{"title":"多组学中介管道揭示了母亲snp影响新生儿肥胖结局的不同途径。","authors":"Nathan P Gill, Alan Kuang, Denise M Scholtens","doi":"10.1186/s12863-025-01355-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>A great deal of previous research describes the impact of the maternal metabolic and genetic milieu on newborn adiposity outcomes. However, much of this research does not focus on all aspects of the problem simultaneously. Studies focusing on metabolic factors may not distinguish between maternal and fetal genetic pathways, while studies that do focus on these different genetic pathways may not incorporate metabolic information into effect estimates or variant classifications. In this paper, we introduce a novel multi-omics pipeline for maternal genetic variant selection and mediation effect testing that can handle all these pathways, and use it to investigate broad patterns in the effects of maternal genetic variants on newborn adiposity outcomes.</p><p><strong>Results: </strong>A Bayesian network model is used to incorporate both metabolomic and genomic data into an initial filter for maternal variants likely to affect newborn adiposity outcomes through a direct maternal genetic effect, an indirect fetal genetic effect, a maternal metabolic effect, or some combination of these pathways. A mediation model is then fit to these candidate variants and associated outcomes to identify which of these pathways, if any, mediate the total effect. We then group maternal genetic variants according to the relative magnitudes of these three effect pathways. In an application to existing mother-newborn data from the HAPO study, we find that of 78 candidate variants, the majority influence newborn birthweight solely through either a direct maternal or indirect fetal genetic effect (37% and 40%, respectively), a smaller number through both of these (14%), relatively few exclusively through the maternal metabolic pathway (6%), and almost none through a combination of the maternal metabolic pathway with either of the two genetic pathways (3%). We also find that these overall patterns of mediation effects are similar across outcomes.</p><p><strong>Conclusions: </strong>Our results reveal broad patterns in the effects of maternal genetic variants on newborn adiposity, and identify both new genetic loci and loci known from previous literature to influence newborn adiposity. These results demonstrate the potential for scientific discovery enabled by our multi-omics mediation pipeline, and the approach is broadly applicable for untangling path-specific contributions in the modern integrated multi-omics landscape.</p>","PeriodicalId":72427,"journal":{"name":"BMC genomic data","volume":"26 1","pages":"66"},"PeriodicalIF":2.5000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12466079/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multi-omics mediation pipeline reveals differential pathways of maternal SNPs affecting newborn adiposity outcomes.\",\"authors\":\"Nathan P Gill, Alan Kuang, Denise M Scholtens\",\"doi\":\"10.1186/s12863-025-01355-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>A great deal of previous research describes the impact of the maternal metabolic and genetic milieu on newborn adiposity outcomes. However, much of this research does not focus on all aspects of the problem simultaneously. Studies focusing on metabolic factors may not distinguish between maternal and fetal genetic pathways, while studies that do focus on these different genetic pathways may not incorporate metabolic information into effect estimates or variant classifications. In this paper, we introduce a novel multi-omics pipeline for maternal genetic variant selection and mediation effect testing that can handle all these pathways, and use it to investigate broad patterns in the effects of maternal genetic variants on newborn adiposity outcomes.</p><p><strong>Results: </strong>A Bayesian network model is used to incorporate both metabolomic and genomic data into an initial filter for maternal variants likely to affect newborn adiposity outcomes through a direct maternal genetic effect, an indirect fetal genetic effect, a maternal metabolic effect, or some combination of these pathways. A mediation model is then fit to these candidate variants and associated outcomes to identify which of these pathways, if any, mediate the total effect. We then group maternal genetic variants according to the relative magnitudes of these three effect pathways. In an application to existing mother-newborn data from the HAPO study, we find that of 78 candidate variants, the majority influence newborn birthweight solely through either a direct maternal or indirect fetal genetic effect (37% and 40%, respectively), a smaller number through both of these (14%), relatively few exclusively through the maternal metabolic pathway (6%), and almost none through a combination of the maternal metabolic pathway with either of the two genetic pathways (3%). We also find that these overall patterns of mediation effects are similar across outcomes.</p><p><strong>Conclusions: </strong>Our results reveal broad patterns in the effects of maternal genetic variants on newborn adiposity, and identify both new genetic loci and loci known from previous literature to influence newborn adiposity. These results demonstrate the potential for scientific discovery enabled by our multi-omics mediation pipeline, and the approach is broadly applicable for untangling path-specific contributions in the modern integrated multi-omics landscape.</p>\",\"PeriodicalId\":72427,\"journal\":{\"name\":\"BMC genomic data\",\"volume\":\"26 1\",\"pages\":\"66\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12466079/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC genomic data\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s12863-025-01355-w\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC genomic data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s12863-025-01355-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Background: A great deal of previous research describes the impact of the maternal metabolic and genetic milieu on newborn adiposity outcomes. However, much of this research does not focus on all aspects of the problem simultaneously. Studies focusing on metabolic factors may not distinguish between maternal and fetal genetic pathways, while studies that do focus on these different genetic pathways may not incorporate metabolic information into effect estimates or variant classifications. In this paper, we introduce a novel multi-omics pipeline for maternal genetic variant selection and mediation effect testing that can handle all these pathways, and use it to investigate broad patterns in the effects of maternal genetic variants on newborn adiposity outcomes.
Results: A Bayesian network model is used to incorporate both metabolomic and genomic data into an initial filter for maternal variants likely to affect newborn adiposity outcomes through a direct maternal genetic effect, an indirect fetal genetic effect, a maternal metabolic effect, or some combination of these pathways. A mediation model is then fit to these candidate variants and associated outcomes to identify which of these pathways, if any, mediate the total effect. We then group maternal genetic variants according to the relative magnitudes of these three effect pathways. In an application to existing mother-newborn data from the HAPO study, we find that of 78 candidate variants, the majority influence newborn birthweight solely through either a direct maternal or indirect fetal genetic effect (37% and 40%, respectively), a smaller number through both of these (14%), relatively few exclusively through the maternal metabolic pathway (6%), and almost none through a combination of the maternal metabolic pathway with either of the two genetic pathways (3%). We also find that these overall patterns of mediation effects are similar across outcomes.
Conclusions: Our results reveal broad patterns in the effects of maternal genetic variants on newborn adiposity, and identify both new genetic loci and loci known from previous literature to influence newborn adiposity. These results demonstrate the potential for scientific discovery enabled by our multi-omics mediation pipeline, and the approach is broadly applicable for untangling path-specific contributions in the modern integrated multi-omics landscape.