Genome sequencing was used to determine the extent to which genes influence human characteristics such as height, weight and susceptibility to diseases such as type 2 diabetes, in a study co-led by researchers from the University of Queensland (UQ) and the genomics technology company Illumina, Inc.
This is the largest study ever conducted in this area and used the DNA sequences of 347,630 individuals of European ancestry from the UK Biobank to quantify how much of the differences between individuals can be explained by genetic factors — a concept known as heritability.
Professor Loïc Yengo, of the Institute for Molecular Bioscience at UQ, explained that whole-genome sequencing enables precise measurement of most genetic variants, unlike traditional methods based on relatives and twin studies.
“One of the big questions in human genetics was to know to what extent heritability estimates obtained from twin studies could be reproduced by modern genomic technologies applied to unrelated individuals,” says Professor Yengo.
“Our study answers this question and demonstrates, for the first time, that this approach works,” he adds.
Among the 34 traits and diseases analyzed by the researchers were height, body mass index (BMI), cholesterol, hypertension, fertility, the onset of smoking, and heart disease.
“Across the studied traits, we estimated that genetic factors explain, on average, about 30% of the differences between people — ranging from 74% for height to 12% in fertility,” explains Yengo.
The researcher added that one limitation of traditional methods is that family members and twins share not only genes but also environmental factors.
“For example, family-based estimates attribute about 50% genetic influence on a person’s BMI, but genomic sequencing showed that this influence is, in fact, 35%.”
The next step, according to Yengo, will be to map the genes or genetic variants among individuals to understand why some people develop certain diseases and others do not.
“This would allow early identification of individuals at risk and the adoption of preventive measures well before the disease manifests,” he says.
Co-author Kyle Farh, Vice President of Artificial Intelligence at Illumina, underscores the importance of large-scale population databases.
“Population-scale genomic datasets, such as the UK Biobank, give researchers access to an enormous wealth of information,” he notes.
The research was published in the scientific journal Nature.
