Ertekin‐Taner, Nilüfer

Abstract Studies assessing genetic associations with neuropathological features in Lewy body disease (LBD) have been limited to candidate gene investigations, and therefore, information is lacking regarding the genetic architecture of the neuropathology of LBD. In the current study, we examined a large series of neuropathologically confirmed LBD cases (n = 980 in the discovery series, n = 503 in the replication series) and performed genome-wide association studies of 11 different neuropathological outcome measures. The 11 neuropathological outcomes included Braak neurofibrillary tangle (NFT) stage, Thal amyloid phase, LBD subtype, Lewy body (LB) counts in five different brain regions, dorsolateral and ventromedial putaminal tyrosine hydroxylase immunoreactivity and neuronal loss in the ventrolateral part of the substantia nigra. Associations between variants and outcomes were assessed using regression models appropriate for the nature of the given neuropathological outcome and that were adjusted for age at death, sex and top principal components of genetic data. In the discovery series, APOE rs429358 (i.e. APOE ε4) was associated with a greater severity of each of Braak NFT stage [odds ratio (OR) = 3.07, P = 2.34 × 10−32], Thal amyloid phase (OR = 3.57, P = 3.28 × 10−29) and LBD subtype (OR = 1.78, P = 9.85 × 10−9), with similar findings observed in the independent replication series (Braak NFT stage, OR = 2.30, P = 2.70 × 10−11; Thal amyloid phase, OR = 3.17, P = 6.39 × 10−18; LBD subtype, OR = 2.68, P = 3.85 × 10−10). In the subgroup of cases with lower levels of Alzheimer's disease pathology (Braak NFT stage ≤ III and Thal amyloid phase ≤2), there was a strong association between APOE rs429358 and LBD subtype even when adjusting for Braak stage and Thal phase in the discovery series (n = 218, OR = 2.47, P = 0.007) and the replication series (n = 141, OR = 3.60, P = 0.006). Although additional genome-wide significant associations were identified in the discovery series between LINC01581/MCTP2 rs547411734 and lower middle frontal LB counts, between TLE3 rs3743309 and lower cingulate LB counts, and between GRIN2A/ATF7IP2 rs1097915 and lower parahippocampal LB counts, these findings were not observed in the replication series. Our results indicate that the APOE ε4 allele is the most prominent genetic determinant of severity of neuropathology in LBD. These findings represent a key step forward in our understanding of genetic drivers of neuropathological features in LBD. Future studies utilizing meta-analytical approaches will be important to more precisely assess other associations that were not quite genome-wide significant in the discovery series.

Abstract Blood-brain barrier (BBB) dysfunction is a key feature of Alzheimer’s disease (AD), particularly in individuals carrying the APOE-ε4 allele. This dysfunction worsens neuroinflammation and hinders the removal of toxic proteins, such as amyloid-beta (Aβ42), from the brain. In post-mortem brain tissues and in animal models, we previously reported that fibronectin accumulates at the BBB predominantly in APOE-ε4 carriers. Furthermore, we found a loss-of-function variant in the fibronectin 1 ( FN1 ) gene significantly reduces aggregated fibronectin levels and decreases AD risk among APOE-ε4 carriers. Yet, the molecular mechanisms downstream of fibronectin at the BBB remain unclear. The extracellular matrix (ECM) plays a crucial role in maintaining BBB homeostasis and orchestrating the interactions between BBB cell types, including endothelia and astrocytes. Understanding the mechanisms affecting the ECM and BBB cell types will be critical for developing effective therapies against AD, especially among APOE-ε4 carriers. Here, we demonstrate that APOE-ε4 , Aβ42, and inflammation drive the induction of FN1 expression in several models including zebrafish, mice, iPSC-derived human 3D astrocyte and 3D cerebrovascular cell cultures, and in human brains. Fibronectin accumulation disrupts astroglial-endothelial interactions and the signalling cascade between vascular endothelial growth factor (VEGF), heparin-binding epidermal growth factor (HBEGF) and Insulin-like growth factor 1 (IGF1). This accumulation of fibronectin in APOE-ε4- associated AD potentiates BBB dysfunction, which strongly implicates reducing fibronectin deposition as a potential therapeutic target for AD. Graphical abstract Accessibility text This image illustrates the effects of different APOE isoforms (ApoE-ε3 and ApoE-ε4) on blood-brain barrier (BBB) integrity, focusing on the molecular interactions between astrocytes and endothelial cells. This figure emphasizes the detrimental effects of ApoE-ε4 on BBB integrity via fibronectin accumulation and altered signaling pathways. The top section provides a schematic overview of the blood-brain barrier, highlighting astrocytes, endothelial cells, and their interface. The left panel represents the ApoE-ε3 condition: Normal fibronectin (FN1) levels support healthy interactions between astrocytes and endothelial cells. Growth factors, including VEGFA, HBEGF, and IGF1, maintain BBB integrity through their respective receptors (VEGFR and EGFR). Green arrows indicate activation of these signaling pathways. The right panel depicts the ApoE-ε4 condition: Elevated fibronectin (FN1) disrupts astrocyte-endothelium interactions. FN1 binds integrins and activates focal adhesion kinase (FAK), inhibiting VEGFA, which is required for endothelial HBEGF that in turn activates IGF1 signaling. Red symbols indicate inhibition of HBEGF, VEGFA, and IGF1 pathways, leading to BBB dysfunction. Highlights APOE-ε4 drives fibronectin deposition in Alzheimer’s, disrupting astrocyte-endothelia interactions. APOE-ε4 and fibronectin co-localize, forming aggregates at blood-brain barrier (BBB). Fibronectin alters the signaling between VEGF, IGF1, and HBEGF impairing BBB function. Reducing fibronectin restores BBB integrity and offsets APOE-ε4 pathology.

AbstractBackgroundAlzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non‐Hispanic White (NHW) population. To address this, Accelerating Medicines Partnership in AD (AMP‐AD) aimed to promote inclusivity in multi‐omics AD research, to unravel unique molecular signatures and pathways. The study aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial groups.MethodDorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (980 unique individuals), 322 were from African American donors, 214 from Latino Americans, 551 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG samples, 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag‐based mass spectrometry (TMT‐MS). Following quality control (QC), proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. Differential protein expression was conducted within and across races after adjusting for batch using regression‐analysis.ResultIn total, 9,180 proteins from the DLPFC, and 9,734 proteins from STG brain tissues were quantified by TMT‐MS. Further analysis identified approximately 3,000 differentially abundant proteins in AD brains compared to controls within race. The AD‐associated differentially abundant proteins were strongly correlated between DLPFC and STG regions and with CERAD and Braak. Protein levels of MAPT and APP demonstrated equivalent disease‐related elevations in both African American and NHW individuals with AD. Notably, after adjusting for AD, significant differences in protein levels were identified across race.ConclusionThe proteomics approach employed by AMP‐AD sheds light on the brain proteome in AD across diverse racial groups, emphasizing the importance of inclusive research in establishing robust and generalizable discoveries. The identified proteins here could underscore racial disparities beyond disease association, contributing to a more nuanced understanding of AD pathophysiology.

AbstractBackgroundTwo main risk factors of Alzheimer’s disease (AD) are aging and APOE‐ε4. However, some individuals remain cognitively normal despite having these risk factors. They are considered “cognitively resilient”. This study aimed to identify molecular factors that confer cognitive resilience in APOE‐ε4 carriers ≥ 80 years of age and may serve as biomarkers.MethodWe applied weighted gene co‐expression network analysis (WGCNA) to generate consensus co‐expression networks from blood of participants in two antemortem cohorts, the Mayo Clinic Study of Aging (MCSA, n=105), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n=91), using RNA‐sequencing and microarray data, respectively. We associated these networks with resilience (resilient vs non‐resilient), cognitive endophenotypes and hippocampal volume. Preservation between consensus networks from blood and those derived from postmortem brain tissues of AD and control donors from AMP‐AD (n=1174) was evaluated. We validated the human findings in four AD mouse models. Finally, machine learning models were utilized to discriminate cases (AD+mild cognitive impairment (MCI)) from controls in MCSA, ADNI and ANMerge antemortem cohorts.ResultFour consensus networks were significantly correlated with a memory phenotype (logical memory delayed recall=LMDR) and hippocampal volume in both MCSA and ADNI. Among these, blood expression module M3 was most preserved with the brain transcriptome. M3 was enriched with NDUF hub genes that are involved in the mitochondrial respiratory chain. Expression levels of M3 and many blood NDUFs had significant associations with better LMDR and hippocampal volume. In brain, NDUFs were upregulated in controls compared to AD, and their expression levels were associated with better global cognition and decreased AD neuropathology. Many NDUFs were significantly downregulated in the hippocampus or cortex of AD mice compared to wild‐types. Lastly, models that included blood NDUFs improved diagnostic accuracy of AD+MCI compared to models that only included demographic and risk variables (age, sex, APOE‐ε4) in MCSA, ADNI and ANMerge. In MCSA and ADNI, adding NDUFs’ expression to models that included established blood biomarkers (Aβ42/40, ptau181, NFL) further improved diagnostic accuracy.ConclusionOur results suggest that mitochondrial NDUFs are centrally‐linked peripheral molecular signatures that may be resilience factors against AD and serve as both therapeutic targets and novel diagnostic biomarkers.

AbstractBackgroundOur Alzheimer Disease Metabolomics Consortium (ADMC), part of the Accelerating Medicines Partnership for AD (AMP‐AD) and in partnership with AD Neuroimaging Initiative (ADNI), applied state‐of‐the‐art metabolomics and lipidomics technologies combined with genomic and imaging data to map metabolic failures across the trajectory of the disease. Our studies confirmed that peripheral metabolic changes influenced by the exposome inform about cognitive changes, brain imaging changes, and ATN markers for disease confirming that peripheral and central changes are connected, in part through the metabolome.MethodsTo map the biochemical changes in AD, we used various targeted and untargeted metabolic platforms to profile ∼800 postmortem brain tissue, and ∼ 5000 blood samples.ResultsRecently, we built a comprehensive reference map of extensive AD‐related metabolic changes in brain, spanning multiple AD‐related traits, including neuropathological b‐amyloid and tau tangle burden, as well as late‐life cognitive performance. Using this resource, we extracted novel metabolic including bioenergetic pathways, cholesterol metabolism, neuroinflammation, broad impairment of osmoregulation, an imbalance between excitatory/inhibitory neurotransmitter ratios and identification of tau load as a potential driver of metabolic dysfunction in the AD brain, with minimal contributions from b‐amyloid load. As AD and progressive supranuclear palsy (PSP) share the pathological feature of tauopathy and metabolic alterations, we compared their metabolomic profiles to identify shared biological pathways that could be targeted for therapeutic interventions. Our findings indicate that both diseases display oxidative stress, mitochondrial dysfunction, and tau‐induced polyamine stress response.ConclusionOverall, through our studies, (1) We identified biochemical processes altered in AD, with findings supported across both metabolomic and proteomic data, indicating multimodal deregulation. (2) Our research pinpointed widespread AD‐related biochemical changes across various brain regions with differing levels of neuropathology. While there are many overlapping changes across the brain regions, each region also has its distinct metabolic alterations. (3) We identified biochemical processes disrupted by AD, with parallel findings in other neurodegenerative diseases, hinting at broader implications in neurodegenerative research. Currently, we are working on mapping widespread connections of the brain metabolome with various determinants of AD namely genome, gut microbiome, exposome, and linking with peripheral metabolic alterations in AD.

AbstractBackgroundPlasma biomarker development is of increasing interest due to improved accessibility compared to established diagnostic modalities for Alzheimer’s disease (AD). However, current plasma biomarker candidates have not been tested comprehensively in diverse populations, and these markers represent only a fraction of pathways perturbed in AD. Therefore, there is a need to identify novel plasma biomarkers that account for both disease heterogeneity and patient diversity. This study seeks to address these knowledge gaps through untargeted plasma biomarker discovery in African Americans (AA), an underrepresented group in AD research despite having a higher risk of developing AD compared to non‐Hispanic Whites.MethodsUntargeted proteomics were performed using the SomaScan 7k assay on plasma samples from AA study participants clinically diagnosed as AD (n=142) or cognitively unimpaired (CU, n=144). Linear regression models adjusted for age, sex, and batch were implemented to identify differentially expressed proteins (DEPs). APOE was additionally adjusted for in a sensitivity analysis. DEPs with the lowest q‐values were selected as predictors in a receiver operating characteristic (ROC) analysis to assess their accuracy to discriminate AD versus CU individuals.ResultsA total of 153 DEPs were identified (q<0.05) when adjusting for age, sex, and batch, and 100 DEPs were identified when additionally adjusting for APOE. Of the 66 proteins overlapping between these models, SERPINA3, C7, IGFBP‐2, DKK3, SMOC1, and ACES had the lowest q‐values and were included in a ROC model adjusted for age, sex, and APOE. That model classified AD versus CU with an area under the curve (AUC) of 0.87 (95%CI: 0.83‐0.91), a 10.4% improvement over the base model including age, sex, and APOE (AUC=0.78; 95%CI: 0.72‐0.83). Despite the unbiased selection of proteins included in the ROC model, all selected proteins have been associated with AD and implicated in related functional pathways such as neuroinflammation, synaptic function, and insulin signaling.ConclusionThis preliminary plasma biomarker panel demonstrates the potential diagnostic capabilities of biomarker discovery through untargeted proteomics. Future directions include validation of findings in external datasets, concomitant assessment of p‐tau217, and evaluation of machine learning models to define the optimal diagnostic and predictive set of plasma protein biomarkers for AD in AA.

AbstractBackgroundAlzheimer’s disease (AD) patients have decline in cognitive domains including memory, language, visuospatial, and/or executive function and brain pathology including amyloid‐β and tau deposition, neurodegeneration, and frequent vascular co‐pathologies detectable by neuroimaging and/or cerebrospinal fluid biomarkers. However, molecular disease mechanisms are complex and heterogeneous. It is necessary to develop cost‐effective blood‐based biomarkers reflecting brain molecular perturbations in AD. We identified blood‐based gene and co‐expression network level changes associated with AD/mild cognitive impairment (MCI) diagnosis and AD‐related phenotypes.MethodWe performed differential gene expression and weighted gene co‐expression network analysis, followed by meta‐analysis, using blood transcriptome data of 391 participants from the Mayo Clinic Study of Aging and 654 participants from the Alzheimer's Disease Neuroimaging Initiative. The neuroimaging phenotypes include microhemorrhages, infarcts, amyloid burden, hippocampal volume, and white matter hyperintensities. The cognitive phenotypes include standardized cognitive subtest scores and composite scores for memory, language, visuospatial, and executive function.ResultFive out of 18 modules(M) are significantly associated with diagnosis or cognition (FDR‐adjusted p<0.05). M1 and M15 both positively associates with memory, M1 positively associated with language and M15 with visuospatial function. M1 and M15 are enriched in differentially expressed genes (DEGs) associated with language and executive function, respectively. M2 negatively associates with logical memory delayed recall scores(LMDR), memory, executive, and language functions and is enriched in DEGs for these phenotypes. M8 negatively associates with memory, language and executive functions and is enriched in DEGs for memory and language. M12 positively associates with LMDR. M1 and M15 are down‐regulated while M2 and M8 are up‐regulated in AD/MCI patients. Cell‐type enrichment analysis showed M2 is enriched in monocytes and neutrophils; M8 in monocytes; M15 in B cells (FDR <0.05). Gene ontology terms enriched in these modules indicated broad consistency with their cell types.ConclusionWe identified five modules significantly associated with AD/MCI or cognitive phenotypes using blood transcriptome data. These findings nominate blood transcriptome changes and their enriched biological processes as potential pathomechanisms in cognitive decline and AD/MCI development. We aim to investigate these blood transcripts as potential biomarkers for AD or AD‐related phenotypes and therapeutic targets through additional replication and experimental validation studies.

AbstractBackgroundAfrican Americans (AA) and Latin Americans (LA) are at a higher risk of developing AD compared to non‐Hispanic whites (NHW) but are traditionally underrepresented in AD research. The disproportionate risk is likely multifactorial including differences in co‐morbidities and structural and social determinants of health (SSDoH). AD risk is thought to result from multiple genetic and environmental factors, and their interactions (GxE). However, the molecular mechanisms underlying these interactions are largely unknown. The best‐established genetic risk factor for AD is APOE‐ε4, while APOE‐ε2 is protective. Environmental factors, such as living in neighborhoods with greater socioeconomic disadvantage, have been associated with greater AD neuropathology and worse cognitive function. Studying the potential modifying role of neighborhood disadvantage regarding associations of APOE‐ε4 and APOE‐ε2 with AD risk using a socioeconomic metric like the Area Deprivation Index (ADI) in a multiethnic post‐mortem cohort could offer valuable insights for precision medicine.MethodWe analyzed a post‐mortem cohort of 421 multi‐ethnic donors (NHW: N = 234, AD = 70, non‐AD = 164; LA: N = 145, AD = 102, non‐AD = 43; AA: N = 42, AD = 24, non‐AD = 18), from Mayo Clinic Florida, Banner Sun Health Research Institute, and the University of Florida Brain Banks as part of the AMP AD Diversity initiative. This study used the same neuropathological criteria to categorize AD vs. non‐AD as in the MayoRNAseq study (syn5550404). ADI from the Neighborhood Atlas® was obtained from de‐identified addresses. Associations of APOE‐ε4, APOE‐ε2, and ADI with AD risk were examined using logistic regression models adjusted for age‐at‐death, sex, and ethnic group; interactions of APOE genotype with ADI were also assessed.ResultAPOE‐ε4 and APOE‐ε2 showed a significant association with AD diagnosis (APOE‐ε4combined cohort OR = 3.23, P = 3.14E‐08; APOE‐ε2combined cohort OR = 0.30, P = 0.003). However, contrary to prior findings, our study found no association between ADI and AD diagnosis [OR = 1.023 (per each 10 unit increase in ADI), P = 0.629]. No significant interactions of ADI with APOE‐ε4 or APOE‐ε2 regarding association with AD diagnosis were identified (P = 0.083, P = 0.781).ConclusionThis is the first study evaluating the potential interaction of neighborhood disadvantage with APOE on AD risk in a multi‐ethnic autopsy cohort. However, these findings require further investigation in larger, more well‐powered cohorts for validation.

AbstractBackgroundSystemic inflammation plays a pivotal role in many chronic diseases including Alzheimer’s disease (AD). Assessing the composition of immune pathways in neurodegenerative diseases can contribute to precision medicine. Using publicly available transcriptomic data, we sought to elucidate transcriptional networks pertinent to inflammatory pathways across brain regions and peripheral blood in AD/mild cognitive impairment (MCI) and peripheral blood in Parkinson’s disease (PD).MethodFor the AD/MCI vs. control dataset, we analyzed bulk‐RNAseq collected from 6 brain regions of donors from ROSMAP, Mayo Clinic, and Mount Sinai School of Medicine (MSSM) brain banks available from the AMP‐AD consortium. Ante‐mortem, blood RNAseq expression data was retrieved from the AMP‐AD Emory Vascular cohort and Mayo Clinic Study of Aging (MCSA). We also collected blood‐derived microarray expression data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For the PD vs Control dataset, blood‐derived bulk‐RNAseq from the PDBP and PPMI cohorts were available through the AMP‐PD consortium. Following quality control, normalization, and residual generation to account for biological and technical variables, co‐expression network modules and their enriched pathways were identified using WGCNA within each dataset. Module/trait correlation tests for aging and diagnosis (cases [AD/MCI or PD] vs control) phenotypes were evaluated. Gene Ontology enrichment analyses were executed to identify enriched pathways and brain or blood cell types within the modules. Modules were tested for preservation across cohorts.ResultWe identified conserved immune signatures across brain regions and cohorts. Modules involved in immune response were preserved across all cohorts. Blood consensus modules involved in immune response were preserved in the brain and vice versa. Some immune modules were associated with AD/MCI, PD, and/or aging. Brain immune modules are significantly associated with aging and/or AD. Significant correlations (q<0.05) with PD diagnosis were present. In the MCSA and Emory vascular cohorts, there were no significant (q<0.05) associations between modules and diagnosis, while in ADNI there were nominal (p<0.05) associations.ConclusionPreserved transcriptional immune networks were identified across blood and brain and across two neurodegenerative diseases. Expanding gene co‐expression network analyses to other diseases and integrating additional omics measures and phenotypes can further strengthen these findings to unravel the immune signatures across complex diseases.

AbstractBackgroundA complex, multicellular disease with genetic and immunological elements, Alzheimer’s disease (AD) affects millions worldwide. There has been previous research linking AD to the missense variants ABI3‐rs616338‐T and PLCG2‐rs72824905‐G, and the altered expression of these genes has been shown to disrupt microglial function. In our understanding of AD risk and resilience, limited research has been conducted on how these variants affect microglial subtypes and states in AD.MethodsWe previously identified DOCK8 protein as a target for fluorescent activated nuclei sorting (FANS) to enrich microglia nuclei from frozen human brains. Using this enrichment strategy, we generated microglia enriched snRNAseq data from temporal cortex tissue of 30 donors harboring ABI3 or PLCG2 missense mutations, or neither mutation. We introduced PLCG2 variant in either homozygote, and heterozygote forms into an AD patient derived iPSC through CRISPR/Cas9 approach, differentiated these cells into microglia cells (IMGLs) following established protocols, and generated scRNAseq data after treatment with Amyloidβ. We applied standard alignment and quality control pipelines to the snRNAseq and scRNAseq datasets in parallel. Established markers of microglia states and subtypes were utilized to annotate the clusters; analyzed for their hub gene expression using comparisons between cluster differential profiling to determine signature pathways. Differential gene expression was assessed using pseudo bulk and MAST approaches.ResultsWe obtained single nuclei transcriptome profiles of 54,000 frozen human brain nuclei, of which 35,000 are microglia, through snRNAseq, and single cell profiles of 63,000 iMGLs through scRNAseq, using our standard alignment and quality control procedures. Our differential gene expression analysis identified novel genes and pathways which were identified as part of resilience or AD risk networks in microglia subtypes and states. These alterations were validated using orthogonal experimental methods and further explored for their conservation using in vivo external datasets. Pseudotime inference will be completed to probe microglia marker gene expression dynamics, treatment conditions, along with continuous cell‐state changes.ConclusionOur study uncovers microglia subtype specific resilience and risk factors provided by AD related genetic variants using snRNAseq from frozen human brain and scRNAseq from IPSC derived microglia cells. These findings nominate novel targets and pathways with therapeutic potential.