{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T08:39:38Z","timestamp":1782895178934,"version":"3.54.5"},"reference-count":66,"publisher":"Walter de Gruyter GmbH","issue":"3","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"j_jtim-2026-0038_s_005\">\n                    <jats:title>Background and Objectives<\/jats:title>\n                    <jats:p>MicroRNAs (miRNAs) are emerging as promising blood-based biomarkers for Alzheimer's disease (AD) because of their stability and regulatory roles in disease-related pathways. This study aimed to develop a serum-based miRNA panel for AD diagnosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_jtim-2026-0038_s_006\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Serum samples from 550 participants were categorized into discovery (85 AD, 65 healthy controls [HCs]), training (73 AD, 53 HCs), and validation (99 AD, 99 HCs, 36 vascular cognitive impairment [VCI], 40 dementia with Lewy bodies [DLB]) cohorts. Through small RNA sequencing and qPCR validation, we identified key miRNAs and constructed a diagnostic panel\n                      <jats:italic>via<\/jats:italic>\n                      machine learning.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_jtim-2026-0038_s_007\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The 7-miRNA panel achieved area under the curve (AUC) values of 0.970 and 0.928 in the training and validation cohorts, respectively. The panel effectively differentiated AD from VCI (AUC = 0.951) and DLB (AUC = 0.851). Diagnostic performance remained robust across subgroups defined by age, gender, disease severity, and comorbidities (AUC 0.758\u20130.988). The risk score derived from the 7-miRNA panel was significantly associated with cognitive impairment (Mini-Mental State Examination [MMSE] score,\n                      <jats:italic>r<\/jats:italic>\n                      = -0.72) and plasma amyloid pathology biomarkers (A\u03b242\/40 ratio,\n                      <jats:italic>r<\/jats:italic>\n                      = -0.25; p-tau217,\n                      <jats:italic>r<\/jats:italic>\n                      = 0.36).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_jtim-2026-0038_s_008\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>A serum-based 7-miRNA panel, which offers a minimally invasive and accessible approach, has strong diagnostic potential for AD.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1515\/jtim-2026-0038","type":"journal-article","created":{"date-parts":[[2026,6,14]],"date-time":"2026-06-14T16:06:48Z","timestamp":1781453208000},"page":"456-469","source":"Crossref","is-referenced-by-count":0,"title":["Development of a serum-based microRNA panel for Alzheimer's disease diagnosis"],"prefix":"10.1515","volume":"14","author":[{"given":"Qi","family":"Qin","sequence":"first","affiliation":[{"name":"Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyi","family":"Xia","sequence":"additional","affiliation":[{"name":"Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Miracle (Shenzhen) Biotechnology Co., Ltd. , Shenzhen , Guangdong Province , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Songtao","family":"Yang","sequence":"additional","affiliation":[{"name":"Miracle (Shenzhen) Biotechnology Co., Ltd. , Shenzhen , Guangdong Province , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guodong","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Chinese Materia Medica, Beijing University of Chinese Medicine , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5428-0878","authenticated-orcid":false,"given":"Chang","family":"Su","sequence":"additional","affiliation":[{"name":"Miracle (Shenzhen) Biotechnology Co., Ltd. , Shenzhen , Guangdong Province , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7235-0227","authenticated-orcid":false,"given":"Yi","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders , Beijing , China"},{"name":"Neurodegenerative Laboratory of Ministry of Education of the People\u2019s Republic of China , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2026,6,13]]},"reference":[{"key":"2026070107013749018_j_jtim-2026-0038_ref_001","doi-asserted-by":"crossref","unstructured":"2024 Alzheimer\u2019s disease facts and figures. 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