Beyond 5×10⁻⁸: MAF-Specific Significance Thresholds for Genome-Wide Association Studies in three major populations

Beyond 5×10⁻⁸: MAF-Specific Significance Thresholds for Genome-Wide Association Studies in three major populations | 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 Article Beyond 5×10⁻⁸: MAF-Specific Significance Thresholds for Genome-Wide Association Studies in three major populations Sandeep C. Vejandia¹, Archish Sadeesh², Vinodh Srinivasasainagendra¹, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6234338/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Introduction : Conventional genome-wide association study (GWAS) thresholds, notably 5×10⁻⁸, were established under assumptions that may not hold across diverse populations and whole-genome sequencing (WGS) analyses. Given the complex linkage disequilibrium structure of the human genome, a single fixed threshold risks inadequate type I error control. Here, we sought to derive minor allele frequency (MAF)-specific, population-tailored significance thresholds using the Li-Ji method across European, African, and Asian cohorts from the 1000 Genomes Project. Methods We partitioned the genome into natural linkage disequilibrium (LD) blocks defined by the LDetect database and applied rigorous quality control measures before generating LD matrices. Using the Li-Ji method—we estimated the effective number of independent tests for each block across six MAF thresholds and then aggregated the results for each population. The resulting effective tests were used to calculate Bonferroni-adjusted significance thresholds. Results Our analysis revealed that for common variants (MAF ≥ 0.05), the significance thresholds in European and Asian populations were somewhat lower than the conventional 5×10⁻⁸ benchmark, whereas the African population required considerably more stringent corrections. The inclusion of rarer variants further increased the effective number of independent tests across all groups, thereby shifting the significance thresholds to levels even more stringent than the 5×10⁻⁸ benchmark. Conclusions By applying the Li-Ji method, this study establishes that MAF-specific and population-specific significance thresholds provide a more accurate framework for GWAS analyses. Our findings suggest that the conventional 5×10⁻⁸ threshold may be suboptimal, particularly when evaluating rare variants or diverse populations, with important implications for future biobank-scale and precision genomic research. Biological sciences/Computational biology and bioinformatics Physical sciences/Mathematics and computing Biological sciences/Genetics Biological sciences/Genetics/Genetic association study Biological sciences/Genetics/Genetic linkage study Biological sciences/Genetics/Genetic markers Biological sciences/Genetics/Genome Biological sciences/Genetics/Haplotypes Biological sciences/Genetics/Population genetics Genome-Wide Association Studies (GWAS) Significance Threshold Linkage Disequilibrium (LD) Li-Ji Method Population-Specific Analysis 1000 Genomes Project Figures Figure 1 Figure 2 Figure 3 Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.xlsx Cite Share Download PDF Status: Published Journal Publication published 04 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 25 Apr, 2025 Reviews received at journal 24 Apr, 2025 Reviews received at journal 14 Apr, 2025 Reviewers agreed at journal 05 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers invited by journal 03 Apr, 2025 Editor assigned by journal 03 Apr, 2025 Editor invited by journal 26 Mar, 2025 Submission checks completed at journal 25 Mar, 2025 First submitted to journal 15 Mar, 2025 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-6234338","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":442677997,"identity":"2499d4b4-ca21-44df-870a-342f1bfde3c4","order_by":0,"name":"Sandeep C. Vejandia¹","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApUlEQVRIiWNgGAWjYJACA4YKEMHAIEG0lgKGM6Rq+cDYRooWg/OHH27mnXdY3pyB+eBtHqK03EgzNubddthwZwNbsjVRWiRn8LCBtDBuOMBjJk2clv4z7L955xy233CA/xtxWvgZchiMeRsOJwJtYSNSi0SageGcY+nJO5vZjC3nEKOFjf/wA4M3Nda229mbH954Q4wWBGAmTfkoGAWjYBSMAnwAAJeELJ1SHhcxAAAAAElFTkSuQmCC","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":true,"prefix":"","firstName":"Sandeep","middleName":"C.","lastName":"Vejandia¹","suffix":""},{"id":442677998,"identity":"966ad920-261c-4dc8-8ce1-ba8bb5b1b887","order_by":1,"name":"Archish Sadeesh²","email":"","orcid":"","institution":"McMaster University","correspondingAuthor":false,"prefix":"","firstName":"Archish","middleName":"","lastName":"Sadeesh²","suffix":""},{"id":442677999,"identity":"dac4af8a-7f91-4ca9-b217-fa2b24ffb0ae","order_by":2,"name":"Vinodh Srinivasasainagendra¹","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Vinodh","middleName":"","lastName":"Srinivasasainagendra¹","suffix":""},{"id":442678001,"identity":"fb6770bc-9b4c-4f3f-b69c-a33030cce555","order_by":3,"name":"Mary Appah¹","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Mary","middleName":"","lastName":"Appah¹","suffix":""},{"id":442678003,"identity":"b9960fe1-16e1-4722-9ddc-1c75c4af079e","order_by":4,"name":"Hemant K Tiwari¹","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Hemant","middleName":"K","lastName":"Tiwari¹","suffix":""}],"badges":[],"createdAt":"2025-03-15 18:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6234338/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6234338/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-19644-w","type":"published","date":"2025-11-04T15:57:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81316833,"identity":"af7fc123-4bc3-4907-b380-8b605e69c688","added_by":"auto","created_at":"2025-04-24 16:24:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27195,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMAF-specific significance thresholds for the European population.\u003c/strong\u003e The upper panel shows the relationship between minor allele frequency (MAF) thresholds and the number of unique variants (blue histograms) and effective independent tests (grey histograms) in the European population from the 1000 Genomes Project. The lower panel illustrates the corresponding Li-Ji derived significance thresholds (solid line) compared to the conventional 5×10⁻⁸ threshold (dotted line). Note that for common variants (MAF ≥ 0.05), the calculated threshold (3.84×10⁻⁸) is close to the conventional threshold but becomes increasingly stringent as rarer variants are included.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6234338/v1/73e58cb4e45606cc4f65b2be.png"},{"id":81316832,"identity":"c833418f-c49b-47ec-bfd4-9919a25f98b1","added_by":"auto","created_at":"2025-04-24 16:24:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":25734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMAF-specific significance thresholds for the African population.\u003c/strong\u003e The upper panel displays the relationship between MAF thresholds and the number of unique variants (blue histograms) and effective independent tests (grey histograms) in the African population. The lower panel shows the Li-Ji derived significance thresholds (solid line) compared to the conventional 5×10⁻⁸ threshold (dotted line). The African population demonstrates substantially more stringent threshold requirements even for common variants (1.78×10⁻⁸ at MAF ≥ 0.05), reflecting the greater genetic diversity in this population.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6234338/v1/b2faccb8e989d1a32d266972.png"},{"id":81317153,"identity":"e49c3873-ebd4-4436-8cca-f9b9bb6c41af","added_by":"auto","created_at":"2025-04-24 16:32:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26302,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMAF-specific significance thresholds for the Asian population.\u003c/strong\u003e The upper panel illustrates the relationship between MAF thresholds and the number of unique variants (blue histograms) and effective independent tests (grey histograms) in the combined Asian population. The lower panel shows the Li-Ji derived significance thresholds (solid line) compared to the conventional 5×10⁻⁸ threshold (dotted line). Note the anomaly at MAF ≥ 0.0001, where the number of unique variants and effective tests unexpectedly decreases compared to MAF ≥ 0.001, due to many ultra-rare variants being exclusive to either East Asian or South Asian sub-populations.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6234338/v1/b7283dbcd82c7b0324762abf.png"},{"id":95564173,"identity":"37aabe5e-6b70-4ba7-9e52-783d698fc1c4","added_by":"auto","created_at":"2025-11-10 16:08:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":587215,"visible":true,"origin":"","legend":"","description":"","filename":"ResearchPaperScientificreports.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6234338/v1_covered_17fe5ee5-1142-42ec-b9b0-5891923c60f0.pdf"},{"id":81317157,"identity":"1449bb05-0b14-4267-a99c-d1d25fc9153c","added_by":"auto","created_at":"2025-04-24 16:32:38","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1950278,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6234338/v1/270295fdc8d2289eaa55274f.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Beyond 5×10⁻⁸: MAF-Specific Significance Thresholds for Genome-Wide Association Studies in three major populations","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Genome-Wide Association Studies (GWAS), Significance Threshold, Linkage Disequilibrium (LD), Li-Ji Method, Population-Specific Analysis, 1000 Genomes Project","lastPublishedDoi":"10.21203/rs.3.rs-6234338/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6234338/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction\u003c/h2\u003e \u003cp\u003e: Conventional genome-wide association study (GWAS) thresholds, notably 5\u0026times;10⁻⁸, were established under assumptions that may not hold across diverse populations and whole-genome sequencing (WGS) analyses. Given the complex linkage disequilibrium structure of the human genome, a single fixed threshold risks inadequate type I error control. Here, we sought to derive minor allele frequency (MAF)-specific, population-tailored significance thresholds using the Li-Ji method across European, African, and Asian cohorts from the 1000 Genomes Project.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe partitioned the genome into natural linkage disequilibrium (LD) blocks defined by the LDetect database and applied rigorous quality control measures before generating LD matrices. Using the Li-Ji method\u0026mdash;we estimated the effective number of independent tests for each block across six MAF thresholds and then aggregated the results for each population. The resulting effective tests were used to calculate Bonferroni-adjusted significance thresholds.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOur analysis revealed that for common variants (MAF\u0026thinsp;\u0026ge;\u0026thinsp;0.05), the significance thresholds in European and Asian populations were somewhat lower than the conventional 5\u0026times;10⁻⁸ benchmark, whereas the African population required considerably more stringent corrections. The inclusion of rarer variants further increased the effective number of independent tests across all groups, thereby shifting the significance thresholds to levels even more stringent than the 5\u0026times;10⁻⁸ benchmark.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eBy applying the Li-Ji method, this study establishes that MAF-specific and population-specific significance thresholds provide a more accurate framework for GWAS analyses. Our findings suggest that the conventional 5\u0026times;10⁻⁸ threshold may be suboptimal, particularly when evaluating rare variants or diverse populations, with important implications for future biobank-scale and precision genomic research.\u003c/p\u003e","manuscriptTitle":"Beyond 5×10⁻⁸: MAF-Specific Significance Thresholds for Genome-Wide Association Studies in three major populations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-24 16:24:33","doi":"10.21203/rs.3.rs-6234338/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-25T07:02:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-24T21:35:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T11:25:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233950772929608398727663746303026889866","date":"2025-04-05T19:07:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66866436343347145660383428596652957152","date":"2025-04-04T10:22:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-03T14:50:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-03T14:37:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-26T16:32:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-25T06:36:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-15T18:19:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8ba4e971-f3ef-4a8e-906a-374a259aa2fc","owner":[],"postedDate":"April 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47126321,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":47126322,"name":"Physical sciences/Mathematics and computing"},{"id":47126323,"name":"Biological sciences/Genetics"},{"id":47126324,"name":"Biological sciences/Genetics/Genetic association study"},{"id":47126325,"name":"Biological sciences/Genetics/Genetic linkage study"},{"id":47126326,"name":"Biological sciences/Genetics/Genetic markers"},{"id":47126327,"name":"Biological sciences/Genetics/Genome"},{"id":47126328,"name":"Biological sciences/Genetics/Haplotypes"},{"id":47126329,"name":"Biological sciences/Genetics/Population genetics"}],"tags":[],"updatedAt":"2025-11-10T16:05:14+00:00","versionOfRecord":{"articleIdentity":"rs-6234338","link":"https://doi.org/10.1038/s41598-025-19644-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-04 15:57:52","publishedOnDateReadable":"November 4th, 2025"},"versionCreatedAt":"2025-04-24 16:24:33","video":"","vorDoi":"10.1038/s41598-025-19644-w","vorDoiUrl":"https://doi.org/10.1038/s41598-025-19644-w","workflowStages":[]},"version":"v1","identity":"rs-6234338","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6234338","identity":"rs-6234338","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}