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Linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: The spurious U–curve in observational study

OBJECTIVE: Hyperlipidemia is traditionally considered a risk factor for diabetes. The effect of low-density lipoprotein cholesterol (LDL-C) is counterintuitive to diabetes. We sought to investigate the relationship between LDL-C and diabetes for better lipid management. METHODS: We tested the shape...

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Autores principales: Ma, Yujia, Zhou, Zechen, Li, Xiaoyi, Ding, Kexin, Xiao, Han, Wu, Yiqun, Wu, Tao, Chen, Dafang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714469/
https://www.ncbi.nlm.nih.gov/pubmed/36465637
http://dx.doi.org/10.3389/fendo.2022.1009095
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author Ma, Yujia
Zhou, Zechen
Li, Xiaoyi
Ding, Kexin
Xiao, Han
Wu, Yiqun
Wu, Tao
Chen, Dafang
author_facet Ma, Yujia
Zhou, Zechen
Li, Xiaoyi
Ding, Kexin
Xiao, Han
Wu, Yiqun
Wu, Tao
Chen, Dafang
author_sort Ma, Yujia
collection PubMed
description OBJECTIVE: Hyperlipidemia is traditionally considered a risk factor for diabetes. The effect of low-density lipoprotein cholesterol (LDL-C) is counterintuitive to diabetes. We sought to investigate the relationship between LDL-C and diabetes for better lipid management. METHODS: We tested the shape of association between LDL-C and diabetes and created polygenic risk scores of LDL-C and generated linear Mendelian randomization (MR) estimates for the effect of LDL-C and diabetes. We evaluated for nonlinearity in the observational and genetic relationship between LDL-C and diabetes. RESULTS: Traditional observational analysis suggested a complex non-linear association between LDL-C and diabetes while nonlinear MR analyses found no evidence for a non-linear association. Under the assumption of linear association, we found a consistently protective effect of LDL-C against diabetes among the females without lipid-lowering drugs use. The ORs were 0.84 (95% CI, 0.72–0.97, P=0.0168) in an observational analysis which was more prominent in MR analysis and suggested increasing the overall distribution of LDL-C in females led to an overall decrease in the risk of diabetes (P=0.0258). CONCLUSIONS: We verified the liner protective effect of LDL-C against diabetes among the females without lipid-lowering drug use. Non-linear associations between LDL-C against diabetes in observational analysis are not causal.
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spelling pubmed-97144692022-12-02 Linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: The spurious U–curve in observational study Ma, Yujia Zhou, Zechen Li, Xiaoyi Ding, Kexin Xiao, Han Wu, Yiqun Wu, Tao Chen, Dafang Front Endocrinol (Lausanne) Endocrinology OBJECTIVE: Hyperlipidemia is traditionally considered a risk factor for diabetes. The effect of low-density lipoprotein cholesterol (LDL-C) is counterintuitive to diabetes. We sought to investigate the relationship between LDL-C and diabetes for better lipid management. METHODS: We tested the shape of association between LDL-C and diabetes and created polygenic risk scores of LDL-C and generated linear Mendelian randomization (MR) estimates for the effect of LDL-C and diabetes. We evaluated for nonlinearity in the observational and genetic relationship between LDL-C and diabetes. RESULTS: Traditional observational analysis suggested a complex non-linear association between LDL-C and diabetes while nonlinear MR analyses found no evidence for a non-linear association. Under the assumption of linear association, we found a consistently protective effect of LDL-C against diabetes among the females without lipid-lowering drugs use. The ORs were 0.84 (95% CI, 0.72–0.97, P=0.0168) in an observational analysis which was more prominent in MR analysis and suggested increasing the overall distribution of LDL-C in females led to an overall decrease in the risk of diabetes (P=0.0258). CONCLUSIONS: We verified the liner protective effect of LDL-C against diabetes among the females without lipid-lowering drug use. Non-linear associations between LDL-C against diabetes in observational analysis are not causal. Frontiers Media S.A. 2022-11-17 /pmc/articles/PMC9714469/ /pubmed/36465637 http://dx.doi.org/10.3389/fendo.2022.1009095 Text en Copyright © 2022 Ma, Zhou, Li, Ding, Xiao, Wu, Wu and Chen https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Ma, Yujia
Zhou, Zechen
Li, Xiaoyi
Ding, Kexin
Xiao, Han
Wu, Yiqun
Wu, Tao
Chen, Dafang
Linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: The spurious U–curve in observational study
title Linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: The spurious U–curve in observational study
title_full Linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: The spurious U–curve in observational study
title_fullStr Linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: The spurious U–curve in observational study
title_full_unstemmed Linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: The spurious U–curve in observational study
title_short Linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: The spurious U–curve in observational study
title_sort linear and nonlinear analyses of the association between low–density lipoprotein cholesterol and diabetes: the spurious u–curve in observational study
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714469/
https://www.ncbi.nlm.nih.gov/pubmed/36465637
http://dx.doi.org/10.3389/fendo.2022.1009095
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