Revealing an association between HPV and systemic lupus erythematosus: A bidirectional two-sample Mendelian randomization study.

BACKGROUND: An increasing number of studies have focused on the association between Human papillomavirus (HPV) infection and systemic lupus erythematosus (SLE). However, current evidence is largely based on retrospective studies, which are susceptible to confounding factors and cannot establish causation. METHODS: A bidirectional two-sample Mendelian randomization (MR) design was used to evaluate the causal relationship between HPV and SLE. Mononucleoside polymers (SNPS) with strong evidence for genome-wide association studies (GWAS) were selected from the HPV exposure dataset and used as an instrumental variable (IV) for this study. For the MR Analysis results, the MR-Egger intercept P test, MR-Presso global test, CochranQ test and leave-one test were used for sensitivity analysis. RESULTS: Based on the evidence of MR Analysis, this study finally determined that there was no causal association between HPV16 and HPV18 and SLE. CONCLUSIONS: Possible regulation of HPV infection is not significantly associated with regulation of SLE. These findings provide new insights into the underlying mechanisms of HPV and SLE and need to be validated by further studies.

Causal Associations of Cognitive Reserve and Hierarchical Aging-Related Outcomes: A Two-Sample Mendelian Randomization Study.

PURPOSE: Two-sample Mendelian randomization methods were used to explore the causal effects of cognitive reserve proxies, such as educational attainment, occupational attainment, and physical activity (PA), on biological (leukocyte telomere length), phenotypic (sarcopenia-related features), and functional (frailty index and cognitive performance) aging levels. RESULTS: Educational attainment had a potential protective effect on the telomere length (ß = 0.10, 95% CI: 0.08-0.11), sarcopenia-related features (ß = 0.04-0.24, 95% CI: 0.02-0.27), frailty risk (ß = -0.31, 95% CI: -0.33 to -0.28), cognitive performance (ß = 0.77, 95% CI: 0.75-0.80). Occupational attainment was causally related with sarcopenia-related features (ß = 0.07-0.10, 95% CI: 0.05-0.14), and cognitive performance (ß = 0.30, 95% CI: 0.24-0.36). Device-measured PA was potentially associated with one sarcopenia-related feature (ß = 0.14, 95% CI: 0.03-0.25). CONCLUSIONS: Our findings support the potential causality of educational attainment on biological, phenotypic, and functional aging outcomes, of occupational attainment on phenotypic and functional aging-related outcomes, and of PA on phenotypic aging-related outcomes.

Sjögren's syndrome and Parkinson's disease: a bidirectional Mendelian randomization study.

Background: Previous epidemiological studies have reported an association between Sjögren's syndrome (SS) and Parkinson's disease (PD); however, the causality and direction of this relationship remain unclear. In this study, we aimed to investigate the causal relationship between genetically determined SS and the risk of PD using bidirectional Mendelian randomization (MR). Methods: Summary statistics for Sjögren's syndrome used as exposure were obtained from the FinnGen database, comprising 1,290 cases and 213,145 controls. The outcome dataset for PD was derived from the United Kingdom Biobank database, including 6,998 cases and 415,466 controls. Various MR methods, such as inverse variance weighted (IVW), Mendelian randomization Egger regression (MR-Egger), weighted median (WM), simple mode, weighted mode, MR-pleiotropy residual sum and outlier (MR-PRESSO), and robust adjusted profile score (RAPS), were employed to investigate the causal effects of SS on PD. Instrumental variable strength evaluation and sensitivity analyses were conducted to ensure the reliability of the results. In addition, reverse MR analysis was performed to examine the causal effects of PD on SS. Results: The WM, IVW, RAPS and MR-PRESSO methods demonstrated a significant association between genetically predicted SS and reduced risk of PD (odds ratio ORWM = 0.9988, ORIVW = 0.9987, ORRAPS = 0.9987, ORMR-PRESSO = 0.9987, respectively, P < 0.05). None of the MR analyses showed evidence of horizontal pleiotropy (P > 0.05) based on the MR-Egger and MR-PRESSO tests, and there was no statistical heterogeneity in the test results of the MR-Egger and IVW methods. The leave-one-out sensitivity analysis confirmed the robustness of the causal relationship between SS and PD. Furthermore, reverse MR analysis did not support any causal effects of PD on SS. Conclusion: Our MR study supports a potential causal association between SS and a reduced risk of PD. Further extensive clinical investigations and comprehensive fundamental research are warranted to elucidate the underlying mechanisms linking SS and PD.

Decreased Circulating Very Small Low-Density Lipoprotein is Likely Causal for Age-Related Macular Degeneration.

Objective: Abnormal changes in metabolite levels in serum or plasma have been highlighted in several studies in age-related macular degeneration (AMD), the leading cause of irreversible vision loss. Specific changes in lipid profiles are associated with an increased risk of AMD. Metabolites could thus be used to investigate AMD disease mechanisms or incorporated into AMD risk prediction models. However, whether particular metabolites causally affect the disease has yet to be established. Design: A 3-tiered analysis of blood metabolites in the United Kingdom (UK) Biobank cohort to identify metabolites that differ in AMD patients with evidence for a putatively causal role in AMD. Participants: A total of 72 376 donors from the UK Biobank cohort including participants with AMD (N = 1353) and non-AMD controls (N = 71 023). Methods: We analyzed 325 directly measured or derived blood metabolites from the UK Biobank for 72 376 donors to identify AMD-associated metabolites. Genome-wide association studies for 325 metabolites in 98 316 European participants from the UK Biobank were performed. The causal effects of these metabolites in AMD were tested using a 2-sample Mendelian randomization approach. The predictive value of these measurements together with sex and age was assessed by developing a machine learning classifier. Main Outcome Measures: Evaluating metabolic biomarkers associated with AMD susceptibility and investigating their potential causal contribution to the development of the disease. Results: This study noted age to be the prominent risk factor associated with AMD development. While accounting for age and sex, we identified 84 metabolic markers as significantly (false discovery rate-adjusted P value < 0.05) associated with AMD. Lipoprotein subclasses comprised the majority of the AMD-associated metabolites (39%) followed by several lipoprotein to lipid ratios. Nineteen metabolites showed a likely causative role in AMD etiology. Of these, 6 lipoproteins contain very small, very low-density lipoprotein (VLDL), and phospholipids to total lipid ratio in medium VLDL. Based on this we postulate that depletion of circulating very small VLDLs is likely causal for AMD. The risk prediction model constructed from the metabolites, age and sex, identified age as the primary predictive factor with a much smaller contribution by metabolites to AMD risk prediction. Conclusions: This study underscores the pronounced role of lipids in AMD susceptibility and the likely causal contribution of particular subclasses of lipoproteins to AMD. Our study provides valuable insights into the metabopathological mechanisms of AMD disease development and progression.

Mendelian randomization analysis reveals a causal relationship between preterm birth and myopia risk.

Background: Preterm birth has been associated with an increased risk of myopia, but the causal relationship between these two factors remains unclear. Traditional epidemiological studies are limited by confounding factors and reverse causality. Mendelian randomization (MR) analysis, utilizing genetic variants as instrumental variables, provides a robust approach to investigate causal relationships. In this study, we aimed to explore the potential causal link between preterm birth and myopia risk using a two-sample MR analysis strategy. Methods: We conducted a Mendelian randomization study to investigate the causal relationship between preterm birth and myopia risk. Genetic variants (single nucleotide polymorphisms, SNPs) were used as instrumental variables, and summary data from genome-wide association studies (GWAS) were utilized. Four regression models, including MR-Egger regression, weighted median regression, inverse variance weighted regression, and Weighted mode regression, were employed to validate the causal relationship. Sensitivity analysis was performed using the leave-one-out method. At the same time, the funnel diagram and MR-Egger test were used to judge the stability of the research results. Results: The MR analysis revealed a significant causal effect of preterm birth on myopia risk. Both the inverse variance weighted regression and weighted median regression models showed a p-value less than 0.05, indicating a robust association. The risk of myopia increased by approximately 30% for everyone standard deviation increase in preterm birth. Sensitivity analysis, funnel plot and MR-Egger test all confirm the stability of the research results. Conclusion: Our findings provide evidence supporting a causal relationship between preterm birth and myopia risk. Preterm infants are at a higher risk of developing myopia, and this association is not likely to be influenced by confounding factors or reverse causality. The SNP loci rs6699397, rs10871582, and rs2570497 should be closely monitored as they may lead to abnormal concentrations of intraocular cytokines, particularly vascular endothelial growth factor, potentially elucidating one of the pathogenic mechanisms contributing to the higher incidence of myopia in preterm infants. However the complex interconnections involved extend beyond these factors alone.

Primary Aldosteronism and Risk of Cardiovascular Outcomes: Genome-Wide Association and Mendelian Randomization Study.

BACKGROUND: Observational studies have reported associations between primary aldosteronism (PA) and cardiovascular outcomes, including coronary artery diseases (CAD), congestive heart failure (CHF), and stroke. However, establishing causality remains a challenge due to the lack of randomized controlled trial data on this topic. We thus aimed to investigate the causal relationship between PA and the risk of developing CAD, CHF, and stroke. METHODS AND RESULTS: Cross-ancestry meta-analysis of genome-wide association studies combining East Asian and European ancestry (1560 PA cases and 742 139 controls) was conducted to identify single-nucleotide variants that are associated with PA. Then, using the identified genetic variants as instrumental variables, we conducted the 2-sample Mendelian randomization analysis to investigate the causal relationship between PA and incident CAD, CHF, and stroke among both East Asian and European ancestry. Summary association results were extracted from large genome-wide association studies consortia. Our cross-ancestry meta-analysis of East Asian and European populations identified 7 genetic loci significantly associated with the risk of PA, for which the genes nearest to the lead variants were CASZ1, WNT2B, HOTTIP, LSP1, TBX3, RXFP2, and NDP. Among the East Asian population, the pooled odds ratio estimates using these 7 genetic instruments of PA were 1.07 (95% CI, 1.03-1.11) for CAD, 1.10 (95% CI, 1.01-1.20) for CHF, and 1.13 (95% CI, 1.09-1.18) for stroke. The results were consistent among the European population. CONCLUSIONS: Our 2-sample Mendelian randomization study revealed that PA had increased risks of CAD, CHF, and stroke. These findings highlight that early and active screening of PA is critical to prevent future cardiovascular events.

Unraveling the causality between gastroesophageal reflux disease and increased cancer risk: evidence from the UK Biobank and GWAS consortia.

BACKGROUND: Gastroesophageal reflux disease (GERD) is a common condition characterized by the reflux of stomach contents into the esophagus. Despite its widespread prevalence worldwide, the causal link between GERD and various cancer risks has not been fully established, and past medical research has often underestimated or overlooked this relationship. METHODS: This study performed Mendelian randomization (MR) to investigate the causal relationship between GERD and 19 different cancers. We leveraged data from 129,080 GERD patients and 473,524 controls, along with cancer-related data, obtained from the UK Biobank and various Genome-Wide Association Studies (GWAS) consortia. Single nucleotide polymorphisms (SNPs) associated with GERD were used as instrumental variables, utilizing methods such as inverse variance weighting, weighted median, and MR-Egger to address potential pleiotropy and confounding factors. RESULTS: GERD was significantly associated with higher risks of nine types of cancer. Even after adjusting for all known risk factors-including smoking, alcohol consumption, major depression, and body mass index (BMI)-these associations remained significant, with higher risks for most cancers. For example, the adjusted risk for overall lung cancer was (OR, 1.23; 95% CI: 1.14-1.33), for lung adenocarcinoma was (OR, 1.18; 95% CI: 1.03-1.36), for lung squamous cell carcinoma was (OR, 1.35; 95% CI: 1.19-1.53), and for oral cavity and pharyngeal cancer was (OR, 1.73; 95% CI: 1.22-2.44). Especially noteworthy, the risk for esophageal cancer increased to (OR, 2.57; 95% CI: 1.23-5.37). Mediation analyses further highlighted GERD as a significant mediator in the relationships between BMI, smoking, major depression, and cancer risks. CONCLUSIONS: This study identifies a significant causal relationship between GERD and increased cancer risk, highlighting its role in cancer development and underscoring the necessity of incorporating GERD management into cancer prevention strategies.

Causal associations between both psoriasis and psoriatic arthritis and multiple autoimmune diseases: a bidirectional two-sample Mendelian randomization study.

Background: Numerous observational studies have identified associations between both psoriasis (PsO) and psoriatic arthritis (PsA), and autoimmune diseases (AIDs); however, the causality of these associations remains undetermined. Methods: We conducted a bidirectional two-sample Mendelian Randomization study to identify causal associations and directions between both PsO and PsA and AIDs, such as systemic lupus erythematosus (SLE), Crohn's disease (CD), ulcerative colitis (UC), multiple sclerosis (MS), uveitis, bullous pemphigoid (BP), Hashimoto's thyroiditis (HT), rheumatoid arthritis (RA), vitiligo, and ankylosing spondylitis (AS). The causal inferences were drawn by integrating results from four regression models: Inverse Variance Weighting (IVW), MR-Egger, Weighted Median, and Maximum Likelihood. Furthermore, we performed sensitivity analyses to confirm the reliability of our findings. Results: The results showed that CD [IVW odds ratio (ORIVW), 1.11; 95% confidence interval (CI), 1.06-1.17; P = 8.40E-06], vitiligo (ORIVW, 1.16; 95% CI, 1.05-1.28; P = 2.45E-03) were risk factors for PsO, while BP may reduce the incidence of PsO (ORIVW, 0.91; 95% CI, 0.87-0.96; P = 1.26E-04). CD (ORIVW, 1.07; 95% CI, 1.02-1.12; P = 0.01), HT (ORIVW, 1.23; 95% CI, 1.08-1.40; P = 1.43E-03), RA (ORIVW, 1.11; 95% CI, 1.02-1.21, P = 2.05E-02), AS (ORIVW, 2.18; 95% CI, 1.46-3.27; P = 1.55E-04), SLE (ORIVW, 1.04; 95% CI, 1.01-1.08; P = 1.07E-02) and vitiligo (ORIVW, 1.27; 95% CI, 1.14-1.42; P = 2.67E-05) were risk factors for PsA. Sensitivity analyses had validated the reliability of the results. Conclusions: Our study provides evidence for potential causal relationships between certain AIDs and both PsO and PsA. Specifically, CD and vitiligo may increase the risk of developing PsO, while CD, HT, SLE, RA, AS, and vitiligo may elevate the risk for PsA. Additionally, it is crucial to closely monitor the condition of PsO patients with specific AIDs, as they have a higher likelihood of developing PsA than those without AIDs. Moving forward, greater attention should be paid to PsA and further exploration of other PsO subtypes is warranted.

Association between genetically plasma proteins and osteonecrosis: a proteome-wide Mendelian randomization analysis.

Background: Previous studies have explored the role of plasma proteins on osteonecrosis. This Mendelian randomization (MR) study further assessed plasma proteins on osteonecrosis whether a causal relationship exists and provides some evidence of causality. Methods: Summary-level data of 4,907 circulating protein levels were extracted from a large-scale protein quantitative trait loci study including 35,559 individuals by the deCODE Genetics Consortium. The outcome data for osteonecrosis were sourced from the FinnGen study, comprising 1,543 cases and 391,037 controls. MR analysis was conducted to estimate the associations between protein and osteonecrosis risk. Additionally, Phenome-wide MR analysis, and candidate drug prediction were employed to identify potential causal circulating proteins and novel drug targets. Results: We totally assessed the effect of 1,676 plasma proteins on osteonecrosis risk, of which 71 plasma proteins had a suggestive association with outcome risk (P < 0.05). Notably, Heme-binding protein 1 (HEBP1) was significant positively associated with osteonecrosis risk with convening evidence (OR, 1.40, 95% CI, 1.19 to 1.65, P = 3.96 × 10-5, P FDR = 0.044). This association was further confirmed in other MR analysis methods and did not detect heterogeneity and pleiotropy (all P > 0.05). To comprehensively explore the health effect of HEBP1, the phenome-wide MR analysis found it was associated with 136 phenotypes excluding osteonecrosis (P < 0.05). However, no significant association was observed after the false discovery rate adjustment. Conclusion: This comprehensive MR study identifies 71 plasma proteins associated with osteonecrosis, with HEBP1, ITIH1, SMOC1, and CREG1 showing potential as biomarkers of osteonecrosis. Nonetheless, further studies are needed to validate this candidate plasma protein.

Insights into maydis leaf blight resistance in maize: a comprehensive genome-wide association study in sub-tropics of India.

BACKGROUND: In the face of contemporary climatic vulnerabilities and escalating global temperatures, the prevalence of maydis leaf blight (MLB) poses a potential threat to maize production. This study endeavours to discern marker-trait associations and elucidate the candidate genes that underlie resistance to MLB in maize by employing a diverse panel comprising 336 lines. The panel was screening for MLB across four environments, employing standard artificial inoculation techniques. Genome-wide association studies (GWAS) and haplotype analysis were conducted utilizing a total of 128,490 SNPs obtained from genotyping-by-sequencing (GBS). RESULTS: GWAS identified 26 highly significant SNPs associated with MLB resistance, among the markers examined. Seven of these SNPs, reported in novel chromosomal bins (9.06, 5.01, 9.01, 7.04, 4.06, 1.04, and 6.05) were associated with genes: bzip23, NAGS1, CDPK7, aspartic proteinase NEP-2, VQ4, and Wun1, which were characterized for their roles in diminishing fungal activity, fortifying defence mechanisms against necrotrophic pathogens, modulating phyto-hormone signalling, and orchestrating oxidative burst responses. Gene mining approach identified 22 potential candidate genes associated with SNPs due to their functional relevance to resistance against necrotrophic pathogens. Notably, bin 8.06, which hosts five SNPs, showed a connection to defense-regulating genes against MLB, indicating the potential formation of a functional gene cluster that triggers a cascade of reactions against MLB. In silico studies revealed gene expression levels exceeding ten fragments per kilobase million (FPKM) for most genes and demonstrated coexpression among all candidate genes in the coexpression network. Haplotype regression analysis revealed the association of 13 common significant haplotypes at Bonferroni ≤ 0.05. The phenotypic variance explained by these significant haplotypes ranged from low to moderate, suggesting a breeding strategy that combines multiple resistance alleles to enhance resistance to MLB. Additionally, one particular haplotype block (Hap_8.3) was found to consist of two SNPs (S8_152715134, S8_152460815) identified in GWAS with 9.45% variation explained (PVE). CONCLUSION: The identified SNPs/ haplotypes associated with the trait of interest contribute to the enrichment of allelic diversity and hold direct applicability in Genomics Assisted Breeding for enhancing MLB resistance in maize.

Risk factors associated with temporomandibular joint disorder: A mendelian randomization analysis.

BACKGROUND: Temporomandibular joint disorder (TMD), a prevalent orofacial disorder with complex aetiologies and considerable socioeconomic costs. This underscores the critical importance of developing a comprehensive understanding of the risk factors associated with TMD, as existing research is hindered by deficiencies in establishing causal relationships and the limitations of traditional research methodologies. OBJECTIVES: This research explores the causal link between certain risk factors and temporomandibular joint disorder (TMD) through Mendelian randomization (MR), providing multidimensional perspectives in addressing this worldwide health issue. METHODS: Utilizing instrumental variables, we applied advanced statistical methods, including the weighted median, inverse variance weighted (IVW) and MR-Egger, to evaluate the impact of twelve potential risk factors on TMD. RESULTS: Our results identified a significant positive association of TMD with malocclusion (p < .001), sleeping disorders (p = .006), anxiety (p = .002), major depression (p = .0002), daily cigarettes consumption (p = .029) and autoimmune diseases (p = .039). Conversely, a negative association was observed with educational attainment (p = .003). CONCLUSION: These findings suggest that malocclusion, sleeping disorders, anxiety, major depression, daily cigarettes consumption and autoimmune diseases, could potentially increase TMD risk while educational attainment might mitigate its increase. No direct causal relationships were established between serum 25-hydroxyvitamin D levels, menopause, frequent alcohol consumption, coffee intake and severely worn dentition and TMD.

Association between blood metabolites and basal cell carcinoma risk: a two-sample Mendelian randomization study.

Background: Circulating metabolites, which play a crucial role in our health, have been reported to be disordered in basal cell carcinoma (BCC). Despite these findings, evidence is still lacking to determine whether these metabolites directly promote or prevent BCC's progression. Therefore, our study aims to examine the potential effects of circulating metabolites on BCC progression. Material and methods: We conducted a two-sample Mendelian randomization (MR) analysis using data from two separate genome-wide association studies (GWAS). The primary study included data for 123 blood metabolites from a GWAS with 25,000 Finnish individuals, while the secondary study had data for 249 blood metabolites from a GWAS with 114,000 UK Biobank participants.GWAS data for BCC were obtained from the UK Biobank for the primary analysis and the FinnGen consortium for the secondary analysis. Sensitivity analyses were performed to assess heterogeneity and pleiotropy. Results: In the primary analysis, significant causal relationships were found between six metabolic traits and BCC with the inverse variance weighted (IVW) method after multiple testing [P < 4 × 10-4 (0.05/123)]. Four metabolic traits were discovered to be significantly linked with BCC in the secondary analysis, with a significance level of P < 2 × 10-4 (0.05/249). We found that all the significant traits are linked to Polyunsaturated Fatty Acids (PUFAs) and their degree of unsaturation. Conclusion: Our research has revealed a direct link between the susceptibility of BCC and Polyunsaturated Fatty Acids and their degree of unsaturation. This discovery implies screening and prevention of BCC.

Causal association between immune cells and lung cancer risk: a two-sample bidirectional Mendelian randomization analysis.

Background: Previous studies have highlighted the crucial role of immune cells in lung cancer development; however, the direct link between immunophenotypes and lung cancer remains underexplored. Methods: We applied two-sample Mendelian randomization (MR) analysis, using genetic variants as instruments to determine the causal influence of exposures on outcomes. This method, unlike traditional randomized controlled trials (RCTs), leverages genetic variants inherited randomly at conception, thus reducing confounding and preventing reverse causation. Our analysis involved three genome-wide association studies to assess the causal impact of 731 immune cell signatures on lung cancer using genetic instrumental variables (IVs). We initially used the standard inverse variance weighted (IVW) method and further validated our findings with three supplementary MR techniques (MR-Egger, weighted median, and MR-PRESSO) to ensure robustness. We also conducted MR-Egger intercept and Cochran's Q tests to assess heterogeneity and pleiotropy. Additionally, reverse MR analysis was performed to explore potential causality between lung cancer subtypes and identified immunophenotypes, using R software for all statistical calculations. Results: Our MR analysis identified 106 immune signatures significantly associated with lung cancer. Notably, we found five suggestive associations across all sensitivity tests (P<0.05): CD25 on IgD- CD24- cells in small cell lung carcinoma (ORIVW =0.885; 95% CI: 0.798-0.983; P IVW =0.022); CD27 on IgD+ CD24+ cells in lung squamous cell carcinoma (ORIVW =1.054; 95% CI: 1.010-1.100; P IVW =0.015); CCR2 on monocyte cells in lung squamous cell carcinoma (ORIVW =0.941; 95% CI: 0.898-0.987; P IVW =0.012); CD123 on CD62L+ plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) as well as on plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) in lung squamous cell carcinoma. Conclusion: This study establishes a significant genomic link between immune cells and lung cancer, providing a robust basis for future clinical research aimed at lung cancer management.

The Benefits of Permutation-Based Genome-Wide Association Studies.

Linear mixed models (LMMs) are a commonly used method for genome-wide association studies (GWAS) that aim to detect associations between genetic markers and phenotypic measurements in a population of individuals while accounting for population structure and cryptic relatedness. In a standard GWAS, hundreds of thousands to millions of statistical tests are performed, requiring control for multiple hypothesis testing. Typically, static corrections that penalize the number of tests performed are used to control for the family-wise error rate, which is the probability of making at least one false positive. However, it has been shown that in practice this threshold is too conservative for normally distributed phenotypes and not stringent enough for non-normally distributed phenotypes. Therefore, permutation-based LMM approaches have recently been proposed to provide a more realistic threshold that takes phenotypic distributions into account. In this work, we will discuss the advantages of permutation-based GWAS approaches, including new simulations and results from a re-analysis of all publicly available Arabidopsis thaliana phenotypes from the AraPheno database.

Pleiotropic effects on Sarcopenia subphenotypes point to potential molecular markers for the disease.

Sarcopenia is a progressive age-related muscle disease characterized by low muscle strength, quantity and quality, and low physical performance. The clinical overlap between these subphenotypes (reduction in muscle strength, quantity and quality, and physical performance) was evidenced, but the genetic overlap is still poorly investigated. Herein, we investigated whether there is a genetic overlap amongst sarcopenia subphenotypes in the search for more effective molecular markers for this disease. For that, a Bioinformatics approach was used to identify and characterize pleiotropic effects at the genome, loci and gene levels using Genome-wide association study results. As a result, a high genetic correlation was identified between gait speed and muscle strength (rG=0.5358, p=3.39 × 10-8). Using a Pleiotropy-informed conditional and conjunctional false discovery rate method we identified two pleiotropic loci for muscle strength and gait speed, one of them was nearby the gene PHACTR1. Moreover, 11 pleiotropic loci and 25 genes were identified for muscle mass and muscle strength. Lastly, using a gene-based GWAS approach three candidate genes were identified in the overlap of the three Sarcopenia subphenotypes: FTO, RPS10 and CALCR. The current study provides evidence of genetic overlap and pleiotropy among sarcopenia subphenotypes and highlights novel candidate genes and molecular markers associated with the risk of sarcopenia.

Optimal variable identification for accurate detection of causal expression Quantitative Trait Loci with applications in heart-related diseases.

Gene expression plays a pivotal role in various diseases, contributing significantly to their mechanisms. Most GWAS risk loci are in non-coding regions, potentially affecting disease risk by altering gene expression in specific tissues. This expression is notably tissue-specific, with genetic variants substantially influencing it. However, accurately detecting the expression Quantitative Trait Loci (eQTL) is challenging due to limited heritability in gene expression, extensive linkage disequilibrium (LD), and multiple causal variants. The single variant association approach in eQTL analysis is limited by its susceptibility to capture the combined effects of multiple variants, and a bias towards common variants, underscoring the need for a more robust method to accurately identify causal eQTL variants. To address this, we developed an algorithm, CausalEQTL, which integrates L 0 +L 1 penalized regression with an ensemble approach to localize eQTL, thereby enhancing prediction performance precisely. Our results demonstrate that CausalEQTL outperforms traditional models, including LASSO, Elastic Net, Ridge, in terms of power and overall performance. Furthermore, analysis of heart tissue data from the GTEx project revealed that eQTL sites identified by our algorithm provide deeper insights into heart-related tissue eQTL detection. This advancement in eQTL mapping promises to improve our understanding of the genetic basis of tissue-specific gene expression and its implications in disease. The source code and identified causal eQTLs for CausalEQTL are available on GitHub: https://github.com/zhc-moushang/CausalEQTL.

Utility of polygenic risk scores to aid in the diagnosis of rheumatic diseases.

Rheumatic diseases (RDs) are characterized by autoimmunity and autoinflammation and are recognized as complex due to the interplay of multiple genetic, environmental, and lifestyle factors in their pathogenesis. The rapid advancement of genome-wide association studies (GWASs) has enabled the identification of numerous single nucleotide polymorphisms (SNPs) associated with RD susceptibility. Based on these SNPs, polygenic risk scores (PRSs) have emerged as promising tools for quantifying genetic risk in this disease group. This chapter reviews the current status of PRSs in assessing the risk of RDs and discusses their potential to improve the accuracy of the diagnosis of these complex diseases through their ability to discriminate among different RDs. PRSs demonstrate a high discriminatory capacity for various RDs and show potential clinical utility. As GWASs continue to evolve, PRSs are expected to enable more precise risk stratification by integrating genetic, environmental, and lifestyle factors, thereby refining individual risk predictions and advancing disease management strategies.

Regulation of MicroRNA-4697-3p by Parkinson's disease-associated SNP rs329648 and its impact on SNCA112 mRNA.

BACKGROUND: Parkinson's disease (PD) is a common neurodegenerative disorder characterized by a multifaceted genetic foundation. Genome-Wide Association Studies (GWAS) have played a crucial role in pinpointing genetic variants linked to PD susceptibility. Current study aims to delve into the mechanistic aspects through which the PD-associated Single Nucleotide Polymorphism (SNP) rs329648, identified in prior GWAS, influences the pathogenesis of PD. METHODS AND RESULTS: Employing the CRISPR/Cas9-mediated genome editing mechanism, we demonstrated the association of the disease-associated allele of rs329648 with increased expression of miR-4697-3p in differentiated SH-SY5Y cells. We revealed that miR-4697-3p contributes to the formation of high molecular weight complexes of α-Synuclein (α-Syn), indicative of α-Syn aggregate formation, as evidenced by Western blot analysis. Furthermore, our study unveiled that miR-4697-3p elevates SNCA112 mRNA levels. The resultant protein product, α-Syn 112, a variant of α-Syn with 112 amino acids, is recognized for augmenting α-Syn aggregation. Notably, this regulatory effect minimally impacts the levels of full-length SNCA140 mRNA, as evidenced by qRT-PCR. Additionally, we observed a correlation between the disease-associated allele and miR-4697-3p with increased cell death, substantiated by assessments including cell viability assays, alterations in cell morphology, and TUNEL assays. CONCLUSION: Our research reveals that the disease-associated allele of rs329648 is linked to higher levels of miR-4697-3p. This increase in miR-4697-3p leads to elevated SNCA112 mRNA levels, consequently promoting the formation of α-Syn aggregates. Furthermore, miR-4697-3p appears to play a role in increased cell death, potentially contributing to the pathogenesis of PD.

PYPE: A pipeline for phenome-wide association and Mendelian randomization in investigator-driven biobank scale analysis.

Phenome-wide association studies (PheWASs) serve as a way of documenting the relationship between genotypes and multiple phenotypes, helping to uncover unexplored genotype-phenotype associations (known as pleiotropy). Secondly, Mendelian randomization (MR) can be harnessed to make causal statements about a pair of phenotypes by comparing their genetic architecture. Thus, approaches that automate both PheWASs and MR can enhance biobank-scale analyses, circumventing the need for multiple tools by providing a comprehensive, end-to-end tool to drive scientific discovery. To this end, we present PYPE, a Python pipeline for running, visualizing, and interpreting PheWASs. PYPE utilizes input genotype or phenotype files to automatically estimate associations between the chosen independent variables and phenotypes. PYPE can also produce a variety of visualizations and can be used to identify nearby genes and functional consequences of significant associations. Finally, PYPE can identify possible causal relationships between phenotypes using MR under a variety of causal effect modeling scenarios.