Epidemiology of Dementia and Alzheimer Disease in Individuals With Down Syndrome

Age of Alzheimer's disease diagnosis in people with Down syndrome and associated factors: Results from the Horizon 21 European Down syndrome consortium

INTRODUCTION

People with Down syndrome (DS) have high risk of developing Alzheimer's disease (AD). This study examined mean ages of AD diagnosis and associations with co-occurring conditions among adults with DS from five European countries.

METHODS

Data from 1335 people with DS from the Horizon 21 European DS Consortium were used for the analysis.

RESULTS

Mean ages of AD diagnosis ranged between 51.4 (SD 7.0) years (United Kingdom) and 55.6 (SD 6.8) years (France). Sleep-related and mental health problems were associated with earlier age of AD diagnosis. The higher number of co-occurring conditions the more likely the person with DS is diagnosed with AD at an earlier age.

DISCUSSION

Mean age of AD diagnosis in DS was relatively consistent across countries. However, co-occurring conditions varied and impacted on age of diagnosis, suggesting that improvements can be made in diagnosing and managing these conditions to delay onset of AD in DS.

HIGHLIGHTS

Mean age of AD diagnosis was relatively consistent between countries Sleep problems and mental health problems were associated with earlier age of AD diagnosis APOE ε4 carriers were diagnosed with AD at an earlier age compared to non-carriers Number of co-occurring conditions was associated with earlier age of AD diagnosis No differences between level of intellectual disability and mean age of AD diagnosis.

Medicaid Enrollment and Service Use Among Adults With Down Syndrome

Importance

Down syndrome is the leading genetic cause of intellectual disability and automatically qualifies individuals for Social Security Insurance. Therefore, Medicaid is the major health insurance provider for a population at high risk for dementia, obesity, and premature mortality. Despite the importance of Medicaid for adults with Down syndrome, little is known about how this population uses Medicaid.

Objective

To describe enrollment in, health care use in, and cost to Medicaid for adults with Down syndrome compared with adults with intellectual disability and a random sample of adults enrolled in Medicaid.

Design, Setting, and Participants

In this cohort study, the data are from a claims cohort of adults aged 18 years or older enrolled in Medicaid at any point between January 1, 2011, and December 31, 2019. Participants were enrollees with 1 or more inpatient claim or 2 or more other claims with an International Classification of Diseases, Ninth Revision code or an International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code for Down syndrome or intellectual disability as well as a random sample of those without developmental disability. Analyses were conducted from June 2022 to February 2023.

Main Outcomes and Measures

Data were linked across 2 data reporting systems. Main outcomes were enrollee demographic characteristics, enrollment characteristics, cost, and service use.

Results

This cohort study included 123 024 individuals with Down syndrome (820 273 person-years of coverage; mean [SD] age, 35 [14.7] years; median age, 33 years [IQR, 21-48 years]; 51.6% men; 14.1% Black individuals; 16.7% Hispanic individuals; and 74.6% White individuals), 1 182 246 individuals with intellectual disability (mean [SD] age, 37.1 [16.8] years; median age, 33 years [IQR, 22-50 years]; 56.5% men; 22.0% Black individuals; 11.7% Hispanic individuals; and 69.5% White individuals), and 3 176 371 individuals with no developmental disabilities (mean [SD] age, 38 [18.6] years; median age, 33 years [IQR, 21-52 years]; 43.8% men; 23.7% Black individuals; 20.7% Hispanic individuals; and 61.3% White individuals). Median enrollment in Medicaid for a person with Down syndrome was 8.0 years (IQR, 5.0-9.0 years; mean [SD], 6.6 [2.6] years). Costs were higher for the Down syndrome group (median, $26 278 per person-year [IQR, $11 145-$55 928 per person-year]) relative to the group with no developmental disabilities (median, $6173 per person-year [IQR, $868-$58 390 per person-year]). Asian, Black, Hispanic, Native American, and Pacific Islander adults with Down syndrome had fewer costs and claims per person-year compared with White adults with Down syndrome.

Conclusion and Relevance

This cohort study of individuals with Down syndrome enrolled in Medicaid found consistent enrollment and high use of health care in a population with high health care needs. Results were similar comparing individuals with Down syndrome and those with intellectual disability, with both groups differing from a sample of Medicaid enrollees with no developmental disabilities. Medicaid data are a useful tool for understanding the health and well-being of individuals with Down syndrome.

Healthcare and Behavior Changes for Adults With Down Syndrome 1-Year Into COVID-19

Individuals with Down syndrome (DS) have been disproportionately harmed by the COVID-19 pandemic and may have been more likely to have sacrificed opportunity and activity to avoid potential exposures. Our objective was to describe the experience one to one and half years into the COVID-19 pandemic for adults with DS, as reported by their caregivers in an online survey conducted between April 2021 and September of 2021. In our sample of 438 adults with DS, caregivers reported that adults with DS lost activities, struggled with employment, had negative behavioral changes, lost skills, and developed more mental health conditions. For adults with DS, one in five caregivers reported less healthcare usage, one in four reported delayed routine care, and 86.5% reported lost activities. As the pandemic continues, targeted support for adults with DS is needed to prevent further skill loss and mental health conditions.

The Global Deterioration Scale for Down Syndrome Population (GDS-DS): A Rating Scale to Assess the Progression of Alzheimer's Disease

The aim of this study is to adapt and validate the global deterioration scale (GDS) for the systematic tracking of Alzheimer's disease (AD) progression in a population with Down syndrome (DS). A retrospective dual-center cohort study was conducted with 83 participants with DS (46.65 ± 5.08 years) who formed the primary diagnosis (PD) group: cognitive stability (n = 48), mild cognitive impairment (n = 24), and Alzheimer's disease (n = 11). The proposed scale for adults with DS (GDS-DS) comprises six stages, from cognitive and/or behavioral stability to advanced AD. Two neuropsychologists placed the participants of the PD group in each stage of the GDS-DS according to cognitive, behavioral and daily living skills data. Inter-rater reliability in staging with the GDS-DS was excellent (ICC = 0.86; CI: 0.80-0.93), and the agreement with the diagnosis categories of the PD group ranged from substantial to excellent with κ values of 0.82 (95% CI: 0.73-0.92) and 0.85 (95% CI: 0.72, 0.99). Performance with regard to the CAMCOG-DS total score and orientation subtest of the Barcelona test for intellectual disability showed a slight progressive decline across all the GDS-DS stages. The GDS-DS scale is a sensitive tool for staging the progression of AD in the DS population, with special relevance in daily clinical practice.

Brain signal complexity in adults with Down syndrome: Potential application in the detection of mild cognitive impairment

Background

Down syndrome (DS) is considered the most frequent cause of early-onset Alzheimer’s disease (AD), and the typical pathophysiological signs are present in almost all individuals with DS by the age of 40. Despite of this evidence, the investigation on the pre-dementia stages in DS is scarce. In the present study we analyzed the complexity of brain oscillatory patterns and neuropsychological performance for the characterization of mild cognitive impairment (MCI) in DS.

Materials and methods

Lempel-Ziv complexity (LZC) values from resting-state magnetoencephalography recordings and the neuropsychological performance in 28 patients with DS [control DS group (CN-DS) (n = 14), MCI group (MCI-DS) (n = 14)] and 14 individuals with typical neurodevelopment (CN-no-DS) were analyzed.

Results

Lempel-Ziv complexity was lowest in the frontal region within the MCI-DS group, while the CN-DS group showed reduced values in parietal areas when compared with the CN-no-DS group. Also, the CN-no-DS group exhibited the expected pattern of significant increase of LZC as a function of age, while MCI-DS cases showed a decrease. The combination of reduced LZC values and a divergent trajectory of complexity evolution with age, allowed the discrimination of CN-DS vs. MCI-DS patients with a 92.9% of sensitivity and 85.7% of specificity. Finally, a pattern of mnestic and praxic impairment was significantly associated in MCI-DS cases with the significant reduction of LZC values in frontal and parietal regions (p = 0.01).

Conclusion

Brain signal complexity measured with LZC is reduced in DS and its development with age is also disrupted. The combination of both features might assist in the detection of MCI within this population.

Cognitive outcome measures for tracking Alzheimer's disease in Down syndrome

Down syndrome (DS) is now viewed as a genetic type of Alzheimer's disease (AD), given the near-universal presence of AD pathology in middle adulthood and the elevated risk for developing clinical AD in DS. As the field of DS prepares for AD clinical intervention trials, there is a strong need to identify cognitive measures that are specific and sensitive to the transition from being cognitively stable to the prodromal (e.g., Mild Cognitive Impairment-Down syndrome) and clinical AD (e.g., Dementia) stages of the disease in DS. It is also important to determine cognitive measures that map onto biomarkers of early AD pathology during the transition from the preclinical to the prodromal stage of the disease, as this transition period is likely to be targeted and tracked in AD clinical trials. The present chapter discusses the current state of research on cognitive measures that could be used to screen/select study participants and as potential outcome measures in future AD clinical trials with adults with DS. In this chapter, we also identify key challenges that need to be overcome and questions that need to be addressed by the DS field as it prepares for AD clinical trials in the coming years.

Prevalence of anxiety symptomatology and diagnosis in syndromic intellectual disability: A systematic review and meta-analysis

Individuals with syndromic intellectual disability are at increased risk of experiencing anxiety. Comparing prevalence estimates of anxiety will allow the identification of at-risk groups and inform causal pathways of anxiety. No known study has explored estimates of anxiety symptomatology and diagnosis, including specific anxiety profiles, across groups whilst accounting for methodological quality of studies. This systematic review and meta-analysis aimed to fill this gap. Prior to review completion, methodology and analysis plans were registered and documented in a protocol (CRD42019123561). Data from 83 papers, involving a pooled sample of 13,708 across eight syndromes were synthesised using a random effects model. Anxiety prevalence ranged from 9 % (95 % CI: 4-14) in Down syndrome to 73% in Rett syndrome (95 % CI: 70-77). Anxiety prevalence across syndromic intellectual disability was higher than for intellectual disability of mixed aetiology and general population estimates. Substantial variability between syndromes identified groups at higher risk than others. The identification of high-risk groups is crucial for early intervention, allowing us to refine models of risk and identify divergent profiles.

Disparities and outcomes of patients living with Down Syndrome undergoing healthcare transitions from pediatric to adult care: A scoping review

Down Syndrome (DS) is one of the most common chromosomal disorders worldwide, and people with DS experience more co-morbidities and have poorer health outcomes compared to the general population. An area that is not well understood is how patients with DS transition from pediatric to adult care, as well as the details, barriers, and difficulties of these transitions for patients. Hence, we aimed to provide a scoping review of the literature in PubMed, Scopus, and CINAHL on the topic of healthcare transitions (HCTs) for patients with DS. Findings suggest patients with DS who continued receiving care as an adult from a pediatric care provider tended to experience co-morbidities and other adverse health issues at higher rates than those who entirely switch to an adult-care team. Patients with DS were unable to undergo transition due to multiple barriers, such as low income, limited/public insurance, gender, and race. We propose potential steps for transition, which focus on ensuring early planning, communicating better, coordinating services, assessing decision-making capacity, and providing ongoing social and financial support. Future research must further identify and address barriers to HCTs for people with DS.

Profiling of circulating chromosome 21-encoded microRNAs, miR-155, and let-7c, in down syndrome

Background

Down syndrome (DS) is the most common chromosomal survival aneuploidy. The increase in DS life expectancy further heightens the risk of dementia, principally early‐onset Alzheimer's disease (AD). AD risk in DS is higher, considering that this population may also develop metabolic diseases such as obesity, dyslipidemias, and diabetes mellitus. The extra genetic material that characterizes DS causes an imbalance in the genetic dosage, including over‐expression of AD's key pathophysiological molecules and the gene expression regulators, the microRNAs (miRNAs). Two miRNAs, chromosome 21‐encoded, miR‐155, and let‐7c, are associated with cognitive impairment and dementia in adults; but, expression dynamics and relationship with clinical variables during the DS's lifespan had remained hitherto unexplored.

Methods

The anthropometric, clinical, biochemical, and profile expression of circulating miR‐155 and let‐7c were analyzed in a population of 52 control and 50 DS subjects divided into the young group (Aged ≤20 years) and the adult group (Aged ≥21 years).

Results

The expression changes for miR‐155 were not significant; nevertheless, a negative correlation with HDL‐Cholesterol concentrations was observed. Notably, let‐7c was over‐expressed in DS from young and old ages.

Conclusion

Overall, our results suggest that let‐7c plays a role from the early stages of DS's cognitive impairment while overexpression of miR‐155 may be related to lipid metabolism changes. Further studies of both miRNAs will shed light on their potential as therapeutic targets to prevent or delay DS's cognitive impairment.

Selective Impairment of Long-Range Default Mode Network Functional Connectivity as a Biomarker for Preclinical Alzheimer's Disease in People with Down Syndrome

BACKGROUND

Down syndrome (DS) is associated with increased risk for Alzheimer's disease (AD). In neurotypical individuals, clinical AD is preceded by reduced resting state functional connectivity in the default mode network (DMN), but it is unknown whether changes in DMN connectivity predict clinical onset of AD in DS.

OBJECTIVE

Does lower DMN functional connectivity predict clinical onset of AD and cognitive decline in people with DS?

METHODS

Resting state functional MRI (rsfMRI), longitudinal neuropsychological, and clinical assessment data were collected on 15 nondemented people with DS (mean age = 51.66 years, SD = 5.34 years, range = 42-59 years) over four years, during which 4 transitioned to dementia. Amyloid-β (Aβ) PET data were acquired on 13 of the 15 participants. Resting state fMRI, neuropsychological, and clinical assessment data were also acquired on an independent, slightly younger unimpaired sample of 14 nondemented people with DS (mean age = 44.63 years, SD = 7.99 years, range = 38-61 years).

RESULTS

Lower functional connectivity between long-range but not short-range DMN regions predicts AD diagnosis and cognitive decline in people with DS. Aβ accumulation in the inferior parietal cortex is associated with lower regional DMN functional connectivity.

CONCLUSION

Reduction of long-range DMN connectivity is a potential biomarker for AD in people with DS that precedes and predicts clinical conversion.

Identifying dementia in Down syndrome with the Severe Impairment Battery, Brief Praxis Test and Dementia Scale for People with Learning Disabilities

BACKGROUND

Individuals with Down syndrome (DS) are at high risk for dementia, specifically Alzheimer's disease. However, many measures regularly used for the detection of dementia in the general population are not suitable for individuals with DS due in part to floor effects. Some measures, including the Severe Impairment Battery (SIB), Brief Praxis Test (BPT) and Dementia Scale for People with Learning Disabilities (DLD), have been used in clinical trials and other research with this population. Validity research is limited, particularly regarding the use of such tools for detection of prodromal dementia in the DS population. The current project presents baseline cross-sectional SIB, BPT and DLD performance in order to characterise their predictive utility in discriminating normal cognition, possible dementia and probable dementia in adult DS.

METHOD

Baseline SIB, BPT and DLD performances from 100 individuals (no dementia = 68, possible dementia = 16 & probable dementia = 16) were examined from a longitudinal cohort of aging individuals with DS. Receiver operating characteristic curves investigated the accuracy of these measures in relation to consensus dementia diagnoses, diagnoses which demonstrated high percent agreement with the examining neurologist's independent diagnostic impression.

RESULTS

The SIB and BPT exhibited fair discrimination ability for differentiating no/possible versus probable dementia [area under the curve (AUC) = 0.61 and 0.66, respectively]. The DLD exhibited good discrimination ability for differentiating no versus possible/probable dementia (AUC = 0.75) and further demonstrated better performance of the DLD Cognitive subscale compared with the DLD Social subscale (AUC = 0.77 and 0.67, respectively).

CONCLUSIONS

Results suggest that the SIB, BPT and DLD are able to reasonably discriminate consensus dementia diagnoses in individuals with DS, supporting their continued use in the clinical assessment of dementia in DS. The general performance of these measures suggests that further work in the area of test development is needed to improve on the AUCs for dementia status discrimination in this unique population. At present, however, the current findings suggest that the DLD may be the best option for reliable identification of prodromal dementia in this population, reinforcing the importance of including informant behaviour ratings in assessment of cognition for adults with DS.

Proposed diagnostic criteria for mild cognitive impairment in Down syndrome population

BACKGROUND

Despite presenting higher risk of dementia, mild cognitive impairment (MCI) is not well defined in Down syndrome population.

OBJECTIVE

We aimed to describe cognitive and neuropsychological patterns associated with MCI in Down syndrome individuals.

METHOD

Two groups of adults with Down syndrome (control and prodromal) were studied throughout 3 years. Two linear mixed models and a model including the variables that best predicted group membership were built.

RESULTS

Behavioural Regulation Index (BRI) (Behaviour Rating Inventory of Executive Function test) and the model composed of BRI, abstraction and delayed verbal memory were the variable and model best predicting group membership, respectively.

CONCLUSION

Suggest a diagnosis of MCI when BRI is the earliest change perceived by caregivers and this is combined with low scores in abstract thinking, and when an amnesic pattern in delayed verbal memory is observed, but adaptive skills are preserved.

Sleep and White Matter in Adults with Down Syndrome

Adults with Down syndrome are at a high risk for disordered sleep. These sleep problems could have marked effects on aging and Alzheimer's disease, potentially altering white matter integrity. This study examined the associations between disordered sleep assessed via an actigraph accelerometer worn on 7 consecutive nights, presence of diagnosis of obstructive sleep apnea, and diffusion tensor imaging indices of white matter integrity in 29 non-demented adults with Down Syndrome (48% female, aged 33-54 years). Average total sleep time was associated with lower mean diffusivity in the left superior longitudinal fasciculus (r = -0.398, p = 0.040). Average sleep efficiency, length of awakenings, and movement index were related to fractional anisotropy in the right inferior longitudinal fasciculus (r = -0.614 to 0.387, p ≤ 0.050). Diagnosis of obstructive sleep apnea was associated with fractional anisotropy in the right inferior longitudinal fasciculus (r = -0.373, p = 0.050). Findings suggest that more disrupted sleep is associated with lower white matter integrity in the major association tracts in middle-aged adults with Down syndrome. Longitudinal work is needed to confirm the directionally of associations. Sleep interventions could be an important component for promoting optimal brain aging in the Down syndrome population.

Metabolite Signature of Alzheimer's Disease in Adults with Down Syndrome

OBJECTIVE

The purpose of this study was to examine the Alzheimer's disease metabolite signature through magnetic resonance spectroscopy in adults with Down syndrome and its relation with Alzheimer's disease biomarkers and cortical thickness.

METHODS

We included 118 adults with Down syndrome from the Down Alzheimer Barcelona Imaging Initiative and 71 euploid healthy controls from the Sant Pau Initiative on Neurodegeneration cohort. We measured the levels of myo-inositol (a marker of neuroinflammation) and N-acetyl-aspartate (a marker of neuronal integrity) in the precuneus using magnetic resonance spectroscopy. We investigated the changes with age and along the disease continuum (asymptomatic, prodromal Alzheimer's disease, and Alzheimer's disease dementia stages). We assessed the relationship between these metabolites and Aβ₄₂ /Aβ₄₀ ratio, phosphorylated tau-181, neurofilament light (NfL), and YKL-40 cerebrospinal fluid levels as well as amyloid positron emission tomography uptake using Spearman correlations controlling for multiple comparisons. Finally, we computed the relationship between cortical thickness and metabolite levels using Freesurfer.

RESULTS

Asymptomatic adults with Down syndrome had a 27.5% increase in the levels of myo-inositol, but equal levels of N-acetyl-aspartate compared to euploid healthy controls. With disease progression, myo-inositol levels increased, whereas N-acetyl-aspartate levels decreased in symptomatic stages of the disease. Myo-inositol was associated with amyloid, tau, and neurodegeneration markers, mainly at symptomatic stages of the disease, whereas N-acetyl-aspartate was related to neurodegeneration biomarkers in symptomatic stages. Both metabolites were significantly associated with cortical thinning, mainly in symptomatic participants.

INTERPRETATION

Magnetic resonance spectroscopy detects Alzheimer's disease related inflammation and neurodegeneration, and could be a good noninvasive disease-stage biomarker in Down syndrome. ANN NEUROL 2021.

A Comparative Analysis of Machine Learning Algorithms to Predict Alzheimer's Disease

Alzheimer's disease has been one of the major concerns recently. Around 45 million people are suffering from this disease. Alzheimer's is a degenerative brain disease with an unspecified cause and pathogenesis which primarily affects older people. The main cause of Alzheimer's disease is Dementia, which progressively damages the brain cells. People lost their thinking ability, reading ability, and many more from this disease. A machine learning system can reduce this problem by predicting the disease. The main aim is to recognize Dementia among various patients. This paper represents the result and analysis regarding detecting Dementia from various machine learning models. The Open Access Series of Imaging Studies (OASIS) dataset has been used for the development of the system. The dataset is small, but it has some significant values. The dataset has been analyzed and applied in several machine learning models. Support vector machine, logistic regression, decision tree, and random forest have been used for prediction. First, the system has been run without fine-tuning and then with fine-tuning. Comparing the results, it is found that the support vector machine provides the best results among the models. It has the best accuracy in detecting Dementia among numerous patients. The system is simple and can easily help people by detecting Dementia among them.

Caregiver resource utilization: Intellectual and development disability and dementia

BACKGROUND

Adults with intellectual and developmental disabilities and their families have high need for support services. This study assessed resource utilization among caregivers of intellectual and developmental disabilities and other conditions.

METHODS

We assessed 366 caregivers of adults with intellectual and developmental disabilities, dementia or other conditions Regressions assessed group differences in number of agency contacts and frequency of service use. A secondary analysis assessed reasons for underutilization of services.

RESULTS

Caregivers of individuals with dementia contacted twice as many agencies as other caregivers and were more likely to report using suggested services. Agency contact and service utilization were similar among caregivers of adults with intellectual and developmental disabilities compared to other caregivers. Caregivers of adults with intellectual and developmental indicated that suggested services were unavailable to them.

CONCLUSION

The findings of this study shed light on challenges with access to and utilization of support services.

White matter microstructure associations with episodic memory in adults with Down syndrome: a tract-based spatial statistics study

BACKGROUND

Nearly all persons with Down syndrome will show pathology of Alzheimer's disease in their 40s. There is a critical need for studies to identify early biomarkers of these various pathological changes of Alzheimer's disease in the Down syndrome population and understand the relationship of these biomarkers to cognitive symptoms in order to inform clinical trials. Although Alzheimer's disease is often considered a disease of gray matter, white matter degeneration has been documented during the preclinical stage of Alzheimer's disease. The current study examined the association between diffusion tensor imaging (DTI) measures of white matter microstructure and episodic memory performance in 52 adults with Down syndrome.

METHODS

Seventy (N = 70) participants (M = 40.13, SD = 7.77 years) received baseline scans as part of the Neurodegeneration in Aging Down Syndrome (NiAD) study at two imaging facilities (36 at the University of Wisconsin-Madison [UW-Madison] and 34 at the University of Pittsburgh Medical Center [UPMC]). All participants had genetically confirmed trisomy 21. Fifty-two (N = 52) participants remained after QC. The DTI measures, fractional anisotropy (FA) and mean diffusivity (MD), were calculated for each participant. A combined measure of episodic memory was generated by summing the z-scores of (1) Free and Cued Recall test and (2) Rivermead Behavioural Memory Test for Children Picture Recognition. The DTI data were projected onto a population-derived FA skeleton and tract-based spatial statistics analysis was conducted using the FSL tool PALM to calculate Pearson's r values between FA and MD with episodic memory.

RESULTS

A positive correlation of episodic memory with FA and a negative correlation of episodic memory and MD in the major association white matter tracts were observed. Results were significant (p < 0.05) after correction for chronological age, imaging site, and premorbid cognitive ability.

CONCLUSION

These findings suggest that white matter degeneration may be implicated in early episodic memory declines prior to the onset of dementia in adults with Down syndrome. Further, our findings suggest a coupling of episodic memory and white matter microstructure independent of chronological age.

Prevalence of Common Disease Conditions in a Large Cohort of Individuals With Down Syndrome in the United States

Purpose

Given the current life expectancy and number of individuals living with Down syndrome (DS), it is important to learn common occurrences of disease conditions across the developmental lifespan. This study analyzed data from a large cohort of individuals with DS in an effort to better understand these disease conditions, inform future screening practices, tailor medical care guidelines, and improve utilization of health care resources.

Methods

This retrospective, descriptive study incorporated up to 28 years of data, compiled from 6078 individuals with DS and 30,326 controls matched on age and sex. Data were abstracted from electronic medical records within a large Midwestern health system.

Results

In general, individuals with DS experienced higher prevalence of testicular cancer, leukemias, moyamoya disease, mental health conditions, bronchitis and pneumonia, gastrointestinal conditions, thyroid disorder, neurological conditions, atlantoaxial subluxation, osteoporosis, dysphagia, diseases of the eyes/adnexa and of the ears/mastoid process, and sleep apnea, relative to matched controls. Individuals with DS experienced lower prevalence of solid tumors, heart disease conditions, sexually transmitted diseases, HIV, influenza, sinusitis, urinary tract infections, and diabetes. Similar rates of prevalence were seen for lymphomas, skin melanomas, stroke, acute myocardial infarction, hepatitis, cellulitis, and osteoarthritis.

Conclusions

While it is challenging to draw a widespread conclusion about comorbidities in individuals with Down syndrome, it is safe to conclude that care for individuals with DS should not automatically mirror screening, prevention, or treatment guidelines for the general U.S. population. Rather, care for those with DS should reflect the unique needs and common comorbidities of this population.

Short forms of Prudhoe Cognitive Function Test in adults and aging people with intellectual disabilities: Italian validation study

BACKGROUND

We aimed to validate the Italian version of the two parallel short forms of the Prudhoe Cognitive Function Test (s-PCFT-I) in adults and seniors with intellectual disabilities (ID) of any aetiology and level of severity.

METHODS

Our validation is a multicentre study attended by 211 subjects with ID, 125 male and 86 female, aged 40 years and above for people with Down syndrome and aged 50 years for people with other forms of disabilities.

RESULTS

The s-PCFT-I shows a wide range of scores in the absence of floor effects with minimal ceiling effects. A Cronbach's α coefficient of 0.85 and a mean inter-item correlation of 0.21 indicate high internal consistency. The tool demonstrates good agreement between testers and near excellent temporal stability with intraclass correlation coefficients respectively of 0.85 and 0.90. s-PCFT-I total scores do not differ by sex or age, while statistically significant differences are observed between people with different levels of severity of ID. Moderate to good and highly significant correlations (-0.40 to -0.66) among the s-PCFT-I total scores and subscores and the Sum of Cognitive Score of the informant-based Dementia Questionnaire for Persons with Intellectual Disabilities suggest an acceptable level of concurrent criterion validity. Cognitive decliners according to Prasher's Dementia Questionnaire for Persons with Intellectual Disabilities cut-off scores perform significantly lower on s-PCFT-I than non-decliners.

CONCLUSIONS

The s-PCFT-I has good psychometric properties and user friendliness and may therefore be a valuable addition to the current informant-rated tools for screening and assessment of cognition in aging people with ID.

Resting-state default mode network connectivity in young individuals with Down syndrome

BACKGROUND

Down syndrome (DS) is a chromosomal disorder that causes intellectual disability. Few studies have been conducted on functional connectivity using resting-state fMRI (functional magnetic resonance imaging) signals or more specifically, on the relevant structure and density of the default mode network (DMN). Although data on this issue have been reported in adult DS individuals (age: >45 years), the DMN properties in young DS individuals have not been studied. The aim of this study was to describe the density and structure of the DMN network from fMRI signals in young DS (age: <36 years).

METHOD

A sample of 22 young people with DS between the ages of 16 and 35 (M = 25.5 and SD = 5.1) was recruited in various centers for people with intellectual disability (ID). In addition to sociodemographic data, a six-minute fMRI session was recorded with a 3. T Philips Ingenia scanner. A control group of 22 young people, matched by age and gender, was obtained from the Human Connectome Project (to compare the networks properties between groups).

RESULTS

The values of the 48 ROIs that configured the DMN were obtained, and the connectivity graphs for each subject, the average connectivity graph for each group, the clustering and degree values for each ROI, and the average functional connectivity network were estimated.

CONCLUSIONS

A higher density of overactivation was identified in DS group in the ventral, sensorimotor, and visual DMN networks, although within a framework of a wide variability of connectivity patterns in comparison with the control group network. These results extend our understanding of the functional connectivity networks pattern and intrasubject variability in DS.

Cognitive indicators of transition to preclinical and prodromal stages of Alzheimer's disease in Down syndrome

INTRODUCTION

There is a critical need to identify measures of cognitive functioning sensitive to early Alzheimer's disease (AD) pathophysiology in Down syndrome to advance clinical trial research in this at-risk population. The objective of the study was to longitudinally track performance on cognitive measures in relation to neocortical and striatal amyloid beta (Aβ) in non-demented Down syndrome.

METHODS

The study included 118 non-demented adults with Down syndrome who participated in two to five points of data collection, spanning 1.5 to 8 years. Episodic memory, visual attention and executive functioning, and motor planning and coordination were assessed. Aβ was measured via [C-11] Pittsburgh Compound-B (PiB) PET.

RESULTS

PiB was associated with level and rate of decline in cognitive performance in episodic memory, visual attention, executive functioning, and visuospatial ability in models controlling for chronological age.

DISCUSSION

The Cued Recall Test emerged as a promising indicator of transition from preclinical to prodromal AD.

Alzheimer's Disease in Down Syndrome: Progress in the Design and Conduct of Drug Prevention Trials

Individuals with Down syndrome (DS) are at high risk for developing Alzheimer's disease (AD) pathology and this has provided significant insights into our understanding of the genetic basis of AD. The present review summarizes recent clinical, neuropathologic, imaging, and fluid biomarker studies of AD in DS (DSAD), highlighting the striking similarities, as well as some notable differences, between DSAD and the more common late-onset form of AD (LOAD) in the general population, as well as the much rarer, autosomal-dominant form of AD (ADAD). There has been significant progress in our understanding of the natural history of AD biomarkers in DS and their relationship to clinically meaningful changes. Additional work is needed to clearly define the continuum of AD that has been described in the general population, such as the preclinical, prodromal, and dementia stages of AD. Multiple therapeutic approaches, including those targeting not only β-amyloid but also tau and the amyloid precursor protein itself, require consideration. Recent developments in the field are presented within the context of such efforts to conduct clinical trials to treat and potentially prevent AD in DS.

Leisure activity in middle-aged adults with Down syndrome: Initiators, social partners, settings and barriers

BACKGROUND

Leisure activity has been linked to optimal ageing outcomes, yet little is known about the type and level of leisure activity adults with Down syndrome currently engage in, and the factors that promote and hinder their leisure activities.

MATERIALS AND METHODS

A daily diary was utilized to provide an in-depth description of the average daily leisure activity of 44 adults with Down syndrome (aged 25-56 years) across a typical 7-day period. Factors related to participation, including initiators, social partners, settings and barriers, were examined.

RESULTS

Findings indicated that the majority of adults with Down syndrome did not meet established physical leisure activity intensity recommendations (i.e., 150 min/week moderately active activity) and did not exceed levels of passive leisure (e.g., watching television) found in the general population (i.e., 2-3 hr/day). Adults with Down syndrome self-initiated and self-engaged in the majority of their leisure activity. Family members and paid staff allocated resources towards initiating and engaging as social partners in social and physical leisure, respectively.

CONCLUSIONS

Interventions and support services should partner with family members and paid staff to foster participation in adaptive leisure activity, perhaps through the establishment of leisure activity as part of daily routines.

Association of Neutrophil-Lymphocyte Ratio with Mild Cognitive Impairment in Elderly Chinese Adults: A Case-control Study

Background:

Inflammation plays a significant role in the pathophysiology of cognitive impairment in previous studies. Neutrophil-lymphocyte ratio (NLR) is a reliable measure of systemic inflammation.

Objective:

The aim of this study was to investigate the association between NLR and mild cognitive impairment (MCI), and further to explore the diagnostic potential of the inflammatory markers NLR for the diagnosis of MCI in elderly Chinese individuals.

Methods:

186 MCI subjects and 153 subjects with normal cognitive function were evaluated consecutively in this study. Neutrophil (NEUT) count and Lymphocyte (LYM) count were measured in fasting blood samples. The NLR was calculated by dividing the absolute NEUT count by the absolute LYM count. Multivariable logistic regression was used to evaluate the potential association between NLR and MCI. NLR for predicting MCI was analyzed using Receiver Operating Characteristic (ROC) curve analysis.

Results:

The NLR of MCI group was significantly higher than that of subjects with normal cognitive function (2.39 ± 0.55 vs. 1.94 ± 0.51, P < 0.001). Logistic regression analysis showed that higher NLR was an independent risk factor for MCI (OR: 4.549, 95% CI: 2.623-7.889, P < 0.001). ROC analysis suggested that the optimum NLR cut-off point for MCI was 2.07 with 73.66% sensitivity, 69.28% specificity, 74.48% Positive Predictive Values (PPV) and 68.36% negative predictive values (NPV). Subjects with NLR ≥ 2.07 showed higher risk relative to NLR < 2.07 (OR: 5.933, 95% CI: 3.467-10.155, P < 0.001).

Conclusion:

The elevated NLR is significantly associated with increased risk of MCI. In particular, NLR level higher than the threshold of 2.07 was significantly associated with the probability of MCI.