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Recently, multi-omics data generated from advanced technology platforms has become available for disease studies. Therefore, the integration of this data with associated clinical data provides a unique opportunity to gain a deeper understanding of disease. However, the effective integration of large-scale multi-omics data remains a major challenge. To address this, we propose a novel deep learning model\u2014the Multi-Omics Graph Attention biomarker Discovery network (MOGAD). MOGAD aims to efficiently classify diseases and discover biomarkers by integrating various omics data such as DNA methylation, gene expression, and miRNA expression. The model consists of three main modules: Multi-head GAT network (MGAT), Multi-Graph Attention Fusion (MGAF), and Attention Fusion (AF), which work together to dynamically model the complex relationships among different omics layers. We incorporate clinical data (e.g., APOE genotype) which enables a systematic investigation of the influence of non-omics factors on disease classification. The experimental results demonstrate that MOGAD achieves a superior performance compared to existing single-omics and multi-omics integration methods in classification tasks for Alzheimer\u2019s disease (AD). In the comparative experiment on the ROSMAP dataset, our model achieved the highest ACC (0.773), F1-score (0.787), and MCC (0.551). The biomarkers identified by MOGAD show strong associations with the underlying pathogenesis of AD. We also apply a Hi-C dataset to validate the biological rationality of the identified biomarkers. Furthermore, the incorporation of clinical data enhances the model\u2019s robustness and uncovers synergistic interactions between omics and non-omics features. Thus, our deep learning model is able to successfully integrate multi-omics data to efficiently classify disease and discover novel biomarkers.<\/jats:p>","DOI":"10.3390\/informatics12030068","type":"journal-article","created":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T13:44:19Z","timestamp":1752241459000},"page":"68","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["MOGAD: Integrated Multi-Omics and Graph Attention for the Discovery of Alzheimer\u2019s Disease\u2019s Biomarkers"],"prefix":"10.3390","volume":"12","author":[{"given":"Zhizhong","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, College of Mathematics and Computer, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuqi","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, College of Mathematics and Computer, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changliang","family":"Wang","sequence":"additional","affiliation":[{"name":"Guangzhou National Laboratory, Guangzhou 510799, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maoni","family":"Guo","sequence":"additional","affiliation":[{"name":"Guangzhou National Laboratory, Guangzhou 510799, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Cai","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, College of Mathematics and Computer, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"He","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, College of Mathematics and Computer, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1147-3968","authenticated-orcid":false,"given":"Yanchun","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Zhuhai College of Science and Technology, Zhuhai 519041, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4566-9958","authenticated-orcid":false,"given":"Garry","family":"Wong","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, University of Macau, Taipa, Macau SAR 999078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6644-477X","authenticated-orcid":false,"given":"Liang","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, College of Mathematics and Computer, Shantou University, Shantou 515063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.pharep.2014.09.004","article-title":"A review on alzheimer\u2019s disease pathophysiology and its management: An update","volume":"67","author":"Kumar","year":"2015","journal-title":"Pharmacol. 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