Demyelination in hereditary sensory neuropathy type-1C

SPTLC2 variants are associated with early-onset ALS and FTD due to aberrant sphingolipid synthesis

OBJECTIVE

Amyotrophic lateral sclerosis (ALS) is a devastating, incurable neurodegenerative disease. A subset of ALS patients manifests with early-onset and complex clinical phenotypes. We aimed to elucidate the genetic basis of these cases to enhance our understanding of disease etiology and facilitate the development of targeted therapies.

METHODS

Our research commenced with an in-depth genetic and biochemical investigation of two specific families, each with a member diagnosed with early-onset ALS (onset age of <40 years). This involved whole-exome sequencing, trio analysis, protein structure analysis, and sphingolipid measurements. Subsequently, we expanded our analysis to 62 probands with early-onset ALS and further included 440 patients with adult-onset ALS and 1163 healthy controls to assess the prevalence of identified genetic variants.

RESULTS

We identified heterozygous variants in the serine palmitoyltransferase long chain base subunit 2 (SPTLC2) gene in patients with early-onset ALS. These variants, located in a region closely adjacent to ORMDL3, bear similarities to SPTLC1 variants previously implicated in early-onset ALS. Patients with ALS carrying these SPTLC2 variants displayed elevated plasma ceramide levels, indicative of increased serine palmitoyltransferase (SPT) activity leading to sphingolipid overproduction.

INTERPRETATION

Our study revealed novel SPTLC2 variants in patients with early-onset ALS exhibiting frontotemporal dementia. The combination of genetic evidence and the observed elevation in plasma ceramide levels establishes a crucial link between dysregulated sphingolipid metabolism and ALS pathogenesis. These findings expand our understanding of ALS's genetic diversity and highlight the distinct roles of gene defects within SPT subunits in its development.

Multiparametric Quantitative MRI of Peripheral Nerves in the Leg: A Reliability Study

BACKGROUND

Patients with polyneuropathies typically have demyelination and/or axonal degeneration in peripheral nerves. Currently, there is a lack of imaging biomarkers to track the changes in these pathologies.

PURPOSE

To develop and evaluate the reliability of a multiparametric quantitative magnetic resonance imaging (qMRI) method of peripheral nerves in the leg.

STUDY TYPE

Prospective.

SUBJECTS

Seventeen healthy volunteers (36.2 ± 13.8 years old, 9 males) with 10 of them scanned twice for test-retest.

FIELD STRENGTH/SEQUENCE

3 T, three-dimensional gradient echo and diffusion tensor imaging.

ASSESSMENT

A qMRI protocol and processing pipeline was established for quantifying the following nerve parameters that are sensitive to myelin and axonal pathologies: magnetization transfer (MT) ratio (MTR), MT saturation index (MTsat), T2 *, T1 , proton density (PD), fractional anisotropy (FA), and mean/axial/radial diffusivities (MD, AD, and RD). The qMRI protocol also measures the volume of nerve fascicles (fVOL) and the fat fraction (FF) of muscles.

STATISTICAL TESTS

The intersession reproducibility and inter-rater reliability of each qMRI parameter were assessed by Bland-Altman analysis and intraclass correlation coefficient (ICC). Pairwise Pearson correlation analyses were performed to investigate the intrinsic association between qMRI parameters. Distal-to-proximal variations were evaluated by paired t-tests with Bonferroni-Holm multiple comparison corrections. P < 0.05 was considered statistically significant.

RESULTS

The MTR, MTsat, T2 *, T1 , PD, FA, AD, and fVOL of the sciatic and tibial nerves, and the FF of leg muscles, had an overall good-to-excellent test-retest agreement (ICC varying from 0.78 to 0.99). All the qMRI parameters had good-to-excellent inter-rater reliability (ICC > 0.80). The data demonstrated a pattern of distal-to-proximal changes of an increased nerve MTsat and FA, and a decreased nerve T1 , PD, MD, and RD, as well as a significantly increased muscle FF.

DATA CONCLUSION

The proposed multiparametric qMRI method of the peripheral nerves is highly reproducible and provided healthy control data which will be used in developing monitoring biomarkers in patients with polyneuropathies.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 2.

A novel HSPB1S139F mouse model of Charcot-Marie-Tooth Disease

Charcot-Marie-Tooth Disease (CMT) is a commonly inherited peripheral polyneuropathy. Clinical manifestations for this disease include symmetrical distal polyneuropathy, altered deep tendon reflexes, distal sensory loss, foot deformities, and gait abnormalities. Genetic mutations in heat shock proteins have been linked to CMT2. Specifically, mutations in the heat shock protein B1 (HSPB1) gene encoding for heat shock protein 27 (Hsp27) have been linked to CMT2F and distal hereditary motor and sensory neuropathy type 2B (dHMSN2B) subtype. The goal of the study was to examine the role of an endogenous mutation in HSPB1 in vivo and to define the effects of this mutation on motor function and pathology in a novel animal model. As sphingolipids have been implicated in hereditary and sensory neuropathies, we examined sphingolipid metabolism in central and peripheral nervous tissues in 3-month-old HspS139F mice. Though sphingolipid levels were not altered in sciatic nerves from HspS139F mice, ceramides and deoxyceramides, as well as sphingomyelins (SMs) were elevated in brain tissues from HspS139F mice. Histology was utilized to further characterize HspS139F mice. HspS139F mice exhibited no alterations to the expression and phosphorylation of neurofilaments, or in the expression of acetylated α-tubulin in the brain or sciatic nerve. Interestingly, HspS139F mice demonstrated cerebellar demyelination. Locomotor function, grip strength and gait were examined to define the role of HspS139F in the clinical phenotypes associated with CMT2F. Gait analysis revealed no differences between HspWT and HspS139F mice. However, both coordination and grip strength were decreased in 3-month-old HspS139F mice. Together these data suggest that the endogenous S139F mutation in HSPB1 may serve as a mouse model for hereditary and sensory neuropathies such as CMT2F.

Specific Deoxyceramide Species Correlate with Expression of Macular Telangiectasia Type 2 (MacTel2) in a SPTLC2 Carrier HSAN1 Family

Hereditary sensory and autonomic neuropathy type 1 (HSAN1/HSN1) is a peripheral neuropathy most commonly associated with pathogenic variants in the serine palmitoyltransferase complex (SPTLC1, SPTLC2) genes, which are responsible for sphingolipid biosynthesis. Recent reports have shown that some HSAN1 patients also develop macular telangiectasia type 2 (MacTel2), a retinal neurodegeneration with an enigmatic pathogenesis and complex heritability. Here, we report a novel association of a SPTLC2 c.529A>G p.(Asn177Asp) variant with MacTel2 in a single member of a family that otherwise has multiple members afflicted with HSAN1. We provide correlative data to suggest that the variable penetrance of the HSAN1/MacTel2-overlap phenotype in the proband may be explained by levels of certain deoxyceramide species, which are aberrant intermediates of sphingolipid metabolism. We provide detailed retinal imaging of the proband and his HSAN1+/MacTel2- brothers and suggest mechanisms by which deoxyceramide levels may induce retinal degeneration. This is the first report of HSAN1 vs. HSAN1/MacTel2 overlap patients to comprehensively profile sphingolipid intermediates. The biochemical data here may help shed light on the pathoetiology and molecular mechanisms of MacTel2.

Automation of Quantifying Axonal Loss in Patients with Peripheral Neuropathies through Deep Learning Derived Muscle Fat Fraction

BACKGROUND

Axonal loss denervates muscle, leading to an increase of fat accumulation in the muscle. Therefore, fat fraction (FF) in whole limb muscle using MRI has emerged as a monitoring biomarker for axonal loss in patients with peripheral neuropathies. In this study, we are testing whether deep learning-based model can automate quantification of the FF in individual muscles. While individual muscle is smaller with irregular shape, manually segmented muscle MRI images have been accumulated in this lab; and make the deep learning feasible.

PURPOSE

To automate segmentation on muscle MRI images through deep learning for quantifying individual muscle FF in patients with peripheral neuropathies.

STUDY TYPE

Retrospective.

SUBJECTS

24 patients and 19 healthy controls.

FIELD STRENGTH/SEQUENCES

3T; Interleaved 3D GRE.

ASSESSMENT

A 3D U-Net model was implemented in segmenting muscle MRI images. This was enabled by leveraging a large set of manually segmented muscle MRI images. B1+ and B1- maps were used to correct image inhomogeneity. Accuracy of the automation was evaluated using Pixel Accuracy (PA), Dice Coefficient (DC) in binary masks; and Bland-Altman and Pearson correlation by comparing FF values between manual and automated methods.

STATISTICAL TESTS

PA and DC were reported with their median value and standard deviation. Two methods were compared using the ± 95% confidence intervals (CI) of Bland-Altman analysis and the Pearson's coefficient (r2 ).

RESULTS

DC values were from 0.83 ± 0.17 to 0.98 ± 0.02 in thigh and from 0.63 ± 0.18 to 0.96 ± 0.02 in calf muscles. For FF values, the overall ± 95% CI and r2 were [0.49, -0.56] and 0.989 in thigh and [0.84, -0.71] and 0.971 in the calf.

DATA CONCLUSION

Automated results well agreed with the manual results in quantifying FF for individual muscles. This method mitigates the formidable time consumption and intense labor in manual segmentations; and enables the use of individual muscle FF as outcome measures in upcoming longitudinal studies.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 1.