| 1. |
- Flannick, Jason, et al.
(författare)
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Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
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| 2. |
- Fuchsberger, Christian, et al.
(författare)
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The genetic architecture of type 2 diabetes
- 2016
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 536:7614, s. 41-47
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Tidskriftsartikel (refereegranskat)abstract
- The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
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| 3. |
- Henjes, Frauke, et al.
(författare)
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Analysis of Autoantibody Profiles in Osteoarthritis Using Comprehensive Protein Array Concepts
- 2014
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 13:11, s. 5218-5229
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Tidskriftsartikel (refereegranskat)abstract
- Osteoarthritis (OA) is the most common rheumatic disease and one of the most disabling pathologies worldwide. To date, the diagnostic methods of OA are very limited, and there are no available medications capable of halting its characteristic cartilage degeneration. Therefore, there is a significant interest in new biomarkers useful for the early diagnosis, prognosis, and therapeutic monitoring. In the recent years, protein microarrays have emerged as a powerful proteomic tool to search for new biomarkers. In this study, we have used two concepts for generating protein arrays, antigen microarrays, and NAPPA (nucleic acid programmable protein arrays), to characterize differential autoantibody profiles in a set of 62 samples from OA, rheumatoid arthritis (RA), and healthy controls. An untargeted screen was performed on 3840 protein fragments spotted on planar antigen arrays, and 373 antigens were selected for validation on bead-based arrays. In the NAPPA approach, a targeted screening was performed on 80 preselected proteins. The autoantibody targeting CHST14 was validated by ELISA in the same set of patients. Altogether, nine and seven disease related autoantibody target candidates were identified, and this work demonstrates a combination of these two array concepts for biomarker discovery and their usefulness for characterizing disease-specific autoantibody profiles.
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| 4. |
- Lourido, Lucia, et al.
(författare)
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Discovery of circulating proteins associated to knee radiographic osteoarthritis
- 2017
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Currently there are no sufficiently sensitive biomarkers able to reflect changes in joint remodelling during osteoarthritis (OA). In this work, we took an affinity proteomic approach to profile serum samples for proteins that could serve as indicators for the diagnosis of radiographic knee OA. Antibody suspension bead arrays were applied to analyze serum samples from patients with OA (n = 273), control subjects (n = 76) and patients with rheumatoid arthritis (RA, n = 244). For verification, a focused bead array was built and applied to an independent set of serum samples from patients with OA (n = 188), control individuals (n = 83) and RA (n = 168) patients. A linear regression analysis adjusting for sex, age and body mass index (BMI) revealed that three proteins were significantly elevated (P < 0.05) in serum from OA patients compared to controls: C3, ITIH1 and S100A6. A panel consisting of these three proteins had an area under the curve of 0.82 for the classification of OA and control samples. Moreover, C3 and ITIH1 levels were also found to be significantly elevated (P < 0.05) in OA patients compared to RA patients. Upon validation in additional study sets, the alterations of these three candidate serum biomarker proteins could support the diagnosis of radiographic knee OA.
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