Cozen, Wendy

Background: Perinatal and early-life factors may influence non-Hodgkin lymphoma (NHL) risk, but study results have been mixed and exposure data for childhood ages are limited. Herein, we investigated associations of these exposures with risk of NHL and common subtypes. Methods: This case–control study included 2280 NHL cases and 2253 controls, enrolled from 2002 to 2014 at the Mayo Clinic Rochester. Self-reported perinatal and early-life exposures included maternal age at birth, birth order, birthweight, time breastfed, height and weight at ages 7, 12, and 18 years relative to peers, and age and weight when growth ceased. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for design variables and potential confounders. Linear trend tests were performed for ordinal variables, and heterogeneity tests were performed to evaluate whether associations varied across four NHL subtypes. Results: After multivariable adjustment, greater birth weight (OR = 1.15 for quartile 4 vs. 1; p-trend = 0.04), weight at age 7 relative to peers (compared to average, OR = 1.05 for heavy and OR = 0.87 for thin; p-trend = 0.002), and weight when growth ceased (OR = 1.30 for quartile 4 vs. 1; p-trend < 0.001) were associated with increased NHL risk. An inverse association was observed for breastfeeding duration with NHL risk (OR = 0.77 for >6 months vs. never; 95% CI 0.61–0.97). Associations did not significantly vary by major NHL subtype (p-heterogeneity > 0.05). Other perinatal and early-life exposures were not associated with NHL risk. Conclusions: Greater body weight at birth and through childhood may be associated with increased NHL risk, potentially extending the life-course perspective on adiposity and lymphomagenesis, with implications for prevention.

Abstract Background: Genome-wide association studies (GWAS) of multiple myeloma in populations of European ancestry (EA) identified and confirmed 24 susceptibility loci. For other cancers (e.g., colorectum and melanoma), risk loci have also been associated with patient survival. Methods: We explored the possible association of all the known risk variants and their polygenic risk score (PRS) with multiple myeloma overall survival (OS) in multiple populations of EA [the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the International Lymphoma Epidemiology consortium, CoMMpass, and the German GWAS] for a total of 3,748 multiple myeloma cases. Cox proportional hazards regression was used to assess the association between each risk SNP with OS under the allelic and codominant models of inheritance. All analyses were adjusted for age, sex, country of origin (for IMMEnSE) or principal components (for the others) and disease stage (ISS). SNP associations were meta-analyzed. Results: SNP associations were meta-analyzed. From the meta-analysis, two multiple myeloma risk SNPs were associated with OS (P &lt; 0.05), specifically POT1-AS1-rs2170352 [HR = 1.37; 95% confidence interval (CI) = 1.09–1.73; P = 0.007] and TNFRSF13B-rs4273077 (HR = 1.19; 95% CI = 1.01–1.41; P = 0.04). The association between the combined 24 SNP MM-PRS and OS, however, was not significant. Conclusions: Overall, our results did not support an association between the majority of multiple myeloma risk SNPs and OS. Impact: This is the first study to investigate the association between multiple myeloma PRS and OS in multiple myeloma.

Abstract Background: A previous International Lymphoma Epidemiology (InterLymph) Consortium evaluation of joint associations between five immune gene variants and autoimmune conditions reported interactions between B-cell response-mediated autoimmune conditions and the rs1800629 genotype on risk of B-cell non–Hodgkin lymphoma (NHL) subtypes. Here, we extend that evaluation using NHL subtype-specific polygenic risk scores (PRS) constructed from loci identified in genome-wide association studies of three common B-cell NHL subtypes. Methods: In a pooled analysis of NHL cases and controls of Caucasian descent from 14 participating InterLymph studies, we evaluated joint associations between B-cell–mediated autoimmune conditions and tertile (T) of PRS for risk of diffuse large B-cell lymphoma (DLBCL; n = 1,914), follicular lymphoma (n = 1,733), and marginal zone lymphoma (MZL; n = 407), using unconditional logistic regression. Results: We demonstrated a positive association of DLBCL PRS with DLBCL risk [T2 vs. T1: OR = 1.24; 95% confidence interval (CI), 1.08–1.43; T3 vs. T1: OR = 1.81; 95% CI, 1.59–2.07; P-trend (Ptrend) &lt; 0.0001]. DLBCL risk also increased with increasing PRS tertile among those with an autoimmune condition, being highest for those with a B-cell–mediated autoimmune condition and a T3 PRS [OR = 6.46 vs. no autoimmune condition and a T1 PRS, Ptrend &lt; 0.0001, P-interaction (Pinteraction) = 0.49]. Follicular lymphoma and MZL risk demonstrated no evidence of joint associations or significant Pinteraction. Conclusions: Our results suggest that PRS constructed from currently known subtype-specific loci may not necessarily capture biological pathways shared with autoimmune conditions. Impact: Targeted genetic (PRS) screening among population subsets with autoimmune conditions may offer opportunities for identifying those at highest risk for (and early detection from) DLBCL.

Purpose: Multiple myeloma (MM) treatment has changed tremendously, with significant improvement in patient out-comes. One group with a suboptimal benefit is patients with high-risk cytogenetics, as tested by conventional karyotyping or fluorescence in situ hybridization (FISH). Methodology for these tests has been published, but not necessarily standardized. Methods: We address variability in the testing and reporting methodology for MM cytogenetics in the United States using the ongoing African American Multiple Myeloma Study (AAMMS). We evaluated clinical and cytogenetic data from 1,221 patients (1,161 with conventional karyotyping and 976 with FISH) tested between 1998 and 2016 across 58 laboratories nationwide. Results: Interlab and intralab variability was noted for the number of cells analyzed for karyotyping, with a significantly higher number of cells analyzed in patients in whom cytogenetics were normal (P 5.0025). For FISH testing, CD138-positive cell enrichment was used in 29.7% of patients and no enrichment in 50% of patients, whereas the remainder had unknown status. A significantly smaller number of cells was analyzed for patients in which CD138 cell enrichment was used compared with those without such enrichment (median, 50 v 200; P, .0001). A median of 7 loci probes (range, 1-16) were used for FISH testing across all laboratories, with variability in the loci probed even within a given laboratory. Chromosome 13–related abnormalities were the most frequently tested abnormality (n5956; 97.9%), and t(14;16) was the least frequently tested abnormality (n 5 119; 12.2%). Conclusions: We report significant variability in cytogenetic testing across the United States for MM, potentially leading to variability in risk stratification, with possible clinical implications and personalized treatment approaches.