Biology subjects

Thompson, K. L.

Publications and source records attributed to Thompson, K. L..

4 recordsLinked to original sources

bioRxiv2026

Identification and characterization of a human antibody profile inversely associated with adverse cardiovascular events

Objective: The immune response is linked to the progression of atherosclerotic cardiovascular disease (CVD). We sought to characterize a predictive cardiovascular antibody biomarker using two independent cohorts. Approach and Results: A human IgG profile serendipitously identified by ELISA was quantified in a well characterized cohort of 359 patients with a history of coronary artery disease (CAD) who experienced a total of 71 incident adverse CVD events (death, myocardial infarction, and stroke) over a median 4.1-year follow-up. Using Cox proportional hazard regression analysis, low biomarker levels were an independent predictor of adverse cardiovascular outcomes after adjustment for age, sex, diabetes mellitus, estimated glomerular filtration rate, presence of obstructive CAD, heart failure, total cholesterol, and high-density lipoprotein (HDL) cholesterol (adjusted hazard ratio of 1.90 [95% CI: 1.03 to 3.49; p=0.038] between lowest and highest tertiles). Validation was then performed in a larger secondary cohort using 4356 baseline samples from the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of cardiovascular outcomes resulting in adjusted odds ratio of 50.5 per unit decrease in log-transformed biomarker [95% CI: 2.4 to 2773.1; p=0.030] over one year by logistic regression analysis. Conclusions: Low levels of human IgG antibodies targeting Bovidae IgG are independently associated with increased incidence of CVD events in patients with or without a history of CAD, indicating the potential clinical predictive power of this antibody profile as an inverse biomarker for CVD.

immunology↗

bioRxiv2024

The vulnerability of overwintering insects to loss of the subnivium

Winter climate change threatens the subnivium (i.e., the microhabitat that exists between the snowpack and the ground), and the community of species that depends on it for overwintering survival. One group of species that will likely exhibit an array of responses to subnivium loss are overwintering insects because they vary in their cold tolerance strategies and lower thermal limits. For an assemblage of eight insect species that range in their cold tolerance strategies and include both pollinators and pests, we investigated species-specific vulnerabilities to shifting subnivium conditions by applying information on each species supercooling point to spatially- and temporally-explicit models of minimum subnivium temperatures for three warming scenarios in the Great Lakes region in the United States: current conditions (i.e., control), +3{degrees}C, and +5{degrees}C. Although species varied in their vulnerabilities, our predictions indicated that exposure to lethal temperatures generally decreased under warming of 3{degrees}C, but increased under warming of 5{degrees}C, indicating that once enough warming happens, a tipping point is reached. We also found that freeze-tolerant species (i.e., species that can survive at temperatures below their supercooling point) possess a more cryptic vulnerability to winter climate change because sustained below-freezing temperatures were sufficient to induce vulnerability (i.e., predicted mortality), even when temperatures were above the supercooling point. This work provides a better understanding of the vulnerability of different insect species to winter climate change, which is critical because overwintering survival and the fitness consequences incurred during overwintering likely represent important bottlenecks for the population dynamics of subnivium-dependent species.

ecology↗

bioRxiv2023

The interacting effects of climate and land-use/land-cover changes on ecological communities

Human activities continue to create land-use/land-cover (LULC) change across the Earths surface, and together with climate change, are major drivers of changes in biodiversity through time. However, the impacts of these spatiotemporally variable drivers on biodiversity change can be complex. We examined the effects of interactions between climate and LULC change on bird communities across the continental United States over nearly three decades. We analyzed temperature and precipitation data alongside data on tree-canopy, cropland, urban, and surface-water cover to understand how climate/LULC-change interactions influence species richness and abundance. Our results revealed stable or increasing trends in species richness, but a decline in overall abundance primarily from common species and a consequent increase in aspects of evenness of communities. We found that areas experiencing warming and drying climates exhibited increased species richness and slower declines in abundance. However, impacts of LULC change had contrasting effects on richness and abundance. Areas that experienced increasing tree-canopy cover over time had increasing trends in species richness, but exacerbated declines in abundance. On the other hand, areas with increasing cropland had moderated abundance declines, but more declining trends in richness. Finally, we found that the effects of climate/LULC-change interactions varied across the range of each pressure. While some interactions support a dominant role of climate change in structuring communities, others indicate that LULC change can mitigate or exacerbate the impact of climate change on biodiversity. Overall, our results highlight the importance of considering the direction and magnitude of each driver when assessing how climate and LULC interactions shape ecological communities.

ecology↗

bioRxiv2017

Summarizing Performance for Genome Scale Measurement of miRNA: Reference Samples and Metrics

BackgroundThe potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls.\n\nResultsThree pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes.\n\nConclusionsThe set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.

genomics↗