{"doi":"10.1002/acr.25402","title":"Coordination and Collaboration to Support Exposome Research in Autoimmune Diseases","abstract":"Recent evidence suggests increasing rates of autoimmune diseases that cannot be explained through genetic predisposition alone.1-3 Although genetic factors play some role in the development of autoimmune diseases, most do not follow a Mendelian pattern of inheritance, and genetic risk scores do not fully predict risk.4-6 Women have a higher risk of autoimmune diseases than men.7 Recent studies suggest that the inactivation of additional X chromosomes by long, non-coding RNA molecules, including X-inactive specific transcript (Xist), may play a role in sex differences in autoimmune diseases.8 However, drivers of autoimmunity in women may be multifactorial, and more research is needed to better understand the female preponderance of autoimmune disease. Current hypotheses propose that autoimmune diseases likely originate via complex interactions between genetic factors and environmental exposures.9 However, autoantibody production may predate clinically evident autoimmune disease by many years, and this apparent prolonged latency, common to many autoimmune diseases, makes ascertainment of exposures inciting autoimmunity challenging.5, 10 Furthermore, at an individual level, different people may respond to the same environmental exposure differently, likely due to a combination of factors, including genetic predisposition, epigenetics, dosing and duration of exposures, the life stage of the individual at time of exposure, and other factors, such as nutrition.11 To understand disease susceptibility in autoimmune disease, there is a need to integrate the complex relationship of genetics with data on varied and cumulative exposures that an individual encounters throughout life, a concept now increasingly referred to as the exposome. The immune system may be critical to connecting these variables and providing the missing link through which environmental exposures and genetics interact to induce autoimmune disease. The study of the exposome through exposomics is a new and rapidly growing field.12, 13 Exposures may be internal or external, including diet, stress, hormones, alcohol, drugs, medications, cigarette smoke, chemicals, heavy metals, and UV radiation, as well as air and water pollutants and other exposures related to geographic location and changing climatic conditions.1, 5, 13-15 Infectious agents, including viruses and the microbiome, also contribute to the exposome and have been implicated in autoimmune diseases.16, 17 Exposures may be more influential during different life stages, and exposures during childhood and adolescence while the immune system is still developing may have more pronounced impact than those later in life, or vice versa depending on the agent involved. The Human Early Life Exposome (HELIX) project has already revealed that prenatal exposures can result in DNA methylation changes in the child and that childhood exposures are associated with metabolomic changes later in life.18 These findings indicate that in utero and very early life exposures may be important in shaping long-term health. Another important component of exposome research, which has been historically challenging to measure, is the influence of behavioral factors and psychosocial stressors, either independently or as they interact with other environmental factors. These dynamic components of the exposome can be very challenging to capture, yet disproportionately affect certain groups such as children, women, pregnant persons, and lower socioeconomic status groups. Exposures may explain higher rates of autoimmune diseases in these groups. Cumulative and time-varying exposures also need to be considered, as well as interactions among exposures, which will require complex modeling to assess for the combined effects of aggregated exposures.14 Measuring multiple exposures concurrently and assessing their impact is complex and will require large sample sizes. Taking this one step further to assess the impact on the human immune system will be vi","journal":"Arthritis Care & Research","year":2024,"id":483534,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9615,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":552819,"name":"Sarah M. Temkin","orcid":"0000-0002-6472-2745","position":1,"is_corresponding":false},{"id":597582,"name":"Janine A. Clayton","orcid":"0000-0003-2981-3622","position":2,"is_corresponding":false},{"id":695331,"name":"Yuxia Cui","orcid":"0000-0002-0425-4206","position":3,"is_corresponding":false},{"id":1325092,"name":"Michael C. Humble","orcid":null,"position":4,"is_corresponding":false},{"id":264511,"name":"Lisa G. Rider","orcid":"0000-0002-6912-2458","position":5,"is_corresponding":false},{"id":1325093,"name":"Susana Serrate‐Sztein","orcid":null,"position":6,"is_corresponding":false},{"id":303341,"name":"Ricardo Cibotti","orcid":null,"position":7,"is_corresponding":false},{"id":2822,"name":"Lindsey A. Criswell","orcid":"0000-0002-0761-7543","position":8,"is_corresponding":false},{"id":445767,"name":"Victoria K. Shanmugam","orcid":"0000-0002-5882-4884","position":0,"is_corresponding":true}],"reference_count":27,"raw_metadata":null,"created_at":"2026-07-19T02:07:33.718973Z","pmid":"38992882","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}