1
|
Laureyssen C, Küçükali F, Van Dongen J, Gawor K, Tomé SO, Ronisz A, Otto M, von Arnim CAF, Van Damme P, Vandenberghe R, Thal DR, Sleegers K. Hypothesis-based investigation of known AD risk variants reveals the genetic underpinnings of neuropathological lesions observed in Alzheimer's-type dementia. Acta Neuropathol 2024; 148:55. [PMID: 39424714 PMCID: PMC11489263 DOI: 10.1007/s00401-024-02815-w] [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: 07/16/2024] [Revised: 10/08/2024] [Accepted: 10/08/2024] [Indexed: 10/21/2024]
Abstract
Alzheimer's disease (AD) is the leading cause of dementia worldwide. Besides neurofibrillary tangles and amyloid beta (Aβ) plaques, a wide range of co-morbid neuropathological features can be observed in AD brains. Since AD has a very strong genetic background and displays a wide phenotypic heterogeneity, this study aims at investigating the genetic underpinnings of co-morbid and hallmark neuropathological lesions. This was realized by obtaining the genotypes for 75 AD risk variants from low-coverage whole-genome sequencing data for 325 individuals from the Leuven Brain Collection. Association testing with deeply characterized neuropathological lesions revealed a strong and likely direct effect of rs117618017, a SNP in exon 1 of APH1B, with tau-related pathology. Second, a relation between APOE and granulovacuolar degeneration, a proxy for necroptosis, was also discovered in addition to replication of the well-known association of APOE with AD hallmark neuropathological lesions. Additionally, several nominal associations with AD risk genes were detected for pTDP pathology, α-synuclein lesions and pTau-related pathology. These findings were confirmed in a meta-analysis with three independent cohorts. For example, we replicated a prior association between TPCN1 (rs6489896) and LATE-NC risk. Furthermore, we identified new putative LATE-NC-linked SNPs, including rs7068231, located upstream of ANK3. We found association between BIN1 (rs6733839) and α-synuclein pathology, and replicated a prior association between USP6NL (rs7912495) and Lewy body pathology. Additionally, we also found that UMAD1 (rs6943429) was nominally associated with Lewy body pathology. Overall, these results contribute to a broader general understanding of how AD risk variants discovered in large-scale clinical genome-wide association studies are involved in the pathological mechanisms of AD and indicate the importance of downstream elimination of phenotypic heterogeneity introduced in these studies.
Collapse
Affiliation(s)
- Celeste Laureyssen
- Complex Genetics of Alzheimer's Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Jasper Van Dongen
- Complex Genetics of Alzheimer's Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Klara Gawor
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, KU Leuven, Louvain, Belgium
| | - Sandra O Tomé
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, KU Leuven, Louvain, Belgium
| | - Alicja Ronisz
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, KU Leuven, Louvain, Belgium
| | - Markus Otto
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | | | - Philip Van Damme
- Laboratory for Neurobiology, VIB-KU Leuven, Louvain, Belgium
- Department of Neurology, UZ Leuven, Louvain, Belgium
| | - Rik Vandenberghe
- Department of Neurology, UZ Leuven, Louvain, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven Brain Institute, Louvain, Belgium
| | - Dietmar Rudolf Thal
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, KU Leuven, Louvain, Belgium
- Department of Pathology, University Hospital Leuven, Louvain, Belgium
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium.
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
| |
Collapse
|
2
|
Zhang Y, Wu B, Chen S, Yang L, Deng Y, Guo Y, Wu X, Liu W, Kang J, Feng J, Cheng W, Yu J. Whole exome sequencing analyses identified novel genes for Alzheimer's disease and related dementia. Alzheimers Dement 2024; 20:7062-7078. [PMID: 39129223 PMCID: PMC11485319 DOI: 10.1002/alz.14181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 07/11/2024] [Accepted: 07/16/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION The heritability of Alzheimer's disease (AD) is estimated to be 58%-79%. However, known genes can only partially explain the heritability. METHODS Here, we conducted gene-based exome-wide association study (ExWAS) of rare variants and single-variant ExWAS of common variants, utilizing data of 54,569 clinically diagnosed/proxy AD and related dementia (ADRD) and 295,421 controls from the UK Biobank. RESULTS Gene-based ExWAS identified 11 genes predicting a higher ADRD risk, including five novel ones, namely FRMD8, DDX1, DNMT3L, MORC1, and TGM2, along with six previously reported ones, SORL1, GRN, PSEN1, ABCA7, GBA, and ADAM10. Single-variant ExWAS identified two ADRD-associated novel genes, SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-β process pathways, microglia, and brain regions like hippocampus. The druggability evidence suggests that DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets. DISCUSSION Our study contributes to the current body of evidence on the genetic etiology of ADRD. HIGHLIGHTS Gene-based analyses of rare variants identified five novel genes for Alzheimer's disease and related dementia (ADRD), including FRMD8, DDX1, DNMT3L, MORC1, and TGM2. Single-variant analyses of common variants identified two novel genes for ADRD, including SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-β process pathways, microglia, and brain regions like hippocampus. DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets.
Collapse
Affiliation(s)
- Ya‐Ru Zhang
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Bang‐Sheng Wu
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Shi‐Dong Chen
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Liu Yang
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Yue‐Ting Deng
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Yu Guo
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Xin‐Rui Wu
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Wei‐Shi Liu
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Ju‐Jiao Kang
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired IntelligenceFudan UniversityMinistry of EducationShanghaiChina
| | - Jian‐Feng Feng
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired IntelligenceFudan UniversityMinistry of EducationShanghaiChina
- Fudan ISTBI—ZJNU Algorithm Centre for Brain‐Inspired IntelligenceZhejiang Normal UniversityJinhuaChina
- Department of Computer ScienceUniversity of WarwickCoventryUK
| | - Wei Cheng
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired IntelligenceFudan UniversityMinistry of EducationShanghaiChina
- Fudan ISTBI—ZJNU Algorithm Centre for Brain‐Inspired IntelligenceZhejiang Normal UniversityJinhuaChina
| | - Jin‐Tai Yu
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| |
Collapse
|
3
|
Huq A, Thompson B, Winship I. Clinical application of whole genome sequencing in young onset dementia: challenges and opportunities. Expert Rev Mol Diagn 2024; 24:659-675. [PMID: 39135326 DOI: 10.1080/14737159.2024.2388765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 08/01/2024] [Indexed: 08/30/2024]
Abstract
INTRODUCTION Young onset dementia (YOD) by its nature is difficult to diagnose. Despite involvement of multidisciplinary neurogenetics services, patients with YOD and their families face significant diagnostic delays. Genetic testing for people with YOD currently involves a staggered, iterative approach. There is currently no optimal single genetic investigation that simultaneously identifies the different genetic variants resulting in YOD. AREAS COVERED This review discusses the advances in clinical genomic testing for people with YOD. Whole genome sequencing (WGS) can be employed as a 'one stop shop' genomic test for YOD. In addition to single nucleotide variants, WGS can reliably detect structural variants, short tandem repeat expansions, mitochondrial genetic variants as well as capture single nucleotide polymorphisms for the calculation of polygenic risk scores. EXPERT OPINION WGS, when used as the initial genetic test, can enhance the likelihood of a precision diagnosis and curtail the time taken to reach this. Finding a clinical diagnosis using WGS can reduce invasive and expensive investigations and could be cost effective. These advances need to be balanced against the limitations of the technology and the genetic counseling needs for these vulnerable patients and their families.
Collapse
Affiliation(s)
- Aamira Huq
- Department of Genomic Medicine, Royal Melbourne Hospital, Parkville, Victoria, Australia
- Department of Medicine, University of Melbourne, Parkville, Victoria, Australia
| | - Bryony Thompson
- Department of Medicine, Royal Melbourne Hospital, Parkville, Victoria, Australia
- Department of Pathology, University of Melbourne, Parkville, Victoria, Australia
| | - Ingrid Winship
- Department of Genomic Medicine, Royal Melbourne Hospital, Parkville, Victoria, Australia
- Department of Medicine, University of Melbourne, Parkville, Victoria, Australia
| |
Collapse
|
4
|
Zeng B, Bendl J, Kosoy R, Fullard JF, Hoffman GE, Roussos P. Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits. Nat Genet 2022; 54:161-169. [PMID: 35058635 PMCID: PMC8852232 DOI: 10.1038/s41588-021-00987-9] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 11/17/2021] [Indexed: 12/11/2022]
Abstract
While large-scale, genome-wide association studies (GWAS) have identified hundreds of loci associated with brain-related traits, identification of the variants, genes and molecular mechanisms underlying these traits remains challenging. Integration of GWAS with expression quantitative trait loci (eQTLs) and identification of shared genetic architecture have been widely adopted to nominate genes and candidate causal variants. However, this approach is limited by sample size, statistical power and linkage disequilibrium. We developed the multivariate multiple QTL approach and performed a large-scale, multi-ancestry eQTL meta-analysis to increase power and fine-mapping resolution. Analysis of 3,983 RNA-sequenced samples from 2,119 donors, including 474 non-European individuals, yielded an effective sample size of 3,154. Joint statistical fine-mapping of eQTL and GWAS identified 329 variant-trait pairs for 24 brain-related traits driven by 204 unique candidate causal variants for 189 unique genes. This integrative analysis identifies candidate causal variants and elucidates potential regulatory mechanisms for genes underlying schizophrenia, bipolar disorder and Alzheimer's disease.
Collapse
Affiliation(s)
- Biao Zeng
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Roman Kosoy
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, NY, USA.
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
| |
Collapse
|
5
|
Cai R, Wang Y, Huang Z, Zou Q, Pu Y, Yu C, Cai Z. Role of RhoA/ROCK signaling in Alzheimer's disease. Behav Brain Res 2021; 414:113481. [PMID: 34302876 DOI: 10.1016/j.bbr.2021.113481] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 06/22/2021] [Accepted: 07/17/2021] [Indexed: 12/11/2022]
Abstract
Rho-associated coiled-coil kinase (ROCK), a serine/threonine kinase regulated by the small GTPase RhoA, is involved in regulating cell migration, proliferation, and survival. Numerous studies have shown that the RhoA/ROCK signaling pathway can promote Alzheimer's disease (AD) occurrence. ROCK activation increases β-secretase activity and promotes amyloid-beta (Aβ) production; moreover, Aβ further activates ROCK. This is suggestive of a possible positive feedback role for Aβ and ROCK. Moreover, ROCK activation promotes the formation of neurofibrillary tangles and abnormal synaptic contraction. Additionally, ROCK activation can promote the neuroinflammatory response by activating microglia and astrocytes to release inflammatory cytokines. Therefore, ROCK is a promising drug target in AD; further, there is a need to elucidate the specific mechanism of action.
Collapse
Affiliation(s)
- RuoLan Cai
- Zunyi Medical University, Zunyi, 563003, China; Department of Neurology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China; Chongqing Key Laboratory of Neurodegenerative Diseases, Chongqing, 400013, China; Department of Neurology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, 400013, China
| | - YangYang Wang
- Chongqing Key Laboratory of Neurodegenerative Diseases, Chongqing, 400013, China; Department of Neurology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, 400013, China
| | - ZhenTing Huang
- Chongqing Key Laboratory of Neurodegenerative Diseases, Chongqing, 400013, China; Department of Neurology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, 400013, China
| | - Qian Zou
- Chongqing Key Laboratory of Neurodegenerative Diseases, Chongqing, 400013, China; Department of Neurology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, 400013, China
| | - YinShuang Pu
- Chongqing Key Laboratory of Neurodegenerative Diseases, Chongqing, 400013, China; Department of Neurology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, 400013, China
| | - Changyin Yu
- Department of Neurology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, China.
| | - Zhiyou Cai
- Chongqing Key Laboratory of Neurodegenerative Diseases, Chongqing, 400013, China; Department of Neurology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, 400013, China.
| |
Collapse
|
6
|
Zhang X, Zhang CM, Prokopenko D, Liang Y, Zhen SY, Weigle IQ, Han W, Aryal M, Tanzi RE, Sisodia SS. An APP ectodomain mutation outside of the Aβ domain promotes Aβ production in vitro and deposition in vivo. J Exp Med 2021; 218:211936. [PMID: 33822840 PMCID: PMC8034382 DOI: 10.1084/jem.20210313] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 03/03/2021] [Accepted: 03/03/2021] [Indexed: 12/28/2022] Open
Abstract
Familial Alzheimer’s disease (FAD)–linked mutations in the APP gene occur either within the Aβ-coding region or immediately proximal and are located in exons 16 and 17, which encode Aβ peptides. We have identified an extremely rare, partially penetrant, single nucleotide variant (SNV), rs145081708, in APP that corresponds to a Ser198Pro substitution in exon 5. We now report that in stably transfected cells, expression of APP harboring the S198P mutation (APPS198P) leads to elevated production of Aβ peptides by an unconventional mechanism in which the folding and exit of APPS198P from the endoplasmic reticulum is accelerated. More importantly, coexpression of APP S198P and the FAD-linked PS1ΔE9 variant in the brains of male and female transgenic mice leads to elevated steady-state Aβ peptide levels and acceleration of Aβ deposition compared with age- and gender-matched mice expressing APP and PS1ΔE9. This is the first AD-linked mutation in APP present outside of exons 16 and 17 that enhances Aβ production and deposition.
Collapse
Affiliation(s)
- Xulun Zhang
- Department of Neurobiology, University of Chicago, Chicago, IL
| | - Can Martin Zhang
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | - Dmitry Prokopenko
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | - Yingxia Liang
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | - Sherri Y Zhen
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | - Ian Q Weigle
- Department of Neurobiology, University of Chicago, Chicago, IL
| | - Weinong Han
- Department of Neurobiology, University of Chicago, Chicago, IL
| | - Manish Aryal
- Department of Neurobiology, University of Chicago, Chicago, IL
| | - Rudolph E Tanzi
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | | |
Collapse
|
7
|
Schwartzentruber J, Cooper S, Liu JZ, Barrio-Hernandez I, Bello E, Kumasaka N, Young AMH, Franklin RJM, Johnson T, Estrada K, Gaffney DJ, Beltrao P, Bassett A. Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes. Nat Genet 2021; 53:392-402. [PMID: 33589840 PMCID: PMC7610386 DOI: 10.1038/s41588-020-00776-w] [Citation(s) in RCA: 318] [Impact Index Per Article: 79.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 12/23/2020] [Indexed: 01/30/2023]
Abstract
Genome-wide association studies have discovered numerous genomic loci associated with Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with >50% probability each of being causally involved in AD risk and others strongly suggested by functional annotation. We followed this with colocalization analyses across 109 gene expression quantitative trait loci datasets and prioritization of genes by using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we found that evidence converged on likely causal genes, including the above four genes, and those at previously discovered AD loci, including BIN1, APH1B, PTK2B, PILRA and CASS4.
Collapse
Affiliation(s)
- Jeremy Schwartzentruber
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK.
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
| | - Sarah Cooper
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Inigo Barrio-Hernandez
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
- Open Targets, Wellcome Genome Campus, Cambridge, UK
| | - Erica Bello
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | | | - Adam M H Young
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Robin J M Franklin
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Toby Johnson
- Target Sciences-R&D, GSK Medicines Research Centre, Stevenage, UK
| | | | - Daniel J Gaffney
- Open Targets, Wellcome Genome Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
- Genomics Plc, Oxford, UK
| | - Pedro Beltrao
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
- Open Targets, Wellcome Genome Campus, Cambridge, UK
| | - Andrew Bassett
- Open Targets, Wellcome Genome Campus, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
| |
Collapse
|