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Elevated alanine aminotransferase predicts new-onset type 2 diabetes independently of classical risk factors, metabolic syndrome, and C-reactive protein in the west of Scotland coronary prevention study.

We examined the association of serum alanine aminotransferase (ALT) with features of the metabolic syndrome and whether it predicted incident diabetes independently of routinely measured factors in 5,974 men in the West of Scotland Coronary Prevention Study. A total of 139 men developed new diabetes over 4.9 years of follow-up. ALT, but not aspartate aminotransferase, levels increased progressively with the increasing number of metabolic syndrome abnormalities from (means +/- SD) 20.9 +/- 7.6 units/l in those with none to 28.1 +/- 10.1 units/l in those with four or more (P < 0.001). In a univariate analysis, men with ALT in the top quartile (ALT >/=29 units/l) had an elevated risk for diabetes (hazard ratio 3.38 [95% CI 1.99-5.73]) versus those in the bottom quartile (<17 units/l). ALT remained a predictor with adjustment for age, BMI, triglycerides, HDL cholesterol, systolic blood pressure, glucose, and alcohol intake (2.04 [1.16-3.58] for the fourth versus first quartile). In stepwise regression, incorporating ALT and C-reactive protein (CRP) together with metabolic syndrome criteria, elevated ALT (>/=29 units/l), and CRP (>/=3 mg/l) predicted incident diabetes, but low HDL cholesterol and hypertension did not. Thus, elevated ALT levels within the "normal" range predict incident diabetes. The simplicity of ALT measurement and its availability in routine clinical practice suggest that this enzyme activity could be included in future diabetes prediction algorithms.

Alanine Transaminase↗

A genotypic drug resistance interpretation algorithm that significantly predicts therapy response in HIV-1-infected patients.

OBJECTIVES: The development of a genotypic drug resistance interpretation algorithm, and the evaluation of its power to predict therapy outcome. DESIGN: A rule-based algorithm was established by an individual expert and was based on published and in-house results, independently from the data of the patients used in this evaluation. The predictive value of the algorithm for virological outcomes was retrospectively evaluated using the baseline genotype observed in patients on highly active antiretroviral therapy, failing virologically and subsequently starting a salvage regimen. METHODS: The independent association between the susceptibility score (calculated according to the algorithm) and the virological response at 3 months, was analysed using multivariable logistic regression and multiple linear regression models. RESULTS: In two clinical centres 240 patients were studied. At 3 months 35% had a viral load of <500 RNA copies/ml. Using multivariable logistic regression, the odds ratio of achieving a viral load <500 RNA copies/ml at month 3 per unit increase of susceptibility score was 2.0 (95% CI 1.3-3.1; P=0.002) after adjusting for baseline viral load, genotype-driven salvage therapy, number of new drugs in the regimen, use of a new drug class in the regimen, nelfinavir-containing salvage therapy and history of prior viral load <500 RNA copies/ml. Using multiple linear regression, the susceptibility score showed a significant linear correlation with the log viral load change (slope=-0.27 log10 RNA copies/ml; 95% CI -0.11 to -0.43; P=0.001) after adjusting for history of prior viral load <500 RNA copies/ml, number of new drugs in the salvage therapy, use of a new drug class in the salvage therapy and baseline viral load. CONCLUSIONS: This algorithm proved to be a significant independent predictor of therapy response at 3 months in this cohort of HIV-1-infected patients on salvage therapy. However, it should be subject to regular updates as is needed in this fast developing field.

Adolescent↗

Screening of transgenic proteins expressed in transgenic food crops for the presence of short amino acid sequences identical to potential, IgE - binding linear epitopes of allergens.

BACKGROUND: Transgenic proteins expressed by genetically modified food crops are evaluated for their potential allergenic properties prior to marketing, among others by identification of short identical amino acid sequences that occur both in the transgenic protein and allergenic proteins. A strategy is proposed, in which the positive outcomes of the sequence comparison with a minimal length of six amino acids are further screened for the presence of potential linear IgE-epitopes. This double track approach involves the use of literature data on IgE-epitopes and an antigenicity prediction algorithm. RESULTS: Thirty-three transgenic proteins have been screened for identities of at least six contiguous amino acids shared with allergenic proteins. Twenty-two transgenic proteins showed positive results of six- or seven-contiguous amino acids length. Only a limited number of identical stretches shared by transgenic proteins (papaya ringspot virus coat protein, acetolactate synthase GH50, and glyphosate oxidoreductase) and allergenic proteins could be identified as (part of) potential linear epitopes. CONCLUSION: Many transgenic proteins have identical stretches of six or seven amino acids in common with allergenic proteins. Most identical stretches are likely to be false positives. As shown in this study, identical stretches can be further screened for relevance by comparison with linear IgE-binding epitopes described in literature. In the absence of literature data on epitopes, antigenicity prediction by computer aids to select potential antibody binding sites that will need verification of IgE binding by sera binding tests. Finally, the positive outcomes of this approach warrant further clinical testing for potential allergenicity.

Algorithms↗

Effects of education and culture on the validity of the Geriatric Mental State and its AGECAT algorithm.

BACKGROUND: The Geriatric Mental State (GMS) is the most widely used psychiatric research assessment for older persons. Evidence for validity comes from the developed world. AIMS: To assess the validity of GMS/AGECAT organicity and depression diagnoses in 26 centres in India, China, Latin America and Africa. METHOD: We studied 2941 persons aged 60 years and over: 742 people with dementia and three groups free of dementia (697 with depression, 719 with high and 783 with low levels of education). Local clinicians diagnosed dementia (DSM-IV) and depression (Montgomery-Asberg Depression Rating Scale score >/=18). RESULTS: For dementia diagnosis GMS/AGECAT performed well in many centres but educational bias was evident. Specificity was poor in India and sensitivity sub-optimal in Latin America. A predictive algorithm excluding certain orientation items but including interviewer judgements improved upon the AGECAT algorithm. For depression, sensitivity was high. The EURO-D depression scale, derived from GMS items using European data, has a similar factor structure in Latin America, India and, to a lesser extent, China. CONCLUSIONS: Valid, comprehensive mental status assessment across cultures seems achievable in principle.

Aged↗

Prediction of plasma levels of aminoglycoside antibiotic in patients with severe illness by means of an artificial neural network simulator.

PURPOSE: The purpose of this work was to predict plasma peak and trough levels of an aminoglycoside antibiotic in patients with severe illness in an intensive care unit by a novel approach. Plasma levels were predicted based on the values of 15 physiological measurements using an artificial neural network (ANN) simulator. METHOD: A data set of 15 physiological measurements for 30 patients was used to develop the model. The ANN structure consisted of three layers: an input layer comprised of 15 processing elements, a hidden layer comprised of 10 processing elements with a sigmoid function as an activation function, and an output layer of two processing elements (peak and trough levels). The weight between neurons was trained according to the delta rule back-propagation of errors algorithm. Predicted values were obtained by "leave-one-out" experiments by both ANN and multiple linear regression analysis (MLRA). RESULTS: The correlation coefficients between observed and predicted values obtained by ANN prediction using standardized data sets were r=0.825 and r=0.854 for peak and trough levels, respectively. The correlation coefficients obtained by MLRA were r=0. 037 and r=0.276 for peak and trough levels, respectively. These results indicate that ANN shows better performance in prediction of aminoglycoside plasma levels from patients' physiological measurements than MLRA. CONCLUSIONS: Prediction of plasma levels of antibiotic in patients with severe illness by ANN was superior to the standard statistical method. Standardization of input data was found to be important for better prediction. ANN has some advantages over standard statistical methods, as it can recognize complex relationships in the data.

Aminoglycosides↗

Deriving non-homogeneous DNA Markov chain models by cluster analysis algorithm minimizing multiple alignment entropy.

Non-homogeneous Markov chain models can represent biologically important regions of DNA sequences. The statistical pattern that is described by these models is usually weak and was found primarily because of strong biological indications. The general method for extracting similar patterns is presented in the current paper. The algorithm incorporates cluster analysis, multiple alignment and entropy minimization. The method was first tested using the set of DNA sequences produced by Markov chain generators. It was shown that artificial gene sequences, which initially have been randomly set up along the multiple alignment panels, are aligned according to the hidden triplet phase. Then the method was applied to real protein-coding sequences and the resulting alignment clearly indicated the triplet phase and produced the parameters of the optimal 3-periodic non-homogeneous Markov chain model. These Markov models were already employed in the GeneMark gene prediction algorithm, which is used in genome sequencing projects. The algorithm can also handle the case in which the sequences to be aligned reveal different statistical patterns, such as Escherichia coli protein-coding sequences belonging to Class II and Class III. The algorithm accepts a random mix of sequences from different classes, and is able to separate them into two groups (clusters), align each cluster separately, and define a non-homogeneous Markov chain model for each sequence cluster.

Algorithms↗

A structure-based approach for prediction of protein binding sites in gene upstream regions.

The challenge of identifying DNA regulatory sequences based on sequence information only has been emphasized in view of the fast accumulation of new genes in the databases. While most predictive algorithms are based on multiple alignments of already known binding sites, here we examine the usefulness of a novel approach that is based on structural information of the protein-DNA complex. It has already been shown that specific recognition between a protein and its DNA target is achieved by stereo-chemical complementarity between the protein amino acids and the DNA bases. The proposed computational scheme uses crystallographic information to define the set of amino acid-base contacts between the proteins of a given DNA-binding protein family and their DNA targets. The compatibility of a given protein to bind to putative regulatory DNA sequences is then evaluated by knowledge-based parameters for amino acid-base interactions. By this procedure gene upstream regions may be screened for potential binding sites for regulatory proteins. Predictions are demonstrated for the E. coli cyclic AMP receptor protein (CRP) which recognizes the DNA via the helix-turn-helix motif, and for various Zif268-like proteins which belong to the Cys2His2 zinc finger family. The advantages and limitations of this approach are discussed.

Algorithms↗

pH and concentration of bilirubin in feeding tube aspirates as predictors of tube placement.

BACKGROUND: Currently available bedside methods for determining feeding tube placement often provide inconclusive results. Therefore, additional data are needed to assist nurses in making decisions regarding tube location. OBJECTIVES: To describe the usual concentration of bilirubin in aspirates from newly inserted feeding tubes and to determine the extent to which these measures can contribute to pH alone in correctly predicting feeding tube location. METHODS: Gastrointestinal samples for concurrent pH and bilirubin testing were obtained from adult, acutely ill patients with newly inserted small-bore feeding tubes (nasogastric, n = 209; nasointestinal, n = 228) within 5 minutes of radiographs taken to determine tube location. Respiratory samples were tested (tracheobronchial, n = 126; pleural, n = 24). pH was measured with a pH meter, and bilirubin content was assayed spectrophotometrically. Results from the pH and bilirubin tests were compared with tube location as determined by radiography. RESULTS: Mean pH levels in the lung (7.73) and intestine (7.35) were significantly higher than the mean pH level in the stomach (3.90; p < .001 for each comparison). Mean bilirubin levels in the lung (.08 mg/dl) and stomach (1.28 mg/dl) were significantly lower than the mean bilirubin level in the intestine (12.73 mg/dl; p < .001 for each). By visually inspecting distribution overlap and mean differences by tube site, results were dichotomized so that a combination of pH and bilirubin values could be used to develop a predictive algorithm. A pH of >5 and a bilirubin value of <5 mg/dl correctly identified all respiratory cases, whereas a pH >5 coupled with a bilirubin level of > or =5 mg/dl correctly identified three fourths of the intestinal cases. A pH of < or =5 coupled with a bilirubin value of <5 correctly identified more than two thirds of the gastric cases. CONCLUSIONS: Preliminary laboratory-based data indicate that appropriate use of the proposed algorithm could significantly reduce the number of x-rays needed to exclude respiratory placement and to distinguish between gastric and intestinal placement.

Adolescent↗

Support-vector-machine classification of linear functional motifs in proteins.

Our algorithm predicts short linear functional motifs in proteins using only sequence information. Statistical models for short linear functional motifs in proteins are built using the database of short sequence fragments taken from proteins in the current release of the Swiss-Prot database. Those segments are confirmed by experiments to have single-residue post-translational modification. The sensitivities of the classification for various types of short linear motifs are in the range of 70%. The query protein sequence is dissected into short overlapping fragments. All segments are represented as vectors. Each vector is then classified by a machine learning algorithm (Support Vector Machine) as potentially modifiable or not. The resulting list of plausible post-translational sites in the query protein is returned to the user. We also present a study of the human protein kinase C family as a biological application of our method.

Databases, Genetic↗

Prediction of autoantibody positivity and progression to type 1 diabetes: Diabetes Autoimmunity Study in the Young (DAISY).

Diabetes Autoimmunity Study in the Young (DAISY) has followed 1972 children for islet autoimmunity and diabetes: 837 first-degree relatives of persons with type 1 diabetes and 1135 general population newborns identified through human leukocyte antigen (HLA) screening. During follow-up of 4.06 yr (range, 0.17-9 yr), serial determination of autoantibodies to glutamic acid decarboxylase, protein tyrosine phosphatase IA2, and insulin has generated approximately 20,000 results. Among 162 children with at least one positive autoantibody, in 31% the test was false positive (autoantibodies were negative twice on blinded duplicate aliquots), in 31% it was transiently positive (confirmed on blinded duplicate aliquots but negative on follow-up), and in 36% it was persistently positive. Using proportional hazards modeling, the HLA-DR3/4 DQ8 genotype, another positive autoantibody at the first positive visit, and level of autoantibody were predictive of persistent positivity. Only HLA-DR3/4 DQ8 genotype was predictive of progression to diabetes in proportional hazards modeling. This prospective study reveals that cross-sectional determination of islet autoantibodies in a population with relatively low previous probability of autoimmunity identifies as "positive" a large number of individuals who are either false or transiently positive. Predictive value of autoantibodies increases with blinded duplicate and independent sample retesting and incorporation of the level of autoantibody in the predictive algorithm.

Autoantibodies↗

When should the doctor order a spine X-ray? Identifying vertebral fractures for osteoporosis care: results from the European Prospective Osteoporosis Study (EPOS).

UNLABELLED: Vertebral fractures are common but usually remain unrecognized in primary care. Data from 2908 women and 2653 men in the EPOS study were used to derive algorithms to indicate the need for a spine X-ray to identify a fracture using easily elicited determinants. At a sensitivity of 50% for identifying cases, the specificity was increased from 50% to 78% in women and from 50% to 72% in men compared with a random allocation of X-rays. Use of X-rays can be optimized by selecting patients at high risk using a short screening procedure. INTRODUCTION: Previous osteoporotic fracture is an independent risk factor for further fractures and an indication for treatment. Vertebral fractures are the most common osteoporotic fractures before age 75, accounting for 48% of all fractures in men and 39% in women over 50. They usually remain unrecognized, so many patients requiring treatment are denied it, doubling their risk of a further fracture. Our objective was to develop an efficient algorithm indicating the need for an X-ray. MATERIALS AND METHODS: Data from 2908 women and 2653 men >or=50 years of age in the European Prospective Osteoporosis Study (EPOS) were analyzed. Lateral thoracic and lumbar spine radiographs were taken at baseline and at an average of 3.8 years later. Prevalent fractures were qualitatively diagnosed by an experienced radiologist. Fracture risk was modeled as a function of age, statural height loss since age 25, gender, and fracture history including limb fractures in the last 3 years using negative binomial regression. Receiver operating characteristic (ROC) curves were used to summarize a model's predictive ability, and a prediction algorithm was devised to identify those most likely to have a fracture. RESULTS: In a multivariate model for women, the risk of prevalent vertebral fracture significantly increased with age (RR, 1.67 [95% CI, 1.46, 1.93] per decade), statural height loss (1.06, [1.03, 1.10] per centimeter decrease), self-reported history of spine fracture (7.52 [5.52, 10.23]), and history of other major fracture (1.83 [1.46, 2.28]). Higher body weight reduced risk (0.86 [0.79, 0.95] per 10-kg increase). In men, the respective RR estimates were as follows: age (1.32 [1.18, 1.49]); height loss (1.06 [1.04, 1.09]); self-reported spine fracture (5.05 [3.69, 6.90]); other major fracture (1.42 [1.12, 1.81]); and weight (0.86 [0.79, 0.94]). Using algorithms based on these easily elicited determinants, specificity was increased from 50% to 78% in women and from 50% to 72% in men at a sensitivity of 50% compared with a random allocation of X-rays. At a sensitivity of 75%, the specificity was 50% in women and 40% in men. Inclusion of hip BMD (femoral neck or trochanter), measured in 1360 women and 1046 men, significantly improved the area under the ROC curves by 4% in women (p < 0.002) but not in men (p > 0.350). Spine BMD, measured in 982 women and 847 men, produced a significant 5% AUC improvement in women (p = 0.007) but not in men (p = 0.554). CONCLUSION: A woman 65 years of age with one vertebral fracture has a one in four chance of another fracture over 5 years, which can be reduced to one in eight by treatment. Positive treatment decisions are often contingent on identifying a vertebral fracture. Selective use of lateral vertebral X-rays can be optimized using a 2-minute screening procedure administered by a nurse.

Age Factors↗

Comparison of intradermal dilutional testing with the Multi-Test II applicator in testing for mold allergy.

OBJECTIVES: To compare and correlate wheal size using the Multi-Test II applicator with the endpoint obtained by intradermal dilutional testing (IDT) for common mold allergens. To validate the safety and efficacy of modified quantitative testing (MQT) for determining immunotherapy starting doses. STUDY DESIGN AND SETTING: Prospective study of 86 subjects with Multi-Test II and IDT for 6 common mold antigens. RESULTS: There was 84% concordance between IDT results and the results expected from the MQT method. When IDT and MQT results differed, the MQT algorithm predicted a safer endpoint for starting immunotherapy in all but 2 cases. CONCLUSION: The correlation between Multi-Test II and IDT is not strong enough to infer IDT endpoint from Multi-Test II results for molds. MQT is nearly as effective as formal IDT in determining endpoint. SIGNIFICANCE: MQT appears to be a safe method for determining starting doses for immunotherapy with fungal allergens.

Adult↗

Better decisions through science: exercise testing scores.

Statistical tools can be used to create scores for assisting in the diagnosis of coronary artery disease and assessing prognosis. General practitioners and internists frequently function as gatekeepers, deciding which patients must be referred to the cardiologist. Therefore, they need to use the basic tools they have available (ie, history, physical examination and the exercise test) in an optimal fashion. Scores derived from multivariable statistical techniques considering clinical and exercise data have demonstrated superior discriminating power compared with diagnosis only using the ST segment response. In addition, by stratifying patients as to probability of disease and prognosis, they provide a more practical management strategy than a response of normal or abnormal. Although computers, as part of information management systems, can calculate complicated equations and derive these scores, physicians are reluctant to trust them. However, when represented as nomograms or simple additive discrete pieces of information, scores are more readily accepted. The scores have been compared with physician judgment and have been found to estimate the presence of coronary disease and prognosis as well as expert cardiologists and often better than nonspecialists. However, the discriminating power of specific variables from the medical history and exercise test remains unclear because of inadequate study design and differences in study populations. Should expired gases be substituted for estimated METs? Should ST/heart rate index be used instead of putting ST depression and heart rate separately into the models? Should right-sided chest leads and heart rate in recovery be considered? There is a need for further evaluation of these easily obtained variables to improve the accuracy of prediction algorithms, especially in women. The portability and reliability of scores must be ensured because access to specialized care must be safeguarded. Assessment of the clinical and exercise test data and application of the newer scores can empower the clinician to assure the cardiac patient access to appropriate and cost-effective cardiologic care.

Age Factors↗

Motif analysis of HLA class II molecules that determine the HPV associated risk of cervical carcinogenesis.

In previous studies, the HLA class II haplotype HLA DRB1*0401-DQB1*0301 was shown to correlate with susceptibility to HPV infection, CIN and cervical cancer while DRB1*0101-DQB1*0501 indicated protection. The present study was designed to identify naturally processed peptide sequences bound to the susceptibility and protective HLA DR-DQ molecules, and use this for T-helper epitope prediction from HPV 16. The HLA class II molecules were obtained by immuno-affinity purification of Epstein-Barr virus B lymphoblastoid cell lines (BCL) homozygous for HLA DQA1*0301-DQB1*0301 and HLA DQA1*0101-DQB1*0501. Peptide pools eluted from the HLA molecules were sequenced by Edman degradation. On the basis of the peptide sequence data obtained, the E6, E7, L1 and L2 proteins of HPV 16 were examined to identify sequences which are likely to bind to HLA DQB1*0301 and DQB1*0501. In addition, motif prediction as well as the binding affinity of predicted peptide motifs for HLA DRB1*0401 and DRB1*0101, the DR alleles associated with susceptibility and protection respectively, was accomplished using published data and a prediction algorithm for the naturally processed peptide sequences bound to these molecules. The HLA DQB1*0501 peptide ligand sequence showed that proline gives an outstanding signal at position 2, Asn/Arg at P1, aliphatic/aromatic amino acids in the central portion, a hydrophobic cluster at P5 with a small contribution by small polar residues and another cluster of aromatic residues towards the C-terminus. The HLA DQB1*0301 sequence also showed that proline gives an outstanding signal at position 2, Thr/Arg at P1, aliphatic/aromatic amino acids in the central portion and an aliphatic cluster with a small contribution by small polar residues at P5. There were no differences in the number of HPV peptides that were predicted as being capable of binding to HLA DQB1*0301 and HLA DQB1*0501, but more HPV peptide motifs were predicted to bind with high affinity to HLA DRB1*0101 than DRB1*0401. The results suggest that HPV 16 peptide epitopes bind with higher affinity to the protective than to susceptible HLA DR-DQ molecules which may lead to a more effective immune response.

Amino Acid Motifs↗

Exploring phenotype space through neutral evolution.

RNA secondary-structure folding algorithms predict the existence of connected networks of RNA sequences with identical secondary structures. Fitness landscapes that are based on the mapping between RNA sequence and RNA secondary structure hence have many neutral paths. A neutral walk on these fitness landscapes gives access to a virtually unlimited number of secondary structures that are a single point mutation from the neutral path. This shows that neutral evolution explores phenotype space and can play a role in adaptation.

Algorithms↗

Prediction of protein backbone conformation based on seven structure assignments. Influence of local interactions.

A method is developed to compute backbone tertiary folds from the amino acid sequence. In this method, the number of degrees of freedom is drastically reduced by neglecting side-chain flexibility, and by describing backbone conformations as combinations of only seven structural states. These are characterized by single values of the dihedral angles phi, psi and omega, representing allowed conformations of the isolated dipeptide. We show that this restrictive model is none the less capable of describing native backbones to within acceptable deviations. Using our backbone description, potentials of mean force are derived from a database of known protein structures, based on statistical influences of single residues and residue pairs on the conformational states in their vicinity along the chain. This yields the force-field component due to local interactions, which is then used to predict lowest-energy conformations from any given amino acid sequence. The prediction algorithm does not require searching conformational space and is therefore extremely fast. Another important asset of our method is that it is able to compute not only the minimum energy conformation, but any number of lowest energy structures, whose relative preferences can be determined from the corresponding computed energy values. The performance of our procedure is tested on short peptides that are likely to be stabilized by local interactions. These include several helical structures and a hexapeptide with a beta-bend conformation, corresponding to peptides shown to have relatively well-defined conformations in aqueous solution, and to protein segments believed to adopt their native conformation early during folding. In addition, several flexible peptides are analysed. Except for the problems encountered in predicting observed disulphide bridges in two of the flexible peptides, and in a somewhat larger fragment comprising residues 30 to 51 of bovine trypsin inhibitor, prediction results compare very favourably with experimental data. Potential applications of our procedure to protein modelling and its extension to protein folding are discussed.

Amino Acid Sequence↗

High-quality MRC document coding.

The mixed raster content (MRC) model can be used to implement highly effective document compression algorithms. MRC document coders are typically based on the use of a binary mask layer that efficiently encodes the text and graphic content. However, while many MRC-based methods can yield much higher compression ratios than conventional color image compression methods, the binary representation tends to distort fine document details, such as thin lines and text edges. In this paper, we propose a method for encoding and decoding the binary mask layer that substantially improves the decoded document fidelity of text and graphics at a fixed bit rate. This method, which we call resolution-enhanced rendering (RER), works by adaptively dithering the encoded binary mask, and then applying a nonlinear predictor to decode a gray level mask at the same resolution. Both the dithering and nonlinear prediction algorithms are jointly optimized to produce the minimal distortion rendering. In addition, we introduce a second method, interpolative RER (IRER), which incorporates interpolation into the MRC decoder. The IRER method increases the compression ratio by allowing a high-resolution document to be coded at lower resolutions. We present experimental results illustrating the performance of our RER/IRER methods and comparing them to some existing MRC-based compression algorithms.

Algorithms↗

Profiling of genes expressed in peripheral blood mononuclear cells predicts glucocorticoid sensitivity in asthma patients.

Gene expression profiles were examined in freshly isolated peripheral blood mononuclear cells (PBMC) from two independent cohorts (training and test sets) of glucocorticoid (GC)-sensitive (n = 64) and GC-resistant (n = 42) asthma patients in search of genes that accurately predict responders and nonresponders to inhaled corticosteroids. A total of 11,812 genes were examined with high-density oligonucleotide microarrays in both resting PBMC (106 patients) and cells treated in vitro with IL-1beta and TNF-alpha combined (88 patients), with or without GC. A total of 5,011 genes were expressed at significant levels in the PBMC, and 1,334 of those were notably up-regulated or down-regulated by IL-1beta/TNF-alpha treatment. The expression changes of 923 genes were significantly reversed in GC responders in the presence of GC. The expression pattern of 15 of these 923 genes that most accurately separated GC responders (n = 26) from the nonresponders (n = 18) in the training set, based on the weighted voting algorithm, predicted the independent test set of equal size with 84% accuracy. The expression accuracy of these genes was confirmed by real-time-quantitative PCR, wherein 11 of the 15 genes predicted GC sensitivity at baseline with 84% accuracy, with one gene predicting at 81% in an independent cohort of 79 patients. We conclude that we have uncovered gene expression profiles in PBMC that predict clinical response to inhaled GC therapy with meaningful accuracy. Upon validation in an independent study, these results support the development of a diagnostic test to guide GC therapy in asthma patients.

Adult↗