Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors’ samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.     

The search for novel diagnostic and prognostic biomarkers in cholangiocarcinoma

The poor prognosis of cholangiocarcinoma (CCA) is in part due to late diagnosis, which is currently achieved by a combination of clinical, radiological and histological approaches. Available biomarkers determined in serum and biopsy samples to assist in CCA diagnosis are not sufficiently sensitive and specific. Therefore, the identification of new biomarkers, preferably those obtained by minimally invasive methods, such as liquid biopsy, is important. The development of innovative technologies has permitted to identify a significant number of genetic, epigenetic, proteomic and metabolomic CCA features with potential clinical usefulness in early diagnosis, prognosis or prediction of treatment response. Potential new candidates must be rigorously evaluated prior to entering routine clinical application. Unfortunately, to date, no such biomarker has achieved validation for these purposes. This review is an up-to-date of currently used biomarkers and the candidates with promising characteristics that could be included in the clinical practice in the next future. This article is part of a Special Issue entitled: Cholangiocytes in Health and Disease edited by Jesus Banales, Marco Marzioni, Nicholas LaRusso and Peter Jansen.     

MicroRNAs and extracellular vesicles in cholangiopathies

Cholangiopathies encompass a heterogeneous group of disorders affecting biliary epithelial cells (i.e. cholangiocytes). Early diagnosis, prognosis and treatment still remain clinically challenging for most of these diseases and are critical for adequate patient care. In the past decade, extensive research has emphasized microRNAs (miRs) as potential non-invasive biomarkers and tools to accurately identify, predict and treat cholangiopathies. MiRs can be released extracellularly conjugated with lipoproteins or encapsulated in extracellular vesicles (EVs). Research on EVs is also gaining attention since they are present in multiple biological fluids and may represent a relevant source of novel non-invasive biomarkers and be vehicles for new therapeutic approaches. This review highlights the most promising candidate miRs and EV-related biomarkers in cholangiopathies, as well as their relevant roles in biliary pathophysiology. This article is part of a Special Issue entitled: Cholangiocytes in Health and Disease edited by Jesus Banales, Marco Marzioni, Nicholas LaRusso and Peter Jansen.

Selected volatile organic compounds as biomarkers for exposure to tobacco smoke

Cutoff levels on the scales for benzene, ethylbenzene, toluene, styrene, o-xylene and m/p-xylene in blood were developed to classify smokers from non-smokers. Self-reported smoking during the last 5 d was used as the true smoking status. Receiver operating characteristics methods that minimized the difference between specificity and sensitivity were used to develop these cutoffs. Data from National Health and Nutrition Examination Survey for the cycle 2005–2006 were used for this purpose. For the total population, a cutoff of 0.038?ng/ml for benzene was able to classify smokers from non-smokers with a sensitivity of 83.6% and specificity of 83.7%.     

Riboflavin as an independent and accurate biomarker for adherence in a randomized double-blind and placebo-controlled clinical trial

Background: Medication adherence is critical for success of clinical trials.

Objective: To assess oral riboflavin is an adherence marker.

Methods: Riboflavin was incorporated into active treatment and placebo pills for a clinical trial lasting for 2 years.

Results: The accuracy (area under the receiver operating curve) of urinary riboflavin was 0.91 as a binary classifier of adherence, and was similar or better than for two active study ingredients daidzein (0.92) and genistein (0.87) (all p?<?0.0001). Decreased adherence over time was similar in the two study groups.

Conclusion: Riboflavin is an accurate and useful biomarker for study pill ingestion.     

Predator exposure alters female mate choice in the green swordtail

Female green swordtails, Xiphophorus helleri, show a matingpreference for males with brightly colored, elongated swords.This preference is thought to be due to a preexisting receiverbias favoring longer sworded males. In this study, we examinedvariation in the expression of this sword bias in females. Specifically,we tested the hypothesis that an increase in perceived predationrisk will decrease female response to males with longer swords.We used a video playback experiment to evaluate female choicebetween two recordings of a displaying male that differed onlyin sword length. We scored responses of females to these recordingsimmediately before and after they had been exposed to a videorecording of a predation event between a cichlid and a malepossessing a long sword. We found that prior to exposure tothis predation event, females preferred the male with the longersword. However, after exposure to the predator, females alteredtheir mating response, preferring the male with the sword removed.Exposure to the predator also caused an increase in the frequencywith which females moved from potential mating positions toa neutral zone. The results presented here suggest that thefemale preference for males with longer swords can be modulatedbased on the perceived risk of predation.     

BMI and waist circumference in predicting cardiovascular risk factor clustering in Chinese adolescents

Objective: To derive the optimal BMI and waist circumference (WC) cut‐off values to predict clustering of cardiovascular risk factors in Hong Kong Chinese adolescents. Research Methods and Procedures: A total of 2102 Hong Kong Chinese 12 to 19 years of age were recruited. Participants were considered to have clustering of risk factors if at least three of the following risk factors were present: 1) high‐density lipoprotein cholesterol (HDL‐C) ≤1.03 mM, 2) low‐density lipoprotein cholesterol (LDL‐C) ≥2.6 mM, 3) triglyceride (TG) ≥1.24 mM, 4) fasting plasma glucose (FPG) ≥6.1 mM, and 5) age‐, sex‐, and height‐adjusted systolic or diastolic blood pressure (BP) ≥ 90th percentile. Receiver operating characteristics (ROC) curves were generated to identify the optimal age‐adjusted BMI and WC cut‐off values to predict clustering of risk factors in boys and girls separately. These age‐adjusted BMI and WC cut‐offs were transformed to percentile values. Cole's lambda‐mu‐sigma (LMS) method was used to obtain smoothed age‐specific BMI and WC at these percentile values. Results: The areas under ROC curves for BMI in girls and boys were 0.85 [95% confidence interval (CI), 0.77 to 0.92] and 0.76 (95% CI, 0.66 to 0.85), respectively. The respective areas under ROC curves for WC in girls and boys were 0.82 (95% CI, 0.74 to 0.91) and 0.78 (95% CI, 0.68 to 0.87). The optimal BMI thresholds were at the 78th percentile for girls and the 72nd percentile for boys. The respective values for WC were at the 77th percentile for girls and the 76th percentile for boys. The sensitivities and specificities of these cut‐off values ranged from 72% to 80%. Discussion: Age‐ and sex‐specific BMI and WC cut‐off values can be used to identify adolescents with clustering of cardiovascular risk factors.