Citations

AbstractBackgroundAutosomal dominant Alzheimer disease (ADAD) is characterized by genetic mutations affecting the beta‐amyloid (Aβ) pathway. However, vascular and immune factors play important roles which are not completely understood. Understanding the function of the neurovascular unit (NVU) comprised of neurons, glial cells, and vasculature, at different disease stages appears ideal to developing and evaluating therapeutics. Omics approaches can inform NVU changes and their disease associations.MethodsCSF proteomic data using the Somalogic® platform was generated from 485 participants in the DIAN study, who also had PiB‐PET and MRI assessing Aβ burden, white matter hyperintensity (WMH), and cerebral microhemorrhage (CMH). From previously published AD studies, we identified 33 NVU‐associated proteins with corresponding Somalogic aptamers (Figure 1). We used Principal Component Analysis (PCA) on participants with complete data (n=262, 166 mutation‐carriers and 96 non‐carriers) to find groups of proteins associated with mutation status and disease stage as measured with estimated year to symptom onset (EYO), PiB‐PET, and clinical status. Linear‐mixed effect models and two‐part zero‐inflated negative binomial mixed models further evaluated the link between significant principal components (PCs) and WMH and CMH, respectively. Models accounted for age, APOE‐e4 status, sex, and education.ResultsThe first ten PCs explained >60% of the variance in NVU‐related protein levels (Figure 2A) with only PC5 (4.8%) associated with mutation*EYO, suggesting relationship with ADAD‐specific disease progression (***p<0.0001, Figure 2B). While asymptomatic PiB‐negative individuals were not significantly different from non‐carriers, asymptomatic PiB‐positive individuals had higher PC5 scores than non‐carriers and symptomatic individuals scored still higher (**p<0.005, ***p<0.0001, Figure 2C). The main proteins composing PC5 were: neurofilament light‐chain, angiopoietin‐2, SMOC1, LRP1, E‐selectin, and sTREM2, suggesting strong association with proinflammatory glial response from neuronal injury (Figure 2D). PC5 was also associated with WMH volumes (*p<0.05, Figure 3A) and with CMH count in participants with CMH (**p<0.005, Figure 3B).ConclusionsThis PCA approach indicates that some groups of NVU‐associated proteins are related with mutation status and disease stage, and that they are differentially associated with features of ADAD such as white matter integrity as measured by WMH volume. Weighted Correlation Network Analysis will be of interest to further understand these associations.Funding: K01AG080123, RF1‐AG044546, UF1AG032438

AbstractBackgroundAlzheimer disease (AD) related cognitive decline occurs at relatively young ages in individuals with Down syndrome (DS, early‐mid 50s) and in those with autosomal dominant mutations (ADAD, 40‐50s). Both groups show similar patterns of amyloid accumulation. We examined if brain volumes are similarly affected by AD pathology in individuals with DS and ADAD.MethodData for cognitively stable and declining participants was obtained from the Alzheimer Biomarker Consortium‐Down Syndrome (ABC‐DS) and the Dominantly Inherited Alzheimer Network (DIAN). Stability/decline was identified based on cognitive testing and interview of individuals and caregivers by trained assessors. Cognitively stable family members without DS/ADAD mutations were recruited as controls from both studies. Participants underwent MRI and amyloid positron emission tomography (PET) scans from which brain volumes and amyloid (centiloids) were derived, respectively. Participants from DIAN had Pittsburgh Compound‐B (PIB) scans, ABC‐DS had PIB or florbetapir. Nonlinear cross‐sectional associations between regional brain volumes and estimated years to onset of cognitive decline (EYO, negative values before onset, positive after) and centiloid were evaluated using generalized additive models while controlling for sex and random effects of family. EYO was set to 52 for all participants with DS and based on parental decline/mutation type for participants with ADAD. EYO for controls was based on the EYO of their family member.ResultData from 239 participants with DS (47 declining), and 340 participants with ADAD (122 declining), and 263 familial controls were included. Higher EYO and centiloid values were associated with lower brain volumes in almost all regions. At earlier EYOs, individuals with DS typically had smaller regional volumes than ADAD or sibling controls, with volume declining linearly across the EYO range. By contrast, ADAD mutation carriers had similar volumes to non‐carriers at early EYOs, with volumes diverging as early as 10 years before decline. Brain volumes and centiloid values were inversely related in ADAD and DSAD. Volume in key cortical regions were similar by the expected year of onset in both groups.ConclusionADAD and DSAD demonstrated different temporal patterns of regional neurodegeneration prior to cognitive change despite being similarly affected by early onset amyloid.

AbstractBackgroundLate‐Onset Alzheimer’s Disease (LOAD) is characterized by genetic heterogeneity and there is no single model explaining the genetic mode of inheritance. To date, more than 70 genetic loci associated with AD have been identified but they explain only a small proportion of AD heritability. Structural variants (SVs) may explain some of the missing AD heritability, and specifically, their segregation in AD families has yet to be investigated.MethodWe analyzed WGS data from 197 NHW families (926 subjects, 58.5% affected) and 214 CH families (1,340 subjects, 59.17% affected). Manta, Absinthe, and MELT were used for large insertions/deletions calling from short‐read WGS, combined with Sniffles2 calls from 4 ONT‐sequenced genomes and an external SV call set from HGSVC on 32 PacBio‐sequenced genomes from the 1000 Genomes Project. Genotyping produced a unified project‐level VCF. We identified 45,251 insertions and 76,566 deletions genome‐wide. Variants were tested for segregation and pathogenicity using Annot‐SV, cadd‐SV, and Variant Effect Predictor. Segregation required SV presence in all affected family members and only in unaffected members five years younger than average disease onset.ResultWe identified 453 insertions and 598 deletions segregating in 78.68% and 87.31% of NHW families, respectively. In CH families, 432 insertions and 460 deletions were segregating in 75.23% and 72.90% of the families, respectively. Genes overlapping with the SVs exhibited high expression levels in brain tissues. Notably, around 93% of insertions and 76% of deletions segregating in NHW and CH families were less than 1 kilobase pair (1kbp) in length. A total of 79 insertions and 96 deletions were found to be segregating in both NHW and CH families. Interestingly, a segregating insertion was observed in CH families overlapping within the CACNA2D3 gene, which was previously reported in a CH GWAS for clinical AD. A deletion segregating in NHW overlapped with the PSEN1, and another in a CH family overlapped with the PTK2B gene.ConclusionOur findings suggested that there are several SVs associated with familial AD across CH and NHW families. Prioritizing the SVs based on their effects on gene function and expression will be helpful in understanding their contributions in AD.

AbstractBackgroundThe prevalence of dementia in populations that are underrepresented in research is projected to increase with population aging. Latino and Black individuals, the largest underrepresented populations in the US, experience a higher dementia burden than non‐Hispanic White individuals, which is not explained by ethnoracial biological factors. Disparities in structural and social determinants of health may contribute to the preponderance of medical conditions known to increase dementia risk, including potentially modifiable factors in Latino and Black communities. To assess the scope of this problem, we measured the frequency of common modifiable dementia risk factors in community‐dwelling, cognitively normal, Latino and Black adults.MethodCognitively normal community‐dwelling Latino and Black adults, ≥45‐years‐old, were enrolled within our longitudinal study of memory and aging at Mayo Clinic in Florida (Jacksonville, FL) and completed a baseline assessment between 3/2022 and 10/2023. Demographics, and self‐reported race/ethnicity and history of dementia risk factors were recorded. Dementia risk factors were objectively sampled through clinical interview (depression: Geriatric Depression Scale ≥5), examination (hypertension: BP >130/80 mmHg; obesity: BMI≥30), and serum analyses (hyperlipidemia: total cholesterol<200mg/dL, HDL>50mg/dL, LDL<100mg/dL, Triglycerides<150mg/dL; diabetes: HbA1C >5.6%, vitamin B12 deficiency: <350 ng/dL).Result86 participants (43 Latino, 43 Black), 65.8 (8.8) years‐old, female (62.8%), with 16 (2.4) years of education were assessed. Dementia risk factors were frequent in Latino and Black participants, including hypertension (63%, 90%; p = 0.005), hyperlipidemia (93%, 89%; p = 0.702), obesity (33%, 44%; p = 0.370), diabetes (60%, 47%; p = 0.370), vitamin B12 deficiency (21%, 21%; p = 0.989), and depression (5%, 24%; p = 0.781). These risk factors were unrecognized or suboptimally managed in a substantial proportion of Latino and Black participants: hypertension (56%, 73%; p = 0.170), hyperlipidemia (80%, 73%; p = 0.591), diabetes (57%, 47%; p = 0.502), vitamin B12 deficiency (21%, 21%; p = 0.789), and depression (5%, 3%; p>0.99).ConclusionPotentially modifiable dementia risk factors were detected in the majority of community‐dwelling Latino and Black cognitively normal older‐adults and were frequently unrecognized or suboptimally managed. Proactive screening for known dementia risk factors may provide opportunities for targeted interventions to improve brain health and decrease dementia disparities in underrepresented populations.

AbstractBackgroundPopulation dementia prevalence is traditionally estimated using cohort studies, surveys, routinely‐collected administrative data, and registries. Hospital Electronic Health Records (EHRs) are comprised of rich structured and unstructured (text) clinical data that are underutilised for this purpose.We aimed to develop a suite of algorithms using routinely‐collected EHR data to reliably identify cases of dementia, as a key step towards incorporating such data in prevalence estimation. Towards this, we developed a novel predictive framework integrating data‐science and biostatistical methods.MethodTraining data were sourced via the National Centre for Healthy Ageing (NCHA) Data Platform, a linked, curated, EHR‐derived data warehouse. Individuals within the platform catchment aged >60 years with confirmed dementia were identified through hospital specialist dementia clinics. A comparison group of individuals aged >60years with EHR records without dementia was recruited from the community.A panel of clinical experts (Neurology, Geriatric Medicine) informed variable and concept selection and guided data cleaning efforts within both streams. Algorithms were developed via two work‐streams; a traditional biostatistical approach to fit logistic regression models using structured data elements, and a data science stream used Natural Language Processing (NLP) to fit models to the unstructured (text) parts of the EHR, for the same individuals.ResultOf 568 individuals (362 with dementia), 434 had clinical notes available. In the data science stream using unstructured data, among a range of NLP derived models, the Random Forest classifier performed best in assigning dementia status, with Area Under the Curve (AUC) 0.95, specificity 90.2% and sensitivity 88.4%. In the biostatistics stream, 15 structured variables were included in the final model, covering demographics, health service attendance, medications, and ICD‐10 Codes, with AUC 0.94, specificity 85.9% and sensitivity 85.6%.ConclusionArtificial intelligence techniques applied to unstructured electronic health data and guided by human clinical expertise may be powerful tools in capturing the presence of dementia, at least comparable to traditional techniques using structured data, and conferring practical and scientific advantages for dementia prevalence estimation. Future validation is required in less crisply delineated real‐world settings.

AbstractBackgroundAutosomal dominant Alzheimer disease (ADAD) is characterized by genetic mutations affecting the beta‐amyloid (Aß) pathway. However, vascular and immune factors play important roles which are not completely understood. Understanding the function of the neurovascular unit (NVU) comprised of neurons, glial cells, and vasculature, at different disease stages appears ideal to developing and evaluating therapeutics. Omics approaches can inform NVU changes and their disease associations.MethodsCSF proteomic data using the Somalogic® platform was generated from 485 participants in the DIAN study, who also had PiB‐PET and MRI assessing Aß burden, white matter hyperintensity (WMH), and cerebral microhemorrhage (CMH). From previously published AD studies, we identified 33 NVU‐associated proteins with corresponding Somalogic aptamers (Figure 1). We used Principal Component Analysis (PCA) on participants with complete data (n = 262, 166 mutation‐carriers and 96 non‐carriers) to find groups of proteins associated with mutation status and disease stage as measured with estimated year to symptom onset (EYO), PiB‐PET, and clinical status. Linear‐mixed effect models and two‐part zero‐inflated negative binomial mixed models further evaluated the link between significant principal components (PCs) and WMH and CMH, respectively. Models accounted for age, APOE‐e4 status, sex, and education.ResultsThe first ten PCs explained >60% of the variance in NVU‐related protein levels (Figure 2A) with only PC5 (4.8%) associated with mutation*EYO, suggesting relationship with ADAD‐specific disease progression (***p<0.0001, Figure 2B). While asymptomatic PiB‐negative individuals were not significantly different from non‐carriers, asymptomatic PiB‐positive individuals had higher PC5 scores than non‐carriers and symptomatic individuals scored still higher (**p<0.005, ***p<0.0001, Figure 2C). The main proteins composing PC5 were: neurofilament light‐chain, angiopoietin‐2, SMOC1, LRP1, E‐selectin, and sTREM2, suggesting strong association with proinflammatory glial response from neuronal injury (Figure 2D). PC5 was also associated with WMH volumes (*p<0.05, Figure 3A) and with CMH count in participants with CMH (**p<0.005, Figure 3B).ConclusionsThis PCA approach indicates that some groups of NVU‐associated proteins are related with mutation status and disease stage, and that they are differentially associated with features of ADAD such as white matter integrity as measured by WMH volume. Weighted Correlation Network Analysis will be of interest to further understand these associations. Funding: K01AG080123, RF1‐AG044546, UF1AG032438

Abstract BMT CTN (Blood and Marrow Transplant Clinical Trials Network) 1506 (“MORPHO”) was a randomized study of gilteritinib compared with placebo as maintenance therapy after hematopoietic cell transplantation (HCT) for patients with FLT3-ITD–mutated acute myeloid leukemia (AML). A key secondary end point was to determine the impact on survival of before and/or after HCT measurable residual disease (MRD), as determined using a highly sensitive assay for FLT3-ITD mutations. Generally, gilteritinib maintenance therapy was associated with improved relapse-free survival (RFS) for participants with detectable peri-HCT MRD, whereas no benefit was evident for those lacking detectable MRD. We conducted a post hoc analysis of the data and found that the level of MRD detected with this approach correlated remarkably with RFS and relapse risk, and that MRD detectable at any level negatively affected RFS. In the placebo arm, 42.2% of participants with detectable FLT3-ITD MRD relapsed compared with 13.4% of those without detectable MRD. We found that 14.8% of participants had multiple FLT3-ITD clones detected as MRD and had worse survival irrespective of treatment arm. Finally, we examined the kinetics of FLT3-ITD clonal relapse or eradication and found that participants on the placebo arm with detectable MRD relapsed rapidly after HCT, often within a few weeks. MRD-positive participants on the gilteritinib arm relapsed either with FLT3 wild-type clones (assessed by capillary electrophoresis), after cessation of gilteritinib with persistent MRD, or on progression of multiclonal disease. These data demonstrate the potential of FLT3-ITD MRD to guide therapy with gilteritinib for this subtype of AML. This trial was registered at www.clinicaltrials.gov as #NCT02997202.

Abstract High-dose methotrexate (MTX) results in high rates of acute kidney injury (AKI), neutropenia, and hepatotoxicity. Glucarpidase is a recombinant enzyme that cleaves MTX, but clinical data supporting its use are scarce. We examined the association between glucarpidase administration and outcomes in adults with MTX-AKI from 28 cancer centers across the United States using a sequential target trial emulation framework. The primary end point was kidney recovery at hospital discharge, defined as survival to discharge with serum creatinine &lt;1.5-fold baseline and without dialysis dependence. Key secondary end points were time to kidney recovery, neutropenia, and transaminitis on day 7, and time to death. Using multivariable logistic and Cox regression models, we compared outcomes in patients who received glucarpidase within 4 days following MTX initiation with those in patients who did not. Among 708 patients with MTX-AKI, 209 (29.5%) received glucarpidase. Overall, 183 (25.8%) had a primary end point event. Glucarpidase receipt was associated with a 2.70-fold higher adjusted odds of kidney recovery (95% confidence interval [CI], 1.69–4.31) compared with no glucarpidase receipt. Patients treated with glucarpidase also had faster time to kidney recovery (adjusted hazard ratio [aHR], 1.88; 95% CI, 1.18–3.33) and lower risks of grade ≥2 neutropenia (adjusted odds ratio [aOR], 0.50; 95% CI, 0.28–0.91) and grade ≥2 transaminitis (aOR, 0.50; 95% CI, 0.28–0.91) on day 7. There was no difference in time to death (aHR, 0.76; 95% CI, 0.49–1.18). These data suggest glucarpidase may improve both renal and extrarenal outcomes in patients with MTX-AKI.

AbstractBackgroundAlzheimer’s disease (AD) missing heritability remains extensive despite numerous genetic risk loci identified by genome‐wide association or sequencing studies. This has been attributed, at least partially, to mechanisms not currently investigated by traditional single‐marker/gene approaches. Polygenic Risk Scores (PRS) aggregate sparse genetic information across the genome to identify individual genetic risk profiles for disease prediction and patient risk stratification. Recent advancements have pivoted on innovative approaches utilizing OMICS data to construct such risk scores.MethodWe employed a random forest algorithm to identify a list of gene candidates from bulk RNA sequencing data in prefrontal cortex from 565 AD brain samples (non‐Hispanic Whites, n = 399; Hispanics, n = 113; African American, n = 12) across six U.S. brain banks. Subsequently, we calculated their effect size on Braak staging using regression models to construct a polytranscriptomic risk score (PTRS). We employed two distinct models: “Ethnicity‐Agnostic” Model (randomly assigning samples to training and testing samples) and “Ethnicity‐Aware” Model (assigning NHW samples to training and Hispanics to testing sample). Analysis of variance and the receiver operating characteristics area under the curve (ROC AUC) was used to evaluate PTRS’s classification performances. We validated findings using the Religious Orders Study/Memory and Aging Project study (ROS/MAP, n = 1,095).ResultWe found a significant difference in PTRS between samples with low vs. high Braak stages (≤4 vs. ≥5, p = 1*E‐04; Figure 1 upper panel). AUC was found to be 79‐81%, consistently in both Ethnicity‐Agnostic and Ethnicity‐Aware models (Figure 1 lower panel). Finally, the PTRS in ROS/MAP yielded a similar classification performance (p = 2*E‐04, AUC = 77%).Conclusioncontrary to prior studies, we developed a PTRS with optimal transferability across ethnicities. This underscores the importance of developing novel tools to stratify and harmonize large brain repositories for AD.

AbstractBackgroundGenome‐wide association studies (GWAS) in Alzheimer’s disease (AD) leveraging endophenotypes beyond case/control diagnosis, such as brain amyloid β pathology, have shown promise in identifying novel variants and understanding their potential functional impact. In this study, we leverage two brain amyloid β pathology measurement modalities, PET imaging and neuropathology, to address sample size limitations and to discover novel genetic drivers of disease.MethodWe conducted a meta‐analysis on an amyloid PET imaging GWAS (N = 7,036, 35% amyloid positive, 53.67% female, age = 71) and an autopsy GWAS of brain amyloidosis (N = 6,519, 63.08% amyloid positive, 51.34% female, age at death = 83), both adjusted for covariates including age, sex and principal components of genetic ancestry. All participants in both GWAS were unrelated individuals of European descent. We defined amyloid positivity as moderate or frequent neuritic plaques using the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) staging scores within each autopsy cohort. A Gaussian mixture model (GMM) was applied to each amyloid PET imaging cohort to identify the cohort and tracer‐specific cut‐offs that differentiate amyloid positive and negative populations.ResultThe genome‐wide significant results from the meta‐analysis identified three known AD loci (APOE, CR1, and BIN1) and a novel chromosome 17 locus (rs35635959, intergenic, MAF = 0.27, OR = 1.18, p = 1.47 × 10‐8). The MAGMA gene‐level analysis excluding the APOE region suggests significant associations between rs35635959 and COASY, PLEKHH3, and TUBG2 on chromosome 17, implying the potential roles of these genes on amyloidosis. Functional annotations of rs35635959 leveraging brain eQTL databases indicate its association with differential gene expression of COASY and TUBG2 in AD brains. ROSMAP bulk and single‐nucleus RNAseq analyses link TUBG2 downregulation to the higher amyloid burden and AD diagnosis while suggesting such observations are enriched in excitatory and inhibitory neurons, reaching FDR significance.ConclusionThis study is the most extensive European GWAS of brain amyloidosis, and our findings replicate known AD loci and identify a possible novel locus (index SNP rs35635959) on chromosome 17. Functional annotations of the novel variant indicate TUBG2, implicating in microtubule organization, warrants further assessment. Ongoing efforts aim to validate these novel effects using independent datasets.