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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 WP, Martin ER, Wang LS, 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. [PMID: 38958117 DOI: 10.1002/alz.13880] [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: 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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Affiliation(s)
- Nicholas R Ray
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Brian W Kunkle
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Kara Hamilton-Nelson
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Jiji T Kurup
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Farid Rajabli
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Min Qiao
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Badri N Vardarajan
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | | | - Caghan Kizil
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Melissa Jean-Francois
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Michael Cuccaro
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Laura Cantwell
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Amanda Kuzma
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Jeffery M Vance
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Sujuan Gao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Hugh C Hendrie
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | | | | | - Wan-Ping Lee
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Eden R Martin
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, University of Miami, Miami, Florida, USA
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Gary W Beecham
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - William S Bush
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Biomedical Research, Cleveland, Ohio, USA
- Department of Population and Quantitative Health Sciences and Cleveland Institute for Computational Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Wanying Xu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Biomedical Research, Cleveland, Ohio, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Biomedical Research, Cleveland, Ohio, USA
- Department of Population and Quantitative Health Sciences and Cleveland Institute for Computational Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Liyong Wang
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Lindsay A Farrer
- Department of Medicine, Biomedical Genetics Section, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Jonathan L Haines
- Department of Population and Quantitative Health Sciences and Cleveland Institute for Computational Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Goldie S Byrd
- Maya Angelou Center for Health Equity, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Gerard D Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, New York, USA
- Department of Neurology, Columbia University, New York, New York, USA
- Department of Psychiatry, Columbia University, New York, New York, USA
- Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Margaret A Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, University of Miami, Miami, Florida, USA
| | - Christiane Reitz
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, New York, USA
- Department of Neurology, Columbia University, New York, New York, USA
- Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York, USA
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Leger BS, Meredith JJ, Ideker T, Sanchez-Roige S, Palmer AA. Rare and common variants associated with alcohol consumption identify a conserved molecular network. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024. [PMID: 39031522 DOI: 10.1111/acer.15399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 06/05/2024] [Accepted: 06/07/2024] [Indexed: 07/22/2024]
Abstract
BACKGROUND Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, genetic studies of alcohol consumption that use rare variants are still in their early stages. No prior studies of alcohol consumption have examined whether common and rare variants implicate the same genes and molecular networks, leaving open the possibility that the two approaches might identify distinct biology. METHODS To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N = 666,978) and whole exome sequencing data (Genebass, N = 393,099) to identify a set of common and rare variants for alcohol consumption. We used gene-based analysis to implicate genes from common and rare variant analyses, which we then propagated onto a shared molecular network using a network colocalization procedure. RESULTS Gene-based analysis of each dataset implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified in only the rare variant analysis, but have been associated with other neuropsychiatric traits. Network colocalization revealed significant network overlap between the genes identified via common and rare variants. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. Seventy-one of the genes in the shared network were previously implicated in neuropsychiatric or substance use disorders but not alcohol-related behaviors (e.g. EXOC2, EPM2A, and CACNG4). Differential gene expression analysis showed enrichment in the liver and several brain regions. CONCLUSIONS Genes implicated by network colocalization identify shared biology relevant to alcohol consumption, which also underlie neuropsychiatric traits and substance use disorders that are comorbid with alcohol use, providing a more holistic understanding of two disparate sources of genetic information.
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Affiliation(s)
- Brittany S Leger
- Program in Biomedical Sciences, University of California San Diego, La Jolla, California, USA
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - John J Meredith
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Trey Ideker
- Department of Medicine, University of California San Diego, La Jolla, California, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
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Gelernter J, Levey DF, Galimberti M, Harrington K, Zhou H, Adhikari K, Gupta P, Gaziano JM, Eliott D, Stein MB. Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations. CELL GENOMICS 2024; 4:100582. [PMID: 38870908 PMCID: PMC11228954 DOI: 10.1016/j.xgen.2024.100582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 02/20/2024] [Accepted: 05/10/2024] [Indexed: 06/15/2024]
Abstract
Epiretinal membrane (ERM) is a common retinal condition characterized by the presence of fibrocellular tissue on the retinal surface, often with visual distortion and loss of visual acuity. We studied European American (EUR), African American (AFR), and Latino (admixed American, AMR) ERM participants in the Million Veteran Program (MVP) for genome-wide association analysis-a total of 38,232 case individuals and 557,988 control individuals. We completed a genome-wide association study (GWAS) in each population separately, and then results were meta-analyzed. Genome-wide significant (GWS) associations were observed in all three populations studied: 31 risk loci in EUR subjects, 3 in AFR, and 2 in AMR, with 48 in trans-ancestry meta-analysis. Many results replicated in the FinnGen sample. Several GWS variants associate to alterations in gene expression in the macula. ERM showed significant genetic correlation to multiple traits. Pathway enrichment analyses implicated collagen and collagen-adjacent mechanisms, among others. This well-powered ERM GWAS identified novel genetic associations that point to biological mechanisms for ERM.
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Affiliation(s)
- Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA; Departments of Genetics and Neuroscience, Yale School of Medicine, New Haven, CT, USA.
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Kelly Harrington
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Keyrun Adhikari
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Priya Gupta
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA; Department of Psychiatry, VA Connecticut Healthcare Center, West Haven, CT, USA
| | - J Michael Gaziano
- Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dean Eliott
- Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, USA
| | - Murray B Stein
- University of California, San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA
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Tesi N, van der Lee S, Hulsman M, van Schoor NM, Huisman M, Pijnenburg Y, van der Flier WM, Reinders M, Holstege H. Cognitively healthy centenarians are genetically protected against Alzheimer's disease. Alzheimers Dement 2024; 20:3864-3875. [PMID: 38634500 PMCID: PMC11180929 DOI: 10.1002/alz.13810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 01/24/2024] [Accepted: 02/26/2024] [Indexed: 04/19/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) prevalence increases with age, yet a small fraction of the population reaches ages > 100 years without cognitive decline. We studied the genetic factors associated with such resilience against AD. METHODS Genome-wide association studies identified 86 single nucleotide polymorphisms (SNPs) associated with AD risk. We estimated SNP frequency in 2281 AD cases, 3165 age-matched controls, and 346 cognitively healthy centenarians. We calculated a polygenic risk score (PRS) for each individual and investigated the functional properties of SNPs enriched/depleted in centenarians. RESULTS Cognitively healthy centenarians were enriched with the protective alleles of the SNPs associated with AD risk. The protective effect concentrated on the alleles in/near ANKH, GRN, TMEM106B, SORT1, PLCG2, RIN3, and APOE genes. This translated to >5-fold lower PRS in centenarians compared to AD cases (P = 7.69 × 10-71), and 2-fold lower compared to age-matched controls (P = 5.83 × 10-17). DISCUSSION Maintaining cognitive health until extreme ages requires complex genetic protection against AD, which concentrates on the genes associated with the endolysosomal and immune systems. HIGHLIGHTS Cognitively healthy cent enarians are enriched with the protective alleles of genetic variants associated with Alzheimer's disease (AD). The protective effect is concentrated on variants involved in the immune and endolysosomal systems. Combining variants into a polygenic risk score (PRS) translated to > 5-fold lower PRS in centenarians compared to AD cases, and ≈ 2-fold lower compared to middle-aged healthy controls.
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Affiliation(s)
- Niccolo’ Tesi
- Delft Bioinformatics LabDelft University of TechnologyDelftThe Netherlands
- Department of Clinical GeneticsSection Genomics of Neurodegenerative Diseases and AgingVrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
| | - Sven van der Lee
- Department of Clinical GeneticsSection Genomics of Neurodegenerative Diseases and AgingVrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
| | - Marc Hulsman
- Delft Bioinformatics LabDelft University of TechnologyDelftThe Netherlands
- Department of Clinical GeneticsSection Genomics of Neurodegenerative Diseases and AgingVrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
| | - Natasja M. van Schoor
- Department of Epidemiology and Data SciencesAmsterdam UMC location Vrije Universiteit AmsterdamAmsterdamThe Netherlands
- Mental Health ProgramAmsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Martijn Huisman
- Department of Epidemiology and Data SciencesAmsterdam UMC location Vrije Universiteit AmsterdamAmsterdamThe Netherlands
- Mental Health ProgramAmsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Yolande Pijnenburg
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
| | - Wiesje M. van der Flier
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
- Department of Epidemiology and Data SciencesAmsterdam UMC location Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Marcel Reinders
- Delft Bioinformatics LabDelft University of TechnologyDelftThe Netherlands
| | - Henne Holstege
- Delft Bioinformatics LabDelft University of TechnologyDelftThe Netherlands
- Department of Clinical GeneticsSection Genomics of Neurodegenerative Diseases and AgingVrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
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Lee S, Hecker J, Hahn G, Mullin K, Lutz SM, Tanzi RE, Lange C, Prokopenko D. On the effect heterogeneity of established disease susceptibility loci for Alzheimer's disease across different genetic ancestries. Alzheimers Dement 2024; 20:3397-3405. [PMID: 38563508 PMCID: PMC11095441 DOI: 10.1002/alz.13796] [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: 11/17/2023] [Revised: 02/14/2024] [Accepted: 02/23/2024] [Indexed: 04/04/2024]
Abstract
INTRODUCTION Genome-wide association studies have identified numerous disease susceptibility loci (DSLs) for Alzheimer's disease (AD). However, only a limited number of studies have investigated the dependence of the genetic effect size of established DSLs on genetic ancestry. METHODS We utilized the whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP) including 35,569 participants. A total of 25,459 subjects in four distinct populations (African ancestry, non-Hispanic White, admixed Hispanic, and Asian) were analyzed. RESULTS We found that nine DSLs showed significant heterogeneity across populations. Single nucleotide polymorphism (SNP) rs2075650 in translocase of outer mitochondrial membrane 40 (TOMM40) showed the largest heterogeneity (Cochran's Q = 0.00, I2 = 90.08), followed by other SNPs in apolipoprotein C1 (APOC1) and apolipoprotein E (APOE). Two additional loci, signal-induced proliferation-associated 1 like 2 (SIPA1L2) and solute carrier 24 member 4 (SLC24A4), showed significant heterogeneity across populations. DISCUSSION We observed substantial heterogeneity for the APOE-harboring 19q13.32 region with TOMM40/APOE/APOC1 genes. The largest risk effect was seen among African Americans, while Asians showed a surprisingly small risk effect.
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Affiliation(s)
- Sanghun Lee
- Department of Medical Consilience, Division of Medicine, Graduate school, Dankook University, Yongin-si, Gyeonggi-do, South Korea
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Julian Hecker
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Georg Hahn
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Kristina Mullin
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Sharon M Lutz
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Christoph Lange
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
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Belloy ME, Guen YL, Stewart I, Herz J, Sherva R, Zhang R, Merritt V, Panizzon MS, Hauger RL, Gaziano JM, Logue M, Napolioni V, Greicius MD. The Role of X Chromosome in Alzheimer's Disease Genetics. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.22.24306094. [PMID: 38712163 PMCID: PMC11071554 DOI: 10.1101/2024.04.22.24306094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Importance The X chromosome has remained enigmatic in Alzheimer's disease (AD), yet it makes up 5% of the genome and carries a high proportion of genes expressed in the brain, making it particularly appealing as a potential source of unexplored genetic variation in AD. Objectives Perform the first large-scale X chromosome-wide association study (XWAS) of AD. Primary analyses are non-stratified, while secondary analyses evaluate sex-stratified effects. Design Meta-analysis of genetic association studies in case-control, family-based, population-based, and longitudinal AD-related cohorts from the US Alzheimer's Disease Genetics Consortium (ADGC) and Alzheimer's Disease Sequencing Project (ADSP), the UK Biobank (UKB), the Finnish health registry (FinnGen), and the US Million Veterans Program (MVP). Risk for AD evaluated through case-control logistic regression analyses. Data were analyzed between January 2023 and March 2024. Setting Genetic data available from high-density single-nucleotide polymorphism (SNP) microarrays and whole-genome sequencing (WGS). Summary statistics for multi-tissue expression and protein quantitative trait loci (QTL) available from published studies, enabling follow-up genetic colocalization analyses. Participants 1,629,863 eligible participants were selected from referred and volunteer samples, of which 477,596 were excluded for analysis exclusion criteria. Number of participants who declined to participate in original studies was not available. Main Outcome and Measures Risk for AD (odds ratio; OR) with 95% confidence intervals (CI). Associations were considered at X-chromosome-wide (P-value<1e-5) and genome-wide (P-value<5e-8) significance. Results Analyses included 1,152,284 non-Hispanic White European ancestry subjects (57.3% females), including 138,558 cases. 6 independent genetic loci passed X-chromosome-wide significance, with 4 showing support for causal links between the genetic signal for AD and expression of nearby genes in brain and non-brain tissues. One of these 4 loci passed conservative genome-wide significance, with its lead variant centered on an intron of SLC9A7 (OR=1.054, 95%-CI=[1.035, 1.075]) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes. Conclusion and Relevance We performed the first large-scale XWAS of AD and identified the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid beta accumulation. Overall, this study significantly advances our knowledge of AD genetics and may provide novel biological drug targets.
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Affiliation(s)
- Michael E. Belloy
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St.Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St.Louis, MO, USA
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Ilaria Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Joachim Herz
- Center for Translational Neurodegeneration Research, Department of Molecular Genetics University of Texas Southwestern Medical Center at Dallas, Dallas, TX, USA
| | - Richard Sherva
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Rui Zhang
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
| | - Victoria Merritt
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Richard L. Hauger
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - J. Michael Gaziano
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Logue
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- 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, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
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7
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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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8
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Gao S, Wang T, Han Z, Hu Y, Zhu P, Xue Y, Huang C, Chen Y, Liu G. Interpretation of 10 years of Alzheimer's disease genetic findings in the perspective of statistical heterogeneity. Brief Bioinform 2024; 25:bbae140. [PMID: 38711368 PMCID: PMC11074593 DOI: 10.1093/bib/bbae140] [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: 08/21/2023] [Revised: 02/22/2024] [Accepted: 03/14/2024] [Indexed: 05/08/2024] Open
Abstract
Common genetic variants and susceptibility loci associated with Alzheimer's disease (AD) have been discovered through large-scale genome-wide association studies (GWAS), GWAS by proxy (GWAX) and meta-analysis of GWAS and GWAX (GWAS+GWAX). However, due to the very low repeatability of AD susceptibility loci and the low heritability of AD, these AD genetic findings have been questioned. We summarize AD genetic findings from the past 10 years and provide a new interpretation of these findings in the context of statistical heterogeneity. We discovered that only 17% of AD risk loci demonstrated reproducibility with a genome-wide significance of P < 5.00E-08 across all AD GWAS and GWAS+GWAX datasets. We highlighted that the AD GWAS+GWAX with the largest sample size failed to identify the most significant signals, the maximum number of genome-wide significant genetic variants or maximum heritability. Additionally, we identified widespread statistical heterogeneity in AD GWAS+GWAX datasets, but not in AD GWAS datasets. We consider that statistical heterogeneity may have attenuated the statistical power in AD GWAS+GWAX and may contribute to explaining the low repeatability (17%) of genome-wide significant AD susceptibility loci and the decreased AD heritability (40-2%) as the sample size increased. Importantly, evidence supports the idea that a decrease in statistical heterogeneity facilitates the identification of genome-wide significant genetic loci and contributes to an increase in AD heritability. Collectively, current AD GWAX and GWAS+GWAX findings should be meticulously assessed and warrant additional investigation, and AD GWAS+GWAX should employ multiple meta-analysis methods, such as random-effects inverse variance-weighted meta-analysis, which is designed specifically for statistical heterogeneity.
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Affiliation(s)
- Shan Gao
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, No. 10, Xitoutiao, You’an Men Wai, Fengtai District, Beijing 100069, China
| | - Tao Wang
- Chinese Institute for Brain Research, No. 26, Kexueyuan Road, Changping District, Beijing 102206, China
| | - Zhifa Han
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, No. 5, Dongdan Santichao, Dongcheng District, Beijing 100193, China
| | - Yang Hu
- School of Computer Science and Technology, Harbin Institute of Technology, No. 92, Xidazhi Street, Nangang District, Harbin 150006, China
| | - Ping Zhu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, No. 10, Xitoutiao, You’an Men Wai, Fengtai District, Beijing 100069, China
| | - Yanli Xue
- School of Biomedical Engineering, Capital Medical University, No. 10 Xitoutiao, You'an Men Wai, Fengtai District, Beijing 100069, China
| | - Chen Huang
- Dr. Neher’s Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida WaiLong, Taipa 999078, Macao SAR, China
| | - Yan Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wannan Medical College, No. 22, Wenchang Road, Wuhu 241002, Anhui, China
- Institute of Chronic Disease Prevention and Control, Wannan Medical College, No. 22, Wenchang Road, Wuhu 241002, Anhui, China
| | - Guiyou Liu
- Chinese Institute for Brain Research, No. 26, Kexueyuan Road, Changping District, Beijing 102206, China
- Department of Epidemiology and Biostatistics, School of Public Health, Wannan Medical College, No. 22, Wenchang Road, Wuhu 241002, Anhui, China
- Institute of Chronic Disease Prevention and Control, Wannan Medical College, No. 22, Wenchang Road, Wuhu 241002, Anhui, China
- Key Laboratory of Cerebral Microcirculation in Universities of Shandong, Department of Neurology, Second Affiliated Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Taian 271000, Shandong, China
- Beijing Key Laboratory of Hypoxia Translational Medicine, National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, No. 45, Changchun Road, Xicheng District, Beijing 100053, China
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9
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Bettencourt C, Skene N, Bandres-Ciga S, Anderson E, Winchester LM, Foote IF, Schwartzentruber J, Botia JA, Nalls M, Singleton A, Schilder BM, Humphrey J, Marzi SJ, Toomey CE, Kleifat AA, Harshfield EL, Garfield V, Sandor C, Keat S, Tamburin S, Frigerio CS, Lourida I, Ranson JM, Llewellyn DJ. Artificial intelligence for dementia genetics and omics. Alzheimers Dement 2023; 19:5905-5921. [PMID: 37606627 PMCID: PMC10841325 DOI: 10.1002/alz.13427] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 08/23/2023]
Abstract
Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. HIGHLIGHTS: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research.
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Affiliation(s)
- Conceicao Bettencourt
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
| | - Nathan Skene
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Emma Anderson
- Department of Mental Health of Older People, Division of Psychiatry, University College London, London, UK
| | | | - Isabelle F Foote
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Jeremy Schwartzentruber
- Open Targets, Cambridge, UK
- Wellcome Sanger Institute, Cambridge, UK
- Illumina Artificial Intelligence Laboratory, Illumina Inc, Foster City, California, USA
| | - Juan A Botia
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | - Mike Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica International LLC, Washington, DC, USA
| | - Andrew Singleton
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Brian M Schilder
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Jack Humphrey
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Sarah J Marzi
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Christina E Toomey
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London, UK
- The Francis Crick Institute, London, UK
| | - Ahmad Al Kleifat
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Eric L Harshfield
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Victoria Garfield
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Cynthia Sandor
- UK Dementia Research Institute. School of Medicine, Cardiff University, Cardiff, UK
| | - Samuel Keat
- UK Dementia Research Institute. School of Medicine, Cardiff University, Cardiff, UK
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, Neurology Section, University of Verona, Verona, Italy
| | - Carlo Sala Frigerio
- UK Dementia Research Institute, Queen Square Institute of Neurology, University College London, London, UK
| | | | | | - David J Llewellyn
- University of Exeter Medical School, Exeter, UK
- The Alan Turing Institute, London, UK
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10
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Godfrey RK, Alsop E, Bjork RT, Chauhan BS, Ruvalcaba HC, Antone J, Gittings LM, Michael AF, Williams C, Hala'ufia G, Blythe AD, Hall M, Sattler R, Van Keuren-Jensen K, Zarnescu DC. Modelling TDP-43 proteinopathy in Drosophila uncovers shared and neuron-specific targets across ALS and FTD relevant circuits. Acta Neuropathol Commun 2023; 11:168. [PMID: 37864255 PMCID: PMC10588218 DOI: 10.1186/s40478-023-01656-0] [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: 08/03/2023] [Accepted: 09/19/2023] [Indexed: 10/22/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) comprise a spectrum of neurodegenerative diseases linked to TDP-43 proteinopathy, which at the cellular level, is characterized by loss of nuclear TDP-43 and accumulation of cytoplasmic TDP-43 inclusions that ultimately cause RNA processing defects including dysregulation of splicing, mRNA transport and translation. Complementing our previous work in motor neurons, here we report a novel model of TDP-43 proteinopathy based on overexpression of TDP-43 in a subset of Drosophila Kenyon cells of the mushroom body (MB), a circuit with structural characteristics reminiscent of vertebrate cortical networks. This model recapitulates several aspects of dementia-relevant pathological features including age-dependent neuronal loss, nuclear depletion and cytoplasmic accumulation of TDP-43, and behavioral deficits in working memory and sleep that occur prior to axonal degeneration. RNA immunoprecipitations identify several candidate mRNA targets of TDP-43 in MBs, some of which are unique to the MB circuit and others that are shared with motor neurons. Among the latter is the glypican Dally-like-protein (Dlp), which exhibits significant TDP-43 associated reduction in expression during aging. Using genetic interactions we show that overexpression of Dlp in MBs mitigates TDP-43 dependent working memory deficits, conistent with Dlp acting as a mediator of TDP-43 toxicity. Substantiating our findings in the fly model, we find that the expression of GPC6 mRNA, a human ortholog of dlp, is specifically altered in neurons exhibiting the molecular signature of TDP-43 pathology in FTD patient brains. These findings suggest that circuit-specific Drosophila models provide a platform for uncovering shared or disease-specific molecular mechanisms and vulnerabilities across the spectrum of TDP-43 proteinopathies.
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Affiliation(s)
- R Keating Godfrey
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA.
- McGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, 3215 Hull Road, Gainesville, FL, 32611, USA.
| | - Eric Alsop
- Translational Genomics Research Institute, 445 N 5th St., Phoenix, AZ, 85004, USA
| | - Reed T Bjork
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Brijesh S Chauhan
- Cellular and Molecular Physiology, Penn State College of Medicine, 500 University Drive Crescent Building C4605, Hershey, PA, 17033, USA
| | - Hillary C Ruvalcaba
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Jerry Antone
- Translational Genomics Research Institute, 445 N 5th St., Phoenix, AZ, 85004, USA
| | - Lauren M Gittings
- Department of Translational Neuroscience, Barrow Neurological Institute, 350 W Thomas Road, Phoenix, AZ, 85013, USA
| | - Allison F Michael
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Christi Williams
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Grace Hala'ufia
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Alexander D Blythe
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Megan Hall
- Translational Genomics Research Institute, 445 N 5th St., Phoenix, AZ, 85004, USA
| | - Rita Sattler
- Department of Translational Neuroscience, Barrow Neurological Institute, 350 W Thomas Road, Phoenix, AZ, 85013, USA
| | | | - Daniela C Zarnescu
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA.
- Cellular and Molecular Physiology, Penn State College of Medicine, 500 University Drive Crescent Building C4605, Hershey, PA, 17033, USA.
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11
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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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12
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Advances in Molecular Psychiatry - March 2023: mitochondrial function, stress, neuroinflammation - bipolar disorder, psychosis, and Alzheimer's disease. Mol Psychiatry 2023; 28:968-971. [PMID: 36899214 DOI: 10.1038/s41380-023-01968-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 03/12/2023]
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13
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Le Guen Y, Raulin AC, Logue MW, Sherva R, Belloy ME, Eger SJ, Chen A, Kennedy G, Kuchenbecker L, O’Leary JP, Zhang R, Merritt VC, Panizzon MS, Hauger RL, Gaziano JM, Bu G, Thornton TA, Farrer LA, Napolioni V, He Z, Greicius MD. Association of African Ancestry-Specific APOE Missense Variant R145C With Risk of Alzheimer Disease. JAMA 2023; 329:551-560. [PMID: 36809323 PMCID: PMC9945061 DOI: 10.1001/jama.2023.0268] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 12/31/2022] [Indexed: 02/23/2023]
Abstract
Importance Numerous studies have established the association of the common APOE ε2 and APOE ε4 alleles with Alzheimer disease (AD) risk across ancestries. Studies of the interaction of these alleles with other amino acid changes on APOE in non-European ancestries are lacking and may improve ancestry-specific risk prediction. Objective To determine whether APOE amino acid changes specific to individuals of African ancestry modulate AD risk. Design, Setting, and Participants Case-control study including 31 929 participants and using a sequenced discovery sample (Alzheimer Disease Sequencing Project; stage 1) followed by 2 microarray imputed data sets derived from the Alzheimer Disease Genetic Consortium (stage 2, internal replication) and the Million Veteran Program (stage 3, external validation). This study combined case-control, family-based, population-based, and longitudinal AD cohorts, which recruited participants (1991-2022) in primarily US-based studies with 1 US/Nigerian study. Across all stages, individuals included in this study were of African ancestry. Exposures Two APOE missense variants (R145C and R150H) were assessed, stratified by APOE genotype. Main Outcomes and Measures The primary outcome was AD case-control status, and secondary outcomes included age at AD onset. Results Stage 1 included 2888 cases (median age, 77 [IQR, 71-83] years; 31.3% male) and 4957 controls (median age, 77 [IQR, 71-83] years; 28.0% male). In stage 2, across multiple cohorts, 1201 cases (median age, 75 [IQR, 69-81] years; 30.8% male) and 2744 controls (median age, 80 [IQR, 75-84] years; 31.4% male) were included. In stage 3, 733 cases (median age, 79.4 [IQR, 73.8-86.5] years; 97.0% male) and 19 406 controls (median age, 71.9 [IQR, 68.4-75.8] years; 94.5% male) were included. In ε3/ε4-stratified analyses of stage 1, R145C was present in 52 individuals with AD (4.8%) and 19 controls (1.5%); R145C was associated with an increased risk of AD (odds ratio [OR], 3.01; 95% CI, 1.87-4.85; P = 6.0 × 10-6) and was associated with a reported younger age at AD onset (β, -5.87 years; 95% CI, -8.35 to -3.4 years; P = 3.4 × 10-6). Association with increased AD risk was replicated in stage 2 (R145C was present in 23 individuals with AD [4.7%] and 21 controls [2.7%]; OR, 2.20; 95% CI, 1.04-4.65; P = .04) and was concordant in stage 3 (R145C was present in 11 individuals with AD [3.8%] and 149 controls [2.7%]; OR, 1.90; 95% CI, 0.99-3.64; P = .051). Association with earlier AD onset was replicated in stage 2 (β, -5.23 years; 95% CI, -9.58 to -0.87 years; P = .02) and stage 3 (β, -10.15 years; 95% CI, -15.66 to -4.64 years; P = 4.0 × 10-4). No significant associations were observed in other APOE strata for R145C or in any APOE strata for R150H. Conclusions and Relevance In this exploratory analysis, the APOE ε3[R145C] missense variant was associated with an increased risk of AD among individuals of African ancestry with the ε3/ε4 genotype. With additional external validation, these findings may inform AD genetic risk assessment in individuals of African ancestry.
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Affiliation(s)
- Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
- Institut du Cerveau–Paris Brain Institute–ICM, Paris, France
| | | | - Mark W. Logue
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, Massachusetts
- Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
- Biomedical Genetics, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Richard Sherva
- Biomedical Genetics, Boston University School of Medicine, Boston, Massachusetts
| | - Michael E. Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
| | - Sarah J. Eger
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
| | - Annabel Chen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
| | - Gabriel Kennedy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
| | | | | | - Rui Zhang
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, Massachusetts
| | - Victoria C. Merritt
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
- Department of Psychiatry, University of California, San Diego, La Jolla
- VA San Diego Healthcare System, San Diego, California
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Richard L. Hauger
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, California
- Department of Psychiatry, University of California, San Diego, La Jolla
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla
| | - J. Michael Gaziano
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston
| | - Guojun Bu
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
| | | | - Lindsay A. Farrer
- Biomedical Genetics, Boston University School of Medicine, Boston, Massachusetts
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
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