bioRxiv. 2023 Aug 6:2023.08.03.551911. doi: 10.1101/2023.08.03.551911. Preprint.

ABSTRACT

Spatial cellular heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx SMI, MERSCOPE, and Xenium delineate the spatial gene expression patterns at the single cell resolution. This provides unprecedented opportunities to identify spatially localized cellular resistance and to optimize the treatment for individual patients. In this work, we present a graph-based domain adaptation model, SpaRx, to reveal the heterogeneity of spatial cellular response to drugs. SpaRx transfers the knowledge from pharmacogenomics profiles to single-cell spatial transcriptomics data, through hybrid learning with dynamic adversarial adaption. Comprehensive benchmarking demonstrates the superior and robust performance of SpaRx at different dropout rates, noise levels, and transcriptomics coverage. Further application of SpaRx to the state-of-art single-cell spatial transcriptomics data reveals that tumor cells in different locations of a tumor lesion present heterogenous sensitivity or resistance to drugs. Moreover, resistant tumor cells interact with themselves or the surrounding constituents to form an ecosystem for drug resistance. Collectively, SpaRx characterizes the spatial therapeutic variability, unveils the molecular mechanisms underpinning drug resistance, and identifies personalized drug targets and effective drug combinations.

KEY POINTS: We have developed a novel graph-based domain adaption model named SpaRx, to reveal the heterogeneity of spatial cellular response to different types of drugs, which bridges the gap between pharmacogenomics knowledgebase and single-cell spatial transcriptomics data.SpaRx is developed tailored for single-cell spatial transcriptomics data and is provided available as a ready-to-use open-source software, which demonstrates high accuracy and robust performance.SpaRx uncovers that tumor cells located in different areas within tumor lesion exhibit varying levels of sensitivity or resistance to drugs. Moreover, SpaRx reveals that tumor cells interact with themselves and the surrounding microenvironment to form an ecosystem capable of drug resistance.

PMID:37577665 | PMC:PMC10418183 | DOI:10.1101/2023.08.03.551911

bioRxiv. 2023 Aug 5:2023.08.04.552083. doi: 10.1101/2023.08.04.552083. Preprint.

ABSTRACT

BACKGROUND: Hantaviruses - dichotomized into New World (i.e. Andes virus, ANDV; Sin Nombre virus, SNV) and Old-World viruses (i.e. Hantaan virus, HTNV) - are zoonotic viruses transmitted from rodents to humans. Currently, no FDA-approved vaccines against hantaviruses exist. Given the recent breakthrough to human-human transmission by the ANDV, an essential step is to establish an effective pandemic preparedness infrastructure to rapidly identify cell tropism, infective potential, and effective therapeutic agents through systematic investigation.

METHODS: We established human cell model systems in lung (airway and distal lung epithelial cells), heart (pluripotent stem cell-derived (PSC-) cardiomyocytes), and brain (PSC-astrocytes) cell types and subsequently evaluated ANDV, HTNV and SNV tropisms. Transcriptomic, lipidomic and bioinformatic data analyses were performed to identify the molecular pathogenic mechanisms of viruses in different cell types. This cell-based infection system was utilized to establish a drug testing platform and pharmacogenomic comparisons.

RESULTS: ANDV showed broad tropism for all cell types assessed. HTNV replication was predominantly observed in heart and brain cells. ANDV efficiently replicated in human and mouse 3D distal lung organoids. Transcriptomic analysis showed that ANDV infection resulted in pronounced inflammatory response and downregulation of cholesterol biosynthesis pathway in lung cells. Lipidomic profiling revealed that ANDV-infected cells showed reduced level of cholesterol esters and triglycerides. Further analysis of pathway-based molecular signatures showed that, compared to SNV and HTNV, ANDV infection caused drastic lung cell injury responses. A selective drug screening identified STING agonists, nucleoside analogues and plant-derived compounds that inhibited ANDV viral infection and rescued cellular metabolism. In line with experimental results, transcriptome data shows that the least number of total and unique differentially expressed genes were identified in urolithin B- and favipiravir-treated cells, confirming the higher efficiency of these two drugs in inhibiting ANDV, resulting in host cell ability to balance gene expression to establish proper cell functioning.

CONCLUSIONS: Overall, our study describes advanced human PSC-derived model systems and systems-level transcriptomics and lipidomic data to better understand Old and New World hantaviral tropism, as well as drug candidates that can be further assessed for potential rapid deployment in the event of a pandemic.

PMID:37577539 | PMC:PMC10418258 | DOI:10.1101/2023.08.04.552083

Front Pharmacol. 2023 Jul 27;14:1186540. doi: 10.3389/fphar.2023.1186540. eCollection 2023.

ABSTRACT

CYP2D6 is one of the most polymorphic drug-metabolizing enzymes in the liver. While genetic CYP2D6 variants serve as clinical biomarkers to predict CYP2D6 activity, large inter-person variability in CYP2D6 expression remains unaccounted for. Previous results suggest that there is variable expression of a CYP2D6 splice isoform with an in-frame deletion of exon 3 (CYP2D6ΔE3) encoding a protein lacking numerous active site residues. Here, using fragment analysis and RT-qPCR, we revealed that rs1058164 G (MAF = 27%-43%) is associated with increased formation of CYP2D6∆E3 in human liver samples (1.4-2.5-fold) and transfected cells. Furthermore, western blots showed that rs1058164 G was associated with a 50% decrease in full-length hepatic CYP2D6 protein expression. In addition, by studying a larger liver cohort, we confirmed our previous results that rs16947 (CYP2D6*2) reduces full-length CYP2D6 mRNA by increasing the production of an unstable splice isoform lacking exon 6 (CYP2D6ΔE6) and that the impact of CYP2D6ΔE6 is offset in carriers of the downstream enhancer variant rs5758550. The three frequent SNPs (rs1058164, rs16947, and rs5758550) form various 3-SNP-haplotypes, each with distinct CYP2D6 expression characteristics. Using an expression score (ES) system, we tested the impact of the 3-SNP-haplotype on improving the standard model to predict hepatic CYP2D6 protein expression based on genotype. A model that incorporates the 3-SNP-haplotype provided the best fit for CYP2D6 expression and also accounted for more variability in CYP2D6 protein levels (59%) than a model based on the accepted standard (36%) or one that only adds rs16947 and rs5758550 (42%). Clinical studies are needed to determine whether including the 3-SNP-haplotype alongside current standard CYP2D6 models improves the predictive value of CYP2D6 panels.

PMID:37576811 | PMC:PMC10412816 | DOI:10.3389/fphar.2023.1186540

J Cancer. 2023 Jul 24;14(12):2315-2328. doi: 10.7150/jca.85966. eCollection 2023.

ABSTRACT

Immune checkpoint inhibitor (ICI) therapy has dramatically changed cancer treatment, opening novel opportunities to cure malignant diseases. To date, most prevalently targeted immune checkpoints are programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), with many others being under extensive investigations. However, according to available data, only a fraction of patients may respond to ICI therapy. Additionally, this therapy may cause severe adverse immune-related side effects, such as diarrhea, headache, muscle weakness, rash, hepatitis and leucopenia, although most of them are not fatal, they can affect the patient's treatment outcome and quality of life. On the other hand, growing evidence has shown that phytochemicals with anticancer effects may combine ICI therapy to augment the safety and effectiveness of the treatment against cancer while reducing the adverse side effects. In this review, we summarize the state of art in the various experiments and clinical application of ICIs plus phytochemicals, with a focus on their combined use as a novel therapeutic strategy to cure cancer.

PMID:37576404 | PMC:PMC10414047 | DOI:10.7150/jca.85966

Front Psychiatry. 2023 Jul 27;14:1174195. doi: 10.3389/fpsyt.2023.1174195. eCollection 2023.

ABSTRACT

BACKGROUND: Kleefstra syndrome is a rare genetic condition, which affects at least 1 in 120,000 individuals who have a neurodevelopmental disorder, characterized by the core clinical phenotype of intellectual disability, hypotonia, severe speech delay, and distinct facial characteristics with additional clinical features including sleep disturbance, overweight, psychiatric disorders, and autism spectrum disorder. To date, a limited number of case reports of Kleefstra syndrome with psychiatric manifestations have been reported.

CASE PRESENTATION: We reported a case of a 35-year-old male diagnosed with Kleefstra syndrome, who also had diagnoses of autism spectrum disorder and moderate to severe intellectual disability. He exhibited various psychiatric manifestations, including temporarily manic-like symptoms, excessive eating/overweight, addictive/gambling behaviors, inappropriate and unsafe internet use, sleep disturbance, rigid routines, and behaviors that challenged in the form of meltdowns. These symptoms were eventually relatively successfully managed with a combination of non-pharmacological and pharmacological treatments.

CONCLUSION: To our knowledge, there is only a limited number of case reports that detail patients with Kleefstra syndrome exhibiting various psychiatric manifestations. Our report adds further knowledge to the paucity of literature and highlights the effectiveness of a combination of non-pharmacological and pharmacological treatments for behavioral/psychiatric difficulties in Kleefstra syndrome.

PMID:37575568 | PMC:PMC10416101 | DOI:10.3389/fpsyt.2023.1174195

Bio Protoc. 2023 Aug 5;13(15):e4731. doi: 10.21769/BioProtoc.4731. eCollection 2023 Aug 5.

ABSTRACT

Resistance of acute lymphoblastic leukemia (ALL) cells to chemotherapy, whether present at diagnosis or acquired during treatment, is a major cause of treatment failure. Primary ALL cells are accessible for drug sensitivity testing at the time of new diagnosis or at relapse, but there are major limitations with current methods for determining drug sensitivity ex vivo. Here, we describe a functional precision medicine method using a fluorescence imaging platform to test drug sensitivity profiles of primary ALL cells. Leukemia cells are co-cultured with mesenchymal stromal cells and tested with a panel of 40 anti-leukemia drugs to determine individual patterns of drug resistance and sensitivity ("pharmacotype"). This imaging-based pharmacotyping assay addresses the limitations of prior ex vivo drug sensitivity methods by automating data analysis to produce high-throughput data while requiring fewer cells and significantly decreasing the labor-intensive time required to conduct the assay. The integration of drug sensitivity data with genomic profiling provides a basis for rational genomics-guided precision medicine. Key features Analysis of primary acute lymphoblastic leukemia (ALL) blasts obtained at diagnosis from bone marrow aspirate or peripheral blood. Experiments are performed ex vivo with mesenchymal stromal cell co-culture and require four days to complete. This fluorescence imaging-based protocol enhances previous ex vivo drug sensitivity assays and improves efficiency by requiring fewer primary cells while increasing the number of drugs tested to 40. It takes approximately 2-3 h for sample preparation and processing and a 1.5-hour imaging time. Graphical overview.

PMID:37575398 | PMC:PMC10415213 | DOI:10.21769/BioProtoc.4731

Trials. 2023 Aug 13;24(1):525. doi: 10.1186/s13063-023-07574-9.

ABSTRACT

In their recent paper, Al and colleagues (Trials 2023;24:233) argue that manipulation of the methods of recruitment using well-known techniques in order to increase enrollment can be ethically acceptable. This brief response challenges that notion as an affront to voluntariness and a devolution of the ethics of human subjects research to the "ethics" of the marketplace.

PMID:37574550 | PMC:PMC10424340 | DOI:10.1186/s13063-023-07574-9

Food Chem. 2023 Aug 11;431:137127. doi: 10.1016/j.foodchem.2023.137127. Online ahead of print.

ABSTRACT

On-site multi-pesticide residues detection is particularly urgent and challenging. Here, we fabricated an enzyme-free ratiometric fluorescent detection system in combination with a hinge-like dual-channel 3D microfluidic paper analytical device (3D μPAD) for simultaneous visual detection of carbaryl and glyphosate. Blue-emission 1-naphthol (Em. 470 nm) was hydrolyzed from carbaryl, while yellow-emission 2,3-diaminophenazine (Em. 570 nm) was produced with the aid of Cu2+ for glyphosate sensing. Inner-filter effect between 1-naphthol or 2,3-diaminophenazine and green-emission carbon dots (Em. 510 nm) realized two ratiometric fluorescent detection systems. Remarkable color variation of green-blue for carbaryl (50.00-1100 μΜ) and yellow-green for glyphosate (5.00-600 μΜ) were observed on a dual-channel 3D μPAD without crosstalk. Their detection limits were 1.11 and 0.63 μΜ, respectively. The strategy realized simultaneous visual detection of carbaryl and glyphosate in food/herbal with excellent accuracy (spiked recoveries, 91.00-107.2%), high precision (RSD ≤ 8.43%), and superior selectivity.

PMID:37573744 | DOI:10.1016/j.foodchem.2023.137127

Nutrients. 2023 Jul 31;15(15):3408. doi: 10.3390/nu15153408.

ABSTRACT

In this study, we collected data from the National Health and Nutrition Examination Survey (NHANES) for the years 2011-2014. Multiple linear regression and logistic regression were used to analyse the association between nonfood pro- or prebiotic use and cognitive function among elderly Americans. To estimate the potential unobserved results, propensity score matching (PSM) was used to analyse the causal effect. Nonfood pro- or prebiotic use was analysed through the Dietary Supplement Use 30-Day Study. Cognitive function was evaluated by the Digit Symbol Substitution Test (DSST), the Animal Fluency Test (AFT), the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), and a composite Z-score calculated by summing the Z-scores of three tests. Male participants who used nonfood pro- or prebiotics tended to have higher comprehensive cognitive function (sum.z) with a β-coefficient of 0.64 (95% CI: 0.08-1.19). Probiotics or prebiotics may be a protective factor against cognitive impairment in males, with an odds ratio of 0.08 (95% CI: 0.02-0.29). Furthermore, the average treatment effect for the treated (ATT) with nonfood pro- or prebiotics (0.555) on sum.z in males was statistically significant (p < 0.05). Our research revealed that nonfood pre- or probiotic use was an effective method to improve cognitive function in elderly men from the USA.

PMID:37571344 | DOI:10.3390/nu15153408

Cancers (Basel). 2023 Jul 26;15(15):3788. doi: 10.3390/cancers15153788.

ABSTRACT

Gastric cancer is characterised by high inter- and intratumour heterogeneity. The majority of patients are older than 65 years and the global burden of this disease is increasing due to the aging of the population. The disease is usually diagnosed at advanced stages, which is a consequence of nonspecific symptoms. Few improvements have been made at the level of noninvasive molecular diagnosis of sporadic gastric cancer, and therefore the mortality rate remains high. A new field of mutational signatures has emerged in the past decade with advances in the genome sequencing technology. These distinct mutational patterns in the genome, caused by exogenous and endogenous mutational processes, can be associated with tumour aetiology and disease progression, and could provide novel perception on the treatment possibilities. This review assesses the mutational signatures found in gastric cancer and summarises their potential for use in clinical setting as diagnostic or prognostic biomarkers. Associated treatment options and biomarkers already implemented in clinical use are discussed, together with those that are still being explored or are in clinical studies.

PMID:37568604 | DOI:10.3390/cancers15153788

NPJ Digit Med. 2023 Aug 11;6(1):142. doi: 10.1038/s41746-023-00880-1.

ABSTRACT

Coronary angiography is the primary procedure for diagnosis and management decisions in coronary artery disease (CAD), but ad-hoc visual assessment of angiograms has high variability. Here we report a fully automated approach to interpret angiographic coronary artery stenosis from standard coronary angiograms. Using 13,843 angiographic studies from 11,972 adult patients at University of California, San Francisco (UCSF), between April 1, 2008 and December 31, 2019, we train neural networks to accomplish four sequential necessary tasks for automatic coronary artery stenosis localization and estimation. Algorithms are internally validated against criterion-standard labels for each task in hold-out test datasets. Algorithms are then externally validated in real-world angiograms from the University of Ottawa Heart Institute (UOHI) and also retrained using quantitative coronary angiography (QCA) data from the Montreal Heart Institute (MHI) core lab. The CathAI system achieves state-of-the-art performance across all tasks on unselected, real-world angiograms. Positive predictive value, sensitivity and F1 score are all ≥90% to identify projection angle and ≥93% for left/right coronary artery angiogram detection. To predict obstructive CAD stenosis (≥70%), CathAI exhibits an AUC of 0.862 (95% CI: 0.843-0.880). In UOHI external validation, CathAI achieves AUC 0.869 (95% CI: 0.830-0.907) to predict obstructive CAD. In the MHI QCA dataset, CathAI achieves an AUC of 0.775 (95%. CI: 0.594-0.955) after retraining. In conclusion, multiple purpose-built neural networks can function in sequence to accomplish automated analysis of real-world angiograms, which could increase standardization and reproducibility in angiographic coronary stenosis assessment.

PMID:37568050 | PMC:PMC10421915 | DOI:10.1038/s41746-023-00880-1

Front Cell Infect Microbiol. 2023 Jul 26;13:1157944. doi: 10.3389/fcimb.2023.1157944. eCollection 2023.

ABSTRACT

BACKGROUND: In patients with invasive fungal infection (IFI), the steady-state serum trough concentration (C min) of voriconazole (VCZ) is highly variable and can lead to treatment failure (C min < 0.5 mg/L) and toxicity (C min ≥ 5.0 mg/L). However, It remains challenging to determine the ideal maintenance dose to achieve the desired C min level quickly.

AIMS: This randomized, prospective observational single-center study aimed to identify factors affecting VCZ-C min and maintenance dose and create an algorithmic model to predict the necessary maintenance dose. MeThe study enrolled 306 adult IFI patients, split into two groups: non-gene-directed (A) (where CYP2C19 phenotype is not involved in determining VCZ dose) and gene-directed (B) (where CYP2C19 phenotype is involved in determining VCZ dose).

RESULTS: Results indicated that CYP2C19 genetic polymorphisms might significantly impact VCZ loading and maintenance dose selection. CYP2C19 phenotype, C-reaction protein (CRP), and average daily dose/body weight were significant influencers on VCZ-C min, while CYP2C19 phenotype, CRP, and body weight significantly impacted VCZ maintenance dose. A feasible predictive formula for VCZ stable maintenance dose was derived from the regression equation as a maintenance dose (mg) =282.774-0.735×age (year)+2.946×body weight(Kg)-19.402×CYP2C19 phenotype (UM/RM/NM:0, IM:1, PM:2)-0.316×CRP (mg/L) (p < 0.001).

DISCUSSION: DiThis formula may serve as a valuable supplement to the Clinical Pharmacogenetics Implementation Consortium (CPIC®) guideline for CYP2C19 and VCZ therapy, especially for IFI patients with highly variable inflammatory cytokines during VCZ therapy.

PMID:37565064 | PMC:PMC10410275 | DOI:10.3389/fcimb.2023.1157944

Lancet Reg Health Am. 2023 Aug 2;25:100566. doi: 10.1016/j.lana.2023.100566. eCollection 2023 Sep.

ABSTRACT

BACKGROUND: Pulmonary fibrosis is characterized by lung parenchymal destruction and can increase morbidity and mortality. Pulmonary fibrosis commonly occurs following hospitalization for SARS-CoV-2 infection. As there are medications that modify pulmonary fibrosis risk, we investigated whether distinct pharmacotherapies (amiodarone, cancer chemotherapy, corticosteroids, and rituximab) are associated with differences in post-COVID-19 pulmonary fibrosis incidence.

METHODS: We used the National COVID-19 Cohort Collaboration (N3C) Data Enclave, which aggregates and harmonizes COVID-19 data across the United States, to assess pulmonary fibrosis incidence documented at least 60 days after COVID-19 diagnosis among adults hospitalized between January 1st, 2020 and July 6th, 2022 without pre-existing pulmonary fibrosis. We used propensity scores to match pre-COVID-19 drug-exposed and unexposed cohorts (1:1) based on covariates with known influence on pulmonary fibrosis incidence, and estimated the association of drug exposure with risk for post-COVID-19 pulmonary fibrosis. Sensitivity analyses considered pulmonary fibrosis incidence documented at least 30- or 90-days post-hospitalization and pulmonary fibrosis incidence in the COVID-19-negative N3C population.

FINDINGS: Among 5,923,394 patients with COVID-19, we analyzed 452,951 hospitalized adults, among whom pulmonary fibrosis incidence was 1.1 per 100-person-years. 277,984 hospitalized adults with COVID-19 were included in our primary analysis, among whom all drug exposed cohorts were well-matched to unexposed cohorts (standardized mean differences <0.1). The post-COVID-19 pulmonary fibrosis incidence rate ratio (IRR) was 2.5 (95% CI 1.2-5.1, P = 0.01) for rituximab, 1.6 (95% CI 1.3-2.0, P < 0.0001) for chemotherapy, and 1.2 (95% CI 1.0-1.3, P = 0.02) for corticosteroids. Amiodarone exposure had no significant association with post-COVID-19 pulmonary fibrosis (IRR = 0.8, 95% CI 0.6-1.1, P = 0.24). In sensitivity analyses, pre-COVID-19 corticosteroid use was not consistently associated with post-COVID-19 pulmonary fibrosis. In the COVID-19 negative hospitalized population (n = 1,240,461), pulmonary fibrosis incidence was lower overall (0.6 per 100-person-years) and for patients exposed to all four drugs.

INTERPRETATION: Recent rituximab or cancer chemotherapy before COVID-19 infection in hospitalized patients is associated with increased risk for post-COVID-19 pulmonary fibrosis.

FUNDING: The analyses described in this publication were conducted with data or tools accessed through the NCATS N3C Data Enclave https://covid.cd2h.org and N3C Attribution & Publication Policy v1.2-2020-08-25b supported by NIHK23HL146942, NIHK08HL150291, NIHK23HL148387, NIHUL1TR002389, NCATSU24 TR002306, and a SECURED grant from the Walder Foundation/Center for Healthcare Delivery Science and Innovation, University of Chicago. WFP received a grant from the Greenwall Foundation. This research was possible because of the patients whose information is included within the data and the organizations (https://ncats.nih.gov/n3c/resources/data-contribution/data-transfer-agreement-signatories) and scientists who have contributed to the on-going development of this community resource (https://doi.org/10.1093/jamia/ocaa196).

PMID:37564420 | PMC:PMC10410516 | DOI:10.1016/j.lana.2023.100566

Drug Metab Dispos. 2023 Aug 10:DMD-AR-2023-001260. doi: 10.1124/dmd.123.001260. Online ahead of print.

ABSTRACT

In pharmacogenomic studies, the use of human liver microsomes as a model system to evaluate the impact of complex genomic traits (i.e., linkage-disequilibrium patterns, coding, and non-coding variation, etc.) on efficiency of drug metabolism is challenging. To accurately predict the true effect size of genomic traits requires large richly sampled datasets representative of the study population. Moreover, the acquisition of this data can be labor-intensive if the study design or bioanalytical methods are not high throughput, and it is potentially unfeasible if the abundance of sample needed for experiments is limited. To overcome these challenges, we developed a novel strategic approach using non-linear mixed effect models (NLME) to determine enzyme kinetic parameters for individual liver specimens using sparse data. This method can facilitate evaluation of the impact of complex genomic traits on the metabolism of xenobiotics in vitro when tissue and other resources are limited. In addition to facilitating the accrual of data, it allows for rigorous testing of covariates as sources of kinetic parameter variability. In this in silico study, we present a practical application of such an approach using previously published in vitro CYP2D6 data and explore the impact of sparse sampling, and experimental error on known kinetic parameter estimates of CYP2D6 mediated formation of 4-hydroxy-atomoxetine in human liver microsomes. Significance Statement This study presents a novel NLME based framework for evaluating the impact of complex genomic traits on Michaelis-Menten parameters in vitro using sparse data. The utility of this approach extends beyond gene variant associations, including determination of covariate effects on in vitro kinetic parameters, and reduced demand for precious experimental material.

PMID:37562955 | DOI:10.1124/dmd.123.001260

BMC Endocr Disord. 2023 Aug 10;23(1):167. doi: 10.1186/s12902-023-01425-z.

ABSTRACT

BACKGROUND AND PURPOSE: Primary hypothyroidism due to abnormality in the thyroid gland is the most common endocrine disease The recommended starting dose of levothyroxine replacement therapy is 1.6 µg/kg. This dose however is not optimal for every patient and dose adjustments are frequently done. Genetic polymorphisms in the absorption and metabolism pathway of levothyroxine are likely to influence its dose requirements. This study aimed to study the influence of genetic polymorphisms on levothyroxine replacement requirements.

METHODS: This was a cross-sectional study. Participants were recruited through a private nutrition clinic and through announcements distributed in the University of Petra in Amman, Jordan between September 2020 and February 2021. Hypothyroid patients had already been on stable doses of levothyroxine for the previous 3 months. A questionnaire was distributed to collect demographic and clinical information and a blood sample was taken for DNA extraction and clinical biochemistry analysis. rs11249460, rs2235544, rs225014, rs225015, rs3806596, rs11185644, rs4588, rs602662 were analyzed using Applied Biosystems TaqMan™ SNP Genotyping Assays on Rotor-Gene® Q and rs3064744 by direct sequencing. SPSS and Excel were used to perform analysis.

RESULTS: 76 patients were studied. The equation we calculated to find predicted daily dose of levothyroxine (mcg/kg) is 3.22+ (0.348 for CT genotype of rs11185644, 0 for other genotypes) + 0.027*disease duration (years) - 0.014*age (years) - 0.434*T3 (pmol/L) levels+ (0.296 for CC genotype of rs2235544, 0 for other genotypes).

CONCLUSION: SNP rs11185644 in RXRA gene and SNP rs2235544 in DIO1 affect dose requirement in hypothyroid patients and if confirmed in larger trials they can be used to individualize thyroxine starting doses.

PMID:37563580 | DOI:10.1186/s12902-023-01425-z

Clin Lab. 2023 Aug 1;69(8). doi: 10.7754/Clin.Lab.2023.230103.

ABSTRACT

BACKGROUND: Next-generation sequencing (NGS) methods have become more commonly performed in clinical and research laboratories.

METHODS: This review summarizes the current laboratory NGS-based diagnostic approaches in pharmacogenomics including targeted multi-gene panel sequencing, whole-exome sequencing (WES), and whole-genome sequencing (WGS).

RESULTS: Clinical laboratories perform multiple non-uniform types of pharmacogenetic panels, which can reduce the overall number of single-gene tests to be more cost-efficient. Compared to the targeted multi-gene panels, which are not typically designed to detect novel variants, WES and WGS have a greater potential to identify secondary pharmacogenomic findings, which might be predictive for the pharmacotherapy outcome of different patient settings. WGS overcomes the limitations of WES enabling a more accurate exome-sequencing at appropriate coverage and the sequencing of non-coding regions. Different NGS-based study designs with different test strategies and study populations, varying sample sizes, and distinct analytical and interpretation procedures lead to different identification results of pharmacogenomic variants.

CONCLUSIONS: The rapid progress in gene sequencing technologies will overcome the clinical and laboratory challenges of WES and WGS. Further high throughput NGS-based pharmacogenomics studies in different populations and patient settings are necessary to expand knowledge about rare functional variants and to enhance translation in clinical practice.

PMID:37560847 | DOI:10.7754/Clin.Lab.2023.230103

Heliyon. 2023 Jul 24;9(8):e18573. doi: 10.1016/j.heliyon.2023.e18573. eCollection 2023 Aug.

ABSTRACT

BACKGROUND: Genetic variations in Idiopathic Pulmonary Fibrosis (IPF) affect survival and outcomes. Current antifibrotic agents are managed based on the patient's reported side effects, although certain single nucleotide polymorphisms (SNPs) might alter treatment response and survival depending on the antifibrotic administered. This study investigated variations in response and outcomes to pirfenidone based on patients-specific genetic profiles.

METHODS: Retrospective clinical data were collected from 56 IPF patients and had blood drawn for DNA extraction between 7/2013 and 3/2016, with the last patient followed until 10/2018. Nine SNPs were selected for pharmacogenetic investigation based on prior associations with IPF treatment outcomes or implications for pirfenidone metabolism. Genetic variants were examined in relation to clinical data and treatment outcomes.

RESULTS: Of the 56 patients, 38 were males (67.85%). The average age of IPF at diagnosis was 66.88 years. At the initiation of pirfenidone, the average percent predicted FVC was 70.7%, and the average DLCO percent predicted was 50.02% (IQR 40-61%). Among the genetic variants tested, the TOLLIP rs5743890 risk allele was significantly associated with improved survival, with increasing pirfenidone duration. This finding was observed with CC or CT genotype carriers but not for those with the TT genotype (p = 0.0457). Similarly, the TGF-B1 rs1800470 risk allele was also significantly associated with improved survival with longer pirfenidone therapy (p = 0.0395), even though it was associated with disease progression.

CONCLUSION: This pilot study suggests that in IPF patients, the TOLLIP rs5743890 genotypes CC and CT, as well as TGF-B1 rs 1800470 may be associated with increased survival when treated with pirfenidone.

PMID:37560683 | PMC:PMC10407116 | DOI:10.1016/j.heliyon.2023.e18573

Am J Transl Res. 2023 Jul 15;15(7):4763-4769. eCollection 2023.

ABSTRACT

OBJECTIVES: Genetic variations contribute significantly to inter-individual responses to drugs and side effects. Pharmacogenomics has the potential to be utilized as a tool in disorders like schizophrenia with a high degree of genetic inheritance, although data on pharmacogenomics of schizophrenia are limited. Olanzapine and risperidone are the frequently used anti-psychotic drugs used in clinics. Studies have observed the variability in the response of both drugs in schizophrenic individuals. Considering the pharmacogenomics importance of both drugs, we aim to examine the cytochrome P 4501A1 (CYP1A1) and regulator of G-protein signaling 4 (RGS4) variants and their metabolizing status in 94 schizophrenic individuals of Indian descent.

METHODS: The present study is retrospective observational study. The metabolizing status of schizophrenic individuals was examined using Axiom Precision Medicine Diversity Array (PMDA) and the data were analyzed with the help of SNP Axiom Analysis Suite v5.1 (Affymetrix). The pharmacogenomics annotation was performed using PharmGKB.

RESULTS: Genotype and allele frequencies were observed. The results reveal the high frequency of poor metabolizers of olanzapine and risperidone in the studied cohort. In lieu of the high distribution of poor metabolizers, we compare observed allele frequencies with global populations' data to understand the variability of the genetic pool attained by Indian schizophrenic individuals.

CONCLUSIONS: Interestingly, the Indian schizophrenic cohort forms a different cluster compared to global populations, suggesting that pharmacogenomics testing might play an important role in clinical decision making for schizophrenia drug management.

PMID:37560209 | PMC:PMC10408541

Camb Prism Precis Med. 2023 Feb 9;1:e18. doi: 10.1017/pcm.2023.6. eCollection 2023.

ABSTRACT

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

PMID:37560024 | PMC:PMC10406571 | DOI:10.1017/pcm.2023.6

Oncol Lett. 2023 Jul 11;26(3):365. doi: 10.3892/ol.2023.13951. eCollection 2023 Sep.

ABSTRACT

Long non-coding RNAs (lncRNAs) serve an important role in cancer progression and may be used as efficient molecular biomarkers. The present study aimed to identify lncRNAs associated with the response to the receptor tyrosine kinase inhibitor sunitinib and transcriptome profile and clinical features of metastatic renal cell carcinoma (mRCC). The gene expression of 84 cancer-associated lncRNAs in tumor and non-malignant tissue samples of 38 patients with mRCC was evaluated using quantitative PCR. In addition, the coding transcriptome was estimated using RNA sequencing in a subgroup of 20 patients and mRNA-lncRNA intersections were identified. In total, 37 and 13 lncRNAs were down- and upregulated, respectively, in tumor compared with non-malignant adjacent tissue samples. A total of 10 and 4 lncRNAs were up- and downregulated, respectively, in good responders to sunitinib compared with poor responders. High expression of HNF1A-AS1 and IPW lncRNAs was associated with prolonged progression-free survival of patients and a high expression of the TUSC7 lncRNA was associated with poor response and worse survival. Significant associations of dysregulated MEG3 and SNHG16 lncRNAs with expression of protein-coding genes representing various pathways, were identified. Furthermore, a significantly higher expression of CLIP4 gene was observed in good responders. The present study revealed promising candidates for predictive and prognostic biomarkers with further therapeutic potential.

PMID:37559591 | PMC:PMC10407709 | DOI:10.3892/ol.2023.13951