6,995 research outputs found
Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data
No full textDiffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample
Pathogen-sugar interactions revealed by universal saturation transfer analysis
No full textMany pathogens exploit host cell-surface glycans. However, precise analyses of glycan ligands binding with heavily modified pathogen proteins can be confounded by overlapping sugar signals and/or compounded with known experimental constraints. Universal saturation transfer analysis (uSTA) builds on existing nuclear magnetic resonance spectroscopy to provide an automated workflow for quantitating protein-ligand interactions. uSTA reveals that early-pandemic, B-origin-lineage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike trimer binds sialoside sugars in an "end-on"manner. uSTA-guided modeling and a high-resolution cryo-electron microscopy structure implicate the spike N-terminal domain (NTD) and confirm end-on binding. This finding rationalizes the effect of NTD mutations that abolish sugar binding in SARS-CoV-2 variants of concern. Together with genetic variance analyses in early pandemic patient cohorts, this binding implicates a sialylated polylactosamine motif found on tetraantennary N-linked glycoproteins deep in the human lung as potentially relevant to virulence and/or zoonosis
An explainable model of host genetic interactions linked to COVID-19 severity
No full textWe employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, supporting their link with COVID-19 severity outcome
Trajectory of Gastrointestinal Symptoms in Previously Hospitalized COVID-19 Survivors: The Long COVID Experience Multicenter Study
No full textThis multicenter cohort study used Sankey plots and exponential bar plots to visualize the fluctuating evolution and the trajectory of gastrointestinal symptoms in previously hospitalized COVID-19 survivors during the first 18 months after acute SARS-CoV-2 infection. A total of 1266 previously hospitalized COVID-19 survivors were assessed at four points: hospital admission (T0), at 8.4 months (T1), at 13.2 months (T2), and at 18.3 months (T3) after hospitalization. Participants were asked about their overall gastrointestinal symptoms and particularly diarrhea. Clinical and hospitalization data were collected from hospital medical records. The prevalence of overall gastrointestinal post-COVID symptomatology was 6.3% (n = 80) at T1, 3.99% (n = 50) at T2 and 2.39% (n = 32) at T3. The prevalence of diarrhea decreased from 10.69% (n = 135) at hospital admission (T0), to 2.55% (n = 32) at T1, to 1.04% (n = 14) at T2, and to 0.64% (n = 8) at T3. The Sankey plots revealed that just 20 (1.59%) and 4 (0.32%) patients exhibited overall gastrointestinal post-COVID symptoms or diarrhea, respectively, throughout the whole follow-up period. The recovery fitted exponential curves revealed a decreasing prevalence trend, showing that diarrhea and gastrointestinal symptoms recover during the first two or three years after COVID-19 in previously hospitalized COVID-19 survivors. The regression models did not reveal any symptoms to be associated with the presence of gastrointestinal post-COVID symptomatology or post-COVID diarrhea at hospital admission or at T1. The use of Sankey plots revealed the fluctuating evolution of gastrointestinal post-COVID symptoms during the first two years after infection. In addition, exponential bar plots revealed the decreased prevalence of gastrointestinal post-COVID symptomatology during the first three years after infection
Shorter androgen receptor polyQ alleles protect against life-threatening COVID-19 disease in European males
No full textBackground: While SARS-CoV-2 similarly infects men and women, COVID-19 outcome is less favorable in men. Variability in COVID-19 severity may be explained by differences in the host genome.
Methods: We compared poly-amino acids variability from WES data in severely affected COVID-19 patients versus SARS-CoV-2 PCR-positive oligo-asymptomatic subjects. Findings: Shorter polyQ alleles (≤22) in the androgen receptor (AR) conferred protection against severe outcome in COVID-19 in the first tested cohort (both males and females) of 638 Italian subjects. The association between long polyQ alleles (≥23) and severe clinical outcome (p = 0.024) was also validated in an independent cohort of Spanish men <60 years of age (p = 0.014). Testosterone was higher in subjects with AR long-polyQ, possibly indicating receptor resistance (p = 0.042 Mann-Whitney U test). Inappropriately low serum testosterone level among carriers of the long-polyQ alleles (p = 0.0004 Mann-Whitney U test) predicted the need for intensive care in COVID-19 infected men. In agreement with the known anti-inflammatory action of testosterone, patients with long-polyQ and age ≥60 years had increased levels of CRP (p = 0.018, not accounting for multiple testing). Interpretation: We identify the first genetic polymorphism that appears to predispose some men to develop more severe disease. Failure of the endocrine feedback to overcome AR signaling defects by increasing testosterone levels during the infection leads to the polyQ tract becoming dominant to serum testosterone levels for the clinical outcome. These results may contribute to designing reliable clinical and public health measures and provide a rationale to test testosterone as adjuvant therapy in men with COVID-19 expressing long AR polyQ repeats.Funding: MIUR project "Dipartimenti di Eccellenza 2018-2020" to Department of Medical Biotechnologies University of Siena, Italy (Italian D.L. n.18 March 17, 2020) and "Bando Ricerca COVID-19 Toscana" project to Azienda Ospedaliero-Universitaria Senese. Private donors for COVID-19 research and charity funds from Intesa San Paol
a European multicenter comparative cohort study
No full textFunding Information: AR received personal fees from Maat Pharma, IML received personal fees from MSD, and Gilead. AA received personal fees from Lilly Foundation, and grants from Grifols and Fisher & Paykel. CEL received personal fees from Bayer, Merck, Aerogen, Biomérieux, ThermoFisher Brahms, and Carmat. SN received personal fees from MSD, Bio-Rad, BioMérieux, Gilead, Fisher and Paykel, and Pfizer. All other authors declare no competing interests. Funding Information: This study was supported in part by a grant from the French government through the « Programme Investissement d’Avenir» (I-SITE ULNE) managed by the Agence Nationale de la Recherche (coVAPid project). Prof. Ignacio Martin-Loeches has been supported by SFI (Science Foundation Ireland), Grant Number 20/COV/0038. The funders of the study had no role in the study design, data collection, analysis, or interpretation, writing of the report, or decision to submit for publication. Publisher Copyright: © 2022, The Author(s).Background: Recent multicenter studies identified COVID-19 as a risk factor for invasive pulmonary aspergillosis (IPA). However, no large multicenter study has compared the incidence of IPA between COVID-19 and influenza patients. Objectives: To determine the incidence of putative IPA in critically ill SARS-CoV-2 patients, compared with influenza patients. Methods: This study was a planned ancillary analysis of the coVAPid multicenter retrospective European cohort. Consecutive adult patients requiring invasive mechanical ventilation for > 48 h for SARS-CoV-2 pneumonia or influenza pneumonia were included. The 28-day cumulative incidence of putative IPA, based on Blot definition, was the primary outcome. IPA incidence was estimated using the Kalbfleisch and Prentice method, considering extubation (dead or alive) within 28 days as competing event. Results: A total of 1047 patients were included (566 in the SARS-CoV-2 group and 481 in the influenza group). The incidence of putative IPA was lower in SARS-CoV-2 pneumonia group (14, 2.5%) than in influenza pneumonia group (29, 6%), adjusted cause-specific hazard ratio (cHR) 3.29 (95% CI 1.53–7.02, p = 0.0006). When putative IPA and Aspergillus respiratory tract colonization were combined, the incidence was also significantly lower in the SARS-CoV-2 group, as compared to influenza group (4.1% vs. 10.2%), adjusted cHR 3.21 (95% CI 1.88–5.46, p < 0.0001). In the whole study population, putative IPA was associated with significant increase in 28-day mortality rate, and length of ICU stay, compared with colonized patients, or those with no IPA or Aspergillus colonization. Conclusions: Overall, the incidence of putative IPA was low. Its incidence was significantly lower in patients with SARS-CoV-2 pneumonia than in those with influenza pneumonia. Clinical trial registration The study was registered at ClinicalTrials.gov, number NCT04359693.publishersversionpublishe
Mortality and pulmonary complications in emergency general surgery patients with COVID-19: A large international multicenter study
No full textObjectives: The outcomes of emergency general surgery (EGS) patients with concomitant COVID-19 infection remain unknown. With a multicenter study in 361 hospitals from 52 countries, we sought to study the mortality and pulmonary complications of COVID-19 patients undergoing EGS.
Methods: All patients 17 years or older and diagnosed preoperatively with COVID-19 between February and July 2020 were included. Emergency general surgery was defined as the urgent/emergent performance of appendectomy, cholecystectomy, or laparotomy. The main outcomes were 30-day mortality and 30-day pulmonary complications (a composite of acute respiratory distress syndrome, unexpected mechanical ventilation, or pneumonia). Planned subgroup analyses were performed based on presence of preoperative COVID-related respiratory findings (e.g., cough, dyspnea, need for oxygen therapy, chest radiology abnormality).
Results: A total of 1,045 patients were included, of which 40.1% were female and 50.0% were older than 50 years; 461 (44.1%), 145 (13.9%), and 439 (42.0%) underwent appendectomy, cholecystectomy, and laparotomy, respectively. The overall mortality rate was 15.1% (158 of 1,045 patients), and the overall pulmonary complication rate was 32.9% (344 of 1,045 patients); in the subgroup of laparotomy patients, the rates were 30.6% (134 of 438 patients) and 59.2% (260 of 439 patients), respectively. Subgroup analyses found mortality and pulmonary complication risk to be especially increased in patients with preoperative respiratory findings.
Conclusion: COVID-19 patients undergoing EGS have significantly high rates of mortality and pulmonary complications, but the risk is most pronounced in those with preoperative respiratory findings.Depto. de CirugíaFac. de MedicinaTRUEpu
The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males
No full textThe polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways
Fatigue and Mental Illness Symptoms in Long COVID: Protocol for a Prospective Cohort Multicenter Observational Study
No full textBackgroundThe aftermath of the COVID-19 pandemic continues to affect millions worldwide, resulting in persisting postvirus complaints and impacting peoples’ quality of life. Long COVID, characterized by lingering symptoms like fatigue and mental illness, can extend beyond a few months, necessitating further research to understand its implications.
ObjectiveThis study aims to quantify the degree of physical and psychological fatigue in patients following COVID-19 infection and examine its correlation with mental health disorders.
MethodsUsing a consecutive nonrandom sampling technique, we will conduct a prospective cohort multicenter observational study in 5 Portuguese hospitals. Symptomatic adult patients with previous COVID-19 attending follow-up consultations will be enrolled. We will include patients who had mild, moderate, and severe acute disease. We will assess clinical outcomes related to COVID-19, including the type of respiratory support such as high-flow nasal cannula, noninvasive ventilation, and invasive mechanical ventilation. The exclusion criteria will include previous severe psychiatric disorders confirmed by a psychiatrist; refusal or inability to respond to the questionnaire; concomitant neurological disorder; persistent fatigue symptoms during the 6 months before infection; and the need for invasive mechanical ventilation during COVID-19 infection due to a high prevalence of postintensive care syndrome. Our primary outcome is the prevalence of fatigue in patients with post–COVID-19 depression and/or anxiety, as measured by the Chalder Fatigue Scale (CFQ-11) and the Hospital Anxiety and Depression Scale (HADS). The secondary outcomes will include an assessment of health-related quality of life via the EQ-5D questionnaire and an exploration of the prevalence of symptoms of posttraumatic stress disorder (PTSD) using the 14-item Posttraumatic Stress Scale (PTSS-14). We will also examine the association between mental health symptoms and the severity of acute COVID-19. The post–COVID-19 data will be collected at least 6 months after the positive test and no longer than 9 months during the clinical appointment.
ResultsWe expect our multicenter study on patients post COVID-19 to reveal a significant link between mental illness symptoms and both physical and psychological fatigue. Patients with heightened depression and anxiety may report increased levels of fatigue. Additionally, we expect to find persistent PTSD symptoms in a subset of participants, indicating the enduring psychological impact of the virus.
ConclusionsThis study may underscore the need for integrated care addressing physical and mental health in patients post COVID-19. The observed connections emphasize the importance of considering mental well-being for long-term health outcomes. Despite study limitations, our findings contribute valuable insights for future treatment strategies and highlight the necessity for comprehensive mental health support in post–COVID-19 care. This research provides valuable insights into the mental health implications of COVID-19 and its impact on post–COVID-19 fatigue and the overall well-being of affected individuals.
Trial RegistrationClinicalTrials.gov NCT05323318; https://clinicaltrials.gov/study/NCT05323318
International Registered Report Identifier (IRRID)DERR1-10.2196/5182
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