Blood immunophenotyping identifies distinct kidney histopathology and outcomes in patients with lupus nephritis

Lupus nephritis (LN) is a frequent manifestation of systemic lupus erythematosus, and fewer than half of patients achieve complete renal response with standard immunosuppressants. Identifying non-invasive, blood-based pathologic immune alterations associated with renal injury could aid therapeutic decisions. Here, we used mass cytometry immunophenotyping of peripheral blood mononuclear cells in 145 patients with biopsy-proven LN and 40 healthy controls to evaluate the heterogeneity of immune activation in patients with LN and to identify correlates of renal parameters and treatment response. Unbiased analysis identified 3 immunologically distinct groups of patients with LN that were associated with different patterns of histopathology, renal cell infiltrates, urine proteomic profiles, and treatment response at one year. Patients with enriched circulating granzyme B+ T cells at baseline showed more severe disease and increased numbers of activated CD8 T cells in the kidney, yet they had the highest likelihood of treatment response. A second group characterized primarily by a high type I interferon signature had a lower likelihood of response to therapy, while a third group appeared immunologically inactive by immunophenotyping at enrollment but with chronic renal injuries. Main immune profiles could be distilled down to 5 simple cytometric parameters that recapitulate several of the associations, highlighting the potential for blood immune profiling to translate to clinically useful non-invasive metrics to assess immune-mediated disease in LN.

An atlas of healthy and injured cell states and niches in the human kidney

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions

Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNA-seq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune-cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell-type-specific intracellular death signatures, cellular angiotensin-converting enzyme 2 (ACE2) expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease.

Plasma proteomics reveals tissue-specific cell death and mediators of cell-cell interactions in severe COVID-19 patients

COVID-19 has caused over 1 million deaths globally, yet the cellular mechanisms underlying severe disease remain poorly understood. By analyzing several thousand plasma proteins in 306 COVID-19 patients and 78 symptomatic controls over serial timepoints using two complementary approaches, we uncover COVID-19 host immune and non-immune proteins not previously linked to this disease. Integration of plasma proteomics with nine published scRNAseq datasets shows that SARS-CoV-2 infection upregulates monocyte/macrophage, plasmablast, and T cell effector proteins. By comparing patients who died to severely ill patients who survived, we identify dynamic immunomodulatory and tissue-associated proteins associated with survival, providing insights into which host responses are beneficial and which are detrimental to survival. We identify intracellular death signatures from specific tissues and cell types, and by associating these with angiotensin converting enzyme 2 (ACE2) expression, we map tissue damage associated with severe disease and propose which damage results from direct viral infection rather than from indirect effects of illness. We find that disease severity in lung tissue is driven by myeloid cell phenotypes and cell-cell interactions with lung epithelial cells and T cells. Based on these results, we propose a model of immune and epithelial cell interactions that drive cell-type specific and tissue-specific damage in severe COVID-19.

The immune cell landscape in kidneys of patients with lupus nephritis

Lupus nephritis is a potentially fatal autoimmune disease for which the current treatment is ineffective and often toxic. To develop mechanistic hypotheses of disease, we analyzed kidney samples from patients with lupus nephritis and from healthy control subjects using single-cell RNA sequencing. Our analysis revealed 21 subsets of leukocytes active in disease, including multiple populations of myeloid cells, T cells, natural killer cells and B cells that demonstrated both pro-inflammatory responses and inflammation-resolving responses. We found evidence of local activation of B cells correlated with an age-associated B-cell signature and evidence of progressive stages of monocyte differentiation within the kidney. A clear interferon response was observed in most cells. Two chemokine receptors, CXCR4 and CX3CR1, were broadly expressed, implying a potentially central role in cell trafficking. Gene expression of immune cells in urine and kidney was highly correlated, which would suggest that urine might serve as a surrogate for kidney biopsies.

Clinical characteristics and renal prognosis associated with interstitial fibrosis and tubular atrophy (IFTA) and vascular injury in lupus nephritis biopsies

BACKGROUND

Interstitial fibrosis and tubular atrophy (IFTA) and vascular injury are frequent histologic features of lupus nephritis renal biopsies, but their clinical correlates and prognostic value are not well understood. This cohort study investigated demographic, clinical and laboratory characteristics, and outcomes, associated with IFTA and vascular injury in lupus nephritis.

METHODS

Reports of all renal biopsies performed at an academic medical center (1990-2017) with WHO/ISN/RPS Class II-V lupus nephritis were reviewed. Demographics, clinical variables and labs at biopsy, treatment, and date of death were collected. Additional data from the U.S. Renal Data System (USRDS) provided dates of ESRD and death after ESRD. Multivariable regression analyses identified demographic and clinical factors associated with each histologic finding. Cumulative incidence functions and multivariable Cox proportional hazard models estimated the risk of progression to ESRD and death.

RESULTS

Within 202 initial biopsies, IFTA was associated with the patient's SLICC/ACR damage index (without renal domain) and serum creatinine, and vascular injury was associated with serum creatinine in multivariable models. In Cox regression models adjusting for age, sex, race, serum creatinine, calendar year, and biopsy class, moderate/severe IFTA was associated with elevated ESRD (HR_SD 5.18, 95% CI 2.53, 10.59) and death (HR 4.19, 95%CI 1.27, 13.81). After adjustment for age, sex and race, moderate/severe vascular injury was associated with ESRD (HR_SD 2.13, 95% CI 1.21, 3.75) and but this relationship was not significant after adjustment for serum creatinine and calendar year.

CONCLUSIONS

IFTA is a strong predictor of ESRD and death, even in proliferative nephritis, and a risk factor for poor outcomes independent of class. Vascular injury is a strong predictor of prognosis, but not independent of serum creatinine and class. The prognostic value of these lesions calls for consideration when determining treatment for lupus nephritis.

Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

Treatment of cancer has been revolutionized by immune checkpoint blockade therapies. Despite the high rate of response in advanced melanoma, the majority of patients succumb to disease. To identify factors associated with success or failure of checkpoint therapy, we profiled transcriptomes of 16,291 individual immune cells from 48 tumor samples of melanoma patients treated with checkpoint inhibitors. Two distinct states of CD8+ T cells were defined by clustering and associated with patient tumor regression or progression. A single transcription factor, TCF7, was visualized within CD8+ T cells in fixed tumor samples and predicted positive clinical outcome in an independent cohort of checkpoint-treated patients. We delineated the epigenetic landscape and clonality of these T cell states and demonstrated enhanced antitumor immunity by targeting novel combinations of factors in exhausted cells. Our study of immune cell transcriptomes from tumors demonstrates a strategy for identifying predictors, mechanisms, and targets for enhancing checkpoint immunotherapy.

STIM1 clusters and activates CRAC channels via direct binding of a cytosolic domain to Orai1

Store-operated Ca(2+) channels activated by the depletion of Ca(2+) from the endoplasmic reticulum (ER) are a major Ca(2+) entry pathway in nonexcitable cells and are essential for T cell activation and adaptive immunity. After store depletion, the ER Ca(2+) sensor STIM1 and the CRAC channel protein Orai1 redistribute to ER-plasma membrane (PM) junctions, but the fundamental issue of how STIM1 activates the CRAC channel at these sites is unresolved. Here, we identify a minimal, highly conserved 107-aa CRAC activation domain (CAD) of STIM1 that binds directly to the N and C termini of Orai1 to open the CRAC channel. Purified CAD forms a tetramer that clusters CRAC channels, but analysis of STIM1 mutants reveals that channel clustering is not sufficient for channel activation. These studies establish a molecular mechanism for store-operated Ca(2+) entry in which the direct binding of STIM1 to Orai1 drives the accumulation and the activation of CRAC channels at ER-PM junctions.

Cryptosporidium parvum mixed genotypes detected by PCR-restriction fragment length polymorphism analysis

Combinations of 10 Cryptosporidium parvum oocysts, with various ratios of genotype I to genotype II, were isolated and subjected to PCR-restriction fragment length polymorphism analysis. Amplification of both genotypes in these samples ranged from 31 to 74% and yielded no information about the genotype proportions. In addition, since both genotypes were not always detected, amplification of a single genotype is not conclusive evidence that the sample contains only a single genotype.

Species-specific, nested PCR-restriction fragment length polymorphism detection of single Cryptosporidium parvum oocysts

Concurrent with recent advances seen with Cryptosporidium parvum detection in both treated and untreated water is the need to properly evaluate these advances. A micromanipulation method by which known numbers of C. parvum oocysts, even a single oocyst, can be delivered to a test matrix for detection sensitivity is presented. Using newly developed nested PCR-restriction fragment length polymorphism primers, PCR sensitivity was evaluated with 1, 2, 3, 4, 5, 7, or 10 oocysts. PCR detection rates (50 samples for each number of oocysts) ranged from 38% for single oocysts to 92% for 5 oocysts, while 10 oocysts were needed to achieve 100% detection. The nested PCR conditions amplified products from C. parvum, Cryptosporidium baileyi, and Cryptosporidium serpentis but no other Cryptosporidium sp. or protozoan tested. Restriction enzyme digestion with VspI distinguished between C. parvum genotypes 1 and 2. Restriction enzyme digestion with DraII distinguished C. parvum from C. baileyi and C. serpentis. Use of known numbers of whole oocysts encompasses the difficulty of liberating DNA from the oocyst and eliminates the standard deviation inherent within a dilution series. To our knowledge this is the first report in which singly isolated C. parvum oocysts were used to evaluate PCR sensitivity. This achievement illustrates that PCR amplification of a single oocyst is feasible, yet sensitivity remains an issue, thereby illustrating the difficulty of dealing with low oocyst numbers when working with environmental water samples.