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Tang AS, Rankin KP, Cerono G, Miramontes S, Mills H, Roger J, Zeng B, Nelson C, Soman K, Woldemariam S, Li Y, Lee A, Bove R, Glymour M, Aghaeepour N, Oskotsky TT, Miller Z, Allen IE, Sanders SJ, Baranzini S, Sirota M. Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights. NATURE AGING 2024; 4:379-395. [PMID: 38383858 PMCID: PMC10950787 DOI: 10.1038/s43587-024-00573-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 01/19/2024] [Indexed: 02/23/2024]
Abstract
Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.
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Affiliation(s)
- Alice S Tang
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
- Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, San Francisco and Berkeley, CA, USA.
| | - Katherine P Rankin
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Gabriel Cerono
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Silvia Miramontes
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Hunter Mills
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Jacquelyn Roger
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Billy Zeng
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Charlotte Nelson
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Karthik Soman
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Sarah Woldemariam
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Yaqiao Li
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Albert Lee
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Riley Bove
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Maria Glymour
- Department of Anesthesiology, Pain, and Perioperative Medicine, Stanford University, Palo Alto, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Pain, and Perioperative Medicine, Stanford University, Palo Alto, CA, USA
- Department of Pediatrics, Stanford University, Palo Alto, CA, USA
- Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA
| | - Tomiko T Oskotsky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Zachary Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Isabel E Allen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Stephan J Sanders
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, UK
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Sergio Baranzini
- Weill Institute for Neuroscience. Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
- Department of Pediatrics, University of California, San Francisco, CA, USA.
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2
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Xu J, Mao C, Hou Y, Luo Y, Binder JL, Zhou Y, Bekris LM, Shin J, Hu M, Wang F, Eng C, Oprea TI, Flanagan ME, Pieper AA, Cummings J, Leverenz JB, Cheng F. Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease. Cell Rep 2022; 41:111717. [PMID: 36450252 PMCID: PMC9837836 DOI: 10.1016/j.celrep.2022.111717] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 09/01/2022] [Accepted: 11/02/2022] [Indexed: 12/03/2022] Open
Abstract
Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify disease-associated genes (NETTAG). We leverage non-coding GWAS loci effects on quantitative trait loci, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions under the protein-protein interactome. Via NETTAG, we identified 156 AD-risk genes enriched in druggable targets. Combining network-based prediction and retrospective case-control observations with 10 million individuals, we identified that usage of four drugs (ibuprofen, gemfibrozil, cholecalciferol, and ceftriaxone) is associated with reduced likelihood of AD incidence. Gemfibrozil (an approved lipid regulator) is significantly associated with 43% reduced risk of AD compared with simvastatin using an active-comparator design (95% confidence interval 0.51-0.63, p < 0.0001). In summary, NETTAG offers a deep learning methodology that utilizes GWAS and multi-genomic findings to identify pathobiology and drug repurposing in AD.
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Affiliation(s)
- Jielin Xu
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Chengsheng Mao
- Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Yuan Hou
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Yuan Luo
- Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Jessica L Binder
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA
| | - Yadi Zhou
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Lynn M Bekris
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA
| | - Jiyoung Shin
- Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA
| | - Fei Wang
- Department of Population Health Sciences, Weill Cornell Medical College, Cornell University, New York, NY 10065, USA
| | - Charis Eng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA
| | - Tudor I Oprea
- Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA
| | - Margaret E Flanagan
- Department of Pathology and Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Andrew A Pieper
- Harrington Discovery Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA; Department of Psychiatry, Case Western Reserve University, Cleveland, OH 44106, USA; Geriatric Psychiatry, GRECC, Louis Stokes Cleveland VA Medical Center, Cleveland, OH 44106, USA; Institute for Transformative Molecular Medicine, School of Medicine, Case Western Reserve University, Cleveland 44106, OH, USA; Department of Neuroscience, Case Western Reserve University, School of Medicine, Cleveland, OH 44106, USA
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - James B Leverenz
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA; Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA; Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA.
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3
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Trout AL, Rutkai I, Biose IJ, Bix GJ. Review of Alterations in Perlecan-Associated Vascular Risk Factors in Dementia. Int J Mol Sci 2020; 21:E679. [PMID: 31968632 PMCID: PMC7013765 DOI: 10.3390/ijms21020679] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 01/09/2020] [Accepted: 01/16/2020] [Indexed: 01/10/2023] Open
Abstract
Perlecan is a heparan sulfate proteoglycan protein in the extracellular matrix that structurally and biochemically supports the cerebrovasculature by dynamically responding to changes in cerebral blood flow. These changes in perlecan expression seem to be contradictory, ranging from neuroprotective and angiogenic to thrombotic and linked to lipid retention. This review investigates perlecan's influence on risk factors such as diabetes, hypertension, and amyloid that effect Vascular contributions to Cognitive Impairment and Dementia (VCID). VCID, a comorbidity with diverse etiology in sporadic Alzheimer's disease (AD), is thought to be a major factor that drives the overall clinical burden of dementia. Accordingly, changes in perlecan expression and distribution in response to VCID appears to be injury, risk factor, location, sex, age, and perlecan domain dependent. While great effort has been made to understand the role of perlecan in VCID, additional studies are needed to increase our understanding of perlecan's role in health and in cerebrovascular disease.
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Affiliation(s)
- Amanda L. Trout
- Department of Neurology, University of Kentucky, Lexington, KY 40536, USA;
| | - Ibolya Rutkai
- Department of Neurosurgery, Clinical Neuroscience Research Center, Tulane University School of Medicine, New Orleans, LA 70112, USA; (I.R.); (I.J.B.)
- Tulane Brain Institute, Tulane University, New Orleans, LA 70118, USA
| | - Ifechukwude J. Biose
- Department of Neurosurgery, Clinical Neuroscience Research Center, Tulane University School of Medicine, New Orleans, LA 70112, USA; (I.R.); (I.J.B.)
| | - Gregory J. Bix
- Department of Neurosurgery, Clinical Neuroscience Research Center, Tulane University School of Medicine, New Orleans, LA 70112, USA; (I.R.); (I.J.B.)
- Tulane Brain Institute, Tulane University, New Orleans, LA 70118, USA
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Roberts RO, Kang YN, Hu C, Moser CD, Wang S, Moore MJ, Graham RP, Lai JP, Petersen RC, Roberts LR. Decreased Expression of Sulfatase 2 in the Brains of Alzheimer's Disease Patients: Implications for Regulation of Neuronal Cell Signaling. J Alzheimers Dis Rep 2017; 1:115-124. [PMID: 30035253 PMCID: PMC6052874 DOI: 10.3233/adr-170028] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Background: The human sulfatase 1 (SULF1) and sulfatase 2 (SULF2) genes modulate cell signaling and homeostasis in many tissues. Gene expression analyses have implicated SULF2 in disease pathogenesis, including Alzheimer’s disease (AD), but changes in brain SULF2 expression have not been directly established. Objective: To investigate the expression of SULF1 and SULF2 in brain tissues from AD cases and cognitively normal controls. Methods: Autopsy tissue from AD cases (n = 20) and age-and gender-matched cognitively normal controls (n = 20) were identified from the Mayo Clinic Alzheimer’s Disease Patient Registry neuropathology database. Tissue slides were stained for SULF1 and SULF2 protein expression in the hippocampus and frontal lobe and an expression score computed from the proportion of cells stained and the intensity of staining (range 0 [no expression] to 9 [marked expression]). Results: SULF2 expression was reduced in AD cases. Compared to cognitively normal controls, SULF2 expression in AD cases was significantly decreased in the hippocampal Cornu Ammonis (CA) (mean score of 6.5 in cases versus 8.3 in controls; p = 0.003), in the gray matter of the parahippocampal gyrus (5.6 in cases versus 7.6 in controls; p = 0.003), and in the frontal lobe gray matter (5.4 in cases versus 7.4 in controls; p = 0.002). There was no difference in SULF1 expression in the hippocampus or frontal lobe of AD cases and controls. As expected there were no differences in SULF1 or SULF2 expression in white matter in AD cases compared to cognitively normal controls. Conclusion: Decreased SULF2 in specific regions of the brain occurs in AD.
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Affiliation(s)
- Rosebud O Roberts
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.,Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Yoo Na Kang
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA.,Department of Pathology, Keimyung University, Daegu, South Korea
| | - Chunling Hu
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - Catherine D Moser
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - Shaoqing Wang
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - Michael J Moore
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - Rondell P Graham
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Jin-Ping Lai
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.,Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Lewis R Roberts
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
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5
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Abstract
Heparan sulphate (HS) polysaccharides are covalently attached to the core proteins of various proteoglycans at cell surfaces and in the extracellular matrix. They are composed of alternating units of hexuronic acid and glucosamine, with sulphate substituents in complex and variable yet cell-specific patterns. Whereas HS is produced by virtually all cells in the body, heparin, a highly sulphated HS variant, is confined to connective-tissue-type mast cells. The polysaccharides interact with a multitude of proteins, mainly through ionic binding, and thereby control key processes in development and homoeostasis. Similar interactions also implicate HS in various pathophysiological settings, including cancer, amyloid diseases, infectious diseases, inflammatory conditions and some developmental disorders. Prospects for the development of HS-based drugs, which are still largely unrealized, are discussed.
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Affiliation(s)
- U Lindahl
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
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Cousin E, Macé S, Rocher C, Dib C, Muzard G, Hannequin D, Pradier L, Deleuze JF, Génin E, Brice A, Campion D. No replication of genetic association between candidate polymorphisms and Alzheimer's disease. Neurobiol Aging 2009; 32:1443-51. [PMID: 19889475 DOI: 10.1016/j.neurobiolaging.2009.09.004] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2008] [Revised: 08/28/2009] [Accepted: 09/27/2009] [Indexed: 11/19/2022]
Abstract
Alzheimer's disease is a genetically complex disorder, for which new putative susceptibility genes are constantly proposed in the literature. We selected 16 candidate genes involved in biological pathways closely related to the pathology, and for which a genetic association with Alzheimer's disease was previously detected: ACE, BACE1, BDNF, ECE1, HSPG2, IDE, IL1a, IL6, IL10, MAPT, PLAU, PrnP, PSEN1, SORL1, TFCP2 and TGFb1. The variants originally associated with the disease were genotyped in a French Caucasian sample including 428 cases and 475 controls and tested for association in order to replicate the initial results. Despite a careful replication study design, we failed to validate the initial findings for any of these variants, with the possible exception of MAPT, SORL1 and TFCP2 for which some nominal but inconsistent evidence of association was observed.
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Affiliation(s)
- Emmanuelle Cousin
- Biological Sciences Department, sanofi-aventis Recherche et Développement, Centre de Génétique humaine, 91057 Evry, France
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7
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Combarros O, Cortina-Borja M, Smith AD, Lehmann DJ. Epistasis in sporadic Alzheimer's disease. Neurobiol Aging 2009; 30:1333-49. [PMID: 18206267 DOI: 10.1016/j.neurobiolaging.2007.11.027] [Citation(s) in RCA: 86] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2007] [Revised: 11/30/2007] [Accepted: 11/30/2007] [Indexed: 10/22/2022]
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Seripa D, Panza F, Franceschi M, D'Onofrio G, Solfrizzi V, Dallapiccola B, Pilotto A. Non-apolipoprotein E and apolipoprotein E genetics of sporadic Alzheimer's disease. Ageing Res Rev 2009; 8:214-36. [PMID: 19496238 DOI: 10.1016/j.arr.2008.12.003] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
The genetic epidemiology of sporadic Alzheimer's disease (SAD) remains a very active area of research,making it one of the most prolifically published areas in medicine and biology. Numerous putative candidate genes have been proposed. However, with the exception of apolipoprotein E (APOE), the only confirmed genetic risk factor for SAD, all the other data appear to be not consistent. Nevertheless, the genetic risk for SAD attributable to the APOE gene in the general population is 20-0%, providing a strong evidence for the existence of additional genetic risk factors. The first part of the present article was dedicated to non-APOE genetics of SAD, reviewing chromosomes-by-chromosomes the available data concerning the major candidate genes. The second part of this article focused on some recently discovered aspects of the APOE polymorphism and their implications for SAD. An attempt to identify the future directions for non-APOE genetic research in SAD was also discussed.
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Affiliation(s)
- Davide Seripa
- Geriatric Unit and Gerontology-Geriatrics Research Laboratory, Department of Medical Sciences, IRCCS Casa Sollievo della Sofferenza, 71013 San Giovanni Rotondo (FG), Italy.
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Onaran M, Yilmaz A, Sen I, Ergun MA, Camtosun A, Küpeli B, Menevse S, Bozkirli I. Heparan sulfate gene polymorphism in calcium oxalate nephrolithiasis. ACTA ACUST UNITED AC 2008; 37:47-50. [PMID: 19066875 DOI: 10.1007/s00240-008-0167-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2008] [Accepted: 11/25/2008] [Indexed: 01/28/2023]
Abstract
Calcium oxalate (CaOx) nephrolithiasis has a complex pathogenic mechanism. Besides environmental factors, genetic factors also have influence on stone formation. This study represents the effects of heparan sulfate (HSPG2) gene polymorphism for determining the risk of urolithiasis. We investigated 143 CaOx stone formers with 158 healthy individuals for the BamHI restriction site polymorphism located in intron 6 of the HSPG gene using the polymerase chain reaction, restriction fragments length polymorphism method. After digestion with BamHI, the polymorphism was assumed to cause three genotypes according to the banding types as GG (242 bp), GT (242, 144, and 98 bp) and TT (144 and 98 bp). According to the genotype frequencies between the groups, TT genotype showed significantly increased risk for urolithiasis than TG and GG genotypes. We concluded that HSPG2 gene polymorphism might be one of the genetic factors affecting the CaOx stone formation.
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Affiliation(s)
- Metin Onaran
- Department of Urology, School of Medicine, Gazi University, Ankara, Turkey.
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10
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Affiliation(s)
- Satomi Nadanaka
- Department of Biochemistry, Kobe Pharmaceutical University, Kobe 658-8558, Japan
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Wang B, Jin F, Yang Z, Lu Z, Zheng C, Wang L. HSPG2 gene C/A polymorphism does not confer susceptibility to Alzheimer's disease in Chinese. Dement Geriatr Cogn Disord 2007; 23:312-5. [PMID: 17356275 DOI: 10.1159/000100902] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/25/2006] [Indexed: 11/19/2022] Open
Abstract
Human HSPG2 participates in the formation of amyloid and tau aggregation in Alzheimer's disease (AD). HSPG2 gene is located on a susceptibility region to late-onset AD (LOAD), and considered as a candidate gene for LOAD because of its function and location. We performed an association study between the HSPG2 BamH I polymorphism C/A of intron 6 and LOAD on 104 patients and 127 healthy controls of Chinese origin. The C allele was more prominent in LOAD patients than in controls, though the difference was not statistically significant. Likewise with the stratification of APOE epsilon4 status, no statistical difference was observed between cases and controls. Our findings suggest that this polymorphism may not represent an additional genetic risk factor for LOAD.
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Affiliation(s)
- Binbin Wang
- Center for Human and Animal Genetics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
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