A liver immune rheostat regulates CD8 T cell immunity in chronic HBV infection.

Chronic hepatitis B virus (HBV) infection affects 300 million patients worldwide1,2, in whom virus-specific CD8 T cells by still ill-defined mechanisms lose their function and cannot eliminate HBV-infected hepatocytes3-7. Here we demonstrate that a liver immune rheostat renders virus-specific CD8 T cells refractory to activation and leads to their loss of effector functions. In preclinical models of persistent infection with hepatotropic viruses such as HBV, dysfunctional virus-specific CXCR6+ CD8 T cells accumulated in the liver and, as a characteristic hallmark, showed enhanced transcriptional activity of cAMP-responsive element modulator (CREM) distinct from T cell exhaustion. In patients with chronic hepatitis B, circulating and intrahepatic HBV-specific CXCR6+ CD8 T cells with enhanced CREM expression and transcriptional activity were detected at a frequency of 12-22% of HBV-specific CD8 T cells. Knocking out the inhibitory CREM/ICER isoform in T cells, however, failed to rescue T cell immunity. This indicates that CREM activity was a consequence, rather than the cause, of loss in T cell function, further supported by the observation of enhanced phosphorylation of protein kinase A (PKA) which is upstream of CREM. Indeed, we found that enhanced cAMP-PKA-signalling from increased T cell adenylyl cyclase activity augmented CREM activity and curbed T cell activation and effector function in persistent hepatic infection. Mechanistically, CD8 T cells recognizing their antigen on hepatocytes established close and extensive contact with liver sinusoidal endothelial cells, thereby enhancing adenylyl cyclase-cAMP-PKA signalling in T cells. In these hepatic CD8 T cells, which recognize their antigen on hepatocytes, phosphorylation of key signalling kinases of the T cell receptor signalling pathway was impaired, which rendered them refractory to activation. Thus, close contact with liver sinusoidal endothelial cells curbs the activation and effector function of HBV-specific CD8 T cells that target hepatocytes expressing viral antigens by means of the adenylyl cyclase-cAMP-PKA axis in an immune rheostat-like fashion.

Longitudinal Analysis of Multiple Neurotransmitter Metabolites in Cerebrospinal Fluid in Early Parkinson's Disease.

BACKGROUND: Cerebrospinal fluid (CSF) levels of monoamine metabolites may represent biomarkers of Parkinson's disease (PD). OBJECTIVE: The aim of this study was quantification of multiple metabolites in CSF from PD versus healthy control subjects (HCs), including longitudinal analysis. METHODS: Absolute levels of multiple monoamine metabolites in CSF were quantified by liquid chromatography coupled with tandem mass spectrometry from 161 individuals with early PD and 115 HCs from the Parkinson's Progression Marker Initiative and de novo PD (DeNoPA) studies. RESULTS: Baseline levels of homovanillic acid (HVA) and 3,4-dihydroxyphenylacetic acid (DOPAC) were lower in individuals with PD compared with HCs. HVA levels correlated with Movement Disorder Society Unified Parkinson's Disease Rating Scale total scores (P < 0.01). Both HVA/dopamine and DOPAC/dopamine levels correlated with caudate nucleus and raw DOPAC with putamen dopamine transporter single-photon emission computed tomography uptake ratios (P < 0.01). No metabolite changed over 2 years in drug-naive individuals, but some changed on starting levodopa treatment. CONCLUSIONS: HVA and DOPAC CSF levels mirrored nigrostriatal pathway damage, confirming the central role of dopaminergic degeneration in early PD. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial.

BACKGROUND: Ubiquitous digital technologies such as smartphone sensors promise to fundamentally change biomedical research and treatment monitoring in neurological diseases such as PD, creating a new domain of digital biomarkers. OBJECTIVES: The present study assessed the feasibility, reliability, and validity of smartphone-based digital biomarkers of PD in a clinical trial setting. METHODS: During a 6-month, phase 1b clinical trial with 44 Parkinson participants, and an independent, 45-day study in 35 age-matched healthy controls, participants completed six daily motor active tests (sustained phonation, rest tremor, postural tremor, finger-tapping, balance, and gait), then carried the smartphone during the day (passive monitoring), enabling assessment of, for example, time spent walking and sit-to-stand transitions by gyroscopic and accelerometer data. RESULTS: Adherence was acceptable: Patients completed active testing on average 3.5 of 7 times/week. Sensor-based features showed moderate-to-excellent test-retest reliability (average intraclass correlation coefficient = 0.84). All active and passive features significantly differentiated PD from controls with P < 0.005. All active test features except sustained phonation were significantly related to corresponding International Parkinson and Movement Disorder Society-Sponsored UPRDS clinical severity ratings. On passive monitoring, time spent walking had a significant (P = 0.005) relationship with average postural instability and gait disturbance scores. Of note, for all smartphone active and passive features except postural tremor, the monitoring procedure detected abnormalities even in those Parkinson participants scored as having no signs in the corresponding International Parkinson and Movement Disorder Society-Sponsored UPRDS items at the site visit. CONCLUSIONS: These findings demonstrate the feasibility of smartphone-based digital biomarkers and indicate that smartphone-sensor technologies provide reliable, valid, clinically meaningful, and highly sensitive phenotypic data in Parkinson's disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

NEMix: single-cell nested effects models for probabilistic pathway stimulation.

Nested effects models have been used successfully for learning subcellular networks from high-dimensional perturbation effects that result from RNA interference (RNAi) experiments. Here, we further develop the basic nested effects model using high-content single-cell imaging data from RNAi screens of cultured cells infected with human rhinovirus. RNAi screens with single-cell readouts are becoming increasingly common, and they often reveal high cell-to-cell variation. As a consequence of this cellular heterogeneity, knock-downs result in variable effects among cells and lead to weak average phenotypes on the cell population level. To address this confounding factor in network inference, we explicitly model the stimulation status of a signaling pathway in individual cells. We extend the framework of nested effects models to probabilistic combinatorial knock-downs and propose NEMix, a nested effects mixture model that accounts for unobserved pathway activation. We analyzed the identifiability of NEMix and developed a parameter inference scheme based on the Expectation Maximization algorithm. In an extensive simulation study, we show that NEMix improves learning of pathway structures over classical NEMs significantly in the presence of hidden pathway stimulation. We applied our model to single-cell imaging data from RNAi screens monitoring human rhinovirus infection, where limited infection efficiency of the assay results in uncertain pathway stimulation. Using a subset of genes with known interactions, we show that the inferred NEMix network has high accuracy and outperforms the classical nested effects model without hidden pathway activity. NEMix is implemented as part of the R/Bioconductor package 'nem' and available at www.cbg.ethz.ch/software/NEMix.

Simultaneous analysis of large-scale RNAi screens for pathogen entry.

BACKGROUND: Large-scale RNAi screening has become an important technology for identifying genes involved in biological processes of interest. However, the quality of large-scale RNAi screening is often deteriorated by off-targets effects. In order to find statistically significant effector genes for pathogen entry, we systematically analyzed entry pathways in human host cells for eight pathogens using image-based kinome-wide siRNA screens with siRNAs from three vendors. We propose a Parallel Mixed Model (PMM) approach that simultaneously analyzes several non-identical screens performed with the same RNAi libraries. RESULTS: We show that PMM gains statistical power for hit detection due to parallel screening. PMM allows incorporating siRNA weights that can be assigned according to available information on RNAi quality. Moreover, PMM is able to estimate a sharedness score that can be used to focus follow-up efforts on generic or specific gene regulators. By fitting a PMM model to our data, we found several novel hit genes for most of the pathogens studied. CONCLUSIONS: Our results show parallel RNAi screening can improve the results of individual screens. This is currently particularly interesting when large-scale parallel datasets are becoming more and more publicly available. Our comprehensive siRNA dataset provides a public, freely available resource for further statistical and biological analyses in the high-content, high-throughput siRNA screening field.

Implications of Ocular Confounding Factors for Aqueous Humor Proteomic and Metabolomic Analyses in Retinal Diseases.

Purpose: To assess the impact of ocular confounding factors on aqueous humor (AH) proteomic and metabolomic analyses for retinal disease characterization. Methods: This study recruited 138 subjects (eyes): 102 with neovascular age-related macular degeneration (nAMD), 18 with diabetic macular edema (DME), and 18 with cataract (control group). AH samples underwent analysis using Olink Target 96 proteomics and Metabolon's metabolomics platform Data analysis included correlation, differential abundance, and gene-set analysis. Results: In total, 756 proteins and 408 metabolites were quantified in AH. Total AH protein concentration was notably higher in nAMD (3.2-fold) and DME (4.1-fold) compared to controls. Pseudophakic eyes showed higher total AH protein concentrations than phakic eyes (e.g., 1.6-fold in nAMD) and a specific protein signature indicative of matrix remodeling. Unexpectedly, pupil-dilating drugs containing phenylephrine/tropicamide increased several AH proteins, notably interleukin-6 (5.4-fold in nAMD). Correcting for these factors revealed functionally relevant protein correlation clusters and disease-relevant, differentially abundant proteins across the groups. Metabolomics analysis, for which the relevance of confounder adjustment was less apparent, suggested insufficiently controlled diabetes and chronic hyperglycemia in the DME group. Conclusions: AH protein concentration, pseudophakia, and pupil dilation with phenylephrine/tropicamide are important confounding factors for AH protein analyses. When these factors are considered, AH analyses can more clearly reveal disease-relevant factors. Translational Relevance: Considering AH protein concentration, lens status, and phenylephrine/tropicamide administration as confounders is crucial for accurate interpretation of AH protein data.

Myeloid-T cell interplay and cell state transitions associated with checkpoint inhibitor response in melanoma.

BACKGROUND: The treatment of melanoma, the deadliest form of skin cancer, has greatly benefited from immunotherapy. However, many patients do not show a durable response, which is only partially explained by known resistance mechanisms. METHODS: We performed single-cell RNA sequencing of tumor immune infiltrates and matched peripheral blood mononuclear cells of 22 checkpoint inhibitor (CPI)-naive stage III-IV metastatic melanoma patients. After sample collection, the same patients received CPI treatment, and their response was assessed. FINDINGS: CPI responders showed high levels of classical monocytes in peripheral blood, which preferentially transitioned toward CXCL9-expressing macrophages in tumors. Trajectories of tumor-infiltrating CD8+ T cells diverged at the level of effector memory/stem-like T cells, with non-responder cells progressing into a state characterized by cellular stress and apoptosis-related gene expression. Consistently, predicted non-responder-enriched myeloid-T/natural killer cell interactions were primarily immunosuppressive, while responder-enriched interactions were supportive of T cell priming and effector function. CONCLUSIONS: Our study illustrates that the tumor immune microenvironment prior to CPI treatment can be indicative of response. In perspective, modulating the myeloid and/or effector cell compartment by altering the described cell interactions and transitions could improve immunotherapy response. FUNDING: This research was funded by Roche Pharma Research and Early Development.

Correlation of Aqueous, Vitreous, and Serum Protein Levels in Patients With Retinal Diseases.

Purpose: To further establish aqueous humor (AH) as a clinically suitable source of protein biomarkers in retinal diseases by evaluating the correlation of a large panel of proteins between AH, vitreous humor (VH), and serum (SE). Methods: We enrolled 60 subjects (eyes) with various non-infectious retinal diseases. AH, VH, and SE proteins were analyzed using the Olink Target 96 platform (1196 protein assays in total). We compared these three matrices in terms of quantification overlap, principal component analysis, and correlation. Results: In the AH, VH, and SE samples, 841, 917, and 1133 proteins, respectively, were consistently quantified above the limit of detection in more than 30% of patients. AH and VH shared 812 of these proteins. AH and VH samples overlapped along principal component 1, but SE samples were distinct. We identified 490 proteins with significant (false discovery rate [FDR]-adjusted P < 0.05) and relevant correlations (correlation coefficient > 0.5) between AH and VH, compared to only 33 and 40 proteins for VH and SE and for AH and SE, respectively. Conclusions: Due to a close correlation between protein concentrations in the AH and VH and a clear difference from the SE, AH has the potential to serve as a substitute for VH and may hold significance in identifying protein biomarkers and novel targets related to retinal diseases. Translational Relevance: This study further supports AH as a clinically suitable source of protein biomarkers in retinal diseases. In addition, the identified AH and VH correlations can inform the selection of protein biomarker candidates in future translational research.

Epigenetic inactivation of the autophagy-lysosomal system in appendix in Parkinson's disease.

The gastrointestinal tract may be a site of origin for α-synuclein pathology in idiopathic Parkinson's disease (PD). Disruption of the autophagy-lysosome pathway (ALP) may contribute to α-synuclein aggregation. Here we examined epigenetic alterations in the ALP in the appendix by deep sequencing DNA methylation at 521 ALP genes. We identified aberrant methylation at 928 cytosines affecting 326 ALP genes in the appendix of individuals with PD and widespread hypermethylation that is also seen in the brain of individuals with PD. In mice, we find that DNA methylation changes at ALP genes induced by chronic gut inflammation are greatly exacerbated by α-synuclein pathology. DNA methylation changes at ALP genes induced by synucleinopathy are associated with the ALP abnormalities observed in the appendix of individuals with PD specifically involving lysosomal genes. Our work identifies epigenetic dysregulation of the ALP which may suggest a potential mechanism for accumulation of α-synuclein pathology in idiopathic PD.

Specific immune modulation of experimental colitis drives enteric alpha-synuclein accumulation and triggers age-related Parkinson-like brain pathology.

Background: In some people with Parkinson's disease (PD), α-synuclein (αSyn) accumulation may begin in the enteric nervous system (ENS) decades before development of brain pathology and disease diagnosis. Objective: To determine how different types and severity of intestinal inflammation could trigger αSyn accumulation in the ENS and the subsequent development of αSyn brain pathology. Methods: We assessed the effects of modulating short- and long-term experimental colitis on αSyn accumulation in the gut of αSyn transgenic and wild type mice by immunostaining and gene expression analysis. To determine the long-term effect on the brain, we induced dextran sulfate sodium (DSS) colitis in young αSyn transgenic mice and aged them under normal conditions up to 9 or 21 months before tissue analyses. Results: A single strong or sustained mild DSS colitis triggered αSyn accumulation in the submucosal plexus of wild type and αSyn transgenic mice, while short-term mild DSS colitis or inflammation induced by lipopolysaccharide did not have such an effect. Genetic and pharmacological modulation of macrophage-associated pathways modulated the severity of enteric αSyn. Remarkably, experimental colitis at three months of age exacerbated the accumulation of aggregated phospho-Serine 129 αSyn in the midbrain (including the substantia nigra), in 21- but not 9-month-old αSyn transgenic mice. This increase in midbrain αSyn accumulation is accompanied by the loss of tyrosine hydroxylase-immunoreactive nigral neurons. Conclusions: Our data suggest that specific types and severity of intestinal inflammation, mediated by monocyte/macrophage signaling, could play a critical role in the initiation and progression of PD.

An Introduction to Machine Learning.

In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever-increasing amount of data and computational power as well as the discovery of improved learning algorithms. However, the idea of a computer learning some abstract concept from data and applying them to yet unseen situations is not new and has been around at least since the 1950s. Many of these basic principles are very familiar to the pharmacometrics and clinical pharmacology community. In this paper, we want to introduce the foundational ideas of ML to this community such that readers obtain the essential tools they need to understand publications on the topic. Although we will not go into the very details and theoretical background, we aim to point readers to relevant literature and put applications of ML in molecular biology as well as the fields of pharmacometrics and clinical pharmacology into perspective.

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor.

Progressive and irreversible muscle atrophy characterizes Spinal Muscular Atrophy (SMA) and other similar muscle disorder diseases. Objective assessment of muscle functions is an essential and important, although challenging, prerequisite for successful clinical trials. Current clinical rating scales restrain the movement abnormalities to certain predefined coarse-grained individual items. The Kinect 3-D sensor has emerged as a low-cost and portable motion sensing technology used to capture and track people's movement in many medical and research fields. A novel approach using this 3-D sensor was developed and a game-like test was designed to objectively measure the upper limb function of patients with SMA. The prototype test targeted joint movement capability. While sitting in a virtual scene, the patient was instructed to extend, flex, and lift the whole arm in order to reach and place some objects. Both kinematic and spatiotemporal characteristics of upper limb movement were extracted and analyzed, e.g., elbow extension and flexion angles, hand velocity, and acceleration. The first study included a small cohort of 18 ambulant SMA patients and 19 age- and gender-matched healthy controls. A comprehensive analysis of arm movement was achieved; however, no significant difference between the groups were found due to the mismatch of patient's capability and the test difficulty. Based on this experience, a second version of the test consisting of a modified version of the first game with increased difficulties and a second game targeting muscle endurance were designed and implemented. The new test has not been conducted in any patient groups yet. Our work has demonstrated the potential capability of the 3-D sensor in assessing such muscle function and suggested an objective approach to complement the clinical rating scales.

HtrA1 Mediated Intracellular Effects on Tubulin Using a Polarized RPE Disease Model.

Age-related macular degeneration (AMD) is the leading cause of irreversible vision loss. The protein HtrA1 is enriched in retinal pigment epithelial (RPE) cells isolated from AMD patients and in drusen deposits. However, it is poorly understood how increased levels of HtrA1 affect the physiological function of the RPE at the intracellular level. Here, we developed hfRPE (human fetal retinal pigment epithelial) cell culture model where cells fully differentiated into a polarized functional monolayer. In this model, we fine-tuned the cellular levels of HtrA1 by targeted overexpression. Our data show that HtrA1 enzymatic activity leads to intracellular degradation of tubulin with a corresponding reduction in the number of microtubules, and consequently to an altered mechanical cell phenotype. HtrA1 overexpression further leads to impaired apical processes and decreased phagocytosis, an essential function for photoreceptor survival. These cellular alterations correlate with the AMD phenotype and thus highlight HtrA1 as an intracellular target for therapeutic interventions towards AMD treatment.

Feasibility of Using Microsoft Kinect to Assess Upper Limb Movement in Type III Spinal Muscular Atrophy Patients.

Although functional rating scales are being used increasingly as primary outcome measures in spinal muscular atrophy (SMA), sensitive and objective assessment of early-stage disease progression and drug efficacy remains challenging. We have developed a game based on the Microsoft Kinect sensor, specifically designed to measure active upper limb movement. An explorative study was conducted to determine the feasibility of this new tool in 18 ambulant SMA type III patients and 19 age- and gender-matched healthy controls. Upper limb movement was analysed elaborately through derived features such as elbow flexion and extension angles, arm lifting angle, velocity and acceleration. No significant differences were found in the active range of motion between ambulant SMA type III patients and controls. Hand velocity was found to be different but further validation is necessary. This study presents an important step in the process of designing and handling digital biomarkers as complementary outcome measures for clinical trials.