Biomarkers For Major Depressive Disorder Research Articles

Combined cognitive, psychomotor and electrophysiological biomarkers in major depressive disorder.

The diagnosis of major depressive disorder (MDD) should be based on multimodal evidence, because MDD not only affects mood, but also psychomotor and cognitive functions. Clinical markers such as executive dysfunctions and a reduction in daily motor activity have been observed in MDD. Neurophysiological biomarkers have also been described. In this study, we investigate the utility of combining biomarkers related to executive dysfunctions, motor activity, neurophysiological patterns (i.e. alpha power asymmetry and EEG-vigilance as indicators of brain arousal), and the interaction of these parameters in the diagnosis of MDD. Twenty (female: 11) patients with MDD (age: 51.05 ± 10.50) and 20 (female: 13) healthy controls (HC; age: 47.15 ± 12.57) underwent a 10-min resting EEG. Executive dysfunctions were assessed using the Trail Making Test B (TMT B). Motor activity was analysed by actigraphy measurements. MDD patients displayed significant impairments in executive functions and reduced daily motor activity. In the EEG, MDD patients showed more right than left frontal activity and lower brain arousal relative to HC. TMT B and asymmetrical frontal alpha power alone discriminated between MDD patients and HC with an accuracy of 78%. The interaction of motor activity and the EEG-vigilance stage alongside TMT B increased the accuracy of the discrimination test to 81%. This improved accuracy suggests that the combination of these biomarkers in a discriminant analysis resulted in a more reliable identification of MDD patients.

Metabolic and Microbiota Measures as Peripheral Biomarkers in Major Depressive Disorder.

Advances in understanding the role of the microbiome in physical and mental health are at the forefront of medical research and hold potential to have a direct impact on precision medicine approaches. In the past 7 years, we have studied the role of microbiota-brain communication on behavior in mouse models using germ-free mice, mice exposed to antibiotics, and healthy specific pathogen free mice. Through our work and that of others, we have seen an amazing increase in our knowledge of how bacteria signal to the brain and the implications this has for psychiatry. Gut microbiota composition and function are influenced both by genetics, age, sex, diet, life experiences, and many other factors of psychiatric and bodily disorders and thus may act as potential biomarkers of the gut-brain axis that could be used in psychiatry and co-morbid conditions. There is a particular need in major depressive disorder and other mental illness to identify biomarkers that can stratify patients into more homogeneous groups to provide better treatment and for development of new therapeutic approaches. Peripheral outcome measures of host-microbe bidirectional communication have significant translational value as biomarkers. Enabling stratification of clinical populations, based on individual biological differences, to predict treatment response to pharmacological and non-pharmacological interventions. Here we consider the links between co-morbid metabolic syndrome and depression, focusing on biomarkers including leptin and ghrelin in combination with assessing gut microbiota composition, as a potential tool to help identify individual differences in depressed population.

Functional connectivity between the thalamus and the primary somatosensory cortex in major depressive disorder: a resting-state fMRI study

BackgroundStudies have confirmed that the thalamus and the primary somatosensory cortex (SI) are associated with cognitive function. These two brain regions are closely related in structure and function. The interactions between SI and the thalamus are of crucial significance for the cognitive process. Patients with major depressive disorder (MDD) have significant cognitive impairment. Based on these observations, we used resting-state functional magnetic resonance imaging (rs-fMRI) to investigate whether there is an abnormality in the SI-thalamic functional connection in MDD. Furthermore, we explored the clinical symptoms related to this abnormality.MethodsWe included 31 patients with first-episode major depressive disorder and 28 age-, gender-, and education-matched healthy controls (HC). The SI-thalamic functional connectivity was compared between the MDD and HC groups. The correlation analyses were performed between areas with abnormal connectivity and clinical characteristics.ResultsCompared with healthy subjects, the MDD patients had enhanced functional connectivity between the thalamus and SI (p < 0.05, corrected). Brain areas with significantly different levels of connectivity had a negative correlation with the Assessment of Neuropsychological Status total score (r = − 0.383, p = 0.033), delayed memory score (r = − 0.376, p = 0.037) and two-digit continuous operation test score (r = − 0.369, p = 0.041) in MDD patients.ConclusionsThese results demonstrate that SI-thalamic functional connectivity is abnormal and associated with the core clinical symptoms in MDD. The SI-thalamic functional connectivity functions as a neurobiological feature and potential biomarker for MDD.

State-independent alterations of intrinsic brain network in current and remitted depression

BackgroundIt has been proposed that state-independent, or trait, neurobiological alterations across illness phases may contribute to the high recurrence of major depressive disorder (MDD). Although intrinsic brain network abnormalities have been implicated consistently in MDD neuropathology, MDD state-independent and -dependent resting-state network alterations have not been clearly studied. MethodsResting-state functional magnetic resonance imaging (fMRI) data were collected from 57 medication-naive first-episode current MDD patients, 35 remitted MDD patients, and 66 healthy controls (HCs). Independent component analysis (ICA) was used to extract subnetworks of the default mode network (DMN), central executive network (CEN), and salience network (SN). ResultsRelative to HCs, the current MDD and remitted MDD groups had decreased intra-intrinsic functional connectivity (iFC) in the dorsal lateral prefrontal cortex (dlPFC) of the left CEN, increased inter-FC between the SN and right CEN (rCEN), and decreased inter-FC between the anterior DMN (aDMN) and rCEN. The altered intra-iFC in the left CEN were correlated negatively with the depressive level in the remitted MDD. ConclusionsHypoactivity of the dlPFC in the left CEN, increased inter-FC between the SN and rCEN, and decreased inter-FC between the aDMN and rCEN may reflect state-independent biomarkers of MDD.

Development and evaluation of a multimodal marker of major depressive disorder

This study aimed to identify biomarkers of major depressive disorder (MDD), by relating neuroimage-derived measures to binary (MDD/control), ordinal (severe MDD/mild MDD/control), or continuous (depression severity) outcomes. To address MDD heterogeneity, factors (severity of psychic depression, motivation, anxiety, psychosis, and sleep disturbance) were also used as outcomes. A multisite, multimodal imaging (diffusion MRI [dMRI] and structural MRI [sMRI]) cohort (52 controls and 147 MDD patients) and several modeling techniques-penalized logistic regression, random forest, and support vector machine (SVM)-were used. An additional cohort (25 controls and 83 MDD patients) was used for validation. The optimally performing classifier (SVM) had a 26.0% misclassification rate (binary), 52.2 ± 1.69% accuracy (ordinal) and r = .36 correlation coefficient (p < .001, continuous). Using SVM, R2 values for prediction of any MDD factors were <10%. Binary classification in the external data set resulted in 87.95% sensitivity and 32.00% specificity. Though observed classification rates are too low for clinical utility, four image-based features contributed to accuracy across all models and analyses-two dMRI-based measures (average fractional anisotropy in the right cuneus and left insula) and two sMRI-based measures (asymmetry in the volume of the pars triangularis and the cerebellum) and may serve as a priori regions for future analyses. The poor accuracy of classification and predictive results found here reflects current equivocal findings and sheds light on challenges of using these modalities for MDD biomarker identification. Further, this study suggests a paradigm (e.g., multiple classifier evaluation with external validation) for future studies to avoid nongeneralizable results.

Diagnosis of major depressive disorder based on changes in multiple plasma neurotransmitters: a targeted metabolomics study

Major depressive disorder (MDD) is a debilitating psychiatric illness. However, there is currently no objective laboratory-based diagnostic tests for this disorder. Although, perturbations in multiple neurotransmitter systems have been implicated in MDD, the biochemical changes underlying the disorder remain unclear, and a comprehensive global evaluation of neurotransmitters in MDD has not yet been performed. Here, using a GC-MS coupled with LC-MS/MS-based targeted metabolomics approach, we simultaneously quantified the levels of 19 plasma metabolites involved in GABAergic, catecholaminergic, and serotonergic neurotransmitter systems in 50 first-episode, antidepressant drug-naïve MDD subjects and 50 healthy controls to identify potential metabolite biomarkers for MDD (training set). Moreover, an independent sample cohort comprising 49 MDD patients, 30 bipolar disorder (BD) patients and 40 healthy controls (testing set) was further used to validate diagnostic generalizability and specificity of these candidate biomarkers. Among the 19 plasma neurotransmitter metabolites examined, nine were significantly changed in MDD subjects. These metabolites were mainly involved in GABAergic, catecholaminergic and serotonergic systems. The GABAergic and catecholaminergic had better diagnostic value than serotonergic pathway. A panel of four candidate plasma metabolite biomarkers (GABA, dopamine, tyramine, kynurenine) could distinguish MDD subjects from health controls with an AUC of 0.968 and 0.953 in the training and testing set, respectively. Furthermore, this panel distinguished MDD subjects from BD subjects with high accuracy. This study is the first to globally evaluate multiple neurotransmitters in MDD plasma. The altered plasma neurotransmitter metabolite profile has potential differential diagnostic value for MDD.

Elevated salivary alpha-amylase levels at awakening in patients with depression

BackgroundSpecific Major Depressive Disorder (MDD) biomarkers could help improve our understanding of MDD pathophysiology and aid in the refinement of current MDD criteria. While salivary cortisol (SC) can differentiate between healthy controls and patients with psychiatric disorders, salivary alpha amylase (sAA), may be a putative candidate biomarker for MDD specifically. MethodsIn a naturalistic cohort of consecutive out-patients and healthy controls, sAA and SC were determined in 833 participants (97 MDD patients, 142 patients with other mood, anxiety, and/or somatoform (MAS-) disorders, and 594 healthy controls). Samples were collected at 7 different time points (at awakening, after 30, 45, and 60 min, at 10:00 p.m., at 11:00 p.m., and at awakening on day 2). ResultsThe mean age of the sample was 43.8 years (SD = 12.9; 63.9% female). Concerning sAA, MDD patients had higher sAA levels upon awakening on two consecutive days (p = 0.04, p = 0.01 respectively), as well as a higher area under the curve with respect to the increase (AUCi; p = 0.04) in comparison to both controls and the other MAS-disorders group. Regarding SC, mean levels of evening SC were elevated in MDD patients (p = 0.049) in comparison to both controls and the other MAS-disorders group. SC values on day 2 after ingestion of dexamethasone were elevated in both MDD patients and the other MAS-disorders group (p = 0.04, p = 0.047 respectively). ConclusionssAA at awakening and not cortisol differentiates MDD from other psychiatric disorders in outpatients. This suggests that sAA may be a valuable candidate biomarker specifically for MDD.

High serum levels of tenascin-C are associated with suicide attempts in depressed patients

The proteomic study reported that Tenascin-C might be a diagnostic biomarker for major depressive disorder, but clinical studies of this potential relationship are lacking. Here we examined the association between tenascin-C levels in serum and suicide attempts. Serum tenascin-C concentrations were compared among depressive patients who had not attempted suicide (n = 86), patients who had attempted it (n = 43), and healthy controls (n = 109). All participants were aged between 18 and 68 years. The association between concentration and suicide attempts was assessed by multivariate analysis after adjusting for sociodemographics, lifestyle and health indicators. Tenascin-C concentrations were higher in patients than in controls, and higher in patients who had attempted suicide than in patients who had not. Higher concentrations were associated with greater risk of attempting suicide. Among patients who had attempted suicide, tenascin-C concentrations were associated with severity of depression. Our results suggest that high tenascin-C levels in depressive patients correlate with suicide attempts and severity of depression. Tenascin-C may contribute to risk of suicide attempts in depressed patients.

Pretreatment and early-treatment cortical thickness is associated with SSRI treatment response in major depressive disorder.

To date, there are no biomarkers for major depressive disorder (MDD) treatment response in clinical use. Such biomarkers could allow for individualized treatment selection, reducing time spent on ineffective treatments and the burden of MDD. In search of such a biomarker, multisite pretreatment and early-treatment (1 week into treatment) structural magnetic resonance (MR) images were acquired from 184 patients with MDD randomized to an 8-week trial of the selective serotonin reuptake inhibitor (SSRI) sertraline or placebo. This study represents a large, multisite, placebo-controlled effort to examine the association between pretreatment differences or early-treatment changes in cortical thickness and treatment-specific outcomes. For standardization, a novel, robust site harmonization procedure was applied to structural measures in a priori regions (rostral and caudal anterior cingulate, lateral orbitofrontal, rostral middle frontal, and hippocampus), chosen based on previously published reports. Pretreatment cortical thickness or volume did not significantly associate with SSRI response. Thickening of the rostral anterior cingulate cortex in the first week of treatment was associated with better 8-week responses to SSRI (p = 0.010). These findings indicate that frontal lobe structural alterations in the first week of treatment may be associated with long-term treatment efficacy. While these associational findings may help to elucidate the specific neural targets of SSRIs, the predictive accuracy of pretreatment or early-treatment structural alterations in classifying treatment remitters from nonremitters was limited to 63.9%. Therefore, in this large sample of adults with MDD, structural MR imaging measures were not found to be clinically translatable biomarkers of treatment response to SSRI or placebo.

Treatment-resistant depression and peripheral C-reactive protein.

C-reactive protein (CRP) is a candidate biomarker for major depressive disorder (MDD), but it is unclear how peripheral CRP levels relate to the heterogeneous clinical phenotypes of the disorder.AimTo explore CRP in MDD and its phenotypic associations. We recruited 102 treatment-resistant patients with MDD currently experiencing depression, 48 treatment-responsive patients with MDD not currently experiencing depression, 48 patients with depression who were not receiving medication and 54 healthy volunteers. High-sensitivity CRP in peripheral venous blood, body mass index (BMI) and questionnaire assessments of depression, anxiety and childhood trauma were measured. Group differences in CRP were estimated, and partial least squares (PLS) analysis explored the relationships between CRP and specific clinical phenotypes. Compared with healthy volunteers, BMI-corrected CRP was significantly elevated in the treatment-resistant group (P = 0.007; Cohen's d = 0.47); but not significantly so in the treatment-responsive (d = 0.29) and untreated (d = 0.18) groups. PLS yielded an optimal two-factor solution that accounted for 34.7% of variation in clinical measures and for 36.0% of variation in CRP. Clinical phenotypes most strongly associated with CRP and heavily weighted on the first PLS component were vegetative depressive symptoms, BMI, state anxiety and feeling unloved as a child or wishing for a different childhood. CRP was elevated in patients with MDD, and more so in treatment-resistant patients. Other phenotypes associated with elevated CRP included childhood adversity and specific depressive and anxious symptoms. We suggest that patients with MDD stratified for proinflammatory biomarkers, like CRP, have a distinctive clinical profile that might be responsive to second-line treatment with anti-inflammatory drugs.Declaration of interestS.R.C. consults for Cambridge Cognition and Shire; and his input in this project was funded by a Wellcome Trust Clinical Fellowship (110049/Z/15/Z). E.T.B. is employed half time by the University of Cambridge and half time by GlaxoSmithKline; he holds stock in GlaxoSmithKline. In the past 3 years, P.J.C. has served on an advisory board for Lundbeck. N.A.H. consults for GlaxoSmithKline. P.d.B., D.N.C.J. and W.C.D. are employees of Janssen Research &amp; Development, LLC., of Johnson &amp; Johnson, and hold stock in Johnson &amp; Johnson. The other authors report no financial disclosures or potential conflicts of interest.

Serum lipidomic analysis for the discovery of biomarkers for major depressive disorder in drug-free patients

Lipidomic analysis can be used to efficiently identify hundreds of lipid molecular species in biological materials and has been recently established as an important tool for biomarker discovery in various neuropsychiatric disorders including major depressive disorder (MDD). In this study, quantitative targeted serum lipidomic profiling was performed on female subjects using liquid chromatography–mass spectrometry. Global lipid profiling of pooled serum samples from 10 patients currently with MDD (cMDD), 10 patients with remitted MDD (rMDD), and 10 healthy controls revealed 37 differentially regulated lipids (DRLs). DRLs were further verified using multiple-reaction monitoring (MRM) in each of the 25 samples from the three groups of independent cohorts. Using multivariate analysis and MRM data we identified serum biomarker panels of discriminatory lipids that differentiated between pairs of groups: lysophosphatidic acid (LPA)(16:1), triglycerides (TG)(44:0), and TG(54:8) distinguished cMDD from controls with 76% accuracy; lysophosphatidylcholines(16:1), TG(44:0), TG(46:0), and TG(50:1) distinguished between cMDD and rMDD at 65% accuracy; and LPA(16:1), TG(52:6), TG(54:8), and TG(58:10) distinguished between rMDD and controls with 60% accuracy. Our lipidomic analysis identified peripheral lipid signatures of MDD, which thereby provides providing important biomarker candidates for MDD.

Early warning biomarkers in major depressive disorder: a strategic approach to a testing question

Purpose: Identification of biomarkers in major depressive disorder (MDD) has proceeded in an extemporised manner. No single biomarker has been identified with utility in screening, diagnosis, prognosis, or monitoring, and screening tests have different characteristics than the other functions. Using chaos, bifurcation, and perturbation (CBP) theories, the aim is to identify biomarkers to aid clinicians in screening for MDD.Materials and methods: MDD is a complex disorder; consequently, a reductionist approach to characterize the complex system changes found in MDD will be inchoate and unreliable. A holistic approach is used to identify biomarkers reflecting the tipping points seen before the catastrophic bifurcation that results in MDD.Results: Applying CBP theories revealed skew, resistance to change, flickering, increased variance and autocorrelation as patterns of biomarkers. Integrals and differentials of extracellular and intracellular biomarkers were identified, specifically focussed on hypothalamo-pituitary axis (HPA) dysfunction, metabolic dysfunction, inflammation and mitochondrial oxidative stress, and tryptophan metabolism.Conclusions: Applying CBP theories to the dysfunctional complex biological systems in MDD led to development of integrals and differentials of biomarkers that can be used in screening for MDD and planning future biomarker research, targeting intracellular and extracellular inflammation, HPA axis dysfunction, and tryptophan metabolism.

Polyunsaturated fatty acids metabolism, purine metabolism and inosine as potential independent diagnostic biomarkers for major depressive disorder in children and adolescents

Major depressive disorder (MDD) in children and adolescents is a recurrent and disabling condition globally but its pathophysiology remains poorly elucidated and there are limited effective treatments available. We performed metabolic profiling of plasma samples based on ultra-high-performance liquid chromatography equipped with quadrupole time-offlight mass spectrometry to explore the potential biomarkers of depression in children and adolescents with MDD. We identified several perturbed pathways, including fatty acid metabolism—particularly the polyunsaturated fatty acids metabolism, and purine metabolism—that were associated with MDD in these young patients. In addition, inosine was shown as a potential independent diagnostic biomarker for MDD, achieving an area under the ROC curve of 0.999 in discriminating drug-naive MDD patients and 0.866 in discriminating drug-treated MDD from healthy controls. Moreover, we found evidence for differences in the pathophysiology of MDD in children and adolescents to that of adult MDD, specifically with tryptophan metabolism. Through metabolomic analysis, we have identified links between a framework of metabolic perturbations and the pathophysiology and diagnostic biomarker of child and adolescent MDD.

T149. Do We Have Evidence for Predictive Biomarkers for Major Depressive Disorder? A Meta-Analysis and Systematic Review of Prospective Studies

T149. Do We Have Evidence for Predictive Biomarkers for Major Depressive Disorder? A Meta-Analysis and Systematic Review of Prospective Studies

T124. Abundance of GABA-producing Gut Bacteria Correlates With Functional Brain Connectivity in Depression

Increased functional connectivity of the Default Mode Network (DMN), a reproducible biomarker of Major Depressive Disorder (MDD), may be related to low cerebral levels of GABA in MDD. GABA circulates in body fluids and can cross the blood-brain barrier. We hypothesize that lower abundance of GABA-producing gut bacteria is associated with MDD and with elevated DMN functional connectivity.

176. Evidence of Differential Changes in Cortical Thickness and Volume Between SSRI and Placebo Treated Patients With Major Depressive Disorder

To date, clinical translation of biomarkers for major depressive disorder (MDD) treatment response has been limited. Development of noninvasive, MRI based biomarkers could allow for individualized treatment selection, reducing time spent on ineffective treatments and the cost burden of MDD.

Plasma metabolome analysis of patients with major depressive disorder.

This study sought to characterize the plasma metabolite profiling of patients with major depressive disorder (MDD). Psychiatric assessments were made with the Structured Clinical Interview for DSM-IV Axis I Disorders. In the exploratory cohort, plasma metabolite profiles of 34 MDD patients and 31 mentally healthy controls were compared using capillary electrophoresis-mass spectrometry. Among the candidate metabolites, we focused on a metabolite showing the largest difference. The absolute concentrations were measured in two cohorts from a psychiatric primary care clinic to characterize the accuracy of the metabolite biomarker. Among 23 metabolites significantly lower in the MDD group than in healthy controls, we focused on phosphoethanolamine (PEA) as a candidate. The reduction of PEA levels in MDD was checked in independent clinical sample sets. An ion-chromatography-fluorescence detection method was developed to measure plasma PEA levels. In the preliminary cohort, we examined 34 MDD and 43 non-MDD subjects. The area under the receiver-operator curve (AUC) was 0.92, with sensitivity/specificity greater than 88%, at a cut-off of 1.46 μM. In the checking cohort, with 10 MDD and 13 non-MDD subjects, AUC was 0.89, with sensitivity/specificity of 86% and 100%, respectively, at a cut-off of 1.48 μM. Plasma PEA inversely correlated with MDD severity, depressed mood, loss of interest, and psychomotor retardation. These results suggest that plasma PEA level could be a candidate biomarker of MDD in the clinical setting. Further studies comparing MDD and mentally healthy controls are needed to confirm the utility of PEA as a biomarker for depression.

Abnormal emotional and neural responses to romantic rejection and acceptance in depressed women

IntroductionResponding adaptively to one's social environment is a key factor predicting the course of major depressive disorder (MDD). Socially rejecting events can exacerbate, whereas socially accepting events can ameliorate depressive symptoms. The neural responses to rejection and acceptance in MDD are relatively unexplored. MethodsWe used functional magnetic resonance imaging (fMRI) to measure neural responses to romantic rejection and acceptance in women diagnosed with current MDD (n = 19) and a matched group of healthy controls (HCs) (n = 19). During fMRI, participants received rejecting, accepting, and neutral feedback from self-selected potential romantic partners. ResultsIn women with MDD but not HCs, rejection significantly increased activity in the right anterior insula relative to neutral feedback. Greater activation during rejection was found in the dorsal anterior cingulate cortex in MDD compared to HCs. Women with MDD reported stronger emotional responses than HCs to both rejection and acceptance. In addition, left and right nucleus accumbens (NAcc) activity mediated the relationship between trait reward responsiveness and increased ratings of feeling “happy and accepted” following acceptance in HCs, but not the MDD group. DiscussionWomen with MDD were behaviorally and neurally hyperresponsive to rejection. Although both groups were behaviorally responsive to acceptance, in MDD this was dissociated from NAcc activity. These findings highlight abnormal behavioral and neural responses to social cues in MDD, with implications for disease prognosis and the development of novel and sensitive biomarkers for MDD focused on neural pathways for social-affective processing. LimitationsConclusions may be limited to depressed women in a romantic context.

Low cocaine- and amphetamine-regulated transcript (CART) peptide levels in human cerebrospinal fluid of major depressive disorder (MDD) patients

BackgroundCocaine- and amphetamine-regulated transcript (CART) peptide is a candidate neuropeptide as a biomarker for major depressive disorder (MDD) because of its effects on emotion and distribution covering brain areas involved in the pathophysiology of MDD symptoms. However, it is unknown whether CART peptide levels are altered in the cerebrospinal fluid (CSF) of patients with MDD patients and are correlated with MDD symptoms. MethodsSubjects were 24 patients with MDD and 25 healthy controls matched for age, gender and ethnicity (Japanese). We measured CSF CART levels by a commercially available immunoassay kit and analyzed the relationships of the levels with antidepressant dose and symptoms assessed with the 21 item Hamilton Depression Rating Scale (HAMD-21). ResultsCSF CART levels were significantly decreased in the patients than in the controls (p < 0.05). In MDD patient group, the CART levels had a negative correlation with antidepressant dose (imipramine-equivalent dose) (ρ = −0.55, p < 0.01) and significantly decreased in antidepressant-treated group (AD-treated group) compared to controls (p < 0.05). CSF CART levels showed significant negative correlations with psychomotor retardation, somatic anxiety, and general somatic symptoms (all p < 0.05) and a positive correlation with obsessive and compulsive symptoms (p < 0.05). LimitationsIn our analysis, all classes of antidepressants were combined together and the effects of medication use in a longitudinal manner did not confirm. ConclusionsWe report for the first time that CSF CART peptide levels are reduced in patients with MDD compared with healthy controls. The CART levels showed negative correlations with antidepressant dose and some symptoms, supporting the possibility that CART peptide is involved in the development of depressive symptoms.

Will imaging individual raphe nuclei in males with major depressive disorder enhance diagnostic sensitivity and specificity?

Positron emission tomography (PET) studies in major depressive disorder (MDD) have reported higher serotonin 1A (5-HT1A ) autoreceptor binding in the raphe. In males, the difference is so large that it can potentially be used as the first biological marker for MDD. However, the raphe includes several nuclei, which project to different regions of the brain and spinal cord and may be differentially involved in disease. We aimed to identify 5-HT1A differences in individual raphe nuclei using PET in order to determine whether use of subnuclei would provide greater sensitivity and specificity of diagnosing MDD. We identified individual nuclei using a hybrid set-level technique on an average [11 C]-WAY100635 PET image derived from 52 healthy volunteers (HV). We delineated three nuclei: dorsal raphe nucleus (DRN), median raphe nucleus (MRN), and raphe magnus (RMg). An atlas image of these nuclei was created and nonlinearly warped to each subject (through an associated MRI) in a separate sample of 41 males (25 HV, 16 MDD) who underwent [11 C]-WAY100635 PET. 5-HT1A binding was elevated in DRN in MDD (P<.01), and was not different in the RMg and MRN between groups. Receiver operating characteristic (ROC) curves showed that combining DRN and MRN produces highest sensitivity (94%) and specificity (84%) to identify MDD. In agreement with postmortem studies, we found higher 5-HT1A autoreceptor binding in MDD selectively in the DRN. 5-HT1A autoreceptor binding in the combined DRN and MRN is a better biomarker for MDD than in the raphe as a whole.