Citations

AbstractBackgroundDisease‐modifying therapies for Alzheimer’s Disease (AD) are likely most beneficial when initiated in the pre‐symptomatic phase. To track success of such interventions fluid biomarkers became instrumental, with neurofilament light chain (NfL) showing particular promise. We previously reported that serum NfL increases in pre‐symptomatic phases of familial (autosomal‐dominantly inherited) AD (fAD) and that within‐person rate‐of‐change in NfL is an earlier predictor of fAD symptom onset compared to cross‐sectional levels. The aim of the study at hand was to extend these initial findings in a larger cohort.MethodParticipants enrolled in the Dominantly Inherited Alzheimer Network (DIAN) with matched cross‐sectional and longitudinal cerebrospinal fluid (CSF; n = 962) as well as plasma (n = 1294) samples were used. NfL measurements have been performed on the SIMOA platform using commercially available assay‐kits. To investigate the influence of physiological factors independent from AD, we first analyzed whether age and body mass index (BMI) could account for observed variation in inter‐individual CSF and plasma NfL levels considering non‐carrier family‐members (NC) as a healthy control group. Next, utilizing estimated years to symptom onset (EYO) and previously published methods (Preische et al., 2019), we determined the point in disease course when baseline and longitudinal CSF and plasma NfL concentrations started to increase in mutation carriers (MC) relative to NC, after adjusting for age and BMI.ResultOur results reveal a tight correlation of CSF and blood NfL values within MC as well as NC (figure 1A‐B). However, within NC, after correction for age and BMI, some unexplained variability remained (figure 1C). Further, a decrease of the NfL plasma/CSF ratio over age was found after correcting for BMI (figure 1D). The discrimination of MC from NC was equally good for plasma compared to CSF, being possible on the group level as early as around ‐15 to almost ‐20 EYO depending on the modelling (figure 2).ConclusionOur results support plasma equivalently to CSF NfL as a clinically useful biomarker to longitudinally track neurodegeneration in fAD. The systemic factors influencing physiological NfL values in blood should be investigated in future studies to further improve interpretation of this biomarker.

AbstractBackgroundThe causes of rapidly progressive dementia are heterogeneous, including neurodegenerative, vascular, and autoimmune/inflammatory diseases. Overlap in presenting symptoms and signs, results of cognitive testing, and findings on brain imaging and other common diagnostic tests confounds the etiologic diagnosis, contributing to diagnostic delays, missed opportunities for treatment, and poorer outcomes in patients with RPD. New tools and approaches are needed to improve diagnostic accuracy, with particular emphasis on improving early recognition of patients with potentially treatable causes of RPD.MethodsEstablished and emerging biomarkers of Alzheimer disease neuropathology (Aβ42/40, p‐tau181, p‐tau231), neuroaxonal and neuronal injury (neurofilament light [NfL], VILIP‐1, total tau), neuroinflammation (YKL‐40, sTREM2, GFAP, MCP‐1), and synaptic dysfunction (SNAP‐25, neurogranin) were measured in cerebrospinal fluid obtained at presentation from 78 prospectively accrued patients with RPD due to neurodegenerative (n = 35), vascular (n = 9), and autoimmune/inflammatory (n = 34) diseases, and 72 age‐ and sex‐similar cognitively normal individuals (controls). Causes of RPD were further classified as potentially treatment‐responsive or nonresponsive, referencing the extant literature. Biomarker levels were compared across etiologic diagnoses and by treatment responsiveness, referencing control values. Analyses were adjusted for the effects of age (ANCOVA).ResultsAlzheimer disease biomarkers (low Aβ42/40 and elevated p‐tau181 and p‐tau231) were associated with neurodegenerative causes of RPD (ANCOVA, p = 0.02 p = 0.30, p = 0.15), while high NfL (p = 0.61), low VILIP‐1 (p = 0.009), and elevated markers of inflammation (sTREM2, p = 0.009; YKL‐40, p<0.001) identified patients with autoimmune/inflammatory diseases (Figure). MCP‐1 levels were highest in patients with vascular causes of RPD (p = 0.08). 44 patients (56.4%) had potentially treatment‐responsive causes of RPD. Treatment responsiveness was associated with higher levels of CSF Aβ42/40 (p = 0.003), NfL (p<0.001), sTREM2 (p<0.001) and YKL‐40 (p<0.001); and lower levels of p‐tau‐181 and p‐tau231 (p<0.001, p<0.001) and VILIP‐1 (p<0.001).ConclusionSelected biomarkers measured in CSF at presentation associate with etiologic diagnosis and treatment responsiveness in patients with neurodegenerative, vascular, and autoimmune/inflammatory causes of RPD. Biomarker panels may be adapted to improve recognition of patients with treatment‐responsive causes of RPD early in the symptomatic course when treatments may be most effective.

AbstractBackgroundThe imaging of patients with implanted electrically‐conductive devices via magnetic resonance imaging at ultra‐high fields is hampered by uncertainties relating to the potential for inducing tissue heating adjacent to the implant due to coupling of energy from the incident electromagnetic field into the implant. Existing data in the peer‐reviewed literature of comparisons across field strengths of tissue heating and its surrogate, the specific absorption rate (SAR), is scarce and contradictory, leading to further doubts pertaining to the safety of imaging patients with such devices.PurposeThe radiofrequency‐induced SAR adjacent to orthopedic screws of varying length and at frequencies of 64 to 498 MHz was investigated via full‐wave electromagnetic simulations, to provide an accurate comparison of SAR across MRI field strengths.MethodsDipole antennas were used for RF transmission to achieve a uniform electric field tangential to the screws located 120 mm above the antenna midpoints, embedded in a bone‐mimicking material. The input power to the antennas was constrained to achieve the following targets without the screw present: (i) E = 100 V/m, (ii) B1+ = 2 μT, and (iii) global‐average‐SAR = 3.2 W/kg. Simulations were performed with a spatial resolution of 0.2 mm in the volume surrounding the screws, resulting in 76–137 MCells, noting the maximum 1 g‐averaged SAR value in each case. Simulations were repeated at 128 and 297 MHz for screws embedded in muscle tissue.ResultsThe peak SAR, occurring at the resonant screw length, substantially increased as the frequency decreased when the input power to the dipole antenna was constrained to achieve constant electric field in background tissue at the screws’ locations. A similar pattern was observed when constraining input power to achieve constant B1+ and global‐average‐SAR. The dielectric properties of the tissue in which the screws were embedded dominated the SAR comparisons between 297 and 128 MHz.ConclusionsThe study design allowed for a direct comparison to be performed of SAR across frequencies and implant lengths without the confounding effect of variable incident electric field. Lower frequencies produced substantially larger SAR values for implants approaching the resonant length for the worst‐case uniform incident electric field along the screws’ length. The data may inform risk‐benefit assessments for imaging patients with orthopedic implants at the new clinical field strength of 7 Tesla.

Over 40 years of controversy surround the nuclear localization of actin. Now, it is well understood that actin localization to the nucleus is highly regulated, suggesting actin has critical nuclear functions. Studies have demonstrated that nuclear actin has roles in regulating transcription, chromatin remodeling, nuclear organization, and DNA damage repair. However, much remains unknown about nuclear actin, including its structure in the nucleus and its functions during development. Here we present our novel finding that Drosophila oogenesis, or follicle development, is a model for studying the structure, regulation, and function of nuclear actin. Follicles are composed of roughly 1000 somatic follicle cells and 16 germline cells, including 15 nurse or support cells and a single oocyte, and progress through a series of 14 morphological stages, from the germanium to Stage 14. During Stages 5–9, nuclear actin levels are high in the oocyte and exhibit variation within the nurse cells. Known regulators of actin nucleocytoplasmic transport, Cofilin and Profilin, also localize to the nuclei during follicle development. Further, germline expression of GFP‐tagged Actin results in nuclear actin rod formation in nurse cells during Stages 5–9. These nuclear actin rods are static, label with both phalloidin and Cofilin. These findings suggest that nuclear actin is tightly regulated during follicle development. As we have previously determined that Fascin, an actin bundling protein, localizes to nurse cell nuclei, we postulated that Fascin may be a novel regulator of nuclear actin. Overexpression of Fascin enhances the frequency and length of GFP‐Actin rods, and Fascin colocalizes with these rods. Additionally, the loss of Fascin reduces, while the overexpression of Fascin increases, the frequency of nurse cells with high levels of endogenous nuclear actin. However, genetic manipulation of Fascin does not alter the overall nuclear level of actin within the ovary. Thus, these data suggest Fascin regulates the ability of specific cells to accumulate nuclear actin. The loss of Fascin reduces nuclear Cofilin suggesting that Fascin positively regulates nuclear actin through Cofilin, a key factor in the nuclear import of actin. Indeed, Fascin and Cofilin genetically interact, as double heterozygotes exhibit a reduction in the number of nurse cells with high nuclear actin levels. In conclusion, we have established Drosophila oogenesis as a new system to uncover the physiologically important functions and regulation of nuclear actin. Further, we have identified Fascin as a novel regulator of nuclear actin. The nuclear localization of Fascin and Actin is highly conserved among systems, indicating these findings are applicable far beyond Drosophila follicle development. Support or Funding Information This project is supported by grants by the National Science Foundation MCB‐1158527, National Institutes of Health R01GM116885 and Carver Trust Medical Research Initiative Grant. D.J.K. is partially supported by NINDS T32NS045549.

Abstract Approximately 5% of Alzheimer’s disease cases have an early age at onset (&lt;65 years), with 5–10% of these cases attributed to dominantly inherited mutations and the remainder considered as sporadic. The extent to which dominantly inherited and sporadic early-onset Alzheimer’s disease overlap is unknown. In this study, we explored the clinical, cognitive and biomarker profiles of early-onset Alzheimer’s disease, focusing on commonalities and distinctions between dominantly inherited and sporadic cases. Our analysis included 117 participants with dominantly inherited Alzheimer’s disease enrolled in the Dominantly Inherited Alzheimer Network and 118 individuals with sporadic early-onset Alzheimer’s disease enrolled at the University of California San Francisco Alzheimer’s Disease Research Center. Baseline differences in clinical and biomarker profiles between both groups were compared using t-tests. Differences in the rates of decline were compared using linear mixed-effects models. Individuals with dominantly inherited Alzheimer’s disease exhibited an earlier age-at-symptom onset compared with the sporadic group [43.4 (SD ± 8.5) years versus 54.8 (SD ± 5.0) years, respectively, P &lt; 0.001]. Sporadic cases showed a higher frequency of atypical clinical presentations relative to dominantly inherited (56.8% versus 8.5%, respectively) and a higher frequency of APOE-ε4 (50.0% versus 28.2%, P = 0.001). Compared with sporadic early onset, motor manifestations were higher in the dominantly inherited cohort [32.5% versus 16.9% at baseline (P = 0.006) and 46.1% versus 25.4% at last visit (P = 0.001)]. At baseline, the sporadic early-onset group performed worse on category fluency (P &lt; 0.001), Trail Making Test Part B (P &lt; 0.001) and digit span (P &lt; 0.001). Longitudinally, both groups demonstrated similar rates of cognitive and functional decline in the early stages. After 10 years from symptom onset, dominantly inherited participants experienced a greater decline as measured by Clinical Dementia Rating Sum of Boxes [3.63 versus 1.82 points (P = 0.035)]. CSF amyloid beta-42 levels were comparable [244 (SD ± 39.3) pg/ml dominantly inherited versus 296 (SD ± 24.8) pg/ml sporadic early onset, P = 0.06]. CSF phosphorylated tau at threonine 181 levels were higher in the dominantly inherited Alzheimer’s disease cohort (87.3 versus 59.7 pg/ml, P = 0.005), but no significant differences were found for t-tau levels (P = 0.35). In summary, sporadic and inherited Alzheimer’s disease differed in baseline profiles; sporadic early onset is best distinguished from dominantly inherited by later age at onset, high frequency of atypical clinical presentations and worse executive performance at baseline. Despite these differences, shared pathways in longitudinal clinical decline and CSF biomarkers suggest potential common therapeutic targets for both populations, offering valuable insights for future research and clinical trial design.

AbstractPurposeDental amalgam contains mercury and is commonly used in dental restorations. The impact of MRI on mercury excretion from dental amalgam is not well understood across clinical field strengths, especially 7T. We investigated the effects of MRI exposure on mercury excretion using fresh, lab‐created dental amalgam restorations and in extracted teeth with old, pre‐existing restorations.MethodsDonated, unfilled human teeth (n = 120) were restored with amalgam before being stored in saline, artificial saliva, or a dry box prior to MRI scanning. The teeth were placed in individual tubes of fresh artificial saliva and scanned at 1.5T, 3T, or 7T or left unscanned as controls. Mercury concentrations were measured 24–30 h later. Donated teeth with pre‐existing restorations (n = 40) were stored in artificial saliva, scanned at 7T or left unscanned as controls, and mercury concentration tested.ResultsFor teeth extracted and restored in a laboratory, no significant difference was found (F = 2.42, P = 0.072) between mean mercury concentrations of unscanned teeth (13.72 μg/L) and teeth scanned at 1.5T (10.88 μg/L), 3T (12.65 μg/L), or 7T (8.88 μg/L). For teeth extracted with previously placed restorations, no significant difference (P = 0.288) was found between unscanned controls (4.28 μg/L) and teeth scanned at 7T (6.63 μg/L).ConclusionMRI of dental amalgam does not significantly increase mercury excretion at 1.5T, 3T, or 7T compared to unscanned teeth. This holds true for controlled laboratory restorations as well as for those placed and lived with prior to extraction and scanning, demonstrating no added risk to the clinical patient or research subject.