Ambient exposure to fine particulate matter with oxidative potential affects oxidative stress biomarkers in pregnancy.

Prenatal exposures to ambient particulate matter (PM2.5) from traffic may generate oxidative stress, and thus contribute to adverse birth outcomes. We investigated whether PM2.5 constituents from brake and tire wear affect levels of oxidative stress biomarkers (malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG)) using urine samples collected up to three times during pregnancy in 156 women recruited from antenatal clinics at the University of California Los Angeles. Land use regression models with co-kriging were employed to estimate average residential outdoor concentrations of black carbon (BC), PM2.5 mass, PM2.5 metal components, and three PM2.5 oxidative potential metrics during the 4-weeks prior to urine sample collection. 8-OHdG concentrations in mid-pregnancy increased by 24.8% (95% CI: 9.0, 42.8) and 14.3% (95% CI: 0.4%, 30.0%) per interquartile range (IQR) increase in PM2.5 mass and BC, respectively. The brake wear marker (barium) and the oxidative potential metrics were associated with increased MDA concentration in the 1st sample collected (10-17 gestational week), but 95% CIs included the null. Traffic-related air pollution contributed in early to mid-pregnancy to oxidative stress generation previously linked to adverse birth outcomes.

Untargeted serum metabolic profiling of diabetes mellitus among Parkinson's disease patients.

Type 2 diabetes mellitus (T2DM) is a common comorbidity among Parkinson's disease (PD) patients. Yet, little is known about dysregulated pathways that are unique in PD patients with T2DM. We applied high-resolution metabolomic profiling in serum samples of 636 PD and 253 non-PD participants recruited from Central California. We conducted an initial discovery metabolome-wide association and pathway enrichment analysis. After adjusting for multiple testing, in positive (or negative) ion mode, 30 (25) metabolic features were associated with T2DM in both PD and non-PD participants, 162 (108) only in PD participants, and 32 (7) only in non-PD participants. Pathway enrichment analysis identified 17 enriched pathways associated with T2DM in both the PD and non-PD participants, 26 pathways only in PD participants, and 5 pathways only in non-PD participants. Several amino acid, nucleic acids, and fatty acid metabolisms were associated with T2DM only in the PD patient group suggesting a possible link between PD and T2DM.

Urinary polycyclic aromatic hydrocarbon metabolites and their association with oxidative stress among pregnant women in Los Angeles.

Background: Polycyclic aromatic hydrocarbons (PAHs) have been linked to adverse birth outcomes, but few epidemiological studies to date have evaluated associations between urinary PAH metabolites and oxidative stress biomarkers in pregnancy. Methods: We measured a total of 7 PAH metabolites and 2 oxidative stress biomarkers (malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG)) in urine samples collected up to three times during pregnancy in 159 women enrolled at antenatal clinics at the University of California Los Angeles during 2016-2019. Using multiple linear regression models, we estimated the percentage change (%) and 95% confidence interval (CI) in 8-OHdG and MDA measured at each sample collection time per doubling of PAH metabolite concentrations. Results: Most PAH metabolites were positively associated with both urinary oxidative stress biomarkers, MDA and 8-OHdG, with stronger associations in early and late pregnancy. Women pregnant with male fetuses exhibited slightly larger increases in both MDA and 8-OHdG in association with PAH exposures in early and late pregnancy. Conclusion: Urinary OH-PAH biomarkers are associated with increases in oxidative stress during pregnancy, especially in early and late pregnancy. Sex differences in associations between PAH exposures and oxidative stress need to be further explored in the future.

Diet and the gut microbiome in patients with Parkinson's disease.

It has been suggested that gut microbiota influence Parkinson's disease (PD) via the gut-brain axis. Here, we examine associations between diet and gut microbiome composition and its predicted functional pathways in patients with PD. We assessed gut microbiota in fecal samples from 85 PD patients in central California using 16S rRNA gene sequencing. Diet quality was assessed by calculating the Healthy Eating Index 2015 (HEI-2015) based on the Diet History Questionnaire II. We examined associations of diet quality, fiber, and added sugar intake with microbial diversity, composition, taxon abundance, and predicted metagenomic profiles, adjusting for age, sex, race/ethnicity, and sequencing platform. Higher HEI scores and fiber intake were associated with an increase in putative anti-inflammatory butyrate-producing bacteria, such as the genera Butyricicoccus and Coprococcus 1. Conversely, higher added sugar intake was associated with an increase in putative pro-inflammatory bacteria, such as the genera Klebsiella. Predictive metagenomics suggested that bacterial genes involved in the biosynthesis of lipopolysaccharide decreased with higher HEI scores, whereas a simultaneous decrease in genes involved in taurine degradation indicates less neuroinflammation. We found that a healthy diet, fiber, and added sugar intake affect the gut microbiome composition and its predicted metagenomic function in PD patients. This suggests that a healthy diet may support gut microbiome that has a positive influence on PD risk and progression.

Ambient long-term exposure to organophosphorus pesticides and the human gut microbiome: an observational study.

BACKGROUND: Organophosphorus pesticides (OP) have been associated with various human health conditions. Animal experiments and in-vitro models suggested that OP may also affect the gut microbiota. We examined associations between ambient chronic exposure to OP and gut microbial changes in humans. METHODS: We recruited 190 participants from a community-based epidemiologic study of Parkinson's disease living in a region known for heavy agricultural pesticide use in California. Of these, 61% of participants had Parkinson's disease and their mean age was 72 years. Microbiome and predicted metagenome data were generated by 16S rRNA gene sequencing of fecal samples. Ambient long-term OP exposures were assessed using pesticide application records combined with residential addresses in a geographic information system. We examined gut microbiome differences due to OP exposures, specifically differences in microbial diversity based on the Shannon index and Bray-Curtis dissimilarities, and differential taxa abundance and predicted Metacyc pathway expression relying on regression models and adjusting for potential confounders. RESULTS: OP exposure was not associated with alpha or beta diversity of the gut microbiome. However, the predicted metagenome was sparser and less evenly expressed among those highly exposed to OP (p = 0.04). Additionally, we found that the abundance of two bacterial families, 22 genera, and the predicted expression of 34 Metacyc pathways were associated with long-term OP exposure. These pathways included perturbed processes related to cellular respiration, increased biosynthesis and degradation of compounds related to bacterial wall structure, increased biosynthesis of RNA/DNA precursors, and decreased synthesis of Vitamin B1 and B6. CONCLUSION: In support of previous animal studies and in-vitro findings, our results suggest that ambient chronic OP pesticide exposure alters gut microbiome composition and its predicted metabolism in humans.

Maternal dietary patterns and placental outcomes among pregnant women in Los Angeles.

INTRODUCTION: Epidemiological studies have linked prenatal maternal diet to fetal growth, but whether diet affects placental outcomes is poorly understood. METHODS: We collected past month dietary intake from 148 women in mid-pregnancy enrolled at University of California Los Angeles (UCLA) antenatal clinics from 2016 to 2019. We employed the food frequency Diet History Questionnaire II and generated the Healthy Eating Index-2015 (HEI-2015), the Alternate Healthy Eating Index for Pregnancy (AHEI-P), and the Alternate Mediterranean Diet (aMED). We conducted T2-weighted magnetic resonance imaging (MRI) in mid-pregnancy (1st during 14-17 and 2nd during 19-24 gestational weeks) to evaluate placental volume (cm3) and we measured placenta weight (g) at delivery. We estimated change and 95 % confidence interval (CI) in placental volume and associations of placenta weight with all dietary index scores and diet items using linear regression models. RESULTS: Placental volume in mid-pregnancy was associated with an 18.9 cm3 (95 % CI 5.1, 32.8) increase per 100 gestational days in women with a higher HEI-2015 (≥median), with stronger results for placentas of male fetuses. We estimated positive associations between placental volume at the 1st and 2nd MRI and higher intake of vegetables, high-fat fish, dairy, and dietary intake of B vitamins. A higher aMED (≥median) score was associated with a 40.5 g (95 % CI 8.5, 72.5) increase in placenta weight at delivery, which was mainly related to protein intake. DISCUSSION: Placental growth represented by volume in mid-pregnancy and weight at birth is influenced by the quality and content of the maternal diet.

Untargeted serum metabolomics reveals novel metabolite associations and disruptions in amino acid and lipid metabolism in Parkinson's disease.

BACKGROUND: Untargeted high-resolution metabolomic profiling provides simultaneous measurement of thousands of metabolites. Metabolic networks based on these data can help uncover disease-related perturbations across interconnected pathways. OBJECTIVE: Identify metabolic disturbances associated with Parkinson's disease (PD) in two population-based studies using untargeted metabolomics. METHODS: We performed a metabolome-wide association study (MWAS) of PD using serum-based untargeted metabolomics data derived from liquid chromatography with high-resolution mass spectrometry (LC-HRMS) using two distinct population-based case-control populations. We also combined our results with a previous publication of 34 metabolites linked to PD in a large-scale, untargeted MWAS to assess external validation. RESULTS: LC-HRMS detected 4,762 metabolites for analysis (HILIC: 2716 metabolites; C18: 2046 metabolites). We identified 296 features associated with PD at FDR<0.05, 134 having a log2 fold change (FC) beyond ±0.5 (228 beyond ±0.25). Of these, 104 were independently associated with PD in both discovery and replication studies at p<0.05 (170 at p<0.10), while 27 were associated with levodopa-equivalent dose among the PD patients. Intriguingly, among the externally validated features were the microbial-related metabolites, p-cresol glucuronide (FC=2.52, 95% CI=1.67, 3.81, FDR=7.8e-04) and p-cresol sulfate. P-cresol glucuronide was also associated with motor symptoms among patients. Additional externally validated metabolites associated with PD include phenylacetyl-L-glutamine, trigonelline, kynurenine, biliverdin, and pantothenic acid. Novel associations include the anti-inflammatory metabolite itaconate (FC=0.79, 95% CI=0.73, 0.86; FDR=2.17E-06) and cysteine-S-sulfate (FC=1.56, 95% CI=1.39, 1.75; FDR=3.43E-11). Seventeen pathways were enriched, including several related to amino acid and lipid metabolism. CONCLUSIONS: Our results revealed PD-associated metabolites, confirming several previous observations, including for p-cresol glucuronide, and newly implicating interesting metabolites, such as itaconate. Our data also suggests metabolic disturbances in amino acid and lipid metabolism and inflammatory processes in PD.

Fine Particulate Matter Metal Composition, Oxidative Potential, and Adverse Birth Outcomes in Los Angeles.

BACKGROUND: Although many studies have linked prenatal exposure to PM2.5 to adverse birth outcomes, little is known about the effects of exposure to specific constituents of PM2.5 or mechanisms that contribute to these outcomes. OBJECTIVES: Our objective was to investigate effects of oxidative potential and PM2.5 metal components from non-exhaust traffic emissions, such as brake and tire wear, on the risk of preterm birth (PTB) and term low birth weight (TLBW). METHODS: For a birth cohort of 285,614 singletons born in Los Angeles County, California, in the period 2017-2019, we estimated speciated PM2.5 exposures modeled from land use regression with cokriging, including brake and tire wear related metals (barium and zinc), black carbon, and three markers of oxidative potential (OP), including modeled reactive oxygen species based on measured iron and copper (ROS), OH formation (OPOH), and dithiothreitol (DTT) loss (OPDTT). Using logistic regression, we estimated odds ratios (OR) and 95% confidence intervals (CI) for PTB and TLBW with speciated PM2.5 exposures and PM2.5 mass as continuous variables scaled by their interquartile range (IQR). RESULTS: For both metals and oxidative potential metrics, we estimated increased risks for PTB (ORs ranging from 1.01 to 1.03) and TLBW (ORs ranging from 1.02 to 1.05) per IQR exposure increment that were robust to adjustment for PM2.5 mass. Associations for PM2.5 mass, black carbon, metal components, and oxidative potential (especially ROS and OPOH) with adverse birth outcomes were stronger in Hispanic, Black, and mixed-race or Native American women. DISCUSSION: Our results indicate that exposure to PM2.5 metals from brake and tire wear and particle components that contribute to oxidative potential were associated with an increased risk of PTB and TLBW in Los Angeles County, particularly among Hispanic, Black, and mixed-race or Native American women. Thus, reduction of PM2.5 mass only may not be sufficient to protect the most vulnerable pregnant women and children from adverse effects due to traffic source exposures. https://doi.org/10.1289/EHP12196.

Diet quality and Parkinson's disease: Potential strategies for non-motor symptom management.

INTRODUCTION: Parkinson's disease (PD) is now considered a systemic disease, and some phenotypes may be modifiable by diet. We will compare the diet quality and intake of specific nutrients and food groups of PD patients with household and community controls to examine how diet may influence PD clinical features. METHODS: We conducted a case-control study of 98 PD patients and 83 controls (household = 53; community = 30) in central California, assessing dietary habits over the past month and calculating the Healthy Eating Index (HEI)-2015. We employed multivariate logistic and linear regression analyses to assess associations between diet and PD status, PD symptom profiles, and medication, adjusting for relevant confounders. RESULTS: PD patients had a lower HEI score than controls, with an OR of 0.65 (95% CI: 0.45, 0.94) per 10-points increase in HEI. Lower-quality diet was characterized by higher intakes of carbohydrates, total and added sugars, and trans fats and lower intakes of fiber, folate, unsaturated fatty acids, protein, and fat. PD patients with chronic constipation had a 4.84 point lower HEI score than those without (ß per 10-point in HEI: -0.48; 95% CI: -0.97, -0.00). Furthermore, patients on high dopamine agonist doses consumed more sugar than those on lower doses. CONCLUSION: PD patients consume a lower-quality diet compared to household and community controls. Dietary modifications may alleviate non-motor symptoms like constipation, and promoting a healthy diet should become a part of routine care and disease management for PD patients, with special attention on agonist-treated and hyposmic patients.

Ethnicity and Parkinson's Disease: Motor and Nonmotor Features and Disease Progression in Latino Patients Living in Rural California.

BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disorder among older adults worldwide. Currently, studies of PD progression rely primarily on White non-Latino (WNL) patients. Here, we compare clinical profiles and PD progression in Latino and WNL patients enrolled in a community-based study in rural Central California. METHOD: PD patients within 5 years of diagnosis were identified from 3 counties between 2001 and 2015. During up to 3 visits, participants were examined by movement disorders specialists and interviewed. We analyzed cross-sectional differences in PD clinical features severity at each study visit and used linear mixed models and Cox proportional hazards models to compare motor, nonmotor, and disability progression longitudinally and to assess time to death in Latinos compared to WNL patients. RESULTS: Of 775 patients included, 138 (18%) self-identified as Latino and presented with earlier age at diagnosis (63.6 vs 68.9) and death (78.6 vs 81.5) than WNL. Motor (hazard ratio [HR] = 1.17 [0.71, 1.94]) and nonmotor symptoms did not progress faster in Latino versus WNL patients after accounting for differences in baseline symptom severity. However, Latino patients progressed to disability stages according to Hoehn and Yahr faster than WNL (HR = 1.81 [1.11, 2.96]). Motor and nonmotor symptoms in Latino patients were also medically managed less well than in WNL. CONCLUSIONS: Our PD study with a large proportion of Latino enrollees and progression data reveals disparities in clinical features and progression by ethnicity that may reflect healthcare access and structural socioeconomic disadvantages in Latino patients with PD.

Proximity to residential and workplace pesticides application and the risk of progression of Parkinson's diseases in Central California.

BACKGROUND: Pesticide exposure has consistently been associated with Parkinson's disease (PD) onset. Yet, fewer epidemiologic studies have examined whether pesticides influence PD motor and non-motor symptom progression. OBJECTIVES: Using a geographic information system tool that integrates agricultural pesticide use reports and land use records to derive ambient exposures at residences and workplaces, we assessed associations between specific pesticides previously related to PD onset with PD symptom progression in two PD patient cohorts living in agricultural regions of California. METHODS: We calculated the pounds of pesticide applied agriculturally near each participant's residential or occupational addresses from 1974 to the year of PD diagnosis, using a geographic information system tool that links the California Pesticide Use Reports database to land use data. We examined 53 pesticides selected a priori as they have previously been associated with PD onset. We longitudinally followed two PD patient cohorts (PEG1 N = 242, PEG2 N = 259) for an average of 5.0 years (SD ± 3.5) and 2.7 years (SD ± 1.6) respectively and assessed PD symptoms using the movement disorder specialist-administered Unified Parkinson's disease Rating Scale part III (UPDRS), Mini-Mental State Examination (MMSE), and Geriatric Depression Scale (GDS). Weighted time-to-event regression models were implemented to estimate effects. RESULTS: Ten agricultural pesticides, including copper sulfate (pentahydrate), 2-methyl-4-chlorophenoxyacetic acid (MCPA) dimethylamine salt, tribufos, sodium cacodylate, methamidophos, ethephon, propargite, bromoxynil octanoate, monosodium methanearsonate (MSMA), and dicamba, were associated with faster symptom progression. Among these pesticides, residential or workplace proximity to higher amounts of copper sulfate (pentahydrate) and MCPA (dimethylamine salt) was associated with all three progression endpoints (copper sulfate: HRs = 1.22-1.36, 95 % CIs = 1.03-1.73; MCPA: HRs = 1.27-1.35, 95 % CIs = 1.02-1.70). CONCLUSIONS: Our findings suggest that pesticide exposure may not only be relevant for PD onset but also PD progression phenotypes. We have implicated ten specific pesticide active ingredients in faster PD motor and non-motor decline.

Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position.

Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 µm in diameter (PM2.5) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical composition and how OP varies by land use type and neighborhood socioeconomic position in the Los Angeles area. We measured OH formation (OPOH), dithiothreitol loss (OPDTT), black carbon, and 52 metals and elements for 54 total PM2.5 samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OPOH: vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OPOH, followed by 21% from brake and tire wear. Similar results were observed for the OPDTT source apportionment. Furthermore, by linking measured PM2.5 and OP with census tract level socioeconomic and health outcome data provided by CalEnviroScreen, we found that the most disadvantaged neighborhoods were exposed to both the most toxic particles and the highest particle concentrations. OPOH exhibited the largest inverse social gradients, followed by OPDTT and PM2.5 mass. Finally, OPOH was the metric most strongly correlated with adverse health outcome indicators.

Immune system disruptions implicated in whole blood epigenome-wide association study of depression among Parkinson's disease patients.

Although Parkinson's Disease (PD) is typically described in terms of motor symptoms, depression is a common feature. We explored whether depression influences blood-based genome-wide DNA methylation (DNAm) in 692 subjects from a population-based PD case-control study, using both a history of clinically diagnosed depression and current depressive symptoms measured by the geriatric depression scale (GDS). While PD patients in general had more immune activation and more accelerated epigenetic immune system aging than controls, the patients experiencing current depressive symptoms (GDS≥5) showed even higher levels of both markers than patients without current depressive symptoms (GDS<5). For PD patients with a history of clinical depression compared to those without, we found no differences in immune cell composition. However, a history of clinical depression among patients was associated with differentially methylated CpGs. Epigenome-wide association analysis (EWAS) revealed 35 CpGs associated at an FDR≤0.05 (569 CpGs at FDR≤0.10, 1718 CpGs at FDR≤0.15). Gene set enrichment analysis implicated immune system pathways, including immunoregulatory interactions between lymphoid and non-lymphoid cells (p-adj = 0.003) and cytokine-cytokine receptor interaction (p-adj = 0.004). Based on functional genomics, 25 (71%) of the FDR≤0.05 CpGs were associated with genetic variation at 45 different methylation quantitative trait loci (meQTL). Twenty-six of the meQTLs were also expression QTLs (eQTLs) associated with the abundance of 53 transcripts in blood and 22 transcripts in brain (substantia nigra, putamen basal ganglia, or frontal cortex). Notably, cg15199181 was strongly related to rs823114 (SNP-CpG p-value = 3.27E-310), a SNP identified in a PD meta-GWAS and related to differential expression of PM20D1, RAB29, SLC41A1, and NUCKS1. The entire set of genes detected through functional genomics was most strongly overrepresented for interferon-gamma-mediated signaling pathway (enrichment ratio = 18.8, FDR = 4.4e-03) and T cell receptor signaling pathway (enrichment ratio = 13.2, FDR = 4.4e-03). Overall, the current study provides evidence of immune system involvement in depression among Parkinson's patients.

Parkinson's Disease and the Gut Microbiome in Rural California.

BACKGROUND: Increasing evidence connects the gut microbiome to Parkinson's disease (PD) etiology, but little is known about microbial contributions to PD progression and its clinical features. OBJECTIVE: We aim to explore the association between the gut microbiome with PD, and the microbial association with PD-specific clinical features. METHODS: In a community-based case-control study of 96 PD patients and 74 controls, microbiome data were obtained from 16S rRNA gene sequencing of fecal samples, and analyzed for microbial diversity, taxa abundance, and predicted functional pathways that differed in PD patients and controls, and their association with PD-specific features (disease duration, motor subtypes, L-DOPA daily dose, and motor function). RESULTS: PD patients' gut microbiome showed lower species diversity (p = 0.04) and were compositionally different (p = 0.002) compared to controls but had a higher abundance of three phyla (Proteobacteria, Verrucomicrobiota, Actinobacteria) and five genera (Akkermansia, Enterococcus, Hungatella, and two Ruminococcaceae) controlling for sex, race, age, and sequencing platform. Also, 35 Metacyc pathways were predicted to be differentially expressed in PD patients including biosynthesis, compound degradation/utilization/assimilation, generation of metabolites and energy, and glycan pathways. Additionally, the postural instability gait dysfunction subtype was associated with three phyla and the NAD biosynthesis pathway. PD duration was associated with the Synergistota phylum, six genera, and the aromatic compound degradation pathways. Two genera were associated with motor function. CONCLUSION: PD patients differed from controls in gut microbiome composition and its predicted metagenome. Clinical features were also associated with bacterial taxa and altered metabolic pathways of interest for PD progression.

Co-kriging with a low-cost sensor network to estimate spatial variation of brake and tire-wear metals and oxidative stress potential in Southern California.

Due to regulations and technological advancements reducing tailpipe emissions, an increasing proportion of emissions arise from brake and tire wear particulate matter (PM). PM from these non-tailpipe sources contains heavy metals capable of generating oxidative stress in the lung. Although important, these particles remain understudied because the high cost of actively collecting filter samples. Improvements in electrical engineering, internet connectivity, and an increased public concern over air pollution have led to a proliferation of dense low-cost air sensor networks such as the PurpleAir monitors, which primarily measure unspeciated fine particulate matter (PM2.5). In this study, we model the concentrations of Ba, Zn, black carbon, reactive oxygen species concentration in the epithelial lining fluid, dithiothreitol (DTT) loss, and OH formation. We use a co-kriging approach, incorporating data from the PurpleAir network as a secondary predictor variable and a land-use regression (LUR) as an external drift. For most pollutant species, co-kriging models produced more accurate predictions than an LUR model, which did not incorporate data from the PurpleAir monitors. This finding suggests that low-cost sensors can enhance predictions of pollutants that are costly to measure extensively in the field.

Aircraft noise and vehicle traffic-related air pollution interact to affect preterm birth risk in Los Angeles, California.

INTRODUCTION: Air pollution has been linked to preterm birth (PTB) while findings for noise exposure have been mixed. Few studies - none considering airports - have investigated combined exposures. We explore the relationship between joint exposure to airport-related noise, airport ultrafine particles (UFP), and vehicle traffic-related air pollution (TRAP) on risk of PTB near Los Angeles International Airport (LAX). METHODS: We used comprehensive birth data for mothers living ≤15 km from LAX from 2008 to 2016 (n = 174,186) Noise data were generated by monitor-validated models. NO2 was used as a TRAP proxy, estimated with a seasonally-adjusted, validated land-use regression model. We estimated the effects of exposure to airport-related noise and TRAP on PTB employing logistic regression models that adjusted for known maternal risk factors for PTB as well as aircraft-origin UFP and neighborhood characteristics. RESULTS: The adjusted odds ratio (aOR) for PTB from high noise exposure (i.e. > 65 dB) was 1.10 (95% CI: 1.01-1.19). Relative to the first quartile, the aORs for PTB in the second, third, and fourth TRAP quartiles were 1.10 (95% CI: 1.05-1.16), 1.11 (95% CI: 1.05-1.16), and 1.15 (95% CI: 1.10-1.22), respectively. When stratifying by increasing TRAP quartiles, the aORs for PTB with high airport-related noise were 1.04 (95% CI: 0.91-1.18), 1.02 (95% CI: 0.88-1.19), 1.24 (95% CI: 1.03-1.48), and 1.44 (95% CI: 1.08-1.91) (p-interaction = 0.06). CONCLUSION: Our results suggest a potential synergism between airport-related noise and TRAP exposures on increasing the risk of PTB in this metropolitan area.

Elemental composition of fine and coarse particles across the greater Los Angeles area: Spatial variation and contributing sources.

The inorganic components of particulate matter (PM), especially transition metals, have been shown to contribute to PM toxicity. In this study, the spatial distribution of PM elements and their potential sources in the Greater Los Angeles area were studied. The mass concentration and detailed elemental composition of fine (PM2.5) and coarse (PM2.5-10) particles were assessed at 46 locations, including urban traffic, urban community, urban background, and desert locations. Crustal enrichment factors (EFs), roadside enrichments (REs), and bivariate correlation analysis revealed that Ba, Cr, Cu, Mo, Pd, Sb, Zn, and Zr were associated with traffic emissions in both PM2.5 and PM2.5-10, while Fe, Li, Mn, and Ti were affected by traffic emissions mostly in PM2.5. The concentrations of Ba, Cu, Mo, Sb, Zr (brake wear tracers), Pd (tailpipe tracer), and Zn (associated with tire wear) were higher at urban traffic sites than urban background locations by factors of 2.6-4.6. Both PM2.5 and PM2.5-10 elements showed large spatial variations, indicating the presence of diverse emission sources across sampling locations. Principal component analysis extracted four source factors that explained 88% of the variance in the PM2.5 elemental concentrations, and three sources that explained 86% of the variance in the PM2.5-10 elemental concentrations. Based on multiple linear regression analysis, the contribution of traffic emissions (27%) to PM2.5 was found to be higher than mineral dust (23%), marine aerosol (18%), and industrial emissions (8%). On the other hand, mineral dust was the dominant source of PM2.5-10 with 45% contribution, followed by marine aerosol (22%), and traffic emissions (19%). This study provides novel insight into the spatial variation of traffic-related elements in a large metropolitan area.

α-Synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson's disease from multiple system atrophy.

The diagnosis of Parkinson's disease (PD) and atypical parkinsonian syndromes is difficult due to the lack of reliable, easily accessible biomarkers. Multiple system atrophy (MSA) is a synucleinopathy whose symptoms often overlap with PD. Exosomes isolated from blood by immunoprecipitation using CNS markers provide a window into the brain's biochemistry and may assist in distinguishing between PD and MSA. Thus, we asked whether α-synuclein (α-syn) in such exosomes could distinguish among healthy individuals, patients with PD, and patients with MSA. We isolated exosomes from the serum or plasma of these three groups by immunoprecipitation using neuronal and oligodendroglial markers in two independent cohorts and measured α-syn in these exosomes using an electrochemiluminescence ELISA. In both cohorts, α-syn concentrations were significantly lower in the control group and significantly higher in the MSA group compared to the PD group. The ratio between α-syn concentrations in putative oligodendroglial exosomes compared to putative neuronal exosomes was a particularly sensitive biomarker for distinguishing between PD and MSA. Combining this ratio with the α-syn concentration itself and the total exosome concentration, a multinomial logistic model trained on the discovery cohort separated PD from MSA with an AUC = 0.902, corresponding to 89.8% sensitivity and 86.0% specificity when applied to the independent validation cohort. The data demonstrate that a minimally invasive blood test measuring α-syn in blood exosomes immunoprecipitated using CNS markers can distinguish between patients with PD and patients with MSA with high sensitivity and specificity. Future optimization and validation of the data by other groups would allow this strategy to become a viable diagnostic test for synucleinopathies.