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  1. AU="Bot, Merel"
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  1. Article: Fibroblasts as an in vitro model of circadian genetic and genomic studies: A temporal analysis.

    Francia, Marcelo / Bot, Merel / Boltz, Toni / De la Hoz, Juan F / Boks, Marco / Kahn, René / Ophoff, Roel

    bioRxiv : the preprint server for biology

    2024  

    Abstract: Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. ...

    Abstract Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. Fibroblasts are a well-established
    Language English
    Publishing date 2024-03-05
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.05.19.541494
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Cell-type deconvolution of bulk-blood RNA-seq reveals biological insights into neuropsychiatric disorders.

    Boltz, Toni / Schwarz, Tommer / Bot, Merel / Hou, Kangcheng / Caggiano, Christa / Lapinska, Sandra / Duan, Chenda / Boks, Marco P / Kahn, Rene S / Zaitlen, Noah / Pasaniuc, Bogdan / Ophoff, Roel

    American journal of human genetics

    2024  Volume 111, Issue 2, Page(s) 323–337

    Abstract: Genome-wide association studies (GWASs) have uncovered susceptibility loci associated with psychiatric disorders such as bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome, and the causal ... ...

    Abstract Genome-wide association studies (GWASs) have uncovered susceptibility loci associated with psychiatric disorders such as bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome, and the causal mechanisms of the link between genetic variation and disease risk is unknown. Expression quantitative trait locus (eQTL) analysis of bulk tissue is a common approach used for deciphering underlying mechanisms, although this can obscure cell-type-specific signals and thus mask trait-relevant mechanisms. Although single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell-type proportions and cell-type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-seq from 1,730 samples derived from whole blood in a cohort ascertained from individuals with BP and SCZ, this study estimated cell-type proportions and their relation with disease status and medication. For each cell type, we found between 2,875 and 4,629 eGenes (genes with an associated eQTL), including 1,211 that are not found on the basis of bulk expression alone. We performed a colocalization test between cell-type eQTLs and various traits and identified hundreds of associations that occur between cell-type eQTLs and GWASs but that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on the regulation of cell-type expression loci and found examples of genes that are differentially regulated according to lithium use. Our study suggests that applying computational methods to large bulk RNA-seq datasets of non-brain tissue can identify disease-relevant, cell-type-specific biology of psychiatric disorders and psychiatric medication.
    MeSH term(s) Humans ; Genome-Wide Association Study/methods ; RNA-Seq ; Lithium ; Quantitative Trait Loci/genetics ; Phenotype ; Polymorphism, Single Nucleotide ; Genetic Predisposition to Disease
    Chemical Substances Lithium (9FN79X2M3F)
    Language English
    Publishing date 2024-02-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 219384-x
    ISSN 1537-6605 ; 0002-9297
    ISSN (online) 1537-6605
    ISSN 0002-9297
    DOI 10.1016/j.ajhg.2023.12.018
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Cell type deconvolution of bulk blood RNA-Seq to reveal biological insights of neuropsychiatric disorders.

    Boltz, Toni / Schwarz, Tommer / Bot, Merel / Hou, Kangcheng / Caggiano, Christa / Lapinska, Sandra / Duan, Chenda / Boks, Marco P / Kahn, Rene S / Zaitlen, Noah / Pasaniuc, Bogdan / Ophoff, Roel

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Genome-wide association studies (GWAS) have uncovered susceptibility loci associated with psychiatric disorders like bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome with unknown causal ... ...

    Abstract Genome-wide association studies (GWAS) have uncovered susceptibility loci associated with psychiatric disorders like bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome with unknown causal mechanisms of the link between genetic variation and disease risk. Expression quantitative trait loci (eQTL) analysis of bulk tissue is a common approach to decipher underlying mechanisms, though this can obscure cell-type specific signals thus masking trait-relevant mechanisms. While single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell type proportions and cell type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-Seq from 1,730 samples derived from whole blood in a cohort ascertained for individuals with BP and SCZ this study estimated cell type proportions and their relation with disease status and medication. We found between 2,875 and 4,629 eGenes for each cell type, including 1,211 eGenes that are not found using bulk expression alone. We performed a colocalization test between cell type eQTLs and various traits and identified hundreds of associations between cell type eQTLs and GWAS loci that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on cell type expression regulation and found examples of genes that are differentially regulated dependent on lithium use. Our study suggests that computational methods can be applied to large bulk RNA-Seq datasets of non-brain tissue to identify disease-relevant, cell type specific biology of psychiatric disorders and psychiatric medication.
    Language English
    Publishing date 2023-05-25
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.05.24.542156
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Quantitative trait loci mapping of circulating metabolites in cerebrospinal fluid to uncover biological mechanisms involved in brain-related phenotypes.

    Reus, Lianne M / Boltz, Toni / Francia, Marcelo / Bot, Merel / Ramesh, Naren / Koromina, Maria / Pijnenburg, Yolande A L / den Braber, Anouk / van der Flier, Wiesje M / Visser, Pieter Jelle / van der Lee, Sven J / Tijms, Betty M / Teunissen, Charlotte E / Loohuis, Loes Olde / Ophoff, Roel A

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Genomic studies of molecular traits have provided mechanistic insights into complex disease, though these lag behind for brain-related traits due to the inaccessibility of brain tissue. We leveraged cerebrospinal fluid (CSF) to study neurobiological ... ...

    Abstract Genomic studies of molecular traits have provided mechanistic insights into complex disease, though these lag behind for brain-related traits due to the inaccessibility of brain tissue. We leveraged cerebrospinal fluid (CSF) to study neurobiological mechanisms
    Language English
    Publishing date 2023-09-27
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.09.26.559021
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Powerful eQTL mapping through low-coverage RNA sequencing.

    Schwarz, Tommer / Boltz, Toni / Hou, Kangcheng / Bot, Merel / Duan, Chenda / Loohuis, Loes Olde / Boks, Marco P / Kahn, René S / Ophoff, Roel A / Pasaniuc, Bogdan

    HGG advances

    2022  Volume 3, Issue 3, Page(s) 100103

    Abstract: Mapping genetic variants that regulate gene expression (eQTL mapping) in large-scale RNA sequencing (RNA-seq) studies is often employed to understand functional consequences of regulatory variants. However, the high cost of RNA-seq limits sample size, ... ...

    Abstract Mapping genetic variants that regulate gene expression (eQTL mapping) in large-scale RNA sequencing (RNA-seq) studies is often employed to understand functional consequences of regulatory variants. However, the high cost of RNA-seq limits sample size, sequencing depth, and, therefore, discovery power in eQTL studies. In this work, we demonstrate that, given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample and increasing the number of individuals sequenced in the assay. We perform RNA-seq of whole-blood tissue across 1,490 individuals at low coverage (5.9 million reads/sample) and show that the effective power is higher than that of an RNA-seq study of 570 individuals at moderate coverage (13.9 million reads/sample). Next, we leverage synthetic datasets derived from real RNA-seq data (50 million reads/sample) to explore the interplay of coverage and number individuals in eQTL studies, and show that a 10-fold reduction in coverage leads to only a 2.5-fold reduction in statistical power to identify eQTLs. Our work suggests that lowering coverage while increasing the number of individuals in RNA-seq is an effective approach to increase discovery power in eQTL studies.
    Language English
    Publishing date 2022-04-02
    Publishing country United States
    Document type Journal Article
    ISSN 2666-2477
    ISSN (online) 2666-2477
    DOI 10.1016/j.xhgg.2022.100103
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: A Longitudinal Model of Human Neuronal Differentiation for Functional Investigation of Schizophrenia Polygenic Risk.

    Ori, Anil P S / Bot, Merel H M / Molenhuis, Remco T / Olde Loohuis, Loes M / Ophoff, Roel A

    Biological psychiatry

    2018  Volume 85, Issue 7, Page(s) 544–553

    Abstract: Background: Common psychiatric disorders are characterized by complex disease architectures with many small genetic effects that contribute and complicate biological understanding of their etiology. There is therefore a pressing need for in vitro ... ...

    Abstract Background: Common psychiatric disorders are characterized by complex disease architectures with many small genetic effects that contribute and complicate biological understanding of their etiology. There is therefore a pressing need for in vitro experimental systems that allow for interrogation of polygenic psychiatric disease risk to study the underlying biological mechanisms.
    Methods: We have developed an analytical framework that integrates genome-wide disease risk from genome-wide association studies with longitudinal in vitro gene expression profiles of human neuronal differentiation.
    Results: We demonstrate that the cumulative impact of risk loci of specific psychiatric disorders is significantly associated with genes that are differentially expressed and upregulated during differentiation. We find the strongest evidence for schizophrenia, a finding that we replicate in an independent dataset. A longitudinal gene cluster involved in synaptic function primarily drives the association with schizophrenia risk.
    Conclusions: These findings reveal that in vitro human neuronal differentiation can be used to translate the polygenic architecture of schizophrenia to biologically relevant pathways that can be modeled in an experimental system. Overall, this work emphasizes the use of longitudinal in vitro transcriptomic signatures as a cellular readout and the application to the genetics of complex traits.
    MeSH term(s) Cell Differentiation ; Gene Expression Profiling ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Humans ; Longitudinal Studies ; Models, Neurological ; Multifactorial Inheritance ; Neural Stem Cells ; Risk ; Schizophrenia/genetics
    Language English
    Publishing date 2018-09-06
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 209434-4
    ISSN 1873-2402 ; 0006-3223
    ISSN (online) 1873-2402
    ISSN 0006-3223
    DOI 10.1016/j.biopsych.2018.08.019
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    In stock of ZB MED Cologne/Königswinter

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