Body mass index and type 2 diabetes and breast cancer survival: a Mendelian randomization study.
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ABSTRACT:
SUBMITTER: Liu YS
PROVIDER: S-EPMC8414374 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background:There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. Methods:We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results:BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01-1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89-1.13, P = 0.95). Conclusions:Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases.
| S-EPMC5837506 | biostudies-literature
Project description:BACKGROUND:High body mass index (BMI) is consistently linked to increased risk of colorectal cancer for men, whereas the association is less clear for women. As risk estimates from observational studies may be biased and/or confounded, we conducted a Mendelian randomization study to estimate the causal association between BMI and colorectal cancer. METHODS:We used data from 10,226 colorectal cancer cases and 10,286 controls of European ancestry. The Mendelian randomization analysis used a weighted genetic risk score, derived from 77 genome-wide association study-identified variants associated with higher BMI, as an instrumental variable (IV). We compared the IV odds ratio (IV-OR) with the OR obtained using a conventional covariate-adjusted analysis. RESULTS:Individuals carrying greater numbers of BMI-increasing alleles had higher colorectal cancer risk [per weighted allele OR, 1.31; 95% confidence interval (CI), 1.10-1.57]. Our IV estimation results support the hypothesis that genetically influenced BMI is directly associated with risk for colorectal cancer (IV-OR per 5 kg/m(2), 1.50; 95% CI, 1.13-2.01). In the sex-specific IV analyses higher BMI was associated with higher risk of colorectal cancer among women (IV-OR per 5 kg/m(2), 1.82; 95% CI, 1.26-2.61). For men, genetically influenced BMI was not associated with colorectal cancer (IV-OR per 5 kg/m(2), 1.18; 95% CI, 0.73-1.92). CONCLUSIONS:High BMI was associated with increased colorectal cancer risk for women. Whether abdominal obesity, rather than overall obesity, is a more important risk factor for men requires further investigation. IMPACT:Overall, conventional epidemiologic and Mendelian randomization studies suggest a strong association between obesity and the risk of colorectal cancer.
| S-EPMC4490960 | biostudies-literature
Project description:Traditional observational studies have reported a positive association between higher body mass index (BMI) and the risk of colorectal cancer (CRC). However, evidence from other approaches to pursue the causal relationship between BMI and CRC is sparse. A two-sample Mendelian randomization (MR) study was undertaken using 68 single nucleotide polymorphisms (SNPs) from the Japanese genome-wide association study (GWAS) and 654 SNPs from the GWAS catalogue for BMI as sets of instrumental variables. For the analysis of SNP-BMI associations, we undertook a meta-analysis with 36 303 participants in the Japanese Consortium of Genetic Epidemiology studies (J-CGE), comprising normal populations. For the analysis of SNP-CRC associations, we utilized 7636 CRC cases and 37 141 controls from five studies in Japan, and undertook a meta-analysis. Mendelian randomization analysis of inverse-variance weighted method indicated that a one-unit (kg/m2 ) increase in genetically predicted BMI was associated with an odds ratio of 1.13 (95% confidence interval, 1.06-1.20; P value <.001) for CRC using the set of 68 SNPs, and an odds ratio of 1.07 (1.03-1.11, 0.001) for CRC using the set of 654 SNPs. Sensitivity analyses robustly showed increased odds ratios for CRC for every one-unit increase in genetically predicted BMI. Our MR analyses strongly support the evidence that higher BMI influences the risk of CRC. Although Asians are generally leaner than Europeans and North Americans, avoiding higher BMI seems to be important for the prevention of CRC in Asian populations.
| S-EPMC8019210 | biostudies-literature
Project description:BACKGROUND:Evidence linking breast size to breast cancer risk has been inconsistent, and its interpretation is often hampered by confounding factors such as body mass index (BMI). Here, we used linkage disequilibrium score regression and two-sample Mendelian randomization (MR) to examine the genetic associations between BMI, breast size and breast cancer risk. METHODS:Summary-level genotype data from 23andMe, Inc (breast size, n = 33 790), the Breast Cancer Association Consortium (breast cancer risk, n = 228 951) and the Genetic Investigation of ANthropometric Traits (BMI, n = 183 507) were used for our analyses. In assessing causal relationships, four complementary MR techniques [inverse variance weighted (IVW), weighted median, weighted mode and MR-Egger regression] were used to test the robustness of the results. RESULTS:The genetic correlation (rg) estimated between BMI and breast size was high (rg = 0.50, P = 3.89x10-43). All MR methods provided consistent evidence that higher genetically predicted BMI was associated with larger breast size [odds ratio (ORIVW): 2.06 (1.80-2.35), P = 1.38x10-26] and lower overall breast cancer risk [ORIVW: 0.81 (0.74-0.89), P = 9.44x10-6]. No evidence of a relationship between genetically predicted breast size and breast cancer risk was found except when using the weighted median and weighted mode methods, and only with oestrogen receptor (ER)-negative risk. There was no evidence of reverse causality in any of the analyses conducted (P > 0.050). CONCLUSION:Our findings indicate a potential positive causal association between BMI and breast size and a potential negative causal association between BMI and breast cancer risk. We found no clear evidence for a direct relationship between breast size and breast cancer risk.
| S-EPMC6659372 | biostudies-literature
Project description:Obesity is a highly prevalent risk factor for cardiometabolic diseases. Observational studies suggest that obesity is associated with psychiatric traits, but causal inference from such studies has several limitations. We used two-sample Mendelian randomization methods (inverse variance weighting, weighted median and MR-Egger regression) to evaluate the association of body mass index (BMI) with three psychiatric traits using data from the Genetic Investigation of Anthropometric Traits and Psychiatric Genomics consortia. Causal odds ratio estimates per 1-standard deviation increment in BMI ranged from 0.88 (95% CI: 0.62; 1.25) to 1.23 (95% CI: 0.65; 2.31) for bipolar disorder; 0.93 (0.78; 1.11) to 1.41 (0.87; 2.27) for schizophrenia; and 1.15 (95% CI: 0.92; 1.44) to 1.40 (95% CI: 1.03; 1.90) for major depressive disorder. Analyses removing potentially influential SNPs suggested that the effect estimates for depression might be underestimated. Our findings do not support the notion that higher BMI increases risk of bipolar disorder and schizophrenia. Although the point estimates for depression were consistent in all sensitivity analyses, the overall statistical evidence was weak. However, the fact that SNP-depression associations were estimated in relatively small samples reduced power to detect causal effects. This should be re-addressed when SNP-depression associations from larger studies become available.
| S-EPMC5013405 | biostudies-literature
Project description:Introduction: High body mass index (BMI) is a positive associated phenotype of type 2 diabetes mellitus (T2DM). Abundant studies have observed this from a clinical perspective. Since the rapid increase in a large number of genetic variants from the genome-wide association studies (GWAS), common SNPs of BMI and T2DM were identified as the genetic basis for understanding their associations. Currently, their causality is beginning to blur. Materials and Methods: To classify it, a Mendelian randomisation (MR), using genetic instrumental variables (IVs) to explore the causality of intermediate phenotype and disease, was utilized here to test the effect of BMI on the risk of T2DM. In this article, MR was carried out on GWAS data using 52 independent BMI SNPs as IVs. The pooled odds ratio (OR) of these SNPs was calculated using inverse-variance weighted method for the assessment of 5 kg/m2 higher BMI on the risk of T2DM. The leave-one-out validation was conducted to identify the effect of individual SNPs. MR-Egger regression was utilized to detect potential pleiotropic bias of variants. Results: We obtained the high OR (1.470; 95% CI 1.170 to 1.847; P = 0.001), low intercept (0.004, P = 0.661), and small fluctuation of ORs {from -0.039 [(1.412 - 1.470) / 1.470)] to 0.075 [(1.568- 1.470) / 1.470)] in leave-one-out validation. Conclusion: We validate the causal effect of high BMI on the risk of T2DM. The low intercept shows no pleiotropic bias of IVs. The small alterations of ORs activated by removing individual SNPs showed no single SNP drives our estimate.
| S-EPMC6413727 | biostudies-literature
Project description:BackgroundLifestyle interventions to reduce body mass index (BMI) are critical public health strategies for type 2 diabetes prevention. While weight loss interventions have shown demonstrable benefit for high-risk and prediabetic individuals, we aimed to determine whether the same benefits apply to those at lower risk.Methods and findingsWe performed a multi-stratum Mendelian randomization study of the effect size of BMI on diabetes odds in 287,394 unrelated individuals of self-reported white British ancestry in the UK Biobank, who were recruited from across the United Kingdom from 2006 to 2010 when they were between the ages of 40 and 69 years. Individuals were stratified on the following diabetes risk factors: BMI, diabetes family history, and genome-wide diabetes polygenic risk score. The main outcome measure was the odds ratio of diabetes per 1-kg/m2 BMI reduction, in the full cohort and in each stratum. Diabetes prevalence increased sharply with BMI, family history of diabetes, and genetic risk. Conversely, predicted risk reduction from weight loss was strikingly similar across BMI and genetic risk categories. Weight loss was predicted to substantially reduce diabetes odds even among lower-risk individuals: for instance, a 1-kg/m2 BMI reduction was associated with a 1.37-fold reduction (95% CI 1.12-1.68) in diabetes odds among non-overweight individuals (BMI < 25 kg/m2) without a family history of diabetes, similar to that in obese individuals (BMI ≥ 30 kg/m2) with a family history (1.21-fold reduction, 95% CI 1.13-1.29). A key limitation of this analysis is that the BMI-altering DNA sequence polymorphisms it studies represent cumulative predisposition over an individual's entire lifetime, and may consequently incorrectly estimate the risk modification potential of weight loss interventions later in life.ConclusionsIn a population-scale cohort, lower BMI was consistently associated with reduced diabetes risk across BMI, family history, and genetic risk categories, suggesting all individuals can substantially reduce their diabetes risk through weight loss. Our results support the broad deployment of weight loss interventions to individuals at all levels of diabetes risk.
| S-EPMC6903707 | biostudies-literature
Project description:BackgroundObservational studies have reported a positive association between body mass index (BMI) and ovarian cancer risk. However, questions remain as to whether this represents a causal effect, or holds for all histological subtypes. The lack of association observed for serous cancers may, for instance, be due to disease-associated weight loss. Mendelian randomization (MR) uses genetic markers as proxies for risk factors to overcome limitations of observational studies. We used MR to elucidate the relationship between BMI and ovarian cancer, hypothesizing that genetically predicted BMI would be associated with increased risk of non-high grade serous ovarian cancers (non-HGSC) but not HGSC.MethodsWe pooled data from 39 studies (14 047 cases, 23 003 controls) in the Ovarian Cancer Association Consortium. We constructed a weighted genetic risk score (GRS, partial F-statistic = 172), summing alleles at 87 single nucleotide polymorphisms previously associated with BMI, weighting by their published strength of association with BMI. Applying two-stage predictor-substitution MR, we used logistic regression to estimate study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted BMI and risk, and pooled these using random-effects meta-analysis.ResultsHigher genetically predicted BMI was associated with increased risk of non-HGSC (pooled OR?=?1.29, 95% CI 1.03-1.61 per 5 units BMI) but not HGSC (pooled OR?=?1.06, 95% CI 0.88-1.27). Secondary analyses stratified by behaviour/subtype suggested that, consistent with observational data, the association was strongest for low-grade/borderline serous cancers (OR?=?1.93, 95% CI 1.33-2.81).ConclusionsOur data suggest that higher BMI increases risk of non-HGSC, but not the more common and aggressive HGSC subtype, confirming the observational evidence.
| S-EPMC5644573 | biostudies-literature
Project description:BACKGROUND:BRCA1/2 mutations confer high lifetime risk of breast cancer, although other factors may modify this risk. Whether height or body mass index (BMI) modifies breast cancer risk in BRCA1/2 mutation carriers remains unclear. METHODS:We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided. RESULTS:Observed height was positively associated with breast cancer risk (HR = 1.09 per 10?cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P?=?1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10?cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P?=?.47). Observed BMI was inversely associated with breast cancer risk (per 5?kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P?=?.007). BMI genetic score was also inversely associated with breast cancer risk (per 5?kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P?=?.02). BMI was primarily associated with premenopausal breast cancer. CONCLUSION:Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.
| S-EPMC6449171 | biostudies-literature
Project description:BACKGROUND:Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. METHODS:We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases? = ?46,325, controls? = ?42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. RESULTS:In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]? = ?0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32?×?10-10). The associations were similar for both premenopausal (OR?? = ??0.44, 95% CI:0.31-0.62, p? = ?9.91?×?10-8) and postmenopausal breast cancer (OR? = ?0.57, 95%?CI: 0.46-0.71, p? = ?1.88?×?10-8). This association was replicated in the data from the DRIVE consortium (OR? = ?0.72, 95%?CI: 0.60-0.84, p?? = ??1.64?×?10-7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p?<?0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. CONCLUSIONS:BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.
| S-EPMC4995025 | biostudies-literature