Citations

AbstractBackgroundA hallmark of Alzheimer’s disease is amyloid‐β (Aβ) deposition in the brain parenchyma as senile plaques which Aß frequently accompanies in the cerebral vasculature as cerebral amyloid angiopathy (CAA). Previous studies demonstrated that the cerebrovascular system is essential for Aβ clearance and interactions exist between cerebrovascular disease and AD. Neuroimaging data, including measures on small vessel disease, amyloid deposits, and microhemorrhages (MCH), can reflect both cerebrovascular disease and AD pathology, thereby serving as intermediate phenotypes of both conditions. We aim to identify genes and co‐expression networks in blood associated with these neuroimaging endophenotypes and the biological pathways enriched in these perturbed transcriptional networks.MethodWe conducted differential gene expression and Weighted Gene Co‐Expression Network analyses (WGCNA) on blood RNA sequencing data of 407 participants from the longitudinally followed Mayo Clinic Study of Aging cohort. The neuroimaging phenotypes include MCH, infarction, and amyloid deposits measured by Pittsburgh compound B positron emission tomography (PiB PET).ResultWGCNA analysis showed a nominally significant association (p<0.05) between several module eigengenes (MEs) and MCH and PiB PET. One module, M42, remained significantly associated with PiB PET after Bonferroni correction for all 43 modules tested. Pathway enrichment analysis of M42 identified two significant pathways (FDR‐adjusted p<0.05) including phosphodiesterase I activity and IgE binding. These pathways contain genes such as MS4A2 encoding the high‐affinity IgE receptor involved in the immune response. Similarly, ENPP2 in the phosphodiesterase I activity pathway represents an additional candidate gene previously implicated in Alzheimer’s disease.ConclusionWe generated co‐expression networks and identified one network module with a statistically significant association between brain amyloid deposits and blood transcriptome data. Further investigations of this network and its enriched pathways are necessary to understand their roles in amyloidosis, CAA, and neurodegeneration. Future studies will include seeking replication of these results in other datasets. Such studies can help elucidate the biological mechanisms of pathogenesis of cerebrovascular damage and amyloid deposits. In addition, in a clinical setting, blood levels of transcripts discovered in this study may serve as predictive or diagnostic biomarkers with mechanistic implications.

AbstractBackgroundGiven the overlap of symptoms between Alzheimer’s disease (AD) and other dementias, it is essential to develop widely accessible biomarkers that will ensure an accurate diagnosis of AD to enable its proper treatment. African Americans (AA) are twice more likely to develop AD than non‐Hispanic whites (NHW) and yet they remain underrepresented in AD research. The few studies conducted in AA suggest that there are different factors that influence AD in this population; therefore, it is possible that different biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study we are testing the hypothesis that genetic variants that show association with AD‐risk in AA and with plasma levels of transcript and proteins may serve as AD biomarkers which are more accessible and less costly than cerebrospinal fluid or neuroimaging biomarkers.MethodsIn 189 AD cases and 183 cognitively unimpaired (CU) AA participants of the Florida Consortium of African American Alzheimer’s Disease Studies (FCA3DS), we performed targeted DNA sequencing of 10 AD‐associated loci. Genetic variants were tested for association with plasma transcripts and plasma total tau protein levels previously measured in this cohort using a nanoString® custom panel (Reddy J, et al. 2022) and Simoa assays (Deniz K, et al. 2021), respectively. In receiver operating characteristic (ROC) analyses, the most significant expression/protein quantitative trait loci (eQTL/pQTL) were added sequentially to a base model that included only age and sex to identify eQTL/pQTL that improved the accuracy to correctly classify AD cases vs. CU.ResultsOf the 5112 variants identified in the targeted sequencing, 71 were nominally associated (p<0.05) with plasma transcript/protein levels and with AD‐risk. ROC analysis of age, sex, eQTL/pQTL in APOE, ABCA7, AKAP9, EPHA1, SORL1, and TLR4, and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE‐ɛ4 dosage achieved 77.6% area under the curve (AUC) to discriminate AD vs. CU, a 19.9% improvement over a model that only included age and sex.ConclusionsPlasma transcript levels and eQTL/pQTL are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD.

AbstractBackgroundPredictive models of tau‐PET accumulation have largely relied on the functional connectome to estimate its spatial patterns in Alzheimer’s disease (AD). Patterns of global functional organization represent a promising avenue as they encapsulate many biological properties relevant to neurodevelopment, cognition and degeneration. We compared approaches based on local connectivity (from task‐free fMRI) and global organization (from FDG‐PET) to predict regional tau‐PET across AD phenotypes.MethodWe included 430 cognitively unimpaired (CU) individuals (214 A+T‐, 216 A+T+) and 62 amnestic mild cognitive impairment (aMCI), 64 amnestic AD, 21 dysexecutive AD (dAD), 41 logopenic progressive aphasia (LPA) and 49 posterior cortical atrophy (PCA) patients (all A+T+) from the Alzheimer’s Disease Research Center, Mayo Clinic Study of Aging, and Neurodegenerative Research Groups (referred to as “Mayo cohort”). The connectivity approach consisted of assessing the relationship between a region’s tau level and its functional connectivity to the region of highest tau (epicenter). The global organization approach consisted of 1) performing a principal component analysis on 3000 FDG‐PET images that did not overlap with the Mayo cohort, 2) projecting FDG‐PET images of the Mayo cohort onto the low‐dimensional space generated in Step 1 and extracting corresponding weighted values across the first 100 components, 3) using these weighted values as predictors of regional tau‐PET in a linear model and determining optimal parameters based on predicted R 2 values, and 4) using the parameters from the model built in Step 3 to predict tau‐PET in the ADNI cohort (n = 86) (Fig.2).ResultThe connectivity‐based approach yielded adjusted R 2 values ranging from 0.19‐0.45 across diagnostic groups (Fig.1). The global organization approach yielded averaged adjusted R 2 and predicted R 2 values of 0.71 and 0.63, respectively, in the Mayo cohort. Out‐of‐sample median R 2 in the ADNI cohort was 0.41 (range 0.10‐0.60) (Fig.3).ConclusionAn unbiased approach based on the global functional organization of the brain and using an imaging modality widely used in clinical settings outperformed a connectome‐based one to predict regional tau‐PET across the AD phenotypic spectrum. Patterns of tau accumulation may better relate to the large‐scale physiology of the brain underlying specific mental functions rather than local connectivity factors.

AbstractBackgroundGlial activation plays a critical role in Alzheimer’s disease (AD) pathogenesis and is associated with amyloid‐β plaques and neurofibrillary tangles composed of phosphorylated tau (phospho‐tau). With approximately 40%‐60% of AD cases having limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), TDP‐43 pathology has become more the rule than the exception in AD brains. However, the effect of LATE‐NC in AD‐related glial activation is unknown.MethodWe analyzed the effect of TDP‐43 pathology on glial activation in three AD subtypes: hippocampal sparing (HpSp) AD, typical AD, and limbic predominant AD. Twenty cases of each subtype (n = 60 total) were selected from the FLorida Autopsied Multi‐Ethnic (FLAME) cohort. Cases were immunohistochemically evaluated on serial sections of the hippocampus in the CA1 and subiculum subsectors, and superior temporal, inferior parietal, and mid‐frontal cortices with antibodies to CD68 (phagocytosis), GFAP (astrogliosis), GT‐38 (conformation‐specific AD‐type tau), 6F/3D (amyloid‐β), and phospho‐Serine 409/410 of TDP‐43 (pTDP‐43). Digital pathology was employed to quantify immunohistochemical staining. Multivariable regression modeling was utilized to understand the relationship between glial activation and AD pathologies.ResultThe level of glial activation, defined as % of immunoreactive surface area for CD68 and GFAP, was lowest in HpSp AD (0.54%, 13%), whereas typical AD (1.3%, 33%) and limbic predominant AD (1.3%, 30%) had similar levels suggesting a ceiling effect, or plateau, of gliosis levels (both p<0.001). HpSp AD was more often male (p<0.001) and younger at disease onset (p<0.001) compared to both typical AD and limbic predominant AD. Multivariable regression modeling of CD68 (subiculum R2 = 0.60) identified advanced tau to be a significant predictor of CD68 in all brain regions. LATE‐NC stage predicted increased CD68 levels in limbic brain regions. Multivariable regression modeling of GFAP (CA1 R2 = 0.60) showed that Aβ was the strongest predictor of astrogliosis in CA1 and subiculum (p<0.001). Advanced tau in CA1 and parietal cortex, LATE‐NC in subiculum and temporal cortex, and APOE4 genotype in CA1 predicted a significant increase in GFAP.ConclusionThese findings highlight the significant role TDP‐43 pathology plays in affecting the microenvironment and interplay between neuroinflammation and neurodegeneration and have important implications for therapeutic strategies in AD with co‐morbid LATE‐NC.

AbstractBackgroundStructural variants range from simple loss or gain of genetic material to complex events that restructure entire chromosomes. This heterogeneity coupled with variant size greater than sequencing read‐length makes structural variant mapping from short‐read sequencing data difficult and error‐prone. Consequently, the role of structural variants is poorly explored in many phenotypes, including dementia.MethodWe used the GATK‐SV pipeline that combines four external structural variant mapping algorithms with machine‐learning to build high‐quality consensus structural variant calls. We applied GATK‐SV to short‐read whole‐genome sequencing data of 2,601 frontotemporal dementia‐amyotrophic lateral sclerosis spectrum (FTD/ALS) patients, 2,612 Lewy body dementia (LBD) patients, and 4,132 neurologically unaffected participants.ResultAfter stringent quality‐control, we performed genome‐wide association studies on 2,307 ALS/FTD patients versus 3,677 controls with 4,699 common structural variants and 2,355 LBD patients versus 3,700 controls with 4,889 common structural variants. In the FTD/ALS cohort, we identified well‐known risk variants at the C9orf72 (p‐value = 4.99×10‐18, OR = 14.47, 95% CI = 7.90–26.49) and MAPT loci (p‐value = 3.48×10‐6, OR = 0.77, 95% CI = 0.68–0.86) corroborating the ability of our pipeline to identify disease‐associated structural variants. Moreover, we discovered, replicated, and validated TPCN1 as a novel risk locus for LBD (p‐value = 9.18×10‐6, OR = 1.43, 95% CI = 1.22–1.67). Further, we identified rare exonic variants with known pathogenic or likely pathogenic effects, such as an SNCA gene duplication in LBD and a deletion of exons 1 and 2 in CHCHD10 in FTD/ALS. We additionally observed structural variants in regulatory regions, e.g. a deletion of a key PSEN2 enhancer, which resulted in an approximate 0.70 fold‐change in PSEN2 expression in LBD. Finally, we built an interactive web app where structural variants can be visualized and explored (https://ndru-ndrs-lng-nih.shinyapps.io/non_ad_dementias_sv_app/).ConclusionCommon and rare structural variants play a role in LBD and FTD/ALS. Our structural variant resource is publicly available and can be used to further explore the role of structural variants in LBD and FTD/ALS.

AbstractBackgroundPredictive models of tau‐PET accumulation have largely relied on the functional connectome to estimate its spatial patterns in Alzheimer’s disease (AD). Patterns of global functional organization represent a promising avenue as they encapsulate many biological properties relevant to neurodevelopment, cognition and degeneration. We compared approaches based on local connectivity (from task‐free fMRI) and global organization (from FDG‐PET) to predict regional tau‐PET across AD phenotypes.MethodWe included 430 cognitively unimpaired (CU) individuals (214 A+T‐, 216 A+T+) and 62 amnestic mild cognitive impairment (aMCI), 64 amnestic AD, 21 dysexecutive AD (dAD), 41 logopenic progressive aphasia (LPA) and 49 posterior cortical atrophy (PCA) patients (all A+T+) from the Alzheimer’s Disease Research Center, Mayo Clinic Study of Aging, and Neurodegenerative Research Groups (referred to as “Mayo cohort”). The connectivity approach consisted of assessing the relationship between a region’s tau level and its functional connectivity to the region of highest tau (epicenter). The global organization approach consisted of 1) performing a principal component analysis on 3000 FDG‐PET images that did not overlap with the Mayo cohort, 2) projecting FDG‐PET images of the Mayo cohort onto the low‐dimensional space generated in Step 1 and extracting corresponding weighted values across the first 100 components, 3) using these weighted values as predictors of regional tau‐PET in a linear model and determining optimal parameters based on predicted R2 values, and 4) using the parameters from the model built in Step 3 to predict tau‐PET in the ADNI cohort (n = 86) (Fig.2).ResultThe connectivity‐based approach yielded adjusted R2 values ranging from 0.19‐0.45 across diagnostic groups (Fig.1). The global organization approach yielded averaged adjusted R2 and predicted R2 values of 0.71 and 0.63, respectively, in the Mayo cohort. Out‐of‐sample median R2 in the ADNI cohort was 0.41 (range 0.10‐0.60) (Fig.3).ConclusionAn unbiased approach based on the global functional organization of the brain and using an imaging modality widely used in clinical settings outperformed a connectome‐based one to predict regional tau‐PET across the AD phenotypic spectrum. Patterns of tau accumulation may better relate to the large‐scale physiology of the brain underlying specific mental functions rather than local connectivity factors.

Abstract Purpose: The neutralizing peptibody trebananib prevents angiopoietin-1 and angiopoietin-2 from binding with Tie2 receptors, inhibiting angiogenesis and proliferation. Trebananib was combined with paclitaxel±trastuzumab in the I-SPY2 breast cancer trial. Patients and Methods: I-SPY2, a phase II neoadjuvant trial, adaptively randomizes patients with high-risk, early-stage breast cancer to one of several experimental therapies or control based on receptor subtypes as defined by hormone receptor (HR) and HER2 status and MammaPrint risk (MP1, MP2). The primary endpoint is pathologic complete response (pCR). A therapy “graduates” if/when it achieves 85% Bayesian probability of success in a phase III trial within a given subtype. Patients received weekly paclitaxel (plus trastuzumab if HER2-positive) without (control) or with weekly intravenous trebananib, followed by doxorubicin/cyclophosphamide and surgery. Pathway-specific biomarkers were assessed for response prediction. Results: There were 134 participants randomized to trebananib and 133 to control. Although trebananib did not graduate in any signature [phase III probabilities: Hazard ratio (HR)-negative (78%), HR-negative/HER2-positive (74%), HR-negative/HER2-negative (77%), and MP2 (79%)], it demonstrated high probability of superior pCR rates over control (92%–99%) among these subtypes. Trebananib improved 3-year event-free survival (HR 0.67), with no significant increase in adverse events. Activation levels of the Tie2 receptor and downstream signaling partners predicted trebananib response in HER2-positive disease; high expression of a CD8 T-cell gene signature predicted response in HR-negative/HER2-negative disease. Conclusions: The angiopoietin (Ang)/Tie2 axis inhibitor trebananib combined with standard neoadjuvant therapy increased estimated pCR rates across HR-negative and MP2 subtypes, with probabilities of superiority &gt;90%. Further study of Ang/Tie2 receptor axis inhibitors in validated, biomarker-predicted sensitive subtypes is warranted.