Investigating the causal relationship between thyroid dysfunction diseases and osteoporosis: a two-sample Mendelian randomization analysis.

The prevalence of thyroid dysfunction diseases (TDFDs) and osteoporosis (OP) is high. Previous studies have indicated a potential association between TDFDs and OP, yet the causal direction remains unclear. This study aimed to investigate the potential causal relationship between TDFDs and the risk of developing OP and related fractures. We obtained pooled data from genome-wide association studies (GWASs) conducted on TDFDs and OP in European populations and identified single-nucleotide polymorphisms (SNPs) with genome-wide significance levels associated with exposure to TDFDs as instrumental variables. Inverse variance weighted (IVW) was employed as the primary method for Mendelian randomization (MR) analysis, supplemented by MR‒Egger, weighted median, simple mode and weighted mode methods. Sensitivity analyses were conducted to evaluate the robustness of the findings. The IVW method demonstrated an increased risk of OP in patients with TDFDs, including hyperthyroidism and hypothyroidism (TDFDs: OR = 1.11; 95% CI 1.09, 1.13; hypothyroidism: OR = 1.14; 95% CI 1.10, 1.17; hyperthyroidism: OR = 1.09; 95% CI 1.06, 1.12). These findings were supported by supplementary analysis, which revealed a positive correlation between TDFDs and the risk of OP. Multiple sensitivity analyses confirmed the absence of horizontal pleiotropy in the study, thus indicating the robustness of our results. The causal relationship between TDFDs and increased risk of OP implies the need for early bone mineral density (BMD) screening and proactive prevention and treatment strategies for individuals with TDFDs.

Genome-wide analysis reveals genomic diversity and signatures of selection in Qinchuan beef cattle.

BACKGROUND: Indigenous Chinese cattle have abundant genetic diversity and a long history of artificial selection, giving local breeds advantages in adaptability, forage tolerance and resistance. The detection of selective sweeps and comparative genome analysis of selected breeds and ancestral populations provide a basis for understanding differences among breeds and for the identification and utilization of candidate genes. We investigated genetic diversity, population structure, and signatures of selection using genome-wide sequencing data for a new breed of Qinchuan cattle (QNC, n = 21), ancestral Qinchuan cattle (QCC, n = 20), and Zaosheng cattle (ZSC, n = 19). RESULTS: A population structure analysis showed that the ancestry components of QNC and ZSC were similar. In addition, the QNC and ZSC groups showed higher proportions of European taurine ancestry than that of QCC, and this may explain the larger body size of QNC, approaching that of European cattle under long-term domestication and selection. A neighbor-joining tree revealed that QCC individuals were closely related, whereas QNC formed a distinct group. To search for signatures of selection in the QNC genome, we evaluated nucleotide diversity (θπ), the fixation index (FST) and Tajima's D. Overlapping selective sweeps were enriched for one KEGG pathway, the apelin signaling pathway, and included five candidate genes (MEF2A, SMAD2, CAMK4, RPS6, and PIK3CG). We performed a comprehensive review of genomic variants in QNC, QCC, and ZSC using whole-genome sequencing data. QCC was rich in novel genetic diversity, while diversity in QNC and ZSC cattle was reduced due to strong artificial selection, with divergence from the original cattle. CONCLUSIONS: We identified candidate genes associated with production traits. These results support the success of selective breeding and can guide further breeding and resource conservation of Qinchuan cattle.

Systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for lung cancer.

BACKGROUND: Drug repurposing provides a cost-effective approach to address the need for lung cancer prevention and therapeutics. We aimed to identify actionable druggable targets using Mendelian randomization (MR). METHODS: Summary-level data of gene expression quantitative trait loci (eQTLs) were sourced from the eQTLGen resource. We procured genetic associations with lung cancer and its subtypes from the TRICL, ILCCO studies (discovery) and the FinnGen study (replication). We implemented Summary-data-based Mendelian Randomization analysis to identify potential therapeutic targets for lung cancer. Colocalization analysis was further conducted to assess whether the identified signal pairs shared a causal genetic variant. FINDINGS: In the main analysis dataset, we identified 55 genes that demonstrate a causal relationship with lung cancer and its subtypes. However, in the replication cohort, only three genes were found to have such a causal association with lung cancer and its subtypes, and of these, HYKK (also known as AGPHD1) was consistently present in both the primary analysis dataset and the replication cohort. Following HEIDI tests and colocalization analyses, it was revealed that HYKK (AGPHD1) is associated with an increased risk of squamous cell carcinoma of the lung, with an odds ratio and confidence interval of OR = 1.28,95%CI = 1.24 to 1.33. INTERPRETATION: We have found that the HYKK (AGPHD1) gene is associated with an increased risk of squamous cell carcinoma of the lung, suggesting that this gene may represent a potential therapeutic target for both the prevention and treatment of lung squamous cell carcinoma.

Assessing the causal relationship of birth weight and childhood obesity on osteoarthritis: a Mendelian randomization study.

Obesity is associated with osteoarthritis (OA), but few studies have used fetal origin to explore the association. Our study aims to disentangle the causality between birth weight, childhood obesity, and adult OA using Mendelian randomization (MR). We identified single nucleotide polymorphisms (SNPs) related to birth weight (n = 298,142) and childhood obesity (n = 24,160) from two genome-wide association studies contributed by the Early Growth Genetics Consortium. Summary statistics of OA and its phenotypes (knee, hip, spine, hand, thumb, and finger OA) from the Genetics of Osteoarthritis Consortium (n = 826,690) were used to estimate the effects of SNPs on OA. Multivariable MR (MVMR) was conducted to investigate the independent effects of exposures. It turned out that genetically predicted standard deviation increase in birth weight was not associated with OA. In contrast, there was a marginally positive effect of childhood obesity on total [odds ratio (OR) = 1.07, 95% confidence interval (CI) = 1.00, 1.15 using IVW], knee (OR = 1.13, 95% CI = 1.05, 1.22 using weighted median), hip (OR = 1.13, 95% CI = 1.04, 1.24 using IVW), and spine OA (OR = 1.12, 95% CI = 1.03, 1.22 using IVW), but not hand, thumb, or finger OA. MVMR indicated a potential adulthood body mass index-dependent causal pathway between childhood obesity and OA. In conclusion, no association of birth weight with OA was suggested. Childhood obesity, however, showed a causality with OA in weight-bearing joints, which seems to be a general association of obesity with OA.

Circulating interleukin-27 is associated with the risk of chronic periodontitis and allergic rhinitis: A Mendelian randomization analysis.

BACKGROUND: Chronic periodontitis (CP) and allergic rhinitis (AR) have attracted wide attention as global public health problems with high incidence. Recent studies have shown that circulating interleukin-27 (IL-27) is associated with the risk of CP and AR. The aim of this study is to analyze the causal effect between them using Mendelian randomization (MR). METHODS: Bidirectional MR analyses were performed with the use of publicly available genome-wide association study (GWAS) data. Summary data on circulating IL-27, CP, and AR published in genome-wide association studies were collected. Instrumental variables (IV) were extracted using assumptions of correlation, independence and exclusivity as criteria. Inverse variance weighting (IVW) was used as the main method, combined with weighted median method (WM) and MR-Egger and other MR Analysis methods for causal inference of exposure and outcome. Cochran's Q and MR-Egger intercept were used for sensitivity analysis. RESULTS: The IVW study showed a causal effect between increased circulating IL-27 levels and increased risk of CP (OR = 1.14, 95%CI = 1.02-1.26, p = .020). Similarly, the increase of circulating IL-27 level had a causal effect on the decreased risk of AR (OR = 0.88, 95%CI = 0.80-0.97, p = .012). In addition, IVW study found that there was a causal between the increased risk of CP and circulating IL-27 level (OR = 1.05, 95%CI = 1.01-1.10, p = .016). However, there was no significant causal relationship between the risk of AR and circulating IL-27 levels (OR = 0.97, 95%CI = 0.91-1.02, p = .209). no significant heterogeneity or horizontal pleiotropy was found in sensitivity analysis. CONCLUSIONS: There is a causal effect between circulating IL-27 level and CP, AR, which will help to find new ideas and methods for the diagnosis and treatment of CP and AR.

Is diet related to skin condition? A Mendelian randomization study.

Observational studies have revealed associations between various dietary factors and skin conditions. However, the causal relationship between diet and skin condition is still unknown. Data on 17 dietary factors were obtained from the UK Biobank. Data on four skin conditions were derived from the UK Biobank and another large-scale GWAS study. Genetic predictions suggested that the intake of oily fish was associated with a lower risk of skin aging (OR: 0.962, P = 0.036) and skin pigmentation (OR: 0.973, P = 0.033); Tea intake was associated with a lower risk of skin pigmentation (OR: 0.972, P = 0.024); Salad/raw vegetables intake was associated with a lower risk of keratinocyte skin cancer (OR: 0.952, P = 0.007). Coffee intake was associated with increased risk of skin aging (OR: 1.040, P = 0.028); Pork intake was associated with increased risk of skin aging (OR: 1.134, P = 0.020); Beef intake was associated with increased risk of cutaneous melanoma (OR: 1.013, P = 0.016); Champagne plus white wine intake was associated with increased risk of cutaneous melanoma (OR: 1.033, P = 0.004); Bread intake was associated with increased risk of keratinocyte skin cancer (OR: 1.026, P = 0.013). Our study results indicate causal relationships between genetically predicted intake of oily fish, tea, salad/raw vegetables, coffee, pork, beef, champagne plus white wine, and bread and skin conditions.

The role of circulating metabolites and gut microbiome in hypertrophic scar: a two-sample Mendelian randomization study.

Hypertrophic scarring is a fibro-proliferative disorder caused by abnormal cutaneous wound healing. Circulating metabolites and the gut microbiome may be involved in the formation of these scars, but high-quality evidence of causality is lacking. To assess whether circulating metabolites and the gut microbiome contain genetically predicted modifiable risk factors for hypertrophic scar formation. Two-sample Mendelian randomization (MR) was performed using MR-Egger, inverse-variance weighting (IVW), Mendelian Randomization Pleiotropy RESidual Sum and Outlier, maximum likelihood, and weighted median methods. Based on the genome-wide significance level, genetically predicted uridine (P = 0.015, odds ratio [OR] = 1903.514, 95% confidence interval [CI] 4.280-846,616.433) and isovalerylcarnitine (P = 0.039, OR = 7.765, 95% CI 1.106-54.512) were positively correlated with hypertrophic scar risk, while N-acetylalanine (P = 0.013, OR = 7.98E-10, 95% CI 5.19E-17-0.012) and glycochenodeoxycholate (P = 0.021, OR = 0.021 95% CI 0.003-0.628) were negatively correlated. Gastranaerophilales and two unknown gut microbe species (P = 0.031, OR = 0.378, 95% CI 0.156-0.914) were associated with an decreased risk of hypertrophic scarring. Circulating metabolites and gut microbiome components may have either positive or negative causal effects on hypertrophic scar formation. The study provides new insights into strategies for diagnosing and limiting hypertrophic scarring.

Data Harmonization Guidelines to Combine Multi-platform Genomic Data from Admixed Populations and Boost Power in Genome-Wide Association Studies.

Data harmonization involves combining data from multiple independent sources and processing the data to produce one uniform dataset. Merging separate genotypes or whole-genome sequencing datasets has been proposed as a strategy to increase the statistical power of association tests by increasing the effective sample size. However, data harmonization is not a widely adopted strategy due to the difficulties with merging data (including confounding produced by batch effects and population stratification). Detailed data harmonization protocols are scarce and are often conflicting. Moreover, data harmonization protocols that accommodate samples of admixed ancestry are practically non-existent. Existing data harmonization procedures must be modified to ensure the heterogeneous ancestry of admixed individuals is incorporated into additional downstream analyses without confounding results. Here, we propose a set of guidelines for merging multi-platform genetic data from admixed samples that can be adopted by any investigator with elementary bioinformatics experience. We have applied these guidelines to aggregate 1544 tuberculosis (TB) case-control samples from six separate in-house datasets and conducted a genome-wide association study (GWAS) of TB susceptibility. The GWAS performed on the merged dataset had improved power over analyzing the datasets individually and produced summary statistics free from bias introduced by batch effects and population stratification. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Processing separate datasets comprising array genotype data Alternate Protocol 1: Processing separate datasets comprising array genotype and whole-genome sequencing data Alternate Protocol 2: Performing imputation using a local reference panel Basic Protocol 2: Merging separate datasets Basic Protocol 3: Ancestry inference using ADMIXTURE and RFMix Basic Protocol 4: Batch effect correction using pseudo-case-control comparisons.

A multi-ethnic reference panel to impute HLA classical and non-classical class I alleles in admixed samples: Testing imputation accuracy in an admixed sample from Brazil.

The MHC class I region contains crucial genes for the innate and adaptive immune response, playing a key role in susceptibility to many autoimmune and infectious diseases. Genome-wide association studies have identified numerous disease-associated SNPs within this region. However, these associations do not fully capture the immune-biological relevance of specific HLA alleles. HLA imputation techniques may leverage available SNP arrays by predicting allele genotypes based on the linkage disequilibrium between SNPs and specific HLA alleles. Successful imputation requires diverse and large reference panels, especially for admixed populations. This study employed a bioinformatics approach to call SNPs and HLA alleles in multi-ethnic samples from the 1000 genomes (1KG) dataset and admixed individuals from Brazil (SABE), utilising 30X whole-genome sequencing data. Using HIBAG, we created three reference panels: 1KG (n = 2504), SABE (n = 1171), and the full model (n = 3675) encompassing all samples. In extensive cross-validation of these reference panels, the multi-ethnic 1KG reference exhibited overall superior performance than the reference with only Brazilian samples. However, the best results were achieved with the full model. Additionally, we expanded the scope of imputation by developing reference panels for non-classical, MICA, MICB and HLA-H genes, previously unavailable for multi-ethnic populations. Validation in an independent Brazilian dataset showcased the superiority of our reference panels over the Michigan Imputation Server, particularly in predicting HLA-B alleles among Brazilians. Our investigations underscored the need to enhance or adapt reference panels to encompass the target population's genetic diversity, emphasising the significance of multiethnic references for accurate imputation across different populations.

Shared genetic aetiology of respiratory diseases: a genome-wide multitraits association analysis.

OBJECTIVE: This study aims to explore the common genetic basis between respiratory diseases and to identify shared molecular and biological mechanisms. METHODS: This genome-wide pleiotropic association study uses multiple statistical methods to systematically analyse the shared genetic basis between five respiratory diseases (asthma, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, lung cancer and snoring) using the largest publicly available genome wide association studies summary statistics. The missions of this study are to evaluate global and local genetic correlations, to identify pleiotropic loci, to elucidate biological pathways at the multiomics level and to explore causal relationships between respiratory diseases. Data were collected from 27 November 2022 to 30 March 2023 and analysed from 14 April 2023 to 13 July 2023. MAIN OUTCOMES AND MEASURES: The primary outcomes are shared genetic loci, pleiotropic genes, biological pathways and estimates of genetic correlations and causal effects. RESULTS: Significant genetic correlations were found for 10 paired traits in 5 respiratory diseases. Cross-Phenotype Association identified 12 400 significant potential pleiotropic single-nucleotide polymorphism at 156 independent pleiotropic loci. In addition, multitrait colocalisation analysis identified 15 colocalised loci and a subset of colocalised traits. Gene-based analyses identified 432 potential pleiotropic genes and were further validated at the transcriptome and protein levels. Both pathway enrichment and single-cell enrichment analyses supported the role of the immune system in respiratory diseases. Additionally, five pairs of respiratory diseases have a causal relationship. CONCLUSIONS AND RELEVANCE: This study reveals the common genetic basis and pleiotropic genes among respiratory diseases. It provides strong evidence for further therapeutic strategies and risk prediction for the phenomenon of respiratory disease comorbidity.

Serum 25-hydroxyvitamin D levels and dermatomyositis: A 2-sample mendelian randomization study.

BACKGROUND: Previous studies have reported low serum 25-hydroxyvitamin D [25(OH)D] levels in dermatomyositis (DM) patients, but the exact causal relationship between them remains elusive. Our aim is to confirm the causal relationship between 25(OH)D and DM risk through a Mendelian randomization study. METHODS: Retrieve genome-wide association study (GWAS) data on 25(OH)D (n = 441 291) and DM (n cases = 201, n controls = 172 834) from the GWAS database (https://gwas.mrcieu.ac.uk/). Select single-nucleotide polymorphisms (SNPs) strongly correlated with 25(OH)D as instrumental variables (IVs). The primary analytical approach involves the use of the inverse-variance weighted method (IVW), supplemented by MR-Egger regression and weighted median methods to enhance the reliability of the results. Heterogeneity and sensitivity analyses were conducted using Cochran's Q and leave-one-out approaches, respectively. RESULTS: The IVW analysis confirmed a positive causal relationship between genetic variation in 25(OH)D levels and DM (OR = 2.36, 95% CI = 1.01-5.52, p = .048). Although not statistically significant (all p > .05), the other methods also suggested a protective effect of 25(OH)D on DM. Based on MR-Egger intercepts and Cochran's Q analysis, the selected SNPs showed no horizontal pleiotropy and heterogeneity. Sensitivity analysis demonstrated the robustness of the results against individual SNPs. CONCLUSION: We provide the first evidence of a causal relationship between 25(OH)D levels and DM. Our findings support the importance of measuring serum 25(OH)D levels and considering vitamin D supplementation in clinical practice for patients with DM.

The causal associations of inflammatory cytokines with obesity and systemic lupus erythematosus: A Mendelian randomization study.

OBJECTIVE: Previous studies have partly discussed the roles of inflammatory cytokines in obesity and systemic lupus erythematosus (SLE), but the causal relationship among inflammatory cytokines, obesity, and SLE is unclear. It is challenging to comprehensively evaluate the causal relationship between these variables. This study aimed to investigate the role of cytokines as intermediates between obesity and SLE. METHODS: The inverse-variance weighted method (IVW) of mendelian randomization (MR) is mainly used to explore the causal relationship between exposure and outcome by using the genetic variation of the open large genome-wide association studies (GWAS), namely single-nucleotide polymorphisms (SNPs) related to obesity (more than 600 000 participants), inflammatory cytokines (8293 healthy participants) and SLE (7219 cases). Methods such as weighted median, MR-Egger are used to evaluate the reliability of causality. Reverse analysis is performed for each MR analysis to avoid reverse causality. Cochran's Q statistic and funnel chart are used to detect heterogeneity, MR-Egger intercept test and leave-one-out sensitivity analyses evaluated pleiotropy. RESULTS: Obesity was associated with 25 cytokines, and 3 cytokines were associated with SLE, including CTACK (OR = 1.19, 95% CI: 1.06, 1.33, p = .002), IL-18 (OR = 1.13, 95% CI: 1.01, 1.26, p = .027), SCGFb (OR = 0.89, 95% CI: 0.79, 0.99, p = .044). In the opposite direction, SLE was associated with 18 cytokines, and 2 cytokines were associated with obesity, including IP-10 (ßIVW = -.03, 95% CI: -0.05, -0.01, p = .002), MIP-1B (ßIVW = -.03, 95% CI: -0.05, -0.01, p = .004). CONCLUSION: Our MR study suggested that CTACK, IL-18 and SCGFb may play an intermediary role in obesity to SLE, while IP-10 and MIP-1B may play an intermediary role in SLE to obesity.

Gastroesophageal reflux disease and non-alcoholic fatty liver disease: a two-sample Mendelian randomization combined with meta-analysis.

Accumulating evidence from observational studies have suggested an association between gastroesophageal reflux disease (GERD) and non-alcoholic fatty liver disease (NAFLD). However, due to that such studies are prone to biases, we imported Mendelian randomization (MR) to explore whether the causal association between two diseases exsit. Hence, we aimed to analysis the potential association with MR. The single nucleotide polymorphisms (SNPs) of GERD were retrieved from the genome-wide association study dataset as the exposure. The SNPs of NAFLD were taken from the FinnGen dataset as the outcome. The relationship was analyzed with the assistance of inverse variance weighted, MR-Egger, and weighted median. We also uitilized the MR-Egger intercept, Cochran's Q test, leave-one-out analysis, MR-PRESSO, and Steiger directionality test to evaluate the robustness of the causal association. The meta-analysis were also implemented to give an overall evaluation. Finally, our analysis showed a causal relationship between GERD and NAFLD with aid of MR and meta-analysis (OR 1.71 95% CI 1.40-2.09; P < 0.0001).

Genome wide association study and genomic risk prediction of age related macular degeneration in Israel.

The risk of developing age-related macular degeneration (AMD) is influenced by genetic background. In 2016, the International AMD Genomics Consortium (IAMDGC) identified 52 risk variants in 34 loci, and a polygenic risk score (PRS) from these variants was associated with AMD. The Israeli population has a unique genetic composition: Ashkenazi Jewish (AJ), Jewish non-Ashkenazi, and Arab sub-populations. We aimed to perform a genome-wide association study (GWAS) for AMD in Israel, and to evaluate PRSs for AMD. Our discovery set recruited 403 AMD patients and 256 controls at Hadassah Medical Center. We genotyped individuals via custom exome chip. We imputed non-typed variants using cosmopolitan and AJ reference panels. We recruited additional 155 cases and 69 controls for validation. To evaluate predictive power of PRSs for AMD, we used IAMDGC summary-statistics excluding our study and developed PRSs via clumping/thresholding or LDpred2. In our discovery set, 31/34 loci reported by IAMDGC were AMD-associated (P < 0.05). Of those, all effects were directionally consistent with IAMDGC and 11 loci had a P-value under Bonferroni-corrected threshold (0.05/34 = 0.0015). At a 5 × 10-5 threshold, we discovered four suggestive associations in FAM189A1, IGDCC4, C7orf50, and CNTNAP4. Only the FAM189A1 variant was AMD-associated in the replication cohort after Bonferroni-correction. A prediction model including LDpred2-based PRS + covariates had an AUC of 0.82 (95% CI 0.79-0.85) and performed better than covariates-only model (P = 5.1 × 10-9). Therefore, previously reported AMD-associated loci were nominally associated with AMD in Israel. A PRS developed based on a large international study is predictive in Israeli populations.

Exercise may delay cognitive decline in Chinese older adults: a causal inference for ordered multi-categorical exposures with a Mendelian randomization approach.

The cognitive problems are prominent in the context of global aging, and the traditional Mendelian randomization method is not applicable to ordered multi-categorical exposures. Therefore, we aimed to address this issue through the development of a method and to investigate the causal inference of cognitive-related lifestyle factors. The study sample was derived from the Chinese Longitudinal Healthy Longevity Survey, which included 897 older adults aged 65 + . This study used genome-wide association analysis to screen genetic loci as instrumental variables and innovatively combined maximum likelihood estimation to infer causal associations between ordered multi-categorical exposures (diet, exercise, etc.) and continuous outcomes (cognitive level). The causal inference method for ordered multi-categorical exposures developed in this study was simple, easy to implement, and able to effectively and reliably discover the potential causal associations between variables. Through this method, we found a potential positive causal association between exercise status and cognitive level in Chinese older adults ( ß ^ = 1.883, 95%CI 0.182-3.512), in which there was no horizontal pleiotropy (p = 0.370). The study provided a causal inference method applicable to ordered multi-categorical exposures, that addressed the limitations of the traditional Mendelian randomization method.

Unveiling genetic signatures associated with resilience to neonatal diarrhea in lambs through two GWAS approaches.

Neonatal diarrhea presents a significant global challenge due to its multifactorial etiology, resulting in high morbidity and mortality rates, and substantial economic losses. While molecular-level studies on genetic resilience/susceptibility to neonatal diarrhea in farm animals are scarce, prior observations indicate promising research directions. Thus, the present study utilizes two genome-wide association approaches, pKWmEB and MLM, to explore potential links between genetic variations in innate immunity and neonatal diarrhea in Karacabey Merino lambs. Analyzing 707 lambs, including 180 cases and 527 controls, revealed an overall prevalence rate of 25.5%. The pKWmEB analysis identified 13 significant SNPs exceeding the threshold of ≥ LOD 3. Moreover, MLM detected one SNP (s61781.1) in the SLC22A8 gene (p-value, 1.85eE-7), which was co-detected by both methods. A McNemar's test was conducted as the final assessment to identify whether there are any major effective markers among the detected SNPs. Results indicate that four markers-oar3_OAR1_122352257, OAR17_77709936.1, oar3_OAR18_17278638, and s61781.1-have a substantial impact on neonatal diarrhea prevalence (odds ratio: 2.03 to 3.10; statistical power: 0.88 to 0.99). Therefore, we propose the annotated genes harboring three of the associated markers, TIAM1, YDJC, and SLC22A8, as candidate major genes for selective breeding against neonatal diarrhea.

Genome-wide association study of BNT162b2 vaccine-related myocarditis identifies potential predisposing functional areas in Hong Kong adolescents.

Vaccine-related myocarditis associated with the BNT162b2 vaccine is a rare complication, with a higher risk observed in male adolescents. However, the contribution of genetic factors to this condition remains uncertain. In this study, we conducted a comprehensive genetic association analysis in a cohort of 43 Hong Kong Chinese adolescents who were diagnosed with myocarditis shortly after receiving the BNT162b2 mRNA COVID-19 vaccine. A comparison of whole-genome sequencing data was performed between the confirmed myocarditis cases and a control group of 481 healthy individuals. To narrow down potential genomic regions of interest, we employed a novel clustering approach called ClusterAnalyzer, which prioritised 2,182 genomic regions overlapping with 1,499 genes for further investigation. Our pathway analysis revealed significant enrichment of these genes in functions related to cardiac conduction, ion channel activity, plasma membrane adhesion, and axonogenesis. These findings suggest a potential genetic predisposition in these specific functional areas that may contribute to the observed side effect of the vaccine. Nevertheless, further validation through larger-scale studies is imperative to confirm these findings. Given the increasing prominence of mRNA vaccines as a promising strategy for disease prevention and treatment, understanding the genetic factors associated with vaccine-related myocarditis assumes paramount importance. Our study provides valuable insights that significantly advance our understanding in this regard and serve as a valuable foundation for future research endeavours in this field.

Using expression data to fine map QTL associated with fertility in dairy cattle.

BACKGROUND: Female fertility is an important trait in dairy cattle. Identifying putative causal variants associated with fertility may help to improve the accuracy of genomic prediction of fertility. Combining expression data (eQTL) of genes, exons, gene splicing and allele specific expression is a promising approach to fine map QTL to get closer to the causal mutations. Another approach is to identify genomic differences between cows selected for high and low fertility and a selection experiment in New Zealand has created exactly this resource. Our objective was to combine multiple types of expression data, fertility traits and allele frequency in high- (POS) and low-fertility (NEG) cows with a genome-wide association study (GWAS) on calving interval in Australian cows to fine-map QTL associated with fertility in both Australia and New Zealand dairy cattle populations. RESULTS: Variants that were significantly associated with calving interval (CI) were strongly enriched for variants associated with gene, exon, gene splicing and allele-specific expression, indicating that there is substantial overlap between QTL associated with CI and eQTL. We identified 671 genes with significant differential expression between POS and NEG cows, with the largest fold change detected for the CCDC196 gene on chromosome 10. Our results provide numerous candidate genes associated with female fertility in dairy cattle, including GYS2 and TIGAR on chromosome 5 and SYT3 and HSD17B14 on chromosome 18. Multiple QTL regions were located in regions with large numbers of copy number variants (CNV). To identify the causal mutations for these variants, long read sequencing may be useful. CONCLUSIONS: Variants that were significantly associated with CI were highly enriched for eQTL. We detected 671 genes that were differentially expressed between POS and NEG cows. Several QTL detected for CI overlapped with eQTL, providing candidate genes for fertility in dairy cattle.

New evidence: Metformin unsuitable as routine adjuvant for breast cancer: a drug-target mendelian randomization analysis.

PURPOSE: The potential efficacy of metformin in breast cancer (BC) has been hotly discussed but never conclusive. This genetics-based study aimed to evaluate the relationships between metformin targets and BC risk. METHODS: Metformin targets from DrugBank and genome-wide association study (GWAS) data from IEU OpenGWAS and FinnGen were used to investigate the breast cancer (BC)-metformin causal link with various Mendelian Randomization (MR) methods (e.g., inverse-variance-weighting). The genetic association between type 2 diabetes (T2D) and the drug target of metformin was also analyzed as a positive control. Sensitivity and pleiotropic tests ensured reliability. RESULTS: The primary targets of metformin are PRKAB1, ETFDH and GPD1L. We found a causal association between PRKAB1 and T2D (odds ratio [OR] 0.959, P = 0.002), but no causal relationship was observed between metformin targets and overall BC risk (PRKAB1: OR 0.990, P = 0.530; ETFDH: OR 0.986, P = 0.592; GPD1L: OR 1.002, P = 0.806). A noteworthy causal relationship was observed between ETFDH and estrogen receptor (ER)-positive BC (OR 0.867, P = 0.018), and between GPD1L and human epidermal growth factor receptor 2 (HER2)-negative BC (OR 0.966, P = 0.040). Other group analyses did not yield positive results. CONCLUSION: The star target of metformin, PRKAB1, does not exhibit a substantial causal association with the risk of BC. Conversely, metformin, acting as an inhibitor of ETFDH and GPD1L, may potentially elevate the likelihood of developing ER-positive BC and HER2-negative BC. Consequently, it is not advisable to employ metformin as a standard supplementary therapy for BC patients without T2D.