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Type 2 Diabetes-Related Variants Influence on the Risk of Developing Multiple Myeloma: Results from the Immense Consortium

Authors :
Mario Petrini
Judit Várkonyi
Krzysztof Jamroziak
Artur Jurczyszyn
Marzena Wątek
Juan Sainz
Rui Manuel Reis
Marek Dudziński
Herlander Marques
Charles Dumontet
H Moreno
Ulla Vogel
Victor Moreno
Gabriele Buda
Stefano Landi
Federico Canzian
Joaquin Martinez-Lopez
Fabienne Lesueur
Rafael Rios
Ramón García-Sanz
Carmen Belén Lupiañez
Zofia Szemraj-Rogucka
Annette Juul Vangsted
Daniele Campa
Source :
Blood. 124:2044-2044
Publication Year :
2014
Publisher :
American Society of Hematology, 2014.

Abstract

Type 2-diabetes (T2D) is thought to be a relevant risk factor for multiple myeloma (MM), but the relationship between both traits is still not well understood. Thus, we decided to conduct a population-based case-control study in a population of 1420 MM patients (705 women and 715 men) and 1858 controls (916 women and 942 men) to evaluate whether 58 genome-wide association studies (GWAS)-identified common variants for T2D influence the risk of developing MM. Logistic regression analyses showed that carriers of the KCNQ1rs2237892T allele or CDKN2A-2Brs2383208G/G, IGF-1rs35767T/T and MADDrs7944584T/T genotypes had an increased risk of MM (OR=1.32, 95%CI 1.01-1.71, P=0.039; OR=1.86, 95%CI 1.12-3.11, P=0.016; OR=2.13, 95%CI 1.35-3.37, P=0.001 and OR=1.33, 95%CI 1.06-1.67, P=0.014, respectively) whereas those carrying the KCNJ11rs5215C, KCNJ11rs5219T and THADArs7578597C alleles or the FTOrs8050136A/A and LTArs1041981C/C genotypes showed a decreased risk for the disease (OR=0.85, 95%CI 0.73-0.99, P=0.38; OR=0.84, 95%CI 0.72-0.99, P=0.034; OR=0.81, 95%CI 0.68-0.98, P=0.032; OR=0.78, 95%CI 0.64-0.95, P=0.013; and OR=0.76, 95%CI 0.58-0.99, P=0.042, respectively). The associations of these T2D-related variants with an increased or decreased risk of MM were due to non-diabetogenic alleles, which suggests a non-diabetogenic mechanism underlying the effect of these variants to determine the risk of the disease. A gender-stratified analysis also revealed a significant gender effect modification for ADAM30rs2641348, and NOTCH2rs10923931 SNPs (Pinteraction=0.001 and 0.0004 and Phet=0.19 and 0.60, respectively), which also underlies the importance of considering gender as a factor modifying the risk for MM. Men harbouring the ADAM30rs2641348C and NOTCH2rs10923931T alleles had a decreased risk of MM (OR=0.71, 95%CI 0.54-0.94, P=0.015 and OR=0.66, 95%CI 0.50-0.86, P=0.0019) whereas an opposite but not significant effect was observed in women. Finally, SNP-SNP interaction analysis revealed overall significant two- and three-locus interaction models to increase the risk of MM (FAM148Brs11071657-KCNJ11rs5219, and SLC30A8rs13266634-KCNJ11rs5219-FTOrs8050136; P=0.01 and 0.001, respectively) whereas a significant four-locus model was also found to increase the risk of MM in men (FADS1rs174550-TSPAN8rs7961581-PROX1rs340874-KCNJ11rs5219, P=0.001). Although further studies in independent populations are warranted to replicate these findings, these results suggest that TD2-related variants may influence the risk of developing MM, likely through non-diabetogenic mechanisms. Abstract 2044. Table 1. Demographical characteristics of IMMEnSE cases and controls. CASES CONTROLS Region* Gender M/F (Total) Mean Age (± STD) Gender M/F (Total) Mean Age (± STD) Control type Italy 117/107 (224) 62.60±9.90 127/105 (232) 58.75±10.92 General population Poland 173/198 (371) 62.35±10.39 124/226 (350) 50.68±19.43 Blood donors Spain 139/133 (272) 63.06±11.04 218/192 (410) 63.12±11.94 Hospitalized subjects France 42/33 (75) 55.80±9.04 95/89 (184) 44.07±15.22 Blood donors Portugal 32/35 (67) 65.79±11.16 52/42 (94) 60.88±07.88 Blood donors Hungary 49/87 (136) 65.83±11.19 50/51 (101) 73.18±10.10 Hospitalized subjects Denmark 163/112 (275) 55.20±07.32 276/211 (487) 43.26±11.84 General population Total 715/705 (1420) 61.06±10.57 942/916 (1858) 53.56±16.45 Table 2. Selected type-2 diabetes-related polymorphisms Gene name dbSNP rs# Gene name dbSNP rs# ADAM30 rs2641348 JAZF1 rs864745 ADAMTS9 rs4607103 KCNJ11 rs5215 ADCY5 rs11708067 rs5219 ADRA2A rs10885122 KCNQ1 rs2237897 ARAPI, CENTD2 rs1552224 rs2074196 BCL11A rs10490072 rs2237892 CDC123 rs12779790 rs2237895 CDKAL1 rs7754840 KCNQ1OT1 rs231362 CDKN2A-2B rs564398 LTA rs1041981 rs10811661 MADD rs7944584 rs2383208 MCR4 rs12970134 COL5A1 rs4240702 MTNR1B rs1387153 CRY2 rs11605924 NOTCH2 rs10923931 DCD rs1153188 PKN2 rs6698181 EXT2 rs1113132 PPARG rs1801282 FADS1 rs174550 PRC1 rs8042680 FAM148B rs11071657 PROX1 rs340874 FLJ39370 rs17044137 RBMS1 rs7593730 FTO rs8050136 SLC2A2 rs11920090 G6PC2 rs560887 SLC30A8 rs13266634 GCK rs1799884 TCF2 rs7501939 GCKR rs1260326 TCF7L2 rs7903146 HHEX rs1111875 TCF7L2 rs12255372 HMGA2 rs1531343 THADA rs7578597 HNF1A, TCF1 rs7957197 TP53INP1 rs896854 IGF1 rs35767 TSPAN8 rs7961581 IGF2BP2 rs4402960 VEGFA rs9472138 IL13 rs20541 WFS1 rs734312 IRS1 rs2943641 rs10010131 Disclosures No relevant conflicts of interest to declare.

Details

ISSN :
15280020 and 00064971
Volume :
124
Database :
OpenAIRE
Journal :
Blood
Accession number :
edsair.doi...........cdff625d45294909ed6356c8257b0903