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.

Colorectal cancer is a common and fatal disease that affects many people globally. CRC is classified as the third most prevalent cancer among males and the second most frequent cancer among females worldwide. The purpose of this article is to examine how personalized medicine might be used to treat colorectal cancer. The classification of colorectal cancer based on molecular profiling, including the detection of significant gene mutations, genomic instability, and gene dysregulation, is the main topic of this discussion. Advanced technologies and biomarkers are among the detection methods that are explored, demonstrating their potential for early diagnosis and precise prognosis. In addition, the essay explores the world of treatment possibilities by providing light on FDA-approved personalized medicine solutions that provide individualized and precise interventions based on patient characteristics. This article assesses targeted treatments like cetuximab and nivolumab, looks at the therapeutic usefulness of biomarkers like microsatellite instability (MSI) and circulating tumor DNA (ctDNA), and investigates new approaches to combat resistance. Through this, our review provides a thorough overview of personalized medicine in the context of colorectal cancer, ultimately highlighting its potential to revolutionize the field and improve patient care.

Background: Preeclampsia (PE) is a gestational disease associated with developing hypertension and proteinuria.

Aim: This study investigated the effects of AKT1 polymorphisms, a key enzyme in cellular signal transmission that regulates various cellular processes associated with PE.

Methods: The PCR-RFLP method was employed to genotype AKT1 rs2494732, rs1130233, and rs1130214 polymorphisms. In silico analysis was conducted using SpliceAid2, RNAsnp, and STRING tools.

Results: The AKT1 rs1130233 variant was associated with an increased risk of PE in log-additive and allelic models. A significant relationship was also observed between the rs1130214 variant and PE risk in several genetic models. Results from the SpliceAid2 server indicated that the rs2494732 A to G substitution creates a new binding site for the SRP-40 protein. Several key protein binding sites were lost for rs1130214 (C-to-A) and rs1130233 (C-to-T) mutations. However, RNAsnp analysis did not show significant changes in secondary structure.

Conclusion: In conclusion, the AKT1 rs1130233 and rs1130214 polymorphisms were found to be associated with an increased risk of PE.

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.

Efforts have been made to leverage technology to accurately identify tumor characteristics and predict how each cancer patient may respond to medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, and drug metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation sequencing, fluorescence in situ hybridization, immunohistochemistry staining, patient-derived tumor xenograft models, patient-derived organoid models, and therapeutic drug monitoring. The utilization of diverse detection technologies in clinical practice has made "individualized treatment" possible, but the desired level of accuracy has not been fully attained yet. Here, we briefly summarize the conventional and state-of-the-art technologies contributing to individualized medication in clinical settings, aiming to explore therapy options enhancing clinical outcomes.

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.