Genetically Determined Height and Risk of Non-hodgkin Lymphoma

Although the evidence is not consistent, epidemiologic studies have suggested that taller adult height may be associated with an increased risk of some non-Hodgkin lymphoma (NHL) subtypes. Height is largely determined by genetic factors, but how these genetic factors may contribute to NHL risk is unknown. We investigated the relationship between genetic determinants of height and NHL risk using data from eight genome-wide association studies (GWAS) comprising 10,629 NHL cases, including 3,857 diffuse large B-cell lymphoma (DLBCL), 2,847 follicular lymphoma (FL), 3,100 chronic lymphocytic leukemia (CLL), and 825 marginal zone lymphoma (MZL) cases, and 9,505 controls of European ancestry. We evaluated genetically predicted height by constructing polygenic risk scores using 833 height-associated SNPs. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) for association between genetically determined height and the risk of four NHL subtypes in each GWAS and then used fixed-effect meta-analysis to combine subtype results across studies. We found suggestive evidence between taller genetically determined height and increased CLL risk (OR = 1.08, 95% CI = 1.00\u20131.17, p = 0.049), which was slightly stronger among women (OR = 1.15, 95% CI: 1.01\u20131.31, p = 0.036). No significant associations were observed with DLBCL, FL, or MZL. Our findings suggest that there may be some shared genetic factors between CLL and height, but other endogenous or environmental factors may underlie reported epidemiologic height associations with other subtypes

Two high-risk susceptibility loci at 6p25.3 and 14q32.13 for Waldenström macroglobulinemia

Waldenström macroglobulinemia (WM)/lymphoplasmacytic lymphoma (LPL) is a rare, chronic B-cell lymphoma with high heritability. We conduct a two-stage genome-wide association study of WM/LPL in 530 unrelated cases and 4362 controls of European ancestry and identify two high-risk loci associated with WM/LPL at 6p25.3 (rs116446171, near EXOC2 and IRF4; OR = 21.14, 95% CI: 14.40–31.03, P = 1.36 × 10−54) and 14q32.13 (rs117410836, near TCL1; OR = 4.90, 95% CI: 3.45–6.96, P = 8.75 × 10−19). Both risk alleles are observed at a low frequency among controls (~2–3%) and occur in excess in affected cases within families. In silico data suggest that rs116446171 may have functional importance, and in functional studies, we demonstrate increased reporter transcription and proliferation in cells transduced with the 6p25.3 risk allele. Although further studies are needed to fully elucidate underlying biological mechanisms, together these loci explain 4% of the familial risk and provide insights into genetic susceptibility to this malignancy

Risk of non-Hodgkin lymphoma associated with polymorphisms in folate-metabolizing genes

Genetic instability, including chromosomal imbalance, is important in the pathogenesis of lymphoproliferative disorders such as non–Hodgkin lymphoma (NHL). DNA synthesis and methylation, which are closely linked to folate metabolism and transport, may be affected by polymorphisms in genes involved in these pathways. Folate metabolism polymorphisms have been linked to acute lymphoblastic leukemia and colorectal cancer. To evaluate whether genetic variation in folate metabolism and transport may have a role in determining the risk of developing NHL, we analyzed several polymorphisms using DNA obtained as part of a large U.K. population-based case-control study of lymphoma. Polymorphisms studied include methylenetetrahydrofolate reductase (MTHFR) 677 C>T and 1298 A>C, methionine synthase (MTR) 2756 A>G, serine hydroxymethyltransferase (SHMT1) 1420 C>T, thymidylate synthase (TYMS) 1494del6 and 28–bp repeat, and reduced folate carrier (RFC) 80 G>A. Increased risks for NHL [odds ratio (OR), 1.48; 95% confidence intervals (CI), 1.12-1.97], and marginal zone lymphoma (OR, 3.38; 95% CI, 1.30-8.82) were associated with the TYMS 2R/3R variant. Marginal increased risks were also observed for diffuse large B cell lymphoma with the TYMS homozygous 6 bp deletion (OR, 1.61; 95% CI, 0.99-2.60) and for follicular lymphoma with RFC 80AA (OR, 1.44; 95% CI, 0.94-2.22) and TYMS 28–bp repeat 2R/3R (OR, 1.45; 95% CI, 0.96-2.2). We observed no association between NHL and haplotypes for MTHFR or TYMS. These findings are somewhat inconsistent with those of others, but may reflect differences in circulating folate levels between study populations. Thus, further investigations are warranted in larger series with dietary information to determine the roles that genetics and folic acid status play in the etiology of lymphoma. (Cancer Epidemiol Biomarkers Prev 2005;14(12):2999–3003

Application of OMICS technologies in occupational and environmental health research; current status and projections.

OMICS technologies are relatively new biomarker discovery tools that can be applied to study large sets of biological molecules. Their application in human observational studies (HOS) has become feasible in recent years due to a spectacular increase in the sensitivity, resolution and throughput of OMICS-based assays. Although, the number of OMICS techniques is ever expanding, the five most developed OMICS technologies are genotyping, transcriptomics, epigenomics, proteomics and metabolomics. These techniques have been applied in HOS to various extents. However, their application in occupational environmental health (OEH) research has been limited. Here, we will discuss the opportunities these new techniques provide for OEH research. In addition we will address difficulties and limitations to the interpretation of the data that is generated by OMICS technologies. To illustrate the current status of the application of OMICS in OEH research, we will provide examples of studies that used OMICS technologies to investigate human health effects of two well-known toxicants, benzene and arsenic

Systems biology of human benzene exposure.

Toxicogenomic studies, including genome-wide analyses of susceptibility genes (genomics), gene expression (transcriptomics), protein expression (proteomics), and epigenetic modifications (epigenomics), of human populations exposed to benzene are crucial to understanding gene-environment interactions, providing the ability to develop biomarkers of exposure, early effect and susceptibility. Comprehensive analysis of these toxicogenomic and epigenomic profiles by bioinformatics in the context of phenotypic endpoints, comprises systems biology, which has the potential to comprehensively define the mechanisms by which benzene causes leukemia. We have applied this approach to a molecular epidemiology study of workers exposed to benzene. Hematotoxicity, a significant decrease in almost all blood cell counts, was identified as a phenotypic effect of benzene that occurred even below 1 ppm benzene exposure. We found a significant decrease in the formation of progenitor colonies arising from bone marrow stem cells with increasing benzene exposure, showing that progenitor cells are more sensitive to the effects of benzene than mature blood cells, likely leading to the observed hematotoxicity. Analysis of transcriptomics by microarray in the peripheral blood mononuclear cells of exposed workers, identified genes and pathways (apoptosis, immune response, and inflammatory response) altered at high (>10 ppm) and low

eALPS: Estimating Abundance Levels in Pooled Sequencing Using Available Genotyping Data

The recent advances in high-throughput sequencing technologies bring the potential of a better characterization of the genetic variation in humans and other organisms. In many occasions, either by design or by necessity, the sequencing procedure is performed on a pool of DNA samples with different abundances, where the abundance of each sample is unknown. Such a scenario is naturally occurring in the case of metagenomics analysis where a pool of bacteria is sequenced, or in the case of population studies involving DNA pools by design. Particularly, various pooling designs were recently suggested that can identify carriers of rare alleles in large cohorts, dramatically reducing the cost of such large-scale sequencing projects. A fundamental problem with such approaches for population studies is that the uncertainly of DNA proportions from different individuals in the pools might lead to spurious associations. Fortunately, it is often the case that the genotype data of at least some of the individuals in the pool is known. Here, we propose a method (eALPS) that uses the genotype data in conjunction with the pooled sequence data in order to accurately estimate the proportions of the samples in the pool, even in cases where not all individuals in the pool were genotyped (eALPS-LD). Using real data from a sequencing pooling study of Non-Hodgkin's Lymphoma, we demonstrate that the estimation of the proportions is crucial, since otherwise there is a risk for false discoveries. Additionally, we demonstrate that our approach is also applicable to the problem of quantification of species in metagenomics samples (eALPS-BCR), and is particularly suitable for metagenomic quantification of closely-related species. © 2013 Springer-Verlag

Coding variants at hexa-allelic amino acid 13 of HLA-DRB1 explain independent SNP associations with follicular lymphoma risk

10.1016/j.ajhg.2013.05.020American Journal of Human Genetics931167-172AJHG

PRRC2A and BCL2L11 gene variants influence risk of non-Hodgkin lymphoma: results from the InterLymph consortium.

Many common genetic variants have been associated with non-Hodgkin lymphoma (NHL), but individual study results are often conflicting. To confirm the role of putative risk alleles in B-cell NHL etiology, we performed a validation genotyping study of 67 candidate single nucleotide polymorphisms within InterLymph, a large international consortium of NHL case-control studies. A meta-analysis was performed on data from 5633 B-cell NHL cases and 7034 controls from 8 InterLymph studies. rs3789068 in the proapoptotic BCL2L11 gene was associated with an increased risk for B-cell NHL (odds ratio = 1.21, P random = 2.21 x 10(-11)), with similar risk estimates for common B-cell subtypes. PRRC2A rs3132453 in the HLA complex class III region conferred a reduced risk of B-cell NHL (odds ratio = 0.68, P random = 1.07 x 10(-9)) and was likewise evident for common B-cell subtypes. These results are consistent with the known biology of NHL and provide insights into shared pathogenic components, including apoptosis and immune regulation, for the major B-cell lymphoma subtypes