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Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization.

ABSTRACT: At the time of cancer diagnosis, body mass index (BMI) is inversely correlated with lung cancer risk, which may reflect reverse causality and confounding due to smoking behavior. We used two-sample univariable and multivariable Mendelian randomization (MR) to estimate causal relationships of BMI and smoking behaviors on lung cancer and histological subtypes based on an aggregated genome-wide association studies (GWASs) analysis of lung cancer in 29 266 cases and 56 450 controls. We observed a positive causal effect for high BMI on occurrence of small-cell lung cancer (odds ratio (OR) = 1.60, 95% confidence interval (CI) = 1.24-2.06, P = 2.70 × 10^-4 ). After adjustment of smoking behaviors using multivariable Mendelian randomization (MVMR), a direct causal effect on small cell lung cancer (OR_MVMR = 1.28, 95% CI = 1.06-1.55, P_MVMR = .011), and an inverse effect on lung adenocarcinoma (OR_MVMR = 0.86, 95% CI = 0.77-0.96, P_MVMR = .008) were observed. A weak increased risk of lung squamous cell carcinoma was observed for higher BMI in univariable Mendelian randomization (UVMR) analysis (OR_UVMR = 1.19, 95% CI = 1.01-1.40, P_UVMR = .036), but this effect disappeared after adjustment of smoking (OR_MVMR = 1.02, 95% CI = 0.90-1.16, P_MVMR = .746). These results highlight the histology-specific impact of BMI on lung carcinogenesis and imply mediator role of smoking behaviors in the association between BMI and lung cancer.

SUBMITTER: Zhou W

PROVIDER: S-EPMC7845289 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization.

Zhou Wen W Liu Geoffrey G Hung Rayjean J RJ Haycock Philip C PC Aldrich Melinda C MC Andrew Angeline S AS Arnold Susanne M SM Bickeböller Heike H Bojesen Stig E SE Brennan Paul P Brunnström Hans H Melander Olle O Caporaso Neil E NE Landi Maria Teresa MT Chen Chu C Goodman Gary E GE Christiani David C DC Cox Angela A Field John K JK Johansson Mikael M Kiemeney Lambertus A LA Lam Stephen S Lazarus Philip P Le Marchand Loïc L Rennert Gad G Risch Angela A Schabath Matthew B MB Shete Sanjay S SS Tardón Adonina A Zienolddiny Shanbeh S Shen Hongbing H Amos Christopher I CI

International journal of cancer 20200923 5

At the time of cancer diagnosis, body mass index (BMI) is inversely correlated with lung cancer risk, which may reflect reverse causality and confounding due to smoking behavior. We used two-sample univariable and multivariable Mendelian randomization (MR) to estimate causal relationships of BMI and smoking behaviors on lung cancer and histological subtypes based on an aggregated genome-wide association studies (GWASs) analysis of lung cancer in 29 266 cases and 56 450 controls. We observed a po ...[more]

PMID: 32914876

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Project description:BackgroundWhether the positive associations of blood lipids with psychiatric disorders are causal is uncertain. We conducted this two-sample Mendelian randomization (MR) analysis to comprehensively investigate associations of blood lipids with psychiatric disorders.MethodsUnivariable and multivariable models were established for MR analyses. Inverse variance-weighted (IVW) MR was employed as the main approach; weighted median and MR-Egger were used as sensitivity analysis methods. The possibility of violating MR assumptions was evaluated utilizing several sensitivity analyses, including heterogeneity statistics, horizontal pleiotropy statistics, single SNP analysis, leave-one-out analysis and MR-PRESSO analysis. As instrumental variables, we screened 362 independent single-nucleotide polymorphisms (SNP) related to blood lipids from a recent genome-wide association study involving 76,627 individuals of European ancestry, with a genome-wide significance level of p < 5 × 10- 8. Summary-level information for the six psychiatric disorders was extracted from Psychiatric Genomics Consortium and Alzheimer Disease Genetics Consortium.ResultsWe observed eight significant associations in univariable MR analysis, four of which were corroborated by multivariable MR (MVMR) analysis modified for the other three lipid traits: high-density lipoprotein cholesterol (HDL-C) level with the risk of PTSD (OR = 0.91, 95% CI = 0.85-0.97, p = 0.002) and AD (OR = 0.79, 95% CI = 0.71-0.88, p < 0.001) and triglycerides (TG) level with the risk of MDD (OR = 1.02, 95% CI = 1.003-1.03, p = 0.01) and panic disorder (OR = 0.83, 95% CI = 0.74-0.92, p < 0.001). In addition, four associations were not significant in MVMR analysis after adjustment for three lipid traits: total cholesterol (TC) level with the risk of PTSD, low-density lipoprotein cholesterol (LDL-C) level with the risk of MDD and AD and TG level with the risk of AD.ConclusionsOur results show that blood lipids and psychiatric disorders may be related in a causal manner. This shows that abnormal blood lipid levels may act as reliable biomarker of psychiatric disorders and as suitable targets for their prevention and treatment.

Project description:BackgroundThis study aims to investigate the independent causal relation between height, screen time, physical activity, sleep and myopia.MethodsInstrumental variables (IVs) for exposures and outcome were obtained from the largest publicly available genome-wide association studies (GWAS) databases. First, we performed a bidirectional univariate MR analysis using primarily the inverse variance weighted method (IVW) with height, screen time, physical activity and sleep as the exposure and myopia as the outcome to investigate the causal relationship between exposures and myopia. Sensitivity analysis was used to demonstrate its robustness. Then the multivariable MR (MVMR) and MR-based mediation approach was further used to estimate the mediating effect of potential confounders (education and time outdoors) on causality.ResultsThe results of univariate MR analysis showed that taller height (OR = 1.009, 95% CI = 1.005-1.012, p = 3.71 × 10-7), longer time on computer (OR = 1.048, 95% CI = 1.029-1.047, p = 3.87 × 10-7) and less moderate physical activity (OR = 0.976, 95% CI = 0.96-0.991 p = 2.37 × 10-3) had a total effect on the increased risk of developing myopia. Meanwhile our results did not have sufficient evidence to support the causal relationship between chronotype (p = 0.637), sleep duration (p = 0.952) and myopia. After adjusting for education, only taller height remains an independent risk factor for myopia. After adjusting for education, the causal relationship between height, screen and myopia still had statistical significance. A reverse causal relationship was not found in our study. Most of the sensitivity analyses showed consistent results with those of the IVW method.ConclusionOur MR study revealed that genetically predicted taller height, longer time on computer, less moderate physical activity increased the risk of myopia. After full adjustment for confounders, only height remained independently associated with myopia. As a complement to observational studies, the results of our analysis provide strong evidence for the improvement of myopia risk factors and provide a theoretical basis for future measures to prevent and control myopia in adolescents.

Project description:BackgroundObservational research has highlighted a potential relationship between rheumatoid arthritis (RA) and neurodegenerative diseases (NDs). However, the confirmation of a causal connection is impeded by the inherent limitations of such studies, including vulnerability to confounding factors and the possibility of reverse causality. This study employs a two-sample Mendelian randomization (MR) approach to assess the causal impact of RA on three NDs, including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).MethodsWe aggregated data from genome-wide association studies (GWASs) targeting RA or NDs within populations of European descent. Single nucleotide polymorphisms (SNPs) with robust associations to RA were identified as instrumental variables (IVs). To estimate the association between RA and AD, PD, and ALS, we utilized the inverse variance weighted (IVW) method in our univariable MR (UVMR) analysis. Validation of the IVW results ensued through supplementary analyses using MR-Egger and weighted median methods. The multivariable MR (MVMR) analysis was conducted, adjusting for body mass index (BMI), alcohol drinking, and type 2 diabetes mellitus (T2DM).ResultsThe UVMR analysis, based on the IVW method, revealed a significantly positive causal association between RA and late-onset (LO) AD (OR [95% CI] = 1.084 [1.020-1.153]; p = 9.980 × 10-3), while suggesting a possible inverse relationship with PD (OR [95% CI] = 0.727 [0.563-0.938]; p = 0.014). Our study did not detect any causal connections between RA and early-onset (EO) AD, atypical or mixed (AM) AD, and ALS (all p > 0.05). The MVMR analysis results indicated that after adjusting for alcohol drinking, RA remains a risk factor for LOAD (OR [95% CI] = 1.094 [1.024-1.169]; p = 0.008). However, MVMR analysis revealed no causal connections between RA and PD after adjustments for BMI, alcohol drinking, or T2DM (all p > 0.05). Sensitivity analyses showed no evidence of heterogeneity and horizontal pleiotropy.ConclusionsThis research provides genetic evidence indicating that RA potentially causes an increased risk of developing LOAD and PD. Such a revelation underscores the importance for individuals suffering from RA to be vigilant about the potential emergence of LOAD and PD. Ongoing monitoring and prompt detection are essential for successfully managing and intervening in this possible risk.

Project description:Introduction The correlation between dyslipidemia and periodontitis is revealed through epidemiological studies. However, the results are affected by several confounding factors. This study aims to elucidate the genetic causal association between circulating lipid traits and periodontitis by two-sample Mendelian randomization (MR) analysis. Methods After the different screening processes, two cohorts of circulating lipid traits from the UK Biobank were used as exposure data, including five circulating lipid traits. The Periodontitis cohort was selected from the GeneLifestyle Interactions in Dental Endpoints (GLIDE) consortium as outcome data. In univariable MR, the inverse variance weighted (IVW) was used in conjunction with six additional analytical methods to assess causality. The Cochran Q test, IGX2 statistic, MR-PRESSO, and MR-Egger intercept were used to quantify heterogeneity and pleiotropy. The multivariable MR-IVW (MVMR-IVW) and MVMR-robust were mainly used as analytical methods in the multiple MR analyses. Results The IVW estimates showed that genetically predicted Apolipoprotein A1 (apo A1) [odds ratio (OR)=1.158, 95% confidence interval (CI)=1.007–1.331, P-value=0.040] was potentially associated with the risk of periodontitis, but the statistical power of the results was low. Multivariable MR analysis did not reveal any significant causal relationship between apo A1 and periodontitis (OR=0.72, 95% CI=0.36–1.41, P-value=0.34). In the validation cohort, there was also no significant causal relationship between apo A1 and periodontitis (OR=1.079, 95% CI=0.903–1.290, P-value=0.401). Meanwhile, genetically predicted Apolipoprotein B (apo B), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) (all P-values>0.05) were not significantly associated with the risk of periodontitis causal inference. Conclusion This MR analysis was unable to provide genetic evidence for the influence of these five circulating lipid traits on periodontitis. However, a more extensive study with a more comprehensive circulating lipid profile and periodontitis data is needed due to study limitations.

Project description:Study questionWhat are the causal relationships between polycystic ovary syndrome (PCOS) and body mass index (BMI)?Summary answerBidirectional Mendelian randomization analyses suggest that increased BMI is causal for PCOS while the reverse is not the case.What is known alreadyThe contribution of obesity to the pathogenesis of PCOS is controversial. To date, published genetic studies addressing this question have generated conflicting results and have not utilized the full extent of known single nucleotide polymorphisms associated with body mass index (BMI).Study design, size, durationThis cross-sectional Mendelian randomization (MR) and genetic association study was conducted in 750 individuals of European origin and with PCOS and 1567 BMI-matched controls.Participants/materials, setting, methodsCases and controls were matched for BMI as well as for distribution of weight categories (normal weight, overweight, obese). Two-sample MR using inverse variance weighting (IVW) was conducted using a 92-SNP instrument variable for BMI with PCOS as the outcome, followed by two-sample MR with a 16-SNP instrument variable for PCOS with BMI as the outcome. Sensitivity analyses included MR-Egger and maximum likelihood methods. Secondary analyses assessed associations of genetic risk scores and individual SNPs with PCOS, BMI and quantitative androgen-related and glucose homeostasis-related traits.Main results and the role of chanceEach standard deviation genetically higher BMI was associated with a 4.89 (95% CI 1.46-16.32) higher odds of PCOS. Conversely, genetic risk of PCOS did not influence BMI. Sensitivity analyses yielded directionally consistent results. The genetic risk score of 92 BMI SNPs was associated with the diagnosis of PCOS (OR 1.043, 95% CI 1.009-1.078, P = 0.012). Of the 92 BMI risk variants evaluated, none were associated individually with PCOS after considering multiple testing. The association of FTO SNP rs1421085 with BMI was stronger in women with PCOS (β = 0.071, P = 0.0006) than in controls (β = 0.046, P = 0.065).Limitations, reasons for cautionThe current sample size, while providing good power for MR and genetic risk score analyses, had limited power to demonstrate association of individual SNPs with PCOS. Cases and controls were not matched for age; however, this was mitigated by adjusting analyses for age. Dietary and lifestyle data, which could have been used to explore the greater association of the FTO SNP with BMI in women with PCOS, was not available.Wider implications of the findingsIncreasing BMI appears to be causal for PCOS but having PCOS does not appear to affect BMI. This study used the most comprehensive set of SNPs for BMI currently available. Prior studies using fewer SNPs had yielded conflicting results and may have been confounded because cases and controls were not matched for weight categories. The current results highlight the potential utility of weight management in the prevention and treatment of PCOS.Study funding/competing interest(s)National Institutes of Health Grants R01-HD29364 and K24-HD01346 (to R.A.), Grant R01-DK79888 (to M.O.G.), Grant U54-HD034449 (to R.S.L.), Grant U19-HL069757 (to R.M.K.). The funders had no influence on the data collection, analyses or conclusions of the study. No conflict of interests to declare.Trial registration numberN/A.

Project description:ObjectiveRecent evidence supports that leukocyte telomere length (LTL) may be positively associated with healthy living and inversely correlated with the risk of age-related diseases, including osteoporosis. Furthermore, it is important to note that sex hormone-binding globulin (SHBG) levels play a crucial role in the regulation of osteoporosis by influencing the availability of sex hormones. Hence, this study holds significant importance as it aims to unravel the roles of LTL and SHBG levels and determine which one acts as a predominant intermediary factor in influencing osteoporosis. Using Mendelian randomization (MR), we can gain valuable insights into the intricate relationships between aging, sex hormones, and bone health.MethodsUnivariable and multivariable and MR analyses were employed in this study. First, we used genetic variants associated with both LTL, as determined from a study involving 472,174 European participants by Codd et al., and SHBG levels, as identified in a study conducted by Ruth et al. with 370,125 participants, as instrumental variables (IVs). Then we aimed to establish a causal relationship between LTL and SHBG levels and their potential impact on osteoporosis using univariable MR. Finally, we conducted multivariable MR to provide insights into the independent and combined effects of LTL, SHBG levels on osteoporosis risk. We used various MR methods, with the primary analysis employing the inverse-variance weighted (IVW) model.ResultsUnivariable MR analysis reveals a potential causal effect of longer LTL on reduced risk of osteoporosis [odds ratio (OR): 0.85; 95% confidence interval (CI): 0.73-0.99; p = 0.03]. Conversely, higher genetically determined SHBG levels affect the risk of osteoporosis positively. (OR: 1.38; 95% CI: 1.09-1.75; p < 0.01). We observed a negative causal effect for LTL on the occurrence of SHBG (OR: 0.96; 95% CI 0.94-0.98, p < 0.01). After adjustment of using multivariable MR, the causal effect of LTL on osteoporosis (OR: 0.92; 95% CI: 0.84-1.03; p = 0.14), and the effect of SHBG on osteoporosis (OR: 1.43; 95% CI: 1.16-1.75; p < 0.01) were observed.ConclusionLonger LTL may confer a protective effect against osteoporosis. Additionally, the levels of SHBG appear to play a crucial role in mediating the relationship between LTL and osteoporosis. By understanding the interplay between these factors, we can gain valuable insights into the mechanisms underlying bone health and aging and potentially identify new avenues for prevention and intervention strategies.

Dataset Information

Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization.

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Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization.

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