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Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer, arising from both B and T cell lineages (B-ALL and T-ALL). Current therapy exploits ALL cells’ low expression of asparagine synthetase (ASNS) by using L-asparaginase, a bacterial enzyme that depletes circulating asparagine. However, resistance can emerge through induction of ASNS, mediated in part by the amino acid stress sensor GCN2. In this study, we addressed the efficacy of L-asparaginase in combination with genetic or pharmacological inhibition of GCN2 and the ASNS inhibitor ASX-173. Using a Kras G12D -driven mouse model of T-ALL, we found that GCN2 is dispensable for leukemogenesis. However, genetic inactivation or pharmacologic inhibition of GCN2 sensitized ALL cells to asparagine depletion, correlating with impaired ASNS induction. While GCN2 targeting enhanced sensitivity to asparagine depletion, a subset of Gcn2 –/– T-ALL cells retained high ASNS expression and remained resistant to L-asparaginase. Likewise, some human T-ALL cells with elevated ASNS levels were refractory to GCN2 inhibition even under asparagine-depleted conditions. When combined with L-asparaginase, ASX-173 effectively eliminated ASNS hi leukemic cells in vitro and in vivo. These findings suggest that direct targeting of ASNS provides therapeutic benefit in leukemias that express high levels of ASNS and are resistant to GCN2 inhibition under asparagine-depleted conditions.

Abstract INTRODUCTION Tau species lacking truncation of the N‐terminal region, including plasma N‐terminal tau fragment 1 (NT1), have been previously associated with cognitive decline, neurodegeneration, and tau pathology in late‐onset sporadic Alzheimer's disease (AD). METHODS Here, we examined cross‐sectional and longitudinal plasma NT1 as a possible predictor of cognitive, clinical, and core AD biomarker trajectories in autosomal dominant AD (ADAD). RESULTS NT1 levels in ADAD mutation carriers (MC; n = 132) increased across the disease continuum, compared to non‐carriers (NC; n = 75), becoming elevated about a decade prior to estimated symptom onset. Cross‐sectional and longitudinal NT1 levels in MC were associated with clinical, cognitive, and biomarker changes. NT1 increases continued in symptomatic phases of disease, a distinct trajectory from that seen with CSF p‐tau217 and other phospho‐tau species. DISCUSSION Together, our results suggest that plasma NT1—alone or combined with other tau measures—may be useful in studying AD‐related clinical, cognitive, and biomarker outcomes. Highlights Leveraging a deeply phenotyped cohort of individuals carrying a pathogenic variant for autosomal dominant Alzheimer's disease (ADAD) and their non‐carrier family members, our results suggest that plasma N‐terminal tau fragment 1 (NT1) levels mirrored changes in clinical, cognitive, and neurodegenerative measures in ADAD, particularly in late asymptomatic and early symptomatic phases of disease. NT1 levels correlated with cerebrospinal fluid (CSF) measures of tau pathology but less so with CSF or imaging measures of β‐amyloid pathology. Together with previous supportive findings in preclinical and symptomatic sporadic AD, these results suggest that plasma NT1—alone or combined with other tau measures—may be useful in studying AD‐related tau pathology and neurodegeneration across a wide spectrum of disease.

Abstract INTRODUCTION Increased white matter hyperintensity (WMH) volume is a common but non‐specific finding in AD. This study investigates the effect of baseline WMH volume and APO E ε4 on magnetic resonance imaging (MRI)‐visible hemorrhagic lesion emergence. METHODS We included A4 participants with 0/1 hemorrhagic lesion at baseline and >1 post‐baseline MRI. We examined age, sex, amyloid, WMH, APOE ε4, and cardiovascular risk as predictors of whether people would accrue ≥2 hemorrhagic lesions by their last MRI. RESULTS Among 1097 individuals with 0/1 baseline lesion, 120 had at least two hemorrhagic lesions on their last MRI. Elevated baseline WMH (odds ratio [OR] = 2.3, p = 0.002) and APOE ɛ4/ɛ4 (OR = 4.8, p < 0.001) independently predicted membership to this group. Both hetero‐ and homozygous APOE ɛ4 carriers with low WMH volume had a low risk of accumulating hemorrhagic lesions. DISCUSSION These results support the independent consideration of WMH and APOE ɛ4 in the natural history of hemorrhagic lesion accumulation and suggest that individuals with low WMH volume have a low short‐term risk, irrespective of APOE genotype. Trial Registration : NCT02008357 Highlights Elevated baseline white matter lesion volume is related to the risk of ARIA‐H emergence. The effects of white matter lesion volume and APOE ɛ4 on ARIA‐H are independent. APOE ɛ4 carriers with low white matter lesion volume had a low risk of ARIA‐H emergence.

AbstractBackgroundThe balance between production, clearance, and toxicity of Ab peptides is central to AD pathobiology. Though highly variable in terms of age of symptom onset (AAO), hundreds of pathogenic variants in Presenilin‐1 (PSEN1) cause autosomal dominant forms of AD (ADAD). PSEN1 forms the catalytic core of the γ‐secretase complex and thereby directly mediates the production of longer, aggregation‐prone Aβ peptides relative to shorter, non‐aggregating peptides. We hypothesized that the broad AAO and biomarker heterogeneity seen across ADAD would be predictable based on mutation‐specific differences in γ‐secretase function, as measured by a ratio of production of shorter vs. longer Aβ species.MethodsAβ‐37, 38, 40, 42, and 43 production was quantified from 162 unique PSEN1 variants expressed in HEK293 cells engineered to lack endogenous wild‐type PSEN1/2 (Figure 1). Prediction of AAO was carried out in 107 PSEN1 variants (characterized by Liu et al, 2022) and then replicated with a set 55 unique PSEN1 variants represented in the Dominantly Inherited Alzheimer Network (DIAN; n = 190 corresponding variant carriers with detailed cognitive and biomarker data; Figure 2).ResultsMutation‐level variations in Aβ production, including a novel composite representing γ‐secretase function (lower score = less g‐processivity), from the cellular model were highly predictive of actual AAO across the 162 mutants examined (Non‐DIAN variants [N = 107]: r = 0.71, p <2.2e‐16; DIAN variants [N = 55]: r = 0.61, p = 6.10e‐07). Our cell‐based γ‐secretase function composite was strongly associated with cerebral PiB‐PET β‐amyloid burden (B[SE] = ‐0.03[0.01], p = 4.06e‐07), MRI gray matter volume (B[SE] = 44.22[6.4], p = 5.15e‐01), cerebrospinal fluid Aβ42/40 (B[SE] = 6.3e‐04[1.5e‐04], p = 4.46e‐05) and phosphorylated tau‐217 (B[SE] = ‐0.01[0.002], p = 1.98e‐05), Clinical Dementia Rating®‐ Sum of Boxes (B[SE] = ‐0.07[0.02], p = 4.86e‐05), and Mini‐Mental State Exam (B[SE] = 0.11[.03], p = 2.17e‐04).ConclusionsBiochemical variations in γ‐secretase function across PSEN1 pathogenic variants broadly predicted the cross‐sectional clinical, cognitive, and biomarker course of ADAD, including AAO. These findings elucidate the critical link between γ‐secretase function, Aβ production, and severity of AD. The novel approach designed here also represents a tool to account for heterogeneity in ADAD clinical trials and to assess the pathogenicity of PSEN1 variants of unknown significance or with limited family history.

In this article, we present a flexible model for microbiome count data. We consider a quasi‐likelihood framework, in which we do not make any assumptions on the distribution of the microbiome count except that its variance is an unknown but smooth function of the mean. By comparing our model to the negative binomial generalized linear model (GLM) and Poisson GLM in simulation studies, we show that our flexible quasi‐likelihood method yields valid inferential results. Using a real microbiome study, we demonstrate the utility of our method by examining the relationship between adenomas and microbiota. We also provide an R package “fql” for the application of our method.

AbstractAlthough pathogenic variants in PSEN1 leading to autosomal‐dominant Alzheimer disease (ADAD) are highly penetrant, substantial interindividual variability in the rates of cognitive decline and biomarker change are observed in ADAD. We hypothesized that this interindividual variability may be associated with the location of the pathogenic variant within PSEN1. PSEN1 pathogenic variant carriers participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study were grouped based on whether the underlying variant affects a transmembrane (TM) or cytoplasmic (CY) protein domain within PSEN1. CY and TM carriers and variant non‐carriers (NC) who completed clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF) as part of their participation in DIAN were included in this study. Linear mixed effects models were used to determine differences in clinical, cognitive, and biomarker measures between the NC, TM, and CY groups. While both the CY and TM groups were found to have similarly elevated Aβ compared to NC, TM carriers had greater cognitive impairment, smaller hippocampal volume, and elevated phosphorylated tau levels across the spectrum of pre‐symptomatic and symptomatic phases of disease as compared to CY, using both cross‐sectional and longitudinal data. As distinct portions of PSEN1 are differentially involved in APP processing by γ‐secretase and the generation of toxic β‐amyloid species, these results have important implications for understanding the pathobiology of ADAD and accounting for a substantial portion of the interindividual heterogeneity in ongoing ADAD clinical trials.

AbstractBackgroundBlood based biomarkers that predict cognitive decline and Alzheimer’s disease (AD) pathology have the potential to accelerate AD therapeutic development and improve clinical care. Prior work suggests that plasma biomarkers of tau pathology (particularly post‐translational modifications of tau) may be highly useful in diagnosis and risk stratification for AD‐related neurodegeneration and cognitive decline. Levels of tau species lacking truncation of the N‐terminal region, particularly plasma and cerebrospinal fluid (CSF) levels of N‐terminal tau fragment 1 (NT1), have previously been shown to predict cognitive decline, neurodegeneration, and tau pathology in preclinical and symptomatic late‐onset AD. Here we examined plasma NT1 as a possible predictor of cognitive, clinical, pathologic, and neurodegenerative trajectories in autosomal dominant AD (ADAD) using data from the Dominantly Inherited Alzheimer Network Observational Study (DIAN‐Obs).MethodsAssociations between plasma NT1 levels and Mini‐Mental State Exam (MMSE), Clinical Dementia Rating SumBox® (CDR‐SB), hippocampal volume (HV), estimated years to symptom onset (EYO), Pittsburgh‐Compound‐B PET, and CSF Aβ42, and p‐tau181 were assessed using linear regression (150 pathogenic variant carriers, 81 non‐carriers; mean[SD] carrier age = 40.1 [10.4] years and EYO = ‐5.4 [10.4]). Plasma NT1 was measured using the Quanterix HD‐X platform. PET, MRI, clinical, and biofluid measures were derived using previously described procedures in DIAN‐Obs.ResultsCross‐sectional plasma NT1 levels in ADAD carriers were significantly associated with MMSE, CDR‐SB, HV, and p‐tau181 even after adjusting for EYO (Table 1; Figure 1). NT1 levels statistically diverged between carriers and non‐carriers 6.8 years before estimated symptom onset (Figure 2). In contrast, plasma NT1 levels were not significantly correlated with measures of β‐amyloid pathology after adjusting for EYO.ConclusionPlasma NT1 levels mirrored changes in clinical, cognitive, and neurodegenerative measures in ADAD, particularly in late asymptomatic and early symptomatic phases of disease. NT1 levels correlated with CSF measures of tau pathology, but NT1 levels were not strongly associated with CSF or PET measures of β‐amyloid pathology, unlike some previously‐studied plasma tau measures. Together with previous supportive findings in preclinical and symptomatic sporadic AD, these results suggest that plasma NT1 may be a useful biomarker of AD‐related tau pathology and neurodegeneration across a broad spectrum of disease.

AbstractBackgroundRates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross‐sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN‐Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini‐Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®‐SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4‐year trial with annual assessments; 80% power; α = 0.05).ResultsPSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = ‐0.42[0.1], p=0.002), CDR®‐SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = ‐58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.

AbstractBackgroundRates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross‐sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN‐Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini‐Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®‐SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4‐year trial with annual assessments; 80% power; α = 0.05).Results PSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = ‐0.42[0.1], p=0.002), CDR®‐SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = ‐58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.

AbstractBackgroundAccurate automated wide QRS complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) can be accomplished using calculations derived from computerized electrocardiogram (ECG) data of paired WCT and baseline ECGs.ObjectiveDevelop and trial novel WCT differentiation approaches for patients with and without a corresponding baseline ECG.MethodsWe developed and trialed WCT differentiation models comprised of novel and previously described parameters derived from WCT and baseline ECG data. In Part 1, a derivation cohort was used to evaluate five different classification models: logistic regression (LR), artificial neural network (ANN), Random Forests [RF], support vector machine (SVM), and ensemble learning (EL). In Part 2, a separate validation cohort was used to prospectively evaluate the performance of two LR models using parameters generated from the WCT ECG alone (Solo Model) and paired WCT and baseline ECGs (Paired Model).ResultsOf the 421 patients of the derivation cohort (Part 1), a favorable area under the receiver operating characteristic curve (AUC) by all modeling subtypes: LR (0.96), ANN (0.96), RF (0.96), SVM (0.96), and EL (0.97). Of the 235 patients of the validation cohort (Part 2), the Solo Model and Paired Model achieved a favorable AUC for 103 patients with (Solo Model 0.87; Paired Model 0.95) and 132 patients without (Solo Model 0.84; Paired Model 0.95) a corroborating electrophysiology procedure or intracardiac device recording.ConclusionAccurate WCT differentiation may be accomplished using computerized data of (i) the WCT ECG alone and (ii) paired WCT and baseline ECGs.