TitleGolgi fragmentation - One of the earliest organelle phenotypes in Alzheimer's disease neurons.
Publication TypeJournal Article
Year of Publication2023
AuthorsHaukedal H, Corsi GI, Gadekar VP, Doncheva NT, Kedia S, de Haan N, Chandrasekaran A, Jensen P, Schiønning P, Vallin S, Marlet FRavnkilde, Poon A, Pires C, Agha FKhoder, Wandall HH, Cirera S, Simonsen AHviid, Nielsen TTolstrup, Nielsen JErik, Hyttel P, Muddashetty R, Aldana BI, Gorodkin J, Nair D, Meyer M, Larsen MRøssel, Freude K
JournalFront Neurosci
Date Published2023

Alzheimer's disease (AD) is the most common cause of dementia, with no current cure. Consequently, alternative approaches focusing on early pathological events in specific neuronal populations, besides targeting the well-studied amyloid beta (Aβ) accumulations and Tau tangles, are needed. In this study, we have investigated disease phenotypes specific to glutamatergic forebrain neurons and mapped the timeline of their occurrence, by implementing familial and sporadic human induced pluripotent stem cell models as well as the 5xFAD mouse model. We recapitulated characteristic late AD phenotypes, such as increased Aβ secretion and Tau hyperphosphorylation, as well as previously well documented mitochondrial and synaptic deficits. Intriguingly, we identified Golgi fragmentation as one of the earliest AD phenotypes, indicating potential impairments in protein processing and post-translational modifications. Computational analysis of RNA sequencing data revealed differentially expressed genes involved in glycosylation and glycan patterns, whilst total glycan profiling revealed minor glycosylation differences. This indicates general robustness of glycosylation besides the observed fragmented morphology. Importantly, we identified that genetic variants in Sortilin-related receptor 1 () associated with AD could aggravate the Golgi fragmentation and subsequent glycosylation changes. In summary, we identified Golgi fragmentation as one of the earliest disease phenotypes in AD neurons in various and complementary disease models, which can be exacerbated additional risk variants in .

Alternate JournalFront Neurosci
PubMed ID36875643
PubMed Central IDPMC9978754