Clinical Impact, Diagnostic Performance, and Prognostic Implications of Plasma Metagenomic Next-Generation Sequencing in Solid Organ Transplant Recipients
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Background
Plasma metagenomic next-generation sequencing (mNGS) may detect pathogens in solid organ transplant (SOT) recipients, but optimal patient selection and result interpretation remain uncertain.
Methods
We studied 145 SOT recipients who received Karius plasma mNGS testing between 2017-2025. Retrospective multi-physician adjudication assessed diagnostic accuracy, clinical impact, and outcomes. We examined whether detection of atypical bacteria, invasive fungi, adenovirus/parvovirus and parasites, termed pre-specified organisms of presumed significance (POPS), predicted positive clinical impact. We applied a GPT-4o large language model (LLM) to limited electronic medical record (EMR) data to identify patients with POPS diagnoses and positive-impact testing.
Results
Of 145 SOT recipients, 119 (82.1%) had positive tests, and 42 (29.0%) had ≥1 POPS organism detected. Twenty-seven of 133 diagnoses (20.3%) were made by mNGS first or mNGS only. Diagnostic performance versus a gold standard of all microbiologic testing varied by organism, ranging from 100% sensitivity and specificity ( Bartonella, Nocardia ) to 60.0% and 53.3% sensitivity for Coccidioides and Aspergillus, respectively. Of 141 patients with interpretable test impact, 27 (19.1%) had positive clinical impact, associated with POPS detection (P<0.001). The LLM identified patients with POPS diagnoses (area under the receiver operating characteristic curve [AUC] 0.86), and patients with positive-impact testing (AUC 0.71).
Conclusions
Plasma mNGS can aid diagnosis and management of infections in SOT recipients, but negative tests do not exclude invasive fungal disease. Positive clinical impact is greatest when POPS organisms are detected, and patients at risk of POPS diagnoses may be identified by an LLM given limited EMR data.
Summary
Optimal use of plasma mNGS in solid organ transplant recipients remains uncertain. We find mNGS is most impactful when atypical bacteria, fungi, key viruses, or parasites are detected, and develop a method to identify patients at risk of those infections.
