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multiomics_analysis_for_dementia [2019/07/03 01:34] – [Related work] adminmultiomics_analysis_for_dementia [2022/05/17 18:20] (current) – [Related work] admin
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 Determine biomarkers for Alzheimer's and other neurodegenerative diseases using comprehensive analysis of multi-omics data including genomics, epigenomics, metabolomics, proteomics, etc. 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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 ===== 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. On 2021-04-23, {{:fhs_multiomics_meeting_msevilla_april21.pdf|Magdalena}}  Sevilla presented a collection of FHS, MESA, and WHI omics datasets and some statistical methods for analyzing them.
   - 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.
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       - 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]], and was used to identify [[http://mostafavilab.stat.ubc.ca/xqtl/|xQTL]] by Philip De Jager.   - 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.
 +  - [[https://bmbls.bmi.osumc.edu/scread/|scREAD]]: A Single-Cell RNA-Seq Database for Alzheimer’s Disease ([[https://www.cell.com/iscience/pdf/S2589-0042(20)30966-4.pdf|pdf]]). 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.
 +  - [[https://www.nature.com/articles/s41586-021-03910-8|Bhaduri]] 's 2021 snRNASeq of the developing human brain.
  
  
 ===== 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, [[https://biggsinstitute.org/team-member/claudia-l-satizabal-phd/|Dr. Claudia Satizabal]], and Dr. [[http://runewarkbiology.rutgers.edu/Dobrowolski Lab/index.html|Radek Dobrowolski]].+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]], Dr. [[https://biggsinstitute.org/team-member/qitao-ran/|Qitao Ran]], and Dr. [[https://school.wakehealth.edu/Faculty/O/Miranda-E-Orr|Miranda Orr]] from Wake Forest University.
  
  
 ===== 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. 
 +  - Identify senescent cells and their characteristics in human brain. 
 +  - Assess the effect of lowering expression of CD33 in microglia on AD phenotypes through [[https://docs.google.com/document/d/1-SStE--v9-ATh1Bi9zqEXaTDD21kX2KjyQ1J6c0Ww74/edit|analysis]] of single cell RNA-Seq data. 
  
 ===== 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]]). \\  Radek's summary: "Showing 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 ADThese enormous cataloging data may help to further pinpoint pathways associated with AD.", and his {{:wiki:img_20190516_162440263.jpg?linkonly|plan}}. Habil'[[https://docs.google.com/presentation/d/1u2rv9FExW44JfJsqPjenJcCsCFnOSUbJUxQwalviNHk/edit#slide=id.p|presentation]] in Biggs journal club on 2 July 2019. +  - [[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|NAPA]] at 10: A decade of Alzheimer’s and related dementias research progress2022. 
-  - 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".+  - Satizabal, Claudia L., et al. "Genetic architecture of subcortical brain structures in 38,851 individuals." //[[https://www.nature.com/articles/s41588-019-0511-y|Nature genetics]]// 51.11 (2019): 1624-1636. \\ 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 diseasepathobiology and targeting strategies.[[https://www.nature.com/articles/s41582-019-0228-7|Nat Rev Neurol ]](2019): 501–518
 +  - FerreiraDaniel., 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. 
 +  - Borghesan, M., et al. "A **Senescence**-Centric View of Aging: Implications for Longevity and Disease." [[https://www.sciencedirect.com/science/article/abs/pii/S0962892420301434|Trends in Cell Biology]] (2020). The review paper suggested by Christi.