Genes encoding agrin (AGRN) and neurotrypsin (PRSS12) are associated with muscle mass, strength and plasma C-terminal agrin fragment concentration

Although physiological data suggest that neuromuscular junction (NMJ) dysfunction is a principal mechanism underpinning sarcopenia, genetic studies have implicated few genes involved in NMJ function. Accordingly, we explored whether genes encoding agrin (AGRN) and neurotrypsin (PRSS12) were associated with sarcopenia phenotypes: muscle mass, strength and plasma C-terminal agrin fragment (CAF). PhenoScanner was used to determine if AGRN and/or PRSS12 variants had previously been implicated with sarcopenia phenotypes. For replication, we combined genotype from whole genome sequencing with phenotypic data from 6715 GenoFit participants aged 18–83 years. Dual energy X-ray absorptiometry assessed whole body lean mass (WBLM) and appendicular lean mass (ALM), hand dynamometry determined grip strength and ELISA measured plasma CAF in a subgroup (n = 260). Follow-up analyses included eQTL analyses, carrier analyses, single-variant and gene-burden tests. rs2710873 (AGRN) and rs71608359 (PRSS12) associate with muscle mass and strength phenotypes, respectively, in the UKBB (p = 8.9 × 10−6 and p = 8.4 × 10−6) and GenoFit cohort (p = 0.019 and p = 0.014). rs2710873 and rs71608359 are eQTLs for AGRN and PRSS12, respectively, in ≥ three tissues. Compared to non-carriers, carriers of rs2710873 had 4.0% higher WBLM and ALM (both p < 0.001), and 9.5% lower CAF concentrations (p < 0.001), while carriers of rs71608359 had 2.3% lower grip strength (p = 0.034). AGRN and PRSS12 are associated with muscle strength and mass in single-variant analyses, while PRSS12 has further associations with muscle strength in gene-burden tests. Our findings provide novel evidence of the relevance of AGRN and PRSS12 to sarcopenia phenotypes and support existing physiological data illustrating the importance of the NMJ in maintaining muscle health during ageing

The Integrated Virtual Environment Rehabilitation Treadmill System

Slow gait speed and interlimb asymmetry are prevalent in a variety of disorders. Current approaches to locomotor retraining emphasize the need for appropriate feedback during intensive, task-specific practice. This paper describes the design and feasibility testing of the integrated virtual environment rehabilitation treadmill (IVERT) system intended to provide real-time, intuitive feedback regarding gait speed and asymmetry during training. The IVERT system integrates an instrumented, split-belt treadmill with a front-projection, immersive virtual environment. The novel adaptive control system uses only ground reaction force data from the treadmill to continuously update the speeds of the two treadmill belts independently, as well as to control the speed and heading in the virtual environment in real time. Feedback regarding gait asymmetry is presented 1) visually as walking a curved trajectory through the virtual environment and 2) proprioceptively in the form of different belt speeds on the split-belt treadmill. A feasibility study involving five individuals with asymmetric gait found that these individuals could effectively control the speed of locomotion and perceive gait asymmetry during the training session. Although minimal changes in overground gait symmetry were observed immediately following a single training session, further studies should be done to determine the IVERT’s potential as a tool for rehabilitation of asymmetric gait by providing patients with congruent visual and proprioceptive feedback

To memorize or to predict: Prominence labeling in conversational speech

The immense prosodic variation of natural conversational speech makes it challenging to predict which words are prosodically prominent in this genre. In this paper, we examine a new feature, accent ratio, which captures how likely it is that a word will be realized as prominent or not. We compare this feature with traditional accent prediction features (based on part of speech and N-grams) as well as with several linguistically motivated and manually labeled information structure features, such as whether a word is given, new, or contrastive. Our results show that the linguistic features do not lead to significant improvements, while accent ratio alone can yield prediction performance almost as good as the combination of any other subset of features. Moreover, this feature is useful even across genres; an accent-ratio classifier trained only on conversational speech predicts prominence with high accuracy in broadcast news. Our results suggest that carefully chosen lexicalized features can outperform less fine-grained features

Genetic variation in prostaglandin synthesis and related pathways, NSAID use and colorectal cancer risk in the Colon Cancer Family Registry

Although use of non-steroidal anti-inflammatory drugs (NSAIDs) generally decreases colorectal cancer (CRC) risk, inherited genetic variation in inflammatory pathways may alter their potential as preventive agents. We investigated whether variation in prostaglandin synthesis and related pathways influences CRC risk in the Colon Cancer Family Registry by examining associations between 192 single nucleotide polymorphisms (SNPs) and two variable nucleotide tandem repeats (VNTRs) within 17 candidate genes and CRC risk. We further assessed interactions between these polymorphisms and NSAID use on CRC risk. Using a case-unaffected-sibling-control design, this study included 1621 primary invasive CRC cases and 2592 sibling controls among Caucasian men and women aged 18–90. After adjustment for multiple comparisons, two intronic SNPs were associated with rectal cancer risk: rs11571364 in ALOX12 [ORhet/hzv = 1.87, 95% confidence interval (CI) = 1.19–2.95, P = 0.03] and rs45525634 in PTGER2 (ORhet/hzv = 0.49, 95% CI = 0.29–0.82, P = 0.03). Additionally, there was an interaction between NSAID use and the intronic SNP rs2920421 in ALOX12 on risk of CRC (P = 0.03); among those with heterozygous genotypes, risk was reduced for current NSAID users compared with never or former users (ORhet = 0.60, 95% CI = 0.45–0.80), though not among those with homozygous wild-type or variant genotypes. The results of this study suggest that genetic variation in ALOX12 and PTGER2 may affect the risk of rectal cancer. In addition, this study suggests plausible interactions between NSAID use and variants in ALOX12 on CRC risk. These results may aid in the development of genetically targeted cancer prevention strategies with NSAIDs

Genetic Detection and Characterization of Lujo Virus, a New Hemorrhagic Fever–Associated Arenavirus from Southern Africa

Lujo virus (LUJV), a new member of the family Arenaviridae and the first hemorrhagic fever–associated arenavirus from the Old World discovered in three decades, was isolated in South Africa during an outbreak of human disease characterized by nosocomial transmission and an unprecedented high case fatality rate of 80% (4/5 cases). Unbiased pyrosequencing of RNA extracts from serum and tissues of outbreak victims enabled identification and detailed phylogenetic characterization within 72 hours of sample receipt. Full genome analyses of LUJV showed it to be unique and branching off the ancestral node of the Old World arenaviruses. The virus G1 glycoprotein sequence was highly diverse and almost equidistant from that of other Old World and New World arenaviruses, consistent with a potential distinctive receptor tropism. LUJV is a novel, genetically distinct, highly pathogenic arenavirus

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Sex Determination:Why So Many Ways of Doing It?

Sexual reproduction is an ancient feature of life on earth, and the familiar X and Y chromosomes in humans and other model species have led to the impression that sex determination mechanisms are old and conserved. In fact, males and females are determined by diverse mechanisms that evolve rapidly in many taxa. Yet this diversity in primary sex-determining signals is coupled with conserved molecular pathways that trigger male or female development. Conflicting selection on different parts of the genome and on the two sexes may drive many of these transitions, but few systems with rapid turnover of sex determination mechanisms have been rigorously studied. Here we survey our current understanding of how and why sex determination evolves in animals and plants and identify important gaps in our knowledge that present exciting research opportunities to characterize the evolutionary forces and molecular pathways underlying the evolution of sex determination