Polymorphisms within autophagy-related genes as susceptibility biomarkers for multiple myeloma: a meta-analysis of three large cohorts and functional characterization

Functional data used in this project have been meticulously catalogued and archived in the BBMRI-NL data infrastructure (https://hfgp.bbmri.nl/, accessed on 12 February 2020) using the MOLGENIS open-source platform for scientific data.Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10−9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10−4−5.79 × 10−14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10−4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10−4) and circulating serum concentrations of Monocyte hemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 SNP corre lated with numbers of CD19+ B cells, CD19+CD3− B cells, CD5+ IgD− cells, IgM− cells, IgD−IgM− cells, and CD4−CD8− PBMCs (p = 4.9 × 10−4−8.6 × 10−4 ) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+EMCD45RO+CD27− cells (p = 9.3 × 10−4 ). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3−, MCP-2−, and IL20-dependent pathways.This work was supported by the European Union’s Horizon 2020 research and innovation program, N° 856620 and by grants from the Instituto de Salud Carlos III and FEDER (Madrid, Spain; PI17/02256 and PI20/01845), Consejería de Transformación Económica, Industria, Conocimiento y Universidades and FEDER (PY20/01282), from the CRIS foundation against cancer, from the Cancer Network of Excellence (RD12/10 Red de Cáncer), from the Dietmar Hopp Foundation and the German Ministry of Education and Science (BMBF: CLIOMMICS [01ZX1309]), and from National Cancer Institute of the National Institutes of Health under award numbers: R01CA186646, U01CA249955 (EEB).This work was also funded d by Portuguese National funds, through the Foundation for Science and Technology (FCT)—project UIDB/50026/2020 and UIDP/50026/2020 and by the project NORTE-01-0145-FEDER-000055, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF)

Trace metal distribution in the bed, bank and suspended sediment of the Ravensbourne River and its implication for sediment monitoring in an urban river

Purpose This study aims to identify a suitable sediment compartment for sediment quality monitoring by: (a) studying the concentration of trace metals (Cd, Cu, Ni, Pb and Zn) in the bed, bank and suspended sediment compartments of the Ravensbourne River to establish any differences in trace metal concentrations with compartment; (b) determining the influence of sediment particle size fractions ( 0.05) in the concentrations of metals between the suspended sediment and the < 63 μm bed sediment fraction, but there was a significant difference (p < 0.05) between the suspended sediment and the < 63 μm bank sediment fraction. There were also significant differences between the concentrations of metals in the < 63 μm and the 63 μm–2 mm fractions. Generally, the Ravensbourne River did not comply with the draft UK sediment quality guidelines for the metals analysed. Conclusions This study shows the importance of identifying a suitable sediment compartment to sample for compliance with sediment quality standards. The bed and suspended sediments are the most widely used sediment compartments for sediment monitoring, but collecting sufficient mass of the < 63 μm sediment fraction for monitoring presents a challenge for urban gravel bed rivers like the Ravensbourne River. It seems appropriate to establish individual monitoring regimes for different rivers

Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization.

Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10(-9)) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10(-4)-5.79 × 10(-14)). Mechanistically, we found that the ULK4(rs6599175) SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10(-4)), whereas the IKBKE(rs17433804) SNP correlated with the number of transitional CD24(+)CD38(+) B cells (p = 4.8 × 10(-4)) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10(-4)). We also found that the CD46(rs1142469) SNP correlated with numbers of CD19(+) B cells, CD19(+)CD3(-) B cells, CD5(+)IgD(-) cells, IgM(-) cells, IgD(-)IgM(-) cells, and CD4(-)CD8(-) PBMCs (p = 4.9 × 10(-4)-8.6 × 10(-4)) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2A(rs2811710) SNP correlated with levels of CD4(+)EMCD45RO(+)CD27(-) cells (p = 9.3 × 10(-4)). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3(-), MCP-2(-), and IL20-dependent pathways

Does a multiple myeloma polygenic risk score predict overall survival of myeloma patients?

Background: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) iden-tified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival Methods: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consor-tium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associa-tions were meta-analyzed. Results: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P &lt; 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09-1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01-1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. Conclusions: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. Impact: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma

Ezetimibe added to statin therapy after acute coronary syndromes

BACKGROUND: Statin therapy reduces low-density lipoprotein (LDL) cholesterol levels and the risk of cardiovascular events, but whether the addition of ezetimibe, a nonstatin drug that reduces intestinal cholesterol absorption, can reduce the rate of cardiovascular events further is not known. METHODS: We conducted a double-blind, randomized trial involving 18,144 patients who had been hospitalized for an acute coronary syndrome within the preceding 10 days and had LDL cholesterol levels of 50 to 100 mg per deciliter (1.3 to 2.6 mmol per liter) if they were receiving lipid-lowering therapy or 50 to 125 mg per deciliter (1.3 to 3.2 mmol per liter) if they were not receiving lipid-lowering therapy. The combination of simvastatin (40 mg) and ezetimibe (10 mg) (simvastatin-ezetimibe) was compared with simvastatin (40 mg) and placebo (simvastatin monotherapy). The primary end point was a composite of cardiovascular death, nonfatal myocardial infarction, unstable angina requiring rehospitalization, coronary revascularization ( 6530 days after randomization), or nonfatal stroke. The median follow-up was 6 years. RESULTS: The median time-weighted average LDL cholesterol level during the study was 53.7 mg per deciliter (1.4 mmol per liter) in the simvastatin-ezetimibe group, as compared with 69.5 mg per deciliter (1.8 mmol per liter) in the simvastatin-monotherapy group (P<0.001). The Kaplan-Meier event rate for the primary end point at 7 years was 32.7% in the simvastatin-ezetimibe group, as compared with 34.7% in the simvastatin-monotherapy group (absolute risk difference, 2.0 percentage points; hazard ratio, 0.936; 95% confidence interval, 0.89 to 0.99; P = 0.016). Rates of pre-specified muscle, gallbladder, and hepatic adverse effects and cancer were similar in the two groups. CONCLUSIONS: When added to statin therapy, ezetimibe resulted in incremental lowering of LDL cholesterol levels and improved cardiovascular outcomes. Moreover, lowering LDL cholesterol to levels below previous targets provided additional benefit