Atul Butte's slides from Medicine X at Stanford September 30, 2012

3. Total 1 million microarrays available
ncbi.nlm.nih.gov
www.ebi.ac.uk

8. Type 2 Diabetes Mellitus
• Affects 20 million in US, 170 million world-wide
• Leading cause of kidney failure, blindness, amputation
• Major risk factor for heart disease, stroke, birth defects
• 12% of all US health-care dollars
• Prevalence in children born after the year 2000 expected
to reach 30%
• Many drugs available to boost insulin secretion,
improve insulin response, lower glucagon secretion
• New drugs still needed and used: DPP-4 inhibitors (2008)

12. Percent of genes
Intersect 130 experiments
Number of positive experiments (out of 130)

13. Percent of genes
Intersect 130 experiments
Most of the 25000 genes in the
genome are positive in very few
diabetes experiments
Number of positive experiments (out of 130)

14. Intersect 130 experiments
Our best known 186 genes are positive
in more experiments!
TCF7L2
Percent of genes
PPARG
LEPR
Number of positive experiments (out of 130)

15. Percent of genes
Intersect 130 experiments
A
Number of positive experiments (out of 130)

16. Gene A is expressed in mouse fat tissue
Gene A is higher in high fat diet
Gene A

17. Gene A knockout mouse has
fewer inflammatory cells in the fat
• Stain for inflammatory cells (macrophages)

18. Humans have inflammatory cells in their fat too,
with Gene A!
• Paraffin-embedded omental fat tissue from an
obese 57 year woman, BMI 36.9 kg/m2

19. Humans even have Gene A in the blood!
It correlates with our average blood sugar (HbA1c)

20. Therapeutic antibody against Gene A 
reduces sugar in mice!

21. • Gene A is CD44 (Hyaluronic Acid Receptor)
• Anti-CD44 in development for multiple cancers
• CD44 is a complicated receptor
Kodama K, Horikoshi M, ..., Maeda S, Kadowaki T,
Butte AJ. PNAS, 2012.

22. Four Lessons Learned
• Sufficient data already exists to impact medicine
– Diagnostics and drugs from public big data
– More data is better, but we see no reason to wait
– Data over dogma
– “Retroactive crowdsourcing”
• Public molecular data is extremely high quality
– Should never wait for perfect data, experiment, conditions
• Sticks seem to work better than carrots for sharing
– Continue exponential growth, more transparency
• Need to train students to initiate science with data
– High school  higher education  career changers

23. Collaborators
• Keiichi Kodama
• Rong Chen, Alex Morgan, Marina Sirota
• Takashi Kadowaki, Momoko Horikoshi, Kazuo Hara,
Hiroshi Ohtsu / University of Tokyo
• Kyoko Toda, Satoru Yamada, Junichiro Irie /
Kitasato University and Hospital
• Junichiro Irie / Keio University
• Shiro Maeda / RIKEN

24. Support
• Lucile Packard Foundation for Children's Health
• National Institutes of Health
• March of Dimes
• Hewlett Packard
• Howard Hughes Medical Institute
• California Institute for Regenerative Medicine
• Scleroderma Research Foundation
• Clayville Research Fund
• PhRMA Foundation
• Stanford Cancer Center, Bio-X
• … and you, the taxpayer who supports and pays for science