Neurometabolic network NMetNet for functional neurological disorder in children and adolescents, 2025, Lan et al.

Neurometabolic network NMetNet for functional neurological disorder in children and adolescents
Lan; Foster; Charney; Grinsven; Breedlove; Kozlowska; Lin

OBJECTIVES
Functional neurological disorder (FND) in children and adolescents is a biopsychosocially-complex condition characterized by a wide range of neurological symptoms. Using magnetic resonance spectroscopy to study neurometabolites has become an important approach to studying the mechanisms of FND. Unlike previous studies focusing on concentration-level analysis, this study examines conditional dependencies between six neurometabolites: N-acetyl aspartate, creatine, glutathione, choline, myo-inositol, and glutamate. Conditional dependence implies that two neurometabolites have joint variability that is not mediated by other neurometabolites.

METHODS
A Bayesian graphical lasso approach was used to estimate neurometabolites’ conditional dependencies in three regions of interest: the anterior default mode network (aDMN), supplementary motor area (SMA), and posterior default mode network (pDMN). We introduce the term neurometabolic network (NMetNet) to describe these conditional dependencies.

RESULTS
Children and adolescents with FND (vs. healthy controls) showed a loss of conditional dependencies related to creatine and glutathione between the aDMN and SMA/pDMN. Glutathione is the primary antioxidant in the brain. Creatine plays a key role in maintaining bioenergetics and also acts as an antioxidant.

CONCLUSIONS
These findings suggest that FND is characterized by dysregulated bioenergetics and increased vulnerability to oxidative stress. Understanding NMetNet in FND offers novel insights into the disorder’s neurobiology, with implications for therapeutic interventions to restore energy homeostasis and oxidative balance.

HIGHLIGHTS

• Using the graphical modeling, the Neurometabolic network (NMetNet) based on magnetic resonance spectroscopy is an innovative conceptual brain network that provides insights into functional neurological disorder.

• Children diagnosed with functional neurological disorder have a statistically significant loss of neurometabolic dependences of creatine and glutathione between the frontal and parietal/posterior regions, with the most pronounced dysconnectivity observed in those with functional seizures.

• Loss of creatine and glutathione dependencies suggests bioenergetic dysregulation, highlighting oxidative stress as a potential therapeutic target in pediatric functional neurological disorder.

Link (NeuroImage: Clinical) [Open Access]

 

The link is open access

 

Thirty-two children who were admitted into the Mind-Body Program for treatment of FND at The Children’s Hospital at Westmead in Australia (January 2019 to July 2021) consented to participate in this MRS study. Each child had completed a thorough neurological evaluation and had been diagnosed with FND according to the DSM-5 criteria by a pediatric neurologist (American Psychiatric Association, 2013). The clinical presentations of the 32 children with FND were diverse. The majority of children (n = 22; 68.75 %) presented with more than one FND symptom (range, 1–8; mean = 3.47; median = 3.00).

Poor kids..

 

Thanks, corrected.

 

5.6. Limitations
Akin to many neuroimaging studies, the sample size for this study is relatively small, although the reproducibility evaluation found the results to be robust. Nonetheless, future studies in a larger pediatric cohort or in adult cohorts are warranted. Larger studies would also help to address the potential role of comorbid conditions on NMetNet conditional dependencies, which are potentially affected by anxiety and depression. In this study, 84.4 % of the patients suffered from anxiety disorder and 43.8 % from depressive disorder. Future larger studies could take these additional factors into account.

The current FND cohort was not medication-free: 81.3 % of children with FND were taking one or more medication. The most common pharmacotherapy was the use of a selective serotonin reuptake inhibitor (SSRI), most commonly fluvoxamine, which is less activating than other SSRIs (see Table 2). Studies have shown that treatment with SSRIs such as fluvoxamine, fluoxetine, and sertraline decrease oxidative stress. In animal models SSRIs decrease levels of malondialdehyde—a biomarker of oxidative stress—and they increase levels of GSH (Poladian et al., 2023). In this context, the use of SSRIs to treat our patients’ comorbid anxiety or depression (as was common during our study; see Table 1) may have increased levels of GSH. Thereby obscuring any changes in GSH concentrations between controls and children with FND. The use of SSRIs should not have affected the strength of the connection (conditional dependence) in the neurometabolic network.

In view of the small sample size, our current statistical methodology needs more developments to account for the above-described confounding factors, and we will further develop our methodology to overcome this limitation in future studies and, wherever possible, to use a larger sample size.

Another limitation of our study is that it only provided group-level results. The estimated NMetNets describe the conditional dependence of a certain group rather than an individual. Providing individual-level results requires replications of neurometabolite measurements. In incoming works, we will introduce our developed pipeline to produce individual-level results, which can potentially be used for clinical diagnostics.