Kechris Lab

RESEARCH

Our group has several focus areas:

  • Analyzing transcription factor binding and miRNA data to study the regulation of transcription and post-transcriptional processing,
  • Examining the genetic and epigenetic factors controlling gene expression,
  • Exploring the metabolome and
  • Integrating multiple omics data.

We also collaborate with investigators studying chronic obstructive pulmonary disease in the COPDGene genetic epidemiology study, substance use disorders using animal models, and early life determinants of diabetes and obesity in children.

ACTIVE GRANTS

Definition, Etiology, Function: INtegration to Enhance Type 2 Diabetes (DEFINE T2D) Consortium Biostatistics Research Center (BRC)

Role: Multi-PI (Kechris, Lange, Perng, Yang); NIH/NIDDK U01 DK140738 2024-2029

The BRC will work with the DEFINE T2D Cohort Sites and NIDDK to employ multi-level, multi-dimensional approaches to characterize heterogeneity in type 2 diabetes. Establishment of the BRC and completion of the proposed goals will result in a broadly applicable framework for identifying type 2 diabetes subtypes and forge new research opportunities for effective precision interventions to prevent, reroute the clinical course, and optimize long- term prognosis of type 2 diabetes in diverse populations.

Multi-Omics and NETwork Analysis Summer Workshop (MONET)

Role: PI (Kechris); NIH/NHBLI R25 HG013296 2024-2029

The Multi- Omics and NETwork analysis workshop (MONET) will provide a 7-day immersive experience for ~25 researchers each summer 2024-2028 to learn about multi-omics analysis and the application of network methods through ~50 hours of lectures, discussion sessions, computational labs, tours and team exercises.

Multi-Omic Networks Associated with COPD progression in TOPMed Cohorts

Role: Multi-PI (Kechris, Banaei-Kashani, Bowler, Lange); NIH/NHLBI R01 HL152735 2020-2025 (NCE)

To help identify why only some smokers develop COPD, this proposal will integrate recently collected extensive molecular multi-omic profiles from three NHLBI cohorts to discover molecular networks that are important in both COPD diagnosis and progression.