{"title":"Dietary patterns and exploratory gut microbiota profiles associated with diabetic retinopathy and cognitive impairment in type 2 diabetes.","authors":"Yuan Sheng, Haiyan Chi, Changling Li, Baogeng Huai, Xuejiao Song, Deshan Liu","doi":"10.1186/s12986-026-01167-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Diabetic retinopathy (DR) and cognitive impairment are closely related complications of type 2 diabetes mellitus (T2DM). Although dietary patterns and gut microbiota have each been linked to these conditions, their combined associations with co-occurring DR and cognitive impairment remain unclear. This study examined dietary patterns and exploratory gut microbiota profiles in relation to co-occurring DR and cognitive impairment in patients with T2DM.</p><p><strong>Methods: </strong>In this cross-sectional study, 306 patients with T2DM were classified into four groups: no DR with normal cognition (DMCN), no DR with cognitive impairment (DMCI), DR with normal cognition (DRCN), and DR with cognitive impairment (DRCI). Dietary patterns were derived using principal component analysis. Gut microbiota composition was assessed using 16 S rRNA sequencing in a subset of 108 participants. Multinomial logistic regression was used to examine associations between dietary patterns and group classification, and microbiome analyses included diversity, taxonomic composition, exploratory differential abundance, and diet-microbiota correlations.</p><p><strong>Results: </strong>Four dietary patterns were identified. In fully adjusted models, DP-I and DP-II were associated with higher odds of DMCI and DRCI, respectively, whereas DP-III was associated with lower odds of both DMCI and DRCN. DP-IV showed no significant association. Gut microbiota analyses showed modest but statistically significant group-related differences in community structure, with partial overlap across groups. Exploratory LEfSe analysis identified group-associated taxa, including higher relative abundances of Bifidobacterium, Streptococcus, and Dubosiella in DMCN and of Pseudomonas, Bilophila, and Sarcina in DRCI. However, these genus-level differences were not significant after covariate-adjusted MaAsLin2 analysis with false discovery rate (FDR) correction. Nominal diet-microbiota correlations were observed but were not statistically robust after FDR correction.</p><p><strong>Conclusion: </strong>Dietary patterns were associated with clinical group classification based on DR and cognitive impairment in patients with T2DM. Gut microbiota analyses suggested modest, exploratory group-related differences, but diet-microbiota correlations were not statistically robust after FDR correction. These cross-sectional findings should be interpreted as hypothesis-generating and require validation in larger longitudinal studies.</p>","PeriodicalId":19196,"journal":{"name":"Nutrition & Metabolism","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nutrition & Metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12986-026-01167-4","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Diabetic retinopathy (DR) and cognitive impairment are closely related complications of type 2 diabetes mellitus (T2DM). Although dietary patterns and gut microbiota have each been linked to these conditions, their combined associations with co-occurring DR and cognitive impairment remain unclear. This study examined dietary patterns and exploratory gut microbiota profiles in relation to co-occurring DR and cognitive impairment in patients with T2DM.
Methods: In this cross-sectional study, 306 patients with T2DM were classified into four groups: no DR with normal cognition (DMCN), no DR with cognitive impairment (DMCI), DR with normal cognition (DRCN), and DR with cognitive impairment (DRCI). Dietary patterns were derived using principal component analysis. Gut microbiota composition was assessed using 16 S rRNA sequencing in a subset of 108 participants. Multinomial logistic regression was used to examine associations between dietary patterns and group classification, and microbiome analyses included diversity, taxonomic composition, exploratory differential abundance, and diet-microbiota correlations.
Results: Four dietary patterns were identified. In fully adjusted models, DP-I and DP-II were associated with higher odds of DMCI and DRCI, respectively, whereas DP-III was associated with lower odds of both DMCI and DRCN. DP-IV showed no significant association. Gut microbiota analyses showed modest but statistically significant group-related differences in community structure, with partial overlap across groups. Exploratory LEfSe analysis identified group-associated taxa, including higher relative abundances of Bifidobacterium, Streptococcus, and Dubosiella in DMCN and of Pseudomonas, Bilophila, and Sarcina in DRCI. However, these genus-level differences were not significant after covariate-adjusted MaAsLin2 analysis with false discovery rate (FDR) correction. Nominal diet-microbiota correlations were observed but were not statistically robust after FDR correction.
Conclusion: Dietary patterns were associated with clinical group classification based on DR and cognitive impairment in patients with T2DM. Gut microbiota analyses suggested modest, exploratory group-related differences, but diet-microbiota correlations were not statistically robust after FDR correction. These cross-sectional findings should be interpreted as hypothesis-generating and require validation in larger longitudinal studies.
期刊介绍:
Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects.
The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases.
Key areas we wish to encourage submissions from include:
-how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes;
-the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components;
-how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved;
-how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.