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.

The most common founder pathogenic variant c.868G > A (p.Val290Met) in the NPHS2 gene in a representative adult Czech cohort with focal segmental glomerulosclerosis is associated with a milder disease and its underdiagnosis in childhood.

Background: Genetic focal segmental glomerulosclerosis (FSGS) is caused by pathogenic variants in a broad spectrum of genes that have a variable representation based on subjects' ethnicity and/or age. The most frequently mutated autosomal recessive gene in FSGS is NPHS2. In this study, we analyzed the spectrum of NPHS2 variants and their associated phenotype in Czech adult FSGS patients. Methods: A representative cohort of 234 adult patients with FSGS, derived from 225 families originating from all regions of Czechia, was analyzed by massively parallel sequencing. In this study, we focused on the comprehensive analysis of the NPHS2 gene. The histological classification of FSGS followed the Columbia classification. Results: We detected seven (3%) cases bearing homozygous or compound heterozygous pathogenic NPHS2 variants. A single pathogenic variant c.868G > A (p.Val290Met) was found in the majority of NPHS2-positive cases (86%; 6 out of 7) in histologically confirmed instances of FSGS. Its allele frequency among unrelated NPHS2-associated FSGS patients was 50% (6/12), and Haplotype analysis predicted its origin to be a result of a founder effect. There is an identical V290M-related haplotype on all V290M alleles spanning a 0,7 Mb region flanking NPHS2 in Central European FSGS populations. The phenotype of the p.Val290Met NPHS2-associated FSGS demonstrated a later onset and a much milder course of the disease compared to other NPHS2 pathogenic variants associated with FSGS. The mean age of the FSGS diagnosis based on kidney biopsy evaluation was 31.2 ± 7.46 years. In 50% of all cases, the initial disease manifestation of proteinuria occurred only in adulthood, with 83% of these cases not presenting with edemas. One-third (33%) of the studied subjects progressed to ESRD (2 out of 6) at the mean age of 35.0 ± 2.82 years. Conclusions: We identified the most prevalent pathogenic variant, p.Val290Met, in the NPHS2 gene among Czech adult FSGS patients, which has arisen due to a founder effect in Central Europe. The documented milder course of the disease associated with this variant leads to the underdiagnosis in childhood. We established the histopathological features of the NPHS2-associated adult FSGS cases based on the Columbia classification. This might improve patient stratification and optimize their treatment.

High-Throughput Sequencing Haplotype Analysis Indicates in LRRK2 Gene a Potential Risk Factor for Endemic Parkinsonism in Southeastern Moravia, Czech Republic.

Parkinson's disease and parkinsonism are relatively common neurodegenerative disorders. This study aimed to assess potential genetic risk factors of haplotypes in genes associated with parkinsonism in a population in which endemic parkinsonism and atypical parkinsonism have recently been found. The genes ADH1C, EIF4G1, FBXO7, GBA, GIGYF2, HTRA2, LRRK2, MAPT, PARK2, PARK7, PINK1 PLA2G6, SNCA, UCHL1, and VPS35 were analyzed in 62 patients (P) and 69 age-matched controls from the researched area (C1). Variants were acquired by high-throughput sequencing using Ion Torrent workflow. As another set of controls, the whole genome sequencing data from 100 healthy non-related individuals from the Czech population were used (C2); the results were also compared with the Genome Project data (C3). We observed shared findings of four intron (rs11564187, rs36220738, rs200829235, and rs3789329) and one exon variant (rs33995883) in the LRRK2 gene in six patients. A comparison of the C1-C3 groups revealed significant differences in haplotype frequencies between ratio of 2.09 for C1, 1.65 for C2, and 6.3 for C3, and odds ratios of 13.15 for C1, 2.58 for C2, and 7.6 for C3 were estimated. The co-occurrence of five variants in the LRRK2 gene (very probably in haplotype) could be an important potential risk factor for the development of parkinsonism, even outside the recently described pedigrees in the researched area where endemic parkinsonism is present.

Improving structural variant clustering to reduce the negative effect of the breakpoint uncertainty problem.

BACKGROUND: Structural variants (SVs) represent an important source of genetic variation. One of the most critical problems in their detection is breakpoint uncertainty associated with the inability to determine their exact genomic position. Breakpoint uncertainty is a characteristic issue of structural variants detected via short-read sequencing methods and complicates subsequent population analyses. The commonly used heuristic strategy reduces this issue by clustering/merging nearby structural variants of the same type before the data from individual samples are merged. RESULTS: We compared the two most used dissimilarity measures for SV clustering in terms of Mendelian inheritance errors (MIE), kinship prediction, and deviation from Hardy-Weinberg equilibrium. We analyzed the occurrence of Mendelian-inconsistent SV clusters that can be collapsed into one Mendelian-consistent SV as a new measure of dataset consistency. We also developed a new method based on constrained clustering that explicitly identifies these types of clusters. CONCLUSIONS: We found that the dissimilarity measure based on the distance between SVs breakpoints produces slightly better results than the measure based on SVs overlap. This difference is evident in trivial and corrected clustering strategy, but not in constrained clustering strategy. However, constrained clustering strategy provided the best results in all aspects, regardless of the dissimilarity measure used.

The Key Role of Purine Metabolism in the Folate-Dependent Phenotype of Autism Spectrum Disorders: An In Silico Analysis.

Folate deficiency in the critical developmental period has been repeatedly associated with an increased risk of Autism spectrum disorders (ASD), but the key pathophysiological mechanism has not yet been identified. In this work, we focused on identifying genes whose defect has similar consequences to folate depletion in the metabolic network. Within the Flux Balance Analysis (FBA) framework, we developed a method of blocked metabolites that allowed us to define the metabolic consequences of various gene defects and folate depletion. We identified six genes (GART, PFAS, PPAT, PAICS, ATIC, and ADSL) whose blocking results in nearly the same effect in the metabolic network as folate depletion. All of these genes form the purine biosynthetic pathway. We found that, just like folate depletion, the blockade of any of the six genes mentioned above results in a blockage of purine metabolism. We hypothesize that this can lead to decreased adenosine triphosphate (ATP) and subsequently, an S-adenosyl methionine (SAM) pool in neurons in the case of rapid cell division. Based on our results, we consider the methylation defect to be a potential cause of ASD, due to the depletion of purine, and consequently S-adenosyl methionine (SAM), biosynthesis.

Body coloration and mechanisms of colour production in Archelosauria: the case of deirocheline turtles.

Animal body coloration is a complex trait resulting from the interplay of multiple mechanisms. While many studies address the functions of animal coloration, the mechanisms of colour production still remain unknown in most taxa. Here we compare reflectance spectra, cellular, ultra- and nano-structure of colour-producing elements, and pigment types in two freshwater turtles with contrasting courtship behaviour, Trachemys scripta and Pseudemys concinna. The two species differ in the distribution of pigment cell-types and in pigment diversity. We found xanthophores, melanocytes, abundant iridophores and dermal collagen fibres in stripes of both species. The yellow chin and forelimb stripes of both P. concinna and T. scripta contain xanthophores and iridophores, but the post-orbital regions of the two species differ in cell-type distribution. The yellow post-orbital region of P. concinna contains both xanthophores and iridophores, while T. scripta has only xanthophores in the yellow-red postorbital/zygomatic regions. Moreover, in both species, the xanthophores colouring the yellow-red skin contain carotenoids, pterins and riboflavin, but T. scripta has a higher diversity of pigments than P. concinna. Trachemys s. elegans is sexually dichromatic. Differences in the distribution of pigment cell types across body regions in the two species may be related to visual signalling but do not match predictions based on courtship position. Our results demonstrate that archelosaurs share some colour production mechanisms with amphibians and lepidosaurs (i.e. vertical layering/stacking of different pigment cell types and interplay of carotenoids and pterins), but also employ novel mechanisms (i.e. nano-organization of dermal collagen) shared with mammals.

Under the mask of Kabuki syndrome: Elucidation of genetic-and phenotypic heterogeneity in patients with Kabuki-like phenotype.

Kabuki syndrome is mainly caused by dominant de-novo pathogenic variants in the KMT2D and KDM6A genes. The clinical features of this syndrome are highly variable, making the diagnosis of Kabuki-like phenotypes difficult, even for experienced clinical geneticists. Herein we present molecular genetic findings of causal genetic variation using array comparative genome hybridization and a Mendeliome analysis, utilizing targeted exome analysis focusing on regions harboring rare disease-causing variants in Kabuki-like patients which remained KMT2D/KDM6A-negative. The aCGH analysis revealed a pathogenic CNV in the 14q11.2 region, while targeted exome sequencing revealed pathogenic variants in genes associated with intellectual disability (HUWE1, GRIN1), including a gene coding for mandibulofacial dysostosis with microcephaly (EFTUD2). Lower values of the MLL2-Kabuki phenotypic score are indicative of Kabuki-like phenotype (rather than true Kabuki syndrome), where aCGH and Mendeliome analyses have high diagnostic yield. Based on our findings we conclude that for new patients with Kabuki-like phenotypes it is possible to choose a specific molecular testing approach that has the highest detection rate for a given MLL2-Kabuki score, thus fostering more precise patient diagnosis and improved management in these genetically- and phenotypically heterogeneous clinical entities.

Identification of likely associations between cerebral folate deficiency and complex genetic- and metabolic pathogenesis of autism spectrum disorders by utilization of a pilot interaction modeling approach.

Recently, cerebral folate deficiency (CFD) was suggested to be involved in the pathogenesis of autism spectrum disorders (ASD). However, the exact role of folate metabolism in the pathogenesis of ASD, identification of underlying pathogenic mechanisms and impaired metabolic pathways remain unexplained. The aim of our study was to develop and test a novel, unbiased, bioinformatics approach in order to identify links between ASD and disturbed cerebral metabolism by focusing on abnormal folate metabolism, which could foster patient stratification and novel therapeutic interventions. An unbiased, automatable, computational workflow interaction model was developed using available data from public databases. The interaction network model of ASD-associated genes with known cerebral expression and function (SFARI) and metabolic networks (MetScape), including connections to known metabolic substrates, metabolites and cofactors involving folates, was established. Intersection of bioinformatically created networks resulted in a limited amount of interaction modules pointing to common disturbed metabolic pathways, linking ASD to CFD. Two independent interaction modules (comprising three pathways) covering enzymes encoded by ASD-related genes and folate cofactors utilizing enzymes were generated. Module 1 suggested possible interference of CFD with serine and lysine metabolism, while module 2 identified correlations with purine metabolism and inosine monophosphate production. Since our approach was primarily conceived as a proof of principle, further amendments of the presented initial model are necessary to obtain additional actionable outcomes. Our modelling strategy identified not only previously known interactions supported by evidence-based analyses, but also novel plausible interactions, which could be validated in subsequent functional and/or clinical studies. Autism Res 2017, 10: 1424-1435. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Modules in the metabolic network of E. coli with regulatory interactions.

We examine the modular structure of the metabolic network when combined with the regulatory network representing direct regulation of enzymes by small metabolites in E. coli. We introduce novel clustering algorithm and compare it with mainstream module detection method based on simulated annealing. Both methods identify the similar modular core. Slight but significant increase in modularity is observed after regulatory interactions addition. We also identify new functional modules in the combined network, which cannot be detected in the metabolic network only. Regulatory loops in the modules are the source of their autonomy, and allow us to hypothesise about module function.

Rhesus factor modulation of effects of smoking and age on psychomotor performance, intelligence, personality profile, and health in Czech soldiers.

BACKGROUND: Rhesus-positive and rhesus-negative persons differ in the presence-absence of highly immunogenic RhD protein on the erythrocyte membrane. This protein is a component of NH(3) or CO(2) pump whose physiological role is unknown. Several recent studies have shown that RhD positivity protects against effects of latent toxoplasmosis on motor performance and personality. It is not known, however, whether the RhD phenotype modifies exclusively the response of the body to toxoplasmosis or whether it also influences effects of other factors. METHODOLOGY/PRINCIPAL FINDINGS: In the present cohort study, we searched for the effects of age and smoking on performance, intelligence, personality and self-estimated health and wellness in about 3800 draftees. We found that the positive effect of age on performance and intelligence was stronger in RhD-positive soldiers, while the negative effect of smoking on performance and intelligence was of similar size regardless of the RhD phenotype. The effect of age on four Cattell's personality factors, i.e., dominance (E), radicalism (Q(1)), self-sentiment integration (Q(3)), and ergic tension (Q(4)), and on Cloninger's factor reward dependency (RD) was stronger for RhD-negative than RhD-positive subjects, while the effect of smoking on the number of viral and bacterial diseases was about three times stronger for RhD-negative than RhD-positive subjects. CONCLUSIONS: RhD phenotype modulates the influence not only of latent toxoplasmosis, but also of at least two other potentially detrimental factors, age and smoking, on human behavior and physiology. The negative effect of smoking on health (estimated on the basis of the self-rated number of common viral and bacterial diseases in the past year) was much stronger in RhD-negative than RhD-positive subjects. It is critically needed to confirm the differences in health response to smoking between RhD-positive and RhD-negative subjects by objective medical examination in future studies.