#AGBTPH – Ramnik Xavier, Microbes, genes and gut immunity

Broad Institute.

Studying health and disease in human:

  • Genetics
  • Microbiome
  • Environment – area of weakness, how do we study this?

Cost of sample prep has dropped dramatically, and that helps us with data gathering.  IBD has enjoyed the greatest success in terms of GWAS discovery.  Our sophistication in doing the analysis has had the biggest impact.

Dysbiosis implicated in disease in human and animal models.  Crones is a good example, where disease causes imbalances in gut bacteria.  Disease activity correlates with micro biome population.  Just counting bugs so far… but look at function.  Those that disappear are the ones that regulate activity in normal gut.  Maybe first insult is the alteration in gut metabolism.

What happens if you look at tissue at those sites?  Also show that you have an altered redox balance.  The host response is tilted in same direction.

What about Viruses?  Similar trends seen – with changes in virus populations altered.

2000 healthy individuals recruited in Netherlands.  Gut microbiome and gwas.  In healthy individuals, there was a richness in loci that related to microbiome health… and other markers too, including food choice.

GWAS for bacterial taxonomies.  (Bonder et al, Nature genetics, accepted)

First example: Ulcerative Colitis.  Crones disease.

If you took all the GWAS, what do they tell you?  They point to pathways that maintain inflammation, healing and homeostasis.  Just one example: Autophagy.  Early GWAS (2007 and 2008) associate autophagy with Crones.  Ability of certain cells (paneth cells?) were altered in cells that lead to crones  – ATG16L1 T330A.  Put that variant into mice, and found that there are less Reg3gamma, which is an antimicrobial. With mutation, bacteria get closer to the cell lining, which potentially leads to more inflammation.

T300A is the risk variant.  There’s a potential caspase cleavage site, show that caspase is likely involved – thus, the protein is probably less stable.

Thus, GWAS has lead to some significant understanding of the disease.   Applications include better prediction of health outcomes for children with crones.

Another Example: CARD9

This protein is a protective gene for IBD. Can we use this to improve therapeutics?  Sure – we know that the risk version binds to a protein, and if you can disrupt that target, then you can prevent the inflammation.  This is a draggable target.

Example on Type I diabetes.  Why study?  3-7% of kids have risk alleles for this type of diabetes.  Incidence is rapidly increasing, and may double in next few years – probably environmental.

Use a “living laboratory”, Finland has very high incidence, while Russia and Estonia do not.  If you take kids who have high risk, and follow them.  You can see major microbiome shifts one year before Type I diabetes kicks in.

VERY cool graph of microbial compositions by country.  Close investigation showed that microbial sensing was affected in kids with Type I diabetes.  LPS different between Russian kids and Finnish kids – the LPS in Finnish kids is not sensed by TLR receptor – preventing the recognition of bacteria in the first year of life.  Kids immune system is not “educated” to recognize bacteria, which later has consequence on whether autoimmune diseases (such as T1D) become triggered.

Future:

  • Tapping into microbiome will help us to understand interactions
  • identify disease triggers

Leave a Reply

Your email address will not be published. Required fields are marked *