| 1. |
- Craddock, Nick, et al.
(författare)
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Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls
- 2010
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 464:7289, s. 713-720
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Tidskriftsartikel (refereegranskat)abstract
- Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed,19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated similar to 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease-IRGM for Crohn's disease, HLA for Crohn's disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetes-although in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.
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| 2. |
- Vafadar-Isfahani, Baharak, et al.
(författare)
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Identification of SPARC-like 1 Protein as Part of a Biomarker Panel for Alzheimer's Disease in Cerebrospinal Fluid
- 2012
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Ingår i: Journal of Alzheimer's Disease. - 1387-2877. ; 28:3, s. 625-636
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Tidskriftsartikel (refereegranskat)abstract
- We have used proteomic fingerprinting to investigate diagnosis of Alzheimer's disease (AD). Samples of lumbar cerebrospinal fluid (CSF) from clinically-diagnosed AD cases (n = 33), age-matched controls (n = 20), and mild cognitive impairment (MCI) patients (n = 10) were used to obtain proteomic profiles, followed by bioinformatic analysis that generated a set of potential biomarkers in CSF samples that could discriminate AD cases from controls. The identity of the biomarker ions was determined using mass spectroscopy. The panel of seven peptide biomarker ions was able to discriminate AD patients from controls with a median accuracy of 95% (sensitivity 85%, specificity 97%). When this model was applied to an independent blind dataset from MCI patients, the intensity of signals was intermediate between the control and AD patients implying that these markers could potentially predict patients with early neurodegenerative disease. The panel were identified, in order of predictive ability, as SPARC-like 1 protein, fibrinogen alpha chain precursor, amyloid-beta, apolipoprotein E precursor, serum albumin precursor, keratin type I cytoskeletal 9, and tetranectin. The 7 ion ANN model was further validated using an independent cohort of samples, where the model was able to classify AD cases from controls with median accuracy of 84.5% (sensitivity 93.3%, specificity 75.7%). Validation by immunoassay was performed on the top three identified markers using the discovery samples and an independent sample cohort which was from postmortem confirmed AD patients (n = 17).
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