Personalized Medicine in Neurodegenerative Diseases: How Far Away?

Abstract

Neurodegenerative diseases are characterized by progressive dysfunction of the nervous system as a result of neuronal loss in the brain and spinal cord. Despite extensive research efforts aimed at development of new disease-modifying therapeutics, there is still no effective treatment to halt neurodegenerative processes. Thus, modification of current therapeutic and diagnostic research strategies is a goal of increasing urgency. The biggest limitation in neurodegenerative disease research is the lack of appropriate biomarkers. Discovery of universal biomarkers capable of diagnosing patients with neurodegenerative diseases, monitoring their response to therapy, and predicting disease progression seems to be a tall order. Instead, a combination of different methodologies in the discovery of biomarkers specific for each described aspect of the disease seems to be a more viable approach. Although application of personalized medicine in diagnosis and treatment of neurodegenerative diseases may seem far off, some recent developments, such as utilizing specific biological therapies in multiple sclerosis, microRNA profiling as a source of novel biomarkers in Parkinson’s disease, or combination of neuroimaging and proteomic analyses in diagnosis of Alzheimer’s disease patients, already point to the way clinical neurology may integrate new achievements in everyday practice. Combination of genomic, proteomic, glycomic, and metabolomic approaches may yield novel insights into molecular mechanisms of disease pathophysiology, which could then be integrated and translated into clinical neurology. Based on the developments during the past decade, it is feasible to predict that a personalized approach to treating neurological disorders will become more widely applicable in the coming years.

Incidence of cognitively defined late‐onset Alzheimer's dementia subgroups from a prospective cohort study

“…For the memory domain, scores for people with Alzheimer’s dementia are substantially lower on Logical Memory II than published normative data for people over age 83 (median age 88) 1 . The group with substantial relative memory impairment had the very lowest performance, as expected.…”

“… Memory: Logical Memory II from the WMS-R 1 Visuospatial Construction 2 Language: Animal Fluency 2 Executive functioning: Trails B 2 Raw Score Norms, Previously Published Normal, 25 th percentile8 – 98.912.4198Normal, 50 th percentile1 1 – 1310.215.3150Normal, 75 th percentile1 610.918.5109 Mean (SD) from people from ACT with incident Alzheimer’s dementia All with AD1.7 (2.6)8.8 (1.7)10.5 (3.9)231 *  0 domains with relative impairment1.4 (2.1)8.9 (1.4)10.4 (3.6)257 *  1 domain with relative impairment  Memory0.1 (0.7)9.7 (1.2)10.7 (4.0)166 *   Visuospatial2.7 (3.1)7.2 (2.0)12.0 (4.2)230 *   Language3.2 (3.2)9.3 (1.4)8.8 (3.5)225 *   Executive functioning…”

“…Meaningfully subdividing a condition into distinct groups is essential to the strategy of personalized medicine 1–3 . Data are currently lacking demonstrating a scalable approach for meaningfully subdividing Alzheimer’s dementia.…”

Integration of metabolomics and proteomics in multiple sclerosis: From biomarkers discovery to personalized medicine

“…The notion “one size fits all” has been replaced by the idea of patient‐tailored healthcare . Based on the developments made during the past decade, it is feasible to predict that a personalized approach for treating neurological disorders will become more widely applicable in the coming years . Researchers conducted genetic, proteomic, and metabolomic studies evaluating the association of genetic and phenotypic variability with disease sensitivity and analgesic response .…”

Textbook of Personalized Medicine

“…1 . Combination of genomic, proteomic, and metabolomic approaches may yield novel insights into molecular mechanisms of disease pathophysiology, which could then be integrated and translated into clinical neurology (Gotovac et al 2014 ). Personalized medicine existed long before the advent of genomic age and non-genomic factors are also taken into consideration in personalizing therapy.…”