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- Went, M, et al.
(författare)
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Author Correction: Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 213-
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Tidskriftsartikel (refereegranskat)abstract
- The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.
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| 2. |
- Went, M, et al.
(författare)
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Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma
- 2018
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1, s. 3707-
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have transformed our understanding of susceptibility to multiple myeloma (MM), but much of the heritability remains unexplained. We report a new GWAS, a meta-analysis with previous GWAS and a replication series, totalling 9974 MM cases and 247,556 controls of European ancestry. Collectively, these data provide evidence for six new MM risk loci, bringing the total number to 23. Integration of information from gene expression, epigenetic profiling and in situ Hi-C data for the 23 risk loci implicate disruption of developmental transcriptional regulators as a basis of MM susceptibility, compatible with altered B-cell differentiation as a key mechanism. Dysregulation of autophagy/apoptosis and cell cycle signalling feature as recurrently perturbed pathways. Our findings provide further insight into the biological basis of MM.
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| 3. |
- Ali, Mina, et al.
(författare)
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The multiple myeloma risk allele at 5q15 lowers ELL2 expression and increases ribosomal gene expression
- 2018
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1, s. 1649-
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Tidskriftsartikel (refereegranskat)abstract
- Recently, we identified ELL2 as a susceptibility gene for multiple myeloma (MM). To understand its mechanism of action, we performed expression quantitative trait locus analysis in CD138+ plasma cells from 1630 MM patients from four populations. We show that the MM risk allele lowers ELL2 expression in these cells (Pcombined = 2.5 × 10−27; βcombined = −0.24 SD), but not in peripheral blood or other tissues. Consistent with this, several variants representing the MM risk allele map to regulatory genomic regions, and three yield reduced transcriptional activity in plasmocytoma cell lines. One of these (rs3777189-C) co-locates with the best-supported lead variants for ELL2 expression and MM risk, and reduces binding of MAFF/G/K family transcription factors. Moreover, further analysis reveals that the MM risk allele associates with upregulation of gene sets related to ribosome biogenesis, and knockout/knockdown and rescue experiments in plasmocytoma cell lines support a cause–effect relationship. Our results provide mechanistic insight into MM predisposition.
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| 4. |
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| 5. |
- Da Silva Filho, M. I., et al.
(författare)
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Genome-wide association study of immunoglobulin light chain amyloidosis in three patient cohorts : Comparison with myeloma
- 2017
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Ingår i: Leukemia. - : Springer Science and Business Media LLC. - 0887-6924 .- 1476-5551. ; 31:8, s. 1735-1742
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Tidskriftsartikel (refereegranskat)abstract
- Immunoglobulin light chain (AL) amyloidosis is characterized by tissue deposition of amyloid fibers derived from immunoglobulin light chain. AL amyloidosis and multiple myeloma (MM) originate from monoclonal gammopathy of undetermined significance. We wanted to characterize germline susceptibility to AL amyloidosis using a genome-wide association study (GWAS) on 1229 AL amyloidosis patients from Germany, UK and Italy, and 7526 healthy local controls. For comparison with MM, recent GWAS data on 3790 cases were used. For AL amyloidosis, single nucleotide polymorphisms (SNPs) at 10 loci showed evidence of an association at P<10 -5 with homogeneity of results from the 3 sample sets; some of these were previously documented to influence MM risk, including the SNP at the IRF4 binding site. In AL amyloidosis, rs9344 at the splice site of cyclin D1, promoting translocation (11;14), reached the highest significance, P=7.80 × 10 -11; the SNP was only marginally significant in MM. SNP rs79419269 close to gene SMARCD3 involved in chromatin remodeling was also significant (P=5.2 × 10 -8). These data provide evidence for common genetic susceptibility to AL amyloidosis and MM. Cyclin D1 is a more prominent driver in AL amyloidosis than in MM, but the links to aggregation of light chains need to be demonstrated.
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| 6. |
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| 7. |
- Johnson, D C, et al.
(författare)
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Genetic factors influencing the risk of multiple myeloma bone disease.
- 2016
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Ingår i: Leukemia. - : Springer Science and Business Media LLC. - 1476-5551 .- 0887-6924. ; 30, s. 883-888
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Tidskriftsartikel (refereegranskat)abstract
- A major complication of multiple myeloma (MM) is the development of osteolytic lesions, fractures and bone pain. To identify genetic variants influencing the development of MM bone disease (MBD), we analyzed MM patients of European ancestry (totalling 3774) which had been radiologically surveyed for MBD. Each patient had been genotyped for ~600 000 SNPs with genotypes for six million common variants imputed using 1000Genomes Project and UK10K as reference. We identified a locus at 8q24.12 for MBD (rs4407910, OPG/TNFRSF11B, odds ratio [OR]=1.38, P=4.09 × 10(-9)) and a promising association at 19q13.43 (rs74676832, OR=1.97, P=9.33 × 10(-7)). Our findings demonstrate that germline variation influences MBD and highlights the importance of RANK/RANKL/OPG pathway in MBD development. These findings will contribute to the development of future strategies for prevention of MBD in the early precancerous phases of MM.Leukemia accepted article preview online, 16 December 2015. doi:10.1038/leu.2015.342.
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| 8. |
- Morgan, G. J., et al.
(författare)
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Inherited genetic susceptibility to multiple myeloma
- 2014
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Ingår i: Leukemia. - : Springer Science and Business Media LLC. - 1476-5551 .- 0887-6924. ; 28:3, s. 518-524
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Forskningsöversikt (refereegranskat)abstract
- Although the familial clustering of multiple myeloma (MM) supports the role of inherited susceptibility, only recently has direct evidence for genetic predisposition been demonstrated. A meta-analysis of two genome-wide association (GWA) studies has identified single-nucleotide polymorphisms (SNPs) localising to a number of genomic regions that are robustly associated with MM risk. In this review, we provide an overview of the evidence supporting a genetic contribution to the predisposition to MM and MGUS (monoclonal gammopathy of unknown significance), and the insight this gives into the biological basis of disease aetiology. We also highlight the promise of future approaches to identify further specific risk factors and their potential clinical utility.
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| 9. |
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| 10. |
- Sachpekidis, C., et al.
(författare)
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Application of an artificial intelligence-based tool in F-18 FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma
- 2023
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Ingår i: European Journal of Nuclear Medicine and Molecular Imaging. - 1619-7070 .- 1619-7089. ; 50:12, s. 3697-3708
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Tidskriftsartikel (refereegranskat)abstract
- Purpose[F-18]FDG PET/CT is an imaging modality of high performance in multiple myeloma (MM). Nevertheless, the inter-observer reproducibility in PET/CT scan interpretation may be hampered by the different patterns of bone marrow (BM) infiltration in the disease. Although many approaches have been recently developed to address the issue of standardization, none can yet be considered a standard method in the interpretation of PET/CT. We herein aim to validate a novel three-dimensional deep learning-based tool on PET/CT images for automated assessment of the intensity of BM metabolism in MM patients.Materials and methodsWhole-body [F-18]FDG PET/CT scans of 35 consecutive, previously untreated MM patients were studied. All patients were investigated in the context of an open-label, multicenter, randomized, active-controlled, phase 3 trial (GMMG-HD7). Qualitative (visual) analysis classified the PET/CT scans into three groups based on the presence and number of focal [F-18]FDG-avid lesions as well as the degree of diffuse [F-18]FDG uptake in the BM. The proposed automated method for BM metabolism assessment is based on an initial CT-based segmentation of the skeleton, its transfer to the SUV PET images, the subsequent application of different SUV thresholds, and refinement of the resulting regions using postprocessing. In the present analysis, six different SUV thresholds (Approaches 1-6) were applied for the definition of pathological tracer uptake in the skeleton [Approach 1: liver SUVmedian x 1.1 (axial skeleton), gluteal muscles SUVmedian x 4 (extremities). Approach 2: liver SUVmedian x 1.5 (axial skeleton), gluteal muscles SUVmedian x 4 (extremities). Approach 3: liver SUVmedian x 2 (axial skeleton), gluteal muscles SUVmedian x 4 (extremities). Approach 4: & GE; 2.5. Approach 5: & GE; 2.5 (axial skeleton), & GE; 2.0 (extremities). Approach 6: SUVmax liver]. Using the resulting masks, subsequent calculations of the whole-body metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in each patient were performed. A correlation analysis was performed between the automated PET values and the results of the visual PET/CT analysis as well as the histopathological, cytogenetical, and clinical data of the patients.ResultsBM segmentation and calculation of MTV and TLG after the application of the deep learning tool were feasible in all patients. A significant positive correlation (p < 0.05) was observed between the results of the visual analysis of the PET/CT scans for the three patient groups and the MTV and TLG values after the employment of all six [F-18]FDG uptake thresholds. In addition, there were significant differences between the three patient groups with regard to their MTV and TLG values for all applied thresholds of pathological tracer uptake. Furthermore, we could demonstrate a significant, moderate, positive correlation of BM plasma cell infiltration and plasma levels of & beta;2-microglobulin with the automated quantitative PET/CT parameters MTV and TLG after utilization of Approaches 1, 2, 4, and 5.ConclusionsThe automated, volumetric, whole-body PET/CT assessment of the BM metabolic activity in MM is feasible with the herein applied method and correlates with clinically relevant parameters in the disease. This methodology offers a potentially reliable tool in the direction of optimization and standardization of PET/CT interpretation in MM. Based on the present promising findings, the deep learning-based approach will be further evaluated in future prospective studies with larger patient cohorts.
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