1
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Cocoș R, Popescu BO. Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens. Hum Genomics 2024; 18:141. [PMID: 39736681 DOI: 10.1186/s40246-024-00704-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2024] [Accepted: 12/10/2024] [Indexed: 01/01/2025] Open
Abstract
Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.
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Affiliation(s)
- Relu Cocoș
- Department of Medical Genetics, 'Carol Davila' University of Medicine and Pharmacy, Bucharest, Romania.
- Genomics Research and Development Institute, Bucharest, Romania.
| | - Bogdan Ovidiu Popescu
- Department of Clinical Neurosciences, 'Carol Davila' University of Medicine and Pharmacy, Bucharest, Romania.
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2
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Shade LMP, Katsumata Y, Abner EL, Aung KZ, Claas SA, Qiao Q, Heberle BA, Brandon JA, Page ML, Hohman TJ, Mukherjee S, Mayeux RP, Farrer LA, Schellenberg GD, Haines JL, Kukull WA, Nho K, Saykin AJ, Bennett DA, Schneider JA, Ebbert MTW, Nelson PT, Fardo DW. GWAS of multiple neuropathology endophenotypes identifies new risk loci and provides insights into the genetic risk of dementia. Nat Genet 2024; 56:2407-2421. [PMID: 39379761 PMCID: PMC11549054 DOI: 10.1038/s41588-024-01939-9] [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: 05/05/2023] [Accepted: 08/30/2024] [Indexed: 10/10/2024]
Abstract
Genome-wide association studies (GWAS) have identified >80 Alzheimer's disease and related dementias (ADRD)-associated genetic loci. However, the clinical outcomes used in most previous studies belie the complex nature of underlying neuropathologies. Here we performed GWAS on 11 ADRD-related neuropathology endophenotypes with participants drawn from the following three sources: the National Alzheimer's Coordinating Center, the Religious Orders Study and Rush Memory and Aging Project, and the Adult Changes in Thought study (n = 7,804 total autopsied participants). We identified eight independent significantly associated loci, of which four were new (COL4A1, PIK3R5, LZTS1 and APOC2). Separately testing known ADRD loci, 19 loci were significantly associated with at least one neuropathology after false-discovery rate adjustment. Genetic colocalization analyses identified pleiotropic effects and quantitative trait loci. Methylation in the cerebral cortex at two sites near APOC2 was associated with cerebral amyloid angiopathy. Studies that include neuropathology endophenotypes are an important step in understanding the mechanisms underlying genetic ADRD risk.
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Affiliation(s)
- Lincoln M P Shade
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Yuriko Katsumata
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
| | - Erin L Abner
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Epidemiology and Environmental Health, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Khine Zin Aung
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
| | - Steven A Claas
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Qi Qiao
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
| | - Bernardo Aguzzoli Heberle
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
| | - J Anthony Brandon
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Madeline L Page
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Richard P Mayeux
- Department of Neurology, Columbia University, New York City, NY, USA
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- Department of Ophthalmology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Department of Epidemiology, School of Public Health, Boston University, Boston, MA, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jonathan L Haines
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Walter A Kukull
- National Alzheimer's Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - David A Bennett
- Department of Neurological Sciences, Rush Medical College, Chicago, IL, USA
- Rush Alzheimer's Disease Center, Rush Medical College, Chicago, IL, USA
| | - Julie A Schneider
- Department of Neurological Sciences, Rush Medical College, Chicago, IL, USA
- Rush Alzheimer's Disease Center, Rush Medical College, Chicago, IL, USA
- Department of Pathology, Rush Medical College, Chicago, IL, USA
| | - Mark T W Ebbert
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
- Division of Biomedical Informatics, Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Peter T Nelson
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA
- Department of Pathology and Laboratory Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - David W Fardo
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA.
- Sanders-Brown Center on Aging and Alzheimer's Disease Research Center, University of Kentucky, Lexington, KY, USA.
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3
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Nomura F, Shimizu A, Togi S, Ura H, Niida Y. SNP Array Screening and Long Range PCR-Based Targeted Next Generation Sequencing for Autosomal Recessive Disease with Consanguinity: Insight from a Case of Xeroderma Pigmentosum Group C. Genes (Basel) 2023; 14:2079. [PMID: 38003022 PMCID: PMC10671442 DOI: 10.3390/genes14112079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 10/30/2023] [Accepted: 11/13/2023] [Indexed: 11/26/2023] Open
Abstract
Advances in genetic technologies have made genetic testing more accessible than ever before. However, depending on national, regional, legal, and health insurance circumstances, testing procedures may still need to be streamlined in real-world clinical practice. In cases of autosomal recessive disease with consanguinity, the mutation locus is necessarily isodisomy because both alleles originate from a common ancestral chromosome. Based on this premise, we implemented integrated genetic diagnostic methods using SNP array screening and long range PCR-based targeted NGS in a Japanese patient with xeroderma pigmentosum (XP) under the limitation of the national health insurance system. SNP array results showed isodisomy only in XPC and ERCC4 loci. NGS, with a minimal set of long-range PCR primers, detected a homozygous frameshift mutation in XPC; NM_004628.5:c.218_219insT p.(Lys73AsnfsTer9), confirmed by Sanger sequencing, leading to a rapid diagnosis of XP group C. This shortcut strategy is applicable to all autosomal recessive diseases caused by consanguineous marriages, especially in scenarios with a moderate number of genes to test, a common occurrence in clinical genetic practice.
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Affiliation(s)
- Fumie Nomura
- Department of Dermatology, Kanazawa Medical University, Uchinada 920-0293, Japan (A.S.)
| | - Akira Shimizu
- Department of Dermatology, Kanazawa Medical University, Uchinada 920-0293, Japan (A.S.)
| | - Sumihito Togi
- Center for Clinical Genomics, Kanazawa Medical University Hospital, Uchinada 920-0293, Japan (H.U.)
- Department of Advanced Medicine, Division of Genomic Medicine, Medical Research Institute, Kanazawa Medical University, Uchinada 920-0293, Japan
| | - Hiroki Ura
- Center for Clinical Genomics, Kanazawa Medical University Hospital, Uchinada 920-0293, Japan (H.U.)
- Department of Advanced Medicine, Division of Genomic Medicine, Medical Research Institute, Kanazawa Medical University, Uchinada 920-0293, Japan
| | - Yo Niida
- Center for Clinical Genomics, Kanazawa Medical University Hospital, Uchinada 920-0293, Japan (H.U.)
- Department of Advanced Medicine, Division of Genomic Medicine, Medical Research Institute, Kanazawa Medical University, Uchinada 920-0293, Japan
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Nott A, Holtman IR. Genetic insights into immune mechanisms of Alzheimer's and Parkinson's disease. Front Immunol 2023; 14:1168539. [PMID: 37359515 PMCID: PMC10285485 DOI: 10.3389/fimmu.2023.1168539] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/17/2023] [Indexed: 06/28/2023] Open
Abstract
Microglia, the macrophages of the brain, are vital for brain homeostasis and have been implicated in a broad range of brain disorders. Neuroinflammation has gained traction as a possible therapeutic target for neurodegeneration, however, the precise function of microglia in specific neurodegenerative disorders is an ongoing area of research. Genetic studies offer valuable insights into understanding causality, rather than merely observing a correlation. Genome-wide association studies (GWAS) have identified many genetic loci that are linked to susceptibility to neurodegenerative disorders. (Post)-GWAS studies have determined that microglia likely play an important role in the development of Alzheimer's disease (AD) and Parkinson's disease (PD). The process of understanding how individual GWAS risk loci affect microglia function and mediate susceptibility is complex. A rapidly growing number of publications with genomic datasets and computational tools have formulated new hypotheses that guide the biological interpretation of AD and PD genetic risk. In this review, we discuss the key concepts and challenges in the post-GWAS interpretation of AD and PD GWAS risk alleles. Post-GWAS challenges include the identification of target cell (sub)type(s), causal variants, and target genes. Crucially, the prediction of GWAS-identified disease-risk cell types, variants and genes require validation and functional testing to understand the biological consequences within the pathology of the disorders. Many AD and PD risk genes are highly pleiotropic and perform multiple important functions that might not be equally relevant for the mechanisms by which GWAS risk alleles exert their effect(s). Ultimately, many GWAS risk alleles exert their effect by changing microglia function, thereby altering the pathophysiology of these disorders, and hence, we believe that modelling this context is crucial for a deepened understanding of these disorders.
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Affiliation(s)
- Alexi Nott
- Department of Brain Sciences, Imperial College London, London, United Kingdom
- UK Dementia Research Institute, Imperial College London, London, United Kingdom
| | - Inge R. Holtman
- Department of Biomedical Sciences of Cells and Systems, Section Molecular Neurobiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
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Bonacina G, Carollo A, Esposito G. The Genetic Side of the Mood: A Scientometric Review of the Genetic Basis of Mood Disorders. Genes (Basel) 2023; 14:genes14020352. [PMID: 36833279 PMCID: PMC9956267 DOI: 10.3390/genes14020352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 01/22/2023] [Accepted: 01/27/2023] [Indexed: 01/31/2023] Open
Abstract
Mood disorders are highly heritable psychiatric disorders. Over the years, many genetic polymorphisms have been identified to pose a higher risk for the development of mood disorders. To overview the literature on the genetics of mood disorders, a scientometric analysis was performed on a sample of 5342 documents downloaded from Scopus. The most active countries and the most impactful documents in the field were identified. Furthermore, a total of 13 main thematic clusters emerged in the literature. From the qualitative inspection of clusters, it emerged that the research interest moved from a monogenic to a polygenic risk framework. Researchers have moved from the study of single genes in the early 1990s to conducting genome-wide association studies around 2015. In this way, genetic overlaps between mood disorders and other psychiatric conditions emerged too. Furthermore, around the 2010s, the interaction between genes and environmental factors emerged as pivotal in understanding the risk for mood disorders. The inspection of thematic clusters provides a valuable insight into the past and recent trends of research in the genetics of mood disorders and sheds light onto future lines of research.
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Zecca C, Tortelli R, Carrera P, Dell'Abate MT, Logroscino G, Ferrari M. Genotype-phenotype correlation in the spectrum of frontotemporal dementia-parkinsonian syndromes and advanced diagnostic approaches. Crit Rev Clin Lab Sci 2022; 60:171-188. [PMID: 36510705 DOI: 10.1080/10408363.2022.2150833] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The term frontotemporal dementia (FTD) refers to a group of progressive neurodegenerative disorders characterized mainly by atrophy of the frontal and anterior temporal lobes. Based on clinical presentation, three main clinical syndromes have traditionally been described: behavioral variant frontotemporal dementia (bvFTD), non-fluent/agrammatic primary progressive aphasia (nfPPA), and semantic variant PPA (svPPA). However, over the last 20 years, it has been recognized that cognitive phenotypes often overlap with motor phenotypes, either motor neuron diseases or parkinsonian signs and/or syndromes like progressive supranuclear palsy (PSP) and cortico-basal syndrome (CBS). Furthermore, FTD-related genes are characterized by genetic pleiotropy and can cause, even in the same family, pure motor phenotypes, findings that underlie the clinical continuum of the spectrum, which has pure cognitive and pure motor phenotypes as the extremes. The genotype-phenotype correlation of the spectrum, FTD-motor neuron disease, has been well defined and extensively investigated, while the continuum, FTD-parkinsonism, lacks a comprehensive review. In this narrative review, we describe the current knowledge about the genotype-phenotype correlation of the spectrum, FTD-parkinsonism, focusing on the phenotypes that are less frequent than bvFTD, namely nfPPA, svPPA, PSP, CBS, and cognitive-motor overlapping phenotypes (i.e. PPA + PSP). From a pathological point of view, they are characterized mainly by the presence of phosphorylated-tau inclusions, either 4 R or 3 R. The genetic correlate of the spectrum can be heterogeneous, although some variants seem to lead preferentially to specific clinical syndromes. Furthermore, we critically review the contribution of genome-wide association studies (GWAS) and next-generation sequencing (NGS) in disentangling the complex heritability of the FTD-parkinsonism spectrum and in defining the genotype-phenotype correlation of the entire clinical scenario, owing to the ability of these techniques to test multiple genes, and so to allow detailed investigations of the overlapping phenotypes. Finally, we conclude with the importance of a detailed genetic characterization and we offer to patients and families the chance to be included in future randomized clinical trials focused on autosomal dominant forms of FTLD.
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Affiliation(s)
- Chiara Zecca
- Department of Clinical Research in Neurology, Center for Neurodegenerative Diseases and the Aging Brain, University of Bari "Aldo Moro", Pia Fondazione Card G. Panico Hospital, Tricase, Italy
| | - Rosanna Tortelli
- Neuroscience and Rare Diseases Discovery and Translational Area, Roche Pharma Research and Early Development, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Paola Carrera
- Unit of Genomics for Human Disease Diagnosis and Clinical Molecular Biology Laboratory, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria Teresa Dell'Abate
- Department of Clinical Research in Neurology, Center for Neurodegenerative Diseases and the Aging Brain, University of Bari "Aldo Moro", Pia Fondazione Card G. Panico Hospital, Tricase, Italy
| | - Giancarlo Logroscino
- Department of Clinical Research in Neurology, Center for Neurodegenerative Diseases and the Aging Brain, University of Bari "Aldo Moro", Pia Fondazione Card G. Panico Hospital, Tricase, Italy.,Department of Basic Medicine Sciences, Neuroscience, and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
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Santamaría-García H, Ogonowsky N, Baez S, Palacio N, Reyes P, Schulte M, López A, Matallana D, Ibanez A. Neurocognitive patterns across genetic levels in behavioral variant frontotemporal dementia: a multiple single cases study. BMC Neurol 2022; 22:454. [PMID: 36474176 PMCID: PMC9724347 DOI: 10.1186/s12883-022-02954-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/06/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Behavioral variant frontotemporal dementia (bvFTD) has been related to different genetic factors. Identifying multimodal phenotypic heterogeneity triggered by various genetic influences is critical for improving diagnosis, prognosis, and treatments. However, the specific impact of different genetic levels (mutations vs. risk variants vs. sporadic presentations) on clinical and neurocognitive phenotypes is not entirely understood, specially in patites from underrepresented regions such as Colombia. METHODS Here, in a multiple single cases study, we provide systematic comparisons regarding cognitive, neuropsychiatric, brain atrophy, and gene expression-atrophy overlap in a novel cohort of FTD patients (n = 42) from Colombia with different genetic levels, including patients with known genetic influences (G-FTD) such as those with genetic mutations (GR1) in particular genes (MAPT, TARDBP, and TREM2); patients with risk variants (GR2) in genes associated with FTD (tau Haplotypes H1 and H2 and APOE variants including ε2, ε3, ε4); and sporadic FTD patients (S-FTD (GR3)). RESULTS We found that patients from GR1 and GR2 exhibited earlier disease onset, pervasive cognitive impairments (cognitive screening, executive functioning, ToM), and increased brain atrophy (prefrontal areas, cingulated cortices, basal ganglia, and inferior temporal gyrus) than S-FTD patients (GR3). No differences in disease duration were observed across groups. Additionally, significant neuropsychiatric symptoms were observed in the GR1. The GR1 also presented more clinical and neurocognitive compromise than GR2 patients; these groups, however, did not display differences in disease onset or duration. APOE and tau patients showed more neuropsychiatric symptoms and primary atrophy in parietal and temporal cortices than GR1 patients. The gene-atrophy overlap analysis revealed atrophy in regions with specific genetic overexpression in all G-FTD patients. A differential family presentation did not explain the results. CONCLUSIONS Our results support the existence of genetic levels affecting the clinical, neurocognitive, and, to a lesser extent, neuropsychiatric presentation of bvFTD in the present underrepresented sample. These results support tailored assessments characterization based on the parallels of genetic levels and neurocognitive profiles in bvFTD.
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Affiliation(s)
- Hernando Santamaría-García
- PhD program in Neuroscience, Pontificia Universidad Javeriana, Bogotá, Colombia.
- Memory and cognition Center, Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia.
- Department of Neurology, Global Brain Health Institute, University of California San Francisco, San Francisco, CA, USA.
| | - Natalia Ogonowsky
- CONICET & Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Sandra Baez
- Faculty of Psychology, Universidad de los Andes, Bogotá, Colombia
| | - Nicole Palacio
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
| | - Pablo Reyes
- PhD program in Neuroscience, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Michael Schulte
- CONICET & Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Andrea López
- Pontificia Universidad Javeriana, Bogotá, Colombia
- Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | | | - Agustín Ibanez
- Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Santiago de Chile, Chile.
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, & National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.
- Trinity Collegue of Dublin, Dublin, Irland.
- Global Brain Health Insititute, Universidad California San Francisco-Trinity College of Dublin, San Francisco, USA.
- Global Brain Health Insititute, Universidad California San Francisco-Trinity College of Dublin, Dublin, Irland.
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Chen Z, Chu M, Liu L, Zhang J, Kong Y, Xie K, Cui Y, Ye H, Li J, Wang L, Wu L. Genetic prion diseases presenting as frontotemporal dementia: clinical features and diagnostic challenge. Alzheimers Res Ther 2022; 14:90. [PMID: 35768878 PMCID: PMC9245249 DOI: 10.1186/s13195-022-01033-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 06/22/2022] [Indexed: 11/10/2022]
Abstract
Abstract
Background
To elucidate the clinical and ancillary features of genetic prion diseases (gPrDs) presenting with frontotemporal dementia (FTD) to aid early identification.
Methods
Global data of gPrDs presenting with FTD caused by prion protein gene mutations were collected from literature review and our records. Fifty-one cases of typical FTD and 136 cases of prion diseases admitted to our institution were included as controls. Clinical and ancillary data of the different groups were compared.
Results
Forty-nine cases of gPrDs presenting with FTD were identified. Compared to FTD or prion diseases, gPrDs presenting with FTD were characterized by earlier onset age (median 45 vs. 61/60 years, P < 0.001, P < 0.001) and higher incidence of positive family history (81.6% vs. 27.5/13.2%, P < 0.001, P < 0.001). Furthermore, GPrDs presenting with FTD exhibited shorter duration (median 5 vs. 8 years) and a higher rate of parkinsonism (63.7% vs. 9.8%, P < 0.001), pyramidal signs (39.1% vs. 7.8%, P = 0.001), mutism (35.9% vs. 0%, P < 0.001), seizures (25.8% vs. 0%, P < 0.001), myoclonus (22.5% vs. 0%, P < 0.001), and hyperintensity on MRI (25.0% vs. 0, P < 0.001) compared to FTD. Compared to prion diseases, gPrDs presenting with FTD had a longer duration of symptoms (median 5 vs. 1.1 years, P < 0.001), higher rates of frontotemporal atrophy (89.7% vs. 3.3%, P < 0.001), lower rates of periodic short-wave complexes on EEG (0% vs. 30.3%, P = 0.001), and hyperintensity on MRI (25.0% vs. 83.0%, P < 0.001). The frequency of codon 129 Val allele in gPrDs presenting with FTD was significantly higher than that reported in the literature for gPrDs in the Caucasian and East Asian populations (33.3% vs. 19.2%/8.0%, P = 0.005, P < 0.001).
Conclusions
GPrDs presenting with FTD are characterized by early-onset, high incidence of positive family history, high frequency of the Val allele at codon 129, overlapping symptoms with prion disease and FTD, and ancillary features closer to FTD. PRNP mutations may be a rare cause in the FTD spectrum, and PRNP genotyping should be considered in patients with these features.
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Sawyer RP, Stone HK, Salim H, Lu X, Weirauch MT, Kottyan L. Frontotemporal degeneration genetic risk loci and transcription regulation as a possible mechanistic link to disease risk. Medicine (Baltimore) 2022; 101:e31078. [PMID: 36253972 PMCID: PMC9575772 DOI: 10.1097/md.0000000000031078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 09/12/2022] [Indexed: 11/26/2022] Open
Abstract
The etiology of Frontotemporal Degeneration (FTD) is not well understood. Genetic studies have established common genetic variants (GVs) that are associated with increased FTD risk. We review previous genome wide association studies (GWAS) of FTD and nominate specific transcriptional regulators as potential key players in the etiology of this disease. A list of GVs associated with FTD was compiled from published GWAS. The regulatory element locus intersection (RELI) tool was used to calculate the enrichment of the overlap between disease risk GVs and the genomic coordinates of data from a collection of >10,000 chromatin immunoprecipitation (ChIP-seq) experiments. After linkage disequilibrium expansion of the previously reported tag associated GVs, we identified 914 GV at 47 independent risk loci. Using the RELI algorithm, we identified several transcriptional regulators with enriched binding at FTD risk loci (0.05 < corrected P value <1.18 × 10-27), including Tripartite motif-containing 28 (TRIM28) and Chromodomain-Helicase DNA-binding 1 (CHD1) which have previously observed roles in FTD. FTD is a complex disease, and immune dysregulation has been previously implicated as a potential underlying cause. This assessment of established FTD risk loci and analysis of possible function implicates transcriptional dysregulation, and specifically particular transcriptional regulators with known roles in the immune response as important in the genetic etiology of FTD.
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Affiliation(s)
- Russell P. Sawyer
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Hillarey K. Stone
- Division of Nephrology and Hypertension, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Division of Allergy and Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - Hanan Salim
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - Xiaoming Lu
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - Matthew T. Weirauch
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Leah Kottyan
- Division of Allergy and Immunology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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10
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Kirola L, Mukherjee A, Mutsuddi M. Recent Updates on the Genetics of Amyotrophic Lateral Sclerosis and Frontotemporal Dementia. Mol Neurobiol 2022; 59:5673-5694. [PMID: 35768750 DOI: 10.1007/s12035-022-02934-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 06/16/2022] [Indexed: 10/17/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) primarily affect the motor and frontotemporal areas of the brain, respectively. These disorders share clinical, genetic, and pathological similarities, and approximately 10-15% of ALS-FTD cases are considered to be multisystemic. ALS-FTD overlaps have been linked to families carrying an expansion in the intron of C9orf72 along with inclusions of TDP-43 in the brain. Other overlapping genes (VCP, FUS, SQSTM1, TBK1, CHCHD10) are also involved in similar functions that include RNA processing, autophagy, proteasome response, protein aggregation, and intracellular trafficking. Recent advances in genome sequencing have identified new genes that are involved in these disorders (TBK1, CCNF, GLT8D1, KIF5A, NEK1, C21orf2, TBP, CTSF, MFSD8, DNAJC7). Additional risk factors and modifiers have been also identified in genome-wide association studies and array-based studies. However, the newly identified genes show higher disease frequencies in combination with known genes that are implicated in pathogenesis, thus indicating probable digenetic/polygenic inheritance models, along with epistatic interactions. Studies suggest that these genes play a pleiotropic effect on ALS-FTD and other diseases such as Alzheimer's disease, Ataxia, and Parkinsonism. Besides, there have been numerous improvements in the genotype-phenotype correlations as well as clinical trials on stem cell and gene-based therapies. This review discusses the possible genetic models of ALS and FTD, the latest therapeutics, and signaling pathways involved in ALS-FTD.
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Affiliation(s)
- Laxmi Kirola
- Department of Molecular and Human Genetics, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India
| | - Ashim Mukherjee
- Department of Molecular and Human Genetics, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India
| | - Mousumi Mutsuddi
- Department of Molecular and Human Genetics, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India.
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11
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Wightman DP, Jansen IE, Savage JE, Shadrin AA, Bahrami S, Holland D, Rongve A, Børte S, Winsvold BS, Drange OK, Martinsen AE, Skogholt AH, Willer C, Bråthen G, Bosnes I, Nielsen JB, Fritsche LG, Thomas LF, Pedersen LM, Gabrielsen ME, Johnsen MB, Meisingset TW, Zhou W, Proitsi P, Hodges A, Dobson R, Velayudhan L, Heilbron K, Auton A, Sealock JM, Davis LK, Pedersen NL, Reynolds CA, Karlsson IK, Magnusson S, Stefansson H, Thordardottir S, Jonsson PV, Snaedal J, Zettergren A, Skoog I, Kern S, Waern M, Zetterberg H, Blennow K, Stordal E, Hveem K, Zwart JA, Athanasiu L, Selnes P, Saltvedt I, Sando SB, Ulstein I, Djurovic S, Fladby T, Aarsland D, Selbæk G, Ripke S, Stefansson K, Andreassen OA, Posthuma D. A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease. Nat Genet 2021; 53:1276-1282. [PMID: 34493870 PMCID: PMC10243600 DOI: 10.1038/s41588-021-00921-z] [Citation(s) in RCA: 565] [Impact Index Per Article: 141.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/16/2021] [Indexed: 12/12/2022]
Abstract
Late-onset Alzheimer's disease is a prevalent age-related polygenic disease that accounts for 50-70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer's disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer's disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer's disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer's disease to identify further genetic variants that contribute to Alzheimer's pathology.
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Affiliation(s)
- Douglas P Wightman
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands
| | - Iris E Jansen
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands
| | - Alexey A Shadrin
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Shahram Bahrami
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dominic Holland
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Arvid Rongve
- Department of Research and Innovation, Helse Fonna, Haugesund Hospital, Haugesund, Norway
- The University of Bergen, Institute of Clinical Medicine (K1), Bergen, Norway
| | - Sigrid Børte
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bendik S Winsvold
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Ole Kristian Drange
- Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Division of Mental Health Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Amy E Martinsen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Anne Heidi Skogholt
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Cristen Willer
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Geir Bråthen
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
- Department of Geriatrics, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ingunn Bosnes
- Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Psychiatry, Hospital Namsos, Nord-Trøndelag Health Trust, Namsos, Norway
| | - Jonas Bille Nielsen
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Lars G Fritsche
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Laurent F Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Linda M Pedersen
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Maiken E Gabrielsen
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Marianne Bakke Johnsen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Tore Wergeland Meisingset
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Petroula Proitsi
- Institute of Psychiatry Psychology and Neurosciences, King's College London, London, UK
| | - Angela Hodges
- Institute of Psychiatry Psychology and Neurosciences, King's College London, London, UK
| | - Richard Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK
- Health Data Research UK London, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
- NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK
| | - Latha Velayudhan
- Institute of Psychiatry Psychology and Neurosciences, King's College London, London, UK
| | | | | | - Julia M Sealock
- Division of Genetic Medicine, Department of Medicine Vanderbilt University Medical Center Nashville, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lea K Davis
- Division of Genetic Medicine, Department of Medicine Vanderbilt University Medical Center Nashville, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Chandra A Reynolds
- Department of Psychology, University of California-Riverside, Riverside, CA, USA
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | | | | | | | - Palmi V Jonsson
- Department of Geriatric Medicine, Landspitali University Hospital, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jon Snaedal
- Department of Geriatric Medicine, Landspitali University Hospital, Reykjavik, Iceland
| | - Anna Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Silke Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Margda Waern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychosis Clinic, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Eystein Stordal
- Department of Mental Health, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Psychiatry, Hospital Namsos, Nord-Trøndelag Health Trust, Namsos, Norway
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - John-Anker Zwart
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Lavinia Athanasiu
- NORMENT Centre, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Ingvild Saltvedt
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Geriatrics, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Sigrid B Sando
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Ingun Ulstein
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Tormod Fladby
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Dag Aarsland
- Institute of Psychiatry Psychology and Neurosciences, King's College London, London, UK
- Centre of Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Geir Selbæk
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| | - Stephan Ripke
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin, Berlin, Germany
| | | | - Ole A Andreassen
- NORMENT Centre, University of Oslo, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, the Netherlands.
- Department of Child and Adolescent Psychiatry and Pediatric Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam University Medical Center, Amsterdam, the Netherlands.
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12
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Jaiswal S, Jagannadham J, Kumari J, Iquebal MA, Gurjar AKS, Nayan V, Angadi UB, Kumar S, Kumar R, Datta TK, Rai A, Kumar D. Genome Wide Prediction, Mapping and Development of Genomic Resources of Mastitis Associated Genes in Water Buffalo. Front Vet Sci 2021; 8:593871. [PMID: 34222390 PMCID: PMC8253262 DOI: 10.3389/fvets.2021.593871] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 04/30/2021] [Indexed: 12/16/2022] Open
Abstract
Water buffalo (Bubalus bubalis) are an important animal resource that contributes milk, meat, leather, dairy products, and power for plowing and transport. However, mastitis, a bacterial disease affecting milk production and reproduction efficiency, is most prevalent in populations having intensive selection for higher milk yield, especially where the inbreeding level is also high. Climate change and poor hygiene management practices further complicate the issue. The management of this disease faces major challenges, like antibiotic resistance, maximum residue level, horizontal gene transfer, and limited success in resistance breeding. Bovine mastitis genome wide association studies have had limited success due to breed differences, sample sizes, and minor allele frequency, lowering the power to detect the diseases associated with SNPs. In this work, we focused on the application of targeted gene panels (TGPs) in screening for candidate gene association analysis, and how this approach overcomes the limitation of genome wide association studies. This work will facilitate the targeted sequencing of buffalo genomic regions with high depth coverage required to mine the extremely rare variants potentially associated with buffalo mastitis. Although the whole genome assembly of water buffalo is available, neither mastitis genes are predicted nor TGP in the form of web-genomic resources are available for future variant mining and association studies. Out of the 129 mastitis associated genes of cattle, 101 were completely mapped on the buffalo genome to make TGP. This further helped in identifying rare variants in water buffalo. Eighty-five genes were validated in the buffalo gene expression atlas, with the RNA-Seq data of 50 tissues. The functions of 97 genes were predicted, revealing 225 pathways. The mastitis proteins were used for protein-protein interaction network analysis to obtain additional cross-talking proteins. A total of 1,306 SNPs and 152 indels were identified from 101 genes. Water Buffalo-MSTdb was developed with 3-tier architecture to retrieve mastitis associated genes having genomic coordinates with chromosomal details for TGP sequencing for mining of minor alleles for further association studies. Lastly, a web-genomic resource was made available to mine variants of targeted gene panels in buffalo for mastitis resistance breeding in an endeavor to ensure improved productivity and the reproductive efficiency of water buffalo.
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Affiliation(s)
- Sarika Jaiswal
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Jaisri Jagannadham
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Juli Kumari
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Anoop Kishor Singh Gurjar
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Varij Nayan
- Indian Council of Agricultural Research (ICAR)-Central Institute for Research on Buffaloes, Hisar, India
| | - Ulavappa B Angadi
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Sunil Kumar
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Rakesh Kumar
- Animal Biotechnology Centre, Indian Council of Agricultural Research (ICAR)-National Dairy research Institute, Karnal, India
| | - Tirtha Kumar Datta
- Animal Biotechnology Centre, Indian Council of Agricultural Research (ICAR)-National Dairy research Institute, Karnal, India
| | - Anil Rai
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Statistics Research Institute, New Delhi, India
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13
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Salman MM, Al-Obaidi Z, Kitchen P, Loreto A, Bill RM, Wade-Martins R. Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases. Int J Mol Sci 2021; 22:4688. [PMID: 33925236 PMCID: PMC8124449 DOI: 10.3390/ijms22094688] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/26/2021] [Accepted: 04/26/2021] [Indexed: 12/11/2022] Open
Abstract
Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.
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Affiliation(s)
- Mootaz M. Salman
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3QX, UK;
- Oxford Parkinson’s Disease Centre, University of Oxford, South Parks Road, Oxford OX1 3QX, UK
| | - Zaid Al-Obaidi
- Department of Pharmaceutical Chemistry, College of Pharmacy, University of Alkafeel, Najaf 54001, Iraq;
- Department of Chemistry and Biochemistry, College of Medicine, University of Kerbala, Karbala 56001, Iraq
| | - Philip Kitchen
- School of Biosciences, College of Health and Life Sciences, Aston University, Aston Triangle, Birmingham B4 7ET, UK; (P.K.); (R.M.B.)
| | - Andrea Loreto
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3QX, UK;
- John Van Geest Centre for Brain Repair, University of Cambridge, Cambridge CB2 0PY, UK
| | - Roslyn M. Bill
- School of Biosciences, College of Health and Life Sciences, Aston University, Aston Triangle, Birmingham B4 7ET, UK; (P.K.); (R.M.B.)
| | - Richard Wade-Martins
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3QX, UK;
- Oxford Parkinson’s Disease Centre, University of Oxford, South Parks Road, Oxford OX1 3QX, UK
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14
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Perrone F, Cacace R, van der Zee J, Van Broeckhoven C. Emerging genetic complexity and rare genetic variants in neurodegenerative brain diseases. Genome Med 2021; 13:59. [PMID: 33853652 PMCID: PMC8048219 DOI: 10.1186/s13073-021-00878-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 03/25/2021] [Indexed: 12/12/2022] Open
Abstract
Knowledge of the molecular etiology of neurodegenerative brain diseases (NBD) has substantially increased over the past three decades. Early genetic studies of NBD families identified rare and highly penetrant deleterious mutations in causal genes that segregate with disease. Large genome-wide association studies uncovered common genetic variants that influenced disease risk. Major developments in next-generation sequencing (NGS) technologies accelerated gene discoveries at an unprecedented rate and revealed novel pathways underlying NBD pathogenesis. NGS technology exposed large numbers of rare genetic variants of uncertain significance (VUS) in coding regions, highlighting the genetic complexity of NBD. Since experimental studies of these coding rare VUS are largely lacking, the potential contributions of VUS to NBD etiology remain unknown. In this review, we summarize novel findings in NBD genetic etiology driven by NGS and the impact of rare VUS on NBD etiology. We consider different mechanisms by which rare VUS can act and influence NBD pathophysiology and discuss why a better understanding of rare VUS is instrumental for deriving novel insights into the molecular complexity and heterogeneity of NBD. New knowledge might open avenues for effective personalized therapies.
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Affiliation(s)
- Federica Perrone
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp – CDE, Universiteitsplein 1, BE-2610 Antwerp, Belgium
| | - Rita Cacace
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp – CDE, Universiteitsplein 1, BE-2610 Antwerp, Belgium
| | - Julie van der Zee
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp – CDE, Universiteitsplein 1, BE-2610 Antwerp, Belgium
| | - Christine Van Broeckhoven
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp – CDE, Universiteitsplein 1, BE-2610 Antwerp, Belgium
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15
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The Role of White Matter Dysfunction and Leukoencephalopathy/Leukodystrophy Genes in the Aetiology of Frontotemporal Dementias: Implications for Novel Approaches to Therapeutics. Int J Mol Sci 2021; 22:ijms22052541. [PMID: 33802612 PMCID: PMC7961524 DOI: 10.3390/ijms22052541] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 02/22/2021] [Accepted: 03/01/2021] [Indexed: 01/01/2023] Open
Abstract
Frontotemporal dementia (FTD) is a common cause of presenile dementia and is characterized by behavioural and/or language changes and progressive cognitive deficits. Genetics is an important component in the aetiology of FTD, with positive family history of dementia reported for 40% of cases. This review synthesizes current knowledge of the known major FTD genes, including C9orf72 (chromosome 9 open reading frame 72), MAPT (microtubule-associated protein tau) and GRN (granulin), and their impact on neuronal and glial pathology. Further, evidence for white matter dysfunction in the aetiology of FTD and the clinical, neuroimaging and genetic overlap between FTD and leukodystrophy/leukoencephalopathy are discussed. The review highlights the role of common variants and mutations in genes such as CSF1R (colony-stimulating factor 1 receptor), CYP27A1 (cytochrome P450 family 27 subfamily A member 1), TREM2 (triggering receptor expressed on myeloid cells 2) and TMEM106B (transmembrane protein 106B) that play an integral role in microglia and oligodendrocyte function. Finally, pharmacological and non-pharmacological approaches for enhancing remyelination are discussed in terms of future treatments of FTD.
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16
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Bi XA, Wu H, Xie Y, Zhang L, Luo X, Fu Y. The exploration of Parkinson's disease: a multi-modal data analysis of resting functional magnetic resonance imaging and gene data. Brain Imaging Behav 2020; 15:1986-1996. [PMID: 32990896 DOI: 10.1007/s11682-020-00392-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/31/2020] [Indexed: 02/02/2023]
Abstract
Parkinson's disease (PD) is the most universal chronic degenerative neurological dyskinesia and an important threat to elderly health. At present, the researches of PD are mainly based on single-modal data analysis, while the fusion research of multi-modal data may provide more meaningful information in the aspect of comprehending the pathogenesis of PD. In this paper, 104 samples having resting functional magnetic resonance imaging (rfMRI) and gene data are from Parkinson's Progression Markers Initiative (PPMI) and Alzheimer's Disease Neuroimaging Initiative (ADNI) database to predict pathological brain areas and risk genes related to PD. In the experiment, Pearson correlation analysis is adopted to conduct fusion analysis from the data of genes and brain areas as multi-modal sample characteristics, and the clustering evolution random forest (CERF) method is applied to detect the discriminative genes and brain areas. The experimental results indicate that compared with several existing advanced methods, the CERF method can further improve the diagnosis of PD and healthy control, and can achieve a significant effect. More importantly, we find that there are some interesting associations between brain areas and genes in PD patients. Based on these associations, we notice that PD-related brain areas include angular gyrus, thalamus, posterior cingulate gyrus and paracentral lobule, and risk genes mainly include C6orf10, HLA-DPB1 and HLA-DOA. These discoveries have a significant contribution to the early prevention and clinical treatments of PD.
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Affiliation(s)
- Xia-An Bi
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China. .,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China.
| | - Hao Wu
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China.,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China
| | - Yiming Xie
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China.,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China
| | - Lixia Zhang
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China.,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China
| | - Xun Luo
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China.,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China
| | - Yu Fu
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, People's Republic of China.,College of Information Science and Engineering, Hunan Normal University, Changsha, People's Republic of China
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17
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Shin J, Ma S, Hofer E, Patel Y, Vosberg DE, Tilley S, Roshchupkin GV, Sousa AMM, Jian X, Gottesman R, Mosley TH, Fornage M, Saba Y, Pirpamer L, Schmidt R, Schmidt H, Carrion-Castillo A, Crivello F, Mazoyer B, Bis JC, Li S, Yang Q, Luciano M, Karama S, Lewis L, Bastin ME, Harris MA, Wardlaw JM, Deary IE, Scholz M, Loeffler M, Witte AV, Beyer F, Villringer A, Armstrong NJ, Mather KA, Ames D, Jiang J, Kwok JB, Schofield PR, Thalamuthu A, Trollor JN, Wright MJ, Brodaty H, Wen W, Sachdev PS, Terzikhan N, Evans TE, Adams HHHH, Ikram MA, Frenzel S, van der Auwera-Palitschka S, Wittfeld K, Bülow R, Grabe HJ, Tzourio C, Mishra A, Maingault S, Debette S, Gillespie NA, Franz CE, Kremen WS, Ding L, Jahanshad N, Sestan N, Pausova Z, Seshadri S, Paus T. Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes. Cereb Cortex 2020; 30:4121-4139. [PMID: 32198502 PMCID: PMC7947185 DOI: 10.1093/cercor/bhaa035] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
We have carried out meta-analyses of genome-wide association studies (GWAS) (n = 23 784) of the first two principal components (PCs) that group together cortical regions with shared variance in their surface area. PC1 (global) captured variations of most regions, whereas PC2 (visual) was specific to the primary and secondary visual cortices. We identified a total of 18 (PC1) and 17 (PC2) independent loci, which were replicated in another 25 746 individuals. The loci of the global PC1 included those associated previously with intracranial volume and/or general cognitive function, such as MAPT and IGF2BP1. The loci of the visual PC2 included DAAM1, a key player in the planar-cell-polarity pathway. We then tested associations with occupational aptitudes and, as predicted, found that the global PC1 was associated with General Learning Ability, and the visual PC2 was associated with the Form Perception aptitude. These results suggest that interindividual variations in global and regional development of the human cerebral cortex (and its molecular architecture) cascade-albeit in a very limited manner-to behaviors as complex as the choice of one's occupation.
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Affiliation(s)
- Jean Shin
- The Hospital for Sick Children, University of Toronto, Toronto, M5G 0A4 ON, M5G 0A4, Canada
- Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute, University of Toronto, Toronto, M4G 1R8 ON, Canada
| | - Shaojie Ma
- Department of Genetics, Yale University School of Medicine, New Haven, 06510 CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, 06510 CT, USA
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, 8036 Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036 Graz, Austria
| | - Yash Patel
- Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute, University of Toronto, Toronto, M4G 1R8 ON, Canada
| | - Daniel E Vosberg
- Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute, University of Toronto, Toronto, M4G 1R8 ON, Canada
| | - Steven Tilley
- Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute, University of Toronto, Toronto, M4G 1R8 ON, Canada
| | - Gennady V Roshchupkin
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
- Department of Medical Informatics, Erasmus MC, 3015 Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
| | - André M M Sousa
- Department of Neuroscience, Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, 06510 CT, USA
| | - Xueqiu Jian
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, 77030 Houston, 77030 TX, USA
| | | | - Thomas H Mosley
- University of Mississippi Medical Center, Jackson, 39216 MS, USA
| | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, 77030 Houston, 77030 TX, USA
| | - Yasaman Saba
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, 8036 Graz, Austria
| | - Lukas Pirpamer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, 8036 Graz, Austria
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, 8036 Graz, Austria
| | - Helena Schmidt
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Medical University of Graz, 8036 Graz, Austria
| | - Amaia Carrion-Castillo
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6525 Nijmegen, The Netherlands
| | - Fabrice Crivello
- Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, Centre National de la Recherche Scientifique, Commissariat à l’Energie Atomique, et Université de Bordeaux, F-33000 Bordeaux, France
| | - Bernard Mazoyer
- Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, Centre National de la Recherche Scientifique, Commissariat à l’Energie Atomique, et Université de Bordeaux, F-33000 Bordeaux, France
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, 98101 WA, USA
| | - Shuo Li
- Department of Biostatistics, Boston University School of Public Health, Boston, 02118, MA, USA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, 02118, MA, USA
| | - Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
- Department of Psychology, University of Edinburgh, EH8 9JZ Edinburgh, UK
| | - Sherif Karama
- Montreal Neurological Institute, McGill University, H3A 2B4 Montreal, QC, Canada
| | - Lindsay Lewis
- Montreal Neurological Institute, McGill University, H3A 2B4 Montreal, QC, Canada
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, EH8 9YL Edinburgh, UK
| | - Mathew A Harris
- Centre for Clinical Brain Sciences, University of Edinburgh, EH8 9YL Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, EH8 9JZ Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, EH8 9JZ Edinburgh, UK
| | - Ian E Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, EH8 9YL Edinburgh, UK
- Department of Psychology, University of Edinburgh, EH8 9JZ Edinburgh, UK
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04109 Leipzig, Germany
- LIFE Research Center for Civilization Diseases, 04103 Leipzig, Germany
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04109 Leipzig, Germany
- LIFE Research Center for Civilization Diseases, 04103 Leipzig, Germany
| | - A Veronica Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
- Faculty of Medicine, CRC 1052 Obesity Mechanisms, University of Leipzig, 04109 Leipzig, Germany
- Day Clinic for Cognitive Neurology, University Hospital Leipzig, 04103 Leipzig, Germany
| | - Frauke Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
- Faculty of Medicine, CRC 1052 Obesity Mechanisms, University of Leipzig, 04109 Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
- Faculty of Medicine, CRC 1052 Obesity Mechanisms, University of Leipzig, 04109 Leipzig, Germany
- Day Clinic for Cognitive Neurology, University Hospital Leipzig, 04103 Leipzig, Germany
| | - Nicola J Armstrong
- Mathematics and Statistics, Murdoch University, 6150 Perth, WA, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, 2052 Sydney, NSW, Australia
- Neuroscience Research Australia, 2031 Sydney, NSW, Australia
| | - David Ames
- National Ageing Research Institute, Royal Melbourne Hospital, 3052 Melbourne, VIC, Australia
- Academic Unit for Psychiatry of Old Age, St. Vincent's Health, The University of Melbourne, 3010 Melbourne, VIC, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, 2052 Sydney, NSW, Australia
| | - John B Kwok
- Brain and Mind Centre, The University of Sydney, 2050 Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, 2052 Sydney, NSW, Australia
| | - Peter R Schofield
- Neuroscience Research Australia, 2031 Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, 2052 Sydney, NSW, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, 2052 Sydney, NSW, Australia
| | - Julian N Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, 2052 Sydney, NSW, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, 2031 Sydney, NSW, Australia
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, 4072 St Lucia, QLD, Australia
- Centre for Advanced Imaging, The University of Queensland, 4072 St Lucia, QLD, Australia
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, 2052 Sydney, NSW, Australia
- Dementia Centre for Research Collaboration, University of New South Wales, 2052 Sydney, NSW, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, 2052 Sydney, NSW, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, 2052 Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, 2031 Sydney, NSW, Australia
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
| | - Tavia E Evans
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
| | - Hieab H H H Adams
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center, 3015 Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC University Medical Centre, 3015 Rotterdam, The Netherlands
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17489 Greifswald, Germany
| | - Sandra van der Auwera-Palitschka
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17489 Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, 37075, Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17489 Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, 37075, Germany
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17489 Greifswald, Germany
| | - Hans Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17489 Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, 37075, Germany
| | - Christophe Tzourio
- Inserm, Bordeaux Population Health Research Center, University of Bordeaux, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
- Department of Neurology, CHU de Bordeaux, F-33000 Bordeaux, France
| | - Aniket Mishra
- Inserm, Bordeaux Population Health Research Center, University of Bordeaux, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
| | - Sophie Maingault
- Institut des Maladies Neurodégénratives, UMR 5293, CEA, CNRS, University of Bordeaux, Ubordeaux, F-33000 Bordeaux, France
| | - Stephanie Debette
- Inserm, Bordeaux Population Health Research Center, University of Bordeaux, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
- Department of Neurology, CHU de Bordeaux, F-33000 Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, 02118 MA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioural Genetics, Virginia Commonwealth University, Richmond, 23284 VA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, 92093 CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, 92093 CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, 92093 CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, 92093 CA, USA
- VA San Diego Center of Excellence for Stress and Mental Health, San Diego, 92161 CA, USA
| | - Linda Ding
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, 90033 CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, 90033 CA, USA
| | | | - Nenad Sestan
- Department of Genetics, Yale University School of Medicine, New Haven, 06510 CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, 06510 CT, USA
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, Toronto, M5G 0A4 ON, M5G 0A4, Canada
- Department of Physiology, University of Toronto, Toronto, M5S 1A8 ON, Canada
- Department of Nutritional Sciences, University of Toronto, Toronto, M5S 1A8 ON, Canada
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, 02118 MA, USA
- Department of Epidemiology and Biostatistics, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, 78229 TX, USA
| | - Tomas Paus
- Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute, University of Toronto, Toronto, M4G 1R8 ON, Canada
- Department of Psychology, University of Toronto, Toronto, M5S 3G3 ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, M5T 1R8 ON, Canada
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18
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Ciani M, Bonvicini C, Scassellati C, Carrara M, Maj C, Fostinelli S, Binetti G, Ghidoni R, Benussi L. The Missing Heritability of Sporadic Frontotemporal Dementia: New Insights from Rare Variants in Neurodegenerative Candidate Genes. Int J Mol Sci 2019; 20:ijms20163903. [PMID: 31405128 PMCID: PMC6721049 DOI: 10.3390/ijms20163903] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 08/02/2019] [Accepted: 08/08/2019] [Indexed: 12/13/2022] Open
Abstract
Frontotemporal dementia (FTD) is a common form of dementia among early-onset cases. Several genetic factors for FTD have been revealed, but a large proportion of FTD cases still have an unidentified genetic origin. Recent studies highlighted common pathobiological mechanisms among neurodegenerative diseases. In the present study, we investigated a panel of candidate genes, previously described to be associated with FTD and/or other neurodegenerative diseases by targeted next generation sequencing (NGS). We focused our study on sporadic FTD (sFTD), devoid of disease-causing mutations in GRN, MAPT and C9orf72. Since genetic factors have a substantially higher pathogenetic contribution in early onset patients than in late onset dementia, we selected patients with early onset (<65 years). Our study revealed that, in 50% of patients, rare missense potentially pathogenetic variants in genes previously associated with Alzheimer's disease, Parkinson disease, amyotrophic lateral sclerosis and Lewy body dementia (GBA, ABCA7, PARK7, FUS, SORL1, LRRK2, ALS2), confirming genetic pleiotropy in neurodegeneration. In parallel, a synergic genetic effect on FTD is suggested by the presence of variants in five different genes in one single patient. Further studies employing genome-wide approaches might highlight pathogenic variants in novel genes that explain the still missing heritability of FTD.
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Affiliation(s)
- Miriam Ciani
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
| | - Cristian Bonvicini
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
| | - Catia Scassellati
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
| | - Matteo Carrara
- Service of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
| | - Carlo Maj
- Institute of Genomic Statistics and Bioinformatics, University of Bonn, 53127 Bonn, Germany
| | - Silvia Fostinelli
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
| | - Giuliano Binetti
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
| | - Roberta Ghidoni
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy
| | - Luisa Benussi
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125 Brescia, Italy.
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