Earliest histopathological changes in COVID-19 pneumonia with comprehensive gene expression analyses: A case series study.

AIMS: In COVID-19 pneumonia, early detection and appropriate treatment are essential to prevent severe exacerbation. Therefore, it is important to understand the initiating events of COVID-19 pneumonia. However, at present, the literature about early stage disease has been very limited. Here, we investigated the earliest histopathological changes and gene expression profiles associated with COVID-19 pneumonia. METHODS AND RESULTS: We carefully examined 25 autopsied cases with different clinical courses. Dilation of capillaries and edematous thickening of the alveolar septa were found even in areas that macroscopically looked almost normal. Pneumocytes, histocytes/macrophages, and vascular endothelial cells were immunohistochemically positive for tissue factor, which is an important early responder to tissue injuries. Comprehensive gene expression analyses revealed that those lesions presented differential profiles compared to those of control lungs and were associated with a significant upregulation of the lysosomal pathway. CONCLUSIONS: Alveolar capillary dilation and edematous thickening may be the earliest histopathological change detected in COVID-19 pneumonia. Intensive investigations of such lesions may lead to an understanding of the initiating event of not only COVID-19 pneumonia but also of general diffuse alveolar damage.

Living Alone and Depressive Symptoms Among Older Adults in the COVID-19 Pandemic: Role of Non-Face-to-Face Social Interactions.

OBJECTIVE: This study examined the association of living alone with changes in depressive symptom status and the moderating effect of non-face-to-face social interactions among older adults during the coronavirus disease (COVID-19) pandemic. DESIGN: A longitudinal study. SETTING AND PARTICIPANTS: This study recruited individuals aged ≥ 65 years without long-term care in one semi-urban city in Japan, who completed mailed questionnaires in March (baseline) and October 2020 (follow-up). METHODS: Based on depressive symptoms assessed by the Two-Question Screening at baseline and follow-up, participants were classified as: "non-case," "onset," "remission," and "persistence." Non-face-to-face social interactions during the pandemic, including phone calls or emails with separated families or friends, were dichotomized as "less than weekly interactions" and "weekly interactions." A multinomial logistic regression analysis was conducted to examine the association of living arrangement (living alone or together) with changes in depressive symptoms status. RESULTS: Data of 1001 participants were analyzed (mean age = 79.9 years). Of them, 13.8% lived alone. Overall, 40.6% participants were grouped as "non-case," 11.7% as "onset," 11.0% as "remission," and 27.1% as "persistence." Living alone was significantly associated with depressive symptom onset (odds ratio: 1.92; 95% CI: 1.03-3.56; P = .039), and a negative interaction (protective effect) was found between living alone and weekly non-face-to-face social interactions for depressive symptom onset. CONCLUSION AND IMPLICATIONS: During the pandemic, older adults living alone had a higher depressive symptom risk, but non-face-to-face social interactions may have buffered this risk. Our findings suggest the importance of supporting older adults living alone in times of social restrictions such as the pandemic, and furthermore, maintaining social connections, including non-face-to-face relationships, is necessary to protect their mental health.

Machine-Learning Approaches for Predicting the Need of Oxygen Therapy in Early-Stage COVID-19 in Japan: Multicenter Retrospective Observational Study.

Background: Early prediction of oxygen therapy in patients with coronavirus disease 2019 (COVID-19) is vital for triage. Several machine-learning prognostic models for COVID-19 are currently available. However, external validation of these models has rarely been performed. Therefore, most reported predictive performance is optimistic and has a high risk of bias. This study aimed to develop and validate a model that predicts oxygen therapy needs in the early stages of COVID-19 using a sizable multicenter dataset. Methods: This multicenter retrospective study included consecutive COVID-19 hospitalized patients confirmed by a reverse transcription chain reaction in 11 medical institutions in Fukui, Japan. We developed and validated seven machine-learning models (e.g., penalized logistic regression model) using routinely collected data (e.g., demographics, simple blood test). The primary outcome was the need for oxygen therapy (≥1 L/min or SpO2 ≤ 94%) during hospitalization. C-statistics, calibration slope, and association measures (e.g., sensitivity) evaluated the performance of the model using the test set (randomly selected 20% of data for internal validation). Among these seven models, the machine-learning model that showed the best performance was re-evaluated using an external dataset. We compared the model performances using the A-DROP criteria (modified version of CURB-65) as a conventional method. Results: Of the 396 patients with COVID-19 for the model development, 102 patients (26%) required oxygen therapy during hospitalization. For internal validation, machine-learning models, except for the k-point nearest neighbor, had a higher discrimination ability than the A-DORP criteria (P < 0.01). The XGboost had the highest c-statistic in the internal validation (0.92 vs. 0.69 in A-DROP criteria; P < 0.001). For the external validation with 728 temporal independent datasets (106 patients [15%] required oxygen therapy), the XG boost model had a higher c-statistic (0.88 vs. 0.69 in A-DROP criteria; P < 0.001). Conclusions: Machine-learning models demonstrated a more significant performance in predicting the need for oxygen therapy in the early stages of COVID-19.

DOCK2 is involved in the host genetics and biology of severe COVID-19.

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1-5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

Association between decreased frequency of seeing friends and the onset of depressive symptoms among community-dwelling older adults: A longitudinal study

Objevtives : Mental health among the older adults has been shown to be affected by reduced social interaction with friends. However, this relationship has not been confirmed in short periods of limited social interaction, such as that experienced during the COVID-19 pandemic. In this study, we investigated the relationship between the development of depressive symptoms and a 6-month decrease in the frequency of visits with friends among community-dwelling elderly in Japan. Methods : Participants were 491 community-dwelling older adults aged 65 years or older (47.5% female, mean age [standard deviation] = 80.5 [4.7] years) who responded to the March 2020 baseline survey by mail questionnaire and the October 2020 follow-up survey. Results : The onset of depressive symptoms was observed in 22.8% in about 6 months. The change in frequency of seeing friends, 56.2% remained unchanged, 23.2% increased, and 20.6% decreased. A logistic regression analysis with maintenance of frequency of seeing friends as a reference showed that a decreased frequency of seeing friends was significantly associated with the incidence of depressive symptoms. (odds ratio = 2.26, 95% confidence interval = 1.32-3.86, p = 0.003). Discussion : A decrease in the frequency of seeing friends over even a short period of time can have a negative impact on older adults’ mental health. The findings suggest that in situations where the frequency of seeing friends decreases during a short period of time, maintaining interaction with friends and avoiding face-to-face restrictions is important for maintaining the mental health of older adults.

Eating alone and weight change in community-dwelling older adults during the coronavirus pandemic: A longitudinal study.

OBJECTIVES: It is likely that the number of older adults who eat alone has increased during the COVID-19 pandemic. Older adults who eat alone tend to experience weight fluctuations. Weight loss and underweight in older adults cause health problems. The study objective was to longitudinally investigate the association between changes in eating alone or with others and body weight status in older adults. METHODS: This longitudinal cohort study was conducted in March and October 2020 in Minokamo City, Gifu Prefecture, Japan. Questionnaire data for 1071 community-dwelling older adults were analyzed. Multinomial logistic regression analysis was performed using changes in eating alone or with others as the independent variable and body weight status as the dependent variable. The analysis was adjusted for age, sex, living arrangements, educational level, diseases receiving medical treatment, cognitive status, depression, and instrumental activities of daily living. Missing data were imputed using multiple imputation. RESULTS: The average age of participants was 81.1 y (SD, 4.9 y). Individuals who reported eating alone in both surveys were more likely to report weight loss than those who reported eating with others in both surveys (adjusted model: odds ratio, 2.25; 95% confidence interval, 1.06-4.78; P = 0.04). CONCLUSIONS: These findings suggest that measures to prevent weight loss in older adults who eat alone are particularly important during the COVID-19 pandemic.

An autopsy case of COVID-19-like acute respiratory distress syndrome after mRNA-1273 SARS-CoV-2 vaccination.

We report the first case with COVID-19-like acute respiratory distress syndrome after mRNA-1273 SARS-CoV-2 vaccination. An 88-year-old woman developed dyspnea several hours after vaccination with the second dose of mRNA-1273. She was hospitalized on day nine due to worsening dyspnea. Chest computed tomography showed bilateral ground-glass opacities and consolidations, mainly in the peripheral lung areas. Repeat polymerase chain reaction tests for SARS-CoV-2 were negative, although the serum level of antibodies against spike protein was extremely elevated. Her condition did not improve with high-dose corticosteroids and high-flow nasal cannula oxygen therapy; she died on day 18. Autopsy findings revealed very early-phase diffuse alveolar damage in the whole lung without other lung diseases. The clinical and pathological findings suggested vaccine-induced acute respiratory distress syndrome. Serological and pathological tests might be useful to differentiate the disease from COVID-19.

Machine-Learning Approaches for Predicting the Need of Oxygen Therapy in Early-Stage COVID-19 in Japan: Multicenter Retrospective Observational Study

Background Early prediction of oxygen therapy in patients with coronavirus disease 2019 (COVID-19) is vital for triage. Several machine-learning prognostic models for COVID-19 are currently available. However, external validation of these models has rarely been performed. Therefore, most reported predictive performance is optimistic and has a high risk of bias. This study aimed to develop and validate a model that predicts oxygen therapy needs in the early stages of COVID-19 using a sizable multicenter dataset. Methods This multicenter retrospective study included consecutive COVID-19 hospitalized patients confirmed by a reverse transcription chain reaction in 11 medical institutions in Fukui, Japan. We developed and validated seven machine-learning models (e.g., penalized logistic regression model) using routinely collected data (e.g., demographics, simple blood test). The primary outcome was the need for oxygen therapy (≥1 L/min or SpO2 ≤ 94%) during hospitalization. C-statistics, calibration slope, and association measures (e.g., sensitivity) evaluated the performance of the model using the test set (randomly selected 20% of data for internal validation). Among these seven models, the machine-learning model that showed the best performance was re-evaluated using an external dataset. We compared the model performances using the A-DROP criteria (modified version of CURB-65) as a conventional method. Results Of the 396 patients with COVID-19 for the model development, 102 patients (26%) required oxygen therapy during hospitalization. For internal validation, machine-learning models, except for the k-point nearest neighbor, had a higher discrimination ability than the A-DORP criteria (P < 0.01). The XGboost had the highest c-statistic in the internal validation (0.92 vs. 0.69 in A-DROP criteria;P < 0.001). For the external validation with 728 temporal independent datasets (106 patients [15%] required oxygen therapy), the XG boost model had a higher c-statistic (0.88 vs. 0.69 in A-DROP criteria;P < 0.001). Conclusions Machine-learning models demonstrated a more significant performance in predicting the need for oxygen therapy in the early stages of COVID-19.

Family Caregiving and Depression among Older Adults in Japan: A Cross-Sectional Study during the COVID-19 Pandemic

COVID-19 infections are particularly lethal in older adults;thus, social activities of older adults and their families in the community have been restricted. The threat of infection, restrictions on social activities, and limitations on the provision of care services for older adults could increase family caregivers’ burden and impact their mental health. This cross-sectional study examined the association between family caregiving and change in depression during the COVID-19 pandemic. In October 2020, we conducted a mailed questionnaire survey on a random sample of functionally independent community-dwelling older adults in a semi-urban area of Japan. Based on the depression status between March and October 2020, participants were classified into four groups: “consistently non-depressed,” “depression onset,” “recovering from depression,” and “remained depressed.” Participants were assessed for providing care for their family members or not. Caregiver participants were also assessed on their caregiving role (primary or secondary), the severity of their care-recipient’s needs, and an increased caregiver burden. Data from 957 older adults were analyzed. The participants’ mean age (SD) was 80.8 (4.8) years, and 53.5% were female. Multivariable multinomial logistic regression analysis revealed that family caregiving was associated with depression onset (OR=3.17 [95%CI=1.57-6.40], p=0.001) and remaining depressed (2.53 [1.36-4.71], p=0.004). Particularly, primary caregivers, those providing care for family members with severer care need-levels, and those with an increased caregiver burden had a higher risk of depression onset and remaining depressed. Family caregivers could have severe mental health conditions during the pandemic. Developing a support system is essential to protect their mental health.

Social frailty and depressive symptoms during the COVID-19 pandemic among older adults in Japan: Role of home exercise habits.

OBJECTIVES: We examined the association between social frailty and depressive symptoms among community-dwelling older adults during the coronavirus disease 2019 pandemic. Additionally, we investigated whether home exercise habits moderated the impact of social frailty on depressive symptoms. METHODS: This cross-sectional study included 1,103 community-dwelling older adults (54.0% female, mean age [standard deviation] = 81.1 [5.0] years) from a semi-urban area of Japan who completed a mailed questionnaire survey in October 2020. Social frailty status was categorized as non-social frailty, pre-social frailty, and social frailty, which was assessed by financial difficulties, living alone, lack of social activity, and contact with neighbors. Depressive symptoms were defined as a Kessler 6 score ≥5. We performed a multivariable logistic regression analysis to examine the association between social frailty and depressive symptoms, and also conducted stratified analysis of home exercise habits during the pandemic. RESULTS: A total of 309 (28.0%) participants had depressive symptoms. Compared with non-social frailty, social frailty was associated with depressive symptoms (odds ratio [OR] = 1.80, 95% confidence interval [95%CI] = 1.16-2.79, p = 0.009). A similar relationship was observed in those who did not exercise at home (OR = 2.10, 95%CI = 1.14-3.84, p =0.017). However, no such relationship was observed in those who did exercise at home (OR = 1.50, 95%CI = 0.79-2.85, p =0.213). CONCLUSIONS: Social frailty was associated with a risk of depressive symptoms during the pandemic. In addition, our findings suggested that home exercise may buffer the association between social frailty and depressive symptoms.

Changes in psychosocial factors among community-dwelling older adults before and after Japan's declaration of a state of emergency over coronavirus disease 2019.

BACKGROUND: Social distancing measures to prevent the spread of coronavirus disease 2019 may cause changes in psychosocial factors. This study aimed to clarify changes in psychosocial factors among older adults before and after Japan's declaration of a state of emergency over coronavirus disease 2019. METHODS: This was a longitudinal cohort questionnaire study. A baseline survey was conducted in March 2020, and a follow-up survey was conducted in August 2020. The subjects were 1103 community-dwelling older adults not certified as having long-term care needs who responded to both the baseline and follow-up surveys. Changes in psychosocial factors before and after the state of emergency declaration were analysed by gender using the McNemar-Bowker test. RESULTS: Data for 397 men (mean age ± standard deviation: 80.6 ± 4.7 years) and 486 women (80.3 ± 4.3 years) were analysed in this study. The frequency of meeting friends increased over the study period for men (P = 0.04). An increasing number of women lived alone (P = 0.01). However, many people's financial status improved (P < 0.01), and the number of friends met in the previous month increased (P < 0.01). CONCLUSIONS: None of the examined psychosocial factors worsened, except for the increase in the number of women living alone. However, many of the study subjects refrained from engaging in certain activities. If the coronavirus disease 2019 pandemic persists, changes in psychosocial factors may occur. Therefore, a long-term investigation of the secondary psychosocial effects of coronavirus disease 2019 is necessary.

Association between family caregivers and depressive symptoms among community-dwelling older adults in Japan: A cross-sectional study during the COVID-19 pandemic.

OBJECTIVES: Novel coronavirus disease (COVID-19) pandemic could increase the mental health burden of family caregivers of older adults, but related reports are limited. We examined the association between family caregiving and changes in the depressive symptom status during the pandemic. METHODS: This cross-sectional study included 957 (mean age [standard deviation] = 80.8 [4.8] years; 53.5% females) community-dwelling older adults aged ≥ 65 years from a semi-urban area of Japan, who completed a mailed questionnaire. Based on the depressive symptom status assessed with the Two-Question Screen between March and October 2020, participants were classified into four groups: "non-depressive symptoms," "incidence of depressive symptoms," "remission from depressive symptoms," or "persistence of depressive symptoms." Participants were assessed in October 2020 for the family caregiving status, caregiving role, the severity of care recipients' needs, and increased caregiver burden during the pandemic, each with the simple question. Multinomial logistic regression analysis was applied to obtain the odds ratios (ORs) and 95% confidence intervals (CIs) for changes in depressive symptom status. RESULTS: Compared to non-caregivers, family caregivers were associated with the incidence (OR [95% CI] = 3.17 [1.55-6.51], p < 0.01) and persistence of depressive symptoms (OR [95% CI] = 2.39 [1.30-4.38], p < 0.01). Primary caregivers, caregivers for individuals with severe care needs, and caregivers with increased burden during the pandemic had a high risk of depressive symptoms. CONCLUSIONS: Family caregivers had a high risk of depressive symptoms during the pandemic. Our findings highlight the need for a support system for family caregivers.

Social Isolation and Self-Reported Cognitive Decline Among Older Adults in Japan: A Longitudinal Study in the COVID-19 Pandemic.

OBJECTIVES: We aimed to examine the association between the transition to social isolation and cognitive decline in older adults during the coronavirus disease 2019 (COVID-19) pandemic. DESIGN: Longitudinal study. SETTING AND PARTICIPANTS: The study included participants from a community in a semiurban area of Japan. We conducted a mailed questionnaire survey of 2000 noninstitutionalized older adults who were randomly sampled. Of those who completed both the baseline and follow-up surveys in March and October 2020, respectively, participants aged ≥70 years without cognitive impairment at baseline were included in the analysis. METHODS: Participants were classified into 4 groups based on their baseline and follow-up social isolation status, which were as follows: "remained nonisolated," "isolated from nonisolation," "nonisolated from isolation," and "consistent isolation." Self-reported cognitive function was assessed using the Cognitive Performance Scale, and level 2 (mild impairment) or higher (moderate to severe impairment) was defined as cognitive impairment. RESULTS: Ultimately, 955 older adults were analyzed. The mean age of the participants was 79.6 years (standard deviation = 4.7) and 54.7% were women. During the follow-up period, 54 (5.7%) participants developed cognitive impairment. Multivariable logistic regression analysis revealed that compared with the group that remained nonisolated, the isolated from nonisolation and consistent isolation groups were significantly associated with the onset of cognitive impairment [isolated from nonisolation: odds ratio (OR) = 2.74, 95% confidence interval (CI) = 1.13-6.61, P = .026; consistent isolation: OR = 2.33, 95% CI = 1.07-5.05, P = .033]. CONCLUSIONS AND IMPLICATIONS: Social isolation during the COVID-19 pandemic was associated with a decline in cognitive function among older adults. Attention to the social isolation process during the pandemic may be necessary to protect older adults' cognitive health.

Highly specific monoclonal antibodies and epitope identification against SARS-CoV-2 nucleocapsid protein for antigen detection tests.

The ongoing coronavirus disease 2019 (COVID-19) pandemic is a major global public health concern. Although rapid point-of-care testing for detecting viral antigen is important for management of the outbreak, the current antigen tests are less sensitive than nucleic acid testing. In our current study, we produce monoclonal antibodies (mAbs) that exclusively react with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and exhibit no cross-reactivity with other human coronaviruses, including SARS-CoV. Molecular modeling suggests that the mAbs bind to epitopes present on the exterior surface of the nucleocapsid, making them suitable for detecting SARS-CoV-2 in clinical samples. We further select the optimal pair of anti-SARS-CoV-2 nucleocapsid protein (NP) mAbs using ELISA and then use this mAb pair to develop immunochromatographic assay augmented with silver amplification technology. Our mAbs recognize the variants of concern (501Y.V1-V3) that are currently in circulation. Because of their high performance, the mAbs of this study can serve as good candidates for developing antigen detection kits for COVID-19.

A Japanese case of COVID-19: An autopsy report.

A 93-year-old woman was admitted with a 10-day history of cough and prostration. Thoracic computed tomography revealed extensive ground-glass opacities in both the lungs. The polymerase chain reaction test of sputum for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) was positive. She was treated with antiviral agents and steroid pulse therapy. However, her oxygen saturation gradually declined, and she died 10 days after hospitalization. The most important autopsy finding was fuzzily segmented diffuse alveolar damage (DAD) that expanded from the subpleural to the medial area. No remarkable changes were observed in organs other than the lungs. Therefore, pneumocytes were suggested as the primary target for SARS-CoV-2, which might explain why coronavirus infectious disease-19 is a serious condition. Thus, early treatment is essential to prevent viral replication from reaching a level that triggers DAD.