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multiomics_analysis_for_dementia [2019/06/07 14:54] – [Related work] adminmultiomics_analysis_for_dementia [2020/04/15 18:21] – [Related work] admin
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 ===== Data ===== ===== Data =====
  
-Large cohorts with phenotype data on dementia are available through:+Large cohorts with phenotype data on dementia are available through the following resources (incomplete [[https://docs.google.com/spreadsheets/d/1NpWRjxwwCJp-AKci239fjCf2IDg-oJONdNAuBojsG9I/edit#gid=305034359|table]] of data types):
  
   - The Cohorts for Heart and Aging Research in Genomic Epidemiology ([[http://www.chargeconsortium.com|CHARGE]]) Consortium.   - The Cohorts for Heart and Aging Research in Genomic Epidemiology ([[http://www.chargeconsortium.com|CHARGE]]) Consortium.
-  - The Trans-Omics for Precision Medicine ([[https://www.nhlbiwgs.org|TOPMed]]) program. The TOPMed Omics [[http://oncinfo.org/_media/wiki:topmed_omics_survey.pdf|Survey]] in 2017 includes Framingham Heart Study (FHS) details, which are described clearer in [[http://oncinfo.org/_media/wiki:omics_fhs.pdf|2016]]. [[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|SABRe]] is a substudy of FHS and has mRNA and miRNA data.+  - The Trans-Omics for Precision Medicine ([[https://www.nhlbiwgs.org|TOPMed]]) program. The TOPMed Omics [[http://oncinfo.org/_media/wiki:topmed_omics_survey.pdf|Survey]] in 2017 includes Framingham Heart Study (FHS) details, which are described clearer in [[http://oncinfo.org/_media/wiki:omics_fhs.pdf|2016]]. [[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|SABRe]] is a substudy of FHS and has mRNA and miRNA data. We obtained [[https://docs.google.com/document/d/1B8uKY2QBuJHAiPrv9y_cR9704RrI7nZM71oVc7jt5Q8/edit|these]] data in 2019.
   - Exome Sequencing Project ([[http://evs.gs.washington.edu|ESP]]), richly-phenotyped for heart, lung and blood disorders.   - Exome Sequencing Project ([[http://evs.gs.washington.edu|ESP]]), richly-phenotyped for heart, lung and blood disorders.
   - Alzheimer's Disease Sequencing Project ([[https://www.niagads.org/adsp/content/study-design|ADSP]]), WES and WGS of thousands of AD and control samples.   - Alzheimer's Disease Sequencing Project ([[https://www.niagads.org/adsp/content/study-design|ADSP]]), WES and WGS of thousands of AD and control samples.
   - Allen Brain [[http://portal.brain-map.org/|Atlases]] has many different [[http://aging.brain-map.org/overview/home|downloadable]] data types, but from a few mouse and human samples. RNA-Seq data of hundreds of dementia cases.   - Allen Brain [[http://portal.brain-map.org/|Atlases]] has many different [[http://aging.brain-map.org/overview/home|downloadable]] data types, but from a few mouse and human samples. RNA-Seq data of hundreds of dementia cases.
-  - The Alzheimer's Disease Neuroimaging Initiative ([[http://adni.loni.usc.edu/data-samples/data-types/|ADNI]]) has genetic and imaging data of 1-3 K samples. 
   - The Image and Data Archive ([[https://ida.loni.usc.edu|IDA]]) contains mostly image data on 43,290 subjects from 119 studies.   - The Image and Data Archive ([[https://ida.loni.usc.edu|IDA]]) contains mostly image data on 43,290 subjects from 119 studies.
 +  - The Alzheimer's Disease Neuroimaging Initiative ([[http://adni.loni.usc.edu/data-samples/data-types/|ADNI]]) has genetic and imaging data of 1-3 K samples, which are available through [[https://ida.loni.usc.edu|IDA]].
   - Several studies share their data through Accelerating Medicines Partnership - Alzheimer's Disease ([[https://www.synapse.org/#!Synapse:syn5550382|AMP-AD]]) including:   - Several studies share their data through Accelerating Medicines Partnership - Alzheimer's Disease ([[https://www.synapse.org/#!Synapse:syn5550382|AMP-AD]]) including:
       - The Adult Changes in Thought ([[https://www.synapse.org/#!Synapse:syn5759376|ACT]]) measured ~4K __proteins__  in ~50 brains and performed WGCNA. Also, proteome data in BLSA (~100 brains), Banner (~200), and UPPpilot (~200).       - The Adult Changes in Thought ([[https://www.synapse.org/#!Synapse:syn5759376|ACT]]) measured ~4K __proteins__  in ~50 brains and performed WGCNA. Also, proteome data in BLSA (~100 brains), Banner (~200), and UPPpilot (~200).
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       - The Mount Sinai Brain Bank ([[https://www.synapse.org/#!Synapse:syn3159438|MSBB]]) includes proteome and gene expression profiles from hundreds of samples.       - The Mount Sinai Brain Bank ([[https://www.synapse.org/#!Synapse:syn3159438|MSBB]]) includes proteome and gene expression profiles from hundreds of samples.
       - The [[https://www.synapse.org/#!Synapse:syn5550404|MayoRNAseq]] includes WGS and RNA-Seq data from 275 Cerebellum (CBE) and 276 Temporal cortex (TCX) samples.       - The [[https://www.synapse.org/#!Synapse:syn5550404|MayoRNAseq]] includes WGS and RNA-Seq data from 275 Cerebellum (CBE) and 276 Temporal cortex (TCX) samples.
-  - The Religious Orders Study and Memory and Aging Project ([[https://www.synapse.org/#!Synapse:syn3219045|ROSMAP]]) is the **richest**  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 [[https://www.radc.rush.edu/docs/omics.htm|documented]].+  - The Religious Orders Study and Memory and Aging Project ([[https://www.synapse.org/#!Synapse:syn3219045|ROSMAP]]) is the **richest**  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 [[https://www.radc.rush.edu/docs/omics.htm|documented]], and was used to identify [[http://mostafavilab.stat.ubc.ca/xqtl/|xQTL]] by Philip De Jager. 
 +  - Mathys, Hansruedi, et al. "**Single-cell**  transcriptomic analysis of Alzheimer’s disease." Nature ([[https://www.nature.com/articles/s41586-019-1195-2|2019]]). \\  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 [[:plan|]]. Habil's [[https://docs.google.com/presentation/d/1u2rv9FExW44JfJsqPjenJcCsCFnOSUbJUxQwalviNHk/edit#slide=id.p|presentation]] in Biggs journal club on 2 July 2019. 
 +  - The Brain eQTL Almanac ([[http://braineac.org/|Braineac]]) 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." 
 +  - Omics data were generated in [[https://www.neurodegenerationresearch.eu/it/cohort/the-rhineland-study/|Rhineland]] Study including DNA methylation from ~2K blood samples. Aslam Imtiaz presented these data in the NeuroCHARGE call on 2019-11-07.
  
  
 ===== Collaborators ===== ===== Collaborators =====
  
-Dr. [[http://gsbs.uthscsa.edu/faculty/sudha-seshadri-m.d.-dm|Sudha Seshadri]], the Founding Director of The Glenn [[https://biggsinstitute.org/|Biggs Institute]] for Alzheimer's & Neurodegenerative Diseases, and [[https://biggsinstitute.org/team-member/claudia-l-satizabal-phd/|Dr. Claudia Satizabal]].+Dr. [[http://gsbs.uthscsa.edu/faculty/sudha-seshadri-m.d.-dm|Sudha Seshadri]], the Founding Director of The Glenn [[https://biggsinstitute.org/|Biggs Institute]] for Alzheimer's & Neurodegenerative Diseases, [[https://biggsinstitute.org/team-member/claudia-l-satizabal-phd/|Dr. Claudia Satizabal]], Dr. [[http://runewarkbiology.rutgers.edu/Dobrowolski Lab/index.html|Radek Dobrowolski]], and Dr. [[https://biggsinstitute.org/team-member/qitao-ran/|Qitao Ran]]. 
  
 ===== Subprojects ===== ===== Subprojects =====
  
-Network analysis on [[https://docs.google.com/document/d/1K89u6OubQUXAycg6JaEqzNgv18ybRy4QWcG_3UVQBuQ/edit|proteome]] data of Fremingham cohort+  - Network analysis on [[https://docs.google.com/document/d/1K89u6OubQUXAycg6JaEqzNgv18ybRy4QWcG_3UVQBuQ/edit|proteome]] data of Fremingham cohort
 +  - [[https://docs.google.com/presentation/d/1gCs39bst5xqxbpLNybRkJg1hUxxWCspmhlvKfdjtTsw/edit?ts=5d41b329#slide=id.g5e1f444b4f_0_0|DE]] 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. 
  
 ===== Related work ===== ===== Related work =====
  
-  - An interactive timeline of Alzheimer's disease by [[https://www.alzforum.org/timeline/alzheimers-disease#2010|AlzForum]]. +  - An interactive **timeline**  of Alzheimer's disease by [[https://www.alzforum.org/timeline/alzheimers-disease#2010|AlzForum]]. 
-  - MathysHansruedi, et al. "Single-cell transcriptomic analysis of Alzheimer’s disease." Nature ([[https://www.nature.com/articles/s41586-019-1195-2|2019]]): 1\\  Radek's summary: "Showing single cell transcriptomic analysis on brain tissues from ~50 patients with Alzheimer'disease. Subpopulations of glia and neurons expressed different gene signatures associated with ADThese enormous cataloging data may help to further pinpoint pathways associated with AD.", and his {{:wiki:img_20190516_162440263.jpg?linkonly|plan}}.+  - SatizabalClaudia L., et al. "Genetic architecture of subcortical brain structures in over 40,000 individuals worldwide." [[https://www.biorxiv.org/content/10.1101/173831v1.full|bioRxiv]] (2017): 173831. \\  They identified a set of genes that is "significantly enriched for //Drosophila//  orthologs associated with neurodevelopmental phenotypes"
 +  - Yamazaki, Yu., et al. "Apolipoprotein E and Alzheimer disease: pathobiology and targeting strategies." [[https://www.nature.com/articles/s41582-019-0228-7|Nat Rev Neurol ]](2019): 501–518. 
 +  - Ferreira, Daniel., et al. Biological subtypes of Alzheimer disease: A systematic review and meta-analysis [[https://n.neurology.org/content/neurology/early/2020/02/11/WNL.0000000000009058.full.pdf|Neurology]] (2020):94:1-13. 
 +  - Sey, Nancy YA, et al. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. [[https://www.nature.com/articles/s41593-020-0603-0|Nature Neuroscience]], 2020.