scholarly journals Meta-analysis of transcriptomic data reveals clusters of consistently deregulated gene and disease ontologies in Down syndrome

2021 ◽  
Vol 17 (9) ◽  
pp. e1009317
Author(s):  
Ilario De Toma ◽  
Cesar Sierra ◽  
Mara Dierssen
Keyword(s):  
Down Syndrome ◽  
Differential Expression ◽  
Web Application ◽  
Meta Analysis ◽  
Chromosome 21 ◽  
Complex Disorders ◽  
Transcriptomic Data ◽  
Genome Wide ◽  
A Genome ◽  
The Impact

Trisomy of human chromosome 21 (HSA21) causes Down syndrome (DS). The trisomy does not simply result in the upregulation of HSA21--encoded genes but also leads to a genome-wide transcriptomic deregulation, which affect differently each tissue and cell type as a result of epigenetic mechanisms and protein-protein interactions. We performed a meta-analysis integrating the differential expression (DE) analyses of all publicly available transcriptomic datasets, both in human and mouse, comparing trisomic and euploid transcriptomes from different sources. We integrated all these data in a “DS network”. We found that genome wide deregulation as a consequence of trisomy 21 is not arbitrary, but involves deregulation of specific molecular cascades in which both HSA21 genes and HSA21 interactors are more consistently deregulated compared to other genes. In fact, gene deregulation happens in “clusters”, so that groups from 2 to 13 genes are found consistently deregulated. Most of these events of “co-deregulation” involve genes belonging to the same GO category, and genes associated with the same disease class. The most consistent changes are enriched in interferon related categories and neutrophil activation, reinforcing the concept that DS is an inflammatory disease. Our results also suggest that the impact of the trisomy might diverge in each tissue due to the different gene set deregulation, even though the triplicated genes are the same. Our original method to integrate transcriptomic data confirmed not only the importance of known genes, such as SOD1, but also detected new ones that could be extremely useful for generating or confirming hypotheses and supporting new putative therapeutic candidates. We created “metaDEA” an R package that uses our method to integrate every kind of transcriptomic data and therefore could be used with other complex disorders, such as cancer. We also created a user-friendly web application to query Ensembl gene IDs and retrieve all the information of their differential expression across the datasets.

scholarly journals Stable DNMT3L overexpression in SH-SY5Y neurons recreates a facet of the genome-wide Down syndrome DNA methylation signature

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Benjamin I. Laufer ◽  
J. Antonio Gomez ◽  
Julia M. Jianu ◽  
Janine M. LaSalle
Keyword(s):  
Dna Methylation ◽  
Down Syndrome ◽  
Neuronal Differentiation ◽  
Molecular Mechanisms ◽  
Cpg Island ◽  
Differential Methylation ◽  
Chromosome 21 ◽  
Pairwise Comparisons ◽  
Genome Wide ◽  
A Genome

Abstract Background Down syndrome (DS) is characterized by a genome-wide profile of differential DNA methylation that is skewed towards hypermethylation in most tissues, including brain, and includes pan-tissue differential methylation. The molecular mechanisms involve the overexpression of genes related to DNA methylation on chromosome 21. Here, we stably overexpressed the chromosome 21 gene DNA methyltransferase 3L (DNMT3L) in the human SH-SY5Y neuroblastoma cell line and assayed DNA methylation at over 26 million CpGs by whole genome bisulfite sequencing (WGBS) at three different developmental phases (undifferentiated, differentiating, and differentiated). Results DNMT3L overexpression resulted in global CpG and CpG island hypermethylation as well as thousands of differentially methylated regions (DMRs). The DNMT3L DMRs were skewed towards hypermethylation and mapped to genes involved in neurodevelopment, cellular signaling, and gene regulation. Consensus DNMT3L DMRs showed that cell lines clustered by genotype and then differentiation phase, demonstrating sets of common genes affected across neuronal differentiation. The hypermethylated DNMT3L DMRs from all pairwise comparisons were enriched for regions of bivalent chromatin marked by H3K4me3 as well as differentially methylated sites from previous DS studies of diverse tissues. In contrast, the hypomethylated DNMT3L DMRs from all pairwise comparisons displayed a tissue-specific profile enriched for regions of heterochromatin marked by H3K9me3 during embryonic development. Conclusions Taken together, these results support a mechanism whereby regions of bivalent chromatin that lose H3K4me3 during neuronal differentiation are targeted by excess DNMT3L and become hypermethylated. Overall, these findings demonstrate that DNMT3L overexpression during neurodevelopment recreates a facet of the genome-wide DS DNA methylation signature by targeting known genes and gene clusters that display pan-tissue differential methylation in DS.

scholarly journals Human iPSC-derived Down syndrome astrocytes display genome-wide perturbations in gene expression, an altered adhesion profile, and increased cellular dynamics

2020 ◽  
Vol 29 (5) ◽  
pp. 785-802 ◽  
Author(s):  
Blandine Ponroy Bally ◽  
W Todd Farmer ◽  
Emma V Jones ◽  
Selin Jessa ◽  
J Benjamin Kacerovsky ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Down Syndrome ◽  
Cell Adhesion ◽  
Brain Development ◽  
Trisomy 21 ◽  
Chromatin Accessibility ◽  
Chromosome 21 ◽  
Genome Wide ◽  
And Function ◽  
The Impact

Abstract Down syndrome (DS), caused by the triplication of human chromosome 21, leads to significant alterations in brain development and is a major genetic cause of intellectual disability. While much is known about changes to neurons in DS, the effects of trisomy 21 on non-neuronal cells such as astrocytes are poorly understood. Astrocytes are critical for brain development and function, and their alteration may contribute to DS pathophysiology. To better understand the impact of trisomy 21 on astrocytes, we performed RNA-sequencing on astrocytes from newly produced DS human induced pluripotent stem cells (hiPSCs). While chromosome 21 genes were upregulated in DS astrocytes, we found consistent up- and down-regulation of genes across the genome with a strong dysregulation of neurodevelopmental, cell adhesion and extracellular matrix molecules. ATAC (assay for transposase-accessible chromatin)-seq also revealed a global alteration in chromatin state in DS astrocytes, showing modified chromatin accessibility at promoters of cell adhesion and extracellular matrix genes. Along with these transcriptomic and epigenomic changes, DS astrocytes displayed perturbations in cell size and cell spreading as well as modifications to cell-cell and cell-substrate recognition/adhesion, and increases in cellular motility and dynamics. Thus, triplication of chromosome 21 is associated with genome-wide transcriptional, epigenomic and functional alterations in astrocytes that may contribute to altered brain development and function in DS.

scholarly journals Stable DNMT3L Overexpression in SH-SY5Y Neurons Recreates a Facet of the Genome-Wide Down Syndrome DNA Methylation Signature

2020 ◽  
Author(s):  
Benjamin I. Laufer ◽  
J. Antonio Gomez ◽  
Julia M. Jianu ◽  
Janine M. LaSalle
Keyword(s):  
Dna Methylation ◽  
Down Syndrome ◽  
Dna Methyltransferase ◽  
Molecular Mechanisms ◽  
Cpg Island ◽  
Neuroblastoma Cell ◽  
Chromosome 21 ◽  
Pairwise Comparisons ◽  
Genome Wide ◽  
A Genome

AbstractDown syndrome (DS) is characterized by a genome-wide profile of differential DNA methylation that is skewed towards hypermethylation in most tissues, including brain. The molecular mechanisms involve the overexpression of genes related to DNA methylation on chromosome 21. Here, we stably overexpressed the chromosome 21 gene DNA methyltransferase 3L (DNMT3L) in the human SH-SY5Y neuroblastoma cell line and assayed DNA methylation at over 26 million CpGs by whole genome bisulfite sequencing at three different developmental phases (undifferentiated, differentiating, and differentiated). DNMT3L overexpression resulted in global CpG and CpG island hypermethylation as well as thousands of differentially methylated regions (DMRs). The DNMT3L DMRs were skewed towards hypermethylation and mapped to genes involved in neurodevelopment, cellular signaling, and gene regulation. Merging the DMRs into a consensus profile where the cell lines clustered by genotype and then phase demonstrated that different regions of common genes are affected. The hypermethylated DMRs from all pairwise comparisons were enriched for regions of bivalent chromatin marked by H3K4me3 as well as differentially methylated CpGs from previous DS studies of diverse tissues. In contrast, the hypomethylated DMRs from all pairwise comparisons displayed a tissue-specific profile enriched for regions of heterochromatin marked by H3K9me3 during embryonic development. Taken together, we propose a mechanism whereby regions of bivalent chromatin that lose H3K4me3 during development are targeted by excess DNMT3L and become hypermethylated, while excess DNMT3L also evicts DNMT3A from heterochromatin, resulting in hypomethylation. Overall, these findings demonstrate that DNMT3L overexpression during neurodevelopment recreates a facet of the DS DNA methylation signature.

scholarly journals ALDH2 genotype modulates the association between alcohol consumption and AST/ALT ratio among middle-aged Japanese men: a genome-wide G × E interaction analysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yoichi Sutoh ◽  
Tsuyoshi Hachiya ◽  
Yuji Suzuki ◽  
Shohei Komaki ◽  
Hideki Ohmomo ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Interaction Analysis ◽  
Meta Analysis ◽  
Drinking Behavior ◽  
Japanese Men ◽  
Genome Wide ◽  
A Genome ◽  
Alcohol Intolerance ◽  
Related Liver Disease ◽  
The Impact

Abstract Liver tests (LT), especially to measure AST, ALT and GGT levels, are widely used to evaluate the risk of alcohol-related liver disease (ALD). In this study, we investigated the potential genetic factors that modulate the association between LTs and alcohol consumption. We conducted a genome-wide interaction meta-analysis in 7856 Japanese subjects from Tohoku Medical Megabank Community-Based Cohort (TMM CommCohort) study recruited in 2013, and identified 2 loci (12q24 and 2p16) with genome-wide significance (P > 5 × 10–8). The significant variants in the 12q24 included rs671, a variant associated with alcohol intolerance and located at a coding exon of ALDH2. We found that the amount of alcohol consumption was associated with increased level AST/ALT ratio among the subjects with the rs671 GA genotype. The elevated AST/ALT ratio among subjects with moderate-to-high levels of drinking behavior and the rs671 GA genotype was due to decreased levels of ALT, which was not accompanied with significant differences in AST levels. Although the interaction effect was significant in both men and women, the effect was much larger in men. Our results suggest that the impact of alcohol consumption on LT varies according to the ALDH2 genotype, providing an insight for the accurate screening of ALD in drinkers with the rs671 GA genotype.

scholarly journals Genome-wide association study of phenotypes measuring progression from first cocaine or opioid use to dependence reveals novel risk genes

2021 ◽  
Author(s):  
Richard Sherva ◽  
Congcong Zhu ◽  
Leah Wetherill ◽  
Howard J. Edenberg ◽  
Emma Johnson ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Chromosome 21 ◽  
Genome Wide Association ◽  
Chromosome 1 ◽  
Opioid Use ◽  
Discovery Sample ◽  
Genome Wide ◽  
A Genome

Aim: Substance use disorders (SUD) result in substantial morbidity and mortality worldwide. Opioids, and to a lesser extent cocaine, contribute to a large percentage of this health burden. Despite their high heritability, few genetic risk loci have been identified for either opioid or cocaine dependence (OD or CD, respectively). A genome-wide association study of OD and CD related phenotypes reflecting the time between first self-reported use of these substances and a first DSM-IV dependence diagnosis was conducted. Methods: Cox proportional hazards regression in a discovery sample of 6,188 African-Americans (AAs) and 6,835 European-Americans (EAs) participants in a genetic study of multiple substance dependence phenotypes were used to test for association between genetic variants and these outcomes. The top findings were tested for replication in two independent cohorts. Results: In the discovery sample, three independent regions containing variants associated with time to dependence at P < 5 x 10-8 were identified, one (rs61835088 = 1.03 x 10-8) for cocaine in the combined EA-AA meta-analysis in the gene FAM78B on chromosome 1, and two for opioids in the AA portion of the sample in intergenic regions of chromosomes 4 (rs4860439, P = 1.37 x 10-8) and 9 (rs7032521, P = 3.30 x 10-8). After meta-analysis with data from the replication cohorts, the signal at rs61835088 improved (HR = 0.87, P = 3.71 x 10-9 and an intergenic SNP on chromosome 21 (rs2825295, HR = 1.14, P = 2.57 x 10-8) that missed the significance threshold in the AA discovery sample became genome-wide significant (GWS) for CD. Conclusions: Although the two GWS variants are not in genes with obvious links to SUD biology and have modest effect sizes, they are statistically robust and show evidence for association in independent samples. These results may point to novel pathways contributing to disease progression and highlight the utility of related phenotypes to better understand the genetics of SUDs.

scholarly journals Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer’s disease and three causality networks of AD: the GR@ACE project

2019 ◽  
Author(s):  
Sonia Moreno-Grau ◽  
Itziar de Rojas ◽  
Isabel Hernández ◽  
Inés Quintela ◽  
Laura Montrreal ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Meta Analysis ◽  
Biological Pathways ◽  
Amyloid Angiopathy ◽  
Clinical Heterogeneity ◽  
Genome Wide ◽  
A Genome ◽  
Co Morbidity ◽  
The Impact

AbstractBackgroundGenetics plays a major role in Alzheimer’s Disease (AD). To date, 40 genes associated with AD have been identified, although most remain undiscovered. Clinical, neuropathological and genetic variability might impact genetic discoveries and complicate dissection of the biological pathways underlying AD.MethodsGR@ACE is a genome-wide study of dementia and its clinical endophenotypes that encompasses 4,120 cases and 3,289 controls from Spain. GR@ACE phenotypes were defined according to AD’s clinical certainty and the presence of vascular co-morbidity. To explore whether clinical endophenotypes reflect variation in underlying biological pathways, we first assessed the impact of known AD loci across endophenotypes to generate three loci categories. Next, we incorporated gene co-expression data and conducted pathway analysis on each category. To assess the impact of heterogeneity in the GWAS findings, the GR@ACE series were meta-analyzed with: 1) genotype-level data from dbGaP (N=21,235); and 2) summary statistics from IGAP Stages I and II (n=61,571 and n=81,455 respectively).FindingsWe classified known AD loci in three categories, which might reflect the disease clinical heterogeneity, from vascular and mixed forms to pure AD pathology. Immune system pathways were detected in all categories. Intriguingly, vascular processes were only detected as a causal mechanism in probable AD. A meta-analysis of GR@ACE with additional GWAS datasets revealed theANKRD31-rs4704171signal in theHMGCRgenomic region. We confirmed NDUFAF6-rs10098778 andSCIMP-rs7225151, which were previously detected by IGAP, to be suggestive signals. We also confirmed CD33-rs3865444 to be genome-wide significant.InterpretationThe regulation of vasculature is a prominent causal component of probable AD. In that context, cerebral amyloid angiopathy, the unique identified link between the vascular and amyloid hypotheses, deserves further investigation. The GR@ACE meta-analysis revealed novel AD genetic signals. GWAS results are strongly driven by the presence of clinical heterogeneity in the AD series.FundingGrifols SA, Fundación bancaria “La Caixa”, Fundació ACE and ISCIII (Instituto de Salud Carlos III).

scholarly journals Common risk variants identified in autism spectrum disorder

2017 ◽  
Author(s):  
Jakob Grove ◽  
Stephan Ripke ◽  
Thomas D. Als ◽  
Manuel Mattheisen ◽  
Raymond Walters ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Meta Analysis ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Complex Disorders ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
A Genome ◽  
Significance Levels ◽  
Near Term

AbstractAutism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes, in contrast to what is typically seen in other complex disorders. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD, just as it has been in a broad range of important psychiatric and diverse medical phenotypes.

scholarly journals Genome-wide association study of phenotypes measuring progression from first cocaine or opioid use to dependence reveals novel risk genes

2021 ◽  
Author(s):  
Richard Sherva ◽  
Congcong Zhu ◽  
Leah Wetherill ◽  
Howard J. Edenberg ◽  
Emma Johnson ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Chromosome 21 ◽  
Genome Wide Association ◽  
Chromosome 1 ◽  
Opioid Use ◽  
Discovery Sample ◽  
Genome Wide ◽  
A Genome

Aim: Substance use disorders (SUD) result in substantial morbidity and mortality worldwide. Opioids, and to a lesser extent cocaine, contribute to a large percentage of this health burden. Despite their high heritability, few genetic risk loci have been identified for either opioid or cocaine dependence (OD or CD, respectively). A genome-wide association study of OD and CD related phenotypes reflecting the time between first self-reported use of these substances and a first DSM-IV dependence diagnosis was conducted. Methods: Cox proportional hazards regression in a discovery sample of 6,188 African-Americans (AAs) and 6,835 European-Americans (EAs) participants in a genetic study of multiple substance dependence phenotypes were used to test for association between genetic variants and these outcomes. The top findings were tested for replication in two independent cohorts. Results: In the discovery sample, three independent regions containing variants associated with time to dependence at P < 5 × 10−8 were identified, one (rs61835088 = 1.03 × 10−8) for cocaine in the combined EA-AA meta-analysis in the gene FAM78B on chromosome 1, and two for opioids in the AA portion of the sample in intergenic regions of chromosomes 4 (rs4860439, P = 1.37 × 10−8) and 9 (rs7032521, P = 3.30 × 10−8). After meta-analysis with data from the replication cohorts, the signal at rs61835088 improved (HR = 0.87, P = 3.71 × 10−9 and an intergenic SNP on chromosome 21 (rs2825295, HR = 1.14, P = 2.57 × 10−8) that missed the significance threshold in the AA discovery sample became genome-wide significant (GWS) for CD. Conclusions: Although the two GWS variants are not in genes with obvious links to SUD biology and have modest effect sizes, they are statistically robust and show evidence for association in independent samples. These results may point to novel pathways contributing to disease progression and highlight the utility of related phenotypes to better understand the genetics of SUDs.

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