Proteomic profiles of cytokines and chemokines in moderate to severe depression: Implications for comorbidities and biomarker discovery.

Objective: This study assessed the proteomic profiles of cytokines and chemokines in individuals with moderate to severe depression, with or without comorbid medical disorders, compared to healthy controls. Two proteomic multiplex platforms were employed for this purpose. Metods: An immunofluorescent multiplex platform and an aptamer-based method were used to evaluate 32 protein analytes from 153 individuals with moderate to severe major depressive disorder (MDD) and healthy controls (HCs). The study focused on determining the level of agreement between the two platforms and evaluating the ability of individual analytes and principal components (PCs) to differentiate between the MDD and HC groups. Additionally, the study investigated the relationship between PCs consisting of chemokines and cytokines and comorbid inflammatory and cardiometabolic diseases. Findings: Analysis revealed a small or moderate correlation between 47% of the analytes measured by the two platforms. Two proteomic profiles were identified that differentiated individuals with moderate to severe MDD from HCs. High eotaxin, age, BMI, IP-10, or IL-10 characterized profile 1. This profile was associated with several cardiometabolic risk factors, including hypertension, hyperlipidemia, and type 2 diabetes. Profile 2 is characterized by higher age, BMI, interleukins, and a strong negative loading for eotaxin. This profile was associated with inflammation but not cardiometabolic risk factors. Conclusion: This study provides further evidence that proteomic profiles can be used to identify potential biomarkers and pathways associated with MDD and comorbidities. Our findings suggest that MDD is associated with distinct profiles of proteins that are also associated with cardiometabolic risk factors, inflammation, and obesity. In particular, the chemokines eotaxin and IP-10 appear to play a role in the relationship between MDD and cardiometabolic risk factors. These findings suggest that a focus on the interplay between MDD and comorbidities may be useful in identifying potential targets for intervention and improving overall health outcomes.

Toward a Precision Treatment Approach for Metabolic Depression: Integrating Epidemiology, Neuroscience, and Psychiatry.

Background: Individuals with comorbid major depressive disorder and type 2 diabetes represent an important subgroup of patients for whom conventional treatment may be insufficient. A precision treatment approach that addresses insulin resistance with an outcome of a positive response to antidepressants may prove beneficial. Methods: This study utilized an emulated target trial on a large dataset from the Optum Clinformatics Data Mart Database. We evaluated the effect of adjuvant pioglitazone, an insulin-sensitizing drug, on antidepressant response among 4696 people with type 2 diabetes, comparing it with DPP4 (dipeptidyl peptidase-4) inhibitors (non-insulin-sensitizing). An additional analysis involving 6518 participants was conducted to assess the efficacy of pioglitazone versus sulfonylureas. Results: The instrumental variable analysis indicated that the initiation of an antidepressant with pioglitazone was superior to DPP4 inhibitors in terms of antidepressant response, with fewer treatment shifts and/or additions of new antidepressant or antipsychotic over a 1-year period. This result was consistent when pioglitazone was compared with sulfonylureas in a supplemental analysis. Conclusions: Our findings suggest that pioglitazone may be more effective than DPP4 inhibitors or sulfonylureas in enhancing antidepressant response among people with comorbid major depressive disorder and type 2 diabetes. This provides a strong case for the use of pioglitazone in patients with these conditions, emphasizing the potential of precision medicine strategies. The results should be interpreted with caution due to inherent limitations associated with observational data.

Longitudinal Digital Mood Charting in Bipolar Disorder: Experiences with ChronoRecord Over 20 Years.

INTRODUCTION: Longitudinal study is an essential methodology for understanding disease trajectories, treatment effects, symptom changes, and long-term outcomes of affective disorders. Daily self-charting of mood and other illness-related variables is a commonly recommended intervention. With the widespread acceptance of home computers in the early 2000s, automated tools were developed for patient mood charting, such as ChronoRecord, a software validated by patients with bipolar disorder. The purpose of this study was to summarize the daily mood, sleep, and medication data collected with ChronoRecord, and highlight some of the key research findings. Lessons learned from implementing a computerized tool for patient self-reporting are also discussed. METHODS: After a brief training session, ChronoRecord software for daily mood charting was installed on a home computer and used by 609 patients with affective disorders. RESULTS: The mean age of the patients was 40.3±11.8 years, a mean age of onset was 22±11.2 years, and 71.4% were female. Patients were euthymic for 70.8% of days, 15.1% had mild depression, 6.6% had severe depression, 6.6% had hypomania, and 0.8% had mania. Among all mood groups, 22.4% took 1-2 medications, 37.2% took 3-4 medications, 25.7 took 5-6 medications, 11.6% took 7-8 medications, and 3.1% took >8 medications. CONCLUSION: The daily mood charting tool is a useful tool for increasing patient involvement in their care, providing detailed patient data to the physician, and increasing understanding of the course of illness. Longitudinal data from patient mood charting was helpful in both clinical and research settings.

Prevalence and outcomes of rapid cycling bipolar disorder: Mixed method systematic meta-review.

Rapid-cycling in bipolar disorder (RC-BD) is associated with greater illness morbidity and inferior treatment response but many aspects remain unclear, prompting this systematic review of its definitions, prevalence, and clinical characteristics. We searched multiple literature databases through April 2022 for systematic reviews or meta-analyses on RC-BD and extracted associated definitions, prevalence, risk-factors, and clinical outcomes. We assessed study quality (NIH Quality Assessment Tool) and levels of evidence (Oxford criteria). Of 146 identified reviews, 22 fulfilling selection criteria were included, yielding 30 studies involving 13,698 BD patients, of whom 3777 (27.6% [CI: 26.8-28.3]) were considered RC-BD, as defined in 14 reports by ≥4 recurrences/year within the past 12 months or in any year, without considering responsiveness to treatment. Random-effects meta-analytically pooled one-year prevalence was 22.3% [CI: 14.4-32.9] in 12 reports and lifetime prevalence was 35.5% [27.6-44.3] in 18 heterogenous reports. Meta-regression indicated greater lifetime prevalence of RC-BD among women than men (p=0.003). Association of RC-BD with suicide attempts, and unsatisfactory response to mood-stabilizers was supported by strong evidence (Level 1); associations with childhood maltreatment, mixed-features, female sex, and type-II BD had moderate evidence (Level 2). Other factors: genetic predisposition, metabolic disturbances or hypothyroidism, antidepressant exposure, predominant depressive polarity (Level 3), along with greater illness duration and immune-inflammatory dysfunction (Level 4) require further study. RC-BD was consistently recognized as having high prevalence (22.3%-35.5% of BD cases) and inferior treatment response. Identified associated factors can inform clinical practice. Long-term illness-course, metabolic factors, and optimal treatment require further investigation.

Carnitine octanoyltransferase is important for the assimilation of exogenous acetyl-L-carnitine into acetyl-CoA in mammalian cells.

In eukaryotes, carnitine is best known for its ability to shuttle esterified fatty acids across mitochondrial membranes for ß-oxidation. It also returns to the cytoplasm, in the form of acetyl-L-carnitine (LAC), some of the resulting acetyl groups for posttranslational protein modification and lipid biosynthesis. While dietary LAC supplementation has been clinically investigated, its effects on cellular metabolism are not well understood. To explain how exogenous LAC influences mammalian cell metabolism, we synthesized isotope-labeled forms of LAC and its analogs. In cultures of glucose-limited U87MG glioma cells, exogenous LAC contributed more robustly to intracellular acetyl-CoA pools than did ß-hydroxybutyrate, the predominant circulating ketone body in mammals. The fact that most LAC-derived acetyl-CoA is cytosolic is evident from strong labeling of fatty acids in U87MG cells by exogenous 13C2-acetyl-L-carnitine. We found that the addition of d3-acetyl-L-carnitine increases the supply of acetyl-CoA for cytosolic posttranslational modifications due to its strong kinetic isotope effect on acetyl-CoA carboxylase, the first committed step in fatty acid biosynthesis. Surprisingly, whereas cytosolic carnitine acetyltransferase is believed to catalyze acetyl group transfer from LAC to coenzyme A, CRAT-/- U87MG cells were unimpaired in their ability to assimilate exogenous LAC into acetyl-CoA. We identified carnitine octanoyltransferase as the key enzyme in this process, implicating a role for peroxisomes in efficient LAC utilization. Our work has opened the door to further biochemical investigations of a new pathway for supplying acetyl-CoA to certain glucose-starved cells.

Shared genetic influences on depression and menopause symptoms.

BACKGROUND: Women experience major depression and post-traumatic stress disorder (PTSD) approximately twice as often as men. Estrogen is thought to contribute to sex differences in these disorders, and reduced estrogen is also known to be a key driver of menopause symptoms such as hot flashes. Moreover, estrogen is used to treat menopause symptoms. In order to test for potential shared genetic influences between menopause symptoms and psychiatric disorders, we conducted a genome-wide association study (GWAS) of estrogen medication use (as a proxy for menopause symptoms) in the UK Biobank. METHODS: The analysis included 232 993 women aged 39-71 in the UK Biobank. The outcome variable for genetic analyses was estrogen medication use, excluding women using hormonal contraceptives. Trans-ancestry GWAS meta-analyses were conducted along with genetic correlation analyses on the European ancestry GWAS results. Hormone usage was also tested for association with depression and PTSD. RESULTS: GWAS of estrogen medication use (compared to non-use) identified a locus in the TACR3 gene, which was previously linked to hot flashes in menopause [top rs77322567, odds ratio (OR) = 0.78, p = 7.7 × 10-15]. Genetic correlation analyses revealed shared genetic influences on menopause symptoms and depression (rg = 0.231, s.e.= 0.055, p = 2.8 × 10-5). Non-genetic analyses revealed higher psychiatric symptoms scores among women using estrogen medications. CONCLUSIONS: These results suggest that menopause symptoms have a complex genetic etiology which is partially shared with genetic influences on depression. Moreover, the TACR3 gene identified here has direct clinical relevance; antagonists for the neurokinin 3 receptor (coded for by TACR3) are effective treatments for hot flashes.

Insulin resistance and accelerated cognitive aging.

Insulin resistance may be an early sign of metabolic dysfunction with the potential to lead to neuropsychiatric sequelae in the long term. In order to identify whether insulin resistance in otherwise healthy young and middle-aged adults is associated with preclinical signs of neuropsychiatric impairment, we recruited 126 overweight but nondiabetic, nondepressed individuals who completed an insulin suppression test for direct measurement of insulin resistance as well as a battery of cognitive and neuropsychiatric measures. Insulin resistance was associated with weaker performance on a fine motor task (Purdue Pegboard) as well as increases in subclinical symptoms of depression. We submit that insulin resistance in early to mid-adulthood may be an important predictor of long-term risk for metabolic, psychiatric, and neurobehavioral dysfunction.

Endophenotypic correlates of cognitive function in reproductive-age individuals with polycystic ovary syndrome.

Objective: To characterize cognitive performance in relation to hormonal and metabolic factors in women with polycystic ovary syndrome (PCOS). Design: Cross-sectional study. Setting: Tertiary university center. Patients: A total of 48 individuals, aged 21-46 years, with PCOS according to the Rotterdam criteria. Interventions: Complete history and physical examinations, endovaginal ultrasounds, dermatologic assessments, neuropsychological assessments, and metabolic and hormonal serum tests. Main Outcome Measures: Sample-based z-scores on a comprehensive cognitive test battery. Results: Subjects were defined as having an androgenic (n = 31) or a nonandrogenic (n = 17) PCOS phenotype. Compared with their nonandrogenized counterparts, subjects with hyperandrogenism demonstrated lower relative performance on the tests of executive function (ß-coefficient for the executive function composite z-score, -0.44; 95% confidence interval, -0.79 to -0.09), despite similar performance on the tests of memory, verbal reasoning, and perceptual reasoning. These differences were independent of age, years of education, and obesity. In an exploratory analysis in which subjects were stratified by the presence of insulin resistance (IR), subjects with PCOS with both IR and hyperandrogenism showed the lowest performance on a composite score of executive function, followed by those with hyperandrogenism alone. Conclusions: In this small study, subjects with hyperandrogenic PCOS demonstrated lower performance on the tests of executive function than subjects with nonandrogenic PCOS. Additional research is needed to confirm these findings in larger cohorts and investigate the role of modifiable factors, including IR, on cognitive outcomes.

Family history of diabetes moderates metabolic depression endophenotypes in overweight/obese adults.

OBJECTIVE: Insulin resistance (IR) is linked to depressive disorders, and there is growing evidence that targeting IR may be beneficial in treating them. We examine the association between depressive symptoms and a direct measure of IR, and whether family history of type 2 diabetes (FHx-T2DM) or major depressive disorder (FHx-MDD) moderate this relationship. METHODS: Cross-sectional data were collected from 96 primarily overweight/obese adults ages 25-50 without diabetes or clinical depression. Multiple regression and correlation analyses were used to assess the association between depressive symptoms and a direct measure of IR (steady-state plasma glucose) as well as moderating effects of FHx-T2DM or FHx-MDD. RESULTS: In the total sample, elevated depressive symptoms were positively associated with IR (p = 0.005). IR was associated with depressive symptoms in subjects with FHx-T2DM (p = 0.002) or FHx-MDD (p = 0.009) whereas BMI was associated with depressive symptoms in subjects without FHx-T2DM (p = 0.049) or FHx-MDD (p = 0.029). The odds of being in the top tertile of IR increased with elevated depressive symptoms alone (OR, 4.22; 95%CI, 1.15 to 17.33), presence of FHx-T2DM alone (OR, 3.42; 95%CI, 1.26 to 10.00), and presence of both FHx-T2DM and elevated depressive symptoms (OR, 10.08; 95%CI, 1.94 to 96.96). CONCLUSIONS: Our findings indicate that depressive symptoms are positively associated with a direct measure of IR in overweight/obese individuals without diabetes or clinical depression. This association is moderated by FHx-T2DM. Early identification of groups vulnerable to IR related to depressive symptomatology may be useful for determining personalized interventions that have the potential to reduce morbidity in later years.

Maternal attachment insecurity, maltreatment history, and depressive symptoms are associated with broad DNA methylation signatures in infants.

The early environment, including maternal characteristics, provides many cues to young organisms that shape their long-term physical and mental health. Identifying the earliest molecular events that precede observable developmental outcomes could help identify children in need of support prior to the onset of physical and mental health difficulties. In this study, we examined whether mothers' attachment insecurity, maltreatment history, and depressive symptoms were associated with alterations in DNA methylation patterns in their infants, and whether these correlates in the infant epigenome were associated with socioemotional and behavioral functioning in toddlerhood. We recruited 156 women oversampled for histories of depression, who completed psychiatric interviews and depression screening during pregnancy, then provided follow-up behavioral data on their children at 18 months. Buccal cell DNA was obtained from 32 of their infants for a large-scale analysis of methylation patterns across 5 × 106 individual CpG dinucleotides, using clustering-based significance criteria to control for multiple comparisons. We found that tens of thousands of individual infant CpGs were alternatively methylated in association with maternal attachment insecurity, maltreatment in childhood, and antenatal and postpartum depressive symptoms, including genes implicated in developmental patterning, cell-cell communication, hormonal regulation, immune function/inflammatory response, and neurotransmission. Density of DNA methylation at selected genes from the result set was also significantly associated with toddler socioemotional and behavioral problems. This is the first report to identify novel regions of the human infant genome at which DNA methylation patterns are associated longitudinally both with maternal characteristics and with offspring socioemotional and behavioral problems in toddlerhood.

Lower functional hippocampal connectivity in healthy adults is jointly associated with higher levels of leptin and insulin resistance.

BACKGROUND: Metabolic dysregulation is currently considered a major risk factor for hippocampal pathology. The aim of the present study was to characterize the influence of key metabolic drivers on functional connectivity of the hippocampus in healthy adults. METHODS: Insulin resistance was directly quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test and fasting levels of insulin, glucose, leptin, and cortisol, and measurements of body mass index and waist circumference were obtained in a sample of healthy cognitively intact adults (n = 104). Resting-state neuroimaging data were also acquired for the quantification of hippocampal functional cohesiveness and integration with the major resting-state networks (RSNs). Data-driven analysis using unsupervised machine learning (k-means clustering) was then employed to identify clusters of individuals based on their metabolic and functional connectivity profiles. RESULTS: K-means clustering identified two clusters of increasing metabolic deviance evidenced by cluster differences in the plasma levels of leptin (40.36 (29.97) vs. 27.59 (25.58) µg/L) and the degree of insulin resistance (SSPG concentration: 161.63 (65.27) vs. 125.72 (66.81) mg/dL). Individuals in the cluster with higher metabolic deviance showed lower functional cohesiveness within each hippocampus and lower integration of posterior and anterior components of the left and right hippocampus with the major RSNs. The two clusters did not differ in general intellectual ability or episodic memory. CONCLUSIONS: We identified two clusters of individuals differentiated by abnormalities in insulin resistance, leptin levels, and hippocampal connectivity, with one of the clusters showing greater deviance. These findings support the link between metabolic dysregulation and hippocampal function even in nonclinical samples.

A novel peripheral biomarker for depression and antidepressant response.

In contrast to healthy controls, the heterotrimeric G protein, Gsalpha (Gsα) is ensconced predominantly in lipid rafts in subjects with major depressive disorder (MDD) resulting in impaired stimulation of adenylyl cyclase. In this small proof-of-concept study, we examined the hypothesis that translocation of Gsα from lipid rafts toward a more facile activation of adenylyl cyclase is a biomarker for clinical response to antidepressants. There were 49 subjects with MDD (HamD17 score ≥15) and 59 healthy controls at the screen visit. The AlphaScreen (PerkinElmer) assay measured both basal activity and prostaglandin E1 (PGE1) stimulation of Gsα-adenylyl cyclase to assess the extent of coupling of Gsα with adenylyl cyclase. At screen, platelet samples obtained from MDD subjects revealed significantly lower PGE1 activation of adenylyl cyclase activity than controls (p = 0.02). Subsequently, 19 consenting MDD subjects completed a 6-week open label antidepressant treatment trial. The 11 antidepressant responders (HamD17 improvement ≥50% from screen) revealed significant increase in PGE1-stimulated adenylyl cyclase compared to non-responders (p = 0.05) with an effect size of 0.83 for the PGE1/Gsα lipid-raft biomarker. PGE1 stimulation increased by ≥30% from screen assessment in eight responders (72.7%) and two non-responders (25.0%) [Fisher exact = 0.07] with a positive predictive value for response of 80.0%. In this small, pilot study, increased PGE1 stimulated adenylyl cyclase was associated with antidepressant response in MDD subjects. These data suggest that a simple, high-throughput-capable assay for depression and antidepressant response can be developed. Future studies are needed to evaluate the utility of this biomarker for the treatment of MDD.

Hippocampal volume reduction is associated with direct measure of insulin resistance in adults.

Hippocampal integrity is highly susceptible to metabolic dysfunction, yet its mechanisms are not well defined. We studied 126 healthy individuals aged 23-61 years. Insulin resistance (IR) was quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test. Body mass index (BMI), adiposity, fasting insulin, glucose, leptin as well as structural neuroimaing with automatic hippocampal subfield segmentation were performed. Data analysis using unsupervised machine learning (k-means clustering) identified two subgroups reflecting a pattern of more pronounced hippocampal volume reduction being concurrently associated with greater adiposity and insulin resistance; the hippocampal volume reductions were uniform across subfields. Individuals in the most deviant subgroup were predominantly women (79 versus 42 %) with higher BMI [27.9 (2.5) versus 30.5 (4.6) kg/m2], IR (SSPG concentration, [156 (61) versus 123 (70) mg/dL] and leptinemia [21.7 (17.0) versus 44.5 (30.4) µg/L]. The use of person-based modeling in healthy individuals suggests that adiposity, insulin resistance and compromised structural hippocampal integrity behave as a composite phenotype; female sex emerged as risk factor for this phenotype.

Multidimensional predictors of antidepressant responses: Integrating mitochondrial, genetic, metabolic and environmental factors with clinical outcomes.

Major depressive disorder (MDD) is a primary psychiatric illness worldwide; there is a dearth of new mechanistic models for the development of better therapeutic strategies. Although we continue to discover individual biological factors, a major challenge is the identification of integrated, multidimensional traits underlying the complex heterogeneity of depression and treatment outcomes. Here, we set out to ascertain the emergence of the novel mitochondrial mediator of epigenetic function acetyl-L-carnitine (LAC) in relation to previously described individual predictors of antidepressant responses to the insulin-sensitizing agent pioglitazone. Herein, we report that i) subjects with MDD and shorter leukocyte telomere length (LTL) show decreased levels of LAC, increased BMI, and a history of specific types of childhood trauma; and that ii) these multidimensional factors spanning mitochondrial metabolism, cellular aging, metabolic function, and childhood trauma provide more detailed signatures to predict longitudinal changes in depression severity in response to pioglitazone than individual factors. The findings of multidimensional signatures involved in the pathophysiology of depression and their role in predicting treatment outcomes provide a starting point for the development of a mechanistic framework linking biological networks and environmental factors to clinical outcomes in pursuit of personalized medicine strategies to effectively treat MDD.

Incident Major Depressive Disorder Predicted by Three Measures of Insulin Resistance: A Dutch Cohort Study.

OBJECTIVE: Major depressive disorder is the leading cause of disability worldwide. Yet, there remain significant challenges in predicting new cases of major depression and devising strategies to prevent the disorder. An important first step in this process is identifying risk factors for the incidence of major depression. There is accumulating biological evidence linking insulin resistance, another highly prevalent condition, and depressive disorders. The objectives of this study were to examine whether three surrogate measures of insulin resistance (high triglyceride-HDL [high-density lipoprotein] ratio; prediabetes, as indicated by fasting plasma glucose level; and high central adiposity, as measured by waist circumference) at the time of study enrollment were associated with an increased rate of incident major depressive disorder over a 9-year follow-up period and to assess whether the new onset of these surrogate measures during the first 2 years after study enrollment was predictive of incident major depressive disorder during the subsequent follow-up period. METHODS: The Netherlands Study of Depression and Anxiety (NESDA) is a multisite longitudinal study of the course and consequences of depressive and anxiety disorders in adults. The study population comprised 601 NESDA participants (18-65 years old) without a lifetime history of depression or anxiety disorders. The study's outcome was incident major depressive disorder, defined using DSM-IV criteria. Exposure measures included triglyceride-HDL ratio, fasting plasma glucose level, and waist circumference. RESULTS: Fourteen percent of the sample developed major depressive disorder during follow-up. Cox proportional hazards models indicated that higher triglyceride-HDL ratio was positively associated with an increased risk for incident major depression (hazard ratio=1.89, 95% CI=1.15, 3.11), as were higher fasting plasma glucose levels (hazard ratio=1.37, 95% CI=1.05, 1.77) and higher waist circumference (hazard ratio=1.11 95% CI=1.01, 1.21). The development of prediabetes in the 2-year period after study enrollment was positively associated with incident major depressive disorder (hazard ratio=2.66, 95% CI=1.13, 6.27). The development of high triglyceride-HDL ratio and high central adiposity (cut-point ≥100 cm) in the same period was not associated with incident major depression. CONCLUSIONS: Three surrogate measures of insulin resistance positively predicted incident major depressive disorder in a 9-year follow-up period among adults with no history of depression or anxiety disorder. In addition, the development of prediabetes between enrollment and the 2-year study visit was positively associated with incident major depressive disorder. These findings may have utility for evaluating the risk for the development of major depression among patients with insulin resistance or metabolic pathology.

Exploring brain insulin resistance in adults with bipolar depression using extracellular vesicles of neuronal origin.

Accumulating evidence suggests that disrupted insulin signaling is involved in bipolar disorder (BD) pathogenesis. Herein, we aimed to directly explore the potential role of neuronal insulin signaling using an innovative technique based on biomarkers derived from plasma extracellular vesicles enriched for neuronal origin (NEVs). We leveraged plasma samples from a randomized, double-blind, placebo-controlled, 12-week clinical trial evaluating infliximab as a treatment of bipolar depression. We isolated NEVs using immunoprecipitation against neuronal marker L1CAM from samples collected at baseline and weeks 2, 6 and 12 (endpoint) and measured NEV biomarkers using immunoassays. We assessed neuronal insulin signaling at its first node (IRS-1) and along the canonical (Akt, GSK-3ß, p70S6K) and alternative (ERK1/2, JNK and p38-MAPK) pathways. A subset of participants (n = 27) also underwent whole-brain magnetic resonance imaging (MRI) at baseline and endpoint. Pre-treatment, NEV biomarkers of insulin signaling were independently associated with cognitive function and MRI measures (i.e. hippocampal and ventromedial prefrontal cortex [vmPFC] volumes). In fact, the association between IRS-1 phosphorylation at serine site 312 (pS312-IRS-1), an indicator of insulin resistance, and cognitive dysfunction was mediated by vmPFC volume. In the longitudinal analysis, patients treated with infliximab, a tumor necrosis factor-alpha antagonist with known insulin sensitizing properties, compared to those treated with placebo, had augmented phosphorylation of proteins from the alternative pathway. Infliximab responders had significant increases in phosphorylated JNK levels, relative to infliximab non-responders and placebo responders. In addition, treatment with infliximab resulted in increase in MRI measures of brain volume; treatment-related changes in the dorsolateral prefrontal cortex volume were mediated by changes in biomarkers from the insulin alternative pathway. In conclusion, our findings support the idea that brain insulin signaling is a target for further mechanistic and therapeutic investigations.

Insulin receptor substrate in brain-enriched exosomes in subjects with major depression: on the path of creation of biosignatures of central insulin resistance.

Insulin signaling is critical for neuroplasticity, cerebral metabolism as well as for systemic energy metabolism. In rodent studies, impaired brain insulin signaling with resultant insulin resistance (IR) modulates synaptic plasticity and the corresponding behavioral functions. Despite discoveries of central actions of insulin, in vivo molecular mechanisms of brain IR until recently have proven difficult to study in the human brain. In the current study, we leveraged recent technological advances in molecular biology and herein report an increased number of exosomes enriched for L1CAM, a marker predominantly expressed in the brain, in subjects with major depressive disorder (MDD) as compared with age- and sex-matched healthy controls (HC). We also report increased concentration of the insulin receptor substrate-1 (IRS-1) in L1CAM+ exosomes in subjects with MDD as compared with age- and sex-matched HC. We found a relationship between expression of IRS-1 in L1CAM+ exosomes and systemic IR as assessed by homeostatic model assessment of IR in HC, but not in subjects with MDD. The increased IRS-1 levels in L1CAM+ exosomes were greater in subjects with MDD and were associated with suicidality and anhedonia. Finally, our data suggested sex differences in serine-312 phosphorylation of IRS-1 in L1CAM+ exosomes in subjects with MDD. These findings provide a starting point for creating mechanistic framework of brain IR in further development of personalized medicine strategies to effectively treat MDD.

Association between Adherence with an Atypical Antipsychotic and with Other Psychiatric Drugs in Patients with Bipolar Disorder.

BACKGROUND: Using U.S. pharmacy and medical claims, medication adherence patterns of patients with serious mental illness suggest that adherence to atypical antipsychotics may be related to adherence to other prescription drugs. This study investigated whether adherence to an atypical antipsychotic was related to adherence to other prescribed psychiatric drugs using self-reported data from patients with bipolar disorder. METHODS: Daily self-reported medication data were available from 123 patients with a diagnosis of bipolar disorder receiving treatment as usual who took at least 1 atypical antipsychotic over a 12-week period. Patients took a mean of 4.0±1.7 psychiatric drugs including the antipsychotic. The adherence rate for the atypical antipsychotic was compared to that for other psychiatric drugs to determine if the adherence rate for the atypical antipsychotic differed from that of the other psychiatric drug by at least ±10%. RESULTS: Of the 123 patients, 58 (47.2%) had an adherence rate for the atypical antipsychotic that differed from the adherence rate for at least 1 other psychiatric drug by at least±10%, and 65 (52.8%) patients had no difference in adherence rates. The patients with a difference took a larger total number of psychiatric drugs (p<0.001), had a larger daily pill burden (p=0.020) and a lower adherence rate with the atypical antipsychotic (p=0.007), and were more likely to take an antianxiety drug (p<0.001). CONCLUSION: Adherence with an atypical antipsychotic was not useful for estimating adherence to other psychiatric drugs in about half of the patients with bipolar disorder.