Detecting Alzheimer's Before it's too Late: BDNF and Hippocampal Texture to the Rescue?

  Over the years the world has seen a substantial increase in Alzheimer's disease (AD)., plaguing the elderly of all demographics, and undoubtedly becoming one of the most pressing future public health crises. The ultimate cause of AD is a part of neuroscience that is still evolving and bridled in heated debates. However, it is relatively well understood that AD is characterized by cortical thinning, hippocampal atrophy, enlargement of ventricles, etc. that lead to loss of executive function, memory and language decline, etc. Moreover, the molecular underpinnings of AD are further associated with the accumulation of β-amyloid plaques, p-Tau tangles, whose accumulation leads to an increase of inflammation mediated by astrocytes and microglia, which then mediate an increase of more β-amyloid plaques, p-Tau tangles. It soon becomes clear how this vicious cycle can wreak havoc on the human brain, leading to AD. Despite this understanding of some of the molecular mechanisms at play it is nearly impossible to detect AD early enough to administer clinically significant treatment. However, recently published studies have utilized various biomarkers such as brain-derived neurotrophic factor (BDNF), as well as hippocampal texture in hopes of detecting AD early enough.

The article “Serum pro-BDNF levels Correlate with Phospho-Tau Staining in Alzheimer’s Disease”, published by Krishna Bharani and colleagues in the Journal of Neurobiology of Aging aimed to link the levels of pro-BDNF in serum and in the brain to the onset and progression of AD. To clarify, Pro-BDNF is the precursor molecule to mBDNF. The researchers were able to establish a brain bank, where they obtained brains from AD patients (n=19) and brains from healthy patients (n=12). Here they looked at four regions of interest: the dorsolateral prefrontal cortex (BA46), the hippocampus, and the entorhinal cortex. More specifically when looking at the hippocampus, the researchers examined the levels of β-amyloid plaques, tangles, NeuN, GFAP, pTau tangles, and the concentration of the BDNF receptors TrkB and p75NTR. It should be noted that the TrkB receptor is typically associated with the promotion of neuronal survival, while p75NTR is associated with the instigation of apoptosis. After completing ELISA and western blot assays it becomes apparent that the hippocampus of the AD brains had significantly more β-amyloid plaques and tangles, which should not come by as too much of a surprise; however, what the researchers did note was that the AD brain had higher   p75NTR receptor expression rates than that of the control brains. Furthermore, TrkB was much lower in the AD brains, as compared to the control brains. Since BDNF levels in AD brains were measured to be lower, it is logical that TrkB would be in a lower concentration, as well. The study also found that serum pro-BDNF levels were negatively correlated to hippocampal BDNF, possibly because pro-BDNF is primarily produced to be sent to the brain and mitigate damage. Moreover, serum pro-BDNF was found to be positively correlated to hippocampal-tau. This plethora of evidence suggests a relationship between BDNF and its receptors to the progression of AD.

With a better understanding of the molecular mechanisms behind AD, as well as some novel evidence pointing to the potential of using biomarkers to detect AD earlier on, we can better appreciate the complexity of this neurological disorder. As it so happens a recent study published by Lauge Sørensen and colleagues, “Early Detection of Alzheimer’s Disease Using MRI Hippocampal Texture” highlights another means to detect AD before characteristic onset. Sørensen et al. recognized that the hippocampus has notable atrophy throughout AD; however, they grew curious as to whether the texture has any association to early cognitive loss. They hypothesized that the accumulation of β-amyloid plaques and neurofibrillary tangles would reach a point in which they could be observed by MRI and that their detection would be early enough before serious atrophy. The researchers also wanted to determine if the MRI marker based on texture would be able to detect conversion from mild cognitive impairment (MCI) to AD. Furthermore, the texture was also tested to see if it reflected changes in hippocampal glucose metabolism by using fluorodeoxyglucose-positron emission tomography (FDG-PET). The experiment posed by the researchers utilized data obtained from the ADNI and AIBL database, which includes information on aging, biomedical imaging, etc. Hippocampus was given a bilateral hippocampal score that was computed by combining a texture descriptor and a support vector machine. From this, the researchers concluded that the ADNI -based results and obtained texture scores make the hippocampal texture a potential new biomarker in early tracking of AD, as it was successful in predicting MCI to AD progression. Finally, the metabolic rate of glucose within the hippocampus showed a significant correlation between texture and decreased glucose uptake. These results are extremely noteworthy as they are measurements that can allude to a decline in cerebral health much sooner than say tissue atrophy. 

Both Bharani et al. and Sørensen et al. aimed to gain a better understanding of Alzheimer's pathology and elucidate on measurable biomarkers that could help detect AD early in its progression. As the hippocampus is one of the main structures to atrophy, in AD, both researcher teams placed heavy emphasis on it and were able to elucidate both molecular and physical mechanisms that were at play.

 

 

 

Work Cited 

 

Bharani, K. L., Ledreux, A., Gilmore, A., Carroll, S. L., & Granholm, A.-C. (2020). Serum pro-BDNF levels correlate with phospho-tau staining in Alzheimer’s disease. Neurobiology of Aging, 87, 49–59. https://doi.org/10.1016/j.neurobiolaging.2019.11.010

Sørensen, L., Igel, C., Liv Hansen, N., Osler, M., Lauritzen, M., Rostrup, E., & Nielsen, M. (2015). Early detection of Alzheimer’s disease using MRI hippocampal texture. Human Brain Mapping, 37(3), 1148–1161. https://doi.org/10.1002/hbm.23091