Metabolomic markers of antepartum depression and suicidal ideation

Maternal Antenatal Depression Is Associated With Metabolic Alterations That Predict Birth Outcomes and Child Neurodevelopment and Mental Health

BACKGROUND

Evidence regarding metabolic alterations associated with maternal antenatal depression (AD) is limited, and their role as potential biomarkers that improve the prediction of AD and adverse childbirth, neurodevelopmental, and mental health outcomes remains unexplored.

METHODS

In a cohort of 331 mother-child dyads, we studied associations between AD (a history of medical register diagnoses and/or a Center for Epidemiological Studies Depression Scale score during pregnancy ≥ 20) and 95 metabolic measures analyzed 3 times during pregnancy. We tested whether the AD-related metabolic measures increased variance explained in AD over its risk factors and in childbirth, neurodevelopmental, and mental health outcomes over AD. We replicated the findings in a cohort of 416 mother-child dyads.

RESULTS

Elastic net regression identified 15 metabolic measures that collectively explained 25% (p < .0001) of the variance in AD, including amino and fatty acids, glucose, inflammation, and lipids. These metabolic measures increased the variance explained in AD over its risk factors (32.3%, p < .0001 vs. 12.6%, p = .004) and in child gestational age (9.0%, p < .0001 vs. 0.7%, p = .34), birth weight (9.0%, p = .03 vs. 0.7%, p = .33), developmental milestones at the age of 2.3 to 5.7 years (21.0%, p = .002 vs. 11.6%, p < .001), and any mental or behavioral disorder by the age of 13.1 to 16.8 years (25.2%, p = .03 vs. 5.0%, p = .11) over AD, child sex, and age. These findings were replicated in the independent cohort.

CONCLUSIONS

AD was associated with alterations in 15 metabolic measures, which collectively improved the prediction of AD over its risk factors and birth, neurodevelopmental, and mental health outcomes in children over AD. These metabolic measures may become biomarkers that can be used to identify at-risk mothers and children for personalized interventions.

Association between gut microbiota and perinatal depression and anxiety among a pregnancy cohort in Hunan, China

BACKGROUND

Perinatal depression and anxiety pose significant risks to maternal health and may lead to suicide. The gut microbiota may play a crucial role in perinatal depression and anxiety. However, the relationship between the alterations in gut microbiota and perinatal depression and anxiety remains unclear. This study aimed to investigate the dynamic changes of gut microbiota over various perinatal stages and their associations with perinatal depression and anxiety symptoms, especially suicide ideation.

METHODS

A total of 177 pregnant and 19 postpartum women were recruited in this study, with 48 of them participating longitudinally. Maternal depression and anxiety symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS), 9-item Patient Health Questionnaire (PHQ-9), and 7-item Generalized Anxiety Disorder Scale (GAD-7). Fecal samples collected during the perinatal period were analyzed using 16S rRNA gene sequencing.

RESULTS

Significant changes in microbial diversity and multi-taxonomic levels were observed during pregnancy. The random forest regression model showed significant associations of some gut microbial features with depression and anxiety symptoms. Several genera were significantly associated with gestation age and perinatal depression and anxiety, such as Akkermansia, Bifidobacterium and Streptococcus. In addition, Erysipelotrichaceae_UCG-003 and Eubacterium_hallii_group were positively associated with suicidal ideation. The glycine biosynthesis pathway might act as a mediator between Eubacterium_hallii_group and suicidal ideation (ab = 3.27, p < 0.05).

CONCLUSION

The gut microbiota undergoes a programmed shift during pregnancy, which may play a critical role in perinatal depression and anxiety. Our findings underscore the impact of certain bacterial genera and metabolic pathways on perinatal mental health, which may help to develop new diagnostic tools and targeted interventions to reduce perinatal mental disorders and improve the outcomes for both mothers and infants.

Biological and behavioral pathways from prenatal depression to offspring cardiometabolic risk: Testing the developmental origins of health and disease hypothesis

Given prior literature focused on the Developmental Origins of Health and Disease framework, there is strong rationale to hypothesize that reducing depression in the prenatal period will cause improvements in offspring cardiometabolic health. The current review outlines evidence that prenatal depression is associated with offspring cardiometabolic risk and health behaviors. We review evidence of these associations in humans and in nonhuman animals at multiple developmental periods, from the prenatal period (maternal preeclampsia, gestational diabetes), neonatal period (preterm birth, small size at birth), infancy (rapid weight gain), childhood and adolescence (high blood pressure, impaired glucose-insulin homeostasis, unfavorable lipid profiles, abdominal obesity), and into adulthood (diabetes, cardiovascular disease). In addition to these cardiometabolic outcomes, we focus on health behaviors associated with cardiometabolic risk, such as child eating behaviors, diet, physical activity, and sleep health. Our review focuses on child behaviors (e.g., emotional eating, preference for highly palatable foods, short sleep duration) and parenting behaviors (e.g., pressuring child to eat, modeling of health behaviors). These changes in health behaviors may be detected before changes to cardiometabolic outcomes, which may allow for early identification of and prevention for children at risk for poor adult cardiometabolic outcomes. We also discuss the methods of the ongoing Care Project, which is a randomized clinical trial to test whether reducing prenatal maternal depression improves offspring's cardiometabolic health and health behaviors in preschool. The goal of this review and the Care Project are to inform future research, interventions, and policies that support prenatal mental health and offspring cardiometabolic health. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Depicting the molecular features of suicidal behavior: a review from an "omics" perspective

Background Suicide is one of the leading global causes of death. Behavior patterns from suicide ideation to completion are complex, involving multiple risk factors. Advances in technologies and large-scale bioinformatic tools are changing how we approach biomedical problems. The "omics" field may provide new knowledge about suicidal behavior to improve identification of relevant biological pathways associated with suicidal behavior. Methods We reviewed transcriptomic, proteomic, and metabolomic studies conducted in blood and post-mortem brains from individuals who experienced suicide or suicidal behavior. Omics data were combined using systems biology in silico, aiming at identifying major biological mechanisms and key molecules associated with suicide. Results Post-mortem samples of suicide completers indicate major dysregulations in pathways associated with glial cells (astrocytes and microglia), neurotransmission (GABAergic and glutamatergic systems), neuroplasticity and cell survivor, immune responses and energy homeostasis. In the periphery, studies found alterations in molecules involved in immune responses, polyamines, lipid transport, energy homeostasis, and amino and nucleic acid metabolism. Limitations We included only exploratory, non-hypothesis-driven studies; most studies only included one brain region and whole tissue analysis, and focused on suicide completers who were white males with almost none confounding factors. Conclusions We can highlight the importance of synaptic function, especially the balance between the inhibitory and excitatory synapses, and mechanisms associated with neuroplasticity, common pathways associated with psychiatric disorders. However, some of the pathways highlighted in this review, such as transcriptional factors associated with RNA splicing, formation of cortical connections, and gliogenesis, point to mechanisms that still need to be explored.

Maternal Metabolites Indicative of Mental Health Status during Pregnancy

Approximately 25% of individuals report poor mental health during their pregnancy or postpartum period, which may impact fetal neurodevelopment, birth outcomes, and maternal behaviors. In the present study, maternal serum samples were collected from pregnancies at 28-32 weeks gestation from the All Our Families (Alberta, Canada) cohort and assessed using nuclear magnetic resonance spectroscopy (¹H-NMR) and inductively coupled plasma-mass spectrometry (ICP-MS). Individuals with poor mental health at 34-36 weeks gestation were age-matched with mentally healthy pregnant controls. Metabolites were examined against validated self-reported mental health questionnaires for associations with depressive symptoms (Edinburgh Perinatal Depression Scale) and anxiety symptoms (Spielberger State-Trait Anxiety Inventory). ¹H-NMR metabolites were identified for depression (alanine, leucine, valine, methionine, phenylalanine, glucose, lactate, 3-hydroxybutyrate, and pyruvate) and anxiety (3-hydroxybutyrate). For ICP-MS, antimony and zinc were significant for depression and anxiety, respectively. Upon false discovery rate (FDR) correction at 10%, five ¹H-NMR metabolites (alanine, leucine, lactate, glucose, and phenylalanine) for depression remained significantly increased. Although results warrant further validation, the identified metabolites may serve as a predictive tool for assessing mental health during pregnancy as earlier identification has the potential to aid intervention and management of poor mental health symptomology, thus avoiding harmful consequences to both mother and offspring.

Peripheral and neural correlates of self-harm in children and adolescents: a scoping review

BACKGROUND

Self-harm in children and adolescents is difficult to treat. Peripheral and neural correlates of self-harm could lead to biomarkers to guide precision care. We therefore conducted a scoping review of research on peripheral and neural correlates of self-harm in this age group.

METHODS

PubMed and Embase databases were searched from January 1980-May 2020, seeking English language peer-reviewed studies about peripheral and neural correlates of self-harm, defined as completed suicide, suicide attempts, suicidal ideation, or non-suicidal self-injury (NSSI) in subjects, birth to 19 years of age. Studies were excluded if only investigating self-harm in persons with intellectual or developmental disability syndromes. A blinded multi-stage assessment process by pairs of co-authors selected final studies for review. Risk of bias estimates were done on final studies.

RESULTS

We screened 5537 unduplicated abstracts, leading to the identification of 79 eligible studies in 76 papers. Of these, 48 investigated peripheral correlates and 31 examined neural correlates. Suicidality was the focus in 2/3 of the studies, with NSSI and any type of self-harm (subjects recruited with suicidality, NSSI, or both) investigated in the remaining studies. All studies used observational designs (primarily case-control), most used convenience samples of adolescent patients which were predominately female and half of which were recruited based on a disorder. Over a quarter of the specific correlates were investigated with only one study. Inter-study agreement on findings from specific correlates with more than one study was often low. Estimates of Good for risk of bias were assigned to 37% of the studies and the majority were rated as Fair.

CONCLUSIONS

Research on peripheral and neural correlates of self-harm is not sufficiently mature to identify potential biomarkers. Conflicting findings were reported for many of the correlates studied. Methodological problems may have produced biased findings and results are mainly generalizable to patients and girls. We provide recommendations to improve future peripheral and neural correlate research in children and adolescents, ages 3-19 years, with self-harm.

Carnitine and Depression

Depression has become one of the most common mental diseases in the world, but the understanding of its pathogenesis, diagnosis and treatments remains insufficient. Carnitine is a natural substance that exists in organisms, which can be synthesized in vivo or supplemented by intake. Relationships of carnitine with depression, bipolar disorder and other mental diseases have been reported in different studies. Several studies show that the level of acylcarnitines (ACs) changes significantly in patients with depression compared with healthy controls while the supplementation of acetyl-L-carnitine is beneficial to the treatment of depression. In this review, we aimed to clarify the effects of ACs in depressive patients and to explore whether ACs might be the biomarkers for the diagnosis of depression and provide new ideas to treat depression.

The prevalence of suicide ideation and predictive factors among pregnant women in the third trimester

BACKGROUND

Pregnancy is a period for women undergo major physical and psychological changes. Suicide is a cause of maternal death and suicidal ideation is a key factor in suicidal behavior. The purpose of this study was to investigate the prevalence of suicidal ideation in the third trimester and associated predictors including psychological factors such as attachment.

METHODS

A cross-sectional study included 432 pregnant women in the third trimester of pregnancy was conducted in a tertiary hospital. The Edinburgh Postpartum Depression Scale (EPDS) was used to assess prenatal depression and suicidal ideation. The Zung Self-Rating Anxiety Scale (SAS) and Experience of Close Relationship (ECR) scale were used to assess anxiety and attachment respectively.

RESULTS

The results showed that the EPDS scale screened 6.71% of pregnant women with suicidal ideation. Compared with those without suicidal ideation, pregnant women with suicidal ideation had a higher prevalence of insecure attachment, higher scores on the two dimensions of attachment (attachment avoidance and attachment anxiety), and higher prevalence of prenatal depression and anxiety. Binary logistic regression showed that marital satisfaction was a protective factor for suicidal ideation, while prenatal depression, prenatal anxiety and attachment anxiety were risk factors for suicidal ideation.

CONCLUSIONS

The suicidal ideation among pregnant women was high, which should be given more attention. In the process of preventing and intervening suicidal ideation, in addition to the emotional state of pregnant women, their psychological factors such as attachment anxiety should also be considered.

'Omics' of suicidal behaviour: A path to personalised psychiatry

Psychiatric disorders, including suicide, are complex disorders that are affected by many different risk factors. It has been estimated that genetic factors contribute up to 50% to suicide risk. As the candidate gene approach has not identified a gene or set of genes that can be defined as biomarkers for suicidal behaviour, much is expected from cutting edge technological approaches that can interrogate several hundred, or even millions, of biomarkers at a time. These include the '-omic' approaches, such as genomics, transcriptomics, epigenomics, proteomics and metabolomics. Indeed, these have revealed new candidate biomarkers associated with suicidal behaviour. The most interesting of these have been implicated in inflammation and immune responses, which have been revealed through different study approaches, from genome-wide single nucleotide studies and the micro-RNA transcriptome, to the proteome and metabolome. However, the massive amounts of data that are generated by the '-omic' technologies demand the use of powerful computational analysis, and also specifically trained personnel. In this regard, machine learning approaches are beginning to pave the way towards personalized psychiatry.

Circulating choline pathway nutrients and depression after ischemic stroke

BACKGROUND AND PURPOSE

Choline pathway nutrients, including choline and betaine, are reported to exert antidepressant effects. However, there is little population-based evidence on the relationships between circulating choline and betaine and poststroke depression (PSD). We aimed to prospectively explore the associations between plasma choline and betaine and depression after ischemic stroke.

METHODS

This study was based on the China Antihypertensive Trial in Acute Ischemic Stroke. A total of 612 participants with plasma choline and betaine concentrations were included in the analysis. The study outcome was depression 3 months after ischemic stroke. Logistic regression models were performed to estimate the relationships between plasma choline and betaine and the risk of PSD. Risk reclassification and calibration of models with choline or betaine were analyzed.

RESULTS

Patients with PSD had lower choline and betaine levels than those without PSD (p < 0.05). Compared with tertile 1, the multivariable-adjusted odds ratios (95% CIs) for tertile 3 of choline and betaine were 0.54 (0.35-0.83) and 0.59 (0.38-0.92), respectively. Per 1 SD increase in choline or betaine was associated with a 25% (95% CI 9%-37%) or an 19% (95% CI 3%-32%) decreased risk of PSD, respectively. Furthermore, the addition of choline or betaine to the established risk factors model improved the risk reclassification for PSD, as shown by an increase in the net reclassification index and integrated discrimination improvement (all p < 0.05).

CONCLUSIONS

Patients with elevated levels of choline and betaine had a lower risk of depression after acute ischemic stroke, suggesting the protective significance of choline pathway nutrients for PSD.

Serum Metabolic Profiling of Late-Pregnant Women With Antenatal Depressive Symptoms

Background: Antenatal depression (AD) is a major public health issue worldwide and lacks objective laboratory-based tests to support its diagnosis. Recently, small metabolic molecules have been found to play a vital role in interpreting the pathogenesis of AD. Thus, non-target metabolomics was conducted in serum. Methods: Liquid chromatography-tandem mass spectrometry-based metabolomics platforms were used to conduct serum metabolic profiling of AD and non-antenatal depression (NAD). Orthogonal partial least squares discriminant analysis, the non-parametric Mann-Whitney U test, and Benjamini-Hochberg correction were used to identify the differential metabolites between AD and NAD groups; Spearman's correlation between the key differential metabolites and Edinburgh Postnatal Depression Scale (EPDS) and the stepwise logistic regression analysis was used to identify potential biomarkers. Results: In total, 79 significant differential metabolites between AD and NAD were identified. These metabolites mainly influence amino acid metabolism and glycerophospholipid metabolism. Then, PC (16:0/16:0) and betaine were significantly positively correlated with EPDS. The simplified biomarker panel consisting of these three metabolites [betaine, PC (16:0/16:0) and succinic acid] has excellent diagnostic performance (95% confidence interval = 0.911-1.000, specificity = 95%, sensitivity = 85%) in discriminating AD and NAD. Conclusion: The results suggested that betaine, PC (16:0/16:0), and succinic acid were potential biomarker panels, which significantly correlated with depression; and it could make for developing an objective method in future to diagnose AD.

Alteration of lipids and amino acids in plasma distinguish schizophrenia patients from controls: A targeted metabolomics study

BACKGROUND

Schizophrenia (SCZ) is a serious psychiatric disorder. Metabolite disturbance is an important pathogenic factor in schizophrenic patients. In this study, we aim to identify plasma lipid and amino acid biomarkers for SCZ using targeted metabolomics.

METHODS

Plasma from 76 SCZ patients and 50 matched controls were analyzed using the LC/MS-based multiple reaction monitoring (MRM) metabolomics approach. A total of 182 targeted metabolites, including 22 amino acids and 160 lipids or lipid-related metabolites were observed. We used binary logistic regression analysis to determine whether the lipid and amino acid biomarkers could discriminate SCZ patients from controls. The area under the curve (AUC) from receiver operation characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the biomarkers panel.

RESULTS

We identified 19 significantly differentially expressed metabolites between the SCZ patients and the controls (false discovery rate < 0.05), including one amino acid and 18 lipids or lipid-related metabolites. The binary logistic regression-selected panel showed good diagnostic performance in the drug-naïve group (AUC = 0.936) and all SCZ patients (AUC = 0.948), especially in the drug-treated group (AUC = 0.963).

CONCLUSIONS

Plasma lipids and amino acids showed significant dysregulation in SCZ, which could effectively discriminate SCZ patients from controls. The LC/MS/MS-based approach provides reliable data for the objective diagnosis of SCZ.

Metabolic Profiling Indicates Diversity in the Metabolic Physiologies Associated With Maternal Postpartum Depressive Symptoms

Background: Postpartum depression (PPD) is a devastating disease requiring improvements in diagnosis and prevention. Blood metabolomics identifies biological markers discriminatory between women with and those without antenatal depressive symptoms. Whether this cutting-edge method can be applied to postpartum depressive symptoms merits further investigation. Methods: As a substudy within the Biology, Affect, Stress, Imagine and Cognition Study, 24 women with PPD symptom (PPDS) assessment at 6 weeks postpartum were included. Controls were selected as having a score of ≤ 6 and PPDS cases as ≥12 on the Edinburgh Postnatal Depression Scale. Blood plasma was collected at 10 weeks postpartum and analyzed with gas chromatography-mass spectrometry metabolomics. Results: Variations of metabolomic profiles within the PPDS samples were identified. One cluster showed altered kidney function, whereas the other, a metabolic syndrome profile, both previously associated with depression. Five metabolites (glycerol, threonine, 2-hydroxybutanoic acid, erythritol, and phenylalanine) showed higher abundance among women with PPDSs, indicating perturbations in the serine/threonine and glycerol lipid metabolism, suggesting oxidative stress conditions. Conclusions: Alterations in certain metabolites were associated with depressive pathophysiology postpartum, whereas diversity in PPDS physiologies was revealed. Hence, plasma metabolic profiling could be considered in diagnosis and pathophysiological investigation of PPD toward providing clues for treatment. Future studies require standardization of various subgroups with respect to symptom onset, lifestyle, and comorbidities.