Mixtures Of Contaminants Research Articles

Evolution of research on air emissions from agricultural activities: A comprehensive review.

Air pollutant emissions from the agricultural sector are among the most critical issues affecting human health and the environment. This sector releases a complex mixture of biological, microbial, and inorganic contaminants into the air from land preparation, crop production, fertilization, harvesting, biomass burning, machinery use, livestock production, manure management, waste management, and deforestation. This article aims to identify the evolution and global research trends related to air contaminant emissions, specifically from the agricultural sector. This study systematically analyzed the knowledge map derived from 4016 scientific publications from 1990 to 2023. From an evolutionary perspective, the bibliometric and networking analysis revealed a consistent increase in scientific publications over the past 34years, with the contribution of 117 countries, more than 1600 authors, and 1300 journals. Additionally, it sheds light on the most studied pollutants, measurement techniques, and modeling employed to comprehend and mitigate the impact of these pollutants on yield, human health, biodiversity, and climate change. Furthermore, the research facilitates the identification of emerging air pollutants considering agricultural activities such as crop production, waste crop management, livestock production, manure management, deforestation, and land change use. These findings underscore the evolution of the research, identifying the main topics of interest, the emerging topics, and the future of research on air pollutant emissions.

Uncertainty Analysis in Ecological Risk Assessment: Sensitivity Analysis of Different Exposure Models

Ecological risk assessments are used for decision making regarding releasing new products to market as well as remedial action required to address contamination at legacy sites. Uncertainty analysis is considered a key part of the process (USEPA 1997) but assessments seldom address uncertainty quantitatively. Key sources of uncertainty include: Sampling and analytical variability (soil/ sediment matrix, lab error), Choice of “Indicator” Species as Target Receptors for Different Exposure Pathways, Sample size. Bioaccumulation and Food Chain Modeling involve assumptions and uncertainty including: Linear assumption of bioaccumulation and selection of bioaccumulation factors; Other model inputs such as: Home range size, Dietary percentages, Body Weights, Ingestion Rate; Literature data on effects, Use of No Observed Adverse Effects Level (NOAEL) or Lowest Observed Adverse Effects Level (LOAEL) as a decision point. Toxicity testing where employed brings its own set of assumptions and interpretation that are subject to uncertainty. These include: Use of single organism, Correlation (or lack thereof) with Contaminants of Concern, Contaminant mixtures, and Reference area selection. Keywords: Ecotoxicology, Risk Assessment, Ecology

Evaluation of pilot-scale drinking water treatment trains using a panel of bioassays

ABSTRACT Chemical water quality monitoring is increasingly complemented with bioassays. The performance of drinking water treatment technologies was evaluated with bioassays. CALUX bioassays and the Ames fluctuation bioassay for mutagenicity were used to analyze the responses of raw feed water with and without a spiking mixture of organic contaminants in different pilot-scale water treatment trains applying advanced oxidation processes, reverse osmosis and filtration with activated carbon for the preparation of drinking water. In general, CALUX responses in the spiked feed water were in the same range as in the unspiked feed water, indicating that spiking did not significantly elevate the activity measured in the feed water. This observation was in line with a calculation of the combined additive behavior of the spiking mixture using bioactivities of the spiked chemicals in analog bioassays from ToxCast. This calculation gave no indication of a measurable response in the bioassays to be expected by the spiking, except for oxidative stress. Responses in the Ames fluctuation assay in most feed water were in some cases increased by advanced oxidation processes (AOPs) and mostly removed by active concentrations. The bioassay responses demonstrate the removal of emerging chemicals with different mechanisms of action by different water treatment technologies.

Determining bad actors: A linear mixed effects model approach to elucidate behavioral toxicity of metal mixtures in drinking water

Mixtures of chemical contaminants can pose a significant health risk to humans and wildlife, even at levels considered safe for each individual chemical. There is a critical need to develop statistical methods to evaluate the drivers of toxic effects in chemical mixtures (i.e., bad actors) from exposure studies. Here, we develop a hierarchical modeling framework to disentangle the toxicity of complex metal mixtures from a screening study of 92 drinking well water samples containing multiple metal elements from Maine and New Hampshire, USA. In order to screen for neurodevelopmental impacts from exposure to these drinking water samples, we use a larval zebrafish (Danio rerio) behavioral assay. Zebrafish are an advantageous toxicological model organism due to combining the complexity of a vertebrate organism and higher-throughput exposure methods. We formulate a linear mixed modeling approach that captures intrinsic complexity in a common larval behavioral assay in order to improve its sensitivity and rigor and identify drivers of behavioral toxicity from the metal mixtures within the drinking water samples. Our analysis identifies lead (Pb), cadmium (Cd), nickel (Ni), copper (Cu), barium (Ba), and uranium (U) as metals that consistently impact larval locomotor activity, individually and across nine pairs of those metals. Our model also elucidates three distinct clusters of metal mixture components that drive behavioral effects: (Ba:Cu:U), (Ni:Pb:U), (Ba:Pb:U). Having identified a set of “bad-actor” metals from the water samples, we conduct exposure experiments for each individual metal (Pb, Cd, Ni, Cu, and Ba) at levels considered safe by the US Environmental Protection Agency drinking water regulatory limits and validate Pb, Ni, Cu, and Ba as behavioral toxicants at these concentrations. Collectively, our modeling approach estimates the impact of metal elements on a complex behavioral outcome in a statistically robust manner and establishes an approach to capture “bad actors” and key chemical interactions in a complex mixture.

Speciation of the Removed Pollutants in Bioremediation of Hydrocarbon-Contaminated Soil

The biological removal of a mixture of soil contaminants, namely, hydrocarbons, is not equally efficient for each compound. Some pollutants can be metabolized by the microbial consortium but also generated again as by-products from the removal of others. At the end of the runs, notwithstanding the high integral removal, single compounds can still be present with a relevant concentration. This paper presents the results achieved in a study of the aerobic degradation of diesel oil in three mesocosms carried out for several months with the same operative conditions. They differed in biological management: Natural Attenuation (NA), Biostimulated without inoculation (BS), and Biostimulated with Inoculation (BS + IN). At the end of the runs, the pollution removal was calculated by measuring the residual diesel oil, both as an average in the total amount of soil and only at the bottom of each column. The overall removal was around 2%, 66%, and 72% for NA, BS and BS + IN, reduced to 0%, 48%, and 47%, respectively, if measured only at the bottom. For the biostimulated mesocosms, the speciation of the hydrocarbons was carried out to assess their concentration. The findings evidence the need to delve deeper into this issue and assess the speciation of contaminants.

Examining Bald Eagle Contaminant Exposure and Reproductive Risk Above and Below Dams on Great Lakes Tributaries

Removing lowermost dams can reestablish fish passage on Great Lakes tributaries. This can increase the transfer of contaminants from anadromous fish to piscivorous wildlife upstream; however, concentrations of bioaccumulative contaminants in Great Lakes fish have decreased over the last several decades. We analyzed concentrations of PCBs and the toxic equivalence (TEQs) calculated from PCBs, DDTs, other organochlorine pesticides, and PBDEs in the plasma of bald eagle nestlings above and below lowermost dams on five river systems in Michigan from 1999 to 2013. We examined relationships between contaminants and metrics of reproductive success from 1997 to 2018, including the effects of year and location relative to the lowermost dam. Σ20PCB and p,p’-DDE were important in characterizing differences in contaminant mixtures above and below dams. Concentrations of contaminants were generally greater below dams than above. There were generally greater nest success and more nestlings per nest below dams, but nest location explained little variability (R2 values = 0.03–0.15). Neither Σ20PCB nor p,p’-DDE was a significant predictor of 5-year productivity means by river reach despite concentrations exceeding previously established effects thresholds for healthy bald eagle populations in the Great Lakes (≥ 1 nestling/nest). Our study indicates that dams may continue to reduce the upstream movement of contaminants to bald eagles, but at the measured concentrations, contaminants did not impair productivity and reproductive success as indicated by nestlings per nest. Additional information about population dynamics could clarify population-level effects of contaminants on bald eagles and to what degree these populations are self-sustaining throughout the Great Lakes.

Morphophysiological Adaptations of Aquatic Macrophytes in Wetland-Based Sewage Treatment Systems: Strategies for Resilience and Efficiency under Environmental Stress

There is a common misconception that aquatic macrophytes face significant challenges in wetland-based sewage treatment systems. This study aims to correct this perception by focusing on the crucial morphophysiological adaptations of aquatic macrophytes that enable them to thrive in wetland-based sewage treatment systems, particularly under environmental stress. These adaptations are vital for improving the efficiency and resilience of wastewater treatment processes, offering sustainable solutions in the face of variable environmental conditions and complex contaminant mixtures. The review emphasizes the role of macrophytes as natural engineers, capable of enhancing pollutant removal and system stability through their unique structural and functional traits. By understanding these adaptations, the review aims to guide the optimization of wetland design and management, ultimately contributing to more sustainable and effective wastewater treatment practices. The findings underscore the importance of species selection and the integration of nature-based solutions in environmental management, advocating for policies that support the use of macrophytes in modern wastewater management.

Toxicity of pesticide cocktails in amphibian larvae: understanding the impact of agricultural activity on aquatic ecosystems in the Salado River basin, Argentina

Aquatic communities are increasingly exposed to complex mixtures of contaminants, mainly pesticides due to the impact of agricultural activity. The aim of this study was to evaluate the toxicity of an eight-pesticide cocktail on larvae of the South American common toad, Rinella arenarum. The cocktail represents a realistic mixture of insecticides (cypermethrin, chlorpyrifos and lambda-cyhalothrin), herbicides (glyphosate, glufosinate ammonium, prometryn and metolachlor), and a fungicide (pyraclostrobin) previously found in aquatic organisms (Prochilodus lineatus) from the Salado River Basin, an area with strong agricultural pressure. Computational simulations through the Density Functional Tight-Binding method indicated a strong spontaneous trend toward the formation of the cocktail, suggesting that it may act as a novel xenobiotic entity in the environment. The cocktail effects were evaluated in early-developing and premetamorphic larvae, at feasible concentrations found in real scenarios. The mixture led to high mortality and teratogenicity in early-developing larvae. Premetamorphic larvae showed endocrine disruption, oxidative stress, and impairments in detoxification and hepatic functioning. Neurotoxicity, genotoxicity, cardiotoxicity and high mortality under stress conditions were also observed in exposed larvae. This novel evaluation highlights the ecotoxicological risk for aquatic organisms exposed to complex mixtures and underscores the need to consider cocktail effects in studies regarding ecosystems health.

Tracing troubles: Unveiling the hidden impact of inorganic contamination on juvenile green sea turtle

Human activities and climate change have negatively affected the world's oceans, leading to a decline of 30 to 60 % in coastal ecosystems' biodiversity and habitats. The projected increase in the human population to 9.7 billion by 2050 raises concerns about the sustainability of marine ecosystem conservation and exploitation. Marine turtles, as sentinel species, accumulate contaminants, including trace elements, due to their extensive migration and long-life span. However, there is a lack of data on the degree of contamination and their effects on marine turtles' health. This study focuses on assessing in-situ inorganic contamination in juvenile green sea turtles from La Réunion Island and its short-term impact on individual health, using conventional biomarkers and proteomics. The goals include examining contamination patterns in different tissues and identifying potential new biomarkers for long-term monitoring and conservation efforts. The study identified differential metal contamination between blood and scute samples, which could help illuminate temporal exposure to trace elements in turtle individuals. We also found that some conventional biomarkers were related to trace element exposure, while the proteome responded differently to various contaminant mixtures. Immune processes, cellular organization, and metabolism were impacted, indicating that contaminant mixtures in the wild would have an effect on turtle's health. Fifteen biomarker candidates associated with strong molecular responses of sea turtle to trace element contamination are proposed for future long-term monitoring. The findings emphasize the importance of using proteomic approaches to detect subtle physiological responses to contaminants in the wild and support the need for non-targeted analysis of trace elements in the biomonitoring of sea turtle health.

Complex interactions of rare earth elements in aquatic systems: Comparing observed and predicted cellular responses on Mytilus galloprovincialis

Recent societal and technological developments have led to new sources of contamination, particularly from electronic waste (e-waste). The rapid increase in e-waste, combined with inadequate disposal and recycling practices has resulted in rising levels of hazardous substances in aquatic systems, including rare-earth elements (REEs). However, the effects of REEs on aquatic organisms remain poorly understood. This lack of understanding is concerning since REEs can simultaneously appear in aquatic systems. Thus, this study aimed to evaluate the impacts of Yttrium (Y), Lanthanum (La), and Gadolinium (Gd), individually and as mixtures on the mussel species Mytilus galloprovincialis. Biomarkers related to metabolism, energy reserves, defence enzymes, redox balance, cellular damage, and neurotoxicity were analyzed. The results obtained showed that Y alone caused minimal stress, while Gd, La, and their mixtures induced from moderate to severe stress, increasing metabolic activity, and enzyme responses. This study highlights the ecological impacts of REEs mixtures on aquatic organisms. The complex interactions and additive effects, especially with Gd, underline the need for further research on contaminant mixtures.

Exposure to mixture particulate contaminants in the air and the risk of oral cancer: An updated systematic review and meta-analysis

The mixture of contaminants in the air (e.g., PM2.5, smoke) is a part of air pollutants that has become a hot environmental issue. Previous epidemiological studies have reported the relationship between wood smoke and PM2.5 exposure and oral cancer, but findings have been inconsistent. Therefore, this work designed to find out the relationship between mixture contaminants in air exposure and oral cancer. Fourteen studies were included through research in three databases before February 2024. Before analysis, the Newcastle-Ottawa Scale was applied to examine the quality of all selected studies. Then, the meta-analysis was carried out by meta-regression analysis, sensitivity analysis and subgroup analysis. The results showed that exposure to PM2.5 may have a positive association with oral cancer (pooled OR = 1.13, 95 % confidence interval: 1.06, 1.20). In contrast, no significant association was found between indoor air pollution and oral cancer. However, the result of the subgroup analysis indicated there is a significant association of indoor air pollution and oral cancer in developing countries (pooled OR = 2.5, 95 % confidence interval: 1.7, 3.6). In addition, the heterogeneity among studies of indoor air pollution exposure and oral cancer may caused by studies carried out in developed countries according to the subgroup and meta-regression analyses. In conclusion, the studies about indoor air pollution exposure and oral cancer are discrepant. The effects of mixed air contaminants for people's health are not simple and more studies are demanded to find out it in the future.

Mixed contaminant exposure in tapwater and the potential implications for human-health in disadvantaged communities in California

Water is an increasingly precious resource in California as years of drought, climate change, pollution, as well as an expanding population have all stressed the state's drinking water supplies. Currently, there are increasing concerns about whether regulated and unregulated contaminants in drinking water are linked to a variety of human-health outcomes particularly in socially disadvantaged communities with a history of health risks. To begin to address this data gap by broadly assessing contaminant mixture exposures, the current study was designed to collect tapwater samples from communities in Gold Country, the San Francisco Bay Area, two regions of the Central Valley (Merced/Fresno and Kern counties), and southeast Los Angeles for 251 organic chemicals and 32 inorganic constituents. Sampling prioritized low-income areas with suspected water quality challenges and elevated breast cancer rates. Results indicated that mixtures of regulated and unregulated contaminants were observed frequently in tapwater throughout the areas studied and the types and concentrations of detected contaminants varied by region, drinking-water source, and size of the public water system. Multiple exceedances of enforceable maximum contaminant level(s) (MCL), non-enforceable MCL goal(s) (MCLG), and other health advisories combined with frequent exceedances of benchmark-based hazard indices were also observed in samples collected in all five of the study regions. Given the current focus on improving water quality in socially disadvantaged communities, our study highlights the importance of assessing mixed-contaminant exposures in drinking water at the point of consumption to adequately address human-health concerns (e.g., breast cancer risk). Data from this pilot study provide a foundation for future studies across a greater number of communities in California to assess potential linkages between breast cancer rates and tapwater contaminants.

Children’s exposure to chemical contaminants: Demographic disparities and associations with the developing basal ganglia

Children are regularly exposed to chemical contaminants that may influence brain development. However, relatively little is known about how these contaminants impact the developing human brain. Here, we combined silicone wristband exposure assessments with neuroimaging for the first time to examine how chemical contaminant mixtures are associated with the developing basal ganglia—a brain region key for the healthy development of emotion, reward, and motor processing, and which may be particularly susceptible to contaminant harm. Further, we examined demographic disparities in exposures to clarify which children were at highest risk for any contaminant-associated neurobiological changes. Participants included 62 community children (average age 7.00 years, 53% female, 66% White) who underwent structural neuroimaging to provide data on their basal ganglia structure and wore a silicone wristband for seven days to track their chemical contaminant exposure. 45 chemical contaminants—including phthalates and their alternatives, brominated flame retardants, organophosphate esters, pesticides, polycyclic aromatic hydrocarbons, and polychlorinated biphenyls—were detected in over 75% of wristbands. Notable demographic disparities in exposure were present, such that Non-White and lower-income children were more exposed to several contaminants. Exposure to chemical contaminant mixtures was not associated with overall basal ganglia volume; however, two organophosphate esters (2IPPDPP and 4IPPDPP) were both associated with a larger globus pallidus, a basal ganglia sub-region. Results highlight demographic disparities in exposure and suggest possible risks to a brain region key for healthy emotional development.

Causal relationship between circulating glutamine levels and idiopathic pulmonary fibrosis: a two-sample mendelian randomization study

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive and debilitating respiratory disease with a median survival of less than 5 years. In recent years, glutamine has been reported to be involved in the regulation of collagen deposition and cell proliferation in fibroblasts, thereby influencing the progression of IPF. However, the relationships between glutamine and the incidence, progression, and treatment response of IPF remain unclear. Our study aimed to investigate the relationship between circulating glutamine levels and IPF, as well as its potential as a therapeutic target.MethodsWe performed a comprehensive Mendelian Randomization (MR) analysis using the most recent genome-wide association study summary-level data. A total of 32 single nucleotide polymorphisms significantly correlated to glutamine levels were identified as instrumental variables. Eight MR analysis methods, including inverse variance weighted, MR-Egger, weighted median, weighted mode, constrained maximum likelihood, contamination mixture, robust adjusted profile score, and debiased inverse-variance weighted method, were used to assess the relationship between glutamine levels with IPF.ResultsThe inverse variance weighted analysis revealed a significant inverse correlation between glutamine levels and IPF risk (Odds Ratio = 0.750; 95% Confidence Interval : 0.592–0.951; P = 0.017). Sensitivity analyses, including MR-Egger regression and MR-PRESSO global test, confirmed the robustness of our findings, with no evidence of horizontal pleiotropy or heterogeneity.ConclusionOur study provides novel evidence for a causal relationship between lower circulating glutamine levels and increased risk of IPF. This finding may contribute to the early identification of high-risk individuals for IPF, disease monitoring, and development of targeted therapeutic strategies.

P25-21 Examining the impact of a realistic mixture of dietary contaminants on the intestinal barrier and compounds absorption

P25-21 Examining the impact of a realistic mixture of dietary contaminants on the intestinal barrier and compounds absorption

Personalized mixture toxicity testing: A proof-of-principle in vitro study evaluating the steroidogenic effects of reconstructed contaminant mixtures measured in blood of individual adults

Chemical risk assessments typically focus on single substances, often overlooking real-world co-exposures to chemical mixtures. Mixture toxicology studies using representative mixtures can reveal potential chemical interactions, but these do not account for the unique chemical profiles that occur in the blood of diverse individuals. Here we used the H295R steroidogenesis assay to screen personalized mixtures of 24 persistent organic pollutants (POPs) for cytotoxicity and endocrine disruption. Each mixture was reconstructed at a human exposure relevant concentration (1×), as well as at 10- and 100-fold higher concentration (10×, 100×) by acoustic liquid handling based on measured blood concentrations in a Swedish cohort. Among the twelve mixtures tested, nine mixtures decreased the cell viability by 4–18%, primarily at the highest concentration. While the median and maximum mixtures based on the whole study population induced no measurable effects on steroidogenesis at any concentration, the personalized mixture from an individual with the lowest total POPs concentration was the only mixture that affected estradiol synthesis (35% increase at the 100× concentration). Mixtures reconstructed from blood levels of three different individuals stimulated testosterone synthesis at the 1× (11–15%) and 10× concentrations (12–16%), but not at the 100× concentration. This proof-of-principle personalized toxicity study illustrates that population-based representative chemical mixtures may not adequately account for the toxicological risks posed to individuals. It highlights the importance of testing a range of real-world mixtures at relevant concentrations to explore potential interactions and non-monotonic effects. Further toxicological studies of personalized contaminant mixtures could improve chemical risk assessment and advance the understanding of human health, as chemical exposome data become increasingly available.

Integrated respiratory toxicity of municipal wastewater to human bronchial epithelial cells and 3D bronchospheres

Respiratory symptoms have been reported in wastewater treatment workers and residents living close to sewage treatment plant. However, toxicological research about the respiratory hazards of municipal wastewater is scarce. The present study aims to gain insight into the comprehensive respiratory hazards induced by the contaminant mixtures in municipal wastewater. The integrated respiratory hazards of effluents from four secondary wastewater treatment plants (SWTPs), a tertiary wastewater treatment plant (TTP), and a constructed wetland (CW) were evaluated using normal human bronchial epithelial cells (NHBE) bioassay, and toxicity reduction efficiency of various treatment techniques was analyzed. Effluents caused cytotoxicity, oxidative damage, inflammation response with the increased levels of IL-6 and CXCL8, and impaired barrier integrity with decreased expressions of ZO-1 and occludin in NHBE. Further, the effluents inhibited the development of 3D bronchospheres, increased irregular surface and cell debris, and suppressed the formation of luminal structures. TTP E effluent significantly increased the expression of MUC5AC in bronchospheres. The integrated biomarker response (IBR) of the influent was removed by 40.2% at SWTPs, 18.2% at TTP, and 36.6% at CW, respectively. The IBR of the final effluents from SWTPs, TTP, and CW were 7.2, 7.7, and 7.7, respectively. Significant correlation with toxicity biomarkers was frequently observed for stearyl alcohol, o-cresol, phenanthrene, butylated hydroxytoluene, and dimethyl phthalate. The present study provided human relevant evidence concerning the adverse respiratory effects associated with discharge. The necessity for deep water treatment, performance optimization, and the potential means were suggested for improving water quality and protecting respiratory health.

Preconception and/or preimplantation exposure to a mixture of environmental contaminants altered fetoplacental development and placental function in a rabbit model

Pregnant women are daily exposed to environmental contaminants, including endocrine disruptors that can impact the offspring's health. This study aimed to evaluate the effects of maternal oral exposure to a mixture of contaminants at a dose mimicking women's exposure, during folliculogenesis and/or preimplantation period (FED and ED groups, respectively) on the fetoplacental phenotype in a rabbit model. The mixture (DEHP, pp’DDE, β-HCH, HCB, BDE-47, BPS, PFOS, PFOA) was defined based on data from HELIX and INMA cohorts. FED and ED females or unexposed females (control) were inseminated, their embryos were collected and transferred to unexposed control recipient rabbits at 80 h post-insemination. The effects of maternal FED and ED exposure were evaluated on fetoplacental growth and development by ultrasound, fetoplacental biometry, fetal metabolism, placental structure and function. The results demonstrated that the mixture weakly affected ultrasound measurements, as only placental volume increased significantly in FED vs ED. Analysis of placental structure demonstrated that the volume fraction of the maternal blood space was increased in FED vs control. Pre- and/or periconception exposure did not affect biometric at the end of gestation, but affected FED fetal biochemistry. Plasma triglyceride concentration was reduced compared to control. However, total cholesterol, urea, ASAT and ALAT in fetal blood were affected in both exposed groups. Multiple factor analysis, including biometric, biochemical, and stereological datasets, indicated that the three groups were significantly different. Additionally, several placental genes were differentially expressed between groups, compared two by two, in a sex-specific manner, with more difference in females than in males. The differentially expressed genes were involved in lipid, cholesterol, and drug/xenobiotic metabolism in both sexes. These results indicate that maternal exposure to environmental contaminants during crucial developmental windows only mildly impaired fetoplacental development but disturbed fetal blood biochemistry and placental gene expression with potential long-term effects on offspring phenotype.

Genetic prediction of blood metabolites mediating the relationship between gut microbiota and Alzheimer's disease: a Mendelian randomization study.

Observational studies have suggested an association between gut microbiota and Alzheimer's disease (AD); however, the causal relationship remains unclear, and the role of blood metabolites in this association remains elusive. To elucidate the causal relationship between gut microbiota and AD and to investigate whether blood metabolites serve as potential mediators. Univariable Mendelian randomization (UVMR) analysis was employed to assess the causal relationship between gut microbiota and AD, while multivariable MR (MVMR) was utilized to mitigate confounding factors. Subsequently, a two-step mediation MR approach was employed to explore the role of blood metabolites as potential mediators. We primarily utilized the inverse variance-weighted method to evaluate the causal relationship between exposure and outcome, and sensitivity analyses including Contamination mixture, Maximum-likelihood, Debiased inverse-variance weighted, MR-Egger, Bayesian Weighted Mendelian randomization, and MR pleiotropy residual sum and outlier were conducted to address pleiotropy. After adjustment for reverse causality and MVMR correction, class Actinobacteria (OR: 1.03, 95% CI: 1.01-1.06, p = 0.006), family Lactobacillaceae (OR: 1.03, 95% CI: 1.00-1.05, p = 0.017), genus Lachnoclostridium (OR: 1.03, 95% CI: 1.00-1.06, p = 0.019), genus Ruminiclostridium9 (OR: 0.97, 95% CI: 0.94-1.00, p = 0.027) and genus Ruminiclostridium6 (OR: 1.03, 95% CI: 1.01-1.05, p = 0.009) exhibited causal effects on AD. Moreover, 1-ribosyl-imidazoleacetate levels (-6.62%), Metabolonic lactone sulfate levels (2.90%), and Nonadecanoate (19:0) levels (-12.17%) mediated the total genetic predictive effects of class Actinobacteria on AD risk. Similarly, 2-stearoyl-GPE (18:0) levels (-9.87%), Octadecanedioylcarnitine (C18-DC) levels (4.44%), 1-(1-enyl-stearoyl)-2-oleoyl-GPE (p-18:0/18:1) levels (38.66%), and X-23639 levels (13.28%) respectively mediated the total genetic predictive effects of family Lactobacillaceae on AD risk. Furthermore, Hexadecanedioate (C16-DC) levels (5.45%) mediated the total genetic predictive effects of genus Ruminiclostridium 6 on AD risk; Indole-3-carboxylate levels (13.91%), X-13431 levels (7.08%), Alpha-ketoglutarate to succinate ratio (-13.91%), 3-phosphoglycerate to glycerate ratio (15.27%), and Succinate to proline ratio (-14.64%) respectively mediated the total genetic predictive effects of genus Ruminiclostridium 9 on AD risk. Our mediation MR analysis provides genetic evidence suggesting the potential mediating role of blood metabolites in the causal relationship between gut microbiota and AD. Further large-scale randomized controlled trials are warranted to validate the role of blood metabolites in the specific mechanisms by which gut microbiota influence AD.

A metabolome-wide Mendelian randomization study prioritizes causal circulating metabolites for reproductive disorders including primary ovarian insufficiency, polycystic ovary syndrome, and abnormal spermatozoa

BackgroundAccumulating studies have highlighted the significant role of circulating metabolomics in the etiology of reproductive system disorders. However, the causal effects between genetically determined metabolites (GDMs) and reproductive diseases, including primary ovarian insufficiency (POI), polycystic ovary syndrome (PCOS), and abnormal spermatozoa (AS), still await thorough clarification.MethodsWith the currently most comprehensive genome-wide association studies (GWAS) data of metabolomics, systematic two-sample Mendelian randomization (MR) analyses were conducted to disclose causal associations between 1,091 blood metabolites and 309 metabolite ratios with reproductive disorders. The inverse-variance weighted (IVW) method served as the primary analysis approach, and multiple effective MR methods were employed as complementary analyses including MR-Egger, weighted median, constrained maximum likelihood (cML-MA), contamination mixture method, robust adjusted profile score (MR-RAPS), and debiased inverse-variance weighted method. Heterogeneity and pleiotropy were assessed via MR-Egger intercept and Cochran’s Q statistical analysis. Outliers were detected by Radial MR and MR-PRESSO methods. External replication and metabolic pathway analysis were also conducted.ResultsPotential causal associations of 63 GDMs with POI were unearthed, and five metabolites with strong causal links to POI were emphasized. Two metabolic pathways related to the pathogenesis of POI were pinpointed. Suggestive causal effects of 70 GDMs on PCOS were detected, among which 7 metabolites stood out for strong causality with elevated PCOS risk. Four metabolic pathways associated with PCOS mechanisms were recognized. For AS, 64 GDMs as potential predictive biomarkers were identified, particularly highlighting two metabolites for their strong causal connections with AS. Three pathways underneath the AS mechanism were identified. Multiple assessments were conducted to further confirm the reliability and robustness of our causal inferences.ConclusionBy extensively assessing the causal implications of circulating GDMs on reproductive system disorders, our study underscores the intricate and pivotal role of metabolomics in reproductive ill-health, laying a theoretical foundation for clinical strategies from metabolic insights.