Age-Related Changes in Myelin of Axons of the Corpus Callosum and Cognitive Decline in Common Marmosets

Executive control is a higher‐level cognitive function that involves a range of different processes that are involved in the planning, coordination, execution, and inhibition of responses. Many of the processes associated with executive control, such as response inhibition and mental flexibility, decline with age. Degeneration of white matter architecture is considered to be the one of the key factors underlying cognitive decline associated with aging. Here we investigated how white matter changes of the corpus callosum were related to cognitive aging in common marmosets (Callithrix jacchus). We hypothesized that reduction in myelin thickness, myelin density, and myelin fraction of axonal fibers in the corpus callosum would be associated with performance on a task of executive function in a small sample of geriatric marmosets (n = 4) and young adult marmosets (n = 2). Our results indicated declines in myelin thickness, density, and myelin fraction with age. Considerable variability was detected on these characteristics of myelin and cognitive performance assessed via the detoured reach task. Age‐related changes in myelin in Region II of the corpus callosum were predictive of cognitive performance on the detoured reach task. Thus the detoured reach task appears to also measure aspects of corticostriatal function in addition to prefrontal cortical function

IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study

PurposeRobust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.MethodsWe conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.ResultsWe show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.ConclusionThese data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus

Adjunct treatment with ketamine enhances the therapeutic effects of extinction learning after chronic unpredictable stress

Post-traumatic stress disorder (PTSD) is a debilitating illness characterized by dysfunction in the medial prefrontal cortex (mPFC). Although both pharmacological and cognitive behavioral interventions have shown some promise at alleviating symptoms, high attrition and persistence of treatment-resistant symptoms pose significant challenges that remain unresolved. Specifically, prolonged exposure therapy, a gold standard intervention to treat PTSD, has high dropout rates resulting in many patients receiving less than a fully effective course of treatment. Administering pharmacological treatments together with behavioral psychotherapies like prolonged exposure may offer an important avenue for enhancing therapeutic efficacy sooner, thus reducing the duration of treatment and mitigating the impact of attrition. In this study, using extinction learning as a rat model of exposure therapy, we hypothesized that administering ketamine as an adjunct treatment together with extinction will enhance the efficacy of extinction in reversing stress-induced deficits in set shifting, a measure of cognitive flexibility. Results showed that combining a sub-effective dose of ketamine with a shortened, sub-effective extinction protocol fully reversed stress-induced cognitive set-shifting deficits in both male and female rats. These effects may be due to shared molecular mechanisms between extinction and ketamine, such as increased neuronal plasticity in common circuitry (e.g., hippocampus-mPFC), or increased BDNF signaling. This work suggests that fast-acting drugs, such as ketamine, can be effectively used in combination with behavioral interventions to reduce treatment duration and potentially mitigate the impact of attrition. Future work is needed to delineate other pharmacotherapies that may complement the effects of extinction via shared or independent mechanisms

Machine Learning Identifies Digital Phenotyping Measures Most Relevant to Negative Symptoms in Psychotic Disorders: Implications for Clinical Trials

BACKGROUND: Digital phenotyping has been proposed as a novel assessment tool for clinical trials targeting negative symptoms in psychotic disorders (PDs). However, it is unclear which digital phenotyping measurements are most appropriate for this purpose. AIMS: Machine learning was used to address this gap in the literature and determine whether: (1) diagnostic status could be classified from digital phenotyping measures relevant to negative symptoms and (2) the 5 negative symptom domains (anhedonia, avolition, asociality, alogia, and blunted affect) were differentially classified by active and passive digital phenotyping variables. METHODS: Participants included 52 outpatients with a PD and 55 healthy controls (CN) who completed 6 days of active (ecological momentary assessment surveys) and passive (geolocation, accelerometry) digital phenotyping data along with clinical ratings of negative symptoms. RESULTS: Machine learning algorithms classifying the presence of a PD diagnosis yielded 80% accuracy for cross-validation in H(2)O AutoML and 79% test accuracy in the Recursive Feature Elimination with Cross Validation feature selection model. Models classifying the presence vs absence of clinically significant elevations on each of the 5 negative symptom domains ranged in test accuracy from 73% to 91%. A few active and passive features were highly predictive of all 5 negative symptom domains; however, there were also unique predictors for each domain. CONCLUSIONS: These findings suggest that negative symptoms can be modeled from digital phenotyping data recorded in situ. Implications for selecting the most appropriate digital phenotyping variables for use as outcome measures in clinical trials targeting negative symptoms are discussed

Lack of GDAP1 Induces Neuronal Calcium and Mitochondrial Defects in a Knockout Mouse Model of Charcot-Marie-Tooth Neuropathy

27 páginas, 9 figuras.Mutations in GDAP1, which encodes protein located in the mitochondrial outer membrane, cause axonal recessive (AR-CMT2), axonal dominant (CMT2K) and demyelinating recessive (CMT4A) forms of Charcot-Marie-Tooth (CMT) neuropathy. Loss of function recessive mutations in GDAP1 are associated with decreased mitochondrial fission activity, while dominant mutations result in impairment of mitochondrial fusion with increased production of reactive oxygen species and susceptibility to apoptotic stimuli. GDAP1 silencing in vitro reduces Ca2+ inflow through store-operated Ca2+ entry (SOCE) upon mobilization of endoplasmic reticulum (ER) Ca2+, likely in association with an abnormal distribution of the mitochondrial network. To investigate the functional consequences of lack of GDAP1 in vivo, we generated a Gdap1 knockout mouse. The affected animals presented abnormal motor behavior starting at the age of 3 months. Electrophysiological and biochemical studies confirmed the axonal nature of the neuropathy whereas histopathological studies over time showed progressive loss of motor neurons (MNs) in the anterior horn of the spinal cord and defects in neuromuscular junctions. Analyses of cultured embryonic MNs and adult dorsal root ganglia neurons from affected animals demonstrated large and defective mitochondria, changes in the ER cisternae, reduced acetylation of cytoskeletal α-tubulin and increased autophagy vesicles. Importantly, MNs showed reduced cytosolic calcium and SOCE response. The development and characterization of the GDAP1 neuropathy mice model thus revealed that some of the pathophysiological changes present in axonal recessive form of the GDAP1-related CMT might be the consequence of changes in the mitochondrial network biology and mitochondria-endoplasmic reticulum interaction leading to abnormalities in calcium homeostasis.This work has been funded by grants from the Spanish Ministry of Economy and Competitiveness, grants no. SAF2009-07063 and SAF2012-32425 (to FP), the Collaborative Joint Project awarded by IRDiRC and funded by ISCIII grant IR11/TREAT-CMT, Instituto de Salud Carlos III (to both FP and JMC), the Generalitat Valenciana Prometeo Programme 2009/059 and 2014/029 (to FP) and the Swiss National Science Foundation, grant no. 31003A_135735/1 (to RC). This work has also been funded by the CIBERER, an initiative from the Instituto de Salud Carlos III. MB-M is the recipient of a FPI fellowship, from the Spanish Ministry of Economy and Competitiveness. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewe

IFI27 transcription is an early predictor for COVID-19 outcomes; a multi-cohort observational study

Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients. We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression is associated with the presence of a high viral load. We further demonstrate that systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 severity. For clinical outcome prediction (e.g. respiratory failure), IFI27 expression displays a high positive (0.83) and negative (0.95) predictive value, outperforming all other known predictors of COVID-19 severity. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 swine influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients. These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus. We searched the scientific literature using PubMed to identify studies that used the IFI27 biomarker to predict outcomes in COVID-19 patients. We used the search terms “IFI27”, “COVID-19, “gene expression” and “outcome prediction”. We did not identify any study that investigated the role of IFI27 biomarker in outcome prediction. Although ten studies were identified using the general terms of “gene expression” and “COVID-19”, IFI27 was only mentioned in passing as one of the identified genes. All these studies addressed the broader question of the host response to COVID-19; none focused solely on using IFI27 to improve the risk stratification of infected patients in a pandemic. Here, we present the findings of a multi-cohort study of the IFI27 biomarker in COVID-19 patients. Our findings show that the host response, as reflected by blood IFI27 gene expression, accurately predicts COVID-19 disease progression (positive and negative predictive values; 0.83 and 0.95, respectively), outperforming age, comorbidity, C-reactive protein and all other known risk factors. The strong association of IFI27 with disease severity occurs not only in SARS-CoV-2 infection, but also in other respiratory viruses with pandemic potential, such as the influenza virus. These findings suggest that host response biomarkers, such as IFI27, could help identify high-risk COVID-19 patients - those who are more likely to develop infection complications - and therefore may help improve patient triage in a pandemic. This is the first systemic study of the clinical role of IFI27 in the current COVID-19 pandemic and its possible future application in other respiratory virus pandemics. The findings not only could help improve the current management of COVID-19 patients but may also improve future pandemic preparedness

IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study

Purpose: Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. Methods: We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients. Results: We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients. Conclusion: These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus