Multiple morbidity across the lifespan in people with Down syndrome or intellectual disabilities: a population-based cohort study using electronic health records

COVID-19 vaccine uptake in individuals with functional difficulty, disability, and comorbid conditions: insights from a national survey in Bangladesh

BACKGROUND

COVID-19 vaccine uptake among individuals with disabilities is crucial for safeguarding their health and well-being. However, the extent of vaccine uptake among this group remains largely unknown in low- and middle-income countries. This study aims to assess the COVID-19 vaccine uptake among persons with functional difficulty, disability and/or comorbidity in Bangladesh and their associated factors.

METHODS

Data from 9,370 respondents extracted from the 2021 National Household Survey on Persons with Disability were analysed. The outcome variable was the uptake of at least one dose of the COVID-19 vaccine (yes, no). Key explanatory variables included the presence of disability (yes, no), comorbidity (yes, no), and both comorbidity and disability (yes, no) among persons with functional difficulty. The relationship between the outcome and explanatory variables was determined using mixed-effects multilevel logistic regressions adjusted for covariates.

RESULTS

The overall uptake of at least one dose of the COVID-19 vaccine among persons with functional difficulty was 57.37%, among persons with functional difficulty and disability was 48.63% and among persons with functional difficulty and single (57.85%) or multi-comorbidity (60.37%). Compared to the respondents with functional difficulty only, the adjusted odds ratio (aOR) of not receiving any dose of the COVID-19 vaccine for individuals with both functional difficulty and disability was 1.37 (95% CI, 1.22-1.53), and for individuals with functional difficulty, disability and one or more comorbid conditions was 1.30 (95% CI, 1.15-1.47). The aOR of receiving at least one dose of the COVID-19 vaccine among individuals with functional difficulty and one or more comorbid conditions was significantly higher than among those with functional difficulty only.

CONCLUSION

In Bangladesh, COVID-19 vaccine uptake was relatively low among individuals with disabilities. The existing COVID-19 vaccine rollout programs and similar future programs should prioritise individuals with disabilities and include targeted strategies to reach them.

Demographic Profile and Clinical Characteristics of Adults with Down Syndrome in North-Eastern Romania

(1) Background: Down syndrome is characterized by physical abnormalities, intellectual disability (ID), and specific patterns of other health issues. Additionally, individuals with DS are known to experience premature aging and early onset of certain age-related medical conditions. These conditions are linked to higher incident disability and reduced survival rates compared to the general population. (2) Methods: Between July 2022 and February 2024, we conducted a prospective, observational study in the Cardiovascular Rehabilitation Clinic at Iasi Clinical Rehabilitation Hospital. The study included 28 patients diagnosed with Down Syndrome and a control group. Interdisciplinary interventions were tailored to address the needs of a complex patient, incorporating cardiological, endocrinological, genetical, biological and developmental support. Data on physical health, cognitive development, and psychosocial well-being were collected. (3) Results: Our DS group consisted of 11 (39%) females and 17 (61%) males. Their age ranged from 20 to 55 years with a mean of 28.07 ± 9.51. All patients were unmarried, living in urban areas, without a partner but with family support. In the study sample, 96.4% of participants had three or more comorbidities. (4) Conclusions: The high prevalence of multimorbidity, combined with little medication, contributes to a high level of clinical complexity, which appears to be similar to the one of the older non-trisomic population. As individuals with Down syndrome transition into adulthood, they may require a more comprehensive and holistic approach to their healthcare.

Amyloid-β peptide signature associated with cerebral amyloid angiopathy in familial Alzheimer's disease with APPdup and Down syndrome

Alzheimer's disease (AD) is characterized by extracellular amyloid plaques containing amyloid-β (Aβ) peptides, intraneuronal neurofibrillary tangles, extracellular neuropil threads, and dystrophic neurites surrounding plaques composed of hyperphosphorylated tau protein (pTau). Aβ can also deposit in blood vessel walls leading to cerebral amyloid angiopathy (CAA). While amyloid plaques in AD brains are constant, CAA varies among cases. The study focuses on differences observed between rare and poorly studied patient groups with APP duplications (APPdup) and Down syndrome (DS) reported to have higher frequencies of elevated CAA levels in comparison to sporadic AD (sAD), most of APP mutations, and controls. We compared Aβ and tau pathologies in postmortem brain tissues across cases and Aβ peptides using mass spectrometry (MS). We further characterized the spatial distribution of Aβ peptides with MS-brain imaging. While intraparenchymal Aβ deposits were numerous in sAD, DS with AD (DS-AD) and AD with APP mutations, these were less abundant in APPdup. On the contrary, Aβ deposits in the blood vessels were abundant in APPdup and DS-AD while only APPdup cases displayed high Aβ deposits in capillaries. Investigation of Aβ peptide profiles showed a specific increase in Aβx-37, Aβx-38 and Aβx-40 but not Aβx-42 in APPdup cases and to a lower extent in DS-AD cases. Interestingly, N-truncated Aβ2-x peptides were particularly increased in APPdup compared to all other groups. This result was confirmed by MS-imaging of leptomeningeal and parenchymal vessels from an APPdup case, suggesting that CAA is associated with accumulation of shorter Aβ peptides truncated both at N- and C-termini in blood vessels. Altogether, this study identified striking differences in the localization and composition of Aβ deposits between AD cases, particularly APPdup and DS-AD, both carrying three genomic copies of the APP gene. Detection of specific Aβ peptides in CSF or plasma of these patients could improve the diagnosis of CAA and their inclusion in anti-amyloid immunotherapy treatments.

Variegated overexpression of chromosome 21 genes reveals molecular and immune subtypes of Down syndrome

Individuals with Down syndrome, the genetic condition caused by trisomy 21, exhibit strong inter-individual variability in terms of developmental phenotypes and diagnosis of co-occurring conditions. The mechanisms underlying this variable developmental and clinical presentation await elucidation. We report an investigation of human chromosome 21 gene overexpression in hundreds of research participants with Down syndrome, which led to the identification of two major subsets of co-expressed genes. Using clustering analyses, we identified three main molecular subtypes of trisomy 21, based on differential overexpression patterns of chromosome 21 genes. We subsequently performed multiomics comparative analyses among subtypes using whole blood transcriptomes, plasma proteomes and metabolomes, and immune cell profiles. These efforts revealed strong heterogeneity in dysregulation of key pathophysiological processes across the three subtypes, underscored by differential multiomics signatures related to inflammation, immunity, cell growth and proliferation, and metabolism. We also observed distinct patterns of immune cell changes across subtypes. These findings provide insights into the molecular heterogeneity of trisomy 21 and lay the foundation for the development of personalized medicine approaches for the clinical management of Down syndrome.

Diagnosis of common health conditions among autistic adults in the UK: evidence from a matched cohort study

Background

Autistic people are disproportionately likely to experience premature mortality and most mental and physical health conditions. We measured the incidence of diagnosed conditions accounting for the most disability-adjusted life years in the UK population according to the Global Burden of Disease study (anxiety, depression, self-harm, harmful alcohol use, substance use, migraine, neck or back pain, and gynaecological conditions).

Methods

Participants were aged 18 years or above and had an autism diagnosis recorded in the IQVIA Medical Research Database between 01/01/2000 and 16/01/2019. We included 15,675 autistic adults without intellectual disability, 6437 autistic adults with intellectual disability, and a comparison group matched (1:10) by age, sex, and primary care practice. We estimated crude incidences and incidence rate ratios (IRRs) adjusted for age and sex.

Findings

Autistic adults without intellectual disability experienced a higher incidence (IRR, 95% CI) of self-harm (2.07, 1.79-2.40), anxiety (1.91, 1.76-2.06), depressive disorders (1.79, 1.67-1.92), and substance use (1.24, 1.02-1.51) relative to comparison participants. Incidences of harmful alcohol use (1.01, 0.85-1.18), migraine (0.99, 0.84-1.17), and gynaecological conditions (1.19, 0.95-1.49) did not differ. Neck or back pain incidence was lower (0.88, 0.82-0.95). Autistic adults with intellectual disability experienced a higher incidence of self-harm (2.08, 1.69-2.56). Incidences of anxiety (1.14, 1.00-1.30), gynaecological conditions (1.22, 0.93-1.62), and substance use (1.08, 0.80-1.47) did not differ, and lower incidences were found for depressive disorders (0.73, 0.64-0.83), harmful alcohol use (0.65, 0.50-0.84), migraine (0.55, 0.42-0.74), and neck or back pain (0.49, 0.44-0.55).

Interpretation

Although our findings cannot be directly compared to previous prevalence studies, they contrast with the higher frequency of mental and physical health conditions in autistic adults reported in studies that directly assessed and/or surveyed autistic people about co-occurring conditions. The present findings may suggest under-diagnosis of common conditions in autistic people, particularly those with intellectual disability. Improved detection should be a clinical and policy priority to reduce health inequalities.

Funding

Dunhill Medical Trust, Economic and Social Research Council, National Institute of Health and Care Research.

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.

Young adults with a 22q11.2 microdeletion and the cost of aging with complexity in a population-based context

PURPOSE

Information about the impact on the adult health care system is limited for complex rare pediatric diseases, despite their increasing collective prevalence that has paralleled advances in clinical care of children. Within a population-based health care context, we examined costs and multimorbidity in adults with an exemplar of contemporary genetic diagnostics.

METHODS

We estimated direct health care costs over an 18-year period for adults with molecularly confirmed 22q11.2 microdeletion (cases) and matched controls (total 60,459 person-years of data) by linking the case cohort to health administrative data for the Ontario population (∼15 million people). We used linear regression to compare the relative ratio (RR) of costs and to identify baseline predictors of higher costs.

RESULTS

Total adult (age ≥ 18) health care costs were significantly higher for cases compared with population-based (RR 8.5, 95% CI 6.5-11.1) controls, and involved all health care sectors. At study end, when median age was <30 years, case costs were comparable to population-based individuals aged 72 years, likelihood of being within the top 1st percentile of health care costs for the entire (any age) population was significantly greater for cases than controls (odds ratio [OR], for adults 17.90, 95% CI 7.43-43.14), and just 8 (2.19%) cases had a multimorbidity score of zero (vs 1483 (40.63%) controls). The 22q11.2 microdeletion was a significant predictor of higher overall health care costs after adjustment for baseline variables (RR 6.9, 95% CI 4.6-10.5).

CONCLUSION

The findings support the possible extension of integrative models of complex care used in pediatrics to adult medicine and the potential value of genetic diagnostics in adult clinical medicine.

Phenotyping Down syndrome: discovery and predictive modelling with electronic medical records

BACKGROUND

Individuals with Down syndrome (DS) have a heightened risk for various co-occurring health conditions, including congenital heart disease (CHD). In this two-part study, electronic medical records (EMRs) were leveraged to examine co-occurring health conditions among individuals with DS (Study 1) and to investigate health conditions linked to surgical intervention among DS cases with CHD (Study 2).

METHODS

De-identified EMRs were acquired from Vanderbilt University Medical Center and facilitated creating a cohort of N = 2282 DS cases (55% females), along with comparison groups for each study. In Study 1, DS cases were one-by-two sex and age matched with samples of case-controls and of individuals with other intellectual and developmental difficulties (IDDs). The phenome-disease association study (PheDAS) strategy was employed to reveal co-occurring health conditions in DS versus comparison groups, which were then ranked for how often they are discussed in relation to DS using the PubMed database and Novelty Finding Index. In Study 2, a subset of DS individuals with CHD [N = 1098 (48%)] were identified to create longitudinal data for N = 204 cases with surgical intervention (19%) versus 204 case-controls. Data were included in predictive models and assessed which model-based health conditions, when more prevalent, would increase the likelihood of surgical intervention.

RESULTS

In Study 1, relative to case-controls and those with other IDDs, co-occurring health conditions among individuals with DS were confirmed to include heart failure, pulmonary heart disease, atrioventricular block, heart transplant/surgery and primary pulmonary hypertension (circulatory); hypothyroidism (endocrine/metabolic); and speech and language disorder and Alzheimer's disease (neurological/mental). Findings also revealed more versus less prevalent co-occurring health conditions in individuals with DS when comparing with those with other IDDs. Findings with high Novelty Finding Index were abnormal electrocardiogram, non-rheumatic aortic valve disorders and heart failure (circulatory); acid-base balance disorder (endocrine/metabolism); and abnormal blood chemistry (symptoms). In Study 2, the predictive models revealed that among individuals with DS and CHD, presence of health conditions such as congestive heart failure (circulatory), valvular heart disease and cardiac shunt (congenital), and pleural effusion and pulmonary collapse (respiratory) were associated with increased likelihood of surgical intervention.

CONCLUSIONS

Research efforts using EMRs and rigorous statistical methods could shed light on the complexity in health profile among individuals with DS and other IDDs and motivate precision-care development.

Long-Term Outcomes in Patients With Trisomy 21 and Obstructive Sleep Apnea

OBJECTIVE

To better understand the long-term health implications of obstructive sleep apnea (OSA) on patients with Trisomy 21 (T21) and the role of sleep surgery as a therapeutic intervention.

STUDY DESIGN

Retrospective large database review.

SETTING

The prevalence of OSA is as high as 75% in patients with T21. We sought to examine the cardiovascular, neurological, and endocrinological outcomes of patients with T21 10 years after their diagnosis of OSA.

METHODS

TriNetX, an electronic medical record database, was queried for health outcomes in patients with T21 after diagnosis of OSA. The group was further analyzed to identify those who underwent sleep surgery, including hypoglossal nerve stimulation, palatopharyngoplasty, or adenotonsillectomy.

RESULTS

Ten years after diagnosis, patients with OSA and T21 had a significantly higher incidence of death, myocardial infarction, cerebral infarction, heart failure, cardiac arrhythmia, ischemic heart disease, atrial fibrillation, essential hypertension, pulmonary hypertension, diabetes mellitus, and Alzheimer's disease compared to patients with T21 alone. Patients with OSA and T21 who underwent sleep surgery had significantly reduced incidence of adverse health outcomes compared to patients using continuous positive airway pressure.

CONCLUSION

Our findings suggest that patients with T21 and OSA are at higher risk of poor health outcomes, which may require closer monitoring for earlier diagnosis and management of comorbid conditions. Sleep surgery is a suitable treatment modality for mitigating the risk of adverse outcomes in this population and should be considered in patients who are eligible surgical candidates.

Voxel-based dysconnectomic brain morphometry with computed tomography in Down syndrome

OBJECTIVE

Alzheimer's disease (AD) is a major health concern for aging adults with Down syndrome (DS), but conventional diagnostic techniques are less reliable in those with severe baseline disability. Likewise, acquisition of magnetic resonance imaging to evaluate cerebral atrophy is not straightforward, as prolonged scanning times are less tolerated in this population. Computed tomography (CT) scans can be obtained faster, but poor contrast resolution limits its function for morphometric analysis. We implemented an automated analysis of CT scans to characterize differences across dementia stages in a cross-sectional study of an adult DS cohort.

METHODS

CT scans of 98 individuals were analyzed using an automatic algorithm. Voxel-based correlations with clinical dementia stages and AD plasma biomarkers (phosphorylated tau-181 and neurofilament light chain) were identified, and their dysconnectomic patterns delineated.

RESULTS

Dementia severity was negatively correlated with gray (GM) and white matter (WM) volumes in temporal lobe regions, including parahippocampal gyri. Dysconnectome analysis revealed an association between WM loss and temporal lobe GM volume reduction. AD biomarkers were negatively associated with GM volume in hippocampal and cingulate gyri.

INTERPRETATION

Our automated algorithm and novel dysconnectomic analysis of CT scans successfully described brain morphometric differences related to AD in adults with DS, providing a new avenue for neuroimaging analysis in populations for whom magnetic resonance imaging is difficult to obtain.

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Down syndrome arises from chromosomal non-disjunction during gametogenesis, resulting in an additional chromosome. This anomaly presents with intellectual impairment, growth limitations, and distinct facial features. Positive correlation exists between maternal age, particularly in advanced cases, and the global annual incidence is over 200,000 cases. Early interventions, including first and second-trimester screenings, have improved DS diagnosis and care. The manifestations of Down syndrome result from complex interactions between genetic factors linked to various health concerns. To explore recent advancements in Down syndrome research, we focus on the integration of artificial intelligence (AI) and machine learning (ML) technologies for improved diagnosis and management. Recent developments leverage AI and ML algorithms to detect subtle Down syndrome indicators across various data sources, including biological markers, facial traits, and medical images. These technologies offer potential enhancements in accuracy, particularly in cases complicated by cognitive impairments. Integration of AI and ML in Down syndrome diagnosis signifies a significant advancement in medical science. These tools hold promise for early detection, personalized treatment, and a deeper comprehension of the complex interplay between genetics and environmental factors. This review provides a comprehensive overview of neurodevelopmental and cognitive profiles, comorbidities, diagnosis, and management within the Down syndrome context. The utilization of AI and ML represents a transformative step toward enhancing early identification and tailored interventions for individuals with Down syndrome, ultimately improving their quality of life.

Common mental health disorders and cognitive decline in a longitudinal Down syndrome cohort

BACKGROUND

Down syndrome is the most common genetic cause of intellectual disability and Alzheimer's disease. In the general population, common mental disorders (CMDs), including anxiety, depression and obsessive-compulsive disorder, are linked to cognitive decline and higher risk for dementia. It is not known how CMDs affect longer-term cognitive outcomes in Down syndrome, and there is often diagnostic uncertainty in older people with Down syndrome and psychiatric comorbidity.

AIMS

To study the influence of CMDs on cognitive ability and whether they are related longitudinally to development of clinical signs of Alzheimer's disease in Down syndrome.

METHOD

We followed 115 individuals with Down syndrome, 27 of whom were diagnosed with a CMD, over approximately 3 years. Changes in cognitive and behavioural outcomes between baseline and follow-up assessment were analysed, with comparisons made between those with and without a comorbid CMD. Age, gender, apolipoprotein E status and level of intellectual disability were included as covariates.

RESULTS

No significant association between presence of a CMD and poorer performance on cognitive tasks or informant-rated decline over time was observed (P > 0.05).

CONCLUSIONS

Our results suggest that a diagnosis of a CMD does not have a significant negative effect on long-term cognitive or behavioural outcomes in individuals with Down syndrome. In individuals with stable or treated CMD, subsequent cognitive decline is likely indicative of Alzheimer's disease rather than a consequence of mental disorder.

Insights from the protein interaction Universe of the multifunctional "Goldilocks" kinase DYRK1A

Human Dual specificity tyrosine (Y)-Regulated Kinase 1A (DYRK1A) is encoded by a dosage-dependent gene located in the Down syndrome critical region of human chromosome 21. The known substrates of DYRK1A include proteins involved in transcription, cell cycle control, DNA repair and other processes. However, the function and regulation of this kinase is not fully understood, and the current knowledge does not fully explain the dosage-dependent function of this kinase. Several recent proteomic studies identified DYRK1A interacting proteins in several human cell lines. Interestingly, several of known protein substrates of DYRK1A were undetectable in these studies, likely due to a transient nature of the kinase-substrate interaction. It is possible that the stronger-binding DYRK1A interacting proteins, many of which are poorly characterized, are involved in regulatory functions by recruiting DYRK1A to the specific subcellular compartments or distinct signaling pathways. Better understanding of these DYRK1A-interacting proteins could help to decode the cellular processes regulated by this important protein kinase during embryonic development and in the adult organism. Here, we review the current knowledge of the biochemical and functional characterization of the DYRK1A protein-protein interaction network and discuss its involvement in human disease.