Exploring RNA Sequencing Data to Identify Disease-Specific Biomarkers for Thyroid Disorders

Shubhangi Vibhor Garg

Mentors: Dr. Karen Ross and Dr. Mark Danielsen, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center

Date/Time: April 25th, 2023 at 12:00pm.

Abstract: The thyroid gland is a little butterfly-shaped gland located in the anterior of the neck, directly below the Adam’s apple. This gland is essential for the body’s endocrine system because it produces two hormones, triiodothyronine (T3) and thyroxine (T4), which help to regulate the body’s metabolism.  These hormones have an impact on nearly every cell in the body and are engaged in a variety of physiological processes such as energy production, growth, and development. Thyroid disorders can develop when the thyroid gland produces too many or too few of these hormones. Hypothyroidism, often known as an underactive thyroid, arises when the thyroid gland does not produce enough T3 and T4. This might result in a variety of symptoms such as fatigue, weight gain, depression, and constipation. Hypothyroidism is most usually caused by Hashimoto’s thyroiditis, an autoimmune illness in which the immune system attacks the thyroid gland. Hyperthyroidism, on the other hand, occurs when the thyroid gland generates an abnormally large amount of T3 and T4. Weight loss, anxiousness, quick heartbeat, and heat intolerance are all possible signs of hyperthyroidism.  The most prevalent cause of hyperthyroidism is Graves’ disease, an autoimmune illness that causes the thyroid gland to produce an excess of thyroid hormones. Other thyroid illnesses include goiter, a thyroid gland enlargement, and thyroid carcinoma, an uncommon but dangerous type of cancer that affects the thyroid gland. Thyroid disease diagnosis and treatment are critical to overall health and well-being. Depending on the underlying cause of the disease, treatment may include drugs, radiation therapy, or surgery.

This internship was carried out with the goal of examining RNA sequencing data to uncover disease-specific biomarkers for thyroid disorders. The primary goal was to evaluate gene expression data from hyperthyroid and hypothyroid patients in order to better understand therapy responses in thyroid disease patients. This was accomplished by writing Python and R programs and employing bioinformatic tools such as DAVID. Principal component analysis revealed no clear differentiation between hypothyroid and hyperthyroid samples, although it did reveal variances within the categories.  Based on a corrected p-value of 0.05, the results of unpaired testing revealed 43 differentially expressed genes. A heatmap revealed strong upregulation of 43 of the genes in four of the six hyperthyroid samples.