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Phongpreecha, T.

Publications and source records attributed to Phongpreecha, T..

3 recordsLinked to original sources

Single-Cell Peripheral Immunoprofiling of Lewy Body Disease in a Multi-site Cohort

Studies implicated peripheral organs involvement in the development of Lewy body disease (LBD), a spectrum of neurodegenerative diagnoses that include Parkinsons Disease (PD) without or with dementia (PDD) and dementia with Lewy bodies (DLB). This study characterized peripheral immune responses unique to LBD at single-cell resolution. Peripheral mononuclear cell (PBMC) samples were collected from sites across the U.S. The diagnosis groups comprise healthy controls (HC, n=164), LBD (n=132), Alzheimers disease dementia (ADD, n=98), other neurodegenerative disease controls (NDC, n=21), and immune disease controls (IDC, n=14). PBMCs were activated with three stimulants, stained by surface and intracellular signal markers, and analyzed by flow cytometry, generating 1,184 immune features. Our model classified LBD from HC with an AUROC of 0.90{+/-}0.06. The same model distinguished LBD from ADD, NDC, IDC, or other common conditions associated with LBD. Model predictions were driven by pPLC{gamma}2, p38, and pSTAT5 signals from specific cell populations and activations.

neuroscience↗

Single-synapse analyses of Alzheimers disease implicate pathologic tau, DJ1, CD47, and ApoE

Synaptic molecular characterization is limited for Alzheimers disease (AD). We used mass cytometry to quantify 38 probes in approximately 17 million single synaptic events from human brains without pathologic change or with pure AD or Lewy body disease (LBD), non-human primates (NHP), and PS/APP mice. Synaptic molecular integrity in humans and NHP was similar. Although not detected in human synapses, A{beta} was in PS/APP mice synaptic events. Clustering and pattern identification of human synapses showed expected disease-specific differences, like increased hippocampal pathologic tau in AD and reduced caudate dopamine transporter in LBD, and revealed novel findings including increased hippocampal CD47 and lowered DJ1 in AD and higher ApoE in AD dementia. Our results were independently supported by multiplex ion beam imaging of intact tissue.

neuroscience↗

Integration of Mechanistic Immunological Knowledge into a Machine Learning Pipeline Increases Predictive Power

The dense network of interconnected cellular signaling responses quantifiable in peripheral immune cells provide a wealth of actionable immunological insights. While high-throughput single-cell profiling techniques, including polychromatic flow and mass cytometry, have matured to a point that enables detailed immune profiling of patients in numerous clinical settings, limited cohort size together with the high dimensionality of data increases the possibility of false positive discoveries and model overfitting. We introduce a machine learning platform, the immunological Elastic-Net (iEN), which incorporates immunological knowledge directly into the predictive models. Importantly, the algorithm maintains the exploratory nature of the high-dimensional dataset, allowing for the inclusion of immune features with strong predictive power even if not consistent with prior knowledge. In three independent studies our method demonstrates improved predictive power for clinically-relevant outcomes from mass cytometry data generated from whole blood, as well as a large simulated dataset.

bioinformatics↗