Serum brain-derived neurotrophic factor, Val66Met polymorphism and open-label SSRI treatment response in Major Depressive Disorder.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) has been implicated in the therapeutic action of antidepressants and possibly in the pathophysiology of Major Depressive Disorder (MDD). Clinical studies of peripheral blood levels of BDNF in MDD have provided conflicting results, and there are also conflicting reports regarding the predictive value of peripheral BDNF levels for antidepressant treatment response. The present study investigated the association between serum BDNF levels, the BDNF Val66Met polymorphism (rs6265), clinical characteristics and SSRI treatment response. METHODS: This open-label clinical trial included 99 physically healthy, unmedicated MDD participants and 70 healthy controls. Following a baseline assessment, 53 of the MDD participants completed an eight-week, open-label course of SSRI antidepressant treatment. Serum BDNF levels and Hamilton Rating Scale for Depression (HDRS) ratings were examined at baseline and after eight weeks of treatment. Antidepressant response was defined as a decrease in HDRS ratings of > 50% from baseline to the end-of-treatment. Finally, serum BDNF levels and SSRI treatment response were compared between MDD participants who were heterozygous or homozygous for the Met allele ("Met-carriers") and individuals homozygous for the Val allele. RESULTS: Serum BDNF levels at baseline were significantly higher in the unmedicated MDD participants compared to healthy controls (15.90 ng/ml vs 13.75 ng/ml, t (167) = -2.041, p = 0.043). In a post-hoc analysis, this difference was seen in the female but not male participants (16.85 ng/ml vs 14.06 ng/ml, t (91) = -2.067, p = 0.042; 14.86 ng/ml vs 13.31 ng/ml, t (74) = -0.923, p = 0.359). Baseline serum BDNF levels were not associated with treatment responder status or with absolute change in depression ratings over the course of 8-week SSRI treatment (p = 0.599). In both Responders and Non-responders, no significant changes in serum BDNF levels were found over the 8-week period of SSRI-treatment (16.32 ng/ml vs 16.23 ng/ml, t (18) = 0.060, p = 0.953; 16.04 ng/ml vs 15.61 ng/ml, t (29) = 0.438, p = 0.665, respectively). Further, no differences were found in serum BDNF levels prior to treatment between MDD Met-carriers and MDD Val/Val homozygotes (15.32 ng/ml vs 16.36 ng/ml, t (85) = 0.747, p = 0.457), and no differences were found in post-treatment serum BDNF (F1,42= 0.031, p = 0.862). However, MDD Val/Val homozygotes showed significantly greater antidepressant responses at week 8 than did MDD Met-carriers (F1,46 = 4.366, p = 0.043). CONCLUSION: Our results do not support sufficient reliability of using peripheral BDNF to characterize depression or to predict antidepressant response in clinical use. The role of sex in moderating BDNF differences in depression, and the role of BDNF gene polymorphisms in predicting antidepressant response, remain to be further investigated. We conclude that, while central nervous system BDNF is likely involved in antidepressant efficacy and in aspects of MDD pathophysiology, its reflection in serum BDNF levels is of limited diagnostic or prognostic utility.

Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders.

BACKGROUND: Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas. METHODS: We constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters. RESULTS: We show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients. CONCLUSIONS: Our results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots.

The frequencies of mental disorders vary by geographic region. Investigating such variations may lead to more equitable access to mental healthcare and to scientific discoveries that reveal specific localized factors that contribute to the causes of mental illness. This study examined the frequency of three disorders with a major impact on public health ­ schizophrenia, bipolar disorder, and major depressive disorder ­ by analyzing electronic health records from a hospital providing comprehensive mental health care for a large region in Colombia. We show that individuals receiving outpatient care mainly live relatively near the facility. Those receiving inpatient care live throughout the region, but cluster in a few scattered locations. Future research could lead to strategies for more equitable provision of mental healthcare in Colombia and identify environmental or genetic factors that affect the likelihood that someone will develop one of these disorders.

Circulating cell-free mitochondrial DNA levels and glucocorticoid sensitivity in a cohort of male veterans with and without combat-related PTSD.

Circulating cell-free mitochondrial DNA (ccf-mtDNA) is a biomarker of cellular injury or cellular stress and is a potential novel biomarker of psychological stress and of various brain, somatic, and psychiatric disorders. No studies have yet analyzed ccf-mtDNA levels in post-traumatic stress disorder (PTSD), despite evidence of mitochondrial dysfunction in this condition. In the current study, we compared plasma ccf-mtDNA levels in combat trauma-exposed male veterans with PTSD (n = 111) with those who did not develop PTSD (n = 121) and also investigated the relationship between ccf mt-DNA levels and glucocorticoid sensitivity. In unadjusted analyses, ccf-mtDNA levels did not differ significantly between the PTSD and non-PTSD groups (t = 1.312, p = 0.191, Cohen's d = 0.172). In a sensitivity analysis excluding participants with diabetes and those using antidepressant medication and controlling for age, the PTSD group had lower ccf-mtDNA levels than did the non-PTSD group (F(1, 179) = 5.971, p = 0.016, partial η2 = 0.033). Across the entire sample, ccf-mtDNA levels were negatively correlated with post-dexamethasone adrenocorticotropic hormone (ACTH) decline (r = -0.171, p = 0.020) and cortisol decline (r = -0.149, p = 0.034) (viz., greater ACTH and cortisol suppression was associated with lower ccf-mtDNA levels) both with and without controlling for age, antidepressant status and diabetes status. Ccf-mtDNA levels were also significantly positively associated with IC50-DEX (the concentration of dexamethasone at which 50% of lysozyme activity is inhibited), a measure of lymphocyte glucocorticoid sensitivity, after controlling for age, antidepressant status, and diabetes status (ß = 0.142, p = 0.038), suggesting that increased lymphocyte glucocorticoid sensitivity is associated with lower ccf-mtDNA levels. Although no overall group differences were found in unadjusted analyses, excluding subjects with diabetes and those taking antidepressants, which may affect ccf-mtDNA levels, as well as controlling for age, revealed decreased ccf-mtDNA levels in PTSD. In both adjusted and unadjusted analyses, low ccf-mtDNA levels were associated with relatively increased glucocorticoid sensitivity, often reported in PTSD, suggesting a link between mitochondrial and glucocorticoid-related abnormalities in PTSD.

Predicting diagnostic conversion from major depressive disorder to bipolar disorder: an EHR based study from Colombia.

Bipolar Disorder (BD) is a severe and chronic disorder characterized by recurrent episodes of depression, mania, and/or hypomania. Most BD patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study leverages electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia to identify features predictive of the transition from Major Depressive Disorder (MDD) to BD. Analyzing EHR data from 13,607 patients diagnosed with MDD over 15 years, we identified 1,610 cases of conversion to BD. Using a multivariate Cox regression model, we identified severity of the initial MDD episode, the presence of psychosis and hospitalization at first episode, family history of mood or psychotic disorders, female gender to be predictive of the conversion to BD. Additionally, we observed associations with medication classes (prescriptions of mood stabilizers, antipsychotics, and antidepressants) and clinical features (delusions, suicide attempt, suicidal ideation, use of marijuana and alcohol use/abuse) derived from natural language processing (NLP) of clinical notes. Together, these risk factors predicted BD conversion within five years of the initial MDD diagnosis, with a recall of 72% and a precision of 38%. Our study confirms many previously identified risk factors identified through registry-based studies (such as female gender and psychotic depression at the index MDD episode), and identifies novel ones (specifically, suicidal ideation and suicide attempt extracted from clinical notes). These results simultaneously demonstrate the validity of using EHR data for predicting BD conversion as well as underscore its potential for the identification of novel risk factors and improving early diagnosis.

Shorter telomere length predicts poor antidepressant response and poorer cardiometabolic indices in major depression.

Telomere length (TL) is a marker of biological aging, and shorter telomeres have been associated with several medical and psychiatric disorders, including cardiometabolic dysregulation and Major Depressive Disorder (MDD). In addition, studies have shown shorter TL to be associated with poorer response to certain psychotropic medications, and our previous work suggested shorter TL and higher telomerase activity (TA) predicts poorer response to Selective Serotonin Reuptake Inhibitor (SSRI) treatment. Using a new group of unmedicated medically healthy individuals with MDD (n = 48), we sought to replicate our prior findings demonstrating that peripheral blood mononuclear cell (PBMC) TL and TA predict response to SSRI treatment and to identify associations between TL and TA with biological stress mediators and cardiometabolic risk indices. Our results demonstrate that longer pre-treatment TL was associated with better response to SSRI treatment (ß = .407 p = .007). Additionally, we observed that TL had a negative relationship with allostatic load (ß = - .320 p = .017) and a cardiometabolic risk score (ß = - .300 p = .025). Our results suggest that PBMC TL reflects, in part, the cumulative effects of physiological stress and cardiovascular risk in MDD and may be a biomarker for predicting SSRI response.

Dimensions of childhood adversity differentially affect biological aging in major depression.

Adverse childhood experiences have been consistently linked with physical and mental health disorders in adulthood that may be mediated, in part, via the effects of such exposures on biological aging. Using recently developed "epigenetic clocks", which provide an estimate of biological age, several studies have demonstrated a link between the cumulative exposure to childhood adversities and accelerated epigenetic aging. However, not all childhood adversities are equivalent and less is known about how distinct dimensions of childhood adversity relate to epigenetic aging metrics. Using two measures of childhood adversity exposure, we assess how the dimensions of Maltreatment and Household Dysfunction relate to epigenetic aging using two "second-generation" clocks, GrimAge and PhenoAge, in a cohort of unmedicated somatically healthy adults with moderate to severe major depression (n = 82). Our results demonstrate that the dimension of Maltreatment is associated with epigenetic age acceleration (EAA) using the PhenoAge but not the GrimAge clock. This association was observed using both the Childhood Trauma questionnaire (CTQ; ß = 0.272, p = 0.013) and the Adverse Childhood Experiences (ACEs) questionnaire (ß = 0.307, p = 0.005) and remained significant when adjusting for exposure to the dimension of Household Dysfunction (ß = 0.322, p = 0.009). In contrast, the dimension of Household Dysfunction is associated with epigenetic age deceleration (ß = -0.194, p = 0.083) which achieved significance after adjusting for exposure to the dimension of Maltreatment (ß = -0.304, p = 0.022). This study is the first to investigate these effects among individuals with Major Depressive Disorder and suggests that these dimensions of adversity may be associated with disease via distinct biological mechanisms.

Development and Implementation of a Chief Resident for Research Role in a Psychiatry Residency Training Program.

Psychiatry residency programs with robust research training can prepare physician-scientists to make contributions that advance the mental health field. Our psychiatry residency developed a chief resident for research position to help provide mentorship, community building, and advising around scholarly activities for residents. We present the process of implementing this new position in our residency to offer a model for engaging psychiatry residents in research.

Blood-based mitochondrial respiratory chain function in major depression.

Mitochondrial dysfunction has been implicated in major depressive disorder (MDD). A measure of mitochondrial respiratory chain (RC) enzymatic activity-the Mitochondrial Health Index (MHI)-has previously been found to correlate with stress and emotional states in caregivers. We here report mitochondrial RC activities, mitochondrial DNA copy number (mtDNAcn), and the composite MHI in unmedicated and somatically healthy subjects with MDD (n = 47) and healthy controls (HC) (n = 11). We also explore, in a subset of the MDD sample (n = 33), whether these markers are associated with response to 8 weeks of SSRI treatment. Mitochondrial RC complexes I, II, IV, citrate synthase (CS), mtDNAcn, and the MHI were assayed in peripheral blood mononuclear cells. Treatment response was defined as >50% decrease on the 25-item Hamilton Depression Rating Scale (HRDS-25). There were no significant differences in MHI or any of the mitochondrial markers between MDD subjects and HCs. Compared to SSRI nonresponders, SSRI responders had significantly higher baseline mitochondrial content markers CS (p = 0.02) and mtDNAcn (p = 0.02), and higher complex I activity (p = 0.01). Complex II activity increased significantly over treatment, irrespective of clinical response (p = 0.03). Complex I activity decreased in responders (n = 9), but increased in nonresponders (n = 18) (group x time interaction, p = 0.02). Absolute treatment-associated change in HDRS-25 scores correlated significantly with change in complex I activity between baseline and week 8 (r = 0.47, p = 0.01). Although mitochondrial markers did not distinguish MDD from controls, they did distinguish SSRI responders from nonresponders. If larger studies validate these mitochondrial differences, they may become useful biomarkers and identify new drug targets.

Serum brain-derived neurotrophic factor remains elevated after long term follow-up of combat veterans with chronic post-traumatic stress disorder.

Attempts to correlate blood levels of brain-derived neurotrophic factor (BDNF) with post-traumatic stress disorder (PTSD) have provided conflicting results. Some studies found a positive association between BDNF and PTSD diagnosis and symptom severity, while others found the association to be negative. The present study investigated whether serum levels of BDNF are different cross-sectionally between combat trauma-exposed veterans with and without PTSD, as well as whether longitudinal changes in serum BDNF differ as a function of PTSD diagnosis over time. We analyzed data of 270 combat trauma-exposed veterans (230 males, 40 females, average age: 33.29 ± 8.28 years) and found that, at the initial cross-sectional assessment (T0), which averaged 6 years after the initial exposure to combat trauma (SD=2.83 years), the PTSD positive group had significantly higher serum BDNF levels than the PTSD negative controls [31.03 vs. 26.95 ng/mL, t(268) = 3.921, p < 0.001]. This difference remained significant after excluding individuals with comorbid major depressive disorder, antidepressant users and controlling for age, gender, race, BMI, and time since trauma. Fifty-nine of the male veterans who participated at the first timepoint (T0) were re-assessed at follow-up evaluation (T1), approximately 3 years (SD=0.88 years) after T0. A one-way ANOVA comparing PTSD positive, "subthreshold PTSD" and control groups revealed that serum BDNF remained significantly higher in the PTSD positive group than the control group at T1 [30.05 vs 24.66 ng/mL, F(2, 56)= 3.420, p = 0.040]. Serum BDNF levels did not correlate with PTSD symptom severity at either time point within the PTSD group [r(128) = 0.062, p = 0.481 and r(28) = 0.157, p = 0.407]. Serum BDNF did not significantly change over time within subjects [t(56) = 1.269, p = 0.210] nor did the change of serum BDNF from T0 to T1 correlate with change in PTSD symptom severity within those who were diagnosed with PTSD at T0 [r(27) = -0.250, p = 0.192]. Our longitudinal data are the first to be reported in combat PTSD and suggest that higher serum BDNF levels may be a stable biological characteristic of chronic combat PTSD independent of symptom severity.

Abnormal levels of mitochondrial proteins in plasma neuronal extracellular vesicles in major depressive disorder.

To characterize neuronal mitochondrial abnormalities in major depressive disorder (MDD), functional mitochondrial proteins (MPs) extracted from enriched plasma neuron-derived extracellular vesicles (NDEVs) of MDD participants (n = 20) were quantified before and after eight weeks of treatment with a selective serotonin reuptake inhibitor (SSRI). Pretreatment baseline NDEV levels of the transcriptional type 2 nuclear respiratory factor (NRF2) which controls mitochondrial biogenesis and many anti-oxidant gene responses, regulators of diverse neuronal mitochondrial functions cyclophilin D (CYPD) and mitofusin-2 (MFN2), leucine zipper EF-hand containing transmembrane 1 protein (LETM1) component of a calcium channel/calcium channel enhancer, mitochondrial tethering proteins syntaphilin (SNPH) and myosin VI (MY06), inner membrane electron transport complexes I (subunit 6) and III (subunit 10), the penultimate enzyme of nicotinamide adenine dinucleotide (NAD) generation nicotinamide mononucleotide adenylytransferase 2 (NMNAT2), and neuronal mitochondrial metabolic regulatory and protective factors humanin and mitochondrial open-reading frame of the 12S rRNA-c (MOTS-c) all were significantly lower than those of NDEVs from matched controls (n = 10), whereas those of pro-neurodegenerative NADase Sterile Alpha and TIR motif-containing protein 1 (SARM1) were higher. The baseline NDEV levels of transcription factor A mitochondrial (TFAM) and the transcriptional master-regulator of mitochondrial biogenesis PPAR γ coactivator-1α (PGC-1α) showed no differences between MDD participants and controls. Several of these potential biomarker proteins showed substantially different changes in untreated MDD than those we reported in untreated first-episode psychosis. NDEV levels of MPs of all functional classes, except complex I-6, NRF2 and PGC-1α were normalized in MDD participants who responded to SSRI therapy (n = 10) but not in those who failed to respond (n = 10) by psychiatric evaluation. If larger studies validate NDEV MP abnormalities, they may become useful biomarkers and identify new drug targets.

Utilization of machine learning for identifying symptom severity military-related PTSD subtypes and their biological correlates.

We sought to find clinical subtypes of posttraumatic stress disorder (PTSD) in veterans 6-10 years post-trauma exposure based on current symptom assessments and to examine whether blood biomarkers could differentiate them. Samples were males deployed to Iraq and Afghanistan studied by the PTSD Systems Biology Consortium: a discovery sample of 74 PTSD cases and 71 healthy controls (HC), and a validation sample of 26 PTSD cases and 36 HC. A machine learning method, random forests (RF), in conjunction with a clustering method, partitioning around medoids, were used to identify subtypes derived from 16 self-report and clinician assessment scales, including the clinician-administered PTSD scale for DSM-IV (CAPS). Two subtypes were identified, designated S1 and S2, differing on mean current CAPS total scores: S2 = 75.6 (sd 14.6) and S1 = 54.3 (sd 6.6). S2 had greater symptom severity scores than both S1 and HC on all scale items. The mean first principal component score derived from clinical summary scales was three times higher in S2 than in S1. Distinct RFs were grown to classify S1 and S2 vs. HCs and vs. each other on multi-omic blood markers feature classes of current medical comorbidities, neurocognitive functioning, demographics, pre-military trauma, and psychiatric history. Among these classes, in each RF intergroup comparison of S1, S2, and HC, multi-omic biomarkers yielded the highest AUC-ROCs (0.819-0.922); other classes added little to further discrimination of the subtypes. Among the top five biomarkers in each of these RFs were methylation, micro RNA, and lactate markers, suggesting their biological role in symptom severity.

"GrimAge," an epigenetic predictor of mortality, is accelerated in major depressive disorder.

Major depressive disorder (MDD) is associated with premature mortality and is an independent risk factor for a broad range of diseases, especially those associated with aging, such as cardiovascular disease, diabetes, and Alzheimer's disease. However, the pathophysiology underlying increased rates of somatic disease in MDD remains unknown. It has been proposed that MDD represents a state of accelerated cellular aging, and several measures of cellular aging have been developed in recent years. Among such metrics, estimators of biological age based on predictable age-related patterns of DNA methylation (DNAm), so-called 'epigenetic clocks', have shown particular promise for their ability to capture accelerated aging in psychiatric disease. The recently developed DNAm metric known as 'GrimAge' is unique in that it was trained on time-to-death data and has outperformed its predecessors in predicting both morbidity and mortality. Yet, GrimAge has not been investigated in MDD. Here we measured GrimAge in 49 somatically healthy unmedicated individuals with MDD and 60 age-matched healthy controls. We found that individuals with MDD exhibited significantly greater GrimAge relative to their chronological age ('AgeAccelGrim') compared to healthy controls (p = 0.001), with a median of 2 years of excess cellular aging. This difference remained significant after controlling for sex, current smoking status, and body-mass index (p = 0.015). These findings are consistent with prior suggestions of accelerated cellular aging in MDD, but are the first to demonstrate this with an epigenetic metric predictive of premature mortality.

The DSM-5 Clinical and Public Health Committee (CPHC): operations, mechanics, controversies and recommendations.

BACKGROUND: For DSM - 5, the American Psychiatric Association Board of Trustees established a robust vetting and review process that included two review committees that did not exist in the development of prior DSMs, the Scientific Review Committee (SRC) and the Clinical and Public Health Committee (CPHC). The CPHC was created as a body that could independently review the clinical and public health merits of various proposals that would fall outside of the strictly defined scientific process. METHODS: This article describes the principles and issues which led to the creation of the CPHC, the composition and vetting of the committee, and the processes developed by the committee - including the use of external reviewers. RESULTS: Outcomes of some of the more involved CPHC deliberations, specifically, decisions concerning elements of diagnoses for major depressive disorder, autism spectrum disorder, catatonia, and substance use disorders, are described. The Committee's extensive reviews and its recommendations regarding Personality Disorders are also discussed. CONCLUSIONS: On the basis of our experiences, the CPHC membership unanimously believes that external review processes to evaluate and respond to Work Group proposals is essential for future DSM efforts. The Committee also recommends that separate SRC and CPHC committees be appointed to assess proposals for scientific merit and for clinical and public health utility and impact.

Genome-wide mapping of brain phenotypes in extended pedigrees with strong genetic loading for bipolar disorder.

Bipolar disorder is a highly heritable illness, associated with alterations of brain structure. As such, identification of genes influencing inter-individual differences in brain morphology may help elucidate the underlying pathophysiology of bipolar disorder (BP). To identify quantitative trait loci (QTL) that contribute to phenotypic variance of brain structure, structural neuroimages were acquired from family members (n = 527) of extended pedigrees heavily loaded for bipolar disorder ascertained from genetically isolated populations in Latin America. Genome-wide linkage and association analysis were conducted on the subset of heritable brain traits that showed significant evidence of association with bipolar disorder (n = 24) to map QTL influencing regional measures of brain volume and cortical thickness. Two chromosomal regions showed significant evidence of linkage; a QTL on chromosome 1p influencing corpus callosum volume and a region on chromosome 7p linked to cortical volume. Association analysis within the two QTLs identified three SNPs correlated with the brain measures.

A DNA methylation clock associated with age-related illnesses and mortality is accelerated in men with combat PTSD.

DNA methylation patterns at specific cytosine-phosphate-guanine (CpG) sites predictably change with age and can be used to derive "epigenetic age", an indicator of biological age, as opposed to merely chronological age. A relatively new estimator, called "DNAm GrimAge", is notable for its superior predictive ability in older populations regarding numerous age-related metrics like time-to-death, time-to-coronary heart disease, and time-to-cancer. PTSD is associated with premature mortality and frequently has comorbid physical illnesses suggestive of accelerated biological aging. This is the first study to assess DNAm GrimAge in PTSD patients. We investigated the acceleration of GrimAge relative to chronological age, denoted "AgeAccelGrim" in combat trauma-exposed male veterans with and without PTSD using cross-sectional and longitudinal data from two independent well-characterized veteran cohorts. In both cohorts, AgeAccelGrim was significantly higher in the PTSD group compared to the control group (N = 162, 1.26 vs -0.57, p = 0.001 and N = 53, 0.93 vs -1.60 Years, p = 0.008), suggesting accelerated biological aging in both cohorts with PTSD. In 3-year follow-up study of individuals initially diagnosed with PTSD (N = 26), changes in PTSD symptom severity were correlated with AgeAccelGrim changes (r = 0.39, p = 0.049). In addition, the loss of CD28 cell surface markers on CD8 + T cells, an indicator of T-cell senescence/exhaustion that is associated with biological aging, was positively correlated with AgeAccelGrim, suggesting an immunological contribution to the accelerated biological aging. Overall, our findings delineate cellular correlates of biological aging in combat-related PTSD, which may help explain the increased medical morbidity and mortality seen in this disease.

Pre-treatment allostatic load and metabolic dysregulation predict SSRI response in major depressive disorder: a preliminary report.

BACKGROUND: Major depressive disorder (MDD) is associated with increased allostatic load (AL; a measure of physiological costs of repeated/chronic stress-responding) and metabolic dysregulation (MetD; a measure of metabolic health and precursor to many medical illnesses). Though AL and MetD are associated with poor somatic health outcomes, little is known regarding their relationship with antidepressant-treatment outcomes. METHODS: We determined pre-treatment AL and MetD in 67 healthy controls and 34 unmedicated, medically healthy MDD subjects. Following this, MDD subjects completed 8-weeks of open-label selective serotonin reuptake inhibitor (SSRI) antidepressant treatment and were categorized as 'Responders' (⩾50% improvement in depression severity ratings) or 'Non-responders' (<50% improvement). Logistic and linear regressions were performed to determine if pre-treatment AL or MetD scores predicted SSRI-response. Secondary analyses examined cross-sectional differences between MDD and control groups. RESULTS: Pre-treatment AL and MetD scores significantly predicted continuous antidepressant response (i.e. absolute decreases in depression severity ratings) (p = 0.012 and 0.014, respectively), as well as post-treatment status as a Responder or Non-responder (p = 0.022 and 0.040, respectively), such that higher pre-treatment AL and MetD were associated with poorer SSRI-treatment outcomes. Pre-treatment AL and MetD of Responders were similar to Controls, while those of Non-responders were significantly higher than both Responders (p = 0.025 and 0.033, respectively) and Controls (p = 0.039 and 0.001, respectively). CONCLUSIONS: These preliminary findings suggest that indices of metabolic and hypothalamic-pituitary-adrenal-axis dysregulation are associated with poorer SSRI-treatment response. To our knowledge, this is the first study to demonstrate that these markers of medical disease risk also predict poorer antidepressant outcomes.

Genetic analysis of activity, brain and behavioral associations in extended families with heavy genetic loading for bipolar disorder.

BACKGROUND: Disturbed sleep and activity are prominent features of bipolar disorder type I (BP-I). However, the relationship of sleep and activity characteristics to brain structure and behavior in euthymic BP-I patients and their non-BP-I relatives is unknown. Additionally, underlying genetic relationships between these traits have not been investigated. METHODS: Relationships between sleep and activity phenotypes, assessed using actigraphy, with structural neuroimaging (brain) and cognitive and temperament (behavior) phenotypes were investigated in 558 euthymic individuals from multi-generational pedigrees including at least one member with BP-I. Genetic correlations between actigraphy-brain and actigraphy-behavior associations were assessed, and bivariate linkage analysis was conducted for trait pairs with evidence of shared genetic influences. RESULTS: More physical activity and longer awake time were significantly associated with increased brain volumes and cortical thickness, better performance on neurocognitive measures of long-term memory and executive function, and less extreme scores on measures of temperament (impulsivity, cyclothymia). These associations did not differ between BP-I patients and their non-BP-I relatives. For nine activity-brain or activity-behavior pairs there was evidence for shared genetic influence (genetic correlations); of these pairs, a suggestive bivariate quantitative trait locus on chromosome 7 for wake duration and verbal working memory was identified. CONCLUSIONS: Our findings indicate that increased physical activity and more adequate sleep are associated with increased brain size, better cognitive function and more stable temperament in BP-I patients and their non-BP-I relatives. Additionally, we found evidence for pleiotropy of several actigraphy-behavior and actigraphy-brain phenotypes, suggesting a shared genetic basis for these traits.

Effect of Combat Exposure and Posttraumatic Stress Disorder on Telomere Length and Amygdala Volume.

BACKGROUND: Traumatic stress can adversely affect physical and mental health through neurobiological stress response systems. We examined the effects of trauma exposure and posttraumatic stress disorder (PTSD) on telomere length, a biomarker of cellular aging, and volume of the amygdala, a key structure of stress regulation, in combat-exposed veterans. In addition, the relationships of psychopathological symptoms and autonomic function with telomere length and amygdala volume were examined. METHODS: Male combat veterans were categorized as having PTSD diagnosis (n = 102) or no lifetime PTSD diagnosis (n = 111) based on the Clinician-Administered PTSD Scale. Subjects were assessed for stress-related psychopathology, trauma severity, autonomic function, and amygdala volumes by magnetic resonance imaging. RESULTS: A significant interaction was found between trauma severity and PTSD status for telomere length and amygdala volume after adjusting for multiple confounders. Subjects with PTSD showed shorter telomere length and larger amygdala volume than those without PTSD among veterans exposed to high trauma, while there was no significant group difference in these parameters among those exposed to low trauma. Among veterans exposed to high trauma, greater telomere shortening was significantly correlated with greater norepinephrine, and larger amygdala volume was correlated with more severe psychological symptoms and higher heart rates. CONCLUSIONS: These data suggest that the intensity of the index trauma event plays an important role in interacting with PTSD symptomatology and autonomic activity in predicting telomere length and amygdala volume. These results highlight the importance of trauma severity and PTSD status in predicting certain biological outcomes.