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The incidence of early-onset colorectal cancer (EOCRC; diagnosed <50 years of age) is rising globally; however, the causes underlying this trend are largely unknown. CRC has strong genetic and environmental determinants, yet common genetic variants and causal modifiable risk factors underlying EOCRC are unknown. We conducted the first EOCRC-specific genome-wide association study (GWAS) and Mendelian randomization (MR) analyses to explore germline genetic and causal modifiable risk factors associated with EOCRC. We conducted a GWAS meta-analysis of 6176 EOCRC cases and 65 829 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colorectal Transdisciplinary Study (CORECT), the Colon Cancer Family Registry (CCFR), and the UK Biobank. We then used the EOCRC GWAS to investigate 28 modifiable risk factors using two-sample MR. We found two novel risk loci for EOCRC at 1p34.1 and 4p15.33, which were not previously associated with CRC risk. We identified a deleterious coding variant (rs36053993, G396D) at polyposis-associated DNA repair gene MUTYH (odds ratio 1.80, 95% confidence interval 1.47-2.22) but show that most of the common genetic susceptibility was from noncoding signals enriched in epigenetic markers present in gastrointestinal tract cells. We identified new EOCRC-susceptibility genes, and in addition to pathways such as transforming growth factor (TGF) β, suppressor of Mothers Against Decapentaplegic (SMAD), bone morphogenetic protein (BMP) and phosphatidylinositol kinase (PI3K) signaling, our study highlights a role for insulin signaling and immune/infection-related pathways in EOCRC. In our MR analyses, we found novel evidence of probable causal associations for higher levels of body size and metabolic factors—such as body fat percentage, waist circumference, waist-to-hip ratio, basal metabolic rate, and fasting insulin—higher alcohol drinking, and lower education attainment with increased EOCRC risk. Our novel findings indicate inherited susceptibility to EOCRC and suggest modifiable lifestyle and metabolic targets that could also be used to risk-stratify individuals for personalized screening strategies or other interventions. • We conducted GWAS and MR analyses to identify the causes of EOCRC. • We identified two novel risk loci specific to EOCRC and confirmed the involvement of several known CRC risk variants in EOCRC. • We also identified new EOCRC risk genes and highlighted the prominent role of pathways such as insulin signaling in EOCRC. • We identified probable causal associations for body size, fasting insulin, alcohol intake, and educational level with EOCRC. [ABSTRACT FROM AUTHOR]

Background: In this study we used Mendelian randomization (MR) to investigate the potential causal association of lipoprotein (a) [Lp(a)] levels with pulse wave velocity (PWV). Methods: Genetic variants associated with Lp(a) were retrieved from the UK Biobank GWAS (N = 290,497). A non‐ overlapping GWAS based on a European cohort (N = 7,000) was used to obtain genetic associations with PWV (outcome) and utilized two different measures for the same trait, brachial–ankle (baPWV) and carotid–femoral (cfPWV) PWV. We applied a two‐sample MR using the inverse variance weighting method (IVW) and a series of sensitivity analyses for 170 SNPs that were selected as instrumental variables (IVs). Results: Our analyses do not support a causal association between Lp(a) and PWV for neither measurement [βiwv(baPWV) = −.0005, p =.8 and βiwv(cfPWV) = −.006, p =.16]. The above findings were consistent across sensitivity analyses including weighted median, mode‐based estimation, MR‐Egger regression and MR‐PRESSO. Conclusion: We did not find evidence indicating that Lp(a) is causally associated with PWV, the gold standard marker of arterial stiffness. [ABSTRACT FROM AUTHOR]

Background: The association between major depressive disorder (MDD) and irritable bowel syndrome (IBS) has been found in observational research; however, the causative relationship between MDD and IBS remains uncertain. Using the two‐sample Mendelian randomization (MR) approach, we attempted to examine the causal effect of MDD on IBS. Methods: Independent genetic variants for MDD identified by Howard et al. based on a genome‐wide meta‐analysis were selected for this study. Gene‐Outcome associations for IBS were gathered from UK Biobank and FinnGen databases. The MR analysis included inverse variance weighted (IVW), MR‐Egger regression, weighted median, weighted mode, and MR‐PRESSO sensitivity analyses. Results: FinnGen database subjected to inverse variance weighted (IVW) analysis revealed that MDD may be a risk factor for the development of IBS (OR = 1.356, 95% CI: 1.125–1.632, p = 0.0013). The same finding was reached in UK Biobank for IVW (OR = 1.011, 95% CI: 1.006–1.015, p = 3.18 × 10−7), MR‐Egger progression (OR = 1.030, 95% CI: 1.008–1.051, p = 0.007), and weighted median (OR = 1.011, 95% CI: 1.005–1.016, p = 0.0001). Conclusion: Our findings supported a causal relationship between MDD and IBS, which may have implications for the clinical management of IBS in individuals with MDD. [ABSTRACT FROM AUTHOR]

Background: Telomere length is a critical metric linked to aging, health, and disease. Currently, the exploration of target proteins related to telomere length is usually limited to the context of aging and specific diseases, which limits the discovery of more relevant drug targets. This study integrated large-scale plasma cis-pQTLs data and telomere length GWAS datasets. We used Mendelian randomization(MR) to identify drug target proteins for telomere length, providing essential clues for future precision therapy and targeted drug development. Methods: Using plasma cis-pQTLs data from a previous GWAS study (3,606 Pqtls associated with 2,656 proteins) and a GWAS dataset of telomere length (sample size: 472,174; GWAS ID: ieu-b-4879) from UK Biobank, using MR, external validation, and reverse causality testing, we identified essential drug target proteins for telomere length. We also performed co-localization, Phenome-wide association studies and enrichment analysis, protein-protein interaction network construction, search for existing intervening drugs, and potential drug/compound prediction for these critical targets to strengthen and expand our findings. Results: After Bonferron correction (p < 0.05/734), RPN1 (OR: 0.96; 95%CI: (0.95, 0.97)), GDI2 (OR: 0.94; 95%CI: (0.92, 0.96)), NT5C (OR: 0.97; 95%CI: (0.95, 0.98)) had a significant negative causal association with telomere length; TYRO3 (OR: 1.11; 95%CI: (1.09, 1.15)) had a significant positive causal association with telomere length. GDI2 shared the same genetic variants with telomere length (coloc.abf-PPH 4 > 0.8). Conclusion: Genetically determined plasma RPN1, GDI2, NT5C, and TYRO3 have significant causal effects on telomere length and can potentially be drug targets. Further exploration of the role and mechanism of these proteins/genes in regulating telomere length is needed. [ABSTRACT FROM AUTHOR]

Mechanisms through which most known Alzheimer's disease (AD) loci operate to increase AD risk remain unclear. Although Apolipoprotein E (APOE) is known to regulate lipid homeostasis, the effects of broader AD genetic liability on non-lipid metabolites remain unknown, and the earliest ages at which metabolic perturbations occur and how these change over time are yet to be elucidated. We examined the effects of AD genetic liability on the plasma metabolome across the life course. Using a reverse Mendelian randomization framework in two population-based cohorts [Avon Longitudinal Study of Parents and Children (ALSPAC, n = 5648) and UK Biobank (n ≤ 118,466)], we estimated the effects of genetic liability to AD on 229 plasma metabolites, at seven different life stages, spanning 8 to 73 years. We also compared the specific effects of APOE ε4 and APOE ε2 carriage on metabolites. In ALSPAC, AD genetic liability demonstrated the strongest positive associations with cholesterol-related traits, with similar magnitudes of association observed across all age groups including in childhood. In UK Biobank, the effect of AD liability on several lipid traits decreased with age. Fatty acid metabolites demonstrated positive associations with AD liability in both cohorts, though with smaller magnitudes than lipid traits. Sensitivity analyses indicated that observed effects are largely driven by the strongest AD instrument, APOE, with many contrasting effects observed on lipids and fatty acids for both ε4 and ε2 carriage. Our findings indicate pronounced effects of the ε4 and ε2 genetic variants on both pro- and anti-atherogenic lipid traits and sphingomyelins, which begin in childhood and either persist into later life or appear to change dynamically. [ABSTRACT FROM AUTHOR]

Genetic relationships between blood eosinophil count (BEC), asthma susceptibility, and severity are unclear. We sought to identify the genetic difference between type 2 (T2) and nontype 2 (non-T2) asthma (defined by BEC) and investigate genetic relationships between high BEC, asthma susceptibility, and severity. Genome-wide association studies (GWASs) were performed for T2 (n = 9,064; BEC ≥ 300 cells/μL) versus non-T2 asthma (n = 14,379; BEC < 150 cells/μL) and asthma susceptibility (37,227 asthmatics vs. 124,132 nonasthma controls) in the UK Biobank and asthma severity (moderate-to-severe asthma [n = 2,153] vs. mild asthma [n = 5165]) in the All of Us Research Program (AoURP). Genetic causality between BEC, asthma susceptibility, and severity were dissected using Mendelian randomization (MR). High BEC was associated with asthma and decreased pulmonary function. GWASs revealed four sets of genetic variants (p < 5 × 10−8): genes associated with only BEC or asthma and genes associated with high BEC and asthma in the same or opposite direction. The C allele of rs653178 in ATXN2 was associated with high BEC, risk for autoimmune diseases, and protection for asthma. Genetic variants associated with BEC or asthma were not associated with asthma severity. MR indicated high BEC and asthma were in bidirectional causal relationship (p <.001); however, they were not causal for asthma severity. Genetic variants associated with asthma or BEC and asthma severity are distinctive. High BEC is a risk factor for asthma; however, it is neither necessary nor sufficient for asthma susceptibility and severity. [ABSTRACT FROM AUTHOR]

The use of lipid-lowering drugs is still highly controversial in patients with amyotrophic lateral sclerosis (ALS). We performed a drug-target Mendelian randomization (MR) analysis to investigate the effect of targeted lipid-lowering drugs on the risk of ALS. First, we evaluated the causal relationship between HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase (HMGCR) inhibitors-taking trait and ALS using a bidirectional two-sample MR study. Second, we investigated the causal relationship between lipid-lowering drugs and ALS through a drug-target MR approach. The summary data for HMGCR inhibitors-taking traits were extracted from a genome-wide association study (GWAS) of medication use and associated disease in the UK Biobank. The summary data for low-density lipoprotein cholesterol and apolipoprotein B (apoB) were extracted from a meta-analysis of GWAS in individuals of European ancestry in the UKB. The GWAS summary data of ALS were obtained from the Project MinE. Our bidirectional two-sample MR showed that genetically determined increased HMGCR inhibitors-taking trait was an independent risk factor for ALS (odds ratio [OR] = 1.090, 95% confidence interval [CI] = 1.035–1.150, p = 0.001). The results of drug-target MR showed that the increased expression of the HMGCR gene in blood with the higher risk of ALS (OR = 1.21, 95% CI = 1.01–1.46; p = 0.042) through SMR method and the apoB level mediated by the APOB gene increased the risk of ALS (OR = 1.15; 95% CI =1.05–1.25; p = 0.001) through inverse-variance weighted MR method. This present study provides genetic support for a positive causal effect of HMGCR inhibitors-taking trait and ALS. The reason for this may be due to the underlying disease condition behind the medication, rather than the medication itself. Our findings also suggested that HMGCR and apoB inhibitors may have potential protective effects on ALS. [ABSTRACT FROM AUTHOR]

Background: Observational studies and randomized controlled trials have found evidence that higher maternal circulating cortisol levels in pregnancy are associated with lower offspring birth weight. However, it is possible that the observational associations are due to residual confounding. Methods: We performed two-sample Mendelian Randomisation (MR) using a single genetic variant (rs9989237) associated with morning plasma cortisol (GWAS; sample 1; N = 25,314). The association between this maternal genetic variant and offspring birth weight, adjusted for fetal genotype, was obtained from the published EGG Consortium and UK Biobank meta-analysis (GWAS; sample 2; N = up to 406,063) and a Wald ratio was used to estimate the causal effect. We also performed an alternative analysis using all GWAS reported cortisol variants that takes account of linkage disequilibrium. We also tested the genetic variant's effect on pregnancy cortisol and performed PheWas to search for potential pleiotropic effects. Results: The estimated effect of maternal circulating cortisol on birth weight was a 50 gram (95% CI, -109 to 10) lower birth weight per 1 SD higher log-transformed maternal circulating cortisol levels, using a single variant. The alternative analysis gave similar results (-33 grams (95% CI, -77 to 11)). The effect of the cortisol variant on pregnancy cortisol was 2-fold weaker than in the original GWAS, and evidence was found of pleiotropy. Conclusions: Our findings provide some evidence that higher maternal morning plasma cortisol causes lower birth weight. Identification of more independent genetic instruments for morning plasma cortisol are necessary to explore the potential bias identified. [ABSTRACT FROM AUTHOR]

Background: Valproate is a candidate for ischemic stroke prevention due to its anti-atherosclerotic effects in vivo. Although valproate use is associated with decreased ischemic stroke risk in observational studies, confounding by indication precludes causal conclusions. Aims: We applied Mendelian randomization to determine whether genetic variants that influence seizure response among valproate users associate with ischemic stroke. Methods: We derived a genetic score for valproate response using genome-wide association data of seizure response after valproate intake from the Epilepsy Pharmacogenomics Consortium. We then tested this score among valproate users of the UK Biobank for association with incident and recurrent ischemic stroke using Cox proportional hazard models. As replication, we tested found associations in an independent cohort of valproate users of the Mass General Brigham Biobank. Results: Among 2150 valproate users (mean 56 years, 54% females), 82 ischemic strokes occurred over a mean 12 year follow-up. Higher valproate response genetic score was associated with higher serum valproate levels (+5.78 µg/ml per 1 standard deviation (SD), 95% confidence interval (CI) (3.45, 8.11)). After adjusting for age and sex, higher valproate response genetic score was associated with lower ischemic stroke risk (hazard ratio (HR) per 1 SD 0.73, 95% CI (0.58, 0.91)) with a halving of absolute risk in the highest compared to the lowest score tertile (4.8% vs 2.5%, p trend = 0.027). Among 194 valproate users with prevalent stroke at baseline, a higher valproate response genetic score was associated with lower recurrent ischemic stroke risk (HR per 1 SD 0.53, 95% CI (0.32, 0.86)) with reduced absolute risk in the highest compared to the lowest score tertile (3/51, 5.9% vs 13/71, 18.3%, p trend = 0.026). The valproate response genetic score was not associated with ischemic stroke among the 427,997 valproate non-users (p = 0.61), suggesting minimal pleiotropy. In 1241 valproate users of the Mass General Brigham Biobank with 99 ischemic stroke events over 6.5 years follow-up, we replicated our observed associations between the valproate response genetic score and ischemic stroke (HR per 1 SD 0.77, 95% CI (0.61, 0.97)). Conclusion: These results demonstrate that a genetically predicted favorable seizure response to valproate is associated with higher serum valproate levels and reduced ischemic stroke risk among valproate users, providing causal support for valproate effectiveness in ischemic stroke prevention. The strongest effect was found for recurrent ischemic stroke, suggesting potential dual-use benefits of valproate for post-stroke epilepsy. Clinical trials will be required in order to identify populations that may benefit most from valproate for stroke prevention. Data access statement: UK Biobank participant data are available after approval of a research proposal. The weights of the used genetic scores are available in the Supplemental Tables. [ABSTRACT FROM AUTHOR]

Major depression (MD) is a well-recognized risk factor for delirium. However, observational studies cannot provide direct evidence of causality between MD and delirium. This study explored the genetic causal association between MD and delirium using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS) summary data for MD were obtained from the UK Biobank. GWAS summary data for delirium were obtained from the FinnGen Consortium. Inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode were used to perform the MR analysis. In addition, the Cochrane's Q test was used to detect heterogeneity in the MR results. Horizontal pleiotropy was detected using the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. Leave-one-out analysis was used to investigate the sensitivity of this association. The IVW method showed that MD was an independent risk factor for delirium (P = 0.013). Horizontal pleiotropy was unlikely to bias causality (P > 0.05), and no evidence of heterogeneity was found between the genetic variants (P > 0.05). Finally, a leave-one-out test showed that this association was stable and robust. All participants included in the GWAS were of European ancestry. Due to database limitations, the MR analysis did not conduct stratified analyses for different countries, ethnicities, or age groups. We conducted a two-sample MR analysis and found the evidence of genetic causal association between MD and delirium. • A two-sample MR analysis was conducted to explore the causal effect between MD and delirium. • Inverse-variance weighted, MR Egger, weighted median, simple mode, and weighted mode were used to perform the MR analysis. • Heterogeneity and horizontal pleiotropy in the MR results were detected. • We found the evidence of genetic causal association between MD and delirium. [ABSTRACT FROM AUTHOR]

Background: The association between cigarette smoking and thyroid cancer has been reported in prospective cohort studies, but the relationship remains controversial. To investigate this potential correlation further, we employed Mendelian randomization methodology to evaluate the causative impact of smoking on thyroid cancer incidence. Methods: From the genome‐wide association study and Sequencing Consortium of Alcohol and Nicotine use, we obtained genetic variants associated with smoking initiation and cigarettes per day (1.2 million individuals). We also extracted genetic variants associated with past tobacco smoking from the UK Biobank (424,960 individuals). Thyroid cancer outcomes were selected from the FinnGen GWAS (989 thyroid cancer cases and 217,803 control cases). Sensitivity analyses employing various approaches such as weighted median, MR‐Egger, and MR‐pleiotropy residual sum and outlier (MR‐PRESSO) have been executed, as well as leave‐one‐out analysis to identify pleiotropy. Results: Using the IVW approach, we did not find evidence that any of the three smoking phenotypes were related to thyroid cancer (smoking initiation: odds ratio (OR) = 1.56, p = 0.61; cigarettes per day: OR = 0.85, p = 0.51; past tobacco smoking: OR = 0.80, p = 0.78). The heterogeneity (p > 0.05) and pleiotropy (p > 0.05) testing provided confirmatory evidence for the validity of our MR estimates. Conclusions: The MR analysis revealed that there may not exist a causative link between smoking exposure and elevated incidence rates of thyroid malignancies. We used Mendelian randomization analysis to evaluate the causal relationship between smoking and thyroid cancer, and found that smoking was not associated with thyroid cancer. [ABSTRACT FROM AUTHOR]

Introduction Genetic associations for variants identified through genome-wide association studies (GWASs) tend to be overestimated in the original discovery data set as, if the association was underestimated, the variant may not have been detected. This bias, known as winner's curse, can affect Mendelian randomization estimates, but its severity and potential impact are unclear. Methods We performed an empirical investigation to assess the potential bias from winner's curse in practice. We considered Mendelian randomization estimates for the effect of body mass index (BMI) on coronary artery disease risk. We randomly divided a UK Biobank data set 100 times into three equally sized subsets. The first subset was treated as the 'discovery GWAS'. We compared genetic associations estimated in the discovery GWAS to those estimated in the other subsets for each of the 100 iterations. Results For variants associated with BMI at P  <   5 × 10–8 in at least one iteration, genetic associations with BMI were up to 5-fold greater in iterations in which the variant was associated with BMI at P  <   5 × 10–8 compared with its mean association across all iterations. If the minimum P -value for association with BMI was P  =   10–13 or lower, then this inflation was <25%. Mendelian randomization estimates were affected by winner's curse bias. However, bias did not materially affect results; all analyses indicated a deleterious effect of BMI on coronary artery disease risk. Conclusions Winner's curse can bias Mendelian randomization estimates, although its practical impact may not be substantial. If avoiding sample overlap is infeasible, analysts should consider performing a sensitivity analysis based on variants strongly associated with the exposure. [ABSTRACT FROM AUTHOR]

Background An increasing proportion of people have a body mass index (BMI) classified as overweight or obese and published studies disagree whether this will be beneficial or detrimental to health. We applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality in a cohort with many deaths: the parents of UK Biobank participants. Methods In Cox regression models, parental BMI was instrumented by offspring BMI using an 'offspring as instrument' (OAI) estimation and by offspring BMI-related genetic variants in a 'proxy-genotype Mendelian randomization' (PGMR) estimation. Results Complete-case analyses were performed in parents of 233 361 UK Biobank participants with full phenotypic, genotypic and covariate data. The PGMR method suggested that higher BMI increased mortality with hazard ratios per kg/m2 of 1.02 (95% CI: 1.01, 1.04) for mothers and 1.04 (95% CI: 1.02, 1.05) for fathers. The OAI method gave considerably higher estimates, which varied according to the parent–offspring pairing between 1.08 (95% CI: 1.06, 1.10; mother–son) and 1.23 (95% CI: 1.16, 1.29; father–daughter). Conclusion Both methods supported a causal role of higher BMI increasing mortality, although caution is required regarding the immediate causal interpretation of these exact values. Evidence of instrument invalidity from measured covariates was limited for the OAI method and minimal for the PGMR method. The methods are complementary for interrogating the average putative causal effects because the biases are expected to differ between them. [ABSTRACT FROM AUTHOR]

Background and Aims: Tobacco smoking is a risk factor for impaired brain function, but its causal effect on white matter brain aging remains unclear. This study aimed to measure the causal effect of tobacco smoking on white matter brain aging. Design: Mendelian randomization (MR) analysis using two non‐overlapping data sets (with and without neuroimaging data) from UK Biobank (UKB). The group exposed to smoking and control group consisted of current smokers and never smokers, respectively. Our main method was generalized weighted linear regression with other methods also included as sensitivity analysis. Setting: United Kingdom. Participants: The study cohort included 23 624 subjects [10 665 males and 12 959 females with a mean age of 54.18 years, 95% confidence interval (CI) = 54.08, 54.28]. Measurements Genetic variants were selected as instrumental variables under the MR analysis assumptions: (1) associated with the exposure; (2) influenced outcome only via exposure; and (3) not associated with confounders. The exposure smoking status (current versus never smokers) was measured by questionnaires at the initial visit (2006–10). The other exposure, cigarettes per day (CPD), measured the average number of cigarettes smoked per day for current tobacco users over the life‐time. The outcome was the 'brain age gap' (BAG), the difference between predicted brain age and chronological age, computed by training machine learning model on a non‐overlapping set of never smokers. Findings The estimated BAG had a mean of 0.10 (95% CI = 0.06, 0.14) years. The MR analysis showed evidence of positive causal effect of smoking behaviors on BAG: the effect of smoking is 0.21 (in years, 95% CI = 6.5 × 10−3, 0.41; P‐value = 0.04), and the effect of CPD is 0.16 year/cigarette (UKB: 95% CI = 0.06, 0.26; P‐value = 1.3 × 10−3; GSCAN: 95% CI = 0.02, 0.31; P‐value = 0.03). The sensitivity analyses showed consistent results. Conclusions: There appears to be a significant causal effect of smoking on the brain age gap, which suggests that smoking prevention can be an effective intervention for accelerated brain aging and the age‐related decline in cognitive function. [ABSTRACT FROM AUTHOR]

Background: The bidirectional causal association between daytime napping frequency and schizophrenia is unclear. Methods: A bidirectional two-sample Mendelian randomization (MR) analysis was conducted with summary statistics of top genetic variants associated with daytime napping frequency and schizophrenia from genome-wide association studies (GWAS). The single nucleotide polymorphisms (SNPs) data of daytime napping frequency GWAS came from the UK Biobank (n = 452,633) and 23andMe study cohort (n = 541,333), while the schizophrenia GWAS came from the Psychiatric Genomics Consortium (PGC, 36,989 cases and 113,075 controls). The inverse variance weighted (IVW) analysis was the primary method, with the weighted median, MR-Robust Adjusted Profile Score (RAPS), Radial MR and MR-Pleiotropy Residual Sum Outlier (PRESSO) as sensitivity analysis. Results: The MR analysis showed a bidirectional causal relationship between more frequent daytime napping and the occurrence of schizophrenia, with the odds ratio (OR) for one-unit increase in napping category (never, sometimes, usually) on schizophrenia was 3.38 (95% confidence interval [CI]: 2.02–5.65, P = 3.58 × 10–6), and the beta for the occurrence of schizophrenia on daytime napping frequency was 0.0112 (95%CI: 0.0060–0.0163, P = 2.04 × 10–5). The sensitivity analysis obtained the same conclusions. Conclusion: Our findings support the bidirectional causal association between more daytime napping frequency and schizophrenia, implying that daytime napping frequency is a potential intervention for the progression and treatment of schizophrenia. [ABSTRACT FROM AUTHOR]

Background: Circulating levels of amino acids were associated with blood pressure (BP) in observational studies. However, the causation of such associations has been hypothesized but is difficult to prove in human studies. Here, we aimed to use two-sample Mendelian randomization analyses to evaluate the potential causal associations of circulating levels of amino acids with BP and risk of hypertension.Methods: We generated genetic instruments for circulating levels of nine amino acids by conducting meta-analyses of genome-wide association study (GWAS) in UK Biobank participants with metabolomic data (n = 98,317) and another published metabolomics GWAS (n = 24,925). Data on the associations of the genetic variants with BP and hypertension were obtained in the UK Biobank participants without metabolomic data (n = 286,390). The causal effects were estimated using inverse-variance weighted method.Results: Significant evidence consistently supported the causal effects of increased branched-chain amino acids (BCAAs, i.e., leucine, isoleucine, and valine) levels on higher BP and risk of hypertension (all P < 0.006 after Bonferroni correction except for Pleucine-on-diastolicBP = 0.008). For example, per standard deviation higher of genetically predicted isoleucine levels were associated with 2.71 ± 0.78 mmHg higher systolic BP and 1.24 ± 0.34 mmHg higher diastolic BP, as well as with 7% higher risk of hypertension (odds ratio: 1.07, [95% CI: 1.04-1.10]). In addition, per standard deviation higher of genetically predicted glycine level was associated with lower systolic BP (- 0.70 ± 0.17 mmHg, P = 4.04 × 10-5) and a lower risk of hypertension (0.99 [0.98-0.99], P = 6.46 × 10-5). In the reverse direction, genetically predicted higher systolic BP was associated with lower circulating levels of glycine (- 0.025±0.008, P = 0.001).Conclusions: This study provides evidence for causal impacts of genetically predicted circulating BCAAs and glycine levels on BP. Meanwhile, genetically predicted higher BP was associated with lower glycine levels. Further investigations are warranted to clarify the underlying mechanisms. [ABSTRACT FROM AUTHOR]

Weight loss or lower body mass index (BMI) could be an early symptom of Alzheimer disease (AD), but when this begins to emerge is difficult to estimate with traditional observational data. In an extension of Mendelian randomization, we leveraged variation in genetic risk for late-onset AD risk to estimate the causal effect of AD on BMI and the earliest ages at which AD-related weight loss (or lower BMI as a proxy) occurs. We studied UK Biobank participants enrolled in 2006–2010, who were without dementia, aged 39–73, with European genetic ancestry. BMI was calculated with measured height/weight (weight (kg)/height (m)2). An AD genetic risk score (AD-GRS) was calculated based on 23 genetic variants. Using linear regressions, we tested the association of AD-GRS with BMI, stratified by decade, and calculated the age of divergence in BMI trends between low and high AD-GRS. AD-GRS was not associated with BMI in 39- to 49-year-olds (β = 0.00, 95% confidence interval (CI): −0.03, 0.03). AD-GRS was associated with lower BMI in 50- to 59-year-olds (β = −0.03, 95% CI: −0.06, −0.01) and 60- to 73-year-olds (β = −0.09, 95% CI:−0.12, −0.07). Model-based BMI age curves for high versus low AD-GRS began to diverge after age 47 years. Sensitivity analyses found no evidence for pleiotropy or survival bias. Longitudinal replication is needed; however, our findings suggest that AD genes might begin to reduce BMI decades prior to dementia diagnosis. [ABSTRACT FROM AUTHOR]

Evidence from observational studies suggests a positive association between serum thyroid-stimulating hormone (TSH) levels and differentiated thyroid carcinoma. However, the cause-effect relationship is poorly understood, and these studies are susceptible to bias and confounding. Using Mendelian randomization (MR) methodology, this study aimed to investigate the causal role of TSH in both benign thyr oid nodules and thyroid cancer in up to 451,025 participants in the UK Biobank. Hospita l Episode Statistics and Cancer Registry databases were used to identify 462 patients with differentiated thyroid carcinoma and 2031 patients with benign nodular thyroid disease. MR methods using genetic variants associated with serum TSH were used to test ca usal relationships between TSH and the two disease outcomes. We observed evidence of an inverse association between TSH levels and both thyroid cancer and benign nodular thyroid disease. Two-sample MR suggested that one standard deviation higher genetically instrumented TSH (approximately 0.8 mlU/L) resulted in an 80% reduction of risk of benign nodular disease (OR 0.20; 95% CI 0.10--0.41) and a 50% re duction of risk of thyroid cancer (OR 0.50; 95% CI 0.27--0.92). In keeping with other recen tly published studies, our results refute a causal role for TSH in both benign nodular thy roid disease and thyroid cancer, with increasing genetically instrumented TSH resulting in a lower risk of both diseases. [ABSTRACT FROM AUTHOR]

Background: Lipoprotein(a) (Lp(a)) concentrations are a major independent risk factor for coronary artery disease (CAD) and are mainly determined by variation in LPA. Up to 70% of the LPA coding sequence is located in the hypervariable kringle IV type 2 (KIV-2) region. It is hardly accessible by conventional technologies, but may contain functional variants.Objectives: This study sought to investigate the new, very frequent splicing variant KIV-2 4733G>A on Lp(a) and CAD.Methods: We genotyped 4733G>A in the GCKD (German Chronic Kidney Disease) study (n = 4,673) by allele-specific polymerase chain reaction, performed minigene assays, identified proxy single nucleotide polymorphisms and used them to characterize its effect on CAD by survival analysis in UK Biobank (n = 440,234). Frequencies in ethnic groups were assessed in the 1000 Genomes Project.Results: The 4733G>A variant (38.2% carrier frequency) was found in most isoform sizes. It reduces allelic expression without abolishing protein production, lowers Lp(a) by 13.6 mg/dL (95% CI: 12.5-14.7; P < 0.0001) and is the strongest variance-explaining factor after the smaller isoform. Splicing of minigenes was modified. Compound heterozygosity (4.6% of the population) for 4733G>A and 4925G>A, another KIV-2 splicing mutation, reduces Lp(a) by 31.8 mg/dL and most importantly narrows the interquartile range by 9-fold (from 42.1 to 4.6 mg/dL) when compared to the wild type. In UK Biobank 4733G>A alone and compound heterozygosity with 4925G>A reduced HR for CAD by 9% (95% CI: 7%-11%) and 12% (95% CI: 7%-16%) (both P < 0.001). Frequencies in ethnicities differ notably.Conclusions: Functional variants in the previously inaccessible LPA KIV-2 region cooperate in determining Lp(a) variance and CAD risk. Even a moderate but lifelong genetic Lp(a) reduction translates to a noticeable CAD risk reduction. [ABSTRACT FROM AUTHOR]