Discovering Novel Biomarkers for Rare Neurological Diseases

Though the Orphanet database currently includes entries for 6,053 rare diseases, some researchers estimate that there are up to 8,000 rare diseases worldwide. Too often, rare diseases go unrecognized, with patients being underdiagnosed and/or misdiagnosed for years. Developing biomarkers, that can effectively identify specific rare diseases is crucial for providing patients with accurate diagnoses, prognoses, and treatments. Effective biomarkers can also improve mechanisms for monitoring disease progression or treatment efficacy, as well as fuel the development of targeted, molecular therapies. However, due to the rarity of these diseases within a given population, researchers face the formidable challenge of collecting enough clinical data to conduct their research. Despite these difficulties, and with the help of multicenter studies, researchers continue to study rare disease biomarkers. For rare neurological diseases, researchers continue to discover and characterize protein-, DNA-, and RNA-based biomarkers.

Serum-based biomarkers to better understand subtypes of multiple sclerosis

Primary progressive multiple sclerosis (PPMS) is a subtype of the neurodegenerative disease multiple sclerosis (MS). PPMS affects 10–15 percent of older MS patients and is characterized by a slow onset of progressive spastic paraplegia primarily in the legs, resulting in the irreversible onset of muscle weakness and stiffness, and difficulty in walking. PPMS is currently diagnosed via observation and tracking symptom progression, MR imaging of spinal or cerebral T2-hyperintense lesions, or sampling cerebrospinal fluid (CSF) for oligoclonal banding (OCB)—a sign of inflammation of the central nervous system. 

However, these methods struggle to differentiate subtypes of MS, as well as to differentiate MS from other diseases with slowly progressive spastic paraplegia, such as hereditary spastic paraplegia (HSP), which is not associated with T2-hyperintense lesions and is primarily detected using HSP genetic analyses that can have a 50 percent detection failure rate. 

To address these diagnostic difficulties, Kessler et al. took a less invasive approach to identifying biomarkers using serum. They collected serum from study participants with PPMS and participants with the most common form of HSP, spastic paraplegia 4 (SPG4), and compared them to a control group. They quantified the protein levels of two prominent MS-related biomarkers: serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP). 

According to their statistical analyses, the researchers found that, in fact, sNfL and sGFAP were not appropriate biomarkers for distinguishing between PPMS and SPG4. However, because the participants in both groups ranged in age from approximately 48 to 61 years old, the researchers did gain insight into the temporal dynamics of sNfL and sGFAP: their data suggest that the elevated levels of sNfL and sGFAP observed in PPMS vs SPG4 were more apparent in the early stages of disease and decreased with increasing age. Despite their small sample size of 25 patients with PPMS, 25 with SPG4, and 60 controls, the researchers conclude that the protein markers sNfL and sGFAP warrant further research to better understand neurological symptoms in PPMS patients.

Uncovering rare mutations associated with hereditary sensory neuropathy and congenital insensitivity to pain

Hereditary sensory neuropathies (HSN) are a group of heterogenous disorders due to various genetic causes, including mutations. HSN patients experience progressive axon degeneration, leading to body-wide loss of sensitivity, ulcerations in the hands and feet, and neuropathic pain. Because treatments for HSN are limited and there are no available gene therapies to address the underlying genetic causes, early and accurate diagnosis is essential to better patient care. 

Researchers in São Paulo recently made a promising contribution to HSN research by performing whole-genome sequencing of 23 unrelated HSN-presenting Brazilian families using BGISEQ-500. Cintra et al. used the GENESIS platform for variant filtering and classification, discovering six pathogenic biomarkers in the ATL3, SPTCL2, and SC9A genes. They found most of the mutations within the SC9A gene that encodes the α-subunit of the voltage-gated sodium channel Nav1.7, which is abundant in nociceptive neurons. 

The researchers concluded that the newly discovered stop variant, p.(Trp702Ter), and splice variant, c.3319–1G>A, were likely pathogenic. Although the pathogenic variants identified in ATL3 and SPTCL2 had been previously characterized, the new data demonstrates the power of whole-genome sequencing for discovering and validating HSN biomarkers.

microRNAs as potential biomarkers for Charcot-Marie-Tooth disease

Despite being rare in the general population, Charcot-Marie-Tooth disease (CMT) is the most common heritable neuromuscular disease. The majority of CMT patients have its most prevalent form, Charcot-Marie-Tooth disease type 1A (CMT1A), which is caused by a duplication in the PMP22 gene that encodes a transmembrane protein component of myelin. CMT1A affects the peripheral nerves and is characterized by increased muscular atrophy and weakness, defects in myelin-forming Schwann cells, and accumulation of intramuscular fat within the calf muscles.

In their study, Wang et al. used next-generation sequencing, or NGS, to determine whether they could differentiate and profile CMT1A-associated microRNA biomarkers from muscle and/or Schwann cells. The researchers gathered plasma samples from 10 CMT1A patients and 10 healthy controls with no history of CMT symptoms, then submitted them to Qiagen for microRNA expression profiling via Illumina sequencing and bioinformatics analysis. 

The initial broad screen found that 35 microRNAs were elevated in the CMT1A samples, leading to high-throughput validation of 21 microRNAs using the Biomark HD qRT-PCR platform conducted on a larger pool of samples. Correlational and gene ontology assessments of the resulting data identified several CMT1A-specific microRNA biomarker candidates for both muscle and Schwann cells. These results provided class 3 evidence suitable for inclusion in future clinical trials.

Advancing biomarkers of neurological disease

Driven by a focus on minimally invasive techniques and next-generation technologies, innovative approaches to studying biomarkers in neurological disease are becoming more commonplace. With the continued discovery and validation of novel proteins and nucleic acid biomarkers, these molecular tools will help improve the screening, diagnosis, and monitoring of rare neurological diseases. And though rare disease research has often been limited by low participant or sample availability, these next-generation technologies and molecular tools have become crucial for producing reliable and accurate results.