Mutations in NSUN2 Cause Autosomal- Recessive Intellectual Disability

With a prevalence between 1 and 3%, hereditary forms of intellectual disability (ID) are among the most important problems in health care. Particularly, autosomal-recessive forms of the disorder have a very heterogeneous molecular basis, and genes with an increased number of disease-causing mutations are not common. Here, we report on three different mutations (two nonsense mutations, c.679C>T [p.Gln227∗] and c.1114C>T [p.Gln372∗], as well as one splicing mutation, g.6622224A>C [p.Ile179Argfs∗192]) that cause a loss of the tRNA-methyltransferase-encoding NSUN2 main transcript in homozygotes. We identified the mutations by sequencing exons and exon-intron boundaries within the genomic region where the linkage intervals of three independent consanguineous families of Iranian and Kurdish origin overlapped with the previously described MRT5 locus. In order to gain further evidence concerning the effect of a loss of NSUN2 on memory and learning, we constructed a Drosophila model by deleting the NSUN2 ortholog, CG6133, and investigated the mutants by using molecular and behavioral approaches. When the Drosophila melanogaster NSUN2 ortholog was deleted, severe short-term-memory (STM) deficits were observed; STM could be rescued by re-expression of the wild-type protein in the nervous system. The humans homozygous for NSUN2 mutations showed an overlapping phenotype consisting of moderate to severe ID and facial dysmorphism (which includes a long face, characteristic eyebrows, a long nose, and a small chin), suggesting that mutations in this gene might even induce a syndromic form of ID. Moreover, our observations from the Drosophila model point toward an evolutionarily conserved role of RNA methylation in normal cognitive development

Enhancing precision in human neuroscience

Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability – in science in general, but also specifically in human neuroscience – have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience

C3 Peptide Promotes Axonal Regeneration and Functional Motor Recovery after Peripheral Nerve Injury

Peripheral nerve injuries are frequently seen in trauma patients and due to delayed nerve repair, lifelong disabilities often follow this type of injury. Innovative therapies are needed to facilitate and expedite peripheral nerve regeneration. The purpose of this study was to determine the effects of a 1-time topical application of a 26-amino-acid fragment (C3156-181), derived from the Clostridium botulinum C3-exoenzyme, on peripheral nerve regeneration in 2 models of nerve injury and repair in adult rats. After sciatic nerve crush, different dosages of C3156-181 dissolved in buffer or reference solutions (nerve growth factor or C3bot-wild-type protein) or vehicle-only were injected through an epineurial opening into the lesion sites. After 10-mm nerve autotransplantation, either 8.0 nmol/kg C3156-181 or vehicle were injected into the proximal and distal suture sites. For a period of 3 to 10 postoperative weeks, C3156-181-treated animals showed a faster motor recovery than control animals. After crush injury, axonal outgrowth and elongation were activated and consequently resulted in faster motor recovery. The nerve autotransplantation model further elucidated that C3156-181 treatment accounts for better axonal elongation into motor targets and reduced axonal sprouting, which are followed by enhanced axonal maturation and better axonal functionality. The effects of C3156-181 are likely caused by a nonenzymatic down-regulation of active RhoA. Our results indicate the potential of C3156-181 as a therapeutic agent for the topical treatment of peripheral nerve repair sites

Personality network neuroscience: Promises and challenges on the way toward a unifying framework of individual variability

We propose that the application of network theory to established psychological personality conceptions has great potential to advance a biologically plausible model of human personality. Stable behavioral tendencies are conceived as personality “traits.” Such traits demonstrate considerable variability between individuals, and extreme expressions represent risk factors for psychological disorders. Although the psychometric assessment of personality has more than hundred years tradition, it is not yet clear whether traits indeed represent “biophysical entities” with specific and dissociable neural substrates. For instance, it is an open question whether there exists a correspondence between the multilayer structure of psychometrically derived personality factors and the organizational properties of traitlike brain systems. After a short introduction into fundamental personality conceptions, this article will point out how network neuroscience can enhance our understanding about human personality. We will examine the importance of intrinsic (task-independent) brain connectivity networks and show means to link brain features to stable behavioral tendencies. Questions and challenges arising from each discipline itself and their combination are discussed and potential solutions are developed. We close by outlining future trends and by discussing how further developments of network neuroscience can be applied to personality research.Peer Reviewe

ADHD symptoms are associated with the modular structure of intrinsic brain networks in a representative sample of healthy adults

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders with significant and often lifelong effects on social, emotional, and cognitive functioning. Influential neurocognitive models of ADHD link behavioral symptoms to altered connections between and within functional brain networks. Here, we investigate whether network-based theories of ADHD can be generalized to understanding variations in ADHD-related behaviors within the normal (i.e., clinically unaffected) adult population. In a large and representative sample, self-rated presence of ADHD symptoms varied widely; only eight out of 291 participants scored in the clinical range. Subject-specific brain-network graphs were modeled from functional MRI resting-state data and revealed significant associations between (non-clinical) ADHD symptoms and region-specific profiles of between-module and within-module connectivity. Effects were located in brain regions associated with multiple neuronal systems including the default-mode network, the salience network, and the central executive system. Our results are consistent with network perspectives of ADHD and provide further evidence for the relevance of an appropriate information transfer between task-negative (default-mode) and task-positive brain regions. More generally, our findings support a dimensional conceptualization of ADHD and contribute to a growing understanding of cognition as an emerging property of functional brain networks