Individual reference values for 2D echocardiographic measurements. The Stockholm - Umeå Study.

OBJECTIVES: Improved reference values for 2D echocardiographic measurements are required, even when more recent echocardiographic technology is employed. In addition, it may be preferable to individualize reference values from age, gender and body characteristics of any subject. DESIGN: A material of 180 healthy subjects was collected and investigated, aiming for an even distribution of sex and age (from 20 to 80 years of age; the Stockholm material). For atrial areas, material from another 216 healthy subjects with similar sex and age distribution was added (the Umeå material). The 2D measures determined were the left and right ventricular diameters in diastole, the left ventricular diameter in systole, the thickness of septum and posterior wall, the diameters of the aortic root (sinotubular junction) and the left atrium (all in parasternal view), together with the left and right ventricular diameters in diastole and left and right atrial areas in end-systole (apical four-chamber view). The width of the inferior vena cava (from subcostal view) was also determined. RESULTS: Confidence intervals for females and males are presented for each of these measures. Multiple linear regression analyses with age, sex and measures of body characteristics as predictors were also performed, and for eight of the 12 measurements, such equations are presented. CONCLUSIONS: It is possible to obtain more highly individualized reference values for these cardiac dimensions, which may clinically be a better way of distinguishing pathological states from normal states.

Identifying COPD patients at increased risk of mortality: predictive value of clinical study baseline data.

BACKGROUND: Identifying chronic obstructive pulmonary disease (COPD) patients at increased risk of mortality is an important component of effective disease management. METHODS: A pooled analysis of patients with severe COPD, from two well-controlled 1-year studies, was conducted using Cox regression and spline analysis to evaluate predictability of baseline demographic data and in-study variables for mortality risk, and to evaluate the effect of treatment allocation to budesonide and formoterol, versus their respective control groups, on these outcomes. RESULTS: In the pooled analysis, a Cox regression model reported a higher baseline St George's Respiratory Questionnaire (SGRQ) total score as a significant predictor of mortality (hazard ratio 1.037 [95% confidence interval 1.021-1.054]; p<0.0001). The 36-item short-form health survey (SF-36) mental and physical component scores were also predictive of an increased mortality risk (p<0.05). Age, forced expiratory volume in 1 s (FEV(1)), body mass index and smoking status were not significant predictors. Spline analysis of baseline variables revealed a linear association between SGRQ total score and mortality risk over 1 year (logarithmic scale). Other baseline variables, including FEV(1), showed different bimodal patterns in the spline analysis. There was no difference in mortality in the formoterol versus the non-formoterol treatment group while budesonide-containing treatment was associated with reduced 1-year, all-cause, in-study mortality compared with non-budesonide therapy. CONCLUSION: Health status measured by SGRQ and SF-36 may be important for predicting COPD patients at increased mortality risk, with SGRQ total score emerging as the strongest predictor compared with other baseline covariates.

Comprehensive comparisons of the current human, mouse, and rat RefSeq, Ensembl, EST, and FANTOM3 datasets: identification of new human genes with specific tissue expression profile.

Our understanding of functional genetic elements in the genomes is continuously growing and new entries are entered in various databases on a regular basis. We have here merged the genetic elements in RefSeq, Ensembl, FANTOM3, HINV, and NCBI:s ESTdb using the genome assemblies in order to achieve a comprehensive picture of the current status of the identity and gene number in human, mouse, and rat. The number of human protein coding genes has not increased (25,043) while the increased sequencing of mouse transcripts has provided the considerably higher number of protein coding genes (31,578) in mouse. The results indicate large discrepancies between the datasets, as considerable numbers of unique transcripts can be found in each dataset. Despite the high number of ncRNA (38,129 in mouse) there are also almost 20,000 EST clusters in both mouse and humans with more than one EST that do not overlap any transcript suggesting that several new genetic elements are still to be found. We also demonstrated presence of new genes by identifying new human ones that have specific tissue profiles, using RT-PCR on rat tissues.

The G protein-coupled receptor subset of the chicken genome.

G protein-coupled receptors (GPCRs) are one of the largest families of proteins, and here we scan the recently sequenced chicken genome for GPCRs. We use a homology-based approach, utilizing comparisons with all human GPCRs, to detect and verify chicken GPCRs from translated genomic alignments and Genscan predictions. We present 557 manually curated sequences for GPCRs from the chicken genome, of which 455 were previously not annotated. More than 60% of the chicken Genscan gene predictions with a human ortholog needed curation, which drastically changed the average percentage identity between the human-chicken orthologous pairs (from 56.3% to 72.9%). Of the non-olfactory chicken GPCRs, 79% had a one-to-one orthologous relationship to a human GPCR. The Frizzled, Secretin, and subgroups of the Rhodopsin families have high proportions of orthologous pairs, although the percentage of amino acid identity varies. Other groups show large differences, such as the Adhesion family and GPCRs that bind exogenous ligands. The chicken has only three bitter Taste 2 receptors, and it also lacks an ortholog to human TAS1R2 (one of three GPCRs in the human genome in the Taste 1 receptor family [TAS1R]), implying that the chicken's ability and mode of detecting both bitter and sweet taste may differ from the human's. The chicken genome contains at least 229 olfactory receptors, and the majority of these (218) originate from a chicken-specific expansion. To our knowledge, this dataset of chicken GPCRs is the largest curated dataset from a single gene family from a non-mammalian vertebrate. Both the updated human GPCR dataset, as well the chicken GPCR dataset, are available for download.

Evaluation of EST-data using the genome assembly.

Using expressed sequence tag (EST) data for genomewide studies requires thorough understanding of the nature of the problems that are related to handling these sequences. We investigated how EST clustering performs when the genome is used as guidance as compared to pairwise sequence alignment methods. We show that clustering with the genome as a template outperforms sequence similarity methods used to create other EST clusters, such as the UniGene set, in respect to the extent ESTs originating from the same transcriptional unit are separated into disjunct clusters. Using our approach, approximately 80% of the RefSeq genes were represented by a single EST cluster and 20% comprised of two or more EST clusters. In contrast, approximately 25% of all RefSeq genes were found to be represented by a single cluster for the UniGene clustering method. The approach minimizes the risk for overestimations due to the amount of disjunct clusters originating from the same transcript. We have also investigated the quality of EST-data by aligning ESTs to the genome. The results show how many ESTs are not adequately trimmed in respect of vector sequences and low quality regions. Moreover, we identified important problems related to ESTs aligned to the genome using BLAT, such as inferring splice junctions, and explained this aspect by simulations with synthetic data. EST-clusters created with the method are available upon request from the authors.

Comparison of the current RefSeq, Ensembl and EST databases for counting genes and gene discovery.

Large amounts of refined sequence material in the form of predicted, curated and annotated genes and expressed sequences tags (ESTs) have recently been added to the NCBI databases. We matched the transcript-sequences of RefSeq, Ensembl and dbEST in an attempt to provide an updated overview of how many unique human genes can be found. The results indicate that there are about 25000 unique genes in the union of RefSeq and Ensembl with 12-18% and 8-13% of the genes in each set unique to the other set, respectively. About 20% of all genes had splice variants. There are a considerable number of ESTs (2200000) that do not match the identified genes and we used an in-house pipeline to identify 22 novel genes from Genscan predictions that have considerable EST coverage. The study provides an insight into the current status of human gene catalogues and shows that considerable refinement of methods and datasets is needed to come to a conclusive gene count.