Predictive factors of the contracture test for diagnosing malignant hyperthermia in a Brazilian population sample: a retrospective observational study

Mello, Jean Marcel de; Andrade, Pâmela Vieira de; Santos, João Paulo Fernandes; Oliveira, Acary Souza Bullé; Vainzof, Mariz; Amaral, José Luiz Gomes do; Silva, Helga Cristina Almeida da

doi:10.1016/j.bjane.2022.06.010

Cited by 2 publications

(1 citation statement)

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“…This study revealed other important pharmacogenes such as ryanodine receptor 1 (RYR1), calcium voltage-gated channel subunit alpha1 S (CACNA1S), and mitochondrially encoded 12S RNA (MT-RNR1), which also interact with several drugs ( n = 7) and possibly impact patient outcomes. Numerous polymorphisms in RYR1 and CACNA1S, which encode the ryanodine receptor and calcium channel in skeletal muscles, respectively, on chromosomes 19 and 1 ( 56 ), are associated with malignant hyperthermia when patients are preoperatively exposed to one of the anesthetic agents from the flurane group (desflurane, enflurane, isoflurane, methoxyflurane, sevoflurane), halothane, or succinylcholine ( 57 , 58 ). Nephrotoxicity and ototoxicity induced by aminoglycosides (amikacin, gentamicin, kanamycin, paromomycin, streptomycin, and tobramycin) are possibly related to variants in MT-RNR1, the mitochondrial RNA gene ( 59 ).…”

Section: Discussionmentioning

confidence: 99%

Pharmacogenes that demonstrate high association evidence according to CPIC, DPWG, and PharmGKB

Alshabeeb

Alyabsi²,

Aziz³

et al. 2022

Front. Med.

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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.

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