Perrin, Richard J.

Abstract 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. We evaluated plasma, serum, and CSF GFAP in families with autosomal dominant AD (ADAD), leveraging the predictable age at symptom onset to determine changes by stage of disease. Plasma GFAP elevations appear a decade before expected symptom onset, after β-amyloid accumulation and prior to neurodegeneration and cognitive decline. Plasma GFAP distinguished β-amyloid-positive from β-amyloid-negative ADAD participants and showed a stronger relationship with β-amyloid 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. Our findings support a role for plasma GFAP as a clinical biomarker for β-amyloid-associated cognitive deterioration in AD.

AbstractIntroductionAs 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.MethodsFrequencies 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.ResultsAD 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.DiscussionADAD features a distinct pattern of neurological examination findings that is useful to estimate prognosis and may inform clinical care and therapeutic trial designs.

AbstractINTRODUCTIONAs the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others.METHODSWe used hierarchical clustering to group 19 cross‐sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation.RESULTSThree primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors.DISCUSSIONThese results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.

AbstractBackgroundThough pathogenic variations in PSEN1 leading to Autosomal Dominant Alzheimer's disease (ADAD) are all highly penetrant, there is substantial inter‐individual variability in the rates of cognitive decline and biomarker change observed in ADAD. We hypothesized that this inter‐individual variability may be associated with the location of the pathogenic variant within PSEN1. We tested this hypothesis using biomarker and cognitive data from the Dominantly Inherited Alzheimer Network (DIAN) observational study.MethodPSEN1 pathogenic variant carriers [grouped based on whether their ADAD genotype affected transmembrane (PSEN1 TM; N = 125) or cytoplasmic (PSEN1 CY; N = 62) domains] and non‐carriers [NC; N = 176] enrolled in DIAN underwent clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF). Linear mixed effects models with a restricted cubic spline were used to determine cross‐sectional differences in clinical and biomarker measures between NC, PSEN1 TM, and PSEN1 CY groups, across the disease course (estimated years to symptom onset; EYO).ResultBackground characteristics are reported in Table 1. PSEN1 CY and PSEN1 TM groups had elevated β‐amyloid (PiB‐PET) and phosphorylated‐tau levels (CSF pTauT181) compared to NC, but these biomarker measures were not different between PSEN1 TM and CY groups (Figure 1a‐b). Additionally, the PSEN1 TM group had decreased glucose metabolism compared to NC but was similar to the PSEN1 CY group (Figure 1c). However, we observed that PSEN1 TM carriers had significantly smaller hippocampal volume, greater lateral ventricle volume, and greater cognitive impairment (Figure 1d‐f) across EYO as compared to PSEN1 CY carriers.ConclusionDespite similar β‐amyloid PET and CSF pTauT181 levels across EYO, individuals with pathogenic variants affecting transmembrane domains in PSEN1 may have more rapid progression of disease as measured by cognitive function and neurodegeneration as compared to those with variants affecting cytoplasmic domains. These results have implications both for understanding the heterogeneity in ongoing ADAD clinical trials and for better understanding the pathobiology of ADAD.

Abstract The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW‐ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public‐private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI‐1, ADNI‐GO, ADNI‐2, and ADNI‐3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW‐ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW‐ADNI researchers who shared updates from ADNI‐3 and their vision for ADNI‐4.

AbstractIntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.MethodsWe identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.ResultsDisease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.DiscussionADNI has had a profound impact in improving clinical trials for AD.

Abstract Introduction Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD‐MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD‐MC and could help predict risk for dementia during trial enrollment. Methods We created a dementia risk score by entering standardized gray‐matter volumes from 231 DIAD‐MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD‐MC followed longitudinally. Results Our risk score separated asymptomatic versus demented DIAD‐MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%–98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD‐MC participants for prevention trials.

Abstract Cognitive resilience is an important modulating factor of cognitive decline in Alzheimer’s disease, but the functional brain mechanisms that support cognitive resilience remain elusive. Given previous findings in normal ageing, we tested the hypothesis that higher segregation of the brain’s connectome into distinct functional networks represents a functional mechanism underlying cognitive resilience in Alzheimer’s disease. Using resting-state functional MRI, we assessed both resting-state functional MRI global system segregation, i.e. the balance of between-network to within-network connectivity, and the alternate index of modularity Q as predictors of cognitive resilience. We performed all analyses in two independent samples for validation: (i) 108 individuals with autosomal dominantly inherited Alzheimer’s disease and 71 non-carrier controls; and (ii) 156 amyloid-PET-positive subjects across the spectrum of sporadic Alzheimer’s disease and 184 amyloid-negative controls. In the autosomal dominant Alzheimer’s disease sample, disease severity was assessed by estimated years from symptom onset. In the sporadic Alzheimer’s sample, disease stage was assessed by temporal lobe tau-PET (i.e. composite across Braak stage I and III regions). In both samples, we tested whether the effect of disease severity on cognition was attenuated at higher levels of functional network segregation. For autosomal dominant Alzheimer’s disease, we found higher functional MRI-assessed system segregation to be associated with an attenuated effect of estimated years from symptom onset on global cognition (P = 0.007). Similarly, for patients with sporadic Alzheimer’s disease, higher functional MRI-assessed system segregation was associated with less decrement in global cognition (P = 0.001) and episodic memory (P = 0.004) per unit increase of temporal lobe tau-PET. Confirmatory analyses using the alternate index of modularity Q revealed consistent results. In conclusion, higher segregation of functional connections into distinct large-scale networks supports cognitive resilience in Alzheimer’s disease.