Plasma neurofilament light levels show elevation two years prior to diagnosis of amyotrophic lateral sclerosis in the UK Biobank

Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank

BACKGROUND AND OBJECTIVES

Amyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function, and a cure for this devastating disease remains elusive. This study aimed to identify pre-disposing genetic, phenotypic, and exposure-related factors for amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential.

METHODS

Utilizing data from the UK (United Kingdom) Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates.

RESULTS

Both PRSs modestly predicted ALS diagnosis but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1 year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved the prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a fourfold higher ALS risk (95% CI [2.04, 7.73]) versus those in the 40%-60% range.

DISCUSSION

By leveraging UK Biobank data, our study uncovers pre-disposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS.

Serum neurofilament light chain in distinct phenotypes of amyotrophic lateral sclerosis: A longitudinal, multicenter study

OBJECTIVE

To assess the performance of serum neurofilament light chain (sNfL) in clinical phenotypes of amyotrophic lateral sclerosis (ALS).

METHODS

In 2949 ALS patients at 16 ALS centers in Germany and Austria, clinical characteristics and sNfL were assessed. Phenotypes were differentiated for two anatomical determinants: (1) upper and/or lower motor involvement (typical, typMN; upper/lower motor neuron predominant, UMNp/LMNp; primary lateral sclerosis, PLS) and (2) region of onset and propagation of motor neuron dysfunction (bulbar, limb, flail-arm, flail-leg, thoracic onset). Phenotypes were correlated to sNfL, progression, and survival.

RESULTS

Mean sNfL was - compared to typMN (75.7 pg/mL, n = 1791) - significantly lower in LMNp (45.1 pg/mL, n = 413), UMNp (58.7 pg/mL n = 206), and PLS (37.6 pg/mL, n = 84). Also, sNfL significantly differed in the bulbar (92.7 pg/mL, n = 669), limb (64.1 pg/mL, n = 1305), flail-arm (46.4 pg/mL, n = 283), flail-leg (53.6 pg/mL, n = 141), and thoracic (74.5 pg/mL, n = 96) phenotypes. Binary logistic regression analysis showed highest contribution to sNfL elevation for faster progression (odds ratio [OR] 3.24) and for the bulbar onset phenotype (OR 1.94). In contrast, PLS (OR 0.20), LMNp (OR 0.45), and thoracic onset (OR 0.43) showed reduced contributions to sNfL. Longitudinal sNfL (median 12 months, n = 2862) showed minor monthly changes (<0.2%) across all phenotypes. Correlation of sNfL with survival was confirmed (p < 0.001).

CONCLUSIONS

This study underscored the correlation of ALS phenotypes - differentiated for motor neuron involvement and region of onset/propagation - with sNfL, progression, and survival. These phenotypes demonstrated a significant effect on sNfL and should be recognized as independent confounders of sNfL analyses in ALS trials and clinical practice.

The Miami Framework for ALS and related neurodegenerative disorders: an integrated view of phenotype and biology

Increasing appreciation of the phenotypic and biological overlap between amyotrophic lateral sclerosis (ALS) and frontotemporal dementia, alongside evolving biomarker evidence for a pre-symptomatic stage of disease and observations that this stage of disease might not always be clinically silent, is challenging traditional views of these disorders. These advances have highlighted the need to adapt ingrained notions of these clinical syndromes to include both the full phenotypic continuum - from clinically silent, to prodromal, to clinically manifest - and the expanded phenotypic spectrum that includes ALS, frontotemporal dementia and some movement disorders. The updated clinical paradigms should also align with our understanding of the biology of these disorders, reflected in measurable biomarkers. The Miami Framework, emerging from discussions at the Second International Pre-Symptomatic ALS Workshop in Miami (February 2023; a full list of attendees and their affiliations appears in the Supplementary Information) proposes a classification system built on: first, three parallel phenotypic axes - motor neuron, frontotemporal and extrapyramidal - rather than the unitary approach of combining all phenotypic elements into a single clinical entity; and second, biomarkers that reflect different aspects of the underlying pathology and biology of neurodegeneration. This framework decouples clinical syndromes from biomarker evidence of disease and builds on experiences from other neurodegenerative diseases to offer a unified approach to specifying the pleiotropic clinical manifestations of disease and describing the trajectory of emergent biomarkers.

Amyotrophic lateral sclerosis; clinical features, differential diagnosis and pathology

Amyotrophic lateral sclerosis (ALS) is a late-onset syndrome characterized by the progressive degeneration of both upper motor neurons (UMN) and lower motor neurons (LMN). ALS forms a clinical continuum with frontotemporal dementia (FTD), in which there are progressive language deficits or behavioral changes. The genetics and pathology underlying both ALS and FTD overlap as well, with cytoplasmatic misvocalization of TDP-43 as the hallmark. ALS is diagnosed by exclusion. Over the years several diagnostic criteria have been proposed, which in essence all require a history of slowly progressive motor symptoms, with UMN and LMN signs on neurological examination, clear spread of symptoms through the body, the exclusion of other disorder that cause similar symptoms and an EMG that it is compatible with LMN loss. ALS is heterogeneous disorder that may present in multitude ways, which makes the diagnosis challenging. Therefore, a systematic approach in the diagnostic process is required in line with the most common presentations. Subsequently, assessing whether there are cognitive and/or behavioral changes within the spectrum of FTD and lastly determining the cause is genetic. This chapter, an outline on how to navigate this 3 step process.

Biomarkers of Alzheimer's disease and neurodegeneration in dried blood spots-A new collection method for remote settings

BACKGROUND

We aimed to evaluate the precision of Alzheimer's disease (AD) and neurodegeneration biomarker measurements from venous dried plasma spots (DPSv enous) for the diagnosis and monitoring of neurodegenerative diseases in remote settings.

METHODS

In a discovery (n = 154) and a validation cohort (n = 115), glial fibrillary acidic protein (GFAP); neurofilament light (NfL); amyloid beta (Aβ) 40, Aβ42; and phosphorylated tau (p-tau181 and p-tau217) were measured in paired DPSvenous and ethylenediaminetetraacetic acid plasma samples with single-molecule array. In the validation cohort, a subset of participants (n = 99) had cerebrospinal fluid (CSF) biomarkers.

RESULTS

All DPSvenous and plasma analytes correlated significantly, except for Aβ42. In the validation cohort, DPSvenous GFAP, NfL, p-tau181, and p-tau217 differed between CSF Aβ-positive and -negative individuals and were associated with worsening cognition.

DISCUSSION

Our data suggest that measuring blood biomarkers related to AD pathology and neurodegeneration from DPSvenous extends the utility of blood-based biomarkers to remote settings with simplified sampling conditions, storage, and logistics.

HIGHLIGHTS

A wide array of biomarkers related to Alzheimer's disease (AD) and neurodegeneration were detectable in dried plasma spots (DPSvenous). DPSvenous biomarkers correlated with standard procedures and cognitive status. DPSvenous biomarkers had a good diagnostic accuracy discriminating amyloid status. Our findings show the potential interchangeability of DPSvenous and plasma sampling. DPSvenous may facilitate remote and temperature-independent sampling for AD biomarker measurement. Innovative tools for blood biomarker sampling may help recognizing the earliest changes of AD.