Neurologic Correlates of Gait Abnormalities in Cerebral Palsy: Implications for Treatment

Cerebral palsy (CP) is the most common movement disorder in children. A diagnosis of CP is often made based on abnormal muscle tone or posture, a delay in reaching motor milestones, or the presence of gait abnormalities in young children. Neuroimaging of high-risk neonates and of children diagnosed with CP have identified patterns of neurologic injury associated with CP, however, the neural underpinnings of common gait abnormalities remain largely uncharacterized. Here, we review the nature of the brain injury in CP, as well as the neuromuscular deficits and subsequent gait abnormalities common among children with CP. We first discuss brain injury in terms of mechanism, pattern, and time of injury during the prenatal, perinatal, or postnatal period in preterm and term-born children. Second, we outline neuromuscular deficits of CP with a focus on spastic CP, characterized by muscle weakness, shortened muscle-tendon unit, spasticity, and impaired selective motor control, on both a microscopic and functional level. Third, we examine the influence of neuromuscular deficits on gait abnormalities in CP, while considering emerging information on neural correlates of gait abnormalities and the implications for strategic treatment. This review of the neural basis of gait abnormalities in CP discusses what is known about links between the location and extent of brain injury and the type and severity of CP, in relation to the associated neuromuscular deficits, and subsequent gait abnormalities. Targeted treatment opportunities are identified that may improve functional outcomes for children with CP. By providing this context on the neural basis of gait abnormalities in CP, we hope to highlight areas of further research that can reduce the long-term, debilitating effects of CP

Routine Clustering of Mobile Sensor Data Facilitates Psychotic Relapse Prediction in Schizophrenia Patients

We aim to develop clustering models to obtain behavioral representations from continuous multimodal mobile sensing data towards relapse prediction tasks. The identified clusters could represent different routine behavioral trends related to daily living of patients as well as atypical behavioral trends associated with impending relapse. We used the mobile sensing data obtained in the CrossCheck project for our analysis. Continuous data from six different mobile sensing-based modalities (e.g. ambient light, sound/conversation, acceleration etc.) obtained from a total of 63 schizophrenia patients, each monitored for up to a year, were used for the clustering models and relapse prediction evaluation. Two clustering models, Gaussian Mixture Model (GMM) and Partition Around Medoids (PAM), were used to obtain behavioral representations from the mobile sensing data. The features obtained from the clustering models were used to train and evaluate a personalized relapse prediction model using Balanced Random Forest. The personalization was done by identifying optimal features for a given patient based on a personalization subset consisting of other patients who are of similar age. The clusters identified using the GMM and PAM models were found to represent different behavioral patterns (such as clusters representing sedentary days, active but with low communications days, etc.). Significant changes near the relapse periods were seen in the obtained behavioral representation features from the clustering models. The clustering model based features, together with other features characterizing the mobile sensing data, resulted in an F2 score of 0.24 for the relapse prediction task in a leave-one-patient-out evaluation setting. This obtained F2 score is significantly higher than a random classification baseline with an average F2 score of 0.042

Androgen receptor phosphorylation at serine 308 and serine 791 predicts enhanced survival in castrate resistant prostate cancer patients

We previously reported that AR phosphorylation at serine 213 was associated with poor outcome and may contribute to prostate cancer development and progression. This study investigates if specific AR phosphorylation sites have differing roles in the progression of hormone naïve prostate cancer (HNPC) to castrate resistant disease (CRPC). A panel of phosphospecific antibodies were employed to study AR phosphorylation in 84 matched HNPC and CRPC tumours. Immunohistochemistry measured Androgen receptor expression phosphorylated at serine residues 94 (pAR<sub>94</sub>), 308 (pAR<sub>308</sub>), 650(pAR<sub>650</sub>) and 791(pAR<sub>791</sub>). No correlations with clinical parameters were observed for pAR<sub>94</sub> or pAR<sub>650</sub> in HNPC or CRPC tumours. In contrast to our previous observation with serine 213, high pAR<sub>308</sub> is significantly associated with a longer time to disease specific death (p= 0.011) and high pAR<sub>791</sub> expression significantly associated with a longer time to disease recurrence (p= 0.018) in HNPC tumours and longer time to death from disease recurrence (p= 0.040) in CRPC tumours. This observation in CRPC tumours was attenuated in high apoptotic tumours (p= 0.022) and low proliferating tumours (p= 0.004). These results demonstrate that understanding the differing roles of AR phosphorylation is necessary before this can be exploited as a target for castrate resistant prostate cancer

Hydrogen Sulfide Promotes Tet1- and Tet2-mediated Foxp3 Demethylation to Drive Regulatory T Cell Differentiation and Maintain Immune Homeostasis

Regulatory T (Treg) cells are essential for maintenance of immune homeostasis. Here we found that hydrogen sulfide (H2S) was required for Foxp3+ Treg cell differentiation and function, and that H2S deficiency led to systemic autoimmune disease. H2S maintained expression of methylcytosine dioxygenases Tet1 and Tet2 by sulfhydrating nuclear transcription factor Y subunit beta (NFYB) to facilitate its binding to Tet1 and Tet2 promoters. Transforming growth factor-β (TGF-β)-activated Smad3 and interleukin-2 (IL-2)-activated Stat5 facilitated Tet1 and Tet2 binding to Foxp3. Tet1 and Tet2 catalyzed conversion of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) in Foxp3 to establish a Treg cell-specific hypomethylation pattern and stable Foxp3 expression. Consequently, Tet1 and Tet2 deletion led to Foxp3 hypermethylation, impaired Treg cell differentiation and function, and autoimmune disease. Thus, H2S promotes Tet1 and Tet2 expression, which are recruited to Foxp3 by TGF-β and IL-2 signaling to maintain Foxp3 demethylation and Treg cell-associated immune homeostasis

Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce \u27annotation principal components\u27, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol

Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease

Pharmaceutical drugs targeting dyslipidemia and cardiovascular disease (CVD) may increase the risk of fatty liver disease and other metabolic disorders. To identify potential novel CVD drug targets without these adverse effects, we perform genome-wide analyses of participants in the HUNT Study in Norway (n = 69,479) to search for protein-altering variants with beneficial impact on quantitative blood traits related to cardiovascular disease, but without detrimental impact on liver function. We identify 76 (11 previously unreported) presumed causal protein-altering variants associated with one or more CVD- or liver-related blood traits. Nine of the variants are predicted to result in loss-of-function of the protein. This includes ZNF529:p.K405X, which is associated with decreased low-density-lipoprotein (LDL) cholesterol (P = 1.3 × 10-8) without being associated with liver enzymes or non-fasting blood glucose. Silencing of ZNF529 in human hepatoma cells results in upregulation of LDL receptor and increased LDL uptake in the cells. This suggests that inhibition of ZNF529 or its gene product should be prioritized as a novel candidate drug target for treating dyslipidemia and associated CVD

Single-cell RNA-seq reveals transcriptomic heterogeneity mediated by host-pathogen dynamics in lymphoblastoid cell lines

Lymphoblastoid cell lines (LCLs) are generated by transforming primary B cells with Epstein-Barr virus (EBV) and are used extensively as model systems in viral oncology, immunology, and human genetics research. In this study, we characterized single-cell transcriptomic profiles of five LCLs and present a simple discrete-time simulation to explore the influence of stochasticity on LCL clonal evolution. Single-cell RNA sequencing (scRNA-seq) revealed substantial phenotypic heterogeneity within and across LCLs with respect to immunoglobulin isotype; virus-modulated host pathways involved in survival, activation, and differentiation; viral replication state; and oxidative stress. This heterogeneity is likely attributable to intrinsic variance in primary B cells and host-pathogen dynamics. Stochastic simulations demonstrate that initial primary cell heterogeneity, random sampling, time in culture, and even mild differences in phenotype-specific fitness can contribute substantially to dynamic diversity in populations of nominally clonal cells