Therapeutic lung lavages in children and adults

BACKGROUND: Pulmonary alveolar proteinosis (PAP) is a rare disease, characterized by excessive intra-alveolar accumulation of surfactant lipids and proteins. Therapeutic whole lung lavages are currently the principle therapeutic option in adults. Not much is known on the kinetics of the wash out process, especially in children. METHODS: In 4 pediatric and 6 adult PAP patients 45 therapeutic half lung lavages were investigated retrospectively. Total protein, protein concentration and, in one child with a surfactant protein C mutation, aberrant pro-SP-C protein, were determined during wash out. RESULTS: The removal of protein from the lungs followed an exponential decline and averaged for adult patients 2 – 20 g and <0.5 to 6 g for pediatric patients. The average protein concentration of consecutive portions was the same in all patient groups, however was elevated in pediatric patients when expressed per body weight. The amount of an aberrant pro-SP-C protein, which was present in one patient with a SP-C mutation, constantly decreased with ongoing lavage. Measuring the optical density of the lavage fluid obtained allowed to monitor the wash out process during the lavages at the bedside and to determine the termination of the lavage procedure at normal protein concentration. CONCLUSION: Following therapeutic half lung lavages by biochemical variables may help to estimate the degree of alveolar filling with proteinaceous material and to improve the efficiency of the wash out, especially in children

Current patch test results with the European baseline series and extensions to it from the 'European Surveillance System on Contact Allergy' network, 2007-2008

BACKGROUND: The pattern of contact sensitization to the supposedly most important allergens assembled in the baseline series differs between countries, presumably at least partly because of exposure differences. Objectives. To describe the prevalence of contact sensitization to allergens tested in consecutive patients in the years 2007 and 2008, and to discuss possible differences. METHODS: Data from the 39 departments in 11 European countries comprising the European Surveillance System on Contact Allergy network (www.essca-dc.org) in this period have been pooled and analysed according to common standards. RESULTS: Patch test results with the European baseline series, and country-specific or department-specific additions to it, obtained in 25 181 patients, showed marked international variation. Metals and fragrances are still the most frequent allergens across Europe. Some allergens tested nationally may be useful future additions to the European baseline series, for example methylisothiazolinone, whereas a few long-term components of the European baseline series, namely primin and clioquinol, no longer warrant routine testing. CONCLUSIONS: The present analysis points to 'excess' prevalences of specific contact sensitization in some countries, although interpretation must be cautious if only few, and possibly specialized, centres are representing one country. A comparison as presented may help to target in-depth research into possible causes of 'excess' exposure, and/or consideration of methodological issues, including modifications to the baseline series

Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars

Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases

BACKGROUND: Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25–30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome. METHODS: We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants. RESULTS: Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving. CONCLUSIONS: Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases.

BACKGROUND: Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome. METHODS: We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants. RESULTS: Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving. CONCLUSIONS: Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing