Complement dysregulation is a prevalent and therapeutically amenable feature of long COVID

BACKGROUND

Long COVID encompasses a heterogeneous set of ongoing symptoms that affect many individuals after recovery from infection with SARS-CoV-2. The underlying biological mechanisms nonetheless remain obscure, precluding accurate diagnosis and effective intervention. Complement dysregulation is a hallmark of acute COVID-19 but has not been investigated as a potential determinant of long COVID.

METHODS

We quantified a series of complement proteins, including markers of activation and regulation, in plasma samples from healthy convalescent individuals with a confirmed history of infection with SARS-CoV-2 and age/ethnicity/sex/infection/vaccine-matched patients with long COVID.

FINDINGS

Markers of classical (C1s-C1INH complex), alternative (Ba, iC3b), and terminal pathway (C5a, TCC) activation were significantly elevated in patients with long COVID. These markers in combination had a receiver operating characteristic predictive power of 0.794. Other complement proteins and regulators were also quantitatively different between healthy convalescent individuals and patients with long COVID. Generalized linear modeling further revealed that a clinically tractable combination of just four of these markers, namely the activation fragments iC3b, TCC, Ba, and C5a, had a predictive power of 0.785.

CONCLUSIONS

These findings suggest that complement biomarkers could facilitate the diagnosis of long COVID and further suggest that currently available inhibitors of complement activation could be used to treat long COVID.

FUNDING

This work was funded by the National Institute for Health Research (COV-LT2-0041), the PolyBio Research Foundation, and the UK Dementia Research Institute.

DNA Methylation Profiles of Ovarian Clear Cell Carcinoma

BACKGROUND

Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC.

METHODS

We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways.

RESULTS

Two approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P < 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P < 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P < 10-4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P < 10-6).

CONCLUSIONS

DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways.

IMPACT

This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

Information theoretical analysis of aging as a risk factor for heart disease

We estimate the weight of various risk factors in heart disease, and the particular weight of age as a risk factor, individually and combined with other factors. To establish the weights we use the information theoretical measure of normalized mutual information that permits determining both individual and combined correlation of diagnostic parameters with the disease status. The present information theoretical methodology takes into account the non-linear correlations between the diagnostic parameters, as well as their non-linear changes with age. Thus it may be better suited to analyze complex biological aging systems than statistical measures that only estimate linear relations. We show that individual parameters, including age, often show little correlation with heart disease. Yet in combination, the correlation improves dramatically. For diagnostic parameters specific for heart disease the increase in the correlative capacity thanks to the combination of diagnostic parameters, is less pronounced than for the less specific parameters. Age shows the highest influence on the presence of disease among the non-specific parameters and the combination of age with other diagnostic parameters substantially improves the correlation with the disease status. Hence age is considered as a primary "metamarker" of aging-related heart disease, whose addition can improve diagnostic capabilities. In the future, this methodology may contribute to the development of a system of biomarkers for the assessment of biological/physiological age, its influence on disease status, and its modifications by therapeutic interventions.

Spectro-Fluor™ Technology for Reliable Detection of Proteins and Biomarkers of Disease: A Pioneered Research Study

Quantitative and qualitative characterization of fluorinated molecules represents an important task. Fluorine-based medicinal chemistry is a fast-growing research area due to the positive impact of fluorine in drug discovery, and clinical and molecular imaging (e.g., magnetic resonance imaging, positron emission tomography). Common detection methods include fluorinated-based labelling using radioactive isotopes or fluorescent dyes. Nevertheless, these molecular imaging methods can be harmful for health due to the potential instability of fluorochromes and cytoxicity of radioisotopes. Therefore, these methods often require expensive precautionary measures. In this context, we have developed, validated and patented carbon-fluorine spectroscopy (CFS™), recently renamed Spectro-Fluor™ technology, which among a non-competitive family of in-house made devices called PLIRFA™ (Pulsed Laser Isochronic Raman and Fluorescence Apparatus™), allows reliable detection of Carbon-Fluorine (C-F) bonds. C-F bonds are known to be stable and safe labels once incorporated to any type of molecules, cells, compounds or (nano-) materials. In this pioneered research study, we used Spectro-Fluor™ to assess biomarkers. As a proof-of-principle experiment, we have established a three-step protocol intended to rapid protein detection, which simply consisted of: (i) incorporating a sufficient concentration of an aromatic amino-acid (fluorinated versus non-fluorinated) into cultured cells; (ii) simultaneously isolating the fluorinated protein of interest and the non-fluorinated form of the protein (control) by immune-precipitation; (iii) comparatively analyzing the respective spectrum obtained for the two protein forms by Spectro-Fluor™. Thereby, we were able to differentiate, from colon cancer cells HCT-116, the fluorinated and non-fluorinated forms of p21, a key transcriptional factor and downstream target of p53, the so-called “guardian of the genome”. Taken together, our data again demonstrates the beneficial alternative use of Spectro-Fluor™, which once combined with an innovative methodology permits one to quickly, reliably, safely and cost-effectively detect physiological or pathological proteins in cells.