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Kui Zhang

Publications and source records attributed to Kui Zhang.

At least 19 recordsLinked to original sources
PubMed2026

A genome-wide cross-trait analysis characterizes the shared genetic architecture between rheumatoid arthritis and psychiatric disorders.

OBJECTIVES: Patients with RA have a 2- to 3-fold elevated risk of psychiatric disorders, suggesting an underlying genetic link between these phenotypes. However, the shared genetic architectures and pathological mechanisms driving RA-psychiatric disorder comorbidity remain to be fully elucidated. Herein, we performed cross-trait analysis to investigate the shared genetic architecture between RA and psychiatric disorders. METHODS: Leveraging European-ancestry genome-wide association studies (GWASs) datasets of RA (n = 1 026 690) and 10 major psychiatric disorders (n = 14 307-1 222 882), we performed cross-trait pleiotropic analysis to identify the shared pleiotropic loci and genes between RA and psychiatric disorders, followed by functional annotation and Mendelian randomization analysis to explore the pathological mechanisms underlying RA-psychiatric disorder comorbidity. RESULTS: Our analysis revealed significant positive genetic correlations between RA and seven psychiatric disorders, such as major depressive disorder. From these correlations, we identified 61 pleiotropic loci jointly influencing RA and psychiatric disorder risk, along with 208 pleiotropic genes predominantly involved in immune and inflammatory response biological processes. Druggable target exploration identified 21 drug-gene interactions involving pleiotropic genes, with two genes (RHOA and TRAF3) classified in the clinically actionable category, representing potential therapeutic targets for both RA and psychiatric disorders. Mendelian randomization further demonstrated a bidirectional causal relationship between RA and schizophrenia, while supporting the causal roles of attention-deficit/hyperactivity disorder, major depressive disorder and post-traumatic stress disorder in increasing RA risk. CONCLUSION: Our findings elucidate the shared genetic architecture between RA and psychiatric disorders, providing novel insights into the pathological mechanisms underlying their comorbidity and laying the groundwork for improved comorbidity management.

Arthritis, Rheumatoid↗
PubMed2006

Increased expression of thymidylate synthetase (TS), ubiquitin specific protease 10 (USP10) and survivin is associated with poor survival in glioblastoma multiforme (GBM).

BACKGROUND: The limited success of empirically designed treatment paradigms for patients diagnosed with glioblastoma multiforme (GBM) emphasizes the need for rationally designed treatment strategies based on the molecular profile of tumor samples and their correlation to clinical parameters. METHODS: In the current study, we utilize a novel real-time quantitative low density array (RTQ-LDA) to identify differentially expressed genes in de novo GBM tissues obtained from patients with distinctly different clinical outcomes. Total RNA was isolated from a cohort of 21 GBM specimens obtained from patients with either good (long-term survival (LTS) >36 months post surgery, n = 8) or poor (died of the disease (DOD) <24 months post surgery, n = 13) prognosis. Non-neoplastic brain tissue (n = 5) was obtained from patients who underwent surgery for refractory epilepsy. Demographic data was assessed for correlation with survival using Cox proportional hazards models. Sufficient RNA was available to use RTQ-LDA to quantify the expression of 93 independent genes in 5 LTS, 4 DOD, and 5 non-neoplastic brain samples. The eight differentially expressed genes identified by RTQ-LDA in LTS versus DOD (P <or= 0.050) were subsequently quantified in all 21 GBM samples by real-time quantitative PCR (RTQ). RESULTS: A correlation between younger patients and good prognosis was demonstrated (P <or= 0.05). The combination of RTQ-LDA and RTQ identified thymidylate synthetase (TS), ubiquitin specific protease 10 (USP10), and survivin as significantly over-expressed (P <or= 0.050) in DOD compared to LTS patients. Ribonucleotide reductase subunit M2 (RRM2) was identified as tumor-specific, but not associated with survival. CONCLUSIONS: Taken collectively, TS, USP10, survivin and RRM2 may be useful as prognostic indicators and/or in the development of rationally designed treatment protocols.

Adolescent↗
PubMed2006

An empirical Bayes method for updating inferences in analysis of quantitative trait loci using information from related genome scans.

Individual genome scans for quantitative trait loci (QTL) mapping often suffer from low statistical power and imprecise estimates of QTL location and effect. This lack of precision yields large confidence intervals for QTL location, which are problematic for subsequent fine mapping and positional cloning. In prioritizing areas for follow-up after an initial genome scan and in evaluating the credibility of apparent linkage signals, investigators typically examine the results of other genome scans of the same phenotype and informally update their beliefs about which linkage signals in their scan most merit confidence and follow-up via a subjective-intuitive integration approach. A method that acknowledges the wisdom of this general paradigm but formally borrows information from other scans to increase confidence in objectivity would be a benefit. We developed an empirical Bayes analytic method to integrate information from multiple genome scans. The linkage statistic obtained from a single genome scan study is updated by incorporating statistics from other genome scans as prior information. This technique does not require that all studies have an identical marker map or a common estimated QTL effect. The updated linkage statistic can then be used for the estimation of QTL location and effect. We evaluate the performance of our method by using extensive simulations based on actual marker spacing and allele frequencies from available data. Results indicate that the empirical Bayes method can account for between-study heterogeneity, estimate the QTL location and effect more precisely, and provide narrower confidence intervals than results from any single individual study. We also compared the empirical Bayes method with a method originally developed for meta-analysis (a closely related but distinct purpose). In the face of marked heterogeneity among studies, the empirical Bayes method outperforms the comparator.

Chromosome Mapping↗
PubMed2006

Two-dimensional transcriptome profiling: identification of messenger RNA isoform signatures in prostate cancer from archived paraffin-embedded cancer specimens.

The expression of specific mRNA isoforms may uniquely reflect the biological state of a cell because it reflects the integrated outcome of both transcriptional and posttranscriptional regulation. In this study, we constructed a splicing array to examine approximately 1,500 mRNA isoforms from a panel of genes previously implicated in prostate cancer and identified a large number of cell type-specific mRNA isoforms. We also developed a novel "two-dimensional" profiling strategy to simultaneously quantify changes in splicing and transcript abundance; the results revealed extensive covariation between transcription and splicing in prostate cancer cells. Taking advantage of the ability of our technology to analyze RNA from formalin-fixed, paraffin-embedded tissues, we derived a specific set of mRNA isoform biomarkers for prostate cancer using independent panels of tissue samples for feature selection and cross-analysis. A number of cancer-specific splicing switch events were further validated by laser capture microdissection. Quantitative changes in transcription/RNA stability and qualitative differences in splicing ratio may thus be combined to characterize tumorigenic programs and signature mRNA isoforms may serve as unique biomarkers for tumor diagnosis and prognosis.

Aged↗
PubMed2006

A comparison of several methods for haplotype frequency estimation and haplotype reconstruction for tightly linked markers from general pedigrees.

Haplotype inference for tightly linked markers from general pedigrees remains a challenging problem. Only a few methods are available to efficiently and accurately estimate haplotype frequencies and reconstruct haplotypes for a large number of tightly linked markers from general pedigrees in the presence of missing data, and their performance has not been carefully and extensively evaluated. In this paper, we compare four published methods for haplotype reconstruction and frequency estimation for tightly linked markers from general pedigrees, including HAPLORE, GENEHUNTER, PedPhase, and MERLIN. We review these methods and discuss the differences between them in terms of the models and computational strategies employed. We assess their performance based on simulations using pedigrees and haplotypes on tightly linked single nucleotide polymorphisms from real studies. We investigate the effect of several factors, including the missing rate, the departure from Hardy-Weinberg Equilibrium, and the sample size, on the accuracy for haplotype inference. We also compare these methods with a widely used method for haplotype inference from unrelated individuals, PHASE, by treating individuals within a pedigree as unrelated samples. This comparison allows us to investigate the relative efficiency in haplotype inference using pedigree data. Our results indicate that incorporation of pedigree information can improve the precision for haplotype frequency estimation and the accuracy for haplotype reconstruction. Among four haplotyping methods capable of analyzing general pedigrees, HAPLORE and MERLIN have comparable performance and outperform the other two methods in almost all situations.

Computer Simulation↗
PubMed2006

[Observation the electroporation of blood cells in vitro by scanning electron microscope].

OBJECTIVE: To observe changes on cell membrane in blood cells after they were been electrified. METHODS: Blood were electrified for 5, 10, 20, 30 s, 1 min respectively, and Scanning electron microscope was used to detect the changes on their cell membranes. RESULTS: Pores were detected both on electrified erythrocytes and leukocytes with round or ellipse shapes. The erythrocytes often have one or more pores while the leukocytes often have more pores looked like cribble. The rates of perforated cells were increased with the prolonging time of electrification, 5 s with 6% and 1 min increased to 40%. CONCLUSIONS: Alternating current can cause the cell perforating, and the rates of perforated cell were increased with the prolonging time of electrification.

Adult↗
PubMed2006

[A study on the expression of HSP70 in endothelial cells pretreated with ethanol and fluid shear stress].

OBJECTIVE: To detect whether ethanol can affect the expression of HSP70 in endothelial cells under fluid shear stress. METHODS: Ethanol at different concentrations was added to the culture medium of endothelial cells, EA. Hy926, which was treated statically or under 1Pa fluid shear stress. After the incubation of 1 h, 2 h, 4 h and 6 h, the expression of HSP70 was detected by immunohistochemical method(SP). RESULTS: In the control group, the expression of HSP70 was negative under static state, while it was positive under 1Pa fluid shear stress lasting 4 h even without ethanol. No statistic difference was found between the 50 mg/dL ethanol group and the control group with the same treatment time of fluid shear stress. HSP70 expression was found under static state with 150 mg/dL ethanol after 4 h or 300 mg/dL ethanol after 2 h respectively. The expression increased greatly under 1Pa fluid shear stress in the same ethanol concentrations. CONCLUSION: Medium to high ethanol concentration in coordination with fluid shear stress can strongly stimulates the expression of HSP70 by a kinetic mechanism of time-dependent.

Cells, Cultured↗
PubMed2005

NOx formation in the plasma treatment of halomethanes.

A nonthermal, atmospheric pressure plasma, made-up of a BaTiO3 packed-bed reactor, has been used to study the formation of NOx and N2O during the plasma destruction of a range of volatile organic compounds (VOCs) and hazardous air pollutants, including chlorinated, brominated, fluorinated, and iodinated methane species, in a carrier gas of air. Using the plasma destruction of pure air as a baseline, it is found that the amount of NOx formed is unaffected by the addition of a few hundred parts per million of a simple hydrocarbon (e.g. methane). In the case of the fluorinated, chlorinated, and brominated methanes, we find enhanced production of NOx and a marked increase in the ratio of NO2 to NO formed, from approximately 1.1 in air and methane to approximately 2.3 in halogenated species. However, iodinated additives (specifically methyl iodide and diiodomethane) have remarkably different results compared to the other halogenated additives; they show enhanced increases in the NO2 to NO ratio ( approximately 6-13) and reduced NOx production. The enhanced conversion of NO to NO2 is attributed to reactions involving halogen oxides, e.g. ClO and IO.

Journal Article↗
PubMed2005

Patterns of antihypertensive therapy in new users of angiotensin II-receptor blockers.

PURPOSE: The patterns of angiotensin II-receptor blocker (ARB) therapy in patients with and without a history of antihypertensive use were studied. METHODS: Data for this retrospective cohort study were obtained from Caremark's data warehouse. Patients were included in the analysis if they filled prescriptions for ARBs only, did not receive ARB therapy within the 6 months before the filling of the first ARB prescription (index date), were continuously eligible for benefits for 6 months before the index date, were eligible for prescription benefits for the 12 months following the index date, and were age 20-80 years. RESULTS: Of the 174,573 patients sampled, 53.4% were new to all antihypertensive therapies. Of the patients receiving an ARB, 67.9% received another antihypertensive during the evaluation period. Over 40% of patients new to all antihypertensive therapies had no other antihypertensive added to their ARB regimen. Of the patients with a history of antihypertensive use, 22.3% discontinued all antihypertensives before starting therapy with an ARB. Patients starting therapy with losartan and valsartan were less likely to be treated with mono-therapy and more likely to be treated with ARB-diuretic therapy than were patients starting therapy with telmisartan, irbesartan, or candesartan. CONCLUSION: Patients who started antihypertensive therapy with ARBs tended to be new to antihypertensive therapy and, in a plurality of cases, continued to receive therapy with ARBs only. More than a fifth of patients who received antihypertensive therapy in the recent past were switched from that therapy to treatment with ARBs only. Treatment patterns differed by initial ARB used and the demographic profile of the patient.

Adult↗
PubMed2005

Selecting additional tag SNPs for tolerating missing data in genotyping.

BACKGROUND: Recent studies have shown that the patterns of linkage disequilibrium observed in human populations have a block-like structure, and a small subset of SNPs (called tag SNPs) is sufficient to distinguish each pair of haplotype patterns in the block. In reality, some tag SNPs may be missing, and we may fail to distinguish two distinct haplotypes due to the ambiguity caused by missing data. RESULTS: We show there exists a subset of SNPs (referred to as robust tag SNPs) which can still distinguish all distinct haplotypes even when some SNPs are missing. The problem of finding minimum robust tag SNPs is shown to be NP-hard. To find robust tag SNPs efficiently, we propose two greedy algorithms and one linear programming relaxation algorithm. The experimental results indicate that (1) the solutions found by these algorithms are quite close to the optimal solution; (2) the genotyping cost saved by using tag SNPs can be as high as 80%; and (3) genotyping additional tag SNPs for tolerating missing data is still cost-effective. CONCLUSION: Genotyping robust tag SNPs is more practical than just genotyping the minimum tag SNPs if we can not avoid the occurrence of missing data. Our theoretical analysis and experimental results show that the performance of our algorithms is not only efficient but the solution found is also close to the optimal solution.

Algorithms↗
PubMed2005

MAASE: an alternative splicing database designed for supporting splicing microarray applications.

Alternative splicing is a prominent feature of higher eukaryotes. Understanding of the function of mRNA isoforms and the regulation of alternative splicing is a major challenge in the post-genomic era. The development of mRNA isoform sensitive microarrays, which requires precise splice-junction sequence information, is a promising approach. Despite the availability of a large number of mRNAs and ESTs in various databases and the efforts made to align transcript sequences to genomic sequences, existing alternative splicing databases do not offer adequate information in an appropriate format to aid in splicing array design. Here we describe our effort in constructing the Manually Annotated Alternatively Spliced Events (MAASE) database system, which is specifically designed to support splicing microarray applications. MAASE comprises two components: (1) a manual/computational annotation tool for the efficient extraction of critical sequence and functional information for alternative splicing events and (2) a user-friendly database of annotated events that allows convenient export of information to aid in microarray design and data analysis. We provide a detailed introduction and a step-by-step user guide to the MAASE database system to facilitate future large-scale annotation efforts, integration with other alternative splicing databases, and splicing array fabrication.

Alternative Splicing↗
PubMed2005

Assessing the power of tag SNPs in the mapping of quantitative trait loci (QTL) with extremal and random samples.

BACKGROUND: Recent studies have indicated that the human genome could be divided into regions with low haplotype diversity interspersed with regions of high haplotype diversity. In regions of low haplotype diversity, a small fraction of SNPs (tag SNPs) are sufficient to account for most of the haplotype diversity of the human genome. These tag SNPs can be extremely useful for testing the association of a marker locus with a qualitative or quantitative trait locus in that it may not be necessary to genotype all the SNPs. When tag SNPs are used to reduce the genotyping effort in association studies, it is important to know how much power is lost. It is also important to know how much power is gained when tag SNPs instead of the same number of randomly chosen SNPs are used. RESULTS: We design a simulation study to tackle these problems for a variety of quantitative association tests using either case-parent samples or unrelated population samples. First, the samples are generated based on the quantitative trait model with the assumption of either an extremal sampling scheme or a random sampling scheme. Second, a small number of samples are selected to determine the haplotype blocks and the tag SNPs. Third, the statistical power of the tests is evaluated using four kinds of data: (1) all the SNPs and the corresponding haplotypes, (2) the tag SNPs and the corresponding haplotypes, (3) the same number of evenly spaced SNPs with minor allele frequency greater than a threshold and the corresponding haplotypes, (4) the same number of randomly chosen SNPs and their corresponding haplotypes. CONCLUSION: Our results suggest that in most situations genotyping efforts can be significantly reduced by using tag SNPs for mapping the QTL in association studies without much loss of power, which is consistent with previous studies on association mapping of qualitative traits. For all situations considered, two-locus haplotype analysis using tag SNPs are more powerful than those using the same number of randomly selected SNPs, but the degree of such power differences depends upon the sampling scheme and the population history.

Chromosome Mapping↗
PubMed2005

Empirical bayes method for incorporating data from multiple genome scans.

Individual genome scans tend to have low power and can produce markedly biased estimates of QTL effects. Further, the confidence interval for their location is often prohibitively large for subsequent fine mapping and positional cloning. Given that a large number of genome scans have been conducted, not to mention the large number of variables and subsets tested, it is difficult to confidently rule out type 1 error as an explanation for significant effects even when there is apparent replication in a separate data set. We adapted Empirical Bayes (EB) methods [1] to analyze data from multiple genome scans simultaneously and alleviate each of these problems while still allowing for different QTL population effects across studies. We investigated the effects of using the EB method to include data from background studies to update the results of a single study of interest via simulation and demonstrated that it has a stable confidence level over a wide range of parameters defining the background studies and increased the power to detect linkage, even when some of the background studies were null or had QTL effect at other markers. This EB method for incorporating data from multiple studies into genome scan analyses seems promising.

Alzheimer Disease↗
PubMed2005

A family-based association study of the MOG gene with schizophrenia in the Chinese population.

Recently the expression of human myelin/oligodendrocyte glycoprotein (MOG) has been found to be significantly downregulated in the brain tissue of subjects with schizophrenia, suggesting that the MOG gene resides within a high-susceptibility locus for schizophrenia. In order to test this prediction, we analyzed three microsatellites from MOG in the Han Chinese population using a sample of 532 trios. Analysis of allele, genotype and haplotype frequencies showed weak positive association between the markers and the disease (p=0.01982). Our results would indicate that the MOG gene may play a significant role in schizophrenia in the Han Chinese. However, further study is required using other methods and involving other populations.

Asian People↗
PubMed2004

HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms.

UNLABELLED: Recent studies have revealed that linkage disequilibrium (LD) patterns vary across the human genome with some regions of high LD interspersed with regions of low LD. Such LD patterns make it possible to select a set of single nucleotide polymorphism (SNPs; tag SNPs) for genome-wide association studies. We have developed a suite of computer programs to analyze the block-like LD patterns and to select the corresponding tag SNPs. Compared to other programs for haplotype block partitioning and tag SNP selection, our program has several notable features. First, the dynamic programming algorithms implemented are guaranteed to find the block partition with minimum number of tag SNPs for the given criteria of blocks and tag SNPs. Second, both haplotype data and genotype data from unrelated individuals and/or from general pedigrees can be analyzed. Third, several existing measures/criteria for haplotype block partitioning and tag SNP selection have been implemented in the program. Finally, the programs provide flexibility to include specific SNPs (e.g. non-synonymous SNPs) as tag SNPs. AVAILABILITY: The HapBlock program and its supplemental documents can be downloaded from the website http://www.cmb.usc.edu/~msms/HapBlock.

Algorithms↗
PubMed2004

HAPLORE: a program for haplotype reconstruction in general pedigrees without recombination.

MOTIVATION: Haplotype reconstruction is an essential step in genetic linkage and association studies. Although many methods have been developed to estimate haplotype frequencies and reconstruct haplotypes for a sample of unrelated individuals, haplotype reconstruction in large pedigrees with a large number of genetic markers remains a challenging problem. METHODS: We have developed an efficient computer program, HAPLORE (HAPLOtype REconstruction), to identify all haplotype sets that are compatible with the observed genotypes in a pedigree for tightly linked genetic markers. HAPLORE consists of three steps that can serve different needs in applications. In the first step, a set of logic rules is used to reduce the number of compatible haplotypes of each individual in the pedigree as much as possible. After this step, the haplotypes of all individuals in the pedigree can be completely or partially determined. These logic rules are applicable to completely linked markers and they can be used to impute missing data and check genotyping errors. In the second step, a haplotype-elimination algorithm similar to the genotype-elimination algorithms used in linkage analysis is applied to delete incompatible haplotypes derived from the first step. All superfluous haplotypes of the pedigree members will be excluded after this step. In the third step, the expectation-maximization (EM) algorithm combined with the partition and ligation technique is used to estimate haplotype frequencies based on the inferred haplotype configurations through the first two steps. Only compatible haplotype configurations with haplotypes having frequencies greater than a threshold are retained. RESULTS: We test the effectiveness and the efficiency of HAPLORE using both simulated and real datasets. Our results show that, the rule-based algorithm is very efficient for completely genotyped pedigree. In this case, almost all of the families have one unique haplotype configuration. In the presence of missing data, the number of compatible haplotypes can be substantially reduced by HAPLORE, and the program will provide all possible haplotype configurations of a pedigree under different circumstances, if such multiple configurations exist. These inferred haplotype configurations, as well as the haplotype frequencies estimated by the EM algorithm, can be used in genetic linkage and association studies. AVAILABILITY: The program can be downloaded from http://bioinformatics.med.yale.edu.

Algorithms↗
PubMed2004

Haplotype block partitioning and tag SNP selection using genotype data and their applications to association studies.

Recent studies have revealed that linkage disequilibrium (LD) patterns vary across the human genome with some regions of high LD interspersed by regions of low LD. A small fraction of SNPs (tag SNPs) is sufficient to capture most of the haplotype structure of the human genome. In this paper, we develop a method to partition haplotypes into blocks and to identify tag SNPs based on genotype data by combining a dynamic programming algorithm for haplotype block partitioning and tag SNP selection based on haplotype data with a variation of the expectation maximization (EM) algorithm for haplotype inference. We assess the effects of using either haplotype or genotype data in haplotype block identification and tag SNP selection as a function of several factors, including sample size, density or number of SNPs studied, allele frequencies, fraction of missing data, and genotyping error rate, using extensive simulations. We find that a modest number of haplotype or genotype samples will result in consistent block partitions and tag SNP selection. The power of association studies based on tag SNPs using genotype data is similar to that using haplotype data.

Algorithms↗