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  1. AU="Voloudakis, Georgios"
  2. AU="WU Guozhu"
  3. AU=Lassmann-Vague V
  4. AU=Koh Kwang Kon
  5. AU="Baxter, Amanda"
  6. AU=de Souza Anacleto Silva
  7. AU="Balandin, Alexander A."
  8. AU=Atasever Arslan Belkis
  9. AU="Kiyama, S"
  10. AU="Bwalya A. Witika"
  11. AU="Zhang, Nianxiang"
  12. AU="Cordova-Heredia, Golda"
  13. AU="Burley, Darcy E"
  14. AU="Jiang, Zhiwen"
  15. AU="Boffa, Daniel J"
  16. AU="Thomas-de-Montpréville, Vincent"
  17. AU=Yoneda Suguru
  18. AU="Collins, Robert D"
  19. AU=Martinez Andres Chacon
  20. AU="Soomro, Taha"
  21. AU=Almazroa Ahmed
  22. AU=Yang Chih-Yu
  23. AU="Sluckin, Tania C"
  24. AU="Amit Bahl"
  25. AU="Autore, Francesco"
  26. AU="Jin, Zhu"
  27. AU="Williams, Dionna W"
  28. AU="Absarul Haque"
  29. AU="Gavin Murphy"

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  1. Artikel ; 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

    Molecular psychiatry

    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.
    Sprache Englisch
    Erscheinungsdatum 2023-12-25
    Erscheinungsland England
    Dokumenttyp 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
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel: 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.
    Sprache Englisch
    Erscheinungsdatum 2024-01-26
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.21203/rs.3.rs-3851590/v1
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel: 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.
    Sprache Englisch
    Erscheinungsdatum 2023-05-02
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.21203/rs.3.rs-2705625/v1
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel: 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.
    Sprache Englisch
    Erscheinungsdatum 2023-01-18
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.1101/2023.01.17.23284670
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Artikel: 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

    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 ... ...

    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.
    Sprache Englisch
    Erscheinungsdatum 2023-03-20
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.1101/2023.03.17.533005
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel ; 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  Band 55, Heft 9, Seite(n) 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-Begriff(e) Humans ; Binge-Eating Disorder/genetics ; Binge-Eating Disorder/psychology ; Genome-Wide Association Study ; Obesity/genetics ; Phenotype ; Iron
    Chemische Substanzen Iron (E1UOL152H7)
    Sprache Englisch
    Erscheinungsdatum 2023-08-07
    Erscheinungsland United States
    Dokumenttyp 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
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  7. Artikel ; 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  Band 9, Heft 1, Seite(n) 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-Begriff(e) 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
    Sprache Englisch
    Erscheinungsdatum 2019-01-17
    Erscheinungsland United States
    Dokumenttyp 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
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  8. Artikel ; Online: Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits.

    Kang, JooEun / Castro, Victor M / Ripperger, Michael / Venkatesh, Sanan / Burstein, David / Linnér, Richard Karlsson / Rocha, Daniel B / Hu, Yirui / Wilimitis, Drew / Morley, Theodore / Han, Lide / Kim, Rachel Youngjung / Feng, Yen-Chen Anne / Ge, Tian / Heckers, Stephan / Voloudakis, Georgios / Chabris, Christopher / Roussos, Panos / McCoy, Thomas H /
    Walsh, Colin G / Perlis, Roy H / Ruderfer, Douglas M

    The American journal of psychiatry

    2024  , Seite(n) 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.
    Sprache Englisch
    Erscheinungsdatum 2024-05-15
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 280045-7
    ISSN 1535-7228 ; 0002-953X
    ISSN (online) 1535-7228
    ISSN 0002-953X
    DOI 10.1176/appi.ajp.20230247
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel: 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.
    Schlagwörter angiogenesis ; brain ; endothelial cells ; enzyme inhibition ; genes ; ligands ; mice ; phosphorylation ; sprouting ; transmembrane proteins
    Sprache Englisch
    Erscheinungsverlauf 2018-08
    Umfang p. 2813-2826.
    Erscheinungsort Springer International Publishing
    Dokumenttyp Artikel
    ZDB-ID 1358415-7
    ISSN 1420-9071 ; 1420-682X
    ISSN (online) 1420-9071
    ISSN 1420-682X
    DOI 10.1007/s00018-018-2762-7
    Datenquelle NAL Katalog (AGRICOLA)

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  10. Artikel ; Online: 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 : CMLS

    2018  Band 75, Heft 15, Seite(n) 2813–2826

    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.
    Mesh-Begriff(e) Amyloid Precursor Protein Secretases/antagonists & inhibitors ; Amyloid Precursor Protein Secretases/genetics ; Amyloid Precursor Protein Secretases/metabolism ; Animals ; Antigens, CD/metabolism ; Cadherins/metabolism ; Cattle ; Cells, Cultured ; Endothelial Cells/drug effects ; Endothelial Cells/metabolism ; Endothelial Cells/physiology ; Enzyme Inhibitors/pharmacology ; Ephrin-B2/metabolism ; Mice, Knockout ; Microscopy, Confocal ; Neovascularization, Physiologic/drug effects ; Peptides/metabolism ; Peptides/pharmacology ; RNA Interference ; Receptor, EphB4/metabolism
    Chemische Substanzen Antigens, CD ; Cadherins ; Enzyme Inhibitors ; Ephrin-B2 ; Peptides ; cadherin 5 ; Receptor, EphB4 (EC 2.7.10.1) ; Amyloid Precursor Protein Secretases (EC 3.4.-)
    Sprache Englisch
    Erscheinungsdatum 2018-02-10
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 1358415-7
    ISSN 1420-9071 ; 1420-682X
    ISSN (online) 1420-9071
    ISSN 1420-682X
    DOI 10.1007/s00018-018-2762-7
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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