Cross-Sectional Exploration of Plasma Biomarkers of Alzheimer's Disease in Down Syndrome: Early Data from the Longitudinal Investigation for Enhancing Down Syndrome Research (LIFE-DSR) Study

With improved healthcare, the Down syndrome (DS) population is both growing and aging rapidly. However, with longevity comes a very high risk of Alzheimer's disease (AD). The LIFE-DSR study (NCT04149197) is a longitudinal natural history study recruiting 270 adults with DS over the age of 25. The study is designed to characterize trajectories of change in DS-associated AD (DS-AD). The current study reports its cross-sectional analysis of the first 90 subjects enrolled. Plasma biomarkers phosphorylated tau protein (p-tau), neurofilament light chain (NfL), amyloid β peptides (Aβ1-40, Aβ1-42), and glial fibrillary acidic protein (GFAP) were undertaken with previously published methods. The clinical data from the baseline visit include demographics as well as the cognitive measures under the Severe Impairment Battery (SIB) and Down Syndrome Mental Status Examination (DS-MSE). Biomarker distributions are described with strong statistical associations observed with participant age. The biomarker data contributes to understanding DS-AD across the spectrum of disease. Collectively, the biomarker data show evidence of DS-AD progression beginning at approximately 40 years of age. Exploring these data across the full LIFE-DSR longitudinal study population will be an important resource in understanding the onset, progression, and clinical profiles of DS-AD pathophysiology

Down Syndrome: Neuropsychological Phenotype across the Lifespan

Down syndrome (DS), caused by triplication of chromosome 21, is the most common genetic cause of intellectual disability (ID), with an estimated incidence of one in 700 live births [...

Language skills as a predictor of cognitive decline in adults with Down syndrome.

IntroductionAdults with Down syndrome (DS) are at high risk for early onset Alzheimer's disease (AD), characterized by a progressive decline in multiple cognitive domains including language, which can impact social interactions, behavior, and quality of life. This cross-sectional study examined the relationship between language skills and dementia.MethodsA total of 168 adults with DS (mean age = 51.4 years) received neuropsychological assessments, including Vineland Communication Domain, McCarthy Verbal Fluency, and Boston Naming Test, and were categorized in one of three clinical groups: cognitively stable (CS, 57.8%); mild cognitive impairment (MCI-DS, 22.6%); and probable/definite dementia (AD-DS, 19.6%). Logistic regression was used to determine how well language measures predict group status.ResultsVineland Communication, particularly receptive language, was a significant predictor of MCI-DS. Semantic verbal fluency was the strongest predictor of AD-DS.DiscussionAssessment of language skills can aid in the identification of dementia in adults with DS. Clinically, indications of emerging language problems should warrant further evaluation and monitoring

Understanding Relationships Between Autism, Intelligence, and Epilepsy: A Cross-Disorder Approach

Aim As relationships between autistic traits, epilepsy, and cognitive functioning remain poorly understood, these associations were explored in the biologically related disorders tuberous sclerosis complex (TSC), neurofibromatosis type 1 (NF1), and epilepsy. Method The Social Responsiveness Scale (SRS), a quantitative measure of autistic traits, was distributed to caregivers or companions of patients with TSC, NF1, and childhood-onset epilepsy of unknown cause (EUC), and these results were compared with SRS data from individuals with idiopathic autism spectrum disorders (ASDs) and their unaffected siblings. Scores and trait profiles of autistic features were compared with cognitive outcomes, epilepsy variables, and genotype. Results A total of 180 SRS questionnaires were filled out in the TSC, NF1, and EUC outpatient clinics at the Massachusetts General Hospital (90 females, 90 males; mean age 21y, range 4–63y), and SRS data from 210 patients with ASD recruited from an autism research collaboration (167 males, 43 females; mean age 9y range 4–22y) and 130 unaffected siblings were available. Regression models showed a significant association between SRS scores and intelligence outcomes (p<0.001) and various seizure variables (p<0.02), but not with a specific underlying disorder or genotype. The level of autistic features was strongly associated with intelligence outcomes in patients with TSC and epilepsy (p<0.01); in patients with NF1 these relationships were weaker (p=0.25). For all study groups, autistic trait subdomains covaried with neurocognitive comorbidity, with endophenotypes similar to that of idiopathic autism. Interpretation Our data show that in TSC and childhood-onset epilepsy, the severity and phenotype of autistic features are inextricably linked with intelligence and epilepsy outcomes. Such relationships were weaker for individuals with NF1. Findings suggest that ASDs are not specific for these conditions

Correction: Hom et al. Cognitive Function during the Prodromal Stage of Alzheimer's Disease in Down Syndrome: Comparing Models. BrainSci. 2021, 11, 1220.

We would like to submit the following correction to our recently published paper [...]

Cognitive Function during the Prodromal Stage of Alzheimer’s Disease in Down Syndrome: Comparing Models

Accurate identification of the prodromal stage of Alzheimer’s disease (AD), known as mild cognitive impairment (MCI), in adults with Down syndrome (MCI-DS) has been challenging because there are no established diagnostic criteria that can be applied for people with lifelong intellectual disabilities (ID). As such, the sequence of cognitive decline in adults with DS has been difficult to ascertain, and it is possible that domain constructs characterizing cognitive function in neurotypical adults do not generalize to this high-risk population. The present study examined associations among multiple measures of cognitive function in adults with DS, either prior to or during the prodromal stage of AD to determine, through multiple statistical techniques, the measures that reflected the same underlying domains of processing. Participants included 144 adults with DS 40–82 years of age, all enrolled in a larger, multidisciplinary study examining biomarkers of AD in adults with DS. All participants had mild or moderate lifelong intellectual disabilities. Overall AD-related clinical status was rated for each individual during a personalized consensus conference that considered performance as well as health status, with 103 participants considered cognitively stable (CS) and 41 to have MCI-DS. Analyses of 17 variables derived from 10 tests of cognition indicated that performance reflected three underlying factors: language/executive function, memory, and visuomotor. All three domain composite scores significantly predicted MCI-DS status. Based upon path modeling, the language/executive function composite score was the most affected by prodromal AD. However, based upon structural equation modeling, tests assessing the latent construct of memory were the most impacted, followed by those assessing visuomotor, and then those assessing language/executive function. Our study provides clear evidence that cognitive functioning in older adults with DS can be characterized at the cognitive domain level, but the statistical methods selected and the inclusion or exclusion of certain covariates may lead to different conclusions. Best practice requires investigators to understand the internal structure of their variables and to provide evidence that their variables assess their intended constructs