Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer

An atlas on risk factors for gastrointestinal cancers: A systematic review of Mendelian randomization studies

OBJECTIVE

Gastrointestinal cancers are one of the most frequent cancer types and seriously threaten human life and health. Recent studies attribute the occurrence of gastrointestinal cancers to both genetic and environmental factors, yet the intrinsic etiology remains unclear. Mendelian randomization is a powerful well-established statistical method that is based on genome-wide association study (GWAS) to evaluate the causal relationship between exposures and outcomes. In the present study, we aimed to conduct a systematic review of Mendelian randomization studies investigating any causal risk factors for gastrointestinal cancers.

METHODS

We systematically searched Mendelian randomization studies that addressed the associations of genetically predicted exposures with five main gastrointestinal cancers from September 2014 to March 2024, as well as testing the research quality and validity.

RESULTS

Our findings suggested robust and consistent causal effects of body mass index (BMI), basal metabolic rate, fatty acids, total cholesterol, total bilirubin, insulin like growth factor-1, eosinophil counts, interleukin 2, alcohol consumption, coffee consumption, apolipoprotein B on colorectal cancer risks, BMI, waist circumference, low-density lipoprotein (LDL), total testosterone, smoking on gastric cancer risks, BMI, fasting insulin, LDL, waist circumference, visceral adipose tissue (VAT), immune cells, type 2 diabetes mellitus (T2DM) on pancreatic cancer risks, waist circumference, smoking, T2DM on esophageal adenocarcinoma risks, and VAT, ferritin, transferrin, alcohol consumption, hepatitis B virus infection, rheumatoid arthritis on liver cancer risks, respectively.

CONCLUSION

Larger, well-designed Mendelian randomization studies are practical in determining the causal status of risk factors for diseases.

Metabolic Dysregulation and Cancer Risk Program (MeDOC): a transdisciplinary approach to obesity-associated cancers

With the escalating prevalence of obesity, the association between obesity and cancer is a growing public health concern. Obesity will soon surpass tobacco smoking as the most important preventable cause of cancer. Obesity-driven mechanisms can alter cell functions to induce metabolic changes, chronic inflammation, and insulin resistance that are believed to contribute to cancer risk and development; yet the specific underlying biological mechanisms of obesity-related cancer development are largely unknown. The Metabolic Dysregulation and Cancer Risk Program: a transdisciplinary approach to obesity-associated cancers (MeDOC) is a trans-National Cancer Institute research initiative supported by the Division of Cancer Control and Population Sciences, the Division of Cancer Biology, the Division of Cancer Prevention, and the Center to Reduce Cancer Health Disparities. The overall purpose of the MeDOC Program is to advance our understanding of the underlying mechanisms that connect obesity, metabolic dysregulation, and increased obesity cancer risk as well as identify markers that will enhance cancer risk prediction, improve screening for high-risk individuals, and identify targets for preventive and therapeutic interventions for cancer interception or treatment. This report describes the funded research projects, the Coordinating Center, and the goals of the MeDOC program.

The potential causal relationship between BMI, T1D, urolithiasis, and hydronephrosis in European ancestry: A Mendelian randomization analysis

Body mass index (BMI), type 1 diabetes (T1D), urolithiasis, and hydronephrosis are interrelated. Our aim was to analyze their causal relationships at the genetic level. Mendelian randomization is an instrumental variable analysis method that follows Mendel genetic law of random allocation of parental alleles to offspring. In observational studies, genetic variants are used as instrumental variables to infer causal relationships between exposure factors and study outcomes. All the genome-wide association study data in our study were publicly available and from published genome-wide association studies, UK Biobank, and FinnGen. Random-effects inverse variance weighted was the primary analysis method, with R Egger, weighted median, and weighted mode as supplementary methods. We examined heterogeneity, horizontal pleiotropy, and the influence of individual single nucleotide polymorphisms on the analysis. We further explored the causal relationships between BMI, T1D, urolithiasis, and hydronephrosis, as well as the robustness of the analysis results. Inverse variance weighted results showed genetic causal relationships between BMI (P = .034, odds ratio [OR] 95% confidence interval [CI] = 1.273 [1.019-1.589]), T1D (P = .028, OR 95% CI = 0.921 [0.855-0.991]), urolithiasis (P < .001, OR 95% CI = 1.361 [1.175-1.576]), and hydronephrosis. Sensitivity analyses confirmed the accuracy and robustness of these findings. Our results support significant causal roles of BMI, T1D, and urolithiasis in hydronephrosis, potentially offering new intervention strategies for preventing its development.

Overweight-years and cancer risk: A prospective study of the association and comparison of predictive performance with body mass index (Atherosclerosis Risk in Communities Study)

Excess body mass index (BMI) is associated with a higher risk of at least 13 cancers, but it is usually measured at a single time point. We tested whether the overweight-years metric, which incorporates exposure time to BMI ≥25 kg/m2 , is associated with cancer risk and compared this with a single BMI measure. We used adulthood BMI readings in the Atherosclerosis Risk in Communities (ARIC) study to derive the overweight-years metric. We calculated associations between the metric and BMI and the risk of cancers using Cox proportional hazards models. Models that either included the metric or BMI were compared using Harrell's C-statistic. We included 13,463 participants, with 3,876 first primary cancers over a mean of 19 years (SD 7) of cancer follow-up. Hazard ratios for obesity-related cancers per standard deviation overweight-years were 1.15 (95% CI: 1.05-1.25) in men and 1.14 (95% CI: 1.08-1.20) in women. The difference in the C-statistic between models that incorporated BMI, or the overweight-years metric was non-significant in men and women. Overweight-years was associated with the risk of obesity-related cancers but did not outperform a single BMI measure in association performance characteristics.

Allometric versus traditional body-shape indices and risk of colorectal cancer: a Mendelian randomization analysis

BACKGROUND

Traditional body-shape indices such as Waist Circumference (WC), Hip Circumference (HC), and Waist-to-Hip Ratio (WHR) are associated with colorectal cancer (CRC) risk, but are correlated with Body Mass Index (BMI), and adjustment for BMI introduces a strong correlation with height. Thus, new allometric indices have been developed, namely A Body Shape Index (ABSI), Hip Index (HI), and Waist-to-Hip Index (WHI), which are uncorrelated with weight and height; these have also been associated with CRC risk in observational studies, but information from Mendelian randomization (MR) studies is missing.

METHODS

We used two-sample MR to examine potential causal cancer site- and sex-specific associations of the genetically-predicted allometric body-shape indices with CRC risk, and compared them with BMI-adjusted traditional body-shape indices, and BMI. Data were obtained from UK Biobank and the GIANT consortium, and from GECCO, CORECT and CCFR consortia.

RESULTS

WHI was positively associated with CRC in men (OR per SD: 1.20, 95% CI: 1.03-1.39) and in women (1.15, 1.06-1.24), and similarly for colon and rectal cancer. ABSI was positively associated with colon and rectal cancer in men (1.27, 1.03-1.57; and 1.40, 1.10-1.77, respectively), and with colon cancer in women (1.20, 1.07-1.35). There was little evidence for association between HI and colon or rectal cancer. The BMI-adjusted WHR and HC showed similar associations to WHI and HI, whereas WC showed similar associations to ABSI only in women.

CONCLUSIONS

This large MR study provides strong evidence for a potential causal positive association of the allometric indices ABSI and WHI with CRC in both sexes, thus establishing the association between abdominal fat and CRC without the limitations of the traditional waist size indices and independently of BMI. Among the BMI-adjusted traditional indices, WHR and HC provided equivalent associations with WHI and HI, while differences were observed between WC and ABSI.

Genetic predisposition to childhood obesity does not influence the risk of developing skin cancer in adulthood

The relationship between body mass index (BMI) and melanoma and other skin cancers remains unclear. The objective of this study was to employ the Mendelian randomization (MR) approach to evaluate the effects of genetically predicted childhood adiposity on the risk of developing skin cancer later in life. Two-sample MR analyses were conducted using summary data from genome-wide association study (GWAS) meta-analyses of childhood BMI, melanoma, cutaneous squamous cell carcinoma (cSCC), and basal cell carcinoma (BCC). We used the inverse-variance-weighted (IVW) methods to obtain a pooled estimate across all genetic variants for childhood BMI. We performed multiple sensitivity analyses to evaluate the potential influence of various assumptions on our findings. We found no evidence that genetically predicted childhood BMI was associated with risks of developing melanoma, cSCC, or BCC in adulthood (OR, 95% CI: melanoma: 1.02 (0.93-1.13), cSCC 0.94 (0.79-1.11), BCC 0.97 (0.84-1.12)). Our findings do not support the conclusions from observational studies that childhood BMI is associated with increased risks of melanoma, cSCC, or BCC in adulthood. Intervening on childhood adiposity will not reduce the risk of common skin cancers later in life.

Artificially sweetened beverages consumption and risk of obesity-related cancers: a wide-angled Mendelian randomization study

Background

The impact of artificially sweetened beverages (ASBs) consumption on obesity-related cancers (ORCs) risk remains controversial. To address this challenging issue, this study employed wide-angle mendelian randomization (MR) analyses to explore the genetic causality between ASB consumption and the risk of ORCs, thereby effectively minimizing the impact of external confounders.

Methods

We conducted a suite of analyses encompassing univariable, multivariable, and two-step MR to evaluate causal associations between ASB consumption (samples = 85,852) and risk of ORCs (total samples = 2,974,770) using summary statistics from genome-wide association studies (GWAS). Total, direct, and intermediary effects were derived by performing inverse-variance weighted (IVW), MR-Egger, weighted mode, weighted median, and lasso method. Additionally, we performed an extensive range of sensitivity analyses to counteract the potential effects of confounders, heterogeneity, and pleiotropy, enhancing the robustness and reliability of the findings.

Results

Genetically predicted ASB consumption was positively associated with the risk of colorectal cancer (CRC, p = 0.011; OR: 6.879; 95% CI: 1.551, 30.512 by IVW) and breast cancer (p = 0.022; OR: 3.881; 95% CI: 2.023, 9.776 by IVW). Multivariable analysis yielded similar results. The results of the two-step MR unveiled that body mass index (BMI) assumes a pivotal role in mediating the association between ASB consumption and CRC risk (intermediary effect = 0.068, p = 0.024).

Conclusion

No causal connection exists between ASB consumption and the majority of ORCs, in addition to CRC and breast cancer. Additionally, our findings suggest that BMI might be a potential mediator in the association between ASB consumption and CRC.

Metabolic syndrome and risk of colorectal cancer: A Mendelian randomization study

Background

Observational studies have previously demonstrated a significant relationship among both metabolic syndrome (Mets) and colorectal cancer (CRC). Whether there is a causal link remains controversial.

Objective

To clarify whether Mets and their components have a causal effect on colorectal cancer, we have carried out a bidirectional Mendelian randomization analysis (MR).

Methods

This study started from genome-wide association data for Mets and its 5 components (hypertension, waist circumference, fasting blood glucose, serum triglycerides, and serum high-density lipoprotein cholesterol) and colorectal cancer. Mendelian randomization (MR) techniques were used in the study to examine their associations.

Results

After Benjamini-Hochberg multiple corrections, genetically predicted significant causal link exists between WC (waist circumference) and CRC. The OR was 1.35 (95 % CI: 1.08-1.69; p = 0.0096). Other Mets components (HBP, FBG, TG, HDL), on the other hand, found no evidence of a genetic link between CRC and Mets. In addition, MR results showed that CRC was not causally related to either Mets or the components. We get the same result in the validated dataset.

Conclusion

According to the bidirectional MR investigation shows a significant causal relationship among obesity and CRC in the Mets component but no causal relationship in the opposite direction.

Genetically predicted serum testosterone and risk of gynecological disorders: a Mendelian randomization study

Background

Testosterone plays a key role in women, but the associations of serum testosterone level with gynecological disorders risk are inconclusive in observational studies.

Methods

We leveraged public genome-wide association studies to analyze the effects of four testosterone related exposure factors on nine gynecological diseases. Causal estimates were calculated by inverse variance-weighted (IVW), MR-Egger and weighted median methods. The heterogeneity test was performed on the obtained data through Cochrane's Q value, and the horizontal pleiotropy test was performed on the data through MR-Egger intercept and MR-PRESSO methods. "mRnd" online analysis tool was used to evaluate the statistical power of MR estimates.

Results

The results showed that total testosterone and bioavailable testosterone were protective factors for ovarian cancer (odds ratio (OR) = 0.885, P = 0.012; OR = 0.871, P = 0.005) and endometriosis (OR = 0.805, P = 0.020; OR = 0.842, P = 0.028) but were risk factors for endometrial cancer (OR = 1.549, P < 0.001; OR = 1.499, P < 0.001) and polycystic ovary syndrome (PCOS) (OR = 1.606, P = 0.019; OR = 1.637, P = 0.017). dehydroepiandrosterone sulfate (DHEAS) is a protective factor against endometriosis (OR = 0.840, P = 0.016) and premature ovarian failure (POF) (OR = 0.461, P = 0.046) and a risk factor for endometrial cancer (OR= 1.788, P < 0.001) and PCOS (OR= 1.970, P = 0.014). sex hormone-binding globulin (SHBG) is a protective factor against endometrial cancer (OR = 0.823, P < 0.001) and PCOS (OR = 0.715, P = 0.031).

Conclusion

Our analysis suggested causal associations between serum testosterone level and ovarian cancer, endometrial cancer, endometriosis, PCOS, POF.

Do Obesity-Related Traits Affect Prostate Cancer Risk through Serum Testosterone? A Mendelian Randomization Study

OBJECTIVE

This study aimed to investigate whether testosterone mediates or confounds the effect of obesity-related traits on prostate cancer (PCa) using Mendelian randomization (MR) analysis.

MATERIALS AND METHODS

Data of obesity-related traits (body mass index [BMI], waist-to-hip ratio [WHR], and waist-to-hip ratio adjusted for body mass index [WHRadjBMI]) were obtained from up to 806,834 people of European ancestry; data of testosterone (bioavailable testosterone [BT], total testosterone [TT], and sex hormone-binding globulin [SHBG]) were extracted from up to 194,453 participants in the UK Biobank; and the summary-level data of PCa (79,194 cases and 61,112 controls) were obtained from the PRACTICAL consortium.

RESULT

The results supported the causal relationship between higher BMI and a reduced risk of PCa (OR = 0.91, 95% confidence interval [CI]: 0.86-0.96). Furthermore, increased BT levels were associated with an elevated risk of PCa (OR = 1.15, 95% CI: 1.06-1.24). Importantly, our analysis revealed a unidirectional causal effect-higher BMI was linked to lower BT levels (beta = -0.27, 95% CI: -0.3--0.24), but not the other way around. This suggests that BT may mediate the effect of BMI on PCa rather than confound it. Our multivariable MR results further demonstrated that considering BT as a mediator led to the weakening of BMI's effect on PCa risk (OR = 0.97, 95% CI: 0.90-1.05), while the impact of BT on PCa remained unchanged when accounting for BMI. Moreover, we identified a significant indirect effect of BMI on PCa risk (OR = 0.96, 95% CI: 0.94-0.98).

CONCLUSION

Our study provided genetic evidence that serum BT can mediate the effect of BMI on the risk of PCa, indicating the possible mechanism by which obesity reduces PCa risk.

Genetically predicted childhood body mass index and lung cancer susceptibility: A two-sample Mendelian randomization study

BACKGROUND

The association between adult body mass index (BMI) and lung cancer (LC) susceptibility have been reported, but the causal relationship with childhood BMI remains largely unclear. To evaluate the causal effect of childhood BMI on LC susceptibility, a two-sample Mendelian randomization (MR) study was performed.

METHODS

The two-sample MR analysis utilized 25 single nucleotide polymorphisms (SNPs) as instrumental variables for childhood BMI. Genetic summary data from the International Lung Cancer Consortium and FinnGen databases were analyzed to estimate the causal effect of these SNPs on LC susceptibility. The IVW method was employed as the primary analysis, supplemented by the Weighted Median, MR-Egger, and MR pleiotropy residual sum and outlier test.

RESULTS

Our findings indicated that there was no causal association between childhood BMI and the susceptibility of LC (odds ratio [OR]: 1.03, 95% confidence interval [CI]: 0.90-1.17, p = 0.705), lung adenocarcinoma (OR: 0.99, 95% CI: 0.86-1.13, p = 0.832), lung squamous cell carcinoma (OR: 0.97, 95% CI: 0.84-1.13, p = 0.726), and small cell LC (OR: 1.09, 95% CI: 0.82-1.45, p = 0.554) based on the IVW as well as other methods employed. Furthermore, these findings indicated no causal effect of childhood BMI on the LC susceptibility in both ever smokers and never smokers.

CONCLUSION

This study did not conclude a causal effect between childhood BMI and LC susceptibility. However, given the complex nature of cancer development, further studies are needed to verify these findings.

Prevention of Epithelial Ovarian Cancer

Given the challenges with achieving effective and durable treatment for epithelial ovarian cancer, primary prevention is highly desirable. Fortunately, decades of research have provided evidence for several strategies that can be deployed to optimize risk reduction. These include surgery, chemoprevention, and lifestyle factor modifications. These broad categories vary in terms of the magnitude of risk reduction possible, the possible short-term and long-term side effects, the degree of difficulty, and acceptability. Thus, the concept of a risk-based model to personalize preventive interventions is advocated to guide discussion between care providers and women at risk. For women with inherited major gene mutations that greatly increase risk of ovarian cancer, surgical approaches have favorable risk to benefit ratios. Chemoprevention and lifestyle factor modifications portend a lower degree of risk reduction but confer lower risk of undesirable side effects. Since complete prevention is not currently possible, better methods for early detection remain a high priority.

Age at Menarche, age at Natural Menopause, and Risk of Lung and Colorectal Cancers: A Mendelian Randomization Study

Background

The roles of age at menarche and age at menopause in the etiology of lung and colorectal cancers are unclear.

Objective

We aimed to investigate potential causal associations between age at menarche, age at natural menopause, and risk of lung and colorectal cancers using a Mendelian randomization (MR) approach.

Methods

From the Trøndelag Health Study in Norway, we defined two cohorts of 35 477 and 17 118 women to study the effects of age at menarche and age at natural menopause, respectively. We ran univariable MR to evaluate the potential causal associations. We performed multivariable MR adjusting for genetic variants of adult body mass index (BMI) to estimate the direct effect of age at menarche.

Results

Genetically predicted 1-year increase in age at menarche was associated with a lower risk of lung cancer overall (hazard ratio [HR, 0.64; 95% CI, 0.48-0.86), lung adenocarcinoma (HR, 0.61; 95% CI, 0.38-0.99), and lung non-adenocarcinoma (HR, 0.66; 95% CI, 0.45-0.95). After adjusting for adult BMI using a multivariable MR model, the direct effect estimates reduced to HR 0.72 (95% CI, 0.54-0.95) for lung cancer overall, HR 0.67 (95% CI, 0.43-1.03) for lung adenocarcinoma, and HR 0.77 (95% CI, 0.54-1.09) for lung non-adenocarcinoma. Age at menarche was not associated with colorectal cancer. Moreover, genetically predicted age at natural menopause was not associated with lung and colorectal cancers.

Conclusion

Our MR study suggested that later age at menarche was causally associated with a decreased risk of lung cancer overall and its subtypes, and adult BMI might be a mediator.

Association of Body Mass Index and the Risk of Gastro-Esophageal Cancer: A Mendelian Randomization Study in a Japanese Population

There are growing concerns that body mass index (BMI) is related to cancer risk at various anatomical sites, including the upper gastrointestinal tract, and the existence of a causal relationship remains unclear. The Mendelian randomization (MR) method uses instrumental genetic variables of risk factors to explore whether a causal relationship exists while preventing confounding. In our study, genome-wide association study (GWAS) data from the BioBank Japan (BBJ) project were used. Genetic variants were chosen as instrumental variables using inverse-variance weighting (IVW), MR-Egger regression and weighted-median methods to estimate the causal relationship between BMI and the risk of gastro-esophageal cancer. We found no evidence to support a causal association between BMI and risk of gastric cancer [odds ratio (OR) =0.99 per standard deviation (SD) increase in BMI; 95% confidence interval (CI): (0.76-1.30); P = 0.96] or esophageal cancer [0.78(0.50-1.22); P = 0.28] using the IVW method. Sensitivity analysis did not reveal any sign of horizontal pleiotropy. Additionally, in the gender-stratified analysis, no causal association was found. Findings from this study do not support a causal effect of BMI on gastro-esophageal cancer risk. However, we cannot rule out a modest or nonlinear effect of BMI.

Reassessing the causal role of obesity in breast cancer susceptibility: a comprehensive multivariable Mendelian randomization investigating the distribution and timing of exposure

BACKGROUND

Previous Mendelian randomization (MR) studies on obesity and risk of breast cancer adopted a small number of instrumental variables and focused mainly on the crude total effect. We aim to investigate the independent causal effect of obesity on breast cancer susceptibility, considering the distribution of fat, covering both early and late life.

METHODS

Using an enlarged set of female-specific genetic variants associated with adult general [body mass index (BMI)] and abdominal obesity [waist-to-hip ratio (WHR) with and without adjustment for BMI, WHR and WHRadjBMI] as well as using sex-combined genetic variants of childhood obesity (childhood BMI), we performed a two-sample univariable MR to re-evaluate the total effect of each obesity-related exposure on overall breast cancer (Ncase = 133 384, Ncontrol = 113 789). We further looked into its oestrogen receptor (ER)-defined subtypes (NER+ = 69 501, NER- = 21 468, Ncontrol = 105 974). Multivariable MR was applied to estimate the independent causal effect of each obesity-related exposure on breast cancer taking into account confounders as well as to investigate the independent effect of adult and childhood obesity considering their inter-correlation.

RESULTS

In univariable MR, the protective effects of both adult BMI [odds ratio (OR) = 0.89, 95% CI = 0.83-0.96, P = 2.06 × 10-3] and childhood BMI (OR = 0.78, 95% CI = 0.70-0.87, P = 4.58 × 10-6) were observed for breast cancer overall. Comparable effects were found in ER+ and ER- subtypes. Similarly, genetically predicted adult WHR was also associated with a decreased risk of breast cancer overall (OR = 0.87, 95% CI = 0.80-0.96, P = 3.77 × 10-3), restricting to ER+ subtype (OR = 0.88, 95% CI = 0.80-0.98, P = 1.84 × 10-2). Conditional on childhood BMI, the effect of adult general obesity on breast cancer overall attenuated to null (BMI: OR = 1.00, 95% CI = 0.90-1.10, P = 0.96), whereas the effect of adult abdominal obesity attenuated to some extent (WHR: OR = 0.90, 95% CI = 0.82-0.98, P = 1.49 × 10-2; WHRadjBMI: OR = 0.92, 95% CI = 0.86-0.99, P = 1.98 × 10-2). On the contrary, an independent protective effect of childhood BMI was observed in breast cancer overall, irrespective of adult measures (adjusted for adult BMI: OR = 0.84, 95% CI = 0.77-0.93, P = 3.93 × 10-4; adjusted for adult WHR: OR = 0.84, 95% CI = 0.76-0.91, P = 6.57 × 10-5; adjusted for adult WHRadjBMI: OR = 0.80, 95% CI = 0.74-0.87, P = 1.24 × 10-7).

CONCLUSION

Although successfully replicating the inverse causal relationship between adult obesity-related exposures and risk of breast cancer, our study demonstrated such effects to be largely (adult BMI) or partly (adult WHR or WHRadjBMI) attributed to childhood obesity. Our findings highlighted an independent role of childhood obesity in affecting the risk of breast cancer as well as the importance of taking into account the complex interplay underlying correlated exposures.

Disentangling the aetiological pathways between body mass index and site-specific cancer risk using tissue-partitioned Mendelian randomisation

BACKGROUND

Body mass index (BMI) is known to influence the risk of various site-specific cancers, however, dissecting which subcomponents of this heterogenous risk factor are predominantly responsible for driving disease effects has proven difficult to establish. We have leveraged tissue-specific gene expression to separate the effects of distinct phenotypes underlying BMI on the risk of seven site-specific cancers.

METHODS

SNP-exposure estimates were weighted in a multivariable Mendelian randomisation analysis by their evidence for colocalization with subcutaneous adipose- and brain-tissue-derived gene expression using a recently developed methodology.

RESULTS

Our results provide evidence that brain-tissue-derived BMI variants are predominantly responsible for driving the genetically predicted effect of BMI on lung cancer (OR: 1.17; 95% CI: 1.01-1.36; P = 0.03). Similar findings were identified when analysing cigarettes per day as an outcome (Beta = 0.44; 95% CI: 0.26-0.61; P = 1.62 × 10-6), highlighting a possible shared aetiology or mediator effect between brain-tissue BMI, smoking and lung cancer. Our results additionally suggest that adipose-tissue-derived BMI variants may predominantly drive the effect of BMI and increased risk for endometrial cancer (OR: 1.71; 95% CI: 1.07-2.74; P = 0.02), highlighting a putatively important role in the aetiology of endometrial cancer.

CONCLUSIONS

The study provides valuable insight into the divergent underlying pathways between BMI and the risk of site-specific cancers.

Obesity and Cancer: A Current Overview of Epidemiology, Pathogenesis, Outcomes, and Management

BACKGROUND

Obesity or excess body fat is a major global health challenge that has not only been associated with diabetes mellitus and cardiovascular disease but is also a major risk factor for the development of and mortality related to a subgroup of cancer. This review focuses on epidemiology, the relationship between obesity and the risk associated with the development and recurrence of cancer and the management of obesity.

METHODS

A literature search using PubMed and Google Scholar was performed and the keywords 'obesity' and cancer' were used. The search was limited to research papers published in English prior to September 2022 and focused on studies that investigated epidemiology, the pathogenesis of cancer, cancer incidence and the risk of recurrence, and the management of obesity.

RESULTS

About 4-8% of all cancers are attributed to obesity. Obesity is a risk factor for several major cancers, including post-menopausal breast, colorectal, endometrial, kidney, esophageal, pancreatic, liver, and gallbladder cancer. Excess body fat results in an approximately 17% increased risk of cancer-specific mortality. The relationship between obesity and the risk associated with the development of cancer and its recurrence is not fully understood and involves altered fatty acid metabolism, extracellular matrix remodeling, the secretion of adipokines and anabolic and sex hormones, immune dysregulation, and chronic inflammation. Obesity may also increase treatment-related adverse effects and influence treatment decisions regarding specific types of cancer therapy. Structured exercise in combination with dietary support and behavior therapy are effective interventions. Treatment with glucagon-like peptide-1 analogues and bariatric surgery result in more rapid weight loss and can be considered in selected cancer survivors.

CONCLUSIONS

Obesity increases cancer risk and mortality. Weight-reducing strategies in obesity-associated cancers are important interventions as a key component of cancer care. Future studies are warranted to further elucidate the complex relationship between obesity and cancer with the identification of targets for effective interventions.

Obesity, Fat Distribution and Risk of Cancer in Women and Men: A Mendelian Randomisation Study

Obesity and upper-body fat distribution are independent, cardiometabolic risk factors but whether they also display comparable associations with cancer risk is unknown. We investigated the causal relationships between body mass index (BMI) and BMI-adjusted waist-to-hip ratio (WHRadjBMI) and cancer risk and searched for potential drivers linking these traits to carcinogenesis using two-sample and multivariable Mendelian randomisation. In women, genetically instrumented higher BMI was associated with lower breast (OR = 0.87, 95% CI 0.81-0.93) and higher endometrial (OR = 1.75, 95% CI 1.55-1.96) cancer risk whilst WHRadjBMI was associated with higher colon cancer risk (OR = 1.22, 95% CI 1.07-1.42). In men, elevated BMI was associated with lower prostate cancer risk (OR = 0.91, 95% CI 0.85-0.98). Mechanistically, testosterone and insulin mediated 21% and 35%, respectively of the total, genetically determined association of BMI with endometrial cancer risk whilst HDL cholesterol and IGF-1 mediated 40% and 22%, respectively of the association between BMI and breast cancer risk. In men, testosterone mediated 21% of the association between BMI and prostate cancer risk. Colon cancer aside, the total amount of body fat might be more important than its location in modulating cancer susceptibility due to differential effects of obesity and fat distribution on adiposity-associated cancer drivers.

Body fatness associations with cancer: evidence from recent epidemiological studies and future directions

This narrative review highlights current evidence linking greater body fatness to risk of various cancers, with focus on evidence from recent large cohort studies and pooled analyses of cohort studies as well as Mendelian randomization studies (which utilized genetic variants associated with body mass index to debrief the causal effect of higher body fatness on cancer risk). This review also provides insights into the biological mechanisms underpinning the associations. Data from both observational and Mendelian randomization studies support the associations of higher body mass index with increased risk of many cancers with the strongest evidence for digestive system cancers, including esophageal, stomach, colorectal, liver, gallbladder, and pancreatic cancer, as well as kidney, endometrial, and ovarian (weak association) cancer. Evidence from observational studies suggests that greater body fatness has contrasting effects on breast cancer risk depending on menopausal status and on prostate cancer risk depending on disease stage. Experimental and Mendelian randomization studies indicate that adiponectin, insulin, and sex hormone pathways play an important role in mediating the link between body fatness and cancer risk. The possible role of specific factors and pathways, such as other adipocytokines and hormones and the gut microbiome in mediating the associations between greater body fatness and cancer risk is yet uncertain and needs investigation in future studies. With rising prevalence of overweight and obesity worldwide, the proportion of cancer caused by excess body fatness is expected to increase. There is thus an urgent need to identify efficient ways at the individual and societal level to improve diet and physical activity patterns to reduce the burden of obesity and accompanying comorbidities, including cancer.

Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches

Background

Traditional observational studies have shown an inverse association between body mass index (BMI) and lung cancer risk. Mendelian randomization (MR) analysis using genetic variants as instruments for BMI may clarify the nature of the association.

Aims

We studied the causal association between BMI and lung cancer incidence using observational and MR approaches.

Methods

We followed up 62,453 cancer-free Norwegian adults from 1995–97 (HUNT2) until 2017. BMI at baseline in HUNT2 was classified as < 25.0, 25.0–29.9 and ≥ 30.0 kg/m2. BMI change over ten years between HUNT1 (1984–86) and HUNT2 was calculated and classified into quartiles. Seventy-five genetic variants were included as instruments for BMI (among which 14 also associated with smoking behavior). Incident lung cancer cases were ascertained from the Cancer Registry of Norway. Cox regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Multivariable MR was used to examine the effect of BMI after genetically controlling for smoking.

Results

During a median follow-up of 21.1 years, 1009 participants developed lung cancer including 327 with lung adenocarcinoma. The HRs and 95% CIs for incidence of adenocarcinoma were 0.73 (0.58–0.92) for BMI 25.0–29.9 kg/m2 and 0.53 (0.37–0.76) for BMI ≥ 30 kg/m2 compared with BMI < 25.0 kg/m2 in HUNT2 (P for trend < 0.001). However, there was little evidence of a dose–response relationship between the BMI change from HUNT1 to HUNT2 in quartiles and the incidence of adenocarcinoma (P for trend = 0.08). Furthermore, multivariable MR approach suggested a positive association between genetically determined 1 kg/m2 increase in BMI and the incidence of adenocarcinoma (HR 1.25, 95% CI 1.02–1.53). No associations were found with other lung cancer histologic types.

Conclusions

Our study suggests that the inverse association between baseline BMI and lung adenocarcinoma in observational analysis may not be causal. More MR studies are needed to confirm our finding of a positive association between BMI and lung adenocarcinoma.

From classical mendelian randomization to causal networks for systematic integration of multi-omics

The number of studies with information at multiple biological levels of granularity, such as genomics, proteomics, and metabolomics, is increasing each year, and a biomedical questaion is how to systematically integrate these data to discover new biological mechanisms that have the potential to elucidate the processes of health and disease. Causal frameworks, such as Mendelian randomization (MR), provide a foundation to begin integrating data for new biological discoveries. Despite the growing number of MR applications in a wide variety of biomedical studies, there are few approaches for the systematic analysis of omic data. The large number and diverse types of molecular components involved in complex diseases interact through complex networks, and classical MR approaches targeting individual components do not consider the underlying relationships. In contrast, causal network models established in the principles of MR offer significant improvements to the classical MR framework for understanding omic data. Integration of these mostly distinct branches of statistics is a recent development, and we here review the current progress. To set the stage for causal network models, we review some recent progress in the classical MR framework. We then explain how to transition from the classical MR framework to causal networks. We discuss the identification of causal networks and evaluate the underlying assumptions. We also introduce some tests for sensitivity analysis and stability assessment of causal networks. We then review practical details to perform real data analysis and identify causal networks and highlight some of the utility of causal networks. The utilities with validated novel findings reveal the full potential of causal networks as a systems approach that will become necessary to integrate large-scale omic data.

Body Size at Different Ages and Risk of 6 Cancers: A Mendelian Randomization and Prospective Cohort Study

It is unclear if body weight in early life affects cancer risk independently of adult body weight. To investigate this question for 6 obesity-related cancers, we performed univariable and multivariable analyses using 1) Mendelian randomization (MR) analysis and 2) longitudinal analyses in prospective cohorts. Both the MR and longitudinal analyses indicated that larger early life body size was associated with higher risk of endometrial (odds ratioMR = 1.61, 95% confidence interval = 1.23 to 2.11) and kidney (odds ratioMR = 1.40, 95% confidence interval = 1.09 to 1.80) cancer. These associations were attenuated after accounting for adult body size in both the MR and cohort analyses. Early life body mass index (BMI) was not consistently associated with the other investigated cancers. The lack of clear independent risk associations suggests that early life BMI influences endometrial and kidney cancer risk mainly through pathways that are common with adult BMI.

The Association of Serum Uric Acid Level, Gout, and Alzheimer's Disease: A Bidirectional Mendelian Randomization Study

BACKGROUND

The relationship between serum uric acid (UA) and Alzheimer's disease (AD) risk still remained ambiguous despite extensive attempts.

OBJECTIVE

Via the two-sample Mendelian randomization (MR) design, we aimed to examine the bidirectional causal relationships of serum UA, gout, and the risk of AD.

METHODS

Genetic variants of UA, gout, and AD were extracted from published genome-wide association summary statistics. The inverse-variance weighted (IVW, the primary method), and several sensitivity methods (MR-Egger, weighted median, and weighted mode) were used to calculate the effect estimates. Egger regression, MR-PRESSO and leave-one-SNP-out analysis were performed to identify potential violations.

RESULTS

Genetic proxies for serum UA concentration [odds ratio (ORIVW) = 1.09, 95% confidence interval (CI) = 1.01-1.19, p = 0.031] were related with an increased risk of AD using 25 single nucleotide polymorphisms (SNPs). This causal effect was confirmed by sensitivity analyses including MR-Egger (1.22, 1.06-1.42, p = 0.014), weighted median (1.18, 1.05-1.33, p = 0.006), and weighted mode (1.20, 1.07-1.35, p = 0.005) methods. No evidence of notable directional pleiotropy and heterogeneity were identified (p >  0.05). Three SNPs (rs2078267, rs2231142, and rs11722228) significantly drove the observed causal effects. Supportive causal effect of genetically determined gout on AD risk was demonstrated using two SNPs (ORIVW = 1.05, 95% CI = 1.00-1.11, p = 0.057). No reverse causal effects of AD on serum UA levels and gout risk were found.

CONCLUSION

The findings revealed a causal relationship between elevated serum UA level and AD risk. However, further research is still warranted to investigate whether serum UA could be a reliable biomarker and therapeutic target for AD.

Genetic Obesity Variants and Risk of Conventional Adenomas and Serrated Polyps

BACKGROUND

Higher body mass index (BMI) is associated with increased risk of colorectal cancer. How genetically predicted BMI may be associated with colorectal cancer precursors is unknown.

AIMS

Our objective was to quantify the association of genetically predicted and measured BMI with risk of colorectal cancer precursors.

METHODS

We evaluated the association of genetically predicted and measured BMI with risk of conventional adenomas, serrated polyps, and synchronous polyps among 27,426 participants who had undergone at least one lower gastrointestinal endoscopy in the Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-up Study. Genetic risk score was derived from 97 BMI-related single nucleotide polymorphisms. Multivariable logistic regression evaluated each polyp subtype compared to non-polyps.

RESULTS

For conventional adenomas, the OR per 2-kg/m² increase was 1.03 (95% CI, 1.01-1.04) for measured BMI and 0.98 (95% CI, 0.88-1.10) for genetically predicted BMI; for serrated polyps, the OR was 1.06 (95% CI, 1.04-1.08) and 1.04 (95% CI, 0.90-1.20), respectively; for synchronous polyps, the OR was 1.10 (95% CI, 1.07-1.13) and 1.09 (95% CI, 0.89-1.34), respectively. Genetically predicted BMI was associated with synchronous polyps in women (OR = 1.37, 95% CI: 1.05-1.79).

CONCLUSION

Genetically predicted BMI was not associated with colorectal cancer precursor lesions. The confidence intervals were wide and encompassed those for measured BMI, indicating that null findings may be due to insufficient power.

Associations between potential causal factors and colorectal cancer risk: A systematic review and meta-analysis of Mendelian randomization studies

OBJECTIVE

To summarize the associations between potential causal factors and colorectal cancer (CRC) risk based on existing Mendelian randomization studies.

METHODS

This systematic review and meta-analysis involved a literature search in Embase and Medline. All published articles using Mendelian randomization to explore potential causal factors of CRC were included. Studies that reported Mendelian randomization estimates of standard deviation changes in exposures were included in the meta-analysis. Subgroup analyses based on sex and anatomical sites were performed.

RESULTS

One hundred and ninety studies presented in 51 articles were included in systematic review, and 114 studies conducted in 32 articles were included in the meta-analysis. Adult body mass index, waist circumference, waist hip ratio, body height, body fat percentage, arm fat ratio, childhood obesity, lifetime cigarette consumption, short sleep, coffee consumption, and blood levels of vitamin B₁₂ , arachidonic acid, stearic acid, and insulin-like growth factor binding protein 3 were positively associated with CRC risk. Conversely, acceleration-vector-magnitude physical activity, milk consumption, and blood levels of adiponectin, linoleic acid, α-linolenic acid, oleic acid, palmitoleic acid, interleukin-6 receptor subunit-α, and tumor necrosis factor were inversely associated with CRC risk.

CONCLUSIONS

Most obesity-related anthropometric characteristics, several unhealthy lifestyles, and blood levels of some micronutrients, fatty acids, and diabetes-related biomarkers were positively associated with CRC risk. In contrast, some lifestyles and blood levels of some fatty acids and inflammatory biomarkers were inversely associated with CRC risk. Future studies with more valid genetic variants are needed for factors with discrepancies between Mendelian randomization and epidemiological studies.

The timing of adiposity and changes in the life course on the risk of cancer

Excess body weight has been established as a risk factor for at least twelve cancer sites, though questions remain as to the timing of associations for adiposity and cancer risk throughout the life course. We conducted a narrative review summarizing existing evidence to provide insights into the complex timing relationship between adiposity and risk of seven common obesity-related cancers. We considered five types of studies, including traditional epidemiologic studies examining adiposity at different time points, studies examining weight gain in specific life phases, studies examining weight loss over a period including from bariatric surgery, life course trajectory analysis, and Mendelian randomization studies. The results showed that lifetime excess body weight is associated with increased risk of cancers of endometrium, colorectum, liver, kidney, and pancreas. Early life obesity is one of the strongest risk factors for pancreatic cancer but less directly important than adult obesity for endometrial and kidney cancer. Interestingly, heavy weight during childhood, adolescence, and early adulthood is protective against pre- and postmenopausal breast cancer and possibly advanced prostate cancer. It is apparent that preventing weight gain later in adulthood would likely reduce risk of many cancers, including postmenopausal breast cancer, endometrial cancer, colorectal cancer (especially in men), liver cancer, kidney cancer, and probably advanced prostate cancer. Furthermore, weight loss even late in life may confer benefits for cancers of breast, endometrium, colorectum, and liver among patients with obesity, as mostly demonstrated by studies of bariatric surgery. Overall, maintaining a healthy weight throughout the life course will help prevent a large number of cancers.

Maternal obesity, pregnancy weight gain, and birth weight and risk of colorectal cancer

OBJECTIVE

Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide. Obesity is a well-established risk factor for CRC, and fetal or developmental origins of obesity may underlie its effect on cancer in adulthood. We examined associations of maternal obesity, pregnancy weight gain, and birth weight and CRC in adult offspring.

DESIGN

The Child Health and Development Studies is a prospective cohort of women receiving prenatal care between 1959 and 1966 in Oakland, California (N=18 751 live births among 14 507 mothers). Clinical information was abstracted from mothers' medical records 6 months prior to pregnancy through delivery. Diagnoses of CRC in adult (age ≥18 years) offspring were ascertained through 2019 by linkage with the California Cancer Registry. We used Cox proportional hazards models to estimate adjusted HR (aHR); we examined effect measure modification using single-referent models to estimate the relative excess risk due to interaction (RERI).

RESULTS

68 offspring were diagnosed with CRC over 738 048 person-years of follow-up, and half (48.5%) were diagnosed younger than age 50 years. Maternal obesity (≥30 kg/m²) increased the risk of CRC in offspring (aHR 2.51, 95% CI 1.05 to 6.02). Total weight gain modified the association of rate of early weight gain (RERI -4.37, 95% CI -9.49 to 0.76), suggesting discordant growth from early to late pregnancy increases risk. There was an elevated association with birth weight (≥4000 g: aHR 1.95, 95% CI 0.8 to 4.38).

CONCLUSION

Our results suggest that in utero events are important risk factors for CRC and may contribute to increasing incidence rates in younger adults.

Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer

Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.

Anthropometric factors and the risk of ovarian cancer: A systematic review and meta-analysis

BACKGROUND

Excess weight is convincingly associated with several cancers, but the association with ovarian cancer is insufficiently clarified, in particular regarding subgroups defined by menopausal status and ovarian cancer histologic type.

AIMS

We carried out a comprehensive systematic review and meta-analysis of overweight and obesity in relation to ovarian cancer with focus on different subgroups.

METHODS AND RESULTS

We searched PubMed and Web of Science for relevant cohort and case-control studies published from inception to June 2021 in English language and using a clear definition of overweight and obesity. We combined maximally adjusted risk estimates using a random effects model. We analyzed data from 15 cohort and 26 case-control studies, including 28 471 ovarian cancer cases. The relative risk of ovarian cancer for overweight and obesity was 1.06 (95% confidence interval [CI] = 1.00-1.12) and 1.19 (95% CI = 1.11-1.28), respectively. Among premenopausal women, increased ovarian cancer risk was noted for overweight (RR 1.34; 95% CI = 1.03-1.75) and obesity (RR 1.51; 95% CI = 1.21-1.88). By comparison, among postmenopausal women no statistically significant association was found for overweight (RR 1.00; 95% CI 0.87-1.14) and obesity (RR1.03; 95% CI = 0.82-1.31). Increased risk was found for mucinous (RR 1.44; 95% CI = 1.03-2.01) and clear cell (RR 1.82; 95% CI = 1.11-2.99) ovarian cancer subtypes, but not for serous (RR1.12; 95% CI = 0.84-1.50;) and endometroid subtypes (RR1.24; 95% CI =0.96-1.60).

CONCLUSIONS

Obesity is associated with increased ovarian cancer risk. That relation is largely due to a positive association between adiposity and ovarian cancer among premenopausal but not postmenopausal women and among cases with mucinous and clear cell but not serous or endometrioid histology.

Field cancerization in breast cancer

Breast cancer affects one in seven women worldwide during their lifetime. Widespread mammographic screening programs and education campaigns allow for early detection of the disease, often during its asymptomatic phase. Current practice in treatment and recurrence monitoring is based primarily on pathological evaluations but can also encompass genomic evaluations, both of which focus on the primary tumor. Although breast cancer is one of the most studied cancers, patients still recur at a rate of up to 15% within the first 10 years post‐surgery. Local recurrence was originally attributed to tumor cells contaminating histologically normal (HN) tissues beyond the surgical margin, but advances in technology have allowed for the identification of distinct aberrations that exist in the peri‐tumoral tissues themselves. One leading theory to explain this phenomenon is the field cancerization theory. Under this hypothesis, tumors arise from a field of molecularly altered cells that create a permissive environment for malignant evolution, which can occur with or without morphological changes. The traditional histopathology paradigm dictates that molecular alterations are reflected in the tissue phenotype. However, the spectrum of inter‐patient variability of normal breast tissue may obfuscate recognition of a cancerized field during routine diagnostics. In this review, we explore the concept of field cancerization focusing on HN peri‐tumoral tissues: we present the pathological and molecular features of field cancerization within these tissues and discuss how the use of peri‐tumoral tissues can affect research. Our observations suggest that pathological and molecular evaluations could be used synergistically to assess risk and guide the therapeutic management of patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Changes in adiposity over the life course and gene expression in postmenopausal women

BACKGROUND

Early life adiposity and changes in adiposity over the life course are associated with mammographic breast density among postmenopausal women. However, the underlying mechanisms are unknown; therefore, we comprehensively examined the associations of early life body mass index (BMI) and changes in BMI from ages 10, 18 to age at mammogram with growth factor, RANK pathway, and sex hormone gene expression in 372 postmenopausal women.

METHODS

We estimated early life BMI at age 10 using the validated 9-level Stunkard pictogram. We calculated BMI at other ages (18, 30, and current age at mammogram) by dividing weight in kilograms at these ages with height in meters squared. Sequencing for gene expression was performed using the NanoString nCounter system. After adjusting for confounders, we estimated associations using multivariable linear regressions.

RESULTS

A 10 kg/m² increase in early life BMI at age 10 was associated with a 17.2% decrease in RANKL gene expression (95% confidence interval [CI] = -30.8, -0.9) but was not associated with changes in other markers. BMI changes from ages 10, 18 to age at mammogram were associated with an increase in BMP2 and decreases in RANK, RANKL, and TNFRSF13B gene expression but were not associated with gene expression of other markers. A 10 kg/m² increase in early life BMI from age 10 to current age was associated with a 7.8% increase in BMP2 (95% CI = -1.4, 17.8), an 8.5% decrease in RANK (95% CI = -13.9, -2.8), a 10.4% decrease in RANKL (95% CI = -16.9, -3.3), and an 8.5% decrease in TNFRSF13B gene expression (95% CI = -13.8, -2.8).

CONCLUSION

The results provide new insights into the biological mechanisms underlying the associations of adiposity changes from early life to adulthood and early life adiposity with mammographic breast density in postmenopausal women.

Body size in early life and the risk of postmenopausal breast cancer

BACKGROUND

Greater early life adiposity has been reported to reduce postmenopausal breast cancer risk but it is unclear whether this association varies by tumour characteristics. We aimed to assess associations of early life body size with postmenopausal breast cancer and its subtypes, allowing for body size at other ages.

METHODS

A total of 342,079 postmenopausal UK women who reported their body size at age 10, clothes size at age 20, and body mass index (BMI) at baseline (around age 60) were followed by record linkage to national databases for cancers and deaths. Cox regression yielded adjusted relative risks (RRs) of breast cancer, overall and by tumour subtype, in relation to body size at different ages.

RESULTS

During an average follow-up of 14 years, 15,506 breast cancers were diagnosed. After adjustment for 15 potential confounders, greater BMI at age 60 was associated with an increased risk of postmenopausal breast cancer (RR per 5 kg/m2=1.20, 95%CI 1.18-1.22) whereas greater adiposity in childhood and, to a lesser extent, early adulthood, was associated with a reduced risk (0.70, 0.66-0.74, and 0.92, 0.89-0.96, respectively). Additional adjustment for midlife BMI strengthened associations with BMI at both age 10 (0.63, 0.60-0.68) and at age 20 (0.78, 0.75-0.81). The association with midlife adiposity was confined to hormone sensitive subtypes but early life adiposity had a similar impact on the risk of all subtypes.

CONCLUSION

Early life and midlife adiposity have opposite effects on postmenopausal breast cancer risk and the biological mechanisms underlying these associations are likely to differ.

The Role of Mendelian Randomization Studies in Deciphering the Effect of Obesity on Cancer

Associations of obesity have been established for at least 11 cancer sites in observational studies, though some questions remain as to causality, strength of associations, and timing of associations throughout the life course. In recent years, Mendelian randomization (MR) has provided complementary information to traditional approaches, but the validity requires that the genetic instrumental variables be causally related to cancers only mediated by the exposure. We summarize and evaluate existing evidence from MR studies in comparison with conventional observational studies to provide insights into the complex relationship between obesity and multiple cancers. MR studies further establish the causality of adult obesity with esophageal adenocarcinoma and cancers of the colorectum, endometrium, ovary, kidney, and pancreas, as well as the inverse association of early life obesity with breast cancer. MR studies, which might account for lifelong adiposity, suggest that the associations in observational studies typically based on single measurement may underestimate the magnitude of the association. For lung cancer, MR studies find a positive association with obesity, supporting that the inverse association observed in some conventional observational studies likely reflects reverse causality (loss of lean body mass before diagnosis) and confounding by smoking. However, MR studies have not had sufficient power for gallbladder cancer, gastric cardia cancer, and multiple myeloma. In addition, more MR studies are needed to explore the effect of obesity at different timepoints on postmenopausal breast cancer and aggressive prostate cancer.

Associations of genetically proxied inhibition of HMG-CoA reductase, NPC1L1, and PCSK9 with breast cancer and prostate cancer

BACKGROUND

Preclinical and epidemiological studies indicate a potential chemopreventive role of low-density lipoprotein cholesterol (LDL-C) -lowering drugs in the risks of breast cancer and prostate cancer, but the causality remains unclear. We aimed to evaluate the association of genetically proxied inhibition of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, Niemann-Pick C1-Like 1 (NPC1L1), and proprotein convertase subtilisin/kexin type 9 (PCSK9) with risks of breast cancer and prostate cancer using a two-sample Mendelian randomization (MR) method.

METHODS

Single-nucleotide polymorphisms (SNPs) in HMGCR, NPC1L1, and PCSK9 associated with LDL-C in a genome-wide association study (GWAS) meta-analysis from the Global Lipids Genetics Consortium (GLGC; up to 188,577 European individuals) were used to proxy inhibition of HMG-CoA reductase, NPC1L1, and PCSK9. Summary statistics with outcomes were obtained from a GWAS meta-analysis of the Breast Cancer Association Consortium (BCAC; 228,951 European females) and a Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL; 140,254 European males) consortium. SNPs were combined into multiallelic models and MR estimates representing lifelong inhibition of targets were generated using the inverse-variance weighted method.

RESULTS

Genetically proxied inhibition of HMG-CoA reductase (OR: 0.84; 95% CI 0.74-0.95; P = 0.005) and NPC1L1 (OR: 0.72; 95% CI 0.58-0.90; P = 0.005) equivalent to a 1-mmol/L (38.7 mg/dL) reduction in LDL-C was associated with reduced breast cancer risk. There were no significant associations of genetically proxied inhibition of PCSK9 with breast cancer. In contrast, genetically proxied inhibition of PCSK9 (OR: 0.81; 95% CI 0.73-0.90; P < 0.001) but not HMG-CoA reductase and NPC1L1 was negatively associated with prostate cancer. In the secondary analysis, genetically proxied inhibition of HMG-CoA reductase (OR: 0.82; 95% CI 0.71-0.95; P = 0.008) and NPC1L1 (OR: 0.66; 95% CI 0.50-0.86; P = 0.002) was associated with estrogen receptor-positive breast cancer, whereas there was no association of HMG-CoA reductase and NPC1L1 with estrogen receptor-negative breast cancer.

CONCLUSIONS

Genetically proxied inhibition of HMG-CoA reductase and NPC1L1 was significantly associated with lower odds of breast cancer, while genetically proxied inhibition of PCSK9 was associated with reduced risk of prostate cancer. Further randomized controlled trials are needed to confirm the respective roles of these LDL-C-lowering drugs in breast cancer and prostate cancer.

Mendelian Randomization: A Review of Methods for the Prevention, Assessment, and Discussion of Pleiotropy in Studies Using the Fat Mass and Obesity-Associated Gene as an Instrument for Adiposity

Pleiotropy assessment is critical for the validity of Mendelian randomization (MR) analyses, and its management remains a challenging task for researchers. This review examines how the authors of MR studies address bias due to pleiotropy in practice. We reviewed Pubmed, Medline, Embase and Web of Science for MR studies published before 21 May 2020 that used at least one single-nucleotide polymorphism (SNP) in the fat mass and obesity-associated (FTO) gene as instrumental variable (IV) for body mass index, irrespective of the outcome. We reviewed: 1) the approaches used to prevent pleiotropy, 2) the methods cited to detect or control the independence or the exclusion restriction assumption highlighting whether pleiotropy assessment was explicitly stated to justify the use of these methods, and 3) the discussion of findings related to pleiotropy. We included 128 studies, of which thirty-three reported one approach to prevent pleiotropy, such as the use of multiple (independent) SNPs combined in a genetic risk score as IVs. One hundred and twenty studies cited at least one method to detect or account for pleiotropy, including robust and other IV estimation methods (n = 70), methods for detection of heterogeneity between estimated causal effects across IVs (n = 72), methods to detect or account associations between IV and outcome outside thought the exposure (n = 85), and other methods (n = 5). Twenty-one studies suspected IV invalidity, of which 16 explicitly referred to pleiotropy, and six incriminating FTO SNPs. Most reviewed MR studies have cited methods to prevent or to detect or control bias due to pleiotropy. These methods are heterogeneous, their triangulation should increase the reliability of causal inference.

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.

Associations Between Relative Grip Strength and the Risk of 15 Cancer Sites

INTRODUCTION

Grip strength is the most commonly used muscle strength proxy in clinical research. However, evidence regarding the associations of grip strength with cancer has been mainly restricted to overall cancer risk. Therefore, this study aims to evaluate the associations between grip strength relative to BMI and 15 cancer sites as well as with all-cause cancer mortality.

METHODS

A total of 445,555 participants (53.8% women, mean age=56.3 years) were recruited across the United Kingdom. The association of grip strength relative to BMI (expressed as 1 SD) with incidence and mortality from 15 cancer sites was investigated using Cox proportional hazard models. All analyses were conducted in April 2021.

RESULTS

Over an 8.8-year follow-up period, 37,291 patients were diagnosed with cancer, and 11,363 died of it. After covariate adjustment, higher relative grip strength per 1 SD was associated with a lower risk of incident endometrial (hazard ratio=0.76, 95% CI=0.71, 0.81), liver (hazard ratio=0.81, 95% CI=0.74, 0.88), gallbladder (hazard ratio=0.83, 95% CI=0.73, 0.94), kidney (hazard ratio=0.89, 95% CI=0.84, 0.95), and colorectal (hazard ratio=0.94, 95% CI=0.91, 0.98) cancer as well as with lower risk of gallbladder, colorectal, endometrial, liver, and all-cause cancer mortality.

CONCLUSIONS

Grip strength relative to BMI was associated with incidence and mortality from endometrial, gallbladder, colorectal, liver, all-cause cancer, and breast and kidney cancer incidence, independent of major confounding factors, including comorbidity, diet, and physical activity.

Pediatric and adult obesity concerns in female health: a Mendelian randomization study

PURPOSE

Adulthood and childhood obesity are both associated with reproductive diseases and gynecological cancers in females. However, the causal factors associated with these observations have yet to be identified. Mendelian randomization is a process that is independent of inverse bias and confounding and can act as a random control trial in which genetic groups are settled during meiosis, thus representing an effective tool with which to investigate causality.

METHODS

We carried out several Mendelian randomization trials based on the combined genetic scores of 75 adult-associated and 15 childhood-associated body mass index (BMI) single nucleotide polymorphisms (SNPs), databases for several gynecological cancers and reproductive diseases from the UK Biobank (with 194,153 participants), using the traditional inverse-variance weighted (IVW) method as the main method.

RESULTS

Elevated adult-associated BMI scores (odds ratio [OR] = 1.003; 95% confidence interval [CI]: 1.001-1.004) and childhood-associated BMI scores (OR = 1.003; 95% CI: 1.001-1.004) were related to a higher risk of the polycystic ovarian syndrome (PCOS), as determined by the traditional IVW method. The random IVW method further revealed a nominal negative causal association between childhood-associated BMI and subsequent endometriosis (OR = 0.995; 95% CI: 0.991-0.999).

CONCLUSIONS

Consistent with observational consequences, our findings indicated that adulthood obesity may play role in the development of PCOS and that childhood obesity can increase the risk of PCOS but may reduce the incidence of endometriosis in later life. Further research is now needed to validate our findings and identify the precise mechanisms involved.

Disease consequences of higher adiposity uncoupled from its adverse metabolic effects using Mendelian randomisation

Background

Some individuals living with obesity may be relatively metabolically healthy, whilst others suffer from multiple conditions that may be linked to adverse metabolic effects or other factors. The extent to which the adverse metabolic component of obesity contributes to disease compared to the non-metabolic components is often uncertain. We aimed to use Mendelian randomisation (MR) and specific genetic variants to separately test the causal roles of higher adiposity with and without its adverse metabolic effects on diseases.

Methods

We selected 37 chronic diseases associated with obesity and genetic variants associated with different aspects of excess weight. These genetic variants included those associated with metabolically 'favourable adiposity' (FA) and 'unfavourable adiposity' (UFA) that are both associated with higher adiposity but with opposite effects on metabolic risk. We used these variants and two sample MR to test the effects on the chronic diseases.

Results

MR identified two sets of diseases. First, 11 conditions where the metabolic effect of higher adiposity is the likely primary cause of the disease. Here, MR with the FA and UFA genetics showed opposing effects on risk of disease: coronary artery disease, peripheral artery disease, hypertension, stroke, type 2 diabetes, polycystic ovary syndrome, heart failure, atrial fibrillation, chronic kidney disease, renal cancer, and gout. Second, 9 conditions where the non-metabolic effects of excess weight (e.g. mechanical effect) are likely a cause. Here, MR with the FA genetics, despite leading to lower metabolic risk, and MR with the UFA genetics, both indicated higher disease risk: osteoarthritis, rheumatoid arthritis, osteoporosis, gastro-oesophageal reflux disease, gallstones, adult-onset asthma, psoriasis, deep vein thrombosis, and venous thromboembolism.

Conclusions

Our results assist in understanding the consequences of higher adiposity uncoupled from its adverse metabolic effects, including the risks to individuals with high body mass index who may be relatively metabolically healthy.

Funding

Diabetes UK, UK Medical Research Council, World Cancer Research Fund, National Cancer Institute.

Mendelian randomisation analyses of UK Biobank and published data suggest that increased adiposity lowers risk of breast and prostate cancer

Breast (BCa) and prostate (PrCa) cancer are the first and second most common types of cancer in women and men, respectively. We aimed to explore the causal effect of adiposity on BCa and PrCa risk in the UK Biobank and published data. We used Mendelian randomisation (MR) to assess the causal effect of body mass index (BMI), body fat percentage (BFP), waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR) on BCa and PrCa risk. We found that increased BMI, WC and HC decreased the risk of breast cancer (OR 0.70 per 5.14 kg/m2 [0.59-0.85, p = 2.1 × 10-4], 0.76 per 12.49 cm [60-0.97, p = 0.028] and 0.73 per 10.31 cm [0.59-0.90, p = 3.7 × 10-3], respectively) and increased WC and BMI decreased the risk of prostate cancer (0.68 per 11.32 cm [0.50-0.91, p = 0.01] and 0.76 per 10.23 kg/m2 [0.61-0.95, p = 0.015], respectively) in UK Biobank participants. We confirmed our results with a two-sample-MR of published data. In conclusion, our results suggest a protective effect of adiposity on the risk of BCa and PrCa highlighting the need to re-evaluate the role of adiposity as cancer risk factor.

Expression profiles of GPR21, GPR39, GPR135, and GPR153 orphan receptors in different cancers

Orphan receptors have unknown endogenous ligands, are expressed in different tissues, and participate in various diseases such as diabetes, hypertension and cancer. We studied the expression profiles of GPR21, GPR39, GPR135 and GPR153 orphan receptors in several tumour tissues. Cervical, breast, skin, prostate, and astrocytoma tissues were analysed for orphan receptor gene expression using Real time PCR analysis. GPR39 is over-expressed in cervical and prostate cancer tissues, and GPR21 and GPR135 receptors are significantly decreased in cervical, breast, skin, prostate, and astrocytoma tissues, when compared with healthy human fibroblasts. In conclusion, GPR21 and GPR135 receptor gene expression is reduced in cancerous tissues. GPR39 may have a role in the development and evolution of cervical and prostate cancer. These data suggest these receptors may be alternative molecules for new diagnostic approaches, and the design of novel therapeutics against oncological pathologies.

Estimating the influence of body mass index (BMI) on mortality using offspring BMI as an instrumental variable

OBJECTIVE

High body mass index (BMI) is an important predictor of mortality but estimating underlying causality is hampered by confounding and pre-existing disease. Here, we use information from the offspring to approximate parental BMIs, with an aim to avoid biased estimation of mortality risk caused by reverse causality.

METHODS

The analyses were based on information on 9674 offspring-mother and 9096 offspring-father pairs obtained from the 1958 British birth cohort. Parental BMI-mortality associations were analysed using conventional methods and using offspring BMI as a proxy, or instrument, for their parents' BMI.

RESULTS

In the conventional analysis, associations between parental BMI and all-cause mortality were U-shaped (P_curvature < 0.001), while offspring BMI had linear associations with parental mortality (P_trend < 0.001, P_curvature > 0.46). Curvature was particularly pronounced for mortality from respiratory diseases and from lung cancer. Instrumental variable analyses suggested a positive association between BMI and mortality from all causes [mothers: HR per SD of BMI 1.43 (95% CI 1.21-1.69), fathers: HR 1.17 (1.00-1.36)] and from coronary heart disease [mothers: HR 1.65 (1.15-2.36), fathers: HR 1.51 (1.17-1.97)]. These were larger than HR from the equivalent conventional analyses, despite some attenuation by adjustment for social indicators and smoking.

CONCLUSIONS

Analyses using offspring BMI as a proxy for parental BMI suggest that the apparent adverse consequences of low BMI are considerably overestimated and adverse consequences of overweight are underestimated in conventional epidemiological studies.

Genetic Liability to Insomnia and Lung Cancer Risk: A Mendelian Randomization Analysis

Lung cancer is the second most frequently diagnosed cancer and the leading cause of cancer death worldwide, making its prevention an urgent issue. Meanwhile, the estimated prevalence of insomnia was as high as 30% globally. Research on the causal effect of insomnia on lung cancer incidence is still lacking. In this study, we aimed to assess the causality between the genetic liability to insomnia and lung cancer. We performed a two-sample Mendelian randomization analysis (inverse variance weighted) to determine the causality between the genetic liability to insomnia and lung cancer. Subgroup analysis was conducted, which included lung adenocarcinoma and lung squamous cell carcinoma. In the sensitivity analysis, we conducted heterogeneity test, MR Egger, single SNP analysis, leave-one-out analysis, and MR PRESSO. There were causalities between the genetic susceptibility to insomnia and increased incidence of lung cancer [odds ratio (95% confidence interval), 1.35 (1.14-1.59); P, < 0.001], lung adenocarcinoma [odds ratio (95% confidence interval), 1.35 (1.07-1.70); P, 0.01], and lung squamous cell carcinoma [odds ratio (95% confidence interval), 1.35 (1.06-1.72), P, 0.02]. No violation of Mendelian randomization assumptions was observed in the sensitivity analysis. There was a causal relationship between the genetic susceptibility to insomnia and the lung cancer, which was also observed in lung adenocarcinoma and lung squamous cell carcinoma. The underlying mechanism remains unknown. Effective intervention and management for insomnia were recommended to improve the sleep quality and to prevent lung cancer. Moreover, regular screening for lung cancer may be beneficial for patients with insomnia.

Identifying causality, genetic correlation, priority and pathways of large-scale complex exposures of breast and ovarian cancers

BACKGROUND

Genetic correlations, causalities and pathways between large-scale complex exposures and ovarian and breast cancers need systematic exploration.

METHODS

Mendelian randomisation (MR) and genetic correlation (GC) were used to identify causal biomarkers from 95 cancer-related exposures for risk of breast cancer [BC: oestrogen receptor-positive (ER + BC) and oestrogen receptor-negative (ER - BC) subtypes] and ovarian cancer [OC: high-grade serous (HGSOC), low-grade serous, invasive mucinous (IMOC), endometrioid (EOC) and clear cell (CCOC) subtypes].

RESULTS

Of 31 identified robust risk factors, 16 were new causal biomarkers for BC and OC. Body mass index (BMI), body fat mass (BFM), comparative body size at age 10 (CBS-10), waist circumference (WC) and education attainment were shared risk factors for overall BC and OC. Childhood obesity, BMI, CBS-10, WC, schizophrenia and age at menopause were significantly associated with ER + BC and ER - BC. Omega-6:omega-3 fatty acids, body fat-free mass and basal metabolic rate were positively associated with CCOC and EOC; BFM, linoleic acid, omega-6 fatty acids, CBS-10 and birth weight were significantly associated with IMOC; and body fat percentage, BFM and adiponectin were significantly associated with HGSOC. Both GC and MR identified 13 shared factors. Factors were stratified into five priority levels, and visual causal networks were constructed for future interventions.

CONCLUSIONS

With analysis of large-scale exposures for breast and ovarian cancers, causalities, genetic correlations, shared or specific factors, risk factor priority and causal pathways and networks were identified.

Body Fat Distribution and Risk of Breast, Endometrial, and Ovarian Cancer: A Two-Sample Mendelian Randomization Study

Simple Summary

The causal impact of body fat distribution on female-specific cancers is largely unknown. For the first time we used a two-sample multivariable Mendelian randomization (MR) approach to elucidate the role and causal relations of body composition assessed by segmental bioelectrical impedance analysis on the risks of breast, endometrial and ovarian cancers and their subtypes. We found that abdominal fat content increases the risk for ovarian cancer and its endometrioid and clear cell subtypes independent of overall fat content. General adiposity has a protective effect on risk of breast cancer and its ER- and ER+ subtypes but increases the risk for endometrial cancer, ovarian cancer, and the endometrioid ovarian cancer subtype. This study extends the literature by addressing specifically the causal role of visceral fat on female-specific cancers.

Abstract

Background: Mounting evidence shows that adiposity increases female-specific cancer risk, but the role of body fat distribution is less clear. We used a two-sample Mendelian randomization (MR) approach to elucidate causal relations of body fat distribution to the risks of breast, endometrial and ovarian cancers and their subtypes. Methods: Body composition was assessed using segmental bioelectrical impedance analysis, yielding trunk, arm, and leg fat ratios (TFR, AFR, LFR) and BMI including 195,043 and 434,794 European women, respectively. The sample sizes for the outcomes ranged between 58,396 and 228,951. Causal effects were estimated per one standard deviation increment in the respective exposure within the radial regression framework. Robust sensitivity analyses were performed to verify MR assumptions. In a multivariable MR setting, the proportion of risk attributable to overall and abdominal fat content was assessed. Results: TFR, which represents abdominal fat content, was associated with ovarian cancer and its clear cell and endometrioid histotypes independent of overall fat content. BMI was inversely associated with breast cancer and its ER− and ER+ subtypes, but positively with endometrial cancer and ovarian cancer, including its endometrioid histotype. These estimates were confirmed using AFR as proxy for overall body fat. Conclusions: Visceral adiposity seems to be a driver of elevated ovarian cancer risk, particularly of the endometrioid and clear cell ovarian cancer histotypes. General adiposity decreases the risk of breast cancer but increases the risk of endometrial and ovarian cancer.

Gene-by-environment modulation of lifespan and weight gain in the murine BXD family

How lifespan and body weight vary as a function of diet and genetic differences is not well understood. Here we quantify the impact of differences in diet on lifespan in a genetically diverse family of female mice, split into matched isogenic cohorts fed a low-fat chow diet (CD, n = 663) or a high-fat diet (HFD, n = 685). We further generate key metabolic data in a parallel cohort euthanized at four time points. HFD feeding shortens lifespan by 12%: equivalent to a decade in humans. Initial body weight and early weight gains account for longevity differences of roughly 4-6 days per gram. At 500 days, animals on a HFD typically gain four times as much weight as control, but variation in weight gain does not correlate with lifespan. Classic serum metabolites, often regarded as health biomarkers, are not necessarily strong predictors of longevity. Our data indicate that responses to a HFD are substantially modulated by gene-by-environment interactions, highlighting the importance of genetic variation in making accurate individualized dietary recommendations.

Review of Mendelian Randomization Studies on Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest gynecological cancers worldwide. Previous observational epidemiological studies have revealed associations between modifiable environmental risk factors and OC risk. However, these studies are prone to confounding, measurement error, and reverse causation, undermining robust causal inference. Mendelian randomization (MR) analysis has been established as a reliable method to investigate the causal relationship between risk factors and diseases using genetic variants to proxy modifiable exposures. Over recent years, MR analysis in OC research has received extensive attention, providing valuable insights into the etiology of OC as well as holding promise for identifying potential therapeutic interventions. This review provides a comprehensive overview of the key principles and assumptions of MR analysis. Published MR studies focusing on the causality between different risk factors and OC risk are summarized, along with comprehensive analysis of the method and its future applications. The results of MR studies on OC showed that higher BMI and height, earlier age at menarche, endometriosis, schizophrenia, and higher circulating β-carotene and circulating zinc levels are associated with an increased risk of OC. In contrast, polycystic ovary syndrome; vitiligo; higher circulating vitamin D, magnesium, and testosterone levels; and HMG-CoA reductase inhibition are associated with a reduced risk of OC. MR analysis presents a2 valuable approach to understanding the causality between different risk factors and OC after full consideration of its inherent assumptions and limitations.

Body size and composition and risk of site-specific cancers in the UK Biobank and large international consortia: A mendelian randomisation study

BACKGROUND

Evidence for the impact of body size and composition on cancer risk is limited. This mendelian randomisation (MR) study investigates evidence supporting causal relationships of body mass index (BMI), fat mass index (FMI), fat-free mass index (FFMI), and height with cancer risk.

METHODS AND FINDINGS

Single nucleotide polymorphisms (SNPs) were used as instrumental variables for BMI (312 SNPs), FMI (577 SNPs), FFMI (577 SNPs), and height (293 SNPs). Associations of the genetic variants with 22 site-specific cancers and overall cancer were estimated in 367,561 individuals from the UK Biobank (UKBB) and with lung, breast, ovarian, uterine, and prostate cancer in large international consortia. In the UKBB, genetically predicted BMI was positively associated with overall cancer (odds ratio [OR] per 1 kg/m2 increase 1.01, 95% confidence interval [CI] 1.00-1.02; p = 0.043); several digestive system cancers: stomach (OR 1.13, 95% CI 1.06-1.21; p < 0.001), esophagus (OR 1.10, 95% CI 1.03, 1.17; p = 0.003), liver (OR 1.13, 95% CI 1.03-1.25; p = 0.012), and pancreas (OR 1.06, 95% CI 1.01-1.12; p = 0.016); and lung cancer (OR 1.08, 95% CI 1.04-1.12; p < 0.001). For sex-specific cancers, genetically predicted elevated BMI was associated with an increased risk of uterine cancer (OR 1.10, 95% CI 1.05-1.15; p < 0.001) and with a lower risk of prostate cancer (OR 0.97, 95% CI 0.94-0.99; p = 0.009). When dividing cancers into digestive system versus non-digestive system, genetically predicted BMI was positively associated with digestive system cancers (OR 1.04, 95% CI 1.02-1.06; p < 0.001) but not with non-digestive system cancers (OR 1.01, 95% CI 0.99-1.02; p = 0.369). Genetically predicted FMI was positively associated with liver, pancreatic, and lung cancer and inversely associated with melanoma and prostate cancer. Genetically predicted FFMI was positively associated with non-Hodgkin lymphoma and melanoma. Genetically predicted height was associated with increased risk of overall cancer (OR per 1 standard deviation increase 1.09; 95% CI 1.05-1.12; p < 0.001) and multiple site-specific cancers. Similar results were observed in analyses using the weighted median and MR-Egger methods. Results based on consortium data confirmed the positive associations between BMI and lung and uterine cancer risk as well as the inverse association between BMI and prostate cancer, and, additionally, showed an inverse association between genetically predicted BMI and breast cancer. The main limitations are the assumption that genetic associations with cancer outcomes are mediated via the proposed risk factors and that estimates for some lower frequency cancer types are subject to low precision.

CONCLUSIONS

Our results show that the evidence for BMI as a causal risk factor for cancer is mixed. We find that BMI has a consistent causal role in increasing risk of digestive system cancers and a role for sex-specific cancers with inconsistent directions of effect. In contrast, increased height appears to have a consistent risk-increasing effect on overall and site-specific cancers.

The Inverse Association of Body Mass Index with Lung Cancer: Exploring Residual Confounding, Metabolic Aberrations and Within-Person Variability in Smoking

BACKGROUND

The inverse observational association between body mass index (BMI) and lung cancer risk remains unclear. We assessed whether the association is explained by metabolic aberrations, residual confounding, and within-person variability in smoking, and compared against other smoking-related cancers.

METHODS

We investigated the association between BMI, and its combination with a metabolic score (MS) of mid-blood pressure, glucose, and triglycerides, with lung cancer and other smoking-related cancers in 778,828 individuals. We used Cox regression, adjusted and corrected for within-person variability in smoking (status/pack-years), calculated from 600,201 measurements in 221,958 participants.

RESULTS

Over a median follow-up of 20 years, 20,242 smoking-related cancers (6,735 lung cancers) were recorded. Despite adjustment and correction for substantial within-person variability in smoking, BMI remained inversely associated with lung cancer [HR per standard deviation increase, 0.87 (95% confidence interval 0.85-0.89)]. Individuals with BMI less than 25 kg/m² and high MS had the highest risk [HR 1.52 (1.44-1.60) vs. BMI ≥25 with low MS]. These associations were weaker and nonsignificant among nonsmokers. Similar associations were observed for head and neck cancers and esophageal squamous cell carcinoma, whereas for other smoking-related cancers, we generally observed positive associations with BMI.

CONCLUSIONS

The increased lung cancer risk with low BMI and high MS is unlikely due to residual confounding and within-person variability in smoking. However, similar results for other cancers strongly related to smoking suggest a remaining, unknown, effect of smoking.

IMPACT

Extensive smoking-adjustments may not capture all the effects of smoking on the relationship between obesity-related factors and risk of smoking-related cancers.

Instrumental Heterogeneity in Sex-Specific Two-Sample Mendelian Randomization: Empirical Results From the Relationship Between Anthropometric Traits and Breast/Prostate Cancer

Background

In two-sample Mendelian randomization (MR) studies, sex instrumental heterogeneity is an important problem needed to address carefully, which however is often overlooked and may lead to misleading causal inference.

Methods

We first employed cross-trait linkage disequilibrium score regression (LDSC), Pearson's correlation analysis, and the Cochran's Q test to examine sex genetic similarity and heterogeneity in instrumental variables (IVs) of exposures. Simulation was further performed to explore the influence of sex instrumental heterogeneity on causal effect estimation in sex-specific two-sample MR analyses. Furthermore, we chose breast/prostate cancer as outcome and four anthropometric traits as exposures as an illustrative example to illustrate the importance of taking sex heterogeneity of instruments into account in MR studies.

Results

The simulation definitively demonstrated that sex-combined IVs can lead to biased causal effect estimates in sex-specific two-sample MR studies. In our real applications, both LDSC and Pearson's correlation analyses showed high genetic correlation between sex-combined and sex-specific IVs of the four anthropometric traits, while nearly all the correlation coefficients were larger than zero but less than one. The Cochran's Q test also displayed sex heterogeneity for some instruments. When applying sex-specific instruments, significant discrepancies in the magnitude of estimated causal effects were detected for body mass index (BMI) on breast cancer (P = 1.63E-6), for hip circumference (HIP) on breast cancer (P = 1.25E-20), and for waist circumference (WC) on prostate cancer (P = 0.007) compared with those generated with sex-combined instruments.

Conclusion

Our study reveals that the sex instrumental heterogeneity has non-ignorable impact on sex-specific two-sample MR studies and the causal effects of anthropometric traits on breast/prostate cancer would be biased if sex-combined IVs are incorrectly employed.