Functional genomics identify causal variant underlying the protective CTSH locus for Alzheimer’s disease
Open accessAbstract
Alzheimer's disease (AD) is the most prevalent age-related neurodegenerative disease, which has a high heritability of up to 79%. Exploring the genetic basis is essential for understanding the pathogenic mechanisms underlying AD development. Recent genome-wide association studies (GWASs) reported an AD-associated signal in the Cathepsin H (CTSH) gene in European populations. However, the exact functional/causal variant(s), and the genetic regulating mechanism of CTSH in AD remain to be determined. In this study, we carried out a comprehensive study to characterize the role of CTSH variants in the pathogenesis of AD. We identified rs2289702 in CTSH as the most significant functional variant that is associated with a protective effect against AD. The genetic association between rs2289702 and AD was validated in independent cohorts of the Han Chinese population. The CTSH mRNA expression level was significantly increased in AD patients and AD animal models, and the protective allele T of rs2289702 was associated with a decreased expression level of CTSH through the disruption of the binding affinity of transcription factors. Human microglia cells with CTSH knockout showed a significantly increased phagocytosis of Aβ peptides. Our study identified CTSH as being involved in AD genetic susceptibility and uncovered the genetic regulating mechanism of CTSH in pathogenesis of AD.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Increased CTSH mRNA levels were observed in AD, while microglia with CTSH knockouts showed increased Aβ phagocytosis.
“Increased CTSH mRNA levels were observed in AD, while microglia with CTSH knockouts showed increased Aβ phagocytosis75.”
From Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for Alzheimer’s disease (2024) · cites this paper as [75]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
The Cellular Phase of Alzheimer’s Disease
De Strooper, B., & Karran, E. (2016) · Cell · doi:10.1016/j.cell.2015.12.056 · Cited by 1,990 · see citing works
Grubman, A., Chew, G., Ouyang, J. F., Sun, G., Choo, X. Y., McLean, C., Simmons, R. K., Buckberry, S., Vargas-Landin, D. B., Poppe, D., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0539-4 · Cited by 956 · see citing works
Brain cell type–specific enhancer–promoter interactome maps and disease <b>-</b> risk association
Nott, A., Holtman, I. R., Coufal, N. G., Schlachetzki, J. C. M., Yu, M., Hu, R., Han, C. Z., Pena, M., Xiao, J., Wu, Y., et al. (2019) · Science · doi:10.1126/science.aay0793 · Cited by 823 · see citing works
Correction of a genetic disease in mouse via use of CRISPR-Cas9
Wu, Y., Liang, D., Wang, Y., Bai, M., Tang, W., Bao, S., Yan, Z., Li, D., & Li, J. (2013) · Cell stem cell · doi:10.1016/j.stem.2013.10.016 · Cited by 614 · cited 1× · see citing works
“After three further washes, the membranes were visualized using the ECL reagents (MilliporeSigma, WBKLS0500).”
MethodHeckmann, B. L., Teubner, B. J. W., Tummers, B., Boada-Romero, E., Harris, L., Yang, M., Guy, C. S., Zakharenko, S. S., & Green, D. R. (2019) · Cell · doi:10.1016/j.cell.2019.05.056 · Cited by 503 · see citing works
Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses
Wallace, C. (2020) · PLOS Genetics · doi:10.1371/journal.pgen.1008720 · Cited by 441 · see citing works
Nativio, R., Lan, Y., Donahue, G., Sidoli, S., Berson, A., Srinivasan, A. R., Shcherbakova, O., Amlie-Wolf, A., Nie, J., Cui, X., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0696-0 · Cited by 380 · see citing works
Enhancer variants associated with Alzheimer’s disease affect gene expression via chromatin looping
Kikuchi, M., Hara, N., Hasegawa, M., Miyashita, A., Kuwano, R., Ikeuchi, T., & Nakaya, A. (2019) · BMC Medical Genomics · doi:10.1186/s12920-019-0574-8 · Cited by 74 · cited 1× · see citing works
“The fi rst cohort included 221 AD patients with an early age at onset (age ≤ 55) and/or an AD familial history (FOAD), in which 169 individuals had been reported in our previous studies [15, 41].”
Flagged first, then by citations
Research works printed but not linked: 84
- Querfurth HW, LaFerla FM. Alzheimer's disease. N Engl J Med. 2010;362:329-44.
- Guo T, Zhang D, Zeng Y, Huang TY, Xu H, Zhao Y. Molecular and cellular mechanisms underlying the pathogenesis of Alzheimer's disease. Mol Neurode- gener. 2020;15:40.
- Karch CM, Goate AM. Alzheimer's disease risk genes and mechanisms of disease pathogenesis. Biol Psychiatry. 2015;77:43-51.
- Bertram L, Lill CM, Tanzi RE. The genetics of Alzheimer disease: back to the future. Neuron. 2010;68:270-81.
- Zhang DF, Xu M, Bi R, Yao YG. Genetic analyses of Alzheimer's disease in China: achievements and perspectives. ACS Chem Neurosci. 2019;10:890-901.
- Gatz M, Reynolds CA, Fratiglioni L, Johansson B, Mortimer JA, Berg S, et al. Role of genes and environments for explaining Alzheimer disease. Arch Gen Psychiatry. 2006;63:168-74.
- Bellenguez C, Kucukali F, Jansen IE, Kleineidam L, Moreno-Grau S, Amin N, et al. New insights into the genetic etiology of Alzheimer's disease and related dementias. Nat Genet. 2022;54:412-36.
- Wingo AP, Liu Y, Gerasimov ES, Gockley J, Logsdon BA, Duong DM, et al. Inte- grating human brain proteomes with genome-wide association data implicates new proteins in Alzheimer's disease pathogenesis. Nat Genet. 2021;53:143-6.
- Jia L, Li F, Wei C, Zhu M, Qu Q, Qin W, et al. Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study. Brain. 2021;144:924-37.
- Jiao B, Xiao X, Yuan Z, Guo L, Liao X, Zhou Y, et al. Associations of risk genes with onset age and plasma biomarkers of Alzheimer's disease: a large case-control study in mainland China. Neuropsychopharmacology. 2022;47:1121-7.
- Wang HZ, Bi R, Hu QX, Xiang Q, Zhang C, Zhang DF, et al. Validating GWAS identified risk loci for Alzheimer's disease in Han Chinese populations. Mol Neurobiol. 2016;53:379-90.
- Tan L, Yu JT, Zhang W, Wu ZC, Zhang Q, Liu QY, et al. Association of GWAS-linked loci with late-onset Alzheimer's disease in a northern Han Chinese population. Alzheimers Dement. 2013;9:546-53.
- Bi R, Zhang W, Zhang DF, Xu M, Fan Y, Hu QX, et al. Genetic association of the cytochrome c oxidase-related genes with Alzheimer's disease in Han Chinese. Neuropsychopharmacology. 2018;43:2264-76.
- Zhang DF, Fan Y, Xu M, Wang G, Wang D, Li J, et al. Complement C7 is a novel risk gene for Alzheimer's disease in Han Chinese. Natl Sci Rev. 2019;6:257-74.
- Luo R, Fan Y, Yang J, Ye M, Zhang DF, Guo K, et al. A novel missense variant in ACAA1 contributes to early-onset Alzheimer's disease, impairs lysosomal func- tion, and facilitates amyloid-β pathology and cognitive decline. Signal Transduct Target Ther. 2021;6:325.
- Liao X, Cai F, Sun Z, Zhang Y, Wang J, Jiao B, et al. Identification of Alzheimer's disease-associated rare coding variants in the ECE2 gene. JCI Insight. 2020; 5:135119.
- Khaire AS, Wimberly CE, Semmes EC, Hurst JH, Walsh KM. An integrated genome and phenome-wide association study approach to understanding Alzheimer's disease predisposition. Neurobiol Aging. 2022;118:117-23.
- Campion D, Pottier C, Nicolas G, Le Guennec K, Rovelet-Lecrux A. Alzheimer disease: modeling an Aβ-centered biological network. Mol Psychiatry. 2016;21: 861-71.
- Johnson ECB, Dammer EB, Duong DM, Ping L, Zhou M, Yin L, et al. Large-scale proteomic analysis of Alzheimer's disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation. Nat Med. 2020;26:769-80.
- Corces MR, Shcherbina A, Kundu S, Gloudemans MJ, Fresard L, Granja JM, et al. Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer's and Parkinson's diseases. Nat Genet. 2020;52:1158-68.
- Wingo AP, Fan W, Duong DM, Gerasimov ES, Dammer EB, Liu Y, et al. Shared proteomic effects of cerebral atherosclerosis and Alzheimer's disease on the human brain. Nat Neurosci. 2020;23:696-700.
- Ioannidis JP, Thomas G, Daly MJ. Validating, augmenting and refining genome- wide association signals. Nat Rev Genet. 2009;10:318-29.
- Gallagher MD, Chen-Plotkin AS. The post-GWAS era: from association to function. Am J Hum Genet. 2018;102:717-30.
- Cannon ME, Mohlke KL. Deciphering the emerging complexities of molecular mechanisms at GWAS Loci. Am J Hum Genet. 2018;103:637-53.
- Kumasaka N, Knights AJ, Gaffney DJ. High-resolution genetic mapping of putative causal interactions between regions of open chromatin. Nat Genet. 2019;51: 128-37.
- Iotchkova V, Ritchie GRS, Geihs M, Morganella S, Min JL, Walter K, et al. GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals. Nat Genet. 2019;51:343-53.
- Rojnik M, Jevnikar ZR, Doljak B, Turk S, Zidar N, Kos J. The influence of differential processing of procathepsin H on its aminopeptidase activity, secretion and subcellular localization in human cell lines. Eur J Cell Biol. 2012;91:757-64.
- Ruiz-Blazquez P, Pistorio V, Fernandez-Fernandez M, Moles A. The multifaceted role of cathepsins in liver disease. J Hepatol. 2021;75:1192-202.
- Ou YN, Yang YX, Deng YT, Zhang C, Hu H, Wu BS, et al. Identification of novel drug targets for Alzheimer's disease by integrating genetics and proteomes from brain and blood. Mol Psychiatry. 2021;26:6065-73.
- Kibinge NK, Relton CL, Gaunt TR, Richardson TG. Characterizing the causal pathway for genetic variants associated with neurological phenotypes using human brain-derived proteome data. Am J Hum Genet. 2020;106:885-92.
- Jansen IE, Savage JE, Watanabe K, Bryois J, Williams DM, Steinberg S, et al. Genome-wide meta-analysis identifies new loci and functional pathways influ- encing Alzheimer's disease risk. Nat Genet. 2019;51:404-13.
- Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010;26:2336-7.
- The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature. 2015;526:68-74.
- Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263-5.
- Consortium GT. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45:580-5.
- Wang G, Zhang DF, Jiang HY, Fan Y, Ma L, Shen Z, et al. Mutation and association analyses of dementia-causal genes in Han Chinese patients with early-onset and familial Alzheimer's disease. J Psychiatr Res. 2019;113:141-7.
- Wang D, Fan Y, Malhi M, Bi R, Wu Y, Xu M, et al. Missense variants in HIF1A and LACC1 contribute to leprosy risk in Han Chinese. Am J Hum Genet. 2018;102: 794-805.
- Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536:285-91.
- Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genome- wide association scans. Bioinformatics. 2010;26:2190-1.
- Xu M, Liu Q, Bi R, Li Y, Zeng C, Yan Z, et al. A multiple-causal-gene-cluster model underlying GWAS signals of Alzheimer's disease. bioRxiv. 2021;https://doi.org/ 10.1101/2021.05.14.444131. · DOI
- Encode Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57-74.
- Davis CA, Hitz BC, Sloan CA, Chan ET, Davidson JM, Gabdank I, et al. The Ency- clopedia of DNA elements (ENCODE): data portal update. Nucleic Acids Res. 2018;46:D794-D801.
- Song M, Yang X, Ren X, Maliskova L, Li B, Jones IR, et al. Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes. Nat Genet. 2019;51:1252-62.
- Fullard JF, Hauberg ME, Bendl J, Egervari G, Cirnaru MD, Reach SM, et al. An atlas of chromatin accessibility in the adult human brain. Genome Res. 2018;28: 1243-52.
- Novakovic B, Habibi E, Wang SY, Arts RJW, Davar R, Megchelenbrink W, et al. β- Glucan reverses the epigenetic state of LPS-induced immunological tolerance. Cell. 2016;167:1354-68.e14.
- Bailey TL, Elkan C. Fitting a mixture model by expectation maximization to dis- cover motifs in biopolymers. Proc Int Conf Intell Syst Mol Biol. 1994;2:28-36.
- Zuo C, Shin S, Keles S. atSNP: transcription factor binding affinity testing for regulatory SNP detection. Bioinformatics. 2015;31:3353-5.
- Consortium GT, Laboratory DA, Coordinating Center -Analysis Working G, Statistical Methods groups-Analysis Working G, Enhancing Gg, Fund NIHC. et al. Genetic effects on gene expression across human tissues. Nature. 2017;550:204-13.
- Consortium GT. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348:648-60.
- Mathys H, Davila-Velderrain J, Peng Z, Gao F, Mohammadi S, Young JZ, et al. Single-cell transcriptomic analysis of Alzheimer's disease. Nature. 2019;570:332-7.
- Xu M, Zhang DF, Luo R, Wu Y, Zhou H, Kong LL, et al. A systematic integrated analysis of brain expression profiles reveals YAP1 and other prioritized hub genes as important upstream regulators in Alzheimer's disease. Alzheimers Dement. 2018;14:215-29.
- Matarin M, Salih DA, Yasvoina M, Cummings DM, Guelfi S, Liu W, et al. A genome- wide gene-expression analysis and database in transgenic mice during development of amyloid or tau pathology. Cell Rep. 2015;10:633-44.
- Ran FA, Hsu PD, Wright J, Agarwala V, Scott DA, Zhang F. Genome engineering using the CRISPR-Cas9 system. Nat Protoc. 2013;8:2281-308.
- Concordet JP, Haeussler M. CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens. Nucleic Acids Res. 2018;46:W242-W5.
- Gao Z, Harwig A, Berkhout B, Herrera-Carrillo E. Mutation of nucleotides around the +1 position of type 3 polymerase III promoters: the effect on transcriptional activity and start site usage. Transcription. 2017;8:275-87.
- Jiao L, Su LY, Liu Q, Luo R, Qiao X, Xie T, et al. GSNOR deficiency attenuates MPTP- induced neurotoxicity and autophagy by facilitating CDK5 S-nitrosation in a mouse model of Parkinson's disease. Free Radic Biol Med. 2022;189:111-21.
- Yao YG, Kajigaya S, Young NS. Mitochondrial DNA mutations in single human blood cells. Mutat Res. 2015;779:68-77.
- Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284-7.
- Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607-D13.
- Lau SF, Cao H, Fu AKY, Ip NY. Single-nucleus transcriptome analysis reveals dysre- gulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer's disease. Proc Natl Acad Sci USA 2020;117:25800-9.
- Korin B, Ben-Shaanan TL, Schiller M, Dubovik T, Azulay-Debby H, Boshnak NT, et al. High-dimensional, single-cell characterization of the brain's immune com- partment. Nat Neurosci. 2017;20:1300-9.
- McAlpine CS, Park J, Griciuc A, Kim E, Choi SH, Iwamoto Y, et al. Astrocytic interleukin-3 programs microglia and limits Alzheimer's disease. Nature. 2021; 595:701-6.
- Kaksonen M, Roux A. Mechanisms of clathrin-mediated endocytosis. Nat Rev Mol Cell Biol. 2018;19:313-26.
- Wu LG, Hamid E, Shin W, Chiang HC. Exocytosis and endocytosis: modes, functions, and coupling mechanisms. Annu Rev Physiol. 2014;76:301-31.
- Shin W, Wei L, Arpino G, Ge L, Guo X, Chan CY, et al. Preformed omega-profile closure and kiss-and-run mediate endocytosis and diverse endocytic modes in neuroendocrine chromaffin cells. Neuron. 2021;109:3119-34.
- Zhao B, Wang Q, Du J, Luo S, Xia J, Chen YG. PICK1 promotes caveolin-dependent degradation of TGF-beta type I receptor. Cell Res. 2012;22:1467-78.
- Bourguignon V, Flamion B. Respective roles of hyaluronidases 1 and 2 in endo- genous hyaluronan turnover. FASEB J. 2016;30:2108-14.
- Lee HW, Kim Y, Han K, Kim H, Kim E. The phosphoinositide 3-phosphatase MTMR2 interacts with PSD-95 and maintains excitatory synapses by modulating endosomal traffic. J Neurosci. 2010;30:5508-18.
- Malecz N, McCabe PC, Spaargaren C, Qiu R, Chuang Y, Symons M. Synaptojanin 2, a novel Rac1 effector that regulates clathrin-mediated endocytosis. Curr Biol. 2000;10:1383-6.
- Cheng ZJ, Singh RD, Holicky EL, Wheatley CL, Marks DL, Pagano RE. Co-regulation of caveolar and Cdc42-dependent fluid phase endocytosis by phosphocaveolin- 1. J Biol Chem. 2010;285:15119-25.
- Saftig P, Klumperman J. Lysosome biogenesis and lysosomal membrane proteins: trafficking meets function. Nat Rev Mol Cell Biol. 2009;10:623-35.
- Braulke T, Bonifacino JS. Sorting of lysosomal proteins. Biochim Biophys Acta. 2009;1793:605-14.
- Nakanishi H. Cathepsin regulation on microglial function. Biochim Biophys Acta Proteins Proteom. 2020;1868:140465.
- Lopez-Otin C, Bond JS. Proteases: multifunctional enzymes in life and disease. J Biol Chem. 2008;283:30433-7.
- Oberstein TJ, Utz J, Spitzer P, Klafki HW, Wiltfang J, Lewczuk P, et al. The role of cathepsin B in the degradation of Aβ and in the production of Aβ pep- tides starting with Ala2 in cultured astrocytes. Front Mol Neurosci. 2020; 13:615740.
- Chai YL, Chong JR, Weng J, Howlett D, Halsey A, Lee JH, et al. Lysosomal cathepsin D is upregulated in Alzheimer's disease neocortex and may be a marker for neurofibrillary degeneration. Brain Pathol. 2019;29:63-74.
- Suire CN, Abdul-Hay SO, Sahara T, Kang D, Brizuela MK, Saftig P, et al. Cathepsin D regulates cerebral Aβ42/40 ratios via differential degradation of Aβ42 and Aβ40. Alzheimers Res Ther. 2020;12:80.
- Hook V, Funkelstein L, Wegrzyn J, Bark S, Kindy M, Hook G. Cysteine Cathepsins in the secretory vesicle produce active peptides: Cathepsin L generates peptide neurotransmitters and cathepsin B produces beta-amyloid of Alzheimer's disease. Biochim Biophys Acta. 2012;1824:89-104.
- Sundelof J, Sundstrom J, Hansson O, Eriksdotter-Jonhagen M, Giedraitis V, Larsson A, et al. Higher cathepsin B levels in plasma in Alzheimer's disease compared to healthy controls. J Alzheimers Dis. 2010;22:1223-30.
- Kim KR, Cho EJ, Eom JW, Oh SS, Nakamura T, Oh CK, et al. S-Nitrosylation of cathepsin B affects autophagic flux and accumulation of protein aggregates in neurodegenerative disorders. Cell Death Differ. 2022;29:2137-50.
- Zamolodchikov D, Duffield M, Macdonald LE, Alessandri-Haber N. Accumulation of high molecular weight kininogen in the brains of Alzheimer's disease patients may affect microglial function by altering phagocytosis and lysosomal cathepsin activity. Alzheimers Dement. 2022;18:1919-29.
- Xie Z, Meng J, Kong W, Wu Z, Lan F, Narengaowa, et al. Microglial cathepsin E plays a role in neuroinflammation and amyloid β production in Alzheimer's disease. Aging Cell. 2022;21:e13565.
- Li Y, Ma C, Li W, Yang Y, Li X, Liu J, et al. A missense variant in NDUFA6 confers schizophrenia risk by affecting YY1 binding and NAGA expression. Mol Psychiatry. 2021;26:6896-911.
- Chen ZY, Zhang Y. Animal models of Alzheimer's disease: applications, evaluation, and perspectives. Zool Res. 2022;43:1026-40.
Cited by
Sorted by citations
Western, D., Timsina, J., Wang, L., Wang, C., Yang, C., Phillips, B., Wang, Y., Liu, M., Ali, M., Beric, A., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01972-8 · Cited by 111 · see citing works
Microglial phagocytosis in Alzheimer disease
Brown, G. C., St George-Hyslop, P., Paolicelli, R. C., & Lemke, G. (2026) · Nature Reviews Neurology · doi:10.1038/s41582-025-01162-y · Cited by 36 · see citing works
- Authors
- Li, Y., Xu, M., Xiang, B.-L., Li, X., Zhang, D.-F., Zhao, H., Bi, R., & Yao, Y.-G.
- Affiliations
- Kunming Institute of Zoology (CN)
- Chinese University of Hong Kong (HK)
- Corresponding author
- Bi, Rui
- Yao, Yong-Gang
- Venue
- Neuropsychopharmacology
- Published
- 2023-02-04
- Volume
- 48
- Issue
- 11
- Pages
- 1555-1566
- ISSN
- 0893-133X (ISSN-L)
- 1740-634X
- PMC
- PMC10516988
- OpenAlex
- W4319228134
- Cited by
- 20
- References
- 9
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 8 · 2023: 1
- FWCI
- 3.32
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Neuropsychopharmacology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (31730037, 31970560)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- Alzheimer's disease, cathepsin H, protective genetic variants, causal variants, transcription factor binding, gene expression, microglia, amyloid-beta phagocytosis, genetic susceptibility, Han Chinese
- MeSH terms
- Alzheimer Disease, Animals, Humans, Neurodegenerative Diseases, Genetic Predisposition to Disease, Genomics, Genome-Wide Association Study, Cathepsin H
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review