{"id":304917,"date":"2023-06-19T17:05:00","date_gmt":"2023-06-19T09:05:00","guid":{"rendered":"https:\/\/www.um.edu.mo\/news-and-press-releases\/campus-news\/detail\/55868-2\/"},"modified":"2023-06-20T14:59:07","modified_gmt":"2023-06-20T06:59:07","slug":"55868","status":"publish","type":"post","link":"https:\/\/www.um.edu.mo\/pt-pt\/news-and-press-releases\/campus-news\/detail\/55868\/","title":{"rendered":"UM faz novas descobertas no diagn\u00f3stico inteligente da doen\u00e7a de Alzheimer"},"content":{"rendered":"\n                        \n                        <p>A team led by Yuan Zhen, professor at the Centre for Cognitive and Brain Sciences (CCBS) of the University of Macau (UM), has made new progress in the study of individual-specific functional connectivity to predict normal cognitive ageing (CA), mild cognitive impairment (MCI), and Alzheimer\u2019s disease (AD). This study is the first to combine individual-specific functional connectivity with artificial intelligence (AI) techniques to reveal differences in functional connectivity between CA, MCI, and AD in elderly people with different APOE \u03b54 genotypes. The research results have been published in Communications Biology, a journal from Nature.<\/p><p>AD is one of the most common neurodegenerative diseases. As of 2019, over 5.16 million people worldwide were diagnosed with AD or other types of dementia. AD patients usually suffer from significant memory loss and executive function impairments, which lead to decreased quality of life. Traditional neuroimaging investigations relying on population-level functional network atlas have difficulty in identifying brain biomarkers for the accurate diagnosis of AD. At the individual level, studies on predicting the process from CA, MCI, to AD are still insufficient, particularly in patients presenting different clinical phenotypes.<\/p><p>In the study, researchers extracted the neuroimaging data of 235 elderly individuals (120 APOE \u03b54 carriers and 115 APOE \u03b54 non-carriers; age: 60-85 years) from the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) dataset and constructed individual-specific functional connectivity for each participant. They then utilised recursive feature selection-based machine learning to reveal individual brain-behaviour relationships and predict changes in the clinical symptoms in AD patients with different genotypes. The study found that individual-specific functional connectivity of elderly people with different APOE \u03b54 genotypes could be used to predict the clinical subgroups from CA, MCI, to AD, and yield moderate-to-strong estimation levels of AD-related clinical symptoms. However, the team failed to detect clinical symptoms in almost all cases with conventional atlas-based functional connectivity.<\/p><p>The study also showed that connections between brain functional networks are more informative than those within the same network in explaining symptom-specific severity of AD, particularly for elderly people with the APOE \u03b54 allele. The research results highlighted the importance of accounting for individual variation in cortical functional anatomy in neurodegenerative research, which can be extended to the healthy population. In addition, individual-specific functional connectivity models could be used to tailor treatment to specific needs. Thus, the study underlined the relationship between individual-specific functional connectivity and clinical symptoms, which can provide clinical utility for the diagnosis, prognosis, and treatment of AD.<\/p><p>The study was led by Prof Yuan, and the first author of the paper is Hua Lin, PhD student in the CCBS and the Faculty of Health Sciences. The study was supported by the Science and Technology Development Fund, Macao SAR (File no: 0048\/2021\/AGJ, 0020\/2019\/AMJ), Macao SAR Government Education Fund (CP-UMAC-2020-01), and UM (MYRG2020-00067-FHS, MYRG2019-00082-FHS). The full version of the paper can be viewed at <a href=\"https:\/\/www.nature.com\/articles\/s42003-023-04952-6\">https:\/\/www.nature.com\/articles\/s42003-023-04952-6<\/a>.<\/p><p><\/p><p><\/p>\n\n<table style=\"width: 44.7597%;height: 201px\"> <tbody> <tr style=\"height: 21px\"> <td style=\"height: 21px;width: 100.095%\" colspan=\"2\">Source: Institute of Collaborative Innovation<\/td> <\/tr> <tr style=\"height: 21px\"> <td style=\"height: 21px;width: 56.3278%;min-width: 120px\"> <\/td> <td style=\"height: 21px;width: 43.7669%\"> <\/td> <\/tr> <tr style=\"height: 21px\"> <td style=\"height: 21px;width: 100.095%\" colspan=\"2\">Media Contact Information:<\/td> <\/tr> <tr style=\"height: 21px\"> <td style=\"height: 12px;width: 100.095%\" colspan=\"2\">Communications Office, University of Macau<\/td> <\/tr> <tr style=\"height: 21px\"> <td style=\"height: 21px;width: 56.3278%;min-width: 120px\"> <\/td> <td style=\"height: 21px;width: 43.7669%\"> <\/td> <\/tr> <tr style=\"height: 21px\"> <td style=\"height: 21px;width: 56.3278%;min-width: 120px\">Albee Lei<\/td> <td style=\"height: 21px;width: 43.7669%\">Tel: (853) 8822 8004<\/td> <\/tr> <tr style=\"height: 21px\"> <td style=\"height: 21px;width: 56.3278%;min-width: 120px\">Bell Leong<\/td> <td style=\"height: 21px;width: 43.7669%\">Tel: (853) 8822 8009<\/td> <\/tr> <tr style=\"height: 21px\"> <td style=\"height: 21px;width: 56.3278%;min-width: 120px\">Email:<\/td> <td style=\"height: 21px;width: 43.7669%\"><a style=\"font-family: Tahoma, Verdana, sans-serif;font-size: small\" href=\"mailto:prs.media@um.edu.mo\">prs.media@um.edu.mo<\/a><\/td>\n<\/tr>\n<tr style=\"height: 21px\">\n<td style=\"height: 21px;width: 56.3278%;min-width: 120px\"> <\/td> <td style=\"height: 21px;width: 43.7669%\"> <\/td> <\/tr> <tr style=\"height: 21px\"> <td style=\"height: 21px;width: 56.3278%;min-width: 120px\"><\/td><td style=\"height: 21px;width: 43.7669%\"><\/td><\/tr>\n<\/tbody>\n<\/table>\n                        \n                        ","protected":false},"excerpt":{"rendered":"<p>A team led by Yuan Zhen, professor at the Centre for Cognitive and Brain Sciences (CCBS) of the University of Macau (UM), has made new progress in the study of&#8230;<\/p>\n","protected":false},"author":1,"featured_media":305019,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[61],"tags":[],"class_list":["post-304917","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-campus-news"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>UM faz novas descobertas no diagn\u00f3stico inteligente da doen\u00e7a de Alzheimer | Universidade de Macau<\/title>\n<meta name=\"description\" content=\"Universidade de Macau: Uma universidade abrangente p\u00fablica de n\u00edvel internacional fundada em 1981\" 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