Genetic data are just part of the bigger picture. Adding other omics will make the image sharper.Credit: Science Photo Library
The first human genome was sequenced in 2003, and it gave researchers a solid baseline from which to measure disease processes. But its information content, though rich, is limited. “Human genetics is like a polaroid snapshot of an individual,” says Ray Deshaies, senior vice president of global research at biopharmaceutical firm Amgen, and host of the new podcast series DNA Unlocked. “What we really want is more like a movie.”
Turning an image into a moving picture means adding more frames. In biology, that equates to identifying and mapping natural genetic variations and the dynamic collection of macromolecules that arise from them. “Ninety-nine per cent of the variants have a very small effect on disease,” says Richard Scheller, chairman of research and development at biotech company BridgeBio. And not all are in protein-coding regions. “They’re in regions that affect gene expression or RNA splicing, etc.” It takes “old-fashioned lab work” to understand the spectrum and effects of these variations, Scheller adds.
A window into complex disease
Genetics is a natural starting point for drug developers to understand complex common diseases, from heart disease to Parkinson’s. But while important, genetics provides just one view, and a largely unchanging one at that. “There are other biological features that do change, for example proteins, RNA or metabolites within cells or in the blood,” says physician-scientist, Saptarsi Haldar, vice president of research at Amgen.
“We need to understand the interplay between variation in the genome and dynamic changes in these other macromolecules,” Haldar says, “so we can understand the molecular mechanisms that underpin human disease progression, identify new drug targets and cellular pathways to manipulate, and refine our ability to predict which patients would most benefit from a specific therapeutic intervention.”
Unbiased and large-scale surveys of RNA (transcriptomics), proteins (proteomics) and metabolites (metabolomics) are part of a suite of ‘omics’ technologies that measure biology’s moving parts. “The dream is that proteomics and genomics will integrate. Genomics will largely be ‘one and done’,” says Larry Gold, founder of proteomics firm SomaLogic. “And proteomics will be the opposite. It’ll be longitudinal.”
Proteins make useful biomarkers, to detect and follow disease. Gold predicts that routine monitoring of biomarkers — potentially using sensors in your toilet — will be critical to future health-care. “You will be the control for yourself as your proteome changes over time,” he adds.
Applications in cancer
Cancer is a disease area with clear links to genetics; in most cases to somatic (acquired) mutations, rather than the inherited genetic code. “Sequencing technology has expanded dramatically over the past 20 years,” says Angela Coxon, vice president for oncology at Amgen. It’s now routine for many patients to have their tumour sample sequenced.
“We’ve been able to use this information to direct therapy for a patient, based on the DNA sequence of their tumour,” Coxon says. This work has also revealed broad heterogeneity: no two tumours look the same, even within the same patient.
“One way to potentially overcome this genetic heterogeneity is by harnessing the patient’s own immune system,” she continues. “This has led to a revolution in the field of cancer therapeutics, and we are now trying to identify other ways to adapt the immune system to recognize cancers and eliminate them.”
A tool for disease prediction
Genetics also plays a role in disease prediction. A recent development is the polygenic risk score: a single number that represents a person’s risk of disease, based on all the different variants they carry, explains Amit V. Khera, a cardiologist at Massachusetts General Hospital. Each variant might alter risk by only 1–2%, but collectively they can have a big influence.
In December 2020, Khera’s hospital started offering a test that assesses 6 million variants, to calculate a person’s polygenic risk score for coronary artery disease. Many of these variants are not in the coding region of the genome. “We know they’re associated with increased risk of heart disease, but the molecular mechanisms remain uncertain,” Khera says. Such a mystery opens a window into new biology.
Putting all these omics together is giving researchers a glimpse of what truly personalized medicine could look like, and it is rapidly turning that static polaroid picture into a full colour, feature-length film.