Diabetes, obesity & metabolism · 2024
The causal relationship between plasma protein-to-protein ratios and type 2 diabetes and its complications: Proteomics mendelian randomization study.
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Zhang Yue-Yang, Chen Bing-Xue, Yang Qin, Wan Qin
Аннотация
AIM: In recent years, proteomics research has surged, with numerous observational studies identifying associations between plasma proteins and type 2 diabetes. However, research specifically focusing on the ratios of plasma proteins in type 2 diabetes remains relatively scarce.
METHODS: This study primarily employed a two-sample, two-step Mendelian randomization (MR) approach, leveraging genetic data from several large, publicly accessible genome-wide association studies, wherein single nucleotide polymorphisms served as proxies for exposures and diseases. Within this framework, we applied two-sample MR to assess the associations between the 2821 plasma protein-to-protein ratios and type 2 diabetes along with its complications and utilized reverse MR to confirm the unidirectionality of these causal relationships. In addition, we employed two-step MR to investigate the potential mediating role of body mass index in these associations. To augment the robustness of our findings, we systematically implemented a series of sensitivity analyses.
RESULTS: The results gleaned from the inverse-variance weighted method elucidated that a cumulative sum of 23 protein-to-protein ratios bore a causal nexus with type 2 diabetes across both sample cohorts. With each incremental elevation of 1 standard deviation in the genetically anticipated protein-to-protein ratio, the susceptibility to type 2 diabetes oscillated from 0.93 (95% confidence interval: 0.87, 1.00) for the CNTN3/NCSS1 protein level ratio to 1.13 (1.06, 1.22) for the DBNL/NCK2 protein level ratio. Moreover, a tally of eight protein-to-protein ratios correlated with a minimum of one complication linked to type 2 diabetes. Diverse sensitivity analyses corroborated the robustness of these observations.
CONCLUSIONS: The outcomes of our investigation unveiled correlations between 23 plasma protein-to-protein ratios and type 2 diabetes, with eight of these ratios entwined with complications of type 2 diabetes. These discoveries offer novel perspectives on the diagnosis and management of type 2 diabetes and its associated complications.
METHODS: This study primarily employed a two-sample, two-step Mendelian randomization (MR) approach, leveraging genetic data from several large, publicly accessible genome-wide association studies, wherein single nucleotide polymorphisms served as proxies for exposures and diseases. Within this framework, we applied two-sample MR to assess the associations between the 2821 plasma protein-to-protein ratios and type 2 diabetes along with its complications and utilized reverse MR to confirm the unidirectionality of these causal relationships. In addition, we employed two-step MR to investigate the potential mediating role of body mass index in these associations. To augment the robustness of our findings, we systematically implemented a series of sensitivity analyses.
RESULTS: The results gleaned from the inverse-variance weighted method elucidated that a cumulative sum of 23 protein-to-protein ratios bore a causal nexus with type 2 diabetes across both sample cohorts. With each incremental elevation of 1 standard deviation in the genetically anticipated protein-to-protein ratio, the susceptibility to type 2 diabetes oscillated from 0.93 (95% confidence interval: 0.87, 1.00) for the CNTN3/NCSS1 protein level ratio to 1.13 (1.06, 1.22) for the DBNL/NCK2 protein level ratio. Moreover, a tally of eight protein-to-protein ratios correlated with a minimum of one complication linked to type 2 diabetes. Diverse sensitivity analyses corroborated the robustness of these observations.
CONCLUSIONS: The outcomes of our investigation unveiled correlations between 23 plasma protein-to-protein ratios and type 2 diabetes, with eight of these ratios entwined with complications of type 2 diabetes. These discoveries offer novel perspectives on the diagnosis and management of type 2 diabetes and its associated complications.