The COVID-19 pandemic, caused by SARS-CoV-2, has resulted in a wide range of symptoms, from asymptomatic to severe illness and death. Many clinical risk factors, including age, sex, smoking, socioeconomic status, and comorbidities like obesity, T2D, respiratory diseases, hypertension, CVD, and dementia, have been linked to worse COVID-19 outcomes. Genetic factors also play a significant role, as evidenced by genome-wide association studies (GWAS). While GWAS have identified genetic variants associated with COVID-19 severity, polygenic risk scores (PRS) offer a more comprehensive approach by combining the effects of multiple SNPs. Previous research has shown an association between COVID-19 PRS or PRS for other diseases and COVID-19 severity, but studies on the impact of T2D and T2D PRS on both severity and mortality are limited. This study aimed to systematically investigate the association of T2D and T2D PRS with COVID-19 severity and mortality, considering the effects of SARS-CoV-2 variants and vaccination status.

Numerous studies have established a correlation between various clinical factors and increased COVID-19 severity, leading to hospitalization or death. These factors include older age, male gender, smoking habits, and lower socioeconomic status. The presence of comorbidities such as obesity, T2D, respiratory diseases, hypertension, cardiovascular disease, and dementia has also been consistently linked to poorer COVID-19 outcomes. Furthermore, a substantial body of research points to the significant influence of an individual's genetic makeup on the severity of COVID-19. Large-scale population-based GWAS have revealed the impact of common genetic variants on the severity of COVID-19 symptoms. The integration of these variants into polygenic risk scores (PRS) allows for the identification of individuals at increased risk of severe COVID-19. While several studies have examined the association between COVID-19 PRS or PRS for other diseases and the severity of COVID-19, research on the impact of PRS on COVID-19 mortality, particularly concerning T2D PRS, is relatively scarce, despite T2D being a known risk factor for severe COVID-19.

This study utilized data from 459,119 participants in the UK Biobank, updated to December 2022. The researchers ascertained T2D cases from self-reported data, hospital records, and death data, identifying 3,170 T2D patients (1.8%). SARS-CoV-2 confirmed cases (10,211, 22.1%) were obtained from COVID-19 test data, hospital records, and death data. Participants were classified into seven variant groups based on the proportions of SARS-CoV-2 variants during the study period. Vaccination status was also included. Genome-wide association studies (GWAS) were performed for T2D, SARS-CoV-2 infection, and severe COVID-19 to estimate heritability and genetic correlations. Polygenic risk scores (PRS) for T2D were calculated using a 10-fold cross-validation approach, adjusting for BMI to mitigate confounding effects. The association between T2D, T2D PRS, and COVID-19 severity was assessed using proportional odds models. The effect of T2D and T2D PRS on survival times was investigated using Cox proportional hazards models with time-dependent coefficients for SARS-CoV-2 infection risk. Stratified analyses were conducted for COVID-19, T2D, and T2D PRS groups, and pairwise log-rank tests were performed to identify significant differences in mortality.

The study found a significant association between T2D and increased severity of COVID-19 (OR 2.824, 95% CI 2.644–3.016). A one-unit increase in T2D PRS was also associated with increased odds of severity (OR 1.080, 95% CI 1.050–1.111). The high T2D PRS group had 1.211 times greater odds of severity compared to the low PRS group. Vaccination significantly reduced the odds of COVID-19 severity (OR 0.206, 95% CI 0.193–0.220). Survival analysis revealed that T2D patients had a 2.266 times higher risk of death than controls (HR 2.266, 95% CI 2.164–3.272). The risk of death was significantly higher for SARS-CoV-2-infected individuals across all time intervals, with the highest risk observed in the early variants. The risk of death was significantly lower in the vaccinated group (HR 0.198, 95% CI 0.186–0.210). Analyses restricted to SARS-CoV-2-infected individuals showed similar results. Concordance indices (C-indices) for the survival models were 0.770 for T2D and 0.755 for T2D PRS groups in the Survival-All model and 0.791 and 0.795 respectively in the Survival-COVID-19 model. Sensitivity analysis using DIAGRAM consortium data showed similar results. Partitioned T2D PRS analysis indicated that only PRS for traits associated with insulin resistance (obesity, lipodystrophy, liver/lipid metabolism) were significantly related to COVID-19 severity, not those related to insulin production.

The findings of this study highlight the significant association between T2D and its genetic predisposition with increased severity and mortality of COVID-19. The use of T2D PRS offers a valuable tool for identifying individuals at increased risk, even in the absence of diagnosed T2D. These results underscore the importance of considering T2D status and genetic susceptibility in managing COVID-19, suggesting that early detection and management could improve outcomes. The significant protective effect of vaccination further reinforces the importance of vaccination programs. The identification of specific genetic factors and pathways involved in the interplay between T2D and COVID-19 warrants further investigation to develop targeted therapies.

This study demonstrates a strong association between T2D, its genetic susceptibility (as measured by T2D PRS), and both the severity and mortality of COVID-19. The findings highlight the potential utility of T2D PRS in risk stratification for COVID-19 patients and emphasize the need for personalized management strategies based on individual genetic risk profiles. Future research should focus on elucidating the underlying biological mechanisms and exploring the potential for targeted interventions.

The study's reliance on observational data precludes establishing causal relationships. The study population is primarily of European ancestry, limiting the generalizability of findings to other populations. The use of self-reported data for some variables introduces potential biases. Furthermore, the study design cannot fully capture the complex interplay of all factors influencing COVID-19 outcomes.