Repeated Low High-Density Lipoprotein Cholesterol and the Risk of Thyroid Cancer: A Nationwide Population- Based Study in Korea

Analysis of risk factors for papillary thyroid carcinoma and the association with thyroid function indicators

Objective

This study aims to analyze the relationship between papillary thyroid carcinoma (PTC) and various factors.

Methods

The study involved two groups-PTC patients and non-PTC controls. We utilized binary logistic regression and Least Absolute Shrinkage and Selection Operator (Lasso) regression for variable selection and risk factor analysis. Correlation analysis was performed using Spearman's rank correlation. The diagnostic value of thyroid stimulating hormone (TSH) levels for PTC was assessed using Receiver Operating Characteristic (ROC) curves.

Results

PTC patients exhibited higher body mass index (BMI) (23.71 vs. 22.66, p<0.05) and TSH levels (3.38 vs. 1.59, p<0.05). Urinary iodine concentration (UIC) was an independent predictor of PTC (OR=1.005, p<0.05). The optimal TSH threshold for PTC diagnosis was 2.4 mIU/L [The Area Under the Curve (AUC)=67.3%, specificity=71.4%, sensitivity=70.1%]. TSH levels positively correlated with BMI (r=0.593, p<0.05) and UIC (r=0.737, p<0.05).

Conclusions

UIC may be an independent predictor of PTC, and TSH levels have some diagnostic value for identifying PTC.

Associations Between Metabolic Obesity Phenotypes and Pathological Characteristics of Papillary Thyroid Carcinoma

OBJECTIVE

The association between obesity, metabolic dysregulation, and the aggressive pathological traits of papillary thyroid carcinoma (PTC) continues to be a contentious issue. To date, no investigations have examined the impact of metabolic status on the malignant pathological features of PTC in relation to obesity.

METHODS

This research involved 855 adult patients with PTC from Shandong Provincial Hospital, classified into 4 groups based on metabolic and obesity status: metabolically healthy nonobese, metabolically unhealthy nonobese (MUNO), metabolically healthy obese, and metabolically unhealthy obese. We employed logistic regression to investigate the relationship between these metabolic obesity phenotypes and PTC's pathological characteristics. Mediation analysis was also performed to determine metabolic abnormalities' mediating role in the nexus between obesity and these characteristics.

RESULTS

Relative to metabolically healthy nonobese individuals, the metabolically unhealthy obese group was significantly associated with an elevated risk of larger tumor sizes and a greater number of tumor foci in PTC. Mediation analysis indicated that obesity directly influences tumor size, whereas its effect on tumor multifocality is mediated through metabolic dysfunctions. Specifically, high-density lipoprotein cholesterol levels were notably associated with tumor multifocality within obese subjects, serving as a mediator in obesity's impact on this trait.

CONCLUSION

The concurrent presence of obesity and metabolic dysregulation is often connected to more aggressive pathological features in PTC. The mediation analysis suggests obesity directly affects tumor size and indirectly influences tumor multifocality via low high-density lipoprotein cholesterol levels.

Lipoprotein alterations in endocrine disorders - a review of the recent developments in the field

Dyslipidemia is one of the most common disorders worldwide, which, if left untreated, results in a multitude of complications. Thus proper diagnostics, which includes identifying of secondary causes of dyslipidemia is crucial. Endocrine disorders are an important cause of secondary dyslipidemia. This paper aims to review the publications on lipoprotein alterations in endocrine disorders from the past two years and provide an overview of the recent discoveries in this dynamically developing and large field. Significant changes in lipoprotein serum concentrations are present in most endocrinological diseases and can be modified with proper treatment. Some lipoproteins have also been proposed as markers in some endocrine diseases, e.g., thyroid carcinoma. From the scope of endocrine disorders, the largest number of studies explored the lipoprotein changes in polycystic ovary syndrome and in women during the menopausal and peri-menopausal period. Even though the association of thyroid disorders with dyslipidemia is already well studied, new research has delivered some exciting findings about lipoprotein alterations in euthyroid patients with either positive antithyroid peroxidase antibodies or reduced sensitivity to thyroid hormones. The problem of the adverse metabolic profile, including dyslipidemia in hypoprolactinemia has been recognized. Moreover, this review describes other significant discoveries encompassing lipoprotein alterations in disorders of the adrenals, thyroid, parathyroid glands, pituitary, and gonads. The up-to-date knowledge of the influence of endocrine disorders and hormonal changes on serum lipoproteins is prudent as it can significantly impact therapeutic decisions.

Association between organophosphate flame retardant exposure and lipid metabolism: data from the 2013-2014 National Health and Nutrition Examination Survey

Organophosphate flame retardants (OPFRs) are emerging environmental pollutants that can be detected in water, dust, and biological organisms. Certain OPFRs can disrupt lipid metabolism in animal models and cell lines. However, the effects of OPFRs on human lipid metabolism remain unclear. We included 1,580 participants (≥20 years) from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) to explore the relationship between OPFR exposure and lipid metabolism biomarkers. After adjusting for confounding factors, results showed that one-unit increases in the log levels of diphenyl phosphate (DPhP) (regression coefficient = -5.755; S.E. = 2.289; p = 0.023) and log bis-(1-chloro-2-propyl) phosphate (BCPP) (regression coefficient = -4.637; S.E. = 2.019; p = 0.036) were negatively associated with the levels of total cholesterol (TC) in all participants. One-unit increases in the levels of DPhP (regression coefficient = -2.292; S.E. = 0.802; p = 0.012), log bis (1,3-dichloro-2-propyl) phosphate (BDCPP) (regression coefficient = -2.046; S.E. = 0.825; p = 0.026), and log bis-2-chloroethyl phosphate (BCEP) (regression coefficient = -2.604; S.E. = 0.704; p = 0.002) were negatively associated with the levels of high-density lipoprotein cholesterol (HDL-C). With increasing quartiles of urine BDCPP levels, the mean TC levels significantly decreased in all participants (p value for trend = 0.028), and quartile increases in the levels of DPhP (p value for trend = 0.01), BDCPP (p value for trend = 0.001), and BCEP (p value for trend<0.001) were negatively corelated with HDL-C, with approximately 5.9, 9.9, and 12.5% differences between the upper and lower quartiles. In conclusion, DPhP, BDCPP, and BCEP were negatively related to HDL-C concentration, whereas DPhP and BCPP levels were negatively associated with TC level. Thus, exposure to OPFRs may interfere with lipid metabolism.

Low serum total cholesterol levels predict inferior prognosis of patients with POEMS syndrome

Low serum cholesterol levels are associated with increased tumor morbidity and mortality. However, the relationship between serum lipid profile and POEMS syndrome (polyneuropathy, organomegaly, endocrinopathy, M-protein, skin changes) is still unclear. The aim of our study was to clarify the importance of the serum lipid profile in predicting the severity and prognosis of patients with POEMS syndrome. Forty-three patients with newly diagnosed POEMS syndrome admitted to the Department of Hematology of Jiangsu Provincial People's Hospital between August 2013 and February 2023 were selected. They had explicit serum lipid profiles. There were 27 males and 16 females with a median age of 54 years (range, 28-77 years). Survival curves were plotted using the Kaplan-Meier method, and comparisons between the two groups were performed using the log-rank test. The Cox proportional-hazards model examined risk factors associated with the prognosis of POEMS syndrome. Receiver-operator characteristic (ROC) curves assessed the predictive accuracy. 23 (53.5%) patients had low total cholesterol (TC) levels. Low levels of TC were concerned with unfavorable progression-free survival (PFS) (p = 0.007) and overall survival (OS) (p = 0.004), and at the same time, the low circulating TC concentration was an independent risk factor for PFS (p = 0.020) and OS (p = 0.011). Low TC values could improve the risk stratification, especially in high-risk patients. In conclusion, low serum TC levels may predict inferior prognosis in patients with POEMS syndrome; in future clinical application, low TC may be a reliable indicator of prognosis.

Association between total cholesterol levels and all-cause mortality among newly diagnosed patients with cancer

We aimed to determine the association between cholesterol values and the risk of all-cause mortality in newly diagnosed patients with cancer in a large-scale longitudinal cohort. Newly diagnosed patients with cancer were reviewed retrospectively. Cox proportional hazards regression models determined the association between baseline levels of total cholesterol (TC), triglycerides, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) cholesterol and the risk of all-cause mortality. A restricted cubic spline curve was used to identify the association between total cholesterol (TC) and low-density lipoprotein (LDL) cholesterol with the risk of death on a continuous scale and to present the lowest values of lipid measurements associated with death. The median follow-up duration of the study was 5.77 years. Of the 59,217 patients with cancer, 12,624 patients were expired. The multivariable adjusted hazard ratio (aHR) for all-cause mortality in patients with cancer with 1st-5th (≤ 97 mg/dL) and 96th-100th (> 233 mg/dL) in TC levels was 1.54 (95% CI 1.43-1.66) and 1.28 (95% CI 1.16-1.41), respectively, compared to 61st-80th (172-196 mg/dL). The TC level associated with the lowest mortality risk in the multivariable model was 181 mg/dL. In comparison with LDL-C levels in the 61st-80th (115-136 mg/dL), the multivariable aHR for all-cause mortality in cancer patients with LDL-C levels in the 1st-5th (≤ 57 mg/dL) and 96th-100th (> 167 mg/dL) was 1.38 (95% CI 1.14-1.68) and 0.94 (95% CI 0.69-1.28), respectively. The 142 mg/dL of LDL cholesterol showed the lowest mortality risk. We demonstrated a U-shaped relationship between TC levels at baseline and risk of mortality in newly diagnosed patients with cancer. Low LDL levels corresponded to an increased risk of all-cause death.

Assessment of causal association between differentiated thyroid cancer and disordered serum lipid profile: a Mendelian randomization study

Background

Research has shown that the disordered serum lipid profile may be associated with the risk of differentiated thyroid cancer (DTC). Whether this association reflect causal effect is still unclear. The aim of this study was to evaluate the causality of circulating lipoprotein lipids on DTC.

Methods

Mendelian randomization (MR) analysis was conducted to evaluate the relationship between the circulating lipoprotein lipids and DTC risk using single-nucleotide polymorphisms (SNPs) from a genome-wide association (GWA) study containing a high-incidence Italian population of 690 cases samples with DTC and 497 controls.

Results

Univariate and multivariate mendelian randomization analysis demonstrated that 'total cholesterol', 'HDL cholesterol', 'apolipoprotein B' and 'ratio of apolipoprotein B to apolipoprotein A1' were correlated with DTC. According to sensitivity analysis, our results were reliable. Furthermore, multivariate analysis revealed that there is no causative association between DTC and any of the many cause factors when they interact with one another, suggesting that there was a deep interaction between the four factors, which could affect each other. Finally, the mechanism of the related effects each other as well as the target genes with significant SNP regulatory effects in DTC was explored by conducting functional enrichment analysis and constructing the regulatory networks.

Conclusions

We obtained four exposure factors (total cholesterol, HDL cholesterol, apolipoprotein B and ratio of apolipoprotein B to apolipoprotein A1) closely related to DTC, which laid a theoretical foundation for the treatment of DTC.

Do metabolic factors increase the risk of thyroid cancer? a Mendelian randomization study

Background

Epidemiological studies emphasize the link between metabolic factors and thyroid cancer. Using Mendelian randomization (MR), we assessed the possible causal impact of metabolic factors on thyroid cancer for the first time.

Methods

Summary statistics for metabolic factors and thyroid cancer were obtained from published Genome-wide association studies. The causal relationships were assessed using the inverse-variance weighted (IVW) method as the primary method through a two-sample Mendelian Randomization (MR) analysis. To account for the potential existence of horizontal pleiotropy, four additional methods were employed, including Mendelian Randomization-Egger (MR-Egger), weighted median method (WM), simple mode, and weighted mode method. Given the presence of interactions between metabolic factors, a multivariable MR analysis was subsequently conducted.

Results

The results showed there was a genetic link between HDL level and protection effect of thyroid cancer using IVW (OR= 0.75, 95% confidence intervals [CIs] 0.60-0.93, p=0.01) and MR-Egger method (OR= 0.70, 95% confidence intervals [CIs] 0.50- 0.97, p=0.03). The results remained robust in multivariable MR analysis for the genetic link between HDL level and protection effect of thyroid cancer (OR= 0.74, 95% confidence intervals [CIs] 0.55-0.99, p=0.04).

Conclusions

This study suggests a protection role for HDL on thyroid cancer. The study findings provide evidence for the public health suggestion for thyroid cancer prevention. HDL's potential as a pharmacological target needs further validation.

Low Serum Cholesterol Level Is a Significant Prognostic Factor That Improves CLL-IPI in Chronic Lymphocytic Leukaemia

Hypocholesterolaemia is associated with elevated cancer risk and mortality, yet the relation between chronic lymphocytic leukaemia (CLL) and serum lipid profile remains unclear. Our study aims to evaluate the prognostic value of cholesterol levels in CLL and develop a prognostic nomogram that incorporates lipid metabolism. We enrolled 761 newly diagnosed CLL patients and separated them into either derivation (n = 507) or validation (n = 254) cohorts. The prognostic nomogram was constructed through multivariate Cox regression analyses, with performance evaluated using C-index, the area under the curve, calibration, and decision curve analyses. Decreased total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) at diagnosis were significantly associated with worse time to first treatment (TTFT) and cancer-specific survival (CSS), and simultaneously, low HDL-C with low LDL-C was identified as an independent prognostic indicator for both TTFT and CSS. CLL patients achieving complete or partial remission post-chemotherapy had significantly increased TC, HDL-C, and LDL-C levels compared with the baseline, and post-therapeutic HDL-C and LDL-C elevation correlated with favourable survival. The prognostic nomogram augmenting the CLL international prognostic index with low cholesterol levels yielded higher predictive accuracy and discrimination capacity for both 3-year and 5-year CSS. In conclusion, cholesterol profiles can be used as a cheap and readily accessible tool for predicting prognosis in CLL practice.

High-density lipoprotein cholesterol and carcinogenesis

High-density lipoprotein cholesterol (HDLC) has been recognized to be associated with atherosclerosis. In the past few years many studies have found that HDLC is also related to tumor development and progression. Despite some opposing views, a large number of studies support a negative association between HDLC and tumor incidence. Measuring serum HDLC concentrations may facilitate assessment of the prognosis of cancer patients and provide a biomarker for tumors. However, there is a lack of molecular mechanism studies on the link between HDLC and tumors. In this review we discuss the impact of HDLC on the incidence and prognosis of cancer in different systems, as well as prospects for the prediction and treatment of cancer in the future.

Big Data Research in the Field of Endocrine Diseases Using the Korean National Health Information Database

The Korean National Health Information Database (NHID) contains big data combining information obtained from the National Health Insurance Service and health examinations. Data are provided in the form of a cohort, and the NHID can be used to conduct longitudinal studies and research on rare diseases. Moreover, data on the cause and date of death are provided by Statistics Korea. Research and publications based on the NHID have increased explosively in the field of endocrine disorders. However, because the data were not collected for research purposes, studies using the NHID have limitations, particularly the need for the operational definition of diseases. In this review, we describe the characteristics of the Korean NHID, operational definitions of endocrine diseases used for research, and an overview of recent studies in endocrinology using the Korean NHID.

Altered serum lipid levels are associated with prognosis of diffuse large B cell lymphoma and influenced by utility of rituximab

Diffuse large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, and the prognosis of the disease varied. This research aims to investigate the impact of serum lipid level on the outcome of DLBCL patients and their interaction with rituximab (RTX). Data of newly diagnosed DLBCL in the third affiliated hospital of Soochow University were retrospectively collected. Baseline serum lipid levels, clinical data, and survival information were simultaneously recorded. Data of healthy controls were collected with age matching. Serum lipid levels significantly differed for the patients. All were transformed into categorical variables for the analysis of survival. During a median follow-up of 58 months, 32.8% patients died. Univariate analysis revealed all serum lipid indicators were associated with overall survival (OS); all except for total cholesterol (TC) and apolipoprotein B (apoB) showed significant impact on progression-free survival (PFS). Multivariable analysis confirmed the adverse effect of triglyceride (TG) on PFS (P = 0.013) and favorable impact of high-density lipoprotein (HDL) on OS (P = 0.003). For cases treated without RTX, apolipoprotein A (apoA) had independent favorable effect on both PFS (P = 0.004) and OS (P = 0.001). Comparably, for patients who received RTX, HDL showed remarkably predictive value of PFS (P = 0.011) and OS (P = 0.019). In conclusion, the abnormal serum lipids occurred throughout the course of DLBCL, and the associations of serum lipids and the prognosis of the disease were interfered by RTX. Trial registration: 2022()CL033; June 26, 2022, retrospectively registered.

Carbohydrate, Lipid, and Apolipoprotein Biomarkers in Blood and Risk of Thyroid Cancer: Findings from the AMORIS Cohort

Background: Previous studies have examined the link between blood metabolic biomarkers and risk of thyroid cancer, with inconclusive results. We performed a cohort study based on the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) Cohort, including 561,388 individuals undergoing health examinations during 1985−1996 with a follow-up of >30 years. Methods: Newly diagnosed cases of thyroid cancer were identified from the Swedish Cancer Register. We assessed the associations of nine blood biomarkers of carbohydrate, lipid, and apolipoprotein metabolism measured at the time of health examinations with the subsequent risk of thyroid cancer and demonstrated the temporal trend of these biomarkers during the 30 years before diagnosis of thyroid cancer. Results: After multivariable adjustment, there was a lower risk of thyroid cancer, per standard deviation increase in total cholesterol (TC; HR 0.91; 95%CI 0.82−0.99) and HDL-C (HR 0.86; 95%CI 0.75−0.99). During the 20 to 30 years before diagnosis, patients with thyroid cancer, as a group, demonstrated constantly lower levels of TC and HDL-C, compared to controls. Further, patients with thyroid cancer demonstrated declining levels of these biomarkers during the ten years before diagnosis, whereas controls demonstrated stable or increasing levels. Conclusions: Taken together, we found blood levels of TC and HDL-C to be associated with the risk of thyroid cancer and that there was a declining level of metabolic biomarkers during the 10 years before diagnosis of thyroid cancer.

Risk factors and diagnostic prediction models for papillary thyroid carcinoma

Thyroid nodules (TNs) represent a common scenario. More accurate pre-operative diagnosis of malignancy has become an overriding concern. This study incorporated demographic, serological, ultrasound, and biopsy data and aimed to compare a new diagnostic prediction model based on Back Propagation Neural Network (BPNN) with multivariate logistic regression model, to guide the decision of surgery. Records of 2,090 patients with TNs who underwent thyroid surgery were retrospectively reviewed. Multivariate logistic regression analysis indicated that Bethesda category (OR=1.90, P<0.001), TIRADS (OR=2.55, P<0.001), age (OR=0.97, P=0.002), nodule size (OR=0.53, P<0.001), and serum levels of Tg (OR=0.994, P=0.004) and HDL-C (OR=0.23, P=0.001) were statistically significant independent differentiators for patients with PTC and benign nodules. Both BPNN and regression models showed good accuracy in differentiating PTC from benign nodules (area under the curve [AUC], 0.948 and 0.924, respectively). Notably, the BPNN model showed a higher specificity (88.3% vs. 73.9%) and negative predictive value (83.7% vs. 45.8%) than the regression model, while the sensitivity (93.1% vs. 93.9%) was similar between two models. Stratified analysis based on Bethesda indeterminate cytology categories showed similar findings. Therefore, BPNN and regression models based on a combination of demographic, serological, ultrasound, and biopsy data, all of which were readily available in routine clinical practice, might help guide the decision of surgery for TNs.