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<h1>Multiomics analysis for dementia</h1>
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<h2>Objectives</h2>
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<p>
Determine biomarkers for Alzheimer's and other neurodegenerative diseases using comprehensive analysis of multi-omics data including genomics, epigenomics, metabolomics, proteomics, etc.
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<p>
Large cohorts with phenotype data on dementia are available through the following resources (incomplete <a href="https://docs.google.com/spreadsheets/d/1NpWRjxwwCJp-AKci239fjCf2IDg-oJONdNAuBojsG9I/edit#gid=305034359" class="urlextern" title="https://docs.google.com/spreadsheets/d/1NpWRjxwwCJp-AKci239fjCf2IDg-oJONdNAuBojsG9I/edit#gid=305034359" rel="ugc nofollow">table</a> of data types):
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<ol>
<li class="level1"> The Cohorts for Heart and Aging Research in Genomic Epidemiology (<a href="http://www.chargeconsortium.com" class="urlextern" title="http://www.chargeconsortium.com" rel="ugc nofollow">CHARGE</a>) Consortium.</li>
<li class="level1"> The Trans-Omics for Precision Medicine (<a href="https://www.nhlbiwgs.org" class="urlextern" title="https://www.nhlbiwgs.org" rel="ugc nofollow">TOPMed</a>) program. The TOPMed Omics <a href="http://oncinfo.org/_media/wiki:topmed_omics_survey.pdf" class="urlextern" title="http://oncinfo.org/_media/wiki:topmed_omics_survey.pdf" rel="ugc nofollow">Survey</a> in 2017 includes Framingham Heart Study (FHS) details, which are described clearer in <a href="http://oncinfo.org/_media/wiki:omics_fhs.pdf" class="urlextern" title="http://oncinfo.org/_media/wiki:omics_fhs.pdf" rel="ugc nofollow">2016</a>. <a href="https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/molecular.cgi?study_id=phs000363.v17.p11&phv=173423&phd=4119&pha=&pht=2941&phvf=&phdf=&phaf=&phtf=&dssp=1&consent=&temp=1" class="urlextern" title="https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/molecular.cgi?study_id=phs000363.v17.p11&phv=173423&phd=4119&pha=&pht=2941&phvf=&phdf=&phaf=&phtf=&dssp=1&consent=&temp=1" rel="ugc nofollow">SABRe</a> is a substudy of FHS and has mRNA and miRNA data. We obtained <a href="https://docs.google.com/document/d/1B8uKY2QBuJHAiPrv9y_cR9704RrI7nZM71oVc7jt5Q8/edit" class="urlextern" title="https://docs.google.com/document/d/1B8uKY2QBuJHAiPrv9y_cR9704RrI7nZM71oVc7jt5Q8/edit" rel="ugc nofollow">these</a> data in 2019. On 2021-04-23, <a href="/lib/exe/fetch.php?media=fhs_multiomics_meeting_msevilla_april21.pdf" class="media mediafile mf_pdf" title="fhs_multiomics_meeting_msevilla_april21.pdf (2.7 MB)">Magdalena</a>  Sevilla presented a collection of FHS, MESA, and WHI omics datasets and some statistical methods for analyzing them.</li>
<li class="level1"> Exome Sequencing Project (<a href="http://evs.gs.washington.edu" class="urlextern" title="http://evs.gs.washington.edu" rel="ugc nofollow">ESP</a>), richly-phenotyped for heart, lung and blood disorders.</li>
<li class="level1"> Alzheimer's Disease Sequencing Project (<a href="https://www.niagads.org/adsp/content/study-design" class="urlextern" title="https://www.niagads.org/adsp/content/study-design" rel="ugc nofollow">ADSP</a>), WES and WGS of thousands of AD and control samples.</li>
<li class="level1"> Allen Brain <a href="http://portal.brain-map.org/" class="urlextern" title="http://portal.brain-map.org/" rel="ugc nofollow">Atlases</a> has many different <a href="http://aging.brain-map.org/overview/home" class="urlextern" title="http://aging.brain-map.org/overview/home" rel="ugc nofollow">downloadable</a> data types, but from a few mouse and human samples. RNA-Seq data of hundreds of dementia cases.</li>
<li class="level1"> The Image and Data Archive (<a href="https://ida.loni.usc.edu" class="urlextern" title="https://ida.loni.usc.edu" rel="ugc nofollow">IDA</a>) contains mostly image data on 43,290 subjects from 119 studies.</li>
<li class="level1"> The Alzheimer's Disease Neuroimaging Initiative (<a href="http://adni.loni.usc.edu/data-samples/data-types/" class="urlextern" title="http://adni.loni.usc.edu/data-samples/data-types/" rel="ugc nofollow">ADNI</a>) has genetic and imaging data of 1-3 K samples, which are available through <a href="https://ida.loni.usc.edu" class="urlextern" title="https://ida.loni.usc.edu" rel="ugc nofollow">IDA</a>.</li>
<li class="level1 node"> Several studies share their data through Accelerating Medicines Partnership - Alzheimer's Disease (<a href="https://www.synapse.org/#!Synapse:syn5550382" class="urlextern" title="https://www.synapse.org/#!Synapse:syn5550382" rel="ugc nofollow">AMP-AD</a>) including:<ol>
<li class="level3"> The Adult Changes in Thought (<a href="https://www.synapse.org/#!Synapse:syn5759376" class="urlextern" title="https://www.synapse.org/#!Synapse:syn5759376" rel="ugc nofollow">ACT</a>) measured ~4K <u>proteins</u>  in ~50 brains and performed WGCNA. Also, proteome data in BLSA (~100 brains), Banner (~200), and UPPpilot (~200).</li>
<li class="level3"> CHDWB and HBTRC, each has a <u>gene expression</u>  profile from ~500 brains, MC-CAA (75), MCADGS (~100 RNA-Seq and GWAS samples).</li>
<li class="level3"> The Mount Sinai Brain Bank (<a href="https://www.synapse.org/#!Synapse:syn3159438" class="urlextern" title="https://www.synapse.org/#!Synapse:syn3159438" rel="ugc nofollow">MSBB</a>) includes proteome and gene expression profiles from hundreds of samples.</li>
<li class="level3"> The <a href="https://www.synapse.org/#!Synapse:syn5550404" class="urlextern" title="https://www.synapse.org/#!Synapse:syn5550404" rel="ugc nofollow">MayoRNAseq</a> includes WGS and RNA-Seq data from 275 Cerebellum (CBE) and 276 Temporal cortex (TCX) samples.</li>
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<li class="level1"> The Religious Orders Study and Memory and Aging Project (<a href="https://www.synapse.org/#!Synapse:syn3219045" class="urlextern" title="https://www.synapse.org/#!Synapse:syn3219045" rel="ugc nofollow">ROSMAP</a>) is the <b>richest</b>  dataset in AMP-AD in terms of variety of data types, which include gene expression, genome, proteome, metabolome, and image data. Also, DNA methylation, miRNA, WGS, WES, and even H3K9Ac are available for ~1K samples. The dataset is very well <a href="https://www.radc.rush.edu/docs/omics.htm" class="urlextern" title="https://www.radc.rush.edu/docs/omics.htm" rel="ugc nofollow">documented</a>, and was used to identify <a href="http://mostafavilab.stat.ubc.ca/xqtl/" class="urlextern" title="http://mostafavilab.stat.ubc.ca/xqtl/" rel="ugc nofollow">xQTL</a> by Philip De Jager.</li>
<li class="level1"> Mathys, Hansruedi, et al. "<b>Single-cell</b>  transcriptomic analysis of Alzheimer’s disease." Nature (<a href="https://www.nature.com/articles/s41586-019-1195-2" class="urlextern" title="https://www.nature.com/articles/s41586-019-1195-2" rel="ugc nofollow">2019</a>). <br/>
 Radek's summary: "Showing ~80K single cell transcriptomic analysis on brain tissues from ~50 patients with Alzheimer's disease. Subpopulations of glia and neurons expressed different gene signatures associated with AD. These enormous cataloging data may help to further pinpoint pathways associated with AD.", and his <a href="/doku.php?id=plan" class="wikilink2" title="plan" rel="nofollow" data-wiki-id="plan">plan</a>. Habil's <a href="https://docs.google.com/presentation/d/1u2rv9FExW44JfJsqPjenJcCsCFnOSUbJUxQwalviNHk/edit#slide=id.p" class="urlextern" title="https://docs.google.com/presentation/d/1u2rv9FExW44JfJsqPjenJcCsCFnOSUbJUxQwalviNHk/edit#slide=id.p" rel="ugc nofollow">presentation</a> in Biggs journal club on 2 July 2019.</li>
<li class="level1"> The Brain eQTL Almanac (<a href="http://braineac.org/" class="urlextern" title="http://braineac.org/" rel="ugc nofollow">Braineac</a>) generated by UK Brain Expression Consortium (UKBEC) "comprises of genomic and transcriptome data of 134 brains from individuals free of neurodegenerative disorders. Up to 12 brain regions were extracted per brain in parallel for mRNA quantification."</li>
<li class="level1"> Omics data were generated in <a href="https://www.neurodegenerationresearch.eu/it/cohort/the-rhineland-study/" class="urlextern" title="https://www.neurodegenerationresearch.eu/it/cohort/the-rhineland-study/" rel="ugc nofollow">Rhineland</a> Study including DNA methylation from ~2K blood samples. Aslam Imtiaz presented these data in the NeuroCHARGE call on 2019-11-07.</li>
<li class="level1"> <a href="https://bmbls.bmi.osumc.edu/scread/" class="urlextern" title="https://bmbls.bmi.osumc.edu/scread/" rel="ugc nofollow">scREAD</a>: A Single-Cell RNA-Seq Database for Alzheimer’s Disease (<a href="https://www.cell.com/iscience/pdf/S2589-0042(20)30966-4.pdf" class="urlextern" title="https://www.cell.com/iscience/pdf/S2589-0042(20)30966-4.pdf" rel="ugc nofollow">pdf</a>). It covers 73 datasets from 15 studies, 10 brain regions, 713640 cells.Useful for: a) listing available datasets, b) easy preliminary DE analysis across cell types and disease vs. control conditions.</li>
<li class="level1"> <a href="https://www.nature.com/articles/s41586-021-03910-8" class="urlextern" title="https://www.nature.com/articles/s41586-021-03910-8" rel="ugc nofollow">Bhaduri</a> 's 2021 snRNASeq of the developing human brain.</li>
<li class="level1"> Leonenko, et al. (2021). Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores. <a href="https://www.nature.com/articles/s41467-021-24082-z#Sec8" class="urlextern" title="https://www.nature.com/articles/s41467-021-24082-z#Sec8" rel="ugc nofollow">Nature communications</a>. A comprehensive list of large dementia cohorts in the Methods.</li>
<li class="level1"> Gabitto, Mariano I., et al. "Integrated multimodal cell atlas of Alzheimer’s disease." <em>bioRxiv</em> (2023). Seattle Alzheimer’s Disease Brain Cell <a href="https://portal.brain-map.org/explore/seattle-alzheimers-disease" class="urlextern" title="https://portal.brain-map.org/explore/seattle-alzheimers-disease" rel="ugc nofollow">Atlas</a>, <a href="https://knowledge.brain-map.org/data/5IU4U8BP711TR6KZ843/2CD0HDC5PS6A58T0P6E/compare?cellType=Whole Taxonomy&geneOption=IL1B&metadata=Cognitive Status&comparison=dotplot" class="urlextern" title="https://knowledge.brain-map.org/data/5IU4U8BP711TR6KZ843/2CD0HDC5PS6A58T0P6E/compare?cellType=Whole Taxonomy&geneOption=IL1B&metadata=Cognitive Status&comparison=dotplot" rel="ugc nofollow">browsable</a> from knowledge.brain-map.org.</li>
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<h2>Collaborators</h2>
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Dr. <a href="http://gsbs.uthscsa.edu/faculty/sudha-seshadri-m.d.-dm" class="urlextern" title="http://gsbs.uthscsa.edu/faculty/sudha-seshadri-m.d.-dm" rel="ugc nofollow">Sudha Seshadri</a>, the Founding Director of The Glenn <a href="https://biggsinstitute.org/" class="urlextern" title="https://biggsinstitute.org/" rel="ugc nofollow">Biggs Institute</a> for Alzheimer's & Neurodegenerative Diseases, <a href="https://biggsinstitute.org/team-member/claudia-l-satizabal-phd/" class="urlextern" title="https://biggsinstitute.org/team-member/claudia-l-satizabal-phd/" rel="ugc nofollow">Dr. Claudia Satizabal</a>, Dr. <a href="http://runewarkbiology.rutgers.edu/Dobrowolski Lab/index.html" class="urlextern" title="http://runewarkbiology.rutgers.edu/Dobrowolski Lab/index.html" rel="ugc nofollow">Radek Dobrowolski</a>, Dr. <a href="https://biggsinstitute.org/team-member/qitao-ran/" class="urlextern" title="https://biggsinstitute.org/team-member/qitao-ran/" rel="ugc nofollow">Qitao Ran</a>, and Dr. <a href="https://school.wakehealth.edu/Faculty/O/Miranda-E-Orr" class="urlextern" title="https://school.wakehealth.edu/Faculty/O/Miranda-E-Orr" rel="ugc nofollow">Miranda Orr</a> from Wake Forest University.
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<h2>Subprojects</h2>
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<li class="level1"> Network analysis on <a href="https://docs.google.com/document/d/1K89u6OubQUXAycg6JaEqzNgv18ybRy4QWcG_3UVQBuQ/edit" class="urlextern" title="https://docs.google.com/document/d/1K89u6OubQUXAycg6JaEqzNgv18ybRy4QWcG_3UVQBuQ/edit" rel="ugc nofollow">proteome</a> data of Fremingham cohort.</li>
<li class="level1"> <a href="https://docs.google.com/presentation/d/1gCs39bst5xqxbpLNybRkJg1hUxxWCspmhlvKfdjtTsw/edit?ts=5d41b329#slide=id.g5e1f444b4f_0_0" class="urlextern" title="https://docs.google.com/presentation/d/1gCs39bst5xqxbpLNybRkJg1hUxxWCspmhlvKfdjtTsw/edit?ts=5d41b329#slide=id.g5e1f444b4f_0_0" rel="ugc nofollow">DE</a> analysis on RNA-Seq data of 5xFAD and Gpx4Tg mouse models for AD. Four biological replicates in each of the four conditions were generated in Ran's Lab.</li>
<li class="level1"> Identify senescent cells and their characteristics in human brain.</li>
<li class="level1"> Assess the effect of lowering expression of CD33 in microglia on AD phenotypes through <a href="https://docs.google.com/document/d/1-SStE--v9-ATh1Bi9zqEXaTDD21kX2KjyQ1J6c0Ww74/edit" class="urlextern" title="https://docs.google.com/document/d/1-SStE--v9-ATh1Bi9zqEXaTDD21kX2KjyQ1J6c0Ww74/edit" rel="ugc nofollow">analysis</a> of single cell RNA-Seq data.</li>
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<h2>Related work</h2>
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<li class="level1"> An interactive <b>timeline</b>  of Alzheimer's disease by <a href="https://www.alzforum.org/timeline/alzheimers-disease#2010" class="urlextern" title="https://www.alzforum.org/timeline/alzheimers-disease#2010" rel="ugc nofollow">AlzForum</a>.</li>
<li class="level1"> <a href="https://www.nia.nih.gov/research/blog/2022/05/napa-at-10?utm_source=NIA+Main&utm_campaign=3c45f80fa9-20220516_blog&utm_medium=email&utm_term=0_ffe42fdac3-3c45f80fa9-18446435" class="urlextern" title="https://www.nia.nih.gov/research/blog/2022/05/napa-at-10?utm_source=NIA+Main&utm_campaign=3c45f80fa9-20220516_blog&utm_medium=email&utm_term=0_ffe42fdac3-3c45f80fa9-18446435" rel="ugc nofollow">NAPA</a> at 10: A decade of Alzheimer’s and related dementias research progress, 2022.</li>
<li class="level1"> Satizabal, Claudia L., et al. "Genetic architecture of subcortical brain structures in 38,851 individuals." <em><a href="https://www.nature.com/articles/s41588-019-0511-y" class="urlextern" title="https://www.nature.com/articles/s41588-019-0511-y" rel="ugc nofollow">Nature genetics</a></em> 51.11 (2019): 1624-1636. <br/>
They identified a set of genes that is "significantly enriched for <em>Drosophila</em>  orthologs associated with neurodevelopmental phenotypes".</li>
<li class="level1"> Yamazaki, Yu., et al. "Apolipoprotein E and Alzheimer disease: pathobiology and targeting strategies." <a href="https://www.nature.com/articles/s41582-019-0228-7" class="urlextern" title="https://www.nature.com/articles/s41582-019-0228-7" rel="ugc nofollow">Nat Rev Neurol </a>(2019): 501–518.</li>
<li class="level1"> Ferreira, Daniel., et al. Biological subtypes of Alzheimer disease: A systematic review and meta-analysis <a href="https://n.neurology.org/content/neurology/early/2020/02/11/WNL.0000000000009058.full.pdf" class="urlextern" title="https://n.neurology.org/content/neurology/early/2020/02/11/WNL.0000000000009058.full.pdf" rel="ugc nofollow">Neurology</a> (2020):94:1-13.</li>
<li class="level1"> Sey, Nancy YA, et al. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. <a href="https://www.nature.com/articles/s41593-020-0603-0" class="urlextern" title="https://www.nature.com/articles/s41593-020-0603-0" rel="ugc nofollow">Nature Neuroscience</a>, 2020.</li>
<li class="level1"> Borghesan, M., et al. "A <b>Senescence</b>-Centric View of Aging: Implications for Longevity and Disease." <a href="https://www.sciencedirect.com/science/article/abs/pii/S0962892420301434" class="urlextern" title="https://www.sciencedirect.com/science/article/abs/pii/S0962892420301434" rel="ugc nofollow">Trends in Cell Biology</a> (2020). The review paper suggested by Christi.</li>
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