Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization
Abstract
:Simple Summary
Abstract
1. Introduction
2. Results
2.1. Association of Autophagy-Related Polymorphisms with the Risk of Developing MM
2.2. Functional Relevance of Autophagy-Related SNPs
3. Discussion
4. Materials and Methods
4.1. Study Populations
4.2. SNP Selection
4.3. Replication Cohort, Genotyping, and Meta-Analysis
4.4. Functional Effect of the Autophagy-Related Variants on Immune Responses
4.5. Correlation between Autophagy-Related SNPs and Steroid Hormone Levels
4.6. Impact of Autophagy-Related Variants on the Autophagy Flux
4.7. In Silico Functional Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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German GWAS (n = 3619) | InterLymph GWAS (n = 5100) | Meta-Analysis (n = 8719) | |||||||
---|---|---|---|---|---|---|---|---|---|
SNP | Gene | A1 | OR (95%CI) | p | OR (95%CI) | p | OR (95%CI) | p | PHet |
rs2299864 | ATG5 | T | 1.18 (1.03–1.33) | 0.015 | 1.24 (1.12–1.36) | 1.96 × 10−5 | 1.22 (1.13–1.32) | 1.48 × 10−6 | 0.545 |
rs1142469 | CD46 | A | 1.14 (1.02–1.25) | 0.020 | 1.11 (1.02–1.21) | 0.012 | 1.12 (1.05–1.20) | 9.68 × 10−4 | 0.694 |
rs2811710 | CDKN2A | C | 1.15 (1.03–1.29) | 0.011 | 1.11 (1.02–1.20) | 0.0176 | 1.12 (1.05–1.20) | 5.28 × 10−4 | 0.623 |
rs143309009 | CTSD | G | 2.22 (1.46–3.38) | 2.1 × 10−4 | 1.24 (0.89–1.72) | 0.2114 | 1.55 (1.20–2.01) | 9.14 × 10−4 | 0.032 |
rs11064698 | HSPB8 | T | 1.53 (1.05–2.24) | 0.027 | 1.16 (1.06–1.27) | 0.0012 | 1.18 (1.08–1.28) | 2.46 × 10−4 | 0.163 |
rs12739461 | IKBKE | T | 1.18 (1.05–1.32) | 0.0053 | 1.10 (1.01–1.20) | 0.028 | 1.13 (1.05–1.21) | 6.36 × 10−4 | 0.337 |
rs2297546 | IKBKE | G | 1.22 (1.09–1.37) | 7.2 × 10−4 | 1.09 (1.01–1.18) | 0.037 | 1.13 (1.06–1.21) | 2.25 × 10−4 | 0.110 |
rs17433804 | IKBKE | C | 1.24 (1.09–1.41) | 0.0011 | 1.08 (1.00–1.18) | 0.066 | 1.13 (1.05–1.21) | 7.51 × 10−4 | 0.086 |
rs1884158 | PARK2 | T | 1.21 (1.08–1.35) | 0.00081 | 1.09 (1.00–1.18) | 0.049 | 1.14 (1.06–1.21) | 3.07 × 10−4 | 0.141 |
rs34048269 | RPTOR | A | 1.30 (1.14–1.48) | 1.3 × 10−4 | 1.06 (0.97–1.17) | 0.199 | 1.14 (1.05–1.23) | 0.0024 | 0.013 |
rs6599175 | ULK4 | C | 1.33 (1.16–1.53) | 5.7 × 10−5 | 1.25 (1.13–1.39) | 3.6 × 10−5 | 1.28 (1.18–1.39) | 4.00 × 10−9 | 0.482 |
rs7202154 | USP10 | G | 1.31 (1.06–1.62) | 0.011 | 1.23 (1.05–1.44) | 0.0126 | 1.26 (1.11–1.43) | 3.83 × 10−4 | 0.640 |
German GWAS (n = 3619) | InterLymph GWAS (n = 5100) | IMMEnSE (n = 3957) | Meta-Analysis (n = 12676) | ||||||
---|---|---|---|---|---|---|---|---|---|
Gene_SNP | OR (95%CI) | p | OR (95%CI) | p | OR (95%CI) | p | OR (95%CI) | PMeta | PHet |
ATG5_rs2299864T | 1.18 (1.03–1.33) | 0.015 | 1.24 (1.12–1.36) | 1.96 × 10−5 | 1.07 (0.92–1.23) | 0.40 | 1.18 (1.11–1.27) | 1.3 × 10−6 Ϯ | 0.254 |
CD46_rs1142469A | 1.14 (1.02–1.25) | 0.020 | 1.11 (1.02–1.21) | 0.012 | 1.09 (0.96–1.23) | 0.19 | 1.12 (1.05–1.18) | 2.2 × 10−4 | 0.851 |
CDKN2A_rs2811710C | 1.15 (1.03–1.29) | 0.011 | 1.11 (1.02–1.20) | 0.0176 | 1.18 (1.06–1.32) | 0.003 | 1.14 (1.08–1.20) | 7.0 × 10−6 Ϯ | 0.666 |
CTSD_rs143309009G | 2.22 (1.46–3.38) | 2.1 × 10−4 | 1.24 (0.89–1.72) | 0.2114 | 0.72 (0.47–1.10) | 0.13 | 1.26 (1.01–1.57) | 0.042 | 0.001 |
HSPB8_rs11064698T | 1.53 (1.05–2.24) | 0.027 | 1.16 (1.06–1.27) | 0.0012 | 0.84 (0.72–0.99) | 0.035 | 1.09 (1.01–1.18) | 0.029 | 0.001 |
IKBKE_rs12739461T | 1.18 (1.05–1.32) | 0.0053 | 1.10 (1.01–1.20) | 0.028 | 1.01 (0.90–1.14) | 0.88 | 1.10 (1.03–1.16) | 0.0022 | 0.179 |
IKBKE_rs2297546G | 1.22 (1.09–1.37) | 7.2 × 10−4 | 1.09 (1.01–1.18) | 0.037 | 1.00 (0.90–1.12) | 0.94 | 1.10 (1.04–1.16) | 0.0013 | 0.047 |
IKBKE_rs17433804C | 1.24 (1.09–1.41) | 0.0011 | 1.08 (1.00–1.18) | 0.066 | 1.16 (1.02–1.31) | 0.024 | 1.14 (1.07–1.21) | 4.6 × 10−5 Ϯ | 0.213 |
PARK2_rs1884158T | 1.21 (1.08–1.35) | 0.00081 | 1.09 (1.00–1.18) | 0.049 | 1.04 (0.91–1.19) | 0.56 | 1.11 (1.05–1.18) | 4.5 × 10−4 | 0.184 |
RPTOR_rs34048269A | 1.30 (1.14–1.48) | 1.3 × 10−4 | 1.06 (0.97–1.17) | 0.199 | 1.04 (0.91–1.19) | 0.56 | 1.11 (1.04–1.19) | 0.0017 | 0.024 |
ULK4_rs6599175C | 1.33 (1.16–1.53) | 5.7 × 10−5 | 1.25 (1.13–1.39) | 3.6 × 10−5 | 1.37 (1.21–1.56) | 2.6 × 10−6 | 1.31 (1.22–1.40) | 5.8 × 10−14 Ϯ | 0.522 |
USP10_rs7202154G | 1.31 (1.06–1.62) | 0.011 | 1.23 (1.05–1.44) | 0.0126 | 0.93 (0.76–1.15) | 0.50 | 1.16 (1.04–1.29) | 0.0075 | 0.048 |
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Clavero, E.; Sanchez-Maldonado, J.M.; Macauda, A.; Ter Horst, R.; Sampaio-Marques, B.; Jurczyszyn, A.; Clay-Gilmour, A.; Stein, A.; Hildebrandt, M.A.T.; Weinhold, N.; et al. Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization. Int. J. Mol. Sci. 2023, 24, 8500. https://doi.org/10.3390/ijms24108500
Clavero E, Sanchez-Maldonado JM, Macauda A, Ter Horst R, Sampaio-Marques B, Jurczyszyn A, Clay-Gilmour A, Stein A, Hildebrandt MAT, Weinhold N, et al. Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization. International Journal of Molecular Sciences. 2023; 24(10):8500. https://doi.org/10.3390/ijms24108500
Chicago/Turabian StyleClavero, Esther, José Manuel Sanchez-Maldonado, Angelica Macauda, Rob Ter Horst, Belém Sampaio-Marques, Artur Jurczyszyn, Alyssa Clay-Gilmour, Angelika Stein, Michelle A. T. Hildebrandt, Niels Weinhold, and et al. 2023. "Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization" International Journal of Molecular Sciences 24, no. 10: 8500. https://doi.org/10.3390/ijms24108500