1. Connecting biobanks - adding value in the genetics of complex traits The 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. 2 pages of authors and affiliations ! How beneficial biobanks can be for research[ers] (2)

5. 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) Australian Twin Registry

6. 198019902000 Cohort 1 Cohort 2 Siblings Parents 1985 1995 N12 5375 N12 6014 N23, A, D 3808 p / 576 s N12, A, D 3051 p / 468 s DSM-IIIR MD, PD 2456 p / 771 s N12, A, D 1279 p / 558 s N12, A, D 2270 p / 518 s 765 N23, CIDI 1172 N23, CIDI 404 N23, CIDI 894 Timetable of Questionnaires and Interviews

7. 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 QIMR GenEpi core interests

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

9. Queensland Twin Registry Adolescent twins + sibs

10. 12yrs14yrs 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 Phenotypes measured on teenage twins included; - no information

11. 12yrs14yrs16yrs 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. 12yrs14yrs16yrs 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)-- Blood phenotypes

13. 12yrs14yrs16yrs Cholesterol, HDL, LDL Triglyceride Apolipoproteins A1,A2.B,E Lp(a) Glucose, Insulin Ca, PO 4 Creatinine Urea, Uric acid Alkaline phosphatase Albumin, Bilirubin AST, ALT, GGT Fe, Ferritin, Transferrin Heavy metals (Pb, As etc) Serum biochemistry

15. Population 21 million Area 7.7 million km 2

17. Preparing Labmailers Biobottle BoxIncoming Blood SamplesReceipting the blood sample Preparing FTA cards External blood collection: Labmailer Process

18. Samples are collected in the following tubes: 2 x EDTA 1 x SERUM 1 x ACD 1 x PAX 1 x BUCCAL 4 x Red Blood Cells 4 x Plasma 2 x Buffy Coats 4 x Serum Stored in Freezer for later RNA work 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 -80 o C freezers MNC Processing Buccal Extraction 1 x Buffy Coat Extraction Standard blood collection and processing

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

20. Stock DNA 400ul New DNA dilution 50ng/ul 500ul+ The DNA dilution tube, and stock DNA tube are stored at 4 o C until required for project plating. Remaining Stock DNA 300ul 1:5 Dilution (100ul stock + 400ul 1 x TE) 1:5 Dilutions 1:100 Dilution (5ul 1:5 + 495ul 1 x TE) 96 deep well plate 50ul of 1:100 transferred to Black OptiPlates in duplicate Picogreen added to plates and standards, fluorescence detected by Ascent Fluoroskan 1 x TE Stock DNA + Based on Fluoroskan results, the 1:5 dilution is modified to 50ng/ul by addition of more buffer or stock + Known DNA Standards AutoQuantitation by Fluroskan

21. 15ul of the 50ng/ul DNA dilution is plated out into a 96 well plate and eluted in 0.2 x TE to give 2.5ng/ul. This process is repeated for 95 other samples required for the project. Once 4 x 96 well plates are prepared, they are then plated out onto a 384 well plate. This plate uses 4-5ul of the 2.5ng/ul DNA dilution. 20 replicates of this plate are prepared and stored in the freezer for later use. One of the 384 well plate replicates is selected and 25 SNP’s are analysed. Eppendorf epMOTION 5075 plating robot DNA Dilutions 384 well plate 96 well plate Project Plating of DNA Dilution Tube

22. Genetic Epidemiology Frozen sample inventory FractionNumber of Samples Plasma128,012 Buffy Coats101,333 Red Blood Cells130,668 Serum97,677 Buccals5,591 FO Plasma7,815 FO BC7,387 FO RBC7,500 Total485,983

23. Genetic Epidemiology DNA sample inventory FractionNumber of Samples DNA Dilutions at 50ng/µl44,926 DNA Stocks50,719 DNA Other16,443 Total112,088

24. StudySubjectsNPlatformSiteFunding CVD RiskAdult MZ ff923Illumina 317kHelsinkiEU Migraine+ NicAdult twins1,234Illumina 610kdeCodeNHMRC Alcohol (1)Adult twins2,736Illumina 370kdeCodeNIH Alcohol (2)Adult sibships4477Illumina 370kCIDRNIH DepressionAdult cases(1,257)Affy 6.0TGenGAIN EndometriosisAdult cases2,383Illumina 660kdeCodeWellcome AdolescentTwin families4,556Illumina 610kdeCodeNHMRC+ Asthma/AngstTwin families1,766Illumina 610kBrownNHMRC TOTAL19,257 GWAS studies at QIMR

25. Australia’s changing ethic composition

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

27. 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 !) (Most) genetic effects are modest

28. a waste product of the normal breakdown of red blood cells excreted from the body after being conjugated with glucuronic acid ~ UGT (Uridine Diphosphate Glucuronyltransferase) 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 Serum Bilirubin

29. rs2070959 Bilirubin in adolescents MeasureAlleleEffect (b)SeR2R2 P Value Age 12A-0.580.0421%3E-59 Age 14A-0.710.0523%1E-50 Age 16A-0.970.0629%4E-65 Age 18A-0.720.0924%5E-15 MeanA-0.760.0328%2.1E-115

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

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

32. ENGAGE meta-analysis to find more iron metabolism genes Large effects of TF and HFE variants MeasuresTF Mutation (rs3811647)HFE mutation (rs1800562) Effect% varpEffect% varp Iron-.01±.10 SD0.81.66±.10 SD103.5 x 10 -11 Transferrin.46±.06 SD133 x 10 -15 -.68±.10 SD91.1 x 10 -10 Saturation-.17±.06 SD2.002.80±.10 SD134.3 x 10 -15 Ferritin-.13±.06 SD1.03.44±.1144.5 x 10 -5

33. Enzyme found in plasma Rare variants in BCHE extensively studied because of pharmacogenetic effects Evidence of involvement with T2DM, CVD, Alzheimer disease (questionable ) 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. Butyrylcholinesterase (BCHE)

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

35. Before and After Adjustment for the BCHE K Variant – many other variants contributing……. QQ Plots

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

39. CD4+/ CD8+ ratio h 2 = 0.84 (0.79–0.87)

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

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

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

43. ~6% variance GWAS for hair curliness

44. Trichohyalin is expressed in hair root sheaths

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

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

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

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

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

53. American Journal of Human Genetics 87, 6–16, 2010 Mole count: Interaction of IRF4 genotype with age

54. 4 point rating (none to severe) 3 sites – face, chest, back at age 12 and 14 at age 16 face only How to combine these 7 measures ? Lots of missingness Item response modelling in WinBUGS enables Bayesian estimation of liability, allowing for twin relatedness and adjusting for age, sex Teenage acne

55. Joint F + M Females Males GWAS for Acne – different genes for males and females ?

56. Is sensitivity to the environment a function of genotype? For MZ twins |twin1 – twin2| is a pure measure of e does |twin1 – twin2| vary systematically between genotypes? A direct test of G x E Gene – environment interaction

57. Systematic GWA search for GxE using MZ twins 1800 MZ female pairs aged 30-70 from AU, UK, NL, DK, SE GWAS using Illumina 317k array Focus on CVD risk factors (lipids), but other phenotypes as well (including depression) GenomEUtwin

58. Genome-wide association scan of MZ pair mean levels of HDL cholesterol

59. 1800 MZ female pairs from GenomEUtwin A gene for environmental sensitivity on Chr 16 ? GWAS of MZ pair |differences| of HDL cholesterol

60. - expression and epigenetic data Adding value to your Biobank (1)

61. Study Design 980 Individuals Full Families Parents + Offspring (MZ / DZ / Sib) MZ and DZ twin pairs PAX MZ, DZ and Sib ~2/3 of samples ~1/3 of samples PAX Gene expression profiles for ~980 individuals Individuals from 3 ‘family’ groups Only PAX gene expression generated expression levels generated using Illumina HumanHT-12 v4.0 chips Expression levels can be correlated with all other phenotypes eQTL Study

62. Study Design 980 Individuals Full Families Parents + Offspring (MZ / DZ / Sib) MZ and DZ twin pairs Methylation MZ, DZ and Sib ~2/3 of samples ~1/3 of samples Methylation From the sample individuals as the full expression study Whole genome methylation levels determined Using Illumina methylation 450k chips Methylation levels can be correlated with expression…and with MZ discordance ! Methylation levels

63. - widespread methylation differences Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus. Javierre BM et al. Genome Res. 2010 20: 170-179, 2010 MZ pairs discordant for SLE

64. - keep adding new phenotypes ! Adding value to your Biobank (2)

65. Associated with: testosterone exposure aggression ADHD homosexuality fertility others Multivariate Genetic Analyses of the 2D:4D Ratio: Examining the Effects of Hand and Measurement Technique in Data from 757 Twin Families. Sarah E. Medland and John C. Loehlin Twin Research and Human Genetics 11: 335–341, 2008 Ratio of 2 nd to 4 th finger length

66. LIN28B SNP associated with: 2D:4D ratio Age of menarche Menopause Height A Variant in LIN28B Is Associated with 2D:4D Finger-Length Ratio, a Putative Retrospective Biomarker of Prenatal Testosterone Exposure Sarah E. Medland…. David M. Evans Am J Human Genetics 86, 519–525, 2010

67. Large consortia…..

68.  Brisbane Adolescent Twin database - (>700 scanned)  Data acquisition: 4 Tesla Bruker Medspec scanner – CMR, UQ  MRI  DTI (HARDI)  fMRI (n-back)  resting-fMRI  Processing and analysis:  MRI - UCLA  DTI (HARDI) -UCLA  fMRI (n-back) - UQ  resting-fMRI – UQ + NYU Twin Imaging Study (TIMS)

70. http://enigma.loni.ucla.edu/

71. - sequencing ! Adding value to your Biobank (3)

72. Whole-genome sequencing Why? Discover novel, rare variants with potential relevance for disease, including CNVs. These can then be imputed/genotyped and tested for association in large cohorts. Pilot study: first look at data 14 cases + 1 control (including trio) sequenced with deep coverage using HiSeq. Cases with strong family history, severe disease and other co-morbid phenotypes. ~97% concordance of sequence with KGP imputation (610k)

73.  Twins and their families for the participation  John Whitfield, Peter Visscher, David Duffy, Grant Montgomery, Dale Nyholt  Dixie Statham, Ann Eldridge, Marlene Grace, Anjali Henders and Megan Campbell, Leanne Wallace for the data collection and sample processing.  Allan McRae, Manuel Ferreira, Brian McEvoy, Scott Gordon, Sarah Medland, Gu Zhu, Beben Benyamin, Rita Middelberg, Margie Wright for helping with data & analysis  Harry Beeby and David Smyth for IT support  Collaborators:  Netherlands Twin Registry: Gonneke Willemsen, Jouke-Jan Hottenga, Eco de Geus, Brenda Penninx, Dorret Boomsma  UK Twin Registry: Tim Spector, Mangimo Massimo  ALSPAC Study: David Evans, George Davey Smith  Sanger Institute / U Helsinki: Aarno Palotie, Leena Peltonen  University of Queensland: Ian Frazer, Rick Sturm, Greig de Zubicaray  Washington University, St. Louis: Andrew Heath, Pam Madden Acknowledgements