Thyroid diseases, including autoimmune thyroid diseases and thyroid cancer, are known to have high heritability. Family and twin studies have indicated that genetics plays a major role in the development of thyroid diseases. Thyroid function, represented by thyroid stimulating hormone (TSH) and free thyroxine (T4), is also known to be partly genetically determined. Before the era of genome-wide association studies (GWAS), the ability to identify genes responsible for susceptibility to thyroid disease was limited. Over the past decade, GWAS have been used to identify genes involved in many complex diseases, including various phenotypes of the thyroid gland. In GWAS of autoimmune thyroid diseases, many susceptibility loci associated with autoimmunity (human leukocyte antigen [HLA], protein tyrosine phosphatase, non-receptor type 22 [PTPN22], cytotoxic T-lymphocyte associated protein 4 [CTLA4], and interleukin 2 receptor subunit alpha [IL2RA]) or thyroid-specific genes (thyroid stimulating hormone receptor [TSHR] and forkhead box E1 [FOXE1]) have been identified. Regarding thyroid function, many susceptibility loci for levels of TSH and free T4 have been identified through genome-wide analyses. In GWAS of differentiated thyroid cancer, associations at FOXE1, MAP3K12 binding inhibitory protein 1 (MBIP)-NK2 homeobox 1 (NKX2-1), disrupted in renal carcinoma 3 (DIRC3), neuregulin 1 (NRG1), and pecanex-like 2 (PCNXL2) have been commonly identified in people of European and Korean ancestry, and many other susceptibility loci have been found in specific populations. Through GWAS of various thyroid-related phenotypes, many susceptibility loci have been found, providing insights into the pathogenesis of thyroid diseases and disease co-clustering within families and individuals.
Autoimmunity ; Genes, Homeobox ; Genetics ; Genome-Wide Association Study* ; Graves Disease ; Hashimoto Disease ; Humans ; Leukocytes ; Neuregulin-1 ; Phenotype ; Protein Tyrosine Phosphatase, Non-Receptor Type 22 ; Receptors, Interleukin-2 ; T-Lymphocytes, Cytotoxic ; Thyroid Diseases* ; Thyroid Gland* ; Thyroid Neoplasms* ; Thyrotropin ; Thyroxine

Hyperglycemia during chemotherapy occurs in approximately 10% to 30% of patients. Glucocorticoids and L-asparaginase are well known to cause acute hyperglycemia during chemotherapy. Long-term hyperglycemia is also frequently observed, especially in patients with hematologic malignancies treated with L-asparaginase-based regimens and total body irradiation. Glucocorticoid-induced hyperglycemia often develops because of increased insulin resistance, diminished insulin secretion, and exaggerated hepatic glucose output. Screening strategies for this condition include random glucose testing, hemoglobin A1c testing, oral glucose loading, and fasting plasma glucose screens. The management of hyperglycemia starts with insulin or sulfonylurea, depending on the type, dose, and delivery of the glucocorticoid formulation. Mammalian target of rapamycin (mTOR) inhibitors are associated with a high incidence of hyperglycemia, ranging from 13% to 50%. Immunotherapy, such as anti-programmed death 1 (PD-1) antibody treatment, induces hyperglycemia with a prevalence of 0.1%. The proposed mechanism of immunotherapy-induced hyperglycemia is an autoimmune process (insulitis). Withdrawal of the PD-1 inhibitor is the primary treatment for severe hyperglycemia. The efficacy of glucocorticoid therapy is not fully established and the decision to resume PD-1 inhibitor therapy depends on the severity of the hyperglycemia. Diabetic patients should achieve optimized glycemic control before initiating treatment, and glucose levels should be monitored periodically in patients initiating mTOR inhibitor or PD-1 inhibitor therapy. With regard to hyperglycemia caused by anti-cancer therapy, frequent monitoring and proper management are important for promoting the efficacy of anti-cancer therapy and improving patients' quality of life.
Blood Glucose ; Drug Therapy ; Fasting ; Glucocorticoids ; Glucose ; Hematologic Neoplasms ; Humans ; Hyperglycemia* ; Immunotherapy ; Incidence ; Insulin ; Insulin Resistance ; Mass Screening ; Prevalence ; Quality of Life ; Sirolimus ; Whole-Body Irradiation

Background: Osteoporosis is the most common metabolic bone disease and can cause fragility fractures. Despite this, screening utilization rates for osteoporosis remain low among populations at risk. Automated bone mineral density (BMD) estimation using computed tomography (CT) can help bridge this gap and serve as an alternative screening method to dual-energy X-ray absorptiometry (DXA). Methods: The feasibility of an opportunistic and population agnostic screening method for osteoporosis using abdominal CT scans without bone densitometry phantom-based calibration was investigated in this retrospective study. A total of 268 abdominal CT-DXA pairs and 99 abdominal CT studies without DXA scores were obtained from an oncology specialty clinic in the Republic of Korea. The center axial CT slices from the L1, L2, L3, and L4 lumbar vertebrae were annotated with the CT slice level and spine segmentation labels for each subject. Deep learning models were trained to localize the center axial slice from the CT scan of the torso, segment the vertebral bone, and estimate BMD for the top four lumbar vertebrae. Results: Automated vertebra-level DXA measurements showed a mean absolute error (MAE) of 0.079, Pearson’s r of 0.852 (P<0.001), and R2 of 0.714. Subject-level predictions on the held-out test set had a MAE of 0.066, Pearson’s r of 0.907 (P<0.001), and R2 of 0.781. Conclusion CT scans collected during routine examinations without bone densitometry calibration can be used to generate DXA BMD predictions.

Objectives: Along with the exponentially-growing data produced and accumulated every day through mobile platforms, social networking services, the Internet, and other media, information is becoming increasingly important as a strategic resource. This report presents specific and clear directions and suggests empirical project plans regarding innovations in regional health information systems to promote the utilization of medical information. Methods: We reviewed and examined documents about global trends and examples of regional health information systems. The problems and solutions of health information utilization and regional health information systems in Korea were analyzed. Results: This study presented examples of the establishment of health information systems, problems in the use of local healthcare information, and an empirical project for improvement. Conclusions The results of this study imply the need for long-term and systematic approaches for the use of medical information and the establishment of a local healthcare information system, along with implementation plans. As a first step, it is imperative to clarify the goal of building a medical information system, the information that must be provided to build the system, and the data that should be collected to provide such information, while moving away from the mentality of focusing on technology-oriented medical information services. In addition, it is necessary to consider information governance, data-based service development, and the medical innovation framework, which are ways to efficiently manage, utilize, and systemize the data to be collected.

Purpose: Obesity has been determined to be associated with fat mass and obesity-associated (FTO) gene and thyroid cancer risk. However, the effect of combined interactions between obesity and the FTO gene on thyroid cancer needs further investigation. This study aimed to examine whether interactions between body mass index (BMI) and the FTO gene are associated with an increased risk of thyroid cancer. Materials and Methods: A total of 705 thyroid cancer cases and 705 sex- and age-matched normal controls were selected from the Cancer Screenee Cohort in National Cancer Center, Korea. A conditional logistic regression model was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for the measure of associations and the combined effect of BMI and FTO gene on thyroid cancer. Results: BMI was associated with an increased risk of thyroid cancer in subclasses of overweight (23-24.9 kg/m2; adjusted OR, 1.50; 95% CI, 1.12 to 2.00) and obese (≥ 25 kg/m2) (adjusted OR, 1.62; 95% CI, 1.23 to 2.14). There were positive associations between the FTO genetic variants rs8047395 and rs8044769 and an increased risk of thyroid cancer. Additionally, the combination of BMI subclasses and FTO gene variants was significantly associated with thyroid cancer risk in the codominant (rs17817288), dominant (rs9937053, rs12149832, rs1861867, and rs7195539), and recessive (rs17817288 and rs8044769) models. Conclusion Findings from this study identified the effects of BMI on thyroid cancer risk among individuals carrying rs17817288, rs9937053, rs12149832, rs1861867, rs7195539, and rs8044769, whereas the effects of BMI may be modified according to individual characteristics of other FTO variants.

Objectives: Along with the exponentially-growing data produced and accumulated every day through mobile platforms, social networking services, the Internet, and other media, information is becoming increasingly important as a strategic resource. This report presents specific and clear directions and suggests empirical project plans regarding innovations in regional health information systems to promote the utilization of medical information. Methods: We reviewed and examined documents about global trends and examples of regional health information systems. The problems and solutions of health information utilization and regional health information systems in Korea were analyzed. Results: This study presented examples of the establishment of health information systems, problems in the use of local healthcare information, and an empirical project for improvement. Conclusions The results of this study imply the need for long-term and systematic approaches for the use of medical information and the establishment of a local healthcare information system, along with implementation plans. As a first step, it is imperative to clarify the goal of building a medical information system, the information that must be provided to build the system, and the data that should be collected to provide such information, while moving away from the mentality of focusing on technology-oriented medical information services. In addition, it is necessary to consider information governance, data-based service development, and the medical innovation framework, which are ways to efficiently manage, utilize, and systemize the data to be collected.

Purpose: Obesity has been determined to be associated with fat mass and obesity-associated (FTO) gene and thyroid cancer risk. However, the effect of combined interactions between obesity and the FTO gene on thyroid cancer needs further investigation. This study aimed to examine whether interactions between body mass index (BMI) and the FTO gene are associated with an increased risk of thyroid cancer. Materials and Methods: A total of 705 thyroid cancer cases and 705 sex- and age-matched normal controls were selected from the Cancer Screenee Cohort in National Cancer Center, Korea. A conditional logistic regression model was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for the measure of associations and the combined effect of BMI and FTO gene on thyroid cancer. Results: BMI was associated with an increased risk of thyroid cancer in subclasses of overweight (23-24.9 kg/m2; adjusted OR, 1.50; 95% CI, 1.12 to 2.00) and obese (≥ 25 kg/m2) (adjusted OR, 1.62; 95% CI, 1.23 to 2.14). There were positive associations between the FTO genetic variants rs8047395 and rs8044769 and an increased risk of thyroid cancer. Additionally, the combination of BMI subclasses and FTO gene variants was significantly associated with thyroid cancer risk in the codominant (rs17817288), dominant (rs9937053, rs12149832, rs1861867, and rs7195539), and recessive (rs17817288 and rs8044769) models. Conclusion Findings from this study identified the effects of BMI on thyroid cancer risk among individuals carrying rs17817288, rs9937053, rs12149832, rs1861867, rs7195539, and rs8044769, whereas the effects of BMI may be modified according to individual characteristics of other FTO variants.

Background: This study aims to elucidate the associations among dietary seaweed (gim and miyeok/dashima) and iodine intakes, the rs77277498 polymorphism of the SLC5A5 gene codifying the sodium/iodine symporter, and thyroid cancer risk in a Korean population. Methods: We conducted a case-control study of 117 thyroid cancer cases and 173 controls who participated in the Cancer Screenee Cohort between 2002 and 2014 at the National Cancer Center, Korea. The amount of seaweed and iodine consumption (g/day) was estimated using the residual energy adjustment method. We calculated odds ratios (ORs) and their 95% confidence intervals (CIs) using a multivariable logistic regression model for the separate and combined effect of dietary iodine-based intake and SLC5A5 polymorphism (rs77277498, C>G) on thyroid cancer. Results: Dietary gim and iodine intakes were inversely associated with thyroid cancer, with ORs of 0.50 (95% CI, 0.30 to 0.83) and 0.57 (95% CI, 0.35 to 0.95), respectively, whereas the associations for dietary miyeok/dashima and total seaweed intakes were not significant. However, compared with individuals carrying the C/C genotype of the rs77277498 polymorphism with a low intake of all dietary factors, those carrying the G allele with a high intake had a lower risk of thyroid cancer, with ORs of 0.25 (95% CI, 0.10 to 0.56), 0.31 (95% CI, 0.12 to 0.77), 0.26 (95% CI, 0.10 to 0.62), and 0.30 (95% CI, 0.12 to 0.73) for the consumption of gim, miyeok/dashima, total seaweed, and iodine, respectively. Conclusion In summary, our results supported the evidence of the protective effects of dietary gim and iodine intake against thyroid cancer risk, and this association can be strengthened by SLC5A5 rs77277498 genotypes.

BACKGROUND: The multiple allergosorbent test chemiluminescent assay (MAST-CLA) system is a simple method for measuring total and allergen-specific IgE antibodies in the serum of patients with atopic dermatitis. Total IgE, however, is much frequently higher, even if no allergen-specific IgE antibodies can be detected in serum. OBJECTIVE: The purpose of this study was to evaluate total IgE class, the allergen frequencies and their correlations in MAST-CLA in child and adult atopic dermatitis patients respectively. METHODS: A total of fifty two adult patients and ninety child patients with atopic dermatitis were evaluated by MAST-CLA between march 2002 and march 2005 at Soonchunhyang hospital. Positive rates of specific IgE and the total serum IgE level of the MAST-CLA allergy system were compared between child and adult patients. RESULTS: Among the subjects, 84.5% (80.0% for child patients and 92.3% for adult patients) of patients showed an elevated serum total IgE (more than class level 2) and 54.9% (45.6% for child patients, 71.2% for adult patients) revealed at least more than one allergen-specific IgE by MAST-CLA. The average 3.76 (3.39 for child patients, 4.16 for adult patients) different allergens was simultaneously detected in a single positive serum. Commonly-positive allergen rates, in descending order, were D. farinae 44.4%, D. pteronyssynos 38.7% and house dust 26.8%. Furthermore, the higher total serum IgE level in adult patients, the more probability of allergen-specific IgE positive results being disclosed (p<0.05). The number of allergen-specific IgE positive results was increased in a higher serum total IgE level (p<0.05). But total IgE positive rates which had allergen-specific antibody negative patients was 37.5% (45.8% for child patients, 25.0% for adult patients). Good correlation was obtained between total IgE levels and number of positive allergen-specific IgE in MAST-CLA, with 0.551 correlation coefficiency (p<0.05). CONCLUSION: Our study suggested that the MAST-CLA allergy system is a useful screening test to detect allergen- specific IgE and to evaluate patients with atopic dermatitis. But other allergen screening tests should be used for detecting allergens, when MAST-CLA total IgE class is increased over class 2 with no detectable specific IgE.
Adult* ; Allergens ; Antibodies ; Child* ; Dermatitis, Atopic* ; Dust ; Humans ; Hypersensitivity* ; Immunoglobulin E* ; Luminescent Measurements ; Mass Screening