Differentially expressed genes from RPE compared to Normal Retina
Description:
Transcriptome profiling from macular retina and RPE/choroid samples from 27 unrelated eye tissue donors, was performed using RNA-sequencing. Human donor eye collection were obtained from Utah Lions Eye Bank within a 6-hour post-mortem interval and donors aged 60-90 years. Sample types were Normal Retina, Intermediate AMD Retina, Neovascular AMD Retina, Normal macular retina pigment epithelium (RPE), Intermediate AMD RPE, and Neovascular AMD RPE. Age Related Macular Degeneration (AMD) phenotyping was determined using the Age-Related Eye Disease Study (AREDS) severity grading scale, where AREDS category 0/1 was considered normal, AREDS category 3 intermediate AMD, and AREDS category 4b neovascular AMD. Samples from Normal RPE were compared to Normal Retina, and are presented with fold change > 1.5 and and P < 0.05. This gene set was annotated from the Supplementry Table of BioRxiv pre-print paper ‘Patterns of gene expression and allele-specific expression vary among macular tissues and clinical stages of Age-related Macular Degeneration’ by Zhang et.al (2022) doi: https://doi.org/10.1101/2022.12.19.521092
Data from GEO GSE194368 and analyzed using GEO2R, only top gene shown. Authors identified transcriptional adaptations of GR signaling in the amygdala of humans with OUD. Thus, GRs, their coregulators and downstream systems may represent viable therapeutic targets to treat the “stress side” of OUD.
Authors:
Stephanie A Carmack, Janaina C M Vendruscolo, M Adrienne McGinn, Jorge Miranda-Barrientos, Vez Repunte-Canonigo, Gabriel D Bosse, Daniele Mercatelli, Federico M Giorgi, Yu Fu, Anthony J Hinrich, Francine M Jodelka, Karen Ling, Robert O Messing, Randall T Peterson, Frank Rigo, Scott Edwards, Pietro P Sanna, Marisela Morales, Michelle L Hastings, George F Koob, Leandro F Vendruscolo
Data from GEO GSE194368 and analyzed using GEO2R, only top gene shown. Authors identified transcriptional adaptations of GR signaling in the amygdala of humans with OUD. Thus, GRs, their coregulators and downstream systems may represent viable therapeutic targets to treat the “stress side” of OUD.
Authors:
Stephanie A Carmack, Janaina C M Vendruscolo, M Adrienne McGinn, Jorge Miranda-Barrientos, Vez Repunte-Canonigo, Gabriel D Bosse, Daniele Mercatelli, Federico M Giorgi, Yu Fu, Anthony J Hinrich, Francine M Jodelka, Karen Ling, Robert O Messing, Randall T Peterson, Frank Rigo, Scott Edwards, Pietro P Sanna, Marisela Morales, Michelle L Hastings, George F Koob, Leandro F Vendruscolo
The dataset used in this study (Bulk RNA-Seq) was previously published and can be found at NCBI GEO (GSE182321), this analysis was conducted by GEO2R to compare control and OUD samples, only top differentially expressed genes are reported. To understand mechanisms and identify potential targets for intervention in the current crisis of opioid use disorder (OUD), postmortem brains represent an under-utilized resource. To refine previously reported gene signatures of neurobiological alterations in OUD from the dorsolateral prefrontal cortex (Brodmann Area 9, BA9), we explored the role of microRNAs (miRNA) as powerful epigenetic regulators of gene function.
The dataset used in this study (Bulk RNA-Seq) was previously published and can be found at NCBI GEO (GSE182321), this analysis was conducted by GEO2R to compare control and OUD samples, only top differentially expressed genes are reported. To understand mechanisms and identify potential targets for intervention in the current crisis of opioid use disorder (OUD), postmortem brains represent an under-utilized resource. To refine previously reported gene signatures of neurobiological alterations in OUD from the dorsolateral prefrontal cortex (Brodmann Area 9, BA9), we explored the role of microRNAs (miRNA) as powerful epigenetic regulators of gene function.
Transcriptional alterations in dorsolateral prefrontal cortex and nucleus accumbens implicate neuroinflammation and synaptic remodeling in opioid use disorder. Transcriptomic profile of 20 control subjects and 20 OUD subjects in brain region DLPFC and NAC. Analyzed using GEO2R (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE174409) separately for each brain region, comparing OUD and control samples.
Authors:
Xiangning Xue, Wei Zong, Jill R Glausier, Sam-Moon Kim, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Marianne L Seney, Ryan W Logan
Transcriptional alterations in dorsolateral prefrontal cortex and nucleus accumbens implicate neuroinflammation and synaptic remodeling in opioid use disorder. Transcriptomic profile of 20 control subjects and 20 OUD subjects in brain region DLPFC and NAC. Analyzed using GEO2R (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE174409) separately for each brain region, comparing OUD and control samples.
Authors:
Xiangning Xue, Wei Zong, Jill R Glausier, Sam-Moon Kim, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Marianne L Seney, Ryan W Logan
Transcriptional alterations in dorsolateral prefrontal cortex and nucleus accumbens implicate neuroinflammation and synaptic remodeling in opioid use disorder. Transcriptomic profile of 20 control subjects and 20 OUD subjects in brain region DLPFC and NAC. Analyzed using GEO2R (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE174409) separately for each brain region, comparing OUD and control samples.
Authors:
Xiangning Xue, Wei Zong, Jill R Glausier, Sam-Moon Kim, Micah A Shelton, BaDoi N Phan, Chaitanya Srinivasan, Andreas R Pfenning, George C Tseng, David A Lewis, Marianne L Seney, Ryan W Logan
Postmortem tissue samples of the dorsolateral prefrontal cortex (DLPFC) from 153 deceased individuals (Mage = 35.4; 62% male; 77% European ancestry). Study groups included 72 brain samples from individuals who died of acute opioid intoxication, 53 psychiatric controls, and 28 normal controls. Whole transcriptome RNA-sequencing was used to generate exon counts, and differential expression was tested using limma-voom. Analyses were adjusted for relevant sociodemographic characteristics, technical covariates, and cryptic relatedness using quality surrogate variables. Weighted correlation network analysis and gene set enrichment analyses also were conducted.
Authors:
David W Sosnowski, Andrew E Jaffe, Ran Tao, Amy Deep-Soboslay, Chang Shu, Sarven Sabunciyan, Joel E Kleinman, Thomas M Hyde, Brion S Maher
Postmortem tissue samples of the dorsolateral prefrontal cortex (DLPFC) from 153 deceased individuals (Mage = 35.4; 62% male; 77% European ancestry). Study groups included 72 brain samples from individuals who died of acute opioid intoxication, 53 psychiatric controls, and 28 normal controls. Whole transcriptome RNA-sequencing was used to generate exon counts, and differential expression was tested using limma-voom. Analyses were adjusted for relevant sociodemographic characteristics, technical covariates, and cryptic relatedness using quality surrogate variables. Weighted correlation network analysis and gene set enrichment analyses also were conducted.
Authors:
David W Sosnowski, Andrew E Jaffe, Ran Tao, Amy Deep-Soboslay, Chang Shu, Sarven Sabunciyan, Joel E Kleinman, Thomas M Hyde, Brion S Maher
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Corradin et al. 2022_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Corradin et al. 2022_qvalue
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Mendez et al 2021_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Seney et al 2021_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Seney et al 2021_qvalue
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Sosnowski et al 2022_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Sosnowski et al 2022_qvalue
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
QTL for METH responses for body temperature on Chr19 at Lpc1 (23.27 Mbp , Build 37)
Description:
METH responses for body temperature spans 0.00 - 48.27 Mbp (NCBI Build 37) on Chr19. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for alcohol preference locus on Chr19 at D19Mit46 (29.54 Mbp , Build 37)
Description:
alcohol preference locus spans 4.54 - 54.54 Mbp (NCBI Build 37) on Chr19. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for alcohol preference locus on Chr19 at D19Mit46 (29.54 Mbp , Build 37)
Description:
alcohol preference locus spans 4.54 - 54.54 Mbp (NCBI Build 37) on Chr19. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
Genes associated with Homo sapiens that interact with the MeSH term 'Demecolcine' (D003703). Incorporates data from 3 publications curated by the Comparative Toxicogenomics Database (CTD). ODE Gene scores represent number of supporting publications per gene.
Genes associated with Homo sapiens that interact with the MeSH term 'Oxygen' (D010100). Incorporates data from 8 publications curated by the Comparative Toxicogenomics Database (CTD). ODE Gene scores represent number of supporting publications per gene.
Genes associated with Homo sapiens that interact with the MeSH term 'Formaldehyde' (D005557). Incorporates data from 2 publications curated by the Comparative Toxicogenomics Database (CTD). ODE Gene scores represent number of supporting publications per gene.
Ethanol induced LORR Chr# 19 rs6194426 (50203520) with right flanking marker rs13483643(45386221) and left marker rs13483682 (55236132). This was mapped in 300 + (b6x129)F2 mice.
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