Adverse childhood experiences and reoccurrence of illness impact the gut microbiome, which affects suicidal behaviours and the phenome of major depression: towards enterotypic phenotypes

Abstract

The first publication demonstrating that major depressive disorder (MDD) is associated with alterations in the gut microbiota appeared in 2008 (Maes et al., 2008). The purpose of the present study is to delineate a) the microbiome signature of the phenome of depression, including suicidal behaviors and cognitive deficits; the effects of adverse childhood experiences (ACE) and recurrence of illness index (ROI) on the microbiome; and the microbiome signature of lowered high-density lipoprotein cholesterol (HDLc). We determined isometric log-ratio abundances or prevalences of gut microbiome phyla, genera, and species by analyzing stool samples from 37 healthy Thai controls and 32 MDD patients using 16S rDNA sequencing. Six microbiome taxa accounted for 36% of the variance in the depression phenome, namely Hungatella and Fusicatenibacter (positive associations) and Butyricicoccus, Clostridium, Parabacteroides merdae, and Desulfovibrio piger (inverse association). This profile (labeled enterotype 1) indicates compositional dysbiosis, is strongly predicted by ACE and ROI, and is linked to suicidal behaviors. A second enterotype was developed that predicted a decrease in HDLc and an increase in the atherogenic index of plasma (Bifidobacterium, P. merdae, and Romboutsia were positively associated, while Proteobacteria and Clostridium sensu stricto were negatively associated). Together, enterotypes 1 and 2 explained 40.4% of the variance in the depression phenome, and enterotype 1 in conjunction with HDLc explained 39.9% of the variance in current suicidal behaviors. In conclusion, the microimmuneoxysome is a potential new drug target for the treatment of severe depression and suicidal behaviors, and possibly for the prevention of future episodes.

T helper-1 activation via interleukin-16 is a key phenomenon in the acute phase of severe, first-episode major depressive disorder and suicidal behaviors

“…All FED patients were in the acute stage of the illness, and none showed signs of complete or partial remission. The MDD patients fulfilled the criteria to be categorized as MDMD (Maes, Vasupanrajit et al 2023). This diagnosis can be made using machine learning models that we constructed based on the Hamilton Depression Rating Scale (HAMD) (Hamilton 1960) and Hamilton Anxiety Rating Scale (HAMA) (Hamilton 1959) rating scores, and SB and ROI scores or when the HAMD score is ≥ 22 and HAMA score ≥ 22.…”

“…These contradictory outcomes may be attributable to differences in the media employed to assay the immune mediators (e.g., serum versus CSF). Importantly, there are two phenotypes of MDD (see Introduction), and failure to account for the biomarker differences between MDMD and SDMD results in erroneous conclusions (Maes, Moraes et al 2021, Simeonova, Stoyanov et al 2021, Maes 2022, Maes, Vasupanrajit et al 2023). In addition, using the MDD diagnosis prevents the discovery of pathways due to the following issues: a) low reliability and validity of the MDD diagnosis; b) people with normal responses of sadness, feeling blue, grieving, and demoralisation are often lumped together with MDD because the criteria do not allow a sharp demarcation; and c) patients with an acute phase, partial remission, and remission are often lumped together Almulla 2022, Maes, Rachayon et al 2022).…”

“…Using machine learning techniques, a new discovery was made that there are in fact two types of MDD, namely major dysmood disorder (MDMD) and simple DMD (SDMD) (Maes, Moraes et al 2021. The first phenotype is characterised by increased severity of depression, anxiety, fatigue, suicidal behaviors (SB), and physio-somatic symptoms, lowered quality of life, more cognitive dysfunctions and disabilities; and disorders in (auto)immune, oxidative stress, antioxidant defenses, and gut microbiota that are not detected in patients with SDMD (Maes, Moraes et al 2021, Simeonova, Stoyanov et al 2021, Maes 2022, Maes, Vasupanrajit et al 2023. Importantly, the stimulated production of M1, Th-1, Th-2, Th-17, Treg, IRS, CIRS, and growth factors, was significantly higher in MDMD than in controls, while no such disorders could be established in SDMD (Maes, Rachayon et al 2022).…”

Analysis of arbuscular mycorrhizal fungi (AMF) community composition associated with alkaline saline sodic soils

“…However, using a clustering and polishing approach, errors can be corrected, and clusters can be obtained to perform ecological analysis. There are few reports of amplicon sequencing that used this approach (Beale et al, 2022; Maes et al, 2023), but with new bioinformatic tools and improved flow cell chemistry this trend will continue to grow. In this work, we used a clustering approach using abPOA, which works faster than other algorithms like sPOA (Vaser et al, 2017), and improved cluster quality with medaka to minimize errors.…”

Redefining Autoimmune Disorders’ Pathoetiology: Implications for Mood and Psychotic Disorders’ Association with Neurodegenerative and Classical Autoimmune Disorders

“…Adverse childhood events/abuse are long associated with MDD pathoetiology and distinct pathophysiology [218]. Recent work indicates that specific alterations in the gut microbiome in MDD lead to distinct pathophysiology-determined phenotypes [219]. This will be important to further investigate, especially given the association of childhood abusive events/abuse with 'autoimmune'/'immune-mediated' disorders [220].…”