Beyond the Social Determinants of Learning™ A Walden University Position Paper

The Social Determinants of Health (SDOH), presented by the World Health Organization (WHO) and a cross-organizational global commission in the early 2000s, provide an understanding of health status of individuals and communities. SDOH consider societal forces and conditions such as housing, work conditions, environment, and education (Braveman & Gottlieb, 2014; WHO, 2021). The U.S. Department of Health and Human Services (n.d.) launched a “Healthy People 2030” initiative, addressing five key social determinants of health and offering a framework from which organizations can build strategy: 1. Healthcare access and quality 2. Education access and quality 3. Social and community context 4. Economic stability 5. Neighborhood and built environment As leaders in preparing provisioners of healthcare, Walden’s nursing and healthcare programs operate from the Social Determinants of Health & Healthcare (SDOH&H) framework (emphasizing both health and healthcare) and address the SDOH&H in every course

A polygenic risk score for multiple myeloma risk prediction

There is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53–4.69, p = 3.55 × 10−15 for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34–4.33, p = 1.62 × 10−13 for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population

Expression quantitative trait loci of genes predicting outcome are associated with survival of multiple myeloma patients

Canadian Institutes of Health Research, Grant/ Award Number: 81274; Huntsman Cancer Institute Pilot Funds; Leukemia Lymphoma Society, Grant/Award Number: 6067-09; the National Institute of Health/National Cancer Institute, Grant/Award Numbers: P30 CA016672, P30 CA042014, P30 CA13148, P50 CA186781, R01 CA107476, R01 CA134674, R01 CA168762, R01 CA186646, R01 CA235026, R21 CA155951, R25 CA092049, R25 CA47888, U54 CA118948; Utah Population Database, Utah Cancer Registry, Huntsman Cancer Center Support Grant, Utah State Department of Health, University of Utah; VicHealth, Cancer Council Victoria, Australian National Health and Medical Research Council, Grant/Award Numbers: 1074383, 209057, 396414; Victorian Cancer Registry, Australian Institute of Health and Welfare, Australian National Death Index, Australian Cancer Database; Mayo Clinic Cancer Center; University of Pisa and DKFZThe authors thank all site investigators that contributed to the studies within the Multiple Myeloma Working Group (Interlymph Consortium), staff involved at each site and, most importantly, the study participants for their contributions that made our study possible. This work was partially supported by intramural funds of University of Pisa and DKFZ. This work was supported in part by the National Institute of Health/National Cancer Institute (R25 CA092049, P30 CA016672, R01 CA134674, P30 CA042014, R01 CA186646, R21 CA155951, U54 CA118948, P30 CA13148, R25 CA47888, R01 CA235026, R01 CA107476, R01 CA168762, P50 CA186781 and the NCI Intramural Research Program), Leukemia Lymphoma Society (6067-09), Huntsman Cancer Institute Pilot Funds, Utah PopulationDatabase, Utah Cancer Registry, Huntsman Cancer Center Support Grant, Utah StateDepartment of Health, University of Utah, Canadian Institutes of Health Research (Grant number 81274), VicHealth, Cancer Council Victoria, Australian National Health and Medical Research Council (Grants 209057, 396414, 1074383), Victorian Cancer Registry, Australian Institute of Health and Welfare, Australian National Death Index, Australian Cancer Database and the Mayo Clinic Cancer Center.Open Access funding enabled and organized by ProjektDEAL.The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.Gene expression profiling can be used for predicting survival in multiple myeloma (MM) and identifying patients who will benefit from particular types of therapy. Some germline single nucleotide polymorphisms (SNPs) act as expression quantitative trait loci (eQTLs) showing strong associations with gene expression levels. We performed an association study to test whether eQTLs of genes reported to be associated with prognosis of MM patients are directly associated with measures of adverse outcome. Using the genotype-tissue expression portal, we identified a total of 16 candidate genes with at least one eQTL SNP associated with their expression with P < 10(-7) either in EBV-transformed B-lymphocytes or whole blood. We genotyped the resulting 22 SNPs in 1327 MM cases from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and examined their association with overall survival (OS) and progression-free survival (PFS), adjusting for age, sex, country of origin and disease stage. Three polymorphisms in two genes (TBRG4-rs1992292, TBRG4-rs2287535 and ENTPD1-rs2153913) showed associations with OS at P < .05, with the former two also associated with PFS. The associations of two polymorphisms in TBRG4 with OS were replicated in 1277 MM cases from the International Lymphoma Epidemiology (InterLymph) Consortium. A meta-analysis of the data from IMMEnSE and InterLymph (2579 cases) showed that TBRG4-rs1992292 is associated with OS (hazard ratio = 1.14, 95% confidence interval 1.04-1.26, P = .007). In conclusion, we found biologically a plausible association between a SNP in TBRG4 and OS of MM patients.Canadian Institutes of Health Research (CIHR) 81274Huntsman Cancer Institute Pilot FundsLeukemia and Lymphoma Society 6067-09United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Cancer Institute (NCI) P30 CA016672 P30 CA042014 P30 CA13148 P50 CA186781 R01 CA107476 R01 CA134674 R01 CA168762 R01 CA186646 R01 CA235026 R21 CA155951 R25 CA092049 R25 CA47888 U54 CA118948Utah Population Database, Utah Cancer Registry, Huntsman Cancer Center Support Grant, Utah State Department of Health, University of UtahVicHealth, Cancer Council Victoria, Australian National Health and Medical Research Council 1074383 209057 396414Victorian Cancer Registry, Australian Institute of Health and Welfare, Australian National Death Index, Australian Cancer DatabaseMayo Clinic Cancer CenterUniversity of PisaHelmholtz Associatio

Identification of miRSNPs associated with the risk of multiple myeloma

Accepted articleMultiple myeloma (MM) is a malignancy of plasma cells usually infiltrating the bone marrow, associated with the production of a monoclonal immunoglobulin (M protein) which can be detected in the blood and/or urine. Multiple lines of evidence suggest that genetic factors are involved in MM pathogenesis, and several studies have identified single nucleotide polymorphisms (SNPs) associated with the susceptibility to the disease. SNPs within miRNA-binding sites in target genes (miRSNPs) may alter the strength of miRNA-mRNA interactions, thus deregulating protein expression. MiRSNPs are known to be associated with risk of various types of cancer, but they have never been investigated in MM. We performed an in silico genome-wide search for miRSNPs predicted to alter binding of miRNAs to their target sequences. We selected 12 miRSNPs and tested their association with MM risk. Our study population consisted of 1,832 controls and 2,894 MM cases recruited from seven European countries and Israel in the context of the IMMEnSE (International Multiple Myeloma rESEarch) consortium. In this population two SNPs showed an association with p<0.05: rs286595 (located in gene MRLP22) and rs14191881 (located in gene TCF19). Results from IMMEnSE were meta-analyzed with data from a previously published genome-wide association study (GWAS). The SNPs rs13409 (located in the 3UTR of the POU5F1 gene), rs1419881 (TCF19), rs1049633, rs1049623 (both in DDR1) showed significant associations with MM risk. In conclusion, we sought to identify genetic polymorphisms associated with MM risk starting from genome-wide prediction of miRSNPs. For some mirSNPs, we have shown promising associations with MM risk. What's new? Even though deregulation of miRNA expression has been associated with human cancers little information is available regarding their relation with MM susceptibility. We performed an in silico genome-wide search for miRSNPs and selected the most promising ones for an association study. The SNPs with the strongest associations with MM risk are localized in genes which have never been related with MM.This work was partially funded by: intramural funds of German Cancer Research Center (DKFZ), Grant ref. HUS412A1271 from the “Gerencia Regional de Salud de la Junta de Castilla y Léon”. This work was supported by grants from the Instituto de Salud Carlos III (Madrid, Spain; PI12/02688). Catalan Government DURSI grant 2014SGR647 and Instituto de Salud Carlos III, co7funded by FEDER funds –a way to build Europe– grants PI11701439 and PIE13/00022info:eu-repo/semantics/publishedVersio

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)

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 \u3c 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 Chemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 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 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

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 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 Chemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 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 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).Peer reviewe

The assessment of manufacturing qualities of the HV machine insulation on the base of low frequency measurements

This paper presents degradation mechanism of epoxy-mica-glass insulation and influence of service conditions on kinetics of this mechanism. But the most important factor here is production quality. Basics of dielectric spectroscopy in time and frequency domain were described and application of this method for estimation of HV insulation condition. Research conducted on insulation models showed that good indicators of insulation condition are value of charge and time of relaxation in low frequencies range. There was given an example of FDS measurements application for estimation of quality of technology in postproduction tests. This method is very accurate and allows to identify defective production technology and insulation aged in service