Toxoplasma gondii (T. gondii) is an opportunistic pathogen affecting about 1/3 of world population. While often asymptomatic in immunocompetent individuals, it can lead to severe toxoplasmosis in immunocompromised patients. Recent research has unveiled a potential link between T. gondii infection and neuropsychiatric diseases. We implemented both a cohort study and a case control study to further identify this association. In the cohort study, we analyzed data from the UK Biobank database, which included 8814 individuals tested for T. gondii SAG1 antibodies and free of neuropsychiatric disorders at baseline. Among them, 22.52% (n = 1985) tested positive for SAG1 antibody. Over an average follow-up period of 12.26 years, Cox proportional hazards models and logistic regression analysis revealed a significant association between the SAG1 seropositivity at baseline and the incidence of schizophrenia (HR: 5.89; 95% CI: 1.69-20.53). In our case-control study, 239 patients diagnosed with schizophrenia and 455 healthy individuals were involved. Using the modified agglutination test (MAT) to detect T. gondii antibodies, logistic regression analysis showed a higher prevalence of T. gondii infection among schizophrenia patients (10.04%) compared to healthy controls (3.74%). T. gondii infection emerged as a significant risk factor for schizophrenia (OR: 3.33; 95% CI: 1.68-6.61). However, our investigations did not reveal a robust association between T. gondii infection and other neuropsychiatric conditions, including Alzheimer\'s disease, dementia, anxiety, depression, neurodegenerative disorders, and peripheral neurological disorders such as neurological and plexus disorders.

Runs of heterozygosity (ROHet) and homozygosity (ROH) harbor useful information related to traits of interest. There is a lack of investigating the effect of ROHet and ROH on reproductive success and the loss of reproduction in mammals. Here, we detected and characterized the ROHet and ROH patterns in the genomes of Chinese indigenous pigs (i.e., Jinhua, Chun\'an, Longyou Black, and Shengxian Spotted pigs), revealing the similar genetic characteristics of indigenous pigs. Later, we highlighted the underlying litter traits-related ROHet and ROH using association analysis with linear model in these four indigenous pig breeds. To pinpoint the promising candidate genes associated with litter traits, we further in-depth explore the selection patterns of other five pig breeds (i.e., Erhualian, Meishan, Minzhu, Rongchang, and Diqing pigs) with different levels of reproduction performance at the underlying litter traits-related ROHet and ROH using F ST and genetic diversity ratio. Then, we identified a set of known and novel candidate genes associated with reproductive performance in pigs. For the novel candidate genes (i.e., CCDC91, SASH1, SAMD5, MACF1, MFSD2A, EPC2, and MBD5), we obtained public available datasets and performed multi-omics analyses integrating transcriptome-wide association studies and comparative single-cell RNA-seq analyses to uncover the roles of them in mammalian reproductive performance. The genes have not been widely reported to be fertility-related genes and can be complementally considered as prior biological information to modify genomic selections models that benefits pig genetic improvement of litter traits. Besides, our findings provide new insights into the function of ROHet and ROH in mammals.

Pancreatic cancer is a deadly disease that accounts for approximately 5% of cancer deaths worldwide, with a dismal 5-year survival rate of 10%. Known genetic risk factors explain only a modest proportion of the heritable risk of pancreatic cancer. We conducted a whole-exome case-control sequencing study in 1,591 pancreatic cancer cases and 2,134 cancer-free controls of European ancestry. In our gene-based analysis, ATM ranked first, with a genome-wide significant p value of 1 × 10-8. The odds ratio for protein-truncating variants in ATM was 24, which is substantially higher than prior estimates, although ours includes a broad 95% confidence interval (4.0-1000). SIK3 was the second highest ranking gene (p = 3.84 × 10-6, false discovery rate or FDR = 0.032). We observed nominally significant association signals in several genes of a priori interest, including BRCA2 (p = 4.3 × 10-4), STK11 (p = 0.003), PALB2 (p = 0.019), and TP53 (p = 0.037), and reported risk estimates for known pathogenic variants and variants of uncertain significance (VUS) in these genes. The rare variants in established susceptibility genes explain approximately 24% of log familial relative risk, which is comparable to the contribution from established common susceptibility variants (17%). In conclusion, this study provides new insights into the genetic susceptibility of pancreatic cancer, refining rare variant risk estimates in known pancreatic cancer susceptibility genes and identifying SIK3 as a novel candidate susceptibility gene. This study highlights the prominent importance of ATM truncating variants and the underappreciated role of VUS in pancreatic cancer etiology.

Aims: We aimed to explore whether RELN contributes to the vulnerability and severity of clinical symptoms of schizophrenia (SZ) in a Chinese population. Methods: The following were conducted in an adult Han Chinese population from southern China: case-control association analyses of 30 representative single nucleotide polymorphisms (SNPs) that were screened according to specific programs based on bioinformatics tools and former research and quantitative trait locus analyses with SNPs and psychiatric symptoms evaluated with the positive and negative symptoms scale. Results: A 4-SNP haplotype consisting of rs362814, rs39339, rs540058, and rs661575 was found to be significantly associated with SZ even after Bonferroni correction (χ2 = 29.024, p = 6.42E-04, p Bonf = 0.017), and the T-C-T-C haplotype was a protective factor for SZ (OR = 0.050, 95% CI = 0.004-0.705). Moreover, the 4-SNP haplotype showed a significant association with G16 (active social avoidance) after false discovery rate correction (χ2 = 28.620, p = 1.697E-04, p FDR = 0.025). In addition, P7 (hostility) was related to the haplotype comprising rs2229864, rs2535764, and rs262355 (χ2 = 31.424, p = 2.103E-05, p adjustment = 0.019) in quantitative trait loci analyses. Conclusion: Overall, this study showed several positive associations between RELN and SZ, as well as psychiatric symptoms, which not only supports the proposition that RELN is a susceptibility gene for SZ but also provides information on a genotype-phenotype correlation for SZ in a Chinese population.

Hundreds of genome-wide association studies were conducted to map the disease genes on autosomes in human beings. It is known that many complex diseases are sex-determined and X chromosome is expected to play an important role. However, only a few single-nucleotide polymorphisms on X chromosome were found to be significantly associated with the diseases under study. On the other hand, to balance the genetic effect between two sexes, X chromosome inactivation occurs in most of X-linked genes by silencing one copy of two X chromosomes in females and dosage compensation is achieved. A few association studies on X chromosome incorporated the information on dosage compensation. However, some of them require the assumption of Hardy-Weinberg equilibrium and some need to specify the underlying genetic model. Therefore, in this article, we propose a novel method for association by taking account of different dosage compensation patterns. The proposed test is a robust approach because it requires neither specifying the underlying genetic models nor the assumption of Hardy-Weinberg equilibrium. Further, the proposed method allows for different deviations from Hardy-Weinberg equilibrium between cases and controls. Simulation results demonstrate that our proposed method generally outperforms the existing methods in terms of controlling the size and the test power. Finally, we apply the proposed test to the meta-analysis of the Graves\' disease data for its practical use.

Breast cancer is the most common cancer in women worldwide. Breast tumorigenesis encompasses both extrinsic and intrinsic factors. Among intrinsic aspects, the appearance of DNA variation can cause genetic instability, which may lead to carcinogenesis. Genome-wide association studies have found several potential breast cancer-associated single nucleotide polymorphisms (SNPs) in many different populations. Among these, seven (rs2046210, rs1219648, rs3817198, rs3803662, rs889312, rs10941679 and rs13281615) have been shown to be significantly associated with breast cancer risk in various populations including those very similar to the Vietnamese. Here, therefore, we have investigated the relationship between these SNPs and breast cancer risk in a Vietnamese population case-control cohort. Real-time PCR high-resolution melt analysis was performed to genotype 300 breast cancer cases and 325 healthy controls, and the association between the seven SNPs and breast cancer risk was determined by analyzing the differences in allelic and genotypic frequencies between case and control groups using R software. While five of the seven showed no association with breast cancer, there was a relationship between the other two SNPs, rs2046210 and rs3803662, and the risk of developing this disease in Vietnamese women. The A allele is the risk allele for both rs2046210 (OR [95% CI] = 1.43 [1.14 - 1.78], P = 0.0015) and rs3803662 (OR [95% CI] = 1.45 [1.16 - 1.83], P = 0.001). We conclude that two polymorphisms, rs2046210 in ESR1 and rs3803662 in TNRC9, are associated with breast cancer risk in the Vietnamese population.

BACKGROUND: Cerebral palsy (CP) is the leading cause of motor disability in children; however, its pathogenesis is unknown in most cases. Growing evidence suggests that Nitric oxide synthase 1 (NOS1) is involved in neural development and neurologic diseases. The purpose of this study was to determine whether genetic variants of NOS1 contribute to CP susceptibility in a Han Chinese population.
METHODS: A case-control study involving 652 CP patients and 636 healthy controls was conducted. Six SNPs in the NOS1 gene (rs3782219, rs6490121, rs2293054, rs10774909, rs3741475, and rs2682826) were selected, and the MassARRAY typing technique was applied for genotyping. Data analysis was conducted using SHEsis online software, and multiple test corrections were performed using SNPSpD online software.
RESULTS: There were no significant differences in genotype and allele frequencies between patients and controls for the SNPs except rs6490121, which deviated from Hardy-Weinberg equilibrium and was excluded from further analyses. Subgroup analysis revealed differences in genotype frequencies between the CP with neonatal encephalopathy group (CP + NE) and control group for rs10774909, rs3741475, and rs2682826 (after SNPSpD correction, p = 0.004, 0.012, and 0.002, respectively). The T allele of NOS1 SNP rs3782219 was negatively associated with spastic quadriplegia (OR = 0.742, 95% CI = 0.600-0.918, after SNPSpD correction, p = 0.023). There were no differences in allele or genotype frequencies between CP subgroups and controls for the other genetic polymorphisms.
CONCLUSIONS: NOS1 is associated with CP + NE and spastic quadriplegia, suggesting that NOS1 is likely involved in the pathogenesis of CP and that it is a potential therapeutic target for treatment of cerebral injury.

The genetic basis of complex diseases often involves multiple causative loci. Under such a disease etiology, assuming one disease locus in linkage disequilibrium mapping is likely to induce bias and lead to efficiency loss in disease locus estimation. An approach is needed for simultaneously localizing multiple functional loci within the same region. However, due to the increasing number of parameters accompanying disease loci, these estimates can be computationally infeasible. To circumvent this problem, we propose to estimate the main and two-adjacent-locus joint effects and a nuisance parameter at the disease loci separately through a linear approximation. Estimates of the genetic effects are entered into a generalized estimating equation to estimate disease loci, and the procedure is conducted iteratively until convergence. The proposed method provides estimates and confidence intervals (CIs) for the disease loci, the genetic main effects, and the joint effects of two adjacent disease loci, with the CIs for the disease loci providing useful regions for further fine-mapping. We apply the proposed approach to a data example of case-control studies. Results of the simulations and data example suggest that the developed method performs well in terms of bias, variance, and coverage probability under scenarios with up to three disease loci.

Rare variants have recently garnered an immense amount of attention in genetic association analysis. However, unlike methods traditionally used for single marker analysis in GWAS, rare variant analysis often requires some method of aggregation, since single marker approaches are poorly powered for typical sequencing study sample sizes. Advancements in sequencing technologies have rendered next-generation sequencing platforms a realistic alternative to traditional genotyping arrays. Exome sequencing in particular not only provides base-level resolution of genetic coding regions, but also a natural paradigm for aggregation via genes and exons. Here, we propose the use of penalized regression in combination with variant aggregation measures to identify rare variant enrichment in exome sequencing data. In contrast to marginal gene-level testing, we simultaneously evaluate the effects of rare variants in multiple genes, focusing on gene-based least absolute shrinkage and selection operator (LASSO) and exon-based sparse group LASSO models. By using gene membership as a grouping variable, the sparse group LASSO can be used as a gene-centric analysis of rare variants while also providing a penalized approach toward identifying specific regions of interest. We apply extensive simulations to evaluate the performance of these approaches with respect to specificity and sensitivity, comparing these results to multiple competing marginal testing methods. Finally, we discuss our findings and outline future research.