Heterogeneity in Type 2 Diabetes

Educational Objectives

The goal of this program is to improve identification of heterogeneity in type 2 diabetes. After hearing and assimilating this program, the clinician will be better able to:

1. Assess C-peptide levels in diagnosis of type 1 diabetes.
2. Differentiate severe autoimmune diabetes from severe insulin-deficient diabetes.

Summary

Background: in the past, diabetes was categorized into type 1 (T1D) and type 2 (T2D), with distinct characteristics; type 1 involved a lack of insulin production, requiring insulin administration; T2D was characterized by insulin resistance, leading to elevated glucose levels; however, current understanding acknowledges overlap and complexity; the American Diabetes Association simplifies it into 3 types, including 1) T1D (autoimmune beta-cell destruction), 2) T2D (nonautoimmune progressive beta-cell loss with insulin resistance and metabolic syndrome), and 3) a broad category for others; despite this, nuances such as latent autoimmune diabetes in adults (LADA) are not officially recognized, though they exhibit differences from pediatric T1D; the evolving understanding may reveal numerous subtypes within T2D; special types encompass diverse cases such as monogenic diseases, endocrine pancreas disorders (eg, cystic fibrosis, pancreatitis), drug-induced diabetes (eg, glucocorticoids, HIV or AIDS treatment, checkpoint inhibitors for cancer), and gestational diabetes, which may involve T1D or T2D during pregnancy

Type 1 diabetes: defined as an autoimmune process, but islet autoantibodies (IAA) lack 100% predictive value; individuals can have T1D with positive or negative autoantibodies, and the same applies to T2D and Maturity Onset Diabetes of the Young (MODY); autoantibody presence does not conclusively define the condition; C-peptide measurement at T1D diagnosis, even >1 yr, is considered based on clinical need; age is no longer a definitive factor, as younger individuals can develop T2D; diabetic ketoacidosis (DKA) occurrence, once associated mainly with T1D, now also happens in some T2D cases, making it an unreliable diagnostic indicator; monogenic forms can disguise as T1D and people with monogenic diabetes (MD) can have auto antibodies; in older individuals, IAA can be used to diagnose T1D, but it does not necessarily mean they have T1D; in cases suspected to be T1D, start by measuring IAA first, do not include islet cell antibodies (meaningless); check for glutamic acid decarboxylase 65 (GAD65) antibody and if that result is negative, measure islet antigen (IA)-2 and/or a zinc transporter antibody; check for insulin autoantibody if the individual has not been on exogenous insulin; any of the data that involves the diagnosis of T1D in adults comes from White, primarily northern European population, which does not tend to be the population usually seen by physicians

Effects of IAA: if positive, classify them as T1D; however, this does not necessarily correlate with abnormal glucose levels; IAA-negative cases, comprising 5% to 10% of adults with new-onset T1D, require age consideration; while no single feature definitively indicates T1D, younger age at diagnosis is a discriminative factor; age alone is not conclusive, as T1D can occur at any age; additional indicators include lower body mass index (<25 kg/m²), unintentional weight loss, ketoacidosis, and glucose >360 mg/dl at presentation; features such as ketosis without acidosis, osmotic symptoms, or autoimmune-family history are less discriminative; clinical diagnosis is challenging, but if T1D is suspected, evaluation is crucial

Effect of age: for individuals <35 yr of age, assessing for MD is necessary; clinical features, lower A1c (≤7.5), and a family history are common in MD; features such as renal cysts, partial lipoid dystrophy, maternal inherited deafness, or severe insulin resistance without obesity indicate a monogenic cause; a MODY calculator can assess risk, although insurance coverage for MODY gene testing may be challenging

C-peptide levels: in cases suspected of MD, measure C-peptide levels; if <0.6 ng/mL, categorize as T1D; if >0.6 ng/mL, consider MODY; if it does not align with MODY or exhibits features of T2D, especially in patients with metabolic syndrome and diabetes resembling T1D, the classification remains unclear, posing a clinical challenge; in such patients, a trial of non-insulin therapy may be appropriate; after ≥3 yr, a repeat C-peptide aids classification; <0.6 ng/mL, indicates T1D, >1.8 ng/mL suggests T2D, if in between, diagnosis is unknown; current preference is for postprandial C-peptide in insulin users, assessing endogenous insulin production; timing is flexible, emphasizing nonfasting conditions; C-peptide ≥1.8 ng/mL, irrespective of circumstances, suggests likely T2D; <0.24 ng/mL leans toward T1D, but repeat if glucose is low; avoid testing within 2 wk of a hyperglycemic emergency to prevent falsely low results; assess nonfasting C-peptide and glucose levels concurrently

Treatment: tailor treatment based on clinical response, regardless of antibody status or initial insulin needs; observe patients over time, allowing their body to guide therapeutic decisions; a recent study in the New England Journal of Medicine explored low-dose semaglutide in patients with newly diagnosed T1D within 3 mo of diagnosis; despite having autoantibodies, they responded well, according to speaker’s observation; in above study patients’ A1c dropped from 11% to 5.7% after 1 yr; the speaker uses low-dose semaglutide for new-onset T1D in adults, especially when not in DKA, as it provides an alternative to multiple daily insulin injections, offering favorable outcomes for an extended period, although eventual insulin needs may arise; regular follow-ups are crucial, considering potential shifts in glycemic control, especially during stress

Type 2 Diabetes

Ahlqvist et al (2020): in this Swedish study on diabetes phenotypic classification, authors identified 5 subtypes of T2D based on GAD antibodies, age at diagnosis, BMI, HbA1c, and fasting C-peptide levels; these subtypes have broad applicability, with some variations in Asian populations

Classifications: severe autoimmune diabetes (SAID) — positive antigen antibodies, lower BMI, younger age, and higher HbA_1c; still considered a subtype of T2D; severe insulin-deficient diabetes (SIDD) — negative antibodies, younger age, lower BMI, higher HbA_1c, and higher risk for retinopathy; severe insulin-resistant diabetes (SIRD) — characterized by obesity, older age, and marked increase of nephropathy; mild obesity-related diabetes (MOD) — early-onset obesity and good metabolic control when treated; mild age-related diabetes (MARD) — the most common kind, characterized by late onset, good metabolic control, and low risk for complications; different subtypes carry varying risks for complications; for eg, SIRD poses a high risk for nephropathy, warranting risk modification with ACE inhibitors or SGLT2 inhibitors; these individuals progress rapidly to renal disease; there are also differences in the time to coronary events and varying risks for fatty liver disease among subtypes

Wesolowska-Anderson et al (2022): authors conducted a comprehensive analysis, considering 32 characteristics and biomarkers; they identified 4 clusters, including A (lean, insulin-deficient type 2 diabetes), B (obese, insulin-sensitive), C (obese, insulin-resistant), and D (global severe), each with distinct diabetes trajectories and treatment responses; A reflects hard clustering, defining specific subtypes, while B demonstrates soft clustering, encompassing various characteristics, mirroring clinical diversity; genetic analyses affirm T2D as polygenic, with numerous genes contributing; overlap among MD, T1D, and T2D has been observed; genetic complexities persist, even in some MD subtypes

Clinical management: involves individualized approaches, considering the diverse patterns observed in continuous glucose monitoring (CGM); case studies illustrating variability in glycemic responses — include 3 women, 53 to 65 yr of age, all maintaining HbA_1c of ≈7; case study 1 is patient on metformin and glimepiride, who showed a stable and desirable glycemic pattern; in contrast, case study 2, patient also on glimepiride, exhibited a unique oscillating pattern, suggesting potential monogenic influences on insulin secretion; case study 3, patient with an HbA_1c of 7.2, presents another distinct glycemic profile; conclusion — highlighting the heterogeneity of T2D, these examples underscore the need for tailored clinical management; rather than adhering strictly to predefined diabetes types, assess each patient individually, adapting treatments based on evolving needs; utilizing C-peptide levels provides insights into insulin deficiency, while MODY gene testing enhances diagnostic precision

Readings

Ahlqvist E, Prasad RB, Groop L. Subtypes of Type 2 diabetes determined from clinical parameters. Diabetes. 2020;69(10):2086-2093. doi:https://doi.org/10.2337/dbi20-0001. View Article; AmbikaG Unnikrishnan, Kumaran Suganthi, Nupur Lalvani, et al. A practical approach to the diagnosis of type 1 diabetes: An Indian perspective. Chronicle of diabetes research and practice. 2023;2(2):73-73. doi:https://doi.org/10.4103/cdrp.cdrp_19_22. View Article; American Diabetes Association. 1. Improving Care and Promoting Health in Populations: Standards of Medical Care in Diabetes — 2021. Diabetes Care. 2020;44(Supplement 1):S7-S14. doi:https://doi.org/10.2337/dc21-s001. View Article; Clinical science: Type 2 diabetes. Diabetic Medicine. 2020;37(S1):16-18. doi:https://doi.org/10.1111/dme.6_14244. View Article; Hadj Kacem, A. Jerbi, Bibi Twaheerah Allymamod, et al. Characteristics of adult-onset auto-immune type 1 diabetes. The American Journal of the Medical Sciences. 2023;366(1):49-56. doi:https://doi.org/10.1016/j.amjms.2023.04.009. View Article; Holt RIG, DeVries JH, Hess-Fischl A, et al. The management of type 1 diabetes in adults. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2021;44(11). doi:https://doi.org/10.2337/dci21-0043. View Article; Mansour A, Zaboon I, Haddad N. Variables associated with persistence of C-Peptide secretion among patients with Type 1 diabetes mellitus. CHRISMED Journal of Health and Research. 2017;4(3):173. doi:https://doi.org/10.4103/cjhr.cjhr_2_17. View Article; Minasian V, Nazari M. The association between type 1 diabetes and exercise/physical activity and prolongation of the honeymoon phase in patients. Life Sciences. 2023;332:122114. doi:https://doi.org/10.1016/j.lfs.2023.122114. View Article.

Disclosures

For this program, the following relevant financial relationships were disclosed and mitigated to ensure that no commercial bias has been inserted into this content: Dr. Peters is a consultant for Novo Nordisk, Vertex, and Zealand; and has received grant/research support from Abbott, Dexcom, and Insulet. Members of the planning committee reported nothing relevant to disclose.

Acknowledgements

Dr. Peters was recorded at the USC Diabetes Symposium 2023, held on September 16, 2023, in Los Angeles, CA, and presented by the Keck School of Medicine of the University of Southern California. For information on upcoming CME activities from this presenter, please visit keck.usc.edu/cme. Audio Digest thanks the speakers and presenters for their cooperation in the production of this program.

CME/CE INFO

Accreditation:

The Audio- Digest Foundation is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The Audio- Digest Foundation designates this enduring material for a maximum of 1.00 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Audio Digest Foundation is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's (ANCC's) Commission on Accreditation. Audio Digest Foundation designates this activity for 1.00 CE contact hours.

Lecture ID:

FP720602

Expiration:

This CME course qualifies for AMA PRA Category 1 Credits™ for 3 years from the date of publication.

Instructions:

To earn CME/CE credit for this course, you must complete all the following components in the order recommended: (1) Review introductory course content, including Educational Objectives and Faculty/Planner Disclosures; (2) Listen to the audio program and review accompanying learning materials; (3) Complete posttest (only after completing Step 2) and earn a passing score of at least 80%. Taking the course Pretest and completing the Evaluation Survey are strongly recommended (but not mandatory) components of completing this CME/CE course.

Estimated time to complete this CME/CE course:

Approximately 2x the length of the recorded lecture to account for time spent studying accompanying learning materials and completing tests.