High and low levels of an NTRK2-driven genetic profile affect motor- and cognition-associated frontal gray matter in prodromal Huntington’s disease

This study assessed how BDNF (brain-derived neurotrophic factor) and other genes involved in its signaling influence brain structure and clinical functioning in pre-diagnosis Huntington’s disease (HD). Parallel independent component analysis (pICA), a multivariate method for identifying correlated patterns in multimodal datasets, was applied to gray matter concentration (GMC) and genomic data from a sizeable PREDICT-HD prodromal cohort (N = 715). pICA identified a genetic component highlighting NTRK2, which encodes BDNF’s TrkB receptor, that correlated with a GMC component including supplementary motor, precentral/premotor cortex, and other frontal areas (p < 0.001); this association appeared to be driven by participants with high or low levels of the genetic profile. The frontal GMC profile correlated with cognitive and motor variables (Trail Making Test A (p = 0.03); Stroop Color (p = 0.017); Stroop Interference (p = 0.04); Symbol Digit Modalities Test (p = 0.031); Total Motor Score (p = 0.01)). A top-weighted NTRK2 variant (rs2277193) was protectively associated with Trail Making Test B (p = 0.007); greater minor allele numbers were linked to a better performance. These results support the idea of a protective role of NTRK2 in prodromal HD, particularly in individuals with certain genotypes, and suggest that this gene may influence the preservation of frontal gray matter that is important for clinical functioning.This project was supported by 1U01NS082074 (V.C. and J.T., co-principal investigators) from the National Institutes of Health, National Institute of Neurological Disorders and Stroke. The PREDICT-HD study was supported by NIH/NINDS grant 5R01NS040068 awarded to J.P.; CHDI Foundation, Inc., A3917 and 6266 awarded to J.P.; Cognitive and Functional Brain Changes in Preclinical Huntington’s Disease (HD) 5R01NS054893 awarded to J.P.; 4D Shape Analysis for Modeling Spatiotemporal Change Trajectories in Huntington’s 1U01NS082086; Functional Connectivity in Premanifest Huntington’s Disease 1U01NS082083; and Basal Ganglia Shape Analysis and Circuitry in Huntington’s Disease 1U01NS082085 awarded to Christopher A. Ross

Clinical and biomarker changes in premanifest Huntington disease show trial feasibility: A decade of the PREDICT-HD study

There is growing consensus that intervention and treatment of Huntington disease (HD) should occur at the earliest stage possible. Various early-intervention methods for this fatal neurodegenerative disease have been identified, but preventive clinical trials for HD are limited by a lack of knowledge of the natural history of the disease and a dearth of appropriate outcome measures. Objectives of the current study are to document the natural history of premanifest HD progression in the largest cohort ever studied and to develop a battery of imaging and clinical markers of premanifest HD progression that can be used as outcome measures in preventive clinical trials. Neurobiological predictors of Huntington’s disease is a 32-site, international, observational study of premanifest HD, with annual examination of 1013 participants with premanifest HD and 301 gene-expansion negative controls between 2001 and 2012. Findings document 39 variables representing imaging, motor, cognitive, functional, and psychiatric domains, showing different rates of decline between premanifest HD and controls. Required sample size and models of premanifest HD are presented to inform future design of clinical and preclinical research. Preventive clinical trials in premanifest HD with participants who have a medium or high probability of motor onset are calculated to be as resource-effective as those conducted in diagnosed HD and could interrupt disease 7–12years earlier. Methods and measures for preventive clinical trials in premanifest HD more than a dozen years from motor onset are also feasible. These findings represent the most thorough documentation of a clinical battery for experimental therapeutics in stages of premanifest HD, the time period for which effective intervention may provide the most positive possible outcome for patients and their families affected by this devastating disease

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Arg-Thz is a minimal substrate for the N-alpha,N-alpha-arginyl methyltransferase involved in the biosynthesis of plantazolicin

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The final biosynthetic step towards plantazolicin (PZN) comprises Nα,Nα-arginyl methyltransferase (PznL) mediated N-terminal bismethylation. We show that PznL processes truncated desmethyl-plantazolicin analogues, but only those with an N-terminal guanidine side chain derived from arginine. PznL specificity, which is narrow, depends on the side chain of the N-terminal amino acid linked to an azole, and not so much on the number of azoles.DFG, EXC 314, Unifying Concepts in Catalysi

Structural aspects of phenylglycines, their biosynthesis and occurrence in peptide natural products

Phenylglycine-type amino acids occur in a wide variety of peptide natural products, including glycopeptide antibiotics and biologically active linear and cyclic peptides. Sequencing of biosynthesis gene clusters of chloroeremomycin, balhimycin and pristinamycin paved the way for intensive investigations on the biosynthesis of 4-hydroxyphenylglycine (Hpg), 3,5-dihydroxyphenylglycine (Dpg) and phenylglycine (Phg) in recent years. The significance and importance of this type of unusual non-proteinogenic aromatic amino acids also for medicinal chemistry has drawn the attention of many research groups and pharmaceutical companies. Herein structures and properties of phenylglycine containing natural products as well as the biosynthetic origin and incorporation of phenylglycines are discussed.DFG, EXC 314, Unifying Concepts in CatalysisEC/FP7/613877/EU/Rewiring the Streptomyces cell factory for cost-effective production of biomolecules/STREPSYNTHDFG, CR 392/1-1, Structural and mechanistic investigation of the Cytochrome P450 enzymes in vancomycin biosynthesis: potential biocatalysts for the development of new antibiotic

Efektivní, jednoduchá aproximace velkých roztroušených 3D vektorových dat pomocí dělení prostoru

Aproximace RBF (Radialní Básové Funkce) je efektivní metoda pro rozptýlená skalární a vektorová pole. Její použití je však v případě velkých rozptýlených dat velmi obtížné. Tato práce prezentuje RBF aproximaci spolu s prostorovou dělící technikou pro velká vektorová pole. Pro velké rozptýlené datové sady je použita technika dělení prostoru s překrývajícími se 3D buňkami. Sloučení překrývajících se 3D buněk se používá k dosažení kontinuity a hladkosti. Navrhovaná metoda je použitelná i pro skalární a vektorové datové sady. Experimenty prokázaly použitelnost tohoto přístupu a jsou prezentovány výsledky s datovým souborem velkého vektorového pole tornáda.The Radial basis function (RBF) approximation is an efficient method for scattered scalar and vector data fields. However its application is very difficult in the case of large scattered data. This paper presents RBF approximation together with space subdivision technique for large vector fields. For large scattered data sets a space subdivision technique with overlapping 3D cells is used. Blending of overlapped 3D cells is used to obtain continuity and smoothness. The proposed method is applicable for scalar and vector data sets as well. Experiments proved applicability of this approach and results with the tornado large vector field data set are presented