The Role of Lipid Biomarkers in Major Depression

Bootstrap inference and machine learning reveal core differential plasma metabolic connectome signatures in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) involves molecular alterations and pathway dysregulation. Metabolic interconnections are crucial for normal functioning, yet current analysis focuses on individual pathways or biomarkers, overlooking intricate metabolic biomarker interactions.

METHODS

Plasma metabolomic data from 182,053 UK Biobank participants [9425 MDD, and 172,628 healthy controls (HC)] were used to construct metabolic correlation networks through bootstrap inference analysis (bootstrap step size: 1000, 3000, 5000, 7000, 9000; n = 1000 times/size). Differential core metabolic network signatures between MDD and HC were identified by machine learning, followed by metabolic pathway analysis. Various deep learning and machine learning models were employed to differentiate MDD from HC groups using the identified network features and baseline characteristics.

RESULTS

The MDD metabolic network showed marked reorganization, with a sparser and more streamlined network structure compared to controls (p < 0.05 for both Vnet-edge and Vnet-node). Analysis of the core network in MDD revealed four key altered pathways, with linoleic acid metabolism being the most influential (p < 0.01, impact = 0.29). An extreme gradient boosting model combining network signatures and baseline features achieved 73 % accuracy, and an AUROC of 0.82 in differentiating MDD from HC groups.

CONCLUSIONS

This large-scale, metabolomic connectome analysis revealed consistent dysregulated metabolic network features in MDD, providing a robust and distinguishable framework compared to controls. The MDD network exhibits distinct connectivity patterns, particularly within linoleic acid metabolism. Integrating metabolomics as networks, rather than isolated markers, offers a promising approach for elucidating MDD pathophysiology and identifying diagnostic biomarkers.

Blood lipid profiles and mood disorders: A principal component analysis of UK Biobank data reveals distinct associations with depression and bipolar disorder

BACKGROUND

Growing evidence suggests that lipid metabolism may play a crucial role in mood disorder pathophysiology, and the correlation between blood lipids and mood disorder remains further clarified.

METHODS

This prospective, population-based cohort study utilized data from the UK Biobank. The study included 268,098 and 292,121 participants who had never been diagnosed with depression or bipolar disorder and who had complete data at both the baseline and follow-up points. A principal component analysis (PCA) was conducted on seven blood lipids, and the first three principal components (PCs) were derived. Cox regression analysis was employed to examine the correlation between the risk of mood disorders and the PCs. Multiplicative interaction and sensitivity analyses were also conducted. The relationship between blood lipids and neurological biomarkers was explored using Spearman's analysis.

RESULTS

PC1, primarily reflecting levels of Apolipoprotein B (ApoB), cholesterol, and low-density lipoprotein cholesterol (LDL-C), showed a protective effect against depression, with HRs of 0.98 (95 % CI: 0.96,1.00) in the fully adjusted Cox regression model. In contrast, PC2, characterized by opposite loadings for triglycerides and high-density lipoprotein cholesterol (HDLC), was positively associated with the risk of depression and bipolar disorder.(HR = 1.03,95 % CI: 1.01,1.06; HR = 1.11, 95 % CI: 1.01,1.23). Increased PC2 level was related to a significant increase in bipolar disorder risk among participants with high genetic risk (genetic risk score > 90 %, HR = 1.22, 95 % CI: 1.02,1.46). Complicated correlations between blood lipids and serum neuroproteins were detected.

CONCLUSION

These findings suggest complex associations between blood lipid profiles and the risk of depression and bipolar disorder.

Liquid Biopsy-Based Detection and Response Prediction for Depression

Proactively predicting antidepressant treatment response before medication failures is crucial, as it reduces unsuccessful attempts and facilitates the development of personalized therapeutic strategies, ultimately enhancing treatment efficacy. The current decision-making process, which heavily depends on subjective indicators, underscores the need for an objective, indicator-based approach. This study developed a method for detecting depression and predicting treatment response through deep learning-based spectroscopic analysis of extracellular vesicles (EVs) from plasma. EVs were isolated from the plasma of both nondepressed and depressed groups, followed by Raman signal acquisition, which was used for AI algorithm development. The algorithm successfully distinguished depression patients from healthy individuals and those with panic disorder, achieving an AUC accuracy of 0.95. This demonstrates the model's capability to selectively diagnose depression within a nondepressed group, including those with other mental health disorders. Furthermore, the algorithm identified depression-diagnosed patients likely to respond to antidepressants, classifying responders and nonresponders with an AUC accuracy of 0.91. To establish a diagnostic foundation, the algorithm applied explainable AI (XAI), enabling personalized medicine for companion diagnostics and highlighting its potential for the development of liquid biopsy-based mental disorder diagnosis.

Discriminating Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and comorbid conditions using metabolomics in UK Biobank

BACKGROUND

Diagnosing complex illnesses like Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is complicated due to the diverse symptomology and presence of comorbid conditions. ME/CFS patients often present with multiple health issues, therefore, incorporating comorbidities into research can provide a more accurate understanding of the condition's symptomatology and severity, to better reflect real-life patient experiences.

METHODS

We performed association studies and machine learning on 1194 ME/CFS individuals with blood plasma nuclear magnetic resonance (NMR) metabolomics profiles, and seven exclusive comorbid cohorts: hypertension (n = 13,559), depression (n = 2522), asthma (n = 6406), irritable bowel syndrome (n = 859), hay fever (n = 3025), hypothyroidism (n = 1226), migraine (n = 1551) and a non-diseased control group (n = 53,009).

RESULTS

We present a lipoprotein perspective on ME/CFS pathophysiology, highlighting gender-specific differences and identifying overlapping associations with comorbid conditions, specifically surface lipids, and ketone bodies from 168 significant individual biomarker associations. Additionally, we searched for, trained, and optimised a machine learning algorithm, resulting in a predictive model using 19 baseline characteristics and nine NMR biomarkers which could identify ME/CFS with an AUC of 0.83 and recall of 0.70. A multi-variable score was subsequently derived from the same 28 features, which exhibited ~2.5 times greater association than the top individual biomarker.

CONCLUSIONS

This study provides an end-to-end analytical workflow that explores the potential clinical utility that association scores may have for ME/CFS and other difficult to diagnose conditions.

The association between Metabolic Score for Visceral Fat and depression in overweight or obese individuals: evidence from NHANES

Background

Depression is a common mental illness with a high prevalence in overweight or obese individuals. Recent studies suggest that the Metabolic Score for Visceral Fat (METS-VF) is a novel metric for assessing visceral fat levels, potentially linking metabolic disturbances to depression. This study explores the association between METS-VF and depression severity in overweight or obese U.S. adults.

Methods

Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2007-2018 dataset, including 9,415 overweight or obese participants. Depression severity was measured using the Patient Health Questionnaire-9 (PHQ-9). To assess the association between METS-VF and depression, the study methodology included multivariate logistic regression, subgroup analyses, generalized additive model (GAM), and smoothed curve fitting. This study also calculated BMI for the Non-Hispanic Asian population from 2011-2018 and incorporated this data as part of a sensitivity analysis.

Results

Elevated levels of METS-VF in overweight or obese participants were significantly associated with increased PHQ-9 scores and an increased likelihood of depression. Notably, this association remained significant after adjustment for multiple covariates. Smoothed curve-fitting plots showed no nonlinear association between METS-VF and PHQ-9 scores. Subgroup analyses confirmed the robustness of these results across populations, particularly among people under the age of fifty. The sensitivity analyses confirmed the robustness of the results in this study.

Conclusion

METS-VF levels were positively associated with depression severity and the likelihood of depression in overweight or obese individuals, with the association being particularly pronounced in people under 50 years of age.

Metabolic features of adolescent major depressive disorder: A comparative study between treatment-resistant depression and first-episode drug-naive depression

Major depressive disorder (MDD) is a psychiatric illness that can jeopardize the normal growth and development of adolescents. Approximately 40% of adolescent patients with MDD exhibit resistance to conventional antidepressants, leading to the development of Treatment-Resistant Depression (TRD). TRD is associated with severe impairments in social functioning and learning ability and an elevated risk of suicide, thereby imposing an additional societal burden. In this study, we conducted plasma metabolomic analysis on 53 adolescents diagnosed with first-episode drug-naïve MDD (FEDN-MDD), 53 adolescents with TRD, and 56 healthy controls (HCs) using hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) and reversed-phase liquid chromatography-mass spectrometry (RPLC-MS). We established a diagnostic model by identifying differentially expressed metabolites and applying cluster analysis, metabolic pathway analysis, and multivariate linear support vector machine (SVM) algorithms. Our findings suggest that adolescent TRD shares similarities with FEDN-MDD in five amino acid metabolic pathways and exhibits distinct metabolic characteristics, particularly tyrosine and glycerophospholipid metabolism. Furthermore, through multivariate receiver operating characteristic (ROC) analysis, we optimized the area under the curve (AUC) and achieved the highest predictive accuracy, obtaining an AUC of 0.903 when comparing FEDN-MDD patients with HCs and an AUC of 0.968 when comparing TRD patients with HCs. This study provides new evidence for the identification of adolescent TRD and sheds light on different pathophysiologies by delineating the distinct plasma metabolic profiles of adolescent TRD and FEDN-MDD.

Clinical Factors and Biomarkers Associated with Depressive Disorders in Older Patients Affected by Chronic Kidney Disease (CKD): Does the Advanced Glycation End Products (AGEs)/RAGE (Receptor for AGEs) System Play Any Role?

Depressive disorders are highly prevalent among subjects suffering from chronic kidney disease (CKD). The aim of the present study is to evaluate clinical and biochemical factors associated with depressive disorders in a sample of older CKD patients, with a focus on advanced glycation end products (AGEs) and their soluble receptors (sRAGEs). A total of 115 older subjects affected by CKD (stages 3 to 5, not in dialysis) were selected for this study. These patients were divided into two groups according to the presence of depressive disorders defined by a score ≥ 10 on the 30-item Geriatric Depression Scale (GDS). The two groups were compared by independent sample t tests for continuous variables and χ2 tests for qualitative ones. Significant variables at univariate analyses were then inserted as predictors of a binary logistic regression model, with the presence or absence of depressive disorders as a dependent variable. The binary logistic regression model showed that patients with concomitant depressive disorders were more frequently of female gender (p < 0.01) and had lower MCP1 (p < 0.01) and AGE circulating levels (p < 0.01) than their counterparts. Depressive disorders in older CKD patients are more prevalent in women and seem to be inversely associated with systemic inflammation and circulating AGEs.

Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and sleep disorders in US adults: NHANES 2005 to 2016

NHHR (non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio) is a novel lipid parameter. However, the association between NHHR and sleep disorders remains unknown.; A cross-sectional analysis was conducted using data from the National Health and Nutrition Examination Survey (NHANES) 2005 to 2016. The association between NHHR and sleep disorders was explored using weighted multivariate logistic regression and generalized summation models. Subgroup analyses were employed to verify the robustness of this association. The prevalence of sleep disorders was 25.83% in a total of 22,221 participants. Compared to the lowest quartile of NHHR, participants in the top quartile had a 14% higher odds of sleep disorders prevalence in fully adjusted model (OR: 1.14, 95% CI: 1.06-1.23). After subgroup analyses and interaction tests, sex, race, marital status, education level, body mass index (BMI), person income ratio (PIR), alcohol consumption, smoking status, hypertension, and diabetes mellitus were not significantly associated with this positive association (P for interaction > 0.05). The NHHR is positively associated with sleep disorders in US adults. The management and monitoring of NHHR may have a potential role in improving sleep disorders.

Examining the cross-sectional relationship of platelet/high-density lipoprotein cholesterol ratio with depressive symptoms in adults in the United States

AIMS

Herein, we examined the correlation between platelet/high-density lipoprotein cholesterol ratio (PHR) and symptoms of depression among United States adults.

METHODS

Data acquired from the 2007-2018 National Health and Nutrition Examination Survey, involving individuals ≥ 20 years of age, with available PHR and depression diagnosis information. We employed weighted uni- and multivariable logistic regression analyses to assess the distinct correlation between PHR and depressive symptoms. Additionally, we conducted subgroup, interaction, and restricted cubic spline analyses.

RESULTS

In all, 28,098 subjects were recruited for analysis, with 8.04% depression status and 19.31 ± 0.11 mean PHR value. Depressive symptoms increased with higher quartiles of PHR. Following fully confounder adjustments in model 2, participants with the largest PHR quartiles exhibited a 53% (OR: 1.53, 95%CI: 1.00-2.33, P = 0.05) raised depressive symptoms, relative to participants with least PHR quartiles. Based on the two-piece-wise regression, the breakpoint was PHR = 23.76, and a positive association was more evident when PHR < 23.76 (OR = 1.06, 95%CI: 1.02-1.10, P = 0.01). When PHR ≥ 23.76, the correlation disappeared (P = 0.85). Using subgroup and interaction analyses, we revealed a positive relationship between PHR and depressive symptoms almost consistent among various population settings.

CONCLUSIONS

A convenient biomarker, the PHR was independently associated with an increased risk of depressive symptoms and may be a promising new bioindicator for the prediction of depression diagnosis.

Potential of niacin skin flush response in adolescent depression identification and severity assessment: a case-control study

BACKGROUND

The diagnosis of adolescent Depressive Disorder (DD) lacks specific biomarkers, posing significant challenges. This study investigates the potential of Niacin Skin Flush Response (NSFR) as a biomarker for identifying and assessing the severity of adolescent Depressive Disorder, as well as distinguishing it from Behavioral and Emotional Disorders typically emerging in childhood and adolescence(BED).

METHODS

In a case-control study involving 196 adolescents, including 128 Depressive Disorder, 32 Behavioral and Emotional Disorders, and 36 healthy controls (HCs), NSFR was assessed. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9) and anxious symptoms with the Generalized Anxiety Disorder 7-item scale (GAD-7). Pearson correlation analysis determined the relationships between NSFR and the severity of depression in DD patients. Receiver Operating Characteristic (ROC) was used to identify DD from BED integrating NSFR data with clinical symptom measures.

RESULTS

The adolescent Depressive Disorder group exhibited a higher rate of severe blunted NSFR (21.4%) compared to BED (12.5%) and HC ( 8.3%). Adolescent Depressive Disorder with psychotic symptoms showed a significant increase in blunted NSFR (p = 0.016). NSFR had negative correlations with depressive (r = -0.240, p = 0.006) and anxious (r = -0.2, p = 0.023) symptoms in adolescent Depressive Disorder. Integrating NSFR with three clinical scales improved the differentiation between adolescent Depressive Disorder and BED (AUC increased from 0.694 to 0.712).

CONCLUSION

The NSFR demonstrates potential as an objective biomarker for adolescent Depressive Disorder, aiding in screening, assessing severity, and enhancing insights into its pathophysiology and diagnostic precision.

High-density lipoprotein (HDL) as an indicator for alcohol use in a psychiatrically ill population

AIMS

To examine the cross sectional and longitudinal associations between the Alcohol Use Disorders Identification Test-Concise (AUDIT-C) and differences in high-density lipoprotein (HDL) in a psychiatrically ill population.

METHODS

Retrospective observational study using electronic health record data from a large healthcare system, of patients hospitalized for a mental health/substance use disorder (MH/SUD) from 1 July 2016 to 31 May 2023, who had a proximal AUDIT-C and HDL (N = 15 915) and the subset who had a repeat AUDIT-C and HDL 1 year later (N = 2915). Linear regression models examined the association between cross-sectional and longitudinal AUDIT-C scores and HDL, adjusting for demographic and clinical characteristics that affect HDL.

RESULTS

Compared with AUDIT-C score = 0, HDL was higher among patients with greater AUDIT-C severity (e.g. moderate AUDIT-C score = 8.70[7.65, 9.75] mg/dl; severe AUDIT-C score = 13.02 [12.13, 13.90] mg/dL[95% confidence interval (CI)] mg/dl). The associations between cross-sectional HDL and AUDIT-C scores were similar with and without adjusting for patient demographic and clinical characteristics. HDL levels increased for patients with mild alcohol use at baseline and moderate or severe alcohol use at follow-up (15.06[2.77, 27.69] and 19.58[2.77, 36.39] mg/dL[95%CI] increase for moderate and severe, respectively).

CONCLUSIONS

HDL levels correlate with AUDIT-C scores among patients with MH/SUD. Longitudinally, there were some (but not consistent) increases in HDL associated with increases in AUDIT-C. The increases were within range of typical year-to-year variation in HDL across the population independent of alcohol use, limiting the ability to use HDL as a longitudinal clinical indicator for alcohol use in routine care.

Depression and cognition are associated with lipid dysregulation in both a multigenerational study of depression and the National Health and Nutrition Examination Survey

Chronic dysregulation of peripheral lipids has been found to be associated with depression and cognition, but their interaction has not been investigated. Growing evidence has highlighted the association between peripheral lipoprotein levels with depression and cognition with inconsistent results. We assessed the association between peripheral lipids, depression, and cognition while evaluating their potential interactions using robust clinically relevant predictors such as lipoprotein levels and chronic medical disorders that dysregulate lipoproteins. We report an association between peripheral lipids, depression, and cognition, suggesting a common underlying biological mechanism driven by lipid dysregulation in two independent studies. Analysis of a longitudinal study of a cohort at high or low familial risk for major depressive disorder (MDD) (n = 526) found metabolic diseases, including diabetes, hypertension, and other cardiovascular diseases, were associated with MDD and cognitive outcomes. Investigating a cross-sectional population survey of adults in the National Health and Nutrition Examination Survey 2011-2014 (NHANES) (n = 2377), depression was found to be associated with high density lipoprotein (HDL) and cognitive assessments. In the familial risk study, medical conditions were found to be associated with chronic lipid dysregulation and were significantly associated with MDD using the structural equation model. A positive association between chronic lipid dysregulation and cognitive scores was found in an exploratory analysis of the familial risk study. In a complementary study, analysis of NHANES revealed a positive association of HDL levels with cognition. Further analysis of the NHANES cohort indicated that depression status mediated the interaction between HDL levels and cognitive tests. Importantly, the protective effect of HDL on cognition was absent in those with depressive symptoms, which may ultimately result in worse outcomes leading to cognitive decline. These findings highlight the potential for the early predictive value of medical conditions with chronic lipid dyshomeostasis for the risk of depression and cognitive decline.

Stress-induced stenotic vascular remodeling via reduction of plasma omega-3 fatty acid metabolite 4-oxoDHA by noradrenaline

Stress has garnered significant attention as a prominent risk factor for inflammation-related diseases, particularly cardiovascular diseases (CVDs). However, the precise mechanisms underlying stress-driven CVDs remain elusive, thereby impeding the development of preventive and therapeutic strategies. To explore the correlation between plasma lipid metabolites and human depressive states, liquid chromatography-mass spectrometry (LC/MS) based analysis of plasma and the self-rating depression (SDS) scale questionnaire were employed. We also used a mouse model with restraint stress to study its effects on plasma lipid metabolites and stenotic vascular remodeling following carotid ligation. In vitro functional and mechanistic studies were performed using macrophages, endothelial cells, and neutrophil cells. We revealed a significant association between depressive state and reduced plasma levels of 4-oxoDHA, a specific omega-3 fatty acid metabolite biosynthesized by 5-lipoxygenase (LO), mainly in neutrophils. In mice, restraint stress decreased plasma 4-oxoDHA levels and exacerbated stenotic vascular remodeling, ameliorated by 4-oxoDHA supplementation. 4-oxoDHA enhanced Nrf2-HO-1 pathways, exerting anti-inflammatory effects on endothelial cells and macrophages. One of the stress hormones, noradrenaline, reduced 4-oxoDHA and the degraded 5-LO in neutrophils through the proteasome system, facilitated by dopamine D2-like receptor activation. Our study proposed circulating 4-oxoDHA levels as a stress biomarker and supplementation of 4-oxoDHA as a novel therapeutic approach for controlling stress-related vascular inflammation.

Biomarker-Guided Tailored Therapy in Major Depression

This chapter provides a comprehensive examination of a broad range of biomarkers used for the diagnosis and prediction of treatment outcomes in major depressive disorder (MDD). Genetic, epigenetic, serum, cerebrospinal fluid (CSF), and neuroimaging biomarkers are analyzed in depth, as well as the integration of new technologies such as digital phenotyping and machine learning. The intricate interplay between biological and psychological elements is emphasized as essential for tailoring MDD management strategies. In addition, the evolving link between psychotherapy and biomarkers is explored to uncover potential associations that shed light on treatment response. This analysis underscores the importance of individualized approaches in the treatment of MDD that integrate advanced biological insights into clinical practice to improve patient outcomes.

Prevalence and Factors Associated with Subclinical Hypothyroidism in Major Depressive Disorder Patients with Dyslipidemia

Background

Major depressive disorder (MDD) is a common psychiatric disorder with a high prevalence of comorbidity with subclinical hypothyroidism. The aim of this study was to investigate the prevalence and factors influencing the comorbidity of subclinical hypothyroidism in patients with dyslipidemic MDD who were hospitalized for the first time in a Chinese population.

Methods

The study incorporated 708 first-time hospitalized MDD patients, all with dyslipidemia. Data collection encompassed socio-demographic information, blood pressure, fasting blood glucose (FBG), lipid, and thyroid hormone levels. Participants were evaluated using the Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), and Positive Symptom Subscale (PSS).

Results

The prevalence of subclinical hypothyroidism in dyslipidemic MDD patients with the first hospitalization was 39.97%. The course of the disease, age at onset, HAMA score, and low-density lipoprotein cholesterol (LDL-C) were risk factors for subclinical hypothyroidism in dyslipidemic MDD patients. The course of disease, age at onset, HAMA score, HAMD score, FBG, and systolic blood pressure (SBP) levels were observed to influence serum Thyroid Stimulating Hormone (TSH) levels.

Conclusion

MDD patients with dyslipidemia have a high prevalence of subclinical hypothyroidism, and the outcome is associated with anxiety, fasting glucose, and lipids. This study provides a potential biomarker for the identification of co-morbid subclinical hypothyroidism in MDD patients with dyslipidaemia.

Apolipoprotein D as a Potential Biomarker in Neuropsychiatric Disorders

Neuropsychiatric disorders (NDs) are a diverse group of pathologies, including schizophrenia or bipolar disorders, that directly affect the mental and physical health of those who suffer from them, with an incidence that is increasing worldwide. Most NDs result from a complex interaction of multiple genes and environmental factors such as stress or traumatic events, including the recent Coronavirus Disease (COVID-19) pandemic. In addition to diverse clinical presentations, these diseases are heterogeneous in their pathogenesis, brain regions affected, and clinical symptoms, making diagnosis difficult. Therefore, finding new biomarkers is essential for the detection, prognosis, response prediction, and development of new treatments for NDs. Among the most promising candidates is the apolipoprotein D (Apo D), a component of lipoproteins implicated in lipid metabolism. Evidence suggests an increase in Apo D expression in association with aging and in the presence of neuropathological processes. As a part of the cellular neuroprotective defense machinery against oxidative stress and inflammation, changes in Apo D levels have been demonstrated in neuropsychiatric conditions like schizophrenia (SZ) or bipolar disorders (BPD), not only in some brain areas but in corporal fluids, i.e., blood or serum of patients. What is not clear is whether variation in Apo D quantity could be used as an indicator to detect NDs and their progression. This review aims to provide an updated view of the clinical potential of Apo D as a possible biomarker for NDs.

Biomarkers of Postpartum Depression: A Narrative Review

Postpartum depression (PPD) is a disorder that impairs the formation of the relationship between mother and child, and reduces the quality of life for affected women to a functionally significant degree. Studying markers associated with PPD can help in early detection, prevention, or monitoring treatment. The purpose of this paper is to review biomarkers linked to PPD and to present selected theories on the pathogenesis of the disease based on data from biomarker studies. The complex etiology of the disorder reduces the specificity and sensitivity of markers, but they remain a valuable source of information to help clinicians. The biggest challenge of the future will be to translate high-tech methods for detecting markers associated with postpartum depression into more readily available and less costly ones. Population-based studies are needed to test the utility of potential PPD markers.

Apolipoproteins and Suicide: A Potential Psychiatric Biomarker

Every year around 800,000 people commit suicide, this represents one death every 40 s. In the search for possible biological biomarkers associated with suicide and/or psychiatric disorders, serum cholesterol levels have been extensively explored. Several studies indicate that cholesterol and associated proteins, especially apolipoproteins (Apos), may play an important role in the diagnosis, prognosis, and susceptibility of suicidal behavior. Here, we describe the current knowledge and findings in the relationship between apolipoproteins and suicide.HIGHLIGHTSThis is the first systematic review of Apos in relation to suicidal behavior.Dysregulations of Apos expression has been observed in patients with suicidal behavior.Apos seem to be associated with cognitive dysfunction in suicide attempters.ApoE is a potential biomarker regarding suicidal behavior.

Lipid Biomarker Research in Bipolar Disorder: A Scoping Review of Trends, Challenges, and Future Directions

Bipolar disorder (BD) is a disabling disorder with heterogeneous symptom profiles and trajectories. Like many other neuropsychiatric disorders, clinical decision making related to diagnoses and choice of treatment is based on clinical assessments alone, and risk prediction for treatment success or resistance at an individual level remains sparse. An enormous effort to add biological markers to this risk prediction is ongoing. The role of lipids in normal brain functioning is well established, and several hypotheses about the role of lipids in the pathogenesis of neuropsychiatric disorders, including BD, have been made. The frequent comorbidity between neuropsychiatric disorders and cardiovascular disease, the genetic overlap of risk genes for severe mental disorders and genes involved in lipid regulation, and the lipid-altering effects of antipsychotics and mood stabilizers indicate that lipids could hold promise as biomarkers for neuropsychiatric disorders, including BD. To date, reviews of lipid biomarkers in schizophrenia and major depression have noted caveats for future investigations, while reviews of lipid biomarker research in BD is missing. In the current scoping review, we present a comprehensive overview of trends in previous research on lipid biomarkers in BD. The current literature varies greatly in the phenotypes investigated and study designs, leading to divergent findings. Small sample size; potential confounders related to physical activity, nutritional status, and medication use; and cross-sectional designs were frequently reported limitations. Future research may benefit from pivoting toward utilization of newer laboratory techniques such as lipidomics, but consistent use of study methods across cohorts is also needed.

Depression symptoms and suicide risk of internal medicine residents before and after first year of the COVID-19 pandemic

Introduction

Depression is a mental health disorder characterized by the presence of sadness or loss of the ability to feel pleasure, with a high incidence in patients with COVID 19. The investigations have focused on patient care and little on the care of health personnel, these being the ones with the highest mortality rate, so the objective of the study was to investigate the prevalence of depression symptoms and suicide risk and understand the association of depressive disorder and suicide risk with levels of serum cholesterol and low levels of serum cortisol among internal medicine fellows in a specialist medical hospital in Leon, Guanajuato, Mexico, before and after COVID-19.

Methods

In this longitudinal study, internal medicine residents were initially monitored for 2months before starting to care for patients with COVID-19. Participants were asked to fill out depression symptoms and suicide risk surveys. We measured the serum cholesterol and cortisol of each participant, and again after 11months of treating COVID-19 patients.

Results

Depression symptoms and suicide risk were assessed; significant differences were found between the two time periods for depression (p < 0.01), and no difference was found for suicide risk (p = 0.182). We found a significant correlation between serum cholesterol levels and suicide risk (r = 0.366, p < 0.01); we also found differences in serum cortisol levels (p < 0.01) and cholesterol (p < 0.0001) before and after the pandemic.

Conclusion

Caring for patients with COVID-19 in the hospital contributed to an increase in levels of depression symptoms and suicidal ideation, as well as differences in levels of cortisol and cholesterol in resident physicians of internal medicine; among the possible reasons for this change could be the conditions of personal protection while treating patients, the uncertainty in the first months of not knowing how the virus was transmitted and not having or knowing when vaccinations would be available, as well as the lack of a strategy of adequate mental health support from the institutions dedicated to their academic training.

The pharmacological bases for repurposing statins in depression: a review of mechanistic studies

Statins are commonly prescribed medications widely investigated for their potential actions on the brain and mental health. Pre-clinical and clinical evidence suggests that statins may play a role in the treatment of depressive disorders, but only the latter has been systematically assessed. Thus, the physiopathological mechanisms underlying statins' putative antidepressant or depressogenic effects have not been established. This review aims to gather available evidence from mechanistic studies to strengthen the pharmacological basis for repurposing statins in depression. We used a broad, well-validated search strategy over three major databases (Pubmed/MEDLINE, Embase, PsychINFO) to retrieve any mechanistic study investigating statins' effects on depression. The systematic search yielded 8068 records, which were narrowed down to 77 relevant papers. The selected studies (some dealing with more than one bodily system) described several neuropsychopharmacological (44 studies), endocrine-metabolic (17 studies), cardiovascular (6 studies) and immunological (15 studies) mechanisms potentially contributing to the effects of statins on mood. Numerous articles highlighted the beneficial effect of statins on depression, particularly through positive actions on serotonergic neurotransmission, neurogenesis and neuroplasticity, hypothalamic-pituitary axis regulation and modulation of inflammation. The role of other mechanisms, especially the association between statins, lipid metabolism and worsening of depressive symptoms, appears more controversial. Overall, most mechanistic evidence supports an antidepressant activity for statins, likely mediated by a variety of intertwined processes involving several bodily systems. Further research in this area can benefit from measuring relevant biomarkers to inform the selection of patients most likely to respond to statins' antidepressant effects while also improving our understanding of the physiopathological basis of depression.

Interplay of Metabolome and Gut Microbiome in Individuals With Major Depressive Disorder vs Control Individuals

Importance

Metabolomics reflect the net effect of genetic and environmental influences and thus provide a comprehensive approach to evaluating the pathogenesis of complex diseases, such as depression.

Objective

To identify the metabolic signatures of major depressive disorder (MDD), elucidate the direction of associations using mendelian randomization, and evaluate the interplay of the human gut microbiome and metabolome in the development of MDD.

Design, Setting and Participants

This cohort study used data from participants in the UK Biobank cohort (n = 500 000; aged 37 to 73 years; recruited from 2006 to 2010) whose blood was profiled for metabolomics. Replication was sought in the PREDICT and BBMRI-NL studies. Publicly available summary statistics from a 2019 genome-wide association study of depression were used for the mendelian randomization (individuals with MDD = 59 851; control individuals = 113 154). Summary statistics for the metabolites were obtained from OpenGWAS in MRbase (n = 118 000). To evaluate the interplay of the metabolome and the gut microbiome in the pathogenesis of depression, metabolic signatures of the gut microbiome were obtained from a 2019 study performed in Dutch cohorts. Data were analyzed from March to December 2021.

Main Outcomes and Measures

Outcomes were lifetime and recurrent MDD, with 249 metabolites profiled with nuclear magnetic resonance spectroscopy with the Nightingale platform.

Results

The study included 6811 individuals with lifetime MDD compared with 51 446 control individuals and 4370 individuals with recurrent MDD compared with 62 508 control individuals. Individuals with lifetime MDD were younger (median [IQR] age, 56 [49-62] years vs 58 [51-64] years) and more often female (4447 [65%] vs 2364 [35%]) than control individuals. Metabolic signatures of MDD consisted of 124 metabolites spanning the energy and lipid metabolism pathways. Novel findings included 49 metabolites, including those involved in the tricarboxylic acid cycle (ie, citrate and pyruvate). Citrate was significantly decreased (β [SE], -0.07 [0.02]; FDR = 4 × 10-04) and pyruvate was significantly increased (β [SE], 0.04 [0.02]; FDR = 0.02) in individuals with MDD. Changes observed in these metabolites, particularly lipoproteins, were consistent with the differential composition of gut microbiota belonging to the order Clostridiales and the phyla Proteobacteria/Pseudomonadota and Bacteroidetes/Bacteroidota. Mendelian randomization suggested that fatty acids and intermediate and very large density lipoproteins changed in association with the disease process but high-density lipoproteins and the metabolites in the tricarboxylic acid cycle did not.

Conclusions and Relevance

The study findings showed that energy metabolism was disturbed in individuals with MDD and that the interplay of the gut microbiome and blood metabolome may play a role in lipid metabolism in individuals with MDD.

Biomarkers in Child and Adolescent Depression

Despite the significant prevalence of Major Depressive Disorder in the pediatric population, the pathophysiology of this condition remains unclear, and the treatment outcomes poor. Investigating tools that might aid in diagnosing and treating early-onset depression seems essential in improving the prognosis of the future disease course. Recent studies have focused on searching for biomarkers that constitute biochemical indicators of MDD susceptibility, diagnosis, or treatment outcome. In comparison to increasing evidence of possible biomarkers in adult depression, the studies investigating this subject in the youth population are lacking. This narrative review aims to summarize research on molecular and biochemical biomarkers in child and adolescent depression in order to advocate future directions in the research on this subject. More studies on depression involving the youth population seem vital to comprehend the natural course of the disease and identify features that may underlie commonly observed differences in treatment outcomes between adults and children.

Heterogeneity in major depressive disorder: The need for biomarker-based personalized treatments

Major Depressive Disorder (MDD) or depression is a pathological mental condition affecting millions of people worldwide. Identification of objective biological markers of depression can provide for a better diagnostic and intervention criteria; ultimately aiding to reduce its socioeconomic health burden. This review provides a comprehensive insight into the major biomarker candidates that have been implicated in depression neurobiology. The key biomarker categories are covered across all the "omics" levels. At the epigenomic level, DNA-methylation, non-coding RNA and histone-modifications have been discussed in relation to depression. The proteomics system shows great promise with inflammatory markers as well as growth factors and neurobiological alterations within the endocannabinoid system. Characteristic lipids implicated in depression together with the endocrine system are reviewed under the metabolomics section. The chapter also examines the novel biomarkers for depression that have been proposed by studies in the microbiome. Depression affects individuals differentially and explicit biomarkers identified by robust research criteria may pave the way for better diagnosis, intervention, treatment, and prediction of treatment response.

Crosstalk between neurological, cardiovascular, and lifestyle disorders: insulin and lipoproteins in the lead role

Insulin resistance and impaired lipoprotein metabolism contribute to a plethora of metabolic and cardiovascular disorders. These alterations have been extensively linked with poor lifestyle choices, such as consumption of a high-fat diet, smoking, stress, and a redundant lifestyle. Moreover, these are also known to increase the co-morbidity of diseases like Type 2 diabetes mellitus and atherosclerosis. Under normal physiological conditions, insulin and lipoproteins exert a neuroprotective role in the central nervous system. However, the tripping of balance between the periphery and center may alter the normal functioning of the brain and lead to neurological disorders such as Alzheimer's disease, Parkinson's disease, stroke, depression, and multiple sclerosis. These neurological disorders are further characterized by certain behavioral and molecular changes that show consistent overlap with alteration in insulin and lipoprotein signaling pathways. Therefore, targeting these two mechanisms not only reveals a way to manage the co-morbidities associated with the circle of the metabolic, central nervous system, and cardiovascular disorders but also exclusively work as a disease-modifying therapy for neurological disorders. In this review, we summarize the role of insulin resistance and lipoproteins in the progression of various neurological conditions and discuss the therapeutic options currently in the clinical pipeline targeting these two mechanisms; in addition, challenges faced in designing these therapeutic approaches have also been touched upon briefly.

Combinatorial panel with endophenotypes from multilevel information of diffusion tensor imaging and lipid profile as predictors for depression

OBJECTIVE

Clinical heterogeneity in major depressive disorder likely reflects the range of etiology and contributing factors in the disorder, such as genetic risk. Identification of more refined subgroups based on biomarkers such as white matter integrity and lipid-related metabolites could facilitate precision medicine in major depressive disorder.

METHODS

A total of 148 participants (15 genetic high-risk participants, 57 patients with first-episode major depressive disorder and 76 healthy controls) underwent diffusion tensor imaging and plasma lipid profiling. Alterations in white matter integrity and lipid metabolites were identified in genetic high-risk participants and patients with first-episode major depressive disorder. Then, shared alterations between genetic high-risk and first-episode major depressive disorder were used to develop an imaging x metabolite diagnostic panel for genetically based major depressive disorder via factor analysis and logistic regression. A fivefold cross-validation test was performed to evaluate the diagnostic panel.

RESULTS

Alterations of white matter integrity in corona radiata, superior longitudinal fasciculus and the body of corpus callosum and dysregulated unsaturated fatty acid metabolism were identified in both genetic high-risk participants and patients with first-episode major depressive disorder. An imaging x metabolite diagnostic panel, consisting of measures for white matter integrity and unsaturated fatty acid metabolism, was identified that achieved an area under the receiver operating characteristic curve of 0.86 and had a significantly higher diagnostic performance than that using either measure alone. And cross-validation confirmed the adequate reliability and accuracy of the diagnostic panel.

CONCLUSION

Combining white matter integrity in corpus callosum, superior longitudinal fasciculus and corona radiata, and unsaturated fatty acid profile may improve the identification of genetically based endophenotypes in major depressive disorder to advance precision medicine strategies.

Changes in regulators of lipid metabolism in the brain: a study of animal models of depression and hypothyroidism

Metabolic disturbances in the brain are assumed to be early changes involved in the pathogenesis of depression, and these alterations may be intensified by a deficiency of thyroid hormones. In contrast to glucose metabolism, the link between altered brain lipids and the pathogenesis of depression is poorly understood, therefore in the present study, we determine transcription factors and enzymes regulating cholesterol and fatty acid biosynthesis in the brain structures in an animal model of depression, hypothyroidism and the coexistence of these diseases.

In used model of depression, a decrease in the active form of the transcription factor SREBP-2 in the hippocampus was demonstrated, thus suggesting a reduction in cholesterol biosynthesis. In turn, in the hypothyroidism model, the reduction of cholesterol biosynthesis in the frontal cortex was demonstrated by both the reduction of mature SREBP-2 and the concentration of enzymes involved in cholesterol biosynthesis. The lower expression of LDL receptors in the frontal cortex indicates the restriction of cholesterol uptake into the cells in the model of coexistence of depression and hypothyroidism. Moreover, the identified changes in the levels of SNAP-25, GLP-1R and GLP-2R pointed to disturbances in synaptic plasticity and neuroprotection mechanisms in the examined brain structures.

In conclusion, a reduction in cholesterol synthesis in the hippocampus in the model of depression may be the reason for the reduction of synaptic plasticity, whereas a lower level of LDL-R occurring in the frontal cortex in rats from the model of depression and hypothyroidism coexistence could be the reason of anxiogenic and depression-like behaviors.

Prognostic Significance of Blood-Based Baseline Biomarkers in Treatment-Resistant Depression: A Literature Review of Available Studies on Treatment Response

Major depressive disorder is a leading cause of disability worldwide and a major contributor to the overall global burden of disease. While there are several options for antidepressant treatment, only about 40–60% of patients respond to initial monotherapy, while 30–40% of patients may even show resistance to treatment. This article offers a narrative review of those studies evaluating the predictive properties of various blood-based baseline biomarkers regarding treatment responses to the pharmacological, stimulation, or behavioral treatment of patients with treatment-resistant depression (TRD). Our results show that overall, there is only a very limited number of studies assessing baseline peripheral biomarkers regarding treatment response in TRD. Although there is some evidence for the predictive significance of particular biomarkers (e.g., IL-6, CRP, BDNF), the majority of the results are either single-study reports or studies with conflicting results. This may contribute to the wide variety of treatment protocols and different TRD definition criteria, the small number of patients included, and the existence of different biological phenotypes of the disorder used within the various studies. Taken together, there does not yet appear to be any specific baseline peripheral biomarker with sufficient discriminative predictive validity that can be used in the routine clinical practice of TRD. The discovery of new biomarkers and the better clinical characterization of known biomarkers could support the better classification and staging of TRD, the development of personalized treatment algorithms with higher rates of remission and fewer side effects, and the development of new precision drugs for specific subgroups of patients.

Evaluation of bi-directional causal association between depression and cardiovascular diseases: a Mendelian randomization study

BACKGROUND

Depression and cardiovascular disease (CVD) are associated with each other but their relationship remains unclear. We aim to determine whether genetic predisposition to depression are causally linked to CVD [including coronary artery disease (CAD), myocardial infarction (MI), stroke and atrial fibrillation (AF)].

METHODS

Using summary statistics from the largest genome-wide association studies (GWAS) or GWAS meta-analysis of depression (primary analysis: n = 500 199), broad depression (help-seeking behavior for problems with nerves, anxiety, tension or depression; secondary analysis: n = 322 580), CAD (n = 184 305), MI (n = 171 875), stroke (n = 446 696) and AF (n = 1 030 836), genetic correlation was tested between two depression phenotypes and CVD [MI, stroke and AF (not CAD as its correlation was previously confirmed)]. Causality was inferred between correlated traits by Mendelian Randomization analyses.

RESULTS

Both depression phenotypes were genetically correlated with MI (depression: r_G = 0.169; p = 9.03 × 10^-9; broad depression: r_G = 0.123; p = 1 × 10^-4) and AF (depression: r_G = 0.112; p = 7.80 × 10^-6; broad depression: r_G = 0.126; p = 3.62 × 10^-6). Genetically doubling the odds of depression was causally associated with increased risk of CAD (OR = 1.099; 95% CI 1.031-1.170; p = 0.004) and MI (OR = 1.146; 95% CI 1.070-1.228; p = 1.05 × 10^-4). Adjustment for blood lipid levels/smoking status attenuated the causality between depression and CAD/MI. Null causal association was observed for CVD on depression. A similar pattern of results was observed in the secondary analysis for broad depression.

CONCLUSIONS

Genetic predisposition to depression may have positive causal roles on CAD/MI. Genetic susceptibility to self-awareness of mood problems may be a strong causal risk factor of CAD/MI. Blood lipid levels and smoking may potentially mediate the causal pathway. Prevention and early diagnosis of depression are important in the management of CAD/MI.

Metabolomic and inflammatory signatures of symptom dimensions in major depression

BACKGROUND

Major depressive disorder (MDD) is a highly heterogenous disease, both in terms of clinical profiles and pathobiological alterations. Recently, immunometabolic dysregulations were shown to be correlated with atypical, energy-related symptoms but less so with the Melancholic or Anxious distress symptom dimensions of depression in The Netherlands Study of Depression and Anxiety (NESDA) study. In this study, we aimed to replicate these immunometabolic associations and to characterize the metabolomic correlates of each of the three MDD dimensions.

METHODS

Using three clinical rating scales, Melancholic, and Anxious distress, and Immunometabolic (IMD) dimensions were characterized in 158 patients who participated in the Predictors of Remission to Individual and Combined Treatments (PReDICT) study and from whom plasma and serum samples were available. The NESDA-defined inflammatory index, a composite measure of interleukin-6 and C-reactive protein, was measured from pre-treatment plasma samples and a metabolomic profile was defined using serum samples analyzed on three metabolomics platforms targeting fatty acids and complex lipids, amino acids, acylcarnitines, and gut microbiome-derived metabolites among other metabolites of central metabolism.

RESULTS

The IMD clinical dimension and the inflammatory index were positively correlated (r = 0.19, p = 0.019) after controlling for age, sex, and body mass index, whereas the Melancholic and Anxious distress dimensions were not, replicating the previous NESDA findings. The three symptom dimensions had distinct metabolomic signatures using both univariate and set enrichment statistics. IMD severity correlated mainly with gut-derived metabolites and a few acylcarnitines and long chain saturated free fatty acids. Melancholia severity was significantly correlated with several phosphatidylcholines, primarily the ether-linked variety, lysophosphatidylcholines, as well as several amino acids. Anxious distress severity correlated with several medium and long chain free fatty acids, both saturated and polyunsaturated ones, sphingomyelins, as well as several amino acids and bile acids.

CONCLUSION

The IMD dimension of depression appears reliably associated with markers of inflammation. Metabolomics provides powerful tools to inform about depression heterogeneity and molecular mechanisms related to clinical dimensions in MDD, which include a link to gut microbiome and lipids implicated in membrane structure and function.

Phenome-wide screening of the putative causal determinants of depression using genetic data

Depression is one of the most common mental health disorders and one of the top causes of disability throughout the world. The present study sought to identify putative causal associations between depression and hundreds of complex human traits through a genome-wide screening of genetic data and a hypothesis-free approach. We leveraged genome-wide association studies (GWAS) summary statistics for depression and 1504 complex traits and investigated potential causal relationships using the latent causal variable method. We identified 559 traits genetically correlated with depression risk at FDR < 5%. Of these, 46 were putative causal genetic determinants of depression, including lifestyle factors, diseases of the nervous system, respiratory disorders, diseases of the musculoskeletal system, traits related to the health of the gastrointestinal system, obesity, vitamin D levels, and the use of prescription medications, among others. No phenotypes were identified as potential outcomes of depression. Our results suggest that genetic liability to multiple complex traits may contribute to a higher risk for depression. In particular, we show a putative causal genetic effect of pain, obesity, and inflammation on depression. These findings provide novel insights into the potential causal determinants of depression and should be interpreted as testable hypotheses for future studies to confirm, which may facilitate the design of new prevention strategies to reduce depression's burden.

Gender-specific association of biochemical variables with depression: a population-based case-control study from North India

Background

Depression is a highly prevalent mental disorder with complex aetiology. An emerging body of evidence shows that depression tends to co-occur with abnormal blood glucose levels and dyslipidaemia. This study aimed to understand the overall and gender-specific associations of abnormal glucose levels and dyslipidaemia with depression in a single Mendelian population from rural Haryana, India. To achieve the aim, a population-based case-control study, which constituted of 251 depressed (cases) and 251 non-depressed (controls) individuals, was set up. The study was conducted among the Jat community of Palwal District, Haryana (North India). Data collection was done using a pre-tested interview schedule through the household survey method. Depression status was ascertained using Beck Depression Inventory-II. Fasting blood glucose analysis and lipid profiling were done using commercial kits (Randox, USA) through spectrophotometry. Statistical analysis was done using MS-Excel 2010 and SPSS version 16.0.

Results

In the present study, overall fasting blood sugar level was not found to be associated with depression. However, high blood sugar posed a 3.6-folds elevated risk for depression among females with borderline significance (p = 0.058). Further, higher levels of TC and LDL were found to be inversely associated with depression. In the sex-wise analysis inverse association of TC and LDL with depression remained significant among males but not among females. Instead, high TG and high VLDL showed an increased risk for depression in females.

Conclusions

This study suggests gender-specific associations of some of the studied biochemical variables with depression. Longitudinal studies are warranted to explicate cause-effect relationships between the studied biochemical variables and depression.

Change in cholesterol level during pregnancy and risk of postpartum depressive symptoms: the Japan Environment and Children's Study (JECS)

OBJECTIVE

Women with postpartum depressive symptoms (PDS) are at higher risk of postpartum depression (PPD) and require further assessment. Emerging evidence indicates a relationship between the total cholesterol (TC) level of blood and PPD but the results are inconsistent. In this study, we investigated the possible association of change in serum TC levels during pregnancy with the risk of PDS in a Japanese population.

METHODS

We analyzed complete data on questionnaire responses and serum lipid profiles of pregnant women from 12 datasets obtained from the Japan Environment and Children's Study (n = 61,585 to n = 72,406; 103,063 pregnancies in total). TC was measured at 3 time points-during early pregnancy, during mid-late pregnancy, and after delivery-and we calculated changes in TC in 3 ways: by subtracting early pregnancy from mid-late pregnancy, subtracting mid-late pregnancy from delivery, and subtracting early pregnancy from delivery. These 6 factors were used as predictors to estimate the risk of PDS at 1 and 6 months after delivery.

RESULTS

In multivariable logistic regression analysis, point serum cholesterol level did not predict PDS at any time point except for during mid-late pregnancy in the second quintile, indicating an increased risk at 6 months. As for change in TC levels, subtracting mid-late pregnancy from delivery and early pregnancy from delivery showed significant risk reduction for PDS at 1 month. A significant risk reduction was also found for subtracting early pregnancy from mid-late pregnancy and early pregnancy from delivery at 6 months.

CONCLUSIONS

Increased cholesterol level during pregnancy is associated with reduced risk of PDS.

Adaptation of Lipid Profiling in Depression Disease and Treatment: A Critical Review

Major depressive disorder (MDD), also called depression, is a serious disease that impairs the quality of life of patients and has a high incidence, affecting approximately 3.8% of the world population. Its diagnosis is very subjective and is not supported by measurable biomarkers mainly due to the lack of biochemical markers. Recently, disturbance of lipid profiling has been recognized in MDD, in animal models of MDD or in depressed patients, which may contribute to unravel the etiology of the disease and find putative new biomarkers, for a diagnosis or for monitoring the disease and therapeutics outcomes. In this review, we provide an overview of current knowledge of lipidomics analysis, both in animal models of MDD (at the brain and plasma level) and in humans (in plasma and serum). Furthermore, studies of lipidomics analyses after antidepressant treatment in rodents (in brain, plasma, and serum), in primates (in the brain) and in humans (in plasma) were reviewed and give evidence that antidepressants seem to counteract the modification seen in lipids in MDD, giving some evidence that certain altered lipid profiles could be useful MDD biomarkers for future precision medicine.

Lipid Biomarkers in Depression: Does Antidepressant Therapy Have an Impact?

Studies have revealed mixed results on how antidepressant drugs affect lipid profiles of patients with major depression disorder (MDD). Even less is known about how patients respond to a switch of antidepressant medication with respect to their metabolic profile. For this, effects of a switch in antidepressants medication on lipid markers were studied in MDD patients. 15 participants (females = 86.67%; males = 13.33%; age: 49.45 ± 7.45 years) with MDD and a prescribed switch in their antidepressant medication were recruited at a psychosomatic rehabilitation clinic. Participants were characterized (with questionnaires and blood samples) at admission to the rehabilitation clinic (baseline, T0) and followed up with a blood sample two weeks (T1) later. HDL, LDL, total cholesterol, and triglycerides were determined (T0), and their change analyzed (Wilcoxon test) at follow up (T1). Decrements in HDL (p = 0.041), LDL (p < 0.001), and total cholesterol (p < 0.001) were observed two weeks after a switch in antidepressant medication. Triglycerides showed no difference (p = 0.699). Overall, LDL, HDL, and total cholesterol are affected by a change in antidepressant drugs in patients with MDD. These observations are of clinical relevance for medical practitioners in the planning and management of treatment strategies for MDD patients.

Food habits and associated risk factors of depressed patients with cardiovascular disease

The present study was carried out to investigate food habits and associated risk factors of depressed patients with cardiovascular disease in Riyadh city, Saudi Arabia. Depressed and healthy females (n = 30 each) and males (n = 30 each) aged 18–65 years were involved in this study. Sociodemographic, anthropometric proxies, and nutritional status were evaluated. Cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-c), and low-density lipoprotein cholesterol (LDL-c) levels of respondents’ blood were determined. The respondents were varied according to demographic factors and anthropometric proxies. The majority of depressed males had higher values than healthy ones. The student t-test analysis showed that the average daily intake of fat especially saturated fat, by depressed respondents was higher than that of the healthy ones as well as the dietary requirement intake (DRI). The analysis of respondents’ blood showed that the number of depressed females had higher abnormal HDL-c than males, who were observed to have an abnormal level of cholesterol and triglycerides. The correlation of daily nutrient intake and depression duration, depression severity, and age showed that the nutrients responsible for the extension and severity of depression were intake of food rich in dietary fat. Factors including demographics daily nutrient intake appeared to be associated with depression.

Molecular mechanisms linking stress and insulin resistance

To date, there is ample evidence to support the strong relationship between stress and insulin resistance. While diabetes mellitus acts as a potent stress inducer, stress may be an upstream event for insulin resistance as well. It is widely recognized that diabetes mellitus is more prevalent among people who have a stressful lifestyle; however, the underlying mechanisms are not well understood. In the current study, we surveyed the scientific literature for possible interactions between stress and insulin resistance and found that stress can impair glucose homeostasis, working through at least six molecular pathways.

Association of serum lipid levels with psychotic symptoms in first-episode and drug naïve outpatients with major depressive disorder: a large-scale cross-sectional study

Background Major depressive disorder (MDD) is a prevalent psychiatric disorder, with increasing evidence that patients with MDD display psychotic symptoms. Studies have shown the association between lipid levels and MDD, but few have explored the relationship between lipids and psychotic symptoms in MDD. The objective of this study was to compare the differences of lipid levels between patients with psychotic major depressive disorder (PMD) and those with non-psychotic major depressive disorder (NPMD) in first-episode and drug-naive (FEDN) MDD patients. Methods A total of 1718 outpatients with FEDN MDD were recruited. In addition to collecting basic information, their blood specimens were also collected to detect serum TC, HDL-C, TG, and LDL-C. The Hamilton depression scale (HAMD), Hamilton anxiety scale (HAMA), and Positive and Negative Syndrome Scale (PANSS) were used to assess their depression, anxiety, and psychotic symptoms respectively. Results Compared to those with NPMD, those with PMD had higher scores on HAMD, HAMA, and more elevated serum TC, TG, and LDL-C levels, but lower HDL-C levels (all p < 0.05). Further logistic regression analysis showed that TG, the severity of depressive and anxiety symptoms were significantly associated with psychotic symptoms (p < 0.05). Limitations No causal relationship could be drawn due to the cross-sectional design. Conclusions Psychotic symptoms in patients with MDD may be predicted by lipid levels in the future. Our findings suggest that TG seems to predict the presence of current psychotic features among patients with FEDN MDD.

COVID 19-transformed nursing education and communication competency: Testing COMFORT educational resources

BACKGROUND

The COVID-19 pandemic brought a disruption to nurse education for both nursing faculty and students as all non-clinical nurse education courses worldwide moved to distance or online learning. The sudden shift to online education meant the loss of traditional activities for students to learn communication skills creating a critical demand for open educational resources for students and nursing faculty. Tools to support nursing faculty development for teaching communication are nearly non-existent and pedagogical content knowledge is needed.

OBJECTIVES

The purpose of this study was to test two COMFORT COVID-19 Communication Modules (PPE and Video/Phone) for undergraduate nursing students and evaluate student communication competency post-intervention.

DESIGN

This pre-post study includes qualitative and quantitative data collected to evaluate student communication competency post-intervention.

SETTINGS

Undergraduate Bachelor of Science in Nursing (BSN) students at four university campuses in the Pacific and MidSouth regions of the United States.

PARTICIPANTS

BSN nursing students (n = 197) predominantly in the third year of study (n = 138, 70%).

METHODS

Students completed online modules as part of a nursing course. Faculty provided information and a link to access online learning modules. A pre-post assessment was completed for each module.

RESULTS

Significant statistical differences were found across variables of communication attitude, knowledge, and skill across both modules.

CONCLUSIONS

As nursing education in the United States shifts to competency-based education which emphasizes skill development across the BSN program, it is imperative to establish communication learning objectives that are measurable and ensure communication theory and evidence-based practice is part of curriculum content.

Brain Versus Blood: A Systematic Review on the Concordance Between Peripheral and Central Kynurenine Pathway Measures in Psychiatric Disorders

Objective

Disturbances in the kynurenine pathway have been implicated in the pathophysiology of psychotic and mood disorders, as well as several other psychiatric illnesses. It remains uncertain however to what extent metabolite levels detectable in plasma or serum reflect brain kynurenine metabolism and other disease-specific pathophysiological changes. The primary objective of this systematic review was to investigate the concordance between peripheral and central (CSF or brain tissue) kynurenine metabolites. As secondary aims we describe their correlation with illness course, treatment response, and neuroanatomical abnormalities in psychiatric diseases.

Methods

We performed a systematic literature search until February 2021 in PubMed. We included 27 original research articles describing a correlation between peripheral and central kynurenine metabolite measures in preclinical studies and human samples from patients suffering from neuropsychiatric disorders and other conditions. We also included 32 articles reporting associations between peripheral KP markers and symptom severity, CNS pathology or treatment response in schizophrenia, bipolar disorder or major depressive disorder.

Results

For kynurenine and 3-hydroxykynurenine, moderate to strong concordance was found between peripheral and central concentrations not only in psychiatric disorders, but also in other (patho)physiological conditions. Despite discordant findings for other metabolites (mainly tryptophan and kynurenic acid), blood metabolite levels were associated with clinical symptoms and treatment response in psychiatric patients, as well as with observed neuroanatomical abnormalities and glial activity.

Conclusion

Only kynurenine and 3-hydroxykynurenine demonstrated a consistent and reliable concordance between peripheral and central measures. Evidence from psychiatric studies on kynurenine pathway concordance is scarce, and more research is needed to determine the validity of peripheral kynurenine metabolite assessment as proxy markers for CNS processes. Peripheral kynurenine and 3-hydroxykynurenine may nonetheless represent valuable predictive and prognostic biomarker candidates for psychiatric disorders.

Causal relationships between blood lipids and depression phenotypes: a Mendelian randomisation analysis

BACKGROUND

The etiology of depression remains poorly understood. Changes in blood lipid levels were reported to be associated with depression and suicide, however study findings were mixed.

METHODS

We performed a two-sample Mendelian randomisation (MR) analysis to investigate the causal relationship between blood lipids and depression phenotypes, based on large-scale GWAS summary statistics (N = 188 577/480 359 for lipid/depression traits respectively). Five depression-related phenotypes were included, namely major depression (MD; from PGC), depressive symptoms (DS; from SSGAC), longest duration and number of episodes of low mood, and history of deliberate self-harm (DSH)/suicide (from UK Biobank). MR was conducted with inverse-variance weighted (MR-IVW), Egger and Generalised Summary-data-based MR (GSMR) methods.

RESULTS

There was consistent evidence that triglyceride (TG) is causally associated with DS (MR-IVW β for one-s.d. increase in TG = 0.0346, 95% CI 0.0114-0.0578), supported by MR-IVW and GSMR and multiple r2 clumping thresholds. We also observed relatively consistent associations of TG with DSH/suicide (MR-Egger OR = 2.514, CI 1.579-4.003). There was moderate evidence for positive associations of TG with MD and the number of episodes of low mood. For HDL-c, we observed moderate evidence for causal associations with DS and MD. LDL-c and TC did not show robust causal relationships with depression phenotypes, except for weak evidence that LDL-c is inversely related to DSH/suicide. We did not detect significant associations when depression phenotypes were treated as exposures.

CONCLUSIONS

This study provides evidence to a causal relationship between TG, and to a lesser extent, altered cholesterol levels with depression phenotypes. Further studies on its mechanistic basis and the effects of lipid-lowering therapies are warranted.

Targeting Metabolic Dysfunction for the Treatment of Mood Disorders: Review of the Evidence

Major depressive disorder (MDD) and bipolar disorder (BD) are often chronic with many patients not responding to available treatments. As these mood disorders are frequently associated with metabolic dysfunction, there has been increased interest in novel treatments that would target metabolic pathways. The objectives of this scoping review were to synthesize evidence on the impact on mood symptoms of lipid lowering agents and anti-diabetics drugs, while also reviewing current knowledge on the association between mood disorders and dyslipidemia or hyperglycemia. We propose that metabolic dysfunction is prevalent in both MDD and BD and it may contribute to the development of these disorders through a variety of pathophysiological processes including inflammation, brain structural changes, hormonal alterations, neurotransmitter disruptions, alteration on brain cholesterol, central insulin resistance, and changes in gut microbiota. Current evidence is conflicting on the use of statins, polyunsaturated fatty acids, thiazolidinediones, glucagon-like peptide agonists, metformin, or insulin for the treatment of MDD and BD. Given the paucity of high-quality randomized controlled trials, additional studies are needed before any of these medications can be repurposed in routine clinical practice. Future trials need to enrich patient recruitment, include evaluations of mechanism of action, and explore differential effects on specific symptom domains such as anhedonia, suicidality, and cognition.

Age-Related Neurometabolomic Signature of Mouse Brain

Neurometabolites are the ultimate gene products in the brain and the most precise biomolecular indicators of brain endophenotypes. Metabolomics is the only "omics" that provides a moment-to-moment "snapshot" of brain circuits' biochemical activities in response to external stimuli within the context of specific genetic variations. Although the expression levels of neurometabolites are highly dynamic, the underlying metabolic processes are tightly regulated during brain development, maturation, and aging. Therefore, this study aimed to identify mouse brain metabolic profiles in neonatal and adult stages and reconstruct both the active metabolic network and the metabolic pathway functioning. Using high-throughput metabolomics and bioinformatics analyses, we show that the neonatal mouse brain has its distinct metabolomic signature, which differs from the adult brain. Furthermore, lipid metabolites showed the most profound changes between the neonatal and adult brain, with some lipid species reaching 1000-fold changes. There were trends of age-dependent increases and decreases among lipids and non-lipid metabolites, respectively. A few lipid metabolites such as HexCers and SHexCers were almost absent in neonatal brains, whereas other non-lipid metabolites such as homoarginine were absent in the adult brains. Several molecules that act as neurotransmitters/neuromodulators showed age-dependent levels, with adenosine and GABA exhibiting around 100- and 10-fold increases in the adult compared with the neonatal brain. Of particular interest is the observation that purine and pyrimidines nucleobases exhibited opposite age-dependent changes. Bioinformatics analysis revealed an enrichment of lipid biosynthesis pathways in metabolites, whose levels increased in adult brains. In contrast, pathways involved in the metabolism of amino acids, nucleobases, glucose (glycolysis), tricarboxylic acid cycle (TCA) were enriched in metabolites whose levels were higher in the neonatal brains. Many of these pathways are associated with pathological conditions, which can be predicted as early as the neonatal stage. Our study provides an initial age-related biochemical directory of the mouse brain and warrants further studies to identify temporal brain metabolome across the lifespan, particularly during adolescence and aging. Such neurometabolomic data may provide important insight about the onset and progression of neurological/psychiatric disorders and may ultimately lead to the development of precise diagnostic biomarkers and more effective preventive/therapeutic strategies.

Multi-Omics Approaches and Radiation on Lipid Metabolism in Toothed Whales

Lipid synthesis pathways of toothed whales have evolved since their movement from the terrestrial to marine environment. The synthesis and function of these endogenous lipids and affecting factors are still little understood. In this review, we focused on different omics approaches and techniques to investigate lipid metabolism and radiation impacts on lipids in toothed whales. The selected literature was screened, and capacities, possibilities, and future approaches for identifying unusual lipid synthesis pathways by omics were evaluated. Omics approaches were categorized into the four major disciplines: lipidomics, transcriptomics, genomics, and proteomics. Genomics and transcriptomics can together identify genes related to unique lipid synthesis. As lipids interact with proteins in the animal body, lipidomics, and proteomics can correlate by creating lipid-binding proteome maps to elucidate metabolism pathways. In lipidomics studies, recent mass spectroscopic methods can address lipid profiles; however, the determination of structures of lipids are challenging. As an environmental stress, the acoustic radiation has a significant effect on the alteration of lipid profiles. Radiation studies in different omics approaches revealed the necessity of multi-omics applications. This review concluded that a combination of many of the omics areas may elucidate the metabolism of lipids and possible hazards on lipids in toothed whales by radiation.

The role of high-density lipoprotein cholesterol, apolipoprotein A and paraoxonase-1 in the pathophysiology of neuroprogressive disorders

Lowered high-density lipoprotein (HDL) cholesterol has been reported in major depressive disorder, bipolar disorder, first episode of psychosis, and schizophrenia. HDL, its major apolipoprotein component, ApoA1, and the antioxidant enzyme paraoxonase (PON)1 (which is normally bound to ApoA1) all have anti-atherogenic, antioxidant, anti-inflammatory, and immunomodulatory roles, which are discussed in this paper. The paper details the pathways mediating the anti-inflammatory effects of HDL, ApoA1 and PON1 and describes the mechanisms leading to compromised HDL and PON1 levels and function in an environment of chronic inflammation. The molecular mechanisms by which changes in HDL, ApoA1 and PON1 might contribute to the pathophysiology of the neuroprogressive disorders are explained. Moreover, the anti-inflammatory actions of ApoM-mediated sphingosine 1-phosphate (S1P) signalling are reviewed as well as the deleterious effects of chronic inflammation and oxidative stress on ApoM/S1P signalling. Finally, therapeutic interventions specifically aimed at improving the levels and function of HDL and PON1 while reducing levels of inflammation and oxidative stress are considered. These include the so-called Mediterranean diet, extra virgin olive oil, polyphenols, flavonoids, isoflavones, pomegranate juice, melatonin and the Mediterranean diet combined with the ketogenic diet.

Urine Albumin/Creatinine Ratio and Microvascular Disease in Elderly Hypertensive Patients without Comorbidities

OBJECTIVES

A high urine albumin/creatinine ratio (UACR) is associated with microvascular disease in hypertensive patients. However, hypertensive patients frequently have other comorbidities. Thus, it is difficult to distinguish the role of UACR from that of comorbidities in microvascular disease. The aim of this study was to evaluate the association between UACR and microvascular disease in elderly hypertension patients without comorbidities.

METHODS

A cross-sectional cohort study of 2252 essential hypertension patients aged 65-94 years without comorbidities between January 1, 2016, and December 31, 2017, was conducted. Microvascular disease was evaluated by hypertension retinopathy (HR). Multivariable adjusted odds of HR by UACR quartiles were determined using logistic regression.

RESULTS

The HR prevalence was 22.1% (n = 472) among the cohort study and was significantly different among UACR quartiles (19.7%, 20.3%, 22.0%, and 26.4% in quartiles 1, 2, 3, and 4, respectively, P = 0.036). After adjustment for covariates, higher UACR (odds ratio (OR) = 1.42, 95% confidence interval (CI) 1.05-1.92, quartile 4 versus 1) were significantly associated with HR. Among male patients, higher UACR (OR = 1.65, 95% CI 1.07-2.55, quartile 4 versus 1) were significantly associated with HR after adjustment for covariates. Among female patients, however, 64% and 40% increased odds of HR were noted in the highest and lowest UACR (quartiles 4 and 1, respectively) compared to UACR quartile 2.

CONCLUSIONS

Microvascular disease was associated with higher UACR in elderly male essential hypertension patients without comorbidities but was associated with lower and higher UACR in female patients without comorbidities.

Association Between Serum Lipid Levels, Resilience, and Self-Esteem in Japanese Adolescents: Results From A-CHILD Study

Previous studies have found that serum lipid levels independently associate with mental health problems in adulthood. However, little is known about the association between serum lipid levels and positive aspects of mental health such as resilience and self-esteem, which develop in adolescence. The aim of this study is to examine the association between serum lipid levels and resilience and self-esteem in Japanese adolescents. Data were pooled data from the Adachi Child Health Impact of Living Difficulty (A-CHILD) study in 2016 and 2018, a school-based, cross-sectional study in Adachi City, Tokyo, Japan (N = 1,056, aged 13–14 years). Resilience of the child was assessed by caregivers, and self-esteem was self-identified via questionnaires. Serum lipid levels [total cholesterol, low-density lipoproteins (LDL), and high-density lipoproteins (HDL)] were assessed in school health checkup, in addition to height and weight measurements. Multiple linear regression was applied to investigate the association between standardized serum lipid levels and resilience and self-esteem. LDL showed inverse association with resilience [β = −1.26, 95% confidence interval (CI) = −2.39 to −0.14] after adjusting for child’s BMI, month of birth, sex, absence of parent, household income, caregiver’s mental health, and lifestyle (e.g., habits of eating, physical activity, and sleep). We also found an inverse association of total cholesterol and higher LDL cholesterol with self-esteem (β = −0.58, 95% CI = −0.99 to −0.18; β = −0.42, 95% CI = −0.83 to −0.01, respectively). HDL cholesterol was not associated with resilience and self-esteem. Among Japanese adolescent, total and LDL cholesterol may be biomarkers of resilience and self-esteem.

Association between Dietary Patterns and Major Depression in Adult Females: A Case-Control Study

Background: Depression is one of the most common mental disorders. This study aimed to determine the association between dietary patterns and major depression in adult females.

Study design: A case-control study.

Methods: This study was conducted on adult females suffering from major depression within the age range from 19 to 65 years. The total participants of this study included 170 cases and 340 controls. Dietary intakes were collected using a 168-item validated semi-quantitative food-frequency questionnaire. Household food security was measured using a locally adapted Household Food Insecurity Access Scale. Moreover, the depression status of the adult females was assessed through a validated "Beck" questionnaire. Logistic regression was utilized to assess the association between dietary pattern scores and depression.

Results: The mean ±SD ages of the participants were 36.97 ±11.28 and 36.07 ±10.58 years in the case and control groups, respectively (P=0.374), and five major dietary patterns were extracted in this study. The odds ratio (OR) in the last adjusted model was (OR: 0.61; 95% CI: 0.46, 0.81); therefore, the "Healthy pattern" was significantly inversely associated with the odds of depression. Adherence to the "Western pattern" significantly increased depression by 29% (OR: 1.29; 95% CI: 1.06, 1.59). Furthermore, the "Traditional pattern" was positively associated with depression (OR: 1.16; 95% CI: 0.94, 1.43). There was no significant association between "Sugar and fast food" and "red meat and oils" dietary pattern and depression.

Conclusions: Healthy dietary pattern reduces the risk of depression in adult females; however, the western and traditional dietary patterns increases this risk.

Lipid and Glycemic Profiles in Patients with Bipolar Disorder: Cholesterol Levels Are Reduced in Mania

Background and Objectives: Bipolar disorder (BD) is a severe mental condition with a lifetime prevalence estimated around 2% among the general population. Due to risk factors, etiological mechanisms, and the chronic use of psychotropic medications, people with BD are frequently affected by medical comorbidities, such as metabolic syndrome (MetS), associated with altered blood levels of glucose, cholesterol, and triglycerides. Moreover, the lipid concentration may be associated with the severity of psychiatric symptoms. Materials and Methods: Five hundred and forty-two in- and outpatients (418 affected by BD and 124 affected by schizophrenia) were recruited in two Italian university hospitals. A blood examination assessing the fasting glucose, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides was performed. Results: No significant differences were found in the lipid and glycemic profiles between patients with BD and schizophrenia. When considering only the BD sample, we found that patients experiencing a manic episode had significantly lower total cholesterol, HDL, and LDL than euthymic patients. Moreover, the total and LDL cholesterol levels were significantly lower in (hypo)manic than depressed patients. Mood episodes did not influence the triglyceride and glucose levels in our sample. Conclusions: Clinicians should pay attention to blood cholesterol levels in patients with BD, as differences in concentrations may predispose them to severe medical conditions and can be associated with the onset of mood episodes.

Good, better, best: clinical scenarios for the use of L-methylfolate in patients with MDD

Depression is among the most prevalent mental disorders worldwide, and a substantial proportion of patients do not respond adequately to standard antidepressants. Our understanding of the pathophysiology of depression is no longer limited to the chemical imbalance of neurotransmitters, but also involves the interplay of proinflammatory modulators in the central nervous system, as well as folate metabolism. Additional factors such as stress and metabolic disorders also may contribute. Multiple inflammatory, metabolic, and genetic markers have been identified and may provide critical information to help clinicians individualize treatments for patients to achieve optimal outcomes. Recent advancements in research have clarified underlying causes of depression and have led to possible new avenues for adjunctive treatment. Among these is L-methylfolate, a medical food that is thought to enhance synthesis of monoamines (serotonin, norepinephrine, and dopamine), suppress inflammation, and promote neural health. Clinical studies that assessed supplemental use of L-methylfolate in patients with usual care-resistant depression found that it resulted in improved outcomes. Patients with selective serotonin reuptake inhibitor-resistant depression, and particularly subgroups with biomarkers of inflammation or metabolic disorders or folate metabolism-related genetic polymorphisms (or ≥2 of these factors), had the best responses. Considering this, the goals of this review are to 1) highlight recent advances in the pathophysiology of major depressive disorder as it pertains to folate and associated biomarkers and 2) establish the profiles of patients with depression who could benefit most from supplemental use of L-methylfolate.