An Evidence-Based Framework for Evaluating Pharmacogenomics Knowledge for Personalized Medicine

Xanthoceras sorbifolium leaves alleviate hyperuricemic nephropathy by inhibiting the PI3K/AKT signaling pathway to regulate uric acid transport

ETHNOPHARMACOLOGICAL RELEVANCE

In China, Xanthoceras sorbifolium Bunge was first documented as "Wen Guan Hua" in the "Jiu Huang Ben Cao" in 1406 A.D. According to the "National Compilation of Chinese Herbal Medicine," X. sorbifolium leaves are sweet and flat in nature and can dispel wind and dampness, suggesting that their extract can be used to treat rheumatoid arthritis. X. sorbifolium Bunge has also been used to treat arteriosclerosis, hyperlipidemia, hypertension, chronic hepatitis, and rheumatism, complications associated with hyperuricemic nephropathy (HN), a condition characterized by kidney damage resulting from high levels of uric acid (UA) in the blood.

AIM OF THE STUDY

The purpose of this study was to investigate the effects and underlying mechanisms of a 70% ethanol extract from X. sorbifolium leaves (EX) in alleviating HN.

MATERIALS AND METHODS

A mouse model of hyperuricemia was established to initially evaluate the hypouricemic effects and determine the effective dose of EX. Phytochemical analyses were conducted using ultra high-performance liquid chromatography and liquid chromatography-mass spectroscopy. The potential key pathways of EX in the alleviation of HN were inferred using network pharmacology and bioinformatics. An HN rat model was then established, and experiments including biomarker detection, western blotting, reverse transcription quantitative polymerase chain reaction, immunohistochemical and Masson's trichrome staining, and transmission electron microscopy were conducted to evaluate the effect of EX on UA transporter expression in vitro.

RESULTS

Network pharmacology and bioinformatics analyses revealed that the phosphoinositide 3-kinase (PI3K)/AKT signaling pathway was the key pathway for the alleviation of HN progression by EX. EX treatment reduced serum biomarkers in HN rats, downregulated the expression of p-PI3K, p-AKT, glucose transporter 9 (GLUT9), urate transporter 1 (URAT1), Collagen I, matrix metalloproteinase (MMP)-2, and MMP-9, and upregulated the expression of ATP binding cassette subfamily G member 2 (ABCG2) to improve renal interstitial fibrosis in HN rats. A high content of both quercitrin and cynaroside were identified in EX; their administration inhibited the increased expression of GLUT9 and URAT1 in damaged HK-2 cells.

CONCLUSION

Our study provides evidence that EX alleviates HN. The potential mechanism underlying this effect may be the regulation of UA transporters, such as GLUT9 and URAT1, by limiting the activation of the PI3K/AKT signaling pathway to improve renal injury.

Influence of CYP2C19 and CYP2D6 on side effects of aripiprazole and risperidone: A systematic review

Variability in hepatic cytochrome P450 (CYP) enzymes such as 2C19 and 2D6 may influence side-effect and efficacy outcomes for antipsychotics. Aripiprazole and risperidone are two commonly prescribed antipsychotics, metabolized primarily through CYP2D6. Here, we aimed to provide an overview of the effect of CYP2C19 and CYP2D6 on side-effects of aripiprazole and risperidone, and expand on existing literature by critically examining methodological issues associated with pharmacogenetic studies. A PRISMA compliant search of six electronic databases (Pubmed, PsychInfo, Embase, Central, Web of Science, and Google Scholar) identified pharmacogenetic studies on aripiprazole and risperidone. 2007 publications were first identified, of which 34 were included. Quality of literature was estimated using Newcastle-Ottowa Quality Assessment Scale (NOS) and revised Cochrane Risk of Bias tool. The average NOS score was 5.8 (range: 3-8) for risperidone literature and 5 for aripiprazole (range: 4-6). All RCTs on aripiprazole were rated as high risk of bias, and four out of six for risperidone literature. Study populations ranged from healthy volunteers to inpatient individuals in psychiatric units and included adult and pediatric samples. All n = 34 studies examined CYP2D6. Only one study genotyped for CYP2C19 and found a positive association with neurological side-effects of risperidone. Most studies did not report any relationship between CYP2D6 and any side-effect outcome. Heterogeneity between and within studies limited the ability to synthesize data and draw definitive conclusions. Studies lacked statistical power due to small sample size, selective genotyping methods, and study design. Large-scale randomized trials with multiple measurements, providing robust evidence on this topic, are suggested.

ABCB1 C1236T, G2677TA and C3435T Genetic Polymorphisms and Antidepressant Response Phenotypes: Results from a Portuguese Major Depressive Disorder Cohort

P-glycoprotein (P-GP) is a transporter molecule expressed on the apical surface of capillary endothelial cells of the Blood-Brain Barrier (BBB), whose activity heavily influences drug distribution, including antidepressants. This transporter is encoded by ABCB1 gene, and genetic variations within ABCB1 gene have been proposed to affect drug efflux and have been previously associated with depression. In this context, we aimed to evaluate the role of C1236T, G2677TA and C3435T ABCB1 genetic polymorphisms in antidepressant treatment phenotypes from a cohort of patients harboring Major Depressive Disorder. Patients enrolled in the study consisted of 80 individuals with Major Depressive Disorder, who took part in a 27-month follow-up study at HML, Portugal. To investigate the correlation between ABCB1 polymorphisms and antidepressant response phenotypes, DNA was extracted from peripheral blood, and C1236T, C3435T and G2677TA polymorphisms were genotyped with TaqMan® SNP Genotyping Assays. Despite the fact that the evaluated polymorphisms (C1236T, C3435T and G2677TA) were not associated with treatment resistant depression, or relapse, we observed that patients carrying TT genotype of the C3435T polymorphism remit earlier than the ones carrying CC or CT genotypes (10.2 weeks vs. 14.9 and 21.3, respectively, p = 0.028, Log-rank test). Since we found an association with C3435T and time to remission, and not to the absence of remission, we suggest that this polymorphism could have an impact on antidepressant drug distribution, and thus influence on the time to remission will occur, without influencing the risk of remission itself.

Potential mechanisms of traditional Chinese medicine in treating insomnia: A network pharmacology, GEO validation, and molecular-docking study

The purpose of this study is to investigate the potential mechanisms of Chinese herbs for the treatment of insomnia using a combination of data mining, network pharmacology, and molecular-docking validation. All the prescriptions for insomnia treated by the academician Qi Wang from 2020 to 2022 were collected. The Ancient and Modern Medical Case Cloud Platform v2.3 was used to identify high-frequency Chinese medicinal herbs and the core prescription. The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were utilized to predict the effective active components and targets of the core herbs. Insomnia-related targets were collected from 4 databases. The intersecting targets were utilized to build a protein-protein interaction network and conduct gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the STRING database, Cytoscape software, and clusterProfiler package. Gene chip data (GSE208668) were obtained from the Gene Expression Omnibus database. The limma package was applied to identify differentially expressed genes (DEGs) between insomnia patients and healthy controls. To create a "transcription factor (TF)-miRNA-mRNA" network, the differentially expressed miRNAs were entered into the TransmiR, FunRich, Targetscan, and miRDB databases. Subsequently, the overlapping targets were validated using the DEGs, and further validations were conducted through molecular docking and molecular dynamics simulations. Among the 117 prescriptions, 65 herbs and a core prescription were identified. Network pharmacology and bioinformatics analysis revealed that active components such as β-sitosterol, stigmasterol, and canadine acted on hub targets, including interleukin-6, caspase-3, and hypoxia-inducible factor-1α. In GSE208668, 6417 DEGs and 7 differentially expressed miRNAs were identified. A "TF-miRNA-mRNA" network was constructed by 4 "TF-miRNA" interaction pairs and 66 "miRNA-mRNA" interaction pairs. Downstream mRNAs exert therapeutic effects on insomnia by regulating circadian rhythm. Molecular-docking analyses demonstrated good docking between core components and hub targets. Molecular dynamics simulation displayed the strong stability of the complex formed by small molecule and target. The core prescription by the academician Qi Wang for treating insomnia, which involves multiple components, targets, and pathways, showed the potential to improve sleep, providing a basis for clinical treatment of insomnia.

H2 antihistamines: May be useful for combination therapies in cancer?

Cancer morbimortality is still a great concern despite advances in research and therapies. Histamine and its receptors' ligands can modulate different biological responses according to the cell type and the receptor subtype involved. Besides the wide variety of histamine functions in normal tissues, diverse roles in the acquisition of hallmarks of cancer such as sustained proliferative signaling, resistance to cell death, angiogenesis, metastasis, altered immunity and modified microenvironment have been described. This review summarizes the present knowledge of the various roles of histamine H2 receptor (H2R) ligands in neoplasias. A bioinformatic analysis of human tumors showed dissimilar results in the expression of the H2R gene according to tumor type when comparing malignant versus normal tissues. As well, the relationship between patients' survival parameters and H2R gene expression levels also varied, signaling important divergences in the role of H2R in neoplastic progression in different cancer types. Revised experimental evidence showed multiple effects of H2R antihistamines on several of the cited hallmarks of cancer. Interventional and retrospective clinical studies evaluated different H2R antihistamines in cancer patients with two main adjuvant uses: improving antitumor efficacy (which includes regulation of immune response) and preventing toxic adverse effects produced by chemo or radiotherapy. While there is a long path to go, research on H2R antihistamines may provide new opportunities for developing more refined combination therapeutic strategies for certain cancer types to improve patients' survival and health-related quality of life.

A Canadian Simulation Model for Major Depressive Disorder: Study Protocol

BACKGROUND

Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD.

METHODS AND ANALYSIS

Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep.

CONCLUSION

SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patient partner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

Determinants of early change in serum creatinine after initiation of dolutegravir-based antiretroviral therapy in South Africa

AIMS

Dolutegravir increases serum creatinine by inhibiting its renal tubular secretion and elimination. We investigated determinants of early changes in serum creatinine in a southern African cohort starting first-line dolutegravir-based antiretroviral therapy (ART).

METHODS

We conducted a secondary analysis of data from participants in a randomized controlled trial of dolutegravir, emtricitabine and tenofovir disoproxil fumarate (TDF) or tenofovir alafenamide fumarate (TAF) (ADVANCE, NCT03122262). We assessed clinical, pharmacokinetic and genetic factors associated with change in serum creatinine from baseline to Week 4 using linear regression models adjusted for age, sex, baseline serum creatinine, HIV-1 RNA concentration, CD4 T-cell count, total body weight and co-trimoxazole use.

RESULTS

We included 689 participants, of whom 470 had pharmacokinetic data and 315 had genetic data. Mean change in serum creatinine was 11.3 (SD 9.9) μmol.L-1. Factors that were positively associated with change in serum creatinine at Week 4 were increased log dolutegravir area under the 24-h concentration-time curve (change in creatinine coefficient [β] = 2.78 μmol.L-1 [95% confidence interval (CI) 0.54, 5.01]), TDF use (β = 2.30 [0.53, 4.06]), male sex (β = 5.20 [2.92, 7.48]), baseline serum creatinine (β = -0.22 [-0.31, -0.12]) and UGT1A1 rs929596 A→G polymorphism with a dominant model (β = -2.33 [-4.49, -0.17]). The latter did not withstand correction for multiple testing.

CONCLUSIONS

Multiple clinical and pharmacokinetic factors were associated with early change in serum creatinine in individuals initiating dolutegravir-based ART. UGT1A1 polymorphisms may play a role, but further research on genetic determinants is needed.

Editorial Commentary: Personalized Anterior Cruciate Ligament Reconstruction and Rehabilitation Mitigate Postoperative Arthrofibrosis: Prevention Is the Best Approach

Arthrofibrosis after anterior cruciate ligament reconstruction can become a major complication requiring surgical intervention. The reported incidence approximates 8% but varies widely (2%-35%) and, as not all patients require surgery, may be underreported. Several risk factors are involved. Female sex, older age, surgery within the first month after injury, and meniscus repair are consistently associated with increased risk. Other factors include graft size and type, concomitant procedures, use of anticoagulants, and genetic factors. By identifying risk factors, we can modify our surgical technique and rehabilitation to meet each patient's needs with fewer complications.

Uncoupling of Cytochrome P450 2B6 and stimulation of reactive oxygen species production in pharmacogenomic alleles affected by interethnic variability

Cytochrome P450 mediated substrate metabolism is generally characterized by the formation of reactive intermediates. In vitro and in vivo reaction uncoupling, results in the accumulation and dissociation of reactive intermediates, leading to increased ROS formation. The susceptibility towards uncoupling and altered metabolic activity is partly modulated by pharmacogenomic alleles resulting in amino acid substitutions. A large variability in the prevalence of these alleles has been demonstrated in CYP2B6, with some being predominantly unique to African populations. The aim of this study is to characterize the uncoupling potential of recombinant CYP2B6*1, CYP2B6*6 and CYP2B6*34 metabolism of specific substrates. Therefore, functional effects of these alterations on enzyme activity were determined by quantification of bupropion, efavirenz and ketamine biotransformation using HPLC-MS/MS. Determination of H2O2 levels was performed by the AmplexRed/horseradish peroxidase assay. Our studies of the amino acid substitutions Q172H, K262R and R487S revealed an exclusive use of the peroxide shunt for the metabolism of bupropion and ketamine by CYP2B6*K262R. Ketamine was also identified as a trigger for the peroxide shunt in CYP2B6*1 and all variants. Concurrently, ketamine acted as an uncoupler for all enzymes. We further showed that the expressed CYP2B6*34 allele results in the highest H2O2 formation. We therefore conclude that the reaction uncoupling and peroxide shunt are directly linked and can be substrate specifically induced with K262R carriers being most likely to use the peroxide shunt and R487S carrier being most prone to reaction uncoupling. This elucidates the functional diversity of pharmacogenomics in drug metabolism and safety.

Polypharmacy as Formal Training and a Model of Practice

Traditional definitions of polypharmacy may largely not account for the market proliferation of herbal and dietary supplements, cannabis products, or incorporate the new science of pharmacogenomics (PGx). Polypharmacy is encountered by most pharmacists providing patient care in many settings. The "polypharmacist" can assist patients and providers with solving medication-related problems (MRPs) in this new and challenging environment of supplements and cannabis products by utilizing traditional pharmacology and pharmacokinetic principles, including PGx, broadly across many medical disciplines. One may encounter polypharmacy more in the geriatric population, though in an age of supplements and cannabis proliferation, polypharmacy is increasingly being encountered at younger ages. Not only is polypharmacy training at best fragmented in pharmacy curricula, but it may also not account for the above-mentioned products that may use the same metabolic pathways to increase drug interactions and adverse drug reactions (ADRs) regarding prescription medications. Polypharmacy being more formally prioritized in pharmacist training may better prepare pharmacists for commonly encountered polypharmacy and can be a viable model of practice.

A systematic review and meta-analysis of the impacts of germline pharmacogenomics on severe toxicity and symptom burden in adult patients with cancer

The clinical application of Pharmacogenomics (PGx) has improved patient safety. However, comprehensive PGx testing has not been widely adopted in clinical practice, and significant opportunities exist to further optimize PGx in cancer care. This systematic review and meta-analysis aim to evaluate the safety outcomes of reported PGx-guided strategies (Analysis 1) and identify well-studied emerging pharmacogenomic variants that predict severe toxicity and symptom burden (Analysis 2) in patients with cancer. We searched MEDLINE, EMBASE, CENTRAL, clinicaltrials.gov, and International Clinical Trials Registry Platform from inception to January 2023 for clinical trials or comparative studies evaluating PGx strategies or unconfirmed pharmacogenomic variants. The primary outcomes were severe adverse events (SAE; ≥ grade 3) or symptom burden with pain and vomiting as defined by trial protocols and assessed by trial investigators. We calculated pooled overall relative risk (RR) and 95% confidence interval (95%CI) using random effects models. PROSPERO, registration number CRD42023421277. Of 6811 records screened, six studies were included for Analysis 1, 55 studies for Analysis 2. Meta-analysis 1 (five trials, 1892 participants) showed a lower absolute incidence of SAEs with PGx-guided strategies compared to usual therapy, 16.1% versus 34.0% (RR = 0.72, 95%CI 0.57-0.91, p = 0.006, I2 = 34%). Meta-analyses 2 identified nine medicine(class)-variant pairs of interest across the TYMS, ABCB1, UGT1A1, HLA-DRB1, and OPRM1 genes. Application of PGx significantly reduced rates of SAEs in patients with cancer. Emergent medicine-variant pairs herald further research into the expansion and optimization of PGx to improve systemic anti-cancer and supportive care medicine safety and efficacy.

Advances in machine intelligence-driven virtual screening approaches for big-data

Virtual screening (VS) is an integral and ever-evolving domain of drug discovery framework. The VS is traditionally classified into ligand-based (LB) and structure-based (SB) approaches. Machine intelligence or artificial intelligence has wide applications in the drug discovery domain to reduce time and resource consumption. In combination with machine intelligence algorithms, VS has emerged into revolutionarily progressive technology that learns within robust decision orders for data curation and hit molecule screening from large VS libraries in minutes or hours. The exponential growth of chemical and biological data has evolved as "big-data" in the public domain demands modern and advanced machine intelligence-driven VS approaches to screen hit molecules from ultra-large VS libraries. VS has evolved from an individual approach (LB and SB) to integrated LB and SB techniques to explore various ligand and target protein aspects for the enhanced rate of appropriate hit molecule prediction. Current trends demand advanced and intelligent solutions to handle enormous data in drug discovery domain for screening and optimizing hits or lead with fewer or no false positive hits. Following the big-data drift and tremendous growth in computational architecture, we presented this review. Here, the article categorized and emphasized individual VS techniques, detailed literature presented for machine learning implementation, modern machine intelligence approaches, and limitations and deliberated the future prospects.

Integrated Analysis of Genomic and Genome-Wide Association Studies Identified Candidate Genes for Nutrigenetic Studies in Flavonoids and Vascular Health: Path to Precision Nutrition for (Poly)phenols

Flavonoids exert vasculoprotective effects in humans, but interindividual variability in their action has also been reported. This study aims to identify genes that are associated with vascular health effects of flavonoids and whose polymorphisms could explain interindividual variability in response to their intake. Applying the predetermined literature search criteria, we identified five human intervention studies reporting positive effects of flavonoids on vascular function together with global genomic changes analyzed using microarray methods. Genes involved in vascular dysfunction were identified from genome-wide association studies (GWAS). By extracting data from the eligible human intervention studies, we obtained 5807 differentially expressed genes (DEGs). The number of identified upstream regulators (URs) varied across the studies, from 227 to 1407. The search of the GWAS Catalog revealed 493 genes associated with vascular dysfunction. An integrative analysis of transcriptomic data with GWAS genes identified 106 candidate DEGs and 42 candidate URs, while subsequent functional analyses and a search of the literature identified 20 top priority candidate genes: ALDH2, APOE, CAPZA1, CYP11B2, GNA13, IL6, IRF5, LDLR, LPL, LSP1, MKNK1, MMP3, MTHFR, MYO6, NCR3, PPARG, SARM1, TCF20, TCF7L2, and TNF. In conclusion, this integrated analysis identifies important genes to design future nutrigenetic studies for development of precision nutrition for polyphenols.

Genetic polymorphisms and clinical parameters associated with renal toxicity in Thai hematologic malignancy patients receiving high dose methotrexate

High-dose methotrexate (HD-MTX) is a widely used chemotherapy regimen for hematologic malignancies such as lymphomas and acute lymphoblastic leukemia, but its use can lead to adverse effects, including acute kidney injury (AKI), impaired liver function, and mucositis, causing extended hospital stays and delayed subsequent chemotherapy. Our study aimed to investigate the predictive factors for renal toxicities associated with HD-MTX in Thai patients undergoing treatment for hematologic malignancies. We enrolled 80 patients who underwent MTX-containing regimens, analyzing 132 chemotherapy cycles. The most common disease was primary central nervous system lymphoma (33%). Genetic polymorphisms were examined using the MassARRAY® system, identifying 42 polymorphisms in 25 genes. Serum creatinine and MTX levels were measured 24 and 48 h after MTX administration. For the primary outcome, we found that the allele A of MTRR rs1801394 was significantly related to renal toxicity (odds ratio 2.084 (1.001-4.301), p-value 0.047). Patients who exceeded the MTX threshold levels at 24 h after the dose had a significantly higher risk of renal toxicity (OR (95%CI) = 6.818 (2.350-19.782), p < 0.001). Multivariate logistic regression analysis with a generalized estimated equation revealed hypertension and age as independent predictors of increased MTX levels at 24 h after the given dose.

Screening of anti-melanoma compounds from Morus alba L.: Sanggenon C promotes melanoma cell apoptosis by disrupting intracellular Ca2+ homeostasis

ETHNOPHARMACOLOGICAL RELEVANCE

Morus alba L. is a widespread plant that has long been considered to have remarkable medical values, including anti-inflammation in Traditional Chinese Medicine (TCM). The components of Morus Alba L. constituents have been extensively studied and have been shown to have high prospects for cancer therapy. However, limited investigations have been done on the bioactive compounds in Morus alba L.

AIM OF THE STUDY

This study aimed to systematically examine the anticancer properties of 28 commercially available compounds from Morus alba L. against melanoma cells in vitro. Additionally, the anticancer mechanisms of the bioactive compound exhibiting the most significant potential were further studied.

MATERIALS AND METHODS

The anti-proliferative effects of Morus alba L.-derived compounds on melanoma cells were determined by colony formation assays. Their effects on cell viability and apoptosis were determined using the CCK8 assay and flow cytometry, respectively. The binding affinity of identified Morus alba L. compounds with anticancer activities towards melanoma targets was analyzed via molecular docking. The molecular mechanism of Sanggenon C was explored using soft agar assays, EdU incorporation assays, flow cytometry, western blotting, transcriptome analysis, and xenograft assays.

RESULTS

Based on colony formation assays, 11 compounds at 20 μM significantly inhibited colony growth on a panel of melanoma cells. These compounds displayed IC50 values (half maximal inhibitory concentrations) ranging from 5 μM to 30 μM. Importantly, six compounds were identified as novel anti-melanoma agents, including Sanggenon C, 3'-Geranyl-3-prenyl-2',4',5,7-tetrahydroxyflavone, Moracin P, Moracin O, Kuwanon A, and Kuwanon E. Among them, Sanggenon C showed the most potent effects, with an IC50 of about 5 μM, significantly reducing proliferation and inducing apoptosis in melanoma cells. Based on the xenograft model assay, Sanggenon C significantly inhibited melanoma cell proliferation in vivo. Sanggenon C triggered ER stress in a dose-dependent manner, which further disrupted cellular calcium ion (Ca2+) homeostasis. The Ca2+ chelator BAPTA partially restored cell apoptosis induced by Sanggenon C, confirming that Ca2+ signaling contributed to the anticancer activity of Sanggenon C against melanoma.

CONCLUSIONS

In our study, 11 compounds demonstrated anti-melanoma properties. Notably, Sanggenon C was found to promote apoptosis by disrupting the intracellular calcium homeostasis in melanoma cells. This study provides valuable information for the future development of novel cancer therapeutic agents from Morus alba L.

Improving single nucleotide polymorphisms genotyping accuracy for dihydropyrimidine dehydrogenase testing in pharmacogenetics

Fluoropyrimidines, crucial in cancer treatment, often cause toxicity concerns even at standard doses. Toxic accumulation of fluoropyrimidine metabolites, culminating in adverse effects, can stem from impaired dihydropyrimidine dehydrogenase (DPYD) enzymatic function. Emerging evidence underscores the role of single nucleotide polymorphisms (SNPs) in DPYD gene, capable of inducing DPYD activity deficiency. Consequently, DPYD genotyping's importance is on the rise in clinical practice before initiating fluoropyrimidine treatment. Although polymerase chain reaction (PCR) followed by Sanger sequencing (SS; PCR-SS) is a prevalent method for DPYD genotyping, it may encounter limitations. In this context, there is reported a case in which a routine PCR-SS approach for genotyping DPYD SNP rs55886062 failed in a proband of African descent. The Clinical Pharmacogenetics Implementation Consortium (CPIC) categorizes the guanine (G) allele of this SNP as non-functional. The enforcement of whole genome sequencing (WGS) approach led to the identification of two adenine (A) insertions near the PCR primers annealing regions in the proband, responsible for a sequence frameshift and a genotyping error for rs55886062. These SNPs (rs145228578, 1-97981199-T-TA and rs141050810, 1-97981622-G-GA) were extremely rare in non-Finnish Europeans (0.05%) but prevalent in African populations (16%). Although limited evidence was available for these SNPs, they were catalogued as benign variants in public databases. Notably, these two SNPs exhibited a high linkage disequilibrium [LD; squared correlation coefficient (R2) = 0.98]. These findings highlighted the importance to consider the prevalence of genetic variants within diverse ethnic populations when designing primers and probes for SNP genotyping in pharmacogenetic testing. This preventive measure is essential to avoid sequence frameshifts or primer misalignments arising from SNP occurrences in the genome, which can compromise PCR-SS and lead to genotyping failures. Furthermore, this case highlights the significance of exploring alternative genotyping approaches, like WGS, when confronted with challenges associated with conventional techniques.

Contradiction in Star-Allele Nomenclature of Pharmacogenes between Common Haplotypes and Rare Variants

The nomenclature of star alleles has been widely used in pharmacogenomics to enhance treatment outcomes, predict drug response variability, and reduce adverse reactions. However, the discovery of numerous rare functional variants through genome sequencing introduces complexities into the star-allele system. This study aimed to assess the nature and impact of the rapid discovery of numerous rare functional variants in the traditional haplotype-based star-allele system. We developed a new method to construct haplogroups, representing a common ancestry structure, by iteratively excluding rare and functional variants of the 25 representative pharmacogenes using the 2504 genomes from the 1000 Genomes Project. In total, 192 haplogroups and 288 star alleles were identified, with an average of 7.68 ± 4.2 cross-ethnic haplogroups per gene. Most of the haplogroups (70.8%, 136/192) were highly aligned with their corresponding classical star alleles (VI = 1.86 ± 0.78), exhibiting higher genetic diversity than the star alleles. Approximately 41.3% (N = 119) of the star alleles in the 2504 genomes did not belong to any of the haplogroups, and most of them (91.3%, 105/116) were determined by a single variant according to the allele-definition table provided by CPIC. These functional single variants had low allele frequency (MAF < 1%), high evolutionary conservation, and variant deleteriousness, which suggests significant negative selection. It is suggested that the traditional haplotype-based naming system for pharmacogenetic star alleles now needs to be adjusted by balancing both traditional haplotyping and newly emerging variant-sequencing approaches to reduce naming complexity.

Tissue-specific atlas of trans-models for gene regulation elucidates complex regulation patterns

BACKGROUND

Deciphering gene regulation is essential for understanding the underlying mechanisms of healthy and disease states. While the regulatory networks formed by transcription factors (TFs) and their target genes has been mostly studied with relation to cis effects such as in TF binding sites, we focused on trans effects of TFs on the expression of their transcribed genes and their potential mechanisms.

RESULTS

We provide a comprehensive tissue-specific atlas, spanning 49 tissues of TF variations affecting gene expression through computational models considering two potential mechanisms, including combinatorial regulation by the expression of the TFs, and by genetic variants within the TF. We demonstrate that similarity between tissues based on our discovered genes corresponds to other types of tissue similarity. The genes affected by complex TF regulation, and their modelled TFs, were highly enriched for pharmacogenomic functions, while the TFs themselves were also enriched in several cancer and metabolic pathways. Additionally, genes that appear in multiple clusters are enriched for regulation of immune system while tissue clusters include cluster-specific genes that are enriched for biological functions and diseases previously associated with the tissues forming the cluster. Finally, our atlas exposes multilevel regulation across multiple tissues, where TFs regulate other TFs through the two tested mechanisms.

CONCLUSIONS

Our tissue-specific atlas provides hierarchical tissue-specific trans genetic regulations that can be further studied for association with human phenotypes.

Innovative target mining stratagems to navigate drug repurposing endeavours

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.

Network Pharmacology Analysis of Liquid-Cultured Armillaria ostoyae Mycelial Metabolites and Their Molecular Mechanism of Action against Gastric Cancer

Armillaria sp. are traditional edible medicinal mushrooms with various health functions; however, the relationship between their composition and efficacy has not yet been determined. Here, the ethanol extract of liquid-cultured Armillaria ostoyae mycelia (AOME), a pure wild Armillaria sp. strain, was analyzed using UHPLC-QTOF/MS, network pharmacology, and molecular docking techniques. The obtained extract affects various metabolic pathways, such as JAK/STAT and PI3K/AKT. The extract also contains important compounds such as 4-(dimethylamino)-N-[7-(hydroxyamino)-7-oxoheptyl] benzamide, isoliquiritigenin, and 7-hydroxycoumarin. Moreover, the extract targets key proteins, including EGFR, SCR, and IL6, to suppress the progression of gastric cancer, thereby synergistically inhibiting cancer development. The molecular docking analyses indicated that the main compounds stably bind to the target proteins. The final cell culture experimental data showed that the ethanol extract inhibited MGC-803 gastric cancer cells. In summary, our research revealed the beneficial components of AOME for treating gastric cancer and its associated molecular pathways. However, further research is needed to confirm its effectiveness and safety in gastric cancer patients.

Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications

Electronic health records (EHRs) coupled with large-scale biobanks offer great promises to unravel the genetic underpinnings of treatment efficacy. However, medication-induced biomarker trajectories stemming from such records remain poorly studied. Here, we extract clinical and medication prescription data from EHRs and conduct GWAS and rare variant burden tests in the UK Biobank (discovery) and the All of Us program (replication) on ten cardiometabolic drug response outcomes including lipid response to statins, HbA1c response to metformin and blood pressure response to antihypertensives (N = 740-26,669). Our findings at genome-wide significance level recover previously reported pharmacogenetic signals and also include novel associations for lipid response to statins (N = 26,669) near LDLR and ZNF800. Importantly, these associations are treatment-specific and not associated with biomarker progression in medication-naive individuals. Furthermore, we demonstrate that individuals with higher genetically determined low-density and total cholesterol baseline levels experience increased absolute, albeit lower relative biomarker reduction following statin treatment. In summary, we systematically investigated the common and rare pharmacogenetic contribution to cardiometabolic drug response phenotypes in over 50,000 UK Biobank and All of Us participants with EHR and identified clinically relevant genetic predictors for improved personalized treatment strategies.

Mulberry Leaf Compounds and Gut Microbiota in Alzheimer's Disease and Diabetes: A Study Using Network Pharmacology, Molecular Dynamics Simulation, and Cellular Assays

Recently, studies have reported a correlation that individuals with diabetes show an increased risk of developing Alzheimer's disease (AD). Mulberry leaves, serving as both a traditional medicinal herb and a food source, exhibit significant hypoglycemic and antioxidative properties. The flavonoid compounds in mulberry leaf offer therapeutic effects for relieving diabetic symptoms and providing neuroprotection. However, the mechanisms of this effect have not been fully elucidated. This investigation aimed to investigate the combined effects of specific mulberry leaf flavonoids (kaempferol, quercetin, rhamnocitrin, tetramethoxyluteolin, and norartocarpetin) on both type 2 diabetes mellitus (T2DM) and AD. Additionally, the role of the gut microbiota in these two diseases' treatment was studied. Using network pharmacology, we investigated the potential mechanisms of flavonoids in mulberry leaves, combined with gut microbiota, in combating AD and T2DM. In addition, we identified protein tyrosine phosphatase 1B (PTP1B) as a key target for kaempferol in these two diseases. Molecular docking and molecular dynamics simulations showed that kaempferol has the potential to inhibit PTP1B for indirect treatment of AD, which was proven by measuring the IC50 of kaempferol (279.23 μM). The cell experiment also confirmed the dose-dependent effect of kaempferol on the phosphorylation of total cellular protein in HepG2 cells. This research supports the concept of food-medicine homology and broadens the range of medical treatments for diabetes and AD, highlighting the prospect of integrating traditional herbal remedies with modern medical research.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction of CYP2C9, HLA-A and HLA-B with anti-epileptic drugs

By developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy, the Dutch Pharmacogenetics Working Group (DPWG) aims to advance the implementation of pharmacogenetics (PGx). This guideline outlines the gene-drug interaction of CYP2C9 and HLA-B with phenytoin, HLA-A and HLA-B with carbamazepine and HLA-B with oxcarbazepine and lamotrigine. A systematic review was performed and pharmacotherapeutic recommendations were developed. For CYP2C9 intermediate and poor metabolisers, the DPWG recommends lowering the daily dose of phenytoin and adjust based on effect and serum concentration after 7-10 days. For HLA-B*15:02 carriers, the risk of severe cutaneous adverse events associated with phenytoin, carbamazepine, oxcarbazepine, and lamotrigine is strongly increased. For carbamazepine, this risk is also increased in HLA-B*15:11 and HLA-A*31:01 carriers. For HLA-B*15:02, HLA-B*15:11 and HLA-A*31:01 positive patients, the DPWG recommends choosing an alternative anti-epileptic drug. If not possible, it is recommended to advise the patient to report any rash while using carbamazepine, lamotrigine, oxcarbazepine or phenytoin immediately. Carbamazepine should not be used in an HLA-B*15:02 positive patient. DPWG considers CYP2C9 genotyping before the start of phenytoin "essential" for toxicity prevention. For patients with an ancestry in which the abovementioned HLA-alleles are prevalent, the DPWG considers HLA-B*15:02 genotyping before the start of carbamazepine, phenytoin, oxcarbazepine, and lamotrigine "beneficial", as well as genotyping for HLA-B*15:11 and HLA-A*31:01 before initiating carbamazepine.

Frequencies of CYP2C19 and CYP2D6 gene variants in a German inpatient sample with mood and anxiety disorders

OBJECTIVES

Previous results demonstrated that CYP2D6 and CYP2C19 gene variants affect serum concentrations of antidepressants. We implemented a PGx service determining gene variants in CYP2D6 and CYP2C19 in our clinical routine care and report on our first patient cohort.

METHODS

We analysed CYP2D6 and CYP2C19 allele, genotype, and phenotype frequencies, and actionable pharmacogenetic variants in this German psychiatric inpatient cohort. Two-tailed z-test was used to investigate for differences in CYP2D6 and CYP2C19 phenotypes and actionable/non-actionable genetic variant frequencies between our cohort and reference cohorts.

RESULTS

Out of the 154 patients included, 44.8% of patients were classified as CYP2D6 normal metabolizer, 38.3% as intermediate metabolizers, 8.4% as poor metabolizers, and 2.6% as ultrarapid metabolizers. As for CYP2C19, 40.9% of patients were classified as normal metabolizers, 19.5% as intermediate metabolizers, 2.6% as poor metabolizers, 31.2% as rapid metabolizers, and 5.8% as ultrarapid metabolizers. Approximately, 80% of patients had at least one actionable PGx variant.

CONCLUSION

There is a high prevalence of actionable PGx variants in psychiatric inpatients which may affect treatment response. Physicians should refer to PGx-informed dosing guidelines in carriers of these variants. Pre-emptive PGx testing in general may facilitate precision medicine also for other drugs metabolised by CYP2D6 and/or CYP2C19.

Machine Learning-Based Prediction of Escitalopram and Sertraline Side Effects With Pharmacokinetic Data in Children and Adolescents

Selective serotonin reuptake inhibitors (SSRI) are the first-line pharmacologic treatment for anxiety and depressive disorders in children and adolescents. Many patients experience side effects that are difficult to predict, are associated with significant morbidity, and can lead to treatment discontinuation. Variation in SSRI pharmacokinetics could explain differences in treatment outcomes, but this is often overlooked as a contributing factor to SSRI tolerability. This study evaluated data from 288 escitalopram-treated and 255 sertraline-treated patients ≤ 18 years old to develop machine learning models to predict side effects using electronic health record data and Bayesian estimated pharmacokinetic parameters. Trained on a combined cohort of escitalopram- and sertraline-treated patients, a penalized logistic regression model achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% confidence interval (CI): 0.66-0.88), with 0.69 sensitivity (95% CI: 0.54-0.86), and 0.82 specificity (95% CI: 0.72-0.87). Medication exposure, clearance, and time since the last dose increase were among the top features. Individual escitalopram and sertraline models yielded an AUROC of 0.73 (95% CI: 0.65-0.81) and 0.64 (95% CI: 0.55-0.73), respectively. Post hoc analysis showed sertraline-treated patients with activation side effects had slower clearance (P = 0.01), which attenuated after accounting for age (P = 0.055). These findings raise the possibility that a machine learning approach leveraging pharmacokinetic data can predict escitalopram- and sertraline-related side effects. Clinicians may consider differences in medication pharmacokinetics, especially during dose titration and as opposed to relying on dose, when managing side effects. With further validation, application of this model to predict side effects may enhance SSRI precision dosing strategies in youth.

Utilizing Pharmacogenomics Results to Guide Antidepressant Selection: A Case Report

The case discussion demonstrates the benefit of using Pharmacogenomic (PGx) results to aid in the selection of antidepressant therapy and improve response to treatment. Nearly half of patients diagnosed with major depressive disorder fail initial therapy and may require multiple trials of antidepressants. Genetic variation in several metabolic enzymes contribute to the variable response to antidepressant therapy. PGx testing provides an opportunity to inform antidepressant selection and optimize therapeutic outcomes, while minimizing risk of adverse events. A 79-year-old female who had been experiencing a suboptimal response to escitalopram following dose escalation over a period of three years was referred for a PGx consultation. A clinical pharmacist assessed significant drug-gene, drug-drug, and drug-drug-gene interactions, and relevant clinical information to recommend alternative antidepressant therapy, which resulted in mood improvement.

Pain Management in Burn Patients: Pharmacologic Management of Acute and Chronic Pain

Burn-related pain can contribute to decreased quality of life and long-term morbidity, limiting functional recovery. Burn-related pain should be assessed first by chronicity (acute or chronic), followed by type (nociceptive, neuropathic, nociplastic), to guide multimodal pharmacologic management in a stepwise algorithm approach. Combination therapies increase the efficacy and reduce toxicity by offering a multimodal approach that targets different receptors in the peripheral nervous system and central nervous system. When multimodal pharmacologic management is ineffective, etiologies of burn-related pain amenable to surgical interventions must be considered. It is important to know when to refer a patient to pain management.

Pharmacogenetic considerations in therapy with novel antiplatelet and anticoagulant agents

Antiplatelets and anticoagulants are extensively used in cardiovascular medicine for the prevention and treatment of thrombosis in the venous and arterial circulations. Wide inter-individual variability has been observed in response to antiplatelets and anticoagulants, which triggered researchers to investigate the genetic basis of this variability. Data from extensive pharmacogenetic studies pointed to strong evidence of association between polymorphisms in candidate genes and the pharmacokinetics and pharmacodynamic action and clinical response of the antiplatelets clopidogrel and the anticoagulant warfarin. In this review, we conducted an extensive search on Medline for the time period of 2009-2023. We also searched the PharmGKB website for levels of evidence of variant-drug combinations and for drug labels and clinical guidelines. We focus on the pharmacogenetics of novel antiplatelets and anticoagulants while excluding acetylsalicylic acid, warfarin and heparins, and discuss the current knowledge with emphasis on the level of evidence.

The therapeutic landscape for COVID-19 and post-COVID-19 medications from genetic profiling of the Vietnamese population and a predictive model of drug-drug interaction for comorbid COVID-19 patients

Despite the raised awareness of the role of pharmacogenomic (PGx) in personalized medicines for COVID-19, data for COVID-19 drugs is extremely scarce and not even a publication on this topic for post-COVID-19 medications to date. In the current study, we investigated the genetic variations associated with COVID-19 and post-COVID-19 therapies by using whole genome sequencing data of the 1000 Vietnamese Genomes Project (1KVG) in comparison with other populations retrieved from the 1000 Genomes Project Phase 3 (1KGP3) and the Genome Aggregation Database (gnomAD). Moreover, we also evaluated the risk of drug interactions in comorbid COVID-19 and post-COVID-19 patients based on pharmacogenomic profiles of drugs using a computational approach. For COVID-19 therapies, variants related to the response of two causal treatment agents (tolicizumab and ritonavir) and antithrombotic drugs are common in the Vietnamese cohort. Regarding post-COVID-19, drugs for mental manipulations possess the highest number of clinical annotated variants carried by Vietnamese individuals. Among the superpopulations, East Asian populations shared the most similar genetic structure with the Vietnamese population, whereas the African population showed the most difference. Comorbid patients are at an increased drug-drug interaction (DDI) risk when suffering from COVID-19 and after recovering as well due to a large number of potential DDIs which have been identified. Our results presented the population-specific understanding of the pharmacogenomic aspect of COVID-19 and post-COVID-19 therapy to optimize therapeutic outcomes and promote personalized medicine strategy. We also partly clarified the higher risk in COVID-19 patients with underlying conditions by assessing the potential drug interactions.

Very important pharmacogenetic variants landscape and potential clinical relevance in the Zhuang population from Yunnan province

The gradual evolution of pharmacogenomics has shed light on the genetic basis for inter-individual drug response variations across diverse populations. This study aimed to identify pharmacogenomic variants that differ in Zhuang population compared with other populations and investigate their potential clinical relevance in gene-drug and genotypic-phenotypic associations. A total of 48 variants from 24 genes were genotyped in 200 Zhuang subjects using the Agena MassARRAY platform. The allele frequencies and genotype distribution data of 26 populations were obtained from the 1000 Genomes Project, followed by a comparison and statistical analysis. After Bonferroni correction, significant differences in genotype frequencies were observed of CYP3A5 (rs776746), ACE (rs4291), KCNH2 (rs1805123), and CYP2D6 (rs1065852) between the Zhuang population and the other 26 populations. It was also found that the Chinese Dai in Xishuangbanna, China, Han Chinese in Beijing, China, and Southern Han Chinese, China showed least deviation from the Zhuang population. The Esan in Nigeria, Gambian in Western Division, The Gambia, and Yoruba in Ibadan, Nigeria exhibited the largest differences. This was also proved by structural analysis, Fst analysis and phylogenetic tree. Furthermore, these differential variants may be associated with the pharmacological efficacy and toxicity of Captopril, Amlodipine, Lisinopril, metoclopramide, and alpha-hydroxymetoprolol in the Zhuang population. Our study has filled the gap of pharmacogenomic information in the Zhuang population and has provided a theoretical framework for the secure administration of drugs in the Zhuang population.

Development of quantitative high-throughput screening assays to identify, validate, and optimize small-molecule stabilizers of misfolded β-glucocerebrosidase with therapeutic potential for Gaucher disease and Parkinson's disease

Glucocerebrosidase (GCase) is implicated in both a rare, monogenic disorder (Gaucher disease, GD) and a common, multifactorial condition (Parkinson's disease); hence, it is an urgent therapeutic target. To identify correctors of severe protein misfolding and trafficking obstruction manifested by the pathogenic L444P-variant of GCase, we developed a suite of quantitative, high-throughput, cell-based assays. First, we labeled GCase with a small pro-luminescent HiBiT peptide reporter tag, enabling quantitation of protein stabilization in cells while faithfully maintaining target biology. TALEN-based gene editing allowed for stable integration of a single HiBiT-GBA1 transgene into an intragenic safe-harbor locus in GBA1-knockout H4 (neuroglioma) cells. This GD cell model was amenable to lead discovery via titration-based quantitative high-throughput screening and lead optimization via structure-activity relationships. A primary screen of 10,779 compounds from the NCATS bioactive collections identified 140 stabilizers of HiBiT-GCase-L444P, including both pharmacological chaperones (ambroxol and non-inhibitory chaperone NCGC326) and proteostasis regulators (panobinostat, trans-ISRIB, and pladienolide B). Two complementary high-content imaging-based assays were deployed to triage hits: the fluorescence-quenched substrate LysoFix-GBA captured functional lysosomal GCase activity, while an immunofluorescence assay featuring antibody hGCase-1/23 provided direct visualization of GCase lysosomal translocation. NCGC326 was active in both secondary assays and completely reversed pathological glucosylsphingosine accumulation. Finally, we tested the concept of combination therapy, by demonstrating synergistic actions of NCGC326 with proteostasis regulators in enhancing GCase-L444P levels. Looking forward, these physiologically-relevant assays can facilitate the identification, pharmacological validation, and medicinal chemistry optimization of new chemical matter targeting GCase, ultimately leading to a viable therapeutic for two protein-misfolding diseases.

Integrative network analysis of differentially methylated regions to study the impact of gestational weight gain on maternal metabolism and fetal-neonatal growth

Integrative network analysis (INA) is important for identifying gene modules or epigenetically regulated molecular pathways in diseases. This study evaluated the effect of excessive gestational weight gain (EGWG) on INA of differentially methylated regions, maternal metabolism and offspring growth. Brazilian women from "The Araraquara Cohort Study" with adequate pre-pregnancy body mass index were divided into EGWG (n=30) versus adequate gestational weight gain (AGWG, n=45) groups. The methylome analysis was performed on maternal blood using the Illumina MethylationEPIC BeadChip. Fetal-neonatal growth was assessed by ultrasound and anthropometry, respectively. Maternal lipid and glycemic profiles were investigated. Maternal triglycerides-TG (p=0.030) and total cholesterol (p=0.014); fetus occipito-frontal diameter (p=0.005); neonate head circumference-HC (p=0.016) and thoracic perimeter (p=0.020) were greater in the EGWG compared to the AGWG group. Multiple linear regression analysis showed that maternal DNA methylation was associated with maternal TG and fasting insulin, fetal abdominal circumference, and fetal and neonate HC. The DMRs studied were enriched in 142 biological processes, 21 molecular functions,and 17 cellular components with terms directed for the fatty acids metabolism. Three DMGMs were identified:COL3A1, ITGA4 and KLRK1. INA targeted chronic diseases and maternal metabolism contributing to an epigenetic understanding of the involvement of GWG in maternal metabolism and fetal-neonatal growth.

Unveiling Anti-Diabetic Potential of Baicalin and Baicalein from Baikal Skullcap: LC-MS, In Silico, and In Vitro Studies

Type 2 diabetes mellitus (T2DM) is marked by persistent hyperglycemia, insulin resistance, and pancreatic β-cell dysfunction, imposing substantial health burdens and elevating the risk of systemic complications and cardiovascular diseases. While the pathogenesis of diabetes remains elusive, a cyclical relationship between insulin resistance and inflammation is acknowledged, wherein inflammation exacerbates insulin resistance, perpetuating a deleterious cycle. Consequently, anti-inflammatory interventions offer a therapeutic avenue for T2DM management. In this study, a herb called Baikal skullcap, renowned for its repertoire of bioactive compounds with anti-inflammatory potential, is posited as a promising source for novel T2DM therapeutic strategies. Our study probed the anti-diabetic properties of compounds from Baikal skullcap via network pharmacology, molecular docking, and cellular assays, concentrating on their dual modulatory effects on diabetes through Protein Tyrosine Phosphatase 1B (PTP1B) enzyme inhibition and anti-inflammatory actions. We identified the major compounds in Baikal skullcap using liquid chromatography-mass spectrometry (LC-MS), highlighting six flavonoids, including the well-studied baicalein, as potent inhibitors of PTP1B. Furthermore, cellular experiments revealed that baicalin and baicalein exhibited enhanced anti-inflammatory responses compared to the active constituents of licorice, a known anti-inflammatory agent in TCM. Our findings confirmed that baicalin and baicalein mitigate diabetes via two distinct pathways: PTP1B inhibition and anti-inflammatory effects. Additionally, we have identified six flavonoid molecules with substantial potential for drug development, thereby augmenting the T2DM pharmacotherapeutic arsenal and promoting the integration of herb-derived treatments into modern pharmacology.

Case report: Avoiding intolerance to antipsychotics through a personalized treatment approach based on pharmacogenetics

Introduction

The standard approach to treatment in psychiatry is known as "treatment as usual" (TAU), in which the same types of treatment are administered to a group of patients. TAU often requires numerous dose adjustments and medication changes due to ineffectiveness and/or the occurrence of adverse drug reactions (ADRs). This process is not only time-consuming but also costly. Antipsychotic medications are commonly used to treat various psychiatric disorders such as schizophrenia and mood disorders. Some of the inter-individual differences in efficacy and ADRs observed in psychopharmacotherapy can be explained by genetic variability in the pharmacokinetics and pharmacodynamics of antipsychotics. A better understanding of (in)efficacy and possible ADRs can be achieved by pharmacogenetic analysis of genes involved in the metabolism of antipsychotics. Most psychotropic drugs are metabolized by genetically variable CYP2D6, CYP1A2, CYP3A4, and CYP2C19 enzymes. To demonstrate the utility of pharmacogenetic testing for tailoring antipsychotic treatment, in this paper, we present the case of a patient in whom a pharmacogenetic approach remarkably altered an otherwise intolerant or ineffective conventional TAU with antipsychotics.

Methods

In this case report, we present a 60-year-old patient with psychotic symptoms who suffered from severe extrapyramidal symptoms and a malignant neuroleptic syndrome during treatment with risperidone, fluphenazine, aripiprazole, brexpiprazole, and olanzapine. Therefore, we performed a pharmacogenetic analysis by genotyping common functional variants in genes involved in the pharmacokinetic pathways of prescribed antipsychotics, namely, CYP2D6, CYP3A4, CYP3A5, CYP1A2, ABCB1, and ABCG2. Treatment recommendations for drug-gene pairs were made according to available evidence-based pharmacogenetic recommendations from the Dutch Pharmacogenetics Working Group (DPWG) or Clinical Pharmacogenetics Implementation Consortium (CPIC).

Results

Pharmacogenetic testing revealed a specific metabolic profile and pharmacokinetic phenotype of the patient, which in retrospect provided possible explanations for the observed ADRs. Based on the pharmacogenetic results, the choice of an effective and safe medication proved to be much easier. The psychotic symptoms disappeared after treatment, while the negative symptoms persisted to a lesser extent.

Conclusion

With the case presented, we have shown that taking into account the pharmacogenetic characteristics of the patient can explain the response to antipsychotic treatment and associated side effects. In addition, pharmacogenetic testing enabled an informed choice of the most appropriate drug and optimal dose adjustment. This approach makes it possible to avoid or minimize potentially serious dose-related ADRs and treatment ineffectiveness. However, due to the complexity of psychopathology and the polypharmacy used in this field, it is of great importance to conduct further pharmacokinetic and pharmacogenetic studies to better assess gene-drug and gene-gene-drug interactions.

Forging the path to precision medicine in Qatar: a public health perspective on pharmacogenomics initiatives

Pharmacogenomics (PGx) is an important component of precision medicine that promises tailored treatment approaches based on an individual's genetic information. Exploring the initiatives in research that help to integrate PGx test into clinical setting, identifying the potential barriers and challenges as well as planning the future directions, are all important for fruitful PGx implementation in any population. Qatar serves as an exemplar case study for the Middle East, having a small native population compared to a diverse immigrant population, advanced healthcare system, national genome program, and several educational initiatives on PGx and precision medicine. This paper attempts to outline the current state of PGx research and implementation in Qatar within the global context, emphasizing ongoing initiatives and educational efforts. The inclusion of PGx in university curricula and healthcare provider training, alongside precision medicine conferences, showcase Qatar's commitment to advancing this field. However, challenges persist, including the requirement for population specific implementation strategies, complex genetic data interpretation, lack of standardization, and limited awareness. The review suggests policy development for future directions in continued research investment, conducting clinical trials for the feasibility of PGx implementation, ethical considerations, technological advancements, and global collaborations to overcome these barriers.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population

INTRODUCTION

Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants.

RESEARCH DESIGN AND METHODS

We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test.

RESULTS

Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs).

CONCLUSIONS

Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Prevalence of CYP2C19*2 and CYP2C19*3 Allelic Variants and Clopidogrel Use in Patients with Cardiovascular Disease in Trinidad & Tobago

INTRODUCTION

Trinidad & Tobago has the highest prevalence of cardiovascular disease (CVD) in the Caribbean and clopidogrel is a ubiquitously used treatment. Yet, the extent of genetically mediated clopidogrel resistance is unknown. To determine this, we investigated whether the association between CYP2C19*2 and CYP2C19*3 genetic variants and clopidogrel resistance holds, and calculated the frequencies of these in the Trinidadian CVD population.

METHODS

Demographic data, clinical data, and a saliva sample were collected under informed consent from 22 patients with CVD on dual anti-platelet therapy whose biochemical resistance to clopidogrel is known, and a further 162 patients accessing the main public CVD clinic in Trinidad and who are either currently being treated or are likely to be treated with clopidogrel. A polymerase chain reaction (PCR) and restriction enzyme digestion procedure was used to genotype each patient for the CYP2C19*2 and CYP2C19*3 allelic variants. Genotype was compared to known clopidogrel resistance in the 22 patients, and to disease status and clopidogrel usage in the larger cohort.

RESULTS

CYP2C19*2 genotype was concordant with clopidogrel resistance. CYP2C19*2 was detected in 61.1% (99/162) of patients and CYP2C19*3 was undetected. Clopidogrel was the most prescribed antiplatelet therapy (42%). A total of 120 people presented with coronary artery disease (CAD) and 52.5% of these (n = 63/120) are currently prescribed clopidogrel. 63.5% (40/63) of patients with CAD who are prescribed clopidogrel carry the CYP2C19*2 allele; ten homozygous and 30 heterozygous. Indian patients comprised 65% of the cohort and were four times more likely to carry the CYP2C19*2 allele than African patients.

CONCLUSIONS

A large proportion of Trinidadian patients with CVD who are prescribed or may be prescribed clopidogrel carry genetic variants associated with clopidogrel resistance. These results emphasize the clinical need for further investigation into whether CYP2C19*2 genotype should guide clopidogrel use for the cardiovascular disease population in Trinidad & Tobago. A slide deck is available for this article.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2D6, CYP3A4 and CYP1A2 and antipsychotics

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy. A guideline describing the gene-drug interaction between the genes CYP2D6, CYP3A4 and CYP1A2 and antipsychotics is presented here. The DPWG identified gene-drug interactions that require therapy adjustments when respective genotype is known for CYP2D6 with aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol, and for CYP3A4 with quetiapine. Evidence-based dose recommendations were obtained based on a systematic review of published literature. Reduction of the normal dose is recommended for aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol for CYP2D6-predicted PMs, and for pimozide and zuclopenthixol also for CYP2D6 IMs. For CYP2D6 UMs, a dose increase or an alternative drug is recommended for haloperidol and an alternative drug or titration of the dose for risperidone. In addition, in case of no or limited clinical effect, a dose increase is recommended for zuclopenthixol for CYP2D6 UMs. Even though evidence is limited, the DPWG recommends choosing an alternative drug to treat symptoms of depression or a dose reduction for other indications for quetiapine and CYP3A4 PMs. No therapy adjustments are recommended for the other CYP2D6 and CYP3A4 predicted phenotypes. In addition, no action is required for the gene-drug combinations CYP2D6 and clozapine, flupentixol, olanzapine or quetiapine and also not for CYP1A2 and clozapine or olanzapine. For identified gene-drug interactions requiring therapy adjustments, genotyping of CYP2D6 or CYP3A4 prior to treatment should not be considered for all patients, but on an individual patient basis only.

Characterization of CYP2B6 and CYP2A6 Pharmacogenetic Variation in Sub-Saharan African Populations

Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub-Saharan African (SSA) populations. We called star alleles from 961 high-depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high-coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21-47% and 2-19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0-6%, 3-10%, and 6-20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African-ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single-Molecule Real-Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent.

Rare variants in pharmacogenes influence clozapine metabolism in individuals with schizophrenia

Clozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. We investigated whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤ 1 %) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β = -0.054, SE = 0.019, P-value = 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. The gene-based analysis identified rare variants in CYP1A2, which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β = 0.324, SE = 0.124, P = 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations; these results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles.

Concentrations of Fluoxetine Enantiomers Decline During Pregnancy and Increase After Birth

RATIONALE

Few studies of the effect of the dynamic physiologic changes during pregnancy on plasma concentrations of fluoxetine (FLX) have been published.

OBJECTIVES

We determined the change in concentration to dose (C/D) ratios of R- and S-FLX and R- and S-norfluoxetine monthly during pregnancy and postpartum, assessed their relationships to cytochrome P450 (CYP) 2D6 and CYP2C9 metabolizer phenotypes, and evaluated the course of their depressive and anxiety symptoms.

METHODS

In this observational study, 10 FLX-treated pregnant individuals provided blood samples at steady state every 4 weeks during pregnancy and once postpartum for measurement of plasma FLX and norfluoxetine enantiomer concentrations. Participants were genotyped for variants in CYP2C9 and CYP2D6 using commercial assays with Taqman probes. At each assessment, depressive and anxiety symptoms were quantified.

RESULTS

The C/D ratios of all FLX and norfluoxetine enantiomers, and the active moiety, decreased steadily through pregnancy and rose after birth. In the final trimester, the mean C/D ratio of the active moiety was 24.9% lower compared with the mean nonpregnant, 12-week postpartum C/D ratio. One individual with CYP2D6 ultrarapid metabolizer status was prescribed the highest FLX dose among participants. In these treated individuals, the mean depressive and anxiety symptoms remained in the mild range across the perinatal period.

CONCLUSIONS

These data do not support a recommendation for routine plasma concentration monitoring or CYP2D6 pharmacogenetic testing for pregnant people treated with FLX; however, monitoring for symptom relapse is recommended because of declining plasma drug concentrations.

dbCRAF: a curated knowledgebase for regulation of radiation response in human cancer

Radiation therapy (RT) is one of the primary treatment modalities of cancer, with 40-60% of cancer patients benefiting from RT during their treatment course. The intrinsic radiosensitivity or acquired radioresistance of tumor cells would affect the response to RT and clinical outcomes in patients. Thus, mining the regulatory mechanisms in tumor radiosensitivity or radioresistance that have been verified by biological experiments and computational analysis methods will enhance the overall understanding of RT. Here, we describe a comprehensive database dbCRAF (http://dbCRAF.xialab.info/) to document and annotate the factors (1,677 genes, 49 proteins and 612 radiosensitizers) linked with radiation response, including radiosensitivity, radioresistance in cancer cells and prognosis in cancer patients receiving RT. On the one hand, dbCRAF enables researchers to directly access knowledge for regulation of radiation response in human cancer buried in the vast literature. On the other hand, dbCRAF provides four flexible modules to analyze and visualize the functional relationship between these factors and clinical outcome, KEGG pathway and target genes. In conclusion, dbCRAF serves as a valuable resource for elucidating the regulatory mechanisms of radiation response in human cancers as well as for the improvement of RT options.

Prasugrel Monotherapy After Percutaneous Coronary Intervention for Chronic Coronary Syndrome: Insights From ASET Pilot Studies

Background

The ASET (Acetyl-Salicylic Elimination Trial) pilot studies recently investigated P2Y12 inhibitor monotherapy without aspirin immediately after percutaneous coronary intervention (PCI) in Brazil and Japan.

Objectives

This comparative analysis of the 2 ASET pilot studies aimed to summarize clinical outcomes and assess geographic and ethnic differences in baseline demographics and procedures.

Methods

Patients undergoing successful platinum-chromium everolimus-eluting stent implantation for chronic coronary syndrome were included. Following the index PCI, patients received prasugrel monotherapy with a maintenance dose of 10 mg/day in Brazil and 3.75 mg/day in Japan. The primary ischemic endpoint was the composite of cardiac death, spontaneous target vessel myocardial infarction, or definite stent thrombosis. The primary bleeding endpoint was Bleeding Academic Research Consortium types 3 and 5 bleeding at up to 3 months.

Results

Of 409 enrollments, 3-month follow-up was completed in 406 patients. Mean age was 64.3 ± 8.4 years, and 73% were men. Overall, post-TIMI flow grade 3 was achieved in 99.8%. Intravascular imaging for poststent optimization was used in 16.8% and 99.6% of treated lesions in Brazil and Japan, respectively. The primary ischemic and bleeding endpoints occurred in the same patient (0.2%). No stent thrombosis events occurred.

Conclusions

Prasugrel monotherapy following PCI was safe and feasible in selected low-risk chronic coronary syndrome patients after optimal platinum-chromium everolimus-eluting stent implantation regardless of the ethnic and geographic differences in baseline demographics, procedures, and prasugrel dosage. Randomized controlled trials will be needed to compare P2Y12 inhibitor monotherapy without aspirin with the current standard of care.

Implementation of pharmacogenomics testing for precision medicine

Great strides have been made in the past decade to lower barriers to clinical pharmacogenomics implementation. Nevertheless, PGx consultation prior to prescribing therapeutics is not yet mainstream. This review addresses the current climate surrounding PGx implementation, focusing primarily on strategies for implementation at academic institutions, particularly at The University of Chicago, and provides an up-to-date guide of resources supporting the development of PGx programs. Remaining challenges and recent strategies for overcoming these challenges to implementation are discussed.

The polymorphisms of candidate pharmacokinetic and pharmacodynamic genes and their pharmacogenetic impacts on the effectiveness of risperidone maintenance therapy among Saudi children with autism

BACKGROUND

Antipsychotics, including risperidone (RIS), are frequently indicated for various autism spectrum disorder (ASD) manifestations; however, "actionable" PGx testing in psychiatry regarding antipsychotic dosing and selection has limited applications in routine clinical practice because of the lack of standard guidelines, mostly due to the inconsistency and scarcity of genetic variant data. The current study is aimed at examining the association of RIS effectiveness, according to ABC-CV and CGI indexes, with relevant pharmacokinetics (PK) and pharmacodynamics (PD) genes.

METHODS

Eighty-nine ASD children who received a consistent RIS-based regimen for at least 8 weeks were included. The Axiom PharmacoFocus Array technique was employed to generate accurate star allele-predicted phenotypes of 3 PK genes (CYP3A4, CYP3A5, and CYP2D6). Genotype calls for 5 candidate PD receptor genes (DRD1, DRD2, DRD3, HTR2C, and HTR2A) were obtained and reported as wild type, heterozygous, or homozygous for 11 variants.

RESULTS

Based on the ABC total score, 42 (47.2%) children were classified as responders, while 47 (52.8%) were classified as nonresponders. Multivariate logistic regression analyses, adjusted for nongenetic factors, suggested nonsignificant impacts of the star allele-predicted phenotypes of all 3 PK genes on improvement in ASD symptoms or CGI scores. However, significant positive or negative associations of certain PD variants involved in dopaminergic and serotonergic pathways were observed with specific ASD core and noncore symptom subdomains. Our significant polymorphism findings, mainly those in DRD2 (rs1800497, rs1799978, and rs2734841), HTR2C (rs3813929), and HTR2A (rs6311), were largely consistent with earlier findings (predictors of RIS effectiveness in adult schizophrenia patients), confirming their validity for identifying ASD children with a greater likelihood of core symptom improvement compared to noncarriers/wild types. Other novel findings of this study, such as significant improvements in DRD3 rs167771 carriers, particularly in ABC total and lethargy/social withdrawal scores, and DRD1 rs1875964 homozygotes and DRD2 rs1079598 wild types in stereotypic behavior, warrant further verification in biochemical and clinical studies to confirm their feasibility for inclusion in a PGx panel.

CONCLUSION

In conclusion, we provide evidence of potential genetic markers involved in clinical response variability to RIS therapy in ASD children. However, replication in prospective samples with greater ethnic diversity and sample sizes is necessary.

Haplotype phasing of CYP2D6: an allelic ratio method using Agena MassARRAY data

Pharmacogenomics aims to use the genetic information of an individual to personalize drug prescribing. There is evidence that pharmacogenomic testing before prescription may prevent adverse drug reactions, increase efficacy, and reduce cost of treatment. CYP2D6 is a key pharmacogene of relevance to multiple therapeutic areas. Indeed, there are prescribing guidelines available for medications based on CYP2D6 enzyme activity as deduced from CYP2D6 genetic data. The Agena MassARRAY system is a cost-effective method of detecting genetic variation that has been clinically applied to other genes. However, its clinical application to CYP2D6 has to date been limited by weaknesses such as the inability to determine which haplotype was present in more than one copy for individuals with more than two copies of the CYP2D6 gene. We report application of a new protocol for CYP2D6 haplotype phasing of data generated from the Agena MassARRAY system. For samples with more than two copies of the CYP2D6 gene for which the prior consensus data specified which one was present in more than one copy, our protocol was able to conduct CYP2D6 haplotype phasing resulting in 100% concordance with the prior data. In addition, for three reference samples known to have more than two copies of CYP2D6 but for which the exact number of CYP2D6 genes was unknown, our protocol was able to resolve the number for two out of the three of these, and estimate the likely number for the third. Finally, we demonstrate that our method is applicable to CYP2D6 hybrid tandem configurations.

Understanding the molecular mechanisms of Acori Tatarinowii Rhizoma: Nardostahyos Radix et Rhizoma in epilepsy treatment using network pharmacology and molecular docking

Acori Tatarinowii Rhizoma (ATR) and Nardostahyos Radix et Rhizoma (NRR) are well-known traditional Chinese medicines that have been extensively used for the treatment of epilepsy (EP). However, the precise molecular mechanism of ATR-NRR action remains unclear because of their intricate ingredients. This study aimed to investigate the underlying mechanism of ATR-NRR in EP treatment using network pharmacology and molecular docking techniques. Herbal medicine and disease gene databases were searched to determine active constituents and shared targets of ATR-NRR and EP. A protein-protein interaction network was constructed using the STRING database, while the Gene Ontology and the Kyoto Encyclopedia of Genes and Genome pathway enrichment were performed using R programming. An ingredient-target-pathway network map was constructed using the Cytoscape software, incorporating network topology calculations to predict active ingredients and hub targets. The binding abilities of active ingredients and hub targets were examined using molecular docking. Nine qualified compounds and 53 common targets were obtained. The prominent active compounds were kaempferol, acacetin, cryptotanshinone, 8-isopentenyl-kaempferol, naringenin, and eudesmin, while the primary targets were RELA, AKT1, CASP3, MAPK8, JUN, TNF, and TP53. Molecular docking analysis revealed that they have substantial binding abilities. These 53 targets were found to influence EP by manipulating PI3K-Akt, IL-17, TNF, and apoptosis signaling pathways. The findings of this study indicate that ATR-NRR functions against EP by acting upon multiple pathways and targets, offering a basis for future study.

Exploratory focused pharmacogenetic testing reveals novel markers associated with risperidone pharmacokinetics in Saudi children with autism

Background: Autism spectrum disorders (ASDs) encompass a broad range of phenotypes characterized by diverse neurological alterations. Genomic studies have revealed considerable overlap between the molecular mechanisms implicated in the etiology of ASD and genes involved in the pharmacokinetic (PK) and pharmacodynamic (PD) pathways of antipsychotic drugs employed in ASD management. Given the conflicting data originating from candidate PK or PD gene association studies in diverse ethnogeographic ASD populations, dosage individualization based on "actionable" pharmacogenetic (PGx) markers has limited application in clinical practice. Additionally, off-label use of different antipsychotics is an ongoing practice, which is justified given the shortage of approved cures, despite the lack of satisfactory evidence for its safety according to precision medicine. This exploratory study aimed to identify PGx markers predictive of risperidone (RIS) exposure in autistic Saudi children. Methods: This prospective cohort study enrolled 89 Saudi children with ASD treated with RIS-based antipsychotic therapy. Plasma levels of RIS and 9-OH-RIS were measured using a liquid chromatography-tandem mass spectrometry system. To enable focused exploratory testing, genotyping was performed with the Axiom PharmacoFocus Array, which included a collection of probe sets targeting PK/PD genes. A total of 720 PGx markers were included in the association analysis. Results: A total of 27 PGx variants were found to have a prominent impact on various RIS PK parameters; most were not located within the genes involved in the classical RIS PK pathway. Specifically, 8 markers in 7 genes were identified as the PGx markers with the strongest impact on RIS levels (p < 0.01). Four PGx variants in 3 genes were strongly associated with 9-OH-RIS levels, while 5 markers in 5 different genes explained the interindividual variability in the total active moiety. Notably, 6 CYP2D6 variants exhibited strong linkage disequilibrium; however, they significantly influenced only the metabolic ratio and had no considerable effects on the individual estimates of RIS, 9-OH-RIS, or the total active moiety. After correction for multiple testing, rs78998153 in UGT2B17 (which is highly expressed in the brain) remained the most significant PGx marker positively adjusting the metabolic ratio. For the first time, certain human leukocyte antigen (HLA) markers were found to enhance various RIS exposure parameters, which reinforces the gut-brain axis theory of ASD etiology and its suggested inflammatory impacts on drug bioavailability through modulation of the brain, gastrointestinal tract and/or hepatic expression of metabolizing enzymes and transporters. Conclusion: Our hypothesis-generating approach identified a broad spectrum of PGx markers that interactively influence RIS exposure in ASD children, which indicated the need for further validation in population PK modeling studies to define polygenic scores for antipsychotic efficacy and safety, which could facilitate personalized therapeutic decision-making in this complex neurodevelopmental condition.

Addressing Ancestry and Sex Bias in Pharmacogenomics

The association of an individual's genetic makeup with their response to drugs is referred to as pharmacogenomics. By understanding the relationship between genetic variants and drug efficacy or toxicity, we are able to optimize pharmacological therapy according to an individual's genotype. Pharmacogenomics research has historically suffered from bias and underrepresentation of people from certain ancestry groups and of the female sex. These biases can arise from factors such as drugs and indications studied, selection of study participants, and methods used to collect and analyze data. To examine the representation of biogeographical populations in pharmacogenomic data sets, we describe individuals involved in gene-drug response studies from PharmGKB, a leading repository of drug-gene annotations, and showcaseCYP2D6, a gene that metabolizes approximately 25% of all prescribed drugs. We also show how the historical underrepresentation of females in clinical trials has led to significantly more adverse drug reactions in females than in males.

The Case for Pre-Emptive Pharmacogenetic Screening in South Africa

Lack of equitable representation of global genetic diversity has hampered the implementation of genomic medicine in under-represented populations, including those on the African continent. Data from the multi-national Pre-emptive Pharmacogenomic Testing for Preventing Adverse Drug Reactions (PREPARE) study suggest that genotype guidance for prescriptions reduced the incidence of clinically relevant adverse drug reactions (ADRs) by 30%. In this study, hospital dispensary trends from a tertiary South African (SA) hospital (Steve Biko Academic Hospital; SBAH) were compared with the drugs monitored in the PREPARE study. Dispensary data on 29 drugs from the PREPARE study accounted for ~10% of total prescriptions and ~9% of the total expenditure at SBAH. VigiLyze data from the South African Health Products Regulatory Authority were interrogated for local ADRs related to these drugs; 27 were listed as being suspected, concomitant, or interacting in ADR reports. Furthermore, a comparison of pharmacogene allele frequencies between African and European populations was used to frame the potential impact of pre-emptive pharmacogenetic screening in SA. Enumerating the benefit of pre-emptive pharmacogenetic screening in SA will only be possible once we initiate its full application. However, regional genomic diversity, disease burden, and first-line treatment options could be harnessed to target stratified PGx today.