A fluid biomarker reveals loss of TDP-43 splicing repression in presymptomatic ALS-FTD.

Although loss of TAR DNA-binding protein 43 kDa (TDP-43) splicing repression is well documented in postmortem tissues of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), whether this abnormality occurs during early-stage disease remains unresolved. Cryptic exon inclusion reflects loss of function of TDP-43, and thus detection of proteins containing cryptic exon-encoded neoepitopes in cerebrospinal fluid (CSF) or blood could reveal the earliest stages of TDP-43 dysregulation in patients. Here we use a newly characterized monoclonal antibody specific to a TDP-43-dependent cryptic epitope (encoded by the cryptic exon found in HDGFL2) to show that loss of TDP-43 splicing repression occurs in ALS-FTD, including in presymptomatic C9orf72 mutation carriers.

A fluid biomarker reveals loss of TDP-43 splicing repression in pre-symptomatic ALS.

Loss of TAR DNA-binding protein 43 kDa (TDP-43) splicing repression is well-documented in postmortem tissues of amyotrophic lateral sclerosis (ALS), yet whether this abnormality occurs during early-stage disease remains unresolved. Cryptic exon inclusion reflects functional loss of TDP-43, and thus detection of cryptic exon-encoded peptides in cerebrospinal fluid (CSF) could reveal the earliest stages of TDP-43 dysregulation in patients. Here, we use a newly characterized monoclonal antibody specific to a TDP-43-dependent cryptic epitope (encoded by the cryptic exon found in ) to show that loss of TDP-43 splicing repression occurs in -associated ALS, including pre-symptomatic mutation carriers.

Cell-specific regulation of gene expression using splicing-dependent frameshifting.

Precise and reliable cell-specific gene delivery remains technically challenging. Here we report a splicing-based approach for controlling gene expression whereby separate translational reading frames are coupled to the inclusion or exclusion of mutated, frameshifting cell-specific alternative exons. Candidate exons are identified by analyzing thousands of publicly available RNA sequencing datasets and filtering by cell specificity, conservation, and local intron length.