X-linked adrenoleukodystrophy (ALD) is an inherited progressive neurometabolic disease caused by mutations in the ABCD1 gene and the accumulation of very long-chain fatty acids in plasma and tissues. Patients present with heterogeneous clinical manifestations which can include adrenal insufficiency, myelopathy, and/or cerebral demyelination. In the absence of a genotype-phenotype correlation, the clinical outcome of an individual cannot be predicted and currently there are no molecular markers available to quantify disease severity. Therefore, there is an unmet clinical need for sensitive biomarkers to monitor and/or predict disease progression and evaluate therapy efficacy. The increasing amount of biological sample repositories (‘biobanking’) as well as the introduction of newborn screening creates a unique opportunity for identification and evaluation of new or existing biomarkers. Here we summarize and review the many studies that have been performed to identify and improve knowledge surrounding candidate molecular biomarkers for ALD. We also highlight several shortcomings of ALD biomarker studies, which often include a limited sample size, no collection of longitudinal data, and no validation of findings in an external cohort. Nonetheless, these studies have generated a list of interesting biomarker candidates and this review aspires to direct future biomarker research.

BackgroundBlood‐based biomarkers can provide a non‐invasive and accessible way to identify neurodegenerative diseases before the clinical onset of dementia. Our study aimed to examine whether levels of phosphorylated‐tau‐181 (pTau181), amyloid beta1‐42/1‐40 (Aβ42/40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) are associated with risk of developing dementia in a memory clinic population of individuals with either subjective cognitive decline (SCD) or mild cognitive impairment (MCI).MethodFrom the Amsterdam Dementia Cohort we included 311 individuals with SCD (age 61±9 years, n=128 (41%) female, MMSE 29±1) and 252 with MCI (age 65±7 years, n=89 (35%) female, MMSE 27±2), who had annual follow‐up visits for re‐evaluation of diagnosis (average follow‐up duration: 2.7±1.7 years.) Baseline plasma biomarkers were measured using Simoa and the associations of the Z‐transformed biomarker concentrations with incident dementia were evaluated using Cox regression models adjusted for age, sex, baseline diagnosis and the interaction between baseline diagnosis (SCD/MCI) and the biomarker concentration. The markers were first evaluated individually and then simultaneously in a combined model. We stratified results for baseline diagnosis when the biomarker*diagnosis interaction was significant.ResultDuring follow‐up, 94 individuals developed dementia (14 with SCD, 80 with MCI at baseline, 86 Alzheimer’s Disease, 8 other forms of dementia; average time to progression: 2.8±1.8 years). We found an interaction between baseline diagnosis and NfL for incident dementia (p=0.03). No other interactions were found. In the total set, both high baseline pTau181 (hazard ratio (HR)=3.4 (95%CI: 1.3–9.0); figure 1A), and high baseline GFAP (HR=5.5 (95%CI: 1.6–18.6); figure 1B) were associated with increased risk of dementia, but the association with Aβ42/40 was not significant (HR=0.4 (95%CI: 0.2–1.1)). NfL had no significant association with increased dementia incident risk in both SCD subset (HR=1.8, (95%CI: 0.9‐3.6)) and the MCI subset (HR= 1.3, (95%CI: 1.0–1.6)). When we simultaneously entered all biomarkers, pTau181 and GFAP remained significantly associated with incident dementia (table 1.)ConclusionOur results suggest that plasma GFAP and pTau181 have prognostic value to predict dementia in individuals presenting at a memory clinic.

BackgroundGlial fibrillary acidic protein (GFAP) is a novel Alzheimer’s Disease (AD) biomarker that associates with amyloid pathology and pathology‐related changes can be detected in different biofluids. We studied how the performance of GFAP to distinguish between controls, AD and dementia with Lewy bodies (DLB), depends on the studied biofluid (cerebrospinal fluid (CSF), serum or plasma) and the confounding effects of age or sex.MethodFrom the Amsterdam Dementia Cohort and a local repository of healthy controls we included 372 cognitively normal individuals (CN), 255 patients with AD and 120 patients with DLB (Table 1) and GFAP levels were measured in one (n=322), two (n=416) or three (n=9) biofluids. GFAP was measured using Simoa in CSF (n=473), plasma (n=257) and serum (n=451) samples. For individuals with DLB, GFAP was measured in CSF and serum only. Effects of clinical diagnosis, age and sex on GFAP levels in each body fluid were estimated with linear models. Estimated differences between diagnostic groups were corrected for age and sex, age effects were corrected for sex and diagnostic group, and sex effects were corrected for age and diagnostic group.ResultGFAP levels were increased in AD relative to controls in all biofluids (fold change (FC): 1.6(CSF), 1.9(plasma) and 1.4(serum), p‐values<0.001) and increased in AD relative to DLB (FC: 1.7(CSF) and 1.3(serum), p‐values<0.001, Figure 1). No difference was found between DLB and controls. CSF GFAP levels increased with age in all clinical groups (range of standard deviation protein level increase per year (SD/year): 0.020‐0.024), while plasma GFAP levels increased with age only in CN (SD/year: 0.032). Serum GFAP levels increased with age in CN and DLB (SD/year: 0.058(CN) and 0.074(DLB), Figure 2). CSF GFAP showed sex effects in AD only (FC in males compared to females: 1.1), whereas serum GFAP showed sex effects in all clinical groups (FC in males: 0.83(AD), 0.85(NC) and 0.72(DLB)), and plasma GFAP showed no sex effects (Figure 3A‐C).ConclusionDifferences in GFAP levels between clinical diagnoses showed the same trend for all three matrices. With older age, differences in GFAP levels between controls and AD become harder to detect.