Banking with precision: transfusion medicine as a potential universal application in clinical genomics

Application of Different Ventilation Modes Combined with AutoFlow Technology in Thoracic Surgery

To investigate the effect of AutoFlow on airway pressure and hemodynamics in mechanical ventilation constant volume-control ventilation mode, 100 patients receiving mechanical ventilation were randomly divided into observation group (SIMV-PSV-PEEP + AutoFlow) and control group (SIMV-PSV-PEEP). The results showed that the peak airway pressure and average airway pressure decreased with different flow rate settings and automatic flow conversion (P < 0.05). The peak airway pressure and mean airway pressure decreased with different resistance settings (P < 0.05). With different compliance settings, the peak airway pressure and average airway pressure decreased after being assisted with an automatic converter (P < 0.05). Adding AutoFlow on the basis of SIMV-PSV mode can significantly reduce peak inspiratory pressure (PIP), mean airway pressure (Pmean), and airway resistance (R). There was no significant difference in hemodynamic monitoring results between the observation group and the control group. It is proved that the SIMV constant volume-controlled ventilation mode combined with AutoFlow can not only ensure tidal volume but also avoid excessive airway pressure, which has little effect on hemodynamics.

An open-source python library for detection of known and novel Kell, Duffy and Kidd variants from exome sequencing

BACKGROUND AND OBJECTIVES

Next generation sequencing (NGS) has promising applications in transfusion medicine. Exome sequencing (ES) is increasingly used in the clinical setting, and blood group interpretation is an additional value that could be extracted from existing data sets. We provide the first release of an open-source software tailored for this purpose and describe its validation with three blood group systems.

MATERIALS AND METHODS

The DTM-Tools algorithm was designed and used to analyse 1018 ES NGS files from the ClinSeq® cohort. Predictions were correlated with serology for 5 antigens in a subset of 108 blood samples. Discrepancies were investigated with alternative phenotyping and genotyping methods, including a long-read NGS platform.

RESULTS

Of 116 genomic variants queried, those corresponding to 18 known KEL, FY and JK alleles were identified in this cohort. 596 additional exonic variants were identified KEL, ACKR1 and SLC14A1, including 58 predicted frameshifts. Software predictions were validated by serology in 108 participants; one case in the FY blood group and three cases in the JK blood group were discrepant. Investigation revealed that these discrepancies resulted from (1) clerical error, (2) serologic failure to detect weak antigenic expression and (3) a frameshift variant absent in blood group databases.

CONCLUSION

DTM-Tools can be employed for rapid Kell, Duffy and Kidd blood group antigen prediction from existing ES data sets; for discrepancies detected in the validation data set, software predictions proved accurate. DTM-Tools is open-source and in continuous development.

Targeted exome sequencing designed for blood group, platelet, and neutrophil antigen investigations: Proof-of-principle study for a customized single-test system

BACKGROUND

Immunohematology reference laboratories provide red blood cell (RBC), platelet (PLT), and neutrophil typing to resolve complex cases, using serology and commercial DNA tests that define clinically important antigens. Broad-range exome sequencing panels that include blood group targets provide accurate blood group antigen predictions beyond those defined by serology and commercial typing systems and identify rare and novel variants. The aim of this study was to design and assess a panel for targeted exome sequencing of RBC, PLT, and neutrophil antigen-associated genes to provide a comprehensive profile in a single test, excluding unrelated gene targets.

STUDY DESIGN AND METHODS

An overlapping probe panel was designed for the coding regions of 64 genes and loci involved in gene expression. Sequencing was performed on 34 RBC and 17 PLT/neutrophil reference samples. Variant call outputs were analyzed using software to predict star allele diplotypes. Results were compared with serology and previous sequence genotyping data.

RESULTS

Average coverage exceeded 250×, with more than 94% of targets at Q30 quality or greater. Increased coverage revealed a variant in the Scianna system that was previously undetected. The software correctly predicted allele diplotypes for 99.5% of RBC blood groups tested and 100% of PLT and HNA antigens excepting HNA-2. Optimal throughput was 12 to 14 samples per run.

CONCLUSION

This single-test system demonstrates high coverage and quality, allowing for the detection of previously overlooked variants and increased sample throughput. This system has the potential to integrate genomic testing across laboratories within hematologic reference settings.

Enabling Technologies for Personalized and Precision Medicine

Individualizing patient treatment is a core objective of the medical field. Reaching this objective has been elusive owing to the complex set of factors contributing to both disease and health; many factors, from genes to proteins, remain unknown in their role in human physiology. Accurately diagnosing, monitoring, and treating disorders requires advances in biomarker discovery, the subsequent development of accurate signatures that correspond with dynamic disease states, as well as therapeutic interventions that can be continuously optimized and modulated for dose and drug selection. This work highlights key breakthroughs in the development of enabling technologies that further the goal of personalized and precision medicine, and remaining challenges that, when addressed, may forge unprecedented capabilities in realizing truly individualized patient care.