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Here, we systematically evaluated how self\u2010reported AD diagnoses in the UK Biobank (UKB) distort Mendelian randomization (MR) analyses. Using seven AD datasets (four GWAS and three GWAX, including IGAP,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u200963\u2009926; FinnGen R10,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009191\u2009061; UKB G30,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009420\u2009531; UKB2024,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009434\u2009286, and GWAX2017,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u200974\u2009366; GWAX2018,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009548\u2009955; GWAX2021,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009408\u2009691) and six education subtypes (including years of schooling,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u20091\u2009131\u2009881; hardest math class completed,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009430\u2009445; self\u2010reported math ability,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009564\u2009698; college completion,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009280\u2009007; cognition test performance,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009257\u2009841; and non\u2010cognitive skills,\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u2009257\u2009841). We also assessed the heterogeneity and pleiotropy across these datasets. We found opposing causal directions between GWAS and GWAX cohorts. In GWAS datasets, genetic variations related to education were causally linked to a lower risk of AD (OR &lt;\u20091,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.05), with years of schooling showing the strongest protective effects (OR\u2009=\u20090.71 in IGAP,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.05). Conversely, UKB\u2010based GWAX analyses paradoxically linked education\u2010related traits to increased AD risk (OR &gt;\u20091,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.05), directly conflicting with the protective associations in clinical AD GWAS results. Genetic heterogeneity was observed in both AD GWAS and GWAX datasets. Pleiotropy was noted in AD outcomes, but MR estimates remained stable after outlier adjustments. Our findings reveal that self\u2010reported AD statuses in UKB distorted genetic effect estimates, particularly for education subtypes requiring validation. The research urges caution in interpreting MR results from GWAX studies that use self\u2010reported endpoints and highlights the need for rigorous phenotyping in biobank studies.\n                    <jats:boxed-text content-type=\"graphic\" position=\"anchor\">\n                      <jats:graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" mimetype=\"image\/png\" position=\"anchor\" specific-use=\"enlarged-web-image\" xlink:href=\"graphic\/jnc70151-fig-0004-m.png\">\n                        <jats:alt-text>image<\/jats:alt-text>\n                      <\/jats:graphic>\n                    <\/jats:boxed-text>\n                  <\/jats:p>","DOI":"10.1111\/jnc.70151","type":"journal-article","created":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T13:45:38Z","timestamp":1752068738000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Self\u2010Report Alzheimer's Disease Statuses in\n                    <scp>UK<\/scp>\n                    Biobank Distort Downstream Analyses"],"prefix":"10.1111","volume":"169","author":[{"given":"Shuyuan","family":"Hu","sequence":"first","affiliation":[{"name":"Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Zhu","sequence":"additional","affiliation":[{"name":"Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shan","family":"Gao","sequence":"additional","affiliation":[{"name":"Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiyang","family":"Wu","sequence":"additional","affiliation":[{"name":"Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yijie","family":"He","sequence":"additional","affiliation":[{"name":"Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengzhen","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders Capital Medical University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Wang","sequence":"additional","affiliation":[{"name":"Office of Academic Research Taishan Vocational College of Nursing  Taian Shandong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1126-2888","authenticated-orcid":false,"given":"Guiyou","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders Capital Medical University  Beijing China"},{"name":"Department of Epidemiology and Biostatistics, School of Public Health Wannan Medical College  Wuhu Anhui China"},{"name":"Dongying Branch Center, Collaborative Innovation Center for Brain Disorders Shengli Oilfield Central Hospital  Dongying China"},{"name":"Beijing Key Laboratory of Hypoxia Translational Medicine, National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital Capital Medical University  Beijing 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