Using pharmacogenetics to predict methotrexate response in rheumatoid arthritis patients.

Expert Opin Drug Metab Toxicol. 2020 Jun 05;:

Authors: Szostak B, Machaj F, Rosik J, Pawlik A

Abstract
INTRODUCTION: Methotrexate (MTX) is a folate antagonist and a first-line drug for the treatment of rheumatoid arthritis (RA). However, in up to 30% of cases, MTX monotherapy is insufficient, while a further 30% of patients suffer with severe adverse effects. Despite extensive clinical evidence, it is not currently possible to predict therapy outcomes and drug toxicity for MTX. Therefore, to establish biomarkers of toxicity and successful disease remission, pharmacogenomic approaches are rapidly becoming more popular.
AREAS: This review summarizes recent pharmacogenomic studies evaluating MTX efficacy and toxicity. In recent years, multiple genetic alterations associated with MTX therapy outcomes and toxicity have been identified in genes associated with MTX metabolism and effector pathways. However, the data are inconsistent and require further validation.
EXPERT OPINION: To date, several single nucleotide polymorphisms (SNPs) have been linked with MTX efficacy. However, thanks to equivocal data, pharmacogenomic testing in routine clinical practice remains a distant prospect. Genome-wide association studies (GWAS) could facilitate the evaluation of current SNPs, and support searches for new genetic variations Once achieved, only then will it be possible to introduce more personalized and individualized therapies for RA patients.

PMID: 32500745 [PubMed - as supplied by publisher]

When to suspect transthyretin amyloidosis in cases of isolated vitreous opacities?

Amyloid. 2020 Jun 05;:1-2

Authors: Poignet B, Cauquil C, Barreau E, Bodaghi B, Terrada C, Adams D, Francou B, Labetoulle M, Rousseau A

PMID: 32500742 [PubMed - as supplied by publisher]

Research Review: Pediatric anxiety disorders - what have we learnt in the last 10 years?

J Child Psychol Psychiatry. 2020 Jun 05;:

Authors: Strawn JR, Lu L, Peris TS, Levine A, Walkup JT

Abstract
BACKGROUND: Anxiety disorders first emerge during the critical developmental periods of childhood and adolescence. This review synthesizes recent findings on the prevalence, risk factors, and course of the anxiety disorders; and their neurobiology and treatment.
METHODS: For this review, searches were conducted using PubMed, PsycINFO, and clinicaltrials.gov. Findings related to the epidemiology, neurobiology, risk factors, and treatment of pediatric anxiety disorders were then summarized.
FINDINGS: Anxiety disorders are high prevalence, and early-onset conditions associated with multiple risk factors including early inhibited temperament, environment stress, and structural and functional abnormalities in the prefrontal-amygdala circuitry as well as the default mode and salience networks. The anxiety disorders are effectively treated with cognitive behavioral therapy (CBT), selective serotonin reuptake inhibitors (SSRIs), and serotonin-norepinephrine reuptake inhibitors (SNRIs).
CONCLUSIONS: Anxiety disorders are high prevalence, early-onset conditions associated with a distinct neurobiological fingerprint, and are consistently responsive to treatment. Questions remain regarding who is at risk of developing anxiety disorders as well as the way in which neurobiology predicts treatment response.

PMID: 32500537 [PubMed - as supplied by publisher]

Clinical utility of next generation sequencing based HLA typing for disease association and pharmacogenetic testing.

Hum Immunol. 2020 Jun 01;:

Authors: Profaizer T, Pole A, Monds C, Delgado JC, Lázár-Molnár E

Abstract
HLA associations have been linked to many diseases and are important for risk assessment of drug hypersensitivity reactions. The increasing number of HLA alleles discovered generated a list of ambiguities that cannot be resolved with the current clinical assays, which commonly include sequence-specific oligonucleotide probe (SSOP) genotyping, and real-time PCR with melting curve analysis. HLA typing by next-generation sequencing (NGS) has recently been adopted by clinical laboratories for transplantation testing, as it provides unambiguous and cost-effective HLA typing. The goal of this study was to evaluate the feasibility of using NGS-based HLA-B and DQ genotyping for clinical HLA disease association testing, and provide direct comparison with the currently used clinical tests, including SSOP genotyping, and real-time PCR with melting curve analysis. While the real-time PCR method is easy and inexpensive to perform, ambiguities are rapidly increasing as more and more HLA alleles are discovered. SSOP genotyping identifies the alleles present but limitations include ambiguities and underreporting less common alleles. Our data show that HLA typing by NGS is superior to the existing clinical methods for identifying HLA alleles associated with disease or drug hypersensitivity, and offers a viable approach for high volume clinical diagnostic laboratories.

PMID: 32499099 [PubMed - as supplied by publisher]

Gene polymorphisms and risk of acute renal graft rejection: A field synopsis of meta-analyses and genome-wide association studies.

Transplant Rev (Orlando). 2020 Jul;34(3):100548

Authors: Cargnin S, Galli U, Lee KS, Shin JI, Terrazzino S

Abstract
In the present study we systematically re-analyzed results from meta-analyses and genome-wide association studies (GWASs) to assess the credibility of genetic associations with acute rejection risk in renal transplantation. A comprehensive literature search was performed on PubMed, Web of Knowledge, Cochrane library, and Open Grey up to July 2019. Methodological quality of systematic meta-analyses was assessed by the AMSTAR tool. Credibility of genetic associations was assessed by employing the Venice criteria and two Bayesian statistical approaches, the false positive report probability (FPRP) and the Bayesian false discovery probability (BFDP). Sixteen systematic meta-analyses, with a moderate-high quality score (median AMSTAR score: 9, range: 6-11) and 1 GWAS fulfilled the inclusion criteria. Overall, our systematic re-analysis has identified 9 polymorphic variants in 8 genes (ACE, CD28, CTLA-4, CYP3A5, IFNG, TNF-α, PTPRO and CCDC67) as potential risk factors for acute renal graft rejection. At the pre-specified prior probability of 0.001, the 2 SNPs identified by the GWAS (rs7976329 and rs10765602) showed no evidence of noteworthiness under FPRP or BFDP, indicating the possibility of false-positive associations. After applying the Venice criteria in combination with FPRP and BFDP to results from systematic meta-analyses, TT/AT vs AA of IFNG +874 T/A reached moderate epidemiological credibility, while weak evidence of association was found for all the other genetic comparisons. Well-designed GWASs and large replication studies with updated meta-analyses are still needed to identify reliable genetic predictors of acute renal graft rejection.

PMID: 32498977 [PubMed - in process]

Evaluation of the Predictive Ability, Environmental Regulation and Pharmacogenetics Utility of a BMI-Predisposing Genetic Risk Score during Childhood and Puberty.

J Clin Med. 2020 Jun 02;9(6):

Authors: Anguita-Ruiz A, González-Gil EM, Rupérez AI, Llorente-Cantarero FJ, Pastor-Villaescusa B, Alcalá-Fdez J, Moreno LA, Gil Á, Gil-Campos M, Bueno G, Leis R, Aguilera CM

Abstract
Polygenetic risk scores (pGRSs) consisting of adult body mass index (BMI) genetic variants have been widely associated with obesity in children populations. The implication of such obesity pGRSs in the development of cardio-metabolic alterations during childhood as well as their utility for the clinical prediction of pubertal obesity outcomes has been barely investigated otherwise. In the present study, we evaluated the utility of an adult BMI predisposing pGRS for the prediction and pharmacological management of obesity in Spanish children, further investigating its implication in the appearance of cardio-metabolic alterations. For that purpose, we counted on genetics data from three well-characterized children populations (composed of 574, 96 and 124 individuals), following both cross-sectional and longitudinal designs, expanding childhood and puberty. As a result, we demonstrated that the pGRS is strongly associated with childhood BMI Z-Score (B = 1.56, SE = 0.27 and p-value = 1.90 × 10-8), and that could be used as a good predictor of obesity longitudinal trajectories during puberty. On the other hand, we showed that the pGRS is not associated with cardio-metabolic comorbidities in children and that certain environmental factors interact with the genetic predisposition to the disease. Finally, according to the results derived from a weight-reduction metformin intervention in children with obesity, we discarded the utility of the pGRS as a pharmacogenetics marker of metformin response.

PMID: 32498346 [PubMed]

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pharmacogenomics

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13 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

pharmacogenomics

These pubmed results were generated on 2020/06/04

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

High-sensitivity C-reactive protein is associated with clonal hematopoiesis of indeterminate potential.

Blood Adv. 2020 Jun 09;4(11):2430-2438

Authors: Busque L, Sun M, Buscarlet M, Ayachi S, Feroz Zada Y, Provost S, Bourgoin V, Mollica L, Meisel M, Hinterleitner R, Jabri B, Dubé MP, Tardif JC

Abstract
Clonal hematopoiesis of indeterminate potential (CHIP) is predictive of hematological cancers and cardiovascular diseases, but the etiology of CHIP initiation and clonal expansion is unknown. Several lines of evidence suggest that proinflammatory cytokines may favor mutated hematopoietic stem cell expansion. To investigate the potential link between inflammation and CHIP, we performed targeted deep sequencing of 11 genes previously implicated in CHIP in 1887 subjects aged >70 years from the Montreal Heart Institute Biobank, of which 1359 had prior coronary artery disease (CAD), and 528 controls did not. We assessed association of CHIP with log transformed high-sensitivity C-reactive protein (hs-CRP), a validated biomarker of inflammation. CHIP was identified in 427 of the 1887 subjects (22.6%). CHIP mutations were more frequently identified in DNMT3A (11.6%) and TET2 (6.1%), with a higher proportion of TET2 mutations occurring in controls than in patients with CAD (9.0% vs 4.9%, P < .001). CHIP carriers had 21% higher hs-CRP levels compared with their noncarrier counterparts (eβ = 1.21, 95% confidence interval [CI]: 1.08 to 1.36; P = .001). A similar effect was observed in the subgroup of patients with known CAD (eβ = 1.22, 95% CI: 1.06 to 1.41; P = .005). These findings confirm the association between inflammation and CHIP. This association may open investigational avenues aimed at documenting mechanisms linking inflammation to clonal progression and ultimately supports prevention interventions to attenuate CHIP's impact on cardiovascular disease and cancer.

PMID: 32492156 [PubMed - as supplied by publisher]

Pharmacogenomics: Current Actionable Variants.

Rev Invest Clin. 2020 May 07;73(3)

Authors: González-Covarrubias V, Lozano K, Texis T, Guzmán-Cruz CK, Rodríguez-Dorantes M, Rubio-Carrasco K, Méndez-Lorenzo LH, Soberón X

Abstract
Pharmacogenomics (PGx), one of the several tools of precision medicine, has been slowly implemented in the clinic during the past decades. This process generally starts with direct and indirect genotype-phenotype associations of gene variants and drug efficacy, or adverse drug reactions, followed by replication and validation studies. Institutional efforts led by the PGx Research Network, The PGx Knowledge Base, and The Clinical Pharmacogenetics Implementation Consortium, mine all available data for further validation or research in additional populations. This data mining gives rise to a detailed classification of over 200 druggene pairs which, with enough documentation, may become part of a publishable guideline to aid clinicians in drug selection and dosing using genetics. The US Food and Drug Administration utilizes these guidelines to issue warnings and recommendations for specific drugs and their cautioning serves clinicians and pharmacists worldwide. Here, we aim to discuss the steps of this process and list existing actionable drug-gene pairs. Moreover, we describe the current status of PGx knowledge in populations from Mexico for actionable variants on the 19 genes listed by present PGx guidelines affecting 47 drugs. Our review collects current allele frequency information for these actionable variants, lists gaps of PGx information for relevant markers, and highlights the importance of continuing PGx research in Native and Mestizo populations.

PMID: 32488227 [PubMed - as supplied by publisher]

PARP Inhibitors as Therapeutic Options for Tyrosine Kinase-dependent Leukemia: A Review.

Anticancer Res. 2020 Jun;40(6):3055-3063

Authors: Machado CB, DA Silva EL, DE Moraes Filho MO, DE Moraes MEA, Moreira-Nunes CA

Abstract
The idea of utilizing poly-ADP-ribose polymerase inhibitors (PARPi) as therapeutics for cancer has grown in popularity since its original approval for clinical usage in treatment of BRCA DNA repair-associated-mutated ovarian cancer. In this study, we evaluated experimental data regarding in vitro studies utilizing PARPi as a treatment for tyrosine kinase (TK)-dependent leukemia. Studies from 2015 to 2019 were compiled and the ones with most relevant TK pathways and PARP inhibition were analyzed. PARPi showed activity against many leukemia cell lines and samples from patients with primary leukemia, especially when combined with other signaling pathway inhibitor drugs, improving upon the hypothesis that the utilization of PARPi has potential as a new therapeutic approach in treatment of primary leukemia and TK-dependent leukemia.

PMID: 32487599 [PubMed - in process]

Using Ethereum blockchain to store and query pharmacogenomics data via smart contracts.

BMC Med Genomics. 2020 Jun 01;13(1):74

Authors: Gürsoy G, Brannon CM, Gerstein M

Abstract
BACKGROUND: As pharmacogenomics data becomes increasingly integral to clinical treatment decisions, appropriate data storage and sharing protocols need to be adopted. One promising option for secure, high-integrity storage and sharing is Ethereum smart contracts. Ethereum is a blockchain platform, and smart contracts are immutable pieces of code running on virtual machines in this platform that can be invoked by a user or another contract (in the blockchain network). The 2019 iDASH (Integrating Data for Analysis, Anonymization, and Sharing) competition for Secure Genome Analysis challenged participants to develop time- and space-efficient Ethereum smart contracts for gene-drug relationship data.
METHODS: Here we design a specific smart contract to store and query gene-drug interactions in Ethereum using an index-based, multi-mapping approach. Our contract stores each pharmacogenomics observation, a gene-variant-drug triplet with outcome, in a mapping searchable by a unique identifier, allowing for time and space efficient storage and query. This solution ranked in the top three at the 2019 IDASH competition. We further improve our "challenge solution" and develop an alternate "fastQuery" smart contract, which combines together identical gene-variant-drug combinations into a single storage entry, leading to significantly better scalability and query efficiency.
RESULTS: On a private, proof-of-authority network, both our challenge and fastQuery solutions exhibit approximately linear memory and time usage for inserting into and querying small databases (<1,000 entries). For larger databases (1000 to 10,000 entries), fastQuery maintains this scaling. Furthermore, both solutions can query by a single field ("0-AND") or a combination of fields ("1- or 2-AND"). Specifically, the challenge solution can complete a 2-AND query from a small database (100 entries) in 35ms using 0.1 MB of memory. For the same query, fastQuery has a 2-fold improvement in time and a 10-fold improvement in memory.
CONCLUSION: We show that pharmacogenomics data can be stored and queried efficiently using Ethereum blockchain. Our solutions could potentially be used to store a range of clinical data and extended to other fields requiring high-integrity data storage and efficient access.

PMID: 32487214 [PubMed - in process]

Brazilian cohort and genes encoding for drug metabolizing enzymes and drug transporters.

Pharmacogenomics. 2020 Jun 03;:

Authors: Kim V, Wal TV, Nishi MY, Montenegro LR, Carrilho FJ, Hoshida Y, Ono SK

Abstract
Background & aim: Genetic variability in drug absorption, distribution, metabolism and excretion (ADME) genes contributes to the high heterogeneity of drug responses. The present study investigated polymorphisms of ADME genes frequencies and compared the findings with populations from other continents, available in the 1 KGP and ExAC databases. Methodology & results: We conducted a study of 100 patients in Brazil and a total of 2003 SNPs were evaluated by targeted next-generation sequencing in 148 genes, including Phase I enzymes (n = 50), Phase II enzymes (n = 38) and drug transporters (n = 60). Overall, the distribution of minor allele frequency (MAF) suggests that the distribution of 2003 SNPs is similar between Brazilian cohort, 1000 Genome Project (1 KGP) and the Exome Aggregation Consortium (ExAC); however, we found moderate SNP allele-frequency divergence between Brazilian cohort and both 1000 KGP and ExAC. These differences were observed in several relevant genes including CYP3A4, NAT2 and SLCO1B1. Conclusion: We concluded that the Brazilian population needs clinical assessment of drug treatment based on individual genotype rather than ethnicity.

PMID: 32486903 [PubMed - as supplied by publisher]

Strategy to effectively and efficiently implement voriconazole pharmacogenetics in clinical practice.

Pharmacogenomics. 2020 Jun 03;:

Authors: García IG, Carcas AJ, Borobia AM

PMID: 32486895 [PubMed - as supplied by publisher]

Matrix Metalloproteinases as Biomarkers of Atherosclerotic Plaque Instability.

Int J Mol Sci. 2020 May 31;21(11):

Authors: Olejarz W, Łacheta D, Kubiak-Tomaszewska G

Abstract
Matrix metalloproteinases (MMPs) are a family of zinc-dependent endopeptidases responsible for tissue remodeling and degradation of extracellular matrix (ECM) proteins. MMPs may modulate various cellular and signaling pathways in atherosclerosis responsible for progression and rupture of atherosclerotic plaques. The effect of MMPs polymorphisms and the expression of MMPs in both the atherosclerotic plaque and plasma was shown. They are independent predictors of atherosclerotic plaque instability in stable coronary heart disease (CHD) patients. Increased levels of MMPs in patients with advanced cardiovascular disease (CAD) and acute coronary syndrome (ACS) was associated with future risk of cardiovascular events. These data confirm that MMPs may be biomarkers in plaque instability as they target in potential drug therapies for atherosclerosis. They provide important prognostic information, independent of traditional risk factors, and may turn out to be useful in improving risk stratification.

PMID: 32486345 [PubMed - in process]

Genetic Variation of the Vitamin D Binding Protein Affects Vitamin D Status and Response to Supplementation in Infants.

J Clin Endocrinol Metab. 2019 11 01;104(11):5483-5498

Authors: Enlund-Cerullo M, Koljonen L, Holmlund-Suila E, Hauta-Alus H, Rosendahl J, Valkama S, Helve O, Hytinantti T, Viljakainen H, Andersson S, Mäkitie O, Pekkinen M

Abstract
CONTEXT: Single nucleotide polymorphisms (SNPs) of the vitamin D binding protein encoding the GC (group component) gene affect 25-hydroxyvitamin D (25OHD) concentrations, but their influence on vitamin D status and response to vitamin D supplementation in infants is unknown.
OBJECTIVE: To study GC genotype-related differences in 25OHD concentrations and the response to supplementation during a vitamin D intervention study in infants.
DESIGN: In this randomized controlled trial, healthy term infants received vitamin D3 (10 or 30 μg/d) from 2 weeks to 24 months of age. GC SNPs rs2282679, rs4588, rs7041, and rs1155563 were genotyped. rs4588/7041 diplotype and haplotypes of rs2282679, rs4588, and rs7041 (Haplo3SNP) and of all four SNPs (Haplo4SNP) were determined.
MAIN OUTCOME MEASURES: 25OHD measured in cord blood at birth and at 12 and 24 months during intervention.
RESULTS: A total of 913 infants were included. Minor allele homozygosity of all studied GC SNPs, their combined haplotypes, and rs4588/rs7041 diplotype 2/2 were associated with lower 25OHD concentrations at all time points in one or both intervention groups [analysis of covariance (ANCOVA) P < 0.043], with the exception of rs7041, which did not affect 25OHD at birth. In the high-dose supplementation group receiving 30 μg/d vitamin D3, but not in those receiving 10 µg/d, genotype of rs2282679, rs4588, and rs7041; diplotype; and Haplo3SNP significantly affected intervention response (repeated measurement ANCOVA Pinteraction < 0.019). Minor allele homozygotes had lower 25OHD concentrations and smaller increases in 25OHD throughout the intervention.
CONCLUSIONS: In infants, vitamin D binding protein genotype affects 25OHD concentration and efficiency of high-dose vitamin D3 supplementation.

PMID: 31365099 [PubMed - indexed for MEDLINE]

Insights into incretin-based therapies for treatment of diabetic dyslipidemia.

Adv Drug Deliv Rev. 2020 May 30;:

Authors: Stemmer K, Finan B, DiMarchi RD, Tschöp MH, Müller TD

Abstract
Derangements in triglyceride and cholesterol metabolism (dyslipidemia) are major risk factors for the development of cardiovascular diseases in obese and type-2 diabetic (T2D) patients. An emerging class of glucagon-like peptide-1 (GLP-1) analogues and next generation peptide dual-agonists such as GLP-1/glucagon or GLP-1/GIP could provide effective therapeutic options for T2D patients. In addition to their role in glucose and energy homeostasis, GLP-1, GIP and glucagon serve as regulators of lipid metabolism. This review summarizes the current knowledge in GLP-1, glucagon and GIP effects on lipid and lipoprotein metabolism and frames the emerging therapeutic benefits of GLP-1 analogs and GLP-1-based multiagonists as add-on treatment options for diabetes associated dyslipidemia.

PMID: 32485206 [PubMed - as supplied by publisher]

Vascular Endothelial Growth Factor (VEGF) as a Vital Target for Brain Inflammation during the COVID-19 Outbreak.

ACS Chem Neurosci. 2020 Jun 02;:

Authors: Yin XX, Zheng XR, Peng W, Wu ML, Mao XY

Abstract
The coronavirus disease 19 (COVID-19) pandemic has brought a great threat to global public health. Currently, mounting evidence has shown the occurrence of neurological symptoms in patients with COVID-19. However, the detailed mechanism by which the SARS-CoV-2 attacks the brain is not well characterized. Recent investigations have revealed that a cytokine storm contributes to brain inflammation and subsequently triggers neurological manifestations during the COVID-19 outbreak. Targeting brain inflammation may provide significant clues to the treatment of neurologic complications caused by SARS-CoV-2. Vascular growth factor (VEGF), which is widely distributed in the brain, probably plays a crucial role in brain inflammation via facilitating the recruitment of inflammatory cells and regulating the level of angiopoietins II (Ang II). Also, Ang II is considered as the products of SARS-CoV-2-attacking target, angiotensin-converting enzyme 2 (ACE2). Further investigation of the therapeutic potential and the underlying mechanisms of VEGF-targeted drugs on the neurological signs of COVID-19 are warranted. In any case, VEGF is deemed a promising therapeutic target in suppressing inflammation during SARS-CoV-2 infection with neurological symptoms.

PMID: 32485101 [PubMed - as supplied by publisher]

Scoring functions for drug-effect similarity.

Brief Bioinform. 2020 Jun 02;:

Authors: Struckmann S, Ernst M, Fischer S, Mah N, Fuellen G, Möller S

Abstract
MOTIVATION: The difficulty to find new drugs and bring them to the market has led to an increased interest to find new applications for known compounds. Biological samples from many disease contexts have been extensively profiled by transcriptomics, and, intuitively, this motivates to search for compounds with a reversing effect on the expression of characteristic disease genes. However, disease effects may be cell line-specific and also depend on other factors, such as genetics and environment. Transcription profile changes between healthy and diseased cells relate in complex ways to profile changes gathered from cell lines upon stimulation with a drug. Despite these differences, we expect that there will be some similarity in the gene regulatory networks at play in both situations. The challenge is to match transcriptomes for both diseases and drugs alike, even though the exact molecular pathology/pharmacogenomics may not be known.
RESULTS: We substitute the challenge to match a drug effect to a disease effect with the challenge to match a drug effect to the effect of the same drug at another concentration or in another cell line. This is welldefined, reproducible in vitro and in silico and extendable with external data. Based on the Connectivity Map (CMap) dataset, we combined 26 different similarity scores with six different heuristics to reduce the number of genes in the model. Such gene filters may also utilize external knowledge e.g. from biological networks. We found that no similarity score always outperforms all others for all drugs, but the Pearson correlation finds the same drug with the highest reliability. Results are improved by filtering for highly expressed genes and to a lesser degree for genes with large fold changes. Also a network-based reduction of contributing transcripts was beneficial, here implemented by the FocusHeuristics. We found no drop in prediction accuracy when reducing the whole transcriptome to the set of 1000 landmark genes of the CMap's successor project Library of Integrated Network-based Cellular Signatures. All source code to re-analyze and extend the CMap data, the source code of heuristics, filters and their evaluation are available to propel the development of new methods for drug repurposing.
AVAILABILITY: https://bitbucket.org/ibima/moldrugeffectsdb.
CONTACT: steffen.moeller@uni-rostock.de.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.

PMID: 32484516 [PubMed - as supplied by publisher]

Influence of genetic variants and antiepileptic drug co-treatment on lamotrigine plasma concentration in Mexican Mestizo patients with epilepsy.

Pharmacogenomics J. 2020 Jun 02;:

Authors: Ortega-Vázquez A, Fricke-Galindo I, Dorado P, Jung-Cook H, Martínez-Juárez IE, Monroy-Jaramillo N, Rojas-Tomé IS, Peñas-Lledó E, Llerena A, López-López M

Abstract
Genetic and nongenetic factors may contribute to lamotrigine (LTG) plasma concentration variability among patients. We simultaneously investigated the association of UGT1A1, UGT1A4, UGT2B7, ABCB1, ABCG2, and SLC22A1 variants, as well as antiepileptic drug co-treatment, on LTG plasma concentration in 97 Mexican Mestizo (MM) patients with epilepsy. UGT1A4*1b was associated with lower LTG dose-corrected concentrations. Patients with the UGT2B7-161T allele were treated with 21.22% higher LTG daily dose than those with CC genotype. Two novel UGT1A4 variants (c.526A>T; p.Thr185= and c.496T>C; p.Ser166Leu) were identified in one patient. Patients treated with LTG + valproic acid (VPA) showed higher LTG plasma concentration than patients did on LTG monotherapy or LTG + inducer. Despite the numerous drug-metabolizing enzymes and transporter genetic variants analyzed, our results revealed that co-treatment with VPA was the most significant factor influencing LTG plasma concentration, followed by UGT1A4*1b, and that patients carrying UGT2B7 c.-161T required higher LTG daily doses. These data provide valuable information for the clinical use of LTG in MM patients with epilepsy.

PMID: 32483200 [PubMed - as supplied by publisher]