Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT).

Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell or pathomics data to find sample-level trajectories or clusters associated with diseases. This remains challenging as single-cell/pathomics data are multi-scale, i.e., a sample is represented by clusters of cells/structures, and samples cannot be easily compared with each other. Here we propose PatIent Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two individual single-cell samples. This allows us to perform unsupervised analysis at the sample level and uncover trajectories or cellular clusters associated with disease progression. We evaluate PILOT and competing approaches in single-cell genomics or pathomics studies involving various human diseases with up to 600 samples/patients and millions of cells or tissue structures. Our results demonstrate that PILOT detects disease-associated samples from large and complex single-cell or pathomics data. Moreover, PILOT provides a statistical approach to find changes in cell populations, gene expression, and tissue structures related to the trajectories or clusters supporting interpretation of predictions.

Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury.

Severe lung damage resulting from COVID-19 involves complex interactions between diverse populations of immune and stromal cells. In this study, we used a spatial transcriptomics approach to delineate the cells, pathways, and genes present across the spectrum of histopathological damage in COVID-19-affected lung tissue. We applied correlation network-based approaches to deconvolve gene expression data from 46 areas of interest covering more than 62,000 cells within well-preserved lung samples from 3 patients. Despite substantial interpatient heterogeneity, we discovered evidence for a common immune-cell signaling circuit in areas of severe tissue that involves crosstalk between cytotoxic lymphocytes and pro-inflammatory macrophages. Expression of IFNG by cytotoxic lymphocytes was associated with induction of chemokines, including CXCL9, CXCL10, and CXCL11, which are known to promote the recruitment of CXCR3+ immune cells. The TNF superfamily members BAFF (TNFSF13B) and TRAIL (TNFSF10) were consistently upregulated in the areas with severe tissue damage. We used published spatial and single-cell SARS-CoV-2 data sets to validate our findings in the lung tissue from additional cohorts of patients with COVID-19. The resulting model of severe COVID-19 immune-mediated tissue pathology may inform future therapeutic strategies.

Use of post-mortem computed tomography during the COVID-19 pandemic.

Post mortem computed tomography (PMCT) is widely used in England and Wales to supplement or replace traditional invasive Coroner's autopsy. Using PMCT and coronary angiography, the cause of death can be determined without invasive examination in approximately 70% of cases, assuming a typical Coroner's autopsy case mix. Coroner's autopsy services continued during the COVID-19 pandemic and have identified deaths resulting from COVID-19 undiagnosed in life. In some areas of England, PMCT was used to replace traditional autopsy due to concerns over infection risk to mortuary staff associated with invasive autopsy. Health and safety concerns also resulted in changes to post mortem scanning protocols. PMCT has been used to identify potential COVID-19 deaths and assist in the selection of cases for viral studies. There is typically bilateral ground-glass opacities and consolidation within the lungs on CT; although these changes are not specific for COVID-19, the diagnosis can be confirmed with post mortem nose and throat swabs.

Clinical information has low sensitivity for postmortem diagnosis of heart valve disease.

BACKGROUND: Accuracy of routinely collected information concerning cause of death is essential for public health and health systems planning. Since clinical examination has relatively low sensitivity for detection of valvular heart disease (VHD), mortality data based on clinical information alone might routinely underestimate the number of deaths due to VHD. METHODS: We compared autopsy findings against premortem clinical information for 8198 consecutive adult postmortems (mean age 69.1 years, 61.3% men), performed in a single UK tertiary referral centre with on-site cardiac surgical facilities over a 10-year period (2004-2013) during which 21% of the adult population underwent postmortem examination. RESULTS: Following postmortem, VHD was the principal cause of death in 165 individuals (2.0%), a principal or contributory cause ('any cause') of death in 326 (4.0%) and an incidental (ie, non-causal) finding in a further 346 (4.2%). Clinical documentation of VHD before death was highly specific but relatively insensitive for postmortem identification of VHD as the principal (specificity 96.8%; 95% CI 96.4% to 97.2%; sensitivity 69.7%, 95% CI 62.1% to 76.6%) or any (specificity 98.1%; 95% CI 97.8% to 98.4%; sensitivity 68.4%, 95% CI 63.1% to 73.4%) cause of death. VHD (principally aortic stenosis, endocarditis and rheumatic heart disease) was newly noted at postmortem and listed as a cause of death in 142 individuals (1.7%). CONCLUSIONS: Clinical information recorded premortem is highly specific but relatively insensitive for the cause of death established at autopsy. Population-based mortality statistics that depend on premortem clinical information are likely to routinely underestimate the mortality burden of VHD.

Risk factors for delayed graft function defined as need for dialysis or failure of creatinine to fall by 10% in the first 24 hours after transplant.

OBJECTIVES: Delayed graft function after deceased-donor transplant remains a significant clinical problem. The conventional definition of delayed graft function is the requirement of dialysis within the first week after transplant, but this criterion has many problems that have led to many controversies including those of incidence and significance. Therefore, we sought to identify the possible risk factors of delayed graft function and to investigate their effect on short-term graft survival, according to a composite criterion. MATERIALS AND METHODS: We reviewed the records of 94 renal transplants obtained from heart-beating deceased donors done at our center during a 2-year period. Variables related to the donor, recipient, and graft were retrospectively collected. Follow-up was 12 months. Delayed graft function was defined as the need for dialysis or the failure of the creatinine level to fall by 10% during the first 24 hours after transplant. To confirm suspected rejection, protocol biopsies were done, irrespective of graft function, on the seventh and 28th days after transplant, or when indicated to confirm suspected rejection. RESULTS: The overall incidence of delayed graft function was 31.9%. Multivariate analysis showed donor age as a significant independent predictor of delayed graft function (OR=1.05, P = .03, 95% CI: 1.01-1.09), whereas donor hypotension was the only independent risk factor associated with a worse 1-year graft survival rate (OR=4.6, P = .021, 95% CI: 1.3-16.5). No association could be established between delayed graft function, acute rejection, and graft survival. CONCLUSIONS: Advanced donor age is a predictor of delayed graft function defined as the need for dialysis or the failure of creatinine to fall by 10% during the first 24 hours after transplant. Preventing hemodynamic instability should be an important aspect of donor care.