Yalu Wen: Fighting serious disease with statistics

02 May 2017

Dr Yalu Wen
Dr Yalu Wen

Yalu Wen’s career was forged from a shattering experience. Two of her grandparents died of cancer, and that drove her to pursue an undergraduate degree in pharmaceutical engineering in her native China. “I really wanted to know if there was any way to postpone cancer development or fully cure cancers,” Dr Wen says.

She found that that the chemistry and biology her undergraduate degree required wasn’t her thing – but maths and computer science were. Statistical modelling, in particular, fascinated Dr Wen: “I really enjoyed building and validating models to understand disease mechanisms, and I realised how important modelling is in many areas.”

From that point, Dr Wen’s drive to curb diseases went down a different path – genetic epidemiology, or studying the effects of genes on diseases. She gained an MSc and a PhD from Michigan State University, the latter on genetic variations and their effects on coronary heart disease and cervical cancer. Dr Wen came to the Department of Statistics in 2014.

She is still driven by the memory of what happened to her grandparents. The reason I chose to work in statistical genetics is that I believe everything happens for a reason,” says Dr Wen. “Other than lifestyles, I believe genetic susceptibilities should be related to many common diseases, such as cancer. If we can fully understand the disease mechanisms from the molecular level, we may be able to identify the therapeutic targets and thus deliver the right treatment to the right person.”

A prolific researcher, Dr Wen has been published in prestigious journals such as Genome Research, Genetic Epidemiology, Bioinformatics and PLoS ONE and holds a patent for an algorithm used to get accurate genotype calling from DNA microarrays. Last year, she won the New Zealand Statistical Association’s Worsley Early Career Award, named after the brain mapping expert Keith Worsley, which recognises outstanding published research from a New Zealand statistician in the early stages of their career. The award is not only a compliment, says Dr Wen, but it “makes me love my own work more”.

At present, Dr Wen is developing and evaluating statistical genetic risk prediction models, using population-based data as well as family-based genetic studies, where the correlation between family members is used as a surrogate variable to improve prediction accuracy. The latter leads to some fascinating work: Dr Wen recently analysed data from the Michigan Twins Study that looked at twins aged three to five years and their non-twin siblings in an effort to find out if children carrying particular genetic markers were more likely to have aggressive behaviour.

“If those markers can be found, we further want to know the percentage of variations these genetic markers can explain and whether these genetic markers can be used to predict kids’ aggressive behaviour,” she explains. “If the predictive model is accurate enough, we could use this model to identify kids who are more likely to have aggressive behaviour and develop special education programmes for them.”