| 1. |
- Ameur, Adam, et al.
(författare)
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SweGen : a whole-genome data resource of genetic variability in a cross-section of the Swedish population
- 2017
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Ingår i: European Journal of Human Genetics. - : NATURE PUBLISHING GROUP. - 1018-4813 .- 1476-5438. ; 25:11, s. 1253-1260
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Tidskriftsartikel (refereegranskat)abstract
- Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.
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| 2. |
- Gyllensten, Ulf B., et al.
(författare)
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Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer
- 2022
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:7
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Tidskriftsartikel (refereegranskat)abstract
- Simple Summary Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. The aim of our study was to broadly measure protein biomarkers to find tests for the early detection of ovarian cancer. We found that combinations of 4-7 protein biomarkers can provide highly accurate detection of early- and late-stage ovarian cancer compared to benign conditions. The performance of the tests was then validated in a second independent cohort. Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.
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| 3. |
- Lahermo, P, et al.
(författare)
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A quality assessment survey of SNP genotyping laboratories
- 2006
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 27:7, s. 711-714
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- To survey the quality of SNP genotyping, a joint Nordic quality assessment (QA) round was organized between 11 laboratories in the Nordic and Baltic countries. The QA round involved blinded genotyping of 47 DNA samples for 18 or six randomly selected SNPs. The methods used by the participating laboratories included all major platforms for small- to medium-size SNP genotyping. The laboratories used their standard procedures for SNP assay design, genotyping, and quality control. Based on the joint results from all laboratories, a consensus genotype for each DNA sample and SNP was determined by the coordinator of the survey, and the results from each laboratory were compared to this genotype. The overall genotyping accuracy achieved in the survey was excellent. Six laboratories delivered genotype data that were in full agreement with the consensus genotype. The average accuracy per SNP varied from 99.1 to 100% between the laboratories, and it was frequently 100% for the majority of the assays for which SNP genotypes were reported. Lessons from the survey are that special attention should be given to the quality of the DNA samples prior to genotyping, and that a conservative approach for calling the genotypes should be used to achieve a high accuracy.
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| 4. |
- Sehat, Bita, et al.
(författare)
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SUMOylation Mediates the Nuclear Translocation and Signaling of the IGF-1 Receptor
- 2010
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Ingår i: Science Signaling. - : American Association for the Advancement of Science (AAAS). - 1945-0877 .- 1937-9145. ; 3:108
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Tidskriftsartikel (refereegranskat)abstract
- The insulin-like growth factor 1 receptor (IGF-1R) plays crucial roles in developmental and cancer biology. Most of its biological effects have been ascribed to its tyrosine kinase activity, which propagates signaling through the phosphatidylinositol 3-kinase and mitogen-activated protein kinase pathways. Here, we report that IGF-1 promotes the modification of IGF-1R by small ubiquitin-like modifier protein-1 (SUMO-1) and its translocation to the nucleus. Nuclear IGF-1R associated with enhancer-like elements and increased transcription in reporter assays. The SUMOylation sites of IGF-1R were identified as three evolutionarily conserved lysine residues-Lys(1025), Lys(1100), and Lys(1120)-in the beta subunit of the receptor. Mutation of these SUMO-1 sites abolished the ability of IGF-1R to translocate to the nucleus and activate transcription, but did not alter its kinase-dependent signaling. Thus, we demonstrate a SUMOylation-mediated mechanism of IGF-1R signaling that has potential implications for gene regulation.
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