Improving Prognostication in Pulmonary Hypertension Using AI-quantified Fibrosis and Radiologic Severity Scoring at Baseline CT

Background There is clinical need to better quantify lung disease severity in pulmonary hypertension (PH), particularly in idiopathic pulmonary arterial hypertension (IPAH) and PH associated with lung disease (PH-LD). Purpose To quantify fibrosis on CT pulmonary angiograms using an artificial intelligence (AI) model and to assess whether this approach can be used in combination with radiologic scoring to predict survival. Materials and Methods This retrospective multicenter study included adult patients with IPAH or PH-LD who underwent incidental CT imaging between February 2007 and January 2019. Patients were divided into training and test cohorts based on the institution of imaging. The test cohort included imaging examinations performed in 37 external hospitals. Fibrosis was quantified using an established AI model and radiologically scored by radiologists. Multivariable Cox regression adjusted for age, sex, World Health Organization functional class, pulmonary vascular resistance, and diffusing capacity of the lungs for carbon monoxide was performed. The performance of predictive models with or without AI-quantified fibrosis was assessed using the concordance index (C index). Results The training and test cohorts included 275 (median age, 68 years [IQR, 60-75 years]; 128 women) and 246 (median age, 65 years [IQR, 51-72 years]; 142 women) patients, respectively. Multivariable analysis showed that AI-quantified percentage of fibrosis was associated with an increased risk of patient mortality in the training cohort (hazard ratio, 1.01 [95% CI: 1.00, 1.02]; P = .04). This finding was validated in the external test cohort (C index, 0.76). The model combining AI-quantified fibrosis and radiologic scoring showed improved performance for predicting patient mortality compared with a model including radiologic scoring alone (C index, 0.67 vs 0.61; P < .001). Conclusion Percentage of lung fibrosis quantified on CT pulmonary angiograms by an AI model was associated with increased risk of mortality and showed improved performance for predicting patient survival when used in combination with radiologic severity scoring compared with radiologic scoring alone. © RSNA, 2024 Supplemental material is available for this article.

Genetic risks of Alzheimer's by APOE and MAPT on cortical morphology in young healthy adults

Genetic risk factors such as APOE ε4 and MAPT (rs242557) A allele are associated with amyloid and tau pathways and grey matter changes at both early and established stages of Alzheimer's disease, but their effects on cortical morphology in young healthy adults remain unclear. A total of 144 participants aged from 18 to 24 underwent 3T MRI and genotyping for APOE and MAPT to investigate unique impacts of these genetic risk factors in a cohort without significant comorbid conditions such as metabolic and cardiovascular diseases. We segmented the cerebral cortex into 68 regions and calculated the cortical area, thickness, curvature and folding index for each region. Then, we trained machine learning models to classify APOE and MAPT genotypes using these morphological features. In addition, we applied a growing hierarchical self-organizing maps algorithm, which clustered the 68 regions into 4 subgroups representing different morphological patterns. Then, we performed general linear model analyses to estimate the interaction between APOE and MAPT on cortical patterns. We found that the classifiers using all cortical features could accurately classify individuals carrying genetic risks of dementia outperforming each individual feature alone. APOE ε4 carriers had a more convoluted and thinner cortex across the cerebral cortex. A similar pattern was found in MAPT A allele carriers only in the regions that are vulnerable for early tau pathology. With the clustering analysis, we found a synergetic effect between APOE ε4 and MAPT A allele, i.e. carriers of both risk factors showed the most deviation of cortical pattern from the typical pattern of that cluster. Genetic risk factors of dementia by APOE ε4 and MAPT (rs242557) A allele were associated with variations of cortical morphology, which can be observed in young healthy adults more than 30 years before Alzheimer's pathology is likely to occur and 50 years before dementia symptoms may begin.

Establishing minimally important differences for cardiac MRI end-points in pulmonary arterial hypertension

BACKGROUND

Cardiac magnetic resonance (CMR) is the gold standard technique to assess biventricular volumes and function, and is increasingly being considered as an end-point in clinical studies. Currently, with the exception of right ventricular (RV) stroke volume and RV end-diastolic volume, there is only limited data on minimally important differences (MIDs) reported for CMR metrics. Our study aimed to identify MIDs for CMR metrics based on US Food and Drug Administration recommendations for a clinical outcome measure that should reflect how a patient "feels, functions or survives".

METHODS

Consecutive treatment-naïve patients with pulmonary arterial hypertension (PAH) between 2010 and 2022 who had two CMR scans (at baseline prior to treatment and 12 months following treatment) were identified from the ASPIRE registry. All patients were followed up for 1 additional year after the second scan. For both scans, cardiac measurements were obtained from a validated fully automated segmentation tool. The MID in CMR metrics was determined using two distribution-based (0.5sd and minimal detectable change) and two anchor-based (change difference and generalised linear model regression) methods benchmarked to how a patient "feels" (emPHasis-10 quality of life questionnaire), "functions" (incremental shuttle walk test) or "survives" for 1-year mortality to changes in CMR measurements.

RESULTS

254 patients with PAH were included (mean±sd age 53±16 years, 79% female and 66% categorised as intermediate risk based on the 2022 European Society of Cardiology/European Respiratory Society risk score). We identified a 5% absolute increase in RV ejection fraction and a 17 mL decrease in RV end-diastolic or end-systolic volumes as the MIDs for improvement. Conversely, a 5% decrease in RV ejection fraction and a 10 mL increase in RV volumes were associated with worsening.

CONCLUSIONS

This study establishes clinically relevant CMR MIDs for how a patient "feels, functions or survives" in response to PAH treatment. These findings provide further support for the use of CMR as a clinically relevant clinical outcome measure and will aid trial size calculations for studies using CMR.

Low expression of EXOSC2 protects against clinical COVID-19 and impedes SARS-CoV-2 replication

New therapeutic targets are a valuable resource for treatment of SARS-CoV-2 viral infection. Genome-wide association studies have identified risk loci associated with COVID-19, but many loci are associated with comorbidities and are not specific to host-virus interactions. Here, we identify and experimentally validate a link between reduced expression of EXOSC2 and reduced SARS-CoV-2 replication. EXOSC2 was one of the 332 host proteins examined, all of which interact directly with SARS-CoV-2 proteins. Aggregating COVID-19 genome-wide association studies statistics for gene-specific eQTLs revealed an association between increased expression of EXOSC2 and higher risk of clinical COVID-19. EXOSC2 interacts with Nsp8 which forms part of the viral RNA polymerase. EXOSC2 is a component of the RNA exosome, and here, LC-MS/MS analysis of protein pulldowns demonstrated interaction between the SARS-CoV-2 RNA polymerase and most of the human RNA exosome components. CRISPR/Cas9 introduction of nonsense mutations within EXOSC2 in Calu-3 cells reduced EXOSC2 protein expression and impeded SARS-CoV-2 replication without impacting cellular viability. Targeted depletion of EXOSC2 may be a safe and effective strategy to protect against clinical COVID-19.

Analysis of brain and spinal MRI measures in a common domain to investigate directional neurodegeneration in motor neuron disease

BACKGROUND

Magnetic resonance imaging (MRI) of the brain and cervical spinal cord is often performed in diagnostic evaluation of suspected motor neuron disease/amyotrophic lateral sclerosis (MND/ALS). Analysis of MRI-derived tissue damage metrics in a common domain facilitates group-level inferences on pathophysiology. This approach was applied to address competing hypotheses of directionality of neurodegeneration, whether anterograde, cranio-caudal dying-forward from precentral gyrus or retrograde, dying-back.

METHODS

In this cross-sectional study, MRI was performed on 75 MND patients and 13 healthy controls. Precentral gyral thickness was estimated from volumetric T1-weighted images using FreeSurfer, corticospinal tract fractional anisotropy (FA) from diffusion tensor imaging using FSL, and cross-sectional cervical cord area between C1-C8 levels using Spinal Cord Toolbox. To analyse these multimodal data within a common domain, individual parameter estimates representing tissue damage at each corticospinal tract level were first converted to z-scores, referenced to healthy control norms. Mixed-effects linear regression models were then fitted to these z-scores, with gradients hypothesised to represent directionality of neurodegeneration.

RESULTS

At group-level, z-scores did not differ significantly between precentral gyral and intracranial corticospinal tract tissue damage estimates (regression coefficient - 0.24, [95% CI - 0.62, 0.14], p = 0.222), but step-changes were evident between intracranial corticospinal tract and C1 (1.14, [95% CI 0.74, 1.53], p < 0.001), and between C5 and C6 cord levels (0.98, [95% CI 0.58, 1.38], p < 0.001).

DISCUSSION

Analysis of brain and cervical spinal MRI data in a common domain enabled investigation of pathophysiological hypotheses in vivo. A cranio-caudal step-change in MND patients was observed, and requires further investigation in larger cohorts.

Loss of TMEM106B exacerbates C9ALS/FTD DPR pathology by disrupting autophagosome maturation

Disruption to protein homeostasis caused by lysosomal dysfunction and associated impairment of autophagy is a prominent pathology in amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD). The most common genetic cause of ALS/FTD is a G4C2 hexanucleotide repeat expansion in C9orf72 (C9ALS/FTD). Repeat-associated non-AUG (RAN) translation of G4C2 repeat transcripts gives rise to dipeptide repeat (DPR) proteins that have been shown to be toxic and may contribute to disease etiology. Genetic variants in TMEM106B have been associated with frontotemporal lobar degeneration with TDP-43 pathology and disease progression in C9ALS/FTD. TMEM106B encodes a lysosomal transmembrane protein of unknown function that is involved in various aspects of lysosomal biology. How TMEM106B variants affect C9ALS/FTD is not well understood but has been linked to changes in TMEM106B protein levels. Here, we investigated TMEM106B function in the context of C9ALS/FTD DPR pathology. We report that knockdown of TMEM106B expression exacerbates the accumulation of C9ALS/FTD-associated cytotoxic DPR proteins in cell models expressing RAN-translated or AUG-driven DPRs as well as in C9ALS/FTD-derived iAstrocytes with an endogenous G4C2 expansion by impairing autophagy. Loss of TMEM106B caused a block late in autophagy by disrupting autophagosome to autolysosome maturation which coincided with impaired lysosomal acidification, reduced cathepsin activity, and juxtanuclear clustering of lysosomes. Lysosomal clustering required Rab7A and coincided with reduced Arl8b-mediated anterograde transport of lysosomes to the cell periphery. Increasing Arl8b activity in TMEM106B-deficient cells not only restored the distribution of lysosomes, but also fully rescued autophagy and DPR protein accumulation. Thus, we identified a novel function of TMEM106B in autophagosome maturation via Arl8b. Our findings indicate that TMEM106B variants may modify C9ALS/FTD by regulating autophagic clearance of DPR proteins. Caution should therefore be taken when considering modifying TMEM106B expression levels as a therapeutic approach in ALS/FTD.

Micro-RNAs Shuttled by Extracellular Vesicles Secreted from Mesenchymal Stem Cells Dampen Astrocyte Pathological Activation and Support Neuroprotection in In-Vitro Models of ALS

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with no effective cure. Astrocytes display a toxic phenotype in ALS and contribute to motoneuron (MN) degeneration. Modulating astrocytes' neurotoxicity can reduce MN death. Our previous studies showed the beneficial effect of mesenchymal stem cell (MSC) administration in SOD1^G93A ALS mice, but the mechanisms are still unclear. We postulated that the effects could be mediated by extracellular vesicles (EVs) secreted by MSCs. We investigated, by immunohistochemical, molecular, and in vitro functional analyses, the activity of MSC-derived EVs on the pathological phenotype and neurotoxicity of astrocytes isolated from the spinal cord of symptomatic SOD1^G93A mice and human astrocytes (iAstrocytes) differentiated from inducible neural progenitor cells (iNPCs) of ALS patients. In vitro EV exposure rescued mouse and human ALS astrocytes' neurotoxicity towards MNs. EVs significantly dampened the pathological phenotype and neuroinflammation in SOD1^G93A astrocytes. In iAstrocytes, exposure to EVs increased the antioxidant factor Nrf2 and reduced reactive oxygen species. We previously found nine miRNAs upregulated in MSC-derived EVs. Here, the transfection of SOD1^G93A astrocytes with single miRNA mimics reduced astrocytes' activation and the expression of neuroinflammatory factors. Moreover, miR-466q and miR-467f mimics downregulate Mapk11, while miR-466m-5p and miR-466i-3p mimics promote the nuclear translocation of Nrf2. In iAstrocytes, transfection with miR-29b-3p mimic upregulated NQO1 antioxidant activity and reduced neurotoxicity towards MNs. MSC-derived EVs modulate astrocytes' reactive phenotype and neurotoxicity through anti-inflammatory and antioxidant-shuttled miRNAs, thus representing a therapeutic strategy in ALS.

A statistical framework for assessing pharmacological responses and biomarkers using uncertainty estimates

High-throughput testing of drugs across molecular-characterised cell lines can identify candidate treatments and discover biomarkers. However, the cells' response to a drug is typically quantified by a summary statistic from a best-fit dose-response curve, whilst neglecting the uncertainty of the curve fit and the potential variability in the raw readouts. Here, we model the experimental variance using Gaussian Processes, and subsequently, leverage uncertainty estimates to identify associated biomarkers with a new Bayesian framework. Applied to in vitro screening data on 265 compounds across 1074 cancer cell lines, our models identified 24 clinically established drug-response biomarkers, and provided evidence for six novel biomarkers by accounting for association with low uncertainty. We validated our uncertainty estimates with an additional drug screen of 26 drugs, 10 cell lines with 8 to 9 replicates. Our method is applicable to any dose-response data without replicates, and improves biomarker discovery for precision medicine.