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Article ; Online: Spatiotemporal expression patterns of anxiety disorder-associated genes.

Karunakaran, Kalyani B / Amemori, Ken-Ichi

2023 Volume 13, Issue 1, Page(s) 385

Abstract: Anxiety disorders (ADs) are the most common form of mental disorder that affects millions of individuals worldwide. Although physiological studies have revealed the neural circuits related to AD symptoms, how AD-associated genes are spatiotemporally ... ...

Abstract	Anxiety disorders (ADs) are the most common form of mental disorder that affects millions of individuals worldwide. Although physiological studies have revealed the neural circuits related to AD symptoms, how AD-associated genes are spatiotemporally expressed in the human brain still remains unclear. In this study, we integrated genome-wide association studies of four human AD subtypes-generalized anxiety disorder, social anxiety disorder, panic disorder, and obsessive-compulsive disorder-with spatial gene expression patterns. Our investigation uncovered a novel division among AD-associated genes, marked by significant and distinct expression enrichments in the cerebral nuclei, limbic, and midbrain regions. Each gene cluster was associated with specific anxiety-related behaviors, signaling pathways, region-specific gene networks, and cell types. Notably, we observed a significant negative correlation in the temporal expression patterns of these gene clusters during various developmental stages. Moreover, the specific brain regions enriched in each gene group aligned with neural circuits previously associated with negative decision-making and anxious temperament. These results suggest that the two distinct gene clusters may underlie separate neural systems involved in anxiety. As a result, our findings bridge the gap between genes and neural circuitry, shedding light on the mechanisms underlying AD-associated behaviors.
MeSH term(s)	Humans ; Genome-Wide Association Study ; Anxiety Disorders/genetics ; Anxiety Disorders/diagnosis ; Anxiety/genetics ; Obsessive-Compulsive Disorder/genetics ; Obsessive-Compulsive Disorder/diagnosis ; Panic Disorder/genetics
Language	English
Publishing date	2023-12-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	2609311-X
ISSN	2158-3188 ; 2158-3188
ISSN (online)	2158-3188
ISSN	2158-3188
DOI	10.1038/s41398-023-02693-y
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Article ; Online: Author Correction: Parkinson's disease and schizophrenia interactomes contain temporally distinct gene clusters underlying comorbid mechanisms and unique disease processes.

Karunakaran, Kalyani B / Jain, Sanjeev / Brahmachari, Samir K / Balakrishnan, N / Ganapathiraju, Madhavi K

Schizophrenia (Heidelberg, Germany)

2024 Volume 10, Issue 1, Page(s) 33

Language	English
Publishing date	2024-03-13
Publishing country	Germany
Document type	Published Erratum
ZDB-ID	3133210-9
ISSN	2754-6993 ; 2754-6993
ISSN (online)	2754-6993
ISSN	2754-6993
DOI	10.1038/s41537-024-00455-3
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Article ; Online: Parkinson's disease and schizophrenia interactomes contain temporally distinct gene clusters underlying comorbid mechanisms and unique disease processes.

Karunakaran, Kalyani B / Jain, Sanjeev / Brahmachari, Samir K / Balakrishnan, N / Ganapathiraju, Madhavi K

Schizophrenia (Heidelberg, Germany)

2024 Volume 10, Issue 1, Page(s) 26

Abstract: Genome-wide association studies suggest significant overlaps in Parkinson's disease (PD) and schizophrenia (SZ) risks, but the underlying mechanisms remain elusive. The protein-protein interaction network ('interactome') plays a crucial role in PD and SZ ...

Abstract	Genome-wide association studies suggest significant overlaps in Parkinson's disease (PD) and schizophrenia (SZ) risks, but the underlying mechanisms remain elusive. The protein-protein interaction network ('interactome') plays a crucial role in PD and SZ and can incorporate their spatiotemporal specificities. Therefore, to study the linked biology of PD and SZ, we compiled PD- and SZ-associated genes from the DisGeNET database, and constructed their interactomes using BioGRID and HPRD. We examined the interactomes using clustering and enrichment analyses, in conjunction with the transcriptomic data of 26 brain regions spanning foetal stages to adulthood available in the BrainSpan Atlas. PD and SZ interactomes formed four gene clusters with distinct temporal identities (Disease Gene Networks or 'DGNs'1-4). DGN1 had unique SZ interactome genes highly expressed across developmental stages, corresponding to a neurodevelopmental SZ subtype. DGN2, containing unique SZ interactome genes expressed from early infancy to adulthood, correlated with an inflammation-driven SZ subtype and adult SZ risk. DGN3 contained unique PD interactome genes expressed in late infancy, early and late childhood, and adulthood, and involved in mitochondrial pathways. DGN4, containing prenatally-expressed genes common to both the interactomes, involved in stem cell pluripotency and overlapping with the interactome of 22q11 deletion syndrome (comorbid psychosis and Parkinsonism), potentially regulates neurodevelopmental mechanisms in PD-SZ comorbidity. Our findings suggest that disrupted neurodevelopment (regulated by DGN4) could expose risk windows in PD and SZ, later elevating disease risk through inflammation (DGN2). Alternatively, variant clustering in DGNs may produce disease subtypes, e.g., PD-SZ comorbidity with DGN4, and early/late-onset SZ with DGN1/DGN2.
Language	English
Publishing date	2024-02-27
Publishing country	Germany
Document type	Journal Article
ZDB-ID	3133210-9
ISSN	2754-6993 ; 2754-6993
ISSN (online)	2754-6993
ISSN	2754-6993
DOI	10.1038/s41537-024-00439-3
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Article: Potentially repurposable drugs for COVID-19 identified from SARS-CoV-2 Host Protein Interactome.

Karunakaran, Kalyani B / Balakrishnan, N / Ganapathiraju, Madhavi

Research square

2020

Abstract: We previously presented the protein-protein interaction network - the 'HoP' or the host protein interactome - of 332 host proteins that were identified to interact with 27 nCoV19 viral proteins by Gordon et al. Here, we studied drugs targeting the ... ...

Abstract	We previously presented the protein-protein interaction network - the 'HoP' or the host protein interactome - of 332 host proteins that were identified to interact with 27 nCoV19 viral proteins by Gordon et al. Here, we studied drugs targeting the proteins in this interactome to identify whether any of them may potentially be repurposable against SARS-CoV-2. We studied each of the drugs using the BaseSpace Correlation Engine and identified those that induce gene expression profiles negatively correlated with SARS-associated expression profile. This analysis resulted in 20 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for SARS (viral infection versus normal). These included drugs that were already being tested for their clinical activity against SARS-CoV-2, those with proven activity against SARS-CoV/MERS-CoV, broad-spectrum antiviral drugs, and those identified/prioritized by other computational re-purposing studies. In summary, our integrated computational analysis of the HoP interactome in conjunction with drug-induced transcriptomic data resulted in drugs that may be repurposable for COVID-19.
Keywords	covid19
Language	English
Publishing date	2020-05-28
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-30363/v1
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Article: Interactome of SARS-CoV-2 / nCoV19 modulated host proteins with computationally predicted PPIs.

Karunakaran, Kalyani B / Balakrishnan, N / Ganapathiraju, Madhavi K

Research square

2020

Abstract: World over, people are looking for solutions to tackle the pandemic coronavirus disease (COVID-19) caused by the virus SARS-CoV-2/nCoV-19. Notable contributions in biomedical field have been characterizing viral genomes, host transcriptomes and proteomes, ...

Abstract	World over, people are looking for solutions to tackle the pandemic coronavirus disease (COVID-19) caused by the virus SARS-CoV-2/nCoV-19. Notable contributions in biomedical field have been characterizing viral genomes, host transcriptomes and proteomes, repurposable drugs and vaccines. In one such study, 332 human proteins targeted by nCoV19 were identified. We expanded this set of host proteins by constructing their protein interactome, including in it not only the known protein-protein interactions (PPIs) but also novel, hitherto unknown PPIs predicted with our High-precision Protein-Protein Interaction Prediction (HiPPIP) model that was shown to be highly accurate. In fact, one of the earliest discoveries made possible by HiPPIP is related to activation of immunity upon viral infection. We found that several interactors of the host proteins are differentially expressed upon viral infection, are related to highly relevant pathways, and that the novel interaction of NUP98 with CHMP5 may activate an antiviral mechanism leading to disruption of viral budding. We are making the interactions available as downloadable files to facilitate future systems biology studies and also on a web-server at http://hagrid.dbmi.pitt.edu/corona that allows not only keyword search but also queries such as "PPIs where one protein is associated with 'virus' and the interactors with 'pulmonary'".
Keywords	covid19
Language	English
Publishing date	2020-05-13
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-28592/v1
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Article ; Online: Novel Protein-Protein Interactions Highlighting the Crosstalk between Hypoplastic Left Heart Syndrome, Ciliopathies and Neurodevelopmental Delays.

Karunakaran, Kalyani B / Gabriel, George C / Balakrishnan, Narayanaswamy / Lo, Cecilia W / Ganapathiraju, Madhavi K

Genes

2022 Volume 13, Issue 4

Abstract: Hypoplastic left heart syndrome (HLHS) is a severe congenital heart disease (CHD) affecting 1 in 5000 newborns. We constructed the interactome of 74 HLHS-associated genes identified from a large-scale mouse mutagenesis screen, augmenting it with 408 ... ...

Abstract	Hypoplastic left heart syndrome (HLHS) is a severe congenital heart disease (CHD) affecting 1 in 5000 newborns. We constructed the interactome of 74 HLHS-associated genes identified from a large-scale mouse mutagenesis screen, augmenting it with 408 novel protein-protein interactions (PPIs) using our High-Precision Protein-Protein Interaction Prediction (HiPPIP) model. The interactome is available on a webserver with advanced search capabilities. A total of 364 genes including 73 novel interactors were differentially regulated in tissue/iPSC-derived cardiomyocytes of HLHS patients. Novel PPIs facilitated the identification of TOR signaling and endoplasmic reticulum stress modules. We found that 60.5% of the interactome consisted of housekeeping genes that may harbor large-effect mutations and drive HLHS etiology but show limited transmission. Network proximity of diabetes, Alzheimer's disease, and liver carcinoma-associated genes to HLHS genes suggested a mechanistic basis for their comorbidity with HLHS. Interactome genes showed tissue-specificity for sites of extracardiac anomalies (placenta, liver and brain). The HLHS interactome shared significant overlaps with the interactomes of ciliopathy- and microcephaly-associated genes, with the shared genes enriched for genes involved in intellectual disability and/or developmental delay, and neuronal death pathways, respectively. This supported the increased burden of ciliopathy variants and prevalence of neurological abnormalities observed among HLHS patients with developmental delay and microcephaly, respectively.
MeSH term(s)	Animals ; Ciliopathies/metabolism ; Humans ; Hypoplastic Left Heart Syndrome/genetics ; Hypoplastic Left Heart Syndrome/metabolism ; Induced Pluripotent Stem Cells/metabolism ; Infant, Newborn ; Mice ; Microcephaly/genetics ; Microcephaly/metabolism ; Myocytes, Cardiac/metabolism ; Nervous System Malformations
Language	English
Publishing date	2022-04-01
Publishing country	Switzerland
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes13040627
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Article: A reference catalog of DNA palindromes in the human genome and their variations in 1000 Genomes.

Ganapathiraju, Madhavi K / Subramanian, Sandeep / Chaparala, Srilakshmi / Karunakaran, Kalyani B

Human genome variation

2020 Volume 7, Issue 1, Page(s) 40

Abstract: A palindrome in DNA is like a palindrome in language, but when read backwards, it is a complement of the forward sequence; effectively, the two halves of a sequence complement each other from its midpoint like in a double strand of DNA. Palindromes are ... ...

Abstract	A palindrome in DNA is like a palindrome in language, but when read backwards, it is a complement of the forward sequence; effectively, the two halves of a sequence complement each other from its midpoint like in a double strand of DNA. Palindromes are distributed throughout the human genome and play significant roles in gene expression and regulation. Palindromic mutations are linked to many human diseases, such as neuronal disorders, mental retardation, and various cancers. In this work, we computed and analyzed the palindromic sequences in the human genome and studied their conservation in personal genomes using 1000 Genomes data. We found that ~30% of the palindromes exhibit variation, some of which are caused by rare variants. The analysis of disease/trait-associated single-nucleotide polymorphisms in palindromic regions showed that disease-associated risk variants are 14 times more likely to be present in palindromic regions than in other regions. The catalog of palindromes in the reference genome and 1000 Genomes is being made available here with details on their variations in each individual genome to serve as a resource for future and retrospective whole-genome studies identifying statistically significant palindrome variations associated with diseases or traits and their roles in disease mechanisms.
Language	English
Publishing date	2020-11-20
Publishing country	England
Document type	Journal Article
ISSN	2054-345X
ISSN	2054-345X
DOI	10.1038/s41439-020-00127-5
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Article ; Online: Potentially repurposable drugs for schizophrenia identified from its interactome.

Karunakaran, Kalyani B / Chaparala, Srilakshmi / Ganapathiraju, Madhavi K

Scientific reports

2019 Volume 9, Issue 1, Page(s) 12682

Abstract: We previously presented the protein-protein interaction network of schizophrenia associated genes, and from it, the drug-protein interactome which showed the drugs that target any of the proteins in the interactome. Here, we studied these drugs further ... ...

Abstract	We previously presented the protein-protein interaction network of schizophrenia associated genes, and from it, the drug-protein interactome which showed the drugs that target any of the proteins in the interactome. Here, we studied these drugs further to identify whether any of them may potentially be repurposable for schizophrenia. In schizophrenia, gene expression has been described as a measurable aspect of the disease reflecting the action of risk genes. We studied each of the drugs from the interactome using the BaseSpace Correlation Engine, and shortlisted those that had a negative correlation with differential gene expression of schizophrenia. This analysis resulted in 12 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for schizophrenia (disorder versus normal). Some of these drugs were already being tested for their clinical activity in schizophrenia and other neuropsychiatric disorders. Several proteins in the protein interactome of the targets of several of these drugs were associated with various neuropsychiatric disorders. The network of genes with opposite drug-induced versus schizophrenia-associated expression profiles were significantly enriched in pathways relevant to schizophrenia etiology and GWAS genes associated with traits or diseases that had a pathophysiological overlap with schizophrenia. Drugs that targeted the same genes as the shortlisted drugs, have also demonstrated clinical activity in schizophrenia and other related disorders. This integrated computational analysis will help translate insights from the schizophrenia drug-protein interactome to clinical research - an important step, especially in the field of psychiatric drug development which faces a high failure rate.
MeSH term(s)	Acetazolamide/chemistry ; Acetazolamide/metabolism ; Acetazolamide/therapeutic use ; Anticonvulsants/chemistry ; Anticonvulsants/metabolism ; Anticonvulsants/therapeutic use ; Carbonic Anhydrases/chemistry ; Carbonic Anhydrases/metabolism ; Drug Repositioning ; Gene Expression Regulation ; Genome-Wide Association Study ; Humans ; Hydroxycholecalciferols/chemistry ; Hydroxycholecalciferols/metabolism ; Hydroxycholecalciferols/therapeutic use ; Protein Interaction Maps/genetics ; Receptors, Calcitriol/chemistry ; Receptors, Calcitriol/metabolism ; Schizophrenia/drug therapy ; Schizophrenia/pathology
Chemical Substances	Anticonvulsants ; Hydroxycholecalciferols ; Receptors, Calcitriol ; Carbonic Anhydrases (EC 4.2.1.1) ; Acetazolamide (O3FX965V0I) ; alfacalcidol (URQ2517572)
Language	English
Publishing date	2019-09-03
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-019-48307-w
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Article ; Online: Cilia interactome with predicted protein-protein interactions reveals connections to Alzheimer's disease, aging and other neuropsychiatric processes.

Karunakaran, Kalyani B / Chaparala, Srilakshmi / Lo, Cecilia W / Ganapathiraju, Madhavi K

Scientific reports

2020 Volume 10, Issue 1, Page(s) 15629

Abstract: Cilia are dynamic microtubule-based organelles present on the surface of many eukaryotic cell types and can be motile or non-motile primary cilia. Cilia defects underlie a growing list of human disorders, collectively called ciliopathies, with ... ...

Abstract	Cilia are dynamic microtubule-based organelles present on the surface of many eukaryotic cell types and can be motile or non-motile primary cilia. Cilia defects underlie a growing list of human disorders, collectively called ciliopathies, with overlapping phenotypes such as developmental delays and cognitive and memory deficits. Consistent with this, cilia play an important role in brain development, particularly in neurogenesis and neuronal migration. These findings suggest that a deeper systems-level understanding of how ciliary proteins function together may provide new mechanistic insights into the molecular etiologies of nervous system defects. Towards this end, we performed a protein-protein interaction (PPI) network analysis of known intraflagellar transport, BBSome, transition zone, ciliary membrane and motile cilia proteins. Known PPIs of ciliary proteins were assembled from online databases. Novel PPIs were predicted for each ciliary protein using a computational method we developed, called High-precision PPI Prediction (HiPPIP) model. The resulting cilia "interactome" consists of 165 ciliary proteins, 1,011 known PPIs, and 765 novel PPIs. The cilia interactome revealed interconnections between ciliary proteins, and their relation to several pathways related to neuropsychiatric processes, and to drug targets. Approximately 184 genes in the cilia interactome are targeted by 548 currently approved drugs, of which 103 are used to treat various diseases of nervous system origin. Taken together, the cilia interactome presented here provides novel insights into the relationship between ciliary protein dysfunction and neuropsychiatric disorders, for e.g. interconnections of Alzheimer's disease, aging and cilia genes. These results provide the framework for the rational design of new therapeutic agents for treatment of ciliopathies and neuropsychiatric disorders.
MeSH term(s)	Aging/physiology ; Alzheimer Disease/metabolism ; Alzheimer Disease/pathology ; Cilia/metabolism ; Cilia/pathology ; Ciliopathies/metabolism ; Ciliopathies/pathology ; Computational Biology ; Humans ; Nervous System Diseases/metabolism ; Nervous System Diseases/pathology ; Protein Interaction Maps ; Protein Transport
Language	English
Publishing date	2020-09-24
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-020-72024-4
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Article ; Online: Generalized and social anxiety disorder interactomes show distinctive overlaps with striosome and matrix interactomes.

Karunakaran, Kalyani B / Amemori, Satoko / Balakrishnan, N / Ganapathiraju, Madhavi K / Amemori, Ken-Ichi

Scientific reports

2021 Volume 11, Issue 1, Page(s) 18392

Abstract: Mechanisms underlying anxiety disorders remain elusive despite the discovery of several associated genes. We constructed the protein-protein interaction networks (interactomes) of six anxiety disorders and noted enrichment for striatal expression among ... ...

Abstract	Mechanisms underlying anxiety disorders remain elusive despite the discovery of several associated genes. We constructed the protein-protein interaction networks (interactomes) of six anxiety disorders and noted enrichment for striatal expression among common genes in the interactomes. Five of these interactomes shared distinctive overlaps with the interactomes of genes that were differentially expressed in two striatal compartments (striosomes and matrix). Generalized anxiety disorder and social anxiety disorder interactomes showed exclusive and statistically significant overlaps with the striosome and matrix interactomes, respectively. Systematic gene expression analysis with the anxiety disorder interactomes constrained to contain only those genes that were shared with striatal compartment interactomes revealed a bifurcation among the disorders, which was influenced by the anterior cingulate cortex, nucleus accumbens, amygdala and hippocampus, and the dopaminergic signaling pathway. Our results indicate that the functionally distinct striatal pathways constituted by the striosome and the matrix may influence the etiological differentiation of various anxiety disorders.
MeSH term(s)	Anxiety/etiology ; Anxiety/metabolism ; Biomarkers ; Connectome ; Corpus Striatum/metabolism ; Cytidine Deaminase/genetics ; Cytidine Deaminase/metabolism ; Disease Susceptibility ; Gene Expression Profiling ; Gene Expression Regulation ; Gene Regulatory Networks ; Humans ; Neural Pathways ; Phobia, Social/etiology ; Phobia, Social/metabolism ; Protein Interaction Mapping ; Protein Interaction Maps ; Signal Transduction
Chemical Substances	Biomarkers ; AICDA (activation-induced cytidine deaminase) (EC 3.5.4.-) ; Cytidine Deaminase (EC 3.5.4.5)
Language	English
Publishing date	2021-09-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-97418-w
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