Biology subjects

Landay, A.

Publications and source records attributed to Landay, A..

3 recordsLinked to original sources

bioRxiv2023

Plasma Glycomic Markers of Accelerated Biological Aging During Chronic HIV Infection

People with HIV (PWH) experience an increased vulnerability to premature aging and inflammation-associated comorbidities, even when HIV replication is suppressed by antiretroviral therapy (ART). However, the factors that contribute to or are associated with this vulnerability remain uncertain. In the general population, alterations in the glycomes of circulating IgGs trigger inflammation and precede the onset of aging-associated diseases. Here, we investigate the IgG glycomes of cross-sectional and longitudinal samples from 1,216 women and men, both living with virally suppressed HIV and those without HIV. Our glycan-based machine learning models indicate that living with chronic HIV significantly accelerates the accumulation of pro-aging-associated glycomic alterations. Consistently, PWH exhibit heightened expression of senescence-associated glycan-degrading enzymes compared to their controls. These glycomic alterations correlate with elevated markers of inflammatory aging and the severity of comorbidities, potentially preceding the development of such comorbidities. Mechanistically, HIV-specific antibodies glycoengineered with these alterations exhibit reduced anti-HIV IgG-mediated innate immune functions. These findings hold significant potential for the development of glycomic-based biomarkers and tools to identify and prevent premature aging and comorbidities in people living with chronic viral infections.

microbiology↗

bioRxiv2022

Markers of Fungal Translocation Are Elevated During Post-Acute Sequelae of SARS-CoV-2 Infection and Induce NF-κB Triggered Inflammation.

Long COVID, a type of Post-Acute Sequelae of SARS CoV-2 infection (PASC), has been associated with sustained elevated levels of immune activation and inflammation. However, the pathophysiological mechanisms that drive this inflammation remain unknown. Inflammation during acute Coronavirus Disease 2019 (COVID-19) could be exacerbated by microbial translocation (from the gut and/or lung) to the blood. Whether microbial translocation contributes to inflammation during PASC is unknown. We found higher levels of fungal translocation - measured as {beta}-glucan, a fungal cell wall polysaccharide - in the plasma of individuals experiencing PASC compared to those without PASC or SARS-CoV-2 negative controls. The higher {beta}-glucan correlated with higher levels of markers of inflammation and elevated levels of host metabolites involved in activating N-Methyl-D-aspartate receptors (such as metabolites within the tryptophan catabolism pathway) with established neuro-toxic properties. Mechanistically, {beta}-glucan can directly induce inflammation by binding to myeloid cells (via the Dectin-1 receptor) and activating Syk/NF-{kappa}B signaling. Using an in vitro Dectin-1/NF-{kappa}B reporter model, we found that plasma from individuals experiencing PASC induced higher NF-{kappa}B signaling compared to plasma from SARS-CoV-2 negative controls. This higher NF-{kappa}B signaling was abrogated by the Syk inhibitor Piceatannol. These data suggest a potential targetable mechanism linking fungal translocation and inflammation during PASC.

microbiology↗

bioRxiv2020

Non-Invasive Plasma Glycomic and Metabolic Biomarkers of Post-treatment Control of HIV

Non-invasive biomarkers that predict HIV remission after antiretroviral therapy (ART) interruption are urgently needed. Such biomarkers can improve the safety of analytic treatment interruption (ATI) and provide mechanistic insights into the pathways involved in post-ART HIV control. We identified plasma glycomic and metabolic signatures of time-to-viral-rebound and probability-of-viral-rebound using samples from two independent cohorts. These samples include a large number of post-treatment controllers, a rare population demonstrating sustained virologic suppression after ART-cessation. The signatures remained significant after adjusting for key demographic and clinical confounders. We also confirmed a mechanistic link between biomarkers and HIV latency reactivation and myeloid inflammation in vitro. Finally, machine learning algorithms selected sets of biomarkers that predict time-to-viral-rebound with 74-76% capacity and probability-of-viral-rebound with 97.5% capacity. In summary, we fill a major gap in HIV cure research by identifying non-invasive biomarkers, with potential functional significance, that predict duration and probability of viral remission after treatment interruption.

microbiology↗