Polygenic risk scores for mood and related disorders and environmental factors: Interaction effects on wellbeing in the UK biobank

Mood disorders have a genetic and environmental component and interactions (GxE) on the risk of psychiatric diseases have been investigated. The same GxE interactions may affect wellbeing measures, which go beyond categorical diagnoses and reflect the health-disease continuum. We evaluated GxE effects in the UK Biobank, considering as outcomes subjective wellbeing (feeling good and functioning well) and objective measures (education and income). We estimated the polygenic risk scores (PRSs) of major depressive disorder, bipolar disorder, schizophrenia, and attention deficit hyperactivity disorder. Stressful/traumatic events during adulthood or childhood were considered as E variables, as well as social support. The addition of the PRSxE interaction to PRS and E variables was tested in linear or multinomial regression models, adjusting for confounders. We included 33 k-380 k participants, depending on the variables considered. Most PRSs and E factors showed additive effects on outcomes, with effect sizes generally 3-5 times larger for E variables than PRSs. We found some interaction effects, particularly when considering recent stress, history of a long illness/disability/infirmity, and social support. Higher PRSs increased the negative effects of stress on wellbeing, but they also increased the positive effects of social support, with interaction effects particularly for the outcomes health satisfaction, loneliness, and income (p < Bonferroni corrected threshold of 1.92e-4). PRSxE terms usually added ∼0.01-0.02% variance explained to the corresponding additive model. PRSxE effects on wellbeing involve both positive and negative E factors. Despite small variance explained at the population level, preventive/therapeutic interventions that modify E factors could be beneficial at the individual level.

A narrative systematic review of associations and temporality between use of methamphetamine, ecstasy/MDMA, or cocaine with anxiety or depressive symptoms

OBJECTIVE

Anxiety and depression are prevalent mental health problems in people who use illicit stimulants. Improved understanding of the temporal relationship between methamphetamine, ecstasy/MDMA, or cocaine use with anxiety or depression informs public health interventions and treatment options for those experiencing this co-occurrence. This narrative systematic review sought to examine associations and temporality between the use of methamphetamine, ecstasy/MDMA, or cocaine, with anxiety or depressive symptoms. Method Systematic searches of 4 electronic databases were conducted up to August 2023. Study eligibility included the measurement of anxiety and/or depressive symptoms, and frequency of illicit stimulant use (methamphetamine, cocaine, or ecstasy/MDMA) at two separate time points, with data analysis of the association between these variables. The Joanna Briggs Critical Appraisal Checklist was utilised to assess quality. Data was extracted, and a narrative synthesis incorporating an eight-criteria framework to assess associations was conducted. Results 4432 studies were screened for eligibility; 11 studies (3 RCTs and 8 prospective cohort studies) were included. Evidence for an association between depressive symptoms and methamphetamine use was demonstrated in six studies, with temporal evidence in three studies supporting methamphetamine use preceding depressive symptoms. Three studies reported an association between cocaine use and depressive symptoms. Evidence for associations with any of the illicit stimulants and anxiety symptoms was lacking.

CONCLUSIONS

There was some evidence to support a case for temporality, particularly for methamphetamine use and depressive symptoms. Investing in longitudinal studies is pivotal to understanding the dynamic and reciprocal relationship between illicit stimulant use and anxiety or depressive symptoms. A limitation of the study was the variation in the measurement and analysis of outcomes.

Association between weekend catch-up sleep and depressive symptoms in American adults: Finding from NHANES 2017-2020

BACKGROUND

The effect of weekend catch-up sleep (WCS) on depressive symptoms is inconsistent among different populations, with limited evidence in Americans. Therefore, we aimed to investigate the association between WCS and depressive symptoms in American adults.

METHODS

We recruited 7719 participants from the National Health and Nutrition Examination Survey (NHANES) 2017-2020. Information on sleep duration and depressive symptoms were assessed by several self-reported questions and Patient Health Questionnaire-9 (PHQ-9), respectively. Then, WCS duration was calculated as weekend sleep duration minus weekday sleep duration, and WCS was further defined as WCS duration >0 h. Survey designed regression analyses were used to assess the association of WCS and depressive symptoms.

RESULTS

In fully adjusted multivariate logistic regression models, the odds ratio (95 % confidence interval) for depressive symptoms and the β (95 % confidence interval) for PHQ-9 score in response to WCS were 0.746 (0.462, 1.204; P = 0.218) and -0.429 (-0.900, 0.042; P = 0.073), respectively. Besides, the smooth relationship presented L-shaped, and only WCS duration of 0-2 h was statistically significantly associated with depressive symptoms or PHQ-9 score. Subgroup analyses showed that the negative associations were stronger among men, adults younger than 65 years, and those with short weekday sleep duration (P for interaction <0.05).

LIMITATIONS

The cross-sectional design limits the capability for causal relationship between WCS and depressive symptoms.

CONCLUSIONS

This study suggests that moderate WCS is associated with reduced odds of depressive symptoms, which provides additional epidemiological evidence for the effects of sleep on depressive symptoms.

Global burden of depression or depressive symptoms in children and adolescents: A systematic review and meta-analysis

BACKGROUND

Depression is the leading cause of health-related disability. A proportion of depression cases begin in childhood and increase dramatically during adolescence. This systematic review and meta-analysis aimed to estimate the global prevalence of depression or depressive symptoms in children and adolescents and explore the temporal and regional distribution of depression or depressive symptoms.

METHODS

This systematic review and meta-analysis identified peer-reviewed literature published through April 8, 2023, using the MEDLINE, Embase and APA PsycINFO databases, supplemented by reverse reference searches. Observational studies published in English and based on validated instruments with prevalence data on depression or depressive symptoms in children and adolescents aged ≤18 years were eligible. Random-effects meta-analysis and meta-regression analysis were performed using R software.

RESULTS

This systematic review and meta-analysis included a total of 96 studies (29 countries, 528,293 participants) published between 1989 and 2022. The pooled prevalence of mild-to-severe, moderate-to-severe, and major depression were 21.3 % (95%CI, 16.7 %-26.7 %), 18.9 % (95%CI, 14.6 %-24.2 %), and 3.7 % (95%CI, 2.7 %-5.1 %) respectively. Meta-regression analysis showed that from 1989 to 2022, the prevalence of mild-to-severe and moderate-to-severe depression increased over time (P = 0.002, P = 0.034, respectively), but the prevalence of major depression did not change significantly (P = 0.636).

LIMITATIONS

Only English articles were included. There was significant heterogeneity across the included studies. The studies included were mostly based on self-report scales to assess depressive symptoms.

CONCLUSION

In this systematic review, about one in five children and adolescents globally suffered from depression or had depressive symptoms, and this proportion was increasing over time.

The effect of maternal prenatal tobacco smoking on offspring academic achievement: A systematic review and meta-analysis

BACKGROUND

Previous epidemiological studies examining the prospective association between maternal prenatal tobacco smoking and offspring academic achievement have reported conflicting results. Therefore, this systematic review and meta-analysis was conducted to examine the magnitude and consistency of association reported by those studies.

METHODS

This systematic review and meta-analysis was guided by the PRISMA protocol. Relevant epidemiological studies on the topic were extracted from four main databases (PubMed/Medline, Embase, PsycINFO, and Scopus). The Newcastle-Ottawa Scale (NOS) was used to appraise the methodological quality of the included studies. We conducted a narrative assessment of the studies that did not report effect estimates. Inverse variance-weighted random effect meta-analysis was used to combine studies reporting effect sizes to estimate pooled adjusted odds ratio with 95% confidence intervals (95% CI). The review was prospectively registered in PROSPERO (CRD42022350901).

RESULTS

Nineteen observational studies, published between 1973 and 2021 with a total of 1.25 million study participants were included in the final review. Of these, fifteen studies (79 %) reported reduced academic achievement in offspring exposed to maternal prenatal tobacco smoking. The eight primary studies (sample size = 723,877) included in the meta-analysis together suggested a 49 % higher risk of reduced academic achievement in offspring exposed to maternal prenatal tobacco smoking when compared to non-exposed offspring (Pooled odds ratio = 1.49, 95 % CI:1.17-1.91).

CONCLUSION

Our review found a positive association between maternal prenatal tobacco smoking and offspring reduced academic achievement. However, variation in the adjustment of potential confounders and significant heterogeneity across included studies limited more conclusive inference. Mechanistic studies to identify causal pathways and specific academic impacts are needed to inform targeted developmental programs to assist child learning and academic performance.

Night shift work, genetic risk, and the risk of depression: A prospective cohort study

BACKGROUND

Genetic factors and night shift work both contribute to the risk of depression, but whether the association of night shift work with depression varies by genetic predisposition remains unclear.

OBJECTIVES

To assess whether night shift work is associated with a higher risk of depression regardless of genetic predisposition.

METHODS

We used data from the UK biobank of 247,828 adults aged 38-71 free of depression at baseline from March 13, 2006, to October 1, 2010. Genetic predisposition to depression was assessed using polygenic risk scores (PRS) weighted sums of genetic variant indicator variables and classified as low (lowest tertile), intermediate (tertile 2), and high (highest tertile). Night shift work exposures were collected using a touchscreen questionnaire and were divided into four categories.

RESULTS

After a median follow-up of 12.7 years, 7315 participants developed depression. Compared with day workers, HRs (95 % CIs) of depression were 1.28 (1.19-1.38) for shift work, but never or rarely night shifts, 1.32 (1.20-1.45) for irregular night shifts, and 1.20 (1.07-1.34) for permanent night shifts. Considering lifetime employment and compared with never shift workers, >8 nights/month (HR: 1.40; 95 % CI: 1.19-1.66) and <10 years (HR: 1.30; 95 % CI: 1.09-1.54) of night shift work were associated with a higher risk of depression. In joint effect analyses, compared to participants with low genetic predisposition and day workers, the HRs (95 % CIs) of depression were 1.49 (1.32-1.69) in those with high genetic predisposition and shift work, but never or rarely night shifts, and 1.36 (1.20-1.55) for those with high genetic predisposition and irregular/permanent night shifts. In addition, there was neither multiplicative nor additive interaction between genetic predisposition and night shift work on the risk of depression.

CONCLUSIONS

Night shift work was associated with an increased risk of depression regardless of genetic risk.

Exercise-with-melatonin therapy improves sleep disorder and motor dysfunction in a rat model of ischemic stroke

JOURNAL/nrgr/04.03/01300535-202406000-00038/inline-graphic1/v/2023-10-30T152229Z/r/image-tiff

Exercise-with-melatonin therapy has complementary and synergistic effects on spinal cord injury and Alzheimer’s disease, but its effect on stroke is still poorly understood. In this study, we established a rat model of ischemic stroke by occluding the middle cerebral artery for 60 minutes. We treated the rats with exercise and melatonin therapy for 7 consecutive days. Results showed that exercise-with-melatonin therapy significantly prolonged sleep duration in the model rats, increased delta power values, and regularized delta power rhythm. Additionally, exercise-with-melatonin therapy improved coordination, endurance, and grip strength, as well as learning and memory abilities. At the same time, it led to higher hippocampal CA1 neuron activity and postsynaptic density thickness and lower expression of glutamate receptor 2 than did exercise or melatonin therapy alone. These findings suggest that exercise-with-melatonin therapy can alleviate sleep disorder and motor dysfunction by increasing glutamate receptor 2 protein expression and regulating hippocampal CA1 synaptic plasticity.

Assessing remission in major depressive disorder using a functional-structural data fusion pipeline: A CAN-BIND-1 study

Neural network-level changes underlying symptom remission in major depressive disorder (MDD) are often studied from a single perspective. Multimodal approaches to assess neuropsychiatric disorders are evolving, as they offer richer information about brain networks. A FATCAT-awFC pipeline was developed to integrate a computationally intense data fusion method with a toolbox, to produce a faster and more intuitive pipeline for combining functional connectivity with structural connectivity (denoted as anatomically weighted functional connectivity (awFC)). Ninety-three participants from the Canadian Biomarker Integration Network for Depression study (CAN-BIND-1) were included. Patients with MDD were treated with 8 weeks of escitalopram and adjunctive aripiprazole for another 8 weeks. Between-group connectivity (SC, FC, awFC) comparisons contrasted remitters (REM) with non-remitters (NREM) at baseline and 8 weeks. Additionally, a longitudinal study analysis was performed to compare connectivity changes across time for REM, from baseline to week-8. Association between cognitive variables and connectivity were also assessed. REM were distinguished from NREM by lower awFC within the default mode, frontoparietal, and ventral attention networks. Compared to REM at baseline, REM at week-8 revealed increased awFC within the dorsal attention network and decreased awFC within the frontoparietal network. A medium effect size was observed for most results. AwFC in the frontoparietal network was associated with neurocognitive index and cognitive flexibility for the NREM group at week-8. In conclusion, the FATCAT-awFC pipeline has the benefit of providing insight on the 'full picture' of connectivity changes for REMs and NREMs while making for an easy intuitive approach.

NSTEMI mortality and hospital outcomes in patients with atrial fibrillation: A propensity score-matched analysis

Background

Atrial fibrillation (AF) is associated with increased cardiovascular mortality. Data regarding the relationship between coronary artery disease (CAD) and AF is mixed. It is uncertain if AF directly increases the risk for future coronary events and if such patients are appropriately evaluated for CAD.

Methods

This cross-sectional study was performed on hospitalized patients with NSTEMI and concurrent AF in 2019 using the National Inpatient Sample. In-hospital mortality, rates of diagnostic cardiac angiography, percutaneous coronary intervention, ventricular tachycardiac (VT), ventricular fibrillation (VF), cardiogenic shock, cardiac arrest, length of stay (LOS), and total hospitalization charges were studied.

Results

A total of 433,965 patients met inclusion criteria (169,725 females [39.1 %], 307,985 Caucasian [71 %], 51,570 African American [11.8 %], 37,265 Hispanic [8.6 %]; mean [SD] age, 67.9 [6.2] years). 86,200 (19.8 %) patients with NSTEMI had AF, including 32,775 (38 %) female patients before propensity matching. Patients with NSTEMI and AF had increased odds of mortality (adjusted Odds ratio, 1.32; CI, 1.21-1.43; p < 0.001). AF patients were less likely to undergo diagnostic coronary angiography and PCI and had higher odds of VT, VF, cardiogenic shock, cardiac arrest, tracheal intubation, mechanical ventilation, increased LOS, and higher hospital charges than those without AF.

Conclusion

AF was independently associated with increased mortality and serious cardiac complications in patients admitted with NSTEMI.

Innate and adaptive immunity in acute myocarditis

Acute myocarditis is an acute inflammatory cardiomyopathy associated with cardiac damage triggered by a virus or a pathological immune activation. It may present with a wide range of clinical presentations, ranging from mild symptoms to severe forms like fulminant myocarditis, characterized by hemodynamic compromise and cardiogenic shock. The immune system plays a central role in the pathogenesis of myocarditis. In fact, while its function is primarily protective, aberrant responses can be detrimental. In this context, both innate and adaptive immunity play pivotal roles; notably, the innate system offers a non-specific and immediate defense, while the adaptive provides specialized protection with immunological memory. However, dysregulation in these systems can misidentify cardiac tissue, triggering autoimmune reactions and possibly leading to significant cardiac tissue damage. This review highlights the importance of innate and adaptive immune responses in the progression and treatment of acute myocarditis.

The importance of LDL-C lowering in atherosclerotic cardiovascular disease prevention: Lower for longer is better

Cumulative exposure to low-density lipoprotein cholesterol (LDL-C) is a key driver of atherosclerotic cardiovascular disease (ASCVD) risk. An armamentarium of therapies to achieve robust and sustained reduction in LDL-C can reduce ASCVD risk. The gold standard for LDL-C assessment is ultracentrifugation but in routine clinical practice LDL-C is usually calculated and the most accurate calculation is the Martin/Hopkins equation. For primary prevention, consideration of estimated ASCVD risk frames decision making regarding use of statins and other therapies, and tools such as risk enhancing factors and coronary artery calcium enable tailoring of risk assessment and decision making. In patients with diabetes, lipid lowering therapy is recommended in most patients to reduce ASCVD risk with an opportunity to tailor therapy based on other risk factors. Patients with primary hypercholesterolemia and familial hypercholesterolemia (FH) with baseline LDL-C greater than or equal to 190 mg/dL are at elevated risk, and LDL-C lowering with high-intensity statin therapy is often combined with non-statin therapies to prevent ASCVD. Secondary prevention of ASCVD, including in patients with prior myocardial infarction or stroke, requires intensive lipid lowering therapy and lifestyle modification approaches. There is no established LDL-C level below which benefit ceases or safety concerns arise. When further LDL-C lowering is required beyond lifestyle modifications and statin therapy, additional medications include oral ezetimibe and bempedoic acid, or injectables such as PCSK9 monoclonal antibodies or siRNA therapy. A novel agent that acts independently of hepatic LDL receptors is evinacumab, which is approved for patients with homozygous FH. Other emerging agents are targeted at Lp(a) and CETP. In light of the expanding lipid treatment landscape, this manuscript reviews the importance of early, intensive, and sustained LDL-C-lowering for primary and secondary prevention of ASCVD.

Exploiting light-based 3D-printing for the fabrication of mechanically enhanced, patient-specific aortic grafts

Despite polyester vascular grafts being routinely used in life-saving aortic aneurysm surgeries, they are less compliant than the healthy, native human aorta. This mismatch in mechanical behaviour has been associated with disruption of haemodynamics contributing to several long-term cardiovascular complications. Moreover, current fabrication approaches mean that opportunities to personalise grafts to the individual anatomical features are limited. Various modifications to graft design have been investigated to overcome such limitations; yet optimal graft functionality remains to be achieved. This study reports on the development and characterisation of an alternative vascular graft material. An alginate:PEGDA (AL:PE) interpenetrating polymer network (IPN) hydrogel has been produced with uniaxial tensile tests revealing similar strength and stiffness (0.39 ± 0.05 MPa and 1.61 ± 0.19 MPa, respectively) to the human aorta. Moreover, AL:PE tubular conduits of similar geometrical dimensions to segments of the aorta were produced, either via conventional moulding methods or stereolithography (SLA) 3D-printing. While both fabrication methods successfully demonstrated AL:PE hydrogel production, SLA 3D-printing was more easily adaptable to the fabrication of complex structures without the need of specific moulds or further post-processing. Additionally, most 3D-printed AL:PE hydrogel tubular conduits sustained, without failure, compression up to 50% their outer diameter and returned to their original shape upon load removal, thereby exhibiting promising behaviour that could withstand pulsatile pressure in vivo. Overall, these results suggest that this AL:PE IPN hydrogel formulation in combination with 3D-printing, has great potential for accelerating progress towards personalised and mechanically-matched aortic grafts.

Inter- and intrapopulation differences in the association between physical multimorbidity and depressive symptoms

BACKGROUND

The association between physical multimorbidity and depression differs by populations. However, no direct inter- or intrapopulation comparison of the association has been conducted. Thus, this study aims to estimate the association in China and the United States and reveal inter- and intrapopulation differences in the association.

METHODS

Middle-aged and older adults from the China Health and Retirement Longitudinal Study and the Health and Retirement Study were included. Physical multimorbidity was defined as the simultaneous presence of two or more chronic physical conditions and depressive symptoms was measured by the Center for Epidemiologic Studies Depression Scale. Generalized estimating equation model and stratification multilevel method were the main statistical models.

RESULTS

The presence of physical multimorbidity was associated with a higher risk of depression in both China (RR = 1.360 [95 % CI: 1.325-1.395]) and the US (RR = 1.613 [95 % CI: 1.529-1.701]). For individuals at a low risk of multimorbidity, multimorbidity was associated with 47.4 % (95 % CI: 1.377-1.579) and 71.1 % (95 % CI: 1.412-2.074) increases in the likelihood of depression in China and the US. The effect size was smaller for individuals at a moderate or high risk. However, the cross-national differences were greater for those with a high risk of multimorbidity.

LIMITATIONS

The self-report measures, attribution bias.

CONCLUSIONS

Compared to Chinese adults, the presence of physical multimorbidity led to an additional increase in depressive symptoms for American counterparts. The association was stronger for individuals at a low risk of multimorbidity, but cross-national differences were observed mostly among individuals at a high risk.

Trying to understand the illness: A qualitative investigation of health literacy of patients undergoing maintenance hemodialysis

Limited health literacy is high among patients with chronic kidney disease, which can pose challenges in health care. Evidence of health literacy in Indonesia, particularly regarding patients undergoing hemodialysis, is lacking. In this study, we aimed to explore health literacy in adult patients undergoing maintenance hemodialysis. An inductive qualitative study was conducted. Individual semi-structured interviews were conducted with 10 adult patients undergoing hemodialysis, four family caregivers, and four healthcare professionals. Interviews were transcribed verbatim and analyzed thematically. Three themes emerged from the data: "Trying to understand the illness," "searching and obtaining health information," and "applying health information." Understanding and accepting the illness included raising awareness of the changes in their lives and accepting these changes. Participants actively sought information from healthcare professionals and other sources and used it carefully. Behavioral changes included patients' adherence to therapy, although participants often felt bored during the illness trajectory. Understanding the illness and being willing to seek and critically evaluate health information before implementing it are important. These aspects may affect patient outcomes and require further intervention and research.

Sleep disturbance and suicidal ideation among youth with depression

BACKGROUND

Sleep disturbance may exacerbate the risk of suicide among youth with depression, but whether this association is independent of psychopathology requires further study.

METHODS

This cross-sectional study included 576 youths (13-25 years old) recruited from January 2022 to May 2023. The patients were first divided into two groups by the presence of suicidal ideation according to the Columbia-Suicide Severity Scale (C-SSRS). Sleep quality was assessed by the Athens Insomnia Scale (AIS) and mental health with the Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA). Logistic regression was conducted to analyze the association between sleep disturbance and suicidal ideation, adjusted for depressive symptoms severity.

RESULTS

The suicidal ideation group exhibited more severe sleep disturbances, anxiety symptoms, and depressive symptoms than the non-suicidal ideation group. Pearson correlation showed that sleep disturbance (AIS) was significantly correlated with the severity of anxiety symptoms, depressive symptoms, and suicidal ideation. Logistic regression analysis revealed that the AIS factor "daytime dysfunction" (β = 0.145; OR = 1.156, 95 % CI: 1.02, 1.309; p = 0.023) was significantly associated with suicidal ideation after adjusting for demographic characteristics and depressive symptoms severity.

LIMITATIONS

Due to the cross-sectional nature of the data, no causal inference can be made regarding the observed associations between sleep disturbance and suicidal ideation.

CONCLUSION

Sleep disturbance, particularly in the realm of daytime dysfunction, is associated with increased suicidal ideation among depressed youth. Clinicians need to assess and manage sleep disturbance in the context of suicidal ideation for young depression patients.

Dietary protein sources, genetics, and cardiovascular disease incidence

BACKGROUND

To explore the potential correlation between the amount and source of dietary protein and cardiovascular disease (CVD), as well as the potential impact of genetic susceptibility on these connections.

METHODS

We performed a prospective analysis of 98,224 participants from the UK. We measured dietary protein intake using two 24-hour dietary recall interviews. To analyze the data, we used multivariable-adjusted Cox regression models and restricted cubic spline models. Additionally, we calculated weighted genetic risk scores.

RESULTS

A total of 8818 new cases of CVD were documented, which included 4076 cases of coronary artery disease (CAD) and 1126 cases of stroke. The study found a J-shaped association (p nonlinearity = 0.005) between CVD risk and the percentage of energy obtained from consuming plant protein. Higher intake of plant protein and whole protein was associated with a decreased risk of CVD. On the other hand, larger intakes of animal protein was linked to a higher occurrence of CAD. Additionally, increased intake of plant protein was also linked to a lower incidence of stroke. Replacing 5 % of animal protein-based energy intake with plant protein-based energy intake resulted in a 5 % decrease in CVD risk.

LIMITATIONS

There remains an effect of residual confounders.

CONCLUSION

The consumption of larger amounts of plant protein, whole protein, and nut protein was found to be associated with a lower risk of CVD events. Conversely, higher intakes of animal protein was associated with an increased risk of CAD events. Furthermore, replacing 5 % of energy intake from animal protein with energy intake from plant protein was found to reduce the risk of CVD by 5 %.

Shared comorbidity of depression, migraine, insomnia, and fibromyalgia in a population-based sample

BACKGROUND

Depression, migraine, insomnia, and fibromyalgia are reportedly comorbidities. Nevertheless, no study has evaluated the comorbidity of all four of these disorders. This study aimed to investigate the comorbidity of these four disorders.

METHODS

Cross-sectional analyses were performed using data of the Circannual Change in Headache and Sleep study, an online nationwide population-based survey. Validated questionnaires were used to diagnose the disorders and measure quality of life. The change of clinical characteristics by addition of any comorbidity was analyzed using the Jonckheere-Terpstra trend test.

RESULTS

The prevalence rates of depression, migraine, insomnia, and fibromyalgia were 7.2 %, 5.6 %, 13.3 %, and 5.8 %, respectively. Among the 3030 included participants, 494 (16.3 %), 164 (5.4 %), 40 (1.3 %), and 6 (0.2 %) had one, two, three, and four of these conditions, respectively. The number of headache days per 30 days (Jonckheere-Terpstra trend test, p = 0.011) and migraine-related disability (migraine disability assessment score, p = 0.021) increased with an increase in the number of comorbidities but not with the intensity of headache (visual analog scale, p = 0.225) among participants with migraine. The severity of insomnia (Insomnia Severity Index, p < 0.001) and fibromyalgia (fibromyalgia severity score, p = 0.002) increased with additional comorbidities; however, depression (Patient Health Questionnaire-9, p = 0.384) did not show such an increase.

LIMITATIONS

The diagnoses of conditions were based on self-reported questionnaires.

CONCLUSIONS

The findings confirmed significant comorbidity between depression, migraine, insomnia, and fibromyalgia. Health professionals should be aware of the probable comorbidity of depression, migraine, insomnia, and fibromyalgia when caring for individuals with any of these four disorders.

Association of change in cardiovascular health based on life's essential 8 with incident cardiovascular disease

Objective

To evaluate whether and to what extent changes in cardiovascular health (CVH) based on life's essential 8 (LE8) are associated with incident cardiovascular disease (CVD).

Methods

A total of 7,194 participants were derived from UK Biobank. CVH was evaluated using a modified version of LE8. Participants were classified into three groups according to their LE8 score: high CVH (LE8 score≥80), moderate CVH (50≤LE8 score<80), and low CVH (LE8 score<50). Changes in CVH between 2006/2010 and 2012/2013 were analyzed.

Results

During a median of 10.3 years of follow-up, CVD was observed in 597 participants. Compared to the consistent moderate group, the moderate to low group was associated with about 128 % increased risk of CVD (Hazard ratio [HR]: 2.28; 95 % confidence interval [CI]: 1.61, 3.23), and the relevant HR (95 % CI) was 2.19 (1.46, 3.29) for the consistent low group; no statistically significant results were observed in the other groups. Moreover, no statistically significant exposure-response association between absolute change in LE8 score and incident CVD was documented (Poverall=0.15).

Conclusion

Change in CVH based on LE8 was associated with the risk of CVD; however, the relationship varied widely in different CVH change patterns.

Expanding roles of circRNAs in cardiovascular diseases

CircRNAs are a class of single-stranded RNAs characterized by covalently looped structures. Emerging advances have promoted our understanding of circRNA biogenesis, nuclear export, biological functions, and functional mechanisms. Roles of circRNAs in diverse diseases have been increasingly recognized in the past decade, with novel approaches in bioinformatics analysis and new strategies in modulating circRNA levels, which have made circRNAs the hot spot for therapeutic applications. Moreover, due to the intrinsic features of circRNAs such as high stability, conservation, and tissue-/stage-specific expression, circRNAs are believed to be promising prognostic and diagnostic markers for diseases. Aiming cardiovascular disease (CVD), one of the leading causes of mortality worldwide, we briefly summarize the current understanding of circRNAs, provide the recent progress in circRNA functions and functional mechanisms in CVD, and discuss the future perspectives both in circRNA research and therapeutics based on existing knowledge.

Machine learning to identify a composite indicator to predict cardiac death in ischemic heart disease

BACKGROUND

Machine learning (ML) employs algorithms that learn from data, building models with the potential to predict events by aggregating a large number of variables and assessing their complex interactions. The aim of this study is to assess ML potential in identifying patients with ischemic heart disease (IHD) at high risk of cardiac death (CD).

METHODS

3987 (mean age 68 ± 11) hospitalized IHD patients were enrolled. We implemented and compared various ML models and their combination into ensembles. Model output constitutes a new ML indicator to be employed for stratification. Primary variable importance was assessed with ablation tests.

RESULTS

An ensemble classifier combining three ML models achieved the best performance to predict CD (AUROC of 0.830, F1-macro of 0.726). ML indicator use through Cox survival analysis outperformed the 18 variables individually, producing a better stratification compared to standard multivariate analysis (improvement of ∼20%). Patients in the low risk group defined through ML indicator had a significantly higher survival (88.8% versus 29.1%). The main variables identified were Dyslipidemia, LVEF, Previous CABG, Diabetes, Previous Myocardial Infarction, Smoke, Documented resting or exertional ischemia, with an AUROC of 0.791 and an F1-score of 0.674, lower than that of 18 variables. Both code and clinical data are freely available with this article.

CONCLUSION

ML may allow a faster, low-cost and reliable evaluation of IHD patient prognosis by inclusion of more predictors and identification of those more significant, improving outcome prediction towards the development of precision medicine in this clinical field.

Cardiometabolic comorbidities and complications of obesity and chronic kidney disease (CKD)

Obesity and chronic kidney disease are two ongoing progressive clinical pandemics of major public health and clinical care significance. Because of their growing prevalence, chronic indolent course and consequent complications both these conditions place significant burden on the health care delivery system especially in developed countries like the United States. Beyond the chance coexistence of both of these conditions in the same patient based on high prevalence it is now apparent that obesity is associated with and likely has a direct causal role in the onset, progression and severity of chronic kidney disease. The causes and underlying pathophysiology of this are myriad, complicated and multi-faceted. In this review, continuing the theme of this special edition of the journal on " The Cross roads between Endocrinology and Nephrology" we review the epidemiology of obesity related chronic kidney disease (ORCKD), and its various underlying causes and pathophysiology. In addition, we delve into the consequent comorbidities and complications associated with ORCKD with particular emphasis on the cardio metabolic consequences and then review the current body of evidence for available strategies for chronic kidney disease modulation in ORCKD as well as the potential unique role of weight reduction and management strategies in its improvement and risk reduction.

MIAT LncRNA: A multifunctional key player in non-oncological pathological conditions

The discovery of non-coding RNAs (ncRNAs) has unveiled a wide range of transcripts that do not encode proteins but play key roles in several cellular and molecular processes. Long noncoding RNAs (lncRNAs) are specific class of ncRNAs that are longer than 200 nucleotides and have gained significant attention due to their diverse mechanisms of action and potential involvement in various pathological conditions. In the current review, the authors focus on the role of lncRNAs, specifically highlighting the Myocardial Infarction Associated Transcript (MIAT), in non-oncological context. MIAT is a nuclear lncRNA that has been directly linked to myocardial infarction and is reported to control post-transcriptional processes as a competitive endogenous RNA (ceRNA) molecule. It interacts with microRNAs (miRNAs), thereby limiting the translation and expression of their respective target messenger RNA (mRNA) and regulating protein expression. Yet, MIAT has been implicated in other numerous pathological conditions such as other cardiovascular diseases, autoimmune disease, neurodegenerative diseases, metabolic diseases, and many others. In this review, the authors emphasize that MIAT exhibits distinct expression patterns and functions across different pathological conditions and is emerging as potential diagnostic, prognostic, and therapeutic agent. Additionally, the authors highlight the regulatory role of MIAT and shed light on the involvement of lncRNAs and specifically MIAT in various non-oncological pathological conditions.

Enhancing accuracy and privacy in speech-based depression detection through speaker disentanglement

Speech signals are valuable biomarkers for assessing an individual's mental health, including identifying Major Depressive Disorder (MDD) automatically. A frequently used approach in this regard is to employ features related to speaker identity, such as speaker-embeddings. However, over-reliance on speaker identity features in mental health screening systems can compromise patient privacy. Moreover, some aspects of speaker identity may not be relevant for depression detection and could serve as a bias factor that hampers system performance. To overcome these limitations, we propose disentangling speaker-identity information from depression-related information. Specifically, we present four distinct disentanglement methods to achieve this - adversarial speaker identification (SID)-loss maximization (ADV), SID-loss equalization with variance (LEV), SID-loss equalization using Cross-Entropy (LECE) and SID-loss equalization using KL divergence (LEKLD). Our experiments, which incorporated diverse input features and model architectures, have yielded improved F1 scores for MDD detection and voice-privacy attributes, as quantified by Gain in Voice Distinctiveness G V   D and De-Identification Scores (DeID). On the DAIC-WOZ dataset (English), LECE using ComparE16 features results in the best F1-Scores of 80% which represents the audio-only SOTA depression detection F1-Score along with a G V   D of -1.1 dB and a DeID of 85%. On the EATD dataset (Mandarin), ADV using raw-audio signal achieves an F1-Score of 72.38% surpassing multi-modal SOTA along with a G V   D of -0.89 dB dB and a DeID of 51.21%. By reducing the dependence on speaker-identity-related features, our method offers a promising direction for speech-based depression detection that preserves patient privacy.

A novel approach to quantifying individual's biological aging using Korea's national health screening program toward precision public health

Accurate prediction of biological age can inform public health measures to extend healthy lifespans and reduce chronic conditions. Multiple theoretical models and methods have been developed; however, their applicability and accuracy are still not extensive. Here, we report Differential Aging and Health Index (DAnHI), a novel measure of age deviation, developed using physical and serum biomarkers from four million individuals in Korea's National Health Screening Program. Participants were grouped into aging statuses (< 26 vs. ≥ 26, < 27 vs. ≥ 27, …, < 75 vs. ≥ 75 years) as response variables in a binary logistic regression model with thirteen biomarkers as independent variables. DAnHI for each individual was calculated as the weighted mean of their relative probabilities of being classified into each older age status, based on model ages ranging from 26 to 75. DAnHI in our large study population showed a steady increase with the increase in age and was positively associated with death after adjusting for chronological age. However, the effect size of DAnHI on the risk of death varied according to the age group and sex. The hazard ratio was highest in the 50-59-year age group and then decreased as the individuals aged. This study demonstrates that routine health check-up biomarkers can be integrated into a quantitative measure for predicting aging-related health status and death via appropriate statistical models and methodology. Our DAnHI-based results suggest that the same level of aging-related health status does not indicate the same degree of risk for death.

Consistent spatial lesion-symptom patterns: A comprehensive analysis using triangulation in lesion-symptom mapping in a cohort of stroke patients

INTRODUCTION

The relationship between brain lesions and stroke outcomes is crucial for advancing patient prognosis and developing effective therapies. Stroke is a leading cause of disability worldwide, and it is important to understand the neurological basis of its varied symptomatology. Lesion-symptom mapping (LSM) methods provide a means to identify brain areas that are strongly associated with specific symptoms. However, inner variations in LSM methods can yield different results. To address this, our study aimed to characterize the lesion-symptom mapping variability using three different LSM methods. Specifically, we sought to determine a lesion symptom core across LSM approaches enhancing the robustness of the analysis and removing potential spatial bias.

MATERIAL & METHODS

A cohort consisting of 35 patients with either right- or left-sided middle cerebral artery strokes were enrolled and evaluated using the NIHSS at 24 h post-stroke. Anatomical T1w MRI scans were also obtained 24 h post-stroke. Lesion masks were segmented manually and three distinctive LSM methods were implemented: ROI correlation-based, univariate, and multivariate approaches.

RESULTS

The results of the LSM analyses showed substantial spatial differences in the extension of each of the three lesion maps. However, upon overlaying all three lesion-symptom maps, a consistent lesion core emerged, corresponding to the territory associated with elevated NIHSS scores. This finding not only enhances the spatial accuracy of the lesion map but also underscores its clinical relevance.

CONCLUSION

This study underscores the significance of exploring complementary LSM approaches to investigate the association between brain lesions and stroke outcomes. By utilizing multiple methods, we can increase the robustness of our results, effectively addressing and neutralizing potential spatial bias introduced by each individual method. Such an approach holds promise for enhancing our understanding of stroke pathophysiology and optimizing patient care strategies.

Melatonin at repeated doses alleviates hyperglycemia-exacerbated cerebral ischemia-reperfusion injury at 72 h via anti-inflammation and anti-apoptosis

Objective

We aimed to investigate how hyperglycemia would exacerbate cerebral ischemia-reperfusion injury (CIRI) in a rat model of type 1 diabetes mellitus (T1DM) and explore the beneficial effects of multiple doses of melatonin in T1DM induced CIRI.

Method

The T1DM rat model was induced with streptozocin, and melatonin (10 mg/kg) was injected at 0.5 h before ischemia as well as at 24 and 48 h after reperfusion.

Results

When compared to normoglycemic (NG) rats, T1DM rats had hyperglycemia with weight loss before CIRI. Despite comparable degrees of ischemia and initial reperfusion, T1DM rats tended to have greater weight loss and had worse neurological deficits and larger infarct volume than NG rats up to 72 h after CIRI. Persistent activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway but not of apoptosis or calpains was a crucial factor in T1DM-mediated exacerbation of CIRI at 72 h. Despite lacking effects on baseline hyperglycemia, ischemia and initial reperfusion, melatonin at multiple doses lessened post-CIRI weight loss, neurological deficits and infarct volume in T1DM rats at 72 h. when compared to vehicle-treated T1DM rats with CIRI. Beneficial effects of melatonin treatment included decreased activation of NF-κB pathway, apoptosis and calpains, leading to reduced expression of inducible nitric oxide synthase and enhanced neuronal density.

Conclusion

Melatonin at multiple doses can alleviate T1DM-mediated exacerbation of CIRI at 72 h through anti-inflammation and anti-apoptosis.

Effect of high-definition transcranial direct current stimulation among late-subacute and chronic stroke survivors with fatigue: A randomized-controlled crossover trial protocol

Post-stroke fatigue (PSF) is a commonly overlooked symptom that impacts daily functioning and quality of life. It is caused by altered functional connectivity within the brain networks, which can potentially be influenced by neuromodulation. Multiple cortical regions have been targeted to reduce PSF, but the most efficient ones remain uncertain. Therefore, we aim to identify the most appropriate cortical stimulation site to reduce PSF. Twenty participants with PSF will be included in this cross-over trial. Each participant will receive one session of active anodal high definition- transcranial direct current stimulation (HD-tDCS) over three different cortical areas and one session of sham tDCS in a cross-over manner, with a two-week of washout period in between. Pre- and post- fatigue will be assessed using Fatigue Severity Scale and fatigability using electromyography by determining the time to task failure. Resting-state electroencephalography will be performed before and after each stimulation session to determine the functional connectivity of the cortical areas stimulated.

Enhancing risk communication and environmental crisis management through satellite imagery and AI for air quality index estimation

Due to climate change, the air pollution problem has become more and more prominent [23]. Air pollution has impacts on people globally, and is considered one of the leading risk factors for premature death worldwide; it was ranked as number 4 according to the website [24]. A study, 'The Global Burden of Disease,' reported 4,506,193 deaths were caused by outdoor air pollution in 2019 [22,25]. The air pollution problem is become even more apparent when it comes to developing countries [22], including Thailand, which is considered one of the developing countries [26]. In this research, we focus and analyze the air pollution in Thailand, which has the annual average PM2.5 (particulate matter 2.5) concentration falls in between 15 and 25, classified as the interim target 2 by 2021's WHO AQG (World Health Organization's Air Quality Guidelines) [27]. (The interim targets refer to areas where the air pollutants concentration is high, with 1 being the highest concentration and decreasing down to 4 [27,28]). However, the methodology proposed here can also be adopted in other areas as well. During the winter in Thailand, Bangkok and its surrounding metroplex have been facing the issue of air pollution (e.g., PM2.5) every year. Currently, air quality measurement is done by simply implementing physical air quality measurement devices at designated-but limited number of locations. In this work, we propose a method that allows us to estimate the Air Quality Index (AQI) on a larger scale by utilizing Landsat 8 images with machine learning techniques. We propose and compare hybrid models with pure regression models to enhance AQI prediction based on satellite images. Our hybrid model consists of two parts as follows:•The classification part and the estimation part, whereas the pure regressor model consists of only one part, which is a pure regression model for AQI estimation.•The two parts of the hybrid model work hand in hand such that the classification part classifies data points into each class of air quality standard, which is then passed to the estimation part to estimate the final AQI. From our experiments, after considering all factors and comparing their performances, we conclude that the hybrid model has a slightly better performance than the pure regressor model, although both models can achieve a generally minimum R2 (R2 > 0.7). We also introduced and tested an additional factor, DOY (day of year), and incorporated it into our model. Additional experiments with similar approaches are also performed and compared. And, the results also show that our hybrid model outperform them. Keywords: climate change, air pollution, air quality assessment, air quality index, AQI, machine learning, AI, Landsat 8, satellite imagery analysis, environmental data analysis, natural disaster monitoring and management, crisis and disaster management and communication.

Reconsidering gas as clean energy: Switching to electricity for household cooking to reduce NO2-attributed disease burden

Nitrogen dioxide (NO2) is a prevalent air pollutant in urban areas, originating from outdoor sources, household gas consumption, and secondhand smoke. The limited evaluation of the disease burden attributable to NO2, encompassing different health effects and contributions from various sources, impedes our understanding from a public health perspective. Based on modeled NO2 exposure concentrations, their exposure-response relationships with lung cancer, chronic obstructive pulmonary disease, and diabetes mellitus, and baseline disability-adjusted life years (DALYs), we estimated that 1,675 (655-2,624) thousand DALYs were attributable to NO2 in urban China in 2019 [138 (54-216) billion Chinese yuan (CNY) economic losses]. The transition from gas to electricity for household cooking was estimated to reduce the attributable economic losses by 35%. This reduction falls within the range of reductions achieved when outdoor air meets the World Health Organization interim target 3 and air quality guidelines for annual NO2, highlighting the significance of raising awareness of gas as a polluting household energy for cooking. These findings align with global sustainable development initiatives, providing a sustainable solution to promote public health while potentially mitigating climate change.

Sex differences in the relationships between macronutrients and all-cause mortality in individuals with metabolically unhealthy overweight/obesity

This study investigates sex differences in the effects of macronutrient quantity, quality, and timing on mortality in metabolically unhealthy overweight/obesity (MUO) populations. The study included 18,345 participants, including 9204 men and 9141 women. The Cox proportional risk model and isocaloric substitution effects were used to examine the association of macronutrient intake and subtype with all-cause mortality in the MUO populations. After adjusting for the potential covariates, The risk of all-cause mortality was elevated in men in the highest 25% percentile of poor-quality carbohydrates compared with men in the lowest quartile (odds ratio [OR]: 2.04; 95% confidence interval [CI], 1.40-2.98). Compared with women in the lowest quartile, the risk of all-cause mortality for women in the highest 25% percentile for high-quality carbohydrates (OR: 0.74; 95% CI, 0.55-0.99) and unsaturated fatty acids (OR: 0.54; 95% CI, 0.32-0.93) were decreased. In women, replacing low-quality carbohydrates with high-quality carbohydrates on an isocaloric basis reduces the risk of all-cause mortality by approximately 9%. We find that different macronutrient consumption subtypes are associated with all-cause mortality in MUO populations, with differential effects between men and women, and that the risk of all-cause mortality is influenced by macronutrient quality and meal timing.

Effect of Combined Physical Exercise Training in Reducing Cardiovascular Risk Among Adults with Obesity: A Randomized Clinical Trial

It is necessary to understand the relationship between different models of exercise periodization and the reduction of cardiovascular risk in adults with obesity. The aim of this study was to verify the effect of two periodization models of combined training on the cardiovascular risk of adults with obesity of both sexes. A randomized clinical trial was conducted with adults of both sexes with obesity. They were divided into three groups: control group (CG), non-periodized combined training group (NG), and combined training group with linear periodization (PG). The NG and PG groups underwent physical exercise training regimen for 16 weeks, in three weekly sessions of 60 min each, with the volume and intensity equalized. Cardiovascular risk was measured by the overall Framingham risk score (FRS). Generalized estimation equations and individual responsiveness analyses were used, stratified by sex. A statistically significant reduction in FRS was observed only in men of the NG (pre: 2.50 ± 0.56; post: 0.50 ± 1.02; p-value = 0.001). There was no statistically significant intervention effect on the women's cardiovascular risk. It was found that, regardless of sex, subjects in the control group mostly presented results of increased cardiovascular risk. In contrast, those belonging to the exercise groups, if not reduced, at least stabilized the chances of suffering a cardiovascular event in the next ten years after 16 weeks of combined training. Sixteen weeks of non-periodized combined training were sufficient to reduce cardiovascular risk in men with obesity. Both periodization models were important to stabilize the risk of developing a cardiovascular disease in the next 10 years.

Brain Derived Neurotrophic Factor Methylation and Long-term Outcomes after Stroke Interacting with Suicidal Ideation

Objective

This study aimed to evaluate the unexplored relationship between BDNF methylation, long-term outcomes, and its interaction with suicidal ideation (SI), which is closely associated with both BDNF expression and stroke outcomes.

Methods

A total of 278 stroke patients were assessed for BDNF methylation status and SI using suicide-related item in the Montgomery-Åsberg Depression Rating Scale at 2 weeks post-stroke. We investigated the incidence of composite cerebro-cardiovascular events (CCVEs) during an 8-14-year period after the initial stroke as long-term stroke outcome. We conducted Cox regression models adjusted for covariates to evaluate the association between BDNF methylation status and CCVEs, as well as its interaction with post-stroke SI at 2 weeks.

Results

Higher methylation status of CpG 1, 3, and 5, but not the average value, predicted a greater number of composite CCVEs during 8-14 years following the stroke. The associations between a higher methylation status of CpGs 1, 3, 5, and 8, as well as the average BDNF methylation value, and a greater number of composite CCVEs, were prominent in patients who had post-stroke SI at 2 weeks. Notably, a significant interaction between methylation status and SI on composite CCVEs was observed only for CpG 8.

Conclusion

The significant association between BDNF methylation and poor long-term stroke outcomes, particularly amplified in individuals who had post-stroke SI at 2 weeks, suggested that evaluating the biological marker status of BDNF methylation along with assessing SI during the acute phase of stroke can help predict long-term outcomes.

Effect of ambient ozone pollution on disease burden globally: A systematic analysis for the global burden of disease study 2019

BACKGROUND

Exposure to ambient ozone pollution causes health loss and even death, and both are the main risk factors for the disease burden worldwide. We comprehensively evaluated the ozone pollution-related disease burden.

METHODS

First, numbers and age-standardized rates of deaths and disability-adjusted life years (DALYs) were assessed globally and by sub-types in 2019. Furthermore, the temporal trend of the disease burden was explored by the linear regression model from 1990 to 2019. The cluster analysis was used to evaluate the changing pattern of related disease burden across Global Burden of Disease Study (GBD) regions. Finally, the age-period-cohort (APC) model and the Bayesian age-period-cohort (BAPC) model were used to predict the future disease burden in the next 25 years.

RESULT

Exposure to ozone pollution contributed to 365,222 deaths and 6,210,145 DALYs globally in 2019, which accounted for 0.65 % of deaths globally and 0.24 % of DALYs globally. The disease burden was consistently increasing with age. Males were high-risk populations and low-middle socio-demographic index (SDI) regions were high-risk areas. The disease burden of ozone pollution varied considerably across the GBD regions and the countries. In 2019, the number of deaths and DALYs cases increased by 76.11 % and 56.37 %, respectively compared to those in 1990. The predicted results showed that the number of deaths cases and DALYs cases for both genders would still increase from 2020 to 2044.

CONCLUSION

In conclusion, ambient ozone pollution has threatened public health globally. More proactive and effective strategic measures should be developed after considering global-specific circumstances.

Predicting particulate matter, nitrogen dioxide, and ozone across Great Britain with high spatiotemporal resolution based on random forest models

In Great Britain, limited studies have employed machine learning methods to predict air pollution especially ozone (O3) with high spatiotemporal resolution. This study aimed to address this gap by developing random forest models for four key pollutants (fine and inhalable particulate matter [PM2.5 and PM10], nitrogen dioxide [NO2] and O3) by integrating multiple-source predictors at a daily level and 1-km resolution. The out-of-bag R2 (root mean squared error, RMSE) between predictions from models and measurements from monitoring stations in 2006-2013 was 0.85 (3.63 μg/m3) for PM2.5, 0.77 (6.00 μg/m3) for PM10, 0.85 (9.71 μg/m3) for NO2, and 0.85 (9.39 μg/m3) for maximum daily 8-h average (MDA8) O3 at daily level, and the predicting accuracy was higher at monthly and annual level. The high-resolution predictions captured characterized spatiotemporal patterns of the four pollutants. Higher concentrations of PM2.5, PM10, and NO2 were distributed in densely populated southern regions of Great Britain while O3 showed an inverse spatial pattern in general, which could not be fully depicted by monitoring stations. Therefore, predictions produced in this study could improve exposure assessment with less exposure misclassification and flexible exposure windows for future epidemiological studies to investigate the impact of air pollution across Great Britain.

A multi-omics investigation of the lung injury induced by PM2.5 at environmental levels via the lung-gut axis

Long-term exposure to fine particulate matter (PM2.5) posed injury for gastrointestinal and respiratory systems, ascribing with the lung-gut axis. However, the cross-talk mechanisms remain unclear. Here, we attempted to establish the response networks of lung-gut axis in mice exposed to PM2.5 at environmental levels. Male Balb/c mice were exposed to PM2.5 (dose of 0.1, 0.5, and 1.0 mg/kg) collected from Chengdu, China for 10 weeks, through intratracheally instillation, and examined the effect of PM2.5 on lung functions of mice. The changes of lung and gut microbiota and metabolic profiles of mice in different groups were determined. Furthermore, the results of multi-omics were conjointly analyzed to elucidate the primary microbes and the associated metabolites in lung and gut responsible for PM2.5 exposure. Accordingly, the cross-talk network and key pathways between lung-gut axis were established. The results indicated that exposed to PM2.5 0.1 mg/kg induced obvious inflammations in mice lung, while emphysema was observed at 1.0 mg/kg. The levels of metabolites guanosine, hypoxanthine, and hepoxilin B3 increased in the lung might contribute to lung inflammations in exposure groups. For microbiotas in lung, PM2.5 exposure significantly declined the proportions of Halomonas and Lactobacillus. Meanwhile, the metabolites in gut including L-tryptophan, serotonin, and spermidine were up-regulated in exposure groups, which were linked to the decreasing of Oscillospira and Helicobacter in gut. Via lung-gut axis, the activations of pathways including Tryptophan metabolism, ABC transporters, Serotonergic synapse, and Linoleic acid metabolism contributed to the cross-talk between lung and gut tissues of mice mediated by PM2.5. In summary, the microbes including Lactobacillus, Oscillospira, and Parabacteroides, and metabolites including hepoxilin B3, guanosine, hypoxanthine, L-tryptophan, and spermidine were the main drivers. In this lung-gut axis study, we elucidated some pro- and pre-biotics in lung and gut microenvironments contributed to the adverse effects on lung functions induced by PM2.5 exposure.

Semaphorin3C identified as mediator of neuroinflammation and microglia polarization after spinal cord injury

Excessive neuroinflammation after spinal cord injury (SCI) is a major hurdle during nerve repair. Although proinflammatory macrophage/microglia-mediated neuroinflammation plays important roles, the underlying mechanism that triggers neuroinflammation and aggravating factors remain unclear. The present study identified a proinflammatory role of semaphorin3C (SEMA3C) in immunoregulation after SCI. SEMA3C expression level peaked 7 days post-injury (dpi) and decreased by 14 dpi. In vivo and in vitro studies revealed that macrophages/microglia expressed SEMA3C in the local microenvironment, which induced neuroinflammation and conversion of proinflammatory macrophage/microglia. Mechanistic experiments revealed that RAGE/NF-κB was downstream target of SEMA3C. Inhibiting SEMA3C-mediated RAGE signaling considerably suppressed proinflammatory cytokine production, reversed polarization of macrophages/microglia shortly after SCI. In addition, inhibition of SEMA3C-mediated RAGE signaling suggested that the SEMA3C/RAGE axis is a feasible target to preserve axons from neuroinflammation. Taken together, our study provides the first experimental evidence of an immunoregulatory role for SEMA3C in SCI via an autocrine mechanism.

Follow-up echocardiographic changes in children and youth aged <25 years with latent rheumatic heart disease: A systematic review and meta-analysis of global data

OBJECTIVES

To estimate progression, regression and persistence rates for borderline and mild-definite latent RHD in children and youth diagnosed at age < 25 years.

METHODS

A review was conducted in accordance with Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines. Electronic databases were searched for latent RHD echocardiography follow-up studies which used World Heart Federation diagnostic criteria. A meta-analysis of outcomes was conducted for borderline and mild-definite disease subcategories.

RESULTS

Data for 1618 individuals from 12 studies were included. For borderline cases, 48.51% regressed (95%CI 45.10-51.93), 13.99% progressed (95%CI 9.72-18.25), and 38.61% had persistent (unchanged) disease at follow-up (95%CI 29.68-47.54). For mild-definite cases, 34.01% regressed (95%CI 28.88-39.15), 8.06% progressed (95%CI 3.65-16.90), and 60.23% had persistent disease (95%CI 55.08-67.38).

CONCLUSIONS

Borderline and mild-definite latent RHD show variable evolution following initial diagnosis. While 8% of mild-definite and 14% borderline cases had signs of disease progression at follow-up, a third of mild-definite and half of borderline cases had disease regression, even with sub adequate antibiotic prophylaxis. The significant variability between study cohorts suggests latent RHD natural history is likely variable between different endemic regions globally. Future research is needed to identify those individuals who would most benefit from antibiotic prophylaxis and determine regional natural history of latent RHD.

Pharmacodynamics and mechanism of Erigeron breviscapus granules in the treatment of ischemic stroke in mice by regulating sphingolipid metabolism based on metabolomics

AIM

Erigeron breviscapus (Vant.) Hand.-Mazz. (EB) granules is the extract preparation of EB, with clear curative effect and unclear mechanism. This study intends to systematically explore the specific mechanism of EB granules in the treatment of IS from the metabolic perspective.

METHODS

The model of transient middle cerebral artery occlusion (tMCAO) in mice was established by the suture-occluded method. The therapeutic effect of EB granules on tMCAO mice was evaluated by behavioral evaluation, brain water content determination, 2,3,5-triphenyltetrazolium chloride (TTC) staining, hematoxylin-eosin (HE) staining, and levels of lactate dehydrogenase (LDH) and neuron specific enolase (NSE) in serum. In order to screen differential metabolites, non-targeted metabolomics technology was used to detect the metabolites in serum before and after administration. Univariate statistics, multivariate statistics and bioinformatics were used to analyze the changes of metabolites in serum of tMCAO mice. The possible related mechanism of EB granules in treating IS was screened by pathway enrichment analysis, and the preliminary verification was carried out at animal level by enzyme linked immunosorbent assay (ELISA) and western blot (WB).

RESULTS

EB granules could significantly improve behavior of tMCAO mice, reduce brain water content and cerebral infarction volume, improve morphology of brain tissue, reduce the levels of LDH and NSE in serum. A total of 232 differential metabolites were screened, which were mainly enriched in many biological processes such as sphingolipid metabolism. The differential metabolite S1P and its receptors S1PR1 and S1PR2 in sphingolipid metabolism were verified. The results showed that the level of S1P in brain tissue increased and the protein expression of S1PR1 decreased significantly after modeling, and reversed after administration, but there was no significant difference in the protein expression of S1PR2.

CONCLUSION

The therapeutic effects of EB granules may be related to affecting sphingolipid metabolism through regulating S1P/S1PR1.

Hypothermia promotes tunneling nanotube formation and the transfer of astrocytic mitochondria into oxygen-glucose deprivation/reoxygenation-injured neurons

Mitochondrial transfer occurs between cells, and it is important for damaged cells to receive healthy mitochondria to maintain their normal function and protect against cell death. Accumulating evidence suggests that the functional mitochondria of astrocytes are released and transferred to oxygen-glucose deprivation/reoxygenation (OGD/R)-injured neurons. Mild hypothermia (33 °C) is capable of promoting this process, which partially restores the function of damaged neurons. However, the pathways and mechanisms by which mild hypothermia facilitates mitochondrial transfer remain unclear. We are committed to studying the role of mild hypothermia in neuroprotection to provide reliable evidences and insights for the clinical application of mild hypothermia in brain protection. Tunneling nanotubes (TNTs) are considered to be one of the routes through which mitochondria are transferred between cells. In this study, an OGD/R-injured neuronal model was successfully established, and TNTs, mitochondria, neurons and astrocytes were double labeled using immunofluorescent probes. Our results showed that TNTs were present and involved in the transfer of mitochondria between cells in the mixed-culture system of neurons and astrocytes. When neurons were subjected to OGD/R exposure, TNT formation and mitochondrial transportation from astrocytes to injured neurons were facilitated. Further analysis revealed that mild hypothermia increased the quantity of astrocytic mitochondria transferred into damaged neurons through TNTs, raised the mitochondrial membrane potential (MMP), and decreased the neuronal damage and death during OGD/R. Altogether, our data indicate that TNTs play an important role in the endogenous neuroprotection of astrocytic mitochondrial transfer. Furthermore, mild hypothermia enhances astrocytic mitochondrial transfer into OGD/R-injured neurons via TNTs, thereby promoting neuroprotection and neuronal recovery.

Maternal separation regulates sensitivity of stress-induced depression in mice by affecting hippocampal metabolism

Depression is a serious mental illness. Previous studies found that early life stress (ELS) plays a vital role in the onset and progression of depression. However, relevant studies have not yet been able to explain the specific effects of early stress on stress-induced depression sensitivity and individual behavior during growth. Therefore, we constructed a maternal separation (MS) model and administered chronic social frustration stress at different stages of their growth while conducting metabolomics analysis on the hippocampus of mice. Our results showed that the immobility time of mice in the forced swimming test was significantly reduced at the end of MS. Meanwhile, mice with MS experience significantly decreased total movement distance in the open field test and sucrose preference ratio in the sucrose preference test when subjected to chronic social defeat stress (CSDS) during adolescence. In adulthood, the results were the opposite. In addition, we found that level changes in metabolites such as Beta-alanine, l-aspartic acid, 2-aminoadipic acid, and Glycine are closely related to behavioral changes. These metabolites are mainly enriched in Pantothenate, CoA biosynthesis, and Beta Alanine metabolism pathways. Our experiment revealed that the effects of ELS vary across different age groups. It will increase an individual's sensitivity to depression when facing CSDS in adolescence, but it will reduce their sensitivity to depression when facing CSDS in adulthood. This may be achieved by regulating the hippocampus's Pantothenate and CoA biosynthesis and Beta Alanine metabolism pathways represented by Beta-alanine, l-Aspartic acid, 2-aminoadipic acid, and Glycine metabolites.

High-throughput synchronous erythrocyte cellular antioxidant activity and protection screening of phenolic-rich extracts: Protocol validation and applications

Oxidative/nitrosative damage takes part in chronic disease development, which generates an urgent need for intervention and better therapies to manage them. The scientific community has demanded easy-to-run, cheap, and reliable methods for cellular antioxidant activity assays. This work standardised and validated an erythrocyte cellular antioxidant activity and membrane protection/injury (HERYCA-P) protocol to study food-derive extracts. The method measures intracellular reactive oxygen species (ROS) generation, lipoperoxidation, and haemolysis induced by 2,2'-azobis(2-amidinopropane) dihydrochloride. Quercetin decreased ROS generation by 50.4% and haemolysis by 2.2%, while ascorbic acid inhibited lipid peroxidation by 40.1%. Total phenolic contents of teas were correlated with decreased ROS generation (r = -0.924), lipoperoxidation (r = -0.951), and haemolysis (r = -0.869). The erythrocyte ROS generation and lipoperoxidation were also associated with CUPRAC (r = -0.925; r = -0.951) and hydroxyl radical scavenging activity (r = -0.936; r = -0.949). The precision rates of antioxidant standards and tea samples were below 15%. HERYCA-P is feasible as a complementary antioxidant assay for food matrices.

The predictive value of serum Dickkopf-1, Dickkopf-3 level to coronary artery disease and acute coronary syndrome

BACKGROUND

Previous studies have already confirmed the association between Dickkopf (Dkk) protein and the occurrence and progression of atherosclerosis. However, there is limited clinical evidence regarding the serum levels of Dickkopf-1 (Dkk1) and Dickkopf-3 (Dkk3) in relation to atherosclerotic cardiovascular disease (ASCVD), particularly acute coronary syndrome (ACS).

MATERIALS AND METHODS

A total of 88 healthy volunteers and 280 patients with coronary artery disease (CAD) undergoing coronary angiography for angina between October 2021 and October 2022, including 96 cases of stable angina (SA), 96 of unstable angina (UA) and 88 of acute myocardial infarction (AMI) were included finally. The serum concentrations of Dkk1 and Dkk3 were measured using electrochemiluminescence of Meso Scale Discovery. The predictive value of single or combined application of serum Dkk1 and Dkk3 in CAD and ACS were evaluated.

RESULTS

The serum levels of Dkk1 were significantly higher in the SA group, UA group, and AMI group compared to the control group. Multivariable logistic regression analysis demonstrated that elevated serum Dkk1 levels were independent predictive factors for increased risk of CAD and ACS (OR = 1.027, 95%CI = 1.019-1.034, p < 0.001; OR = 1.045, 95%CI = 1.028-1.053, p < 0.001, respectively). Receiver operating characteristic curve (ROC) analysis showed that the optimal cutoff value of serum Dkk1 for predicting ACS was 205 ng/dl, with a sensitivity of 82.6% and specificity of 96.6%. The area under the curve (AUC) was 0.930 (95%CI: 0.899-0.961, p < 0.001). Regarding Dkk3, serum Dkk3 levels were elevated in CAD patients compared to the healthy control group, and significantly higher in ACS patients compared to SA patients. Serum Dkk3 was significantly associated with increased risk of CAD and ACS (OR = 1.131, 95%CI = 1.091-1.173, p < 0.001; OR = 1.201, 95%CI = 1.134-1.271, p < 0.001, respectively). ROC curve analysis showed that the optimal cutoff value of serum Dkk3 for predicting ACS was 50.82 ng/ml, with a sensitivity of 85.9% and specificity of 87.5%. The AUC was 0.925 (95%CI: 0.894-0.956, p < 0.001). When serum Dkk1 and Dkk3 are combined as predictive factors for ACS, the AUC was 0.975.

CONCLUSION

Serum levels of Dkk1 and Dkk3 are significantly associated with an increased risk of CAD and ACS, and they possess predictive value for CAD and ACS. The combination of serum Dkk1 and Dkk3 is a superior predictive factor for CAD and ACS.

Burden of Stroke Attributable to Nonoptimal Temperature in 204 Countries and Territories: A Population-Based Study, 1990-2019

BACKGROUND AND OBJECTIVES

Stroke attributable to nonoptimal temperature needs more attention with dramatic climate change. The aim of this study was to estimate the global burden and distribution characteristics of the burden.

METHODS

In this ecological study, we collected data from the Climate Research Unit Gridded Time Series, the World Bank databases, and the Global Burden of Diseases study to estimate the distribution of burden. We used the joinpoint model, decomposition analysis, age-period-cohort model, panel data analysis, and health inequality analysis to assess the different types of stroke burden attributable to different climatic conditions.

RESULTS

The burden of stroke attributable to nonoptimal temperature continued to grow, and aging was a key factor in this increase. In 2019, 521,031 (95% uncertainty interval [UI] 402,433-663,996) deaths and 9,423,649 (95% UI 7,207,660-12,055,172) disability-adjusted life years [DALYs] attributable to stroke due to nonoptimal temperature were recorded globally. Globally, men (age-standardized mortality rate [ASMR] 7.70, 95% UI 5.80-9.73; age-standardized DALY rate [ASDR] 139.69, 95% UI 102.96-178.54 in 2019) had a heavier burden than women (ASMR 5.89, 95% UI 4.50-7.60; ASDR 96.02, 95% UI 72.62-123.85 in 2019). Central Asia (ASMR 18.12, 95% UI 13.40-24.53; ASDR 327.35, 95% UI 240.24-440.61 in 2019) had the heaviest burden at the regional level. In the national level, North Macedonia (ASMR 32.97, 95% UI 20.57-47.44 in 2019) and Mongolia (ASDR 568.54, 95% UI 242.03-1,031.14 in 2019) had the highest ASMR/ASDR, respectively. Low temperature currently contributes to the main burden (deaths 474,002, 95% UI 355,077-606,537; DALYs 8,357,198, 95% UI 6,186,217-10,801,911 attributable to low temperature vs deaths 48,030, 95% UI 5,630-104,370; DALYs 1,089,329, 95% UI 112,690-2,375,345 attributable to high temperature in 2019). However, the burden due to high temperature has increased rapidly, especially among people aged older than 10 years, and was disproportionately concentrated in low sociodemographic index (SDI) regions such as Africa. In addition, the rapid increase in the stroke burden due to high temperature in Central Asia also requires special attention.

DISCUSSION

This is the first study to assess the global stroke burden attributed to nonoptimal temperature. The dramatic increase in the burden due to high temperature requires special attention, especially in low-SDI countries.

Feasibility of a novel blended-care intervention for fatigue after acquired brain injury: a pilot study of the Tied by Tiredness intervention

PURPOSE

Evidence-based treatments for fatigue after brain injury are scarce and often not personalized. An approach to foster personalization is Experience Sampling Methodology (ESM), consisting of repeated daily measurements of fatigue and related factors in daily life. We investigated the feasibility and usability of a novel six-week ESM-based intervention for fatigue after brain injury.

MATERIALS AND METHODS

Ten individuals with acquired brain injury (six men; four women) aged between 36-70 years (M = 53.3, SD = 12.9) used a mHealth application for three days each week during six-weeks; seven completed the intervention. Momentary fatigue, activities, mood, worrying, and social context were assessed with ESM and participants received weekly personalized feedback by a therapist..

RESULTS

56% of ESM-questionnaires (568/1008) were completed, providing detailed insights into individual fatigue patterns. No statistically significant decrease in response rate was found over the course of treatment. Qualitative feedback from participants revealed increased insight into factors underlying fatigue, and no problems with treatment duration or difficulties using the app. Five participants showed a decline in fatigue level during treatment.

CONCLUSIONS

This pilot study provides initial support for the feasibility and usability of this novel blended-care intervention, aimed at alleviating fatigue through personalized feedback and treatment strategies.

β-asarone inhibits autophagy by activating the PI3K/Akt/mTOR pathway in a rat model of depression in Parkinson's disease

OBJECTIVE

It is unclear whether β-asarone has a good antidepressant effect and what is the main mechanism in Depression in Parkinson's disease (DPD) model rats.

METHODS

In this study, DPD model rats were screened from 6-OHDA induced rats by sucrose preference test (SPT) and forced swimming test (FST). DPD model rats were divided into eight groups: model group, pramipexole group, β-asarone low-dose group (β-asarone 7.5 group), β-asarone medium-dose group (β-asarone 15 group), β-asarone high-dose group (β-asarone 30 group), 3-MA group, rapamycin group, and PI3K inhibitor group. 28 days after the end of treatment, open field test (OFT), SPT and FST were conducted in rats. The level of α-synuclein (α-syn) in the striatum was determined by enzyme-linked immunosorbent assay (ELISA). The expression of Beclin-1, p62 in the striatum was determined by western blot. The expression of PI3K, p-PI3K, Akt, p-Akt, mTOR, p-mTOR, Beclin-1, and p62 in the hippocampus was determined by western blot. The spine density of neurons in the hippocampus was detected by golgi staining.

RESULTS

The results showed that 4-week oral administration of β-asarone improve the motor and depressive symptoms of DPD model rats, and decrease the content of α-syn in the striatum. β-asarone inhibited the expression of autophagy in the striatum of DPD model rats. Furthermore, β-asarone decreased the levels of Beclin-1 protein, increased the expression of p62, p-PI3K, p-AKT, and p-mTOR, and improved the density of neuron dendritic spine in the hippocampus.

CONCLUSIONS

We concluded that β-asarone might improve the behavior of DPD model rats by activating the PI3K/Akt/mTOR pathway, inhibiting autophagy and protecting neuron.

Residential energy transition and chronic respiratory diseases

Obtaining clean energy is of prime importance for planetary health and sustainable development. We aimed to assess the association between residential energy transition and the risk of chronic respiratory diseases. Using data from the Global Health Observatory and Global Burden of Diseases, Injuries, and Risk Factors Study, we delineated the spatial distribution and temporal trends of the population using clean fuels for cooking at a global scale. In the China Health and Retirement Longitudinal Study, we performed rigorous and well-structured multistage analyses incorporating both cross-sectional and prospective data analyses to examine the associations between solid fuel use, residential energy transition, duration of solid fuel use, and the risk of chronic respiratory diseases. Despite great progress, huge disparities in access to clean energy persist globally. Residential energy transition was associated with a lower risk of chronic respiratory diseases. In the period of 2011-2013, compared with persistent solid fuel users, both participants who switched from solid to clean fuels (adjusted risk ratio [RR] 0.78, 95% confidence interval [CI] 0.62-0.98) and persistent clean fuel users (adjusted RR 0.71, 95% CI 0.57-0.89) had significantly lower risk of chronic respiratory diseases (p < 0.001 for trend). Consistent associations were observed in the period of 2011-2015 and 2011-2018. Household energy transition from solid to clean fuels could reduce the risk of chronic respiratory diseases. This is a valuable lesson for policy-makers and the general public to accelerate energy switching to alleviate the burden of chronic respiratory diseases and achieve health benefits, particularly in low- and middle-income countries.

DNA methylation mediates the effects of PM2.5 and O3 on ceramide metabolism: A novel mechanistic link between air pollution and insulin resistance

Insulin resistance (IR), linked to air pollution, is an initial stage of early-onset Type 2 diabetes mellitus (T2DM). While ceramide metabolism plays an important role in IR pathogenesis, the effects of air pollution on this process and its mechanisms remain unclear. We recruited young adults aged 18-30 years to a panel study in Wuhan, China. Using personal portable devices and stationary monitoring stations, we tracked particulate matter with aerodynamic diameters≤ 2.5 µm (PM2.5) and Ozone (O3) levels. Liquid chromatography/mass spectrometry (LC-MS) based metabolomics quantified ceramide metabolism, and Illumina Infinium Human Methylation 850 kBeadChip assay measured deoxyribonucleic acid (DNA) methylation. Linear mixed-effects models assessed relationships of air pollution with i) IR indexes, ii) ceramide metabolism, and iii) DNA methylation. Mediation analysis was subsequently performed to evaluate the potential mediating effect of DNA methylation in the association between air pollution and ceramide metabolism. PM2.5 and O3 were associated with elevated IR. Specifically, each 10 μg/m3 increase in PM2.5 and O3 at lag0-12 h significantly increased triglyceride‑glucose index (TyG index) and TyG-BMI (TyG - Body mass index) by 0.88%, 0.89% and 0.26%, 0.26%, respectively. Furthermore, levels of eight ceramides were altered by air pollution exposure, and nine methylated CpG sites in inflammation genes mediated the effects of air pollution on ceramide metabolism. Our findings imply the existence of a novel mechanism connecting air pollution to IR.

Impact of fine particulate matter on liver injury: evidence from human, mice and cells

BACKGROUND

A recently discovered risk factor for chronic liver disease is ambient fine particulate matter (PM2.5). Our research aims to elucidate the effects of PM2.5 on liver injury and the potential molecular mechanisms.

METHODS AND RESULTS

A population-based longitudinal study involving 102,918 participants from 15 Chinese cities, using linear mixed-effect models, found that abnormal alterations in liver function were significantly associated with long-term exposure to PM2.5. The serum levels of alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, direct bilirubin, and triglyceride increased by 2.05%, 2.04%, 0.58%, 2.99%, and 1.46% with each 10 µg/m3 increase in PM2.5. In contrast, the serum levels of total protein, albumin, and prealbumin decreased by 0.27%, 0.48%, and 2.42%, respectively. Mice underwent chronic inhalation exposure to PM2.5 experienced hepatic inflammation, steatosis and fibrosis. In vitro experiments found that hepatocytes experienced an inflammatory response and lipid metabolic dysregulation due to PM2.5, which also activated hepatic stellate cells. The down-regulation and mis-localization of polarity protein Par3 mediated PM2.5-induced liver injury.

CONCLUSIONS

PM2.5 exposure induced liver injury, mainly characterized by steatosis and fibrosis. The down-regulation and mis-localization of Par3 were important mechanisms of liver injury induced by PM2.5.

Causal association between long-term exposure to air pollution and incident Parkinson's disease

Epidemiological evidence for long-term air pollution exposure and Parkinson's disease (PD) is controversial, and analysis of causality is limited. We identified 293,888 participants who were free of PD at baseline in the UK Biobank (2006-2010). Time-varying air pollution [fine particulate (PM2.5) and ozone (O3)] exposures were estimated using spatio-temporal models. Incident cases of PD were identified using validated algorithms. Four methods were used to investigate the associations between air pollution and PD, including (1) standard time-varying Cox proportional-hazard model; (2) Cox models weighted by generalized propensity score (GPS) and inverse-probability weights (IPW); (3) instrumental variable (IV) analysis; and (4) negative control outcome analysis. During a median of 11.6 years of follow-up, 1822 incident PD cases were identified. Based on standard Cox regression, the hazard ratios (95% confidence interval) for a 1 µg/m3 or ppb increase in PM2.5 and O3 were 1.23 (1.17, 1.30) and 1.02 (0.98, 1.05), respectively. Consistent results were found in models weighted by GPS and IPW, and in IV analysis. There were no significant associations between air pollution and negative control outcomes. This study provides evidence to support a causal association between PM2.5 exposure and PD. Mitigation of air pollution could be a protective measure against PD.