Suitability of Automated Writing Measures for Clinical Trial Outcome in Writer's Cramp.

BACKGROUND: Writer's cramp (WC) dystonia is a rare disease that causes abnormal postures during the writing task. Successful research studies for WC and other forms of dystonia are contingent on identifying sensitive and specific measures that relate to the clinical syndrome and achieve a realistic sample size to power research studies for a rare disease. Although prior studies have used writing kinematics, their diagnostic performance remains unclear. OBJECTIVE: This study aimed to evaluate the diagnostic performance of automated measures that distinguish subjects with WC from healthy volunteers. METHODS: A total of 21 subjects with WC and 22 healthy volunteers performed a sentence-copying assessment on a digital tablet using kinematic and hand recognition softwares. The sensitivity and specificity of automated measures were calculated using a logistic regression model. Power analysis was performed for two clinical research designs using these measures. The test and retest reliability of select automated measures was compared across repeat sentence-copying assessments. Lastly, a correlational analysis with subject- and clinician-rated outcomes was performed to understand the clinical meaning of automated measures. RESULTS: Of the 23 measures analyzed, the measures of word legibility and peak accelerations distinguished subjects with WC from healthy volunteers with high sensitivity and specificity and demonstrated smaller sample sizes suitable for rare disease studies, and the kinematic measures showed high reliability across repeat visits, while both word legibility and peak accelerations measures showed significant correlations with the subject- and clinician-rated outcomes. CONCLUSIONS: Novel automated measures that capture key aspects of the disease and are suitable for use in clinical research studies of WC dystonia were identified. © 2022 International Parkinson and Movement Disorder Society.

The Duke Myasthenia Gravis Clinic Registry: II. Analysis of outcomes.

INTRODUCTION/AIMS: The Duke Myasthenia Gravis (MG) Clinic Registry contains comprehensive physician-derived data on patients with MG seen in the Duke MG Clinic since 1980. The aim of this study was to report outcomes in patients seen in the clinic and treated according to the International Consensus Guidance statements. METHODS: This is a retrospective cohort study of patients initially seen after 2000 and followed for at least 2 years in the clinic. Treatment goal (TG) was defined as achieving MGFA post-intervention status of "minimal manifestations" or better; PIS was determined by the treating neurologist. Time-to-event analysis, including Cox proportional hazards modeling, was performed to assess the effect of sex, acetylcholine receptor antibody (AChR-Ab) status, age at disease onset, distribution (ocular vs generalized), thymectomy, and thymoma on the time to achieve TG. RESULTS: Among the 367 cohort patients, 72% achieved TG (median time less than 2 years). A greater proportion of patients with AChR-Abs and thymectomy achieved TG and they did so sooner than patients without these antibodies or thymectomy. Otherwise, there were no significant differences in these findings within the tested subgroups. The disease duration at the first Duke Clinic visit was shorter in patients who achieved TG than in those who did not. DISCUSSION: These results demonstrate outcomes that can be achieved in patients with MG treated according to the current Consensus Guidance statements. Among other things, they can be used to determine the added value and potential role of new treatment modalities developed since 2018.

Bioinformatics pipeline to guide post-GWAS studies in Alzheimer's: A new catalogue of disease candidate short structural variants.

BACKGROUND: Short structural variants (SSVs), including insertions/deletions (indels), are common in the human genome and impact disease risk. The role of SSVs in late-onset Alzheimer's disease (LOAD) has been understudied. In this study, we developed a bioinformatics pipeline of SSVs within LOAD-genome-wide association study (GWAS) regions to prioritize regulatory SSVs based on the strength of their predicted effect on transcription factor (TF) binding sites. METHODS: The pipeline utilized publicly available functional genomics data sources including candidate cis-regulatory elements (cCREs) from ENCODE and single-nucleus (sn)RNA-seq data from LOAD patient samples. RESULTS: We catalogued 1581 SSVs in candidate cCREs in LOAD GWAS regions that disrupted 737 TF sites. That included SSVs that disrupted the binding of RUNX3, SPI1, and SMAD3, within the APOE-TOMM40, SPI1, and MS4A6A LOAD regions. CONCLUSIONS: The pipeline developed here prioritized non-coding SSVs in cCREs and characterized their putative effects on TF binding. The approach integrates multiomics datasets for validation experiments using disease models.

A Bayesian perspective on Biogen's aducanumab trial.

This perspective is a companion to a recent editorial on the use of Bayesian analysis in clinical research. We aim to introduce and highlight the relevance and advantages that Bayesian inference offers to clinical trials using the data on the amyloid antibody aducanumab presented at a Food and Drug Administration hearing in November 2020 as an applied example. We apply Bayesian analysis of model plausibility and effect sizes based on simulated data of the two phase 3 trials of aducanumab in prodromal and mild dementia stages of Alzheimer's disease (AD). Bayesian analysis can quantify evidence in favor of, or against, the presence of an effect (i.e., provide evidence of absence), as well as assess the strength of the effect. This is in contrast to the binary conclusions provided by frequentist tests.

Clinical research in dementia: A perspective on implementing innovation.

The increasing global prevalence of dementia demands concrete actions that are aimed strategically at optimizing processes that drive clinical innovation. The first step in this direction requires outlining hurdles in the transition from research to practice. The different parties needed to support translational processes have communication mismatches; methodological gaps hamper evidence-based decision-making; and data are insufficient to provide reliable estimates of long-term health benefits and costs in decisional models. Pilot projects are tackling some of these gaps, but appropriate methods often still need to be devised or adapted to the dementia field. A consistent implementation perspective along the whole translational continuum, explicitly defined and shared among the relevant stakeholders, should overcome the "research-versus-adoption" dichotomy, and tackle the implementation cliff early on. Concrete next steps may consist of providing tools that support the effective participation of heterogeneous stakeholders and agreeing on a definition of clinical significance that facilitates the selection of proper outcome measures.

TOMM40-APOE haplotypes are associated with cognitive decline in non-demented Blacks.

INTRODUCTION: The goal was to investigate effects of APOE-TOMM40-'523 haplotypes on cognitive decline in non-demented non-Hispanic Blacks (NHB), and determine whether effects differ from non-Hispanic Whites (NHW). METHODS: The impact of zero to two copies of the '523-Short variant (S; poly-T alleles < 20) within apolipoprotein E (APOE) genotype on a composite measure of global cognition and five domains was examined. RESULTS: In NHB with ε3/ε3 (N = 294), '523-S/S was associated with faster decline in global cognition (ß = -0.048, P = 0.017), episodic memory (ß = -0.05, P = 0.031), and visuospatial ability (ß = -0.037, P = 0.034) relative to those without '523-S. For NHB ε4+ (N = 182), '523-S/S had slower decline in global cognition (ß = 0.047, P = 0.042) and visuospatial ability (ß = 0.07, P = 0.0005) relative to '523-S non-carriers. NHB ε4+ with '523-S also had a slower rate of decline than NHWs ε4+ with '523-S. DISCUSSION: '523-S/S has a different effect on cognitive decline among NHB dependent on APOE allele. Differences in the effect of ε4-'523-S in NHB may explain prior mixed findings on ε4 and decline in this population.

Likelihood ratio statistics for gene set enrichment in Alzheimer's disease pathways.

INTRODUCTION: The study of Alzheimer's disease (AD) has revealed biological pathways with implications for disease neuropathology and pathophysiology. These pathway-level effects may also be mediated by individual characteristics or covariates such as age or sex. Evaluation of AD biological pathways in the context of interactions with these covariates is critical to the understanding of AD as well as the development of model systems used to study the disease. METHODS: Gene set enrichment methods are powerful tools used to interpret gene-level statistics at the level of biological pathways. We introduce a method for quantifying gene set enrichment using likelihood ratio-derived test statistics (gsLRT), which accounts for sample covariates like age and sex. We then use our method to test for age and sex interactions with protein expression levels in AD and to compare the pathway results between human and mouse species. RESULTS: Our method, based on nested logistic regressions is competitive with the existing standard for gene set testing in the context of linear models and complex experimental design. The gene sets we identify as having a significant association with AD-both with and without additional covariate interactions-are validated by previous studies. Differences between gsLRT results on mouse and human datasets are observed. DISCUSSION: Characterizing biological pathways involved in AD builds on the important work involving single gene drivers. Our gene set enrichment method finds pathways that are significantly related to AD while accounting for covariates that may be relevant to disease development. The method highlights commonalities and differences between human AD and mouse models, which may inform the development of higher fidelity models for the study of AD.

A Triage Model for Interhospital Transfers of Low Risk Intracerebral Hemorrhage Patients.

OBJECTIVES: Intracerebral hemorrhage comprises a large proportion of inter-hospital transfers to comprehensive stroke centers from centers without comprehensive stroke center resources despite lack of mortality benefit and low comprehensive stroke center resource utilization. The subset of patients who derive the most benefit from inter-hospital transfers is unclear. Here, we create a triage model to identify patients who can safely avoid transfer to a comprehensive stroke center. MATERIALS AND METHODS: A retrospective cohort of spontaneous intracerebral hemorrhage patients transferred to our comprehensive stroke center from surrounding centers was used. Patients with early discharge from the Neuroscience Intensive Care Unit without use of comprehensive stroke center resources were identified as low risk, non-utilizers. Variables associated with this designation were used to develop and validate a triage model. RESULTS: The development and replication cohorts comprised 358 and 99 patients respectively, of whom 78 (22%) and 26 (26%) were low risk, non-utilizers. Initial Glasgow Coma Scale and baseline hemorrhage volume were associated with low risk, non-utilizers in multivariate analysis. Initial Glasgow Coma Scale >13, intracerebral hemorrhage volume <15ml, absence of intraventricular hemorrhage, and supratentorial location had an area under curve, specificity, and sensitivity of 0.72, 91.4%, 52.6%, respectively, for identifying low risk, non-utilizers, and 0.75, 84.9%, 65.4%, respectively, in the replication cohort. CONCLUSIONS: Spontaneous intracerebral hemorrhage patients with Glasgow Coma Scale >13, intracerebral hemorrhage volume <15 ml, absence of intraventricular hemorrhage, and supratentorial location might safely avoid inter-hospital transfer to a comprehensive stroke center. Validation in a prospective, multicenter cohort is warranted.

The association between neighborhood socioeconomic status, cardiovascular and cerebrovascular risk factors, and cognitive decline in the Health and Retirement Study (HRS).

Background: A small but growing body of evidence supports a relationship between neighborhood socioeconomic status (NSES) and cognitive decline. Additional work is needed to characterize this relationship controlling for risk factors such as cardiovascular, cerebrovascular, and genetic risk factors.Methods: Cognitive decline was assessed in association with NSES, and cardiovascular and cerebrovascular risk factors (heart disease, diabetes, hypertension, and stroke) in 8,198 individuals from the 1992-2010 waves of the Health and Retirement Study (HRS). Latent class trajectory analysis determined the number of cognitive trajectory classes that best fit the data, and a multinomial logistic regression model in the latent class framework assessed the risk for cognitive classes conferred by NSES index score and heart disease, diabetes, hypertension, and stroke across three trajectory classes of cognitive function. The analyses controlled for genetic risk for cognitive decline (including APOE genotype) and demographic variables, including education.Results: The HRS sample was 57.6% female and 85.5% White, with a mean age of 67.5(3.5) years at baseline. The three-quadratic-class model best fit the data, where higher classes represented better cognitive function. Those with better cognitive function were mainly younger white females. Those in the highest quartile of NSES had 57% higher odds of being in the high cognitive function class. Heart disease, diabetes, hypertension, and stroke each increased the odds having of lower cognitive function.Conclusions: In examining the relationship of cognitive status with various variables, neighborhood socioeconomic status, cardiovascular risk, and cerebrovascular risk persisted across the cognitive trajectory classes.

Shared genetic etiology underlying late-onset Alzheimer's disease and posttraumatic stress syndrome.

INTRODUCTION: Late-onset Alzheimer's disease (LOAD) manifests comorbid neuropsychiatric symptoms and posttraumatic stress disorder (PTSD) is associated with an increased risk for dementia in late life, suggesting the two disorders may share genetic etiologies. METHODS: We performed genetic pleiotropy analysis using LOAD and PTSD genome-wide association study (GWAS) datasets from white and African-American populations, followed by functional-genomic analyses. RESULTS: We found an enrichment for LOAD across increasingly stringent levels of significance with the PTSD GWAS association (LOAD|PTSD) in the discovery and replication cohorts and a modest enrichment for the reverse conditional association (PTSD|LOAD). LOAD|PTSD association analysis identified and replicated the MS4A genes region. These genes showed similar expression pattern in brain regions affected in LOAD, and across-brain-tissue analysis identified a significant association for MS4A6A. The African-American samples showed moderate enrichment; however, no false discovery rate-significant associations. DISCUSSION: We demonstrated common genetic signatures for LOAD and PTSD and suggested immune response as a common pathway for these diseases.

A systems-based model of Alzheimer's disease.

The new National Institute on Aging and the Alzheimer's Association Research Framework for Alzheimer's disease has been developed to accelerate drug discovery and offer a common structure and language to construct new Alzheimer's disease conceptual models. However, as a "complex" disease, a model based on systems-level understanding is needed to accommodate the complex, interacting etiologic pathways and the system-level changes associated with Alzheimer's disease pathogenesis and interventions that are currently known and which will be identified in the future. To accomplish this, the evolution of the structure of the research framework itself should be encouraged.

Bioinformatics strategy to advance the interpretation of Alzheimer's disease GWAS discoveries: The roads from association to causation.

INTRODUCTION: Genome-wide association studies (GWAS) discovered multiple late-onset Alzheimer's disease (LOAD)-associated SNPs and inferred the genes based on proximity; however, the actual causal genes are yet to be identified. METHODS: We defined LOAD-GWAS regions by the most significantly associated SNP ±0.5 Mb and developed a bioinformatics pipeline that uses and integrates chromatin state segmentation track to map active enhancers and virtual 4C software to visualize interactions between active enhancers and gene promoters. We augmented our pipeline with biomedical and functional information. RESULTS: We applied the bioinformatics pipeline using three ∼1 Mb LOAD-GWAS loci: BIN1, PICALM, CELF1. These loci contain 10-24 genes, an average of 106 active enhancers and 80 CTCF sites. Our strategy identified all genes corresponding to the promoters that interact with the active enhancer that is closest to the LOAD-GWAS-SNP and generated a shorter list of prioritized candidate LOAD genes (5-14/loci), feasible for post-GWAS investigations of causality. DISCUSSION: Interpretation of LOAD-GWAS discoveries requires the integration of brain-specific functional genomic data sets and information related to regulatory activity.

The effects of the TOMM40 poly-T alleles on Alzheimer's disease phenotypes.

The TOMM40 poly-T is a polymorphism in intron 6 of the TOMM40 gene, which is adjacent to and in linkage disequilibrium with APOE. Roses et al. identified the association between the length of TOMM40 poly-T with the risk and age of onset of late-onset Alzheimer's disease (LOAD). Following the original discovery, additional studies found associations between the TOMM40 poly-T and LOAD-related phenotypes independent of APOE genotypes, while others did not replicate these associations. Furthermore, the identity of the TOMM40 poly-T risk allele has been controversial between different LOAD-related phenotypes. Here, we propose a framework to address the conflicting findings with respect to the TOMM40 poly-T allele associations with LOAD phenotypes and their functional effects. The framework is used to interpret previous studies as means to gain insights regarding the nature of the risk allele, very long versus short. We suggest that the identity of the TOMM40 poly-T risk allele depends on the phenotype being evaluated, the ages of the study subjects at the time of assessment, and the context of the APOE genotypes. In concluding remarks, we outline future studies that will inform the mechanistic interpretation of the genetic data.

Neighborhoods, sleep quality, and cognitive decline: Does where you live and how well you sleep matter?

INTRODUCTION: We evaluated the association between neighborhood socioeconomic status (NSES) and sleep quality on cognitive decline in the Health and Retirement Study. METHODS: Health and Retirement Study participants (n = 8090), aged 65+ with DNA and multiple biennial cognitive observations (abbreviated Telephone Interview for Cognitive Status), were included. Participants were grouped into quartiles of NSES and sleep quality scores. We adjusted for apolipoprotein E ε4, demographic, and cardiovascular risk factors. Random effects modeling evaluated cognitive change over time. RESULTS: NSES and sleep were significantly associated with cognitive decline, and there was a significant interaction between them (P = .02). Significant differences between high/low NSES and high/low sleep quality (P < .0001) were found. DISCUSSION: Sleep and NSES were associated with cognitive decline; the association between sleep and cognition appeared stronger among those with low NSES. The association between low NSES, poor sleep quality, and cognitive decline was roughly equivalent to the association between apolipoprotein E ε4 and cognitive decline.

The Alu neurodegeneration hypothesis: A primate-specific mechanism for neuronal transcription noise, mitochondrial dysfunction, and manifestation of neurodegenerative disease.

It is hypothesized that retrotransposons have played a fundamental role in primate evolution and that enhanced neurologic retrotransposon activity in humans may underlie the origin of higher cognitive function. As a potential consequence of this enhanced activity, it is likely that neurons are susceptible to deleterious retrotransposon pathways that can disrupt mitochondrial function. An example is observed in the TOMM40 gene, encoding a ß-barrel protein critical for mitochondrial preprotein transport. Primate-specific Alu retrotransposons have repeatedly inserted into TOMM40 introns, and at least one variant associated with late-onset Alzheimer's disease originated from an Alu insertion event. We provide evidence of enriched Alu content in mitochondrial genes and postulate that Alus can disrupt mitochondrial populations in neurons, thereby setting the stage for progressive neurologic dysfunction. This Alu neurodegeneration hypothesis is compatible with decades of research and offers a plausible mechanism for the disruption of neuronal mitochondrial homeostasis, ultimately cascading into neurodegenerative disease.

Genetic analysis of α-synuclein 3' untranslated region and its corresponding microRNAs in relation to Parkinson's disease compared to dementia with Lewy bodies.

INTRODUCTION: The α-synuclein (SNCA) gene has been implicated in the etiology of Parkinson's disease (PD) and dementia with Lewy bodies (DLB). METHODS: A computational analysis of SNCA 3' untranslated region to identify potential microRNA (miRNA) binding sites and quantitative real-time polymerase chain reaction (PCR) to determine their expression in isogenic induced pluripotent stem cell-derived dopaminergic and cholinergic neurons as a model of PD and DLB, respectively, were performed. In addition, we performed a deep sequencing analysis of the SNCA 3' untranslated region of autopsy-confirmed cases of PD, DLB, and normal controls, followed by genetic association analysis of the identified variants. RESULTS: We identified four miRNA binding sites and observed a neuronal-type-specific expression profile for each miRNA in the different isogenic induced pluripotent stem cell-derived dopaminergic and cholinergic neurons. Furthermore, we found that the short structural variant rs777296100-polyT was moderately associated with DLB but not with PD. DISCUSSION: We suggest that the regulation of SNCA expression through miRNAs is neuronal-type-specific and possibly plays a part in the phenotypic heterogeneity of synucleinopathies. Furthermore, genetic variability in the SNCA gene may contribute to synucleinopathies in a pathology-specific manner.

Family history and TOMM40 '523 interactive associations with memory in middle-aged and Alzheimer's disease cohorts.

INTRODUCTION: Family history (FH) of Alzheimer's disease (AD) affects mitochondrial function and may modulate effects of translocase of the outer mitochondrial membrane 40 kDa (TOMM40) rs10524523 ('523) poly-T length on memory decline. METHODS: For 912 nonapolipoprotein ε4 middle-aged adults and 365 aged adults across the AD spectrum, linear mixed models gauged FH and TOMM40 '523 interactions on memory and global cognition between baseline and up to 10 years later. A cerebrospinal fluid mitochondrial function biomarker was also assessed. RESULTS: For FH negative participants, gene-dose preservation of memory and global cognition was seen for "very long" versus "short" carriers. For FH positive, an opposite gene-dose decline was seen for very long versus short carriers. Maternal FH was a stronger predictor in aged, but not middle-aged, participants. Similar gene-dose effects were seen for the mitochondrial biomarker aspartate aminotransferase. DISCUSSION: These results may clarify conflicting findings on TOMM40 poly-T length and AD-related decline.

Neuropathologic features of TOMM40 '523 variant on late-life cognitive decline.

INTRODUCTION: The study investigated the role of neuropathologies in the relationship between TOMM40 '523 genotype and late-life cognitive decline. METHODS: Participants were community-dwelling older persons who had annual cognitive assessments and brain autopsies after death. Genotyping used DNA from peripheral blood or postmortem brain tissue. Linear mixed models assessed the extent to which the association of '523 genotype with cognitive decline is attributable to neuropathologies. RESULTS: Relative to ε3/ε3 homozygotes with '523-S/VL or '523-VL/VL genotype, both '523-L carriers and ε3/ε3 homozygotes with '523-S/S genotype had faster cognitive decline. The association of '523-L with cognitive decline was attenuated and no longer significant after controlling for Alzheimer's and other neuropathologies. By contrast, the association of '523-S/S was unchanged. DISCUSSION: There are two distinct TOMM40 '523 signals in relation to late-life cognitive decline. One signal primarily acts through AD and other common neuropathologies, whereas the other operates through a different mechanism.

The SSV Evaluation System: A Tool to Prioritize Short Structural Variants for Studies of Possible Regulatory and Causal Variants.

Short structural variants (SSVs) are short genomic variants (<50 bp) other than SNPs. It has been suggested that SSVs contribute to many human complex traits. However, high-throughput analysis of SSVs presents numerous technical challenges. In order to facilitate the discovery and assessment of SSVs, we have developed a prototype bioinformatics tool, "SSV evaluation system," which is a searchable, annotated database of SSVs in the human genome, with associated customizable scoring software that is used to evaluate and prioritize SSVs that are most likely to have significant biological effects and impact on disease risk. This new bioinformatics tool is a component in a larger strategy that we have been using to discover potentially important SSVs within candidate genomic regions that have been identified in genome-wide association studies, with the goal to prioritize potential functional/causal SSVs and focus the follow-up experiments on a relatively small list of strong candidate SSVs. We describe our strategy and discuss how we have used the SSV evaluation system to discover candidate causal variants related to complex neurodegenerative diseases. We present the SSV evaluation system as a powerful tool to guide genetic investigations aiming to uncover SSVs that underlie human complex diseases including neurodegenerative diseases in aging.