Quantifying Pathway Identifiability under Partial Metabolomics for Measurement Prioritization

Quantifying Pathway Identifiability under Partial Metabolomics for Measurement Prioritization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Quantifying Pathway Identifiability under Partial Metabolomics for Measurement Prioritization Anas Enoch This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9084589/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Motivation: Incomplete metabolite coverage is a persistent limitation in pathway-level analysis. Under partial metabolomics, multiple pathway configurations may be consistent with the same observed measurements, leading to structural ambiguity in biological interpretation. Existing approaches typically rely on imputation or enrichment scoring but do not explicitly quantify pathway identifiability or guide measurement prioritization. Results: We introduce a unified operator-based framework for pathway identifiability under partial metabolomics. Condition-specific pathway graphs are aligned using a Johnson-Lindenstrauss stabilized fused Gromov-Wasserstein (JL-FGW) operator, integrating topology and metabolite features under het- erogeneous coverage. Pathway ambiguity is quantified through a composite underdetermination functional combining transport entropy, alignment instability, and structural risk. Measurement prioritization is formulated as an optimization problem over the sensitivity of this functional, yielding a computable estimator for next-best metabolite selection without enumerating latent pathway completions. Rather than proposing another generic pathway scoring method, we address a different decision problem: under incomplete metabolite observation, which additional measurements are expected to maximally reduce pathway-level uncertainty? Under synthetic masking, the framework achieves low regret relative to mechanistic and heuristic measurement-selection baselines. In real metabolomics cohorts, pathway coverage is highly dataset-dependent, and the framework identifies a compact set of pathways for which recommendation-based identifiability benchmarking is feasible. Sensitivity analysis indicates stable ranking under moderate perturbations of composite weights, and runtime analysis confirms tractability for curated pathways and moderate genome-scale models. Availability: Code and synthetic evaluation scripts are available for peer review and will be publicly released upon publication. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9084589","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":604534229,"identity":"06d808a2-053b-42b5-858a-915418ee2379","order_by":0,"name":"Anas Enoch","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYFAD9gYG5h+kaeE5wMBMoi0SCURq4Z/d/PgD4w6bxO0z35huLmCwk2cQO/wAv9l3jplJMJ5JS5xzO8fs9gyGZMMG6TQD/NbcSDBjYGw7nDhDOsfsBg8DcwKDdAJ+LfI30j9/AGuRPAPSUg/Ukv4BrxaDGzkGEmAtEjxmt3kYDgO15OC3xfBGThlQS5rxDJ60spszDI4btknnFODVIncjfTPQYTayM9gPb7vxoaJanl86fQNeLSDA/AfhTgYGNoLqR8EoGAWjYBQQBACmL0EJOQGrawAAAABJRU5ErkJggg==","orcid":"","institution":"Université Mohammed VI des Sciences de la Santé","correspondingAuthor":true,"prefix":"","firstName":"Anas","middleName":"","lastName":"Enoch","suffix":""}],"badges":[],"createdAt":"2026-03-10 13:25:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9084589/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9084589/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107699086,"identity":"5ed6c9f9-6b75-4be8-bf59-bb426134193a","added_by":"auto","created_at":"2026-04-24 07:42:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1797381,"visible":true,"origin":"","legend":"","description":"","filename":"Pathwaysidentifiability.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9084589/v1_covered_42b3ed82-22ce-45a8-9cd7-0d0db51c64a7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantifying Pathway Identifiability under Partial Metabolomics for Measurement Prioritization","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9084589/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9084589/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMotivation: Incomplete metabolite coverage is a persistent limitation in pathway-level analysis. Under partial metabolomics, multiple pathway configurations may be consistent with the same observed measurements, leading to structural ambiguity in biological interpretation. Existing approaches typically rely on imputation or enrichment scoring but do not explicitly quantify pathway identifiability or guide measurement prioritization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: We introduce a unified operator-based framework for pathway identifiability under partial metabolomics. Condition-specific pathway graphs are aligned using a Johnson-Lindenstrauss stabilized fused Gromov-Wasserstein (JL-FGW) operator, integrating topology and metabolite features under het- erogeneous coverage. Pathway ambiguity is quantified through a composite underdetermination functional combining transport entropy, alignment instability, and structural risk. Measurement prioritization is formulated as an optimization problem over the sensitivity of this functional, yielding a computable estimator for next-best metabolite selection without enumerating latent pathway completions. Rather than proposing another generic pathway scoring method, we address a different decision problem: under incomplete metabolite observation, which additional measurements are expected to maximally reduce pathway-level uncertainty? Under synthetic masking, the framework achieves low regret relative to mechanistic and heuristic measurement-selection baselines. In real metabolomics cohorts, pathway coverage is highly dataset-dependent, and the framework identifies a compact set of pathways for which recommendation-based identifiability benchmarking is feasible. Sensitivity analysis indicates stable ranking under moderate perturbations of composite weights, and runtime analysis confirms tractability for curated pathways and moderate genome-scale models.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability: Code and synthetic evaluation scripts are available for peer review and will be publicly released upon publication.\u003c/p\u003e","manuscriptTitle":"Quantifying Pathway Identifiability under Partial Metabolomics for Measurement Prioritization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-13 21:09:16","doi":"10.21203/rs.3.rs-9084589/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"95f09f5a-b6db-415b-93f4-1e82f570a0a8","owner":[],"postedDate":"March 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-24T07:40:49+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-13 21:09:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9084589","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9084589","identity":"rs-9084589","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}