Risk Alleles for Multiple Myeloma Susceptibility in ADME Genes

Our plain-English summary of Risk Alleles for Multiple Myeloma Susceptibility in ADME Genes, by F. Scionti, G. Agapito, D. Caracciolo, et al (Cells, 2022).

The study

• Authors: F. Scionti, G. Agapito, D. Caracciolo, C. Riillo, K. Grillone, M. Cannataro, M.T. Di Martino, P. Tagliaferri, P. Tassone, M. Arbitrio
• Journal: Cells
• Published: 2022;11(2)
• Cited by: 12 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

The cause of multiple myeloma (MM) remains largely unknown. Several pieces of evidence support the involvement of genetic and multiple environmental factors (i.e., chemical agents) in MM onset. The inter-individual variability in the bioactivation, detoxification, and clearance of chemical carcinogens such as asbestos, benzene, and pesticides might increase the MM risk. This inter-individual variability can be explained by the presence of polymorphic variants in absorption, distribution, metabolism, and excretion (ADME) genes. Despite the high relevance of this issue, few studies have focused on the inter-individual variability in ADME genes in MM risk. To identify new MM susceptibility loci, we performed an extended candidate gene approach by comparing high-throughput genotyping data of 1936 markers in 231 ADME genes on 64 MM patients and 59 controls from the CEU population. Differences in genotype and allele frequencies were validated using an internal control group of 35 non-cancer samples from the same geographic area as the patient group. We detected an association between MM risk and ADH1B rs1229984 (OR = 3.78; 95% CI, 1.18-12.13; p = 0.0282), PPARD rs6937483 (OR = 3.27; 95% CI, 1.01-10.56; p = 0.0479), SLC28A1 rs8187737 (OR = 11.33; 95% CI, 1.43-89.59; p = 0.005), SLC28A2 rs1060896 (OR = 6.58; 95% CI, 1.42-30.43; p = 0.0072), SLC29A1 rs8187630 (OR = 3.27; 95% CI, 1.01-10.56; p = 0.0479), and ALDH3A2 rs72547554 (OR = 2.46; 95% CI, 0.64-9.40; p = 0.0293). The prognostic value of these genes in MM was investigated in two public datasets showing that shorter overall survival was associated with low expression of ADH1B and SLC28A1. In conclusion, our proof-of-concept findings provide novel insights into the genetic bases of MM susceptibility.

In plain English

This brief report was a genetic study of multiple myeloma, a blood cancer. Asbestos appeared only in the background, as one of several chemicals that might raise myeloma risk. The study did not measure asbestos or any other exposure in its participants. The authors tested 1936 genetic markers in 231 genes involved in how the body handles chemicals. They studied 64 myeloma patients enrolled in Catanzaro, Italy, between 2012 and 2017. They compared them with 59 people from a public European-ancestry reference group (CEU) and with 35 local non-cancer samples. One variant, SLC28A2 rs1060896, was associated with myeloma risk against both groups (odds ratio 6.58; 95% CI 1.42 to 30.43, against the local group). Five other variants were also reported as associated against the local group. These were absent in the reference group and rare locally. They included SLC28A1 rs8187737 (odds ratio 11.33; 95% CI 1.43 to 89.59). In two public patient datasets, low expression of the ADH1B and SLC28A1 genes was associated with shorter survival. The authors called their findings preliminary. They noted the small sample size and the lack of validation in an independent population.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Brief report; genetic case-control association study using an extended candidate gene approach (genotyping array), with an analysis of gene expression and survival in public datasets and a pathway enrichment analysis
• Who was studied: 64 multiple myeloma patients at diagnosis, enrolled February 2012 to June 2017 at Mater Domini Hospital, Magna Graecia University, Catanzaro, Italy. They were compared with 59 CEU HapMap reference samples and with an internal group of 35 non-cancer samples from the same geographic area. Survival analysis used public datasets of 414 untreated and 264 relapsed myeloma patients.
• Exposure: Inherited variants (SNPs) in absorption, distribution, metabolism and excretion (ADME) genes. Asbestos, benzene, dioxin and pesticides are named only in the introduction as examples of chemical carcinogens. No exposure to asbestos or any chemical was measured.
• Main results:
  • 738 SNPs met the quality criteria for analysis
  • SLC28A2 rs1060896 was associated with myeloma risk compared with CEU controls (p = 0.0125). The association was confirmed against the internal control group (OR = 6.58; 95% CI, 1.42 to 30.43; p = 0.0072).
  • Seven variant alleles in seven genes were absent in the CEU control group and over-represented in the myeloma patients
  • Five of these seven alleles were found at very low frequency in the internal control group and were reported as associated with myeloma risk. Two (POR rs2286824 and SLC19A1 rs60881836) remained absent and were excluded from further analysis.
  • Myeloma patients compared with internal controls, by variant: ADH1B rs1229984 OR = 3.78 (95% CI, 1.18 to 12.13; p = 0.0282); PPARD rs6937483 OR = 3.27 (95% CI, 1.01 to 10.56; p = 0.0479); SLC28A1 rs8187737 OR = 11.33 (95% CI, 1.43 to 89.59; p = 0.005).
  • Myeloma patients compared with internal controls, by variant: SLC29A1 rs8187630 OR = 3.27 (95% CI, 1.01 to 10.56; p = 0.0479); ALDH3A2 rs72547554 OR = 2.46 (95% CI, 0.64 to 9.40; p = 0.0293).
  • Cross-validation of the selected SNPs within the myeloma dataset gave an accuracy of 94.99%
  • In two public datasets of myeloma patients (414 and 264 patients), low expression of ADH1B and SLC28A1 was associated with shorter overall survival. This analysis used gene expression, not the patients' genotypes.
  • Pathway enrichment analysis identified 14 pathways involving the listed genes
• The authors' conclusion: The authors concluded that their proof-of-concept study gives preliminary evidence that these variants may be genetic indicators of multiple myeloma risk. They said the findings need validation in a larger, independent group and in other populations.
• Limitations the authors state:
  • Small sample size
  • No validation of the findings in an independent population
  • Survival analysis was limited to gene expression values, not genotype classes
  • No functional studies of the SNPs and no direct mechanistic biological insights
  • The findings did not replicate genetic loci linked to myeloma risk in earlier studies

Topics

Medical terms in this study, explained in our Lexicon: Myeloma, Overall Survival.

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