Docosapentaenoic acid and lung cancer risk: A Mendelian randomization study

Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants

BACKGROUND

While circulating metabolites have been increasingly linked to cancer risk, the causality underlying these associations remains largely uninterrogated.

METHODS

We conducted a comprehensive 2-sample Mendelian randomization (MR) study to evaluate the potential causal relationship between 913 plasma metabolites and the risk of seven cancers among European-ancestry individuals. Data on variant-metabolite associations were obtained from a genome-wide association study (GWAS) of plasma metabolites among 14,296 subjects. Data on variant-cancer associations were gathered from large-scale GWAS consortia for breast (N = 266,081), colorectal (N = 185,616), lung (N = 85,716), ovarian (N = 63,347), prostate (N = 140,306), renal cell (N = 31,190), and testicular germ cell (N = 28,135) cancers. MR analyses were performed with the inverse variance-weighted (IVW) method as the primary strategy to identify significant associations at Bonferroni-corrected P < 0.05 for each cancer type separately. Significant associations were subjected to additional scrutiny via weighted median MR, Egger regression, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and reverse MR analyses. Replication analyses were performed using an independent dataset from a plasma metabolite GWAS including 8,129 participants of European ancestry.

RESULTS

We identified 94 significant associations, suggesting putative causal associations between 66 distinct plasma metabolites and the risk of seven cancers. Remarkably, 68.2% (45) of these metabolites were each associated with the risk of a specific cancer. Among the 66 metabolites, O-methylcatechol sulfate and 4-vinylphenol sulfate demonstrated the most pronounced positive and negative associations with cancer risk, respectively. Genetically proxied plasma levels of these two metabolites were significantly associated with the risk of lung cancer and renal cell cancer, with an odds ratio and 95% confidence interval of 2.81 (2.33-3.37) and 0.49 (0.40-0.61), respectively. None of these 94 associations was biased by weak instruments, horizontal pleiotropy, or reverse causation. Further, 64 of these 94 were eligible for replication analyses, and 54 (84.4%) showed P < 0.05 with association patterns consistent with those shown in primary analyses.

CONCLUSIONS

Our study unveils plausible causal relationships between 66 plasma metabolites and cancer risk, expanding our understanding of the role of circulating metabolites in cancer genetics and etiology. These findings hold promise for enhancing cancer risk assessment and prevention strategies, meriting further exploration.

The association between circulating docosahexaenoic acid and lung cancer: A Mendelian randomization study

BACKGROUND

Lung cancer is a malignant tumor with a high incidence, it is vital to identify modifiable and avoidable risk factors for primary prevention, which can significantly lower the risk of cancer by preventing exposure to hazards and altering risky behavior. Some observational studies suggest that an increase in docosahexaenoic acid (DHA) consumption can reduce lung cancer risk. However, interpretation of these observational findings is difficult due to residual confounding or reverse causality. To evaluate the link between DHA and lung cancer, we have undertaken this analysis to examine the causal association between DHA and the risk of lung cancer using a two-sample Mendelian randomization (MR) framework.

METHODS

We performed a two-sample MR analysis to evaluate the causal effect of plasma DHA levels on lung cancer risk. For the exposure data, we extracted genetic variants as instrumental variables (IVs) that are strongly associated with DHA from a large-scale genome-wide association study (GWAS). We obtained the corresponding effect estimates for IVs on the risk of lung cancer with 11,348 cases and 15,861 controls. Finally, we applied Mendelian randomization analysis to obtain preliminary MR results and performed sensitivity analyses to verify the robustness of our results.

RESULTS

According to the primary MR estimates and further sensitivity analyses, a higher serum DHA level was associated with a higher risk of lung cancer [OR = 1.159, 95% CI (1.04-1.30), P = 0.01]. For lung adenocarcinoma, the results also showed a close correlation between the DHA level and lung adenocarcinoma [OR = 1.277, 95% CI (1.09-1.50), P = 0.003], but it was not statistically significant for squamous cell carcinoma [OR = 1.071, 95% CI (0.89-1.29), P = 0.467].

CONCLUSIONS

Our study revealed that plasma DHA is positively associated with the risk of lung cancer overall, especially for lung adenocarcinoma. This study provides new information to develop dietary guidelines for primary lung cancer prevention.

A Causal Relationship between Vitamin C Intake with Hyperglycemia and Metabolic Syndrome Risk: A Two-Sample Mendelian Randomization Study

Excessive oxidative stress can contribute to metabolic syndrome (MetS), and antioxidants can protect against its development. Vitamin C (VC) is a well-known antioxidant, and observational studies have associated a deficiency with an increased MetS risk. This study tested the hypothesis that dietary VC intake caused an inverse relation of MetS and its components risk using a two-sample Mendelian randomization (MR) method in adults ≥40 years in a city hospital-based (n = 58,701) and Ansan/Ansung plus rural (n = 13,598) cohorts. Independent genetic variants associated with dietary VC intake were explored using a genome-wide association study (GWAS) with significance levels of p < 5 × 10−5 and linkage disequilibrium (r2 threshold of 0.001), after adjusting for the covariates related to MetS, in a city hospital-based cohort (n = 52,676) excluding the participants having vitamin supplementation. MR methods, including inverse-variance weighting (IVW), weighted median, MR-Egger, and weighted model, were used to determine the causal relationship between the dietary VC intake and the risk of MetS and its components in Ansan/Ansung plus rural cohorts (n = 11,733). Heterogeneity and leave-one-out sensitivity analyses were conducted. Energy intake, as well as other nutrient intakes, were significantly lower in the low VC intake group than in the high VC intake group, but the incidence of MetS and its components, including hyperglycemia, hypertriglyceridemia, and hypertension, was observationally higher in inadequate low VC intake in the combined cohorts. In MR analysis, insufficient dietary VC intake increased the risk of MetS, hyperglycemia, hypertriglyceridemia, and hypertension in an IVW (p < 0.05). In contrast, only the serum fasting blood glucose concentration was significantly associated with VC intake in weight median analysis (p < 0.05), but there was no significant association of low dietary VC with MetS and its components in MR-Egger. There was no likelihood of heterogeneity and horizontal pleiotropy in MetS and its components. A single genetic variant did not affect their association in the leave-one-out sensitivity analysis. In conclusion, insufficient dietary VC intake potentially increased the MetS and hyperglycemia risk in Asian adults. Low VC intake can contribute to increasing type 2 diabetes incidence in Asians.

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.

Combined application of high-throughput sequencing and UHPLC-Q/TOF-MS-based metabolomics in the evaluation of microorganisms and metabolites of dry-cured ham of different origins

Ham fermentation relies on environmental and indigenous microorganisms forming a rich microbiome, which is pivotal to taste and flavor formation. Previous studies have focused on the appearance of differences of microorganisms and metabolites, this study aims to establish the relationship between microorganisms and metabolites over a period of two years in the fermentation of hams from Jinghua (JH2), Xuanwei (XW2), Rugao (RG2), Iberian (IB2) and Parma (PA2). We profiled bacterial communities by sequencing the V3-V4 region of the 16S rRNA genes and metabolites were analyzed using LC-Q-TOF-MS. LefSe analysis showed that different biomarkers in five ham groups. OPLS analysis showed that most differential metabolites are amino acids and were associated with four metabolic pathways. Correlation analysis implies a firm positive relationship between microorganisms and metabolites. This study provides novel insights into the taste and flavor quality of dry-cured hams of different origins due to fermentation.

Plasma-metabolite-based machine learning is a promising diagnostic approach for esophageal squamous cell carcinoma investigation

The aim of this study was to develop a diagnostic strategy for esophageal squamous cell carcinoma (ESCC) that combines plasma metabolomics with machine learning algorithms. Plasma-based untargeted metabolomics analysis was performed with samples derived from 88 ESCC patients and 52 healthy controls. The dataset was split into a training set and a test set. After identification of differential metabolites in training set, single-metabolite-based receiver operating characteristic (ROC) curves and multiple-metabolite-based machine learning models were used to distinguish between ESCC patients and healthy controls. Kaplan-Meier survival analysis and Cox proportional hazards regression analysis were performed to investigate the prognostic significance of the plasma metabolites. Finally, twelve differential plasma metabolites (six up-regulated and six down-regulated) were annotated. The predictive performance of the six most prevalent diagnostic metabolites through the diagnostic models in the test set were as follows: arachidonic acid (accuracy: 0.887), sebacic acid (accuracy: 0.867), indoxyl sulfate (accuracy: 0.850), phosphatidylcholine (PC) (14:0/0:0) (accuracy: 0.825), deoxycholic acid (accuracy: 0.773), and trimethylamine N-oxide (accuracy: 0.653). The prediction accuracies of the machine learning models in the test set were partial least-square (accuracy: 0.947), random forest (accuracy: 0.947), gradient boosting machine (accuracy: 0.960), and support vector machine (accuracy: 0.980). Additionally, survival analysis demonstrated that acetoacetic acid was an unfavorable prognostic factor (hazard ratio (HR): 1.752), while PC (14:0/0:0) (HR: 0.577) was a favorable prognostic factor for ESCC. This study devised an innovative strategy for ESCC diagnosis by combining plasma metabolomics with machine learning algorithms and revealed its potential to become a novel screening test for ESCC.

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Six most prevalent diagnostic plasma metabolites were identified in ESCC.

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Plasma-metabolite-based machine learning models (PLS, RF, GBM, and SVM) for ESCC diagnosis.

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Acetoacetic acid was an unfavorable prognostic factor, while PC (14:0/0:0) was a favorable prognostic factor for ESCC.

Causal Effects of N-6 Polyunsaturated Fatty Acids on Age-related Macular Degeneration: A Mendelian Randomization Study

CONTEXT

Although the role of n-6 polyunsaturated fatty acids (PUFAs) in age-related macular degeneration (AMD) has been studied in previous observational studies, the precise manner in which 1 or more n-6 PUFAs account for this relationship remains unclear.

OBJECTIVE

Using genetic instruments for n-6 PUFAs traits implemented through mendelian randomization (MR), we aimed to study possible causal associations between n-6 PUFAs and AMD.

METHODS

The 2-sample MR method was used to obtain unconfounded causal estimates. We selected genetic variants strongly associated (P < 5 × 10-8) with circulating linoleic acid (LA) and arachidonic acid (AA) from a study involving 8 631 individuals and applied to an AMD case-control study (33 526 participants and 16 144 cases). The weighted median and MR Egger methods were used for the sensitivity analysis.

RESULTS

Our MR analysis suggested that circulating LA was a causal protective factor for AMD, with an odds ratio (OR) estimate of 0.967 (95% CI 0.945 to 0.990; P = .005) per percentage in total fatty acid increase in LA. In contrast, higher genetically predicted circulating AA causally increased the AMD risk (OR = 1.034; 95% CI 1.012 to 1.056; P = .002). Sensitivity analysis provided no indication of unknown pleiotropy. The findings from different single-nucleotide polymorphism selections and analytic methods were consistent, suggesting the robustness of the causal associations.

CONCLUSION

Our study provided genetic evidence that circulating LA accounted for protective effects of n-6 PUFAs against the risk of AMD, whereas AA was responsible for deleterious effects on higher AMD risk.

Polyunsaturated Fatty Acid Levels and the Risk of Keratinocyte Cancer: A Mendelian Randomization Analysis

BACKGROUND

Keratinocyte cancer is the commonest cancer, imposing a high economic burden on the health care system. Observational studies have shown mixed associations between polyunsaturated fatty acids (PUFA) and keratinocyte cancer, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). We explored whether genetically predicted PUFA levels are associated with BCC and SCC risks.

METHODS

We conducted a two-sample Mendelian randomization study using PUFA level genome-wide association studies (GWAS) from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n > 8,000), and the meta-analysis GWASs from UKB, 23andMe, and Qskin for BCC (n = 651,138) and SCC (n = 635,331) risk.

RESULTS

One SD increase in genetically predicted levels of linoleic acid [OR = 0.94, 95% confidence interval (CI) = 0.91-0.97, P = 1.4 × 10^-4] and alpha-linolenic acid (OR = 0.91, 95% CI = 0.86-0.96, P = 5.1 × 10^-4) was associated with a reduced BCC risk, while arachidonic acid (OR = 1.04, 95% CI = 1.02-1.06, P = 3.2 × 10^-4) and eicosapentaenoic acid (OR = 1.10, 95% CI = 1.04-1.16, P = 1.5 × 10^-3) were associated with an increased BCC risk.

CONCLUSIONS

Higher genetically predicted levels of linoleic acid and alpha-linolenic acid were associated with a reduced BCC risk, but arachidonic acid and eicosapentaenoic acid were associated with a higher BCC risk.

IMPACT

PUFA-related diet and supplementation could influence BCC etiology.

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.

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.