Biomarker Insights最新文献

Objectives: Elevated soluble urokinase Plasminogen Activator Receptor (suPAR) is a biomarker associated with adverse outcomes. We aimed to investigate the associations between plasma suPAR levels (testing the cut-offs ⩽4, 4-6, and ⩾6 ng/mL) with risk of 14-day mortality, and with the risk of mechanical ventilation in patients that tested positive for SARS-CoV-2.

Methods: Observational cohort study of patients presenting with symptoms of COVID-19 at Department of Emergency Medicine, Amager and Hvidovre Hospital, Denmark from March 19th, 2020 to April 3rd, 2020. Plasma suPAR was measured using suPARnostic technologies. Patients were followed for development of mechanical ventilation and mortality for 14 days. Validation of our findings were carried out in a similar sized COVID-19 patient cohort from Mikkeli Central Hospital, Finland.

Results: Among 386 patients with symptoms of COVID-19, the median (interquartile range) age was 64 years (46-77), 57% were women, median suPAR was 4.0 ng/mL (2.7-5.9). In total, 35 patients (9.1%) died during the 14 days follow-up. Patients with suPAR ⩽4 ng/mL (N = 196; 50.8%) had a low risk of mortality (N = 2; 1.0%; negative predictive value of 99.0%, specificity 55.3%, sensitivity 95.2%, positive predictive value 17.4%). Among patients with suPAR ⩾6 ng/mL (N = 92; 23.8%), 16 died (17.4%). About 99 patients (25.6%) tested positive for SARS CoV-2 and of those 12 (12.1%) developed need for mechanical ventilation. None of the SARS-CoV-2 positive patients with suPAR ⩽4 ng/mL (N = 28; 38.8%) needed mechanical ventilation or died. The Mikkeli Central Hospital validation cohort confirmed our findings concerning suPAR cut-offs for risk of development of mechanical ventilation and mortality.

Conclusions: Patients with symptoms of COVID-19 and suPAR ⩽4 or ⩾6 ng/mL had low or high risk, respectively, concerning the need for mechanical ventilation or mortality. We suggest cut-offs for identification of risk groups in patients presenting to the ED with symptoms of or confirmed COVID-19.

The availability of disease modifying therapies for spinal muscular atrophy (SMA) has created an urgent need to identify clinically meaningful biomarkers. Biomarkers present a means to measure and evaluate neurological disease across time. Changes in biomarkers provide insight into disease progression and may reveal biologic, physiologic, or pharmacologic phenomena occurring prior to clinical detection. Efforts to identify biomarkers for SMA, a genetic motor neuron disease characterized by motor neuron degeneration and weakness, have culminated in a number of putative molecular and physiologic markers that evaluate biological media (eg, blood and cerebrospinal fluid [CSF]) or nervous system function. Such biomarkers include SMN2 copy number, SMN mRNA and protein levels, neurofilament proteins (NFs), plasma protein analytes, creatine kinase (CK) and creatinine (Crn), and various electrophysiology and imaging measures. SMN2 copy number inversely correlates with disease severity and is the best predictor of clinical outcome in untreated individuals. SMN mRNA and protein are commonly measured in the blood or CSF of patients receiving SMA therapies, particularly those aimed at increasing SMN protein expression, and provide insight into current disease state. NFs have proven to be robust prognostic, disease progression, and pharmacodynamic markers for SMA infants undergoing treatment, but less so for adolescents and adults. Select plasma proteins are altered in SMA individuals and may track response to therapy. CK and Crn from blood correlate with motor function and disease severity status and are useful for predicting which individuals will respond to therapy. Electrophysiology measures comprise the most reliable means for monitoring motor function throughout disease course and are sensitive enough to detect neuromuscular changes before overt clinical manifestation, making them robust predictive and pharmacodynamic biomarkers. Finally, magnetic resonance imaging and muscle ultrasonography are non-invasive techniques for studying muscle structure and physiology and are useful diagnostic tools, but cannot reliably track disease progression. Importantly, biomarkers can provide information about the underlying mechanisms of disease as well as reveal subclinical disease progression, allowing for more appropriate timing and dosing of therapy for individuals with SMA. Recent therapeutic advancements in SMA have shown promising results, though there is still a great need to identify and understand the impact of biomarkers in modulating disease onset and progression.

Background: The current knowledge about novel coronavirus-2019 (COVID-19) indicates that the immune system and inflammatory response play a crucial role in the severity and prognosis of the disease. In this study, we aimed to investigate prognostic value of systemic inflammatory biomarkers including C-reactive protein/albumin ratio (CAR), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in patients with severe COVID-19.

Methods: This single-center, retrospective study included a total of 223 patients diagnosed with severe COVID-19. Primary outcome measure was mortality during hospitalization. Multivariate logistic regression analyses were performed to identify independent predictors associated with mortality in patients with severe COVID-19. Receiver operating characteristic (ROC) curve was used to determine cut-offs, and area under the curve (AUC) values were used to demonstrate discriminative ability of biomarkers.

Results: Compared to survivors of severe COVID-19, non-survivors had higher CAR, NLR, and PLR, and lower LMR and lower PNI (P < .05 for all). The optimal CAR, PNI, NLR, PLR, and LMR cut-off values for detecting prognosis were 3.4, 40.2, 6. 27, 312, and 1.54 respectively. The AUC values of CAR, PNI, NLR, PLR, and LMR for predicting hospital mortality in patients with severe COVID-19 were 0.81, 0.91, 0.85, 0.63, and 0.65, respectively. In ROC analysis, comparative discriminative ability of CAR, PNI, and NLR for hospital mortality were superior to PLR and LMR. Multivariate analysis revealed that CAR (⩾0.34, P = .004), NLR (⩾6.27, P = .012), and PNI (⩽40.2, P = .009) were independent predictors associated with mortality in severe COVID-19 patients.

Conclusions: The CAR, PNI, and NLR are independent predictors of mortality in hospitalized severe COVID-19 patients and are more closely associated with prognosis than PLR or LMR.

Human health biobanks are forms of research infrastructure that supply biospecimens and associated data to researchers, and therefore juxtapose the activities of clinical care and biomedical research. The discipline of biobanking has existed for over 20 years and is supported by several international professional societies and dedicated academic journals. However, despite both rising research demand for human biospecimens, and the growth of biobanking as an academic discipline, many individual biobanks continue to experience sustainability challenges. This commentary will summarize how the COVID-19 pandemic is creating new challenges and opportunities for both the health biobanking sector and the supporting discipline of biobanking. While the challenges for biobanks may be numerous and acute, there are opportunities for both individual biobanks and the discipline of biobanking to embrace change such that biobanks can continue to support and drive biomedical research. We will therefore describe numerous practical steps that individual biobanks and/or the discipline of biobanking can take to survive and possibly thrive in response to the COVID-19 pandemic.

Corticosteroids reduced mortality rate in patients with coronavirus disease 2019 (COVID-19). Previously, we hypothesized that corticosteroids mitigate the inflammation response resulting in reduced coagulation and thrombosis. In this retrospective study, we included 27 patients with COVID-19 that received high-dose corticosteroids (methylprednisolone 1000 mg i.v. daily for 3 days) for persistent respiratory failure or an excessive inflammation response. We found that inflammation, coagulation, and ventilation parameters improved significantly after methylprednisolone. The viral loads of SARS-CoV-2 remained stable or decreased. These results provides insight into the reduced mortality rate observed in patients with COVID-19 treated with corticosteroids.

Cognitive impairment due to cancer and its therapy is a major concern among cancer patients and survivors. Extracellular vesicle (EVs) composition altered by cancer and chemotherapy may affect neurological processes such as neuroplasticity, potentially impacting the cognitive abilities of cancer patients and survivors. We investigated the EV proteome of breast cancer patients with and without cognitive impairment following anthracycline-based chemotherapy from longitudinally collected plasma. EVs were cup-shaped and positive for Flotillin-1 and TSG-101. We identified 517 differentially expressed EV proteins between the cognitive impaired and non-impaired groups during and post-chemotherapy. The observed decreased expression of p2X purinoceptor, cofilin-1, ADAM 10, and dynamin-1 in the plasma EVs of the cognitive impaired group may suggest alterations in the mechanisms underlying synaptic plasticity. The reduced expression of tight junction proteins among cognitive-impaired patients may imply weakening of the blood-brain barrier. These EV protein signatures may serve as a fingerprint that underscores the mechanisms underlying cognitive impairment in cancer patients and survivors.

Serum microfibrillar-associated protein 4 (sMFAP4) has been investigated as a biomarker for various diseases and is demonstrated to show significant gradual increase with severity of liver fibrosis. Ideal biomarkers used for disease diagnosis or prognosis should display deviating levels in affected individuals only and be robust to factors unrelated to the disease. Here we show the impact of normal physiological variation of sMFAP4 by characterizing the circadian variation, week-to-week variation, and physical exercise-induced levels. Serum samples from 3 groups of healthy volunteers were drawn: 7 times during a 24-hour period, 5 times during a 3-week period, and before and after a standardized physical exercise challenge. sMFAP4 was determined by AlphaLISA. Statistical analysis was performed using mixed effects modeling of repeated measurements. Circadian variation of sMFAP4 was demonstrated, with time of peak and nadir values depending on age and gender. For males, the peak values were observed during nighttime whereas for females, peak values were observed in the morning. Individual sMFAP4 levels remained stable over a period of 3 weeks and physical exercise inferred a mild negative influence. In conclusion, the circadian sMFAP4 variation was significant, and the levels could be influenced by physical activity. However, these variations were of limited magnitude relative to previously observed disease-induced levels in support of the biomarker potential of sMFAP4.

Multiple sclerosis (MS) is an autoimmune inflammatory disorder of the central nervous system (CNS) resulting in demyelination and axonal loss in the brain and spinal cord. The precise pathogenesis and etiology of this complex disease are still a mystery. Despite many studies that have been aimed to identify biomarkers, no protein marker has yet been approved for MS. There is urgently needed for biomarkers, which could clarify pathology, monitor disease progression, response to treatment, and prognosis in MS. Proteomics and metabolomics analysis are powerful tools to identify putative and novel candidate biomarkers. Different human compartments analysis using proteomics, metabolomics, and bioinformatics approaches has generated new information for further clarification of MS pathology, elucidating the mechanisms of the disease, finding new targets, and monitoring treatment response. Overall, omics approaches can develop different therapeutic and diagnostic aspects of complex disorders such as multiple sclerosis, from biomarker discovery to personalized medicine.

Over the past 10 years, there has been limited progress for the treatment of brain cancer and outcomes for patients are not much improved. For brain cancer researchers, a major obstacle to biomarker driven research is limited access to brain cancer tissue for research purposes. The Mark Hughes Foundation Brain Biobank is one of the first post-mortem adult brain banks in Australia to operate with protocols specifically developed for brain cancer. Located within the Hunter New England Local Health District and operated by Hunter Cancer Biobank, the boundaries of service provided by the Brain Bank extend well into the surrounding regional and rural areas of the Local Health District and beyond. Brain cancer biobanking is challenging. There are conflicting international guidelines for best practice and unanswered questions relating to scientific, psychosocial and operational practices. To address this challenge, a best practice model was developed, informed by a consensus of existing data but with consideration of the difficulties associated with operating in regional or resource poor settings. The regional application of this model was challenged following the presentation of a donor located in a remote area, 380km away from the biobank. This required biobank staff to overcome numerous obstacles including long distance patient transport, lack of palliative care staff, death in the home and limited rural outreach services. Through the establishment of shared goals, contingency planning and the development of an informal infrastructure, the donation was facilitated within the required timeframe. This experience demonstrates the importance of collaboration and networking to overcome resource insufficiency and geographical challenges in rural cancer research programmes.