Diagnostic potential of the plasma lipidome in infectious disease: application to acute SARS-CoV-2 infection

Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management

An NMR-based model to investigate the metabolic phenoreversion of COVID-19 patients throughout a longitudinal study.

After SARS-CoV-2 infection, the molecular phenoreversion of the immunological response and its associated metabolic dysregulation are required for a full recovery of the patient. This process is patient-dependent due to the manifold possibilities induced by virus severity, its phylogenic evolution and the vaccination status of the population. We have here investigated the natural history of COVID-19 disease at the molecular level, characterizing the metabolic and immunological phenoreversion over time in large cohorts of hospitalized severe patients (n = 886) and non-hospitalized recovered patients that self-reported having passed the disease (n = 513). Non-hospitalized recovered patients do not show any metabolic fingerprint associated with the disease or immune alterations. Acute patients are characterized by the metabolic and lipidomic dysregulation that accompanies the exacerbated immunological response, resulting in a slow recovery time with a maximum probability of around 62 days. As a manifestation of the heterogeneity in the metabolic phenoreversion, age and severity become factors that modulate their normalization time which, in turn, correlates with changes in the atherogenesis-associated chemokine MCP-1. Our results are consistent with a model where the slow metabolic normalization in acute patients results in enhanced atherosclerotic risk, in line with the recent observation of an elevated number of cardiovascular episodes found in post-COVID-19 cohorts

Mitochondrial bioenergetics boost macrophage activation, promoting liver regeneration in metabolically compromised animals

Background and aims: Hepatic ischemia-reperfusion injury (IRI) is the leading cause of early posttransplantation organ failure as mitochondrial respiration and ATP production are affected. A shortage of donors has extended liver donor criteria, including aged or steatotic livers, which are more susceptible to IRI. Given the lack of an effective treatment and the extensive transplantation waitlist, we aimed at characterizing the effects of an accelerated mitochondrial activity by silencing methylation-controlled J protein (MCJ) in three preclinical models of IRI and liver regeneration, focusing on metabolically compromised animal models. Approach and results: Wild-type (WT), MCJ knockout (KO), and Mcj silenced WT mice were subjected to 70% partial hepatectomy (Phx), prolonged IRI, and 70% Phx with IRI. Old and young mice with metabolic syndrome were also subjected to these procedures. Expression of MCJ, an endogenous negative regulator of mitochondrial respiration, increases in preclinical models of Phx with or without vascular occlusion and in donor livers. Mice lacking MCJ initiate liver regeneration 12 h faster than WT and show reduced ischemic injury and increased survival. MCJ knockdown enables a mitochondrial adaptation that restores the bioenergetic supply for enhanced regeneration and prevents cell death after IRI. Mechanistically, increased ATP secretion facilitates the early activation of Kupffer cells and production of TNF, IL-6, and heparin-binding EGF, accelerating the priming phase and the progression through G1 /S transition during liver regeneration. Therapeutic silencing of MCJ in 15-month-old mice and in mice fed a high-fat/high-fructose diet for 12 weeks improves mitochondrial respiration, reduces steatosis, and overcomes regenerative limitations. Conclusions: Boosting mitochondrial activity by silencing MCJ could pave the way for a protective approach after major liver resection or IRI, especially in metabolically compromised, IRI-susceptible organs.Funding information: Supported by grants from Ministerio de Ciencia, Innovación y Universidades MICINN (PID2020-117116RB-100, RTI2018-096759-A-100, RTI2018-095114-B-I00, PID2019-108977RB-100 and RTI2018-095700-B100, integrado en el Plan Estatal de Investigación Científica y Técnica y Innovación, cofinanciado con Fondos FEDER, to M.L.M.-C., T.C.D., C.P., P.M.-S., and N.G.A.A., respectively), Subprograma Retos Colaboración RTC2019-007125-1; Fundación Científica de la Asociación Española Contra el Cáncer (AECC Scientific Foundation) Rare Tumor Calls 2017 (to M.L.M.-C.); Asociación Española contra el Cáncer (to T.C.D. and M.S.-M); La Caixa Foundation Program (HR17-00601, to M.L.M.-C.), Proyectos Investigación en Salud DTS20/00138 (to M.L.M.-C.); Departamento de Industria del Gobierno Vasco (to M.L.M.-C.); Departamento de Educación del Gobierno Vasco (to N.G.-U. and J.S.); Acción Estratégica Ciber Emergentes 2018 (Ciberehd-ISCIII) and Gilead Sciences International Research Scholars Program in Liver Disease (to M.V.-R.); Ciberehd_ISCIII_MINECO is funded by the Instituto de Salud Carlos IIIAcknowledgments: We thank MINECO for the Severo Ochoa Excellence Accreditation to CIC bioGUNE (SEV-2016-0644). We acknowledge Begoña Rodríguez Iruretagoyena for the technical support provided

Diagnostic potential of the plasma lipidome in infectious disease: application to acute SARS-CoV-2 infection

Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management

Genomic and functional regulation of TRIB1 contributes to prostate cancer pathogenesis

Prostate cancer is the most frequent malignancy in European men and the second worldwide. One of the major oncogenic events in this disease includes amplification of the transcription factor cMYC. Amplification of this oncogene in chromosome 8q24 occurs concomitantly with the copy number increase in a subset of neighboring genes and regulatory elements, but their contribution to disease pathogenesis is poorly understood. Here we show that TRIB1 is among the most robustly upregulated coding genes within the 8q24 amplicon in prostate cancer. Moreover, we demonstrate that TRIB1 amplification and overexpression are frequent in this tumor type. Importantly, we find that, parallel to its amplification, TRIB1 transcription is controlled by cMYC. Mouse modeling and functional analysis revealed that aberrant TRIB1 expression is causal to prostate cancer pathogenesis. In sum, we provide unprecedented evidence for the regulation and function of TRIB1 in prostate cancer

Integrative modeling of plasma metabolic and lipoprotein biomarkers of SARS-CoV-2 infection in Spanish and Australian COVID-19 patient cohorts

Quantitative plasma lipoprotein and metabolite profiles were measured on an autonomous community of the Basque Country (Spain) cohort consisting of hospitalized COVID-19 patients (n = 72) and a matched control group (n = 75) and a Western Australian (WA) cohort consisting of (n = 17) SARS-CoV-2 positives and (n = 20) healthy controls using 600 MHz 1H nuclear magnetic resonance (NMR) spectroscopy. Spanish samples were measured in two laboratories using one-dimensional (1D) solvent-suppressed and T2-filtered methods with in vitro diagnostic quantification of lipoproteins and metabolites. SARS-CoV-2 positive patients and healthy controls from both populations were modeled and cross-projected to estimate the biological similarities and validate biomarkers. Using the top 15 most discriminatory variables enabled construction of a cross-predictive model with 100% sensitivity and specificity (within populations) and 100% sensitivity and 82% specificity (between populations). Minor differences were observed between the control metabolic variables in the two cohorts, but the lipoproteins were virtually indistinguishable. We observed highly significant infection-related reductions in high-density lipoprotein (HDL) subfraction 4 phospholipids, apolipoproteins A1 and A2,that have previously been associated with negative regulation of blood coagulation and fibrinolysis. The Spanish and Australian diagnostic SARS-CoV-2 biomarkers were mathematically and biologically equivalent, demonstrating that NMR-based technologies are suitable for the study of the comparative pathology of COVID-19 via plasma phenotyping