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- Snellman, Anniina, et al.
(författare)
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ASIC-E4: Interplay of Beta-Amyloid, Synaptic Density and Neuroinflammation in Cognitively Normal Volunteers With Three Levels of Genetic Risk for Late-Onset Alzheimer's Disease - Study Protocol and Baseline Characteristics
- 2022
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Ingår i: Frontiers in Neurology. - : Frontiers Media SA. - 1664-2295. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Background:& nbsp;Detailed characterization of early pathophysiological changes in preclinical Alzheimer's disease (AD) is necessary to enable development of correctly targeted and timed disease-modifying treatments. ASIC-E4 study ( "Beta-Amyloid, Synaptic loss, Inflammation and Cognition in healthy APOE epsilon 4 carriers ") combines state-of-the-art neuroimaging and fluid-based biomarker measurements to study the early interplay of three key pathological features of AD, i.e., beta-amyloid (A beta) deposition, neuroinflammation and synaptic dysfunction and loss in cognitively normal volunteers with three different levels of genetic (APOE-related) risk for late-onset AD.& nbsp;Objective:& nbsp;Here, our objective is to describe the study design, used protocols and baseline demographics of the ASIC-E4 study.& nbsp;Methods/Design:& nbsp;ASIC-E4 is a prospective observational multimodal imaging study performed in Turku PET Centre in collaboration with University of Gothenburg. Cognitively normal 60-75-year-old-individuals with known APOE epsilon 4/epsilon 4 genotype were recruited via local Auria Biobank (Turku, Finland). Recruitment of the project has been completed in July 2020 and 63 individuals were enrolled to three study groups (Group 1: APOE epsilon 4/epsilon 4, N = 19; Group 2: APOE epsilon 4/epsilon 3, N = 22; Group 3: APOE epsilon 3/epsilon 3, N = 22). At baseline, all participants will undergo positron emission tomography imaging with tracers targeted against A beta deposition (C-11-PIB), activated glia (C-11-PK11195) and synaptic vesicle glycoprotein 2A (C-11-UCB-J), two brain magnetic resonance imaging scans, and extensive cognitive testing. In addition, blood samples are collected for various laboratory measurements and blood biomarker analysis and cerebrospinal fluid samples are collected from a subset of participants based on additional voluntary informed consent. To evaluate the predictive value of the early neuroimaging findings, neuropsychological evaluation and blood biomarker measurements will be repeated after a 4-year follow-up period.& nbsp;Discussion:& nbsp;Results of the ASIC-E4 project will bridge the gap related to limited knowledge of the synaptic and inflammatory changes and their association with each other and A beta in "at-risk " individuals. Thorough in vivo characterization of the biomarker profiles in this population will produce valuable information for diagnostic purposes and future drug development, where the field has already started to look beyond A beta.
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| 4. |
- Pulli, E. P., et al.
(författare)
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Prenatal exposures and infant brain: Review of magnetic resonance imaging studies and a population description analysis
- 2019
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 40:6, s. 1987-2000
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Tidskriftsartikel (refereegranskat)abstract
- Brain development is most rapid during the fetal period and the first years of life. This process can be affected by many in utero factors, such as chemical exposures and maternal health characteristics. The goal of this review is twofold: to review the most recent findings on the effects of these prenatal factors on the developing brain and to qualitatively assess how those factors were generally reported in studies on infants up to 2 years of age. To capture the latest findings in the field, we searched articles from PubMed 2012 onward with search terms referring to magnetic resonance imaging (MRI), brain development, and infancy. We identified 19 MRI studies focusing on the effects of prenatal environment and summarized them to highlight the recent advances in the field. We assessed population descriptions in a representative sample of 67 studies and conclude that prenatal factors that have been shown to affect brain metrics are not generally reported comprehensively. Based on our findings, we propose some improvements for population descriptions to account for plausible confounders and in time enable reliable meta-analyses to be performed. This could help the pediatric neuroimaging field move toward more reliable identification of biomarkers for developmental outcomes and to better decipher the nuances of normal and abnormal brain development.
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