Citations

Abstract Alzheimer's disease (AD) is neuropathologically defined by amyloid‐beta (Aβ) plaques and tau neurofibrillary tangles. However, co‐pathologies and other pathobiological processes are involved in the pathogenesis of AD, contributing to neurodegeneration and clinical symptoms. The most common co‐pathologies in people with AD are alpha‐synucleinopathy, vascular brain injury and transactive response DNA‐binding protein of 43 kDa‐related pathology. Neuroinflammation, iron accumulation, cholinergic dysfunction and cellular senescence are recognized pathobiological processes beyond Aβ‐ and tau‐related pathology. However, the exact mechanisms by which these co‐pathologies and pathobiological processes contribute to the neurodegeneration and clinical symptoms in people with AD remain unclear. The individual combination of these co‐pathologies and pathobiological processes increases phenotypical heterogeneity in people with AD. This highlights the unmet need to advance their current understanding, and the field strives to develop accurate biomarkers for personalized assessment and investigation. Elucidating this biologic‐clinical complexity and heterogeneity is crucial for increasing our current understanding of AD, with implications for diagnosis, prognosis and therapeutics.

AbstractBackgroundGlial fibrillary acidic protein (GFAP) is a marker of cerebral astrogliosis and occasionally elevated in patients with dementia. GFAP in cerebrospinal fluid (CSF), is routinely requested in referrals to neurochemistry laboratories; however, its ability to differentiate dementias and diagnostic capability is unclear. Our aim was to elucidate this, using two large datasets.MethodFirst, GFAP data measured since 2015 was retrieved from the database of the Clinical Neurochemistry Laboratory at the Sahlgrenska University hospital. We then cross‐referenced with the Swedish dementia registry (SveDem). Here, information on ten different diagnoses such as early onset AD (EAD [<65 years]), late onset AD (LAD [≥65 years]), Parkinson disease with dementia (PDD), vascular dementia (VaD) and frontotemporal dementia (FTD), each with specific diagnostic criteria, were retrieved.The GFAP data was log10‐transformed, followed by an analysis of covariance (ANCOVA) and a subsequent post‐hoc Tukey’s test, with GFAP as dependent variable, diagnosis as independent variable and sex and age as covariates.ResultIn total, 1912 individuals (mean [SD] age, 71.9 [8.2] years; 52% male), were included. Lower log10‐transformed GFAP concentrations were seen in PDD (mean [SD], 2.68, [0.28] pg/mL), than in EAD, LAD, VaD and FTD; here, mean concentrations of 2.76 (0.24), 2.89 (0.23), 2.89 (0.32) and 2.76 (0.25) pg/mL were observed, respectively.In the post hoc analysis, GFAP differentiated VaD from EAD (p<0.001). PDD concentrations were significantly different from VaD (p<0.001) and LAD (p<0.001). Further, it also differentiated FTD from VaD (p=0.006) and LAD (p=0.001).ConclusionCSF GFAP could on a group level help differentiate VaD from EAD, FTD and PDD. Also, it could differentiate PDD from LAD. These results bear potential clinical relevance, where clinicians in some uncertain cases could use this marker as a differential tool.