Toledo, Jon B.

AbstractBackgroundThere is limited information on biomarker‐defined Alzheimer’s disease (AD) pathology in community‐recruited individuals of diverse racial and ethnic groups. Here, we assessed the association of race/ethnicity with baseline biomarkers and cognitive measures and hypothesized a lower impact of AD pathology in non‐Hispanic White (nHW) participants in the U.S. POINTER study clinical trial, which evaluates the benefits of a multidomain lifestyle intervention on cognition of community‐recruited at‐risk elderly individuals.MethodWe included 879 participants from the U.S. POINTER study enrolled in the imaging substudy (∼50% of participants) who self‐identified as nHW (n=644), African American/Black (AA/B, n=132), Asian (n=29), and Hispanic (n=74). Outcomes measures included global Aβ pathology (18F‐florbetaben), temporal meta‐ROI tau (18F‐MK‐6240), MRI‐measured white matter hyperintensity volume (WMH) volumes, global clinical dementia rating (gCDR), and global, executive, and memory standardized cognitive scores. The nHW participants were selected as reference. Power transformations normalized skewed distributions. Multivariable linear regressions include age, sex, education, Framingham risk score, and area deprivation index (ADI) as covariates.ResultAA/B harbored lower WMHs, and meta‐temporal tau ROI values. In the full model, 0.5 gCDR participants had higher centiloid values, were more likely to be AA/B and Hispanic, and had a greater burden of WMHs. In addition, higher centiloid values were associated with a 0.5 gCDR in all groups except for the AA/B participants. Hispanic, AA/B, and Asian participants had lower cognitive scores than the nHW group. A higher ADI score was associated with lower global and executive cognitive scores but not with WMH volume or Aβ centiloid score.ConclusionThe analyses of the community‐based U.S. POINTER indicate that AA/B individuals present differences in AD and related dementia biomarker values. nHW had higher fully adjusted cognitive scores. These results indicate a significant heterogeneity in the cognitive testing performance and biomarker values of individuals at risk for dementia in the community.

Abstract Dementia with Lewy bodies (DLB) is clinically defined by the presence of visual hallucinations, fluctuations, rapid eye movement (REM) sleep behavioral disorder, and parkinsonism. Neuropathologically, it is characterized by the presence of Lewy pathology. However, neuropathological studies have demonstrated the high prevalence of coexistent Alzheimer's disease, TAR DNA‐binding protein 43 (TDP‐43), and cerebrovascular pathologic cases. Due to their high prevalence and clinical impact on DLB individuals, clinical trials should account for these co‐pathologies in their design and selection and the interpretation of biomarkers values and outcomes. Here we discuss the frequency of the different co‐pathologies in DLB and their cross‐sectional and longitudinal clinical impact. We then evaluate the utility and possible applications of disease‐specific and disease‐nonspecific biomarkers and how co‐pathologies can impact these biomarkers. We propose a framework for integrating multi‐modal biomarker fingerprints and step‐wise selection and assessment of DLB individuals for clinical trials, monitoring target engagement, and interpreting outcomes in the setting of co‐pathologies.

As potential treatments for C9ORF72‐associated amyotrophic lateral sclerosis (c9ALS) approach clinical trials, the identification of prognostic biomarkers for c9ALS becomes a priority. We show that levels of phosphorylated neurofilament heavy chain (pNFH) in cerebrospinal fluid (CSF) predict disease status and survival in c9ALS patients, and are largely stable over time. Moreover, c9ALS patients exhibit higher pNFH levels, more rapid disease progression, and shorter survival after disease onset than ALS patients without C9ORF72 expansions. These data support the use of CSF pNFH as a prognostic biomarker for clinical trials, which will increase the likelihood of successfully developing a treatment for c9ALS. Ann Neurol 2017;82:139–146

Poly(GP) proteins are a promising pharmacodynamic marker for developing and testing therapeutics for treating C9ORF72 -associated amyotrophic lateral sclerosis.

AbstractIntroductionWe describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1–42), t‐tau, and p‐tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids.MethodsReview publications authored or coauthored by ADNI Biomarker core faculty and selected non‐ADNI studies to deepen the understanding and interpretation of CSF Aβ1–42, t‐tau, and p‐tau181 data.ResultsCSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non‐ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies.DiscussionFurther studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease‐modifying therapeutic trials.

AbstractBackgroundThere is epidemiological evidence that cardiovascular risk factors (CVRF) also are risk factors for Alzheimer's disease, but there is limited information on this from neuropathological studies, and even less from in vivo studies. Therefore, we examined the relationship between CVRF and amyloid‐β (Aβ) brain burden measured by Pittsburgh Compound B‐positron emission tomography (PiB‐PET) studies in the Alzheimer's Disease Neuroimaging Initiative.MethodsNinety‐nine subjects from the Alzheimer's Disease Neuroimaging Initiative cohort who had a PiB‐PET study measure, apolipoprotein E genotyping data, and information available on CVRF (body mass index [BMI], systolic blood pressure, diastolic blood pressure [DBP], and cholesterol and fasting glucose test results) were included. Eighty‐one subjects also had plasma cortisol, C‐reactive protein, and superoxide dismutase 1 measurements. Stepwise regression models were used to assess the relation between the CVRF and the composite PiB‐PET score.ResultsThe first model included the following as baseline variables: age, clinical diagnosis, number of apolipoprotein ε4 alleles, BMI (P = .023), and DBP (P = .012). BMI showed an inverse relation with PiB‐PET score, and DBP had a positive relation with PiB‐PET score. In the second adjusted model, cortisol plasma levels were also associated with PiB‐PET score (P = .004). Systolic blood pressure, cholesterol, or impaired fasting glucose were not found to be associated with PiB‐PET values.ConclusionIn this cross‐sectional study, we found an association between Aβ brain burden measured in vivo and DBP and cortisol, indicating a possible link between these CVRF and Aβ burden measured by PiB‐PET. These findings highlight the utility of biomarkers to explore potential pathways linking diverse Alzheimer's disease risk factors.