchi YKawashima YSekiya AKatahira KTaira MHatakeyama AHozawa AHamanaka YYoshino MTakahashi EKoike THatakeyama SIshimori KKogure MHara YImai KShoji IShoji HShoji MFunata MOhi NTakita SNishi HKonno YOgawa SShoji WKumadaki RYokoyama THaga MMiura NHamada HHaga YWagatsuma MYokoyama MKondo AKimura MTanaka STerui CMiura AKinoshita KIshii OUruno AIshii KKawashima JMetoki HYokota HMatsuzaki MGonoi KIshii CHirano INagasaka TMiyagi ROnuma MFuse NShima YOnuma TYoshida YIshii TArai HFujita YAhiko SKoide MIshigaka EKasahara NGoto YKobayashi TIto NGoto MIto MKikuchi JIdo KIto SKobayashi MGoto TIto RHoshi TYaegashi NTokioka SIto KHidaka TKoide CGouko KFushiya KTadaka SOhneda KMotoike IKano MObara TYamamoto MMinami YObara SSakamoto HIwabuchi FSakamoto MYamamoto HHiratsuka YIshida MUchiya JUmeda KIshida NSakamoto KSonobe SSou IHirata TIwabuchi MMitate KMochida ASakai HKashiwa HKoreeda SSakaida MHiratsuka MKohagizawa TKomatsu JItabashi MKodama EKawabata THishinuma EShimizu RKurokawa ENarita AEndo HNoguchi KIshikuro MTakahashi YOohashi KSomeya SKuriyama SHasegawa ATakahashi RMatsukawa NShimizu AKato MMizuno STakahashi NNoda ASugai RTakahashi MTakahashi JTakahashi HMatsushita YOhori HGamo TKato YIshikawa TTanno NHatanaka NNishijima IShirakawa NSakamono HKabata YNakajo NSeo MNarita YOzawa YOkada YTsunasawa JOyama YTanno CYamada KDMatsuoka TArakawa MHanazawa MMotohashi HMatsumoto MfalseSimulating metabolic pathways to enhance interpretations of metabolome genome-wide association studies.Advancements in large-scale analysis of metabolites in human peripheral blood samples revealed the links between metabolite concentrations and genetic variations. This field is known as metabolome-genome-wide association study (MGWAS). Although MGWAS is a powerful tool, it has some limitations, particularly in terms of the number of metabolites that can be measured. Whether the observed associations are directly due to genetic variation or indirectly due to changes in unmeasured metabolites is unclear. To address this, we used simulations of metabolic pathway models to investigate the influence of genetic variants on metabolite concentrations and enhance the interpretation of MGWAS results. By systematically adjusting the enzyme reaction rates to simulate genetic variants, we observed chan2025-01-01T00:00:00Z2025 May2026-04-08T19:52:25.054Z2026-04-08T14:31:22.636ZS-EPMC120846084037978410.1038/s41598-025-01634-7