Like the infamous Marauder’s Map in the Harry Potter novels, which revealed all the secrets of Hogwarts Castle, a recently published proteo-genomic map uncovers hundreds of novel connections between human diseases. An international team of researchers led by scientists at the Medical Research Council (MRC) Epidemiology Unit at the University of Cambridge compiled the data to create the map, and they detailed the results in Science in October 2021.
Their research builds on a long history of evolving biological understanding. For decades, biologists have known that proteins are essential to human health, performing many functions in our cells and maintaining the body’s tissues and organs. Proteins are made up of amino acids and are built based on DNA blueprints in our genes. When the human genome was mapped in 2003, scientists hoped they would find direct links between genes and disease. While several multiple genome-wide association studies (GWAS) have identified many thousands of variants in our DNA sequence that are associated with disease, the underlying mechanisms of disease have remained elusive because of challenges linking a genetic variation to a gene to a specific protein to a disease.
Making the Map
For the new study, researchers analyzed blood samples from more than 10,000 subjects who participated in the Fenland Study. They showed that natural variation in 2,500 regions of the human genome is very strongly associated with differences in abundance or function of 4,775 proteins circulating in the blood. Next, they identified 10,674 protein–quantitative trait loci (pQTLs) — genetic variants that correlate with the plasma level of proteins. Then, they looked more specifically for cis-pQTLs. To understand why, it helps to understand that peptide bonds in proteins can come in two configurations, trans or cis. In trans configurations, the atoms of certain amino acids are arranged spatially in one plane. In cis configurations, the exact same atoms are arranged in a different plane. These structural differences can cause the proteins to fold differently, which affects their function. Evidence indicates that cis folding may indicate a stronger link between the protein and the precise location of the gene that encodes it.
The researchers identified 1,548 cis-pQTLs as candidate causal genes, which were then mapped to expressed traits in human tissues. What emerged was a cis-anchored proteo-genomic map of human health that included 1,859 gene-protein-phenotype connections comprising 412 proteins and 506 curated traits. The map clarified how many diverse diseases can be linked to the same underlying protein — i.e., multiple diseases appear to be linked to variations in a single gene and its associated protein products.
Senior author Claudia Langenberg, from the MRC Epidemiology Unit and the Berlin Institute of Health, described one instance in a press release. “An extreme example we discovered of how one protein can be connected to several diseases is the protein Fibulin-3, which we connected to 37 conditions, including hypermobility, hernias, varicose veins, and a lower risk of carpal tunnel syndrome. A likely explanation is atypical formation of elastic fibers covering our organs and joints, leading to differences in elasticity of soft and connective tissues. This is also in line with features that others have observed in mice where this gene was deleted.”
Another example involves a region of the human genome, known as KAT8, that has been linked to Alzheimer’s disease. The specific gene involved was unknown. By analyzing the combined gene and protein data, the researchers identified the gene, PRSS8 (the gene that encodes the protein prostatin) as a candidate gene in Alzheimer’s disease.
Fueling Future Research
The study authors hope similar connections can be made for other diseases. Information from the proteo-genomic map could be used to help researchers zero in on the gene responsible for a disease and experiment with possible therapeutic options based on a very specific protein target. According to Eleanor Wheeler, another researcher on the project: “We envisage that the large amount of information we are sharing with the scientific community will help ongoing and emerging efforts to connect genes to diseases more directly via the encoded protein, thus facilitating accelerated identification of drug targets.”
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