Can serial PEF measurements separate occupational asthma from allergic alveolitis?

BACKGROUND: Occupational asthma commonly results in work-related changes in serial peak expiratory flow (PEF) measurements. Whether alveolitis can result in similar changes is unknown. AIMS: To identify differences and similarities of serial PEF between workers with occupational alveolitis and asthma seen during an outbreak investigation in a factory with metal-working fluid exposure. METHODS: Workers with respiratory symptoms and rest-day improvement were identified by questionnaire. Each was asked to measure PEF 8 times daily for 4 weeks at home and work. Alveolitis was subsequently diagnosed from a validated scoring system including radiological changes, carbon monoxide diffusing capacity, bronchoalveolar lavage and biopsy results. Occupational asthma was confirmed with a positive Oasys score >2.5 and a mean rest-work PEF >16 l/min from serial 2-hourly PEF measurements. The Oasys PEF plotter calculated differences between rest and workdays for mean PEF, diurnal variation and the scores were used to confirm an occupational effect (Oasys, area between curve and time point). Records were compared between the alveolitis group and the group with occupational asthma without alveolitis. RESULTS: Forty workers with occupational asthma and 16 with alveolitis had indistinguishable PEF changes on workdays in terms of magnitude (median reduction 18.5 and 16.1 l/min, respectively) and diurnal variation. Immediate reactions were more common with occupational asthma and late reactions more common with alveolitis. CONCLUSIONS: PEF responses to metal-working fluid aerosols do not distinguish occupational asthma from alveolitis except in timing. They can be used to identify the workplace as the cause of asthma and also alveolitis.

Shift work effects on serial PEF measurements for occupational asthma.

BACKGROUND: Diurnal variation (DV) affects lung function but the changes are thought to be related to sleep patterns rather than time of day. When diagnosing occupational asthma (OA), serial peak expiratory flow (PEF) measurements are the recommended first line investigation, but could be confounded by shift work. AIMS: The aim of the study was to investigate the effects of shift work on PEF measurements used for diagnosing OA. METHODS: PEF records containing more than one shift pattern with ≥ 4 days per shift were identified. OA diagnosis was based on an Oasys-2 score ≥ 2.51 and non-OA on having an alternative clinical diagnosis and Oasys-2 score <2.51. The mean area between curves (ABC) score, mean PEF DV and cross-shift PEF changes were calculated for each shift. RESULTS: Records from 123 workers with OA and 69 without OA satisfied inclusion criteria. In the OA group, PEF declined more on afternoon and night shifts than days (P < 0.001). The ABC score was lower in the OA group on night (P < 0.05) and afternoon shifts (P < 0.05) as compared with days, without significant differences in DV. Among those without OA, cross-shift PEF increased more on day shifts (mean + 25 l/min) than afternoon or night shifts (+1 l/min) (P < 0.001). The sensitivity for the ABC score and DV were good and similar across shifts, but specificity was reduced using DV (DV mean 39%; ABC 98%). CONCLUSIONS: PEF responses between work and rest show small differences according to shift type. The ABC score has a high sensitivity and specificity for all shifts; differences in DV have lower specificity.

An outbreak of occupational asthma due to chromium and cobalt.

BACKGROUND: Five metal turners employed by an aerospace manufacturer presented to the Birmingham Chest Clinic occupational lung disease unit. Four cases of occupational asthma (OA) due to chromium salt (3) and cobalt (1) were diagnosed by serial peak-expiratory flow measurements and specific inhalation challenge testing. AIMS: To measure the extent of the outbreak and to provide epidemiological data to ascertain the aetiology. METHODS: Participants answered a detailed, self-administered questionnaire, designed to detect occupational lung disease. Urine chromium and cobalt excretion, spirometry and exhaled nitric oxide measurements were taken. Those with possible, probable or definite non-OA or OA, after questionnaire, were invited to undertake two-hourly peak flow measurements and received specialist follow-up. RESULTS: A total of 62 workers (95% of workforce) participated. Sixty-one per cent of employees were working in higher metalworking fluid (MWF) exposure areas. Ninety per cent of workers had urinary chromium excretion indicating occupational exposure. Sixty-six per cent of workers reported active respiratory symptoms, although there were no significant differences between exposure groups. Two further workers with probable OA were identified and had significantly higher urinary chromium and cobalt concentration than asymptomatic controls. Eighteen cases of occupational rhinitis (OR) were identified, with significantly raised urinary chromium concentration compared with asymptomatic controls. CONCLUSIONS: Chromium salt and cobalt can be responsible for OA and OR in workers exposed to MWF aerosols. Onset of symptoms in those with positive specific challenges followed change in MWF brand. Workers with OA had increased urinary concentrations of chromium and cobalt, and those with OR had increased urinary concentrations of chromium.

Diagnosis of occupational asthma from time point differences in serial PEF measurements.

BACKGROUND: The diagnosis of occupational asthma requires objective confirmation. Analysis of serial measurements of peak expiratory flow (PEF) is usually the most convenient first step in the diagnostic process. A new method of analysis originally developed to detect late asthmatic reactions following specific inhalation testing is described. This was applied to serial PEF measurements made over many days in the workplace to supplement existing methods of PEF analysis. METHODS: 236 records from workers with independently diagnosed occupational asthma and 320 records from controls with asthma were available. The pooled standard deviation for rest day measurements was obtained from an analysis of variance by time. Work day PEF measurements were meaned into matching 2-hourly time segments. Time points with mean work day PEF statistically lower (at the Bonferroni adjusted 5% level) than the rest days were counted after adjusting for the number of contributing measurements. RESULTS: A minimum of four time point comparisons were needed. Records with >or=2 time points significantly lower on work days had a sensitivity of 67% and a specificity of 99% for the diagnosis of occupational asthma against independent diagnoses. Reducing the requirements to >or=1 non-waking time point difference increased sensitivity to 77% and reduced specificity to 93%. The analysis was only applicable to 43% of available records, mainly due to differences in waking times on work and rest days. CONCLUSION: Time point analysis complements other validated methods of PEF analysis for the diagnosis of occupational asthma. It requires shorter records than are required for the Oasys score and can identify smaller changes than other methods, but is dependent on low rest day PEF variance.

Serial PEF measurement is superior to cross-shift change in diagnosing occupational asthma.

Cross-shift measurements of peak expiratory flow (PEF) are commonly employed in the diagnosis of occupational asthma, although evidence for this approach is lacking. The current paper presents an evaluation of the technique. Mean changes in PEF across morning/day shifts were compared between workers with occupational asthma, confirmed using specific challenge testing, and non-working asthmatics. Individuals were divided into a development set, used to identify the optimum cross-shift change for diagnosing occupational asthma, and an evaluation set, used to test the sensitivity and specificity of this value. Comparative analysis of serial PEF records was performed using the Oasys-2 computerised system. A cross-shift decrease in PEF of 5 L.min(-1) achieved acceptable specificity in the development set. Applied to the evaluation set, this cut-off had a specificity of 90.9% and a sensitivity of 50%. Sensitivity could not be improved without unacceptable compromise to specificity. Analysis of serial PEF records using linear discriminant analysis identified occupational asthma with a sensitivity of 83.3% and a specificity of 90.9%. Serial analysis using mean work/rest day PEF comparison had a sensitivity of 66.7% and a specificity of 100%. Cross-shift changes in PEF in morning/day-shift workers have poor sensitivity in diagnosing occupational asthma, and are inferior to serial techniques.

Clinical investigation of an outbreak of alveolitis and asthma in a car engine manufacturing plant.

BACKGROUND: Exposure to metal working fluid (MWF) has been associated with outbreaks of extrinsic allergic alveolitis (EAA) in the USA, with bacterial contamination of MWF being a possible cause, but is uncommon in the UK. Twelve workers developed EAA in a car engine manufacturing plant in the UK, presenting clinically between December 2003 and May 2004. This paper reports the subsequent epidemiological investigation of the whole workforce. The study had three aims: (1) to measure the extent of the outbreak by identifying other workers who may have developed EAA or other work-related respiratory diseases; (2) to provide case detection so that those affected could be treated; and (3) to provide epidemiological data to identify the cause of the outbreak. METHODS: The outbreak was investigated in a three-phase cross-sectional survey of the workforce. In phase I a respiratory screening questionnaire was completed by 808/836 workers (96.7%) in May 2004. In phase II 481 employees with at least one respiratory symptom on screening and 50 asymptomatic controls were invited for investigation at the factory in June 2004. This included a questionnaire, spirometry and clinical opinion. 454/481 (94.4%) responded and 48/50 (96%) controls. Workers were identified who needed further investigation and serial measurements of peak expiratory flow (PEF). In phase III 162 employees were seen at the Birmingham Occupational Lung Disease clinic. 198 employees returned PEF records, including 141 of the 162 who attended for clinical investigation. Case definitions for diagnoses were agreed. RESULTS: 87 workers (10.4% of the workforce) met case definitions for occupational lung disease, comprising EAA (n = 19), occupational asthma (n = 74) and humidifier fever (n = 7). 12 workers had more than one diagnosis. The peak onset of work-related breathlessness was Spring 2003. The proportion of workers affected was higher for those using MWF from a large sump (27.3%) than for those working all over the manufacturing area (7.9%) (OR = 4.39, p<0.001). Two workers had positive specific provocation tests to the used but not the unused MWF solution. CONCLUSIONS: Extensive investigation of the outbreak of EAA detected a large number of affected workers, not only with EAA but also occupational asthma. This is the largest reported outbreak in Europe. Mist from used MWF is the likely cause. In workplaces using MWF there is a need to carry out risk assessments, to monitor and maintain fluid quality, to control mist and to carry out respiratory health surveillance.

Assessment of the total number of human transcription units.

Variation in the estimates of the number of genes encoded by the human genome (28,000-120,000) attests to the difficulty of systematically identifying human genes. Sequencing of human chromosome 22 (Chr22) provided the first comprehensive, unbiased view of an entire human chromosome, and intensive analysis of this sequence identified 545 genes and 134 pseudogenes that had similarity or identity to known proteins and/or ESTs and which were listed in the gene annotation (http://www.sanger.ac.uk/HGP/Chr22). This analysis yielded an estimate of approximately 36,000 functional expressed genes in the human genome (and 9000 pseudogenes). However, a key uncertainty in this estimate was that hundreds of additional genes beyond those annotated in the Chr22 sequence are predicted by the gene prediction program Genscan, an unknown number of which might represent additional expressed genes. To determine what fraction of these "predicted novel genes" (PNGs) represents expressed human genes, we used a sensitive RT-PCR assay to detect predicted transcripts in 17 tissues and one cell line. Our results indicate that at least 5000-9000 additional human genes which lack similarity to known genes or proteins exist in the human genome, increasing baseline gene estimates to approximately 41,000-45,000.

A computational analysis of sequence features involved in recognition of short introns.

Splicing of short introns by the nuclear pre-mRNA splicing machinery is thought to proceed via an "intron definition" mechanism, in which the 5' and 3' splice sites (5'ss, 3'ss, respectively) are initially recognized and paired across the intron. Here, we describe a computational analysis of sequence features involved in recognition of short introns by using available transcript data from five eukaryotes with complete or nearly complete genomic sequences. The information content of five different transcript features was measured by using methods from information theory, and Monte Carlo simulations were used to determine the amount of information required for accurate recognition of short introns in each organism. We conclude: (i) that short introns in Drosophila melanogaster and Caenorhabditis elegans contain essentially all of the information for their recognition by the splicing machinery, and computer programs that simulate splicing specificity can predict the exact boundaries of approximately 95% of short introns in both organisms; (ii) that in yeast, the 5'ss, branch signal, and 3'ss can accurately identify intron locations but do not precisely determine the location of 3' cleavage in every intron; and (iii) that the 5'ss, branch signal, and 3'ss are not sufficient to accurately identify short introns in plant and human transcripts, but that specific subsets of candidate intronic enhancer motifs can be identified in both human and Arabidopsis that contribute dramatically to the accuracy of splicing simulators.

Computational inference of homologous gene structures in the human genome.

With the human genome sequence approaching completion, a major challenge is to identify the locations and encoded protein sequences of all human genes. To address this problem we have developed a new gene identification algorithm, GenomeScan, which combines exon-intron and splice signal models with similarity to known protein sequences in an integrated model. Extensive testing shows that GenomeScan can accurately identify the exon-intron structures of genes in finished or draft human genome sequence with a low rate of false-positives. Application of GenomeScan to 2.7 billion bases of human genomic DNA identified at least 20,000-25,000 human genes out of an estimated 30,000-40,000 present in the genome. The results show an accurate and efficient automated approach for identifying genes in higher eukaryotic genomes and provide a first-level annotation of the draft human genome.

Computational and experimental analysis identifies many novel human genes.

Because of advances in automation, human genomic sequences are being deposited in public databases at a dramatic rate. However, the process of detecting genes in these sequences is still something of an art. Here we describe the implementation and testing of a relatively straightforward computational approach, the Virtual Transcribed Sequence project, which analyzes their gene content using the gene prediction program GENSCAN (GENSCAN 1.0 1,2) in combination with similarity-based methods. This approach identifies many novel human genes not found even in EST databases.

Development of an expert system for the interpretation of serial peak expiratory flow measurements in the diagnosis of occupational asthma. Midlands Thoracic Society Research Group.

If asthma is due to work exposures there must be a relation between these exposures and the asthma. Asthma causes airway hyperresponsiveness and obstruction; the obstruction can be measured with portable meters, which usually measure peak expiratory flow, or sometimes forced expiratory volume in 1 second (FEV1). These can be measured serially (for instance 2 hourly) over several weeks at and away from work. Once occupational asthma develops, the asthma will be induced by many non-specific triggers common to non-occupational asthma. The challenge is to identify changes in peak expiratory flow due to work among other non-occupational causes. Standard statistical tests have been found to be insensitive or non-specific, principally because of the variable period for deterioration to occur after exposure, and the sometimes prolonged time for recovery to occur, such that days away from work may initially have lower measurements than days at work. A computer assisted diagnostic aid (Oasys) has been developed to separate occupational from non-occupational causes of airflow obstruction. Oasys-2 is based on a discriminant analysis, and achieved a sensitivity of 75% and a specificity of at least 94%; therefore peak expiratory flow monitoring combined with Oasys-2 analysis is better to confirm than to exclude occupational asthma. A neural network version in development has improved on this. Both have been based on expert interpretation of peak flow measurements plotted as daily maximum, mean, and minimum, with the first reading at work taken as the first reading of the day. Oasys has been evaluated with independent criteria against measurements made in a wide range of occupational situations. Oasys is sufficiently developed to be the initial method for the confirmation, although less so for exclusion of occupational asthma.

Finding the genes in genomic DNA.

Genome sequencing efforts will soon generate hundreds of millions of bases of human genomic DNA containing thousands of novel genes. In the past year, the accuracy of computational gene-finding methods has improved significantly, to the point where a reasonable approximation of the gene structures within an extended genomic region can often be predicted in advance of more detailed experimental studies.

Evolutionary fates and origins of U12-type introns.

U2-type and U12-type introns are spliced by distinct spliceosomes in eukaryotic nuclei. A classification method was devised to distinguish these two types of introns based on splice site sequence properties and was used to identify 56 different genes containing U12-type introns in available genomic sequences. U12-type introns occur with consistently low frequency in diverse eukaryotic taxa but have almost certainly been lost from C. elegans. Comparisons with available homologous sequences demonstrate subtype switching of U12 introns between termini of AT-AC and GT-AG as well as conversion of introns from U12-type to U2-type and provide evidence for a fission/fusion model in which the two splicing systems evolved in separate lineages that were fused in a eukaryotic progenitor.