Annals of Laboratory Medicine最新文献

Background: Facioscapulohumeral muscular dystrophy (FSHD) is a common form of muscular dystrophy that mainly affects skeletal muscle. FSHD1 accounts for 95% of all FSHD cases and can be diagnosed based on the pathogenic contraction of the D4Z4-repeat array on chromosome 4q35. Genetic diagnosis of FSHD1 is challenging because of the large size and repetitive nature of the D4Z4 region. We evaluated the clinical applicability of optical genome mapping (OGM) for the genetic diagnosis of FSHD1.

Methods: We included 25 individuals with clinically confirmed or suspected/probable FSHD and their families. Ultra-high-molecular-weight DNA from peripheral blood was labeled, stained, and imaged using a single-molecule OGM platform (Bionano Genomics Saphyr system). D4Z4 repeat size and haplotype information were analyzed using the manufacturer's dedicated pipeline. We also compared the workflow and test time between Southern blot analysis and OGM.

Results: We obtained concordant OGM and Southern blot results with 10 samples from patients with clinically confirmed FSHD. The D4Z4 repeat size differed within 1 unit between the Southern blot analysis and OGM. Among nine patients with clinically suspected or probable FSHD, six patients were confirmed to have pathogenic contractions by OGM. In our cohort, one de novo mosaic FSHD1 patient was successfully diagnosed with OGM. Moreover, OGM has a more straightforward and less time-consuming workflow than Southern blot analysis.

Conclusions: OGM enables accurate and reliable detection of pathogenic contraction of the D4Z4-repeat array and is a valuable tool for the genetic diagnosis of FSHD1.

The term "multiple primary (MP) cancers" refers to the existence of more than one cancer in the same patient. The combination of MP cancers with hematological malignancies is relatively uncommon. In this study, we present five patients diagnosed with MP cancers concomitant with hematological malignancies. We comprehensively analyzed their clinical characteristics, cytogenetic profiles, and germline and somatic variants. As first primaries, two patients had solid cancer not followed by cytotoxic therapy and three had hematologic cancer, followed by cytotoxic therapy. The second primaries were all hematologic malignancies that did not meet the criteria for therapy-related myeloid neoplasm. Notably, two (40%) out of the five patients harbored pathogenic potential/presumed germline variants in cancer predisposition genes. Therefore, germline variant testing should be considered when MP cancers with hematological malignancies require consideration for related donor stem cell transplantation.

Background: Millions of patients undergo cardiac surgery each year. The red blood cell distribution width (RDW) could help predict the prognosis of patients who undergo percutaneous coronary intervention or coronary artery bypass surgery. We investigated whether the RDW has robust predictive value for the 30-day mortality among patients in an intensive care unit (ICU) after undergoing cardiac surgery.

Methods: Using the Medical Information Mart for Intensive Care-IV Database, we retrieved data for 11,634 patients who underwent cardiac surgery in an ICU. We performed multivariate Cox regression analysis to model the association between the RDW and 30-day mortality and plotted Kaplan-Meier curves. Subgroup analyses were stratified using relevant covariates. Receiver operating characteristic (ROC) curves were used to determine the predictive value of the RDWs.

Results: The total 30-day mortality rate was 4.2% (485/11,502). The elevated-RDW group had a higher 30-day mortality rate than the normal-RDW group (P&0.001). The robustness of our data analysis was confirmed by performing subgroup analyses. Each unit increase in the RDW was associated with a 17% increase in 30-day mortality when the RDW was used as a continuous variable (adjusted hazard ratio=1.17, 95% confidence interval, 1.10-1.25). Our ROC results showed the predictive value of the RDW.

Conclusions: An elevated RDW was associated with a higher 30-day mortality in patients after undergoing cardiac surgery in an ICU setting. The RDW can serve as an efficient and accessible method for predicting the mortality of patients in ICUs following cardiac surgery.

Background: Coronavirus disease (COVID-19) induces inflammation, coagulopathy following platelet and monocyte activation, and fibrinolysis, resulting in elevated D-dimer levels. Activated platelets and monocytes produce microvesicles (MVs). We analyzed the differences in platelet and monocyte MV counts in mild, moderate, and severe COVID-19, as well as their correlation with D-dimer levels.

Methods: In this cross-sectional study, blood specimens were collected from 90 COVID-19 patients and analyzed for D-dimers using SYSMEX CS-2500. Platelet MVs (PMVs; PMVCD42b⁺ and PMVCD41a⁺), monocyte MVs (MMVs; MMVCD14⁺), and phosphatidylserine-binding annexin V (PS, AnnV⁺) were analyzed using a BD FACSCalibur instrument.

Results: PMV and MMV counts were significantly increased in COVID-19 patients. AnnV⁺ PMVCD42b⁺ and AnnV⁺ PMVCD41a⁺ cell counts were higher in patients with severe COVID-19 than in those with moderate clinical symptoms. The median (range) of AnnV⁺ PMVCD42b⁺ (MV/μL) in mild, moderate, and severe COVID-19 was 1,118.3 (328.1-1,910.5), 937.4 (311.4-2,909.5), and 1,298.8 (458.2-9,703.5), respectively (P =0.009). The median (range) for AnnV⁺ PMVCD41a⁺ (MV/μL) in mild, moderate, and severe disease was 885.5 (346.3-1,682.7), 663.5 (233.8-2,081.5), and 1,146.3 (333.3-10,296.6), respectively (P =0.007). D-dimer levels (ng/mL) weak correlated with AnnV⁺ PMVCD41a⁺ (P =0.047, r=0.258).

Conclusions: PMV PMVCD42b⁺ and PMVCD41a⁺ counts were significantly increased in patients with severe clinical symptoms, and PMVCD41a⁺ counts correlated with D-dimer levels. Therefore, MV counts can be used as a potential biomarker of COVID-19 severity.

Background: The Jr^a antigen is a high-prevalence red blood cell (RBC) antigen. Reports on cases of fatal hemolytic disease of the fetus and newborn and acute hemolytic transfusion reactions suggest that antibodies against Jr^a (anti-Jr^a) have potential clinical significance. Identifying anti-Jr^a is challenging owing to a lack of commercially available antisera. We developed an alternative approach to rapidly predict the presence of anti-Jr^a using the TaqMan single-nucleotide polymorphism (SNP)-genotyping method.

Methods: Residual peripheral blood samples from 10 patients suspected of having the anti-Jr^a were collected. Two samples with confirmed Jr(a-) RBCs and anti-Jr^a were used to validate the TaqMan genotyping assay by comparing the genotyping results with direct sequencing. The accuracy of the assay in predicting the presence of anti-Jr^a was verified through crossmatching with in-house Jr(a-) O+ RBCs.

Results: The TaqMan-genotyping method was validated with two Jr(a-) RBC- and anti-Jr^a-confirmed samples that showed concordant Jr^a genotyping and direct sequencing results. Jr^a genotyping for the remaining samples and crossmatching the serum samples with inhouse Jr(a-) O+ RBCs showed consistent results.

Conclusions: We validated a rapid, simple, accurate, and cost-effective method for predicting the presence of anti-Jr^a using a TaqMan-based SNP-genotyping assay. Implementing this method in routine practice in clinical laboratories will assist in solving difficult problems regarding alloantibodies to high-prevalence RBC antigens and ultimately aid in providing safe and timely transfusions and proper patient care.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Vancomycin variable Enterococcus (VVE) bacteria are phenotypically susceptible to vancomycin, but they harbor the vanA gene. We aimed to ascertain the prevalence of VVE among clinically isolated vancomycin-susceptible Enterococcus faecium (VSE) isolates, as well as elucidate the molecular characteristics of the vanA gene cluster within these isolates. Notably, we investigated the prevalence and structure of the vanA gene cluster of VVE. Between June 2021 and May 2022, we collected consecutive, non-duplicated vancomycin-susceptible Enterococcus faecium (VSE) samples. Real-time PCR was performed to detect the presence of vanA, vanB, and vanC. Overlapping PCR with sequencing and whole-genome sequencing were performed for structural analysis. Sequence types (STs) were determined by multilocus sequence typing. Exposure testing was performed to assess the ability of the isolates to acquire vancomycin resistance. Among 282 VSE isolates tested, 20 isolates (7.1%) were VVE. Among them, 17 isolates had partial deletions in the IS1216 or IS1542 sequences in vanS (N=10), vanR (N=5), or vanH (N=2). All VVE isolates belonged to the CC17 complex and comprised five STs, namely ST17 (40.0%), ST1421 (25.0%), ST80 (25.0%), ST787 (5.0%), and ST981 (5.0%). Most isolates were related to three hospital-associated clones (ST17, ST1421, and ST80). After vancomycin exposure, 18 of the 20 VVEs acquired vancomycin resistance. Considering the high reversion rate, detecting VVE by screening VSE for vanA is critical for appropriate treatment and infection control.