Liebow, Mark

AbstractEpidemiologic studies show an increased risk of non‐Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen‐stimulation in one disease leads to another. Here we assess shared genetic risk in genome‐wide‐association‐studies (GWAS).Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B‐cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta‐analysis.Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta‐analysis (combing AD with NHL) implicated genes of apoptosis and telomere length.This GWAS‐based analysis four NHL subtypes and three ADs revealed few weakly‐associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.

Abstract Background: Chronic lymphocytic leukemia (CLL) is a lymphoid malignancy with a strong genetic component. There are over 30 common single nucleotide polymorphisms (SNPs) associated with the risk of CLL. Moreover, in the InterLymph Subtypes Project a number of non-genetic exposures have been found to be associated with CLL, including family history (FH), height, history of atopic conditions, UV radiation, and farming exposures. However there has not been a study evaluating the joint effects among these genetic and non-genetic factors with CLL risk. Methods: Using the Mayo Clinic CLL case-control study of 587 newly diagnosed CLL cases and 790 controls, we performed analyses evaluating joint effects of genetic and non-genetic factors. For genetic effects, we computed a polygenetic risk score (PRS), a weighted averaged of the number of risk alleles across 34 SNPs, with the weights being the log of the odds ratio for each SNP. Exposure data was available for 65% of the cases and 79% of the controls. We evaluated individual and joint associations of FH of any hematological malignancy, total sun exposure categorized by quartiles based on the controls, ever living or working on a farm, any atopy, any allergies, asthma, height, and PRSs categorized by quintiles based on the controls. Multivariate logistic regression analyses were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Results: In our preliminary results, the frequency of CLL cases in the upper PRS quintile was 49% while in the lowest quintile only 5%. The PRS has a strong evidence of association with CLL (OR= 3.04, CI =2.20-4.20 for highest versus the middle quintile). When adjusting for PRS, we still found a positive association with FH for any hematological malignancy (OR = 1.90, CI = 1.25-2.88), FH of non-Hodgkin lymphoma (OR = 2.02, CI = 1.08-3.79), and FH of leukemia (OR = 1.73, CI = 0.98-3.07). When stratifying by FH, the upper quintile of the PRS had a 5.85-fold (CI = 1.69-20.3) increased risk of CLL relative to those in the middle quintile in the FH strata, and a 2.65-fold (CI = 1.75-4.01) increased risk in the non-FH strata. After adjusting for PRS, FH and age, there remained an inverse association with sun exposure in the highest quartile (hours per week) (OR = 0.49, CI = 0.31-0.79) and a positive association with height (per 10 cm change) (OR = 1.37, CI = 1.17-1.62), but there were no associations with atopy, any allergies, history of asthma, or farming. No statistical evidence of an interaction among the variables was observed. Conclusions: We found evidence of independent effects among the genetic and non-genetic factors with risk of CLL. Among these factors, the PRS had the largest effect size. Although we did not observe any statistical interactions, larger sample sizes are warranted to fully evaluate these effects on risk of CLL. We are currently increasing our sample size through collaboration with other research groups. Final results will be presented in the meeting. This abstract is also being presented as Poster A06. Citation Format: Geffen Kleinstern, Dennis Robinson, Tim G. Call, Mark Liebow, Silvia de Sanjosé, Yolanda Benavente, James R. Cerhan, Susan L. Slager. Association of environmental risk factors, family history, and polygenic risk scores with chronic lymphocytic leukemia. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR03.

Abstract This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR03) of the Conference Proceedings. Citation Format: Geffen Kleinstern, Dennis Robinson, Tim G. Call, Mark Liebow, Silvia de Sanjosé, Yolanda Benavente, James R. Cerhan, Susan L. Slager. Association of environmental risk factors, family history, and polygenic risk scores with chronic lymphocytic leukemia. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr A06.

SummaryWe evaluated the association of Human Pegivirus (HPgV) viraemia with risk of developing lymphoma, overall and by major subtypes. Because this virus has also been associated with better prognosis in the setting of co‐infection with human immunodeficiency virus, we further assessed the association of HPgV with prognosis. We used risk factor data and banked plasma samples from 2094 lymphoma cases newly diagnosed between 2002 and 2009 and 1572 frequency‐matched controls. Plasma samples were tested for HPgV RNA by reverse transcription polymerase chain reaction (RT‐PCR), and those with RNA concentrations <5000 genome equivalents/ml were confirmed using nested RT‐PCR methods. To assess the role of HPgV in lymphoma prognosis, we used 2948 cases from a cohort study of newly diagnosed lymphoma patients (included all cases from the case‐control study). There was a positive association of HPgV viraemia with risk of lymphoma overall (Odds ratio = 2·14; 95% confidence interval [CI] 1·63–2·80; P < 0·0001), and for all major subtypes except Hodgkin lymphoma and chronic lymphocytic leukaemia/small lymphocytic lymphoma, and this was not confounded by other lymphoma risk factors. In contrast, there was no association of HPgV viraemia with event‐free survival (Hazard ratio [HR] = 1·00; 95% CI 0·85–1·18) or overall survival (HR = 0·97; 95% CI 0·79–1·20) for lymphoma overall, or any of the subtypes. These data support the hypothesis for a role of HPgV in the aetiology of multiple lymphoma subtypes.

Key Points PRS, based on the known CLL loci, predicts CLL risk with high discrimination. This PRS predicts risk of monoclonal B-cell lymphocytosis, a precursor to CLL and a condition that has clinical impact beyond risk for CLL.

Objective Determinants of the increased risk of diffuse large B-cell lymphoma (DLBCL) in SLE are unclear. Using data from a recent lymphoma genome-wide association study (GWAS), we assessed whether certain lupus-related single nucleotide polymorphisms (SNPs) were also associated with DLBCL. Methods GWAS data on European Caucasians from the International Lymphoma Epidemiology Consortium (InterLymph) provided a total of 3857 DLBCL cases and 7666 general-population controls. Data were pooled in a random-effects meta-analysis. Results Among the 28 SLE-related SNPs investigated, the two most convincingly associated with risk of DLBCL included the CD40 SLE risk allele rs4810485 on chromosome 20q13 (OR per risk allele=1.09, 95% CI 1.02 to 1.16, p=0.0134), and the HLA SLE risk allele rs1270942 on chromosome 6p21.33 (OR per risk allele=1.17, 95% CI 1.01 to 1.36, p=0.0362). Of additional possible interest were rs2205960 and rs12537284. The rs2205960 SNP, related to a cytokine of the tumour necrosis factor superfamily TNFSF4, was associated with an OR per risk allele of 1.07, 95% CI 1.00 to 1.16, p=0.0549. The OR for the rs12537284 (chromosome 7q32, IRF5 gene) risk allele was 1.08, 95% CI 0.99 to 1.18, p=0.0765. Conclusions These data suggest several plausible genetic links between DLBCL and SLE.

Abstract Background Thirty-four single nucleotide polymorphisms (SNPs) are associated with CLL risk to-date. Moreover, family history (FH) of hematological malignancy has been consistently found to be associated with CLL, with an 8.5-fold increased risk of CLL among first-degree relatives. However, there has not been an evaluation of the interactive effects among genetic factors and FH with CLL risk. Methods We pooled data from 8 CLL case-control studies within the InterLymph Consortium (1499 CLL cases and 2601 controls). We computed a polygenic risk score (PRS), a weighted average of the number of risk alleles across the 34 SNPs, with the weights being the log of the previously reported odds ratio (OR) for each SNP. We categorized the PRS by quintiles using the cutoff points based on the distribution of all InterLymph controls (N=8228). Self-reported FH data was available for 60% of cases and 73% of controls. FH was defined as any hematological malignancy in one or more first-degree relative. Logistic regression was used to estimate ORs and 95% confidence intervals (CIs) adjusted for age, sex, socioeconomic status and study. Results The median age at diagnosis of CLL was 63 years and median age of consent was 60 years in the controls. 67% were male in CLL cases and 57% in controls. As expected, FH was associated with CLL risk (OR= 2.14, CI= 1.60-2.86). The median PRS in the cases was 0.40 and in the controls was -0.36 with the frequency of CLL cases in the upper PRS quintile as 48% while in the lowest quintile only 6%. The PRS was strongly associated with CLL risk (OR= 2.90, CI= 2.35-3.56 for upper versus middle quintile). When jointly modeling FH with PRS, a significant interaction was observed (P=0.03). When stratifying by FH, the upper quintile of the PRS had an 11.8-fold (CI= 3.97-34.8) increased risk relative to those in the middle quintile in the FH+ strata, while a 3.11-fold (CI= 2.35-4.10) increased risk was observed in the FH- strata. Conclusions Our data suggest that the PRS has a strong association with CLL risk and this association varies with FH status. Among those with FH-, the risk of CLL was 3-fold for those with many inherited variants while the CLL risk was much higher than that in those with a FH+. Studies are needed to see whether this PRS stratifies risk among those with monoclonal B-cell lymphocytosis, the CLL precursor condition that affects 5-7% of the general population. Citation Format: Geffen Kleinstern, Silvia de Sanjosé, Nicola Camp, Claire M. Vajdic, Timothy G. Call, Mark Liebow, Dennis Robinson, Neil E. Kay, Julie Cunningham, Yolanda Benavente, Alain Monnereau, John Spinelli, James R. Cerhan, Susan L. Slager. Association of polygenic risk scores and family history with the risk of chronic lymphocytic leukemia (CLL) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4267. doi:10.1158/1538-7445.AM2017-4267