Physiological biomarkers of silent brain damage leading to cognitive impairment and Dementia – direct and accessible clinical evidence

Abstract

AbstractBackgroundCognitive assessment is the best clinical tool to detect cognitive impairments, yet it is evident only at late stages of disease progression. In contrast, silent brain network changes occur at early stages of the disease and it is estimated that a large proportion of dementias may be prevented or at‐least delayed if detected during early pathophysiology stages. Neuroimaging studies have shown that silent brain network findings, including white matter hyperintensities, lacunar infarctions and temporal atrophy are evident before objective cognitive impairment is detected and even more in ‘at risk’ population with risk factors for dementia. We aimed to evaluate direct physiological biomarkers that provide accessible clinical evidence of silent brain network damage that precede clinical cognitive findings and provide early clinical biomarkers that can facilitate early interventions.MethodBrain network performance was evaluated in 168 subjects ‘at risk’ for developing dementia (Table 1). Direct electrophysiological imaging (“Delphi”) was used to measure magnetically induced brain network electrophysiological response. MRI scans included T1, T2, FLAIR, Diffusion Weighted Imaging (DWI) and (SWI). They were analysed according to Fazekas scale for white matter Hyperintensities (WMH), lacunar Infarctions and medial temporal lobe atrophy (MTA). Objective cognitive evaluations were performed by a neuropsychologist interview and a computerized cognitive battery (NeurotraxTM).ResultDirect electrophysiological imaging (“Delphi”) was able to distinguish between severities of different MRI detected silent brain network damage findings. Magnetically induced direct electrophysiological response wave form adherence (WFA) significantly decreased with increase in WMH (Fig.1A; p<0.0001) and increase in MTA levels (Fig.1B; p<0.0001). Furthermore, WFA significantly decreased in subjects with lacunar infarctions (Fig.1C; p<0.0001).ConclusionSilent brain network deficits preceding dementia and cognitive decline are widely under detected due to lack of accessible tools. Data presented in this study demonstrates “Delphi” technology’s ability to detect silent brain network damage findings and severity levels that are identified in MRI scans. “Delphi” is a clinically accessible, direct, and objective technology that can facilitate early detection, prevention, delayed progression and management of mild cognitive impairment and dementia.