Down syndrome (DS) is caused by trisomy of chromosome 21 (Hsa21) and is associated with a number of deleterious phenotypes, including learning disability, heart defects, early-onset Alzheimer's disease and childhood leukaemia. Individuals with DS are affected by these phenotypes to a variable extent; understanding the cause of this variation is a key challenge. Here, we review recent research progress in DS, both in patients and relevant animal models. In particular, we highlight exciting advances in therapy to improve cognitive function in people with DS and the significant developments in understanding the gene content of Hsa21. Moreover, we discuss future research directions in light of new technologies. In particular, the use of chromosome engineering to generate new trisomic mouse models and large-scale studies of genotype–phenotype relationships in patients are likely to significantly contribute to the future understanding of DS.

Wiseman et al. show that triplication of genes other than APP is sufficient to exacerbate Aβ deposition and associated cognitive changes in a mouse model of Down syndrome – Alzheimer’s disease. This occurs independently of changes to γ-secretase but results from a novel mechanism that lowers the soluble Aβ40/42 ratio.

Down syndrome (DS) is caused by trisomy of chromosome 21 (Hsa21) and presents a complex phenotype that arises from abnormal dosage of genes on this chromosome. However, the individual dosage-sensitive genes underlying each phenotype remain largely unknown. To help dissect genotype – phenotype correlations in this complex syndrome, the first fully transchromosomic mouse model, the Tc1 mouse, which carries a copy of human chromosome 21 was produced in 2005. The Tc1 strain is trisomic for the majority of genes that cause phenotypes associated with DS, and this freely available mouse strain has become used widely to study DS, the effects of gene dosage abnormalities, and the effect on the basic biology of cells when a mouse carries a freely segregating human chromosome. Tc1 mice were created by a process that included irradiation microcell-mediated chromosome transfer of Hsa21 into recipient mouse embryonic stem cells. Here, the combination of next generation sequencing, array-CGH and fluorescence in situ hybridization technologies has enabled us to identify unsuspected rearrangements of Hsa21 in this mouse model; revealing one deletion, six duplications and more than 25 de novo structural rearrangements. Our study is not only essential for informing functional studies of the Tc1 mouse but also (1) presents for the first time a detailed sequence analysis of the effects of gamma radiation on an entire human chromosome, which gives some mechanistic insight into the effects of radiation damage on DNA, and (2) overcomes specific technical difficulties of assaying a human chromosome on a mouse background where highly conserved sequences may confound the analysis. Sequence data generated in this study is deposited in the ENA database, Study Accession number: ERP000439.

Multi-atlas segmentation propagation has evolved quickly in recent years, becoming a state-of-the-art methodology for automatic parcellation of structural images. However, few studies have applied these methods to preclinical research. In this study, we present a fully automatic framework for mouse brain MRI structural parcellation using multi-atlas segmentation propagation. The framework adopts the similarity and truth estimation for propagated segmentations (STEPS) algorithm, which utilises a locally normalised cross correlation similarity metric for atlas selection and an extended simultaneous truth and performance level estimation (STAPLE) framework for multi-label fusion. The segmentation accuracy of the multi-atlas framework was evaluated using publicly available mouse brain atlas databases with pre-segmented manually labelled anatomical structures as the gold standard, and optimised parameters were obtained for the STEPS algorithm in the label fusion to achieve the best segmentation accuracy. We showed that our multi-atlas framework resulted in significantly higher segmentation accuracy compared to single-atlas based segmentation, as well as to the original STAPLE framework.

BackgroundDown syndrome (DS), caused by chromosome 21 trisomy, is associated with an ultra-high risk of dementia due to Alzheimer’s disease (AD), driven by amyloid precursor protein (APP) gene triplication. Understanding relevant molecular differences between those with DS, those with sporadic AD (sAD) without DS, and controls will aid in understanding AD development in DS. We explored group differences in plasma concentrations of amyloid-β peptides and tau (as their accumulation is a characteristic feature of AD) and cytokines (as the inflammatory response has been implicated in AD development, and immune dysfunction is common in DS).MethodsWe used ultrasensitive assays to compare plasma concentrations of the amyloid-β peptides Aβ40 and Aβ42, total tau (t-tau), and the cytokines IL1β, IL10, IL6, and TNFα between adults with DS (n = 31), adults with sAD (n = 27), and controls age-matched to the group with DS (n = 27), and explored relationships between molecular concentrations and with age within each group. In the group with DS, we also explored relationships with neurofilament light (NfL) concentration, due to its potential use as a biomarker for AD in DS.ResultsAβ40, Aβ42, and IL1β concentrations were higher in DS, with a higher Aβ42/Aβ40 ratio in controls. The group with DS showed moderate positive associations between concentrations of t-tau and both Aβ42 and IL1β. Only NfL concentration in the group with DS showed a significant positive association with age.ConclusionsConcentrations of Aβ40 and Aβ42 were much higher in adults with DS than in other groups, reflecting APP gene triplication, while no difference in the Aβ42/Aβ40 ratio between those with DS and sAD may indicate similar processing and deposition of Aβ40 and Aβ42 in these groups. Higher concentrations of IL1β in DS may reflect an increased vulnerability to infections and/or an increased prevalence of autoimmune disorders, while the positive association between IL1β and t-tau in DS may indicate IL1β is associated with neurodegeneration. Finally, NfL concentration may be the most suitable biomarker for dementia progression in DS. The identification of such a biomarker is important to improve the detection of dementia and monitor its progression, and for designing clinical intervention studies.