Genome-wide Association Data Research Articles

Hypnotic use and the risk of cardiovascular diseases in insomnia patients

Abstract Background Insomnia, commonly treated with hypnotic agents, is an independent risk factor of cardiovascular diseases. Previous research demonstrated the detrimental effect of hypnotics on the prognosis of cardiovascular patients. Purpose We aimed to examine the association between hypnotic agents and cardiovascular outcomes in general individuals with insomnia. Methods In a propensity score matched cohort of UK Biobank (UKB) participants with insomnia, Cox proportional hazard model was used to estimate the association between regular use of hypnotic agents and predetermined cardiovascular outcomes including incident coronary heart diseases (CHD), heart failure (HF), stroke, and cardiovascular death. Inverse probability of treatment weighting and competing risk models were further performed during sensitivity analysis. Drug-target Mendelian randomization (MR) analyses were employed for further evaluation of hypnotics-related genes and cardiovascular disease association. The genome-wide association data of CHD, HF, and stroke were there large-scale genome-wide association analyses. Tissue-specified expression quantitative trait loci (eQTL) data was derived from BrainSeq phase II. Results During a median follow-up of 14.3 years, the matched cohort documented a total of 1,019 CHD cases, 406 HF cases, 285 stroke cases, and 197 cardiovascular deaths. No significant association was detected between Z-meds and CHD, stroke, and cardiovascular mortality. Benzodiazepine use was significantly associated with the increased risk of CHD, HF, and cardiovascular mortality (Figure 1). The inverse probability of treatment weighting and competing risk models didn’t alter the above associations. Moreover, drug-target MR analyses corroborated the safety of Z-meds in the general population regarding cardiovascular health. However, GABRG1—a drug target for benzodiazepines—was associated with heightened risks for heart failure, and ischemic stroke (Figure 2). Conclusions Our findings suggested the heterogeneous associations between different categories of hypnotics and incident cardiovascular events in individuals with insomnia. Z-meds are safe regarding the risk of cardiovascular outcomes in the UKB population with insomnia.Figure 1Figure 2

Identification of immune traits associated with neurodevelopmental disorders by two-sample Mendelian randomization analysis

BackgroundOne of the main causes of health-related issues in children is neurodevelopmental disorders (NDDs), which include attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and Tourette syndrome (TS). Nonetheless, there is relatively little prior research looking at the link between immunological inflammation and NDDs. Our work uses a two-sample Mendelian Randomization (MR) approach to provide a thorough evaluation of the causal effects of immune traits on ADHD, ASD, and TS.MethodsAs exposures, 731 immunological traits’ genetic associations were chosen, and the outcomes were genome-wide association data for ADHD, ASD, and TS. The inverse-variance weighted (IVW), weighted median (WM), and MR-Egger methods were used to conduct MR analysis. The results’ robustness, heterogeneity, and horizontal pleiotropy were confirmed using extensive sensitivity analysis.ResultsWith single-nucleotide polymorphisms serving as instruments and false discovery rate (FDR) correction applied, the study found that significantly higher expression of CD62L on CD62L+ myeloid DC (IVW, OR: 0.926, 95% CI 0.896~0.958, P = 9.42 × 10–6, FDR = 0.007) and suggestively higher absolute cell count (AC) of CD28 + DN (CD4-CD8-) (IVW, OR: 0.852, 95% CI = 0.780 ∼ 0.932, P-value = 4.65 × 10−4, FDR = 0.170) was associated with a lower risk of ADHD. There was no pleiotropy, and the causal relationships were strong according to sensitivity, leave-one-out, and MR-Steiger directionality tests. For ASD and TS, no harmful or protective immune traits were observed.ConclusionsThe results of the study lend credence to the theory that deficiency in CD62L on CD62L+ myeloid DC and CD28 + DN (CD4-CD8) AC may contribute to the onset of ADHD.

Causal and mediating effects of lipid and facial aging: association study integrating GWAS, eQTL, mQTL, and pQTL data

BackgroundIncreasing evidence suggests a potential causal association between lipid levels and facial aging. The aim of this study was to investigate the relationship between levels of specific lipids and facial aging via Mendelian randomization methods. Additionally, this study aimed to identify mediators and explore relevant genes and drug targets.MethodsIn this study, genome-wide association data on plasma lipids from 7,174 Finnish individuals in the UK Biobank were used. Two-sample Mendelian randomization was applied to assess the causal effects of specific lipids on facial aging. Sensitivity and pleiotropy analyses were conducted to ensure the robustness and reliability of the results. Multivariate Mendelian randomization was conducted to account for the potential impact of confounding factors. Furthermore, summary-data-based Mendelian randomization was used to identify relevant genes, which were validated through multiomics data. Finally, drug‒gene interactions were explored via molecular docking techniques.ResultsTwo-sample Mendelian randomization analysis revealed a causal relationship between lipid levels and facial aging. According to the multivariate Mendelian randomization results, smoking was found to mediate this association, and these lipids remained significantly associated with facial aging, even after accounting for environmental confounders. Using summary-data-based Mendelian randomization, CYP21A2, CCND1, PSMA4, and MED1 were identified as potential gene targets, with MED1 further validated through pQTL and mQTL data. Additionally, the MED1 protein was found to bind spontaneously with astragalin, fenofibrate, and ginsenoside.ConclusionsThe results revealed a causal relationship between lipid levels and facial aging, revealing key gene targets that were still significantly associated with facial aging after controlling for environmental confounders. Additionally, the interactions between MED1 and certain drugs may indicate potential pathways for therapeutic interventions related to facial aging.

A multi-omics study of brain tissue transcription and DNA methylation revealing the genetic pathogenesis of ADHD.

Attention-deficit/hyperactivity disorder (ADHD) is a chronic psychiatric disease that often affects a patient's whole life. Research has found that genetics plays an important role in the development of ADHD. However, there is still a lack of knowledge about the tissue-specific causal effects of biological processes beyond gene expression, such as alternative splicing (AS) and DNA methylation (DNAm), on ADHD. In this paper, a multi-omics study was conducted to investigate the causal effects of the transcription and the DNAm on ADHD, by integrating ADHD genome-wide association data with quantitative trait loci data of gene expression, AS, and DNAm across 14 different brain tissues. The causal effects were estimated using four different two-sample Mendelian randomization methods. Finally, we also prioritized the expression of 866 genes showing significant causal effects, including COMMD5, ENSG00000271904, HYAL3, etc., within at least one brain tissue. We prioritized 966 unique genes that have statistically significant causal AS events, within at least one of the 14 different brain tissues. These genes include PPP1R16A, GGT7, TREM2, etc. Furthermore, through mediation analysis, 106 regulatory pathways were inferred where DNAm influences ADHD through gene expression or AS processes. Our research findings provide guidance for future experimental studies on the molecular mechanisms of ADHD development, and also put forward valuable knowledge for the prevention, diagnosis, and treatment of ADHD.

The relationship between mental health problems and risk of infectious diseases: A Mendelian randomization analysis.

The causal effects of mental health problems on the risk of infectious diseases remain vague. Investigating them via observational study is challenging as it presents possible confounding factors. Therefore, the objective of this study was to utilize Mendelian randomization (MR) techniques to evaluate the causal relationship between mental health problems and the risk of infectious diseases. Multivariable MR analyses were performed using genome-wide association data for sleep disorders (N = 216,700), depression (N = 500,199), anxiety (N = 290,361), nervous feelings (N = 450,700), unspecified mental disorder (N = 218,792), pneumonia (N = 486,484), skin and subcutaneous tissue infection (SSTI; N = 218,792), intestinal infectious diseases (IIDs; N = 218,792), urinary tract infection (N = 463,010), and central nervous system (CNS) infections (N = 218,792) among individuals of European ancestry. Independent genetic variants significantly (P < 10-8) associated with each exposure were considered instruments. The primary analysis used an inverse variance-weighted method, followed by a series of sensitivity analyses. Genetically predicted sleep disorders were associated with an increased risk of SSTI (odds ratio [OR], 1.29 [95% confidence interval (CI), 1.05-1.59]; P = .017). Genetically predicted depression was linked with an increased risk of CNS infections (OR, 1.59 [95% CI, 1.00-2.53]; P = .049) and SSTI (1.24 [95% CI, 1.03-1.49]; P = .024). Genetically predicted anxiety was associated with IIDs (OR, 1.19 [95% CI, 1.03-1.37]; P = .017) and SSTI (OR, 1.21 [95% CI, 1.02-1.43]; P = .029). There was no significant causal evidence for genetic prediction of nervous feelings and unspecified mental disorders in IIDs, CNS infections, SSTI, pneumonia, or urinary tract infection. Sensitivity analyses showed that the above causal association estimates were robust. In this MR study, we demonstrated a causal relationship between sleep disorders, depression, anxiety, and the risk of infectious diseases. However, no evidence was found to support causality between nervous feelings, unspecified mental disorders, and the risk of infectious diseases.

Hypothyroidism and dermato/polymyositis: a two-sample Mendelian randomization study.

Observational studies have revealed a higher probability of hypothyroidism in patients with dermatomyositis (DM) or polymyositis (PM), but there is no consensus on whether hypothyroidism causally influences DM or PM. In the present study, we assessed the causal association between hypothyroidism and the risk of dermatomyositis or polymyositis using two-sample Mendelian randomization (TSMR). The genome-wide association data of hypothyroidism and dermatomyositis/polymyositis were obtained from the IEU Open GWAS project. Then, TSMR was used to determine whether hypothyroidism is causally associated with DM or PM. Single-nucleotide polymorphisms (SNPs) significantly associated with hypothyroidism were identified and used as instrumental variables (IVs), and the causal relationship between hypothyroidism and DM/PM was examined using TSMR. MR pleiotropy and Cochran's Q test were used to confirm the heterogeneity and pleiotropy of identified IVs, then four different models, including the inverse variance weighted model (IVW), MR-Egger, weighted median and weighted model were applied in this MR analysis. Sixty-eight SNPs for DM and 68 SNPs for PM were selected as the IVs (P<5×10-8; linkage disequilibrium R2 <0.001) to assess the causal association between hypothyroidism and DM/PM selected from GWASs on hypothyroidism. The results revealed a positive causal effect of hypothyroidism on both DM and PM (DM: OR 2.563, 95% CI [1.348, 4.874], P = 0.00156; PM: OR1.709, 95% CI [1.157, 2.525], P =0.007). Moreover, there was no heterogeneity or pleiotropy in the results. In conclusion, the MR analysis results provided strong evidence to indicate that hypothyroidism might be causally associated with DM and PM. These findings may have important implications for the pathogenesis and possible future therapies of DM/PM.

Plasma Proteomes and Genome-Wide Association Data for Causal Protein Identification in Stroke.

Plasma proteins are promising biomarkers and potential drug targets for stroke. This study aimed to explore whether there is a causal relationship between plasma proteins and subtypes of stroke using a Mendelian randomization (MR) approach. A two-sample bidirectional Mendelian randomization approach was employed to investigate the causal link between plasma proteins and stroke. Data on plasma proteins were obtained from three studies, including INTERVAL, and pooled stroke information was sourced from the MEGASTROKE consortium and the UK Biobank dataset, covering four subtypes of stroke. MR analyses were primarily conducted using inverse variance weighting, and sensitivity analyses were also performed. Finally, potential reverse causality was assessed using bidirectional MR. We identified two proteins causally associated with stroke: one as a potential therapeutic target and another as a protective factor. CXCL8 was found to be positively associated with the risk of developing large-artery atherosclerotic (LAA) stroke (OR, 1.005; 95% CI 1.001 to 1.010; p = 0.022), whereas TNFRSF11b was negatively correlated with the risk of developing LAA stroke (OR, 0.937; 95% CI 0.892 to 0.984; p = 0.010), independently of other stroke subtypes. Reverse bivariate analysis did not indicate that ischemic stroke was causally associated with CXCL8 and TNFRSF11b. There is a causal relationship between CXCL8 and TNFRSF11b with LAA stroke, independent of other subtypes. This study offers a new perspective on the genetics of stroke.

Revealing the link between gut microbiota and brain tumor risk: a new perspective from Mendelian randomization.

Recent studies have shown that gut microbiota may be related to the occurrence of brain tumors, but direct evidence is lacking. This study used the Mendelian randomization study (MR) method to explore the potential causal link between gut microbiota and brain tumors. We analyzed the genome-wide association data between 211 gut microbiota taxa and brain tumors, using the largest existing gut microbiota Genome-Wide Association Studies meta-analysis data (n=13266) and combining it with brain tumor data in the IEU OpenGWAS database. We use inverse-variance weighted analysis, supplemented by methods such as Mendelian randomization-Egger regression, weighted median estimator, simple mode, and weighted mode, to assess causality. In addition, we also conducted the Mendelian randomization-Egger intercept test, Cochran's Q test, and Mendelian randomization Steiger directionality test to ensure the accuracy of the analysis. Quality control includes sensitivity analysis, horizontal gene pleiotropy test, heterogeneity test, and MR Steiger directionality test. Our study found that specific gut microbial taxa, such as order Lactobacillales and family Clostridiaceae1, were positively correlated with the occurrence of brain tumors, while genus Defluviitaleaceae UCG011 and genus Flavonifractor were negatively correlated with the occurrence of brain tumors. The Mendelian randomization-Egger intercept test showed that our analysis was not affected by pleiotropy (P>0.05). This study reveals for the first time the potential causal relationship between gut microbiota and brain tumors, providing a new perspective for the prevention and treatment of early brain tumors. These findings may help develop new clinical intervention strategies and point the way for future research.

Causal association between brain structure and obstructive sleep apnea: A mendelian randomization study

ObjectivePrevious studies have reported contradictory findings regarding the relationship between obstructive sleep apnea (OSA) and abnormal brain morphology. Furthermore, the causal relationship between OSA and brain morphology has not been clearly established. The aim of this study was to utilize Mendelian randomization (MR) analysis to investigate the impact of obstructive sleep apnea (OSA) on brain morphology and determine its potential causal relationship. MethodsFirstly, the inverse-variance weighted (IVW) method was employed to assess the causal effects of OSA on cortical surface area and brain structure volume. Additionally, two additional MR methods, namely weighted median and MR-Egger, were used to supplement the results from IVW. Subsequently, a reverse MR analysis was conducted to determine the direction of causality. Furthermore, sensitivity analyses were performed including Cochrane's Q test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis. ResultsThe results of the study showed that OSA patients had a tendency towards decreased cortical surface area and hippocampal volume in the precuneus region compared to individuals without OSA, while the superior temporal cortical surface area showed an increase. The results from the weighted median and MR-Egger analyses were consistent with those from the IVW analysis. Sensitivity tests confirmed the reliability of the causal estimates. ConclusionsThis study provides preliminary evidence of an association between OSA and brain structure using large-scale genome-wide association data. The results demonstrate that OSA is associated with changes in brain structure. Therefore, individuals with OSA should be vigilant about the risks of related diseases due to alterations in brain tissue.

GWAS-based polygenic risk scoring for predicting cerebral artery dissection in the Chinese population

ObjectiveCerebral artery dissection (CeAD) is a rare but serious disease. Genetic risk assessment for CeAD is lacking in Chinese population. We performed genome-wide association study (GWAS) and computed polygenic risk score (PRS) to explore genetic susceptibility factors and prediction model of CeAD based on patients in Huashan Hospital.MethodsA total of 210 CeAD patients and 280 controls were enrolled from June 2017 to September 2022 in Department of Neurology, Huashan Hospital, Fudan University. We performed GWAS to identify genetic variants associated with CeAD in 140 CeAD patients and 210 control individuals according to a case and control 1:1.5 design rule in the training dataset, while the other 70 patients with CeAD and 70 controls were used as validation. Then Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses were utilized to identify the significant pathways. We constructed a PRS by capturing all independent GWAS SNPs in the analysis and explored the predictivity of PRS, age, and sex for CeAD.ResultsThrough GWAS analysis of the 140 cases and 210 controls in the training dataset, we identified 13 leading SNPs associated with CeAD at a genome-wide significance level of P < 5 × 10− 8. Among them, 10 SNPs were annotated in or near (in the upstream and downstream regions of ± 500Kb) 10 functional genes. rs34508376 (OR2L13) played a suggestive role in CeAD pathophysiology which was in line with previous observations in aortic aneurysms. The other nine genes were first-time associations in CeAD cases. GO enrichment analyses showed that these 10 genes have known roles in 20 important GO terms clustered into two groups: (1) cellular biological processes (BP); (2) molecular function (MF). We used genome-wide association data to compute PRS including 32 independent SNPs and constructed predictive model for CeAD by using age, sex and PRS as predictors both in training and validation test. The area under curve (AUC) of PRS predictive model for CeAD reached 99% and 95% in the training test and validation test respectively, which were significantly larger than the age and sex models of 83% and 86%.ConclusionsOur study showed that ten risk loci were associated with CeAD susceptibility, and annotated functional genes had roles in 20 important GO terms clustered into biological process and molecular function. The PRS derived from risk variants was associated with CeAD incidence after adjusting for age and sex both in training test and validation.

Nonadditive Effects of Common Genetic Variants Have a Negligent Contribution to Cancer Heritability.

Contribution of dominance effects to cancer heritability is unknown. We leveraged existing genome-wide association data for seven cancers to estimate the contribution of dominance effects to the heritability of individual cancer types. We estimated the proportion of phenotypic variation caused by dominance genetic effects using genome-wide association data for seven cancers (breast, colorectal, lung, melanoma, nonmelanoma skin, ovarian, and prostate) in a total of 166,772 cases and 284,824 controls. We observed no evidence of a meaningful contribution of dominance effects to cancer heritability. By contrast, additive effects ranged between 0.11 and 0.34. In line with studies of other human traits, the dominance effects of common genetic variants play a minimal role in cancer etiology. These results support the assumption of an additive inheritance model when conducting cancer association studies with common genetic variants.

Integrating plasma proteomics with genome-wide association data to identify novel drug targets for inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic disease that includes Crohn’s disease (CD) and ulcerative colitis (UC). Although genome-wide association studies (GWASs) have identified many relevant genetic risk loci, the impact of these loci on protein abundance and their potential utility as clinical therapeutic targets remain uncertain. Therefore, this study aimed to investigate the pathogenesis of IBD and identify effective therapeutic targets through a comprehensive and integrated analysis. We systematically integrated GWAS data related to IBD, UC and CD (N = 25,305) by the study of de Lange KM with the human blood proteome (N = 7213) by the Atherosclerosis Risk in Communities (ARIC) study. Proteome-wide association study (PWAS), mendelian randomisation (MR) and Bayesian colocalisation analysis were used to identify proteins contributing to the risk of IBD. Integrative analysis revealed that genetic variations in IBD, UC and CD affected the abundance of five (ERAP2, RIPK2, TALDO1, CADM2 and RHOC), three (VSIR, HGFAC and CADM2) and two (MST1 and FLRT3) cis-regulated plasma proteins, respectively (P < 0.05). Among the proteins identified via Bayesian colocalisation analysis, CADM2 was found to be an important common protein between IBD and UC. A drug and five druggable target genes were identified from DGIdb after Bayesian colocalisation analysis. Our study's findings from genetic and proteomic approaches have identified compelling proteins that may serve as important leads for future functional studies and potential drug targets for IBD (UC and CD).

Mendelian randomization analysis reveals higher whole body water mass may increase risk of bacterial infections

Background and purposeThe association of water loading with several infections remains unclear. Observational studies are hard to investigate definitively due to potential confounders. In this study, we employed Mendelian randomization (MR) analysis to assess the association between genetically predicted whole body water mass (BWM) and several infections.MethodsBWM levels were predicted among 331,315 Europeans in UK Biobank using 418 SNPs associated with BWM. For outcomes, we used genome-wide association data from the UK Biobank and FinnGen consortium, including sepsis, pneumonia, intestinal infections, urinary tract infections (UTIs) and skin and soft tissue infections (SSTIs). Inverse-variance weighted MR analyses as well as a series of sensitivity analyses were conducted.ResultsGenetic prediction of BWM is associated with an increased risk of sepsis (OR 1.34; 95% CI 1.19 to 1.51; P = 1.57 × 10− 6), pneumonia (OR: 1.17; 95% CI 1.08 to 1.29; P = 3.53 × 10− 4), UTIs (OR: 1.26; 95% CI 1.16 to 1.37; P = 6.29 × 10− 8), and SSTIs (OR: 1.57; 95% CI 1.25 to 1.96; P = 7.35 × 10− 5). In the sepsis and pneumonia subgroup analyses, the relationship between BWM and infection was observed in bacterial but not in viral infections. Suggestive evidence suggests that BWM has an effect on viral intestinal infections (OR: 0.86; 95% CI 0.75 to 0.99; P = 0.03). There is limited evidence of an association between BWM levels and bacteria intestinal infections, and genitourinary tract infection (GUI) in pregnancy. In addition, MR analyses supported the risk of BWM for several edematous diseases. However, multivariable MR analysis shows that the associations of BWM with sepsis, pneumonia, UTIs and SSTIs remains unaffected when accounting for these traits.ConclusionsIn this study, the causal relationship between BWM and infectious diseases was systematically investigated. Further prospective studies are necessary to validate these findings.

Integrating molecular pathway with genome-wide association data for causality identification in breast cancer

ObjectiveThe study purpose was to explore the causal association between pyruvate metabolism and breast cancer (BC), as well as the molecular role of key metabolic genes, by using bioinformatics and Mendelian randomization (MR) analysis.MethodsWe retrieved and examined diverse datasets from the GEO database to ascertain differentially acting genes (DAGs) in BC via differential expression analysis. Following this, we performed functional and pathway enrichment analyses to ascertain noteworthy molecular functions and metabolic pathways in BC. Employing MR analysis, we established a causal association between pyruvate metabolism and the susceptibility to BC. Additionally, utilizing the DGIdb database, we identified potential targeted medications that act on genes implicated in the pyruvate metabolic pathway and formulated a competing endogenous RNA (ceRNA) regulatory network in BC.ResultsWe collected the datasets GSE54002, GSE70947, and GSE22820, and identified a total of 1127 DEGs between the BC and NC groups. GO and KEGG enrichment analysis showed that the molecular functions of these DEGs mainly included mitotic nuclear division, extracellular matrix, signaling receptor activator activity, etc. Metabolic pathways were mainly concentrated in PI3K−Akt signaling pathway, Cytokine−cytokine receptor binding and Pyruvate, Tyrosine, Propanoate and Phenylalanine metabolism, etc. In addition, MR analysis demonstrated a causal relationship between pyruvate metabolism and BC risk. Finally, we constructed a regulatory network between pathway genes (ADH1B, ACSS2, ACACB, ADH1A, ALDH2, and ADH1C) and targeted drugs, as well as a ceRNA (lncRNA-miRNA-mRNA) regulatory network for BC, further revealing their interactions.ConclusionsOur research revealed a causal association between pyruvate metabolism and BC risk, found that ADH1B, ACSS2, ACACB, ADH1A, ALDH2, and ADH1C takes place an important part in the development of BC in the molecular mechanisms related to pyruvate metabolism, and identified some potential targeted small molecule drugs.

Identification of Novel Protein Biomarkers and Drug Targets for Acne Vulgaris by Integrating Human Plasma Proteome with Genome-Wide Association Data.

Despite the availability of numerous therapies, the treatment of acne vulgaris remains challenging. Novel drug targets for acne vulgaris are still needed. We conducted a Mendelian randomization analysis to explore possible drug targets for acne vulgaris. We utilized summary statistics obtained from the dataset of acne vulgaris, including 399,413 individuals of European ancestry. We gathered genetic instruments for 566 plasma proteins from genome-wide association studies. In order to strengthen the findings from Mendelian randomization, various methods were employed, including bidirectional Mendelian randomization analysis, Bayesian co-localization, phenotype scanning, and single-cell analysis. These methods facilitated the identification of reverse causality, the search for reported variant-trait associations, and the determination of the cell types that is the primary source of protein. Furthermore, using the plasma proteins in the deCODE cohort, we conducted a replication of the Mendelian randomization analysis as an external validation. At the significance level of Bonferroni (P < 8.83×10-5), a protein-acne pair was discovered through Mendelian randomization analysis. In plasma, increasing TIMP4 (OR = 1.15; 95% CI, 1.09-1.21; P = 1.01×10-7) increased the risk of acne vulgaris. The absence of reverse causality was observed in the TIMP4 protein. According to Bayesian co-localization analysis, TIMP4 shared the same variant with acne vulgaris (PPH4 = 0.93). TIMP4 was replicated in deCODE cohort (OR = 1.17; 95% CI, 1.10-1.24; P = 1.48×10-7). Single-cell analysis revealed that TIMP4 was predominantly detected in myeloid cells in blood, and was detected in almost all cell types in skin tissue. The integrative analysis revealed that the level of plasma TIMP4 has a direct influence on the risk of developing acne vulgaris. This implies that TIMP4 protein could serve as a potential target for the development of drugs aimed at treating acne vulgaris.

Diabetes, glycemic profile and risk of vitiligo: A Mendelian randomization study.

Previous observational studies have shown that vitiligo usually co-manifests with a variety of dysglycemic diseases, such as Type 1 diabetes mellitus (T1DM) and Type 2 diabetes mellitus (T2DM). Mendelian randomization (MR) analysis was performed to further evaluate the causal association between fasting plasma glucose, glycosylated hemoglobin (HbA1c), T1DM, T2DM and vitiligo. We used aggregated genome-wide association data from the Integrative Epidemiology Unit (IEU) online database of European adults vitiligo; HbA1c data were from IEU. Fasting blood glucose data were obtained from the European Bioinformatics Institute (EBI). T1DM and T2DM data were from FinnGen. We used bidirectional two-sample and multivariate MR analyses to test whether dysglycemic measures (fasting blood glucose, HbA1c), diabetes-related measures (T1DM, T2DM) are causatively associated with vitiligo. Inverse variance weighting (IVW) method was used as the main test method, MR-Egger, Weighted mode and Weighted median were used as supplementary methods. We found no statistically significant evidence to support a causal association between dysglycemic traits and vitiligo, but in the correlation analysis of diabetic traits, our data supported a positive causal association between T1DM and vitiligo (p=0.018). In the follow-up multivariate MR analysis, our results still supported this conclusion (p=0.016), and suggested that HbA1c was not a mediator of T1DM affecting the pathogenesis of vitiligo. No reverse causality was found in any of the reverse MR Analyses of dysglycemic traits and diabetic traits. Our findings support that T1DM is a risk factor for the development of vitiligo, and this conclusion may explain why the co-presentation of T1DM and vitiligo is often seen in observational studies. Clinical use of measures related to T1DM may be a new idea for the prevention or treatment of vitiligo.

Role of plasma fatty acid in age-related macular degeneration: insights from a mendelian randomization analysis

BackgroundAn imbalance in lipid metabolism has been linked to the development of AMD, but the causal relationship between AMD and plasma fatty acids (FAs) remains controversial. Using a two-sample Mendelian randomization (MR) approach, we sought to evaluate the impact of specific FA plasma levels on the risk of different AMD subtypes.MethodsWe analysed genome-wide association data of circulating FAs from 115,006 European-descended individuals in the UK Biobank. These data were used in a two-sample MR framework to assess the potential role of circulating FAs in developing wet and dry AMD. Sensitivity analyses were conducted to ensure the robustness of our findings. Additional multivariable and locus-specific MR analyses were conducted to evaluate direct effects of FA on AMD subtypes, minimizing biases from lipoprotein-related traits and triglycerides.ResultsMendelian randomization revealed associations of omega-3 was associated with decreased wet (OR 0.78, 95%CI 0.66–0.92) and dry AMD (0.85, 0.74–0.97) risk, showed a protective effect on AMD. Notably, the omega-6 to omega-3 ratio showed potential causal effects on both wet (1.27, 1.03–1.56) and dry AMD (1.18, 1.02–1.37). Multivariable MR suggested that the causal relationship of omega-3, omega-6 to omega-3 ratio on wet AMD persists after conditioning on HDL, LDL and triglycerides, albeit with slightly diminished evidence strength. Locus-specific MR linked to omega-3(FADS1, 0.89, 0.82–0.98; FADS2, 0.88, 0.81–0.96) and omega-6 to omega-3 ratio (FADS1, 1.10, 1.02–1.20; FADS2, 1.11, 1.03–1.20) suggests causal effects of these factors on wet AMD.ConclusionsThe associations between plasma FA concentrations and AMD, suggest potential causal role of omega-3, and the omega-6 to omega-3 ratio in wet AMD. These results underscore the impact of an imbalanced circulating omega-3 and omega-6 FA ratio on AMD pathophysiology from MR perspective.

Causal Association Between BMI and Polycystic Ovarian Syndrome: Bidirectional 2-Sample Mendelian Randomization Study

Abstract Objective This study aimed to explore the causal effect of body mass index (BMI) on polycystic ovarian syndrome (PCOS). Methods Genome-wide association data for BMI and PCOS were sourced from the Mendelian randomization (MR) base platform. Significantly associated single nucleotide polymorphisms (SNPs) for BMI served as instrumental variables in bidirectional 2-sample MR analyses to investigate the causal relationship between BMI and PCOS. Analytical techniques utilized encompassed the inverse variance weighted (IVW) method, weighted median estimator, and MR-Egger regression. Results We identified 427 SNPs significantly associated with BMI (P &amp;lt; 5 × 10−8; linkage disequilibrium r2 &amp;lt; 0.001). Various methods consistently revealed a positive association between BMI and PCOS (IVW: odds ratio [OR] 2.027 [95% CI 1.599-2.596]; weighted median estimator: OR 2.368 [95% CI 1.653-3.392]; MR-Egger method: OR 3.610 [95% CI 1.795-7.263]), indicating that higher BMI correlates with an increased risk of PCOS. Additionally, we observed a causal effect of genetic predisposition to PCOS on BMI (IVW: OR 1.020 [95% CI 1.019-1.022]; weighted median estimator: OR 1.017 [95% CI 1.015-1.019]; MR-Egger method: OR 1.000 [95% CI 0.995-1.005]). Conclusion The MR analysis furnished compelling evidence suggesting a causal relationship between elevated BMI and the risk of PCOS, as well as indicating that the severity of PCOS may contribute to elevated BMI levels.

Prescription glucocorticoid medication and iridocyclitis are associated with an increased risk of senile cataract occurrence: a Mendelian randomization study.

Iridocyclitis and the use of glucocorticoid medication have been widely studied as susceptibility factors for cataracts. However, the causal relationship between them remains unclear. This study aimed to investigate the causal relationship between the development of iridocyclitis and the genetic liability of glucocorticoid medication use on the risk of senile cataracts occurrence by performing Two-sample Mendelian randomization (MR) analyses. Instrumental variables (IVs) significantly associated with exposure factors (P < 5 × 10-8) were identified using published genome-wide association data from the FinnGen database and UK Biobank. Reliability analyses were conducted using five approaches, including inverse-variance weighted (IVW), MR-Egger regression, simple median, weighted median, and weighted mode. A sensitivity analysis using the leave-one-out method was also performed. Genetic susceptibility to glucocorticoid use was associated with an increased risk of developing senile cataracts (OR, 1.10; 95% CI, 1.02-1.17; P < 0.05). Moreover, iridocyclitis was significantly associated with a higher risk of developing senile cataracts (OR, 1.03; 95% CI, 1.01-1.05; P < 0.05). Nonetheless, some heterogeneity in the IVs was observed, but the MR results remained consistent after penalizing for outliers. The estimates were consistent in multivariate analyses by adjusting for body mass index (BMI) and diabetes mellitus type 2 (T2DM). This study provides new insights into the prevention and management of senile cataracts by highlighting the increased risk associated with iridocyclitis and the use of glucocorticoids.

Identifying Novel Proteins for Chronic Pain: Integration of Human Brain Proteomes and Genome-wide Association Data

Numerous genome-wide association studies have identified risk genes for chronic pain, yet the mechanisms by which genetic variants modify susceptibility have remained elusive. We sought to identify key genes modulating chronic pain risk by regulating brain protein expression. We integrated brain proteomic data with the largest genome-wide dataset for multisite chronic pain (N = 387,649) in a proteome-wide association study (PWAS) using discovery and confirmatory proteomic datasets (N = 376 and 152) from the dorsolateral prefrontal cortex. Leveraging summary data-based Mendelian randomization and Bayesian colocalization analysis, we pinpointed potential causal genes, while a transcriptome-wide association study integrating 452 human brain transcriptomes investigated whether cis-effects on protein abundance extended to the transcriptome. Single-cell RNA-sequencing data and single-nucleus transcriptomic data revealed cell-type-specific expression patterns for identified causal genes in the dorsolateral prefrontal cortex and dorsal root ganglia (DRG), complemented by RNA microarray analysis of expression profiles in other pain-related brain regions. Of the 22 genes cis-regulating protein abundance identified by the discovery PWAS, 18 (82%) were deemed causal by summary data-based Mendelian randomization or Bayesian colocalization analysis analyses, with 7 of these 18 genes (39%) replicating in the confirmatory PWAS, including guanosine diphosphate-mannose pyrophosphorylase B, which also associated at the transcriptome level. Several causal genes exhibited selective expression in excitatory and inhibitory neurons, oligodendrocytes, and astrocytes, while most identified genes were expressed across additional pain-related brain regions. This integrative proteogenomic approach identified 18 high-confidence causal genes for chronic pain, regulated by cis-effects on brain protein levels, suggesting promising avenues for treatment research and indicating a contributory role for the DRG. PerspectiveThe current post genome-wide association study analyses identified 18 high-confidence causal genes regulating chronic pain risk via cis-modulation of brain protein abundance, suggesting promising avenues for future chronic pain therapies. Additionally, the significant expression of these genes in the DRG indicated a potential contributory role, warranting further investigation.