Biomarkers in Motor Neuron Disease: A State of the Art Review

Abstract

Motor neuron disease can be viewed as an umbrella term describing a heterogeneous group of conditions, all of which are relentlessly progressive and ultimately fatal. The average life expectancy is 2 years, but with a broad range of months to decades. Biomarker research deepens disease understanding through exploration of pathophysiological mechanisms which, in turn, highlights targets for novel therapies. It also allows differentiation of the disease population into sub-groups, which serves two general purposes: (a) provides clinicians with information to better guide their patients in terms of disease progression, and (b) guides clinical trial design so that an intervention may be shown to be effective if population variation is controlled for. Biomarkers also have the potential to provide monitoring during clinical trials to ensure target engagement. This review highlights biomarkers that have emerged from the fields of systemic measurements including biochemistry (blood, cerebrospinal fluid, and urine analysis); imaging and electrophysiology, and gives examples of how a combinatorial approach may yield the best results. We emphasize the importance of systematic sample collection and analysis, and the need to correlate biomarker findings with detailed phenotype and genotype data.

Keywords: ALS (Amyotrophic lateral sclerosis); biofluid; biomarker; cerebrospinal fluid (CSF); electrophysiology; motor neuron disease (MND); neuroimaging.

Figure 1

Summary of biomarker categorization.

Figure 2

Motor cortical atrophy in a patient with ALS, more pronounced on left side (which correlated with the pattern of weakness clinically). Sequence: 3T, T1w IR, TR 8.4 ms, TE 3.9 ms, TI 1000, FOV 240 mm, Acq voxel 1 × 1 × 1 mm Recon matrix 0.94 × 0.94 × 1 mm. Segmentation algorithm according to Chuang et al. (183).

Figure 3

GSH spectrum (B) from medial parietal cortex (A) (MEGA-PRESS sequence, HERMES spectral editing). (B) Green line showing spectral edited GSH peak.

Figure 4

T2-weighted whole body image acquired in a patient: 3T, single shot TSE, TR 1107 ms, TE 80 ms, FOV 37 × 55 cm, voxel size 1.25 × 1.5 × 5 mm recon 0.78 × 0.78 × 5—used with permission from Jenkins et al. (288).

Figure 5

(A) EIM: alternating current is applied to the muscle and the ensuing voltage measured. The phase angle is a metric of tissue impedance and describes, in degrees, the angle of asynchrony between the two sinusoidal waveforms. (B) Multiple compound muscle action potentials recorded during the incremental motor unit number estimation technique. Each change in amplitude is thought to represent the addition of a new motor unit. (C) Surface interference patterns obtained during the motor unit number index technique. After recording a maximal compound muscle action potential the subject performs isometric contraction of the muscle of interest with increasing force. Parameters from these recordings are then used together with data from the CMAP to compute the index.