Personalized medicine最新文献

Precision medicine promises improved health outcomes by tailoring treatments to individual genetic and environmental factors. However, achieving this potential is hindered by persistent health disparities and the underrepresentation of racially and ethnically diverse populations in clinical trials. Limited diversity in research exacerbates health inequities, reducing the generalizability of findings and widening gaps in access to effective treatments. This review outlines a multi-faceted strategy to bridge diversity gaps in clinical trials, focusing on community engagement, clinical pharmacology, and regulatory science. Key approaches include decentralized trials, targeted recruitment, advanced data modeling, and comprehensive integration of genetic and social determinants of health data. Regulatory frameworks, such as diversity action plans, play a crucial role in ensuring equitable access to precision health innovations. Increasing representation in research enhances the reliability of clinical data and fosters health equity by addressing differences in disease prevalence, treatment responses, and healthcare access. By leveraging technological advancements and inclusive research methodologies, this framework aims to transform clinical trials into a roadmap for equitable healthcare. Ensuring diverse participation in research is essential for the successful implementation of precision medicine and realizing the full potential of precision health, ultimately reducing health disparities and promoting fair access to medical advancements across all populations.

Aim: In this study, we aimed to reveal the sequence analysis of 69 pharmacogenes in 635 patients and the clinical explanation of variants.

Materials and methods: Genomic DNA was isolated from peripheral blood of patients. Next-Generation Sequence analysis and bioinformatic analysis were performed to identify 69 pharmacogene variants. Variants with clinical annotation were identified.

Results: Analysis of 69 pharmacogenes in a total of 635 patients identified 9485 variants. The number of distinct variants identified in each gene was 1409. Of these 1409 variants, the number of variants registered in PharmGKB was 126. Among the 126 variants registered in PharmGKB, 26 variants were identified that had a direct association with clinical annotation and drug efficacy or toxicity. The most common variant genes were DPYD, CYP2C19, VKORC1,UGT1A1, RYR1 and MTHFR. These 26 variants with clinical annotation were identified in 327 (51%) different individuals.

Conclusions: Such a high frequency of critical variants (51%) points to the need for pharmacogenetic studies. The results are extremely important in terms of determining the drug dose according to the genomic status of individuals receiving drug therapy and preventing unnecessary health expenditures.

Background: -Omics technologies - including genomics, transcriptomics, proteomics, and metabolomics - are increasingly used in acute care settings. However, the current extent of this research has not been systematically assessed.

Objectives: To characterize how -omics analyses are applied to acute medical conditions and identify trends, gaps, and implementation barriers.

Methods: Eligible studies included human subjects with acute conditions and used -omics biosample analyses for diagnostic, prognostic, or predictive purposes. Feedback from the SAEM Precision Emergency Medicine Consensus Conference informed the search and inclusion criteria. Studies of infectious diseases were excluded for separate analysis.

Results: Of 7,531 screened articles, 421 met inclusion criteria. Most were observational cohort studies, with single nucleotide polymorphism analysis being most common. Cardiovascular and trauma-related conditions were frequently studied. Only 12.4% of studies included children, and just 7 focused exclusively on older adults. One-third were conducted outside of emergency departments. Many studies addressed diverse, uncategorized acute conditions.

Conclusions: While -omics research in acute care is growing, it remains predominantly observational with limited clinical implementation. Barriers include delayed turnaround times, insufficient EHR integration, and underrepresentation of vulnerable populations. Advancing this field requires cross-disciplinary collaboration, focused research priorities, and investment in implementation studies.

Innovations, such as genomics, are expected to transform the practice of the healthcare workforce. Workplace learning is an established and fundamental component of healthcare workforce training. We propose that it can be leveraged to facilitate workforce preparedness to adopt innovations relevant to practice. To explore this, this study aimed to develop a workplace learning framework premised on primary literature. Four databases were systematically searched to identify and synthesize contemporary research articles investigating doctors' workplace learning, with an additional focus on genetics/genomics. From the articles included, factors influencing workplace learning were extracted. Informed by structuration and workplace learning theories, thematic analysis was conducted on these factors to generate the framework. Despite the lack of articles on doctors' genetics/genomics workplace learning, 50 articles on doctors' workplace learning were included. Extracted influencing factors were synthesized into five major domains, across three social system levels and the agentic learner, to generate the Workplace Learning Social System framework. Innovations in healthcare require its workforce to change work practices. The Workplace Learning Social System framework holistically conceptualizes workplace learning based on contemporary literature. It provides pragmatic insights to inform workforce development when implementing innovations as part of system-wide change.

Objectives: The genetic variant rs13137 of miR-21 is associated with susceptibility in many diseases. However, the association with cognitive dysfunction (CD) in Chinese patients with systemic lupus erythematosus (SLE) remains unclear.

Materials and methods: Two hundred and thirty SLE patients (Non-CD) and 230 SLE-related CD patients (CD) were recruited. MiR-21 level was calculated by qRT-PCR. The ROC curve was established to evaluate the diagnosibility. The independent risk factors were identified by multivariate logistic regression analysis.

Results: The miR-21 in CD group was obviously increased. Compared to AA carriers, the miR-21 level in carriers of rs13137 AT/TT in CD group were significantly lower than those in Non-CD group. The AUC was 0.9023 with sensitivity of 78.70% and specificity of 90.87%. Comparison of genotype and allele frequencies indicated that SLE patients carrying rs13137 AT/TT genotype had low risk of CD. Multivariate logistic regression analysis showed that the rs13137 polymorphism, education years, and MoCA score were correlated with CD risk.

Conclusion: The miR-21 rs13137 polymorphism was correlated with CD risk in the Chinese population. MiR-21 in rs13137 AT/TT carriers was significantly lower than that of AA genotype and the AT/TT genotype was correlated with low CD risk in SLE patients.

Purpose: To investigate patient reactions to and understanding of secondary genomic findings with limited to no medical actionability (LMA-SFs) from diagnostic genome sequencing.

Methods: We analyzed LMA-SFs returned to 47 adults who elected to receive a broad set of these results from 6 categories. Findings indicated elevated risk (reportable/positive) or not (negative/normal). Most participants (N = 43) also completed surveys to report their distress, decision regret, expected health anxiety, and whether and how they perceived results as reassuring or troubling.

Results: Most participants received some reportable LMA-SFs for common risk, pharmacogenetic, and carrier status variants. Fewer received reportable APOE haplotype or monogenetic condition variants. None received results indicating high risk for severe neurological disease. Overall, participants (76.7% female, 97.7% White) had low distress, decision regret, and expected health anxiety. None described negative/normal findings as troubling. However, their interpretations of reportable/positive results varied. Even within the same result type, some participants found them troubling, while others found them reassuring based on their perception of the results' utility.

Conclusion: Participants' short-term well-being was not reduced by receiving LMA-SFs. Their interpretations suggested varied personal utilities and the need for post-test resources to aid understanding of these types of results and their health significance.

Background: Gastric carcinogenesis is associated with defects in DNA damage repair pathways, in which the XRCC gene family (XRCC1, XRCC5, and XRCC6) play an important role in DNA repair. It is also well known that the CDH1 gene, as a tumor suppressor, influences the development of gastric cancer.

Methods: We recruited 484 gastric cancer patients and 471 controls. DNA genotyping and Helicobacter pylori infection were determined by commercial kits. Association between polymorphisms and gastric cancer risk and survival was evaluated through SPSS 26.0.

Results: Stratified analysis revealed that XRCC1 rs25487 TC/TT was associated with increased gastric cancer risk in the following four subgroups of males (adjusted OR = 1.40, 95% CI: 1.03-1.90, p = 0.031), positive Helicobacter pylori (adjusted OR = 1.58, 95% CI: 1.09-2.28, p = 0.015), tumor stage III-IV (adjusted OR = 1.42, 95% CI: 1.06-1.89, p = 0.017), and non-gastric cardiac adenocarcinoma (adjusted OR = 1.36, 95% CI: 1.02-1.82, p = 0.034). Additionally, survival analysis indicated that XRCC1 rs25487 TC/TT genotype (HR = 1.35, 95% CI: 1.08-1.69, p = 0.010) was associated with unfavorable survival in gastric cancer patients.

Conclusion: XRCC1 rs25487 CC genotype decreased the risk of gastric cancer, and predicted a favorable survival prognosis.

Objective: We aimed to explore the relationship between the MBOAT7 rs641738 gene polymorphism and liver fibrosis and inflammation.

Methods: A total of 214 patients with metabolic dysfunction-associated steatotic liver disease (MASLD) were allocated into the mild-to-moderate and severe liver fibrosis groups based on liver fibrosis degree. The genotypes at the MBOAT7 rs641738 locus were evaluated. Differences in clinical and biochemical indicators, as well as the genotype and allele frequency distributions of the MBOAT7 rs641738 polymorphism, were analyzed across groups with varying degrees of liver fibrosis. Additionally, the clinical and biochemical differences among patients with different genotypes were examined.

Results: Significant differences were observed in the distribution of CC, CT, and TT genotypes, as well as C and T allele frequencies at the MBOAT7 rs641738 locus, between patients with mild-to-moderate and severe fibrosis. Carriers of the CT + TT genotype had a higher risk of developing severe liver fibrosis compared to those with the CC genotype (OR > 1). Furthermore, CT + TT carriers had higher levels of inflammatory cytokines and more severe fibrosis than CC genotype carriers (all p < 0.05).

Conclusion: The MBOAT7 rs641738 gene polymorphism is associated with the severity of liver fibrosis and inflammation.

Background: Metastatic renal cell carcinoma (RCC) is often treated with a combination of immunotherapy and tyrosine kinase inhibitors (TKIs). Patient-derived RCC cells were cultured and inter-individual differences to treatment with a panel of TKIs were evaluated.

Methods: Tumor tissue was collected during nephrectomy. Cells were cultured and treated with a panel of clinically relevant TKIs (sunitinib, cabozantinib, pazopanib, axitinib) at concentrations of 5 µM for 48-72 hours. Cell viability was evaluated using MTT assays. One-sided T-tests were used to evaluate results.

Results: Patient-derived cancer cells were able to be grown beyond 10 passages from 12/38 samples collected (27%). Four patient-derived samples were tested against the TKI panel. No substantial difference between drugs was seen for two samples. In one sample, there was a clear superior response to sunitinib (48% mean viability, vs >75% for the other drugs). For the final sample, sunitinib, cabozantinib, and axitinib demonstrated a superior response compared with pazopanib (71%, 77%, 70%, and 85% mean viability, respectively).

Conclusions: Inter-individual variability in the responses of patient-derived RCC cultures to TKIs was seen, which may have biological and clinical significance. Future directions could build on this work to develop personalized cancer susceptibility profiles, with potential for translation into a clinical trial.

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.