Link between amino acid and a range of common diseases could help predict personal risk – Innovita Research

Link between amino acid and a range of common diseases could help predict personal risk

One of the first population-scale studies on how common genetic traits are influenced by variations in the DNA of mitochondria, the powerhouses of human cells, has been completed by scientists at the Wellcome Sanger Institute, the University of Cambridge, EMBL’s European Bioinformatics Institute (EMBL-EBI), and their collaborators.

The team identified associations between mtDNA variants and an amino acid, N-formylmethionine (fMet), and effects of fMet on the risk of developing a range of common, late-onset illnesses.

Image credit: Gerd Altmann via Pixabay, free licence

The study, published in Nature Medicine found that higher fMet levels are associated with increased risk of a wide range of late-onset diseases and all-cause mortality, demonstrating fMet’s potential as a biomarker of ageing and disease risk, as well as the importance of research into mitochondrial DNA variants.

Mitochondria are organelles that are found in the cells of all complex organisms. They perform a number of vital biological functions, including the production of around 90 per cent of the energy that cells need to function. Mitochondria are unique in that they have their own genetic code, knowns as mitochondrial DNA (mtDNA), which is distinct from the DNA contained in the nucleus of every cell in an organism’s body1. mtDNA is passed on from mother to child.

Many common diseases are influenced by mitochondrial damage or disruption, including genetic diseases such as diabetes, heart disease and depression that are influenced by mutations in mtDNA.

Over time, the accumulation of mutations in mtDNA leads to distinct lineages in the population, known as haplogroups, which confer particular traits. Previous research has shown that haplogroup Uk, found in 10 per cent of the European population, is protective against diseases such as Parkinson’s Disease and ischaemic stroke (IS).

In this study, two large-scale datasets were analysed to look for associations between genetic variants in mtDNA and thousands of common molecular traits such as blood cell counts and plasma proteins, in order to understand the molecular mechanisms behind mtDNA associations with diseases.

In the INTERVAL dataset of up to 16,000 participants, the researchers identified significant associations between levels of fMet and mtDNA variants in haplogroups Uk and H32. The team then verified these associations using cellular models. When fMet levels were measured in a cohort of ischaemic stroke patients, they found lower fMet levels compared to those in a healthy control group.

The researchers then analysed data from EPIC-Norfolk, a study that tracked the health of participants over a 20-year period, to ask whether differences in fMet between individuals were associated with a wider-range of late onset diseases. In contrast to ischaemic stroke, higher fMet levels were associated with increased risk of illnesses such as kidney disease and heart failure.

Source: Sanger Institute