Frontiers in Endocrinology最新文献

Purpose: To evaluate the all-cause mortality rate and renal outcomes in patients with diabetes and chronic kidney disease (CKD) following hospital discharge for COVID-19.

Methods: This single-center prospective observational study included 187 discharged COVID-19 patients with diabetes and CKD, admitted between December 2022 and January 2023 at West China Hospital, Sichuan University. Cox regression analysis was used to assess mortality risk, and logistic regression was applied to identify risk factors for rapid CKD progression after discharge.

Results: During the one-year follow-up, the all-cause mortality rate was 26.7%, with a COVID-19-related acute kidney injury (AKI) incidence of 35.3%, and 35.8% of patients experienced rapid CKD progression after discharge. Cox proportional hazards regression indicated that sepsis and mechanical ventilation were major risk factors for post-discharge all-cause mortality. Logistic regression identified baseline eGFR < 60 mL/min/1.73 m² as an independent risk factor for rapid CKD progression.

Conclusions: During the one-year follow-up period, we observed that patients with diabetes and CKD exhibited higher all-cause mortality and experienced rapid deterioration of kidney function after acute infection with COVID-19. This underscores the importance of ongoing longitudinal follow-up to more accurately track the long-term health effects of COVID-19 on patients with diabetes and CKD.

Introduction: Patients with neurofibromatosis type 1 (NF1) are at risk for developing various neoplasms. Since the early twentieth century, multiple cases of pituitary neuroendocrine tumors (PitNETs) occurring in this context have been published. Yet, the role of NF1 (17q11.2) loss-of-function (LOF) variants in pituitary tumorigenesis remains unclear.

Aim: We report the clinical and molecular characterization of a case of PitNET diagnosed in a patient with NF1. We also review the available data for and against a causal association between NF1 defects and pituitary tumors.

Methods: Our patient was recruited via an ongoing prospective study of individuals with neuroendocrine neoplasms. Genetic testing was carried out by means of targeted next generation sequencing (NGS) and Sanger sequencing in blood and tumor DNA, respectively. NF1 expression was analyzed via quantitative polymerase chain reaction (qPCR) in blood and tumor cDNA. Similar cases were searched in the literature.

Results: A 54-year-old-man was incidentally diagnosed with a clinically non-functioning PitNET via brain imaging. He had a personal and family history of NF1 and carried the germline pathogenic variant NF1 (NM_001042492.3): c.147C>A, p.Y49*. Via transsphenoidal surgery, a 16 mm lesion was resected, showing strong granular cytoplasmic immunoreactivity with patchy distribution for NF1 and preserved heterozygosity for the NF1 defect. Additional NGS ruled out germline defects in PitNET-associated genes. By qPCR, NF1 was significantly overexpressed in the tumor when compared with another NF-PitNET, but not when compared with a corticotropinoma. We reviewed twenty-three case reports of PitNETs occurring in patients with either clinical NF1 without genetic study, individuals with NF1 germline variants with or without clinical NF1 or associated with somatic NF1 defects. Predominance of GH-secreting and large PitNETs, with young-onset in around half of the cases, were noticed. Two individuals developed multiple endocrine neoplasia-like phenotypes but tested negative for other relevant genetic defects.

Conclusions: Although the association of NF1 and PitNETs could be coincidental, the clinical characteristics of the reviewed cases differ from those of typical incidentalomas. NF1 could drive pituitary tumorigenesis via haploinsufficiency, but this hypothesis requires further research. Additional clinical and molecular data from large cohorts of affected individuals should help clarify this question.

Circadian rhythms are critical to coordinating body processes to external environmental cues, such as light and feeding, to ensure efficiency and maintain optimal health. These rhythms are controlled by 'clock' transcription factors, such as Clock, Bmal1, Per1/2, Cry1/2, and Rev-erbs, which are present in almost every tissue. In modern society, disruptions to normal circadian rhythms are increasingly prevalent due to extended lighting, shift work, and long-distance travel. These disruptions misalign external cues to body processes and contribute to diseases such as obesity and non-alcoholic fatty liver disease. They also exacerbate pre-existing health issues, such as depression and inflammatory bowel disease. The normal inflammatory response to acute infection displays remarkable circadian rhythmicity in humans with increased inflammatory activity during the normal night or rest period. Severe bloodborne infections, exemplified in sepsis and the progression to septic shock, can not only disrupt the circadian rhythmicity of inflammatory processes but can be exacerbated by circadian misalignment. Examples of circadian disruptions during sepsis and septic shock include alteration or loss of hormonal rhythms controlling blood pressure and inflammation, white blood cell counts, and cytokine secretions. These changes to circadian rhythms hinder sepsis and septic shock recovery and also increase mortality. Chronotherapy and chronopharmacotherapy are promising approaches to resynchronise circadian rhythms or leverage circadian rhythms to optimise medication efficacy, respectively, and hold much potential in the treatment of sepsis and septic shock. Despite knowledge of how circadian rhythms change in these grave conditions, very little research has been undertaken on the use of these therapies in support of sepsis management. This review details the circadian disruptions associated with sepsis and septic shock, the influence they have on morbidity and mortality, and the potential clinical benefits of circadian-modulating therapies.

Background: Cardiovascular disease (CVD) remains a major contributor to the global disease burden. Previous studies have established a link between the atherogenic index of plasma (AIP) and CVD. However, it remains unclear whether cumulative AIP and AIP control influence the future incidence of CVD in individuals with Cardiovascular-Kidney-Metabolic (CKM) syndrome. This study aims to explore the association between cumulative AIP, AIP control levels, and the risk of CVD in individuals with CKM syndrome from stages 1 to 3.

Methods: Participants with CKM syndrome were drawn from the China Health and Retirement Longitudinal Study (CHARLS). Cumulative AIP was calculated using triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C), while AIP control levels were categorized into four groups via k-means clustering. CVD was defined by self-reported heart disease or stroke. Multivariable logistic regression and restricted cubic spline analysis were employed to examine the association between AIP and incident CVD in individuals with CKM syndrome.

Results: A total of 793 participants (18.84%) developed CVD. After adjusting for confounders, cumulative AIP were associated with the developing CVD (OR=1.139, 95% CI: 1.017-1.275, P=0.0245). Compared to group 1 (best AIP control), the OR (95% CI) for incident CVD were 1.278 (0.959-1.702) for group 2, 1.329 (1.076-1.641) for group 3, and 1.195 (0.974-1.465) for group 4. Restricted cubic spline regression indicated the relationship between cumulative AIP and CVD risk is linear (P for nonlinear = 0.3377).

Conclusions: In middle-aged and elderly individuals with CKM syndrome, higher cumulative AIP and poorer AIP control were associated with an elevated incidence of CVD. These findings suggest that enhanced assessment of the AIP index could inform targeted prevention strategies for CVD in the context of CKM syndrome.

Background: The Atherogenic Index of Plasma (AIP) was originally developed primarily as a marker for assessing atherosclerosis. Consequently, this study investigates the potential association between AIP and type 2 diabetic complications through a cross-sectional design.

Methods: The National Metabolic Management Center(MMC) serves as a comprehensive platform dedicated to the establishment of standardized protocols for the diagnosis, treatment, and long-term follow-up of metabolic diseases. Following the relevant inclusion and exclusion criteria, a total of 3,094 patients were enrolled for subsequent analysis. In this study, logistic regression, restricted cubic splines, and subgroup analyses were employed to evaluate the association between the AIP and four major complications of type 2 diabetes, namely, type 2 diabetes with carotid atherosclerosis (DA), diabetic kidney disease (DKD), diabetic retinopathy (DR), and diabetic peripheral neuropathy (DPN).

Results: The logistic regression results demonstrate that in the fully adjusted model, each SD increase in AIP correlates with an elevated risk of type 2 diabetic kidney disease (DKD), with the risk of kidney damage intensifying alongside higher AIP groupings. The RCS analysis and subgroup analyses similarly revealed a dose-response relationship between AIP levels and the risk of DKD. Furthermore, the AIP was not found to be statistically significantly associated with DA, DR,and DPN.

Conclusions: The AIP may serve as a valuable predictive indicator for evaluating kidney damage in patients with type 2 diabetes, and regular screening of AIP in this population could provide significant benefits in the prevention of DKD.

Objective: Previous studies have found that the relationship between metabolic indicators and Hashimoto's thyroiditis (HT) in non-diabetic adults remains unclear. This study aims to explore the association between metabolic indicators and HT, providing new theoretical insights for the clinical management of HT.

Methods: Clinical data were collected from 2,015 non-diabetic adults at Guangdong Provincial Hospital of Chinese Medicine. The relationship between metabolic indicators and HT was analyzed using SPSS 26.0, R (version 4.2.1), and Zstats.

Results: Among the 2,015 non-diabetic adult participants included in the study, 1,877 were in the non-HT group, while 138 were in the HT group. Significant differences were observed in metabolic indicators, including serum uric acid (SUA), serum creatinine (SCr), albumin (ALB) and high-density lipoprotein cholesterol (HDL-C), between the two groups, with statistical significance. A binary logistic regression model was established, revealing that SCr had a significant impact in both univariate and multivariate analyses. To further investigate the relationship between metabolic indicators and HT, we conducted a restricted cubic spline (RCS) analysis. The results demonstrated a clear non-linear relationship between SUA and HT, both before and after adjustment (All P < 0.01). Therefore, based on the inflection points derived from the RCS analysis, a segmented logistic regression analysis was performed. The findings indicated a significant association between both low and high levels of SUA and HT (Lower OR: 2.043; 95% CI: 1.405-3.019; P < 0.001; Higher OR: 2.369; 95% CI: 0.998-4.999; P = 0.034).

Conclusion: This study is the first to reveal a U-shaped association between SUA levels and the risk of HT, suggesting that maintaining SUA levels within the range of 359.0-540.0 μmol/L may help reduce the risk of HT occurrence. This finding provides a new perspective for early intervention and long-term management of HT, particularly in terms of SUA regulation in HT patients, which holds potential clinical value.