Citations

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Lung Cancer Screening provide criteria for selecting individuals for screening and offer recommendations for evaluating and managing lung nodules detected during initial and subsequent annual screening. These NCCN Guidelines Insights focus on recent updates to the NCCN Guidelines for Lung Cancer Screening.

Abstract There are ~100 genes or copy number variants (CNVs) used in genetic testing for Autism Spectrum Disorder (ASD, or autism). These genes are protein-coding, and the associated phenotypes often extend beyond socio-behavioral traits seen in autism including cognitive/medical complexities, epilepsy, and ADHD. Here, we characterize 27 males with ASD through whole genome sequencing (WGS), delineating X-chromosome microdeletions that implicate the long non-coding RNA (lncRNA) PTCHD1-AS as an ASD-susceptibility gene (OR=2.56, p=0.01). Two Ptchd1-as knockout (KO) murine models, created by removing the evolutionarily conserved exon-3, show ASD-like features in males, increasing repetitive behaviors and impairing typical social behavior and communication without overt cognitive comorbidities or ADHD-like behaviors. Hippocampus-dependent synaptic function, complex learning, and locomotor activity are unaffected in KO mice. Native nuclear-enriched mouse Ptchd1-as showed sustained expression from post-natal day-7 onward in the dorsal striatum, a predominantly GABAergic brain region implicated in ASD. Multi-omics revealed transcriptomic alterations in striatal oligodendrocyte, astrocyte and neurons impacting myelination and plasticity pathways. Disrupting Ptchd1-as led to reductions in conventional Protein Kinase-C, altered Src and GSK3α/β phosphorylation, and an enhancement of synaptic plasticity (long-term potentiation and long-term depression). Together, these findings implicate striatal molecular and circuit level dysregulation via Ptchd1-as in ASD etiology.

Background: Previous studies have shown that people with multiple sclerosis (MS) had frequent healthcare visits up to 10 years before being diagnosed but with no information from magnetic resonance imaging (MRI) scans of the connection with the radiologically isolated syndrome (RIS). Objective: To analyze healthcare use 3 years before the RIS diagnosis. Methods: We examined healthcare usage before the first scan in RIS cases from 2010 to 2019. RIS subjects were identified from the French National MS observatory and compared to the general population (matched 10:1) and MS patients (matched 4:1). Results: Among 482 RIS individuals, 223 (46.3%) were not linked to the healthcare resources database. The remaining RIS individuals (53.7%) had higher healthcare usage before their RIS diagnosis for issues related to neurology visits, headaches (odds ratio (OR): 3.34, confidence interval (CI): [2.00–5.57], p < 0.0001), and the use of anti-migraine drugs (OR: 2.61, CI: [1.37–4.99], p = 0.004) compared to MS. Conclusion: Only about half of RIS patients had MS-selected healthcare resources, which allowed for data linkage. Those who did seek care before their RIS diagnosis were most commonly known for other neurological comorbidities. These findings do not support the idea of a systemic prodrome before RIS diagnosis.

AbstractBackgroundIn 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), mild cognitive impairment (MCI), and controls (CG) with a Mini‐Mental State Exam scores ≥28.MethodsSleep 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, isolated REM sleep behavior disorder=15, and 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. Distributions of NDD risk were then assigned to AD=37, LBD=19, MCI=71, and CG=106 records.Records with CG output probabilities ≥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 Probably‐ LBD, AD, pSYN, or Mixed based on the group probabilities. Likely‐Normal with indications consistent with the diagnosis trended toward agreement.ResultsThe proportions of each group with classifications consistent with the diagnosis or trended toward agreement were CG=86%, MCI=75%, LBD=79%, and AD=87%.In the CG group, NDD risk assignments were Probably‐Normal=68% and Likely‐Normal with NDD indications=18%, Likely‐NDD=10%, and Probable‐NDD=4%.The MCI group was assigned Probable‐NDD=38% (AD=26%, Mixed=10%, LBD/pSYN=2%), Likely‐NDD=17% (AD=7%, Mixed=6%, LBD=3%, pSYN=1%), Likely‐Normal with indications=20% (AD=9%, pSYN=7%, Mixed=4%) and Probably‐Normal=25%The LBD group’s assigned risks consistent with the diagnoses included Probable‐NDD=74% and Likely‐Normal with pSYN indications=6% but included inconsistencies from Probable‐AD=5%, Likely‐Normal with AD indications=5%, and Probably‐Normal=11%.AD group’s consistent risk classifications included Probable‐NDD=60%, Likely‐NDD=11%, Likely‐Normal with AD/Mixed indications=13% and countered by inconsistencies from Probable‐LBD/pSYN=8%, Likely‐Normal with pSYN indications=3%, and Probably‐Normal=5%.ConclusionsConsistencies between the diagnoses and assigned NDD risks agreements exceeded 75% in all four groups. Studies are underway to confirm the test‐retest reliability and/or evaluate NDD risk probabilities in other patient populations.Support: NIH grants R44AG050326, R44AG054256, RO1AG060477, R33AG064271, ULRR024150, R34AG056639.

INTRODUCTION: The alfapump system has been shown to be a possible alternative to repeat therapeutic paracentesis (TP) in selected patients with refractory ascites (RA). The objective of this study was to assess the safety and efficacy of alfapump on ascites control and quality of life in these patients. METHODS: Patients with cirrhosis and RA requiring ≥2 TPs 30 days prior were enrolled and followed for 24 months postimplant. Primary efficacy end point assessed at 6 months was reduction in paracentesis requirement; safety end point was device-related adverse events resulting in intervention, explant, or death. RESULTS: Forty patients with RA (mean Model of End-stage Liver Disease-Sodium: 15 ± 4) received an alfapump. TP requirement was decreased from 3.2 ± 1.5 sessions per month preimplant to 0.2 ± 0.6 sessions per month at 6 months postimplant ( P < 0.001), with 77% of patients having ≥50% reduction. Six pumps (15%) were explanted within 6 months due to device-related adverse events, 3 (7.5%) due to pump site skin erosion, and 3 (7.5%) due to bladder discomfort. Twenty-four renal events occurred in the 0–6 month postimplant period; 16 cases were readily reversible stage 1 acute kidney injury. Ascites-related symptoms assessed with an Ascites Q score improved from 51.0 ± 19.3 preimplant to 32.2 ± 21.9 at 6 months postimplant ( P < 0.001). Physical but not mental components of Short Form 36 improved ( P < 0.001). The 5 deaths within 6 months postimplant were not directly related to the device or alfapump therapy. DISCUSSION: The alfapump system effectively controlled ascites, which improved quality of life. It may be considered as an alternative to repeat TP in select patients with RA. Complication rates were similar to those expected in patients with RA.

AbstractBackgroundLate Onset Alzheimer’s Disease (LOAD) is the most common neurodegenerative disorder. Carriers of an ɛ4 allele of the apolipoprotein E gene (APOE) have significantly increased risk of developing LOAD. LOAD is also strongly sex biased. Besides the well‐established role of sex hormones, the impact of genetic sex combined with APOE genotypes has not been studied. Sex chromosome dosage (SCD) is the main genetic difference between females (XX) and males (XY). Despite dosage compensation by X chromosome inactivation (XCI), some X‐linked genes remain expressed from the inactive X (Xi) and are female biased in expression. Many of these genes are related to neurological and immune functions and could contribute to neuroinflammation in AD.MethodTo understand the genetic interactions between autosomal risk (APOE) and sex‐bias in AD, we are generating isogenic sets of hiPSCs with various sex chromosome complements and APOE genotypes. We have derived XXY/XY, XY/X, and XX/X isogenic pairs by reprogramming cells from naturally mosaic individuals or by selective removal of the Xi in vitro. These lines uniquely position us to differentiate the effects of X chromosome dosage and/or presence of a Y chromosome, while minimizing genetic variability and environmental or hormonal confounders. Currently, we are also constructing APOE ɛ3 and ɛ4 alleles in our paired hiPSC lines with differing sex chromosome content using gene editing.ResultStarting from an XXY/XY isogenic pair, we have generated an hiPSC series with six different genotypes of APOE ɛ3/ɛ3, ɛ3/ɛ4 or ɛ4/ɛ4 alleles with either the XXY or XY genotype. Preliminary results in differentiated neural precursor cells show differential expression of sex‐linked genes in relation to SCD. We also observed genome‐wide changes in gene expression and DNA methylation. Subsets of autosomal sex‐biased genes were differentially affected either by X chromosome dosage, presence of a Y, or both.ConclusionThe new hiPSC lines are being differentiated to AD‐relevant cell types, including neurons, microglia, and cortical organoids, for transcriptomic and functional analyses to elucidate how APOE alleles and genetic sex interact to modulate risk in LOAD pathology.

AbstractBackgroundMild Cognitive Impairment (MCI) is a pre‐dementia state where impaired cognitive domains (memory, executive, visuospatial processing, language) may predict underlying pathology, e.g. Alzheimer’s disease(AD), Lewy body (LB), and other. Delineating neuropathological heterogeneity in MCI and their associations with neuropsychological profiles are important in identifying individuals at risk of further deterioration. We aimed to characterize the neuropathological heterogeneity in cases with a diagnosis of MCI.MethodCases with a final consensus cognitive diagnosis of MCI (n = 128) prior to death were selected from the Arizona Study of Aging and Neurodegenerative disorders (AZSAND). Groups were divided into amnestic (aMCI) and non‐amnestic MCI (naMCI), single and multi‐domain impairment, and specific domain impairment (executive, language, visuospatial) was explored. Presence and severity of neuropathology including AD, LB, cerebral white matter rarefaction (CWMR), cerebral amyloid angiopathy (CAA), cerebral infarcts and microinfarcts (cortical and subcortical), TAR DNA‐binding protein 43 (TDP‐43), and apolipoprotein E (ApoE) status were compared between MCI subtypes.ResultThe number of cases meeting neuropathological criteria for AD was not different between aMCI (36.4%) and naMCI (22.6%) while co‐existent PD was less frequent in aMCI (19.5% vs 38.7%). When compared to naMCI (n = 31), the aMCI (n = 85) group had an older age of death (p = 0.001), less educational years (p = 0.04), a higher number of subcortical infarcts (p = 0.012), a higher regional density of neurofibrillary tangles (p = 0.027) and a lower density of LB (p = 0.015) in the temporal lobe, and CWMR in tended to be more severe in the frontal lobe (p = 0.052). Those with single domain aMCI had less CWMR (p = 0.001) compared to the multidomain. Within the naMCI group, those with single domain MCI had higher proportions of CAA (p = 0.042), and lower LB density (p = 0.019) compared to multidomain. CWMR was more severe (p = 0.026) inConclusionA high heterogeneity was observed between MCI subtypes. While AD pathology was similar between groups, regional anatomical differences were observed. Vascular pathology including subcortical infarcts, CWMR and CAA appear to be commonly associated with both aMCI and naMCI respectively while CWMR was associated with executive dysfunctions. CWMR, CAA and LBs appear to be more frequent in multidomain aMCI and naMCI respectively.

AbstractBackgroundLewy body (LB) diseases can present with overlapping prodromal, cognitive, motor, autonomic or neuropsychiatric symptoms. Intuitively, greater symptom severity should correlate with greater pathological burden, but this has not been consistently shown. LB pathology does not translate to clinical expression in Incidental LB disease. While several composite scores/toolkits utilize overlapping schemes for diagnosis, a composite data‐derived score to predict LB pathologic burden is lacking. We aimed to utilize an autopsy‐confirmed cohort, and validated, brief, and standardized clinical, functional, pathologic assessments, and machine learning (ML)/quantitative modeling techniques to identify clusters and importance rankings among assessments/measures to predict LB pathologic severity and density.MethodA total of 234 subjects with neuropathological finding of LB at autopsy in the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) who were classified as Cognitively Unimpaired or Mild Cognitive Impairment after their first study clinical evaluation were included. Of these, 145 subjects had complete scores for 32 of 46 measures (clinical, cognitive, behavioral and functional) that were utilized as predictors of LB pathology. Olfactory function was assessed using the University of Pennsylvania Smell Identification Test (UPSIT). LB severity was assessed by the Unified Staging System for Lewy Body Disorders (USSLB). Several ML algorithms and quantitative prediction models were explored and compared: artificial neural network (ANN), partial least square regression (PLSR), support vector regression (SVR), relevance vector regression (RVR) and ensemble forest regression (EFR) with leave‐one‐out (LOO) scheme. Game‐theory based Shapley methods assessed the impact, including rankings, consistency and magnitude, of model predictors.ResultRVR predicted aggregate LB density with large effect size (R2 = 0.691, p<0.00001). ANN predicted USSLB severity stage with large effect size (R2 = 0.74, p<2.5e‐43). All other ML algorithms/models provided substantial prediction. Across all models, UPSIT was the most influential predictor (>65%), followed by Controlled Oral Word Association Test (COWAT) and age.ConclusionThese preliminary and exploratory results support the utilization of ML techniques/models to assess LB pathologic burden with key measures collected in relatively small samples. UPSIT was consistently ranked highest impactful among clinical and functional measures/predictors. Integrated together in ML/data‐derived composites, UPSIT, COWAT and other clinical characteristics may be of antemortem utility to predict USSLB stages.