Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UNIPROT:P01034 (cystatin C)
 3,397 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Cerebral amyloid angiopathy (CAA) is associated with apolipoprotein E (APOE gene, apoE protein) polymorphism: current evidence suggests that the epsilon4 allele is a risk factor for the development of CAA and the epsilon2 allele predisposes to hemorrhage. We sought to determine the relationship between the APOE epsilon2 allele and both the immunoreactivity profiles and vascular complications of CAA. We performed immunohistochemistry for amyloid beta-protein (A beta), apoE, cystatin C, and activated microglia, and examined the morphology of cortical and leptomeningeal vessels in 37 CAA-related hemorrhage (CAAH), 26 Alzheimer disease (AD) patients, and 20 controls. The extent of immunostaining of vessels for A beta, apoE, cystatin C, and perivascular activated microglia increased from controls through AD to a maximum in CAAH patients. Among cases with CAA (37 CAAH, 19 AD, and 6 controls, n = 62) vascular apoE (p < 5 x 10(-4)), cystatin C (p < 10(-4)), activated microglia (p < 10(-4)), vessels with a high ratio of wall thickness to lumen diameter (p < 0.003) as well as dilated/microaneurysmal vessels (p < 0.01) were present more frequently in patients with hemorrhage than without; however, these features were not associated with the APOE epsilon2 allele. Fibrinoid necrosis alone was associated with the APOE epsilon2 allele (p < 0.04) and we suggest that over-representation of APOE epsilon2 in CAAH may result from its association with fibrinoid necrosis.
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PMID:The apolipoprotein E epsilon2 allele and the pathological features in cerebral amyloid angiopathy-related hemorrhage. 1041 41

Twelve patients who had surgical removal of a cerebral haematoma had a biopsy or autopsy diagnosis of cerebral amyloid angiopathy-related haemorrhage (CAAH). Ten had a cortical biopsy at the time of surgery and eight reports of these were interpreted as showing CAA to be the cause of the haemorrhage. The diagnosis in the remaining two was made at autopsy. Six patients had a biopsy and autopsy, resulting in a 67% (four of six) biopsy sensitivity. Amyloid beta-protein (A beta) immunohistochemistry was more sensitive than tinctorial stains in detecting CAA. As previously reported in CAAH there was an excess of patients with the APOE epsilon 2 allele (33% versus 16% in a control group). Four patients (33%) were alive at 3 months. Despite surgical intervention, CAAH has a poor outcome in patients with impaired consciousness. Clinical awareness of CAAH and use of A beta immunostaining may increase the diagnostic yield from cerebral biopsy.
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PMID:Surgical intervention, biopsy and APOE genotype in cerebral amyloid angiopathy-related haemorrhage. 1062 76

Alzheimer's disease (AD) is a complex disorder associated with multiple genetic defects either mutational or of susceptibility. Information available on AD genetics does not explain in full the etiopathogenesis of AD, suggesting that environmental factors and/or epigenetic phenomena may also contribute to AD pathology and phenotypic expression of dementia. The genomics of AD is still in its infancy, but is helping to understand novel aspects of the disease including genetic epidemiology, multifactorial risk factors, pathogenic mechanisms associated with genetic networks and genetically-regulated metabolic cascades. AD genomics is also helping to develop new strategies in pharmacogenomic research and prevention. Functional genomics, proteomics, pharmacogenomics, high-throughput methods, combinatorial chemistry and modern bioinformatics will greatly contribute to accelerate drug development for AD and other complex disorders. Main genes involved in AD include mutational loci (APP, PS1, PS2, TAU) and multiple susceptibility loci (APOE, A2M, AACT, LRP1, IL1A, TNF, ACE, BACE, BCHE, CST3, MTHFR, GSK3B, NOS) distributed across the human genome. Genomic associations integrate bigenic, trigenic, tetragenic or polygenic matrix models to investigate the genomic organization of AD in comparison to the control population. Similar genetic models are used in pharmacogenomics to elucidate genotype-specific responses of AD patients to a particular drug or combination of drugs. Using APOE-related monogenic models it has been demonstrated that the therapeutic response to drugs in AD is genotype-specific. A multifactorial therapy combining 3 different drugs yielded positive results during the 6-12 months in approximately 60% of the patients. With this therapeutic strategy, APOE-4/4 carriers were the worst responders, and patients with the APOE-3/4 genotype were the best responders. In bigenic and trigenic models it was possible to differentiate the influencial effect of PS1 and PS2 polymorphic variants on mental performance in response to multifactorial therapy. The application of functional genomics to AD can be a suitable strategy for harmonization in molecular diagnosis and drug clinical trials. Furthermore, the pharmacogenomics of AD may contribute in the future to optimise drug development and therapeutics, increasing efficacy and safety, and reducing side-effects and unnecessary costs.
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PMID:Pharmacogenomics in Alzheimer's disease. 1236 58

Alzheimer's disease (AD) is a genetically complex disorder associated with multiple genetic defects either mutational or of susceptibility. Current AD genetics does not explain in full the etiopathogenesis of AD, suggesting that environmental factors and/or epigenetic phenomena may also contribute to AD pathology and phenotypic expression of dementia. The genomics of AD is still in its infancy, but is helping us to understand novel aspects of the disease including genetic epidemiology, multifactorial risk factors, pathogenic mechanisms associated with genetic networks and genetically-regulated metabolic cascades. AD genomics is also fostering new strategies in pharmacogenomic research and prevention. Functional genomics, proteomics, pharmacogenomics, high-throughput methods, combinatorial chemistry and modern bioinformatics will greatly contribute to accelerating drug development for AD and other complex disorders. The multifactorial genetic dysfunction in AD includes mutational loci (APP, PS1, PS2) and diverse susceptibility loci (APOE, A2M, AACT, LRP1, IL1A, TNF, ACE, BACE, BCHE, CST3, MTHFR, GSK3B, NOS3) distributed across the human genome, probably converging in common pathogenic mechanisms that lead to premature neuronal death. Genomic associations integrate polygenic matrix models to elucidate the genomic organization of AD in comparison to the control population. Using APOE-related monogenic models it has been demonstrated that the therapeutic response to drugs (e.g., cholinesterase inhibitors, non-cholinergic compounds) in AD is genotype-specific. A multifactorial therapy combining three different drugs yielded positive results during 6-12 months in approximately 60% of the patients. With this therapeutic strategy, APOE-4/4 carriers were the worst responders and patients with the APOE-3/4 genotype were the best responders. Other polymorphic variants (PS1, PS2) also influence the therapeutic response to different drugs in AD patients, suggesting that the final pharmacological outcome is the result of multiple genomic interactions, including AD-related genes and genes associated with drug metabolism, disposition, and elimination. The pharmacogenomics of AD may contribute in the future to optimise drug development and therapeutics, increasing efficacy and safety, and reducing side-effects and unnecessary costs.
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PMID:Pharmacogenomics for the treatment of dementia. 1245 80

Hereditary cerebral hemorrhage with amyloidosis-Dutch type (HCHWA-D) is a rare autosomal dominant disorder caused by an amyloid-beta precursor protein (AbetaPP) 693 mutation that clinically leads to recurrent hemorrhagic strokes and dementia. The disease is pathologically characterised by the deposition of Abeta in cerebral blood vessels and as plaques in the brain parenchyma. This study measured the Abeta40 and Abeta42 concentration in plasma of Dutch AbetaPP693 mutation carriers and controls. We found that the Abeta40 concentration was not different between AbetaPP693 mutation carriers and controls. However, the Abeta42 concentration was significantly decreased in the mutation carriers. No correlation exists between the APOE(epsilon)4 allele and the plasma of Abeta40 and Abeta42 levels in HCHWA-D patients. This finding contrasted with the increased concentrations found in Alzheimer's disease. Therefore it is suggested that the Dutch AbetaPP693 mutation located within the Abeta coding region of the AbetaPP gene has a different effect not only on clinical and pathological expression but also on Abeta processing.
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PMID:Hereditary cerebral hemorrhage with amyloidosis Dutch type (AbetaPP 693): decreased plasma amyloid-beta 42 concentration. 1467 76

Alzheimer's disease is a genetically complex disorder associated with multiple genetic defects, either mutational or of susceptibility. Although potentially associated with an accelerated stochastically driven aging process, Alzheimer's disease is an independent clinical entity in which the aging process exerts a deleterious effect on brain activity in conjunction with polymodal genetic factors and other pathological conditions (i.e., age-related cerebrovascular deterioration) and environmental factors (i.e., nutrition). Alzheimer's disease genetics does not explain in full the etiopathogenesis of this disease. Therefore, it is likely that environmental factors and/or epigenetic phenomena also contribute to Alzheimer's disease pathology and phenotypic expression of dementia. The genomics of Alzheimer's disease is still in its infancy, but this field is aiding the understanding of novel aspects of this disease, including genetic epidemiology, multifactorial risk factors, pathogenic mechanisms associated with genetic networks and genetically regulated metabolic cascades. Alzheimer's disease genomics is also helping to develop new strategies in pharmacogenomic research and prevention. Functional genomics, proteomics, pharmacogenomics, high-throughput methods, combinatorial chemistry and modern bioinformatics will greatly contribute to accelerate drug development for Alzheimer's disease and other complex disorders. The multifactorial genetic dysfunction in dementia includes mutational loci (APP, PS1, PS2, TAU) and diverse susceptibility loci (APOE, alpha2M, alphaACT, LRP1, IL1 alpha, TNF, ACE, BACE, BCHE, CST3, MTHFR, GSK3 beta, NOS3 and many other genes) distributed across the human genome, probably converging in a common pathogenic mechanism that leads to premature neuronal death, in which mitochondrial DNA mutations may contribute to increased genetic variability and heterogeneity. In Alzheimer's disease, multiple pathogenic events, including genetic factors, accumulation of aberrant or misfolded proteins, protofibril formation, ubiquitin-proteasome system dysfunction, excitotoxic reactions, oxidative and nitrosative stress, mitochondrial injury, synaptic failure, altered metal homeostasis, dysfunction of axonal and dendritic transport, and chaperone misoperation may converge in pathogenic pathways leading to premature death and neurodegeneration. Some of these mechanisms are common to several neurodegenerative disorders, which differ depending upon the gene(s) affected and the involvement of specific genetic networks, together with epigenetic factors and environmental events. Many genes potentially associated with Alzheimer's disease in some studies cannot be confirmed as candidate genes in replication studies, indicating that methodological problems and genomic complexity are leading to erroneous conclusions. A different approach to Alzheimer's disease functional genomics is to integrate individual genetic information in polygenic genotypes (haplotype-like model) and to investigate genotype-phenotype correlations and genotype-related pharmacogenomic behaviors. The application of functional genomics to Alzheimer's disease can be a suitable strategy for molecular diagnosis and for understanding pathophysiological mechanisms associated with Alzheimer's disease-related neurodegeneration. Furthermore, the pharmacogenomics of Alzheimer's disease may contribute in the future to optimize drug development and therapeutics, increasing efficacy and safety, and reducing side-effects and unnecessary costs.
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PMID:Molecular genetics of Alzheimer's disease and aging. 1647 Feb 48

The multiple polymorphisms contributing to Alzheimer disease (AD) have been difficult to identify. Three essentially sufficient risk sets were found using a fuzzy latent classification statistical model; that is, grade-of-membership analysis, and genotypes for APOE, APOCI, LDLr, cystatin C, and cathepsin D (180 cases, 120 controls). These were: (a) CST3:GA and CTSD:CT; (b) APOE44 and LDLr8:GG and LDLr13:TT; and (c) APOE34 and LDLr13:TC. Consonance with one of the groups and high aggregate membership carried >800-fold elevated risk for AD. The absence of these combinations defined low risk. APOE3/- with heterozygous promoter and receptor genotypes predicted long life without dementia.
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PMID:Membership in genetic groups predicts Alzheimer disease. 1660 2

The past decade has witnessed hundreds of reports declaring or refuting genetic association with putative Alzheimer disease susceptibility genes. This wealth of information has become increasingly difficult to follow, much less interpret. We have created a publicly available, continuously updated database that comprehensively catalogs all genetic association studies in the field of Alzheimer disease (http://www.alzgene.org). We performed systematic meta-analyses for each polymorphism with available genotype data in at least three case-control samples. In addition to identifying the epsilon4 allele of APOE and related effects, we pinpointed over a dozen potential Alzheimer disease susceptibility genes (ACE, CHRNB2, CST3, ESR1, GAPDHS, IDE, MTHFR, NCSTN, PRNP, PSEN1, TF, TFAM and TNF) with statistically significant allelic summary odds ratios (ranging from 1.11-1.38 for risk alleles and 0.92-0.67 for protective alleles). Our database provides a powerful tool for deciphering the genetics of Alzheimer disease, and it serves as a potential model for tracking the most viable gene candidates in other genetically complex diseases.
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PMID:Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. 1719 85

Genetic factors have a variable impact on Alzheimer's Disease (AD), ranging from familial forms that are transmitted in an autosomal dominant fashion to sporadic AD, where a polygenic component is present. Most genes conferring susceptibility to AD are related to amyloid-beta deposition (APP; PS1; PS2; APOE; Cystatin-C; ubiquilin-1), oxidative stress (NOS2; NOS3) and inflammatory response (IL-1 alpha; IL-1 beta; IL-6; TNF-alpha). Genome-wide analyses, transcriptomics and proteomics approaches have pointed also to proapoptotic genes as increasing AD liability. Depression and psychotic symptoms that occur in a large proportion of AD patients have been associated with monoamine genes coding for metabolic enzymes (COMT), transporters (5-HTTLPR) and receptors (DRD1; DRD3). Genetic testing may be useful to confirm the diagnosis of AD in individuals with clinical signs of dementia, while it is generally not recommended as a predictive testing for AD in asymptomatic individuals. Drugs currently in use to treat AD are effective in only 20% of patients; their therapeutic effect is predominantly under genetic control (CYP26 gene; APOE). Environmental factors have been shown to moderate the effects of genes on psychiatric disorders such as depression, schizophrenia and ADHD. The study of gene-environment interactions in AD, that are still poorly understood, is essential to predict disease-risk in asymptomatic individuals. Genomics will provide a dynamic picture of biological processes in AD and new targets for the forthcoming anti-AD drugs.
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PMID:Genetics of Alzheimer's disease. A rapidly evolving field. 1785 Nov 96

Multiple genetic variants may contribute to the risk of developing Alzheimer's disease. We have analyzed polymorphisms in 9 genes to determine whether particular combinations would contribute to this risk. The genes were APOE, LDLr, CST3, CTSD, TNF, BACE1, MAPT, STH, eNOS, and TFCP2. Three risk groups for the disease were identified. Risk group I was younger, was heterozygous for the CST3 (GA), CTSD2936 (AG), TNF -308 (AG) genetic variants. Risk group II was older, was homozygous for the -427 APOE promoter polymorphism (TT), and heterozygous for the MAPT deletion and for the STH variant (QR). Group III had both the youngest and oldest subjects, were heterozygous for the -863 (AC) and -1031 (CT) TNF promoter polymorphisms. All three groups carried the APOE 4 allele and were heterozygous for both BACE1 polymorphisms. The control groups were carriers of the APOE 3 allele and were homozygous for the BACE1 genetic variants.
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PMID:Cluster analysis of risk factor genetic polymorphisms in Alzheimer's disease. 1830 33


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