Postmortem human brain tissue from the caudate nucleus region of a total of 48 individuals with Alcohol Use Disorder (AUD) and 51 control individuals were taken and RNA extracted from frozen tissue. Sequencing was carried out using the NovaSeq 6000 (Illumina) platform, and gene expression analysis was carried out with respect to AUD and control samples. Gene symbols from Entrez ids are used and Logbase2 FC as provided by the authors are annotated.
Authors:
Lea Zillich, Eric Poisel, Josef Frank, Jerome C Foo, Marion M Friske, Fabian Streit, Lea Sirignano, Stefanie Heilmann-Heimbach, André Heimbach, Per Hoffmann, Franziska Degenhardt, Anita C Hansson, Georgy Bakalkin, Markus M Nöthen, Marcella Rietschel, Rainer Spanagel, Stephanie H Witt
Postmortem human brain tissue from the putamen region of a total of 48 individuals with Alcohol Use Disorder (AUD) and 51 control individuals were taken and RNA extracted from frozen tissue. Sequencing was carried out using the NovaSeq 6000 (Illumina) platform, and gene expression analysis was carried out with respect to AUD and control samples. Gene symbols from Entrez ids are used and Logbase2 FC as provided by the authors are annotated.
Authors:
Lea Zillich, Eric Poisel, Josef Frank, Jerome C Foo, Marion M Friske, Fabian Streit, Lea Sirignano, Stefanie Heilmann-Heimbach, André Heimbach, Per Hoffmann, Franziska Degenhardt, Anita C Hansson, Georgy Bakalkin, Markus M Nöthen, Marcella Rietschel, Rainer Spanagel, Stephanie H Witt
Postmortem human brain tissue from the ventral striatum from postmortem human brain tissue with Alcohol Use Disorder (AUD) region of a total of 48 individuals with Alcohol Use Disorder (AUD) and 51 control individuals were taken and RNA extracted from frozen tissue. Sequencing was carried out using the NovaSeq 6000 (Illumina) platform, and gene expression analysis was carried out with respect to AUD and control samples. Gene symbols from Entrez ids are used and Logbase2 FC as provided by the authors are annotated.
Authors:
Lea Zillich, Eric Poisel, Josef Frank, Jerome C Foo, Marion M Friske, Fabian Streit, Lea Sirignano, Stefanie Heilmann-Heimbach, André Heimbach, Per Hoffmann, Franziska Degenhardt, Anita C Hansson, Georgy Bakalkin, Markus M Nöthen, Marcella Rietschel, Rainer Spanagel, Stephanie H Witt
Dysregulation of NRSF/REST via EHMT1 is associated with psychiatric disorders and Kleefstra syndrome, Z scores
Description:
EHMT1 is an epigenetic repressor that is causal for Kleefstra Syndrome (KS), a neurodevelopmental disorder (NDD) leading to intelectual disability, and is associated with schizophrenia. Here, the researchers aim to show we show that reduced EHMT1 activity decreases NRSF/REST protein leading to abnormal neuronal gene expression and progression of neurodevelopment in human iPSC. Five induced pluripotent stem cell samples (from fibroblasts of adult, male, skin) were used. The stem cells were gifted from: Lieber Institute for Brain Development, Johns Hopkins Medical Campus. Total RNA extracted from a control hiPSC line and control cells treated for 72h with various concentrations of UNC0638 i.e 50, 100, 200 or 250nM as a model for Kleefstra syndrome. Polyadenylated adaptors were ligated to the 3′-end, 5′-adaptors were then ligated, and the resulting RNAs were reverse transcribed to generate cDNA that can be amplified by PCR. The amplified product was run on low range ultra agarose in TBE buffer and a size-selection was performed to ensure that the cDNA used for sequencing primarily contains miRNAs rather than other RNA contaminants. Expression values were calculated by the method detailed in 'HBA-DEALS: accurate and simultaneous identification of differential expression and splicing using hierarchical Bayesian analysis' (Genome Biol. 2020, PMID: 32660516), and Z scores calculated. Genes were annotated as Ensembl gene ids. SRA Study id ERP130338.
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
RNA sequencing of a limited number of archived patients' specimens with extended opioid exposure or non-opioid exposure was performed. Immune infiltration and changes in the microenvironment were evaluated using CIBERSORT.
Authors:
Mamatha Garige, Sarah Poncet, Alexis Norris, Chao-Kai Chou, Wells W Wu, Rong-Fong Shen, Jacob W Greenberg, Louis Spencer Krane, Carole Sourbier
RNA sequencing of a limited number of archived patients' specimens with extended opioid exposure or non-opioid exposure was performed. Immune infiltration and changes in the microenvironment were evaluated using CIBERSORT.
Authors:
Mamatha Garige, Sarah Poncet, Alexis Norris, Chao-Kai Chou, Wells W Wu, Rong-Fong Shen, Jacob W Greenberg, Louis Spencer Krane, Carole Sourbier
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
Differential gene expression between CS13 and CS22 - Log2FC
Description:
Human craniofacial tissues were collected from the Joint MRC/Wellcome Trust Human Developmental Biology (HDBR). Donations of tissue to HDBR are made under-informed ethical consent with Research Tissue Bank ethical approval by women undergoing termination of pregnancy. Gene expression profiles were generated from multiple biological replicates of primary craniofacial (CF) tissue from Carnegie Stages (CS) of the embryonic period, CS13, CS14, CS17, CS17, and CS22. Here the differential expression comparison between CS13 and CS22 is shown. Gene expressions values with log to the base 2, FC are presented with P-Adj <0.05. UBERON:0015789, cranial or facial muscle.
Authors:
Tara N Yankee, Sungryong Oh, Emma Wentworth Winchester, Andrea Wilderman, Kelsey Robinson, Tia Gordon, Jill A Rosenfeld, Jennifer VanOudenhove, Daryl A Scott, Elizabeth J Leslie, Justin Cotney
Differential gene expression between CS13 and CS22 - Adj-P value
Description:
Human craniofacial tissues were collected from the Joint MRC/Wellcome Trust Human Developmental Biology (HDBR). Donations of tissue to HDBR are made under-informed ethical consent with Research Tissue Bank ethical approval by women undergoing termination of pregnancy. Gene expression profiles were generated from multiple biological replicates of primary craniofacial (CF) tissue from Carnegie Stages (CS) of the embryonic period, CS13, CS14, CS17, CS17 and CS22. Here the differential expression comparison between CS13 and CS22 is shown. Gene expressions values, Ensembl Gene ids and the corresponding Adjusted P value are presented. UBERON:0015789, cranial or facial muscle.
Authors:
Tara N Yankee, Sungryong Oh, Emma Wentworth Winchester, Andrea Wilderman, Kelsey Robinson, Tia Gordon, Jill A Rosenfeld, Jennifer VanOudenhove, Daryl A Scott, Elizabeth J Leslie, Justin Cotney
Differential gene expression between CS14 and CS22 - Log2FC
Description:
Human craniofacial tissues were collected from the Joint MRC/Wellcome Trust Human Developmental Biology (HDBR). Donations of tissue to HDBR are made under-informed ethical consent with Research Tissue Bank ethical approval by women undergoing termination of pregnancy. Gene expression profiles were generated from multiple biological replicates of primary craniofacial (CF) tissue from Carnegie Stages (CS) of the embryonic period, CS13, CS14, CS17, CS17, and CS22. Here the differential expression comparison between CS14 and CS22 is shown. Gene expressions values with log to the base 2, FC are presented with P-Adj <0.05. UBERON:0015789, cranial or facial muscle.
Authors:
Tara N Yankee, Sungryong Oh, Emma Wentworth Winchester, Andrea Wilderman, Kelsey Robinson, Tia Gordon, Jill A Rosenfeld, Jennifer VanOudenhove, Daryl A Scott, Elizabeth J Leslie, Justin Cotney
Differential gene expression between CS14 and CS22 - Adj-P value
Description:
Human craniofacial tissues were collected from the Joint MRC/Wellcome Trust Human Developmental Biology (HDBR). Donations of tissue to HDBR are made under-informed ethical consent with Research Tissue Bank ethical approval by women undergoing termination of pregnancy. Gene expression profiles were generated from multiple biological replicates of primary craniofacial (CF) tissue from Carnegie Stages (CS) of the embryonic period, CS13, CS14, CS17, CS17 and CS22. Here the differential expression comparison between CS14 and CS22 is shown. Gene expressions values, Ensembl Gene ids and the corresponding Adjusted P value are presented. UBERON:0015789, cranial or facial muscle.
Authors:
Tara N Yankee, Sungryong Oh, Emma Wentworth Winchester, Andrea Wilderman, Kelsey Robinson, Tia Gordon, Jill A Rosenfeld, Jennifer VanOudenhove, Daryl A Scott, Elizabeth J Leslie, Justin Cotney
DEG methadone human cortical organoids cell line A_pvalue
Description:
Human induced pluripotent stem cell (iPSC) lines, A and B, derived from two healthy adult male individuals, were used to generate hCOs for RNA-sequencing. Methodone treatment began on Day 9 of organoid culture, the first day of the neural proliferation stage, and concluded at Day 60. Nuclease-free water was used as a vehicular control. Cortical organoids were collected 2 months (60 days) after initiating organoid culture. Each well of hCOs (15–20 organoids) was a separate biological replicate for a given treatment condition (i.e., treated or untreated). RNA was extracted from frozen organoid pellets using the Direct-Zol Miniprep Plus Kit (Zymo, Irvine, CA) according to the manufacturer’s instructions. Samples were multiplexed and sequenced on the Illumina NovaSeq 6000 S4 to produce approximately 100 million, 100 base pair, paired end reads per sample. 3 control and 3 methadone-treated samples were sequenced from cell line A, and 4 control and 4 treated samples from cell line B. Raw fastq file quality assessment and read alignment to the hg19 genome (GRCh37, RefSeq GCF_000001405.13) were performed. Significantly differentially expressed genes (DEGs) were selected based on the confident effect size of their log2(Fold Change) values at FDR<0.05. Genes presented are without cutoffs and were obtained using the GEO2R tool by GW curators (GEO accession: GSE210682).
Authors:
Ila Dwivedi, Andrew B Caldwell, Dan Zhou, Wei Wu, Shankar Subramaniam, Gabriel G Haddad
DEG methadone human cortical organoids cell line A_qvalue
Description:
Human induced pluripotent stem cell (iPSC) lines, A and B, derived from two healthy adult male individuals, were used to generate hCOs for RNA-sequencing. Methodone treatment began on Day 9 of organoid culture, the first day of the neural proliferation stage, and concluded at Day 60. Nuclease-free water was used as a vehicular control. Cortical organoids were collected 2 months (60 days) after initiating organoid culture. Each well of hCOs (15–20 organoids) was a separate biological replicate for a given treatment condition (i.e., treated or untreated). RNA was extracted from frozen organoid pellets using the Direct-Zol Miniprep Plus Kit (Zymo, Irvine, CA) according to the manufacturer’s instructions. Samples were multiplexed and sequenced on the Illumina NovaSeq 6000 S4 to produce approximately 100 million, 100 base pair, paired end reads per sample. 3 control and 3 methadone-treated samples were sequenced from cell line A, and 4 control and 4 treated samples from cell line B. Raw fastq file quality assessment and read alignment to the hg19 genome (GRCh37, RefSeq GCF_000001405.13) were performed. Significantly differentially expressed genes (DEGs) were selected based on the confident effect size of their log2(Fold Change) values at FDR<0.05. Genes presented are without cutoffs and were obtained using the GEO2R tool by GW curators (GEO accession: GSE210682).
Authors:
Ila Dwivedi, Andrew B Caldwell, Dan Zhou, Wei Wu, Shankar Subramaniam, Gabriel G Haddad
DEG methadone human cortical organoids cell line B_pvalue
Description:
Human induced pluripotent stem cell (iPSC) lines, A and B, derived from two healthy adult male individuals, were used to generate hCOs for RNA-sequencing. Methodone treatment began on Day 9 of organoid culture, the first day of the neural proliferation stage, and concluded at Day 60. Nuclease-free water was used as a vehicular control. Cortical organoids were collected 2 months (60 days) after initiating organoid culture. Each well of hCOs (15–20 organoids) was a separate biological replicate for a given treatment condition (i.e., treated or untreated). RNA was extracted from frozen organoid pellets using the Direct-Zol Miniprep Plus Kit (Zymo, Irvine, CA) according to the manufacturer’s instructions. Samples were multiplexed and sequenced on the Illumina NovaSeq 6000 S4 to produce approximately 100 million, 100 base pair, paired end reads per sample. 3 control and 3 methadone-treated samples were sequenced from cell line A, and 4 control and 4 treated samples from cell line B. Raw fastq file quality assessment and read alignment to the hg19 genome (GRCh37, RefSeq GCF_000001405.13) were performed. Significantly differentially expressed genes (DEGs) were selected based on the confident effect size of their log2(Fold Change) values at FDR<0.05. Genes presented are without cutoffs and were obtained using the GEO2R tool by GW curators (GEO accession: GSE210682).
Authors:
Ila Dwivedi, Andrew B Caldwell, Dan Zhou, Wei Wu, Shankar Subramaniam, Gabriel G Haddad
DEG methadone human cortical organoids cell line B_qvalue
Description:
Human induced pluripotent stem cell (iPSC) lines, A and B, derived from two healthy adult male individuals, were used to generate hCOs for RNA-sequencing. Methodone treatment began on Day 9 of organoid culture, the first day of the neural proliferation stage, and concluded at Day 60. Nuclease-free water was used as a vehicular control. Cortical organoids were collected 2 months (60 days) after initiating organoid culture. Each well of hCOs (15–20 organoids) was a separate biological replicate for a given treatment condition (i.e., treated or untreated). RNA was extracted from frozen organoid pellets using the Direct-Zol Miniprep Plus Kit (Zymo, Irvine, CA) according to the manufacturer’s instructions. Samples were multiplexed and sequenced on the Illumina NovaSeq 6000 S4 to produce approximately 100 million, 100 base pair, paired end reads per sample. 3 control and 3 methadone-treated samples were sequenced from cell line A, and 4 control and 4 treated samples from cell line B. Raw fastq file quality assessment and read alignment to the hg19 genome (GRCh37, RefSeq GCF_000001405.13) were performed. Significantly differentially expressed genes (DEGs) were selected based on the confident effect size of their log2(Fold Change) values at FDR<0.05. Genes presented are without cutoffs and were obtained using the GEO2R tool by GW curators (GEO accession: GSE210682).
Authors:
Ila Dwivedi, Andrew B Caldwell, Dan Zhou, Wei Wu, Shankar Subramaniam, Gabriel G Haddad
DEG HepG2.2.15 liver cells fentanyl vs control_pvalue
Description:
Differential mRNA expression of liver cells exposed to fentanyl vs control in human liver cells. The Huh7.5JFH1 and HepG2.2.15 hepatocyte cell lines were seeded at 500,000 cells per well. Fentanyl or carfentanil was added to culture medium after 24 hours. After 24 hours of incubation with drug, hepatitis C virus (HCV) core (ng/mL), or hepatitis B surface antigen (HBsAg) (ng/mL) was quantified in culture supernatants. Differential expression was assessed using moderated t-tests with a cutoff of p < 0.05 and fold change > 1.25. Transcripts meeting significance criteria were submitted to ToppGene and ToppCluster for ontological analyses. RNAseq data are available through GEO using accession number GSE167922. Differential expression of mRNA in fentanyl treated vs control cells was analyzed for each cell line using the GEO2R tool.
Authors:
Ling Kong, Rebekah Karns, Mohamed Tarek M Shata, Jennifer L Brown, Michael S Lyons, Kenneth E Sherman, Jason T Blackard
"We amassed a set of phenotype-specific GWAS summary statistics for different externalizing phenotypes, either by collecting existing results or by performing GWAS in UK Biobank (UKB) (Supplementary Information section 2). The multivariate method “genomic structural equation modelling” (Genomic SEM) was applied on a subset of the summary statistics (N = 53,293–1,251,809) deemed adequately heritable and statistically powered, in order to estimate a series of model specifications representing
different genetic factor structures (Supplementary Information section 3). The best-fitting and most parsimonious solution (“the preferred model specification”) specified a
single common genetic factor with seven indicator phenotypes (which we hereafter refer to as “the latent genetic externalizing factor”, or simply, “the externalizing factor”). The 7 phenotypes eventually used to estimate the latent genetic externalizing factor were (1) ADHD, (2) age at first sexual intercourse (FSEX), (3) problematic alcohol use (ALCP), (4) lifetime cannabis use (CANN), (5) lifetime smoking initiation (SMOK), (6) general risk tolerance (RISK), and (7) number of sexual partners (NSEX). We used an extension of MAGMA v1.08, “Hi-C coupled MAGMA” or “H-MAGMA” (version June 14, 2019), to assign non-coding (intergenic and intronic) SNPs to cognate genes based on their chromatin interactions. Exonic and promoter SNPs were assigned to genes based on physical position. We used four Hi-C datasets derived from adult brain, fetal brain, and iPSC derived neurons and astrocytes. We evaluated Bonferroni corrected P-value thresholds, adjusted for multiple testing within each analysis (one-sided P < 9.84×10–7). Displaying genes with P value less than 1E–5. From supplementary table 17."
Authors:
Richard Karlsson Linnér, Travis T Mallard, Peter B Barr, Sandra Sanchez-Roige, James W Madole, Morgan N Driver, Holly E Poore, Ronald de Vlaming, Andrew D Grotzinger, Jorim J Tielbeek, Emma C Johnson, Mengzhen Liu, Sara Brin Rosenthal, Trey Ideker, Hang Zhou, Rachel L Kember, Joëlle A Pasman, Karin J H Verweij, Dajiang J Liu, Scott Vrieze, , Henry R Kranzler, Joel Gelernter, Kathleen Mullan Harris, Elliot M Tucker-Drob, Irwin D Waldman, Abraham A Palmer, K Paige Harden, Philipp D Koellinger, Danielle M Dick
"We amassed a set of phenotype-specific GWAS summary statistics for different externalizing phenotypes, either by collecting existing results or by performing GWAS in UK Biobank (UKB) (Supplementary Information section 2). The multivariate method “genomic structural equation modelling” (Genomic SEM) was applied on a subset of the summary statistics (N = 53,293–1,251,809) deemed adequately heritable and statistically powered, in order to estimate a series of model specifications representing different genetic factor structures (Supplementary Information section 3). The best-fitting and most parsimonious solution (“the preferred model specification”) specified a single common genetic factor with seven indicator phenotypes (which we hereafter refer to as “the latent genetic externalizing factor”, or simply, “the externalizing factor”). The 7 phenotypes eventually used to estimate the latent genetic externalizing factor were (1) ADHD, (2) age at first sexual intercourse (FSEX), (3) problematic alcohol use (ALCP), (4) lifetime cannabis use (CANN), (5) lifetime smoking initiation (SMOK), (6) general risk tolerance (RISK), and (7) number of sexual partners (NSEX). We used an extension of MAGMA v1.08, “Hi-C coupled MAGMA” or “H-MAGMA” (version June 14, 2019), to assign non-coding (intergenic and intronic) SNPs to cognate genes based on their chromatin interactions. Exonic and promoter SNPs were assigned to genes based on physical position. We used four Hi-C datasets derived from adult brain, fetal brain, and iPSC derived neurons and astrocytes. We evaluated Bonferroni corrected P-value thresholds, adjusted for multiple testing within each analysis (one-sided P < 9.84×10–7). Displaying genes with P value less than 1E–5. From supplementary table 18."
Authors:
Richard Karlsson Linnér, Travis T Mallard, Peter B Barr, Sandra Sanchez-Roige, James W Madole, Morgan N Driver, Holly E Poore, Ronald de Vlaming, Andrew D Grotzinger, Jorim J Tielbeek, Emma C Johnson, Mengzhen Liu, Sara Brin Rosenthal, Trey Ideker, Hang Zhou, Rachel L Kember, Joëlle A Pasman, Karin J H Verweij, Dajiang J Liu, Scott Vrieze, , Henry R Kranzler, Joel Gelernter, Kathleen Mullan Harris, Elliot M Tucker-Drob, Irwin D Waldman, Abraham A Palmer, K Paige Harden, Philipp D Koellinger, Danielle M Dick
H-MAGMA genes in iPSC neurons from EXT GWAS_pvalue
Description:
"We amassed a set of phenotype-specific GWAS summary statistics for different externalizing phenotypes, either by collecting existing results or by performing GWAS in UK Biobank (UKB) (Supplementary Information section 2). The multivariate method “genomic structural equation modelling” (Genomic SEM) was applied on a subset of the summary statistics (N = 53,293–1,251,809) deemed adequately heritable and statistically powered, in order to estimate a series of model specifications representing
different genetic factor structures (Supplementary Information section 3). The best-fitting and most parsimonious solution (“the preferred model specification”) specified a
single common genetic factor with seven indicator phenotypes (which we hereafter refer to as “the latent genetic externalizing factor”, or simply, “the externalizing factor”). The 7 phenotypes eventually used to estimate the latent genetic externalizing factor were (1) ADHD, (2) age at first sexual intercourse (FSEX), (3) problematic alcohol use (ALCP), (4) lifetime cannabis use (CANN), (5) lifetime smoking initiation (SMOK), (6) general risk tolerance (RISK), and (7) number of sexual partners (NSEX). We used an extension of MAGMA v1.08, “Hi-C coupled MAGMA” or “H-MAGMA” (version June 14, 2019), to assign non-coding (intergenic and intronic) SNPs to cognate genes based on their chromatin interactions. Exonic and promoter SNPs were assigned to genes based on physical position. We used four Hi-C datasets derived from adult brain, fetal brain, and iPSC derived neurons and astrocytes. We evaluated Bonferroni corrected P-value thresholds, adjusted for multiple testing within each analysis (one-sided P < 9.84×10–7). Displaying genes with P value less than 1E–5. From supplementary table 19."
Authors:
Richard Karlsson Linnér, Travis T Mallard, Peter B Barr, Sandra Sanchez-Roige, James W Madole, Morgan N Driver, Holly E Poore, Ronald de Vlaming, Andrew D Grotzinger, Jorim J Tielbeek, Emma C Johnson, Mengzhen Liu, Sara Brin Rosenthal, Trey Ideker, Hang Zhou, Rachel L Kember, Joëlle A Pasman, Karin J H Verweij, Dajiang J Liu, Scott Vrieze, , Henry R Kranzler, Joel Gelernter, Kathleen Mullan Harris, Elliot M Tucker-Drob, Irwin D Waldman, Abraham A Palmer, K Paige Harden, Philipp D Koellinger, Danielle M Dick
GeneWeaver