Genome-wide Association Studies Datasets Research Articles

Effects of major depression and bipolar disorder on erectile dysfunction: a two-sample mendelian randomization study

Background and AimsThere are currently no clear conclusions about whether major depression (MD) and bipolar disorder (BD) increase the risk of erectile dysfunction (ED). In our study, we used a Mendelian randomization (MR) analysis to discover the causal associations between MD, BD and ED.MethodsWe got single-nucleotide polymorphisms (SNPs) related to MD, BD and ED from the MRC IEU Open genome-wide association study (GWAS) datasets. After a series of selection, SNPs left were selected as instrumental variables (IVs) of MD and BD for the following MR test to evaluate the relationship of genetically predicted MD or BD with the incidence of ED. Among them, we used the random-effects inverse-variance weighted (IVW) method as the main analysis. Finally, sensitivity analyses were further performed using Cochran’s Q test, funnel plots, MR-Egger regression, Leave-one-out method and MR- pleiotropy residual sum and outlier (PRESSO).ResultsGenetically-predicted MD was causally related to the incidence of ED in the IVW methods (odds ratio (OR), 1.53; 95% confidence interval (CI), 1.19–1.96; p = 0.001), while no causal impact of BD on the risk of ED (OR = 0.95, 95% CI 0.87–1.04; p = 0.306). The results of sensitivity analyses supported our conclusion, and no directional pleiotropy were found.ConclusionThe findings of this research found evidence of a causal relationship between MD and ED. However, we did not find a causal relationship between BD and ED in European populations.

Relationship between rheumatoid arthritis and cardiovascular comorbidity, causation or co-occurrence: A Mendelian randomization study.

In recent years, the incidence rates of rheumatoid arthritis (RA) and heart disease (HD) have noticeably increased worldwide. Previous studies have found that patients with RA are more likely to develop HD, while the cause and effect have still remained elusive. In this study, Mendelian randomization (MR) analysis was used to indicate whether there was a potential association between RA and HD. Data of RA, ischemic heart disease (IHD), myocardial infarction (MI), atrial fibrillation (AF), and arrhythmia were based on the genome-wide association study (GWAS) dataset. No disease group was intersected. Inverse-variance weighted (IVW) method was used to calculate MR estimates, and sensitivity analysis was performed. The primary MR analysis showed that genetic susceptibility to RA was significantly associated with the risk of IHD and MI, rather than with AF and arrhythmia. Besides, there was no heterogeneity and horizontal pleiotropy between the primary and replicated analyses. There was a significant correlation between RA and the risk of IHD (odds ratio (OR), 1.0006; 95% confidence interval (CI), 1.000244-1.00104; P = 0.001552), meanwhile, there was a significant correlation between RA and the risk of MI (OR, 1.0458; 95% CI, 1.07061-1.05379; P = 0.001636). The results were similar to those of sensitivity analysis, and the sensitivity analysis also verified the conclusion. Furthermore, sensitivity and reverse MR analyses suggested that no heterogeneity, horizontal pleiotropy or reverse causality was found between RA and cardiovascular comorbidity. RA was noted to be causally associated with IHD and MI, rather than with AF and arrhythmia. This MR study might provide a new genetic basis for the causal relationship between RA and the risk of CVD. The findings suggested that the control of RA activity might reduce the risk of cardiovascular disease.

Potential causal association between leisure sedentary behaviors, physical activity and musculoskeletal health: A Mendelian randomization study.

Increasing evidence shows that leisure sedentary behaviors (LSB) and physical activity (PA) are associated with various musculoskeletal disorders. However, the causality between LSB/PA and musculoskeletal health remained unknown. In this study, we aimed to evaluate the causal relationships between LSB/PA and lower back pain (LBP), intervertebral disc disorder (IVDD), rheumatoid arthritis (RA), and bone mineral density (BMD) by using a two-sample Mendelian randomization method. The exposure data were obtained from large-scale genome-wide association studies (GWAS), including the PA dataset (self-reported PA, n = 377,234; accelerometer-assessed PA, n = 91,084) and LSB dataset (n = 422,218). The outcome data were derived from the FinnGen LBP dataset (n = 248,528), FinnGen IVDD dataset (n = 256,896), BMD GWAS dataset (n = 56,284), and RA GWAS dataset (n = 58,284). The causal relationships were estimated with inverse variance weighted (IVW), MR-Egger, and weighted median methods. Sensitivity analyses were performed with Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis to estimate the robustness of our findings. Genetically predicted leisure television watching increased the risk of LBP (OR = 1.68, 95% CI 1.41 to 2.01; P = 8.23×10-9) and IVDD (OR = 1.62, 95% CI 1.37 to 1.91; P = 2.13 × 10-8). In addition, this study revealed a potential causal relationship between computer use and a reduced risk of IVDD (OR = 0.60, 95% CI 0.42 to 0.86; P = 0.005) and RA (OR = 0.28, 95% CI 0.13 to 0.60; P = 0.001). Our results suggest that leisure television watching is a risk factor for LBP and IVDD, whereas leisure computer use may act as a protective factor against IVDD and RA. These findings emphasized the importance of distinguishing between different sedentary behaviors in musculoskeletal disease studies.

Testing relationship between tea intake and the risk of rheumatoid arthritis and systemic lupus erythematosus: a Mendelian randomization study

BackgroundWe performed Mendelian randomization (MR) to assess the causal effect of tea intake on rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE).MethodsGenetic instruments for tea intake were obtained from a large genome-wide association study (GWAS) dataset of the UK Biobank. Genetic association estimates for RA (6236 cases and 147,221 controls) and SLE (538 cases and 213,145 controls) were obtained from the FinnGen study through the IEU GWAS database.ResultsMR analyses using the inverse-variance weighted method showed that tea intake was not associated with risk of RA [odds ratio (OR) per standard deviation increment in genetically predicted tea intake = 0.997, 95% confidence interval (CI) 0.658–1.511] and SLE (OR per standard deviation increment in genetically predicted tea intake = 0.961, 95% CI 0.299–3.092). Weighted median, weighted mode, MR-Egger, leave-one-out and multivariable MR controlling for several confounding factors including current tobacco smoking, coffee intake, and alcoholic drinks per week yielded completely consistent results. No evidence of heterogeneity and pleiotropy was found.ConclusionOur MR study did not suggest a causal effect of genetically predicted tea intake on RA and SLE.

Causal relationship between human blood omega-3 fatty acids and the risk of epilepsy: A two-sample Mendelian randomization study.

Though omega-3 fatty acids reduce seizures in several animal models, considerable controversy exists regarding the association between omega-3 fatty acids and epilepsy in human. To assess whether genetically determined human blood omega-3 fatty acids are causally associated with the risk of epilepsy outcomes. We conducted a two-sample Mendelian randomization (MR) analysis by applying summary statistics of genome-wide association study datasets of both exposure and outcomes. Single nucleotide polymorphisms significantly associated with blood omega-3 fatty acids levels were selected as instrumental variables to estimate the causal effects on epilepsy. Five MR analysis methods were conducted to analyze the final results. The inverse-variance weighted (IVW) method was used as the primary outcome. The other MR analysis methods (MR-Egger, weighted median, simple mode, and weighted mode) were conducted as the complement to IVW. Sensitivity analyses were also conducted to evaluate heterogeneity and pleiotropy. Genetically predicted the increase of human blood omega-3 fatty acids levels was associated with a higher risk of epilepsy (OR = 1.160, 95%CI = 1.051-1.279, P = 0.003). This study revealed a causal relationship between blood omega-3 fatty acids and the risk of epilepsy, thus providing novel insights into the development mechanism of epilepsy.

The causal effect of physical activity intensity on COVID-19 susceptibility, hospitalization, and severity: Evidence from a mendelian randomization study.

The protection of physical activity (PA) against COVID-19 is a rising research interest. However, the role of physical activity intensity on this topic is yet unclear. To bridge the gap, we performed a Mendelian randomization (MR) study to verify the causal influence of light and moderate-to-vigorous PA on COVID-19 susceptibility, hospitalization, and severity. The Genome-Wide Association Study (GWAS) dataset of PA (n = 88,411) was obtained from the UK biobank and the datasets of COVID-19 susceptibility (n = 1,683,768), hospitalization (n = 1,887,658), and severity (n = 1,161,073) were extracted from the COVID-19 Host Genetics Initiative. A random-effect inverse variance weighted (IVW) model was carried out to estimate the potential causal effects. A Bonferroni correction was used for counteracting. The problem of multiple comparisons. MR-Egger test, MR-PRESSO test, Cochran's Q statistic, and Leave-One-Out (LOO) were used as sensitive analysis tools. Eventually, we found that light PA significantly reduced the risk of COVID-19 infection (OR = 0.644, 95% CI: 0.480-0.864, p = 0.003). Suggestive evidence indicated that light PA reduced the risks of COVID-19 hospitalization (OR = 0.446, 95% CI: 0.227 to 0.879, p = 0.020) and severe complications (OR = 0.406, 95% CI: 0.167-0.446, p = 0.046). By comparison, the effects of moderate-to-vigorous PA on the three COVID-19 outcomes were all non-significant. Generally, our findings may offer evidence for prescribing personalized prevention and treatment programs. Limited by the available datasets and the quality of evidence, further research is warranted to re-examine the effects of light PA on COVID-19 when new GWAS datasets emerge.

Effect of C-reactive protein on the risk of Heart failure: a mendelian randomization study

BackgroundTraditional observational studies have shown positive associations between c-reactive protein (CRP) and heart failure (HF) risk. However, this association has not been fully elucidated. Therefore, Mendelian randomization was used to examine CRP’s possible etiological roles with HF.MethodsWe implemented a two-sample Mendelian randomization framework to examine the causality of the association between CRP and HF based on summary statistics by large-scale genome-wide association studies (GWAS) datasets of European ancestry through inverse-variance weighted, weighted median, MREgger regression, and MR-PRESSO methods. The summary statistics dataset on the association of genetic variants with CRP was used from the published GWAS of European descent in UK Biobank participants (N = 427,367) and the CHARGE consortium (N = 575,531). The GWAS dataset used to identify genetic variants underlying HF from the HERMES consortium includes 977,323 participants (47,309 cases and 930,014 controls). The odds ratio (OR) with 95% confidence intervals (CIs) was employed to examine this association.ResultsThe results of our IVW indicated that CRP was strongly associated with HF (OR = 4.18, 95% CI = 3.40–5.13, p < 0.001). The Cochran heterogeneity test showed significant heterogeneity among SNPs of CRP (Q = 317.55, p < 0.001; I2 = 37.6%), and no considerable pleiotropy was detected for the association of CRP with HF [intercept = 0.003; p = 0.234]. This finding remained consistent using different Mendelian randomization methods and sensitivity analyses.ConclusionOur MR study did identify convincing evidence to support CRP associated with HF risk. Human genetic data suggest that CRP is a causative factor in HF. Hence, CRP assessment may offer additional prognostic information as an adjuvant to overall risk assessment in HF patients. These findings prompt significant questions about the function of inflammation in the progression of HF. More research into the role of inflammation in HF is needed to guide trials of anti-inflammation management.

Causal Association between Iritis or Uveitis and Glaucoma: A Two-Sample Mendelian Randomisation Study.

Recent studies have suggested an association between iritis or uveitis and glaucoma. This study investigated the causal relationship between glaucoma and iritis and uveitis as exposures in a multi-ethnic population. Single-nucleotide polymorphisms associated with exposures to iritis and uveitis from the genome-wide association study (GWAS) data of Biobank Japan (BBJ) and the meta-analysis data from BBJ and UK Biobank (UKB) were used as instrumental variables (IVs). The GWAS dataset for glaucoma was extracted from the meta-analysis data (n = 240,302) of Genetic Epidemiology Research in Adult Health and Aging and UKB. The casual estimates were assessed with a two-sample Mendelian randomisation (MR) test using the inverse-variance-weighted (IVW) method, weighted median method, MR-Egger method, and MR-Pleiotropy Residual Sum and Outlier test. The IVW method revealed a significant causal association between iritis and glaucoma using IVs (p < 5.0 × 10-8) from the East Asian population (n = 2) (odds ratio [OR] = 1.01, p = 0.017), a significant association between iritis exposures (p < 5.0 × 10-8) in the multi-ethnic population (n = 11) (OR = 1.04, p = 0.001), and a significant causal association between uveitis exposures (n = 10 with p < 5.0 × 10-8) and glaucoma in the multi-ethnic population (OR = 1.04, p = 0.001). Iritis and uveitis had causal effects on glaucoma risk based on IVs from the multi-ethnic population. These findings imply that the current classifications of uveitic glaucoma and open-angle glaucoma overlap, indicating the need for further investigating these complex relationships.

Mendelian randomization eradicates the causal relationship between educational attainment, household income, and oropharyngeal cancer.

It was reported that educational attainment and household income are associated with oropharyngeal cancer. However, whether such an association is causal is still unknown. The Mendelian randomization (MR) design was performed to disentangle their causal relationship. Initially, genetic variants proxied for educational attainment and household income were extracted from the largest genome-wide association studies (GWAS), and two oropharyngeal GWAS datasets were used in the discovery and validation stages separately. A reverse MR analysis was carried out to judge whether oropharyngeal cancer affects educational attainment and household income. The results from the two stages were combined using meta-analysis. The heterogeneity and horizontal pleiotropy were appraised using several methods. All selected genetic variants were valid. In the discovery stage, genetically elevated years of education might decrease the risk of oropharyngeal cancer (IVW OR = 0.148 [0.025, 0.872], p-value = 0.035), while such a result became insignificant in the validation stage (IVW p-value >0.05). Household income cannot change the risk of oropharyngeal cancer at both stages. The reverse MR suggested that oropharyngeal cancer should slightly alter household income (IVW OR = 1.001 [1.000, 1.003], p-value = 0.036) in the discovery set, but the result cannot be replicated in the validation stage. The meta-analysis did not find any significant results either. The results were also assessed by sensitivity analyses, and there was no heterogeneity or horizontal pleiotropy in the analyses. The statistical powers were all above 80% at the discovery stage. There should be no causal association between educational attainment, household income, and oropharyngeal cancer.

Genetic predisposition to female infertility in relation to epithelial ovarian and endometrial cancers.

The associations between female infertility and epithelial ovarian cancer (EOC) or endometrial cancer (EC) have been reported in observational studies, but its causal relationship remains unknown. We intended to assess the causal effect of female infertility on EOCs and ECs using a two-sample Mendelian Randomization (MR) approach. Large pooled genome-wide association study (GWAS) datasets for female infertility (6481 cases and 68 969 controls), EOC (25 509 cases and 40 941 controls), and EC (12 906 cases and 108 979 controls) were derived from public GWAS databases and published studies. The Inverse Variance Weighted method, Weighted Median method, MR-Egger regression, and MR-Pleiotropy Residual Sum and Outlier test were adopted for MR analyses. Our results suggested that genetically predicted infertility was positively associated with the risk of EOC (OR = 1.117, 95% CI = 1.003-1.245, P = .045), but did not find a causal relationship between infertility and EC (OR = 1.081, 95% CI = 0.954-1.224, P = .223). As to the reverse direction, our study did not obtain evidence from genetics that EOCs (OR = 0.974, 95% CI = 0.825-1.150, P = .755) and ECs (OR = 1.039, 95% CI = 0.917-1.177, P = .548) were associated with an increased risk of infertility. This large MR analysis supported a causal association between female infertility and increased risk of EOCs, but did not find a causal relationship between infertility and ECs.

Roles of gut microbiome in epilepsy risk: A Mendelian randomization study.

Recent studies have suggested an association between gut microbiomes (GMs) and epilepsy. However, the GM taxa identified in different studies are variable. In addition, observational studies cannot indicate causality. Therefore, our study aimed to explore the causal association of GMs with epilepsy and identify the most influential GM taxa. We conducted a Mendelian randomization (MR) study using summary statistics from genome-wide association studies (GWAS) of 211 GM taxa and epilepsy. The GWAS summary statistics for 211 GM taxa (from phylum to genus level) were generated by the MiBioGen consortium, while the FinnGen consortium provided the GWAS summary statistics for epilepsy. The primary analytical method to assess causality was the inverse-variance weighted (IVW) approach. To complement the IVW method, we also applied four additional MR methods: MR-Egger, weighted median, simple mode, and weighted. In addition, we conducted sensitivity analyses using Cochrane's Q-test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis. We evaluated the causal effect of 211 GM taxa (from phylum to genus level) on epilepsy, generalized epilepsy, and focal epilepsy. After using the Bonferroni method for multiple testing correction, Class Betaproteobacteria [odds ratio (OR) = 1.357, 95% confidence interval (CI): 1.126-1.635, p = 0.001] and Order Burkholderiales (OR = 1.336, 95% CI: 1.112-1.606, p = 0.002). In addition, 21 nominally significant causal relationships were also identified. Further, the MR-Egger intercept test and MR-PRESSO global test suggested that our MR analysis was unaffected by horizontal pleiotropy (p > 0.05). Finally, the leave-one-out analysis suggested the robustness of the results. Through the MR study, we analyzed the causal relationship of 211 GM taxa with epilepsy and determined the specific intestinal flora associated with increased epilepsy risk. Our findings may provide helpful biomarkers for disease progression and potential candidate therapeutic targets for epilepsy. In addition, in-depth analysis of large-scale microbiome GWAS datasets based on metagenomics sequencing is necessary for future studies.

Systemic lupus erythematosus is causally associated with hypothyroidism, but not hyperthyroidism: A Mendelian randomization study.

The relationship between systemic lupus erythematosus (SLE) and thyroid diseases is still controversial. Due to confounders and reverse causation, previous studies were not convincing. We aimed to investigate the relationship between SLE and hyperthyroidism or hypothyroidism by Mendelian randomization (MR) analysis. We performed a two-step analysis using bidirectional two-sample univariable and multivariable MR (MVMR) to explore the causality of SLE and hyperthyroidism or hypothyroidism in three genome-wide association studies (GWAS) datasets, including 402,195 samples and 39,831,813 single-nucleotide polymorphisms (SNPs). In the first step analysis, with SLE as exposure and thyroid diseases as outcomes, 38 and 37 independent SNPs strongly (P < 5*10-8) associated with SLE on hyperthyroidism or SLE on hypothyroidism were extracted as valid instrumental variables (IVs). In the second step analysis, with thyroid diseases as exposures and SLE as outcome, 5 and 37 independent SNPs strongly associated with hyperthyroidism on SLE or hypothyroidism on SLE were extracted as valid IVs. In addition, MVMR analysis was performed in the second step analysis to eliminate the interference of SNPs that were strongly associated with both hyperthyroidism and hypothyroidism. 2 and 35 valid IVs for hyperthyroidism on SLE and hypothyroidism on SLE were obtained in MVMR analysis. MR results of two steps analysis were estimated respectively by multiplicative random effects-inverse variance weighted (MRE-IVW), simple mode (SM), weighted median (WME) and MR-Egger regression methods. Sensitivity analysis and visualization of MR results were performed by heterogeneity test, pleiotropy test, leave-one-out test, scatter plots, forest plots and funnel plots. The MRE-IVW method in the first step of MR analysis revealed that SLE was causally associated with hypothyroidism (OR = 1.049, 95% CI = 1.020-1.079, P < 0.001), but not causally associated with hyperthyroidism (OR = 1.045, 95% CI = 0.987-1.107, P = 0.130). In the inverse MR analysis, the MRE-IVW method revealed that both hyperthyroidism (OR = 1.920, 95% CI = 1.310-2.814, P < 0.001) and hypothyroidism (OR = 1.630, 95% CI = 1.125-2.362, P = 0.010) were causally associated with SLE. Results from other MR methods were consistent with MRE-IVW. However, when MVMR analysis was performed, there was no longer a causal relationship of hyperthyroidism on SLE (OR = 1.395, 95% CI = 0.984-1.978, P = 0.061), nor was there a causal relationship of hypothyroidism on SLE (OR = 1.290, 95% CI = 0.823-2.022, P = 0.266). The stability and reliability of the results were confirmed by sensitivity analysis and visualization. Our univariable and multivariable MR analysis revealed that systemic lupus erythematosus was causally associated with hypothyroidism, but did not provided evidence to support a causal relationship of hypothyroidism on SLE or between SLE and hyperthyroidism.

Association between inflammation and cognition: Triangulation of evidence using a population-based cohort and Mendelian randomization analyses

BackgroundInflammation is associated with cognitive functioning and dementia in older adults, but whether inflammation is related to cognitive functioning in youth and whether these associations are causal remains unclear. MethodsIn a population-based cohort (Avon Longitudinal Study of Parents and Children; ALSPAC), we investigated cross-sectional associations of inflammatory markers (C-reactive protein [CRP], Interleukin-6 [IL-6] and Glycoprotein acetyls [GlycA]) with measures of cold (working memory, response inhibition) and hot (emotion recognition) cognition at age 24 (N = 3,305 in multiple imputation models). Furthermore, we conducted one-sample and two-sample bidirectional Mendelian randomization (MR) analyses to examine potential causal effects of genetically-proxied inflammatory markers (CRP, GlycA, IL-6, IL-6 receptor, soluble IL-6 receptor) on cognitive measures (above) and on general cognitive ability. ResultsIn the ALSPAC cohort, there was limited evidence of an association between standardised inflammatory markers and standardised cognitive measures at age 24 after adjusting for potential confounders (N = 3,305; beta range, −0.02 [95 % confidence interval (CI) −0.06 to 0.02, p = 0.27] to 0.02 [95 % CI −0.02 to 0.05, p = 0.33]). Similarly, we found limited evidence of potential effects of 1-unit increase in genetically-proxied inflammatory markers on standardised working memory, emotion recognition or response inhibition in one-sample MR using ALSPAC data (beta range, −0.73 [95 % CI −2.47 to 1.01, p = 0.41] to 0.21 [95 % CI −1.42 to 1.84, p = 0.80]; or on standardised general cognitive ability in two-sample MR using the latest Genome-Wide Association Study (GWAS) datasets (inverse-variance weighted beta range, −0.02 [95 % CI −0.05 to 0.01, p = 0.12] to 0.03 [95 % CI −0.01 to 0.07, p = 0.19]). ConclusionsOur MR findings do not provide strong evidence of a potential causal effect of inflammatory markers (CRP, IL-6, IL-6 receptor, GlycA) on the cognitive functions examined here. Given the large confidence intervals in the one-sample MR, larger GWAS of specific cognitive measures are needed to enable well-powered MR analyses to investigate whether inflammation causally influences specific cognitive domains.

Causal Associations of PM2.5 and GDM: A Two-Sample Mendelian Randomization Study

Epidemiological studies have linked particulate matter (PM2.5) to gestational diabetes mellitus (GDM). However, the causality of this association has not been established; Mendelian randomization was carried out using summary data from genome-wide association studies (GWAS). For the analysis of the causal relationship between PM2.5 and GDM, the inverse variance weighted (IVW) method was used. The exposure data came from a GWAS dataset of IEU analysis of the United Kingdom Biobank phenotypes consisting of 423,796 European participants. The FinnGen consortium provided the GDM data, which included 6033 cases and 123,000 controls. We also performed multivariate MR (MVMR), adjusting for body mass index (BMI) and smoking. As a result, we found that each standard deviation increase in PM2.5 is associated with a 73.6% increase in the risk of GDM (OR: 1.736; 95%CI: 1.226-2.457). Multivariable MR analysis showed that the effect of PM2.5 on GDM remained after accounting for BMI and smoking. Our results demonstrate a causal relationship between PM2.5 and GDM.

Integrating genome-wide association study with regulatory SNP annotations identified novel candidate genes for osteoporosis.

Osteoporosis (OP) is a metabolic bone disease, characterized by a decrease in bone mineral density (BMD). However, the research of regulatory variants has been limited for BMD. In this study, we aimed to explore novel regulatory genetic variants associated with BMD. We conducted an integrative analysis of BMD genome-wide association study (GWAS) and regulatory single nucleotide polymorphism (rSNP) annotation information. Firstly, the discovery GWAS dataset and replication GWAS dataset were integrated with rSNP annotation database to obtain BMD associated SNP regulatory elements and SNP regulatory element-target gene (E-G) pairs, respectively. Then, the common genes were further subjected to HumanNet v2 to explore the biological effects. Through discovery and replication integrative analysis for BMD GWAS and rSNP annotation database, we identified 36 common BMD-associated genes for BMD irrespective of regulatory elements, such as FAM3C (pdiscovery GWAS = 1.21 × 10-25, preplication GWAS = 1.80 × 10-12), CCDC170 (pdiscovery GWAS = 1.23 × 10-11, preplication GWAS = 3.22 × 10-9), and SOX6 (pdiscovery GWAS = 4.41 × 10-15, preplication GWAS = 6.57 × 10-14). Then, for the 36 common target genes, multiple gene ontology (GO) terms were detected for BMD such as positive regulation of cartilage development (p = 9.27 × 10-3) and positive regulation of chondrocyte differentiation (p = 9.27 × 10-3). We explored the potential roles of rSNP in the genetic mechanisms of BMD and identified multiple candidate genes. Our study results support the implication of regulatory genetic variants in the development of OP.

Identification of candidate genes and pathways associated with juvenile idiopathic arthritis by integrative transcriptome-wide association studies and mRNA expression profiles

AimJuvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease of childhood, with genetic susceptibility and pathological processes such as autoimmunity and autoinflammation, but its pathogenesis is unclear. We conducted a transcriptome-wide association study (TWAS) using expression interpolation from a large-scale genome-wide association study (GWAS) dataset to identify genes, biological pathways, and environmental chemicals associated with JIA.MethodsWe obtained published GWAS data on JIA for TWAS and used mRNA expression profiling to validate the genes identified by TWAS. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. A protein–protein interaction (PPI) network was generated, and central genes were obtained using Molecular Complex Detection (MCODE). Finally, chemical gene expression datasets were obtained from the Comparative Toxicogenomics database for chemical genome enrichment analysis.ResultsTWAS identified 1481 genes associated with JIA, and 154 differentially expressed genes were identified based on mRNA expression profiles. After comparing the results of TWAS and mRNA expression profiles, we obtained eight overlapping genes. GO and KEGG enrichment analyses of the genes identified by TWAS yielded 163 pathways, and PPI network analysis as well as MCODE resolution identified a total of eight clusters. Through chemical gene set enrichment analysis, 287 environmental chemicals associated with JIA were identified.ConclusionBy integrating TWAS and mRNA expression profiles, genes, biological pathways, and environmental chemicals associated with JIA were identified. Our findings provide new insights into the pathogenesis of JIA, including candidate genetic and environmental factors contributing to its onset and progression.

Assessing the effect of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes.

Longitudinal changes in brain structure and lifestyle can affect sleep phenotypes. However, the influence of the interaction between longitudinal changes in brain structure and lifestyle on sleep phenotypes remains unclear. Genome-wide association study dataset of longitudinal changes in brain structure was obtained from published study. Phenotypic data of lifestyles and sleep phenotypes were obtained from UK Biobank cohort. Using genotype data from UK Biobank, we calculated polygenetic risk scores of longitudinal changes in brain structure phenotypes. Linear/logistic regression analysis was conducted to evaluate interactions between longitudinal changes in brain structure and lifestyles on sleep duration, chronotype, insomnia, snoring and daytime dozing. Multiple lifestyle × longitudinal changes in brain structure interactions were detected for 5 sleep phenotypes, such as physical activity×caudate_age2 for daytime dozing (OR = 1.0389, P = 8.84 × 10-3) in total samples, coffee intake×cerebellar white matter volume_age2 for daytime dozing (OR = 0.9652, P = 1.13 × 10-4) in females. Besides, we found 4 overlapping interactions in different sleep phenotypes. We conducted sex stratification analysis and identified one overlapping interaction between female and male. Our results support the moderate effects of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes, and deepen our understanding of the pathogenesis of sleep disorders.

Can Intelligence Affect Alcohol-, Smoking-, and Physical Activity-Related Behaviors? A Mendelian Randomization Study

People with high levels of intelligence are more aware of risk factors, therefore choosing a healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies appear to agree and disagree. To cope with the uncertainty, we designed a mendelian randomization (MR) study to examine the causal effects of genetically proxied intelligence on alcohol-, smoking-, and physical activity (PA)-related behaviors. We obtained genome-wide association study (GWAS) datasets concerning these variables from separate studies or biobanks and used inverse-variance weighted (IVW) or MR-Egger estimator to evaluate the causal effects according to an MR protocol. The MR-Egger intercept test, MR-PRESSO, and funnel plots were employed for horizontal pleiotropy diagnosis. The Steiger test (with reliability test), Cochran's Q test, MR-PRESSO, and leave-one-out method were employed for sensitivity analysis. We found significant or potential effects of intelligence on alcohol dependence (OR = 0.749, p = 0.003), mental and behavioral disorders due to alcohol (OR = 0.814, p = 0.009), smoking (OR = 0.585, p = 0.005), and smoking cessation (OR = 1.334, p = 0.001). Meanwhile, we found significant or potential effects on walking duration (B = -0.066, p < 0.001), walking frequency (B = -0.055, p = 0.031), moderate PA frequency (B = -0.131, p < 0.001), and vigorous PA frequency (B = -0.070, p = 0.001), but all in a negative direction. In conclusion, our findings reinforce some existing knowledge, indicate the complexity of the health impacts of human intelligence, and underline the value of smoking and alcohol prevention in less intelligent populations. Given the existing limitations in this study, particularly the potential reverse causality in some estimations, re-examinations are warranted in future research.

The genetic correlation and causal association between key factors that influence vascular calcification and cardiovascular disease incidence.

Serum calcium (Ca), vitamin D (VD), and vitamin K (VK) levels are key determinants of vascular calcification, which itself impacts cardiovascular disease (CVD) risk. The specific relationships between the levels of these different compounds and particular forms of CVD, however, remain to be fully defined. This study was designed to explore the associations between these serum levels and CVDs with the goal of identifying natural interventions capable of controlling vascular calcification and thereby protecting against CVD pathogenesis, extending the healthy lifespan of at-risk individuals. Linkage disequilibrium score (LDSC) regression and a two-sample Mendelian randomization (MR) framework were leveraged to systematically examine the causal interplay between these serum levels and nine forms of CVD, as well as longevity through the use of large publically accessible Genome-Wide Association Studies (GWAS) datasets. The optimal concentrations of serum Ca and VD to lower CVD risk were examined through a restrictive cubic spline (RCS) approach. After Bonferroni correction, the positive genetic correlations were observed between serum Ca levels and myocardial infarction (MI) (p = 1.356E-04), as well as coronary artery disease (CAD) (p = 3.601E-04). Negative genetic correlations were detected between levels of VD and CAD (p = 0.035), while elevated VK1 concentrations were causally associated with heart failure (HF) [odds ratios (OR) per 1-standard deviation (SD) increase: 1.044], large artery stroke (LAS) (OR per 1-SD increase: 1.172), and all stroke (AS) (OR per 1-SD increase: 1.041). Higher serum Ca concentrations (OR per 1-SD increase: 0.865) and VD levels (OR per 1-SD increase: 0.777) were causally associated with reduced odds of longevity. These findings remained consistent in sensitivity analyses, and serum Ca and VD concentrations of 2.376 mmol/L and 46.8 nmol/L, respectively, were associated with a lower CVD risk (p < 0.001). Our findings support a genetic correlation between serum Ca and VD and CVD risk, and a causal relationship between VK1 levels and CVD risk. The optimal serum Ca (2.376 mmol/L) and VD levels (46.8 nmol/L) can reduce cardiovascular risk.

Risk assessment for colorectal cancer via polygenic risk score and lifestyle exposure: a large-scale association study of East Asian and European populations

BackgroundThe genetic architectures of colorectal cancer are distinct across different populations. To date, the majority of polygenic risk scores (PRSs) are derived from European (EUR) populations, which limits their accurate extrapolation to other populations. Here, we aimed to generate a PRS by incorporating East Asian (EAS) and EUR ancestry groups and validate its utility for colorectal cancer risk assessment among different populations.MethodsA large-scale colorectal cancer genome-wide association study (GWAS), harboring 35,145 cases and 288,934 controls from EAS and EUR populations, was used for the EAS-EUR GWAS meta-analysis and the construction of candidate EAS-EUR PRSs via different approaches. The performance of each PRS was then validated in external GWAS datasets of EAS (727 cases and 1452 controls) and EUR (1289 cases and 1284 controls) ancestries, respectively. The optimal PRS was further tested using the UK Biobank longitudinal cohort of 355,543 individuals and ultimately applied to stratify individual risk attached by healthy lifestyle.ResultsIn the meta-analysis across EAS and EUR populations, we identified 48 independent variants beyond genome-wide significance (P < 5 × 10−8) at previously reported loci. Among 26 candidate EAS-EUR PRSs, the PRS-CSx approach-derived PRS (defined as PRSCSx) that harbored genome-wide variants achieved the optimal discriminatory ability in both validation datasets, as well as better performance in the EAS population compared to the PRS derived from known variants. Using the UK Biobank cohort, we further validated a significant dose-response effect of PRSCSx on incident colorectal cancer, in which the risk was 2.11- and 3.88-fold higher in individuals with intermediate and high PRSCSx than in the low score subgroup (Ptrend = 8.15 × 10−53). Notably, the detrimental effect of being at a high genetic risk could be largely attenuated by adherence to a favorable lifestyle, with a 0.53% reduction in 5-year absolute risk.ConclusionsIn summary, we systemically constructed an EAS-EUR PRS to effectively stratify colorectal cancer risk, which highlighted its clinical implication among diverse ancestries. Importantly, these findings also supported that a healthy lifestyle could reduce the genetic impact on incident colorectal cancer.