Consistent Direction Of Effect Research Articles

Genomic predictors of fat mass response to the standardized exercise training.

To explore the genetic architecture underlying exercise-induced fat mass change, we performed a genome-wide association study with a Chinese cohort consisting of 442 physically inactive healthy adults in response to a 12-week exercise training (High-intensity Interval Training or Resistance Training). The inter-individual response showed an exercise-induced fat mass change and ten novel lead SNPs were associated with the response on the level of P<1×10-5. Four of them (rs7187742, rs1467243, rs28629770 and rs10848501) showed a consistent effect direction in the European ancestry. The Polygenic Predictor Score (PPS) derived from ten lead SNPs, sex, baseline body mass and exercise protocols explained 40.3% of the variance in fat mass response, meanwhile importantly the PPS had the greatest contribution. Of note, the subjects whose PPS was lower than -9.301 had the highest response in exercise-induced fat loss. Finally, we highlight a series of pathways and biological processes regarding the fat mass response to exercise, e.g. apelin signaling pathway, insulin secretion pathway and fat cell differentiation biological process.

Proteome-wide associations of pulse pressure in the UK Biobank

Abstract Introduction Large artery stiffness (LAS) significantly contributes to the burden of cardiovascular morbidity and mortality, and is marked by an increased pulse pressure (PP)(1). Therapeutically targeting LAS may help in mitigating cardiovascular disease and other comorbidities. Purpose We aimed to investigate the proteomic associations of PP, and their putative causal role using Mendelian randomization (MR). Methods We first investigated associations between baseline circulating protein levels for 2,941 protein analytes measured using Olink technology, and PP in the UK Biobank (N=54,219). Regression analyses were adjusted for age, sex, mean arterial pressure, body mass index and stroke volume. Next, we conducted two-sample MR analyses to evaluate associations between genetically-predicted plasma protein levels and PP, for 1,820 proteins with available genetic instruments. We conducted inverse-variance weighted MR as our main analysis, and genetic colocalization analyses as sensitivity. We used a 5% false discovery rate (FDR) threshold to account for multiple comparisons. Results After correction for multiple comparisons, measured levels of 61 out of 2,923 proteins were significantly associated with PP (Figure 1). Genetically-predicted levels for 58 proteins were significantly associated with PP after FDR correction (Figure 2). At nominal significance, 31 proteins were concordantly associated with PP in both analyses, and 19 had consistent directions of effect, including natriuretic peptide B (NPPB, βobservational=0.04, Standard Error (SE)=0.009, PFDR&amp;lt;0.001), thrombospondin-2 (THBS2, βobservational=0.05, SE=0.009, PFDR&amp;lt;0.001), paraoxonase-2 (PON2, βobservational=-0.03, SE=0.008, PFDR&amp;lt;0.001), and sclerostin (SOST, βobservational=-0.03, SE=0.009, PFDR&amp;lt;0.001). NPPB was concordant in direction of effect and met an FDR-corrected significance threshold. Conclusions Our study identifies multiple novel proteins with a putative causal effect on PP. Our findings identify NPPB with a high level of statistical confidence, which could have important implications given the current availability of FDA-approved medications to boost NPPB effects. Our findings will lead to further investigations regarding the biology and clinical role of the identified candidate therapeutic targets.

Rare variants and survival of patients with idiopathic pulmonary fibrosis.

The clinical course of idiopathic pulmonary fibrosis (IPF) is highly variable and unpredictable, with multiple genetic variants influencing IPF outcomes. Notably, rare pathogenic variants in telomere-related genes are associated with poorer clinical outcomes in these patients. Here we assessed whether rare qualifying variants (QVs) in monogenic adult-onset pulmonary fibrosis (PF) genes are associated with IPF survival. Using polygenic risk scores (PRS), we also evaluated the influence of common IPF risk variants in individuals carrying these QVs. We identified QVs in telomere and non-telomere genes linked to monogenic PF forms using whole-genome sequences (WGS) from 888 Pulmonary Fibrosis Foundation Patient Registry (PFFPR) individuals. We also derived a PRS for IPF (PRS-IPF) from 19 previously published common sentinel IPF variants. Using regression models, we then examined the mutual relationships of QVs and PRS-IPF and their association with survival. Validation of results was sought in WGS from an independent IPF study (PROFILE, n=472), and results from the two cohorts were meta-analyzed. Carriers of QVs in monogenic adult-onset PF genes, representing nearly 1 out of 6 IPF patients, were associated with lower PRS-IPF (Odds Ratio [OR]: 1.79; 95% Confidence Interval [CI]: 1.15-2.81; p=0.010) and shorter survival (Hazard Ratio [HR]: 1.53; 95% CI: 1.12-2.10; p=7.3×10 -3 ). Notably, carriers of pathogenic variants at telomere genes showed the strongest association with survival (HR: 1.76; 95% CI: 1.13-2.76; p=0.013). The meta-analysis of the results showed a consistent direction of effect across both cohorts. We revealed the opposite effects of QVs and PRS-IPF on IPF survival. Thus, a distinct IPF molecular subtype might be defined by QVs in monogenic adult-onset PF genes. Assessing the carrier status for QVs and modelling PRS-IPF promises to further contribute to predicting disease progression among IPF patients.

Evidence of the association between asthma and lung cancer risk from mendelian randomization analysis

Asthma and lung cancer are both significant public health concerns worldwide. Previous observational studies have indicated a potential link between asthma and an increased risk of lung cancer, whereas the causal relationship remains uncertain. We aimed to investigate the potential causal relationship between asthma and lung cancer risk utilizing Mendelian randomization (MR) design.The present study employed a two-sample MR analysis utilizing summary statistics from genome-wide association studies (GWAS) with European descent of asthma and lung cancer. The MR analysis was performed using inverse variance weighting (IVW), supplemented with MR-Egger regression and weighted median method to investigate the potential causality between asthma and lung cancer. Furthermore, Sensitivity analyses were also conducted to ensure the reliability of the findings. The MR analysis showed that genetically predicted asthma had suggestive causal association with the elevated risk of lung cancer [odds ratio (OR), 1.05 (95%Cl,1.01–1.09), P = 0.01]. The consistent direction of effects observed in the three methods further supported this finding. In addition, sensitivity analyses demonstrated the reliability of the results. This study provided potential evidence supporting a causal association between asthma and lung cancer. These findings highlighted the importance of early detection and prevention strategies for lung cancer in individuals with asthma. Further research was needed to elucidate the underlying mechanisms linking asthma and lung cancer.

Characterization of primary Sjögren's syndrome in the Taiwan Han population through a genome-wide association study and polygenic risk score analysis

BackgroundSjögren's syndrome (SS) is an autoimmune disorder that primarily affects the exocrine glands, leading to dryness of mucous membranes and systemic manifestations. This study aimed to identify genetic markers associated with primary SS (pSS) in the Taiwan Han population through a hospital-based genome-wide association study (GWAS) and polygenic risk score (PRS) analysis, addressing the lack of genetic research. ResultsThis study included 11,390 patients diagnosed with pSS and 113,900 controls. GWAS identified one known locus and eight novel loci. Known HLA alleles, including HLA-DRB1*15:01 and HLA-DQA1*03:01, were successfully replicated in a consistent effect direction. PRS analysis revealed that several autoimmune diseases share similar genetic backgrounds with pSS. ConclusionThis study represents the largest cohort to date on the genetics of pSS in the Taiwan Han population. Our findings provide valuable insights into the pathogenesis of pSS and emphasize the comorbidities associated with it as an autoimmune disease.

Multitrait Analysis to Decipher the Intertwined Genetic Architecture of Neuroanatomical Phenotypes and Psychiatric Disorders

BackgroundThere is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven to be challenging, and new approaches are needed to infer the genetic structures that may underlie those phenotypes. Multivariate analyses are a meaningful approach to reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches. MethodsFirst, we conducted univariate and multivariate genome-wide association studies for 9 MRI-derived brain volume phenotypes in 20,000 UK Biobank participants. Next, we performed various complementary enrichment analyses to assess whether and how univariate and multitrait approaches could distinguish disorder-associated and non–disorder-associated variants from 6 psychiatric disorders: bipolar disorder, attention-deficit/hyperactivity disorder, autism, schizophrenia (SCZ), obsessive-compulsive disorder, and major depressive disorder. Finally, we conducted a clustering analysis of top associated variants based on their MRI multitrait association using an optimized k-medoids approach. ResultsA univariate MRI genome-wide association study revealed only negligible genetic correlations with psychiatric disorders, while a multitrait genome-wide association study identified multiple new associations and showed significant enrichment for variants related to both attention-deficit/hyperactivity disorder and SCZ. Clustering analyses also detected 2 clusters that showed not only enrichment for association with attention-deficit/hyperactivity disorder and SCZ but also a consistent direction of effects. Functional annotation analyses of those clusters pointed to multiple potential mechanisms, suggesting a role of neurotrophin pathways in particular in both MRI and SCZ. ConclusionsOur results show that multitrait association signature can be used to infer genetically driven latent MRI variables associated with psychiatric disorders, thereby opening paths for future biomarker development.

Mendelian Randomization and Bayesian Colocalization Analysis Implicate Glycoprotein VI as a Potential Drug Target for Cardioembolic Stroke in South Asian Populations.

Circulating plasma proteins are clinically useful biomarkers for stroke risk. We examined the causal links between plasma proteins and stroke risk in individuals of South Asian ancestry. We applied proteome-wide Mendelian randomization and colocalization approaches to understand causality of 2922 plasma proteins on stroke risk in individuals of South Asian ancestry. We obtained genetic instruments (proxies) for plasma proteins from the UK Biobank (N=920). Genome-wide association studies summary data for strokes (N≤11 312) were sourced from GIGASTROKE consortium. Our primary approach involved the Wald ratio or inverse-variance-weighted methods, with statistical significance set at false discovery rate <0.1. Additionally, a Bayesian colocalization approach assessed shared causal variants among proteome, transcriptome, and stroke phenotypes to minimize bias from linkage disequilibrium. We found evidence of a potential causal effect of plasma GP6 (glycoprotein VI) levels on cardioembolic stroke (odds ratio [OR]Wald ratio=2.53 [95% CI, 1.59-4.03]; P=9.2×10-5, false discovery rate=0.059). Generalized Mendelian randomization accounting for correlated single nucleotide polymorphisms (SNPs), with the P value threshold at P<5×10-8 and clumped at r2=0.3, showed consistent direction of effect of GP6 on cardioembolic stroke (ORgeneralized inverse-variance-weighted=2.21 [95% CI, 1.46-3.33]; P=1.6×10-4). Colocalization analysis indicated that plasma GP6 levels colocalize with cardioembolic stroke (posterior probability=91.4%). Multitrait colocalization combining transcriptome, proteome, and cardioembolic stroke showed moderate to strong evidence that these 2 traits colocalize with GP6 expression in the coronary artery and brain tissues (multitrait posterior probability>50%). The potential causal effect of GP6 on cardioembolic stroke was not significant in European populations (ORinverse-variance-weighted=1.08 [95% CI, 0.93-1.26]; P=0.29). Our joint Mendelian randomization and colocalization analyses suggest that genetically predicted GP6 is potentially causally associated with cardioembolic stroke risk in individuals of South Asian ancestry. As genetic data on individuals of South Asian ancestry increase, future Mendelian randomization studies with larger sample size for plasma GP6 levels should be implemented to further validate our findings. Additionally, clinical studies will be necessary to verify GP6 as a therapeutic target for cardioembolic stroke in South Asians.

Multi-omics Mendelian randomization integrating GWAS, eQTL and pQTL data revealed GSTM4 as a potential drug target for migraine

IntroductionMigraine, as a complex neurological disease, brings heavy burden to patients and society. Despite the availability of established therapies, existing medications have limited efficacy. Thus, we aimed to find the drug targets that improve the prognosis of migraine.MethodWe used Mendelian Randomization (MR) and Summary-data-based MR (SMR) analyses to study possible drug targets of migraine by summary statistics from FinnGen cohorts (nCase = 44,616, nControl = 367,565), with further replication in UK Biobank (nCase = 26,052, nControl = 487,214). Genetic instruments were obtained from eQTLGen and UKB-PPP to verify the drug targets at the gene expression and protein levels. The additional analyses including Bayesian co-localization, the heterogeneity in dependent instruments(HEIDI), Linkage Disequilibrium Score(LDSC), bidirectional MR, multivariate MR(MVMR), heterogeneity test, horizontal pleiotropy test, and Steiger filtering were implemented to consolidate the findings further. Lastly, drug prediction analysis and phenome-wide association study(PheWAS) were employed to imply the possibility of drug targets for future clinical applications.ResultThe MR analysis of eQTL data showed that four drug targets (PROCR, GSTM4, SLC4A1, and TNFRSF10A) were significantly associated with migraine risk in both the FinnGen and UK Biobank cohorts. However, only GSTM4 exhibited consistent effect directions across the two outcomes(Discovery cohort: OR(95%CI) = 0.94(0.93–0.96); p = 2.70e − 10; Replication cohort: OR(95%CI) = 0.93(0.91–0.94); p = 4.21e − 17). Furthermore, GSTM4 passed the SMR at p < 0.05 and HEIDI test at p > 0.05 at both the gene expression and protein levels. The protein-level MR analysis revealed a strong correlation between genetically predicted GSTM4 with a lower incidence of migraine and its subtypes(Overall migraine: OR(95%CI) = 0.91(0.87–0.95); p = 6.98e-05; Migraine with aura(MA): OR(95%CI) = 0.90(0.85–0.96); p = 2.54e-03; Migraine without aura(MO): OR(95%CI) = 0.90(0.83–0.96); p = 2.87e-03), indicating a strong co-localization relationship (PPH4 = 0.86). Further analyses provided additional validation for the possibility of GSTM4 as a migraine treatment target.ConclusionThis study identifies GSTM4 as a potential druggable gene and promising therapeutic target for migraine.

Causal effects of genetically determined blood metabolites on asthma: a bidirectional Mendelian randomization study

Objective The observational association between blood metabolites and asthma has been extensively studied. However, it is still unclear whether this association is causal. In this study, we aimed to investigate the causal relationship between blood metabolites and asthma using a bidirectional Mendelian randomization (MR) analysis. Additionally, we aimed to explore the potential mechanisms underlying this relationship. Methods The study design involved the use of genetic instruments as instrumental variables (IVs) to fulfill the assumptions of MR analysis. The data on 1,091 metabolites and 309 metabolite ratios were obtained from the Canadian Longitudinal Study on Aging (CLSA), while the data on asthma were obtained from the Integrative Epidemiology Unit (IEU) Open GWAS Project. Utilizing the inverse variance-weighted (IVW) method as the primary MR analysis approach, sensitivity tests were conducted to assess the reliability of the findings, which involved employing Cochran’s Q and the MR-Egger intercept. Furthermore, Bayesian weighted MR was used to further test the robustness of the results. Additionally, pathway analysis was conducted to explore the metabolic explanations underlying asthma. Result In our study, a comprehensive MR Analysis identified 10 metabolites and 6 metabolite ratios significantly associated with the development of asthma (FDR < 0.05). The metabolites included glycerophosphocholines(GPCs), glycerophosphoethanolamines(GPEs), and an unknown metabolite. Of these, 1-arachidonoyl-GPC, 1-myristoyl-2-arachidonoyl-GPC, 1-palmitoyl-2-arachidonoyl-GPC, and 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC were associated with an increased risk of asthma, whereas 1,2-dilinoleoyl-GPC, 1-palmitoyl-2-linoleoyl-GPC, 1,2-dilinoleoyl-GPE, 1 − oleoyl − 2 − linoleoyl − GPE, 1-palmitoyl-2-linoleoyl-GPE, and X-21470 were found to have a protective effect. No heterogeneity and pleiotropy were observed in the significant metabolites (p > 0.05), and each metabolite exhibited a consistent effect direction across all five methods. BWMR analysis results confirmed the significance and direction of effects across exposures, except for Cholesterol to linoleoyl-arachidonoyl-glycerol ratio(p = 0.673). Pathway analysis suggests that glycerophospholipid metabolism may potentially be a mechanism underlying the development of asthma. Conclusion Our MR findings suggest that the identified metabolites and pathways can serve as biomarkers for clinical asthma screening and prevention, while also providing new insights for future mechanistic exploration and drug target selection.

Gene-age interaction study of breast cancer prognosis based on epigenomic data

Objective: Exploring gene-age interactions associated with breast cancer prognosis based on epigenomic data. Methods: Differential expression analysis of DNA methylation was conducted using multiple independent epigenomic datasets of breast cancer from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The false discovery rate (FDR) method was used for multiple corrections, retaining differentially methylated sites with q-FDR≤0.05. A three-stage analytic strategy was implemented, using a multivariable Cox proportional hazards regression model to examine gene-age interactions. In the discovery phase, signals with q-FDR ≤ 0.05 were screened out using TCGA-BRCA database. In validation phaseⅠ, the interaction was validated using GSE72245 data, with criteria of P≤0.05 and consistent effect direction. In validation phaseⅡ, the signals were further validated using GSE37754 and GSE75067 data. A prognostic prediction model was constructed by incorporating clinical indicators and interaction signals. Results: The three-stage analytic strategy identified a methylation site (cg16126280EBF1), which interacted with age to jointly affect the overall survival time of patients (interaction HR= 1.001 1,95%CI:1.000 7-1.001 5,P<0.001). Stratified analysis by age showed that the effect of hypermethylation of cg16126280EBF1 was completely opposite in younger patients (HR=0.550 5, 95%CI: 0.383 8-0.789 6, P=0.001) and older patients (HR=2.166 5, 95%CI: 1.285 2-3.652 2, P=0.004). Conclusions: The DNA methylation site cg16126280EBF1 exhibits an interaction with age, jointly influencing the prognosis of breast cancer in a complex association pattern. This finding contributes new population-based evidence for the development of age-specific targeted drugs.

Genetic overlap between schizophrenia and cognitive performance

Schizophrenia (SCZ), a highly heritable mental disorder, is characterized by cognitive impairment, yet the extent of the shared genetic basis between schizophrenia and cognitive performance (CP) remains poorly understood. Therefore, we aimed to explore the polygenic overlap between SCZ and CP. Specifically, the bivariate causal mixture model (MiXeR) was employed to estimate the extent of genetic overlap between SCZ (n = 130,644) and CP (n = 257,841), and conjunctional false discovery rate (conjFDR) approach was used to identify shared genetic loci. Subsequently, functional annotation and enrichment analysis were carried out on the identified genomic loci. The MiXeR analyses revealed that 9.6 K genetic variants are associated with SCZ and 10.9 K genetic variants for CP, of which 9.5 K variants are shared between these two traits (Dice coefficient = 92.8%). By employing conjFDR, 236 loci were identified jointly associated with SCZ and CP, of which 139 were novel for the two traits. Within these shared loci, 60 exhibited consistent effect directions, while 176 had opposite effect directions. Functional annotation analysis indicated that the shared genetic loci were mainly located in intronic and intergenic regions, and were found to be involved in relevant biological processes such as nervous system development, multicellular organism development, and generation of neurons. Together, our findings provide insights into the shared genetic architecture between SCZ and CP, suggesting common pathways and mechanisms contributing to both traits.

Synthesis methods used to combine observational studies and randomised trials in published meta-analyses.

This study examined the synthesis methods used in meta-analyses pooling data from observational studies (OSs) and randomised controlled trials (RCTs) from various medical disciplines. We searched Medline via PubMed to identify reports of systematic reviews of interventions, including and pooling data from RCTs and OSs published in 110 high-impact factor general and specialised journals between 2015 and 2019. Screening and data extraction were performed in duplicate. To describe the synthesis methods used in the meta-analyses, we considered the first meta-analysis presented in each article. Overall, 132 reports were identified with a median number of included studies of 14 [9-26]. The median number of OSs was 6.5 [3-12] and that of RCTs was 3 [1-6]. The effect estimates recorded from OSs (i.e., adjusted or unadjusted) were not specified in 82% (n = 108) of the meta-analyses. An inverse-variance common-effect model was used in 2% (n = 3) of the meta-analyses, a random-effects model was used in 55% (n = 73), and both models were used in 40% (n = 53). A Poisson regression model was used in 1 meta-analysis, and 2 meta-analyses did not report the model they used. The mean total weight of OSs in the studied meta-analyses was 57.3% (standard deviation, ± 30.3%). Only 44 (33%) meta-analyses reported results stratified by study design. Of them, the results between OSs and RCTs had a consistent direction of effect in 70% (n = 31). Study design was explored as a potential source of heterogeneity in 79% of the meta-analyses, and confounding factors were investigated in only 10% (n = 13). Publication bias was assessed in 70% (n = 92) of the meta-analyses. Tau-square was reported in 32 meta-analyses with a median of 0.07 [0-0.30]. The inclusion of OSs in a meta-analysis on interventions could provide useful information. However, considerations of several methodological and conceptual aspects of OSs, that are required to avoid misleading findings, were often absent or insufficiently reported in our sample.

Modifiable risk factors mediate the effect of gastroesophageal reflux disease on stroke and subtypes: A Mendelian randomization study

ObjectivesPrevious observational studies have suggested that gastroesophageal reflux disease (GERD) increases the risk of stroke, but the specific underlying mechanisms are unclear. We investigated the causal associations of GERD with stroke and its subtypes using Mendelian randomization (MR), and evaluated the potential mediating effects of modifiable stroke risk factors in the causal pathway. MethodsGenetic instrumental variables for GERD were extracted from the latest genome-wide association study (GWAS) summary level data. We initially performed two-sample MR to examine the association of GERD with stroke and its subtypes, including ischemic stroke, intracranial hemorrhage, and the major subtypes of ischemic stroke. Two-step MR was further employed to investigate the mediating effect of 15 risk factors in the causal pathway. ResultsWe found significant causal associations of genetically predicted GERD with increased risk of stroke (OR: 1.22 95% CI: 1.126–1.322), ischemic stroke (OR: 1.19 95% CI: 1.098–1.299), and large-artery stroke (OR: 1.49 95% CI: 1.214–1.836). Replication and sensitivity analyses yielded consistent effect directions and similar estimates. Further mediation analyses indicated that hypertension (HTN), systolic blood pressure (SBP), and type 2 diabetes (T2D) mediated 36.0%, 9.0%, and 15.8% of the effect of GERD on stroke; 42.9%, 10.8%, and 21.4% for ischemic stroke, and 23.3%; 7.9%, and 18.7% for large-artery stroke, respectively. ConclusionsThis study supports that GERD increases susceptibility to stroke, ischemic stroke, and large-artery stroke, and is partially mediated by HTN, SBP, and T2D.

Abstract 133: Associations of Genetically Predicted Iron Status and Ischemic Stroke Subtypes: A Mendelian Randomization Study

Mendelian randomization (MR) studies suggest a causal effect of Fe status on ischemic stroke (IS). It is currently unknown if these associations are confounded by pleiotropic effects of the instrumental variables (IV) on cardiovascular disease (CVD) risk factors, such as low-density lipoprotein cholesterol (LDL), diastolic blood pressure (DBP), and body mass index (BMI). We aimed to investigate the effect of iron (Fe) status on risk of IS subtypes (cardioembolic (CES), small vessel (SVS), and large artery atherosclerotic (LAS)) controlling for CVD risk factors. Fe biomarker IVs (total Fe binding capacity (TIBC), transferrin saturation (TSAT), serum Fe (SI), serum ferritin (SF)) were selected from a European GWAS (n=198K-258K) and filtered based on genome-wide significance ( P &lt;5e -8 ), F-statistic&gt;10, R 2 &lt;0.001, minor allele frequency &gt;1%, and consistent effect direction for all Fe traits. We performed univariate two-sample MR of each Fe trait on IS subtypes from MEGASTROKE (n cases: CES=7,193; SVS =5,386; LAS= 4,373) and implemented multivariate MR conditioning on LDL, DBP, and BMI from the UK Biobank. Estimates are expressed as odds ratio [95%CI] per SD unit increase in Fe. Univariate MR showed a detrimental effect of higher Fe status on CES, no effect on SVS, and a protective effect on LAS across all Fe markers ( Figure 1 ). The negative effect of Fe status on CES persisted when conditioning on LDL (TSAT: 1.17 [1.03-1.34]; TIBC: 0.84 [0.71-0.98]), DBP (TSAT: 1.15 [1.01-1.31]; TIBC: 0.82 [0.70-0.96]), or BMI (TSAT: 1.18 [1.04-1.34]; TIBC: 0.82 [0.70-0.95]) (all P &lt;0.05). However, the apparent positive effect of Fe status on LAS disappeared when conditioning on CVD risk factors ( Figure 1 ), particularly LDL (all P &lt;0.05). Higher Fe status is associated with a greater risk of CES independent of CVD risk factors. These findings support the role of Fe status as a modifiable risk factor for CES. Future studies are needed to assess the mechanisms mediating this effect.

QTL epistasis plays a role of homeostasis on heading date in rice

If there was no gene interaction, the gene aggregation effect would increase infinitely with the increase of gene number. Epistasis avoids the endless accumulation of gene effects, playing a role of homeostasis. To confirm the role, QTL epistases were analyzed by four single-segment substitution lines with heading date QTLs in this paper. We found that QTLs of three positive effects and one negative effect generated 62.5% negative dual QTL epistatic effects and 57.7% positive triple QTL epistatic effects, forming the relationship “positive QTLs-negative one order interactions-positive two order interactions”. In this way, the aggregation effect of QTLs was partially neutralized by the opposite epistatic effect sum. There also were two exceptions, QTL OsMADS50 and gene Hd3a-2 were always with consistent effect directions with their epistases, implying they could be employed in pyramiding breeding with different objectives. This study elucidated the mechanism of epistatic interactions among four QTLs and provided valuable genetic resources for improving heading date in rice.

Dissecting the shared genetic basis of Alzheimer’s disease and hippocampal volumes

AbstractBackgroundHippocampal atrophy is an important pathophysiological event in Alzheimer’s disease (AD) etiopathology. Still the mechanistic link between these volumetric abnormalities and AD remains poorly understood. In this study, we estimated polygenic overlap with mixed effect directions between AD and bilateral hippocampal volumes, and identified commonly shared genetic variants between two traits, involved in several synaptic and immunomodulatory genes.MethodFor this study we used GWAS summary statistics on AD (1,11,326 cases and 6,77,663 controls) (Bellenguezet et al., 2022) and hippocampal volumes (33,224 populations controls) (Smith et al., 2021). First, we applied Bivariate causal mixture model (MiXeR version1.3, Frei et al., 2021) to quantify the polygenic overlap between AD and bilateral hippocampal volumes. For each AD‐volume pair, MiXeR estimated the shared polygenic architecture between two traits, irrespective of the direction of individual variants effects.To explore the MiXeR estimated shared genetic basis at individual variant level, we used the conjunctional false discovery rate (conjFDR) analysis (Andreassen et al., 2013) on the association of AD with bilateral hippocampal volumes, and vice versa. The conjFDR analysis is built on an empirical Bayesian statistical framework. Four regions (MHC, 8p23.1, MAPT, APOE) with complex LD patterns were excluded from the analyses because complex correlations in regions with intricate LD might bias the estimation.ResultMiXeR univariate analysis estimated the number of AD risk variants to be around 343 genetic variants, and the number of variants for bilateral hippocampal volumes between 901 and 942 variants. MiXeR bivariate analysis estimated that the number of shared variants between AD and bilateral hippocampal volumes was around 75 and 96 variants (see Figure 1). At conjFDR &lt; 0.05, we identified 10 common loci shared by AD and left hippocampal volume,6 lead SNPs had consistent effect directions, while 4 loci have opposite effect directions according to their Z value. 8 common loci shared by AD and right hippocampal volume, 5 lead SNPs have consistent effect directions, 3 have opposite effect directions. (see Figure 2 and Table 1)ConclusionThis study provides evidence of a shared genetic architecture between AD and bilateral hippocampal volumes. The identification of common loci helps to understand the role of hippocampus in AD pathology.

Proteomic Biomarkers of Survival in Idiopathic Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) causes progressive lung scarring and high mortality. Reliable and accurate prognostic biomarkers are urgently needed. Objectives: To identify and validate circulating protein biomarkers of IPF survival. Methods: High-throughput proteomic data were generated using prospectively collected plasma samples from patients with IPF from the Pulmonary Fibrosis Foundation Patient Registry (discovery cohort) and the Universities of California, Davis; Chicago; and Virginia (validation cohort). Proteins associated with three-year transplant-free survival (TFS) were identified using multivariable Cox proportional hazards regression. Those associated with TFS after adjustment for false discovery in the discovery cohort were advanced for testing in the validation cohort, with proteins maintaining TFS association with consistent effect direction considered validated. After combining cohorts, functional analyses were performed, and machine learning was used to derive a proteomic signature of TFS. Measurements and Main Results: Of 2,921 proteins tested in the discovery cohort (n = 871), 231 were associated with differential TFS. Of these, 140 maintained TFS association with consistent effect direction in the validation cohort (n = 355). After cohorts were combined, the validated proteins with the strongest TFS association were latent-transforming growth factor β-binding protein 2 (hazard ratio [HR], 2.43; 95% confidence interval [CI] = 2.09-2.82), collagen α-1(XXIV) chain (HR, 2.21; 95% CI = 1.86-2.39), and keratin 19 (HR, 1.60; 95% CI = 1.47-1.74). In decision curve analysis, a proteomic signature of TFS outperformed a similarly derived clinical prediction model. Conclusions: In the largest proteomic investigation of IPF outcomes performed to date, we identified and validated 140 protein biomarkers of TFS. These results shed important light on potential drivers of IPF progression.

Modifiable risk factors for multiple sclerosis have consistent directions of effect across diverse ethnic backgrounds: a nested case–control study in an English population-based cohort

BackgroundMultiple sclerosis is a leading cause of non-traumatic neurological disability among young adults worldwide. Prior studies have identified modifiable risk factors for multiple sclerosis in cohorts of White ethnicity, such as infectious mononucleosis, smoking, and obesity during adolescence/early adulthood. It is unknown whether modifiable exposures for multiple sclerosis have a consistent impact on risk across ethnic groups.AimTo determine whether modifiable risk factors for multiple sclerosis have similar effects across diverse ethnic backgrounds.MethodsWe conducted a nested case–control study using data from the UK Clinical Practice Research Datalink. Multiple sclerosis cases diagnosed from 2001 until 2022 were identified from electronic healthcare records and matched to unaffected controls based on year of birth. We used stratified logistic regression models and formal statistical interaction tests to determine whether the effect of modifiable risk factors for multiple sclerosis differed by ethnicity.ResultsWe included 9662 multiple sclerosis cases and 118,914 age-matched controls. The cohort was ethnically diverse (MS: 277 South Asian [2.9%], 251 Black [2.6%]; Controls: 5043 South Asian [5.7%], 4019 Black [4.5%]). The age at MS diagnosis was earlier in the Black (40.5 [SD 10.9]) and Asian (37.2 [SD 10.0]) groups compared with White cohort (46.1 [SD 12.2]). There was a female predominance in all ethnic groups; however, the relative proportion of males was higher in the South Asian population (proportion of women 60.3% vs 71% [White] and 75.7% [Black]). Established modifiable risk factors for multiple sclerosis—smoking, obesity, infectious mononucleosis, low vitamin D, and head injury—were consistently associated with multiple sclerosis in the Black and South Asian cohorts. The magnitude and direction of these effects were broadly similar across all ethnic groups examined. There was no evidence of statistical interaction between ethnicity and any tested exposure, and no evidence to suggest that differences in area-level deprivation modifies these risk factor-disease associations. These findings were robust to a range of sensitivity analyses.Conclusions and relevanceEstablished modifiable risk factors for multiple sclerosis are applicable across diverse ethnic backgrounds. Efforts to reduce the population incidence of multiple sclerosis by tackling these risk factors need to be inclusive of people from diverse ethnicities.

Minimal effect of sleep on the risk of age-related macular degeneration: a Mendelian randomization study.

Observational studies have shown that sleep pattern is associated with age-related macular degeneration (AMD), but whether sleep pattern is a causal factor for AMD remains unclear. This study aims to use Mendelian randomization (MR) analysis to investigate the potential causal relationship between sleep traits and AMD. This is a two-sample MR study. The single-nucleotide polymorphisms associated with AMD and early AMD were selected as the outcome from two different genome-wide association studies (GWAS): the early AMD GWAS with 14,034 cases and 91,214 controls, and AMD GWAS with 3,553 cases and 147,089 controls. The datasets of sleep duration, daytime dozing, and sleeplessness were used as exposure, which comprised nearly 0.46 million participants. Inverse-variance weighted method was used as the main result, and comprehensive sensitivity analyses were conducted to estimate the robustness of identified associations and the impact of potential horizontal pleiotropy. Through MR analysis, we found that sleep duration was significantly associated with AMD (OR = 0.983, 95% CI = 0.970-0.996, P-value = 0.01). We also found suggestive evidence for the association of genetically predicted sleep duration with early AMD, which showed a consistent direction of effect with a marginal significance (OR = 0.724, 95% CI = 0.503-1.041, P-value = 0.08). Sensitivity analyses further supported the robustness of the causal relationship between sleep duration and AMD. However, we were unable to determine the relationship between daytime dozing or sleeplessness and AMD (including early AMD) (P-value > 0.05). Sleep duration affects the causal risk for AMD; that is, longer sleep duration reduces the risk of AMD, while shorter sleep duration increases the risk of AMD. Although the influence is minimal, keeping adequate sleep duration is recommended, especially for patients with intermediate or advanced AMD.

Association of Risk Variants in the CFH Gene With Elevated Levels of Coagulation and Complement Factors in Idiopathic Multifocal Choroiditis

Idiopathic multifocal choroiditis (MFC) is poorly understood, thereby hindering optimal treatment and monitoring of patients. To identify the genes and pathways associated with idiopathic MFC. This was a case-control genome-wide association study (GWAS) and protein study of blood plasma samples conducted from March 2006 to February 2022. This was a multicenter study involving 6 Dutch universities. Participants were grouped into 2 cohorts: cohort 1 consisted of Dutch patients with idiopathic MFC and controls, and cohort 2 consisted of patients with MFC and controls. Plasma samples from patients with idiopathic MFC who had not received treatment were subjected to targeted proteomics. Idiopathic MFC was diagnosed according to the Standardization of Uveitis Nomenclature (SUN) Working Group guidelines for punctate inner choroidopathy and multifocal choroiditis with panuveitis. Data were analyzed from July 2021 to October 2022. Genetic variants associated with idiopathic MFC and risk variants associated with plasma protein concentrations in patients. This study included a total of 4437 participants in cohort 1 (170 [3.8%] Dutch patients with idiopathic MFC and 4267 [96.2%] controls; mean [SD] age, 55 [18] years; 2443 female [55%]) and 1344 participants in cohort 2 (52 [3.9%] patients with MFC and 1292 [96.1%] controls; 737 male [55%]). The primary GWAS association mapped to the CFH gene with genome-wide significance (lead variant the A allele of rs7535263; odds ratio [OR], 0.52; 95% CI, 0.41-0.64; P = 9.3 × 10-9). There was no genome-wide significant association with classical human leukocyte antigen (HLA) alleles (lead classical allele, HLA-A*31:01; P = .002). The association with rs7535263 showed consistent direction of effect in an independent cohort of 52 cases and 1292 control samples (combined meta-analysis OR, 0.58; 95% CI, 0.38-0.77; P = 3.0 × 10-8). In proteomic analysis of 87 patients, the risk allele G of rs7535263 in the CFH gene was strongly associated with increased plasma concentrations of factor H-related (FHR) proteins (eg, FHR-2, likelihood ratio test, adjusted P = 1.1 × 10-3) and proteins involved in platelet activation and the complement cascade. Results suggest that CFH gene variants increase systemic concentrations of key factors of the complement and coagulation cascades, thereby conferring susceptibility to idiopathic MFC. These findings suggest that the complement and coagulation pathways may be key targets for the treatment of idiopathic MFC.