Investigating the Causal Relationship Between Physical Activity and Chronic Back Pain: A Bidirectional Two-Sample Mendelian Randomization Study

Background: Recent observational studies have reported a negative association between physical activity and chronic back pain (CBP), but the causality of the association remains unknown. We introduce bidirectional Mendelian randomization (MR) to assess potential causal inference between physical activity and CBP.Materials and Methods: This two-sample MR used independent genetic variants associated with physical activity and CBP as genetic instruments from large genome-wide association studies (GWASs). The effects of both directions (physical activity to CBP and CBP to physical activity) were examined. Inverse variance-weighted meta-analysis and alternate methods (weighted median and MR-Egger) were used to combine the MR estimates of the genetic instruments. Multiple sensitivity analyses were conducted to examine the robustness of the results.Results: The MR set parallel GWAS cohorts, among which, those involved in the primary analysis were comprised of 337,234 participants for physical activity and 158,025 participants (29,531 cases) for CBP. No evidence of a causal relationship was found in the direction of physical activity to CBP [odds ratio (OR), 0.98; 95% CI, 0.85–1.13; p = 0.81]. In contrast, a negative causal relationship in the direction of CBP to physical activity was detected (β = −0.07; 95% CI, −0.12 to −0.01; p = 0.02), implying a reduction in moderate-vigorous physical activity (approximately 146 MET-minutes/week) for participants with CBP relative to controls.Conclusion: The negative relationship between physical activity and CBP is probably derived from the reduced physical activity of patients experiencing CBP rather than the protective effect of physical activity on CBP.

Evaluating and implementing block jackknife resampling Mendelian randomization to mitigate bias induced by overlapping samples

Participant overlap has been thought to induce overfitting bias into Mendelian randomization (MR) and polygenic risk score (PRS) studies. This hinders the potential research into many unique traits and disease outcomes from large-scale biobanks. Here, we evaluated a block jackknife resampling framework for genome-wide association studies (GWAS) and PRS construction to mitigate the influence of overfitting bias on MR analyses compared to alternative approaches and implemented this study design in causal inference setting using data from the UK Biobank.We simulated PRS and MR under three scenarios: (1) using weighted SNP estimates from an external GWAS, (2) using weighted SNP estimates from an overlapping GWAS sample and (3) using a block jackknife resampling framework. Based on a conventional P-value threshold to derive genetic instruments for MR studies (P<5×10−8), our block-jackknifing PRS did not suffer from overfitting bias (mean R2=0.034) compared to the externally weighted PRS (mean R2=0.040). In contrast, genetic instruments derived from overlapping samples explained a higher proportion of variance (mean R2=0.048) compared to the externally derived score. The detrimental impact of overfitting bias became considerably larger when using a more liberal P-value threshold to construct PRS (e.g., P<0.05, mean R2=0.103), whereas estimates using jackknife score remained robust to overfitting (mean R2=0.084).In an applied setting, we examined (A) the effects of body mass index on circulating biomarkers and (B) the effect of childhood body size on levels of testosterone in adulthood using methods described above. In the first applied analysis, overlapping sample PRS and block jackknife resampled PRS led to comparable effect sizes, whereas narrower confidence intervals were identified when using the overlapping sample instrument. In the second example, through sex-stratified multivariable and bi-directional MR, we demonstrate that childhood body size indirectly leads to lower testosterone levels in adulthood in males, an effect mediated through adult body size.Author summaryUsing genetic variants as instrumental variables for risk factors, Mendelian randomization (MR) provides an approach to explore the genetically predicted effects of modifiable risk factors on disease which is robust to confounding and reverse causation. Genetic instrumental variables are conventionally selected from results of genome-wide association studies on an independent dataset whose sample does not overlap with the dataset being analysed using MR analysis, as this can lead to overfitting bias. This can often be challenging to entirely avoid however, as such association studies are increasingly being performed by meta-analysing several biobanks to achieve the maximum power to detect variants with smaller effect sizes. Moreover, when investigating exposures and outcomes which only a single biobank has measured in sufficiently large samples, avoiding participant overlap requires splitting the study population into subgroups which can limit statistical power. Block jackknife resampling MR provides a solution to conduct causal inference under these circumstances with the maximum statistical power while avoiding bias due to overlapping participants. In this study, we evaluated this study design with simulated dataset in comparison to MR using genetic variants discovered from an external dataset or one with overlapping samples. We applied this approach using UK Biobank to investigate the role of body mass index on circulating biomarkers, as well as the causal relationship between childhood adiposity and testosterone levels in adulthood.

Differential Sleep Traits Have No Causal Effect on Inflammatory Bowel Diseases: A Mendelian Randomization Study

Background: Previous studies suggested an association of sleep disorders with inflammatory bowel disease (IBD) and indicated that using pharmacological treatments for the modulation of circadian rhythms might prevent IBD pathogenesis or aggravation, but whether the effect of sleep traits on IBD was causal is inconclusive and, therefore, prevents drug repurposing based on the previous studies. We aimed to examine the causal effect of different sleep traits on the pathogenesis of IBD.Methods: Genetic instruments for sleep traits were selected from the largest GWAS studies available in the UK Biobank (n = 449,734) and the 23andMe Research (n = 541,333). A two-sample Mendelian randomization (MR) study was conducted to examine the association of the genetic instruments with IBD (12,882 cases and 21,770 controls), ulcerative colitis (6,968 cases, 20,464 controls), and Crohn’s disease (5,956 cases and 14,927 controls). We applied the inverse-variance weighted (IVW) method to estimate causal effects, and we used the weighted median and MR-Egger method for sensitivity analyses.Results: We found that sleep duration (OR, 1.00, 95% CI 1.00–1.01), short sleep duration (OR, 1.07, 95% CI 0.41–2.83), morningness (OR, 1.05, 95% CI 0.87–1.27), daytime napping (OR, 1.64, 95% CI 0.62–4.4), frequent insomnia (OR, 1.17, 95% CI 0.8–1.72), any insomnia (OR, 1.17, 95% CI 0.69–1.97), and snoring (OR, 0.31, 95% CI 0.06–1.54) had no causal effect on IBD, and these sleep traits had no causal effect on ulcerative colitis and Crohn’s disease either. Most of the sensitivity analyses showed consistent results with those of the IVW method.Conclusion: Our MR study did not support the causal effect of sleep traits on IBD. Pharmacological modulation of circadian rhythms for the prevention of IBD pathogenesis was unwarranted.

Maternal polycystic ovary syndrome and offspring birth weight: a Mendelian randomization study

Background Observational associations between maternal polycystic ovary syndrome (PCOS) and offspring birth weight (BW) have been inconsistent and the causal relationship is still uncertain. Objective We conducted a two-sample Mendelian randomization (MR) study to estimate the causal effect of maternal PCOS on offspring BW. Methods We constructed genetic instruments for PCOS with 14 single nucleotide polymorphisms (SNPs) which were identified in the genome-wide association study (GWAS) meta-analysis including 10,074 PCOS cases and 103,164 controls of European ancestry from seven cohorts. The genetic associations of these SNPs with the offspring BW were extracted from summary statistics estimated by the Early Growth Genetics (EGG) consortium (n = 406,063 European-ancestry individuals) using the weighted linear model (WLM), an approximation method of structural equation model (SEM), which separated maternal genetic effects from fetal genetic effects. We used a two-sample MR design to examine the causal relationship between maternal PCOS and offspring BW. Sensitivity analyses were conducted to assess the robustness of the MR results. Results We found little evidence for a causal effect of maternal PCOS on offspring BW (-6.1 g, 95% confidence interval [CI]: -16.8 g, 4.6 g). Broadly consistent results were found in the sensitivity analyses. Conclusion Despite the large scale of this study, our results suggested little causal effect of maternal PCOS on offspring BW. MR studies with a larger sample size of women with PCOS or more genetic instruments that would increase the variation of PCOS explained are needed in the future.

Causal Association of Coffee Consumption and Total, Knee, Hip and Self-Reported Osteoarthritis: A Mendelian Randomization Study

BackgroundThe causal association between coffee consumption and the risk of OA is limited. This study was conducted to identify the potential causal effects of coffee consumption on total, knee, hip, and self-reported OA.MethodsGenome-wide association studies (GWAS) of OA were derived from the UK Biobank, comprising 50,508 participants of European ancestry (10,083 with cases and 40,425 controls), and genetic data for specific diagnosed knee OA (4462 cases and 17,885 controls), hip OA (12,625 cases and 50,898 controls), and self-reported OA (12,658 cases and 50,898 controls). Primary and secondary genetic instruments (11 SNPs and 8 SNPs) were selected as instrumental variants from GWAS among 375,833 and 91,462 participants. Two-sample Mendelian randomization (MR) analyses were performed to test the effects of the selected single nucleotide polymorphisms (SNPs) and the OA risk. The causal effects were primarily estimated using weighted median and inverse-variance weighted method with several sensitivity analyses.ResultsThe MR analyses suggested that genetically predicted 1% increase of coffee consumption was associated with an increased risk of overall OA (OR:1.009, 95% CI:1.003-1.016), knee OA (OR:1.023, 95% CI:1.009-1.038), self-reported OA (OR:1.007, 95% CI:1.003-1.011), but not hip OA (OR: 1.012, 95%CI:0.999-1.024) using primary genetic instruments. Similar results were found when using secondary genetic instruments that genetically predicted coffee consumption (cups/day). Additionally, the sensitivity analyses for leave-one-out methods supported a robust association between exposure traits and OA.ConclusionOur findings indicate that genetically predicted coffee consumption exerts a causal effect on total, knee, and self-reported OA risk, but not at the hip. Further research is required to unravel the role of coffee consumption in OA prevention.

Sex steroid hormones and risk of breast cancer incidence and survival: A two-sample Mendelian randomization study

Background Breast cancer (BC) is the cancer with the highest incidence and mortality in women worldwide. Observational epidemiological studies suggest a positive association between testosterone, estradiol, dehydroepiandrosterone sulphate (DHEAS) and both pre- and post-menopausal BC. Since previous studies may be prone to bias and confounding, we used a two-sample Mendelian randomization (MR) analysis to investigate this association. Methods Genetic instruments for nine sex steroid hormones and sex hormone binding globulin (SHBG) were obtained from genome-wide association studies (GWAS) conducted in the UK Biobank (total testosterone (TT) N:230,454, bioavailable testosterone (BT) N: 188,507 and SHBG N: 189,473), The United Kingdom Household Longitudinal Study (DHEAS N: 9,722), the LIFE-Adult and LIFE-Heart cohorts (estradiol N: 2,607), the LIFE-Heart cohort only (androstenedione N: 711, aldosterone N: 685, progesterone N: 1,259 and 17-hydroxyprogesterone N: 711) and the CORtisol NETwork (CORNET) consortium (cortisol N: 25,314). GWAS summary statistics were also obtained from the Breast Cancer Association Consortium (BCAC) for overall BC risk (N: 122,977 cases and 105,974 controls) and BC mortality (96,661 BC cases and 7,697 BC-specific deaths). Subtype specific analysis were carried out for incidence of estrogen receptor (ER)+ BC, ER- BC, luminal A-like BC, luminal B-like BC, luminal B/HER2-negative-like BC, HER2-enriched-like BC, triple negative BC (TNBC) and BRCA1 mutated TNBC. Results Using an inverse-variance weighted (IVW) approach, we found that a standard deviation (SD) increase in TT, BT and estradiol increased the risk of overall BC (OR: 1.14, 95% CI: 1.09-1.21, OR: 1.19, 95% CI: 1.07-1.33 and OR: 1.03, 95% CI: 1.01-1.06, respectively) and ER+ BC (OR: 1.19, 95% CI: 1.12-1.27, OR: 1.25, 95% CI: 1.11-1.40 and OR: 1.06, 95% CI: 1.03-1.09, respectively). A SD increase in DHEAS also increased ER+ BC risk (OR: 1.09, 95% CI: 1.03-1.09). Subtype specific analyses showed similar associations with ER+ expressing subtypes: luminal A-like BC, luminal B-like BC and luminal B/HER2-negative-like BC. A SD increase in cortisol was associated with poor survival after a diagnosis of ER- BC (HR: 2.35, 95% CI: 1.00-5.49). Discussion/Conclusion TT, BT, DHEAS and estradiol increase the risk of ER+ type BCs similar to observational studies, but none of these hormone measures are associated with BC survival. We found some evidence that cortisol reduced ER- BC survival. Stronger genetic instruments are required before definitive conclusions can be made about the role of other sex-steroid hormones in breast cancer. Understanding the role of sex steroid hormones in BC risk, particularly subtype-specific risks, highlights the potential importance of attempts to modify and/or monitor hormone levels in order to prevent BC.

Suggestive Evidence for Causal Effect of Leptin Levels on Risk for Anorexia Nervosa: Results of a Mendelian Randomization Study

Genetic correlations suggest a coexisting genetic predisposition to both low leptin levels and risk for anorexia nervosa (AN). To investigate the causality and direction of these associations, we performed bidirectional two-sample Mendelian randomization (MR) analyses using data of the most recent genome-wide association study (GWAS) for AN and both a GWAS and an exome-wide-association-study (EWAS) for leptin levels. Most MR methods with genetic instruments from GWAS showed a causal effect of lower leptin levels on higher risk of AN (e.g. IVW b = −0.923, p = 1.5 × 10−4). Because most patients with AN are female, we additionally performed analyses using leptin GWAS data of females only. Again, there was a significant effect of leptin levels on the risk of AN (e.g. IVW b = −0.826, p = 1.1 × 10−04). MR with genetic instruments from EWAS showed no overall effect of leptin levels on the risk for AN. For the opposite direction, MR revealed no causal effect of AN on leptin levels. If our results are confirmed in extended GWAS data sets, a low endogenous leptin synthesis represents a risk factor for developing AN.

Investigating the causal relationship between physical activity and chronic back pain: a bidirectional two-sample Mendelian randomization study

Background Recent observational studies have reported a negative association between physical activity and chronic back pain (CBP), but the causality of the association remains unknown. We introduce bidirectional Mendelian randomization (MR) to assess potential causal inference between physical activity and CBP. Methods The two-sample MR was used with independent genetic variants associated with physical activity phenotypes and CBP as genetic instruments from large genome-wide association studies (GWASs) on individuals of European ancestry. The effects of both directions (physical activity to CBP and CBP to physical activity) were examined. Inverse variance-weighted meta-analysis and alternate methods (weighted median and MR-Egger) were used to combine the MR estimates of the genetic instruments. Multiple sensitivity analyses were conducted to examine the robustness of the results. Results For primary analysis, instrumental variables were extracted from 337,234 participants for physical activity (the same as the outcome cohort) and 158,025 participants (29,531 cases) for CBP, while the outcome cohort for CBP included 117,404 participants (80,588 cases). No evidence of a causal relationship was found in the direction of physical activity to CBP (odds ratio [OR], 0.98; 95% CI, 0.85-1.13; P = 0.81). In contrast, a negative causal relationship in the direction of CBP to physical activity was detected (β = -0.07; 95% CI, -0.12 to -0.01; P = 0.02), implying a reduction in moderate-vigorous physical activity (approximately 146 MET-minutes/week) for participants with CBP relative to controls. Conclusions The negative relationship between physical activity and CBP is probably derived from the reduced physical activity of patients experiencing CBP rather than the protective effect of physical activity on CBP.

The Relationship Between Glycaemia, Cognitive Function, Structural Brain Outcomes and Dementia: A Mendelian Randomization Study in the UK Biobank

We investigated the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR). Data were from UK Biobank (n~500,000). Our exposures were genetic instruments for type-2 diabetes (157 variants) and HbA_1c(51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal and white matter hyperintensity volumes, Alzheimer’s dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and, diabetes and HbA_1c. We used conventional inverse-variance weighted (IVW) MR, alongside MR sensitivity analyses. Using IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (WMHV) (expß=0.99, 95%CI=0.97; 1.01), hippocampal volume (HV) (ß coefficient mm³=4.56, 95%CI=-3.98; 13.09) or AD (OR 0.89, 95%CI=0.78; 1.01). HbA_1cwas not associated with RT (expß=1.01, 95%CI=1.00; 1.01), WMHV (expß=0.94, 95%CI=0.81; 1.08), HV (ß=7.21, 95%CI=-54.06; 68.48), or risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA_1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median. IVW showed that reaction time was not associated with diabetes risk (OR 0.96, 95%CI=0.63; 1.46) or with HbA_1c(ß coefficient mmol/mol=-0.08, 95%CI=-0.57; 0.42). Overall, we observed little evidence of causal association between genetic instruments for T2D or peripheral glycaemia and some measures of cognition and brain structure in midlife.

Coffee Consumption and Prostate Cancer Risk: Results from National Health and Nutrition Examination Survey 1999–2010 and Mendelian Randomization Analyses

The aim of this study was to examine the association between coffee and prostate cancer. Firstly, we conducted an observational study using data from National Health and Nutrition Examination Survey (NHANES) 1999–2010. Coffee intake was derived from 24 h dietary recalls. Weighted multivariable-adjusted logistic regression was applied to evaluate the association. Then, we performed Mendelian randomization (MR) to explore the possible causal effect of coffee on prostate cancer risk. Primary and secondary genetic instruments were obtained from genome-wide association studies among 375,833 and 91,462 individuals separately. Prostate cancer summary statistics were extracted from Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) (79,194 cases and 61,112 controls) and FinnGen project (4754 cases and 63,465 controls). Inverse variance weighted (IVW) was the primary analytical method. Through selection, we enrolled 8336 individuals (weighted number = 58,796,070) for our observational study in NHANES. Results suggested that there was no association between coffee and prostate cancer. MR analyses with primary genetic instruments also did not support a causal association between coffee intake and prostate cancer risk, whether using summary data from PRACTICAL (IVW: OR 1.001, 95% CI 0.997–1.005) or FinnGen (IVW: OR 1.005, 95% CI 0.998–1.012). Similar results were observed when using secondary genetic instruments. Therefore, our study did not support a causal association between coffee intake and prostate cancer risk. Further studies with a larger sample size are needed to examine if an association exists by different coffee bean types, roasting procedures, and brewing methods.