Integrated GWAS, linkage, and transcriptome analysis to identify genetic loci and candidate genes for photoperiod sensitivity in maize.

Introduction: Maize photosensitivity and the control of flowering not only are important for reproduction, but also play pivotal roles in the processes of domestication and environmental adaptation, especially involving the utilization strategy of tropical maize in high-latitude regions. Methods: In this study, we used a linkage mapping population and an inbred association panel with the photoperiod sensitivity index (PSI) phenotyped under different environments and performed transcriptome analysis of T32 and QR273 between long-day and short-day conditions. Results: The results showed that PSIs of days to tasseling (DTT), days to pollen shedding (DTP), and days to silking (DTS) indicated efficacious interactions with photoperiod sensitivity for maize latitude adaptation. A total of 48 quantitative trait loci (QTLs) and 252 quantitative trait nucleotides (QTNs) were detected using the linkage population and the inbred association panel. Thirteen candidate genes were identified by combining the genome-wide association study (GWAS) approach, linkage analysis, and transcriptome analysis, wherein five critical candidate genes, MYB163, bif1, burp8, CADR3, and Zm00001d050238, were significantly associated with photoperiod sensitivity. Discussion: These results would provide much more abundant theoretical proofs to reveal the genetic basis of photoperiod sensitivity, which would be helpful to understand the genetic changes during domestication and improvement and contribute to reducing the barriers to use of tropical germplasm.

A genome-wide association study reveals molecular mechanism underlying powdery mildew resistance in cucumber.

BACKGROUND: Powdery mildew is a disease with one of the most substantial impacts on cucumber production globally. The most efficient approach for controlling powdery mildew is the development of genetic resistance; however, few genes associated with inherent variations in cucumber powdery mildew resistance have been identified as of yet. RESULTS: In this study, we re-sequence 299 cucumber accessions, which are divided into four geographical groups. A genome-wide association study identifies 50 sites significantly associated with natural variations in powdery mildew resistance. Linkage disequilibrium analysis further divides these 50 sites into 32 linkage disequilibrium blocks containing 41 putative genes. Virus-induced gene silencing and gene expression analysis implicate CsGy5G015960, which encodes a phosphate transporter, as the candidate gene regulating powdery mildew resistance. On the basis of the resequencing data, we generate five CsGy5G015960 haplotypes, identifying Hap.1 as the haplotype most likely associated with powdery mildew resistance. In addition, we determine that a 29-bp InDel in the 3' untranslated region of CsGy5G015960 is responsible for mRNA stability. Overexpression of CsGy5G015960Hap.1 in the susceptible line enhances powdery mildew resistance and phosphorus accumulation. Further comparative RNA-seq analysis demonstrates that CsGy5G015960Hap.1 may regulate cucumber powdery mildew resistance by maintaining a higher H2O2 level through the depletion of multiple class III peroxidases. CONCLUSIONS: Here we identify a candidate powdery mildew-resistant gene in cucumber using GWAS. The identified gene may be a promising target for molecular breeding and genetic engineering in cucumber to enhance powdery mildew resistance.

Genetic characterization of cashmere goat (Capra hircus) populations in Mongolia.

Objective: Characterization studies of the phenotypic and genetic diversity of Mongolian goats are limited, despite several goat breeds being registered in the country. This study aimed to evaluate the phenotypic and genetic diversity of 14 cashmere goat populations in Mongolia, consisting largely of identified goat breeds. Methods: Body weight, cashmere quality, and coat color were the phenotypic traits considered in this study. A linear model was used to fit body weight and cashmere traits, and least squares means (LSMs) were estimated for the region and location classes. Genetic diversity and structure were assessed using a goat 50K SNP array. Results: The studied populations exhibited greater phenotypic diversity at the regional level. A very small overall differentiation index (Fst: 0.017) was revealed by Wright's Fst and a very small overall inbreeding index (F ROH1 :0.019) was revealed based on runs of homozygosity. Genetic clustering of populations by principal components showed large variances for the two goat populations of the Russian admixture (Gobi Gurvan Saikhan and Uuliin Bor), and smaller but differentiated clusters for the remaining populations. Similar results were observed in the admixture analysis, which identified populations with the highest (Govi Gurvan Saikhan and Uuliin Bor) and lowest (Tsagaan Ovoo Khar) exotic admixtures. A genomewide association study (GWAS) of body weight and cashmere traits identified a few significant variants on chromosomes 2, 4, 5, 9, and 15, with the strongest variant for cashmere yield on chromosome 4. The GWAS on coat color yielded nine significant variants, with the strongest variants located on chromosomes 6, 13, and 18 and potential associations with KIT, ASIP, and MC1R genes. These signals were also found in other studies on coat color and patterns in goats. Conclusion: Mongolian cashmere goats showed relatively low genetic differentiation and low inbreeding levels, possibly caused by the traditional pastoral livestock management system and the practice of trading breeding bucks across provinces, along with a recent increase in the goat population. Further investigation of cashmere traits using larger samples and alternative methods may help identify the genes or genomic regions underlying cashmere quality in goats.

Cross-ancestry analysis of brain QTLs enhances interpretation of schizophrenia genome-wide association studies.

Research on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet most of these studies have been centered on European populations, leading to a constrained understanding of population diversities and disease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA, n = 158), Europeans (EUR, n = 408), and East Asians (EAS, n = 217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patterns of genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737 cis-eQTLs linked to 1,276 genes and 198,769 SNPs were found to be specific to non-EUR populations. Over 90% of observed population differences in eQTLs could be traced back to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare in the EUR population. Integrating brain eQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched populations compared to mismatched ones. Prioritization analysis identified five risk genes (SFXN2, VPS37B, DENR, FTCDNL1, and NT5DC2) and three potential regulatory variants in known risk genes (CNNM2, MTRFR, and MPHOSPH9) that were missed in the EUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merely increasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the biological underpinnings of population structures but also pave the way for the identification of risk genes in SCZ.

A Mendelian analysis of the causality between inflammatory cytokines and digestive tract cancers.

PURPOSE: In this study, we performed a two-sample Mendelian randomization (MR) analysis to assess the causality between inflammatory cytokines and the risk of digestive tract cancers (DTCs). Furthermore, we conducted a molecular docking study to predict the therapeutic mechanisms of traditional Chinese medicine (TCM) compounds in the treatment of DTCs. METHODS: In our MR analysis, genetic variations associated with eight types of DTCs were utilized, which were sourced from a large publicly available genome-wide association study dataset (7929 cases and 1 742 407 controls of European ancestry) and inflammatory cytokines data from a genome-wide association study summary of 8293 European participants. Inverse-variance weighted method, MR-Egger, and weighted median were performed to analyze and strengthen the final results. We investigated the effects of 41 inflammatory molecules on 8 types of DTCs. Subsequently, the effect of DTCs on positive inflammatory factors was analyzed by means of inverse MR. Molecular docking was exploited to predict therapeutic targets with TCM compounds. RESULTS: Interleukin-7, interleukin-16, macrophage colony-stimulating factor, monokine induced by interferon-gamma, and vascular endothelial growth factor may be significantly associated with various types of DTCs. Five TCM compounds (baicalin, berberine, curcumin, emodin, and salidroside) demonstrated better binding energies to both interleukin-7 and vascular endothelial growth factor than carboplatin. CONCLUSION: This study provides strong evidence to support the potential causality of some inflammatory cytokines on DTCs and indicates the potential molecular mechanism of TCM compounds in the treatment of DTCs. Key message What is already known on this topic  The increasing evidence indicates that inflammatory cytokines are implicated in the pathogenesis of digestive tract cancers (DTCs). Nevertheless, the causal relationship between inflammatory cytokines and DTCs remains indistinct. Additionally, certain traditional Chinese medicine compounds have been demonstrated to treat DTCs by influencing inflammatory factors, yet their underlying potential mechanisms remain ambiguous. What this study adds  In this study, Mendelian randomization analysis was performed for the first time regarding the causality between human inflammatory cytokines and eight types of DTCs, which revealed that inflammatory factors may play different roles in different types of DTCs. Moreover, molecular docking of key inflammatory factors was implemented, indicating the targets for drug actions. How this study might affect research, practice, or policy  This research has the potential to reveal the causality between 41 inflammatory factors and 8 DTCs, offering novel perspectives for the prevention and management strategies of DTCs. Additionally, it indicates the targets for the actions of traditional Chinese medicine on the key inflammatory factors of these cancers.

GWAS and polygenic risk score of severe COVID-19 in Eastern Europe.

Background: COVID-19 disease has infected more than 772 million people, leading to 7 million deaths. Although the severe course of COVID-19 can be prevented using appropriate treatments, effective interventions require a thorough research of the genetic factors involved in its pathogenesis. Methods: We conducted a genome-wide association study (GWAS) on 7,124 individuals (comprising 6,400 controls who had mild to moderate COVID-19 and 724 cases with severe COVID-19). The inclusion criteria were acute respiratory distress syndrome (ARDS), acute respiratory failure (ARF) requiring respiratory support, or CT scans indicative of severe COVID-19 infection without any competing diseases. We also developed a polygenic risk score (PRS) model to identify individuals at high risk. Results: We identified two genome-wide significant loci (P-value <5 × 10-8) and one locus with approximately genome-wide significance (P-value = 5.92 × 10-8-6.15 × 10-8). The most genome-wide significant variants were located in the leucine zipper transcription factor like 1 (LZTFL1) gene, which has been highlighted in several previous GWAS studies. Our PRS model results indicated that individuals in the top 10% group of the PRS had twice the risk of severe course of the disease compared to those at median risk [odds ratio = 2.18 (1.66, 2.86), P-value = 8.9 × 10-9]. Conclusion: We conducted one of the largest studies to date on the genetics of severe COVID-19 in an Eastern European cohort. Our results are consistent with previous research and will guide further epidemiologic studies on host genetics, as well as for the development of targeted treatments.

A Next-Generation Combinatorial Genomic Strategy Scans Genomic Loci Governing Heat Stress Tolerance in Chickpea.

In the wake of rising earth temperature, chickpea crop production is haunted by the productivity crisis. Chickpea, a cool season legume manifests tolerance in several agro-physiological level, which is complex quantitative in nature, and regulated by multiple genes and genetic networks. Understanding the molecular genetic basis of this tolerance and identifying key regulators can leverage chickpea breeding against heat stress. This study employed a genomics-assisted breeding strategy utilizing multi-locus GWAS to identify 10 key genomic regions linked to traits contributing to heat stress tolerance in chickpea. These loci subsequently delineated few key candidates and hub regulatory genes, such as RAD23b, CIPK25, AAE19, CK1 and WRKY40, through integrated genomics, transcriptomics and interactive analyses. The differential transcript accumulation of these identified candidates in contrasting chickpea accessions suggests their potential role in heat stress tolerance. Differential ROS accumulation along with their scavengers' transcript abundance aligning with the expression of identified candidates in the contrasting chickpea accessions persuade their regulatory significance. Additionally, their functional significance is ascertained by heterologous expression and subsequent heat stress screening. The high confidence genomic loci and the superior genes and natural alleles delineated here has great potential for swift genomic interventions to enhance heat resilience and yield stability in chickpea.

Integrated GWAS and transcriptome analysis reveals key genes associated with muscle fibre and fat traits in Gushi chicken.

1. In the following experiment meat quality traits of a Gushi-Anka F2 resource population were measured, and their heritability estimated. Intramuscular fat (IMF) had medium heritability (0.35) but leg muscle fibre density (LMD), leg muscle fibre diameter (LMF), breast muscle fibre density (BMD), fresh fat content (FFA), and absolute dry fat content (AFC) had low heritability (0-0.2). The IMF presented the most important genetic additive effect among the poultry meat quality-related traits studied.2. The phenotypic data of meat quality traits in the Gushi-Anka F2 resource population were combined with genotyping by sequencing (GBS) data to obtain genotype data. Six meat quality traits in 734 birds were analysed by GWAS. Based on these variants, 83 significant (-log10(p) > 4.42) single nucleotide polymorphisms and four quantitative trait loci (QTL) regions corresponding to 175 genes were identified. Further linkage disequilibrium (LD) analysis was conducted on chromosome 13 (Chr13) and chromosome 27 (Chr27) QTL regions.3. Based on the transcriptome data and GWAS results, 12 shared genes - ITGB3, DNAJC27, ETV4, C7orf50, FKBP1B, G3BP1, IGF2BP1, KCNH6, LOC416263, SCARA5, SMIM5 and TBL1XR1 were identified as candidate genes influencing muscle fibre and fat traits.

Novel risk loci for COVID-19 hospitalization among admixed American populations.

The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

Potentially functional variants of PARK7 and DDR2 in ferroptosis-related genes predict survival of non-small cell lung cancer patients.

Ferroptosis, a form of regulated cell death, is characterized by iron-dependent lipid peroxidation. It is recognized increasingly for its pivotal role in both cancer development and the response to cancer treatments. We assessed associations between 370,027 single-nucleotide polymorphisms (SNPs) within 467 ferroptosis-related genes and survival of non-small cell lung cancer (NSCLC) patients. Data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial served as our discovery dataset, while the Harvard Lung Cancer Susceptibility Study used as our validation dataset. For SNPs that remained statistically significantly associated with overall survival (OS) in both datasets, we employed a multivariable stepwise Cox proportional hazards regression model with the PLCO dataset. Ultimately, two independent SNPs, PARK7 rs225120 C>T and DDR2 rs881127 T>C, were identified with adjusted hazard ratios of 1.32 (95% confidence interval = 1.15-1.52, p = .0001) and 1.34 (95% confidence interval = 1.09-1.64, p = .006) for OS, respectively. We aggregated these two SNPs into a genetic score reflecting the number of unfavorable genotypes (NUG) in further multivariable analysis, revealing a noteworthy association between increased NUG and diminished OS (ptrend = .001). Additionally, an expression quantitative trait loci analysis indicated that PARK7 rs225120T genotypes were significantly associated with higher PARK7 mRNA expression levels in both whole blood and normal lung tissue. Conversely, DDR2 rs881127C genotypes were significantly associated with lower DDR2 mRNA expression levels in normal lung tissue. Our findings suggest that genetic variants in the ferroptosis-related genes PARK7 and DDR2 are associated with NSCLC survival, potentially through their influence on gene expression levels.

Causal interpretations of family GWAS in the presence of heterogeneous effects.

Family-based genome-wide association studies (GWASs) are often claimed to provide an unbiased estimate of the average causal effects (or average treatment effects; ATEs) of alleles, on the basis of an analogy between the random transmission of alleles from parents to children and a randomized controlled trial. We show that this claim does not hold in general. Because Mendelian segregation only randomizes alleles among children of heterozygotes, the effects of alleles in the children of homozygotes are not observable. This feature will matter if an allele has different average effects in the children of homozygotes and heterozygotes, as can arise in the presence of gene-by-environment interactions, gene-by-gene interactions, or differences in linkage disequilibrium patterns. At a single locus, family-based GWAS can be thought of as providing an unbiased estimate of the average effect in the children of heterozygotes (i.e., a local average treatment effect; LATE). This interpretation does not extend to polygenic scores (PGSs), however, because different sets of SNPs are heterozygous in each family. Therefore, other than under specific conditions, the within-family regression slope of a PGS cannot be assumed to provide an unbiased estimate of the LATE for any subset or weighted average of families. In practice, the potential biases of a family-based GWAS are likely smaller than those that can arise from confounding in a standard, population-based GWAS, and so family studies remain important for the dissection of genetic contributions to phenotypic variation. Nonetheless, their causal interpretation is less straightforward than has been widely appreciated.

Cluster Buster: A Machine Learning Algorithm for Genotyping SNPs from Raw Data.

Genotyping single nucleotide polymorphisms (SNPs) is fundamental to disease research, as researchers seek to establish links between genetic variation and disease. Although significant advances in genome technology have been made with the development of bead-based SNP genotyping and Genome Studio software, some SNPs still fail to be genotyped, resulting in "no-calls" that impede downstream analyses. To recover these genotypes, we introduce Cluster Buster, a genotyping neural network and visual inspection system designed to improve the quality of neurodegenerative disease (NDD) research. Concordance analysis with whole genome sequencing (WGS) and imputed genotypes validated the reliability of predicted genotypes, with dozens of high-performing SNPs across LRRK2, APOE, and GBA loci achieving at least 90% concordance per SNP location. Further analysis of concordance between Genome Studio genotypes and imputed and WGS genotypes revealed discrepancies between the genotyping technologies, highlighting the need for selective application of Cluster Buster on SNP locations based on concordance rates. Cluster Buster's implementation significantly reduces manual labor for recovering no-call SNPs, refining genotype quality for the Global Parkinson's Genetics Program (GP2). This system facilitates better imputation and GWAS outcomes, ultimately contributing to a deeper understanding of genetic factors in NDDs.

SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model.

Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.

Investigative power of Genomic Informational Field Theory (GIFT) relative to GWAS for genotype-phenotype mapping.

Identifying associations between phenotype and genotype is the fundamental basis of genetic analyses. Inspired by frequentist probability and the work of R.A. Fisher, genome-wide association studies (GWAS) extract information using averages and variances from genotype-phenotype datasets. Averages and variances are legitimated upon creating distribution density functions obtained through the grouping of data into categories. However, as data from within a given category cannot be differentiated, the investigative power of such methodologies is limited. Genomic Informational Field Theory (GIFT) is a method specifically designed to circumvent this issue. The way GIFT proceeds is opposite to that of GWAS. Whilst GWAS determines the extent to which genes are involved in phenotype formation (bottom-up approach), GIFT determines the degree to which the phenotype can select microstates (genes) for its subsistence (top-down approach). Doing so requires dealing with new genetic concepts, a.k.a. genetic paths, upon which significance levels for genotype-phenotype associations can be determined. By using different datasets obtained in ovis aries related to bone growth (Dataset-1) and to a series of linked metabolic and epigenetic pathways (Dataset-2), we demonstrate that removing the informational barrier linked to categories enhances the investigative and discriminative powers of GIFT, namely that GIFT extracts more information than GWAS. We conclude by suggesting that GIFT is an adequate tool to study how phenotypic plasticity and genetic assimilation are linked.

Causal relationship between rheumatoid arthritis and carpal tunnel syndrome: a bidirectional two-sample Mendelian randomization study.

BACKGROUND: Although there is considerable evidence of a robust correlation between rheumatoid arthritis (RA) and carpal tunnel syndrome (CTS) in previous research, the causal link between the two remains a topic of controversy. METHODS: We conducted a two-sample Mendelian randomization (MR) study to explore the causal impact of RA on CTS. We obtained aggregate data from genome-wide association studies (GWAS) of CTS (ebi database and GEO database) and RA (FinnGen database). This study employed five MR analysis methods, with a focus on the inverse variance-weighted (IVW) method. Sensitivity analyses were conducted to ensure the robustness of the results of this study. Additionally, we performed reverse MR analysis. RESULTS: We selected 84 and 78 single nucleotide polymorphisms (SNPs) significantly associated with RA from two databases as instrumental variables (IVs), respectively. Our results showed that RA patients have a higher risk of getting CTS regardless of whether the ebi database (IVW, OR = 1.045, 95% CI: 1.016-1.075, P = 0.002) or the GEO database (IVW, OR = 1.001, 95% CI: 1.001-1.002, P = 0.001) is selected for CTS data. However, the MR analysis showed no causal link between CTS and the increased risk of RA (ebi: IVW, OR = 1.084, 95% CI: 0.918-1.279, P = 0.341; GEO: IVW, OR = 1.968, 95% CI: 0.011-360.791, P = 0.799). CONCLUSION: The analysis revealed that RA can increase the risk of CTS, but did not support the causal relationship that CTS can increase the risk of RA.

Regulatory elements in SEM1-DLX5-DLX6 (7q21.3) locus contribute to genetic control of coronal nonsyndromic craniosynostosis and bone density-related traits.

Purpose: The etiopathogenesis of coronal nonsyndromic craniosynostosis (cNCS), a congenital condition defined by premature fusion of 1 or both coronal sutures, remains largely unknown. Methods: We conducted the largest genome-wide association study of cNCS followed by replication, fine mapping, and functional validation of the most significant region using zebrafish animal model. Results: Genome-wide association study identified 6 independent genome-wide-significant risk alleles, 4 on chromosome 7q21.3 SEM1-DLX5-DLX6 locus, and their combination conferred over 7-fold increased risk of cNCS. The top variants were replicated in an independent cohort and showed pleiotropic effects on brain and facial morphology and bone mineral density. Fine mapping of 7q21.3 identified a craniofacial transcriptional enhancer (eDlx36) within the linkage region of the top variant (rs4727341; odds ratio [95% confidence interval], 0.48[0.39-0.59]; P = 1.2E-12) that was located in SEM1 intron and enriched in 4 rare risk variants. In zebrafish, the activity of the transfected human eDlx36 enhancer was observed in the frontonasal prominence and calvaria during skull development and was reduced when the 4 rare risk variants were introduced into the sequence. Conclusion: Our findings support a polygenic nature of cNCS risk and functional role of craniofacial enhancers in cNCS susceptibility with potential broader implications for bone health.

Branched-chain amino acids and risk of lung cancer: insights from mendelian randomization and NHANES III.

Background: Recent studies have observed the relationships of circulatory and dietary intake of branched-chain amino acids (BCAAs) with long-term risk of certain cancers. However, the exact causality of BCAA with lung cancer (LUCA) and its pathological subtypes remains obscure. The aim of this study is to investigate the association between BCAA metabolism and risk of LUCA. Methods: Here we conducted Mendelian randomization (MR) and observational epidemiological analyses to investigate the association between BCAA and risk of LUCA. With single nucleotide polymorphism (SNP)-phenotype association data extracted from genome-wide association studies (GWAS), we performed univariate and multivariate MR analyses to infer the causal effect of circulatory BCAA concentrations on LUCA. We further investigated the effects of several potential mediators and quantified the mediation effects. Population-level analyses were performed in the National Health and Nutrition Examination Survey (NHANES) III. Results: Our results demonstrated that genetically predicted circulatory valine concentrations causally increased the risk of overall LUCA [odds ratio (OR) =1.324, 95% confidence interval (CI): 1.058-1.658, P=0.01]. For pathological subgroups, elevated levels of leucine, isoleucine, valine, and total BCAA were founded to be significantly associated with a higher risk of squamous cell lung cancer (LUSC); however, they did not significantly affect lung adenocarcinoma (LUAD). Moreover, body mass index (BMI) mediated approximately 3.91% (95% CI: 1.22-7.18%) of the total effect of leucine on LUSC. In the NHANES III population, dietary total BCAA intake was significantly associated with BMI ≥30 kg/m2, while no non-linear relationships were observed. Conclusions: This study provides genetic evidence for the histology-specific causality of BCAA on LUCA and implies the mediation role of BMI in this relationship. Further studies are needed to confirm these findings and elucidate the underlying mechanisms.

Causal relationship between gut microbiota and male erectile dysfunction: a Mendelian randomization analysis.

Background: Several observational studies have reported an association between gut microbiota and male erectile dysfunction (ED). However, it remains unclear whether there is a causal relationship between gut microbiota and male ED. Thus, we aimed to investigate the potential causal relationship between gut microbiota and male ED through Mendelian randomization (MR) analysis. Objective: To assess the causal relationship between gut microbiota and male ED, we performed a two-sample MR analysis. Methods: We obtained gut microbiota genome-wide association studies (GWAS) data from the MiBioGen consortium and publicly available GWAS data on male ED from the OPEN GWAS database. Subsequently, we performed a two-sample MR analysis to evaluate the causal relationship between gut microbiota and male ED. Finally, we performed sensitivity analysis, including Cochran's Q test, MR-Egger intercept analysis, MR-PRESSO, and leave-one-out analysis, to assess the level of heterogeneity and horizontal pleiotropy in the results. Results: Our MR analysis revealed a negative causal relationship between the genus Ruminococcaceae UCG013 and male ED (OR = 0.761, 95% CI 0.626-0.926), while the family Lachnospiraceae, genus Lachnospiraceae NC2004 group, genus Oscillibacter, and genus Tyzzerella3 may be associated with an increased risk of male ED, with the highest risk observed for family Lachnospiraceae (OR = 1.264, 95% CI 1.063-1.504). Furthermore, sensitivity analysis confirmed the reliability of our positive findings. Conclusion: Our MR analysis revealed a causal relationship between gut microbiota and male ED. This may contribute to a better understanding of the potential applications of gut microbiota in the occurrence and treatment of male ED.