The Clinical Spectrum of Young Onset Dementia Points to Its Stochastic Origins

Essential New Complexity-Based Themes for Patient-Centered Diagnosis and Treatment of Dementia and Predementia in Older People: Multimorbidity and Multilevel Phenomenology

Dementia is a highly prevalent condition with devastating clinical and socioeconomic sequela. It is expected to triple in prevalence by 2050. No treatment is currently known to be effective. Symptomatic late-onset dementia and predementia (SLODP) affects 95% of patients with the syndrome. In contrast to trials of pharmacological prevention, no treatment is suggested to remediate or cure these symptomatic patients. SLODP but not young onset dementia is intensely associated with multimorbidity (MUM), including brain-perturbating conditions (BPCs). Recent studies showed that MUM/BPCs have a major role in the pathogenesis of SLODP. Fortunately, most MUM/BPCs are medically treatable, and thus, their treatment may modify and improve SLODP, relieving suffering and reducing its clinical and socioeconomic threats. Regrettably, the complex system features of SLODP impede the diagnosis and treatment of the potentially remediable conditions (PRCs) associated with them, mainly due to failure of pattern recognition and a flawed diagnostic workup. We suggest incorporating two SLODP-specific conceptual themes into the diagnostic workup: MUM/BPC and multilevel phenomenological themes. By doing so, we were able to improve the diagnostic accuracy of SLODP components and optimize detecting and favorably treating PRCs. These revolutionary concepts and their implications for remediability and other parameters are discussed in the paper.

Electroencephalography in young onset dementia

BACKGROUND

Young onset dementia (YOD) is a major diagnostic and management problem.

METHODS

We set out to explore if electroencephalography (EEG) might be useful in the diagnosis of young onset Alzheimer's disease (YOAD) and young onset frontotemporal dementia (YOFTD). The ARTEMIS project is a 25-year prospective study of YOD based in Perth, Western Australia. 231 participants were included: YOAD: n = 103, YOFTD: n = 28, controls: n = 100. EEGs were performed prospectively, with 30-minute recording time for each subject, without knowledge of diagnosis or other diagnostic data.

RESULTS

80.9% of patients with YOD had abnormal EEGs (P < 0.00001). Slow wave changes were more frequent in YOAD that YOFTD (P < 0.00001), but no difference in the frequency of epileptiform activity (P = 0.32), with 38.8% of YOAD and 28.6% of YOFTD patients having epileptiform activity. Slow wave changes were more generalized in YOAD (P = 0.001). Slow wave changes and epileptiform activity were not sensitive to the diagnosis of YOD, but highly specific (97-99%). The absence of slow wave changes and epileptiform activity had a 100% negative predictive value and likelihood radio 0.14 and 0.62 respectively, meaning that those without slow wave changes or epileptiform activity had low probability of having YOD. No relationship was established between EEG findings and the patient's presenting problem. Eleven patients with YOAD developed seizures during the study, and only one with YOFTD.

CONCLUSIONS

The EEG is highly specific for the diagnosis of YOD with the absence of slow wave changes and epileptiform phenomena making the diagnosis unlikely, with 100% negative predictive value and with low probability for the dementia diagnosis.

Stochasticity, Entropy and Neurodegeneration

We previously suggested that stochastic processes are fundamental in the development of sporadic adult onset neurodegenerative disorders. In this study, we develop a theoretical framework to explain stochastic processes at the protein, DNA and RNA levels. We propose that probability determines random sequencing changes, some of which favor neurodegeneration in particular anatomical spaces, and that more than one protein may be affected simultaneously. The stochastic protein changes happen in three-dimensional space and can be considered to be vectors in a space-time continuum, their trajectories and kinetics modified by physiological variables in the manifold of intra- and extra-cellular space. The molecular velocity of these degenerative proteins must obey the second law of thermodynamics, in which entropy is the driver of the inexorable progression of neurodegeneration in the context of the N-body problem of interacting proteins, time-space manifold of protein-protein interactions in phase space, and compounded by the intrinsic disorder of protein-protein networks. This model helps to elucidate the existence of multiple misfolded proteinopathies in adult sporadic neurodegenerative disorders.