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Unravelling the complexity of height, intelligence, obesity and schizophrenia: 2017 Frank Fenner Prize for Life Scientist of the Year
Professor Jian Yang
The publication of the human genome near fifteen years ago revealed that the human genome is complicated. Jian Yang has created pioneering new techniques to unravel that complexity and solve the ‘missing heritability paradox’.
His work will enable researchers to determine the genetic factors behind complex diseases, opening the way to new drugs and better genomic risk prediction.
Some aspects of the human genome are ‘simple’ – red hair, Huntington’s disease, and haemophilia for example are determined by changes on one or a few genes. Most inherited traits are far more complex and current gene analysis tools can only track down a small fraction of the DNA variants responsible for many inherited conditions.
Jian Yang developed a new statistical method to analyse genomic variation and showed that genetic variation in obesity, cognitive ability, and schizophrenia are due to the contribution of a large number of genetic variants across the genome.
So, to understand the heritability of complex traits and diseases we will have to analyse the genomes of hundreds of thousands, even millions of people. Jian is now creating the tools to enable these large analyses. Thousands of geneticists around the world are already using his software.
Professor Jian Yang receives the $50,000 Frank Fenner Prize for Life Scientist of the Year for creating ways to understand inherited traits and the human genome.
What are the genetic influences on our height, or on our risk of mental illness? What controls yield or stem height in wheat. What determines how many eggs a bird lays?
These days we can rapidly read the whole genetic code or genome of a person, a plant, or a bird. So, it seemed it would be easy to identify all the genes influencing inherited traits using technologies such as genome wide association study (GWAS).
But the genome is more complex that we expected. Researchers found that for important traits in humans, they could only find less than ten per cent of the genetic differences predicted by studies of families and twins. They called it the ‘missing heritability paradox’. It became a significant hurdle for human genetic studies. Perhaps the human genome really was too complex to understand.
The answer, in theory, was simple. Analyse many more genomes in much more detail. But virtually no-one thought that would be possible. The calculations would be too complex for even today’s computers.
Jian proved the sceptics wrong. He developed new statistical tools and elegant studies to find the missing genetic variation. In a series of papers, he showed that for traits such as height, obesity, and schizophrenia there are a large number of associated variants across the human genome.
The impact in the genetics world is illustrated by his publication history. He has published 97 papers, 30 of them in Nature or Nature Genetics and his work has been cited over 20,000 times.
His work opens the way to a new era of genomic analysis using tools that he has developed and made available to the wider research community.
Jian Yang received his degree in biological science and a PhD statistical genetics from Zhejiang University in Hangzhou, west of Shanghai. The story of how he came to Australia in 2008 says a lot about him and his character.
His Australian mentor Professor Peter Visscher remembers encountering him as he was about to speak at a conference in Hangzhou. A young man he had never met came up to him saying, “You must be Peter Visscher,” and began to talk to him. Jian had memorised the names, history and pictures of all the key speakers at the conference so he could get the most out of interacting with them.
By the end of the week, Peter was convinced that Jian should come and join his team in Australia. “I was very impressed by his attitude towards science. He asked all the right questions, and had already had several papers published in international journals,” says Peter.
Today, Jian Yang’s work is at the interface of human disease genetics, statistical modelling and big data analysis. His work is highly innovative, and typically uses large human cohort studies to (simultaneously) do two things: develop state-of-the-art methods; and, make fundamental insights into genetic questions that have been troublesome for around a century.
