Evidence mapPaperPMID 42284519Full record

ArticleArchives of endocrinology and metabolism2026

Relationships between glucose variability with white matter hyperintensity and cerebrovascular abnormalities.

Cheng-Chieh Lin, Chia-Ing Li, Chiu-Shong Liu, Chih-Hsueh Lin, Shing-Yu Yang, Tsai-Chung Li

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Article in Archives of endocrinology and metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Cheng-Chieh LinSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.ORCID 0000-0002-9625-6216
Chia-Ing LiSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.ORCID 0000-0002-7937-2928
Chiu-Shong LiuSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.ORCID 0000-0003-0274-2465
Chih-Hsueh LinSchool of Medicine, College of Medicine, China Medical University, Taichung, Taiwan.ORCID 0000-0002-9159-6326
Shing-Yu YangDepartment of Public Health, College of Public Health, China Medical University, Taichung, Taiwan.ORCID 0009-0008-1873-5191
Tsai-Chung LiDepartment of Public Health, College of Public Health, China Medical University, Taichung, Taiwan.ORCID 0000-0002-3346-7462

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveEpidemiological studies have revealed that glucose variability (GV) is a predictor of stroke, cognitive impairment, and dementia in patients with type 2 diabetes mellitus (T2DM). However, evidence on the associations of GV with white matter hyperintensity (WMH) and cerebrovascular abnormalities remains scarce. This study aimed to explore the relationships of GV with WMH and cerebrovascular abnormalities using epidemiological and Mendelian randomization (MR) approaches. The MR approach was used to assess the effects of genetic proxies for GV on MRI outcomes. SUBJECTS AND

methodsThis cross-sectional study was conducted at a medical center where patients with T2DM were recruited. The measures for fasting plasma glucose (FPG) and HbA1c variability included the standard deviation, coefficient of variation, average real variability (ARV), and variability independent of the mean (VIM). Brain magnetic resonance images were analyzed to assess WMHs and cerebrovascular abnormalities. For MR, instrumental variables were used to assess the causal relationships between glycemic variability and outcome based on two-stage regression analysis.

resultsThis study included 2,247 subjects, of whom 1,122 had WMH and 957 had cerebrovascular abnormalities. We found 80 independent single-nucleotide polymorphisms associated with GV but not with WMH or cerebrovascular abnormalities, which were subsequently used as genetic instruments. Genetically increased, unweighted FPG-VIM was linked with WMH (odds ratio 1.17 [95% CI 1.08, 1.27] per standard deviation). All genetically increased, unweighted and weighted GV measures were associated with cerebrovascular abnormalities, except FPG-ARV.

conclusionOur study provided evidence that genetically predicted GV was associated with WMH and cerebrovascular abnormalities, supporting a potential causal link under MR assumptions.

Indexed as

Blood GlucoseCerebrovascular DisordersDiabetes Mellitus, Type 2White MatterAgedCross-Sectional StudiesFemaleGlycated HemoglobinHumansMagnetic Resonance ImagingMaleMendelian Randomization AnalysisMiddle AgedPolymorphism, Single NucleotideBlood GlucoseGlycated Hemoglobincerebrovascular abnormalitiesglycemic variabilityType 2 diabeteswhite matter hyperintensity

Identifiers

PMID42284519
PMCPMC13271090

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.