PHOEBE UK Biobank: how big is “big”? Paul Burton Dept of Health Sciences Dept of Genetics University of Leicester

PHOEBE Structure of talk  What is UK Biobank?  How big is “big”?  Expected event rates in UK Biobank  Biobank harmonisation

PHOEBE What is UK Biobank?

PHOEBE  A prospective cohort study  500,000 adults across UK  Middle aged (40-69 years)  A population-based biobank Not disease or exposure based  “Broad spectrum” not “fully representative”  Individuals not families  MRC, Wellcome Trust, DH, Scottish Executive £61M Basic design features

PHOEBE  Longitudinal health tracking  Nested case-control studies  Long time-horizon  Owned by the Nation  Central Administration – Manchester PI: Prof Rory Collins - Oxford  6 collaborating groups (RCCs) of university scientists Basic design features

PHOEBE  Primary justifications Roles that can best be fulfilled by a new large cohort study of the type represented by UK Biobank  Secondary justifications Roles that could be provided by other types of study, but given that UK Biobank is to go ahead anyway these additional roles can be taken on at relatively low marginal cost Justification for UK Biobank

PHOEBE A platform for research in biomedical science  Studies of the joint effects of genes and environment/life-style  Genotype-based studies***  The genetics of disease progression  Direct association of genes with disease***  Universal controls  Family-based studies

PHOEBE How big is “big”? With Anna Hansell, Imperial College

PHOEBE  Contemporary pre-eminence of genetic association studies rather than genetic linkage studies  Covers both stand-alone case-control studies, and nested case-control studies in large cohorts  Sample size determining in both settings The statistical power of case-control studies

PHOEBE Power calculations  Work with the least powerful setting Binary disease, binary genotype, binary environmental exposure  Logistic regression; interactions = departure from a multiplicative model  Complexity (arbitrary but realistic)

PHOEBE Summarise power using MDORs calculated by ‘iterative simulation’  Estimate minimum ORs detectable with 80% power at stated level of statistical significance under specified scenario

PHOEBE Summary of results  80% power for genotype frequency = 0.1 Genetic main effect  1.5, p=10 -4  5,000 cases Genetic main effect  1.3, p=10 -4  10,000 cases Genetic main effect  1.2, p=10 -4  20,000 cases Genetic main effect  1.4, p=10 -7  10,000 cases Genetic main effect  1.3, p=10 -7  20,000 cases G:E interaction with environmental exposure prevalance = 0.2  2.0, p=10 -4  20,000 cases

PHOEBE Expected event rates in UK Biobank With Anna Hansell, Imperial College

PHOEBE Taking account of  Age range at recruitment years  Recruitment over 5 years  All cause mortality  Disease incidence (“healthy cohort effect”)  Migration overseas  Withdrawal from the study

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Smaller sample sizes

PHOEBE Conclusions  Having taken account of realistic bioclinical complexity, a cohort-based biobank such as UK Biobank needs to be very large if it is to provide a stand-alone infrastructure  Anything much less than 500,000 recruits will severely curtail the number of diseases that will be able to be studied based on that biobank alone  The value of any biobank will be greatly augmented if it proves possible to set up a coherent and scientifically harmonised international network of biobanks and large cohort studies

PHOEBE Harmonising biobanks internationally

PHOEBE Why harmonise?  Investigate less common (but not rare!!!) conditions UKBB: Ca stomach 2,500 cases in 29 years  6 UKBB equivalents:  10,000 cases in 20 years  Investigate smaller ORs GME 1.5  1.2 requires 5,000  20,000  4 UKBB equivalents  Analysis based on subsets – homogeneous classes of phenotype, or e.g. by sex

PHOEBE Why harmonise?  Earlier analyses UKBB: Alzheimers disease, 10,000 cases in 18 yrs  5 UKBB equivalents  9 years  Events at younger ages  Broad range of environmental exposures  Aim for 4-6 UKBB equivalents 2M – 3M recruits

PHOEBE International biobank harmonisation programs  Public Population Program in Genomics (P 3 G) Tom Hudson, Bartha Knoppers, Leena Peltonen …  Population Biobanks FP6 Co-ordination Action (PHOEBE – Promoting Harmonization Of Epidemiological Biobanks in Europe) Camilla Stoltenberg, Leena Peltonen, Paul Burton …  Human Genome Epidemiology Network (HuGENet) Muin Khoury, Julian Little …

PHOEBE Extra slides

PHOEBE Hattersley AT, McCarthy MI. Lancet 2005;366: Examples of some polymorphisms or haplotypes that have shown consistent association with complex disease

PHOEBE Genetic main effects

PHOEBE Whole genome scan  Genetic main effect, p<10 -7

PHOEBE Gene-environment interaction  20,000 cases

PHOEBE Gene-environment interaction  10,000 cases

PHOEBE Rarer genotypes  Genetic main effects

PHOEBE Proposed assessment visit model Welcome5 Consent5 Blood/Urine10 Touchscreen Questionnaire25 Interviewer Questionnaire5 Physical Measures15 Exit5 TOTAL70

PHOEBE Taking account of  Age range at recruitment years  Recruitment over 5 years  All cause mortality  Disease incidence (“healthy cohort effect”)  Migration overseas  Comprehensive withdrawal (max 1/500 p.a.)  Partial withdrawal ( c.f Birth Cohort)

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Necessary to contact subjects

PHOEBE Issues that are often ignored in standard power calculations  Multiple testing/low prior probability of association*  Interactions*  Unobserved frailty  Misclassification* Genotype Environmental determinant Case-control status  Subgroup analyses*  Population substructure

PHOEBE Harmonisation  Prospective  Retrospective Description Comparison Harmonised synthesis

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