Background Previous studies have shown that the gut microbiome is associated with thyroid diseases, including Graves’ disease, Hashimoto's disease, thyroid nodules, and thyroid cancer. However, the association between intestinal flora and primary hypothyroidism remains elusive. We aimed to characterize gut microbiome in primary hypothyroidism patients. Methods Fifty-two primary hypothyroidism patients and 40 healthy controls were recruited. The differences in gut microbiota between the two groups were analyzed by 16S rRNA sequencing technology. Fecal microbiota transplantation (FMT) was performed in mice using flora from both groups; changes in thyroid function were then assessed in the mice. Results There were significant differences in α and β diversities of gut microbiota between primary hypothyroidism patients and healthy individuals. The random forest analysis indicated that four intestinal bacteria (Veillonella, Paraprevotella, Neisseria, and Rheinheimera) could distinguish untreated primary hypothyroidism patients from healthy individuals with the highest accuracy; this was confirmed by receiver operator characteristic curve analysis. The short chain fatty acid producing ability of the primary hypothyroidism patients’ gut was significantly decreased, which resulted in the increased serum lipopolysaccharide (LPS) levels. The FMT showed that mice receiving the transplant from primary hypothyroidism patients displayed decreased total thyroxine levels. Conclusions Our study suggests that primary hypothyroidism causes changes in gut microbiome. In turn, an altered flora can affect thyroid function in mice. These findings could help understand the development of primary hypothyroidism and might be further used to develop potential probiotics to facilitate the adjuvant treatment of this disease.

Background: Increasing evidence has linked the thyroid dysfunction to the pathogenesis of dementia. Evidence from clinical studies has demonstrated that hypothyroidism is related to an increased risk of dementia. But the association of hyperthyroidism with dementia is largely unknown. Methods: We used the adenovirus containing thyrotropin receptor (TSHR) amino acid residues 1-289 (Ad-TSHR289)-induced Graves’ disease (GD) phenotype in Alzheimer’s disease (AD) model mice (APP/PS1 mice) to evaluate the effect of hyperthyroidism on the cognitive function and β-amyloid (Aβ) accumulation. Results: GD mice exhibited a stable long-term hyperthyroidism and cognitive deficits. Single Cell RNA-sequencing analysis indicated that microglia function played a critical role in the pathophysiological processes in GD mice. Neuroinflammation and polarization of microglia (M1/M2 phenotype) and activated receptor-interacting serine/threonine protein kinase 3 (RIPK3)/mixed lineage kinase domain–like pseudo-kinase (MLKL)-mediated necroptosis contributed to the pathological process, including Aβ deposition and neuronal loss. RIPK3 inhibitor could inhibit GD-mediated Aβ accumulation and neuronal loss. Conclusions: Our findings reveal that GD hyperthyroidism aggravates cognitive deficits in AD mice and induces Aβ deposition and neuronal loss by inducing neuroinflammation and RIPK3/MLKL-mediated necroptosis.

SREBP-2, a new target of metformin? Fengxia Zhang,1,* Wenxiu Sun,2,* Jianbo Chen,3 Lusheng Jiang,3 Ping Yang,3 Yufang Huang,3 Aihua Gong,3 Shudong Liu,3 Shizhan Ma4 1Department of Neurology, Affiliated Hospital of Shandong Traditional Chinese Medicine University, Jinan 250011, China; 2Department of Pharmacy, Taishan Vocational College of Nursing, Taian 271000, China; 3Department of Endocrinology, Shandong Rongjun General Hospital, Jinan 250013, China; 4Department of Endocrinology and Metabolism, Shandong Provincial Hospital Affiliated to Shandong University, Jinan 250021, China *These authors contributed equally to this work Background: Metformin, as the first-line treatment anti-diabetic drug, represents increasing evidence of a potential efficacy in improving dyslipidemia. However, the exact molecular mechanism(s) by which metformin influences lipid metabolism remains incompletely understood. Methods: The HepG2 cells were treated with metformin and the AMP-activated protein kinase (AMPK) inhibitor compound C or a dominant-negative form of AMPK plasmid. ELISA assay was employed to measure AMPK activity, and cellular cholesterol content was determined by enzymatic colorimetric method. RT-PCR and western blotting were used to detect SREBP-2 mRNA levels and its target protein levels. Results: We found that metformin significantly stimulated AMPK activity and decreased intracellular total cholesterol contents in HepG2 cells. Metformin reduced the sterol regulatory element-binding protein-2 (SREBP-2) and its downstream target proteins and increased low-density lipoprotein receptor (LDLR) levels. Conclusion: Our preliminary results demonstrate that metformin as a first-line and initial medication suppresses the synthesis of SREBP-2 and upregulates LDLR, and consequently decreases cholesterol production via activation of AMPK, at least partly. These findings suggest a therapeutic target and potential beneficial effects of metformin on the prevention of dyslipidemia or related diseases. Keywords: type 2 diabetes mellitus, cholesterol, metformin, AMP-activated protein kinase, sterol regulatory element-binding protein-2

Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the interrelated pathophysiology of obesity, insulin resistance, type 2 diabetes, chronic kidney disease, and cardiovascular disease. Conventional CKM staging often detects risk only after substantial organ dysfunction and may overlook early metabolic heterogeneity. This study aimed to employ plasma metabolomics to identify metabolic subtypes linked to CKM severity and explore early biomarkers for high-risk individuals. A cross-sectional study was conducted involving 163 adults, which included 86 individuals clinically staged as CKM 0–3 according to the criteria proposed by the American Heart Association (AHA). Plasma samples underwent untargeted metabolomic and lipidomic profiling using liquid chromatography–mass spectrometry (LC–MS). Unsupervised clustering identified metabolic subtypes, with validation via random forest analysis. Group differences were assessed using orthogonal partial least squares–discriminant analysis (OPLS-DA) and logistic regression classifiers. A total of 390 metabolites, categorized into 9 superclasses and 30 subclasses, were identified. Three distinct metabolic clusters emerged: Cluster 1 (glycerophospholipid-enriched), Cluster 2 (fatty acyl–dominant), and Cluster 3 (glycolipid-enriched). At the individual differential metabolite level, Cluster 1 exhibited a generally low metabolic status, Cluster 2 demonstrated an intermediate metabolic profile, and Cluster 3 showed a high metabolic status. High-risk CKM individuals were predominantly assigned to Cluster 3 (p < 0.001). Within each cluster, OPLS-DA effectively differentiated high- and low-risk individuals based on lipid profiles, highlighting triglycerides, fatty acids, phosphatidylcholines, sphingolipids, and acylcarnitines as key discriminators. Secondary clustering among stage 3 of CKM patients revealed substantial metabolic heterogeneity. A panel of 20 metabolites achieved high diagnostic performance for stage 3 of CKM individual (AUC = 0.875). Untargeted plasma metabolomic profiling reveals distinct metabolic subtypes corresponding to CKM severity and uncovers marked heterogeneity within the high-risk group. Key metabolite signatures may enhance early risk stratification and support more personalized management strategies beyond conventional CKM staging. Overview of study design, metabolicsubtypes, CKM stratification, and key findings.

Many studies indicate the gut microbiome is associated with diseases caused by administering high-dose glucocorticoids (GCs), such as hypertension, hyperglycemia, and osteoporosis. However, the association between intestinal flora and the use of high-dose GCs remains elusive. We aimed to characterize gut microbiome in Graves’ ophthalmopathy (GO) patients after administering high-dose GCs. In this study, 20 primary GO patients were recruited. The differences in gut microbiota of GO patients before and after administering high-dose GCs were analyzed by 16S rDNA sequencing technology. Untargeted metabolomic analysis was used to examine the differences in gut metabolites between two groups. There were significant differences in α and β diversities of gut microbiota in GO patients before and after administering high-dose GCs. The random forest analysis indicated that three intestinal bacteria ( Faecalibacterium, Streptococcus, and Prevotella ) could distinguish the two groups with the highest accuracy, which was proven by receiver operator characteristic curve and linear discriminant analysis effect size analysis. The short-chain fatty acid-producing ability in GO patients’ gut after high-dose GC administration was significantly decreased. The 5-hydroxytryptamine levels significantly increased in the gut of GO patients after administering high-dose GCs. Our study suggests that high-dose GC administration causes the changes in gut microbiome and metabolites. Moreover, the altered flora and metabolites are related to hypertension, hyperglycemia, and osteoporosis. These findings can help understand the development of side effects caused by high-dose GCs and can be further used to develop potential probiotics to facilitate the prevention for those side effects. IMPORTANCE: For the first time, we revealed that gut microbiome and metabolome in Graves’ ophthalmopathy patients after high-dose glucocorticoid (GC) administration significantly changed, and the altered flora and metabolites are related to hypertension, hyperglycemia, and osteoporosis. These findings can help understand the development of side effects caused by high-dose GCs and can be further used to develop potential probiotics to facilitate the prevention for those side effects.