Biomarkers.

Background: Younger-onset neurocognitive symptoms result from a heterogenous group of neurological and psychiatric disorders which present a diagnostic challenge. To identify such factors, we analysed the BeYOND (Biomarkers in Younger-Onset Neurocognitive Disorders) cohort, a study of individuals less than 65 years old presenting with neurocognitive symptoms for a clinical diagnosis and who have undergone cognitive and biomarker analyses.

Method: 65 participants were recruited during their index presentation to the Royal Melbourne Hospital Neuropsychiatry Centre, a tertiary specialist service in Melbourne, Australia. Specific diagnoses were clinically determined and categorised as either early-onset Alzheimer's disease (AD, n=18), non-AD neurodegeneration (nAD-ND, n=23) or primary psychiatric disorders (PPD, n=24). Using Simoa technology, blood levels of neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), phosphorylated-tau at threonine 181 (p-tau181), amyloid-β (Aβ), Aβ and Aβ ratio were measured. Apolipoprotein E (APOE) genotypes and polygenic risk scores (PRSs), based on genome-wide association studies for late-onset AD, were determined. Generalized linear and multinomial models, as well as information-theoretic model selection, were used to identify discriminatory factors, adjusted for age and sex.

Result: NfL, GFAP and p-tau181 levels were up to 3-fold higher in individuals with AD compared to nAD-ND and PPD (Dunn-adjusted p<0.05). Aβ-species levels were not significantly different between the groups. While the PRS was not associated with diagnostic categories (p=0.25), a higher PRS was associated with increased NfL and GFAP levels (OR=1.08, p<0.05). Multi-omic model selection identified various combinations of NfL and p-tau181 levels, APOE genotype and global cognitive function as parsimonious models that discriminated between AD and PPD with AUC≥0.975 (95% CI: 0.925-1.000). A model containing only p-tau181 significantly discriminated between AD and nAD-ND causes (AUC=0.950, 95% CI: 0.877-1.000). Multinomial regression models identified NfL, GFAP and p-tau181 as significant variables for discriminating between the three diagnostic categories (p<0.0005).

Conclusion: Discriminating between AD, nAD-ND and PPD causes of younger-onset neurocognitive symptoms is possible using a combination of cognitive profiling with protein and genetic biomarkers. These results support utilising blood biomarkers for work-up of younger-onset neurocognitive symptoms as well as highlight the need for the development of a younger-onset AD-specific PRS.