Clinical Impact, Diagnostic Performance, and Prognostic Implications of Plasma Metagenomic Next-Generation Sequencing in Solid Organ Transplant Recipients
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Introduction
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
In a retrospective cohort study, physicians reviewed SOT recipients with first-instance clinical plasma mNGS testing (Karius, Inc.) and determined microbiological diagnoses, clinical impact of results, diagnostic yield, and clinical outcome. mNGS results were compared to microbiological diagnoses. A HIPAA-compliant large language model (GPT-4) was used to analyze electronic medical record (EMR) data and predict risk of infection with atypical bacteria, invasive fungi, mycobacteria, or parasites (collectively: pre-specified organisms of presumed significance, POPS) and identify patients with positive-impact mNGS testing.
Results
Of 145 SOT recipients, 119 (82.1%) had positive tests, 42 (29.0%) had ≥ 1 POPS organism, and 27 (19.1%) had ≥ 1 organism causing positive clinical impact. Positive impact was highly correlated with POPS status, with 24 (88.9%) of 27 positive-impact organisms categorized as POPS (P<0.001). GPT-4 scores accurately identified patients with POPS diagnoses (AUC 0.86), and assigned higher scores to patients with positive-impact tests (P=0.001). mNGS testing had highest sensitivity for atypical bacteria (82.4% sensitivity) and lower sensitivity for Aspergillus spp (53.3% sensitivity). Detection of greater numbers of organisms by mNGS was associated with increased mortality (odds ratio 1.32 per organism detected).
Discussion
Plasma mNGS is a valuable clinical tool in SOT recipients. Positive clinical impact is associated with detection of atypical bacteria, fungi, mycobacteria, or parasites. GPT-4 analysis of EMR data identifies patients at risk of infection from these organisms and most likely to benefit from mNGS testing.
Summary
The optimal use of plasma mNGS in solid organ transplant recipients remains uncertain. We demonstrate that mNGS is most impactful when atypical bacteria, fungi, or parasites are detected, and create an artificial intelligence tool to identify patients with those infections.
