Personalized medicine最新文献

Aims: Considerable inter-individual variability in the efficacy of valproic acid (VPA) has been reported, with approximately 20-45% of patients failing to achieve satisfactory seizure control after VPA monotherapy. The aim of this study was to investigate the influence of non-genetic and genetic factors on 12-month VPA-response in a cohort of 194 pediatric patients.

Materials & methods: Trough concentrations were determined, and a panel of 48 variants located in pharmacokinetic and pharmacodynamic gene were genotyped.

Results: Aetiology was highlighted as a significant factor for the response to VPA. Specifically, patients with idiopathic epilepsy demonstrated poorer 12-month outcomes (p < 0.001). Trough VPA concentrations did not significantly affect outcomes. Marginal association was found between VPA efficacy and the following genetic variants: GABRA1 rs10068980 (p = 0.02), SLC16A1 rs7169 (p = 0.02), ABCC2 rs1885301 (p = 0.092), ACADM rs1251079 (p = 0.061) and GABRA1 rs6883877 (p = 0.085), as indicated by Fisher's exact test. A significant cumulative effect of two genetic factors (GABRA1 rs10068980 and SLC16A1 rs7169) was observed after a multiple logistic analysis, with ORs of 2.828 (1.213, 6.594) and 4.066 (1.148,14.398), respectively.

Conclusion: Our study indicated that GABRA1 rs10068980 and SLC16A1 rs7169 might serve as potential biomarkers for predicting the 12-month VPA treatment outcomes in pediatric patients with epilepsy.

Personalized treatment optimization considers individual clinical, genetic, and environmental factors influencing drug efficacy and tolerability. As evidence accumulates, these approaches may become increasingly integrated into standard psychiatric care, potentially transforming the treatment landscape for mental health disorders. While personalized treatment optimization shows promise in enhancing therapeutic outcomes and minimizing adverse effects, further research is needed to establish its clinical utility and cost-effectiveness across various psychiatric disorders. This review examines the potential utility of personalized treatment optimization in psychiatry, addressing the challenge of suboptimal effectiveness and variable patient responses to psychiatric medications. It explores how therapeutic drug monitoring, pharmacogenomics, and biomarker testing can be used to individualize and optimize pharmacotherapy for mental disorders such as depression, bipolar disorder, and schizophrenia.

Pharmacogenomics (PGx), an integral part of functional genomics and molecular pharmacology, has evolved significantly over the past decade. Our study reveals that PGx education in China and the United States has made substantial progress, with a particular emphasis on integrating PGx into medical curricula and clinical practice, leading to improved therapeutic strategies and patient outcomes. Consequently, both China and the United States are dedicated to fostering advancements in PGx education. This paper reviews PGx education in these two countries, highlighting its importance and providing an in-depth look at the current status and challenges within universities and clinical settings. Furthermore, it offers recommendations for advancing PGx education and contemplates future trends in both nations.

High altitude pulmonary edema (HAPE) is a life-threatening form of non-cardiogenic pulmonary edema. In recent years, association studies have become the main method for identifying HAPE genetic loci. A genome-wide association study (GWAS) of HAPE risk-associated loci was performed in Chinese male Han individuals (164 HAPE cases and 189 healthy controls) by the Precision Medicine Diversity Array Chip with 2,771,835 loci (Applied Biosystems Axiom™). Eight overlapping candidate loci in CCNG2, RP11-445O3.2, NUPL1 and WWOX were finally selected. In silico functional analyses displayed the PPI network, functional enrichment and signal pathways related to CCNG2, NUPL1, WWOX and NRXN1. This study provides data supplements for HAPE susceptibility gene loci and new insights into HAPE susceptibility.

Background: Statins are commonly used medications. Variants in SLCO1B1, CYP2C9, and ABCG2 are known predictors of muscle effects when taking statins. More exploratory genes include RYR1 and CACNA1S, which can also be associated with disease conditions. Methods: Patients with pathogenic/likely pathogenic variants in RYR1 or CACNA1S were identified through an elective genomic testing program. Through chart review, patients with a history of statin use were assessed for statin-associated muscle symptoms (SAMS) along with collection of demographics and other known risk factors for SAMS. Results: Of the 23 patients who had a pathogenic or likely pathogenic RYR1 or CACNA1S variant found, 12 had previous statin use; of these, SAMS were identified in four patients. Conclusion: These data contribute to previous literature suggesting patients with RYR1 variants may have an increased SAMS risk. Additional research will be helpful in further investigating this relationship and providing recommendations.

Background: Colorectal cancer (CRC) is a prominent form of cancer globally, ranking second in terms of prevalence and serving as a leading cause of cancer-related deaths, but the underlying biological interpretation remains largely unknown. Methods: We used the summary data-based Mendelian randomization method to integrate CRC genome-wide association studies (n_case = 7062; n_control = 195,745) and expression quantitative trait loci summary data in peripheral whole blood (Consortium for Architecture of Gene Expression: n = 2765; Genotype-Tissue Expression [v8]: n = 755) and colon tissue (colon-transverse: n = 406; colon-sigmoid: n = 373) and identified related genes. Results: Genes ABTB1, CYP21A2, NLRP1, PHKG1 and PIP5K1C have emerged as significant prognostic markers for CRC patient survival. Functional analysis revealed their involvement in cancer cell migration and invasion mechanisms, providing valuable insights for the development of future anti-CRC drugs. Conclusion: We successfully identified five CRC risk genes, providing new insights and research directions for the effective mechanisms of CRC.

Multi-cancer early detection tests are emerging as a revolutionary technology for the early detection of dozens of cancers from a single blood sample, including cancers without proven screening methods. However, they also come with challenges, including false-positive and false-negative results. To help patients make informed decisions, patient education materials are crucial. A review of available materials reveals that, while some materials provide understandable and actionable information, most lack a balanced presentation of the current benefits and risks of multi-cancer early detection testing. The dynamic nature of this field necessitates continuous updates to educational materials, incorporating current evidence and uncertainties.