Skip Navigation LinksHome > March 2014 - Volume 30 - Issue 1 > Biological Markers in Noninvasive Brain Stimulation Trials i...
Journal of ECT:
doi: 10.1097/YCT.0b013e31828b34d8
Reviews

Biological Markers in Noninvasive Brain Stimulation Trials in Major Depressive Disorder: A Systematic Review

Fidalgo, Thiago M. MD*†; Morales-Quezada, J. Leon MD, MSc*‡; Muzy, Guilherme S. C. MD§; Chiavetta, Noelle M. BS*; Mendonca, Mariana E. PT*; Santana, Marcus V. B. PT*; Goncalves, Oscar F. PhD; Brunoni, Andre R. MD§; Fregni, Felipe MD*

Free Access
Article Outline
Collapse Box

Author Information

From the *Laboratory of Neuromodulation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA; †Department of Psychiatry, Federal University of São Paulo, São Paulo, Brazil; ‡Faculty of Health and Life Sciences, De Montfort University, Leicester, United Kingdom; §Santa Casa Medical School, São Paulo, Brazil; and ∥Neuropsychophysiology Lab, CIpsi, School of Psychology, University of Minho, Braga, Portugal.

Received for publication August 7, 2012; accepted February 1, 2013.

Reprints: Felipe Fregni, MD, PhD, Laboratory of Neuromodulation, Spaulding Rehabilitation Hospital, Harvard Medical School, 125 Nashua Street #727, Boston, MA 02114 (e-mail: fregni.felipe@mgh.harvard.edu).

These authors contributed equally to the article.

Dr Fregni is granted by The Christopher and Dana Reeve Foundation, The Ruth Judy Goldberg Foundation, The National Institutes of Health, and by the American Heart Association.

Collapse Box

Abstract

Objectives: The therapeutic effects of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation in patients with major depression have shown promising results; however, there is a lack of mechanistic studies using biological markers (BMs) as an outcome. Therefore, our aim was to review noninvasive brain stimulation trials in depression using BMs.

Methods: The following databases were used for our systematic review: MEDLINE, Web of Science, Cochrane, and SCIELO. We examined articles published before November 2012 that used TMS and transcranial direct current stimulation as an intervention for depression and had BM as an outcome measure. The search was limited to human studies written in English.

Results: Of 1234 potential articles, 52 articles were included. Only studies using TMS were found. Biological markers included immune and endocrine serum markers, neuroimaging techniques, and electrophysiological outcomes. In 12 articles (21.4%), end point BM measurements were not significantly associated with clinical outcomes. All studies reached significant results in the main clinical rating scales. Biological marker outcomes were used as predictors of response, to understand mechanisms of TMS, and as a surrogate of safety.

Conclusions: Functional magnetic resonance imaging, single-photon emission computed tomography, positron emission tomography, magnetic resonance spectroscopy, cortical excitability, and brain-derived neurotrophic factor consistently showed positive results. Brain-derived neurotrophic factor was the best predictor of patients’ likeliness to respond. These initial results are promising; however, all studies investigating BMs are small, used heterogeneous samples, and did not take into account confounders such as age, sex, or family history. Based on our findings, we recommend further studies to validate BMs in noninvasive brain stimulation trials in MDD.

Major depressive disorder (MDD) is a common condition that is widespread in the population. Community-based surveys conducted in several countries using International Classification of Diseases, 10th Revision criteria have shown a lifetime prevalence of MDD ranging from 6% to 12%, with an annual prevalence of 3% to 11%.1–4 Major depressive disorder is a chronic, recurrent disorder, with nearly 80% of patients relapsing after the treatment of an episode.5 Finally, about one third of patients have treatment-resistant depression, which is defined as the failure to achieve adequate response of symptoms after 2 or more antidepressant treatment trials.6,7 In fact, the high prevalence of treatment-resistant depression associated with failure to respond to antidepressants is an important concern when managing major depression.

During the last decades, the understanding of the pathophysiologic mechanisms of different psychiatric disorders has increased dramatically. Consequently, there have been gains in available pharmacological, psychological, and physical treatments.8–10 In this context, noninvasive brain stimulation techniques, such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have received special attention as potential clinical tools.11,12 Repetitive TMS (rTMS) is a commonly used type of TMS that consists of using varying magnetic fields to induce cortical electric currents to a specific brain area to modulate cortical excitability.12 On the other hand, tDCS is the application of a weak constant electrical current through the skull and into cortical areas via cranial (and also extracephalic) electrodes.12 The aim in both types of stimulation is to induce therapeutic neuroplasticity through the application of electrical currents in the brain.

Past studies have revealed encouraging results for the therapeutic use of these techniques in the mental health field; however, results are still mixed despite many positive clinical outcomes.11,12 One reason for the lack of more robust results is the variety of stimulation parameters being applied because there is still no consensus on the optimal parameters of stimulation. One possible resolution to this issue is the use of biological markers (BMs) as a guide to stimulation parameters. In addition to shedding light on the mechanisms of action, BMs are useful in psychiatry as they provide an objective marker, therefore providing a more reliable (uniform) evaluation of biological state.13,14

Biological markers are defined as biochemical, physiological, or anatomical traits that are specific to particular conditions. An important aim of BM discovery is the detection of disease correlates that can be used as diagnostic tools. Ideally, BMs should have predictive power, should be available during routine assays, and allow the identification of individuals at risk. Furthermore, useful markers should allow the monitoring of progress of not only the disease, but also its treatment. In the field of psychiatry, they are of great interest because they can aid researchers in understanding the cause of diseases such as depression or schizophrenia and can also serve as surrogate outcomes to measure the efficacy of treatments.15 Serum levels of several hormones, functional magnetic resonance imaging (fMRI), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and electroencephalography (EEG) are some of the techniques that have been used in psychiatric trials to measure BMs.13,14

Because of the importance of BMs and surrogate outcomes to provide more information, guide treatment, and provide a deeper understanding for neurophysiologic mechanisms of noninvasive brain stimulation techniques, we aimed to review the TMS and tDCS trials in MDD using BMs as outcomes. Our main goal was to review the most commonly utilized BMs to provide insights for future research.

Back to Top | Article Outline

METHODS

We screened all articles that used TMS and tDCS as an intervention for MDD. We searched for all articles published before November 2012 using the following databases: MEDLINE, Web of Science, Cochrane, and SCIELO. We also examined reference lists in systematic reviews and retrieved articles that seemed to fulfill our criteria.

Our search strategy included (TMS OR tDCS) AND (depressive disorder). The reviewed studies are shown in Table 1.

Table 1
Table 1
Image Tools
Back to Top | Article Outline
Search Criteria

The following inclusion criteria were adopted: (i) article written in English; (ii) studies using TMS or tDCS as an intervention, including clinical trials and case reports, for MDD; (iii) studies using any BM as an outcome (main or secondary outcome); (iv) studies conducted in humans; and (v) studies published before November 2012.

Back to Top | Article Outline
Positive Versus Negative Finding

In our research, we define positive findings when there was a significant clinical improvement. On the other hand, negative findings are the clinical results that were not significant.

Back to Top | Article Outline
Data Extraction

Data were extracted independently by the authors (G.S.C.M., T.M.F., M.E.M., M.V.B.S., and N.M.C.) using a structured form. The following variables were extracted: (1) author and year of publication; (2) number of patients studied in the article; (3) parameters of stimulation (ie, frequency, intensity, duration, and number of sessions); (4) study design; (5) main findings; and (6) conclusion. The discrepancies were resolved by consensus, and the corresponding author (F.F.) was consulted when needed.

Back to Top | Article Outline
Data Analysis

We described results qualitatively as there was no quantitative information to perform a meta-analysis.

Back to Top | Article Outline

RESULTS

Overview

We found 1234 references in our preliminary search. We initially selected articles that used TMS or tDCS as an intervention for MDD. Of those, 1008 articles were excluded in the first analysis, and 239 articles were further reviewed. Of the 235 remaining articles, 52 articles met our inclusion criteria, and data were extracted from all of them. All articles were published between 1999 and 2012, and all used rTMS.

The parameters used most frequently were 10 daily sessions of brain stimulation (20 articles [38.5%]) at 100% of the motor evoked potential (MEP) (17 articles [32.7%]) with frequency of 10 Hz (10 articles [19.2%]). Interestingly, most did not use a sham group, which was present in only 17 of the articles (32.7%). Crossover (9 articles [17.3%]), randomized clinical trials (16 articles [30.1%]), and open-label trials (22 articles [42.3%]) were the most common experimental designs used and within these trials; most had small sample sizes (the highest sample size was n = 90).

With the exception of 3 articles, the BM was the main outcome studied. In all of the articles, the BMs were assessed along with other clinical outcomes, such as the Hamilton Depression Rating Scale (HDRS) and the Montgomery-Åsberg Depression Rating Scale.

In 16 of the reviewed articles (30.8%), there was no significant correlation between BMs and clinical outcomes; however, in some of the articles such as the one by Szuba et al,63 there was a significant difference between the BMs’ assessment before and after brain stimulation. Interestingly, all articles reached positive findings in the main clinical rating scales; however, a placebo effect is possible because many of these studies did not have a control-sham group.

Back to Top | Article Outline
Biological Markers

We grouped the BMs into the following categories: neuroimaging, electrophysiological, and neuroimmunoendocrine studies. Advantages and disadvantages of the selected BMs are summarized in Table 2.16,17

Table 2
Table 2
Image Tools
Back to Top | Article Outline
Neuroimaging Studies

Neuroimaging was the most commonly used BMs and was used in 27 of the 52 reviewed articles (51.9%). Functional magnetic resonance imaging, SPECT, PET, magnetic resonance spectroscopy (MRS), and near-infrared spectroscopy (NIRS) were among the available neuroimaging modalities and are discussed below.

Back to Top | Article Outline
Functional Magnetic Resonance Imaging

Functional magnetic resonance imaging is a tool that detects regional blood flow in cerebral areas.18 It analyzes variations in signal intensity from hemoglobin according to the blood oxygenation level dependence (BOLD effect). In addition, when combined with TMS, fMRI allows for the mapping of corticocortical and corticosubcortical connectivity in the brain. Despite the fact that combining TMS and fMRI can be technically challenging (due to magnetic interference of TMS and fMRI scanner), it is valuable in that fMRI has good time and spatial resolution and can be repeated without limitation because it does not expose subjects to radioactive tracers, among other advantages.19 In our review, we found 8 fMRI studies.20–24

Functional magnetic resonance imaging studies have shown activity changes in the site of stimulation as well as in distant areas. In fact, the main use of fMRI data is to detect the neural network associated with TMS effects. For instance, in a study using fMRI as its BMs, Fitzgerald et al24 found that the antidepressant effects of TMS are related to a bilateral reduction in task-related prefrontal cortex (PFC) activation. In this case, the subject’s task was to silently articulate words beginning with a standard letter that were presented to him/her. In this context, the task-related deactivation changes observed in the study may represent an optimization of the executive network for planning and reasoning supported by rTMS applications, assuming a pattern of overactivation when performing cognitive process when compared with baseline. The researchers also found that TMS produces a reduction in bilateral PFC activation. Another study by Li et al21 found that TMS was associated with an increase in blood flow at the site of stimulation and in connected limbic regions in a sample of 14 depressed patients. Significant deactivation was found in the right ventromedial frontal cortex. However, because of the small sample size, the different medications, and different dosages, these results cannot be generalized.21 Functional MRI and PET have shown how depressive behavior can be correlated with hypermetabolism of the subgenual cingulate cortex and amygdala,94 as well as hypometabolism of the dorsal PFC and striatal regions93; based on these imaging studies, a “depressive circuit” can be drawn having the amygdala as disinhibited structure due to lesion-like effects at the striatum, PFC, and orbital PFC. It might be possible for rTMS to exert its modulatory influence via white matter tracts, thus being able to regulate the fMRI/PET responses at these structural levels.

Back to Top | Article Outline
PET and SPECT

Positron emission tomography and SPECT are 2 emission tomography techniques that allow for real-time viewing of brain functioning through the detection of gamma rays.18,25 This information is then used to reconstruct a tridimensional image of active brain areas. Although it maps more limited brain areas, SPECT presents gamma rays with longer half-lives and does not require a cyclotron for image generation as does PET. Thus, it is less expensive and more easily obtained. Moreover, the longer half-lives make it possible for researchers to observe biological processes in vivo for several hours or days after the administration of the compound.18,25 In our review, we found 2 studies that used PET, 10 studies that used SPECT, and 1 study that used both PET and SPECT.26–34

Similar to fMRI, PET studies also found clinically related changes in cerebral blood flow (CBF) in the stimulated area or related areas, such as the cingulate cortex. Kito et al,26,27 studying 14 treatment-resistant patients, found a significant increase in CBF in the left dorsolateral PFC (DLPFC), according to their SPECT images after TMS stimulation. This increase also correlated to an increase in subgenual cingulated and the limbic-paralimbic regions. These alterations were clearly correlated with a decrease in HDRS. In a PET study, Baeken et al33 found that a higher baseline brain glucose metabolism of the anterior cingulate cortex was a marker of a positive intervention response. In this study, 21 treatment-resistant depressed patients were included. Small sample size and the absence of a sham group are the 2 main limitations of these and most of the other PET and SPECT studies included.

Although imaging studies are demonstrating promising evidence for the understanding of MDD, the previously mentioned techniques rely on regional changes of CBF and glucose metabolism. Consequently, we can assume these dynamic alterations are the result of activity-dependent terminal field synaptic transmission. If the network activity is increased, then augmented neurotransmission via afferent pathways originating at the observed structure or distally interconnected circuits will demand an elevation of metabolic consumption and increases in CBF. Imaging studies have demonstrated that this pattern of changes can be modulated by either rTMS or tDCS; nevertheless, studies using fMRI, PET, or SPECT still lacking the effect size needed to reach the desired sensitivity or specificity. Temporal and spatial resolutions are unique characteristics of functional imaging studies; to reliably determine the functional area, a high signal-to-noise ratio is critical to map accurately those foci being imaged for functional assessment. Therefore, it is important to understand how specific those areas really are for MDD involvement. Using traditional BOLD methodology for resolution, increases in neural activity will induce increases in tissue metabolic demand, and this will yield to a certain spatial specificity for metabolic changes. However, those changes also will affect and modulate hemodynamic responses, including CBF, cerebral blood volume, and venous oxygenation levels; thus, the assessment of these parameters will enhance dramatically the specificity and sensitivity for structure-related pathology. The advancement and refinements of such techniques will permit the development of receptor-binding neurotransmitter for PET utilization or high-resolution CBF and discriminatory hemodynamic assessment, which in turn might allow better imagining resolution in real time and to identify the mechanistic properties of the MDD involved structures, also by getting a better categorization of these changes; fMRI, PET, and SPECT will become specific and sensitive enough to consider them as reliable BM.

Back to Top | Article Outline
Magnetic Resonance Spectroscopy

Another brain imaging technique, MRS, allows a thorough view of brain chemical activity.35,36 Using spectroscopic analysis, specific brain metabolites such as γ-aminobutyric acid (GABA) and glutamate can be investigated by examining the area under each peak produced.19,36 When MRS is combined with TMS, it is also possible to examine the underlying mechanisms of long-term changes in brain excitability and to investigate the metabolic and neurotransmitter effects of rTMS and tDCS, directly and noninvasively.16,19 In our review, we found 1 MRS study.37

Because MRS provides levels of neurochemical metabolites, it provides valuable information also on baseline states. In fact, Luborzewski et al37 used MRS to assess glutamate concentration on the DLPFC of the patients before and after rTMS. According to their findings, 6 of 17 patients responded to the treatment, and in those, the baseline concentrations were lower than those for nonresponders. After treatment, these concentrations were elevated in responders and decreased in nonresponders. However 1 main limitation of MRS is that the location of stimulation needs to be determined a priori.37

It is important to notice that in this study the previously mentioned changes happened in cases of unipolar depression, where most studies have reported decreased glutamate levels, whereas subjects with bipolar depression have shown elevated glutamate/glutamine levels; thus, the abnormalities reported in unipolar and bipolar seemed to have an opposite hypodirectionality/hyperdirectionality. Although there are no MRS studies reporting metabolite changes in bipolar or unipolar depression using tDCS, it would be attractive to evaluate if polarity-dependent tDCS modulation is able to modify neurochemical signaling in MRS as TMS already showed. In the case of MDD, the choline (Cho) peak has been considered a BM for alterations of signal transduction at the membrane metabolic level98; nevertheless, inconsistent results among studies are still the main obstacle to consider this metabolite as a good neurochemical marker for TMS or tDCS effects in neural tissue. A comprehensive MRS assessment must be performed when estimating BMs for MDD and noninvasive brain stimulation. These should include a varied range of neurochemicals, such as N-acetyl aspartate, myoinositol, glutamate and N-methyl-D-aspartate, glutamate and glutamine, choline, and GABA.

Back to Top | Article Outline
Near-Infrared Spectroscopy

Near-infrared spectroscopy is a neuroimaging technique that allows for the visualization of hemodynamics in the brain. One study by Eschweiler et al38 examined such changes within the brain before and after rTMS. After two 5-day periods of stimulation, Eschweiler et al38 observed significant decreases (−5.4 average points on the HDRS) in feelings of depression in their patients and an absence of task-related increase in hemoglobin concentration at the immediate site of stimulation, but not in other brain areas.38 Near-infrared spectroscopy technology uses the BOLD signal principle to measure changes in deoxyhemoglobin.

A wide variety of both commercial and custom-built NIRS instruments are currently in use. Three distinct types of NIRS implementation have been developed for functional assessment: time-resolved systems, frequency-domain systems, and continuous wave spectroscopy systems, each with its own strengths and limitations. Time-resolved and frequency-domain systems provide information on shifts in both phase and amplitude of the light and are necessary for more precise quantification of functional signals. Continuous wave systems apply either continuous or a slow-pulsed light to tissue and measure the attenuation of amplitude of the incident light.116 Thus, for better characterization of cortical activity response to TMS or tDCS, a frequency-domain system will be preferable because of its specificity for superior parameter assessment and the possibility to reduce physiological noise in response to the stimulation by itself; also, absolute physiological measurements will provide better information than just relative measurements.

Functional NIRS relies on this optical technique to detect changes in the hemodynamic response within the cortex when sensory, motor, or cognitive activation occurs. Following this principle, functional NIRS may be particularly applicable to some of the unique research problems associated with neuropsychiatric disorders.

Back to Top | Article Outline
Electrophysiological Studies

Another method to detect brain activity directly is using electrophysiological methods that have an important advantage of measuring electrical activity directly and thus a better temporal resolution; however, the spatial resolution is usually more limited than that of neuroimaging methods. A total of 12 articles among the 52 reviewed (23%) used electrophysiological outcomes such as EEG and TMS-indexed cortical excitability and saccadic eye movements.

Back to Top | Article Outline
Electroencephalography

Electrophysiological tools such as EEG are also used as BMs.39 Electroencephalography is a graphic representation of the difference in voltage between 2 distinct brain points. Most of the electrical activity measured is generated in the cortex and is captured by volume conduction after overcoming the resistance of the skull and of the scalp.40–42 Several attempts were made to identify surrogate patterns of EEG to some psychiatric disorders, without success.41 In addition, the search for a surrogate pattern remains, trying to correlate EEG alterations with fMRI or PET/SPECT findings. In our review, we found 6 studies using EEG.43–46

Electroencephalographic studies add important information to TMS applications. Because of the detailed information that EEG provides on cortical brain oscillations that is different than fMRI, which detects only a change as compared with a previous time point, EEG has been used also to predict patients who may be responders to TMS treatment. Narushima et al,45 using a LORETA technique, identified that increased low-theta power in the subgenual anterior cingulated cortex was associated with antidepressant response, suggesting that EEG could be used as a predictor for antidepressant response to rTMS among patients with treatment-resistant vascular depression. Arns et al43 also stated a marker of positive response to TMS application by using EEG. The author declared that a high individual α peak function acted as a predictor of response. This seems to be a promising application for EEG to be used to identify surrogates of intervention response.43 Micolaud-Franchi et al100 also reported changes in the parietotemporal α power as predictor of TMS response; however, to reliably use EEG parameters as predictors of treatment, a large database is needed to recognize phenotypic EEG features as BMs of TMS or tDCS response. On the other hand, Price et al44 also explored EEG as a correlate of clinical changes in rTMS treatment of depression and also found no significant difference between patients suffering from depression and normal and clinical control groups. Price et al44 suggest that although they did not find a significance in this study, several other findings provide support to continue research on this topic.44

Electroencephalographic recordings have been long considered, as the activity generated at thalamic level; thus, the conceptualization of the so-called thalamocortical circuits is the foundation for the analysis of healthy and disease EEG patterns; this establishment may not be sensitive enough to accept specific EEG characteristics as BMs in MDD, because the neuromodulatory effects promoted by noninvasive stimulation act at a network level that includes extrathalamic and cortical structures, although new research is focusing in the presence and influence of localized rhythms at cortical, thalamic, and extrathalamic areas, to understand the role of the intrinsic oscillatory properties that any given network can generate, rather than just the spectral analysis of specific frequencies. This is mainly due to the fact that a certain frequency band may ambiguously reflect various conditions or phenomena originating at different locations of the brain. The understanding of these properties will provide a functional meaning for the oscillatory network activity that can be then used as BMs during TMS and tDCS applications; therefore, spatial characteristics can be distinguished from just frequency aspects of the EEG recordings. In the particular case of TMS, an initial disruption of the ongoing network activity will be seen immediately under the coil area and interconnected systems as well. Thus, spatiotemporal changes generated by the evoked TMS stimuli can be detected and measured by EEG network oscillations models. As a result of this, oscillatory network patterns can be described as possible neurophysiologic BMs, although specificity may be a problem due to “multiconnectivity” epiphenomena or the so-called “noise to signal” dilemma. On the other hand, the development of better modeling methods, including those for source localization and the fact that TMS will generate an immediate measurable electrophysiological response, may be the answer for the use of EEG-based BM approach. As for the case of tDCS, spectral analysis of frequency bands can be a more suitable method for BM development, especially when applying quantitative methodology for full EEG analysis; because tDCS effects on the EEG recording are not going to be immediately measurable, mathematical signal characterization coupled with cognitive task could be used for measurements of coherence and synchronization network activity; by taking advantage of the relationship between cognitive processing and network modulation by tDCS, electrographic changes can be measured with a better specificity and sensitivity because network connectivity and oscillations can be either facilitated in the case of anodal or inhibited if cathodal stimulation is being applied.

On the other hand, EEG can also be used as a surrogate for safety. The study by Berman et al46 applied rTMS while using EEG at baseline, before treatment and after treatment. The authors found no differences between different EEG measures, which according to the authors suggest that rTMS under the parameters used is a safe technique. Advances in the use of ongoing EEG recording while stimulation and cognitive tasks are applied in real time can be facilitated by using the methods and technology described by Schestatsky et al47 allowing the continuous assessment of raw signal, and frequency spectrogram analysis as well.

Back to Top | Article Outline
TMS-Indexed Cortical Excitability

Cortical excitability is an individual measure related to the responsiveness of the brain to a stimulus.48 This technique uses a TMS approach to measure cortical excitability by assessing the integrity of central motor pathways.11,12 Those magnetic pulses induce a secondary electric current in the brain that causes cell depolarization. Single-pulse TMS is used to measure motor threshold and MEPs,11,12,48 whereas the paired-pulse technique assesses intracortical inhibition or facilitation, possibly indexing gabaergic and glutamatergic activity, respectively.49 In our review, we found 5 studies using cortical excitability.49–52

One important limitation of TMS studies in depression is that it can measure only excitability of motor and visual cortex; therefore, the information is somewhat limited. However, because TMS has good temporal resolution, it may be an important marker especially to assess interhemispheric differences. In fact, Maeda et al52 showed that patients with major depression presented interhemispheric differences in motor threshold with lower excitability in the left side. This can be related to a change in the balance of neurotransmitters on left hemisphere of the brain.49,52 With the same objective, Bajwa et al49 found that patients with major depression have an imbalance in the right and left prefrontal and motor cortex measured with MEP after the use of rTMS (1 Hz). These differences are related to slow interhemispheric switching mechanisms. Also, this difference was associated with patients with a higher level of disease severity.49 Other studies have also shown that high frequency rTMS can alter the amplitude of MEPs, which was also related with improvement of depressive symptoms.5,50,51 These studies help at some extent for better understanding of the mechanisms related to these diseases and also form of treatment used for depression, correlating neurophysiologic and clinical data.

Back to Top | Article Outline
Saccadic Eye Movement

Saccadic eye movements are the rapid movements of both eyes, which are largely controlled by the PFC in the brain.53 Saccades can be measured through the use of visual targets in guided reflexive tasks, prosaccade tasks, and antisaccade tasks. In guided reflexive tasks, subjects are required to look toward peripheral targets that appear randomly in the left and right visual field. Prosaccade tasks present the subject with 2 targets (one to the right and the other to the left), an arrow that switched direction unpredictably pointed to which target the subject should be looking toward. Finally, antisaccade tasks require the subject to look opposite of the randomly presented target.53,54 In our review, we found 1 study using saccadic eye movements.52

As aforementioned, saccadic eye movements would provide an indirect measurement of prefrontal activity and therefore another useful neurophysiologic index of TMS effects especially when applied to PFC as usually done in depression. Crevits et al53 used the 3 saccade measurement techniques described above to examine the before and after effects of rTMS on saccadic eye movement in patients with depression. In this study, it was found that the use of rTMS over the left DLPFC did not significantly influence reflexive or prosaccade movements. On the other hand, the study did show that rTMS had a shortening effect on the latency of antisaccade movement, suggesting that rTMS may affect certain aspects of saccade movement in patients with depression. Because this was only a pilot study using a small sample population of 11 subjects, the results must be interpreted with discretion.

Back to Top | Article Outline
Neuroimmunoendocrine Studies

In our review, 13 articles measured neuroimmunoendocrine factors, such as serum cortisol, serum thyroid hormones (thyroid-stimulating hormone [TSH] or thyroxine), BDNF (brain-derived neurotrophic factor), homovanillic acid, interleukins (ILs), and sexual hormones such as luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol, progesterone, and dehydroepiandrosterone (DHEA).

Back to Top | Article Outline
Serum Cortisol

Reid and Pridmore55 measured cortisol level using the dexamethasone (DEX) suppression test before and after rTMS. In this setting, the author found out that rTMS was capable of changing DEX suppression test status from positive to negative, showing a link between serum cortisol levels and depression. However, because this is a case report, these findings should be interpreted with caution.

In light of the previous study, Zwanzger et al56 performed a clinical trial similar to that of Pridmore,6 where drug-free patients with treatment-resistant depression were evaluated by the combined DEX–corticotropin-releasing hormone (CRH) test before and after 13 daily sessions of rTMS.6,56 There was a significant time versus group effect for basal cortisol levels, but not for basal adrenocorticotropic hormone (ACTH) levels, and a significant positive correlation between the reduction of HDRS scores after rTMS and the reduction of post-DEX basal cortisol levels. However, there was no significant difference in stimulation patterns of cortisol and ACTH after CRH challenge between responders and nonresponders before and after rTMS treatment. Moreover, the CRH-induced ACTH and cortisol increase did not change significantly after rTMS, even in patients showing a remission of depressive symptoms. These results indicate that the hypothalamic-pituitary-adrenocortical system remains overactive after rTMS treatment, and thus, there may be a high risk for relapse of depressive symptoms in responders to rTMS.57 In this context, serum cortisol may identify patients who may respond to rTMS treatment and may also be useful to identify risk of relapse.

Back to Top | Article Outline
Brain-Derived Neurotrophic Factor

Brain-derived neurotrophic factor is a neurotrophin related to neuronal survival, synaptic signaling, and synaptic consolidation.57 It has been associated with several disorders, such as substance-related disorders, eating disorders, mood disorders, schizophrenia, pain modulation, and epilepsy15,57,59 as it may provide a general index of neuroplasticity. Given the effects of rTMS on neuroplasticity, this biomarker has been investigated; however, it has important limitations such as lack of spatial resolution—in other words, if there is a change in BDNF, it is not possible to determine where these changes were originated.

rain-derived neurotrophic factor has also been studied as a main marker to identify responders to rTMS treatment. Two studies included BDNF as a BM.60,61 In an article by Zanardini et al,61 the authors assessed BDNF serum levels with enzyme-linked immunosorbent assay in 16 patients with treatment-resistant depression before and after rTMS. The study revealed a negative correlation between BDNF serum levels and the severity of the disease as assessed by the HDRS. In addition, they also showed that by using TMS they where able to raise BDNF levels, suggesting a normalizing effect of the rTMS antidepressant treatment. These promising results should be considered with caution, because the sample size in this study is small.61 However, these are important findings that strengthen the link between BDNF and depression. Experimental increases of hippocampal BDNF levels produced antidepressant-like effects in behavioral models of depression,98 whereas an impairment of BDNF signaling produces certain depression-related behaviors and impairs the action of antidepressants97; in this context, BDNF can be considered an ideal BM for stress-related behaviors, cognitive impairments, and promotion of synaptic plasticity within MDD. The increments in the expression of BDNF by rTMS may provide therapeutic neuroprotection against chronic stress in patients with MDD and facilitate plastic changes aimed to modify the occurrence of “depressive circuitry.” Thus, it may be possible for rTMS to induce BDNF expression and possibly reverse some of the neural atrophic changes observed in postmortem studies.93 Direct current stimulation in the rat model has demonstrated modulatory effects on BDNF by increasing its secretion and promoting dependent synaptic plasticity that can be observed in the primary motor cortex and hippocampus as well, although no studies have reported these findings in the DCS depressed animal model yet; it can be reasonable to speculate that tDCS may have also BDNF modulatory effects when applied in subjects with MDD, although more experimental research needs to be performed before we can accept this statement.

In another article by Yukimasa et al,60 BDNF levels were assessed along with catecholamines MHPG (3-methoxy-4-hydroxyphenylglycol) and homovanillic acid (HVA) in 26 treatment-resistant patients. Again, these results suggest that rTMS treatment brings about some improvement in refractory depression, especially for symptoms such as agitation, by influencing MHPG and BDNF. These results are in accordance with previous reports showing that BDNF was increased by various antidepressants treatments. However, this study also has a small sample size and did not use a control group, and the patients were on antidepressants, which are factors that may cloud the effects of TMS.60

Brain-derived neurotrophic factor normalization by rTMS applications may represent itself as optimal electrochemical treatment and a marker of clinical improvement for the depressive disorders. It is important to recognize how the electric stimulation generated by a train of magnetic fields is capable to induce changes of endogenous trophic factors. This transition from externally induced physical forces to endogenous modulated biochemical processes exemplifies the importance of noninvasive stimulation as an adjunctive technique for the management of MDD. To better understand these BDNF findings and to make relevant clinical correlations with the reported rTMS beneficial effects, more research must be done, especially when BDNF physiological variability is considered and rTMS parameters still not completely standardized.

Back to Top | Article Outline
Serum Thyroid Hormones

Serum thyroid hormones may also be a useful biomarker as the hypothalamus-pituitary-thyroid system has also been shown to be dysfunctional in major depression and that antidepressant treatment may revert some of this dysfunctional state.62

Although there is a rationale for using thyroid hormones as biomarkers, results in rTMS trials are mixed. In a clinical trial by Kito et al,63 the serum levels of TSH, fT3, and fT4 of treatment-resistant patients were evaluated before and after rTMS. Clinical improvements were observed as assessed by HDRS. The serum levels of fT3 and fT4 showed no significant differences between the responders and nonresponders; however, TSH levels in pretreatment responders were significantly lower compared with TSH levels in nonresponders. Thyroid-stimulating hormone showed a significant therapeutic efficacy-by-time interaction. Responders and nonresponders were analyzed separately, and the outcomes showed a significant decrease in TSH levels for responders. In addition, the results revealed that TSH levels of responders rose significantly and that TSH levels of nonresponders tended to decrease following TMS treatment sessions.63

Conversely, Szuba et al64 found no significant difference between mood and TSH. Although both mood (measured by HDRS) and TSH levels (measured by radioimmunoassay) increased after active TMS, no cause-and-effect relationship between the two could be demonstrated. Possible reasons for the lack of correlation are the small sample size and late timing of the blood draw leading to less than peak TSH level achieved, or it may also be that mood and TSH levels are unrelated, as no correlation was found in a similar study in healthy subjects.64,65

Back to Top | Article Outline
Dopamine and Serotonin

Dopamine and serotonin are 2 important neurotransmitters that play a role in mood control. Dopamine acts on the mesolimbic and mesocortical circuits in the brain and is responsible for the experience of pleasurable feelings.66–68 The 5-HT systems of serotonin extend throughout the brain and are thought to be involved in many functions such as mood, aggression, feeding, and sleep. Disturbances in the serotonin pathways have been linked to impulsivity, depression, and, in some cases, suicide.69 For these reasons, antidepressant medications seek to regulate these 2 neurotransmitters by inhibiting reuptake to increase their extracellular levels. Although antidepressants work for some, treatment-resistant depression is common (35%–40%), thus the possible role of noninvasive brain stimulation in these patients.67,70

Although neurotransmitter levels may be a very useful biomarker, the main limitation is that these neurotransmitters are measured in the plasma; thus, correlation with brain levels may be decreased. In fact, a study examining TMS in drug-resistant MDD patients by Miniussi et al67 revealed that despite seeing a clinical response after active treatment, no clear relationship could be established between clinical response and biochemical outcomes of dopamine and serotonin. Despite this, the authors suggest that there is still a possibility that the observed improvement is partially attributed to the effects of TMS on the dopaminergic system due to the significant correlation found between pre- and post-TMS HVA levels as HVA is dopamine’s main metabolite. Some limitations to the study that may have negatively impacted significance between clinical response and biochemical response were the small sample size, a non-TMS control group, and the short duration of treatment, which lasted 5 days.17,67

Back to Top | Article Outline
Other Neuroimmunoendocrine Markers

Other neuroimmunoendocrine markers such as LH, FSH, estradiol, progesterone, and DHEA have been tested. These studies show positive clinical outcomes, but vary in their finding of significant marker differences before and after rTMS. For example, a study by Padberg et al71 revealed that patients’ depression decreased by about 40% post-rTMS, although they observed no change in progesterone and DHEA levels. Huang et al72 observed a reduction in depression as well an association between rTMS response and LH, FSH, and estradiol levels in women. The latter study suggests that sexual hormone changes may be related to mood improvement rather than a direct effect of rTMS on hypophyseal hormones as suggested by electroconvulsive therapy studies.73

Back to Top | Article Outline

DISCUSSION

Major depressive disorder is still an entity difficult to dissect completely from the pure clinical perspective and the pathology behind it. Elusive functional and structural alterations by imaging studies continue presenting heterogeneous data that cannot be completely accepted as a landmark source for clinical relevance. Biochemical profiling has the potential as an option to characterize specific “depressive syndromes,” and genetic/epigenetic assessment will definitely provide a great insight into the nature and evolution of the disease; unfortunately, we are still waiting for the advancement and refinement of such technologies. Until now, surrogate biomarkers, when analyzed carefully in the context of clinical evidence, can provide the information that will point toward a better understanding of MDD.

We reviewed all published articles that evaluated TMS as an intervention among patients with MDD through the use of BMs. No studies on tDCS were found according to our inclusion criteria. The majority, but not all of the studies, reported clinical improvement in patients and positive correlation to BMs.

According to our findings, fMRI, SPECT, PET, MRS, cortical excitability, and BDNF consistently showed positive results in the articles reviewed. Positive correlations between EEG and TSH were also found, but results were inconsistent as some articles included in the review found no significance between the outcomes measured. On the other hand, saccadic eye movements, dopamine, and serotonin were all found to have no significance in the articles we reviewed.

There are a number of similarities between the articles reviewed that could possibly account for the results obtained. First, because of the fact that most of the studies reviewed used a small sample size, the trials may be lacking the power to show a significant difference. This is also the reason that the measures that were found to be consistently positive cannot yet be implemented as surrogate outcomes for MDD as small sample sizes may also lead to type I error. Another reason that could account for these results is that the stimulation parameters were inconsistent between trials. One important parameter to note is the length of the study. The majority of the studies lasted for 3 weeks within which subjects underwent 10 sessions of rTMS. This time period may not be long enough to detect a change in the expression of those biomarkers. In fact, we found only 2 large trials in this review.50,67

In addition, many of the reviewed studies used heterogeneous samples and did not take into account confounders such as age, sex, or family history. Creating a standardized biochemical evaluation would improve the power of comparison among studies and therefore add more data to the field, as was stated by the Consensus of the Seventh Expert Meeting on Psychiatry and Immunology.74

Back to Top | Article Outline
The Use of Biomarkers as Surrogate Outcomes

It is important to address the use of BMs as surrogate outcomes. Although there are several possible definitions for surrogate outcomes, they are usually understood as measurements that substitute clinically meaningful outcomes and are direct measures of a patient’s state of health. In addition, surrogate outcomes should also be able to predict the outcomes of therapies.5,75 The major difference between BMs and surrogate outcomes is that BMs are the precursors to official surrogate outcomes.

The great advantage in finding BMs to act as surrogate outcomes is that surrogate outcomes substitute “hard” clinical outcomes such as death or serious disabilities and reduce the need for long-term, usually very expensive, research. In order for a BM to be implemented as a surrogate outcome, the BMs must demonstrate sensitivity, specificity, and a decrease in symptoms (assessed by validated measures) in an adequate number of well-designed clinical trials.75 In our review, the BMs that showed the greatest potential for becoming surrogate outcomes were BDNF and neuroimaging studies.

When considering the role BDNF plays in neuroplasticity and the proposed neurotrophic hypothesis presented by Pittenger and Duman,96 it is reasonable to assume that rTMS therapeutic effects are based on its intrinsic neuromodulatory properties on cortical excitability. The changes in synaptic plasticity as a result of rTMS application could possibly be the effect of BDNF modulation under the site of stimulation and deeper areas as well, the last as a result of cortical-subcortical connections. If local increments of BDNF and production of other growth factors at the hippocampal level have already shown antidepressive-like effects in animal models, it may have a profound impact as a treatment for MDD; however, peripheral administration of BDNF is still challenging pharmacokinetic principles, and the potential for adverse effects outweighs the use of BDNF. It is then reasonable to use rTMS as exogenous tool to facilitate BDNF secretion.

Brain-derived neurotrophic factor in particular had the greatest support for use as a surrogate outcome. All studies that used BDNF as a correlate for depression post-rTMS treatment showed positive results. In a secondary search, a systematic review examining the role of neuroplasticity on BDNF levels by Brunoni et al,76 10 case-control studies and 13 clinical trials were analyzed showing a strong correlation between BDNF levels and depression. The main finding was that BDNF levels in the blood increased if depression was treated with rTMS and antidepressants, suggesting that BDNF levels in patients with MDD are associated with changes in neuroplasticity76; modulation of BDNF levels and downstream of its signaling can be considered a stressor that might lead to impaired adult hippocampal neurogenesis, promoting the development of atrophic changes and deficits in synaptic plasticity, which in turn may explain the hippocampal atrophy observed in postmortem studies.96 One question here though is whether BDNF levels would be a general marker of antidepressant response or be specific for the type of treatment—that is, pharmacological versus nonpharmacological. While these results are encouraging, further studies are necessary to elucidate the link between this and other biomarkers and depression to identify strong surrogate outcomes.

The significance of genetic variability and its influence in treatment responses is becoming an area to explore in the fields of genetic/epigenetic research. For instance, BDNF polymorphisms has a direct impact in the development of synaptic plasticity; thus, biomolecular assessments aimed to recognize such genetic variations may become the foundation for personalized pharmacological and nonpharmacological treatments, thus including noninvasive brain stimulation.

It is also important to consider the role of cognitive performance as functional marker in the treatment of MDD. Noninvasive brain stimulation, especially in the case of TMS and tDCS, can be used as therapeutic techniques to improve the cognitive impairments observed in neuropsychiatric disorders,117 and on the other hand, cognitive dysfunction may also be a functional and therapeutic marker for disorders associated with cognitive dysfunction such as MDD.118

Back to Top | Article Outline
Future Directions

In addition to performing larger, longer, and sham-controlled studies on the biomarkers reviewed here, in the future other potential parameters, techniques, and markers should be considered. An interesting finding of our review is that the majority of studies explored the alterations of the DLPFC and the effects of TMS on the activity of that area. In addition to the DLPFC, recent studies in noninvasive brain stimulation and functional imaging have identified the ventromedial PFC (VMPFC) as an area involved in the pathophysiology of depression. According to several authors, depression is associated with abnormally high levels of VMPFC activity77–80 and abnormally low levels of DLPFC activity.77,81,82 Whereas a study by Koenigs and Grafman83 found that patients with bilateral VMPFC lesions had significantly lower levels of depression than patients with bilateral lesions of the DLPFC, Li et al21 found that performing rTMS on the VLPFC led to a considerable decrease in activity of that area. Thus, the VLPFC would be an interesting site of stimulation for future studies as it may be able to elicit results that would allow for the identification of BMs and implementation of surrogate outcomes.

Another factor that may affect BM results is the type of stimulation used. As was mentioned before, all of the studies reviewed used TMS techniques; however, it is important to realize the potential of tDCS in this setting as well.58,74 Unlike the pulses that cause action potentials in TMS, tDCS is thought to manipulate neuronal signaling by applying a low electric current through electrodes placed on the scalp.84 Although the perceived mechanism of action may be slightly different, both TMS and tDCS techniques allow for the induction of excitatory or inhibitory effects. Because tDCS is also able to induce these changes, it may be a good choice for patients with depression. Transcranial direct current stimulation also has the advantage of being more user-friendly during double-blind or sham-controlled trials as well being easier to use when used with other measures and tasks, allowing for further exploration of BMs and surrogate outcomes.84

One important finding by Langguth et al85 in 2005 revealed that there might be a link between inflammation and depression. According to several authors, it has been demonstrated that there is in fact an increase in proinflammatory cytokines such as IL-186,87 and IL-686,88–90 in depressed patients. In turn, inflammation may lead to plastic changes in the nervous system.91 Because of this relationship, it may be possible in the future to use these cytokines as BMs in depression; however, the effect of noninvasive brain stimulation on these cytokines is not clear from current studies.85,92 A case study revealed an improvement in the patient’s depression, but an increase in her rheumatoid arthritis after treatment with rTMS. These results were obtained multiple times in the same patient, and the reproducibility suggests a link between rTMS immunomodulatory effects.85 On the other hand, a study performed in rats by Okada et al92 found no significant increase in the up-regulation of proinflammatory cytokines. Thus, additional studies must be performed to determine the effect of noninvasive brain stimulation techniques on these potential BMs.

Back to Top | Article Outline
Final Remarks

In summary, TMS is a strong choice for the treatment of depression, with several studies trying to explain its clinical effects due to biological changes or find the best predictors of response as to optimize response to rTMS. Although we are not yet able to use the BMs as surrogate outcomes for depression treatment response, there are strong candidates that will hopefully be able to fulfill this role in the future. In order for these BMs and surrogate outcomes to be identified, it is important that more funding be directed not only to neuromodulation studies, but also to neurobiological studies in psychiatry. This would make the measurements of larger samples and the inclusion of a sham or control group possible. As a result, advances in psychiatric evaluation would be possible, leading to higher-quality care of patients and, in turn, better clinical outcomes.

Back to Top | Article Outline
Acknowledgments

The authors thank Lauren Richardson, who assisted us with manuscript copyediting.

Back to Top | Article Outline

REFERENCES

1. Anderson IM, Ferrier IN, Baldwin RC, et al. Evidence-based guidelines for treating depressive disorders with antidepressants: a revision of the 2000 British Association for Psychopharmacology guidelines. J Psychopharmacol. 2008; 22: 343–396.

2. Murray CJ, Lopez AD. Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study. Lancet. 1997; 349: 1498–1504.

3. Nemeroff CB. Prevalence and management of treatment-resistant depression. J Clin Psychiatry. 2007; 68 (suppl 8): 17–25.

4. Waraich P, Goldner EM, Somers JM, et al. Prevalence and incidence studies of mood disorders: a systematic review of the literature. Can J Psychiatry. 2004; 49: 124–138.

5. Brunoni AR, Teng CT, Correa C, et al. Neuromodulation approaches for the treatment of major depression: challenges and recommendations from a working group meeting. Arq Neuropsiquiatr. 2010; 68: 433–451.

6. Pridmore S. Rapid transcranial magnetic stimulation and normalization of the dexamethasone suppression test. Psychiatry Clin Neurosci. 1999; 53: 33–37.

7. Zobel AW, Yassouridis A, Frieboes RM, et al. Prediction of medium-term outcome by cortisol response to the combined dexamethasone-CRH test in patients with remitted depression. Am J Psychiatry. 1999; 156: 949–951.

8. A decade for psychiatric disorders. Nature. 2010; 463: 9.

9. Akil H, Brenner S, Kandel E, et al. Medicine. The future of psychiatric research: genomes and neural circuits. Science. 2010; 327: 1580–1581.

10. Insel TR, Wang PS. Rethinking mental illness. JAMA. 2010; 303: 1970–1971.

11. Kobayashi M, Pascual-Leone A. Transcranial magnetic stimulation in neurology. Lancet Neurol. 2003; 2: 145–156.

12. LR, R. Magnetic stimulation of the central and peripheral nervous systems. In: Dumitru D, ed. Electrodiagnostic Medicine. Philadelphia, PA: Hadley & Belfus Inc; 1995: 415–427.

13. Hahn T, Marquand AF, Ehlis AC, et al. Integrating neurobiological markers of depression. Arch Gen Psychiatry. 2011; 68: 361–368.

14. Schneider P, Hampel H, Buerger K. Biological marker candidates of Alzheimer’s disease in blood, plasma, and serum. CNS Neurosci Ther. 2009; 15: 358–374.

15. Koyama R, Ikegaya Y. To BDNF or not to BDNF: that is the epileptic hippocampus. Neuroscientist. 2005; 11: 282–287.

16. Otte A, Halsband U. Brain imaging tools in neurosciences. J Physiol Paris. 2006; 99: 281–292.

17. Serkova NJ, Brown MS. Quantitative analysis in magnetic resonance spectroscopy: from metabolic profiling to in vivo biomarkers. Bioanalysis. 2012; 4: 321–341.

18. Malhi GS, Lagopoulos J. Making sense of neuroimaging in psychiatry. Acta Psychiatr Scand. 2008; 117: 100–117.

19. Ziemann U. Transcranial magnetic stimulation at the interface with other techniques: a powerful tool for studying the human cortex. Neuroscientist. 2011; 17: 368–381.

20. Nahas Z, DeBrux C, Chandler V, et al. Lack of significant changes on magnetic resonance scans before and after 2 weeks of daily left prefrontal repetitive transcranial magnetic stimulation for depression. J ECT. 2000; 16: 380–390.

21. Li X, Nahas Z, Kozel FA, et al. Acute left prefrontal transcranial magnetic stimulation in depressed patients is associated with immediately increased activity in prefrontal cortical as well as subcortical regions. Biol Psychiatry. 2004; 55: 882–890.

22. Li X, Nahas Z, Lomarev M, et al. Prefrontal cortex transcranial magnetic stimulation does not change local diffusion: a magnetic resonance imaging study in patients with depression. Cogn Behav Neurol. 2003; 16: 128–135.

23. Herbsman T, Avery D, Ramsey D, et al. More lateral and anterior prefrontal coil location is associated with better repetitive transcranial magnetic stimulation antidepressant response. Biol Psychiatry. 2009; 66: 509–515.

24. Fitzgerald PB, Sritharan A, Daskalakis ZJ, et al. A functional magnetic resonance imaging study of the effects of low frequency right prefrontal transcranial magnetic stimulation in depression. J Clin Psychopharmacol. 2007; 27: 488–492.

25. Rahmim A, Zaidi H. PET versus SPECT: strengths, limitations and challenges. Nucl Med Commun. 2008; 29: 193–207.

26. Kito S, Fujita K, Koga Y. Regional cerebral blood flow changes after low-frequency transcranial magnetic stimulation of the right dorsolateral prefrontal cortex in treatment-resistant depression. Neuropsychobiology. 2008; 58: 29–36.

27. Kito S, Fujita K, Koga Y. Changes in regional cerebral blood flow after repetitive transcranial magnetic stimulation of the left dorsolateral prefrontal cortex in treatment-resistant depression. J Neuropsychiatry Clin Neurosci. 2008; 20: 74–80.

28. Conca A, Peschina W, König P, et al. Effect of chronic repetitive transcranial magnetic stimulation on regional cerebral blood flow and regional cerebral glucose uptake in drug treatment-resistant depressives. A brief report. Neuropsychobiology. 2002; 45: 27–31.

29. Loo CK, Sachdev PS, Haindl W, et al. High (15 Hz) and low (1 Hz) frequency transcranial magnetic stimulation have different acute effects on regional cerebral blood flow in depressed patients. Psychol Med. 2003; 33: 997–1006.

30. Pogarell O, Koch W, Pöpperl G, et al. Striatal dopamine release after prefrontal repetitive transcranial magnetic stimulation in major depression: preliminary results of a dynamic [123I] IBZM SPECT study. J Psychiatr Res. 2006; 40: 307–314.

31. Nadeau SE, McCoy KJ, Crucian GP, et al. Cerebral blood flow changes in depressed patients after treatment with repetitive transcranial magnetic stimulation: evidence of individual variability. Neuropsychiatry Neuropsychol Behav Neurol. 2002; 15: 159–175.

32. Peschina W, Conca A, König P, et al. Low frequency rTMS as an add-on antidepressive strategy: heterogeneous impact on 99mTc-HMPAO and 18F-FDG uptake as measured simultaneously with the double isotope SPECT technique. Pilot study. Nucl Med Commun. 2001; 22: 867–873.

33. Baeken C, De Raedt R, Van Hove C, et al. HF-rTMS treatment in medication-resistant melancholic depression: results from 18FDG-PET brain imaging. CNS Spectr. 2009; 14: 439–448.

34. Herwig U, Lampe Y, Juengling FD, et al. Add-on rTMS for treatment of depression: a pilot study using stereotaxic coil-navigation according to PET data. J Psychiatr Res. 2003; 37: 267–275.

35. McLean MA, Cross JJ. Magnetic resonance spectroscopy: principles and applications in neurosurgery. Br J Neurosurg. 2009; 23: 5–13.

36. Thaker GK. Neurophysiological endophenotypes across bipolar and schizophrenia psychosis. Schizophr Bull. 2008; 34: 760–773.

37. Luborzewski A, Schubert F, Seifert F, et al. Metabolic alterations in the dorsolateral prefrontal cortex after treatment with high-frequency repetitive transcranial magnetic stimulation in patients with unipolar major depression. J Psychiatr Res. 2007; 41: 606–615.

38. Eschweiler GW, Wegerer C, Schlotter W, et al. Left prefrontal activation predicts therapeutic effects of repetitive transcranial magnetic stimulation (rTMS) in major depression. Psychiatry Res. 2000; 99: 161–172.

39. Boutros NN, Miano AP, Hoffman RE, et al. EEG monitoring in depressed patients undergoing repetitive transcranial magnetic stimulation. J Neuropsychiatry Clin Neurosci. 2001; 13: 197–205.

40. Olejniczak P. Neurophysiologic basis of EEG. J Clin Neurophysiol. 2006; 23: 186–189.

41. O’Sullivan SS, Mullins GM, Cassidy EM, et al. The role of the standard EEG in clinical psychiatry. Hum Psychopharmacol. 2006; 21: 265–271.

42. Cracco RQ, Amassian VE, Maccabee PJ, et al. Comparison of human transcallosal responses evoked by magnetic coil and electrical stimulation. Electroencephalogr Clin Neurophysiol. 1989; 74: 417–424.

43. Arns M, Spronk D, Fitzgerald PB. Potential differential effects of 9Hz rTMS and 10 Hz rTMS in the treatment of depression. Brain Stimul. 2010; 3: 124–126.

44. Price GW, Lee JW, Garvey C, et al. Appraisal of sessional EEG features as a correlate of clinical changes in an rTMS treatment of depression. Clin EEG Neurosci. 2008; 39: 131–138.

45. Narushima K, McCormick LM, Yamada T, et al. Subgenual cingulate theta activity predicts treatment response of repetitive transcranial magnetic stimulation in participants with vascular depression. J Neuropsychiatry Clin Neurosci. 2010; 22: 75–84.

46. Berman RM, Narasimhan M, Sanacora G, et al. A randomized clinical trial of repetitive transcranial magnetic stimulation in the treatment of major depression. Biol Psychiatry. 2000; 47: 332–337.

47. Schestatsky P, Morales-Quezada L, Fregni F. Simultaneous EEG monitoring during transcranial direct current stimulation (tDCS). J Vis Exp. 2012. In press.

48. Ziemann U, Corwell B, Cohen LG. Modulation of plasticity in human motor cortex after forearm ischemic nerve block. J Neurosci. 1998; 18: 1115–1123.

49. Bajwa S, Bermpohl F, Rigonatti SP, et al. Impaired interhemispheric interactions in patients with major depression. J Nerv Ment Dis. 2008; 196: 671–677.

50. Chistyakov AV, Kaplan B, Rubichek O, et al. Antidepressant effects of different schedules of repetitive transcranial magnetic stimulation vs. clomipramine in patients with major depression: relationship to changes in cortical excitability. Int J Neuropsychopharmacol. 2005; 8: 223–233.

51. Triggs WJ, McCoy KJ, Greer R, et al. Effects of left frontal transcranial magnetic stimulation on depressed mood, cognition, and corticomotor threshold. Biol Psychiatry. 1999; 45: 1440–1446.

52. Maeda F, Keenan JP, Pascual-Leone A. Interhemispheric asymmetry of motor cortical excitability in major depression as measured by transcranial magnetic stimulation. Br J Psychiatry. 2000; 177: 169–173.

53. Crevits L, Van den Abbeele D, Audenaert K, et al. Effect of repetitive transcranial magnetic stimulation on saccades in depression: a pilot study. Psychiatry Res. 2005; 135: 113–119.

54. Liang WK, Juan CH. Modulation of motor control in saccadic behaviors by TMS over the posterior parietal cortex. J Neurophysiol. 2012; 108: 741–752.

55. Reid PD, Pridmore S. Dexamethasone suppression test reversal in rapid transcranial magnetic stimulation-treated depression. Aust N Z J Psychiatry. 1999; 33: 274–277.

56. Zwanzger P, Baghai TC, Padberg F, et al. The combined dexamethasone-CRH test before and after repetitive transcranial magnetic stimulation (rTMS) in major depression. Psychoneuroendocrinology. 2003; 28: 376–385.

57. Gratacòs M, González JR, Mercader JM, et al. Brain-derived neurotrophic factor Val66Met and psychiatric disorders: meta-analysis of case-control studies confirm association to substance-related disorders, eating disorders, and schizophrenia. Biol Psychiatry. 2007; 61: 911–922.

58. Yukimasa Fleck T, Yoshimura R, Tamagawa A, et al. Review of the guidelines of the Brazilian Medical Association for the treatment of depression (complete version). Rev Bras Psiquiatr. 2009; 31 (suppl 1): S7–S17.

59. Ren K, Dubner R. Pain facilitation and activity-dependent plasticity in pain modulatory circuitry: role of BDNF-TrkB signaling and NMDA receptors. Mol Neurobiol. 2007; 35: 224–235.

60. Yukimasa T, Yoshimura R, Tamagawa A, et al. High-frequency repetitive transcranial magnetic stimulation improves refractory depression by influencing catecholamine and brain-derived neurotrophic factors. Pharmacopsychiatry. 2006; 39: 52–59.

61. Zanardini R, Gazzoli A, Ventriglia M, et al. Effect of repetitive transcranial magnetic stimulation on serum brain derived neurotrophic factor in drug resistant depressed patients. J Affect Disord. 2006; 91: 83–86.

62. Stipcevic T, Pivac N, Kozaric Kovacic D, et al. Thyroid activity in patients with major depression. Coll Antropol. 2008; 32: 973–976.

63. Kito S, Hasegawa T, Fujita K, et al. Changes in hypothalamic-pituitary-thyroid axis following successful treatment with low-frequency right prefrontal transcranial magnetic stimulation in treatment-resistant depression. Psychiatry Res. 2010; 175: 74–77.

64. Szuba MP, O’Reardon JP, Rai AS, et al. Acute mood and thyroid stimulating hormone effects of transcranial magnetic stimulation in major depression. Biol Psychiatry. 2001; 50: 22–27.

65. George MS, Wassermann EM, Williams WA, et al. Changes in mood and hormone levels after rapid-rate transcranial magnetic stimulation (rTMS) of the prefrontal cortex. J Neuropsychiatry Clin Neurosci. 1996; 8: 172–180.

66. IsHak WW, Davis M, Jeffrey J, et al. The role of dopaminergic agents in improving quality of life in major depressive disorder. Curr Psychiatry Rep. 2009; 11: 503–508.

67. Miniussi C, Bonato C, Bignotti S, et al. Repetitive transcranial magnetic stimulation (rTMS) at high and low frequency: an efficacious therapy for major drug-resistant depression? Clin Neurophysiol. 2005; 116: 1062–1071.

68. Kuroda Y, Motohashi N, Ito H, et al. Effects of repetitive transcranial magnetic stimulation on [11C]raclopride binding and cognitive function in patients with depression. J Affect Disord. 2006; 95: 35–42.

69. Meltzer CC, Smith G, DeKosky ST, et al. Serotonin in aging, late-life depression, and Alzheimer’s disease: the emerging role of functional imaging. Neuropsychopharmacology. 1998; 18: 407–430.

70. Souery D, Papakostas GI, Trivedi MH. Treatment-resistant depression. J Clin Psychiatry. 2006; 67 (suppl 6): 16–22.

71. Padberg F, di Michele F, Zwanzger P, et al. Plasma concentrations of neuroactive steroids before and after repetitive transcranial magnetic stimulation (rTMS) in major depression. Neuropsychopharmacology. 2002; 27: 874–878.

72. Huang CC, Wei IH, Chou YH, et al. Effect of age, gender, menopausal status, and ovarian hormonal level on rTMS in treatment-resistant depression. Psychoneuroendocrinology. 2008; 33: 821–831.

73. Esel E, Turan T, Kula M, et al. Effects of electroconvulsive therapy on hypothalamic-pituitary-thyroid axis activity in depressed patients. Prog Neuropsychopharmacol Biol Psychiatry. 2002; 26: 1171–1175.

74. Andrade L, Caraveo-Anduaga JJ, Berglund P, et al. The epidemiology of major depressive episodes: results from the International Consortium of Psychiatric Epidemiology (ICPE) surveys. Int J Methods Psychiatr Res. 2003; 12: 3–21.

75. Katz R. Biomarkers and surrogate markers: an FDA perspective. NeuroRx. 2004; 1: 189–195.

76. Brunoni AR, Lopes M, Fregni F. A systematic review and meta-analysis of clinical studies on major depression and BDNF levels: implications for the role of neuroplasticity in depression. Int J Neuropsychopharmacol. 2008; 11: 1169–1180.

77. Biver F, Goldman S, Delvenne V, et al. Frontal and parietal metabolic disturbances in unipolar depression. Biol Psychiatry. 1994; 36: 381–388.

78. Drevets WC, Videen TO, Price JL, et al. A functional anatomical study of unipolar depression. J Neurosci. 1992; 12: 3628–3641.

79. Greicius MD, Flores BH, Menon V, et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry. 2007; 62: 429–437.

80. Mayberg HS, Lozano AM, Voon V, et al. Deep brain stimulation for treatment-resistant depression. Neuron. 2005; 45: 651–660.

81. Baxter LR Jr, Schwartz JM, Phelps ME, et al. Reduction of prefrontal cortex glucose metabolism common to three types of depression. Arch Gen Psychiatry. 1989; 46: 243–250.

82. Galynker II, Cai J, Ongseng F, et al. Hypofrontality and negative symptoms in major depressive disorder. J Nucl Med. 1998; 39: 608–612.

83. Koenigs M, Grafman J. The functional neuroanatomy of depression: distinct roles for ventromedial and dorsolateral prefrontal cortex. Behav Brain Res. 2009; 201: 239–243.

84. Bolognini N, Pascual-Leone A, Fregni F. Using non-invasive brain stimulation to augment motor training-induced plasticity. J Neuroeng Rehabil. 2009; 6: 8.

85. Langguth B, Braun S, Aigner JM, et al. Repetitive transcranial magnetic stimulation in a patient suffering from depression and rheumatoid arthritis: evidence for immunomodulatory effects. Neuro Endocrinol Lett. 2005; 26: 314–316.

86. Howren MB, Lamkin DM, Suls J. Associations of depression with C-reactive protein, IL-1, and IL-6: a meta-analysis. Psychosom Med. 2009; 71: 171–186.

87. Owen BM, Eccleston D, Ferrier IN, et al. Raised levels of plasma interleukin-1beta in major and postviral depression. Acta Psychiatr Scand. 2001; 103: 226–228.

88. Kim YK, Na KS, Shin KH, et al. Cytokine imbalance in the pathophysiology of major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2007; 31: 1044–1053.

89. Levine J, Barak Y, Chengappa KN, et al. Cerebrospinal cytokine levels in patients with acute depression. Neuropsychobiology. 1999; 40: 171–176.

90. Zorrilla EP, Luborsky L, McKay JR, et al. The relationship of depression and stressors to immunological assays: a meta-analytic review. Brain Behav Immun. 2001; 15: 199–226.

91. Fregni F, Potvin K, Dasilva D, et al. Clinical effects and brain metabolic correlates in non-invasive cortical neuromodulation for visceral pain. Eur J Pain. 2011; 15: 53–60.

92. Okada K, Matsunaga K, Yuhi T, et al. The long-term high-frequency repetitive transcranial magnetic stimulation does not induce mRNA expression of inflammatory mediators in the rat central nervous system. Brain Res. 2002; 957: 37–41.

93. Hercher C, Turecki G, Mechawar N. Through the looking glass: examining neuroanatomical evidence for cellular alterations in major depression. J Psychiatr Res. 2009; 43: 947–961.

94. Savitz J, Drevets WC. Bipolar and major depressive disorder: neuroimaging the developmental-degenerative divide. Neurosci Biobehav Rev. 2009; 33: 699–771.

95. Ressler KJ, Mayberg HS. Targeting abnormal neural circuits in mood and anxiety disorders: from the laboratory to the clinic. Nat Neurosci. 2007; 10: 1116–1124.

96. Pittenger C, Duman RS. Stress, depression, and neuroplasticity: a convergence of mechanisms. Neuropsychopharmacology. 2008; 33: 88–109.

97. Li Y, Luikart BW, Birnbaum S, et al. Trkb regulates hippocampal neurogenesis and governs sensitivity to antidepressive treatment. Neuron. 2008; 59: 399–412.

98. Shirayama Y, Chen AC, Nakagawa S, et al. Brain-derived neurotrophic factor produces antidepressant effects in behavioral models of depression. J Neurosci. 2002; 22: 3251–3261.

99. Steingard RJ, Yurgelun-Todd DA, Hennen J, et al. Increased orbitofrontal cortex levels of choline in depressed adolescents as detected by in vivo proton magnetic resonance spectroscopy. Biol Psychiatry. 2000; 48: 1053–1061.

100. Furtado CP, Hoy KE, Maller JJ, et al. Cognitive and volumetric predictors of response to repetitive transcranial magnetic stimulation (rTMS)—a prospective follow-up study [published online ahead of print May 17, 2012]. Psychiatry Res. 2012; 202: 12–19.

101. Micolaud-Franchi JA, Richieri R, Cermolacce M, et al. Parieto-temporal alpha EEG band power at baseline as a predictor of antidepressant treatment response with repetitive transcranial magnetic stimulation: a preliminary study [published online ahead of print January 12, 2012]. J Affect Disord. 2012; 137: 156–160.

102. Kito S, Hasegawa T, Koga Y. Cerebral blood flow in the ventromedial prefrontal cortex correlates with treatment response to low-frequency right prefrontal repetitive transcranial magnetic stimulation in the treatment of depression. Psychiatry Clin Neurosci. 2012; 66: 138–145.

103. Peng H, Zheng H, Li L, et al. High-frequency rTMS treatment increases white matter FA in the left middle frontal gyrus in young patients with treatment-resistant depression [published online ahead of print January 2, 2012]. J Affect Disord. 2012; 136: 249–257.

104. Croarkin PE, Wall CA, Nakonezny PA, et al. Increased cortical excitability with prefrontal high- frequency repetitive transcranial magnetic stimulation in adolescents with treatment-resistant major depressive disorder [published online ahead of print January 18, 2012]. J Child Adolesc Psychopharmacol. 2012; 22: 56–64.

105. Paillère Martinot ML, Martinot JL, Ringuenet D, et al. Baseline brain metabolism in resistant depression and response to transcranial magnetic stimulation [published online ahead of print August 17, 2011]. Neuropsychopharmacology. 2011; 36: 2710–2719.

106. Trojak B, Chauvet-Gelinier JC, Vergès B, et al. Significant increase in plasma thyroid-stimulating hormone during low-frequency repetitive transcranial magnetic stimulation. J Neuropsychiatry Clin Neurosci. 2011; 23: E12.

107. Richieri R, Boyer L, Farisse J, et al. Predictive value of brain perfusion SPECT for rTMS response in pharmacoresistant depression [published online ahead of print June 7, 2011]. Eur J Nucl Med Mol Imaging. 2011; 38: 1715–1722.

108. Malaguti A, Rossini D, Lucca A, et al. Role of COMT, 5-HT(1A), and SERT genetic polymorphisms on antidepressant response to transcranial magnetic stimulation. Depress Anxiety. 2011; 28: 568–573.

109. Baeken C, De Raedt R, Bossuyt A, et al. The impact of HF-rTMS treatment on serotonin(2A) receptors in unipolar melancholic depression [published online ahead of print September 27, 2010]. Brain Stimul. 2011; 4: 104–111.

110. Kito S, Hasegawa T, Okayasu M, et al. A 6-month follow-up case report of regional cerebral blood flow changes in treatment-resistant depression after successful treatment with bilateral transcranial magnetic stimulation. J ECT. 2011; 27: e12–e14.

111. Kozel FA, Johnson KA, Nahas Z, et al. Fractional anisotropy changes after several weeks of daily left high-frequency repetitive transcranial magnetic stimulation of the prefrontal cortex to treat major depression. J ECT. 2011; 27: 5–10.

112. Khodayari-Rostamabad A, Reilly JP, Hasey GM, et al. Using pre-treatment electroencephalography data to predict response to transcranial magnetic stimulation therapy for major depression. Conf Proc IEEE Eng Med Biol Soc. 2011; 2011: 6418–6421.

113. Li CT, Wang SJ, Hirvonen J, et al. Antidepressant mechanism of add-on repetitive transcranial magnetic stimulation in medication-resistant depression using cerebral glucose metabolism [published online ahead of print July 3, 2010]. J Affect Disord. 2010; 127: 219–229.

114. Kuroda Y, Motohashi N, Ito H, et al. Chronic repetitive transcranial magnetic stimulation failed to change dopamine synthesis rate: preliminary L-[β-11C]DOPA positron emission tomography study in patients with depression. Psychiatry Clin Neurosci. 2010; 64: 659–662.

115. Zheng H, Zhang L, Li L, et al. High-frequency rTMS treatment increases left prefrontal myo-inositol in young patients with treatment-resistant depression [published online ahead of print June 23, 2010]. Prog Neuropsychopharmacol Biol Psychiatry. 2010; 34: 1189–1195.

116. Baunce S, Izzetoglu M, Izzetoglu K, et al. Functional near-infrared spectroscopy. An emerging neuroimaging modality. IEEE Eng Med Biol Mag. 2006 ;25: 54––62.

117. Demirtas-Tatlidede A, Vahabzadeh-Hagh AM, Pascual-Leone A. Can noninvasive brain stimulation enhance cognition in neuropsychiatric disorders? Neuropharmacology. 2013; 64: 566–578.

118. Bermpohl F, Fregni F, Boggio PS, et al. Effect of low-frequency transcranial magnetic stimulation on an affective go/no-go task in patients with major depression: role of stimulation site and depression severity. Psychiatry Res. 2006; 141: 1–13.

Keywords:

transcranial magnetic stimulation; biological markers; neuroimaging; BDNF and EEG

© 2014 by Lippincott Williams & Wilkins

Login

Article Tools

Images

Share

Article Level Metrics

Search for Similar Articles
You may search for similar articles that contain these same keywords or you may modify the keyword list to augment your search.