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Delayed diagnosis of ASD is common and problematic. The complexity of ASD and the low sensitivity of available screening tools are key factors in delayed diagnosis. Identification of biomarkers that reduce complexity through stratification into reliable subpopulations can assist in earlier diagnosis, provide insight into the biology of ASD, and potentially suggest targeted interventions. Quantitative metabolomic analysis was performed on plasma samples from 708 fasting children, aged 18 to 48\u2009months, enrolled in the Children's Autism Metabolome Project (CAMP). The primary goal was to identify alterations in metabolism helpful in stratifying ASD subjects into subpopulations with shared metabolic phenotypes (i.e., metabotypes). Metabotypes associated with ASD were identified in a discovery set of 357 subjects. The reproducibility of the metabotypes was validated in an independent replication set of 351 CAMP subjects. Thirty\u2010four candidate metabotypes that differentiated subsets of ASD from typically developing participants were identified with sensitivity of at least 5% and specificity greater than 95%. The 34 metabotypes formed six metabolic clusters based on ratios of either lactate or pyruvate, succinate, glycine, ornithine, 4\u2010hydroxyproline, or \u03b1\u2010ketoglutarate with other metabolites. Optimization of a subset of new and previously defined metabotypes into a screening battery resulted in 53% sensitivity (95% confidence interval [CI], 48%\u201357%) and 91% specificity (95% CI, 86%\u201394%). Thus, our metabolomic screening tool detects more than 50% of the autistic participants in the CAMP study. Further development of this metabolomic screening approach may facilitate earlier referral and diagnosis of ASD and, ultimately, more targeted treatments.<\/jats:p><\/jats:sec><jats:sec><jats:title>Lay Summary<\/jats:title><jats:p>Analysis of a selected set of metabolites in blood samples from children with autism and typically developing children identified reproducible differences in the metabolism of about half of the children with autism. Testing for these differences in blood samples can be used to help screen children as young as 18\u2009months for risk of autism that, in turn, can facilitate earlier diagnoses. In addition, differences may lead to biological insights that produce more precise treatment options. We are exploring other blood\u2010based molecules to determine if still a higher percentage of children with autism can be detected using this strategy. <jats:italic><jats:bold>Autism Res<\/jats:bold> 2020, 13: 1270\u20131285<\/jats:italic>. \u00a9 2020 The Authors. <jats:italic>Autism Research published by International Society for Autism Research<\/jats:italic> published by Wiley Periodicals LLC.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aur.2330","type":"journal-article","created":{"date-parts":[[2020,6,18]],"date-time":"2020-06-18T13:44:22Z","timestamp":1592487862000},"page":"1270-1285","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["A Metabolomics Approach to Screening for Autism Risk in the Children's Autism Metabolome Project"],"prefix":"10.1002","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0341-5650","authenticated-orcid":false,"given":"Alan M.","family":"Smith","sequence":"first","affiliation":[{"name":"Stemina Biomarker Discovery, Inc  Madison Wisconsin USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3018-546X","authenticated-orcid":false,"given":"Marvin R.","family":"Natowicz","sequence":"additional","affiliation":[{"name":"Pathology and Laboratory Medicine Genomics, Neurology, and Pediatrics Institutes, Cleveland Clinic  Cleveland Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Braas","sequence":"additional","affiliation":[{"name":"Stemina Biomarker Discovery, Inc  Madison Wisconsin USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael A.","family":"Ludwig","sequence":"additional","affiliation":[{"name":"Stemina Biomarker Discovery, Inc  Madison Wisconsin USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Denise M.","family":"Ney","sequence":"additional","affiliation":[{"name":"Department of Nutritional Sciences University of Wisconsin\u2010Madison  Madison Wisconsin USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth L. 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