Cerebrospinal fluid proteomic profiling in nusinersen-treated patients with spinal muscular atrophy.
Tobias KesslerPauline LatzerDominic SchmidUwe WarnkenAfshin SaffariAndreas ZieglerJennifer KollmerMarkus MöhlenbruchChristian UlfertChristian HerwehBrigitte WildemannWolfgang WickMarkus WeilerPublished in: Journal of neurochemistry (2020)
Promising results from recent clinical trials on the approved antisense oligonucleotide nusinersen in pediatric patients with 5q-linked spinal muscular atrophy (SMA) still have to be confirmed in adult patients but are hindered by a lack of sensitive biomarkers that indicate an early therapeutic response. Changes in the overall neurochemical composition of cerebrospinal fluid (CSF) under therapy may yield additive diagnostic and predictive information. With this prospective proof-of-concept and feasibility study, we evaluated non-targeted CSF proteomic profiles by mass spectrometry along with basic CSF parameters of 10 adult patients with SMA types 2 or 3 before and after 10 months of nusinersen therapy, in comparison with 10 age- and gender-matched controls. These data were analyzed by bioinformatics and correlated with clinical outcomes assessed by the Hammersmith Functional Rating Scale Expanded (HFMSE). CSF proteomic profiles of SMA patients differed from controls. Two groups of SMA patients were identified based on unsupervised clustering. These groups differed in age and expression of proteins related to neurodegeneration and neuroregeneration. Intraindividual CSF differences in response to nusinersen treatment varied between patients who clinically improved and those who did not. Data are available via ProteomeXchange with identifier PXD016757. Comparative CSF proteomic analysis in adult SMA patients before and after treatment with nusinersen-identified subgroups and treatment-related changes and may therefore be suitable for diagnostic and predictive analyses.
Keyphrases
- cerebrospinal fluid
- end stage renal disease
- newly diagnosed
- ejection fraction
- mass spectrometry
- clinical trial
- chronic kidney disease
- prognostic factors
- healthcare
- electronic health record
- machine learning
- mental health
- peritoneal dialysis
- mesenchymal stem cells
- social media
- young adults
- binding protein
- long non coding rna
- deep learning
- combination therapy
- label free
- smoking cessation
- health information
- high performance liquid chromatography
- patient reported
- ms ms
- replacement therapy
- rna seq