Autoantibodies against beta cells to predict early insulin requirements in pediatric patients with clinically diagnosed type 2 diabetes

Abstract

BACKGROUND

Autoimmunity has emerged as a probable disease modifier in patients with clinically diagnosed type 2 diabetes mellitus (T2DM), that is, patients who have insulin resistance, obesity, and other cardiovascular risk factors, suggesting that the presence of glutamic acid decarboxylase (anti-GAD65), islet antigen 2 (anti-IA2), and zinc transporter 8 (anti-Zn8T) antibodies could have deleterious effects on beta cell function, causing failure and earlier requirement for insulin treatment.

AIM

To evaluate anti-GAD65, anti-IA2 and anti-Zn8T as predictors of early insulin requirement in adolescents with a clinical diagnosis of T2DM.

METHODS

This was a case–control study in patients with clinically diagnosed with T2DM (68 cases and 64 controls with and without early insulin dependence respectively), male and female, aged 12–18 years. Somatometry, blood pressure, glucose, insulin, C-peptide, glycated hemoglobin A1c, and lipid profiles were assessed. ELISA was used to measure anti-GAD65, anti-IA2, and anti-Zn8T antibodies. Descriptive statistics, Pearson's χ² test, Student's t test, and logistic regression was performed. P < 0.05 was considered statistically significant.

RESULTS

There were 132 patients (53.8% female), with a mean age was 15.9 ± 1.3 years, and there was a disease evolution time of 4.49 ± 0.88 years. The presence of anti-GAD65, anti-IA2, and anti-Zn8T positivity was found in 29.5%, 18.2%, and 15.9%, respectively. Dividing the groups by early or no insulin dependence showed that the group with insulin had a higher frequency of antibody positivity: anti-GAD65 odds ratio (OR): 2.42 (1.112–5.303, P = 0.026); anti-IA2: OR: 1.55 (0.859–2.818, P = 0.105); and anti-Zn8T: OR: 7.32 (2.039–26.279, P = 0.002).

CONCLUSION

Anti-GAD65 positivity was high in our study. Anti-GAD65 and anti-Zn8T positivity showed a significantly depleted beta cell reserve phenotype, leading to an increased risk of early insulin dependence.

Key Words: Diabetes; Obesity; Adolescents; Autoimmunity; Beta cell; Insulin requirements

Core tip: We found that adolescent patients with type 2 diabetes mellitus (T2DM) showed a more aggressive phenotype of the disease, with a significant depletion of beta cell function, and where antibodies against pancreatic beta cells were associated with lower levels of insulin and C-peptide conferring a higher risk of early dependence on exogenous insulin. Therefore, in a pediatric patient with T2DM phenotype, the determination of pancreatic antibodies can be a clinical tool to predict early insulin requirements, leading to closer control of the disease to avoid chronic complications.

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is characterized by a state of chronic hyperglycemia secondary to resistance to the action of insulin, with a progressive defect in beta cell function causing relative or absolute insulin deficiency[1,2]. The diagnosis of T2DM includes confirmation of the presence of DM according to the criteria of the American Diabetes Association, and the subsequent determination of the type of diabetes according to the clinical and biochemical phenotype[3]. Also, clinical data that may support the presence of T2DM are: Being overweight or obese, acanthosis nigricans, dyslipidemia, hypertension, and fatty liver. The rapid progression of T2DM is significantly influenced by genetic factors, with over 130 variants in different susceptibility and candidate genes identified as being linked to the disease[4]. However, due to the growing epidemic of obesity, these data can also be found in type 1 diabetes mellitus (T1DM), with the evolution of the diabetes being what can sometimes define the specific type in each individual[5].

The mechanisms involved in the pathophysiology of T2DM include 11 metabolic pathways that mediate hyperglycemia, which contribute to beta cell dysfunction; with immunological dysregulation and inflammation being recently described mechanisms that perpetuate elevated glucose levels[6,7]. Autoimmune destruction of the pancreatic beta cells is the main mechanism of damage in T1DM; however, these autoimmune markers may be also present in 15%–40% of patients with clinically diagnosed T2DM[8,9].

Various studies, primarily in the adult population, have connected the presence of autoantibodies with greater damage at the beta cell level, observing an earlier start of insulin treatment and representing a possible predictive marker of early insulin initiation[10-12].

Autoantibodies for glutamic acid decarboxylase (anti-GAD65), islet antigen 2 (anti-IA2), and zinc transporter 8 (anti-Zn8T) are used as markers for diagnosis and prognosis of T1DM by ELISA. The objective of the study was to evaluate the presence of anti-GAD65, anti-IA2, and anti-Zn8T antibodies as predictors of early insulin requirements in adolescents with T2DM.

MATERIALS AND METHODS

Study design and setting

A retrospective case–control study was performed in adolescents from the clinic for patients living with diabetes at the Federico Gómez Children´s Hospital in Mexico, from August 2018 to January 2023.

Participants

Inclusion criteria were as follows: (1) Adolescents aged 12–18 years; (2) Male or female sex; (3) Clinically diagnosed with T2DM according to their biochemical and clinical phenotype (overweight/obesity, acanthosis nigricans, and insulin resistance) with C-peptide at diagnosis of ≥ 0.5 ng/mL; (4) Early insulin dependence (cases): Patients requiring continuous insulin administration for at least 3 years after diabetes onset. The insulinization criterion was patients with poor metabolic control, defined by glycated hemoglobin A1c (HbA1c) ≥ 9.0%, and insulin treatment was with a basal-bolus scheme or basal insulin; (5) No insulin dependence (controls): Patients with treatment with biguanides (metformin), glucagon-like peptide 1 analogs (liraglutide), or only lifestyle modifications; and (6) Ketoacidosis and improved glycemic control: Patients who presented with ketoacidosis at the onset of diabetes and requiring insulin administration for < 4 mo due to improvement in glycemic control. Exclusion criteria were as follows: (1) Family history of early-onset diabetes: Patients with a history of diabetes before the age of 25 years in first and second-degree relatives, to rule out maturity-onset diabetes of the young; and (2) Diabetes duration: Number of years from diabetes onset until the measurement of antibodies was not specified as a criterion for inclusion or exclusion.

Anthropometric, biochemical, and immunological measurements

To perform the anthropometry, patients were evaluated with as little clothing as possible and without footwear. Weight assessment was performed with a digital scale (Seca 884, Hamburg, Germany) with an accuracy of 0.1 kg. Height was determined using a stadiometer (Seca 225) with an accuracy of 0.1 cm. Body mass index (BMI) was calculated using both of the aforementioned measurements. Waist circumference was measured at the end of expiration with a flexible nonelastic tape with an accuracy of 0.1cm (Seca 200), in a standing position, on the point mid-way between the lower edge of the last rib and the iliac crest. Blood pressure (BP) was measured with a mercury sphygmomanometer on the right arm held at the level of the heart, after a 5-min rest, with the subject in a sitting position, using a cuff appropriate for the age and size of the patient. Three BP measurements were made using the first and fifth Korotkoff sounds with the nearest reading every 2 mmHg, obtaining an average of the measurements.

After a 12-h fast, blood samples were obtained to measure: Glucose (Dimension RXL MAX; SiemensEuro, UK), insulin (chemiluminescence, IMULITE 1000; Siemens, Euro-DPC, Llanberis, UK), C-peptide (chemiluminescence, IMULITE 1000), HbA1c (Dimension RXL MAX), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and triglycerides (Hitachi 902, Tokyo, Japan). Low-density lipoprotein-cholesterol (LDL-C) measurement was calculated using the Friedewald formula (TC in mg/dL, HDL-C in mg/dL, triglycerides in mg/dL/5). To assess pancreatic reserve, the homeostatic model assessment of beta cell function (HOMA-β) index [(fasting insulin in mIU/mL × 20]/(fasting glucose in mmol/L 3.5)] was obtained.

Qualitative and quantitative determinations of anti-GAD65, anti-IA2, and anti-Zn8T antibodies were performed using ELISA. For anti-Zn8T the KRONUS kit (KR7730-96),Kronus, Star, ID, USA was used, and values ≥ 15 IU/mL were considered positive. The IBL International Kit (RE70391) (Tecan Trading, Switzerland) was used to measure anti-IA2Ab and anti-GAD65Ab, taking as positive the samples that had an optical density (OD) greater than that of the minimum control [calibrator cut-off (cc)], and as negative those less than that of the minimum control OD value. Absorbances were read at 450 nm using the Varioskas TM LUX multimode microplate reader from ThermoFisher Scientific (Waltham, MA, USA).

Statistical analysis

Descriptive statistical analysis (measures of dispersion and central tendency) of the demographic, clinical, biochemical, and immunological variables was performed. The normal distribution of variables was determined by the Kolmogorov–Smirnov test, expressing them in means and standard deviation, and variables without normal distribution were expressed in medians and minimum and maximum ranges. The Student t test or Mann–Whitney U test was used for independent samples depending on the distribution of the variables, and Pearson's χ² test was used for categorical variables. Logistic regression was performed to determine the odds ratio (OR) for early insulin dependence. SPSS version 23.0 was used, and P < 0.05 was considered statistically significant.

RESULTS

A total of 132 patients (53.8% female) were included in the study, with a mean age of 15.9 ± 1.3 years. The duration of diabetes was 4.49 ± 0.88 years. When dividing the groups by early insulin dependence, no significant differences were observed in age and sex, however, in terms of diabetes duration, a difference was shown (Table 1).

Table 1 Demographic characteristics by insulin dependence, mean ± SD.

Variable	Total (n = 132)	No insulin dependence (n = 64)	Insulin dependence (n = 68)	P value
Sex (M) (%)	71 (53.8)	34 (53.1)	37 (54.4)	0.51
Age (years)	15.9 ± 1.3	15.98 ± 1.3	15.9 ± 1.4	0.85
Weight (kg)	73.4 ± 10.1	72.2 ± 10.4	74.5 ± 9.8	0.06
Height (cm)	165.3 ± 6.4	164.7 ± 6.5	165.9 ± 6.3	0.11
BMI (kg/m2)	25.2 ± 3.5	24.9 ± 3.8	25.5 ± 3.1	0.09
BMI z-score	1.39 ± 0.44	1.35 ± 0.46	1.43 ± 0.41	0.42
WC (cm)	87.4 ± 9.9	85.1 ± 10.6	89.1 ± 8.9	0.22
WHtR	0.52 ± 0.05	0.52 ± 0.06	0.53 ± 0.04	0.08
SBP (mm/Hg)	111.6 ± 11.2	110.3 ± 10.7	112.9 ± 11.6	0.05
DBP (mm/Hg)	72.0 ± 8.5	70.6 ± 7.8	73.3 ± 9.0	0.1
DD (years)	4.49 ± 0.88	4.73 ± 0.09	4.27 ± 0.70	0.03

BMI: Body mass index; WC: Waist circumference; WHtR: Waist-to-height ratio; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; DD: Diabetes duration in years.

In the metabolic variables, no differences were observed in terms of TC, HDL-C, LDL-C, and triglycerides. Patients with insulin dependence show metabolic decontrol with higher HbA1c. C-peptide reserve was lower in the group with early insulin dependence with a decreased HOMA-β (Table 2).

Table 2 Metabolic characteristics by insulin dependence, mean ± SD.

Variable	Total (n = 132)	No insulin dependence (n = 64)	Insulin dependence (n = 68)	P value
TC (mg/dL)	175.9 ± 48.3	164.2 ± 37.4	186.9 ± 54.8	0.54
HDL-C (mg/dL)	44.1 ± 9.3	44.6 ± 7.5	43.6 ± 10.8	0.11
LDL-C (mg/dL)	107.1 ± 41.1	93.3 ± 28.8	118.3 ± 47.5	0.1
TG (mg/dL)	158.5 ± 21.1	148.5 ± 14.0	187.9 ± 19.9	0.18
Fasting glucose (mmol/L)	10.95 ± 0.55	7.62 ± 0.37	14.07 ± 0.51	0.08
HbA1c (%)	8.8 ± 2.9	6.7 ± 1.6	10.8 ± 2.3	0.001
Insulin (mUI/mL)	11.4 ± 7.7	12.7 ± 9.6	10.3 ± 5.0	0.3
C- peptide (ng/dL)	1.4 ± 1.3	2.53 ± 1.2	0.41 ± 0.36	0.001
HOMA-β	85.38 ± 16.6	125.5 ± 15.6	50.9 ± 16.8	0.022

TC: Total cholesterol; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein-cholesterol; TG: Triglycerides; HbA1c: Glycated hemoglobin A1c; HOMA-β: Homeostatic model assessment of beta cell function.

When dividing the groups by the presence of autoimmunity, significant differences were observed between the weight and height of the group positive for antibodies, with their values being lower compared to the group without autoimmunity (Table 3).

Table 3 Demographic characteristics by autoimmunity.

Variable	At the time of diagnosis	NID		P value	At the time of diagnosis	ID		P value
	NID (n = 64)	(Ab+) (n = 16)	(Ab-) (n = 48)		ID (n = 68)	(Ab+) (n = 27)	(A-) (n = 41)
Sex (F) (%)		8 (50.0)	26 (54.1)	0.77		16 (59.2)	21 (51.2)	0.51
Age (years)	12.9 ± 0.7	15.9 ± 1.4	16.0 ± 1.3	0.87	13.1 ± 0.9	16.1 ± 1.4	15.7 ± 1.4	0.3
Weight (kg)	68.9 ± 13.9	67.2 ± 11.2	73.9 ± 9.6	0.04	74.6 ± 10.5	73.6 ± 8.4	75.0 ± 10.6	0.57
Height (cm)	159.2 ± 6.0	161.7 ± 7.6	165.7 ± 5.9	0.03	162.2 ± 5.96	165.9 ± 6.2	166.0 ± 6.5	0.95
BMI (kg/m2)	26.0 ± 5.0	24.8 ± 3.3	25.0 ± 4.0	0.81	26.6 ± 4.2	25.6 ± 2.5	25.4 ± 3.5	0.85
BMI z-score	1.61 ± 0.6	1.25 ± 0.4	1.38 ± 0.4	0.31	1.68 ± 0.4	1.40 ± 0.3	1.46 ± 0.4	0.52
WC (cm)	92.6 ± 9.4	85.9 ± 9.5	85.1 ± 11.1	0.91	94.6 ± 10.8	89.0 ± 7.1	89.1 ± 10.0	0.95
WHtR (cm)	0.56 ± 0.06	0.53 ± 0.05	0.51 ± 0.07	0.47	0.56 ± 0.06	0.53 ± 0.03	0.53 ± 0.50	0.94
SBP (mmHg)	112 ± 12.2	109.8 ± 10.0	110.5 ± 11.0	0.82	18 ± 14.6	112.3 ± 13.2	113.2 ± 10.6	0.75
DBP (mmHg)	74.5 ± 8.4	70.7 ± 7.0	70.6 ± 8.1	0.96	78.8 ± 9.2	73.1 ± 10.2	73.5 ± 8.2	0.86
DD (years)		4.76 ± 0.95	4.72 ± 0.09	0.87		4.38 ± 0.82	4.19 ± 0.73	0.34

NID: No insulin dependence; ID: Insulin dependent; Ab: Antibodies; BMI: Body mass index; WC: Waist circumference; WHtR: Waist-to-height ratio; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; DD: Diabetes duration in years.

The percentage of obesity at the time of diagnosis in the total population was 60.5%; however, the percentage was reduced at the time of antibody measurement to 35.6%. There were no differences observed in metabolic variables in terms of TC, HDL-C cholesterol, LDL-C, and triglycerides. Despite having insulin therapy, patients had higher serum glucose, which was reflected in the levels of HbA1c; the latter of which was significant. Regarding the pancreatic reserve, C-peptide was lowest in the group with early insulin dependence, showing a decreased HOMA-β that indicated a lower pancreatic reserve (Table 4).

Table 4 Metabolic characteristics of the groups by autoimmunity.

Variable	At the time of diagnosis	NID		P value	At the time of diagnosis	ID		P value
	NID (n = 64)	Ab+) (n = 16)	(Ab-) (n = 48)		ID (n = 68)	(Ab+) (n = 27)	(A-) (n = 41)
TC (mg/dL)	164.8 ± 39	170 ± 32.9	162.1 ± 38.8	0.44	170 ± 37.5	189.2 ± 60.7	185.3 ± 51.3	0.77
HDL-C (mg/dL)	41.9 ± 11.4	45.8 ± 6.9	44.1 ± 7.7	0.42	43.6 ± 8.0	42.2 ± 8.0	44.5 ± 12.4	0.39
LDL-C (mg/dL)	97.9 ± 30	96.8 ± 23.2	94.8 ± 30.6	0.82	96.2 ± 29.3	124.8 ± 51.6	114.0 ± 44.8	0.38
TG (mg/dL)	136.4 ± 28	162.5 ± 21.1	143.8 ± 11.0	0.65	153.3 ± 22	172.6 ± 9.8	164.8 ± 10.9	0.75
Glucose (mmol/L)	14.77 ± 2.16	7.58 ± 2.93	7.64 ± 3.97	0.96	13.27 ± 2.55	13.66 ± 0.54	14.68 ± 0.25	0.43
HbA1c (%)	9.7 ± 2.7	6.8 ± 1.8	6.3 ± 0.9	0.91	9.2 ± 2.2	11.4 ± 2.6	10.4 ± 2.1	0.09
Insulin (mUI/mL)	16.7 ± 1.6	9.3 ± 4.8	13.8 ± 9.5	0.02	21.1 ± 2.8	9.5 ± 3.7	10.7 ± 5.7	0.04
C-peptide (ng/mL)	0.3 ± 0.09	2.3 ± 1.2	2.6 ± 1.2	0.42	1.1 ± 0.26	0.30 ± 0.25	0.40 ± 0.04	0.19
HOMA-β	72.3 ± 33.9	64.8 ± 45.3	125.7 ± 15.8	0.02	91.5 ± 30.6	25.8 ± 34.6	61.3 ± 20.2	0.02

NID: No insulin dependence; ID: Insulin dependent; TC: total cholesterol; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein-cholesterol; TG: Triglycerides; HbA1c: Glycated hemoglobin A1c; HOMA-β: Homeostatic model assessment of beta-cell function.

By analyzing the metabolic variables and dividing them into groups based on the presence or absence of antibodies, the group without early insulin dependence had lower insulin levels in the presence of autoimmunity as well as lower HOMA-β levels, which was significant (Table 4).

Control of glycemia in the total population studied was 40.2%; however, on stratifying the groups by early or no early insulin dependency, the group without insulin dependency had a higher percentage of glycemia control (81.3%), while in the other group, despite having insulin treatment, only 1.5% had glycemic control (P = 0.000).

The presence of anti-GAD65 was positive in 39 patients (29.5%), and, when dividing the groups by early or no early insulin dependence, anti-GAD65 was positive in 38.2% of the cases (Table 5).

Table 5 Frequency of antibody positivity, n (%).

Variable	Total (n = 132)	No insulin dependence (n = 64)	Insulin dependent (n = 68)	P value
Anti-GAD 65	39 (29.5)	13 (20.3)	26 (38.2)	0.02
Anti-IA2	24 (18.2)	8 (12.5)	16 (23.5)	0.07
Anti-Zn8T	21 (15.9)	3 (4.7)	18 (26.5)	0
Anti-GAD65 + anti-IA2	20 (15.2)	5 (7.8)	15 (22.1)	0.02
Anti-GAD65 + anti-Zn8T	15 (11.4)	3 (4.7)	12 (17.6)	0.01
Anti-IA2 + anti-Zn8T	12 (9.1)	2 (3.1)	10 (14.7)	0.02
Three antibodies	12 (9.1)	2 (3.1)	10 (14.7)	0.02

GAD65: Glutamic acid decarboxylase; IA2: Islet antigen 2; Zn8T: Zinc transporter 8.

Regarding antibody titers, anti-Zn8T showed higher titers compared with the other antibodies in the total population; however, when dividing the groups by insulin dependence, lower levels of the three were found. Antibodies in the group without early insulin dependence were compared with those in the group with dependence; however, these differences were not significant (Table 6).

Table 6 Antibody titers according to insulin dependence.

Variable	Total (n = 132)	No insulin dependence (n = 64)	Insulin dependent (n = 68)	P value
Anti-GAD65 (UI/mL)	11.0 (5-543)	6.8 (5-543)	12.0 (5-186)	0.69
Anti-IA2 (UI/mL)	14.6 (5-245)	8.45 (5-111)	21.6 (5-245)	0.6
Anti-Zn8T (UI/mL)	68.5 (15.9-178.2)	64.5 (47-74.5)	73.7 (15.9-178.2)	0.68

Median and minimum and maximum ranges. Mann–Witney U test. GAD65: Glutamic acid decarboxylase; IA2: Islet antigen 2; Zn8T: Zinc transporter 8.

Multivariate analysis showed that the presence of anti-GAD65 antibody positivity conferred an OR = 2.42 (95% confidence interval: 1.04–5.60, P = 0.026), adjusted for sex, BMI, and diabetes duration. Anti-IA2 had an OR of 1.55 but this was not significant. As for anti-Zn8T, a higher OR of 7.32 was found compared with the other two antibodies (Table 7).

Table 7 Estimation of risks according to antibodies.

Variable	Odds ratio early insulin requirements (n = 132)
	OR adj (95%CI)	P value
Anti-GAD65	2.42 (1.112- 5.303)	0.026
Anti-IA2	1.55 (0.859- 2.818)	0.101
Anti-Zn8T	7.32 (2.039-26.279)	0.002
Anti-GAD65 + Anti-IA2	3.34 (1.136- 9.814)	0.028
Anti-GAD65 + anti-Zn8T	4.35 (1.168-16.248)	0.028
Anti-IA2 + anti-Zn8T	5.34 (1.123-25.431)	0.035
Anti-GAD65 + Anti-IA2 + anti-Zn8T	5.34 (1.123-25.431)	0.035

Adjusted for age, body mass index, and time of evolution of diabetes. GAD65: Glutamic acid decarboxylase; IA2: Islet antigen 2; Zn8T: Zinc transporter 8.

DISCUSSION

Although T2DM is traditionally considered a nonautoimmune disease, it is currently known that it is multifactorial, involving 11 well-established mechanisms, with immune dysregulation being one of them[6]. In international guidelines, such as that of the German Diabetes Association in its clinical practice guideline for the diagnosis, therapy and monitoring of diabetes in children and adolescents from 2019, it only suggests taking laboratory tests to provide additional information and power to differentiate between T1DM and T2DM[13]. However, the 2018 Canadian clinical practice guidelines on T2DM in pediatric age state that diagnosis can be difficult, because 10%–20% may find one or more positive antibodies, so other factors need to be considered[14].

In that sense, there are confounding factors, since there may be T1DM with an accelerating phenotype, that is, overweight/obesity and insulin resistance that will end with faster beta cell exhaustion. However, the onset of diabetes in puberty with an insidious and more prolonged clinical picture may be factors strongly associated with T2DM in addition to those already known[15]. In our study, the patients had a phenotype of insulin resistance, dyslipidemia, overweight/obesity initially, which even persisted years later, allowing a prolonged time without exogenous insulin of > 3 years, which is not compatible with a “honeymoon” period in a context of T1DM, therefore, their clinical behavior was more towards T2DM.

According to ISPAD 2022, it is important to evaluate autoimmunity preferably with the four antibodies as long as exogenous insulin has not been started, since the anti-insulin antibody may not be assessable after treatment. This guideline recognizes the presence of autoimmunity in a subgroup of T2DM, which, given the positivity of the antibodies, predicts early insulin requirements as we reported in this study[16]. However, a key point is the follow-up of these patients, since the evolution and behavior of the disease can also be a factor to consider to reclassify diabetes as type 2, and prolonged suspension of exogenous insulin with good glycemic control for months or years will give rise to considering it as type 2, as was the case in our study.

In the present study, 51.5% of adolescent patients clinically diagnosed with T2DM presented with an earlier dependence on insulin treatment, which is a shorter time compared to the adult population when periods of > 6 years are observed, as referred to in the UKPDS group in the UK[11].

When dividing the groups by early insulin dependence and by positive antibodies, it was observed that the group without insulin therapy and positive antibodies showed lower weight and shorter height compared to the insulin-dependent group and positive antibodies, but without being significant, as well as in BMI, which differed from that reported by Turner et al[11], who reported that patients with early insulin dependence had a lower BMI.

Regarding the metabolic variables, the glycemic control exceeded the percentage reported in the literature of 20%–25%[9,17]. The lipid profile did not show significant differences between the groups. However, lower insulin levels were observed in antibody-positive patients without early insulin dependency, as well as lower C-peptide levels. This correlates with lower endogenous production of insulin; similar to the determination of HOMA-β where a significantly lower pancreatic reserve of insulin occurred in the presence of autoimmunity, similar to that reported by Bottazzo et al[12]. However, these patients with antibody positivity without insulin dependence have a HOMA-β similar to the group without antibody but with insulin dependence, which suggests they experienced continuous beta cell failure to rule out probable evolution of T1DM. We are aware that the participants in the present study who had positive antibodies, especially two or more, could be representative of a group of patients with undetected autoimmune diabetes.

The anti-GAD65 positivity was higher than that reported in the UKPDS study (6%) and the TODAY study (5.9%)[9,11]. Regarding anti-IA2, it was more frequent than the 2.2% reported by Bottazzo et al[12]; however, these percentages varied when the groups were stratified by age ranges, being higher in the younger groups[12]. The positivity of both antibodies was also higher than the 3.9% reported in the TODAY study[9].

Anti-GAD65 was the most frequent antibody in the group with early insulin dependence and was similar to the 38% reported by Turner et al[11]. Anti IA2 was the second antibody that predominated in the group with early insulin dependence, but it was lower than that reported by Buzzetti et al[10], who, when stratifying by age, found a positivity of 93% in the youngest group (< 45 years). The positivity of combined antibodies showed than anti-GAD65 and anti-IA2 was the most prevalent combination in the insulin-dependence group. However, this was lower than the UKPDS data, with 100% in the under 45 years, but in the over 45 years the percentage dropped to 40%.

The OR for anti-GAD65 was significant, but this was lower than that reported by Turner et al[11] with an OR of 13.0, possibly due to the sample size. Regarding anti-AI2, a lower OR was also reported by Bottazzo et al[12]. Lastly, despite the fact that anti-Zn8T positivity was lower, its presence conferred a higher risk compared to the other two antibodies. When two antibodies were positive, the combination of positive anti-IA2 and anti-Zn8T conferred an OR of 5.34, which was sustained when there was positivity for all three antibodies.

Our study is supported by Lampasona et al in 2010, who reported that ZnT8As can be detected in some patients with adult-onset autoimmune diabetes and appear to be a useful marker for distinguishing different clinical phenotypes[18].

Determination of the four antibodies against beta cells should be integrated into the current clinical practice guidelines. Their positivity can complement the diagnosis in a more comprehensive way and predict more rapid depletion of the pancreatic reserve, which leads to closer treatment and monitoring of the patient, avoiding lack of glycemic control and the presence of complications in the medium or long term.

While our study provides valuable insights into the role of antibody positivity in characterizing T2DM phenotypes and predicting early insulin dependence, there were several limitations that should be considered. First, our sample size may not be large enough to generalize the findings to all patients with T2DM, and larger studies are needed to confirm these results. Second, the cross-sectional design does not allow for the establishment of a causal relationship between antibody positivity and beta cell depletion. Longitudinal studies would be necessary to track changes over time and to establish causality. Third, the study was conducted at a single tertiary hospital, which may limit the generalizability of the findings to other populations or healthcare settings.

Finally, we did not account for potential confounding factors such as genetic predisposition, lifestyle factors, and concurrent medical conditions, which could influence the development of antibody positivity and insulin dependence. Despite these limitations, our findings suggest that antibodies such as anti-GAD65, anti-Zn8T, and anti-IA2 are valuable markers in the management of T2DM, highlighting the need for more comprehensive studies in this area.

Interactions with drugs and antigens: There is a need to explore potential interactions between the autoimmune antibody panel and various drugs, natural antigens, or acquired antigens present in the body. It remains unclear whether medications or external antigens could influence the expression or levels of these autoantibodies, thereby affecting their diagnostic and prognostic value.

Pharmacological interactions: Some drugs might modulate immune responses or interfere with antibody production, potentially affecting the accuracy of the autoimmune panel.

Natural and acquired antigens: The presence of other antigens, whether natural or acquired through infections, could affect the immune response, leading to false positives or negatives in antibody testing.

Despite these limitations, our findings suggest that antibodies such as anti-GAD65, anti-Zn8T, and anti-IA2 are valuable markers in the management of T2DM. These antibodies highlight the need for more comprehensive studies to understand their interactions and to improve diabetes management strategies effectively.

CONCLUSION

We can conclude that patients clinically diagnosed with T2DM demonstrate an early depletion of endogenous insulin reserves since > 50% required the application of exogenous insulin as a cornerstone in their treatment. Antibody positivity was associated with a phenotype of depleted beta cell reserves, thus lower insulin levels, conferring a higher risk of early insulin dependence. Anti-GAD65 was the most prevalent. However, positivity for anti-Zn8T conferred a greater risk of early insulin dependence, and its combination with positive anti-IA2 conferred an even greater risk. Therefore, these antibodies can be useful specific immunological markers in the approach to T2DM to characterize the patient more specifically. When they are positive it could be possible to further intensify diabetes education and tighten glycemia control to prevent further depletion of the beta cells, and delay chronic complications that accompany the disease.

ACKNOWLEDGEMENTS

The authors extend a special thanks to the Endocrinology and Nutrition Epidemiological Research Unit of the Federico Gómez Children's Hospital in Mexico for allowing them to carry out this study.