Peripheral serotonin levels as a predictor of antidepressant treatment response: A systematic review.

There are currently no reliable biomarkers to predict clinical response to pharmacological treatments of depressive disorders. Peripheral blood 5-hydroxytryptamine (5-HT; serotonin) has been suggested as a biomarker of antidepressant treatment response, but there has not been an attempt to systematically summarize and evaluate the scientific evidence of this hypothesis. In this systematic review we searched MEDLINE, Embase, PsycINFO, and the Cochrane Central Register of Controlled Trials. Twenty-six relevant studies investigating peripheral 5-HT as an antidepressant biomarker were identified. In all, we did not find robust support for an association between baseline 5-HT and treatment response. Several larger studies with lower risk of bias, however, showed that higher baseline 5-HT was associated with a greater antidepressant response to SSRIs, prompting future studies to investigate this hypothesis. Our results also confirm previous reports that SSRI treatment is associated with a decrease in peripheral 5-HT levels; however, we were not able to confirm that larger decreases of 5-HT are associated with better treatment outcome as results were inconclusive.

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.

Omega-3 fatty acids for inflamed depression - A match/mismatch study.

Despite decades of research on the pathophysiology of depression, the development of new therapeutic interventions has been slow, and no biomarkers of treatment response have been clinically implemented. Several lines of evidence suggest that the clinical and biological heterogeneity among patients with major depressive disorder (MDD) has hampered progress in this field. MDD with low-grade inflammation - "inflamed depression" - is a subtype of depression that may be associated with a superior antidepressant treatment response to anti-inflammatory compounds. Omega-3 fatty acid eicosapentaenoic acid (EPA) has anti-inflammatory properties, and preliminary data suggest that it may be particularly efficacious in inflamed depression. In this study we tested the hypothesis that add-on EPA has greater antidepressant efficacy in MDD patients with high baseline high-sensitivity C-reactive protein (hs-CRP) compared to MDD patients with low hs-CRP. All subjects received 2.2 g EPA, 400 mg docosahexaenoic acid and 800 mg of other fatty acids daily for 8 weeks, added to stable ongoing antidepressant treatment. The primary outcome was change in the 17-item Hamilton Depression Rating Scale (HAMD-17). Patients and raters were blind to baseline hs-CRP status. In an intention-to-treat analysis including all subjects with at least one post baseline visit (n = 101), ahs-CRPcut-off of ≥1 mg/L, but not ≥3 mg/L, was associated with a greater improvement in HAMD-17 total score. In addition to a general antidepressant effect among patients with hs-CRP ≥ 1 mg/L, adjuvant EPA treatment improved symptoms putatively related to inflamed depression such as fatigue and sleep difficulties. This adds to the mounting evidence that delineation of MDD subgroups based on inflammation may be clinically relevant to predict treatment response to anti-inflammatory interventions.

Painful physical symptoms and antidepressant treatment outcome in depression: a systematic review and meta-analysis.

BACKGROUND: Painful physical symptoms (PPS) are highly prevalent in patients with major depressive disorder (MDD). Presence of PPS in depressed patients are potentially associated with poorer antidepressant treatment outcome. We aimed to evaluate the association of baseline pain levels and antidepressant treatment outcomes. METHODS: We searched PubMed, Embase and Cochrane Library databases from inception through February 2023 based on a pre-registered protocol (PROSPERO: CRD42022381349). We included original studies that reported pretreatment pain measures in antidepressant treatment responder/remitter and non-responder/non-remitter among patients with MDD. Data extraction and quality assessment were performed following the Preferred Reporting Items for Systematic Reviews and Meta-analyses by two reviewers independently. The primary outcome was the difference of the pretreatment pain levels between antidepressant treatment responder/remitter and non-responder/non-remitter. Random-effects meta-analysis was used to calculate effect sizes (Hedge's g) and subgroup and meta-regression analyses were used to explore sources of heterogeneity. RESULTS: A total of 20 studies were included. Six studies reported significantly higher baseline pain severity levels in MDD treatment non-responders (Hedge's g = 0.32; 95% CI, 0.13-0.51; P = 0.0008). Six studies reported the presence of PPS (measured using a pain severity scale) was significantly associated with poor treatment response (OR = 1.46; 95% CI, 1.04-2.04; P = 0.028). Five studies reported significant higher baseline pain interference levels in non-responders (Hedge's g = 0.46; 95% CI, 0.32-0.61; P < 0.0001). Four studies found significantly higher baseline pain severity levels in non-remitters (Hedge's g = 0.27; 95% CI, 0.14-0.40; P < 0.0001). Eight studies reported the presence of PPS significantly associated with treatment non-remission (OR = 1.70; 95% CI, 1.24-2.32; P = 0.0009). CONCLUSIONS: This study suggests that PPS are negatively associated with the antidepressant treatment outcome in patients with MDD. It is possible that better management in pain conditions when treating depression can benefit the therapeutic effects of antidepressant medication in depressed patients.

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.

Integrated analysis of proteomics, epigenomics and metabolomics data revealed divergent pathway activation patterns in the recent versus chronic post-traumatic stress disorder.

Metabolomics, proteomics and DNA methylome assays, when done in tandem from the same blood sample and analyzed together, offer an opportunity to evaluate the molecular basis of post-traumatic stress disorder (PTSD) course and pathogenesis. We performed separate metabolomics, proteomics, and DNA methylome assays on blood samples from two well-characterized cohorts of 159 active duty male participants with relatively recent onset PTSD (<1.5 years) and 300 male veterans with chronic PTSD (>7 years). Analyses of the multi-omics datasets from these two independent cohorts were used to identify convergent and distinct molecular profiles that might constitute potential signatures of severity and progression of PTSD and its comorbid conditions. Molecular signatures indicative of homeostatic processes such as signaling and metabolic pathways involved in cellular remodeling, neurogenesis, molecular safeguards against oxidative stress, metabolism of polyunsaturated fatty acids, regulation of normal immune response, post-transcriptional regulation, cellular maintenance and markers of longevity were significantly activated in the active duty participants with recent PTSD. In contrast, we observed significantly altered multimodal molecular signatures associated with chronic inflammation, neurodegeneration, cardiovascular and metabolic disorders, and cellular attritions in the veterans with chronic PTSD. Activation status of signaling and metabolic pathways at the early and late timepoints of PTSD demonstrated the differential molecular changes related to homeostatic processes at its recent and multi-system syndromes at its chronic phase. Molecular alterations in the recent PTSD seem to indicate some sort of recalibration or compensatory response, possibly directed in mitigating the pathological trajectory of the disorder.

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.

Associations of stress and stress-related psychiatric disorders with GrimAge acceleration: review and suggestions for future work.

The notion of "biological aging" as distinct from chronological aging has been of increasing interest in psychiatry, and many studies have explored associations of stress and psychiatric illness with accelerated biological aging. The "epigenetic clocks" are one avenue of this research, wherein "biological age" is estimated using DNA methylation data from specific CpG dinucleotide sites within the human genome. Many iterations of the epigenetic clocks have been developed, but the GrimAge clock continues to stand out for its ability to predict morbidity and mortality. Several studies have now explored associations of stress, PTSD, and MDD with GrimAge acceleration (GrimAA). While stress, PTSD, and MDD are distinct psychiatric entities, they may share common mechanisms underlying accelerated biological aging. Yet, no one has offered a review of the evidence on associations of stress and stress-related psychopathology with GrimAA. In this review, we identify nine publications on associations of stress, PTSD, and MDD with GrimAA. We find that results are mixed both within and across each of these exposures. However, we also find that analytic methods - and specifically, the choice of covariates - vary widely between studies. To address this, we draw upon popular methods from the field of clinical epidemiology to offer (1) a systematic framework for covariate selection, and (2) an approach to results reporting that facilitates analytic consensus. Although covariate selection will differ by the research question, we encourage researchers to consider adjustment for tobacco, alcohol use, physical activity, race, sex, adult socioeconomic status, medical comorbidity, and blood cell composition.

Molecular signatures of post-traumatic stress disorder in war-zone-exposed veteran and active-duty soldiers.

Post-traumatic stress disorder (PTSD) is a multisystem syndrome. Integration of systems-level multi-modal datasets can provide a molecular understanding of PTSD. Proteomic, metabolomic, and epigenomic assays are conducted on blood samples of two cohorts of well-characterized PTSD cases and controls: 340 veterans and 180 active-duty soldiers. All participants had been deployed to Iraq and/or Afghanistan and exposed to military-service-related criterion A trauma. Molecular signatures are identified from a discovery cohort of 218 veterans (109/109 PTSD+/-). Identified molecular signatures are tested in 122 separate veterans (62/60 PTSD+/-) and in 180 active-duty soldiers (PTSD+/-). Molecular profiles are computationally integrated with upstream regulators (genetic/methylation/microRNAs) and functional units (mRNAs/proteins/metabolites). Reproducible molecular features of PTSD are identified, including activated inflammation, oxidative stress, metabolic dysregulation, and impaired angiogenesis. These processes may play a role in psychiatric and physical comorbidities, including impaired repair/wound healing mechanisms and cardiovascular, metabolic, and psychiatric diseases.

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.

The Genetic Basis for the Increased Prevalence of Metabolic Syndrome among Post-Traumatic Stress Disorder Patients.

Post-traumatic stress disorder (PTSD) is a highly debilitating psychiatric disorder that can be triggered by exposure to extreme trauma. Even if PTSD is primarily a psychiatric condition, it is also characterized by adverse somatic comorbidities. One illness commonly co-occurring with PTSD is Metabolic syndrome (MetS), which is defined by a set of health risk/resilience factors including obesity, elevated blood pressure, lower high-density lipoprotein cholesterol, higher low-density lipoprotein cholesterol, higher triglycerides, higher fasting blood glucose and insulin resistance. Here, phenotypic association between PTSD and components of MetS are tested on a military veteran cohort comprising chronic PTSD presentation (n = 310, 47% cases, 83% male). Consistent with previous observations, we found significant phenotypic correlation between the various components of MetS and PTSD severity scores. To examine if this observed symptom correlations stem from a shared genetic background, we conducted genetic correlation analysis using summary statistics data from large-scale genetic studies. Our results show robust positive genetic correlation between PTSD and MetS (rg[SE] = 0.33 [0.056], p = 4.74E-09), and obesity-related components of MetS (rg = 0.25, SE = 0.05, p = 6.4E-08). Prioritizing genomic regions with larger local genetic correlation implicate three significant loci. Overall, these findings show significant genetic overlap between PTSD and MetS, which may in part account for the markedly increased occurrence of MetS among PTSD patients.

An immunogenomic phenotype predicting behavioral treatment response: Toward precision psychiatry for mothers and children with trauma exposure.

Inflammatory pathways predict antidepressant treatment non-response among individuals with major depression; yet, this phenomenon may have broader transdiagnostic and transtherapeutic relevance. Among trauma-exposed mothers (Mage = 32 years) and their young children (Mage = 4 years), we tested whether genomic and proteomic biomarkers of pro-inflammatory imbalance prospectively predicted treatment response (PTSD and depression) to an empirically-supported behavioral treatment. Forty-three mother-child dyads without chronic disease completed Child Parent Psychotherapy (CPP) for roughly 9 months. Maternal blood was drawn pre-treatment, CD14 + monocytes isolated, gene expression derived from RNA sequencing (n = 34; Illumina HiSeq 4000;TruSeqcDNA library), and serum assayed (n = 43) for C-Reactive Protein (CRP) and interleukin-1ß (IL-1ß). Symptoms of PTSD and depression decreased significantly from pre- to post-treatment for both mothers and children (all p's < 0.01). Nonetheless, a higher pre-treatment maternal pro-inflammatory imbalance of M1-like versus M2-like macrophage-associated RNA expression (M1/M2) (ß = 0.476, p = .004) and IL-1ß (ß=0.333, p = .029), but not CRP, predicted lesser improvements in maternal PTSD symptoms, unadjusted and adjusting for maternal age, BMI, ethnicity, antidepressant use, income, education, and US birth. Only higher pre-treatment M1/M2 predicted a clinically-relevant threshold of PTSD non-response among mothers (OR = 3.364, p = .015; ROC-AUC = 0.78). Additionally, higher M1/M2 predicted lesser decline in maternal depressive symptoms (ß = 0.556, p = .001), though not independent of PTSD symptoms. For child outcomes, higher maternal IL-1ß significantly predicted poorer PTSD and depression symptom trajectories (ß's = 0.318-0.429, p's < 0.01), while M1/M2 and CRP were marginally associated with poorer PTSD symptom improvement (ß's = 0.295-0.333, p's < 0.056). Pre-treatment pro-inflammatory imbalance prospectively predicts poorer transdiagnostic symptom response to an empirically-supported behavioral treatment for trauma-exposed women and their young children.

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.

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.

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.

"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.

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.

Epigenetic biotypes of post-traumatic stress disorder in war-zone exposed veteran and active duty males.

Post-traumatic stress disorder (PTSD) is a heterogeneous condition evidenced by the absence of objective physiological measurements applicable to all who meet the criteria for the disorder as well as divergent responses to treatments. This study capitalized on biological diversity observed within the PTSD group observed following epigenome-wide analysis of a well-characterized Discovery cohort (N = 166) consisting of 83 male combat exposed veterans with PTSD, and 83 combat veterans without PTSD in order to identify patterns that might distinguish subtypes. Computational analysis of DNA methylation (DNAm) profiles identified two PTSD biotypes within the PTSD+ group, G1 and G2, associated with 34 clinical features that are associated with PTSD and PTSD comorbidities. The G2 biotype was associated with an increased PTSD risk and had higher polygenic risk scores and a greater methylation compared to the G1 biotype and healthy controls. The findings were validated at a 3-year follow-up (N = 59) of the same individuals as well as in two independent, veteran cohorts (N = 54 and N = 38), and an active duty cohort (N = 133). In some cases, for example Dopamine-PKA-CREB and GABA-PKC-CREB signaling pathways, the biotypes were oppositely dysregulated, suggesting that the biotypes were not simply a function of a dimensional relationship with symptom severity, but may represent distinct biological risk profiles underpinning PTSD. The identification of two novel distinct epigenetic biotypes for PTSD may have future utility in understanding biological and clinical heterogeneity in PTSD and potential applications in risk assessment for active duty military personnel under non-clinician-administered settings, and improvement of PTSD diagnostic markers.

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.

Pre-deployment risk factors for PTSD in active-duty personnel deployed to Afghanistan: a machine-learning approach for analyzing multivariate predictors.

Active-duty Army personnel can be exposed to traumatic warzone events and are at increased risk for developing post-traumatic stress disorder (PTSD) compared with the general population. PTSD is associated with high individual and societal costs, but identification of predictive markers to determine deployment readiness and risk mitigation strategies is not well understood. This prospective longitudinal naturalistic cohort study-the Fort Campbell Cohort study-examined the value of using a large multidimensional dataset collected from soldiers prior to deployment to Afghanistan for predicting post-deployment PTSD status. The dataset consisted of polygenic, epigenetic, metabolomic, endocrine, inflammatory and routine clinical lab markers, computerized neurocognitive testing, and symptom self-reports. The analysis was computed on active-duty Army personnel (N = 473) of the 101st Airborne at Fort Campbell, Kentucky. Machine-learning models predicted provisional PTSD diagnosis 90-180 days post deployment (random forest: AUC = 0.78, 95% CI = 0.67-0.89, sensitivity = 0.78, specificity = 0.71; SVM: AUC = 0.88, 95% CI = 0.78-0.98, sensitivity = 0.89, specificity = 0.79) and longitudinal PTSD symptom trajectories identified with latent growth mixture modeling (random forest: AUC = 0.85, 95% CI = 0.75-0.96, sensitivity = 0.88, specificity = 0.69; SVM: AUC = 0.87, 95% CI = 0.79-0.96, sensitivity = 0.80, specificity = 0.85). Among the highest-ranked predictive features were pre-deployment sleep quality, anxiety, depression, sustained attention, and cognitive flexibility. Blood-based biomarkers including metabolites, epigenomic, immune, inflammatory, and liver function markers complemented the most important predictors. The clinical prediction of post-deployment symptom trajectories and provisional PTSD diagnosis based on pre-deployment data achieved high discriminatory power. The predictive models may be used to determine deployment readiness and to determine novel pre-deployment interventions to mitigate the risk for deployment-related PTSD.