Association between thyroid dysfunction and insulin resistance: a retrospective cohort study

Abstract

Objective

To evaluate the association between thyroid disease and diabetes markers.

Design

Retrospective cohort study.

Setting

The study was conducted in a diagnostic setting where the primary care providers recommended the patients to test for thyroid and diabetes panels.

Participants

The thyroid and diabetes markers were tested in 32 787 subjects with suspected thyroid and related conditions who visited Vibrant America Clinical Laboratory between January 2015 and June 2019.

Results

Our general prevalence results showed that homeostatic model assessment-insulin resistance (HOMA-IR) was elevated in overt hypothyroid subjects (43.7%) and overt hyperthyroid subjects (42.2%). Glycated hemoglobin (HbA1C) was elevated in subclinical hypothyroid subjects (19.2%), overt hypothyroid subjects (22.3%) and overt hyperthyroid subjects (21.2%). Glucose was significantly elevated in subclinical hypothyroid subjects (24.2%) and overt hyperthyroid subjects (31.0%). Insulin was significantly elevated in overt hypothyroid subjects (15.1%). Interestingly, we found that 70.3% of subjects who had their HOMA-IR score escalated from negative (HOMA-IR<2.7) to positive (HOMA-IR>2.7) during their multiple visits had anti-thyroid peroxidase (anti-TPO) 369 (±242) days prior to the onset of this change.

Conclusion

Our findings showed that anti-TPO levels are elevated before the onset of insulin resistance, indicating its potential use as a predictive marker.

Correspondence to Mr Hari Krishnamurthy; [email protected]

STRENGTHS AND LIMITATIONS OF THIS STUDY

• A large population size with a large set of thyroid and diabetes markers was used in this study.

• The Elecsys assays used for the analysis of thyroid hormones are highly efficient, with a wide analytical range, quick turnaround time, reproducibility and precision.

• The Beckman Coulter AU analyser used to analyse the diabetes markers is highly accurate, precise and throughput and has a broad test menu.

• The male-to-female ratio was distorted.

Introduction

Thyroid hormones exert a fine balance in glucose metabolism, acting as both an insulin agonist and an antagonist in different organs. An imbalance, a deficit or an excess of thyroid hormones could cause disequilibria leading to different disorders, especially in carbohydrate metabolism and insulin resistance.¹ Thyroid diseases and diabetes are the two most common endocrine disorders encountered in clinical practice. Thyroid disease is mainly classified into hypothyroidism and hyperthyroidism. Elevated levels of thyroid hormones are seen in hyperthyroidism while low levels of thyroid hormones are prevalent in hypothyroidism. Insulin resistance is a condition either caused by defects in insulin production by pancreatic β-cells or defects in effectively employing its function in target cells leading to diabetes. The prevalence of thyroid disease in patients with diabetes is significantly higher than that in the general population. A study conducted by Perros et al demonstrated a prevalence of 31.4% of thyroid disease in type 1 female diabetes and 6.9% in type 2 male diabetes.² In addition to diabetes, studies have indicated a possible relationship between thyroid status and insulin sensitivity. Though the results of the studies on the effect of thyroid dysfunction on insulin resistance are controversial, many studies have shown that hyperthyroidism may cause impaired glucose tolerance leading to hepatic insulin resistance while hypothyroidism may cause insulin resistance in peripheral tissues.³ Additionally, insulin resistance and autoimmune thyroid disease have shown to mutually influence each other. Studies have reported positive connections between thyroid autoantibodies and insulin resistance.^4–6 Most of these studies have used the homeostatic model assessment (HOMA) method to evaluate the insulin resistance of individuals.

HOMA-IR (HOMA-insulin resistance) is a mathematical model for assessing β-cell function and insulin resistance from fasting glucose and insulin. The HOMA-IR score is determined from glucose and insulin levels in blood in baseline/fasting conditions. In the HOMA-IR score, the plasma glucose and insulin concentrations reflect the hepatic and peripheral glucose efflux and uptake, respectively, while a decrease in β-cell function is modelled by changing the β-cell response to plasma glucose concentrations.^{7 8} The HOMA-IR has proven to be a robust tool for the surrogate assessment of insulin resistance.

Previous studies have suggested a close correlation between insulin resistance and thyroid autoantibodies. However, studies to evaluate the sequence of occurrence of each marker have not been performed. Anti-TPO has been shown to precede years before the onset of many diseases, such as autoimmune thyroid disease and connective tissue disorders.^9–11 In the present study, we aim to investigate the prevalence of diabetes markers in thyroid disease individuals and then explore the sequential occurrence of thyroid autoantibodies, anti-TPO and anti-thyroglobulin (anti-Tg) in relation to HOMA-IR score changes. Understanding the sequential occurrence of these biomarkers will not only help to recognise the disease pathogenesis but may also help to identify at-risk individuals.

Methods

Study design and population

A total of 32 787 subjects who had suspected thyroid disease or related conditions were tested for thyroid panel and diabetes markers at the Vibrant America Clinical Laboratory by the standard thyroid panel and the diabetes panel between January 2015 and June 2019. Subjects were characterised based on their serum thyroid markers as subclinical hypothyroidism, overt hypothyroidism, subclinical hyperthyroidism, overt hypothyroidism and controls (thyroid hormones in range). The clinical information on the majority of these patients was provided by physicians as ICD-10-CM (International Classification of Diseases, 10th Revision, Clinical Modification) codes. The percentage distribution of the top 20 ICD-10-CM codes reported is listed in online supplemental table S1. This cohort was subdivided into single visit subjects (only visited once between January 2015 and June 2019) and multiple visit subjects (three or more visits between January 2015 and June 2019) for different analysis purposes.

Thyroid panel

Thryoid-stimulating hormone (TSH), free thyroxine (FT4), anti-TPO and anti-Tg were measured using the commercial Roche e601 analyser (Roche Diagnostics, Indianapolis, Indiana, USA) according to the manufacturer’s recommendations. All reagents were purchased from Roche Diagnostics (Indianapolis, Indiana, USA). Human serum specimens were used on Elecsys immunoassay analysers. Elecsys TSH assay was based on specific TSH monoclonal antibodies specifically directed against humans. The antibodies labelled with a ruthenium complex consist of a chimeric construct from human-specific and mouse-specific components. As a result, interfering effects due to HAMA (human anti-mouse antibodies) were largely eliminated. The Elecsys FT4 test employed a specific anti-T4 antibody labelled with a ruthenium complex to determine the free thyroxine. The Elecsys T3 assay employs polyclonal antibodies specifically directed against T3. Endogenous T3, released by the action of 8-anilino-1-naphthalene sulfonic acid (ANS), competes with the added biotinylated T3-derivative for the binding sites on the antibodies labelled with the ruthenium complex. In the Elecsys FT3 test, the determination of free triiodothyronine is made with the aid of a specific anti-T3 antibody labelled with a ruthenium complex. The Elecsys T4 assay employs an antibody specifically directed against T4. Endogenous T4, released by the action of 8-ANS, competes with the added biotinylated T4-derivative for the binding sites on the antibodies labelled with the ruthenium complex. RT3 was measured using liquid chromatography-mass spectrometry (LC-MS) on the Xevo TQ-XS mass spectrometer. Elecsys anti-TPO assay employed recombinant antigens and polyclonal anti-TPO antibodies whereas Elecsys anti-Tg assay employed monoclonal human anti-Tg antibodies.

Reference ranges for thyroid markers

Thyroid hormone reference ranges are subject to the lab where the test is performed. In this study, we followed the reference ranges that the majority of the labs used. The reference range of hormones and autoantibody levels in a healthy control used in this study is shown in table 1. Subclinical hypothyroidism, subclinical hyperthyroidism, overt hypothyroidism and overt hyperthyroidism were attributed using these ranges.

Table 1

Reference ranges for thyroid markers studied

Marker	Reference range
TSH	0.3–4.2 mIU/L
FT4	0.9–1.7 ng/dL
Anti-TPO	<9.0 IU/mL
Anti-Tg	<4.0 IU/mL

FT4, Free thyroxine; Tg, Thyroglobulin; TPO, Thyroid peroxidase; TSH, Thyroid-stimulating hormone.

The categorisation of thyroid disease status by evaluating TSH and FT4 levels used in this study is shown in table 2.

Table 2

Thyroid disease categorisation

Disease condition	TSH	FT4
Subclinical hypothyroidism	>4.2 mIU/L	0.9–1.7 ng/dL
Subclinical hyperthyroidism	<0.3 mIU/L	0.9–1.7 ng/dL
Overt hypothyroidism	>4.2 mIU/L	<0.9 ng/dL
Overt hyperthyroidism	<0.3 mIU/L	>1.7 ng/dL
Thyroid disease negative	0.3–4.2 mIU/L	0.9–1.7 ng/dL

FT4, Free thyroxine; TSH, Thyroid-stimulating hormone.

Diabetes panel

The diabetes panel consists of HbA1C, adiponectin (ADIP), glucose, Glymark, Glycated serum protein (GSP) and insulin. The HbA1c determination was based on the turbidimetric inhibition immunoassay for haemolysed whole blood. The glucose assay was based on the enzymatic reference method with hexokinase. Hexokinase catalysed the phosphorylation of glucose to glucose-6-phosphate by adenosine triphosphate(ATP). Glucose-6-phosphate dehydrogenase oxidised glucose-6-phosphate in the presence of nicotinamide adenine dinucleotide phosphate (NADP) to gluconate-6-phosphate. No other carbohydrate was oxidised. The rate of nicotinamide adenine dinucleotide phosphate hydrogen (NADPH) formation during the reaction was directly proportional to the glucose concentration and was measured photometrically. The diazyme insulin assay was used to determine insulin in serum samples. Latex particles coated with antibody specific to human insulin were used to react with insulin present in the sample. Immunoturbidimetry using a Beckman Couter AU series analyser (Beckman Coulter, Georgia, USA) was used to measure the turbidity at 600 nm primary and 800 nm secondary. The glycated serum protein assay used proteinase K to digest GSP into low molecular weight glycated protein fragments and used diazyme’s specific fructosamine. The colorimetric product was measured at 546–600 nm. ADIP assay was based on adiponectin and anti-adiponectin-coated latex complexation. The turbidity of the antibody-antigen complex was measured at 570 nm via Roche Cobas 6000 c501 (Roche Diagnostics, Indiana, USA).

HOMA-IR calculation

HOMA-IR was calculated as follows: HOMA-IR = (fasting plasma glucose (mg/dL) × fasting insulin(µU/mL))/405.

Statistical analysis

The data were analysed using Java for Windows V.1.8.161 and R for Windows V.3.5.0. Data were expressed as mean±SD. Two-way ANOVA between HOMA-IR (dependent variable) and thyroid markers was performed. The association between Prostate-specific antigen (PSA) and autoimmune markers and controls was tested using non-parametric χ² test with a 95% CI. P value<0.05 was considered statistically significant.

Patient and public involvement

None.

Results

Patient clinical characteristics

A total of 32 787 subjects who ordered the thyroid panel and the diabetes panel were included in this retrospective study. Table 3 shows the demographics of thyroid-positive subjects (different thyroid diseases based on their serum thyroid hormone levels) and negative controls in this study.

Table 3

Demographics of subjects with different thyroid disease profiles

	Subclinical hypothyroidism	Overt hypothyroidism	Subclinical hyperthyroidism	Overt hyperthyroidism	Thyroid (control)
N	3455/52 662 (6.6%)	637/52 662 (1.2%)	1626/52 662 (3.1%)	494/52 662 (0.9%)	46 450/52 662 (88.2)
Gender	1258M/2197F	134M/503F	168M/1458F	72M/422F	16 812M/29 638F
Age	50.0M/48.2F	53.4M/51.3F	55.8M/52.5F	52.9M/53.0F	47.1M/45.6F

Prevalence of diabetes markers in thyroid disease

To evaluate the general prevalence of diabetes markers in thyroid disease subjects, we first assessed single visit subjects who had tested for both thyroid disease and diabetes markers (HOMA-IR, HbA1C, ADIP, glucose, Glymark, GSP and insulin). Figure 1 shows the diabetes markers significantly elevated in different thyroid disease subjects grouped as subclinical hypothyroidism, overt hypothyroidism, subclinical hyperthyroidism and overt hyperthyroidism based on their serum TSH and FT4 levels. HOMA-IR was elevated in overt hypothyroid subjects (171/391, 43.7%) and overt hyperthyroid subjects (129/306, 42.2%) compared with its controls, the thyroid-negative group (10 763/28 896, 37.2%). HbA1C was elevated in subclinical hypothyroid subjects (639/3325, 19.2%), overt hypothyroid subjects (137/614, 22.3%) and overt hyperthyroid subjects (101/476, 21.2%) compared with the controls (7237/44 829, 16.1%). Glucose was significantly elevated in subclinical hypothyroid subjects (579/2394, 24.2%) and overt hyperthyroid subjects (106/342, 31.0%) compared with the control (6984/31 803, 22%). Insulin was only significantly elevated in overt hypothyroid subjects (72/478, 15.1%) compared with the controls (4022/35 197, 11.4%). Subclinical hyperthyroidism did not show a significant relationship with any of the diabetes markers.

Figure 1. Prevalence of diabetes markers in subjects with different thyroid disease profiles compared with their controls (thyroid disease negative). Diabetes markers significantly elevated/reduced are only shown. HbA1c, glycated hemoglobin; HOMA, homeostatic model assessment,

Next, we tested the prevalence of these diabetes markers in antibodies (anti-TPO and anti-Tg) and individual thyroid hormones (TSH, FT4, FT3, RT3, T3 and T4). Table 4 provides the prevalence of diabetes markers in subjects with elevated thyroid autoantibodies. HOMA-IR score was elevated in subjects seropositive to anti-TPO and anti-Tg. High insulin levels were seen in subjects with anti-TPO positivity. The prevalence of diabetes markers in subjects with elevated/reduced levels of individual thyroid hormones is listed in online supplemental table S2.

Table 4

Prevalence of diabetes markers in subjects with elevated thyroid autoantibodies

	Anti-TPO+	Anti-TPO−	P value	Anti-Tg+	Anti-Tg−	P value
HOMA-IR positive	45.5% (1869/4104)	37.5% (11 015/29 387)	<0.0001	41.1% (1747/4255)	37% (8285/22 364)	<0.0001
High HbA1C	16.3% (990/6076)	15.4% (6502/42 088)	0.0930	14% (872/6210)	14.7% (4701/32 057)	0.2100
Low ADIP	2.2% (94/4184)	3.1% (918/29 592)	0.0028	1.7% (74/4391)	3% (671/22 699)	<0.0001
High glucose	22.1% (1001/4525)	22% (7097/32 218)	0.9022	19.8% (908/4595)	21.5% (5186/24 139)	0.0093
Low glucose	1.7% (75/4525)	1.8% (567/32 218)	0.6659	1.8% (84/4595)	1.9% (463/24 139)	0.7262
Low glymark	10.3% (314/3058)	10.1% (2250/22 345)	0.7564	8.6% (259/2998)	10.1% (1509/14 881)	0.0132
GSP	10.7% (438/4104)	10.7% (3159/29 601)	1.0000	11.3% (476/4215)	11.4% (2540/22 266)	0.8507
High insulin	14.1% (266/1888)	11.5% (4490/39 169)	0.0006	11.2% (588/5238)	11.1% (2990/26 991)	0.7735
Low insulin	2.9% (144/5005)	2.8% (986/34 815)	0.8936	2.8% (149/5238)	2.8% (764/26 991)	0.9916

ADIP, Adiponectin; GSP, Glycated serum protein; HbA1c, Glycated hemoglobin; HOMA-IR, homeostatic model assessment-insulin resistance; Tg, Thyroglobulin; TPO, Thyroid peroxidase.

Early detection of anti-TPO antibodies predicted HOMA-IR score change

To evaluate the direction of disease correlation between diabetes and thyroid disease, we extracted subjects who had multiple visits during the time of the study (January 2015 to June 2019). First, a subcohort who had HOMA-IR<2.7 (negative) in their initial test but increased over time (HOMA-IR>2.7-positive) during their subsequent visits was selected to analyse their clinical profiles to identify any predictive markers for insulin resistance. A total of 155 subjects were included in this group. As shown in figure 2, 109/155 (70.3%) had anti-TPO 369 (±242) days (ranging from 55 days to 1229 days) prior to the onset of HOMA-IR change from negative to positive. It was significantly different from the control group that had 46/155 (29.7%) subjects with either no anti-TPO presence or anti-TPO on or after the negative HOMA-IR change to positivity. Anti-Tg (56/155, 36.1%) or any thyroid disease profile (subclinical hypothyroidism, 8/155, 5.2%; overt hypothyroidism, 2/155, 1.3%; subclinical hyperthyroidism, 12/155, 7.7%; overt hypothyroidism, 2/155, 1.3%) did not show this predictive behaviour. Next, we analysed the early occurrence of HOMA-IR positivity in subjects who have converted from seronegative to seropositive for anti-TPO, anti-Tg and thyroid profiles to identify whether high HOMA-IR scores could predict thyroid disease. Of 206 subjects, 36 (17.5%) had HOMA-IR positivity before the onset of anti-TPO seropositivity. Moreover, 13/70 (18.6%) subjects only had HOMA-IR positivity before the onset of thyroid disease, and 16/64 (25.0%) had HOMA-IR change prior to the onset of anti-Tg negativity. These data did not show any significant relationship with HOMA-IR positivity occurring ahead of either anti-TPO, anti-Tg or thyroid disease.

Figure 2. The prevalence of different thyroid diseases, anti-TPO and anti-Tg prior to the onset of homeostatic model assessment-insulin resistance (HOMA-IR) elevation compared with their respective control groups. The thyroid control group consists of subjects who had thyroid disease-parallel, thyroid disease-following and no thyroid disease to the onset of HOMA elevation. Anti-TPO control group consists of subjects who had anti-TPO-parallel, anti-TPO-following and no anti-TPO to the onset of HOMA elevation. Anti-Tg control group consists of subjects who had anti-Tg-parallel, anti-Tg-following and no anti-Tg to the onset of HOMA elevation. Tg, Thyroglobulin; TPO, Thyroid peroxidase.

Two-way ANOVA was performed with HOMA-IR as the dependent variable and the thyroid hormones (TSH, FT4, FT3, RT3, T4 and T3) as the independent variables. Significant differences were observed between TSH and FT4 (p=0.000197), TSH-RT3 (p=0.000122), TSH-T3 (p=0.000198), TSH-T4 (p=0.000162), TSH-FT3 (p=0.000185), FT4-FT3 (p=0.000193), FT4-T3 (p=0.000206), FT4-RT3 (p=0.000127), FT4-T4 (p=0.000169), FT3-RT3 (p=0.00012), FT3-T3 (p=0.000193), FT3-T4 (0.000159), RT3-T3 (p=0.000127), RT3-T4 (p=0.000105) and T3-T4 (p=0.000169) across various groups. The antibodies, anti-TPO and anti-Tg did not show a significant difference with the thyroid hormones (table 5).

Table 5

Two-way ANOVA between homeostatic model assessment-insulin resistance (dependent variable) and the thyroid markers

Source of variation	Sum of squares (SS)	df	Mean square (MS)	F value	P value
TSH-FT4	7.33E+08	2	3.67E+08	8.533169	0.000197
TSH-ATPO	8.83E+08	2	4.41E+08	10.27449	3.46E-05
TSH-A-TG	1E+09	2	5.02E+08	11.67741	8.52E-06
TSH-FT3	7.38E+08	2	3.69E+08	8.59521	0.000185
TSH-RT3	7.74E+08	2	3.87E+08	9.013417	0.000122
TSH-T3	7.33E+08	2	3.66E+08	8.530798	0.000198
TSH-T4	7.5E+08	2	3.75E+08	8.729806	0.000162
FT4-ATPO	8.8E+08	2	4.4E+08	10.24098	3.58E-05
FT4-A-TG	1E+09	2	5.01E+08	11.64849	8.77E-06
FT4-FT3	7.35E+08	2	3.67E+08	8.55491	0.000193
FT4-RT3	7.71E+08	2	3.85E+08	8.975	0.000127
FT4-T3	7.29E+08	2	3.65E+08	8.490192	0.000206
FT4-T4	7.47E+08	2	3.73E+08	8.69013	0.000169
ATPO-A-TG	1.11E+09	2	5.57E+08	12.96656	2.35E-06
ATPO-FT3	8.84E+08	2	4.42E+08	10.29246	3.4E-05
ATPO-RT3	9.14E+08	2	4.57E+08	10.64307	2.4E-05
ATPO-T3	8.8E+08	2	4.4E+08	10.23902	3.59E-05
ATPO-T4	8.94E+08	2	4.47E+08	10.40464	3.04E-05
A-TG-FT3	1E+09	2	5.02E+08	11.69294	8.39E-06
A-TG-RT3	1.03E+09	2	5.16E+08	11.99863	6.18E-06
A-TG-T3	1E+09	2	5E+08	11.64679	8.78E-06
A-TG-T4	1.01E+09	2	5.07E+08	11.79022	7.61E-06
FT3-RT3	7.76E+08	2	3.88E+08	9.034001	0.00012
FT3-T3	7.35E+08	2	3.67E+08	8.552545	0.000193
FT3-T4	7.52E+08	2	3.76E+08	8.751058	0.000159
RT3-T3	7.71E+08	2	3.85E+08	8.972747	0.000127
RT3-T4	7.87E+08	2	3.94E+08	9.162147	0.000105
T3-T4	7.46E+08	2	3.73E+08	8.687803	0.000169

The values that are statistically significant are mentioned in bold.

Discussion

Patients with thyroid disparities are known to have glucose and insulin metabolism disorders; however, none of the studies have elucidated the disease marker sequence. To our knowledge, this is the first study to evaluate the sequence of markers occurring in thyroid disease and insulin resistance comorbidity. The direction of disease correlation is important for effective follow-up testing and treatment strategies for at-risk subjects.

To understand the general prevalence, we first evaluated the association between thyroid disease and diabetes markers in single visit subjects. We evaluated thyroid disease profiles categorised based on their serum TSH and FT4 levels. We found that both overt hypothyroidism and overt hyperthyroidism had elevated levels of HOMA-IR. HbA1C was elevated in subclinical hypothyroidism, overt hypothyroidism and overt hyperthyroidism. Glucose was elevated in both subclinical hypothyroidism and overt hyperthyroidism, and insulin was only elevated in overt hypothyroidism. Clinical hyperthyroidism is associated with abnormal glucose tolerance and insulin resistance.¹² Specifically, overt hyperthyroidism has increased demand for insulin which is often due to accelerated metabolism, tissue resistance to insulin and elevated insulin degradation.¹³ Many theories have been established to explain the peripheral insulin resistance in hyperthyroidism. Some studies show that increased secretion of adiponectin such as interleukin-6 and Tumor necrosis factor alpha (TNF-α) in hyperthyroid patients may be related to the development of insulin resistance.¹⁴ Another mechanism by which thyroid hormones increase hepatic glucose production is through the increased expression of glucose transporter 2 (GLUT2) on the hepatic plasma membrane which was found to be twice as high in hyperthyroid patients compared with hypothyroid patients.¹ There are comparatively lesser human studies conducted to evaluate the association between hypothyroidism and insulin resistance. In hypothyroidism, it is speculated that decreased intestinal glucose absorption rate and decreased adrenergic activity may lead to a reduction in glycogenolysis in the liver and muscles and gluconeogenesis that could further decrease the baseline insulin secretion.^{12 15} This study reported a significant prevalence of increased HOMA-IR scores in hypothyroid subjects indicating the possibility of insulin resistance. Similarly, other studies have reported that hypothyroidism induced a decrease in the insulin-mediated glucose disposal that reverted on treatment.^16–18

Autoimmune thyroid disease and insulin resistance are two chronic inflammatory diseases. Hence, we evaluated the relationship between subjects that were seropositive for thyroid autoantibodies and insulin resistance. Our results showed that subjects with thyroid antibodies, anti-TPO and anti-Tg had significantly elevated HOMA-IR scores compared with their respective control groups. Moreover, seropositive subjects for anti-TPO had elevated insulin levels compared with seronegative subjects. Studies have reported an association between anti-TPO titre, the secretory function of monocytes, lymphocytes and pro-inflammatory cytokines such as TNF-α and interleukin-6 (IL-6).¹⁹ These monocytes, lymphocytes and their secretary cytokines TNF-α and IL-6 are also responsible for developing insulin resistance.²⁰ Our results were consistent with Mazaheri et al where they found significantly high insulin levels in subjects with anti-TPO antibodies more than 1000 IU/mL.²¹ However, their HOMA-IR score did not show any significant difference.

The association between insulin resistance and autoimmune thyroid diseases has long been a topic of controversy. To assess the sequence of occurrence of these disease markers, we evaluated the predictive characteristics of anti-TPO, anti-Tg and thyroid disease in insulin resistance and vice versa. Interestingly, we found that 70.3% of subjects had anti-TPO prior to the HOMA-IR change from negative to positive, indicating a possible predictive role of anti-TPO in insulin resistance. None of the thyroid disease profiles (15.5%) nor anti-Tg (36.1%) preceded the HOMA-IR score change, indicating that thyroid disease profiles or anti-Tg does not contain any significant predictability on insulin resistance. However, the occurrence of insulin resistance (in terms of high HOMA-IR scores) before anti-TPO positivity, anti-Tg positivity or any thyroid disease positivity did not provide any significant results, eliminating the hypothesis of the occurrence of insulin resistance before anti-TPO, anti-Tg or thyroid disease seropositivity.

The two-way ANOVA results indicate that HOMA-IR is significantly affected by the thyroid hormones whereas there is no association between HOMA-IR and the thyroid autoantibodies (no significance). This suggests the role of these hormones in insulin resistance and ultimately in diabetes risk as shown by previous studies.²² Moreover, the significant differences between the thyroid hormone levels indicate the interactions among these hormones that has a role in thyroid functions as well as disorders. The ANOVA results are in accordance with the normal functioning of thyroid hormones and autoantibodies which suggests the importance of analysing these hormones and antibodies during thyroid function assessment and diagnosis of thyroid disorders.

In this study, we examined the effect of the direction of comorbid diseases, thyroid disease and insulin resistance. The primary strength of our study is the large population size including a larger set of markers from both thyroid disease and diabetes. The use of Elecsys assays and the Beckman Coulter AU analyser enabled precise and accurate measurement of the thyroid and diabetes markers, respectively. However, a limitation in our study is the distorted male-to-female ratio. A study with similar male-to-female ratio with all-inclusive clinical characteristics such as thyroid treatments and female menopausal status would be required to extrapolate the results to eventually achieve a generalised outcome. In conclusion, we showed that high levels of the thyroid autoantibody and anti-TPO precedes the changes in insulin resistance (in terms of HOMA-IR score change from negative to positive). This suggests that anti-TPO could potentially be used as a predictive marker for disease stratification.

We acknowledge Vibrant America LLC for supporting this research.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

The study was conducted under the ethical principles that have their origins in the Declaration of Helsinki. This is a retrospective study conducted from remnant samples of individuals that visited Vibrant Clinical Lab for routine tests. The IRB (WCG IRB (Western Institutional Review Board; #1-1098539-1)) exemption enabled us to use the de-identified laboratory data for the retrospective analysis.

Footnote

Contributors Conception and study design: HK, JJR and VJ. Performing experiments: KK and TW. Analysis and interpretation: TS, KB, QS and HK. Manuscript preparation: TS and HK. HK is the guarantor. All authors read and approved the final manuscript.

Funding Vibrant America provided funding for this study in the form of salaries for authors (TS, QS, KK, VJ, TW, KB, HK, JJR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests The authors have read the journal’s policy, and the authors of this manuscript have the following competing interests: TS and QS are paid employees of Vibrant America. KK, VJ, TW, KB, HK and JJR are paid employees of Vibrant Sciences. Vibrant Sciences or Vibrant America could benefit from increased testing based on the results. There are no patents, products in development or marketed products to declare.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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