We did not observe highly statistically signficant associations with multiple myeloma risk for any of the 70 SNPs in the present analysis. However, we observed strong suggestive associations of several SNPs in IRS1 and IL6R with risk of multiple myeloma. In the secondary analysis, we also observed suggestive associations for SNPs in IGF1 and IGFBP3. Additional SNPs in IGF1, IGFBP2, IRS2, and IL6ST may demonstrate significant associations with multiple myeloma in a larger study population. We did not observe associations for SNPs in IGFBP1, IGF1R, or IL6.
The secondary analysis provided reassurance regarding the impact of sample size on our main analytic findings. Among the SNPs that demonstrated stronger suggestive associations with multiple myeloma in the primary analysis, we observed ORs of a similar magnitude in both the original and secondary analyses when the corresponding genotype frequencies were not too sparse. The emergence of a few novel statistically significant associations in the secondary analysis suggested that we may have been unable to detect some potentially informative markers in the primary analysis due to limited sample size.
Of the SNPs included in the present analysis, only three have been previously examined in relation to risk of multiple myeloma. Consistent with previous reports (10
), the IL6 SNP rs1800795 (i.e., -174 G/C) was not associated with multiple myeloma risk in the present analysis. We did not observe an association for rs1800796 in IL6, in contrast to Cozen and colleagues (10
). The latter study reported a 2.4-fold increase (95% CI=1.2-4.7) in multiple myeloma risk among carriers of the C allele for rs1800796 when 150 cases were compared with 126 population controls (10
). The discrepancies beween the two studies may be due in part to differences in the frequency of the C allele in the study populations. Also in contrast to the present findings, Cozen et al. did not observe an association of rs8192284 (i.e., D358A) in IL6R with multiple myeloma (cases v. population controls, OR=0.9, 95% CI=0.5-1.6) but did report an association of the minor allele with obesity among the population controls (BMI ≥ 30 v. < 30 kg/m2
, OR=5.4, 95% CI=1.7-17.4) (10
). The latter finding is noteworthy because obesity has been consistently related to multiple myeloma risk (32
) and to increased secretion of IL-6 (41
Several of the SNPs for which we observed stronger suggestive associations with multiple myeloma have been associated with other IGF-1- or IL-6-related conditions, or have demonstrated functional effects on the signaling pathways. For example, the minor allele of rs1801278 (i.e., G972R) in IRS1 was associated with an increased risk of colorectal cancer (43
). Of interest, IRS-1, which is involved in insulin signaling, is also required to activate signaling pathways that mediate both anti-apoptotic and mitogenic effects of IGF-1 (44
). In IL6R, the minor allele of rs8192284 was significantly associated with higher circulating levels of IL-6 in the Nurses' Health Study population (37
), and with levels of IL-6 and the soluble form of the IL-6 receptor in other populations (46
). In the present analysis, we observed a suggestive inverse association with multiple myeloma risk for rs2373722 in IGF1. In the Nurses' Health Study, rs2373722 in IGF1 was significantly associated with mammographic density (35
); the minor (A) allele was associated with lower mammographic density, and thus the direction of association was consistent with the present findings. In addition, in the Multiethnic Cohort, participants with the C/T genotype for rs7965399 in IGF1 had a significant increase in risk of prostate cancer (23
Strengths of the present analysis include a strong a priori hypothesis based on the well-established roles of IGF-1 and IL-6 in multiple myeloma pathogenesis. We used a tag SNP approach to SNP selection, to improve the opportunity to detect as yet unknown susceptibility markers. The excellent concordance of the QC sample genotypes and low percentage of missing genotypes indicate that measurement error did not distort the findings. In addition, we matched cases to controls closely on other risk factors for multiple myeloma (age, gender) and adjusted for these factors and BMI in the analysis, so that the reported 95% CIs account for variability in risk related to those factors. The availability of additional control data for the secondary analyses enabled us to explore the impact of sample size on our results.
Limitations of the study should also be noted. It is possible that we did not include potentially informative susceptibility markers due to inadequate coverage of the genes by the selected tagging SNPs, or due to weak associations of causal and tag SNPs. Also, the inability to genotype two tagging SNPs in each of IRS2 and IL6R precluded the evaluation of markers at the SNP and haplotype level in those genes. For the two SNPs with evidence for departure from Hardy-Weinberg equilibrium, misclassification of genotypes may have biased the effect estimates, although the genotype distributions may have resulted from sampling variability rather than genotyping errors. The high concordance of genotypes that we observed in the quality control samples corroborates the latter explanation. We included both prevalent and incident male cases, which could introduce a survival bias; however, sensitivity analyses that excluded the prevalent cases yielded similar results to the main analyses. We relied upon self-reported ethnicity and did not have genotype data with which to control for potential bias due to population stratification (48
). In a recent analysis of population structure among Nurses' Health Study participants who are also included in the National Cancer Institute's Cancer Genetic Markers of Susceptibility (CGEMS) Project, fewer than 1% of the individuals who self-reported to be of European ancestry were found to have genetic markers indicative of substantial African or Asian ancestry (50
). Furthermore, we are not aware of evidence that the SNPs in the present analysis vary systematically across European populations. Therefore, although we cannot directly demonstrate a lack of this bias, we consider it unlikely that population stratification explains or has distorted the present findings. We conducted a large number of statistical tests relative to the sample size, and any of the findings may simply be due to chance. We did not perform adjustment for multiple comparisons because most of the suggestive associations were only nominally significant at best and would not have been significant after adjustment. Nonetheless, the strong a priori hypotheses and the reports of associations for some of the SNPs with IGF-1- or IL-6-related cancers, other conditions, and/or relevant functional effects, lend credibility to the present findings.
In conclusion, we report findings that are consistent with the hypothesis that inherited variation in genes that encode molecules important to IGF-1 and IL-6 signaling may influence susceptibility to multiple myeloma. For all but three of the variants that we examined, the present study is the first to explore their association with multiple myeloma. Future studies to examine the interaction of IGF-1- and IL-6-related susceptibility markers with obesity are of interest (32
). In addition, because only preliminary conclusions can be drawn from the present analysis regarding the association of the IGF-1- or IL-6-related genes with risk of multiple myeloma, confirmation of the present findings in both Caucasian and non-Caucasian populations is of paramount interest. The identification of variants in IGF-1 and IL-6 signaling-related genes that are associated with risk of multiple myeloma could provide valuable clues to mechanisms of susceptibility to this malignancy, which may in turn inform the development of effective strategies for prevention.