The discovery of reliable biomarkers has the potential to revolutionize clinical practice by enabling earlier and more accurate diagnosis of CP, which can lead to timely and targeted therapeutic interventions. Early identification of at-risk individuals allows for the implementation of neuroprotective strategies and tailored rehabilitation programs, potentially mitigating the severity of motor impairments and improving long-term outcomes. This study’s findings set the stage for future research to validate and refine these biomarkers in larger, diverse populations. Ultimately, the integration of biomarker-based diagnostics into routine clinical practice could transform the management of cerebral palsy, offering new hope for improved quality of life for affected individuals and their families.

Cerebral palsy (CP) remains one of the most prevalent childhood motor disorders, affecting approximately 2–2.5 per 1,000 live births worldwide [1]. It encompasses a heterogeneous group of non-progressive disorders of movement and posture caused by early brain injury or malformation, with implications for motor function throughout an individual’s lifespan [2]. Despite extensive research, the etiology of CP often remains elusive, hindering both early diagnosis and the implementation of targeted therapeutic interventions.

Skeletal muscles in patients with CP are altered due to neurological lesions. These brain lesions cause various neurological symptoms, including dystonia, ataxia, athetosis, and particularly spasticity [3, 4]. Loss of upper motor neuron inhibition on the lower motor neurons resulted in spasticity, altered muscle tone, and increased or impaired motor unit firing [5]. Although the mechanism is unknown, spastic muscle often shortens to create muscle contractures, which is a primary disability of CP that leads to further complications. CP is the most prevalent non-genetic cause of secondary dystonia, and its clinical management poses significant challenges [6]. The primary objectives in treating dystonia associated with CP are to mitigate dystonic symptoms, optimize functional capacity, alleviate pain, and enhance overall care convenience [7]. Oral medications, physical therapy techniques, chemical neurectomies with phenol or alcohol, chemodenervation using neurotoxins, and deep brain stimulation have been utilized to decrease spasticity and dystonic symptoms among children with CP, but often yield suboptimal results [8].

Skeletal muscle in patients with CP exhibits distinct characteristics, including muscle tissue and fiber atrophy, decreased cross-sectional area, muscle shortening, and reduced specific tension [9]. Identifying reliable biomarkers associated with CP is crucial for understanding its diverse etiologies, facilitating early diagnosis, prognostication, and targeted therapeutic interventions. However, the identification of reliable biomarkers and their translation into clinical practice remain significant challenges.

This study aimed to address these challenges by systematically identifying potential biomarkers for CP and developing robust prediction models. By leveraging advanced computational algorithms, we sought to uncover biomarkers that could serve as reliable indicators of CP risk and severity. In this study, we provided a detailed description of our methods for the discovery of biomarkers and the development of predictive models. We discussed the implications of the findings for clinical practice and proposed strategies for the future integration of biomarker-based diagnostics in the management of CP.

This study emphasizes the urgent need for early and accurate identification of biomarkers for CP to enhance diagnostic precision and improve patient outcomes. Through rigorous analysis, several potential biomarkers were identified, providing insights into the pathophysiological mechanisms related to CP. Developing predictive models based on these biomarkers offers opportunities for early diagnosis and personalized therapeutic interventions for CP. In our research, we identified 45 potential key genes through differential expression and WGCNA. Subsequent GO and KEGG analyses revealed that these genes are primarily involved in energy metabolism-related pathways in the development of CP, underscoring their crucial role in muscle movement. Further dataset validation identified CKMT2 as the key gene most closely associated with CP. Additionally, we established a predictive model for CP by combining five other significantly differentially expressed genes (TNNT2, MYH4, MYH1, GOT1, and LPL).

Previous studies had also identified differential genes and pathways associated with CP, which share many similarities with our research. Our study, along with those by Pingel and Robinson et al., identified genes related to energy production and muscle function as significant in CP [15, 16]. Genes involved in ECM structure and turnover have been emphasized in multiple studies. Increased ECM turnover and net collagen synthesis enable ECM remodeling as an adaptive response to the increased mechanical load and functional demands caused by spasticity [17]. Previous research had shown significantly lower LPL expression and increased intramuscular fat levels in CP patients, which was consistent with our findings [18, 19]. Additionally, Pingel et al.’s study highlighted the importance of calcium homeostasis in skeletal muscle movement and plasticity, finding distorted calcium ion handling in CP [11]. Stress, cell death, and autophagy also had contributed to the pathology of CP. Each study provided unique insights into the specific genes and mechanisms involved in CP pathology, underscoring the importance of genes related to energy metabolism, muscle function, and ECM structure in CP.

In our diagnostic model, CKMT2 was identified as the key gene most closely related to CP. The CKMT2 gene encodes mitochondrial creatine kinase, an enzyme crucial for energy metabolism in tissues with high and fluctuating energy demands, such as the brain and muscles. CKMT2 plays a primary role in maintaining cellular energy homeostasis by facilitating the reversible transfer of phosphate groups between adenosine triphosphate (ATP) and creatine [20]. This process allows for the storage and transportation of energy within cells, particularly in mitochondria-rich tissues. Additionally, mitochondrial creatine kinase is believed to be essential for maintaining mitochondrial morphology by stabilizing contact sites between the inner and outer mitochondrial membranes. Impaired activity of CKMT2 has been associated with the loss of mitochondrial membrane potential and apoptosis [21]. In the intact rabbit heart, a rapid and irreversible loss of CKMT2 was observed, which was directly related to the duration of ischemia. This loss of CKMT2 correlated with contractile dysfunction during reperfusion [22].

Further studies have demonstrated that CKMT2 overexpression protects against cellular oxidative stress damage, likely due to increased creatine kinase activity and its role in promoting mitochondrial integrity [23, 24]. CKMT2 is crucial for regulating energy production and utilization in the brain, ensuring a constant energy supply essential for neuronal function, neurotransmission, and brain health. Beyond energy provision, CKMT2 maintains cellular energy reserves and buffers against energy fluctuations. Variations or mutations in the CKMT2 gene may contribute to mitochondrial dysfunction, disrupting energy balance in neurons and potentially influencing the onset or severity of CP. Therefore, studying the correlation between CKMT2 variants and CP clinical features (such as severity, motor impairment patterns, or associated comorbidities) can deepen the understanding of disease subtypes and their pathological mechanisms, providing opportunities for personalized treatment. Exploring pathways aimed at regulating mitochondrial function or enhancing energy metabolism may serve as therapeutic strategies to alleviate symptoms or prevent the progression of related damage. Further large-scale genetic studies, functional analyses, and investigations into mitochondrial function will be essential to determine their significance in disease development and identify potential therapeutic targets.

The remaining five genes in the diagnostic model (TNNT2, MYH4, MYH1, GOT1, and LPL) also contribute to the pathology of CP through different mechanisms. TNNT2 encodes a component of the troponin complex critical for muscle contraction regulation, with variants linked to neuromuscular disorders [25]. In CP, TNNT2 variations might affect muscle tone regulation, contributing to motor impairments. MYH4 and MYH1 encode myosin heavy chain proteins, which are essential for muscle contraction. Alterations in these genes may impact muscle fiber composition or contractile properties, potentially leading to abnormalities in motor function and muscle tone observed in CP [26, 27]. GOT1 (Glutamic-Oxaloacetic Transaminase 1) is involved in amino acid metabolism [28]. Although its direct role in CP is not yet clear, disruptions in amino acid metabolism pathways could potentially affect brain development or neural function, thus contributing to the complex etiology of CP. LPL (Lipoprotein Lipase) plays a crucial role in lipid metabolism, affecting neurodevelopment and neuronal health [29]. Dysregulation of LPL may lead to changes in lipid metabolism, which correlates with the previously observed increase in intramuscular fat levels [18]. In conclusion, while the roles of TNNT2, MYH4, MYH1, GOT1, and LPL genes in CP are still under investigation, their involvement in muscle function, metabolic pathways, and potentially neurodevelopmental processes could contribute to the diverse clinical manifestations observed in individuals with CP. Variations in TNNT2, MYH4, and MYH1 may affect muscle structure, contractility, or neuromuscular junction function, contributing to motor impairments and muscle tone abnormalities. Meanwhile, genes such as GOT1 and LPL, involved in amino acid and lipid metabolism respectively, may indirectly affect neurodevelopmental processes and lipogenesis in muscle. Dysregulation of these pathways could impact substance synthesis and neuronal health within muscle, potentially contributing to the multifactorial nature of CP. Further research is needed to validate the differential expression of these genes and their direct impact on the pathogenesis of CP. Experimental models and functional assays are necessary to elucidate their specific contributions to neuronal development or muscle function. Additionally, studying the differential expression of genes and their potential association with birth complications may provide valuable insights into the etiology of CP.

Through the DGIdb database, we obtained potential therapeutic agents targeting the biomarkers. Purpurogallin (PPG) possesses significant antioxidant properties. By inhibiting the TLR4/NF-κB pathway and thereby attenuating endoplasmic reticulum stress and neuroinflammation, PPG demonstrates potential neuroprotective effects against cerebral ischemia-reperfusion injury [30]. Insulin, beyond its role in glucose metabolism, has shown neuroprotective effects and might influence brain development and neuroplasticity, which could be relevant in CP management. Lymphokine-activated killer (LAK) Cells and recombinant lymphokine have cytotoxic activity against tumor cells when activated in vitro, but their effects on CP remain unexplored. Levosimendan has a vasodilatory effect, and its potential impact on cerebral circulation and muscle tissue blood supply in CP patients needs further clarification [31]. Statins (Lovastatin, Pravastatin) have shown neuroprotective and anti-inflammatory effects, potentially beneficial in managing neuroinflammation in CP. Diazoxide, a vasodilator and potassium channel opener, does not have well-documented effects on CP but might influence blood flow or neural excitability. Triamcinolone, a corticosteroid, has the potential to suppress inflammation and immune responses, making it a potential option for managing inflammation-related aspects of CP. In a frozen shoulder rat model, the injection of triamcinolone acetonide has shown effective anti-fibrosis, anti-angiogenesis, and anti-inflammatory properties [32]. While these drugs show promise in affecting neurological functions or mechanisms related to CP, their specific impacts on CP patients require extensive clinical studies. Considerations such as dosage, duration, individual variability, and underlying pathology are crucial when evaluating their effects. Some drugs’ impacts on CP may not be well-documented or explored in clinical trials specifically for this condition, necessitating targeted research or clinical trials to evaluate their efficacy and safety in this population.

The study used samples from various muscle groups, with tissue collection sites as potential confounders. Different muscle groups exhibited unique gene expression profiles due to their physiological functions and fiber types [33]. Wrist muscles, crucial for fine motor skills and complex hand movements, showed a high gene expression in pathways involved in neuromuscular junctions, muscle contraction, and calcium handling [34, 35]. Conversely, hamstring and quadriceps muscles, involved in gross motor functions, exhibited increased gene expression in ECM tissue and muscle fiber composition for structural integrity and weight-bearing [36]. Additionally, elevated expression related to oxidative phosphorylation, muscle repair, and regeneration supported endurance and adaptive recovery [37, 38]. These differences highlight the unique needs of each muscle group and suggest personalized strategies for treating related diseases. However, obtaining muscle biopsy tissue from high-risk CP patients is an unavoidable challenge. Ethical considerations and strict informed consent procedures, especially for children, must be given primary consideration. The invasiveness of the surgery, along with the risks of postoperative infection, bleeding, and discomfort, may deter participation. Additionally, the medical fragility and anesthesia risks in CP patients complicate the procedure. Despite these challenges, muscle biopsies are crucial for studying the pathophysiology of CP and subsequently developing targeted therapies to improve muscle function and quality of life. Careful planning and ethical oversight are required, balancing the need for high-quality data with alternative, less invasive methods.

The CP prediction model based on hub genes demonstrates superior predictive power and accuracy compared to utilizing single genes. However, certain limitations related to the data must be acknowledged. The limited size of the cohorts in our dataset was a significant constraint, restricting the statistical power and robustness of our findings. Additionally, differences in age and sex between the control and CP groups represented potential confounding factors. Age-related gene expression differences and sex-specific biological variations can impact results, making it challenging to attribute observed differences solely to CP. Secondly, variability in the severity of CP may exhibit different molecular characteristics. Stratifying CP patients based on detailed clinical data and severity could help elucidate the relationship between CP severity and biomarker expression. It is essential to dynamically monitor changes in gene expression profiles throughout disease progression in longitudinal cohorts. Furthermore, variability among different muscle samples needs further clarification. In CP patients, muscle tissue often exhibits unique pathological changes such as increased ECM, fat infiltration, and heightened inflammation, which can affect gene expression outcomes due to differences in tissue composition. Isolating specific cell types or using single-cell RNA sequencing can provide a more precise understanding of the molecular basis of CP.

Our study highlights the importance of considering demographic variables, repeated measures, and tissue composition in biomarker research. Despite the limitations, our findings provide valuable insights into the molecular underpinnings of CP. Future research should focus on using larger, well-matched cohorts and advanced analytical techniques to improve the accuracy and applicability of biomarker discoveries. By addressing these factors, we can enhance the diagnostic and therapeutic potential of CP biomarkers.

This study provides new insights into identifying potential biomarkers for CP and developing predictive models for early diagnosis and personalized treatment. Using comprehensive bioinformatics approaches, promising biomarkers (CKMT2, TNNT2, MYH4, MYH1, GOT1, and LPL) were identified, and robust predictive models for muscle sample markers specific to CP were developed. The findings highlight the importance of incorporating biomarker-based diagnostics into clinical practice to enable early and accurate diagnosis, leading to timely interventions and improved long-term outcomes. Future research should validate these biomarkers and models in larger cohorts and translate them into practical diagnostic tools and treatment protocols, ultimately enhancing the quality of life for individuals with CP and their families.