Heat and moisture transfer behaviour in Phyllostachys edulis (Moso bamboo) based panels

This study focuses on the heat and moisture transfer behaviours in the Phyllostachys edulis (Moso bamboo) panels in various temperature and relative humidity (RH) conditions. Moso bamboo panels with different lamination methods were prepared by bamboo strips from different layers of bamboo culm wall. The dynamic coupled heat and moisture transfer experiments were conducted. Unsteady state numerical modelling was conducted by COMSOL MultiphysicsTM. A rigorous approach was adopted in this paper, firstly a series of parametric studies of numerical simulation are firstly presented in this paper and then validated by the experiments. Both experiment and simulation results appear to be consistent with the results of measurements of the basic hygrothermal parameters, which demonstrates the robustness of the results. The temperature and RH results indicated that although the layer of panel made by the internal part of bamboo culm wall can provide good insulation performance, its ability to resist high RH variation is inferior to the layer from the external part of bamboo culm wall. The parametric study found that density is the most critical parameters to influence the temperature distributions in the transient state. The thermal conductivity dominates the temperature variation at the steady states. The water vapour diffusion resistance factor is the key parameter which influences the RH simulation results. Numerical simulation with moisture transfer shows better consistency than the simulation without moisture in both equilibrium and transient states. The results of this study demonstrated that the external part of the bamboo culm wall can be utilised to minimise the RH variation of the panel while the internal part is suitable for increasing the thermal insulation performance of the panel

Limitations and pitfalls of using family letters to communicate genetic risk: a qualitative study with patients and healthcare professionals

European genetic testing guidelines recommend that healthcare professionals (HCPs) discuss the familial implications of any test with a patient and offer written material to help them share the information with family members. Giving patients these “family letters” to alert any relatives of their risk has become part of standard practice and has gone relatively unquestioned over the years. Communication with at-risk relatives will become an increasingly pressing issue as mainstream and routine practice incorporates broad genome tests and as the number of findings potentially relevant to relatives increases. This study therefore explores problems around the use of family letters to communicate about genetic risk. We conducted 16 focus groups with 80 HCPs, and 35 interviews with patients, recruited from across the UK. Data were analyzed thematically and we constructed four themes: 1) HCPs writing family letters: how to write them and why?, 2) Patients’ issues with handing out family letters, 3) Dissemination becomes an uncontrolled form of communication, and 4) When the relative has the letter, is the patient’s and HCP’s duty discharged? We conclude by suggesting alternative and supplementary methods of communication, for example through digital tools, and propose that in comparison to communication by family letter, direct contact by HCPs might be a more appropriate and successful option

Reevaluation of the South Asian MYBPC3Δ25bp Intronic Deletion in Hypertrophic Cardiomyopathy.

BACKGROUND: The common intronic deletion, MYBPC3Δ25, detected in 4% to 8% of South Asian populations, is reported to be associated with cardiomyopathy, with ≈7-fold increased risk of disease in variant carriers. Here, we examine the contribution of MYBPC3Δ25 to hypertrophic cardiomyopathy (HCM) in a large patient cohort. METHODS: Sequence data from 2 HCM cohorts (n=5393) was analyzed to determine MYBPC3Δ25 frequency and co-occurrence of pathogenic variants in HCM genes. Case-control and haplotype analyses were performed to compare variant frequencies and assess disease association. Analyses were also undertaken to investigate the pathogenicity of a candidate variant MYBPC3 c.1224-52G>A. RESULTS: Our data suggest that the risk of HCM, previously attributed to MYBPC3Δ25, can be explained by enrichment of a derived haplotype, MYBPC3Δ25/-52, whereby a small subset of individuals bear both MYBPC3Δ25 and a rare pathogenic variant, MYBPC3 c.1224-52G>A. The intronic MYBPC3 c.1224-52G>A variant, which is not routinely evaluated by gene panel or exome sequencing, was detected in ≈1% of our HCM cohort. CONCLUSIONS: The MYBPC3 c.1224-52G>A variant explains the disease risk previously associated with MYBPC3Δ25 in the South Asian population and is one of the most frequent pathogenic variants in HCM in all populations; genotyping services should ensure coverage of this deep intronic mutation. Individuals carrying MYBPC3Δ25 alone are not at increased risk of HCM, and this variant should not be tested in isolation; this is important for the large majority of the 100 million individuals of South Asian ancestry who carry MYBPC3Δ25 and would previously have been declared at increased risk of HCM

Maximal Wall Thickness Measurement in Hypertrophic Cardiomyopathy: Biomarker Variability and its Impact on Clinical Care

OBJECTIVES: The aim of this study was to define the variability of maximal wall thickness (MWT) measurements across modalities and predict its impact on care in patients with hypertrophic cardiomyopathy (HCM). BACKGROUND: Left ventricular MWT measured by echocardiography or cardiovascular magnetic resonance (CMR) contributes to the diagnosis of HCM, stratifies risk, and guides key decisions, including whether to place an implantable cardioverter-defibrillator (ICD). METHODS: A 20-center global network provided paired echocardiographic and CMR data sets from patients with HCM, from which 17 paired data sets of the highest quality were selected. These were presented as 7 randomly ordered pairs (at 6 cardiac conferences) to experienced readers who report HCM imaging in their daily practice, and their MWT caliper measurements were captured. The impact of measurement variability on ICD insertion decisions was estimated in 769 separately recruited multicenter patients with HCM using the European Society of Cardiology algorithm for 5-year risk for sudden cardiac death. RESULTS: MWT analysis was completed by 70 readers (from 6 continents; 91% with >5 years' experience). Seventy-nine percent and 68% scored echocardiographic and CMR image quality as excellent. For both modalities (echocardiographic and then CMR results), intramodality inter-reader MWT percentage variability was large (range -59% to 117% [SD ±20%] and -61% to 52% [SD ±11%], respectively). Agreement between modalities was low (SE of measurement 4.8 mm; 95% CI 4.3 mm-5.2 mm; r = 0.56 [modest correlation]). In the multicenter HCM cohort, this estimated echocardiographic MWT percentage variability (±20%) applied to the European Society of Cardiology algorithm reclassified risk in 19.5% of patients, which would have led to inappropriate ICD decision making in 1 in 7 patients with HCM (8.7% would have had ICD placement recommended despite potential low risk, and 6.8% would not have had ICD placement recommended despite intermediate or high risk). CONCLUSIONS: Using the best available images and experienced readers, MWT as a biomarker in HCM has a high degree of inter-reader variability and should be applied with caution as part of decision making for ICD insertion. Better standardization efforts in HCM recommendations by current governing societies are needed to improve clinical decision making in patients with HCM

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

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges