Environmental noise has been increasingly linked to cardiometabolic dysfunction, whereas its potential relationship with lipid metabolism during pregnancy remains insufficiently characterized. This study examined whether residential environmental noise exposure was associated with maternal serum lipid profiles in early pregnancy. A retrospective cohort of 12,911 pregnant women receiving prenatal care at a tertiary hospital in Shanghai, China, was analyzed. Residential environmental noise exposure was estimated using a land use regression model with 50 × 50 m spatial resolution. Fasting concentrations of total cholesterol (TC) and triglycerides (TG) were quantified enzymatically, whereas apolipoprotein A1 (ApoA1) and apolipoprotein B (ApoB) were measured by immunoturbidimetric methods. The associations between residential noise and serum lipid parameters were examined using restricted cubic spline regression and segmented multivariable linear regression. Nonlinear exposure-response patterns were observed between noise exposure and TC (exploratory breakpoint, 64.75 dB (A)) and ApoB (exploratory breakpoint, 64.41 dB (A)), whereas no significant associations were observed for TG or ApoA1. Above the respective breakpoints, noise exposure was significantly and positively associated with serum TC, whereas the positive association between ApoB and noise exposure was not statistically significant. Each 5-dB (A) increase in noise exposure corresponded to a 0.130 mmol/L increase in TC (β = 0.130, 95
Women with gestational diabetes mellitus (GDM) are at increased risk of future cardiovascular disease, but whether this risk is accompanied by early alterations in lipid-related and cardiovascular biomarkers during pregnancy remains unclear. We investigated the cardiometabolic biomarker profile associated with GDM during mid-pregnancy. In this observational study within the prospective EpiDG cohort, 295 pregnant women with a positive 50-g O’Sullivan screening test underwent a diagnostic 100-g oral glucose tolerance test (OGTT) at 24–28 weeks of gestation. Of these, 111 met the National Diabetes Data Group (NDDG) diagnostic criteria for GDM and 184 did not meet these criteria and served as screen-positive controls. Conventional lipid parameters, apolipoproteins, lipoprotein(a), high-sensitivity cardiac troponin I (hs-cTnI), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were measured. Multivariable logistic regression and receiver operating characteristic (ROC) analyses were performed. Compared with controls, women with GDM had lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A-I (ApoA-I) concentrations and higher triglyceride levels, triglyceride-to-HDL cholesterol, and triglyceride-to-ApoA-I ratios. ApoA-I (adjusted odds ratio [OR] per 10 mg/dL 0.88, 95
Brain and skin health are becoming global priorities due to the aging population and increased exposure to environmental stressors such as pollution, ultraviolet radiation, and oxidative stress. As lipid-rich organs, the brain and skin are highly susceptible to oxidative damage and serve as sensitive indicators of environmental stress. Lipids play essential roles in maintaining cellular membrane integrity and mediating stress-related signaling pathways. While lipidomics has emerged as a powerful tool to assess biological responses, challenges remain in extracting meaningful biological insights from complex lipid data in relation to cellular systems, molecular pathways, and phenotypic outcomes. This review highlights recent advances in multivariate data analysis, network modeling, and pathway-based tools that enhance the interpretation of lipidomics datasets, and provides an overview of current lipid bioinformatics tools and databases and their limitations. These tools are crucial for biomarker discovery and understanding lipid-mediated mechanisms in skin aging, neurodegeneration, and adaptation to environmental stress. This review also discusses the potential of marine-derived bioactives, such as those from seaweeds and sea cucumbers, alongside plant-derived lipids, in relation to emerging nootropic and cosmeceutical applications. Marine sources such as seaweed and sea cucumber are rich in bioactive lipids, including omega-3 fatty acids, glycolipids, phospholipids, and betaine lipids, which exhibit antioxidant, anti-inflammatory, and regenerative properties, yet remain largely underexplored. Continued innovation in lipid bioinformatics is essential to unlock the full potential of marine bioactives and guide precision strategies for brain and skin health while promoting the sustainable use of marine and plant resources. This review emphasizes the potential of lipid bioinformatics in enabling discovery and functional characterization of bioactive lipids for health-related applications within a systems biology framework. Lipidomics can assess biological responses but is limited by data complexity. Multivariate, pathway, and network analysis enhance lipidomics data interpretation. The brain and skin are lipid-rich organs highly susceptible to oxidative stress. Marine bioactive lipids have potential applications in brain and skin health. Lipid bioinformatics can support biomarker discovery and systems-level insights.
Routine lipid fractions incompletely summarize atherogenic cholesterol and triglyceride-rich dyslipidemia. We developed a Residual Atherogenic Lipid Burden Score (RALBS) integrating complementary information from non-HDL-C, the atherogenic index of plasma (AIP), and HDL-C, and assessed its association with incident stroke. In CHARLS, adults aged at least 45 years without stroke were followed from 2011 to 2020. RALBS combined standardized non-HDL-C, atherogenic index of plasma (AIP), and HDL-C using direction-constrained elastic-net Cox regression. Internal validation used 500 bootstrap samples. Baseline and 2015 landmark cumulative associations were assessed using Cox and competing-risk models. Incremental prediction compared RALBS with simpler lipid markers against a common clinical-plus-LDL-C reference. For external evaluation, the unchanged CHARLS score and prediction coefficients were applied to stroke-free ELSA wave-6 participants and followed through wave 10; five-year discrimination and calibration of absolute-risk estimates were evaluated. The CHARLS exposure cohort included 10,505 participants and 938 incident strokes; the primary complete-case model included 8,670 participants and 796 events. Per development-cohort SD, RALBS was associated with stroke after clinical adjustment (HR 1.15, 95
Elevated concentrations of lipoprotein (a) [Lp(a)] are a well-established risk factor for the development of coronary artery diseases and acute myocardial infarction (AMI). The objective of the present study was to analyze the association between plasma concentrations of Lp(a) and long-term all-cause mortality among individuals with a history of hospitalized AMI. The analysis was based on data from 617 patients with a history of AMI recruited by the Augsburg Myocardial Infarction Registry and examined in a follow-up visit within the scope of the KORA Family Heart Study in 1996 and 1997 (median time between AMI and follow-up examination: 6.2 years). In addition, 545 siblings of the patients were included in the study and underwent examination. The examination included venous blood sampling and a patient interview. Plasma concentrations of Lp(a) were measured using a latex-enhanced immunoassay. Information on vital status was obtained in November 2025 in a comprehensive mortality follow-up [median follow-up time: 18.2 years (IQR: 10.8–27.7)]. Follow-up time was calculated from examination date to date of death or censoring. Kaplan-Meier curves were used to display estimated survival probability of Lp(a) high (≥ 50 mg/dL) and low (< 50 mg/dL) group. Multivariable adjusted Cox regression models with restricted cubic splines were used to analyze the association between Lp(a) concentrations and long-term all-cause mortality after AMI. Kaplan-Meier curves and log rank test (p value: 0.273) demonstrated no differences in long-term all-cause mortality between the high and low Lp(a) group. The multivariable adjusted Cox regression confirmed the absence of a significant association between Lp(a) concentrations and total mortality (HR for the high Lp(a) group: 1.04, 95
