UNASSIGNED: Intracerebral hemorrhage (ICH) is a severe form of stroke with high mortality and limited treatment options. While traditional risk factors like hypertension have been well-studied, the role of emotional states as acute triggers for ICH remains unclear. This study employs Mendelian Randomization (MR) to investigate the causal relationship between emotional traits of worry and anxiety and the incidence of ICH.
UNASSIGNED: We used a two-sample MR approach, leveraging summary-level data from genome-wide association studies (GWAS) for emotional traits and ICH. The primary analysis was conducted using the Inverse-Variance Weighted (IVW) method, supplemented by multiple sensitivity analyses including Maximum Likelihood and MR PRESSO methods.
UNASSIGNED: Our MR analysis revealed a robust and significant causal relationship between the emotional trait \"Worrier/anxious feelings\" and ICH, supported by 195 instrumental variables (SNPs). The odds ratio (OR) was 2.98 (95% CI: 1.16, 7.61) with a p-value of 0.0229. Sensitivity analyses corroborated these findings, enhancing the reliability of our results. In contrast, other emotional traits such as \"Nervous feelings\" and \"Sensitivity/hurt feelings\" did not show significant associations, reinforcing the specificity of our primary finding.
UNASSIGNED: Our study provides compelling evidence for a causal relationship between the emotional traits of worry and anxiety and the incidence of ICH, offering a new dimension in our understanding of this devastating condition and paving the way for more nuanced risk stratification and preventive strategies.

OBJECTIVE: Migraine is a condition that is often observed to run in families, but its complex genetic background remains unclear. This study aimed to identify the genetic factors influencing migraines and their potential association with the family medical history.
METHODS: We performed a comprehensive genome-wide association study of a cohort of 1,561 outpatients with migraine and 473 individuals without migraine in Taiwan, including Han Chinese individuals with or without a family history of migraine. By analyzing the detailed headache history of the patients and their relatives we aimed to isolate potential genetic markers associated with migraine while considering factors such as sex, episodic vs. chronic migraine, and the presence of aura.
RESULTS: We revealed novel genetic risk loci, including rs2287637 in DEAD-Box helicase 1 and long intergenic non-protein coding RNA 1804 and rs12055943 in engulfment and cell motility 1, that were correlated with the family history of migraine. We also found a genetic location downstream of mesoderm posterior BHLH transcription factor 2 associated with episodic migraine, whereas loci within the ubiquitin-specific peptidase 26 exonic region, dual specificity phosphatase 9 and pregnancy-upregulated non-ubiquitous CaM kinase intergenic regions, and poly (ADP-ribose) polymerase 1 and STUM were linked to chronic migraine. We additionally identified genetic regionsassociated with the presence or absence of aura. A locus between LINC02561 and urocortin 3 was predominantly observed in female patients. Moreover, three different single-nucleotide polymorphisms were associated with the family history of migraine in the control group.
CONCLUSIONS: This study has identified new genetic locations associated with migraine and its family history in a Han Chinese population, reinforcing the genetic background of migraine. The findings point to potential candidate genes that should be investigated further.

UNASSIGNED: The rate at which the anticancer drug paclitaxel is cleared from the body markedly impacts its dosage and chemotherapy effectiveness. Importantly, paclitaxel clearance varies among individuals, primarily because of genetic polymorphisms. This metabolic variability arises from a nonlinear process that is influenced by multiple single nucleotide polymorphisms (SNPs). Conventional bioinformatics methods struggle to accurately analyze this complex process and, currently, there is no established efficient algorithm for investigating SNP interactions.
UNASSIGNED: We developed a novel machine-learning approach called GEP-CSIs data mining algorithm. This algorithm, an advanced version of GEP, uses linear algebra computations to handle discrete variables. The GEP-CSI algorithm calculates a fitness function score based on paclitaxel clearance data and genetic polymorphisms in patients with nonsmall cell lung cancer. The data were divided into a primary set and a validation set for the analysis.
UNASSIGNED: We identified and validated 1184 three-SNP combinations that had the highest fitness function values. Notably, SERPINA1, ATF3 and EGF were found to indirectly influence paclitaxel clearance by coordinating the activity of genes previously reported to be significant in paclitaxel clearance. Particularly intriguing was the discovery of a combination of three SNPs in genes FLT1, EGF and MUC16. These SNPs-related proteins were confirmed to interact with each other in the protein-protein interaction network, which formed the basis for further exploration of their functional roles and mechanisms.
UNASSIGNED: We successfully developed an effective deep-learning algorithm tailored for the nuanced mining of SNP interactions, leveraging data on paclitaxel clearance and individual genetic polymorphisms.

UNASSIGNED: Multiple myeloma (MM), a malignant disease of plasma cells originating in the bone marrow, is influenced significantly by genetic factors. Although plasma liposomes have been linked to MM, the nature of their potential causal relationship remains to be elucidated. This study aims to explore this relationship using Mendelian randomization (MR) analysis.
UNASSIGNED: Liposome-associated genetic instrumental variables (IVs) were identified from plasma lipidomics data of 7,174 Finnish individuals within a Genome-Wide Association Study (GWAS) pooled database. A MM pooled dataset was sourced from a GWAS meta-analysis encompassing 150,797 individuals, including 598 MM patients and 218,194 controls. These IVs underwent MR analysis, adhering to strict criteria for correlation, independence, and the exclusion of confounders. The inverse variance weighted (IVW) method, MR-Egger method, weighted median (WM) method, and simple median were utilized for MR analysis assessment, alongside Cochran\'s Q test, MR-Egger intercept, MR-Pleiotropy Residual Sum and Outlier (MR-RESSO) method, and leave-one-out analysis for evaluating heterogeneity, multiplicity, and instrumental bias.
UNASSIGNED: The study identified 88 significant, independent single nucleotide polymorphisms (SNPs) as IVs for MR analysis, each with an F-statistic value above 10, indicating robustness against weak instrument bias. IVW analysis revealed associations between six plasma liposome components and MM risk (p < 0.05). Phosphatidylinositol (16:0_18:1) serum levels (odds ratio [OR] = 1.769, 95% confidence interval [CI]: 1.132-2.763, p = 0.012) and triacylglycerol (56:4) levels (p = 0.026, OR = 1.417, 95% CI: 1.042-1.926) were positively correlated with the risk of multiple myeloma development. Phosphatidylethanolamine (18:0_20:4) (p = 0.004, 95% CI: 0.621-0.916, OR = 0.754), phosphatidylcholine (18:2_20:4) (p = 0.004, OR = 0.680, 95% CI: 0.519-0.889), sterol ester (27:1/18:3) levels (p = 0.013, OR = 0.677, 95% CI: 0.498-0.922), and phosphatidylcholine (O-18:2_20:4) levels (OR = 0.710, 95% CI: 0.517-0.913, p = 0.033) were negatively associated with the risk of developing multiple myeloma. The Cochran\'s Q test did not detect statistical method heterogeneity, nor did the MR-RESSO test or the MR-Egger intercept detect horizontal pleiotropy; leave-one-out analyses confirmed the absence of bias from individual SNPs.
UNASSIGNED: Our findings suggest a complex relationship between plasma liposome components and MM risk. Elevated serum levels of triacylglycerol and phosphatidylinositol are positively associated with MM risk, while certain phospholipids and sterol esters offer a protective effect. This study provides valuable insights into the clinical relevance of liposomes in the pathology of multiple myeloma.

UNASSIGNED: Type I diabetes mellitus (T1DM) is a significant health challenge, especially for children, owing to its chronic autoimmune nature. Although the exact etiology of T1DM remains elusive, the interplay of genetic predisposition, immune responses, and environmental factors are postulated. Genetic factors control immune reactivity against β-cells. Given the pivotal roles of CIITA and CLEC2D genes in modulating a variety of immune pathologies, we hypothesized that genetic variations in CIITA and CLEC2D genes may impact T1DM disease predisposition. This study was designed to explore the association between gene polymorphisms in CIITA (rs8048002) and CLEC2D (rs2114870) and type 1 diabetes (T1DM), with a focus on analyzing the functional consequence of those gene variants.
UNASSIGNED: The study enlisted 178 healthy controls and 148 individuals with type 1 diabetes (T1DM) from Suez Canal University Hospital. Genotyping for CIITA and CLEC2D was done using allelic-discrimination polymerase chain reaction (PCR). Levels of glycated hemoglobin (HbA1c) and lipid profiles were determined through automated analyzer, while fasting blood glucose and insulin serum levels were measured using the enzyme-linked immunosorbent assay (ELISA) technique. RegulomeDB was used to examine the regulatory functions of CIITA (rs8048002) and CLEC2D (rs2114870) gene variants.
UNASSIGNED: Analysis of the genotype distribution of the CIITA rs8048002 polymorphism revealed a significantly higher prevalence of the rare C allele in T1DM patients compared to the control group (OR = 1.77; P = 0.001). Both the CIITA rs8048002 heterozygote TC genotype (OR = 1.93; P = 0.005) and the rare homozygote CC genotype (OR = 3.62; P = 0.006) were significantly more frequent in children with T1DM when compared to the control group. Conversely, the rare A allele of CLEC2D rs2114870 was found to be significantly less frequent in T1DM children relative to the control group (OR = 0.58; P = 0.002). The heterozygote GA genotype (OR = 0.61; P = 0.033) and the rare homozygote AA genotype (OR = 0.25; P = 0.004) were also significantly less frequent in T1DM patients compared to the control group. Both CIITA (rs8048002) and CLEC2D (rs2114870) gene variants were predicted to have regulatory functions, indicated by a RegulomeDB score of (1f) for each.
UNASSIGNED: The rare C allele of CIITA rs8048002 genetic variant was associated with an increased risk of developing T1DM, while the less common A allele of CLEC2D rs2114870 was associated with a reduced risk of T1DM.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s40200-024-01402-w.

BACKGROUND: Reports suggest that lipid profiles may be linked to the likelihood of developing skin cancer, yet the exact causal relationship is still unknown.
OBJECTIVE: This study aimed to examine the connection between lipidome and skin cancers, as well as investigate any possible mediators.
METHODS: A two-sample Mendelian randomization (MR) analysis was conducted on 179 lipidomes and each skin cancer based on a genome-wide association study (GWAS), including melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Then, Bayesian weighted MR was performed to verify the analysis results of two-sample MR. Moreover, a two-step MR was employed to investigate the impact of TNF-like weak inducer of apoptosis (TWEAK)-mediated lipidome on skin cancer rates.
RESULTS: MR analysis identified higher genetically predicted phosphatidylcholine (PC) (17:0_18:2) could reduce the risk of skin tumors, including BCC (OR = 0.9149, 95% CI: 0.8667-0.9658), SCC (OR = 0.9343, 95% CI: 0.9087-0.9606) and melanoma (OR = 0.9982, 95% CI: 0.9966-0.9997). The proportion of PC (17:0_18:2) predicted by TWEAK-mediated genetic prediction was 6.6 % in BCC and 7.6% in SCC. The causal relationship between PC (17:0_18:2) and melanoma was not mediated by TWEAK.
CONCLUSIONS: This study identified a negative causal relationship between PC (17:0_18:2) and keratinocyte carcinomas, a small part of which was mediated by TWEAK, and most of the remaining mediating factors are still unclear. Further research on other risk factors is needed in the future.

Lung cancer has an unfavorable prognosis with a rate of low overall survival, caused by the difficulty of diagnosis in the early stages and resistance to therapy. In recent years, there have been new therapies that use specific molecular targets and are effective in increasing the survival chances of advanced cancer. Therefore, it is necessary to find more specific biomarkers that can identify early changes in carcinogenesis and allow the earliest possible treatment. Vitamin D (VD) plays an important role in immunity and carcinogenesis. Furthermore, the vitamin D receptor (VDR) regulates the expression of various genes involved in the physiological functions of the human organism. The genes encoding the VDR are extremely polymorphic and vary greatly between human populations. To date, there are significant associations between VDR polymorphism and several types of cancer, but the data on the involvement of VDR polymorphism in lung cancer are still conflicting. Therefore, in this review, our aim was to investigate the relationship between VDR single-nucleotide polymorphisms in humans and the degree of risk for developing lung cancer. The studies showcased different gene polymorphisms to be associated with an increased risk of lung cancer: TaqI, ApaI, BsmI, FokI, and Cdx2. In addition, there is a strong positive correlation between VD deficiency and lung cancer development. Still, due to a lack of awareness, the assessment of VD status and VDR polymorphism is rarely considered for the prediction of lung cancer evolution and their clinical applicability, despite the fact that studies have shown the highest risk for lung cancer given by TaqI gene polymorphisms and that VDR polymorphisms are associated with more aggressive cancer evolution.

Worldwide molecular research of economically important Phalaris arundinacea (Poaceae) is mainly focused on the invasions of this species from Europe to North America. Until the present study, the genetic diversity of the P. arundinacea had not been studied across the Baltic countries. The objective of this research is to evaluate the diversity of Lithuanian populations of P. arundinacea at simple sequence repeat (SSR) loci comparatively among populations of the Baltic countries, Luxembourg, and the Russian Far East (Eurasian), evaluating differentiation between Lithuanian populations and ornamental accessions, and relating these with environmental features. For six selected Lithuanian river basin populations, GBS low density SNPs were used to determine genetic diversity. Bayesian analysis showed that Eurasian populations of Phalaris arundinacea consist of two gene clusters. Statistically significant genetic differentiation among European and Eurasian populations was documented. Lithuanian genotypes growing naturally along rivers are genetically distinct from cultivated ornamentals. GBS-SNPs divided the six selected Nemunas river basins into three distinct groups with one, two, or three rivers in separate groupings for genetic diversity. Genetic diversity is primarily within, rather than among, Lithuanian, eastern European, and Eurasian populations of P. arundinacea across the continent. Thus, restoration efforts would benefit from local population seed origination.

Pepper agronomic traits serve as pivotal indicators for characterizing germplasm attributes and correlations. It is important to study differential genotypic variation through phenotypic differences of target traits. Whole genome resequencing was used to sequence the whole genome among different individuals of species with known reference genomes and annotations, and based on this, differential analyses of individuals or populations were carried out to identify SNPs for agronomic traits related to pepper. This study conducted a genome-wide association study encompassing 26 key agronomic traits in 182 upward-growing fruits of C. frutescens and C. annuum. The population structure (phylogenetics, population structure, population principal component analysis, genetic relationship) and linkage disequilibrium analysis were realized to ensure the accuracy and reliability of GWAS results, and the optimal statistical model was determined. A total of 929 SNPs significantly associated with 26 agronomic traits, were identified, alongside the detection of 519 candidate genes within 100 kb region adjacent to these SNPs. Additionally, through gene annotation and expression pattern scrutiny, genes such as GAUT1, COP10, and DDB1 correlated with fruit traits in Capsicum frutescens and Capsicum annuum were validated via qRT-PCR. In the CH20 (Capsicum annuum) and YB-4 (Capsicum frutescens) cultivars, GAUT1 and COP10 were cloned with cDNA lengths of 1065 bp and 561 bp, respectively, exhibiting only a small number of single nucleotide variations and nucleotide deletions. This validation provides a robust reference for molecular marker-assisted breeding of pepper agronomic traits, offering both genetic resources and theoretical foundations for future endeavors in molecular marker-assisted breeding for pepper.

UNASSIGNED: To investigate the causal relationship between gut microbiota (GM) and chalazion through Mendelian randomization (MR) analysis.
UNASSIGNED: GM-related genome-wide association studies (GWAS) were obtained from the International Consortium MiBioGen. Genetic data for chalazion were sourced from the MRC Integrative Epidemiology Unit (IEU) Open GWAS database. Five MR methods, including inverse variance weighted (IVW), were employed to estimate causal relationships. Cochran\'s Q test was used to detect heterogeneity, the MR-Egger intercept test and MR-PRESSO regression were utilized to detect horizontal pleiotropy, and the leave-one-out method was employed to validate data stability.
UNASSIGNED: We identified 1,509 single nucleotide polymorphisms (SNPs) across 119 genera as instrumental variables (IVs) (p < 1 × 10-5). According to the inverse variance weighted (IVW) estimate, the Family XIII AD3011 group (OR = 1.0018, 95% CI 1.0002-1.0035, p = 0.030) and Catenibacterium (OR = 1.0013, 95% CI 1.0002-1.0025, p = 0.022) were potentially associated with increased risk of chalazion. Conversely, Veillonella (OR = 0.9986, 95% CI 0.9974-0.9999, p = 0.036) appeared to provide protection against chalazion. There was no evidence of heterogeneity or pleiotropy.
UNASSIGNED: This study uncovered the causal relationship between GM and chalazion, pinpointing Catenibacterium and Family XIII AD3011 group as potential risk contributors, while highlighting Veillonella as a protective factor. In-depth investigation into the potential mechanisms of specific bacteria in chalazion was essential for providing novel therapeutic and preventive strategies in the future.