Robert Carreras-Torres

Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.

Background Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. Methods and findings We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01–1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15–2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79–1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84–0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25–2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. Conclusions Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.

The Role of Obesity, Type 2 Diabetes, and Metabolic Factors in Pancreatic Cancer: A Mendelian Randomization Study

Abstract Background Risk factors for pancreatic cancer include a cluster of metabolic conditions such as obesity, hypertension, dyslipidemia, insulin resistance, and type 2 diabetes. Given that these risk factors are correlated, separating out causal from confounded effects is challenging. Mendelian randomization (MR), or the use of genetic instrumental variables, may facilitate the identification of the metabolic drivers of pancreatic cancer. Methods We identified genetic instruments for obesity, body shape, dyslipidemia, insulin resistance, and type 2 diabetes in order to evaluate their causal role in pancreatic cancer etiology. These instruments were analyzed in relation to risk using a likelihood-based MR approach within a series of 7110 pancreatic cancer patients and 7264 control subjects using genome-wide data from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Potential unknown pleiotropic effects were assessed using a weighted median approach and MR-Egger sensitivity analyses. Results Results indicated a robust causal association of increasing body mass index (BMI) with pancreatic cancer risk (odds ratio [OR] = 1.34, 95% confidence interval [CI] = 1.09 to 1.65, for each standard deviation increase in BMI [4.6 kg/m2]). There was also evidence that genetically increased fasting insulin levels were causally associated with an increased risk of pancreatic cancer (OR = 1.66, 95% CI = 1.05 to 2.63, per SD [44.4 pmol/L]). Notably, no evidence of a causal relationship was observed for type 2 diabetes, nor for dyslipidemia. Sensitivity analyses did not indicate that pleiotropy was an important source of bias. Conclusions Our results suggest a causal role of BMI and fasting insulin in pancreatic cancer etiology.

The causal relevance of body mass index in different histological types of lung cancer: A Mendelian randomization study

Body mass index (BMI) is inversely associated with lung cancer risk in observational studies, even though it increases the risk of several other cancers, which could indicate confounding by tobacco smoking or reverse causality. We used the two-sample Mendelian randomization (MR) approach to circumvent these limitations of observational epidemiology by constructing a genetic instrument for BMI, based on results from the GIANT consortium, which was evaluated in relation to lung cancer risk using GWAS results on 16,572 lung cancer cases and 21,480 controls. Results were stratified by histological subtype, smoking status and sex. An increase of one standard deviation (SD) in BMI (4.65 Kg/m2) raised the risk for lung cancer overall (OR = 1.13; P = 0.10). This was driven by associations with squamous cell (SQ) carcinoma (OR = 1.45; P = 1.2 × 10−3) and small cell (SC) carcinoma (OR = 1.81; P = 0.01). An inverse trend was seen for adenocarcinoma (AD) (OR = 0.82; P = 0.06). In stratified analyses, a 1 SD increase in BMI was inversely associated with overall lung cancer in never smokers (OR = 0.50; P = 0.02). These results indicate that higher BMI may increase the risk of certain types of lung cancer, in particular SQ and SC carcinoma.

Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank

Abstract Objective To determine whether body mass index, body fat percentage, and waist circumference influence smoking status and intensity. Design Mendelian randomisation study. Setting UK Biobank, with replication of results from the Tobacco and Genetics (TAG) consortium. Participants European descent participants from the UK Biobank cohort (n=372 791) and the TAG consortium (n=74 035). Main outcome measures Risk of current and past smoking, number of cigarettes smoked per day, age of smoking initiation. Results The Mendelian randomisation analysis indicated that each standard deviation increment in body mass index (4.6) increased the risk of being a smoker (odds ratio 1.18 (95% confidence interval 1.13 to 1.23), P<0.001). This association was replicated in the TAG consortium data (1.19 (1.06 to 1.33), P=0.003). Furthermore, each standard deviation increment in body mass index was estimated to increase smoking intensity by 0.88 cigarettes per day (95% confidence interval 0.50 to 1.26, P<0.001) in UK Biobank and 1.27 cigarettes per day in the TAG consortium (0.46 to 2.07, P=0.002). Similar results were also seen for body fat percentage and waist circumference in both UK Biobank and the TAG consortium data. Conclusions These results strongly suggest that higher adiposity influences smoking behaviour and could have implications for the implementation of public health interventions aiming to reduce the prevalence of these important risk factors.

Genetic contributions to the association between adult height and head and neck cancer: a Mendelian randomization analysis

With the aim to dissect the effect of adult height on head and neck cancer (HNC), we use the Mendelian randomization (MR) approach to test the association between genetic instruments for height and the risk of HNC. 599 single nucleotide polymorphisms (SNPs) were identified as genetic instruments for height, accounting for 16% of the phenotypic variation. Genetic data concerning HNC cases and controls were obtained from a genome-wide association study. Summary statistics for genetic association were used in complementary MR approaches: the weighted genetic risk score (GRS) and the inverse-variance weighted (IVW). MR-Egger regression was used for sensitivity analysis and pleiotropy evaluation. From the GRS analysis, one standard deviation (SD) higher height (6.9 cm; due to genetic predisposition across 599 SNPs) raised the risk for HNC (Odds ratio (OR), 1.14; 95% Confidence Interval (95%CI), 0.99–1.32). The association analyses with potential confounders revealed that the GRS was associated with tobacco smoking (OR = 0.80, 95% CI (0.69–0.93)). MR-Egger regression did not provide evidence of overall directional pleiotropy. Our study indicates that height is potentially associated with HNC risk. However, the reported risk could be underestimated since, at the genetic level, height emerged to be inversely associated with smoking.

Abstract 1298: Genetic variants related to longer telomere length are associated with increased risk of renal cell carcinoma

Telomere length in peripheral blood leukocytes has been evaluated as a potential biomarker for renal cell carcinoma (RCC) risk in numerous observational studies, but association results have been inconsistent. These findings may have been affected by several limitations, including bias from reverse causation, reliance on a single blood specimen, residual confounding or measurement outside of the etiologically relevant time period. Germline genetic variations associated with leukocyte telomere length are not affected by an individual’s exposure to confounders and may act as unconfounded markers of the relationship between telomere length and RCC risk. We performed an analysis of genetic variants associated with leukocyte telomere length to assess the relationship between telomere length and RCC risk. Genotypes from nine telomere length associated variants were aggregated for 10,785 RCC cases and 21,579 cancer-free controls. We found that the number of telomere length variants associated with RCC risk (P-value Citation Format: Mitchell J. Machiela, Jonathan N. Hofmann, Robert Carreras-Torres, Nathaniel Rothman, Paul Brennan, Mattias Johansson, Stephen J. Chanock, Kevin M. Brown, Ghislaine Scelo, Mark P. Purdue. Genetic variants related to longer telomere length are associated with increased risk of renal cell carcinoma [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 1298. doi:10.1158/1538-7445.AM2017-1298

Abstract 4349: Identifying causal risk factors of metabolic syndrome for renal cell carcinoma. A Mendelian randomization approach

Epidemiological studies have convincingly demonstrated that several factors of the metabolic syndrome (MetS) are associated with the risk of Renal Cell Carcinoma (RCC)These factors often occur together and it is therefore challenging to disentangle their individual causal relevance in the etiology of RCC. In order to circumvent this limitation, we have applied a Mendelian randomization (MR) approach whereby genetic markers are evaluated in relation to RCC risk as unconfounded markers of the individual MetS factors. We focused on MetS parameters from which genetic instruments could be identified from large-scale genome-wide association studies (GWAS). The following MetS factors were instrumented using multiple gene-variants: general and central obesity (body mass index (BMI) and waist-to-hip ratio), elevated blood pressure (systolic and diastolic blood pressure), dyslipidemia (high and low density cholesterol, total cholesterol, and triglycerides), hyperglycemia (fasting glucose and glucose levels at 2 hours after glucose intolerance tests), and hyperinsulinemia (fasting insulin). Genetic proxies for these parameters were identified from GIANT, ICBP, GLGC and MAGIC Consortia. Summary statistics on RCC risk for instrumental SNPs of each MetS factor, including OR estimates and standard errors, were available from GWAS coordinated by the International Agency for Research on Cancer, the US National Cancer Institute, the Institute for Cancer Research UK, and the MD Anderson Cancer Center US. Together these studies comprised a total of 12,104 RCC cases and 24,999 controls from European origin that were genotyped using different genotyping platforms. Imputation was conducted on each dataset and only SNPs with an imputation quality higher than 0.6 were considered for the analyses. The causal effect of each MetS parameter on RCC risk was subsequently estimated using the MR likelihood-based approach, assuming a linear relationship between the risk factor and the outcome and a bivariate normal distribution for the genetic association estimates. The MR risk analysis using genetic instruments of the individual MetS factors indicated that elevated BMI (P: 1×10-08) and fasting insulin (P: 7×10-04)increased the risk of RCC, whereas elevated post-load glucose levels were associated with a lower risk (P: 2×10-3). The odds ratio per standard deviation increase were estimated at 1.58 (95% CI: 1.35-1.86) for BMI, 1.77 (95%CI: 1.27-2.46) for fasting insulin, and 0.62 (95%CI: 0.46-0.83) for post-load glucose. No associations were seen for genetic instruments of blood pressure or lipids. These results provide a clear support for a causal role of obesity in RCC etiology, and suggest that factors related to hyperglycemia and/or hyperinsulinemia may be involved in the causal pathway. This study may guide future efforts aiming to clarify the biological mechanisms whereby the metabolic syndrome influences RCC pathogenesis. Citation Format: Robert Carreras-Torres, Mattias Johansson, Ghislaine Scelo, Philip Haycock, Mark Purdue, Xifeng Wu, Richard Houlston, Stephen Chanock, Paul Brennan. Identifying causal risk factors of metabolic syndrome for renal cell carcinoma. A Mendelian randomization approach. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4349.