Biological variation of peripheral blood T-lymphocytes

Within- and between-subject biological variation estimates for the enumeration of lymphocyte deep immunophenotyping and monocyte subsets

OBJECTIVES

This study aimed to deliver biological variation (BV) estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping (memory T/B cells, regulatory T cells, etc.) and classical, intermediate, and nonclassical monocyte subsets based on the full spectrum flow cytometry (FS-FCM) and a Biological Variation Data Critical Appraisal Checklist (BIVAC) design.

METHODS

Samples were collected biweekly from 60 healthy Chinese adults over 10 consecutive two-week periods. Each sample was measured in duplicate within a single run for lymphocyte deep immunophenotyping and monocyte subset determination using FS-FCM, including the percentage (%) and absolute count (cells/μL). After trend adjustment, a Bayesian model was applied to deliver the within-subject BV (CVI) and between-subject BV (CVG) estimates with 95 % credibility intervals.

RESULTS

Enumeration (% and cells/μL) for 25 types of lymphocyte deep immunophenotyping and three types of monocyte subset percentages showed considerable variability in terms of CVI and CVG. CVI ranged from 4.23 to 47.47 %. Additionally, CVG ranged between 10.32 and 101.30 %, except for CD4+ effector memory T cells re-expressing CD45RA. No significant differences were found between males and females for CVI and CVG estimates. Nevertheless, the CVGs of PD-1+ T cells (%) may be higher in females than males. Based on the desired analytical performance specification, the maximum allowable imprecision immune parameter was the CD8+PD-1+ T cell (cells/μL), with 23.7 %.

CONCLUSIONS

This is the first study delivering BV estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping, along with classical, intermediate, and nonclassical monocyte subsets, using FS-FCM and adhering to the BIVAC design.

Mechanism of action of Coptidis Rhizome in treating periodontitis based on network pharmacology and in vitro validation

OBJECTIVE

Explore the therapeutic mechanism of Coptidis Rhizome (CR) in periodontitis using network pharmacology, and validate it through molecular docking and in vitro experiments.

METHODS

Screened potential active components and target genes of CR from TCMSP and Swiss databases. Identified periodontitis-related target genes using GeneCards. Found common target genes using Venny. Conducted GO and KEGG pathway analysis. Performed molecular docking and in vitro experiments using Berberine, the main active component of CR, on lymphocytes from healthy and periodontitis patients. Assessed effects on inflammatory factors using CCK-8, flow cytometry, and ELISA.

RESULTS

Fourteen active components and 291 targets of CR were identified. 30 intersecting target genes with periodontitis were found. GO and KEGG analysis revealed oxidative stress response and IL-17 signaling pathway as key mechanisms. Molecular docking showed strong binding of Berberine with ALOX5, AKT1, NOS2, and TNF. In vitro experiments have demonstrated the ability of berberine to inhibit the expression of Th17 + and other immune related cells in LPS stimulated lymphocytes, and reduce the secretion of IL-6, IL-8, and IL-17.

CONCLUSION

CR treats periodontitis through a multi-component, multi-target, and multi-pathway approach. Berberine, its key component, acts through the IL-17 signaling pathway to exert anti-inflammatory effects.

Establishment and Clinical Application of a Method for Detecting T Lymphocyte Subsets by Cellular Immunochip Technology

Objective

To establish and verify the method for detecting the immune phenotype of peripheral blood T lymphocytes by cellular immune chip technology, analyze the immune status, and discuss its clinical diagnostic value of different populations in the Qingyuan area.

Methods

First, a cellular immune chip was used to detect the number of T lymphocyte subsets CD3+, CD4+, CD8+, and CD4/CD8, followed by evaluating the accuracy and precision through a comparison with flow cytometry. After passing the performance verification, a large-scale detection was performed by a cellular immune chip in 8389 cases. Immunochip technology detects the expression of T lymphocyte subsets and analyzes the differences in cellular immune function among people with physical examination, inflammation, and cancer, as well as different cancer types and in genders.

Results

The cell immunochip method and flow cytometry method have the same accuracy and precision in detecting specimens, and the former is fast and simple, and is suitable for clinical use; big data analysis is expected to establish a reference range for CD3+, CD4+, and CD8+ T cell counts in Qingyuan. There are statistical differences in CD3+, CD4+, CD8+ T cell counts in physical examination, inflammation and cancer populations; there are also certain differences in CD3+, CD4+, CD8+ T cell counts and CD4/CD8 ratios between different cancer types and different diseases.

Conclusion

The method of cell immunochip technology to detect T lymphocyte subsets is simple and practical, with accurate results and rapid detection. It can be used for immune function monitoring and treatment prognosis evaluation of people with different diseases, and it is worthy of popularization and application in clinical practice.

The development of autoverification system of lymphocyte subset assays on the flow cytometry platform

OBJECTIVES

Peripheral blood lymphocyte subsets are important parameters for monitoring immune status; however, lymphocyte subset detection is time-consuming and error-prone. This study aimed to explore a highly efficient and clinically useful autoverification system for lymphocyte subset assays performed on the flow cytometry platform.

METHODS

A total of 94,402 lymphocyte subset test results were collected. To establish the limited-range rules, 80,427 results were first used (69,135 T lymphocyte subset tests and 11,292 NK, B, T lymphocyte tests), of which 15,000 T lymphocyte subset tests from human immunodeficiency virus (HIV) infected patients were used to set customized limited-range rules for HIV infected patients. Subsequently, 13,975 results were used for historical data validation and online test validation.

RESULTS

Three key autoverification rules were established, including limited-range, delta-check, and logical rules. Guidelines for addressing the issues that trigger these rules were summarized. The historical data during the validation phase showed that the total autoverification passing rate of lymphocyte subset assays was 69.65% (6,941/9,966), with a 67.93% (5,268/7,755) passing rate for T lymphocyte subset tests and 75.67% (1,673/2,211) for NK, B, T lymphocyte tests. For online test validation, the total autoverification passing rate was 75.26% (3,017/4,009), with 73.23% (2,191/2,992) for the T lymphocyte subset test and 81.22% (826/1,017) for the NK, B, T lymphocyte test. The turnaround time (TAT) was reduced from 228 to 167 min using the autoverification system.

CONCLUSIONS

The autoverification system based on the laboratory information system for lymphocyte subset assays reduced TAT and the number of error reports and helped in the identification of abnormal cell populations that may offer clues for clinical interventions.

Dysfunction of adaptive immunity is related to severity of COVID-19: a retrospective study

Background:

In December of 2019, coronavirus disease 2019 (Covid-19) was reported in Wuhan, China, and has now rapidly swept around the world. Much research has been carried out since the outbreak, but few studies have focused on the dysfunction of the adaptive immunity.

Methods:

In this retrospective and multi-center study, 373 patients with laboratory-confirmed COVID-19 from Shanghai Public Health Clinical Center and Affiliated Hospital of Putian University were recruited. Demographic, clinical, radiological features, and laboratory data were recorded and analyzed at admission and at discharge. Results of immunological tests were followed up until the patients were discharged.

Results:

Of the 373 patients with COVID-19 pneumonia, 322 were in the non-severe group and 51 were in the severe group. Number of T cells, CD4+ and CD8+ T cells, and total lymphocytes declined remarkably upon admission and elevated when the patients were discharged. At admission, counts of total lymphocytes, T cells, CD4+ and CD8+ T cells, and levels of C3 and C4 in the severe group were lower than those in the non-severe group, whereas the neutrophil to lymphocyte ratio (NLR) was higher in the severe group. Counts of T cells, CD4+ and CD8+ T cells, and total lymphocytes were negatively correlated with lactate dehydrogenase and C-reactive protein.

Conclusion:

COVID-19 might target adaptive immunity and cause a decrease in lymphocytes, especially T cells and subsets. Physicians should pay close attention to the adaptive immunity of patients upon admission. Monitoring NLR, T lymphocytes, and subsets would help physicians with the proper diagnosis and treatment of COVID-19.

The reviews of this paper are available via the supplemental material section.

Long-term biological variation estimates of 13 hematological parameters in healthy Chinese subjects

Background The complete blood count (CBC) is a basic test routinely ordered by physicians as a part of initial diagnostic work-up on their patients. To ensure safe clinical application of the CBC, reliable biological variation (BV) data are needed to establish analytical performance specifications. Our aim was to define the BV of CBC parameters using a rigorous protocol that is compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) provided by the European Federation of Clinical Chemistry and Laboratory Medicine. Methods Blood samples drawn from 41 healthy Chinese subjects (22 females and 19 males; 23-59 years of age) once monthly for 6 consecutive months were analyzed using an ABX Pentra 80 instrument. The instrument was precisely calibrated. All samples were analyzed in duplicate for 13 CBC parameters. The data were assessed for outliers, normality, and variance homogeneity prior to nested ANOVA. Gender-stratified within-subject (CVI) and between-subject (CVG) BV estimates were calculated. Results The number of remaining data for each subject was 442-484 after removing outliers. No significant differences existed between female/male CVI estimates. Except for leukocytes, neutrophils, and lymphocytes, the mean values of 10 parameters differed significantly between genders, rendering partitioning of CVG data between genders. No significant differences were detected between most BV estimates and recently published estimates representing a Europid population. Conclusions Most BV estimates in BIVAC-compliant studies are similar. The turnover time of blood cells and age distribution of participants should be considered in a CBC BV study. Our study will contribute to global BV estimates and future studies.

Study of total error specifications of lymphocyte subsets enumeration using China National EQAS data and Biological Variation Data Critical Appraisal Checklist (BIVAC)-compliant publications

Objectives

It is important to select proper quality specifications for laboratories and external quality assessment (EQA) providers for their quality control and assessment. The aim of this study is to produce new total error (TE) specifications for lymphocyte subset enumeration by analyzing the allowable TE using EQAS data and comparing them with that based on reliable biological variation (BV).

Methods

A total of 54,400 results from 1,716 laboratories were collected from China National EQAS for lymphocyte subset enumeration during the period 2017-2019. The EQA data were grouped according to lower limits of reference intervals for establishing concentration-dependent specifications. The TE value that 80% of laboratories can achieve were considered as TE specifications based on state of the art. The BV studies compliant with Biological Variation Data Critical Appraisal Checklist (BIVAC) were used to calculate the three levels of TE specifications. Then these TE specifications were compared for determining the recommended TE specifications.

Results

Four parameters whose quality specifications could achieve the optimum criteria were as follows: the percentages of CD3+, CD3+CD4+ (high concentration) and CD3-CD16/56+ cells, and the absolute count of CD3-CD16/56+ cells. Only the TE specifications of CD3-CD19+ cells could achieve the minimum criteria. The TE specifications of remaining parameters should reach the desirable criteria.

Conclusions

New TE specifications were established by combining the EQA data and reliable BV data, which could help laboratories to apply proper criteria for continuous improvement of quality control, and EQA providers to use robust acceptance limits for better evaluation of EQAS results.