Niemann-Pick Type C (NPC) is a genetic neurodegenerative lysosomal storage disorder commonly associated with psychiatric symptoms and delays to accurate diagnosis and treatment. This study investigated biomarker levels and diagnostic utility of plasma neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in NPC compared to healthy controls.

Patients with NPC were recruited from a specialist assessment and management service. Data was available from an age and sex-matched healthy control group. NfL and GFAP were measured on Quanterix Simoa HD-X analysers and groups compared using generalised linear models. NfL levels were compared to, and percentiles derived from, recently developed NfL reference ranges.

Plasma NfL was significantly elevated in 11 patients with NPC compared to 25 controls (mean 17.1 vs. 7.4 pg/ml, p < 0.001), and reference ranges (all >98th percentile). NfL distinguished NPC from controls with high accuracy. GFAP levels were not elevated in NPC (66.6 vs. 75.1 pg/ml).

The study adds important evidence on the potential diagnostic utility of plasma NfL in NPC, extends the literature of NfL as a diagnostic tool to differentiate neurodegenerative from primary psychiatric disorders, and adds support to the pathology in NPC primarily involving neuronal, particularly axonal, degeneration.

Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.

This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.

The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).

Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.

Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).

This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.

Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.

The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.

Novel blood-based biomarkers for Alzheimer's disease (AD) could transform AD diagnosis in the community; however, their interpretation in individuals with medical comorbidities is not well understood. Specifically, kidney function has been shown to influence plasma levels of various brain proteins. This study sought to evaluate the effect of one common marker of kidney function (estimated glomerular filtration rate (eGFR)) on the association between various blood-based biomarkers of AD/neurodegeneration (glial fibrillary acidic protein (GFAP), neurofilament light (NfL), amyloid-b42 (Ab42), total tau) and established CSF biomarkers of AD (Ab42/40 ratio, tau, phosphorylated-tau (p-tau)), neuroimaging markers of AD (AD-signature region cortical thickness), and episodic memory performance.

Vanderbilt Memory and Aging Project participants (n=329, 73±7 years, 40% mild cognitive impairment, 41% female) completed fasting venous blood draw, fasting lumbar puncture, 3T brain MRI, and neuropsychological assessment at study entry and at 18-month, 3-year, and 5-year follow-up visits. Plasma GFAP, Ab42, total tau, and NfL were quantified on the Quanterix single molecule array platform. CSF biomarkers for Ab were quantified using Meso Scale Discovery immunoassays and tau and p-tau were quantified using INNOTEST immunoassays. AD-signature region atrophy was calculated by summing bilateral cortical thickness measurements captured on T1-weighted brain MRI from regions shown to distinguish individuals with AD from normal cognition. Episodic memory functioning was measured using a previously developed composite score. Linear mixed-effects regression models related predictors to each outcome adjusting for age, sex, education, race/ethnicity, apolipoprotein E-e4 status, and cognitive status. Models were repeated with a blood-based biomarker x eGFR x time interaction term with follow-up models stratified by chronic kidney disease (CKD) staging (stage 1/no CKD: eGFR>90 mL/min/1.73m2, stage 2: eGFR=60-89 mL/min/1.73m2; stage 3: eGFR=44-59mL/min/1.73m2 (no participants with higher than stage 3)).

Cross-sectionally, GFAP was associated with all outcomes (p-values<0.005) and NfL was associated with memory and AD-signature region cortical thickness (p-values<0.05). In predictor x eGFR interaction models, GFAP and NfL interacted with eGFR on AD-signature cortical thickness, (p-values<0.004) and Ab42 interacted with eGFR on tau, p-tau, and memory (p-values<0.03). Tau did not interact with eGFR. Stratified models across predictors showed that associations were stronger in individuals with better renal functioning and no significant associations were found in individuals with stage 3 CKD. Longitudinally, higher GFAP and NfL were associated with memory decline (p-values<0.001). In predictor x eGFR x time interaction models, GFAP and NfL interacted with eGFR on p-tau (p-values<0.04). Other models were nonsignificant. Stratified models showed that associations were significant only in individuals with no CKD/stage 1 CKD and were not significant in participants with stage 2 or 3 CKD.

In this community-based sample of older adults free of dementia, plasma biomarkers of AD/neurodegeneration were associated with AD-related clinical outcomes both cross-sectionally and longitudinally; however, these associations were modified by renal functioning with no associations in individuals with stage 3 CKD. These results highlight the value of blood-based biomarkers in individuals with healthy renal functioning and suggest caution in interpreting these biomarkers in individuals with mild to moderate CKD.

People with neuropsychiatric symptoms often experience delay in accurate diagnosis. Although cerebrospinal fluid neurofilament light (CSF NfL) shows promise in distinguishing neurodegenerative disorders (ND) from psychiatric disorders (PSY), its accuracy in a diagnostically challenging cohort longitudinally is unknown.

We collected longitudinal diagnostic information (mean = 36 months) from patients assessed at a neuropsychiatry service, categorising diagnoses as ND/mild cognitive impairment/other neurological disorders (ND/MCI/other) and PSY. We pre-specified NfL > 582 pg/mL as indicative of ND/MCI/other.

Diagnostic category changed from initial to final diagnosis for 23% (49/212) of patients. NfL predicted the final diagnostic category for 92% (22/24) of these and predicted final diagnostic category overall (ND/MCI/other vs. PSY) in 88% (187/212), compared to 77% (163/212) with clinical assessment alone.

CSF NfL improved diagnostic accuracy, with potential to have led to earlier, accurate diagnosis in a real-world setting using a pre-specified cut-off, adding weight to translation of NfL into clinical practice.