View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by King's Research Portal King’s Research Portal DOI: 10.3233/JAD-181085 Document Version Publisher's PDF, also known as Version of record Link to publication record in King's Research Portal Citation for published version (APA): Patel, H., Dobson, R. J. B., & Newhouse, S. J. (2019). A Meta-Analysis of Alzheimer’s Disease Brain Transcriptomic Data. Journal of Alzheimer's Disease, 68(4), 1635-1656. https://doi.org/10.3233/JAD-181085 Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. 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Download date: 09. May. 2019 Journal of Alzheimer’s Disease 68 (2019) 1635–1656 1635 DOI 10.3233/JAD-181085 IOS Press A Meta-Analysis of Alzheimer’s Disease Brain Transcriptomic Data Hamel Patela,b,1,∗, Richard J.B. Dobsona,b,c,d,e,1 and Stephen J. Newhousea,b,c,d,e,1 aDepartment of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK bNIHR 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’s College London, London, UK cHealth Data Research UK London, University College London, London, UK dInstitute of Health Informatics, University College London, London, UK eThe National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK Accepted 11 February 2019 Abstract. Background: Microarray technologies have identified imbalances in the expression of specific genes and biological pathways in Alzheimer’s 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. Objective: Meta-analyze publicly available transcriptomic data from multiple brain-related disorders to identify robust transcriptomic changes specific to AD brains. Methods: Twenty-two AD, eight schizophrenia, five bipolar disorder, four Huntington’s disease, two major depressive disorder, and one Parkinson’s 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. Results: 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 “metabolism of proteins” and viral components were significantly enriched across AD brains. Conclusion: 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. Keywords: Alzheimer’s disease, gene expression, human, mental disorders, meta-analysis, microarray analysis, neurodegen- erative disorders, neuropathology INTRODUCTION 1These authors are joint last authors. ∗ Correspondence to: Hamel Patel, Department of Biostatistics Alzheimer’s disease (AD) is the most common & Health Informatics, SGDP Centre, IoPPN, De Crespigny Park, Denmark Hill London, SE5 8AF, UK. Tel.: +44 207 848 0969; form of dementia affecting over 44 million individu- E-mail: [email protected]. als worldwide, and numbers are expected to triple by ISSN 1387-2877/19/$35.00 © 2019 – IOS Press and the authors. All rights reserved This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC 4.0). 1636 H. Patel et al. / Meta-Analysis of AD Brain Transcriptomic Data 2050 [1]. The hallmark of the disease is characterized for multiple testing, no gene was replicated between by the abnormal brain accumulation of amyloid-␤ the two studies. The Miller study consisted of 7 (A␤) protein and hyperphosphorylated tau filaments, AD and 10 control subjects expression profiled on which forms structures known as plaques and tan- the Affymetrix platform while the Hakoma study gles, respectively. The accumulation of these proteins consisted of 31 AD and 32 control subjects expres- contributes to the loss of connections between neuron sion profiled on the Illumina platform. Replication synapses, leading to the loss of brain tissue and the between the Illumina and Affymetrix platform has disruption of normal cognitive functions. been shown to be generally very high [9]; therefore, As AD progresses, the spread of plaques and tan- the lack of replication between the two studies is gles in the brain usually occurs in a predictable pattern probably down to a range of other factors includ- and can begin up to 18 years prior to the onset of clini- ing low statistical power, sampling bias, and disease cal symptoms [2]. In the earliest stages of the disease, heterogeneity. plaques and tangles form in areas of the brain primar- Unlike DEGs, replication of the molecular changes ily involved in learning and memory, specifically the at a pathway level are more consistent and have hippocampus and entorhinal cortex, both situated in provided insights into the biological processes dis- the temporal lobe (TL) region [3]. Next, the frontal turbed in AD. Numerous studies have consistently lobe (FL), a region involved in voluntary movement, highlighted disruptions in immune response [10–13], is affected, followed by the parietal lobe (PL), a region protein transcription/translation [10, 11, 14–17], cal- involved in processing reading and writing. In the cium signaling [10, 18, 19], MAPK signaling [7, 16], later stage of the disease, the occipital lobe, a region various metabolism pathways such as carbohydrates involved in processing information from the eyes, can [16], lipids [16, 20], glucose [17, 21, 22], iron [11, become affected, followed by the cerebellum (CB), 23], chemical synapse [7, 18, 19], and neurotransmit- a region which receives information from the sen- ter [11, 18, 19]. However, many of these pathways sory systems and the spinal cord to regulates motor have also been suggested to be disrupted in other movement. Nerve cell death, tissue loss, and atrophy brain-related disorders. For example, disruptions in occur throughout the brain as AD progresses, leading calcium signaling, MAPK, chemical synapse, and to the manifestation of clinical symptoms associated various neurotransmitter pathways have also been with loss of normal brain function. However, not all implicated in Parkinson’s disease (PD) [24, 25]. In brain regions are neuropathologically affected in the addition, glucose metabolism, protein translation, same manner. The CB, which only accounts for 10% and various neurotransmission pathways have also of the brain but contains over 50% of the brain’s total been suggested to be disrupted in bipolar disorder neurons, is often neglected in AD research because (BD) [26–29]. Although the biological disruptions it is generally considered to be partially spared from involved in AD are steadily being identified, many the disease as plaques are only occasionally seen but other neurodegenerative and mental disorders are tangles are generally not reported [4, 5]. showing similar perturbations. We are yet to identify The histopathological spread of the disease is well robust transcriptomic changes specific to AD brains. documented, and with the advent of high throughput In this study, we combined publicly available genomics approaches, we are now able to study the microarray gene expression data generated from AD transcriptomic and biological pathways disrupted in human brain tissue and matched cognitively healthy AD brains. Microarrays can simultaneously exam- controls to