HDGF2 Human

What is HDGF2 and what are its main functional roles in human cells?

HDGF2 is a histone-binding protein expressed throughout the brain that plays crucial roles in transcriptional regulation. It functions primarily as a chromatin-associated factor that allows RNA polymerase II (RNAPII) to overcome nucleosome-induced barriers during transcription elongation . This activity is similar to that of the FACT (Facilitates Chromatin Transcription) complex, suggesting HDGF2 helps maintain chromatin in a transcription-competent state . HDGF2 contains PWWP domains that recognize specific histone modifications and HMGA-like AT hooks that interact with DNA sequences . Beyond its transcriptional functions, HDGF2 has recently gained attention in neurodegenerative disease research, where its cryptic protein variants serve as potential biomarkers for TDP-43 pathology .

How does HDGF2 interact with chromatin to regulate gene expression?

HDGF2 interacts with chromatin primarily through binding to specific histone modifications, particularly H3K36me2 and H3K36me3 (histone H3 lysine 36 di- and tri-methylation) . Quantitative ChIP-MS experiments have demonstrated that nucleosomes associated with HDGF2 are highly enriched in these modifications compared to genome-wide histones . Importantly, HDGF2-bound nucleosomes are depleted of repressive chromatin marks like H3K27me2 and H3K27me3, confirming HDGF2's preference for actively transcribed regions .

Functionally, HDGF2 facilitates RNAPII progression through nucleosomes. In vitro transcription assays showed that HDGF2 allows RNAPII to transcribe through nucleosomes similarly to the FACT complex, with at least two molecules of HDGF2 per nucleosome required for efficient transcription . PRO-Seq data from HDGF2 knockout cells revealed that HDGF2 specifically affects the transition from transcription initiation to elongation, as evidenced by increased RNAPII occupancy at promoter-proximal regions, particularly at the first nucleosome position . This suggests HDGF2 helps RNAPII overcome the nucleosome barrier during elongation rather than affecting transcription initiation.

What structural domains characterize HDGF2 and how do they contribute to its function?

HDGF2 contains several critical structural domains that enable its chromatin-associated functions:

• PWWP domains: These domains are crucial for HDGF2's ability to recognize and bind specific histone modifications, particularly H3K36me2 and H3K36me3 . PWWP domains function as "readers" of histone methylation marks, directing HDGF2 to regions of active transcription.

• HMGA-like AT hooks: HDGF2 contains AT hook motifs similar to those found in High Mobility Group A (HMGA) proteins, which bind to the minor groove of AT-rich DNA sequences . These AT hooks appear essential for HDGF2's FACT-like activity in facilitating transcription through nucleosomes, as related proteins lacking these hooks (such as HDGF) did not substitute for FACT in transcription assays .

The combination of these domains enables HDGF2 to recognize specific chromatin states through the PWWP domain and interact with nucleosomal DNA through the AT hooks, thereby facilitating RNAPII progression through chromatin barriers. Experimental evidence suggests that multiple HDGF2 molecules are required per nucleosome for efficient transcription, indicating that HDGF2 may function as a multimer in remodeling nucleosomes during transcription elongation .

What is the relationship between HDGF2 and TDP-43 pathology in neurodegenerative diseases?

HDGF2 has emerged as a significant reporter of TDP-43 pathology through mechanisms involving cryptic exon inclusion. TAR DNA-binding protein 43 (TDP-43) normally suppresses cryptic exons in mature mRNAs, but when TDP-43 becomes dysfunctional—as occurs in TDP-43 proteinopathies like frontotemporal lobar degeneration (FTLD-TDP), amyotrophic lateral sclerosis (ALS), and some Alzheimer's disease cases (AD-TDP)—these cryptic exons become incorporated into transcripts .

In the case of HDGF2, TDP-43 dysfunction leads to the inclusion of a cryptic exon in HDGF2 mRNA (referred to as HDGFL2-CE), which produces a novel, stable cryptic protein . Research has demonstrated that this HDGFL2-CE protein accumulates specifically in brain regions affected by TDP-43 pathology . Notably, the abundance of HDGFL2-CE protein associates significantly with phosphorylated TDP-43 (pTDP-43) burden in tissues from patients with FTLD-TDP and AD-TDP .

Immunofluorescence studies have confirmed that HDGFL2-CE proteins accumulate in cells exhibiting pTDP-43 pathology in motor cortex and hippocampus tissues from patients with ALS-FTD . This direct association makes HDGFL2-CE proteins valuable reporters of TDP-43 pathology, as they reflect the functional consequence of TDP-43 dysfunction at the molecular level.

How can HDGF2 cryptic proteins serve as biomarkers for neurodegenerative diseases?

HDGFL2 cryptic proteins (HDGFL2-CE) show significant promise as biomarkers for TDP-43 proteinopathies, with several advantages over existing approaches:

• Anatomical specificity: HDGFL2-CE is significantly increased in brain regions with TDP-43 pathology in patients with FTLD-TDP and AD-TDP compared to controls . In the amygdala, both FTLD-TDP and AD-TDP cases show significant elevation of HDGFL2-CE, while in the frontal cortex, elevation is primarily observed in FTLD-TDP cases, consistent with the typical distribution of TDP-43 pathology in these diseases .

• Diagnostic discrimination: HDGFL2-CE demonstrates excellent discriminatory ability between individuals with and without TDP-43 pathology. In the amygdala, HDGFL2-CE distinguished controls from individuals with TDP-43 pathology with an area under the receiver operating characteristic curve (AUC) of 0.92 for FTLD-TDP and 0.85 for AD-TDP, indicating excellent diagnostic potential . It also showed moderate ability (AUC of 0.68) to distinguish AD without TDP-43 pathology from AD with TDP-43 pathology .

• Biofluid detection: HDGFL2-CE proteins are detectable in cerebrospinal fluid (CSF) from patients with conditions likely to have TDP-43 pathology, including C9orf72 repeat expansion carriers and patients with sporadic ALS . This makes it a potentially valuable fluid biomarker for clinical applications.

• Pathological correlation: HDGFL2-CE protein levels significantly associate with phosphorylated TDP-43 (pTDP-43) burden in both FTLD-TDP and AD-TDP cases, with estimated β coefficients higher for HDGFL2-CE protein than for HDGFL2-CE RNA, indicating that the protein serves as a more accurate indicator of TDP-43 dysfunction .

These properties position HDGFL2-CE as a promising biomarker for selecting participants for clinical trials targeting TDP-43 pathology and for developing precision medicine approaches for FTLD and AD subtypes .

How do HDGF2 expression patterns differ between neurologically healthy subjects and patients with TDP-43 proteinopathies?

The primary differences in HDGF2 expression between healthy subjects and patients with TDP-43 proteinopathies center on the production of cryptic HDGF2 proteins (HDGFL2-CE). Several significant patterns have been observed:

• Regional expression differences: In FTLD-TDP patients, HDGFL2-CE is significantly increased in both the amygdala and frontal cortex compared to cognitively normal controls . In AD-TDP patients, HDGFL2-CE is primarily elevated in the amygdala but not the frontal cortex, consistent with the typical distribution of TDP-43 pathology in AD .

• Disease specificity: When comparing AD cases without TDP-43 pathology to AD-TDP cases, HDGFL2-CE was significantly increased only in the amygdala of AD-TDP cases . This indicates that HDGFL2-CE elevation is specifically associated with TDP-43 pathology rather than with general AD pathology.

• Quantitative differences: HDGFL2-CE was significantly increased in the amygdala of FTLD-TDP and AD-TDP cases compared to controls in both unadjusted analysis and when adjusting for age at death and sex . This elevation provided good to excellent discriminatory ability between cases and controls.

• Cellular localization: Immunofluorescent staining studies have demonstrated that HDGFL2-CE proteins accumulate specifically in cells exhibiting pTDP-43 pathology in tissues from patients with ALS-FTD . This cellular colocalization provides strong evidence for the direct relationship between TDP-43 dysfunction and HDGFL2-CE production.

• Correlation with pathology: The abundance of HDGFL2-CE protein significantly associates with phosphorylated TDP-43 (pTDP-43) burden in affected brain regions . This correlation indicates that HDGFL2-CE levels reflect the severity of TDP-43 pathology.

These differences establish HDGFL2-CE production as a direct consequence of TDP-43 pathology and support its potential as a sensitive reporter of TDP-43 dysfunction in neurodegenerative diseases.

What are the current methods to measure HDGF2 and its cryptic proteins in biological samples?

Several methodological approaches have been developed to detect and quantify HDGF2 and its cryptic proteins in various biological samples:

• Immunoassays for tissue samples: Researchers have developed sensitive and specific immunoassays to detect HDGFL2-CE proteins in brain tissue samples from neurodegenerative disease cases . These optimized assays can detect HDGFL2-CE in multiple brain regions characterized by TDP-43 pathology, including the amygdala and frontal cortex .

• Immunofluorescent staining: HDGFL2-CE antibodies have been used for immunofluorescent staining of tissue sections, enabling visualization of HDGFL2-CE protein accumulation in cells exhibiting pTDP-43 pathology . This technique has been successfully applied to motor cortex and hippocampus tissues from patients with ALS-FTD .

• CSF detection methods: Methods have been developed to detect HDGFL2-CE in cerebrospinal fluid, showing statistically significant elevations in individuals likely to have TDP-43 pathology compared to controls . These CSF detection approaches are particularly valuable for ante-mortem diagnosis.

• RNA analysis: For detecting HDGFL2-CE at the transcript level, techniques for quantifying cryptic exon inclusion in HDGF2 mRNAs have been employed . These analyses showed that HDGFL2-CE RNA abundance associates with pTDP-43 burden in affected brain regions, though the correlation was stronger for the protein than for the RNA .

For studying HDGF2's chromatin interactions and transcriptional functions:

• ChIP-seq and ChIP-MS: Chromatin immunoprecipitation followed by sequencing (ChIP-seq) or mass spectrometry (ChIP-MS) has been used to analyze HDGF2 binding to chromatin and its association with specific histone modifications . These techniques revealed that HDGF2 preferentially binds to regions with H3K36me2 and H3K36me3 modifications .

• PRO-Seq: Precision Run-On Sequencing has been used to map engaged RNA polymerase II on genes in HDGF2 knockout versus wild-type cells, revealing HDGF2's role in transcription elongation .

• In vitro transcription assays: Reconstituted transcription systems have been developed to assess HDGF2's ability to facilitate RNAPII transcription through nucleosomes, demonstrating its FACT-like activity .

These methodological approaches provide complementary information about HDGF2 and its cryptic proteins in different biological contexts and at different molecular levels.

How can researchers generate and validate HDGF2 knockout models to study its function?

Researchers have successfully developed several approaches for generating HDGF2 knockout models to investigate its function. Based on the literature, here is a methodological guide:

• CRISPR/Cas9 gene editing:

  • The primary method described for generating HDGF2 knockout models is CRISPR/Cas9 technology .

  • This approach has been used to create both single HDGF2 knockouts and double knockouts with LEDGF (a factor with similar function) in mouse embryonic stem cells (mESCs) .

  • For myoblast studies, HDGF2 knockout models were successfully generated using the same technology .

• Cell line selection considerations:

  • When studying HDGF2 function, it's critical to consider the expression levels of related proteins that might have redundant functions, such as FACT complex components (SPT16, SSRP1) and LEDGF.

  • The myoblast (MB) to myotube (MT) differentiation system has been identified as ideal for studying HDGF2 function because protein levels of FACT components and LEDGF decrease during differentiation while HDGF2 remains constant . This minimizes confounding effects from functional redundancy.

• Validation strategies:

  • Western blot analysis should be performed to confirm the absence of HDGF2 protein in knockout models .

  • RNA-seq can identify genes that fail to properly induce during differentiation in HDGF2 knockout models compared to wild-type cells .

  • Multiple independent knockout cell lines should be generated to ensure that observed phenotypes are due to HDGF2 elimination rather than off-target effects .

• Functional rescue experiments:

  • To further confirm knockout specificity, rescue experiments should be performed by stably reintroducing HDGF2 expression via lentiviral transduction .

  • Research has demonstrated that phenotypes observed in HDGF2 knockout myoblast cell lines could be rescued by stable lentiviral expression of HDGF2, confirming that the effects were specifically due to HDGF2 elimination .

• Phenotypic analysis methods:

  • PRO-Seq is particularly valuable for analyzing HDGF2 knockout effects on transcription elongation, as it precisely maps engaged RNAPII positions .

  • RNA-seq should be used to evaluate global gene expression changes in knockout models, particularly during differentiation processes .

  • ChIP-seq can examine changes in chromatin occupancy patterns of transcription-related factors in the absence of HDGF2 .

These methodological approaches enable researchers to generate robust HDGF2 knockout models and comprehensively analyze the resulting phenotypes to understand HDGF2's biological functions.

What ChIP-seq strategies are most effective for studying HDGF2 binding to chromatin?

Based on published research, the following ChIP-seq strategies are most effective for studying HDGF2's interactions with chromatin:

• Protein tagging approach:

  • Utilizing FLAG-tagged HDGF2 for ChIP-seq experiments provides highly specific immunoprecipitation using anti-FLAG antibodies . This approach typically yields cleaner results than antibodies against native proteins.

  • Expression systems should be carefully designed to maintain physiologically relevant expression levels of the tagged protein.

• Chromatin preparation optimization:

  • Standard crosslinking with formaldehyde should preserve protein-DNA interactions.

  • Sonication conditions must be optimized to generate chromatin fragments of appropriate size (typically 200-500 bp) for high-resolution binding analysis.

• Comprehensive control strategy:

  • Include input chromatin and mock IP controls (with non-specific IgG) to account for background and assess enrichment properly.

  • Consider spike-in controls for quantitative comparisons between different conditions.

• Integrated multi-omics analysis:

  • Correlate HDGF2 ChIP-seq data with RNA polymerase II (RNAPII) occupancy to understand the relationship between HDGF2 binding and active transcription .

  • Compare HDGF2 binding patterns with those of other chromatin-associated factors (e.g., SPT16 from the FACT complex) to identify regions of overlap or unique binding .

  • Generate average density profiles across gene bodies to visualize HDGF2 binding patterns in relation to transcription start sites .

• Histone modification correlation:

  • Perform parallel ChIP-seq for relevant histone modifications, particularly H3K36me2 and H3K36me3, which are associated with HDGF2 binding .

  • Calculate correlation coefficients between HDGF2 binding and various histone modifications to identify patterns of association .

  • Consider performing ChIP-MS to quantitatively analyze the histone modifications associated with HDGF2-bound nucleosomes .

• Differential binding analysis:

  • Compare HDGF2 binding patterns across different cellular states, such as before and after differentiation, to identify dynamic changes in occupancy .

  • Correlate changes in HDGF2 binding with changes in gene expression to identify functional consequences of differential binding .

• Validation approaches:

  • Examine individual gene loci to validate genome-wide patterns, focusing on representative examples such as genes that change expression during differentiation .

  • Perform ChIP-qPCR at selected loci to validate ChIP-seq findings with an orthogonal method.

By implementing these methodological approaches, researchers can comprehensively characterize HDGF2's interaction with chromatin and relate it to transcriptional regulation and other chromatin-associated processes.

How does HDGF2 cooperate with other proteins to regulate transcription during cellular differentiation?

HDGF2 participates in a dynamic network of protein interactions to regulate transcription during cellular differentiation, with its role becoming particularly crucial in differentiated cells where other transcription factors may be downregulated. The research reveals several key aspects of these cooperative interactions:

• Functional relationship with LEDGF and FACT:

  • HDGF2 functions similarly to LEDGF (another chromatin-associated protein) and the FACT complex in allowing RNA polymerase II to overcome nucleosome barriers during transcription elongation .

  • In mouse embryonic stem cell differentiation, genes gaining RNAPII binding also recruit HDGF2 and/or SPT16 (a FACT component), indicating coordinated action in regulating newly activated genes .

  • Double knockout studies of LEDGF and HDGF2 revealed that many genes failed to properly induce during differentiation, but genes maintaining normal induction often showed increased SPT16 binding, suggesting compensation by FACT .

• Context-dependent cooperation during differentiation:

  • During myoblast to myotube differentiation, protein levels of FACT components (SPT16 and SSRP1) and LEDGF decrease while HDGF2 remains constant .

  • In this context, HDGF2 becomes the predominant factor facilitating transcription through nucleosomes, as evidenced by its increased binding to induced genes in myotubes and the failure of these genes to activate in HDGF2 knockout cells .

  • A clear example is the myosin heavy chain (MHC) gene cluster, where HDGF2 binding increases on induced genes during differentiation while LEDGF binding decreases and SPT16 becomes undetectable .

• Dynamic interplay with histone modifications:

  • HDGF2 binding associates with specific histone modifications, particularly H3K36me2 and H3K36me3 .

  • During cellular differentiation, histone modifications reorganize, and HDGF2 appears to reorganize with them to maintain chromatin in a transcriptionally competent state .

  • This reorganization helps sustain unique transcriptional profiles of particular cell types, especially in differentiated cells where FACT is no longer expressed .

• Interaction with repressive chromatin domains:

  • Research has observed interplay between HDGF2 and H3K27me3 domains (repressive chromatin) during differentiation .

  • For example, a silent gene located within an H3K27me3 domain in myoblasts became induced in myotubes, concurrent with loss of H3K27me3 and accumulation of HDGF2 .

  • This gene's expression was dependent on HDGF2, suggesting HDGF2 may facilitate the transition from repressive to active chromatin states during differentiation .

These cooperative interactions highlight HDGF2's role in a dynamic system of chromatin regulation that adapts during cellular differentiation to maintain appropriate gene expression patterns, particularly when other transcription factors become downregulated.

What is the mechanism by which HDGF2 overcomes nucleosome-induced barriers to transcription?

HDGF2 plays a crucial role in facilitating transcription elongation by helping RNA polymerase II overcome nucleosome-induced barriers. Multiple lines of evidence illuminate this function:

• Biochemical evidence for FACT-like activity:

  • In vitro transcription assays demonstrate that HDGF2 allows RNA polymerase II to transcribe through nucleosomes similar to the FACT (Facilitates Chromatin Transcription) complex .

  • This activity requires specific structural features of HDGF2, particularly the HMGA-like AT hooks, as related proteins lacking these elements (such as HDGF) failed to substitute for FACT in transcription assays .

  • The efficiency appears dose-dependent, with at least two or more molecules of HDGF2 per nucleosome required for efficient transcription .

• Cellular evidence from knockout studies:

  • PRO-Seq analysis of HDGF2 knockout myoblasts revealed increased RNA polymerase II occupancy within the promoter-proximal region of many HDGF2 target genes compared to wild-type cells .

  • This increased polymerase peak precisely correlates with the position of the first nucleosome, indicating that without HDGF2, RNA polymerase II becomes stalled at this nucleosome barrier .

  • This stalling phenotype was observed in multiple independent HDGF2 knockout cell lines and could be rescued by stable lentiviral expression of HDGF2, confirming the effect was specifically due to HDGF2 elimination .

• Mechanistic details:

  • HDGF2 does not impact transcription initiation but specifically affects the transition from initiation to elongation .

  • HDGF2 likely functions by temporarily destabilizing or reorganizing nucleosome structure to allow RNA polymerase II passage, similar to FACT's proposed mechanism .

  • The requirement for multiple HDGF2 molecules per nucleosome suggests it may form multimeric complexes to effectively remodel chromatin during transcription .

• Context-dependent significance:

  • HDGF2's role becomes particularly critical in differentiated cells where FACT components are downregulated .

  • In myotubes, where FACT is undetectable and LEDGF levels are low, HDGF2 becomes essential for the induction of specific genes during differentiation .

  • This indicates HDGF2 serves as an alternative mechanism to FACT for facilitating transcription through nucleosomes in certain cell types or developmental stages .

The research concludes that HDGF2 (along with LEDGF) represents a class of factors that allow RNA polymerase II to overcome nucleosome barriers in differentiated cells that no longer express FACT . This function is essential for maintaining chromatin in a transcriptionally competent state and supporting unique gene expression patterns during development and differentiation.

How do histone modifications influence HDGF2 chromatin binding and functional activity?

Histone modifications play a determinative role in HDGF2 binding patterns and influence its function in transcriptional regulation. Research has revealed several key aspects of this relationship:

• Preferential binding to specific modifications:

  • Quantitative ChIP-MS revealed that nucleosomes associated with HDGF2 are highly enriched in H3K36me2 (histone H3 lysine 36 di-methylation) compared to whole genome histones .

  • HDGF2 also shows enrichment for H3K36me3 (histone H3 lysine 36 tri-methylation) .

  • Conversely, nucleosomes associated with HDGF2 are depleted of repressive modifications, particularly H3K27me2 and H3K27me3 (histone H3 lysine 27 di- and tri-methylation) .

• Structural basis for modification recognition:

  • The PWWP domain of HDGF2 is critical for recognizing and binding specific histone modifications, particularly H3K36me2 and H3K36me3 .

  • PWWP domains function as "readers" of histone methylation marks, providing a structural explanation for HDGF2's binding preferences.

• Correlation with active transcription:

  • Spearman correlation analysis showed opposition between H3K27me3 (a repressive mark) and H3K36me2 (associated with active transcription) .

  • HDGF2 binding patterns correlate with regions of active transcription and RNA polymerase II occupancy, consistent with its preference for histone modifications associated with active genes .

• Dynamic interactions during differentiation:

  • During cellular differentiation, histone modifications undergo reorganization, and HDGF2 appears to reorganize accordingly .

  • Research observed examples where genes transitioning from silent to active states showed concurrent changes in histone modifications and HDGF2 binding .

  • For instance, a silent gene within an H3K27me3 domain in myoblasts became induced in myotubes with concurrent loss of H3K27me3 and accumulation of HDGF2 .

• Functional consequences of modification-guided binding:

  • By binding to regions with specific histone modifications, HDGF2 is directed to chromatin states where its function in facilitating transcription elongation is most needed.

  • This targeted binding enables HDGF2 to efficiently support transcription of active genes, particularly in differentiated cells where other factors like FACT may be downregulated .

  • The overlap between HDGF2 binding and active chromatin marks ensures that its activity in helping RNA polymerase II overcome nucleosome barriers is focused on genes that are being actively transcribed.

This relationship between histone modifications and HDGF2 binding illustrates how epigenetic information guides the recruitment of transcriptional regulators to specific genomic locations, ensuring proper gene expression patterns during development and differentiation.

How can HDGF2-based biomarkers improve the diagnosis of TDP-43 proteinopathies?

HDGF2-based biomarkers, particularly the cryptic protein HDGFL2-CE, show significant potential to transform the diagnosis of TDP-43 proteinopathies in several important ways:

• Addressing a critical diagnostic gap:

  • Currently, there is a lack of robust methods to measure pathological TDP-43 in biofluids .

  • HDGFL2-CE provides a surrogate marker that reflects TDP-43 dysfunction at the molecular level, potentially allowing more accurate diagnosis without requiring brain tissue .

• Superior diagnostic accuracy:

  • Research demonstrates that HDGFL2-CE has excellent discriminatory ability for detecting TDP-43 pathology, with area under the receiver operating characteristic curve (AUC) values of 0.92 for FTLD-TDP and 0.85 for AD-TDP when distinguishing from controls .

  • Even within Alzheimer's disease, HDGFL2-CE showed moderate ability (AUC of 0.68) to distinguish cases with TDP-43 pathology from those without . This is valuable since approximately 40-50% of AD cases have comorbid TDP-43 pathology, which is associated with more rapid clinical decline.

• Non-invasive detection in cerebrospinal fluid:

  • HDGFL2-CE proteins are detectable in cerebrospinal fluid from patients with conditions likely to have TDP-43 pathology, including presymptomatic or symptomatic C9orf72 repeat expansion carriers and patients with sporadic ALS .

  • This allows for ante-mortem diagnosis of TDP-43 pathology, which currently can only be definitively diagnosed at autopsy.

• Correlation with pathological burden:

  • HDGFL2-CE levels correlate with phosphorylated TDP-43 (pTDP-43) burden in affected brain regions , suggesting that CSF levels might reflect the severity of pathology.

  • This correlation could potentially enable monitoring of disease progression or therapeutic intervention effects.

• Disease specificity:

  • HDGFL2-CE is specifically elevated in the presence of TDP-43 pathology rather than as a general marker of neurodegeneration .

  • In AD cases, HDGFL2-CE was significantly increased only in those with TDP-43 pathology compared to those without , indicating its specificity for TDP-43-related processes.

These properties position HDGFL2-CE as a promising biomarker for improving diagnostic accuracy, enabling earlier intervention, supporting clinical trial enrollment for TDP-43-targeted therapies, and ultimately contributing to precision medicine approaches for neurodegenerative diseases.

What therapeutic potential does HDGF2 research offer for neurodegenerative diseases?

While current research doesn't directly address HDGF2 as a therapeutic target, several promising avenues can be derived from our understanding of its biology:

• Targeting consequences of TDP-43 dysfunction:

  • HDGFL2-CE production results directly from TDP-43 dysfunction in neurodegenerative diseases . If HDGF2 cryptic exon inclusion contributes to disease pathogenesis, strategies to prevent this cryptic splicing could prove therapeutically valuable.

  • Potential approaches might include antisense oligonucleotides designed to block the cryptic exon in HDGF2 mRNA, similar to approaches being developed for other genes affected by TDP-43 dysfunction.

• Leveraging HDGFL2-CE as a pharmacodynamic biomarker:

  • Even if not directly targeted, HDGFL2-CE levels could serve as a valuable biomarker to assess the efficacy of therapies aimed at restoring TDP-43 function or reducing TDP-43 pathology .

  • The strong correlation between HDGFL2-CE levels and pTDP-43 burden suggests it could provide a measurable outcome for clinical trials testing TDP-43-directed therapeutics.

• Modulating HDGF2's transcriptional function:

  • HDGF2 facilitates transcription through nucleosomes, particularly in differentiated cells where FACT is not expressed .