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Single cell multi-omics approaches in identifying driving cells and genes in pediatric MODS patients requiring ECMO support

Award Number: R00HD111575
ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 06/01/2026
PERIOD OF PERFORMANCE END DATE: 05/31/2029

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Single cell multi-omics approaches in identifying driving cells and genes in pediatric MODS patients requiring ECMO support - PROJECT SUMMARY (See instructions): This NIH R00 proposal seeks support for developing an independent research program to gain a deeper understanding of the cellular and molecular mechanisms associated with MODS deterioration, who may require advanced life support. My long-term goal is to develop innovative diagnostic and therapeutic methods for pediatric diseases in the intensive care unit (ICU), using cutting-edge single-cell multi-omics techniques and machine learning approaches. My previous research focused on identifying novel drugs, biomarkers, prognostic, and diagnostic markers for various diseases and cancers using big data approaches. However, MODS in pediatric patients with veno-arterial extracorporeal membrane oxygenation (ECMO) support has drawn my attention, as the survival rate for severe MODS patients with ECMO support is very low and there are no clinical or molecular biomarkers available to diagnose deterioration of MODS patients requiring ECMO support. To gain a deeper understanding of the cellular and molecular mechanisms associated with MODS deterioration, who may require advanced life support, I aim to utilize advanced single-cell multi-omics and machine learning approaches. My previous research using bulk RNA-seq analysis on a small sample size showed that dysregulation of the immune response and epigenetic variations are significant factors associated with MODS deterioration in patients requiring ECMO support. However, a more detailed analysis using advanced single-cell multi-omics and machine learning is needed. The objective of this award is to use cutting-edge single-cell multi-omics techniques to investigate the cellular heterogeneity and their dynamics, as well as their transcriptional regulatory elements in MODS and ECMO patients at two different time points. Furthermore, a machine learning approach along with bulk RNA-seq will be implemented to identify crucial cells and genes associated with MODS patients' deterioration who may require ECMO support. The successful completion of this research will expand my knowledge in single-cell multi-omics, statistics, machine learning approaches, immune responses, and pediatric diseases.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $248,999 )
2026	2026	LOYOLA UNIVERSITY OF CHICAGO	2160 S 1ST AVE	MAYWOOD	IL	60153	COOK	USA	Child Health and Human Development Extramural Research	000	3	7/14/2026	EXTENSION WITH OR WITHOUT FUNDS	$248,999
														Subtotal = $248,999

Grand Total All Awards = $248,999

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Single cell multi-omics approaches in identifying driving cells and genes in pediatric MODS patients requiring ECMO support

Award Number: R00HD111575

ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 06/01/2026

PERIOD OF PERFORMANCE END DATE: 05/31/2029

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