Am J Health Syst Pharm. 2024 Mar 28:zxae083. doi: 10.1093/ajhp/zxae083. Online ahead of print.

ABSTRACT

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

PURPOSE: We describe the implementation and ongoing maintenance of CYP2C19 and CYP2D6 focused pharmacogenetic (PGx) testing to guide antidepressant and antianxiety medication prescriptions in a large rural, nonprofit health system.

SUMMARY: Depression and anxiety are common psychiatric conditions. Sanford Health implemented PGx testing for metabolism of cytochrome P450 (CYP) isozymes 2C19 and 2D6 in 2014 to inform prescribing for multiple medications, including antidepressant and antianxiety therapies. As guidelines, genotype to phenotype translation, panel offerings, and other resources are updated, we adapt our approach. We make educational and informational materials available to providers and patients. Pharmacogenomic clinical pharmacists review PGx results with discrete values and provide guidance documentation in the electronic medical record. A robust clinical decision support system is in place to provide interruptive alerts, noninterruptive alerts, and genomic indicators. A referral-based interdisciplinary clinic is also available to provide in-depth education to patients regarding PGx results and implications. Additionally, partnering with our health plan has expanded access to PGx testing for patients with anxiety or depression.

CONCLUSION: The implementation and maintenance of Sanford Health's PGx program to guide antidepressant and antianxiety medication use continues to evolve and requires a multipronged approach relying on both human and informatics-based resources.

PMID:38546726 | DOI:10.1093/ajhp/zxae083

Cancer Res Commun. 2024 Mar 26;4(3):919-937. doi: 10.1158/2767-9764.CRC-23-0161.

ABSTRACT

Lung cancer is the leading cause of cancer deaths. Lethal pulmonary adenocarcinomas (ADC) present with frequent mutations in the EGFR. Genetically engineered murine models of lung cancer expedited comprehension of the molecular mechanisms driving tumorigenesis and drug response. Here, we systematically analyzed the evolution of tumor heterogeneity in the context of dynamic interactions occurring with the intermingled tumor microenvironment (TME) by high-resolution transcriptomics. Our effort identified vulnerable tumor-specific epithelial cells, as well as their cross-talk with niche components (endothelial cells, fibroblasts, and tumor-infiltrating immune cells), whose symbiotic interface shapes tumor aggressiveness and is almost completely abolished by treatment with Unesbulin, a tubulin binding agent that reduces B cell-specific Moloney murine leukemia virus integration site 1 (BMI-1) activity. Simultaneous magnetic resonance imaging (MRI) analysis demonstrated decreased tumor growth, setting the stage for future investigations into the potential of novel therapeutic strategies for EGFR-mutant ADCs.

SIGNIFICANCE: Targeting the TME is an attractive strategy for treatment of solid tumors. Here we revealed how EGFR-mutant landscapes are affected at the single-cell resolution level during Unesbulin treatment. This novel drug, by targeting cancer cells and their interactions with crucial TME components, could be envisioned for future therapeutic advancements.

PMID:38546390 | DOI:10.1158/2767-9764.CRC-23-0161

Heliyon. 2024 Mar 16;10(6):e28243. doi: 10.1016/j.heliyon.2024.e28243. eCollection 2024 Mar 30.

ABSTRACT

Pancreatic cancer (PC) is a malignant digestive system tumor with a very poor prognosis. N6-methyladenosine (m6A) is mediated by a variety of readers and participates in important regulatory roles in PC. Based on TCGA_PAAD, ICGC_AU_PAAD, ICGC_CA_PAAD, GSE28735 and GSE62452 datasets, We mapped the multi-omics changes of m6A readers in PC and found that m6A readers, especially IGF2BP family genes, had specific changes and were significantly associated with poor prognosis. An unsupervised consensus clustering algorithm was used to explore the correlation between specific expression patterns of m6A readers in PC and enrichment pathways, tumor immunity and clinical molecular subtypes. Then, the principal component analysis (PCA) algorithm was used to quantify specific expression patterns and screen core genes. Machine learning algorithms such as Bootstrapping and RSF were used to quantify the expression patterns of core genes and construct a prognostic scoring model for PC patients. What's more, pharmacogenomic databases were used to screen sensitive drug targets and small molecule compounds for high-risk PC patients in an all-around and multi-angle way. Our study has not only provided new insights into personalized prognostication approaches, but also thrown light on integrating tailored risk stratification with precision therapy based on IGF2BP2-mediated m6A modification patterns.

PMID:38545193 | PMC:PMC10965819 | DOI:10.1016/j.heliyon.2024.e28243

Pharmaceutics. 2024 Mar 12;16(3):388. doi: 10.3390/pharmaceutics16030388.

ABSTRACT

Genetic polymorphisms can exert a considerable impact on drug pharmacokinetics (PK) and the development of adverse drug reactions (ADR). However, the effect of genetic polymorphisms on the anti-tuberculosis (anti-TB) drug, and particularly rifampicin (RIF), exposure or anti-TB drug-induced liver injury (DILI) remains uncertain. Here, we evaluated the relationship between single nucleotide polymorphisms (SNPs) detected in the RIF pharmacogenes (AADAC, SLCO1B1, SLCO1B3, ABCB1, and NR1I2) and RIF PK parameters, as well as anti-TB treatment-associated DILI. In total, the study enrolled 46 patients with drug-susceptible pulmonary TB. The RIF plasma concentration was measured using the LC-MS/MS method in the blood samples collected pre-dose and 2 and 6 h post-dose, whilst the DILI status was established using the results from blood biochemical analysis performed before and 10-12 days after treatment onset. The genotyping was conducted using a targeted NGS approach. After adjustment for confounders, the patients carrying the rs3732357 GA/AA genotype of the NR1I2 gene were found to have significantly lower RIF plasma AUC0-6 h in comparison to those with GG genotype, while the difference in RIF plasma Cmax was insignificant. None of the analyzed SNPs was related to DILI. Hence, we are the first to report NR1I2 intronic SNP rs3732357 as the genetic component of variability in RIF exposure. Regarding anti-TB treatment-associated DILI, the other preexisting factors promoting this ADR should be considered.

PMID:38543282 | DOI:10.3390/pharmaceutics16030388

Pharmaceuticals (Basel). 2024 Mar 2;17(3):331. doi: 10.3390/ph17030331.

ABSTRACT

Antibiotic-related adverse events are common in both adults and children, and knowledge of the factors that favor the development of antibiotic-related adverse events is essential to limit their occurrence and severity. Genetics can condition the development of antibiotic-related adverse events, and the screening of patients with supposed or demonstrated specific genetic mutations may reduce drug-related adverse events. This narrative review discusses which genetic variations may influence the risk of antibiotic-related adverse events and which conclusions can be applied to clinical practice. An analysis of the literature showed that defined associations between genetic variations and specific adverse events are very few and that, at the moment, none of them have led to the implementation of a systematic screening process for patients that must be treated with a given antibiotic in order to select those at risk of specific adverse events. On the other hand, in most of the cases, more than one variation is implicated in the determination of adverse events, and this can be a limitation in planning a systematic screening. Moreover, presently, the methods used to establish whether a patient carries a "dangerous" genetic mutation require too much time and waiting for the result of the test can be deleterious for those patients urgently requiring therapy. Further studies are needed to definitively confirm which genetic variations are responsible for an increased risk of a well-defined adverse event.

PMID:38543117 | DOI:10.3390/ph17030331

J Pers Med. 2024 Feb 25;14(3):246. doi: 10.3390/jpm14030246.

ABSTRACT

BACKGROUND: Although inhaled corticosteroids (ICS) are the first-line therapy for patients with persistent asthma, many patients continue to have exacerbations. We developed machine learning models to predict the ICS response in patients with asthma.

METHODS: The subjects included asthma patients of European ancestry (n = 1371; 448 children; 916 adults). A genome-wide association study was performed to identify the SNPs associated with ICS response. Using the SNPs identified, two machine learning models were developed to predict ICS response: (1) least absolute shrinkage and selection operator (LASSO) regression and (2) random forest.

RESULTS: The LASSO regression model achieved an AUC of 0.71 (95% CI 0.67-0.76; sensitivity: 0.57; specificity: 0.75) in an independent test cohort, and the random forest model achieved an AUC of 0.74 (95% CI 0.70-0.78; sensitivity: 0.70; specificity: 0.68). The genes contributing to the prediction of ICS response included those associated with ICS responses in asthma (TPSAB1, FBXL16), asthma symptoms and severity (ABCA7, CNN2, PTRN3, and BSG/CD147), airway remodeling (ELANE, FSTL3), mucin production (GAL3ST), leukotriene synthesis (GPX4), allergic asthma (ZFPM1, SBNO2), and others.

CONCLUSIONS: An accurate risk prediction of ICS response can be obtained using machine learning methods, with the potential to inform personalized treatment decisions. Further studies are needed to examine if the integration of richer phenotype data could improve risk prediction.

PMID:38540988 | DOI:10.3390/jpm14030246

Biomolecules. 2024 Mar 19;14(3):367. doi: 10.3390/biom14030367.

ABSTRACT

Inherited macular dystrophies (iMDs) are a group of genetic disorders, which affect the central region of the retina. To investigate the genetic basis of iMDs, we used single-molecule Molecular Inversion Probes to sequence 105 maculopathy-associated genes in 1352 patients diagnosed with iMDs. Within this cohort, 39.8% of patients were considered genetically explained by 460 different variants in 49 distinct genes of which 73 were novel variants, with some affecting splicing. The top five most frequent causative genes were ABCA4 (37.2%), PRPH2 (6.7%), CDHR1 (6.1%), PROM1 (4.3%) and RP1L1 (3.1%). Interestingly, variants with incomplete penetrance were revealed in almost one-third of patients considered solved (28.1%), and therefore, a proportion of patients may not be explained solely by the variants reported. This includes eight previously reported variants with incomplete penetrance in addition to CDHR1:c.783G>A and CNGB3:c.1208G>A. Notably, segregation analysis was not routinely performed for variant phasing-a limitation, which may also impact the overall diagnostic yield. The relatively high proportion of probands without any putative causal variant (60.2%) highlights the need to explore variants with incomplete penetrance, the potential modifiers of disease and the genetic overlap between iMDs and age-related macular degeneration. Our results provide valuable insights into the genetic landscape of iMDs and warrant future exploration to determine the involvement of other maculopathy genes.

PMID:38540785 | DOI:10.3390/biom14030367

Genes (Basel). 2024 Mar 20;15(3):379. doi: 10.3390/genes15030379.

ABSTRACT

Beta adrenergic receptor antagonists, known as beta blockers, are one of the most prescribed medications in both pediatric and adult cardiology. Unfortunately, most of these agents utilized in the pediatric clinical setting are prescribed off-label. Despite regulatory efforts aimed at increasing pediatric drug labeling, a majority of pediatric cardiovascular drug agents continue to lack pediatric-specific data to inform precision dosing for children, adolescents, and young adults. Adding to this complexity is the contribution of development (ontogeny) and genetic variation towards the variability in drug disposition and response. In the absence of current prospective trials, the purpose of this comprehensive review is to illustrate the current knowledge gaps regarding the key drivers of variability in beta blocker drug disposition and response and the opportunities for investigations that will lead to changes in pediatric drug labeling.

PMID:38540438 | DOI:10.3390/genes15030379

Genes (Basel). 2024 Mar 11;15(3):352. doi: 10.3390/genes15030352.

ABSTRACT

BACKGROUND: The advancement of next-generation sequencing (NGS) technologies provides opportunities for large-scale Pharmacogenetic (PGx) studies and pre-emptive PGx testing to cover a wide range of genotypes present in diverse populations. However, NGS-based PGx testing is limited by the lack of comprehensive computational tools to support genetic data analysis and clinical decisions.

METHODS: Bioinformatics utilities specialized for human genomics and the latest cloud-based technologies were used to develop a bioinformatics pipeline for analyzing the genomic sequence data and reporting PGx genotypes. A database was created and integrated in the pipeline for filtering the actionable PGx variants and clinical interpretations. Strict quality verification procedures were conducted on variant calls with the whole genome sequencing (WGS) dataset of the 1000 Genomes Project (G1K). The accuracy of PGx allele identification was validated using the WGS dataset of the Pharmacogenetics Reference Materials from the Centers for Disease Control and Prevention (CDC).

RESULTS: The newly created bioinformatics pipeline, Pgxtools, can analyze genomic sequence data, identify actionable variants in 13 PGx relevant genes, and generate reports annotated with specific interpretations and recommendations based on clinical practice guidelines. Verified with two independent methods, we have found that Pgxtools consistently identifies variants more accurately than the results in the G1K dataset on GRCh37 and GRCh38.

CONCLUSIONS: Pgxtools provides an integrated workflow for large-scale genomic data analysis and PGx clinical decision support. Implemented with cloud-native technologies, it is highly portable in a wide variety of environments from a single laptop to High-Performance Computing (HPC) clusters and cloud platforms for different production scales and requirements.

PMID:38540411 | DOI:10.3390/genes15030352

Genes (Basel). 2024 Feb 28;15(3):309. doi: 10.3390/genes15030309.

ABSTRACT

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive disease that affects motor neurons, leading to paralysis and death usually 3-5 years after the onset of symptoms. The investigation of both sporadic and familial ALS highlighted four main genes that contribute to the pathogenesis of the disease: SOD1, FUS, TARDBP and C9orf72. This study aims to provide a comprehensive investigation of genetic variants found in SOD1, FUS and TARDBP genes in Greek sporadic ALS (sALS) cases. Our sequencing analysis of the coding regions of the abovementioned genes that include the majority of the variants that lead to ALS in 32 sALS patients and 3 healthy relatives revealed 6 variants in SOD1, 19 variants in FUS and 37 variants in TARDBP, of which the SOD1 p.D90A and the FUS c.*356G>A (rs886051940) variants have been previously associated with ALS, while two novel nonsense pathogenic variants were also identified, namely FUS p.R241* and TDP-43 p.Y214*. Our study contributes to the worldwide effort toward clarifying the genetic basis of sALS to better understand the disease's molecular pathology.

PMID:38540370 | DOI:10.3390/genes15030309

Biomedicines. 2024 Mar 12;12(3):627. doi: 10.3390/biomedicines12030627.

ABSTRACT

Metabolic syndrome (MetS) is common among schizophrenia patients, and one of MetS's causes may be an imbalance in nitric oxide regulation. In this study, we examined associations of three polymorphic variants of the nitric oxide synthase 1 adapter protein (NOS1AP) gene with MetS in schizophrenia. NOS1AP regulates neuronal nitric oxide synthase, which controls intracellular calcium levels and may influence insulin secretion. The aim of the investigation was to study polymorphic variants of the NOS1AP gene as possible markers of MetS in patients with schizophrenia. A total of 489 Caucasian patients with schizophrenia (ICD-10) from Siberia (Russia) were included in the study, and 131 (26.8%) patients had MetS (IDF classification, 2007). The participants were genotyped for three single-nucleotide polymorphisms in NOS1AP (rs12143842, rs10494366, and rs12029454). Logistic regression was used for association analysis. Single-nucleotide polymorphisms, sex, and age served as covariates; the dependent variable was the coded parameter of the presence/absence of MetS. Polymorphisms rs12143842 and rs10494366 showed a stable association even after Bonferroni's correction for multiple comparisons (p = 0.005 and 0.002, respectively), indicating a statistically significant contribution of these polymorphic variants to the pathogenesis of MetS. Our results suggest that in patients with schizophrenia, NOS1AP may be involved in MetS pathophysiology.

PMID:38540239 | DOI:10.3390/biomedicines12030627

Antioxidants (Basel). 2024 Feb 24;13(3):277. doi: 10.3390/antiox13030277.

ABSTRACT

This systematic review extensively investigated the role of the genetic and transcriptomic factors in late complications of type 2 diabetes mellitus (T2DM) and the current approaches targeting oxidative-stress-related pathways with antioxidant therapies. To cover our broad research area, we have conducted two systematic searches, the first focusing on genetic and transcriptomic factors affecting oxidative stress and the second one focusing on the antioxidant therapies in late complications of T2DM. The final review included 33 genetic and transcriptomic studies and 23 interventional randomized clinical trials. The conducted systematic review highlights the important role of oxidative stress in the development of late complications in T2DM patients. However, the current level of evidence does not support the use of genetic and transcriptomic factors as predictive and prognostic biomarkers for the development of T2DM late complications. Further studies are needed to elucidate the potential of targeting oxidative-stress-related pathways for novel preventative and therapeutic approaches. Additionally, antioxidants both in dietary and supplement form have been shown to improve different metabolic and biochemical parameters in T2DM patients with developed late complications. In recent years, studies have improved in methodological quality despite still mainly focusing on microvascular late complications of T2DM. Furthermore, the observed interventional studies suggest non-homogeneity in the duration of observation. As many studies do not provide post-intervention follow-up testing, it is difficult to assess the long-term health benefits of antioxidant supplementation.

PMID:38539811 | DOI:10.3390/antiox13030277

Children (Basel). 2024 Feb 23;11(3):278. doi: 10.3390/children11030278.

ABSTRACT

The two primary classes of opioid substances are morphine and its synthetic derivative, heroin. Opioids can cross the placental barrier, reaching fetal circulation. Therefore, at any gestational age, the fetus is highly exposed to pharmacologically active opioid metabolites and their associated adverse effects. This review aimed to investigate all the studies reported in a timeframe of forty years about prenatal and postnatal outcomes of opioid exposition during pregnancy. Clinical and toxicological aspects, as well as pharmacogenetic and epigenetic research focusing on fetal and infant effects of opioid use during pregnancy together with their medico-legal implications are exposed and discussed.

PMID:38539313 | DOI:10.3390/children11030278

BMC Med Genomics. 2024 Mar 27;17(1):79. doi: 10.1186/s12920-024-01849-z.

ABSTRACT

BACKGROUND: Hypothyroidism is a common endocrine disorder that exerts a substantial influence on people all over the world. Levothyroxine (LT-4) is the drug of choice for the treatment of hypothyroidism and the starting oral dose is typically ranging from 1.5 to 1.7 µg/kg/day. The target is to achieve an optimum serum TSH level of 0.4-4.0 mIU/L; hence, the dose is titrated accordingly. Once the LT-4 dose is adjusted to obtain the target TSH level, it usually remains stable for a long period of time in most cases. However, some of the patients require frequent dose adjustments and some of them require unusually high doses. Therefore, the aim of this study is to determine the association of pharmacogenomic, clinical and behavioural factors with the oral levothyroxine (LT-4) dose requirement of hypothyroid patients in Sri Lanka.

METHOD: This study will be conducted as a matched case-control study and will involve primary hypothyroid patients who visit the diabetes and endocrinology clinic at the National Hospital, Kandy, Sri Lanka. We will recruit a total of 292 cases and select 292 controls from the clinic who are matched in terms of age, sex and Body Mass Index (BMI). An interviewer-administered questionnaire will be used to collect data from the participants (n = 584). Of the 584 patients, blood samples will be collected from a sub-sample (n = 150) for DNA extraction. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) will be performed for single nucleotide polymorphisms (SNP) analysis.

DISCUSSION: Frequent dose adjustments of levothyroxine cause a serious economic burden to the healthcare system. By identifying the root causes of the variations in LT-4 dosage, a more comprehensive comprehension of hypothyroidism and its management can be attained in Sri Lanka. Furthermore, upon identification of a positive association/correlation between genetic polymorphisms and the LT-4 dose, SNP profiles can be used as a possible genetic marker for dose adjustment determination in future patients.

PMID:38539190 | DOI:10.1186/s12920-024-01849-z

Transl Psychiatry. 2024 Mar 26;14(1):165. doi: 10.1038/s41398-024-02880-5.

ABSTRACT

Alcohol use disorder (AUD) is the most prevalent substance use disorder worldwide. Acamprosate and naltrexone are anti-craving drugs used in AUD pharmacotherapy. However, molecular mechanisms underlying their anti-craving effect remain unclear. This study utilized a patient-derived induced pluripotent stem cell (iPSC)-based model system and anti-craving drugs that are used to treat AUD as "molecular probes" to identify possible mechanisms associated with alcohol craving. We examined the pathophysiology of craving and anti-craving drugs by performing functional genomics studies using iPSC-derived astrocytes and next-generation sequencing. Specifically, RNA sequencing performed using peripheral blood mononuclear cells from AUD patients with extreme values for alcohol craving intensity prior to treatment showed that inflammation-related pathways were highly associated with alcohol cravings. We then performed a genome-wide assessment of chromatin accessibility and gene expression profiles of induced iPSC-derived astrocytes in response to ethanol or anti-craving drugs. Those experiments identified drug-dependent epigenomic signatures, with IRF3 as the most significantly enriched motif in chromatin accessible regions. Furthermore, the activation of IRF3 was associated with ethanol-induced endoplasmic reticulum (ER) stress which could be attenuated by anti-craving drugs, suggesting that ER stress attenuation might be a target for anti-craving agents. In conclusion, we found that craving intensity was associated with alcohol consumption and treatment outcomes. Our functional genomic studies suggest possible relationships among craving, ER stress, IRF3 and the actions of anti-craving drugs.

PMID:38531832 | PMC:PMC10965952 | DOI:10.1038/s41398-024-02880-5

Front Biosci (Schol Ed). 2024 Feb 29;16(1):3. doi: 10.31083/j.fbs1601003.

ABSTRACT

Age-related macular degeneration (AMD) is a multifactorial genetic disease, with at least 52 identifiable associated gene variants at 34 loci, including variants in complement factor H (CFH) and age-related maculopathy susceptibility 2/high-temperature requirement A serine peptidase-1 (ARMS2/HTRA1). Genetic factors account for up to 70% of disease variability. However, population-based genetic risk scores are generally more helpful for clinical trial design and stratification of risk groups than for individual patient counseling. There is some evidence of pharmacogenetic influences on various treatment modalities used in AMD patients, including Age-Related Eye Disease Study (AREDS) supplements, photodynamic therapy (PDT), and anti-vascular endothelial growth factor (anti-VEGF) agents. However, there is currently no convincing evidence that genetic information plays a role in routine clinical care.

PMID:38538345 | DOI:10.31083/j.fbs1601003

Neuron. 2024 Mar 18:S0896-6273(24)00154-5. doi: 10.1016/j.neuron.2024.02.021. Online ahead of print.

ABSTRACT

A postulated role of subcortical neuromodulators is to control brain states. Mechanisms by which different neuromodulators compete or cooperate at various temporal scales remain an open question. We investigated the interaction of acetylcholine (ACh) and oxytocin (OXT) at slow and fast timescales during various brain states. Although these neuromodulators fluctuated in parallel during NREM packets, transitions from NREM to REM were characterized by a surge of ACh but a continued decrease of OXT. OXT signaling lagged behind ACh. High ACh was correlated with population synchrony and gamma oscillations during active waking, whereas minimum ACh predicts sharp-wave ripples (SPW-Rs). Optogenetic control of ACh and OXT neurons confirmed the active role of these neuromodulators in the observed correlations. Synchronous hippocampal activity consistently reduced OXT activity, whereas inactivation of the lateral septum-hypothalamus path attenuated this effect. Our findings demonstrate how cooperative actions of these neuromodulators allow target circuits to perform specific functions.

PMID:38537642 | DOI:10.1016/j.neuron.2024.02.021

J Clin Psychiatry. 2024 Mar 27;85(2):23m15008. doi: 10.4088/JCP.23m15008.

ABSTRACT

Objective: The aim of this study was to evaluate valproate dose association with weight change, blood glucose, lipid levels, and blood pressure in a psychiatric population.

Methods: Data from 215 patients taking valproate for up to 1 year were collected from 2 longitudinal studies that monitored metabolic variables between 2007 and 2022. Linear mixed-effect models and logistic regressions were used to analyze the associations between valproate doses and metabolic outcomes.

Results: An increase in valproate dose of 500 mg was associated with a weight change of +0.52% per month over a year (P < .001). The association between valproate dose and weight change was evident both before and after 3 months of treatment. Weight increase was greater for treatment durations of < 3 months compared to ≥ 3 months (+0.56%, P < .001 and +0.12%, P = .02 per month, respectively). Using piecewise regression, a significant association between dose and weight gain was observed in patients receiving doses equal to or above the median dose (1,300 mg/d), with a +0.50% increase in weight for each dose increment of 500 mg (P = .004). Among men, each 500 mg dose increment was associated with weight increases of +0.59% per month (P = .004), whereas a trend was observed for women (+0.40%, P = .09). No associations were found between valproate doses and blood glucose, lipid levels, or blood pressure over a 6-month treatment period.

Conclusions: This study provides evidence that valproate dose, mainly for doses at or above 1,300 mg/d, is associated with weight gain in psychiatric patients, suggesting that the lowest effective doses should be prescribed to minimize weight gain.

PMID:38535509 | DOI:10.4088/JCP.23m15008

Medicines (Basel). 2024 Feb 20;11(3):6. doi: 10.3390/medicines11030006.

ABSTRACT

Pharmacogenomics (PGx) can facilitate the transition to patient-specific drug regimens and thus improve their efficacy and reduce toxicity. The aim of this study was to evaluate the overlap of PGx classification for drug absorption, distribution, metabolism, and elimination (ADME)-related genes in the U.S. Food and Drug Administration (FDA) PGx labeling and in the Clinical Pharmacogenetics Implementation Consortium (CPIC) database. FDA-approved drugs and PGx labeling for ADME genes were identified in the CPIC database. Drugs were filtered by their association with ADME (pharmacokinetics)-related genes, PGx FDA labeling class, and CPIC evidence level. FDA PGx labeling was classified as either actionable, informative, testing recommended, or testing required, and varying CPIC evidence levels as either A, B, C, or D. From a total of 442 ADME and non-ADME gene-drug pairs in the CPIC database, 273, 55, and 48 pairs were excluded for lack of FDA labeling, mixed CPIC evidence level provisional classification, and non-ADME gene-drug pairs, respectively. The 66 ADME gene-drug pairs were classified into the following categories: 10 (15%) informative, 49 (74%) actionable, 6 (9%) testing recommended, and 1 (2%) testing required. CYP2D6 was the most prevalent gene among the FDA PGx labeling. From the ADME gene-drug pairs with both FDA and CPIC PGx classification, the majority of the drugs were for depression, cancer, and pain medications. The ADME gene-drug pairs with FDA PGx labeling considerably overlap with CPIC classification; however, a large number of ADME gene-drug pairs have only CPIC evidence levels but not FDA classification. PGx actionable labeling was the most common classification, with CYP2D6 as the most prevalent ADME gene in the FDA PGx labeling. Health professionals can impact therapeutic outcomes via pharmacogenetic interventions by analyzing and reconciling the FDA labels and CPIC database.

PMID:38535119 | DOI:10.3390/medicines11030006

Curr Oncol. 2024 Feb 23;31(3):1195-1206. doi: 10.3390/curroncol31030089.

ABSTRACT

Precision cancer medicine primarily aims to identify individual patient genomic variations and exploit vulnerabilities in cancer cells to select suitable patients for specific drugs. These genomic features are commonly determined by gene sequencing prior to therapy, to identify individuals who would be most responsive. This precision approach in cancer therapeutics remains a powerful tool that benefits a smaller pool of patients, sparing others from unnecessary treatments. A limitation of this approach is that proteins, not genes, are the ultimate effectors of biological functions, and therefore the targets of therapeutics. An additional dimension in precision medicine that considers an individual's cytokine response to cancer therapeutics is proposed. Cytokine responses to therapy are multifactorial and vary among individuals. Thus, precision is dictated by the nature and magnitude of cytokine responses in the tumor microenvironment exposed to therapy. This review highlights cytokine responses as modules for precision medicine in cancer therapy, including potential challenges. For solid tumors, both detectability of cytokines in tissue fluids and their being amenable to routine sensitive analyses could address the difficulty of specimen collection for diagnosis and monitoring. Therefore, in precision cancer medicine, cytokines offer rational targets that can be utilized to enhance the efficacy of cancer therapy.

PMID:38534922 | DOI:10.3390/curroncol31030089