Nick Martin Queensland Institute of Medical Research Brisbane MRC CAiTE Symposium Bristol

1. Connecting biobanks - adding value in the genetics of complex traitsThe Australian Twin Collections Biobank Nick Martin Queensland Institute of Medical Research Brisbane MRC CAiTE Symposium Bristol January 12, 2011

2. My brief… • how biobanks can be beneficial for researchers • what’s happening and what is accomplished • some results of projects I’m involved in

3. How beneficial biobanks can be  for research[ers] (1) 1 page of authors and affiliations!

4. How beneficial biobanks can be  for research[ers] (2) 2 pages of authors and affiliations !

5. Australian Twin Registry • Founded 1978 • Voluntary enrolment – schools, media, etc • ~30,000 pairs enrolled (~15% of all pairs) • Two adult cohorts studied • 1893-1964 (5967 pairs), 1965-1971 (4629 pairs) • Typical of population wrt psychiatric symptoms, personality, social class & education (females) • Males slightly more educated and middle class • New cohort of ~8000 pairs (born 1972-85)

6. Timetable of Questionnaires and Interviews Cohort 1 DSM-IIIR MD, PD 2456 p / 771 s N23, A, D 3808 p / 576 s N12, A, D 3051 p / 468 s N23, CIDI 894 N12, A, D 1279 p / 558 s Cohort 2 N23, CIDI 404 N12, A, D 2270 p / 518 s Siblings N23, CIDI 1172 N12 5375 Parents N12 6014 765 1980 1985 1990 2000 1995

7. QIMR GenEpi core interests Quantitative phenotypes related to disease risk: Metabolic / cardiovascular risks Biochemical test results Lipids Glucose, insulin Urate, CRP, ferritin Liver enzymes GGT, ALT, AST, BCHE Personality, depression, anxiety, cognition, MRI, taste, smell Addictions (alcohol, nicotine, cannabis, opioids, gambling) Melanoma; endometriosis; asthma; migraine; twinning

8. Data (Twins and families) • Biochemical phenotypes N ≈ 19,000 adults • N ≈ 2,500 adolescents • GWAS N ≈ 20,000 ENGAGE participation • Meta-analysis of lipids, urate, alcohol, liver function tests, glucose • Meta-analysis of iron markers, transferrinisoforms

9. Queensland Twin Registry Adolescent twins + sibs

10. Phenotypes measured on teenage twins  included; - no information 12yrs 14yrs 16yrs Sun exposure - Sun protective behaviour - Mole counts and locations - Melanoma family history - Mosquito bite susceptibility - Mouth ulcers - Sociodemographic Variables  Eye, hair and skin colour  Personality (JEPQ, NEO) Acne Height, weight  Blood pressure  Fingerprints, handprints

11. 12yrs 14yrs 16yrs Photoaging (skin mould)  Visual acuity  AutoRefractometry (myopia)  ENT (grommets, T&A)  Asthma, eczema Laterality (hand, eye, foot)  Hand preference (peg board)  Binocular rivalry (bipolar) - Computer Use -- Reading Ability (CCRT) -- Cognitive Ability (IQ – MAB) -- Information Processing (IT) -- Working Memory (DRT) -- ERPs (DRT) -- EEG (power, coherence) -- Academic achievement (QCST) -- Taste (PTC, bitter, sweet)  Smell (BSIT, NatGeo) -- Psychiatric signs (SPHERE)  Relationships -- Leisure activity --

12. Blood phenotypes 12yrs 14yrs 16yrs Haemoglobin  Red blood cell count  Packed cell volume  Mean corpuscular volume  Platelet count  White blood cell count  Neutrophils Monocytes  Eosinophils Basophils Total lymphocytes  CD3+ T-cells  CD4+ helper T-cells  CD8+ cytotoxic T-cells  CD19+ B cells  CD56+ natural killer cells  CD4+/CD8+ T-cell ratio  Blood groups (ABO, MNS, Rh) - - 

13. Serum biochemistry 12yrs 14yrs 16yrs Cholesterol, HDL, LDL  Triglyceride  Apolipoproteins A1,A2.B,E  Lp(a)  Glucose, Insulin  Ca, PO4 Creatinine  Urea, Uric acid  Alkaline phosphatase Albumin, Bilirubin AST, ALT, GGT  Fe, Ferritin, Transferrin Heavy metals (Pb, As etc) 

15. Population 21 million Area 7.7 million km2

17. External blood collection: Labmailer Process Preparing Labmailers Preparing FTA cards Biobottle Box Incoming Blood Samples Receipting the blood sample

18. Standard blood collection and processing Samples are collected in the following tubes: 2 x EDTA 1 x SERUM 1 x ACD 1 x PAX 1 x BUCCAL MNC Processing Buccal Extraction 4 x Red Blood Cells 4 x Serum The 2 x EDTA & 1 x SERUM tubes are centrifuged at 3000rpm for 10mins and then the fractions are collected. All fractions & 1 x Buffy Coat are stored in the -80oC freezers Stored in Freezer for later RNA work 4 x Plasma 2 x Buffy Coats 1 x Buffy Coat Extraction

19. Average DNA Yield per buffy coat (10ml EDTA blood collection) Mean = 171.291 Std. Dev = 68.5431 N = 3,554

20. Genetic Epidemiology Frozen sample inventory

21. Genetic Epidemiology DNA sample inventory

22. GWAS studies at QIMR

23. Australia’s changing ethic composition

24. Published Genome-Wide Associations through 6/2010 904 published GWA at p<5x10-8 for 165 traits NHGRI GWA Catalog www.genome.gov/GWAStudies

25. (Most) genetic effects are modest • Genetic risks for complex traits are modest • A genetic risk (OR) of 1.3 (2% variance) is large • Most genetic risks are in the 1.1 to 1.2 range or less (<1% variance) • This is true for most complex diseases (e.g. alcoholism, schizophrenia, bipolar disorder, lung cancer) and traits (height, BMI, lipids) BUT not always………….(use your Biobank !)

26. Serum Bilirubin • a waste product of the normal breakdown of red blood cells • excreted from the body after being conjugated with glucuronic acid ~ UGT (UridineDiphosphateGlucuronyltransferase) enzyme • a diagnostic marker of liver and blood disorders • acts as an antioxidant: an increase in bilirubin levels is associated with a reduced risk of cardiovascular diseases

27. Bilirubin in adolescents rs2070959

28. Genetics of Iron Status • What genes affect iron status (e.g. serum iron, transferin, saturation, ferritin), and the risk of either deficiency or overload in general population?

29. GWAS (N = 8942) Serum iron TMPRSS6 P = 7E-27 HFE P = 5E-38 TF P = 3E-104 HFE P = 1E-73 Transferrin HFE P = 8E-83 TMPRSS6 P = 2E-27 Tf saturation ZNF521 (Zinc Finger Protein 521) P = 4E-08 HFE P = 4E-12 Ferritin

30. Large effects of TF and HFE variants ENGAGE meta-analysis to find more iron metabolism genes

31. Butyrylcholinesterase (BCHE) Correlations ≥ 0.25 for: BMI Blood pressure ApoB ApoE Total cholesterol Triglycerides GGT + significant but smaller correlations for ALT, AST, HDL-C, LDL-C, urate. • Enzyme found in plasma • Rare variants in BCHE extensively studied because of pharmacogenetic effects • Evidence of involvement with T2DM, CVD, Alzheimer disease (questionable)

32. Cholinesterase GWAS Meta-Analysis (3 studies, total N = 8781)

33. QQ Plots Before and AfterAdjustment for the BCHE K Variant – many other variants contributing…….

34. Ingenuity Pathway Analysis on all butyrlcholinesterase GWAS data All SNPs with p ≤ 0.001 (Total 5662, of which 2003 mapped to 440 genes)

37. CD4+/ CD8+ ratio h2 = 0.84 (0.79–0.87)

38. Not only blood variables show large SNP effects...

39. Hair curliness – straight, wavy, curly λ = 1.00008

40. GWAS for curliness in three independent Australian Cohorts P = 10-31 Other peaks

41. GWAS for hair curliness ~6% variance

42. Trichohyalin is expressed in hair root sheaths

46. Heterogeneity of gene effects by age, and sex...and environment?

47. Liver function: gamma glutamyltransferase (GGT) Several significant hits in the combined data, but not the expected one on Chr. 22 ? Heterogeneity between adult and adolescent results at this locus!

48. Multiple SNPs show heterogeneity between adult and adolescent results for GGT

49. Melanocytic naevi (common moles) The largest risk factor for melanoma

50. QIMR GWAS for total, flat and raised nevi IRF4 MTAP Note inverse association signals for MTAP and IRF4 with flat and raised nevi