TY - UNPB
T1 - Multi-Omic Factor Analysis uncovers immunological signatures with pathophysiologic and clinical implications in coronary syndromes
AU - Pekayvaz, Kami
AU - Losert, Corinna
AU - Knottenberg, Viktoria
AU - van Blokland, Irene V.
AU - Oelen, Roy
AU - Groot, Hilde E.
AU - Benjamins, Jan Walter
AU - Brambs, Sophia
AU - Kaiser, Rainer
AU - Eivers, Luke
AU - Polewka, Vivien
AU - Escaig, Raphael
AU - Joppich, Markus
AU - Janjic, Aleksandar
AU - Popp, Oliver
AU - Petzold, Tobias
AU - Zimmer, Ralf
AU - Enard, Wolfgang
AU - Saar, Kathrin
AU - Mertins, Philipp
AU - Huebner, Norbert
AU - van der Harst, Pim
AU - Franke, Lude H.
AU - van der Wijst, Monique G. P.
AU - Massberg, Steffen
AU - Heinig, Matthias
AU - Nicolai, Leo
AU - Stark, Konstantin
PY - 2023/5/3
Y1 - 2023/5/3
N2 - Acute and chronic coronary syndromes (ACS and CCS) are leading causes of mortality. Inflammation is considered to be a key pathogenic driver, but immune states in humans and their clinical implications remain poorly understood. We hypothesized that Multi-Omic blood analysis combined with Multi-Omic Factor Analysis (MOFA) might uncover hidden sources of variance providing pathophysiological insights linked to clinical needs. Here, we compile a single cell longitudinal dataset of the circulating immune states in ACS & CCS (13x103 clinical & Multi-Omic variables, n=117 subjects, n=838 analyzed samples) from two independent cohorts. Using MOFA, we identify multilayered factors, characterized by distinct classical monocyte and CD4+ & CD8+ T cell states that explain a large proportion of inter-patient variance. Three factors either reflect disease course or predict outcome in coronary syndromes. The diagnostic performance of these factors reaches beyond established biomarkers highlighting the potential use of MOFA as a novel tool for multilayered patient risk stratification.
AB - Acute and chronic coronary syndromes (ACS and CCS) are leading causes of mortality. Inflammation is considered to be a key pathogenic driver, but immune states in humans and their clinical implications remain poorly understood. We hypothesized that Multi-Omic blood analysis combined with Multi-Omic Factor Analysis (MOFA) might uncover hidden sources of variance providing pathophysiological insights linked to clinical needs. Here, we compile a single cell longitudinal dataset of the circulating immune states in ACS & CCS (13x103 clinical & Multi-Omic variables, n=117 subjects, n=838 analyzed samples) from two independent cohorts. Using MOFA, we identify multilayered factors, characterized by distinct classical monocyte and CD4+ & CD8+ T cell states that explain a large proportion of inter-patient variance. Three factors either reflect disease course or predict outcome in coronary syndromes. The diagnostic performance of these factors reaches beyond established biomarkers highlighting the potential use of MOFA as a novel tool for multilayered patient risk stratification.
U2 - 10.1101/2023.05.02.23289392
DO - 10.1101/2023.05.02.23289392
M3 - Preprint
BT - Multi-Omic Factor Analysis uncovers immunological signatures with pathophysiologic and clinical implications in coronary syndromes
PB - MedRxiv
ER -