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Article ; Online: Convergence of the dysregulated regulome in schizophrenia with polygenic risk and evolutionarily constrained enhancers.

Dong, Pengfei / Voloudakis, Georgios / Fullard, John F / Hoffman, Gabriel E / Roussos, Panos

2023

Abstract: Enhancers play an essential role in the etiology of schizophrenia; however, the dysregulation of enhancer activity and its impact on the regulome in schizophrenia remains understudied. To address this gap in our knowledge, we assessed enhancer and gene ... ...

Abstract	Enhancers play an essential role in the etiology of schizophrenia; however, the dysregulation of enhancer activity and its impact on the regulome in schizophrenia remains understudied. To address this gap in our knowledge, we assessed enhancer and gene expression in 1,382 brain samples comprising cases with schizophrenia and unaffected controls. Dysregulation of enhancer expression was concordant with changes in gene expression, and was more closely associated with schizophrenia polygenic risk, suggesting that enhancer dysregulation is proximal to the genetic etiology of the disease. Modeling the shared variance of cis-coordinated genes and enhancers revealed a gene regulatory program that was highly associated with genetic vulnerability to schizophrenia. By integrating coordinated factors with evolutionary constraints, we found that enhancers acquired during human evolution are more likely to regulate genes that are implicated in neuropsychiatric disorders and, thus, hold potential as therapeutic targets. Our analysis provides a systematic view of regulome dysregulation in schizophrenia and highlights its convergence with schizophrenia polygenic risk and human-gained enhancers.
Language	English
Publishing date	2023-12-25
Publishing country	England
Document type	Journal Article
ZDB-ID	1330655-8
ISSN	1476-5578 ; 1359-4184
ISSN (online)	1476-5578
ISSN	1359-4184
DOI	10.1038/s41380-023-02370-y
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Article: Alzheimer's disease transcriptional landscape in ex-vivo human microglia.

Roussos, Panos / Kosoy, Roman / Fullard, John / Bendl, Jaroslav / Kleopoulos, Steven / Shao, Zhiping / Argyriou, Stathis / Mathur, Deepika / Vicari, James / Ma, Yixuan / Humphrey, Jack / Brophy, Erica / Raj, Towfique / Katsel, Pavel / Voloudakis, Georgios / Lee, Donghoon / Bennett, David / Haroutunian, Vahram / Hoffman, Gabriel

Research square

2024

Abstract: Microglia are resident immune cells of the brain and are implicated in the etiology of Alzheimer's Disease (AD) and other diseases. Yet the cellular and molecular processes regulating their function throughout the course of the disease are poorly ... ...

Abstract	Microglia are resident immune cells of the brain and are implicated in the etiology of Alzheimer's Disease (AD) and other diseases. Yet the cellular and molecular processes regulating their function throughout the course of the disease are poorly understood. Here, we present the transcriptional landscape of primary microglia from 189 human postmortem brains, including 58 healthy aging individuals and 131 with a range of disease phenotypes, including 63 patients representing the full spectrum of clinical and pathological severity of AD. We identified transcriptional changes associated with multiple AD phenotypes, capturing the severity of dementia and neuropathological lesions. Transcript-level analyses identified additional genes with heterogeneous isoform usage and AD phenotypes. We identified changes in gene-gene coordination in AD, dysregulation of co-expression modules, and disease subtypes with distinct gene expression. Taken together, these data further our understanding of the key role of microglia in AD biology and nominate candidates for therapeutic intervention.
Language	English
Publishing date	2024-01-26
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-3851590/v1
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Article ; Online: Single-cell multi-cohort dissection of the schizophrenia transcriptome.

Ruzicka, W Brad / Mohammadi, Shahin / Fullard, John F / Davila-Velderrain, Jose / Subburaju, Sivan / Tso, Daniel Reed / Hourihan, Makayla / Jiang, Shan / Lee, Hao-Chih / Bendl, Jaroslav / Voloudakis, Georgios / Haroutunian, Vahram / Hoffman, Gabriel E / Roussos, Panos / Kellis, Manolis

Science (New York, N.Y.)

2024 Volume 384, Issue 6698, Page(s) eadg5136

Abstract: The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation and the development of more effective therapies. Here, we performed single-cell dissection of schizophrenia-associated transcriptomic changes in the human prefrontal ... ...

Abstract	The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation and the development of more effective therapies. Here, we performed single-cell dissection of schizophrenia-associated transcriptomic changes in the human prefrontal cortex across 140 individuals in two independent cohorts. Excitatory neurons were the most affected cell group, with transcriptional changes converging on neurodevelopment and synapse-related molecular pathways. Transcriptional alterations included known genetic risk factors, suggesting convergence of rare and common genomic variants on neuronal population-specific alterations in schizophrenia. Based on the magnitude of schizophrenia-associated transcriptional change, we identified two populations of individuals with schizophrenia marked by expression of specific excitatory and inhibitory neuronal cell states. This single-cell atlas links transcriptomic changes to etiological genetic risk factors, contextualizing established knowledge within the human cortical cytoarchitecture and facilitating mechanistic understanding of schizophrenia pathophysiology and heterogeneity.
MeSH term(s)	Schizophrenia/genetics ; Single-Cell Analysis ; Transcriptome ; Humans ; Prefrontal Cortex/metabolism ; Neurons/metabolism ; Cohort Studies ; Male ; Female ; Genetic Predisposition to Disease ; Adult ; Synapses/metabolism ; Risk Factors
Language	English
Publishing date	2024-05-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	128410-1
ISSN	1095-9203 ; 0036-8075
ISSN (online)	1095-9203
ISSN	0036-8075
DOI	10.1126/science.adg5136
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Article: Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet.

Hoffman, Gabriel E / Lee, Donghoon / Bendl, Jaroslav / Fnu, Prashant / Hong, Aram / Casey, Clara / Alvia, Marcela / Shao, Zhiping / Argyriou, Stathis / Therrien, Karen / Venkatesh, Sanan / Voloudakis, Georgios / Haroutunian, Vahram / Fullard, John F / Roussos, Panos

Research square

2023

Abstract: Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of ... ...

Abstract	Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimer's disease cases and 149 controls.
Language	English
Publishing date	2023-05-02
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-2705625/v1
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Article: Detecting and Adjusting for Hidden Biases due to Phenotype Misclassification in Genome-Wide Association Studies.

Burstein, David / Hoffman, Gabriel / Mathur, Deepika / Venkatesh, Sanan / Therrien, Karen / Fanous, Ayman H / Bigdeli, Tim B / Harvey, Philip D / Roussos, Panos / Voloudakis, Georgios

medRxiv : the preprint server for health sciences

2023

Abstract: With the advent of healthcare-based genotyped biobanks, genome-wide association studies (GWAS) leverage larger sample sizes, incorporate patients with diverse ancestries and introduce noisier phenotypic definitions. Yet the extent and impact of ... ...

Abstract	With the advent of healthcare-based genotyped biobanks, genome-wide association studies (GWAS) leverage larger sample sizes, incorporate patients with diverse ancestries and introduce noisier phenotypic definitions. Yet the extent and impact of phenotypic misclassification on large-scale datasets is not currently well understood due to a lack of statistical methods to estimate relevant parameters from empirical data. Here, we develop a statistical method and scalable software, PheMED, Phenotypic Measurement of Effective Dilution, to quantify phenotypic misclassification across GWAS using only summary statistics. We illustrate how the parameters estimated by PheMED relate to the negative and positive predictive value of the labeled phenotype, compared to ground truth, and how misclassification of the phenotype yields diluted effect-sizes of variant-phenotype associations. Furthermore, we apply our methodology to detect multiple instances of statistically significant dilution in real-world data. We demonstrate how effective dilution biases downstream GWAS replication and heritability analyses despite utilizing current best practices, and provide a dilution-aware meta-analysis approach that outperforms existing methods. Consequently, we anticipate that PheMED will be a valuable tool for researchers to address phenotypic data quality issues both within and across cohorts.
Language	English
Publishing date	2023-01-18
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.01.17.23284670
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Article: Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet.

bioRxiv : the preprint server for biology

2023

Abstract	Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimer's disease cases and 149 controls.
Language	English
Publishing date	2023-03-20
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.03.17.533005
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Article ; Online: Genome-wide analysis of a model-derived binge eating disorder phenotype identifies risk loci and implicates iron metabolism.

Burstein, David / Griffen, Trevor C / Therrien, Karen / Bendl, Jaroslav / Venkatesh, Sanan / Dong, Pengfei / Modabbernia, Amirhossein / Zeng, Biao / Mathur, Deepika / Hoffman, Gabriel / Sysko, Robyn / Hildebrandt, Tom / Voloudakis, Georgios / Roussos, Panos

Nature genetics

2023 Volume 55, Issue 9, Page(s) 1462–1470

Abstract: Binge eating disorder (BED) is the most common eating disorder, yet its genetic architecture remains largely unknown. Studying BED is challenging because it is often comorbid with obesity, a common and highly polygenic trait, and it is underdiagnosed in ... ...

Abstract	Binge eating disorder (BED) is the most common eating disorder, yet its genetic architecture remains largely unknown. Studying BED is challenging because it is often comorbid with obesity, a common and highly polygenic trait, and it is underdiagnosed in biobank data sets. To address this limitation, we apply a supervised machine-learning approach (using 822 cases of individuals diagnosed with BED) to estimate the probability of each individual having BED based on electronic medical records from the Million Veteran Program. We perform a genome-wide association study of individuals of African (n = 77,574) and European (n = 285,138) ancestry while controlling for body mass index to identify three independent loci near the HFE, MCHR2 and LRP11 genes and suggest APOE as a risk gene for BED. We identify shared heritability between BED and several neuropsychiatric traits, and implicate iron metabolism in the pathophysiology of BED. Overall, our findings provide insights into the genetics underlying BED and suggest directions for future translational research.
MeSH term(s)	Humans ; Binge-Eating Disorder/genetics ; Binge-Eating Disorder/psychology ; Genome-Wide Association Study ; Obesity/genetics ; Phenotype ; Iron
Chemical Substances	Iron (E1UOL152H7)
Language	English
Publishing date	2023-08-07
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-023-01464-1
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Article ; Online: Assessment of somatic single-nucleotide variation in brain tissue of cases with schizophrenia.

Fullard, John F / Charney, Alexander W / Voloudakis, Georgios / Uzilov, Andrew V / Haroutunian, Vahram / Roussos, Panos

Translational psychiatry

2019 Volume 9, Issue 1, Page(s) 21

Abstract: The genetic architecture of schizophrenia (SCZ) includes numerous risk loci across a range of frequencies and sizes, including common and rare single-nucleotide variants and insertions/deletions (indels), as well as rare copy number variants (CNVs). ... ...

Abstract	The genetic architecture of schizophrenia (SCZ) includes numerous risk loci across a range of frequencies and sizes, including common and rare single-nucleotide variants and insertions/deletions (indels), as well as rare copy number variants (CNVs). Despite the clear heritability of the disease, monozygotic twins are discordant for SCZ at a significant rate. Somatic variants-genetic changes that arise after fertilization rather than through germline inheritance-are widespread in the human brain and known to contribute to risk for both rare and common neuropsychiatric conditions. The contribution of somatic variants in the brain to risk of SCZ remains to be determined. In this study, we surveyed somatic single-nucleotide variants (sSNVs) in the brains of controls and individuals with SCZ (n = 10 and n = 9, respectively). From each individual, whole-exome sequencing (WES) was performed on DNA from neuronal and non-neuronal nuclei isolated by fluorescence activated nuclear sorting (FANS) from frozen postmortem prefrontal cortex (PFC) samples, as well as DNA extracted from temporal muscle as a reference. We identified an increased burden of sSNVs in cases compared to controls (SCZ rate = 2.78, control rate = 0.70; P = 0.0092, linear mixed effects model), that included a higher rate of non-synonymous and loss-of-function variants (SCZ rate = 1.33, control rate = 0.50; P = 0.047, linear mixed effects model). Our findings suggest sSNVs in the brain may constitute an additional component of the complex genetic architecture of SCZ. This perspective argues for the need to further investigate somatic variation in the brain as an explanation of the discordance in monozygotic twins and a potential guide to the identification of novel therapeutic targets.
MeSH term(s)	Brain/pathology ; Case-Control Studies ; DNA Copy Number Variations ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Humans ; Polymorphism, Single Nucleotide ; Schizophrenia/genetics ; Schizophrenia/pathology ; Twins, Monozygotic/genetics ; Whole Exome Sequencing
Language	English
Publishing date	2019-01-17
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2609311-X
ISSN	2158-3188 ; 2158-3188
ISSN (online)	2158-3188
ISSN	2158-3188
DOI	10.1038/s41398-018-0342-0
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Article ; Online: Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits.

The American journal of psychiatry

2024 , Page(s) appiajp20230247

Abstract: Objective: Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability ... ...

Abstract	Objective: Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD. Methods: Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks. Results: Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. Conclusions: This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.
Language	English
Publishing date	2024-05-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	280045-7
ISSN	1535-7228 ; 0002-953X
ISSN (online)	1535-7228
ISSN	0002-953X
DOI	10.1176/appi.ajp.20230247
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Article: The product of the γ-secretase processing of ephrinB2 regulates VE-cadherin complexes and angiogenesis

Warren, Noel A / Voloudakis, Georgios / Yoon, Yonejung / Robakis, Nikolaos K / Georgakopoulos, Anastasios

Cellular and molecular life sciences. 2018 Aug., v. 75, no. 15

2018

Abstract: Presenilin-1 (PS1) gene encodes the catalytic component of γ-secretase, which proteolytically processes several type I transmembrane proteins. We here present evidence that the cytosolic peptide efnB2/CTF2 produced by the PS1/γ-secretase cleavage of ... ...

Abstract	Presenilin-1 (PS1) gene encodes the catalytic component of γ-secretase, which proteolytically processes several type I transmembrane proteins. We here present evidence that the cytosolic peptide efnB2/CTF2 produced by the PS1/γ-secretase cleavage of efnB2 ligand promotes EphB4 receptor-dependent angiogenesis in vitro. EfnB2/CTF2 increases endothelial cell sprouting and tube formation, stimulates the formation of angiogenic complexes that include VE-cadherin, Raf-1 and Rok-α, and increases MLC2 phosphorylation. These functions are mediated by the PDZ-binding domain of efnB2. Acute downregulation of PS1 or inhibition of γ-secretase inhibits the angiogenic functions of EphB4 while absence of PS1 decreases the VE-cadherin angiogenic complexes of mouse brain. Our data reveal a mechanism by which PS1/γ-secretase regulates efnB2/EphB4 mediated angiogenesis.
Keywords	angiogenesis ; brain ; endothelial cells ; enzyme inhibition ; genes ; ligands ; mice ; phosphorylation ; sprouting ; transmembrane proteins
Language	English
Dates of publication	2018-08
Size	p. 2813-2826.
Publishing place	Springer International Publishing
Document type	Article
ZDB-ID	1358415-7
ISSN	1420-9071 ; 1420-682X
ISSN (online)	1420-9071
ISSN	1420-682X
DOI	10.1007/s00018-018-2762-7
Database	NAL-Catalogue (AGRICOLA)

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