Mendelian randomisation: A powerful and inexpensive method for identifying and excluding non-genetic risk factors for colorectal cancer.
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ABSTRACT:
SUBMITTER: Cornish AJ
PROVIDER: S-EPMC6856712 | biostudies-literature | 2019 Oct
REPOSITORIES: biostudies-literature
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Project description:Mendelian randomisation (MR) analysis is an important tool to elucidate the causal relevance of environmental and biological risk factors for disease. However, causal inference is undermined if genetic variants used to instrument a risk factor also influence alternative disease-pathways (horizontal pleiotropy). Here we report how the 'no horizontal pleiotropy assumption' is strengthened when proteins are the risk factors of interest. Proteins are typically the proximal effectors of biological processes encoded in the genome. Moreover, proteins are the targets of most medicines, so MR studies of drug targets are becoming a fundamental tool in drug development. To enable such studies, we introduce a mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. We illustrate key model decisions and introduce an analytical framework for maximising power and evaluating the robustness of analyses.
| S-EPMC7320010 | biostudies-literature
Project description:BackgroundEpidemiological studies have linked lifestyle, cardiometabolic, reproductive, developmental, and inflammatory factors to the risk of colorectal cancer. However, which specific factors affect risk and the strength of these effects are unknown. We aimed to examine the relationship between potentially modifiable risk factors and colorectal cancer.MethodsWe used a random-effects model to examine the relationship between 39 potentially modifiable risk factors and colorectal cancer in 26 397 patients with colorectal cancer and 41 481 controls (ie, people without colorectal cancer). These population data came from a genome-wide association study of people of European ancestry, which was amended to exclude UK BioBank data. In the model, we used genetic variants as instruments via two-sample mendelian randomisation to limit bias from confounding and reverse causation. We calculated odds ratios per genetically predicted SD unit increase in each putative risk factor (ORSD) for colorectal cancer risk. We did mendelian randomisation Egger regressions to identify evidence of potential violations of mendelian randomisation assumptions. A Bonferroni-corrected threshold of p=1·3 × 10-3 was considered significant, and p values less than 0·05 were considered to be suggestive of an association.FindingsNo putative risk factors were significantly associated with colorectal cancer risk after correction for multiple testing. However, suggestive associations with increased risk were noted for genetically predicted body fat percentage (ORSD 1·14 [95% CI 1·03-1·25]; p=0·0086), body-mass index (1·09 [1·01-1·17]; p=0·023), waist circumference (1·13 [1·02-1·26]; p=0·018), basal metabolic rate (1·10 [1·03-1·18]; p=0·0079), and concentrations of LDL cholesterol (1·14 [1·04-1·25]; p=0·0056), total cholesterol (1·09 [1·01-1·18]; p=0·025), circulating serum iron (1·17 [1·00-1·36]; p=0·049), and serum vitamin B12 (1·21 [1·04-1·42]; p=0·016), although potential pleiotropy among genetic variants used as instruments for vitamin B12 constrains the finding. A suggestive association was also noted between adult height and increased risk of colorectal cancer (ORSD 1·04 [95% CI 1·00-1·08]; p=0·032). Low blood selenium concentration had a suggestive association with decreased risk of colorectal cancer (ORSD 0·85 [95% CI 0·75-0·96]; p=0·0078) based on a single variant, as did plasma concentrations of interleukin-6 receptor subunit α (also based on a single variant; 0·98 [0·96-1·00]; p=0·035). Risk of colorectal cancer was not associated with any sex hormone or reproductive factor, serum calcium, or circulating 25-hydroxyvitamin D concentrations.InterpretationThis analysis identified several modifiable targets for primary prevention of colorectal cancer, including lifestyle, obesity, and cardiometabolic factors, that should inform public health policy.FundingCancer Research UK, UK Medical Research Council Human Genetics Unit Centre, DJ Fielding Medical Research Trust, EU COST Action, and the US National Cancer Institute.
| S-EPMC7026696 | biostudies-literature
Project description:BackgroundUnderstanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention.MethodsWe investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets.FindingsWe identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions.InterpretationOur findings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.FundingThis work was supported by Cancer Research UK (grant no. C8221/A29017).
| S-EPMC11233900 | biostudies-literature
Project description:While elevated blood cholesterol has been associated with an increased risk of colorectal cancer (CRC) in observational studies, causality is uncertain. Here we apply a Mendelian randomisation (MR) analysis to examine the potential causal relationship between lipid traits and CRC risk. We used single nucleotide polymorphisms (SNPs) associated with blood levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) as instrumental variables (IV). We calculated MR estimates for each risk factor with CRC using SNP-CRC associations from 9,254 cases and 18,386 controls. Genetically predicted higher TC was associated with an elevated risk of CRC (odds ratios (OR) per unit SD increase?=?1.46, 95% confidence interval [CI]: 1.20-1.79, p = 1.68 × 10-4 ). The pooled ORs for LDL, HDL, and TG were 1.05 (95% CI: 0.92-1.18, p = 0.49), 0.94 (95% CI: 0.84-1.05, p = 0.27), and 0.98 (95% CI: 0.85-1.12, p = 0.75) respectively. A genetic risk score for 3-hydoxy-3-methylglutaryl-coenzyme A reductase (HMGCR) to mimic the effects of statin therapy was associated with a reduced CRC risk (OR?=?0.69, 95% CI: 0.49-0.99, p = 0.046). This study supports a causal relationship between higher levels of TC with CRC risk, and a further rationale for implementing public health strategies to reduce the prevalence of hyperlipidaemia.
| S-EPMC6135234 | biostudies-literature
Project description:Mendelian randomisation studies from Asia suggest detrimental influences of alcohol on cardiovascular risk factors, but such associations are observed mainly in men. The absence of associations of genetic variants (e.g. rs671 in ALDH2) with such risk factors in women - who drank little in these populations - provides evidence that the observations are not due to genetic pleiotropy. Here, we present a Mendelian randomisation study in a South Korean population (3,365 men and 3,787 women) that 1) provides robust evidence that alcohol consumption adversely affects several cardiovascular disease risk factors, including blood pressure, waist to hip ratio, fasting blood glucose and triglyceride levels. Alcohol also increases HDL cholesterol and lowers LDL cholesterol. Our study also 2) replicates sex differences in associations which suggests pleiotropy does not underlie the associations, 3) provides further evidence that association is not due to pleiotropy by showing null effects in male non-drinkers, and 4) illustrates a way to measure population-level association where alcohol intake is stratified by sex. In conclusion, population-level instrumental variable estimation (utilizing interaction of rs671 in ALDH2 and sex as an instrument) strengthens causal inference regarding the largely adverse influence of alcohol intake on cardiovascular health in an Asian population.
| S-EPMC4685310 | biostudies-literature
Project description:BackgroundWomen's reproductive factors include their age at menarche and menopause, the age at which they start and stop having children and the number of children they have. Studies that have linked these factors with disease risk have largely investigated individual reproductive factors and have not considered the genetic correlation and total interplay that may occur between them. This study aimed to investigate the nature of the relationships between eight female reproductive factors.MethodsWe used data from the UK Biobank and genetic consortia with data available for the following reproductive factors: age at menarche, age at menopause, age at first birth, age at last birth, number of births, being parous, age first had sexual intercourse and lifetime number of sexual partners. Linkage disequilibrium score regression (LDSC) was performed to investigate the genetic correlation between reproductive factors. We then applied Mendelian randomisation (MR) methods to estimate the causal relationships between these factors. Sensitivity analyses were used to investigate directionality of the effects, test for evidence of pleiotropy and account for sample overlap.ResultsLDSC indicated that most reproductive factors are genetically correlated (rg range: |0.06-0.94|), though there was little evidence for genetic correlations between lifetime number of sexual partners and age at last birth, number of births and ever being parous (rg < 0.01). MR revealed potential causal relationships between many reproductive factors, including later age at menarche (1 SD increase) leading to a later age at first sexual intercourse (beta (B) = 0.09 SD, 95% confidence intervals (CI) = 0.06,0.11), age at first birth (B = 0.07 SD, CI = 0.04,0.10), age at last birth (B = 0.06 SD, CI = 0.04,0.09) and age at menopause (B = 0.06 SD, CI = 0.03,0.10). Later age at first birth was found to lead to a later age at menopause (B = 0.21 SD, CI = 0.13,0.29), age at last birth (B = 0.72 SD, CI = 0.67, 0.77) and a lower number of births (B = -0.38 SD, CI = -0.44, -0.32).ConclusionThis study presents evidence that women's reproductive factors are genetically correlated and causally related. Future studies examining the health sequelae of reproductive factors should consider a woman's entire reproductive history, including the causal interplay between reproductive factors.
| S-EPMC8944090 | biostudies-literature
Project description:BackgroundOnly a few of the 34 biochemical biomarkers measured in the UK Biobank (UKB) have been associated with breast cancer, with many associations suffering from possible confounding and reverse causation. This study aimed to screen and rank all UKB biochemical biomarkers for possible causal relationships with breast cancer.MethodsWe conducted two-sample Mendelian randomisation (MR) analyses on ~420,000 women by leveraging summary-level genetic exposure associations from the UKB study (n = 194,174) and summary-level genetic outcome associations from the Breast Cancer Association Consortium (n = 228,951). Our exposures included all 34 biochemical biomarkers in the UKB, and our outcomes were overall, oestrogen-positive, and oestrogen-negative breast cancer. We performed inverse-variance weighted MR, weighted median MR, MR-Egger, and MR-PRESSO for 30 biomarkers for which we found multiple instrumental variables. We additionally performed multivariable MR to adjust for known risk factors, bidirectional MR to investigate reverse causation, and MR Bayesian model averaging to rank the significant biomarkers by their genetic evidence.ResultsIncreased genetic liability to overall breast cancer was robustly associated with the following biomarkers by decreasing importance: testosterone (odds ratio (OR): 1.12, 95% confidence interval (CI): 1.04-1.21), high-density lipoprotein (HDL) cholesterol (OR: 1.08, 95% CI: 1.04-1.13), insulin-like growth factor 1 (OR: 1.08, 95% CI: 1.02-1.13), and alkaline phosphatase (ALP) (OR: 0.93, 95% CI: 0.89-0.98).ConclusionsOur findings support a likely causal role of genetically predicted levels of testosterone, HDL cholesterol, and IGF-1, as well as a novel potential role of ALP in breast cancer aetiology. Further studies are needed to understand full disease pathways that may inform breast cancer prevention.
| S-EPMC9685978 | biostudies-literature
Project description:BackgroundObservational studies have associated adiposity with an increased risk of colorectal cancer (CRC). However, such studies do not establish a causal relationship. To minimise bias from confounding we performed a Mendelian randomisation (MR) analysis to examine the relationship between adiposity and CRC.MethodsWe used SNPs associated with adult body mass index (BMI), waist-hip ratio (WHR), childhood obesity and birth weight as instrumental variables in a MR analysis of 9254 CRC cases and 18 386 controls.ResultsIn the MR analysis, the odds ratios (ORs) of CRC risk per unit increase in BMI, WHR and childhood obesity were 1.23 (95% CI: 1.02-1.49, P=0.033), 1.59 (95% CI: 1.08-2.34, P=0.019) and 1.07 (95% CI: 1.03-1.13, P=0.018), respectively. There was no evidence for association between birth weight and CRC (OR=1.22, 95% CI: 0.89-1.67, P=0.22). Combining these data with a concurrent MR-based analysis for BMI and WHR with CRC risk (totalling to 18 190 cases, 27 617 controls) provided increased support, ORs for BMI and WHR were 1.26 (95% CI: 1.10-1.44, P=7.7 × 10(-4)) and 1.40 (95% CI: 1.14-1.72, P=1.2 × 10(-3)), respectively.ConclusionsThese data provide further evidence for a strong causal relationship between adiposity and the risk of developing CRC highlighting the urgent need for prevention and treatment of adiposity.
| S-EPMC4947703 | biostudies-literature
Project description:This review explores the criteria used for the selection of genetic instruments of sleep traits in the context of Mendelian randomisation studies. This work was motivated by the fact that instrument selection is the most important decision when designing a Mendelian randomisation study. As far as we are aware, no review has sought to address this to date, even though the number of these studies is growing rapidly. The review is divided into the following sections which are essential for genetic instrument selection: 1) Single-gene region vs polygenic analysis; 2) Polygenic analysis: biologically-vs statistically-driven approaches; 3) P-value; 4) Linkage disequilibrium clumping; 5) Sample overlap; 6) Type of exposure; 7) Total (R2) and average strength (F-statistic) metrics; 8) Number of single-nucleotide polymorphisms; 9) Minor allele frequency and palindromic variants; 10) Confounding. Our main aim is to discuss how instrumental choice impacts analysis and compare the strategies that Mendelian randomisation studies of sleep traits have used. We hope that our review will enable more researchers to take a more considered approach when selecting genetic instruments for sleep exposures.
| S-EPMC7615498 | biostudies-literature
Project description:Physical activity has been associated with lower risks of breast and colorectal cancer in epidemiological studies; however, it is unknown if these associations are causal or confounded. In two-sample Mendelian randomisation analyses, using summary genetic data from the UK Biobank and GWA consortia, we found that a one standard deviation increment in average acceleration was associated with lower risks of breast cancer (odds ratio [OR]: 0.51, 95% confidence interval [CI]: 0.27 to 0.98, P-value = 0.04) and colorectal cancer (OR: 0.66, 95% CI: 0.48 to 0.90, P-value = 0.01). We found similar magnitude inverse associations for estrogen positive (ER+ve) breast cancer and for colon cancer. Our results support a potentially causal relationship between higher physical activity levels and lower risks of breast cancer and colorectal cancer. Based on these data, the promotion of physical activity is probably an effective strategy in the primary prevention of these commonly diagnosed cancers.
| S-EPMC6992637 | biostudies-literature