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postgraduate thesis: Exploring the determinants of type 2 diabetes using metabolomics and proteomics data via Mendelian randomization

TitleExploring the determinants of type 2 diabetes using metabolomics and proteomics data via Mendelian randomization
Authors
Advisors
Issue Date2025
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Mo, M. J. [毛文源]. (2025). Exploring the determinants of type 2 diabetes using metabolomics and proteomics data via Mendelian randomization. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
AbstractType 2 diabetes (T2D) is projected to impact over 1.3 million people worldwide by 2050. Known risk factors may not have fully explained differences in the aetiology of T2D highlighting the need for alternative approaches in elucidating the factors driving these patterns. Advances in high-throughput omics technologies, such as proteomics and metabolomics, have enabled the identification of novel disease determinants. However, these omics studies suffer from the same methodological limitations - confounding and selection bias - as conventional observational designs. Mendelian randomization (MR), a study design that utilizes genetic instruments randomly allocated at conception, is more resistant to confounding, and so provides more reliable evidence for causal inference. Using summary statistics from large genome-wide association studies (GWAS) (N ≤1,812,017), this thesis explored the determinants of T2D by investigating the role of amino acids in T2D and glycaemic traits and by identifying the proteomics linkage between metabolic dysfunction-associated steatotic liver disease (MASLD), a disease causally linked to T2D, and T2D. This thesis also explored the complementary question of the differential impact of glycaemic traits and liability to T2D on circulating metabolites using two-sample MR, two-step MR, and cis-MR analyses. Using all nine proteogenic amino acids available in the UK Biobank summary statistics, alanine was associated with higher T2D risk, fasting glucose and glycated haemoglobin and with lower fasting insulin, whereas isoleucine may explain the positive association of branched-chain amino acids with T2D. Among 4,907 circulating proteins, alcohol dehydrogenase 1B (ADH1B), a key alcohol-metabolizing enzyme, may partially mediate the mechanistic link of MASLD with T2D. Regarding the metabolomic profiling of glycaemic traits, liability to T2D shared a signature with insulin, but not other glycaemic traits, highlighting the hyperglycemia-independent role of insulin in the pathophysiology of T2D. This thesis provides evidence for dietary guidelines and recommendations on amino acids intake and supplementation. My study also showed ADH1B has a dual role, taking part in the pathophysiological pathway of both alcohol and non-alcoholic fatty liver disease. Moreover, the heterogeneity in metabolomic signatures for different glycaemic criteria provides insights to the association of T2D with other metabolic diseases, providing an opportunity to reduce the T2D burden and T2D-related mortality.
DegreeDoctor of Philosophy
SubjectMetabolites
Proteomics
Type 2 diabetes - Genetic aspects
Dept/ProgramPublic Health
Persistent Identifierhttp://hdl.handle.net/10722/358273

 

DC FieldValueLanguage
dc.contributor.advisorAu Yeung, SLR-
dc.contributor.advisorSchooling, CM-
dc.contributor.authorMo, Man-yuen, Jacky-
dc.contributor.author毛文源-
dc.date.accessioned2025-07-31T14:06:15Z-
dc.date.available2025-07-31T14:06:15Z-
dc.date.issued2025-
dc.identifier.citationMo, M. J. [毛文源]. (2025). Exploring the determinants of type 2 diabetes using metabolomics and proteomics data via Mendelian randomization. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/358273-
dc.description.abstractType 2 diabetes (T2D) is projected to impact over 1.3 million people worldwide by 2050. Known risk factors may not have fully explained differences in the aetiology of T2D highlighting the need for alternative approaches in elucidating the factors driving these patterns. Advances in high-throughput omics technologies, such as proteomics and metabolomics, have enabled the identification of novel disease determinants. However, these omics studies suffer from the same methodological limitations - confounding and selection bias - as conventional observational designs. Mendelian randomization (MR), a study design that utilizes genetic instruments randomly allocated at conception, is more resistant to confounding, and so provides more reliable evidence for causal inference. Using summary statistics from large genome-wide association studies (GWAS) (N ≤1,812,017), this thesis explored the determinants of T2D by investigating the role of amino acids in T2D and glycaemic traits and by identifying the proteomics linkage between metabolic dysfunction-associated steatotic liver disease (MASLD), a disease causally linked to T2D, and T2D. This thesis also explored the complementary question of the differential impact of glycaemic traits and liability to T2D on circulating metabolites using two-sample MR, two-step MR, and cis-MR analyses. Using all nine proteogenic amino acids available in the UK Biobank summary statistics, alanine was associated with higher T2D risk, fasting glucose and glycated haemoglobin and with lower fasting insulin, whereas isoleucine may explain the positive association of branched-chain amino acids with T2D. Among 4,907 circulating proteins, alcohol dehydrogenase 1B (ADH1B), a key alcohol-metabolizing enzyme, may partially mediate the mechanistic link of MASLD with T2D. Regarding the metabolomic profiling of glycaemic traits, liability to T2D shared a signature with insulin, but not other glycaemic traits, highlighting the hyperglycemia-independent role of insulin in the pathophysiology of T2D. This thesis provides evidence for dietary guidelines and recommendations on amino acids intake and supplementation. My study also showed ADH1B has a dual role, taking part in the pathophysiological pathway of both alcohol and non-alcoholic fatty liver disease. Moreover, the heterogeneity in metabolomic signatures for different glycaemic criteria provides insights to the association of T2D with other metabolic diseases, providing an opportunity to reduce the T2D burden and T2D-related mortality. -
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.lcshMetabolites-
dc.subject.lcshProteomics-
dc.subject.lcshType 2 diabetes - Genetic aspects-
dc.titleExploring the determinants of type 2 diabetes using metabolomics and proteomics data via Mendelian randomization-
dc.typePG_Thesis-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplinePublic Health-
dc.description.naturepublished_or_final_version-
dc.date.hkucongregation2025-
dc.identifier.mmsid991045004488203414-

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