Author
Marc J. Gunter
Bio: Marc J. Gunter is an academic researcher from International Agency for Research on Cancer. The author has contributed to research in topics: Mendelian randomization & Cancer. The author has an hindex of 9, co-authored 18 publications receiving 208 citations.
Papers
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International Agency for Research on Cancer1, Utrecht University2, Aarhus University3, Aalborg University4, University of Copenhagen5, Université Paris-Saclay6, Institut Gustave Roussy7, German Cancer Research Center8, National and Kapodistrian University of Athens9, Prevention Institute10, Imperial College London11, University of Naples Federico II12, University of Tromsø13, University of Leeds14, University of Granada15, Cancer Epidemiology Unit16, University of Ioannina17, King's College London18
TL;DR: These findings point to potentially novel pathways and biomarkers of breast cancer development, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity.
Abstract: Metabolomics is a promising molecular tool to identify novel etiologic pathways leading to cancer. Using a targeted approach, we prospectively investigated the associations between metabolite concentrations in plasma and breast cancer risk. A nested case-control study was established within the European Prospective Investigation into Cancer cohort, which included 1624 first primary incident invasive breast cancer cases (with known estrogen and progesterone receptor and HER2 status) and 1624 matched controls. Metabolites (n = 127, acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, sphingolipids) were measured by mass spectrometry in pre-diagnostic plasma samples and tested for associations with breast cancer incidence using multivariable conditional logistic regression. Among women not using hormones at baseline (n = 2248), and after control for multiple tests, concentrations of arginine (odds ratio [OR] per SD = 0.79, 95% confidence interval [CI] = 0.70–0.90), asparagine (OR = 0.83 (0.74–0.92)), and phosphatidylcholines (PCs) ae C36:3 (OR = 0.83 (0.76–0.90)), aa C36:3 (OR = 0.84 (0.77–0.93)), ae C34:2 (OR = 0.85 (0.78–0.94)), ae C36:2 (OR = 0.85 (0.78–0.88)), and ae C38:2 (OR = 0.84 (0.76–0.93)) were inversely associated with breast cancer risk, while the acylcarnitine C2 (OR = 1.23 (1.11–1.35)) was positively associated with disease risk. In the overall population, C2 (OR = 1.15 (1.06–1.24)) and PC ae C36:3 (OR = 0.88 (0.82–0.95)) were associated with risk of breast cancer, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity. These findings point to potentially novel pathways and biomarkers of breast cancer development. Results warrant replication in other epidemiological studies.
66 citations
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University of Bristol1, International Agency for Research on Cancer2, Fred Hutchinson Cancer Research Center3, National Institutes of Health4, University of Leeds5, German Cancer Research Center6, Royal Melbourne Hospital7, University of Melbourne8, Kaiser Permanente9, University of Virginia10, University of Barcelona11, University of Hamburg12, Imperial College London13, Ohio State University14, Cedars-Sinai Medical Center15, University of Southern California16, Lunenfeld-Tanenbaum Research Institute17, American Cancer Society18, Monash University, Clayton campus19, Cancer Council Victoria20, Dresden University of Technology21, University of Washington22, Johns Hopkins University23, University of North Carolina at Chapel Hill24, Chonnam National University25, University of Hawaii26, Karolinska University Hospital27, Karolinska Institutet28, University of León29, Utrecht University30, Cornell University31, Memorial Sloan Kettering Cancer Center32, Rappaport Faculty of Medicine33, University of Pittsburgh34, University of Utah35, University of Ioannina36, Huntsman Cancer Institute37, Wageningen University and Research Centre38, Umeå University39, Charles University in Prague40, First Faculty of Medicine, Charles University in Prague41, Academy of Sciences of the Czech Republic42, Memorial University of Newfoundland43, Vanderbilt University44
TL;DR: Adiposity was associated with numerous metabolic alterations, but none of these explained associations between adiposity and CRC, and it is suggested that higher BMI more greatly raises CRC risk among men, whereas higher WHR more greatly rises CRCrisk among women.
Abstract: Higher adiposity increases the risk of colorectal cancer (CRC), but whether this relationship varies by anatomical sub-site or by sex is unclear. Further, the metabolic alterations mediating the effects of adiposity on CRC are not fully understood. We examined sex- and site-specific associations of adiposity with CRC risk and whether adiposity-associated metabolites explain the associations of adiposity with CRC. Genetic variants from genome-wide association studies of body mass index (BMI) and waist-to-hip ratio (WHR, unadjusted for BMI; N = 806,810), and 123 metabolites from targeted nuclear magnetic resonance metabolomics (N = 24,925), were used as instruments. Sex-combined and sex-specific Mendelian randomization (MR) was conducted for BMI and WHR with CRC risk (58,221 cases and 67,694 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry). Sex-combined MR was conducted for BMI and WHR with metabolites, for metabolites with CRC, and for BMI and WHR with CRC adjusted for metabolite classes in multivariable models. In sex-specific MR analyses, higher BMI (per 4.2 kg/m2) was associated with 1.23 (95% confidence interval (CI) = 1.08, 1.38) times higher CRC odds among men (inverse-variance-weighted (IVW) model); among women, higher BMI (per 5.2 kg/m2) was associated with 1.09 (95% CI = 0.97, 1.22) times higher CRC odds. WHR (per 0.07 higher) was more strongly associated with CRC risk among women (IVW OR = 1.25, 95% CI = 1.08, 1.43) than men (IVW OR = 1.05, 95% CI = 0.81, 1.36). BMI or WHR was associated with 104/123 metabolites at false discovery rate-corrected P ≤ 0.05; several metabolites were associated with CRC, but not in directions that were consistent with the mediation of positive adiposity-CRC relations. In multivariable MR analyses, associations of BMI and WHR with CRC were not attenuated following adjustment for representative metabolite classes, e.g., the univariable IVW OR for BMI with CRC was 1.12 (95% CI = 1.00, 1.26), and this became 1.11 (95% CI = 0.99, 1.26) when adjusting for cholesterol in low-density lipoprotein particles. Our results suggest that higher BMI more greatly raises CRC risk among men, whereas higher WHR more greatly raises CRC risk among women. Adiposity was associated with numerous metabolic alterations, but none of these explained associations between adiposity and CRC. More detailed metabolomic measures are likely needed to clarify the mechanistic pathways.
59 citations
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International Agency for Research on Cancer1, National Institutes of Health2, Imperial College London3, University of Bristol4, St. Jude Children's Research Hospital5, University of Texas MD Anderson Cancer Center6, Max Planck Society7, Alternatives8, Fondation Jean Dausset Centre d'Etude du Polymorphisme Humain9, Russian Academy of Sciences10, Mayo Clinic11, Charles University in Prague12, Palacký University, Olomouc13, Carol Davila University of Medicine and Pharmacy14, Pomeranian Medical University15, Institut Gustave Roussy16, French Institute of Health and Medical Research17, Umeå University18, Uppsala University19, Cancer Council Victoria20, QIMR Berghofer Medical Research Institute21, University of Queensland22, Université Paris-Saclay23, Royal Melbourne Hospital24, Norwegian University of Science and Technology25, University of London26, Karolinska Institutet27, St James's University Hospital28, National Institute for Health Research29, University of Cambridge30, Vanderbilt University31, American Cancer Society32, Harvard University33, Brown University34, Brigham and Women's Hospital35, Spectrum Health36, Michigan State University37, Van Andel Institute38, Ferris State University39, Fred Hutchinson Cancer Research Center40, Indiana University41, Institute of Cancer Research42, Icahn School of Medicine at Mount Sinai43, McGill University44, University Hospitals Bristol NHS Foundation Trust45
TL;DR: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk.
Abstract: Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question usin ...
56 citations
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King's College London1, Imperial College London2, University of Ioannina3, International Agency for Research on Cancer4, Aarhus University5, Aalborg University6, University of Copenhagen7, Université Paris-Saclay8, Institut Gustave Roussy9, university of lille10, German Cancer Research Center11, National and Kapodistrian University of Athens12, Prevention Institute13, University of Naples Federico II14, University of Turin15, University of Granada16, University of Antioquia17, Lund University18, Uppsala University19, Umeå University20, Utrecht University21, University of Cambridge22, Cancer Epidemiology Unit23, Oslo University Hospital24, Academy of Athens25, Harvard University26
TL;DR: The results are largely compatible with published studies and support weak associations of blood pressure with cancers in specific locations and morphologies.
Abstract: Several studies have reported associations of hypertension with cancer, but not all results were conclusive. We examined the association of systolic (SBP) and diastolic (DBP) blood pressure with th ...
49 citations
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Cancer Epidemiology Unit1, International Agency for Research on Cancer2, Clinical Trial Service Unit3, University of Oxford4, University of Bristol5, University Hospitals Bristol NHS Foundation Trust6, University of Ioannina7, Imperial College London8, Fiona Stanley Hospital9, University of Western Australia10
TL;DR: Findings implicate IGF‐I and free testosterone in prostate cancer development and/or progression and two‐sample Mendelian randomisation analysis of IGF-I and risk.
Abstract: Insulin-like growth factor-I (IGF-I) and testosterone have been implicated in prostate cancer aetiology. Using data from a large prospective full-cohort with standardised assays and repeat blood measurements, and genetic data from an international consortium, we investigated the associations of circulating IGF-I, sex hormone-binding globulin (SHBG), and total and calculated free testosterone concentrations with prostate cancer incidence and mortality. For prospective analyses, risk was estimated using multivariable-adjusted Cox regression in 199 698 male UK Biobank participants. Hazard ratios (HRs) were corrected for regression dilution bias using repeat hormone measurements from a subsample. Two-sample Mendelian randomisation (MR) analysis of IGF-I and risk used genetic instruments identified from UK Biobank men and genetic outcome data from the PRACTICAL consortium (79 148 cases and 61 106 controls). We used cis- and all (cis and trans) SNP MR approaches. A total of 5402 men were diagnosed with and 295 died from prostate cancer (mean follow-up 6.9 years). Higher circulating IGF-I was associated with elevated prostate cancer diagnosis (HR per 5 nmol/L increment = 1.09, 95% CI 1.05-1.12) and mortality (HR per 5 nmol/L increment = 1.15, 1.02-1.29). MR analyses also supported the role of IGF-I in prostate cancer diagnosis (cis-MR odds ratio per 5 nmol/L increment = 1.34, 1.07-1.68). In observational analyses, higher free testosterone was associated with a higher risk of prostate cancer (HR per 50 pmol/L increment = 1.10, 1.05-1.15). Higher SHBG was associated with a lower risk (HR per 10 nmol/L increment = 0.95, 0.94-0.97), neither was associated with prostate cancer mortality. Total testosterone was not associated with prostate cancer. These findings implicate IGF-I and free testosterone in prostate cancer development and/or progression.
38 citations
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01 Jan 2019Abstract: This paper reviews a theory of causal inference based on the Structural Causal Model (SCM) described in (Pearl, 2000a). The theory unifies the graphical, potential-outcome (Neyman-Rubin), decision analytical, and structural equation approaches to causation, and provides both a mathematical foundation and a friendly calculus for the analysis of causes and counterfactuals. In particular, the paper establishes a methodology for inferring (from a combination of data and assumptions) the answers to three types of causal queries: (1) queries about the effect of potential interventions, (2) queries about counterfactuals, and (3) queries about the direct (or indirect) effect of one event on another.
579 citations
01 Jan 2018
Abstract: We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency <5%, 14 with estimated allelic odds ratio >2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
379 citations
01 Jan 2012
TL;DR: In this article, the associations of metabolites with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways, using regression models adjusted for age, waist, and standard lipids.
Abstract: Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gln but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.
230 citations
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TL;DR: A review of the established modifiable and inherited risk factors for pancreatic cancer can be found in this paper, where the authors provide an up-to-date overview of these risk factors.
Abstract: Pancreatic cancer is a leading cause of cancer death worldwide and its global burden has more than doubled over the past 25 years. The highest incidence regions for pancreatic cancer include North America, Europe and Australia, and although much of this increase is due to ageing worldwide populations, there are key modifiable risk factors for pancreatic cancer such as cigarette smoking, obesity, diabetes and alcohol intake. The prevalence of these risk factors is increasing in many global regions, resulting in increasing age-adjusted incidence rates for pancreatic cancer, but the relative contribution from these risk factors varies globally due to variation in the underlying prevalence and prevention strategies. Inherited genetic factors, although not directly modifiable, are an important component of pancreatic cancer risk, and include pathogenic variants in hereditary cancer genes, genes associated with hereditary pancreatitis, as well as common variants identified in genome-wide association studies. Identification of the genetic changes that underlie pancreatic cancer not only provides insight into the aetiology of this cancer but also provides an opportunity to guide early detection strategies. The goal of this Review is to provide an up-to-date overview of the established modifiable and inherited risk factors for pancreatic cancer.
204 citations