Illumina in Nature:
There are more than 120 biobanks worldwide, having evolved over the past 30 years. They range from small, predominantly university-based repositories, to large, government-supported resources. As well as collecting and storing samples, they also provide clinical, pathological, molecular and radiological information for research into personalized medicine. Biobanks allow researchers to explore the causes of disease by helping them link genotypes to phenotypes. This is a process that has been underway for years through genome-wide association studies (GWAS), but it has proved far from straightforward. “What we have learned from GWAS over the last 15 to 20 years is that there are many variants, they have small effect sizes and, even if you total most of the common variants throughout the genome, they account for only a small fraction of phenotypic variance,” says Judy Cho, a translational geneticist at Icahn School of Medicine at Mount Sinai, New York.
Biobanks are speeding up progress. They allow researchers to easily analyse increasing numbers of biological samples and associated clinical data to characterize disease mechanisms, find novel drug targets, and identify patients most likely to benefit from a particular treatment approach. “Embedding genomic information in electronic health-care records, so it can be used through the course of life, is an appealing vision,” says Dan Roden, a clinical pharmacologist and Director of the BioVU Biobank at Vanderbilt University Medical Center, Tennessee. “But it’s one that is hard to realise; there are lots of logistical problems in creating an infrastructure like that.” BioVU’s step towards achieving this vision is to store DNA extracted from discarded blood, collected during routine clinical testing, linked to de-identified medical records. Around 250,000 DNA samples are now available for Vanderbilt investigators.
But going big isn’t the only solution: insights into common diseases can also be found by analysing smaller disease- and/or ethnic-specific cohorts, which concentrate on important genomic signals. Advances in genetic technologies and increased efforts to capture genetic diversity in biobanks are helping researchers to make robust geno-pheno associations in a cost-effective manner (see ‘Biobanks and geno-pheno associations’).