The effect of air-free administration of intravenous drugs on microemboli during cardiopulmonary bypass.

OBJECTIVE: During cardiopulmonary bypass (CPB), gaseous microemboli (GME) that originate from the extracorporeal circuit are released into the arterial blood stream of the patient. Gaseous microemboli may contribute to adverse outcome after cardiac surgery with CPB. Possibly, air may be collected in the right atrium during induction of anesthesia and released during CPB start. The aim of this study was to assess if the GME load entering the venous line of the CPB circuit could be reduced by training of anesthesia personal in avoiding air introduction during administration of intravenous medication. METHODS: In 94 patients undergoing coronary artery bypass grafting with CPB, GME number and volume were measured intraoperatively with a bubble counter (BCC300). The quantity and the relationship between GME number and volume in the venous and arterial line were determined in 2 periods before and after education of the anesthesiologists and nurses. RESULTS: In the venous line no significant differences were observed between numbers and volumes of GME between groups. Comparing patients with low versus high GME load, showed significantly more patients from the intervention group in the low GME-load group, namely 29 versus 18. Administration of medication by anesthesia was confirmed as a clear cause of GME/air-introduction into the venous circulation. Scavenging properties of the CPB circuit including the oxygenator showed a 99.9% reduction of GME. CONCLUSIONS: A wide spread of GME generation during perfusion was present with no difference in generation of GME between groups. Lower GME load observed in patients (intervention group) and examples of air introduction during drug administration suggest that air introduced by anesthesia contributes to the GME load during CPB. Scavenging properties of the CPB circuit contribute very much to patient safety regarding reduction of venous air. Awareness and education create the possibilities for further reduction of GME during cardiopulmonary bypass.

Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples.

Mobile element insertions (MEIs) are a known cause of genetic disease but have been underexplored due to technical limitations of genetic testing methods. Various bioinformatic tools have been developed to identify MEIs in Next Generation Sequencing data. However, most tools have been developed specifically for genome sequencing (GS) data rather than exome sequencing (ES) data, which remains more widely used for routine diagnostic testing. In this study, we benchmarked six MEI detection tools (ERVcaller, MELT, Mobster, SCRAMble, TEMP2 and xTea) on ES data and on GS data from publicly available genomic samples (HG002, NA12878). For all the tools we evaluated sensitivity and precision of different filtering strategies. Results show that there were substantial differences in tool performance between ES and GS data. MELT performed best with ES data and its combination with SCRAMble increased substantially the detection rate of MEIs. By applying both tools to 10,890 ES samples from Solve-RD and 52,624 samples from Radboudumc we were able to diagnose 10 patients who had remained undiagnosed by conventional ES analysis until now. Our study shows that MELT and SCRAMble can be used reliably to identify clinically relevant MEIs in ES data. This may lead to an additional diagnosis for 1 in 3000 to 4000 patients in routine clinical ES.

Genome sequencing as a generic diagnostic strategy for rare disease.

BACKGROUND: To diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease. METHODS: We performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels < 50 bp), large variants (copy number variants and short tandem repeats) and other variants (structural variants and aneuploidies). Variant calling format files were queried per variant, from which workflow-specific true positive rates (TPRs) for detection were determined. A TPR of ≥ 98% was considered the threshold for transition to GS. A GS-first scenario was generated for our laboratory, using diagnostic efficacy and predicted false negative as primary outcome measures. As input, we modeled the diagnostic path for all 24,570 individuals referred in 2022, combining the clinical referral, the transition of the underlying workflow(s) to GS, and the variant type(s) to be detected. RESULTS: Overall, 95% (1206/1271) of variants were detected. Detection rates differed per variant category: small variants in 96% (826/860), large variants in 93% (341/366), and other variants in 87% (39/45). TPRs varied between workflows (79-100%), with 7/10 being replaceable by GS. Models for our laboratory indicate that a GS-first strategy would be feasible for 84.9% of clinical referrals (750/883), translating to 71% of all individuals (17,444/24,570) receiving GS as their primary test. An estimated false negative rate of 0.3% could be expected. CONCLUSIONS: GS can capture clinically relevant germline variants in a 'GS-first strategy' for the majority of clinical indications in a genetics diagnostic lab.

Unravelling undiagnosed rare disease cases by HiFi long-read genome sequencing.

Solve-RD is a pan-European rare disease (RD) research program that aims to identify disease-causing genetic variants in previously undiagnosed RD families. We utilised 10-fold coverage HiFi long-read sequencing (LRS) for detecting causative structural variants (SVs), single nucleotide variants (SNVs), insertion-deletions (InDels), and short tandem repeat (STR) expansions in extensively studied RD families without clear molecular diagnoses. Our cohort includes 293 individuals from 114 genetically undiagnosed RD families selected by European Rare Disease Network (ERN) experts. Of these, 21 families were affected by so-called 'unsolvable' syndromes for which genetic causes remain unknown, and 93 families with at least one individual affected by a rare neurological, neuromuscular, or epilepsy disorder without genetic diagnosis despite extensive prior testing. Clinical interpretation and orthogonal validation of variants in known disease genes yielded thirteen novel genetic diagnoses due to de novo and rare inherited SNVs, InDels, SVs, and STR expansions. In an additional four families, we identified a candidate disease-causing SV affecting several genes including an MCF2 / FGF13 fusion and PSMA3 deletion. However, no common genetic cause was identified in any of the 'unsolvable' syndromes. Taken together, we found (likely) disease-causing genetic variants in 13.0% of previously unsolved families and additional candidate disease-causing SVs in another 4.3% of these families. In conclusion, our results demonstrate the added value of HiFi long-read genome sequencing in undiagnosed rare diseases.

The performance of genome sequencing as a first-tier test for neurodevelopmental disorders.

Genome sequencing (GS) can identify novel diagnoses for patients who remain undiagnosed after routine diagnostic procedures. We tested whether GS is a better first-tier genetic diagnostic test than current standard of care (SOC) by assessing the technical and clinical validity of GS for patients with neurodevelopmental disorders (NDD). We performed both GS and exome sequencing in 150 consecutive NDD patient-parent trios. The primary outcome was diagnostic yield, calculated from disease-causing variants affecting exonic sequence of known NDD genes. GS (30%, n = 45) and SOC (28.7%, n = 43) had similar diagnostic yield. All 43 conclusive diagnoses obtained with SOC testing were also identified by GS. SOC, however, required integration of multiple test results to obtain these diagnoses. GS yielded two more conclusive diagnoses, and four more possible diagnoses than ES-based SOC (35 vs. 31). Interestingly, these six variants detected only by GS were copy number variants (CNVs). Our data demonstrate the technical and clinical validity of GS to serve as routine first-tier genetic test for patients with NDD. Although the additional diagnostic yield from GS is limited, GS comprehensively identified all variants in a single experiment, suggesting that GS constitutes a more efficient genetic diagnostic workflow.

Diagnostic analysis of the highly complex OPN1LW/OPN1MW gene cluster using long-read sequencing and MLPA.

Pathogenic variants in the OPN1LW/OPN1MW gene cluster are causal for a range of mild to severe visual impairments with color deficiencies. The widely utilized short-read next-generation sequencing (NGS) is inappropriate for the analysis of the OPN1LW/OPN1MW gene cluster and many patients with pathogenic variants stay underdiagnosed. A diagnostic genetic assay was developed for the OPN1LW/OPN1MW gene cluster, consisting of copy number analysis via multiplex ligation-dependent probe amplification and sequence analysis via long-read circular consensus sequencing. Performance was determined on 50 clinical samples referred for genetic confirmation of the clinical diagnosis (n = 43) or carrier status analysis (n = 7). A broad range of pathogenic haplotypes were detected, including deletions, hybrid genes, single variants and combinations of variants. The developed genetic assay for the OPN1LW/OPN1MW gene cluster is a diagnostic test that can detect both structural and nucleotide variants with a straightforward analysis, improving diagnostic care of patients with visual impairment.

Long-read technologies identify a hidden inverted duplication in a family with choroideremia.

The lack of molecular diagnoses in rare genetic diseases can be explained by limitations of current standard genomic technologies. Upcoming long-read techniques have complementary strengths to overcome these limitations, with a particular strength in identifying structural variants. By using optical genome mapping and long-read sequencing, we aimed to identify the pathogenic variant in a large family with X-linked choroideremia. In this family, aberrant splicing of exon 12 of the choroideremia gene CHM was detected in 2003, but the underlying genomic defect remained elusive. Optical genome mapping and long-read sequencing approaches now revealed an intragenic 1,752 bp inverted duplication including exon 12 and surrounding regions, located downstream of the wild-type copy of exon 12. Both breakpoint junctions were confirmed with Sanger sequencing and segregate with the X-linked inheritance in the family. The breakpoint junctions displayed sequence microhomology suggestive for an erroneous replication mechanism as the origin of the structural variant. The inverted duplication is predicted to result in a hairpin formation of the pre-mRNA with the wild-type exon 12, leading to exon skipping in the mature mRNA. The identified inverted duplication is deemed the hidden pathogenic cause of disease in this family. Our study shows that optical genome mapping and long-read sequencing have significant potential for the identification of (hidden) structural variants in rare genetic diseases.