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Ray NR, Kunkle BW, Hamilton‐Nelson K, Kurup JT, Rajabli F, Qiao M, Vardarajan BN, Cosacak MI, Kizil C, Jean‐Francois M, Cuccaro M, Reyes‐Dumeyer D, Cantwell L, Kuzma A, Vance JM, Gao S, Hendrie HC, Baiyewu O, Ogunniyi A, Akinyemi RO, Lee W, Martin ER, Wang L, Beecham GW, Bush WS, Xu W, Jin F, Wang L, Farrer LA, Haines JL, Byrd GS, Schellenberg GD, Mayeux R, Pericak‐Vance MA, Reitz C. Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry. Alzheimers Dement 2024; 20:5247-5261. [PMID: 38958117 PMCID: PMC11350055 DOI: 10.1002/alz.13880] [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: 09/20/2023] [Revised: 04/03/2024] [Accepted: 04/12/2024] [Indexed: 07/04/2024]
Abstract
INTRODUCTION Despite a two-fold risk, individuals of African ancestry have been underrepresented in Alzheimer's disease (AD) genomics efforts. METHODS Genome-wide association studies (GWAS) of 2,903 AD cases and 6,265 controls of African ancestry. Within-dataset results were meta-analyzed, followed by functional genomics analyses. RESULTS A novel AD-risk locus was identified in MPDZ on chromosome (chr) 9p23 (rs141610415, MAF = 0.002, p = 3.68×10-9). Two additional novel common and nine rare loci were identified with suggestive associations (P < 9×10-7). Comparison of association and linkage disequilibrium (LD) patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 (ASCL1), suggesting that this association is modulated by regional origin of local African ancestry. DISCUSSION These analyses identified novel AD-associated loci in individuals of African ancestry and suggest that degree of African ancestry modulates some associations. Increased sample sets covering as much African genetic diversity as possible will be critical to identify additional loci and deconvolute local genetic ancestry effects. HIGHLIGHTS Genetic ancestry significantly impacts risk of Alzheimer's Disease (AD). Although individuals of African ancestry are twice as likely to develop AD, they are vastly underrepresented in AD genomics studies. The Alzheimer's Disease Genetics Consortium has previously identified 16 common and rare genetic loci associated with AD in African American individuals. The current analyses significantly expand this effort by increasing the sample size and extending ancestral diversity by including populations from continental Africa. Single variant meta-analysis identified a novel genome-wide significant AD-risk locus in individuals of African ancestry at the MPDZ gene, and 11 additional novel loci with suggestive genome-wide significance at p < 9×10-7. Comparison of African American datasets with samples of higher degree of African ancestry demonstrated differing patterns of association and linkage disequilibrium at one of these loci, suggesting that degree and/or geographic origin of African ancestry modulates the effect at this locus. These findings illustrate the importance of increasing number and ancestral diversity of African ancestry samples in AD genomics studies to fully disentangle the genetic architecture underlying AD, and yield more effective ancestry-informed genetic screening tools and therapeutic interventions.
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Kuchenbecker LA, Thompson KJ, Hurst CD, Opdenbosch BM, Heckman MG, Reddy JS, Nguyen T, Casellas HL, Sotelo KD, Reddy DJ, Lucas JA, Day GS, Willis FB, Graff-Radford N, Ertekin-Taner N, Kalari KR, Carrasquillo MM. Nomination of a novel plasma protein biomarker panel capable of classifying Alzheimer's disease dementia with high accuracy in an African American cohort. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.27.605373. [PMID: 39131392 PMCID: PMC11312441 DOI: 10.1101/2024.07.27.605373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Introduction African Americans (AA) are widely underrepresented in plasma biomarker studies for Alzheimer's disease (AD) and current diagnostic biomarker candidates do not reflect the heterogeneity of AD. Methods Untargeted proteome measurements were obtained using the SomaScan 7k platform to identify novel plasma biomarkers for AD in a cohort of AA clinically diagnosed as AD dementia (n=183) or cognitively unimpaired (CU, n=145). Machine learning approaches were implemented to identify the set of plasma proteins that yields the best classification accuracy. Results A plasma protein panel achieved an area under the curve (AUC) of 0.91 to classify AD dementia vs CU. The reproducibility of this finding was observed in the ANMerge plasma and AMP-AD Diversity brain datasets (AUC=0.83; AUC=0.94). Discussion This study demonstrates the potential of biomarker discovery through untargeted plasma proteomics and machine learning approaches. Our findings also highlight the potential importance of the matrisome and cerebrovascular dysfunction in AD pathophysiology.
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Affiliation(s)
- Lindsey A. Kuchenbecker
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Center for Clinical and Translational Science, Mayo Clinic, Rochester, MN, USA
| | - Kevin J. Thompson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Michael G. Heckman
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Joseph S. Reddy
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Thuy Nguyen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Katie D. Sotelo
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Delila J. Reddy
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - John A. Lucas
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Floyd B. Willis
- Department of Family Medicine, Mayo Clinic, Jacksonville, FL USA
| | | | - Nilufer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Krishna R. Kalari
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
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3
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Gunasekaran TI, Reyes-Dumeyer D, Faber KM, Goate A, Boeve B, Cruchaga C, Pericak-Vance M, Haines JL, Rosenberg R, Tsuang D, Mejia DR, Medrano M, Lantigua RA, Sweet RA, Bennett DA, Wilson RS, Alba C, Dalgard C, Foroud T, Vardarajan BN, Mayeux R. Missense and Loss of Function Variants at GWAS Loci in Familial Alzheimer's Disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.12.18.23300145. [PMID: 38196599 PMCID: PMC10775337 DOI: 10.1101/2023.12.18.23300145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
BACKGROUND Few rare variants have been identified in genetic loci from genome wide association studies of Alzheimer's disease (AD), limiting understanding of mechanisms and risk assessment, and genetic counseling. METHODS Using genome sequencing data from 197 families in The NIA Alzheimer's Disease Family Based Study, and 214 Caribbean Hispanic families, we searched for rare coding variants within known GWAS loci from the largest published study. RESULTS Eighty-six rare missense or loss of function (LoF) variants completely segregated in 17.5% of families, but in 91 (22.1%) of families APOE-e4 was the only variant segregating. However, in 60.3% of families neither APOE-e4 nor missense or LoF variants were found within the GWAS loci. DISCUSSION Although APOE-ε4 and several rare variants were found to segregate in both family datasets, many families had no variant accounting for their disease. This suggests that familial AD may be the result of unidentified rare variants.
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Llibre‐Guerra JJ, Jiang M, Acosta I, Sosa AL, Acosta D, Jimenez‐Velasquez IZ, Guerra M, Salas A, Rodriguez Salgado AM, Llibre‐Guerra JC, Sánchez ND, Prina M, Renton A, Albanese E, Yokoyama JS, Llibre Rodriguez JJ. Social determinants of health but not global genetic ancestry predict dementia prevalence in Latin America. Alzheimers Dement 2024; 20:4828-4840. [PMID: 38837526 PMCID: PMC11247688 DOI: 10.1002/alz.14041] [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: 03/04/2024] [Revised: 05/08/2024] [Accepted: 05/09/2024] [Indexed: 06/07/2024]
Abstract
INTRODUCTION Leveraging the nonmonolithic structure of Latin America, which represents a large variability in social determinants of health (SDoH) and high levels of genetic admixture, we aim to evaluate the relative contributions of SDoH and genetic ancestry in predicting dementia prevalence in Latin American populations. METHODS Community-dwelling participants aged 65 and older (N = 3808) from Cuba, Dominican Republic, Mexico, and Peru completed the 10/66 protocol assessments. Dementia was diagnosed using the cross-culturally validated 10/66 algorithm. Multivariate linear regression models adjusted for SDoH were used in the main analysis. This study used cross-sectional data from the 1066 population-based study. RESULTS Individuals with higher proportions of Native American (>70%) and African American (>70%) ancestry were more likely to exhibit factors contributing to worse SDoH, such as lower educational levels (p < 0.001), lower socioeconomic status (p < 0.001), and higher frequency of vascular risk factors (p < 0.001). After adjusting for measures of SDoH, there was no association between ancestry proportion and dementia probability, and ancestry proportions no longer significantly accounted for the variance in cognitive performance (African predominant p = 0.31 [-0.19, 0.59] and Native predominant p = 0.74 [-0.24, 0.33]). DISCUSSION The findings suggest that social and environmental factors play a more crucial role than genetic ancestry in predicting dementia prevalence in Latin American populations. This underscores the need for public health strategies and policies that address these social determinants to effectively reduce dementia risk in these communities. HIGHLIGHTS Countries in Latin America express a large variability in social determinants of health and levels of admixture. After adjustment for downstream societal factors linked to SDoH, genetic ancestry shows no link to dementia. Population ancestry profiles alone do not influence cognitive performance. SDoH are key drivers of racial disparities in dementia and cognitive performance.
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Affiliation(s)
- Jorge J. Llibre‐Guerra
- Department of NeurologyWashington University School of Medicine in St. LouisSt LouisMissouriUSA
| | - Miao Jiang
- Institute of Public HealthFaculty of Biomedical SciencesUniversità della Svizzera italianaLuganoSwitzerland
| | - Isaac Acosta
- Laboratory of the DementiasNational Institute of Neurology and NeurosurgeryMexico CityMexico
- National Autonomous University of MexicoMexico CityMexico
| | - Ana Luisa Sosa
- Laboratory of the DementiasNational Institute of Neurology and NeurosurgeryMexico CityMexico
- National Autonomous University of MexicoMexico CityMexico
| | - Daisy Acosta
- Internal Medicine DepartmentUniversidad Nacional Pedro Henriquez Ureña (UNPHU), Geriatric SectionSanto DomingoDominican Republic
| | - Ivonne Z. Jimenez‐Velasquez
- Internal Medicine DepartmentGeriatrics Program, School of MedicineMedical Sciences CampusUniversity of Puerto RicoSan JuanPuerto RicoUSA
| | - Mariella Guerra
- Instituto de la Memoria Depresion y Enfermedades de Riesgo IMEDERLimaPerú
| | - Aquiles Salas
- Medicine DepartmentCaracas University Hospital, Faculty of Medicine, Universidad Central de VenezuelaCaracasVenezuela
| | | | | | - Nedelys Díaz Sánchez
- Dementia Research Unit, Facultad de Medicina Finlay‐AlbarranMedical University of HavanaHavanaCuba
| | - Matthew Prina
- Population Health Sciences InstituteFaculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Alan Renton
- Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Emiliano Albanese
- Institute of Public HealthFaculty of Biomedical SciencesUniversità della Svizzera italianaLuganoSwitzerland
| | - Jennifer S. Yokoyama
- Department of NeurologyUCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Juan J. Llibre Rodriguez
- Dementia Research Unit, Facultad de Medicina Finlay‐AlbarranMedical University of HavanaHavanaCuba
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Malamon JS, Farrell JJ, Xia LC, Dombroski BA, Das RG, Way J, Kuzma AB, Valladares O, Leung YY, Scanlon AJ, Lopez IAB, Brehony J, Worley KC, Zhang NR, Wang LS, Farrer LA, Schellenberg GD, Lee WP, Vardarajan BN. A comparative study of structural variant calling in WGS from Alzheimer's disease families. Life Sci Alliance 2024; 7:e202302181. [PMID: 38418088 PMCID: PMC10902710 DOI: 10.26508/lsa.202302181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 03/01/2024] Open
Abstract
Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp.
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Affiliation(s)
- John S Malamon
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John J Farrell
- Biomedical Genetics Section, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, USA
| | - Li Charlie Xia
- https://ror.org/03mtd9a03 Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Beth A Dombroski
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rueben G Das
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jessica Way
- Broad Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Amanda B Kuzma
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Otto Valladares
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yuk Yee Leung
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Allison J Scanlon
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Irving Antonio Barrera Lopez
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jack Brehony
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kim C Worley
- https://ror.org/02pttbw34 Human Genome Sequencing Center, and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Nancy R Zhang
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Lindsay A Farrer
- Biomedical Genetics Section, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, USA
- Departments of Neurology and Ophthalmology, Boston University School of Medicine, Boston University, Boston, MA, USA
- Departments of Epidemiology and Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Badri N Vardarajan
- https://ror.org/01esghr10 Gertrude H. Sergievsky Center and Taub Institute of Aging Brain, Department of Neurology, Columbia University Medical Center, New York, NY, USA
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Reddy JS, Heath L, Vander Linden A, Allen M, de Paiva Lopes K, Seifar F, Wang E, Ma Y, Poehlman WL, Quicksall ZS, Runnels A, Wang Y, Duong DM, Yin L, Xu K, Modeste ES, Shantaraman A, Dammer EB, Ping L, Oatman SR, Scanlan J, Ho C, Carrasquillo MM, Atik M, Yepez G, Mitchell AO, Nguyen TT, Chen X, Marquez DX, Reddy H, Xiao H, Seshadri S, Mayeux R, Prokop S, Lee EB, Serrano GE, Beach TG, Teich AF, Haroutunian V, Fox EJ, Gearing M, Wingo A, Wingo T, Lah JJ, Levey AI, Dickson DW, Barnes LL, De Jager P, Zhang B, Bennett D, Seyfried NT, Greenwood AK, Ertekin-Taner N. Bridging the Gap: Multi-Omics Profiling of Brain Tissue in Alzheimer's Disease and Older Controls in Multi-Ethnic Populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.16.589592. [PMID: 38659743 PMCID: PMC11042309 DOI: 10.1101/2024.04.16.589592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
INTRODUCTION Multi-omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked African Americans (AA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS To bridge this gap, Accelerating Medicines Partnership in AD (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors. RESULTS We generated multi-omics data and curated and harmonized phenotypic data from AA (n=306), LA (n=326), or AA and LA (n=4) brain donors plus Non-Hispanic White (n=252) and other (n=20) ethnic groups, to establish a foundational dataset enriched for AA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION Inclusion of traditionally underrepresented groups in multi-omics studies is essential to discover the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD.
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Affiliation(s)
- Joseph S Reddy
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Laura Heath
- Sage Bionetworks, 2901 3rd Ave #330, Seattle, WA 98121
| | | | - Mariet Allen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Katia de Paiva Lopes
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Fatemeh Seifar
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Erming Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029
| | - Yiyi Ma
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | | | | | - Alexi Runnels
- New York Genome Center, 101 6th Ave, New York, NY 10013
| | - Yanling Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Duc M Duong
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Luming Yin
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Kaiming Xu
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Erica S Modeste
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | | | - Eric B Dammer
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Lingyan Ping
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | | | - Jo Scanlan
- Sage Bionetworks, 2901 3rd Ave #330, Seattle, WA 98121
| | - Charlotte Ho
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | | | - Merve Atik
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Geovanna Yepez
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | | | - Thuy T Nguyen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Xianfeng Chen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - David X Marquez
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
- University of Illinois Chicago, 1200 West Harrison St., Chicago, Illinois 60607
| | - Hasini Reddy
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Harrison Xiao
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Sudha Seshadri
- The Glen Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas, 8300 Floyd Curl Drive, San Antonio TX 78229
| | - Richard Mayeux
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | | | - Edward B Lee
- Center for Neurodegenerative Disease Brain Bank at the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA 19104-2676
| | - Geidy E Serrano
- Banner Sun Health Research Institute, 10515 W Santa Fe Dr, Sun City, AZ 85351
| | - Thomas G Beach
- Banner Sun Health Research Institute, 10515 W Santa Fe Dr, Sun City, AZ 85351
| | - Andrew F Teich
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Varham Haroutunian
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
| | - Edward J Fox
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Marla Gearing
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Aliza Wingo
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Thomas Wingo
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - James J Lah
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Allan I Levey
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Dennis W Dickson
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Lisa L Barnes
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Philip De Jager
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029
| | - David Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
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Ray NR, Kunkle BW, Hamilton-Nelson K, Kurup JT, Rajabli F, Cosacak MI, Kizil C, Jean-Francois M, Cuccaro M, Reyes-Dumeyer D, Cantwell L, Kuzma A, Vance JM, Gao S, Hendrie HC, Baiyewu O, Ogunniyi A, Akinyemi RO, Lee WP, Martin ER, Wang LS, Beecham GW, Bush WS, Farrer LA, Haines JL, Byrd GS, Schellenberg GD, Mayeux R, Pericak-Vance MA, Reitz C. Extended genome-wide association study employing the African Genome Resources Panel identifies novel susceptibility loci for Alzheimer's Disease in individuals of African ancestry. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.29.23294774. [PMID: 37693582 PMCID: PMC10491365 DOI: 10.1101/2023.08.29.23294774] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
INTRODUCTION Despite a two-fold increased risk, individuals of African ancestry have been significantly underrepresented in Alzheimer's Disease (AD) genomics efforts. METHODS GWAS of 2,903 AD cases and 6,265 cognitive controls of African ancestry. Within-dataset results were meta-analyzed, followed by gene-based and pathway analyses, and analysis of RNAseq and whole-genome sequencing data. RESULTS A novel AD risk locus was identified in MPDZ on chromosome 9p23 (rs141610415, MAF=.002, P =3.68×10 -9 ). Two additional novel common and nine novel rare loci approached genome-wide significance at P <9×10 -7 . Comparison of association and LD patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 ( ASCL1 ), suggesting that the association is modulated by regional origin of local African ancestry. DISCUSSION Increased sample sizes and sample sets from Africa covering as much African genetic diversity as possible will be critical to identify additional disease-associated loci and improve deconvolution of local genetic ancestry effects.
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8
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Logue MW, Dasgupta S, Farrer LA. Genetics of Alzheimer's Disease in the African American Population. J Clin Med 2023; 12:5189. [PMID: 37629231 PMCID: PMC10455208 DOI: 10.3390/jcm12165189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 08/02/2023] [Accepted: 08/06/2023] [Indexed: 08/27/2023] Open
Abstract
Black/African American (AA) individuals have a higher risk of Alzheimer's disease (AD) than White non-Hispanic persons of European ancestry (EUR) for reasons that may include economic disparities, cardiovascular health, quality of education, and biases in the methods used to diagnose AD. AD is also heritable, and some of the differences in risk may be due to genetics. Many AD-associated variants have been identified by candidate gene studies, genome-wide association studies (GWAS), and genome-sequencing studies. However, most of these studies have been performed using EUR cohorts. In this paper, we review the genetics of AD and AD-related traits in AA individuals. Importantly, studies of genetic risk factors in AA cohorts can elucidate the molecular mechanisms underlying AD risk in AA and other populations. In fact, such studies are essential to enable reliable precision medicine approaches in persons with considerable African ancestry. Furthermore, genetic studies of AA cohorts allow exploration of the ways the impact of genes can vary by ancestry, culture, and economic and environmental disparities. They have yielded important gains in our knowledge of AD genetics, and increasing AA individual representation within genetic studies should remain a priority for inclusive genetic study design.
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Affiliation(s)
- Mark W. Logue
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA 02130, USA;
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Shoumita Dasgupta
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Medical Sciences and Education, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
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9
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Scharaw S, Sola-Carvajal A, Belevich I, Webb AT, Das S, Andersson S, Pentinmikko N, Villablanca EJ, Goldenring JR, Jokitalo E, Coffey RJ, Katajisto P. Golgi organization is a determinant of stem cell function in the small intestine. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.23.533814. [PMID: 36993731 PMCID: PMC10055334 DOI: 10.1101/2023.03.23.533814] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Cell-to-cell signalling between niche and stem cells regulates tissue regeneration. While the identity of many mediating factors is known, it is largely unknown whether stem cells optimize their receptiveness to niche signals according to the niche organization. Here, we show that Lgr5+ small intestinal stem cells (ISCs) regulate the morphology and orientation of their secretory apparatus to match the niche architecture, and to increase transport efficiency of niche signal receptors. Unlike the progenitor cells lacking lateral niche contacts, ISCs orient Golgi apparatus laterally towards Paneth cells of the epithelial niche, and divide Golgi into multiple stacks reflecting the number of Paneth cell contacts. Stem cells with a higher number of lateral Golgi transported Epidermal growth factor receptor (Egfr) with a higher efficiency than cells with one Golgi. The lateral Golgi orientation and enhanced Egfr transport required A-kinase anchor protein 9 (Akap9), and was necessary for normal regenerative capacity in vitro . Moreover, reduced Akap9 in aged ISCs renders ISCs insensitive to niche-dependent modulation of Golgi stack number and transport efficiency. Our results reveal stem cell-specific Golgi complex configuration that facilitates efficient niche signal reception and tissue regeneration, which is compromised in the aged epithelium.
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10
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Pan X, Coban Akdemir ZH, Gao R, Jiang X, Sheynkman GM, Wu E, Huang JH, Sahni N, Yi SS. AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning. Brief Bioinform 2023; 24:bbad030. [PMID: 36752347 PMCID: PMC10025433 DOI: 10.1093/bib/bbad030] [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: 07/09/2022] [Revised: 12/19/2022] [Accepted: 01/13/2023] [Indexed: 02/09/2023] Open
Abstract
Alzheimer's disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple risk factors. Increasing research evidence demonstrates that genetics may be a key factor responsible for the occurrence of the disease. Although previous reports identified quite a few AD-associated genes, they were mostly limited owing to patient sample size and selection bias. There is a lack of comprehensive research aimed to identify AD-associated risk mutations systematically. To address this challenge, we hereby construct a large-scale AD mutation and co-mutation framework ('AD-Syn-Net'), and propose deep learning models named Deep-SMCI and Deep-CMCI configured with fully connected layers that are capable of predicting cognitive impairment of subjects effectively based on genetic mutation and co-mutation profiles. Next, we apply the customized frameworks to data sets to evaluate the importance scores of the mutations and identified mutation effectors and co-mutation combination vulnerabilities contributing to cognitive impairment. Furthermore, we evaluate the influence of mutation pairs on the network architecture to dissect the genetic organization of AD and identify novel co-mutations that could be responsible for dementia, laying a solid foundation for proposing future targeted therapy for AD precision medicine. Our deep learning model codes are available open access here: https://github.com/Pan-Bio/AD-mutation-effectors.
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Affiliation(s)
- Xingxin Pan
- Livestrong Cancer Institutes, and Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
| | - Zeynep H Coban Akdemir
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Ruixuan Gao
- Departments of Chemistry and Biological Sciences, University of Illinois Chicago, Chicago, IL 60607, USA
| | - Xiaoqian Jiang
- School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX 77030, USA
| | - Gloria M Sheynkman
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA 22903, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Center for Public Health Genomics, and UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA 22903, USA
| | - Erxi Wu
- Livestrong Cancer Institutes, and Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
- Neuroscience Institute and Department of Neurosurgery, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Surgery, Texas A & M University Health Science Center, College of Medicine, Temple, TX 76508, USA
- Department of Pharmaceutical Sciences, Texas A & M University Health Science Center, College of Pharmacy, College Station, TX 77843, USA
| | - Jason H Huang
- Neuroscience Institute and Department of Neurosurgery, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Surgery, Texas A & M University Health Science Center, College of Medicine, Temple, TX 76508, USA
| | - Nidhi Sahni
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
- Quantitative and Computational Biosciences Program, Baylor College of Medicine, Houston, TX 77030, USA
| | - S Stephen Yi
- Livestrong Cancer Institutes, and Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
- Oden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, Austin, TX 78712, USA
- Interdisciplinary Life Sciences Graduate Programs (ILSGP), College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX 78712, USA
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11
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Sherva R, Zhang R, Sahelijo N, Jun G, Anglin T, Chanfreau C, Cho K, Fonda JR, Gaziano JM, Harrington KM, Ho YL, Kremen WS, Litkowski E, Lynch J, Neale Z, Roussos P, Marra D, Mez J, Miller MW, Salat DH, Tsuang D, Wolf E, Zeng Q, Panizzon MS, Merritt VC, Farrer LA, Hauger RL, Logue MW. African ancestry GWAS of dementia in a large military cohort identifies significant risk loci. Mol Psychiatry 2023; 28:1293-1302. [PMID: 36543923 PMCID: PMC10066923 DOI: 10.1038/s41380-022-01890-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 11/02/2022] [Accepted: 11/15/2022] [Indexed: 12/24/2022]
Abstract
While genome wide association studies (GWASs) of Alzheimer's Disease (AD) in European (EUR) ancestry cohorts have identified approximately 83 potentially independent AD risk loci, progress in non-European populations has lagged. In this study, data from the Million Veteran Program (MVP), a biobank which includes genetic data from more than 650,000 US Veteran participants, was used to examine dementia genetics in an African descent (AFR) cohort. A GWAS of Alzheimer's disease and related dementias (ADRD), an expanded AD phenotype including dementias such as vascular and non-specific dementia that included 4012 cases and 18,435 controls age 60+ in AFR MVP participants was performed. A proxy dementia GWAS based on survey-reported parental AD or dementia (n = 4385 maternal cases, 2256 paternal cases, and 45,970 controls) was also performed. These two GWASs were meta-analyzed, and then subsequently compared and meta-analyzed with the results from a previous AFR AD GWAS from the Alzheimer's Disease Genetics Consortium (ADGC). A meta-analysis of common variants across the MVP ADRD and proxy GWASs yielded GWAS significant associations in the region of APOE (p = 2.48 × 10-101), in ROBO1 (rs11919682, p = 1.63 × 10-8), and RNA RP11-340A13.2 (rs148433063, p = 8.56 × 10-9). The MVP/ADGC meta-analysis yielded additional significant SNPs near known AD risk genes TREM2 (rs73427293, p = 2.95 × 10-9), CD2AP (rs7738720, p = 1.14 × 10-9), and ABCA7 (rs73505251, p = 3.26 × 10-10), although the peak variants observed in these genes differed from those previously reported in EUR and AFR cohorts. Of the genes in or near suggestive or genome-wide significant associated variants, nine (CDA, SH2D5, DCBLD1, EML6, GOPC, ABCA7, ROS1, TMCO4, and TREM2) were differentially expressed in the brains of AD cases and controls. This represents the largest AFR GWAS of AD and dementia, finding non-APOE GWAS-significant common SNPs associated with dementia. Increasing representation of AFR participants is an important priority in genetic studies and may lead to increased insight into AD pathophysiology and reduce health disparities.
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Affiliation(s)
- Richard Sherva
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
- Boston University Chobanian & Avedisian School of Medicine, Biomedical Genetics, Boston, MA, USA
| | - Rui Zhang
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
| | - Nathan Sahelijo
- Boston University Chobanian & Avedisian School of Medicine, Biomedical Genetics, Boston, MA, USA
| | - Gyungah Jun
- Boston University Chobanian & Avedisian School of Medicine, Biomedical Genetics, Boston, MA, USA
| | - Tori Anglin
- VA Informatics and Computing Infrastructure (VINCI), Salt Lake City, UT, USA
| | - Catherine Chanfreau
- VA Informatics and Computing Infrastructure (VINCI), Salt Lake City, UT, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jennifer R Fonda
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Educational and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kelly M Harrington
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Elizabeth Litkowski
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- VA Eastern Colorado Healthcare System, Aurora, CO, USA
| | - Julie Lynch
- VA Informatics and Computing Infrastructure (VINCI), Salt Lake City, UT, USA
| | - Zoe Neale
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Departments of Psychiatry and Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, NY, USA
| | - David Marra
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Jesse Mez
- Boston University Chobanian & Avedisian School of Medicine, Biomedical Genetics, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Boston University Alzheimer's Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Mark W Miller
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - David H Salat
- Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, USA
| | - Debby Tsuang
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | - Erika Wolf
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Qing Zeng
- VA Washington DC Healthcare System, Washington, DC, USA
| | - Matthew S Panizzon
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Victoria C Merritt
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- VA San Diego Healthcare System, 3350 La Jolla Village Dr, San Diego, CA, USA
| | - Lindsay A Farrer
- Boston University Chobanian & Avedisian School of Medicine, Biomedical Genetics, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Boston University Alzheimer's Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Richard L Hauger
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
- VA San Diego Healthcare System, 3350 La Jolla Village Dr, San Diego, CA, USA
| | - Mark W Logue
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA.
- Boston University Chobanian & Avedisian School of Medicine, Biomedical Genetics, Boston, MA, USA.
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA.
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
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Abstract
PURPOSE OF REVIEW This article discusses the spectrum of genetic risk in familial and sporadic forms of early- and late-onset Alzheimer disease (AD). Recent work illuminating the complex genetic architecture of AD is discussed in the context of high and low risk and what is known in different populations. RECENT FINDINGS A small proportion of AD is autosomal dominant familial AD caused by variants in PSEN1, PSEN2, or APP, although more recently described rare genetic changes can also increase risk substantially over the general population, with odds ratios estimated at 2 to 4. APOE remains the strongest genetic risk factor for late-onset AD, and understanding the biology of APOE has yielded mechanistic insights and leads for therapeutic interventions. Genome-wide studies enabled by rapidly developing technologic advances in sequencing have identified numerous risk factors that have a low impact on risk but are widely shared throughout the population and involve a repertoire of cell pathways, again shining light on potential paths to intervention. Population studies aimed at defining and stratifying genetic AD risk have been informative, although they are not yet widely applicable clinically because the studies were not performed in people with diverse ancestry and ethnicity and thus population-wide data are lacking. SUMMARY The value of genetic information to practitioners in the clinic is distinct from information sought by researchers looking to identify novel therapeutic targets. It is possible to envision a future in which genetic stratification joins other biomarkers to facilitate therapeutic choices and inform prognosis. Genetics already has transformed our understanding of AD pathogenesis and will, no doubt, continue to reveal the complexity of brain biology in health and disease.
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Transcript levels in plasma contribute substantial predictive value as potential Alzheimer's disease biomarkers in African Americans. EBioMedicine 2022; 78:103929. [PMID: 35307406 PMCID: PMC9044003 DOI: 10.1016/j.ebiom.2022.103929] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 02/14/2022] [Accepted: 02/24/2022] [Indexed: 01/15/2023] Open
Abstract
Background African Americans (AA) remain underrepresented in Alzheimer's disease (AD) research, despite the prevalence of AD being double in AA compared to non-Hispanic whites. To address this disparity, our group has established the Florida Consortium for African American Alzheimer's Disease Studies (FCA3DS), focusing on the identification of genetic risk factors and novel plasma biomarkers. Method Utilizing FCA3DS whole exome sequence (WES) and plasma RNA samples from AD cases (n=151) and cognitively unimpaired (CU) elderly controls (n=269), we have performed differential gene expression (DGE) and expression quantitative trait locus (eQTL) analyses on 50 transcripts measured with a custom nanoString® panel. We designed this panel to measure, in plasma, cell-free mRNA (cf-mRNA) levels of AD-relevant genes. Findings Association with higher plasma CLU in CU vs. AD remained significant after Bonferroni correction. Study-wide significant eQTL associations were observed with 105 WES variants in cis with 22 genes, including variants in genes previously associated with AD risk in AA such as ABCA7 and AKAP9. Results from this plasma eQTL analysis identified AD-risk variants in ABCA7 and AKAP9 that are significantly associated with lower and higher plasma mRNA levels of these genes, respectively. Receiver operating characteristic analysis of age, sex APOE-ε4 dosage, CLU, APP, CD14, ABCA7, AKAP9 and APOE mRNA levels, and ABCA7 and AKAP9 eQTLs, achieved 77% area under the curve to discriminate AD vs. CU, an 8% improvement over a model that only included age, sex and APOE-ε4 dosage. Interpretation Incorporating plasma mRNA levels could contribute to improved predictive value of AD biomarker panels. Funding This work was supported by the National Institute on Aging [RF AG051504, U01 AG046139, R01 AG061796 to NET; P30 AG062677 to JAL and NGR]; Florida Health Ed and Ethel Moore Alzheimer's Disease grants [5AZ03 and 7AZ17 to NET; 7AZ07 to MMC; 8AZ08 to JAL].
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14
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Khani M, Gibbons E, Bras J, Guerreiro R. Challenge accepted: uncovering the role of rare genetic variants in Alzheimer's disease. Mol Neurodegener 2022; 17:3. [PMID: 35000612 PMCID: PMC8744312 DOI: 10.1186/s13024-021-00505-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 12/06/2021] [Indexed: 12/11/2022] Open
Abstract
The search for rare variants in Alzheimer's disease (AD) is usually deemed a high-risk - high-reward situation. The challenges associated with this endeavor are real. Still, the application of genome-wide technologies to large numbers of cases and controls or to small, well-characterized families has started to be fruitful.Rare variants associated with AD have been shown to increase risk or cause disease, but also to protect against the development of AD. All of these can potentially be targeted for the development of new drugs.Multiple independent studies have now shown associations of rare variants in NOTCH3, TREM2, SORL1, ABCA7, BIN1, CLU, NCK2, AKAP9, UNC5C, PLCG2, and ABI3 with AD and suggested that they may influence disease via multiple mechanisms. These genes have reported functions in the immune system, lipid metabolism, synaptic plasticity, and apoptosis. However, the main pathway emerging from the collective of genes harboring rare variants associated with AD is the Aβ pathway. Associations of rare variants in dozens of other genes have also been proposed, but have not yet been replicated in independent studies. Replication of this type of findings is one of the challenges associated with studying rare variants in complex diseases, such as AD. In this review, we discuss some of these primary challenges as well as possible solutions.Integrative approaches, the availability of large datasets and databases, and the development of new analytical methodologies will continue to produce new genes harboring rare variability impacting AD. In the future, more extensive and more diverse genetic studies, as well as studies of deeply characterized families, will enhance our understanding of disease pathogenesis and put us on the correct path for the development of successful drugs.
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Affiliation(s)
- Marzieh Khani
- School of Biology, College of Science, University of Tehran, Tehran, Iran
| | - Elizabeth Gibbons
- Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave. N.E., Grand Rapids, Michigan 49503-2518 USA
| | - Jose Bras
- Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave. N.E., Grand Rapids, Michigan 49503-2518 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, 333 Bostwick Ave. N.E., Grand Rapids, Michigan 49503-2518 USA
- Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI USA
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15
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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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16
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Xue D, Bush WS, Renton AE, Marcora EA, Bis JC, Kunkle BW, Boerwinkle E, DeStefano AL, Farrer L, Goate A, Mayeux R, Pericak‐Vance M, Schellenberg G, Seshadri S, Wijsman E, Haines JL, Blue EE. Large-scale sequencing studies expand the known genetic architecture of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12255. [PMID: 35005195 PMCID: PMC8720139 DOI: 10.1002/dad2.12255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 09/21/2021] [Indexed: 11/12/2022]
Abstract
INTRODUCTION Genes implicated by genome-wide association studies and family-based studies of Alzheimer's disease (AD) are largely discordant. We hypothesized that genes identified by sequencing studies like the Alzheimer's Disease Sequencing Project (ADSP) may bridge this gap and highlight shared biological mechanisms. METHODS We performed structured literature review of genes prioritized by ADSP studies, genes underlying familial dementias, and genes nominated by genome-wide association studies. Gene set enrichment analyses of each list identified enriched pathways. RESULTS The genes prioritized by the ADSP, familial dementia studies, and genome-wide association studies minimally overlapped. Each gene set identified dozens of enriched pathways, several of which were shared (e.g., regulation of amyloid beta clearance). DISCUSSION Alternative study designs provide unique insights into AD genetics. Shared pathways enriched by different genes highlight their relevance to AD pathogenesis, while the patterns of pathway enrichment unique to each gene set provide additional targets for functional studies.
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Affiliation(s)
- Diane Xue
- Institute for Public Health GeneticsUniversity of WashingtonSeattleWashingtonUSA
| | - William S. Bush
- Department of Population and Quantitative Health Sciences and Department of Genetics and Genome SciencesCase Western Reserve UniversityClevelandOhioUSA
- Cleveland Institute for Computational BiologyClevelandOhioUSA
| | - Alan E. Renton
- Department of Genetics and Genomic SciencesNash Family Department of Neuroscienceand Ronald M. Loeb Center for Alzheimer's DiseaseIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Edoardo A. Marcora
- Department of Genetics and Genomic SciencesNash Family Department of Neuroscienceand Ronald M. Loeb Center for Alzheimer's DiseaseIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Joshua C. Bis
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Brian W. Kunkle
- The John P. Hussman Institute for Human GenomicsUniversity of MiamiMiamiFloridaUSA
- Dr. John T Macdonald Foundation Department of Human GeneticsMiller School of MedicineUniversity of MiamiMiamiFloridaUSA
| | | | - Eric Boerwinkle
- Human Genome Sequencing CenterDepartment of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
- School of Public HealthUniversity of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Anita L. DeStefano
- Department of BiostatisticsBoston UniversityBostonMassachusettsUSA
- Department of NeurologyBoston UniversityBostonMassachusettsUSA
| | - Lindsay Farrer
- Department of BiostatisticsBoston UniversityBostonMassachusettsUSA
- Department of NeurologyBoston UniversityBostonMassachusettsUSA
- Division of Biomedical GeneticsDepartment of MedicineDepartment of Epidemiologyand Department of OphthalmologyBoston UniversityBostonMassachusettsUSA
| | - Alison Goate
- Department of Genetics and Genomic SciencesNash Family Department of Neuroscienceand Ronald M. Loeb Center for Alzheimer's DiseaseIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Genetics and Genomics Sciences and Friedman Brain InstituteMount Sinai School of MedicineNew YorkNew YorkUSA
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainGertrude H. Sergievsky CenterDepartment of NeurologyDepartment of Psychiatryand EpidemiologyColumbia UniversityNew YorkNew YorkUSA
| | - Margaret Pericak‐Vance
- The John P. Hussman Institute for Human GenomicsUniversity of MiamiMiamiFloridaUSA
- Dr. John T Macdonald Foundation Department of Human GeneticsMiller School of MedicineUniversity of MiamiMiamiFloridaUSA
| | - Gerard Schellenberg
- Penn Neurodegeneration Genomics CenterDepartment of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases and Department of NeurologyUniversity of Texas Health Science CenterSan AntonioTexasUSA
| | - Ellen Wijsman
- Institute for Public Health GeneticsUniversity of WashingtonSeattleWashingtonUSA
- Division of Medical GeneticsUniversity of WashingtonSeattleWashingtonUSA
- Department of BiostatisticsUniversity of WashingtonSeattleWashingtonUSA
| | - Jonathan L. Haines
- Department of Population and Quantitative Health Sciences and Department of Genetics and Genome SciencesCase Western Reserve UniversityClevelandOhioUSA
- Cleveland Institute for Computational BiologyClevelandOhioUSA
| | - Elizabeth E. Blue
- Institute for Public Health GeneticsUniversity of WashingtonSeattleWashingtonUSA
- Division of Medical GeneticsUniversity of WashingtonSeattleWashingtonUSA
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17
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Rubin L, Ingram LA, Resciniti NV, Ashford-Carroll B, Leith KH, Rose A, Ureña S, McCollum Q, Friedman DB. Genetic Risk Factors for Alzheimer's Disease in Racial/Ethnic Minority Populations in the U.S.: A Scoping Review. Front Public Health 2021; 9:784958. [PMID: 35004586 PMCID: PMC8739784 DOI: 10.3389/fpubh.2021.784958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 11/23/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: As the United States (U.S.) population rapidly ages, the incidence of Alzheimer's Disease and Related Dementias (ADRDs) is rising, with racial/ethnic minorities affected at disproportionate rates. Much research has been undertaken to test, sequence, and analyze genetic risk factors for ADRDs in Caucasian populations, but comparatively little has been done with racial/ethnic minority populations. We conducted a scoping review to examine the nature and extent of the research that has been published about the genetic factors of ADRDs among racial/ethnic minorities in the U.S. Design: Using an established scoping review methodological framework, we searched electronic databases for articles describing peer-reviewed empirical studies or Genome-Wide Association Studies that had been published 2005-2018 and focused on ADRD-related genes or genetic factors among underrepresented racial/ethnic minority population in the U.S. Results: Sixty-six articles met the inclusion criteria for full text review. Well-established ADRD genetic risk factors for Caucasian populations including APOE, APP, PSEN1, and PSEN2 have not been studied to the same degree in minority U.S. populations. Compared to the amount of research that has been conducted with Caucasian populations in the U.S., racial/ethnic minority communities are underrepresented. Conclusion: Given the projected growth of the aging population and incidence of ADRDs, particularly among racial/ethnic minorities, increased focus on this important segment of the population is warranted. Our review can aid researchers in developing fundamental research questions to determine the role that ADRD risk genes play in the heavier burden of ADRDs in racial/ethnic minority populations.
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Affiliation(s)
- Lindsey Rubin
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Lucy A. Ingram
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Nicholas V. Resciniti
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, United States
| | - Brianna Ashford-Carroll
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Katherine Henrietta Leith
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Aubrey Rose
- School of Medicine, University of South Carolina, Columbia, SC, United States
| | - Stephanie Ureña
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Quentin McCollum
- College of Social Work, University of South Carolina, Columbia, SC, United States
| | - Daniela B. Friedman
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
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18
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Association of low-frequency and rare coding variants with information processing speed. Transl Psychiatry 2021; 11:613. [PMID: 34864818 PMCID: PMC8643353 DOI: 10.1038/s41398-021-01736-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 10/20/2021] [Accepted: 11/10/2021] [Indexed: 11/25/2022] Open
Abstract
Measures of information processing speed vary between individuals and decline with age. Studies of aging twins suggest heritability may be as high as 67%. The Illumina HumanExome Bead Chip genotyping array was used to examine the association of rare coding variants with performance on the Digit-Symbol Substitution Test (DSST) in community-dwelling adults participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. DSST scores were available for 30,576 individuals of European ancestry from nine cohorts and for 5758 individuals of African ancestry from four cohorts who were older than 45 years and free of dementia and clinical stroke. Linear regression models adjusted for age and gender were used for analysis of single genetic variants, and the T5, T1, and T01 burden tests that aggregate the number of rare alleles by gene were also applied. Secondary analyses included further adjustment for education. Meta-analyses to combine cohort-specific results were carried out separately for each ancestry group. Variants in RNF19A reached the threshold for statistical significance (p = 2.01 × 10-6) using the T01 test in individuals of European descent. RNF19A belongs to the class of E3 ubiquitin ligases that confer substrate specificity when proteins are ubiquitinated and targeted for degradation through the 26S proteasome. Variants in SLC22A7 and OR51A7 were suggestively associated with DSST scores after adjustment for education for African-American participants and in the European cohorts, respectively. Further functional characterization of its substrates will be required to confirm the role of RNF19A in cognitive function.
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19
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Zhan L, Li J, Jew B, Sul JH. Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences. PLoS Genet 2021; 17:e1009772. [PMID: 34516545 PMCID: PMC8460036 DOI: 10.1371/journal.pgen.1009772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 09/23/2021] [Accepted: 08/10/2021] [Indexed: 11/19/2022] Open
Abstract
Late-onset Alzheimer's disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic pathway to AD, with an emphasis on common loci. However, the contribution of rare variants in this pathway to AD has not been thoroughly investigated. In this study, we focused on the effect of rare variants on AD by first applying a rare-variant gene-set burden analysis using genes in the endocytic pathway on over 3,000 individuals with European ancestry from three large whole-genome sequencing (WGS) studies. We identified significant associations of rare-variant burden within the endocytic pathway with AD, which were successfully replicated in independent datasets. We further demonstrated that this endocytic rare-variant enrichment is associated with neurofibrillary tangles (NFTs) and age-related phenotypes, increasing the risk of obtaining severer brain damage, earlier age-at-onset, and earlier age-of-death. Next, by aggregating rare variants within each gene, we sought to identify single endocytic genes associated with AD and NFTs. Careful examination using NFTs revealed one significantly associated gene, ANKRD13D. To identify functional associations, we integrated bulk RNA-Seq data from over 600 brain tissues and found two endocytic expression genes (eGenes), HLA-A and SLC26A7, that displayed significant influences on their gene expressions. Differential expressions between AD patients and controls of these three identified genes were further examined by incorporating scRNA-Seq data from 48 post-mortem brain samples and demonstrated distinct expression patterns across cell types. Taken together, our results demonstrated strong rare-variant effect in the endocytic pathway on AD risk and progression and functional effect of gene expression alteration in both bulk and single-cell resolution, which may bring more insight and serve as valuable resources for future AD genetic studies, clinical research, and therapeutic targeting.
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Affiliation(s)
- Lingyu Zhan
- Molecular Biology Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Jiajin Li
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Brandon Jew
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Jae Hoon Sul
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, United States of America
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20
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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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21
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Qin W, Zhou A, Zuo X, Jia L, Li F, Wang Q, Li Y, Wei Y, Jin H, Cruchaga C, Benitez BA, Jia J. Exome sequencing revealed PDE11A as a novel candidate gene for early-onset Alzheimer's disease. Hum Mol Genet 2021; 30:811-822. [PMID: 33835157 PMCID: PMC8161517 DOI: 10.1093/hmg/ddab090] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 11/14/2022] Open
Abstract
To identify novel risk genes and better understand the molecular pathway underlying Alzheimer's disease (AD), whole-exome sequencing was performed in 215 early-onset AD (EOAD) patients and 255 unrelated healthy controls of Han Chinese ethnicity. Subsequent validation, computational annotation and in vitro functional studies were performed to evaluate the role of candidate variants in EOAD. We identified two rare missense variants in the phosphodiesterase 11A (PDE11A) gene in individuals with EOAD. Both variants are located in evolutionarily highly conserved amino acids, are predicted to alter the protein conformation and are classified as pathogenic. Furthermore, we found significantly decreased protein levels of PDE11A in brain samples of AD patients. Expression of PDE11A variants and knockdown experiments with specific short hairpin RNA (shRNA) for PDE11A both resulted in an increase of AD-associated Tau hyperphosphorylation at multiple epitopes in vitro. PDE11A variants or PDE11A shRNA also caused increased cyclic adenosine monophosphate (cAMP) levels, protein kinase A (PKA) activation and cAMP response element-binding protein phosphorylation. In addition, pretreatment with a PKA inhibitor (H89) suppressed PDE11A variant-induced Tau phosphorylation formation. This study offers insight into the involvement of Tau phosphorylation via the cAMP/PKA pathway in EOAD pathogenesis and provides a potential new target for intervention.
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Affiliation(s)
- Wei Qin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Aihong Zhou
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Xiumei Zuo
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Longfei Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Fangyu Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Qi Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Ying Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Yiping Wei
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Hongmei Jin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University, St. Louis, MO 63110, USA
- Department of Genetics, Washington University, St. Louis, MO 63110, USA
| | - Bruno A Benitez
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University, St. Louis, MO 63110, USA
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
- Beijing Key Laboratory of Geriatric Cognitive Disorders, Capital Medical University, Beijing 10053, China
- Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing 10053, China
- Center of Alzheimer’s Disease, Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 10053, China
- To whom correspondence should be addressed at: Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Beijing 100053, P.R. China. Tel: 0086 10 83199449; Fax: 0086 10 83128678; ,
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22
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Patel D, Zhang X, Farrell JJ, Lunetta KL, Farrer LA. Set-Based Rare Variant Expression Quantitative Trait Loci in Blood and Brain from Alzheimer Disease Study Participants. Genes (Basel) 2021; 12:419. [PMID: 33804025 PMCID: PMC7999141 DOI: 10.3390/genes12030419] [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: 02/12/2021] [Revised: 03/04/2021] [Accepted: 03/10/2021] [Indexed: 12/12/2022] Open
Abstract
Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived from blood donated by 713 Alzheimer's Disease Neuroimaging Initiative participants and from brain tissues donated by 475 Religious Orders Study/Memory and Aging Project participants. The association of gene or pathway expression with a set of all cis potentially regulatory low-frequency and rare variants within 1 Mb of genes was evaluated using SKAT-O. A total of 65 genes expressed in the brain were significant targets for rare expression single nucleotide polymorphisms (eSNPs) among which 17% (11/65) included established AD genes HLA-DRB1 and HLA-DRB5. In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, GNMT, LDHC, RBPMS2, DUS2, and HP were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain (n = 9) and blood (n = 16). Pathways for apoptosis signaling, cholecystokinin receptor (CCKR) signaling, and inflammation mediated by chemokine and cytokine signaling were common to both tissues. Significant rare eQTLs in inflammation pathways included five genes in the blood (ALOX5AP, CXCR2, FPR2, GRB2, IFNAR1) that were previously linked to AD. This study identified several significant gene- and pathway-level rare eQTLs, which further confirmed the importance of the immune system and inflammation in AD and highlighted the advantages of using a set-based eQTL approach for evaluating the effect of low-frequency and rare variants on gene expression.
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Affiliation(s)
- Devanshi Patel
- Bioinformatics Graduate Program, Boston University, Boston, MA 02215, USA;
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA; (X.Z.); (J.J.F.)
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA; (X.Z.); (J.J.F.)
| | - John J. Farrell
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA; (X.Z.); (J.J.F.)
| | - Kathryn L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA;
| | - Lindsay A. Farrer
- Bioinformatics Graduate Program, Boston University, Boston, MA 02215, USA;
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA; (X.Z.); (J.J.F.)
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA;
- Department of Ophthalmology, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
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Hoogmartens J, Cacace R, Van Broeckhoven C. Insight into the genetic etiology of Alzheimer's disease: A comprehensive review of the role of rare variants. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12155. [PMID: 33665345 PMCID: PMC7896636 DOI: 10.1002/dad2.12155] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 12/22/2020] [Accepted: 12/29/2020] [Indexed: 12/12/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) is generally known as a dominant disease due to highly penetrant pathogenic mutations in the amyloid precursor protein, presenilin 1 and 2. However, they explain only a fraction of EOAD patients (5% to 10%). Furthermore, only 10% to 15% of EOAD families present with clear autosomal dominant inheritance. Studies showed that only 35% to 60% of EOAD patients have at least one affected first-degree relative. Parent-offspring concordance in EOAD was estimated to be <10%, indicating that full penetrant dominant alleles are not the sole players in EOAD. We aim to summarize current knowledge of rare variants underlying familial and seemingly sporadic Alzheimer's disease (AD) patients. Genetic findings indicate that in addition to the amyloid beta pathway, other pathways are of importance in AD pathophysiology. We discuss the difficulties in interpreting the influence of rare variants on disease onset and we underline the value of carefully selected ethnicity-matched cohorts in AD genetic research.
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Affiliation(s)
- Julie Hoogmartens
- Neurodegenerative Brain DiseasesVIB Center for Molecular NeurologyAntwerpBelgium
- Department of Biomedical SciencesUniversity of AntwerpAntwerpBelgium
| | - Rita Cacace
- Neurodegenerative Brain DiseasesVIB Center for Molecular NeurologyAntwerpBelgium
- Department of Biomedical SciencesUniversity of AntwerpAntwerpBelgium
| | - Christine Van Broeckhoven
- Neurodegenerative Brain DiseasesVIB Center for Molecular NeurologyAntwerpBelgium
- Department of Biomedical SciencesUniversity of AntwerpAntwerpBelgium
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24
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Abstract
The field of cAMP signaling is witnessing exciting developments with the recognition that cAMP is compartmentalized and that spatial regulation of cAMP is critical for faithful signal coding. This realization has changed our understanding of cAMP signaling from a model in which cAMP connects a receptor at the plasma membrane to an intracellular effector in a linear pathway to a model in which cAMP signals propagate within a complex network of alternative branches and the specific functional outcome strictly depends on local regulation of cAMP levels and on selective activation of a limited number of branches within the network. In this review, we cover some of the early studies and summarize more recent evidence supporting the model of compartmentalized cAMP signaling, and we discuss how this knowledge is starting to provide original mechanistic insight into cell physiology and a novel framework for the identification of disease mechanisms that potentially opens new avenues for therapeutic interventions. SIGNIFICANCE STATEMENT: cAMP mediates the intracellular response to multiple hormones and neurotransmitters. Signal fidelity and accurate coordination of a plethora of different cellular functions is achieved via organization of multiprotein signalosomes and cAMP compartmentalization in subcellular nanodomains. Defining the organization and regulation of subcellular cAMP nanocompartments is necessary if we want to understand the complex functional ramifications of pharmacological treatments that target G protein-coupled receptors and for generating a blueprint that can be used to develop precision medicine interventions.
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Affiliation(s)
- Manuela Zaccolo
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Anna Zerio
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Miguel J Lobo
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
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25
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Kunkle BW, Schmidt M, Klein HU, Naj AC, Hamilton-Nelson KL, Larson EB, Evans DA, De Jager PL, Crane PK, Buxbaum JD, Ertekin-Taner N, Barnes LL, Fallin MD, Manly JJ, Go RCP, Obisesan TO, Kamboh MI, Bennett DA, Hall KS, Goate AM, Foroud TM, Martin ER, Wang LS, Byrd GS, Farrer LA, Haines JL, Schellenberg GD, Mayeux R, Pericak-Vance MA, Reitz C. Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel: A Meta-analysis. JAMA Neurol 2021; 78:102-113. [PMID: 33074286 PMCID: PMC7573798 DOI: 10.1001/jamaneurol.2020.3536] [Citation(s) in RCA: 126] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 04/09/2020] [Indexed: 12/11/2022]
Abstract
Importance Compared with non-Hispanic White individuals, African American individuals from the same community are approximately twice as likely to develop Alzheimer disease. Despite this disparity, the largest Alzheimer disease genome-wide association studies to date have been conducted in non-Hispanic White individuals. In the largest association analyses of Alzheimer disease in African American individuals, ABCA7, TREM2, and an intergenic locus at 5q35 were previously implicated. Objective To identify additional risk loci in African American individuals by increasing the sample size and using the African Genome Resource panel. Design, Setting, and Participants This genome-wide association meta-analysis used case-control and family-based data sets from the Alzheimer Disease Genetics Consortium. There were multiple recruitment sites throughout the United States that included individuals with Alzheimer disease and controls of African American ancestry. Analysis began October 2018 and ended September 2019. Main Outcomes and Measures Diagnosis of Alzheimer disease. Results A total of 2784 individuals with Alzheimer disease (1944 female [69.8%]) and 5222 controls (3743 female [71.7%]) were analyzed (mean [SD] age at last evaluation, 74.2 [13.6] years). Associations with 4 novel common loci centered near the intracellular glycoprotein trafficking gene EDEM1 (3p26; P = 8.9 × 10-7), near the immune response gene ALCAM (3q13; P = 9.3 × 10-7), within GPC6 (13q31; P = 4.1 × 10-7), a gene critical for recruitment of glutamatergic receptors to the neuronal membrane, and within VRK3 (19q13.33; P = 3.5 × 10-7), a gene involved in glutamate neurotoxicity, were identified. In addition, several loci associated with rare variants, including a genome-wide significant intergenic locus near IGF1R at 15q26 (P = 1.7 × 10-9) and 6 additional loci with suggestive significance (P ≤ 5 × 10-7) such as API5 at 11p12 (P = 8.8 × 10-8) and RBFOX1 at 16p13 (P = 5.4 × 10-7) were identified. Gene expression data from brain tissue demonstrate association of ALCAM, ARAP1, GPC6, and RBFOX1 with brain β-amyloid load. Of 25 known loci associated with Alzheimer disease in non-Hispanic White individuals, only APOE, ABCA7, TREM2, BIN1, CD2AP, FERMT2, and WWOX were implicated at a nominal significance level or stronger in African American individuals. Pathway analyses strongly support the notion that immunity, lipid processing, and intracellular trafficking pathways underlying Alzheimer disease in African American individuals overlap with those observed in non-Hispanic White individuals. A new pathway emerging from these analyses is the kidney system, suggesting a novel mechanism for Alzheimer disease that needs further exploration. Conclusions and Relevance While the major pathways involved in Alzheimer disease etiology in African American individuals are similar to those in non-Hispanic White individuals, the disease-associated loci within these pathways differ.
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Affiliation(s)
- Brian W. Kunkle
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
- Dr. John T. MacDonald Foundation, Department of Human Genetics, University of Miami, Miami, Florida
| | - Michael Schmidt
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
- Dr. John T. MacDonald Foundation, Department of Human Genetics, University of Miami, Miami, Florida
| | - Hans-Ulrich Klein
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
| | - Adam C. Naj
- Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | | | - Eric B. Larson
- Department of Medicine, University of Washington, Seattle
- Group Health Research Institute, Group Health, Seattle, Washington
| | - Denis A. Evans
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois
| | - Phil L. De Jager
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
| | - Paul K. Crane
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Joe D. Buxbaum
- Department of Psychiatry, Mount Sinai School of Medicine, New York, New York
- Department of Genetics and Genomics Sciences, Mount Sinai School of Medicine, New York, New York
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York
- Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York
| | - Nilufer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
- Department of Neurology, Mayo Clinic, Jacksonville, Florida
| | - Lisa L. Barnes
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
- Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - M. Daniele Fallin
- Department of Epidemiology, Johns Hopkins University School of Public Health, Baltimore, Maryland
| | - Jennifer J. Manly
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
| | - Rodney C. P. Go
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham
| | | | - M. Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania
- Alzheimer’s Disease Research Center, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - David A. Bennett
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Kathleen S. Hall
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis
| | - Alison M. Goate
- Department of Genetics and Genomics Sciences, Mount Sinai School of Medicine, New York, New York
- Department of Neuroscience, Mount Sinai School of Medicine, New York, New York
- Friedman Brain Institute, Mount Sinai School of Medicine, New York, New York
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Tatiana M. Foroud
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis
| | - Eden R. Martin
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
- Dr. John T. MacDonald Foundation, Department of Human Genetics, University of Miami, Miami, Florida
| | - Li-Sao Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Goldie S. Byrd
- Maya Angelou Center for Health Equity, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
- Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | - Jonathan L. Haines
- Department of Population and Quantitative Health Sciences, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio
| | - Gerard D. Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
- Department of Psychiatry, Columbia University, New York, New York
- Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York
| | - Margaret A. Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
- Dr. John T. MacDonald Foundation, Department of Human Genetics, University of Miami, Miami, Florida
| | - Christiane Reitz
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, Columbia University, New York, New York
- Department of Neurology, Columbia University, New York, New York
- Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York
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26
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Rombaut B, Kessels S, Schepers M, Tiane A, Paes D, Solomina Y, Piccart E, Hove DVD, Brône B, Prickaerts J, Vanmierlo T. PDE inhibition in distinct cell types to reclaim the balance of synaptic plasticity. Theranostics 2021; 11:2080-2097. [PMID: 33500712 PMCID: PMC7797685 DOI: 10.7150/thno.50701] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 11/17/2020] [Indexed: 02/06/2023] Open
Abstract
Synapses are the functional units of the brain. They form specific contact points that drive neuronal communication and are highly plastic in their strength, density, and shape. A carefully orchestrated balance between synaptogenesis and synaptic pruning, i.e., the elimination of weak or redundant synapses, ensures adequate synaptic density. An imbalance between these two processes lies at the basis of multiple neuropathologies. Recent evidence has highlighted the importance of glia-neuron interactions in the synaptic unit, emphasized by glial phagocytosis of synapses and local excretion of inflammatory mediators. These findings warrant a closer look into the molecular basis of cell-signaling pathways in the different brain cells that are related to synaptic plasticity. In neurons, intracellular second messengers, such as cyclic guanosine or adenosine monophosphate (cGMP and cAMP, respectively), are known mediators of synaptic homeostasis and plasticity. Increased levels of these second messengers in glial cells slow down inflammation and neurodegenerative processes. These multi-faceted effects provide the opportunity to counteract excessive synapse loss by targeting cGMP and cAMP pathways in multiple cell types. Phosphodiesterases (PDEs) are specialized degraders of these second messengers, rendering them attractive targets to combat the detrimental effects of neurological disorders. Cellular and subcellular compartmentalization of the specific isoforms of PDEs leads to divergent downstream effects for these enzymes in the various central nervous system resident cell types. This review provides a detailed overview on the role of PDEs and their inhibition in the context of glia-neuron interactions in different neuropathologies characterized by synapse loss. In doing so, it provides a framework to support future research towards finding combinational therapy for specific neuropathologies.
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27
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Brookhouser N, Nguyen T, Tekel SJ, Standage-Beier K, Wang X, Brafman DA. A Cas9-mediated adenosine transient reporter enables enrichment of ABE-targeted cells. BMC Biol 2020. [PMID: 33317513 DOI: 10.1186/s12915-020-00929-7.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Adenine base editors (ABE) enable single nucleotide modifications without the need for double-stranded DNA breaks (DSBs) induced by conventional CRIPSR/Cas9-based approaches. However, most approaches that employ ABEs require inefficient downstream technologies to identify desired targeted mutations within large populations of manipulated cells. In this study, we developed a fluorescence-based method, named "Cas9-mediated adenosine transient reporter for editing enrichment" (CasMAs-TREE; herein abbreviated XMAS-TREE), to facilitate the real-time identification of base-edited cell populations. RESULTS To establish a fluorescent-based assay able to detect ABE activity within a cell in real time, we designed a construct encoding a mCherry fluorescent protein followed by a stop codon (TGA) preceding the coding sequence for a green fluorescent protein (GFP), allowing translational readthrough and expression of GFP after A-to-G conversion of the codon to "TGG." At several independent loci, we demonstrate that XMAS-TREE can be used for the highly efficient purification of targeted cells. Moreover, we demonstrate that XMAS-TREE can be employed in the context of multiplexed editing strategies to simultaneous modify several genomic loci. In addition, we employ XMAS-TREE to efficiently edit human pluripotent stem cells (hPSCs), a cell type traditionally resistant to genetic modification. Furthermore, we utilize XMAS-TREE to generate clonal isogenic hPSCs at target sites not editable using well-established reporter of transfection (RoT)-based strategies. CONCLUSION We established a method to detect adenosine base-editing activity within a cell, which increases the efficiency of editing at multiple genomic locations through an enrichment of edited cells. In the future, XMAS-TREE will greatly accelerate the application of ABEs in biomedical research.
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Affiliation(s)
- Nicholas Brookhouser
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA.,Graduate Program in Clinical Translational Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, 85004, USA
| | - Toan Nguyen
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA
| | - Stefan J Tekel
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA
| | - Kylie Standage-Beier
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA.,Molecular and Cellular Biology Graduate Program, Arizona State University, Tempe, AZ, 85287, USA
| | - Xiao Wang
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA.
| | - David A Brafman
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA.
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28
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Brookhouser N, Nguyen T, Tekel SJ, Standage-Beier K, Wang X, Brafman DA. A Cas9-mediated adenosine transient reporter enables enrichment of ABE-targeted cells. BMC Biol 2020; 18:193. [PMID: 33317513 PMCID: PMC7737295 DOI: 10.1186/s12915-020-00929-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 11/18/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Adenine base editors (ABE) enable single nucleotide modifications without the need for double-stranded DNA breaks (DSBs) induced by conventional CRIPSR/Cas9-based approaches. However, most approaches that employ ABEs require inefficient downstream technologies to identify desired targeted mutations within large populations of manipulated cells. In this study, we developed a fluorescence-based method, named "Cas9-mediated adenosine transient reporter for editing enrichment" (CasMAs-TREE; herein abbreviated XMAS-TREE), to facilitate the real-time identification of base-edited cell populations. RESULTS To establish a fluorescent-based assay able to detect ABE activity within a cell in real time, we designed a construct encoding a mCherry fluorescent protein followed by a stop codon (TGA) preceding the coding sequence for a green fluorescent protein (GFP), allowing translational readthrough and expression of GFP after A-to-G conversion of the codon to "TGG." At several independent loci, we demonstrate that XMAS-TREE can be used for the highly efficient purification of targeted cells. Moreover, we demonstrate that XMAS-TREE can be employed in the context of multiplexed editing strategies to simultaneous modify several genomic loci. In addition, we employ XMAS-TREE to efficiently edit human pluripotent stem cells (hPSCs), a cell type traditionally resistant to genetic modification. Furthermore, we utilize XMAS-TREE to generate clonal isogenic hPSCs at target sites not editable using well-established reporter of transfection (RoT)-based strategies. CONCLUSION We established a method to detect adenosine base-editing activity within a cell, which increases the efficiency of editing at multiple genomic locations through an enrichment of edited cells. In the future, XMAS-TREE will greatly accelerate the application of ABEs in biomedical research.
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Affiliation(s)
- Nicholas Brookhouser
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA
- Graduate Program in Clinical Translational Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, 85004, USA
| | - Toan Nguyen
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA
| | - Stefan J Tekel
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA
| | - Kylie Standage-Beier
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA
- Molecular and Cellular Biology Graduate Program, Arizona State University, Tempe, AZ, 85287, USA
| | - Xiao Wang
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA.
| | - David A Brafman
- School of Biological and Health Systems Engineering, Arizona State University, 501 E. Tyler Mall, ECG 334A, Tempe, AZ, 85287, USA.
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29
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Kim YW, Al‐Ramahi I, Koire A, Wilson SJ, Konecki DM, Mota S, Soleimani S, Botas J, Lichtarge O. Harnessing the paradoxical phenotypes of APOE ɛ2 and APOE ɛ4 to identify genetic modifiers in Alzheimer's disease. Alzheimers Dement 2020; 17:831-846. [PMID: 33576571 PMCID: PMC8247413 DOI: 10.1002/alz.12240] [Citation(s) in RCA: 8] [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: 06/29/2020] [Revised: 09/08/2020] [Accepted: 10/22/2020] [Indexed: 01/05/2023]
Abstract
The strongest genetic risk factor for idiopathic late‐onset Alzheimer's disease (LOAD) is apolipoprotein E (APOE) ɛ4, while the APOE ɛ2 allele is protective. However, there are paradoxical APOE ɛ4 carriers who remain disease‐free and APOE ɛ2 carriers with LOAD. We compared exomes of healthy APOE ɛ4 carriers and APOE ɛ2 Alzheimer's disease (AD) patients, prioritizing coding variants based on their predicted functional impact, and identified 216 genes with differential mutational load between these two populations. These candidate genes were significantly dysregulated in LOAD brains, and many modulated tau‐ or β42‐induced neurodegeneration in Drosophila. Variants in these genes were associated with AD risk, even in APOE ɛ3 homozygotes, showing robust predictive power for risk stratification. Network analyses revealed involvement of candidate genes in brain cell type‐specific pathways including synaptic biology, dendritic spine pruning and inflammation. These potential modifiers of LOAD may constitute novel biomarkers, provide potential therapeutic intervention avenues, and support applying this approach as larger whole exome sequencing cohorts become available.
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Affiliation(s)
- Young Won Kim
- Program in Integrative Molecular and Biomedical SciencesBaylor College of MedicineHoustonTexasUSA
| | - Ismael Al‐Ramahi
- Jan and Dan Duncan Neurological Research InstituteHoustonTexasUSA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
| | - Amanda Koire
- Graduate Program in Quantitative and Computational BiosciencesBaylor College of MedicineHoustonTexasUSA
- Medical Scientist Training ProgramBaylor College of MedicineHoustonTexasUSA
| | - Stephen J. Wilson
- Biochemistry and Molecular BiologyBaylor College of MedicineHoustonTexasUSA
| | - Daniel M. Konecki
- Graduate Program in Quantitative and Computational BiosciencesBaylor College of MedicineHoustonTexasUSA
| | - Samantha Mota
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
| | - Shirin Soleimani
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
| | - Juan Botas
- Jan and Dan Duncan Neurological Research InstituteHoustonTexasUSA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
- Graduate Program in Quantitative and Computational BiosciencesBaylor College of MedicineHoustonTexasUSA
| | - Olivier Lichtarge
- Program in Integrative Molecular and Biomedical SciencesBaylor College of MedicineHoustonTexasUSA
- Jan and Dan Duncan Neurological Research InstituteHoustonTexasUSA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
- Graduate Program in Quantitative and Computational BiosciencesBaylor College of MedicineHoustonTexasUSA
- Medical Scientist Training ProgramBaylor College of MedicineHoustonTexasUSA
- Biochemistry and Molecular BiologyBaylor College of MedicineHoustonTexasUSA
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30
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Bis JC, Jian X, Kunkle BW, Chen Y, Hamilton-Nelson KL, Bush WS, Salerno WJ, Lancour D, Ma Y, Renton AE, Marcora E, Farrell JJ, Zhao Y, Qu L, Ahmad S, Amin N, Amouyel P, Beecham GW, Below JE, Campion D, Cantwell L, Charbonnier C, Chung J, Crane PK, Cruchaga C, Cupples LA, Dartigues JF, Debette S, Deleuze JF, Fulton L, Gabriel SB, Genin E, Gibbs RA, Goate A, Grenier-Boley B, Gupta N, Haines JL, Havulinna AS, Helisalmi S, Hiltunen M, Howrigan DP, Ikram MA, Kaprio J, Konrad J, Kuzma A, Lander ES, Lathrop M, Lehtimäki T, Lin H, Mattila K, Mayeux R, Muzny DM, Nasser W, Neale B, Nho K, Nicolas G, Patel D, Pericak-Vance MA, Perola M, Psaty BM, Quenez O, Rajabli F, Redon R, Reitz C, Remes AM, Salomaa V, Sarnowski C, Schmidt H, Schmidt M, Schmidt R, Soininen H, Thornton TA, Tosto G, Tzourio C, van der Lee SJ, van Duijn CM, Valladares O, Vardarajan B, Wang LS, Wang W, Wijsman E, Wilson RK, Witten D, Worley KC, Zhang X, Bellenguez C, Lambert JC, Kurki MI, Palotie A, Daly M, Boerwinkle E, Lunetta KL, Destefano AL, Dupuis J, Martin ER, Schellenberg GD, Seshadri S, Naj AC, Fornage M, Farrer LA. Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation. Mol Psychiatry 2020; 25:1859-1875. [PMID: 30108311 PMCID: PMC6375806 DOI: 10.1038/s41380-018-0112-7] [Citation(s) in RCA: 163] [Impact Index Per Article: 40.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 05/01/2018] [Accepted: 05/14/2018] [Indexed: 12/21/2022]
Abstract
The Alzheimer's Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- and APOE based risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes: IGHG3 (p = 9.8 × 10-7), an immunoglobulin gene whose antibodies interact with β-amyloid, a long non-coding RNA AC099552.4 (p = 1.2 × 10-7), and a zinc-finger protein ZNF655 (gene-based p = 5.0 × 10-6). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.
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Affiliation(s)
- Joshua C Bis
- Department of Medicine (General Internal Medicine), University of Washington, Seattle, WA, USA
| | - Xueqiu Jian
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Brian W Kunkle
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Yuning Chen
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Kara L Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - William S Bush
- Case Western Reserve University, Cleveland Heights, OH, USA
| | - William J Salerno
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Daniel Lancour
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Yiyi Ma
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Alan E Renton
- Department of Neuroscience and Ronald M Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Edoardo Marcora
- Department of Neuroscience and Ronald M Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John J Farrell
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Yi Zhao
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Liming Qu
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Shahzad Ahmad
- Erasmus University Medical Center, Rotterdam, Netherlands
| | - Najaf Amin
- Inserm, U1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Philippe Amouyel
- Inserm, U1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
- Institut Pasteur de Lille, Lille, France
- University Lille, U1167-Excellence Laboratory LabEx DISTALZ, Lille, France
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jennifer E Below
- Department of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dominique Campion
- Department of Genetics and CNR-MAJ, Normandie Université, UNIROUEN, Inserm U1245 and Rouen University Hospital, F 76000, Normandy Centre for Genomic and Personalized Medicine, Rouen, France
- Department of Research, Centre Hospitalier du Rouvray, Sotteville-lès-, Rouen, France
| | - Laura Cantwell
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Camille Charbonnier
- Department of Genetics and CNR-MAJ, Normandie Université, UNIROUEN, Inserm U1245 and Rouen University Hospital, F 76000, Normandy Centre for Genomic and Personalized Medicine, Rouen, France
| | - Jaeyoon Chung
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Paul K Crane
- Department of Medicine (General Internal Medicine), University of Washington, Seattle, WA, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - L Adrienne Cupples
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Jean-François Dartigues
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, F-33000, Bordeaux, France
| | - Stéphanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, F-33000, Bordeaux, France
- Department of Neurology and Institute for Neurodegenerative Diseases, Bordeaux University Hospital, Memory Clinic, F-33000, Bordeaux, France
| | - Jean-François Deleuze
- Centre National de Recherche en Génomique Humaine, Institut François Jacob, Direction de le Recherche Fondamentale, CEA, Evry, France
| | - Lucinda Fulton
- McDonnell Genome Institute, Washington University, St. Louis, MO, USA
| | | | | | - Richard A Gibbs
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Alison Goate
- Department of Neuroscience and Ronald M Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benjamin Grenier-Boley
- Inserm, U1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Aki S Havulinna
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Seppo Helisalmi
- Institute of Clinical Medicine - Neurology and Department of Neurology, University of Eastern Finland, Kuopio, Finland
| | - Mikko Hiltunen
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Daniel P Howrigan
- Program in Medical and Population Genetics and Genetic Analysis Platform, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - M Arfan Ikram
- Erasmus University Medical Center, Rotterdam, Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jan Konrad
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Amanda Kuzma
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mark Lathrop
- McGill University and Génome Québec Innovation Centre, Montréal, Canada
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Honghuang Lin
- Department of Medicine (Computational Biomedicine), Boston University School of Medicine, Boston, MA, USA
| | - Kari Mattila
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | | | - Donna M Muzny
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Waleed Nasser
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Benjamin Neale
- Program in Medical and Population Genetics and Genetic Analysis Platform, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Kwangsik Nho
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Gaël Nicolas
- Department of Genetics and CNR-MAJ, Normandie Université, UNIROUEN, Inserm U1245 and Rouen University Hospital, F 76000, Normandy Centre for Genomic and Personalized Medicine, Rouen, France
| | - Devanshi Patel
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Markus Perola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- University of Tartu, Estonian Genome Center, Tartu, Estonia
| | - Bruce M Psaty
- Department of Medicine (General Internal Medicine), University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Olivier Quenez
- Department of Genetics and CNR-MAJ, Normandie Université, UNIROUEN, Inserm U1245 and Rouen University Hospital, F 76000, Normandy Centre for Genomic and Personalized Medicine, Rouen, France
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Richard Redon
- Inserm, CNRS, Univ. Nantes, CHU Nantes, l'institut du thorax, Nantes, France
| | | | - Anne M Remes
- Institute of Clinical Medicine - Neurology and Department of Neurology, University of Eastern Finland, Kuopio, Finland
- Unit of Clinical Neuroscience, Neurology, University of Oulu and Medical Research Center, Oulu University Hospital, Oulu, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Chloe Sarnowski
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Helena Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University of Graz, Graz, Austria
| | - Michael Schmidt
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University of Graz, Graz, Austria
| | - Hilkka Soininen
- Institute of Clinical Medicine - Neurology and Department of Neurology, University of Eastern Finland, Kuopio, Finland
- Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | | | | | - Christophe Tzourio
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, F-33000, Bordeaux, France
| | | | | | - Otto Valladares
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Li-San Wang
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Weixin Wang
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ellen Wijsman
- Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Richard K Wilson
- McDonnell Genome Institute, Washington University, St. Louis, MO, USA
| | - Daniela Witten
- Department of Statistics, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Kim C Worley
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Xiaoling Zhang
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Celine Bellenguez
- Inserm, U1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Jean-Charles Lambert
- Inserm, U1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
| | - Mitja I Kurki
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics and Genetic Analysis Platform, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics and Genetic Analysis Platform, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Mark Daly
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Eric Boerwinkle
- Human Genome Sequencing Center and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kathryn L Lunetta
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Anita L Destefano
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Departments of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Josée Dupuis
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Eden R Martin
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | | | - Sudha Seshadri
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Departments of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Adam C Naj
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
- School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Lindsay A Farrer
- Departments of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA.
- Departments of Neurology, Boston University School of Medicine, Boston, MA, USA.
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
- Department of Ophthalmology, Boston University School of Medicine, Boston, MA, USA.
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31
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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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32
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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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33
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Misiura MB, Howell JC, Wu J, Qiu D, Parker MW, Turner JA, Hu WT. Race modifies default mode connectivity in Alzheimer's disease. Transl Neurodegener 2020; 9:8. [PMID: 32099645 PMCID: PMC7029517 DOI: 10.1186/s40035-020-0186-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 02/04/2020] [Indexed: 12/11/2022] Open
Abstract
Background Older African Americans are more likely to develop Alzheimer's disease (AD) than older Caucasians, and this difference cannot be readily explained by cerebrovascular and socioeconomic factors alone. We previously showed that mild cognitive impairment and AD dementia were associated with attenuated increases in the cerebrospinal fluid (CSF) levels of total and phosphorylated tau in African Americans compared to Caucasians, even though there was no difference in beta-amyloid 1-42 level between the two races. Methods We extended our work by analyzing early functional magnetic resonance imaging (fMRI) biomarkers of the default mode network in older African Americans and Caucasians. We calculated connectivity between nodes of the regions belonging to the various default mode network subsystems and correlated these imaging biomarkers with non-imaging biomarkers implicated in AD (CSF amyloid, total tau, and cognitive performance). Results We found that race modifies the relationship between functional connectivity of default mode network subsystems and cognitive performance, tau, and amyloid levels. Conclusion These findings provide further support that race modifies the AD phenotypes downstream from cerebral amyloid deposition, and identifies key inter-subsystem connections for deep imaging and neuropathologic characterization.
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Affiliation(s)
- Maria B Misiura
- 1Department of Psychology, Georgia State University, Atlanta, GA USA.,2Departments of Neurology, Emory University, 615 Michael Street, Suite 505, Atlanta, GA 30322 USA
| | - J Christina Howell
- 2Departments of Neurology, Emory University, 615 Michael Street, Suite 505, Atlanta, GA 30322 USA
| | - Junjie Wu
- 3Departments of Radiology, Emory University, Atlanta, GA USA
| | - Deqiang Qiu
- 3Departments of Radiology, Emory University, Atlanta, GA USA
| | - Monica W Parker
- 2Departments of Neurology, Emory University, 615 Michael Street, Suite 505, Atlanta, GA 30322 USA
| | - Jessica A Turner
- 1Department of Psychology, Georgia State University, Atlanta, GA USA
| | - William T Hu
- 2Departments of Neurology, Emory University, 615 Michael Street, Suite 505, Atlanta, GA 30322 USA
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34
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Morris JC, Schindler SE, McCue LM, Moulder KL, Benzinger TLS, Cruchaga C, Fagan AM, Grant E, Gordon BA, Holtzman DM, Xiong C. Assessment of Racial Disparities in Biomarkers for Alzheimer Disease. JAMA Neurol 2020; 76:264-273. [PMID: 30615028 DOI: 10.1001/jamaneurol.2018.4249] [Citation(s) in RCA: 197] [Impact Index Per Article: 49.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Importance Racial differences in molecular biomarkers for Alzheimer disease may suggest race-dependent biological mechanisms. Objective To ascertain whether there are racial disparities in molecular biomarkers for Alzheimer disease. Design, Setting, and Participants A total of 1255 participants (173 African Americans) were enrolled from January 1, 2004, through December 31, 2015, in longitudinal studies at the Knight Alzheimer Disease Research Center at Washington University and completed a magnetic resonance imaging study of the brain and/or positron emission tomography of the brain with Pittsburgh compound B (radioligand for aggregated amyloid-β) and/or cerebrospinal fluid (CSF) assays for the concentrations of amyloid-β42, total tau, and phosphorylated tau181. Independent cross-sectional analyses were conducted from April 22, 2016, to August 27, 2018, for each biomarker modality with an analysis of variance or analysis of covariance including age, sex, educational level, race, apolipoprotein E (APOE) ε4 allele status, and clinical status (normal cognition or dementia). All biomarker assessments were conducted without knowledge of the clinical status of the participants. Main Outcomes and Measures The primary outcomes were hippocampal volumes adjusted for differences in intracranial volumes, global cerebral amyloid burden as transformed into standardized uptake value ratios (partial volume corrected), and CSF concentrations of amyloid-β42, total tau, and phosphorylated tau181. Results Of the 1255 participants (707 women and 548 men; mean [SD] age, 70.8 [9.9] years), 116 of 173 African American participants (67.1%) and 724 of 1082 non-Hispanic white participants (66.9%) had normal cognition. There were no racial differences in the frequency of cerebral ischemic lesions noted on results of brain magnetic resonance imaging, mean cortical standardized uptake value ratios for Pittsburgh compound B, or for amyloid-β42 concentrations in CSF. However, in individuals with a reported family history of dementia, mean (SE) total hippocampal volumes were lower for African American participants than for white participants (6418.26 [138.97] vs 6990.50 [44.10] mm3). Mean (SE) CSF concentrations of total tau were lower in African American participants than in white participants (293.65 [34.61] vs 443.28 [18.20] pg/mL; P < .001), as were mean (SE) concentrations of phosphorylated tau181 (53.18 [4.91] vs 70.73 [2.46] pg/mL; P < .001). There was a significant race by APOE ε4 interaction for both CSF total tau and phosphorylated tau181 such that only APOE ε4-positive participants showed the racial differences. Conclusions and Relevance The results of this study suggest that analyses of molecular biomarkers of Alzheimer disease should adjust for race. The lower CSF concentrations of total tau and phosphorylated tau181 in African American individuals appear to reflect a significant race by APOE ε4 interaction, suggesting a differential effect of this Alzheimer risk variant in African American individuals compared with white individuals.
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Affiliation(s)
- John C Morris
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri
| | - Lena M McCue
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri.,Division of Biostatistics, Washington University School of Medicine, St Louis, Missouri
| | - Krista L Moulder
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri
| | - Tammie L S Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri.,Department of Radiology, Washington University School of Medicine, St Louis, Missouri
| | - Carlos Cruchaga
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri.,Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Anne M Fagan
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri
| | - Elizabeth Grant
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri.,Division of Biostatistics, Washington University School of Medicine, St Louis, Missouri
| | - Brian A Gordon
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri.,Department of Radiology, Washington University School of Medicine, St Louis, Missouri
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri
| | - Chengjie Xiong
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri.,Division of Biostatistics, Washington University School of Medicine, St Louis, Missouri
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35
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Alosco ML, Tripodis Y, Koerte IK, Jackson JD, Chua AS, Mariani M, Haller O, Foley ÉM, Martin BM, Palmisano J, Singh B, Green K, Lepage C, Muehlmann M, Makris N, Cantu RC, Lin AP, Coleman M, Pasternak O, Mez J, Bouix S, Shenton ME, Stern RA. Interactive Effects of Racial Identity and Repetitive Head Impacts on Cognitive Function, Structural MRI-Derived Volumetric Measures, and Cerebrospinal Fluid Tau and Aβ. Front Hum Neurosci 2019; 13:440. [PMID: 31920598 PMCID: PMC6933867 DOI: 10.3389/fnhum.2019.00440] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 12/02/2019] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Factors of increased prevalence among individuals with Black racial identity (e.g., cardiovascular disease, CVD) may influence the association between exposure to repetitive head impacts (RHI) from American football and later-life neurological outcomes. Here, we tested the interaction between racial identity and RHI on neurobehavioral outcomes, brain volumetric measures, and cerebrospinal fluid (CSF) total tau (t-tau), phosphorylated tau (p-tau181), and Aβ1 - 42 in symptomatic former National Football League (NFL) players. METHODS 68 symptomatic male former NFL players (ages 40-69; n = 27 Black, n = 41 White) underwent neuropsychological testing, structural MRI, and lumbar puncture. FreeSurfer derived estimated intracranial volume (eICV), gray matter volume (GMV), white matter volume (WMV), subcortical GMV, hippocampal volume, and white matter (WM) hypointensities. Multivariate generalized linear models examined the main effects of racial identity and its interaction with a cumulative head impact index (CHII) on all outcomes. Age, years of education, Wide Range Achievement Test, Fourth Edition (WRAT-4) scores, CVD risk factors, and APOEε4 were included as covariates; eICV was included for MRI models. P-values were false discovery rate adjusted. RESULTS Compared to White former NFL players, Black participants were 4 years younger (p = 0.04), had lower WRAT-4 scores (mean difference = 8.03, p = 0.002), and a higher BMI (mean difference = 3.09, p = 0.01) and systolic blood pressure (mean difference = 8.15, p = 0.03). With regards to group differences on the basis of racial identity, compared to White former NFL players, Black participants had lower GMV (mean adjusted difference = 45649.00, p = 0.001), lower right hippocampal volume (mean adjusted difference = 271.96, p = 0.02), and higher p-tau181/t-tau ratio (mean adjusted difference = -0.25, p = 0.01). There was not a statistically significant association between the CHII with GMV, right hippocampal volume, or p-tau181/t-tau ratio. However, there was a statistically significant Race x CHII interaction for GMV (b = 2206.29, p = 0.001), right hippocampal volume (b = 12.07, p = 0.04), and p-tau181/t-tau ratio concentrations (b = -0.01, p = 0.004). CONCLUSION Continued research on racial neurological disparities could provide insight into risk factors for long-term neurological disorders associated with American football play.
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Affiliation(s)
- Michael L. Alosco
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - Yorghos Tripodis
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Inga K. Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatic, and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - Jonathan D. Jackson
- CARE Research Center, Massachusetts General Hospital, Boston, MA, United States
| | - Alicia S. Chua
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Megan Mariani
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - Olivia Haller
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - Éimear M. Foley
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
| | - Brett M. Martin
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, United States
| | - Joseph Palmisano
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, United States
| | - Bhupinder Singh
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Katie Green
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Christian Lepage
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Marc Muehlmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Center for Morphometric Analysis, Massachusetts General Hospital, Boston, MA, United States
- Center for Neural Systems Investigations, Massachusetts General Hospital, Boston, MA, United States
| | - Robert C. Cantu
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
- Concussion Legacy Foundation, Boston, MA, United States
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA, United States
- Department of Neurosurgery, Emerson Hospital, Concord, MA, United States
| | - Alexander P. Lin
- Department of Radiology, Center for Clinical Spectroscopy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Michael Coleman
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Jesse Mez
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Brockton, MA, United States
| | - Robert A. Stern
- Boston University Alzheimer’s Disease Center and Boston University CTE Center, Boston University School of Medicine, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA, United States
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
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Cochran JN, McKinley EC, Cochran M, Amaral MD, Moyers BA, Lasseigne BN, Gray DE, Lawlor JMJ, Prokop JW, Geier EG, Holt JM, Thompson ML, Newberry JS, Yokoyama JS, Worthey EA, Geldmacher DS, Love MN, Cooper GM, Myers RM, Roberson ED. Genome sequencing for early-onset or atypical dementia: high diagnostic yield and frequent observation of multiple contributory alleles. Cold Spring Harb Mol Case Stud 2019; 5:mcs.a003491. [PMID: 31836585 PMCID: PMC6913143 DOI: 10.1101/mcs.a003491] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Accepted: 10/25/2019] [Indexed: 12/14/2022] Open
Abstract
We assessed the results of genome sequencing for early-onset dementia. Participants were selected from a memory disorders clinic. Genome sequencing was performed along with C9orf72 repeat expansion testing. All returned sequencing results were Sanger-validated. Prior clinical diagnoses included Alzheimer's disease, frontotemporal dementia, and unspecified dementia. The mean age of onset was 54 (41–76). Fifty percent of patients had a strong family history, 37.5% had some, and 12.5% had no known family history. Nine of 32 patients (28%) had a variant defined as pathogenic or likely pathogenic (P/LP) by American College of Medical Genetics and Genomics standards, including variants in APP, C9orf72, CSF1R, and MAPT. Nine patients (including three with P/LP variants) harbored established risk alleles with moderate penetrance (odds ratios of ∼2–5) in ABCA7, AKAP9, GBA, PLD3, SORL1, and TREM2. All six patients harboring these moderate penetrance variants but not P/LP variants also had one or two APOE ε4 alleles. One patient had two APOE ε4 alleles with no other established contributors. In total, 16 patients (50%) harbored one or more genetic variants likely to explain symptoms. We identified variants of uncertain significance (VUSs) in ABI3, ADAM10, ARSA, GRID2IP, MME, NOTCH3, PLCD1, PSEN1, TM2D3, TNK1, TTC3, and VPS13C, also often along with other variants. In summary, genome sequencing for early-onset dementia frequently identified multiple established or possible contributory alleles. These observations add support for an oligogenic model for early-onset dementia.
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Affiliation(s)
| | - Emily C McKinley
- Alzheimer's Disease Center, Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
| | - Meagan Cochran
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - Michelle D Amaral
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - Bryan A Moyers
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | | | - David E Gray
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - James M J Lawlor
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - Jeremy W Prokop
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA.,Department of Pediatrics and Human Development, Michigan State University, East Lansing, Michigan 48824, USA
| | - Ethan G Geier
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California 94158, USA
| | - James M Holt
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | | | - J Scott Newberry
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - Jennifer S Yokoyama
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, California 94158, USA
| | | | - David S Geldmacher
- Alzheimer's Disease Center, Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
| | - Marissa Natelson Love
- Alzheimer's Disease Center, Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
| | - Gregory M Cooper
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - Erik D Roberson
- Alzheimer's Disease Center, Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
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Carmichael O, Newton R. Brain MRI findings related to Alzheimer's disease in older African American adults. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 165:3-23. [PMID: 31481168 DOI: 10.1016/bs.pmbts.2019.04.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Although a substantial body of research has identified brain MRI measures as important markers of Alzheimer's disease (AD) risk, progression, and treatment response, most of that research has been performed in non-Hispanic white American populations, leading to questions about the utility of the brain MRI measures among individuals of other races or ethnicities. African American individuals in particular are under-represented in AD research, and may exhibit differences in prevalence of AD risk factors, prevalence of AD, incidence of AD, the clinical course of cognitive decline, and AD neuropathology, each of which could influence the utility of brain MRI markers. Unfortunately, while current evidence suggests that African Americans exhibit poorer brain health late in life based on brain MRI measurements, several other aspects of brain MRI markers in this population are unclear, including trajectories of brain MRI markers leading up to old age, relationships between traditional brain health risk factors and brain MRI findings, and the status of brain MRI markers as correlates of cognitive impairment. This unclear state of affairs highlights the urgency of future research in which large numbers of older African American adults contribute longitudinal brain MRI measurements concurrent with clinical, cognitive, and molecular biomarker measurements, ideally in the context of AD preventive or therapeutic trials.
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Affiliation(s)
- Owen Carmichael
- Pennington Biomedical Research Center, Baton Rouge, LA, United States.
| | - Robert Newton
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
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Patel D, Mez J, Vardarajan BN, Staley L, Chung J, Zhang X, Farrell JJ, Rynkiewicz MJ, Cannon-Albright LA, Teerlink CC, Stevens J, Corcoran C, Gonzalez Murcia JD, Lopez OL, Mayeux R, Haines JL, Pericak-Vance MA, Schellenberg G, Kauwe JSK, Lunetta KL, Farrer LA. Association of Rare Coding Mutations With Alzheimer Disease and Other Dementias Among Adults of European Ancestry. JAMA Netw Open 2019; 2:e191350. [PMID: 30924900 PMCID: PMC6450321 DOI: 10.1001/jamanetworkopen.2019.1350] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 02/01/2019] [Indexed: 12/26/2022] Open
Abstract
Importance Some of the unexplained heritability of Alzheimer disease (AD) may be due to rare variants whose effects are not captured in genome-wide association studies because very large samples are needed to observe statistically significant associations. Objective To identify genetic variants associated with AD risk using a nonstatistical approach. Design, Setting, and Participants Genetic association study in which rare variants were identified by whole-exome sequencing in unrelated individuals of European ancestry from the Alzheimer's Disease Sequencing Project (ADSP). Data were analyzed between March 2017 and September 2018. Main Outcomes and Measures Minor alleles genome-wide and in 95 genes previously associated with AD, AD-related traits, or other dementias were tabulated and filtered for predicted functional impact and occurrence in participants with AD but not controls. Support for several findings was sought in a whole-exome sequencing data set comprising 19 affected relative pairs from Utah high-risk pedigrees and whole-genome sequencing data sets from the ADSP and Alzheimer's Disease Neuroimaging Initiative. Results Among 5617 participants with AD (3202 [57.0%] women; mean [SD] age, 76.4 [9.3] years) and 4594 controls (2719 [59.0%] women; mean [SD] age, 86.5 [4.5] years), a total of 24 variants with moderate or high functional impact from 19 genes were observed in 10 or more participants with AD but not in controls. These variants included a missense mutation (rs149307620 [p.A284T], n = 10) in NOTCH3, a gene in which coding mutations are associated with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), that was also identified in 1 participant with AD and 1 participant with mild cognitive impairment in the whole genome sequencing data sets. Four participants with AD carried the TREM2 rs104894002 (p.Q33X) high-impact mutation that, in homozygous form, causes Nasu-Hakola disease, a rare disorder characterized by early-onset dementia and multifocal bone cysts, suggesting an intermediate inheritance model for the mutation. Compared with controls, participants with AD had a significantly higher burden of deleterious rare coding variants in dementia-associated genes (2314 vs 3354 cumulative variants, respectively; P = .006). Conclusions and Relevance Different mutations in the same gene or variable dose of a mutation may be associated with result in distinct dementias. These findings suggest that minor differences in the structure or amount of protein may be associated with in different clinical outcomes. Understanding these genotype-phenotype associations may provide further insight into the pathogenic nature of the mutations, as well as offer clues for developing new therapeutic targets.
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Affiliation(s)
- Devanshi Patel
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
- Bioinformatics Graduate Program, Boston University, Boston, Massachusetts
| | - Jesse Mez
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | | | - Lyndsay Staley
- Department of Biology, Brigham Young University, Provo, Utah
| | - Jaeyoon Chung
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
- Bioinformatics Graduate Program, Boston University, Boston, Massachusetts
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - John J. Farrell
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
| | - Michael J. Rynkiewicz
- Department of Physiology & Biophysics, Boston University School of Medicine, Boston, Massachusetts
| | - Lisa A. Cannon-Albright
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
- Huntsman Cancer Institute, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - Craig C. Teerlink
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - Jeffery Stevens
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | | | | | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Richard Mayeux
- Department of Neurology, Columbia University, New York, New York
| | - Jonathan L. Haines
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida
| | - Gerard Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | | | - Kathryn L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
- Bioinformatics Graduate Program, Boston University, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
- Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
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Benefits and Challenges of Rare Genetic Variation in Alzheimer’s Disease. CURRENT GENETIC MEDICINE REPORTS 2019. [DOI: 10.1007/s40142-019-0161-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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Zhang X, Zhu C, Beecham G, Vardarajan BN, Ma Y, Lancour D, Farrell JJ, Chung J, Mayeux R, Haines JL, Schellenberg GD, Pericak-Vance MA, Lunetta KL, Farrer LA. A rare missense variant of CASP7 is associated with familial late-onset Alzheimer's disease. Alzheimers Dement 2019; 15:441-452. [PMID: 30503768 PMCID: PMC6408965 DOI: 10.1016/j.jalz.2018.10.005] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 10/04/2018] [Accepted: 10/11/2018] [Indexed: 12/21/2022]
Abstract
INTRODUCTION The genetic architecture of Alzheimer's disease (AD) is only partially understood. METHODS We conducted an association study for AD using whole sequence data from 507 genetically enriched AD cases (i.e., cases having close relatives affected by AD) and 4917 cognitively healthy controls of European ancestry (EA) and 172 enriched cases and 179 controls of Caribbean Hispanic ancestry. Confirmation of top findings from stage 1 was sought in two family-based genome-wide association study data sets and in a whole genome-sequencing data set comprising members from 42 EA and 115 Caribbean Hispanic families. RESULTS We identified associations in EAs with variants in 12 novel loci. The most robust finding is a rare CASP7 missense variant (rs116437863; P = 2.44 × 10-10) which improved when combined with results from stage 2 data sets (P = 1.92 × 10-10). DISCUSSION Our study demonstrated that an enriched case design can strengthen genetic signals, thus allowing detection of associations that would otherwise be missed in a traditional case-control study.
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Affiliation(s)
- 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
| | - Congcong Zhu
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Gary Beecham
- Hussman Institute of Human Genetics, University of Miami, Miami, FL, USA
| | | | - Yiyi Ma
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Daniel Lancour
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, 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
| | - Richard Mayeux
- Department of Neurology, Columbia University, New York, NY, USA
| | - Jonathan L Haines
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Lindsay A Farrer
- 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; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Department of 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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Takatori S, Wang W, Iguchi A, Tomita T. Genetic Risk Factors for Alzheimer Disease: Emerging Roles of Microglia in Disease Pathomechanisms. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1118:83-116. [PMID: 30747419 DOI: 10.1007/978-3-030-05542-4_5] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The accumulation of aggregated amyloid β (Aβ) peptides in the brain is deeply involved in Alzheimer disease (AD) pathogenesis. Mutations in APP and presenilins play major roles in Aβ pathology in rare autosomal-dominant forms of AD, whereas pathomechanisms of sporadic AD, accounting for the majority of cases, remain unknown. In this chapter, we review current knowledge on genetic risk factors of AD, clarified by recent advances in genome analysis technology. Interestingly, TREM2 and many genes associated with disease risk are predominantly expressed in microglia, suggesting that these risk factors are involved in pathogenicity through common mechanisms involving microglia. Therefore, we focus on factors closely associated with microglia and discuss their possible roles in pathomechanisms of AD. Furthermore, we review current views on the pathological roles of microglia and emphasize the importance of microglial changes in response to Aβ deposition and mechanisms underlying the phenotypic changes. Importantly, functional outcomes of microglial activation can be both protective and deleterious to neurons. We further describe the involvement of microglia in tau pathology and the activation of other glial cells. Through these topics, we shed light on microglia as a promising target for drug development for AD and other neurological disorders.
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Affiliation(s)
- Sho Takatori
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
| | - Wenbo Wang
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
| | - Akihiro Iguchi
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
| | - Taisuke Tomita
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan.
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García JC, Bustos RH. The Genetic Diagnosis of Neurodegenerative Diseases and Therapeutic Perspectives. Brain Sci 2018; 8:brainsci8120222. [PMID: 30551598 PMCID: PMC6316116 DOI: 10.3390/brainsci8120222] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 11/26/2018] [Accepted: 12/07/2018] [Indexed: 12/12/2022] Open
Abstract
Genetics has led to a new focus regarding approaches to the most prevalent diseases today. Ascertaining the molecular secrets of neurodegenerative diseases will lead to developing drugs that will change natural history, thereby affecting the quality of life and mortality of patients. The sequencing of candidate genes in patients suffering neurodegenerative pathologies is faster, more accurate, and has a lower cost, thereby enabling algorithms to be proposed regarding the risk of neurodegeneration onset in healthy persons including the year of onset and neurodegeneration severity. Next generation sequencing has resulted in an explosion of articles regarding the diagnosis of neurodegenerative diseases involving exome sequencing or sequencing a whole gene for correlating phenotypical expression with genetic mutations in proteins having key functions. Many of them occur in neuronal glia, which can trigger a proinflammatory effect leading to defective proteins causing sporadic or familial mutations. This article reviews the genetic diagnosis techniques and the importance of bioinformatics in interpreting results from neurodegenerative diseases. Risk scores must be established in the near future regarding diseases with a high incidence in healthy people for defining prevention strategies or an early start for giving drugs in the absence of symptoms.
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Affiliation(s)
- Julio-César García
- Evidence-Based Therapeutics Group, Department of Clinical Pharmacology, Universidad de La Sabana, Chía 140013, Colombia.
- Department of Clinical Pharmacology, Clínica Universidad de La Sabana, Chía 140013, Colombia.
| | - Rosa-Helena Bustos
- Evidence-Based Therapeutics Group, Department of Clinical Pharmacology, Universidad de La Sabana, Chía 140013, Colombia.
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Systematic Analysis and Biomarker Study for Alzheimer's Disease. Sci Rep 2018; 8:17394. [PMID: 30478411 PMCID: PMC6255913 DOI: 10.1038/s41598-018-35789-3] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 10/28/2018] [Indexed: 12/31/2022] Open
Abstract
Revealing the relationship between dysfunctional genes in blood and brain tissues from patients with Alzheimer’s Disease (AD) will help us to understand the pathology of this disease. In this study, we conducted the first such large systematic analysis to identify differentially expressed genes (DEGs) in blood samples from 245 AD cases, 143 mild cognitive impairment (MCI) cases, and 182 healthy control subjects, and then compare these with DEGs in brain samples. We evaluated our findings using two independent AD blood datasets and performed a gene-based genome-wide association study to identify potential novel risk genes. We identified 789 and 998 DEGs common to both blood and brain of AD and MCI subjects respectively, over 77% of which had the same regulation directions across tissues and disease status, including the known ABCA7, and the novel TYK2 and TCIRG1. A machine learning classification model containing NDUFA1, MRPL51, and RPL36AL, implicating mitochondrial and ribosomal function, was discovered which discriminated between AD patients and controls with 85.9% of area under the curve and 78.1% accuracy (sensitivity = 77.6%, specificity = 78.9%). Moreover, our findings strongly suggest that mitochondrial dysfunction, NF-κB signalling and iNOS signalling are important dysregulated pathways in AD pathogenesis.
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Single nucleotide polymorphisms alter kinase anchoring and the subcellular targeting of A-kinase anchoring proteins. Proc Natl Acad Sci U S A 2018; 115:E11465-E11474. [PMID: 30455320 DOI: 10.1073/pnas.1816614115] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
A-kinase anchoring proteins (AKAPs) shape second-messenger signaling responses by constraining protein kinase A (PKA) at precise intracellular locations. A defining feature of AKAPs is a helical region that binds to regulatory subunits (RII) of PKA. Mining patient-derived databases has identified 42 nonsynonymous SNPs in the PKA-anchoring helices of five AKAPs. Solid-phase RII binding assays confirmed that 21 of these amino acid substitutions disrupt PKA anchoring. The most deleterious side-chain modifications are situated toward C-termini of AKAP helices. More extensive analysis was conducted on a valine-to-methionine variant in the PKA-anchoring helix of AKAP18. Molecular modeling indicates that additional density provided by methionine at position 282 in the AKAP18γ isoform deflects the pitch of the helical anchoring surface outward by 6.6°. Fluorescence polarization measurements show that this subtle topological change reduces RII-binding affinity 8.8-fold and impairs cAMP responsive potentiation of L-type Ca2+ currents in situ. Live-cell imaging of AKAP18γ V282M-GFP adducts led to the unexpected discovery that loss of PKA anchoring promotes nuclear accumulation of this polymorphic variant. Targeting proceeds via a mechanism whereby association with the PKA holoenzyme masks a polybasic nuclear localization signal on the anchoring protein. This led to the discovery of AKAP18ε: an exclusively nuclear isoform that lacks a PKA-anchoring helix. Enzyme-mediated proximity-proteomics reveal that compartment-selective variants of AKAP18 associate with distinct binding partners. Thus, naturally occurring PKA-anchoring-defective AKAP variants not only perturb dissemination of local second-messenger responses, but also may influence the intracellular distribution of certain AKAP18 isoforms.
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Logue MW, Lancour D, Farrell J, Simkina I, Fallin MD, Lunetta KL, Farrer LA. Targeted Sequencing of Alzheimer Disease Genes in African Americans Implicates Novel Risk Variants. Front Neurosci 2018; 12:592. [PMID: 30210277 PMCID: PMC6119822 DOI: 10.3389/fnins.2018.00592] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Accepted: 08/07/2018] [Indexed: 11/16/2022] Open
Abstract
The genetic architecture of late-onset Alzheimer disease (AD) in African Americans (AAs) differs from that in persons of European ancestry. In addition to APOE, genome-wide association studies (GWASs) of AD in AA samples have implicated ABCA7, COBL, and SLC10A2 as AA-AD risk genes. Previously, we identified by whole exome sequencing a small number of AA AD cases and subsequent genotyping in a large AA sample of AD cases and controls association of AD risk with a pair of rare missense variants in AKAP9. In this study, we performed targeted deep sequencing (including both introns and exons) of approximately 100 genes previously linked to AD or AD-related traits in an AA cohort of 489 AD cases and 472 controls to find novel AD risk variants. We observed association with an 11 base-pair frame-shift loss-of-function (LOF) variant in ABCA7 (rs567222111) for which the evidence was bolstered when combined with data from a replication AA cohort of 484 cases and 484 controls (OR = 2.42, p = 0.022). We also found association of AD with a rare 9 bp deletion (rs371245265) located very close to the AKAP9 transcription start site (rs371245265, OR = 10.75, p = 0.0053). The most significant findings were obtained with a rare protective variant in F5 (OR = 0.053, p = 6.40 × 10-5), a gene that was previously associated with a brain MRI measure of hippocampal atrophy, and two common variants in KIAA0196 (OR = 1.51, p<8.6 × 10-5). Gene-based tests of aggregated rare variants yielded several nominally significant associations with KANSL1, CNN2, and TRIM35. Although no associations passed multiple test correction, our study adds to a body of literature demonstrating the utility of examining sequence data from multiple ethnic populations for discovery of new and impactful risk variants. Larger sample sizes will be needed to generate well-powered epidemiological investigations of rare variation, and functional studies are essential for establishing the pathogenicity of variants identified by sequencing.
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Affiliation(s)
- Mark W Logue
- National Center for Posttraumatic Stress Disorder (PTSD), United States Department of Veterans Affairs, Boston Healthcare System, Boston, MA, United States.,Department of Psychiatry, Boston University School of Medicine, Boston University, Boston, MA, United States.,Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, United States.,Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, MA, United States
| | - Daniel Lancour
- Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, United States
| | - John Farrell
- Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, United States
| | - Irina Simkina
- Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, United States
| | - M Daniele Fallin
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, MA, United States
| | - Lindsay A Farrer
- Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, United States.,Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, MA, United States.,Departments of Neurology and Ophthalmology, Boston University School of Medicine, Boston University, Boston, MA, United States.,Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
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47
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Kumar S, Yadav N, Pandey S, Thelma BK. Advances in the discovery of genetic risk factors for complex forms of neurodegenerative disorders: contemporary approaches, success, challenges and prospects. J Genet 2018. [DOI: 10.1007/s12041-018-0953-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Kumar S, Yadav N, Pandey S, Thelma BK. Advances in the discovery of genetic risk factors for complex forms of neurodegenerative disorders: contemporary approaches, success, challenges and prospects. J Genet 2018; 97:625-648. [PMID: 30027900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Neurodegenerative diseases constitute a large proportion of disorders in elderly, majority being sporadic in occurrence with ∼5-10% familial. A strong genetic component underlies the Mendelian forms but nongenetic factors together with genetic vulnerability contributes to the complex sporadic forms. Several gene discoveries in the familial forms have provided novel insights into the pathogenesis of neurodegeneration with implications for treatment. Conversely, findings from genetic dissection of the sporadic forms, despite large genomewide association studies and more recently whole exome and whole genome sequencing, have been limited. This review provides a concise account of the genetics that we know, the pathways that they implicate, the challenges that are faced and the prospects that are envisaged for the sporadic, complex forms of neurodegenerative diseases, taking four most common conditions, namely Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis and Huntington disease as examples. Poor replication across studies, inability to establish genotype-phenotype correlations and the overall failure to predict risk and/or prevent disease in this group poses a continuing challenge. Among others, clinical heterogeneity emerges as the most important impediment warranting newer approaches. Advanced computational and system biology tools to analyse the big data are being generated and the alternate strategy such as subgrouping of case-control cohorts based on deep phenotyping using the principles of Ayurveda to overcome current limitation of phenotype heterogeneity seem to hold promise. However, at this point, with advances in discovery genomics and functional analysis of putative determinants with translation potential for the complex forms being minimal, stem cell therapies are being attempted as potential interventions. In this context, the possibility to generate patient derived induced pluripotent stem cells, mutant/gene/genome correction through CRISPR/Cas9 technology and repopulating the specific brain regions with corrected neurons, which may fulfil the dream of personalized medicine have been mentioned briefly. Understanding disease pathways/biology using this technology, with implications for development of novel therapeutics are optimistic expectations in the near future.
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Affiliation(s)
- Sumeet Kumar
- Department of Genetics, University of Delhi South Campus, New Delhi 110 021, India.
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Chung J, Wang X, Maruyama T, Ma Y, Zhang X, Mez J, Sherva R, Takeyama H, Lunetta KL, Farrer LA, Jun GR. Genome-wide association study of Alzheimer's disease endophenotypes at prediagnosis stages. Alzheimers Dement 2018; 14:623-633. [PMID: 29274321 PMCID: PMC5938137 DOI: 10.1016/j.jalz.2017.11.006] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 09/25/2017] [Accepted: 11/07/2017] [Indexed: 11/17/2022]
Abstract
INTRODUCTION Genetic associations for endophenotypes of Alzheimer's disease (AD) in cognitive stages preceding AD have not been thoroughly evaluated. METHODS We conducted genome-wide association studies for AD-related endophenotypes including hippocampal volume, logical memory scores, and cerebrospinal fluid Aβ42 and total/phosphorylated tau in cognitively normal (CN), mild cognitive impairment, and AD dementia subjects from the Alzheimer's Disease Neuroimaging Initiative study. RESULTS In CN subjects, study-wide significant (P < 8.3 × 10-9) loci were identified for total tau near SRRM4 and C14orf79 and for hippocampal volume near MTUS1. In mild cognitive impairment subjects, study-wide significant association was found with single nucleotide polymorphisms (SNPs) near ZNF804B for logical memory test of delayed recall scores. We found consistent expression patterns of C14orf40 and MTUS1 in carriers with risk alleles of expression SNPs and in brains of AD patients, compared with in the noncarriers and in brains of controls. DISCUSSION Our findings for AD-related brain changes before AD provide insight about early AD-related biological processes.
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Affiliation(s)
- Jaeyoon Chung
- Bioinformatics Graduate Program, Boston University, Boston, MA, USA; Department of Medicine (Biomedical Genetics), Boston University, Boston, MA, USA
| | - Xulong Wang
- Neurogenetics and Integrated Genomics, Andover Innovative Medicines (AiM) Institute, Eisai Inc, Andover, MA, USA
| | - Toru Maruyama
- Department of Life Science & Medical Bioscience, Waseda University, Tokyo, Japan; Computational Bio-Big Data Open Innovation Lab, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
| | - Yiyi Ma
- Department of Medicine (Biomedical Genetics), Boston University, Boston, MA, USA
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University, Boston, MA, USA
| | - Jesse Mez
- Department of Neurology, Boston University, Boston, MA, USA
| | - Richard Sherva
- Department of Medicine (Biomedical Genetics), Boston University, Boston, MA, USA
| | - Haruko Takeyama
- Department of Life Science & Medical Bioscience, Waseda University, Tokyo, Japan; Computational Bio-Big Data Open Innovation Lab, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan; Research Organization for Nano & Life Innovation, Waseda University, Tokyo, Japan
| | | | - Lindsay A Farrer
- Bioinformatics Graduate Program, Boston University, Boston, MA, USA; Department of Medicine (Biomedical Genetics), Boston University, Boston, MA, USA; Department of Neurology, Boston University, Boston, MA, USA; Department of Biostatistics, Boston University, Boston, MA, USA; Department of Ophthalmology, Boston University, Boston, MA, USA; Department of Epidemiology, Boston University, Boston, MA, USA
| | - Gyungah R Jun
- Department of Medicine (Biomedical Genetics), Boston University, Boston, MA, USA; Neurogenetics and Integrated Genomics, Andover Innovative Medicines (AiM) Institute, Eisai Inc, Andover, MA, USA.
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Freudenberg-Hua Y, Li W, Davies P. The Role of Genetics in Advancing Precision Medicine for Alzheimer's Disease-A Narrative Review. Front Med (Lausanne) 2018; 5:108. [PMID: 29740579 PMCID: PMC5928202 DOI: 10.3389/fmed.2018.00108] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2018] [Accepted: 04/03/2018] [Indexed: 12/12/2022] Open
Abstract
Alzheimer's disease (AD) is the most common type of dementia, which has a substantial genetic component. AD affects predominantly older people. Accordingly, the prevalence of dementia has been rising as the population ages. To date, there are no effective interventions that can cure or halt the progression of AD. The only available treatments are the management of certain symptoms and consequences of dementia. The current state-of-the-art medical care for AD comprises three simple principles: prevent the preventable, achieve early diagnosis, and manage the manageable symptoms. This review provides a summary of the current state of knowledge of risk factors for AD, biological diagnostic testing, and prospects for treatment. Special emphasis is given to recent advances in genetics of AD and the way genomic data may support prevention, early intervention, and development of effective pharmacological treatments. Mutations in the APP, PSEN1, and PSEN2 genes cause early onset Alzheimer's disease (EOAD) that follows a Mendelian inheritance pattern. For late onset Alzheimer's disease (LOAD), APOE4 was identified as a major risk allele more than two decades ago. Population-based genome-wide association studies of late onset AD have now additionally identified common variants at roughly 30 genetic loci. Furthermore, rare variants (allele frequency <1%) that influence the risk for LOAD have been identified in several genes. These genetic advances have broadened our insights into the biological underpinnings of AD. Moreover, the known genetic risk variants could be used to identify presymptomatic individuals at risk for AD and support diagnostic assessment of symptomatic subjects. Genetic knowledge may also facilitate precision medicine. The goal of precision medicine is to use biological knowledge and other health information to predict individual disease risk, understand disease etiology, identify disease subcategories, improve diagnosis, and provide personalized treatment strategies. We discuss the potential role of genetics in advancing precision medicine for AD along with its ethical challenges. We outline strategies to implement genomics into translational clinical research that will not only improve accuracy of dementia diagnosis, thus enabling more personalized treatment strategies, but may also speed up the discovery of novel drugs and interventions.
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Affiliation(s)
- Yun Freudenberg-Hua
- Litwin-Zucker Center for the study of Alzheimer’s Disease, The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, United States
- Division of Geriatric Psychiatry, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, United States
| | - Wentian Li
- Robert S Boas Center for Genomics and Human Genetics, The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Peter Davies
- Litwin-Zucker Center for the study of Alzheimer’s Disease, The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, United States
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