Utility of Polygenic Scores for Differentiating Diabetes Diagnosis Among Patients With Atypical Phenotypes of Diabetes

CONTEXT

Misclassification of diabetes type occurs in people with atypical presentations of type 1 diabetes (T1D) or type 2 diabetes (T2D). Although current clinical guidelines suggest clinical variables and treatment response as ways to help differentiate diabetes type, they remain insufficient for people with atypical presentations.

OBJECTIVE

This work aimed to assess the clinical utility of 2 polygenic scores (PGSs) in differentiating between T1D and T2D.

METHODS

Patients diagnosed with diabetes in the UK Biobank were studied (N = 41 787), including 464 (1%) and 15 923 (38%) who met the criteria for classic T1D and T2D, respectively, and 25 400 (61%) atypical diabetes. The validity of 2 published PGSs for T1D (PGST1D) and T2D (PGST2D) in differentiating classic T1D or T2D was assessed using C statistic. The utility of genetic probability for T1D based on PGSs (GenProb-T1D) was evaluated in atypical diabetes patients.

RESULTS

The joint performance of PGST1D and PGST2D for differentiating classic T1D or T2D was outstanding (C statistic = 0.91), significantly higher than that of PGST1D alone (0.88) and PGST2D alone (0.70), both P less than .001. Using an optimal cutoff of GenProb-T1D, 23% of patients with atypical diabetes had a higher probability of T1D and its validity was independently supported by clinical presentations that are characteristic of T1D.

CONCLUSION

PGST1D and PGST2D can be used to discriminate classic T1D and T2D and have potential clinical utility for differentiating these 2 types of diseases among patients with atypical diabetes.

Association of Diabetes Subgroups With Race/Ethnicity, Risk Factor Burden and Complications: The MASALA and MESA Studies

INTRODUCTION

There are known disparities in diabetes complications by race and ethnicity. Although diabetes subgroups may contribute to differential risk, little is known about how subgroups vary by race/ethnicity.

METHODS

Data were pooled from 1293 (46% female) participants of the Mediators of Atherosclerosis in South Asians Living in America (MASALA) and the Multi-Ethnic Study of Atherosclerosis (MESA) who had diabetes (determined by diabetes medication use, fasting glucose, and glycated hemoglobin [HbA1c]), including 217 South Asian, 240 non-Hispanic white, 125 Chinese, 387 African American, and 324 Hispanic patients. We applied k-means clustering using data for age at diabetes diagnosis, body mass index, HbA1c, and homeostatic model assessment measures of insulin resistance and beta cell function. We assessed whether diabetes subgroups were associated with race/ethnicity, concurrent cardiovascular disease risk factors, and incident diabetes complications.

RESULTS

Five diabetes subgroups were characterized by older age at diabetes onset (43%), severe hyperglycemia (26%), severe obesity (20%), younger age at onset (1%), and requiring insulin medication use (9%). The most common subgroup assignment was older onset for all race/ethnicities with the exception of South Asians where the severe hyperglycemia subgroup was most likely. Risk for renal complications and subclinical coronary disease differed by diabetes subgroup and, separately, race/ethnicity.

CONCLUSIONS

Racial/ethnic differences were present across diabetes subgroups, and diabetes subgroups differed in risk for complications. Strategies to eliminate racial/ethnic disparities in complications may need to consider approaches targeted to diabetes subgroup.

Risk of cardiac autonomic neuropathy in latent autoimmune diabetes in adults is similar to type 1 diabetes and lower compared to type 2 diabetes: A cross-sectional study

AIMS

Microvascular complications' risk differs between people with latent autoimmune diabetes in adults (LADA) and people with type 2 diabetes. We aimed to investigate whether the prevalence of cardiac autonomic neuropathy, a life-threatening complication of diabetes, also varies depending on diabetes type.

METHODS

In this cross-sectional study, 43 adults with LADA, 80 with type 1 diabetes and 61 with type 2 diabetes were screened for cardiac autonomic neuropathy with recommended tests. Logistic regression models were used to test differences between diabetes types adjusting for confounders.

RESULTS

Cardiac autonomic neuropathy was diagnosed in 17 (40%) participants with LADA, 21 (26%) participants with type 1 diabetes and 39 (64%) participants with type 2 diabetes (p < 0.001). The odds ratio (OR) for cardiac autonomic neuropathy in type 1 diabetes and in type 2 diabetes compared to LADA were 0.54 (95% CI: 0.25-1.20, p-value: 0.13) and 2.71 (95% CI: 1.21-6.06, p-value 0.015) respectively. Smoking (_adj OR 3.09, 95% CI: 1.40-6.82, p-value: 0.005), HDL cholesterol (_adj OR 0.29, 95% CI: 0.09-0.93, p-value: 0.037) and hypertension (_adj OR 2.11, 95% CI: 1.05-4.24, p-value: 0.037) were independent modifiable risk factors for cardiac autonomic neuropathy. Differences among diabetes types did not change after correction for confounders.

CONCLUSIONS

This is the first study offering a comparative evaluation of cardiac autonomic neuropathy among LADA, type 1 and type 2 diabetes, showing a lower risk of cardiac autonomic neuropathy in LADA compared to type 2 diabetes and similar compared to type 1 diabetes. This disparity was not due to differences in age, metabolic control or cardiovascular risk factors.

Precision medicine in diabetes: an opportunity for clinical translation

Metabolic disorders present a public health challenge of staggering proportions. In diabetes, there is an urgent need to better understand disease heterogeneity, clinical trajectories, and related comorbidities. A pressing and timely question is whether we are ready for precision medicine in diabetes. Some biological insights that have emerged during the last decade have already been used to direct clinical decision making, especially in monogenic forms of diabetes. However, much work is necessary to integrate high-dimensional explorations into complex disease architectures, less penetrant biological alterations, and broader phenotypes, such as type 2 diabetes. In addition, for precision medicine to take hold in diabetes, reproducibility, interpretability, and actionability remain key guiding objectives. In this review, we examine how mounting data sets generated during the last decade to understand biological variability are now inspiring new venues to clarify diabetes nosology and ultimately translate findings into more effective prevention and treatment strategies.

Phosphotyrosine-protein-phosphatase and diabetic disorders. Further studies on the relationship between low molecular weight acid phosphatase genotype and degree of glycemic control

We have studied a new sample of 276 NIDDM patients from the population of Penne (Italy). Comparison of the new data with those of 214 diabetic pregnant women from the population of Rome reported in a previous paper has shown that the pattern of association between low molecular weight acid phosphatase genotype and degree of glycemic control is similar in the two classes of diabetic patients. Among nonobese subjects the proportion of ACP1*A (the allele showing the lowest enzymatic activity) is lower in diabetic patients with high glycemic levels (mean value greater than 8.9 mmol/l) than in diabetic patients with a low glycemic level (mean value less than 8.9 mmol/l). Among obese subjects no significant association is observed between glycemic levels and ACP1. Among nonobese subjects the concentration of f isoform of ACP1 is higher in patients showing a high glycemic level than in patients showing a low glycemic level. No significant difference is observed for s isoform.