{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,11]],"date-time":"2026-10-11T13:50:01Z","timestamp":1791726601605,"version":"4.3.4"},"reference-count":79,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2019,3,18]],"date-time":"2019-03-18T00:00:00Z","timestamp":1552867200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2019,4,23]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Microarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer\u2019s disease (AD) brains. However, there is a lack of reproducibility across individual AD studies, and many related neurodegenerative and mental health disorders exhibit similar perturbations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>Meta-analyze publicly available transcriptomic data from multiple brain-related disorders to identify robust transcriptomic changes specific to AD brains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Twenty-two AD, eight schizophrenia, five bipolar disorder, four Huntington\u2019s disease, two major depressive disorder, and one Parkinson\u2019s disease dataset totaling 2,667 samples and mapping to four different brain regions (temporal lobe, frontal lobe, parietal lobe, and cerebellum) were analyzed. Differential expression analysis was performed independently in each dataset, followed by meta-analysis using a combining p-value method known as Adaptively Weighted with One-sided Correction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Meta-analysis identified 323, 435, 1,023, and 828 differentially expressed genes specific to the AD temporal lobe, frontal lobe, parietal lobe, and cerebellum brain regions, respectively. Seven of these genes were consistently perturbed across all AD brain regions with SPCS1 gene expression pattern replicating in RNA-Seq data. A further nineteen genes were perturbed specifically in AD brain regions affected by both plaques and tangles, suggesting possible involvement in AD neuropathology. In addition, biological pathways involved in the \u201cmetabolism of proteins\u201d and viral components were significantly enriched across AD brains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>This study identified transcriptomic changes specific to AD brains, which could make a significant contribution toward the understanding of AD disease mechanisms and may also provide new therapeutic targets.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3233\/jad-181085","type":"journal-article","created":{"date-parts":[[2019,3,19]],"date-time":"2019-03-19T17:23:21Z","timestamp":1553016201000},"page":"1635-1656","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":100,"title":["A Meta-Analysis of Alzheimer\u2019s Disease Brain Transcriptomic Data"],"prefix":"10.1177","volume":"68","author":[{"given":"Hamel","family":"Patel","sequence":"first","affiliation":[{"name":"Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King\u2019s College London, London, UK"},{"name":"NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) and Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King\u2019s College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard J.B.","family":"Dobson","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King\u2019s College London, London, UK"},{"name":"NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) and Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King\u2019s College London, London, UK"},{"name":"Health Data Research UK London, University College London, London, UK"},{"name":"Institute of Health Informatics, University College London, London, UK"},{"name":"The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen J.","family":"Newhouse","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King\u2019s College London, London, UK"},{"name":"NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) and Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King\u2019s College London, London, UK"},{"name":"Health Data Research UK London, University College London, London, UK"},{"name":"Institute of Health Informatics, University College London, London, UK"},{"name":"The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2019,3,18]]},"reference":[{"key":"ref001","volume-title":"World Alzheimer Report 2014. 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