Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2023 May 9;24(10):8500.
doi: 10.3390/ijms24108500.

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

Esther Clavero  1 , José Manuel Sanchez-Maldonado  2   3 , Angelica Macauda  4 , Rob Ter Horst  5   6 , Belém Sampaio-Marques  7 , Artur Jurczyszyn  8 , Alyssa Clay-Gilmour  9   10 , Angelika Stein  4 , Michelle A T Hildebrandt  11 , Niels Weinhold  12   13 , Gabriele Buda  14 , Ramón García-Sanz  15 , Waldemar Tomczak  16 , Ulla Vogel  17 , Andrés Jerez  18 , Daria Zawirska  19 , Marzena Wątek  20   21 , Jonathan N Hofmann  22 , Stefano Landi  23 , John J Spinelli  24   25 , Aleksandra Butrym  26   27 , Abhishek Kumar  28   29 , Joaquín Martínez-López  30 , Sara Galimberti  14 , María Eugenia Sarasquete  15 , Edyta Subocz  31 , Elzbieta Iskierka-Jażdżewska  32 , Graham G Giles  33   34   35 , Malwina Rybicka-Ramos  36 , Marcin Kruszewski  37 , Niels Abildgaard  38 , Francisco García Verdejo  39 , Pedro Sánchez Rovira  39 , Miguel Inacio da Silva Filho  40 , Katalin Kadar  41 , Małgorzata Razny  42 , Wendy Cozen  43 , Matteo Pelosini  44 , Manuel Jurado  1   3   45 , Parveen Bhatti  46   47 , Marek Dudzinski  48 , Agnieszka Druzd-Sitek  49 , Enrico Orciuolo  14 , Yang Li  5   50 , Aaron D Norman  10   51 , Jan Maciej Zaucha  52 , Rui Manuel Reis  53   54 , Miroslaw Markiewicz  48 , Juan José Rodríguez Sevilla  55 , Vibeke Andersen  56 , Krzysztof Jamroziak  57 , Kari Hemminki  58   59 , Sonja I Berndt  22 , Vicent Rajkumar  60 , Grzegorz Mazur  61 , Shaji K Kumar  60 , Paula Ludovico  7 , Arnon Nagler  62 , Stephen J Chanock  22 , Charles Dumontet  63 , Mitchell J Machiela  22 , Judit Varkonyi  64 , Nicola J Camp  65 , Elad Ziv  66 , Annette Juul Vangsted  67 , Elizabeth E Brown  68 , Daniele Campa  23 , Celine M Vachon  10 , Mihai G Netea  5   69 , Federico Canzian  4 , Asta Försti  70   71 , Juan Sainz  2   3   72
Affiliations
Meta-Analysis

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

Esther Clavero et al. Int J Mol Sci. .

Abstract

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.

Keywords: autophagy; genetic susceptibility; genetic variants; multiple myeloma.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Functional impact of the ULK4rs6599175 and IKBKErs17433804 SNPs [A-C]. (A) Vitamin D3 levels (pg/mL) according to the ULK4rs6599175 SNP; (B) Numbers of transitional CD24+CD38+ B cells according to the IKBKErs17433804 SNP; (C) Serum levels of MCP-2 according to the IKBKErs17433804 SNP.
Figure 2
Figure 2
Functional impact of the CD46rs1142469 SNP (A–G). (A) Numbers of CD19+ B cells according to the CD46rs1142469 SNP; (B) Numbers of CD19+CD3− B cells according to the CD46rs1142469 SNP; (C) Numbers of IgD−CD5+ cells according to the CD46rs1142469 SNP; (D) Numbers of IgM− cells according to the CD46rs1142469 SNP; (E) Numbers of IgD+IgM− cells according to the CD46rs1142469 SNP; (F) Numbers of CD4+CD8− PBMCs according to the CD46rs1142469 SNP; and (G) Serum IL20 levels (ng/mL) according to the CD46rs1142469 SNP.
Figure 3
Figure 3
Functional impact of the CDKN2Ars2811710 and USP10rs7202154 SNPs. (A) Numbers of CD4+ Effector Memory CD45RO−CD27− cells according to the CDKN2Ars2811710 SNP; (B) p62 synthesis according to the USP10rs7202154 SNP; (C) LC3 synthesis according to the USP10rs7202154 SNP.
Figure 3
Figure 3
Functional impact of the CDKN2Ars2811710 and USP10rs7202154 SNPs. (A) Numbers of CD4+ Effector Memory CD45RO−CD27− cells according to the CDKN2Ars2811710 SNP; (B) p62 synthesis according to the USP10rs7202154 SNP; (C) LC3 synthesis according to the USP10rs7202154 SNP.
Figure 4
Figure 4
Flow diagram of the study.
See this image and copyright information in PMC

References

    1. Palumbo A., Anderson K. Multiple myeloma. N. Engl. J. Med. 2011;364:1046–1060. doi: 10.1056/NEJMra1011442. - DOI - PubMed
    1. Kyle R.A., Gertz M.A., Witzig T.E., Lust J.A., Lacy M.Q., Dispenzieri A., Fonseca R., Rajkumar S.V., Offord J.R., Larson D.R., et al. Review of 1027 patients with newly diagnosed multiple myeloma. Mayo Clin. Proc. 2003;78:21–33. doi: 10.4065/78.1.21. - DOI - PubMed
    1. Kastritis E., Zagouri F., Symeonidis A., Roussou M., Sioni A., Pouli A., Delimpasi S., Katodritou E., Michalis E., Michael M., et al. Preserved levels of uninvolved immunoglobulins are independently associated with favorable outcome in patients with symptomatic multiple myeloma. Leukemia. 2014;28:2075–2079. doi: 10.1038/leu.2014.110. - DOI - PubMed
    1. Bradwell A., Harding S., Fourrier N., Mathiot C., Attal M., Moreau P., Harousseau J.L., Avet-Loiseau H. Prognostic utility of intact immunoglobulin Ig’kappa/Ig’lambda ratios in multiple myeloma patients. Leukemia. 2013;27:202–207. doi: 10.1038/leu.2012.159. - DOI - PMC - PubMed
    1. Hoang B., Benavides A., Shi Y., Frost P., Lichtenstein A. Effect of autophagy on multiple myeloma cell viability. Mol. Cancer Ther. 2009;8:1974–1984. doi: 10.1158/1535-7163.MCT-08-1177. - DOI - PubMed

Publication types