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Abstract
Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI but does not manifest as clinical stroke, is highly prevalent in the general population, particularly with increasing age. Advances in technologies and collaborative work have led to substantial progress in the identification of common genetic variants that are associated with cSVD-related stroke (ischaemic and haemorrhagic) and MRI-defined covert cSVD. In this Review, we provide an overview of collaborative studies - mostly genome-wide association studies (GWAS) - that have identified >50 independent genetic loci associated with the risk of cSVD. We describe how these associations have provided novel insights into the biological mechanisms involved in cSVD, revealed patterns of shared genetic variation across cSVD traits, and shed new light on the continuum between rare, monogenic and common, multifactorial cSVD. We consider how GWAS summary statistics have been leveraged for Mendelian randomization studies to explore causal pathways in cSVD and provide genetic evidence for drug effects, and how the combination of findings from GWAS with gene expression resources and drug target databases has enabled identification of putative causal genes and provided proof-of-concept for drug repositioning potential. We also discuss opportunities for polygenic risk prediction, multi-ancestry approaches and integration with other omics data.
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52
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Bellou E, Escott-Price V. Are Alzheimer's and coronary artery diseases genetically related to longevity? Front Psychiatry 2022; 13:1102347. [PMID: 36684006 PMCID: PMC9859055 DOI: 10.3389/fpsyt.2022.1102347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 12/12/2022] [Indexed: 01/07/2023] Open
Abstract
INTRODUCTION In the last decade researchers have attempted to investigate the shared genetic architecture of longevity and age-related diseases and assess whether the increased longevity in certain people is due to protective alleles in the risk genes for a particular condition or whether there are specific "longevity" genes increasing the lifespan independently of age-related conditions' risk genes. The aim of this study was to investigate the shared genetic component between longevity and two age-related conditions. METHODS We performed a cross-trait meta-analysis of publicly available genome-wide data for Alzheimer's disease, coronary artery disease and longevity using a subset-based approach provided by the R package ASSET. RESULTS Despite the lack of strong genetic correlation between longevity and the two diseases, we identified 38 genome-wide significant lead SNPs across 22 independent genomic loci. Of them 6 were found to be potentially shared among the three traits mapping to genes including DAB2IP, DNM2, FCHO1, CLPTM1, and SNRPD2. We also identified 19 novel genome-wide associations for the individual traits in this study. Functional annotations and biological pathway enrichment analyses suggested that pleiotropic variants are involved in clathrin-mediated endocytosis and plasma lipoprotein and neurotransmitter clearance processes. DISCUSSION In summary, we have been able to advance in the knowledge of the genetic overlap existing among longevity and the two most common age-related disorders.
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Affiliation(s)
- Eftychia Bellou
- UK Dementia Research Institute, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Valentina Escott-Price
- Division of Neuroscience and Mental Health, School of Medicine, Cardiff University, Cardiff, United Kingdom
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53
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Abstract
Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5-10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.
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Affiliation(s)
- M Ilyas Kamboh
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
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54
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Gupta R, Kumar P. CREB1 K292 and HINFP K330 as Putative Common Therapeutic Targets in Alzheimer's and Parkinson's Disease. ACS OMEGA 2021; 6:35780-35798. [PMID: 34984308 PMCID: PMC8717564 DOI: 10.1021/acsomega.1c05827] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 12/07/2021] [Indexed: 05/16/2023]
Abstract
Integration of omics data and deciphering the mechanism of a biological regulatory network could be a promising approach to reveal the molecular mechanism involved in the progression of complex diseases, including Alzheimer's and Parkinson's. Despite having an overlapping mechanism in the etiology of Alzheimer's disease (AD) and Parkinson's disease (PD), the exact mechanism and signaling molecules behind them are still unknown. Further, the acetylation mechanism and histone deacetylase (HDAC) enzymes provide a positive direction toward studying the shared phenomenon between AD and PD pathogenesis. For instance, increased expression of HDACs causes a decrease in protein acetylation status, resulting in decreased cognitive and memory function. Herein, we employed an integrative approach to analyze the transcriptomics data that established a potential relationship between AD and PD. Data preprocessing and analysis of four publicly available microarray datasets revealed 10 HUB proteins, namely, CDC42, CD44, FGFR1, MYO5A, NUMA1, TUBB4B, ARHGEF9, USP5, INPP5D, and NUP93, that may be involved in the shared mechanism of AD and PD pathogenesis. Further, we identified the relationship between the HUB proteins and transcription factors that could be involved in the overlapping mechanism of AD and PD. CREB1 and HINFP were the crucial regulatory transcription factors that were involved in the AD and PD crosstalk. Further, lysine acetylation sites and HDAC enzyme prediction revealed the involvement of 15 and 27 potential lysine residues of CREB1 and HINFP, respectively. Our results highlighted the importance of HDAC1(K292) and HDAC6(K330) association with CREB1 and HINFP, respectively, in the AD and PD crosstalk. However, different datasets with a large number of samples and wet lab experimentation are required to validate and pinpoint the exact role of CREB1 and HINFP in the AD and PD crosstalk. It is also possible that the different datasets may or may not affect the results due to analysis parameters. In conclusion, our study potentially highlighted the crucial proteins, transcription factors, biological pathways, lysine residues, and HDAC enzymes shared between AD and PD at the molecular level. The findings can be used to study molecular studies to identify the possible relationship in the AD-PD crosstalk.
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Affiliation(s)
- Rohan Gupta
- Molecular Neuroscience and
Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University (Formerly DCE), Delhi 110042, India
| | - Pravir Kumar
- Molecular Neuroscience and
Functional Genomics Laboratory, Department of Biotechnology, Delhi Technological University (Formerly DCE), Delhi 110042, India
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Nuclear factor I-C disrupts cellular homeostasis between autophagy and apoptosis via miR-200b-Ambra1 in neural tube defects. Cell Death Dis 2021; 13:17. [PMID: 34930914 PMCID: PMC8688449 DOI: 10.1038/s41419-021-04473-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 11/25/2021] [Accepted: 12/10/2021] [Indexed: 02/07/2023]
Abstract
Impaired autophagy and excessive apoptosis disrupt cellular homeostasis and contribute to neural tube defects (NTDs), which are a group of fatal and disabling birth defects caused by the failure of neural tube closure during early embryonic development. However, the regulatory mechanisms underlying NTDs and outcomes remain elusive. Here, we report the role of the transcription factor nuclear factor I-C (NFIC) in maintaining cellular homeostasis in NTDs. We demonstrated that abnormally elevated levels of NFIC in a mouse model of NTDs can interact with the miR-200b promoter, leading to the activation of the transcription of miR-200b, which plays a critical role in NTD formation, as reported in our previous study. Furthermore, miR-200b represses autophagy and triggers apoptosis by directly targeting the autophagy-related gene Ambra1 (Autophagy/Beclin1 regulator 1). Notably, miR-200b inhibitors mitigate the unexpected effects of NFIC on autophagy and apoptosis. Collectively, these results indicate that the NFIC-miR-200b-Ambra1 axis, which integrates transcription- and epigenome-regulated miRNAs and an autophagy regulator, disrupts cellular homeostasis during the closure of the neural tube, and may provide new insight into NTD pathogenesis.
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56
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Miyoshi E, Morabito S, Swarup V. Systems biology approaches to unravel the molecular and genetic architecture of Alzheimer's disease and related tauopathies. Neurobiol Dis 2021; 160:105530. [PMID: 34634459 PMCID: PMC8616667 DOI: 10.1016/j.nbd.2021.105530] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 08/30/2021] [Accepted: 10/07/2021] [Indexed: 11/19/2022] Open
Abstract
Over the years, genetic studies have identified multiple genetic risk variants associated with neurodegenerative disorders and helped reveal new biological pathways and genes of interest. However, genetic risk variants commonly reside in non-coding regions and may regulate distant genes rather than the nearest gene, as well as a gene's interaction partners in biological networks. Systems biology and functional genomics approaches provide the framework to unravel the functional significance of genetic risk variants in disease. In this review, we summarize the genetic and transcriptomic studies of Alzheimer's disease and related tauopathies and focus on the advantages of performing systems-level analyses to interrogate the biological pathways underlying neurodegeneration. Finally, we highlight new avenues of multi-omics analysis with single-cell approaches, which provide unparalleled opportunities to systematically explore cellular heterogeneity, and present an example of how to integrate publicly available single-cell datasets. Systems-level analysis has illuminated the function of many disease risk genes, but much work remains to study tauopathies and to understand spatiotemporal gene expression changes of specific cell types.
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Affiliation(s)
- Emily Miyoshi
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697, USA; Institute for Memory Impairments and Neurological Disorders (MIND), University of California, Irvine, CA 92697, USA
| | - Samuel Morabito
- Institute for Memory Impairments and Neurological Disorders (MIND), University of California, Irvine, CA 92697, USA; Mathematical, Computational and Systems Biology (MCSB) Program, University of California, Irvine, CA 92697, USA
| | - Vivek Swarup
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697, USA; Institute for Memory Impairments and Neurological Disorders (MIND), University of California, Irvine, CA 92697, USA.
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57
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Herranz-Montoya I, Park S, Djouder N. A comprehensive analysis of prefoldins and their implication in cancer. iScience 2021; 24:103273. [PMID: 34761191 PMCID: PMC8567396 DOI: 10.1016/j.isci.2021.103273] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Prefoldins (PFDNs) are evolutionary conserved co-chaperones, initially discovered in archaea but universally present in eukaryotes. PFDNs are prevalently organized into hetero-hexameric complexes. Although they have been overlooked since their discovery and their functions remain elusive, several reports indicate they act as co-chaperones escorting misfolded or non-native proteins to group II chaperonins. Unlike the eukaryotic PFDNs which interact with cytoskeletal components, the archaeal PFDNs can bind and stabilize a wide range of substrates, possibly due to their great structural diversity. The discovery of the unconventional RPB5 interactor (URI) PFDN-like complex (UPC) suggests that PFDNs have versatile functions and are required for different cellular processes, including an important role in cancer. Here, we summarize their functions across different species. Moreover, a comprehensive analysis of PFDNs genomic alterations across cancer types by using large-scale cancer genomic data indicates that PFDNs are a new class of non-mutated proteins significantly overexpressed in some cancer types.
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Affiliation(s)
- Irene Herranz-Montoya
- Growth Factors, Nutrients and Cancer Group, Molecular Oncology Programme, Centro Nacional de Investigaciones Oncológicas, CNIO, Madrid 28029, Spain
| | - Solip Park
- Computational Cancer Genomics Group, Structural Biology Programme, Centro Nacional de Investigaciones Oncológicas, CNIO, Madrid 28029, Spain
| | - Nabil Djouder
- Growth Factors, Nutrients and Cancer Group, Molecular Oncology Programme, Centro Nacional de Investigaciones Oncológicas, CNIO, Madrid 28029, Spain
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A missense variant in SHARPIN mediates Alzheimer's disease-specific brain damages. Transl Psychiatry 2021; 11:590. [PMID: 34785643 PMCID: PMC8595886 DOI: 10.1038/s41398-021-01680-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 08/04/2021] [Accepted: 08/27/2021] [Indexed: 01/23/2023] Open
Abstract
Established genetic risk factors for Alzheimer's disease (AD) account for only a portion of AD heritability. The aim of this study was to identify novel associations between genetic variants and AD-specific brain atrophy. We conducted genome-wide association studies for brain magnetic resonance imaging measures of hippocampal volume and entorhinal cortical thickness in 2643 Koreans meeting the clinical criteria for AD (n = 209), mild cognitive impairment (n = 1449) or normal cognition (n = 985). A missense variant, rs77359862 (R274W), in the SHANK-associated RH Domain Interactor (SHARPIN) gene was associated with entorhinal cortical thickness (p = 5.0 × 10-9) and hippocampal volume (p = 5.1 × 10-12). It revealed an increased risk of developing AD in the mediation analyses. This variant was also associated with amyloid-β accumulation (p = 0.03) and measures of memory (p = 1.0 × 10-4) and executive function (p = 0.04). We also found significant association of other SHARPIN variants with hippocampal volume in the Alzheimer's Disease Neuroimaging Initiative (rs3417062, p = 4.1 × 10-6) and AddNeuroMed (rs138412600, p = 5.9 × 10-5) cohorts. Further, molecular dynamics simulations and co-immunoprecipitation indicated that the variant significantly reduced the binding of linear ubiquitination assembly complex proteins, SHPARIN and HOIL-1 Interacting Protein (HOIP), altering the downstream NF-κB signaling pathway. These findings suggest that SHARPIN plays an important role in the pathogenesis of AD.
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59
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Zai CC, Fabbri C, Hosang GM, Zhang RS, Koyama E, de Luca V, Tiwari AK, King N, Strauss J, Jones I, Jones L, Breen G, Farmer AE, McGuffin P, Vincent JB, Kennedy JL, Lewis CM. Genome-wide association study of suicidal behaviour severity in mood disorders. World J Biol Psychiatry 2021; 22:722-731. [PMID: 33783297 PMCID: PMC11195685 DOI: 10.1080/15622975.2021.1907711] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 12/08/2020] [Accepted: 01/17/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVE Suicide is a major public health problem and it has a prominent genetic component. We performed a genome-wide association study (GWAS) of suicidal behaviour severity. METHODS Suicide behaviour severity was assessed within the Schedules for Clinical Assessment in Neuropsychiatry in our mood disorder sample (n = 3506) for the GWAS. We also performed polygenic risk score analyses to explore genetic sharing between suicidal behaviour severity and a number of phenotypes, including bipolar disorder, major depressive disorder, alcoholism, post-traumatic stress disorder, impulsivity, insomnia, educational attainment, loneliness, maltreatment, and amygdala volume. RESULTS We did not detect genome-wide significant findings at the single-marker or gene level. We report a number of suggestive single-marker and gene-based findings. Our polygenic risk score analyses did not yield significant findings with these phenotypes. CONCLUSIONS Larger sample sizes are required to detect moderate effects.
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Affiliation(s)
- Clement C. Zai
- Neurogenetics Section, Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
- Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
- Harvard Chan School of Public Health, Boston, MA, USA
| | - Chiara Fabbri
- Social, Genetic & Developmental Psychiatry Centre, King’s College London, London, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Georgina M. Hosang
- Centre for Psychiatry, Wolfson Institute of Preventive Medicine, Barts and the London School of Dentistry and Medicine, Queen Mary University of London, London, UK
| | - Ruo Su Zhang
- Neurogenetics Section, Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
| | - Emiko Koyama
- Neurogenetics Section, Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
| | - Vincenzo de Luca
- Neurogenetics Section, Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Arun K. Tiwari
- Neurogenetics Section, Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Nicole King
- Neurogenetics Section, Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
| | - John Strauss
- Neurogenetics Section, Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Ian Jones
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Lisa Jones
- Department of Psychological Medicine, University of Worcester, Worcester, UK
| | - Gerome Breen
- Social, Genetic & Developmental Psychiatry Centre, King’s College London, London, UK
| | - Anne E. Farmer
- Social, Genetic & Developmental Psychiatry Centre, King’s College London, London, UK
| | - Peter McGuffin
- Social, Genetic & Developmental Psychiatry Centre, King’s College London, London, UK
| | - John B. Vincent
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
- Molecular Neuropsychiatry and Development (MiND) Laboratory, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
| | - James L. Kennedy
- Neurogenetics Section, Tanenbaum Centre for Pharmacogenetics, Molecular Brain Science Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Cathryn M. Lewis
- Social, Genetic & Developmental Psychiatry Centre, King’s College London, London, UK
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Okuzono Y, Sakuma H, Miyakawa S, Ifuku M, Lee J, Das D, Banerjee A, Zhao Y, Yamamoto K, Ando T, Sato S. Reduced TREM2 activation in microglia of patients with Alzheimer's disease. FEBS Open Bio 2021; 11:3063-3080. [PMID: 34523252 PMCID: PMC8564098 DOI: 10.1002/2211-5463.13300] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 08/27/2021] [Accepted: 09/13/2021] [Indexed: 12/13/2022] Open
Abstract
Loss-of-function variants of triggering receptor expressed on myeloid cells 2 (TREM2) increase the risk of developing Alzheimer's disease (AD). The mechanism through which TREM2 contributes to the disease (TREM2 activation vs inactivation) is largely unknown. Here, we analyzed changes in a gene set downstream of TREM2 to determine whether TREM2 signaling is modified by AD progression. We generated an anti-human TREM2 agonistic antibody and defined TREM2 activation in terms of the downstream expression changes induced by this antibody in microglia developed from human induced pluripotent stem cells (iPSC). Differentially expressed genes (DEGs) following TREM2 activation were compared with the gene set extracted from microglial single nuclear RNA sequencing data of patients with AD, using gene set enrichment analysis. We isolated an anti-TREM2-specific agonistic antibody, Hyb87, from anti-human TREM2 antibodies generated using binding and agonism assays, which helped us identify 300 upregulated and 251 downregulated DEGs. Pathway enrichment analysis suggested that TREM2 activation may be associated with Th2-related pathways. TREM2 activation was lower in AD microglia than in microglia from healthy subjects or patients with mild cognitive impairment. TREM2 activation also showed a significant negative correlation with disease progression. Pathway enrichment analysis of DEGs controlled by TREM2 activity indicated that TREM2 activation in AD may lead to anti-apoptotic signaling, immune response, and cytoskeletal changes in the microglia. We showed that TREM2 activation decreases with AD progression, in support of a protective role of TREM2 activation in AD. In addition, the agonistic anti-TREM2 antibody can be used to identify TREM2 activation state in AD microglia.
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Affiliation(s)
- Yuumi Okuzono
- Immune Cell Engineered TherapeuticsResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
| | - Hiroyuki Sakuma
- Neuroscience Drug Discovery UnitResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
| | - Shuuichi Miyakawa
- Immune Cell Engineered TherapeuticsResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
| | - Masataka Ifuku
- Immune Cell Engineered TherapeuticsResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
| | - Jonghun Lee
- Computational BiologyResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
| | - Debashree Das
- Early Target DiscoveryResearch, Takeda California, Inc.San DiegoCAUSA
| | - Antara Banerjee
- GI ImmunologyResearch, Takeda California, Inc.San DiegoCAUSA
| | - Yang Zhao
- Computational BiologyResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
| | - Koji Yamamoto
- Computational BiologyResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
| | - Tatsuya Ando
- Computational BiologyResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
| | - Shuji Sato
- Neuroscience Drug Discovery UnitResearch, Takeda Pharmaceutical Company LimitedFujisawaJapan
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Abuelezz NZ, Nasr FE, AbdulKader MA, Bassiouny AR, Zaky A. MicroRNAs as Potential Orchestrators of Alzheimer's Disease-Related Pathologies: Insights on Current Status and Future Possibilities. Front Aging Neurosci 2021; 13:743573. [PMID: 34712129 PMCID: PMC8546247 DOI: 10.3389/fnagi.2021.743573] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 09/13/2021] [Indexed: 12/17/2022] Open
Abstract
Alzheimer's disease (AD) is a progressive and deleterious neurodegenerative disease, strongly affecting the cognitive functions and memory of seniors worldwide. Around 58% of the affected patients live in low and middle-income countries, with estimates of increasing deaths caused by AD in the coming decade. AD is a multifactor pathology. Mitochondrial function declines in AD brain and is currently emerging as a hallmark of this disease. It has been considered as one of the intracellular processes severely compromised in AD. Many mitochondrial parameters decline already during aging; mitochondrial efficiency for energy production, reactive oxygen species (ROS) metabolism and the de novo synthesis of pyrimidines, to reach an extensive functional failure, concomitant with the onset of neurodegenerative conditions. Besides its impact on cognitive functions, AD is characterized by loss of synapses, extracellular amyloid plaques composed of the amyloid-β peptide (Aβ), and intracellular aggregates of hyperphosphorylated Tau protein, accompanied by drastic sleep disorders, sensory function alterations and pain sensitization. Unfortunately, till date, effective management of AD-related disorders and early, non-invasive AD diagnostic markers are yet to be found. MicroRNAs (miRNAs) are small non-coding nucleic acids that regulate key signaling pathway(s) in various disease conditions. About 70% of experimentally detectable miRNAs are expressed in the brain where they regulate neurite outgrowth, dendritic spine morphology, and synaptic plasticity. Increasing studies suggest that miRNAs are intimately involved in synaptic function and specific signals during memory formation. This has been the pivotal key for considering miRNAs crucial molecules to be studied in AD. MicroRNAs dysfunctions are increasingly acknowledged as a pivotal contributor in AD via deregulating genes involved in AD pathogenesis. Moreover, miRNAs have been proved to control pain sensitization processes and regulate circadian clock system that affects the sleep process. Interestingly, the differential expression of miRNA panels implies their emerging potential as diagnostic AD biomarkers. In this review, we will present an updated analysis of miRNAs role in regulating signaling processes that are involved in AD-related pathologies. We will discuss the current challenges against wider use of miRNAs and the future promising capabilities of miRNAs as diagnostic and therapeutic means for better management of AD.
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Affiliation(s)
- Nermeen Z Abuelezz
- Biochemistry Department, College of Pharmaceutical Sciences and Drug Manufacturing, Misr University for Science and Technology, Giza, Egypt
| | - Fayza Eid Nasr
- Department of Biochemistry, Faculty of Science, Alexandria University, Alexandria, Egypt
| | | | - Ahmad R Bassiouny
- Department of Biochemistry, Faculty of Science, Alexandria University, Alexandria, Egypt
| | - Amira Zaky
- Department of Biochemistry, Faculty of Science, Alexandria University, Alexandria, Egypt
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Sanyal N, Napolioni V, de Rochemonteix M, Belloy ME, Caporaso NE, Landi MT, Greicius MD, Chatterjee N, Han SS. A Robust Test for Additive Gene-Environment Interaction Under the Trend Effect of Genotype Using an Empirical Bayes-Type Shrinkage Estimator. Am J Epidemiol 2021; 190:1948-1960. [PMID: 33942053 DOI: 10.1093/aje/kwab124] [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: 07/01/2020] [Revised: 04/19/2021] [Accepted: 04/21/2021] [Indexed: 11/12/2022] Open
Abstract
Evaluating gene by environment (G × E) interaction under an additive risk model (i.e., additive interaction) has gained wider attention. Recently, statistical tests have been proposed for detecting additive interaction, utilizing an assumption on gene-environment (G-E) independence to boost power, that do not rely on restrictive genetic models such as dominant or recessive models. However, a major limitation of these methods is a sharp increase in type I error when this assumption is violated. Our goal was to develop a robust test for additive G × E interaction under the trend effect of genotype, applying an empirical Bayes-type shrinkage estimator of the relative excess risk due to interaction. The proposed method uses a set of constraints to impose the trend effect of genotype and builds an estimator that data-adaptively shrinks an estimator of relative excess risk due to interaction obtained under a general model for G-E dependence using a retrospective likelihood framework. Numerical study under varying levels of departures from G-E independence shows that the proposed method is robust against the violation of the independence assumption while providing an adequate balance between bias and efficiency compared with existing methods. We applied the proposed method to the genetic data of Alzheimer disease and lung cancer.
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63
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Kang S, Gim J, Lee J, Gunasekaran TI, Choi KY, Lee JJ, Seo EH, Ko PW, Chung JY, Choi SM, Lee YM, Jeong JH, Park KW, Song MK, Lee HW, Kim KW, Choi SH, Lee DY, Kim SY, Kim H, Kim BC, Ikeuchi T, Lee KH. Potential Novel Genes for Late-Onset Alzheimer's Disease in East-Asian Descent Identified by APOE-Stratified Genome-Wide Association Study. J Alzheimers Dis 2021; 82:1451-1460. [PMID: 34151794 PMCID: PMC8461686 DOI: 10.3233/jad-210145] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
The present study reports two novel genome-wide significant loci for late-onset Alzheimer’s disease (LOAD) identified from APOE ε4 non-carrier subjects of East Asian origin. A genome-wide association study of Alzheimer’s disease was performed in 2,291 Korean seniors in the discovery phase, from the Gwangju Alzheimer’ and Related Dementias (GARD) cohort study. The study was replicated in a Japanese cohort of 1,956 subjects that suggested two novel susceptible SNPs in two genes: LRIG1 and CACNA1A. This study demonstrates that the discovery of AD-associated variants is feasible in non-European ethnic groups using samples comprising fewer subjects from the more homogeneous genetic background.
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Affiliation(s)
- Sarang Kang
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Integrative Biological Sciences, Chosun University, Gwangju, Republic of Korea
| | - Jungsoo Gim
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Integrative Biological Sciences, Chosun University, Gwangju, Republic of Korea.,Neurozen Inc., Seoul, Republic of Korea.,Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Jiwoon Lee
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Tamil Iniyan Gunasekaran
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Kyu Yeong Choi
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea
| | - Jang Jae Lee
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea
| | - Eun Hyun Seo
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Premedical Science, Chosun University College of Medicine, Gwangju, Republic of Korea
| | - Pan-Woo Ko
- Department of Neurology, Kyungpook National University School of Medicine, Daegu, Republic of Korea
| | - Ji Yeon Chung
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Neurology, Chosun University Hospital, Gwangju, Republic of Korea
| | - Seong-Min Choi
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Neurology, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Young Min Lee
- Department of Psychiatry, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha WomansUniversity School of Medicine, Seoul, Republic of Korea
| | - Kyung Won Park
- Department of Neurology, Donga University College of Medicine, Busan, Republic of Korea
| | - Min Kyung Song
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Chonnam National University Gwangju 2nd Geriatric Hospital, Gwangju, Republic of Korea
| | - Ho-Won Lee
- Department of Neurology, Kyungpook National University School of Medicine, Daegu, Republic of Korea
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Seong Hye Choi
- Department of Neurology, Inha University School of Medicine, Incheon, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Sang Yun Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Hoowon Kim
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Neurology, Chosun University Hospital, Gwangju, Republic of Korea
| | - Byeong C Kim
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Neurology, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kun Ho Lee
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Integrative Biological Sciences, Chosun University, Gwangju, Republic of Korea.,Neurozen Inc., Seoul, Republic of Korea.,Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea.,Korea Brain Research Institute, Daegu, Republic of Korea
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Horimoto ARVR, Xue D, Thornton TA, Blue EE. Admixture mapping reveals the association between Native American ancestry at 3q13.11 and reduced risk of Alzheimer's disease in Caribbean Hispanics. Alzheimers Res Ther 2021; 13:122. [PMID: 34217363 PMCID: PMC8254995 DOI: 10.1186/s13195-021-00866-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/20/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND Genetic studies have primarily been conducted in European ancestry populations, identifying dozens of loci associated with late-onset Alzheimer's disease (AD). However, much of AD's heritability remains unexplained; as the prevalence of AD varies across populations, the genetic architecture of the disease may also vary by population with the presence of novel variants or loci. METHODS We conducted genome-wide analyses of AD in a sample of 2565 Caribbean Hispanics to better understand the genetic contribution to AD in this population. Statistical analysis included both admixture mapping and association testing. Evidence for differential gene expression within regions of interest was collected from independent transcriptomic studies comparing AD cases and controls in samples with primarily European ancestry. RESULTS Our genome-wide association study of AD identified no loci reaching genome-wide significance. However, a genome-wide admixture mapping analysis that tests for association between a haplotype's ancestral origin and AD status detected a genome-wide significant association with chromosome 3q13.11 (103.7-107.7Mb, P = 8.76E-07), driven by a protective effect conferred by the Native American ancestry (OR = 0.58, 95%CI = 0.47-0.73). Within this region, two variants were significantly associated with AD after accounting for the number of independent tests (rs12494162, P = 2.33E-06; rs1731642, P = 6.36E-05). The significant admixture mapping signal is composed of 15 haplotype blocks spanning 5 protein-coding genes (ALCAM, BBX, CBLB, CCDC54, CD47) and four brain-derived topologically associated domains, and includes markers significantly associated with the expression of ALCAM, BBX, CBLB, and CD47 in the brain. ALCAM and BBX were also significantly differentially expressed in the brain between AD cases and controls with European ancestry. CONCLUSION These results provide multiethnic evidence for a relationship between AD and multiple genes at 3q13.11 and illustrate the utility of leveraging genetic ancestry diversity via admixture mapping for new insights into AD.
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Affiliation(s)
| | - Diane Xue
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA
| | - Elizabeth E Blue
- Institute for Public Health Genetics, University of Washington, Seattle, WA, USA.
- Division of Medical Genetics, University of Washington, BOX 357720, Seattle, WA, 98195-7720, USA.
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Suthar SK, Alam MM, Lee J, Monga J, Joseph A, Lee SY. Bioinformatic Analyses of Canonical Pathways of TSPOAP1 and its Roles in Human Diseases. Front Mol Biosci 2021; 8:667947. [PMID: 34212002 PMCID: PMC8239723 DOI: 10.3389/fmolb.2021.667947] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 05/21/2021] [Indexed: 12/19/2022] Open
Abstract
TSPO-associated protein 1 (TSPOAP1) is a cytoplasmic protein and is closely associated with its mitochondrial transmembrane protein partner translocator protein (TSPO). To decipher the canonical signalling pathways of TSPOAP1, its role in human diseases and disorders, and relationship with TSPO; expression analyses of TSPOAP1- and TSPO-associated human genes were performed by Qiagen Ingenuity Pathway Analysis (IPA). In the expression analysis, necroptosis and sirtuin signalling pathways, mitochondrial dysfunction, and inflammasome were the top canonical pathways for both TSPOAP1 and TSPO, confirming the close relationship between these two proteins. A distribution analysis of common proteins in all the canonical pathways predicted for TSPOAP1 revealed that tumor necrosis factor receptor 1 (TNFR1), vascular cell adhesion molecule 1 (VCAM1), cyclic AMP response element-binding protein 1 (CREB1), T-cell receptor (TCR), nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain containing 3 (NLRP3), DNA-dependent protein kinase (DNA-PK or PRKDC), and mitochondrial permeability transition pore (mPTP) were the major interaction partners of TSPOAP1, highlighting the role of TSPOAP1 in inflammation, particularly neuroinflammation. An analysis of the overlap between TSPO and TSPOAP1 Homo sapiens genes and top-ranked canonical pathways indicated that TSPO and TSPOAP1 interact via voltage-dependent anion-selective channels (VDAC1/2/3). A heat map analysis indicated that TSPOAP1 has critical roles in inflammatory, neuroinflammatory, psychiatric, and metabolic diseases and disorders, and cancer. Taken together, this information improves our understanding of the mechanism of action and biological functions of TSPOAP1 as well as its relationship with TSPO; furthermore, these results could provide new directions for in-depth functional studies of TSPOAP1 aimed at unmasking its detailed functions.
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Affiliation(s)
- Sharad Kumar Suthar
- Neuroscience Research Institute, Gachon University, Incheon, South Korea
- Manipal College of Pharmaceutical Sciences, Manipal University, Manipal, India
| | | | - Jihye Lee
- Neuroscience Research Institute, Gachon University, Incheon, South Korea
| | - Jitender Monga
- Department of Urology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Alex Joseph
- Manipal College of Pharmaceutical Sciences, Manipal University, Manipal, India
| | - Sang-Yoon Lee
- Neuroscience Research Institute, Gachon University, Incheon, South Korea
- Department of Neuroscience, College of Medicine, Gachon University, Incheon, South Korea
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66
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Onaolapo OJ, Onaolapo AY, Olowe OA, Udoh MO, Udoh DO, Nathaniel TI. Melatonin and Melatonergic Influence on Neuronal Transcription Factors: Implications for the Development of Novel Therapies for Neurodegenerative Disorders. Curr Neuropharmacol 2021; 18:563-577. [PMID: 31885352 PMCID: PMC7457420 DOI: 10.2174/1570159x18666191230114339] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 12/16/2019] [Accepted: 12/28/2019] [Indexed: 01/04/2023] Open
Abstract
Melatonin is a multifunctional signalling molecule that is secreted by the mammalian pineal gland, and also found in a number of organisms including plants and bacteria. Research has continued to uncover an ever-increasing number of processes in which melatonin is known to play crucial roles in mammals. Amongst these functions is its contribution to cell multiplication, differentiation and survival in the brain. Experimental studies show that melatonin can achieve these functions by influencing transcription factors which control neuronal and glial gene expression. Since neuronal survival and differentiation are processes that are important determinants of the pathogenesis, course and outcome of neurodegenerative disorders; the known and potential influences of melatonin on neuronal and glial transcription factors are worthy of constant examination. In this review, relevant scientific literature on the role of melatonin in preventing or altering the course and outcome of neurodegenerative disorders, by focusing on melatonin's influence on transcription factors is examined. A number of transcription factors whose functions can be influenced by melatonin in neurodegenerative disease models have also been highlighted. Finally, the therapeutic implications of melatonin's influences have also been discussed and the potential limitations to its applications have been highlighted.
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Affiliation(s)
- Olakunle J. Onaolapo
- Behavioural Neuroscience/Neuropharmacology Unit, Department of Pharmacology, Ladoke Akintola University of Technology, Osogbo, Osun State, Nigeria
| | - Adejoke Y. Onaolapo
- Behavioural Neuroscience/Neurobiology Unit, Department of Anatomy, Ladoke Akintola University of Technology, Ogbomosho, Oyo State, Nigeria
| | - Olugbenga A. Olowe
- Molecular Bacteriology and Immunology Unit, Department of Medical Microbiology and Parasitology, Ladoke Akintola University of Technology, Osogbo, Osun State, Nigeria
| | - Mojisola O. Udoh
- Department of Pathology, University of Benin Teaching Hospital, Benin City, Nigeria
| | - David O. Udoh
- Division of Neurological Surgery, Department of Surgery, University of Benin Teaching Hospital, Benin City, Edo State, Nigeria
| | - Thomas I. Nathaniel
- University of South Carolina School of Medicine-Greenville, Greenville, South Carolina, 29605, United States
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67
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Novel Alzheimer's disease risk variants identified based on whole-genome sequencing of APOE ε4 carriers. Transl Psychiatry 2021; 11:296. [PMID: 34011927 PMCID: PMC8134477 DOI: 10.1038/s41398-021-01412-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 04/16/2021] [Accepted: 04/22/2021] [Indexed: 02/01/2023] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with a complex genetic etiology. Besides the apolipoprotein E ε4 (APOE ε4) allele, a few dozen other genetic loci associated with AD have been identified through genome-wide association studies (GWAS) conducted mainly in individuals of European ancestry. Recently, several GWAS performed in other ethnic groups have shown the importance of replicating studies that identify previously established risk loci and searching for novel risk loci. APOE-stratified GWAS have yielded novel AD risk loci that might be masked by, or be dependent on, APOE alleles. We performed whole-genome sequencing (WGS) on DNA from blood samples of 331 AD patients and 169 elderly controls of Korean ethnicity who were APOE ε4 carriers. Based on WGS data, we designed a customized AD chip (cAD chip) for further analysis on an independent set of 543 AD patients and 894 elderly controls of the same ethnicity, regardless of their APOE ε4 allele status. Combined analysis of WGS and cAD chip data revealed that SNPs rs1890078 (P = 6.64E-07) and rs12594991 (P = 2.03E-07) in SORCS1 and CHD2 genes, respectively, are novel genetic variants among APOE ε4 carriers in the Korean population. In addition, nine possible novel variants that were rare in individuals of European ancestry but common in East Asia were identified. This study demonstrates that APOE-stratified analysis is important for understanding the genetic background of AD in different populations.
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68
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Patel D, Zhang X, Farrell JJ, Chung J, Stein TD, Lunetta KL, Farrer LA. Cell-type-specific expression quantitative trait loci associated with Alzheimer disease in blood and brain tissue. Transl Psychiatry 2021; 11:250. [PMID: 33907181 PMCID: PMC8079392 DOI: 10.1038/s41398-021-01373-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 03/24/2021] [Accepted: 04/08/2021] [Indexed: 02/02/2023] Open
Abstract
Because regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1 Mb of genes was evaluated using linear regression models for unrelated subjects and linear-mixed models for related subjects. Cell-type-specific eQTL (ct-eQTL) models included an interaction term for the expression of "proxy" genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell types is supported by the observation that a large portion of GWS ct-eQTLs map within 1 Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type-specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type-specific analysis.
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Affiliation(s)
- Devanshi Patel
- Bioinformatics Graduate Program, Boston University, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - John J Farrell
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Jaeyoon Chung
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Thor D Stein
- Department of Pathology & Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Lindsay A Farrer
- Bioinformatics Graduate Program, Boston University, Boston, MA, USA.
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA.
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
- Departments of Neurology and Ophthalmology, Boston University School of Medicine, Boston, MA, USA.
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
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69
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Dehghani N, Bras J, Guerreiro R. How understudied populations have contributed to our understanding of Alzheimer's disease genetics. Brain 2021; 144:1067-1081. [PMID: 33889936 DOI: 10.1093/brain/awab028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 10/30/2020] [Accepted: 11/17/2020] [Indexed: 12/14/2022] Open
Abstract
The majority of genome-wide association studies have been conducted using samples with a broadly European genetic background. As a field, we acknowledge this limitation and the need to increase the diversity of populations studied. A major challenge when designing and conducting such studies is to assimilate large samples sizes so that we attain enough statistical power to detect variants associated with disease, particularly when trying to identify variants with low and rare minor allele frequencies. In this review, we aimed to illustrate the benefits to genetic characterization of Alzheimer's disease, in researching currently understudied populations. This is important for both fair representation of world populations and the translatability of findings. To that end, we conducted a literature search to understand the contributions of studies, on different populations, to Alzheimer's disease genetics. Using both PubMed and Alzforum Mutation Database, we systematically quantified the number of studies reporting variants in known disease-causing genes, in a worldwide manner, and discuss the contributions of research in understudied populations to the identification of novel genetic factors in this disease. Additionally, we compared the effects of genome-wide significant single nucleotide polymorphisms across populations by focusing on loci that show different association profiles between populations (a key example being APOE). Reports of variants in APP, PSEN1 and PSEN2 can initially determine whether patients from a country have been studied for Alzheimer's disease genetics. Most genome-wide significant associations in non-Hispanic white genome-wide association studies do not reach genome-wide significance in such studies of other populations, with some suggesting an opposite effect direction; this is likely due to much smaller sample sizes attained. There are, however, genome-wide significant associations first identified in understudied populations which have yet to be replicated. Familial studies in understudied populations have identified rare, high effect variants, which have been replicated in other populations. This work functions to both highlight how understudied populations have furthered our understanding of Alzheimer's disease genetics, and to help us gauge our progress in understanding the genetic architecture of this disease in all populations.
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Affiliation(s)
- Nadia Dehghani
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, USA
| | - Jose Bras
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, USA.,Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI, USA
| | - Rita Guerreiro
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, USA.,Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI, USA
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Zhou K, Wang Y, Bretonnel Cohen K, Kim JD, Ma X, Shen Z, Meng X, Xia J. Bridging heterogeneous mutation data to enhance disease gene discovery. Brief Bioinform 2021; 22:6224263. [PMID: 33847357 DOI: 10.1093/bib/bbab079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 02/01/2021] [Accepted: 02/19/2021] [Indexed: 12/18/2022] Open
Abstract
Bridging heterogeneous mutation data fills in the gap between various data categories and propels discovery of disease-related genes. It is known that genome-wide association study (GWAS) infers significant mutation associations that link genotype and phenotype. However, due to the differences of size and quality between GWAS studies, not all de facto vital variations are able to pass the multiple testing. In the meantime, mutation events widely reported in literature unveil typical functional biological process, including mutation types like gain of function and loss of function. To bring together the heterogeneous mutation data, we propose a 'Gene-Disease Association prediction by Mutation Data Bridging (GDAMDB)' pipeline with a statistic generative model. The model learns the distribution parameters of mutation associations and mutation types and recovers false-negative GWAS mutations that fail to pass significant test but represent supportive evidences of functional biological process in literature. Eventually, we applied GDAMDB in Alzheimer's disease (AD) and predicted 79 AD-associated genes. Besides, 12 of them from the original GWAS, 60 of them are supported to be AD-related by other GWAS or literature report, and rest of them are newly predicted genes. Our model is capable of enhancing the GWAS-based gene association discovery by well combining text mining results. The positive result indicates that bridging the heterogeneous mutation data is contributory for the novel disease-related gene discovery.
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Affiliation(s)
- Kaiyin Zhou
- Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province, P.R. China
| | - Yuxing Wang
- Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province, P.R. China
| | - Kevin Bretonnel Cohen
- Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province, P.R. China
| | - Jin-Dong Kim
- Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province, P.R. China
| | - Xiaohang Ma
- Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province, P.R. China
| | - Zhixue Shen
- Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province, P.R. China
| | - Xiangyu Meng
- Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province, P.R. China
| | - Jingbo Xia
- Hubei Key Lab of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, Hubei Province, P.R. China
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Dharshini SAP, Jemimah S, Taguchi YH, Gromiha MM. Exploring Common Therapeutic Targets for Neurodegenerative Disorders Using Transcriptome Study. Front Genet 2021; 12:639160. [PMID: 33815473 PMCID: PMC8017312 DOI: 10.3389/fgene.2021.639160] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 02/22/2021] [Indexed: 11/13/2022] Open
Abstract
Alzheimer's disease (AD) and Parkinson's disease (PD) are well-known neuronal degenerative disorders that share common pathological events. Approved medications alleviate symptoms but do not address the root cause of the disease. Energy dysfunction in the neuronal population leads to various pathological events and ultimately results in neuronal death. Identifying common therapeutic targets for these disorders may help in the drug discovery process. The Brodmann area 9 (BA9) region is affected in both the disease conditions and plays an essential role in cognitive, motor, and memory-related functions. Analyzing transcriptome data of BA9 provides deep insights related to common pathological pathways involved in AD and PD. In this work, we map the preprocessed BA9 fastq files generated by RNA-seq for disease and control samples with reference hg38 genomic assembly and identify common variants and differentially expressed genes (DEG). These variants are predominantly located in the 3' UTR (non-promoter) region, affecting the conserved transcription factor (TF) binding motifs involved in the methylation and acetylation process. We have constructed BA9-specific functional interaction networks, which show the relationship between TFs and DEGs. Based on expression signature analysis, we propose that MAPK1, VEGFR1/FLT1, and FGFR1 are promising drug targets to restore blood-brain barrier functionality by reducing neuroinflammation and may save neurons.
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Affiliation(s)
- S Akila Parvathy Dharshini
- Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India
| | - Sherlyn Jemimah
- Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India
| | - Y H Taguchi
- Department of Physics, Chuo University, Hachioji, Japan
| | - M Michael Gromiha
- Protein Bioinformatics Lab, Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India
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72
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Vogrinc D, Goričar K, Dolžan V. Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review. Front Aging Neurosci 2021; 13:646901. [PMID: 33815092 PMCID: PMC8012500 DOI: 10.3389/fnagi.2021.646901] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 02/16/2021] [Indexed: 12/14/2022] Open
Abstract
Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting a significant part of the population. The majority of AD cases occur in the elderly with a typical age of onset of the disease above 65 years. AD presents a major burden for the healthcare system and since population is rapidly aging, the burden of the disease will increase in the future. However, no effective drug treatment for a full-blown disease has been developed to date. The genetic background of AD is extensively studied; numerous genome-wide association studies (GWAS) identified significant genes associated with increased risk of AD development. This review summarizes more than 100 risk loci. Many of them may serve as biomarkers of AD progression, even in the preclinical stage of the disease. Furthermore, we used GWAS data to identify key pathways of AD pathogenesis: cellular processes, metabolic processes, biological regulation, localization, transport, regulation of cellular processes, and neurological system processes. Gene clustering into molecular pathways can provide background for identification of novel molecular targets and may support the development of tailored and personalized treatment of AD.
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Affiliation(s)
| | | | - Vita Dolžan
- Pharmacogenetics Laboratory, Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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73
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Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer's disease risk. Transl Psychiatry 2021; 11:151. [PMID: 33654092 PMCID: PMC7925686 DOI: 10.1038/s41398-021-01272-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 01/21/2021] [Accepted: 02/01/2021] [Indexed: 12/20/2022] Open
Abstract
Alzheimer's disease (AD) has no cure, but early detection and risk prediction could allow earlier intervention. Genetic risk factors may differ between ethnic populations. To discover novel susceptibility loci of AD in the Japanese population, we conducted a genome-wide association study (GWAS) with 3962 AD cases and 4074 controls. Out of 4,852,957 genetic markers that passed stringent quality control filters, 134 in nine loci, including APOE and SORL1, were convincingly associated with AD. Lead SNPs located in seven novel loci were genotyped in an independent Japanese AD case-control cohort. The novel locus FAM47E reached genome-wide significance in a meta-analysis of association results. This is the first report associating the FAM47E locus with AD in the Japanese population. A trans-ethnic meta-analysis combining the results of the Japanese data sets with summary statistics from stage 1 data of the International Genomics of Alzheimer's Project identified an additional novel susceptibility locus in OR2B2. Our data highlight the importance of performing GWAS in non-European populations.
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74
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Schwartzentruber J, Cooper S, Liu JZ, Barrio-Hernandez I, Bello E, Kumasaka N, Young AMH, Franklin RJM, Johnson T, Estrada K, Gaffney DJ, Beltrao P, Bassett A. Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes. Nat Genet 2021; 53:392-402. [PMID: 33589840 PMCID: PMC7610386 DOI: 10.1038/s41588-020-00776-w] [Citation(s) in RCA: 241] [Impact Index Per Article: 80.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 12/23/2020] [Indexed: 01/30/2023]
Abstract
Genome-wide association studies have discovered numerous genomic loci associated with Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with >50% probability each of being causally involved in AD risk and others strongly suggested by functional annotation. We followed this with colocalization analyses across 109 gene expression quantitative trait loci datasets and prioritization of genes by using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we found that evidence converged on likely causal genes, including the above four genes, and those at previously discovered AD loci, including BIN1, APH1B, PTK2B, PILRA and CASS4.
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Affiliation(s)
- Jeremy Schwartzentruber
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK.
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
| | - Sarah Cooper
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Inigo Barrio-Hernandez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
- Open Targets, Wellcome Genome Campus, Cambridge, UK
| | - Erica Bello
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Adam M H Young
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Robin J M Franklin
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Toby Johnson
- Target Sciences-R&D, GSK Medicines Research Centre, Stevenage, UK
| | | | - Daniel J Gaffney
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
- Genomics Plc, Oxford, UK
| | - Pedro Beltrao
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
- Open Targets, Wellcome Genome Campus, Cambridge, UK
| | - Andrew Bassett
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
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75
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Genome-wide association analysis of cognitive function in Danish long-lived individuals. Mech Ageing Dev 2021; 195:111463. [PMID: 33607172 DOI: 10.1016/j.mad.2021.111463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 01/21/2021] [Accepted: 02/10/2021] [Indexed: 11/23/2022]
Abstract
Cognitive function is a substantially heritable trait related to numerous important life outcomes. Several genome-wide association studies of cognitive function have in recent years led to the identification of thousands of significantly associated loci and genes. Individuals included in these studies have rarely been nonagenarians and centenarians, and since cognitive function is an important component of quality of life for this rapidly expanding demographic group, there is a need to explore genetic factors associated with individual differences in cognitive function at advanced ages. In this study, we pursued this by performing a genome-wide association study of cognitive function in 490 long-lived Danes (age range 90.1-100.8 years). While no genome-wide significant SNPs were identified, suggestively significant SNPs (P < 1 × 10-5) were mapped to several interesting genes, including ZWINT, CELF2, and DNAH5, and the glutamate receptor genes GRID2 and GRM7. Additionally, results from a gene set over-representation analysis indicated potential roles of gene sets related to G protein-coupled receptor (GPCR) signaling, interaction between L1 and ankyrins, mitogen-activated protein kinase (MAPK) signaling, RNA degradation, and cell cycle. Larger studies are needed to shed further light on the possible importance of these suggestive genes and pathways in cognitive function in nonagenarians and centenarians.
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76
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Blue EE, Thornton TA, Kooperberg C, Liu S, Wactawski-Wende J, Manson J, Kuller L, Hayden K, Reiner AP. Non-coding variants in MYH11, FZD3, and SORCS3 are associated with dementia in women. Alzheimers Dement 2021; 17:215-225. [PMID: 32966694 PMCID: PMC7920533 DOI: 10.1002/alz.12181] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 07/17/2020] [Accepted: 08/03/2020] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Recent studies suggest that both sex-specific genetic risk factors and those shared between dementia and stroke are involved in dementia pathogenesis. METHODS We performed both single-variant and gene-based genome-wide association studies of >11,000 whole genome sequences from the Women's Health Initiative cohort to discover loci associated with dementia, with adjustment for age, ethnicity, stroke, and venous thromboembolism status. Evidence for prior evidence of association and differential gene expression in dementia-related tissues and samples was gathered for each locus. RESULTS Our multiethnic studies identified significant associations between variants within APOE, MYH11, FZD3, SORCS3, and GOLGA8B and risk of dementia. Ten genes implicated by these loci, including MYH11, FZD3, SORCS3, and GOLGA8B, were differentially expressed in the context of Alzheimer's disease. DISCUSSION Our association of MYH11, FZD3, SORCS3, and GOLGA8B with dementia is supported by independent functional studies in human subjects, model systems, and associations with shared risk factors for stroke and dementia.
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Affiliation(s)
- Elizabeth E. Blue
- Division of Medical Genetics, University of Washington, Seattle, Washington, USA
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Charles Kooperberg
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Simin Liu
- Department of Epidemiology, Brown University, Providence, Rhode Island, USA
- Department of Surgery, Brown University, Providence, Rhode Island, USA
- Department of Medicine, Brown University, Providence, Rhode Island, USA
| | - Jean Wactawski-Wende
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, New York, USA
| | - JoAnn Manson
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Lew Kuller
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Kathleen Hayden
- Department of Social Science and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Alexander P. Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
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77
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de Rochemonteix M, Napolioni V, Sanyal N, Belloy ME, Caporaso NE, Landi MT, Greicius MD, Chatterjee N, Han SS. A Likelihood Ratio Test for Gene-Environment Interaction Based on the Trend Effect of Genotype Under an Additive Risk Model Using the Gene-Environment Independence Assumption. Am J Epidemiol 2021; 190:129-141. [PMID: 32870973 DOI: 10.1093/aje/kwaa132] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 06/30/2020] [Accepted: 06/30/2020] [Indexed: 12/22/2022] Open
Abstract
Several statistical methods have been proposed for testing gene-environment (G-E) interactions under additive risk models using data from genome-wide association studies. However, these approaches have strong assumptions from underlying genetic models, such as dominant or recessive effects that are known to be less robust when the true genetic model is unknown. We aimed to develop a robust trend test employing a likelihood ratio test for detecting G-E interaction under an additive risk model, while incorporating the G-E independence assumption to increase power. We used a constrained likelihood to impose 2 sets of constraints for: 1) the linear trend effect of genotype and 2) the additive joint effects of gene and environment. To incorporate the G-E independence assumption, a retrospective likelihood was used versus a standard prospective likelihood. Numerical investigation suggests that the proposed tests are more powerful than tests assuming dominant, recessive, or general models under various parameter settings and under both likelihoods. Incorporation of the independence assumption enhances efficiency by 2.5-fold. We applied the proposed methods to examine the gene-smoking interaction for lung cancer and gene-apolipoprotein E $\varepsilon$4 interaction for Alzheimer disease, which identified 2 interactions between apolipoprotein E $\varepsilon$4 and loci membrane-spanning 4-domains subfamily A (MS4A) and bridging integrator 1 (BIN1) genes at genome-wide significance that were replicated using independent data.
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78
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Ruffini N, Klingenberg S, Schweiger S, Gerber S. Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale. Cells 2020; 9:E2642. [PMID: 33302607 PMCID: PMC7764447 DOI: 10.3390/cells9122642] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 11/24/2020] [Accepted: 12/04/2020] [Indexed: 02/06/2023] Open
Abstract
Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.
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Affiliation(s)
- Nicolas Ruffini
- Institute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, Germany; (N.R.); (S.K.); (S.S.)
- Leibniz Institute for Resilience Research, Leibniz Association, Wallstraße 7, 55122 Mainz, Germany
| | - Susanne Klingenberg
- Institute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, Germany; (N.R.); (S.K.); (S.S.)
| | - Susann Schweiger
- Institute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, Germany; (N.R.); (S.K.); (S.S.)
| | - Susanne Gerber
- Institute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, Germany; (N.R.); (S.K.); (S.S.)
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79
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Sargurupremraj M, Suzuki H, Jian X, Sarnowski C, Evans TE, Bis JC, Eiriksdottir G, Sakaue S, Terzikhan N, Habes M, Zhao W, Armstrong NJ, Hofer E, Yanek LR, Hagenaars SP, Kumar RB, van den Akker EB, McWhirter RE, Trompet S, Mishra A, Saba Y, Satizabal CL, Beaudet G, Petit L, Tsuchida A, Zago L, Schilling S, Sigurdsson S, Gottesman RF, Lewis CE, Aggarwal NT, Lopez OL, Smith JA, Valdés Hernández MC, van der Grond J, Wright MJ, Knol MJ, Dörr M, Thomson RJ, Bordes C, Le Grand Q, Duperron MG, Smith AV, Knopman DS, Schreiner PJ, Evans DA, Rotter JI, Beiser AS, Maniega SM, Beekman M, Trollor J, Stott DJ, Vernooij MW, Wittfeld K, Niessen WJ, Soumaré A, Boerwinkle E, Sidney S, Turner ST, Davies G, Thalamuthu A, Völker U, van Buchem MA, Bryan RN, Dupuis J, Bastin ME, Ames D, Teumer A, Amouyel P, Kwok JB, Bülow R, Deary IJ, Schofield PR, Brodaty H, Jiang J, Tabara Y, Setoh K, Miyamoto S, Yoshida K, Nagata M, Kamatani Y, Matsuda F, Psaty BM, Bennett DA, De Jager PL, Mosley TH, Sachdev PS, Schmidt R, Warren HR, Evangelou E, Trégouët DA, Ikram MA, Wen W, DeCarli C, Srikanth VK, Jukema JW, Slagboom EP, Kardia SLR, Okada Y, Mazoyer B, Wardlaw JM, Nyquist PA, Mather KA, Grabe HJ, Schmidt H, Van Duijn CM, Gudnason V, Longstreth WT, Launer LJ, Lathrop M, Seshadri S, Tzourio C, Adams HH, Matthews PM, Fornage M, Debette S. Cerebral small vessel disease genomics and its implications across the lifespan. Nat Commun 2020; 11:6285. [PMID: 33293549 PMCID: PMC7722866 DOI: 10.1038/s41467-020-19111-2] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 09/10/2020] [Indexed: 12/14/2022] Open
Abstract
White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
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Affiliation(s)
- Muralidharan Sargurupremraj
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Hideaki Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo, Aoba, Sendai, 980-8573, Japan
- Department of Cardiovascular Medicine, Tohoku University Hospital, 1-1, Seiryo, Aoba, Sendai, 980-8574, Japan
- Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
| | - Xueqiu Jian
- University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, 77030, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Tavia E Evans
- Department of Clinical Genetics, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
| | | | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
- Department of Allergy and Rheumatology, Graduate School of Medicine, the University of Tokyo, Tokyo, 113-0033, Japan
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Nicola J Armstrong
- Mathematics and Statistics, Murdoch University, Murdoch, WA, 6150, Australia
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, 8036, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
| | - Lisa R Yanek
- GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Saskia P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Social Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Rajan B Kumar
- Department of Public Health Sciences, University of California at Davis, Davis, CA, 95616, USA
| | - Erik B van den Akker
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
- Pattern Recognition & Bioinformatics, Delft University of Technology, Delft, NL, 2629 HS, USA
- Leiden Computational Biology Centre, Leiden University Medical Centre, 2333 ZA, Leiden, The Netherlands
| | - Rebekah E McWhirter
- Centre for Law and Genetics, Faculty of Law, University of Tasmania, Hobart, TAS, 7005, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - Stella Trompet
- Department of Internal Medicine, section of gerontology and geriatrics, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Aniket Mishra
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Yasaman Saba
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
- Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry, Medical University of Graz, 8010, Graz, Austria
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Gregory Beaudet
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Laurent Petit
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Ami Tsuchida
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Laure Zago
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Sabrina Schilling
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | | | | | - Cora E Lewis
- University of Alabama at Birmingham School of Medicine, Birmingham, AL, 35233, USA
| | - Neelum T Aggarwal
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Oscar L Lopez
- Departments of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Maria C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Jeroen van der Grond
- Department of Radiology, Leiden University medical Center, 2333 ZA, Leiden, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia
- Centre for Advanced Imaging, The University of Queensland, St Lucia, QLD, 4072, Australia
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, 17475, Greifswald, Germany
| | - Russell J Thomson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Centre for Research in Mathematics and Data Science, Western Sydney University, Penrith, NSW, 2751, Australia
| | - Constance Bordes
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Quentin Le Grand
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Marie-Gabrielle Duperron
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | | | | | - Pamela J Schreiner
- University of Minnesota School of Public Health, Minneapolis, MN, 55455, USA
| | - Denis A Evans
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Alexa S Beiser
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Marian Beekman
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Julian Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Meike W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, 17489, Greifswald, Germany
| | - Wiro J Niessen
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Faculty of Applied Sciences, Delft University of Technology, Delft, NL, 2629 HS, USA
| | - Aicha Soumaré
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Eric Boerwinkle
- University of Texas Health Science Center at Houston School of Public Health, Houston, TX, 77030, USA
| | - Stephen Sidney
- Kaiser Permanente Division of Research, Oakland, CA, 94612, USA
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, 55905, USA
| | - Gail Davies
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Anbupalam Thalamuthu
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Mark A van Buchem
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - R Nick Bryan
- The University of Texas at Austin Dell Medical School, Austin, TX, 78712, USA
| | - Josée Dupuis
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Mark E Bastin
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - David Ames
- National Ageing Research Institute Royal Melbourne Hospital, Parkville, VIC, 3052, Australia
- Academic Unit for Psychiatry of Old Age, University of Melbourne, St George's Hospital, Kew, VIC, 3101, Australia
| | - Alexander Teumer
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Internal Medicine B, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Philippe Amouyel
- Inserm U1167, 59000, Lille, France
- Department of Epidemiology and Public Health, Pasteur Institute of Lille, 59000, Lille, France
| | - John B Kwok
- Brain and Mind Centre - The University of Sydney, Camperdown, NSW, 2050, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Robin Bülow
- Department of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17489, Greifswald, Germany
| | - Ian J Deary
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Peter R Schofield
- School of Medical Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
| | - Henry Brodaty
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Dementia Centre for Research Collaboration, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Jiyang Jiang
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Kazuya Setoh
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Manabu Nagata
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Bruce M Psaty
- Departments of Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, 98195, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, 10032, USA
- Program in Population and Medical Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Thomas H Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - Perminder S Sachdev
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, 2031, Australia
| | - Reinhold Schmidt
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Helen R Warren
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 4NS, UK
- National Institute for Health Research Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, SW7 2AZ, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Mpizani, 455 00, Greece
| | - David-Alexandre Trégouët
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Mohammad A Ikram
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA, 95817, USA
| | - Velandai K Srikanth
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Peninsula Clinical School, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Eline P Slagboom
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, 565-0871, Osaka, Japan
| | - Bernard Mazoyer
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- MRC UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH8 9YL, UK
| | - Paul A Nyquist
- Department of Neurology, Johns Hopkins School of Medicine, Baltimone, MD, 21205, USA
- General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, 17475, Greifswald, Germany
| | - Helena Schmidt
- Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry, Medical University of Graz, 8010, Graz, Austria
| | - Cornelia M Van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Vilmundur Gudnason
- Icelandic Heart Association, IS-201, Kópavogur, Iceland
- University of Iceland, Faculty of Medicine, 101, Reykjavík, Iceland
| | - William T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, 98104-2420, USA
| | - Lenore J Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute of Aging, The National Institutes of Health, Bethesda, MD, 20892, USA
- Intramural Research Program/National Institute on Aging/National Institutes of Health, Bethesda, MD, 20892, USA
| | - Mark Lathrop
- University of McGill Genome Center, Montreal, QC, H3A 0G1, Canada
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Christophe Tzourio
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
- CHU de Bordeaux, Pole de santé publique, Service d'information médicale, 33000, Bordeaux, France
| | - Hieab H Adams
- Department of Clinical Genetics, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
- UK Dementia Research Institute, London, WC1E 6BT, UK
- Data Science Institute, Imperial College London, London, SW7 2AZ, UK
| | - Myriam Fornage
- University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, 77030, USA.
| | - Stéphanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France.
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA.
- Department of Neurology, CHU de Bordeaux, 33000, Bordeaux, France.
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80
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Mo SJ, Zhao HC, Tian YZ, Zhao HL. The Role of Prefoldin and Its Subunits in Tumors and Their Application Prospects in Nanomedicine. Cancer Manag Res 2020; 12:8847-8856. [PMID: 33061580 PMCID: PMC7520118 DOI: 10.2147/cmar.s270237] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 08/24/2020] [Indexed: 12/15/2022] Open
Abstract
Prefoldin (PFDN) is a hexameric chaperone complex that is widely found in eukaryotes and archaea and consists of six different subunits (PFDN1-6). Its main function is to transfer actin and tubulin monomers to the eukaryotic cell cytoplasmic chaperone protein (c-CPN) specific binding during the assembly of the cytoskeleton, to stabilize the newly synthesized peptides so that they can be folded correctly. The current study found that each subunit of PFDN has different functions, which are closely related to the occurrence, development and prognosis of tumors. However, the best characteristics of each subunit have not been fully affirmed. The connection between research and tumors can change the understanding of PFDN and further extend its potential prognostic role and structural function to cancer research and clinical practice. This article mainly reviews the role of canonical PFDN and its subunits in tumors and other diseases, and discusses the potential prospects of the unique structure and function of PFDN in nanomedicine.
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Affiliation(s)
- Shao-Jian Mo
- Department of General Surgery, The Affiliated Bethune Hospital of Shanxi Medical University, Taiyuan 030032, People's Republic of China
| | - Hai-Chao Zhao
- Department of General Surgery, The Affiliated Bethune Hospital of Shanxi Medical University, Taiyuan 030032, People's Republic of China
| | - Yan-Zhang Tian
- Department of General Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan 030032, People's Republic of China
| | - Hao-Liang Zhao
- Department of General Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan 030032, People's Republic of China
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81
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Comprehensive Analysis of RNA-Seq Gene Expression Profiling of Brain Transcriptomes Reveals Novel Genes, Regulators, and Pathways in Autism Spectrum Disorder. Brain Sci 2020; 10:brainsci10100747. [PMID: 33080834 PMCID: PMC7603078 DOI: 10.3390/brainsci10100747] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 10/09/2020] [Accepted: 10/14/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a neurodevelopmental disorder with deficits in social communication ability and repetitive behavior. The pathophysiological events involved in the brain of this complex disease are still unclear. METHODS In this study, we aimed to profile the gene expression signatures of brain cortex of ASD patients, by using two publicly available RNA-seq studies, in order to discover new ASD-related genes. RESULTS We detected 1567 differentially expressed genes (DEGs) by meta-analysis, where 1194 were upregulated and 373 were downregulated genes. Several ASD-related genes previously reported were also identified. Our meta-analysis identified 235 new DEGs that were not detected using the individual RNA-seq studies used. Some of those genes, including seven DEGs (PAK1, DNAH17, DOCK8, DAPP1, PCDHAC2, and ERBIN, SLC7A7), have been confirmed in previous reports to be associated with ASD. Gene Ontology (GO) and pathways analysis showed several molecular pathways enriched by the DEGs, namely, osteoclast differentiation, TNF signaling pathway, complement and coagulation cascade. Topological analysis of protein-protein interaction of the ASD brain cortex revealed proteomics hub gene signatures: MYC, TP53, HDAC1, CDK2, BAG3, CDKN1A, GABARAPL1, EZH2, VIM, and TRAF1. We also identified the transcriptional factors (TFs) regulating DEGs, namely, FOXC1, GATA2, YY1, FOXL1, USF2, NFIC, NFKB1, E2F1, TFAP2A, HINFP. CONCLUSION Novel core genes and molecular signatures involved with ASD were identified by our meta-analysis.
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82
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Neuner SM, Tcw J, Goate AM. Genetic architecture of Alzheimer's disease. Neurobiol Dis 2020; 143:104976. [PMID: 32565066 PMCID: PMC7409822 DOI: 10.1016/j.nbd.2020.104976] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 05/30/2020] [Accepted: 06/13/2020] [Indexed: 02/06/2023] Open
Abstract
Advances in genetic and genomic technologies over the last thirty years have greatly enhanced our knowledge concerning the genetic architecture of Alzheimer's disease (AD). Several genes including APP, PSEN1, PSEN2, and APOE have been shown to exhibit large effects on disease susceptibility, with the remaining risk loci having much smaller effects on AD risk. Notably, common genetic variants impacting AD are not randomly distributed across the genome. Instead, these variants are enriched within regulatory elements active in human myeloid cells, and to a lesser extent liver cells, implicating these cell and tissue types as critical to disease etiology. Integrative approaches are emerging as highly effective for identifying the specific target genes through which AD risk variants act and will likely yield important insights related to potential therapeutic targets in the coming years. In the future, additional consideration of sex- and ethnicity-specific contributions to risk as well as the contribution of complex gene-gene and gene-environment interactions will likely be necessary to further improve our understanding of AD genetic architecture.
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Affiliation(s)
- Sarah M Neuner
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Julia Tcw
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Alison M Goate
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA.
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83
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Abdolmohammadi B, Dupre A, Evers L, Mez J. Genetics of Chronic Traumatic Encephalopathy. Semin Neurol 2020; 40:420-429. [DOI: 10.1055/s-0040-1713631] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
AbstractAlthough chronic traumatic encephalopathy (CTE) garners substantial attention in the media and there have been marked scientific advances in the last few years, much remains unclear about the role of genetic risk in CTE. Two athletes with comparable contact-sport exposure may have varying amounts of CTE neuropathology, suggesting that other factors, including genetics, may contribute to CTE risk and severity. In this review, we explore reasons why genetics may be important for CTE, concepts in genetic study design for CTE (including choosing controls, endophenotypes, gene by environment interaction, and epigenetics), implicated genes in CTE (including APOE, MAPT, and TMEM106B), and whether predictive genetic testing for CTE should be considered.
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Affiliation(s)
- Bobak Abdolmohammadi
- Boston University Alzheimer’s Disease Center, Boston University School of Medicine, Boston, MA
- Boston University Chronic Traumatic Encephalopathy Center, Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
| | - Alicia Dupre
- Boston University Alzheimer’s Disease Center, Boston University School of Medicine, Boston, MA
- Boston University Chronic Traumatic Encephalopathy Center, Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
| | - Laney Evers
- Boston University Alzheimer’s Disease Center, Boston University School of Medicine, Boston, MA
- Boston University Chronic Traumatic Encephalopathy Center, Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
| | - Jesse Mez
- Boston University Alzheimer’s Disease Center, Boston University School of Medicine, Boston, MA
- Boston University Chronic Traumatic Encephalopathy Center, Boston University School of Medicine, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA
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84
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Griswold AJ, Sivasankaran SK, Van Booven D, Gardner OK, Rajabli F, Whitehead PL, Hamilton-Nelson KL, Adams LD, Scott AM, Hofmann NK, Vance JM, Cuccaro ML, Bush WS, Martin ER, Byrd GS, Haines JL, Pericak-Vance MA, Beecham GW. Immune and Inflammatory Pathways Implicated by Whole Blood Transcriptomic Analysis in a Diverse Ancestry Alzheimer's Disease Cohort. J Alzheimers Dis 2020; 76:1047-1060. [PMID: 32597797 DOI: 10.3233/jad-190855] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Significant work has identified genetic variants conferring risk and protection for Alzheimer's disease (AD), but functional effects of these variants is lacking, particularly in under-represented ancestral populations. Expression studies performed in easily accessible tissue, such as whole blood, can recapitulate some transcriptional changes occurring in brain and help to identify mechanisms underlying neurodegenerative processes. OBJECTIVE We aimed to identify transcriptional differences between AD cases and controls in a cohort of diverse ancestry. METHODS We analyzed the protein coding transcriptome using RNA sequencing from peripheral blood collected from 234 African American (AA) (115 AD, 119 controls) and 240 non-Hispanic Whites (NHW) (121 AD, 119 controls). To identify case-control differentially expressed genes and pathways, we performed stratified, joint, and interaction analyses using linear regression models within and across ancestral groups followed by pathway and gene set enrichment analyses. RESULTS Overall, we identified 418 (291 upregulated, 127 downregulated) and 488 genes (352 upregulated, 136 downregulated) differentially expressed in the AA and NHW datasets, respectively, with only 16 genes commonly differentially expressed in both ancestral groups. Joint analyses provided greater power to detect case-control differences and identified 1,102 differentially expressed genes between cases and controls (812 upregulated, 290 downregulated). Interaction analysis identified only 27 genes with different effects in AA compared to NHW. Pathway and gene-set enrichment analyses revealed differences in immune response-related pathways that were enriched across the analyses despite different underlying gene sets. CONCLUSION These results support the hypothesis of converging underlying pathophysiological processes in AD across ancestral groups.
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Affiliation(s)
- Anthony J Griswold
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA.,Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | | | - Derek Van Booven
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Olivia K Gardner
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Patrice L Whitehead
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | | | - Larry D Adams
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Aja M Scott
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Natalia K Hofmann
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Jeffery M Vance
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA.,Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA.,Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - William S Bush
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.,Cleveland Institute for Computational Biology, Cleveland, OH, USA
| | - Eden R Martin
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA.,Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - Goldie S Byrd
- Department of Public Health Sciences, Wake Forest University, Winston-Salem, NC, USA
| | - Jonathan L Haines
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.,Cleveland Institute for Computational Biology, Cleveland, OH, USA
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA.,Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA.,Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
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85
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Chung J, Marini S, Pera J, Norrving B, Jimenez-Conde J, Roquer J, Fernandez-Cadenas I, Tirschwell DL, Selim M, Brown DL, Silliman SL, Worrall BB, Meschia JF, Demel S, Greenberg SM, Slowik A, Lindgren A, Schmidt R, Traylor M, Sargurupremraj M, Tiedt S, Malik R, Debette S, Dichgans M, Langefeld CD, Woo D, Rosand J, Anderson CD. Genome-wide association study of cerebral small vessel disease reveals established and novel loci. Brain 2020; 142:3176-3189. [PMID: 31430377 DOI: 10.1093/brain/awz233] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 05/30/2019] [Accepted: 06/04/2019] [Indexed: 01/08/2023] Open
Abstract
Intracerebral haemorrhage and small vessel ischaemic stroke (SVS) are the most acute manifestations of cerebral small vessel disease, with no established preventive approaches beyond hypertension management. Combined genome-wide association study (GWAS) of these two correlated diseases may improve statistical power to detect novel genetic factors for cerebral small vessel disease, elucidating underlying disease mechanisms that may form the basis for future treatments. Because intracerebral haemorrhage location is an adequate surrogate for distinct histopathological variants of cerebral small vessel disease (lobar for cerebral amyloid angiopathy and non-lobar for arteriolosclerosis), we performed GWAS of intracerebral haemorrhage by location in 1813 subjects (755 lobar and 1005 non-lobar) and 1711 stroke-free control subjects. Intracerebral haemorrhage GWAS results by location were meta-analysed with GWAS results for SVS from MEGASTROKE, using 'Multi-Trait Analysis of GWAS' (MTAG) to integrate summary data across traits and generate combined effect estimates. After combining intracerebral haemorrhage and SVS datasets, our sample size included 241 024 participants (6255 intracerebral haemorrhage or SVS cases and 233 058 control subjects). Genome-wide significant associations were observed for non-lobar intracerebral haemorrhage enhanced by SVS with rs2758605 [MTAG P-value (P) = 2.6 × 10-8] at 1q22; rs72932727 (P = 1.7 × 10-8) at 2q33; and rs9515201 (P = 5.3 × 10-10) at 13q34. In the GTEx gene expression library, rs2758605 (1q22), rs72932727 (2q33) and rs9515201 (13q34) are significant cis-eQTLs for PMF1 (P = 1 × 10-4 in tibial nerve), NBEAL1, FAM117B and CARF (P < 2.1 × 10-7 in arteries) and COL4A2 and COL4A1 (P < 0.01 in brain putamen), respectively. Leveraging S-PrediXcan for gene-based association testing with the predicted expression models in tissues related with nerve, artery, and non-lobar brain, we found that experiment-wide significant (P < 8.5 × 10-7) associations at three genes at 2q33 including NBEAL1, FAM117B and WDR12 and genome-wide significant associations at two genes including ICA1L at 2q33 and ZCCHC14 at 16q24. Brain cell-type specific expression profiling libraries reveal that SEMA4A, SLC25A44 and PMF1 at 1q22 and COL4A1 and COL4A2 at 13q34 were mainly expressed in endothelial cells, while the genes at 2q33 (FAM117B, CARF and NBEAL1) were expressed in various cell types including astrocytes, oligodendrocytes and neurons. Our cross-phenotype genetic study of intracerebral haemorrhage and SVS demonstrates novel genome-wide associations for non-lobar intracerebral haemorrhage at 2q33 and 13q34. Our replication of the 1q22 locus previous seen in traditional GWAS of intracerebral haemorrhage, as well as the rediscovery of 13q34, which had previously been reported in candidate gene studies with other cerebral small vessel disease-related traits strengthens the credibility of applying this novel genome-wide approach across intracerebral haemorrhage and SVS.
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Affiliation(s)
- Jaeyoon Chung
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Sandro Marini
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Joanna Pera
- Department of Neurology, Jagiellonian University Medical College, Krakow, Poland
| | - Bo Norrving
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden.,Department of Neurology and Rehabilitation Medicine, Skåne University Hospital, Lund, Sweden
| | - Jordi Jimenez-Conde
- Department of Neurology, Neurovascular Research Unit, Institut Hospital del Mar d'Investigacions Mèdiques, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Jaume Roquer
- Department of Neurology, Neurovascular Research Unit, Institut Hospital del Mar d'Investigacions Mèdiques, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Israel Fernandez-Cadenas
- Neurovascular Research Laboratory and Neurovascular Unit, Institut de Recerca, Hospital Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona, Spain.,Stroke Pharmacogenomics and Genetics, Sant Pau Institute of Research, Hospital de la Santa Creu I Sant Pau, Barcelona, Spain
| | - David L Tirschwell
- Stroke Center, Harborview Medical Center, University of Washington, Seattle, WA, USA
| | - Magdy Selim
- Department of Neurology, Stroke Division, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Devin L Brown
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Scott L Silliman
- Department of Neurology, University of Florida College of Medicine, Jacksonville, FL, USA
| | - Bradford B Worrall
- Department of Neurology and Public Health Sciences, University of Virginia Health System, Charlottesville, VA, USA
| | | | - Stacie Demel
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Steven M Greenberg
- The J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Agnieszka Slowik
- Department of Neurology, Jagiellonian University Medical College, Krakow, Poland
| | - Arne Lindgren
- Department of Clinical Sciences Lund, Neurology, Lund University, Lund, Sweden.,Department of Neurology and Rehabilitation Medicine, Skåne University Hospital, Lund, Sweden
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Matthew Traylor
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - Steffen Tiedt
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Rainer Malik
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Stéphanie Debette
- University of Bordeaux, INSERM U1219, Bordeaux Population Health Research Center, Bordeaux, France.,Department of Neurology, Memory Clinic, Bordeaux University Hospital, University of Bordeaux, Bordeaux, France
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
| | - Carl D Langefeld
- Center for Public Health Genomics and Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Daniel Woo
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.,Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Christopher D Anderson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.,Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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86
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McGuirl MR, Smith SP, Sandstede B, Ramachandran S. Detecting Shared Genetic Architecture Among Multiple Phenotypes by Hierarchical Clustering of Gene-Level Association Statistics. Genetics 2020; 215:511-529. [PMID: 32245788 PMCID: PMC7268989 DOI: 10.1534/genetics.120.303096] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 03/31/2020] [Indexed: 12/31/2022] Open
Abstract
Emerging large-scale biobanks pairing genotype data with phenotype data present new opportunities to prioritize shared genetic associations across multiple phenotypes for molecular validation. Past research, by our group and others, has shown gene-level tests of association produce biologically interpretable characterization of the genetic architecture of a given phenotype. Here, we present a new method, Ward clustering to identify Internal Node branch length outliers using Gene Scores (WINGS), for identifying shared genetic architecture among multiple phenotypes. The objective of WINGS is to identify groups of phenotypes, or "clusters," sharing a core set of genes enriched for mutations in cases. We validate WINGS using extensive simulation studies and then combine gene-level association tests with WINGS to identify shared genetic architecture among 81 case-control and seven quantitative phenotypes in 349,468 European-ancestry individuals from the UK Biobank. We identify eight prioritized phenotype clusters and recover multiple published gene-level associations within prioritized clusters.
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Affiliation(s)
- Melissa R McGuirl
- Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912
| | - Samuel Pattillo Smith
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island 02912
- Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island 02912
| | - Björn Sandstede
- Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912
- Data Science Initiative, Brown University, Providence, Rhode Island 02912
| | - Sohini Ramachandran
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island 02912
- Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island 02912
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87
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Hypermethylation of the TSPOAP1-AS1 Promoter May Be Associated with Obesity in Overweight/Obese Korean Subjects. Int J Mol Sci 2020; 21:ijms21093307. [PMID: 32392798 PMCID: PMC7246878 DOI: 10.3390/ijms21093307] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 05/04/2020] [Accepted: 05/05/2020] [Indexed: 01/18/2023] Open
Abstract
Obesity is a major chronic disease associated with the risk of serious cardiovascular or endocrinal diseases, such as hypertension, diabetes, atherosclerosis and stroke. Considerable interest has been directed towards the potential effects of epigenetic variations in obesity. In this study, we evaluated DNA methylation level at the promoter region of the gene encoding TSPO-associated protein 1 antisense RNA 1 (TSPOAP1-AS1) in 80 overweight/obese subjects (body mass index (BMI) > 25) and 104 non-obese subjects who participated in the SOPI-Stroke study in Korea. DNA methylation was measured using bisulfite amplicon sequencing (BSAS). A general linear model or relative correlation was used to determine the effects of DNA methylation on obesity and obese phenotypes. Notably, the mean level of DNA methylation was significantly higher in the overweight/obese group than in the non-obese group (18.62% vs. 17.18%). Further analyses revealed significant positive correlations of the BMI, the serum total cholesterol and low-density lipoprotein cholesterol levels with the DNA methylation level (p = 0.0493, p = 0.003, and p = 0.0094, respectively). The study findings suggest an association between DNA methylation at the TSPOAP1-AS1 promoter and overweight/obesity. Accordingly, methylation in this promoter region might be a potential predictor of obesity.
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88
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Andrews SJ, Fulton-Howard B, Goate A. Interpretation of risk loci from genome-wide association studies of Alzheimer's disease. Lancet Neurol 2020; 19:326-335. [PMID: 31986256 PMCID: PMC8176461 DOI: 10.1016/s1474-4422(19)30435-1] [Citation(s) in RCA: 194] [Impact Index Per Article: 48.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 10/18/2019] [Accepted: 10/23/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Alzheimer's disease is a debilitating and highly heritable neurological condition. As such, genetic studies have sought to understand the genetic architecture of Alzheimer's disease since the 1990s, with successively larger genome-wide association studies (GWAS) and meta-analyses. These studies started with a small sample size of 1086 individuals in 2007, which was able to identify only the APOE locus. In 2013, the International Genomics of Alzheimer's Project (IGAP) did a meta-analysis of all existing GWAS using data from 74 046 individuals, which stood as the largest Alzheimer's disease GWAS until 2018. This meta-analysis discovered 19 susceptibility loci for Alzheimer's disease in populations of European ancestry. RECENT DEVELOPMENTS Three new Alzheimer's disease GWAS published in 2018 and 2019, which used larger sample sizes and proxy phenotypes from biobanks, have substantially increased the number of known susceptibility loci in Alzheimer's disease to 40. The first, an updated GWAS from IGAP, included 94 437 individuals and discovered 24 susceptibility loci. Although IGAP sought to increase sample size by recruiting additional clinical cases and controls, the two other studies used parental family history of Alzheimer's disease to define proxy cases and controls in the UK Biobank for a genome-wide association by proxy, which was meta-analysed with data from GWAS of clinical Alzheimer's disease to attain sample sizes of 388 324 and 534 403 individuals. These two studies identified 27 and 29 susceptibility loci, respectively. However, the three studies were not independent because of the large overlap in their participants, and interpretation can be challenging because different variants and genes were highlighted by each study, even in the same locus. Furthermore, neither the variant with the strongest Alzheimer's disease association nor the nearest gene are necessarily causal. This situation presents difficulties for experimental studies, drug development, and other future research. WHERE NEXT?: The ultimate goal of understanding the genetic architecture of Alzheimer's disease is to characterise novel biological pathways that underly Alzheimer's disease pathogenesis and to identify novel drug targets. GWAS have successfully contributed to the characterisation of the genetic architecture of Alzheimer's disease, with the identification of 40 susceptibility loci; however, this does not equate to the discovery of 40 Alzheimer's disease genes. To identify Alzheimer's disease genes, these loci need to be mapped to variants and genes through functional genomics studies that combine annotation of variants, gene expression, and gene-based or pathway-based analyses. Such studies are ongoing and have validated several genes at Alzheimer's disease loci, but greater sample sizes and cell-type specific data are needed to map all GWAS loci.
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Affiliation(s)
- Shea J Andrews
- Ronald M Loeb Center for Alzheimer's disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian Fulton-Howard
- Ronald M Loeb Center for Alzheimer's disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison Goate
- Ronald M Loeb Center for Alzheimer's disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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89
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Bellenguez C, Grenier-Boley B, Lambert JC. Genetics of Alzheimer’s disease: where we are, and where we are going. Curr Opin Neurobiol 2020; 61:40-48. [DOI: 10.1016/j.conb.2019.11.024] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 11/27/2019] [Accepted: 11/27/2019] [Indexed: 12/31/2022]
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90
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Prokopenko D, Hecker J, Kirchner R, Chapman BA, Hoffman O, Mullin K, Hide W, Bertram L, Laird N, DeMeo DL, Lange C, Tanzi RE. Identification of Novel Alzheimer's Disease Loci Using Sex-Specific Family-Based Association Analysis of Whole-Genome Sequence Data. Sci Rep 2020; 10:5029. [PMID: 32193444 PMCID: PMC7081222 DOI: 10.1038/s41598-020-61883-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 02/17/2020] [Indexed: 11/21/2022] Open
Abstract
With the advent of whole genome-sequencing (WGS) studies, family-based designs enable sex-specific analysis approaches that can be applied to only affected individuals; tests using family-based designs are attractive because they are completely robust against the effects of population substructure. These advantages make family-based association tests (FBATs) that use siblings as well as parents especially suited for the analysis of late-onset diseases such as Alzheimer's Disease (AD). However, the application of FBATs to assess sex-specific effects can require additional filtering steps, as sensitivity to sequencing errors is amplified in this type of analysis. Here, we illustrate the implementation of robust analysis approaches and additional filtering steps that can minimize the chances of false positive-findings due to sex-specific sequencing errors. We apply this approach to two family-based AD datasets and identify four novel loci (GRID1, RIOK3, MCPH1, ZBTB7C) showing sex-specific association with AD risk. Following stringent quality control filtering, the strongest candidate is ZBTB7C (Pinter = 1.83 × 10-7), in which the minor allele of rs1944572 confers increased risk for AD in females and protection in males. ZBTB7C encodes the Zinc Finger and BTB Domain Containing 7C, a transcriptional repressor of membrane metalloproteases (MMP). Members of this MMP family were implicated in AD neuropathology.
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Affiliation(s)
- Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Julian Hecker
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Rory Kirchner
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brad A Chapman
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Oliver Hoffman
- Department of Clinical Pathology, University of Melbourne, Victoria, 3000, Melbourne, Australia
| | - Kristina Mullin
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Winston Hide
- Harvard Medical School, Boston, MA, USA
- Department of Neuroscience, Sheffield Institute for Translational Neurosciences, University of Sheffield, Sheffield, UK
- Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, US
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Nan Laird
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Dawn L DeMeo
- Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Christoph Lange
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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91
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Rao CV, Asch AS, Carr DJJ, Yamada HY. "Amyloid-beta accumulation cycle" as a prevention and/or therapy target for Alzheimer's disease. Aging Cell 2020; 19:e13109. [PMID: 31981470 PMCID: PMC7059149 DOI: 10.1111/acel.13109] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 12/16/2019] [Accepted: 12/25/2019] [Indexed: 02/06/2023] Open
Abstract
The cell cycle and its regulators are validated targets for cancer drugs. Reagents that target cells in a specific cell cycle phase (e.g., antimitotics or DNA synthesis inhibitors/replication stress inducers) have demonstrated success as broad-spectrum anticancer drugs. Cyclin-dependent kinases (CDKs) are drivers of cell cycle transitions. A CDK inhibitor, flavopiridol/alvocidib, is an FDA-approved drug for acute myeloid leukemia. Alzheimer's disease (AD) is another serious issue in contemporary medicine. The cause of AD remains elusive, although a critical role of latent amyloid-beta accumulation has emerged. Existing AD drug research and development targets include amyloid, amyloid metabolism/catabolism, tau, inflammation, cholesterol, the cholinergic system, and other neurotransmitters. However, none have been validated as therapeutically effective targets. Recent reports from AD-omics and preclinical animal models provided data supporting the long-standing notion that cell cycle progression and/or mitosis may be a valid target for AD prevention and/or therapy. This review will summarize the recent developments in AD research: (a) Mitotic re-entry, leading to the "amyloid-beta accumulation cycle," may be a prerequisite for amyloid-beta accumulation and AD pathology development; (b) AD-associated pathogens can cause cell cycle errors; (c) thirteen among 37 human AD genetic risk genes may be functionally involved in the cell cycle and/or mitosis; and (d) preclinical AD mouse models treated with CDK inhibitor showed improvements in cognitive/behavioral symptoms. If the "amyloid-beta accumulation cycle is an AD drug target" concept is proven, repurposing of cancer drugs may emerge as a new, fast-track approach for AD management in the clinic setting.
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Affiliation(s)
- Chinthalapally V. Rao
- Center for Cancer Prevention and Drug DevelopmentDepartment of MedicineHematology/Oncology SectionUniversity of Oklahoma Health Sciences Center (OUHSC)Oklahoma CityOKUSA
| | - Adam S. Asch
- Stephenson Cancer CenterDepartment of MedicineHematology/Oncology SectionUniversity of Oklahoma Health Sciences Center (OUHSC)Oklahoma CityOKUSA
| | - Daniel J. J. Carr
- Department of OphthalmologyUniversity of Oklahoma Health Sciences Center (OUHSC)Oklahoma CityOKUSA
| | - Hiroshi Y. Yamada
- Center for Cancer Prevention and Drug DevelopmentDepartment of MedicineHematology/Oncology SectionUniversity of Oklahoma Health Sciences Center (OUHSC)Oklahoma CityOKUSA
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92
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Sims R, Hill M, Williams J. The multiplex model of the genetics of Alzheimer's disease. Nat Neurosci 2020; 23:311-322. [PMID: 32112059 DOI: 10.1038/s41593-020-0599-5] [Citation(s) in RCA: 247] [Impact Index Per Article: 61.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 01/24/2020] [Indexed: 12/25/2022]
Abstract
Genes play a strong role in Alzheimer's disease (AD), with late-onset AD showing heritability of 58-79% and early-onset AD showing over 90%. Genetic association provides a robust platform to build our understanding of the etiology of this complex disease. Over 50 loci are now implicated for AD, suggesting that AD is a disease of multiple components, as supported by pathway analyses (immunity, endocytosis, cholesterol transport, ubiquitination, amyloid-β and tau processing). Over 50% of late-onset AD heritability has been captured, allowing researchers to calculate the accumulation of AD genetic risk through polygenic risk scores. A polygenic risk score predicts disease with up to 90% accuracy and is an exciting tool in our research armory that could allow selection of those with high polygenic risk scores for clinical trials and precision medicine. It could also allow cellular modelling of the combined risk. Here we propose the multiplex model as a new perspective from which to understand AD. The multiplex model reflects the combination of some, or all, of these model components (genetic and environmental), in a tissue-specific manner, to trigger or sustain a disease cascade, which ultimately results in the cell and synaptic loss observed in AD.
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Affiliation(s)
- Rebecca Sims
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Matthew Hill
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
- UK Dementia Research Institute, School of Medicine, Cardiff University, Cardiff, UK
| | - Julie Williams
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK.
- UK Dementia Research Institute, School of Medicine, Cardiff University, Cardiff, UK.
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93
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Quantitative proteomics to study aging in rabbit liver. Mech Ageing Dev 2020; 187:111227. [PMID: 32126221 DOI: 10.1016/j.mad.2020.111227] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 01/24/2020] [Accepted: 02/27/2020] [Indexed: 12/23/2022]
Abstract
Aging globally effects cellular and organismal metabolism across a range of mammalian species, including humans and rabbits. Rabbits (Oryctolagus cuniculus are an attractive model system of aging due to their genetic similarity with humans and their short lifespans. This model can be used to understand metabolic changes in aging especially in major organs such as liver where we detected pronounced variations in fat metabolism, mitochondrial dysfunction, and protein degradation. Such changes in the liver are consistent across several mammalian species however in rabbits the downstream effects of these changes have not yet been explored. We have applied proteomics to study changes in the liver proteins from young, middle, and old age rabbits using a multiplexing cPILOT strategy. This resulted in the identification of 2,586 liver proteins, among which 45 proteins had significant p < 0.05) changes with aging. Seven proteins were differentially-expressed at all ages and include fatty acid binding protein, aldehyde dehydrogenase, enoyl-CoA hydratase, 3-hydroxyacyl CoA dehydrogenase, apolipoprotein C3, peroxisomal sarcosine oxidase, adhesion G-protein coupled receptor, and glutamate ionotropic receptor kinate. Insights to how alterations in metabolism affect protein expression in liver have been gained and demonstrate the utility of rabbit as a model of aging.
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94
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Genetic architecture of neurodegenerative dementias. Neuropharmacology 2020; 168:108014. [PMID: 32097768 DOI: 10.1016/j.neuropharm.2020.108014] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 02/03/2020] [Accepted: 02/14/2020] [Indexed: 12/14/2022]
Abstract
Molecular genetics has been an invaluable tool to help understand the molecular basis of neurodegenerative dementias. In this review, we provide an overview of the genetic architecture underlying some of the most prevalent causes of dementia, including Alzheimer's dementia, frontotemporal lobar degeneration, Lewy body dementia, and prion diseases. We also discuss the complexity of the human genome and how the novel technologies have revolutionized and accelerated the way we screen the variety of our DNA. Finally, we also provide some examples about how this genetic knowledge is being transferred into the clinic through personalized medicine. This article is part of the special issue entitled 'The Quest for Disease-Modifying Therapies for Neurodegenerative Disorders'.
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95
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Alzheimer’s Disease Genetics: Review of Novel Loci Associated with Disease. CURRENT GENETIC MEDICINE REPORTS 2020. [DOI: 10.1007/s40142-020-00182-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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96
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Blue EE, Horimoto ARVR, Mukherjee S, Wijsman EM, Thornton TA. Local ancestry at APOE modifies Alzheimer's disease risk in Caribbean Hispanics. Alzheimers Dement 2019; 15:1524-1532. [PMID: 31606368 PMCID: PMC6925639 DOI: 10.1016/j.jalz.2019.07.016] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 07/22/2019] [Accepted: 07/25/2019] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Although the relationship between APOE and Alzheimer's disease (AD) is well established in populations of European descent, the effects of APOE and ancestry on AD risk in diverse populations is not well understood. METHODS Logistic mixed model regression and survival analyses were performed in a sample of 3067 Caribbean Hispanics and 3028 individuals of European descent to assess the effects of APOE genotype, local ancestry, and genome-wide ancestry on AD risk and age at onset. RESULTS Among the Caribbean Hispanics, individuals with African-derived ancestry at APOE had 39% lower odds of AD than individuals with European-derived APOE, after adjusting for APOE genotype, age, and genome-wide ancestry. While APOE E2 and E4 effects on AD risk and age at onset were significant in the Caribbean Hispanics, they were substantially attenuated compared with those in European ancestry individuals. DISCUSSION These results suggest that additional genetic variation in the APOE region influences AD risk beyond APOE E2/E3/E4.
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Affiliation(s)
- Elizabeth E Blue
- Division of Medical Genetics, University of Washington, Seattle, WA, USA.
| | | | | | - Ellen M Wijsman
- Division of Medical Genetics, University of Washington, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA; Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, USA; Department of Statistics, University of Washington, Seattle, WA, USA.
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97
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Gardner OK, Wang L, Van Booven D, Whitehead PL, Hamilton-Nelson KL, Adams LD, Starks TD, Hofmann NK, Vance JM, Cuccaro ML, Martin ER, Byrd GS, Haines JL, Bush WS, Beecham GW, Pericak-Vance MA, Griswold AJ. RNA editing alterations in a multi-ethnic Alzheimer disease cohort converge on immune and endocytic molecular pathways. Hum Mol Genet 2019; 28:3053-3061. [PMID: 31162550 PMCID: PMC6737295 DOI: 10.1093/hmg/ddz110] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 03/28/2019] [Accepted: 05/13/2019] [Indexed: 01/08/2023] Open
Abstract
Little is known about the post-transcriptional mechanisms that modulate the genetic effects in the molecular pathways underlying Alzheimer disease (AD), and even less is known about how these changes might differ across diverse populations. RNA editing, the process that alters individual bases of RNA, may contribute to AD pathogenesis due to its roles in neuronal development and immune regulation. Here, we pursued one of the first transcriptome-wide RNA editing studies in AD by examining RNA sequencing data from individuals of both African-American (AA) and non-Hispanic White (NHW) ethnicities. Whole transcriptome RNA sequencing and RNA editing analysis were performed on peripheral blood specimens from 216 AD cases (105 AA, 111 NHW) and 212 gender matched controls (105 AA, 107 NHW). 449 positions in 254 genes and 723 positions in 371 genes were differentially edited in AA and NHW, respectively. While most differentially edited sites localized to different genes in AA and NHW populations, these events converged on the same pathways across both ethnicities, especially endocytic and inflammatory response pathways. Furthermore, these differentially edited sites were preferentially predicted to disrupt miRNA binding and induce nonsynonymous coding changes in genes previously associated with AD in molecular studies, including PAFAH1B2 and HNRNPA1. These findings suggest RNA editing is an important post-transcriptional regulatory program in AD pathogenesis.
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Affiliation(s)
- Olivia K Gardner
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Lily Wang
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL USA
| | - Derek Van Booven
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Patrice L Whitehead
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kara L Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Larry D Adams
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Takiyah D Starks
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Natalia K Hofmann
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jeffery M Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Eden R Martin
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Goldie S Byrd
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Jonathan L Haines
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
- Cleveland Institute for Computational Biology, Cleveland, OH, USA
| | - William S Bush
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
- Cleveland Institute for Computational Biology, Cleveland, OH, USA
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Anthony J Griswold
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
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98
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Wang L, Ying J, Fan P, Weamer EA, DeMichele-Sweet MAA, Lopez OL, Kofler JK, Sweet RA. Effects of Vitamin D Use on Outcomes of Psychotic Symptoms in Alzheimer Disease Patients. Am J Geriatr Psychiatry 2019; 27:908-917. [PMID: 31126722 PMCID: PMC6693492 DOI: 10.1016/j.jagp.2019.03.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 03/13/2019] [Accepted: 03/21/2019] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To identify medications that may prevent psychosis in patients with Alzheimer disease (AD). METHODS The authors compared the frequency of medication usage among patients with AD with or without psychosis symptoms (AD + P versus AD - P). The authors also conducted survival analysis on time to psychosis for patients with AD to identify drugs with beneficial effects. The authors further explored the potential molecular mechanisms of identified drugs by gene-signature analysis. Specifically, the gene expression profiles induced by the identified drug(s) were collected to derive a list of most perturbed genes. These genes were further analyzed by the associations of their genetic variations with AD or psychosis-related phenotypes. RESULTS Vitamin D was used more often in AD - P patients than in AD + P patients. Vitamin D was also significantly associated with delayed time to psychosis. AD and/or psychosis-related genes were enriched in the list of genes most perturbed by vitamin D, specifically genes involved in the regulation of calcium signaling downstream of the vitamin D receptor. CONCLUSION Vitamin D was associated with delayed onset of psychotic symptoms in patients with AD. Its mechanisms of action provide a novel direction for development of drugs to prevent or treat psychosis in AD. In addition, genetic variations in vitamin D-regulated genes may provide a biomarker signature to identify a subpopulation of patients who can benefit from vitamin D treatment.
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Affiliation(s)
- Lirong Wang
- Department of Pharmaceutical Sciences (LW, PF), Computational Chemical Genomics Screening, University of Pittsburgh School of Pharmacy, Pittsburgh
| | - Jian Ying
- Department of Internal Medicine (JY), University of Utah, Salt Lake City
| | - Peihao Fan
- Department of Pharmaceutical Sciences (LW, PF), Computational Chemical Genomics Screening, University of Pittsburgh School of Pharmacy, Pittsburgh
| | - Elise A Weamer
- Department of Neurology (EAW, OLL, RAS), University of Pittsburgh School of Medicine, Pittsburgh
| | | | - Oscar L Lopez
- Department of Neurology (EAW, OLL, RAS), University of Pittsburgh School of Medicine, Pittsburgh; Department of Psychiatry (MAADS, OLL, RAS), University of Pittsburgh School of Medicine, Pittsburgh
| | - Julia K Kofler
- Department of Pathology (JKK), University of Pittsburgh School of Medicine, Pittsburgh
| | - Robert A Sweet
- Department of Neurology (EAW, OLL, RAS), University of Pittsburgh School of Medicine, Pittsburgh; Department of Psychiatry (MAADS, OLL, RAS), University of Pittsburgh School of Medicine, Pittsburgh; VISN 4 Mental Illness Research, Education and Clinical Center (RAS), VA Pittsburgh Healthcare System, Pittsburgh.
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Ma Y, Jun GR, Zhang X, Chung J, Naj AC, Chen Y, Bellenguez C, Hamilton-Nelson K, Martin ER, Kunkle BW, Bis JC, Debette S, DeStefano AL, Fornage M, Nicolas G, van Duijn C, Bennett DA, De Jager PL, Mayeux R, Haines JL, Pericak-Vance MA, Seshadri S, Lambert JC, Schellenberg GD, Lunetta KL, Farrer LA. Analysis of Whole-Exome Sequencing Data for Alzheimer Disease Stratified by APOE Genotype. JAMA Neurol 2019; 76:1099-1108. [PMID: 31180460 PMCID: PMC6563544 DOI: 10.1001/jamaneurol.2019.1456] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Accepted: 03/22/2019] [Indexed: 12/13/2022]
Abstract
IMPORTANCE Previous genome-wide association studies of common variants identified associations for Alzheimer disease (AD) loci evident only among individuals with particular APOE alleles. OBJECTIVE To identify APOE genotype-dependent associations with infrequent and rare variants using whole-exome sequencing. DESIGN, SETTING, AND PARTICIPANTS The discovery stage included 10 441 non-Hispanic white participants in the Alzheimer Disease Sequencing Project. Replication was sought in 2 independent, whole-exome sequencing data sets (1766 patients with AD, 2906 without AD [controls]) and a chip-based genotype imputation data set (8728 patients with AD, 9808 controls). Bioinformatics and functional analyses were conducted using clinical, cognitive, neuropathologic, whole-exome sequencing, and gene expression data obtained from a longitudinal cohort sample including 402 patients with AD and 647 controls. Data were analyzed between March 2017 and September 2018. MAIN OUTCOMES AND MEASURES Score, Firth, and sequence kernel association tests were used to test the association of AD risk with individual variants and genes in subgroups of APOE ε4 carriers and noncarriers. Results with P ≤ 1 × 10-5 were further evaluated in the replication data sets and combined by meta-analysis. RESULTS Among 3145 patients with AD and 4213 controls lacking ε4 (mean [SD] age, 83.4 [7.6] years; 4363 [59.3.%] women), novel genome-wide significant associations were obtained in the discovery sample with rs536940594 in AC099552 (odds ratio [OR], 88.0; 95% CI, 9.08-852.0; P = 2.22 × 10-7) and rs138412600 in GPAA1 (OR, 1.78; 95% CI, 1.44-2.2; meta-P = 7.81 × 10-8). GPAA1 was also associated with expression in the brain of GPAA1 (β = -0.08; P = .03) and its repressive transcription factor, FOXG1 (β = 0.13; P = .003), and global cognition function (β = -0.53; P = .009). Significant gene-wide associations (threshold P ≤ 6.35 × 10-7) were observed for OR8G5 (P = 4.67 × 10-7), IGHV3-7 (P = 9.75 × 10-16), and SLC24A3 (P = 2.67 × 10-12) in 2377 patients with AD and 706 controls with ε4 (mean [SD] age, 75.2 [9.6] years; 1668 [54.1%] women). CONCLUSIONS AND RELEVANCE The study identified multiple possible novel associations for AD with individual and aggregated rare variants in groups of individuals with and without APOE ε4 alleles that reinforce known and suggest additional pathways leading to AD.
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Affiliation(s)
- Yiyi Ma
- Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Center for Translational & Computational Neuroimmunology, Multiple Sclerosis Clinical Care and Research Center, Division of Neuroimmunology, Columbia University Medical Center, New York, New York
- Department of Neurology, Columbia University Medical Center, New York, New York
| | - Gyungah R. Jun
- Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Department of Biostatistics, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Jaeyoon Chung
- Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Adam C. Naj
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Yuning Chen
- Department of Biostatistics, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Celine Bellenguez
- Universite de Lille, INSERM UMR1167, Institute Pasteur de Lille, Lille, France
| | - Kara Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida
| | - Eden R. Martin
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida
| | - Brian W. Kunkle
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Stéphanie Debette
- Bordeaux Population Health Research Center, UMR1219, University Bordeaux, Inserm, Bordeaux, France
- Department of Neurology, Bordeaux University Hospital, Bordeaux, France
| | - Anita L. DeStefano
- Department of Biostatistics, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Department of Neurology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Myriam Fornage
- School of Public Health, University of Texas Health Science Center at Houston, Houston
| | - Gaël Nicolas
- UNIROUEN, Inserm U1245, Normandie University, Rouen, France
- Department of Genetics, Rouen University Hospital, Rouen, France
- Normandy Centre for Genomic and Personalized Medicine, Centre National de Référence pour les Malades Alzheimer Jeunes, Rouen, France
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Philip L. De Jager
- Center for Translational & Computational Neuroimmunology, Multiple Sclerosis Clinical Care and Research Center, Division of Neuroimmunology, Columbia University Medical Center, New York, New York
- Department of Neurology, Columbia University Medical Center, New York, New York
- Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Richard Mayeux
- Department of Neurology, Columbia University Medical Center, New York, New York
| | - Jonathan L Haines
- Institute for Computational Biology, Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida
| | - Sudha Seshadri
- Department of Neurology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
| | | | | | - Kathryn L. Lunetta
- Department of Biostatistics, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Department of Biostatistics, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Department of Neurology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Department of Ophthalmology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
- Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts
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100
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Moreno-Grau S, de Rojas I, Hernández I, Quintela I, Montrreal L, Alegret M, Hernández-Olasagarre B, Madrid L, González-Perez A, Maroñas O, Rosende-Roca M, Mauleón A, Vargas L, Lafuente A, Abdelnour C, Rodríguez-Gómez O, Gil S, Santos-Santos MÁ, Espinosa A, Ortega G, Sanabria Á, Pérez-Cordón A, Cañabate P, Moreno M, Preckler S, Ruiz S, Aguilera N, Pineda JA, Macías J, Alarcón-Martín E, Sotolongo-Grau O, Marquié M, Monté-Rubio G, Valero S, Benaque A, Clarimón J, Bullido MJ, García-Ribas G, Pástor P, Sánchez-Juan P, Álvarez V, Piñol-Ripoll G, García-Alberca JM, Royo JL, Franco E, Mir P, Calero M, Medina M, Rábano A, Ávila J, Antúnez C, Real LM, Orellana A, Carracedo Á, Sáez ME, Tárraga L, Boada M, Ruiz A. Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer's disease and three causality networks: The GR@ACE project. Alzheimers Dement 2019; 15:1333-1347. [PMID: 31473137 DOI: 10.1016/j.jalz.2019.06.4950] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 06/19/2019] [Accepted: 06/19/2019] [Indexed: 01/10/2023]
Abstract
INTRODUCTION Large variability among Alzheimer's disease (AD) cases might impact genetic discoveries and complicate dissection of underlying biological pathways. METHODS Genome Research at Fundacio ACE (GR@ACE) is a genome-wide study of dementia and its clinical endophenotypes, defined based on AD's clinical certainty and vascular burden. We assessed the impact of known AD loci across endophenotypes to generate loci categories. We incorporated gene coexpression data and conducted pathway analysis per category. Finally, to evaluate the effect of heterogeneity in genetic studies, GR@ACE series were meta-analyzed with additional genome-wide association study data sets. RESULTS We classified known AD loci into three categories, which might reflect the disease clinical heterogeneity. Vascular processes were only detected as a causal mechanism in probable AD. The meta-analysis strategy revealed the ANKRD31-rs4704171 and NDUFAF6-rs10098778 and confirmed SCIMP-rs7225151 and CD33-rs3865444. DISCUSSION The regulation of vasculature is a prominent causal component of probable AD. GR@ACE meta-analysis revealed novel AD genetic signals, strongly driven by the presence of clinical heterogeneity in the AD series.
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Affiliation(s)
- Sonia Moreno-Grau
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Itziar de Rojas
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Isabel Hernández
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Inés Quintela
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII). Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Laura Montrreal
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Montserrat Alegret
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Begoña Hernández-Olasagarre
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Laura Madrid
- CAEBI, Centro Andaluz de Estudios Bioinformáticos, Sevilla, Spain
| | | | - Olalla Maroñas
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII). Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Maitée Rosende-Roca
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Ana Mauleón
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Liliana Vargas
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Asunción Lafuente
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Carla Abdelnour
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Octavio Rodríguez-Gómez
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Silvia Gil
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Miguel Ángel Santos-Santos
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Ana Espinosa
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Gemma Ortega
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Ángela Sanabria
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Alba Pérez-Cordón
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Pilar Cañabate
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Mariola Moreno
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Silvia Preckler
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Susana Ruiz
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Nuria Aguilera
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Juan Antonio Pineda
- Unidad Clínica de Enfermedades Infecciosas y Microbiología. Hospital Universitario de Valme, Sevilla, Spain
| | - Juan Macías
- Unidad Clínica de Enfermedades Infecciosas y Microbiología. Hospital Universitario de Valme, Sevilla, Spain
| | - Emilio Alarcón-Martín
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; Department of Surgery, Biochemistry and Molecular Biology, School of Medicine, University of Málaga, Málaga, Spain
| | - Oscar Sotolongo-Grau
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | | | | | | | - Marta Marquié
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Gemma Monté-Rubio
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Sergi Valero
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Alba Benaque
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Jordi Clarimón
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; Memory Unit, Neurology Department and Sant Pau Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Maria Jesus Bullido
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; Centro de Biologia Molecular Severo Ochoa (C.S.I.C.-U.A.M.), Universidad Autonoma de Madrid, Madrid, Spain; Instituto de Investigacion Sanitaria "Hospital la Paz" (IdIPaz), Madrid, Spain
| | | | - Pau Pástor
- Fundació per la Recerca Biomèdica i Social Mútua Terrassa, and Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, University of Barcelona School of Medicine, Terrassa, Spain
| | - Pascual Sánchez-Juan
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; Neurology Service 'Marqués de Valdecilla' University Hospital (University of Cantabria and IDIVAL), Santander, Spain
| | - Victoria Álvarez
- Laboratorio de Genética Hospital Universitario Central de Asturias, Oviedo, Spain; Instituto de Investigación Biosanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Gerard Piñol-Ripoll
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Institut de Recerca Biomédica de Lleida (IRBLLeida), Lleida, Spain
| | | | - José Luis Royo
- Department of Surgery, Biochemistry and Molecular Biology, School of Medicine, University of Málaga, Málaga, Spain
| | - Emilio Franco
- Unidad de Demencias, Servicio de Neurología y Neurofisiología. Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Pablo Mir
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología. Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Miguel Calero
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain; Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Miguel Medina
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Alberto Rábano
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; CIEN Foundation, Queen Sofia Foundation Alzheimer Center, Madrid, Spain; BT-CIEN, Madrid, Spain
| | - Jesús Ávila
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain; Department of Molecular Neuropathology, Centro de Biología Molecular "Severo Ochoa" (CBMSO), Consejo Superior de Investigaciones Científicas (CSIC)/Universidad Autónoma de Madrid (UAM), Madrid, Spain
| | - Carmen Antúnez
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Murcia, Spain
| | - Luis Miguel Real
- Unidad Clínica de Enfermedades Infecciosas y Microbiología. Hospital Universitario de Valme, Sevilla, Spain; Department of Surgery, Biochemistry and Molecular Biology, School of Medicine, University of Málaga, Málaga, Spain
| | - Adelina Orellana
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Ángel Carracedo
- Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII). Universidade de Santiago de Compostela, Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica- CIBERER-IDIS, Santiago de Compostela, Spain
| | | | - Lluís Tárraga
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Mercè Boada
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Agustín Ruiz
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain.
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