Large-scale Genome-wide Association Study Datasets Research Articles

Association between dried fruit intake and kidney function: research from univariate and multivariate Mendelian randomized studies.

Observational studies have identified an association between dried fruit intake and kidney function. However, these studies have limitations such as vulnerability to confounders and reverse causality bias. Therefore, this study aimed to explore the potential causal relationship between dried fruit intake and kidney function. A two-sample Mendelian randomization (MR) study was conducted using a large-scale genome-wide association study dataset to investigate the causal relationship between dried fruit intake and kidney function markers (blood urea nitrogen (BUN), creatinine (CR), uric acid (UA), cystatin C (CyC), hematuria, microalbuminuria). The main analytical method was inverse variance weighting. In addition, we applied the MR Egger and weighted median to assess the robustness of the results. Finally, Multivariate Mendelian randomization (MVMR) was used to estimate the direct effect of dried fruit intake on kidney function markers. The univariate MR analysis showed that increased dried fruit intake was associated with lower kidney function markers, including BUN (β: -0.171, 95% confidence interval (CI): -0.239 to -0.102, p = 1.063 × 10-6), CR (β: -0.205, 95% CI: -0.311 to -0.099, p = 1.455 × 10-4), UA (β = -0.317, 95% CI: -0.384 to -0.249, p = 4.439 × 10-20), and CysC (β = -0.323, 95% CI: -0.384 to -0.249, p = 1.074 × 10-11); however, it was unrelated to hematuria and microalbuminuria. Causality persisted after performing MVMR analysis; however, with the addition of alcohol consumption and smoking as exposure factors, the causality for UA (β = -0.296, 95% CI: -0.523 to -0.068, p = 1.094 × 10-2) and CysC (β = -0.238, 95% CI: -0.465 to -0.011, p = 4.024× 10-2) weakened, while the causality for BUN (β = -0.038, 95% CI: -0.215 to 0.138, p = 6.698 × 10-1) and CR (β = -0.038, 95% CI: -0.431 to 0.046, p = 1.347 × 10-1) disappeared. Increased dried fruit intake was associated with lower kidney function markers (BUN, CR, UA, and CysC) in the absence of smoking and alcohol consumption; however, the causal relationship between dried fruit intake and BUN and CR disappeared in the presence of smoking and alcohol consumption. These results provide a promising avenue for delaying the course of chronic kidney disease.

Causal Effects of Kidney Function and Chronic Kidney Disease on Alzheimer's Disease by Analyzing Large-Scale Genome-Wide Association Study Datasets.

Alzheimer's disease (AD) is the leading cause of dementia. Genetic components play an important role in AD and have been widely evaluated by genome-wide association studies (GWAS) and exome sequencing, and some common and rare genetic variants have been identified. In addition to genetic factors, environment factors have a role in AD. Growing evidence from observational studies linked impaired kidney function to cognitive impairment and AD; however, there are inconsistences in these findings. To determine the causal effects of impaired kidney function and chronic kidney disease (CKD) on AD. Mendelian randomization (MR) methods have been widely used to infer causal associations between exposure and outcome. Here, we conducted an MR study to investigate the causal effects of impaired kidney function and CKD on the risk of AD by analyzing large-scale GWAS datasets from FinnGen and CKD Genetics (CKDGen) Consortium. We found no significant but a suggestive effect of CKD on decreased risk of AD using inverse-variance weighted (IVW) (p = 8.46E-02) and simple mode (p = 7.60E-02) methods. We identified a statistically significant effect of the estimated glomerular filtration rate (eGFR) on increased risk of AD using IVW (p = 1.11E-02), weighted median regression (p = 5.60E-03), and weighted mode (p = 2.45E-02) methods. Together, our findings indicate that high eGFR levels may increase the risk of AD. These findings need to be verified in future studies.

Reverse causation between multiple sclerosis and psoriasis: a genetic correlation and Mendelian randomization study

Observational studies have found a potential bidirectional positive association between multiple sclerosis and psoriasis, but these studies are susceptible to confounding factors. We examined the directionality of causation using Mendelian randomization and estimated the genetic correlation using the linkage disequilibrium score. We performed Mendelian randomization analysis using large-scale genome-wide association studies datasets from the International Multiple Sclerosis Genetics Consortium (IMSGC, 115,803 individuals of European ancestry) and FinnGen (252,323 individuals of European ancestry). We selected several Mendelian randomization methods including causal analysis using summary effect (CAUSE), inverse variance-weighted (IVW), and pleiotropy-robust methods. According to CAUSE and IVW the genetic liability to MS reduces the risk of psoriasis (CAUSE odds ratio [OR] 0.93, p = 0.045; IVW OR 0.93, p = 2.51 × 10–20), and vice versa (CAUSE OR 0.72, p = 0.001; IVW OR 0.71, p = 4.80 × 10–26). Pleiotropy-robust methods show the same results, with all p-values < 0.05. The linkage disequilibrium score showed no genetic correlation between psoriasis and MS (rg = − 0.071, p = 0.2852). In summary, there is genetic evidence that MS reduces the risk of psoriasis, and vice versa.

Plasma metabolites and risk of myocardial infarction: a bidirectional Mendelian randomization study.

Myocardial infarction (MI) is a critical cardiovascular event with multifaceted etiology, involving several genetic and environmental factors. It is essential to understand the function of plasma metabolites in the development of MI and unravel its complex pathogenesis. This study employed a bidirectional Mendelian randomization (MR) approach to investigate the causal relationships between plasma metabolites and MI risk. We used genetic instruments as proxies for plasma metabolites and MI and conducted MR analyses in both directions to assess the impact of metabolites on MI risk and vice versa. In addition, the large-scale genome-wide association studies datasets was used to identify genetic variants associated with plasma metabolite (1400 metabolites) and MI (20,917 individuals with MI and 440,906 individuals without MI) susceptibility. Inverse variance weighted was the primary method for estimating causal effects. MR estimates are expressed as beta coefficients or odds ratio (OR) with 95% CI. We identified 14 plasma metabolites associated with the occurrence of MI (P < 0.05), among which 8 plasma metabolites [propionylglycine levels (OR = 0.922, 95% CI: 0.881-0.965, P < 0.001), gamma-glutamylglycine levels (OR = 0.903, 95% CI: 0.861-0.948, P < 0.001), hexadecanedioate (C16-DC) levels (OR = 0.941, 95% CI: 0.911-0.973, P < 0.001), pentose acid levels (OR = 0.923, 95% CI: 0.877-0.972, P = 0.002), X-24546 levels (OR = 0.936, 95% CI: 0.902-0.971, P < 0.001), glycine levels (OR = 0.936, 95% CI: 0.909-0.964, P < 0.001), glycine to serine ratio (OR = 0.930, 95% CI: 0.888-0.974, P = 0.002), and mannose to trans-4-hydroxyproline ratio (OR = 0.912, 95% CI: 0.869-0.958, P < 0.001)] were correlated with a decreased risk of MI, whereas the remaining 6 plasma metabolites [1-palmitoyl-2-arachidonoyl-GPE (16:0/20:4) levels (OR = 1.051, 95% CI: 1.018-1.084, P = 0.002), behenoyl dihydrosphingomyelin (d18:0/22:0) levels (OR = 1.076, 95% CI: 1.027-1.128, P = 0.002), 1-stearoyl-2-docosahexaenoyl-GPE (18:0/22:6) levels (OR = 1.067, 95% CI: 1.027-1.109, P = 0.001), alpha-ketobutyrate levels (OR = 1.108, 95% CI: 1.041-1.180, P = 0.001), 5-acetylamino-6-formylamino-3-methyluracil levels (OR = 1.047, 95% CI: 1.019-1.076, P < 0.001), and N-acetylputrescine to (N (1) + N (8))-acetylspermidine ratio (OR = 1.045, 95% CI: 1.018-1.073, P < 0.001)] were associated with an increased risk of MI. Furthermore, we also observed that the mentioned relationships were unaffected by horizontal pleiotropy (P > 0.05). On the contrary, MI did not lead to significant alterations in the levels of the aforementioned 14 plasma metabolites (P > 0.05 for each comparison). Our bidirectional MR study identified 14 plasma metabolites associated with the occurrence of MI, among which 13 plasma metabolites have not been reported previously. These findings provide valuable insights for the early diagnosis of MI and potential therapeutic targets.

Identification of heel bone mineral density as a risk factor of Alzheimer’s disease by analyzing large-scale genome-wide association studies datasets

Introduction: Both low bone mineral density (BMD) and Alzheimer’s disease (AD) commonly co_occur in the older adult. Until now, the association between AD and BMD has been widely reported by observational studies. However, Mendelian randomization (MR) studies did not support the causal association between BMD and AD. We think that the lack of significant causal association between AD and BMD identified by recent MR studies may be caused by small number of potential instrumental variables.Methods: We conduct a MR study to evaluate the causal effect of heel BMD on the risk of AD using 1,362 genome-wide significant and independent (p &amp;lt; 5.00E-08) heel BMD genetic variants as the potential instrumental variables, which are identified by a large-scale genome wide association study (GWAS) of heel BMD in 394,929 UK Biobank individuals. Using these 1,362 genome-wide significant and independent heel BMD genetic variants, we extracted their corresponding AD GWAS summary results in IGAP AD GWAS dataset (n = 63,926) and FinnGen AD GWAS dataset (n = 377,277). Five methods including inverse-variance weighted meta-analysis (IVW), weighted median, MR-Egger, MR-PRESSO, and MRlap were selected to perform the MR analysis. 951 of these 1,362 genetic variants are available in AD GWAS dataset.Results: We observed statistically significant causal effect of heel BMD on the risk of AD using IVW in IGAP AD GWAS dataset (OR = 1.048, 95%CI: 1.002–1.095, p = 0.04) and FinnGen AD GWAS dataset (OR = 1.053, 95% CI:1.011–1.098, p = 0.011). Importantly, meta-analysis of IVW estimates from IGAP and FinnGen further supported the causal effect of heel BMD on the risk of AD (OR = 1.051, 95% CI: 1.02–1.083, p = 0.0013).Discussion: Collectively, our current MR study supports heel BMD to be a risk factor of AD by analyzing the large-scale heel BMD and AD GWAS datasets. The potential mechanisms underlying the association between heel BMD and AD should be further evaluated in future.

Investigating genetic causal relationships between blood pressure and anxiety, depressive symptoms, neuroticism and subjective well-being

BackgroundHigh blood pressure is a leading cardiovascular disease risk factor and considered to be associated with psychological factors. However, the causal relationships between blood pressure and anxiety, depressive symptoms, neuroticism...

Evaluating the Causal Association Between Educational Attainment and Asthma Using a Mendelian Randomization Design.

Asthma is a common chronic respiratory disease. In the past 10 years, genome-wide association study (GWAS) has been widely used to identify the common asthma genetic variants. Importantly, these publicly available asthma GWAS datasets provide important data support to investigate the causal association of kinds of risk factors with asthma by a Mendelian randomization (MR) design. It is known that socioeconomic status is associated with asthma. However, it remains unclear about the causal association between socioeconomic status and asthma. Here, we selected 162 independent educational attainment genetic variants as the potential instruments to evaluate the causal association between educational attainment and asthma using large-scale GWAS datasets of educational attainment (n = 405,072) and asthma (n = 30,810). We conducted a pleiotropy analysis using the MR-Egger intercept test and the MR pleiotropy residual sum and outlier (MR-PRESSO) test. We performed an MR analysis using inverse-variance weighted, weighted median, MR-Egger, and MR-PRESSO. The main analysis method inverse-variance weighted indicated that each 1 standard deviation increase in educational attainment (3.6 years) could reduce 35% asthma risk [odds ratio (OR) = 0.65, 95% confidence interval (CI) 0.51–0.85, P = 0.001]. Importantly, evidence from other MR methods further supported this finding, including weighted median (OR = 0.55, 95% CI 0.38–0.80, P = 0.001), MR-Egger (OR = 0.48, 95% CI 0.16–1.46, P = 0.198), and MR-PRESSO (OR = 0.65, 95% CI 0.51–0.85, P = 0.0015). Meanwhile, we provide evidence to support that educational attainment protects against asthma risk dependently on cognitive performance using multivariable MR analysis. In summary, we highlight the protective role of educational attainment against asthma. Our findings may have public health applications and deserve further investigation.

Is type 2 diabetes mellitus an inverse risk factor for the development of rheumatoid arthritis?

Type 2 diabetes mellitus (T2DM) and rheumatoid arthritis (RA) are both chronic diseases. Although the link between metabolic abnormalities and dysregulated inflammation has received much attention, it is not known whether T2DM can be a risk for the development of RA. Also, observational studies have the disadvantage that the possibility of confounding factors, such as environmental factors, cannot be ruled out. Therefore, the current study performed the mendelian randomization (MR) analysis using recent large-scale genome-wide association studies datasets of T2DM and RA separately European and Asian ancestries. As a result, T2DM had an inverse causal effect on the risk of RA. This study proposed a novel hypothesis that a protective effect of T2DM for the risk of RA.

Evaluating the current state of Mendelian randomization studies: a protocol for a systematic review on methodological and clinical aspects using neurodegenerative disorders as outcome

BackgroundMendelian randomization (MR) is fast becoming a popular method to judge causality from routinely conducted observational studies. However, stringent underlying statistical assumptions, missing biological information, and high sample size requirement might make it prone to misuse. Furthermore, rapidly updating methodologies and increasingly available datasets to researchers are making the interpretations of heterogeneous results even more complicated. In this protocol, we provide our design for a multifaceted systematic review on MR studies using neurodegenerative disease as an example outcome. The planned systematic review which has already passed the pilot stage will help to develop an in-depth understanding of how various MR methods have been applied, what has been achieved, and what can be done in future for to arrive at true causal risk factors.MethodsDuring the pilot phase of this systematic review, several versions of questionnaires and frequent consultations between reviewers helped us to finalize a comprehensive list of questions. This will be used to extract information on systematically searched MR articles investigating causality underlying neurodegenerative diseases. A literature search of the electronic databases (Embase, MEDLINE, Web of Science, Scopus, and databases listed in the Cochrane library) will be conducted. The search strategy will include terms related to MR and the spectrum of neurodegenerative diseases. Two independent reviewers will screen the studies, and three will extract the data. The included studies will be further judged by two reviewers for accuracy and completeness of available information. We will perform descriptive and quantitative synthesis using sensitivity analyses of causal association by study design, selection of genetic instrument, validity of MR assumptions, MR method, and sensitivity analysis based on exclusion of potential pleiotropic variants. The quality of conduct as well as quality of reporting in the included studies will be assessed and reported. A meta-analysis will be conducted, if effect estimates on identical genetic instruments are available for both exposure and outcome in the studies using data from participants from ethnically similar populations.DiscussionThis systematic review protocol utilizes a unique comprehensive data abstraction tool based on recent methodological advancements in the field of MR. The planned systematic review will further integrate information on methodological details with clinical findings in latest available large-scale genome-wide association study datasets. Our findings aim to help raising awareness and promoting transparent reporting of MR studies.Systematic review registrationPROSPERO CRD42018091434.

Re-assessment of multiple testing strategies for more efficient genome-wide association studies.

Although enormous costs have been dedicated to discovering relevant disease-related genetic variants, especially in genome-wide association studies (GWASs), only a small fraction of estimated heritability can be explained by these results. This is the so-called missing heritability problem. The conventional use of overly conservative multiple testing strategies based on controlling the familywise error rate (FWER), in particular with a genome-wide significance threshold of P <5 × 10-8, is one of the most important issues from a statistical perspective. To help resolve this problem, we performed comprehensive re-assessments of currently available strategies using recently published, extremely large-scale GWAS data sets of rheumatoid arthritis and schizophrenia (>50,000 subjects). The estimates of statistical power averaged for all disease-related genetic variants of the standard FWER-based strategy were only 0.09% for the rheumatoid arthritis data and 0.04% for the schizophrenia data. To design more efficient strategies, we also conducted an extensive comparison of multiple testing strategies by applying false discovery rate (FDR)-controlling procedures to these data sets and simulations, and found that the FDR-based procedures achieved higher power than the FWER-based strategy, even at a strict FDR level (e.g., FDR = 1%). We also discuss a useful alternative measure, namely "partial power," which is an averaged power for detecting the clinically and biologically meaningful genetic factors with the largest effects. Simulation results suggest that the FDR-based procedures can achieve sufficient partial power (>80%) for detecting these factors (odds ratios of >1.05) with 80,000 subjects, and thus this may be a useful measure for defining realistic objectives of future GWASs.

High-performance epistasis detection in quantitative trait GWAS

epiSNP is a program for identifying pairwise single nucleotide polymorphism (SNP) interactions (epistasis) in quantitative-trait genome-wide association studies (GWAS). A parallel MPI version (EPISNPmpi) was created in 2008 to address this computationally expensive analysis on large data sets with many quantitative traits and SNP markers. However, the falling cost of genotyping has led to an explosion of large-scale GWAS data sets that challenge EPISNPmpi’s ability to compute results in a reasonable amount of time. Therefore, we optimized epiSNP for modern multi-core and highly parallel many-core processors to efficiently handle these large data sets. This paper describes the serial optimizations, dynamic load balancing using MPI-3 RMA operations, and shared-memory parallelization with OpenMP to further enhance load balancing and allow execution on the Intel Xeon Phi coprocessor (MIC). For a large GWAS data set, our optimizations provided a 38.43× speedup over EPISNPmpi on 126 nodes using 2 MICs on TACC’s Stampede Supercomputer. We also describe a Coarray Fortran (CAF) version that demonstrates the suitability of PGAS languages for problems with this computational pattern. We show that the Coarray version performs competitively with the MPI version on the NERSC Edison Cray XC30 supercomputer. Finally, the performance benefits of hyper-threading for this application on Edison (average 1.35× speedup) are demonstrated.