Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases.

BACKGROUND: Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD. METHODS: Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets. RESULTS: Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure. CONCLUSIONS: This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.

Identification of Pancreatic Cancer Germline Risk Variants With Effects That Are Modified by Smoking.

PURPOSE: Pancreatic cancer (PC) is a deadly disease most often diagnosed in late stages. Identification of high-risk subjects could both contribute to preventative measures and help diagnose the disease at earlier timepoints. However, known risk factors, assessed independently, are currently insufficient for accurately stratifying patients. We use large-scale data from the UK Biobank (UKB) to identify genetic variant-smoking interaction effects and show their importance in risk assessment. METHODS: We draw data from 15,086,830 genetic variants and 315,512 individuals in the UKB. There are 765 cases of PC. Crucially, robust resampling corrections are used to overcome well-known challenges in hypothesis testing for interactions. Replication analysis is conducted in two independent cohorts totaling 793 cases and 570 controls. Integration of functional annotation data and construction of polygenic risk scores (PRS) demonstrate the additional insight provided by interaction effects. RESULTS: We identify the genome-wide significant variant rs77196339 on chromosome 2 (per minor allele odds ratio in never-smokers, 2.31 [95% CI, 1.69 to 3.15]; per minor allele odds ratio in ever-smokers, 0.53 [95% CI, 0.30 to 0.91]; P = 3.54 × 10-8) as well as eight other loci with suggestive evidence of interaction effects (P < 5 × 10-6). The rs77196339 region association is validated (P < .05) in the replication sample. PRS incorporating interaction effects show improved discriminatory ability over PRS of main effects alone. CONCLUSION: This study of genome-wide germline variants identified smoking to modify the effect of rs77196339 on PC risk. Interactions between known risk factors can provide critical information for identifying high-risk subjects, given the relative inadequacy of models considering only main effects, as demonstrated in PRS. Further studies are necessary to advance toward comprehensive risk prediction approaches for PC.

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles.

Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.

Genetic susceptibility of urolithiasis: comprehensive results from genome-wide analysis.

BACKGROUND: The pathogenesis of urolithiasis is multi-factorial and genetic factors have been shown to play a significant role in the development of urolithiasis. We tried to apply genome-wide Mendelian randomization (MR) analysis and figure out reliable gene susceptibility of urolithiasis from the largest samples to date in two independent genome-wide association studies (GWAS) database of European ancestry. METHODS: We extracted summary statistics of expression quantitative trait locus (eQTL) from eQTLGen consortium. Urolithiasis phenotype information was obtained from both FinnGen Biobank and UK Biobank. Multiple two-sample MR analysis with a Bonferroni-corrected P threshold (P < 2.5e-06) was conducted. The primary endpoint was the causal effect calculated by random-effect inverse variance weighted (IVW) method. Sensitivity analysis, volcano plots, scatter plots, and regional plots were also performed and visualized. RESULTS: After multiple MR tests between 19942 eQTLs and urolithiasis phenotype from both cohorts, 30 common eQTLs with consistent effect size direction were found to be causally associated with urolithiasis risk. Finally only one gene (LMAN2) was simultaneously identified among all top significant eQTLs from both FinnGen Biobank (beta = 0.6758, se = 0.0327, P = 6.775e-95) and UK Biobank (beta = 0.0044, se = 0.0009, P = 2.417e-06). We also found that LMAN2 was with the largest beta effect size on urolithiasis phenotype from the two cohorts. CONCLUSION: We for the first time implemented genome-wide MR analysis to investigate the genetic susceptibility of urolithiasis in general population of European ancestry. Our results provided novel insights into common genetic variants of urinary stone disease, which was of great help to subsequent researches.

The causal relationship between atopic dermatitis and brain cancer: A bidirectional Mendelian randomization study.

BACKGROUND: Atopic dermatitis ranks among the prevalent skin disorders. Research has indicated a potential association with brain cancer. Yet, establishing a direct causal relationship between atopic dermatitis and brain cancer continues to be challenging. MATERIALS AND METHODS: We extracted single nucleotide polymorphisms (SNPs) significantly associated with atopic dermatitis (sample size = 382 254) at a genome-wide level from a large Finnish Genome-Wide Association Study (GWAS) dataset (n cases = 15 208, n controls = 367 046). Summary data for 372 622 cases of brain cancer (n cases = 606, n controls = 372 016) were obtained via the IEU Open GWAS database. We employed the Inverse Variance Weighted (IVW) method as our primary analytical approach for Mendelian Randomization (MR) analysis. Additionally, heterogeneity was measured using Cochran's Q value, and horizontal pleiotropy was evaluated using MR-Egger 、Mendelian Randomization Pleiotropy RESidual Sum and Outlier and leave-one-out analyses. RESULTS: The risk of brain cancer increases with the presence of atopic dermatitis, as evidenced by the odds ratios (ORs) and 95% confidence intervals (CIs),(OR = 1.0005; 95% CI = 1.0001, 1.0009; p = 0.0096). However, when conducting the analysis in reverse, no significant link was observed. CONCLUSION: The findings from our study indicate a causative link between atopic dermatitis and brain cancer, highlighting the importance of conducting broader clinical investigations into their potential association going forward.

EGR3 Polymorphism Is a Potential Susceptibility Factor of Schizophrenia Risk in a Chinese Population.

Objective: The purpose of this study was to evaluate the association between the single nucleotide polymorphisms (SNPs) (EGR3 rs1996147; EGR4 rs3813226, rs6747506; ERBB3 rs2292238; and ERBB4 rs707284, rs7560730) and the risk of schizophrenia (SZ) in a Chinese population. Materials and Methods: We conducted a case-control study, including 248 patients with SZ and 236 healthy controls matched for age and sex. The Mass-array platform was used to detect all the genotypes of the SNPs. Results: The results revealed that the EGR3 rs1996147 AA genotype was associated with borderline decreased SZ risk (AA vs. GG: adjusted OR = 0.43, 95% CI: 0.18-1.02, p = 0.06). However, no significant correlation was found between the other SNPs and overall SZ risk. Subgroup analysis also failed to show any significant association between all SNPs and the risk of SZ. Conclusion: In summary, this study revealed that the EGR3 rs1996147 AA genotype was associated with a borderline risk for SZ.

HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations.

Existing studies have shown that the abnormal expression of microRNAs (miRNAs) usually leads to the occurrence and development of human diseases. Identifying disease-related miRNAs contributes to studying the pathogenesis of diseases at the molecular level. As traditional biological experiments are time-consuming and expensive, computational methods have been used as an effective complement to infer the potential associations between miRNAs and diseases. However, most of the existing computational methods still face three main challenges: (i) learning of high-order relations; (ii) insufficient representation learning ability; (iii) importance learning and integration of multi-view embedding representation. To this end, we developed a HyperGraph Contrastive Learning with view-aware Attention Mechanism and Integrated multi-view Representation (HGCLAMIR) model to discover potential miRNA-disease associations. First, hypergraph convolutional network (HGCN) was utilized to capture high-order complex relations from hypergraphs related to miRNAs and diseases. Then, we combined HGCN with contrastive learning to improve and enhance the embedded representation learning ability of HGCN. Moreover, we introduced view-aware attention mechanism to adaptively weight the embedded representations of different views, thereby obtaining the importance of multi-view latent representations. Next, we innovatively proposed integrated representation learning to integrate the embedded representation information of multiple views for obtaining more reasonable embedding information. Finally, the integrated representation information was fed into a neural network-based matrix completion method to perform miRNA-disease association prediction. Experimental results on the cross-validation set and independent test set indicated that HGCLAMIR can achieve better prediction performance than other baseline models. Furthermore, the results of case studies and enrichment analysis further demonstrated the accuracy of HGCLAMIR and unconfirmed potential associations had biological significance.

Obstructive sleep apnea and mental disorders: a bidirectional mendelian randomization study.

BACKGROUND: Previous studies have reported associations between obstructive sleep apnea (OSA) and several mental disorders. However, further research is required to determine whether these associations are causal. Therefore, we evaluated the bidirectional causality between the genetic liability for OSA and nine mental disorders by using Mendelian randomization (MR). METHOD: We performed two-sample bidirectional MR of genetic variants for OSA and nine mental disorders. Summary statistics on OSA and the nine mental disorders were extracted from the FinnGen study and the Psychiatric Genomics Consortium. The primary analytical approach for estimating causal effects was the inverse-variance weighted (IVW), with the weighted median and MR Egger as complementary methods. The MR Egger intercept test, Cochran's Q test, Rucker's Q test, and the MR pleiotropy residual sum and outlier (MR-PRESSO) test were used for sensitivity analyses. RESULT: MR analyses showed that genetic liability for major depressive disorder (MDD) was associated with an increased risk of OSA (odds ratio [OR] per unit increase in the risk of MDD, 1.29; 95% CI, 1.11-1.49; P < 0.001). In addition, genetic liability for OSA may be associated with an increased risk of attention-deficit/hyperactivity disorder (ADHD) (OR = 1.26; 95% CI, 1.02-1.56; p = 0.032). There was no evidence that OSA is associated with other mental disorders. CONCLUSION: Our study indicated that genetic liability for MDD is associated with an increased risk of OSA without a bidirectional relationship. Additionally, there was suggestive evidence that genetic liability for OSA may have a causal effect on ADHD. These findings have implications for prevention and intervention strategies targeting OSA and ADHD. Further research is needed to investigate the biological mechanisms underlying our findings and the relationship between OSA and other mental disorders.

Benchmarking multi-ancestry prostate cancer polygenic risk scores in a real-world cohort.

Prostate cancer is a heritable disease with ancestry-biased incidence and mortality. Polygenic risk scores (PRSs) offer promising advancements in predicting disease risk, including prostate cancer. While their accuracy continues to improve, research aimed at enhancing their effectiveness within African and Asian populations remains key for equitable use. Recent algorithmic developments for PRS derivation have resulted in improved pan-ancestral risk prediction for several diseases. In this study, we benchmark the predictive power of six widely used PRS derivation algorithms, including four of which adjust for ancestry, against prostate cancer cases and controls from the UK Biobank and All of Us cohorts. We find modest improvement in discriminatory ability when compared with a simple method that prioritizes variants, clumping, and published polygenic risk scores. Our findings underscore the importance of improving upon risk prediction algorithms and the sampling of diverse cohorts.

TBX5 genetic variants and SCD-CAD susceptibility: insights from Chinese Han cohorts.

Background: The prevention and prediction of sudden cardiac death (SCD) present persistent challenges, prompting exploration into common genetic variations for potential insights. T-box 5 (TBX5), a critical cardiac transcription factor, plays a pivotal role in cardiovascular development and function. This study systematically examined variants within the 500-bp region downstream of the TBX5 gene, focusing on their potential impact on susceptibility to SCD associated with coronary artery disease (SCD-CAD) in four different Chinese Han populations. Methods: In a comprehensive case-control analysis, we explored the association between rs11278315 and SCD-CAD susceptibility using a cohort of 553 controls and 201 SCD-CAD cases. Dual luciferase reporter assays and genotype-phenotype correlation studies using human cardiac tissue samples as well as integrated in silicon analysis were applied to explore the underlining mechanism. Result: Binary logistic regression results underscored a significantly reduced risk of SCD-CAD in individuals harboring the deletion allele (odds ratio = 0.70, 95% CI [0.55-0.88], p = 0.0019). Consistent with the lower transcriptional activity of the deletion allele observed in dual luciferase reporter assays, genotype-phenotype correlation studies on human cardiac tissue samples affirmed lower expression levels associated with the deletion allele at both mRNA and protein levels. Furthermore, our investigation revealed intriguing insights into the role of rs11278315 in TBX5 alternative splicing, which may contribute to alterations in its ultimate functional effects, as suggested by sQTL analysis. Gene ontology analysis and functional annotation further underscored the potential involvement of TBX5 in alternative splicing and cardiac-related transcriptional regulation. Conclusions: In summary, our current dataset points to a plausible correlation between rs11278315 and susceptibility to SCD-CAD, emphasizing the potential of rs11278315 as a genetic risk marker for aiding in molecular diagnosis and risk stratification of SCD-CAD.

Relationship between XPA, XPB/ERCC3, XPF/ERCC4, and XPG/ERCC5 Polymorphisms and the Susceptibility to Head and Neck Carcinoma: A Systematic Review, Meta-Analysis, and Trial Sequential Analysis.

Background and Objectives: Nucleotide Excision Repair (NER), the most extensively researched DNA repair mechanism, is responsible for repairing a variety of DNA damages, and Xeroderma Pigmentosum (XP) genes participate in NER. Herein, we aimed to update the previous results with a meta-analysis evaluating the association of XPA, XPB/ERCC3, XPF/ERCC4, and XPG/ERCC5 polymorphisms with the susceptibility to HNC. Materials and Methods: PubMed/Medline, Web of Science, Scopus, and Cochrane Library databases were searched without any restrictions until 18 November 2023 to find relevant studies. The Review Manager 5.3 (RevMan 5.3) software was utilized to compute the effect sizes, which were expressed as the odds ratio (OR) with a 95% confidence interval (CI). Results: Nineteen articles were involved in the systematic review and meta-analysis that included thirty-nine studies involving ten polymorphisms. The results reported that the CC genotype of rs17655 polymorphism showed a significantly decreased risk of HNC in the recessive model (OR: 0.89; 95%CI: 0.81, 0.99; p-value is 0.03). In addition, the CT genotype (OR: 0.65; 95%CI: 0.48, 0.89; p-value is 0.008) of the rs751402 polymorphism was associated with a decreased risk, and the T allele (OR: 1.28; 95%CI: 1.05, 1.57; p-value is 0.02), the TT (OR: 1.74; 95%CI: 1.10, 2.74; p-value is 0.02), and the TT + CT (OR: 2.22; 95%CI: 1.04, 4.74; p-value is 0.04) genotypes were associated with an increased risk of HNC. Conclusions: The analysis identified two polymorphisms, rs17655 and rs751402, as being significantly associated with the risk of HNC. The study underscored the influence of various factors, such as the type of cancer, ethnicity, source of control, and sample size on these associations.

The Role of DNA Repair (XPC, XPD, XPF, and XPG) Gene Polymorphisms in the Development of Myeloproliferative Neoplasms.

Background and Objectives: Several polymorphisms have been described in various DNA repair genes. Nucleotide excision DNA repair (NER) detects defects of DNA molecules and corrects them to restore genome integrity. We hypothesized that the XPC, XPD, XPF, and XPG gene polymorphisms influence the appearance of myeloproliferative neoplasms (MPNs). Materials and Methods: We investigated the XPC 1496C>T (rs2228000, XPC Ala499Val), XPC 2920A>C (rs228001, XPC Lys939Gln), XPD 2251A>C (rs13181, XPD Lys751Gln), XPF-673C>T (rs3136038), XPF 11985A>G (rs254942), and XPG 3507G>C (rs17655, XPG Asp1104His) polymorphisms by polymerase chain reaction-restriction fragment length polymorphism analysis in 393 MPN patients [153 with polycythemia vera (PV), 201 with essential thrombocythemia (ET), and 39 with primary myelofibrosis (PMF)] and 323 healthy controls. Results: Overall, we found that variant genotypes of XPD 2251A>C were associated with an increased risk of MPN (OR = 1.54, 95% CI = 1.15-2.08, p = 0.004), while XPF-673C>T and XPF 11985A>G were associated with a decreased risk of developing MPN (OR = 0.56, 95% CI = 0.42-0.76, p < 0.001; and OR = 0.26, 95% CI = 0.19-0.37, p < 0.001, respectively). Conclusions: In light of our findings, XPD 2251A>C polymorphism was associated with the risk of developing MPN and XPF-673C>T and XPF 11985A>G single nucleotide polymorphisms (SNPs) may have a protective role for MPN, while XPC 1496C>T, XPC 2920A>C, and XPG 3507G>C polymorphisms do not represent risk factors in MPN development.

Association of TIMP2 418 G/C and MMP Gene Polymorphism with Risk of Urinary Cancers: Systematic Review and Meta-analysis.

Aim: The matrix metalloproteinases (MMPs) inhibit tissue inhibitors of metalloproteinases (TIMPs), playing a notable role in various biological processes, and mutations in TIMP2 genes impact a variety of urinary cancers. In this study, we analyze and evaluate the potential involvement of the TIMP2 418 G/C and MMP gene polymorphism in the etiology of urinary cancer. Methodology: For suitable case-control studies, a literature search was undertaken from various database sources such as PubMed, EMBASE, and Google Scholar. Incorporated into the analysis were case-control or cohort studies that documented the correlation between TIMP2 418 G/C and urological cancers. MetaGenyo served as the tool for conducting the meta-analysis, employing a fixed-effects model. The collective odds ratios, along with their corresponding 95% confidence intervals, were calculated and presented to assess the robustness of the observed associations. Results: A total of seven studies involving controls and cases out of recorded 1265 controls and 1154 cases were analyzed to ascertain the significant association of the TIMP2 gene with urologic cancer. No statistically significant correlation was observed between allelic, recessive, dominant, and overdominant models for the genetic variant under investigation. A 95% confidence interval (CI) and odds ratio (OR) were computed for each model, considering p-values <0.05. The OR and 95% CI for the allelic model were 0.99 and 0.77-1.27, respectively, whereas the respective values were 1.00 and 0.76-1.32 for the recessive model. In the dominant contrast model, OR and 95% CI were 1.09 and 0.62-1.90, while the same were 0.93 and 0.77-1.12 for the overdominant model. A funnel plot was used to reanalyze and detect the results as statically satisfactory. Conclusions: As a result of the data obtained, the TIMP2 gene polymorphism does not correlate statistically with cancer risk. The significance of this finding can only be confirmed using a large population, extensive epidemiological research, a comprehensive survey, and a better understanding of the molecular pathways associated.

Novel genetic loci of inhibitory control in ADHD and healthy children and genetic correlations with ADHD.

Cumulative evidence has showed the deficits of inhibitory control in patients with attention deficit hyperactivity disorder (ADHD), which is considered as an endophenotype of ADHD. Genetic study of inhibitory control could advance gene discovery and further facilitate the understanding of ADHD genetic basis, but the studies were limited in both the general population and ADHD patients. To reveal genetic risk variants of inhibitory control and its potential genetic relationship with ADHD, we conducted genome-wide association studies (GWAS) on inhibitory control using three datasets, which included 783 and 957 ADHD patients and 1350 healthy children. Subsequently, we employed polygenic risk scores (PRS) to explore the association of inhibitory control with ADHD and related psychiatric disorders. Firstly, we identified three significant loci for inhibitory control in the healthy dataset, two loci in the case dataset, and one locus in the meta-analysis of three datasets. Besides, we found more risk genes and variants by applying transcriptome-wide association study (TWAS) and conditional FDR method. Then, we constructed a network by connecting the genes identified in our study, leading to the identification of several vital genes. Lastly, we identified a potential relationship between inhibitory control and ADHD and autism by PRS analysis and found the direct and mediated contribution of the identified genetic loci on ADHD symptoms by mediation analysis. In conclusion, we revealed some genetic risk variants associated with inhibitory control and elucidated the benefit of inhibitory control as an endophenotype, providing valuable insights into the mechanisms underlying ADHD.

Association of single nucleotide polymorphisms in ITLN1 gene with ischemic stroke risk in Xi'an population, Shaanxi province.

Background: Ischemic stroke (IS) is the main cause of death and adult disability. However, the pathogenesis of this complicated disease is unknown. The present study aimed to assess the relationship between ITLN1 single nucleotide polymorphisms (SNPs) and the susceptibility to IS in Xi'an population, Shaanxi province. Methods: In this study, we designed polymerase chain reaction (PCR) primers located at -3,308 bp upstream of the transcription initiation site within promoter region of the ITLN1 gene. The target fragment was amplified by PCR and identified by agarose gel electrophoresis. Sanger sequencing was then performed in the samples extracted from a cohort comprising 1,272 participants (636 controls and 636 cases), and the obtained sequences were compared with the reference sequences available on the National Center for Biotechnology Information (NCBI) website to detect SNPs in the ITLN1 gene promoter region. Logistic regression analysis was employed to assess the relationship between ITLN1 polymorphisms and IS risk, with adjustments for age and gender. Significant positive results were tested by false-positive report probability (FPRP) and false discovery rate (FDR). The interaction among noteworthy SNPs and their predictive relationship with IS risk were explored using the Multi-Factor Dimensionality Reduction (MDR) software. Results: The results of Sanger sequencing were compared with the reference sequences on the NCBI website, and we found 14 SNPs in ITLN1 gene promoter satisfied Hardy-Weinberg equilibrium (HWE). Logistic regression analysis showed that ITLN1 was associated with a decreased risk of IS (rs6427553: Homozygous C/C: adjusted OR: 0.69, 95% CI [0.48-0.97]; Log-additive: adjusted OR: 0.83, 95% CI [0.70-0.98]; rs7411035: Homozygous G/G: adjusted OR: 0.66, 95% CI [0.47-0.94]; Dominant G/T-G/G: adjusted OR: 0.78, 95% CI [0.62-0.98]; Log-additive: adjusted OR: 0.81, 95% CI [0.69-0.96]; rs4656958: Heterozygous G/A: adjusted OR: 0.74, 95% CI [0.59-0.94]; Homozygous A/A: adjusted OR: 0.51, 95% CI [0.31-0.84]; Dominant G/A-A/A: adjusted OR: 0.71, 95% CI [0.57-0.89]; Recessive A/A: adjusted OR: 0.59, 95% CI [0.36-0.96]; Log-additive: adjusted OR: 0.73, 95% CI [0.61-0.88]), especially in people aged less than 60 years and males. Conclusions: In short, our study revealed a correlation between ITLN1 variants (rs6427553, rs7411035 and rs4656958) and IS risk in Xi'an population, Shaanxi province, laying a foundation for ITLN1 gene as a potential biomarker for predicting susceptibility to IS.

An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer's Disease.

Background: The X chromosome is often omitted in disease association studies despite containing thousands of genes that may provide insight into well-known sex differences in the risk of Alzheimer's disease (AD). Objective: To model the expression of X chromosome genes and evaluate their impact on AD risk in a sex-stratified manner. Methods: Using elastic net, we evaluated multiple modeling strategies in a set of 175 whole blood samples and 126 brain cortex samples, with whole genome sequencing and RNA-seq data. SNPs (MAF > 0.05) within the cis-regulatory window were used to train tissue-specific models of each gene. We apply the best models in both tissues to sex-stratified summary statistics from a meta-analysis of Alzheimer's Disease Genetics Consortium (ADGC) studies to identify AD-related genes on the X chromosome. Results: Across different model parameters, sample sex, and tissue types, we modeled the expression of 217 genes (95 genes in blood and 135 genes in brain cortex). The average model R2 was 0.12 (range from 0.03 to 0.34). We also compared sex-stratified and sex-combined models on the X chromosome. We further investigated genes that escaped X chromosome inactivation (XCI) to determine if their genetic regulation patterns were distinct. We found ten genes associated with AD at p < 0.05, with only ARMCX6 in female brain cortex (p = 0.008) nearing the significance threshold after adjusting for multiple testing (α = 0.002). Conclusions: We optimized the expression prediction of X chromosome genes, applied these models to sex-stratified AD GWAS summary statistics, and identified one putative AD risk gene, ARMCX6.

IGF2BP2 and IGFBP3 Genotypes, Haplotypes, and Genetic Models Studies in Polycystic Ovary Syndrome.

BACKGROUND: Insulin resistance has been correlated with the genetic diversity within the insulin-like binding proteins genes. Moreover, insulin resistance is one of the key characteristics of the widespread reproductive endocrine condition known as polycystic ovarian syndrome (PCOS). Hence, this study is aimed to determine the association between IGFBP3 and IGF2BP2 gene variants and PCOS risk. METHODS: A total of 300 subjects (150 PCOS cases diagnosed based on Rotterdam ESHRE/ASRM consensus criteria and 150 healthy subjects) were recruited in this case-control cross-sectional study. Tetra-primer amplification refractory mutation system polymerase chain reaction (ARMS-PCR) was used for genotyping rs11705701, whereas genotyping of rs1470579 and rs2854744 was done employing PCR-restriction fragment length polymorphism (PCR-RFLP) technique. RESULTS: The CC and AA+AC genotypes of rs1470579 conferred an increased risk of PCOS in our population. Regarding the rs2854744, an increased risk of PCOS was observed under the codominant homozygous (TT vs. GG) model by 2.54 fold. The C allele of rs1470579 and T allele of rs2854744 enhanced PCOS risk by 1.97 and 1.46 folds, respectively. Haplotype analysis showed that the Ars1470579Ars11705701 haplotype conferred a decreased risk of PCOS (odds ratio = 0.53, 95% confidence interval = 0.34-0.83, p = 0.006). The AC/GG/GT, AA/GA/GT, AC/GA/GG, and AC/GA/GT genotype combinations of rs1470579/rs11705701/rs2854744 were associated with a decreased risk of the disease. CONCLUSIONS: IGF2BP2 rs1470579 and IGFBP3 rs2854744 enhanced PCOS susceptibility in a Southeastern Iranian population. Further investigation involving larger cohorts representing diverse ethnic backgrounds is needed to confirm the current findings.

Sex-specific genetic architecture of blood pressure.

The genetic and genomic basis of sex differences in blood pressure (BP) traits remain unstudied at scale. Here, we conducted sex-stratified and combined-sex genome-wide association studies of BP traits using the UK Biobank resource, identifying 1,346 previously reported and 29 new BP trait-associated loci. Among associated loci, 412 were female-specific (Pfemale ≤ 5 × 10-8; Pmale > 5 × 10-8) and 142 were male-specific (Pmale ≤ 5 × 10-8; Pfemale > 5 × 10-8); these sex-specific loci were enriched for hormone-related transcription factors, in particular, estrogen receptor 1. Analyses of gene-by-sex interactions and sexually dimorphic effects identified four genomic regions, showing female-specific associations with diastolic BP or pulse pressure, including the chromosome 13q34-COL4A1/COL4A2 locus. Notably, female-specific pulse pressure-associated loci exhibited enriched acetylated histone H3 Lys27 modifications in arterial tissues and a female-specific association with fibromuscular dysplasia, a female-biased vascular disease; colocalization signals included Chr13q34: COL4A1/COL4A2, Chr9p21: CDKN2B-AS1 and Chr4q32.1: MAP9 regions. Sex-specific and sex-biased polygenic associations of BP traits were associated with multiple cardiovascular traits. These findings suggest potentially clinically significant and BP sex-specific pleiotropic effects on cardiovascular diseases.