Multiomics Profiling of Plasma Reveals Molecular Alterations Prior to a Diagnosis with Stroke Among Chinese Hypertension Patients.

We aimed to investigate the correlation between plasma proteins and metabolites and the occurrence of future strokes using mass spectrometry and bioinformatics as well as to identify other biomarkers that could predict stroke risk in hypertensive patients. In a nested case-control study, baseline plasma samples were collected from 50 hypertensive subjects who developed stroke and 50 gender-, age- and body mass index-matched controls. Plasma untargeted metabolomics and data independent acquisition-based proteomics analysis were performed in hypertensive patients, and 19 metabolites and 111 proteins were found to be differentially expressed. Integrative analyses revealed that molecular changes in plasma indicated dysregulation of protein digestion and absorption, salivary secretion, and regulation of actin cytoskeleton, along with significant metabolic suppression. C4BPA, Caprolactam, Col15A1, and HBB were identified as predictors of stroke occurrence, and the Support Vector Machines (SVM) model was determined to be the optimal predictive model by integrating six machine-learning classification models. The SVM model showed strong performance in both the internal validation set (area under the curve [AUC]: 0.977, 95% confidence interval [CI]: 0.941-1.000) and the external independent validation set (AUC: 0.973, 95% CI: 0.921-0.999).

Relationship between socioeconomic status and stroke: an observational and network Mendelian randomization study.

BACKGROUND: The relationship between socioeconomic status (SES) and stroke remains controversial, and the underlying mediator is unclear. This study aimed to assess the causal relationship of SES with stroke and its subtypes and to identify potential modifiable risk factors responsible for this relationship. METHODS: The study included 372,437 participants from the UK Biobank. Over an average period of 12.13 years, 6,457 individuals (2.7%) were recorded as having experienced a stroke. Cox proportional hazards model was used to determine the relationship between SES (average annual household income before tax and age at the end of full-time education) and stroke, ischemic stroke, and hemorrhagic stroke. Two-sample Mendelian randomization (MR) was employed to assess the causal relationship between SES and stroke and its subtypes. Furthermore, network MR was utilized to evaluate the potential mediating role of modifiable risk factors for stroke in this causal relationship. RESULTS: After adjusting for factors such as sociodemographic characteristics, health behaviors, health status, and past medical history, participants in the second highest income group showed the lowest risk of stroke, with a hazard ratio (HR) of 0.780 (95% confidence interval [CI]: 0.702-0.866), and for ischemic stroke, the HR was 0.701 (95% CI: 0.618-0.795). Those who completed full-time education at the latest age group(>18 years) had the lowest risk of stroke (HR: 0.906, 95% CI: 0.830-0.988) and ischemic stroke (HR: 0.897, 95% CI: 0.811-0.992). MR analysis showed that higher income and education were both associated with a lower risk of stroke (income: inverse-variance-weighted odds ratio [ORIVW] =0.796, 95% CI: 0.675-0.940, education: ORIVW = 0.631, 95% CI: 0.557-0.716) and ischemic stroke (income: ORIVW = 0.813, 95% CI: 0.684-0.966, education: ORIVW = 0.641, 95% CI: 0.559-0.735). Additionally, hypertension had the highest mediating effect on this relationship. It accounted for 57.12% of the effect of income on stroke, 51.24% on ischemic stroke, and 27% and 24% for education. CONCLUSION: Higher SES was associated with a lower risk of stroke and ischemic stroke, and hypertension had the highest mediating effect on this causal relationship. The results have significant public health implications, emphasizing the importance of early intervention to reduce the risk of stroke in low SES populations.

Identification of Blood Biomarkers in Ischemic Stroke by Integrated Analysis of Metabolomics and Proteomics.

We aimed to uncover the pathological mechanism of ischemic stroke (IS) using a combined analysis of untargeted metabolomics and proteomics. The serum samples from a discovery set of 44 IS patients and 44 matched controls were analyzed using a specific detection method. The same method was then used to validate metabolites and proteins in the two validation sets: one with 30 IS patients and 30 matched controls, and the other with 50 IS patients and 50 matched controls. A total of 105 and 221 differentially expressed metabolites or proteins were identified, and the association between the two omics was determined in the discovery set. Enrichment analysis of the top 25 metabolites and 25 proteins in the two-way orthogonal partial least-squares with discriminant analysis, which was employed to identify highly correlated biomarkers, highlighted 15 pathways relevant to the pathological process. One metabolite and seven proteins exhibited differences between groups in the validation set. The binary logistic regression model, which included metabolite 2-hydroxyhippuric acid and proteins APOM_O95445, MASP2_O00187, and PRTN3_D6CHE9, achieved an area under the curve of 0.985 (95% CI: 0.966-1) in the discovery set. This study elucidated alterations and potential coregulatory influences of metabolites and proteins in the blood of IS patients.

Causal association between plasma metabolites and neurodegenerative diseases.

BACKGROUND: Establishing causal relationships between metabolic biomarkers and neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) is a challenge faced by observational studies. In this study, our aim was to investigate the causal associations between plasma metabolites and neurodegenerative diseases using Mendelian Randomization (MR) methods. METHODS: We utilized genetic associations with 1400 plasma metabolic traits as exposures. We used large-scale genome-wide association study (GWAS) summary statistics for AD and PD as our discovery datasets. For validation, we performed repeated analyses using different GWAS datasets. The main statistical method employed was inverse variance-weighted (IVW). We also conducted enrichment pathway analysis for IVW-identified metabolites. RESULTS: In the discovered dataset, there are a total of 69 metabolites (36 negatively, 33 positively) potentially associated with AD, and 47 metabolites (24 negatively， 23 positively) potentially associated with PD. Among these, 4 significant metabolites overlap with significant metabolites (PIVW < 0.05)in the validation dataset for AD, and 1 metabolite overlaps with significant metabolites in the validation dataset for PD. Three metabolites serve as common potential metabolic markers for both AD and PD, including Tryptophan betaine, Palmitoleoylcarnitine (C16:1), and X-23655 levels. Further pathway enrichment analysis suggests that the SLC-mediated transmembrane transport pathway, involving tryptophan betaine and carnitine metabolites, may represent potential intervention targets for treating AD and PD. CONCLUSION: This study offers novel insights into the causal effects of plasma metabolites on degenerative diseases through the integration of genomics and metabolomics. The identification of metabolites and metabolic pathways linked to AD and PD enhances our comprehension of the underlying biological mechanisms and presents promising targets for future therapeutic interventions in AD and PD.

Methods and clinical biomarker discovery for targeted proteomics using Olink technology.

PURPOSE: This paper is to offer insights for designing research utilizing Olink technology to identify biomarkers and potential therapeutic targets for disease treatment. EXPERIMENTAL DESIGN: We discusses the application of Olink technology in oncology, cardiovascular, respiratory and immune-related diseases, and Outlines the advantages and limitations of Olink technology. RESULTS: Olink technology simplifies the search for therapeutic targets, advances proteomics research, reveals the pathogenesis of diseases, and ultimately helps patients develop precision treatments. CONCLUSIONS: Although proteomics technology has been rapidly developed in recent years, each method has its own disadvantages, so in the future research, more methods should be selected for combined application to verify each other.

A machine learning algorithm based on circulating metabolic biomarkers offers improved predictions of neurological diseases.

BACKGROUND AND AIMS: A machine learning algorithm based on circulating metabolic biomarkers for the predictions of neurological diseases (NLDs) is lacking. To develop a machine learning algorithm to compare the performance of a metabolic biomarker-based model with that of a clinical model based on conventional risk factors for predicting three NLDs: dementia, Parkinson's disease (PD), and Alzheimer's disease (AD). MATERIALS AND METHODS: The eXtreme Gradient Boosting (XGBoost) algorithm was used to construct a metabolic biomarker-based model (metabolic model), a clinical risk factor-based model (clinical model), and a combined model for the prediction of the three NLDs. Risk discrimination (c-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index values were determined for each model. RESULTS: The results indicate that incorporation of metabolic biomarkers into the clinical model afforded a model with improved performance in the prediction of dementia, AD, and PD, as demonstrated by NRI values of 0.159 (0.039-0.279), 0.113 (0.005-0.176), and 0.201 (-0.021-0.423), respectively; and IDI values of 0.098 (0.073-0.122), 0.070 (0.049-0.090), and 0.085 (0.068-0.101), respectively. CONCLUSION: The performance of the model based on circulating NMR spectroscopy-detected metabolic biomarkers was better than that of the clinical model in the prediction of dementia, AD, and PD.

Serum Olink Proteomics-Based Identification of Protein Biomarkers Associated with the Immune Response in Ischemic Stroke.

The immune response is considered essential for pathology of ischemic stroke (IS), but it remains unclear which immune response-related proteins exhibit altered expression in IS patients. Here, we used Olink proteomics to examine the expression levels of 92 immune response-related proteins in the sera of IS patients (n = 88) and controls (n = 88), and we found that 59 of these proteins were differentially expressed. Feature variables were screened from the differentially expressed proteins by the least absolute shrinkage and selection operator (LASSO) and the random forest and by determining whether their proteins had an area under the curve (AUC) greater than 0.8. Ultimately, we identified six potential protein biomarkers of IS, namely, MASP1, STC1, HCLS1, CLEC4D, PTH1R, and PIK3AP1, and established a logistic regression model that used these proteins to diagnose IS. The AUCs of the models in the internal validation and the test set were 0.962 (95% confidence interval (CI): 0.895-1.000) and 0.954 (95% CI: 0.884-1.000), respectively, and the same protein detection method was performed in an external independent validation set (AUC: 0.857 (95% CI: 0.801-0.913)). These proteins may play a role in immune regulation via the C-type lectin receptor signaling pathway, the PI3K-AKT signaling pathway, and the B-cell receptor signaling pathway.

Association between sleep pattern and incidence of hypertension: A prospective cohort study of older adult participants in the Chinese longitudinal healthy longevity survey.

BACKGROUND: The relationship between sleep duration or sleep quality and the risk of hypertension has been previously examined. However, little is known regarding the association between sleep duration and quality and the risk of developing hypertension in the older adult Chinese population. METHODS: The sleep patterns of 5683 participants without hypertension at baseline from the Chinese Longitudinal Healthy Longevity Survey were analyzed. Cox proportional hazard models were used to study the associations between sleep patterns and hypertension. RESULTS: It was found that 1712 (30.12%) of the 5683 participants had an unhealthy sleep pattern. After an average follow-up of 3.31 years, 1350 of the participants had hypertension. Compared with participants with an unhealthy sleep pattern, those with a healthy sleep pattern had a 20% (hazard ratio = 0.80, 95% confidence interval = 0.67-0.94, P = = 0.008) lower risk of incident hypertension in the fully adjusted models. In addition, an approximately linear dose-response association was observed between sleep duration and the incidence of hypertension (P for non-linear =0.43). Subgroup analyses demonstrated significant interactions between age and sleep pattern concerning hypertension (P for interaction <0.05). Several sensitivity analyses were conducted, and the obtained findings were similar to the main results. CONCLUSIONS: A healthy sleep pattern, comprising an adequate sleep duration and good sleep quality, can help reduce hypertension risk. Thus, a healthy sleep pattern is crucial to decreasing hypertension in older Chinese adults in a rapidly aging society.

Plasma lipidomic profiling reveals six candidate biomarkers for the prediction of incident stroke in patients with hypertension.

INTRODUCTION: The burden of stroke in patients with hypertension is very high, and its prediction is critical. OBJECTIVES: We aimed to use plasma lipidomics profiling to identify lipid biomarkers for predicting incident stroke in patients with hypertension. METHODS: This was a nested case-control study. Baseline plasma samples were collected from 30 hypertensive patients with newly developed stroke, 30 matched patients with hypertension, 30 matched patients at high risk of stroke, and 30 matched healthy controls. Lipidomics analysis was performed by ultrahigh-performance liquid chromatography-tandem mass spectrometry, and differential lipid metabolites were screened using multivariate and univariate statistical methods. Machine learning methods (least absolute shrinkage and selection operator, random forest) were used to identify candidate biomarkers for predicting stroke in patients with hypertension. RESULTS: Co-expression network analysis revealed that the key molecular alterations of the lipid network in stroke implicate glycerophospholipid metabolism and choline metabolism. Six lipid metabolites were identified as candidate biomarkers by multivariate statistical and machine learning methods, namely phosphatidyl choline(40:3p)(rep), cholesteryl ester(20:5), monoglyceride(29:5), triglyceride(18:0p/18:1/18:1), triglyceride(18:1/18:2/21:0) and coenzyme(q9). The combination of these six lipid biomarkers exhibited good diagnostic and predictive ability, as it could indicate a risk of stroke at an early stage in patients with hypertension (area under the curve = 0.870; 95% confidence interval: 0.783-0.957). CONCLUSIONS: We determined lipidomic signatures associated with future stroke development and identified new lipid biomarkers for predicting stroke in patients with hypertension. The biomarkers have translational potential and thus may serve as blood-based biomarkers for predicting hypertensive stroke.

Identification of Serum Biomarkers of Ischemic Stroke in a Hypertensive Population Based on Metabolomics and Lipidomics.

Hypertensive individuals are at a high risk of stroke, and thus, prevention of stroke in hypertensive patients is essential. Metabolomics and lipidomics can be used to identify diagnostic biomarkers and conduct early assessments of stroke risk in hypertensive populations. In this study, serum samples were collected from 30 hypertensive ischemic stroke (IS), 30 matched hypertensive and 30 matched healthy participants. Metabolomics and lipidomics analyses were conducted via liquid chromatography-tandem mass spectrometry, and the data were analyzed using multivariate and univariate statistical methods. A random forest algorithm and binary logistic regression were used to screen the biomarkers and establish diagnostic model. We detected 21 differential metabolites and 38 differential lipids between the hypertensive IS and healthy group. Moreover, we found 18 differential metabolites and 31 differential lipids between the hypertensive IS and hypertension group. In particular, the following seven metabolites or lipids distinguished the hypertensive IS from the healthy group: 4-hydroxyphenylpyruvic acid, cafestol, phosphatidylethanolamine (PE) (18:0p/18:2), PE (16:0e/20:4), (O-acyI)-1-hydroxy fatty acid (36:3), PE (16:0p/20:3) and PE (18:1p/18:2) (rep). The following seven biomarkers distinguished the hypertensive IS from the hypertension group: diglyceride (DG) (20:1/18:2), PE (18:0p/18:2), PE (16:0e/22:5), phosphatidylcholine (40:7), dimethylphosphatidylethanolamine (50:3), DG (18:1/18:2), and 4-hydroxyphenylpyruvic acid. The aforementioned panels had good diagnostic and predictive ability for hypertensive IS. Our study determines the metabolomic and lipidomic profiles of hypertensive IS patients and thereby identifies potential biomarkers of the presence of IS in hypertensive populations.

Proteomic advance of ischemic stroke: preclinical, clinical, and intervention.

Ischemic stroke (IS) is the most common type of stroke and is characterized by high rates of mortality and long-term injury. The prediction and early diagnosis of IS are therefore crucial for optimal clinical intervention. Proteomics has provided important techniques for exploring protein markers associated with IS, but there has been no systematic evaluation and review of research that has used these techniques. Here, we review the differential proteins that have been found in cell- and animal- based studies and clinical trials of IS in the past 10 years; determine the key pathological proteins that have been identified in clinical trials; summarize the target proteins affected by interventions aimed at treating IS, with a focus on traditional Chinese medicine treatments. Overall, we clarify findings and problems that have been identified in recent proteomics research on IS and provide suggestions for improvements in this area. We also suggest areas that could be explored for determining the pathogenesis and developing interventions for IS.

Global Burden of Cardiovascular Disease from 1990 to 2019 Attributable to Dietary Factors.

BACKGROUND: Although dietary factors play a crucial role in the incidence of cardiovascular disease (CVD), the specific dietary risk factors vary across regions and require further investigation. OBJECTIVE: We aimed to analyze the burden of CVD due to different dietary factors by sex, age, and sociodemographic index (SDI) for 204 countries and territories between 1990 and 2019. METHODS: Data were extracted from the Global Burden of Disease 2019 and analyzed to determine population attributable fractions (PAFs), mortality, disability-adjusted life years (DALYs), and trends thereof, for CVDs attributable to dietary risk factors from 1990 to 2019. We used a generalized linear model with a Gaussian distribution to calculate the estimated annual percentage changes (EAPCs) in CVD mortality and DALY rates attributable to dietary risk factors. We also used a comparative risk-assessment framework to estimate CVD mortality and DALYs attributable to dietary risk factors. RESULTS: Approximately 40% of CVD mortality and DALY rates were attributable to dietary risk factors, with high-sodium intake, low whole grain intake, and low legume intake being the greatest dietary risk factors globally. Moreover, high SDI regions had the highest PAFs for CVD mortality and DALYs associated with high red and processed meat intake, middle SDI regions had the highest PAFs with high-sodium intake, and low SDI regions had the highest PAFs with low fruit and vegetable intake. The highest PAFs for CVD mortality and DALYs were associated with low whole grain intake in 13 and 9 regions, respectively. CONCLUSION: Reducing sodium intake and increasing whole grain and legume intake should be the top priority worldwide for improving regional diets and thereby decreasing CVD burdens. Other priorities should be set for regions with different SDIs, depending on the predominant dietary risk factors for CVDs in the respective regions.

Projected Global Trends in Ischemic Stroke Incidence, Deaths and Disability-Adjusted Life Years From 2020 to 2030.

BACKGROUND: We projected global trends in ischemic stroke from 2020 to 2030 according to age, sex, and socio-demographic index (SDI) quintile. METHODS: Estimated annual percentage changes (EAPCs) were used to project trends in the incidence of deaths from and disability-adjusted life years (DALYs) due to ischemic stroke between 2020 and 2030. EAPCs were computed using generalized additive models and data from the Global Burden of Disease study during the 1990 to 2019 period. RESULTS: The global age-standardized incidence rate of ischemic stroke was projected to increase to 89.32 per 100 000 population in 2030 (EAPC=0.89), whereas the associated global age-standardized death and DALY rates were projected to decrease to 18.28 (EAPC, -3.58) and 500.37 per 100 000 (EAPC=-1.75), respectively, in 2030. The projections indicated a higher age-standardized incidence rate of ischemic stroke among women than among men in 2030 (90.70 versus 87.64 per 100 000). The incidence rate of ischemic stroke was projected to increase across all age groups and SDI quintiles between 2020 and 2030. At the national level, the greatest increase in the age-standardized incidence rate of ischemic stroke between 2020 and 2030 was projected to occur in Cyprus (EAPC=4.16), followed by Palestine (EAPC=3.50) and South Africa (EAPC=2.64). Additionally, the projections suggested increases in the age-standardized death and DALY rates due to ischemic stroke for countries in low-SDI quintiles (EAPC=3.68 and EAPC=5.30, respectively). CONCLUSIONS: The projections indicated that the incidence rate of ischemic stroke will increase both sexes, all age groups, and all SDI quintiles and in some countries between 2020 and 2030. Furthermore, countries with a low SDI should be aware of potential increases in the age-standardized death and DALY due to ischemic stroke.

Triglyceride-glucose index and triglyceride to high-density lipoprotein cholesterol ratio as potential cardiovascular disease risk factors: an analysis of UK biobank data.

BACKGROUND: The triglyceride-glucose (TyG) index and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, two simple surrogate indicators of insulin resistance, have been demonstrated to predict cardiovascular disease (CVD). However, very few studies have investigated their associations with CVD in European populations. METHODS: A total of 403,335 participants from the UK Biobank with data for TyG index and TG/HDL-C ratio and free from CVD at baseline were included. Cox models were applied to evaluate the association between TyG index and TG/HDL-C ratio and incident CVD. Mediation analyses were performed to evaluate the contribution of prevalent diabetes, hypertension, and dyslipidemia to observed associations. RESULTS: During a median follow-up of 8.1 years, 19,754 (4.9%) individuals developed CVD, including 16,404 (4.1%) cases of CHD and 3976 (1.0%) cases of stroke. The multivariable-adjusted hazard ratios of total CVD in higher quartiles versus the lowest quartiles were 1.05, 1.05, and 1.19, respectively, for TyG index, and 1.07, 1.13, and 1.29, respectively, for TG/HDL-C ratio. There were significant trends toward an increasing risk of CVD across the quartiles of TyG index and TG/HDL-C ratio. In mediation analyses, dyslipidemia, type 2 diabetes, and hypertension explained 45.8%, 27.0%, and 15.0% of TyG index's association with CVD, respectively, and 40.0%, 11.8%, and 13.3% of TG/HDL-C ratio's association with CVD, respectively. CONCLUSIONS: Elevated baseline TyG index and TG/HDL-C ratio were associated with a higher risk of CVD after adjustment for the well-established CVD risk factors. These associations were largely mediated by greater prevalence of dyslipidemia, type 2 diabetes, and hypertension.

Global Burden of Ischemic Stroke in Young Adults in 204 Countries and Territories.

BACKGROUND AND OBJECTIVES: To estimate the rates of incidence, death, and disability-adjusted life years (DALYs) of ischemic stroke in young adults aged 15-49 years and the relevant risk factors by sex, age group, and sociodemographic index (SDI) in 204 countries and territories. METHODS: Data from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) 2019 study were used. The estimated annual percentage changes (EAPCs) were calculated to evaluate the temporal trends from 1990 to 2019. We also estimated the risk factors contributing to DALYs resulting from ischemic stroke. RESULTS: From 1990 to 2019, the global age-standardized incidence (EAPC = -0.97), death (EAPC = -0.11), and DALYs rates (EAPC = -0.55) of ischemic stroke in young adults decreased. The largest increases in age-standardized incidence, death, and DALYs rates were observed in the low and low-middle SDI quintiles. At the regional level, North Africa and the Middle East and Southeast Asia showed the largest increases in the age-standardized incidence, death, and DALYs rates of ischemic stroke. The age-standardized incidence rate was higher among young women than among young men in 2019. Globally, a high environmental temperature, high body mass index (BMI), and a high fasting plasma glucose contributed to the largest increases in age-standardized DALYs rates between 1990 and 2019. In the same period, the largest increases in the age-standardized DALYs rates in high-SDI and low-SDI regions were attributable to high environmental temperatures and alcohol use, respectively. DISCUSSION: The burden of ischemic stroke in young adults continues to increase in low-SDI regions such as North Africa and the Middle East and Southeast Asia. There were differences in the primary risk factors related to the burden of ischemic stroke in different SDI regions. Targeted implementation of cost-effective policies and interventions is an urgent need to reduce the burden of ischemic stroke in young adults.

Metabolomics of ischemic stroke: insights into risk prediction and mechanisms.

Ischemic stroke (IS) is the most prevalent type of stroke. The early diagnosis and prognosis of IS are crucial for successful therapy and early intervention. Metabolomics, a tool in systems biology based on several innovative technologies, can be used to identify disease biomarkers and unveil underlying pathophysiological processes. Accordingly, in recent years, an increasing number of studies have identified metabolites from cerebral ischemia patients and animal models that could improve the diagnosis of IS and prediction of its outcome. In this paper, metabolomic research is comprehensively reviewed with a focus on describing the metabolic changes and related pathways associated with IS. Most clinical studies use biofluids (e.g., blood or plasma) because their collection is minimally invasive and they are ideal for analyzing changes in metabolites in patients of IS. We review the application of animal models in metabolomic analyses aimed at investigating potential mechanisms of IS and developing novel therapeutic approaches. In addition, this review presents the strengths and limitations of current metabolomic studies on IS, providing a reference for future related studies.

Associations of Serum Biomarkers of Fruit and Vegetable Intake With the Risk of Cause-Specific Mortality and All-Cause Mortality: A National Prospective Cohort Study.

Objective: The purpose of this study was to evaluate the associations of serum biomarkers of fruit and vegetable intake (vitamin C and carotenoids) with cause-specific mortality and all-cause mortality in a nationally representative sample of US adults. Methods: We analyzed data from 12,530 participants from the National Health and Nutrition Examination Survey III (1988-1994). The Cox proportional hazards models with restricted cubic spline were used for the analysis. Results: During 246,027 person-years of follow-up, 4,511 deaths occurred, including 1,395 deaths from cardiovascular disease, 1,072 deaths from heart disease, 323 deaths from cerebral disease, and 954 deaths from cancer. The serum vitamin C was significantly associated with the cancer and all-cause mortality, with hazard ratios (HRs) (95% CIs) for each one SD of 0.80 (0.71-0.91) and 0.91 (0.86-0.96). The serum alpha-carotene was significantly associated with the cancer mortality, with HRs (95% CIs) of 0.70 (0.54-0.90), 0.68 (0.48-0.95), 0.64 (0.43-0.95), and 0.44 (0.33-0.60) for comparisons of groups 2-5 with group 1 in model 2, respectively. The change for each one SD in the composite biomarker score, equivalent to a 0.483 times/month difference in total fruits and vegetables intake, gave an HR of 0.79 (0.69-0.90) for cancer mortality. Conclusion: Inverse associations were found between serum vitamin C, carotenoids, and composite biomarker score and outcomes expect for cerebral disease, heart disease, and cardiovascular disease mortality. This finding supports an increase in dietary fruit and vegetable intake as a primary prevention strategy for cancer and all-cause mortality.

Global Burden of Vitamin A Deficiency in 204 Countries and Territories from 1990-2019.

Vitamin A deficiency (VAD) is one of the important public health issues worldwide. However, a detailed understanding of the incidence and disability-adjusted life years (DALYs) due to VAD in recent years is lacking. We aimed to estimate the incidence and DALYs of VAD at global, regional, and national levels in terms of sex, age, and socio-demographic index (SDI). Using data from the 2019 Global Burden of Disease (GBD) study, the estimated annual percentage change (EAPC) was measured to assess trends in the age-standardized incidence and DALY rates from 1990 to 2019. The global age-standardized incidence and DALY rates of VAD decreased with an EAPC of −3.11% (95% confidence interval (CI): −3.24% to −2.94%) and −2.18% (95% CI: −2.38% to −1.93%), respectively. The age-standardized incidence and DALY rates decreased least in low-SDI regions, which had the highest age-standardized incidence and DALY rates of all SDI regions. Sub-Saharan Africa, especially central sub-Saharan Africa, had the highest age-standardized incidence and DALY rates in 2019. At the national level, Somalia and Niger had the highest age-standardized incidence and DALY rates. The age-standardized incidence and DALY rates were higher in males than in females. Younger children, especially those aged < 5 years in low-SDI regions, had a higher VAD burden than other age groups. Although the global burden of VAD has decreased, future work should aim to improve the prevention and treatment strategies for VAD, particularly in children aged < 5 years in countries and territories with low SDI values, such as sub-Saharan Africa.

Association of dietary intake of branched-chain amino acids with long-term risks of CVD, cancer and all-cause mortality.

OBJECTIVES: We aimed to investigate the associations between dietary branched-chain amino acids (BCAA) intake and long-term risks of CVD, cancer and all-cause mortality in nationwide survey participants aged ≥ 18. DESIGN: This was a prospective cohort study. Dietary intakes of BCAA (leucine, isoleucine and valine) were determined from the total nutrient intake document. The main outcomes were CVD, cancer and all-cause mortality. SETTING: A nationally representative sample of US adults were recruited by the National Center for Health Statistics (NCHS) from 1988 to 1994. PARTICIPANTS: A total of 14 397 adults aged ≥ 18 who participated in the United States National Health and Nutrition Examination Survey III (NHANES III) were included. RESULTS: During 289 406 person-years of follow-up, we identified 4219 deaths, including 1133 from CVD and 926 from cancer. After multivariate adjustment, the hazard ratios (95 % confidence intervals) of all-cause mortality in the highest dietary BCAA and isoleucine intake quintile (reference: lowest quintiles) were 0·68 (0·48, 0·97) and 0·68 (0·48, 0·97), respectively. Each one-standard-deviation increase in total dietary BCAA or isoleucine intake was associated with an 18 % or 21 % decrease in the risk of all-cause mortality, respectively. The serum triglyceride (TAG) concentration was found to modify the association between the dietary BCAA intake and all-cause mortality (Pfor interaction = 0·008). CONCLUSIONS: In a nationally representative cohort, higher dietary intakes of BCAA and isoleucine were independently associated with a lower risk of all-cause mortality, and these associations were stronger in participants with higher serum TAG concentrations.

Multimorbidity study with different levels of depression status.

OBJECTIVE: Depression is one of the leading causes of disability burden and frequently co-occurs with multiple chronic diseases, but limited research has yet evaluated the correlation between multimorbidity and depression status by sex and age. METHODS: 29303 adults from 2005-2016 National Health and Nutrition Examination Survey were involved in the study. The validated Patient Health Questionnaire (PHQ-9) was used to assess depression status. The linear trend of the prevalence of multimorbidity was tested by logistic regressions, which was visualized by the weighted network. Gamma coefficient (γ) was used to evaluate the correlation between multimorbidity and depression status. RESULTS: The prevalence of multimorbidity in participants with no depression, mild depression, moderate depression and severe depression was 52.1%, 63.0%, 68.4% and 76.1%, respectively (p for trend < 0.001). In network analysis, the absolute network density increased with the levels of depression status (from 4.54 to 15.04). Positive correlation was identified between multimorbidity and depression status (γ=0.21, p<0.001), and the correlation was different by sex and age, where it was stronger in women than men (females: γ=0.23, males: γ=0.16), and stronger in the young and the middle-age (young: γ=0.30, middle-age: γ=0.29, old: γ=0.22). LIMITATIONS: This is a cross-sectional study and thus we cannot draw firm conclusions on causal correlations. CONCLUSIONS: Positive correlation between multimorbidity and depression status was identified, where the number of multimorbidity increased with the levels of depression status, especially in females, the young and the middle-age.