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"https://publications-affiliated.scilifelab.se/researcher/78b7a44839bb42c89538cf2e4979c6f8.json"}}, {"family": "Pennell", "given": "Kurt D", "initials": "KD", "orcid": "0000-0002-5788-6397", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5acb4005e2564f718e490678a61542e5.json"}}, {"family": "Jones", "given": "Dean P", "initials": "DP"}, {"family": "Miller", "given": "Gary W", "initials": "GW", "orcid": "0000-0001-8984-1284", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/dc6141f6c7384400a880de33387d00b9.json"}}], "type": "journal article", "published": "2024-07-23", "journal": {"title": "Environ. Sci. Technol.", "issn": "1520-5851", "volume": "58", "issue": "29", "pages": "12784-12822", "issn-l": "0013-936X"}, "abstract": "In the modern \"omics\" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.", "doi": "10.1021/acs.est.4c01156", "pmid": "38984754", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11271014"}], "notes": [], "created": "2026-08-20T08:09:51.127Z", "modified": "2026-08-20T08:09:52.045Z"}, {"entity": "publication", "iuid": "492d4806caab49db9fdff3fbd4323ae3", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/492d4806caab49db9fdff3fbd4323ae3.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/492d4806caab49db9fdff3fbd4323ae3"}}, "title": "The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry.", "authors": [{"family": "Mohammed Taha", 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"issn-l": null}, "abstract": "The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for \"suspect screening\" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.\n\nThe NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).\n\nThe NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the \"one substance, one assessment\" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/).\n\nThe online version contains supplementary material available at 10.1186/s12302-022-00680-6.", "doi": "10.1186/s12302-022-00680-6", "pmid": "36284750", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC9587084"}, {"db": "pii", "key": "680"}], "notes": [], "created": "2026-08-20T12:19:25.309Z", "modified": "2026-08-20T12:19:28.198Z"}]}