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Keszler G, Vékony B, Elek Z, Nemoda Z, Angyal N, Bánlaki Z, Kovács-Nagy R, Rónai Z, Réthelyi JM. MicroRNA-Mediated Suppression of Glial Cell Line-Derived Neurotrophic Factor Expression Is Modulated by a Schizophrenia-Associated Non-Coding Polymorphism. Int J Mol Sci 2024; 25:4477. [PMID: 38674063 PMCID: PMC11050407 DOI: 10.3390/ijms25084477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/15/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Plasma levels of glial cell line-derived neurotrophic factor (GDNF), a pivotal regulator of differentiation and survival of dopaminergic neurons, are reportedly decreased in schizophrenia. To explore the involvement of GDNF in the pathogenesis of the disease, a case-control association analysis was performed between five non-coding single nucleotide polymorphisms (SNP) across the GDNF gene and schizophrenia. Of them, the 'G' allele of the rs11111 SNP located in the 3' untranslated region (3'-UTR) of the gene was found to associate with schizophrenia. In silico analysis revealed that the rs11111 'G' allele might create binding sites for three microRNA (miRNA) species. To explore the significance of this polymorphism, transient co-transfection assays were performed in human embryonic kidney 293T (HEK293T) cells with a luciferase reporter construct harboring either the 'A' or 'G' allele of the 3'-UTR of GDNF in combination with the hsa-miR-1185-1-3p pre-miRNA. It was demonstrated that in the presence of the rs11111 'G' (but not the 'A') allele, hsa-miR-1185-2-3p repressed luciferase activity in a dose-dependent manner. Deletion of the miRNA binding site or its substitution with the complementary sequence abrogated the modulatory effect. Our results imply that the rs11111 'G' allele occurring more frequently in patients with schizophrenia might downregulate GDNF expression in a miRNA-dependent fashion.
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Affiliation(s)
- Gergely Keszler
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, 1094 Budapest, Hungary; (Z.E.); (Z.N.); (N.A.); (Z.B.); (R.K.-N.); (Z.R.)
| | - Bálint Vékony
- Doctoral School, Semmelweis University, 1085 Budapest, Hungary;
| | - Zsuzsanna Elek
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, 1094 Budapest, Hungary; (Z.E.); (Z.N.); (N.A.); (Z.B.); (R.K.-N.); (Z.R.)
| | - Zsófia Nemoda
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, 1094 Budapest, Hungary; (Z.E.); (Z.N.); (N.A.); (Z.B.); (R.K.-N.); (Z.R.)
| | - Nóra Angyal
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, 1094 Budapest, Hungary; (Z.E.); (Z.N.); (N.A.); (Z.B.); (R.K.-N.); (Z.R.)
| | - Zsófia Bánlaki
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, 1094 Budapest, Hungary; (Z.E.); (Z.N.); (N.A.); (Z.B.); (R.K.-N.); (Z.R.)
| | - Réka Kovács-Nagy
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, 1094 Budapest, Hungary; (Z.E.); (Z.N.); (N.A.); (Z.B.); (R.K.-N.); (Z.R.)
| | - Zsolt Rónai
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, 1094 Budapest, Hungary; (Z.E.); (Z.N.); (N.A.); (Z.B.); (R.K.-N.); (Z.R.)
| | - János M. Réthelyi
- Department of Psychiatry and Psychotherapy, Semmelweis University, 1083 Budapest, Hungary;
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2
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Eysert F, Coulon A, Boscher E, Vreulx AC, Flaig A, Mendes T, Hughes S, Grenier-Boley B, Hanoulle X, Demiautte F, Bauer C, Marttinen M, Takalo M, Amouyel P, Desai S, Pike I, Hiltunen M, Chécler F, Farinelli M, Delay C, Malmanche N, Hébert SS, Dumont J, Kilinc D, Lambert JC, Chapuis J. Alzheimer's genetic risk factor FERMT2 (Kindlin-2) controls axonal growth and synaptic plasticity in an APP-dependent manner. Mol Psychiatry 2021; 26:5592-5607. [PMID: 33144711 PMCID: PMC8758496 DOI: 10.1038/s41380-020-00926-w] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 10/02/2020] [Accepted: 10/19/2020] [Indexed: 12/24/2022]
Abstract
Although APP metabolism is being intensively investigated, a large fraction of its modulators is yet to be characterized. In this context, we combined two genome-wide high-content screenings to assess the functional impact of miRNAs and genes on APP metabolism and the signaling pathways involved. This approach highlighted the involvement of FERMT2 (or Kindlin-2), a genetic risk factor of Alzheimer's disease (AD), as a potential key modulator of axon guidance, a neuronal process that depends on the regulation of APP metabolism. We found that FERMT2 directly interacts with APP to modulate its metabolism, and that FERMT2 underexpression impacts axonal growth, synaptic connectivity, and long-term potentiation in an APP-dependent manner. Last, the rs7143400-T allele, which is associated with an increased AD risk and localized within the 3'UTR of FERMT2, induced a downregulation of FERMT2 expression through binding of miR-4504 among others. This miRNA is mainly expressed in neurons and significantly overexpressed in AD brains compared to controls. Altogether, our data provide strong evidence for a detrimental effect of FERMT2 underexpression in neurons and insight into how this may influence AD pathogenesis.
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Affiliation(s)
- Fanny Eysert
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Audrey Coulon
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Emmanuelle Boscher
- Centre de Recherche du CHU de Québec-Université Laval, CHUL, Axe Neurosciences, Québec City, QC, Canada
- Faculté de Médecine, Département de Psychiatrie et de Neurosciences, Université Laval, Québec City, QC, Canada
| | - Anaїs-Camille Vreulx
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Amandine Flaig
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Tiago Mendes
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Sandrine Hughes
- E-Phy-Science, Bioparc de Sophia Antipolis, 2400 route des Colles, Biot, 06410, France
| | - Benjamin Grenier-Boley
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Xavier Hanoulle
- Université de Lille, CNRS, UMR8576-Labex DISTALZ, Villeneuve d'Ascq, 59655, France
| | - Florie Demiautte
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Charlotte Bauer
- Université Côte d'Azur, Inserm, CNRS, IPMC, DistAlz Laboratory of Excellence, Valbonne, France
| | - Mikael Marttinen
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Mari Takalo
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Philippe Amouyel
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Shruti Desai
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Ian Pike
- Proteome Sciences plc, Hamilton House, London, WC1H 9BB, UK
| | - Mikko Hiltunen
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Frédéric Chécler
- Université Côte d'Azur, Inserm, CNRS, IPMC, DistAlz Laboratory of Excellence, Valbonne, France
| | - Mélissa Farinelli
- E-Phy-Science, Bioparc de Sophia Antipolis, 2400 route des Colles, Biot, 06410, France
| | - Charlotte Delay
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Nicolas Malmanche
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Sébastien S Hébert
- Centre de Recherche du CHU de Québec-Université Laval, CHUL, Axe Neurosciences, Québec City, QC, Canada
- Faculté de Médecine, Département de Psychiatrie et de Neurosciences, Université Laval, Québec City, QC, Canada
| | - Julie Dumont
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Devrim Kilinc
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Jean-Charles Lambert
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France
| | - Julien Chapuis
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, 59019, France.
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3
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Boscher E, Husson T, Quenez O, Laquerrière A, Marguet F, Cassinari K, Wallon D, Martinaud O, Charbonnier C, Nicolas G, Deleuze JF, Boland A, Lathrop M, Frébourg T, Campion D, Hébert SS, Rovelet-Lecrux A. Copy Number Variants in miR-138 as a Potential Risk Factor for Early-Onset Alzheimer's Disease. J Alzheimers Dis 2020; 68:1243-1255. [PMID: 30909216 DOI: 10.3233/jad-180940] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) accounts for 5-10% of all AD cases, with a heritability ranging between 92% to 100%. With the exception of rare mutations in APP, PSEN1, and PSEN2 genes causing autosomal dominant EOAD, little is known about the genetic factors underlying most of the EOAD cases. In this study, we hypothesized that copy number variations (CNVs) in microRNA (miR) genes could contribute to risk for EOAD. miRs are short non-coding RNAs previously implicated in the regulation of AD-related genes and phenotypes. Using whole exome sequencing, we screened a series of 546 EOAD patients negative for autosomal dominant EOAD mutations and 597 controls. We identified 86 CNVs in miR genes of which 31 were exclusive to EOAD cases, including a duplication of the MIR138-2 locus. In functional studies in human cultured cells, we could demonstrate that miR-138 overexpression leads to higher Aβ production as well as tau phosphorylation, both implicated in AD pathophysiology. These changes were mediated in part by GSK-3β and FERMT2, a potential risk factor for AD. Additional disease-related genes were also prone to miR-138 regulation including APP and BACE1. This study suggests that increased gene dosage of MIR138-2 could contribute to risk for EOAD by regulating different biological pathways implicated in amyloid and tau metabolism. Additional studies are now required to better understand the role of miR-CNVs in EOAD.
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Affiliation(s)
- Emmanuelle Boscher
- Centre de recherche du CHU de Québec-Université Laval, CHUL, Axe Neurosciences, Québec, Canada.,Faculté de médecine, Département de psychiatrie et de neurosciences, Université Laval, Québec, Canada
| | - Thomas Husson
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - Olivier Quenez
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - Annie Laquerrière
- Department of Pathology, Normandie Univ, UNIROUEN, Rouen University Hospital, Rouen, France
| | - Florent Marguet
- Department of Pathology, Normandie Univ, UNIROUEN, Rouen University Hospital, Rouen, France
| | - Kevin Cassinari
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - David Wallon
- Department of Neurology and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - Olivier Martinaud
- Normandie Univ, UNICAEN, EPHE, INSERM, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Camille Charbonnier
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - Gaël Nicolas
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - Jean-François Deleuze
- Centre National de recherche en Génomique Humaine, Institut de Génomique, CEA, Evry, France
| | - Anne Boland
- Centre National de recherche en Génomique Humaine, Institut de Génomique, CEA, Evry, France
| | - Mark Lathrop
- McGill University and Génome Québec Innovation Centre, Montréal, Canada
| | - Thierry Frébourg
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | | | - Dominique Campion
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - Sébastien S Hébert
- Centre de recherche du CHU de Québec-Université Laval, CHUL, Axe Neurosciences, Québec, Canada.,Faculté de médecine, Département de psychiatrie et de neurosciences, Université Laval, Québec, Canada
| | - Anne Rovelet-Lecrux
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, Rouen, France
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4
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Verheijen J, Sleegers K. Understanding Alzheimer Disease at the Interface between Genetics and Transcriptomics. Trends Genet 2018; 34:434-447. [PMID: 29573818 DOI: 10.1016/j.tig.2018.02.007] [Citation(s) in RCA: 125] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Revised: 02/20/2018] [Accepted: 02/26/2018] [Indexed: 12/21/2022]
Abstract
Over 25 genes are known to affect the risk of developing Alzheimer disease (AD), the most common neurodegenerative dementia. However, mechanistic insights and improved disease management remains limited, due to difficulties in determining the functional consequences of genetic associations. Transcriptomics is increasingly being used to corroborate or enhance interpretation of genetic discoveries. These approaches, which include second and third generation sequencing, single-cell sequencing, and bioinformatics, reveal allele-specific events connecting AD risk genes to expression profiles, and provide converging evidence of pathophysiological pathways underlying AD. Simultaneously, they highlight brain region- and cell-type-specific expression patterns, and alternative splicing events that affect the straightforward relation between a genetic variant and AD, re-emphasizing the need for an integrated approach of genetics and transcriptomics in understanding AD.
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Affiliation(s)
- Jan Verheijen
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, B-2610, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, B-2610, Belgium
| | - Kristel Sleegers
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, B-2610, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, B-2610, Belgium.
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5
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Abstract
Genome-wide association studies (GWASs) discovered a number of SNPs and genes associated with Alzheimer's disease (AD). However, how these SNPs and genes influence the liability to AD is not fully understood. We deployed computational approaches to explore the function and action mechanisms of AD -related SNPs and genes identified by GWASs, including the effects of 195 GWAS lead SNPs and 338 proxy SNPs on miRNAs binding and protein phosphorylation, their RegulomeDB and 3DSNP scores, and gene ontology, pathway enrichment and protein-protein interaction network of 126 AD-associated genes. Our computational analysis identified 6 lead SNPs (rs10119, rs1048699, rs148763909, rs610932, rs6857 and rs714948) and 2 proxy SNPs (rs12539172 and rs2847655) that potentially impacted the miRNA binding. Lead SNP rs2296160 and proxy SNPs rs679620 and rs2228145 were identified as PhosSNPs potentially influencing protein phosphorylation. AD-associated genes showed enrichment of “regulation of beta-amyloid formation”, “regulation of neurofibrillary tangle assembly”, “leukocyte mediated immunity” and “protein-lipid complex assembly” signaling pathway. Protein-protein interaction network and functional module analyses identified highly-interconnected “hub” genes (APOE, PICALM, BIN1, ABCA7, CD2AP, CLU, CR1, MS4A4E and MS4A6A) and bottleneck genes (APOE, TOMM40, NME8, PICALM, CD2AP, ZCWPW1, FAM180B, GAB2 and PTK2B) that created three tight subnetworks. Our results provided the targets for further experimental assessment and further insight on AD pathophysiology.
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Affiliation(s)
- Zengpeng Han
- School of Life Sciences, Central China Normal University, Wuhan, China
| | - Han Huang
- School of Life Sciences, Central China Normal University, Wuhan, China
| | - Yue Gao
- School of Life Sciences, Central China Normal University, Wuhan, China
| | - Qingyang Huang
- School of Life Sciences, Central China Normal University, Wuhan, China
- * E-mail:
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Genome-wide, high-content siRNA screening identifies the Alzheimer's genetic risk factor FERMT2 as a major modulator of APP metabolism. Acta Neuropathol 2017; 133:955-966. [PMID: 27933404 PMCID: PMC5427165 DOI: 10.1007/s00401-016-1652-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 11/29/2016] [Accepted: 11/29/2016] [Indexed: 10/30/2022]
Abstract
Genome-wide association studies (GWASs) have identified 19 susceptibility loci for Alzheimer's disease (AD). However, understanding how these genes are involved in the pathophysiology of AD is one of the main challenges of the "post-GWAS" era. At least 123 genes are located within the 19 susceptibility loci; hence, a conventional approach (studying the genes one by one) would not be time- and cost-effective. We therefore developed a genome-wide, high-content siRNA screening approach and used it to assess the functional impact of gene under-expression on APP metabolism. We found that 832 genes modulated APP metabolism. Eight of these genes were located within AD susceptibility loci. Only FERMT2 (a β3-integrin co-activator) was also significantly associated with a variation in cerebrospinal fluid Aβ peptide levels in 2886 AD cases. Lastly, we showed that the under-expression of FERMT2 increases Aβ peptide production by raising levels of mature APP at the cell surface and facilitating its recycling. Taken as a whole, our data suggest that FERMT2 modulates the AD risk by regulating APP metabolism and Aβ peptide production.
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Roy J, Mallick B. Altered gene expression in late-onset Alzheimer's disease due to SNPs within 3'UTR microRNA response elements. Genomics 2017; 109:177-185. [PMID: 28286146 DOI: 10.1016/j.ygeno.2017.02.006] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Revised: 02/24/2017] [Accepted: 02/27/2017] [Indexed: 01/26/2023]
Abstract
Late-onset Alzheimer's disease (LOAD) is a progressive and fatal neurodegenerative disease found in people older than 65years of age. Disease etiology is complex, as susceptibility has been linked to multiple gene variants conferred by single nucleotide polymorphisms (SNPs). However, the molecular mechanisms by which SNPs contribute to LOAD pathogenesis have not been extensively studied, particularly for SNPs within the 3' untranslated regions (3'UTRs), the hubs for microRNA binding. Therefore, we screened for SNPs within the 3'UTRs of LOAD-associated genes that may create or destroy microRNA response elements (MREs) and thus alter gene expression. This investigation adopted an in-silico approach that integrated structural and thermodynamic features of miRNA target binding with screening using CLIP-seq data, followed by network analysis. This strategy identified three 3'UTR SNPs, rs10876135, rs5848, and rs5786996 that may alter the respective binding sites for the miRNAs hsa-miR-197-5p, hsa-miR-185-5p, and hsa-miR-34a-5p, all of which are upregulated in LOAD. The functional significance of these MRE-SNPs was assessed by potential regulation of biological networks known to be associated with LOAD. This is the first study to demonstrate a possible role for above 3'UTR MRE-SNPs in aberrant expression of target genes with functional consequences for LOAD.
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Affiliation(s)
- Jyoti Roy
- RNAi & Functional Genomics Lab, Department of Life Science, National Institute of Technology, Rourkela 769008, Odisha, India
| | - Bibekanand Mallick
- RNAi & Functional Genomics Lab, Department of Life Science, National Institute of Technology, Rourkela 769008, Odisha, India.
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microRNA-132/212 deficiency enhances Aβ production and senile plaque deposition in Alzheimer's disease triple transgenic mice. Sci Rep 2016; 6:30953. [PMID: 27484949 PMCID: PMC4971468 DOI: 10.1038/srep30953] [Citation(s) in RCA: 91] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Accepted: 07/11/2016] [Indexed: 01/02/2023] Open
Abstract
The abnormal regulation of amyloid-β (Aβ) metabolism (e.g., production, cleavage, clearance) plays a central role in Alzheimer’s disease (AD). Among endogenous factors believed to participate in AD progression are the small regulatory non-coding microRNAs (miRs). In particular, the miR-132/212 cluster is severely reduced in the AD brain. In previous studies we have shown that miR-132/212 deficiency in mice leads to impaired memory and enhanced Tau pathology as seen in AD patients. Here we demonstrate that the genetic deletion of miR-132/212 promotes Aβ production and amyloid (senile) plaque formation in triple transgenic AD (3xTg-AD) mice. Using RNA-Seq and bioinformatics, we identified genes of the miR-132/212 network with documented roles in the regulation of Aβ metabolism, including Tau, Mapk, and Sirt1. Consistent with these findings, we show that the modulation of miR-132, or its target Sirt1, can directly regulate Aβ production in cells. Finally, both miR-132 and Sirt1 levels correlated with Aβ load in humans. Overall, our results support the hypothesis that the miR-132/212 network, including Sirt1 and likely other target genes, contributes to abnormal Aβ metabolism and senile plaque deposition in AD. This study strengthens the importance of miR-dependent networks in neurodegenerative disorders, and opens the door to multifactorial drug targets of AD by targeting Aβ and Tau.
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