Precision medicine has been increasingly incorporated into clinical practice and is enabling a new era for disease prevention and treatment. As an important constituent of precision medicine, precision nutrition has also been drawing more attention during physical examinations. The main aim of precision nutrition is to provide safe and efficient intervention methods for disease treatment and management, through fully considering the genetics, lifestyle (dietary, exercise and lifestyle choices), metabolic status, gut microbiota and physiological status (nutrient level and disease status) of individuals. Three major components should be considered in precision nutrition, including individual criteria for sufficient nutritional status, biomarker monitoring or techniques for nutrient detection and the applicable therapeutic or intervention methods. It was suggested that, in clinical practice, many inherited and chronic metabolic diseases might be prevented or managed through precision nutritional intervention. For generally healthy populations, because lifestyles, dietary factors, genetic factors and environmental exposures vary among individuals, precision nutrition is warranted to improve their physical activity and reduce disease risks. In summary, research and practice is leading toward precision nutrition becoming an integral constituent of clinical nutrition and disease prevention in the era of precision medicine.

Precision medicine has been increasingly incorporated into clinical practice and is enabling a new era for disease prevention and treatment. As an important constituent of precision medicine, precision nutrition has also been drawing more attention during physical examinations. The main aim of precision nutrition is to provide safe and efficient intervention methods for disease treatment and management, through fully considering the genetics, lifestyle (dietary, exercise and lifestyle choices), metabolic status, gut microbiota and physiological status (nutrient level and disease status) of individuals. Three major components should be considered in precision nutrition, including individual criteria for sufficient nutritional status, biomarker monitoring or techniques for nutrient detection and the applicable therapeutic or intervention methods. It was suggested that, in clinical practice, many inherited and chronic metabolic diseases might be prevented or managed through precision nutritional intervention. For generally healthy populations, because lifestyles, dietary factors, genetic factors and environmental exposures vary among individuals, precision nutrition is warranted to improve their physical activity and reduce disease risks. In summary, research and practice is leading toward precision nutrition becoming an integral constituent of clinical nutrition and disease prevention in the era of precision medicine.

Objective:To explore the causal relationship between body mass index (BMI) and hypothyroidism using the two-sample Mendelian randomization model.Methods:A large-scale anthropometric genome-wide association study published in the GIANT database was used to select single nucleotide polymorphisms (SNPs) which were statistically significantly associated with BMI as an instrumental variable ( P<5×10 -8, linkage disequilibrium r 2<0.1). The causal relationship between BMI and hypothyroidism was determined by the inverse variance weighted (IVW), weighted median method and the MR-Egger method, respectively. A heterogeneity test, gene pleiotropy test, and sensitivity analysis were performed to evaluate the stability and reliability of the results. Results:A total of 89 SNPs related to BMI were screened out as instrumental variables. IVW analysis suggested that for every standard deviation increase in BMI, the risk of hypothyroidism increased by 0.9% (odd ratio ( OR)=1.009, 95% confidence interval ( CI): 1.006-1.012, P<0.001). Similar results were obtained with the weighted median method ( OR=1.007, 95% CI: 1.002-1.011, P=0.003) and the MR-Egger method ( OR=1.008, 95% CI: 1.001-1.015, P=0.006). The MR-Egger analysis showed that genetic pleiotropy did not bias the results (intercept=0.000 1, P=0.776), the one-by-one exclusion method did not show that a single instrumental variable SNP had a significant impact on the results, and the difference was not statistically significant ( P>0.05). Conclusion:Mendelian randomized analysis showed a positive causal relationship between BMI and hypothyroidism.

Background::Heterogeneity of tumor cells and the tumor microenvironment (TME) is significantly associated with clinical outcomes and treatment responses in patients with urothelial carcinoma (UC). Comprehensive profiling of the cellular diversity and interactions between malignant cells and TME may clarify the mechanisms underlying UC progression and guide the development of novel therapies. This study aimed to extend our understanding of intra-tumoral heterogeneity and the immunosuppressive TME in UC and provide basic support for the development of novel UC therapies.Methods::Seven patients with UC were included who underwent curative surgery at our hospital between July 2020 and October 2020. We performed single-cell RNA sequencing (scRNA-seq) analysis in seven tumors with six matched adjacent normal tissues and integrated the results with two public scRNA-seq datasets. The functional properties and intercellular interactions between single cells were characterized, and the results were validated using multiplex immunofluorescence staining, flow cytometry, and bulk transcriptomic datasets. All statistical analyses were performed using the R package with two-sided tests. Wilcoxon-rank test, log-rank test, one-way analysis of variance test, and Pearson correlation analysis were used properly.Results::Unsupervised t-distributed stochastic neighbor embedding clustering analysis identified ten main cellular subclusters in urothelial tissues. Of them, seven urothelial subtypes were noted, and malignant urothelial cells were characterized with enhanced cellular proliferation and reduced immunogenicity. CD8 + T cell subclusters exhibited enhanced cellular cytotoxicity activities along with increased exhaustion signature in UC tissues, and the recruitment of CD4 + T regulatory cells was also increased in tumor tissues. Regarding myeloid cells, coordinated reprogramming of infiltrated neutrophils, M2-type polarized macrophages, and LAMP3 + dendritic cells contribute to immunosuppressive TME in UC tissues. Tumor tissues demonstrated enhanced angiogenesis mediated by KDR + endothelial cells and RGS5 +/ACTA2 + pericytes. Through deconvolution analysis, we identified multiple cellular subtypes may influence the programmed death-ligand 1 (PD-L1) immunotherapy response in patients with UC. Conclusion::Our scRNA-seq analysis clarified intra-tumoral heterogeneity and delineated the pro-tumoral and immunosuppressive microenvironment in UC tissues, which may provide novel therapeutic targets.