A data-driven study of Alzheimer's disease related amyloid and tau pathology progression

Amyloid-β is thought to facilitate the spread of tau throughout the neocortex in Alzheimer's disease, though how this occurs is not well understood. This is because of the spatial discordance between amyloid-β, which accumulates in the neocortex, and tau, which accumulates in the medial temporal lobe during ageing. There is evidence that in some cases amyloid-β-independent tau spreads beyond the medial temporal lobe where it may interact with neocortical amyloid-β. This suggests that there may be multiple distinct spatiotemporal subtypes of Alzheimer's-related protein aggregation, with potentially different demographic and genetic risk profiles. We investigated this hypothesis, applying data-driven disease progression subtyping models to post-mortem neuropathology and in vivo PET-based measures from two large observational studies: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Religious Orders Study and Rush Memory and Aging Project (ROSMAP). We consistently identified 'amyloid-first' and 'tau-first' subtypes using cross-sectional information from both studies. In the amyloid-first subtype, extensive neocortical amyloid-β precedes the spread of tau beyond the medial temporal lobe, while in the tau-first subtype, mild tau accumulates in medial temporal and neocortical areas prior to interacting with amyloid-β. As expected, we found a higher prevalence of the amyloid-first subtype among apolipoprotein E (APOE) ε4 allele carriers while the tau-first subtype was more common among APOE ε4 non-carriers. Within tau-first APOE ε4 carriers, we found an increased rate of amyloid-β accumulation (via longitudinal amyloid PET), suggesting that this rare group may belong within the Alzheimer's disease continuum. We also found that tau-first APOE ε4 carriers had several fewer years of education than other groups, suggesting a role for modifiable risk factors in facilitating amyloid-β-independent tau. Tau-first APOE ε4 non-carriers, in contrast, recapitulated many of the features of primary age-related tauopathy. The rate of longitudinal amyloid-β and tau accumulation (both measured via PET) within this group did not differ from normal ageing, supporting the distinction of primary age-related tauopathy from Alzheimer's disease. We also found reduced longitudinal subtype consistency within tau-first APOE ε4 non-carriers, suggesting additional heterogeneity within this group. Our findings support the idea that amyloid-β and tau may begin as independent processes in spatially disconnected regions, with widespread neocortical tau resulting from the local interaction of amyloid-β and tau. The site of this interaction may be subtype-dependent: medial temporal lobe in amyloid-first, neocortex in tau-first. These insights into the dynamics of amyloid-β and tau may inform research and clinical trials that target these pathologies.

Tau seeds from patients induce progressive supranuclear palsy pathology and symptoms in primates

Progressive supranuclear palsy is a primary tauopathy affecting both neurons and glia and is responsible for both motor and cognitive symptoms. Recently, it has been suggested that progressive supranuclear palsy tauopathy may spread in the brain from cell to cell in a 'prion-like' manner. However, direct experimental evidence of this phenomenon, and its consequences on brain functions, is still lacking in primates. In this study, we first derived sarkosyl-insoluble tau fractions from post-mortem brains of patients with progressive supranuclear palsy. We also isolated the same fraction from age-matched control brains. Compared to control extracts, the in vitro characterization of progressive supranuclear palsy-tau fractions demonstrated a high seeding activity in P301S-tau expressing cells, displaying after incubation abnormally phosphorylated (AT8- and AT100-positivity), misfolded, filamentous (pentameric formyl thiophene acetic acid positive) and sarkosyl-insoluble tau. We bilaterally injected two male rhesus macaques in the supranigral area with this fraction of progressive supranuclear palsy-tau proteopathic seeds, and two other macaques with the control fraction. The quantitative analysis of kinematic features revealed that progressive supranuclear palsy-tau injected macaques exhibited symptoms suggestive of parkinsonism as early as 6 months after injection, remaining present until euthanasia at 18 months. An object retrieval task showed the progressive appearance of a significant dysexecutive syndrome in progressive supranuclear palsy-tau injected macaques compared to controls. We found AT8-positive staining and 4R-tau inclusions only in progressive supranuclear palsy-tau injected macaques. Characteristic pathological hallmarks of progressive supranuclear palsy, including globose and neurofibrillary tangles, tufted astrocytes and coiled bodies, were found close to the injection sites but also in connected brain regions that are known to be affected in progressive supranuclear palsy (striatum, pallidum, thalamus). Interestingly, while glial AT8-positive lesions were the most frequent near the injection site, we found mainly neuronal inclusions in the remote brain area, consistent with a neuronal transsynaptic spreading of the disease. Our results demonstrate that progressive supranuclear palsy patient-derived tau aggregates can induce motor and behavioural impairments in non-human primates related to the prion-like seeding and spreading of typical pathological progressive supranuclear palsy lesions. This pilot study paves the way for supporting progressive supranuclear palsy-tau injected macaque as a relevant animal model to accelerate drug development targeting this rare and fatal neurodegenerative disease.

Increased KL-6 levels in moderate to severe COVID-19 infection

BACKGROUND

The global coronavirus disease 2019 (COVID-19) has presented significant challenges and created concerns worldwide. Besides, patients who have experienced a SARS-CoV-2 infection could present post-viral complications that can ultimately lead to pulmonary fibrosis. Serum levels of Krebs von den Lungen 6 (KL-6), high molecular weight human MUC1 mucin, are increased in the most patients with various interstitial lung damage. Since its production is raised during epithelial damages, KL-6 could be a helpful non-invasive marker to monitor COVID-19 infection and predict post-infection sequelae.

METHODS

We retrospectively evaluated KL-6 levels of 222 COVID-19 infected patients and 70 healthy control. Serum KL-6, fibrinogen, lactate dehydrogenase (LDH), platelet-lymphocytes ratio (PLR) levels and other biological parameters were analyzed. This retrospective study also characterized the relationships between serum KL-6 levels and pulmonary function variables.

RESULTS

Our results showed that serum KL-6 levels in COVID-19 patients were increased compared to healthy subjects (470 U/ml vs 254 U/ml, P <0.00001). ROC curve analysis enabled us to identify that KL-6 > 453.5 U/ml was associated with COVID-19 (AUC = 0.8415, P < 0.0001). KL-6 level was positively correlated with other indicators of disease severity such as fibrinogen level (r = 0.1475, P = 0.0287), LDH level (r = 0,31, P = 0,004) and PLR level (r = 0.23, P = 0.0005). However, KL-6 levels were not correlated with pulmonary function tests (r = 0.04, P = 0.69).

CONCLUSIONS

KL-6 expression was correlated with several disease severity indicators. However, the association between mortality and long-term follow-up outcomes needs further investigation. More extensive trials are required to prove that KL-6 could be a marker of disease severity in COVID-19 infection.

OUP accepted manuscript

Objective

This systematic review aims to assess how information from unstructured text is used to develop and validate clinical prognostic prediction models. We summarize the prediction problems and methodological landscape and determine whether using text data in addition to more commonly used structured data improves the prediction performance.

Materials and Methods

We searched Embase, MEDLINE, Web of Science, and Google Scholar to identify studies that developed prognostic prediction models using information extracted from unstructured text in a data-driven manner, published in the period from January 2005 to March 2021. Data items were extracted, analyzed, and a meta-analysis of the model performance was carried out to assess the added value of text to structured-data models.

Results

We identified 126 studies that described 145 clinical prediction problems. Combining text and structured data improved model performance, compared with using only text or only structured data. In these studies, a wide variety of dense and sparse numeric text representations were combined with both deep learning and more traditional machine learning methods. External validation, public availability, and attention for the explainability of the developed models were limited.

Conclusion

The use of unstructured text in the development of prognostic prediction models has been found beneficial in addition to structured data in most studies. The text data are source of valuable information for prediction model development and should not be neglected. We suggest a future focus on explainability and external validation of the developed models, promoting robust and trustworthy prediction models in clinical practice.