Biomedical subjects

Jie Qin

Publications and source records attributed to Jie Qin.

7 recordsLinked to original sources

PubMed2004

Using the gene ontology for microarray data mining: a comparison of methods and application to age effects in human prefrontal cortex.

One of the challenges in the analysis of gene expression data is placing the results in the context of other data available about genes and their relationships to each other. Here, we approach this problem in the study of gene expression changes associated with age in two areas of the human prefrontal cortex, comparing two computational methods. The first method, "overrepresentation analysis" (ORA), is based on statistically evaluating the fraction of genes in a particular gene ontology class found among the set of genes showing age-related changes in expression. The second method, "functional class scoring" (FCS), examines the statistical distribution of individual gene scores among all genes in the gene ontology class and does not involve an initial gene selection step. We find that FCS yields more consistent results than ORA, and the results of ORA depended strongly on the gene selection threshold. Our findings highlight the utility of functional class scoring for the analysis of complex expression data sets and emphasize the advantage of considering all available genomic information rather than sets of genes that pass a predetermined "threshold of significance."

Adolescent↗

PubMed2004

Coexpression analysis of human genes across many microarray data sets.

We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function.

Cluster Analysis↗

PubMed2004

Gene expression signatures in chronic and aggressive periodontitis: a pilot study.

This pilot study examined gene expression signatures in pathological gingival tissues of subjects with chronic or aggressive periodontitis, and explored whether new subclasses of periodontitis can be identified based on gene expression profiles. A total of 14 patients, seven with chronic and seven with aggressive periodontitis, were examined with respect to clinical periodontal status, composition of subgingival bacterial plaque assessed by checkerboard hybridizations, and levels of serum IgG antibodies to periodontal bacteria assayed by checkerboard immunoblotting. In addition, at least two pathological pockets/patient were biopsied, processed for RNA extraction, amplification and labeling, and used to study gene expression using Affymetrix U-133 A arrays. Based on a total of 35 microarrays, no significantly different gene expression profiles appeared to emerge between chronic and aggressive periodontitis. However, a de novo grouping of the 14 subjects into two fairly robust clusters was possible based on similarities in gene expression. These two groups had similar clinical periodontal status and subgingival bacterial profiles, but differed significantly with respect to serum IgG levels against the important periodontal pathogens Porphyromonas gingivalis, Tannerella forsythensis and Campylobacter rectus. These early data point to the usefulness of gene expression profiling techniques in the identification of subclasses of periodontitis with common pathobiology.

Acute Disease↗

PubMed2004

Amino acids protects against renal ischemia-reperfusion injury and attenuates renal endothelin-1 disorder in rats.

OBJECTIVE: To investigate nephroprotective effects of a mixture of 8 L-amino acids on renal ischemia-reperfusion injury and its effects on renal endothelin-1 (ET-1). METHODS: The mixture of 8 L-amino acids includes glycine, alanine, threonine, serine, valine, leucine, isoleucine and proline. Acute ischemic renal injury was induced by clamping renal pedicle for 45 minutes in rats. Sixty male Sprague-Dawley rats were randomly divided into 3 groups: a sham-operated group (Group A, n=8), a control group (Group B, n=26) and an amino acid-treated group (Group C, n=26). Amino acids were infused at a rate of 1 ml x 100g(-1) x h(-1) I hour before ischemia and during 3 hours of the whole reperfusion. The serum creatinine values, BUN levels, creatinine clearance, urine sodium and potassium excretion, urine lactate dehydrogenase (LDH), the rate of urine flow and histological examination were measured. Renal ET-1 levels were assayed with radioimmunological assay (RIA) RESULTS: The creatinine clearance was 471.0 microl/min+/-121.5 microl/min in Group C and 227.0 microl/min+/-27.0 microl/min in Group B 3 hours after reperfusion, P<0.01). The urine flow rate was 63.6 microl/min+/-15.2 microl/min in Group C and 24.3 microl/min+/-7.7 microl/minin Group B, P<0.01) 1.5 hours after reperfusion. The serum creatinine was 85.0 microl/min+/-7.7 micromol/L and BUN concentration 11.4 mmol/L+/-3.9 mmol/L in Group C and 112.7 micromol/L+/-19.5 micromol/L and 20.7 mmol/L+/-6.6 mmol/L respectively in Group B after 24 hours of reperfusion (P<0.05). The mean histological score by standards of Paller in kidneys was 108.7+/-15.7 in Group C, and 168.8+/-14.8in Group B (P<0.01). The renal ET-1 levels 15 minute and 3 hours after reperfusion were 7.2 pg/mg+/-0.8 pg/mg and 9.6 pg/ml+/-1.0 pg/ml in Group C, and 10.1 pg/ml+/-2.8 pg/ml and 13.0 pg/ml+/-2.7pg/ml in Group B (P<0.01). CONCLUSIONS: The mixture of 8 L-amino acids can provide remarkable protection against renal ischemia-reperfusion injury in rats. This may associate with attenuation of renal ET-1 disorder.

Amino Acids↗

PubMed2003

Kernel hierarchical gene clustering from microarray expression data.

MOTIVATION: Unsupervised analysis of microarray gene expression data attempts to find biologically significant patterns within a given collection of expression measurements. For example, hierarchical clustering can be applied to expression profiles of genes across multiple experiments, identifying groups of genes that share similar expression profiles. Previous work using the support vector machine supervised learning algorithm with microarray data suggests that higher-order features, such as pairwise and tertiary correlations across multiple experiments, may provide significant benefit in learning to recognize classes of co-expressed genes. RESULTS: We describe a generalization of the hierarchical clustering algorithm that efficiently incorporates these higher-order features by using a kernel function to map the data into a high-dimensional feature space. We then evaluate the utility of the kernel hierarchical clustering algorithm using both internal and external validation. The experiments demonstrate that the kernel representation itself is insufficient to provide improved clustering performance. We conclude that mapping gene expression data into a high-dimensional feature space is only a good idea when combined with a learning algorithm, such as the support vector machine that does not suffer from the curse of dimensionality. AVAILABILITY: Supplementary data at www.cs.columbia.edu/compbio/hiclust. Software source code available by request.

Algorithms↗

PubMed2003

Effects of the combination of an angiotensin II antagonist with an HMG-CoA reductase inhibitor in experimental diabetes.

BACKGROUND: Angiotensin II type 1 (AT1) receptor antagonists and 3-hydroxy-3-methylglutaryl conenzyme A (HMG-CoA) reductase inhibitors have been shown to confer renoprotection. However, the renal effects of the combination of an AT1 receptor antagonist and an HMG-CoA reductase inhibitor in experimental diabetes are unknown. METHODS: Diabetes was induced by injection of streptozotocin in Wistar rats. Diabetic rats were randomly treated with losartan, an AT1 receptor antagonist, or simvastatin, an HMG-CoA reductase inhibitor, as well as the combination of both for eight weeks. Albumin excretion rate (AER) and plasma concentrations of blood urea nitrogen (BUN), creatinine, cholesterol, and triglycerides were measured. Renal injury was evaluated. Immunohistochemical staining of transforming growth factor beta1 (TGF beta 1) and vascular endothelial growth factor (VEGF) were performed. RESULTS: Increased AER in diabetic rats was attenuated by treatment with either losartan or simvastatin and further reduced by the combination of the two. Elevated plasma concentrations of BUN and creatinine were only reduced by the combination. There was no significant difference in plasma concentrations of cholesterol and triglycerides between control and diabetic rats and neither was influenced by losartan or simvastatin. Kidney pathologic injury was attenuated by losartan, but not simvastatin, compared to diabetic animals. Overexpression of TGF beta 1 and VEGF was observed in the glomeruli of diabetic rats and was attenuated by losartan, simvastatin, or the combination of both to a similar level. CONCLUSION: The combination of an angiotensin antagonist with an HMG-CoA reductase inhibitor confers superiority over monotherapies on renal function, as assessed by prevention of albuminuria and rise in plasma BUN and creatinine. However, no advantage of combination therapy was seen with respect to attenuating renal structural injury and renal expression of TGF beta and VEGF in experimental diabetes.

Albuminuria↗

PubMed2003

[Effects of testosterone on GDNF mRNA expression in rat ventral prostate].

OBJECTIVE: To investigate the effects of testosterone on GDNF(glial cell-derived neurotrophic factor) expression in rat ventral prostate. METHODS: Twenty-four male Sprague-Dawley rats were randomized into 3 groups, group A(n = 8, sham operation, uncastrated controls), group B (n = 8, castrated), group C (n = 8, castrated and given testosterone undecanoate (TU) 50 mg/kg by intramuscular injection). Ventral prostate tissues removed from adult male rats at 3 days after operation were analyzed for the expression of GDNF mRNA by semiquantitative RT-PCR assay. RESULTS: The ventral prostate tissues shrank remarkably in the castrated rats, and prostatic hyperplasia accurred in those that had received both castration and testosterone undecanoate. GDNF mRNA expressed in the normal rats ventral prostates, and the prostatic expression of GDNF mRNA decreased significantly at 3 days after castration(P < 0.05), but increased significantly (P < 0.05) in those that had received both castration and TU. CONCLUSIONS: The gene expression of glial cell-derived neurotrophic factor in the ventral prostate of rats is dependent on testosterone, and GDNF is involved in the growth of rat ventral prostate.

Animals↗