Translational Research Core
PI:   Steve Cummings, MD FACP
California Pacific Medical Center, San Francisco

The Translational Research Core (TRC) facilitates the development of drugs that will slow the aging process and/or improve healthy aging using leads provided principally by studies of the genetics of human aging and longevity. Once targets are identified, proposals are solicited from qualified laboratories and research groups to further test and develop targets. This may include screening libraries of molecules and drugs, and functional genomics. Drugs, natural products and small molecules identified in initial screening will then be re-screened in a progression of animal models to set the basis for pilot studies in human subjects. Current Longevity Consortium efforts are focused on the FOXO3 transcription factor but other potential targets are anticipated. Dan Evans, PhD leads the effort.

Contact Information:
Steve Cummings, MD, FACP
SCummings [AT]

Dan Evans, PhD, MPH
DEvans [AT]


Genomics Core
PI:          Pui Kwok, MD
Co-PI:    Ludmilla Pawlikowska, PhD
University of California, San Francisco

The Genomics Core supports the genomics needs of all Longevity Consortium Projects, utilizing a variety of cutting-edge genomics platforms, including massively high-throughput sequencing and genotyping. For the Miller Project, the Genomics Core is performing RNASeq to analyze the transcriptomes of 20+ bird species of varying lifespan in order to correlate gene expression patterns with aging and stress-resistance phenotypes. The resources and expertise of the Genomics Core are also available for Translational Opportunity Projects.

Contact Information:
Pui Kwok, MD
pui.kwok [AT]

Ludmilla Pawlikowska, PhD
pawlikowskal [AT]


Biostatistics and Bioinformatics Core
PI: Nik Schork, PhD
J. Craig Venter Institute

The Bioinformatics and Biostatistics Core (BBC) of the Longevity Consortium (LC) focus is on four areas of research:

  1. The development of sequencing assay-based bioinformatics tools for, e.g., genome assembly, RNA-seq analysis, and variant annotation;
  2. The development of data analysis methods for cross-species phenotypic variation studies and phylogenetic signal detection;
  3. The development of novel association analysis methods and,
  4. The development of better drug screening designs and in silico drug effect characterization tools.

Contact Information:
Nik Schork, PhD
NSchork [AT]