d i a b e t e s r e s e a r c h a n d c l i n i c a l p r a c t i c e 191 (2022) 110031 Contents lists available at ScienceDirect Diabetes Research and Clinical Practice journal homepage: www.journals.elsevier.com/diabetes-research-and-clinical-practice Comorbid autoimmune diseases and burden of diabetes-related complications in patients with type 1 diabetes from a Mediterranean area Gabriel Gimenez-Perez a, b, Bogdan Vlacho c, d, Elena Navas c, Manel Mata-Cases c, e, f, Jordi Real c, f, Xavier Cos c, g, Josep Franch-Nadal c, e, h, *, Didac Mauricio c, e, i, j a Endocrinology Section, Department of Medicine, Hospital General de Granollers, Granollers, Spain b School of Medicine and Health Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Spain c DAP‑Cat group, Unitat de Suport a la Recerca Barcelona, Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain d Institut de Recerca Hospital de la Santa Creu i Sant Pau (IIBSantPau), Barcelona, Spain e CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Barcelona, Spain f Primary Health Care Center La Mina, Gerència d’Atenció Primària Barcelona Ciutat, Institut Català de la Salut, Sant Adrià de Besòs, Spain g Primary and Hospital Innovation Department, Innovation Office at Institut Català de la Salut, Barcelona, Spain h Primary Health Care Center Raval Sud, Gerència d’Atenció Primaria Barcelona Ciutat, Institut Català de la Salut, Barcelona, Spain i Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain j Departament of Medicine, University of Vic-Central University of Catalonia, Catalonia, Spain A R T I C L E I N F O A B S T R A C T Keywords: Aim: To assess the prevalence of autoimmune diseases (AID) in patients with type 1 diabetes (T1D) and to Type 1 diabetes mellitus evaluate whether the rate of diabetes-related complications differs depending on the presence of AID. Autoimmunity Methods: Cross-sectional analysis of 13,570 T1D patients aged ≥ 18 years registered in the SIDIAP database. The Glycemic control association between AID and diabetes-related complications was assessed by multivariable logistic regression Diabetes complications models. Results: The prevalence of AID was 18.3% with thyroid AID being the most common. Patients with T1D and AID were more often female and their current age, age of diabetes onset and diabetes duration were higher. Patients with only thyroid AID experienced a lower risk of peripheral artery disease (odds ratio [OR] = 0.51, 95%; confidence interval [CI] 0.31 to 0.81) and kidney disease (OR = 0.68, 95%; 95% CI 0.54 to 0.85), whereas patients with other AID had an increased risk of ischemic heart disease (OR = 1.48, 95%; 95% CI 1.04 to 2.06). Conclusions: The burden of diabetes-related complications in patients with T1D differs according to the type of additional AID. The presence of diabetes complications is lower in those with autoimmune thyroid disease while the presence of other AID is associated with higher rates of ischemic heart disease. 1. Introduction epidemiology and risk factors for microvascular and macrovascular complications in T1D patients have been extensively studied [7,8,9], but Type 1 diabetes (T1D) is a frequent autoimmune disease (AID) with less attention has been paid to the presence of comorbid AIDs and their and estimated prevalence of 9 million people worldwide [1]. T1D is impact on the presence of complications. Additional autoimmune dis­ characterized by the destruction of pancreatic islet β-cells that leads to eases may negatively affect metabolic control in patients with T1D the need for lifelong treatment with insulin. Patients with T1D are [10,11], thereby potentially increasing the risk of micro or macro­ exposed to an increased risk for microvascular and macrovascular vascular complications. Furthermore, most autoimmune diseases confer complications and to a considerable disease-related distress [2]. The an increased risk of cardiovascular disease [12,13], which could add to prevalence of other AIDs in T1D patients, either endocrine or non- the already high baseline cardiovascular risk of T1D. Existing data on endocrine, is high [3,4,5], adding morbidity and treatment complexity this matter are controversial, showing either a higher [14] or lower [15] to a people already under significant disease associated burden [6]. The prevalence of cardiovascular disorders related to the presence of * Corresponding author. E-mail addresses: ggimenez@fphag.org (G. Gimenez-Perez), josep.franch@gmail.com (J. Franch-Nadal), didacmauricio@gmail.com (D. Mauricio). https://doi.org/10.1016/j.diabres.2022.110031 Received 19 May 2022; Received in revised form 8 July 2022; Accepted 1 August 2022 Available online 5 August 2022 0168-8227/© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). G. Gimenez-Perez et al. Diabetes Research and Clinical Practice 191 (2022) 110031 additional AIDs in patients with T1D. Furthermore, the prevalence of 2.1. Statistical analysis microvascular complications in the presence of additional AIDs shows conflicting results [16,17]. Descriptive statistics were performed to summarize the sociodemo­ The largest studies that have characterized different aspects of pa­ graphic characteristics of the study population, as well as the study tients with T1D and concomitant AIDs come from North America variables (clinical, comorbidities and autoimmune diseases). [4,14,15], Northern Europe [5] and Germany-Austria [17]. However, Descriptive data were calculated for the total population according the prevalence of AIDs and their co-existence with T1D may be subject to to the absence/presence of any autoimmune disease. geographical differences [18] and, to our knowledge, so far no studies Owing to the high prevalence of thyroid disease in the study popu­ have been performed on the relationship between T1D and its chronic lation, autoimmune disease was treated as a 3-category factor: none, complications with other AIDs in the Mediterranean area. thyroid autoimmune disease only and other autoimmune disease To address this gap, we aimed to evaluate in a well-characterized (regardless of the presence of thyroid autoimmune disease). population of T1D adult patients [19] from a Mediterranean area, i.e. Differences between categorical and quantitative variables were Catalonia (Northern Spain): 1) the prevalence of additional AIDs, and 2) analyzed using compareGroups R package [24]. whether the rate of diabetes complications differs depending on the Multivariate logistic regression models were performed with mac­ presence of additional AIDs. rovascular complications (ischemic heart disease, cerebrovascular dis­ ease, and peripheral artery disease) and microvascular complications 2. Materials and methods (retinopathy, neuropathy, and kidney disease) as response variables. Statistically significant variables with a value of p < 0.05 in the uni­ This was a retrospective cross-sectional study of patients with T1D variate analysis, and those variables that were considered relevant, were registered in the SIDIAP database [20]. A detailed description of the included in the multivariate models. Prevalences and Odds ratio (OR) SIDIAP database and how T1D patients were identified in the database estimations were expressed with confidence interval 95% (95 %CI). has recently been published [19]. Briefly, SIDIAP is a primary healthcare Statistical analyses were performed using R software for Windows database which captures anonymized information of approximately 5.8 version 3.6.1 [25]. million people in Catalonia registered with a family physician from the Institut Català de la Salut (ICS, Catalan Institute of Health). ICS provides 3. Results primary health care to around 75% of the Catalan population that is representative of all the Catalonia’s population in terms of geography, The final sample consisted of 13,570 cases with T1D aged 18 years or age, and sex. Although, patients with T1D are usually attended at the over (mean age ± SD, 45.2 ± 15.3 years). Sex distribution was 7,745 specialist care setting bound to a hospital facility, prescriptions of (57.1%) men and 5,826 (42.9%) women. Mean ± SD age at diagnosis chronic treatments and glucose control materials are provided at the was 31.7 ± 16.5 years, with a mean duration of diabetes of 14.1 ± 9.9 primary care centres, guaranteeing that regardless of where clinical care years. is provided, the registry of patients with T1D of any age by the ICS and CatSalut databases can be considered complete. SIDIAP includes data 3.1. Additional AIDs according to clinical characteristics from the common primary care electronic medical records (de­ mographics, diagnoses, clinical variables, prescriptions, referrals and The prevalence of additional autoimmune disease in this study laboratory results). It also includes medications dispensed in pharmacy population was 18.3% (95% CI 17.6% to 18.9%). The mean time since offices and incorporates data of hospital discharges obtained from the diagnosis of additional AID was significantly shorter than that of T1D Basic Minimum Set of Data (BMSD). The SIDIAP database has previously (8.0 ± 6.6 vs 14.1 ± 9.9; p < 0.001). been used to conduct several observational studies that evaluate clinical Patients with T1D and additional AID were more often female and characteristics and outcomes in Type 1 [19,21] and Type 2 [22,23] their current age, age of diabetes onset and diabetes duration were diabetes in Catalonia. higher than those without additional AID. (Table 1). We retrieved data from subjects older than 18 years with a registered Regarding the group of patients with autoimmune disease, 89.5% diagnosis of T1D (International Classification of Diseases 10 [ICD-10] (2,225) had only one additional AID disease, whereas we found 239 code E10) prior to January 1, 2017 with no concomitant diagnosis of (9.6%) patients with 2 additional AIDs, and 21 (0.8%) with 3 or more other types of diabetes (E11, E13, E14). To refine the patient selection, additional AIDs. we applied restrictive criteria by excluding patients with an E10 diag­ Again, patients with more than one AID were more often female nosis treated with glucose-lowering agents other than insulin and those (71.1%), and were currently older (49.7 ± 15.5 vs 45.2 ± 15.3 years in who were not treated with short acting insulins more than two years those without AID), with an older age at diagnosis (34.2 ± 17.2 vs 31.7 after the registered date of diagnosis. These restrictive criteria were ± 16.5 years) and a longer duration of diabetes (16.1 ± 11 vs 14.1 ± based on records of medications retrieved at pharmacies during the data 9.9). collection period from January 1, 2016 through December 31, 2016, Table 2 shows the prevalence of autoimmune diseases grouped ac­ thus limiting the cross-sectional cohort to patients who had contacted cording to the organ or system affected and the most prevalent disease in the ICS system during this period. If not otherwise stated, the last each group. The most prevalent autoimmune disease was hypothyroid­ registered measure during the year 2016 was recorded. Data collected ism that was clearly more prevalent in women. In the rest of AIDs with a for the present analysis included age, sex, duration of diabetes (2016 prevalence sufficient to show differences, this was again higher in minus year of diabetes diagnosis), HbA1c (mean of all values available women except for “diseases of the skin and subcutaneous tissue” where during the study period), estimated glomerular filtration rate (GFR) no differences were observed. using the CKD-EPI (Chronic Kidney Disease Epidemiology Collabora­ tion) formula, and urinary albumin/creatinine ratio. Registered diag­ 3.2. Additional AIDs glycemic control and diabetes complications nosis of T1D complications were retrieved using ICD-10 codes as previously described [19] (Supplementary Table 1). Additionally, Table 1 also shows the frequency of diabetes-related complications of registered codes for autoimmune diseases were retrieved as specified in T1D patients according to the presence of additional AIDs. Furthermore, Supplementary Table 2. patients with additional AID are separated in two groups according to The study was approved by the Ethics Committee of the Primary the presence of only thyroid autoimmune disorders or other AIDs Health Care University Research Institute Jordi Gol (approval number: (whether or not with thyroid disease). Glucose control, reflected by P17/115, date of approval: 07/06/2017). mean HbA1c levels during the study year, showed significant, but 2 G. Gimenez-Perez et al. Diabetes Research and Clinical Practice 191 (2022) 110031 Table 1 Table 2 Clinical characteristics and prevalence of micro- and macrovascular complica­ Prevalence of autoimmune diseases patients with type 1 diabetes ≥ 18 years of tions according to the presence of autoimmune diseases1. age according to sex1. All Without With With With All population Males n = Females n P- Population AID n = any AID only another n = 13,571 7,745 = 5,826 Value n = 13,571 11,086 n= Thyroid AID2 n (100.0%) (57.1%) (42.9%) (100%) (81.7%) 2,485 AI = 1,111 Any AID 2,485 (18,3) 935 (12.1) 1550 (26.6) (18.3%) disease (8.2%) Thyroid gland disorders 1,592 (11.7) 466 (6.0) 1,126 < n= (19.3) 0.001 1,374 Hypothyroidism or 1,388 (10.2) 404 (5.2) 984 (16.9) < (10.1%) chronic autoimmune 0.001 Female, n (%) 5,826 4,276 1,550 969 581 thyroiditis (42.9) (38.6) (62.4)a (70.5)a (52.3)a Hyperthyroidism 146 (1.0) 46 (0.5) 100 (1.7) < Age (years) 45.2 (15.3) 44.6 47.8 46.9 48.9 0.001 (15.2) (15.6)a (15.1)a (16.1)a Addison’s disease 21 (0.1) 8 (0.1) 13 (0.2) 0.124 Age of diabetes 31.7 (16.5) 31.3 33.2 32.2 34.4 Autoimmune 3 (0.0) 2 (0.0) 1 (0.0) 1.000 diagnosis (16.3) (17.3)a (16.6) (18.1)a polyglandular failure (years) Primary ovarian failure 0 (0.0) 0 (0.0) 0 (0.0) . Diabetes duration 14.1 (9.9) 13.8 15.2 15.3 15.1 Diseases of the nervous 66 (0.4) 26 (0.3) 40 (0.6) 0.005 (years) (9.7) (10.5)a (10.6)a (10.5)a system Stratified Multiple sclerosis 50 (0.3) 19 (0.2) 31 (0.5) 0.010 diabetes Gastrointestinal disease 411 (3.0) 172 (2.2) 239 (4.1) < durationb 0.001 ≤ 10 years, n (%) 4,850 4,038 812 438 374 Celiac disease 219 (1.6) 83 (1.0) 136 (2.3) < (35.7) (36.4) (32.7) (31.9) (33.7) 0.001 11 – 20 years, n 6,264 5,142 1,122 627 495 Chronic atrophic 132 (0.9) 49 (0.6) 83 (1.4) < (%) (46.2) (46.4) (45.2) (45.6) (44.6) gastritis and/or 0.001 21 – 30 years, n 1,397 1,096 301 174 127 pernicious anemia (%) (10.3) (9.8) (12.1) (12.7) (11.4) Ulcerative colitis 46 (0.3) 30 (0.3) 16 (0.2) 0.333 31 – 40 years, n 657 (4.8) 499 158 84 (6.1) 74 (6.6) Liver and biliary tract 17 (0.1) 9 (0.1) 8 (0.1) 0.921 (%) (4.5) (6.3) disease ≥ 41 years, n (%) 403 (2.9) 311 92 (3.7) 51 (3.7) 41 (3.6) Primary sclerosing 13 (0.1) 8 (0.1) 5 (0.1) 0.964 (2.8) cholangitis Smoking (yes)3, n 6,895 5,724 1,171 639 532 Diseases of the skin and 526 (3.8) 288 (3.7) 238 (4.0) 0.294 (%) (50.8) (51.6) (47.1)a (46.5)a (47.9)a subcutaneous tissue HbA1c4 (%) 8.1 (1.5) 8.1 (1.5) 8.0 8.0 7.9 Psoriasis 370 (2.7) 209 (2.7) 161 (2.7) 0.860 (1.3)c (1.3)b (1.3)b Vitiligo 165 (1.2) 86 (1.1) 79 (1.3) 0.225 4 HbA1c (mmol/ 65 (12) 65 (12) 64 (10) 64 (10)b 63 (10)b Diseases of the 132 (0.9) 44 (0.5) 88 (1.5) < c mol) musculoskeletal 0.001 HbA1c4 system and < 7% (53 mmol/ 1,767 1,426 341 178 163 connective tissue mol) n (%) (20.7) (20.6) (20.9) (19.8) (22.3) Rheumatoid arthritis 65 (0.4) 23 (0.3) 42 (0.7) 0.001 ≥ 7% (53 mmol/ 6,786 5,497 1289 720 569 mol) n (%) (79.3) (79.4) (79.1) (80.2) (77.7) Data are n (%); 1 Grouped according to organ/system affected and the most Retinopathy, n 2,977 2,401 576 304 272 prevalent in each group. (%) (21.9) (21.7) (23.2) (22.1) (24.5)b Albuminuria > 919 (14.3) 760 159 67 (9.7)b 92 clinically non-relevant differences between groups and, in any case, it 30 mg/g5, n (14.6) (12.9) (16.9) (%) was slightly better in patients with additional AIDs who also showed a Impaired renal 682 (9.6) 537 145 76 (9.7) 69 lower prevalence of smoking (either ex-smoker or current smoker). function6, n (%) (9.4) (10.3) (11.1) Patients with any AID showed a higher prevalence of ischemic heart Kidney disease7, 1,485 1,201 284 134 150 disease (23.2%) with a 95% confidence interval of 20.1% to 26.5%. n (%) (25.8) (26.1) (24.7) (20.8)c (29.5) However, this difference was not significant in the logistic regression Neuropathy, n 1,046 (7.7) 829 217 111 106 (%) (7.4) (8.7)c (8.0) (9.5)b analysis adjusted for age, sex, diabetes duration, dyslipidemia, hyper­ Ischemic heart 668 (4.9) 513 155 75 (5.4) 80 tension and smoking (OR = 1.31; 95% CI 1.00–1.70; p = 0.050; Sup­ disease, n (%) (4.6) (6.2)b (7.2)a plementary Table 3). Cerebrovascular 488 (3.6) 392 96 (3.8) 38 (2.7) 58 (5.2)c Patients with only thyroid autoimmune disorders showed a signifi­ disease, n (%) (3.5) Peripheral artery 609 (4.4) 509 100 38 (2.7)b 62 (5.5) cantly lower prevalence of kidney disease and peripheral artery disease. disease, n (%) (4.5) (4.0) In contrast, patients with other AID (excluding patients with only thy­ Statin use n (%) 4353 (32.1) 3,422 931 512 419 roid autoimmune disorders) showed a higher prevalence of retinopathy, (30.9) (37.5)a (37.3)a (37.7)a neuropathy, ischemic heart disease and cerebrovascular disease. Antihypertensive 4069 (30.0) 3,251 818 420 398 In the logistic regression analysis, after adjusting for age, sex, dia­ drugs use (%) (29.3) (32.9)a (30.6) (35.8)a betes duration, dyslipidemia, hypertension, smoking and kidney dis­ 1 Data are n (%), mean (SD) or median[IQR]. ease, the presence of autoimmune diseases, excluding patients with 2 Patients with AIDs excluding patients with only Thyroid AI disease; thyroid autoimmune disorders only, was associated with a higher like­ 3 Either ex-smoker or current smoker. 4 lihood of ischemic heart disease (p for trend, 0.025; Table 3), with all the Available for 6,913 patients. 5 other variables highlighted in the bivariate analysis losing significance Available for 6,426 patients. 6 CKD-EPI < 60 ml/min, available for 7,104 patients. (Tables 3, 4). In the group of patients with only thyroid autoimmune 7 Includes albuminuria and/or impaired renal function and/or recorded disease, after the logistic regression analysis, the lower odds of periph­ diagnosis of Type 1 diabetes with renal complications (E10.2); eral vascular disease and nephropathy persisted (p for trend, 0.006 and a p < 0.001 vs. T1D without AID. 0.001; Tables 3, 4). b p < 0.005 vs. T1D without AID. c p < 0.05 vs. T1D without AID. 3 G. Gimenez-Perez et al. Diabetes Research and Clinical Practice 191 (2022) 110031 Table 3 Multivariable logistic regression model for macrovascular complications. Covariates Ischemic heart disease Cerebrovascular disease Peripheral artery disease Odds ratio 95 %CI P-Value Odds ratio 95 %CI P-Value Odds ratio 95 %CI P-Value No autoimmune disease (reference) – – – – – – Only thyroid AI disease 1.14 0.78 to 1.63 0.478 1.10 0.72 to 1.65 0.643 0.51 0.31 to 0.81 0.006 Other AID1 1.48 1.04 to 2.06 0.025 1.36 0.94 to 1.98 0.117 1.26 0.88 to 1.79 0.197 Sex (reference = male) 0.66 0.52 to 0.85 0.001 0.57 0.43 to 0.76 < 0.001 0.54 0.42 to 0.70 < 0.001 Age (years) 1.05 1.04 to 1.06 < 0.001 1.05 1.04 to 1.06 < 0.001 1.04 1.03 to 1.05 < 0.001 Diabetes duration (reference ≤ 10 years) – – – – – – Diabetes duration: 11 – 20 years 0.98 0.76 to 1.27 0.884 0.98 0.73 to 1.31 0.880 0.90 0.69 to 1.17 0.425 Diabetes duration: 21 – 30 years 0.70 0.43 to 1.09 0.129 1.06 0.66 to 1.66 0.804 1.05 0.69 to 1.57 0.807 Diabetes duration: 31 – 40 years 1.67 1.08 to 2.53 0.018 1.52 0.92 to 2.43 0.087 1.15 0.70 to 1.82 0.568 Diabetes duration: ≥41 years 2.01 1.33 to 2.98 0.001 1.32 0.80 to 2.11 0.261 1.89 1.23 to 2.87 0.003 Smoking2 (reference = no) 1.31 1.03 to 1.67 0.031 1.47 1.12 to 1.94 0.005 2.59 2.01 to 3.38 < 0.001 Hypertension (reference = no) 1.94 1.46 to 2.59 < 0.001 2.76 1.99 to 3.87 < 0.001 2.31 1.73 to 3.10 < 0.001 Dyslipidemia (reference = no) 1.21 0.97 to 1.53 0.095 1.46 1.14 to 1.89 0.003 1.29 1.02 to 1.62 0.033 Chronic kidney disease (reference = no) 2.33 1.83 to 2.99 < 0.001 1.55 1.18 to 2.04 0.002 3.61 2.81 to 4.66 < 0.001 1 Excluding patients with only thyroid AI disease. 2 Either ex-smoker or current smoker. Table 4 Multivariable logistic regression model for microvascular complications. Covariates Retinopathy Neuropathy Kidney disease1 Odds ratio 95 %CI P-Value Odds ratio 95 %CI P-Value Odds ratio 95 %CI P-Value No autoimmune disease (reference) – – – – – – Only thyroid AI disease 0.95 0.82 to 1.10 0.485 1.02 0.81 to 1.26 0.882 0.68 0.54 to 0.85 0.001 Other AID2 0.98 0.84 to 1.15 0.828 1.09 0.87 to 1.35 0.468 1.04 0.83 to 1.31 0.734 Sex (reference = male) 0.84 0.76 to 0.92 < 0.001 0.89 0.77 to 1.02 0.099 0.99 0.86 to 1.14 0.921 Age (years) 1.03 1.02 to 1.03 < 0.001 1.04 1.03 to 1.04 < 0.001 1.03 1.03 to 1.04 < 0.001 Diabetes duration (reference ≤ 10 years) – – – – – Diabetes duration: 11 – 20 years 1.99 1.79 to 2.22 < 0.001 1.25 1.06 to 1.46 0.007 0.91 0.78 to 1.06 0.204 Diabetes duration: 21 – 30 years 3.29 2.83 to 3.81 < 0.001 1.66 1.32 to 2.07 < 0.001 0.96 0.76 to 1.21 0.749 Diabetes duration: 31 – 40 years 4.63 3.85 to 5.57 < 0.001 1.91 1.46 to 2.47 < 0.001 0.95 0.71 to 1.26 0.726 Diabetes duration: ≥41 years 5.90 4.70 to 7.43 < 0.001 2.76 2.11 to 3.59 < 0.001 0.99 0.72 to 1.37 0.960 Smoker3 (reference = no) 1.26 1.17 to 1.41 < 0.001 1.43 1.24 to 1.64 < 0.001 1.37 1.19 to 1.58 < 0.001 Hypertension (reference = no) 2.18 1.96 to 2.43 < 0.001 1.89 1.62 to 2.21 < 0.001 4.51 3.88 to 5.26 < 0.001 Dyslipidemia (reference = no) 1.35 1.22 to 1.49 < 0.001 1.33 1.15 to 1.53 < 0.001 1.20 1.04 to 1.39 0.012 1 Includes albuminuria and/or impaired renal function and/or registered diagnosis of Type 1 diabetes with renal complications (E10.2). 2 Excluding patients with only thyroid AI disease. 3 Either ex-smoker or current smoker. 4. Discussion variations in genetic and environmental risk factors [30] which may also be different for T1D compared to other AIDs [18]. Furthermore, the The main finding of this cross-sectional study in a large sample of heterogeneity of screening practices may have contributed to our subjects with T1D from a Mediterranean area is that the burden of somewhat discordant results. In patients with T1D, screening for diabetes-related complications differs according to the presence of asymptomatic or oligosymptomatic autoimmune diseases such as auto­ additional AIDs. Specifically, the presence of isolated autoimmune immune thyroiditis [31], celiac disease and pernicious anemia [32] is thyroid disease is associated with a lower prevalence of kidney disease generally recommended with a reasonably degree of evidence, and and peripheral artery disease, whereas the presence of other AIDs is repeated screening procedures in asymptomatic patients have been associated with a higher prevalence of ischemic heart disease. shown to lead to a higher prevalence, at least in the case of autoimmune The prevalence of additional AIDs in this study is lower, especially thyroid disorders [33]. However, the lack of solid evidence on the for thyroid diseases, compared to other studies from Finland [5] or USA benefit of these strategies [32] may deter healthcare providers from [3,4] with prevalences around 25%, but higher than the one described in implementing these recommendations thus leading to underdiagnosis of a recent study from Germany [17] that reported a prevalence of thyroid these conditions. disease of 5.7% in younger T1D patients. Differences in prevalence may The distribution of additional AIDs in the present study is similar to be related to the age of the study population, as in most studies the that in other studies in which thyroid diseases are the most prevalent prevalence of additional AIDs, specifically hypothyroidism, increases AIDs. However, we found a higher prevalence of skin disorders, espe­ with age [4,5] and the age of diagnosis of T1D [5,26]. However, the age cially psoriasis, not described in other studies [4,13]. It should be noted characteristics do not justify these differences since current age in our that the reported prevalence of psoriasis is Catalonia is lower [34] than population is in between other reports with a higher prevalence of AIDs our findings and similar to that in northern Europe or USA [35]. [4,5] and the age at diagnosis is consistently higher than in other studies The clinical characteristics of patients with additional AIDs are [3,4,5]. In addition, the proportion of women, especially prone to AID, similar to previous studies showing a higher prevalence in women, older in our cohort is lower than in other studies [3,14,26] but similar to patients and patients diagnosed of T1D at older ages [4,5,26]. It has been others [5]; our findings are also consistent with the incidence rates of hypothesized that the coexistence of different autoimmune disease may T1D according to sex in Catalonia [27]. Differences found may also be deteriorate glucose control at least in children and adolescents [36]. In attributed to regional differences of AIDs’ prevalence [17,28,29] due to our population, however, we did not observe a clinical relevant 4 G. Gimenez-Perez et al. Diabetes Research and Clinical Practice 191 (2022) 110031 difference in terms of glucose control as assessed by HbA1c values over includes a large population of subjects which makes its findings the study period, a finding in line with other studies [5]. relevant. Data on the prevalence of diabetes-related complications in large In summary, in this Mediterranean population of patients with T1D populations with T1D and concomitant AIDs is limited [14,17]. Prinz the presence of concomitant autoimmune thyroid diseases is associated et al. [17], in accordance with our results, have shown in a recent report with a lower prevalence of kidney disease and peripheral artery disease a lower prevalence of microalbuminuria in young patients with T1D and while the presence of other AIDs is associated with the presence of Hashimoto’s thyroiditis or Graves’ disease. In contrast, in a smaller ischemic heart disease. These results may have implications regarding study in 332 European Caucasian adult patients, Rogowicz-Frontczak et the need for early detection of AIDs and for a more aggressive treatment al [16] found a higher prevalence of diabetes kidney disease and reti­ of cardiovascular risk factors in the presence of certain AIDs in patients nopathy in patients with T1D and Hashimoto’s thyroiditis with no effect with T1D. Additional cohort studies are needed to establish prediction of thyroxine treatment. Some studies point to a deleterious effect of models on morbidity and mortality according to the presence of addi­ hypothyroidism on the development of diabetic nephropathy at least in tional AID in patients with type 1 diabetes. patients with type 2 diabetes [37] which could be reversed by treatment GGP has received speaking fees from Lilly and Astra-Zeneca. BV, EN with levothyroxine [38]. Unfortunately, data on TSH or thyroxine and JR have nothing to disclose. MMC has received advisory honorar­ treatment were not available in our study and we cannot speculate ium from for Astra-Zeneca, Bayer, Boehringer Ingelheim, GSK, Lilly, further on this topic. We also found in T1D patients with isolated thyroid MSD, NOVARTIS, NovoNordisk, Sanofi; speaker honorarium from Astra- disease a lower prevalence of peripheral artery disease even after Zeneca, Bayer, Boehringer Ingelheim, GSK, Lilly, Menarini, MSD, adjusting for kidney disease of which we are not aware in the literature. Novartis, NovoNordisk, and Sanofi; and research grants to institution In contrast to patients with isolated thyroid disease, in patients with from Astra-Zeneca, GSK, Lilly, MSD, Novartis, NovoNordisk, and Sanofi. T1D and other AIDs, we found a higher prevalence of ischemic heart XC has received consultant and/or speaking fees or research support disease independent of other well-known risk factors, also significant, from AstraZeneca, Boehringer Ingelheim, Lilly, Novartis, Novo Nordisk such as age, sex, diabetes duration, smoking, hypertension and chronic and Sanofi Diabetes, Sanofi Pasteur and Esteve. JFN has received advi­ kidney disease. This finding is in line with a previous study [14] showing sory and/or speaking fees from Astra-Zeneca, Ascensia, Boehringer an association of concomitant AIDs (including thyroid disease) with Ingelheim, GSK, Lilly, MSD, Novartis, Novo Nordisk and Sanofi and myocardial infarction. In their study Rogers et al. [14] found associa­ received research grants to the institution from Astra-Zeneca, GSK, Lilly, tions with ischemic stroke and kidney disease which were not observed MSD, Novartis, Novo Nordisk, Sanofi, and Boehringer. DM has received in our population. Our results differ from those found in the Canadian Consultant and/or speaking fees from Almirall, Esteve, Ferrer, Jansen, Study of Longevity in Type 1 Diabetes where in longstanding type 1 Lilly, Merck Sharp & Dohme, Novo Nordisk, and Sanofi. diabetes, the probability of cardiovascular disease was lower in patients with autoimmune diseases driven mostly by non-thyroid diseases [15]. Funding The presence of a higher burden of cardiovascular diseases in patients with T1D and additional AIDs seems plausible. Different studies have This research was partially funded by an unrestricted grant by Lilly S. reported an increased risk of cardiovascular disease in autoimmune A. disorders [13], probably related to chronic inflammation [39]. Author contributions. GGP, JFN and DM conceived the study. BV, EN and JR performed the 4.1. Limitations data collection and statistical analysis. GGP, EN, JFN and DM analysed and interpreted the data. GGP drafted and edited the manuscript. MMC, The present study has some limitations. As we relied on registered JR, XC, JFN and DM provided critical revision. All authors read, pro­ codes without external validation measures, we cannot exclude the vided feedback and approved the final version of the manuscript. JFN is possibility of underreporting of diabetes complications or autoimmune the guarantor of this work and, as such, had full access to all of the data diseases, especially those not associated with specific treatments such as in the study and takes responsibility for the integrity of the data and the chronic autoimmune thyroiditis or celiac disease. These are common accuracy of the data analysis. limitations of current primary-care-based electronic record databases highlighting the need for additional validation studies using external Declaration of Competing Interest databases, the development of internal control algorithms, and the comparison of the results to other similar studies. In addition, we cannot The authors declare that they have no known competing financial exclude a misdiagnosis of other forms of diabetes (specifically pancre­ interests or personal relationships that could have appeared to influence atic diabetes which is usually treated with insulin only) as type 1 dia­ the work reported in this paper. betes, which would decrease the proportion of patients with susceptibility to develop other autoimmune conditions. Also, we were unable to identify patients with latent autoimmune diabetes (LADA) Appendix A. Supplementary material since ICD10 codes do not differentiate this form of diabetes. Patients with LADA should presumably be classified as T1D but misclassification Supplementary data to this article can be found online at https://doi. is frequent, and their burden of diabetes-related complications and org/10.1016/j.diabres.2022.110031. concomitant AIDs may be different from that of conventional T1D [40]. The proportion of missing data for laboratory parameters is also a References significant limitation. This fact may be due to the fact that T1D patients [1] Green A, Hede SM, Patterson CC, Wild SH, Imperatore G, Roglic G, et al. Type 1 are mainly managed at hospital level, with a relevant proportion of diabetes in 2017: global estimates of incident and prevalent cases in children and health care providers other than ICS, while only ICS hospitals transfer adults. Diabetologia 2021;64:2741–50. https://doi.org/10.1007/s00125-021- automatically laboratory data to the SIDIAP database. Moreover, there is 05571-8. 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