Abstract
Nasu-Hakola Disease (NHD) is a recessively inherited systemic leukodystrophy disorder characterized by a combination of frontotemporal presenile dementia and lytic bone lesions. NHD is known to be genetically related to a structural defect of TREM2 and DAP12, two genes that encode for different subunits of the membrane receptor signaling complex expressed by microglia and osteoclast cells. Because of its rarity, molecular or proteomic studies on this disorder are absent or scarce, only case reports based on neuropsychological and genetic tests being reported. In light of this, the aim of this paper is to provide evidence on the potential of a label-free proteomic platform based on the Multidimensional Protein Identification Technology (MudPIT), combined with in-house software and on-line bioinformatics tools, to characterize the protein expression trends and the most involved pathways in NHD. The application of this approach on the Lymphoblastoid cells from a family composed of individuals affected by NHD, healthy carriers and control subjects allowed for the identification of about 3000 distinct proteins within the three analyzed groups, among which proteins anomalous to each category were identified. Of note, several differentially expressed proteins were associated with neurodegenerative processes. Moreover, the protein networks highlighted some molecular pathways that may be involved in the onset or progression of this rare frontotemporal disorder. Therefore, this fully automated MudPIT platform which allowed, for the first time, the generation of the whole protein profile of Lymphoblastoid cells from Nasu-Hakola subjects, could be a valid approach for the investigation of similar neurodegenerative diseases.
Highlights
Based on the last report edited by Alzheimer’s Disease International [1], every 3.2 s a person falls ill worldwide with “dementia” [2], an umbrella term that indicates a broad category of brain diseases linked to cognitive decline
The application of a gel-free proteomic platform, based on a bi-dimensional μliquidchromatographic system combined to a high resolution mass spectrometer [12,13], allowed the identification of 10,253 unique peptides and 3458 distinct proteins from a total of 19 protein lists, by analyzing Lymphoblastoid cell lines (LCLs) obtained from the healthy (Wt), heterozygous (He) and homozygous (Ho) components of the family indicated in the Materials and Methods section
Sci. 2021, 22, 9959 as Multidimensional Protein Identification Technology (MudPIT)) [12,13], allowed the identification of 10,253 unique peptides and 3,458 distinct proteins from a total of 19 protein lists, by analyzing Lymphoblastoid cell lines (LCLs) obtained from the healthy (Wt), heterozygous (He) and homozygous (Ho) components of the family indicated in the Materials and Methods section
Summary
Based on the last report edited by Alzheimer’s Disease International [1], every 3.2 s a person falls ill worldwide with “dementia” [2], an umbrella term that indicates a broad category of brain diseases linked to cognitive decline. These include Alzheimer’s Disease (AD), Vascular Dementia (VD), Lewy Bodies Dementia (LBD) and Frontotemporal. In 5–15% of dementia cases, FTD is the second most common cause of presenile dementias. The overlap of several symptoms with other neurological syndromes makes this category even more puzzling
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