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NRSF and BDNF polymorphisms as biomarkers of cognitive dysfunction in adults with newly diagnosed epilepsy.

ABSTRACT: Cognitive dysfunction is a common comorbidity in people with epilepsy, but its causes remain unclear. It may be related to the etiology of the disorder, the consequences of seizures, or the effects of antiepileptic drug treatment. Genetics may also play a contributory role. We investigated the influence of variants in the genes encoding neuron-restrictive silencer factor (NRSF) and brain-derived neurotrophic factor (BDNF), proteins previously associated with cognition and epilepsy, on cognitive function in people with newly diagnosed epilepsy. A total of 82 patients who had previously undergone detailed neuropsychological assessment were genotyped for single nucleotide polymorphisms (SNPs) across the NRSF and BDNF genes. Putatively functional SNPs were included in a genetic association analysis with specific cognitive domains, including memory, psychomotor speed, and information processing. Cross-sectional and longitudinal designs were used to explore genetic influences on baseline cognition at diagnosis and change from baseline over the first year since diagnosis, respectively. We found a statistically significant association between genotypic variation and memory function at both baseline (NRSF: rs1105434, rs2227902 and BDNF: rs1491850, rs2030324, rs11030094) and in our longitudinal analysis (NRSF: rs2227902 and BDNF: rs12273363). Psychomotor speed was also associated with genotype (NRSF rs3796529) in the longitudinal assessment. In line with our previous work on general cognitive function in the healthy aging population, we observed an additive interaction between risk alleles for the NRSF rs2227902 (G) and BDNF rs6265 (A) polymorphisms which was again consistent with a significantly greater decline in delayed recall over the first year since diagnosis. These findings support a role for the NRSF-BDNF pathway in the modulation of cognitive function in patients with newly diagnosed epilepsy.

SUBMITTER: Warburton A

PROVIDER: S-EPMC4732989 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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NRSF and BDNF polymorphisms as biomarkers of cognitive dysfunction in adults with newly diagnosed epilepsy.

Warburton Alix A Miyajima Fabio F Shazadi Kanvel K Crossley Joanne J Johnson Michael R MR Marson Anthony G AG Baker Gus A GA Quinn John P JP Sills Graeme J GJ

Epilepsy & behavior : E&B 20151217

Cognitive dysfunction is a common comorbidity in people with epilepsy, but its causes remain unclear. It may be related to the etiology of the disorder, the consequences of seizures, or the effects of antiepileptic drug treatment. Genetics may also play a contributory role. We investigated the influence of variants in the genes encoding neuron-restrictive silencer factor (NRSF) and brain-derived neurotrophic factor (BDNF), proteins previously associated with cognition and epilepsy, on cognitive ...[more]

PMID: 26708060

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Project description:IntroductionEpilepsy is one of the most common serious brain disorders, characterised by seizures that severely affect a person's quality of life and, frequently, their cognitive and mental health. Although most existing work has examined chronic epilepsy, newly diagnosed patients present a unique opportunity to understand the underlying biology of epilepsy and predict effective treatment pathways. The objective of this prospective cohort study is to examine whether cognitive dysfunction is associated with measurable brain architectural and connectivity impairments at diagnosis and whether the outcome of antiepileptic drug treatment can be predicted using these measures.Methods and analysis107 patients with newly diagnosed focal epilepsy from two National Health Service Trusts and 48 healthy controls (aged 16-65 years) will be recruited over a period of 30 months. Baseline assessments will include neuropsychological evaluation, structural and functional Magnetic Resonance Imaging (MRI), Electroencephalography (EEG), and a blood and saliva sample. Patients will be followed up every 6 months for a 24-month period to assess treatment outcomes. Connectivity- and network-based analyses of EEG and MRI data will be carried out and examined in relation to neuropsychological evaluation and patient treatment outcomes. Patient outcomes will also be investigated with respect to analysis of molecular isoforms of high mobility group box-1 from blood and saliva samples.Ethics and disseminationThis study was approved by the North West, Liverpool East Research Ethics Committee (19/NW/0384) through the Integrated Research Application System (Project ID 260623). Health Research Authority (HRA) approval was provided on 22 August 2019. The project is sponsored by the UoL (UoL001449) and funded by a UK Medical Research Council (MRC) research grant (MR/S00355X/1). Findings will be presented at national and international meetings and conferences and published in peer-reviewed journals.Trial registration numberIRAS Project ID 260623.

Project description:ImportanceTolerability is a key determinant of the effectiveness of epilepsy treatment. It is important to evaluate whether the overall tolerability has improved.ObjectiveTo identify factors associated with poor tolerability of antiseizure medications (ASMs) and examine temporal changes in tolerability.Design, setting, and participantsThis was a longitudinal cohort study at a specialist clinic in Glasgow, Scotland. Patients with newly diagnosed and treated epilepsy between July 1982 and October 2012 were included from 2282 eligible individuals. They were followed up until April 2016 or death. Data analysis was completed in August 2019.ExposuresAntiseizure medications.Main outcomes and measuresUnivariable and multivariable survival analyses were performed to examine associations between potential risk factors and development of intolerable adverse effects (AEs). Intolerable AE rates of the ASMs as the initial monotherapy were compared between 3 epochs (July 1982-June 1992, July 1992-June 2002, and July 2002-April 2016).ResultsOf 1795 patients, 969 (54.0%) were male, and the median (interquartile range) age was 33 (21-50) years. A total of 3241 ASMs were prescribed during the period, of which 504 (15.6%) were discontinued within 6 months owing to intolerable AEs. Children younger than 18 years had lower intolerable AE rates than adults (vs aged 18-64 years: adjusted hazard ratio [aHR],?1.58; 95% CI, 1.07-2.32; vs aged ?65 years: aHR,?1.90; 95% CI, 1.19-3.02) while female individuals (aHR,?1.60; 95% CI, 1.30-1.96) and those who had more than 5 pretreatment seizures (aHR,?1.24; 95% CI, 1.03-1.49) were associated with having higher risk. For each ASM trial, the risk of intolerable AEs increased with the number of previous drug withdrawals due to AEs (aHR,?1.18; 95% CI, 1.09-1.28) and the number of concomitant ASMs (aHR,?1.31; 95% CI, 1.04-1.64). The proportion of second-generation ASMs prescribed as the initial monotherapy increased from 22.3% (33 of 148) in the first epoch to 68.7% (645 of 939) in the last (P?<?.001). Although differences in intolerable AE rates and types of AEs were found between the ASMs, there was no difference in the overall intolerable AEs rates to the initial monotherapy across the 3 epochs (first: 10.1% [15 of 148]; second: 13.8% [98 of 708]; third: 14.0% [131 of 939]; P?=?.41).Conclusions and relevanceIn this cohort study, the increased use of the second-generation ASMs had not improved overall treatment tolerability. Greater effort to improve tolerability in ASM development is needed.

Project description:BackgroundParkinson's disease is associated with an increased incidence of cognitive impairment and dementia. Predicting who is at risk of cognitive decline early in the disease course has implications for clinical prognosis and for stratification of participants in clinical trials. We assessed the use of clinical information and biomarkers as predictive factors for cognitive decline in patients with newly diagnosed Parkinson's disease.MethodsThe Parkinson's Progression Markers Initiative (PPMI) study is a cohort study in patients with newly diagnosed Parkinson's disease. We evaluated cognitive performance (Montreal Cognitive Assessment [MoCA] scores), demographic and clinical data, APOE status, and biomarkers (CSF and dopamine transporter [DAT] imaging results). Using change in MoCA scores over 2 years, MoCA scores at 2 years' follow-up, and a diagnosis of cognitive impairment (combined mild cognitive impairment or dementia) at 2 years as outcome measures, we assessed the predictive values of baseline clinical variables and separate or combined additions of APOE status, DAT imaging, and CSF biomarkers. We did univariate and multivariate linear analyses with MoCA change scores between baseline and 2 years, and with MoCA scores at 2 years as dependent variables, using backwards linear regression analysis. Additionally, we constructed a prediction model for diagnosis of cognitive impairment using logistic regression analysis.Findings390 patients with Parkinson's disease recruited between July 1, 2010, and May 31, 2013, and for whom data on MoCA scores at baseline and 2 years were available. In multivariate analyses, baseline age, University of Pennsylvania Smell Inventory Test (UPSIT) scores, CSF amyloid - (Aβ42) to t-tau ratio, and APOE status were associated with change in MoCA scores over time. Baseline age, MoCA and UPSIT scores, and CSF Aβ42 to t-tau ratio were associated with MoCA score at 2 years (using a backwards p-removal threshold of 0·1). Accuracy of prediction of cognitive impairment using age alone (area under the curve 0·68, 95% CI 0·60-0·76) significantly improved by addition of clinical scores (UPSIT, Rapid Eye Movement Sleep Behaviour Disorder Screening Questionnaire [RBDSQ], Geriatric Depression Scale, and Movement Disorder Society Unified Parkinson's Disease Rating Scale motor scores; 0·76, 0·68-0·83), CSF variables (0·74, 0·68-0·81), or DAT imaging results (0·76, 0·68-0·83). In combination, the five variables showing the most significant associations with cognitive impairment (age, UPSIT, RBDSQ, CSF Aβ42, and caudate uptake on DAT imaging) allowed prediction of cognitive impairment at 2 years (0·80, 0·74-0·87; p=0·0003 compared to age alone).InterpretationIn newly diagnosed Parkinson's disease, the occurrence of cognitive impairment at 2 year follow-up can be predicted with good accuracy using a model combining information on age, non-motor assessments, DAT imaging, and CSF biomarkers.FundingNone.

Dataset Information

NRSF and BDNF polymorphisms as biomarkers of cognitive dysfunction in adults with newly diagnosed epilepsy.

Publications

NRSF and BDNF polymorphisms as biomarkers of cognitive dysfunction in adults with newly diagnosed epilepsy.

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