Further understanding the connection between Alzheimer’s disease and Down syndrome

2.1 |. Biological underpinnings of DS and AD

Neuropathological studies of DS brains demonstrate that by age 40, there are changes fully consistent with the neuropathological diagnosis of AD. Interestingly, comparisons of DS brains from individuals with and without dementia have demonstrated the same differences in Aβ burden in the frontal cortex and striatum, but greater tau pathology and atrophy in the brains of individuals with dementia.²⁴ Some work suggests that there may be a greater role of tau lesions in the onset of dementia.¹⁸ Single gene expression profiling of tau containing cortical projection neurons revealed a differential downregulation of several gene classes in the brains of individuals with DS and dementia compared to individuals with DS but no dementia, including genes related to Aβ and tau biology, neuro-transmission, and cell death, suggesting potential novel drug discovery targets.²⁴

Dendritic spines are integral to synaptic plasticity and memory storage. Spine pathology has been reported not only in traumatic brain injury and neurodegenerative diseases including AD, but has also been reported in DS.²⁵ Spine density declines significantly and early in brain regions affected by AD pathology.²⁶ Reduced spine number and altered spine morphology also characterize the DS brain. Molecular pathways underlying spine defects in DS include those involving DSCR1, which helps regulate spine morphogenesis, and DYRK1A, which regulates spine formation and actin dynamics.²⁷

Trisomic astrocytes also play a role in spine pathology and reduced spine density.²⁸ Co-culture of human DS astrocytes with rat hippocampal neurons showed deficient secretion of thrombospondin 1 (TSP-1), a protein that modulates spine density and morphology in DS astrocytes.²⁹ Increased interferon (IFN) signaling also inhibits TSP-1 secretion in DS astrocytes.³⁰ These overlapping mechanisms suggest the potential for therapeutic approaches that target TSP-1, IFN, and amyloid in the DS brain.

Cerebrovascular pathology seen in people with DS-AD differs from those with sporadic AD. Cerebral amyloid angiopathy (CAA) occurs more frequently and is more severe in individuals with DS-AD compared to those with sporadic AD, probably as a result of APP overexpression.^31,32 AD-specific neuropathology is also associated with CAA small vessel disease, which can contribute to the development of dementia. Further, CAA accumulation may reflect an imbalance between Aβ production and clearance and exacerbate Aβ plaque deposition,³³ although this has not been explored systematically in people with DS. Further, the presence of CAA may lower the threshold for the development of cognitive impairments.³⁴ However, other vascular pathologies such as hypertension, atherosclerosis, and arteriosclerosis are rarely seen in DS, and in comparison with individuals with duplication of APP (thus a similar overdose of amyloid protein), which would suggest that individuals with DS appear to have some degree of protection against severe CAA.³⁵ However, given that CAA is higher in DS, it is likely that APP overexpression overrides these systemic protective factors. The consequences of increased CAA in the DS and sporadic AD brain include an increased frequency of microhemorrhages, which increase exponentially with age and can contribute to earlier onset of dementia.^31,36 CAA magnetic resonance imaging (MRI)-related abnormalities including micro-and macrohemorrhages and white matter malformations are found more frequently in DS (and in ADAD) than in sporadic AD or healthy controls, however; this is likely due to a multitude of factors and may be independent of one another.³⁷ If mechanisms contributing to AD pathology are different in DS-AD compared to sporadic AD, this may have implications regarding therapeutic development for DS-AD.

Even non-DS forms of AD may result, in part, from the occur-rence of chromosome 21 trisomy in other cells—a phenomenon known as mosaic aneuploidy caused by nondisjunction during mitosis.³⁸ Trisomy 21 mosaicism has been observed in cells from people with sporadic AD, familial AD, and autosomal dominant presenilin mutations.³⁹ The number of hyperploid neurons increases in relation to AD-related pathophysiological changes in the brain but decreases at later stages of disease progression because hyperploid neurons are more prone to cell death.⁴⁰ Increased aneuploidy and apoptosis have also been observed in other neurodegenerative diseases such as frontotemporal lobar degeneration (FTLD)⁴¹ and Huntington’s disease (HD)⁴² and in developmental disorders such as autism.⁴³ These findings suggest that genomic instability may represent a common mechanism across neurodegenerative and neurodevelopmental diseases and could be a therapeutic target. They further suggest that DS-AD and other co-occurring conditions may arise in people with DS through both developmental and aging-related cell cycle defects leading to variable mosaic aneuploidy in addition to trisomy 21. This could explain the high level of variability.⁴⁴

2.2 |. Regional pathology

In DS, amyloid pathology begins in the late teens with deposits of diffuse plaques initially within the temporal lobe consistent with Thal phase 1,⁴⁵ then spreading to neocortical regions and the hippocampus (Thal phase 2), reaching subcortical regions (Thal phases 3 and 4) and the cerebellum (Thal phase 5) by the late 40s. After 50 years of age, every region of the brain, including the cerebellum, is littered with amyloid plaques (Thal phase 5).⁴⁵ Over the lifespan, amyloid pathology begins as early as age 13 years with a pattern typical of AD typically reached by 55 years of age.⁴⁶ CAA begins at ≈40 years of age, ≈25 years after initial deposition of Aβ as plaques.³¹

The earliest sites of tau pathology include the entorhinal and transentorhinal cortex, spreading to the hippocampus, then temporal cortex and eventually to other regions of cerebral cortex, finally reaching the visual association cortex and primary visual cortex.⁴⁶ Tau pathology begins at ≈35 years of age within the hippocampus and spreads to neocortical regions after 45 years of age.

2.3 |. Co-occurring conditions in DS-AD

Hypothyroidism, epilepsy, anemia, and weight loss are more common in people with DS and dementia compared to those without dementia.⁴⁷ Early-onset epilepsy and multi-morbidity may be associated with earlier onset of dementia;⁴⁸ however, the contribution of other co-occurring conditions (such as hypothyroidism) to both age of onset and survival of individuals with DS-AD appears relatively modest.¹¹ Diagnostic issues may explain some of the variability in age of onset. Individuals with more severe intellectual disability and sensory impairment may be more difficult to diagnose. In addition, studies suggest that individuals living at home rather than in care facilities are diagnosed earlier, possibly because families are more sensitive to subtle changes in cognition and function.¹¹

In individuals with DS, dementia is also associated with a five-fold increase in mortality rate compared to individuals without dementia; age is also a confounder that should be considered.⁴⁸ In individuals with DS, it is unclear if apolipoprotein E (ApoE) ε4 impacts AD and mortality risk as in the general population; some studies suggest the risk is similar and some studies have suggested otherwise.^49–51 Seizures are also linked to dementia in DS, with new-onset epilepsy often appearing in the early stages of dementia.⁵² Seizures may eventually occur in >70% of individuals with DS-AD,⁶ which are associated with accelerated cognitive decline⁵³ and increased mortality.⁴⁸

2.4 |. Risk factors in DS-AD

In the general population, studies have shown an association between risk of developing AD and lifestyle factors such as diet, physical activity, and social and cognitively stimulating leisure activities.^54–56 Adults with DS often have maladaptive lifestyles (eg, low physical activity and few social or leisure activities); thus, researchers have begun to investigate the association between lifestyle factors and biomarkers of early AD neuropathology and cognitive decline in DS. In a recent study, adults with DS without dementia who engaged in higher levels of cognitively stimulating and social leisure activity experienced less decline across three years in episodic memory. Moreover, leisure activity at baseline mitigated the association between an increase in Aβ assessed via positron emission tomography (PET) imaging and decline in episodic memory across three years, suggesting that these behaviors could play a role in benefiting cognition in the early stages of AD in DS.⁵⁷

In the general non-DS population, high blood pressure, hypertension, and other vascular risk factors appear to increase the risk of developing dementia as well as cerebrovascular and AD pathology, presumably by putting white matter at risk of injury.⁵⁸ Although hypertension is low in DS, high rates of cerebrovascular disease (CVD) including microbleeds are seen, suggesting vascular contributions to the DS-AD phenotype need to be better understood.³⁷ It is possible that lifestyle factors that reduce risk of vascular disease could potentially also be an important target for intervention of dementia.

Sleep is another factor that may play a bi-directional role in the development of AD.⁵⁹ Sleep disorders are not only more prevalent in AD but also may predict future development of AD.⁶⁰ Sleep is thought to increase the clearance of toxins such as amyloid.⁶¹ Adults with DS frequently experience sleep disruption, which could have multiple causes, and also have a high prevalence of obstructive sleep apnea (OSA),⁶² which is a risk factor for AD.⁶³ OSA has been hypothesized to be associated with cognitive decline in DS.⁶⁴ In large population studies of elderly individuals without DS, OSA is associated with increased amyloid burden as individuals age.⁶⁵ The high prevalence of sleep disruption in DS suggests that this population may provide a window into understanding the links among sleep, amyloid, and dementia.⁶²

Cognitive reserve is the idea that individuals who engage in more cognitively stimulating lifestyles, often measured by level of formal education or complexity of employment and mentally engaging activities (eg, crossword puzzles), better tolerate early AD pathology.⁶⁶ Specifically, such lifestyles are posited to promote the recruitment of alternative neural networks and/or foster more efficient use of existing networks to cope with early AD pathophysiologic insult (Stern, 2012).⁶⁷ In aging non-DS populations, cognitively stimulating lifestyles have been found to be associated with reduced Aβ accumulation⁶⁸ and a longer preclinical AD stage, in which early AD neurodegeneration is present but cognitive functioning remains intact (eg, Kemppainen et al.⁶⁹). Historically, adults with DS have experienced lifestyles with low cognitive stimulation as a result of limited adult disability services, low community involvement, and a lack of employment opportunities.^70,71 However, more recent shifts in the disability and employment system have provided a pathway for more cognitively stimulating lifestyles. The extent to which these shifts, and/or variability in level of cognitive stimulation, delay the onset of AD in the DS population needs more research attention.

3.1 |. Imaging biomarkers

Neuroimaging provides insight into the pathogenesis and progression of AD, enables diagnosis, and provides biomarkers for drug discovery and clinical trials.⁷³ When Jack et al. published the landmark hypothetical model of dynamic biomarkers of the AD pathological cascade in 2010, the major imaging modalities included PET to assess fibrillar Aβ plaque deposition (Aβ PET) and two measures of neurodegeneration: fluorodeoxyglucose PET (FDG-PET), a measure of brain metabolism, and structural MRI to assess brain atrophy.⁷⁴ It is worth noting that while these tools have advanced biomarker development, they may not yet detect the earliest protein deposits, containing diffuse, non-fibrillar plaques. Over the years, many other imaging modalities have been applied to the study of AD and related dementias; examples of these modalities include additional PET ligands to image tau and other pathologies, functional MRI (fMRI) to examine the functional activity of brain networks, diffusion weighted MRI (DW-MRI) to assess microstructure, electroencephalography, and retinal imaging.⁷⁵

Cross-sectional studies of individuals with DS without dementia evaluated with Pittsburgh compound B (PiB-PET) demonstrated that when compared to individuals without DS, there was a similar prevalence of elevated amyloid in the absence of cognitive symptoms. In addition, it appears that the deposition of Aβ follows a similar time course, becoming evident about 20 years before the median age of symptom onset, however, at an earlier age of onset.^76–79 There is a wide variability in the age of PiB-PET positivity onset.⁵⁷ Individuals with DS show a pattern of Aβ accumulation—initiating in the striatum—similar to patterns seen in people with ADAD but different from what is seen in sporadic AD in which Aβ deposition predominates in the neocortex.^45,80 Longitudinal studies suggested that AD pathogenesis shifts from Aβ-negative to Aβ-positive earlier in DS compared to the general population but does not progress at a faster rate.⁸¹

Assessment of tau burden by PET scanning in people with DS shows similarities to the binding pattern and progression observed in non-DS AD.⁸² Specifically, tau accumulation is associated with amyloid positivity and age, as well as with progressive neurodegeneration measurable using FDG and MRI. Accumulation of tau correlates with cognitive decline, as do AD-specific hypometabolism and atrophy.⁸² Studies are ongoing to assess longitudinally the relationship of tau burden to cognitive and behavioral measures in DS.

The ABC-DS Project includes a study examining the correlation among Aβ burden, hypometabolism, and gray matter volume reductions in people with DS. FDG-PET can be used to assess brain metabolism; it is thought to provide a measure of glucose uptake and may mirror synaptic activity. In this same study, regional brain volume is assessed by MRI. In sporadic AD, changes in glucose uptake are seen prior to AD clinical symptom development and follow a characteristic pattern. In ADAD, one study suggests that glucose metabolism declines about 5 to 8 years before symptom onset and in another 14 years before expected onset.^83,84 In DS-AD as in sporadic AD, glucose hypometabolism and AD-related gray matter volume reductions occur only in older subjects with higher Aβ burden.⁸⁵ Interestingly, early work using FDG-PET in nondemented adults with DS suggests hypermetabolism in the entorhinal cortex prior to the development of dementia, suggesting a possible compensatory effect.⁸⁶ These studies confirm that glucose hypometabolism and brain atrophy both represent biomarkers of neurodegeneration in DS.

With lower rates of hypertension compared to the general population, people with DS provide a window into the role of CVD in dementia without the confound of systemic vascular disease.⁸⁷ CVD does not appear to be associated with elevated levels of Aβ (as measured by PET), suggesting that these features are not driven by Aβ pathophysiological changes. CVD seen in individuals with DS may be related to specific AD pathophysiological changes or may be independent; this is an area of further research needed to better understand the roles these factors may play related to clinical progression. In DS, markers of CVD visualized with MRI—white matter hyperintensities (WMH), micro-bleeds, infarcts, and enlarged perivascular spaces—increase in a dose-response manner across dementia-related diagnostic groups.

Changes in structural connectivity in white matter, which are detectable using DW-MRI, are also under investigation as potential biomarkers of AD progression in studies of individuals with DS-AD. As young as 35 years of age, people with DS show frontal white matter integrity losses that correlate with cognitive function.⁸⁸ In sporadic AD, regional structural changes in white matter across the continuum of disease begin in the preclinical stage, with decreased connectivity associated with increased Aβ burden.⁸⁹ Functional connectivity deficits of the default mode network assessed using fMRI⁹⁰ also show changes correlating with amyloid deposition in people with DS.

3.2 |. Non-imaging biomarkers

Low levels of cerebrospinal fluid (CSF) Aβ42 (soluble) and elevated levels of total tau (t-tau) and phosphorylated tau (p-tau) are detectable in people with mild cognitive impairment (MCI) or AD. There have been a limited number of CSF studies in individuals with DS. These studies show that elevated levels of Aβ42 and other amyloid species are apparent in early childhood, although CSF tau levels remain low. As these individuals age, however, CSF Aβ42 levels decline and CSF tau levels increase.⁹¹ To understand Aβ and tau dynamics in individuals with DS, further CSF studies are needed, as well as studies of other blood-based biomarkers that would not require individuals to undergo lumbar puncture (LP).

The DABNI study demonstrated good diagnostic performance of CSF AD-associated biomarkers and plasma neurofilament light (NfL, a component of the axonal cytoskeleton, is a marker of neuronal damage and degeneration⁹²) in adults with DS;⁹³ and that LP is a safe procedure in this population.⁹⁴

While not specific to AD,⁹⁵ CSF NfL concentrations increase during disease progression.⁹⁶ In the context of DS, in which the differential diagnosis often involves non-degenerative conditions (comorbidities) that do not elevate NfL levels, it is also specific for measures related to neurodegeneration. Similarly, plasma NfL concentrations increase as cognition declines in the non-DS population, and importantly, NfL is the only biomarker for which there is good correlation between plasma and CSF levels.⁹⁷ In the ADAD population, serum NfL predicted both cortical thinning and cognitive change in the presymptomatic stage of disease.⁹⁸ In people with DS, plasma NfL levels appear to increase with age, can distinguish between DS and DS-AD, and are associated with decreased adaptive behavior scores, supporting its role as a predictive biomarker of dementia in DS.^93,99–101 Plasma NfL levels correlate with standard biomarkers of AD pathology such as amyloid PET along with markers of neurodegeneration (regional cerebral glucose metabolism as assessed with FDG-PET and hippocampal atrophy) as well as cognitive and functional decline.¹⁰²

Endophenotype strategies are also being used to identify biomarker profiles for diagnosing or predicting risk of AD in different populations, including DS.¹⁰³ This approach groups individuals by endophenotypes established using cognitive, biochemical, genetic, neuroimaging, and behavioral markers to identify subgroups who may respond to different therapeutic approaches. For example, a proinflammatory endophenotype may be able to predict who would respond to anti-inflammatory therapy. Metabolic and depressive endophenotypes may also prove relevant to better understanding and developing treatments for DS-AD.

Exosomes are small, endosomal-derived vesicles released into the bloodstream from all cells, including neurons, that contain proteins, lipids, messenger RNA, long non-coding RNA, and microRNA, as well as cell-identifying surface markers. Exosomes may have potential to provide more accurate disease biomarkers, because their cargo contains specific cellular content from the cell of origin, that is, brain tissue.¹⁰⁴ Exosomes facilitate cell signaling and transfer of cellular pathogens among cells and help in the removal of waste products.¹⁰⁵ In AD, exosomes are thought to play a role in Aβ clearance and possibly in the cell-to-cell spread of tau and Aβ peptides.⁹⁷ It has been shown that AD biomarkers including Aβ and p-tau are present in the cargo of neuron-as well as astrocyte-derived exosomes many years before any onset of dementia symptoms in the general population.^106,126 A study of neuron-derived exosomes purified from the blood of individuals with DS suggested that levels of exosomal Aβ peptides and p-tau are significantly elevated in early life compared to individuals without DS,¹⁰⁵ decades prior to the onset of dementia. The findings in that study demonstrated no association between age and exosomal Aβ42 levels, but a continuous increase in levels of p-S396-tau with the diagnosis of dementia in DS-AD. Levels of these exosomal biomarkers also correlate with cognitive measures and with some CSF biomarkers in the DABNI study. Further studies in additional cohorts will be needed to validate these findings but initial data suggest that exosomal cargo biomarkers may provide a more targeted biomarker method without having to perform repeated LPs in those with DS, because we can isolate exosomes originating only from neurons and glia from a single blood sample.¹²⁷

The blood-brain barrier and choroid plexus are likely to play a role in determining pathology by controlling which biochemical factors, sub-cellular fractions, or cell subtypes traverse into and out of the brain parenchyma; some of which may be putative biomarkers with roles such as neuroprotection distributed in various fluid compartments being measured.^107,108

4.1 |. Pipeline of clinical interventions

At the time of the workshop, only a few clinical trials were focused on DS-AD, yet there are many potential pharmacological and non-pharmacological approaches that may be able to benefit people with DS-AD. Moreover, successful trials in DS may translate readily to AD in the non-DS population.³ There is a strong rationale for testing anti-Aβ therapies in the DS population and such approaches may be even more efficacious in this population due to less age-related co-occurring conditions and fewer non-amyloid vascular risk factors.

The anti-Aβ vaccine ACI-24 is being evaluated in an NIH-funded phase Ib study in adults with DS (NCT02738450). It is a multi-center, double-blind, randomized, placebo-controlled, dose-escalation study of the safety, tolerability, and immunogenicity of ACI-24 in adults with DS. The study is fully enrolled with 16 adults with DS, aged 25–45 years. Primary endpoints include measures of safety, tolerability, and immunogenicity. Secondary endpoints include effects on biomarkers of AD pathology as well as cognitive and clinical function. Another study in DS involved scyllo-inositol, which is an endogenous myo-inositol isomer that has shown amyloid anti-aggregation effects.^114,115 It has also shown amyloid-lowering effects in CSF and brain and demonstrated beneficial trends on cognition in mild AD.¹¹⁶ A phase II randomized, double-blind, placebo-controlled study of oral scyllo-inositol, which included pharmacokinetic studies, has been successfully completed in 24 adults with DS.¹¹⁷

Normalization of APP gene dose represents a potential therapeutic strategy to further explore. In a mouse model of DS, deleting one copy of APP eliminated endosomal pathology.¹¹⁸ Reducing APP gene dose could potentially be accomplished by targeting APP mRNA levels with antisense oligonucleotides (ASOs), APP mRNA translation, APP processing with γ-secretase modulators, removal of Aβ with immunotherapy, or reducing a key regulator of intracellular trafficking, Ras related protein a4 (Rab5), activation with ASOs.

Non-Aβ treatment approaches such as those that target tau, microglial function, interferon-related signal transduction, oxidative stress, or inflammatory events could also be beneficial in DS-AD. For example, granulocyte-macrophage colony-stimulating factor (GM-CSF), a cytokine produced by the innate immune system, has been shown to reduce Aβ deposition in vivo and reverse memory deficits in aged DS and normal mice. However, GM-CSF, as a therapeutic, may have side effects that should be considered for therapeutic development.¹¹⁹

4.2 |. Practical considerations for clinical trials

The conduct of clinical trials in the DS population raises many methodological challenges. Given the wide variability in baseline intellectual capabilities, the demands on memory, attention, and language ability must be taken into account for successful and accurate cognitive assessment and interpretation of results. Indeed, in the clinic, there can be a tremendous challenge in arriving at a firm diagnosis of AD dementia. The main defining feature of dementia in the typical population is a decline from the baseline level of function and performance of daily skills. Consensus guidelines for the evaluation and management in DS have been proposed.⁷¹ In the absence of a personal historian who can accurately attest to an individual’s baseline level of functioning, the assessment of a reported change may be exponentially more complicated in DS. Moreover, the earliest signs of dementia in adults with DS may be subtle and will often require an astute observer to identify such changes. The history is the cornerstone of a dementia diagnosis. Currently, a thorough history must be obtained to build evidence consistent with declining cognition while probing for other features that might suggest other contributing factors. These contributing factors include concomitant medications, recent medical illnesses (including laboratory testing such as TSH and Vitamin B12), changes in health status (vision or hearing), or recent life events that can impact psychosocial functioning. Although some valid measures exist,^120,121 there is currently no standard clinical instrument for the assessment of dementia in adults with DS. Assessment of decline should therefore always be individualized and patient specific, with judgments made on the basis of deterioration from the patient’s own individual baseline level of functioning.

Moreover, thoughtfully designed cognitive testing sessions using validated instruments that reflect clinical meaningfulness will be critical. In addition, developing inclusion and exclusion criteria for clinical trials in DS-AD can be challenging for several reasons including the high rate of sensory impairments and other health concerns, which may limit the generalizability of the sample.¹²² Identifying prodromal symptoms or MCI in people with DS may also be difficult because of pre-existing impairments. Assessment tools must be able to demonstrate change in participants, which may require verbal abilities not present in all potential trial participants; however, it is also important to include people representative of the larger DS population, and not limit participation to those who are more cognitively advanced or motivated. In addition, trial design should take into consideration factors such as where the participant lives—in the home verses an assisted living facility—and how this may contribute to overall study engagement. This coincides with the role the care provider may play in trial participation, such as transport and identification of behavioral changes.

There is currently no generally accepted validated test battery to monitor medication effects in DS, and the variability in cognition and behavior among people with DS makes it difficult to assess treatment outcomes. A working group assembled by NICHD has identified measures that may be modifiable for use in people with DS to assess multiple cognitive and behavioral domains; however, additional work is needed to evaluate and validate these measures.¹²³ Recently, there has been progress in demonstrating the sequence of decline events and onset of symptoms during the prodromal stages of AD in DS. These studies are using standardized informant ratings of symptoms with tools such as the CAMDEX-DS questionnaire¹²⁴ to explore changes in behaviors related to frontal lobe dysfunction, and comprehensive cognitive test batteries such as the LonDownS battery to demonstrate early decline in memory and attention.

While neuroimaging biomarkers have demonstrated their value in AD clinical trials, DS-AD participants may have increased challenges because of the difficulty they may have in keeping still during the scan session and/or the length of the scan; these challenges increase as the disease progresses. As such, use of neuroimaging biomarkers may become more problematic as individuals with DS progress in AD. This complication should be considered as these biomarkers are developed and validated for potential use in clinical trials.

Finally, selection of appropriate interventions to evaluate in the DS-AD population should consider factors such as the increased CAA and inflammation in these individuals for both evaluation of interventions and cross-target complexities.