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Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
by
Cao, Han
, Meyer-Lindenberg, Andreas
, Weber-Fahr, Wolfgang
, Schwarz, Emanuel
, Didriksen, Michael
, Chen, Junfang
, Sartorius, Alexander
, Schwarz, Adam J.
, Nickl-Jockschat, Thomas
, Stensbøl, Tine Bryan
, Gass, Natalia
, Klemme, Gabrielle
, Peterson, Zeru
, Sack, Markus
, Reinwald, Jonathan
in
22q11.2 deletion
/ Animal models
/ Animal welfare
/ Animals
/ Catechol O-Methyltransferase - genetics
/ Chromosome Deletion
/ Comt
/ Copy number
/ DiGeorge Syndrome - genetics
/ Disease Models, Animal
/ DNA Copy Number Variations
/ Functional connectivity
/ Gene deletion
/ Gene Expression
/ Humans
/ Learning algorithms
/ Machine learning
/ Magnetic fields
/ Magnetic Resonance Imaging
/ Male
/ Mental disorders
/ Mice
/ Mouse
/ Neural networks
/ Physiology
/ Protein interaction
/ Proteins
/ Respiration
/ Risk factors
/ Schizophrenia
/ Schizophrenia - genetics
/ Software
/ String protein
/ Time series
/ Trmt2a
/ tRNA Methyltransferases - genetics
/ ventral tegmental area
2021
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Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
by
Cao, Han
, Meyer-Lindenberg, Andreas
, Weber-Fahr, Wolfgang
, Schwarz, Emanuel
, Didriksen, Michael
, Chen, Junfang
, Sartorius, Alexander
, Schwarz, Adam J.
, Nickl-Jockschat, Thomas
, Stensbøl, Tine Bryan
, Gass, Natalia
, Klemme, Gabrielle
, Peterson, Zeru
, Sack, Markus
, Reinwald, Jonathan
in
22q11.2 deletion
/ Animal models
/ Animal welfare
/ Animals
/ Catechol O-Methyltransferase - genetics
/ Chromosome Deletion
/ Comt
/ Copy number
/ DiGeorge Syndrome - genetics
/ Disease Models, Animal
/ DNA Copy Number Variations
/ Functional connectivity
/ Gene deletion
/ Gene Expression
/ Humans
/ Learning algorithms
/ Machine learning
/ Magnetic fields
/ Magnetic Resonance Imaging
/ Male
/ Mental disorders
/ Mice
/ Mouse
/ Neural networks
/ Physiology
/ Protein interaction
/ Proteins
/ Respiration
/ Risk factors
/ Schizophrenia
/ Schizophrenia - genetics
/ Software
/ String protein
/ Time series
/ Trmt2a
/ tRNA Methyltransferases - genetics
/ ventral tegmental area
2021
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Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
by
Cao, Han
, Meyer-Lindenberg, Andreas
, Weber-Fahr, Wolfgang
, Schwarz, Emanuel
, Didriksen, Michael
, Chen, Junfang
, Sartorius, Alexander
, Schwarz, Adam J.
, Nickl-Jockschat, Thomas
, Stensbøl, Tine Bryan
, Gass, Natalia
, Klemme, Gabrielle
, Peterson, Zeru
, Sack, Markus
, Reinwald, Jonathan
in
22q11.2 deletion
/ Animal models
/ Animal welfare
/ Animals
/ Catechol O-Methyltransferase - genetics
/ Chromosome Deletion
/ Comt
/ Copy number
/ DiGeorge Syndrome - genetics
/ Disease Models, Animal
/ DNA Copy Number Variations
/ Functional connectivity
/ Gene deletion
/ Gene Expression
/ Humans
/ Learning algorithms
/ Machine learning
/ Magnetic fields
/ Magnetic Resonance Imaging
/ Male
/ Mental disorders
/ Mice
/ Mouse
/ Neural networks
/ Physiology
/ Protein interaction
/ Proteins
/ Respiration
/ Risk factors
/ Schizophrenia
/ Schizophrenia - genetics
/ Software
/ String protein
/ Time series
/ Trmt2a
/ tRNA Methyltransferases - genetics
/ ventral tegmental area
2021
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Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
Journal Article
Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
2021
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Overview
Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a, were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level.
Publisher
Elsevier Inc,Elsevier Limited,Elsevier
Subject
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