Eur J Clin Pharmacol. 2024 Dec 20. doi: 10.1007/s00228-024-03786-3. Online ahead of print.

ABSTRACT

BACKGROUND: Women are underrepresented in drug development trials and there is no sex-tailored drug regimen for most medications. It has been repeatedly shown that women have more adverse drug reactions than men for several medications. These differences could be explained by higher dose-adjusted drug concentrations in women. Thus, we aim to identify sex-related differences and to characterize the clinical and genetic predictors of these differences in drug concentrations, dosing, and adherence for 47 commonly used drugs in a large cohort. The objective of this article is to present an overview of the methods and characteristics of the study population.

METHODS: We performed a cross-sectional study that included 10,082 men and women of European ancestry aged ≥ 18 years from the Montreal Heart Institute Hospital Cohort taking at least one of the 47 medications regularly.

RESULTS: Of the 10,082 participants included, 36% were women. Women had lower weight, height, waist girth, and body mass index than men, but they had higher hip girth (all p < 0.001). Men had a higher level of education and annual income and were more likely to be employed full-time compared to women. Furthermore, men had a higher prevalence of hypertension, type 2 diabetes, dyslipidemia, and myocardial infarction (all p < 0.001) and were more likely receiving lipid-lowering agents, beta-blockers, antidiabetic drugs, and angiotensin-converting enzyme inhibitors. Conversely, proton pump inhibitors were more prevalent in women. Interestingly, nearly half of the women had a history of drug allergy or intolerance, compared with less than one-third of the men (p < 0.001).

CONCLUSION: This study has a high potential in understanding eventual sex differences in drug dosing requirements and will most likely provide useful information to personalize drug regimens in women.

PMID:39704823 | DOI:10.1007/s00228-024-03786-3

Microbiol Spectr. 2024 Dec 20:e0087224. doi: 10.1128/spectrum.00872-24. Online ahead of print.

ABSTRACT

Genetic characterization of multidrug-resistant (MDR) Acinetobacter baumannii remains scarce in Malaysia. This study aimed to characterize antibiotic resistance, genomic location, and genetic relatedness among the A. baumannii isolates obtained from a tertiary hospital in Malaysia. A total of 128 MDR A. baumannii isolates were collected from patients admitted to various wards (intensive care unit [ICU], neonatal intensive care unit, coronary care unit, high dependency ward [HDW], and general wards). The isolates were identified by Vitek 2 and PCR amplification of the 16S rRNA gene followed by sequencing. The isolates were tested against imipenem, ceftazidime, amikacin, gentamicin, ampicillin, and ciprofloxacin using disk diffusion, Epsilometer test, and broth microdilution. The antibiotic resistance genes, blaOXA-23, blaOXA-24, blaADC, blaVIM, and blaIMP, were detected in chromosomal and plasmid DNA using PCR. Insertion sequence ISAba1/blaOXA-23 gene was detected on chromosomal DNA only. Isolates with different antibiotic susceptibility patterns and PCR profiles were subjected to multi-locus sequence typing. MDR A. baumannii was predominantly found in HDW (39.84%), general wards (29.69%), and ICU (28.13%). All isolates conferred resistance to carbapenem and more than 90% resistance to the remaining antibiotics. The antibiotic resistance genes blaOXA-23, blaVIM, and blaADC were detected in both chromosomal and plasmid DNA. The ISAba1/blaOXA-23 gene was detected in 99.22% of the isolates. Four sequence types (STs) were distinguished: ST2 (76.67%), ST164 (10%), ST642 (10%), and ST643 (3.33%). ST164 and ST642 were unique and represent a significant finding in Malaysia's surveillance data. These STs are associated with acquired blaOXA-23, indicating an evolutionary adaptation of A. baumannii within the hospital setting.IMPORTANCEAcinetobacter baumannii is a ubiquitous Gram-negative coccobacillus bacterium that is primarily associated with nosocomial infections that can colonize biotic and abiotic surfaces to enhance cell-to-cell adhesion, ensuring the establishment of infections. To date, the spread of multidrug-resistant A. baumannii (MDRAB) has become rampant and a great concern in the hospital setting, as the available antibiotics are insufficient to treat infections. The antibiotic resistance island resides in a mobile element and rapidly evolved. The antibiotic susceptibility data with its resistance mechanisms would contribute to and facilitate the management and infection control caused by MDRAB.

PMID:39704504 | DOI:10.1128/spectrum.00872-24

Dent Med Probl. 2024 Nov-Dec;61(6):885-892. doi: 10.17219/dmp/183776.

ABSTRACT

BACKGROUND: Multiple myeloma (MM) is a hematological malignancy characterized by the presence of abnormal plasma cells. It is associated with anemia, bone lesions and renal dysfunction. Immunomodulatory drugs (IMiDs) are commonly used in MM treatment. Recent studies indicate that their therapeutic effect is caused by binding to cereblon (CRBN), which in turn causes the degradation of 2 important immune cell regulatory factors, IKZF1 and IKZF3. These are necessary for the anti-myeloma effect of IMiDs. Their expression level has been shown to affect MM survival and response to treatment. Potentially important single-nucleotide polymorphisms (SNPs) in the genes coding for IKZF1 and IKZF3 have been identified, but they have not been analyzed in MM patients before.

OBJECTIVES: The study was designed to establish the relationship between 4 SNPs in the genes coding for IKZF1 (rs61731359, rs4132601 and rs10272724) and IKZF3 (rs907091), and MM survival, response to treatment and other parameters.

MATERIAL AND METHODS: The study involved 222 MM patients, as well as 100 control individuals. The IKZF1 and IKZF3 genotypes were determined by the LightSNiP assay. Genotyping was performed in the real-time polymerase chain reaction (PCR) LightCycler 480 device.

RESULTS: No difference was observed between the patients and the controls for any of the SNPs, but the IKZF1 and IKZF3 variants were associated with various clinical parameters. Allele IKZF1 rs4132601 G was more common in the patients with worse response to first-line therapy (p = 0.040), particularly in the patients treated with thalidomide (p = 0.017). The patients tended to have worse overall survival. IKZF3 rs907091 CC was detected more commonly in the patients in stage I than in those in stages II and III, according to the International Staging System (ISS) criteria (p = 0.015). This genotype was also associated with a higher albumin level (p = 0.033), and was less common in the patients with the albumin level below 3.5 g/dL (p = 0.030).

CONCLUSIONS: Our results suggest that IKZF1 rs4132601 and IKZF3 rs907091 may affect response to treatment and progression in patients with MM.

PMID:39704419 | DOI:10.17219/dmp/183776

Amyloid. 2024 Dec 19:1-3. doi: 10.1080/13506129.2024.2441784. Online ahead of print.

NO ABSTRACT

PMID:39699273 | DOI:10.1080/13506129.2024.2441784

Health Sci Rep. 2024 Dec 17;7(12):e70262. doi: 10.1002/hsr2.70262. eCollection 2024 Dec.

ABSTRACT

BACKGROUND AND AIMS: Schizophrenia (SCZ) is among the most persistent and devastating psychological problems. Different genetic polymorphisms are responsible for the predisposition of SCZ, and we screened NOTCH4 (rs2071287, rs204993) and CYP2E1 (rs2070673) polymorphisms in this study to find the connection with SCZ development.

METHODS: We investigated a total of 420 samples (210 patients and 210 controls) and used the PCR-RFLP technique to genotype all SNPs. For statistical analyses, SPSS (version 25.0) was applied.

RESULTS: In the case of NOTCH4 rs2071287, no evidence of a link was found in any genetic models, whereas NOTCH4 rs204993 and CYP2E1 rs2070673 showed a significant linkage in four genetic models with SCZ risk (for NOTCH4 rs204993, additive model 2: OR = 3.39, CI = 1.84-6.23, p = 0.0001; dominant: OR = 1.84, CI = 1.22-2.76, p = 0.0032; recessive: OR = 2.67, CI = 1.53-4.64, p = 0.0005; allelic: OR = 1.75, CI = 1.32-2.30, p = 0.0001 and for CYP2E1 rs2070673, additive model 2: OR = 0.39, CI = 0.22-0.69, p = 0.0013; recessive: OR = 0.45, CI = 0.29-0.68, p = 0.0002; overdominant: OR = 1.49, CI = 1.02-2.19, p = 0.0408; allelic: OR = 0.61, CI = 0.46-0.80, p = 0.0004).

CONCLUSIONS: The findings of our study suggest that the polymorphisms NOTCH4 rs204993 and CYP2E1 rs2070673 in the Bangladeshi ethnicity are connected to the risk of SCZ.

PMID:39698532 | PMC:PMC11652386 | DOI:10.1002/hsr2.70262

Pharmacogenomics. 2024 Dec 19:1-13. doi: 10.1080/14622416.2024.2441104. Online ahead of print.

ABSTRACT

BACKGROUND: Dolutegravir (DTG) is an antiviral agent used for the treatment of HIV, however, there is uncertainty over the influence of genetic variation on DTG exposure, and whether it has clinical implications for the efficacy or toxicity in different populations. This systematic review aims to create an overview of the impact of pharmacogenomics (PGx) on DTG exposure, efficacy, and toxicity.

METHODS: Publications up to 14 November 2023 were searched and articles were selected on the following criteria: original research articles providing data on people with HIV, data on PGx and either PK or PD or both PD and PGx.

RESULTS: 711 records were identified, and after screening 10 articles were included. Commonly analyzed genes across the articles were UGT1A1, ABCB1, ABCG2, and NR1I2. The most reported variant associated with PD variability was in SLC22A2, with carriers at higher risk of neuropsychiatric adverse events.

CONCLUSIONS: This review concludes that while PGx testing may help explain some variability in DTG pharmacokinetics when combined with therapeutic drug monitoring (TDM), current evidence is insufficient to support its routine clinical use. The role of PGx research for DTG remains relevant, especially in specific patient populations where interindividual PK variations are still unexplained.

PMID:39697075 | DOI:10.1080/14622416.2024.2441104

BMC Med Genomics. 2024 Dec 18;17(1):286. doi: 10.1186/s12920-024-02064-6.

ABSTRACT

BACKGROUND: Postoperative pain is a common complication following surgery, with severity and duration varying between patients. Chronic postoperative pain after inguinal hernia surgery has an incidence rate of approximately 10%. Risk factors for acute and chronic pain following hernia surgery include age, sex, psychosocial factors, and demographic background. Additionally, genetic polymorphisms in enzymes involved in pain mechanisms, as well as the metabolism of analgesics might influence pain perception, pain development, and response to pain medications. Key enzymes include the catechol-o-methyltransferase (COMT), the µ-opioid receptor 1 (OPRM1), and the cytochrome P450 2D6 (CYP2D6). CYP2D6 plays a crucial role in metabolizing analgesics such as tramadol, codeine, and oxycodone. It is also suspected to be involved in the synthesis of catecholamines and endogenous morphines suggesting a potential role in pathophysiology of pain. We hypothesize that the CYP2D6 activity influences the development of postoperative pain after hernia surgery.

METHODS: This study is a prospective, observational, multicenter association study investigating adult patients scheduled for inguinal hernia surgery using a robotic-assisted (rTAPP) approach. Patients are enrolled during the preoperative surgical consultation. A buccal swab is collected for genetic testing at this time. Pain at the site of the hernia is assessed using the validated EuraHSQoL score preoperatively and at 2, 4, and 6 weeks postoperatively. Additionally, information on co-medication and details of the surgery will be collected. The planned number of participants is 350 patients. The primary objective is to analyze the association between different genotype-predicted CYP2D6 phenotypes and patient-reported pain intensity 6 weeks after surgery. Secondary objectives include the association between further genetic variants, such as the COMT rs4680 and OPRM1 rs1799971 genotype, and pain severity. Additionally, the potential of pharmacogenetic panel testing to optimize analgesic therapy in hernia surgery patients will be explored.

DISCUSSION: The findings of this study are expected to provide valuable insights into identifying patients at higher risk for postoperative pain before surgery. This knowledge could pave the way for tailored interventions during and after surgery for these specific patients.

TRIAL REGISTRATION: Deutsches Register Klinischer Studien https://www.drks.de/DRKS00034796 Registered on August 07, 2024.

PMID:39696400 | DOI:10.1186/s12920-024-02064-6

BMC Nephrol. 2024 Dec 18;25(1):458. doi: 10.1186/s12882-024-03871-w.

ABSTRACT

BACKGROUND: This study aimed to develop a nomogram for predicting persistent renal dysfunction in acute kidney injury (AKI) following lung transplantation (LTx).

METHOD: A total of 229 LTx patients were enrolled, and genotyping for 153 single nucleotide polymorphisms (SNPs) was performed. The cohort was randomly divided into training (n = 183) and validation (n = 46) sets in an 8:2 ratio. Statistically significant SNPs identified through pharmacogenomic analysis were combined with clinical factors to construct a comprehensive prediction model for persistent AKI using multivariate logistic regression analysis. Discrimination and calibration analyses were conducted to evaluate the performance of the model. Decision curve analysis was used to assess its clinical utility. Due to the small sample size, bootstrap internal sampling with 500 iterations was adopted for validation to prevent overfitting of the model.

RESULTS: The final nomogram comprised nine predictors, including body mass index, thrombin time, tacrolimus initial concentration, rs757210, rs1799884, rs6887695, rs1494558, rs2069762 and rs2275913. In the training set, the area under the receiver operating characteristic curve of the nomogram was 0.781 (95%CI: 0.715-0.846), while in the validation set it was 0.698 (95%CI: 0.542-0.855), indicating good model fit. As demonstrated by 500 Bootstrap internal sampling validations, the model has high discrimination and calibration. Additionally, decision curve analysis confirmed its clinical applicability.

CONCLUSION: This study presents a genotype-guided nomogram that can be used to assess the risk of persistent AKI following LTx and may assist in guiding personalized prevention strategies in clinical practice.

PMID:39696008 | DOI:10.1186/s12882-024-03871-w

Cancer Cell Int. 2024 Dec 18;24(1):398. doi: 10.1186/s12935-024-03593-x.

ABSTRACT

BACKGROUND: AMD1 is the gene encoding S-adenosylmethionine decarboxylase 1. How AMD1 affects the prognosis of hepatocellular carcinoma (HCC) patients is unclear.

METHODS: Using the Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma datasets, gene enrichment and immunological traits were compared between groups with high and low AMD1 expression. After altering AMD1 expression in HCC cells, cell viability, the clonal formation rate, and migration and invasion ability were detected. Univariate Cox regression analysis and Pearson correlation were used to screen for AMD1-related genes (ARGs). Multidimensional bioinformatic algorithms were utilized to establish a risk score model for ARGs.

RESULTS: AMD1 expression was notably increased in the majority of cancer types. High AMD1 expression was associated with adverse outcomes and poorer immunotherapy response in HCC patients. AMD1 exhibited higher expression levels in HCC cell lines. The efficient inhibition of HCC cell proliferation, migration, and invasion in vitro can be achieved through the downregulation of AMD1. The AMD1-related risk score was constructed with the expression of 9 ARGs, and demonstrated high predictive efficacy in multiple validation cohorts. Patients with high risk scores exhibited greater resistance to classical chemotherapy drugs. The nomogram, which consists of age, stage, and the AMD1-related risk score, was used to calculate the probability of survival for each individual.

CONCLUSION: The present study indicates that AMD1 functions as a potential role in HCC progression and may serve as a therapeutic target in HCC. This study constructed a novel AMD1-related scoring system for predicting the prognosis and treatment responsiveness of patients with HCC, enabling the prediction of prognosis and identification of potential treatment targets.

PMID:39695661 | DOI:10.1186/s12935-024-03593-x

Genes Cells. 2025 Jan;30(1):e13185. doi: 10.1111/gtc.13185.

ABSTRACT

Aggregation of alpha-synuclein (α-Syn) is implicated in the pathogenesis of several neurodegenerative disorders, such as Parkinson's disease and Dementia with Lewy bodies, collectively termed synucleinopathies. Thus, tremendous efforts are being made to develop strategies to prevent or inhibit α-Syn aggregation. Here, we genetically engineered fission yeast to express human α-Syn C-terminally fused to green fluorescent protein (GFP) at low and high levels. α-Syn was localized at the cell tips and septa at low-level expression. At high-level expression, α-Syn was observed to form cytoplasmic aggregates. Notably, rapamycin, a natural product that allosterically inhibits the mammalian target of rapamycin (mTOR) by forming a complex with FKBP12, and Torin1, a synthetic mTOR inhibitor that blocks ATP binding to mTOR, markedly reduced the number of cells harboring α-Syn aggregates. These mTOR inhibitors abrogate α-Syn aggregation without affecting α-Syn expression levels. Rapamycin, but not Torin1, failed to reduce α-Syn aggregation in the deletion cells of fkh1+, encoding FKBP12, indicating the requirement of FKBP12 for rapamycin-mediated inhibition of α-Syn aggregation. Importantly, the effect of rapamycin was also observed in the cells lacking atg1+, a key regulator of autophagy. Collectively, rapamycin abrogates human α-Syn aggregation expressed in fission yeast via an autophagy-independent mechanism mediated by FKBP12.

PMID:39695344 | DOI:10.1111/gtc.13185

Diabetologia. 2024 Dec 19. doi: 10.1007/s00125-024-06339-6. Online ahead of print.

ABSTRACT

Progress in developing therapies for the maintenance of endogenous insulin secretion in, or the prevention of, type 1 diabetes has been hindered by limited animal models, the length and cost of clinical trials, difficulties in identifying individuals who will progress faster to a clinical diagnosis of type 1 diabetes, and heterogeneous clinical responses in intervention trials. Classic placebo-controlled intervention trials often include monotherapies, broad participant populations and extended follow-up periods focused on clinical endpoints. While this approach remains the 'gold standard' of clinical research, efforts are underway to implement new approaches harnessing the power of artificial intelligence and machine learning to accelerate drug discovery and efficacy testing. Here, we review emerging approaches for repurposing agents used to treat diseases that share pathogenic pathways with type 1 diabetes and selecting synergistic combinations of drugs to maximise therapeutic efficacy. We discuss how emerging multi-omics technologies, including analysis of antigen processing and presentation to adaptive immune cells, may lead to the discovery of novel biomarkers and subsequent translation into antigen-specific immunotherapies. We also discuss the potential for using artificial intelligence to create 'digital twin' models that enable rapid in silico testing of personalised agents as well as dose determination. To conclude, we discuss some limitations of artificial intelligence and machine learning, including issues pertaining to model interpretability and bias, as well as the continued need for validation studies via confirmatory intervention trials.

PMID:39694914 | DOI:10.1007/s00125-024-06339-6

Cell Genom. 2024 Dec 12:100724. doi: 10.1016/j.xgen.2024.100724. Online ahead of print.

ABSTRACT

Achieving diverse representation in biomedical data is critical for healthcare equity. Failure to do so perpetuates health disparities and exacerbates biases that may harm patients with underrepresented ancestral backgrounds. We present a quantitative assessment of representation in datasets used across human genomics, including genome-wide association studies (GWASs), pharmacogenomics, clinical trials, and direct-to-consumer (DTC) genetic testing. We suggest that relative proportions of ancestries represented in datasets, compared to the global census population, provide insufficient representation of global ancestral genetic diversity. Some populations have greater proportional representation in data relative to their population size and the genomic diversity present in their ancestral haplotypes. As insights from genomics become increasingly integrated into evidence-based medicine, strategic inclusion and effective mechanisms to ensure representation of global genomic diversity in datasets are imperative.

PMID:39694036 | DOI:10.1016/j.xgen.2024.100724

Pharmacogenet Genomics. 2024 Dec 19. doi: 10.1097/FPC.0000000000000557. Online ahead of print.

ABSTRACT

This short communication serves as an update to previously published pilot study results on bronchodilator response (BDR) in children with asthma. We expanded our cohort from 54 to 165 pediatric patients seeking emergency department care for an asthma exacerbation. We obtained measured BDR before and after albuterol administration using the Pediatric Asthma Severity Score and collected genomic DNA. Based on a literature review, we analyzed whether 21 candidate single-nucleotide polymorphisms (SNPs) were associated with BDR. Among the three SNPs initially reported in our pilot study as significantly associated with BDR (rs912142, rs7081864, and rs7903366), we confirmed that rs7081864 was still significantly associated with suboptimal BDR (odds ratio, 0.47; confidence interval, 0.24-0.92). If externally validated in broader studies, simple outpatient testing for that SNP variant could help guide pharmacologic therapy for acute asthma symptoms.

PMID:39693206 | DOI:10.1097/FPC.0000000000000557

J Am Assoc Nurse Pract. 2024 Dec 18. doi: 10.1097/JXX.0000000000001108. Online ahead of print.

ABSTRACT

Depression is a leading cause of disability worldwide, with treatment-resistant depression (TRD) affecting approximately 30% of patients who do not respond to standard antidepressants. In underserved and uninsured communities, where Nurse Practitioners (NPs) often provide essential mental health care, the challenges of managing TRD are compounded by limited access to specialized services. Pharmacogenomic testing offers a promising approach to overcoming these barriers by providing personalized medication recommendations based on a patient's genetic profile. This brief report examines the medical records of 46 patients from underserved communities who underwent genetic testing for TRD. Of the patients reviewed, 31 achieved remission within 2 months of receiving genetically guided treatment, resulting in a remission rate of 67.39%. Patients with specific genetic markers, such as poor metabolizers for CYP2D6 or CYP2C19, experienced the most significant benefits. These findings suggest that pharmacogenomic testing can significantly improve treatment outcomes for TRD in underserved populations, enabling NPs to provide more personalized, effective care. Further research is necessary to explore the long-term benefits and cost-effectiveness of integrating pharmacogenomic testing into NP-led practices, particularly in resource-limited settings.

PMID:39692864 | DOI:10.1097/JXX.0000000000001108

Exp Biol Med (Maywood). 2024 Dec 3;249:10393. doi: 10.3389/ebm.2024.10393. eCollection 2024.

ABSTRACT

Pharmacogenomics (PGx) holds the promise of personalizing medical treatments based on individual genetic profiles, thereby enhancing drug efficacy and safety. However, the current landscape of PGx research is hindered by fragmented data sources, time-consuming manual data extraction processes, and the need for comprehensive and up-to-date information. This study aims to address these challenges by evaluating the ability of Large Language Models (LLMs), specifically Llama3.1-70B, to automate and improve the accuracy of PGx information extraction from the FDA Table of Pharmacogenomic Biomarkers in Drug Labeling (FDA PGx Biomarker table), which is well-structured with drug names, biomarkers, therapeutic area, and related labeling texts. Our primary goal was to test the feasibility of LLMs in streamlining PGx data extraction, as an alternative to traditional, labor-intensive approaches. Llama3.1-70B achieved 91.4% accuracy in identifying drug-biomarker pairs from single labeling texts and 82% from mixed texts, with over 85% consistency in aligning extracted PGx categories from FDA PGx Biomarker table and relevant scientific abstracts, demonstrating its effectiveness for PGx data extraction. By integrating data from diverse sources, including scientific abstracts, this approach can support pharmacologists, regulatory bodies, and healthcare researchers in updating PGx resources more efficiently, making critical information more accessible for applications in personalized medicine. In addition, this approach shows potential of discovering novel PGx information, particularly of underrepresented minority ethnic groups. This study highlights the ability of LLMs to enhance the efficiency and completeness of PGx research, thus laying a foundation for advancements in personalized medicine by ensuring that drug therapies are tailored to the genetic profiles of diverse populations.

PMID:39691764 | PMC:PMC11650518 | DOI:10.3389/ebm.2024.10393

Front Pharmacol. 2024 Dec 3;15:1476765. doi: 10.3389/fphar.2024.1476765. eCollection 2024.

ABSTRACT

Adverse drug reactions (ADRs) pose substantial public health issues, necessitating population-specific characterization due to variations in pharmacogenes. This study delineates the pharmacogenomic (PGx) landscape of the South Korean (SKR) population, focusing on 21 core pharmacogenes. Whole genome sequencing (WGS) was conducted on 396 individuals, including 99 healthy volunteers, 95 patients with chronic diseases, 81 with colon cancer, 81 with breast cancer, and 40 with gastric cancer, to identify genotype-specific drug dosing recommendations. Our detailed analysis, utilizing high-throughput genotyping (HTG) of CYP2D6 and comparative data from the 1,000 Genomes Project (1 KG) and the US National Marrow Donor Program (NMDP), revealed significant pharmacogenetic diversity in core pharmacogenes such as CYP2B6, CYP2C19, CYP4F2, NUDT15, and CYP2D6. Notably, intermediate metabolizer frequencies for CYP2B6 in SKR (3.28%) were comparable to Europeans (5.77%) and East Asians (5.36%) but significantly differed from other global populations (p < 0.01). For CYP2C19, 48.74% of SKR individuals were classified as intermediate metabolizers, with the *35 allele (2.02%) being unique to SKR, the allele not observed in other East Asian populations. Additionally, the high-risk *3 allele in CYP4F2 was significantly more frequent in SKR (34.72%) than in other East Asian populations (p < 0.01). NUDT15 poor metabolizers were found in 0.76% of SKR, aligning closely with other East Asians (1.59%), while TPMT poor metabolizers were predominantly observed in Europeans and Africans, with one case in SKR. We identified significant allele frequency differences in CYP2D6 variants rs1065852 and rs1135840. Among the 72 drugs analyzed, 93.43% (n = 370) of patients required dosage adjustments for at least one drug, with an average of 4.5 drugs per patient. Moreover, 31.31% (n = 124) required adjustments for more than five drugs. These findings reveal the substantial pharmacogenetic diversity of the SKR population within the global population, emphasizing the urgency of integrating population-specific PGx data into clinical practice to ensure safe and effective drug therapies. This comprehensive PGx profiling in SKR not only advances personalized medicine but also holds the potential to significantly improve healthcare outcomes on a broader scale.

PMID:39691389 | PMC:PMC11650365 | DOI:10.3389/fphar.2024.1476765

Cancers (Basel). 2024 Nov 25;16(23):3941. doi: 10.3390/cancers16233941.

ABSTRACT

BACKGROUND: Oncogene-driven NSCLC is usually treated with targeted therapies using tyrosine kinase inhibitors (TKIs) to inhibit oncogene downstream signaling pathways, affecting tumor survival and proliferation. EGFR- and KRAS-mutant NSCLCs are the most represented subtypes, and they are treated in clinical practice with oncogene-targeting drugs in the first and second line, respectively. Unfortunately, the development of oncogene-independent resistant clones limits TKI efficacy. Here, we used non-oncogene addiction (NOA) as an innovative therapeutic strategy to target other essential proteins that support changes in tumor phenotype. Specifically, we tested, for the first time, a combination of inhibitors, namely ATR, involved in DNA damage response, and pyruvate dehydrogenase kinases (PDKs), involved in energy metabolism.

METHODS: Sensitive PC9 and the corresponding EGFR-TKI-resistant PC9/OR, EGFR-mutant H1975, and KRAS-mutant A549 NSCLC cells, were treated with TKIs (osimertinib and selumetinib, respectively). In parallel, cells were exposed to two combination regimens: one using the TKI with an ATR inhibitor and the other one combining the two selected NOA inhibitors (ATR inhibitor, M4344; and PDK inhibitor, DCA).

RESULTS: The effect of these two combined approaches, compared to TKI alone, produced similar results in terms of cell proliferation, cell death, and migration. Thus, depending on tumor biology, selecting between the proposed therapeutic strategies will be different, to maximize tumor response.

CONCLUSIONS: The major translational relevance of this study is to exploit new targets for the development of innovative and improved therapeutic strategies with NOA drugs, over combinations including target genes within the oncogene pathway, to overcome resistance to TKI therapies in patients with NSCLC who are oncogene-addicted.

PMID:39682133 | PMC:PMC11639923 | DOI:10.3390/cancers16233941

Int J Pharm. 2024 Dec 15:125070. doi: 10.1016/j.ijpharm.2024.125070. Online ahead of print.

ABSTRACT

Over the next decade, Precision Medicine (PM) is poised to become the standard of care in pharmaceutical therapy, necessitating a fundamental transformation in the design and development of innovative custom-made drug products. To date, a comprehensive review linking PM with practical personalized drug formulations is missing. This review attempts to provide an overview of state-of-the-art formulation approaches capable of translating PM evaluation and resulting recommendations (clinical research) into tailored drug products (non-clinical research) for real-world patients. Comprehensive literature searches in four scientific databases (Scopus, SciFinder, Web of Science, and PubMed) were performed. Current approaches to point-of-care PM formulations and needs-based locally distributed manufacturing presently under research & development (R&D) as alternatives to conventional large-scale manufacturing of one-size-fits-all drug products are discussed. The following methods were identified as the most promising PM formulation strategies: tablet splitting, liquid dispensing, compounding pharmacies, additive manufacturing, drug impregnation, drug extrusion, and orodispersible films (ODFs). The challenges and opportunities of current state-of-the-art formulation technologies that can enable making PM routinely accessible in practice settings will be discussed. Additionally, light will be shed on point-of-use manufacturing (Pharmacy on Demand) as an uncharted territory for PM and its pathway towards practical implementation.

PMID:39689830 | DOI:10.1016/j.ijpharm.2024.125070

J Mol Neurosci. 2024 Dec 17;75(1):1. doi: 10.1007/s12031-024-02301-8.

ABSTRACT

BACKGROUND AND OBJECTIVES: Data on the association between BDNF rs6265 and multiple sclerosis (MS) are scarce and heterogeneous.

MATERIALS AND METHODS: We undertook a case-control study design. Newly diagnosed individuals with MS based on the 2017 revision of the McDonald criteria were recruited from the Neurology Department of the General University Hospital of Larissa. Healthy controls with a free medical and family history were also recruited. The relationship between BDNF rs6265 and MS was defined as the primary outcome. The association between rs6265 and age of MS onset, spinal lesions, and clinical manifestations at the time of MS onset were defined as the secondary outcomes.

RESULTS: We genotyped a total of 200 patients with MS and 205 healthy controls, yielding a sample power of approximately 80%. BDNF rs6265 was in Hardy-Weinberg Equilibrium among healthy participants (p = 0.64). No significant relationship was revealed between rs6265 and MS [log-additive OR = 0.83 (0.57,1.21), over-dominant OR = 0.73 (0.48,1.14), recessive OR = 1.24 (0.37,4.12), dominant OR = 0.77 (0.50,1.17), co-dominant OR1 = 0.74 (0.48,1.14) and co-dominant OR2 = 1.13 (0.34,3.80)]. Additionally, rs6265 was unrelated to the age of MS onset according to both unadjusted and sex-adjusted cox-proportional models. Finally, rs6265 was not associated with the presence of spinal lesions (cervical or thoracic) at MS onset, according to both unadjusted and age and sex-adjusted logistic regression models.

CONCLUSIONS: We failed to establish an association between BDNF rs6265 and the risk of MS, the age of onset, the presence of spinal lesions, and the clinical manifestations at the onset.

PMID:39690366 | DOI:10.1007/s12031-024-02301-8

Neuro Endocrinol Lett. 2024 Nov 28;45(5):333-340. Online ahead of print.

ABSTRACT

OBJECTIVES: To determine whether selected single nucleotide polymorphisms (SNPs) of genes encoding proteins responsible for the activation, transport, or metabolism of dabigatran and apixaban might be associated with a risk of gastrointestinal bleeding in a cohort of adult patients treated with these drugs. No previous study has focused specifically on the association with gastrointestinal bleeding.

MATERIALS AND METHODS: Ninety-one patients treated with dabigatran or apixaban were genotyped for selected polymorphisms. The following polymorphisms were studied: ABCB1 gene rs1045642, rs4148738, rs1128503 and rs2032582; CES1 gene rs2244613, rs8192935 and rs2244614; and SULT1A1 gene rs9282861 and SULT1A2 gene rs1136703. Two groups divided by particular drugs and genotypes were compared in terms of the presence (bleeding group) or absence (nonbleeding group) of gastrointestinal bleeding. The genotype distribution was expressed via dominant and recessive models.

RESULTS: In patients treated either with dabigatran or with apixaban, no evidence was found to support the association of gastrointestinal bleeding with any genotype for any of the studied SNPs.

CONCLUSION: In both dabigatran- and apixaban-treated patients, no associations between the selected polymorphisms and gastrointestinal bleeding risk were found, however the results should be interpreted with caution because of the small cohort size.

PMID:39688660