Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts.

BACKGROUND: SARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae of SARS-CoV-2 infection (PASC, or Long COVID), involve a diverse set of organ systems. Limited studies have investigated the predictability of Long COVID development and its associated risk factors. METHODS: In this retrospective cohort study, we used electronic healthcare records from two large-scale PCORnet clinical research networks, INSIGHT (~1.4 million patients from New York) and OneFlorida+ (~0.7 million patients from Florida), to identify factors associated with having Long COVID, and to develop machine learning-based models for predicting Long COVID development. Both SARS-CoV-2-infected and non-infected adults were analysed during the period of March 2020 to November 2021. Factors associated with Long COVID risk were identified by removing background associations and correcting for multiple tests. RESULTS: We observed complex association patterns between baseline factors and a variety of Long COVID conditions, and we highlight that severe acute SARS-CoV-2 infection, being underweight, and having baseline comorbidities (e.g., cancer and cirrhosis) are likely associated with increased risk of developing Long COVID. Several Long COVID conditions, e.g., dementia, malnutrition, chronic obstructive pulmonary disease, heart failure, PASC diagnosis U099, and acute kidney failure are well predicted (C-index > 0.8). Moderately predictable conditions include atelectasis, pulmonary embolism, diabetes, pulmonary fibrosis, and thromboembolic disease (C-index 0.7-0.8). Less predictable conditions include fatigue, anxiety, sleep disorders, and depression (C-index around 0.6). CONCLUSIONS: This observational study suggests that association patterns between investigated factors and Long COVID are complex, and the predictability of different Long COVID conditions varies. However, machine learning-based predictive models can help in identifying patients who are at risk of developing a variety of Long COVID conditions.

Most people who develop COVID-19 make a full recovery, but some go on to develop post-acute sequelae of SARS-CoV-2 infection, commonly known as Long COVID. Up to now, we did not know why some people are affected by Long COVID whilst others are not. We conducted a study to identify risk factors for Long COVID and developed a mathematical modeling approach to predict those at risk. We find that Long COVID is associated with some factors such as experiencing severe acute COVID-19, being underweight, and having conditions including cancer or cirrhosis. Due to the wide variety of symptoms defined as Long COVID, it may be challenging to come up with a set of risk factors that can predict the whole spectrum of Long COVID. However, our approach could be used to predict a variety of Long COVID conditions.

Clinical Arterial Spin-Labeling MR Imaging to Screen for Typical and Atypical Neurodegenerative Disease in the New Era of Alzheimer Treatment.

The clinical standard of care in the diagnosis of neurodegenerative diseases relies on [18F] FDG-PET/CT or PET MR imaging. Limitations of FDG-PET include cost, the need for IV access, radiation exposure, and availability. Arterial spin-labeling MR imaging has been shown in research settings to be useful as a proxy for FDG-PET in differentiating Alzheimer disease from frontotemporal dementia. However, it is not yet widely used in clinical practice, except in cerebrovascular disease. Here, we present 7 patients, imaged with our routine clinical protocol with diverse presentations of Alzheimer disease and other neurodegenerative diseases, in whom arterial spin-labeling-derived reduced CBF correlated with hypometabolism or amyloid/tau deposition on PET. Our case series illustrates the clinical diagnostic utility of arterial spin-labeling MR imaging as a fast, accessible, and noncontrast screening tool for neurodegenerative disease. Arterial spin-labeling MR imaging can guide patient selection for subsequent PET or fluid biomarker work-up, as well as for possible therapy with antiamyloid monoclonal antibodies.

Impaired sleep is associated with tau deposition on 18F-flortaucipir PET and accelerated cognitive decline, accounting for medications that affect sleep.

BACKGROUND: Impaired sleep is commonly associated with Alzheimer's disease (AD), although the underlying mechanisms remain unclear. Furthermore, the moderating effects of sleep-affecting medications, which have been linked to AD pathology, are incompletely characterized. Using data from the Alzheimer's Disease Neuroimaging Initiative, we investigated whether a medical history of impaired sleep, informant-reported nighttime behaviors, and sleep-affecting medications are associated with beta-amyloid and tau deposition on PET and cognitive change, cross-sectionally and longitudinally. METHODS: We included 964 subjects with 18F-florbetapir PET scans. Measures of sleep impairment and medication use were obtained from medical histories and the Neuropsychiatric Inventory Questionnaire. Multivariate models, adjusted for covariates, were used to assess associations among sleep-related features, beta-amyloid and tau, and cognition. Cortical tau deposition, categorized by Braak stage, was assessed using the standardized uptake value peak alignment (SUVP) method on 18F-flortaucipir PET. RESULTS: Medical history of sleep impairment was associated with greater baseline tau in the meta-temporal, Braak 1, and Braak 4 regions (p = 0.04, p < 0.001, p = 0.025, respectively). Abnormal nighttime behaviors were also associated with greater baseline tau in the meta-temporal region (p = 0.024), and greater cognitive impairment, cross-sectionally (p = 0.007) and longitudinally (p < 0.001). Impaired sleep was not associated with baseline beta-amyloid (p > 0.05). Short-term use of selective serotonin reuptake inhibitors and benzodiazepines slightly weakened the sleep-tau relationship. CONCLUSIONS: Sleep impairment was associated with tauopathy and cognitive decline, which could be linked to increased tau secretion from neuronal hyperactivity. Clinically, our results help identify high-risk individuals who could benefit from sleep-related interventions aimed to delay cognitive decline and AD.

Brain fog in long COVID limits function and health status, independently of hospital severity and preexisting conditions.

Importance: The U.S. government has named post-acute sequelae of COVID-19 (longCOVID) as influential on disability rates. We previously showed that COVID-19 carries a medical/functional burden at 1 year, and that age and other risk factors of severe COVID-19 were not associated with increased longCOVID risk. Long-term longCOVID brain fog (BF) prevalence, risk factors and associated medical/functional factors are poorly understood, especially after mild SARS-CoV-2 infection. Methods: A retrospective observational cohort study was conducted at an urban tertiary-care hospital. Of 1,032 acute COVID-19 survivors from March 3-May 15, 2020, 633 were called, 530 responded (59.2 ± 16.3 years, 44.5% female, 51.5% non-White) about BF prevalence, other longCOVID, post-acute ED/hospital utilization, perceived health/social network, effort tolerance, disability. Results: At approximately 1-year, 31.9% (n = 169) experienced BF. Acute COVID-19 severity, age, and premorbid cardiopulmonary comorbidities did not differ between those with/without BF at 1 year. Patients with respiratory longCOVID had 54% higher risk of BF than those without respiratory longCOVID. BF associated with sleep disturbance (63% with BF vs.29% without BF, p < 0.0001), shortness of breath (46% vs.18%, p < 0.0001), weakness (49% vs.22%, p < 0.0001), dysosmia/dysgeusia (12% vs.5%, p < 0.004), activity limitations (p < 0.001), disability/leave (11% vs.3%, p < 0.0001), worsened perceived health since acute COVID-19 (66% vs.30%, p < 0.001) and social isolation (40% vs.29%, p < 0.02), despite no differences in premorbid comorbidities and age. Conclusions and relevance: A year after COVID-19 infection, BF persists in a third of patients. COVID-19 severity is not a predictive risk factor. BF associates with other longCOVID and independently associates with persistent debility.

Peripheral immune cell imbalance is associated with cortical beta-amyloid deposition and longitudinal cognitive decline.

Neuroinflammation is believed to be a key process in Alzheimer's disease (AD) pathogenesis. Recently, the neutrophil-to-lymphocyte (NLR) and lymphocyte-to-monocyte ratios (LMR) have been proposed to be useful peripheral markers of inflammation. However, it is unclear how these inflammatory ratios relate to AD pathology, such as ß-amyloid (Aß) plaques and tau tangles. Using 18F-florbetapir and 18F-flortaucipir positron emission tomography (PET), we sought to determine how the NLR and LMR are associated with AD pathology both cross-sectionally and longitudinally. We further evaluated associations between the NLR and LMR and longitudinal cognitive decline. Using data from the Alzheimer's Disease Neuroimaging Initiative, we analyzed blood, PET, and cognitive data from 1544 subjects-405 cognitively normal, 838 with mild cognitive impairment (MCI), and 301 with AD. Associations between the NLR and LMR and Aß and tau on PET were assessed using ordinary least-squares and mixed-effects regression models, while adjusting for age, sex, years of education, and apolipoprotein E ε2 or ε4 carrier status. Associations between the NLR and LMR and cognitive function, as measured by the AD Assessment Scale-Cognitive Subscale, 13-item version, were also assessed. MCI and AD subjects had higher NLR (p = 0.017, p < 0.001, respectively) and lower LMR (p = 0.013, p = 0.023). The NLR, but not the LMR, was significantly associated with Aß (p = 0.028), suggesting that higher NLR was associated with greater Aß deposition in the brain. Neither the NLR nor the LMR was associated with tau deposition (p > 0.05). A higher NLR was associated with greater longitudinal cognitive decline (p < 0.001). A higher ratio of peripheral neutrophils to lymphocytes, possibly reflecting an imbalance in innate versus adaptive immunity, is related to greater Aß deposition and longitudinal cognitive decline. As the field moves toward blood-based biomarkers of AD, the altered balance of innate versus adaptive immunity could be a useful biomarker of underlying pathology and may also serve as a potential therapeutic target.

Exercise intolerance associated with impaired oxygen extraction in patients with long COVID.

OBJECTIVE: Chronic mental and physical fatigue and post-exertional malaise are the more debilitating symptoms of long COVID-19. The study objective was to explore factors contributing to exercise intolerance in long COVID-19 to guide development of new therapies. Exercise capacity data of patients referred for a cardiopulmonary exercise test (CPET) and included in a COVID-19 Survivorship Registry at one urban health center were retrospectively analyzed. RESULTS: Most subjects did not meet normative criteria for a maximal test, consistent with suboptimal effort and early exercise termination. Mean O2 pulse peak % predicted (of 79 ± 12.9) was reduced, supporting impaired energy metabolism as a mechanism of exercise intolerance in long COVID, n = 59. We further identified blunted rise in heart rate peak during maximal CPET. Our preliminary analyses support therapies that optimize bioenergetics and improve oxygen utilization for treating long COVID-19.

Data-driven analysis to understand long COVID using electronic health records from the RECOVER initiative.

Recent studies have investigated post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) using real-world patient data such as electronic health records (EHR). Prior studies have typically been conducted on patient cohorts with specific patient populations which makes their generalizability unclear. This study aims to characterize PASC using the EHR data warehouses from two large Patient-Centered Clinical Research Networks (PCORnet), INSIGHT and OneFlorida+, which include 11 million patients in New York City (NYC) area and 16.8 million patients in Florida respectively. With a high-throughput screening pipeline based on propensity score and inverse probability of treatment weighting, we identified a broad list of diagnoses and medications which exhibited significantly higher incidence risk for patients 30-180 days after the laboratory-confirmed SARS-CoV-2 infection compared to non-infected patients. We identified more PASC diagnoses in NYC than in Florida regarding our screening criteria, and conditions including dementia, hair loss, pressure ulcers, pulmonary fibrosis, dyspnea, pulmonary embolism, chest pain, abnormal heartbeat, malaise, and fatigue, were replicated across both cohorts. Our analyses highlight potentially heterogeneous risks of PASC in different populations.

Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative.

Background: Patients who were SARS-CoV-2 infected could suffer from newly incidental conditions in their post-acute infection period. These conditions, denoted as the post-acute sequelae of SARS-CoV-2 infection (PASC), are highly heterogeneous and involve a diverse set of organ systems. Limited studies have investigated the predictability of these conditions and their associated risk factors. Method: In this retrospective cohort study, we investigated two large-scale PCORnet clinical research networks, INSIGHT and OneFlorida+, including 11 million patients in the New York City area and 16.8 million patients from Florida, to develop machine learning prediction models for those who are at risk for newly incident PASC and to identify factors associated with newly incident PASC conditions. Adult patients aged 20 with SARS-CoV-2 infection and without recorded infection between March 1st, 2020, and November 30th, 2021, were used for identifying associated factors with incident PASC after removing background associations. The predictive models were developed on infected adults. Results: We find several incident PASC, e.g., malnutrition, COPD, dementia, and acute kidney failure, were associated with severe acute SARS-CoV-2 infection, defined by hospitalization and ICU stay. Older age and extremes of weight were also associated with these incident conditions. These conditions were better predicted (C-index >0.8). Moderately predictable conditions included diabetes and thromboembolic disease (C-index 0.7-0.8). These were associated with a wider variety of baseline conditions. Less predictable conditions included fatigue, anxiety, sleep disorders, and depression (C-index around 0.6). Conclusions: This observational study suggests that a set of likely risk factors for different PASC conditions were identifiable from EHRs, predictability of different PASC conditions was heterogeneous, and using machine learning-based predictive models might help in identifying patients who were at risk of developing incident PASC.

Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes.

The post-acute sequelae of SARS-CoV-2 infection (PASC) refers to a broad spectrum of symptoms and signs that are persistent, exacerbated or newly incident in the period after acute SARS-CoV-2 infection. Most studies have examined these conditions individually without providing evidence on co-occurring conditions. In this study, we leveraged the electronic health record data of two large cohorts, INSIGHT and OneFlorida+, from the national Patient-Centered Clinical Research Network. We created a development cohort from INSIGHT and a validation cohort from OneFlorida+ including 20,881 and 13,724 patients, respectively, who were SARS-CoV-2 infected, and we investigated their newly incident diagnoses 30-180 days after a documented SARS-CoV-2 infection. Through machine learning analysis of over 137 symptoms and conditions, we identified four reproducible PASC subphenotypes, dominated by cardiac and renal (including 33.75% and 25.43% of the patients in the development and validation cohorts); respiratory, sleep and anxiety (32.75% and 38.48%); musculoskeletal and nervous system (23.37% and 23.35%); and digestive and respiratory system (10.14% and 12.74%) sequelae. These subphenotypes were associated with distinct patient demographics, underlying conditions before SARS-CoV-2 infection and acute infection phase severity. Our study provides insights into the heterogeneity of PASC and may inform stratified decision-making in the management of PASC conditions.

COVID-19 induces CNS cytokine expression and loss of hippocampal neurogenesis.

Infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with acute and postacute cognitive and neuropsychiatric symptoms including impaired memory, concentration, attention, sleep and affect. Mechanisms underlying these brain symptoms remain understudied. Here we report that SARS-CoV-2-infected hamsters exhibit a lack of viral neuroinvasion despite aberrant blood-brain barrier permeability. Hamsters and patients deceased from coronavirus disease 2019 (COVID-19) also exhibit microglial activation and expression of interleukin (IL)-1ß and IL-6, especially within the hippocampus and the medulla oblongata, when compared with non-COVID control hamsters and humans who died from other infections, cardiovascular disease, uraemia or trauma. In the hippocampal dentate gyrus of both COVID-19 hamsters and humans, we observed fewer neuroblasts and immature neurons. Protracted inflammation, blood-brain barrier disruption and microglia activation may result in altered neurotransmission, neurogenesis and neuronal damage, explaining neuropsychiatric presentations of COVID-19. The involvement of the hippocampus may explain learning, memory and executive dysfunctions in COVID-19 patients.

Machine Learning for Identifying Data-Driven Subphenotypes of Incident Post-Acute SARS-CoV-2 Infection Conditions with Large Scale Electronic Health Records: Findings from the RECOVER Initiative.

The post-acute sequelae of SARS-CoV-2 infection (PASC) refers to a broad spectrum of symptoms and signs that are persistent, exacerbated, or newly incident in the post-acute SARS-CoV-2 infection period of COVID-19 patients. Most studies have examined these conditions individually without providing concluding evidence on co-occurring conditions. To answer this question, this study leveraged electronic health records (EHRs) from two large clinical research networks from the national Patient-Centered Clinical Research Network (PCORnet) and investigated patients' newly incident diagnoses that appeared within 30 to 180 days after a documented SARS-CoV-2 infection. Through machine learning, we identified four reproducible subphenotypes of PASC dominated by blood and circulatory system, respiratory, musculoskeletal and nervous system, and digestive system problems, respectively. We also demonstrated that these subphenotypes were associated with distinct patterns of patient demographics, underlying conditions present prior to SARS-CoV-2 infection, acute infection phase severity, and use of new medications in the post-acute period. Our study provides novel insights into the heterogeneity of PASC and can inform stratified decision-making in the treatment of COVID-19 patients with PASC conditions.

COVID-19 induces neuroinflammation and loss of hippocampal neurogenesis.

Infection with the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is associated with onset of neurological and psychiatric symptoms during and after the acute phase of illness 1-4 . Acute SARS-CoV-2 disease (COVID-19) presents with deficits of memory, attention, movement coordination, and mood. The mechanisms of these central nervous system symptoms remain largely unknown.In an established hamster model of intranasal infection with SARS-CoV-2 5 , and patients deceased from COVID-19, we report a lack of viral neuroinvasion despite aberrant BBB permeability, microglial activation, and brain expression of interleukin (IL)-1ß and IL-6, especially within the hippocampus and the inferior olivary nucleus of the medulla, when compared with non-COVID control hamsters and humans who died from other infections, cardiovascular disease, uremia or trauma. In the hippocampus dentate gyrus of both COVID-19 hamsters and humans, fewer cells expressed doublecortin, a marker of neuroblasts and immature neurons.Despite absence of viral neurotropism, we find SARS-CoV-2-induced inflammation, and hypoxia in humans, affect brain regions essential for fine motor function, learning, memory, and emotional responses, and result in loss of adult hippocampal neurogenesis. Neuroinflammation could affect cognition and behaviour via disruption of brain vasculature integrity, neurotransmission, and neurogenesis, acute effects that may persist in COVID-19 survivors with long-COVID symptoms.

Anxiety, depression, insomnia, and trauma-related symptoms following COVID-19 infection at long-term follow-up.

A developing finding from the novel coronavirus 2019 (COVID-19) pandemic is the burden of neuropsychiatric symptoms seen in COVID-19 survivors. While studies have shown clinically significant rates of depression, anxiety, insomnia, and trauma-related symptoms such as post-traumatic stress disorder (PTSD) after COVID-19, little is known about how these symptoms evolve over time. Here, we report findings from a cohort study of 52 participants recruited from the greater New York City area following acute COVID-19 infection. Participants completed the Patient Health Questionnaire-9 (PHQ-9) for depressive symptoms, the Generalized Anxiety Disorder-7 (GAD-7) for anxiety-related symptoms, the Insomnia Severity Scale (ISS) for sleep-related symptoms, and the PTSD Checklist-Civilian version (PCL-C) for trauma-related symptoms both at baseline and at long-term (24-60 weeks post-infection) follow-up. We found a high degree of correlation between psychiatric symptom scales within participants. More participants met established cutoffs for clinically significant insomnia and post-traumatic stress at follow-up compared to baseline. Symptom scales for depression, insomnia, and PTSD were increased at long-term follow-up, with only increased PCL-C scores surviving correction for multiple comparisons (Z â€‹= â€‹2.92, W â€‹= â€‹434, p â€‹= â€‹0.004). Our results present evidence from a small cohort that neuropsychiatric symptoms, particularly those related to PTSD, may worsen over time in COVID-19 survivors. Future studies should continue to investigate these questions in broader populations, while additionally exploring the potential biological and sociological mechanisms that may contribute to neuropsychiatric pathology after COVID-19 infection.

Potential Neurologic Manifestations of COVID-19.

PURPOSE OF REVIEW: Neurologic complications are increasingly recognized in the coronavirus disease 2019 (COVID-19) pandemic. COVID-19 is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This coronavirus is related to severe acute respiratory syndrome coronavirus (SARS-CoV) and other human coronavirus-related illnesses that are associated with neurologic symptoms. These symptoms raise the question of a neuroinvasive potential of SARS-CoV-2. RECENT FINDINGS: Potential neurologic symptoms and syndromes of SARS-CoV-2 include headache, fatigue, dizziness, anosmia, ageusia, anorexia, myalgias, meningoencephalitis, hemorrhage, altered consciousness, Guillain-Barré syndrome, syncope, seizure, and stroke. In addition, we discuss neurologic effects of other coronaviruses, special considerations for management of neurologic patients, and possible long-term neurologic and public health sequelae. SUMMARY: As SARS-CoV-2 is projected to infect a large part of the world's population, understanding the potential neurologic implications of COVID-19 will help neurologists and others recognize and intervene in neurologic morbidity during and after the pandemic of 2020.

COVID-19 neuropathology at Columbia University Irving Medical Center/New York Presbyterian Hospital.

Many patients with SARS-CoV-2 infection develop neurological signs and symptoms; although, to date, little evidence exists that primary infection of the brain is a significant contributing factor. We present the clinical, neuropathological and molecular findings of 41 consecutive patients with SARS-CoV-2 infections who died and underwent autopsy in our medical centre. The mean age was 74 years (38-97 years), 27 patients (66%) were male and 34 (83%) were of Hispanic/Latinx ethnicity. Twenty-four patients (59%) were admitted to the intensive care unit. Hospital-associated complications were common, including eight patients (20%) with deep vein thrombosis/pulmonary embolism, seven (17%) with acute kidney injury requiring dialysis and 10 (24%) with positive blood cultures during admission. Eight (20%) patients died within 24 h of hospital admission, while 11 (27%) died more than 4 weeks after hospital admission. Neuropathological examination of 20-30 areas from each brain revealed hypoxic/ischaemic changes in all brains, both global and focal; large and small infarcts, many of which appeared haemorrhagic; and microglial activation with microglial nodules accompanied by neuronophagia, most prominently in the brainstem. We observed sparse T lymphocyte accumulation in either perivascular regions or in the brain parenchyma. Many brains contained atherosclerosis of large arteries and arteriolosclerosis, although none showed evidence of vasculitis. Eighteen patients (44%) exhibited pathologies of neurodegenerative diseases, which was not unexpected given the age range of our patients. We examined multiple fresh frozen and fixed tissues from 28 brains for the presence of viral RNA and protein, using quantitative reverse-transcriptase PCR, RNAscope® and immunocytochemistry with primers, probes and antibodies directed against the spike and nucleocapsid regions. The PCR analysis revealed low to very low, but detectable, viral RNA levels in the majority of brains, although they were far lower than those in the nasal epithelia. RNAscope® and immunocytochemistry failed to detect viral RNA or protein in brains. Our findings indicate that the levels of detectable virus in coronavirus disease 2019 brains are very low and do not correlate with the histopathological alterations. These findings suggest that microglial activation, microglial nodules and neuronophagia, observed in the majority of brains, do not result from direct viral infection of brain parenchyma, but more likely from systemic inflammation, perhaps with synergistic contribution from hypoxia/ischaemia. Further studies are needed to define whether these pathologies, if present in patients who survive coronavirus disease 2019, might contribute to chronic neurological problems.

Post-acute COVID-19 syndrome.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) pandemic, which has resulted in global healthcare crises and strained health resources. As the population of patients recovering from COVID-19 grows, it is paramount to establish an understanding of the healthcare issues surrounding them. COVID-19 is now recognized as a multi-organ disease with a broad spectrum of manifestations. Similarly to post-acute viral syndromes described in survivors of other virulent coronavirus epidemics, there are increasing reports of persistent and prolonged effects after acute COVID-19. Patient advocacy groups, many members of which identify themselves as long haulers, have helped contribute to the recognition of post-acute COVID-19, a syndrome characterized by persistent symptoms and/or delayed or long-term complications beyond 4 weeks from the onset of symptoms. Here, we provide a comprehensive review of the current literature on post-acute COVID-19, its pathophysiology and its organ-specific sequelae. Finally, we discuss relevant considerations for the multidisciplinary care of COVID-19 survivors and propose a framework for the identification of those at high risk for post-acute COVID-19 and their coordinated management through dedicated COVID-19 clinics.

COVID-19 and possible links with Parkinson's disease and parkinsonism: from bench to bedside.

This Viewpoint discusses insights from basic science and clinical perspectives on coronavirus disease 2019 (COVID-19)/severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection in the brain, with a particular focus on Parkinson's disease. Major points include that neuropathology studies have not answered the central issue of whether the virus enters central nervous system neurons, astrocytes or microglia, and the brain vascular cell types that express virus have not yet been identified. Currently, there is no clear evidence for human neuronal or astrocyte expression of angiotensin-converting enzyme 2 (ACE2), the major receptor for viral entry, but ACE2 expression may be activated by inflammation, and a comparison of healthy and infected brains is important. In contrast to the 1918 influenza pandemic and avian flu, reports of encephalopathy in COVID-19 have been slow to emerge, and there are so far no documented reports of parkinsonism apart from a single case report. We recommend consensus guidelines for the clinical treatment of Parkinson's patients with COVID-19. While a role for the virus in causing or exacerbating Parkinson's disease appears unlikely at this time, aggravation of specific motor and non-motor symptoms has been reported, and it will be important to monitor subjects after recovery, particularly for those with persisting hyposmia.

Neuronophagia and microglial nodules in a SARS-CoV-2 patient with cerebellar hemorrhage.

We document the neuropathologic findings of a 73-year old man who died from acute cerebellar hemorrhage in the context of relatively mild SARS-CoV2 infection. The patient developed sudden onset of headache, nausea, and vomiting, immediately followed by loss of consciousness on the day of admission. Emergency medical services found him severely hypoxemic at home, and the patient suffered a cardiac arrest during transport to the emergency department. The emergency team achieved return of spontaneous circulation after over 17 min of resuscitation. A chest radiograph revealed hazy bilateral opacities; and real-time-PCR for SARS-CoV-2 on the nasopharyngeal swab was positive. Computed tomography of the head showed a large right cerebellar hemorrhage, with tonsillar herniation and intraventricular hemorrhage. One day after presentation, he was transitioned to comfort care and died shortly after palliative extubation. Autopsy performed 3 h after death showed cerebellar hemorrhage and acute infarcts in the dorsal pons and medulla. Remarkably, there were microglial nodules and neuronophagia bilaterally in the inferior olives and multifocally in the cerebellar dentate nuclei. This constellation of findings has not been reported thus far in the context of SARS-CoV-2 infection.

Extrapulmonary manifestations of COVID-19.

Although COVID-19 is most well known for causing substantial respiratory pathology, it can also result in several extrapulmonary manifestations. These conditions include thrombotic complications, myocardial dysfunction and arrhythmia, acute coronary syndromes, acute kidney injury, gastrointestinal symptoms, hepatocellular injury, hyperglycemia and ketosis, neurologic illnesses, ocular symptoms, and dermatologic complications. Given that ACE2, the entry receptor for the causative coronavirus SARS-CoV-2, is expressed in multiple extrapulmonary tissues, direct viral tissue damage is a plausible mechanism of injury. In addition, endothelial damage and thromboinflammation, dysregulation of immune responses, and maladaptation of ACE2-related pathways might all contribute to these extrapulmonary manifestations of COVID-19. Here we review the extrapulmonary organ-specific pathophysiology, presentations and management considerations for patients with COVID-19 to aid clinicians and scientists in recognizing and monitoring the spectrum of manifestations, and in developing research priorities and therapeutic strategies for all organ systems involved.

The cognitive aspects of sexual intimacy in dementia patients: a neurophysiological review.

Changes in higher-order cognitive behaviors such as reward recognition, salience processing, novelty perception, decision-making, emotional contagion, motivation, and empathy may contribute to intimacy dysfunction. Network circuitry underlying these cognitive functions is often activated in sexually intimate behavior. We propose that sexual dysfunction in AD and bvFTD is more nuanced than is commonly believed, and propose how AD and bvFTD atrophy may correlate neuroanatomically to brain regions and networks that contribute to the higher-order cognitive aspects of intimacy. The characterization of sexual intimacy in dementias must be expanded to meet the needs of our dementia patients and their romantic partners.