Novel KCNQ2 Mutation in a Large Emirati Family With Benign Familial Neonatal Seizures

Mutations in voltage-gated potassium channel Kv7.2 are responsible for benign familial neonatal seizures type 1, a rare monogenic autosomal dominant inherited epilepsy syndrome. We describe a novel mutation (c.1126_1127delA) in exon 9 of KCNQ2, the gene encoding for the Kv7.2 channel, in a large Emirati family with benign familial neonatal seizures type 1. The mutation leads to a frameshift at amino acid position 376, triggering loss of function and haploinsufficiency. Patients with this mutation manifest repeated clonic seizures with normal interictal electroencephalograms and favorable prognoses. Signs occur within the first days of age, lingering well into puberty. KCNQ2 mutation screening, alongside genetic counseling, should be included in diagnostic evaluations of neonatal epileptic patients, potentially sparing the need for unnecessary investigations and treatment. To our knowledge, this report is the first of a KCNQ2 mutation in an Emirati family with benign familial neonatal seizures type 1.     

Improved accuracy of anticoagulant dose prediction using a pharmacogenetic and artificial neural network-based method

Background

The unpredictability of acenocoumarol dose needed to achieve target blood thinning level remains a challenge. We aimed to apply and compare a pharmacogenetic least-squares model (LSM) and artificial neural network (ANN) models for predictions of acenocoumarol dosing.

Methods

LSM and ANN models were used to analyze previously collected data on 174 participants (mean age: 67.45 SD 13.49 years) on acenocoumarol maintenance therapy. The models were based on demographics, lifestyle habits, concomitant diseases, medication intake, target INR, and genotyping results for CYP2C9 and VKORC1. LSM versus ANN performance comparisons were done by two methods: by randomly splitting the data as 50 % derivation and 50 % validation cohort followed by a bootstrap of 200 iterations, and by a 10-fold leave-one-out cross-validation technique.

Results

The ANN-based pharmacogenetic model provided higher accuracy and larger R value than all other LSM-based models. The accuracy percentage improvement ranged between 5 % and 24 % for the derivation cohort and between 12 % and 25 % for the validation cohort. The increase in R value ranged between 6 % and 31 % for the derivation cohort and between 2 % and 31 % for the validation cohort. ANN increased the percentage of accurately dosed subjects (mean absolute error ≤1 mg/week) by 14.1 %, reduced the percentage of mis-dosed subjects (mean absolute error 2-3 mg/week) by 7.04 %, and reduced the percentage of grossly mis-dosed subjects (mean absolute error ≥4 mg/week) by 24 %.

Conclusions

ANN-based pharmacogenetic guidance of acenocoumarol dosing reduces the error in dosing to achieve target INR. These results need to be ascertained in a prospective study.     

The epidemiology of non-alcoholic steatohepatitis (NASH) in the United States between 2010-2020: a population-based study

Introduction and objectivesNon-alcoholic steatohepatitis (NASH) is a severe form of non-alcoholic fatty liver disease (NAFLD) that can progress to liver cirrhosis, liver failure and hepatocellular carcinoma. It is the second leading cause of liver transplant in the US. We aim to investigate the prevalence, demographics and risk factors NASH patients in the US.Patients and methodsWe used a large database (Explorys IBM) that aggregates electronic health records from 26 nationwide healthcare systems. We identified adults with NASH between 2010-2020. Demographics including age, gender and race were collected. NASH risk factors including Diabetes Millets (DM), Hyperlipidemia (HLD), Hypertension (HTN) and Obesity were also collected. Cochran-Armitage test was used to assess the statistical significance of year-by-year trend. Univariable and multivariable logistic regression were used to estimate the odds ratio (OR) of risk factors.ResultsNASH annual prevalence rate increased from 1.51% in 2010 to 2.79% in 2020 (p < 0.0001). The proportion of patients with NASH by gender was 54.1% female vs 45.9% male (OR 1.04 [0.91-1.11]). Caucasian had higher odds of NASH than non-Caucasian (OR 1.42 [1.31-1.54]). NASH is strongly associated with DM and obesity (OR 18.61 [17.35-19.94]) and (OR 20.97 [17.87-23.21]), respectively. Other components of metabolic syndrome were associated with NASH to a lesser degree; HTN (OR 3.24 [3.20-3.28]) and HLD (OR 4.93 [4.85-4.01]).ConclusionThe prevalence of NASH has significantly increased in the US in the last decade. This is likely related to the increased prevalence of risk factors as well as increased awareness of the disease.