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- Bellenguez, C, et al.
(författare)
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New insights into the genetic etiology of Alzheimer's disease and related dementias
- 2022
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Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 54:4, s. 412-436
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Tidskriftsartikel (refereegranskat)abstract
- Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.
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- Perfecto-Avalos, Yocanxóchitl, et al.
(författare)
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Denaturing high-performance liquid chromatography and principal component analysis for identification of DNA point mutations in breast cancer and lymphoma samples
- 2018
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Ingår i: Journal of Chemometrics. - : Wiley. - 0886-9383. ; 32:10
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Tidskriftsartikel (refereegranskat)abstract
- Abstract DNA mutations are identified by techniques that use the knowledge of the wild-type DNA sequence and its mutated variant. The involved analytic methods must be accurate, rapid, and sustainable, if a clinical application is pursued. High-performance liquid chromatography under denaturing conditions is a useful technique to screen mutations. Denaturing high-performance liquid chromatography resultant chromatograms are suitable for feature extraction analysis with multivariate methods such as principal component analysis. In this work, principal component analysis was applied to analyze the chromatograms from 3 different genes. Fragments with verified wild-type sequence were used as reference and samples with sequence unknown were tested. A statistical characterization based on Tukey’s boxplot equation of principal component scores allowed us to analyze the distance distribution between reference and sample clusters to establish a classification criterion: an outlier could represent a mutated sample, and a typical value could be a wild-type sample. Identified outliers were further analyzed by sequencing and proved to carry a mutation. From 72 datasets with a total of 4258 injections, we successfully assessed the classification criterion, identifying mutated samples in lymphoma and breast cancer patients with ratio of prediction Gmean = [0.89, 1.00]. Compared with sequencing analysis, this procedure reduced time and costs.
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