The establishment of neuron-specific enolase reference interval for the healthy population in southwest China

Neurological Damage Measured by S-100b and Neuron-Specific Enolase in Patients Treated with Electroconvulsive Therapy

Electroconvulsive therapy (ECT) is considered one of the most effective treatments for psychiatric disorders. ECT has proven effective in the treatment of depression, mania, catatonia and psychosis. It is presumed that seizures induced during ECT administration cause toxicity and potentially neuronal and glial cell death. A broad range of neurological disorders increase cerebrospinal fluid and serum levels of neuron-specific enolase (NSE) and S-100b protein. This study aims to investigate the effect of ECT on NSE and S-100b levels, which, together, serve as a proxy for neuronal cell damage. Serum concentrations of S-100b and NSE of adult patients who received ECT were measured by immunoluminometric analysis before and after treatment. A two-way ANOVA test was used to estimate the statistical differences in marker concentrations between the subgroups of the study population. Results: A total of 55 patients were included in the analysis: 52.73% (n = 29) were diagnosed with depression, 21.82% (n = 12) with schizophrenia or other psychosis, 16.36% (n = 9) with mania and 9.09% (n = 5) with catatonia. There were no statistically significant changes in NSE (p = 0.288) and S-100b (p = 0.243) levels. We found no evidence that ECT induced neuronal damage based on NSE and S-100b protein levels measured in the serum of patients before and after treatment.

Which neuroimaging and fluid biomarkers method is better in theranostic of Alzheimer's disease? An umbrella review

Biomarkers are measured to evaluate physiological and pathological processes as well as responses to a therapeutic intervention. Biomarkers can be classified as diagnostic, prognostic, predictor, clinical, and therapeutic. In Alzheimer's disease (AD), multiple biomarkers have been reported so far. Nevertheless, finding a specific biomarker in AD remains a major challenge. Three databases, including PubMed, Web of Science, and Scopus were selected with the keywords of Alzheimer's disease, neuroimaging, biomarker, and blood. The results were finalized with 49 potential CSF/blood and 35 neuroimaging biomarkers. To distinguish normal from AD patients, amyloid-beta42 (Aβ42), plasma glial fibrillary acidic protein (GFAP), and neurofilament light (NFL) as potential biomarkers in cerebrospinal fluid (CSF) as well as the serum could be detected. Nevertheless, most of the biomarkers fairly change in the CSF during AD, listed as kallikrein 6, virus-like particles (VLP-1), galectin-3 (Gal-3), and synaptotagmin-1 (Syt-1). From the neuroimaging aspect, atrophy is an accepted biomarker for the neuropathologic progression of AD. In addition, Magnetic resonance spectroscopy (MRS), diffusion weighted imaging (DWI), diffusion tensor imaging (DTI), tractography (DTT), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI), can be used to detect AD. Using neuroimaging and CSF/blood biomarkers, in combination with artificial intelligence, it is possible to obtain information on prognosis and follow-up on the different stages of AD. Hence physicians could select the suitable therapy to attenuate disease symptoms and follow up on the efficiency of the prescribed drug.

Molecular biomarkers of diffuse axonal injury: recent advances and future perspectives

INTRODUCTION

Diffuse axonal injury (DAI), with high mortality and morbidity both in children and adults, is one of the most severe pathological consequences of traumatic brain injury. Currently, clinical diagnosis, disease assessment, disability identification, and postmortem diagnosis of DAI is mainly limited by the absent of specific molecular biomarkers.

AREAS COVERED

In this review, we first introduce the pathophysiology of DAI, summarized the reported biomarkers in previous animal and human studies, and then the molecular biomarkers such as β-Amyloid precursor protein, neurofilaments, S-100β, myelin basic protein, tau protein, neuron-specific enolase, Peripherin and Hemopexin for DAI diagnosis is summarized. Finally, we put forward valuable views on the future research direction of diagnostic biomarkers of DAI.

EXPERT OPINION

In recent years, the advanced technology has ultimately changed the research of DAI, and the numbers of potential molecular biomarkers was introduced in related studies. We summarized the latest updated information in such studies to provide references for future research and explore the potential pathophysiological mechanism on diffuse axonal injury.

Brain damage serum biomarkers induced by COVID-19 in patients from northeast Brazil

Neurological symptoms have been often reported in COVID-19 disease. In the present study, we evaluated brain damage associated with the increase of serum levels of neurological biomarkers S100B and neuron-specific enolase (NSE) induced by SARS-CoV-2 infection, in a population from Northeastern Brazil. Thirty-six healthy control (G1) individuals and 141 patients with confirmed COVID-19 were enrolled in this study. Positive-COVID-19 patients were divided into two groups according to the severity of illness by the National Institute of Health (NIH) criteria, 76 patients with mild symptoms for COVID-19 and (G2) and 65 with acute respiratory conditions requiring supplemental oxygenation via intensive care unit (ICU) admission (G3). A follow-up study was conducted with 23 patients from G2 14 (D14) and 21 (D21) days after the onset of symptoms. Serum levels of NSE and S100B were measured using the enzyme-linked immunoassay method (ELISA). Results revealed a significant positive association between G3 patients and S100B serum expression (p = 0.0403). The serum levels of NSE were also significantly enhanced in the G3 group compared to the control (p < 0.0001) and G2 group (p < 0.0001). In addition, clinical features such as symptoms and oxygenation status were not correlated with NSE or S100B serum expression. The follow-up study demonstrated a decrease over time (21 days) in NSE serum expression (p < 0.0001). These results suggest that brain damage is followed by acute virus exposure, with no long-term effects. Future work examining COVID-19 recovery will shed light on chronic neurological damage of SARS-CoV-2 infection.

Application of the Hoffmann, Bhattacharya, nonparametric test, and Q-Q plot methods for establishing reference intervals from laboratory databases

BACKGROUND

Reference intervals (RIs) are vital for interpreting laboratory biomarkers and enabling clinical decision-making. Among various RI-estimation methods, we explored the application value of Hoffmann, Bhattacharya, nonparametric test, and Q-Q plot methods for estimating the RI of urea, creatinine, and uric acid (UA).

METHOD

This cross-sectional study collected patient data recorded between January 2020 and April 2022 at the Chongqing University Central Hospital Laboratory Information System. The RIs of urea, creatinine, and UA levels were established using the Hoffmann, Bhattacharya, nonparametric, and Q-Q plot methods, and RI differences with different computational methods were verified using the reference change value (RCV%) of biological variability.

RESULTS

We included 16,474 and 123,570 patients in the physical examination and clinical groups, respectively. In the clinical group, differences in the RI upper limit of analytes with the four methods (excluding the Q-Q plot method) were within the permissible RCV% range; only the nonparametric test produced an RI of urea with the lower limit within the permissible RCV% range. In the physical examination group, the relative RI differences among the four methods (excluding the lower limit of RI obtained using the Q-Q plot) were all within the acceptable RCV% range; the relative deviation of the RI of UA with the four methods was within the acceptable RCV% range (excluding the lower RI limit obtained using the Q-Q plot and nonparametric test).

CONCLUSION

The Hoffmann and Bhattacharya methods may provide reliable RIs for indirect estimations of urea, creatinine, and UA based on laboratory datasets.

Changes in lung cancer-related serum tumor markers in patients with chronic kidney disease and determination of upper reference limit

Aims

To investigate the changes in lung cancer-related serum tumor markers in patients with chronic kidney disease (CKD) and determine the upper reference limit for patients with different stages.

Methods

Included inpatients diagnosed with CKD who did not receive dialysis temporarily in our hospital from March to September 2020. Changes in serum CA125, HE4, CYFRA21-1, SCCA, NSE and ProGRP in CKD patients were analyzed. The non-parametric method was used to estimate the upper reference limit of the above indicators in patients with CKD stages 2-5.

Results

The serum levels of HE4, CYFRA21-1, SCCA, and ProGRP in the CKD group were significantly higher than those in the healthy control group; CA125 and NSE levels were not statistically different. The false positives of SCC, CYFRA21-1, ProGRP, and HE4 increased significantly with the CKD stage. Still, NSE and CA125 did not show a significant increasing trend. Both HE4 and ProGRP have independent upper reference limits from CKD2 to CKD5 stage, namely 220.8 pmol/l and 101.4 pg/ml in the CKD2 stage, 496.7 pmol/l and 168.63 pg/ml in CKD3 stage, 4592.4 pmol/l and 272.8 pmol/l for CKD4 stage, CKD5 stage was 4778.2 pmol/l and 491.6 pmol/l.

Conclusion

This study preliminarily determined the upper reference limits of Lung cancer-related tumor markers in patients with different CKD stages and provided laboratory support for the rational use and interpretation of Lung cancer-related tumor markers in special populations.

An exploratory study; the gap between real reference interval and currently used reference interval of RBC AChE activities in South Korea

The current reference interval (RI) FOR red blood cell acetylcholinesterase (RBC AChE) activity in South Korea was established with data obtained from populations outside the country. The aim of this study was to assess the transferability of current RI of RBC AChE activity for organophosphate (OP) poisoning and determine the biological characteristics, real RI, and interindividual variation in RBC AChE activity in South Korea. Data were retrospectively collected for RBC AChE activity as measured by the modified Ellman's method for 782 patients who presented to our hospital. The clinical course did not differ significantly with the degree of deviation of RBC AChE activity from the currently used RI in 195 patients exposed to OP. RBC AChE activity was associated with gender and smoking status but not age or body mass index (BMI); however, a regression model incorporating age, gender, smoking status and BMI explained only a small portion of the variance in RBC AChE activity in South Korea. The RI of RBC AChE activity was 9,403-16,825 U/L, with 13.9% interindividual variation. The range of RBC AChE activity in South Korea is wider than RI currently used in clinical practice and exhibited a high degree of interindividual variation. In the absence of collecting pre-exposure values, it is recommended to conduct serial measurements, rather than one-point measurements, of RBC AChE activity as evidenced by the RI in OP poisoning.

Big data and reference intervals

Although reference intervals (RIs) play an important role in clinical diagnosis, there remain significant differences with respect to race, gender, age and geographic location. Accordingly, the Clinical Laboratory Standards Institute (CLSI) EP28-A3c has recommended that clinical laboratories establish RIs appropriate to their subject population. Unfortunately, the traditional and direct approach to establish RIs relies on the recruitment of a sufficient number of healthy individuals of various age groups, collection and testing of large numbers of specimens and accurate data interpretation. The advent of the big data era has, however, created a unique opportunity to "mine" laboratory information. Unfortunately, this indirect method lacks standardization, consensus support and CLSI guidance. In this review we provide a historical perspective, comprehensively assess data processing and statistical methods, and post-verification analysis to validate this big data approach in establishing laboratory specific RIs.