Metabolome-wide association study identified the association between a circulating polyunsaturated fatty acids variant rs174548 and lung cancer

Novel insights into the genetic architecture of pregnancy glycemic traits from 14,744 Chinese maternities

Glycemic traits are critical indicators of maternal and fetal health during pregnancy. We performed genetic analysis for five glycemic traits in 14,744 Chinese pregnant women. Our genome-wide association study identified 25 locus-trait associations, including established links between gestational diabetes mellitus (GDM) and the genes CDKAL1 and MTNR1B. Notably, we discovered a novel association between fasting glucose during pregnancy and the ESR1 gene (estrogen receptor), which was validated by an independent study in pregnant women. The ESR1-GDM link was recently reported by the FinnGen project. Our work enhances the findings in East Asian populations and highlights the need for independent studies. Further analyses, including genetic correlation, Mendelian randomization, and transcriptome-wide association studies, provided genetic insights into the relationship between pregnancy glycemic traits and hypertension. Overall, our findings advance the understanding of genetic architecture of pregnancy glycemic traits, especially in East Asian populations.

The association between genetically elevated polyunsaturated fatty acids and risk of cancer

BACKGROUND

The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain.

METHODS

Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures.

FINDINGS

Genetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07-1.11]), esophageal squamous cell carcinoma (1.16 [1.06-1.26]), lung cancer (1.06 [1.03-1.08]) and basal cell carcinoma (1.05 [1.02-1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99-1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99-1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95-1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98-1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding.

INTERPRETATION

The PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease.

FUNDING

Cancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

Metabolic and Genetic Markers Improve Prediction of Incident Type 2 Diabetes: A Nested Case-Control Study in Chinese

CONTEXT

It is essential to improve the current predictive ability for type 2 diabetes (T2D) risk.

OBJECTIVE

We aimed to identify novel metabolic markers for future T2D in Chinese individuals of Han ethnicity and to determine whether the combined effect of metabolic and genetic markers improves the accuracy of prediction models containing clinical factors.

METHODS

A nested case-control study containing 220 incident T2D patients and 220 age- and sex- matched controls from normoglycemic Chinese individuals of Han ethnicity was conducted within the Wuxi Non-Communicable Disease cohort with a 12-year follow-up. Metabolic profiling detection was performed by high-performance liquid chromatography‒mass spectrometry (HPLC-MS) by an untargeted strategy and 20 single nucleotide polymorphisms (SNPs) associated with T2D were genotyped using the Iplex Sequenom MassARRAY platform. Machine learning methods were used to identify metabolites associated with future T2D risk.

RESULTS

We found that abnormal levels of 5 metabolites were associated with increased risk of future T2D: riboflavin, cnidioside A, 2-methoxy-5-(1H-1, 2, 4-triazol-5-yl)- 4-(trifluoromethyl) pyridine, 7-methylxanthine, and mestranol. The genetic risk score (GRS) based on 20 SNPs was significantly associated with T2D risk (OR = 1.35; 95% CI, 1.08-1.70 per SD). The area under the receiver operating characteristic curve (AUC) was greater for the model containing metabolites, GRS, and clinical traits than for the model containing clinical traits only (0.960 vs 0.798, P = 7.91 × 10-16).

CONCLUSION

In individuals with normal fasting glucose levels, abnormal levels of 5 metabolites were associated with future T2D. The combination of newly discovered metabolic markers and genetic markers could improve the prediction of incident T2D.

Fatty acid desaturase 1 (FADS1) is a cancer marker for patient survival and a potential novel target for precision cancer treatment

Fatty Acid Desaturase-1 (FADS1) or delta 5 desaturase (D5D) is a rate-limiting enzyme involved in the biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFAs), i.e., arachidonic acid (ARA) and eicosapentaenoic (EPA). These LC-PUFAs and their metabolites play essential and broad roles in cancer cell proliferation, metastasis, and tumor microenvironment. However, the role of FADS1 in cancers remains incompletely understood. Utilizing The Cancer Genome Atlas (TCGA) database, we explored the role of FADS1 across different cancer types using multiple bioinformatics and statistical tools. Moreover, we studied the impact of a FADS1 inhibitor (D5D-IN-326) on proliferation of multiple cancer cell lines. We identified that FADS1 gene is a predictor for cancer survival in multiple cancer types. Compared to normal tissue, the mRNA expression of FADS1 is significantly increased in primary tumors while even higher in metastatic and recurrent tumors. Mechanistically, pathway analysis demonstrated that FADS1 is associated with cholesterol biosynthesis and cell cycle control genes. Interestingly, FADS1 expression is higher when TP53 is mutated. Tumors with increased FADS1 expression also demonstrated an increased signatures of fibroblasts and macrophages infiltration among most cancer types. Our in vitro assays showed that D5D-IN-326 significantly inhibited cell proliferation of kidney, colon, breast, and lung cancer cell lines in a dose-dependent manner. Lastly, single nucleotide polymorphisms (SNPs) which are well-established expression quantitative trait loci (eQTLs) for FADS1 in normal human tissues are also significantly correlated with FADS1 expression in tumors of multiple tissue types, potentially serving as a marker to stratify cancer patients with high/low FADS1 expression in their tumor tissue. Our study suggests that FADS1 plays multiple roles in cancer biology and is potentially a novel target for precision cancer treatment.

An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference

SUMMARY

An R package that can implement multiple linear learners, including penalized regression and regression with spike and slab priors, in a single model has been developed. Solutions are obtained with fast minorize-maximization algorithms in the framework of variational Bayesian inference. This package helps to incorporate multimodal and high-dimensional explanatory variables in a single regression model.

AVAILABILITY AND IMPLEMENTATION

The R package VIGoR (Variational Bayesian Inference for Genome-wide Regression) is available at the Comprehensive R Archive Network (CRAN) (https://cran.r-project.org/) and at github (https://github.com/Onogi/VIGoR).

SUPPLEMENTARY INFORMATION

Supplementary Materials are provided at the journal homepage. R scripts to reproduce the experiment results and pdf manual of the package are provided at https://github.com/Onogi/VIGoR.

Systematic review of Mendelian randomization studies on risk of cancer

BACKGROUND

We aimed to map and describe the current state of Mendelian randomization (MR) literature on cancer risk and to identify associations supported by robust evidence.

METHODS

We searched PubMed and Scopus up to 06/10/2020 for MR studies investigating the association of any genetically predicted risk factor with cancer risk. We categorized the reported associations based on a priori designed levels of evidence supporting a causal association into four categories, namely robust, probable, suggestive, and insufficient, based on the significance and concordance of the main MR analysis results and at least one of the MR-Egger, weighed median, MRPRESSO, and multivariable MR analyses. Associations not presenting any of the aforementioned sensitivity analyses were not graded.

RESULTS

We included 190 publications reporting on 4667 MR analyses. Most analyses (3200; 68.6%) were not accompanied by any of the assessed sensitivity analyses. Of the 1467 evaluable analyses, 87 (5.9%) were supported by robust, 275 (18.7%) by probable, and 89 (6.1%) by suggestive evidence. The most prominent robust associations were observed for anthropometric indices with risk of breast, kidney, and endometrial cancers; circulating telomere length with risk of kidney, lung, osteosarcoma, skin, thyroid, and hematological cancers; sex steroid hormones and risk of breast and endometrial cancer; and lipids with risk of breast, endometrial, and ovarian cancer.

CONCLUSIONS

Despite the large amount of research on genetically predicted risk factors for cancer risk, limited associations are supported by robust evidence for causality. Most associations did not present a MR sensitivity analysis and were thus non-evaluable. Future research should focus on more thorough assessment of sensitivity MR analyses and on more transparent reporting.

Investigation of Causal Effect of Type 2 Diabetes Mellitus on Lung Cancer: A Mendelian Randomization Study

Background

Although several observational studies have attempted to investigate the association between type 2 diabetes mellitus (T2DM) and lung cancer risk, the results are controversial. Here, we intend to examine whether there is a causal association between T2DM and lung cancer risk.

Materials and Methods

We conducted a Mendelian randomization (MR) study to systematically investigate the effect of T2DM on lung cancer among 13,327 cases and 13,328 controls. A weighted genetic risk score (wGRS) was constructed as a proxy instrument by using 82 previously reported T2DM-related single nucleotide polymorphisms (SNPs). The logistic regression model was utilized to estimate associations of T2DM-related SNPs and wGRS with lung cancer risk. Sensitivity analyses were also performed to assess the robustness of the observed associations.

Results

We found no evidence for a causal relationship between T2DM and lung cancer risk (odds ratio, OR = 0.96, 95% confidence interval: 0.91–1.01, p = 0.96), and the association did not vary among populations of different age, sex, smoking status, and histological type. Sensitivity analyses (e.g., MR-Egger test) suggest that pleiotropic effects did not bias the result.

Conclusion

In this MR study with a large number of lung cancer cases, we found no evidence to support the causal role of T2DM in lung cancer risk. Further large-scale prospective studies are warranted to replicate our findings.

Delta-5-desaturase: A novel therapeutic target for cancer management

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D5D is an independent prognostic factor in cancer.

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D5D aggravates cancer progression via mediating AA/PGE₂ production from DGLA.

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AA/PGE₂ promotes cancer progression via regulating the tumor microenvironment.

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Inhibition of D5D redirects COX-2 catalyzed DGLA peroxidation, producing 8-HOA.

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8-HOA suppress cancer by regulating proliferation, apoptosis, and metastasis.

Delta-5 desaturase (D5D) is a rate-limiting enzyme that introduces double-bonds to the delta-5 position of the n-3 and n-6 polyunsaturated fatty acid chain. Since fatty acid metabolism is a vital factor in cancer development, several recent studies have revealed that D5D activity and expression could be an independent prognostic factor in cancers. However, the mechanistic basis of D5D in cancer progression is still controversial. The classical concept believes that D5D could aggravate cancer progression via mediating arachidonic acid (AA)/prostaglandin E₂ production from dihomo-γ-linolenic acid (DGLA), resulting in activation of EP receptors, inflammatory pathways, and immunosuppression. On the contrary, D5D may prevent cancer progression through activating ferroptosis, which is iron-dependent cell death. Suppression of D5D by RNA interference and small-molecule inhibitor has been identified as a promising anti-cancer strategy. Inhibition of D5D could shift DGLA peroxidation pattern from generating AA to a distinct anti-cancer free radical byproduct, 8-hydroxyoctanoic acid, resulting in activation of apoptosis pathway and simultaneously suppression of cancer cell survival, proliferation, migration, and invasion. Hence, understanding the molecular mechanisms of D5D on cancer may therefore facilitate the development of novel therapeutical applications. Given that D5D may serve as a promising target in cancer, in this review, we provide an updated summary of current knowledge on the role of D5D in cancer development and potentially useful therapeutic strategies.

A modifiable risk factors atlas of lung cancer: A Mendelian randomization study

BACKGROUND

There has been no study systematically assessing the causal effects of putative modifiable risk factors on lung cancer. In this study, we aimed to construct a modifiable risk factors atlas of lung cancer by using the two-sample Mendelian randomization framework.

METHODS

We included 46 modifiable risk factors identified in previous studies. Traits with p-value smaller than 0.05 were considered as suggestive risk factors. While the Bonferroni corrected p-value for significant risk factors was set to be 8.33 × 10-4 .

RESULTS

In this two-sample Mendelian randomization analysis, we found that higher socioeconomic status was significantly correlated with lower risk of lung cancer, including years of schooling, college or university degree, and household income. While cigarettes smoked per day, time spent watching TV, polyunsaturated fatty acids, docosapentaenoic acid, eicosapentaenoic acid, and arachidonic acid in blood were significantly associated with higher risk of lung cancer. Suggestive risk factors for lung cancer were found to be serum vitamin A1, copper in blood, docosahexaenoic acid in blood, and body fat percentage.

CONCLUSIONS

This study provided the first Mendelian randomization assessment of the causality between previously reported risk factors and lung cancer risk. Several modifiable targets, concerning socioeconomic status, lifestyle, dietary, and obesity, should be taken into consideration for the development of primary prevention strategies for lung cancer.

Pleiotropic effects of telomere length loci with brain morphology and brain tissue expression

Several studies have reported association between leukocyte telomere length (LTL) and neuropsychiatric disorders. Although telomere length is affected by environmental factors, genetic variants in certain loci are strongly associated with LTL. Thus, we aimed to identify the genomic relationship between genetic variants of LTL with brain-based regulatory changes and brain volume. We tested genetic colocalization of seven and nine LTL loci in two ancestry groups, European (EUR) and East-Asian (EAS), respectively, with brain morphology measures for 101 T1-magnetic resonance imaging-based region of interests (n = 21 821). The posterior probability (>90%) was observed for 'fourth ventricle', 'gray matter' and 'cerebellar vermal lobules I-IV' volumes. We then tested causal relationship using LTL loci for gene and methylation expression. We found causal pleiotropy for gene (EAS = four genes; EUR = five genes) and methylation expression (EUR = 17 probes; EAS = 4 probes) of brain tissues (P ≤ 2.47 × 10-6). Integrating chromatin profiles with LTL-single nucleotide polymorphisms identified 45 genes (EUR) and 79 genes (EAS) (P ≤ 9.78×10-7). We found additional 38 LTL-genes using chromatin-based gene mapping for EUR ancestry population. Gene variants in three LTL-genes-GPR37, OBFC1 and RTEL1/RTEL1-TNFRSF6B-show convergent evidence of pleiotropy with brain morphology, gene and methylation expression and chromatin association. Mapping gene functions to drug-gene interactions, we identified process 'transmission across chemical synapses' (P < 2.78 × 10-4). This study provides evidence that genetic variants of LTL have pleiotropic roles with brain-based effects that could explain the phenotypic association of LTL with several neuropsychiatric traits.

Cross-Cancer Pleiotropic Analysis Reveals Novel Susceptibility Loci for Lung Cancer

Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with cancer risk, several of which have shown pleiotropic effects across cancers. Therefore, we performed a systematic cross-cancer pleiotropic analysis to detect the effects of GWAS-identified variants from non-lung cancers on lung cancer risk in 12,843 cases and 12,639 controls from four lung cancer GWASs. The overall association between variants in each cancer and risk of lung cancer was explored using sequential kernel association test (SKAT) analysis. For single variant analysis, we combined the result of specific study using fixed-effect meta-analysis. We performed functional exploration of significant associations based on features from public databases. To further detect the biological mechanism underlying identified observations, pathway enrichment analysis were conducted with R package “clusterProfiler.” SNP-set analysis revealed the overall associations between variants of 8 cancer types and lung cancer risk. Single variant analysis identified 6 novel SNPs related to lung cancer risk after multiple correction (P_fdr < 0.10), including rs1707302 (1p34.1, OR = 0.93, 95% CI: 0.90–0.97, P = 7.60 × 10⁻⁴), rs2516448 (6p21.33, OR = 1.07, 95% CI: 1.03–1.11, P = 1.00 × 10⁻³), rs3869062 (6p22.1, OR = 0.91, 95% CI: 0.86–0.96, P = 7.10 × 10⁻⁴), rs174549 (11q12.2, OR = 0.90, 95% CI: 0.87–0.94, P = 1.00 × 10⁻⁷), rs7193541 (16q23.1, OR = 0.93, 95% CI: 0.90–0.96, P = 1.20 × 10⁻⁴), and rs8064454 (17q12, OR = 1.07, 95% CI: 1.03–1.11, P = 4.30 × 10⁻⁴). The eQTL analysis and functional annotation suggested that these variants might modify lung cancer susceptibility through regulating the expression of related genes. Pathway enrichment analysis showed that genes modulated by these variants play important roles in cancer carcinogenesis. Our findings demonstrate the pleiotropic associations between non-lung cancer susceptibility loci and lung cancer risk, providing important insights into the shared mechanisms of carcinogenesis across cancers.

Lung Cancer Risk in Never-Smokers of European Descent is Associated With Genetic Variation in the 5p15.33 TERT-CLPTM1Ll Region

INTRODUCTION

Inherited susceptibility to lung cancer risk in never-smokers is poorly understood. The major reason for this gap in knowledge is that this disease is relatively uncommon (except in Asians), making it difficult to assemble an adequate study sample. In this study we conducted a genome-wide association study on the largest, to date, set of European-descent never-smokers with lung cancer.

METHODS

We conducted a two-phase (discovery and replication) genome-wide association study in never-smokers of European descent. We further augmented the sample by performing a meta-analysis with never-smokers from the recent OncoArray study, which resulted in a total of 3636 cases and 6295 controls. We also compare our findings with those in smokers with lung cancer.

RESULTS

We detected three genome-wide statistically significant single nucleotide polymorphisms rs31490 (odds ratio [OR]: 0.769, 95% confidence interval [CI]: 0.722-0.820; p value 5.31 × 10-16), rs380286 (OR: 0.770, 95% CI: 0.723-0.820; p value 4.32 × 10-16), and rs4975616 (OR: 0.778, 95% CI: 0.730-0.829; p value 1.04 × 10-14). All three mapped to Chromosome 5 CLPTM1L-TERT region, previously shown to be associated with lung cancer risk in smokers and in never-smoker Asian women, and risk of other cancers including breast, ovarian, colorectal, and prostate.

CONCLUSIONS

We found that genetic susceptibility to lung cancer in never-smokers is associated to genetic variants with pan-cancer risk effects. The comparison with smokers shows that top variants previously shown to be associated with lung cancer risk only confer risk in the presence of tobacco exposure, underscoring the importance of gene-environment interactions in the etiology of this disease.

Docosapentaenoic acid and lung cancer risk: A Mendelian randomization study

BACKGROUND

Observational studies have shown that excessive dietary fat may be associated with lung carcinogenesis. However, findings from previous studies are inconsistent and it remains unclear whether docosapentaenoic acid (DPA), a kind of polyunsaturated fatty acid, is linked to the risk of lung cancer. The aim of this study is to investigate the causal effect of DPA on lung cancer with Mendelian randomization (MR) method.

METHODS

With a two-sample MR approach, we analyzed the summary data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE, 8866 individuals of European ancestry) Consortium and International Lung Cancer Consortium (ILCCO, 11 348 lung cancer cases and 15 861 controls; European ancestry) to assess the possible causal relationship of DPA on the risk of lung cancer.

RESULTS

Our results indicated that genetically predicted higher DPA level has a positive association with lung cancer, where 1% higher DPA was associated with a 2.01-fold risk of lung cancer (odds ratio [OR]: 2.01, 95% CI = 1.34-3.01; P = 7.40 × 10^-4 ). Additionally, lung cancer was not a causal factor for DPA. The results of MR-Egger regression analysis showed that there was no evidence for the presence of directional horizontal pleiotropy.

CONCLUSIONS

Genetically elevated DPA is positively associated with risk of lung cancer, and more work is needed to investigate the potential mechanisms.

Metabolomics in the study of retinal health and disease

Metabolomics is the qualitative and quantitative assessment of the metabolites (small molecules < 1.5 kDa) in body fluids. The metabolites are the downstream of the genetic transcription and translation processes and also downstream of the interactions with environmental exposures; thus, they are thought to closely relate to the phenotype, especially for multifactorial diseases. In the last decade, metabolomics has been increasingly used to identify biomarkers in disease, and it is currently recognized as a very powerful tool with great potential for clinical translation. The metabolome and the associated pathways also help improve our understanding of the pathophysiology and mechanisms of disease. While there has been increasing interest and research in metabolomics of the eye, the application of metabolomics to retinal diseases has been limited, even though these are leading causes of blindness. In this manuscript, we perform a comprehensive summary of the tools and knowledge required to perform a metabolomics study, and we highlight essential statistical methods for rigorous study design and data analysis. We review available protocols, summarize the best approaches, and address the current unmet need for information on collection and processing of tissues and biofluids that can be used for metabolomics of retinal diseases. Additionally, we critically analyze recent work in this field, both in animal models and in human clinical disease, including diabetic retinopathy and age-related macular degeneration. Finally, we identify opportunities for future research applying metabolomics to improve our current assessment and understanding of mechanisms of vitreoretinal diseases, and to hence improve patient assessment and care.

Whole-genome sequencing reveals genomic signatures associated with the inflammatory microenvironments in Chinese NSCLC patients

Chinese lung cancer patients have distinct epidemiologic and genomic features, highlighting the presence of specific etiologic mechanisms other than smoking. Here, we present a comprehensive genomic landscape of 149 non-small cell lung cancer (NSCLC) cases and identify 15 potential driver genes. We reveal that Chinese patients are specially characterized by not only highly clustered EGFR mutations but a mutational signature (MS3, 33.7%), that is associated with inflammatory tumor-infiltrating B lymphocytes (P = 0.001). The EGFR mutation rate is significantly increased with the proportion of the MS3 signature (P = 9.37 × 10⁻⁵). TCGA data confirm that the infiltrating B lymphocyte abundance is significantly higher in the EGFR-mutated patients (P = 0.007). Additionally, MS3-high patients carry a higher contribution of distant chromosomal rearrangements >1 Mb (P = 1.35 × 10⁻⁷), some of which result in fusions involving genes with important functions (i.e., ALK and RET). Thus, inflammatory infiltration may contribute to the accumulation of EGFR mutations, especially in never-smokers.

The distinct genomic and epidemiological features of Chinese lung cancer patients suggest the presence of alternative causal mechanisms. Here, the authors present the genomic landscape of 149 Chinese NSCLC patients and reveal distinct mutational signatures associated with inflammatory microenvironments.

Mendelian randomization studies of cancer risk: a literature review

Purpose of review

In this paper, we summarize prior studies that have used Mendelian Randomization (MR) methods to study the effects of exposures, lifestyle factors, physical traits, and/or biomarkers on cancer risk in humans. Many such risk factors have been associated with cancer risk in observational studies, and the MR approach can be used to provide evidence as to whether these associations represent causal relationships. MR methods require a risk factor of interest to have known genetic determinants that can be used as proxies for the risk factor (i.e., "instrumental variables" or IVs), and these can be used to obtain an effect estimate that, under certain assumptions, is not prone to bias caused by unobserved confounding or reverse causality. This review seeks to describe how MR studies have contributed to our understanding of cancer causation.

Recent findings

We searched the published literature and identified 76 MR studies of cancer risk published prior to October 31, 2017. Risk factors commonly studied included alcohol consumption, Vitamin D, anthropometric traits, telomere length, lipid traits, glycemic traits, and markers of inflammation. Risk factors showing compelling evidence of a causal association with risk for at least one cancer type include alcohol consumption (for head/neck and colorectal), adult body mass index (increases risk for multiple cancers, but decreases risk for breast), height (increases risk for breast, colorectal, and lung; decreases risk for esophageal), telomere length (increases risk for lung adenocarcinoma, melanoma, renal cell carcinoma, glioma, B-cell lymphoma subtypes, chronic lymphocytic leukemia, and neuroblastoma), and hormonal factors (affects risk for sex-steroid sensitive cancers).

Summary

This review highlights alcohol consumption, body mass index, height, telomere length, and the hormonal exposures as factors likely to contribute to cancer causation. This review also highlights the need to study specific cancer types, ideally subtypes, as the effects of risk factors can be heterogeneous across cancer types. As consortia-based genome-wide association studies increase in sample size and analytical methods for MR continue to become more sophisticated, MR will become an increasingly powerful tool for understanding cancer causation.