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Briefings in Bioinformatics May 2024The development of deep learning models plays a crucial role in advancing precision medicine. These models enable personalized medical treatments and interventions based...
The development of deep learning models plays a crucial role in advancing precision medicine. These models enable personalized medical treatments and interventions based on the unique genetic, environmental and lifestyle factors of individual patients, and the promotion of precision medicine is achieved mainly through genomic data analysis, variant annotation and interpretation, pharmacogenomics research, biomarker discovery, disease typing, clinical decision support and disease mechanism interpretation. Extensive research has been conducted to address precision medicine challenges using attention mechanism models such as SAN, GAT and transformers. Especially, the recent popularity of ChatGPT has significantly propelled the application of this model type to a new height. Therefore, I propose a Special Issue for Briefings in Bioinformatics about the topic 'Attention Mechanism Models for Precision Medicine'. This Special Issue aims to provide a comprehensive overview and presentation of innovative researches on the application of graph attention mechanism models in precision medicine.
Topics: Precision Medicine; Humans; Deep Learning; Computational Biology; Genomics
PubMed: 38811359
DOI: 10.1093/bib/bbae156 -
ELife May 2024Alterations in the function of K channels such as the voltage- and Ca-activated K channel of large conductance (BK) reportedly promote breast cancer (BC) development and...
Alterations in the function of K channels such as the voltage- and Ca-activated K channel of large conductance (BK) reportedly promote breast cancer (BC) development and progression. Underlying molecular mechanisms remain, however, elusive. Here, we provide electrophysiological evidence for a BK splice variant localized to the inner mitochondrial membrane of murine and human BC cells (mitoBK). Through a combination of genetic knockdown and knockout along with a cell permeable BK channel blocker, we show that mitoBK modulates overall cellular and mitochondrial energy production, and mediates the metabolic rewiring referred to as the 'Warburg effect', thereby promoting BC cell proliferation in the presence and absence of oxygen. Additionally, we detect mitoBK and BK transcripts in low or high abundance, respectively, in clinical BC specimens. Together, our results emphasize, that targeting mitoBK could represent a treatment strategy for selected BC patients in future.
Topics: Humans; Animals; Mice; Breast Neoplasms; Cell Line, Tumor; Cell Proliferation; Mitochondria; Large-Conductance Calcium-Activated Potassium Channel alpha Subunits; Mitochondrial Membranes; Female; Energy Metabolism
PubMed: 38808578
DOI: 10.7554/eLife.92511 -
The Pharmacogenomics Journal May 2024Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of...
Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.
Topics: Humans; Pharmacogenetics; Pharmacogenomic Variants; Precision Medicine; Algorithms; Computational Biology
PubMed: 38802404
DOI: 10.1038/s41397-024-00338-x -
Cellular and Molecular Neurobiology May 2024Considering the variability in individual responses to opioids and the growing concerns about opioid addiction, prescribing opioids for postoperative pain management...
Considering the variability in individual responses to opioids and the growing concerns about opioid addiction, prescribing opioids for postoperative pain management after spine surgery presents significant challenges. Therefore, this study undertook a novel pharmacogenomics-based in silico investigation of FDA-approved opioid medications. The DrugBank database was employed to identify all FDA-approved opioids. Subsequently, the PharmGKB database was utilized to filter through all variant annotations associated with the relevant genes. In addition, the dpSNP ( https://www.ncbi.nlm.nih.gov/snp/ ), a publicly accessible repository, was used. Additional analyses were conducted using STRING-MODEL (version 12), Cytoscape (version 3.10.1), miRTargetLink.2, and NetworkAnalyst (version 3). The study identified 125 target genes of FDA-approved opioids, encompassing 7019 variant annotations. Of these, 3088 annotations were significant and pertained to 78 genes. During variant annotation assessments (VAA), 672 variants remained after filtration. Further in-depth filtration based on variant functions yielded 302 final filtered variants across 56 genes. The Monoamine GPCRs pathway emerged as the most significant signaling pathway. Protein-protein interaction (PPI) analysis revealed a fully connected network comprising 55 genes. Gene-miRNA Interaction (GMI) analysis of these 55 candidate genes identified miR-16-5p as a pivotal miRNA in this network. Protein-Drug Interaction (PDI) assessment showed that multiple drugs, including Ibuprofen, Nicotine, Tramadol, Haloperidol, Ketamine, L-Glutamic Acid, Caffeine, Citalopram, and Naloxone, had more than one interaction. Furthermore, Protein-Chemical Interaction (PCI) analysis highlighted that ABCB1, BCL2, CYP1A2, KCNH2, PTGS2, and DRD2 were key targets of the proposed chemicals. Notably, 10 chemicals, including carbamylhydrazine, tetrahydropalmatine, Terazosin, beta-methylcholine, rubimaillin, and quinelorane, demonstrated dual interactions with the aforementioned target genes. This comprehensive review offers multiple strong, evidence-based in silico findings regarding opioid prescribing in spine pain management, introducing 55 potential genes. The insights from this report can be applied in exome analysis as a pharmacogenomics (PGx) panel for pain susceptibility, facilitating individualized opioid prescribing through genotyping of related variants. The article also points out that African Americans represent an important group that displays a high catabolism of opioids and suggest the need for a personalized therapeutic approach based on genetic information.
Topics: Humans; Pain, Postoperative; Precision Medicine; Analgesics, Opioid; Pharmacogenetics; Pain Management; Computer Simulation; Spine
PubMed: 38801645
DOI: 10.1007/s10571-024-01466-5 -
Therapeutic Advances in Cardiovascular... 2024Atrial fibrillation (AF) accounts for 40% of all cardiac arrhythmias and is associated with a high risk of stroke and systemic thromboembolic complications. Dabigatran,... (Review)
Review
Atrial fibrillation (AF) accounts for 40% of all cardiac arrhythmias and is associated with a high risk of stroke and systemic thromboembolic complications. Dabigatran, rivaroxaban, apixaban, and edoxaban are direct oral anticoagulants (DOACs) that have been proven to prevent stroke in patients with non-valvular AF. This review summarizes the pharmacokinetics, pharmacodynamics, and drug interactions of DOACs, as well as new data from pharmacogenetic studies of these drugs. This review is aimed at analyzing the scientific literature on the gene polymorphisms involved in the metabolism of DOACs. We searched PubMed, Cochrane, Google Scholar, and CyberLeninka (Russian version) databases with keywords: 'dabigatran', 'apixaban', 'rivaroxaban', 'edoxaban', 'gene polymorphism', 'pharmacogenetics', '', '', '', '', and ''. The articles referred for this review include (1) full-text articles; (2) study design with meta-analysis, an observational study in patients taking DOAC; and (3) data on the single-nucleotide polymorphisms and kinetic parameters of DOACs (plasma concentration), or a particular clinical outcome, published in English and Russian languages during the last 10 years. The ages of the patients ranged from 18 to 75 years. Out of 114 reviewed works, 24 were found eligible. As per the available pharmacogenomic data, polymorphisms affecting DOACs are different. This may aid in developing individual approaches to optimize DOAC pharmacotherapy to reduce the risk of hemorrhagic complications. However, large-scale population studies are required to determine the dosage of the new oral anticoagulants based on genotyping. Information on the genetic effects is limited owing to the lack of large-scale studies. Uncovering the mechanisms of the genetic basis of sensitivity to DOACs helps in developing personalized therapy based on patient-specific genetic variants and improves the efficacy and safety of DOACs in the general population.
Topics: Humans; Atrial Fibrillation; Administration, Oral; Hemorrhage; Pharmacogenomic Variants; Risk Factors; Anticoagulants; Treatment Outcome; Stroke; Risk Assessment; Phenotype; Polymorphism, Single Nucleotide; Vitamin K; Drug Interactions
PubMed: 38801157
DOI: 10.1177/17539447241249886 -
Frontiers in Immunology 2024Desmoplastic melanoma (DM) is a rare subtype of melanoma characterized by high immunogenicity which makes it particularly suitable for immune checkpoint inhibitors...
BACKGROUND
Desmoplastic melanoma (DM) is a rare subtype of melanoma characterized by high immunogenicity which makes it particularly suitable for immune checkpoint inhibitors (ICIs) treatment.
CASE PRESENTATION
We report the case of a 53-year-old man with metastatic DM successfully treated with the combination of anti-CTLA-4 and anti-PD-1 antibodies, who developed serious immune-related adverse events (irAEs). The primary tumor was characterized by absent PD-L1 expression and no-brisk lymphocytes infiltration. NGS showed absence of BRAF mutation, a high tumor mutational burden, and an UV-induced DNA damage signature. Metastatic lesions regressed rapidly after few cycles of ICIs until complete response, however the patient developed serious irAEs including hypothyroidism, adrenal deficiency, and acute interstitial nephritis which led to the definitive suspension of treatment. Currently, the patient has normal renal functionality and no disease relapse after 26 months from starting immunotherapy, and after 9 months from its definitive suspension.
CONCLUSION
Efficacy and toxicity are two sides of the same coin of high sensitivity to ICIs in DM. For this reason, these patients should be closely monitored during ICIs therapy to promptly identify serious side effects and to correctly manage them.
Topics: Humans; Male; Melanoma; Middle Aged; Immune Checkpoint Inhibitors; Immunotherapy; Skin Neoplasms; CTLA-4 Antigen; Treatment Outcome; Programmed Cell Death 1 Receptor
PubMed: 38799429
DOI: 10.3389/fimmu.2024.1369531 -
BMC Psychiatry May 2024Tailoring antidepressant drugs (AD) to patients' genetic drug-metabolism profile is promising. However, literature regarding associations of ADs' treatment effect and/or...
BACKGROUND
Tailoring antidepressant drugs (AD) to patients' genetic drug-metabolism profile is promising. However, literature regarding associations of ADs' treatment effect and/or side effects with drug metabolizing genes CYP2D6 and CYP2C19 has yielded inconsistent results. Therefore, our aim was to longitudinally investigate associations between CYP2D6 (poor, intermediate, and normal) and CYP2C19 (poor, intermediate, normal, and ultrarapid) metabolizer-status, and switching/discontinuing of ADs. Next, we investigated whether the number of perceived side effects differed between metabolizer statuses.
METHODS
Data came from the multi-site naturalistic longitudinal cohort Netherlands Study of Depression and Anxiety (NESDA). We selected depression- and/or anxiety patients, who used AD at some point in the course of the 9 years follow-up period (n = 928). Medication use was followed to assess patterns of AD switching/discontinuation over time. CYP2D6 and CYP2C19 alleles were derived using genome-wide data of the NESDA samples and haplotype data from the PharmGKB database. Logistic regression analyses were conducted to investigate the association of metabolizer status with switching/discontinuing ADs. Mann-Whitney U-tests were conducted to compare the number of patient-perceived side effects between metabolizer statuses.
RESULTS
No significant associations were observed of CYP metabolizer status with switching/discontinuing ADs, nor with the number of perceived side effects.
CONCLUSIONS
We found no evidence for associations between CYP metabolizer statuses and switching/discontinuing AD, nor with side effects of ADs, suggesting that metabolizer status only plays a limited role in switching/discontinuing ADs. Additional studies with larger numbers of PM and UM patients are needed to further determine the potential added value of pharmacogenetics to guide pharmacotherapy.
Topics: Humans; Cytochrome P-450 CYP2D6; Cytochrome P-450 CYP2C19; Male; Antidepressive Agents; Female; Middle Aged; Adult; Longitudinal Studies; Netherlands; Anxiety Disorders; Depressive Disorder
PubMed: 38797832
DOI: 10.1186/s12888-024-05764-6 -
Pharmaceuticals (Basel, Switzerland) Apr 2024Polypharmacy is a global healthcare concern, especially among the elderly, leading to drug interactions and adverse reactions, which are significant causes of death in...
Polypharmacy is a global healthcare concern, especially among the elderly, leading to drug interactions and adverse reactions, which are significant causes of death in developed nations. However, the integration of pharmacogenetics can help mitigate these risks. In this study, the data from 483 patients, primarily elderly and polymedicated, were analyzed using Eugenomic's personalized prescription software, g-Nomic. The most prescribed drug classes included antihypertensives, platelet aggregation inhibitors, cholesterol-lowering drugs, and gastroprotective medications. Drug-lifestyle interactions primarily involved inhibitions but also included inductions. Interactions were analyzed considering gender. Significant genetic variants identified in the study encompassed , and . To prevent adverse reactions and enhance medication effectiveness, it is strongly recommended to consider pharmacogenetics testing. This approach shows great promise in optimizing medication regimens and ultimately improving patient outcomes.
PubMed: 38794134
DOI: 10.3390/ph17050565 -
Pharmaceuticals (Basel, Switzerland) Apr 2024Tacrolimus (Tac) is pivotal in preventing acute graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplantation (alloHSCT). It has been...
Tacrolimus (Tac) is pivotal in preventing acute graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplantation (alloHSCT). It has been reported that genetic factors, including * and 22 polymorphisms, have an impact on Tac metabolism, dose requirement, and response to Tac. There is limited information regarding this topic in alloHSCT. The genotype and a low Tac trough concentration/dose ratio (Tac C/D ratio) can be used to identify fast metabolizers and predict the required Tac dose to achieve target concentrations earlier. We examined 62 Caucasian alloHSCT recipients with a fast metabolizer phenotype (C/dose ratio ≤ 1.5 ng/mL/mg), assessing genotypes and acute GVHD incidence. Forty-nine patients (79%) were poor metabolizers (2 copies of the variant *3 allele) and 13 (21%) were CYP3A5 expressers ( or genotypes). CYP3A5 expressers had lower C at 48 h (3.7 vs. 6.2 ng/mL, = 0.03) and at 7 days (8.6 vs. 11.4 ng/mL, = 0.04) after Tac initiation, tended to take longer to reach Tac therapeutic range (11.8 vs. 8.9 days, = 0.16), and had higher incidence of both global (92.3% vs. 38.8%, < 0.001) and grade II-IV acute GVHD (61.5% vs. 24.5%, = 0.008). These results support the adoption of preemptive pharmacogenetic testing to better predict individual Tac initial dose, helping to achieve the therapeutic range and reducing the risk of acute GVHD earlier.
PubMed: 38794124
DOI: 10.3390/ph17050553 -
Journal of Personalized Medicine Apr 2024The causal effect and pathways of gut microbiota and plasma metabolome on lung cancer have been important topics for personalized medicine; however, the heterogeneity of...
The causal effect and pathways of gut microbiota and plasma metabolome on lung cancer have been important topics for personalized medicine; however, the heterogeneity of lung cancer subtypes has not gained enough attention in previous studies. This study sought to employ a Mendelian randomization analysis to screen the specific gut microbiota and plasma metabolome, which may have a causal effect on lung cancer. We further extended our analysis to estimate the effects of these exposures on various pathological subtypes of lung cancer. Furthermore, a mediation analysis was performed to identify the potential pathway underlying the influence of microbiota and metabolites. Our study identified 13 taxa and 15 metabolites with a causal association with the overall risk of lung cancer. Furthermore, we found 8 taxa and 14 plasma metabolites with a causal effect on lung adenocarcinoma, 4 taxa and 10 metabolites with a causal effect on squamous cell lung carcinoma, and 7 taxa and 16 metabolites with a causal effect on SCLC. We also identified seven mediation pathways that could potentially elucidate the influence of these microbiota and metabolites on overall lung cancer or special subtypes. Our study highlighted the heterogeneity of the gut microbiome and plasma metabolome in a lung cancer subtype and elucidated the potential underlying mechanisms. This could pave the way for more personalized lung cancer prevention and treatment.
PubMed: 38793035
DOI: 10.3390/jpm14050453