Patterns and determinants of serum amylase, lipase concentrations in Indian adolescents and youth with type 1 diabetes

Nimisha Shankar Dange; Chirantap Oza; Vaman Khadilkar; Ketan Gondhalekar; Sushil Yewale; Anuradha Khadilkar

doi:10.1515/jpem-2024-0314

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Patterns and determinants of serum amylase, lipase concentrations in Indian adolescents and youth with type 1 diabetes

Nimisha Shankar Dange , Chirantap Oza , Vaman Khadilkar , Ketan Gondhalekar , Sushil Yewale and Anuradha Khadilkar

Published/Copyright: December 24, 2024

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From the journal Journal of Pediatric Endocrinology and Metabolism Volume 38 Issue 2

Abstract

Objectives

Exocrine pancreatic insufficiency has been demonstrated in type 1 diabetes (T1D); lower concentrations of pancreatic enzymes have been associated with metabolic risk (MR). Influence of puberty and MR factors on serum concentrations of amylase and lipase remain unexplored in Indian youth with T1D. 1) To characterize and predict determinants of serum amylase and lipase concentrations in adolescents/youth with T1D. 2) To assess relationship between amylase, lipase, and prevalence of MR.

Methods

Cross sectional, observational study on 291 (155 girls) adolescents/youth (10–24 years) with T1D. History, examination, body composition, biochemistry (glycated hemoglobin [HbA1c], thyroid stimulating hormone [TSH], lipids).

Results

Mean age, diabetes duration and HbA1c were 15.3, 7.0 years and 10.0 ± 2.1, respectively. Relative risk of lower amylase/higher lipase concentrations (<median) in participants with poor glycemic control (HbA1c>9.5 %) was 1.42 and 1.34, respectively, though these did not reach statistical significance. In pubertal participants, amylase was lower and lipase higher; association was not found with MR. Higher TSH and lower serum calcium were significantly associated with higher lipase (p<0.001).

Conclusions

We have characterized amylase and lipase concentrations across puberty; poor glycemic control tended to be associated with lower amylase and higher lipase, though these findings did not reach statistical significance. Amylase and lipase concentrations should be monitored in Indian adolescents with T1D, particularly in those with poor metabolic control, puberty, uncontrolled hypothyroidism, or reduced calcium intake, while further longitudinal and larger studies are needed to generalize these findings.

Keywords: Indian adolescents and youth with type 1 diabetes; metabolic risk; metabolic syndrome; pancreatic enzymes; serum amylase and lipase

Introduction

The endocrine pancreas is a distinct functional unit, even though it is anatomically embedded within the exocrine pancreas. Islet acinar cell axis plays a major role in the relationship between exocrine and endocrine functions of the pancreas. The paracrine influence of insulin, which involves somatostatin and pancreatic polypeptides, and intensifies the action of secretin and cholecystokinin, has been well-documented in previous studies [1]. Insulin affects the basal amylase secretion, perhaps the accurate appreciation of its effects on exocrine pancreatic function is hindered by metabolic complexities. Various concentrations of exocrine dysfunction, such as reduced pancreatic size, have been studied for potential interactions with islet abnormalities associated with diabetes [2].

Exocrine pancreatic insufficiency (EPI) has been demonstrated in individuals with type 1 diabetes (T1D) through various markers, including fecal pancreatic elastase, as well as serum concentrations of amylase, lipase, and trypsinogen. These markers indicate a potential link between T1D and impaired exocrine pancreatic function, highlighting the importance of monitoring exocrine pancreatic health in individuals with T1D [3], 4]. In the realm of autoimmunity, lipase and trypsinogen have emerged as significant serological biomarkers that hold promise for refining the staging of pre- T1D. Their identification as biomarkers highlights the complex relationship between pancreatic function and the autoimmune mechanisms that drive the development of type 1 diabetes (T1D). This suggests the possibility of early detection and intervention in individuals at risk for T1D [3].

Reduced concentrations of amylase in blood have been linked to various metabolic disturbances such as obesity and insulin resistance; this has been suggested by metabolomic studies [5]. These observations led to the conclusion that there is a notable decrease in pancreatic enzyme concentrations in obese individuals compared to lean ones, suggesting the beneficial impact of diet and weight loss on improving amylase concentrations in obese individuals [6]. Pancreatic fat content has been reported to be higher in individuals with type 2 diabetes (T2D), further, the volume and diameter of the pancreas are significantly reduced in patients with T1D [2]. Research indicates a clear association between low serum amylase concentrations and an increased prevalence of metabolic syndrome (MS), non-alcoholic fatty pancreatic disease (NAFPD), and non-alcoholic fatty liver disease (NAFLD) [7].

Puberty, which is known to be associated with increased metabolism and insulin resistance, significantly influences the progression and course of T1D [8]. This phase also involves changes in body composition and increases in adiposity, which may elevate the risk of T1D-related complications. Importantly, the prevalence of vascular complications is known to be higher during the pubertal years [9]. It would be interesting to examine the pancreatic enzyme profile in adolescents and youth with T1D at different stages of the disease, correlating with their changing glycemic control [4]. An extensive literature search did not yield data on Indian adolescents and youth with type 1 diabetes in this perspective. The main objective of our study was thus to characterize and predict determinants of amylase and lipase concentrations in adolescents and youth with type 1 diabetes (T1D) and to assess the relationship between serum amylase, lipase, and the prevalence of metabolic risk in them.

Methods

Adolescents and youth (10–24 years) with type 1 diabetes attending diabetes clinic at a tertiary care hospital in Pune, India, were approached to take part in this cross sectional, observational study. Due to the fluctuation in weight and metabolic instability which is usually seen at the onset and during the initial therapy for T1D, participants with diabetes duration less than 1 year were not included in the study [10]. Those with primary multisystemic disease (polyendocrinopathies, Wolfram syndrome, syndrome H) or comorbidities like eating disorders, untreated hypothyroidism were also excluded from the study. All 356 patients who were approached agreed to take part in the study, of these, 291 met the inclusion and exclusion criteria. Of the 65 participants who were not included, 22 participants did not meet the age and disease duration criteria, four participants had non-autoimmune etiology and two patients were on pancreatic enzyme replacement therapy. Another 51 adolescents and youth were excluded as they had complications of diabetes, out of these 29 participants were on statin therapy which would possibly have an effect serum amylase and lipase concentrations [11]. Sample size of 291 was sufficient post-hoc to achieve power (1-β) of 0.8, at alpha 0.05 (two-tailed) using G power software (version 3.1) for exact linear regression model for eight predictors. The study was approved by the institutional ethics committee (EC letter dated 22 July 2021). Written informed consent was obtained from participants and for those below 18 years, parental consent and participant’s assent was obtained. This study was conducted between September 2021 to March 2022.

Clinical history and examination

Data on age of the participants, age at onset of diabetes, duration of diabetes, current medications, family and personal medical history, type of insulin regimen and total dose of insulin per day were collected using standardized questionnaires by treating doctors. Medical history provided by parents was verified from hospital medical records. Tanner staging for sexual maturity was performed by a pediatric endocrinologist. Blood pressure (BP) was recorded in the sitting or supine position with the cubital fossa was supported at the heart level using a sphygmomanometer, with an appropriately sized cuff. In case of a high reading, repeat measurement was performed at least after 10 min and also confirmed by another examiner. Systolic BP (SBP) and/or diastolic BP (DBP) >90th percentile and <95th percentile was considered as pre-hypertension and SBP and/or DBP >95th percentile was classified as hypertensive. In adults, hypertension was defined as BP reading of 140/90 and higher [12]. BP percentiles were computed using the American Academy of Pediatrics (AAP, 2017) reference standards [13].

Anthropometry

Standing height using a portable stadiometer (Leicester Height Meter, Child Growth Foundation, UK) was measured to the nearest millimeter and weight was measured using an electronic scale to the nearest 100 g. Body mass index (BMI) was computed by dividing weight in kilograms by height in meter square. Subsequently, the height, weight and BMI were converted to Z scores using Indian references [14].

Biochemical measurements

Glycemic control was evaluated by measuring glycosylated hemoglobin (HbA1c). A fasting blood sample (5 mL) was collected between 7 and 9 am by a pediatric phlebotomist. HbA1c was measured by high-performance liquid chromatography (HPLC, BIO-RAD, Germany). Thyroid stimulating hormone (TSH) concentrations were measured by Chemiluminiscent Microparticle Immuno Assay (CMIA). The fasting blood samples were then assessed for lipid profile (total cholesterol, triglycerides and HDL-C) using the enzymatic method and low-density lipoprotein-cholesterol (LDL-C) concentrations were calculated by the Friedewald formula [15]. Dyslipidemia was defined if one or more of the following lipid parameters were abnormal: (LDL-C) >100 mg/dL (>2.6 mmol/L), high density lipoprotein-cholesterol (HDL-C) <40 mg/dL (<1.1 mmol/L), total cholesterol (TC) >200 mg/dL (>5.2 mmol/L) and triglycerides (TG) >130 mg/dL (>1.5 mmol/L) in participants aged >10 years and 100–130 mg/dL (1.1–1.5 mmol/L) in participants <10 years [16], [17], [18]. The serum concentration of 25-hydroxy vitamin D was measured using enzyme linked immunosorbent assay (ELISA) (DLD). Serum concentrations of total calcium were measured using a calorimetric assay (ISA; AVL List GmbH, Graz, Austria). Concentrations of amylase and lipase were measured using Selectra ProS machine (Q-Line S Clinical Systems AMYLASE SL and Q-line LIPASE SL) by colorimetric method with coefficient of variation of <10 % for both enzymes.

Body composition

Body composition was assessed using Bioelectrical Impedance Analyzer (BIA), (Tanita Model BC-420 MA) after a minimum of 3 h of fasting and voiding before measurements [19]. BIA measures body composition as fat percentage, fat mass, fat free mass, total body water and bone mineral amount included in the entire bone (bone mass) by measuring bioelectrical impedance in the standing position. Fat Z-scores were computed using Indian reference intervals for pediatric population [20].

Metabolic syndrome (MS) in children was defined by IDF consensus 2017 as: for children age 10 years or older: MS may be diagnosed with abdominal obesity and the presence of two or more other clinical features viz elevated triglycerides, low HDL-cholesterol, high blood pressure and increased plasma glucose. Abdominal obesity was defined as WC >90th centile for age and gender using Indian waist circumference percentiles [21] or adult cut off of >80 cm in females or >90 cm in males as per ethnicity-specific values. Other parameters were defined as follow: Raised triglycerides ≥150 mg/dL (1.7 mmol/L), reduced HDL-cholesterol <40 mg/dL (1.03 mmol/L) in males and <50 mg/dL (1.29 mmol/L) in females, raised blood pressure: systolic ≥130 mmHg or diastolic ≥85 mmHg and impaired fasting glycemia ≥100 mg/dL (5.6 mmol/L). All/many of the participants with diabetes had elevated fasting blood sugar (FBS). Thus, participants who had one or more criteria as per the definition of MS (except elevated FBS) were termed to have metabolic risk (MR). Since cardiovascular risk increases with increasing numbers of MS risk factors [22], participants were categorized as having no risk, having one risk (MS-1) and having >1 risk factors (MS >1 risk) as in previous studies [23], 24].

Statistical analysis

All statistical analysis were carried out using the SPSS for Windows software program, version 26 (SPSS, Chicago, IL, USA). All outcome variables were tested for normality before performing statistical analysis. Differences in means were tested using Student’s t-test for parametric data and Mann–Whitney U test for non-parametric data. For testing relationships between continuous dependent variables and multiple continuous independent variables, multiple linear regression was carried out. Dependent variable in the model was lipase while the independent variables were gender, age, fat mass percentage, total daily dose (TDD) of insulin, serum thyroid stimulating hormone (TSH) concentration, HbA1c, vitamin D and serum calcium concentration. p values <0.05 were considered as statistically significant.

Results

Of the 291 study participants, 155 (53.3 %) were girls and 136 (46.7 %) were boys. The mean age of the study participants was 15.3 ± 3.1 and average duration of diabetes was 7.0 ± 3.7. The minimum and maximum age of participants involved in the study was 10.1 and 22.1 years respectively with mean BMI Z-score of −0.4 ± 0.9. Forty-two participants (14.4 %) were found to be overweight or obese. Disease duration wise distribution was as follows: 88 (30.2 %) children below 5 years and 203 (69.8 %) were above 5 years. The mean HbA1c was 10.0 ± 2.1. All participants were on basal bolus regimen of insulin with mean insulin requirement 1.2 ± 0.4 U/kg/day. Thirteen (4.5 %) participants were prepubertal and remaining 278 (95.5 %) were in puberty or had completed their puberty. Patient’s demographic and lab findings have been depicted in Table 1.

Table 1:

Table showing study population descriptive statistics.

Characteristic parameters	Male (n=136) Mean ± SD	Female (n=155) Mean ± SD	Total (n=291) Mean ± SD
Age, years	15.6 ± 2.9	14.9 ± 3.2	15.3 ± 3.1
Height-for-age Z score	−0.7 ± 1.2	−0.7 ± 1.1	−0.7 ± 1.2
Weight-for-age Z score	−0.7 ± 1.0	−0.6 ± 1.1	−0.7 ± 1.0
BMI-for-age Z score	−0.4 ± 0.9	−0.3 ± 1.0	−0.4 ± 0.9
Waist circumference for age Z score	−1.2 ± 1.0	−1.1 ± 1.0	−1.2 ± 1.0
Fat percentage (using BIA)	13.7 ± 7.0^b	24.1 ± 7.2^b	19.2 ± 8.8
Fat percentage Z score	−0.4 ± 0.9	−0.3 ± 1.0	−0.3 ± 1.0
Systolic blood pressure, mmHg	109.9 ± 12.3^b	106.3 ± 10.9^b	107.8 ± 11.7
Diastolic blood pressure, mmHg	65.0 ± 13.9	66.1 ± 11.7	65.6 ± 12.7
Disease duration of diabetes, years	7.1 ± 3.8	7.0 ± 3.5	7.0 ± 3.7
Total daily dose of insulin, U/kg/day	1.1 ± 0.3	1.2 ± 0.4	1.2 ± 0.4
HbA1C, mmol/mol	88.0 ± 1.0	85.0 ± 0	86.0 ± 0
Serum 25-hydroxy vitamin D, nmol/L^a	51.0 (35.0–68.3)^b	40 (27.8–54.3)^b	43 (30.3–60.5)
TSH, microIU/mL^a	1.8 (1.1–2.6)	1.7 (1.2–2.6)	1.8 (1.2–2.3)
HDL-cholesterol, mmol/L^a	1.1 (0.9–1.3)^b	1.2 (1.0–1.4)^b	1.2 (1.0–1.3)
Serum triglycerides, mmol/L^a	0.8 (0.6–1.0)	0.8 (0.6–0.9)	0.7 (0.6–1.0)
Serum amylase, U/L^a	62.5 (49.3–82.0)	62.0 (47.0–84.0)	62.0 (48.0–82.0)
Serum lipase, U/L^a	38.0 (27.0–61.8)	35.0 (27.0–48.0)	37.0 (27.0–52.0)

^aValues given in median and inter-quartile range. ^bSignificant at p-value <0.05.

There was no significant difference in mean amylase and lipase concentrations of participants with disease duration above 5 years when compared to those with disease duration below 5 years. With glycemic target at HbA1c 7 % as per International Society for Pediatric and Adolescent Diabetes (ISPAD) recommendations [25], 11 (3.8 %) participants were controlled while 280 (96.2 %) in study group had poor control depicting no statistical significance for mean amylase and lipase between two groups. As the mean HbA1c of study participants was 10.0, ADA definition of poor control (above goal) at HbA1c >9.5 % was used to broadly classify children into two groups- 138 (47.4 %) participants with good/intermediate control (at goal) and 153 (52.6 %) with poor control [26]. Mean amylase and lipase concentrations did not show any significant difference between the two group. Mean total daily dose requirement of insulin (U/kg/day) was 1.3 (±0.3) in pre-pubertal, 1.2 (±0.3) in pubertal and 1.1 (±0.4) in post-pubertal participants. No significant difference was noted in the insulin requirement when one way ANOVA test was applied across pubertal categories. No significant correlation was observed between C-peptide concentrations and serum amylase or lipase concentrations.

Out of 153 adolescents and youth with glycemic control ‘above goal’, 82 (53.6 %) had amylase values in lower half of range, and 76 (55.1 %) out of 138 adolescents and youth with ‘at goal’ glycemic control had amylase values upper half of range. Relative risk of lower amylase concentrations (lower half of the range) in participants with ‘above goal’ glycemic control (HbA1c >9.5 %) was 1.42 (95 % CI 0.95–1.50), i.e. these participants had 42 % higher risk of having lower amylase concentrations as compared to adolescents with HbA1c <9.5 %. Out of 153 participants with ‘above goal’ glycemic control, 82 (53.6 %) had lipase concentrations in upper half of the range (higher), whereas 74 (53.6 %) out of 138 participants with ‘at goal’ glycemic control had lower lipase values. Relative risk of higher lipase concentrations given that participant had ‘above goal’ glycemic control was 1.34 (95 % CI 0.84–2.12), i.e. adolescents and youth with HbA1c >9.5 % had 33 % higher risk of having higher lipase concentrations as compared to those with HbA1c <9.5 %. Serum amylase and lipase trends across pubertal status in adolescents and youth with ‘at goal’ and ‘above goal’ glycemic control are illustrated in Figure 1.

Figure 1:

Trends of median serum amylase and lipase values across pubertal status.

Serum lipase was noted to be significantly higher in overweight or obese participants in comparison with participants with normal BMI (independent t-test, mean difference = −18.37, p value=0.013). Figure 2 shows the scatter of amylase and lipase across fat percentile Z-scores. One hundred forty-three participants (49.2 %) were at metabolic risk and 148 (50.8 %) were free of metabolic risk. A significant correlation was found between fat percentile values and metabolic risk (r²=0.27, p value<0.001). Amongst participants at metabolic risk, 109 (76.2 %) had long term disease. However, metabolic risk had no statistically significant correlation either with serum amylase or lipase concentrations.

Figure 2:

Scatter plot showing serum amylase and lipase concentrations across fat percentile Z-score categories of study population.

A multiple regression analysis was performed to predict factors affecting serum amylase and lipase concentrations from gender, age, fat percentage, total daily insulin requirement, serum TSH, HbA1c, serum vitamin D and serum calcium concentrations. As a prerequisite for multiple linear regression analysis, we assessed the multicollinearity of the independent variables and no significant correlation was found between independent variables. The multiple regression model significantly predicted serum lipase, F=3.322, adjusted R²=0.061. Serum TSH and serum calcium added statistical significance to the prediction, p value <0.001. Regression coefficients and standard errors can be found in Table 2. There were no significant predictors of serum amylase concentrations.

Table 2:

Table showing multiple linear regression model with lipase as dependent variable (predictors of lipase).

Serum lipase	B	p-Value	95 % Confidence interval		Standard error B	β	R²	ΔR²
Serum lipase	B	p-Value	Upper limit	Lower limit	Standard error B	β	R²	ΔR²
Model		0.001^a					0.088	0.061
Constant	179.7	0.022^a	25.980	333.505	78.11
Gender	7.5	0.269	−5.778	20.613	6.70	0.08
Age	0.99	0.264	−0.746	2.718	0.88	0.07
Fat %	−0.097	0.798	−0.843	0.649	0.38	−0.02
TDD insulin	4.9	0.523	−10.208	20.017	7.68	0.04
TSH	1.2	0.005^a	0.384	2.079	0.43	0.17
HbA1c	1.7	0.188	−0.825	4.177	1.27	0.08
Vit. D	0.3	0.164	−0.128	0.752	0.22	0.08
Serum calcium	−19.2	0.014^a	−34.436	−3.951	7.74	−0.15

^aSignificant at p-value <0.05.

Discussion

In our study on characterizing serum amylase and lipase concentrations in participants with T1D who were poorly controlled, long-term disease had no impact on pancreatic enzyme concentrations. Lower amylase concentrations were more likely to be associated with HbA1c >9.5 %, while the risk of higher serum lipase concentrations tended to be higher with ‘above goal’ glycemic control, although these results did not reach statistical significance. Pubertal and post-pubertal adolescents with ‘above goal’ glycemic control had below median values for amylase and above median lipase concentrations. Multiple linear regression model with lipase as dependent variable predicted significant risk of higher lipase in males as compared to females. Serum calcium and higher TSH were also found to be significant predictors of lipase concentrations. Higher serum lipase concentrations were found in participants with higher BMI. With higher fat percentiles, spread of amylase and lipase concentrations was between 30–100 and 10–60 U/L, respectively. A large number of study participants had fat mass above the 75th percentile indicating increased MR; however, pancreatic enzymes did not exhibit any particular pattern in relation to fat percentiles or MR.

For a considerable duration, researchers have noted reduced concentrations of pancreatic enzymes in patients with diabetes, especially those with T1D [27], 28]. Recent studies have ascertained low curve of pancreatic enzymes in children with long term T1D, confirming co-existence of exocrine pancreatic insufficiency (EPI) [4], 29]. However, it has also been reported that disease duration had no major role in influencing lipase concentrations in prediabetics with positive auto-antibodies as well as in children with established T1D [3], 4].

Obesity and insulin resistance have been reported to have a notable association and this is further related to insufficient amylase concentrations. Despite an increase in the rate of amylase production, the concentration of amylase is reduced in individuals with obesity and insulin resistance [30]. Individuals with low serum amylase concentrations have been observed to develop MS in a 5-year follow up study. This imbalance suggests a potential role of amylase dysregulation in metabolic disorders [31]. In another study, intravenous administration of secretin stimulated amylase was more accurate for prediction of obesity and MS related parameters [27], 32] in contrast to measured baseline amylase concentrations.

In our study participants, ‘above goal’ glycemic control was a potential factor for determining the behavior of pancreatic enzymes with amylase concentrations tending to be lower and lipase concentrations tending to be higher. Serum amylase has been reported to increase with ‘at goal’ glycemic control and achieved a plateau at HbA1c 5.6–6 %; the curve then fell with increasing HbA1c. A steep fall in amylase concentrations has been reported when fasting plasma glucose was beyond 111–125 mg/dL [33]. Prior studies have reported elevation lipase in patients with T1D presenting in diabetic ketoacidosis as well as in type 2 diabetes [34], [35], [36]. However, we did not find literature that reported elevated lipase concentrations in chronic T1D as well as stratification of lipase concentrations in pediatric and adolescent T1D as per their glycemic control. Higher concentrations of serum lipase with ‘above goal’ glycemic control was noted in adolescents during puberty, suggesting that lipase may be a pro-inflammatory marker during this dynamic state.

Low profile curve of serum lipase has previously been reported in individuals with both type 1 and type 2 diabetes [37], [38], [39]. Many studies have used 13C- mixed triglyceride breath test for assessing chymotrypsin, amylase and lipase output with direct correlation to intestinal lipolysis, but with low specificity, limiting its accuracy. Consequently, the results cannot be easily extrapolated to individuals that may have underlying issues affecting lipid absorption and metabolism [40]. Kondo et al. reported that healthy obese participants had similar serum lipase pattern in comparison with lean ones [6]. This may thus indicate that poorly controlled blood sugar concentrations may have a greater negative impact on lipase concentrations than adiposity or body fat mass. Indian literature suggests similar findings of serum lipase concentrations in adults with type 1 and type 2 diabetes [41], 42]. We, on similar lines, could not find significant contribution of HbA1c, 24-h insulin requirement or fat mass percentiles (proxy for metabolic risk) for prediction of lipase in our study population. Further, although the prevalence of MR was high (almost half the study population) in our study, we did not find a significant difference in pancreatic enzyme concentrations between participants with or without metabolic risk.

We observed that higher TSH and lower serum calcium were significantly associated with higher serum lipase concentrations in children and adolescents with T1D. Thyroid dysfunction with raised TSH is known to be associated with obesity and MS [43]. TSH being the risk factor in predicting serum lipase concentration supports the fact that deranged lipid metabolism is linked with MS, as is thyroid dysfunction. This has been reported earlier by our group; we found an association of raised TSH with prevalence of dyslipidemia in pediatric participants with T1D [44].

We also found that lower serum calcium significantly affected serum lipase concentrations in adolescents with T1D. Calcium ions, in earlier days, were reported to be a cofactor for enzymatic action of lipoprotein lipase [45]. An experimental study showed the preventive role of lipase in cytosolic calcium overload in pancreatic acinar cells [46]. Although not a significant factor, vitamin D could predict changes in lipase, possibly due to an increase in lipase activity and lipase mRNA [47].

The strengths of our study are that ours is the first study in Indian adolescents with T1D describing patterns of serum amylase and lipase in adolescents and youth with T1D. We could not find literature relating to poorly controlled Asian adolescents with T1D. To the best of our knowledge, the speculation of pubertal physiology in trends of both the enzymes has been evaluated for the first time. Our study is limited in that we could not evaluate a more sensitive parameter such as the fecal elastase enzyme for determining ‘exocrine pancreatic insufficiency’ as ours is a resource limited setting, and that fasting amylase and lipase concentrations do not have diagnostic role in EPI. Overall glycemic control of the study participants was poor; thus, our results may not be applicable to adolescents and youth with good glycemic control. Further, our study exclusively included patients with type 1 diabetes, and assessment of amylase, lipase concentrations in relation with fasting glucose levels was not feasible. Enrollment of age and gender matched healthy controls would have helped in better interpretation of our results. However, finding the control group with similar body composition, nutrient intake and physical activity was difficult. In addition, as this was a single center study, our study population may not be an overall representative of youth with T1D in India.

Conclusions

Very few studies have evaluated exocrine pancreatic enzymes in patients with T1D. The present study characterizes pancreatic enzymes in adolescents/youth with T1D across puberty and fat percentiles. Puberty and poor glycemic control tended to be associated with lower amylase and higher lipase levels, however, these changes did not reach statistical significance. Further, the enzyme levels remained unchanged in the presence of metabolic risk. Lipase concentrations were affected by concentrations of TSH and serum calcium. Further longitudinal and larger studies are required in Indian adolescents with T1D especially pubertal age-group, male sex and those with hypothyroidism to generalize these findings.

Corresponding author: Dr. Anuradha Khadilkar, Deputy Director and Consultant Pediatrician, Department of Growth and Pediatric Endocrinology, Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, Maharashtra, India; Interdisciplinary School of Health Sciences, Savitribai Phule University, Pune, Maharahstra, India; and Hirabai Cowasji Jehangir Medical Research Institute, Block V Lower Basement Jehangir Hospital, 32 Sassoon Road, Pune 411001, India, E-mail: anuradhavkhadilkar@gmail.com

Research ethics: This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Ethics approval was obtained from institutional review board (EC letter dated 22 July 2021).
Informed consent: Informed consent was obtained from all individuals included in this study, or their legal guardians or wards.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Use of Large Language Models, AI and Machine Learning Tools: None declared.
Conflict of interest: The authors state no conflict of interest.
Research funding: None declared.
Data availability: The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Received: 2024-07-02

Accepted: 2024-12-08

Published Online: 2024-12-24

Published in Print: 2025-02-25

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

https://doi.org/10.1515/jpem-2024-0314

Keywords for this article

Indian adolescents and youth with type 1 diabetes; metabolic risk; metabolic syndrome; pancreatic enzymes; serum amylase and lipase

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