Cytochrome allelic variants and clopidogrel metabolism in cardiovascular diseases therapy

Variations in Citations Across Databases: Implications for Journal Impact Factors

The Journal Impact Factor (JIF) is a widely used metric for ranking journals based on the number of citations garnered by papers published over a specific timeframe. To assess the accuracy of JIF values, I compared citation counts for 30 of my own publications across six major bibliography databases: CrossRef, Web of Science, Publisher records, Google Scholar, PubMed and Scopus. The analysis revealed noteworthy variations in citation counts, ranging from 10% to over 50% between the lowest and highest citation counts. Google Scholar records the highest citation numbers, while PubMed reported the lowest. Notably, Web of Science, whose citation data are used in JIF calculations, tend to underestimate citation counts compared to other databases. These observations raise concerns about the accuracy of JIF calculation based on Web of Science's citation data. The real JIF values for most journals would differ from those annually reported by Clarivate's journal citation reports (JCR). These citation discrepancies underscore the importance of comprehensive data collection and the necessity to include additional citation sources. Not because a paper is cited in one journal rather than another should it have a less or more citation weight. Ultimately, one citation remains one citation, regardless of its origin. Clarivate Analytics may thus need to consider integrating all citation sources for more accurate JIF values. Alternatively, Google Scholar could potentially develop its own journal or citation impact based on its extensive journal citation records. However, while making adjustments to how the Journal Impact Factor is calculated can make it more mathematically precise, it doesn't address the fundamental biases built into the metric. Even with refinements, the Journal Impact Factor will remain skewed due to how it's defined and used.

Cannabis Pharmacogenomics: A Path to Personalized Medicine

Cannabis and related compounds have created significant research interest as a promising therapy in many disorders. However, the individual therapeutic effects of cannabinoids and the incidence of side effects are still difficult to determine. Pharmacogenomics may provide the answers to many questions and concerns regarding the cannabis/cannabinoid treatment and help us to understand the variability in individual responses and associated risks. Pharmacogenomics research has made meaningful progress in identifying genetic variations that play a critical role in interpatient variability in response to cannabis. This review classifies the current knowledge of pharmacogenomics associated with medical marijuana and related compounds and can assist in improving the outcomes of cannabinoid therapy and to minimize the adverse effects of cannabis use. Specific examples of pharmacogenomics informing pharmacotherapy as a path to personalized medicine are discussed.

Pharmacogenomics Informs Cardiovascular Pharmacotherapy

Precision medicine exemplifies the emergence of personalized treatment options which may benefit specific patient populations based upon their genetic makeup. Application of pharmacogenomics requires an understanding of how genetic variations impact pharmacokinetic and pharmacodynamic properties. This particular approach in pharmacotherapy is helpful because it can assist in and improve clinical decisions. Application of pharmacogenomics to cardiovascular pharmacotherapy provides for the ability of the medical provider to gain critical knowledge on a patient's response to various treatment options and risk of side effects.

OpenCYP: An open source database exploring human variability in activities and frequencies of polymophisms for major cytochrome P-450 isoforms across world populations

The open source database "OpenCYP database" has been developed based on the results of extensive literature searches from the peer-reviewed literature. OpenCYP provides data on human variability on baseline of activities and polymophism frequencies for selected cytochrome P-450 isoforms (CYP1A2, CYP2A6, CYP2D6, CYP3A4/3A5 and CYP3A7) in healthy adult populations from world populations. CYP enzymatic activities were generally expressed as the metabolic ratio (MR) between an unchanged probe drug and its metabolite(s) in urine or plasma measured in healthy adults. Data on other age groups were very limited and fragmented, constituting an important data gap. Quantitative comparisons were often hampered by the different experimental conditions used. However, variability was quite limited for CYP1A2, using caffeine as a probe substrate, with a symmetrical distribution of metabolic activity values. For CYP3A4, human variability was dependent on the probe substrate itself with low variability when data considering the dextromethorphan/demethilathed metabolite MR were used and large variability when the urinary 6β-hydroxycortisol/cortisol ratio was used. The largest variability in CYP activity was shown for CYP2D6 activity, after oral dosing of dextromethorphan, for which genetic polymorphisms are well characterised and constitute a significant source of variability. It is foreseen that the OpenCYP database can contribute to promising tools to support the further development of QIVIVE and PBK models for human risk assessment of chemicals particularly when combined with information on isoform-specific content in cells using proteomic approaches.

Allele frequencies of single nucleotide polymorphisms of clinically important drug-metabolizing enzymes CYP2C9, CYP2C19, and CYP3A4 in a Thai population

Prior knowledge of allele frequencies of cytochrome P450 polymorphisms in a population is crucial for the revision and optimization of existing medication choices and doses. In the current study, the frequency of the CYP2C9*2, CYP2C9*3, CYP2C19*2, CYP2C19*3, CYP2C19*6, CYP2C19*17, and CYP3A4 (rs4646437) alleles in a Thai population across different regions of Thailand was examined. Tests for polymorphisms of CYP2C9 and CYP3A4 were performed using TaqMan SNP genotyping assay and CYP2C19 was performed using two different methods; TaqMan SNP genotyping assay and Luminex x Tag V3. The blood samples were collected from 1205 unrelated healthy individuals across different regions within Thailand. Polymorphisms of CYP2C9 and CYP2C19 were transformed into phenotypes, which included normal metabolizer (NM), intermediate metabolizer (IM), poor metabolizer (PM), and rapid metabolizers (RM). The CYP2C9 allele frequencies among the Thai population were 0.08% and 5.27% for the CYP2C9*2 and CYP2C9*3 alleles, respectively. The CYP2C19 allele frequencies among the Thai population were 25.60%, 2.50%, 0.10%, and 1.80% for the CYP2C19*2, CYP2C19*3, CYP2C19*6, and CYP2C19*17 alleles, respectively. The allele frequency of the CYP3A4 (rs4646437) variant allele was 28.50% in the Thai population. The frequency of the CYP2C9*3 allele was significantly lower among the Northern Thai population (P < 0.001). The frequency of the CYP2C19*17 allele was significantly higher in the Southern Thai population (P < 0.001). Our results may provide an understanding of the ethnic differences in drug responses and support for the utilization of pharmacogenomics testing in clinical practice.

Hepatocyte gene expression and DNA methylation as ancestry-dependent mechanisms in African Americans

African Americans (AAs) are an admixed population with widely varying proportion of West African ancestry (WAA). Here we report the correlation of WAA to gene expression and DNA methylation in AA-derived hepatocytes, a cell type important in disease and drug response. We perform mediation analysis to test whether methylation is a mediator of the effect of ancestry on expression. GTEx samples and a second cohort are used as validation. One hundred and thirty-one genes are associated with WAA (FDR < 0.10), 28 of which replicate and represent 220 GWAS phenotypes. Among PharmGKB pharmacogenes, VDR, PTGIS, ALDH1A1, CYP2C19, and P2RY1 nominally associate with WAA (p < 0.05). We find 1037 WAA-associated, differentially methylated regions (FDR < 0.05), with hypomethylated genes enriched in drug-response pathways. In conclusion, WAA contributes to variability in hepatocyte expression and DNA methylation with identified genes previously implicated for diseases disproportionately affecting AAs, including cardiovascular (PTGIS, PLAT) and renal (APOL1) disease, and drug response (CYP2C19).

Si-Miao-Yong-An Decoction Protects Against Cardiac Hypertrophy and Dysfunction by Inhibiting Platelet Aggregation and Activation

Objective: The aim of this study was to determine whether Si-Miao-Yong-An decoction (SMYAD) could ameliorate pressure overload-induced heart hypertrophy and its mechanisms.

Methods: C57BL/6 mice were subjected to either sham or transverse aortic constriction (TAC) surgery to induce heart hypertrophy. SMYAD (14.85 g/kg/day, ig) or captopril (16.5 mg/kg/day, ig) was administered to the mice for 4 weeks. Cardiac function was evaluated based on echocardiography. Heart hypertrophy was detected using hematoxylin and eosin or wheat germ agglutinin staining. Protein expression of CD41, CD61, and P-selectin were measured with Western blot and immunohistochemistry. The expression levels of atrial natriuretic peptide, brain natriuretic peptide, β-myosin heavy chain, β-thromboglobulin, and von Willebrand factor were evaluated by quantitative polymerase chain reaction.

Results: Four weeks after TAC, mice developed exaggerated cardiac hypertrophy and demonstrated a strong decrease in left ventricular ejection fraction compared with sham (29.9 ± 9.3% versus 66.0 ± 9.9%; P < 0.001). Conversely, SMYAD improved cardiac dysfunction with preserved left ventricular ejection fraction (66.5 ± 17.2%; P < 0.001). Shortening fraction was increased by SMYAD, while the left ventricular internal diameter and left ventricular volume were decreased in SMYAD group. SMYAD treatment significantly attenuated cardiac hypertrophy as reflected by the inhibition of atrial natriuretic peptide, brain natriuretic peptide, β-myosin heavy chain mRNA expression, and by the decreasing of cardiac myocyte cross-sectional area. Furthermore, Western blot and immunohistochemistry indicated that the protein expression of platelet aggregation markers (CD41 and CD61) and platelet activation marker (P-selectin) were significantly higher in model mice compared with control. These pathological alterations in TAC-induced mice were significantly ameliorated or blocked by SMYAD administration.

Conclusions: Our results suggested that SMYAD exerted its effect by inhibiting platelet aggregation and activation as revealed by CD41/CD61/P-selectin downregulation. Inhibition the activation of the platelets might contribute to the therapeutic effect of SMYAD in failing heart.

Distribution of CYP2C19 polymorphisms in Mongolian and Han nationals and the choice of specific antiplatelet drugs

Background Individualized medication reviews may improve our understanding of the distribution of CYP2C19 polymorphisms in ethnic populations. Objective To evaluate differences in CYP2C19 gene polymorphisms between Mongolian and Han nationals and determine the effect of adjustments of antiplatelet treatments according to the genetic profile in patients undergoing percutaneous coronary intervention (PCI). Setting Prospective, observational, single-center study. Methods 397 patients diagnosed with acute coronary syndrome were enrolled. Additionally, 186 patients undergoing PCI were given different treatments according to their CYP2C19 genotypes. Patients with the genotype of an extensive metabolizers (EMs; *1/*1) were co-administered aspirin 100 mg/day and clopidogrel 75 mg/day, following a loading dose of 300 mg; intermediate metabolizers (IMs; e.g., *1/*2 and *1/*3) and poor metabolizers (PMs; e.g., *2/*2 and *2/*3) were administered a loading dose of 180 mg ticagrelor, followed by a maintenance dose of 90 mg twice a day. Results In Mongolians, 60.79% of patients were EMs, which was significantly higher than that in Han nationals (P = 0.002). In Han individuals, 62.14% of patients were IMs and PMs, which was significantly higher than that in Mongolians (P < 0.05). Three patients died, and the frequency of adverse events during follow-up was significantly higher in patients given conventional treatment than in patients given tailored treatment (P = 0.039). However, differences in metabolism subtypes did not affect the incidence of adverse reactions. Conclusions There were differences in CYP2C19 polymorphisms between Mongolians and Hans. Effective, safe therapy was achieved by tailoring antiplatelet drug therapy based on genotype.