Fagan, Anne M.

AbstractBackgroundComparisons of late‐onset Alzheimer's disease (LOAD) and autosomal dominant AD (ADAD) are confounded by age.MethodsWe compared biomarkers from cerebrospinal fluid (CSF), magnetic resonance imaging, and amyloid imaging with Pittsburgh Compound‐B (PiB) across four groups of 387 cognitively normal participants, 42 to 65 years of age, in the Dominantly Inherited Alzheimer Network (DIAN) and the Adult Children Study (ACS) of LOAD: DIAN mutation carriers (MCs) and non‐carriers (NON‐MCs), and ACS participants with a positive (FH+) and negative (FH–) family history of LOAD.ResultsAt baseline, MCs had the lowest age‐adjusted level of CSF Aβ42 and the highest levels of total and phosphorylated tau‐181, and PiB uptake. Longitudinally, MC had similar increase in PiB uptake to FH+, but drastically faster decline in hippocampal volume than others, and was the only group showing cognitive decline.DiscussionPreclinical ADAD and LOAD share many biomarker signatures, but cross‐sectional and longitudinal differences may exist.

Abstract Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer’s disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer’s disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer’s disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer’s disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer’s disease.

Background: Estimates of ‘brain-predicted age’ quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. Methods: We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A−) participants (18–89 years old). In independent samples of 144 CN/A−, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. Results: All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A−. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. Conclusions: Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences. Funding: This work was supported by the National Institutes of Health (P01-AG026276, P01- AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, and U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer’s Association (SG-20-690363-DIAN).

Abstract Background Glial fibrillary acidic protein (GFAP) is a promising candidate blood‐based biomarker for Alzheimer's disease (AD) diagnosis and prognostication. The timing of its disease‐associated changes, its clinical correlates, and biofluid‐type dependency will influence its clinical utility. Methods We evaluated plasma, serum, and cerebrospinal fluid (CSF) GFAP in families with autosomal dominant AD (ADAD), leveraging the predictable age at symptom onset to determine changes by stage of disease. Results Plasma GFAP elevations appear a decade before expected symptom onset, after amyloid beta (Aβ) accumulation and prior to neurodegeneration and cognitive decline. Plasma GFAP distinguished Aβ‐positive from Aβ‐negative ADAD participants and showed a stronger relationship with Aβ load in asymptomatic than symptomatic ADAD. Higher plasma GFAP was associated with the degree and rate of neurodegeneration and cognitive impairment. Serum GFAP showed similar relationships, but these were less pronounced for CSF GFAP. Conclusion Our findings support a role for plasma GFAP as a clinical biomarker of Aβ‐related astrocyte reactivity that is associated with cognitive decline and neurodegeneration. Highlights Plasma glial fibrillary acidic protein (GFAP) elevations appear a decade before expected symptom onset in autosomal dominant Alzheimer's disease (ADAD). Plasma GFAP was associated to amyloid positivity in asymptomatic ADAD. Plasma GFAP increased with clinical severity and predicted disease progression. Plasma and serum GFAP carried similar information in ADAD, while cerebrospinal fluid GFAP did not.

AbstractBackgroundBlood based biomarkers that predict cognitive decline and Alzheimer’s disease (AD) pathology have the potential to accelerate AD therapeutic development and improve clinical care. Prior work suggests that plasma biomarkers of tau pathology (particularly post‐translational modifications of tau) may be highly useful in diagnosis and risk stratification for AD‐related neurodegeneration and cognitive decline. Levels of tau species lacking truncation of the N‐terminal region, particularly plasma and cerebrospinal fluid (CSF) levels of N‐terminal tau fragment 1 (NT1), have previously been shown to predict cognitive decline, neurodegeneration, and tau pathology in preclinical and symptomatic late‐onset AD. Here we examined plasma NT1 as a possible predictor of cognitive, clinical, pathologic, and neurodegenerative trajectories in autosomal dominant AD (ADAD) using data from the Dominantly Inherited Alzheimer Network Observational Study (DIAN‐Obs).MethodsAssociations between plasma NT1 levels and Mini‐Mental State Exam (MMSE), Clinical Dementia Rating SumBox® (CDR‐SB), hippocampal volume (HV), estimated years to symptom onset (EYO), Pittsburgh‐Compound‐B PET, and CSF Aβ42, and p‐tau181 were assessed using linear regression (150 pathogenic variant carriers, 81 non‐carriers; mean[SD] carrier age = 40.1 [10.4] years and EYO = ‐5.4 [10.4]). Plasma NT1 was measured using the Quanterix HD‐X platform. PET, MRI, clinical, and biofluid measures were derived using previously described procedures in DIAN‐Obs.ResultsCross‐sectional plasma NT1 levels in ADAD carriers were significantly associated with MMSE, CDR‐SB, HV, and p‐tau181 even after adjusting for EYO (Table 1; Figure 1). NT1 levels statistically diverged between carriers and non‐carriers 6.8 years before estimated symptom onset (Figure 2). In contrast, plasma NT1 levels were not significantly correlated with measures of β‐amyloid pathology after adjusting for EYO.ConclusionPlasma NT1 levels mirrored changes in clinical, cognitive, and neurodegenerative measures in ADAD, particularly in late asymptomatic and early symptomatic phases of disease. NT1 levels correlated with CSF measures of tau pathology, but NT1 levels were not strongly associated with CSF or PET measures of β‐amyloid pathology, unlike some previously‐studied plasma tau measures. Together with previous supportive findings in preclinical and symptomatic sporadic AD, these results suggest that plasma NT1 may be a useful biomarker of AD‐related tau pathology and neurodegeneration across a broad spectrum of disease.

AbstractBackgroundPreviously, we found that female sex is associated with greater pathology burden in early‐onset Alzheimer’s disease (EOAD) in the Longitudinal EOAD Study (LEADS). Here, we have expanded our analyses by adding APOE‐ε4 carrier status as a further predictor of EOAD pathologic burden.MethodWe included 180 EOAD LEADS participants with available APOE genotype, Flortaucipir PET, Florbetaben PET, and MRI data. Demographic and biomarker differences were analyzed using ANOVA. EOAD participants were split by sex and APOE‐ε4 carrier status. Box plots were created in R and a voxel‐wise multiple linear regression in SPM12 yielded statistical brain maps of gray matter density (GMD), amyloid and tau burden.ResultCompared to males, EOAD females showed significantly greater global amyloid uptake (mean SUVR, p=0.002) and greater tau SUVR in the MetaROI, Braak 3&4 and 5&6 regions (p=0.0007, p=0.001, p=0.01, resp., Table 1). Female APOE‐ε4 carriers showed greater tau SUVR in Braak regions 1&2 than female non‐carriers (p<0.01, Figure 2B). Male APOE‐ε4 carriers showed trend‐level thinner entorhinal cortex than male non‐carriers (p=0.06, Figure 1). Interestingly however, femaleAPOE‐ε4 non‐carriers showed greater global amyloid SUVR than female carriers (p<0.01, Figure 2A). Further, APOE‐ε4 non‐carriers showed significantly thinner medial temporal cortices than carriers in both sexes (M, p<0.05; F, p<0.01). Male APOE‐ε4 non‐carriers also showed significantly lower mean cortical thickness than male carriers (p<0.05, Figure 1). Female APOE‐ε4 non‐carriers showed trend‐level lower mean cortical thickness than female carriers (p=0.06, Figure 1). The FWE corrected SPM12 maps showed significantly greater GM atrophy in the right temporal lobe and greater amyloid burden in a right lateralized occipitoparietal pattern in female APOE‐ε4 non‐carriers compared to female carriers. Further, male APOE‐ε4 non‐carriers showed greater tau uptake in the left frontal lobe than male carriers (Figure 3).ConclusionThese results suggest that APOE‐ε4 non‐carrier status is associated with greater atrophy, amyloid and tau deposition in EOAD. This might be due to the presence of other strong genetic drivers of disease pathology in EOAD.

AbstractBackgroundWhite matter (WM) injury visible on MRI is a common finding in Alzheimer’s disease (AD) and is often attributed to small vessel ischemic changes secondary to increased systemic vascular risk. Increased WM injury has been associated with the progression of Autosomal Dominant AD (ADAD), though ADAD pathogenic variant carriers are relatively young and may not have elevated vascular risk factors. We hypothesized that WM injury in ADAD may reflect worsening of cerebral amyloid angiopathy (CAA) and neurodegeneration. Here we examine this hypothesis using cross‐sectional and longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN).MethodMRI data from ADAD pathogenic variant carriers (n=223) and non‐carriers (n=136) were used in the present study (Table 1). We extracted FreeSurfer‐based WM lesion (WML) volume from T1‐weighted images (hypointensities). Cortical microbleed (CMB) burden was assessed visually on susceptibility weighted/T2*‐weighted gradient echo images by experienced radiologists (blineded to the mutation status) at the Mayo Clinic in Rochester. Linear regression models compared WML volume at baseline in people with and without CMB. Linear mixed effect models assessed the relationships between longitudinal WML and both CMBs and FreeSurfer‐based total gray matter (GM) volume. Models were corrected for age and estimated years to symptom onset (EYO).ResultGreater baseline WML volume was seen in ADAD carriers vs. non‐carriers, particularly close to the age of estimated symptom onset. Baseline WML volume was greater in carriers with CMBs compared to those without (t=2.9, p=0.003, Figure 1). Longitudinal increase in WML amongst ADAD pathogenic variant carriers with CMBs was estimated to be 214 mm3/year greater than that amongst carriers without CMBs (t=4.1, p<0.001, Figure 2). Independent of this CMB effect, decreasing GM volume was strongly associated with increasing longitudinal WML volume (t=‐6.2, p<0.001, Figure 3). Similar analyses in the non‐carrier group yielded no significant findings.ConclusionConsistent with prior reports, WML volume was increased in ADAD pathogenic variant carriers. However, the results here suggest WML in ADAD may not solely be due to small vessel ischemic changes, but rather may be a result of worsening CAA and more rapid neurodegeneration.

AbstractBackgroundGiven the triplication of chromosome 21 and the location of the amyloid precursor protein gene on chromosome 21, almost all adults with Down syndrome (DS) develop Alzheimer disease (AD)‐like pathology and dementia during their lifetime. Comparing amyloid accumulation in DS to autosomal dominant AD (ADAD), another genetic form of AD, may improve our understanding of early AD pathology development.MethodWe assessed amyloid positron emission tomography (PET) imaging in 192 participants with DS and 33 sibling controls from the Alzheimer’s Biomarker Consortium‐Down Syndrome (ABC‐DS) and 265 mutation‐carriers (MC) and 169 familial controls from the Dominantly Inherited Alzheimer Network (DIAN) (Table 1). We calculated regional standard uptake value ratios (SUVR) using a cerebellar cortex reference region and converted global amyloid burden SUVR to centiloids. We compared amyloid PET by cognitive status and estimated‐years‐to‐symptom‐onset (EYO). EYO was calculated for DIAN participants by subtracting their age from parental age of symptom onset and for ABC‐DS participants by subtracting their age from 50.2 years, a published average age of symptom onset in a large sample of individuals with DS (Fortea et al., 2020). In a subset of participants, we assessed the relationship between amyloid PET and CSF Aβ42/40.ResultThe relationship between CSF Aβ42/40 and amyloid PET was similar in DS and MC participants (Figure 1). We did not observe significant differences between MC and DS grouped by cognitive status (Figure 2). However, when assessed over EYO, global amyloid burden was significantly elevated in MC at EYO ≥ ‐23 but was not elevated in DS until EYO ≥ ‐15 (Figure 3). We observed early cortical and subcortical amyloid PET increases in both groups, but we also measured some regional differences in amyloid PET changes between MC and DS, specifically in the medial occipital region (Figure 4 and 5).ConclusionThese results demonstrate similarities in the relationship between amyloid biomarkers and the levels of amyloid accumulation in ADAD and DS. However, we also observed a 5‐10 year delay and some regional differences in amyloid accumulation in DS. This is important for future clinical trials to consider when recruiting participants and determining treatment efficacy.

AbstractBackgroundRates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross‐sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN‐Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini‐Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®‐SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4‐year trial with annual assessments; 80% power; α = 0.05).ResultsPSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = ‐0.42[0.1], p=0.002), CDR®‐SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = ‐58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.

AbstractBackgroundRates of cognitive and biomarker change in Autosomal Dominant Alzheimer disease (ADAD) vary substantially across individuals. Prior cross‐sectional work suggests that the location of the pathogenic variant within PSEN1, specifically whether the underlying variant affects transmembrane (TM) or cytoplasmic (CY) domains in PSEN1, may be a key determinant in these differential rates of progression. Here we use longitudinal data from the Dominantly Inherited Alzheimer Network observational study (DIAN‐Obs) to examine whether variants affecting TM versus CY domains in PSEN1 have differential rates of change in key cognitive and neurodegenerative markers, and whether these differences are relevant to ADAD clinical trials.MethodsUsing longitudinal clinical, cognitive, and MRI data from PSEN1 pathogenic variant carriers [TM group N=76 and CY group N=44; Table 1], we assessed rates of change in Mini‐Mental State Exam (MMSE), Clinical Dementia Rating® Sum of Boxes (CDR®‐SOB), and hippocampal volume (HV) using linear mixed effects models accounting for disease stage (estimated years to symptom onset [EYO]). We further assessed how PSEN1 mutation location (TM versus CY) impacts sample size and detectable effect size in a potential ADAD clinical trial (modeled as a 4‐year trial with annual assessments; 80% power; α = 0.05).Results PSEN1 TM and PSEN1 CY groups did not differ on baseline age, EYO, or CDR®. The PSEN1 TM group had significantly greater rates of change on MMSE (B[SE] = ‐0.42[0.1], p=0.002), CDR®‐SOB (B[SE] = 0.23[0.1], p=0.001), and HV atrophy (B[SE] = ‐58.93[14.3], p=0.0006 compared to the PSEN1 CY group (Fig.1). Consistent with these differential rates of change, power analyses indicated the required sample size to detect a 30% treatment effect on MMSE or HV would be reduced by 59.6% for MMSE and 91.0% for HV for a trial population comprised of PSEN1 TM versus CY carriers (Fig.2).ConclusionsIndividuals who had a variant affecting the transmembrane domains of PSEN1 had greater rates of cognitive decline and neurodegeneration compared to those with variants affecting cytoplasmic domains. In addition to having implications for ADAD pathophysiology, these results suggest that incorporating information regarding the location of PSEN1 variants may be beneficial in analyzing and designing stratification approaches for ADAD trials.