Ann Fam Med. 2023 Jan 1;(21 Suppl 1). doi: 10.1370/afm.21.s1.3642.

ABSTRACT

Context: Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines exist for many medications commonly prescribed prior to hospital discharge, yet there is limited data regarding the contribution of gene-x-drug interactions to hospital readmissions. Objective: The present study evaluated the relationship between prescription of CPIC medications prescribed within 30 days of hospital admission and 90-day hospital readmission from 2010-2020. Study Design and Analysis: Retrospective cohort study. Multivariable logistic regression analyzed the association between one or more gene-x-drug interactions with 90-day readmission. Population Studied: Primary care patients (N=10,104) who underwent sequencing with a 14-gene pharmacogenetic panel. Intervention/Instrument: Primary care physicians ordered a Color genetic panel that included pharmacogenetic genes reported through electronic health records. Outcome Measures: The primary endpoint was 90-day hospital readmission. The presence of at least one pharmacogenetic indicator for a medication prescribed within 30 days of hospital admission was considered a gene-x-drug interaction. Results: There were 2,211/2,354 (93.9%) admitted patients who were prescribed at least one CPIC medication. Univariate analyses indicated that the presence of at least one identified gene-x-drug interaction increased risk of 90-day readmission by more than 40% (OR=1.42, 95% confidence interval (CI) 1.09-1.84)(p=0.01). A multivariable model adjusting for age, race, sex, employment status, body mass index, and medical conditions, slightly attenuated the effect (OR=1.32, 95% CI 1.02-1.73)(p=0.04). Conclusions: Our results suggest that the presence of one or more CPIC gene-x-drug interactions increases the risk of 90-day hospital readmission, even after adjustment for demographic and clinical risk factors.

PMID:36944076 | DOI:10.1370/afm.21.s1.3642

Microbiol Spectr. 2023 Mar 21:e0487022. doi: 10.1128/spectrum.04870-22. Online ahead of print.

ABSTRACT

In order to ensure the prevention and control of methicillin-resistant Staphylococcus aureus (MRSA) infection, rapid and accurate detection of pathogens and their resistance phenotypes is a must. Therefore, this study aimed to develop a fast and precise nucleic acid detection platform for identifying S. aureus and MRSA. We initially constructed a CRISPR-Cas12a detection system by designing single guide RNAs (sgRNAs) specifically targeting the thermonuclease (nuc) and mecA genes. To increase the sensitivity of the CRISPR-Cas12a system, we incorporated PCR, loop-mediated isothermal amplification (LAMP), and recombinase polymerase amplification (RPA). Subsequently, we compared the sensitivity and specificity of the three amplification methods paired with the CRISPR-Cas12a system. Finally, the clinical performance of the methods was tested by analyzing the fluorescence readout of 111 clinical isolates. In order to visualize the results, lateral-flow test strip technology, which enables point-of-care testing, was also utilized. After comparing the sensitivity and specificity of three different methods, we determined that the nuc-LAMP-Cas12a and mecA-LAMP-Cas12a methods were the optimal detection methods. The nuc-LAMP-Cas12a platform showed a limit of detection (LOD) of 10 aM (~6 copies μL-1), while the mecA-LAMP-Cas12a platform demonstrated a LOD of 1 aM (~1 copy μL-1). The LOD of both platforms reached 4 × 103 fg/μL of genomic DNA. Critical evaluation of their efficiencies on 111 clinical bacterial isolates showed that they were 100% specific and 100% sensitive with both the fluorescence readout and the lateral-flow readout. Total detection time for the present assay was approximately 80 min (based on fluorescence readout) or 85 min (based on strip readout). These results indicated that the nuc-LAMP-Cas12a and mecA-LAMP-Cas12a platforms are promising tools for the rapid and accurate identification of S. aureus and MRSA. IMPORTANCE The spread of methicillin-resistant Staphylococcus aureus (MRSA) poses a major threat to global health. Isothermal amplification combined with the trans-cleavage activity of Cas12a has been exploited to generate diagnostic platforms for pathogen detection. Here, we describe the design and clinical evaluation of two highly sensitive and specific platforms, nuc-LAMP-Cas12a and mecA-LAMP-Cas12a, for the detection of S. aureus and MRSA in 111 clinical bacterial isolates. With a limit of detection (LOD) of 4 × 103 fg/μL of genomic DNA and a turnaround time of 80 to 85 min, the present assay was 100% specific and 100% sensitive using either fluorescence or the lateral-flow readout. The present assay promises clinical application for rapid and accurate identification of S. aureus and MRSA in limited-resource settings or at the point of care. Beyond S. aureus and MRSA, similar CRISPR diagnostic platforms will find widespread use in the detection of various infectious diseases, malignancies, pharmacogenetics, food contamination, and gene mutations.

PMID:36943040 | DOI:10.1128/spectrum.04870-22

Radiol Oncol. 2023 Mar 22;57(1):111-120. doi: 10.2478/raon-2023-0003. eCollection 2023 Mar 1.

ABSTRACT

BACKGROUND: Tramadol is an opioid analgesic often used for pain management after breast cancer surgery. Its analgesic activity is due to the activation of the μ-opioid receptor, encoded by the OPRM1 gene. This study investigated the association of genetic variability in OPRM1 and its regulatory miRNA genes with outcomes of tramadol/paracetamol treatment after breast cancer surgery with axillary lymphadenectomy.

PATIENTS AND METHODS: The study included 113 breast cancer patients after breast cancer surgery with axillary lymphadenectomy treated with either 75/650 mg or 37.5/325 mg of tramadol with paracetamol for pain relief within the randomized clinical trial KCT 04/2015-DORETAonko/si at the Institute of Oncology Ljubljana. All patients were genotyped for OPRM1 rs1799971 and rs677830, MIR23B rs1011784, and MIR107 rs2296616 using competitive allele-specific PCR. The association of genetic factors with acute and chronic pain as well as adverse effects of tramadol treatment was evaluated using logistic regression, Fisher's exact test, and Mann-Whitney test.

RESULTS: The investigated OPRM1 related polymorphisms were not associated with acute pain assessed with the VAS scale within four weeks after surgery (all P > 0.05). Carriers of at least one polymorphic OPRM1 rs1799971 allele had a higher risk of constipation in the first four weeks after surgery compared to non-carriers (OR = 4.5, 95% CI = 1.6-12.64, P = 0.004). Carriers of at least one polymorphic OPRM1 rs677830 allele had a higher risk of constipation after third week of tramadol treatment (OR = 3.11, 95% CI = 1.08-8.89, P = 0.035). Furthermore, carriers of two polymorphic MIR23B rs1011784 alleles had a higher risk of nausea after 28 days of tramadol treatment (OR = 7.35, 95% CI = 1.27-42.6, P = 0.026), while heterozygotes for MIR107 rs2296616 allele had a lower risk of nausea after 21 days of tramadol treatment (OR = 0.21, 95% CI = 0.05-0.87, P = 0.031). In carriers of two polymorphic MIR107 rs2296616 alleles, chronic pain was significantly more common than in carriers of two wild-type alleles (P = 0.004). Carriers of at least one polymorphic MIR23B rs1011784 allele experienced more neuropathic pain after adjustment for tramadol dose (OR = 2.85, 95% CI = 1.07-7.59, P = 0.036), while carriers of at least one polymorphic OPRM1 rs677830 allele experienced less neuropathic pain compared to carriers of two wild-type alleles (OR = 0.38, 95% CI = 0.15-0.99, P = 0.047).

CONCLUSIONS: Genetic variability of OPRM1 and genes coding for miRNAs that could affect OPRM1 expression may be associated with adverse effects of tramadol/paracetamol treatment as well as with chronic and neuropathic pain after breast cancer surgery with axillary lymphadenectomy.

PMID:36942908 | DOI:10.2478/raon-2023-0003

J Pharm Pharm Sci. 2023 Jan 30;26:11136. doi: 10.3389/jpps.2023.11136. eCollection 2023.

ABSTRACT

Purpose: To investigate whether interindividual variability in the CYP2C9 (*2 and *3 alleles) and VKORC1 (rs9923231) genes is associated with increased risk of upper gastrointestinal bleeding (UGIB) in users of non-steroidal anti-inflammatory drugs (NSAIDs) or low-dose aspirin (LDA). Methods: A full case-control study including 200 cases of patients diagnosed with UGIB and 706 controls was conducted in a Brazilian hospital complex. To perform an analysis of NSAIDs dose-effect, the defined daily dose (DDD) for NSAIDs was calculated in the 7-day etiologic window preceding the data index. Three categories of DDD, considering the genotypes of the genetic variants, were established: non-users of NSAIDs (DDD = 0), DDD ≤0.5, and DDD >0.5. Genetic variants and LDA or NSAIDs use synergism was estimated through Synergism Index (SI) and Relative Excess Risk Due To Interaction (RERI). Results: For DDDs of NSAIDs upward of 0.50, a risk of UGIB was identified in carriers of the *3 allele (OR: 15,650, 95% CI: 1.41-174.10) and in carriers of the variant homozygous genotype (TT) of rs9923231 (OR: 38,850, 95% CI: 2.70-556.00). In LDA users, the risk of UGIB was observed to be similar between carriers of the wild type homozygous genotype and carriers of the variant alleles for the CYP2C9 and VKORC1 genes. No synergism was identified. Conclusion: Our findings suggest an increased risk of UGIB in carriers of the variant allele of rs9923231 and in carriers of the *3 allele associated with doses of NSAIDs greater than 0.5. Hence, the assessment of these variants might reduce the incidence of NSAIDs-related UGIB and contribute to the safety of the NSAIDs user.

PMID:36942299 | PMC:PMC9990631 | DOI:10.3389/jpps.2023.11136

Ann Rheum Dis. 2023 Mar 20:ard-2022-223618. doi: 10.1136/ard-2022-223618. Online ahead of print.

ABSTRACT

OBJECTIVES: Teriparatide (TPTD) is an effective treatment for osteoporosis but the individual response to therapy is variable for reasons that are unclear. This study aimed to determine whether the response to TPTD might be influenced by genetic factors.

METHODS: We searched for predictors of the response of bone mineral density (BMD) to TPTD using a two-stage genome-wide association study in 437 patients with osteoporosis from three referral centres. Demographic and clinical data including the response of BMD to treatment at the lumbar spine and hip were extracted from the medical records of each participant.

RESULTS: Allelic variation at rs6430612 on chromosome 2, close to the CXCR4 gene was associated with the response of spine BMD to TPTD at a genome wide significant level (p=9.2×10-9 beta=-0.35 (-0.47 to -0.23)). The increase in BMD was almost twice as great in AA homozygotes at rs6430612 as compared with GG homozygotes with intermediate values in heterozygotes. The same variant was also associated with response of femoral neck and total hip BMD (p=0.007). An additional locus on chromosome 19 tagged by rs73056959 was associated with the response of femoral neck BMD to TPTD (p=3.5×10-9, beta=-1.61 (-2.14 to -1.07)).

CONCLUSIONS: Genetic factors influence the response to TPTD at the lumbar spine and hip with a magnitude of effect that is clinically relevant. Further studies are required to identify the causal genetic variants and underlying mechanisms as well as to explore how genetic testing for these variants might be implemented in clinical practice.

PMID:36941031 | DOI:10.1136/ard-2022-223618

Neurol Sci. 2023 Mar 20. doi: 10.1007/s10072-023-06758-0. Online ahead of print.

ABSTRACT

BACKGROUND: The Cluster Headache Impact Questionnaire (CHIQ) is a specific and easy-to-use questionnaire to assess the current impact of cluster headache (CH). The aim of this study was to validate the Italian version of the CHIQ.

METHODS: We included patients diagnosed with episodic CH (eCH) or chronic CH (cCH) according to the ICHD-3 criteria and included in the "Italian Headache Registry" (RICe). The questionnaire was administered to patients through an electronic form in two sessions: at first visit for validation, and after 7 days for test-retest reliability. For internal consistency, Cronbach's alpha was calculated. Convergent validity of the CHIQ with CH features and the results of questionnaires assessing anxiety, depression, stress, and quality of life was evaluated using Spearman's correlation coefficient.

RESULTS: We included 181 patients subdivided in 96 patients with active eCH, 14 with cCH, and 71 with eCH in remission. The 110 patients with either active eCH or cCH were included in the validation cohort; only 24 patients with CH were characterized by a stable attack frequency after 7 days, and were included in the test-retest cohort. Internal consistency of the CHIQ was good with a Cronbach alpha value of 0.891. The CHIQ score showed a significant positive correlation with anxiety, depression, and stress scores, while showing a significant negative correlation with quality-of-life scale scores.

CONCLUSION: Our data show the validity of the Italian version of the CHIQ, which represents a suitable tool for evaluating the social and psychological impact of CH in clinical practice and research.

PMID:36939946 | DOI:10.1007/s10072-023-06758-0

Front Pharmacol. 2023 Feb 27;14:1130100. doi: 10.3389/fphar.2023.1130100. eCollection 2023.

ABSTRACT

Pharmacokinetics varies widely between children. Many factors play an important role in this variability, such as ontogeny, pharmacogenetics, gender, comorbidities, and drug-drug interactions. Significant work has already been done in adults to understand the impact of genetic polymorphisms on drug-metabolizing enzyme activity and drug response. Data remain poor in children due to ontogeny that impacts genotyping-phenotyping correlation and the difficulty enrolling children in prospective studies. Our study aimed to describe the use of cytochromes P450 (CYP) phenotyping and/or genotyping tests in children in a real-life setting and assess the correlation between the genotype and the phenotype. We reviewed the results of tests performed between January 2005 and December 2020. Fifty-two children were genotyped and/or phenotyped. Four patients were excluded from the present analysis as they only underwent ABCB1 genotyping, without CYP testing. Of the remainder, 18 underwent simultaneous CYP genotyping and phenotyping, while 17 underwent CYP genotyping only, and 13 underwent CYP phenotyping only. In all cases, investigations were performed after the following situations: insufficient clinical response to treatment, low plasma concentrations, and adverse drug reactions (ADR). The vast majority of cases were related to immunosuppressive or antipsychotic therapy. Genotyping and/or phenotyping explained or contributed to the aforementioned clinical events in 56% of cases. The correlation between the genotype and the phenotype showed variability depending on the assessed cytochrome. In several cases, the phenotype did not correspond to the genotype because of comedications. In conclusion, there is clearly value in guiding drug based on CYP activity in children.

PMID:36937881 | PMC:PMC10022732 | DOI:10.3389/fphar.2023.1130100

Front Pharmacol. 2023 Mar 1;14:1076574. doi: 10.3389/fphar.2023.1076574. eCollection 2023.

ABSTRACT

Background: Inter-individual differences in drug response based on genetic variations can lead to drug toxicity and treatment inefficacy. A large part of this variability is caused by genetic variants in pharmacogenes. Unfortunately, the Single Nucleotide Variant arrays currently used in clinical pharmacogenomic (PGx) testing are unable to detect all genetic variability in these genes. Long-read sequencing, on the other hand, has been shown to be able to resolve complex (pharmaco) genes. In this study we aimed to assess the value of long-read sequencing for research and clinical PGx focusing on the important and highly polymorphic CYP2C19 gene. Methods and Results: With a capture-based long-read sequencing panel we were able to characterize the entire region and assign variants to their allele of origin (phasing), resulting in the identification of 813 unique variants in 37 samples. To assess the clinical utility of this data we have compared the performance of three different *-allele tools (Aldy, PharmCat and PharmaKU) which are specifically designed to assign haplotypes to pharmacogenes based on all input variants. Conclusion: We conclude that long-read sequencing can improve our ability to characterize the CYP2C19 locus, help to identify novel haplotypes and that *-allele tools are a useful asset in phenotype prediction. Ultimately, this approach could help to better predict an individual's drug response and improve therapy outcomes. However, the added value in clinical PGx might currently be limited.

PMID:36937863 | PMC:PMC10014917 | DOI:10.3389/fphar.2023.1076574

Front Pharmacol. 2023 Mar 3;14:1172265. doi: 10.3389/fphar.2023.1172265. eCollection 2023.

NO ABSTRACT

PMID:36937855 | PMC:PMC10020586 | DOI:10.3389/fphar.2023.1172265

Quant Biol. 2022 Dec;10(4):307-320.

ABSTRACT

BACKGROUND: Pooled CRISPR screen is a promising tool in drug targets or essential genes identification with the utilization of three different systems including CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa). Aside from continuous improvements in technology, more and more bioinformatics methods have been developed to analyze the data obtained by CRISPR screens which facilitate better understanding of physiological effects.

RESULTS: Here, we provide an overview on the application of CRISPR screens and bioinformatics approaches to analyzing different types of CRISPR screen data. We also discuss mechanisms and underlying challenges for the analysis of dropout screens, sorting-based screens and single-cell screens.

CONCLUSION: Different analysis approaches should be chosen based on the design of screens. This review will help community to better design novel algorithms and provide suggestions for wet-lab researchers to choose from different analysis methods.

PMID:36937794 | PMC:PMC10019185

Front Psychiatry. 2023 Mar 2;14:1159000. doi: 10.3389/fpsyt.2023.1159000. eCollection 2023.

NO ABSTRACT

PMID:36937716 | PMC:PMC10018804 | DOI:10.3389/fpsyt.2023.1159000

Front Genet. 2023 Mar 1;14:1124439. doi: 10.3389/fgene.2023.1124439. eCollection 2023.

ABSTRACT

Introduction: A copper-dependent cell death, cuproptosis, involves copper binding with lipoylated tricarboxylic acid (TCA) cycle components. In cuproptosis, ferredoxin 1 (FDX1) and lipoylation act as key regulators. The mechanism of cuproptosis differs from the current knowledge of cell death, which may invigorate investigations into copper's potential as a cancer treatment. An extremely dismal prognosis is associated with gliomas, the most prevalent primary intracranial tumor. In patients with glioma, conventional therapies, such as surgery and chemotherapy, have shown limited improvement. A variety of cell death modes have been confirmed to be operative in glioma oncogenesis and participate in the tumor microenvironment (TME), implicated in glioma development and progression. In this study, we aimed to explore whether cuproptosis influences glioma oncogenesis. Methods: Gene expression profiles related to cuproptosis were comprehensively evaluated by comparing adjacent tissues from glioma tissues in The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) database. Gene expression, prognostic, clinical, and pathological data of lower-grade gliomas (LGG) and glioblastoma were retrieved from TCGA and Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. The datasets were managed by "Combat" algorithm to eliminate batch effects and then combined. A consensus clustering algorithm based on the Partitioning Around Medoid (PAM) algorithm was used to classified 725 patients with LGG and glioblastoma multiforme (GBM) into two cuproptosis subtypes. According to the differentially expressed genes in the two cuproptosis subtypes, 725 patients were divided into 2 gene subtypes. Additionally, a scoring system that associated with TME was constructed to predict patient survival and patient immunotherapy outcomes. Furthermore, we constructed a prognostic CRG-score and nomogram system to predict the prognosis of glioma patients. 95 tissue specimens from 83 glioma patients undergoing surgical treatment were collected, including adjacent tissues. Using immunohistochemistry and RT-qPCR, we verified cuproptosis-related genes expression and CRG-score predictive ability in these clinical samples. Results: Our results revealed extensive regulatory mechanisms of cuproptosis-related genes in the cell cycle, TME, clinicopathological characteristics, and prognosis of glioma. We also developed a prognostic model based on cuproptosis. Through the verifications of database and clinical samples, we believe that cuproptosis affects the prognosis of glioma and potentially provides novel glioma research approaches. Conclusion: We suggest that cuproptosis has potential importance in treating gliomas and could be utilized in new glioma research efforts.

PMID:36936439 | PMC:PMC10014798 | DOI:10.3389/fgene.2023.1124439

Korean J Anesthesiol. 2022 Dec 5. doi: 10.4097/kja.22654. Online ahead of print.

ABSTRACT

Responses to sedatives, analgesics and muscle relaxants vary among patients under general anesthesia, which could be ascribed to the disparities of clinical characteristics and genetic factors of individuals. Accumulating researches have indicated that gene polymorphisms of the receptors, transporters and metabolizing enzymes associated with anesthetics play a considerable role in their efficacy. However, a systematically summarized study on the mechanisms of gene polymorphisms on pharmacodynamics and pharmacokinetics of anesthetics is still lacking. In this paper, the recent researches on pharmacogenomics of sedatives, analgesics and muscle relaxants are comprehensively reviewed, and the contributions and mechanisms of polymorphisms to the differences of individual efficacy of these drugs are discussed, so as to provide guidance for the formulation of a rational anesthesia regimen for patients with various genotypes.

PMID:36935389 | DOI:10.4097/kja.22654

Funct Integr Genomics. 2023 Mar 17;23(2):85. doi: 10.1007/s10142-023-01021-3.

ABSTRACT

Pharmacogenomics has been widely used to study the very important pharmacogenetic (VIP) variants among different populations. However, there is little pharmacogenomic information about the Chinese Hui population. Our research aimed to reveal the outstandingly different loci in the Hui population, and provide a theoretical foundation for personalized drug use in the Hui population, so as to facilitate more effective treatment of diseases. This study genotyped 53 VIP variants of 26 genes in 200 independent Hui individuals based on the Pharmacogenetics and Pharmacogenomics Knowledge Base (PharmGKB). Remarkable differences in the genotype and allele frequencies between the Hui and 26 other populations from the 1000 Genomes Project were assessed using the χ2 test. The genotype and allele frequencies of single nucleotide polymorphisms (SNPs) in PTGS2 (rs20417), NAT2 (rs1801280), NAT2 (rs1208), ACE (rs4291), and CYP2D6 (rs1065852) were considerably different in the Hui population compared with those in the other 26 populations. Besides, using the PharmGKB database, we identified several VIP variants that may alter the drug metabolism of ibuprofen, rofecoxib (PTGS2), captopril (ACE), citalopram, and escitalopram (CYP2D6). We also discovered other variants associated with adverse reactions to cisplatin and cyclophosphamide (NAT2). Our study indicated that the loci of PTGS2 (rs20417), NAT2 (rs1801280 and rs1208), ACE (rs4291), and CYP2D6 (rs1065852) in the Hui population were obviously different from those in the other 26 populations, which provides reliable information for predicting drug efficacy. Besides, it supplements the pharmacogenomic knowledge of the Hui population and lays the foundation for the individualized treatment for the Hui population.

PMID:36930384 | DOI:10.1007/s10142-023-01021-3

Methods Mol Biol. 2023;2629:305-330. doi: 10.1007/978-1-0716-2986-4_14.

ABSTRACT

Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.

PMID:36929083 | DOI:10.1007/978-1-0716-2986-4_14

Adv Neurobiol. 2023;30:363-385. doi: 10.1007/978-3-031-21054-9_15.

ABSTRACT

The Human Genome Project mapped the 3 billion base pairs in the human genome, which ushered in a new generation of genomically focused treatment development. While this has been very successful in other areas, neuroscience has been largely devoid of such developments. This is in large part because there are very few neurological or mental health conditions that are related to single-gene variants. While developments in pharmacogenomics have been somewhat successful, the use of genetic information in practice has to do with drug metabolism and adverse reactions. Studies of drug metabolism related to genetic variations are an important part of drug development. However, outside of cancer biology, the actual translation of genomic information into novel therapies has been limited. Epigenetics, which relates in part to the effects of the environment on DNA, is a promising newer area of relevance to CNS disorders. The environment can induce chemical modifications of DNA (e.g., cytosine methylation), which can be induced by the environment and may represent either shorter- or longer-term changes. Given the importance of environmental influences on CNS disorders, epigenetics may identify important treatment targets in the future.

PMID:36928858 | DOI:10.1007/978-3-031-21054-9_15

Pharmacol Rev. 2023 Mar 16:PHARMREV-AR-2022-000810. doi: 10.1124/pharmrev.122.000810. Online ahead of print.

ABSTRACT

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all 'omics' fields, e.g., proteomics, transcriptomics, metabolomics, and metagenomics. This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. FDA approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multi-component biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review will address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues - providing insights into the current status and future direction of health care. Significance Statement Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

PMID:36927888 | DOI:10.1124/pharmrev.122.000810

Pharmacogenomics. 2023 Mar 17. doi: 10.2217/pgs-2022-0180. Online ahead of print.

ABSTRACT

Purpose: The aim of this study was to analyze the effects of various genetic polymorphisms and clinical factors on tacrolimus (TAC) concentration in the convalescence period (CP) and stabilization period (SP) post-liver transplantation. Patients & methods: A total of 13 SNPs were genotyped in 97 Chinese liver transplant recipients. Associations between SNPs and TAC trough blood concentration/dose ratio (C0/D) were analyzed using different genetic models in both CP and SP. Results: Only five SNPs were significantly associated with TAC log (C0/D) in the CP, and none showed a significant association in the SP. We identified rs15524 (CYP3A5), rs9200 (C6), albumin and creatinine as independent predictors of TAC C0/D in the CP. Furthermore, a final model in the CP explained a total of 30.5% TAC variation. Conclusion: Our study results suggest that in the early stages post-transplantation surgery, recipients' genetic and clinical factors exert a short-term impact on TAC metabolism that gradually decreases with time.

PMID:36927114 | DOI:10.2217/pgs-2022-0180

ACS Pharmacol Transl Sci. 2023 Feb 24;6(3):399-409. doi: 10.1021/acsptsci.2c00212. eCollection 2023 Mar 10.

ABSTRACT

Breast cancer is one of the major causes of death in women worldwide. It is a diverse illness with substantial intersubject heterogeneity, even among individuals with the same type of tumor, and customized therapy has become increasingly important in this sector. Because of the clinical and physical variability of different kinds of breast cancers, multiple staging and classification systems have been developed. As a result, these tumors exhibit a wide range of gene expression and prognostic indicators. To date, no comprehensive investigation of model training procedures on information from numerous cell line screenings has been conducted together with radiation data. We used human breast cancer cell lines and drug sensitivity information from Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) databases to scan for potential drugs using cell line data. The results are further validated through three machine learning approaches: Elastic Net, LASSO, and Ridge. Next, we selected top-ranked biomarkers based on their role in breast cancer and tested them further for their resistance to radiation using the data from the Cleveland database. We have identified six drugs named Palbociclib, Panobinostat, PD-0325901, PLX4720, Selumetinib, and Tanespimycin that significantly perform on breast cancer cell lines. Also, five biomarkers named TNFSF15, DCAF6, KDM6A, PHETA2, and IFNGR1 are sensitive to all six shortlisted drugs and show sensitivity to the radiations. The proposed biomarkers and drug sensitivity analysis are helpful in translational cancer studies and provide valuable insights for clinical trial design.

PMID:36926455 | PMC:PMC10012252 | DOI:10.1021/acsptsci.2c00212

Clin Pharmacol Ther. 2023 Mar 16. doi: 10.1002/cpt.2890. Online ahead of print.

ABSTRACT

Over 20% of Food and Drug Administration (FDA)-approved drugs in the United States are metabolized by the hepatic enzyme cytochrome P450 2D6 (CYP2D6). The gene encoding CYP2D6 is highly polymorphic and genetic variation has been shown to impact drug response for many commonly dispensed drugs including opioids and antidepressants. Thus, it is important to understand an individual's CYP2D6 metabolizer status to optimize treatment outcomes for patients taking medications that are metabolized by this enzyme. Consequently, clinical CYP2D6 pharmacogenetic testing is being implemented by a growing number of health centers. Furthermore, clinical guidelines currently recommend adapting therapeutic regimens based on CYP2D6 genotype-informed phenotype. However, CYP2D6 genetic variation varies considerably across global populations and many allelic variants, or star alleles, are predominantly found in certain ancestral populations. Although CYP2D6 genetic variation has been extensively studied, there is still a paucity of information for many non-European populations. As has been shown for other pharmacogenes in randomized controlled trials, results from European populations cannot simply be extrapolated to other groups and in some cases even has the potential to cause harm. Therefore, enhanced inclusion in pharmacogenetic studies is urgently needed to increase ancestral representation, determine the extent of global CYP2D6 genetic variation (e.g., ancestry-specific variants), and determine the clinical impact of this variation on clinical treatment outcome. This review highlights knowledge gaps, challenges, and future directions in CYP2D6 pharmacogenomics through a unique pharmacoequity lens to address health inequities that hamper our ability to optimize drug therapy for improved pharmacological outcomes in diverse populations globally.

PMID:36924260 | DOI:10.1002/cpt.2890