Introduction

Celiac disease (CD) is a chronic disease occurring in all age groups and affecting approximately 1% of the population1, although many cases of CD remain undiagnosed2,3,4,5,6,7,8. This condition is caused by an abnormal immune response in genetically susceptible individuals triggered by the ingestion of gluten proteins from wheat, rye and barley2,3,4.

Celiac disease primarily affects the small intestine, often leading to malabsorption and micronutrient deficiencies. A small intestinal biopsy with recognition of villus atrophy and inflammation has been the gold standard for diagnosis; however, serological testing is increasingly used in the diagnostic process and screening for CD, mainly by the detection of CD-specific antibodies, primarily immunoglobulin (Ig) A against tissue transglutaminase (TTG), the autoantigen in CD5,9,10. Management consists of a life-long gluten-free diet.

Screening for CD among individuals without typical symptoms—or even in the general population—remains controversial because many screen-detected cases have few or no symptoms, and little is known about the prognosis of undiagnosed CD. Nevertheless, studies suggest that asymptomatic patients with serological biomarkers indicative of CD may also benefit from a gluten-free diet11,12, and we have recently reported that undiagnosed CD may have an increased risk of adverse long-term consequences such as cancer and cardiovascular diseases13.

In Denmark, the prevalence of diagnosed CD is lower than in other European countries, despite recent increases in the prevalence of diagnosed cases as recorded in national registries14,15. Furthermore, we have previously shown that CD is markedly underdiagnosed in the general population: the prevalence found by screening (screening prevalence) was up to ten times the registered prevalence of diagnosed CD16. In line with other studies, we found no differences in symptoms between participants with and without screen-detected disease17,18,19. This suggests that screening for symptoms may not be an effective strategy for the detection of undiagnosed CD in a population setting. However, there is evidence that patients with CD often have hematological and other biochemical abnormalities at the time of diagnosis20. Furthermore, CD is known to be associated with malabsorption, especially before diagnosis, as evidenced by various deficiencies in nutrients, vitamins, minerals and trace elements, resulting in iron-deficiency anemia as well as calcium and vitamin B and D deficiencies20,21,22.

Diagnostic delay is a challenge in CD, and an average time to diagnosis of up to 10 years has been reported23,24,25,26. A Swedish study found that the mean delay to diagnosis was ten years from the first symptoms and six years from the first doctor’s visit27. The long diagnostic delay is a potential burden for both the patient and society, resulting in more health care contacts and costs, as well as costs for sick leave and decreased productivity. Casuistic reports indicate that the diagnostic delay is also significant in Denmark28, although we do not yet have survey data investigating the delay from first symptom/health care contact to a diagnosis of CD.

The overall aim of the present study was to describe the pattern of hematological and other biochemical test results among individuals referred for CD antibody blood testing in a primary health care setting in Denmark. In a primary health care setting, we aimed to investigate whether there were distinct hematological and/or other biochemical abnormalities associated with being CD antibody test positive and/or diagnosed with CD. Identification of hematological and/or biochemical abnormalities that predict CD will potentially enable us to reduce diagnostic delay and underdiagnosis of CD. This could, in turn, lead to early treatment and prevention of complications in patients with CD.

Methods

Data

The Copenhagen primary care laboratory (CopLab) database

This observational cohort study included results from primary care in the Copenhagen area of Denmark. In Denmark, citizens have direct access to primary care and hospital care at no cost. Approximately 98% of Danish citizens are listed with a general practitioner (GP), and Danish GPs are gatekeepers to more specialized patient care by specialized consultants as well as most in- and outpatient hospital care29. In the Copenhagen area (the Copenhagen Municipality and the former Copenhagen County), with its approximately 1.2 million inhabitants, only one laboratory served general practitioners and practicing specialists until 2015, the Copenhagen General Practitioners’ Laboratory (CGPL, Københavns Praktiserende Lægers Laboratorium). The CGPL provided a broad range of blood and urine biochemical tests, clinical physiological tests, and various cardiac tests and was accredited for International Organization for Standardization (ISO) standards ISO17025 and ISO15189. All data regarding the analyses performed since July 2000 have been saved in The Copenhagen Primary Care Laboratory (CopLab) database containing all results (n = 176,000,000) from July 1, 2000 to December 31, 2015 from the CGPL. Materials concerning the CopLab database have also been described elsewhere30,31.

For the present study, we used data from the CopLab database. The CopLab database contains information concerning the date of blood testing and thereby the age at antibody measurement. Celiac antibody tests performed prior to 2006 were externally analyzed, and since the database does not include numerical results from these tests, they were not included in the study population. However, information concerning the number of tests was used for Table 2, providing an overview of the distribution of tests in the study period.

National registers

In Denmark, all citizens are registered with a unique civil registration number, which enables person-level linkages across nationwide registers. The study population was linked to The Danish Civil Registration System32, which provides information on vital status; Statistics Denmark33, with information on income; Danish Education Registers34, which provides information on highest attained education; Danish National Health Register35, which provides information on the number of contacts with the health care system; and The Danish National Patient Register (NPR)36, which contains recorded information on all hospital contacts in Denmark since 1977, with individual diagnoses registered according to the World Health Organization’s (WHO) International Classification of Diseases (ICD- system)37.

For the present study, we used data from NPR from 1978 to 2018 and The Danish Civil Registration System until 2018. The ICD codes used for this study were the diagnosis codes for CD: ICD-8 269.00 and ICD-10: K90.0 to exclude individuals with a prior known diagnosis of CD from the study population. The age at antibody measurement and sex were derived from the unique civil registration number in the CopLab database. Education, income and country of origin were registered on January 1 in the year of CD measurement;

The household equivalized income takes into consideration the total income of the household as well as the composition of the household (number of adults and children). Hence, household equivalized income accurately reflects purchasing power. Information on equivalized household income was obtained from income registers at Statistics Denmark and was adjusted for inflation and related to the consumer price index in 2015. Income was recorded in Danish crowns (DKK) but displayed in Euros using the conversion rate from 2015 (100€ = 744 DKK).

Educational attainment was retrieved from the education registry at the year of the CD test and classified into three categories according to the International Standard Classification of Education (ISCED)-system (UNESCO 1997): up to 10 years of education = primary or lower secondary education (ISCED level 0–2), 11–12 years of education = upper secondary education (ISCED level 3) and 13 and more years of education = post-secondary and tertiary education (ISCED level 4–6). For individuals aged 24 or younger, information on the educational level of both parents was categorized as described above, and the individual was assigned the highest value of one’s own, the father’s and mother’s education.

Country of origin was derived from the population registry and grouped into Danish versus non-Danish (comprising migrants and descendants of migrants).

Biochemical blood tests

Celiac disease antibody tests

Tissue transglutaminase antibody (IgA) (TTG-IgA), tissue transglutaminase antibody (IgG) (TTG-IgG), deamidated gliadin peptide antibody (IgA) (DGP-IgA) and deamidated gliadin peptide antibody (IgG) (DGP-IgG) were measured in serum by fluorescence enzyme immunoassay (EIA) on the UniCAP 100 and ImmunoCAP 250 platforms (Phadia Laboratory Systems, Thermo Fisher Scientific, Hvidovre Denmark) according to the instructions of the manufacturer. For all four assays, the results were reported as negative (< 7 kU/L), equivocal (7–10 kU/L) or positive (> 10 kU/L). The results are valid from CGPL from July 13, 2006 (TTG-IgA) and July 1, 2013 (TTG-IgG, DGP-IgA and DGP-IgG). Before these dates, the CD antibodies were analyzed by the same method by an external collaborator, Phadia/Thermo Fisher, and the results were saved at CGPL. The interserial (day to day) coefficient of variation percentage determined on internal quality control material from the manufacturer was 17.3% (at level 0,28 kU/L, n = 1552) and 11.7% (at level 66,4 kU/L, n = 1545) for TTG-IgA; 23.6% (at level 0.117 kU/L n = 12) and 7.3% (at level 38.4 kU/L, n = 18) for TTG-IgG; 15.0% (at level 0.43 kU/L, n = 12) and 5.7% (at level 33.2 kU/L, n = 27) for DGP-IgA; and 34.6% (at level 0.042 kU/L, n = 12) and 8.6% (at level 65.2 kU/L, n = 28). The interserial (day to day) coefficient of variation determined on patient samples was estimated at 5–10% (at levels 7–10 kU/L), which indicates that the probability of a test result changing from negative to positive or vice versa due to random variation is highly unlikely (p < 0,01). The reportable ranges were 0.1–128 kU/L (TTG-IgA), 0.6–600 kU/L (TTG-IgG), 0.1–142 kU/L (DGP-IgA) and 0.4–302 kU/L (DGP-IgG). The four assays were subject to external quality control through participation in the UK NEQAS for COELIAC DISEASE external quality assessment service (Sheffield, United Kingdom). The assessment scheme included 6 distributions annually. Each distribution comprised 1 sample classified as either positive, negative or equivocal. The results from the UK NEQAS confirmed the reliability of the assay, and the samples were correctly classified in all cases for TTG-IgA (n = 54), TTG-IgG (n = 14) and DGP-IgA (n = 14). For DGP-IgG disease, 13 of 14 samples were correctly classified, and 1 equivocal sample was classified as positive.

In the present study, we defined, as in earlier studies13,38, CD antibody positivity as IgA TTG ≥ 7 kU/L, IgG TTG ≥ 7 kU/L and/or IgG DGP ≥ 10 kU/L.

Other hematological and biochemical tests

Other variables used from the CopLab database were hemoglobin, MCV (erythrocytes, mean corpuscular volume), MCHC (mean corpuscular hemoglobin concentration), transferrin, hematocrit, ferritin, ALAT (alanine transaminase), alkaline phosphate, 25-OH vitamin D, folic acid, cobalamin, CRP (C-reactive protein), ReticMCH (reticulocyte, mean corpuscular hemoglobin), RDW (erythrocyte volume, relative distribution width), and immunoglobulin A. A basic characterization of other blood tests is summarized in Additional Table S1 (Additional file 1). Reference intervals used to define abnormal values are presented in Additional Table S2 (Additional file 1).

Study population

The flow chart in Fig. 1 depicts the study population, which comprised all individuals referred to CGPL during 2000–2015, both from GPs and practicing specialists, for measurement of CD antibodies: IgA- and IgG-TTG and IgG and IgG deamidated gliadin (DGP). The CopLab database included a total of 76,265 blood sample analyses with at least one celiac antibody analysis during 2000–2015. As mentioned under “Data”, CD antibody tests performed prior to 2006 were externally analyzed, and since the database does not include numerical results from these tests, they were not included in the study population. However, the numbers of tests were used for Table 2, giving an overview of the distribution of tests in the study period. The study population ultimately consisted of individuals with a first-time CD antibody measurement who were living in Denmark on January 1 of the year of CD measurement without migrations six months before and one month after the first CD antibody testing. Individuals with a prior diagnosis ICD-8/10 code for CD in the registries were excluded.

Figure 1
figure 1

Flow diagram, description of the selection of the study population.

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Statistics

Differences in baseline characteristics between CD antibody-positive and CD antibody-negative patients and trends in requisitions (Tables 1 and 2)

The distribution of categorical covariates was summarized using counts and percentages. Continuous covariates with a nonnormal distribution were summarized using the median and interquartile range (IQR).

In Table 1, chi-square tests were used to test differences between categorical variables. For continuous variables (age and income), the Wilcoxon test was used, as none of the included variables were normally distributed. Two-sided p values were reported for all tests. The p values were adjusted for multiple testing, and values < 0.05 were considered statistically significant39.

Table 1 Characteristics of individuals with positive and negative celiac disease antibody test results.
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Associations with biochemical biomarkers (Tables 3 and 4)

The distribution of categorical covariates was estimated using counts and percentages. Continuous covariates with a log-normal distribution were summarized using the median, calculated as the exponential of the mean of the log-transformed values which is also known as the geometric mean40. The 95% confidence intervals were calculated using a robust variance estimator to account for dependence between tests from the same person41. Only for CRP was a parametric survival model with Gaussian errors and a robust variance estimator used to account for the left censoring due to lower limits of detection42.

Ethics approval and consent to participate

Ethical and data handling approval were obtained by the Faculty of Health Science, University of Copenhagen (case no. 514-0460/20-3000). According to Danish legislation, no ethical approval or consent is required for registry-based research projects, in which individuals included in the study are not approached at any time during the conduct of the study.

Results

The selection of individuals in the study is shown in Fig. 1, resulting in a population of 706 CD antibody-positive and 56,355 CD antibody-negative individuals.

We compared the characteristics of CD antibody-positive individuals with those of CD antibody-negative individuals (Table 1). We found that the antibody-positive individuals were younger, and a larger percentage were women. There was no statistically significant difference in the number of contacts with primary health care during the five-year period prior to CD antibody measurement, but we observed differences with regard to country of origin, education, and income (Table 1); however, these differences were small. Trends in the frequency of requisitions for CD antibody tests from primary care per calendar year are illustrated in Table 2. There was a clear and continuously increasing trend in the number of persons tested throughout the observed 15-year period, and more women than men were tested. The median age of persons tested was approximately 30 throughout the study period, varying from a median age of 26 to a median age of 32 when calculated per year.

Table 2 Trends in frequency of requisitions of celiac disease antibody tests from primary care, both general practitioners (GP) and private practicing specialists, from 2000 to 2015.
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Table 3 depicts differences in median levels of hematological and other biochemical biomarkers between individuals, referred to the laboratory, with positive and negative CD antibody tests stratified by sex. The most remarkable difference was, for both men and women, the markedly lower ferritin among the CD antibody-positive individuals compared with the CD antibody-negative individuals; for women 13.8 versus 35.9 µg/L and for men 34.3 versus 80.4 µg/L, respectively. We also found a tendency of lower hemoglobin among CD antibody-positive individuals; for women, 7.8 versus 8.1 mmol/L; and for men, 8.5 versus 8.8 mmol/L, respectively. Furthermore, we observed lower cobalamin and folic acid levels, while higher levels of transferrin, ALAT and alkaline phosphate were noted among CD antibody-positive men and women.

Table 3 Results of hematological and biochemical measurements during the period six months before to one month after blood drawing and testing among individuals with positive and negative celiac antibody tests.
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Table 4 presents, for each hematological and other biochemical biomarker, the proportion of tests with biomarker measurements outside (below or above) sex-specific reference intervals for each measurement among individuals, referred to CD antibody testing, with positive and negative CD antibodies. We found that a greater proportion of tests among the CD antibody-positive individuals compared with negative individuals exhibited hemoglobin (10.2% vs. 2.7%), MCV (7.1% vs. 2.9%), MCHC (6.8% vs. 1.2%), and ferritin (37.6% vs. 7.6%) below, while transferrin (20.7% vs. 9.5%) was above the reference interval. Furthermore, deficiency of cobalamin and folic acid was more common among tests from individuals with positive CD antibodies.

Table 4 Results of hematological and biochemical biomarker measurements during the period six months prior to one month after celiac disease antibody measurement among individuals with positive and negative celiac antibody testsa. Test results are defined as below or above sex-specific reference intervals for each measurement of the biomarkerb.
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Discussion

This study has revealed relevant prediagnostic differences in hematological and other biochemical test results between individuals with positive and negative CD antibodies among individuals referred to the laboratory for celiac disease antibody measurements. Thus, individuals with positive CD antibodies were more likely to have blood levels of hemoglobin, MCV, MCHC, ferritin, cobalamin and folic acid below and transferrin above the reference interval. These results suggest that hematological and other biochemical abnormalities may be important markers of undiagnosed CD.

Overall, the pattern of these biomarkers suggests malabsorption, for example iron deficiency anemia, among individuals with positive CD antibodies. CD is known to be associated with malabsorption, especially before diagnosis, as exemplified by various deficiencies of micronutrients, resulting in iron-deficiency anemia and vitamin B and D deficiencies, among others21,22. Even though malabsorption is described as a classic sign of CD6,23, studies have found malabsorption to be associated with an increased risk of a long delay of diagnosis24,26. This study confirms the association of CD and malabsorption, as we observed more measurements below the reference interval for hemoglobin, ferritin, cobalamin and folic acid among individuals referred to CD antibody testing with positive CD antibodies. These results confirm the potential of screening for CD among individuals with specific laboratory signs of malabsorption. However, the results are not adjusted for age and we do not have information on mineral or vitamin supplements, which might affect the results, and the association could likely be stronger if this adjustment had been possible. Furthermore, several measurements could be included form the same individual, e.g. controls for abnormal results, but we used calculated values taking repeated measurements into account in the statistical methods.

The increase in CD antibody measurements during 2000–2015 corresponds to the increase in CD diagnoses seen in the Danish registers14,15, as well as to the increase observed internationally20. From 2013, the DGP tests were introduced, but not all individuals were tested with both TTG and DGP. There were some combined tests that could be requested; from 2003, a ‘CD test’ included both TTG-IgA and total IgA, and an algorithm resulted in a test for TTG-IgG if both TTG-IgA and IgA were low. Starting in 2013, if TTG-IgG was low in children, both DGP-IgA and DGP-IgG were measured. These algorithms might have influenced the measurements, possibly resulting in more awareness among the GPs and an increase in the number of tests per person, but the physicians could also request separate CD antibodies. The number and type of CD antibody measurements are consistent with the acceptance and considerable evidence supporting the use of TTG-IgA assays as the first-line test for the diagnosis of CD20. More women than men were tested for CD, and these numbers are in line with the notion that more women than men are diagnosed with CD15 but also in line with the knowledge of an increased risk for CD among girls and women43.

A strength of this study is that it includes data from primary care, which is the most important setting for identifying persons in need of diagnostic work-up. This is a unique possibility to describe patterns of CD antibody measurements requested from primary health care. It is also a strength that the same methods for CD antibody measurement were used throughout the study period and that we had the results of hematological and other biochemical tests even before the CD measurements were performed at CGPL. The possibility of linkage to the Danish national registers is a strength for comparing the groups. Moreover, it is a strength that the CopLab database includes all blood samples from the Copenhagen area for primary care, resulting in a large number of tests and individuals. Nevertheless, as the prevalence of CD is so low, even with this large number of individuals, the number of CD antibody-positive individuals was small. It is also important to note, that the results in Table 4 are presented by number of tests, and the same individual potentially could have several measurements included, e.g. controls for abnormal results. However, the percentages and 95% confidence intervals are calculated taking repeated measurements into account. Furthermore, the population is highly selected, as they are referred to the laboratory for a CD antibody test, and individuals with other biomarker measurements might be a further selected group. Therefore, the results of this highly selected population of seropositive individuals cannot be generalized to all seropositive cases. Moreover, the control group should not be considered healthy controls, as there might be other reasons for their tests, and we do not know the reason for referral to the laboratory. For example, deficiencies could be a symptom/condition causing testing for CD antibodies and may thereby affect the number of tests, especially iron-deficiency anemia, as guidelines recommend screening for CD if iron-deficiency anemia is unexplained44,45. It is important to note that diagnoses in primary care, e.g., privately practicing gastroenterologists, are not listed in the NPR; therefore, not all diagnosed CD cases are known, and some antibody-negative individuals could have a diagnosis of CD.

Conclusion

This study identified several biochemical abnormalities associated with CD antibody positivity in a primary care setting, among individuals referred to CD antibody testing. The present study shows more measurements below the reference interval for hemoglobin, MCV, MCHC, ferritin, cobalamin and folic acid among the individuals with a positive CD antibody test. The pattern of the included biomarkers suggested that micronutrient deficiencies were common among CD antibody-positive individuals and confirmed malabsorption as a sign of CD. These findings illustrate the possibility of prospective development of biochemical algorithms to improve guidelines for CD screening to reduce diagnostic delay and underdiagnosis of CD and to lead to early treatment and prevention of comorbidities in patients with CD.