Lipids in Health and Disease最新文献

Background: Sun sensitivity, an abnormal skin reaction to ultraviolet radiation, increases the risk of melanoma and impairs the quality of life. In recent times, the body roundness index (BRI) has been suggested to be associated with various health conditions. Nevertheless, the association between the BRI and sun sensitivity remains not well understood. The purpose of this research was to investigate the association between the BRI and sun sensitivity.

Methods: This research utilized information acquired from the National Health and Nutrition Examination Survey (NHANES) conducted in the United States (2001-2006, 2009-2018; n = 9,999, including 1,085 cases of sun sensitivity). The association between the BRI and sun sensitivity was analyzed, and the Boruta algorithm was employed for feature selection. Subsequently, seven machine learning (ML) models were used to predict the risk of sun sensitivity, and the independent effect of the BRI was analyzed using Shapley additive explanations (SHAP).

Results: After full adjustment, each one-unit increase in the BRI significantly increased the risk of sun sensitivity (OR = 1.08, 95% CI: 1.04-1.11, P < 0.001). Quartile analysis showed that participants in the highest BRI quartile (≥ 6.32) had a 47% higher risk of sun sensitivity (OR = 1.47, 95% CI: 1.17-1.83, P < 0.001) than those in the lowest quartile. RCS confirmed a linear dose-response relationship (P_{- nonlinear} >0.05). The LightGBM model outperformed the other models (test AUC = 0.859, 95% CI: 0.847-0.871), with the BRI identified as a key predictor alongside race, the poverty-income ratio, and hypertension, as determined by SHAP analysis.

Conclusions: This is the first study to systematically evaluate the relationship between the BRI and risk of sun sensitivity using ML methods. The study identified a significant association between the BRI and risk of sun sensitivity. These findings provide new evidence regarding the etiology of sun sensitivity and offer a scientific basis for personalized disease management and public health interventions.

Background: Chronic Obstructive Pulmonary Disease (COPD), defined by persistent airflow obstruction, is increasingly understood as a systemic inflammatory disorder. This condition is also frequently accompanied by profound metabolic dysregulation. The ratios comparing certain immune cell populations to High-density lipoprotein cholesterol (HDL-C) values are gaining attention as potential markers of inflammation in multiple chronic illnesses. However, the relationship connecting inflammatory indices related to HDL-C with the frequency of COPD occurrence is not yet well-established.

Methods: This study analyzed data from the 2007-2012 US National Health and Nutrition Examination Survey (NHANES), covering 9,998 participants (1,619 with COPD). We examined four inflammatory indices derived from the ratio of lymphocytes (LHR), monocytes (MHR), neutrophils (NHR), and platelets (PHR) to HDL-C. A multi-faceted approach was employed, integrating machine learning for predictor selection, multivariable logistic regression for association analysis, and both mediation analysis and Mendelian randomization (MR) to investigate potential causality. The selected predictors were then used to construct and evaluate a predictive model.

Results: In fully adjusted models, MHR was associated with a 28% (95% CI, 8%-51%) increase in the odds of COPD, while NHR was linked to a 37% (95% CI, 15%-63%) increase. Both associations exhibited consistent dose-response relationships. Mediation analysis revealed these associations were primarily direct rather than indirect. Mendelian randomization suggested a potential causal role of a higher neutrophil count in COPD risk. Machine learning analysis consistently identified MHR and NHR as important predictors of COPD. The final model demonstrated robust predictive performance, with a nomogram and SHAP analysis enhancing its clinical utility and interpretability.

Conclusions: Our comprehensive analytical approach demonstrates that MHR and NHR are promising biomarkers associated with increased COPD prevalence. The consistency of results across epidemiological, causal inference, and machine learning methods provides robust evidence for their potential clinical utility in risk stratification and guiding early intervention strategies.

Background: Industrialized eating habits have disrupted the balance between n-6 to n-3 polyunsaturated fatty acids, a change reflected in human tissue composition. Increased n-6 to n-3 ratios may contribute to the emergence of several neurodevelopmental conditions. This study aims to determine how the balance between dietary n-6 and n-3 fatty acids relates to attention-deficit/hyperactivity disorder (ADHD) in kids and teenagers in the U.S.

Methods: Data were derived from 5,882 participants aged 4-15 years who participated in the National Health and Nutrition Examination Survey between 1999 and 2004. To examine the connection between dietary n-6 to n-3 fatty acid ratios and ADHD, multivariable logistic regression models were utilized. Additionally, restricted cubic spline models were used to analyze dose-response relationships while conducting stratified, interaction, and sensitivity analyses to support the robustness of the findings.

Results: Among 5,882 participants, 386 (6.6%) were diagnosed with ADHD. Relative to the lowest tertile (T1: < 8.56), participants in the second tertile (T2: 8.56-11.21) exhibited a 44% higher adjusted likelihood of having ADHD (95% confidence interval: 1.09-1.90; P = 0.011), while those in the top tertile (T3: > 11.21) had a 49% increased adjusted likelihood of having ADHD (95% confidence interval: 1.11-1.99; P = 0.007). Restricted cubic-spline modeling revealed an approximately linear relationship between dietary n-6 to n-3 fatty acid ratios and ADHD risk, without significant non-linearity (P = 0.547). These findings remained consistent in subgroup and sensitivity analyses.

Conclusions: Higher ratios of n-6 to n-3 fatty acids in diets correlated with a greater likelihood of ADHD in American kids and teens. These findings suggest that dietary modification to restore a healthier fatty acid balance reduces ADHD risk. Further research, particularly long-term cohort studies and randomized controlled trials, remains warranted to establish causality and to determine whether reducing the n-6 to n-3 ratio provides protective effects.

Background: Diabetes mellitus (DM) significantly increases the risk of atrial fibrillation (AF), yet the underlying mechanisms remain poorly defined. Arachidonic acid (AA), a key omega-6 fatty acid involved in redox and inflammatory regulation, has been implicated in cardiovascular homeostasis, but its role in diabetes-related atrial remodeling and AF susceptibility is unclear.

Methods: AA levels were measured in atrial tissues and serum from diabetic mice and AF patients. Diabetic mice were supplemented with AA, followed by structural, electrophysiological, and molecular analyses. Transcriptional regulation was assessed using Cut&Tag and dual-luciferase assays. To evaluate the γ-glutamylcysteine synthetase (γ-GCS)/γ-glutamylcysteine (γ-GC) pathway, mice were treated with the γ-GCS inhibitor L-Buthionine- (S, R)-sulfoximine (BSO) or supplemented with γ-GC.

Results: AA levels were significantly decreased in diabetic mice and AF patients and negatively correlated with atrial size. AA supplementation reduced atrial remodeling, oxidative stress, inflammation, and AF inducibility in diabetic mice, largely via activation of the Nrf2/γ-GCS pathway. BSO treatment reversed these benefits, while γ-GC supplementation mimicked the effects of AA.

Conclusion: These results reveal a previously unrecognized protective role of AA against diabetes-induced atrial remodeling and AF, primarily mediated via redox modulation, and suggest AA as a promising therapeutic target in diabetic atrial cardiomyopathy.

Cancer remains one of the most formidable diseases affecting human health, particularly because it involves complex reprogramming of metabolic pathways, especially pathways involved in lipid metabolism. Ether lipids (ELs), which alter membrane fluidity and signaling pathways that promote tumor initiation and development, have emerged as important regulators of cancer biology, positioning them as emerging candidate targets for diagnosis and treatment. The main focus of this review is the metabolic dysregulation of ELs in tumors, particularly the metabolic, genetic, and epigenetic processes that promote invasion, proliferation, and drug resistance. This review highlights preclinical treatment strategies designed to target EL synthases, aiming to provide novel perspectives for future translational applications that support more sustainable therapeutic options. In addition to future prospects centered on standardized detection and multiomics integration to improve precision oncology, important hurdles, including tissue specificity and metabolic heterogeneity, are covered.

Introduction: Visceral (VAT), subcutaneous (SFT), and total body fat (FM) contribute to hepatic steatosis, yet their relative and sex-specific effects across total, regional, and site-specific levels remain unclear. We investigated associations between fat depots, standardized skinfold sites, and liver fat (LF) while adjusting for key metabolic covariates.

Methods: In this secondary data analysis of a cross-sectional study, 48 adults (50% women; 49.6 ± 20.9 y; BMI 25.7 ± 3.7 kg/m²) underwent quantitative MRI to assess VAT and LF and ultrasound-based body mapping to quantify total and regional SFT as well as standardized skinfold sites. Bioelectrical impedance analysis determined FM. Regression analyses were conducted with LF as the dependent variable, identifying and controlling for significant covariates (diabetes mellitus [DM], arterial hypertension [aHT], hypercholesterolemia [HC], physical activity, age) (partial r). The Lindeman-Merenda-Gold (LMG) method decomposed total R² into fat-specific contributions. Total fat depots were adjusted for body surface area (BSA).

Results: All regression models examining associations with LF showed total r values ranging from 0.63 to 0.79. In men, DM was the only significant covariate (p = 0.002). Values are given as: partial r, LMG share (% of R²). LF correlated with VAT/BSA (0.40, 51%), total SFT/BSA (0.38, 42%), and FM/BSA (0.36, 51%). Regionally, upper-body SFT (0.40, 45%) and SFT_arms (0.37, 47%) contributed most, whereas lower-body SFT (0.35, 13%) showed minimal impact. The triceps skinfold was the most influential site among skinfolds (0.45, 50%). In women, HC was the only significant covariate (p = 0.02). LF correlated with VAT/BSA (0.40, 49%), total SFT/BSA (0.51, 27%), and FM/BSA (0.47, 36%). Regional models yielded upper-body SFT (0.43, 36%), SFT_arms (0.38, 23%), and lower-body SFT (0.41, 9%). Among single sites, the umbilical skinfold was most relevant (0.43, 36%), followed by the biceps (0.42, 33%).

Conclusion: VAT remains pivotal for LF in both sexes, yet SFT exhibits clear sex- and region-specific relevance. Only subcutaneous fat of the upper-body and arms contributed meaningfully to liver fat. Simple skinfold assessments-particularly triceps in men-may serve as practical indicator for early risk stratification. Larger, prospective cohorts are needed to confirm these findings.

Trial registration: Not applicable this study did not involve any health care intervention.