Citations

AbstractBackgroundScanning laser ophthalmoscopy (SLO) visualizes two important markers of cognitive dysfunction in the retina: vascular changes and amyloid plaque (AP) deposition. The relationship between retinal arteriolar versus venular changes and perivascular amyloid deposition across the continuum of neurodegeneration is imperfectly understood. We investigate the retinal perivascular AP distribution in relationship to cognitive and neuroimaging measures in a cohort of cognitively normal and impaired individuals.Method34 subjects with normal or impaired cognition underwent retinal SLO, brain magnetic resonance imaging and standard neuropsychometric testing. Retinal peri‐arteriolar and peri‐venular curcumin positive AP were quantified in the supero‐temporal retinal quadrant, in the first, second and third‐order retinal vascular branches. The peri‐venular and peri‐arteriolar AP count were compared between patients with normal and impaired cognition, and their correlation with brain volumes, white matter hyperintensities and cognitive Z‐scores was determined.ResultWe analyzed retinal para‐venous and para‐arteriolar amyloid count in 28 subjects, mean (SD) age 65 (7.3), 50% female, 19 (52.6%) with impaired cognition. Para‐arteriolar plaque count was higher than peri‐venular plaque in the entire cohort (p<0.0001). Secondary branch peri‐venular amyloid plaque count was higher in patients with MOCA ≤26. Tertiary branch perivascular AP count significantly and negatively correlated with hippocampal volume and positively correlated white matter hyperintensity lesion count.ConclusionRetinal AP deposit peri‐arteriolarly overall and peri‐venularly in the secondary branches in cognitively impaired. Perivascular amyloid burden in small retinal branches correlates with hippocampal volume and white matter hyperintensities.

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.

AbstractBackgroundAlthough the rate of Alzheimer’s disease (AD) in African‐ancestry (AA) Americans is higher than that of persons from European‐ancestry (EA) populations, AA participants have been underrepresented in AD neuropathological studies.MethodUtilizing the AD Research Centers (ADRC) infrastructure, we obtained AA donor pre‐frontal cortex (PFC) tissue from brain repositories of 12 ADRC and generated bulk RNA sequencing (RNA‐seq) data for 179 samples that met QC and inclusion criteria. Previously generated PFC RNAseq data were obtained for 28 additional AA donors from the Columbia University ADRC. Differential gene expression was evaluated among 125 donors with a neuropathological diagnosis of AD (NIA‐Reagan intermediate or high likelihood) and 82 neuropathologically confirmed controls using regression models including covariates for age at death, sex, cell‐type frequencies, and RNA integrity number (RIN) calculated with Limma. FDR‐corrected p‐values (padj) were calculated to control for the 33,611 genes examined.ResultA total of 482 genes surpassed the multiple‐testing threshold. The most significant, ADAMTS2 (p = 2.96 × 10‐8, padj = 0.001), showed increased expression in AD cases (see Table/Figure). We note that ADAMTS2 was differentially expressed in a prior EA study of neuropathologically confirmed AD cases and controls (Panitch et al. Molecular Psychiatry 2021). Additionally, a recent analysis of cognitive resilience in EA neuropathological AD cases identified a strong association with ADAMTS2 (See Li et al. AAIC2024 abstract). Of the differentially expressed genes observed in the Panitch et al. EA study, 385 (35%) were nominally significant,65 (5.8%) were corrected significant, and most (89%) of these genes had the same effect direction in the AA cohort. Some of the observed associations appear to be AA specific (e.g., EFR3B, IRS4, and CA12; see Table). Additionally, we found nominally significant (p<0.05) associations with expression of APOE (Log2 fold change [L2FC = ‐0.20, p = 0.012) and several other established AD genes including SORL1 (L2FC = ‐0.10, p = 0.014) and IGF1R(L2FC = 0.11, p = 0.0013).ConclusionThis largest‐ever (to our knowledge) gene expression study of AD in postmortem brain tissue from AA donors implicates many more genes as having a role in AD in this population than previously identified in genome‐wide association studies and provides insight into trans‐ancestry differences risk for AD.

Abstract Digital pathology (DP) has transformative potential, especially for Alzheimer disease and related disorders. However, infrastructure barriers may limit adoption. To provide benchmarks and insights into implementation barriers, a survey was conducted in 2019 within National Institutes of Health’s Alzheimer’s Disease Centers (ADCs). Questions covered infrastructure, funding sources, and data management related to digital pathology. Of the 35 ADCs to which the survey was sent, 33 responded. Most respondents (81%) stated that their ADC had digital slide scanner access, with the most frequent brand being Aperio/Leica (62.9%). Approximately a third of respondents stated there were fees to utilize the scanner. For DP and machine learning (ML) resources, 41% of respondents stated none was supported by their ADC. For scanner purchasing and operations, 50% of respondents stated they received institutional support. Some were unsure of the file size of scanned digital images (37%) and total amount of storage space files occupied (50%). Most (76%) were aware of other departments at their institution working with ML; a similar (76%) percentage were unaware of multiuniversity or industry partnerships. These results demonstrate many ADCs have access to a digital slide scanner; additional investigations are needed to further understand hurdles to implement DP and ML workflows.

Abstract Chronic traumatic encephalopathy (CTE) is a tauopathy associated with repetitive mild head impacts characterized by perivascular hyperphosphorylated tau (p-tau) in neurofibrillary tangles (NFTs) and neurites in the depths of the neocortical sulci. In moderate to advanced CTE, NFTs accumulate in the hippocampus, potentially overlapping neuroanatomically with primary age-related tauopathy (PART), an age-related tauopathy characterized by Alzheimer disease-like tau pathology in the hippocampus devoid of amyloid plaques. We measured p-tau burden using positive-pixel counts on immunohistochemically stained and neuroanatomically segmented hippocampal tissue. Subjects with CTE had a higher total p-tau burden than PART subjects in all sectors (p = 0.005). Within groups, PART had significantly higher total p-tau burden in CA1/subiculum compared to CA3 (p = 0.02) and CA4 (p = 0.01) and total p-tau burden in CA2 trended higher than CA4 (p = 0.06). In CTE, total p-tau burden in CA1/subiculum was significantly higher than in the dentate gyrus; and CA2 also trended higher than dentate gyrus (p = 0.01, p = 0.06). When controlling for p-tau burden across the entire hippocampus, CA3 and CA4 had significantly higher p-tau burden in CTE than PART (p &lt; 0.0001). These data demonstrate differences in hippocampal p-tau burden and regional distribution in CTE compared to PART that might be helpful in differential diagnosis and reveal insights into disease pathogenesis.

Abstract Primary age-related tauopathy (PART) is a neurodegenerative entity defined as Alzheimer-type neurofibrillary degeneration primarily affecting the medial temporal lobe with minimal to absent amyloid-β (Aβ) plaque deposition. The extent to which PART can be differentiated pathoanatomically from Alzheimer disease (AD) is unclear. Here, we examined the regional distribution of tau pathology in a large cohort of postmortem brains (n = 914). We found an early vulnerability of the CA2 subregion of the hippocampus to neurofibrillary degeneration in PART, and semiquantitative assessment of neurofibrillary degeneration in CA2 was significantly greater than in CA1 in PART. In contrast, subjects harboring intermediate-to-high AD neuropathologic change (ADNC) displayed relative sparing of CA2 until later stages of their disease course. In addition, the CA2/CA1 ratio of neurofibrillary degeneration in PART was significantly higher than in subjects with intermediate-to-high ADNC burden. Furthermore, the distribution of tau pathology in PART diverges from the Braak NFT staging system and Braak stage does not correlate with cognitive function in PART as it does in individuals with intermediate-to-high ADNC. These findings highlight the need for a better understanding of the contribution of PART to cognitive impairment and how neurofibrillary degeneration interacts with Aβ pathology in AD and PART.

AbstractBackgroundDigital pathology and machine learning (ML) workflows have paradigm shifting potential especially in the field of Alzheimer’s disease and related disorders. However, many institutions/centers may not have access to these technologies. To provide benchmark data, a survey was developed and distributed to National Institutes of Health’s Alzheimer’s Disease Centers (ADCs) in the United States.MethodSurvey questions covered topics such as: infrastructure (i.e. type of digital slide scanners used), funding sources (i.e. how the scanner was funded), and data management/storage (i.e. size of digital files). After development, review, and approval by the ADC digital pathology working group, the survey was distributed via email to 35 past and current ADC directors and/or ADC neuropathology core leaders. Participation in the survey was completely voluntary and answers did not contain any personal data.ResultThe survey generated over a 90% response rate, and the majority of those who completed the survey were neuropathology core leaders; 81% stated their ADC had access to a digital slide scanner, most common brand being Aperio/Leica. One third of respondents stated there was a fee for service to utilize the scanner. For digital pathology and/or ML resources, 40% of respondents stated none are supported in any way by their ADC. To cover the purchase and operation of the scanner, 50% stated they had institutional support. Many were unsure of the approximate average scanned file size of digital images (37%) and total amount of storage space that files occupied (50%). Many (75%) were aware of other departments at their institution working with digital pathology and/or ML, but a similar percentage was unaware of multi‐university or industry partnerships.ConclusionThese results demonstrate many ADCs have access to a digital slide scanner and had institutional support to cover the purchase. However, further investigation is needed to understand hurdles and barriers for implementing both digital pathology and ML workflows aiding in standardized methods across ADCs.

Abstract Vascular contributions to cognitive impairment and dementia (VCID) are characterized by the aging neurovascular unit being confronted with and failing to cope with biological insults due to systemic and cerebral vascular disease, proteinopathy including Alzheimer's biology, metabolic disease, or immune response, resulting in cognitive decline. This report summarizes the discussion and recommendations from a working group convened by the National Heart, Lung, and Blood Institute and the National Institute of Neurological Disorders and Stroke to evaluate the state of the field in VCID research, identify research priorities, and foster collaborations. As discussed in this report, advances in understanding the biological mechanisms of VCID across the wide spectrum of pathologies, chronic systemic comorbidities, and other risk factors may lead to potential prevention and new treatment strategies to decrease the burden of dementia. Better understanding of the social determinants of health that affect risks for both vascular disease and VCID could provide insight into strategies to reduce racial and ethnic disparities in VCID.