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Ballasch I, López-Molina L, Galán-Ganga M, Sancho-Balsells A, Rodríguez-Navarro I, Borràs-Pernas S, Rabadan MA, Chen W, Pastó-Pellicer C, Flotta F, Maoyu W, Fernández-Irigoyen J, Santamaría E, Aguilar R, Dobaño C, Egri N, Hernandez C, Alfonso M, Juan M, Alberch J, Del Toro D, Arranz B, Canals JM, Giralt A. Alterations of the IKZF1-IKZF2 tandem in immune cells of schizophrenia patients regulate associated phenotypes. J Neuroinflammation 2024; 21:326. [PMID: 39695786 DOI: 10.1186/s12974-024-03320-3] [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: 06/21/2024] [Accepted: 12/06/2024] [Indexed: 12/20/2024] Open
Abstract
Schizophrenia is a complex multifactorial disorder and increasing evidence suggests the involvement of immune dysregulations in its pathogenesis. We observed that IKZF1 and IKZF2, classic immune-related transcription factors (TFs), were both downregulated in patients' peripheral blood mononuclear cells (PBMCs) but not in their brain. We generated a new mutant mouse model with a reduction in Ikzf1 and Ikzf2 to study the impact of those changes. Such mice developed deficits in the three dimensions (positive-negative-cognitive) of schizophrenia-like phenotypes associated with alterations in structural synaptic plasticity. We then studied the secretomes of cultured PBMCs obtained from patients and identified potentially secreted molecules, which depended on IKZF1 and IKZF2 mRNA levels, and that in turn have an impact on neural synchrony, structural synaptic plasticity and schizophrenia-like symptoms in in vivo and in vitro models. Our results point out that IKZF1-IKZF2-dependent immune signals negatively impact on essential neural circuits involved in schizophrenia.
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Affiliation(s)
- Iván Ballasch
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Laura López-Molina
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Marcos Galán-Ganga
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Anna Sancho-Balsells
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Irene Rodríguez-Navarro
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Sara Borràs-Pernas
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | | | - Wanqi Chen
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Carlota Pastó-Pellicer
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Francesca Flotta
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Wang Maoyu
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Joaquín Fernández-Irigoyen
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra UPNA, IdiSNA, 31008, Pamplona, Spain
| | - Enrique Santamaría
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra UPNA, IdiSNA, 31008, Pamplona, Spain
| | - Ruth Aguilar
- ISGlobal, Hospital Clínic - Universitat de Barcelona, Barcelona, Catalonia, Spain
| | - Carlota Dobaño
- ISGlobal, Hospital Clínic - Universitat de Barcelona, Barcelona, Catalonia, Spain
- CIBER Enfermedades Infecciosas (CIBERINFEC), Barcelona, Catalonia, Spain
| | - Natalia Egri
- Servei d'Immunologia, Hospital Clinic Barcelona (HCB) - CDB, Fundació Clínic de Recerca Biomèdica - IDIBAPS, Barcelona, Spain
| | | | - Miqueu Alfonso
- Parc Sanitari Sant Joan de Déu, CIBERSAM, Barcelona, Spain
| | - Manel Juan
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Servei d'Immunologia, Hospital Clinic Barcelona (HCB) - CDB, Fundació Clínic de Recerca Biomèdica - IDIBAPS, Barcelona, Spain
- Plataforma d'Immunoteràpia HSJD-HCB, Barcelona, Spain
| | - Jordi Alberch
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
- Production and Validation Centre of Advanced Therapies (Creatio), Faculty of Medicine and Health Science, University of Barcelona, 08036, Barcelona, Spain
| | - Daniel Del Toro
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
| | - Belén Arranz
- Parc Sanitari Sant Joan de Déu, CIBERSAM, Barcelona, Spain
| | - Josep M Canals
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain
- Production and Validation Centre of Advanced Therapies (Creatio), Faculty of Medicine and Health Science, University of Barcelona, 08036, Barcelona, Spain
| | - Albert Giralt
- Departament de Biomedicina, Facultat de Medicina, Institut de Neurociències, Universitat de Barcelona, 08036, Barcelona, Spain.
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain.
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28031, Madrid, Spain.
- Production and Validation Centre of Advanced Therapies (Creatio), Faculty of Medicine and Health Science, University of Barcelona, 08036, Barcelona, Spain.
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Peña-Bautista C, Álvarez-Sánchez L, Balaguer Á, Raga L, García-Vallés L, Baquero M, Cháfer-Pericás C. Defining Alzheimer's Disease through Proteomic CSF Profiling. J Proteome Res 2024; 23:5096-5106. [PMID: 39373095 DOI: 10.1021/acs.jproteome.4c00590] [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] [Indexed: 10/08/2024]
Abstract
Alzheimer disease (AD) is the main cause of dementia, and its complexity is not yet completely understood. Proteomic profiles can provide useful information to explore the pathways involved and the heterogeneity among AD patients. A proteomic analysis was performed in cerebrospinal fluid (CSF) samples from mild cognitive impairment due to AD (MCI-AD) and control individuals; both groups were classified by amyloid β42/amyloid β40 levels in CSF (data available in BioStudies database (S-BSST1456)). The analysis based on PLS regression and volcano plot identified 7 proteins (FOLR2, PPP3CA, SMOC2, STMN1, TAGLN3, TMEM132B, and UCHL1) mainly related to protein phosphorylation, structure maintenance, inflammation, and protein degradation. Enrichment analysis revealed the involvement of different biological processes related to neuronal mechanisms and synapses, lipid and carbohydrate metabolism, immune system and inflammation, vascular, hormones, and response to stimuli, and cell signaling and adhesion. In addition, the proteomic profile showed some association with the levels of AD biomarkers in CSF. Regarding the subtypes, two MCI-AD subgroups were identified: one could be related to synapsis and neuronal functions and the other to innate immunity. The study of the proteomic profile in the CSF of AD patients reflects the heterogeneity of biochemical pathways involved in AD.
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Affiliation(s)
- Carmen Peña-Bautista
- Alzheimer's Disease Research Group, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain
| | - Lourdes Álvarez-Sánchez
- Alzheimer's Disease Research Group, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain
| | - Ángel Balaguer
- Faculty of Mathematical Sciences, University of Valencia, 46100 Burjassot, Valencia, Spain
| | - Luis Raga
- Alzheimer's Disease Research Group, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain
| | - Lorena García-Vallés
- Alzheimer's Disease Research Group, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain
| | - Miguel Baquero
- Division of Neurology, Hospital Universitari I Politècnic La Fe, 46026 Valencia, Spain
| | - Consuelo Cháfer-Pericás
- Alzheimer's Disease Research Group, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain
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Ostermann PN, Wu Y, Bowler SA, Siddiqui MA, Herrera A, Sidharta M, Ramnarine K, Martínez-Meza S, St. Bernard LA, Nixon DF, Jones RB, Yamashita M, Ndhlovu LC, Zhou T, Evering TH. A Transcriptional Signature of Induced Neurons Differentiates Virologically Suppressed People Living With HIV from People Without HIV. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.22.619617. [PMID: 39484396 PMCID: PMC11526917 DOI: 10.1101/2024.10.22.619617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/03/2024]
Abstract
Neurocognitive impairment is a prevalent and important co-morbidity in virologically suppressed people living with HIV (PLWH), yet the underlying mechanisms remain elusive and treatments lacking. Here, we explored for the first time, use of participant-derived directly induced neurons (iNs) to model neuronal biology and injury in PLWH. iNs retain age- and disease-related features of the donors, providing unique opportunities to reveal novel aspects of neurological disorders. We obtained primary dermal fibroblasts from six virologically suppressed PLWH (range: 27 - 64 years, median: 53); 83% Male; 50% White) and seven matched people without HIV (PWOH) (range: 27 - 66, median: 55); 71% Male; 57% White). iNs were generated using transcription factors NGN2 and ASCL1, and validated by immunocytochemistry and single-cell-RNAseq. Transcriptomic analysis using bulk-RNAseq identified 29 significantly differentially expressed genes between iNs from PLWH and PWOH. Of these, 16 genes were downregulated and 13 upregulated in PLWH iNs. Protein-protein interaction network mapping indicates that iNs from PLWH exhibit differences in extracellular matrix organization and synaptic transmission. IFI27 was upregulated in iNs from PLWH, which complements independent post-mortem studies demonstrating elevated IFI27 expression in PLWH-derived brain tissue, indicating that iN generation reconstitutes this pathway. Finally, we observed that expression of the FOXL2NB-FOXL2-LINC01391 genome locus is reduced in iNs from PLWH and negatively correlates with neurocognitive impairment. Thus, we have identified an iN gene signature of HIV through direct reprogramming of skin fibroblasts into neurons revealing novel mechanisms of neurocognitive impairment in PLWH.
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Affiliation(s)
- Philipp N. Ostermann
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Youjun Wu
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan Kettering Institute, New York, NY 10065, USA
| | - Scott A. Bowler
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Mohammad Adnan Siddiqui
- Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY. 10032, USA
| | - Alberto Herrera
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Mega Sidharta
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan Kettering Institute, New York, NY 10065, USA
| | - Kiran Ramnarine
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan Kettering Institute, New York, NY 10065, USA
| | - Samuel Martínez-Meza
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Leslie Ann St. Bernard
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Douglas F. Nixon
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - R. Brad Jones
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Masahiro Yamashita
- Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY. 10032, USA
| | - Lishomwa C. Ndhlovu
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
| | - Ting Zhou
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan Kettering Institute, New York, NY 10065, USA
| | - Teresa H. Evering
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
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Willett JDS, Waqas M, Choi Y, Ngai T, Mullin K, Tanzi RE, Prokopenko D. Identification of 16 novel Alzheimer's disease susceptibility loci using multi-ancestry meta-analyses of clinical Alzheimer's disease and AD-by-proxy cases from four whole genome sequencing datasets. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.11.24313439. [PMID: 39314934 PMCID: PMC11419201 DOI: 10.1101/2024.09.11.24313439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Alzheimer's disease (AD) is the most prevalent form of dementia. While many AD-associated genetic determinants have been previously identified, few studies have analyzed individuals of non-European ancestry. Here, we describe a multi-ancestry genome-wide association study of clinically-diagnosed AD and AD-by-proxy using whole genome sequencing data from NIAGADS, NIMH, UKB, and All of Us (AoU) consisting of 49,149 cases (12,074 clinically-diagnosed and 37,075 AD-by-proxy) and 383,225 controls. Nearly half of NIAGADS and AoU participants are of non-European ancestry. For clinically-diagnosed AD, we identified 14 new loci - five common (FBN2,/SCL27A6, AC090115.1, DYM, KCNG1/AL121785.1, TIAM1) and nine rare (VWA5B1, RNU6-755P/LMX1A, MOB1A, MORC1-AS1, LINC00989, PDE4D, RNU2-49P/CDO1, NEO1, and SLC35G3/AC022916.1). Meta-analysis of UKB and AoU AD-by-proxy cases yielded two new rare loci (RPL23/LASP1 and CEBPA/ AC008738.6) which were also nominally significant in NIAGADS. In summary, we provide evidence for 16 novel AD loci and advocate for more studies using WGS-based GWAS of diverse cohorts.
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Affiliation(s)
- Julian Daniel Sunday Willett
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Mohammad Waqas
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Younjung Choi
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Tiffany Ngai
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
- University of Waterloo, Department of Systems Design Engineering, Waterloo, Ontario, Canada
| | - Kristina Mullin
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Rudolph E. Tanzi
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit and the McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA
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Jessop M, Broadway BJ, Miller K, Guettler S. Regulation of PARP1/2 and the tankyrases: emerging parallels. Biochem J 2024; 481:1097-1123. [PMID: 39178157 DOI: 10.1042/bcj20230230] [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: 06/10/2024] [Revised: 07/31/2024] [Accepted: 08/06/2024] [Indexed: 08/25/2024]
Abstract
ADP-ribosylation is a prominent and versatile post-translational modification, which regulates a diverse set of cellular processes. Poly-ADP-ribose (PAR) is synthesised by the poly-ADP-ribosyltransferases PARP1, PARP2, tankyrase (TNKS), and tankyrase 2 (TNKS2), all of which are linked to human disease. PARP1/2 inhibitors have entered the clinic to target cancers with deficiencies in DNA damage repair. Conversely, tankyrase inhibitors have continued to face obstacles on their way to clinical use, largely owing to our limited knowledge of their molecular impacts on tankyrase and effector pathways, and linked concerns around their tolerability. Whilst detailed structure-function studies have revealed a comprehensive picture of PARP1/2 regulation, our mechanistic understanding of the tankyrases lags behind, and thereby our appreciation of the molecular consequences of tankyrase inhibition. Despite large differences in their architecture and cellular contexts, recent structure-function work has revealed striking parallels in the regulatory principles that govern these enzymes. This includes low basal activity, activation by intra- or inter-molecular assembly, negative feedback regulation by auto-PARylation, and allosteric communication. Here we compare these poly-ADP-ribosyltransferases and point towards emerging parallels and open questions, whose pursuit will inform future drug development efforts.
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Affiliation(s)
- Matthew Jessop
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, U.K
- Division of Cancer Biology, The Institute of Cancer Research (ICR), London, U.K
| | - Benjamin J Broadway
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, U.K
- Division of Cancer Biology, The Institute of Cancer Research (ICR), London, U.K
| | - Katy Miller
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, U.K
- Division of Cancer Biology, The Institute of Cancer Research (ICR), London, U.K
| | - Sebastian Guettler
- Division of Structural Biology, The Institute of Cancer Research (ICR), London, U.K
- Division of Cancer Biology, The Institute of Cancer Research (ICR), London, U.K
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Singh MK, Shin Y, Ju S, Han S, Kim SS, Kang I. Comprehensive Overview of Alzheimer's Disease: Etiological Insights and Degradation Strategies. Int J Mol Sci 2024; 25:6901. [PMID: 39000011 PMCID: PMC11241648 DOI: 10.3390/ijms25136901] [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: 05/21/2024] [Revised: 06/19/2024] [Accepted: 06/21/2024] [Indexed: 07/14/2024] Open
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and affects millions of individuals globally. AD is associated with cognitive decline and memory loss that worsens with aging. A statistical report using U.S. data on AD estimates that approximately 6.9 million individuals suffer from AD, a number projected to surge to 13.8 million by 2060. Thus, there is a critical imperative to pinpoint and address AD and its hallmark tau protein aggregation early to prevent and manage its debilitating effects. Amyloid-β and tau proteins are primarily associated with the formation of plaques and neurofibril tangles in the brain. Current research efforts focus on degrading amyloid-β and tau or inhibiting their synthesis, particularly targeting APP processing and tau hyperphosphorylation, aiming to develop effective clinical interventions. However, navigating this intricate landscape requires ongoing studies and clinical trials to develop treatments that truly make a difference. Genome-wide association studies (GWASs) across various cohorts identified 40 loci and over 300 genes associated with AD. Despite this wealth of genetic data, much remains to be understood about the functions of these genes and their role in the disease process, prompting continued investigation. By delving deeper into these genetic associations, novel targets such as kinases, proteases, cytokines, and degradation pathways, offer new directions for drug discovery and therapeutic intervention in AD. This review delves into the intricate biological pathways disrupted in AD and identifies how genetic variations within these pathways could serve as potential targets for drug discovery and treatment strategies. Through a comprehensive understanding of the molecular underpinnings of AD, researchers aim to pave the way for more effective therapies that can alleviate the burden of this devastating disease.
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Affiliation(s)
- Manish Kumar Singh
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Yoonhwa Shin
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Songhyun Ju
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Sunhee Han
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Sung Soo Kim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Insug Kang
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea
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Jiang Z, Sullivan PF, Li T, Zhao B, Wang X, Luo T, Huang S, Guan PY, Chen J, Yang Y, Stein JL, Li Y, Liu D, Sun L, Zhu H. The pivotal role of the X-chromosome in the genetic architecture of the human brain. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.08.30.23294848. [PMID: 37693466 PMCID: PMC10491353 DOI: 10.1101/2023.08.30.23294848] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Genes on the X-chromosome are extensively expressed in the human brain. However, little is known for the X-chromosome's impact on the brain anatomy, microstructure, and functional network. We examined 1,045 complex brain imaging traits from 38,529 participants in the UK Biobank. We unveiled potential autosome-X-chromosome interactions, while proposing an atlas outlining dosage compensation (DC) for brain imaging traits. Through extensive association studies, we identified 72 genome-wide significant trait-locus pairs (including 29 new associations) that share genetic architectures with brain-related disorders, notably schizophrenia. Furthermore, we discovered unique sex-specific associations and assessed variations in genetic effects between sexes. Our research offers critical insights into the X-chromosome's role in the human brain, underscoring its contribution to the differences observed in brain structure and functionality between sexes.
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Ji MT, Pashankar N, Harter AM, Nemesh M, Przybyl KJ, Mulligan MK, Chen H, Redei EE. Limited WKY chromosomal regions confer increases in anxiety and fear memory in a F344 congenic rat strain. Physiol Genomics 2024; 56:327-342. [PMID: 38314698 PMCID: PMC11283897 DOI: 10.1152/physiolgenomics.00114.2023] [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: 10/05/2023] [Revised: 01/16/2024] [Accepted: 01/29/2024] [Indexed: 02/07/2024] Open
Abstract
This study investigated the interaction between genetic differences in stress reactivity/coping and environmental challenges, such as acute stress during adolescence on adult contextual fear memory and anxiety-like behaviors. Fischer 344 (F344) and the inbred F344;WKY-Stresp3/Eer congenic strain (congenic), in which chromosomal regions from the Wistar-Kyoto (WKY) strain were introgressed into the F344 background, were exposed to a modified forced swim test during adolescence, while controls were undisturbed. In adulthood, fear learning and memory, assessed by contextual fear conditioning, were significantly greater in congenic animals compared with F344 animals, and stress during adolescence increased them even further in males of both strains. Anxiety-like behavior, measured by the open field test, was also greater in congenic than F344 animals, and stress during adolescence increased it further in both strains of adult males. Whole genome sequencing of the F344;WKY-Stresp3/Eer strain revealed an enrichment of WKY genotypes in chromosomes 9, 14, and 15. An example of functional WKY sequence variations in the congenic strain, cannabinoid receptor interacting protein 1 (Cnrip1) had a Cnrip1 transcript isoform that lacked two exons. Although the original hypothesis that the genetic predisposition to increased anxiety of the WKY donor strain would exaggerate fear memory relative to the background strain was confirmed, the consequences of adolescent stress were strain independent but sex dependent in adulthood. Molecular genomic approaches combined with genetic mapping of WKY sequence variations in chromosomes 9, 14, and 15 could aid in finding quantitative trait genes contributing to the variation in fear memory.NEW & NOTEWORTHY This study found that 1) whole genome sequencing of congenic strains should be a criterion for their recognition; 2) sequence variations between Wistar-Kyoto and Fischer 344 strains at regions of chromosomes 9, 14, and 15 contribute to differences in contextual fear memory and anxiety-like behaviors; and 3) stress during adolescence affects these behaviors in males, but not females, and is independent of strain.
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Affiliation(s)
- Michelle T Ji
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Neha Pashankar
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Aspen M Harter
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Mariya Nemesh
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Katherine J Przybyl
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Megan K Mulligan
- Department of Genetics, University of Tennessee Health Science Center, Memphis, Tennessee, United States
| | - Hao Chen
- Department of Pharmacology, Addiction Science, and Toxicology, University of Tennessee Health Science Center, Memphis, Tennessee, United States
| | - Eva E Redei
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
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9
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Ji Y, Izadi-Seitz M, Landmann A, Schwintzer L, Qualmann B, Kessels MM. EHBP1 Is Critically Involved in the Dendritic Arbor Formation and Is Coupled to Factors Promoting Actin Filament Formation. J Neurosci 2024; 44:e0236232023. [PMID: 38129132 PMCID: PMC10860635 DOI: 10.1523/jneurosci.0236-23.2023] [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: 02/07/2023] [Revised: 12/01/2023] [Accepted: 12/05/2023] [Indexed: 12/23/2023] Open
Abstract
The coordinated action of a plethora of factors is required for the organization and dynamics of membranous structures critically underlying the development and function of cells, organs, and organisms. The evolutionary acquisition of additional amino acid motifs allows for expansion and/or specification of protein functions. We identify a thus far unrecognized motif specific for chordata EHBP1 proteins and demonstrate that this motif is critically required for interaction with syndapin I, an F-BAR domain-containing, membrane-shaping protein predominantly expressed in neurons. Gain-of-function and loss-of-function studies in rat primary hippocampal neurons (of mixed sexes) unraveled that EHBP1 has an important role in neuromorphogenesis. Surprisingly, our analyses uncovered that this newly identified function of EHBP1 did not require the domain responsible for Rab GTPase binding but was strictly dependent on EHBP1's syndapin I binding interface and on the presence of syndapin I in the developing neurons. These findings were underscored by temporally and spatially remarkable overlapping dynamics of EHBP1 and syndapin I at nascent dendritic branch sites. In addition, rescue experiments demonstrated the necessity of two additional EHBP1 domains for dendritic arborization, the C2 and CH domains. Importantly, the additionally uncovered critical involvement of the actin nucleator Cobl in EHBP1 functions suggested that not only static association with F-actin via EHBP1's CH domain is important for dendritic arbor formation but also actin nucleation. Syndapin interactions organize ternary protein complexes composed of EHBP1, syndapin I, and Cobl, and our functional data show that only together these factors give rise to proper cell shape during neuronal development.
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Affiliation(s)
- Yuanyuan Ji
- Institute of Biochemistry I, Jena University Hospital/Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Maryam Izadi-Seitz
- Institute of Biochemistry I, Jena University Hospital/Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Annemarie Landmann
- Institute of Biochemistry I, Jena University Hospital/Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Lukas Schwintzer
- Institute of Biochemistry I, Jena University Hospital/Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Britta Qualmann
- Institute of Biochemistry I, Jena University Hospital/Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Michael M Kessels
- Institute of Biochemistry I, Jena University Hospital/Friedrich Schiller University Jena, 07743 Jena, Germany
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10
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Casciano F, Zauli E, Celeghini C, Caruso L, Gonelli A, Zauli G, Pignatelli A. Retinal Alterations Predict Early Prodromal Signs of Neurodegenerative Disease. Int J Mol Sci 2024; 25:1689. [PMID: 38338966 PMCID: PMC10855697 DOI: 10.3390/ijms25031689] [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: 12/21/2023] [Revised: 01/25/2024] [Accepted: 01/27/2024] [Indexed: 02/12/2024] Open
Abstract
Neurodegenerative diseases are an increasingly common group of diseases that occur late in life with a significant impact on personal, family, and economic life. Among these, Alzheimer's disease (AD) and Parkinson's disease (PD) are the major disorders that lead to mild to severe cognitive and physical impairment and dementia. Interestingly, those diseases may show onset of prodromal symptoms early after middle age. Commonly, the evaluation of these neurodegenerative diseases is based on the detection of biomarkers, where functional and structural magnetic resonance imaging (MRI) have shown a central role in revealing early or prodromal phases, although it can be expensive, time-consuming, and not always available. The aforementioned diseases have a common impact on the visual system due to the pathophysiological mechanisms shared between the eye and the brain. In Parkinson's disease, α-synuclein deposition in the retinal cells, as well as in dopaminergic neurons of the substantia nigra, alters the visual cortex and retinal function, resulting in modifications to the visual field. Similarly, the visual cortex is modified by the neurofibrillary tangles and neuritic amyloid β plaques typically seen in the Alzheimer's disease brain, and this may reflect the accumulation of these biomarkers in the retina during the early stages of the disease, as seen in postmortem retinas of AD patients. In this light, the ophthalmic evaluation of retinal neurodegeneration could become a cost-effective method for the early diagnosis of those diseases, overcoming the limitations of functional and structural imaging of the deep brain. This analysis is commonly used in ophthalmic practice, and interest in it has risen in recent years. This review will discuss the relationship between Alzheimer's disease and Parkinson's disease with retinal degeneration, highlighting how retinal analysis may represent a noninvasive and straightforward method for the early diagnosis of these neurodegenerative diseases.
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Affiliation(s)
- Fabio Casciano
- Department of Translational Medicine and LTTA Centre, University of Ferrara, 44121 Ferrara, Italy
| | - Enrico Zauli
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Claudio Celeghini
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Lorenzo Caruso
- Department of Environment and Prevention Sciences, University of Ferrara, 44121 Ferrara, Italy
| | - Arianna Gonelli
- Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy
| | - Giorgio Zauli
- Research Department, King Khaled Eye Specialistic Hospital, Riyadh 12329, Saudi Arabia
| | - Angela Pignatelli
- Department of Neuroscience and Rehabilitation, University of Ferrara, 44124 Ferrara, Italy
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11
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Zhu L, Yan S, Cao X, Zhang S, Sha Q. Integrating External Controls by Regression Calibration for Genome-Wide Association Study. Genes (Basel) 2024; 15:67. [PMID: 38254957 PMCID: PMC10815702 DOI: 10.3390/genes15010067] [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: 12/13/2023] [Revised: 12/30/2023] [Accepted: 01/01/2024] [Indexed: 01/24/2024] Open
Abstract
Genome-wide association studies (GWAS) have successfully revealed many disease-associated genetic variants. For a case-control study, the adequate power of an association test can be achieved with a large sample size, although genotyping large samples is expensive. A cost-effective strategy to boost power is to integrate external control samples with publicly available genotyped data. However, the naive integration of external controls may inflate the type I error rates if ignoring the systematic differences (batch effect) between studies, such as the differences in sequencing platforms, genotype-calling procedures, population stratification, and so forth. To account for the batch effect, we propose an approach by integrating External Controls into the Association Test by Regression Calibration (iECAT-RC) in case-control association studies. Extensive simulation studies show that iECAT-RC not only can control type I error rates but also can boost statistical power in all models. We also apply iECAT-RC to the UK Biobank data for M72 Fibroblastic disorders by considering genotype calling as the batch effect. Four SNPs associated with fibroblastic disorders have been detected by iECAT-RC and the other two comparison methods, iECAT-Score and Internal. However, our method has a higher probability of identifying these significant SNPs in the scenario of an unbalanced case-control association study.
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Affiliation(s)
| | | | | | | | - Qiuying Sha
- Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA; (L.Z.); (S.Y.); (X.C.); (S.Z.)
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12
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Zhang X, Gomez L, Below JE, Naj AC, Martin ER, Kunkle BW, Bush WS. An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer's Disease. J Alzheimers Dis 2024; 98:1053-1067. [PMID: 38489177 DOI: 10.3233/jad-231075] [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] [Indexed: 03/17/2024]
Abstract
Background The X chromosome is often omitted in disease association studies despite containing thousands of genes that may provide insight into well-known sex differences in the risk of Alzheimer's disease (AD). Objective To model the expression of X chromosome genes and evaluate their impact on AD risk in a sex-stratified manner. Methods Using elastic net, we evaluated multiple modeling strategies in a set of 175 whole blood samples and 126 brain cortex samples, with whole genome sequencing and RNA-seq data. SNPs (MAF > 0.05) within the cis-regulatory window were used to train tissue-specific models of each gene. We apply the best models in both tissues to sex-stratified summary statistics from a meta-analysis of Alzheimer's Disease Genetics Consortium (ADGC) studies to identify AD-related genes on the X chromosome. Results Across different model parameters, sample sex, and tissue types, we modeled the expression of 217 genes (95 genes in blood and 135 genes in brain cortex). The average model R2 was 0.12 (range from 0.03 to 0.34). We also compared sex-stratified and sex-combined models on the X chromosome. We further investigated genes that escaped X chromosome inactivation (XCI) to determine if their genetic regulation patterns were distinct. We found ten genes associated with AD at p < 0.05, with only ARMCX6 in female brain cortex (p = 0.008) nearing the significance threshold after adjusting for multiple testing (α = 0.002). Conclusions We optimized the expression prediction of X chromosome genes, applied these models to sex-stratified AD GWAS summary statistics, and identified one putative AD risk gene, ARMCX6.
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Affiliation(s)
- Xueyi Zhang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adam C Naj
- Department of Biostatistics, Epidemiology, and Informatics, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Eden R Martin
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Brian W Kunkle
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - William S Bush
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
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13
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Wang KW, Yuan YX, Zhu B, Zhang Y, Wei YF, Meng FS, Zhang S, Wang JX, Zhou JY. X chromosome-wide association study of quantitative biomarkers from the Alzheimer's Disease Neuroimaging Initiative study. Front Aging Neurosci 2023; 15:1277731. [PMID: 38035272 PMCID: PMC10682795 DOI: 10.3389/fnagi.2023.1277731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 10/20/2023] [Indexed: 12/02/2023] Open
Abstract
Introduction Alzheimer's disease (AD) is a complex neurodegenerative disease with high heritability. Compared to autosomes, a higher proportion of disorder-associated genes on X chromosome are expressed in the brain. However, only a few studies focused on the identification of the susceptibility loci for AD on X chromosome. Methods Using the data from the Alzheimer's Disease Neuroimaging Initiative Study, we conducted an X chromosome-wide association study between 16 AD quantitative biomarkers and 19,692 single nucleotide polymorphisms (SNPs) based on both the cross-sectional and longitudinal studies. Results We identified 15 SNPs statistically significantly associated with different quantitative biomarkers of the AD. For the cross-sectional study, six SNPs (rs5927116, rs4596772, rs5929538, rs2213488, rs5920524, and rs5945306) are located in or near to six genes DMD, TBX22, LOC101928437, TENM1, SPANXN1, and ZFP92, which have been reported to be associated with schizophrenia or neuropsychiatric diseases in literature. For the longitudinal study, four SNPs (rs4829868, rs5931111, rs6540385, and rs763320) are included in or near to two genes RAC1P4 and AFF2, which have been demonstrated to be associated with brain development or intellectual disability in literature, while the functional annotations of other five novel SNPs (rs12157031, rs428303, rs5953487, rs10284107, and rs5955016) have not been found. Discussion 15 SNPs were found statistically significantly associated with the quantitative biomarkers of the AD. Follow-up study in molecular genetics is needed to verify whether they are indeed related to AD. The findings in this article expand our understanding of the role of the X chromosome in exploring disease susceptibility, introduce new insights into the molecular genetics behind the AD, and may provide a mechanistic clue to further AD-related studies.
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Affiliation(s)
- Kai-Wen Wang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yu-Xin Yuan
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Bin Zhu
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yi Zhang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yi-Fang Wei
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Fan-Shuo Meng
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Shun Zhang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jing-Xuan Wang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ji-Yuan Zhou
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
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14
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Lundberg M, Sng LMF, Szul P, Dunne R, Bayat A, Burnham SC, Bauer DC, Twine NA. Novel Alzheimer's disease genes and epistasis identified using machine learning GWAS platform. Sci Rep 2023; 13:17662. [PMID: 37848535 PMCID: PMC10582044 DOI: 10.1038/s41598-023-44378-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 10/07/2023] [Indexed: 10/19/2023] Open
Abstract
Alzheimer's disease (AD) is a complex genetic disease, and variants identified through genome-wide association studies (GWAS) explain only part of its heritability. Epistasis has been proposed as a major contributor to this 'missing heritability', however, many current methods are limited to only modelling additive effects. We use VariantSpark, a machine learning approach to GWAS, and BitEpi, a tool for epistasis detection, to identify AD associated variants and interactions across two independent cohorts, ADNI and UK Biobank. By incorporating significant epistatic interactions, we captured 10.41% more phenotypic variance than logistic regression (LR). We validate the well-established AD loci, APOE, and identify two novel genome-wide significant AD associated loci in both cohorts, SH3BP4 and SASH1, which are also in significant epistatic interactions with APOE. We show that the SH3BP4 SNP has a modulating effect on the known pathogenic APOE SNP, demonstrating a possible protective mechanism against AD. SASH1 is involved in a triplet interaction with pathogenic APOE SNP and ACOT11, where the SASH1 SNP lowered the pathogenic interaction effect between ACOT11 and APOE. Finally, we demonstrate that VariantSpark detects disease associations with 80% fewer controls than LR, unlocking discoveries in well annotated but smaller cohorts.
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Affiliation(s)
- Mischa Lundberg
- Transformational Bioinformatics, Commonwealth Scientific and Industrial Research Organisation, Sydney, NSW, Australia.
- UQ Frazer Institute, The University of Queensland, Woolloongabba, QLD, Australia.
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia.
| | - Letitia M F Sng
- Transformational Bioinformatics, Commonwealth Scientific and Industrial Research Organisation, Sydney, NSW, Australia
| | - Piotr Szul
- Health Data Semantics and Interoperability, Commonwealth Scientific and Industrial Research Organisation AU, Brisbane, QLD, Australia
| | - Rob Dunne
- Data61, Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia
| | - Arash Bayat
- The Kinghorn Cancer Center (KCCG), Garvan Institute of Medical Research, Sydney, NSW, Australia
| | | | - Denis C Bauer
- Transformational Bioinformatics, Commonwealth Scientific and Industrial Research Organisation, Sydney, NSW, Australia
- Department of Biomedical Sciences, Faculty of Medicine and Health Science, Macquarie University, Macquarie Park, NSW, Australia
- Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW, Australia
| | - Natalie A Twine
- Transformational Bioinformatics, Commonwealth Scientific and Industrial Research Organisation, Sydney, NSW, Australia.
- Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW, Australia.
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15
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Kim BH, Lee H, Ham H, Kim HJ, Jang H, Kim JP, Park YH, Kim M, Seo SW. Clinical effects of novel susceptibility genes for beta-amyloid: a gene-based association study in the Korean population. Front Aging Neurosci 2023; 15:1278998. [PMID: 37901794 PMCID: PMC10602697 DOI: 10.3389/fnagi.2023.1278998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 09/25/2023] [Indexed: 10/31/2023] Open
Abstract
Amyloid-beta (Aβ) is a pathological hallmark of Alzheimer's disease (AD). We aimed to identify genes related to Aβ uptake in the Korean population and investigate the effects of these novel genes on clinical outcomes, including neurodegeneration and cognitive impairments. We recruited a total of 759 Korean participants who underwent neuropsychological tests, brain magnetic resonance imaging, 18F-flutemetamol positron emission tomography, and microarray genotyping data. We performed gene-based association analysis, and also performed expression quantitative trait loci and network analysis. In genome-wide association studies, no single nucleotide polymorphism (SNP) passed the genome-wide significance threshold. In gene-based association analysis, six genes (LCMT1, SCRN2, LRRC46, MRPL10, SP6, and OSBPL7) were significantly associated with Aβ standardised uptake value ratio in the brain. The three most significant SNPs (rs4787307, rs9903904, and rs11079797) on these genes are associated with the regulation of the LCMT1, OSBPL7, and SCRN2 genes, respectively. These SNPs are involved in decreasing hippocampal volume and cognitive scores by mediating Aβ uptake. The 19 enriched gene sets identified by pathway analysis included axon and chemokine activity. Our findings suggest novel susceptibility genes associated with the uptake of Aβ, which in turn leads to worse clinical outcomes. Our findings might lead to the discovery of new AD treatment targets.
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Affiliation(s)
- Bo-Hyun Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - HyunWoo Lee
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hongki Ham
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Hee Jin Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hyemin Jang
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Neurology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jun Pyo Kim
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yu Hyun Park
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Mansu Kim
- Artificial Intelligence Graduate School, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
| | - Sang Won Seo
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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16
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Neumann A, Ohlei O, Küçükali F, Bos IJ, Timsina J, Vos S, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Scheltens P, Teunissen CE, Engelborghs S, Frisoni GB, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Marsh TW, Gorijala P, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Van Broeckhoven C, Tanzi RE, Ten Kate M, Lill CM, Barkhof F, Cruchaga C, Lovestone S, Streffer J, Zetterberg H, Visser PJ, Sleegers K, Bertram L. Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning. Genome Med 2023; 15:79. [PMID: 37794492 PMCID: PMC10548686 DOI: 10.1186/s13073-023-01233-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 09/12/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences. METHODS We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects. RESULTS Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers. CONCLUSIONS These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.
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Affiliation(s)
- Alexander Neumann
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Isabelle J Bos
- Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Stephanie Vos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospital Leuven, Leuven, Belgium
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Universitair Ziekenhuis Brussel (UZ Brussel) and Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Giovanni B Frisoni
- Memory Center, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Oliver Blin
- Clinical Pharmacology & Pharmacovigilance Department, Marseille University Hospital, Marseille, France
| | | | - Régis Bordet
- Neuroscience & Cognition, CHU de Lille, University of Lille, Inserm, France
| | - Alberto Lleó
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Julius Popp
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zurich, Switzerland
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Thomas W Marsh
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Division of Biology & Biomedical Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Christopher Clark
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zurich, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pablo Martinez-Lage
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Mikel Tainta
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
- Zumarraga Hospital, Osakidetza, Integrated Health Organization (OSI) Goierri-Urola Garia, Basque Country, Spain
| | - Richard J B Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Boston, UK
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), 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
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - Cristina Legido-Quigley
- Steno Diabetes Center, Copenhagen, Denmark
- Institute of Pharmaceutical Science, King's College London, London, UK
| | - Christine Van Broeckhoven
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Mara Ten Kate
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Simon Lovestone
- Janssen Medical Ltd, Wycombe, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Johannes Streffer
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- AC Immune SA, Lausanne, Switzerland
- Janssen R&D, LLC, Beerse, Belgium
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute, University College London, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Pieter Jelle Visser
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany.
- Centre for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
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17
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Chakraborty S, Kahali B. Exome-wide analysis reveals role of LRP1 and additional novel loci in cognition. HGG ADVANCES 2023; 4:100208. [PMID: 37305557 PMCID: PMC10248556 DOI: 10.1016/j.xhgg.2023.100208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 05/16/2023] [Indexed: 06/13/2023] Open
Abstract
Cognitive functioning is heritable, with metabolic risk factors known to accelerate age-associated cognitive decline. Identifying genetic underpinnings of cognition is thus crucial. Here, we undertake single-variant and gene-based association analyses upon 6 neurocognitive phenotypes across 6 cognition domains in whole-exome sequencing data from 157,160 individuals of the UK Biobank cohort to expound the genetic architecture of human cognition. We report 20 independent loci associated with 5 cognitive domains while controlling for APOE isoform-carrier status and metabolic risk factors; 18 of which were not previously reported, and implicated genes relating to oxidative stress, synaptic plasticity and connectivity, and neuroinflammation. A subset of significant hits for cognition indicates mediating effects via metabolic traits. Some of these variants also exhibit pleiotropic effects on metabolic traits. We further identify previously unknown interactions of APOE variants with LRP1 (rs34949484 and others, suggestively significant), AMIGO1 (rs146766120; pAla25Thr, significant), and ITPR3 (rs111522866, significant), controlling for lipid and glycemic risks. Our gene-based analysis also suggests that APOC1 and LRP1 have plausible roles along shared pathways of amyloid beta (Aβ) and lipid and/or glucose metabolism in affecting complex processing speed and visual attention. In addition, we report pairwise suggestive interactions of variants harbored in these genes with APOE affecting visual attention. Our report based on this large-scale exome-wide study highlights the effects of neuronal genes, such as LRP1, AMIGO1, and other genomic loci, thus providing further evidence of the genetic underpinnings for cognition during aging.
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Affiliation(s)
- Shreya Chakraborty
- Centre for Brain Research, Indian Institute of Science, Bangalore, Karnataka 560012, India
- Interdisciplinary Mathematical Sciences, Indian Institute of Science, Bangalore, Karnataka 560012, India
| | - Bratati Kahali
- Centre for Brain Research, Indian Institute of Science, Bangalore, Karnataka 560012, India
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18
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Arora S, Santiago JA, Bernstein M, Potashkin JA. Diet and lifestyle impact the development and progression of Alzheimer's dementia. Front Nutr 2023; 10:1213223. [PMID: 37457976 PMCID: PMC10344607 DOI: 10.3389/fnut.2023.1213223] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 06/08/2023] [Indexed: 07/18/2023] Open
Abstract
Dementia is a growing public health concern, with an estimated prevalence of 57 million adults worldwide. Alzheimer's disease (AD) accounts for 60-80% of the cases. Clinical trials testing potential drugs and neuroprotective agents have proven futile, and currently approved drugs only provide symptomatic benefits. Emerging epidemiological and clinical studies suggest that lifestyle changes, including diet and physical activity, offer an alternative therapeutic route for slowing and preventing cognitive decline and dementia. Age is the single most common risk factor for dementia, and it is associated with slowing cellular bioenergetics and metabolic processes. Therefore, a nutrient-rich diet is critical for optimal brain health. Furthermore, type 2 diabetes (T2D) is a risk factor for AD, and diets that reduce the risk of T2D may confer neuroprotection. Foods predominant in Mediterranean, MIND, and DASH diets, including fruits, leafy green vegetables, fish, nuts, and olive oil, may prevent or slow cognitive decline. The mechanisms by which these nutrients promote brain health, however, are not yet completely understood. Other dietary approaches and eating regimes, including ketogenic and intermittent fasting, are also emerging as beneficial for brain health. This review summarizes the pathophysiology, associated risk factors, and the potential neuroprotective pathways activated by several diets and eating regimes that have shown promising results in promoting brain health and preventing dementia.
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Affiliation(s)
- Sarah Arora
- Center for Neurodegenerative Diseases and Therapeutics, Cellular and Molecular Pharmacology Discipline, The Chicago Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States
| | | | - Melissa Bernstein
- Department of Nutrition, College of Health Professions, The Chicago Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States
| | - Judith A. Potashkin
- Center for Neurodegenerative Diseases and Therapeutics, Cellular and Molecular Pharmacology Discipline, The Chicago Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States
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19
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Kang M, Ang TFA, Devine SA, Sherva R, Mukherjee S, Trittschuh EH, Gibbons LE, Scollard P, Lee M, Choi SE, Klinedinst B, Nakano C, Dumitrescu LC, Durant A, Hohman TJ, Cuccaro ML, Saykin AJ, Kukull WA, Bennett DA, Wang LS, Mayeux RP, Haines JL, Pericak-Vance MA, Schellenberg GD, Crane PK, Au R, Lunetta KL, Mez JB, Farrer LA. A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores. Mol Neurodegener 2023; 18:40. [PMID: 37349795 PMCID: PMC10286470 DOI: 10.1186/s13024-023-00633-4] [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: 02/17/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes. METHODS We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP × age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software. RESULTS Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 × 10-9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 × 10-8) and LINC02712 in the total sample (rs145012974, P = 3.66 × 10-8). GRN (rs5848, P = 4.21 × 10-8) and PURG (rs117523305, P = 1.73 × 10-8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 × 10-8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 × 10-9) and PTPRD (rs145989094, P = 8.34 × 10-9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 × 10-8) and PTPRD (rs145989094, P = 3.85 × 10-8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD. CONCLUSION Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias.
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Affiliation(s)
- Moonil Kang
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
| | - Ting Fang Alvin Ang
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Sherral A. Devine
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Richard Sherva
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
| | - Shubhabrata Mukherjee
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Emily H. Trittschuh
- Geriatric Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, WA USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Laura E. Gibbons
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Phoebe Scollard
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Michael Lee
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Seo-Eun Choi
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Brandon Klinedinst
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Connie Nakano
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Logan C. Dumitrescu
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Alaina Durant
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Timothy J. Hohman
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, Miami, FL USA
| | - Andrew J. Saykin
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Services, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, WA USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Richard P. Mayeux
- Department of Neurology, Columbia University School of Medicine, New York, NY USA
| | - Jonathan L. Haines
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH USA
| | | | - Gerard D. Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Paul K. Crane
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA USA
| | - Kathryn L. Lunetta
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
| | - Jesse B. Mez
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
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20
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Wang T, Chen X, Zhang J, Feng Q, Huang M. Deep multimodality-disentangled association analysis network for imaging genetics in neurodegenerative diseases. Med Image Anal 2023; 88:102842. [PMID: 37247468 DOI: 10.1016/j.media.2023.102842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 03/01/2023] [Accepted: 05/15/2023] [Indexed: 05/31/2023]
Abstract
Imaging genetics is a crucial tool that is applied to explore potentially disease-related biomarkers, particularly for neurodegenerative diseases (NDs). With the development of imaging technology, the association analysis between multimodal imaging data and genetic data is gradually being concerned by a wide range of imaging genetics studies. However, multimodal data are fused first and then correlated with genetic data in traditional methods, which leads to an incomplete exploration of their common and complementary information. In addition, the inaccurate formulation in the complex relationships between imaging and genetic data and information loss caused by missing multimodal data are still open problems in imaging genetics studies. Therefore, in this study, a deep multimodality-disentangled association analysis network (DMAAN) is proposed to solve the aforementioned issues and detect the disease-related biomarkers of NDs simultaneously. First, the imaging data are nonlinearly projected into a latent space and imaging representations can be achieved. The imaging representations are further disentangled into common and specific parts by using a multimodal-disentangled module. Second, the genetic data are encoded to achieve genetic representations, and then, the achieved genetic representations are nonlinearly mapped to the common and specific imaging representations to build nonlinear associations between imaging and genetic data through an association analysis module. Moreover, modality mask vectors are synchronously synthesized to integrate the genetic and imaging data, which helps the following disease diagnosis. Finally, the proposed method achieves reasonable diagnosis performance via a disease diagnosis module and utilizes the label information to detect the disease-related modality-shared and modality-specific biomarkers. Furthermore, the genetic representation can be used to impute the missing multimodal data with our learning strategy. Two publicly available datasets with different NDs are used to demonstrate the effectiveness of the proposed DMAAN. The experimental results show that the proposed DMAAN can identify the disease-related biomarkers, which suggests the proposed DMAAN may provide new insights into the pathological mechanism and early diagnosis of NDs. The codes are publicly available at https://github.com/Meiyan88/DMAAN.
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Affiliation(s)
- Tao Wang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Xiumei Chen
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Jiawei Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
| | - Qianjin Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China; Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510515, China.
| | - Meiyan Huang
- School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China; Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou 510515, China; Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510515, China.
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21
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Reitz C, Pericak-Vance MA, Foroud T, Mayeux R. A global view of the genetic basis of Alzheimer disease. Nat Rev Neurol 2023; 19:261-277. [PMID: 37024647 PMCID: PMC10686263 DOI: 10.1038/s41582-023-00789-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/21/2023] [Indexed: 04/08/2023]
Abstract
The risk of Alzheimer disease (AD) increases with age, family history and informative genetic variants. Sadly, there is still no cure or means of prevention. As in other complex diseases, uncovering genetic causes of AD could identify underlying pathological mechanisms and lead to potential treatments. Rare, autosomal dominant forms of AD occur in middle age as a result of highly penetrant genetic mutations, but the most common form of AD occurs later in life. Large-scale, genome-wide analyses indicate that 70 or more genes or loci contribute to AD. One of the major factors limiting progress is that most genetic data have been obtained from non-Hispanic white individuals in Europe and North America, preventing the development of personalized approaches to AD in individuals of other ethnicities. Fortunately, emerging genetic data from other regions - including Africa, Asia, India and South America - are now providing information on the disease from a broader range of ethnicities. Here, we summarize the current knowledge on AD genetics in populations across the world. We predominantly focus on replicated genetic discoveries but also include studies in ethnic groups where replication might not be feasible. We attempt to identify gaps that need to be addressed to achieve a complete picture of the genetic and molecular factors that drive AD in individuals across the globe.
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Affiliation(s)
- Christiane Reitz
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA
- The Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
- Department of Neurology, Columbia University, New York, NY, USA
- Department of Epidemiology, Columbia University, New York, NY, USA
| | - Margaret A Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Richard Mayeux
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.
- The Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA.
- Department of Neurology, Columbia University, New York, NY, USA.
- Department of Epidemiology, Columbia University, New York, NY, USA.
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22
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Papadopoulou E, Pepe G, Konitsiotis S, Chondrogiorgi M, Grigoriadis N, Kimiskidis VK, Tsivgoulis G, Mitsikostas DD, Chroni E, Domouzoglou E, Tsaousis G, Nasioulas G. The evolution of comprehensive genetic analysis in neurology: Implications for precision medicine. J Neurol Sci 2023; 447:120609. [PMID: 36905813 DOI: 10.1016/j.jns.2023.120609] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/28/2023] [Accepted: 03/01/2023] [Indexed: 03/07/2023]
Abstract
Technological advancements have facilitated the availability of reliable and thorough genetic analysis in many medical fields, including neurology. In this review, we focus on the importance of selecting the appropriate genetic test to aid in the accurate identification of disease utilizing currently employed technologies for analyzing monogenic neurological disorders. Moreover, the applicability of comprehensive analysis via NGS for various genetically heterogeneous neurological disorders is reviewed, revealing its efficiency in clarifying a frequently cloudy diagnostic picture and delivering a conclusive and solid diagnosis that is essential for the proper management of the patient. The feasibility and effectiveness of medical genetics in neurology require interdisciplinary cooperation among several medical specialties and geneticists, to select and perform the most relevant test according to each patient's medical history, using the most appropriate technological tools. The prerequisites for a comprehensive genetic analysis are discussed, highlighting the utility of appropriate gene selection, variant annotation, and classification. Moreover, genetic counseling and interdisciplinary collaboration could improve diagnostic yield further. Additionally, a sub-analysis is conducted on the 1,502,769 variation records with submitted interpretations in the Clinical Variation (ClinVar) database, with a focus on neurology-related genes, to clarify the value of suitable variant categorization. Finally, we review the current applications of genetic analysis in the diagnosis and personalized management of neurological patients and the advances in the research and scientific knowledge of hereditary neurological disorders that are evolving the utility of genetic analysis towards the individualization of the treatment strategy.
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Affiliation(s)
| | - Georgia Pepe
- GeneKor Medical SA, Spaton 52, Gerakas 15344, Greece
| | - Spiridon Konitsiotis
- Department of Neurology, University of Ioannina, Stavrou Niarchou Avenue, Ioannina 45500, Greece
| | - Maria Chondrogiorgi
- Department of Neurology, University of Ioannina, Stavrou Niarchou Avenue, Ioannina 45500, Greece
| | - Nikolaos Grigoriadis
- Second Department of Neurology, "AHEPA" University Hospital, Aristotle University of Thessaloniki, St. Kiriakidis 1, Thessaloniki 54636, Greece
| | - Vasilios K Kimiskidis
- First Department of Neurology, "AHEPA" University hospital, Aristotle University of Thessaloniki, St. Kiriakidis 1, Thessaloniki 54636, Greece
| | - Georgios Tsivgoulis
- Second Department of Neurology, School of Medicine, "Attikon" University Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Dimos D Mitsikostas
- First Department of Neurology, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Elisabeth Chroni
- Department of Neurology, School of Medicine, University of Patras, Rio-Patras, Greece
| | - Eleni Domouzoglou
- Department of Pediatrics, University Hospital of Ioannina, Stavrou Niarchou Avenue, Ioannina 45500, Greece
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