Pub Date : 2022-11-24DOI: 10.1038/s41397-022-00297-1
Shujun Huang, Pingzhao Hu, Ted M. Lakowski
Our previous studies demonstrated that the FOXM1 pathway is upregulated and the PPARA pathway downregulated in breast cancer (BC), and especially in the triple negative breast cancer (TNBC) subtype. Targeting the two pathways may offer potential therapeutic strategies to treat BC, especially TNBC which has the fewest effective therapies available among all BC subtypes. In this study we identified small molecule compounds that could modulate the PPARA and FOXM1 pathways in BC using two methods. In the first method, data were initially curated from the Connectivity Map (CMAP) database, which provides the gene expression profiles of MCF7 cells treated with different compounds as well as paired controls. We then calculated the changes in the FOXM1 and PPARA pathway activities from the compound-induced gene expression profiles under each treatment to identify compounds that produced a decreased activity in the FOXM1 pathway or an increased activity in the PPARA pathway. In the second method, the CMAP database tool was used to identify compounds that could reverse the expression pattern of the two pathways in MCF7 cells. Compounds identified as repressing the FOXM1 pathway or activating the PPARA pathway by the two methods were compared. We identified 19 common compounds that could decrease the FOXM1 pathway activity scores and reverse the FOXM1 pathway expression pattern, and 13 common compounds that could increase the PPARA pathway activity scores and reverse the PPARA pathway expression pattern. It may be of interest to validate these compounds experimentally to further investigate their effects on TNBCs.
{"title":"Bioinformatics driven discovery of small molecule compounds that modulate the FOXM1 and PPARA pathway activities in breast cancer","authors":"Shujun Huang, Pingzhao Hu, Ted M. Lakowski","doi":"10.1038/s41397-022-00297-1","DOIUrl":"10.1038/s41397-022-00297-1","url":null,"abstract":"Our previous studies demonstrated that the FOXM1 pathway is upregulated and the PPARA pathway downregulated in breast cancer (BC), and especially in the triple negative breast cancer (TNBC) subtype. Targeting the two pathways may offer potential therapeutic strategies to treat BC, especially TNBC which has the fewest effective therapies available among all BC subtypes. In this study we identified small molecule compounds that could modulate the PPARA and FOXM1 pathways in BC using two methods. In the first method, data were initially curated from the Connectivity Map (CMAP) database, which provides the gene expression profiles of MCF7 cells treated with different compounds as well as paired controls. We then calculated the changes in the FOXM1 and PPARA pathway activities from the compound-induced gene expression profiles under each treatment to identify compounds that produced a decreased activity in the FOXM1 pathway or an increased activity in the PPARA pathway. In the second method, the CMAP database tool was used to identify compounds that could reverse the expression pattern of the two pathways in MCF7 cells. Compounds identified as repressing the FOXM1 pathway or activating the PPARA pathway by the two methods were compared. We identified 19 common compounds that could decrease the FOXM1 pathway activity scores and reverse the FOXM1 pathway expression pattern, and 13 common compounds that could increase the PPARA pathway activity scores and reverse the PPARA pathway expression pattern. It may be of interest to validate these compounds experimentally to further investigate their effects on TNBCs.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"23 4","pages":"61-72"},"PeriodicalIF":2.8,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382320/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9899616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Head and neck squamous cell carcinomas (HNSCCs) are introduced as the sixth most common cancer in the world. Detection of predictive biomarkers improve early diagnosis and prognosis. Recent cancer researches provide a new avenue for organoids, known as “mini-organs” in a dish, such as patient-derived organoids (PDOs), for cancer modeling. HNSCC burden, heterogeneity, mutations, and organoid give opportunities for the evaluation of drug sensitivity/resistance response according to the unique genetic profile signature. The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) nucleases, as an efficient genome engineering technology, can be used for genetic manipulation in three-dimensional (3D) organoids for cancer modeling by targeting oncogenes/tumor suppressor genes. Moreover, single-cell analysis of circulating tumor cells (CTCs) improved understanding of molecular angiogenesis, distance metastasis, and drug screening without the need for tissue biopsy. Organoids allow us to investigate the biopathogenesis of cancer, tumor cell behavior, and drug screening in a living biobank according to the specific genetic profile of patients.
头颈部鳞状细胞癌（HNSCC）是全球第六大常见癌症。检测预测性生物标志物可改善早期诊断和预后。最近的癌症研究为癌症建模提供了一个新的途径，即在培养皿中使用被称为 "微型器官 "的器官组织，如患者衍生器官组织（PDOs）。HNSCC的负担、异质性、突变和器官组织为根据独特的基因图谱特征评估药物敏感性/耐药性反应提供了机会。作为一种高效的基因组工程技术，CRISPR（Clustered Regularly Interspaced Short Palindromic Repeat）核酸酶可用于三维（3D）器官组织中的基因操作，通过靶向致癌基因/抑癌基因建立癌症模型。此外，循环肿瘤细胞（CTCs）的单细胞分析提高了对分子血管生成、远距离转移和药物筛选的认识，而无需进行组织活检。有机体使我们能够根据患者的具体基因特征，在活体生物库中研究癌症的生物发病机制、肿瘤细胞行为和药物筛选。
{"title":"The organoid as reliable cancer modeling in personalized medicine, does applicable in precision medicine of head and neck squamous cell carcinoma?","authors":"Alieh Farshbaf, Malihe Lotfi, Reza Zare, Nooshin Mohtasham","doi":"10.1038/s41397-022-00296-2","DOIUrl":"10.1038/s41397-022-00296-2","url":null,"abstract":"Head and neck squamous cell carcinomas (HNSCCs) are introduced as the sixth most common cancer in the world. Detection of predictive biomarkers improve early diagnosis and prognosis. Recent cancer researches provide a new avenue for organoids, known as “mini-organs” in a dish, such as patient-derived organoids (PDOs), for cancer modeling. HNSCC burden, heterogeneity, mutations, and organoid give opportunities for the evaluation of drug sensitivity/resistance response according to the unique genetic profile signature. The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) nucleases, as an efficient genome engineering technology, can be used for genetic manipulation in three-dimensional (3D) organoids for cancer modeling by targeting oncogenes/tumor suppressor genes. Moreover, single-cell analysis of circulating tumor cells (CTCs) improved understanding of molecular angiogenesis, distance metastasis, and drug screening without the need for tissue biopsy. Organoids allow us to investigate the biopathogenesis of cancer, tumor cell behavior, and drug screening in a living biobank according to the specific genetic profile of patients.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"23 2-3","pages":"37-44"},"PeriodicalIF":2.8,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9620652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-04DOI: 10.1038/s41397-022-00294-4
Erik Joas, Lina Jonsson, Alexander Viktorin, Erik Smedler, Erik Pålsson, Guy M. Goodwin, Mikael Landén
Antidepressant medication is used extensively to treat bipolar depression despite uncertain efficacy. The cytochrome P450 (CYP) 2C19 enzyme metabolize several antidepressants, and polymorphisms in the corresponding gene CYP2C19 influence plasma concentration and hence treatment outcomes in major depressive disorder. Here, we investigate if CYP2C19 polymorphisms are associated with antidepressant treatment patterns and the risk of mania when antidepressants are used in bipolar disorder. Two single nucleotide polymorphisms (rs4244285 and rs12248560) were used to classify 5019 bipolar disorder patients into CYP2C19 metabolic phenotypes ranging from poor to ultra-rapid metabolizers. We used Swedish national registry data 2005–2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19 were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04–1.62, p = 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05–2.02, p = 0.024). In a large study of the impact of CYP2C19 metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. There were, however, no clear associations with early treatment persistence, treatment discontinuation, and switching to a new antidepressant.
{"title":"Effect of CYP2C19 polymorphisms on antidepressant prescription patterns and treatment emergent mania in bipolar disorder","authors":"Erik Joas, Lina Jonsson, Alexander Viktorin, Erik Smedler, Erik Pålsson, Guy M. Goodwin, Mikael Landén","doi":"10.1038/s41397-022-00294-4","DOIUrl":"10.1038/s41397-022-00294-4","url":null,"abstract":"Antidepressant medication is used extensively to treat bipolar depression despite uncertain efficacy. The cytochrome P450 (CYP) 2C19 enzyme metabolize several antidepressants, and polymorphisms in the corresponding gene CYP2C19 influence plasma concentration and hence treatment outcomes in major depressive disorder. Here, we investigate if CYP2C19 polymorphisms are associated with antidepressant treatment patterns and the risk of mania when antidepressants are used in bipolar disorder. Two single nucleotide polymorphisms (rs4244285 and rs12248560) were used to classify 5019 bipolar disorder patients into CYP2C19 metabolic phenotypes ranging from poor to ultra-rapid metabolizers. We used Swedish national registry data 2005–2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19 were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04–1.62, p = 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05–2.02, p = 0.024). In a large study of the impact of CYP2C19 metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. There were, however, no clear associations with early treatment persistence, treatment discontinuation, and switching to a new antidepressant.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"23 1","pages":"28-35"},"PeriodicalIF":2.8,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925376/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10844374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-27DOI: 10.1038/s41397-022-00292-6
Krista N. Bohlen, Julie M. Kittelsrud, Morgan E. Nelson, Lisa K. Weisser, Neil J. Matthiesen, Julie A. Fieldsend, Nicholas B. Buschette, Leslie L. Cooper, Gareth E. Davies, Erik A. Ehli
This study evaluated the timing, use, and clinical outcomes of the GeneFolio® Pharmacogenomic Panel in a healthcare setting with patients managed by primary care providers or by psychiatrists. Participants were randomized to receive a pharmacogenetics report at four weeks or 12 weeks. After DNA collection and genetic analysis, pharmacists produced a recommendation report which was given to providers at the randomization week. The four-week group decreased depression severity (PHQ-9 and BDI) faster than the 12-week group (p = 0.0196), and psychiatrists’ patients decreased their depression severity faster than primary care patients (PHQ-9 p = 0.0005, BDI p = 0.0218). Mean mental quality of life increased over time (p < 0.0001), but it increased slower for patients taking drugs in the Significant drug-drug-gene interaction category (p = 0.0012). Mental quality of life, depression severity, and clinical outcomes were improved by GeneFolio® pharmacogenomic testing regardless of provider type, with earlier testing improving outcomes sooner.
这项研究评估了 GeneFolio® 药物基因组面板在医疗机构中的使用时间、使用情况和临床效果，研究对象是由初级保健提供者或精神科医生管理的患者。参与者被随机分配在四周或十二周时接受药物基因组学报告。经过 DNA 采集和基因分析后，药剂师会生成一份建议报告，在随机化的那一周交给医疗服务提供者。四周组抑郁严重程度（PHQ-9 和 BDI）的下降速度快于 12 周组（P = 0.0196），精神科患者抑郁严重程度的下降速度快于初级保健患者（PHQ-9 P = 0.0005，BDI P = 0.0218）。随着时间的推移，平均精神生活质量有所提高（p <0.0001），但服用药物-药物-基因相互作用显著类别药物的患者的精神生活质量提高较慢（p = 0.0012）。无论医疗机构的类型如何，GeneFolio®药物基因组学检测都能改善患者的精神生活质量、抑郁严重程度和临床疗效，而更早的检测能更快地改善疗效。
{"title":"Clinical utility of pharmacogenetics in a psychiatric and primary care population","authors":"Krista N. Bohlen, Julie M. Kittelsrud, Morgan E. Nelson, Lisa K. Weisser, Neil J. Matthiesen, Julie A. Fieldsend, Nicholas B. Buschette, Leslie L. Cooper, Gareth E. Davies, Erik A. Ehli","doi":"10.1038/s41397-022-00292-6","DOIUrl":"10.1038/s41397-022-00292-6","url":null,"abstract":"This study evaluated the timing, use, and clinical outcomes of the GeneFolio® Pharmacogenomic Panel in a healthcare setting with patients managed by primary care providers or by psychiatrists. Participants were randomized to receive a pharmacogenetics report at four weeks or 12 weeks. After DNA collection and genetic analysis, pharmacists produced a recommendation report which was given to providers at the randomization week. The four-week group decreased depression severity (PHQ-9 and BDI) faster than the 12-week group (p = 0.0196), and psychiatrists’ patients decreased their depression severity faster than primary care patients (PHQ-9 p = 0.0005, BDI p = 0.0218). Mean mental quality of life increased over time (p < 0.0001), but it increased slower for patients taking drugs in the Significant drug-drug-gene interaction category (p = 0.0012). Mental quality of life, depression severity, and clinical outcomes were improved by GeneFolio® pharmacogenomic testing regardless of provider type, with earlier testing improving outcomes sooner.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"23 1","pages":"21-27"},"PeriodicalIF":2.8,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10833112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study aimed to conduct a meta-analysis of studies comparing pharmacogenetically guided dosing of antidepressants with empiric standard of care. Publications referring to genotype-guided antidepressant therapy were identified via PubMed, Google Scholar, Scopus, Web of Science, Embase, and Cochrane databases from the inception of the databases to 2021. In addition, bibliographies of all articles were manually searched for additional references not identified in primary searches. Studies comparing clinical outcomes between two groups of patients who received antidepressant treatment were included in meta-analysis. Analysis of the data revealed statistically significant differences between the experimental group receiving pharmacogenetically guided dosing and the empirically treated controls. Specifically, genotype-guided treatment significantly improved response and remission of patients after both eight and twelve weeks of therapy, whereas no effect on the development of adverse drug reactions was observed. This meta-analysis indicates that the use of preemptive genotyping to guide dosing of antidepressants might increase treatment efficacy.
该研究旨在对比较药物基因指导下的抗抑郁药剂量与经验性标准治疗的研究进行荟萃分析。研究人员通过PubMed、Google Scholar、Scopus、Web of Science、Embase和Cochrane等数据库查找了从数据库建立之初到2021年期间有关基因型指导抗抑郁治疗的文献。此外，还对所有文章的书目进行了人工检索，以查找主要检索中未发现的其他参考文献。荟萃分析纳入了对两组接受抗抑郁治疗的患者的临床疗效进行比较的研究。数据分析显示，接受药物基因指导剂量的实验组与接受经验治疗的对照组之间存在显著的统计学差异。具体来说，基因型指导治疗显著改善了患者在接受八周和十二周治疗后的反应和缓解情况，而对药物不良反应的发生没有影响。这项荟萃分析表明，使用先期基因分型来指导抗抑郁药物的剂量可能会提高疗效。
{"title":"Meta-analysis of pharmacogenetic clinical decision support systems for the treatment of major depressive disorder","authors":"Valentin Skryabin, Ilya Rozochkin, Mikhail Zastrozhin, Volker Lauschke, Johan Franck, Evgeny Bryun, Dmitry Sychev","doi":"10.1038/s41397-022-00295-3","DOIUrl":"10.1038/s41397-022-00295-3","url":null,"abstract":"The study aimed to conduct a meta-analysis of studies comparing pharmacogenetically guided dosing of antidepressants with empiric standard of care. Publications referring to genotype-guided antidepressant therapy were identified via PubMed, Google Scholar, Scopus, Web of Science, Embase, and Cochrane databases from the inception of the databases to 2021. In addition, bibliographies of all articles were manually searched for additional references not identified in primary searches. Studies comparing clinical outcomes between two groups of patients who received antidepressant treatment were included in meta-analysis. Analysis of the data revealed statistically significant differences between the experimental group receiving pharmacogenetically guided dosing and the empirically treated controls. Specifically, genotype-guided treatment significantly improved response and remission of patients after both eight and twelve weeks of therapy, whereas no effect on the development of adverse drug reactions was observed. This meta-analysis indicates that the use of preemptive genotyping to guide dosing of antidepressants might increase treatment efficacy.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"23 2-3","pages":"45-49"},"PeriodicalIF":2.8,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9995629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-20DOI: 10.1038/s41397-022-00293-5
Rohan Gurjar, Laura Dickinson, Daniel Carr, Wolfgang Stöhr, Stefano Bonora, Andrew Owen, Antonio D’Avolio, Adam Cursley, Nathalie De Castro, Gerd Fätkenheuer, Linos Vandekerckhove, Giovanni Di Perri, Anton Pozniak, Christine Schwimmer, François Raffi, Marta Boffito, the NEAT001/ANRS143 Study Group
Using concentration-time data from the NEAT001/ARNS143 study (single sample at week 4 and 24), we determined raltegravir pharmacokinetic parameters using nonlinear mixed effects modelling (NONMEM v.7.3; 602 samples from 349 patients) and investigated the influence of demographics and SNPs (SLC22A6 and UGT1A1) on raltegravir pharmacokinetics and pharmacodynamics. Demographics and SNPs did not influence raltegravir pharmacokinetics and no significant pharmacokinetic/pharmacodynamic relationships were observed. At week 96, UGT1A1*28/*28 was associated with lower virological failure (p = 0.012), even after adjusting for baseline CD4 count (p = 0.048), but not when adjusted for baseline HIV-1 viral load (p = 0.082) or both (p = 0.089). This is the first study to our knowledge to assess the influence of SNPs on raltegravir pharmacodynamics. The lack of a pharmacokinetic/pharmacodynamic relationship is potentially an artefact of raltegravir’s characteristic high inter and intra-patient variability and also suggesting single time point sampling schedules are inadequate to thoroughly assess the influence of SNPs on raltegravir pharmacokinetics.
{"title":"Influence of UGT1A1 and SLC22A6 polymorphisms on the population pharmacokinetics and pharmacodynamics of raltegravir in HIV-infected adults: a NEAT001/ANRS143 sub-study","authors":"Rohan Gurjar, Laura Dickinson, Daniel Carr, Wolfgang Stöhr, Stefano Bonora, Andrew Owen, Antonio D’Avolio, Adam Cursley, Nathalie De Castro, Gerd Fätkenheuer, Linos Vandekerckhove, Giovanni Di Perri, Anton Pozniak, Christine Schwimmer, François Raffi, Marta Boffito, the NEAT001/ANRS143 Study Group","doi":"10.1038/s41397-022-00293-5","DOIUrl":"10.1038/s41397-022-00293-5","url":null,"abstract":"Using concentration-time data from the NEAT001/ARNS143 study (single sample at week 4 and 24), we determined raltegravir pharmacokinetic parameters using nonlinear mixed effects modelling (NONMEM v.7.3; 602 samples from 349 patients) and investigated the influence of demographics and SNPs (SLC22A6 and UGT1A1) on raltegravir pharmacokinetics and pharmacodynamics. Demographics and SNPs did not influence raltegravir pharmacokinetics and no significant pharmacokinetic/pharmacodynamic relationships were observed. At week 96, UGT1A1*28/*28 was associated with lower virological failure (p = 0.012), even after adjusting for baseline CD4 count (p = 0.048), but not when adjusted for baseline HIV-1 viral load (p = 0.082) or both (p = 0.089). This is the first study to our knowledge to assess the influence of SNPs on raltegravir pharmacodynamics. The lack of a pharmacokinetic/pharmacodynamic relationship is potentially an artefact of raltegravir’s characteristic high inter and intra-patient variability and also suggesting single time point sampling schedules are inadequate to thoroughly assess the influence of SNPs on raltegravir pharmacokinetics.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"23 1","pages":"14-20"},"PeriodicalIF":2.8,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9584256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9477454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-15DOI: 10.1038/s41397-022-00290-8
Philippa D. K. Curry, Andrew P. Morris, Anne Barton, James Bluett
Psoriatic arthritis (PsA) is a heterogeneous chronic musculoskeletal disease, affecting up to 30% of people with psoriasis. Research into PsA pathogenesis has led to the development of targeted therapies, including Tumor Necrosis Factor inhibitors (TNF-i). Good response is only achieved by ~60% of patients leading to ‘trial and error’ drug management approaches, adverse reactions and increasing healthcare costs. Robust and well-validated biomarker identification, and subsequent development of sensitive and specific assays, would facilitate the implementation of a stratified approach into clinical care. This review will summarise potential genetic biomarkers for TNF-i (adalimumab, etanercept and infliximab) response that have been reported to date. It will also comment upon the importance of managing clinical confounders when understanding drug response prediction. Variants in multiple gene regions including TNF-A, FCGR2A, TNFAIP3, TNFR1/TNFR1A/TNFRSF1A, TRAIL-R1/TNFRSF10A, FCGR3A have been reported to correlate with TNF-i response at various levels of statistical significance in patients with PsA. However, results were often from heterogenous and underpowered cohorts and none are currently implemented into clinical practice. External validation of genetic biomarkers in large, well-documented cohorts is required, and assessment of the predictive value of combining multiple genetic biomarkers with clinical measures is essential to clinically embed pharmacogenomics into PsA drug management.
{"title":"Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?","authors":"Philippa D. K. Curry, Andrew P. Morris, Anne Barton, James Bluett","doi":"10.1038/s41397-022-00290-8","DOIUrl":"10.1038/s41397-022-00290-8","url":null,"abstract":"Psoriatic arthritis (PsA) is a heterogeneous chronic musculoskeletal disease, affecting up to 30% of people with psoriasis. Research into PsA pathogenesis has led to the development of targeted therapies, including Tumor Necrosis Factor inhibitors (TNF-i). Good response is only achieved by ~60% of patients leading to ‘trial and error’ drug management approaches, adverse reactions and increasing healthcare costs. Robust and well-validated biomarker identification, and subsequent development of sensitive and specific assays, would facilitate the implementation of a stratified approach into clinical care. This review will summarise potential genetic biomarkers for TNF-i (adalimumab, etanercept and infliximab) response that have been reported to date. It will also comment upon the importance of managing clinical confounders when understanding drug response prediction. Variants in multiple gene regions including TNF-A, FCGR2A, TNFAIP3, TNFR1/TNFR1A/TNFRSF1A, TRAIL-R1/TNFRSF10A, FCGR3A have been reported to correlate with TNF-i response at various levels of statistical significance in patients with PsA. However, results were often from heterogenous and underpowered cohorts and none are currently implemented into clinical practice. External validation of genetic biomarkers in large, well-documented cohorts is required, and assessment of the predictive value of combining multiple genetic biomarkers with clinical measures is essential to clinically embed pharmacogenomics into PsA drug management.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"23 1","pages":"1-7"},"PeriodicalIF":2.8,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925377/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10849646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1038/s41397-022-00291-7
Charalabos Antonatos, Aikaterini Patsatsi, Efterpi Zafiriou, Eleana F. Stavrou, Andreas Liaropoulos, Aikaterini Kyriakoy, Evangelos Evangelou, Danai Digka, Angeliki Roussaki-Schulze, Dimitris Sotiriadis, Sophia Georgiou, Katerina Grafanaki, Nicholas Κ. Moschonas, Yiannis Vasilopoulos
Although cyclosporine comprises a well-established systemic therapy for psoriasis, patients show important heterogeneity in their treatment response. The aim of our study was the pharmacogenetic analysis of 200 Greek patients with psoriasis based on the cyclosporine pathway related protein-protein interaction (PPI) network, reconstructed through the PICKLE meta-database. We genotyped 27 single nucleotide polymorphisms, mapped to 22 key protein nodes of the cyclosporine pathway, via the utilization of the iPLEX®GOLD panel of the MassARRAY® System. Single-SNP analyses showed statistically significant associations between CALM1 rs12885713 (P = 0.0108) and MALT1 rs2874116 (P = 0.0006) polymorphisms with positive response to cyclosporine therapy after correction for multiple comparisons, with the haplotype analyses further enhancing the predictive value of rs12885713 as a pharmacogenetic biomarker for cyclosporine therapy (P = 0.0173). Our findings have the potential to improve our prediction of cyclosporine efficacy and safety in psoriasis patients, as well as provide the framework for the pharmacogenetics of biological therapies in complex diseases.
{"title":"Protein network and pathway analysis in a pharmacogenetic study of cyclosporine treatment response in Greek patients with psoriasis","authors":"Charalabos Antonatos, Aikaterini Patsatsi, Efterpi Zafiriou, Eleana F. Stavrou, Andreas Liaropoulos, Aikaterini Kyriakoy, Evangelos Evangelou, Danai Digka, Angeliki Roussaki-Schulze, Dimitris Sotiriadis, Sophia Georgiou, Katerina Grafanaki, Nicholas Κ. Moschonas, Yiannis Vasilopoulos","doi":"10.1038/s41397-022-00291-7","DOIUrl":"10.1038/s41397-022-00291-7","url":null,"abstract":"Although cyclosporine comprises a well-established systemic therapy for psoriasis, patients show important heterogeneity in their treatment response. The aim of our study was the pharmacogenetic analysis of 200 Greek patients with psoriasis based on the cyclosporine pathway related protein-protein interaction (PPI) network, reconstructed through the PICKLE meta-database. We genotyped 27 single nucleotide polymorphisms, mapped to 22 key protein nodes of the cyclosporine pathway, via the utilization of the iPLEX®GOLD panel of the MassARRAY® System. Single-SNP analyses showed statistically significant associations between CALM1 rs12885713 (P = 0.0108) and MALT1 rs2874116 (P = 0.0006) polymorphisms with positive response to cyclosporine therapy after correction for multiple comparisons, with the haplotype analyses further enhancing the predictive value of rs12885713 as a pharmacogenetic biomarker for cyclosporine therapy (P = 0.0173). Our findings have the potential to improve our prediction of cyclosporine efficacy and safety in psoriasis patients, as well as provide the framework for the pharmacogenetics of biological therapies in complex diseases.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"23 1","pages":"8-13"},"PeriodicalIF":2.8,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10850066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-28DOI: 10.1038/s41397-022-00289-1
Theodosia Charitou, Panagiota I. Kontou, Ioannis A. Tamposis, Georgios A. Pavlopoulos, Georgia G. Braliou, Pantelis G. Bagos
Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the gene-disease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient.
{"title":"Drug genetic associations with COVID-19 manifestations: a data mining and network biology approach","authors":"Theodosia Charitou, Panagiota I. Kontou, Ioannis A. Tamposis, Georgios A. Pavlopoulos, Georgia G. Braliou, Pantelis G. Bagos","doi":"10.1038/s41397-022-00289-1","DOIUrl":"10.1038/s41397-022-00289-1","url":null,"abstract":"Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the gene-disease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 5-6","pages":"294-302"},"PeriodicalIF":2.8,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9517961/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40379690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-28DOI: 10.1038/s41397-022-00287-3
Xiao Chen, Fei Shen, Nina Gonzaludo, Alka Malhotra, Cande Rogert, Ryan J. Taft, David R. Bentley, Michael A. Eberle
{"title":"Publisher Correction: Cyrius: accurate CYP2D6 genotyping using whole-genome sequencing data","authors":"Xiao Chen, Fei Shen, Nina Gonzaludo, Alka Malhotra, Cande Rogert, Ryan J. Taft, David R. Bentley, Michael A. Eberle","doi":"10.1038/s41397-022-00287-3","DOIUrl":"10.1038/s41397-022-00287-3","url":null,"abstract":"","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 5-6","pages":"308-308"},"PeriodicalIF":2.8,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674515/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40379691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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