Alzheimer’s disease (AD) diagnosis remains challenging, with misdiagnoses and underdiagnoses being prevalent. There is an increased focus on putative, blood-based biomarkers that may be useful for the diagnosis as well as early detection of AD. Here, we used an unbiased combination of machine learning and functional network analyses to identify blood gene biomarker candidates in AD. Using supervised machine learning, we also determined whether these candidates were indeed unique to AD or whether they were indicative of other neurodegenerative diseases. Our analyses showed that genes involved in spliceosome assembly, RNA binding, transcription, protein synthesis, mitoribosomes, and NADH dehydrogenase were the best-performing genes for identifying AD patients relative to cognitively healthy controls. This transcriptomic signature, however, was not unique to AD, and subsequent machine learning showed that this signature could also predict PD and ALS relative to controls without neurodegenerative disease. Combined, our results suggest that mRNA from whole blood can indeed be used to screen for patients with neurodegeneration but may be less effective in diagnosing the specific neurodegenerative disease.

1. Shvetcov
2. Thomson
3. Spathos

A.N. Cho

H.M. Wilkins

S.J. Andrews

1. Delerue

T.A. Couttas

J.K. Issar

1. Isik
2. Kaur
3. Drummond
4. Dobson-Stone

S.L. Duffy, N.M. Rogers, D. Catchpoole, W.A. Gold, R.H. Swerdlow, D.A. Brown, C.A. Finney.

Alzheimer’s disease (AD) is the most common form of dementia. There is no treatment and AD models have focused on a small subset of genes identified in familial AD. Microarray studies have identified thousands of dysregulated genes in the brains of patients with AD yet identifying the best gene candidates to both model and treat AD remains a challenge. We performed a meta-analysis of microarray data from the frontal cortex (n = 697) and cerebellum (n = 230) of AD patients and healthy controls. A two-stage artificial intelligence approach, with both unsupervised and supervised machine learning, combined with a functional network analysis was used to identify functionally connected and biologically relevant novel gene candidates in AD. We found that in the frontal cortex, genes involved in mitochondrial energy, ATP, and oxidative phosphorylation, were the most significant dysregulated genes.

C.A. Finney, F. Delerue, W.A. Gold, D.A. Brown, A. Shvetcov

Spinal cord injury (SCI) occurs when the spinal cord is damaged from either a traumatic event or disease. SCI is characterised by multiple injury phases that affect the transmission of sensory and motor signals and lead to temporary or long-term functional deficits. There are few treatments for SCI. Estrogens and estrogenic compounds, however, may effectively mitigate the effects of SCI and therefore represent viable treatment options. This review systematically examines the pre-clinical literature on estrogen and estrogenic compound neuroprotection after SCI. Several estrogens were examined by the included studies: estrogen, estradiol benzoate, Premarin, isopsoralen, genistein, and selective estrogen receptor modulators. Across these pharmacotherapies, we find significant evidence that estrogens indeed offer protection against myriad pathophysiological effects of SCI and lead to improvements in functional.

A. Shvetcov, M.J. Ruitenberg, F. Delerue, W.A. Gold, D.A. Brown, C.A. Finney.

Silent infarcts (SI) are subcortical cerebral infarcts occurring in the absence of typical ischemia symptoms and are linked to cognitive decline and dementia development. There are no approved treatments for SI. One potential treatment is tamoxifen, a selective estrogen receptor modulator. It is critical to establish whether treatments effectively target the early consequences of SI to avoid progression to complete injury. We induced SI in the dorsal hippocampal CA1 of rats and assessed whether tamoxifen is protective 24 h later against cognitive deficits and injury responses including gliosis, apoptosis, inflammation and changes in estrogen receptors (ERs). SI led to subtle cognitive impairment on the object place task, an effect ameliorated by tamoxifen administration. SI did not lead to detectable hippocampal cell loss but increased apoptosis, astrogliosis, microgliosis and inflammation.

C.A. Finney, A. Shvetcov, R.F. Westbrook, M.J. Morris, N.M. Jones

C.A. Finney, N.M. Jones, M.J. Morris.