Genome-wide Association Research Articles

From metabolomics to therapeutics: identifying causal metabolites and potential drugs for the treatment of osteoarthritis.

Osteoarthritis (OA) is a common age-related disease that causes pain and impaired mobility. Various blood metabolites are reportedly associated with bone health; however, their impact on OA remains unclear. Therefore, we conducted a metabolome-wide Mendelian randomization (MR) study to identify causal metabolites and therapeutic targets in OA. Genetic associations of metabolites were derived from the largest genome-wide association study (GWAS) of the blood metabolome, which provided summary-level data on 1091 blood metabolites. Genetic associations with OA were obtained from four large-scale GWAS: McDonald's study (140,025 cases, 344,349 controls), Zengini's study (12,658 cases, 50,898 controls), Dönertaş's study (39,515 cases, 445,083 controls), and Tachmazidou's study (39,427 cases, 378,169 controls). MR and colocalization analyses were performed to validate the causal roles of the candidate metabolites. Further analyses were conducted using expression quantitative trait locus-based MR, single-cell sequencing data, protein-protein interaction networks, and druggability assessments. These analyses aimed to identify the differentially expressed genes and prioritize them as potential therapeutic targets. The genetically predicted levels of 10 metabolites were associated with OA. Elevated levels of five metabolites and reduced levels of another five metabolites were associated with an increased OA risk. Among these, five metabolites were prioritized based on the most compelling evidence. Seven genes were identified as potentially involved and could serve as novel therapeutic targets for OA. Several blood metabolites were associated with OA, providing new insights into the etiology of OA and highlighting promising therapeutic targets.

Causal Effects of Gastroesophageal Reflux on Chronic Rhinosinusitis: A Bidirectional Two-Sample Mendelian Randomization Study.

Observational studies have shown a bidirectional association between gastroesophageal reflux (GER) and chronic rhinosinusitis (CRS) or chronic rhinitis (CR), but it is not clear whether this association is causal. This study was to investigate the causality between GER and CRS or CR using bidirectional two-sample Mendelian randomization (MR) analysis. Using pooled data from large genome-wide association studies (GWAS), genetic loci independently associated with GER, CRS and CR in populations of European and American ancestry were selected as instrumental variables (IVs). The inverse variance weighted (IVW) method was used to analyse the random effects model of MR, and the odds ratio (OR) was used as the evaluation index to explore the bidirectional causality between GER and CRS or CR. Single nucleotide polymorphism (SNP) outliers were detected using MR-pleiotropy Residual Sum and Outliers (MR-PRESSO). The MR-Egger intercept test examined the horizontal pleiotropy of SNPs. The "leave-one-out" sensitivity analysis examined whether MR results were affected by a single SNP. The main results of IVW showed that GER increased the risk of CRS (OR = 1.3795, 95% CI = 1.188-1.603, p < 0.0500) and CR (OR = 1.3941, 95% CI = 1.1671-1.6652, p < 0.0500). The obtained SNPs as IVs for GER, CRS and CR had no significant horizontal pleiotropy, heterogeneity or bias. Regarding the reverse directions, no notable associations could be found. This MR analysis revealed that genetically predicted GER had a causal effect on an increased risk of CRS or CR, but not vice versa. These results have great implications for the management of CRS (especially for refractory CRS) or CR in clinical practice.

Skimmed milk intake reduces the risk of ER− breast cancer: a Mendelian randomization analysis

BackgroundIn prior observational investigations, it has been demonstrated that the consumption of milk is associated with the incidence of breast cancer (BC). Despite the existence of a two-sample Mendelian randomization (MR) that suggests a causal relationship between milk intake and breast cancer risk, the outcomes still lack a definitive conclusion. This ambiguity may be attributed to variables such as the variety of milk ingested, estrogen levels, the specific type of BC, and potential confounding factors. Therefore, our principal objective is to establish the causal association between the consumption of skimmed milk and full cream milk and the risk of different types of BC through the utilization of two-sample and two-step MR analyses.MethodsIn this study, we analyzed single nucleotide polymorphisms associated with skimmed and full-cream milk consumption in a cohort of 360,806 individuals from European populations through genome-wide association studies. We conducted a two-sample MR analysis using three different methods: inverse variance weighting (IVW) was used as the main analysis, and MR-Egger and Weighted median were used as supplementary analyses to IVW. We also performed sensitivity analysis, which included leave-one-out analysis, Cochran's Q test to detect heterogeneity, and MR-Egger intercept analysis to detect potential biases caused by pleiotropy. We used two-step MR analysis to evaluate potential mediators of associations.ResultsIn the two-sample MR analysis, IVW analysis suggests a potential inverse causal relationship between skimmed milk and BC [OR 0.34, 95% CI (0.12–1.00), P = 0.05]. Subgroup analysis revealed that skimmed milk reduces the risk of estrogen receptor-negative (ER−) breast cancer [OR 0.18, 95% CI (0.04–0.90), P = 0.04], but not estrogen receptor-positive (ER+) breast cancer [OR 0.42, 95% CI (0.15–1.22), P = 0.11]. MR Egger reached similar results, that is, skimmed milk reduces the risk of ER− breast cancer [OR 0.006, 95% CI (0.00–0.70), P = 0.04], but not BC [OR 0.16, 95% CI (0.01–4.66), P = 0.30] and ER+ breast cancer [OR 0.50, 95% CI (0.02–12.61), P = 0.65]. Additionally, we found no causal relationship between full cream milk and BC (P > 0.05). In two-step MR analysis, we found evidence for a mediating role of BMI in the relationship between skimmed milk intake and ER-breast cancer risk.ConclusionOur findings strengthen the evidence for a protective effect of skimmed milk consumption on ER-breast cancer risk. Further two-step MR analyses suggest that this protective effect may partly result from body mass index (BMI). There is no evidence that full cream milk consumption affects the risk of BC.

The causal relationship between anti-CD20 antibodies and endometrial cancer: a Mendelian randomization study

PurposeTo determine the effects of anti-B cell surface marker CD20 antibody on the occurrence and progression of endometrial cancer to provide insights into clinical treatment in the future.MethodsWe performed a two-sample Mendelian randomization analysis (MR) to analyze the causal relationship between EC and immune cell markers. The genome-wide association study (GWAS) data of MS4A1 single nucleotide polymorphism encoding gene of CD20 were collected, and a drug target MR analysis was performed to detect the causal relationship between anti-CD20 antibody and the risk of EC. The risk of follicular lymphoma was used as a positive control, and EC was used as the outcome.ResultsEC exerted an effect on 28 immunophenotypes, predominantly on CD20. CD20 in immunoglobulin D+ CD38− B cells, memory B cells, and unsw memory B cells increased after EC onset. In addition, we detected one immunophenotype that exerted a dangerous effect on EC, i.e., CD3/TD CD4+ (mature stage of the T cell group). Simultaneously, CD20 could be used as both a risk factor and a protective factor for EC (P > 0.05). Anti-CD20 antibodies significantly reduced the risk of follicular lymphoma, including two GWAS pooled datasets. In addition, anti-CD20 antibodies exerted a protective effect on EC in two GWAS pooled datasets (P > 0.05).ConclusionOur study confirms the close relationship between CD20 and EC. Anti-CD20 antibodies may exert a protective effect on EC and reduce the risk of EC morbidity, providing a reference for future clinical diagnosis and treatment. However, further clinical verification of our results is warranted.

Phenotypic insights into genetic risk factors for immune-related adverse events in cancer immunotherapy

BackgroundImmune-related adverse events (irAEs) pose substantial challenges in the realm of cancer immunotherapy, frequently affecting treatment efficacy and patient safety. To address the urgent need for identifying risk factors associated with irAEs, we conducted a comprehensive phenotype-wide Mendelian randomization analysis (MR-PheWAS).MethodsUtilizing publicly accessible genome-wide association study (GWAS) data, this investigation evaluated the impact of over 5000 exposure variables on susceptibility to irAEs using univariate Mendelian randomization (MR). We categorized these correlations and further explored potential mechanisms by which associated traits might influence irAEs through multivariate MR.ResultsMR-PheWAS identified numerous risk factors for irAEs, encompassing both previously documented and novel associations. Specifically, we identified 105 traits with probable causal relationships to all-grade irAEs and 119 traits with suggestive associations. For high-grade irAEs, we categorized 122 traits as probably associated and 141 as suggestively associated. Notably, multivariate MR analyses uncovered intricate interactions, particularly highlighting how diabetes impacts all-grade irAEs through mediators such as body mass index and sex hormone-binding globulin.ConclusionsThis study has not only identified new risk factors for irAEs but also confirmed several well-established ones. Further investigation is crucial to validate and assess these identified risk factors within clinical trials. A mechanistic understanding of these causal factors is essential for improving the management and prevention of irAEs.

Association of depression with longitudinal changes in brain structure across the lifespan: A mendelian randomization study.

Understanding the impact of depression on brain aging benefits the prognosis of this disease and of the risk that other age-related brain disorders will develop in the same population. The aim of the present study was to explore the genetic effect of depression on longitudinal changes in brain structure throughout the lifespan using a Mendelian randomization approach. Summary data from a genome-wide association study of 195,321 to 377,277 participants in the FinnGen consortium were used to predict depression, anxiety disorders, mood disorders, and antidepressant use genetically. Data from 15,640 participants in the ENIGMA consortium were included to predict changes in 15 brain structures throughout the lifespan. The causal relationship between these depressive traits and the brain structure parameters was assessed by two-sample Mendelian randomization (including inverse-variance weighted). Sensitivity analyses were conducted for quality control. Depression slowed the decrease of cortical gray matter volume significantly throughout the lifespan (p = 0.001). Depression, anxiety, and mood disorders nominally decreased the rates of change of volume in the cerebellum gray matter, lateral ventricles, and cortical gray matter throughout the lifespan (p = 0.048, p = 0.021, p = 0.038, respectively). Antidepressants did not affect these rates of change significantly (p > 0.05). Sensitivity analyses confirmed the reliability of this study. Depression and its main symptoms have a slight effect on longitudinal changes in a few brain structures throughout the lifespan at the genetic level. These findings do not support the notion that depression affects macro-aging in the brain crucially.

Genome- and transcriptome-wide association studies reveal the genetic basis of seed palmitic acid content in Brassica napus

Rapeseed (Brassica napus L.) is one of the most important oilseed crops worldwide. Development of rapeseed varieties with high-quality oil is a long-term breeding goal. Reducing the contents of palmitic acid, the main saturated fatty acid in rapeseed oil, could greatly improve oil quality. Here, we performed genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) of seed palmitic acid content (SPAC) using 393 diverse B. napus accessions. Four genes (BnaA08.DAP, BnaA08.PAA1, BnaA08. DUF106, and BnaC03.DAP) were identified by both GWAS and TWAS. The transcripts per million (TPM) values of these candidate genes at 20 and 40 days after flowering (DAF) were significantly correlated with SPAC in this association panel. Based on genetic variation in the candidate genes, we identified four low-SPAC haplotypes by combining candidate gene association analysis and haplotype analysis. Brassica napus accessions carrying low-SPAC haplotypes had lower SPAC than those carrying high-SPAC haplotypes without affecting seed oil content, seed protein content, or seed yield. Based on the functional single-nucleotide polymorphism (SNP) chrA08_9529850 (C/A) in the promoter of BnaA08.DUF106, we developed a molecular marker (Bn_A8_SPAC_Marker) that could be used to facilitate breeding for low SPAC in B. napus. Our findings provide valuable information for studying the genetic control of SPAC in B. napus. Moreover, the candidate genes, favorable haplotypes, and molecular marker identified in this study will be useful for breeding low-SPAC B. napus varieties.

The effect of depression status on osteoarthritis: A powerful two-step Mendelian randomization study.

There is no conclusive epidemiological evidence regarding the relationship between OA, depression, and whole-body fat mass. In this study, we conducted a two-step Mendelian randomization analysis to determine the causal relationships between them. The published summary-level data are from genome-wide association studies (GWAS). Our study included 357,957 samples and 10,828,862 SNPs. Finally, the outcome GWAS data for OA came from a GWAS on the genetic architecture of OA using UK Biobank data. This study included 50,508 samples and 15,845,511 SNPs. We used five different modes of analysis, including inverse variance weighted meta-analysis (IVW), MR-Egger regression, weighted median, simple mode, and weighted mode, to explore causal relationships. We found a positive correlation between depression and body fat mass, with depression leading to body fat mass an increase in (IVW result: p=3.39E-07, OR (95% CI) =2.16 (1.61, 2.90)). We also found a positive correlation between body fat mass and OA, with body fat mass increasing the risk of OA (IVW result: p=1.65E-33, OR (95% CI)=1.98 (1.77, 2.21). Body fat mass played an important role as a mediator in the causal relationship between depression and OA, with approximately 14% of the risk of OA caused by depression being mediated by body fat mass. Our study offers reliable evidence that depression has a detrimental impact on the risk of OA. Future research can support these associations from improving depressed effect, including social, biological, and behavioral factors, to reduce the risk of chronic diseases such as osteoarthritis. And we identified high-risk variation of alleles which associated with OA and depression can be used to predict disease and provide a basis for clinical intervention and treatment of OA.

Genomic study in opioid-treated cancer patients identifies variants associated with nausea-vomiting

ContextOpioids are the mainstay therapy for patients affected by cancer pain. However, about 10-20% of patients do not benefit from the received analgesic treatment or experience side effects. Genetic variability might account for the variation in individual responses to opioids, both in terms of efficacy and toxicity. ObjectivesThe aim of this genome-wide association study (GWAS) was to identify genetic markers of opioid toxicity, in terms of nausea-vomiting. MethodsCancer patients receiving morphine, oxycodone, buprenorphine, and fentanyl were recruited from different European countries. Data about toxicity (nausea-vomiting score, NVS) and other relevant clinical information were collected, as well as genotyping data. Regression analysis between genotypes of 2,052 patients and NVS was performed, using appropriate covariates, with REGENIE software. ResultsWe found 65 variants associated with NVS (P-value < 1.0×10−5). Of note, 14 intronic variants on chromosome 2 were in NPAS2 gene, encoding a circadian transcription factor reported to play a role in another opioid side effect, the alteration of sleep. Some of these variants were previously identified as splicing quantitative trait loci of the NPAS2 gene. ConclusionsThis is the first GWAS, performed in more than two thousand individually genotyped patients treated with opioids for cancer pain, that investigated the genetic bases of opioid-induced nausea-vomiting. Although further studies are needed to confirm our findings and to characterize the functional role of the identified variants, our results emphasize the importance of performing large pharmacogenomic studies to identify germline variants associated with opioid response, with the ultimate goal of tailoring cancer pain therapies.

Cefadroxil targeting of SLC15A2/PEPT2 protects from colistin nephrotoxicity

Acute kidney injury (AKI) and chronic kidney disease (CKD) are considered interconnected syndromes, as AKI episodes may accelerate CKD progression and CKD increases the risk of AKI. Genome-wide association studies (GWAS) may identify novel actionable therapeutic targets. Human genome-wide association studies (GWAS) for AKI or CKD were combined with murine AKI transcriptomics datasets to identify 13 (ACACB, ACSM5, CNDP1, DPEP1, GATM, SLC6A12, AGXT2L1, SLC15A2, CTSS, ICAM1, ITGAX, ITGAM, PPM1J) potentially actionable therapeutic targets to modulate kidney disease severity across species and across the AKI-CKD spectrum. Among them, SLC15A2, encoding the cell membrane proton-coupled peptide transporter 2 (PEPT2), was prioritized for data mining and functional intervention studies in vitro and in vivo because of its known function to transport nephrotoxic drugs such as colistin and the possibility for targeting with small molecules already in clinical use, such as cefadroxil. Data mining disclosed that SLC15A2 was upregulated in the tubulointerstitium of human CKD, including diabetic nephropathy, and the upregulation was localized to proximal tubular cells. Colistin elicited cytotoxicity and a proinflammatory response in cultured human and murine proximal tubular cells that was decreased by concomitant exposure to cefadroxil. In proof-of-concept in vivo studies, cefadroxil protected from colistin nephrotoxicity in mice. The GWAS association of SLC15A2 with human kidney disease may be actionable and related to the modifiable transport of nephrotoxins causing repeated subclinical episodes of AKI and/or chronic nephrotoxicity.

Northwestern Himalayan common beans: A Treasure Trove for breeding resistant bean cultivars for multiple foliar pathogens

Common bean (Phaseolus vulgaris. L) is attacked by a lot of important foliar diseases like anthracnose, Bean Common Mosaic Virus, angular leaf spot, Bean Golden Yellow Mosaic Virus, and common bacterial blight. In the present study, we exploited anthracnose resistant germplasm of 122 common bean genotypes for the identification of broad spectrum and durable resistance for multiple foliar diseases. We utilized linked molecular markers and found some promising genotypes with 11 resistance genes. These genotypes possess significant potential as parental lines for gene pyramiding strategies, to enhance disease resistance in common beans. We also highlighted the need for new generation markers over SCAR markers to streamline genotypic screening and expedite the breeding of disease-resistant common bean varieties. Our phenotypic studies identified a few bean landraces highly resistant to the new BCMV NL-1n strain. Consequently, the genome wide association study also confirms the presence of already identified resistance genes. Additionally, our study reconfirms the presence of the recently identified bc-urgene in our material. The bean landraces of northern India contain novel regions associated with BCMV resistance on Pv03, Pv05, Pv04, Pv06, Pv07, Pv09, and Pv11. This study provides the list of bean genotypes that can be used to breed resistant cultivars and may also contain new resistance genes to a most important viral disease of common beans.

Chronic Overlapping Pain Conditions and Nociplastic Pain

Chronic Overlapping Pain Conditions (COPCs) are a subset of chronic pain conditions commonly comorbid with one another and more prevalent in women and assigned female at birth (AFAB) individuals. Pain experience in these conditions may better fit with a new mechanistic pain descriptor, nociplastic pain, and nociplastic pain may represent a shared underlying factor among COPCs. We applied GenomicSEM common-factor genome wide association study (GWAS) and multivariate transcriptome-wide association (TWAS) analyses to existing GWAS output for six COPCs in order to find genetic variation associated with nociplastic pain, followed by genetic correlation (linkage-disequilibrium score regression), gene-set and tissue enrichment analyses. We found 24 independent single nucleotide polymorphisms (SNPs), and 127 unique genes significantly associated with nociplastic pain, and showed nociplastic pain to be a polygenic trait with significant SNP-heritability. We found significant genetic overlap between multisite chronic pain and nociplastic pain, and to a smaller extent with rheumatoid arthritis and a neuropathic pain phenotype. Tissue enrichment analyses highlighted cardiac and thyroid tissue, and gene set enrichment analyses emphasized potential shared mechanisms in cognitive, personality, and metabolic traits and nociplastic pain along with distinct pathology in migraine and headache. We use a well-powered network approach to investigate nociplastic pain using existing COPC GWAS output, and show nociplastic pain to be a complex, heritable trait, in addition to contributing to understanding of potential mechanisms in development of nociplastic pain.

Syncope in Migraine: A Genome-Wide Association Study Revealing Distinct Genetic Susceptibility Variants Across Subtypes.

Syncope is characterized by the temporary loss of consciousness and is commonly associated with migraine. However, the genetic factors that contribute to this association are not well understood. This study investigated the specific genetic loci that make patients with migraine more susceptible to syncope as well as the genetic factors contributing to syncope and migraine comorbidity in a Han Chinese population in Taiwan. A genome-wide association study was applied to 1,724 patients with migraine who visited a tertiary hospital in Taiwan. The patients were genotyped using the Affymetrix Axiom Genome-Wide TWB 2.0 array and categorized into the following subgroups based on migraine type: episodic migraine, chronic migraine, migraine with aura, and migraine without aura. Multivariate regression analyses were used to assess the relationships between specific single-nucleotide polymorphisms (SNPs) and the clinical characteristics in patients with syncope and migraine comorbidity. In patients with migraine, SNPs were observed to be associated with syncope. In particular, the rs797384 SNP located in the intron region of LOC102724945 was associated with syncope in all patients with migraine. Additionally, four SNPs associated with syncope susceptibility were detected in the nonmigraine control group, and these SNPs differed from those in the migraine group, suggesting distinct underlying mechanisms. Furthermore, the rs797384 variant in the intron region of LOC102724945 was associated with the score on the Beck Depression Inventory. The novel genetic loci identified in this study will improve our understanding of the genetic basis of syncope and migraine comorbidity.

Network-based hub biomarker discovery for glaucoma

ObjectiveGlaucoma is an optic neuropathy and the leading cause of irreversible blindness worldwide. However, the early detection of glaucoma remains challenging, as chronic forms of glaucoma remain largely asymptomatic until...

Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study

Artificial intelligence (AI)-enabled electrocardiography (ECG) can be used to predict risk of future disease and mortality but has not yet been adopted into clinical practice. Existing model predictions do not have actionability at an individual patient level, explainability, or biological plausibi. We sought to address these limitations of previous AI-ECG approaches by developing the AI-ECG risk estimator (AIRE) platform. The AIRE platform was developed in a secondary care dataset (Beth Israel Deaconess Medical Center [BIDMC]) of 1 163 401 ECGs from 189 539 patients with deep learning and a discrete-time survival model to create a patient-specific survival curve with a single ECG. Therefore, AIRE predicts not only risk of mortality, but also time-to-mortality. AIRE was validated in five diverse, transnational cohorts from the USA, Brazil, and the UK (UK Biobank [UKB]), including volunteers, primary care patients, and secondary care patients. AIRE accurately predicts risk of all-cause mortality (BIDMC C-index 0·775, 95% CI 0·773-0·776; C-indices on external validation datasets 0·638-0·773), future ventricular arrhythmia (BIDMC C-index 0·760, 95% CI 0·756-0·763; UKB C-index 0·719, 95% CI 0·635-0·803), future atherosclerotic cardiovascular disease (0·696, 0·694-0·698; 0·643, 0·624-0·662), and future heart failure (0·787, 0·785-0·789; 0·768, 0·733-0·802). Through phenome-wide and genome-wide association studies, we identified candidate biological pathways for the prediction of increased risk, including changes in cardiac structure and function, and genes associated with cardiac structure, biological ageing, and metabolic syndrome. AIRE is an actionable, explainable, and biologically plausible AI-ECG risk estimation platform that has the potential for use worldwide across a wide range of clinical contexts for short-term and long-term risk estimation. British Heart Foundation, National Institute for Health and Care Research, and Medical Research Council.

Causal association between COVID-19 vaccination and thrombosis-related biomarkers/thrombosis/ischemic stroke: Mendelian randomization study

BackgroundObservational studies about the association between coronavirus disease 2019 (COVID-19) vaccination and thrombosis/ischemic stroke are inconsistent. The aim of this study is to assess the causality between COVID-19 vaccination and thrombosis-related biomarkers/thrombosis/ischemic stroke using mendelian randomization (MR) analysis. MethodsA two-sample MR analysis using publicly available genome-wide association study (GWAS) data was conducted. Causal effects were appraised using inverse variance weighted (IVW, as a primary method), with supplementary methods including constrained maximum likelihood and model averaging, MR-Robust Adjusted Profile Score, MR-Egger regression, simple mode, weighted median, and weighted mode. Sensitivity analyses were conducted using Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis. ResultsGenetically predicted COVID-19 vaccination was negatively associated with C-C motif chemokine 3 [CCL3, odds ratio (OR): 0.694, 95% confidence intervals (CI): 0.484-0.995] and multiple coagulation factor deficiency protein 2 (MCFD2, OR: 0.806, 95% CI: 0.675-0.963). Meanwhile, the IVW analysis revealed significant causal effects between genetically predicted COVID-19 vaccination and ischemic stroke (OR: 1.088, 95% CI: 1.006-1.177), large artery stroke (LAS, OR: 1.251, 95% CI: 1.028-1.521). The leave-one-out analysis revealed that no individual SNP exerted a significant effect on the overall causal estimate. ConclusionOur study provided evidence supporting a potential causal association of genetically predicted COVID-19 vaccination with CCL3 levels, MCFD2 levels, ischemic stroke risk and LAS risk. These results provide preliminary evidence of potential adverse associations, but further studies are required to fully understand the mechanisms and to validate these findings across broader populations.

The causal effects of lifestyle, circulating, pigment, and metabolic factors on early age-related macular degeneration: a comprehensive Mendelian randomization study

PurposeEarly detection of lifestyle factors, skin and hair color, circulating parameters, and metabolic comorbidities is crucial for personalized prevention and treatment of early age-related macular degeneration (AMD). This study aimed to assess the relationships between genetically predicted comprehensive risk factors and early AMD.Methods and resultsPublicly available genome-wide association study (GWAS) data were utilized to identify genetic variants significantly associated with each trait. We applied a Bonferroni-corrected significance level of P < 0.0017. P values between 0.0017 and 0.05 were considered suggestive associations. Univariable Mendelian randomization (MR) analyses revealed that elevated serum HDL-C, lower serum TG, and decreased three circulating fatty acids levels were robust indicators of an increased risk of early AMD (all P < 0.0017), with odds ratios (ORs) and 95% confidence intervals (CIs) of 1.218 (1.140–1.303), 0.784 (0.734–0.837), 0.772 (0.698–0.855), 0.776 (0.706–0.852), and 0.877 (0.798–0.963), respectively. Additionally, the “never eat wheat products”, “age started wearing glasses”, and “skin color” were significantly associated with the risk of early AMD (both P < 0.0017), with ORs (95% CIs) of 23.853 (2.731–208.323), 1.605 (1.269–2.030) and 1.190 (1.076–1.317), respectively. Multivariable MR analysis confirmed that elevated serum HDL-C (OR = 1.187, 1.064–1.324) increased the risk of early AMD, while higher serum TG (OR = 0.838, 0.738–0.950) was associated with a significantly lower risk. Furthermore, validation results indicated that serum HDL-C 1.201 (1.101–1.310) and TG 0.795 (0.732–0.864) were significantly associated with the risk of early AMD. There were suggestive associations of smoothies, chronotype, and hair color (0.0017 < P < 0.05), but sun/UV protection, smoking, BMI, diabetes, high blood pressure, cardiovascular diseases, fresh fruit intake, fish oil/cod liver oil supplement, sleeplessness, serum C-reactive protein level, and iron level were not associated with the risk of early AMD.ConclusionsOur comprehensive MR analysis demonstrated that elevated circulating HDL-C levels increase the risk of early AMD, while TG and fatty acid levels are associated with a decreased risk. These findings provide robust evidence for improved diagnosis and personalized prevention and treatment of early AMD.

Combining GWAS and RNA-Seq approaches identifies the FtADH1 gene for drought resistance in Tartary buckwheat

Drought is one of the major environmental constraints that significantly affects seedling emergence, yield, and quality of Tartary buckwheat, thereby hindering the development of its industry. However, the molecular mechanisms underlying drought tolerance genes in Tartary buckwheat remain largely unexplored. Alcohol dehydrogenase (ADH), one of the essential plant proteins, plays a crucial role in growth, development, and stress responses, but its specific role in drought resistance is still unclear. In this study, we identified an ADH gene FtADH1, using a membership function value of drought tolerance (MFVD) combined with a genome-wide association study (GWAS) and transcriptomic profiles that confers drought tolerance in Tartary buckwheat. Our findings demonstrated that the overexpression of FtADH1 in Arabidopsis and Tartary buckwheat hairy roots enhances drought tolerance by promoting root elongation and mitigating elevated levels of reactive oxygen species (ROS). Our findings demonstrated that FtADH1 can enhanced tolerance to drought stresses in both Tartary buckwheat and Arabidopsis. This study identifies the FtADH1 as a new player in affecting ROS level and the stress response of Tartary buckwheat by regulating protective enzyme activities at a high level to scavenge ROS and modulating root growth under drought stress. Further, we identified proteins interacting with FtADH1 through a prokaryotic expression pull-down assay combined with mass spectrometry, revealing that FtADH1 specifically interacts with the S-adenosyl-L-methionine (SAM) synthetase protein, FtSAMS1. Overexpression of FtSAMS1 was found to enhance ADH enzymatic activity, leading to increased SAM content in overexpressing Tartary buckwheat hairy roots under water-deficit conditions. Additionally, FtSAMS1 overexpression induced a drought-resistant phenotype in Arabidopsis and Tartary buckwheat hairy roots under drought stress, revealing the biological function of FtADH1. Evolutionary analysis indicates that ADH1 in Fagopyrum species has undergone significant evolutionary events, including duplication and purifying selection, which may contribute to functional diversification and adaptive advantages such as drought resistance in cultivated buckwheat. In summary, this study proposes that FtADH1 is a key contributor to drought tolerance, and its interaction with FtSAMS1 holds potential for the development of drought-resistant varieties in Tartary buckwheat and its relative species.

Alzheimer’s disease-associated protective variant Plcg2-P522R modulates peripheral macrophage function in a sex-dimorphic manner

Genome-wide association studies have identified a protective mutation in the phospholipase C gamma 2 (PLCG2) gene which confers protection against Alzheimer’s disease (AD)-associated cognitive decline. Therefore, PLCG2, which is primarily expressed in immune cells, has become a target of interest for potential therapeutic intervention. The protective allele, known as P522R, has been shown to be hyper-morphic in microglia, increasing phagocytosis of amyloid-beta (Aβ), and increasing the release of inflammatory cytokines. However, the effect of this protective mutation on peripheral tissue-resident macrophages, and the extent to which sex modifies this effect, has yet to be assessed. Herein, we show that peripheral macrophages carrying the P522R mutation do indeed show functional differences compared to their wild-type (WT) counterparts, however, these alterations occur in a sex-dependent manner. In macrophages from females, the P522R mutation increases lysosomal protease activity, cytokine secretion, and gene expression associated with cytokine secretion and apoptosis. In contrast, in macrophages from males, the mutation causes decreased phagocytosis and lysosomal protease activity, modest increases in cytokine secretion, and induction of gene expression associated with negative regulation of the immune response. Taken together, these results suggest that the mutation may be conferring different effects dependent on sex and cell type, and highlight the importance of considering sex as a biological variable when assessing the effects of genetic variants and implications for potential immune system-targeted therapies.

Causal Association Between Heart Failure and Sepsis: Insights from Mendelian Randomization and Observational Studies.

We aimed to identify the association between heart failure (HF) with sepsis and its mortality through Mendelian randomization (MR) and observational studies. In MR study, we utilized public summary statistics from genome-wide association studies (GWAS). We conducted univariable, multivariable and network MR analyses to investigate causal relationships between HF and sepsis, and mediating roles of cytokines and growth factors. We performed an observational analysis using the MIMIC-IV database. Propensity score matching (PSM) and logistic regression models were employed to explore causal relationships between HF and sepsis, besides short-, medium-, and long-term mortality associated with sepsis. In univariable MR analysis, there was a causal relationship between genetically predicted HF (OR = 1.15, 95% CI = 1.02-1.29, P = 0.025) and sepsis. In multivariable and network MR analyses, βNGF was independently associated with sepsis. And it mediated 17.6% (95% CI 2.45-30.72%) of HF effect on sepsis. In the real-world observational study, acute on chronic diastolic (congestive) heart failure (DCHF) (OR = 1.59, 95% CI = 1.31-1.93, P < 0.001), acute DCHF (OR = 2.52, 95% CI = 1.61-3.95, P = 0.010), and acute diastolic heart failure (DHF) (OR = 1.52, 95% CI = 1.06-2.19, P = 0.024) after PSM were associated with occurrence of sepsis. Chronic systolic (congestive) heart failure (SCHF) was associated with increased 28-day (OR = 1.75, 95% CI = 1.06-2.91, P = 0.030), 1-year (OR = 1.80, 95% CI = 1.08-3.00, P = 0.023), and 2-year (OR = 1.86, 95% CI = 1.12-3.10, P = 0.018) mortality in sepsis. Observational and MR analyses showed a causal relationship between HF and sepsis. Chronic SCHF was related to increased short/long-term mortality in sepsis. Our study indicated βNGF a key factor in HF-induced sepsis.