Joseph‐Mathurin, Nelly

AbstractBackgroundDisease‐modifying therapies for Alzheimer’s Disease (AD) are likely most beneficial when initiated in the pre‐symptomatic phase. To track success of such interventions fluid biomarkers became instrumental, with neurofilament light chain (NfL) showing particular promise. We previously reported that serum NfL increases in pre‐symptomatic phases of familial (autosomal‐dominantly inherited) AD (fAD) and that within‐person rate‐of‐change in NfL is an earlier predictor of fAD symptom onset compared to cross‐sectional levels. The aim of the study at hand was to extend these initial findings in a larger cohort.MethodParticipants enrolled in the Dominantly Inherited Alzheimer Network (DIAN) with matched cross‐sectional and longitudinal cerebrospinal fluid (CSF; n = 962) as well as plasma (n = 1294) samples were used. NfL measurements have been performed on the SIMOA platform using commercially available assay‐kits. To investigate the influence of physiological factors independent from AD, we first analyzed whether age and body mass index (BMI) could account for observed variation in inter‐individual CSF and plasma NfL levels considering non‐carrier family‐members (NC) as a healthy control group. Next, utilizing estimated years to symptom onset (EYO) and previously published methods (Preische et al., 2019), we determined the point in disease course when baseline and longitudinal CSF and plasma NfL concentrations started to increase in mutation carriers (MC) relative to NC, after adjusting for age and BMI.ResultOur results reveal a tight correlation of CSF and blood NfL values within MC as well as NC (figure 1A‐B). However, within NC, after correction for age and BMI, some unexplained variability remained (figure 1C). Further, a decrease of the NfL plasma/CSF ratio over age was found after correcting for BMI (figure 1D). The discrimination of MC from NC was equally good for plasma compared to CSF, being possible on the group level as early as around ‐15 to almost ‐20 EYO depending on the modelling (figure 2).ConclusionOur results support plasma equivalently to CSF NfL as a clinically useful biomarker to longitudinally track neurodegeneration in fAD. The systemic factors influencing physiological NfL values in blood should be investigated in future studies to further improve interpretation of this biomarker.

AbstractCarriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (μ) and standard deviation (σ) of standardized image intensities of T1‐weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR‐μ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1‐σ and FLAIR‐σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR‐μ decreased and T1‐σ and FLAIR‐σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity‐based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients.

ImportanceIncreased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors.ObjectiveTo estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes.Design, Setting, and ParticipantsThis cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers—the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer’s Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019).Main Outcome and MeasuresThe main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH.ResultsData from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = −3.1 [P = .002]; ADNI: t = −5.6 [P < .001]; HABS: t = −2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P < .001]; ADNI: t = 9.1 [P < .001]; HABS: t = 5.4 [P < .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P < .001).Conclusions and RelevanceThe findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.

AbstractAlthough pathogenic variants in PSEN1 leading to autosomal‐dominant Alzheimer disease (ADAD) are highly penetrant, substantial interindividual variability in the rates of cognitive decline and biomarker change are observed in ADAD. We hypothesized that this interindividual variability may be associated with the location of the pathogenic variant within PSEN1. PSEN1 pathogenic variant carriers participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study were grouped based on whether the underlying variant affects a transmembrane (TM) or cytoplasmic (CY) protein domain within PSEN1. CY and TM carriers and variant non‐carriers (NC) who completed clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF) as part of their participation in DIAN were included in this study. Linear mixed effects models were used to determine differences in clinical, cognitive, and biomarker measures between the NC, TM, and CY groups. While both the CY and TM groups were found to have similarly elevated Aβ compared to NC, TM carriers had greater cognitive impairment, smaller hippocampal volume, and elevated phosphorylated tau levels across the spectrum of pre‐symptomatic and symptomatic phases of disease as compared to CY, using both cross‐sectional and longitudinal data. As distinct portions of PSEN1 are differentially involved in APP processing by γ‐secretase and the generation of toxic β‐amyloid species, these results have important implications for understanding the pathobiology of ADAD and accounting for a substantial portion of the interindividual heterogeneity in ongoing ADAD clinical trials.

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.

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.

ObjectiveTo determine the characteristics of participants with amyloid‐related imaging abnormalities (ARIA) in a trial of gantenerumab or solanezumab in dominantly inherited Alzheimer disease (DIAD).Methods142 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.ResultsEleven 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 (odds ratio [OR] = 9.1, confidence interval [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 225 mg/month gantenerumab dose, and most cases were observed at doses >675 mg. 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.InterpretationIn DIAD, solanezumab was not associated with ARIA. Gantenerumab dose over 225 mg 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. ANN NEUROL 2022;92:729–744

Autosomal‐dominant, Dutch‐type cerebral amyloid angiopathy (D‐CAA) offers a unique opportunity to develop biomarkers for pre‐symptomatic cerebral amyloid angiopathy (CAA). We hypothesized that neuroimaging measures of white matter injury would be present and progressive in D‐CAA prior to hemorrhagic lesions or symptomatic hemorrhage. In a longitudinal cohort of D‐CAA carriers and non‐carriers, we observed divergence of white matter injury measures between D‐CAA carriers and non‐carriers prior to the appearance of cerebral microbleeds and >14 years before the average age of first symptomatic hemorrhage. These results indicate that white matter disruption measures may be valuable cross‐sectional and longitudinal biomarkers of D‐CAA progression. ANN NEUROL 2022;92:358–363