Proteomics and mathematical modeling of longitudinal CSF differentiates fast versus slow ALS progression

Dysregulated Cerebrospinal Fluid Proteome of Spinocerebellar Ataxia Type 2 and its Clinical Implications

BACKGROUND

Abnormalities in ataxin-2 associated with spinocerebellar ataxia type 2 (SCA2) may lead to widespread disruptions in the proteome. This study was performed to identify dysregulated proteome in SCA2 and to explore its clinical-radiological correlations.

METHODS

Cerebrospinal fluid (CSF) samples from 21 genetically confirmed SCA2 were subjected to shotgun proteome analysis using mass spectrometry (MS) and tandem mass tag (TMT)-based multiplexing. Proteins with at least 1.5-fold change in abundance were identified. Their relative abundance was measured using parallel reaction monitoring (PRM) and correlated against disease-related factors.

RESULTS

Eleven proteins were significantly upregulated in SCA2. They belonged to the family of cell adhesion molecules and granins. Their fold changes showed significant clinical, genetic, and radiological correlations.

CONCLUSIONS

Significant dysregulation of CSF proteome is seen in SCA2. The dysregulated protein may have potential use in clinical evaluation of patients with SCA2. © 2024 International Parkinson and Movement Disorder Society.

State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia

Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. From the transcriptome, we constructed a CML state-space and a three-well leukemogenic potential landscape. The potential's stable critical points defined observable disease states. Early states were characterized by anti-CML genes opposing leukemia; late states were characterized by pro-CML genes. Genes with expression patterns shaped similarly to the potential landscape were identified as drivers of disease transition. Re-introduction of tetracycline to silence the BCR::ABL gene returned diseased mice transcriptomes to a near healthy state, without reaching it, suggesting parts of the transition are irreversible. TKI only reverted the transcriptome to an intermediate disease state, without approaching a state of health; disease relapse occurred soon after treatment. Using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response, supporting this as a potentially valuable approach to time clinical intervention, before phenotypic changes become detectable.

Unraveling the Heterogeneity of ALS-A Call to Redefine Patient Stratification for Better Outcomes in Clinical Trials

Despite tremendous efforts in basic research and a growing number of clinical trials aiming to find effective treatments, amyotrophic lateral sclerosis (ALS) remains an incurable disease. One possible reason for the lack of effective causative treatment options is that ALS may not be a single disease entity but rather may represent a clinical syndrome, with diverse genetic and molecular causes, histopathological alterations, and subsequent clinical presentations contributing to its complexity and variability among individuals. Defining a way to subcluster ALS patients is becoming a central endeavor in the field. Identifying specific clusters and applying them in clinical trials could enable the development of more effective treatments. This review aims to summarize the available data on heterogeneity in ALS with regard to various aspects, e.g., clinical, genetic, and molecular.