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To study the mechanism of Cistanche deserticola in the treatment of colorectal cancer by network pharmacology. Methods: The chemical constituents of Cistanche deserticola and the related targets were screened by TCMSP. Gene Cards, OMIM, PharmGkb, GrugBank, and TTD databases were used to screen colorectal cancer-related targets. The network of “active components-targets” was constructed and the common targets were chosen as potentially therapeutic. The GO function enrichment analysis and KEGG pathway analysis were carried out for the target screening by the R package cluster profiler. Finally, Auto dock Vina was used to realize the molecular docking of core components and key targets. Results: There were 6 active compounds and 154 potential targets for Cistanche deserticola; 12877 targets for Colorectal cancer were obtained. There were 149 intersecting targets, which were enriched in multiple malignancies including colorectal cancer pathways. Conclusion: This study provides a scientific basis for explicating the potential of Cistanche deserticola in the treatment of colorectal cancer and establishing a foundation for further investigation of the role of its active components in cancer drug design.

Objective. To investigate the potential mechanism of action of Yi-Qi-Huo-Xue-Tong-Luo formula (YQHXTLF) in the treatment of diabetic peripheral neuropathy (DPN). Methods. Network pharmacology and molecular docking techniques were used in this study. Firstly, the active ingredients and the corresponding targets of YQHXTLF were retrieved using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) platform; subsequently, the targets related to DPN were retrieved using GeneCards, Online Mendelian Inheritance in Man (OMIM), Pharmgkb, Therapeutic Target Database (TTD) and Drugbank databases; the common targets of YQHXTLF and DPN were obtained by Venn diagram; afterwards, the “YQHXTLF Pharmacodynamic Component-DPN Target” regulatory network was visualized using Cytoscape 3.6.1 software, and Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the potential targets using R 3.6.3 software. Finally, molecular docking of the main chemical components in the PPI network with the core targets was verified by Autodock Vina software. Results. A total of 86 active ingredients and 229 targets in YQHXTLF were screened, and 81 active ingredients and 110 targets were identified to be closely related to diabetic peripheral neuropathy disease. PPI network mapping identified TP53, MAPK1, JUN, and STAT3 as possible core targets. KEGG pathway analysis showed that these targets are mostly involved in AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, and MAPK signaling pathway. The molecular docking results showed that the main chemical components of YQHXTLF have a stable binding activity to the core pivotal targets. Conclusion. YQHXTLF may act on TP53, MAPK1, JUN, and STAT3 to regulate inflammatory response, apoptosis, or proliferation as a molecular mechanism for the treatment of diabetic peripheral neuropathy, reflecting its multitarget and multipathway action, and providing new ideas to further uncover its pharmacological basis and mechanism of action.

Genetic variations have an established impact on the pharmacological response. Investigating this variation resulted in a compilation of variants in “pharmacogenes”. The emergence of next-generation sequencing facilitated large-scale pharmacogenomic studies and exhibited the extensive variability of pharmacogenes. Some rare and population-specific variants proved to be actionable, suggesting the significance of population pharmacogenomic research. A profound gap exists in the knowledge of pharmacogenomic variants enriched in some populations, including the United Arab Emirates (UAE). The current study aims to explore the landscape of variations in relevant pharmacogenes among healthy Emiratis. Through the resequencing of 100 pharmacogenes for 100 healthy Emiratis, we identified 1243 variants, of which 63% are rare (minor allele frequency ≤ 0.01), and 30% were unique. Filtering the variants according to Pharmacogenomics Knowledge Base (PharmGKB) annotations identified 27 diplotypes and 26 variants with an evident clinical relevance. Comparison with global data illustrated a significant deviation of allele frequencies in the UAE population. Understudied populations display a distinct allelic architecture and various rare and unique variants. We underscored pharmacogenes with the highest variation frequencies and provided investigators with a list of candidate genes for future studies. Population pharmacogenomic studies are imperative during the pursuit of global pharmacogenomics implementation.

Background and Purpose: There is an increasing number of evidence-based indications for pharmacogenetic (PGx) tests and a growing demand for PGx screening. We aimed to evaluate clinical relevance of a 16-gene panel test for PGx-guided pharmacotherapy. Experimental Approach: Observational cohort study of subjects tested with a PGx panel for variants of ABCB1, COMT, CYP1A2, CYP2B6, CYP3A4, CYP3A5, CYP2C9, CYP2C19, CYP2D6, CYP4F2, DPYD, OPRM1, POR, SLCO1B1, TPMT and VKORC1. Specialized clinical pharmacology consultations with PGx-guided pharmacotherapy management were supported by the PGx expert system SONOGEN XP. Study outcomes were PGx-based changes and recommendations regarding current and potential future medication. Key Results: PGx-testing was triggered by specific drug-gene pairs in 102 subjects, whereas screening was performed in 33. Based on PHARMGKB expert guidelines the 16-gene panel identified at least one “actionable” variant relevant for current or potential future medication in all 135 (100%) tested patients. Drugs that triggered PGx-testing were clopidogrel in 60, tamoxifen in 15, polypsychopharmacotherapy in 9, opioids in 7, and other in 11 patients. Among those, PGx variants resulted in clinical recommendations to change PGx-triggering drugs in 33 (32.4 %), and other current pharmacotherapy in 23 (22.5%). Conclusion and Implications: The 16-gene PGx panel detected clinically relevant variants in a high proportion of tested patients, and SONOGEN XP supported their interpretation based on latest evidence. Additional costs of panel vs. single gene tests are moderate, and the efficiency of PGx panel testing challenges traditional cost-benefit calculations for single drug-gene pairs. However, PGx-guided pharmacotherapy requires specialized consultations with interdisciplinary collaborations.

Background Explore the possible mechanism of anti-influenza virus, based on the study of the active components-drug-target network, Protein-Protein Interaction (PPI) network and molecular docking verification, we explored the potential action mechanism of TCM in Chinese protocol for diagnosis and treatment of influenza 2019. Methods Screening the active components and potential targets of 12 drugs in the scheme by using TCMSP database, and Obtaining the target of influenza by GeneCard, Durgbank, OMIM, TTD and PharmGkb databases. Then, constructed the “component-durg-target” network and PPI network were by Cytoscape3.8.0 software. Morethan, analyzed and the biological function and pathway, verified the molecular docking by AutoDock Vina software. Results The 12 drugs in the recommended scheme (XBCQ) for severe influenza contain 192 active components and involve 31 key antiviral targets, which may play an antiviral role through biological processes such as lipopolysaccharide, pathogen molecular reaction and regulate signaling pathway via the IL-17, influenza A, TNF, Toll-like receptors. Conclusion TCM play critical therapeutic roles through “multi-components, multi-targets and multi-pathways” mechanisms in influenza infection. The antiviral pharmacological mechanism of Xuanbai Chengqi decoction, which was analyzed by network pharmacology and molecular docking, provide a new idea for further exploring the diagnosis and treatment of severe influenza.

Background: Polycystic ovary syndrome (PCOS) is a disease that causes low fertility in females. Coptis chinensis (CC) has been used to clear away heat and dampness, purify fire, and detoxify in traditional Chinese medicine (TCM). Although CC has demonstrated efficacy against PCOS in clinical practice, there is no available data regarding the bioactive ingredients, component targets, and confirmed molecular mechanism of this drug combination.Methods: A network pharmacology approach was applied to analyze the bioactive ingredients, component targets, and core signaling pathways of CC. The TCM systems pharmacology database and analysis platform (TCMSP) was used to screen effective active ingredients and targets of CC. The GeneCards, OMIM, and PharmGkb databases was utilized to screen disease targets for PCOS. R language software was used to screen common targets of drugs and diseases. Cytoscape software (version 3.7.1) was utilized to build a drug-active ingredient-disease target interaction network, and the STRING platform was utilized to construct a common target protein-protein interaction network, including 102 nodes and 221 edges. OmicShare tools was used to analysis Gene ontology (GO) biological function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) path enrichment. Schrodinger software was used to evaluate the interaction between active components and their targets and explore binding modes.Results: 14 effective active ingredients and 218 targets of CC were screened by TCMSP platform. 3517 disease targets for PCOS were obtianed by the disease database and 102 common targets of drugs and diseases were screened through R language software. Key targets of CC for the treatment of PCOS included JUN, MAPK, IL-6, CXCL8, FOS, and IL1B. A total of 123 Gene Ontology (GO) terms and 129 pathways were acquired by analyzing the enrichment of GO and KEGG. It is speculated that the AGEs/RAGE, TNF, IL-17, MAPK and HIF-1 signaling pathways are closely related to PCOS and may be the core pathways involved in PCOS. The molecular docking results showed that quercetin has a higher degree of binding to core targets (eg: IL-6, IL- 1β, MAPK, CXCL8) related to the inflammatory pathway.Conclusions: This preliminary study verified the basic pharmacological effects and mechanisms of CC, a Chinese medicine, in the treatment of PCOS. Particularly, the effect of CC on inflammation and glucose metabolism pathway was noteworthy. This study provides new insights for the systematic exploration of the mechanism of action of Chinese medicine.

Purpose Pharmacogenomic biomarkers are increasingly listed on medication labels and authoritative guidelines but pharmacogenomic-guided prescribing is not yet common. Our objective was to assess the potential for incorporating knowledge of patients' genomic characteristics into prescribing practices. Methods We performed a retrospective analysis of claims data for 2,096,971 beneficiaries with pharmacy coverage from a national, commercial health insurance plan between January 2017 and December 2019. Children between 0 and 17 years comprised 21% of the cohort. Adults were age 18 to 64. Medications with actionable pharmacogenomic biomarkers (MAPBs) were identified using public information from the US Food and Drug Administration (FDA), Clinical Pharmacogenomics Implementation Consortium (CPIC), and PharmGKB. Results MAPBs were dispensed to 63% of the adults and 29% of the children in the cohort. Most frequently dispensed were ibuprofen, ondansetron, codeine, and oxycodone. Most common were medications with CYP2D6, G6PD, or CYPC19 pharmacogenomic biomarkers. Ten percent of the cohort were codispensed more than one MAPB for at least 30 days. Conclusion The number of people who might benefit from pharmacogenomic-guided prescribing is substantial. Future work should address obstacles to integrating genomic data into prescriber workflows, complex factors contributing to the magnitude of benefit, and the clinical availability of reliable on-demand or pre-emptive pharmacogenomic testing.

Background Yuzhi Zhixue Granule (YZG) is a traditional Chinese patent medicine for treating excessive menstrual flow caused by ovulatory dysfunctional uterine bleeding (ODUB) accompanied by heat syndrome. However, the underlying molecular mechanisms, potential targets, and active ingredients of this prescription are still unknown. Therefore, it is imperative to explore the molecular mechanism of YZG. Methods The active compounds in YZG were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The putative targets of YZG were collected via TCMSP and Search Tool for Interacting Chemicals (STITCH) databases. The Therapeutic Target Database (TTD) and Pharmacogenomics Knowledgebase (PharmGKB) databases were used to identify the therapeutic targets of ODUB. A protein–protein interaction (PPI) network containing both the putative targets of YZG and known therapeutic targets of ODUB was built. Furthermore, bioinformatics resources from the database for annotation, visualization and integrated discovery (DAVID) were utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking was performed to verify the binding effect between the YZG screened compounds and potential therapeutic target molecules. Results The study employed a network pharmacology method, mainly containing target prediction, network construction, functional enrichment analysis, and molecular docking to systematically research the mechanisms of YZG in treating ODUB. The putative targets of YZG that treat ODUB mainly involved PTGS1, PTGS2, ALOX5, CASP3, LTA4H, F7 and F10. The functional enrichment analysis suggested that the produced therapeutic effect of YZG against ODUB is mediated by synergistical regulation of several biological pathways, including apoptosis arachidonic acid (AA) metabolism, serotonergic synapse, complement and coagulation cascades and C-type lectin receptor signaling pathways. Molecular docking simulation revealed good binding affinity of the seven putative targets with the corresponding compounds. Conclusion This novel and scientific network pharmacology-based study holistically elucidated the basic pharmacological effects and the underlying mechanisms of YZG in the treatment of ODUB.

What is known and objective Pharmacogenomic biomarkers are now used in many clinical care settings and represent one of the successes of precision medicine. Genetic variants are associated with pharmacokinetic and pharmacodynamic changes leading to medication adverse effects and changes in clinical response. Actionable pharmacogenomic variants are common in transplant recipients and have implications for medications used in transplant, but yet are not broadly incorporated into practice. Methods From the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group guidelines, and PharmGKB databases, 12 pharmacogenomic genes with 30 variants were selected and used to create diplotypes and actionable pharmacogenomic phenotypes. A total of 853 kidney allograft recipients who had genomic information available from a genome-wide association study were included. Results Each recipient had at least one actionable pharmacogenomic diplotype/phenotype, whereas the majority (58%) had three or four actionable diplotypes/phenotypes and 17.4% had five or more among the 12 genes. The participants carried actionable diplotypes/phenotypes for multiple medications, including tacrolimus, azathioprine, clopidogrel, warfarin, simvastatin, voriconazole, antidepressants and proton-pump inhibitors. What is new and conclusion Pharmacogenomic variants are common in transplant recipients, and transplant recipients receive medications that have actionable variants. Clinical trial Genomics of Transplantation, clinicaltrials.gov (NCT01714440).

Background: Polypharmacy is most prevalent among the elderly population and in particular among nursing home residents. The frequency of the use of drugs with pharmacogenomics (PGx)-based dosing guidelines for CYP2D6, CYP2C9, CYP2C19 and SLCO1B1 were measured among nursing home residents in the Capital Region of Denmark as well as drug&ndash, drug interactions. The aim was to evaluate the potential of applying PGx-test as a supportive tool in medication reviews. Methods: Drug use among nursing home residents during 2017&ndash, 2018 in the Capital Region of Copenhagen, for drugs with PGx-based dosing guidelines available through the PharmGKB website, were measured. Drug&ndash, drug interactions were scored in severity by using drug interaction checkers. Results: The number of residents using drugs with PGx-based actionable dosing guidelines (AG) were 119 out of 141 residents (84.3%). Of these 119 residents, 87 residents used drugs with AG for CYP2C19, 47 residents for CYP2D6, and 42 residents for SLCO1B1. In addition, 30 residents used two drugs with an AG for CYP2C19, and for CYP2D6, it was only seven residents. The most used drugs with AG were clopidogrel (42), pantoprazole (32), simvastatin (30), metoprolol (25), and citalopram (24). The most frequent drug interactions found with warnings were combinations of proton pump inhibitors and clopidogrel underscoring the potential for phenoconversion. Conclusion: this study clearly showed that the majority of the nursing home residents were exposed to drugs or drug combinations for which there exist PGx-based AG. This indeed supports the notion of accessing and accounting for not only drug&ndash, gene but also drug&ndash, drug&ndash, gene interactions as a supplement to medication review.

Background Xianlinggubao formula (XLGB), a Chinese State Food and Drug Administration-permitted traditional Chinese herbal medicine, has been extensively used to treat osteoporosis. Although XLGB was shown to improve bone mass in ovariectomized rats and clinically alleviate osteoporosis symptoms, its pharmacological mechanisms remain unclear. Methods In this study, we used a network pharmacological approach to explore the potential mechanism of XLGB in treating osteoporosis. We obtained XLGB compounds from the TCMSP and TCMID databases and identified potential targets of these compounds through target fishing based on the TCMSP and Swiss Target Prediction databases. Next, we identified the osteoporosis targets by using the CTD, TTD, GeneCards, OMIM and PharmGKB databases. Then, the overlapping genes between the XLGB potential targets and the osteoporosis targets were used to establish a protein-protein interaction (PPI) network and to analyze their interactions and identify the major hub genes in this network. Subsequently, the Metascape database was utilized to conduct the enrichment of Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Results There were 104 active compounds and 295 related targets identified overall. After the Metascape enrichment analysis, we identified the top 25 cellular biological processes and top 15 pathways based on the logP value and found that the XLGB-mediated anti-osteoporosis effect was mainly associated with reactive oxygen species, organonitrogen compound response and cell migration. Furthermore, 36 hub genes of XLGB, such as EGF, EGFR, MTOR, MAPK14 and NFKB1, were considered potential therapeutic targets, suggesting the underlying mechanisms of XLGB acting on osteoporosis. Conclusion We investigated the possible therapeutic mechanisms of XLGB from a systemic perspective. These key targets and pathways provide promising directions for future research to reveal the exact regulatory mechanisms of XLGB.

Pharmacogenomics (PGx) is a key area of precision medicine, which is already being implemented in some health systems and may help guide clinicians toward effective therapies for individual patients. Over the last 2 decades, the Pharmacogenomics Knowledgebase (PharmGKB) has built a unique repository of PGx knowledge, including annotations of clinical guideline and regulator-approved drug labels in addition to evidence-based drug pathways and annotations of the scientific literature. All of this knowledge is freely accessible on the PharmGKB website. In the first of a series of PharmGKB tutorials, we introduce the PharmGKB coronavirus disease 2019 (COVID-19) portal and, using examples of drugs found in the portal, demonstrate some of the main features of PharmGKB. This paper is intended as a resource to help users become quickly acquainted with the wealth of information stored in PharmGKB.

Yinzhihuang granules (YZHG) is a patented Chinese medicine for the treatment of hepatitis B. This study aimed to investigate the intrinsic mechanisms of YZHG in the treatment of hepatitis B and to provide new evidence and insights for its clinical application. The chemical compounds of YZHG were searched in the CNKI and PUBMED databases, and their putative targets were then predicted through a search of the SuperPred and Swiss Target Prediction databases. In addition, the targets of hepatitis B were obtained from TTD, PharmGKB and DisGeNET. The abovementioned data were visualized using Cytoscape 3.7.1, and network construction identified a total of 13 potential targets of YZHG in the treatment of hepatitis B. Molecular docking verification showed that CDK6, CDK2, TP53 and BRCA1 might be strongly correlated with hepatitis B treatment. Furthermore, GO and KEGG analyses indicated that the treatment of hepatitis B by YZHG might be related to positive regulation of transcription, positive regulation of gene expression, the hepatitis B pathway and the viral carcinogenesis pathway. Network pharmacology intuitively shows the multicomponent, multitarget and multichannel pharmacological effects of YZHG in the treatment of hepatitis B and provides a scientific basis for its mechanism of action.

Recent advances in next-generation sequencing technology have led to the production of an unprecedented volume of genomic data, thus further advancing our understanding of the role of genetic variation in clinical pharmacogenomics. In the present study, we used whole exome sequencing data from 50,726 participants, as derived from the DiscovEHR cohort, to identify pharmacogenomic variants of potential clinical relevance, according to their occurrence within the PharmGKB database. We further assessed the distribution of the identified rare and common pharmacogenomics variants amongst different GnomAD subpopulations. Overall, our findings show that the use of publicly available sequence data, such as the DiscovEHR dataset and GnomAD, provides an opportunity for a deeper understanding of genetic variation in pharmacogenes with direct implications in clinical pharmacogenomics.

Objective: To demonstrate the types of clinical recommendations a pharmacogenomics pharmacist may make to medical clinicians with regard to medication management to improve therapeutic outcomes based on varied levels of medical literature evidence. Summary: This case demonstrates how a common type of patient seen in a pharmacist practice may present with a varied pharmacogenomic (PGx) profile, how they may benefit from PGx analysis, and how varying levels of medical literature evidence can be used with clinical decision making. Conclusion: PGx testing can help avoid adverse drug reactions (ADRs) or medication inefficacy by assisting in the adjustment of current or future medication doses. It can also help predict the best medications to use or those to avoid in advance by eliminating much of the existing dosing or medication selection method of trial and error. Article Type: Case Study

Background Shen Gui capsule (SGC) is a new national drug in China that is widely used in clinical practice and has significant therapeutic effects on coronary heart disease (CHD). However, its active ingredients and mechanism of action for treating coronary heart disease remain unknown. Therefore, the purpose of this paper is to systematically explore the mechanism and efficacy of SGC in the “multicomponent-multitarget- multipathway” treatment for CHD using network pharmacology technology. Methods The potential active ingredients of SGC were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and screened by pharmacokinetic parameters. Their possible targets were predicted using the TCMSP and DrugBank database. The CHD-related targets were identified from Comparative Toxicogenomics Database (CTD), UniProt, and PharmGKB database. The compound-target-disease network was constructed using Cytoscape for visualization. Additionally, the protein functional annotation and identification of signaling pathways of potential targets were performed by Gene Ontology (GO) and KEGG enrichment analysis using the Metascape platform. Results The 61 active ingredients of SGC were found to regulate neuroactive ligand-receptor interaction, fluid shear stress and atherosclerosis, estrogen signaling pathway and other pathways through 62 targets. SGC is involved in regulating the circulatory system, nervous system and immune system and other aspects of the body, and thus plays a significant role in the treatment of CHD and its complications, showing the mechanism of SGC's “multicomponent, multitarget, and multipathway” prevention and treatment of CHD. In addition, three predictive components were first found to have potential biological activity by this method. Conclusion The studies we have performed successfully predict the effective components and potential targets of SGC in the prevention and treatment of CHD, which helped to systematically clarify its mechanism of action and provided a direction for future research on the modern mechanism of SGC in the treatment of CHD.

The complexity of modern-day diseases often requires drug treatment therapies consisting of multiple pharmaceutical interventions, which can lead to adverse drug reactions for patients. A priori prediction of these reactions would not only improve the quality of life for patients but also save both time and money in regards to pharmaceutical research. Consequently, the drug-gene-pathway (DRUGPATH) meta-database was developed to map known interactions between drugs, genes, and pathways among other information in order to easily identify potential adverse drug events. DRUGPATH utilizes expert-curated sources such as PharmGKB, DrugBank, and the FDA&rsquo, s NDC database to identify known as well as previously unknown/overlooked relationships, and currently contains 12,940 unique drugs, 3933 unique pathways, 5185 unique targets, and 3662 unique genes. Moreover, there are 59,561 unique drug-gene interactions, 77,808 unique gene-pathway interactions, and over 1 million unique drug-pathway interactions.

Background: The cytochrome P450 drug metabolizing enzymes CYP2D6 and CYP2C19 are the major targets for pharmacogenomics (PGx) testing and determining for drug response. Clinical dosing guidelines for specific drug-gene interactions (DGI) are publicly available through PharmGKB. The aim of this register study was to map the use of drugs in Denmark for drugs having actionable dosing guidelines (AG) i.e., dosing recommendations different from standard dosing for CYP2D6 or CYP2C19 DGI in terms of consumption. Methods: The Danish Register of Medicinal Product Statistics was the source to retrieve consumption in Defined Daily Dose (DDD) i.e., the assumed average maintenance dose per day for a drug used for its main indication in adults and number of users (2017 data). Clinical dosing guidelines were available from the PharmGKB website. Results: Forty-nine drugs have guidelines corresponding to 14.5% of total sales in DDD. Twenty-eight drugs have AG corresponding to 375.2 million DDD. Pantoprazole, lansoprazole, omeprazole, clopidogrel, and metoprolol constituted fifty-eight percent of the consumption in DDD of drugs having AG. The consumption of antidepressant drugs, opioids, and antipsychotic drugs were 157.0 million DDD, with 441,850 users, 48.9 million DDD, with 427,765 users, and 23.7 million DDD, with 128,935 users, respectively. Age distributions of consumption of drugs and drug combinations, e.g., for sertraline redeemed either alone or in combination with metoprolol and tramadol, are presented. Conclusion: This exploratory register study clearly showed that a large fraction of the Danish population, especially the elderly, are exposed to drugs or drug combinations for which there exist AG related to PGx of CYP2D6 or CYP2C19.

Background Pharmacogenomics plays a crucial role in individualized therapy, but the variant information of pharmacogenomics in the Dai population is limited. We therefore aimed to screen very important pharmacogenetic (VIP) in the Dai population and compared differences between Dai and other 25 populations. Methods In this study, we genotyped 73 VIP variants from the PharmGKB and compared genotype distribution of variants in Dai with other 25 populations by χ2 test. To assess the genetic relationship among 26 populations, we performed the structure analysis. In addition, pair‐wise F‐statistics (Fst) was calculated to measure the population differentiation. Results We found 12, 10, 13, 17, 11, 39, 46, 46, 45, 43, 49, 46, 46, 46, 49, 45, 41, 42, 48, 53, 45, 50, 50, 51, 47, and 50 significantly different variants in Dai compared with other 25 populations. Genetic structure analysis showed Dai had close relationships with CDX (Chinese Dai in Xishuangbanna), CHB (Han Chinese in Beijing), JPT (Japanese in Tokyo), and KHV (Kinh in Ho Chi Minh City, Vietnam). Moreover, Dai is the most similar to KHV according to Fst analysis. Conclusions Our study complement the pharmacogenomics information of Dai population from Yunnan province and provide a theoretical basis for personalized medicine.

The purpose of this study is to provide the researchers with the bigger academic network for the understanding of the incorporated proof about current pharmacogenomics information on pediatric oncology and hematology. This primary assessment will help and guide the researchers and clinicians by giving a thought about the current situation of research, as far as customizing drug for kids with malignant growth (cancer). This study also describes the gene-drug associations with substantial and adequate power of association put forward by PharmGKB (Pharmacogenomics Knowledgebase). Some drugs with strong pharmacogenetic evidence like thiopurines and some with moderate pharmacogenetic evidence like vincristine are also discussed. Upcoming suggestions to achieve this objective will help to put forward the recommendations. Pharmacogenetic gene-drug link studies, thus, influence the reconsidering of study plans to produce sensible results. Genetic roots of oxidative force reaction or genome stability disturbing reaction were categorized as association with moderate evidence but have not yet been tested in children.

Background. Mahai capsules (MHC) have been deemed to be an effective herb combination for treatment of cardiovascular diseases (CVD) development and improvement of the life quality of CVD patients. To systematically explore the mechanisms of MHC in CVD, a network pharmacology approach mainly comprising target prediction, network construction, biological process and pathway analysis, and related diseases was adopted in this study. Methods. We collected the bioactive compounds and potential targets of MHC through the TCMSP servers. Candidate targets related to CVD were collected from Therapeutic Targets Database and PharmGkb database and analyzed using ClueGO plugin in Cytoscape. KEGG pathway was enriched and analyzed through the EnrichR platform, and protein-protein interaction networks were calculated by STRING platform. The compound-target, target-disease, and compound-target-disease networks were constructed using Cytoscape. Results. A total of 303 targets of the 57 active ingredients in MHC were obtained. The network analysis showed that PTGS2, PTGS1, HSP90, Scn1a, estrogen receptor, calmodulin, and thrombin were identified as key targets of MHC in the treatment of CVD. The functional enrichment analysis indicated that MHC probably produced the therapeutic effects against CVD by synergistically regulating many biological pathways, such as PI3K-Akt, TNF, HIF-1, FoxO, apoptosis, calcium, T-cell receptor, VEGF, and NF-kappa B signaling pathway. Conclusions. In summary, the analysis of the complete profile of the pharmacological properties, as well as the elucidation of targets, networks, and pathways, can further illuminate that the underlying mechanisms of MHC in CVD might be strongly associated with its synergic regulation of inflammation, apoptosis, and immune function, and provide new clues for its future development of therapeutic strategies and basic research.

Using pharmacogenetics in guiding drug therapy experiences a steady increase in uptake, although still leads to discussions as to its clinical use. Psychiatry constitutes a field where pharmacogenomic testing might help in guiding drug therapy. To address current challenges, this minireview provides an update regarding genotyping (SNP analysis/arrays/NGS), structural variant detection (star-alleles/CNVs/hybrid alleles), genotype-to-phenotype translations, cost-effectiveness, and actionability of results (FDA/CPIC/PharmGKB) regarding clinical importance of pre-emptive pharmacogenomic testing for prescription of antidepressants and antipsychotics.

Organ transplantation has become a powerful strategy for the treatment of malignant diseases. Nevertheless, graft rejection is one of the main factors affecting graft survival after organ transplantation. Under this circumstance, the transplant-related mortality still keeps up. This invention includes the precise medication guidance of Tacrolimus (FK506) inapplicable population, against the side-effects of this drug. This invention, based on second-generation sequencing, has the advantages of relatively low cost and high sequencing throughput. During the design process, we collect the data of single nucleotide polymorphism (SNP) concerning the adverse drug reactions of Tacrolimus. Then we filter and summarize fifteen SNPs basing on importance degree (level >key enzyme>race). Thenceforth, after the process of analyzing the raw extract by operating BWA, Picard-tools, GATK, and Perl, we annotate SNPs by Annovar. Through this innovation, people can obtain further feedback on drugs that targets different genes in order to achieve the purpose of precision medication and minimizing the risks of misusing Tacrolimus. panel design database selection path pharmgkb pubred drugbank SNPs Level Level1,2,3 filtering conduit Key Enzyme V Key Enzyme ENDe Eastern Asian Figure

Pharmacogenetic analysis has generated translational data that could be applied to guide treatments according to individual genetic variations. However, pharmacogenetic counseling in some mestizo (admixed) populations may require tailoring to different patterns of admixture. The identification and clustering of individuals with related admixture patterns in such populations could help to refine the practice of pharmacogenetic counseling. This study identifies related groups in a highly admixed population-based sample from Mexico, and analyzes the differential distribution of actionable pharmacogenetic variants. A subsample of 1728 individuals from the Mexican Genomic Database for Addiction Research (MxGDAR/Encodat) was analyzed. Genotyping was performed with the commercial PsychArray BeadChip, genome-wide ancestry was estimated using EIGENSOFT, and model-based clustering was applied to defined admixture groups. Actionable pharmacogenetic variants were identified with a query to the Pharmacogenomics Knowledge Base (PharmGKB) database, and functional prediction using the Variant Effect Predictor (VEP). Allele frequencies were compared with chi-square tests and differentiation was estimated by FST. Seven admixture groups were identified in Mexico. Some, like Group 1, Group 4, and Group 5, were found exclusively in certain geographic areas. More than 90% of the individuals, in some groups (Group 1, Group 4 and Group 5) were found in the Central-East and Southeast region of the country. MTRR p.I49M, ABCG2 p.Q141K, CHRNA5 p.D398N, SLCO2B1 rs2851069 show a low degree of differentiation between admixture groups. ANKK1 p.G318R and p.H90R, had the lowest allele frequency of Group 1. The reduction in these alleles reduces the risk of toxicity from anticancer and antihypercholesterolemic drugs. Our analysis identified different admixture patterns and described how they could be used to refine the practice of pharmacogenetic counseling for this admixed population.

Successfully implementing pharmacogenomics into routine clinical practice requires an efficient process to order genetic tests and report the results to clinicians and patients. Lack of standardized approaches and terminology in clinical laboratory processes, ordering of the test and reporting of test results all impede this workflow. Expert groups such as the Association for Molecular Pathology and the Clinical Pharmacogenetics Implementation Consortium have published recommendations for standardizing laboratory genetic testing, reporting and terminology. Other resources such as PharmGKB, ClinVar, ClinGen and PharmVar have established databases of nomenclature for pharmacogenetic alleles and variants. Opportunities remain to develop new standards and further disseminate existing standards which will accelerate the implementation of pharmacogenomics.

Understanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue‐naïve assumptions. Many target proteins, however, have tissue‐specific expression. A systematic study connecting drugs to target pathways in in vivo human tissues is needed. We introduced a data‐driven method that integrates drug‐target relationships with gene expression, protein‐protein interaction, and pathway annotation data. We applied our method to four independent genomewide expression datasets and built 467,396 connections between 1,034 drugs and 954 pathways in 259 human tissues or cell lines. We validated our results using data from L1000 and Pharmacogenomics Knowledgebase (PharmGKB), and observed high precision and recall. We predicted and tested anticoagulant effects of 22 compounds experimentally that were previously unknown, and used clinical data to validate these effects retrospectively. Our systematic study provides a better understanding of the cellular response to drugs and can be applied to many research topics in systems pharmacology.

Hair provides a direct measure of long-term exposure of atazanavir (ATV). We report the results of the first genome-wide association study (GWAS) of ATV exposure measured in hair in an observational cohort representative of US women living with HIV; the Women's Interagency HIV Study. Approximately 14.1 million single nucleotide polymorphisms (SNPs) were analyzed in linear regression-based GWAS, with replication, adjusted for nongenetic predictors collected under conditions of actual use of ATV in 398 participants. Lastly, the PharmGKB database was used to identify pharmacogene associations with ATV exposure. The rs73208473, within intron 1 of SORCS2, resulted in a 0.46-fold decrease in ATV exposure, with the strongest association (P=1.71×10-8) in GWAS. A priori pharmacogene screening did not identify additional variants statistically significantly associated with ATV exposure, including those previously published in ATV plasma candidate pharmacogene studies. The findings demonstrate the potential value of pharmacogenomic GWAS in ethnically diverse populations under conditions of actual use.

With rapid developments of pharmacogenomics (PGx) and regulatory science, it is important to understand the current PGx integration in product life cycle, impact on clinical practice thus far and opportunities ahead. We conducted a cross-sectional review on PGx-related regulatory documents and implementation guidelines in the United States and Europe. Our review found that although PGx-related guidance in both markets span across the entire product life cycle, the scope of implementation guidelines varies across two continents. Approximately one-third of Food and Drug Administration (FDA)-approved drugs with PGx information in drug labels and half of the European labels posted on PharmGKB website contain recommendations on genetic testing. The drugs affected 19 and 15 World Health Organization Anatomical Therapeutic Chemical drug classes (fourth level) in the United States and Europe, respectively, with protein kinase inhibitors (13 drugs in the United States and 16 drugs in Europe) being most prevalent. Topics of emerging interest were novel technologies, adaptive design in clinical trial and sample collection.