Multiple Kernel Learning Captures a Systems-Level Functional Connectivity Biomarker Signature in Amyotrophic Lateral Sclerosis

<div><p>There is significant clinical and prognostic heterogeneity in the neurodegenerative disorder amyotrophic lateral sclerosis (ALS), despite a common immunohistological signature. Consistent extra-motor as well as motor cerebral, spinal anterior horn and distal neuromuscular junction pathology supports the notion of ALS a system failure. Establishing a disease biomarker is a priority but a simplistic, coordinate-based approach to brain dysfunction using MRI is not tenable. Resting-state functional MRI reflects the organization of brain networks at the systems-level, and so changes in of motor functional connectivity were explored to determine their potential as the substrate for a biomarker signature. Intra- as well as inter-motor functional networks in the 0.03–0.06 Hz frequency band were derived from 40 patients and 30 healthy controls of similar age, and used as features for pattern detection, employing multiple kernel learning. This approach enabled an accurate classification of a group of patients that included a range of clinical sub-types. An average of 13 regions-of-interest were needed to reach peak discrimination. Subsequent analysis revealed that the alterations in motor functional connectivity were widespread, including regions not obviously clinically affected such as the cerebellum and basal ganglia. Complex network analysis showed that functional networks in ALS differ markedly in their topology, reflecting the underlying altered functional connectivity pattern seen in patients: 1) reduced connectivity of both the cortical and sub-cortical motor areas with non motor areas 2)reduced subcortical-cortical motor connectivity and 3) increased connectivity observed within sub-cortical motor networks. This type of analysis has potential to non-invasively define a biomarker signature at the systems-level. As the understanding of neurodegenerative disorders moves towards studying pre-symptomatic changes, there is potential for this type of approach to generate biomarkers for the testing of neuroprotective strategies.</p></div

Altered topology of functional connectivity in the motor cortices in the 0.03–0.06 Hz frequency band.

<p>Right motor cortex and left supplementary motor cortex exhibited reduced degree i.e. extent of functional connectivity to other brain areas. Motor cortex and SMA exhibited increased path length bilaterally, indicating a reduced capacity for functional integration. *denotes <i>p</i><0.05 corrected for ROI number (4) using an FDR approach.</p

A graphical representation of classification results.

<p>The features and ROIs implicated by the classifier were embedded into 2D using principal component analysis.</p

Aberrant functional connectivity in ALS.

<p><i>Top left</i>: Group differences in gray matter functional connectivity to the right motor cortex (patients>control). Patients exhibited significant (<i>p</i><0.01 random field corrected <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085190#pone.0085190-Cao1" target="_blank">[61]</a>) clusters of reduced connectivity in the 0.03–0.06 Hz frequency band mostly in the cerebellum, cuneus, rectus and fusiform gyri. <i>Top right</i>: Group differences in gray matter functional connectivity to the left Pallidum (patients>control). Patients exhibited significant (<i>p</i><0.01 random field corrected) clusters of increased connectivity in the 0.03–0.06 Hz frequency band mainly in the cerebellum and rectus and reduced connectivity to cingulate and frontal areas as well as right SMA. <i>Bottom:</i> Group differences in gray matter functional connectivity to the left cerebellum (area 4/5 according to AAL classification - patients>control). Patients exhibited significant (<i>p</i><0.01 random field corrected) clusters of decreased functional connectivity in the 0.03–0.06 Hz frequency band in the motor and somatosensory cortices together with clusters of increased connectivity mostly in the basal ganglia and cerebellum. Image was thresholded at <i>p</i> = 0.001 and cluster extent of 5 voxels.</p

Complex network analysis.

<p>ALS results in global changes in the topology of inter-area functional connectivity. Inter area functional connectivity in the 0.03–0.06 Hz band exhibited increased assortativity i.e. correlation in degree between connected nodes in ALS patients. This reflects the existence of hyper-connected sub-cortical motor networks. We present the differences in the neighborhood of the chosen threshold (o.35). * denotes <i>p</i><0.05 corrected using an FDR approach.</p

The longitudinal cerebrospinal fluid metabolomic profile of amyotrophic lateral sclerosis

<p>Neurochemical biomarkers are urgently sought in ALS. Metabolomic analysis of cerebrospinal fluid (CSF) using proton nuclear magnetic resonance (¹H-NMR) spectroscopy is a highly sensitive method capable of revealing nervous system cellular pathology. The ¹H-NMR CSF metabolomic signature of ALS was sought in a longitudinal cohort. Six-monthly serial collection was performed in ALS patients across a range of clinical sub-types (<i>n = </i>41) for up to two years, and in healthy controls at a single time-point (<i>n = </i>14). A multivariate statistical approach, partial least squares discriminant analysis, was used to determine differences between the NMR spectra from patients and controls. Significantly predictive models were found using those patients with at least one year's interval between recruitment and the second sample. Glucose, lactate, citric acid and, unexpectedly, ethanol were the discriminating metabolites elevated in ALS. It is concluded that ¹H-NMR captured the CSF metabolomic signature associated with derangements in cellular energy utilization connected with ALS, and was most prominent in comparisons using patients with longer disease duration. The specific metabolites identified support the concept of a hypercatabolic state, possibly involving mitochondrial dysfunction specifically. Endogenous ethanol in the CSF may be an unrecognized novel marker of neuronal tissue injury in ALS.</p

Regression analysis of VBI-processed T1 intensities of all ALS patients and their ALSFRS-R.

<p>Clusters of significant correlation between VBI intensity and ALSFRS-R scores are given in coronal slices (a, level at b). Projection on VBI group mean generic brain, CST highlighted according to JHU DTI atlas (yellow). Mean intensity inside ROIs in the PLIC (f, 5 mm sphere), paraventricular (e, 10 mm sphere) and subcentral white matter (d, 10 mm sphere) reveals overall decrease in intensity (mean VBI intensity versus ALSFRS-R; g, right; h, left). This illustrates a disability-related MRI intensity change in ‘core’ regions of ALS-related white matter disturbances. Inference was done using Threshold Free Cluster Enhancement (10000 permutations). Color spectrum giving p-value indication (c).</p

Intensity response in key CST areas and control regions.

<p>Mean intensity inside ROIs along the CST and in ALS independent white matter regions are shown. The absolute difference of the mean in patients versus controls is referenced to the total white matter intensity spread to allow comparability to other study settings. Significances are given as * (p<0.05), ** (p<0.01), ***(P<0.001) or as not significant (n.s.). The highest response was found in the left PLIC (8.7% higher intensity in patients than in controls). The non ALS disease related white matter regions did not significantly differ between patients and controls.</p

Clinical characteristics of participants.

<p>Clinical characteristics of participants.</p

Group comparison of bulbar and limb phenotype patient subgroups versus healthy controls.

<p>Wholebrain group-mean of VBI images projected on generic brain (c) and Maximum Intensity Projection (MIP) of significantly different regions (d, e, f). The patterns of MRI intensity change in bulbar (a) and limb (b) subgroups significantly differ despite no significant differences in age, sex or ALSFRS-R score between groups. Coronal (d), sagittal (e) and axial (f) MIPs illustrate apparently more widespread involvement of cerebral white matter in bulbar-onset ALS. Inference was done using Threshold Free Cluster Enhancement (10000 permutations) und Family-wise error rate correction for multiple comparisons. Color spectrum giving p-value indication (g).</p