{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T19:49:27Z","timestamp":1792180167217,"version":"4.4.0"},"reference-count":151,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cells"],"abstract":"<jats:p>Dementia with Lewy bodies (DLB) is a significant public health issue. It is the second most common neurodegenerative dementia and presents with severe neuropsychiatric symptoms. Genomic and transcriptomic analyses have provided some insight into disease pathology. Variants within SNCA, GBA, APOE, SNCB, and MAPT have been shown to be associated with DLB in repeated genomic studies. Transcriptomic analysis, conducted predominantly on candidate genes, has identified signatures of synuclein aggregation, protein degradation, amyloid deposition, neuroinflammation, mitochondrial dysfunction, and the upregulation of heat-shock proteins in DLB. Yet, the understanding of DLB molecular pathology is incomplete. This precipitates the current clinical position whereby there are no available disease-modifying treatments or blood-based diagnostic biomarkers. Data science methods have the potential to improve disease understanding, optimising therapeutic intervention and drug development, to reduce disease burden. Genomic prediction will facilitate the early identification of cases and the timely application of future disease-modifying treatments. Transcript-level analyses across the entire transcriptome and machine learning analysis of multi-omic data will uncover novel signatures that may provide clues to DLB pathology and improve drug development. This review will discuss the current genomic and transcriptomic understanding of DLB, highlight gaps in the literature, and describe data science methods that may advance the field.<\/jats:p>","DOI":"10.3390\/cells13030223","type":"journal-article","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T03:59:42Z","timestamp":1706155182000},"page":"223","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Dementia with Lewy Bodies: Genomics, Transcriptomics, and Its Future with Data Science"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5350-2878","authenticated-orcid":false,"given":"Thomas R.","family":"Goddard","sequence":"first","affiliation":[{"name":"Mental Health and Clinical Neurosciences Academic Unit, Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham NG7 2TU, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2427-2513","authenticated-orcid":false,"given":"Keeley J.","family":"Brookes","sequence":"additional","affiliation":[{"name":"Department of Biosciences, School of Science & Technology, Nottingham Trent University, Nottingham NG11 8NS, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9769-9270","authenticated-orcid":false,"given":"Riddhi","family":"Sharma","sequence":"additional","affiliation":[{"name":"Biodiscovery Institute, School of Medicine, University of Nottingham, Nottingham NG7 2RD, UK"},{"name":"UK Health Security Agency, Radiation Effects Department, Radiation Protection Science Division, Harwell Science Campus, Didcot, Oxfordshire OX11 0RQ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Armaghan","family":"Moemeni","sequence":"additional","affiliation":[{"name":"School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3203-6326","authenticated-orcid":false,"given":"Anto P.","family":"Rajkumar","sequence":"additional","affiliation":[{"name":"Mental Health and Clinical Neurosciences Academic Unit, Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham NG7 2TU, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,25]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization, and Alzheimer\u2019s Disease International (2012). 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