2023 Impact Factor
2023 Impact Factor
According to the World Health Organization [1], major depressive disorder (MDD) has the fourth highest prevalence among all disorders in the world, and results in a high economic burden, which ranks third in the world. A survey on the prevalence of mental disorders among South Korean children and adolescents found that MDD (7.4%) had the third highest prevalence [2]. The prevalence of MDD during childhood is approximately 2%; however, it increases to 4−8% during adolescence. Spe-cifically, the prevalence increases drastically in late adolescence, at an average age of approximately 15 years [3,4]. If MDD during adolescence is not treated properly, it can lead to various problematic behaviors such as substance abuse, poor academic performance, physical health problems, running away from home, refusal to attend school, and even suicide in severe cases [5]. Specifi-cally, depression is a major risk factor of suicide attempts among adolescents [6]. Kovacs et al. [7] compared patients diagnosed with MDD with patients diagnosed with other mental disorders and found that children diagnosed with MDD had a higher risk for suicide attempt during adolescence. Mental disorders during adolescence have different patterns of onset depending on the individual’s age, with the symptoms becoming more like those of adults as adolescents age [2].
The period of adolescence, when growth hormones increase by approximately 2−3 times compared with previous developmental stages, is the second stage of rapid brain development [8,9]. Hormones affect brain development: hormonal organization plays a role in creating the brain structure and hormonal activation changes the brain function at specific periods [10,11]. Both hormonal organization and activation effects appear during adoles-cence [12]. In addition to hormones, structural maturation of gray matter and white matter tracts, which support higher cognitive functions such as cognitive control and social cognition, is achieved. This maturation is associated with greater strengthening and separation in the structure and function of the brain network. In contrast to the development of self-control abilities, the subcortical responsiveness of adolescents, which is a part of emotions and rewards, explains their greater sensitivity to social impact contexts [13]. Neuroimaging technology has demonstrated functional and structural changes in the brain during adolescence [14]. Thus, psychiatric attention is needed during this stage of development, and early diagnosis of and treatment for MDD are important. Since adolescence is a time that cognition, emotion including body growth are developed sharply at 16 years and depression in adolescents increases after the age of 15, it can be divided by 12−15 years old and 16−18 years [15].
To date, mental disorders have been diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), or the International Clas-sification of Diseases, Eleventh Revision, based on the symptoms explained to doctors by patients or the symptoms observed by doctors. However, this method of diagnosis faces some problems, such as requiring much time for accurate diagnosis or risking a diagnostic error [16]. Such characteristics of MDD call for the need for a new clinical approach for diagnosis and treatment. Moreover, because early treatment of MDD has a positive effect on prognosis, tools for accurate early diagnosis are needed [17]. Neuroimaging technologies, such as electroence-phalogram, functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS), are widely used as biomarker tools that can help assess and diagnose the symptoms of patients with mental disorders [18-23]. Regarding MDD, reduced oxygenated-hemo-globin (oxy-Hb) level during cognitive activation has been proposed as a potential biomarker [24]. According to some studies that used neuroimaging technology to investigate brain functions in depressive patients, reduced blood flow in the prefrontal cortex is associated with reduced activity in the cingulate cortex [25]. Most fMRI studies on adults reported that patients with MDD have reduced activity in the left frontal region [23]. In fNIRS studies, patients with MDD showed decreased oxy-Hb level in the frontal lobe during the performance of cognitive tasks, such as the Verbal Fluency Test (VFT), compared with healthy controls [26]. fNIRS studies also found that older adults with depressive symptoms displayed reduced executive functions owing to decreased activities in the frontal lobe [27]. Compared with other assessment tools, fNIRS offers several advantages. Since it is non-invasive, there is no radiation exposure and it has high spatial and temporal resolution. Moreover, it is useful for eva-luating children and teenagers because it can be implemented in a comfortable position without much preparation in a short time. It is one of the neuroimaging techniques that is relatively inexpensive compared to other devices, can directly measure neural activity, alongside mea-suring hemodynamic and metabolic responses associated with neural activity. If significant results are achieved through this easy-to-carry tool, it is expected to be used in the clinical field due to its aforementioned advantages [19,28,29]. In addition, a previous study of adolescents suffering from depression confirmed that fNIRS could be used as a practical tool in the clinical field after further validation [29]. This shows that fNIRS can be used as a potential biomarker for MDD adolescents.
There have been many studies on adults with MDD; however, only a limited number of fNIRS studies exist on adolescents with MDD. One such study identified activation of the frontopolar prefrontal cortex (FPC) [30]. Since this study was limited to adolescents aged 12−15 years, additional studies on adolescents with a broader age range are needed. A systematic review of 64 studies that used fNIRS found that all patients in all studies were adults [19]. In this study, adolescents with rapidly developing brains were divided into those in early and those in late adolescence, and it was hypothesized that oxy-Hb level in the frontal lobe would be significantly reduced in participants in late adolescence. Accordingly, the study used fNIRS to investigate the effects of severity of depression on the frontal lobe according to adolescents’ age.
The frontal lobe is responsible for executive functions, including maintaining concentration, selecting appropriate stimuli, and responding [31]. Among the various areas in the frontal lobe, our study focused on the right dorsolateral prefrontal cortex (RDLPFC), which is the area most sensitive to motor impulsivity; notably, its activity suggests that it can be an indicator of the personal ability to inhibit responses [32]. Highly depressed patients with MDD tend to have more impulsive behavior; increased impulsivity is associated with functional impairment in the frontal lobe [33,34]. Among various areas of the frontal lobe, we examined how RDLPFC changes according to the severity of depression.
The objective was to identify the correlations between the severity of depression and changes in oxy-Hb level in eight frontal lobe regions by age in adolescents with MDD and identify the potential of fNIRS as a potential biomarker tool to be helpful to future studies.
This study retrospectively reviewed data on 30 adolescents aged 12−18 years who were diagnosed with MDD according to DSM-5 through outpatient visits to the De-partment of Psychiatry at Soonchunhyang University Seoul Hospital between January 2018 and June 2021. Adoles-cence is a time when the brain develops rapidly. Since there are functional and structural changes in the brain during this period, participants were divided into two groups by age: 12 participants were aged 12−15 years and 18 were aged 16−18 years [8,9,14]. Ten adolescents were taking medication during the test (escitalopram oxalate: 4; sertraline: 4; sodium valproate: 2; methylphenidate: 1; aripiprazole: 3; lamotrigine: 3; propranolol: 1; quetiapine fumarate: 1; trazodone: 1; alprazolam: 1; and buspirone: 1). Based on previous studies reporting that fNIRS is a potential biomarker tool for MDD that is unaffected by medication, use or non-use of medication was not differentiated [26,35]. Sociodemographic information such as age, sex, and dominant hand was collected for all partici-pants. Moreover, VFT was performed using fNIRS for objective assessment of cognitive and brain functions. This study was conducted with approval from the Institutional Review Board of Soonchunhyang University Seoul Hos-pital (2021-11-002). Informed consent was collected from all participants.
CDI is a tool for measuring depressive symptoms in children [36]. CDI was modified from the Beck Depres-sion Inventory for adults to be suitable for children aged 7−17 years, and the Korean version was adapted accordingly [37]. This self-reporting scale consists of 27 items, and respondents are asked to select the one answer that best describes their feelings over the past two weeks. Each item is rated on a scale of 0−2 points, with higher scores indicating more severe depression. It consists of five sub- factors: negative mood, physical symptoms, ineffectiveness, interpersonal problems, and externalization [38]. A score of 22−25 points indicates mild depression, 26−28 points indicates moderate depression, and ≥ 29 points indi-cates severe depression. In Cho and Lee [37], Cronbach’s α for internal consistency was 0.88, and Pearson’s correlation coefficient for test‒retest reliability was 0.82.
fNIRS is a neuroimaging technique that hemodynamically measures the frontal lobe of the brain under situations such as cognition, thinking, exercise, and emotion [39]. This non-invasive method measures hemodynamic changes in brain activity by emitting near-infrared (NIR) light that does not harm the human body and by receiving returning light attenuated according to the levels of oxy-Hb and deoxygenated-hemoglobin (deoxy-Hb) [40]. After NIR light (650−950 nm, suitable for non-invasive measurement owing to high permeability in the scalp) is emitted, light returning to the scalp surface after scattering can be measured using a detector [28,41].
EquipmentThe fNIRS equipment used in this study was NS’1- H20AM, which is a multichannel high density fNIRS device (NIRSIT; OBELAB). The experimental equipment mea-sured changes in oxy-Hb and deoxy-Hb levels using NIR light with dual laser wavelengths of 780 nm and 850 nm [42]. The device is an easy-to-wear piece of headgear with a curved surface on the outside. Inside the device are rubber stoppers that enable the emitter and detector sensors to be attached securely to the forehead. It consists of 32 detector sensors with blue terminals and 24 emitter sensors with red terminals separated by 3 cm. Pairs of detector and emitter sensors consisted of 48 channels in the frontal cerebral cortex region at 1.5 cm deep in the scalp of the measurer. As shown in Figure 1 and Supplementary Table 1 (available online), the frontal lobe region was divided into eight Brodmann areas, and the change in oxy-Hb level in each area was measured. The relative hemodynamic change of each channel was measured using the Modified Beer–Lambert Law. Additionally, the differential pathlength factor (DPF) values in this study were 6.0 at 785 nm and 5.2 at 850 nm. The DPF obtained experi-mentally by Frequency Domain-NIRS or Time Domain-NIRS can be multiplied by the source-detector distance to estimate the path length within the entire sampling area. How-ever, if DPF data are not available, researchers may rely on other options that do not use the mean path length to extract concentration variations from the Beer–Lambert law.
VFT involves the task of saying words that begin with a specific consonant, as many as possible, within a set time. This study chose VFT as the cognitive task based on a previous study that demonstrated relative decrease in oxygen saturation in the left frontal lobe of depressive patients during VFT [18]. VFT was administered using E-prime 3.0, measuring changes in oxygen saturation during the test. All participants sat comfortably in a chair and were instructed to minimize head movement. VFT consisted of 30 seconds of rest, 30 seconds of control task, 60 seconds of activity tasks, and 30 seconds of control task (Fig. 2). Before starting the task, the tester provided the following explanation to participants. During 30 seconds of the control task, participants were instructed to repeatedly make “ah,” “ae,” “ee,” “oh,” and “ooh” sounds at an appropriate tempo. During 60 seconds of the activity task, participants were instructed to say words that begin with specific consonants presented, as many as possible. They attempted to say words that begin with the consonants “g,” “s,” and “y,” as many as possible, within 20 seconds each. The number of words spoken during the activity task was recorded and confirmed by the tester.
All statistical analyses were performed using IBM SPSS Statistics 27.0 (IBM Corp.). Participants were divided into two groups based on age: 1) the younger MDD group (adolescents with MDD who were aged 12−15 years) and 2) the older MDD group (adolescents with MDD who were aged 16−18 years. A duration of 30 seconds of control task was set as the baseline, after which the activity task was divided into three stages of 20 seconds each of “g,” “s,” and “y” to establish four stages, which were set as “time” variables. First, the demographic characteristics of the adolescents with MDD (age, sex, and dominant hand), psychiatric evaluation results, and VFT score were recorded using descriptive statistics. Second, the correlations between the changes in oxy-Hb level in eight areas of the frontal lobe and psychiatric characteristics were analyzed using Pearson’s correlation coefficients. Third, considering repeated measures, the VFT task was divided by time, and generalized estimation equations (GEEs)—an expanded version of the conventional generalized linear model (GLM)—were used [43]. GEEs are increasingly used to analyze longitudinal and other correlated data; notably, they have been used to estimate parameters of GLMs that may have unmeasured correlations between observations at different time periods [43]. The analysis was performed with age groups (younger MDD and older MDD groups) and four-time stages as factors and CDI as covariates. At the time of analysis, nonparametric tests were used and Bonferroni multiple correction was applied. Significance was set to p < 0.05.
The demographic characteristics of participants are shown in Table 1. The mean CDI scores indicate moderate depression in both groups.
Changes in oxy-Hb levels during VFT are shown in Table 2. Figure 3 shows the overall changes in oxy-Hb levels in the younger and older MDD groups during 60 seconds of VFT. While Table 2 shows no significant differences between the two groups in eight frontal regions, Figure 3 shows that the overall changes in oxy-Hb levels were more active in the older MDD group than in the younger MDD group during 60 seconds of VFT.
Correlations between changes in oxy-Hb level in the RDLPFC and CDI score over time are shown in Figure 4. At Time 1, the correlation between changes in oxy-Hb level in the RDLPFC and CDI score in the younger MDD group was non-significant (p = 0.2) but negative (r = −0.4). The correlation between changes in oxy-Hb level in the RDLPFC and CDI score in the older MDD group was also non-significant and negative (p = 0.97; r = −0.009). At Time 2, the correlation between changes in oxy-Hb level in the RDLPFC and CDI score in the younger MDD group was significant and positive (p = 0.049; r = 0.58). The correlation between changes in oxy-Hb level in the RDLPFC and CDI score in the older MDD group was also non-significant but negative (p = 0.36; r = −0.23). At Time 3, the correlation between changes in oxy-Hb level in the RDLPFC and CDI score in the younger MDD group was non-significant but positive (p = 0.12; r = 0.47). The correlation between changes in oxy-Hb level in the RDLPFC and CDI score in the older MDD group was also non-significant but negative (p = 0.06; r = −0.46). Lastly, at Time 4, the correlation between changes in oxy-Hb level in the RDLPFC and CDI score in the younger MDD group was non-significant but positive (p = 0.2; r = 0.4). The correlation between changes in oxy-Hb level in the RDLPFC and CDI score in the older MDD group was also non-significant but negative (p = 0.27; r = −0.27).
The results of applying GEE for changes in oxy-Hb level in the RDLPFC are shown in Table 3. As VFT was performed over time, GEE analysis on changes in oxy-Hb level in the RDLPFC was performed after giving due consideration to the time-series measurement of participants’ characteristics. While the difference over time was not significant (β = −0.1, SE = 0.18, p = 0.6), there was a significant difference between the groups according to age (β = −2.92, standard error [SE] = 1.08, p = 0.007). The interaction between the two age groups and CDI scores was significant (β = 0.11, SE = 0.04, p = 0.03).
The present study measured changes in oxy-Hb level in adolescents with MDD during VFT to identify the difference in the severity of depression according to age. Unlike the younger MDD group, the older MDD group showed a negative correlation between changes in oxy-Hb level in the RDLPFC and the severity of depression. Moreover, the GEE analysis results showed a significant difference in the response rate of change in the oxy-Hb level in the RDLPFC according to the severity of depression in the two age groups during the VFT task. The younger MDD group showed an increased oxy-Hb level in the RDLPFC with increases in the severity of depression, whereas the older MDD group showed a decrease in the oxy-Hb level in the RDLPFC with increases in the severity of depression. Since adolescence is a time when growth hormones increase and structural maturity of the brain takes place, the subjects in our study were divided into two groups by age and compared.
Previous studies support the current findings [19,44-46]. In a study that used fMRI to compare adults and adolescents, adolescents showed drastically decreased activities in the DLPFC, ventromedial PFC, posterior cingulate, and temporoparietal junction compared with adults [19,44-46]. In a previous study on adolescents, the mean age was 16.26 years, which would correspond to the older MDD group in this study, and low activity was found in the DLPFC, which was partially consistent with the findings of this study [44]. In some fNIRS studies on adults, the results were like those of the older MMD group in this study. In one Japanese study, a negative correlation was found between changes in oxy-Hb level in the RDLPFC and total score on the Hamilton Rating Scale for Depression 21- item, which indicates the severity of depression during VFT [45]. In another study that compared adult patients with the MDD group and healthy control group, there was much less change in oxy-Hb levels in the RDLPFC, OFC, and RFPC as depression became more severe [46]. In fNIRS studies on patients with MDD, adult MDD groups consistently showed weaker hemodynamic changes compared with the healthy control groups [19]. Considering that the older MDD group had more similarities with adult brain development than the younger MDD group, these studies support the findings in this study. Such findings suggest that brain development in the older MDD group is very similar to that of adult patient groups.
An fNIRS study by Papasideris et al. [47] reported that changes in oxy-Hb level in the frontal lobe associated with depression and anxiety symptoms were stronger in older adolescents than in younger adolescents, which con-tradicted the findings in this study. There may be many reasons why the prior results were different from those in this study. Unlike this study, in which most participants were women (77.78%), Papasideris et al. [47] had a higher percentage of male participants. In addition, the tasks performed during psychiatric evaluation and fNIRS measurement were different, which may have produced different results. Papasideris et al. [47] also used a multi-source interference task (MSIT), whereas this study used VFT. Since MSIT is, in principle, a task used to evaluate Attention- Deficit/Hyperactivity Disorder subjects, it seems to show different results from this study using VFT. Just as in this study, previous studies also demonstrated a relative decrease in oxygen saturation in the frontal lobe during VFT [18]. Moreover, as a validated test for identifying executive function, most existing fNIRS studies on adult patients with MDD used VFT and found distinct differences in neuroimaging responses between the patient group and healthy control group [48]. However, it is necessary for future studies to use various cognitive tasks other than VFT during fNIRS measurement. A study by Lee et al. [49] on young adults with MDD who have suicidal ideation focused on the LVLPFC, unlike this study. More drastic decrease in oxy-Hb level in the LVLPFC was associated with greater suicidal ideation. Lee et al. [49] included a healthy control group, and none of participants in the patient groups had a history of taking medication, unlike in this study. Moreover, different results may have appeared because the severity of suicidal ideation was also con-sidered. In another fNIRS study of adolescents aged 12−15 years, after six weeks of treatment, adolescents with MDD showed improved activity in the FPC [30]. That study considered the effects of drug therapy on hemodynamic response; only 10 participants had depression. Future studies should use a larger sample size and consider drug therapy in examining specific areas of the frontal lobe.
While the older MDD group showed similar results to the adult MDD group, the younger MDD group showed different results. This is presumably because the brains of the younger MDD group were more immature than those of the older MDD group. According to previous studies on event-related potentials, which have been widely used in brain development research [50,51], P300 latency decreased from childhood to adolescence [51-53]. P300 latency, which is sensitive to changes in nerve cells owing to development and aging, increases over time and can provide useful information about development [53-55]. Specifically, it is inversely proportional to age owing to brain maturation, including cognitive development in children and adolescents [52,56].
This study had some limitations. First, it had a small sample size with only adolescents with MDD from a single center. Therefore, there are limitations in generalizing the findings. Future studies should employ larger sample sizes and recruit from multiple centers while including a healthy control group. Second, this study did not consider the comorbidities of adolescents with MDD. Third, since ten subjects were taking some medications as mentioned in methods, it is necessary to consider hemodynamic changes caused by medications in subsequent studies. Fourth, the number of tasks performed was limited to just one. Other cognitive tasks can produce different patterns in adolescents with MDD; thus, it is necessary to conduct future studies with more cognitive task variety. Fifth, at the time of analysis, both the younger and older MDD groups used general-purpose DPF, not their optimal DPF, and this can be analyzed without dividing DPF. Sixth, following previous studies, this study did not consider skin blood flow; however, several approaches have been developed recently to eliminate the effects of extracranial tissue. Therefore, skin blood flow should be considered using recently developed approaches [45,57]. Seventh, correlation analyses yielded no significant results; however, considering the small sample size, GEE—an expanded version of the conventional GLM—was used to estimate the regression analysis coefficients. Therefore, caution is needed when interpreting the results. Lastly, there is a limit to controlling and interpreting whether the results of this study are due to the effects of normal development and age-related brain maturity rather than the age-specific aspect of depression. Previous studies have shown that the brain development of normal and depressed patients may be different because they were judged by high frontal alpha asymmetry in MDD patients with higher depression than the normal control group [58]. Therefore, we conducted a study on adolescents with MDD, which may differ from those with normal brain development. However, follow-up studies will need to consider both brain development in normal control groups by age and brain development in MDD.
Despite these limitations, this study identified changes in the oxy-Hb level in the RDLPFC according to the severity of depression in adolescents with MDD by age. The findings suggested that the older MDD group, compared with the younger MDD group, had hemodynamic changes in the frontal lobe that were more similar to those of adults. Through this study, we confirmed the utility of fNIRS in evaluating frontal lobe development changes. To generalize the findings, future studies should use a large sample size and a healthy control group to identify changes in oxy-Hb levels in eight areas in the frontal lobe through more objective assessment tools and cognitive tasks, while screening for comorbidities, as well.
No potential conflict of interest relevant to this article was reported.
Conceptualization: Jeong Eun Shin, Yeon Jung Lee. Data acquisition: Jeong Eun Shin, Yun Sung Lee, Seo Young Park, Mi Young Jeong. Formal analysis: Jeong Eun Shin, Yeon Jung Lee. Supervision: Yeon Jung Lee. Writing: Jeong Eun Shin. Data analysis and analysis advice: Jong Kwan Choi, Ji Hyun Cha. Approval of the final manuscript: all authors.
Fig. 1. Forty-eight channel of func-tional near-infrared spectroscopy and Brodmann area.
Fig. 2. Verbal fluency test protocol.
Fig. 3. Changes in oxygenated- hemoglobin concentration of the prefrontal cortex during the Verbal Fluency Test in younger and older adolescents with major depressive disorder (n = 30).
Fig. 4. Correlation between oxygenated-hemoglobin concentration changes in the right dorsolateral prefrontal cortex and CDI by time.
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Author ORCID Information Jeong Eun Shin Yun Sung Lee Seo Young Park Mi Young Jeong Jong Kwan Choi Ji Hyun Cha Yeon Jung Lee
Funding Information Ministry of Science and ICT, South Korea Soonchunhyang University National Research Foundation of Korea |
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