Scientific psychiatry within technical reach

Abstract

This is an invited commentary on the paper by Zou et al, accepted for publication in World Journal of Psychiatry. It reflects the findings of the authors in the broader context of the search for scientifically sound and evidence based nomothetic system for diagnosis and treatment in psychiatry, with a special focus on the application of translational neuroimaging in that effort.

Key Words: Depression; Prefrontal cortex; Neuroimaging; Nomothetic network psychiatry; Translational neuroimaging

Core Tip: The advances in the field of translational neuroscience over the past decade have facilitated the introduction of nomothetic network knowledge, which is a key prerequisite for any medical discipline. Neuroimaging in its various modalities has pivotal contribution in that context, and particularly for the better explanation and management of depression.

TO THE EDITOR

Eleven years before our program article[1] and after the publication of the seminal Oxford University Press volume on psychiatric validation[2], there has been a substantial advance in the field of translational applications of neuroscience in psychiatry. Those applications neither challenge nor undermine the efforts to understand the values and comprehensive experiences of the mentally ill[3], which supervene neurobiological mechanisms. Its ultimate goal is to provide a meta-stable epistemic basis for nomothetic network diagnosis and treatment, which are typical for all medical knowledge[4].

The pursuit of objective biomarkers in psychiatric research has been significant in recent years, driven by the need for such tools in clinical practice. A primary research focus is developing objective diagnostic criteria that align with the current gold standard in psychiatry, the clinical interview. Despite the advancements in science-based medicine, psychiatry continues to rely heavily on clinical interviews as a primary diagnostic tool. Recognizing the inherent subjectivity of this method, researchers are actively exploring innovative approaches to address this challenge. By integrating translational methods that bridge the gap between the diverse clinical manifestations of psychiatric symptoms and their underlying biological substrates, we can work towards developing more objective and reliable diagnostic criteria. Translational cross-validation serves as a crucial mechanism to ensure the validity and reliability of these new methods. This field rich in complexity, with a lot of promising new ideas and studies arising, paving the way to an answer piece by piece. Psychiatric research is transitioning towards a more data-driven approach. This shift aligns with the principles of nomothetic network psychiatry. Studies like this one contribute to building the foundation for a data-driven approach that can address the complexity of mental disorders. Establishing this foundation, interpreting its role within the network perspective, and identifying common transdiagnostic factors based on a biological science-driven approach represent a promising direction for advancing psychiatric clinical medicine toward a more objective and personalized model of care.

Magnetic resonance spectroscopy is one of the techniques applied in neuropsychiatric research, aiming to investigate the biochemical changes associated with psychopathology[5]. It is considered to potentially serve as a valuable tool for identifying biomarkers that could be of use in the diagnostic and therapeutic process.

Zou et al[1] explored this topic using biochemical and neuroimaging techniques in depressed adolescents. They looked for metabolic alterations in the prefrontal white matter (PWM), anterior cingulate, gray matter and thalami using proton magnetic resonance spectroscopy (H-MRS), with the target metabolites being N-acetyl aspartate (NAA), choline (Cho) complexes, Creatine (Cr) and myo-inositol (mI). They calculated NAA/Cr, Cho/Cr, and MI/Cr ratios. The Hamilton Depression Scale-24 item (HAMD-24) and Wechsler Memory Scale (WMS) scores served as both diagnostic criteria and confirmatory metrics in the analysis of the depressed adolescent and control groups. A cross-validation approach enhances the reliability of the neuroimaging data.

The study's primary findings suggest a correlation between PWM and grey matter biochemical imbalances in adolescents and the development of depressive symptoms, particularly those associated with cognitive impairment. PWM has been a focus of research in adolescent neuropsychiatry. Studies exploring its role in the development of depression have yielded inconsistent results, emphasizing the need for additional research to understand its contribution to the disorder fully[6]. Zou et al’s results showed that depressed adolescents have lower NAA/Cr and Cho/Cr ratios in the bilateral PWM, which could be linked with memory impairment[1], and the lower Cho/Cr and mI/Cr in bilateral thalami compared to controls were linked to altered metabolism of nerve cell membranes (Table 1).

Table 1 Differences in metabolites between healthy adolescents and depressed adolescents.

	NAA/Cr	Cho/Cr	mI/Cr
Bilateral PWM	DA < HA	DA < HA	Similar
Bilateral ACGM	No difference
Bilateral thalami	DA < HA	No difference	DA < HA

DA: Depressed adolescents; HA: Healthy adolescents; NAA: N-acetylaspartate; Cr: Creatine; Cho: Choline; mI: Myo-inositol; PWM: Prefrontal white matter; ACGM: Anterior cingulate grey matter.

Considering the extensive body of research on adults with depression, this study provides a valuable contribution to the field. Therefore, in contrast to studies in adolescents-the prefrontal cortex in depressed adults has been well-researched. Shifting our studies on adults-some are showing the importance of prefrontal structural abnormalities in patients even more-linking it to suicidal ideation and attempts[7]. Findings of low Cho/Cr ratios in the PWM of major depressive disorders (MDD) patients, which increased following SSRI treatment, suggest that these metabolic alterations may play a role in the pathophysiology of MDD[8]. Given the findings of this study, there may be assumed a connection between the observed metabolic alterations and their potential impact on the neurodevelopment and function of this region in the adult brain.

Considering the prefrontal cortex's well-established role in cognitive functions and its association with depressive symptoms, the metabolic alterations identified in this study could offer valuable insights into the neurobiological underpinnings of depression in adolescents[9]. This shows a possibility to find an explanation for the occurrence of cognitive symptoms in patients, such as altered concentration, memory impairments, slowed processing speed, and deficits in social cognition. By examining the developmental trajectories of these regions in depressed individuals compared to healthy controls, researchers can explore how disrupted prefrontal cortex development may contribute to the emergence of depressive symptoms. The study used the WMS to evaluate the subjects’ long-term, short-term, and immediate memory, generating a memory quotient (MQ). The study group exhibited significantly higher HAMD-24 scores and significantly lower MQ scores.

Furthermore, bilateral thalamic Cho/Cr and mI/Cr values were reported to be lower in the patient group. It's proposed that this result could be linked to a metabolic disorder of the membranes of neurons in the thalamus. There is data on structural changes, specifically reduced volume, of the bilateral thalami in adults with depression[10]. Findings of reduced thalamic volume and altered metabolism provide converging evidence for the thalamus as a critical region involved in the pathophysiology of depression. The observed abnormalities of thalamic metabolism could potentially be interpreted in two primary hypotheses: Both structural and metabolic changes in the thalamic region are responsible for some of the clinical symptoms, or metabolic alterations in adolescents could lead to structural abnormalities in the thalamic regions of adult patients. As mentioned in the study, the thalamus is a core component of the reward circuit and is linked to anhedonia. Therefore, abnormalities in this area have yielded meaningful results as an approach to a neurotopical explanation of clinical symptoms[11].

To a great extent, the reported results are also consistent with earlier findings of our group, with structural magnetic resonance imaging (MRI) and multivariate analysis combining various MRI modalities for precision diagnostics in psychiatry[12,13].

Through studying the interplay between metabolic, structural, and functional brain changes, a deeper understanding of the underlying mechanisms of mental disorders could be gained, and potentially more targeted treatments developed[13]. The authors should consider applying this methodology to larger populations and addressing the possible effect of medication interpreting results. While metabolic alterations could potentially serve as reliable biomarkers in psychiatry, as they do in other medical fields, it's crucial to consider the translational context. The brain regions affected by these alterations correspond to key cognitive functions, emphasizing the need to interpret these findings considering clinical presentation. This approach aims to bridge the gap between traditional clinical evaluation methods in psychiatry and a novel biological perspective. While challenging, this strategy represents a promising avenue for unraveling the complexities of mental disorders and developing more precise diagnostic criteria, ultimately leading to more effective and targeted treatments.

Establishing and confirming the significance and underlying mechanisms of these metabolic alterations and their impact on neurodevelopment could identify potential therapeutic targets on a metabolic level. This may offer avenues for interventions that could help mitigate the occurrence of structural alterations in adulthood. A biomarker derived from this data could support personalized medicine by enabling diagnostic and treatment plans tailored to the specific needs of each patient.

A promising avenue for future research would involve a multi-faceted approach. A longitudinal cohort study examining the prefrontal cortex development in adolescents utilizing this methodology, followed by continued assessments in adulthood, could yield valuable insights into the long-term neurodevelopmental alterations and their connections to the metabolic abnormalities found in adolescents.

This study revealed significant correlations between clinical interview findings and neuroimaging data. Findings revealed an inverse relationship between depression severity (HAMD-24) and metabolite levels (NAA/Cr, Cho/Cr, and mI/Cr) in both the PWM and thalamus. Conversely, the MQ exhibited positive correlations with these metabolites in specific brain regions (right PWM NAA/Cr, left PWM Cho/Cr, and bilateral thalamus Cho/Cr and mI/Cr). These results suggest that lower metabolite levels may contribute to both increased depression severity and cognitive impairment in these brain regions (Figure 1).

Figure 1 Significant correlations between clinical scales and proton magnetic resonance spectroscopy. HAMD-24: Hamilton Depression Rating Scale-24 items; biPWM: Bilateral prefrontal white matter; NAA: N-acetylaspartate; Cho: Choline; Cr: Creatine; mi: Myoinositol; MQ: Memory quotient; rPWM: Right prefrontal white matter; lPWM: Left prefrontal white matter; biThalamus: Bilateral thalamus.

The core take-home message from this study is that metabolic abnormalities in the PWM may play a significant role in the development of depressive symptoms, particularly those related to cognitive impairment. However, it is essential to acknowledge the complex interplay between biological factors and clinical presentation in psychiatric disorders. The study's findings highlight the need for further research to clarify the specific mechanisms underlying this relationship and to explore the potential impact of medications and other factors on the development and course of depression. These results present intriguing possibilities that warrant further exploration and could significantly contribute to the development of contemporary psychiatric diagnostic tools.

Based on the entire scope of such findings, scientific psychiatry is currently within technical reach.