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)

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

Hierarchical clustering is frequently used for grouping results in expression or haplotype analyses. These methods can elucidate patterns between measures that can then be applied to discerning their validity in discriminating between experimental conditions. Here a hierarchical clustering method is used to analyze the results of an imaging genetics study using multiple brain morphology and cognitive testing endpoints for older adults with amnestic mild cognitive impairment (MCI) or cognitive complaints (CC) compared to healthy controls (HC). The single nucleotide polymorphisms (SNPs) are a subset of those included on a larger array that are found in a reported Alzheimer's disease (AD) and neurodegeneration pathway. The results indicate that genetic models within the endpoints cluster together, while there are 4 distinct sets of SNPs that differentiate between the endpoints, with most significant results associated with morphology endpoints rather than cognitive testing of patients' reported symptoms. The genes found in at least one cluster are ABCB1, APBA1, BACE1, BACE2, BCL2, BCL2L1, CASP7, CHAT, CST3, DRD3, DRD5, IL6, LRP1, NAT1, and PSEN2. The greater associations with morphology endpoints suggests that changes in brain structure can be influenced by an individual's genetic background in the absence of dementia and in some cases (Cognitive Complaints group) even without those effects necessarily being detectable on commonly used clinical tests of cognition. The results are consistent with polygenic influences on early neurodegenerative changes and demonstrate the effectiveness of hierarchical clustering in identifying genetic associations among multiple related phenotypic endpoints.
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PMID:Genetic pathway-based hierarchical clustering analysis of older adults with cognitive complaints and amnestic mild cognitive impairment using clinical and neuroimaging phenotypes. 2046 60