Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

Background: Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. Methods and findings: The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2). Conclusions: TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust method for patient stratification and treatment planning targeting identified biomarkers in future clinical trials in TBI patients

Nanoparticle clearance is governed by Th1/Th2 immunity and strain background

Extended circulation of nanoparticles in blood is essential for most clinical applications. Nanoparticles are rapidly cleared by cells of the mononuclear phagocyte system (MPS). Approaches such as grafting polyethylene glycol onto particles (PEGylation) extend circulation times; however, these particles are still cleared, and the processes involved in this clearance remain poorly understood. Here, we present an intravital microscopy–based assay for the quantification of nanoparticle clearance, allowing us to determine the effect of mouse strain and immune system function on particle clearance. We demonstrate that mouse strains that are prone to Th1 immune responses clear nanoparticles at a slower rate than Th2-prone mice. Using depletion strategies, we show that both granulocytes and macrophages participate in the enhanced clearance observed in Th2-prone mice. Macrophages isolated from Th1 strains took up fewer particles in vitro than macrophages from Th2 strains. Treating macrophages from Th1 strains with cytokines to differentiate them into M2 macrophages increased the amount of particle uptake. Conversely, treating macrophages from Th2 strains with cytokines to differentiate them into M1 macrophages decreased their particle uptake. Moreover, these results were confirmed in human monocyte–derived macrophages, suggesting that global immune regulation has a significant impact on nanoparticle clearance in humans

Cutting Edge: NLRC5-Dependent Activation of the Inflammasome

The nucleotide-binding domain (NBD) leucine rich repeat (LRR) containing proteins, NLRs, are intracellular sensors of PAMPs and DAMPs. A subgroup of NLRs can form inflammasome complexes, which facilitate the maturation of pro-caspase-1 to caspase-1, leading to IL-1β and IL-18 cleavage and secretion. NLRC5 is predominantly expressed in hematopoetic cells and has not been studied for inflammasome function. RNAi-mediated knockdown of NLRC5 nearly eliminated caspase-1, IL-1β and IL-18 processing in response to bacterial infection, PAMPs and DAMPs. This was confirmed in primary human monocytic cells. NLRC5 together with procaspase-1, pro-IL-1β and the inflammasome adaptor, ASC, reconstituted inflammasome activity which showed cooperativity with NLPR3. The range of pathogens that activate NLRC5 inflammasome overlaps with those that activate NLRP3. Furthermore, NLRC5 biochemically associates with NLRP3 in an NBD-dependent but LRR-inhibitory fashion. These results invoke a model where NLRC5 interacts with NLRP3 to cooperatively activate the inflammasome

Presenilin 1 Maintains Lysosomal Ca2+ Homeostasis via TRPML1 by Regulating vATPase-Mediated Lysosome Acidification

Presenilin 1 (PS1) deletion or Alzheimer’s disease (AD)-linked mutations disrupt lysosomal acidification and proteolysis, which inhibits autophagy. Here, we establish that this phenotype stems from impaired glycosylation and instability of vATPase V0a1 subunit, causing deficient lysosomal vATPase assembly and function. We further demonstrate that elevated lysosomal pH in Presenilin 1 knockout (PS1KO) cells induces abnormal Ca2+ efflux from lysosomes mediated by TRPML1 and elevates cytosolic Ca2+. In WT cells, blocking vATPase activity or knockdown of either PS1 or the V0a1 subunit of vATPase reproduces all of these abnormalities. Normalizing lysosomal pH in PS1KO cells using acidic nanoparticles restores normal lysosomal proteolysis, autophagy, and Ca2+ homeostasis, but correcting lysosomal Ca2+ deficits alone neither re-acidifies lysosomes nor reverses proteolytic and autophagic deficits. Our results indicate that vATPase deficiency in PS1 loss-of-function states causes lysosomal/autophagy deficits and contributes to abnormal cellular Ca2+ homeostasis, thus linking two AD-related pathogenic processes through a common molecular mechanism

Nanoparticle clearance is governed by Th1/Th2 immunity and strain background

Extended circulation of nanoparticles in blood is essential for most clinical applications. Nanoparticles are rapidly cleared by cells of the mononuclear phagocyte system (MPS). Approaches such as grafting polyethylene glycol onto particles (PEGylation) extend circulation times; however, these particles are still cleared, and the processes involved in this clearance remain poorly understood. Here, we present an intravital microscopy–based assay for the quantification of nanoparticle clearance, allowing us to determine the effect of mouse strain and immune system function on particle clearance. We demonstrate that mouse strains that are prone to Th1 immune responses clear nanoparticles at a slower rate than Th2-prone mice. Using depletion strategies, we show that both granulocytes and macrophages participate in the enhanced clearance observed in Th2-prone mice. Macrophages isolated from Th1 strains took up fewer particles in vitro than macrophages from Th2 strains. Treating macrophages from Th1 strains with cytokines to differentiate them into M2 macrophages increased the amount of particle uptake. Conversely, treating macrophages from Th2 strains with cytokines to differentiate them into M1 macrophages decreased their particle uptake. Moreover, these results were confirmed in human monocyte–derived macrophages, suggesting that global immune regulation has a significant impact on nanoparticle clearance in humans