<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Petyuk VA</submitter><funding>National Center for Research Resources</funding><funding>NIA NIH HHS</funding><funding>Medical Research Council</funding><funding>NIMH NIH HHS</funding><funding>National Institute for Health Research (NIHR)</funding><funding>NINDS NIH HHS</funding><funding>National Institutes of Health</funding><funding>NIH</funding><funding>National Institute of General Medical Sciences</funding><funding>NIGMS NIH HHS</funding><pagination>2721-2739</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6136080</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>141(9)</volume><pubmed_abstract>Our hypothesis is that changes in gene and protein expression are crucial to the development of late-onset Alzheimer&amp;rsquo;s disease. Previously we examined how DNA alleles control downstream expression of RNA transcripts and how those relationships are changed in late-onset Alzheimer&amp;rsquo;s disease. We have now examined how proteins are incorporated into networks in two separate series and evaluated our outputs in two different cell lines. Our pipeline included the following steps: (i) predicting expression quantitative trait loci; (ii) determining differential expression; (iii) analysing networks of transcript and peptide relationships; and (iv) validating effects in two separate cell lines. We performed all our analysis in two separate brain series to validate effects. Our two series i</pubmed_abstract><journal>Brain : a journal of neurology</journal><pubmed_title>The human brainome: network analysis identifies HSPA2 as a novel Alzheimer&amp;rsquo;s disease target.</pubmed_title><pmcid>PMC6136080</pmcid><funding_grant_id>P30 AG013846</funding_grant_id><funding_grant_id>P50 AG005128</funding_grant_id><funding_grant_id>P41GM103493</funding_grant_id><funding_grant_id>P30 AG053760</funding_grant_id><funding_grant_id>P50 AG005146</funding_grant_id><funding_grant_id>AG041232</funding_grant_id><funding_grant_id>P50 AG005681</funding_grant_id><funding_grant_id>P50 AG005144</funding_grant_id><funding_grant_id>G0502157</funding_grant_id><funding_grant_id>P41 GM103493</funding_grant_id><funding_grant_id>P30 AG019610</funding_grant_id><funding_grant_id>P41RR018522</funding_grant_id><funding_grant_id>G0900652</funding_grant_id><funding_grant_id>R01 AG041232</funding_grant_id><funding_grant_id>R01 AG034504</funding_grant_id><funding_grant_id>P50 AG005134</funding_grant_id><funding_grant_id>U01 AG016976</funding_grant_id><funding_grant_id>P50 AG005136</funding_grant_id><funding_grant_id>NF-SI-0611-10048</funding_grant_id><funding_grant_id>P30 AG010161</funding_grant_id><funding_grant_id>RF1 AG057457</funding_grant_id><funding_grant_id>P50-AG08671</funding_grant_id><funding_grant_id>RF1 AG015819</funding_grant_id><funding_grant_id>P50 MH060451</funding_grant_id><funding_grant_id>G1100540</funding_grant_id><funding_grant_id>G0400074</funding_grant_id><funding_grant_id>P50 NS039764</funding_grant_id><funding_grant_id>R01 AG017917</funding_grant_id><funding_grant_id>P50 AG016570</funding_grant_id><pubmed_authors>Lieberman AP</pubmed_authors><pubmed_authors>Beckmann ND</pubmed_authors><pubmed_authors>Smith RD</pubmed_authors><pubmed_authors>Andreev V</pubmed_authors><pubmed_authors>Lovestone S</pubmed_authors><pubmed_authors>Myers AJ</pubmed_authors><pubmed_authors>Navarro L</pubmed_authors><pubmed_authors>Xie F</pubmed_authors><pubmed_authors>Ferrer I</pubmed_authors><pubmed_authors>Piehowski PD</pubmed_authors><pubmed_authors>Wang S</pubmed_authors><pubmed_authors>Schadt E</pubmed_authors><pubmed_authors>Engel A</pubmed_authors><pubmed_authors>De Jager P</pubmed_authors><pubmed_authors>Sue LI</pubmed_authors><pubmed_authors>Hardy JA</pubmed_authors><pubmed_authors>Morris CM</pubmed_authors><pubmed_authors>Reiman EM</pubmed_authors><pubmed_authors>Henrion MYR</pubmed_authors><pubmed_authors>Ervin JF</pubmed_authors><pubmed_authors>Chang R</pubmed_authors><pubmed_authors>Ramirez-Restrepo M</pubmed_authors><pubmed_authors>McKeith IG</pubmed_authors><pubmed_authors>Perry RH</pubmed_authors><pubmed_authors>Serrano GE</pubmed_authors><pubmed_authors>Hulette CM</pubmed_authors><pubmed_authors>Clarke J</pubmed_authors><pubmed_authors>Petyuk VA</pubmed_authors><pubmed_authors>Schneider JA</pubmed_authors><pubmed_authors>Bennett DA</pubmed_authors><pubmed_authors>Zhu K</pubmed_authors><pubmed_authors>Guettoche T</pubmed_authors><pubmed_authors>Woltjer RL</pubmed_authors><pubmed_authors>Beach TG</pubmed_authors><pubmed_authors>Albin RL</pubmed_authors><pubmed_authors>Mash DC</pubmed_authors><pubmed_authors>Huentelman MJ</pubmed_authors></additional><is_claimable>false</is_claimable><name>The human brainome: network analysis identifies HSPA2 as a novel Alzheimer&amp;rsquo;s disease target.</name><description>Our hypothesis is that changes in gene and protein expression are crucial to the development of late-onset Alzheimer&amp;rsquo;s disease. Previously we examined how DNA alleles control downstream expression of RNA transcripts and how those relationships are changed in late-onset Alzheimer&amp;rsquo;s disease. We have now examined how proteins are incorporated into networks in two separate series and evaluated our outputs in two different cell lines. Our pipeline included the following steps: (i) predicting expression quantitative trait loci; (ii) determining differential expression; (iii) analysing networks of transcript and peptide relationships; and (iv) validating effects in two separate cell lines. We performed all our analysis in two separate brain series to validate effects. Our two series i</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Sep</publication><modification>2025-04-18T13:29:14.2Z</modification><creation>2019-03-26T23:56:53Z</creation></dates><accession>S-EPMC6136080</accession><cross_references><pubmed>30137212</pubmed><doi>10.1093/brain/awy215</doi></cross_references></HashMap>