Zimmermann-Laband syndrome in monozygotic twins with a mild neurobehavioral phenotype lacking gingival overgrowth-A case report of a novel KCNN3 gene variant.

Zimmermann-Laband syndrome is a rare, heterogeneous disorder characterized by gingival hypertrophy or fibromatosis, aplastic/hypoplastic nails, hypoplasia of the distal phalanges, hypertrichosis, various degrees of intellectual disability, and distinctive facial features. Three genes are considered causative for ZLS: KCNH1, KCNN3, and ATP6V1B2. We report on a pair of female concordant monozygotic twins, both carrying a novel pathogenic variant in the KCNN3 gene, identified using exome sequencing. Only six ZLS patients with the KCNN3 pathogenic variant have been reported so far. The twins show facial dysmorphism, hypoplastic distal phalanges, aplasia or hypoplasia of nails, and hypertrichosis. During infancy, they showed mild developmental delays, mainly speech. They successfully completed secondary school education and are socio-economically independent. Gingival overgrowth is absent in both individuals. Our patients exhibited an unusually mild phenotype compared to published cases, which is an important diagnostic finding for proper genetic counseling for Zimmermann-Laband syndrome patients and their families.

Expanding the phenotype spectrum associated with pathogenic variants in the COL2A1 and COL11A1 genes.

We report the clinical findings of 26 individuals from 16 unrelated families carrying variants in the COL2A1 or COL11A1 genes. Using Sanger and next-generation sequencing, 11 different COL2A1 variants (seven novel), were identified in 13 families (19 affected individuals), all diagnosed with Stickler syndrome (STL) type 1. In nine families, the COL2A1 disease-causing variant arose de novo. Phenotypically, we observed myopia (95%) and retinal detachment (47%), joint hyperflexibility (92%), midface retrusion (84%), cleft palate (53%), and various degrees of hearing impairment (50%). One patient had a splenic artery aneurysm. One affected individual carrying pathogenic variant in COL2A1 showed no ocular signs including no evidence of membranous vitreous anomaly. In three families (seven affected individuals), three novel COL11A1 variants were found. The propositus with a de novo variant showed an ultrarare Marshall/STL overlap. In the second family, the only common clinical sign was postlingual progressive sensorineural hearing impairment (DFNA37). Affected individuals from the third family had typical STL2 signs. The spectrum of disease phenotypes associated with COL2A1 or COL11A1 variants continues to expand and includes typical STL and various bone dysplasias, but also nonsyndromic hearing impairment, isolated myopia with or without retinal detachment, and STL phenotype without clinically detectable ocular pathology.

Body mass index is an overlooked confounding factor in existing clustering studies of 3D facial scans of children with autism spectrum disorder.

Cluster analyzes of facial models of autistic patients aim to clarify whether it is possible to diagnose autism on the basis of facial features and further to stratify the autism spectrum disorder. We performed a cluster analysis of sets of 3D scans of ASD patients (116) and controls (157) using Euclidean and geodesic distances in order to recapitulate the published results on the Czech population. In the presented work, we show that the major factor determining the clustering structure and consequently also the correlation of resulting clusters with autism severity degree is body mass index corrected for age (BMIFA). After removing the BMIFA effect from the data in two independent ways, both the cluster structure and autism severity correlations disappeared. Despite the fact that the influence of body mass index (BMI) on facial dimensions was studied many times, this is the first time to our knowledge when BMI was incorporated into the faces clustering study and it thereby casts doubt on previous results. We also performed correlation analysis which showed that the only correction used in the existing clustering studies-dividing the facial distance by the average value within the face-is not eliminating correlation between facial distances and BMIFA within the facial cohort.

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

Cost-of-illness analysis and regression modeling in cystic fibrosis: a retrospective prevalence-based study.

BACKGROUND: Economic data pertaining to cystic fibrosis (CF), is limited in Europe generally, and completely lacking in Central and Eastern Europe. We performed an analysis of all direct costs associated with CF relative to key disease features and laboratory examinations. METHODS: A retrospective prevalence-based cost-of-illness (COI) study was performed in a representative cohort of 242 CF patients in the Czech Republic, which represents about 65 % of all Czech CF patients. Medical records and invoices to health insurance companies for reference year 2010 were analyzed. RESULTS: The mean total health care costs were €14,486 per patient, with the majority of the costs going towards medicinal products and devices (€10,321). Medical procedures (€2676) and inpatient care (€1829) represented a much smaller percentage of costs. A generalized linear model showed that the strongest cost drivers, for all cost categories, were associated with patient age and lung disease severity (assessed using the FEV1 spirometric parameter), when compounded by chronic Pseudomonas aeruginosa airway infections. Specifically, maximum total costs are around the age 16 years; a FEV1 increase of 1 % point represented a cost decrease of: 0.9 % (medicinal products), 1.7 % (total costs), 2.8 % (procedures) and 7.0 % (inpatient care). CONCLUSIONS: COI analysis and regression modeling using the most recent data available can provide a better understanding of the overall economic CF burden. A comparison of our results with other methodologically similar studies demonstrates that although overall costs may differ, FEV1 can nonetheless be utilized as a generally transferrable indicator of the relative economic impact of CF.

Correction: A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics.

[This corrects the article DOI: 10.1371/journal.pone.0162866.].

A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics.

Pharmacogenomics aims to correlate inter-individual differences of drug efficacy and/or toxicity with the underlying genetic composition, particularly in genes encoding for protein factors and enzymes involved in drug metabolism and transport. In several European populations, particularly in countries with lower income, information related to the prevalence of pharmacogenomic biomarkers is incomplete or lacking. Here, we have implemented the microattribution approach to assess the pharmacogenomic biomarkers allelic spectrum in 18 European populations, mostly from developing European countries, by analyzing 1,931 pharmacogenomics biomarkers in 231 genes. Our data show significant inter-population pharmacogenomic biomarker allele frequency differences, particularly in 7 clinically actionable pharmacogenomic biomarkers in 7 European populations, affecting drug efficacy and/or toxicity of 51 medication treatment modalities. These data also reflect on the differences observed in the prevalence of high-risk genotypes in these populations, as far as common markers in the CYP2C9, CYP2C19, CYP3A5, VKORC1, SLCO1B1 and TPMT pharmacogenes are concerned. Also, our data demonstrate notable differences in predicted genotype-based warfarin dosing among these populations. Our findings can be exploited not only to develop guidelines for medical prioritization, but most importantly to facilitate integration of pharmacogenomics and to support pre-emptive pharmacogenomic testing. This may subsequently contribute towards significant cost-savings in the overall healthcare expenditure in the participating countries, where pharmacogenomics implementation proves to be cost-effective.

Distribution of CFTR mutations in the Czech population: positive impact of integrated clinical and laboratory expertise, detection of novel/de novo alleles and relevance for related/derived populations.

BACKGROUND: This two decade long study presents a comprehensive overview of the CFTR mutation distribution in a representative cohort of 600 Czech CF patients derived from all regions of the Czech Republic. METHODS: We examined the most common CF-causing mutations using the Elucigene CF-EU2v1™ assay, followed by MLPA, mutation scanning and/or sequencing of the entire CFTR coding region and splice site junctions. RESULTS: We identified 99.5% of all mutations (1194/1200 CFTR alleles) in the Czech CF population. Altogether 91 different CFTR mutations, of which 20 were novel, were detected. One case of de novo mutation and a novel polymorphism was revealed. CONCLUSION: The commercial assay achieved 90.7%, the MLPA added 1.0% and sequencing increased the detection rate by 7.8%. These comprehensive data provide a basis for the improvement of CF DNA diagnostics and/or newborn screening in our country. In addition, they are relevant to related Central European populations with lower mutation detection rates, as well as to the sizeable North American "Bohemian diaspora".