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.</p

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.</p

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

Variation within and between digital pathology and light microscopy for the diagnosis of histopathology slides:blinded crossover comparison study

BackgroundDigital pathology refers to the conversion of histopathology slides to digital image files for examination on computer workstations as opposed to conventional microscopes. Prior to adoption, it is important to demonstrate pathologists provide equivalent reports when using digital pathology in comparison to bright-field and immunofluorescent light microscopy, the current standard of care.ObjectiveA multicentre comparison of digital pathology with light microscopy for reporting of histopathology slides, measuring variation within and between pathologists on both modalities.DesignA blinded crossover 2000-case study estimating clinical management concordance (identical diagnoses plus differences not affecting patient management). Each sample was assessed twice by four pathologists (once using light microscopy, once using digital pathology, the order randomly assigned and a 6-week gap between viewings). Random-effects logistic regression models, including crossed random-effects terms for case and pathologist, estimated percentage clinical management concordance. Findings were interpreted with reference to 98.3% concordance (Azam AS, Miligy IM, Kimani PKU, Maqbool H, Hewitt K, Rajpoot NM, Snead DRJ. Diagnostic concordance and discordance in digital pathology: a systematic review and meta-analysis. J Clin Pathol 2021;74:448–55. https://doi.org/10.1136/jclinpath-2020-206764).SettingSixteen consultant pathologists, four for each specialty, from six National Health Service laboratories. Experience ranged from 3 to 35 years. Some were early adopters of digital pathology, but the majority were new to digital pathology.InterventionsEight viewings per sample (four pathologists with light microscopy and with digital pathology), culminating in a consensus ground truth, enabling measurement of agreement within and between readers. Samples enrolled reflected routine practice, included cancer screening biopsies, and were enriched for areas of difficulty [e.g. dysplasia (7, 10, 11)]. State-of-the-art digital pathology equipment designed for diagnosis, and holding either Conformité Européene or Food and Drug Administration approval, was used.Main outcomeIntra-pathologist variation between reports issued on digital pathology and light microscopy, inter-pathologist variation against ground-truth diagnosis using light microscopy and digital pathology.Secondary outcomesPathologist-recorded reporting times, along with their confidence in diagnosis, analysis of eye-tracking evaluating examination techniques, and a qualitative study examining attitudes of pathologists and laboratory staff to digital pathology adoption.ResultsTwo thousand and twenty-four cases (608 breast, 607 gastrointestinal, 609 skin, 200 renal) were recruited, with breast and gastrointestinal including screening samples [207 (34%) breast, 250 (41%) gastrointestinal]. Overall, in light microscopy versus digital pathology comparisons, clinical management concordance levels were 99.95% (95% confidence interval 99.91 to 99.97). Similar results were observed within specialties [breast: 99.40% (95% confidence interval 99.06 to 99.62); gastrointestinal 99.96% (95% confidence interval 99.89 to 99.99); skin 99.99% (95% confidence interval 99.92 to 100.0); renal 99.99% (95% confidence interval 99.57 to 100.0)], and within screening cases [98.96% (95% confidence interval 98.42 to 99.32), breast 96.27% (94.63 to 97.43), gastrointestinal 99.93% (95% confidence interval 99.68 to 99.98)]. Reporting time between digital pathology and light microscopy was similar, but pathologists became faster on digital pathology with familiarity. Pathologists recorded high levels of confidence in their diagnosis with light microscopy, significantly higher than digital pathology.LimitationsCytology cases and specialty groups outside those tested were not examined. The study used two digital pathology scanning systems. Other systems available on the market were not tested.ConclusionsClinical management concordance levels between the two modalities exceed the reference 98.3% in breast, gastrointestinal, skin and renal specialties, and pooled breast and large bowel cancer screening cases. Subgroup analysis of clinically significant differences revealed a range of differences including areas where interobserver variability is known to be high, which were distributed between reads performed with both platforms and without apparent trends to either.Future workThe use of digital pathology for cytology samples remains an area for further research.Study registration:This study is registered as ISRCTN14513591.FundingThis award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/84/07) and is published in full in Health Technology Assessment; Vol. 29, No. 30. See the NIHR Funding and Awards website for further award information

Regulatory cell therapy in kidney transplantation (The ONE Study): a harmonised design and analysis of seven non-randomised, single-arm, phase 1/2A trials.

BackgroundUse of cell-based medicinal products (CBMPs) represents a state-of-the-art approach for reducing general immunosuppression in organ transplantation. We tested multiple regulatory CBMPs in kidney transplant trials to establish the safety of regulatory CBMPs when combined with reduced immunosuppressive treatment.MethodsThe ONE Study consisted of seven investigator-led, single-arm trials done internationally at eight hospitals in France, Germany, Italy, the UK, and the USA (60 week follow-up). Included patients were living-donor kidney transplant recipients aged 18 years and older. The reference group trial (RGT) was a standard-of-care group given basiliximab, tapered steroids, mycophenolate mofetil, and tacrolimus. Six non-randomised phase 1/2A cell therapy group (CTG) trials were pooled and analysed, in which patients received one of six CBMPs containing regulatory T cells, dendritic cells, or macrophages; patient selection and immunosuppression mirrored the RGT, except basiliximab induction was substituted with CBMPs and mycophenolate mofetil tapering was allowed. None of the trials were randomised and none of the individuals involved were masked. The primary endpoint was biopsy-confirmed acute rejection (BCAR) within 60 weeks after transplantation; adverse event coding was centralised. The RTG and CTG trials are registered with ClinicalTrials.gov, NCT01656135, NCT02252055, NCT02085629, NCT02244801, NCT02371434, NCT02129881, and NCT02091232.FindingsThe seven trials took place between Dec 11, 2012, and Nov 14, 2018. Of 782 patients assessed for eligibility, 130 (17%) patients were enrolled and 104 were treated and included in the analysis. The 66 patients who were treated in the RGT were 73% male and had a median age of 47 years. The 38 patients who were treated across six CTG trials were 71% male and had a median age of 45 years. Standard-of-care immunosuppression in the recipients in the RGT resulted in a 12% BCAR rate (expected range 3·2-18·0). The overall BCAR rate for the six parallel CTG trials was 16%. 15 (40%) patients given CBMPs were successfully weaned from mycophenolate mofetil and maintained on tacrolimus monotherapy. Combined adverse event data and BCAR episodes from all six CTG trials revealed no safety concerns when compared with the RGT. Fewer episodes of infections were registered in CTG trials versus the RGT.InterpretationRegulatory cell therapy is achievable and safe in living-donor kidney transplant recipients, and is associated with fewer infectious complications, but similar rejection rates in the first year. Therefore, immune cell therapy is a potentially useful therapeutic approach in recipients of kidney transplant to minimise the burden of general immunosuppression.FundingThe 7th EU Framework Programme

Acupuncture and counselling for depression in primary care : a randomised controlled trial

Background: Depression is a significant cause of morbidity. Many patients have communicated an interest in nonpharmacological therapies to their general practitioners. Systematic reviews of acupuncture and counselling for depression in primary care have identified limited evidence. The aim of this study was to evaluate acupuncture versus usual care and counselling versus usual care for patients who continue to experience depression in primary care. Methods and Findings: In a randomised controlled trial, 755 patients with depression (Beck Depression Inventory BDI-II score $20) were recruited from 27 primary care practices in the North of England. Patients were randomised to one of three arms using a ratio of 2:2:1 to acupuncture (302), counselling (302), and usual care alone (151). The primary outcome was the difference in mean Patient Health Questionnaire (PHQ-9) scores at 3 months with secondary analyses over 12 months follow-up. Analysis was by intention-to-treat. PHQ-9 data were available for 614 patients at 3 months and 572 patients at 12 months. Patients attended a mean of ten sessions for acupuncture and nine sessions for counselling. Compared to usual care, there was a statistically significant reduction in mean PHQ-9 depression scores at 3 months for acupuncture (22.46, 95% CI 23.72 to 21.21) and counselling (21.73, 95% CI 23.00 to 20.45), and over 12 months for acupuncture (21.55, 95% CI 22.41 to 20.70) and counselling (21.50, 95% CI 22.43 to 20.58). Differences between acupuncture and counselling were not significant. In terms of limitations, the trial was not designed to separate out specific from non-specific effects. No serious treatment-related adverse events were reported. Conclusions: In this randomised controlled trial of acupuncture and counselling for patients presenting with depression, after having consulted their general practitioner in primary care, both interventions were associated with significantly reduced depression at 3 months when compared to usual care alone