In Lewy body diseases-including Parkinson's disease, without or with dementia, dementia with Lewy bodies, and Alzheimer's disease with Lewy body co-pathology 1 -α-synuclein (α-Syn) aggregates in neurons as Lewy bodies and Lewy neurites 2 . By contrast, in multiple system atrophy α-Syn accumulates mainly in oligodendrocytes as glial cytoplasmic inclusions (GCIs) 3 . Here we report that pathological α-Syn in GCIs and Lewy bodies (GCI-α-Syn and LB-α-Syn, respectively) is conformationally and biologically distinct. GCI-α-Syn forms structures that are more compact and it is about 1,000-fold more potent than LB-α-Syn in seeding α-Syn aggregation, consistent with the highly aggressive nature of multiple system atrophy. GCI-α-Syn and LB-α-Syn show no cell-type preference in seeding α-Syn pathology, which raises the question of why they demonstrate different cell-type distributions in Lewy body disease versus multiple system atrophy. We found that oligodendrocytes but not neurons transform misfolded α-Syn into a GCI-like strain, highlighting the fact that distinct α-Syn strains are generated by different intracellular milieus. Moreover, GCI-α-Syn maintains its high seeding activity when propagated in neurons. Thus, α-Syn strains are determined by both misfolded seeds and intracellular environments.

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Cellular milieu imparts distinct pathological α-synuclein strains in α-synucleinopathies

Lewy bodies commonly occur in Alzheimer's disease, and Alzheimer's disease pathology is frequent in Lewy body diseases, but the burden of co-pathologies across neurodegenerative diseases is unknown. We assessed the extent of tau, amyloid-β, α-synuclein and TDP-43 proteinopathies in 766 autopsied individuals representing a broad spectrum of clinical neurodegenerative disease. We interrogated pathological Alzheimer's disease (n = 247); other tauopathies (n = 95) including Pick's disease, corticobasal disease and progressive supranuclear palsy; the synucleinopathies (n = 164) including multiple system atrophy and Lewy body disease; the TDP-43 proteinopathies (n = 188) including frontotemporal lobar degeneration with TDP-43 inclusions and amyotrophic lateral sclerosis; and a minimal pathology group (n = 72). Each group was divided into subgroups without or with co-pathologies. Age and sex matched logistic regression models compared co-pathology prevalence between groups. Co-pathology prevalence was similar between the minimal pathology group and most neurodegenerative diseases for each proteinopathy: tau was nearly universal (92-100%), amyloid-β common (20-57%); α-synuclein less common (4-16%); and TDP-43 the rarest (0-16%). In several neurodegenerative diseases, co-pathology increased: in Alzheimer's disease, α-synuclein (41-55%) and TDP-43 (33-40%) increased; in progressive supranuclear palsy, α-synuclein increased (22%); in corticobasal disease, TDP-43 increased (24%); and in neocortical Lewy body disease, amyloid-β (80%) and TDP-43 (22%) increased. Total co-pathology prevalence varied across groups (27-68%), and was increased in high Alzheimer's disease, progressive supranuclear palsy, and neocortical Lewy body disease (70-81%). Increased age at death was observed in the minimal pathology group, amyotrophic lateral sclerosis, and multiple system atrophy cases with co-pathologies. In amyotrophic lateral sclerosis and neocortical Lewy body disease, co-pathologies associated with APOE ɛ4. Lewy body disease cases with Alzheimer's disease co-pathology had substantially lower Mini-Mental State Examination scores than pure Lewy body disease. Our data imply that increased age and APOE ɛ4 status are risk factors for co-pathologies independent of neurodegenerative disease; that neurodegenerative disease severity influences co-pathology as evidenced by the prevalence of co-pathology in high Alzheimer's disease and neocortical Lewy body disease, but not intermediate Alzheimer's disease or limbic Lewy body disease; and that tau and α-synuclein strains may also modify co-pathologies since tauopathies and synucleinopathies had differing co-pathologies and burdens. These findings have implications for clinical trials that focus on monotherapies targeting tau, amyloid-β, α-synuclein and TDP-43.

Neurodegenerative disease concomitant proteinopathies are prevalent, age-related and APOE4-associated

Precision medicine has the potential to profoundly improve the practice of medicine. However, the advances required will take time to implement. Genetics is already being used to direct clinical decision-making and its contribution is likely to increase. To accelerate these advances, fundamental changes are needed in the infrastructure and mechanisms for data collection, storage and sharing. This will create a continuously learning health-care system with seamless cycling between clinical care and research. Patients must be educated about the benefits of sharing data. The building blocks for such a system are already forming and they will accelerate the adoption of precision medicine.

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Building the foundation for genomics in precision medicine

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with a complex and heterogeneous pathophysiology. The number of people living with AD is predicted to increase; however, there are no disease-modifying therapies currently available and none have been successful in late-stage clinical trials. Fluid biomarkers measured in cerebrospinal fluid (CSF) or blood hold promise for enabling more effective drug development and establishing a more personalized medicine approach for AD diagnosis and treatment. Biomarkers used in drug development programmes should be qualified for a specific context of use (COU). These COUs include, but are not limited to, subject/patient selection, assessment of disease state and/or prognosis, assessment of mechanism of action, dose optimization, drug response monitoring, efficacy maximization, and toxicity/adverse reactions identification and minimization. The core AD CSF biomarkers Aβ42, t-tau, and p-tau are recognized by research guidelines for their diagnostic utility and are being considered for qualification for subject selection in clinical trials. However, there is a need to better understand their potential for other COUs, as well as identify additional fluid biomarkers reflecting other aspects of AD pathophysiology. Several novel fluid biomarkers have been proposed, but their role in AD pathology and their use as AD biomarkers have yet to be validated. In this review, we summarize some of the pathological mechanisms implicated in the sporadic AD and highlight the data for several established and novel fluid biomarkers (including BACE1, TREM2, YKL-40, IP-10, neurogranin, SNAP-25, synaptotagmin, α-synuclein, TDP-43, ferritin, VILIP-1, and NF-L) associated with each mechanism. We discuss the potential COUs for each biomarker.

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Current state of Alzheimer's fluid biomarkers.

We examined regional distribution patterns of phosphorylated 43-kDa TAR DNA-binding protein (pTDP-43) intraneuronal inclusions in frontotemporal lobar degeneration (FTLD). Immunohistochemistry was performed on 70 μm sections from FTLD-TDP autopsy cases (n = 39) presenting with behavioral variant frontotemporal dementia. Two main types of cortical pTDP-43 pathology emerged, characterized by either predominantly perikaryal pTDP-43 inclusions (cytoplasmic type, cFTLD) or long aggregates in dendrites (neuritic type, nFTLD). Cortical involvement in nFTLD was extensive and frequently reached occipital areas, whereas cases with cFTLD often involved bulbar somatomotor neurons and the spinal cord. We observed four patterns indicative of potentially sequential dissemination of pTDP-43: cases with the lowest burden of pathology (pattern I) were characterized by widespread pTDP-43 lesions in the orbital gyri, gyrus rectus, and amygdala. With increasing burden of pathology (pattern II) pTDP-43 lesions emerged in the middle frontal and anterior cingulate gyrus as well as in anteromedial temporal lobe areas, the superior and medial temporal gyri, striatum, red nucleus, thalamus, and precerebellar nuclei. More advanced cases showed a third pattern (III) with involvement of the motor cortex, bulbar somatomotor neurons, and the spinal cord anterior horn, whereas cases with the highest burden of pathology (pattern IV) were characterized by pTDP-43 lesions in the visual cortex. We interpret the four neuropathological patterns in bvFTD to be consistent with the hypothesis that pTDP-43 pathology can spread sequentially and may propagate along axonal pathways.

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Sequential distribution of pTDP-43 pathology in behavioral variant frontotemporal dementia (bvFTD)

Neurodegenerative diseases (NDs) are defined by the accumulation of abnormal protein deposits in the central nervous system (CNS), and only neuropathological examination enables a definitive diagnosis. Brain banks and their associated scientific programs have shaped the actual knowledge of NDs, identifying and characterizing the CNS deposits that define new diseases, formulating staging schemes, and establishing correlations between neuropathological changes and clinical features. However, brain banks have evolved to accommodate the banking of biofluids as well as DNA and RNA samples. Moreover, the value of biobanks is greatly enhanced if they link all the multidimensional clinical and laboratory information of each case, which is accomplished, optimally, using systematic and standardized operating procedures, and in the framework of multidisciplinary teams with the support of a flexible and user-friendly database system that facilitates the sharing of information of all the teams in the network. We describe a biobanking system that is a platform for discovery research at the Center for Neurodegenerative Disease Research at the University of Pennsylvania.

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A platform for discovery: The University of Pennsylvania Integrated Neurodegenerative Disease Biobank

/pdf/identifying-amyloid-pathology-related-cerebrospinal-fluid-5a9zq2ddzz.pdf

Identifying amyloid pathology-related cerebrospinal fluid biomarkers for Alzheimer's disease in a multicohort study.

Introduction
The dynamic range of cerebrospinal fluid (CSF) amyloid β (Aβ1–42) measurement does not parallel to cognitive changes in Alzheimer's disease (AD) and cognitively normal (CN) subjects across different studies. Therefore, identifying novel proteins to characterize symptomatic AD samples is important.

Young Baek

Papers

A platform for discovery: The University of Pennsylvania Integrated Neurodegenerative Disease Biobank

Identifying amyloid pathology-related cerebrospinal fluid biomarkers for Alzheimer's disease in a multicohort study.

Identifying amyloid pathology-related cerebrospinal fluid biomarkers for Alzheimer's disease in a multicohort study