Neuropsychological effects of the CSMD1 genome‐wide associated schizophrenia risk variant rs10503253

The single‐nucleotide polymorphism (SNP) rs10503253, located within the CUB and Sushi multiple domains‐1 (CSMD1) gene on 8p23.2, was recently identified as genome‐wide significant for schizophrenia (SZ), but is of unknown function. We investigated the neurocognitive effects of this CSMD1 variant in vivo in patients and healthy participants using behavioral and imaging measures of brain structure and function. We compared carriers and non‐carriers of the risk ‘A’ allele on measures of neuropsychological performance typically impaired in SZ (general cognitive ability, episodic and working memory and attentional control) in independent samples of Irish patients (n = 387) and controls (n = 171) and German patients (205) and controls (n = 533). Across these groups, the risk ‘A’ allele at CSMD1 was associated with deleterious effects across a number of neurocognitive phenotypes. Specifically, the risk allele was associated with poorer performance on neuropsychological measures of general cognitive ability and memory function but not attentional control. These effects, while significant, were subtle, and varied between samples. Consistent with previous evidence suggesting that CSMD1 may be involved in brain mechanisms related to memory and learning, these data appear to reflect the deleterious effects of the identified ‘A’ risk allele on neurocognitive function, possibly as part of the mechanism by which CSMD1 is associated with SZ risk.     

Towards Precision Medicine: Advances in Computational Approaches for the Analysis of Human Variants

Variations and similarities in our individual genomes are part of our history, our heritage, and our identity. Some human genomic variants are associated with common traits such as hair and eye color, while others are associated with susceptibility to disease or response to drug treatment. Identifying the human variations producing clinically relevant phenotypic changes is critical for providing accurate and personalized diagnosis, prognosis, and treatment for diseases. Furthermore, a better understanding of the molecular underpinning of disease can lead to development of new drug targets for precision medicine. Several resources have been designed for collecting and storing human genomic variations in highly structured, easily accessible databases. Unfortunately, a vast amount of information about these genetic variants and their functional and phenotypic associations is currently buried in the literature, only accessible by manual curation or sophisticated text text-mining technology to extract the relevant information. In addition, the low cost of sequencing technologies coupled with increasing computational power has enabled the development of numerous computational methodologies to predict the pathogenicity of human variants. This review provides a detailed comparison of current human variant resources, including HGMD, OMIM, ClinVar, and UniProt/Swiss-Prot, followed by an overview of the computational methods and techniques used to leverage the available data to predict novel deleterious variants. We expect these resources and tools to become the foundation for understanding the molecular details of genomic variants leading to disease, which in turn will enable the promise of precision medicine.     

Reliability of surface EMG matrix in locating the innervation zone of upper trapezius muscle

The identification of the motor unit (MU) innervation zone (IZ) using surface electromyographic (sEMG) signals detected on the skin with a linear array or a matrix of electrodes has been recently proposed in the literature. However, an analysis of the reliability of this procedure and, therefore, of the suitability of the sEMG signals for this purpose has not been reported.The purpose of this work is to describe the intra and inter-rater reliability and the suitability of surface EMG in locating the innervation zone of the upper trapezius muscle.Two operators were trained on electrode matrix positioning and sEMG signal analysis. Ten healthy subjects, instructed to perform a series of isometric contractions of the upper trapezius muscle participated in the study. The two operators collected sEMG signals and then independently estimated the IZ location through visual analysis.Results showed an almost perfect agreement for intra-rater and inter-rater reliability. The constancy of IZ location could be affected by the factors reflecting the population of active MUs and their IZs, including: the contraction intensity, the acquisition period analyzed, the contraction repetition. In almost all cases the IZ location shift due to these factors did not exceed 4 mm. Results generalization to other muscles should be made with caution.     

Genome-Wide Association Analysis Identifies a Genetic Basis of Infectivity in a Model Bacterial Pathogen

Knowledge of the genetic architecture of pathogen infectivity and host resistance is essential for a mechanistic understanding of coevolutionary processes, yet the genetic basis of these interacting traits remains unknown for most host–pathogen systems. We used a comparative genomic approach to explore the genetic basis of infectivity in Pasteuria ramosa, a Gram-positive bacterial pathogen of planktonic crustaceans that has been established as a model for studies of Red Queen host–pathogen coevolution. We sequenced the genomes of a geographically, phenotypically, and genetically diverse collection of P. ramosa strains and performed a genome-wide association study to identify genetic correlates of infection phenotype. We found multiple polymorphisms within a single gene, Pcl7, that correlate perfectly with one common and widespread infection phenotype. We then confirmed this perfect association via Sanger sequencing in a large and diverse sample set of P. ramosa clones. Pcl7 codes for a collagen-like protein, a class of adhesion proteins known or suspected to be involved in the infection mechanisms of a number of important bacterial pathogens. Consistent with expectations under Red Queen coevolution, sequence variation of Pcl7 shows evidence of balancing selection, including extraordinarily high diversity and absence of geographic structure. Based on structural homology with a collagen-like protein of Bacillus anthracis, we propose a hypothesis for the structure of Pcl7 and the physical location of the phenotype-associated polymorphisms. Our results offer strong evidence for a gene governing infectivity and provide a molecular basis for further study of Red Queen dynamics in this model host–pathogen system.     

Trans-ancestral fine-mapping of MHC reveals key amino acids associated with spontaneous clearance of hepatitis C in HLA-DQβ1

Spontaneous clearance of acute hepatitis C virus (HCV) infection is associated with single nucleotide polymorphisms (SNPs) on the MHC class II. We fine-mapped the MHC region in European (n = 1,600; 594 HCV clearance/1,006 HCV persistence) and African (n = 1,869; 340 HCV clearance/1,529 HCV persistence) ancestry individuals and evaluated HCV peptide binding affinity of classical alleles. In both populations, HLA-DQβ1Leu26 (p value_Meta = 1.24 × 10^?14) located in pocket 4 was negatively associated with HCV spontaneous clearance and HLA-DQβ1Pro55 (p value_Meta = 8.23 × 10^?11) located in the peptide binding region was positively associated, independently of HLA-DQβ1Leu26. These two amino acids are not in linkage disequilibrium (r² < 0.1) and explain the SNPs and classical allele associations represented by rs2647011, rs9274711, HLA-DQB1¹03:01, and HLA-DRB1¹01:01. Additionally, HCV persistence classical alleles tagged by HLA-DQβ1Leu26 had fewer HCV binding epitopes and lower predicted binding affinities compared to clearance alleles (geometric mean of combined IC₅₀ nM of persistence versus clearance; 2,321 nM versus 761.7 nM, p value = 1.35 × 10^?38). In summary, MHC class II fine-mapping revealed key amino acids in HLA-DQβ1 explaining allelic and SNP associations with HCV outcomes. This mechanistic advance in understanding of natural recovery and immunogenetics of HCV might set the stage for much needed enhancement and design of vaccine to promote spontaneous clearance of HCV infection.     

Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene‐mapping approach

Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small‐effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine‐spined sticklebacks (Pungitius pungitius) with the aid of novel multilocus QTL‐mapping approaches based on a de‐biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL‐mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single‐locus analyses of an F₂ interpopulation cross with 239 individuals and 15 198, fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multilocus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multilocus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1–6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small‐effect loci. Apart from suggesting moderately heritable (h² ≈ 0.15–0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL‐mapping approach developed here has distinctive advantages over the traditional QTL‐mapping methods in analyses of dense marker panels.     

Viscosity-mediated motion coupling between pairs of trichobothria on the leg of the spider <Emphasis Type="Italic">Cupiennius salei</Emphasis>

Arachnids and insects use long, thin hairs as motion sensors to detect signals contained in the movement of the surrounding air. These hairs often form groups with a small spacing of tens to hundreds of micrometers between them. For air oscillation frequencies of biological interest, the potential exists for viscosity-mediated coupling among hairs in a group affecting their response characteristics. Even a small diameter hair can, in principle, affect the flow field around it and the dynamics of the hairs in its neighborhood. The viscosity-mediated coupling between a pair of hairs is investigated here both experimentally and theoretically. The conditions for the existence of the coupling effect, and its magnitude as a function of relevant parameters, are determined. In the range of biologically relevant frequencies (30–300 Hz), viscous coupling between pairs of hairs is only very small in the case of the spider Cupiennius salei. Theoretical analysis points to the relatively large spacing between hairs (20 to 50 hair diameters) and the tuning of the hairs to the above-mentioned frequencies to explain the practical absence of coupling.     

Telomere length and metabolic syndrome traits: A Mendelian randomisation study

Observational studies have revealed associations between short leucocyte telomere length (LTL), a TL marker in somatic tissues and multiple Metabolic Syndrome (MetS) traits. Animal studies have supported these findings by showing that increased telomere attrition leads to adipose tissue dysfunction and insulin resistance. We investigated the associations between genetically instrumented LTL and MetS traits using Mendelian Randomisation (MR). Fifty‐two independent variants identified at FDR<0.05 from a genome‐wide association study (GWAS) including 78,592 Europeans and collectively accounting for 2.93% of LTL variance were selected as genetic instruments for LTL. Summary‐level data for MetS traits and for the MetS as a binary phenotype were obtained from the largest publicly available GWAS and two‐sample MR analyses were used to estimate the associations of LTL with these traits. The combined effect of the genetic instruments was modelled using inverse variance weighted regression and sensitivity analyses with MR‐Egger, weighted‐median and MR‐PRESSO were performed to test for and correct horizonal pleiotropy. Genetically instrumented longer LTL was associated with higher waist‐to‐hip ratio adjusted for body mass index (β = 0.045 SD, SE = 0.018, p = 0.01), raised systolic (β = 1.529 mmHg, SE = 0.332, p = 4x10⁻⁶) and diastolic (β = 0.633 mmHg, SE = 0.222, p = 0.004) blood pressure, and increased MetS risk (OR = 1.133, 95% CI 1.057–1.215). Consistent results were obtained in sensitivity analyses, which provided no evidence of unbalanced horizontal pleiotropy. Telomere shortening might not be a major driver of cellular senescence and dysfunction in human adipose tissue. Future experimental studies should examine the mechanistic bases for the links between longer LTL and increased upper‐body fat distribution and raised blood pressure.