Pesticides are important chemicals or biological agents that deter or kill pests. The use of pesticides has continued to increase as it is still considered the most effective method to reduce pests and increase crop growth. However, pesticides have other consequences, including potential toxicity to humans and wildlife. Pesticides have been associated with increased risk of cardiovascular disease, cancer, and birth defects. Labels on pesticides also suggest limiting exposure to these hazardous chemicals. Based on experimental evidence, various types of pesticides all seem to have a common effect, the induction of oxidative stress in different cell types and animal models. Pesticide-induced oxidative stress is caused by both reactive oxygen species (ROS) and reactive nitrogen species (RNS), which are associated with several diseases including cancer, inflammation, and cardiovascular and neurodegenerative diseases. ROS and RNS can activate at least five independent signaling pathways including mitochondrial-induced apoptosis. Limited in vitro studies also suggest that exogenous antioxidants can reduce or prevent the deleterious effects of pesticides.

OBJECTIVE: The relationship between multiple sclerosis and the gut microbiome has been supported by animal models in which commensal microbes are required for the development of experimental autoimmune encephalomyelitis. However, observational study findings in humans have only occasionally converged when comparing multiple sclerosis cases and controls which may in part reflect confounding by comorbidities and disease duration. The study of microbiome in pediatric-onset multiple sclerosis offers unique opportunities as it is closer to biological disease onset and minimizes confounding by comorbidities and environmental exposures. METHODS: A multicenter case-control study in which 35 pediatric-onset multiple sclerosis cases were 1:1 matched to healthy controls on age, sex, self-reported race, ethnicity, and recruiting site. Linear mixed effects models, weighted correlation network analyses, and PICRUSt2 were used to identify microbial co-occurrence networks and for predicting functional abundances based on marker gene sequences. RESULTS: Two microbial co-occurrence networks (one reaching significance after adjustment for multiple comparisons; q < 0.2) were identified, suggesting interdependent bacterial taxa that exhibited association with disease status. Both networks indicated a potentially protective effect of higher relative abundance of bacteria observed in these clusters. Functional predictions from the significant network suggested a contribution of short-chain fatty acid producers through anaerobic fermentation pathways in healthy controls. Consistent family-level findings from an independent Canadian-US study (19 case/control pairs) included Ruminococaccaeae and Lachnospiraceae (p < 0.05). Macronutrient intake was not significantly different between cases and controls, minimizing the potential for dietary confounding. INTERPRETATION: Our results suggest that short-chain fatty acid producers may be important contributors to multiple sclerosis onset.

Motivation

Knowledge graphs (KGs) are being adopted in industry, commerce and academia. Biomedical KG presents a challenge due to the complexity, size and heterogeneity of the underlying information.

Results

In this work, we present the Scalable Precision Medicine Open Knowledge Engine (SPOKE), a biomedical KG connecting millions of concepts via semantically meaningful relationships. SPOKE contains 27 million nodes of 21 different types and 53 million edges of 55 types downloaded from 41 databases. The graph is built on the framework of 11 ontologies that maintain its structure, enable mappings and facilitate navigation. SPOKE is built weekly by python scripts which download each resource, check for integrity and completeness, and then create a 'parent table' of nodes and edges. Graph queries are translated by a REST API and users can submit searches directly via an API or a graphical user interface. Conclusions/Significance: SPOKE enables the integration of seemingly disparate information to support precision medicine efforts.

Availability and implementation

The SPOKE neighborhood explorer is available at https://spoke.rbvi.ucsf.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Changes in gut microbiota composition and a diverse role of B cells have recently been implicated in multiple sclerosis (MS), a central nervous system (CNS) autoimmune disease. Immunoglobulin A (IgA) is a key regulator at the mucosal interface. However, whether gut microbiota shape IgA responses and what role IgA⁺ cells have in neuroinflammation are unknown. Here, we identify IgA-bound taxa in MS and show that IgA-producing cells specific for MS-associated taxa traffic to the inflamed CNS, resulting in a strong, compartmentalized IgA enrichment in active MS and other neuroinflammatory diseases. Unlike previously characterized polyreactive anti-commensal IgA responses, CNS IgA cross-reacts with surface structures on specific bacterial strains but not with brain tissue. These findings establish gut microbiota-specific IgA⁺ cells as a systemic mediator in MS and suggest a critical role of mucosal B cells during active neuroinflammation with broad implications for IgA as an informative biomarker and IgA-producing cells as an immune subset to harness for therapeutic interventions.