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Aims Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to angiotensin converting enzyme 2 (ACE2) enabling entrance of the virus into cells and causing the infection termed coronavirus disease of 2019 (COVID-19). Here, we investigate associations between plasma ACE2 and outcome of COVID-19. Methods and results This analysis used data from a large longitudinal study of 306 COVID-19 positive patients and 78 COVID-19 negative patients (MGH Emergency Department COVID-19 Cohort). Comprehensive clinical data were collected on this cohort, including 28-day outcomes. The samples were run on the Olink® Explore 1536 platform which includes measurement of the ACE2 protein. High admission plasma ACE2 in COVID-19 patients was associated with increased maximal illness severity within 28 days with OR = 1.8, 95%-CI: 1.4–2.3 (P < 0.0001). Plasma ACE2 was significantly higher in COVID-19 patients with hypertension compared with patients without hypertension (P = 0.0045). Circulating ACE2 was also significantly higher in COVID-19 patients with pre-existing heart conditions and kidney disease compared with patients without these pre-existing conditions (P = 0.0363 and P = 0.0303, respectively). Conclusion This study suggests that measuring plasma ACE2 is potentially valuable in predicting COVID-19 outcomes. Further, ACE2 could be a link between COVID-19 illness severity and its established risk factors hypertension, pre-existing heart disease and pre-existing kidney disease.

Understanding the dynamics of the human proteome is crucial for developing biomarkers to be used as measurable indicators for disease severity and progression, patient stratification, and drug development. The Proximity Extension Assay (PEA) is a technology that translates protein information into actionable knowledge by linking protein-specific antibodies to DNA-encoded tags. In this report we demonstrate how we have combined the unique PEA technology with an innovative and automated sample preparation and high-throughput sequencing readout enabling parallel measurement of nearly 1500 proteins in 96 samples generating close to 150,000 data points per run. This advancement will have a major impact on the discovery of new biomarkers for disease prediction and prognosis and contribute to the development of the rapidly evolving fields of wellness monitoring and precision medicine., Graphical Abstract, Highlights • Novel tool for protein discovery and quantification. • PEA technology in combination with high-throughput sequencing read-out. • Parallel measurement of nearly 1500 proteins. • Innovative, miniaturized, and automated sample preparation protocol., In Brief Wik et al. presents a groundbreaking method based on the PEA technology in combination with NGS readout to measure nearly 1500 validated proteins in parallel. The protocol contains an innovative and automated sample preparation workflow generating close to 150,000 data points per run while consuming minimal amount of sample. Using dual DNA tags as readout enables high multiplex detection with exceptional specificity. This protocol meets all the requirements for a proteomic tool of the 21st century healthcare.

Background People with human immunodeficiency virus (PWH) demonstrate increased atherosclerotic cardiovascular disease (ASCVD). Statins are being studied to prevent ASCVD in human immunodeficiency virus (HIV), but little is known regarding the effects of statins on a broad range of inflammatory and cardiovascular proteins in this population. Methods We used a highly specific discovery proteomic approach (Protein Extension Assay), to determine statin effects on over 350 plasma proteins in relevant ASCVD pathways among HIV and non-HIV groups. Responses to pitavastatin calcium were assessed in 89 PWH in the INTREPID trial and 46 non-HIV participants with features of central adiposity and insulin resistance. History of cardiovascular disease was exclusionary for both studies. Results Among participants with HIV, PCOLCE (enzymatic cleavage of type I procollagen) significantly increased after pitavastatin therapy and PLA2G7 (systemic marker of arterial inflammation) decreased. Among participants without HIV, integrin subunit alpha M (integrin adhesive function) and defensin alpha-1 (neutrophil function) increased after pitavastatin therapy and PLA2G7 decreased. At baseline, comparing participants with and without HIV, differentially expressed proteins included proteins involved in platelet and endothelial function and immune activation. Conclusions Pitavastatin affected proteins important to platelet and endothelial function and immune activation, and effects differed to a degree within PWH and participants without HIV.

Recent advances in the treatment of multiple myeloma have led to significant improvements in overall survival. One contributor to this progress was the 2012 FDA approval of carfilzomib for the trea...

Objective HIV patients have increased atherosclerotic coronary vascular disease (ASCVD), thought to be mediated through inflammatory mechanisms. We hypothesized that among asymptomatic HIV-infected patients with subclinical coronary plaque, statin therapy would modulate unique inflammatory and cardiovascular proteins in relation to change in subclinical coronary plaque volume. We tested this hypothesis using a novel proteomics approach. Design Forty HIV-infected participants were randomized to atorvastatin (40 mg/day) versus placebo, and underwent computed tomography coronary angiography to quantify plaque volume at baseline and 1 year. Methods We used Olink Cardiovascular III and Cardiometabolic panels based on dual antibody epitope recognition with linked DNA amplification to compare change over time in 184 proteins in treatment versus placebo and in relation to change in coronary plaque volume. Results Six proteins (TFPI, CCL24, NT-Pro BNP, MBL2, LTBR, PCOLCE) changed significantly in the atorvastatin versus placebo group, many in innate immune and other novel inflammatory pathways. Twenty-six proteins changed significantly in relationship to total coronary plaque volume over 1 year. Notably, many of these proteins changed only weakly in relationship to change in low-density lipoprotein (LDL). Overlapping these two broad discovery approaches, proteins involved in myocardial fibrosis/collagen formation and monocyte chemoattraction changed with statin treatment, in relationship to plaque volume, but not LDL. Conclusion This proof-of-concept study employing a proteomic discovery platform offers insight into statin effects on novel immune pathways relevant to ASCVD progression in HIV. Novel biomarker discovery may enhance precision medicine strategies to estimate the efficacy of targeted therapies to reduce ASCVD progression and events in HIV.

Background People with HIV (PWH) demonstrate increased cardiovascular disease (CVD), due in part to increased immune activation, inflammation, and endothelial dysfunction. Methods In a randomized trial (INTREPID), 252 HIV-infected participants with dyslipidemia and no history of coronary artery disease were randomized (1:1) to pitavastatin 4 mg vs. pravastatin 40 mg for 52 weeks. Using a proteomic discovery approach, 92 proteins biomarkers were assessed using Proximity Extension Assay technology to determine the effects of statins on key atherosclerosis and CVD pathways among PWH. 225 participants had specimens available for biomarker analysis pre- and post-baseline. Findings The mean age was 49.5 ± 8.0 (mean ± SD), LDL-C 155 ± 25 mg/dl and CD4 count 620 ± 243 cell/mm3. Among all participants, three proteins significantly decreased: tissue factor pathway inhibitor [TFPI; t-statistic = -6.38, FDR p-value Interpretation Using a proteomics approach, we demonstrated that statins led to a significant reduction in the levels of TFPI, PON3, and LDLR and an increase in Gal-4 and IGFBP-2, key proteins involved in coagulation, redox signaling, oxidative stress, and glucose metabolism. Pitavastatin led to a greater reduction in TFPI than pravastatin. These data highlight potential novel mechanisms of statin effects among PWH. FUND: This work was supported by an investigator-initiated grant to S.K.G. from KOWA Pharmaceuticals America, Inc. and the National Institutes of Health [P30 DK040561; Nutrition Obesity Research Center at Harvard]. M.T. was support by National Institutes of Health [5KL2TR001100-05; Harvard Catalyst KL2 grant].

Current assays for somatic mutation analysis are based on extracts from tissue sections that often contain morphologically heterogeneous neoplastic regions with variable contents of genetically normal stromal and inflammatory cells, obscuring the results of the assays. We have developed an RNA-based in situ mutation assay that targets oncogenic mutations in a multiplex fashion that resolves the heterogeneity of the tissue sample. Activating oncogenic mutations are targets for a new generation of cancer drugs. For anti-EGFR therapy prediction, we demonstrate reliable in situ detection of KRAS mutations in codon 12 and 13 in colon and lung cancers in three different types of routinely processed tissue materials. High-throughput screening of KRAS mutation status was successfully performed on a tissue microarray. Moreover, we show how the patterns of expressed mutated and wild-type alleles can be studied in situ in tumors with complex combinations of mutated EGFR, KRAS and TP53. This in situ method holds great promise as a tool to investigate the role of somatic mutations during tumor progression and for prediction of response to targeted therapy.

INTRODUCTION Dendritic cells (DCs) and monocytes consist of multiple specialized subtypes that play a central role in pathogen sensing, phagocytosis, and antigen presentation. However, their identities and interrelationships are not fully understood, as these populations have historically been defined by a combination of morphology, physical properties, localization, functions, developmental origins, and expression of a restricted set of surface markers. RATIONALE To overcome this inherently biased strategy for cell identification, we performed single-cell RNA sequencing of ~2400 cells isolated from healthy blood donors and enriched for HLA-DR + lineage − cells. This single-cell profiling strategy and unbiased genomic classification, together with follow-up profiling and functional and phenotypic characterization of prospectively isolated subsets, led us to identify and validate six DC subtypes and four monocyte subtypes, and thus revise the taxonomy of these cells. RESULTS Our study reveals: 1) A new DC subset, representing 2 to 3% of the DC populations across all 10 donors tested, characterized by the expression of AXL , SIGLEC1 , and SIGLEC6 antigens, named AS DCs. The AS DC population further divides into two populations captured in the traditionally defined plasmacytoid DC (pDC) and CD1C + conventional DC (cDC) gates. This split is further reflected through AS DC gene expression signatures spanning a spectrum between cDC-like and pDC-like gene sets. Although AS DCs share properties with pDCs, they more potently activate T cells. This discovery led us to reclassify pDCs as the originally described “natural interferon-producing cells (IPCs)” with weaker T cell proliferation induction ability. 2) A new subdivision within the CD1C + DC subset: one defined by a major histocompatibility complex class II–like gene set and one by a CD14 + monocyte–like prominent gene set. These CD1C + DC subsets, which can be enriched by combining CD1C with CD32B, CD36, and CD163 antigens, can both potently induce T cell proliferation. 3) The existence of a circulating and dividing cDC progenitor giving rise to CD1C + and CLEC9A + DCs through in vitro differentiation assays. This blood precursor is defined by the expression of CD100 + CD34 int and observed at a frequency of ~0.02% of the LIN – HLA-DR + fraction. 4) Two additional monocyte populations: one expressing classical monocyte genes and cytotoxic genes, and the other with unknown functions. 5) Evidence for a relationship between blastic plasmacytoid DC neoplasia (BPDCN) cells and healthy DCs. CONCLUSION Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease. The discovery of AS DCs within the traditionally defined pDC population explains many of the cDC properties previously assigned to pDCs, highlighting the need to revisit the definition of pDCs. Furthermore, the discovery of blood cDC progenitors represents a new therapeutic target readily accessible in the bloodstream for manipulation, as well as a new source for better in vitro DC generation. Although the current results focus on DCs and monocytes, a similar strategy can be applied to build a comprehensive human immune cell atlas.

We have developed an approach for simultaneous detection of individual endogenous protein modifications and mRNA molecules in single cells in situ. For this purpose we combined two methods previously developed in our lab: in situ proximity ligation assay for the detection of individual protein interactions and -modifications and in situ detection of single mRNA molecules using padlock probes. As proof-of-principle, we demonstrated the utility of the method for simultaneous detection of phosphorylated PDGFRβ and DUSP6/MKP-3 mRNA molecules in individual human fibroblasts upon PDGF-BB stimulation. Further we applied drugs disrupting the PDGFRβ signaling pathway at various sites to show that this combined method can concurrently monitor the molecular effect of the drugs, i.e. inhibition of downstream signaling from the targeted node in the signaling pathway. Due to its ability to detect different types of molecules in single cells in situ the method presented here can contribute to a deeper understanding of cell-to-cell variations and can be applied to e.g. pinpoint effector sites of drugs in a signaling pathway.

Increasing knowledge about the heterogeneity of mRNA expression within cell populations highlights the need to study transcripts at the level of single cells. We present a method for detection and genotyping of individual transcripts based on padlock probes and in situ target-primed rolling-circle amplification. We detect a somatic point mutation, differentiate between members of a gene family and perform multiplex detection of transcripts in human and mouse cells and tissue.