Assessment of Mendelian and risk-factor genes in Alzheimer disease: A prospective nationwide clinical utility study and recommendations for genetic screening.

PURPOSE: To assess the likely pathogenic/pathogenic (LP/P) variants rates in Mendelian dementia genes and the moderate-to-strong risk factors rates in patients with Alzheimer disease (AD). METHODS: We included 700 patients in a prospective study and performed exome sequencing. A panel of 28 Mendelian and 6 risk-factor genes was interpreted and returned to patients. We built a framework for risk variant interpretation and risk gradation and assessed the detection rates among early-onset AD (EOAD, age of onset (AOO) ≤65 years, n = 608) depending on AOO and pedigree structure and late-onset AD (66 < AOO < 75, n = 92). RESULTS: Twenty-one patients carried a LP/P variant in a Mendelian gene (all with EOAD, 3.4%), 20 of 21 affected APP, PSEN1, or PSEN2. LP/P variant detection rates in EOAD ranged from 1.7% to 11.6% based on AOO and pedigree structure. Risk factors were found in 69.5% of the remaining 679 patients, including 83 (12.2%) being heterozygotes for rare risk variants, in decreasing order of frequency, in TREM2, ABCA7, ATP8B4, SORL1, and ABCA1, including 5 heterozygotes for multiple rare risk variants, suggesting non-monogenic inheritance, even in some autosomal-dominant-like pedigrees. CONCLUSION: We suggest that genetic screening should be proposed to all EOAD patients and should no longer be prioritized based on pedigree structure.

Penetrance estimation of Alzheimer disease in SORL1 loss-of-function variant carriers using a family-based strategy and stratification by APOE genotypes.

BACKGROUND: Alzheimer disease (AD) is a common complex disorder with a high genetic component. Loss-of-function (LoF) SORL1 variants are one of the strongest AD genetic risk factors. Estimating their age-related penetrance is essential before putative use for genetic counseling or preventive trials. However, relative rarity and co-occurrence with the main AD risk factor, APOE-ε4, make such estimations difficult. METHODS: We proposed to estimate the age-related penetrance of SORL1-LoF variants through a survival framework by estimating the conditional instantaneous risk combining (i) a baseline for non-carriers of SORL1-LoF variants, stratified by APOE-ε4, derived from the Rotterdam study (N = 12,255), and (ii) an age-dependent proportional hazard effect for SORL1-LoF variants estimated from 27 extended pedigrees (including 307 relatives ≥ 40 years old, 45 of them having genotyping information) recruited from the French reference center for young Alzheimer patients. We embedded this model into an expectation-maximization algorithm to accommodate for missing genotypes. To correct for ascertainment bias, proband phenotypes were omitted. Then, we assessed if our penetrance curves were concordant with age distributions of APOE-ε4-stratified SORL1-LoF variant carriers detected among sequencing data of 13,007 cases and 10,182 controls from European and American case-control study consortia. RESULTS: SORL1-LoF variants penetrance curves reached 100% (95% confidence interval [99-100%]) by age 70 among APOE-ε4ε4 carriers only, compared with 56% [40-72%] and 37% [26-51%] in ε4 heterozygous carriers and ε4 non-carriers, respectively. These estimates were fully consistent with observed age distributions of SORL1-LoF variant carriers in case-control study data. CONCLUSIONS: We conclude that SORL1-LoF variants should be interpreted in light of APOE genotypes for future clinical applications.

MYT1L-associated neurodevelopmental disorder: description of 40 new cases and literature review of clinical and molecular aspects.

Pathogenic variants of the myelin transcription factor-1 like (MYT1L) gene include heterozygous missense, truncating variants and 2p25.3 microdeletions and cause a syndromic neurodevelopmental disorder (OMIM#616,521). Despite enrichment in de novo mutations in several developmental disorders and autism studies, the data on clinical characteristics and genotype-phenotype correlations are scarce, with only 22 patients with single nucleotide pathogenic variants reported. We aimed to further characterize this disorder at both the clinical and molecular levels by gathering a large series of patients with MYT1L-associated neurodevelopmental disorder. We collected genetic information on 40 unreported patients with likely pathogenic/pathogenic MYT1L variants and performed a comprehensive review of published data (total = 62 patients). We confirm that the main phenotypic features of the MYT1L-related disorder are developmental delay with language delay (95%), intellectual disability (ID, 70%), overweight or obesity (58%), behavioral disorders (98%) and epilepsy (23%). We highlight novel clinical characteristics, such as learning disabilities without ID (30%) and feeding difficulties during infancy (18%). We further describe the varied dysmorphic features (67%) and present the changes in weight over time of 27 patients. We show that patients harboring highly clustered missense variants in the 2-3-ZNF domains are not clinically distinguishable from patients with truncating variants. We provide an updated overview of clinical and genetic data of the MYT1L-associated neurodevelopmental disorder, hence improving diagnosis and clinical management of these patients.

Impaired SorLA maturation and trafficking as a new mechanism for SORL1 missense variants in Alzheimer disease.

The SorLA protein, encoded by the SORL1 gene, is a major player in Alzheimer's disease (AD) pathophysiology. Functional and genetic studies demonstrated that SorLA deficiency results in increased production of Aß peptides, and thus a higher risk of AD. A large number of SORL1 missense variants have been identified in AD patients, but their functional consequences remain largely undefined. Here, we identified a new pathophysiological mechanism, by which rare SORL1 missense variants identified in AD patients result in altered maturation and trafficking of the SorLA protein. An initial screening, based on the overexpression of 70 SorLA variants in HEK293 cells, revealed that 15 of them (S114R, R332W, G543E, S564G, S577P, R654W, R729W, D806N, Y934C, D1535N, D1545E, P1654L, Y1816C, W1862C, P1914S) induced a maturation and trafficking-deficient phenotype. Three of these variants (R332W, S577P, and R654W) and two maturation-competent variants (S124R and N371T) were further studied in details in CRISPR/Cas9-modified hiPSCs. When expressed at endogenous levels, the R332W, S577P, and R654W SorLA variants also showed a maturation defective profile. We further demonstrated that these variants were largely retained in the endoplasmic reticulum, resulting in a reduction in the delivery of SorLA mature protein to the plasma membrane and to the endosomal system. Importantly, expression of the R332W and R654W variants in hiPSCs was associated with a clear increase of Aß secretion, demonstrating a loss-of-function effect of these SorLA variants regarding this ultimate readout, and a direct link with AD pathophysiology. Furthermore, structural analysis of the impact of missense variants on SorLA protein suggested that impaired cellular trafficking of SorLA protein could be due to subtle variations of the protein 3D structure resulting from changes in the interatomic interactions.

Effects of eight neuropsychiatric copy number variants on human brain structure.

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen's d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions.

Clinical and neuropathological diversity of tauopathy in MAPT duplication carriers.

Microduplications of the 17q21.31 chromosomal region encompassing the MAPT gene, which encodes the Tau protein, were identified in patients with a progressive disorder initially characterized by severe memory impairment with or without behavioral changes that can clinically mimic Alzheimer disease. The unique neuropathological report showed a primary tauopathy, which could not be unanimously classified in a given known subtype, showing both 4R- and 3R-tau inclusions, mainly within temporal cortical subregions and basal ganglia, without amyloid deposits. Recently, two subjects harboring the same duplication were reported with an atypical extrapyramidal syndrome and gait disorder. To decipher the phenotypic spectrum associated with MAPT duplications, we studied ten carriers from nine families, including two novel unrelated probands, gathering clinical (n = 10), cerebrospinal fluid (n = 6), MRI (n = 8), dopamine transporter scan (n = 4), functional (n = 5), amyloid (n = 3) and Tau-tracer (n = 2) PET imaging data as well as neuropathological examination (n = 4). Ages at onset ranged from 37 to 57 years, with prominent episodic memory impairment in 8/10 patients, associated with behavioral changes in four, while two patients showed atypical extrapyramidal syndrome with gait disorder at presentation, including one with associated cognitive deficits. Amyloid imaging was negative but Tau imaging showed significant deposits mainly in both mesiotemporal cortex. Dopaminergic denervation was found in 4/4 patients, including three without extrapyramidal symptoms. Neuropathological examination exclusively showed Tau-immunoreactive lesions. Distribution, aspect and 4R/3R tau aggregates composition suggested a spectrum from predominantly 3R, mainly cortical deposits well correlating with cognitive and behavioral changes, to predominantly 4R deposits, mainly in the basal ganglia and midbrain, in patients with prominent extrapyramidal syndrome. Finally, we performed in vitro seeding experiments in HEK-biosensor cells. Morphological features of aggregates induced by homogenates of three MAPT duplication carriers showed dense/granular ratios graduating between those induced by homogenates of a Pick disease and a progressive supranuclear palsy cases. These results suggest that MAPT duplication causes a primary tauopathy associated with diverse clinical and neuropathological features.

Genome-wide analysis of gene dosage in 24,092 individuals estimates that 10,000 genes modulate cognitive ability.

Genomic copy number variants (CNVs) are routinely identified and reported back to patients with neuropsychiatric disorders, but their quantitative effects on essential traits such as cognitive ability are poorly documented. We have recently shown that the effect size of deletions on cognitive ability can be statistically predicted using measures of intolerance to haploinsufficiency. However, the effect sizes of duplications remain unknown. It is also unknown if the effect of multigenic CNVs are driven by a few genes intolerant to haploinsufficiency or distributed across tolerant genes as well. Here, we identified all CNVs > 50 kilobases in 24,092 individuals from unselected and autism cohorts with assessments of general intelligence. Statistical models used measures of intolerance to haploinsufficiency of genes included in CNVs to predict their effect size on intelligence. Intolerant genes decrease general intelligence by 0.8 and 2.6 points of intelligence quotient when duplicated or deleted, respectively. Effect sizes showed no heterogeneity across cohorts. Validation analyses demonstrated that models could predict CNV effect sizes with 78% accuracy. Data on the inheritance of 27,766 CNVs showed that deletions and duplications with the same effect size on intelligence occur de novo at the same frequency. We estimated that around 10,000 intolerant and tolerant genes negatively affect intelligence when deleted, and less than 2% have large effect sizes. Genes encompassed in CNVs were not enriched in any GOterms but gene regulation and brain expression were GOterms overrepresented in the intolerant subgroup. Such pervasive effects on cognition may be related to emergent properties of the genome not restricted to a limited number of biological pathways.

Effect Sizes of Deletions and Duplications on Autism Risk Across the Genome.

OBJECTIVE: Deleterious copy number variants (CNVs) are identified in up to 20% of individuals with autism. However, levels of autism risk conferred by most rare CNVs remain unknown. The authors recently developed statistical models to estimate the effect size on IQ of all CNVs, including undocumented ones. In this study, the authors extended this model to autism susceptibility. METHODS: The authors identified CNVs in two autism populations (Simons Simplex Collection and MSSNG) and two unselected populations (IMAGEN and Saguenay Youth Study). Statistical models were used to test nine quantitative variables associated with genes encompassed in CNVs to explain their effects on IQ, autism susceptibility, and behavioral domains. RESULTS: The "probability of being loss-of-function intolerant" (pLI) best explains the effect of CNVs on IQ and autism risk. Deleting 1 point of pLI decreases IQ by 2.6 points in autism and unselected populations. The effect of duplications on IQ is threefold smaller. Autism susceptibility increases when deleting or duplicating any point of pLI. This is true for individuals with high or low IQ and after removing de novo and known recurrent neuropsychiatric CNVs. When CNV effects on IQ are accounted for, autism susceptibility remains mostly unchanged for duplications but decreases for deletions. Model estimates for autism risk overlap with previously published observations. Deletions and duplications differentially affect social communication, behavior, and phonological memory, whereas both equally affect motor skills. CONCLUSIONS: Autism risk conferred by duplications is less influenced by IQ compared with deletions. The model applied in this study, trained on CNVs encompassing >4,500 genes, suggests highly polygenic properties of gene dosage with respect to autism risk and IQ loss. These models will help to interpret CNVs identified in the clinic.

Mutations associated with neuropsychiatric conditions delineate functional brain connectivity dimensions contributing to autism and schizophrenia.

16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear. Here we report an analysis of resting-state FC using magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We characterize CNV FC-signatures and use them to identify dimensions contributing to complex idiopathic conditions. CNVs have large mirror effects on FC at the global and regional level. Thalamus, somatomotor, and posterior insula regions play a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibit worse cognitive and behavioral symptoms. Deletion similarities identified at the connectivity level could be related to the redundant associations observed genome-wide between gene expression spatial patterns and FC-signatures. Results may explain why many CNVs affect a similar range of neuropsychiatric symptoms.

Estimating the effects of copy-number variants on intelligence using hierarchical Bayesian models.

It is challenging to estimate the phenotypic impact of the structural genome changes known as copy-number variations (CNVs), since there are many unique CNVs which are nonrecurrent, and most are too rare to be studied individually. In recent work, we found that CNV-aggregated genomic annotations, that is, specifically the intolerance to mutation as measured by the pLI score (probability of being loss-of-function intolerant), can be strong predictors of intellectual quotient (IQ) loss. However, this aggregation method only estimates the individual CNV effects indirectly. Here, we propose the use of hierarchical Bayesian models to directly estimate individual effects of rare CNVs on measures of intelligence. Annotation information on the impact of major mutations in genomic regions is extracted from genomic databases and used to define prior information for the approach we call HBIQ. We applied HBIQ to the analysis of CNV deletions and duplications from three datasets and identified several genomic regions containing CNVs demonstrating significant deleterious effects on IQ, some of which validate previously known associations. We also show that several CNVs were identified as deleterious by HBIQ even if they have a zero pLI score, and the converse is also true. Furthermore, we show that our new model yields higher out-of-sample concordance (78%) for predicting the consequences of carrying known recurrent CNVs compared with our previous approach.

Combining Whole-Genome Sequencing and Multimodel Phenotyping To Identify Genetic Predictors of Salmonella Virulence.

Salmonella comprises more than 2,600 serovars. Very few environmental and uncommon serovars have been characterized for their potential role in virulence and human infections. A complementary in vitro and in vivo systematic high-throughput analysis of virulence was used to elucidate the association between genetic and phenotypic variations across Salmonella isolates. The goal was to develop a strategy for the classification of isolates as a benchmark and predict virulence levels of isolates. Thirty-five phylogenetically distant strains of unknown virulence were selected from the Salmonella Foodborne Syst-OMICS (SalFoS) collection, representing 34 different serovars isolated from various sources. Isolates were evaluated for virulence in 4 complementary models of infection to compare virulence traits with the genomics data, including interactions with human intestinal epithelial cells, human macrophages, and amoeba. In vivo testing was conducted using the mouse model of Salmonella systemic infection. Significant correlations were identified between the different models. We identified a collection of novel hypothetical and conserved proteins associated with isolates that generate a high burden. We also showed that blind prediction of virulence of 33 additional strains based on the pan-genome was high in the mouse model of systemic infection (82% agreement) and in the human epithelial cell model (74% agreement). These complementary approaches enabled us to define virulence potential in different isolates and present a novel strategy for risk assessment of specific strains and for better monitoring and source tracking during outbreaks.IMPORTANCESalmonella species are bacteria that are a major source of foodborne disease through contamination of a diversity of foods, including meat, eggs, fruits, nuts, and vegetables. More than 2,600 different Salmonella enterica serovars have been identified, and only a few of them are associated with illness in humans. Despite the fact that they are genetically closely related, there is enormous variation in the virulence of different isolates of Salmonella enterica Identification of foodborne pathogens is a lengthy process based on microbiological, biochemical, and immunological methods. Here, we worked toward new ways of integrating whole-genome sequencing (WGS) approaches into food safety practices. We used WGS to build associations between virulence and genetic diversity within 83 Salmonella isolates representing 77 different Salmonella serovars. Our work demonstrates the potential of combining a genomics approach and virulence tests to improve the diagnostics and assess risk of human illness associated with specific Salmonella isolates.

Dysregulation of peripheral expression of the YWHA genes during conversion to psychosis.

The seven human 14-3-3 proteins are encoded by the YWHA-gene family. They are expressed in the brain where they play multiple roles including the modulation of synaptic plasticity and neuronal development. Previous studies have provided arguments for their involvement in schizophrenia, but their role during disease onset is unknown. We explored the peripheral-blood expression level of the seven YWHA genes in 92 young individuals at ultra-high risk for psychosis (UHR). During the study, 36 participants converted to psychosis (converters) while 56 did not (non-converters). YWHA genes expression was evaluated at baseline and after a mean follow-up of 10.3 months using multiplex quantitative PCR. Compared with non-converters, the converters had a significantly higher baseline expression levels for 5 YWHA family genes, and significantly different longitudinal changes in the expression of YWHAE, YWHAG, YWHAH, YWHAS and YWAHZ. A principal-component analysis also indicated that the YWHA expression was significantly different between converters and non-converters suggesting a dysregulation of the YWHA co-expression network. Although these results were obtained from peripheral blood which indirectly reflects brain chemistry, they indicate that this gene family may play a role in psychosis onset, opening the way to the identification of prognostic biomarkers or new drug targets.

How to analyze and interpret recurrent events data in the presence of a terminal event: An application on readmission after colorectal cancer surgery.

Recurrent events arise when an event occurs many times for a subject. Many models have been developed to analyze these kind of data: the Andersen-Gill's model is one of them as well as the Prentice-William and the Peterson's model, the Wei Lee and Weissfeld's model, or even frailty models, all assuming an independent and noninformative censoring. However, in practice, these assumptions may be violated by the existence of a terminal event that permanently stops the recurrent process (eg, death). Indeed, a patient who experiences an early terminal event is more likely to have a lower number of recurrent events than a patient who experiences a terminal event later. Thus, ignoring terminal events in the analysis may lead to biased results. Many methods have been developed to handle terminal events. In this paper, we describe the existing methods classifying into conditional or marginal methods and compare them in a simulation study to highlight bias in results if an inappropriate method is used, when recurrent events and terminal event are correlated. In addition, we apply the different models on a real dataset to show how results should be interpreted. Finally, we provide recommendations for choosing the appropriate method for analyzing recurrent events in the presence of a terminal event.

The role of the striatum in linguistic selection: Evidence from Huntington's disease and computational modeling.

Though accumulating evidence indicates that the striatum is recruited during language processing, the specific function of this subcortical structure in language remains to be elucidated. To answer this question, we used Huntington's disease as a model of striatal lesion. We investigated the morphological deficit of 30 early Huntington's disease patients with a novel linguistic task that can be modeled within an explicit theory of linguistic computation. Behavioral results reflected an impairment in HD patients on the linguistic task. Computational model-based analysis compared the behavioral data to simulated data from two distinct lesion models, a selection deficit model and a grammatical deficit model. This analysis revealed that the impairment derives from an increased randomness in the process of selecting between grammatical alternatives, rather than from a disruption of grammatical knowledge per se. Voxel-based morphometry permitted to correlate this impairment to dorsal striatal degeneration. We thus show that the striatum holds a role in the selection of linguistic alternatives, just as in the selection of motor and cognitive programs.

Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples.

Importance;: Copy number variants (CNVs) classified as pathogenic are identified in 10% to 15% of patients referred for neurodevelopmental disorders. However, their effect sizes on cognitive traits measured as a continuum remain mostly unknown because most of them are too rare to be studied individually using association studies. Objective: To measure and estimate the effect sizes of recurrent and nonrecurrent CNVs on IQ. Design, Setting, and Participants: This study identified all CNVs that were 50 kilobases (kb) or larger in 2 general population cohorts (the IMAGEN project and the Saguenay Youth Study) with measures of IQ. Linear regressions, including functional annotations of genes included in CNVs, were used to identify features to explain their association with IQ. Validation was performed using intraclass correlation that compared IQ estimated by the model with empirical data. Main Outcomes and Measures: Performance IQ (PIQ), verbal IQ (VIQ), and frequency of de novo CNV events. Results: The study included 2090 European adolescents from the IMAGEN study and 1983 children and parents from the Saguenay Youth Study. Of these, genotyping was performed on 1804 individuals from IMAGEN and 977 adolescents, 445 mothers, and 448 fathers (484 families) from the Saguenay Youth Study. We observed 4928 autosomal CNVs larger than 50 kb across both cohorts. For rare deletions, size, number of genes, and exons affect IQ, and each deleted gene is associated with a mean (SE) decrease in PIQ of 0.67 (0.19) points (P = 6 × 10-4); this is not so for rare duplications and frequent CNVs. Among 10 functional annotations, haploinsufficiency scores best explain the association of any deletions with PIQ with a mean (SE) decrease of 2.74 (0.68) points per unit of the probability of being loss-of-function intolerant (P = 8 × 10-5). Results are consistent across cohorts and unaffected by sensitivity analyses removing pathogenic CNVs. There is a 0.75 concordance (95% CI, 0.39-0.91) between the effect size on IQ estimated by our model and IQ loss calculated in previous studies of 15 recurrent CNVs. There is a close association between effect size on IQ and the frequency at which deletions occur de novo (odds ratio, 0.86; 95% CI, 0.84-0.87; P = 2.7 × 10-88). There is a 0.76 concordance (95% CI, 0.41-0.91) between de novo frequency estimated by the model and calculated using data from the DECIPHER database. Conclusions and Relevance: Models trained on nonpathogenic deletions in the general population reliably estimate the effect size of pathogenic deletions and suggest omnigenic associations of haploinsufficiency with IQ. This represents a new framework to study variants too rare to perform individual association studies and can help estimate the cognitive effect of undocumented deletions in the neurodevelopmental clinic.

Clustering of longitudinal data by using an extended baseline: A new method for treatment efficacy clustering in longitudinal data.

Heterogeneity in treatment efficacy is a major concern in clinical trials. Clustering may help to identify the treatment responders and the non-responders. In the context of longitudinal cluster analyses, sample size and variability of the times of measurements are the main issues with the current methods. Here, we propose a new two-step method for the Clustering of Longitudinal data by using an Extended Baseline. The first step relies on a piecewise linear mixed model for repeated measurements with a treatment-time interaction. The second step clusters the random predictions and considers several parametric (model-based) and non-parametric (partitioning, ascendant hierarchical clustering) algorithms. A simulation study compares all options of the clustering of longitudinal data by using an extended baseline method with the latent-class mixed model. The clustering of longitudinal data by using an extended baseline method with the two model-based algorithms was the more robust model. The clustering of longitudinal data by using an extended baseline method with all the non-parametric algorithms failed when there were unequal variances of treatment effect between clusters or when the subgroups had unbalanced sample sizes. The latent-class mixed model failed when the between-patients slope variability is high. Two real data sets on neurodegenerative disease and on obesity illustrate the clustering of longitudinal data by using an extended baseline method and show how clustering may help to identify the marker(s) of the treatment response. The application of the clustering of longitudinal data by using an extended baseline method in exploratory analysis as the first stage before setting up stratified designs can provide a better estimation of treatment effect in future clinical trials.

COMT Val158Met Polymorphism Modulates Huntington's Disease Progression.

Little is known about the genetic factors modulating the progression of Huntington's disease (HD). Dopamine levels are affected in HD and modulate executive functions, the main cognitive disorder of HD. We investigated whether the Val158Met polymorphism of the catechol-O-methyltransferase (COMT) gene, which influences dopamine (DA) degradation, affects clinical progression in HD. We carried out a prospective longitudinal multicenter study from 1994 to 2011, on 438 HD gene carriers at different stages of the disease (34 pre-manifest; 172 stage 1; 130 stage 2; 80 stage 3; 17 stage 4; and 5 stage 5), according to Total Functional Capacity (TFC) score. We used the Unified Huntington's Disease Rating Scale to evaluate motor, cognitive, behavioral and functional decline. We genotyped participants for COMT polymorphism (107 Met-homozygous, 114 Val-homozygous and 217 heterozygous). 367 controls of similar ancestry were also genotyped. We compared clinical progression, on each domain, between groups of COMT polymorphisms, using latent-class mixed models accounting for disease duration and number of CAG (cytosine adenine guanine) repeats. We show that HD gene carriers with fewer CAG repeats and with the Val allele in COMT polymorphism displayed slower cognitive decline. The rate of cognitive decline was greater for Met/Met homozygotes, which displayed a better maintenance of cognitive capacity in earlier stages of the disease, but had a worse performance than Val allele carriers later on. COMT polymorphism did not significantly impact functional and behavioral performance. Since COMT polymorphism influences progression in HD, it could be used for stratification in future clinical trials. Moreover, DA treatments based on the specific COMT polymorphism and adapted according to disease duration could potentially slow HD progression.

Interventions to reduce nurses' medication administration errors in inpatient settings: A systematic review and meta-analysis.

BACKGROUND AND OBJECTIVES: Serious medication administration errors are common in hospitals. Various interventions, including barcode-based technologies, have been developed to help prevent such errors. This systematic review and this meta-analysis focus on the efficacy of interventions for reducing medication administration errors. The types of error and their gravity were also studied. METHODS: MEDLINE, EMBASE, the Cochrane Library and reference lists of relevant articles published between January 1975 and August 2014 were searched, without language restriction. Randomized controlled trials, interrupted time-series studies, non-randomized controlled trials and controlled before-and-after studies were included. Studies evaluating interventions for decreasing administration errors based on total opportunity for error method were included. Nurses administering medications to adult or child inpatients were considered eligible as participants. Two reviewers independently assessed studies for eligibility, extracted data and assessed the risk of bias. The main outcome was the error rate without wrong-time errors measured at study level. A random effects model was used to evaluate the effects of interventions on administration errors. RESULTS: 5312 records from electronic database searches were identified. Seven studies were included: five were randomized controlled trials (including one crossover trial) and two were non-randomized controlled trials. Interventions were training-related (n=4; dedicated medication nurses, interactive CD-ROM program, simulation-based learning, pharmacist-led training program), and technology-related (n=3; computerized prescribing and automated medication dispensing systems). All studies were subject to a high risk of bias, mostly due to a lack of blinding to outcome assessment and a risk of contamination. No difference between the control group and the intervention group was found (OR=0.72 [0.39; 1.34], p=0.3). No fatal error was observed in the three studies evaluating the gravity of errors. CONCLUSIONS: This review did not find evidence that interventions can effectively decrease administration errors. In addition, most studies had a high risk of bias. More evaluation studies with stronger designs are required.

How to Capitalize on the Retest Effect in Future Trials on Huntington's Disease.

The retest effect-improvement of performance on second exposure to a task-may impede the detection of cognitive decline in clinical trials for neurodegenerative diseases. We assessed the impact of the retest effect in Huntington's disease trials, and investigated its possible neutralization. We enrolled 54 patients in the Multicentric Intracerebral Grafting in Huntington's Disease (MIG-HD) trial and 39 in the placebo arm of the Riluzole trial in Huntington's Disease (RIL-HD). All were assessed with the Unified Huntington's Disease Rating Scale (UHDRS) plus additional cognitive tasks at baseline (A1), shortly after baseline (A2) and one year later (A3). We used paired t-tests to analyze the retest effect between A1 and A2. For each task of the MIG-HD study, we used a stepwise algorithm to design models predictive of patient performance at A3, which we applied to the RIL-HD trial for external validation. We observed a retest effect in most cognitive tasks. A decline in performance at one year was detected in 3 of the 15 cognitive tasks with A1 as the baseline, and 9 of the 15 cognitive tasks with A2 as the baseline. We also included the retest effect in performance modeling and showed that it facilitated performance prediction one year later for 14 of the 15 cognitive tasks. The retest effect may mask cognitive decline in patients with neurodegenerative diseases. The dual baseline can improve clinical trial design, and better prediction should homogenize patient groups, resulting in smaller numbers of participants being required.