Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma.

We performed the first proteogenomic characterization of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) using paired tumor and adjacent liver tissues from 159 patients. Integrated proteogenomic analyses revealed consistency and discordance among multi-omics, activation status of key signaling pathways, and liver-specific metabolic reprogramming in HBV-related HCC. Proteomic profiling identified three subgroups associated with clinical and molecular attributes including patient survival, tumor thrombus, genetic profile, and the liver-specific proteome. These proteomic subgroups have distinct features in metabolic reprogramming, microenvironment dysregulation, cell proliferation, and potential therapeutics. Two prognostic biomarkers, PYCR2 and ADH1A, related to proteomic subgrouping and involved in HCC metabolic reprogramming, were identified. CTNNB1 and TP53 mutation-associated signaling and metabolic profiles were revealed, among which mutated CTNNB1-associated ALDOA phosphorylation was validated to promote glycolysis and cell proliferation. Our study provides a valuable resource that significantly expands the knowledge of HBV-related HCC and may eventually benefit clinical practice.

Genomic characterization and immunotherapy for microsatellite instability-high in cholangiocarcinoma.

BACKGROUND: Microsatellite instability-high (MSI-H) is a unique genomic status in many cancers. However, its role in the genomic features and immunotherapy in cholangiocarcinoma (CCA) is unclear. This study aimed to systematically investigate the genomic characterization and immunotherapy efficacy of MSI-H patients with CCA. METHODS: We enrolled 887 patients with CCA in this study. Tumor samples were collected for next-generation sequencing. Differences in genomic alterations between the MSI-H and microsatellite stability (MSS) groups were analyzed. We also investigated the survival of PD-1 inhibitor-based immunotherapy between two groups of 139 patients with advanced CCA. RESULTS: Differential genetic alterations between the MSI-H and MSS groups included mutations in ARID1A, ACVR2A, TGFBR2, KMT2D, RNF43, and PBRM1 which were enriched in MSI-H groups. Patients with an MSI-H status have a significantly higher tumor mutation burden (TMB) (median 41.7 vs. 3.1 muts/Mb, P < 0.001) and more positive programmed death ligand 1 (PD-L1) expression (37.5% vs. 11.9%, P < 0.001) than those with an MSS status. Among patients receiving PD-1 inhibitor-based therapy, those with MSI-H had a longer median overall survival (OS, hazard ratio (HR) = 0.17, P = 0.001) and progression-free survival (PFS, HR = 0.14, P < 0.001) than patients with MSS. Integrating MSI-H and PD-L1 expression status (combined positive score ≥ 5) could distinguish the efficacy of immunotherapy. CONCLUSIONS: MSI-H status was associated with a higher TMB value and more positive PD-L1 expression in CCA tumors. Moreover, in patients with advanced CCA who received PD-1 inhibitor-based immunotherapy, MSI-H and positive PD-L1 expression were associated with improved both OS and PFS. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov on 07/01/2017 (NCT03892577).

MmisAT and MmisP: an efficient and accurate suite of variant analysis toolkit for primary mitochondrial diseases.

Recent advances in next-generation sequencing (NGS) technology have greatly accelerated the need for efficient annotation to accurately interpret clinically relevant genetic variants in human diseases. Therefore, it is crucial to develop appropriate analytical tools to improve the interpretation of disease variants. Given the unique genetic characteristics of mitochondria, including haplogroup, heteroplasmy, and maternal inheritance, we developed a suite of variant analysis toolkits specifically designed for primary mitochondrial diseases: the Mitochondrial Missense Variant Annotation Tool (MmisAT) and the Mitochondrial Missense Variant Pathogenicity Predictor (MmisP). MmisAT can handle protein-coding variants from both nuclear DNA and mtDNA and generate 349 annotation types across six categories. It processes 4.78 million variant data in 76 min, making it a valuable resource for clinical and research applications. Additionally, MmisP provides pathogenicity scores to predict the pathogenicity of genetic variations in mitochondrial disease. It has been validated using cross-validation and external datasets and demonstrated higher overall discriminant accuracy with a receiver operating characteristic (ROC) curve area under the curve (AUC) of 0.94, outperforming existing pathogenicity predictors. In conclusion, the MmisAT is an efficient tool that greatly facilitates the process of variant annotation, expanding the scope of variant annotation information. Furthermore, the development of MmisP provides valuable insights into the creation of disease-specific, phenotype-specific, and even gene-specific predictors of pathogenicity, further advancing our understanding of specific fields.

Structural diversity in the membrane-bound hIAPP dimer correlated with distinct membrane disruption mechanisms.

Amyloid deposits of the human islet amyloid polypeptide (hIAPP) have been identified in 90% of patients with type II diabetes. Cellular membranes accelerate the hIAPP fibrillation, and the integrity of membranes is also disrupted at the same time, leading to the apoptosis of ß cells in pancreas. The molecular mechanism of hIAPP-induced membrane disruption, especially during the initial membrane disruption stage, has not been well understood yet. Herein, we carried out extensive all-atom molecular dynamics simulations investigating the hIAPP dimerization process in the anionic POPG membrane, to provide the detailed molecular mechanisms during the initial hIAPP aggregation stage in the membrane environment. Compared to the hIAPP monomer on the membrane, we observed not only an increase of α-helical structures, but also a substantial increase of ß-sheet structures upon spontaneous dimerization. Moreover, the random coiled and α-helical dimer structures insert deep into the membrane interior with a few inter-chain contacts at the C-terminal region, while the ß-sheet-rich structures reside on the membrane surface accompanied by strong inter-chain hydrophobic interactions. The coexistence of α and ß structures constitutes a diverse structural ensemble of the membrane-bound hIAPP dimer. From α-helical to ß-sheet structures, the degree of membrane disruption decreases gradually, and thus the membrane damage induced by random coiled and α-helical structures precedes that induced by ß-sheet structures. We speculate that insertion of random coiled and α-helical structures contributes to the initial stage of membrane damage, while ß-sheet structures on the membrane surface are more involved in the later stage of fibril-induced membrane disruption.

Towards more precise automatic analysis: a systematic review of deep learning-based multi-organ segmentation.

Accurate segmentation of multiple organs in the head, neck, chest, and abdomen from medical images is an essential step in computer-aided diagnosis, surgical navigation, and radiation therapy. In the past few years, with a data-driven feature extraction approach and end-to-end training, automatic deep learning-based multi-organ segmentation methods have far outperformed traditional methods and become a new research topic. This review systematically summarizes the latest research in this field. We searched Google Scholar for papers published from January 1, 2016 to December 31, 2023, using keywords "multi-organ segmentation" and "deep learning", resulting in 327 papers. We followed the PRISMA guidelines for paper selection, and 195 studies were deemed to be within the scope of this review. We summarized the two main aspects involved in multi-organ segmentation: datasets and methods. Regarding datasets, we provided an overview of existing public datasets and conducted an in-depth analysis. Concerning methods, we categorized existing approaches into three major classes: fully supervised, weakly supervised and semi-supervised, based on whether they require complete label information. We summarized the achievements of these methods in terms of segmentation accuracy. In the discussion and conclusion section, we outlined and summarized the current trends in multi-organ segmentation.

Multi-task learning-based histologic subtype classification of non-small cell lung cancer.

PURPOSE: In clinical applications, accurate histologic subtype classification of lung cancer is important for determining appropriate treatment plans. The purpose of this paper is to evaluate the role of multi-task learning in the classification of adenocarcinoma and squamous cell carcinoma. MATERIAL AND METHODS: In this paper, we propose a novel multi-task learning model for histologic subtype classification of non-small cell lung cancer based on computed tomography (CT) images. The model consists of a histologic subtype classification branch and a staging branch, which share a part of the feature extraction layers and are simultaneously trained. By optimizing on the two tasks simultaneously, our model could achieve high accuracy in histologic subtype classification of non-small cell lung cancer without relying on physician's precise labeling of tumor areas. In this study, 402 cases from The Cancer Imaging Archive (TCIA) were used in total, and they were split into training set (n = 258), internal test set (n = 66) and external test set (n = 78). RESULTS: Compared with the radiomics method and single-task networks, our multi-task model could reach an AUC of 0.843 and 0.732 on internal and external test set, respectively. In addition, multi-task network can achieve higher accuracy and specificity than single-task network. CONCLUSION: Compared with the radiomics methods and single-task networks, our multi-task learning model could improve the accuracy of histologic subtype classification of non-small cell lung cancer by sharing network layers, which no longer relies on the physician's precise labeling of lesion regions and could further reduce the manual workload of physicians.

Label correlation transformer for automated chest X-ray diagnosis with reliable interpretability.

Computer-aided diagnosis of chest X-ray (CXR) images can help reduce the huge workload of radiologists and avoid the inter-observer variability in large-scale early disease screening. Recently, most state-of-the-art studies employ deep learning techniques to address this problem through multi-label classification. However, existing methods still suffer from low classification accuracy and poor interpretability for each diagnostic task. This study aims to propose a novel transformer-based deep learning model for automated CXR diagnosis with high performance and reliable interpretability. We introduce a novel transformer architecture into this problem and utilize the unique query structure of transformer to capture the global and local information of the images and the correlation between labels. In addition, we propose a new loss function to help the model find correlations between the labels in CXR images. To achieve accurate and reliable interpretability, we generate heatmaps using the proposed transformer model and compare with the true pathogenic regions labeled by the physicians. The proposed model achieves a mean AUC of 0.831 on chest X-ray 14 and 0.875 on PadChest dataset, which outperforms existing state-of-the-art methods. The attention heatmaps show that our model could focus on the exact corresponding areas of related truly labeled pathogenic regions. The proposed model effectively improves the performance of CXR multi-label classification and the interpretability of label correlations, thus providing new evidence and methods for automated clinical diagnosis.

Distinct binding interactions trigger opposite conformational modulations on pathogenic and wildtype Huntingtin exon 1 proteins.

Abnormal elongation of the polyglutamine tract transforms exon 1 of the Huntingtin protein (Htt-exon-1) from wildtype to pathogenic form, and causes Huntington's disease. As an intrinsically disordered protein, the structural ensemble of Htt-exon-1 is highly heterogeneous and the detailed conformation of toxic species is still under debate. Ispinesib, a potential small-molecule drug, has been identified to selectively link the pathogenic Htt-exon-1 into the autophagosome to degrade, thus opening an innovative therapeutic direction. However, the molecular mechanisms behind this selectivity remain largely elusive. Herein, we carry out extensive molecular dynamics simulations with an enhanced sampling method to investigate the ispinesib inducing conformational changes of pathogenic and wildtype Htt-exon-1 and the corresponding binding mechanisms. Our simulations reveal that the ispinesib binding induces opposite conformational changes in pathogenic and wildtype Htt-exon-1, i.e., the 'entropy collapse' with significant reduction of ß-sheets versus the 'entropy expansion' with a slight increase of α-helices. Network analyses further reveal that there are two stable binding sites in the pathogenic Htt-exon-1, while the binding on the wildtype Htt-exon-1 is highly dynamic and non-specific. These dramatic differences originate from the underlying distinct binding interactions. More specifically, stronger hydrogen bonds serve as the specific binding anchors in pathogenic Htt-exon-1, while stronger hydrophobic interactions dominate in the dynamic binding with wildtype Htt-exon-1. Our simulations provide an atomistic mechanism for the ispinesib selective binding on the pathogenic Htt-exon-1, and further shed light on the general mechanisms of small molecule modulation on intrinsically disordered proteins.

Alternative splicing patterns reveal prognostic indicator in muscle-invasive bladder cancer.

BACKGROUND: Bladder cancer is one of the most lethal malignancy in urological system, and 20-25% of bladder cancer patients are muscle invasive with unfavorable prognosis. However, the role of alternative splicing (AS) in muscle-invasive bladder cancer (MIBC) remains to be elucidated. METHODS: Percent spliced in (PSI) data obtained from the Cancer Genome Atlas (TCGA) SpliceSeq database (n = 394) were utilized to evaluate the AS events in MIBC. Prognosis-associated AS events were screened out by univariate Cox regression. LASSO Cox regression was used to identify reliable prognostic patterns in a training set and further validated in a test set. Splicing regulatory networks were constructed by correlations between PSI of AS events and RNA expression of splicing factors. RESULTS: As a result, a total of 2589 prognosis-related AS events in MIBC were identified. Pathways of spliceosomal complex (FDR = 0.017), DNA-directed RNA polymerase II, core complex (FDR = 0.032), and base excision repair (FDR = 0.038) were observed to be significantly enriched. Additionally, we noticed that most of the prognosis-related AS events were favorable factors. According to the LASSO and multivariate Cox regression analyses, 15-AS-based signature was established with the area under curve (AUC) of 0.709, 0.823, and 0.857 at 1-, 3-, and 5- years, respectively. The MIBC patients were further divided into high- and low-risk groups based on median risk sores. Interestingly, we observed that the prevalence of FGFR3 with mutations and focal amplification was significantly higher in low-risk group. Functional and immune infiltration analysis suggested potential signaling pathways and distinct immune states between these two groups. Moreover, splicing correlation network displayed a regulatory mode of prognostic splicing factors (SF) in MIBC patients. CONCLUSIONS: This study not only provided novel insights into deciphering the possible mechanism of tumorgenesis and pathogenesis but also help refine risk stratification systems and potential treatment of decision-making for MIBC.

Clinically significant genomic alterations in the Chinese and Western patients with intrahepatic cholangiocarcinoma.

BACKGROUND: The goal of this study is to disclose the clinically significant genomic alterations in the Chinese and Western patients with intrahepatic cholangiocarcinoma. METHODS: A total of 86 Chinese patients were enrolled in this study. A panel of 579 pan-cancer genes was sequenced for the qualified samples from these patients. Driver genes, actionability, and tumor mutational burden were inferred and compared to a cohort of Western patients. RESULTS: Totally, 36 and 12 driver genes were identified in the Chinese and Western cohorts, respectively. Of them, seven driver genes (IDH1, KRAS, TP53, BAP1, PBRM1, ARID1A, and NRAS) were shared by the two cohorts. Four driver genes (SPTA1, ARID2, TP53, and GATA1) were found significantly correlated with the tumor mutational burden. For both cohorts, half of the patients had actionable mutations. The two cohorts shared the most actionable genes but differed much in their frequency. Though KRAS mutations were at the first and second actionable rank respectively for the Chinese and Western populations, they were still at a relatively low level of actionable evidence. CONCLUSIONS: The study on the clinical significance of genomic alterations directs the future development of precision medicine for intrahepatic cholangiocarcinoma treatment.

Germline Mutations in CDH23, Encoding Cadherin-Related 23, Are Associated with Both Familial and Sporadic Pituitary Adenomas.

Pituitary adenoma (PA) is one of the most common intracranial neoplasms. Several genetic predisposing factors for PA have been identified, but they account for a small portion of cases. In this study, we sought to identify the PA genetic risk factors by focusing on causative mutations for PAs. Among the 4 affected and 17 asymptomatic members from one family with familial PA, whole-exome sequencing identified cosegregation of the PA phenotype with the heterozygous missense mutation c.4136G>T (p.Arg1379Leu) in cadherin-related 23 (CDH23). This mutation causes an amino acid substitution in the calcium-binding motif of the extracellular cadherin (EC) domains of CDH23 and is predicted to impair cell-cell adhesion. Genomic screening in a total of 12 families with familial PA (20 individuals), 125 individuals with sporadic PA, and 260 control individuals showed that 33% of the families with familial PA (4/12) and 12% of individuals with sporadic PA (15/125) harbored functional CDH23 variants. In contrast, 0.8% of the healthy control individuals (2/260) carried functional CDH23 variants. Gene-based analysis also revealed a significant association between CDH23 genotype and PA (p = 5.54 × 10-7). Moreover, PA individuals who did not harbor functional CDH23 variants displayed tumors that were larger in size (p = 0.005) and more invasive (p < 0.001). Therefore, mutations in CDH23 are linked with familial and sporadic PA and could play important roles in the pathogenesis of PA.

Whole-exome sequencing of oral mucosal melanoma reveals mutational profile and therapeutic targets.

Oral mucosal melanoma (OMM) is a rare and aggressive subtype of melanoma with little known about its pathogenesis or carcinogenesis. We therefore performed whole-exome sequencing (WES) on 19 matched OMM tumor/normal pairs in order to gain insight into potential genetic drivers of tumor formation. For the first time, we describe the comprehensive mutational profile of OMM. Our data suggest that the genetic background of OMM differs from those of other melanoma subtypes. We identified recurrent mutations involving KIT, POLE, PTPRD, PTCHD2, and DMXL2. Notably, copy number analysis revealed recurrently amplified regions of 12q14 (57.9%, containing CDK4) and 5p15 (47.4%, containing TERT). CNV analysis in a separate cohort of 15 samples validated the frequent CNV in CDK4 and TERT. We also observed that the melanocyte development and pigmentation signaling pathway is frequently altered in OMM. Furthermore, our data suggest several altered genes that may be amenable for targeted therapy. We identified one patient with metastatic OMM in our cohort who was identified to harbor a targetable KIT mutation using our WES results. This patient was able to achieve complete remission following implementation of KIT-targeted therapy. These findings provide further insight into the genetic underpinnings of OMM development and suggest that patients with OMM may benefit from WES analysis to identify potential targetable genetic mutations. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Formation of α-helical and ß-sheet structures in membrane-bound human IAPP monomer and the resulting membrane deformation.

The amyloid formation of human islet amyloid polypeptide (hIAPP)-an intrinsically disordered peptide, is associated with type II diabetes. Cellular membranes, especially those composed of negatively-charged lipids, accelerate the hIAPP amyloid fibrillation, and their integrity is disrupted during the aggregation process, leading to cell apoptosis. However, the underlying molecular mechanism is not well understood. Herein, we investigated the conformational dynamics during the interactions of hIAPP monomer with POPG membrane bilayer, by carrying out µs-long all-atom molecular dynamics simulations. Starting from the metastable coiled conformations in water, hIAPP monomers tend to adopt transient α-helical and ß-sheet structures when adsorbing to the membrane surface. The amphiphilic N-terminal region further inserts into the membrane interior and is located at the lipid head-tail interface, mainly in turn and α-helical structures. In contrast, the ß-hairpin structures reside on the membrane surface without insertion, and expand laterally with the hydrophobic residues exposed to the solvent. Moreover, the adsorption and insertion of hIAPP monomers induce two distinct local membrane deformations: (1) the hIAPP adsorption on the membrane surface mainly causes membrane bending; (2) the insertion of both turns and α-helices synchronizes with the formation of hydrophobic defects on the POPG membrane, leading to stronger membrane stretching and a longer coherence length of membrane thinning. Based on the structural and dynamical results, we propose that ß-hairpin structures may be a precursor for the fibrillation on the membrane surface due to the flat geometry and hydrophobic regions exposed to solvent, while N-terminal amphiphilic α-helices would facilitate hIAPP assembling into toxic oligomers inside the membrane.

SLC39A8 is a risk factor for schizophrenia in Uygur Chinese: a case-control study.

BACKGROUND: Schizophrenia is a severe mental disease with high morbidity and heritability. The SLC39A8 gene is located in 4q24 and encodes a protein that transports many metal ions. Multiple previous studies found that one of the most pleiotropic single nucleotide polymorphisms (SNPs) in SLC39A8, rs13107325, is associated with schizophrenia in the European population. However, the polymorphism of this locus is rare in other populations. In China, the Han Chinese and the Uygur Chinese are two ethnic populations that originate from different races. METHODS: A case-control study was conducted with 983 schizophrenia cases and 1230 healthy controls of the Chinese Uygur population. To validate the most promising SNP, meta-analyses were conducted with the Han Chinese and the European PGC2 data sets reported previously. RESULTS: A susceptible locus, rs10014145 (pallele = 0.014, pallele = 0.098 after correction; pgenotype = 0.004, pgenotype = 0.032 after correction) was identified in case-control study of the Chinese Uygur population. Further, the association between rs10014145 and schizophrenia was supported by a meta-analysis of Han and Uygur Chinese samples (pooled OR [95% CI] =1.10 [1.03-1.17], Z = 2.73, p = 0.006). The association between rs10014145 and schizophrenia was not significant in a meta-analysis of combined Chinese and European samples (pooled OR [95% CI] =1.07 [1.00-1.14], Z = 1.88, and p = 0.06). In addition, the "CCAC" haplotype of rs4698844-rs233814-rs13114343-rs151394 was significantly associated with schizophrenia in Uygur Chinese (P = 0.003, corrected p = 0.012). CONCLUSIONS: The results of this study support that SLC39A8 is a susceptible gene for schizophrenia in the populations of Han Chinese and Uygur Chinese in China, further studies are suggested to validate the association.

Identification of a novel susceptibility locus at 16q23.1 associated with childhood acute lymphoblastic leukemia in Han Chinese.

Recently, genome-wide association studies (GWAS) have identified several susceptibility loci for childhood acute lymphoblastic leukemia (ALL) in populations of European descent; only a few loci could be confirmed in Asian populations because of those populations' genetic heterogeneity. To identify genetic factors associated with childhood ALL risk in the Chinese population, we performed a three-stage GWAS of 1184 childhood ALL cases and 3219 non-ALL controls. The combined analysis identified a new locus (rs1121404 in WWOX) at 16q23.1 associated with childhood ALL susceptibility (odds ratio (OR) = 1.38, P = 5.29 × 10-10), especially in the subtype of B-ALL (OR = 1.39, P = 2.47 × 10-9). The functional studies subsequently revealed that the expression of WWOX in ALL bone marrow was significantly lower than that in normal bone marrow. The G allele of rs1121404 displayed significantly decreased levels of mRNA expression of WWOX These results suggest that WWOX plays an important role in the development of childhood ALL and provide new insights into the etiology of childhood ALL.

Renal hypouricemia caused by novel compound heterozygous mutations in the SLC22A12 gene: a case report with literature review.

BACKGROUND: Renal hypouricemia (RHUC) is a heterogeneous genetic disorder that is characterized by decreased serum uric acid concentration and increased fractional excretion of uric acid. Previous reports have revealed many functional mutations in two urate transporter genes, SLC22A12 and/or SLC2A9, to be the causative genetic factors of this disorder. However, there are still unresolved patients, suggesting the existence of other causal genes or new mutations. Here, we report an RHUC patient with novel compound heterozygous mutations in the SLC22A12 gene. CASE PRESENTATION: A 27-year-old female presenting with recurrent hypouricemia during routine checkups was referred to our hospital. After obtaining the patient's consent, both the patient and her healthy parents were analyzed using whole-exome sequencing (WES) and Sanger sequencing to discover and validate causal mutations, respectively. The prioritization protocol of WES screened out two mutations of c.269G > A/p.R90H and c.1289_1290insGG/p.M430fsX466, which are both located in the SLC22A12 gene, in the patient. Sanger sequencing further confirmed that the patient's heterozygous c.269G > A/p.R90H mutation, which has been reported previously, derived from her mother, and the heterozygous c.1289_1290insGG/p.M430fsX466 mutation, which was found for the first time, derived from her father. p.R90H, which is highly conserved among different species, may decrease the stability of this domain and was considered to be almost damaging in silicon analysis. p.M430fsX466 lacks the last three transmembrane domains, including the tripeptide motif (S/T)XΦ (X = any amino acid and Φ = hydrophobic residue), at the C-terminal, which interact with scaffolding protein PDZK1 and thus will possibly lead to weak functioning of urate transport through the disruption of the "transporter complex" that is formed by URAT1 and PDZK1. CONCLUSIONS: We report a Chinese patient with RHUC, which was caused by compound heterozygous mutations of the SLC22A12 gene, using WES and Sanger sequencing for the first time. Mutation-induced structural instability or malfunction of the urate transporter complex may be the main mechanisms for this hereditary disorder.

Computer-aided detection in chest radiography based on artificial intelligence: a survey.

As the most common examination tool in medical practice, chest radiography has important clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease based on chest radiography has become one of the hot topics in medical imaging research. Based on the clinical applications, the study conducts a comprehensive survey on computer-aided detection (CAD) systems, and especially focuses on the artificial intelligence technology applied in chest radiography. The paper presents several common chest X-ray datasets and briefly introduces general image preprocessing procedures, such as contrast enhancement and segmentation, and bone suppression techniques that are applied to chest radiography. Then, the CAD system in the detection of specific disease (pulmonary nodules, tuberculosis, and interstitial lung diseases) and multiple diseases is described, focusing on the basic principles of the algorithm, the data used in the study, the evaluation measures, and the results. Finally, the paper summarizes the CAD system in chest radiography based on artificial intelligence and discusses the existing problems and trends.

Genetic risk between the CACNA1I gene and schizophrenia in Chinese Uygur population.

BACKGROUND: Schizophrenia (SCZ) is a common mental disorder with high heritability, and genetic factors play a major role in the pathogenesis. Recent researches indicated that the CACNA1I involved in calcium channels probably affect the potential pathogenesis of SCZ. RESULTS: In this study, we attempted to investigate whether the CACNA1I gene contributes the risk to SCZ in the Uighur Chinese population, and performed a case-control study involving 985 patient samples and 1218 normal controls to analyze nine SNPs within the CACNA1I gene. Among these sites, six SNPs were significantly associated with SCZ in the allele distribution: rs132575 (adjusted Pallele  = 0.039, OR = 1.159), rs713860 (adjusted Pallele  = 0.039, OR = 0.792), rs738168 (adjusted Pallele  = 0.039, OR = 0.785), rs136805 (adjusted Pallele  = 0.014, OR = 1.212), rs5757760 (adjusted Pallele  = 0.042, OR = 0.873) and rs5750871 (adjusted Pallele  = 0.039, OR = 0.859). In addition, two SNPs turned to be risk factors for SCZ not only in the allele distribution, but also in the genotype distribution: rs132575 (adjusted Pgenotype  = 0.037) and rs136805 (adjusted Pgenotype  = 0.037). CONCLUSIONS: Overall, the present study provided evidence that significant association exists between the CACNA1I gene and SCZ in the Uighur Chinese population, subsequent validation of functional analysis and genetic association studies are needed to further extend this study.

Genome-wide two-locus interaction analysis identifies multiple epistatic SNP pairs that confer risk of prostate cancer: A cross-population study.

Prostate cancer is one of the most common carcinomas among adult males. Recently, genome-wide association studies (GWAS) have identified several susceptibility genes of prostate cancer. However, these single locus results can only explain a small proportion of the genetic etiology. In order to understand how multiple genetic variants may contribute to the penetrance of prostate cancer, we conducted a genome-wide SNP-SNP interaction study in four populations, involving 5,269 cases and 5,289 controls. We exhaustively evaluated all pairs of SNP-SNP interactions for 661,658 SNPs that were consensus in all four groups, and then performed a meta-analysis to combine the results. We found multiple variants within region 7p21.3 and 18p11.22 significantly interacted with each other and reached genome-wide significance levels. The most significant epistasis was between rs1105255 (intergenic, near RBSG3) and rs651431 (intergenic, near VAPA) (p = 1.4 × 10-14 ). Notably, VAPA was identified to be the protein-coding transcripts as PTEN competing endogenous RNA in prostate cancer. And PTEN is a critical tumor suppressor gene frequently altered in cancers. In addition, 7p21.3 involves several pseudogenes, whose parental genes are cancer-related. Recently, growing evidence strongly suggests they are of multifaceted involvements in the pathogenesis of cancer. Multiple regulatory elements were found within 7p21.3 and 18p11.22, indicating the variants might regulate the nearby genes and confer risk of disease. Additionally, we also found several other significant epistasis, most of which were near or in cancer-related genes. Drug target enrichment analysis suggested genes in top epistasis significantly overlapped with target genes of FDA-approved drugs for treatment of prostate cancer.