An atlas of cortical circular RNA expression in Alzheimer disease brains demonstrates clinical and pathological associations.

Parietal cortex RNA-sequencing (RNA-seq) data were generated from individuals with and without Alzheimer disease (AD; ncontrol = 13; nAD = 83) from the Knight Alzheimer Disease Research Center (Knight ADRC). Using this and an independent (Mount Sinai Brain Bank (MSBB)) AD RNA-seq dataset, cortical circular RNA (circRNA) expression was quantified in the context of AD. Significant associations were identified between circRNA expression and AD diagnosis, clinical dementia severity and neuropathological severity. It was demonstrated that most circRNA-AD associations are independent of changes in cognate linear messenger RNA expression or estimated brain cell-type proportions. Evidence was provided for circRNA expression changes occurring early in presymptomatic AD and in autosomal dominant AD. It was also observed that AD-associated circRNAs co-expressed with known AD genes. Finally, potential microRNA-binding sites were identified in AD-associated circRNAs for miRNAs predicted to target AD genes. Together, these results highlight the importance of analyzing non-linear RNAs and support future studies exploring the potential roles of circRNAs in AD pathogenesis

CSF Tau phosphorylation at Thr205 is associated with loss of white matter integrity in autosomal dominant Alzheimer disease

BACKGROUND: Hyperphosphorylation of tau leads to conformational changes that destabilize microtubules and hinder axonal transport in Alzheimer\u27s disease (AD). However, it remains unknown whether white matter (WM) decline due to AD is associated with specific Tau phosphorylation site(s). METHODS: In autosomal dominant AD (ADAD) mutation carriers (MC) and non-carriers (NC) we compared cerebrospinal fluid (CSF) phosphorylation at tau sites (pT217, pT181, pS202, and pT205) and total tau with WM measures, as derived from diffusion tensor imaging (DTI), and cognition. A WM composite metric, derived from a principal component analysis, was used to identify spatial decline seen in ADAD. RESULTS: The WM composite explained over 70% of the variance in MC. WM regions that strongly contributed to the spatial topography were located in callosal and cingulate regions. Loss of integrity within the WM composite was strongly associated with AD progression in MC as defined by the estimated years to onset (EYO) and cognitive decline. A linear regression demonstrated that amyloid, gray matter atrophy and phosphorylation at CSF tau site pT205 each uniquely explained a reduction in the WM composite within MC that was independent of vascular changes (white matter hyperintensities), and age. Hyperphosphorylation of CSF tau at other sites and total tau did not significantly predict WM composite loss. CONCLUSIONS: We identified a site-specific relationship between CSF phosphorylated tau and WM decline within MC. The presence of both amyloid deposition and Tau phosphorylation at pT205 were associated with WM composite loss. These findings highlight a primary AD-specific mechanism for WM dysfunction that is tightly coupled to symptom manifestation and cognitive decline

Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.Fil: Dincer, Aylin. Washington University in St. Louis; Estados UnidosFil: Gordon, Brian A.. Washington University in St. Louis; Estados UnidosFil: Hari-Raj, Amrita. Ohio State University; Estados UnidosFil: Keefe, Sarah J.. Washington University in St. Louis; Estados UnidosFil: Flores, Shaney. Washington University in St. Louis; Estados UnidosFil: McKay, Nicole S.. Washington University in St. Louis; Estados UnidosFil: Paulick, Angela M.. Washington University in St. Louis; Estados UnidosFil: Shady Lewis, Kristine E.. University of Kentucky; Estados UnidosFil: Feldman, Rebecca L.. Washington University in St. Louis; Estados UnidosFil: Hornbeck, Russ C.. Washington University in St. Louis; Estados UnidosFil: Allegri, Ricardo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Ances, Beau M.. Washington University in St. Louis; Estados UnidosFil: Berman, Sarah B.. University of Pittsburgh; Estados UnidosFil: Brickman, Adam M.. Columbia University; Estados UnidosFil: Brooks, William S.. Neuroscience Research Australia; Australia. University of New South Wales; AustraliaFil: Cash, David M.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Chhatwal, Jasmeer P.. Harvard Medical School; Estados UnidosFil: Farlow, Martin R.. Indiana University; Estados UnidosFil: Fougère, Christian la. German Center for Neurodegenerative Diseases; Alemania. University Hospital of Tübingen; AlemaniaFil: Fox, Nick C.. UCL Queen Square Institute of Neurology; Reino UnidoFil: Fulham, Michael J.. Royal Prince Alfred Hospital; Australia. University of Sydney; AustraliaFil: Jack, Clifford R.. Mayo Clinic; Estados UnidosFil: Joseph-Mathurin, Nelly. Washington University in St. Louis; Estados UnidosFil: Karch, Celeste M.. Washington University in St. Louis; Estados UnidosFil: Lee, Athene. University Brown; Estados UnidosFil: Levin, Johannes. German Center for Neurodegenerative Diseases; Alemania. Ludwig Maximilians Universitat; Alemania. Munich Cluster for Systems Neurology; AlemaniaFil: Masters, Colin L.. University of Melbourne; AustraliaFil: McDade, Eric M.. Washington University in St. Louis; Estados UnidosFil: Oh, Hwamee. University Brown; Estados UnidosFil: Perrin, Richard J.. Washington University in St. Louis; Estados Unido

Cerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer’s disease

Alzheimer’s disease (AD) pathology develops many years before the onset of cognitive symptoms. Two pathological processes—aggregation of the amyloid- (A ) peptide into plaques and the microtubule protein tau into neurofibrillary tangles (NFTs)—are hallmarks of the disease. However, other pathological brain processes are thought to be key disease mediators of A plaque and NFT pathology. How these additional pathologies evolve over the course of the disease is currently unknown. Here we show that proteomic measurements in autosomal dominant AD cerebrospinal fluid (CSF) linked to brain protein coexpression can be used to characterize the evolution of AD pathology over a timescale spanning six decades. SMOC1 and SPON1 proteins associated with A plaques were elevated in AD CSF nearly 30 years before the onset of symptoms, followed by changes in synaptic proteins, metabolic proteins, axonal proteins, inflammatory proteins and finally decreases in neurosecretory proteins. The proteome discriminated mutation carriers from noncarriers before symptom onset as well or better than A and tau measures. Our results highlight the multifaceted landscape of AD pathophysiology and its temporal evolution. Such knowledge will be critical for developing precision therapeutic interventions and biomarkers for AD beyond those associated with A and tau

Circular RNA detection identifies circPSEN1 alterations in brain specific to autosomal dominant Alzheimer's disease

Background: Autosomal-dominant Alzheimer's disease (ADAD) is caused by pathogenic mutations in APP, PSEN1, and PSEN2, which usually lead to an early age at onset (< 65). Circular RNAs are a family of non-coding RNAs highly expressed in the nervous system and especially in synapses. We aimed to investigate differences in brain gene expression of linear and circular transcripts from the three ADAD genes in controls, sporadic AD, and ADAD. Methods: We obtained and sequenced RNA from brain cortex using standard protocols. Linear counts were obtained using the TOPMed pipeline; circular counts, using python package DCC. After stringent quality control (QC), we obtained the counts for PSEN1, PSEN2 and APP genes. Only circPSEN1 passed QC. We used DESeq2 to compare the counts across groups, correcting for biological and technical variables. Finally, we performed in-silico functional analyses using the Circular RNA interactome website and DIANA mirPath software. Results: Our results show significant differences in gene counts of circPSEN1 in ADAD individuals, when compared to sporadic AD and controls (ADAD = 21, AD = 253, Controls = 23-ADADvsCO: log2FC = 0.794, p = 1.63 × 10-04, ADADvsAD: log2FC = 0.602, p = 8.22 × 10-04). The high gene counts are contributed by two circPSEN1 species (hsa_circ_0008521 and hsa_circ_0003848). No significant differences were observed in linear PSEN1 gene expression between cases and controls, indicating that this finding is specific to the circular forms. In addition, the high circPSEN1 levels do not seem to be specific to PSEN1 mutation carriers; the counts are also elevated in APP and PSEN2 mutation carriers. In-silico functional analyses suggest that circPSEN1 is involved in several pathways such as axon guidance (p = 3.39 × 10-07), hippo signaling pathway (p = 7.38 × 10-07), lysine degradation (p = 2.48 × 10-05) or Wnt signaling pathway (p = 5.58 × 10-04) among other KEGG pathways. Additionally, circPSEN1 counts were able to discriminate ADAD from sporadic AD and controls with an AUC above 0.70. Conclusions: Our findings show the differential expression of circPSEN1 is increased in ADAD. Given the biological function previously ascribed to circular RNAs and the results of our in-silico analyses, we hypothesize that this finding might be related to neuroinflammatory events that lead or that are caused by the accumulation of amyloid-beta

Patterns and implications of neurological examination findings in autosomal dominant Alzheimer disease

Introduction: As knowledge about neurological examination findings in autosomal dominant Alzheimer disease (ADAD) is incomplete, we aimed to determine the frequency and significance of neurological examination findings in ADAD. Methods: Frequencies of neurological examination findings were compared between symptomatic mutation carriers and non mutation carriers from the Dominantly Inherited Alzheimer Network (DIAN) to define AD neurological examination findings. AD neurological examination findings were analyzed regarding frequency, association with and predictive value regarding cognitive decline, and association with brain atrophy in symptomatic mutation carriers. Results: AD neurological examination findings included abnormal deep tendon reflexes, gait disturbance, pathological cranial nerve examination findings, tremor, abnormal finger to nose and heel to shin testing, and compromised motor strength. The frequency of AD neurological examination findings was 65.1 %. Cross-sectionally, mutation carriers with AD neurological examination findings showed a more than two-fold faster cognitive decline and had greater parieto-temporal atrophy, including hippocampal atrophy. Longitudinally, AD neurological examination findings predicted a significantly greater decline over time. Discussion: ADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs

Autosomal dominant and sporadic late onset Alzheimer's disease share a common in vivo pathophysiology

The extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of 'sporadic' late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease. We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer's Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset. Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants. These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct

Amyloid-related imaging abnormalities in the DIAN-TU-001 trial of gantenerumab and solanezumab: lessons from a trial in dominantly inherited Alzheimer disease

OBJECTIVE: To determine the characteristics of participants with amyloid-related imaging abnormalities (ARIA) in a trial of gantenerumab or solanezumab in dominantly inherited Alzheimer disease (DIAD). METHODS: 142 DIAD mutation carriers received either gantenerumab SC (n=52), solanezumab IV (n=50), or placebo (n=40). Participants underwent assessments with the Clinical Dementia Rating® (CDR®), neuropsychological testing, CSF biomarkers, β-amyloid positron emission tomography (PET), and magnetic resonance imaging (MRI) to monitor ARIA. Cross-sectional and longitudinal analyses evaluated potential ARIA-related risk factors. RESULTS: Eleven participants developed ARIA-E, including 3 with mild symptoms. No ARIA-E was reported under solanezumab while gantenerumab was associated with ARIA-E compared to placebo (OR=9.1, CI[1.2, 412.3]; p=0.021). Under gantenerumab, APOE-ɛ4 carriers were more likely to develop ARIA-E (OR=5.0, CI[1.0, 30.4]; p=0.055), as were individuals with microhemorrhage at baseline (OR=13.7, CI[1.2, 163.2]; p=0.039). No ARIA-E was observed at the initial 225mg/month gantenerumab dose, and most cases were observed at doses >675mg. At first ARIA-E occurrence, all ARIA-E participants were amyloid-PET+, 60% were CDR>0, 60% were past their estimated year to symptom onset, and 60% had also incident ARIA-H. Most ARIA-E radiologically resolved after dose adjustment and developing ARIA-E did not significantly increase odds of trial discontinuation. ARIA-E was more frequently observed in the occipital lobe (90%). ARIA-E severity was associated with age at time of ARIA-E. INTERPRETATION: In DIAD, solanezumab was not associated with ARIA. Gantenerumab dose over 225mg increased ARIA-E risk, with additional risk for individuals APOE-ɛ4(+) or with microhemorrhage. ARIA-E was reversible on MRI in most cases, generally asymptomatic, without additional risk for trial discontinuation. This article is protected by copyright. All rights reserved

Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers

Positron emission tomography and magnetic resonance imaging methods and datasets within the dominantly inherited Alzheimer network (DIAN)

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case–control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual’s point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of ‘sporadic’ AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers