Genetic insights into the risk of metabolic syndrome and its components on psoriasis: A bidirectional Mendelian randomization

The impact of metabolic syndrome on the cerebral cortex: a Mendelian randomization study

Metabolic syndrome exhibits associations with diverse neurological disorders, and its potential influence on the cerebral cortex may be one of the many potential factors contributing to these adverse outcomes. In this study, we aimed to investigate the causal relationship between metabolic syndrome and changes in cerebral cortex structure using Mendelian randomization analysis. Genome-wide association study data for the 5 components of metabolic syndrome were obtained from individuals of European descent in the UK Biobank. Genome-wide association study data for 34 known cortical functional regions were sourced from the ENIGMA Consortium. Data on Alzheimer's disease, major depression, and anxiety disorder were obtained from the IEU Open genome-wide association study database. The causal links between metabolic syndrome elements and cerebral cortex architecture were evaluated using inverse variance weighting, Mendelian randomization-Egger, and weighted median techniques, with inverse variance weighting as the primary method. Inverse variance weighting, Mendelian randomization Egger, weighted median, simple mode, and weighted mode methods were employed to assess the relationships between metabolic syndrome and neurological diseases (Alzheimer's disease, major depression, and anxiety disorder). Outliers, heterogeneity, and pleiotropy were assessed using Cochran's Q test, MR-PRESSO, leave-one-out analysis, and funnel plots. Globally, no causal link was found between metabolic syndrome and overall cortical thickness or surface area. However, regionally, metabolic syndrome may influence the surface area of specific regions, including the caudal anterior cingulate, postcentral, posterior cingulate, rostral anterior cingulate, isthmus cingulate, superior parietal, rostral middle frontal, middle temporal, insula, pars opercularis, cuneus, and inferior temporal. It may also affect the thickness of the medial orbitofrontal, caudal middle frontal, paracentral, superior frontal, superior parietal, and supramarginal regions. These findings were nominally significant and withstood sensitivity analyses, showing no substantial heterogeneity or pleiotropy. Furthermore, we found an association between metabolic syndrome and the risk of Alzheimer's disease, major depression, and anxiety disorder. This study suggests a potential association between metabolic syndrome and changes in cerebral cortex structure, which may underlie certain neurological disorders. Furthermore, we found an association between metabolic syndrome and the risk of Alzheimer's disease, major depression, and anxiety disorder. Early diagnosis of metabolic syndrome holds significance in preventing these neurological disorders.

Positive association between different triglyceride glucose index-related indicators and psoriasis: evidence from NHANES

Background

Psoriasis is a chronic inflammatory skin disease with effects that extend beyond the skin. Insulin resistance (IR) has been associated with psoriasis, but it remains unclear how indicators related to the triglyceride glucose (TyG) index, which were associate with IR, are associated with the condition.

Objective

The purpose of this study was to investigate the association between psoriasis and three TyG-related indicators: triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist to height ratio (TyG-WHtR), and triglyceride glucose-waist circumference (TyG-WC).

Methods

Data from adults aged 20 to 80 years in the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2006 and 2009 to 2014 were utilized. Institutional Review Board approval and documented written consent was obtained from participants by NHANES (Protocol #2005-06). The patients were divided into three groups based on TyG-BMI, TyG-WC, and TyG-WHtR: Q1 (1st quintile), Q2 (2nd-3rd quintiles), and Q3 (4th-5th quintiles). Differences between the groups were further explored. Multivariate logistic regressions were used to investigate the correlation between these three indicators and psoriasis, with results expressed as odds ratios (OR) and 95% confidence intervals (CI). Subgroup analysis and supplementary analysis was further conducted to explore potential influencing factors.

Results

The study included 9,291 participants, of which 260 had psoriasis. Compared Q2 and Q3 of TyG-BMI, TyG-WC, and TyG-WHtR to Q1, there were significantly associate with psoriasis. Among the three indicators, TyG-WC consistently had the highest OR values in Models 1 and 2 (Model 1: Q3 OR (95% CI) = 2.155 (1.442-3.220); Model 2: Q3 OR (95% CI) = 2.029 (1.341-3.069)). While in Model 3, the TyG-BMI shows more significant relationship with psoriasis (Model 3 of TyG-BMI: Q3 OR (95% CI) = 1.948 (1.300-3.000)). Similar results were observed in the majority of subgroups and in supplementary analysis.

Conclusion

This study identified a stable and strong positive association between TyG-related indicators (TyG-BMI, TyG-WC, and TyG-WHtR) and psoriasis. This association persisted even after adjusting for multiple factors. It is suggested that high IR is significantly associated with psoriasis.