Citations

Abstract The American Joint Committee on Cancer (AJCC) staging system for all cancer sites, including gastroenteropancreatic neuroendocrine tumors (GEP‐NETs), is meant to be dynamic, requiring periodic updates to optimize AJCC staging definitions. This entails the collaboration of experts charged with evaluating new evidence that supports changes to each staging system. GEP‐NETs are the second most prevalent neoplasm of gastrointestinal origin after colorectal cancer. Since publication of the AJCC eighth edition, the World Health Organization has updated the classification and separates grade 3 GEP‐NETs from poorly differentiated neuroendocrine carcinoma. In addition, because of major advancements in diagnostic and therapeutic technologies for GEP‐NETs, AJCC version 9 advocates against the use of serum chromogranin A for the diagnosis and monitoring of GEP‐NETs. Furthermore, AJCC version 9 recognizes the increasing role of endoscopy and endoscopic resection in the diagnosis and management of NETs, particularly in the stomach, duodenum, and colorectum. Finally, T1NXM0 has been added to stage I in these disease sites as well as in the appendix.

Importance Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD). Objective To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment. Design, Setting, and Participants From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD. Carriers of gene variants were assigned 3:1 to either drug or placebo. The present analysis was conducted from April to June 2023. DIAN-TU-001 spans 25 study sites in 7 countries. Biofluids and neuroimaging from carriers of DIAD gene variants in the gantenerumab, solanezumab, and placebo groups were analyzed. Interventions In 2016, initial dosing of gantenerumab, 225 mg (subcutaneously every 4 weeks) was increased every 8 weeks up to 1200 mg. In 2017, initial dosing of solanezumab, 400 mg (intravenously every 4 weeks) was increased up to 1600 mg every 4 weeks. Main Outcomes and Measures Longitudinal changes in CSF levels of neurogranin, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), chitinase 3–like 1 protein (YKL-40), glial fibrillary acidic protein (GFAP), neurofilament light protein (NfL), and plasma levels of GFAP and NfL. Results Of 236 eligible participants screened, 43 were excluded. A total of 142 participants (mean [SD] age, 44 [10] years; 72 female [51%]) were included in the study (gantenerumab, 52 [37%]; solanezumab, 50 [35%]; placebo, 40 [28%]). Relative to placebo, gantenerumab significantly reduced CSF neurogranin level at year 4 (mean [SD] β = −242.43 [48.04] pg/mL; P < .001); reduced plasma GFAP level at year 1 (mean [SD] β = −0.02 [0.01] ng/mL; P = .02), year 2 (mean [SD] β = −0.03 [0.01] ng/mL; P = .002), and year 4 (mean [SD] β = −0.06 [0.02] ng/mL; P < .001); and increased CSF sTREM2 level at year 2 (mean [SD] β = 1.12 [0.43] ng/mL; P = .01) and year 4 (mean [SD] β = 1.06 [0.52] ng/mL; P = .04). Solanezumab significantly increased CSF NfL (log) at year 4 (mean [SD] β = 0.14 [0.06]; P = .02). Correlation analysis for rates of change found stronger correlations between CSF markers and fluid markers with Pittsburgh compound B positron emission tomography for solanezumab and placebo. Conclusions and Relevance This randomized clinical trial supports the importance of fibrillar amyloid reduction in multiple AD-related processes of neuroinflammation and neurodegeneration in CSF and plasma in DIAD. Additional studies of antiaggregated amyloid therapies in sporadic AD and DIAD are needed to determine the utility of nonamyloid biomarkers in determining disease modification. Trial Registration ClinicalTrials.gov Identifier: NCT04623242

Site specific targeting remains an elusive goal for stem cell and gene therapies in the cardiovascular field. One promising option involves use of modified 3D stent designs that deliver larger cell/gene payloads to specific disease sites using the versatility of percutaneous vascular access. Here, we engineered smooth muscle cells (SMCs) placed in a 3D metallic stent scaffold to deliver high local concentrations of an angiogenic gene (VEGF165) in a porcine model of chronic total occlusion involving ameroid placement on the proximal left circumflex (LCx) artery(n≥8 per group). Engineered SMCs were retained within the mesh stent structure (479 ± 47.4 SMC/mm2) and were competent for VEGF production in vitro (8.8 ± 1.8 ng/ml in media). Following implantation, micro CT analyses revealed that stents loaded with VEGF producing SMCs significantly enhanced vasa vasora microvessel density (5.43 ± 0.46 vs 2.14 ± 0.19 vessels/mm2, p<0.001) with a concomitant increase in tissue VEGF protein levels (277.9 ± 85.7 vs 18.8 ± 4.4 pg/mg protein, p<0.0001). Formation of endothelial cell colonies from peripheral blood mononuclear cells was significantly increased with the implantation of VEGF-secreting cells suggesting increased angiogenic potential (7.0 ± 2.0 versus 41.6 ± 4.5, EC:CFU p<0.0001). VEGF secreting mesh stent placement enhanced regional blood flow analyses determined by microsphere analyses as well as improving regional wall motion in the LCx-related territory (p<0.05) as well as left ventricular function assessed in terms of ejection fraction (34.2 ± 6.7% vs 61.2 ± 5.2% P<0.001) and dp/dt (p<0.001) Our data indicate robust clinically relevant angiogenesis can be achieved in a human scale porcine chronic vascular occlusion model following stent based delivery of angiogenic cells. This may have implications for percutaneous delivery of stem cells, genes and secreted therapeutic factors in cardiovascular disease in general and in creation of percutaneous microvascular bypass networks in the setting of chronic vaso-occlusive disease in particular.

Fragile X tremor/ataxia syndrome (FXTAS) is an adult-onset neurodegenerative disorder characterized by premutation expansion of fragile X mental retardation 1 (FMR1) gene. It is a common single-gene cause of tremor, ataxia, and cognitive decline in adults. FXTAS affects the central, peripheral and autonomic nervous systems, leading to a range of neurological symptoms from dementia to dysautonomia. A characteristic imaging feature of FXTAS is symmetric T2 hyperintensity in the deep white matter of the cerebellar hemispheres and middle cerebral peduncle. However, recent studies have reported additional findings on diffusion weighted images (DWI), such as a symmetric high-intensity band-like signal at the cerebral corticomedullary junction. These findings, along with the characteristic cerebellar signal alterations, overlap with imaging findings seen in adult-onset neuronal intranuclear inclusion disease (NIID). Importantly, recent pathology studies have shown that both FXTAS and NIID can manifest intranuclear inclusion bodies, posing a diagnostic challenge and potential for misdiagnosis. We describe a 58-year-old man with FXTAS who received an erroneous diagnosis based on imaging and histopathology results. We emphasize the potential pitfalls in distinguishing NIID from FXTAS and stress the importance of genetic analysis in all cases with suspected NIID and FXTAS for confirmation. Additionally, we present the 7T MRI brain findings of FXTAS.

Abstract Introduction Quantitative rapid eye movement (REM) sleep without atonia (RSWA) recorded during polysomnography (PSG) represents loss of normal REM sleep atonia. RSWA is the neurophysiologic signature of REM sleep behavior disorder (RBD). Visually scored RSWA is a candidate biomarker for synucleinopathies. However, visual RSWA scoring requires expert scoring, limiting widespread application. We comparatively analyzed RSWA in DLB and iRBD using the automated Ferri REM Atonia Index (RAI). Methods We quantitatively analyzed the RAI in 17 DLB and 20 iRBD patients, compared to 20 controls using Hypnolab Software for Sleep Analysis (SWS Soft, Colognola ai Colli, Italy). PSG data were converted to European Data Format (.EDF), and the submentalis surface electromyogram (EMG) signal was notch-filtered at 60 Hertz and rectified. Automatically calculated RAI scores were comparatively analyzed across groups (DLB, iRBD, controls) using Kruskal Wallis H tests for group comparisons, and regression analyses determined relationships between diagnosis, age, and sex. Logistic regression ROC determined optimal RAI for distinguishing iRBD from DLB. When interpreting RAI, lower values represent greater amounts of RSWA, and higher values represent more normal REM atonia. Results Median age was no different between DLB (72.6 years), iRBD (69.4 years), and controls (68.0 years). The DLB group consisted of 16 men and one woman, the iRBD group had 18 men and 2 women, and controls were comprised of 16 men and 4 women. Median RAI was lowest in DLB (0.32), intermediate in iRBD (0.84) and highest in controls (0.96), indicating a gradient in RSWA amounts from DLB patients (highest) to controls (lowest). Regression demonstrated diagnosis independently predicted RAI, controlling for age and sex (adjusted R2=0.64, p=0.0001). The RAI that optimally distinguished iRBD from DLB was 0.48 (specificity 85%, sensitivity 76%, AUC=0.88). Conclusion The RAI demonstrated a clear gradient throughout the Lewy body spectrum; highest (indicating lowest RSWA amounts) in controls, intermediate in iRBD, and lowest (indicating greatest RSWA) in DLB. The RAI is a promising, time efficient and broadly applicable candidate biomarker for DLB and iRBD. Automated quantitative RSWA could be a valuable tool for deep phenotyping throughout the Lewy body disease spectrum. Support (if any) This study was supported by: U01NS100620, R34AG056639, U19AG071754, and P30AG62677.

Abstract Introduction Central sleep apnea (CSA) is associated with several medical conditions (e.g., heart failure, atrial fibrillation) and medications (e.g., opioids, ticagrelor, sodium oxybate and valproic acid). We report a case of a 31-year-old female with bipolar disorder treated with valproic acid diagnosed with central sleep apnea on polysomnography, which revealed an apnea-hypopnea index of 150/hour, central apnea index of 112/hour, nadir oxygen saturation of 78%, and 38.6 minutes with oxygen saturation ≤ 88%. Echocardiogram, electrocardiogram, brain magnetic resonance imaging, serum acylcarnitine and serum ammonia levels were unremarkable. Total and free serum valproic acid level was 33 and &lt; 3 mcg/mL, respectively. Two cases of central sleep apnea associated with valproic acid use, both of which improved upon discontinuation of valproic acid, have been reported in the literature. We started the patient on positive airway pressure and suggested she taper off valproic acid and then repeat polysomnography. Given the possible association between central sleep apnea and valproic acid use, we retrospectively analyzed patients receiving valproic acid at time of polysomnography. Methods We retrospectively identified patients between 2005-2017 who were prescribed valproic acid (n=6,169), and of these 72 received valproic acid within 90 days of polysomnography. After chart review, we were able to confirm that 29 received valproic acid at time of polysomnography via blood levels or clear chart documentation. Results Four patients (13.8 %) demonstrated a central apnea index ≥ 5 per hour (mean apnea-hypopnea index 39.2/hour +/- 32.2/ hour including a central apnea index 11.7 +/- 6.6/hour) during polysomnography. Although one patient (3.4 %), a 2-year-old child with Dravet syndrome and refractory/drug resistant generalized epilepsy, was diagnosed clinically with central sleep apnea, the other three patients were diagnosed with obstructive sleep apnea and had other potential reason(s) for the elevated central apnea index (e.g., opioid use as needed for migraines). Conclusion Our case describes a third report of central sleep apnea possibly associated with valproic acid, and our retrospective study indicates that this association is rare. Prospective sleep studies on patients before and after receiving valproic acid are warranted to determine if valproic acid causes central sleep apnea. Support (if any)

Abstract Introduction n this cross-validation study, the distributions of sleep biomarker-based neurodegenerative disorder (NDD) risk were evaluated across a spectrum of NDD patients and presumed controls which were independent of the model development dataset. Methods Variables that included age, time-REM, non-REM hypertonia, autonomic-activation index, spindle-duration, atypical-N3, time-supine, sleep-efficiency, relative-theta, and theta/alpha obtained with Sleep Profiler were used to train a 4-class machine learning algorithm that generated probabilities of NDD risk for the groups: Alzheimer’s dementia (AD), Lewy body disorder (LBD), prodromal synucleinopathy (pSYN based on REM sleep behavior disorder patients), and controls (CG). Records with CG output probabilities &gt;70% were labeled Probably-normal, and from 45-70% Likely-normal with indications of a NDD added when the LBD, AD or pSYN risks exceeded approximately 25%. Similar thresholds were used to assign Likely- or Probable- LBD, AD, pSYN or Mixed based on the group probabilities. This cross-validation study was designed to use datasets that were independent of those used to train the classification algorithm. Thus, NDD risk distributions were evaluated in patients with mild cognitive impairment (MCI=71), Parkinson’s disease (PD=16), progressive supranuclear palsy (PSP=21) and control subjects (NC=41) with Mini-Mental State Exam scores&gt;28 and/or normal for MCI by Petersen criteria. Results In the MCI group, NDD risk assignments were Probable-AD=26%, -Mixed=10%, -LBD=1%, Likely-AD= 7%, -Mixed=6%, -LBD=3%, -pSYN=1%, Likely-Normal indications-AD=9%, -pSYN=7%, -Mixed=4%, and Probably-Normal=26% In the PSP group, Probable-LBD=43%, -Mixed=29% and -pSYN=4%, Likely-Mixed=10%, Likely-Normal indications AD=10%, and Probably-Normal=4%. In the PD group, Probable-LBD=13%, -pSYN=13%, -AD=6%, Likely-Mixed=19%, -pSYN=6%, Likely-Normal Indications-pSYN=19%, -AD=12%, Likely-Normal=6% and Probably-Normal=6% In the NC group, 83% were assigned minimal NDD risk with Probably-Normal=70%, Likely-Normal plus indications=13%, but with Likely NDD=13% and Probable NDD=4%. Conclusion NDD risks were disbursed in a manner consistent with the range of severities expected In MCI and PD groups, with 25% exhibiting relatively normal sleep patterns. Over 70% of the PSP patients exhibited probable NDD risk, with patterns similar to those with LBD. The NC NDD risk distributions were consistent with those assigned to the CG used for model development. Support (if any) NIH grants R44AG050326, R44AG054256, RO1AG060477, R33AG064271, ULRR024150, R34AG056639.

Abstract Introduction In this pilot study, the diagnostic agreement for sleep biomarker-based neurodegenerative disorder (NDD) risk probabilities was evaluated in patients with Alzheimer’s disease dementia (AD), Lewy Body disease (LBD), and isolated REM sleep behavior disorder (iRBD) and controls with a Mini-Mental State Exam scores&gt;28. Methods Sleep biomarkers recorded with the Sleep Profiler (Advanced Brain Monitoring, Inc) were used as inputs to a 4-class machine learning algorithm trained to assign NDD risk probabilities to AD=27, LBD=19, iRBD=15 and controls (CG=58). Input variables included age, time-REM, non-REM hypertonia, autonomic-activation index, spindle-duration, atypical-N3, time-supine, sleep-efficiency, relative-theta, and theta/alpha. Records with CG output probabilities &gt;70% were labeled Probably-normal, and from 45-70% Likely-normal with indications of a NDD added when the LBD, AD or prodromal synucleinopathy (pSYN) risks exceeded approximately 25%. Similar thresholds were used to assign Likely- or Probable- LBD, AD, or pSYN based each of the group probabilities. Classification accuracies were evaluated in AD=37, LBD=19, iRBD=19 and CG=61 records. Longitudinal test-retest reliabilities were assessed for CG (n=45, range 8-56 months), and after six-months for LBD (n=10) and AD (n=9). Results In the AD group, NDD risk assignments were consistent with diagnoses=85%, with Probable-NDD=59%, Likely-NDD=11%, Normal plus AD/Mixed indications=15%, but with 5%=Probably-normal. In the LBD group, assigned risks were consistent with the diagnosis=79%, with Probable-NDD=74%, Normal with pSYN indications=5%, but with 11%=Probably-normal. In the iRBD group, Probable-NDD=42%, Normal plus pSYN indications=26% and Probably-normal=32%. In the CG group, 89% were assigned minimal NDD risks with Probably-normal=67%, Normal plus indications=22%, but with Likely NDD=8% and Probable NDD=3%. The AD test-retest reliability showed the same NDD classifications=78%, with slightly increasing=11% and decreased=11%. In the LBD group, the same NDD classifications were achieved=80%, with trending equivalence=10%, and decreasing severity=20%. The CG test-retest reliability showed the same NDD classifications=76%, with trending equivalence=22%, and increased severity=2%. Conclusion Consistencies between the diagnoses and assigned NDD risks and test-retest classification agreements were approximately 80% in the AD, LBD, and CG groups. In the iRBD group, the NDD risks were disbursed consistent with the range of expected severities. These results needed to be cross-validated in independent NDD datasets. Support (if any) NIH grants R44AG050326, R44AG054256, RO1AG060477, R33AG064271, ULRR024150, R34AG056639.