Viral co-infection, autoimmunity, and CSF HIV antibody profiles in HIV central nervous system escape.

Antiretroviral therapy (ART) suppresses plasma and cerebrospinal fluid (CSF) HIV replication. Neurosymptomatic (NS) CSF escape is a rare exception in which CNS HIV replication occurs in the setting of neurologic impairment. The origins of NS escape are not fully understood. We performed a case-control study of asymptomatic (AS) escape and NS escape subjects with HIV-negative subjects as controls in which we investigated differential immunoreactivity to self-antigens in the CSF of NS escape by employing neuroanatomic CSF immunostaining and massively multiplexed self-antigen serology (PhIP-Seq). Additionally, we utilized pan-viral serology (VirScan) to deeply profile the CSF anti-viral antibody response and metagenomic next-generation sequencing (mNGS) for pathogen detection. We detected Epstein-Barr virus (EBV) DNA more frequently in the CSF of NS escape subjects than in AS escape subjects. Based on immunostaining and PhIP-Seq, there was evidence for increased immunoreactivity against self-antigens in NS escape CSF. Finally, VirScan revealed several immunodominant epitopes that map to the HIV envelope and gag proteins in the CSF of AS and NS escape subjects. Whether these additional inflammatory markers are byproducts of an HIV-driven process or whether they independently contribute to the neuropathogenesis of NS escape will require further study.

Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics.

The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.