Heike Bickeböller

Hierarchical modeling identifies novel lung cancer susceptibility variants in inflammation pathways among 10,140 cases and 11,012 controls

Recent evidence suggests that inflammation plays a pivotal role in the development of lung cancer. In this study, we used a two-stage approach to investigate associations between genetic variants in inflammation pathways and lung cancer risk based on genome-wide association study (GWAS) data. A total of 7,650 sequence variants from 720 genes relevant to inflammation pathways were identified using keyword and pathway searches from Gene Cards and Gene Ontology databases. In Stage 1, six GWAS datasets from the International Lung Cancer Consortium were pooled (4,441 cases and 5,094 controls of European ancestry), and a hierarchical modeling (HM) approach was used to incorporate prior information for each of the variants into the analysis. The prior matrix was constructed using (1) role of genes in the inflammation and immune pathways; (2) physical properties of the variants including the location of the variants, their conservation scores and amino acid coding; (3) LD with other functional variants and (4) measures of heterogeneity across the studies. HM affected the priority ranking of variants particularly among those having low prior weights, imprecise estimates and/or heterogeneity across studies. In Stage 2, we used an independent NCI lung cancer GWAS study (5,699 cases and 5,818 controls) for in silico replication. We identified one novel variant at the level corrected for multiple comparisons (rs2741354 in EPHX2 at 8q21.1 with p valuexa0=xa07.4xa0×xa010−6), and confirmed the associations between TERT (rs2736100) and the HLA region and lung cancer risk. HM allows for prior knowledge such as from bioinformatic sources to be incorporated into the analysis systematically, and it represents a complementary analytical approach to the conventional GWAS analysis.

Association between Adult Height and Risk of Colorectal, Lung, and Prostate Cancer: Results from Meta-analyses of Prospective Studies and Mendelian Randomization Analyses.

Background Observational studies examining associations between adult height and risk of colorectal, prostate, and lung cancers have generated mixed results. We conducted meta-analyses using data from prospective cohort studies and further carried out Mendelian randomization analyses, using height-associated genetic variants identified in a genome-wide association study (GWAS), to evaluate the association of adult height with these cancers. Methods and Findings A systematic review of prospective studies was conducted using the PubMed, Embase, and Web of Science databases. Using meta-analyses, results obtained from 62 studies were summarized for the association of a 10-cm increase in height with cancer risk. Mendelian randomization analyses were conducted using summary statistics obtained for 423 genetic variants identified from a recent GWAS of adult height and from a cancer genetics consortium study of multiple cancers that included 47,800 cases and 81,353 controls. For a 10-cm increase in height, the summary relative risks derived from the meta-analyses of prospective studies were 1.12 (95% CI 1.10, 1.15), 1.07 (95% CI 1.05, 1.10), and 1.06 (95% CI 1.02, 1.11) for colorectal, prostate, and lung cancers, respectively. Mendelian randomization analyses showed increased risks of colorectal (odds ratio [OR] = 1.58, 95% CI 1.14, 2.18) and lung cancer (OR = 1.10, 95% CI 1.00, 1.22) associated with each 10-cm increase in genetically predicted height. No association was observed for prostate cancer (OR = 1.03, 95% CI 0.92, 1.15). Our meta-analysis was limited to published studies. The sample size for the Mendelian randomization analysis of colorectal cancer was relatively small, thus affecting the precision of the point estimate. Conclusions Our study provides evidence for a potential causal association of adult height with the risk of colorectal and lung cancers and suggests that certain genetic factors and biological pathways affecting adult height may also affect the risk of these cancers.

Novel Association of Genetic Markers Affecting CYP2A6 activity and Lung Cancer Risk

Metabolism of nicotine by cytochrome P450 2A6 (CYP2A6) is a suspected determinant of smoking dose and, consequently, lung cancer risk. We conducted a genome-wide association study (GWAS) of CYP2A6 activity, as measured by the urinary ratio of trans-3-hydroxycotinine and its glucuronide conjugate over cotinine (total 3HCOT/COT), among 2,239 smokers in the Multiethnic Cohort (MEC) study. We identified 248 CYP2A6 variants associated with CYP2A6 activity (P < 5 × 10-8). CYP2A6 activity was correlated (r = 0.32; P < 0.0001) with total nicotine equivalents (a measure of nicotine uptake). When we examined the effect of these variants on lung cancer risk in the Transdisciplinary Research in Cancer of the Lung (TRICL) consortium GWAS dataset (13,479 cases and 43,218 controls), we found that the vast majority of these individual effects were directionally consistent and associated with an increased lung cancer risk. Two hundred and twenty-six of the 248 variants associated with CYP2A6 activity in the MEC were available in TRICL. Of them, 81% had directionally consistent risk estimates, and six were globally significantly associated with lung cancer. When conditioning on nine known functional variants and two deletions, the top two SNPs (rs56113850 in MEC and rs35755165 in TRICL) remained significantly associated with CYP2A6 activity in MEC and lung cancer in TRICL. The present data support the hypothesis that a greater CYP2A6 activity causes smokers to smoke more extensively and be exposed to higher levels of carcinogens, resulting in an increased risk for lung cancer. Although the variants identified in these studies may be used as risk prediction markers, the exact causal variants remain to be identified. Cancer Res; 76(19); 5768-76. ©2016 AACR.

Impact of the MICA-129Met/Val Dimorphism on NKG2D-Mediated Biological Functions and Disease Risks.

The major histocompatibility complex (MHC) class I chain-related A (MICA) is the most polymorphic non-classical MHC class I gene in humans. It encodes a ligand for NKG2D (NK group 2, member D), an activating natural killer (NK) receptor that is expressed mainly on NK cells and CD8+ T cells. The single-nucleotide polymorphism (SNP) rs1051792 causing a valine (Val) to methionine (Met) exchange at position 129 of the MICA protein is of specific interest. It separates MICA into isoforms that bind NKG2D with high (Met) and low affinities (Val). Therefore, this SNP has been investigated for associations with infections, autoimmune diseases, and cancer. Here, we systematically review these studies and analyze them in view of new data on the functional consequences of this polymorphism. It has been shown recently that the MICA-129Met variant elicits a stronger NKG2D signaling, resulting in more degranulation and IFN-γ production in NK cells and in a faster costimulation of CD8+ T cells than the MICA-129Val variant. However, the MICA-129Met isoform also downregulates NKG2D more efficiently than the MICA-129Val isoform. This downregulation impairs NKG2D-mediated functions at high expression intensities of the MICA-Met variant. These features of the MICA-129Met/Val dimorphism need to be considered when interpreting disease association studies. Particularly, in the field of hematopoietic stem cell transplantation, they help to explain the associations of the SNP with outcome including graft-versus-host disease and relapse of malignancy. Implications for future disease association studies of the MICA-129Met/Val dimorphism are discussed.

Genetic Risk Can Be Decreased: Quitting Smoking Decreases and Delays Lung Cancer for Smokers With High and Low CHRNA5 Risk Genotypes — A Meta-Analysis

Background Recent meta-analyses show that individuals with high risk variants in CHRNA5 on chromosome 15q25 are likely to develop lung cancer earlier than those with low-risk genotypes. The same high-risk genetic variants also predict nicotine dependence and delayed smoking cessation. It is unclear whether smoking cessation confers the same benefits in terms of lung cancer risk reduction for those who possess CHRNA5 risk variants versus those who do not. Methods Meta-analyses examined the association between smoking cessation and lung cancer risk in 15 studies of individuals with European ancestry who possessed varying rs16969968 genotypes (N = 12,690 ever smokers, including 6988 cases of lung cancer and 5702 controls) in the International Lung Cancer Consortium. Results Smoking cessation (former vs. current smokers) was associated with a lower likelihood of lung cancer (OR = 0.48, 95%CI = 0.30–0.75, p = 0.0015). Among lung cancer patients, smoking cessation was associated with a 7-year delay in median age of lung cancer diagnosis (HR = 0.68, 95%CI = 0.61–0.77, p = 4.9 ∗ 10–10). The CHRNA5 rs16969968 risk genotype (AA) was associated with increased risk and earlier diagnosis for lung cancer, but the beneficial effects of smoking cessation were very similar in those with and without the risk genotype. Conclusion We demonstrate that quitting smoking is highly beneficial in reducing lung cancer risks for smokers regardless of their CHRNA5 rs16969968 genetic risk status. Smokers with high-risk CHRNA5 genotypes, on average, can largely eliminate their elevated genetic risk for lung cancer by quitting smoking- cutting their risk of lung cancer in half and delaying its onset by 7 years for those who develop it. These results: 1) underscore the potential value of smoking cessation for all smokers, 2) suggest that CHRNA5 rs16969968 genotype affects lung cancer diagnosis through its effects on smoking, and 3) have potential value for framing preventive interventions for those who smoke.

Genetic variant in DNA repair gene GTF2H4 is associated with lung cancer risk: a large-scale analysis of six published GWAS datasets in the TRICL consortium

DNA repair pathways maintain genomic integrity and stability, and dysfunction of DNA repair leads to cancer. We hypothesize that functional genetic variants in DNA repair genes are associated with risk of lung cancer. We performed a large-scale meta-analysis of 123,371 single nucleotide polymorphisms (SNPs) in 169 DNA repair genes obtained from six previously published genome-wide association studies (GWASs) of 12160 lung cancer cases and 16838 controls. We calculated odds ratios (ORs) with 95% confidence intervals (CIs) using the logistic regression model and used the false discovery rate (FDR) method for correction of multiple testing. As a result, 14 SNPs had a significant odds ratio (OR) for lung cancer risk with P FDR < 0.05, of which rs3115672 in MSH5 (OR = 1.20, 95% CI = 1.14-1.27) and rs114596632 in GTF2H4 (OR = 1.19, 95% CI = 1.12-1.25) at 6q21.33 were the most statistically significant (P combined = 3.99×10(-11) and P combined = 5.40×10(-10), respectively). The MSH5 rs3115672, but not GTF2H4 rs114596632, was strongly correlated with MSH5 rs3131379 in that region (r (2) = 1.000 and r (2) = 0.539, respectively) as reported in a previous GWAS. Importantly, however, the GTF2H4 rs114596632 T, but not MSH5 rs3115672 T, allele was significantly associated with both decreased DNA repair capacity phenotype and decreased mRNA expression levels. These provided evidence that functional genetic variants of GTF2H4 confer susceptibility to lung cancer.

Impact of genomic risk factors on survival after haematopoietic stem cell transplantation for patients with acute leukaemia.

The EBMT risk score is an established tool successfully used in the prognosis of survival post‐HSCT and is applicable for a range of haematological disorders. One of its main advantages is that score generation involves summation of clinical parameters that are available pretransplant. However, the EBMT risk score is recognized as not being optimal. Previous analyses, involving patients with various diagnoses, have shown that non‐HLA gene polymorphisms influence outcome after allogeneic HSCT. This study is novel as it focuses only on patients having acute leukaemia (N = 458) and attempts to demonstrate how non‐HLA gene polymorphisms can be added to the EBMT risk score in a Cox regression model to improve prognostic ability for overall survival. The results of the study found that three genetic factors improved EBMT risk score. The presence of MAL (rs8177374) allele T in the patient, absence of glucocorticoid receptor haplotype (consisting of rs6198, rs33389 and rs33388) ACT in the patient and absence of heat‐shock protein 70‐hom (+2437) (rs2227956) allele C in the patient were associated with decreased survival time. When compared to the EBMT risk score, the scores combining EBMT risk score with the genetic factors had an improved correlation with clinical outcome and better separation of risk groups. A bootstrapping technique, involving repeated testing of a model using multiple validation sets, also revealed that the newly proposed model had improved predictive value when compared to the EBMT risk score alone. Results support the view that non‐HLA polymorphisms could be useful for pretransplant clinical assessment and provide evidence that polymorphisms in the recipient genotype may influence incoming donor cells, suppressing the initiation of the graft versus leukaemia effect and reducing survival.

Comparing strategies for combined testing of rare and common variants in whole sequence and genome-wide genotype data

We used our extension of the kernel score test to family data to analyze real and simulated baseline systolic blood pressure in extended pedigrees. We compared the power for different kernels and for different weightings of genetic markers. Moreover, we compared the power of rare and common markers with 3 strategies for joint testing and on marker panels with different densities. Marker weights had much greater influence on power than the kernel chosen. Inverse minor allele frequency weights often increased power on common markers but could decrease power on rare markers. Furthermore, defining the gene region based on linkage disequilibrium blocks often yielded robust power of joint tests of rare and common markers.

Polymorphisms of the centrosomal gene (FGFR1OP) and lung cancer risk: a meta-analysis of 14,463 cases and 44,188 controls.

Centrosome abnormalities are often observed in premalignant lesions and in situ tumors and have been associated with aneuploidy and tumor development. We investigated the associations of 9354 single-nucleotide polymorphisms (SNPs) in 106 centrosomal genes with lung cancer risk by first using the summary data from six published genome-wide association studies (GWASs) of the Transdisciplinary Research in Cancer of the Lung (TRICL) (12,160 cases and 16 838 controls) and then conducted in silico replication in two additional independent lung cancer GWASs of Harvard University (984 cases and 970 controls) and deCODE (1319 cases and 26,380 controls). A total of 44 significant SNPs with false discovery rate (FDR) ≤ 0.05 were mapped to one novel gene FGFR1OP and two previously reported genes (TUBB and BRCA2). After combined the results from TRICL with those from Harvard and deCODE, the most significant association (P combined = 8.032 × 10(-6)) was with rs151606 within FGFR1OP. The rs151606 T>G was associated with an increased risk of lung cancer [odds ratio (OR) = 1.10, 95% confidence interval (95% CI) = 1.05-1.14]. Another significant tagSNP rs12212247 T>C (P combined = 9.589 × 10(-6)) was associated with a decreased risk of lung cancer (OR = 0.93, 95% CI = 0.90-0.96). Further in silico functional analyzes revealed that rs151606 might affect transcriptional regulation and result in decreased FGFR1OP expression (P trend = 0.022). The findings shed some new light on the role of centrosome abnormalities in the susceptibility to lung carcinogenesis.