Pharmacogenomics. 2021 Dec 16. doi: 10.2217/pgs-2021-0080. Online ahead of print.

ABSTRACT

Aim: The present study has been carried out to evaluate the association of the N-acetyl transferase 2 (NAT2) variants in North Indian lung cancer patients and healthy controls. Furthermore, we have also determined the effect of the polymorphic variants of the NAT2 gene on the clinical outcomes and overall survival among lung cancer (LC) subjects treated with platinum-based doublet chemotherapy. Methods: This case-control study comprised a total of 550 cases and 550 healthy controls. The genotyping was carried out using polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) and the statistical analysis was carried out using MedCalc. Results: There was a lack of any significant association for both 590G>A and 803A>G polymorphisms toward risk for LC, but 857G>A polymorphism exhibited a risk toward LC (p = 0.005). Whereas, variant alleles for the 481C>T polymorphism had a decreased risk for LC (p = 0.0003). Further, 857G>A polymorphism conferred a positive association between genotype and ADCC (p = 0.001) and 481C>T polymorphism had a decreased risk for SQCC (OR = 0.39, p = 0.0006) and SCLC (p = 0.001) subjects. The smokers carrying mutant genotype for the 481C>T polymorphism had a decreased risk toward LC (p < 0.0001) even in light (p = 0.002) as well as heavy smokers (p = 0.001). In case of females, 2.59-fold and 3.66-fold increased risk of LC development was observed in subjects with intermediate and slow acetylator for the 857G>A polymorphism. Whereas, in case of males this polymorphism depicts a reduced risk for LC. On the other hand, 803A>G depicted a 2.82-fold risk of LC in case of female subjects who were slow acetylators. Our study exhibits a significant difference in the overall haplotype distribution between cases and controls. In our study overall, (857G>A, 481C>T, 803A>G) was found to be best model, but was not significant using MDR. Considering the CART results 481C>T polymorphism came out to be the most significant factor in determining the LC risk. For the 803A>G polymorphism, a threefold odds of lymph node invasion were observed for mutant genotype, the recessive model exhibited an odd of 2.8. 590G>A appears to be a potential prognostic factor for OS of SCLC patients after irinotecan therapy as the survival time for such patients was better. Conclusion: These results suggest that NAT2 variant genotype for 590G>A and 803A>G was not found to modulate risk toward LC, but 857G>A polymorphism exhibited a risk toward LC and 481C>T polymorphism had a decreased risk for LC. NAT2 590G>A appears to be a potential prognostic factor for OS of SCLC patients after irinotecan therapy and 481C>T came out to be significant factor using CART.

PMID:34911343 | DOI:10.2217/pgs-2021-0080

Pharmacopsychiatry. 2021 Dec 15. doi: 10.1055/a-1625-6388. Online ahead of print.

ABSTRACT

This international guideline proposes improving clozapine package inserts worldwide by using ancestry-based dosing and titration. Adverse drug reaction (ADR) databases suggest that clozapine is the third most toxic drug in the United States (US), and it produces four times higher worldwide pneumonia mortality than that by agranulocytosis or myocarditis. For trough steady-state clozapine serum concentrations, the therapeutic reference range is narrow, from 350 to 600 ng/mL with the potential for toxicity and ADRs as concentrations increase. Clozapine is mainly metabolized by CYP1A2 (female non-smokers, the lowest dose; male smokers, the highest dose). Poor metabolizer status through phenotypic conversion is associated with co-prescription of inhibitors (including oral contraceptives and valproate), obesity, or inflammation with C-reactive protein (CRP) elevations. The Asian population (Pakistan to Japan) or the Americas' original inhabitants have lower CYP1A2 activity and require lower clozapine doses to reach concentrations of 350 ng/mL. In the US, daily doses of 300-600 mg/day are recommended. Slow personalized titration may prevent early ADRs (including syncope, myocarditis, and pneumonia). This guideline defines six personalized titration schedules for inpatients: 1) ancestry from Asia or the original people from the Americas with lower metabolism (obesity or valproate) needing minimum therapeutic dosages of 75-150 mg/day, 2) ancestry from Asia or the original people from the Americas with average metabolism needing 175-300 mg/day, 3) European/Western Asian ancestry with lower metabolism (obesity or valproate) needing 100-200 mg/day, 4) European/Western Asian ancestry with average metabolism needing 250-400 mg/day, 5) in the US with ancestries other than from Asia or the original people from the Americas with lower clozapine metabolism (obesity or valproate) needing 150-300 mg/day, and 6) in the US with ancestries other than from Asia or the original people from the Americas with average clozapine metabolism needing 300-600 mg/day. Baseline and weekly CRP monitoring for at least four weeks is required to identify any inflammation, including inflammation secondary to clozapine rapid titration.

PMID:34911124 | DOI:10.1055/a-1625-6388

Curr Res Pharmacol Drug Discov. 2021 May 6;2:100025. doi: 10.1016/j.crphar.2021.100025. eCollection 2021.

ABSTRACT

This article summarizes the current literature and documents new evidence concerning drug-drug interactions (DDI) stemming from pharmacogenomic and circadian rhythm determinants of therapies used to treat common cardiovascular diseases (CVD), such as atherosclerosis and hypertension. Patients with CVD often have more than one pathophysiologic condition, namely metabolic syndromes, hypertension, hyperlipidemia, and hyperglycemia, among others, which necessitate polytherapeutic or polypharmaceutic management. Interactions between drugs, drugs and food/food supplements, or drugs and genetic/epigenetic factors may have adverse impacts on the cardiovascular and other systems of the body. The mechanisms underlying cardiovascular DDI may involve the formation of a complex pharmacointeractome, including the absorption, distribution, metabolism, and elimination of drugs, which affect their respective bioavailability, efficacy, and/or harmful metabolites. The pharmacointeractome of cardiovascular drugs is likely operated with endogenous rhythms controlled by circadian clock genes. Basic and clinical investigations have improved the knowledge and understanding of cardiovascular pharmacogenomics and pharmacointeractomes, and additionally they have presented new evidence that the staging of deterministic circadian rhythms, according to the dosing time of drugs, e.g., upon awakening vs. at bedtime, cannot only differentially impact their pharmacokinetics and pharmacodynamics but also mediate agonistic/synergetic or antagonistic DDI. To properly manage CVD patients and avoid DDI, it is important that clinicians have sufficient knowledge of their multiple risk factors, i.e., age, gender, and life style elements (like diet, smoking, psychological stress, and alcohol consumption), and comorbidities, such as diabetes, hypertension, dyslipidemia, and depression, and the potential interactions between genetic or epigenetic background of their prescribed therapeutics.

PMID:34909660 | PMC:PMC8663962 | DOI:10.1016/j.crphar.2021.100025

J Clin Invest. 2021 Dec 15;131(24):e140436. doi: 10.1172/JCI140436.

ABSTRACT

Activation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway is a pervasive event in tumorigenesis due to PI3K mutation and dysfunction of phosphatase and tensin homolog deleted on chromosome 10 (PTEN). Pharmacological inhibition of PI3K has resulted in variable clinical outcomes, however, raising questions regarding the possible mechanisms of unresponsiveness and resistance to treatment. WWP1 is an oncogenic HECT-type ubiquitin E3 ligase frequently amplified and mutated in multiple cancers, as well as in the germ lines of patients predisposed to cancer, and was recently found to activate PI3K signaling through PTEN inactivation. Here, we demonstrate that PTEN dissociated from the plasma membrane upon treatment with PI3K inhibitors through WWP1 activation, whereas WWP1 genetic or pharmacological inhibition restored PTEN membrane localization, synergizing with PI3K inhibitors to suppress tumor growth both in vitro and in vivo. Furthermore, we demonstrate that WWP1 inhibition attenuated hyperglycemia and the consequent insulin feedback, which is a major tumor-promoting side effect of PI3K inhibitors. Mechanistically, we found that AMPKα2 was ubiquitinated and, in turn, inhibited in its activatory phosphorylation by WWP1, whereas WWP1 inhibition facilitated AMPKα2 activity in the muscle to compensate for the reduction in glucose uptake observed upon PI3K inhibition. Thus, our identification of the cell-autonomous and systemic roles of WWP1 inhibition expands the therapeutic potential of PI3K inhibitors and reveals new avenues of combination cancer therapy.

PMID:34907909 | DOI:10.1172/JCI140436

Br J Clin Pharmacol. 2021 Dec 15. doi: 10.1111/bcp.15181. Online ahead of print.

ABSTRACT

Pharmacogenomics (PGx) relates to the study of genetic factors determining variability in drug response. Implementing PGx testing in paediatric patients can enhance drug safety, helping to improve drug efficacy or reduce the risk of toxicity. Despite its clinical relevance, the implementation of PGx testing in paediatric practice to date has been variable and limited. As with most paediatric pharmacological studies, there are well-recognised barriers to obtaining high quality PGx evidence, particularly when patient numbers may be small, and off-label or unlicensed prescribing remains widespread. Furthermore, trials enrolling small numbers of children can rarely, in isolation, provide sufficient PGx evidence to change clinical practice, so extrapolation from larger PGx studies in adult patients, where scientifically sound, is essential. This review paper discusses the relevance of PGx to paediatrics and considers implementation strategies from a child health perspective. Examples are provided from Canada, the Netherlands, and the UK, with consideration of the different healthcare systems and their distinct approaches to implementation, followed by future recommendations based on these cumulative experiences. Improving the evidence-base demonstrating the clinical utility and cost-effectiveness of paediatric PGx testing will be critical to drive implementation forwards. International, interdisciplinary collaborations will enhance paediatric data collation, interpretation and evidence curation, while also supporting dedicated paediatric PGx educational initiatives. PGx consortia and paediatric clinical research networks will continue to play a central role in the streamlined development of effective PGx implementation strategies to help optimise paediatric pharmacotherapy.

PMID:34907575 | DOI:10.1111/bcp.15181

Sci Rep. 2021 Dec 14;11(1):23933. doi: 10.1038/s41598-021-03418-1.

ABSTRACT

Effective treatment options for head and neck squamous cell carcinoma (HNSCC) are currently lacking. We exploited the drug response and genomic data of the 28 HNSCC cell lines, screened with 4,518 compounds, from the PRISM repurposing dataset to uncover repurposing drug candidates for HNSCC. A total of 886 active compounds, comprising of 418 targeted cancer, 404 non-oncology, and 64 chemotherapy compounds were identified for HNSCC. Top classes of mechanism of action amongst targeted cancer compounds included PI3K/AKT/MTOR, EGFR, and HDAC inhibitors. We have shortlisted 36 compounds with enriched killing activities for repurposing in HNSCC. The integrative analysis confirmed that the average expression of EGFR ligands (AREG, EREG, HBEGF, TGFA, and EPGN) is associated with osimertinib sensitivity. Novel putative biomarkers of response including those involved in immune signalling and cell cycle were found to be associated with sensitivity and resistance to MEK inhibitors respectively. We have also developed an RShiny webpage facilitating interactive visualization to fuel further hypothesis generation for drug repurposing in HNSCC. Our study provides a rich reference database of HNSCC drug sensitivity profiles, affording an opportunity to explore potential biomarkers of response in prioritized drug candidates. Our approach could also reveal insights for drug repurposing in other cancers.

PMID:34907286 | DOI:10.1038/s41598-021-03418-1

J Affect Disord. 2021 Dec 11:S0165-0327(21)01330-6. doi: 10.1016/j.jad.2021.12.012. Online ahead of print.

ABSTRACT

BACKGROUND: Pharmacological studies have yielded valuable insights into the role of the serotonin 4 receptor (HTR4) in major depressive episodes (MDE) and response to antidepressant drugs (AD). A genetic association has been shown between HTR4 and susceptibility to mood disorders. Our study aims at assessing the association between the HTR4 genetic polymorphism, rs1345697, and improvement in depressive symptoms and remission after antidepressant treatment in MDE patients.

METHODS: 492 depressed patients from the METADAP cohort were treated prospectively for 6 months with ADs. The clinical outcomes according to HTR4 rs1345697 were compared after 1 (M1), 3 (M3), and 6 (M6) months of treatment. Mixed-effects logistic regression and adjusted linear models assessed the association between rs1345697 and 17-item Hamilton Depression Rating Scale (HDRS) score improvement and response/remission.

RESULTS: Over the 6 months of treatment, mixed-effects regressions showed lower improvements in HDRS scores (Coefficient=1.52; Confident Interval (CI) 95% [0.37-2.67]; p=0.009) and lower remission rates (Odds Ratio=2.0; CI95% [1.0-4.1]; p=0.05) in GG homozygous patients as compared to allele A carriers.

LIMITATIONS: The major limitations of our study are the uncertainty of the rs1345697 effect on HTR4 function, the substantial drop-out rate, and the fact that analysis is not based on randomization between polymorphism groups.

CONCLUSIONS: In our study, patients who were homozygous carriers of the variant G of the HTR4 rs1345697 had lower depressive symptoms improvement and 2-fold lower remission rates after antidepressant treatment as compared to allele A carriers. Randomization study should be done to confirm these results.

PMID:34906639 | DOI:10.1016/j.jad.2021.12.012

Genet Med. 2021 Nov 17:S1098-3600(21)04130-7. doi: 10.1016/j.gim.2021.09.003. Online ahead of print.

ABSTRACT

PURPOSE: More than half of the familial cutaneous melanomas have unknown genetic predisposition. This study aims at characterizing a novel melanoma susceptibility gene.

METHODS: We performed exome and targeted sequencing in melanoma-prone families without any known melanoma susceptibility genes. We analyzed the expression of candidate gene DENND5A in melanoma samples in relation to pigmentation and UV signature. Functional studies were carried out using microscopic approaches and zebrafish model.

RESULTS: We identified a novel DENND5A truncating variant that segregated with melanoma in a Swedish family and 2 additional rare DENND5A variants, 1 of which segregated with the disease in an American family. We found that DENND5A is significantly enriched in pigmented melanoma tissue. Our functional studies show that loss of DENND5A function leads to decrease in melanin content in vitro and pigmentation defects in vivo. Mechanistically, harboring the truncating variant or being suppressed leads to DENND5A losing its interaction with SNX1 and its ability to transport the SNX1-associated vesicles from melanosomes. Consequently, untethered SNX1-premelanosome protein and redundant tyrosinase are redirected to lysosomal degradation by default, causing decrease in melanin content.

CONCLUSION: Our findings provide evidence of a physiological role of DENND5A in the skin context and link its variants to melanoma susceptibility.

PMID:34906508 | DOI:10.1016/j.gim.2021.09.003

Genet Med. 2021 Nov 17:S1098-3600(21)01122-9. doi: 10.1016/j.gim.2021.08.008. Online ahead of print.

ABSTRACT

PURPOSE: Large-scale genetics education appropriate for general practice providers is a growing priority. We describe the content and impact of a mandatory system-wide program implemented at Sanford Health.

METHODS: The Imagenetics Initiative at Sanford Health developed a 2-year genetics education program with quarterly web-based modules that were mandatory for all physicians and advanced practice providers. Scores of 0 to 5 were calculated for each module on the basis of the number of objectives that the participants reported as fulfilled. In addition, the participants completed surveys before starting and after finishing the education program, which included a 7-item measure scored 7 to 28 on the perceived preparedness to practice genetics.

RESULTS: Between 2252 and 2822 Sanford Health employees completed each of the 8 quarterly education modules. The ratings were highest for the module about using genomics to improve patient management (mean score = 4.3) and lowest for the module about different types of genetic tests and specialists. The mean perceived preparedness scores increased from 15.7 at pre-education to 19.1 at post-education (P < .001).

CONCLUSION: Web-based genetics education was highly effective in increasing health care providers' confidence about using genetics. Both comfort with personal knowledge and confidence regarding access to the system's genomic medicine experts increased significantly. The results demonstrate how scalable approaches can improve provider preparedness.

PMID:34906462 | DOI:10.1016/j.gim.2021.08.008

Trials. 2021 Dec 14;22(1):919. doi: 10.1186/s13063-021-05724-5.

ABSTRACT

BACKGROUND: It is known that only 50% of patients diagnosed with major depressive disorders (MDD) respond to the first-line antidepressant treatment. Accordingly, there is a need to improve response rates to reduce healthcare costs and patient suffering. One approach to increase rates of treatment response might be the integration of pharmacogenetic (PGx) testing to stratify antidepressant drug selection. The goal of PGx assessments is to identify patients who have an increased risk to experience adverse drug reactions or non-response to specific drugs. Especially for antidepressants, there is compiling evidence on PGx influencing drug exposure as well as response.

METHODS: This study is an open-label, randomized controlled trial conducted in two study centers in Switzerland: (1) the Psychiatric Clinic of Solothurn and (2) the Private Clinic Wyss in Münchenbuchsee. Adult inpatients diagnosed with a unipolar moderate or severe depressive episode are recruited at clinic admission and are included in the study. If the adjustment to a new antidepressant pharmacotherapy is necessary, the participants are randomized to either Arm A (intervention group) or Arm B (control group). If no new antidepressant pharmacotherapy is introduced the participants will be followed up in an observational arm. The intervention is the service of pharmacist-guided pre-emptive PGx testing to support clinical decision making on antidepressant selection and dosing. As a comparison, in the control group, the antidepressant pharmacotherapy is selected by the treating physician according to current treatment guidelines (standard of care) without the knowledge of PGx test results and support of clinical pharmacists. The primary outcome of this study compares the response rates under antidepressant treatment after 4 weeks between intervention and control arm.

DISCUSSION: The findings from this clinical trial are expected to have a direct impact on inter-professional collaborations for the handling and use of PGx data in psychiatric practice.

TRIAL REGISTRATION: ClinicalTrials.gov NCT04507555 . Registered on August 11, 2020. Swiss National Clinical Trials Portal SNCTP000004015 . Registered August 18, 2020.

PMID:34906208 | DOI:10.1186/s13063-021-05724-5

Pharmacogenomics. 2021 Dec 15. doi: 10.2217/pgs-2021-0097. Online ahead of print.

ABSTRACT

Aim: Polymorphisms at LPA, LDLR, APOE, APOC1, MYLIP and ABCG2 are attractive targets for assessment of their impact on lipid-lowering therapy with rosuvastatin. The present study investigated whether polymorphisms at these genes are associated with the risk of coronary artery disease (CAD) development, and reduction of atherogenic lipids and carotid intima-media thickness (CIMT) in CAD patients, taking rosuvastatin. Materials & methods: 190 CAD patients and 1697 subjects were enrolled in pharmacogenetic and genetic association study, respectively. SNP genotyping was done using the MassARRAY-4 system. Results: MYLIP rs6924995, rs3757354, APOC1 rs445925, LDLR rs6511720, APOE rs7412, ABCG2 rs2199936, rs1481012 variants were significantly associated with CAD susceptibility (p = 0.016, 0.0003, <0.0001, <0.0001, 0.013, 0.016, 0.0035, respectively), as well as with CIMT regression (except ABCG2 variants; p = 0.05, 0.039, 0.039, 0.016, 0.0065), and changes in plasma lipids during rosuvastatin therapy. Conclusion: The studied polymorphisms possess pleiotropic effects on plasma lipids and CIMT, CAD susceptibility, and determine lipid-lowering response to rosuvastatin.

PMID:34905955 | DOI:10.2217/pgs-2021-0097

Am J Respir Crit Care Med. 2021 Dec 14. doi: 10.1164/rccm.202109-2079PP. Online ahead of print.

ABSTRACT

Despite numerous therapeutic advances in pulmonary arterial hypertension, patients continue to suffer high morbidity and mortality, particularly considering a median age of 50 years. This article explores whether early, robust reduction of right ventricular afterload would facilitate substantial improvement in right ventricular function and thus whether afterload reduction should be a treatment goal for pulmonary arterial hypertension. The earliest clinical studies of prostanoid treatment in pulmonary arterial hypertension demonstrated an important link between lowering mean pulmonary arterial pressure (or pulmonary vascular resistance) and improved survival. Subsequent studies of oral monotherapy or sequential combination therapy demonstrated smaller reductions in mean pulmonary arterial pressure and pulmonary vascular resistance. More recently, retrospective reports of initial aggressive prostanoid treatment or initial combination oral and parenteral therapy have shown marked afterload reduction along with significant improvements in right ventricular function. Some data suggest that reaching threshold levels for pressure or resistance (components of right ventricular afterload) may be key to interrupting the self-perpetuating injury of pulmonary vascular disease in pulmonary arterial hypertension and could translate into improved long-term clinical outcomes. Based on these clues, the authors postulate that improved clinical outcomes might be achieved by targeting significant afterload reduction with initial oral combination therapy and early parenteral prostanoids.

PMID:34905704 | DOI:10.1164/rccm.202109-2079PP

Clin Pharmacol Ther. 2021 Dec 14. doi: 10.1002/cpt.2511. Online ahead of print.

ABSTRACT

Machine Learning (ML) algorithms have been used to forecast clinical outcomes or drug adverse effect by analysing different datasets such as electronic health records, diagnostic data, and molecular data. However, ML implementation in phase I clinical trial is still an unexplored strategy that implies challenges such as the selection of the best development strategy when dealing with limited sample size. In the attempt to better define prechemotherapy baseline clinical and biomolecular predictors of drug toxicity, we trained and compared five ML algorithms starting from clinical, blood biochemistry, and genotype data derived from a previous phase Ib study aimed to define the maximum tolerated dose of irinotecan (FOLFIRI plus bevacizumab regimen) in metastatic colorectal cancer patients. During cross-validation the Random Forest algorithm achieved the best performance with a mean Matthews correlation coefficient of 0.549 and a mean accuracy of 80.4%; the best predictors of dose limiting toxicity (DLT) at baseline were hemoglobin, SGOT, and albumin. The feasibility of a prediction model prototype was in principle assessed using the two distinct dose escalation cohorts where in the validation cohort the model scored a Matthews correlation coefficient of 0.59 and an accuracy of 82.0%. Moreover, we found a strong relationship between SGOT and irinotecan pharmacokinetics suggesting its role as surrogates' estimators of the irinotecan metabolism equilibrium. In conclusion, the potential application of ML techniques to phase I study could provide clinicians with early prediction tools useful both to ameliorate the management of clinical trial and to make more adequate treatment decisions.

PMID:34905217 | DOI:10.1002/cpt.2511

Mol Diagn Ther. 2021 Dec 14. doi: 10.1007/s40291-021-00567-x. Online ahead of print.

ABSTRACT

On the basis of scientific evidence, information on the option, recommendation or requirement to test for pharmacogenetic or pharmacogenomic biomarkers is incorporated in the Summary of Product Characteristics of an increasing number of drugs in Europe. A screening of the Genetic Testing Registry (GTR) showed that a variety of molecular genetic testing methods is currently offered worldwide in testing services with regard to according drugs and biomarkers. Thereby, among the methodology indicated in the screened GTR category 'Molecular Genetics', next-generation sequencing is applied for identification of the largest proportion of evaluated biomarkers that are relevant for therapeutic management of centrally approved drugs in Europe. However, sufficient information on regulatory clearances, clinical utility, analytical and clinical validity of applied methods is rarely provided.

PMID:34905151 | DOI:10.1007/s40291-021-00567-x

Lab Chip. 2021 Dec 14. doi: 10.1039/d1lc00564b. Online ahead of print.

ABSTRACT

Single-nucleotide polymorphism (SNP) plays a critical role in personalized medicine, forensics, pharmacogenetics, and disease diagnostics. Among different existing SNP genotyping techniques, melting curve analysis (MCA) becomes increasingly popular due to its high accuracy and straightforward procedures in extracting the melting temperature (Tm). Yet, its study on existing digital microfluidic (DMF) platforms has intrinsic limitations due to the temperature inhomogeneity within a thickened droplet during the on-chip rapid heating process. Although the utilization of an on-chip thermostat can regulate and monitor the dynamic melting process in real time, the limited Tm accuracy resulting from the insufficient system response time to accommodate the fast-melting evolution still poses a great challenge for precise MCA with high throughput. This work proposes a one-shot MCA on a DMF platform. The tailoring of a functional substrate with hierarchical micro/nano structure enables high-resolution patterning of pL-scale droplets. Specifically, the hydrothermal and photocatalysis treatment allows the functional substrate to exhibit a superwettability contrast of >170°, facilitating passive isolation of the pL-scale DNA sample into highly-resolved pL droplets above the 200 μm superhydrophilic patterns. This high-resolution MCA technique can successfully discriminate KRAS gene targets with single-nucleotide mutations in 3 seconds. The high accuracy and consistency in the acquired Tm when compared with off-chip results demonstrate its opportunities for near-patient diagnostics, precision medicines, genetic counseling, and prevention strategies on DMF platforms.

PMID:34904611 | DOI:10.1039/d1lc00564b

Clin Toxicol (Phila). 2021 Dec 14:1-6. doi: 10.1080/15563650.2021.2013494. Online ahead of print.

ABSTRACT

BACKGROUND: The lockdown periods imposed in 2020 by governments had deleterious consequences on population mental health. Several studies based on declarative data have suggested that the lockdown periods were associated with changes in psychoactive substance use but few relied on toxicological analyses.

AIMS: We studied the impact of lockdowns on the pattern of routine care toxicological screening performed on patients hospitalized at the emergency ward (EW) and intensive care units (ICU) at the Grenoble University Hospital.

METHOD: This was a retrospective, monocentric study comparing routine care toxicology biological tests performed in children older than 12 years of age and adults hospitalized at the ICU and EW in 2018, 2019, and 2020. Alcohol, illicit drugs, and medications were screened. Generalized linear models were generated to evaluate the effect of the lockdown periods on toxicology results, considering age and sex.

RESULTS: The study included 13,910 samples from 11,786 patients. There was no significant difference in the repartition of sex or age over the three years. The frequency of positive toxicological tests increased during the lockdown periods (adjusted odds ratio (OR) 95% confidence interval (CI): 1.14, (1.01-1.28), p = .026). The frequency of poly-exposures also rose during these periods (OR 1.43 (1.11-1.82), p = .004) mostly among men (OR 1.54 (1.02-2.04), p = .022), 12-25-year-old patients (OR 1.69 (1.07-2.31), p = .016), and seniors (>56 years) (OR 1.54 (1.00-1.97), p = .032).

CONCLUSIONS: This study suggests that lockdown episodes were associated with increased incidence of psychoactive substance poly-exposures, highlighting the need for preventive strategies for high-risk populations.

PMID:34904494 | DOI:10.1080/15563650.2021.2013494

Arthritis Care Res (Hoboken). 2021 Dec 13. doi: 10.1002/acr.24834. Online ahead of print.

ABSTRACT

OBJECTIVE: To test the ability of machine learning (ML) approaches with clinical and genomic biomarkers to predict methotrexate treatment response in patients with early rheumatoid arthritis (RA).

METHODS: Demographic, clinical and genomic data from 643 patients of European ancestry with early RA (mean age 54 years; 70% female) subdivided into a training (n=336) and validation cohort (n=307) were used. The genomic data comprised 160 single nucleotide polymorphisms (SNPs) previously associated with RA or methotrexate metabolism. Response to methotrexate monotherapy was defined as good or moderate by the European League Against Rheumatism (EULAR) response criteria at 3-month follow-up. Supervised ML methods were trained with 5-repeats and 10-fold cross-validation using the training cohort. Prediction performance was validated in the independent validation cohort.

RESULTS: Supervised ML methods combining age, sex, smoking, rheumatoid factor, baseline Disease Activity Score with 28-joint count (DAS28) and 160 SNPs predicted EULAR response at 3 months with the area under the receiver operating curve of 0.84 (p=0.05) in the training cohort and achieved a prediction accuracy of 76% (p=0.05) in the validation cohort (sensitivity 72%, specificity 77%). Intergenic SNPs rs12446816, rs13385025, rs113798271, and ATIC (rs2372536) had variable importance above 60.0 and along with baseline DAS28 were among the top predictors of methotrexate response.

CONCLUSION: Pharmacogenomic biomarkers combined with baseline DAS28 can be useful in predicting response to methotrexate in patients with early RA. Applying ML to predict treatment response holds promise for guiding effective RA treatment choices, including timely escalation of RA therapies. This article is protected by copyright. All rights reserved.

PMID:34902228 | DOI:10.1002/acr.24834

Methods Mol Biol. 2022;2401:263-271. doi: 10.1007/978-1-0716-1839-4_17.

ABSTRACT

Microarrays are broadly used in the omic investigation and have several areas of applications in biology and medicine, providing a significant amount of data for a single experiment. Different kinds of microarrays are available, identifiable by characteristics such as the type of probes, the surface used as support, and the method used for the target detection. To better deal with microarray datasets, the development of microarray data analysis protocols simple to use as well as able to produce accurate reports, and comprehensible results arise. The object of this paper is to provide a general protocol showing how to choose the best software tool to analyze microarray data, allowing to efficiently figure out genomic/pharmacogenomic biomarkers.

PMID:34902134 | DOI:10.1007/978-1-0716-1839-4_17

Methods Mol Biol. 2022;2401:13-27. doi: 10.1007/978-1-0716-1839-4_2.

ABSTRACT

Pharmacogenomics is an important research field that studies the impact of genetic variation of patients on drug responses, looking for correlations between single nucleotide polymorphisms (SNPs) of patient genome and drug toxicity or efficacy. The large number of available samples and the high resolution of the instruments allow microarray platforms to produce huge amounts of SNP data. To analyze such data and find correlations in a reasonable time, high-performance computing solutions must be used. Cloud4SNP is a bioinformatics tool, based on Data Mining Cloud Framework (DMCF), for parallel preprocessing and statistical analysis of SNP pharmacogenomics microarray data.This work describes how Cloud4SNP has been extended to execute applications on Apache Spark, which provides faster execution time for iterative and batch processing. The experimental evaluation shows that Cloud4SNP is able to exploit the high-performance features of Apache Spark, obtaining faster execution times and high level of scalability, with a global speedup that is very close to linear values.

PMID:34902119 | DOI:10.1007/978-1-0716-1839-4_2

Methods Mol Biol. 2022;2401:1-12. doi: 10.1007/978-1-0716-1839-4_1.

ABSTRACT

The understanding of the biological differences which underlie the inter-individual variability in drug response improved the efficacy of cancer therapy in the era of precision medicine. In fact molecularly targeted drugs and immunotherapy represent a revolution in cancer treatment. The identification of genetic predictive and/or prognostic biomarkers linked to drug pharmacokinetics (PK) and pharmacodynamics (PD) is allowed by the development of high-throughput omics tools for detecting and understanding biological differences among individuals, in order to improve drug efficacy and minimize risk of toxicity. Personalized medicine in cancer treatment reduces costs of the healthcare system. Unfortunately, pharmacogenomics biomarkers discovery is influenced by complexity, need of high-quality evidence, and a validation process for regulatory purposes. This chapter is focused on the critic analysis of presently available pharmacogenomics tools for discovering or testing genetic polymorphic variants in drug metabolizing enzyme to be introduced in clinical practice for the prospective stratification of cancer patients.

PMID:34902118 | DOI:10.1007/978-1-0716-1839-4_1