Publications by authors named "Charles Malpas"

67 Publications

Odor Identification Testing Can Assist in the Clinical Distinction Between Psychiatric Disorders and Neurological/Neurodegenerative Disorders.

Alzheimer Dis Assoc Disord 2021 Mar 23. Epub 2021 Mar 23.

1st Department of Neurology, Eginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece Department of Neuropsychiatry Department of Neurology, Royal Melbourne Hospital Melbourne Neuropsychiatry Centre, University of Melbourne and North Western Mental Health, Department of Medicine, Royal Melbourne Hospital, The University of Melbourne Florey Institute of Neuroscience and Mental Health Department of Psychiatry, University of Melbourne, Parkville, Vic., Australia.

Background/objectives: The aim was to identify whether performance on olfactory identification can distinguish neurological/neurodegenerative disorders (NNDs) from primary psychiatric disorders (PPDs).

Methods: This is a cross-sectional retrospective study of inpatients assessed in Neuropsychiatry, Royal Melbourne Hospital. Data extracted from the admission records included: demographics, tobacco use, medical comorbidities, cognitive function using the Neuropsychiatry Unit Cognitive Assessment Tool (NUCOG), and odor identification using the Sniffin' Sticks Screening 12 test. The final diagnosis for patients was informed by established diagnostic criteria.

Results: A total 121 patients were included. Eighty-eight patients (73%) were diagnosed with neurological or neurodegenerative disease, including Alzheimers dementia, frontotemporal dementia, Lewy body parkinsonian-related dementias (Parkinson disease, multiple system atrophy, dementia with Lewy bodies) and other neurological causes of dementia; 33 patients (27%) were diagnosed with PPDs (including mood and psychotic disorders). Patients who scored ≤8 on the Sniffin' Sticks Screening 12 test were more likely to have NND than PPD, even after adjustment for age, sex and tobacco use (P=0.009, adjusted odds ratios=3.85, 95% confidence interval=1.40-10.62). Receiver operating characteristic curve analyses demonstrated that a score of ≤8 differentiated NND from PPD with sensitivity of 57% and specificity of 73% (receiver operating characteristic area under the curve of 0.67, P=0.004).

Conclusions: Patients with neuropsychiatric difficulties who score 8 or less on Sniffin' Sticks are more likely to have a neurodegenerative illness. A cut-off score of 8 is potentially a "red flag" for clinicians faced with the diagnostic question of PPD versus NND.
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http://dx.doi.org/10.1097/WAD.0000000000000441DOI Listing
March 2021

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets.

Authors:
Merel C Postema Martine Hoogman Sara Ambrosino Philip Asherson Tobias Banaschewski Cibele E Bandeira Alexandr Baranov Claiton H D Bau Sarah Baumeister Ramona Baur-Streubel Mark A Bellgrove Joseph Biederman Janita Bralten Daniel Brandeis Silvia Brem Jan K Buitelaar Geraldo F Busatto Francisco X Castellanos Mara Cercignani Tiffany M Chaim-Avancini Kaylita C Chantiluke Anastasia Christakou David Coghill Annette Conzelmann Ana I Cubillo Renata B Cupertino Patrick de Zeeuw Alysa E Doyle Sarah Durston Eric A Earl Jeffery N Epstein Thomas Ethofer Damien A Fair Andreas J Fallgatter Stephen V Faraone Thomas Frodl Matt C Gabel Tinatin Gogberashvili Eugenio H Grevet Jan Haavik Neil A Harrison Catharina A Hartman Dirk J Heslenfeld Pieter J Hoekstra Sarah Hohmann Marie F Høvik Terry L Jernigan Bernd Kardatzki Georgii Karkashadze Clare Kelly Gregor Kohls Kerstin Konrad Jonna Kuntsi Luisa Lazaro Sara Lera-Miguel Klaus-Peter Lesch Mario R Louza Astri J Lundervold Charles B Malpas Paulo Mattos Hazel McCarthy Leyla Namazova-Baranova Rosa Nicolau Joel T Nigg Stephanie E Novotny Eileen Oberwelland Weiss Ruth L O'Gorman Tuura Jaap Oosterlaan Bob Oranje Yannis Paloyelis Paul Pauli Felipe A Picon Kerstin J Plessen J Antoni Ramos-Quiroga Andreas Reif Liesbeth Reneman Pedro G P Rosa Katya Rubia Anouk Schrantee Lizanne J S Schweren Jochen Seitz Philip Shaw Tim J Silk Norbert Skokauskas Juan C Soliva Vila Michael C Stevens Gustavo Sudre Leanne Tamm Fernanda Tovar-Moll Theo G M van Erp Alasdair Vance Oscar Vilarroya Yolanda Vives-Gilabert Georg G von Polier Susanne Walitza Yuliya N Yoncheva Marcus V Zanetti Georg C Ziegler David C Glahn Neda Jahanshad Sarah E Medland Paul M Thompson Simon E Fisher Barbara Franke Clyde Francks

J Child Psychol Psychiatry 2021 Mar 22. Epub 2021 Mar 22.

Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.

Objective: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

Methods: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.

Results: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.

Conclusion: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.
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http://dx.doi.org/10.1111/jcpp.13396DOI Listing
March 2021

Clinical predictors of discordance between screening tests and psychiatric assessment for depressive and anxiety disorders among patients being evaluated for seizure disorders.

Epilepsia 2021 Mar 18. Epub 2021 Mar 18.

Department of Neurology, Alfred Health, Prahran, Victoria, Australia.

Objective: This study was undertaken to identify factors that predict discordance between the screening instruments Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) and Generalized Anxiety Disorder scale (GAD-7), and diagnoses made by qualified psychiatrists among patients with seizure disorders. Importantly, this is not a validation study; rather, it investigates clinicodemographic predictors of discordance between screening tests and psychiatric assessment.

Methods: Adult patients admitted for inpatient video-electroencephalographic monitoring completed eight psychometric instruments, including the NDDI-E and GAD-7, and psychiatric assessment. Patients were grouped according to agreement between the screening instrument and psychiatrists' diagnoses. Screening was "discordant" if the outcome differed from the psychiatrist's diagnosis, including both false positive and false negative results. Bayesian statistical analyses were used to identify factors associated with discordance.

Results: A total of 411 patients met inclusion criteria; mean age was 39.6 years, and 55.5% (n = 228) were female. Depression screening was discordant in 33% of cases (n = 136/411), driven by false positives (n = 76/136, 56%) rather than false negatives (n = 60/136, 44%). Likewise, anxiety screening was discordant in one third of cases (n = 121/411, 29%) due to false positives (n = 60/121, 50%) and false negatives (n = 61/121, 50%). Seven clinical factors were predictive of discordant screening for both depression and anxiety: greater dissociative symptoms, greater patient-reported adverse events, subjective cognitive impairment, negative affect, detachment, disinhibition, and psychoticism. When the analyses were restricted to only patients with psychogenic nonepileptic seizures (PNES) or epilepsy, the rate of discordant depression screening was higher in the PNES group (n = 29, 47%) compared to the epilepsy group (n = 70, 30%, Bayes factor for the alternative hypothesis = 4.65).

Significance: Patients with seizure disorders who self-report a variety of psychiatric and other symptoms should be evaluated more thoroughly for depression and anxiety, regardless of screening test results, especially if they have PNES and not epilepsy. Clinical assessment by a qualified psychiatrist remains essential in diagnosing depressive and anxiety disorders among such patients.
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http://dx.doi.org/10.1111/epi.16871DOI Listing
March 2021

Evolution of Brain Volume Loss Rates in Early Stages of Multiple Sclerosis.

Neurol Neuroimmunol Neuroinflamm 2021 05 16;8(3). Epub 2021 Mar 16.

From the CORe (T.U., C.M., T.K.), Department of Medicine, the University of Melbourne, VIC, Australia; Department of Neurology and Center of Clinical Neuroscience (T.U., E.K.H., D.H.), Charles University in Prague, 1st Faculty of Medicine and General University Hospital; Department of Radiology (J.K., M.V.), Charles University in Prague, First Faculty of Medicine and General University Hospital in Prague, Czech Republic; Buffalo Neuroimaging Analysis Center (N.B., M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York; IRCCS (N.B.), Fondazione Don Carlo Gnocchi, Milan, Italy; Center for Biomedical Imaging at Clinical Translational Science Institute (R.Z.), University at Buffalo, State University of New York; and Melbourne MS Centre (T.K.), Department of Neurology, the Royal Melbourne Hospital, VIC, Australia.

Objective: To describe the dynamics of brain volume loss (BVL) at different stages of relapsing-remitting multiple sclerosis (RRMS), to describe the association between BVL and clinical measures, and to investigate an effect of treatment escalation on the rate of BVL.

Methods: Together, 1903 patients predominantly with RRMS from the Avonex-Steroids-Azathioprine cohort (N = 166), the study of early IFN-β1a treatment cohort (N = 180), and the quantitative MRI cohort (N = 1,557) with ≥2 MRI scans and ≥1-year of follow-up were included. Brain MRI scans (N = 7,203) were performed using a single 1.5-T machine. Relationships between age or disease duration and global and tissue-specific BVL rates were analyzed using mixed models.

Results: Age was not associated with the rate of BVL (β = -0.003; Cohen f2 = 0.0005; adjusted = 0.39). Although disease duration was associated with the rate of BVL, its effect on the BVL rate was minimal (β = -0.012; Cohen f2 = 0.004; adjusted = 4 × 10). Analysis of association between tissue-specific brain volume changes and age (β = -0.019 to -0.011; adjusted = 0.028-1.00) or disease duration (β = -0.028 to -0.008; adjusted = 0.16-0.96) confirmed these results. Although increase in the relapse rate (β = 0.10; adjusted = 9 × 10), Expanded Disability Status Scale (EDSS; β = 0.17; adjusted = 8 × 10), and EDSS change (β = 0.15; adjusted = 2 × 10) were associated with accelerated rate of BVL, their effect on the rate of BVL was minimal (all Cohen f2 ≤ 0.007). In 94 patients who escalated therapy, the rate of BVL decreased following treatment escalation by 0.29% (β = -0.29; Cohen f2 = 0.133; = 5.5 × 10).

Conclusions: The rate of BVL is relatively stable throughout the course of RRMS. The accelerated BVL is weakly associated with concurrent higher disease activity, and timely escalation to high-efficacy immunotherapy helps decrease the rate of BVL.
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http://dx.doi.org/10.1212/NXI.0000000000000979DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984675PMC
May 2021

Psychiatric symptoms are the strongest predictors of quality of life in patients with drug-resistant epilepsy or psychogenic nonepileptic seizures.

Epilepsy Behav 2021 04 6;117:107861. Epub 2021 Mar 6.

The Departments of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne, Victoria, Australia; Department of Neuroscience, Central Clinical School, The Alfred Hospital, Monash University, Victoria, Australia. Electronic address:

Objective: This cross-sectional study aimed to determine the effect of psychiatric comorbidity and neurocognitive deficits on the quality of life in a cohort of patients admitted for Video-EEG Monitoring (VEM) for investigation into a presumed seizure disorder.

Methods: Patients were recruited from an inpatient VEM unit between January 2009 and December 2016. All patients had formal neuropsychiatric assessment. All patients completed questionnaires assessing psychiatric symptomatology (SCL-90-R), Anxiety and Depression (HADS), quality of life (QOLIE-89), and cognition (NUCOG).

Results: A total of 451 patients were enrolled. Upon discharge, 204 patients were diagnosed to have epilepsy, 118 psychogenic nonepileptic seizures (PNES), and 29 both epilepsy and PNES, while the diagnosis was uncertain diagnosis in 100. Diagnosis (p = .002), HADS Depression score (p < .001), SCL-90-R positive symptoms total (p < .001), and NUCOG total score (p < .001) were found to be significant predictors of QOLIE-89 total scores, together explaining 65.4% of variance in quality of life. Seizure frequency was not a significant predictor of quality of life (p = .082). Patients with PNES had significantly worse quality of life, and scored higher on measures of psychiatricsymptomatology, compared to patients with epilepsy alone. The prevalence of psychiatric comorbidity was significantly higher in patients with PNES (70.3%) or both PNES and epilepsy (62.1%) compared to patients with epilepsy alone (41.2%) (p < .001).

Significance: Psychiatric symptomatology, depression, and cognition were stronger determinants of quality of life than seizure frequency in this study population of patients with drug-resistant epilepsy and PNES. Patients with PNES with or without comorbid epilepsy had similar neuropsychiatric profiles.
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http://dx.doi.org/10.1016/j.yebeh.2021.107861DOI Listing
April 2021

Assessment of the DTI-ALPS Parameter Along the Perivascular Space in Older Adults at Risk of Dementia.

J Neuroimaging 2021 Feb 8. Epub 2021 Feb 8.

Department of Medicine and Radiology, University of Melbourne, Melbourne, Victoria, Australia.

Background And Purpose: Recently, there has been growing interest in the glymphatic system (the functional waste clearance pathway for the central nervous system and its role in flushing solutes (such as amyloid ß and tau), metabolic, and other cellular waste products in the brain. Herein, we investigate a recent potential biomarker for glymphatic activity (the diffusion tensor imaging along the perivascular space [DTI-ALPS] parameter) using diffusion MRI imaging in an elderly cohort comprising 10 cognitively normal, 10 mild cognitive impairment (MCI), and 16 Alzheimer's disease (AD).

Methods: All 36 participants imaged on a Siemens 3.0T Tim Trio. Single-SE diffusion weighted Echo-planar imaging scans were acquired as well as T1 magnetization prepared rapid gradient echo, T2 axial, and susceptibility weighted imaging. Three millimeter regions of interest were drawn in the projection and association fibers adjacent to the medullary veins at the level of the lateral ventricle. The DTI-ALPS parameter was calculated in these regions and correlated with cognitive status, Mini-Mental State Examination (MMSE), and ADASCog11 measures.

Results: Significant correlations were found between DTI-ALPS and MMSE and ADASCog11 in the right hemisphere adjusting for age, sex, and APoE ε4 status. Significant differences were also found in the right DTI-ALPS indices between cognitively normal and AD groups (P < .026) and MCI groups (P < .025) in a univariate general linear model corrected for age, sex, and APoE ε4. Significant differences in apparent diffusion coefficient between cognitively normal and AD groups were found in the right projection fibers (P = .028).

Conclusion: Further work is needed to determine the utility of DTI-ALPS index in larger elderly cohorts and whether it measures glymphatic activity.
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http://dx.doi.org/10.1111/jon.12837DOI Listing
February 2021

Prenatal valproate exposure and adverse neurodevelopmental outcomes: Does sex matter?

Epilepsia 2021 Mar 5;62(3):709-719. Epub 2021 Feb 5.

Departments of Medicine and Neurology, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia.

Objective: Prenatal exposure to the antiepileptic drug (AED) valproic acid (VPA) is associated with an increased risk of impaired postnatal neurodevelopment, including autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). We aimed to evaluate the influence of sex and drug dosage on the association between prenatal VPA exposure and postnatal behavioral outcomes.

Methods: The Australian Pregnancy Register of AEDs was interrogated to identify children aged 4-11 years prenatally exposed to AEDs. Parents reported on their child's behavior using the Autism Spectrum Quotient-Children's Version and the National Institute for Children's Health Quality Vanderbilt Assessment Scale for ADHD. General linear mixed-effects models were used to investigate the relationship between clinicodemographic variables and psychometric scores.

Results: A total of 121 children were studied: 54 prenatally exposed to VPA (28 males, 26 females; mean dose ± SD: 644 ± 310 mg/day) and 67 exposed to other AEDs. There was a main effect of sex showing higher ASD scores in males compared to females (p = .006). An interaction between sex and VPA exposure revealed that males had higher ASD symptoms among children exposed to AEDs other than VPA (p = .01); however, this typical sex dynamic was not evident in VPA-exposed children. There was no evidence of any dose-response relationship between VPA exposure and ASD symptoms. Males had higher ADHD scores compared to females, but there was no evidence for a link between ADHD symptoms and VPA exposure.

Significance: Prenatal VPA exposure seems to negate the usual male sex-related predominance in the incidence of ASD. These initial findings deepen the concept of VPA as a "behavioral teratogen" by indicating that its effect might be influenced by sex, with females appearing particularly sensitive to the effects of VPA. No association between VPA doses and adverse postnatal behavioral outcomes was detected, possibly related to the low VPA doses used in this study.
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http://dx.doi.org/10.1111/epi.16827DOI Listing
March 2021

The effect of improved dietary control on cognitive and psychiatric functioning in adults with phenylketonuria: the ReDAPT study.

Orphanet J Rare Dis 2021 Jan 18;16(1):35. Epub 2021 Jan 18.

Neuropsychiatry Unit, Royal Melbourne Hospital, Level 2, John Cade Building, Melbourne,, 3050, Australia.

Background: Phenylketonuria (PKU) is an autosomal recessive inherited disorder characterised by a deficiency in phenylalanine hydroxylase. Untreated, PKU is associated with a wide range of cognitive and psychiatric sequelae. Contemporary management guidelines recommend lifetime dietary control of phenylalanine (Phe) levels, however many individuals who discontinue dietary control subsequently suffer symptoms of anxiety, depression and disturbances to cognition. We undertook a prospective cohort study of patients with early-treated phenylketonuria who had ceased dietary control to test the hypothesis that resumption of dietary control of PKU is associated with improvements in measures of psychiatric morbidity and cognitive functioning.

Methods: We re-initiated dietary control for early-treated patients with PKU and monitored cognitive and psychiatric outcomes over a twelve-month period. Assessments included objective cognitive function (measured by cognitive proficiency index (CPI)), anxiety and depression scales. General linear mixed model (GLMM) analyses were performed to assess change in psychometric variables from baseline over twelve months after resumption of dietary control.

Results: A total of nine patients were recruited. Mean age was 33 years (SD = 8.75), five were female. Mean time off dietary control was 19.1 years (SD = 11.3), and mean baseline phenylalanine (Phe) levels were 1108 µmol/L (SD = 293). GLMM analysis demonstrated a positive relationship between CPI and time on diet (b = 0.56 [95% CI = 0.17, 0.95]). Age, time off diet, Phe levels and depression scores were not associated with cognitive function. There was a negative relationship between time on diet and anxiety (b = - 0.88 95% CI = [- 1.26, - 0.50]) and depression ratings (b = - 0.61, 95% CI = [- 0.95, - 0.26]).

Conclusions: This study demonstrated improvements in cognitive function, anxiety, and depression ratings associated with resumption of dietary control of PKU. Raw Phe levels were not strongly associated with psychiatric or cognitive scores in this cohort. These findings support the importance of lifelong treatment for PKU in improving the cognitive and psychiatric sequelae of the disease.
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http://dx.doi.org/10.1186/s13023-020-01668-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814424PMC
January 2021

Determinants of therapeutic lag in multiple sclerosis.

Mult Scler 2021 Jan 11:1352458520981300. Epub 2021 Jan 11.

CORe, Department of Medicine, University of Melbourne, Melbourne, VIC, Australia/Melbourne MS Centre, Department of Neurology, Royal Melbourne Hospital, Melbourne, VIC, Australia.

Background: A delayed onset of treatment effect, termed therapeutic lag, may influence the assessment of treatment response in some patient subgroups.

Objectives: The objective of this study is to explore the associations of patient and disease characteristics with therapeutic lag on relapses and disability accumulation.

Methods: Data from MSBase, a multinational multiple sclerosis (MS) registry, and OFSEP, the French MS registry, were used. Patients diagnosed with MS, minimum 1 year of exposure to MS treatment and 3 years of pre-treatment follow-up, were included in the analysis. Studied outcomes were incidence of relapses and disability accumulation. Therapeutic lag was calculated using an objective, validated method in subgroups stratified by patient and disease characteristics. Therapeutic lag under specific circumstances was then estimated in subgroups defined by combinations of clinical and demographic determinants.

Results: High baseline disability scores, annualised relapse rate (ARR) ⩾ 1 and male sex were associated with longer therapeutic lag on disability progression in sufficiently populated groups: females with expanded disability status scale (EDSS) < 6 and ARR < 1 had mean lag of 26.6 weeks (95% CI = 18.2-34.9), males with EDSS < 6 and ARR < 1 31.0 weeks (95% CI = 25.3-36.8), females with EDSS < 6 and ARR ⩾ 1 44.8 weeks (95% CI = 24.5-65.1), and females with EDSS ⩾ 6 and ARR < 1 54.3 weeks (95% CI = 47.2-61.5).

Conclusions: Pre-treatment EDSS and ARR are the most important determinants of therapeutic lag.
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http://dx.doi.org/10.1177/1352458520981300DOI Listing
January 2021

Effect of Disease-Modifying Therapy on Disability in Relapsing-Remitting Multiple Sclerosis Over 15 Years.

Neurology 2021 02 28;96(5):e783-e797. Epub 2020 Dec 28.

From CORe (T.K., I.D., S.S., C.M.), Department of Medicine, University of Melbourne; MS Centre (T.K., I.D., S.S., C.M.), Department of Neurology, Royal Melbourne Hospital, Australia; Karolinska Institute (T.S.), Stockholm, Sweden; Department of Neuroscience (T.S., V.J., A.v.d.W., O.S., H.B.), Central Clinical School, Monash University, Melbourne; Burnet Institute (T.S.), Melbourne, Australia; Department of Neurology and Center of Clinical Neuroscience (D.H., E.K.H.), General University Hospital and Charles University in Prague, Czech Republic; Department of Basic Medical Sciences, Neuroscience and Sense Organs (M. Trojano), University of Bari, Italy; Hospital Universitario Virgen Macarena (G.I.), Sevilla, Spain; Department of Neuroscience, Imaging and Clinical Sciences (A.L.), University "G. d'Annunzio," Chieti; Department of Biomedical and Neuromotor Sciences (A.L.), University of Bologna, IRCCS Istituto delle Scienze Neurologiche di Bologna, Italy; Hopital Notre Dame (A.P., M.G., P.D.), Montreal; CHUM and Universite de Montreal (A.P., M.G., P.D.); CISSS Chaudière-Appalache (P.G.), Levis, Canada; Department of Neurology (V.J., A.v.d.W., O.S., H.B.), Alfred Hospital, Melbourne, Australia; Neuro Rive-Sud (F. Grand'Maison), Quebec, Canada; Department of Neuroscience (P.S., D.F.), Azienda Ospedaliera Universitaria, Modena, Italy; Isfahan University of Medical Sciences (V.S.), Isfahan, Iran; Amiri Hospital (R. Alroughani), Kuwait City, Kuwait; Zuyderland Ziekenhuis (R.H.), Sittard, the Netherlands; Medical Faculty (M. Terzi), 19 Mayis University, Samsun; KTU Medical Faculty Farabi Hospital (C.B.), Karadeniz Technical University, Trabzon, Turkey; School of Medicine and Public Health (J.L.-S.), University Newcastle; Department of Neurology (J.L.-S.), John Hunter Hospital, Newcastle, Australia; UOC Neurologia (E.P.), Azienda Sanitaria Unica Regionale Marche-AV3, Macerata, Italy; Cliniques Universitaires Saint-Luc (V.V.P.), Brussels, Belgium; University of Parma (F. Granella); C. Mondino National Neurological Institute (R.B.), Pavia; Azienda Ospedaliera di Rilievo Nazionale San Giuseppe Moscati Avellino (D.S.), Italy; Flinders University (M. Slee), Adelaide; Westmead Hospital (S.V.), Sydney, Australia; Nemocnice Jihlava (R. Ampapa), Czech Republic; University of Queensland (P.M.), Brisbane; Royal Brisbane and Women's Hospital (P.M.), Brisbane, Australia; Hospital Germans Trias i Pujol (C.R.-T.), Badalona, Spain; CSSS Saint-Jérôme (J.P.), Canada; Hospital Universitario Donostia (J.O.), Paseo de Begiristain, San Sebastián, Spain; Hospital Italiano (E.C.), Buenos Aires, Argentina; Brain and Mind Centre (M.B.), University of Sydney, Australia; INEBA-Institute of Neuroscience Buenos Aires (M.L.S.), Argentina; Hospital de Galdakao-Usansolo (J.L.S.-M.), Galdakao, Spain; Liverpool Hospital (S. Hodgkinson), Sydney, Australia; Jahn Ferenc Teaching Hospital (C.R.), Budapest, Hungary; Craigavon Area Hospital (S. Hughes), UK; Jewish General Hospital (F.M.), Montreal, Canada; Deakin University (C.S.), Geelong; Monash Medical Centre (E.B.), Melbourne, Australia; South East Trust (O.G.), Belfast, UK; Perron Institute (A.K.), University of Western Australia, Nedlands; Institute of Immunology and Infectious Diseases (A.K.), Murdoch University; Sir Charles Gairdner Hospital (A.K.), Perth, Australia; Department of Neurology (T.C.), Faculty of Medicine, University of Debrecen, Hungary; Bombay Hospital Institute of Medical Sciences (B.S.), Mumbai, India; St Vincents Hospital (N.S.), Fitzroy, Melbourne, Australia; Veszprém Megyei Csolnoky Ferenc Kórház zrt (I.P.), Veszprem, Hungary; Royal Hobart Hospital (B.T.), Australia; Semmelweis University Budapest (M. Simo), Hungary; Central Military Emergency University Hospital (C.-A.S.), Bucharest; Titu Maiorescu University (C.-A.S.), Bucharest, Romania; BAZ County Hospital (A.S.), Miskolc, Hungary; and Box Hill Hospital (H.B.), Melbourne, Australia.

Objective: To test the hypothesis that immunotherapy prevents long-term disability in relapsing-remitting multiple sclerosis (MS), we modeled disability outcomes in 14,717 patients.

Methods: We studied patients from MSBase followed for ≥1 year, with ≥3 visits, ≥1 visit per year, and exposed to MS therapy, and a subset of patients with ≥15-year follow-up. Marginal structural models were used to compare the cumulative hazards of 12-month confirmed increase and decrease in disability, Expanded Disability Status Scale (EDSS) step 6, and the incidence of relapses between treated and untreated periods. Marginal structural models were continuously readjusted for patient age, sex, pregnancy, date, disease course, time from first symptom, prior relapse history, disability, and MRI activity.

Results: A total of 14,717 patients were studied. During the treated periods, patients were less likely to experience relapses (hazard ratio 0.60, 95% confidence interval [CI] 0.43-0.82, = 0.0016), worsening of disability (0.56, 0.38-0.82, = 0.0026), and progress to EDSS step 6 (0.33, 0.19-0.59, = 0.00019). Among 1,085 patients with ≥15-year follow-up, the treated patients were less likely to experience relapses (0.59, 0.50-0.70, = 10) and worsening of disability (0.81, 0.67-0.99, = 0.043).

Conclusion: Continued treatment with MS immunotherapies reduces disability accrual by 19%-44% (95% CI 1%-62%), the risk of need of a walking aid by 67% (95% CI 41%-81%), and the frequency of relapses by 40-41% (95% CI 18%-57%) over 15 years. This study provides evidence that disease-modifying therapies are effective in improving disability outcomes in relapsing-remitting MS over the long term.

Classification Of Evidence: This study provides Class IV evidence that, for patients with relapsing-remitting MS, long-term exposure to immunotherapy prevents neurologic disability.
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http://dx.doi.org/10.1212/WNL.0000000000011242DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884998PMC
February 2021

Adverse events related to antiepileptic drugs.

Epilepsy Behav 2021 02 22;115:107657. Epub 2020 Dec 22.

Department of Neurology, The Royal Melbourne Hospital, Parkville, Australia; Department of Neurology, Alfred Health, Melbourne, Australia; Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, Australia; Clinical Outcomes Research (CORe) Unit, Department of Medicine (RMH), The University of Melbourne, Parkville, Australia.

Objective: Adverse events (AEs) related to antiepileptic drugs (AEDs) may interfere with adequate dosing and patient adherence, leading to suboptimal seizure control, and relatedly, increased injuries, hospitalizations, and mortality. This study investigated the clinicodemographic factors associated with AEs related to AEDs as reported by the Liverpool Adverse Events Profile (LAEP), and explored the ability of LAEP to discriminate between epilepsy and psychogenic nonepileptic seizures (PNES). We hypothesized that female sex, mood disorders, AED-polytherapy, duration, and severity of epilepsy are associated with increased endorsement of AEs related to AEDs, and that endorsement of AEs related to AEDs would significantly differ between epilepsy and PNES patients.

Methods: We prospectively enrolled adult patients admitted to two inpatient video-electroencephalogram monitoring units. Clinicodemographic variables and psychometric measures of depression, anxiety, and cognitive function were recorded. Patient-reported AE endorsement was obtained using the LAEP, which was reduced to four latent domains using exploratory structural equation modeling. General linear models identified variables associated with each domain. Logistic regression determined the ability of LAEP scores to differentiate between epilepsy and PNES.

Results: 311 patients met inclusion criteria. Mean age was 38 years and 56% of patients were female. Network analysis demonstrated strong relationships between depression and anxiety with physical, sleep, psychiatric, and dermatological AE endorsement. Depression, female sex, and AED polytherapy were associated with greater AE endorsement. Epilepsy, compared to PNES, was associated with lower AE endorsement. Fewer prescribed AEDs and greater reported physical AE endorsement were associated with PNES diagnosis.

Significance: There is a strong relationship between patient-reported AEs and psychiatric symptomatology. Those with PNES paradoxically endorse greater physical AEs despite receiving fewer AEDs. Patients who endorse AEs in clinical practice should be screened for comorbid depression or anxiety and treated accordingly.
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http://dx.doi.org/10.1016/j.yebeh.2020.107657DOI Listing
February 2021

Cognitive profiles in patients with epileptic and nonepileptic seizures evaluated using a brief cognitive assessment tool.

Epilepsy Behav 2021 02 11;115:107643. Epub 2020 Dec 11.

Melbourne Brain Centre, The Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia; Department of Neurology, Royal Melbourne Hospital, Melbourne, VIC, Australia; Department of Neuroscience, Central Clinical School, Alfred Health, Monash University, Melbourne, VIC, Australia. Electronic address:

Background: There is a need for the development of brief tools to screen for cognitive impairments in epilepsy patients in order to prioritize and direct formal comprehensive cognitive testing. Yet, shorter cognitive screening tools are limited in their breadth of cognitive domains or have not been intensively studied on an epilepsy population. This study used a brief cognitive screening tool in order to compare cognitive profiles between patients with epilepsy and those with nonepileptic seizures.

Methods: Patients admitted to the Royal Melbourne Hospital video-EEG monitoring unit between 2005 and 2017 were included. Patients were categorized according to seizure etiology (epileptic, psychogenic or other nonepileptic seizures), epilepsy syndrome (focal or generalized; temporal lobe (TLE) or extra-temporal lobe epilepsy (ETLE)), seizure frequency, and anti-seizure medications (ASMs). Attention, visuoconstructional, memory, executive, and language functioning were assessed with the Neuropsychiatry Unit Cognitive Assessment Tool (NUCOG). General linear mixed models were computed to investigate cognitive profiles according to diagnostic group and other clinicodemographic variables.

Results: 800 patients were included in the analysis (61% female and 39 % male, median age 36 years). Patients with both epileptic seizures and psychogenic seizures (n = 25) had the lowest total scores on NUCOG, followed by patients with epileptic seizures (n = 411), psychogenic seizures (n = 185), and nonepileptic seizures (n = 179, p = 0.002). Specifically, patients with epileptic seizures performed worse than those with nonepileptic seizures in the executive, language, and memory domain, and had lower language domain scores than those with psychogenic seizures. Patients with bilateral TLE had poorer performance than those with unilateral TLE, particularly for memory function. Specific ASMs and polypharmacy but not seizure frequency had a negative effect on cognition (p < 0.001). NUCOG scores did not differ between focal and generalized epilepsies, or between TLE and ETLE.

Conclusion: The NUCOG differentiated cognitive profiles in patients with uncontrolled seizures due to different etiologies. Bilateral TLE and medication adversely affected cognitive performance, and overall patients with epilepsy performed worse than those with nonepileptic seizures. These results provide further evidence for sensitivity of the NUCOG for detecting cognitive impairment in patients with seizure disorders.
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http://dx.doi.org/10.1016/j.yebeh.2020.107643DOI Listing
February 2021

A study protocol for a phase II randomised, double-blind, placebo-controlled trial of sodium selenate as a disease-modifying treatment for behavioural variant frontotemporal dementia.

BMJ Open 2020 11 16;10(11):e040100. Epub 2020 Nov 16.

Department of Neuroscience, Monash University, Melbourne, Victoria, Australia.

Introduction: Behavioural variant frontotemporal dementia (bvFTD) is a neurodegenerative disorder often neuropathologically associated with the accumulation of abnormally hyperphosphorylated tau, for which there is currently no disease-modifying treatment. Previous work by our group has shown sodium selenate upregulates the activity of protein phosphatase 2 in the brain, increasing the rate of tau dephosphorylation. The objective of this study is to evaluate the efficacy and safety of sodium selenate as a disease-modifying treatment for bvFTD.

Methods And Analysis: This will be a multisite, phase IIb, double-blind placebo-controlled trial of sodium selenate. One hundred and twenty participants will be enrolled across 4 Australian academic hospitals. Following screening eligible participants will be randomised (1:1) to sodium selenate (15 mg three times a day) or placebo for 52 weeks. Participants will have regular safety and efficacy visits throughout the study period. The primary study outcome will be percentage brain volume change (PBVC) as measured on MRI over 52 weeks of treatment. This will be analysed with a general linear model (analysis of covariance (ANCOVA)) with the PBVC as an output, the treatment as an input and the baseline brain volume as covariate for adjustment purposes. Secondary outcomes include safety and tolerability measures, and efficacy measures; change in cerebrospinal fluid total-tau, Addenbrooke's Cognitive Examination-III and Cambridge Behavioural Inventory-Revised scores over the 52 weeks of treatment. These will also be analysed with ANCOVA where the corresponding baseline measure will be incorporated in the model. Additional exploratory outcomes will include other imaging, cognitive and biospecimen analyses.

Ethics And Dissemination: The study was approved by the Human Research and Ethics Committee of the lead site as part of the Australian Multisite Ethics approval system. The results of the study will be presented at national and international conferences and published in peer-reviewed journals.

Trial Registration Number: ACTRN12620000236998 .
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http://dx.doi.org/10.1136/bmjopen-2020-040100DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670941PMC
November 2020

Development and validation of a screening questionnaire for psychogenic nonepileptic seizures.

Epilepsy Behav 2020 11 28;112:107482. Epub 2020 Sep 28.

The Epilepsy Unit, Alfred Health, Melbourne, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia; Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Australia; Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, Australia; Melbourne School of Psychological Sciences, The University of Melbourne, Australia.

Objective: Epilepsy and psychogenic nonepileptic seizures (PNES) are serious conditions, associated with substantial morbidity and mortality. Although prompt diagnosis is essential, these conditions are frequently misdiagnosed, delaying appropriate treatment. We developed and validated the Anxiety, Abuse, and Somatization Questionnaire (AASQ), a quick and clinically practical tool to differentiate PNES from epilepsy.

Method: We retrospectively identified psychological variables that differentiated epilepsy from PNES in a discovery cohort of patients admitted to a video-electroencephalography monitoring (VEM) unit from 2002 to 2017. From these findings, we developed the AASQ and prospectively validated it in an independent cohort of patients with gold-standard VEM diagnosis.

Results: One thousand two hundred ninety-one patients were included in the retrospective study; mean age was 39.5 years (range: 18-99), 58% were female, 67% had epilepsy, and 33% had PNES. Psychometric data for 192 instrument items were reviewed, receiver operating characteristic curves were computed, and a 20-item AASQ was created. Prospective validation in 74 patients showed that a one-point increase in the AASQ score was associated with 11 times increase in the odds of having PNES compared with epilepsy. Low scores on the AASQ were associated with a low probability of PNES with a negative predictive value of 95%.

Significance: The AASQ is quick, inexpensive, and clinically useful for workup of seizure disorders. The AASQ excludes PNES with a high degree of confidence and can predict PNES with significance when combined with basic clinicodemographic variables. Future research will investigate diagnostic performance of the AASQ in relevant clinical subgroups, such as patients with comorbid epilepsy and PNES.
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http://dx.doi.org/10.1016/j.yebeh.2020.107482DOI Listing
November 2020

Reply: Aggressive multiple sclerosis: a matter of measurement and timing.

Brain 2020 12;143(11):e98

CORe, Department of Medicine, University of Melbourne, Melbourne, Australia.

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http://dx.doi.org/10.1093/brain/awaa307DOI Listing
December 2020

Burnout and psychological distress amongst Australian healthcare workers during the COVID-19 pandemic.

Australas Psychiatry 2021 02 12;29(1):26-30. Epub 2020 Oct 12.

Department of Psychiatry, The Alfred Hospital, Melbourne, VIC, Australia.

Objective: To examine psychological distress in healthcare workers (HCWs) during the COVID-19 pandemic in April-May 2020.

Methods: A cross-sectional survey examining demographic, employment and mental health characteristics of HCWs in a large metropolitan hospital in Australia.

Results: HCWs showed significant symptoms of moderate-severe level depression (21%), anxiety (20%) and posttraumatic stress disorder (PTSD; 29%), associated with burnout, prior psychiatric history, profession and resilience.

Conclusion: Despite low levels of COVID contact, moderate to high levels of psychological distress were reported. Continued monitoring and support for HCWs' mental well-being is warranted as the COVID-19 pandemic develops.
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http://dx.doi.org/10.1177/1039856220965045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554409PMC
February 2021

Correction to: Serum microRNA is a biomarker for post-operative monitoring in glioma.

J Neurooncol 2020 Sep;149(3):401

Department of Surgery, University of Melbourne, Parkville, VIC, Australia.

For the reference citation '[57]' in the second paragraph of the Results section of the original article there was no corresponding entry in the References section. It should have referred to the below mentioned article by Ebrahimkhani et al. (2018).
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http://dx.doi.org/10.1007/s11060-020-03630-5DOI Listing
September 2020

Treatment Response Score to Glatiramer Acetate or Interferon Beta-1a.

Neurology 2021 01 6;96(2):e214-e227. Epub 2020 Oct 6.

From the Department of Health Sciences (DISSAL) (F.B., M.P.S.), University of Genoa, Italy; CORe (T.K., C.M.), Department of Medicine, University of Melbourne, Australia; Department of Neurology (F.L.), Icahn School of Medicine at Mount Sinai, New York, NY; Department of Biostatistics (G.C.), University of Alabama at Birmingham; Department of Neurology and Center for Clinical Neuroscience (D.H., E.K.H.), First Medical Faculty, Charles University, Prague, Czech Republic; Department of Basic Medical Sciences, Neuroscience and Sense Organs (M. Trojano), University of Bari, Italy; Department of Neuroscience (A.P., M.G., P.D.), Faculty of Medicine, Université de Montréal, Quebec, Canada; Department of Neuroscience, Imaging, and Clinical Sciences (M.O.), University G. d'Annunzio, Chieti; IRCCS Istituto delle Scienze Neurologiche di Bologna (A.L.); Dipartimento di Scienze Biomediche e Neuromotorie (A.L.), Università di Bologna, Italy; Hospital Universitario Virgen Macarena (G. Izquierdo. S.E.), Sevilla, Spain; Department of Medical, Surgical Science and Advanced Technology "GF Ingrassia" (F.P.), University of Catania, Italy; Ondokuz Mayis University (M. Terzi), Department of Neurology, Samsun, Turkey; CISSS Chaudi're-Appalache (P.G.), Centre-Hospitalier, Levis, Quebec, Canada; IRCCS Mondino Foundation (R.B.), Pavia; Department of Neuroscience (P.S., D.F.), Azienda Ospedaliera Universitaria, Modena, Italy; Department of Neurology (S.O.), Dokuz Eylul University, Izmir, Turkey; Ospedali Riuniti di Salerno (G. Iuliano), Salerno, Italy; Department of Neurology (C.B.), Karadeniz Technical University, Trabzon, Turkey; Department of Neurology (R.H.), Zuyderland Medical Center, Sittard, the Netherlands; Neuro Rive-Sud (F.G.), Hôpital Charles LeMoyne, Greenfield Park, Quebec, Canada; Clinico San Carlos (C.O.-G), Madrid, Spain; Cliniques Universitaires Saint-Luc (V.v.P.); Université Catholique de Louvain (V.v.P.), Brussels, Belgium; UOC Neurologia (E.C.), Azienda Sanitaria Unica Regionale Marche-AV3, Macerata, Italy; Kommunehospitalet (T.P.), Arhus C, Denmark; Koc University (A.A.), School of Medicine; Bakirkoy Education and Research Hospital for Psychiatric and Neurological Diseases (A.S.), Istanbul, Turkey; Hospital Germans Trias i Pujol (C.R.-T.), Badalona, Spain; University of Queensland (P.M.), Brisbane, Australia; Haydarpasa Numune Training and Research Hospital (R.T.), Istanbul, Turkey; Central Clinical School (H.B.), Monash University, Melbourne, Australia; The University of Texas Health Science Center at Houston (J.S.W.); Rehabilitation Unit (C.S.), "Mons. L. Novarese" Hospital, Moncrivello; and IRCCS Ospedale Policlinico San Martino (M.P.S.), Genoa, Italy.

Objective: To compare the effectiveness of glatiramer acetate (GA) vs intramuscular interferon beta-1a (IFN-β-1a), we applied a previously published statistical method aimed at identifying patients' profiles associated with efficacy of treatments.

Methods: Data from 2 independent multiple sclerosis datasets, a randomized study (the Combination Therapy in Patients With Relapsing-Remitting Multiple Sclerosis [CombiRx] trial, evaluating GA vs IFN-β-1a) and an observational cohort extracted from MSBase, were used to build and validate a treatment response score, regressing annualized relapse rates (ARRs) on a set of baseline predictors.

Results: The overall ARR ratio of GA to IFN-β-1a in the CombiRx trial was 0.72. The response score (made up of a linear combination of age, sex, relapses in the previous year, disease duration, and Expanded Disability Status Scale score) detected differential response of GA vs IFN-β-1a: in the trial, patients with the largest benefit from GA vs IFN-β-1a (lower score quartile) had an ARR ratio of 0.40 (95% confidence interval [CI] 0.25-0.63), those in the 2 middle quartiles of 0.90 (95% CI 0.61-1.34), and those in the upper quartile of 1.14 (95% CI 0.59-2.18) (heterogeneity = 0.012); this result was validated on MSBase, with the corresponding ARR ratios of 0.58 (95% CI 0.46-0.72), 0.92 (95% CI 0.77-1.09,) and 1.29 (95% CI 0.97-1.71); heterogeneity < 0.0001).

Conclusions: We demonstrate the possibility of a criterion, based on patients' characteristics, to choose whether to treat with GA or IFN-β-1a. This result, replicated on an independent real-life cohort, may have implications for clinical decisions in everyday clinical practice.
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http://dx.doi.org/10.1212/WNL.0000000000010991DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7905777PMC
January 2021

Delay from treatment start to full effect of immunotherapies for multiple sclerosis.

Brain 2020 09;143(9):2742-2756

CORe, Department of Medicine, University of Melbourne, Melbourne, 3050, Australia.

In multiple sclerosis, treatment start or switch is prompted by evidence of disease activity. Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. In this study we aimed to develop a method that allows identification of the time to manifest fully and clinically the effect of multiple sclerosis treatments ('therapeutic lag') on clinical disease activity represented by relapses and progression-of-disability events. Data from two multiple sclerosis registries, MSBase (multinational) and OFSEP (French), were used. Patients diagnosed with multiple sclerosis, minimum 1-year exposure to treatment, minimum 3-year pretreatment follow-up and yearly review were included in the analysis. For analysis of disability progression, all events in the subsequent 5-year period were included. Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy. Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start; this point represented the point of stabilization of treatment effect, after the maximum treatment effect was observed. The method was developed in a discovery cohort (MSBase), and externally validated in a separate, non-overlapping cohort (OFSEP). A merged MSBase-OFSEP cohort was used for all subsequent analyses. Annualized relapse rates were compared in the time before treatment start and after the stabilization of treatment effect following commencement of each therapy. We identified 11 180 eligible treatment epochs for analysis of relapses and 4088 treatment epochs for disability progression. External validation was performed in four therapies, with no significant difference in the bootstrapped mean differences in therapeutic lag duration between registries. The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12 and 30 weeks. The duration of therapeutic lag for disability progression was calculated for seven therapies and ranged between 30 and 70 weeks. Significant differences in the pre- versus post-treatment annualized relapse rate were present for all therapies apart from intramuscular interferon beta-1a. In conclusion we have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies in patients more than 3 years from multiple sclerosis onset. Objectively defined periods of expected therapeutic lag allows insights into the evaluation of treatment response in randomized clinical trials and may guide clinical decision-making in patients who experience early on-treatment disease activity. This method will subsequently be applied in studies that evaluate the effect of patient and disease characteristics on therapeutic lag.
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http://dx.doi.org/10.1093/brain/awaa231DOI Listing
September 2020

Longitudinal patterns of white matter fibre density and morphology in children are associated with age and pubertal stage.

Dev Cogn Neurosci 2020 10 28;45:100853. Epub 2020 Aug 28.

Developmental Imaging, Murdoch Children's Research Institute, Parkville, Australia; Department of Paediatrics, University of Melbourne, Parkville, Australia.

The pubertal period involves dynamic white matter development. This period also corresponds with rapid gains in higher cognitive functions including attention, as well as increased risk of developing mental health difficulties. This longitudinal study comprised children aged 9-13 years (n = 130). Diffusion magnetic resonance imaging (dMRI) data were acquired (b = 2800s/mm, 60 directions) at two time-points. We derived measures of fibre density and morphology using the fixel-based analysis framework and performed a tract-based mixed-effects modelling analysis to understand patterns of white matter development with respect to age, sex, pubertal stage, and the change in pubertal stage. We observed significant increases in apparent fibre density across a large number of white matter pathways, including major association and commissural pathways. We observed a linear relationship between pubertal stage and fibre density and morphology in the right superior longitudinal fasciculus, and fibre morphology in the right inferior longitudinal fasciculus. Finally, we report a significant interaction between the change in pubertal stage and age in the development of fibre density, for left-lateralised association tracts. Overall, white matter development across ages 9-13 years involves the expansion of major white matter fibre pathways, with key association pathways linked with pubertal stage.
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http://dx.doi.org/10.1016/j.dcn.2020.100853DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498759PMC
October 2020

Serum microRNA is a biomarker for post-operative monitoring in glioma.

J Neurooncol 2020 Sep 11;149(3):391-400. Epub 2020 Sep 11.

Department of Surgery, University of Melbourne, Parkville, VIC, Australia.

Purpose: A circulating biomarker has potential to provide more accurate information for glioma progression post treatment, however no such biomarker is currently available. We aimed to discover a microRNA serum biomarker for longitudinal monitoring of glioma patients.

Methods: A prospectively collected cohort of 91 glioma patients and 17 healthy controls underwent pre and post-operative serum miRNA profiling using Nanostring®. Differentially expressed miRNAs were discovered using a machine learning random forest analysis. Candidate miRNAs were then assessed by droplet digital PCR in 11 patients with multiple follow up samples and compared to tumor volume based on magnetic resonance imaging.

Results: A 9-gene miRNA signature was identified that could distinguish between glioma and healthy controls with 99.8% accuracy. Two miRNAs miR-223 and miR-320e, best demonstrated dynamic changes that correlated closely with tumor volume in LGG and GBM respectively. Importantly, miRNA levels did not increase in two cases of pseudo-progression, indicating the potential utility of this test in guiding treatment decisions.

Conclusions: We identified a highly accurate 9-miRNA signature associated with glioma serum. Additionally, we observed dynamic changes in specific miRNAs correlating with tumor volume over long-term follow up. These results support a large prospective validation study of serum miRNA biomarkers in glioma.
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http://dx.doi.org/10.1007/s11060-020-03566-wDOI Listing
September 2020

Longitudinal Trajectories of Sustained Attention Development in Children and Adolescents with ADHD.

J Abnorm Child Psychol 2020 12;48(12):1529-1542

Department of Paediatrics, The University of Melbourne, Melbourne, Australia.

The present study characterizes changes in sustained attention ability over ages 9-14, and whether longitudinal trajectories of attention development differ between persistent ADHD, remitted ADHD and control groups. The Sustained Attention to Response Task (SART) was administered to 120 children with ADHD and 123 controls on three occasions between ages 9 and 14. Trajectories of sustained attention development, indicated by changes in SART performance (standard deviation of response time [SDRT], omission errors, and ex-Gaussian parameters sigma and tau), were examined using generalized additive mixed models. For all measures there was a significant main effect of age; response time variability and number of omission errors improved linearly as children aged. However, children with ADHD had significantly greater SDRT, tau and omission errors than controls across waves. There were no significant group differences in sigma, indicating that the greater overall response time variability (SDRT) observed in ADHD was likely driven by more intermittent long responses (larger tau). Trajectories of sustained attention performance did not differ between children with persistent ADHD or ADHD in remission. Longitudinal trajectories of sustained attention development are comparable between ADHD and controls, however children with ADHD (regardless of remission status) display a performance deficit equivalent to typical controls 1-3 years younger. Findings highlight the need for continued clinical support for children in remission from ADHD and provide support for tau as an endophenotype of ADHD.
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http://dx.doi.org/10.1007/s10802-020-00698-5DOI Listing
December 2020

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders.

Authors:
Yash Patel Nadine Parker Jean Shin Derek Howard Leon French Sophia I Thomopoulos Elena Pozzi Yoshinari Abe Christoph Abé Alan Anticevic Martin Alda Andre Aleman Clara Alloza Silvia Alonso-Lana Stephanie H Ameis Evdokia Anagnostou Andrew A McIntosh Celso Arango Paul D Arnold Philip Asherson Francesca Assogna Guillaume Auzias Rosa Ayesa-Arriola Geor Bakker Nerisa Banaj Tobias Banaschewski Cibele E Bandeira Alexandr Baranov Núria Bargalló Claiton H D Bau Sarah Baumeister Bernhard T Baune Mark A Bellgrove Francesco Benedetti Alessandro Bertolino Premika S W Boedhoe Marco Boks Irene Bollettini Caterina Del Mar Bonnin Tiana Borgers Stefan Borgwardt Daniel Brandeis Brian P Brennan Jason M Bruggemann Robin Bülow Geraldo F Busatto Sara Calderoni Vince D Calhoun Rosa Calvo Erick J Canales-Rodríguez Dara M Cannon Vaughan J Carr Nicola Cascella Mara Cercignani Tiffany M Chaim-Avancini Anastasia Christakou David Coghill Annette Conzelmann Benedicto Crespo-Facorro Ana I Cubillo Kathryn R Cullen Renata B Cupertino Eileen Daly Udo Dannlowski Christopher G Davey Damiaan Denys Christine Deruelle Annabella Di Giorgio Erin W Dickie Danai Dima Katharina Dohm Stefan Ehrlich Benjamin A Ely Tracy Erwin-Grabner Thomas Ethofer Damien A Fair Andreas J Fallgatter Stephen V Faraone Mar Fatjó-Vilas Jennifer M Fedor Kate D Fitzgerald Judith M Ford Thomas Frodl Cynthia H Y Fu Janice M Fullerton Matt C Gabel David C Glahn Gloria Roberts Tinatin Gogberashvili Jose M Goikolea Ian H Gotlib Roberto Goya-Maldonado Hans J Grabe Melissa J Green Eugenio H Grevet Nynke A Groenewold Dominik Grotegerd Oliver Gruber Patricia Gruner Amalia Guerrero-Pedraza Raquel E Gur Ruben C Gur Shlomi Haar Bartholomeus C M Haarman Jan Haavik Tim Hahn Tomas Hajek Benjamin J Harrison Neil A Harrison Catharina A Hartman Heather C Whalley Dirk J Heslenfeld Derrek P Hibar Eva Hilland Yoshiyuki Hirano Tiffany C Ho Pieter J Hoekstra Liesbeth Hoekstra Sarah Hohmann L E Hong Cyril Höschl Marie F Høvik Fleur M Howells Igor Nenadic Maria Jalbrzikowski Anthony C James Joost Janssen Fern Jaspers-Fayer Jian Xu Rune Jonassen Georgii Karkashadze Joseph A King Tilo Kircher Matthias Kirschner Kathrin Koch Peter Kochunov Gregor Kohls Kerstin Konrad Bernd Krämer Axel Krug Jonna Kuntsi Jun Soo Kwon Mikael Landén Nils I Landrø Luisa Lazaro Irina S Lebedeva Elisabeth J Leehr Sara Lera-Miguel Klaus-Peter Lesch Christine Lochner Mario R Louza Beatriz Luna Astri J Lundervold Frank P MacMaster Luigi A Maglanoc Charles B Malpas Maria J Portella Rachel Marsh Fiona M Martyn David Mataix-Cols Daniel H Mathalon Hazel McCarthy Colm McDonald Genevieve McPhilemy Susanne Meinert José M Menchón Luciano Minuzzi Philip B Mitchell Carmen Moreno Pedro Morgado Filippo Muratori Clodagh M Murphy Declan Murphy Benson Mwangi Leila Nabulsi Akiko Nakagawa Takashi Nakamae Leyla Namazova Janardhanan Narayanaswamy Neda Jahanshad Danai D Nguyen Rosa Nicolau Ruth L O'Gorman Tuura Kirsten O'Hearn Jaap Oosterlaan Nils Opel Roel A Ophoff Bob Oranje Victor Ortiz García de la Foz Bronwyn J Overs Yannis Paloyelis Christos Pantelis Mara Parellada Paul Pauli Maria Picó-Pérez Felipe A Picon Fabrizio Piras Federica Piras Kerstin J Plessen Edith Pomarol-Clotet Adrian Preda Olga Puig Yann Quidé Joaquim Radua J Antoni Ramos-Quiroga Paul E Rasser Lisa Rauer Janardhan Reddy Ronny Redlich Andreas Reif Liesbeth Reneman Jonathan Repple Alessandra Retico Vanesa Richarte Anja Richter Pedro G P Rosa Katya K Rubia Ryota Hashimoto Matthew D Sacchet Raymond Salvador Javier Santonja Kelvin Sarink Salvador Sarró Theodore D Satterthwaite Akira Sawa Ulrich Schall Peter R Schofield Anouk Schrantee Jochen Seitz Mauricio H Serpa Esther Setién-Suero Philip Shaw Devon Shook Tim J Silk Kang Sim Schmitt Simon Helen Blair Simpson Aditya Singh Antonin Skoch Norbert Skokauskas Jair C Soares Noam Soreni Carles Soriano-Mas Gianfranco Spalletta Filip Spaniel Stephen M Lawrie Emily R Stern S Evelyn Stewart Yoichiro Takayanagi Henk S Temmingh David F Tolin David Tomecek Diana Tordesillas-Gutiérrez Michela Tosetti Anne Uhlmann Therese van Amelsvoort Nic J A van der Wee Steven J A van der Werff Neeltje E M van Haren Guido A van Wingen Alasdair Vance Javier Vázquez-Bourgon Daniela Vecchio Ganesan Venkatasubramanian Eduard Vieta Oscar Vilarroya Yolanda Vives-Gilabert Aristotle N Voineskos Henry Völzke Georg G von Polier Esther Walton Thomas W Weickert Cynthia Shannon Weickert Andrea S Weideman Katharina Wittfeld Daniel H Wolf Mon-Ju Wu T T Yang Kun Yang Yuliya Yoncheva Je-Yeon Yun Yuqi Cheng Marcus V Zanetti Georg C Ziegler Barbara Franke Martine Hoogman Jan K Buitelaar Daan van Rooij Ole A Andreassen Christopher R K Ching Dick J Veltman Lianne Schmaal Dan J Stein Odile A van den Heuvel Jessica A Turner Theo G M van Erp Zdenka Pausova Paul M Thompson Tomáš Paus

JAMA Psychiatry 2021 Jan;78(1):47-63

Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.

Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.

Design, Setting, And Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.

Main Outcomes And Measures: Interregional profiles of group difference in cortical thickness between cases and controls.

Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.

Conclusions And Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.2694DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450410PMC
January 2021

Time to diagnosis in younger-onset dementia and the impact of a specialist diagnostic service.

Int Psychogeriatr 2020 Aug 28:1-9. Epub 2020 Aug 28.

Neuropsychiatry, NorthWestern Mental Health, Royal Melbourne Hospital, Parkville, Victoria3050, Australia.

Objectives: While early diagnosis of younger-onset dementia (YOD) is crucial in terms of accessing appropriate services and future planning, diagnostic delays are common. This study aims to identify predictors of delay to diagnosis in a large sample of people with YOD and to investigate the impact of a specialist YOD service on this time to diagnosis.

Design: A retrospective cross-sectional study.

Setting: The inpatient unit of a tertiary neuropsychiatry service in metropolitan Victoria, Australia.

Participants: People diagnosed with a YOD.

Measurements And Methods: We investigated the following predictors using general linear modeling: demographics including sex and location, age at onset, dementia type, cognition, psychiatric diagnosis, and number of services consulted with prior to diagnosis.

Results: A total of 242 inpatients were included. The mean time to diagnosis was 3.4 years. Significant predictors of delay included younger age at onset, dementia type other than Alzheimer's disease (AD) and behavioral-variant frontotemporal dementia (bvFTD), and increased number of services consulted. These predictors individually led to an increased diagnostic delay of approximately 19 days, 5 months, and 6 months, respectively. A specialized YOD service reduced time to diagnosis by 12 months.

Conclusion: We found that younger age at onset, having a dementia which was not the most commonly occurring AD or bvFTD, and increasing number of services were significant predictors of diagnostic delay. A novel result was that a specialist YOD service may decrease diagnostic delay, highlighting the importance of such as service in reducing time to diagnosis as well as providing post-diagnostic support.
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http://dx.doi.org/10.1017/S1041610220001489DOI Listing
August 2020

Association of Sustained Immunotherapy With Disability Outcomes in Patients With Active Secondary Progressive Multiple Sclerosis.

JAMA Neurol 2020 Jul 27. Epub 2020 Jul 27.

Clinical Outcomes Research Unit (CORe), Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia.

Importance: It is unclear whether relapses and disease-modifying therapies are associated with the rate of disability accumulation in patients with secondary progressive multiple sclerosis (SPMS).

Objective: To examine the association of relapses with the rate of disability accumulation in patients with SPMS and to assess whether treatment before or during the secondary progressive phase can slow the progression of disability accumulation.

Design, Setting, And Participants: In this observational cohort study, patient data were prospectively collected from the MSBase international registry between January 1, 1995, and February 1, 2018. Among 53 680 patients in the MSBase registry, 4997 patients with SPMS (using the Lorscheider definition) were identified. Of those, 1621 patients were eligible for study inclusion based on sufficient follow-up before and after the onset of SPMS. Data were analyzed from November 15, 2017, to January 13, 2020.

Exposures: The association between disability accumulation and several clinical and demographic variables, including relapses and exposure to immunotherapy, was evaluated.

Main Outcomes And Measures: Two outcomes were analyzed as measures of disability accumulation during SPMS: the rate of disability accumulation during the secondary progressive phase (change relative to the reference population of patients with MS and absolute change) and the risk of becoming wheelchair dependent. A third outcome, the cumulative risk of experiencing confirmed disability progression events, was used for a secondary analysis. Outcomes were evaluated using multivariable mixed models (ie, linear and Cox models).

Results: Of 1621 patients eligible for inclusion, 1103 patients (68.0%) were female, with a mean (SD) age at MS onset of 33.9 (10.6) years. A total of 661 patients (40.8%) experienced superimposed relapses during SPMS. Therapy receipt and relapses during early relapsing-remitting MS were not associated with disability accumulation during the secondary progressive phase. Higher relapse rates during the secondary progressive disease stage were associated with an increased risk of becoming wheelchair dependent (hazard ratio [HR], 1.87; 95% CI, 1.17-3.00; P = .009). Among patients who experienced superimposed relapses during SPMS, greater receipt of disease-modifying therapies was significantly associated with a reduced rate of disability progression and a lower risk of becoming wheelchair dependent.

Conclusions And Relevance: In this study, the rate of disability progression after the onset of SPMS was not associated with the early disease course and treatment decisions. Relapses during SPMS were associated with accelerated disability progression and represent an accessible treatment target. Disease-modifying therapy was associated with improvements in disability outcomes among patients with active relapses during SPMS. The study's results suggest that inflammatory disease activity remains a substantial yet modifiable component of SPMS.
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http://dx.doi.org/10.1001/jamaneurol.2020.2453DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7385679PMC
July 2020

Mortality in patients with psychogenic nonepileptic seizures.

Neurology 2020 08 20;95(6):e643-e652. Epub 2020 Jul 20.

From the Department of Neuroscience, Central Clinical School (R.N., S.B., C.B.M., P.P., Z.C., S.S., P.K., T.J.O.), and Clinical Epidemiology, School of Public Health and Preventive Medicine (Z.C.), Monash University, Melbourne; Departments of Medicine (R.N., C.A., G.T., C.B.M., P.P., A.M., Z.C., S.S., P.K., T.J.O.) and Neurology (R.N., C.A., G.T., C.B.M., P.P., S.S., P.K., T.J.O.) and Neuropsychiatry Unit (L.M., S.J., S.A., D.V.), The Royal Melbourne Hospital, and The Melbourne School of Psychological Sciences (C.B.M.), The University of Melbourne, Parkville; Department of Medicine (R.N.) and Epilepsy Research Centre, Department of Medicine (A.M., S.F.B.), Austin Health, The University of Melbourne, Heidelberg; Department of Neurology (C.B.M., P.P., A.M., S.S., P.K., T.J.O.), The Alfred Hospital, Melbourne; and Department of Medicine (S.I., M.J.C., W.D.), St. Vincent's Hospital, The University of Melbourne, Fitzroy, Australia.

Objective: To investigate the hypothesis that patients diagnosed with psychogenic nonepileptic seizures (PNES) on video-EEG monitoring (VEM) have increased mortality by comparison to the general population.

Methods: This retrospective cohort study included patients evaluated in VEM units of 3 tertiary hospitals in Melbourne, Australia, between January 1, 1995, and December 31, 2015. Diagnosis was based on consensus opinion of experienced epileptologists and neuropsychiatrists at each hospital. Mortality was determined in patients diagnosed with PNES, epilepsy, or both conditions by linkage to the Australian National Death Index. Lifetime history of psychiatric disorders in PNES was determined from formal neuropsychiatric reports.

Results: A total of 5,508 patients underwent VEM. A total of 674 (12.2%) were diagnosed with PNES, 3064 (55.6%) with epilepsy, 175 (3.2%) with both conditions, and 1,595 (29.0%) received other diagnoses or had no diagnosis made. The standardized mortality ratio (SMR) of patients diagnosed with PNES was 2.5 (95% confidence interval [CI] 2.0-3.3). Those younger than 30 had an 8-fold higher risk of death (95% CI 3.4-19.8). Direct comparison revealed no significant difference in mortality rate between diagnostic groups. Among deaths in patients diagnosed with PNES (n = 55), external causes contributed 18%, with 20% of deaths in those younger than 50 years attributed to suicide, and "epilepsy" was recorded as the cause of death in 24%.

Conclusions: Patients diagnosed with PNES have a SMR 2.5 times above the general population, dying at a rate comparable to those with drug-resistant epilepsy. This emphasizes the importance of prompt diagnosis, identification of risk factors, and implementation of appropriate strategies to prevent potential avoidable deaths.
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http://dx.doi.org/10.1212/WNL.0000000000009855DOI Listing
August 2020

Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups.

Authors:
Premika S W Boedhoe Daan van Rooij Martine Hoogman Jos W R Twisk Lianne Schmaal Yoshinari Abe Pino Alonso Stephanie H Ameis Anatoly Anikin Alan Anticevic Celso Arango Paul D Arnold Philip Asherson Francesca Assogna Guillaume Auzias Tobias Banaschewski Alexander Baranov Marcelo C Batistuzzo Sarah Baumeister Ramona Baur-Streubel Marlene Behrmann Mark A Bellgrove Francesco Benedetti Jan C Beucke Joseph Biederman Irene Bollettini Anushree Bose Janita Bralten Ivanei E Bramati Daniel Brandeis Silvia Brem Brian P Brennan Geraldo F Busatto Sara Calderoni Anna Calvo Rosa Calvo Francisco X Castellanos Mara Cercignani Tiffany M Chaim-Avancini Kaylita C Chantiluke Yuqi Cheng Kang Ik K Cho Anastasia Christakou David Coghill Annette Conzelmann Ana I Cubillo Anders M Dale Sara Dallaspezia Eileen Daly Damiaan Denys Christine Deruelle Adriana Di Martino Ilan Dinstein Alysa E Doyle Sarah Durston Eric A Earl Christine Ecker Stefan Ehrlich Benjamin A Ely Jeffrey N Epstein Thomas Ethofer Damien A Fair Andreas J Fallgatter Stephen V Faraone Jennifer Fedor Xin Feng Jamie D Feusner Jackie Fitzgerald Kate D Fitzgerald Jean-Paul Fouche Christine M Freitag Egill A Fridgeirsson Thomas Frodl Matt C Gabel Louise Gallagher Tinatin Gogberashvili Ilaria Gori Patricia Gruner Deniz A Gürsel Shlomi Haar Jan Haavik Geoffrey B Hall Neil A Harrison Catharina A Hartman Dirk J Heslenfeld Yoshiyuki Hirano Pieter J Hoekstra Marcelo Q Hoexter Sarah Hohmann Marie F Høvik Hao Hu Chaim Huyser Neda Jahanshad Maria Jalbrzikowski Anthony James Joost Janssen Fern Jaspers-Fayer Terry L Jernigan Dmitry Kapilushniy Bernd Kardatzki Georgii Karkashadze Norbert Kathmann Christian Kaufmann Clare Kelly Sabin Khadka Joseph A King Kathrin Koch Gregor Kohls Kerstin Konrad Masaru Kuno Jonna Kuntsi Gerd Kvale Jun Soo Kwon Luisa Lázaro Sara Lera-Miguel Klaus-Peter Lesch Liesbeth Hoekstra Yanni Liu Christine Lochner Mario R Louza Beatriz Luna Astri J Lundervold Charles B Malpas Paulo Marques Rachel Marsh Ignacio Martínez-Zalacaín David Mataix-Cols Paulo Mattos Hazel McCarthy Jane McGrath Mitul A Mehta José M Menchón Maarten Mennes Mauricio Moller Martinho Pedro S Moreira Astrid Morer Pedro Morgado Filippo Muratori Clodagh M Murphy Declan G M Murphy Akiko Nakagawa Takashi Nakamae Tomohiro Nakao Leyla Namazova-Baranova Janardhanan C Narayanaswamy Rosa Nicolau Joel T Nigg Stephanie E Novotny Erika L Nurmi Eileen Oberwelland Weiss Ruth L O'Gorman Tuura Kirsten O'Hearn Joseph O'Neill Jaap Oosterlaan Bob Oranje Yannis Paloyelis Mara Parellada Paul Pauli Chris Perriello John Piacentini Fabrizio Piras Federica Piras Kerstin J Plessen Olga Puig J Antoni Ramos-Quiroga Y C Janardhan Reddy Andreas Reif Liesbeth Reneman Alessandra Retico Pedro G P Rosa Katya Rubia Oana Georgiana Rus Yuki Sakai Anouk Schrantee Lena Schwarz Lizanne J S Schweren Jochen Seitz Philip Shaw Devon Shook Tim J Silk H Blair Simpson Norbert Skokauskas Juan Carlos Soliva Vila Anastasia Solovieva Noam Soreni Carles Soriano-Mas Gianfranco Spalletta Emily R Stern Michael C Stevens S Evelyn Stewart Gustavo Sudre Philip R Szeszko Leanne Tamm Margot J Taylor David F Tolin Michela Tosetti Fernanda Tovar-Moll Aki Tsuchiyagaito Theo G M van Erp Guido A van Wingen Alasdair Vance Ganesan Venkatasubramanian Oscar Vilarroya Yolanda Vives-Gilabert Georg G von Polier Susanne Walitza Gregory L Wallace Zhen Wang Thomas Wolfers Yuliya N Yoncheva Je-Yeon Yun Marcus V Zanetti Fengfeng Zhou Georg C Ziegler Kathrin C Zierhut Marcel P Zwiers Paul M Thompson Dan J Stein Jan Buitelaar Barbara Franke Odile A van den Heuvel

Am J Psychiatry 2020 09 16;177(9):834-843. Epub 2020 Jun 16.

The full list of authors in the ENIGMA working groups, author affiliations, author disclosures, and acknowledgments are provided in online supplements.

Objective: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.

Methods: Structural T-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures).

Results: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood.

Conclusions: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.
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http://dx.doi.org/10.1176/appi.ajp.2020.19030331DOI Listing
September 2020

Disability outcomes of early cerebellar and brainstem symptoms in multiple sclerosis.

Mult Scler 2021 Apr 15;27(5):755-766. Epub 2020 Jun 15.

CORe, Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia.

Background: Cerebellar and brainstem symptoms are common in early stages of multiple sclerosis (MS) yet their prognostic values remain unclear.

Objective: The aim of this study was to investigate long-term disability outcomes in patients with early cerebellar and brainstem symptoms.

Methods: This study used data from MSBase registry. Patients with early cerebellar/brainstem presentations were identified as those with cerebellar/brainstem relapse(s) or functional system score ⩾ 2 in the initial 2 years. Early pyramidal presentation was chosen as a comparator. Andersen-Gill models were used to compare cumulative hazards of (1) disability progression events and (2) relapses between patients with and without early cerebellar/brainstem symptoms. Mixed effect models were used to estimate the associations between early cerebellar/brainstem presentations and expanded disability status scale (EDSS) scores.

Results: The study cohort consisted of 10,513 eligible patients, including 2723 and 3915 patients with early cerebellar and brainstem symptoms, respectively. Early cerebellar presentation was associated with greater hazard of progression events (HR = 1.37,  < 0.001) and EDSS (β = 0.16,  < 0.001). Patients with early brainstem symptoms had lower hazard of progression events (HR = 0.89,  = 0.01) and EDSS (β = -0.06,  < 0.001). Neither presentation was associated with changes in relapse risk.

Conclusion: Early cerebellar presentation is associated with unfavourable outcomes, while early brainstem presentation is associated with favourable prognosis. These presentations may be used as MS prognostic markers and guide therapeutic approach.
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http://dx.doi.org/10.1177/1352458520926955DOI Listing
April 2021

The neuropsychological spectrum of anti-LGI1 antibody mediated autoimmune encephalitis.

J Neuroimmunol 2020 08 22;345:577271. Epub 2020 May 22.

Department of Neurosciences, Faculty of Medicine, Nursing and Health Sciences, Central Clinical School, Monash University, Melbourne, VIC, Australia; Department of Neurology, Alfred Health, Melbourne, VIC, Australia; Department of Neurology, Melbourne Health, Parkville, VIC, Australia. Electronic address:

Anti-Leucine Glioma Inactivated 1 (LGI-1) autoimmune encephalitis (AE) is a rare neuroinflammatory brain condition. Individuals afflicted with this condition can present with cognitive and psychological manifestations that can impact the individual's quality of life, day to day functioning, independence, return to work and interpersonal relationships. Our knowledge of the cognitive profiles and disease associated psychopathology is severely lacking. This review provides a comprehensive summary of the currently available literature, conceptualising our current understanding of the neuropsychological manifestations of anti LGI-1 AE and summarises methodological limitations of the current research to inform and improve future investigations. Key Terms: Autoimmune Diseases; Neuroimmunology; Autoimmune Encephalitis, Limbic Encephalitis; Anti-LGI1 Encephalitis, LGI1; Neuropsychology, Cognitive Assessment.
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http://dx.doi.org/10.1016/j.jneuroim.2020.577271DOI Listing
August 2020

Early clinical markers of aggressive multiple sclerosis.

Brain 2020 05;143(5):1400-1413

CORe Unit, Department of Medicine, University of Melbourne, Melbourne, Australia.

Patients with the 'aggressive' form of multiple sclerosis accrue disability at an accelerated rate, typically reaching Expanded Disability Status Score (EDSS) ≥ 6 within 10 years of symptom onset. Several clinicodemographic factors have been associated with aggressive multiple sclerosis, but less research has focused on clinical markers that are present in the first year of disease. The development of early predictive models of aggressive multiple sclerosis is essential to optimize treatment in this multiple sclerosis subtype. We evaluated whether patients who will develop aggressive multiple sclerosis can be identified based on early clinical markers. We then replicated this analysis in an independent cohort. Patient data were obtained from the MSBase observational study. Inclusion criteria were (i) first recorded disability score (EDSS) within 12 months of symptom onset; (ii) at least two recorded EDSS scores; and (iii) at least 10 years of observation time, based on time of last recorded EDSS score. Patients were classified as having 'aggressive multiple sclerosis' if all of the following criteria were met: (i) EDSS ≥ 6 reached within 10 years of symptom onset; (ii) EDSS ≥ 6 confirmed and sustained over ≥6 months; and (iii) EDSS ≥ 6 sustained until the end of follow-up. Clinical predictors included patient variables (sex, age at onset, baseline EDSS, disease duration at first visit) and recorded relapses in the first 12 months since disease onset (count, pyramidal signs, bowel-bladder symptoms, cerebellar signs, incomplete relapse recovery, steroid administration, hospitalization). Predictors were evaluated using Bayesian model averaging. Independent validation was performed using data from the Swedish Multiple Sclerosis Registry. Of the 2403 patients identified, 145 were classified as having aggressive multiple sclerosis (6%). Bayesian model averaging identified three statistical predictors: age > 35 at symptom onset, EDSS ≥ 3 in the first year, and the presence of pyramidal signs in the first year. This model significantly predicted aggressive multiple sclerosis [area under the curve (AUC) = 0.80, 95% confidence intervals (CIs): 0.75, 0.84, positive predictive value = 0.15, negative predictive value = 0.98]. The presence of all three signs was strongly predictive, with 32% of such patients meeting aggressive disease criteria. The absence of all three signs was associated with a 1.4% risk. Of the 556 eligible patients in the Swedish Multiple Sclerosis Registry cohort, 34 (6%) met criteria for aggressive multiple sclerosis. The combination of all three signs was also predictive in this cohort (AUC = 0.75, 95% CIs: 0.66, 0.84, positive predictive value = 0.15, negative predictive value = 0.97). Taken together, these findings suggest that older age at symptom onset, greater disability during the first year, and pyramidal signs in the first year are early indicators of aggressive multiple sclerosis.
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http://dx.doi.org/10.1093/brain/awaa081DOI Listing
May 2020