# Clinical value of macrogenome next-generation sequencing on infections

**Authors:** Benfa Han, Xiaoli Zhang, Xiuxi Li, Mei Chen, Yanlin Ma, Yunxia Zhang, Song Huo

PMC · DOI: 10.1515/biol-2022-0938 · Open Life Sciences · 2024-09-09

## TL;DR

This study shows that macrogenome next-generation sequencing improves the detection of intracranial infections after neurosurgery compared to traditional methods.

## Contribution

The study demonstrates the superior clinical value of mNGS in diagnosing intracranial infections compared to traditional pathogen detection methods.

## Key findings

- mNGS had a positivity rate of 71.67% compared to 28.33% with traditional methods.
- mNGS showed a sensitivity of 83.7%, significantly higher than 34.88% with traditional methods.
- mNGS identified multiple microorganisms like Cryptococcus and Staphylococcus associated with intracranial infections.

## Abstract

Intracranial infection (ICI) is a frequent and serious complication after neurosurgery. Macrogenome next-generation sequencing (mNGS) technology can provide reference for clinical diagnosis and treatment of ICI. This work aimed to explore the application value of mNGS technology in analyzing the clinical characteristics of human immunodeficiency virus (HIV) infection and ICI after neurosurgery. A total of 60 patients with ICI were enrolled as the research objects, all patients underwent routine cerebrospinal fluid analysis and traditional pathogen detection, followed by mNGS genome analysis. Using clinical diagnosis of ICI as the gold standard, the sensitivity, specificity, positive predictive value, and negative predictive value for both detection methods were calculated. Receiver operating characteristic curves were constructed to assess the area under the curve (AUC) for evaluating the clinical value of mNGS in suspected intracranial infectious pathogen diagnosis. Results showed a positivity rate of 71.67% (43 cases) with mNGS compared to 28.33% (17 cases) with traditional pathogen detection methods, demonstrating a significant difference (P < 0.05). The sensitivity of mNGS for detecting ICIs was 83.7%, significantly higher than the 34.88% observed with traditional methods (P < 0.05). The pathogen detection rate of mNGS was higher than traditional methods (P = 0.002), with an AUC of 0.856 (95% CI: 0.638–0.967), significantly greater than the AUC of 0.572 (95% CI: 0.350–0.792) for traditional methods (P < 0.05). mNGS successfully identified microorganisms such as Cryptococcus, Propionibacterium, Staphylococcus, Corynebacterium, Micrococcus, and Candida associated with ICIs. These findings underscore the clinical applicability of mNGS technology in analyzing the characteristics of HIV infection and ICI post-neurosurgical procedures. This technology enables more accurate diagnosis and treatment of ICIs, providing valuable insights for developing effective therapeutic strategies.

## Linked entities

- **Species:** Cryptococcus (taxon 5206), Propionibacterium (taxon 1743), Staphylococcus (taxon 1279), Corynebacterium (taxon 1716), Micrococcus (taxon 1269), Candida (taxon 5475)

## Full-text entities

- **Diseases:** ICI (MESH:D007239), HIV infection (MESH:D015658), intracranial infectious pathogen (MESH:D003141)
- **Species:** Corynebacterium (genus) [taxon 1716], Micrococcus (genus) [taxon 1269], Candida [taxon 1535326], Staphylococcus (genus) [taxon 1279], Propionibacterium (genus) [taxon 1743], Homo sapiens (human, species) [taxon 9606], Cryptococcus (genus) [taxon 79213]

## Full text

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## Figures

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Source: https://tomesphere.com/paper/PMC11406221