Rare variant analysis reveals genetic spectrum of monogenic diabetes genes

Genetic research uncovers a continuum between diabetes forms, offering insights for precision medicine.

Study: Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes. Image Credit: Billion Photos/Shutterstock.com

In a recent study published in Nature Genetics, researchers investigated the association of rare genetic variants with type 2 diabetes, focusing on the variants associated with monogenic diabetes. By analyzing genetic data from thousands of cases of type 2 diabetes and controls, they identified genetic variants that have a significant impact on type 2 diabetes risk, providing insights into variant pathogenicity and genetic risk assessment.

Background

Type 2 diabetes is a complex condition with known genetic and environmental influences, with genome-wide association studies (GWAS) having identified numerous common variants associated with increased disease risk. However, most GWAS focus on common variants, overlooking the potential impact of rare genetic variations that might play substantial roles, especially in individuals of non-European ancestry who remain underrepresented in genetic research.

Monogenic diabetes is rare and caused by mutations in a single gene, which can have very large effect sizes and can carry significantly high risks. However, the limited evidence on their effects across diverse populations has also led to these variants not being fully incorporated into the diagnostic and clinical decision-making process. Consequently, there is a need for a systematic evaluation of the role of rare variants and their potential interplay with broader genetic risk factors of type 2 diabetes. 

About the study

In the present study, the team conducted a large-scale meta-analysis on type 2 diabetes cases and controls using imputed data from the Trans-Omics for Precision Medicine or TOPMed reference panel from the National Heart, Lung, and Blood Institute and whole-genome sequencing data.

They gathered data from over 51,000 type 2 diabetes cases and more than 370,000 controls across three major cohorts — the United Kingdom (UK) Biobank, the Genetic Epidemiology Research on Adult Health and Aging cohort, and the Mass General Brigham Biobank — and combined it with whole-genome sequences from the All of Us research program. The focus of the analyses was on variants that had minor allele frequencies as low as 0.00005.

Furthermore, the study examined approximately 1,634 variants within 22 genes that had known associations with monogenic diabetes and evaluated their link to the risk of type 2 diabetes. For this, the researchers used a logistic regression model with cohort weighting, while rigorous quality control measures were applied to ensure robust variant imputation, particularly for rare and low-frequency variants.

The study also analyzed the interplay of these rare variants with polygenic risk scores (PRS) constructed from common variants to examine the extent to which a polygenic background could modify the disease risk posed by each variant.

Additionally, the researchers used external cohorts to replicate the findings and verify the consistency of rare variant effects on type 2 diabetes risk, particularly in populations of diverse ancestries. Further analyses included testing the functional effects of certain identified variants, using techniques such as luciferase reporter assays to measure the impact on gene regulation.

Results

The study found that specific rare variants within monogenic diabetes genes are significantly associated with increased type 2 diabetes risk, with certain variants showing very high levels of diabetes risk. The researchers identified 12 new variants associated with type 2 diabetes, including a variant near the leptin-producing gene LEP that was more common in African and African American populations, which showed a fourfold increase in type 2 diabetes risk.

Another variant in the hepatocyte nuclear factor 4 alpha gene HNF4A, which had previously been implicated in monogenic diabetes, was observed to increase the risk of type 2 diabetes by eightfold, expanding its potential impact beyond its known association with maturity-onset diabetes in young people.

Furthermore, among the variants analyzed, several rare variants were further assessed for their pathogenicity, and the findings suggested that about 21% of variants with unclear significance might be benign based on lack of association with type 2 diabetes risk.

Notably, variants in the hepatocyte nuclear factor-1 alpha (HNF1A) and glucokinase (GCK) genes were associated with five- and eight-fold increases in type 2 diabetes risk, respectively. The study also indicated that polygenic risk scores (PRS) could modify the impact of these rare variants, with individuals carrying high PRS values exhibiting even greater disease risk.

Conclusions

Overall, this study highlighted the value of large-scale imputed data and whole-genome sequences in identifying and assessing rare variants linked to type 2 diabetes risk. Moreover, the framework used in the study also supported the integration of rare variant effects into precision medicine for diabetes, emphasizing the combined impact of rare genetic variants and broader polygenic factors on disease susceptibility.