A multi-omic approach utilizing a single biospecimen is important to avoid intra-sample heterogeneity associated with testing multiple omic single-samples, and for more efficient use of small volumes of precious biopsies (<30 mg). This is especially true for the microanatomy of post-mortem human brain samples. Using post-mortem human brain biospecimens from the NIH NeuroBioBank, a penta-omic sequential extraction method is described, Simultaneous Metabolomic, Proteomic, Lipidomic, DNA, RNA Extraction (SiMPL-DREx). Each sequential omic extract was compared to those obtained by the gold standard single omic method. Preserving RIN is critical for brain and tissue banks, as it is a primary measure of tissue quality. For all five omic extracts, the tissue integrity numbers and omic profiles did not significantly differ from those obtained by the respective omic gold standard method. Unlike past multi-omic studies, this study quantified the relative solvent percentages and upstream losses for both the organic and aqueous phases, confirming an omics loss of under 5%.

Understanding the genetic foundations of dementia is critical to unraveling its complex molecular basis. Given that a clinical diagnosis of Alzheimer's disease (AD) dementia often results from interplay between multiple underlying neuropathologic co-morbidities, previous genome-wide association studies (GWAS) of clinically diagnosed AD are restricted in their ability to translate genetic associations to potential targeted therapeutics. The current study seeks to address these limitations by presenting the largest GWAS to date (n = 12,509) of neuropathologic hallmarks of AD and AD related dementias (ADRDs). We further performed a candidate-variant analysis using loci previously identified in GWAS of clinically diagnosed AD dementia and Parkinson's disease (PD). Finally, we conducted heritability and genetic correlation analyses using linkage disequilibrium (LD) score regression. We found broad genome-wide significant associations with APOE across AD and ADRDs but not cerebrovascular disease and vascular brain injury. We further identified 12 significant loci across 10 neuropathologic phenotypes, including 5 loci previously implicated in GWAS of clinical AD and ADRDs (variants on BIN1, PICALM/ EED, TMEM106B, GRN, and SNCA/ SNCA-AS1) and 7 novel genome-wide associations (variants on EPHA5, PSMG1, LINC00276, VAPA, LINC00290, DOCK4 and SLAIN2/ SLC10A4). Our analysis of AD and PD clinical candidate variants demonstrated several that were associated with AD neuropathologic change and Lewy body disease, as well as substantial overlap with neuropathologic lesions other than the primary neuropathologic hallmarks of these diseases. Heritability analyses demonstrated heritability that was high for amyloid plaques (78%) relative to prior clinical AD heritability analyses, intermediate for TDP-43 inclusions (41%), and low for remaining AD and ADRD pathologic features. This study underscores the importance of investigating the underlying neuropathologic hallmarks of AD and ADRDs as a step toward refining the translation of genetic associations to biomarker interpretation and development of targeted therapeutics.

In aging men, mosaic loss of chromosome Y (mLOY) is a possible biomarker for increased risk of disease, including Alzheimer disease (AD). We previously reported mLOY increased with age and carriers of mLOY had an increased risk of AD. We also found plasma Aβ42/p-tau181 ratio (APR) was significantly lower among AD Amish individuals compared to cognitively-unimpaired (CU) individuals. We now examine how these two biomarkers interplay with cognitive status in Amish males. mLOY was determined using the Mosaic Chromosomal Alterations(MoChA) pipeline. Extensive QC was done for both mLOY and plasma biomarker measures. Consensus review of medical history and neuropsychological testing categorized individuals into AD, Mild-cognitive-impairment (MCI) or Cognitive-impairment-not-AD (CINAD) or CU. The cognitively-impaired (CI) group combined AD, MCI and CINAD. We compared 1) CI to CU and 2) AD to CU. Correlation between APR and mLOY were estimated accounting for relatedness. Receiver operating characteristic analysis was performed to evaluate the discriminatory ability of the two biomarkers compared to the baseline model with age and presence/absence of APOE ε4 alleles. p -value <0.05 was noted as statistically significant. 249 males (mean age=82.89±5.57) had measurements for both biomarkers. Of these, a subset had consensus diagnoses AD ( n  = 30; mean age=85.63±5.31), CINAD, MCI or CU ( n  = 105; mean age=82.01±5.36). The mean age of 82 CI individuals was 84.34±4.73. mLOY was observed in 20.1% of CU vs. 29.3% of CI ( p -value=0.23). APR was significantly negatively correlated with CI and AD as expected, was positively correlated with mLOY but not significantly and remained positively correlated when stratified, with the stronger correlation in AD. For AD, the area under the curve (AUC) improved from 0.70 to 0.82 with the inclusion of APR, with mLOY showing little effect. For CI, AUC improved from 0.63 to 0.68 by including mLOY, with no independent effect of APR. When including both in the model, AUC improves from 0.63 to 0.69. We observed two promising biomarkers of AD, mLOY and APR, both contribute discriminating AD and CI but differently. This and the stringer correlation in AD may indicate they are more specific to AD than non-specific CI.

INTRODUCTION:Cognitive SuperAgers (SAs) are individuals aged 80+ with exceptional episodic memory performance for their age, exceeding middle-aged adult norms. This study integrates family- and association-based methods to identify genetic variants associated with SAs in the Midwestern Amish population. METHODS:Eighty-three Amish SAs were grouped into 16 pedigrees for parametric and non-parametric linkage analysis. Variants in linked regions (heterogeneity logarithm of the odds [HLOD] or Kong and Cox logarithm of the odds [LOD*] ≥ 3) were tested for association with SAs using two contrasts: SA versus Alzheimer's disease (AD; n = 40) and SA versus cognitively unimpaired (CU), age-matched non-SA individuals (CU80+; n = 157). RESULTS:Evidence of linkage for SAs was observed on chromosomes 1, 2, 7, 16, and 20, with the strongest signal around the AD-associated locus WDR12 on chromosome 2. Association analysis for SA versus AD identified eight variants in HIVEP3 (chromosome 1) that were nominally significant when comparing SA versus CU80+. DISCUSSION:WDR12 and HIVEP3 are potential candidate genes contributing to SAs in the Amish population.

CNS diseases are a prevailing cause of morbidity and mortality worldwide, and are influenced by environmental and biological factors, including genetic risk. Here, we generated genome-wide genetic data on a large cohort of brain tissue donors with in-depth clinical and neuropathological phenotyping, allowing for broad investigations into the risk and mechanisms of these neurological, neurodevelopmental and psychiatric conditions. This resource consists of 9663 donors with array-based genotyping and 9543 donors with whole-genome sequencing completed. The clinical diagnoses of these donors include 148 CNS diseases clustered into 15 broad categories by International Classification of Diseases-10 (ICD-10) coding. These donors were collected by six repositories comprising the National Institutes of Health NeuroBioBank, with an average participant age of 60 years. While primarily older individuals of European descent, the cohort also contains younger donors and individuals from non-European backgrounds. Variants were detected in whole-genome sequencing, normalized and annotated to describe their functional impact, resulting in 171 121 209 unique variants and 1 078 774 non-silent variants. These raw and normalized data have been made available as a neurogenomics resource in the National Institute of Mental Health Data Archive (nda.nih.gov), combined with donor-matched deep demographic and phenotypic data from the NeuroBioBank Portal (neurobiobank.nih.gov). To illustrate applications, we replicated the strong association observed in previous studies between pathogenic CAG nucleotide repeat expansions in the HTT gene with the clinical diagnosis of Huntington's disease, as well as associations of the APOE gene with Alzheimer's disease, and examined the association of polygenic risk scores with the three most common disease diagnoses in the cohort.

Objective:Both the phosphatidylinositol binding clathrin assembly protein gene (PICALM) and the embryonic ectoderm development gene (EED) have been implicated as causal genes driving a genome-wide association for Alzheimer disease (AD) risk. We employed a new virtual approach using genome-wide chromatin interactions (Hi-C) called enhanced Hi-C Capture Analysis (eHiCA) to identify the genes and regulatory regions that are driving this important AD risk association. Methods:Hi-C data from the frontal cortex of eight AD patients, as well as inducible pluripotent stem cell-derived microglia and spheroids of AD and control patients were used. We applied 14 eHiCA baits each containing a GWAS SNP to identify the cis regulatory interactions in this GWAS locus at a 5kb resolution. Results:The baits derived from the GWAS associated haplotype primarily interacted with the PICALM promoter and the large cis-regulatory elements cluster (CREe) lying upstream of the EED promoter. The EED promoter interacts with PICALM gene body and promoter region but not directly with the associated risk haplotype. Although the AD-associated variants segregate together as a haplotype in the population, each bait exhibited distinct functional chromatin interactions. Interpretation:The PICALM gene is the primary driver of the association in microglia along with the CREe locus. Different SNPs in a segregating haplotype can display different physical Hi-C interactions. This study demonstrates that eHiCA can help resolve the casual genes driving complex GWAS associations, opening new pathways to study Alzheimer disease and other disorders.

The impact of host genetic variability on Staphylococcus aureus bacteremia (SAB) risk is unknown. In genome-wide association studies, we identified specific HLA-class II variants associated with higher risk (HLA-DRB1*04:01 [OR = 1.121 (0.952, 1.321)] & 03:01 [OR = 1.103 (0.960, 1.269)] or lower risk (HLA-DRB1*07:01) of SAB. The aim of this study is to determine how HLA-DRB1 variants, which differ in S. aureus peptide presentation, may also differ in their ability to activate T cells and therefore protective immunity.Fig. 2Cytokine production by MOI and HLA-DRB1 variants To measure differential CD4+ T cell responses elicited by HLA-class II variation, CD4 T cells isolated from healthy donor HLA-DRB1 heterozygous peripheral blood mononuclear cells were split and separately co-cultured for 72 hrs with homozygous HLA-DRB1 matched B- lymphoblastoid cell lines that were unchallenged or pulsed overnight with dead S. aureus (USA 300) across a range of concentrations (multiplicity of infection [MOI = 0.5, 5, 50]). CD4 T cell activation (CD69+ CD25+) was assessed by flow cytometry (BD Fortessa & FlowJo) using monoclonal antibodies specific for CD4 PerCP-Cy5.5, CD69-PE, and CD25-APC and expressed as mean and standard deviation (Prism). Culture supernatants were collected for cytokine quantification (ProcartaPlex) using the Luminex 200 analyzer (xPONENT). Comparisons between MOI and HLA-DRB1 allele were determined with a two-way ANOVA (Prism). We observed variable T cell responses to S. aureus across different HLA-DRB1 alleles. HLA-DRB1*07:01 elicited a greater fold change in CD4+ T cell activation (MOI 0.5= 2.84 ±1.5; MOI 5= 6.65 ±3.6; MOI 50= 7.96 ±4.1) compared to HLA-DRB1*04:01 (MOI 0.5= 1.48 ±0.27; MOI 5= 3.15 ±0.77; MOI 50= 4.96 ±1.7) or 03:01 (MOI 0.5 =1.95 ±0.66; MOI 5= 2.56 ±0.81; MOI 50= 2.42 ±0.86) across S. aureus concentrations. Variable CD4 T cell cytokine response to recognition of S. aureus peptide was also observed across HLA-DRB1*04:01, 03:01, and 07:01 variants. Cytokines associated with Th1 response and T cell proliferation are shown, but these markers did not reach statistical significance. We provide in vitro evidence to suggest that HLA-DRB1 variation in S. aureus peptide presentation impacts CD4+ T cell activation and may explain the association between certain HLA-DRB1 haplotypes and SAB. Vance G. Fowler, MD, MHS, Affinergy, Janssen, Contrafect: Advisor/Consultant|AstraZeneca; EDE; Basilea: Grant/Research Support|Debiopharm, GSK; Affinium, Basilea,: Advisor/Consultant|Destiny, Amphliphi, Armata, Akagera: Advisor/Consultant|Merck; Contrafect; Karius; Janssen: Grant/Research Support|UpToDate: Royalties|Valanbio: Stock options

INTRODUCTION:Plasma biomarkers for Alzheimer's disease (AD) hold promise for disease diagnosis and prediction, yet their genetic underpinnings remain under explored. METHODS:We measured plasma amyloid beta (Aβ)40, Aβ42, Aβ42/Aβ40, total tau (t-tau), phosphorylated tau 181 (p-tau181), Aβ42/t-tau, Aβ42/p-tau181, neurofilament light chain, and glial fibrillary acidic protein in the Midwestern Amish. Pedigree-based heritability ( h ped 2 ) was estimated from multigenerational pedigrees, and single nucleotide polymorphism (SNP)-based heritability ( h SNP 2 ) was derived from SNPs. RESULTS:Among all Amish individuals, additive genetic effects ( h ped 2 ) explained 11.1% to 36.6% of biomarker variances. h SNP 2 estimates were consistently lower, ranging from 6.7% to 28.7%. The heritability of these biomarkers in subgroups of cognitively normal individuals and apolipoprotein E ε4 non-carriers yielded similar results. DISCUSSION:Plasma biomarkers such as Aβ, t-tau, and p-tau181 are moderately heritable in the Amish, underscoring the impact of genetic determinants of plasma biomarkers associated with AD.

Purpose:Age-related Macular Degeneration (AMD), a degenerative disease of aging, leads to central vision loss and has a strong genetic risk. Genetic heritability, used to quantify genetic influence on a trait, has mainly focused on twin study designs but these are vulnerable to bias. Studying relatives beyond twins is necessary to bring clarity to the genetic burden of AMD and help focus the search for additional genetic risk loci. Methods:Through both single nucleotide polymorphism (SNP) and pedigree-based heritability methods, the heritability of AMD was analyzed using relationship informed analyses of families from an Amish population (n = 525). AMD status was determined using the Beckman grading scale (285 controls and 240 cases). An estimate of genetic relatedness preceded SNP heritability estimation, whereas the pedigree heritability model utilized genealogical reports. Primary models were adjusted for age, sex, and population structure. A comparison of SNP- and pedigree-based models followed heritability estimation. Sensitivity models adjusting for all possible combinations of three known strong AMD genetic risk variants were constructed. Results:SNP heritability is 55% +/- 13% (p= 9.87e-06) and the pedigree heritability is 49% +/- 18% (p= 3.06e-04). The sensitivity analyses revealed that the estimates were robust to changes in the inclusion of AMD variants as covariates. Conclusions:These heritability estimates support existing twin and SNP-based AMD heritability estimates and corroborate the substantial involvement of genetics in AMD. Adjusting for known AMD variants revealed that additional genetic contribution exists, supporting a large polygenic effect in AMD.

Late-onset Alzheimer disease (LOAD), the most common form of dementia among older adults, is a neurodegenerative disease characterized by brain amyloid-β (Aβ) plaque deposition and neurofibrillary tangles. The causes of LOAD are not known but several recent lines of evidence implicate the adaptive immune system. Here, we sought to characterize somatic T-cell receptor (TCR) sequence diversity profiles and class I and II human leukocyte antigen (HLA) alleles from DNA extracted from peripheral tissues from Midwestern Amish participating in longitudinal studies of aging. We immunosequenced the TCR beta chain from genomic DNA of 72 Midwestern Amish, including participants with clinically diagnosed LOAD (n=6), mild cognitive impairment (MCI; n=16), cognitive impairment but not AD (CINAD; n=3), and 35 cognitively unaffected. TCR sequence diversity by cognitive status was examined using a variety of metrics, and tests of association were performed between cognitive status and HLA alleles. For a subset of participants, plasma biomarkers for LOAD pathogenesis were available to evaluate TCR sequence diversity by cognitive status. TCR sequence diversity measured as Simpson's clonality was lower among LOAD+MCI compared with non-LOAD, but these differences were not independent of age. Relatively few clonotypes (exact nucleotide sequences) were shared across participants; of those few shared include the Epstein Barr virus associated clonotype. HLA-A*03:01 and several HLA-DRB1 alleles were under-represented among LOAD+MCI participants compared with cognitively unaffected participants, but these associations were no longer significant in adjusted analyses. Among LOAD+MCI participants with plasma biomarkers, increased p-tau181 was associated decreased TCR sequence diversity, and the association was independent of age. In this limited Midwestern Amish sample, the observed TCR diversity associations are consistent with the involvement of the adaptive immune system in LOAD.

The effect size of APOE4 varies across genetic ancestries with African (AFR) local ancestry conferring a lower risk when compared to other ancestries. Recently, we identified a strong effect of the A allele of rs10423769 (with a minor allele frequency of 0.12 in AFR and 0.003 in Europeans), which lowers the risk of AD by 71% in APOE4 carriers. rs10423769 is 2 MB from APOEe4 in a region of segmental duplications (SD) containing a cluster of pregnancy specific beta-1 glycoprotein genes ( PSGs) and a lncRNA. To gain insights into the mechanism of protection, we characterized the haplotype harboring the variant and investigated differences in methylation and structural variation (SV) between haplotypes. We used the Alzheimer’s Disease Sequencing Project (ADSP) short read sequencing database to fine map and extend the protective haplotype using Haploview 4.2. In addition, long read sequencing (LRS) with the Oxford Nanopore PromethION was performed on 16 samples of individuals carrying one or two copies of rs10423769_A. LRS was used for SV calling with Sniffles2 and differential methylation analysis using Nanomethphase. The minimum shared haplotype harboring rs10423769_A allele was ∼21kbp (chr19:43099521- 43120243). Though the region is rich in SDs, high quality LRS reads mapped uniquely to the region around the A allele confirming that the haplotype is unique and not duplicated elsewhere in the genome of the sequenced individuals. Moreover, the rs10423769_A haplotype harbors 23 differential CpG sites (fdr<0.05) compared to rs10423769_G, although no differential methylated region was identified. LRS revealed a 140bp insertion of repetitive MEF2 binding motifs. Initial examination demonstrated that the insertion was present in 80% of the A allele carriers. We have identified an AF-specific haplotype protective against AD risk conferred by APOE ε4. Considering the distance from APOE and the complexity of the highly SD region where the variant is located, we have identified the minimum shared haplotype from AFR origin and are investigating the potential effects of SVs and differential CpG sites. Ongoing analyses include 3D chromatin structure and LRS at higher coverage to assemble and resolve the complex genomic context of the allele.

Annotation of target genes of non-coding GWAS loci remains a challenge since 1) regulatory elements identified by GWAS can be metabases away from its actual target, 2) one regulatory element can target multiple genes, and 3) multiple regulatory elements can target one gene. AD GWAS in populations with different ancestries have identified different loci, suggesting ancestry-specific genetic risks. To understand the connection between associated loci (potential regulatory elements) and their target genes, we conducted Hi-C analysis in frontal cortex of African American (AA) and Non-Hispanic Whites (NHW) AD patients to map chromatin loops, which often represent enhancer-promoter (EP) interactions. In our initial analyses, we applied HiC to uncover the regulatory architecture of rs3851179 linked to the embryonic ectoderm development gene ( EED ) in the ADSP gene verification list. Hi-C libraries were derived from four AA and four NHW donors matched for age, sex, and APOE genotype. The AA samples had 68∼88% African (AF) genome while NHW samples had >95% European (EU) genome. DeepLoop was used to generate robust maps of chromatin loops. Hi-C data from each population were pooled to generate reference chromatin loop maps for the AF and EU genomes. rs3851179 (OR = 0.9, P = 3.0 × 10 −48 ) resides between EED and PICALM , about 80 Kb away from both with each gene transcribed in opposite directions. Although PICALM is designated as a causal gene, EED is designated a susceptibility gene by ADSP based on the transcription direction and distance from rs3851179. Hi-C data from both AF and EU genome in frontal cortex revealed that rs3851179 co-localizes with a loop anchor, connecting H3K27ac peaks (enhancer) overlapping rs3851179 to the proximal promoter of PICALM , suggesting that PICALM but not EED is the target gene, corroborated by the GTEX e-QTL data. This initial application of Hi-C data demonstrates the utility of chromatin regulatory maps in nominating target genes of GWAS hits in non-coding loci. The generation and eventual application of Hi-C maps in African and Amerindian genomes (which are part of the AA or American Hispanic genomic admixture) will be key dissecting ancestry-specific genetic loci and, thereby, broadening diversity in AD research.

Non-Hispanic White APOE4 carriers have a higher risk of developing AD compared to African American APOE4 carriers. The local ancestry (LA) surrounding the APOE region was previously shown to be the primary factor in this risk difference. APOE4 carriers of European LA (ELA) have been found to have higher APOE4 expression and chromatin accessibility compared to African LA (ALA). We sought to investigate whether the LA around APOE3 has the same effect between ancestries. Differences between alleles could provide insight into ancestry-specific regulatory areas controlling the APOE4 expression. We identified AD autopsy samples by GSA, all homozygous for APOE3 and LA from 4 ADRC brain banks: Miami, Emory, Duke, and Rush. We performed single nuclei RNA sequencing (snRNA-seq) on eight frozen frontal cortex (B9 area) samples using 10x Genomics. We performed snRNA-seq in a total of 51,462 nuclei from eight brains (4 ELA and 4 ALA). We identified 35 distinct cell clusters at a resolution of 0.6. The proportion of cells per cluster between ELA and ALA samples was similar for all clusters, except for cluster 32 (Excitatory Neurons) which had a greater than 2-fold difference in ALA. Our data shows that APOE3 carriers with ELA have a significantly higher APOE expression in Excitatory Neurons (cluster 7) than those of ALA and contrary to our previous observations in APOE4 carriers (Griswold, A. et al , (2021)), APOE3 carriers of ALA express higher APOE in astrocytes (cluster 2) and Microglia (cluster 6). However, overall, comparison of APOE3 vs APOE4 carriers in this study demonstrated that APOE3 alleles have significantly lower gene expression than APOE4 carriers of the same LA. Our preliminary data suggest that the LA surrounding APOE3 is associated with different effects on APOE expression compared to APOE4 allele. Further, within the same LA, we observed that, overall, the different cell types express less APOE in APOE3 carriers compared to APOE4 carriers. Altogether, this may provide additional insight into the regulatory mechanisms affecting APOE4 expression.

Late-onset Alzheimer Disease (LOAD) shares multiple pathologic features and genetic risk factors with Age-related Macular Degeneration (AMD). Amyloid-beta (Ab) forms amyloid plaques in the brain and aggregates with other proteins and lipids to form drusen deposits in the retina of AMD eyes. CFH and HTRA1 , genes coding for Ab-processing complement proteins, are the strongest genetic risk factors for AMD, but the association with LOAD has been equivocal. In addition, the APOE e4 allele, LOAD's strongest genetic risk factor, has the opposite effect (e.g. is protective) for AMD. Therefore, we investigated whether the strongest genetic risk factors for AMD, CFH and ARMS2/HTRA1 also influence risk of LOAD. Utilizing our large dataset of mid-Western Amish individuals, we performed single nucleotide polymorphism (SNP) association analysis on the ARMS2/HTRA1 and CFH loci to determine their association with LOAD. This analysis included 152 LOAD cases and 746 cognitively unimpaired controls, all evaluated by consensus review of clinical test results. Those with known AMD were excluded from this study. Our preliminary results found no significant association between LOAD and the individual SNPs defining the CFH or ARMS2/HTRA1 loci. As these genes are in regions of strong linkage disequilibrium, these SNPs define a small set of extended haplotypes, which have known differential impact on AMD. Single SNP association analyses did not expose any significant associations between LOAD and single SNPs at the CFH or ARMS2/HTRA1 loci. Examining the haplotype association with LOAD will allow for increased power and better understanding of the risk these two loci confer to LOAD.

We have reported a statistical interaction between the African ancestry specific A allele at rs10423769 and APOEε4 , where the presence of the A allele is associated with a reduction in AD risk up to 75% in APOEε4 homozygotes. The mechanism by which this variant confers protection could provide insights into new therapeutics for APOEε4 carriers. However, the genomic context of this protective variant is complex with a high number of segmental duplications (SD) and structural variants (SVs). Thus, we have used advanced genomic techniques to investigate the region of ∼2MB between rs10423769_A and APOE to gain further insights into potential AD-protective mechanisms. We used high-coverage (90x) PacBio HiFi whole genome sequencing on 9 samples of rs10423769_A/A, rs10423769_A/G, and rs10423769_G/G carriers. We performed genome assembly with hifiasm to identify contigs spanning the whole region between the protective allele and APOE . We compared the contigs using minigraph and Bandage. We performed Hi-C sequencing from 13 brain autopsy samples (seven rs10423769_A carriers) and used in-house bioinformatics tools (enhanced Hi-C Capture Analysis - eHiCA) to identify chromatin loops indicative of potential interactions between the protective and APOE loci. Long read sequencing detected the co-occurrence of an expanded VNTR containing multiple MEF2D transcription factor binding sites within the protective haplotype. A higher number of SVs in the SD region surrounding rs10423769_A haplotype were detected when compared to the reference and are under investigation. eHiCA using rs10423769 or the APOE promoter as the bait suggested that rs10423769 locus and the APOE promoter region have evidence of long-range, physical interactions. Furthermore, both rs10423769 locus and the APOE promoter interact with common regions in between the two baits, including a cluster of zinc finger ( ZNF ) genes upstream of APOE . The reciprocal eHiCAs suggest high confidence interactions between these loci and with other regions of chr19. Our results show that the protective haplotype locus of African origin has long-range, physical interactions with the APOE promoter and other regions on chr19. It also carries an expanded VNTR specific to the protective haplotype containing multiple transcription factor binding sites.

Plasma amyloid-beta (Aβ) 42/40 ratio and phosphorylated tau 181 (pTau181) are promising blood biomarkers for AD. Compared to heterogenous clinical phenotypes, they are more objective and proximal to the pathological hallmarks of Aβ plaques and tau tangles. Biomarker-guided clustering using Aβ42/40 and pTau181 can potentially establish subpopulations that share similar mechanisms of AD and treatment responses. Plasma biomarkers were measured using Simoa™ Neuro-3Plex, 4Plex, and pTau181 Advantage V2 assays. To eliminate potential confounding effects, age, sex, and study center were regressed out of Aβ42/40 and pTau181 using a quadratic regression model. Adjusted biomarkers were then normalized for unsupervised K-means clustering, with the optimal number of clusters determined by the elbow method and Silhouette score. To interpret the cluster profiles, we explored the differences in demographics and clinical features between clusters. We also examined the association between clusters and neuropsychological tests adjusting for age, sex, study center, APOE e4 alleles, and diagnosis. We analyzed plasma biomarkers from 593 Amish individuals (age ³ 60 years old) living in Ohio and Indiana. 62% were females, and the average age was 81.7 ± 5.7 years. Utilizing plasma Aβ42/40 and pTau181, the clustering approach yielded six distinct clusters (N = 92, 95, 94, 152, 75, and 85) whose composition was driven by varying burdens of amyloid and tau pathology. There was no significant difference in proportion of cognitive impairment or of family structure across clusters. As expected, the low Aβ42/40 and high ptau cluster (Cluster 6) featured a significantly higher proportion of APOE e4 carriers than other clusters combined (51% vs 22%, p = 0.002). No significant associations were found between clusters and neuropsychological tests. The integrated analysis of plasma Aβ42/40 and pTau181 in the Amish established six clusters with varying levels of amyloid and tau burden, suggesting possible differences that need to be further explored. Examination of potential genetic or pathophysiological differences across the clusters are underway.

Studies of older adults with exceptional cognitive performance can enhance understanding of the mechanisms that protect against Alzheimer's disease (AD). Cognitive SuperAgers (SA) are individuals aged 80 and above with above-average episodic memory performance exceeding norms for middle-aged adults. This study integrates family- and association-based analytical approaches to identify genetic variants associated with SA in the Midwestern Amish population. A comprehensive neuropsychological evaluation was conducted among adult Amish participants ( N  = 515). SA were defined as those aged ≥ 80 with episodic memory task performance at or above the mean for ages 35-44, and non-episodic memory tasks within one standard deviation of the mean or better for the participant's age ( N  = 83). SA were grouped into 16 pedigrees for parametric and non-parametric linkage analysis allowing for locus heterogeneity in MERLIN. Variants located in regions exhibiting HLOD or LOD* scores ≥ 3 were tested for association with SA in GENESIS. Comparison groups included cognitively unimpaired, age-matched non-SA individuals (CU 80+, n  = 157) and individuals with AD ( n  = 40). Significance thresholds for each region were determined using SimpleM, which estimates the number of independent tests in the presence of high linkage disequilibrium. Linkage analysis identified HLOD scores > 3 on chromosomes 1 (HLOD = 3.10, GRCh38 44.6 Mb), 2 (HLOD = 3.92, 202.9 Mb), 7 (HLOD = 3.14, 30.2 Mb), 16 (HLOD = 3.18, 22.7 Mb), and 20 (HLOD = 3.71 16.7). Regional analysis revealed significant associations for eight correlated variants in the HIVEP3 gene on chromosome 1, comparing SA to AD (peak signal at rs12734651, OR = 0.24, p  = 6.46 x 10 -6 ). These variants were nominally associated when comparing SA to CU 80+ (rs12734651, OR = 0.61, p  = 0.032). This study identified variants in HIVEP3 associated with SA. Previous studies have linked variants in HIVEP3 to increased risk of AD, as well as with hippocampal volume and cognitive trajectories in unimpaired adults, suggesting that variants in HIVEP3 may influence both AD risk and cognitive performance in unimpaired individuals. These findings indicate that HIVEP3 represents a plausible candidate for further investigation into the mechanisms promoting exceptional cognitive performance in older adults.

Parkinson's disease (PD) is a progressive neurodegenerative disorder with complex and heterogeneous molecular pathology across the brain. However, the full cellular architecture of PD progression remains unresolved. Here, we present a comprehensive single-nucleus transcriptomic atlas of PD spanning multiple anatomically and clinically relevant brain regions to capture shared and region-influenced transcriptomic features from 97 deeply phenotyped donors, including individuals across the full spectrum of Braak Lewy body stages. Profiling over 2 million nuclei, we define 62 transcriptionally distinct cell subtypes and uncover widespread, cell-type-specific gene expression changes across neurons, glia, and vascular cells. We identify convergent upregulation of stress-responsive transcriptional programs - such as unfolded protein response, DNA damage repair, and autophagy - across multiple cell types, with key regulators including HSF1, MYC, and FOXO3. Integrative analyses link these transcriptional alterations to PD genetic risk, revealing transcription factor to target gene networks enriched for PD GWAS loci in microglia and neuronal subpopulations. To quantify disease burden at cellular resolution, we introduce a transcriptomic pathology score, revealing early-stage activation in neurons and myeloid cells, followed by delayed engagement of vascular populations. We further demonstrate that microglia undergo dynamic, subtype-specific transitions across disease stages, including early adaptive responses and late-phase stress and proliferative programs. Altered cell-cell communication networks, particularly involving myeloid-neuronal signaling, highlight a progressive rewiring of neuroimmune interactions. This atlas provides a foundational resource for understanding PD progression at single-cell resolution, linking genetic risk to dynamic molecular pathology, and illuminating stage-specific targets for therapeutic intervention.

Inflammation is a key driver of Alzheimer’s disease (AD) and may connect all known AD risk factors. Recently, AD resilience outcomes have been developed which have helped to uncover mechanisms that enable some individuals to withstand significant AD pathology or genetic risk, while retaining cognitive function. We conducted a series of transcriptome-wide association studies (TWAS) focusing on monocytes, key innate immune cells that respond to pathogens and invade the CNS. Monocyte expression data under various immune stimulation states (naive, LPS 2 h, LPS 24 h, IFN 24 h) and corresponding genotype data from 432 individuals (Fairfax et al. [1]) were analyzed. We developed cis-genetic expression models using both elastic-net, and MASH combined with LD-pruning; capturing polygenic structures and independent inflammatory eQTLs across conditions, respectively. These models were applied to GWAS summary statistics of three AD resilience phenotypes: cognitive and global AD-resilience, and Amish cognitive preservation. We identified 180 TWAS results surpassing a suggestive significance threshold of PFDR < 0.20, including 92 unique genes. APP, a well-known AD gene, showed the strongest overall association, which may inform ongoing efforts targeting its action in the brain. Whole-blood RNA-seq data from a separate AD cohort confirmed differential expression between AD cases and controls in 35 putative targets, including: SURF1, ACKR3, LILRA5, FBXO2, ITPR1, and HRH4. We also demonstrate that the regulation of these genes is specific to monocytes. Finally, in-silico cell sorting (CIBERSORTx) revealed differential monocyte abundance by AD status, supporting monocyte-driven inflammation as a distinct, complementary pathway of myeloid cell involvement in AD. Together, these findings highlight monocytes as a critical and understudied cellular component for AD resilience mechanisms, with potential implications for novel immunotherapeutic strategies and precision medicine approaches in AD.