Medicine (RMH) - Research Publications

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    Industry Viable Electrochemical DNA Detection Sensor Architecture via a Stem-Loop Methylene Blue Redox Reporter and Rapid In Situ Probe Immobilization Method for Pharmacogenetic Biomarker Testing Application
    Jayawardena, A ; Tan, SM ; Richardson, MB ; Chan, J ; Thissen, H ; Voelcker, NH ; Kwan, P (ELECTROCHEMICAL SOC INC, 2022-01-01)
    Identification of biomarkers in clinical applications for diagnostics at the point-of-care (POC) setting requires the development of industry viable biosensing platform. Herein, we report such development of biosensor architecture for the detection of pharmacogenetic biomarker HLA-B*15:02 gene. The biosensor architecture comprises of an oligonucleotide stem-loop probe modified with a methylene blue redox (MB) reporter, immobilized via a rapid “printing” method on the commercially available disposable screen-printed electrodes (SPE). The square wave voltammetric measurements on the DNA sensor showed a clear peak difference of ∼80 nA with a significant difference in peak height values of the faradaic current generated for the MB redox moiety between the positive control (biotin-modified 19 based oligonucleotides with the sequence mimicking the specific region of the HLA-B*15:02 allele and complementary to the probe sequence) and negative control samples (biotin-modified 19 based oligonucleotides with the sequence unrelated to the probe sequence and the HLA-B*15:02 allele). These initial proof of concept results provide support for the possibility of using this signal-off biosensor architecture in the intended pharmacogenetic biomarker testing.
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    Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy
    Park, B-Y ; Lariviere, S ; Rodriguez-Cruces, R ; Royer, J ; Tavakol, S ; Wang, Y ; Caciagli, L ; Caligiuri, ME ; Gambardella, A ; Concha, L ; Keller, SS ; Cendes, F ; Alvim, MKM ; Yasuda, C ; Bonilha, L ; Gleichgerrcht, E ; Focke, NK ; Kreilkamp, BAK ; Domin, M ; von Podewils, F ; Langner, S ; Rummel, C ; Rebsamen, M ; Wiest, R ; Martin, P ; Kotikalapudi, R ; Bender, B ; O'Brien, TJ ; Law, M ; Sinclair, B ; Vivash, L ; Kwan, P ; Desmond, PM ; Malpas, CB ; Lui, E ; Alhusaini, S ; Doherty, CP ; Cavalleri, GL ; Delanty, N ; Kalviainen, R ; Jackson, GD ; Kowalczyk, M ; Mascalchi, M ; Semmelroch, M ; Thomas, RH ; Soltanian-Zadeh, H ; Davoodi-Bojd, E ; Zhang, J ; Lenge, M ; Guerrini, R ; Bartolini, E ; Hamandi, K ; Foley, S ; Weber, B ; Depondt, C ; Absil, J ; Carr, SJA ; Abela, E ; Richardson, MP ; Devinsky, O ; Severino, M ; Striano, P ; Parodi, C ; Tortora, D ; Hatton, SN ; Vos, SB ; Duncan, JS ; Galovic, M ; Whelan, CD ; Bargallo, N ; Pariente, J ; Conde-Blanco, E ; Vaudano, AE ; Tondelli, M ; Meletti, S ; Kong, X-Z ; Francks, C ; Fisher, SE ; Caldairou, B ; Ryten, M ; Labate, A ; Sisodiya, SM ; Thompson, PM ; McDonald, CR ; Bernasconi, A ; Bernasconi, N ; Bernhardt, BC (OXFORD UNIV PRESS, 2022-03-25)
    Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.
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    Long-term cannabidiol treatment for seizures in patients with tuberous sclerosis complex: An open-label extension trial
    Thiele, EA ; Bebin, EM ; Filloux, F ; Kwan, P ; Loftus, R ; Sahebkar, F ; Sparagana, S ; Wheless, J (WILEY, 2021-12-27)
    OBJECTIVE: To evaluate the long-term safety and efficacy of add-on cannabidiol (CBD) in patients with seizures associated with tuberous sclerosis complex (TSC) in the open-label extension (OLE) of the randomized, placebo-controlled phase 3 trial GWPCARE6 (NCT02544763). Results of an interim (February 2019 data cut) analysis are reported. METHODS: Patients who completed the randomized trial enrolled to receive CBD (Epidiolex® in the United States; Epidyolex® in the EU; 100 mg/mL oral solution). The initial target dose was 25 mg/kg/day, which, based on response and tolerability, could be decreased or increased up to 50 mg/kg/day. The primary end point was safety. Key secondary end points included percentage reduction in TSC-associated (countable focal and generalized) seizures, responder rates, and Subject/Caregiver Global Impression of Change (S/CGIC). RESULTS: Of 201 patients who completed the randomized phase, 199 (99%) entered the OLE. Mean age was 13 years (range, 1-57). At the time of analysis, 5% of patients had completed treatment, 20% had withdrawn, and 75% were ongoing. One-year retention rate was 79%. Median treatment time was 267 days (range, 18-910) at a 27 mg/kg/day mean modal dose. Most patients (92%) had an adverse event (AE). Most common AEs were diarrhea (42%), seizure (22%), and decreased appetite (20%). AEs led to permanent discontinuation in 6% of patients. There was one death that was deemed treatment unrelated by the investigator. Elevated liver transaminases occurred in 17 patients (9%) patients; 12 were taking valproate. Median percentage reductions in seizure frequency (12-week windows across 48 weeks) were 54%-68%. Seizure responder rates (≥50%, ≥75%, 100% reduction) were 53%-61%, 29%-45%, and 6%-11% across 12-week windows for 48 weeks. Improvement on the S/CGIC scale was reported by 87% of patients/caregivers at 26 weeks. SIGNIFICANCE: In patients with TSC, long-term add-on CBD treatment was well tolerated and sustainably reduced seizures through 48 weeks, with most patients/caregivers reporting global improvement.
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    Machine learning approaches for imaging-based prognostication of the outcome of surgery for mesial temporal lobe epilepsy
    Sinclair, B ; Cahill, V ; Seah, J ; Kitchen, A ; Vivash, LE ; Chen, Z ; Malpas, CB ; O'Shea, MF ; Desmond, PM ; Hicks, RJ ; Morokoff, AP ; King, JA ; Fabinyi, GC ; Kaye, AH ; Kwan, P ; Berkovic, SF ; Law, M ; O'Brien, TJ (WILEY, 2022-03-25)
    OBJECTIVES: Around 30% of patients undergoing surgical resection for drug-resistant mesial temporal lobe epilepsy (MTLE) do not obtain seizure freedom. Success of anterior temporal lobe resection (ATLR) critically depends on the careful selection of surgical candidates, aiming at optimizing seizure freedom while minimizing postoperative morbidity. Structural MRI and FDG-PET neuroimaging are routinely used in presurgical assessment and guide the decision to proceed to surgery. In this study, we evaluate the potential of machine learning techniques applied to standard presurgical MRI and PET imaging features to provide enhanced prognostic value relative to current practice. METHODS: Eighty two patients with drug resistant MTLE were scanned with FDG-PET pre-surgery and T1-weighted MRI pre- and postsurgery. From these images the following features of interest were derived: volume of temporal lobe (TL) hypometabolism, % of extratemporal hypometabolism, presence of contralateral TL hypometabolism, presence of hippocampal sclerosis, laterality of seizure onset volume of tissue resected and % of temporal lobe hypometabolism resected. These measures were used as predictor variables in logistic regression, support vector machines, random forests and artificial neural networks. RESULTS: In the study cohort, 24 of 82 (28.3%) who underwent an ATLR for drug-resistant MTLE did not achieve Engel Class I (i.e., free of disabling seizures) outcome at a minimum of 2 years of postoperative follow-up. We found that machine learning approaches were able to predict up to 73% of the 24 ATLR surgical patients who did not achieve a Class I outcome, at the expense of incorrect prediction for up to 31% of patients who did achieve a Class I outcome. Overall accuracies ranged from 70% to 80%, with an area under the receiver operating characteristic curve (AUC) of .75-.81. We additionally found that information regarding overall extent of both total and significantly hypometabolic tissue resected was crucial to predictive performance, with AUC dropping to .59-.62 using presurgical information alone. Incorporating the laterality of seizure onset and the choice of machine learning algorithm did not significantly change predictive performance. SIGNIFICANCE: Collectively, these results indicate that "acceptable" to "good" patient-specific prognostication for drug-resistant MTLE surgery is feasible with machine learning approaches utilizing commonly collected imaging modalities, but that information on the surgical resection region is critical for optimal prognostication.
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    Network Preservation Analysis Reveals Dysregulated Synaptic Modules and Regulatory Hubs Shared Between Alzheimer's Disease and Temporal Lobe Epilepsy.
    Harutyunyan, A ; Jones, NC ; Kwan, P ; Anderson, A (Frontiers Media SA, 2022)
    Background: There is increased prevalence of epilepsy in patients with Alzheimer's disease (AD). Although shared pathological and clinical features have been identified, the underlying pathophysiology and cause-effect relationships are poorly understood. We aimed to identify commonly dysregulated groups of genes between these two disorders. Methods: Using publicly available transcriptomic data from hippocampal tissue of patients with temporal lobe epilepsy (TLE), late onset AD and non-AD controls, we constructed gene coexpression networks representing all three states. We then employed network preservation statistics to compare the density and connectivity-based preservation of functional gene modules between TLE, AD and controls and used the difference in significance scores as a surrogate quantifier of module preservation. Results: The majority (>90%) of functional gene modules were highly preserved between all coexpression networks, however several modules identified in the TLE network showed various degrees of preservation in the AD network compared to that of control. Of note, two synaptic signalling-associated modules and two metabolic modules showed substantial gain of preservation, while myelination and immune system-associated modules showed significant loss of preservation. The genes SCN3B and EPHA4 were identified as central regulatory hubs of the highly preserved synaptic signalling-associated module. GABRB3 and SCN2A were identified as central regulatory hubs of a smaller neurogenesis-associated module, which was enriched for multiple epileptic activity and seizure-related human phenotype ontologies. Conclusion: We conclude that these hubs and their downstream signalling pathways are common modulators of synaptic activity in the setting of AD and TLE, and may play a critical role in epileptogenesis in AD.
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    Interictal EEG and ECG for SUDEP Risk Assessment: A Retrospective Multicenter Cohort Study
    Chen, ZS ; Hsieh, A ; Sun, G ; Bergey, GK ; Berkovic, SF ; Perucca, P ; D'Souza, W ; Elder, CJ ; Farooque, P ; Johnson, EL ; Barnard, S ; Nightscales, R ; Kwan, P ; Moseley, B ; O'Brien, TJ ; Sivathamboo, S ; Laze, J ; Friedman, D ; Devinsky, O (FRONTIERS MEDIA SA, 2022-03-18)
    Objective: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls. Methods: This multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve. Results: The logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73-0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction. Conclusions: Our results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP risk may help clinicians to identify high-risk patients and initiate preventive strategies.
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    Design and Optimisation of Elliptical-Shaped Planar Hall Sensor for Biomedical Applications
    Uddin, SM ; Sayad, A ; Chan, J ; Skafidas, E ; Kwan, P (MDPI, 2022-02-01)
    The magnetic beads detection-based immunoassay, also called magneto-immunoassay, has potential applications in point-of-care testing (POCT) due to its unique advantage of minimal background interference from the biological sample and associated reagents. While magnetic field detection technologies are well established for numerous applications in the military, as well as in geology, archaeology, mining, spacecraft, and mobile phones, adaptation into magneto-immunoassay is yet to be explored. The magnetic field biosensors under development tend to be multilayered and require an expensive fabrication process. A low-cost and affordable biosensing platform is required for an effective point-of-care diagnosis in a resource-limited environment. Therefore, we evaluated a single-layered magnetic biosensor in this study to overcome this limitation. The shape-induced magnetic anisotropy-based planar hall effect sensor was recently developed to detect a low-level magnetic field, but was not explored for medical application. In this study, the elliptical-shaped planar hall effect (EPHE) sensor was designed, fabricated, characterized, and optimized for the magneto-immunoassay, specifically. Nine sensor variants were designed and fabricated. A customized measurement setup incorporating a lock-in amplifier was used to quantify 4.5 µm magnetic beads in a droplet. The result indicated that the single-domain behaviour of the magnetic film and larger sensing area with a thinner magnetic film had the highest sensitivity. The developed sensor was tested with a range of magnetic bead concentrations, demonstrating a limit of detection of 200 beads/μL. The sensor performance encourages employing magneto-immunoassay towards developing a low-cost POCT device in the future.
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    Vagus nerve stimulation therapy in people with drug-resistant epilepsy (CORE-VNS): rationale and design of a real-world post-market comprehensive outcomes registry
    Sen, A ; Verner, R ; Valeriano, JP ; Lee, R ; Zafar, M ; Thomas, R ; Kotulska, K ; Jespers, E ; Dibue, M ; Kwan, P (BMJ PUBLISHING GROUP, 2021-12-01)
    INTRODUCTION: The Vagus Nerve Stimulation Therapy System (VNS Therapy) is an adjunctive neuromodulatory therapy that can be efficacious in reducing the frequency and severity of seizures in people with drug-resistant epilepsy (DRE). CORE-VNS aims to examine the long-term safety and clinical outcomes of VNS in people with DRE. METHODS AND ANALYSIS: The CORE-VNS study is an international, multicentre, prospective, observational, all-comers, post-market registry. People with DRE receiving VNS Therapy for the first time as well as people being reimplanted with VNS Therapy are eligible. Participants have a baseline visit (prior to device implant). They will be followed for a minimum of 36 months and a maximum of 60 months after implant. Analysis endpoints include seizure frequency (average number of events per month), seizure severity (individual-rated categorical outcome including very mild, mild, moderate, severe or very severe) as well as non-seizure outcomes such as adverse events, use of antiseizure medications, use of other non-pharmacological therapies, quality of life, validated measures of quality of sleep (Pittsburgh Sleep Quality Index or Children's Sleep Habit Questionnaire) and healthcare resource utilisation. While the CORE-VNS registry was not expressly designed to test hypotheses, subgroup analyses and exploratory analysis that require hypothesis testing will be conducted across propensity score matched treatment groups, where possible based on sampling. ETHICS AND DISSEMINATION: The CORE-VNS registry has already enrolled 823 participants from 61 centres across 15 countries. Once complete, CORE-VNS will represent one of the largest real-world clinical data sets to allow a more comprehensive understanding of the management of DRE with adjunctive VNS. Manuscripts derived from this database will shed important new light on the characteristics of people receiving VNS Therapy; the practical use of VNS across different countries, and factors influencing long-term response. TRAIL REGISTRATION NUMBER: NCT03529045.
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    Asymmetric distribution of enlarged perivascular spaces in centrum semiovale may be associated with epilepsy after acute ischemic stroke
    Yu, N ; Sinclair, B ; Posada, LMG ; Chen, Z ; Di, Q ; Lin, X ; Kolbe, S ; Hlauschek, G ; Kwan, P ; Law, M (WILEY, 2022-01-03)
    OBJECTIVE: To investigate the factors influencing enlarged perivascular space (EPVS) characteristics at the onset of acute ischemic stroke (AIS), and whether the PVS characteristics can predict later post-stroke epilepsy (PSE). METHODS: A total of 312 patients with AIS were identified, of whom 58/312 (18.6%) developed PSE. Twenty healthy participants were included as the control group. The number of PVS in the basal ganglia (BG), centrum semiovale (CS), and midbrain (MB) was manually calculated on T2 -weighted MRI. The scores and asymmetry index (AI) of EPVS in each region were compared among the enrolled participants. Other potential risk factors for PSE were also analyzed, including NIHSS at admission and stroke etiologies. RESULTS: The EPVS scores were significantly higher in the bilateral BG and CS of AIS patients compared to those of the control group (both p < 0.01). No statistical differences in EPVS scores in BG, CS, and MB were obtained between the PSE group and the nonepilepsy AIS group (all p > 0.01). However, markedly different AI scores in CS were found between the PSE group and the nonepilepsy AIS group (p = 0.004). Multivariable analysis showed that high asymmetry index of EPVS (AI≥0.2) in CS was an independent predictor for PSE (OR = 3.7, 95% confidence interval 1.5-9.1, p = 0.004). CONCLUSIONS: Asymmetric distribution of EPVS in CS may be an independent risk factor and a novel imaging biomarker for the development of PSE. Further studies to understand the mechanisms of this association and confirmation with larger patient populations are warranted.
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    Prospective multisite cohort study of patient-reported outcomes in adults with new-onset seizures
    Foster, E ; Chen, Z ; Vaughan, DN ; Tailby, C ; Carney, PW ; D'Souza, W ; Yong, HMA ; Nicolo, J-P ; Pellinen, J ; de Albornoz, SC ; Liew, D ; O'Brien, TJ ; Kwan, P ; Ademi, Z (WILEY, 2021-12-20)
    OBJECTIVE: New-onset seizures affect up to 10% of people over their lifetime, however, their health economic impact has not been well-studied. This prospective multicenter study will collect patient-reported outcome measures (PROMs) from adults with new-onset seizures seen in six Seizure Clinics across Melbourne, Australia and The University of Colorado, USA. METHODS: Approximately 450 eligible patients will be enrolled in the study at or following their initial attendance to Seizure Clinics at the study hospitals. Inclusion criteria for the study group are those with new-onset acute symptomatic seizures, new-onset unprovoked seizures, and new-onset epilepsy. Inclusion criteria for the three comparator groups are those with noncardiac syncope, those with psychogenic nonepileptic seizures, as well as published PROMs data from the Australian general population. Exclusion criteria are those aged less than 18 years, those with a preexisting epilepsy diagnosis, and those with intellectual disabilities or other impairments which would preclude them from comprehending and completing the questionnaires. Patients will complete eight online questionnaires regarding the effect that their seizures (or seizure mimics) have had on various aspects of their life. These questionnaires will be readministered at 6 and 12 months. Patients with new-diagnosis epilepsy will also be asked to share the reasons why they have accepted or declined antiseizure medications. ANALYSIS: Primary outcome measures will be quality of life, work productivity, informal care needs, and mood, at baseline compared to 6 and 12 months later for those with new-onset seizures and comparing these outcomes to those in the three comparator groups. Secondary outcomes include mapping of QoLIE-31 to the EQ-5D-5L in epilepsy, modelling indirect costs of new-onset seizures, and exploring why patients may or may not wish to take antiseizure medications. SIGNIFICANCE: These data will form an evidence-base for future studies that examine the effectiveness of various healthcare interventions for new-onset seizure patients. ETHICS AND DISSEMINATION: This study is approved by the Alfred Health Human Research Ethics Committee (SERP: 52 538, Alfred HREC: 307/19), the Austin Health Human Research Ethics Committee (HREC/59148/Austin-2019), and the Colorado Multiple Institutional Review Board (COMIRB) (COMIRB #20-3028). ANZCTR TRIAL REGISTRATION NUMBER: ACTRN12621000908831.