The risk factors for type 2 diabetes are both environmental and genetic, and while researchers have identified many genetic risk factors thus far, the largest ever genome-wide association study of people with type 2 diabetes has discovered even more locations of risk variants than before.
It has also identified different clusters of variants adding to the risk of developing the disease, revealing more about the different mechanisms underpinning the disease, reports Medical News Today.
Genome-wide association studies have been possible since the human genome was first sequenced in 2003, and coupled with the advent of cell maps and genomic libraries, it is now possible for researchers to identify not only the variants that could affect risk, but also understand what they control and the cellular mechanisms in which they play a role.
What genetic markers can teach us about widespread conditions, like type 2 diabetes, was the focus of global researchers recently, whose findings of a large study was published in Nature.
Genetics and type 2 diabetes
Type 2 diabetes is characterised by reduced insulin sensitivity of cells, meaning they are less able to take up glucose in the bloodstream, leading to chronically elevated blood glucose levels and increasing the risk of complications like cardiovascular disease and nerve damage.
There are many known risk factors for type 2 diabetes, including heredity, being of African or Asian ancestry, high blood pressure, obesity and polycystic ovary syndrome (PCOS), among others.
Genome-wide association studies have revealed some other interesting links between type 2 diabetes and other conditions. One showed that a number of genetic risk variants were shared by type 2 diabetes and depressive symptoms.
New genetic variants tied to complications
The Nature research is the largest genome-wide association study of type 2 diabetes to date, and included genomic data from 2 535 601 individuals, of whom 428 452 had type 2 diabetes.
It featured data from six ancestral groups: European, East Asian, African American, South Asian, South African and Hispanic with American, West African and European ancestry.
However, most participants were still predominantly European in ancestry, with 60% of the cohort comprising this group.
The global consortium of researchers discovered 1 289 genetic variants, at 611 areas of the genome known as loci, of which 145 were new discoveries.
They then mapped these variants to 37 cardiometabolic phenotypes, including waist-height ratio, liver fat percentage, LDL and HDL cholesterol, blood pressure, fasting insulin and others, to discover if certain variants were associated with certain phenotypes, or traits.
They then identified eight non-overlapping “clusters” characterised by subsets of variants associated with certain cardiometabolic traits.
These clusters included beta-cell dysfunction, obesity, and liver and lipid (fat) metabolism, among others, and also characterised whether people with these clusters exhibited increased or decreased insulin secretion, or increased or decreased insulin sensitivity.
One of the corresponding authors, Dr Benjamin Voight, of the University of Pennsylvania–Perelman School of Medicine, said: “It turns out the genetic variants that contributed to our clusters do not overlap with one another – so patients have their disease risk influenced to different extents by these clusters.”
Can genetics predict cardiovascular outcomes in diabetes?
Next, researchers looked at whether the eight clusters they had determined could be used to predict cardiovascular disease outcomes in these participants.
They developed polygenic scores in a further 279 552 individuals for whom they had genomic data, including 30 288 with type 2 diabetes, and investigated whether there was an association with cardiovascular outcomes and genetic variant clusters.
The most significant associations discovered showed risk of hospitalisation for heart failure was increased by 15% in people positive for the obesity cluster of genetic variants.
They also found that having the beta cell pro-insulin positive cluster of genetic variants decreased the risk of hospitalisation for heart failure by 10%. This cluster was also associated with 10% lower risk of cardiovascular death and 6% lower risk of major cardiovascular events and heart attack.
“I think the potential doorway that this type of work opens is where one can start to dissect how different genetic ‘subtypes’ of type 2 diabetes could modulate risk to complications of diabetes – either a little or a lot,” said Voight. “Moreover, genetic subtyping might also give us better clues about the underlying genes and biology that contribute most importantly to those complications.”
Study details
Genetic drivers of heterogeneity in type 2 diabetes pathophysiology
Ken Suzuki, Konstantinos Hatzikotoulas, Eleftheria Zeggini et al.
Published in Nature on 19 February 2024
Abstract
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2 535 601 individuals (39.7% not of European ancestry), including 428 452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10−8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279 552 individuals of diverse ancestry, including 30 288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimise global access to genetically informed diabetes care.
Nature article – Genetic drivers of heterogeneity in type 2 diabetes pathophysiology (Open access)
See more from MedicalBrief archives:
Nine-year US study gives clue to predicting who gets diabetes
Genetic link between blood sugar levels, headaches – Australian study
Type 2 diabetes study shows ‘obesity paradox’
Evidence for changing the way type 2 diabetes is treated
CVD the leading cause of death in patients with type 2 diabetes