Nan Hu

Dr. Nan Hu

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2020 in Diabetes, Metabolic Syndrome and Obesity
Verified
Journal Article
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QZQi Zhang
Qi Zhang
NHNan Hu
Nan Hu
Metformin is a first-line treatment for type 2 diabetes mellitus (T2DM); however, its underlying mechanism is not fully understood. Gut microbiota affect the development and progression of T2DM. In recent years, an increasing number of studies has focused on the relationship between metformin and gut microbiota, suggesting that metformin might exert part of its hypoglycemic effect through these microbes. However, most of these results were not consistent due to the complex composition of the microbiota, the differences between species, the large variation between individuals, and the differences in experimental design, bringing great obstacle for our better understanding of the effects of metformin on the gut microbiota. Here, we reviewed the published papers concerning about the impacts of metformin on the gut microbiota of mice, rats, and humans with obesity or T2DM, and summarized the changes of gut microbiota composition caused by metformin and the possible underlying hypoglycemic mechanism which is related to gut microbiota. It was found that the proportions of some microbiota, such as phyla Bacteroidetes and Verrucomicrobia and genera Akkermansia, Bacteroides and Escherichia, were significantly affected by metformin in several studies. Metformin may exert part of hypoglycemic effects by altering the gut microbiota in ways that maintain the integrity of the intestinal barrier, promote the production of short-chain fatty acids (SCFAs), regulate bile acid metabolism, and improve glucose homeostasis.

10 June 2020 in Xenobiotica
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Journal Article
Closed access
JLJing Ling
Jing Ling
LDLu-Lu Dong
Lu-Lu Dong
XYXu-Ping Yang
Xu-Ping Yang
QQQing Qian
Qing Qian
YJYan Jiang
Yan Jiang
NHNan Hu
Nan Hu
We aimed to establish a population pharmacokinetic (PK) model of tacrolimus and identify clinical covariates, especially the genetic polymorphisms of CYP3A5, ABCB1 and POR*28 that affected the PK t...

1 December 2021 in Microbial Pathogenesis
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Journal Article
Closed access
MGMin Gu
Min Gu
PWPeipei Wang
Peipei Wang
SXShoukui Xiang
Shoukui Xiang
DXDan Xu
Dan Xu
CJChun Jin
Chun Jin
NHNan Hu
Nan Hu

20 August 2024 in Frontiers in Pharmacology
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Journal Article
Open access
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JLJing Ling
Jing Ling
XYXuping Yang
Xuping Yang
LDLulu Dong
Lulu Dong
YJYan Jiang
Yan Jiang
SZSulan Zou
Sulan Zou
NHNan Hu
Nan Hu
Voriconazole is a broad-spectrum triazole antifungal agent. A number of studies have revealed that the impact of C-reactive protein (CRP) on voriconazole pharmacokinetics was associated with the CYP2C19 phenotype. However, the combined effects of CYP2C19 genetic polymorphisms and inflammation on voriconazole pharmacokinetics have not been considered in previous population pharmacokinetic (PPK) studies, especially in the Chinese population. This study aimed to analyze the impact of inflammation on the pharmacokinetics of voriconazole in patients with different CYP2C19 genotypes and optimize the dosage of administration. Data were obtained retrospectively from adult patients aged ≥16 years who received voriconazole for invasive fungal infections from October 2020 to June 2023. Plasma voriconazole levels were measured via high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). CYP2C19 genotyping was performed using the fluorescence in situ hybridization method. A PPK model was developed using the nonlinear mixed-effect model (NONMEM). The final model was validated using bootstrap, visual predictive check (VPC), and normalized prediction distribution error (NPDE). The Monte Carlo simulation was applied to evaluate and optimize the dosing regimens. A total of 232 voriconazole steady-state trough concentrations from 167 patients were included. A one-compartment model with first order and elimination adequately described the data. The typical clearance (CL) and the volume of distribution (V) of voriconazole were 3.83 L/h and 134 L, respectively. The bioavailability was 96.5%. Covariate analysis indicated that the CL of voriconazole was substantially influenced by age, albumin, gender, CRP, and CYP2C19 genetic variations. The V of voriconazole was significantly associated with body weight. An increase in the CRP concentration significantly decreased voriconazole CL in patients with the CYP2C19 normal metabolizer (NM) and intermediate metabolizer (IM), but it had no significant effect on patients with the CYP2C19 poor metabolizer (PM). The Monte Carlo simulation based on CRP levels indicated that patients with high CRP concentrations required a decreased dose to attain the therapeutic trough concentration and avoid adverse drug reactions in NM and IM patients. These results indicate that CRP affects the pharmacokinetics of voriconazole and is associated with the CYP2C19 phenotype. Clinicians dosing voriconazole should consider the patient’s CRP level, especially in CYP2C19 NMs and IMs.

28 September 2021 in Pharmacogenomics
Verified
Journal Article
Closed access
ZJZhenwei Jiang
Zhenwei Jiang
NHNan Hu
Nan Hu
Mycophenolic acid (MPA) is a common immunosuppressive drug for kidney transplantation patients, and is characterized by a narrow therapeutic index and significant individual variability. UGTs are t...

1 July 2025 in Drug Design, Development and Therapy
Verified
Journal Article
Open access
PDF file
ZHzhou hua
zhou hua
XMXiaodie Mu
Xiaodie Mu
HHHuiyue Hu
Huiyue Hu
SZShuya Zhao
Shuya Zhao
NHNan Hu
Nan Hu
JJJingting Jiang
Jingting Jiang
Purpose: Diabetic kidney disease (DKD) is a major contributor to chronic kidney disease worldwide. Bile acids (BAs) are increasingly recognized as key regulators of glucose metabolism and kidney function. This study aimed to investigate the role of BA metabolism in the progression of DKD. Methods: Plasma BA profiles were measured in healthy controls (HC), patients with type 2 diabetes mellitus (T2DM), and patients with DKD using ultra-high-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). After identifying potential BA biomarkers in the clinical cohort, in vivo validation was conducted using dehydrolithocholic acid (DHLCA) intervention in DKD mouse model. Kidney injury markers, as well as the expression of Takeda G protein-coupled receptor 5 (TGR5) and farnesoid X receptor (FXR), were evaluated. In addition, gut microbiota (GM) composition was analyzed via metagenomic sequencing following DHLCA treatment. Results: The plasma DHLCA levels were significantly lower in DKD with macroalbuminuria group compared to T2DM group and DKD with microalbuminuria group (P < 0.01). Partial Spearman correlation analysis adjusted for age and diabetes duration showed that DHLCA levels were negatively correlated with urine albumin (ρ = – 0.347; 95% CI, – 0.531 to – 0.135; q = 0.008) and urine albumin-to-creatinine ratio (UACR) (ρ = – 0.332; 95% CI, – 0.499 to – 0.155; q = 0.010). In vivo, DHLCA administration significantly reduced UACR and fasting blood glucose (FBG) levels (P < 0.01), and improved liver function (ALT, P < 0.05) in DKD mice. DHLCA treatment attenuated renal tubular injury, restored TGR5 and FXR expression in kidney tissue, and decreased levels of kidney injury molecule-1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL). Metagenomic analysis revealed an enrichment of Lachnospiraceae bacterium following DHLCA treatment. Conclusion: DHLCA may represent a promising therapeutic candidate for DKD by targeting the TGR5/FXR signaling pathway and GM remodeling. Its metabolic and kidney benefits, along with an improved hepatic profile and absence of hepatotoxicity, support further translational investigation.