Neuroimaging Akademie i.R. der Alzheimer-Tagung — 20.09. - 21.09.2019

Jahrestagung 2019: Poster-Preisträger

Jahrestagung 2019: Poster-Preisträger


Die ÖGN gratuliert den Gewinnern! Der Preis ist mit € 1.000,- dotiert.

 

P10: Pharmacoepidemiology in dementia: insights from the Austrian population


Wurm R1, Stamm T2, Reichardt B3, Schwarz-Nemec F1, Parvizi T1, Silvaieh S1, König T1, Stögmann E1
1 Department of Neurology, Medical University of Vienna
2 Section for Outcomes Research, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna
3 Unit for Healthcare Economics, Regional Sickness Fund of the county Burgenland, Eisenstadt

Background: Dementia is a leading cause of global morbidity and mortality and its prevalence is expected to rise dramatically in the next decades. The escalating number of dementia cases will require long term na-tional strategies. However, current prevalence estimates for Austria are based on statistical modeling only. This highlights the need for robust epidemiologic data for policy making.
Material and Methods: Insurance claims data was obtained from the Association of Austrian Social Security Institutions covering 98% of the Austrian population. We identified patients treated with anti-dementives, either one of three cholinesterase inhibitors (ChEIs) − rivastigmine, galantamine, donepezil − or the glutamate antagonist memantine in the period of 2013−16 and calculated prescription rates. Cox proportional hazard models to assess the association with mortality were adjusted for age at start of treatment and sex. Calculations were per-formed in R (version 3.4.4).
Results: 78,089 (0.92% of the insured population) persons were treated with antidementives in 2014 and 83,111 in 2015 (0.98%). 76.1% were treated with ChEIs, 18.8% with memantine, 5.1% with a combination of both. Treatment with memantine was associated with an increased mortality (HR 1.47, 95% CI 1.43 − 1.51, p < 0.001). Comparing the different ChEI options, donepezil was associated with a decreased (HR 0.82, 0.8 − 0.84, p < 0.001) and galantamine with an increased mortality (HR 1.44, 1.37 − 1.5, p < 0.001). 18% of patients switched medication during the observation period, of those 61% from ChEIs to memantine and 39% from memantine to ChEIs. Switching to memantine was associated with an increase in mortality (HR 1.36, 1.28 − 1.44, p < 0.001). The median time to switch was 191 days (IQR 72 − 413) and was longer to memantine than reverse (241 vs 134, p < 0.001).
Conclusion: More than 80,000 people were treated with anti-dementives in Austria in 2015. Most of the patients were treated with one of the three ChEIs, roughly 19% were treat-ed with memantine, and combination therapy was rare. Therapy with memantine or switching to it was associated with increased mortality, possibly reflecting more advanced disease in these patients. The negative effect of galantamine on mortality warrants further investigation.

P59: Serum neurofilament light levels in normal aging: associations with morphologic brain changes


Khalil M1, Pirpamer L1, Hofer E1, Voortman M1, Barro C2, Ropele S1, Enzinger C1, Fazekas F1, Schmidt R1, Kuhle J2
1 Medical University of Graz
2 University Hospital Basel, Switzerland

Objective: Neurofilament light (NfL) protein is a marker of neuroaxonal damage and can be measured not only in cerebrospinal fluid but also in serum, which allows repeated assessment. While serum NfL (sNfL) has already been studied in several disorders, there is still limited knowledge regarding the association of sNfL with age and sub-clinical morphologic brain changes in the normal population.
Methods: We measured sNfL by a single molecule array (Simoa) assay in 335 individ-uals (age range 38.5−85.6 years [y]) from the Austrian Stroke Prevention Study, which is a prospective community-based study on brain health and aging in Graz, Austria. A follow-up serum sample was available in 103 individuals (mean follow-up time 5.9 ± 1.0 y). All participants underwent detailed clinical examination, laboratory evaluation, cognitive testing, and brain MRI at 3T to exclude any significant cerebral disorder. White matter hyperintensity (WMH) volumes, brain vo-lumes and their changes over time were measured as markers of subclinical brain damage.
Results: Mean sNfL (pg/mL) levels were stable below 60 y {20.4 (SD 5.6) [40−50 y, n = 54] and 22.9 (SD 7.7) [50−60 y, n = 45]} but then increased in a non-linear manner: 34.7 (SD 13.1) [60−70 y, n = 102]; 45.9 (SD 15.3) [> 70 y, n = 134]; regression analysis p < 0.0001, R2 = 0.42. This was paralleled by an increase of group variances in sNfL levels above the age of 60 y (p < 0.0001). In individuals < 60 y the annualized change in sNfL was the strongest independent predictor of brain volume loss (b = 0.52, p < 0.01), whereas in older individuals (> 60 y), both baseline sNfL (b = 0.57, p < 0.0001) and annualized change of sNfL (b = 0.50, p < 0.0001) were associated with increased brain volume loss over time using stepwise linear regression analysis. The models exclud-ed age, baseline normalized brain volume, WMH volume and annualized change of WMH volume.
Interpretation: We here provide detailed description of age-associated changes in sNfL within an aging normal population. Rising and more variable sNfL in individuals > 60 y indicate an acceleration of neurodegenera-tion at that age which may be confounded by subclinical pathologic brain changes. This is supported by the close association of sNfL with brain volume changes in a cross-section-al and especially longitudinal manner.

P73: Exome sequencing of 112 patients highlights a major role of mTOR signalling pathway genes in non-acquired focal epilepsies


Krenn M1,2, Wagner M2,3, Graf E3, Hotzy C1, Stögmann E1, Pataraia E1, Zimprich A1, Meitinger T2,3, Zimprich F1
1 Department of Neurology, Medical University of Vienna
2 Institute of Human Genetics, Technical University Munich, Germany
3 Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany

Background and purpose: In spite of the high heritability of non-acquired focal epilepsies (NAFE), mainly demonstrated by genome-wide association and family studies, risk gene discovery is often challenging due to the complex genetic architecture. The purpose of this study is to address the yield of exome sequencing (ES) and to character-ize the molecular findings in NAFE with a suspected genetic basis.
Methods: We performed ES on 112 consecutive patients with NAFE and at least one of the following additional features suggestive of a genetic background: a positive fam-ily history of seizures or disease onset under 18 years or febrile seizures or multifocal seizure origin. Exclusion criteria were intellectual disability and/or structural brain malformations (except for hippocampal sclerosis).
Results: 9/112 (8%) patients had pathogenic or likely pathogenic variants detected in the epilepsy-associated genes DEPDC5 (4x), NPRL3 (2x), PCDH19 (1x), SCN1A (1x) and STX1B (1x). The (likely) pathogenic variants included two frameshift and two nonsense mutations, one splice site mutation and two copy number variants (CNVs), i.e. deletions involving the genes NPRL3 and PCDH19, respectively. One missense mutation in SCN1A was previously reported as pathogen-ic according to the ClinVar database. Additionally, we detected 23 very rare missense variants (minor allele frequency < 0.01%) in 14 different epilepsy-associated genes in 21/112 (18.8%) patients with an assumed, but unconfirmed pathogenic effect, hence classified as variants of unknown significance (VUS). Genes involved in the mTOR signalling pathway (i.e. DEPDC5, NPRL3 and MTOR) accounted for 66.7% of (likely) pathogenic and for 46.9% of all reported hits (including pathogenic variants and VUS). Two patients with familial temporal lobe epilepsy each carried two rare missense variants in different epilepsy-associated genes (LGI1/NPRL3 and SCN3A/DEPDC5). Actionable (incidental) variants were reported in 2/112 (1.8%) patients (BRCA1 and APC).
Conclusion: Although ES detected (likely) pathogenic variants in only 8% of patients, there is a high rate of very rare VUS in epilepsy-associated genes, potentially acting as intermediate- or high-risk variants in an oligogenic or polygenic context. Our results corroborate a major role of mTOR signalling pathway genes in the pathogenesis of NAFE and suggest that pathogenic CNVs might not only contribute to syndromic seizure disorders, but also to the common focal epilepsies.

P85: Sample size considerations in spinal cord injury research


Zimmermann G1,2,3, Kieser M4, Trinka E1, Bathke A3
1 Department of Neurology, Christian Doppler Clinic And Centre For Cognitive Neuroscience, Paracelsus Medical University, Salzburg
2 Spinal Cord Injury and Tissue Regeneration Centre Salzburg, Paracelsus Medical University, Salzburg
3 Department of Mathematics, Paris Lodron University, Salzburg
4 Institute of Medical Biometry and Informatics, University of Heidelberg, Germany

Introduction: Consider the situation of comparing two groups of patients (e.g., patients with spinal cord injury, who are randomly assigned to either standard treatment or a new therapeutic approach) with respect to a univariate outcome of interest (e.g., maximum detrusor pressure, or time needed to complete a walking test), adjusting for one or several covariates (e.g., baseline measurements such as age or time since injury). The analysis of covariance (ANCOVA) is a classical method, which allows adjusted group comparisons. In the planning phase of such a study, the calculation of the sample size that is required to achieve the target power (usually 80 percent) is a very important issue, as emphasized in various regulatory guidelines. However, especially in an early development stage (e.g., novel indication, preclinical experiment), there might be considerable uncertainty regarding the parameters that are required for sample size calculation (e.g., the variance). Erroneous initial specifications might lead to the inclusion of either too many or too few subjects, which is methodologically and ethically inappropriate. Therefore, allowing for a sample size adjustment at a particular time point during the study might be considered as an attractive alternative option to the fixed sample size calculation approach.
Materials and Methods: We conducted simulation studies for a particular sample size recalculation procedure and compared the results to various fixed calculation approaches in a broad range of small, moderate and large sample size scenarios with equal and unequal group allocation ratios. For each setting, we conducted 1,000,000 simulation runs. The performance of the different approaches was assessed by examining the type I error rates (i.e., the estimated probability of falsely claiming a group difference), power and final sample sizes. Moreover, we illus-trate the potential application of the methods under investigation by referring to a preclin-ical study in a rat model of spinal cord injury as well as to a clinical trial from stroke research.
Results: For scenarios where all initial pa-rameter specifications were correct (i.e., no uncertainty in the planning phase), the performance of the fixed sample size calculation approaches was similar to the recalculation procedure. However, when one of the parameters was misspecified (i.e., some uncertainty was present in the planning phase), the recalculation method still showed a good performance, with empirical power values close to the target 80 percent level, whereas the fixed sample size planning -approaches yielded substantially over- or underpowered results (e.g., the empirical power dropped below 40 percent in some settings). In all scenarios, the one-sided type I error level of 2.5 percent was well maintained. Moreover, under correct specification of all parameters, the sample sizes resulting from the recalculation procedure exceeded the fixed sample sizes by only 6 to 7 subjects on average, which was the “price to pay” for the increased flexibility due to the interim analysis.
Discussion and conclusion: Our proposed recalculation procedure allows for an interim reassessment of the initially calculated sample size and shows a good performance regardless whether uncertainty is present in the planning phase or not. By contrast, classical fixed sample size calculation ap-proaches are sensitive to deviations from the initial assumptions. Hence, especially in early development stages, our proposed method might serve as a safeguard against substantially over- or underpowered studies and is therefore recommended for ethical and methodological reasons. We would like to emphasize that the recalculation procedure is not only applicable in research on rare neurological diseases, but also in virtually any treatment group comparison setting. More-over, the proposed approach does not require unblinding of the treatment allocation and thus meets a key regulatory requirement. However, further research is still warranted, in order to extend our proposed method to other settings that are of high relevance in neurology.