Type 2 Diabetes and Thyroid Disease: What's the Connection?

Research Aims 

Type 2 Diabetes is a major global epidemic. However, despite the significant strides made towards the management of T2DM, a significant number of patients still presen complications resulting from impaired glycemic control. The major reason for this is that the thyroid dysfunctions and type 2 diabetes signs and symptoms are very comparable and thus are snubbed at times. The main aim of this research proposal is to lay down a foundation for future studies that can allow for the setting up of thyroid dysfunction management and screening in make an effort to attain glycemic control in T2DM.

Research Questions 

What is the burden of thyroid disease among patients with type 2 diabetes?

What is the relationship between type 2 diabetes and thyroid disease?

Research Objectives 

To determine the patterns of thyroid disease in type 2 diabetes patients

To determine the prevalence of thyroid disease in type 2 diabetes patients.

Significance 

Diabetes mellitus is a leading cause of death across the globe. The disorder is also regarded as being one of the most common endocrine disorders. The onset of type 2 diabetes is insulin secretion and action defects. In 2002, the global prevalence of type 2 diabetes was over 160 million, and the number was anticipated to reach over 360 million by 2030 (Telwani et al., 2017). Other most common disorder among people is thyroid dysfunctions, and it is regarded as being the second most common endocrine disorder. This is an indication that an individual can suffer from both diabetes and thyroid disorders. Very few studies have shown the correlation existing between type 2 diabetes and thyroid disorders. Insulin and thyroid hormones are antagonists, and they play a significant part in the metabolism of lipids, proteins and carbohydrates. In case the level of the two hormones changes, a functional impairment occurs.

Thyroid dysfunction diagnosis in patients with T2DM has always been a difficult undertaking as the clinical manifestation of the two disorders presents similar signs and symptoms. This can lead to the overlooking of the signs and symptoms of thyroid disorders, which can be attributed to other medical conditions. It is an indication that there is an interdependent affiliation between type 2 diabetes and thyroid disease. However, due to the minimal research into the relationship, clinicians cannot optimally manage the two disorders. It is this gap that this proposed research aims at filling as it would provide information on the incidence of thyroid disease in type 2 diabetes patients. Future researchers that can allow for the setting up of thyroid dysfunction management and screening to make an effort in attaining glycemic control in type 2 diabetes will use the findings from the proposed research. Moreover, the findings of the proposed research will help clinicians in identifying the two disorders much earlier as this will lead to an improvement of lipid profiles, blood pressure and cardiovascular function thus decreasing the long-standing risks related with T2DM.

Background and Justification 

The two most common endocrine related disorders found in the overall populace include diabetes and thyroid disease. Diabetes control is negatively affected by thyroid disease, and this can lead to higher levels of adverse outcomes in a patient. Hyperglycemia is caused by hyperthyroidism while episodes of hypoglycemia are caused by events of hypothyroidism (Liu et al., 2018). These two conditions do not just affect the type 2 diabetes management but also deteriorates the metabolic sustenance of the disorder. Nonetheless, uncontrolled management of diabetes impairs the thyroid-stimulating hormone and thyroid-releasing hormone though glycemic control management can assist in the controlling of the impairment.

Various studies have been able to show the relation between thyroid disorders and T2DM. According to Wang (2013), the researches have been able to show there are various risk factors that allow the relationship to exist, which include hormonal genetic and biochemical functions. Ogbonna & Ezani (2019) cited that comorbidities and gender are the most common risk factors associated with the two disorders. The most-at-risk population likely to suffer from thyroid disease and T2DM is the neonates and elderly. As an individual advances in age, one is likely to suffer from an increased insulin secretion abnormality and insulin resistance, and this makes the older people suffering from thyroid disorders to have a higher probability of developing type 2 diabetes (Heidari, Abdani & Mansourina,2018). Individuals who have had type 1 diabetes for a long time, especially the women, are also regarded as being at-risk.

A study by Tsatsoulis (2018) found that 1 in every 10 people suffering from T2DM have thyroid dysfunctions. The study found out that there is n higher likelihood of developing thyroid disorders in a patient with diabetes. Autoimmune diseases have a substantial number of related environmental and genetic triggers that are also associated with diabetes. The co-occurring conditions and symptoms associated with diabetes in most cases are similar to those of thyroid dysfunction, and this increases the risk of the disorders, which forms the relationship. Tsatsoulis (2018) states that some studies have linked hypothyroidism amongst type 2 diabetic patients despite the disease not being an autoimmune disorder.

A similar study by Pihlajamaki et al. (2009) found out that thyroid gland nodularity is increased because of insulin resistance associated with diabetes. The lipid balance in the body is impaired by subclinical hypothyroidism resulting from insulin resistance, and this leads to the development of metabolic syndrome in a patient. A study carried out by Arduc et al. (2014) was able to find similar results on the relationship between diabetes and subclinical hypothyroidism. Insulin resistance is the major cause of subclinical and clinical hypothyroidism. Hypothyroidism is the state whereby the insulin signal on taking sugar out of the body is not adhered to by the body. Diabetes mellitus is thus triggered once there is an increased sugar in blood following insulin resistance (Arduc et al., 2014; Heidari, Andani & Mansournia, 2018).

In a study by Ogbonna & Ezani (2019), it found out that patients with thyroid dysfunctions have a higher risk of kidney failure because of increased rates of blood sugar. The major cause for this is the increase size of thyroid gland nodes resulting from insulin resistance. Zhenet al. (2019) cited that this could lead to the development of other chronic diseases such as coronary heart diseases and kidney failure.

Liu et al. (2018) found out that diabetes alters the functional abilities of the thyroid hormone, and this leads thyroid conditions. Similarly, the thyroid gland can be blocked from producing thyroid hormone by the insulin hormone as it can imitate the gland’s functions. In the study by Liu et al. (2018), it found out that type 2 diabetes patients will also tend to have thyroid disease-related symptoms.

From the literature review above, it is an indication that the relationship between thyroid disease and T2DM is complex and interdependent. The two disorders are hormonal and endocrine, and this makes their symptoms similar. From the studies, they have been able to point out that there is a positive relationship between the two. However, the studies have not pointed out the means through which one can distinguish the two disorders. This proposed research aims at filling this gap.

Approach 

To answer the research question, a cross-sectional descriptive survey design was used. The major reason for using this type of research design is that it allows one in learning about the relationship between a disease and any other interest variables that exist in a given populace at a single point in time. This study design was selected, as it would enable the researcher to measuring the prevalence and patterns of all factors under investigation. However, the major disadvantage of this type of study design is that it cannot be used in studying the occurrence rare diseases and is at times not able to measure incidence. The study location will be a selected healthcare facility that offers both inpatient and outpatient services. The minimum sample for the study will be 200 patients with type 2 diabetes. A systemic random sampling will be used in selecting the study sample whereby numbers will be issued to all participants who meet the inclusion criteria. Every third patient will be selected to be part of proposed research. However, every patient will have to sign an informed consent form before becoming part of the study. The exclusion criteria will involve patients who have been earlier diagnosed with type 1 diabetes, patients aged 35 years and below and those who will not have signed the informed consent form. For the patients who will be chosen as participants, a brief physical and history examination will be conducted. The type 2 diabetes co-morbidities and duration will be determined, and all this information entered to the proposed research proforma.

The minimization of pre-analytical errors shall be enabled by strictly adhering to standard storage, preparation and specimen collection procedures. The Immunology laboratory swill also is used in carrying out laboratory tests to ensure quality is maintained. During each batch of the test. Standard internal quality and calibration of the machines will be conducted. Specimens recorded as being hemolysed or highly lipemic shall also be replaced

Laboratory Experiments 

Collection, Transportation and Storage of Specimen 

Each patient will provide 4mls of blood, which will be put into a plain vacutainer bearing a blue lid. After collecting the required amount of blood from the participants, the blood will be transported to the immunology laboratory, whereby it will undergo batch assaying and stored. The temporary storage of the blood samples will be facilitated by cooler boxes having a temperature of 4 degree Celsius. Once the samples reach the laboratory, serum will be separated from the blood, which will be frozen and later stored any matter that will not be useful for the study will be filtrated or centrifuged out of the required sample matter.

Analysis of Specimen 

Thyroid Stimulating Hormone (TSH) 

The classic sandwich ELISA will be used in assaying the TSH. This allows one to use the Biotin-Streptavidin that has a high affinity. The microtitre wells walls are coated using streptavidin together with the gathered enzymes, controls and specimens. Another biotinylated monoclonal anti-thyroid stimulating hormone is mixed leading to the formation of a sandwich-like structure that is attracted to the surface of the wells following the immobilized streptavidin and biotin interaction.

Free Thyroxine (FT4) 

The FT4 assay was enabled through competitive binding the T4 peroxidase and free thyroxine conjugate for a restricted quantity of binding spots on the anti-T4 coated well.

Data Analysis 

The data from the study shall be entered into a password-protected Microsoft Access database system. To eliminate any form of inconsistency simple frequencies and correlations shall be run after comparing the data generated in the hard copy forms with that in the MS Database. Measures of central tendency such as standard deviation, maximum mode, medians and means will be used in summarizing continuous data such as FT4, TSH, BMI, weight, height, blood pressure, diabetes mellitus and age. Proportions, counts and frequencies will be used in summarizing nominal variables such as patterns and evaluation of thyroid disease, history of thyroid disease, educational level, gender, thyroid disease management and marital status. The entire data analysis shall be carried using the Statistical Package for the Social Sciences version 17.0.

Innovation 

The following approach is very innovative, as it will use the enzyme-linked immunosorbent assay test (ELISA) that is used in the measuring of antibodies within the human body. The ELISA test is important as it helps one in ascertaining whether there are antibodies in the body that are related to a certain illness. It is evident that thyroid disease and type 2 diabetes have similar signs and symptoms and thus distinguishing between the two is not an easy task using standard testing techniques such as the. Through the ELISA, it will have an ability to distinguish the antibodies related to each of the two disorders. Antibodies are produced by the body in response to antigens. The ELISA tests are carried out using blood sample from the patient. In most of the studies, they have relied on rapid diagnostic tests. According to a study by Mehra et al. (2014), the rapid diagnostic tests missed 17 out of 30 samples that were later confirmed as being reactive by the ELISA test when testing HIV infection. The accuracy rates of ELISA tests have also been recorded at 99.9%.

Expected Outcomes/Potential Problems and Difficulties 

The proposed research will be able to find out that a higher risk of diabetes and prediabetes to diabetes advancement is likely to cause higher thyroid-stimulating hormone and FT4 levels. The results of the study are in line with those from a study by Deiz et al. (2011) that found out there is positive and strong correlation between thyroid dysfunction and T2DM. The study shall also find out that that the elderly population has a higher risk of contracting type 2 diabetes that is parallel to the results of a research carried out by Celani et al. (1994). The thyroid function tests carried out using the ELISA tests to assess for FT4, and TSH found out that the rate of thyroid dysfunction in the study sample was 67% with a large number having subclinical hypothyroidism at 60%, 5% over hypothyroidism and 2 participants had subclinical hyperthyroidism. Generally, the proposed research shall find out that what has been found in earlier little research that there is a positive affiliation between thyroid dysfunction and type 2 diabetes.

The major problem encountered in the proposed research could be the inability to carry out the T3 assay test. This result from the fact that 85% of the thyroid hormone released by the thyroid glands is T4 while 155 accounts for T3. For one to come up with conclusive T3 results, one must measure many tests, and a single test may not give one a definitive answer to the problem. It is as a result of this that the T4 and TSH were used in the study as they can give one a much clearer picture of the thyroid functions.

Alternative Approaches 

In case the ELISA test does not provide conclusive T3 results, the MSD electrochemiluminescence detection technology shall become used. The labels used in electrochemiluminescent allow for the generation of light once stimulated within an appropriate chemical environment. The MSD assays electrochemiluminescent labels referred to as SULFO-TAGs are conjugated to allow for the detection of antibodies. The major advantages of electrochemiluminescence labels is that they are highly sensitive, easier and quicker to use and have unsurpassed performance and quality as compared to the ELISA tests.

References

Arduc, A., Isik, S., Ozuguz, U., Tutuncu, Y. A., Kucukler, F. K., Ozcan, H. N. ... & Guler, S. (2014). Relationship between thyroid nodules and non-functioning adrenal incidentalomas and their association with insulin resistance.  Endocrine Research ,  39 (3), 99-104. 

Celani, M. F., Bonati, M. E., & Stucci, N. (1994). Prevalence of abnormal thyrotropin concentrations measured by a sensitive assay in patients with type 2 diabetes mellitus.  Diabetes research (Edinburgh, Scotland) ,  27 (1), 15-25. 

Diez, J. J., Sánchez, P., & Iglesias, P. (2011). Prevalence of thyroid dysfunction in patients with type 2 diabetes.  Experimental and Clinical Endocrinology & Diabetes ,  119 (04), 201-207. 

Heidari, Z., Abdani, M., & Mansournia, M. A. (2018). Insulin resistance associated with differentiated thyroid carcinoma: penalized conditional logistic regression analysis of a matched case-control study data.  International journal of endocrinology and metabolism ,  16 (1). 

Liu, J., Duan, Y., Fu, J., & Wang, G. (2018). Association between thyroid hormones, thyroid antibodies, and cardiometabolic factors in non-obese individuals with normal thyroid function.  Frontiers in endocrinology ,  9 , 130 

Mehra, B., Bhattar, S., Bhalla, P., & Rawat, D. (2014). Rapid tests versus ELISA for the screening of HIV infection: our experience from a voluntary counselling and testing facility of a tertiary care centre in North India.  Isrn Aids ,  2014 . 

Ogbonna, S., & Ezeani, I. (2019). Risk Factors of Thyroid Dysfunction in Patients With Type 2 Diabetes Mellitus.  Frontiers in endocrinology ,  10 , 440. 

Pihlajamäki, J., Boes, T., Kim, E. Y., Dearie, F., Kim, B. W., Schroeder, J. ... & Goldfine, A. B. (2009). Thyroid hormone-related regulation of gene expression in human fatty liver.  The Journal of Clinical Endocrinology & Metabolism ,  94 (9), 3521-3529. 

Telwani, A. A., Wani, Z. H., Ashraf, Y., & Shah, A. A. (2017). Prevalence of thyroid dysfunction in type 2 diabetes mellitus: a case-control study.  Int J Res Med Sci ,  5 (10), 4527-4531.

Tsatsoulis, A. (2018). The role of insulin resistance/hyperinsulinism on the rising trend of the thyroid and adrenal nodular disease in the current environment.  Journal of clinical medicine ,  7 (3), 37

Wang, C. (2013). The relationship between type 2 diabetes mellitus and related thyroid diseases.  Journal of diabetes research ,  2013 .

Zheng, M., Wang, D., Chen, L., Chen, M. N., Wang, W., & Ye, S. D. (2019). The association between thyroid dysfunction (TD) and diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM).  International journal of clinical practice , e13415.