Markus Hansson

Markus Hansson

orcid

Research Focus & Metrics

Academic Career Length

31Years (1996-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 May 2017 in Leukemia
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Journal Article
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SKS K Kumar
S K Kumar
MDM A Dimopoulos
M A Dimopoulos
EKE Kastritis
E Kastritis
ETE Terpos
E Terpos
HNH Nahi
H Nahi
BDB G M Durie
B G M Durie

16 October 2020 in Blood Cancer Journal
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Journal Article
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María Victoria MateosMaría Victoria Mateos
María Victoria Mateos
SKShaji Kumar
Shaji Kumar
Meletios-Athanasios DimopoulosMeletios-Athanasios Dimopoulos
Meletios-Athanasios Dimopoulos
VGVerónica González-Calle
Verónica González-Calle
EKEfstathios Kastritis
Efstathios Kastritis
JSJesús San-Miguel
Jesús San-Miguel
Smoldering multiple myeloma (SMM) is an asymptomatic precursor state of multiple myeloma (MM). Recently, MM was redefined to include biomarkers predicting a high risk of progression from SMM, thus necessitating a redefinition of SMM and its risk stratification. We assembled a large cohort of SMM patients meeting the revised IMWG criteria to develop a new risk stratification system. We included 1996 patients, and using stepwise selection and multivariable analysis, we identified three independent factors predicting progression risk at 2 years: serum M-protein >2 g/dL (HR: 2.1), involved to uninvolved free light-chain ratio >20 (HR: 2.7), and marrow plasma cell infiltration >20% (HR: 2.4). This translates into 3 categories with increasing 2-year progression risk: 6% for low risk (38%; no risk factors, HR: 1); 18% for intermediate risk (33%; 1 factor; HR: 3.0), and 44% for high risk (29%; 2–3 factors). Addition of cytogenetic abnormalities (t(4;14), t(14;16), +1q, and/or del13q) allowed separation into 4 groups (low risk with 0, low intermediate risk with 1, intermediate risk with 2, and high risk with ≥3 risk factors) with 6, 23, 46, and 63% risk of progression in 2 years, respectively. The 2/20/20 risk stratification model can be easily implemented to identify high-risk SMM for clinical research and routine practice and will be widely applicable.

1 January 2006 in Archives of Biochemistry and Biophysics
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MHMarkus Hansson
Markus Hansson
IOInge Olsson
Inge Olsson
WNWilliam M. Nauseef
William M. Nauseef

1 July 2016 in Nature Communications
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JMJonathan S. Mitchell
Jonathan S. Mitchell
NLNi Li
Ni Li
NWNiels Weinhold
Niels Weinhold
AFAsta Försti
Asta Försti
MAMina Ali
Mina Ali
Richard HoulstonRichard Houlston
Richard Houlston
Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a new GWAS and perform replication analyses resulting in 9,866 cases and 239,188 controls. We confirm all nine known risk loci and discover eight new loci at 6p22.3 (rs34229995, P=1.31 × 10−8), 6q21 (rs9372120, P=9.09 × 10−15), 7q36.1 (rs7781265, P=9.71 × 10−9), 8q24.21 (rs1948915, P=4.20 × 10−11), 9p21.3 (rs2811710, P=1.72 × 10−13), 10p12.1 (rs2790457, P=1.77 × 10−8), 16q23.1 (rs7193541, P=5.00 × 10−12) and 20q13.13 (rs6066835, P=1.36 × 10−13), which localize in or near to JARID2, ATG5, SMARCD3, CCAT1, CDKN2A, WAC, RFWD3 and PREX1. These findings provide additional support for a polygenic model of MM and insight into the biological basis of tumour development.

19 June 2017 in Nature Genetics
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SJStefan Jonsson
Stefan Jonsson
GSGardar Sveinbjornsson
Gardar Sveinbjornsson
APAitzkoa Lopez de Lapuente Portilla
Aitzkoa Lopez de Lapuente Portilla
BSBhairavi Swaminathan
Bhairavi Swaminathan
RPRosina Plomp
Rosina Plomp
KSKari Stefansson
Kari Stefansson

13 September 2018 in Nature Communications
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Journal Article
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MWMolly Went
Molly Went
ASAmit Sud
Amit Sud
AFAsta Försti
Asta Försti
BHBritt-Marie Halvarsson
Britt-Marie Halvarsson
NWNiels Weinhold
Niels Weinhold
STStephen N. Thibodeau
Stephen N. Thibodeau
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.