Research led by scientists at St George’s, University of London has discovered 119 areas in the genome that help to determine the size and shape of blood vessels at the back of the eye, and that an increase in ‘twisting’ of the arteries could cause high blood pressure and heart disease.

It’s relatively easy to take a high-resolution digital image of the back of the eye, allowing medical professionals and researchers to visualize the retina and its associated blood vessels and nerves. The eyes can act as a ‘window’ into the body, allowing researchers to directly study the characteristics of these blood vessels and gain information about the body.

Scientists have previously shown that the shape and size of blood vessels on the retina are associated with health conditions including high blood pressure, heart disease, diabetes, and obesity. However, until now, little was known about how genetics play a role in determining the architectural characteristics of these blood vessels.

Researchers studied retinal images from nearly 53,000 people who were enrolled in a large study called the UK Biobank.

They applied artificial intelligence (AI) technology to the images to quickly and automatically distinguish between the different types of blood vessels (arteries and veins), and to measure blood vessel width and the extent to which the vessels twist and turn.

The team then used a technique called a genome-wide association study (GWAS) to determine whether there were similarities in the DNA of people with similar blood vessel characteristics. They carried this out on the genetic data of 52,798 UK Biobank members.

The team then repeated the analyses on 5000 people who were part of the EPIC-Norfolk’s Eye Study. Together with the UK Biobank, they identified 119 sections of the genome that are associated with retinal blood vessel shape and size characteristics – more than any previous study. Of the 119 sections found, 89 regions were linked to arterial twisting.

The level of twisting and turning of retinal arteries was the feature that was most strongly genetically determined. A higher level of twisting to the arteries also appeared to cause high diastolic blood pressure and heart disease. Diastolic blood pressure is a measure of the pressure in the arteries when the heart is between beats.

Professor Christopher Owen, Head of Chronic Disease Epidemiology at St George’s, University of London said: “It had been thought that high blood pressure might cause twisted arteries, but our work unveils that it’s the other way around. This genetic information is a vital piece of the puzzle in our understanding and could pave the way for new treatments in the future.

“Retinal imaging is already a mainstay in high-street optometrists. Our AI analysis of these images as part of routine eye checks could easily be done as part of a health check to identify those at high risk of developing high blood pressure or heart disease and in need of early intervention.”

The study was funded by the Medical Research Council and the British Heart Foundation.

With a big assist from artificial intelligence and a heavy dose of human touch, Tim Cernak’s lab at the University of Michigan made a discovery that dramatically speeds up the time-consuming chemical process of building molecules that will be tomorrow’s medicines, agrichemicals, or materials.

The discovery, published in the Feb. 3 issue of Science, is the culmination of years of chemical synthesis and data science research by the Cernak Lab in the College of Pharmacy and Department of Chemistry.

The goal of the research was to identify key reactions in the synthesis of a molecule, ultimately reducing the process to as few steps as possible. In the end, Cernak and his team achieved the synthesis of a complex alkaloid found in nature in just three steps. Previous syntheses took between seven and 26 steps. 

“Making a chemical structure that has atoms in just the right place to give you efficacious and nontoxic medicines, for instance, is tricky,” said Cernak, assistant professor of medicinal chemistry and chemistry. “It requires a chemical synthesis strategy grounded in the chemical building blocks you can actually buy and then stitch together using chemical reactions.”

The accomplishment has powerful implications for speeding up the development of medicines.

Cernak compared the construction of these complex molecules to playing chess. You need to orchestrate a series of moves to get to the end of the game. While there’s a near-infinite number of possible moves, there’s a logic that can be followed.

“We developed a logic here, based on graph theory, to get to the end as quickly as possible,” he said.

Cernak and colleagues used SYNTHIA Retrosynthesis Software, which provides scientists with a database of pathways, or steps, and formulas for millions of molecular structures. This gave the team an enormous amount of computational synthesis data to play with.

Using an algorithm they developed to curate the data, the researchers identified the steps along the pathway that was high impact, or key steps, and the steps that were making progress toward completing the synthesis but ultimately inefficient for the whole process.

“We hope this research can lead to better medicines,” Cernak said. “So far, we have been limited in the molecular structures we can quickly access with chemical synthesis.”

Co-authors include Yingfu Lin, a senior research fellow in pharmacy; Rui (Sam) Zhang, a doctoral student in chemistry; and Di Wang, a doctoral student in pharmacy.