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Background: The drugs impacted by genetic variants are known as pharmacogenetic (PGx) drugs. Patients’ responses to these drugs may vary according to the variability in patients’ genetic makeup. Hence, exploring the pharmacogenes that affect drug treatment is vital to ensure optimal therapy and patients’ safety. This study aimed to describe the usage rate of PGx drugs and the frequency of relevant variants in the Saudi population. Methodology: Prescription patterns over seven years (2015–2021) for Saudi patients on PGx drugs treated at the Ministry of National Guard-Health Affairs (MNG-HA) were investigated. Only registered drugs in the MNG-HA formulary (n = 78) were included. The patients were subgrouped into four age groups: ≤24, 25–44, 45–64, and ≥65 years. Further subgrouping was made according to gender and drugs’ therapeutic categories following anatomical therapeutic chemical (ATC) classification.Furthermore, an online searching was carried out to identify the pharmacogenes reported in the literature among healthy Saudis. The search included 45 genes that may affect drug outcomes based on evidence rated by either CPIC (A-B levels) or PharmGKB (1–2 levels). Results: The screened patients were 1,483,905. Patients on PGx drugs accounted for 46.7% (n = 693,077 patients). The analgesic group was the most prescribed drug category (47%), which included ibuprofen (20.5%), celecoxib (6.3%), tramadol (5.8%), and others. Cardiovascular agents were the second-most utilized drug class (24.4%). Omeprazole was the second most commonly used medication (11.1%) but ranked third as a class (gastroenterology). Females used PGx drugs more frequently than males (53.5% versus 46.5%) and a higher usage rate by patients aged 45–64 years (31.3%) was noted. The cytochrome P450 genes (CYP2C9, CYP2C19, and CYP2D6) were estimated to impact responses of 54.3% (n = 1,156,113) of the used drugs (27.2% are possibly affected by CYP2C9, 12.8% by CYP2C19, and 14.3% by CYP2D6). Thirty-five pharmacogenes that characterize Saudi population and their variants’ allele frequencies were identified from previous reports. This study presents the largest reported number of genes that may affect drug therapies among Saudis. Conclusion: This study confirmed that a high percentage of Saudi patients use PGx drugs and various genotypes of certain pharmacogenes are inherited by the Saudi population.

BackgroundThe lockdown at the start of coronavirus disease 2019 (COVID-19) pandemic in Saudi Arabia (March 2020 to June 2020) shifted routine in-person care for patients with type 2 diabetes mellitus (T2DM) to telemedicine. The aim of this study was to investigate the impact telemedicine had during this period on glycemic control (HbA1c) in patients with T2DMMethods4,266 patients with T2DM were screened from five Ministry of National Guard Health Affairs hospitals in the Kingdom of Saudi Arabia. Age, gender, body mass index (BMI), HbA1c (before and after the COVID-19 lockdown), duration of T2DM, comorbidities and antidiabetic medications data were obtained. Mean and standard deviation of differences in HbA1c were calculated to assess the impact of telemedicine intervention. Correlations between clinically significant variances (when change in the level is ≥0.5%) in HbA1c with demographics and clinical characteristic data were determined using chi square test.ResultsMost of the participants were Saudis (97.7%) with 59.7% female and 56.4% ≥60 years of age. Obesity was 63.8%, dyslipidemia 91%, and hypertension 70%. Mean HbA1c of all patients slightly rose from 8.52% ± 1.5% before lockdown to 8.68% ± 1.6% after lockdown. There were n=1,064 patients (24.9%) whose HbA1c decreased by ≥0.5%, n =1,574 patients whose HbA1c increased by ≥0.5% (36.9%), and n =1,628 patients whose HbA1c changed by

BackgroundDifferent levels of evidence related to the variable responses of individuals to drug treatment have been reported in various pharmacogenomic (PGx) databases. Identification of gene-drug pairs with strong association evidence can be helpful in prioritizing the implementation of PGx guidelines and focusing on a gene panel. This study aimed to determine the pharmacogenes with the highest evidence-based association and to indicate their involvement in drug-gene interactions.MethodologyThe publicly available datasets CPIC, DPWG, and PharmGKB were selected to determine the pharmacogenes with the highest drug outcome associations. The upper two levels of evidence rated by the three scoring methods were specified (levels A–B in CPIC, 3–4 in DPWG, or 1–2 levels in PharmGKB). The identified pharmacogenes were further ranked in this study based on the number of medications they interacted with.ResultsFifty pharmacogenes, with high to moderately high evidence of associations with drug response alterations, with potential influence on the therapeutic and/or toxicity outcomes of 152 drugs were identified. CYP2D6, CYP2C9, CYP2C19, G6PD, HLA-B, SLCO1B1, CACNA1S, RYR1, MT-RNR1, and IFNL4 are the top 10 pharmacogenes, where each is predicted to impact patients' responses to ≥5 drugs.ConclusionThis study identified the most important pharmacogenes based on the highest-ranked association evidence and their frequency of involvement in affecting multiple drugs. The obtained data is useful for customizing a gene panel for PGx testing. Identifying the strength of scientific evidence supporting drug-gene interactions aids drug prescribers in making the best clinical decision.

Abstract Background Limb-girdle muscular dystrophies (LGMDs) are large group of heterogeneous genetic diseases, having a hallmark feature of muscle weakness. Pathogenic mutations in the gene encoding the giant skeletal muscle protein titin (TTN) are associated with several muscle disorders, including cardiomyopathy, recessive congenital myopathies and limb-girdle muscular dystrophy (LGMD) type10. The phenotypic spectrum of titinopathies is expanding, as next generation sequencing (NGS) technology makes screening of this large gene possible. Aim This study aimed to identify the pathogenic variant in a consanguineous Pakistani family with autosomal recessive LGMD type 10. Methods DNA from peripheral blood samples were obtained, whole exome sequencing (WES) was performed and several molecular and bioinformatics analysis were conducted to identify the pathogenic variant. TTN coding and near coding regions were further amplified using PCR and sequenced via Sanger sequencing. Results Whole exome sequencing analysis revealed a novel homozygous missense variant (c.98807G > A; p.Arg32936His) in the TTN gene in the index patients. No heterozygous individuals in the family presented LGMD features. The variant p.Arg32936His leads to a substitution of the arginine amino acid at position 32,936 into histidine possibly causing LGMD type 10. Conclusion We identified a homozygous missense variant in TTN, which likely explains LGMD type 10 in this family in line with similar previously reported data. Our study concludes that WES is a successful molecular diagnostic tool to identify pathogenic variants in large genes such as TTN in highly inbred population.

Split hand/split foot malformation (SHFM) or ectrodactyly is characterized by a deep median cleft of the hand or foot, hypoplasia or aplasia of the metacarpals, metatarsals, and phalanges. It is a clinically and genetically heterogeneous group of limb malformations. This study aimed to identify the pathogenic variant in a consanguineous Pakistani family with autosomal recessive SHFM. Peripheral blood samples were obtained, DNA was extracted, WNT10B coding and noncoding regions were PCR amplified and Sanger sequencing was performed using workflow suggested by Thermo Fisher Scientific. A novel homozygous nonsense variant (c.1098C>A; p.Cys366*) was identified in the WNT10B gene in the index patients, which probably explains SHFM type 6 in this family in comparison with similar data from the literature.

IntroductionThe Dutch Pharmacogenetics Working Group (DPWG) indicated a list of actionable genotypes that affect patients’ response to more 50 drugs; these drugs which show variable effects based on patients’ genetic traits were named as pharmacogenetics (PGX) drugs. Preemptive genetic testing before using these drugs may protect certain patients from serious adverse reactions and could help in avoiding treatment failures. The objectives of this study include identifying the rate of PGX drug usage among Dutch population, estimating the level of users who carry the actionable genotypes and determining the main genes involved in drug’s effect variability.MethodsUsage of PGX drugs over 2011–2017 by the insured population (an average of 11.4 million) in outpatient clinics in Netherlands was obtained from the publically available GIP databank. The data of 45 drugs were analyzed and their interactions with selected pharmacogenes were estimated. Frequency of actionable genotypes of 249 Dutch parents was obtained from the public database: Genome of Netherlands (GoNL), to identify the pattern of genetic characteristics of Dutch population.ResultsOver a 7 year period, 51.3 million exposures of patients to PGX drugs were reported with an average of 5.3 exposures per each drug user. One quarterof the exposures (12.4 million) are predicted to be experienced by individuals with actionable genotypes (risky exposures). Up to 60% of the risky exposures (around 7.5 million) were related to drugs metabolized by CYP2D6. SLCO1B1, and CYP2C19 were also identified among the top genes affecting response of drugs users (involved in about 22 and 12.4% of the risky exposures, respectively). Cardiovascular medications were the top prescribed PGX drug class (43%), followed by gastroenterology (29%) and psychiatry/neurology medications (15%). Women use more PGX drugs than men (55.8 vs. 44.2%, respectively) with the majority (84%) of users in both sexes are above 45 years.ConclusionPGX drugs are commonly used in Netherlands. Preemptive panel testing for CYP2D6, SLCO1B1, and CYP2C19 only could be useful to predict 95% of vulnerable patients’ exposures to PGX drugs. Future studies to assess the economic impact of preemptive panel testing on patients of older age are suggested.

Please be advised that following publication of the original article [1], the authors have identified the following errors with the scientific content.