Biology subjects

Post, W. S.

Publications and source records attributed to Post, W. S..

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↗

bioRxiv2021

Classification of Free-Living Body Posture with ECG Patch Accelerometers: Application to the Multicenter AIDS Cohort Study

SO_SCPLOWUMMARYC_SCPLOWAs health studies increasingly monitor free-living heart performance via ECG patches with accelerometers, researchers will seek to investigate cardio-electrical responses to physical activity and sedentary behavior, increasing demand for fast, scalable methods to process accelerometer data. We provide the first published analysis of tri-axial accelerometry data from Zio XT patch and introduce an extension of posture classification algorithms for use with ECG patches worn in the free-living environment. Our novel extensions to posture classification include (1) estimation of an upright posture for each individual without the reference measurements used by existing posture classification algorithms; (2) correction for device removal and re-positioning using novel spherical change-point detection; and (3) classification of upright and recumbent periods using a clustering and voting process rather than a simple inclination threshold used in other algorithms. Methods were built using data from 14 participants from the Multicenter AIDS Cohort Study (MACS), and applied to 1, 250 MACS participants. As no posture labels exist in the free-living environment, we evaluate the algorithm against labelled data from the Towson Accelerometer Study and against data labelled by hand from the MACS study.

bioengineering↗

bioRxiv2018

Efficient variant set mixed model association tests for continuous and binary traits in large-scale whole genome sequencing studies

With advances in Whole Genome Sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and Sequence Kernel Association Test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally-efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-Set Mixed Model Association Tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institutes Trans-Omics for Precision Medicine (TOPMed) program. SMMAT tests share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be only fit once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMAT tests correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

genetics↗