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ORIGINAL RESEARCH
published: 06 August 2020
doi: 10.3389/fendo.2020.00476
Frontiers in Endocrinology | www.frontiersin.org 1August 2020 | Volume 11 | Article 476
Edited by:
Aneta Monika Gawlik,
Medical University of Silesia, Poland
Reviewed by:
Maurizio Delvecchio,
Giovanni XXIII Children’s Hospital, Italy
George Paltoglou,
National and Kapodistrian University
of Athens, Greece
*Correspondence:
Barbara Głowi ´
nska-Olszewska
barbara.glowinska-olszewska
@umb.edu.pl
Specialty section:
This article was submitted to
Pediatric Endocrinology,
a section of the journal
Frontiers in Endocrinology
Received: 04 April 2020
Accepted: 17 June 2020
Published: 06 August 2020
Citation:
Głowi ´
nska-Olszewska B,
Szabłowski M, Panas P, ˙
Zoł ¸adek K,
Jamiołkowska-Sztabkowska M,
Milewska AJ, Kadłubiska A,
Polkowska A, Łuczy ´
nski W and
Bossowski A (2020) Increasing
Co-occurrence of Additional
Autoimmune Disorders at Diabetes
Type 1 Onset Among Children and
Adolescents Diagnosed in Years
2010–2018—Single-Center Study.
Front. Endocrinol. 11:476.
doi: 10.3389/fendo.2020.00476
Increasing Co-occurrence of
Additional Autoimmune Disorders at
Diabetes Type 1 Onset Among
Children and Adolescents Diagnosed
in Years 2010–2018—Single-Center
Study
Barbara Głowi ´
nska-Olszewska 1
*, Maciej Szabłowski1, Patrycja Panas 1, Karolina ˙
Zoł ¸adek 1,
Milena Jamiołkowska-Sztabkowska 1, 2, Anna Justyna Milewska 3, Anna Kadłubiska 1,
Agnieszka Polkowska 1, Włodzimierz Łuczy ´
nski 1,4 and Artur Bossowski 1
1Department of Pediatrics, Endocrinology, Diabetology With Cardiology Division, Medical University of Bialystok, Białystok,
Poland, 2Department of Pediatrics, Rheumatology, Immunology and Metabolic Bone Diseases, Medical University of
Bialystok, Białystok, Poland, 3Department of Statistics and Medical Informatics, Medical University of Bialystok, Białystok,
Poland, 4Department of Medical Simulations, Medical University of Bialystok, Białystok, Poland
Objectives: The prevalence of type 1 diabetes mellitus (T1D) in children is growing, but
its relation to other autoimmune disorders that coexist since the onset of diabetes is
not recognized. The objective of this study was to assess the incidence of T1D and the
prevalence of autoimmune illnesses additionally coexisting since the diabetes mellitus
onset in children during a period of 9 years’ observation.
Methods: In this retrospective study, the incidence rate (IR) of the T1D was calculated
as the total number of all cases that were newly diagnosed per 100,000 population
people between 0 and 18 years of age. The selected age groups (0–4, 5–9, 10–14, and
15–18 years) were examined, respectively. The studied group included 493 children (264
[53.55%] boys) between 0 and 18 years old newly diagnosed with T1D in one of the Polish
centers in the years 2010–2018. Other autoimmune illnesses diagnoses were obtained
from medical records taken from the first hospital treatment, when T1D was recognized.
Results: The annual standardized IR of T1D increased from 19.2/100,000 in year 2010
to 31.7/100,000 in 2018 (1.7-fold over 9 years’ observation), with an increase in the
incidence rate ratio (IRR) by 4% per year. The highest growth in IR was recorded in 5- to
9-year-olds (from 19.61 in 2010 to 43.45 in 2018). In 61 (12.4%) of the studied group,
at least one additional autoimmune disease was diagnosed. The prevalence doubled
from 10.4% in the year 2010 to 20.8% in the year 2018. Autoimmune thyroid illnesses
were found in 37 children (7.5%); their incidence increased from 6.3% to almost 2-fold,
12.5%, in 2018. In 26 children (5.3%), celiac disease was recognized; the prevalence
increased from 4.2 to 9.8% in the study period. The prevalence of additional autoimmune
thyroid disease was higher in glutamic acid decarboxylase–positive antibodies (χ2=3.4,
p=0.04) patients, the oldest age group (15–18 years) (χ2=7.1, p=0.06), and in girls
(χ2=7.1, p=0.007).
Głowi ´
nska-Olszewska et al. Autoimmune Comorbidities in T1D Children
Conclusions: The standardized IR of T1D in children increased 1.7-fold over the
9-year observation period, and IRR increased 4% per year. Additional autoimmunity
represents a significant comorbidity in patients with new-onset T1D. The number of
children diagnosed with additional autoimmune diseases that accompany T1D is rapidly
growing in all age groups throughout recent years.
Keywords: diabetes type 1, autoimmune thyroid diseases, celiac disease, children, epidemiology
INTRODUCTION
The prevalence of type 1 diabetes mellitus (T1D) has received
much attention lately, and the rapid increase in the number
of patients should not be disregarded. According to the ninth
edition of IDF Diabetes Atlas 2019 (1), it is estimated that
1,110,100 young people younger than 20 years have T1D
worldwide. Type 1 diabetes incidence in children increases by 2–
5% annually worldwide, according to large epidemiologic studies
(2), and it depends on the geographic region; for example,
in Asian countries, the incidence rates (IRs) are usually very
low (3), whereas the rates in some European countries, for
example, Finland, are indisputably high (4). In European cases,
the incidence among girls is currently the highest in the age group
between 5 and 9 years, whereas that of boys is highest in the
10- to 14-years age group (5). In years 2010–2014 in Poland,
incidence rate ratio (IRR) increased 1.5-fold (by 12.73% annually)
in children and adolescents aged 0–17 years (6).
It has been reported recently, among them in meta-
analysis, that frequency of autoimmune diseases (AD) in
general, has increased significantly over the last 30 years, with
thorough research of risk factors and environmental impacts
on susceptibility to AD (7,8). The global prevalence of AD in
pediatric age is ∼5%, and the most frequent autoimmunities are
represented by autoimmune thyroid diseases (AITDs) (9). The
incidence of autoimmune hypothyroidism in children is rated
at 1–2% with a dominance of female 4:1 (10). Even subclinical
course of the disease is known to result in many adverse effects
such as increased risk of congestive cardiac failure and coronary
heart disease events. What is more, subclinical hypothyroidism is
likely to cause cognitive impairment and non-specific symptoms,
for example, fatigue and mood changes (11). Hyperthyroidism
constitutes 15% of children’s thyroid disorders, and most of
the cases can be attributed to hyperthyroidism of autoimmune
origin, Graves disease (GD) (10).
It is now recognized that the prevalence of additional
autoimmunity is increasingly encountered in clinical practice
of pediatric diabetologists. Additional ADs (AADs) frequently
occur in the same individual over the course of T1D,
suggesting strong shared genetic susceptibility and pathological
mechanisms. Patients with T1D demonstrate an increased
exposure to other autoimmune disorders, for example, AITD
(Hashimoto thyroiditis and GD, 15–30%), Addison disease
(0.5%), autoimmune gastritis (5–10%), celiac disease (CD; 4–
9%), and vitiligo (2–10%) (12,13). Revealed high prevalence of
associated autoimmune conditions generated the need for early
screening of these diseases (14).
There is increasing knowledge about the prevalence of AAD
in the course of long-lasting T1D in children with T1D (15,16).
Notably, the association of T1D with other autoimmune illnesses
that coexist from the onset of diabetes and the actual trend of
this connection over the years are not fully recognized. We aimed
to estimate the prevalence of patients diagnosed with the most
common autoimmune disorders: AITD and CD at the diagnosis
of T1D and the changes in prevalence of these diseases during 9
years (2010–2018) observation. Second, we intended to search for
possible clinical factors connected with multiple autoimmunities
since T1D onset. We hypothesized that together with increasing
prevalence of diabetes type 1 in children over the years, the
number of patients diagnosed with AAD will also increase.
PATIENTS AND METHODS
The study was planned as a retrospective, hospital records–based
study including 493 children and adolescents (264 boys and 229
girls, aged 0–18 years), who were diagnosed for T1D between
2010 and 2018 at the Department of Pediatrics, Endocrinology,
Diabetology with Cardiology Division, Medical University of
Białystok, Poland. This is the only center for diabetic children
in the Podlasie Voivodeship Region (northeast part of Poland),
where all young patients with newly diagnosed T1D from the
region are treated. The IR of the T1D was calculated as the
total number of all cases that were newly diagnosed per 100,000
people between 0 and 18 years of age. General population
figure was obtained from the Central Statistical Office of Poland
(Polish: Glowny Urzad Statystyczny) (17). The selected age
groups (0–4, 5–9, 10–14, and 15–18 years) were examined
separately. Laboratory and anthropometric data were obtained
from electronic medical records, body mass index (BMI), and
standard-deviation-score (SDS) for BMI was calculated using
age- and sex-specific BMI growth charts according to local Polish
OLAF study (18).
The diagnosis of T1D was made on the basis of criteria
for diabetes type 1 recognition according to the International
Society for Pediatric and Adolescent Diabetes guidelines: history
of polyuria, polydipsia, and weight loss with an elevated random
plasma glucose of ≥11.1 mmol/L or fasting plasma glucose of
≥7 mmol/L (19). Diabetic autoimmunity was confirmed on the
basis of at least one positive titer of autoantibodies to islet
cells (ICAs), glutamic acid decarboxylase (GADA), and also the
protein tyrosine phosphatase (IA2). Analysis was performed in
the same laboratory for all the study period. The diagnosis date
referred to the date of the very first injection of insulin, according
to EURODIAB criteria (20), and our previous publications. The
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Głowi ´
nska-Olszewska et al. Autoimmune Comorbidities in T1D Children
age of the patients was calculated in completed years on the day
of T1DM diagnosis (21,22).
Serologically screening tests for thyroid autoimmunity
included anti-thyroid peroxidase antibodies (aTPO) and
antithyroglobulin (aTg), and, in cases of hyperthyroidism
suspicion, anti-thyroid stimulating hormone (TSH) antibodies
(TR-Ab). Confirmation of thyroid autoimmunity was based on
the elevated titer of aTPO, aTg, or TR-Ab. Both hypothyroid
and hyperthyroid autoimmunity was taken into consideration.
Children were screened for the thyroid diseases using TSH
and free thyroxine (fT4) levels at the moment of diagnosing.
Furthermore, in each case of newly diagnosed T1D, according
to our local recommendations, thyroid ultrasound has been
performed since 2016. The clinical entities found in AITDs
are diverse and vary depending on whether it is in a state
of autoimmune hypothyroidism (HT, Hashimoto disease) or
hyperthyroidism (GD). Patients suffering from HT represented
clinical and biochemical characteristics of hypothyroidism
and demonstrated an elevated TSH with presence of elevated
anti-TPO and/or aTg autoantibodies. Graves disease was
diagnosed in children with large goiter, hyperthyroidism in
laboratory tests and positive thyrotropin receptor (TR-Ab)
antibodies, anti-TPO antibodies, and aTg antibodies. Subclinical
hypothyroidism, without confirmed autoimmunity, was not
taken into consideration into further analyses. The diagnosis of
AITDs was set on the basis of clinical, laboratory, and ultrasound
investigations and was always set with experienced pediatric
endocrinologist, and pharmacological treatment was introduced
if needed.
To diagnose celiac autoimmunity, anti-tissue
transglutaminase (anti-tTGA) antibodies were performed.
With titer of ≥10 IU/mL or with questionable results, anti-
endomysial (EMA) and anti-reticulin (ARA) antibodies were
also implemented. In this case, small intestine–associated
autoimmunity was recognized. The CD was diagnosed on the
basis of the revised criteria of CD diagnosis according to the
European Society Pediatric Gastroenterology, Hepatology, and
Nutrition criteria (21,23) and always consulted with experienced
gastroenterologist. Patients positively serologically tested for
tTGA, EMA, and ARA had a gastroscopy performed if needed
for diagnosis. Children recognized with the disease started
gluten-free diet since diabetes onset. We did not test our patients
for Addison disease because it is out of obligatory screening in
Poland. Yet, none of the children represented clinical symptoms
of this or any other ADs that may accompany T1D (gastritis,
vitiligo, etc.).
Laboratory Analyses
The analyses were performed with routine laboratory methods
in hospital laboratory on an ongoing basis. Fasting blood sample
for analysis was collected in the morning. Serum levels of TSH,
fT4, and triiodothyronine (fT3) were assessed with the use of
electrochemiluminescence “ECLIA” with Cobas E411 analyzer
(Roche Diagnostics, Warsaw, Poland). Values within the norm
presented the range between 0.28 and 4.3 µIU/L for TSH,
between 1.1 and 1.7 ng/dL for fT4, and between 2.6 and 5.4 ng/dL
for fT3. Anti-TPO, aTg, and TR-Ab antibodies were analyzed in
all samples with the use of ECLIA with Modular Analytics E170
TABLE 1 | General characteristics of the study group.
Parameters at
diagnosis
No. of valid results % of valid results Median [interquartile range] Minimal value Maximal value
Age at diagnosis (years) 493 100.00 9.50 [5.50–12.50] 0.50 18.00
0–4 n=109
5–9 n=151
10–14 n=172
15–18 n=61
HbA1c (%) 369 75 10.70 [9.46–12.42] 6.00 21.0
pH 487 99 7.37 [7.28–7.41] 6.93 7.64
HCO3220 45 16.60 [8.50–20.95] 2.60 43.4
C-peptide (ng/mL) 295 60 0.47 [0.28–0.79] 0.00 1.1
GADA (U/mL)
[86.82%—positive]
433 88 63.20 [8.67–280.03] 0.27 5,775
IA2A (U/mL)
[86%—positive]
434 88 188.05 [8.16–777.51] 0.00 3,626
ICA (JDF U)
[64.91%—positive]
431 87 20.00 [10.00–40.00] 0.00 640
TPO (IU/mL) 474 96 5.00 [5.00–6.90] 5.00 600.00
ATG (IU/mL) 474 96 10.00 [10.00–10.00] 3.15 4,000.00
TTGA (UI/mL) 461 93 10.00 [10.00–10.00] 0.4 1,700
BMI 470 95 15.7 [14.2–18.1] 8.9 35.01
SDS-BMI 429 87 −0.43 [−1.08 to 0.29] −3.40 5.07
Gender (%), nBoys: 53.55%
n=264
Girls: 46.45%
n=229
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Głowi ´
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analyzer (Roche Diagnostics). The positive values for antithyroid
antibodies were >1.75 U/L for TR-Ab, >34 IU/mL for anti-
TPO-Abs, and >115 IU/mL for aTg-Abs. Tests for beta cells and
thyroid and celiac antibodies were performed after recovery from
ketoacidosis and the initiation of subcutaneous insulin therapy,
usually between the fifth and the seventh day of the child’s stay in
the ward (in our hospital, hospitalization usually lasts 8–10 and
is related to patient’s education).
The study was performed in accordance with the Guidelines
of Good Clinical Practice. The protocol was approved by the
Medical University in Białystok, Poland Bioethical Committee.
Parents/legal guardians and their children both provided their
written informed consent. The study adhered to ethical standards
including ethics committee approval and consent procedure.
Also, standard biosecurity and institutional safety procedures
were adhered to.
Statistical Analysis
The IR of the T1D was calculated as the total number of all cases
that were newly diagnosed per 100,000 population people at 0- to
FIGURE 1 | (A) T1D IR Directly Standardized in years 2010–2018 in all age groups (0–18 y.o.) A incidence rate directly standardized is the number of new cases
occurring in a specified population during a year, expressed as the number of cases per 100,000 population of Podlaskie Voivedeship aged 0–18 yrs, standardized to
the age-matched population of Poland from 2010. Slope =0.948, P=0.057. (B) T1D incidence rate (IR) in years 2010–2018 in certain age groups. A crude
incidence rate is the number of new cases occuring, in a specified population during a year, expressed as the number of cases per 100,000 population of Podlaskie.
Voivodeship in these age groups.
0–4 y.o. slope =0.561, p=0.566.
5–9 y.o slope =1.78, p=0.095.
10–14 y.o slope =1.82, p=0.127.
15–18 y.o slope =1.78, p=0.521.
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Głowi ´
nska-Olszewska et al. Autoimmune Comorbidities in T1D Children
18-year age per year. A multifactorial Poisson regression model
was made to assess the IRR, depending on age and year. For
the needs of the model for age, dummy variable was created, in
which the 0- to 4-year age group is the base (reference) variable.
Model fit was assessed using the Pearson goodness-of-fit test.
One-way linear regression models were used in the time trend
analysis. For IRR by age group and year, exact Poisson 95%
confidence intervals (CIs) were calculated. The IRs were directly
standardized by age according to the population of Poland 2010.
The prevalence of T1D and additional AID was evaluated using
χ2or Fisher exact test when appropriate. A multiple logistic
regression analysis was used to recognize independent factors
and their influence on additional autoimmunity prevalence. The
odds ratios with 95% CIs were calculated. p-value lower than
0.05 was determined as statistically significant. The results are
presented as mean ±SD, or numbers (n), and percentages (%).
Statistically significant results were found at p<0.05. The data
were calculated using Stata/IC 12.1 package from StataCorp
LP, College Station, TX, USA and STATISTICA 13.0 software,
StatSoft Polska Sp. z o.o. Kraków, Poland.
RESULTS
We analyzed the data from total 493 pediatric patients (264
male and 229 female) aged 0 to 18 years [median (interquartile
range) of age at diagnosis 9.50 (5.50–12.50) years], diagnosed
successively between 2010 and 2018. During the study period,
23 children were diagnosed with other types of diabetes
(11 with maturity-onset diabetes of the young 2, six with
type 2, and six were insulin dependent, but autoantibody
negative—not included into the present analysis as T1D).
Two of our patients were diagnosed with AITD, and one,
CD before the diagnosis of T1D. The general characteristics
of the studied group are presented in Table 1. Mean IR
of T1D among children and adolescent patients during the
study period was 23.78/100,000 age-matched population. We
found that incidence of diabetes mellitus type 1 in Podlaskie
Voivodeship keeps rising. During the time of the study, the
age-standardized annual incidence increased from 19.2/100,000
in 2010 up to 31.7/100,000 in 2018 over 9 years, in total
1.7-fold in the observed period. Annual fluctuations, with
the lowest IR in 2016, were noticed. Time trend analysis
revealed increase in incidence ratio (slope 1.06, p=0.039),
although statistically insignificant when standardized for age
(p=0.057) (Figure 1A). The increase in the IRR was 4%
per year.
We divided the studied population into certain age groups
and assessed the IR one by one. We discovered the growth in
three of the age groups (from 8.22 to 21.08 in group 0–4 years
old; from 19.61 to 43.45 in group 5–9 years old; from 29.26
to 52.01 in group 10–14 years old) and decrease in the oldest
(15–18 years) age group of patients, from 20.16 to 10.95. The
overall upward trend in incidence of T1DM seems to come
from the increase in groups 5–9 years old and 10–14 years old,
in which the rise in IR was the greatest. The lowest mean IR
was found in group 15–18 years old (12.52/100,000), and the
TABLE 2 | Model of Poisson regression for IRR based on a group of 0–4 years old.
Age group (years) IRR (95% CI) P
0–4 Base
5–9 1.37 (1.06–1.75) 0.013
10–14 1.57 (1.23–1.99) 0.000
15–18 0.61 (0.44–0.83) 0.002
Year 1.04 (1.00–1.07) 0.021
Pearson goodness of fit =33.0039.
TABLE 3 | Age-standardized incidence rates (per 100,000 person-years) of type 1
diabetes according to gender.
IR (95% CI) age standardized
Year Girls Boys Total
2010 17.5 (9.8–24.4) 21.2 (13.2–29.2) 19.2 (13.7–24.6)
2011 24.2 (15.2–22.2) 21.3 (13.1–29.4) 22.7 (16.6–28.8)
2012 20.9 (12.5–29.3) 24.2 (15.4–33) 22.6 (16.5–28.7)
2013 21.3 (12.6–29.6) 25.5 (16.4–24.6) 23.5 (17.2–29.7)
2014 23.3 (14.2–32.2) 26.9 (17.4–36.4) 25.1 (15.6–31.7)
2015 19.9 (11.5–28.3) 24.7 (15.7–33.8) 22.4 (16.2–28.3)
2016 21.6 (12.9–30.2) 16.7 (9.2–24.3) 19.1 (13.20–24.8)
2017 29.6 (19.2–39.9) 25.9 (16.5–35.4) 27.7 (20.7–34.7)
2018 25.2 (15.9–34.6) 37.9 (26.7–49.2) 31.7 (24.4–39.1)
highest IR was noticed in group 10–14 years old (32.89/100,000).
In other age groups, it was, respectively, 20.95 in group 0–
4 years old and 28.78 in group 5–9 years old. In the time
trend analysis, we did not prove significant differences when
selected age groups were studied (Figure 1B). The Poisson
regression model adjusted for the year of diagnosis and age
group demonstrated the incidence risk ratio increasing 1.37 in
children aged 5–9 years, 1.57 for children aged 10–14 years,
and 0.61 for children aged 15–18 years. The year of diagnosis
increased the IRR 1.04 times (4%) (Table 2). The differences
in the standardized incidence ratios of diagnosed T1D cases
between male and female were not statistically different and are
presented in Table 3. In Supplementary Table 1, we included the
data of incidence ratios with 95% CI in separated age groups in
every studied year.
Next, we assessed the prevalence of additional autoimmunity
and AD in all new-onset cases of T1D in subsequent years
of analysis. In total, thyroid autoimmunity was recognized in
66 patients (13.39%), and AITD was recognized in 37 patients
(7.51%) during the study period. Celiac autoimmunity was
recognized in 38 patients (7.7%), whereas CD was found in 26
patients (5.3%). We found that general specific autoimmunity
(other than diabetic antibodies) at T1D diagnosis remained stable
during the study period (from 25% of patients in 2010 up to
23.6% in 2018; χ2=1.2 p=0.26). As for AADs (celiac and
AITD), their prevalence fluctuated during the study: it started
from 10.4% in 2010, next increased in years 2012–2014, and then
fell in years 2015–2017 to eventually finish at 20.83% in 2018. In
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Głowi ´
nska-Olszewska et al. Autoimmune Comorbidities in T1D Children
FIGURE 2 | Prevalence of additional autoimmune diseases (autoimmune thyroid disease and celiac disease) in new-onset type 1 diabetes mellitus patients.
TABLE 4 | Other organ autoimmunity and autoimmune diseases among DMT1 patients aged 0–18 years diagnosed in years 2010–2018.
Annual distribution
Year Total 2010 2011 2012 2013 2014 2015 2016 2017 2018 χ2and
p-value total
χ2and p-value
2010 vs. 2018
T1D, n493 48 54 50 54 57 51 43 61 72
TAI, n
(%)
66
(13.5)
8
(16.6)
10
(18.5)
9
(18.0)
8
(14.8)
6
(10.5)
6
(11.8)
4
(9.3)
5
(8.2)
10
(13.8)
χ2=5.2
p=0.7
χ2=2.3 p=0.12
Y=1.6 p=0.19
Fi p=0.09
TTGA, n
(%)
38
(7.8)
5
(10.4)
7
(13.7)
1
(1.9)
3
(5.6)
6
(10.5)
3
(5.9)
2
(4.6)
4
(6.5)
7
(9.8)
χ2=7.8
p=0.45
χ2=0.4 p=0.50
Y=0.09 p=0.70
Fi p=0.30
AI, n
(%)
99
(20.1)
12
(25)
15
(27.7)
10
(18.8)
10
(18.5)
11
(19.3)
9
(17.6)
6
(13.9)
9
(14.7)
17
(23.6)
χ2=5.7
p=0.68
χ2=1.2 p=0.26
Y=0.7 p=0.37
Fi p=0.18
AITD, n
(%)
37
(7.5)
3
(6.25)
2
(3.7)
7
(13.2)
5
(9.3)
3
(5.3)
3
(5.9)
3
(7)
2
(3.3)
9
(12.5)
χ2=8.7
p=0.36
χ2=1.2 p=0.20
Y=0.6 p=0.40
Fi p=0.20
CD, n
(%)
26
(5.3)
2
(4.2)
1
(1.8)
1
(1.9)
1
(1.8)
6
(10.5)
2
(3.9)
2
(4.6)
4
(6.7)
7
(9.8)
χ2=10.4
p=0.2
χ2=1.3 p=0.20
Y=0.6 p=0.42
Fi p=0.21
AAD, n
(%)
61
(12.4)
5
(10.4)
3
(5.6)
8
(15.1)
6
(11.1)
8
(14.0)
5
(9.8)
5
(11.6)
6
(9.8)
15
(20.8)
χ2=8.5
p=0.38
χ2=2.7 p=0.09
Y=1.9 p=1.50
Fi p=0.07
n, no. of patients; X2- Chi-squared; Y, Yates correction; Fi, Fisher exact test; T1D, type 1 diabetes mellitus; TAI, thyroid-positive autoimmunity; TTGA, anti-tissue transglutaminase
antibodies positive; AI, autoimmunity (thyroid +celiac); AITD, autoimmune thyroid disease; CD, celiac disease; AAD, additional autoimmune disease (total).
the end, this gives a 2-fold increase in the percentage of patients
with AADs during the 9-year study period (Figure 2,Table 4).
In further analysis, considering the frequency of
autoimmunity in T1D age groups, we did not show statistically
significant differences (χ2=1.7, p=0.63). As for AITD, it
was similar; we found higher prevalence of these diseases in
the oldest age group, although it was not statistically significant
(χ2=7.1, p=0.06) (Figure 3). The detailed comparison of
the differences in mean age between additional autoimmunity
“positive” and “negative” patients is presented in Table 5. We
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FIGURE 3 | Prevalence of autoimmune thyroid disease and celiac disease in new-onset T1D. Comparison between age groups.
TABLE 5 | Mean age at diagnosis of T1D in the groups of “positive” and
“negative” patients in terms of total autoimmunity, AITD, thyroid autoimmunity,
celiac disease, TTGA autoimmunity, and additional autoimmune disease.
Additional
autoimmunity
“positive” patients
Additional
autoimmunity
“negative” patients
p-value
Mean age
Autoimmunity 10.13 ±4.42 8.80 ±4.58 0.009
AITD 11.14 ±4.33 8.91 ±4.56 0.004
Thyroid autoimmunity 10.14 ±4.68 8.92 ±4.55 0.040
Celiac disease 10.69 ±3.52 8.98 ±4.62 0.064
TTGA autoimmunity 10.03 ±4.29 9.02 ±4.59 0.203
Additional autoimmune
disease
10.70 ±3.96 8.85 ±4.62 0.004
found that patients with additional autoimmmune problem,
especially thyroid disease, were significantly older. Thyroid
autoimmunity varied significantly between male (9.13%) and
female (18.5%) (χ2=9.2, p=0.002), as well as thyroid AD
(male 4.55%, female 10.92%, χ2=7.2, p=0.007) (Figure 4).
Such differences were not found for CD.
Finally, we analyzed the prevalence of AAD according to
the presence of GADA antibodies. We discovered that children
with positive anti-GAD antibodies were much more likely to
develop thyroid autoimmunity at diagnosis of T1D than patients
with negative anti-GAD, and this difference was observed
as statistically significant (p=0.024). We also obtained a
significant difference in frequency of AITD between both groups
(p=0.045). As presented in Figure 5, in GADA(+) patients,
8.54% had AITD, and 14.33% had thyroid autoimmunity at
diagnosis of T1D, whereas in GADA(–) patients, it was 3.42 and
6.9%, respectively, p<0.05 (Figure 5). We have also assessed the
possible relationship between the age of patients and the titers of
GADA, ICAs, IA2, and antithyroid antibodies without showing a
statistically significant difference (Student t-test; data not shown).
Furthermore, we performed a multiple logistic regression
analysis, which showed that female gender (p=0.01), year of
onset (p=0.01), and GADA positive (p=0.04) influenced the
presence of additional thyroid autoimmunity at diabetes type
1 onset. In this analysis, we did not confirm the independent
influence for the age at onset. As for AITD, the independent
influencing factors were female gender (p=0.03), GADA-
positive antibodies (p=0.01), and age at onset (p=0.01)
(Table 6).
Autoimmune hyperthyroidism was found in three of our
patients. Their cases were included into the AITD group. Four of
the children had developed both CD and AITD; they were treated
separately in the analyses. None of our patients represented
clinical symptoms of any other autoimmune disorder.
DISCUSSION
In our study, we presented high, in our opinion, overall
prevalence of AADs (thyroid and celiac) in children and
adolescents who newly received the diagnosis of T1D. Our
results showed increasing T1D IRs over the observed years,
accompanied with growing prevalence of other coexisting
ADs, with the 2-fold increase in AITD. To the best of our
knowledge, this work represents the first report considering the
epidemiological trends and distribution by demographic data
(gender and age) of the most common AAD—AITD and CD—
among newly diagnosed T1D pediatric patients. Therefore, we
believe that our study may provide new insight into the relation
of T1D and other autoimmunities in pediatric population.
Moreover, we reported significant association between specific
diabetic autoimmunity (GADA) and female preponderance with
increased prevalence of thyroid autoimmunity and AITD. Last
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Głowi ´
nska-Olszewska et al. Autoimmune Comorbidities in T1D Children
FIGURE 4 | Prevalence of patients with thyroid autoimmunity and autoimmune thyroid disease at diabetes type 1 diagnosis.
FIGURE 5 | Prevalence of autoimmune thyroid disease and thyroid autoimmunity in patient with positive or negative GADA autoantibodies.
but not least, we observed a trend for increase of AAD at T1D
onset with the older age at diagnosis.
In our present results, we observed increasing T1D incidence
over the observed 2010–2018 years; the overall IRR amounted to
4% a year (1.7-fold), and we noticed the highest IR in children
aged 10–14 years. According to the latest data, incidence of T1D
is increasing irrespectively of the genetics characteristic for the
region and geographical location. Numerous research tried to
find demographic trends concerning age and gender (6,24). The
recent literature emphasizes the trend of increased prevalence
of T1D among all age groups of people (25–27). Observed
worldwide IR of T1D incidence in children is increasing by 2–5%
annually. Nevertheless, IRs vary among regions of the world. In
Asia, the incidence of T1D is very low: China (Shanghai), 3.1 per
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Głowi ´
nska-Olszewska et al. Autoimmune Comorbidities in T1D Children
TABLE 6 | Independent factors influencing additional thyroid autoimmunity and
thyroid disease at diabetes type 1 onset in a multiple logistic regression analysis.
OR 95% CI p-value
Additional thyroid autoimmunity
Gender 1.9 (1.1–3.4) 0.01
Year of onset 0.9 (0.7–1.0) 0.01
GADA antibodies 1.0 (1.0–1.0) 0.04
Age at onset 1.2 (0.9–1.6) 0.09
Autoimmune thyroid disease
Gender 1.9 (0.9–4.0) 0.03
Year of onset 1.0 (0.9–1.1) 0.4
GADA antibodies 2.1 (0.7–6.1) 0.01
Age at onset 1.6 (1.1–2.3) 0.01
CI, confidence interval; OR, odds ratio.
100,000 (28). Some research was made, looking for a possible link
between these differences in IR and HLA specific to Caucasians
and Asian populations (29,30). In Europe, newly diagnosed cases
of T1D are increasing by 3.4% per year (25). According to the
large nationwide studies, in Poland, incidence of T1D is also
increasing year after year (6). In the previous study considering
our region, the lowest IR was observed in the youngest group of
children aged (0–4 years), whereas the highest IR was identified
in older children (10–14 years) (21). American SEARCH for
Diabetes in Youth, a multicenter study of American population,
also confirmed this phenomenon (an incidence of 33.9/100,000
between 10 and 14 years old, regardless of ethnic group and
region of residence). The researchers link this to an increase
in insulin resistance during puberty and pathogenic impact of
infections (31).
One of the main findings of our study is the general increase
in prevalence of AAD at T1D onset. During the study period, the
percentage of patients diagnosed with CD and AITD doubled,
with the greatest rise between 2017 and 2018. Numerous studies
reported that incidence and prevalence of autoimmunity and
AID in diabetic patients increase with age and are more common
in females (32,33), what we also confirmed in our research.
Although statistically significant differences were noted only
regarding AITD and thyroid autoimmunity, for autoimmunity
connected to CD, we observed only percentage differences.
The frequency of AITD in a combined population of
Europe is calculated as 3% for hypothyroidism and 0.75% for
hyperthyroidism (34). Autoimmune thyroid disease affects as
much as up to 3% of the pediatric population, so it represents the
example of the most common ADs (9). In T1D, patients’ reported
weighted mean prevalence of hypothyroidism was 9.8%, whereas
in hyperthyroidism it was 1.3% according to one of the recent
meta-analyses (35), so it is significantly increased compared to
general population. What is more, we could speculate that if
prevalence of AITD increases during the disease (36), and we
noticed incidence >20% at diagnosis in 2018, the prevalence of
AITD in children diagnosed in 2018 may in the further course
of the disease exceed the peak value of 30% reported by some
studies (37).
The presence of thyroid antibodies among new-onset T1D
patients occurs to be a common phenomenon, which may be
significant for predicting the possible clinical manifestation of
AITD at the same time of setting the T1D diagnosis (37).
According to a previously conducted study (38), thyroid function
at T1D onset is largely affected by metabolic derangement,
and the assessment of thyroid antibodies may be valuable in
recognizing patients prone to developing hypothyroidism. Our
findings provide further evidence that the highest number of
patients diagnosed with AITD was observed among teenagers
(15–18 years). We also found a solid female predominance in
both thyroid autoimmunity and AITD at diagnosis of T1D. Our
results are consistent with existing studies that notice thyroid
autoimmunity more often in girls (33,39) and increase by 4.6%
in prevalence of hypothyroidism (including subclinical cases) for
every 10-year increase of age in T1D and with diabetes duration
(15). These findings correlate with overall trends of thyroid
autoimmunity incidence in other countries (39,40) and also in
Poland (41). Contrary to our findings, the meta-analysis based
on 14 studies shows that the risk of thyroid dysfunction is much
higher in children in comparison to adults (42).
Another very interesting finding of our study is the
correlation between GADA and thyroid autoimmunity. In our
study, we found vital correspondence between the presence
of GADA antibodies and both clinically manifested thyroid
AD and asymptomatic thyroid autoimmunity. Our results are
consistent with previously published data (39,43). Glutamic acid
decarboxylase antibodies are found in ∼70–80% of patients who
suffer from T1DM, long before the onset of clinical symptoms,
and they remain positive over a long time after. The GADA
presence is linked positively to gender (female) and older age
at the time of diabetes onset (44). The association between
GADA and TPOAb was previously observed. Glutamic acid
decarboxylase in patients with T1D not only could indicate
higher risk of more severe course of T1D but also could
be a marker that takes part in reflecting other endocrine
autoimmunity such as thyroid autoimmunity (39).
Deficiency of thyroid hormones, even subclinical, may
lead to serious complications. Because of their influence on
heart, vessels, and adipose tissue function, they play an
important role in atherosclerotic processes (45,46). Moreover, a
possible link was found between subclinical hypothyroidism and
cardiovascular risk factors and heart failure in adult patients (47).
Despite the fact that similar conclusions have not been confirmed
in pediatric patients yet, several studies have found some subtle
proatherogenic abnormalities in children with a slight increase in
TSH levels, showing improvement after levothyroxine treatment
(45). All the facts mentioned above together with the results of
our analyses confirm the need for screening and early treatment
for AITD among T1D patients.
Celiac disease perception by clinicians has changed
remarkably over past 50 years (48), and it became to be
known as chronic, food-induced autoimmune disorder that is
common and is diagnosed worldwide in patients of any age.
Celiac disease keeps increasing in general population over last
decades (49,50). Some studies suggest that accuracy in diagnosis
of CD (51) depends on the criteria used for selection of patients
for the biopsy (the percentage of patients diagnosed increased
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Głowi ´
nska-Olszewska et al. Autoimmune Comorbidities in T1D Children
with the percentage of patients qualified for biopsy) (35). Celiac
disease, when untreated, could lead to malnutrition and also
extraintestinal manifestations of this disease: impaired bone
density and stunted growth in children, liver failure, or even
infertility (52,53). Celiac disease, except for the aforementioned
complications, may lead to increased risk of occurrence of
other disorders. A retrospective study reported that patients
who were on a gluten-free diet for a long time developed 50%
fewer number of ADs during the period up to about 15 years
of follow-up (54). Because of this, screening, possibly early
identification and diagnosis are undoubtedly vital. The strong
association of CD and AITDs was widely described in literature
(55,56). In patients with T1D, prevalence of CD is higher (4.7%)
than in general population (1.4%) (35). Similarly to these results,
prevalence of CD was increased among our patients, and the
growth trend over the years was also noted.
Nowadays, there is a great effort in research trying
to find the possible reasons for increased and multiple
autoimmunity in T1D young patients (35). One of the possible
explanations could be a common genetic background and
defective immunoregulation (44). As for a shared genetic
background, we can observe familial aggregation of ADs. It is
widely known that some haplotypes of HLA predispose to both
T1D and other ADs, i.e., HLA-DQ2, DQ4, and CD (57,58).
Also both T1D and AITD represent similar susceptibility gene
polymorphisms, with HLA and non-HLA variants, which may
cause such a clustering (59).
The TEDDY Study Group has already assessed a number
of environmental candidate triggers, which include probiotics,
infections, micronutrient, and microbiome, which could be
responsible for recent increase in AD incidence (60). Other
possible factors are altering the balance of gut microbiota due
to probiotic or antibiotics use (61,62) and epigenetic changes
induced by air pollutants (63).
The increase in incidence of ADs over the last decades is
accompanied by the outbreak of obesity. Complex interplay
between the metabolic and immune processes is not fully
understood, but may interact in developing various disorders
(64). However, there are researches describing a visible
correlation between obesity and greater prevalence or a worse
prognosis of numerous immune-mediated conditions. In our
study, the trend in annual changes of SDS-BMI was not
considered, unfortunately. Numerous researches have described
the properties of white adipose tissue as a crucial site in the
dissolvable mediators generation defined as “adipokines” that
in majority carry a proinflammatory activity. These adipokines
occur to be the link between immune system and adipose
tissue (65).
LIMITATIONS OF THE STUDY
The first and foremost limitation to our study is the retrospective
design, the improvement over the years in the diagnosis of many
conditions, and not testing specifically for other autoimmune
conditions. Second is the fact that data were sourced from
electronic medical records. Tests screening for ADs other than
those mentioned in the study were not performed because of
lack of specific guidelines and lack of symptoms manifested
by patients accounted for in the study. Controversial finding
of our study is that we noticed a lack of simultaneous
significant increase in prevalence of laboratory-recognized
autoimmunity. It may be caused by growth in the amount of
currently unknown factors triggering the development of AD
in patients with present autoimmunity. We must also admit
that, over the observed years, the diagnostic methods improved,
ultrasonography of the thyroid gland was introduced into routine
diagnostic method in all T1D patients, and diagnostic criteria
for CD changed as well. These factors may have influence on
this discrepancy. Further analysis of data gathered by us is
required in order to identify factors possibly responsible for the
observed phenomenon.
CONCLUSIONS
The IRR of T1D in children increased 4% a year, and the
standardized IR increased 1.7-fold over the 9-year observation
period. Additional autoimmunity represents a significant
comorbidity in patients with new-onset T1D. The number of
children diagnosed with AADs that accompany T1D is rapidly
growing in all age groups throughout recent years. The most
prone group of patients occurred in girls, older children, and
patients who tested positive for GADA antibodies. Thus, more
attention should be paid on subjects with other coexisting AD
since T1D onset, and we hope that our work will contribute to
greater emphasis on monitoring this problem. We believe that
getting the comprehensive knowledge on this epidemiological
problem with great clinical impact will help to establish better
interdisciplinary treatment approach.
DATA AVAILABILITY STATEMENT
The raw data supporting the conclusions of this article will be
made available by the authors, without undue reservation.
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by Medical University Bioethical Committee (no
of approval: APK.002.112.2020). Written informed consent to
participate in this study was provided by the participants’ legal
guardian/next of kin.
AUTHOR CONTRIBUTIONS
BG-O made substantial contributions to study design and
conception, acquisition, analysis and interpretation of data, and
wrote the paper. PP and KZ partially gathered the data, analyzed
and interpreted it, and co-wrote the paper. MS prepared the
figures, partially gathered the data, analyzed and interpreted it,
and co-wrote the paper. MJ-S made substantial contributions
to study conception and design, acquisition, analysis, and
interpretation of data. AM performed and interpreted statistical
analyses. AK, AP, and WŁ were involved in the critical revision
for important intellectual content. AB was involved in the
design, conception, analysis, and revised the paper. All authors
Frontiers in Endocrinology | www.frontiersin.org 10 August 2020 | Volume 11 | Article 476
Głowi ´
nska-Olszewska et al. Autoimmune Comorbidities in T1D Children
contributed in discussions, read, and approved the final version
of the manuscript.
FUNDING
This research was supported by grants from Medical University
of Bialystok, Poland.
ACKNOWLEDGMENTS
The part of the data were presented during 45th Annual
Meeting of the International Society for Pediatric and Adolescent
Diabetes (ISPAD), October 30–November 2, 2019, Boston, USA.
Poster presentation: P107 Increasing coexistence of additional
autoimmune diseases at diabetes type 1 onset among children
and adolescents in Podlaskie Voivodeship (Poland) diagnosed in
years 2010–2018.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fendo.
2020.00476/full#supplementary-material
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Conflict of Interest: The authors declare that the research was conducted in the
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potential conflict of interest.
Copyright © 2020 Głowi´
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nski and
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Frontiers in Endocrinology | www.frontiersin.org 12 August 2020 | Volume 11 | Article 476