1. A genome-wide perspective of genetic variation in human metabolism Thomas Illig, Christian Gieger, Guangju Zhai, Werner Römisch-Margl, Rui Wang-Sattler, Cornelia Prehn, Elisabeth Altmaier, Gabi Kastenmüller, Bernet S Kato, Hans-Werner Mewes, Thomas Meitinger, Martin Hrabé de Angelis, Florian Kronenberg, Nicole Soranzo, H-Erich Wichmann, Tim D Spector, Jerzy Adamski & Karsten Suhre Presentation by: Muaeen Obadi and Tu Nguyen

2. Key Definitions metabolomics: whole genome approach to the study of metabolites ❖ systematic study of unique chemical fingerprints that specific cellular processes leave behind (Wiki) ❖ these include amino acids, carbohydrates, lipids, steroids, etc.. GWAS: genome-wide association study

3. Goals ❖ The purpose was to identify new metabotypes. ❖ Using these metabotypes they will provide new insight in gene- environment interactions for complex diseases. ❖ Provide their data to others to expand the list of loci. ➢ Some of the SNPs are patented – SNP in ACADL

4. Background Information ❖ Previous study found genetic polymorphism leads to individuals with altered metabolics. ➢ smaller sample size was used (n = 284) ❖ Used metabolite concentration ratio instead of enzymatic reaction rate.

5. ❖ Affymetrix 6.0 GeneChip array ❖ TwinsUK -- Illumina Hap317K chip ❖ 163 metabolites (amino acids, sugars, phospholiipds) ➢ blood sampling after fasting ➢ electrospray ionization tanderm mass spec. ➢ Biocrates AbsoluteIDQ Methods

6. Replication of TwinsUK ❖ national pool of twins from the UK ❖ they had similar age, similar diseases and lifestyle characteristics ❖ genotyped SNPs for 2,277 individuals of European descent ➢ Of these only 422 females were selected for the study

7. ❖ First step (initial discovery step) ➢ 1,029 males of South German origin ➢ selected loci for: ■ P < 10 -7 for metabolite concentrations ■ P < 10 -9 for concentration ratios in GWA ➢ 32 loci satisfied the above criteria Two-Step discovery design KORA F4

9. ❖ Second step ➢ tested SNP for each 32 loci in an independent sample of 780 participates selected from the remaining KORA F4 group ➢ metabolomics and genotyping conducted independently and months after first step ➢ 15 loci were selected ■ strength of association increased when additional data was added Two-Step discovery design KORA F4

16. Discussion ❖ genetic variant is located in or near enzyme-encoding or solute carrier-encoding genes for which the associating metabolic traits match the protein’s function ➢ 8 of the 9 fully replicated genetic polymorphisms ➢ 4 out of the 5 suggested possible loci ■ CPS1, SCD, SLC22A4 and PHGH

17. So what? ❖ SLC16A9 and PLKHH1 -- new hypothesis on gene function derived from associating metabolite pattern ❖ genetic variants may lead to loss of function of corresponding gene leading to severe disorders ❖ despite the differences between the KORA F4 and TwinsUK sample population, the results were similar ❖ Parallel association of loci with relevant parameters and metabolic traits to be discovered by other GWAS. ❖ The SNP discovered can be used for clinical studies of drug treatment.

18. Possible Pitfalls and Future Studies ❖ TwinUK has 20% signal to noise background sample compared to KORA. ❖ Was not the most powerful GWAS due to not being able to test more parameters from their samples. ❖ The SNP chips detect only ~10% of common SNPs ➢ novel SNPs may not have been detected ❖ Sample population was limited to European descent ➢ future studies should include different ethnicities

19. Questions?