Unraveling the complex interplay of immunometabolic systems that contribute to the neuroprogression of psychiatric disorders

Serum proteomic correlates of mental health symptoms in a representative UK population sample

Poor mental health constitutes a public health crisis due to its high prevalence, unmet need and its mechanistic heterogeneity. A comprehensive understanding of the biological correlates of poor mental health in the population could enhance epidemiological research and eventually help guide treatment strategies. The human bloodstream contains many proteins, several of which have been linked to diagnosed mental health conditions but not to population mental health symptoms, however recent technological advances have made this possible. Here we perform exploratory factor analyses of 184 proteins from two panels (cardiometabolic and neurology-related) measured using proximity extension assays from Understanding Society (the UK Household Longitudinal Study; UKHLS). Data reduction results in 28 factors that explain 55-59% of the variance per panel. We perform multiple linear regressions in up to 5304 participants using two mental health symptom-based outcomes: psychological distress assessed with the general health questionnaire (GHQ-12) and mental health functioning assessed with the 12-Item Short Form Survey, Mental Component Summary (SF12-MCS) using the proteomic factors as explanatory variables and adjusting for demographic covariates. We use backward selection to discard non-significant proteomic factors from the models. Ten factors are independently associated with population mental health symptoms, three of which are immune-related (immunometabolism, immune cell-mediated processes, acute phase processes), three brain-related (neurodevelopment, synaptic processes, neuroprotective processes), two proteolysis-related (proteolysis & the kynurenine pathway, haemostasis & proteolysis), growth factors & muscle, and oxidative stress & the cytoskeleton. Associations partially overlap across the two outcomes, and a sensitivity analysis excluding people taking antidepressants or other central nervous system medications suggestively implicates some of the factors in treatment-resistant poor mental health. Our findings replicate those of case-control studies and expand these to underlie mental health symptomatology in the adult population. More work is needed to understand the direction of causality in these associations.

Lower pattern recognition memory scores in anorexia nervosa

BACKGROUND

There is extensive evidence for volumetric reductions in the hippocampus in patients with anorexia nervosa (AN), however the impact on function is unclear. Pattern separation and recognition are hippocampus-dependent forms of learning thought to underlie stimulus discrimination.

METHODS

The present study used the Mnemonic Similarity Task to investigate pattern separation and recognition for the first time in patients with AN (N = 46) and healthy controls (N = 56). An Analysis of Covariance examined between-group differences, controlling for age, antidepressant use and method of task delivery (remote vs. in person).

RESULTS

When controlling for covariates, pattern recognition memory scores were lower in the AN group with a medium effect size (d = 0.51). In contrast, there was a small effect whereby patients with AN had a greater pattern separation score than controls (d = 0.34), albeit this difference was not significant at the p = 0.05 threshold (p = 0.133). Furthermore, pattern separation and recognition memory abilities were not related to age, body mass index, eating disorder psychopathology or trait anxiety levels.

CONCLUSIONS

This preliminary study provides initial evidence for an imbalance in pattern separation and recognition abilities in AN, a hippocampus-dependent cognitive ability. Further studies should endeavour to investigate pattern separation and recognition performance further in AN, as well as investigate other hippocampus-dependent functions.

Treatment-Resistant Depression Revisited: A Glimmer of Hope

Major Depressive Disorder (MDD) is a highly prevalent psychiatric disorder worldwide. It causes individual suffering, loss of productivity, increased health care costs and high suicide risk. Current pharmacologic interventions fail to produce at least partial response to approximately one third of these patients, and remission is obtained in approximately 30% of patients. This is known as Treatment-Resistant Depression (TRD). The burden of TRD exponentially increases the longer it persists, with a higher risk of impaired functional and social functioning, vast losses in quality of life and significant risk of somatic morbidity and suicidality. Different approaches have been suggested and utilized, but the results have not been encouraging. In this review article, we present new approaches to identify and correct potential causes of TRD, thereby reducing its prevalence and with it the overall burden of this disease entity. We will address potential contributory factors to TRD, most of which can be investigated in many laboratories as routine tests. We discuss endocrinological aberrations, notably, hypothalamic-pituitary-adrenal (HPA) axis dysregulation and thyroid and gonadal dysfunction. We address the role of Vitamin D in contributing to depression. Pharmacogenomic testing is being increasingly used to determine Single Nucleotide Polymorphisms in Cytochrome P450, Serotonin Transporter, COMT, folic acid conversion (MTHFR). As the role of immune system dysregulation is being recognized as potentially a major contributory factor to TRD, the measurement of C-reactive protein (CRP) and select immune biomarkers, where testing is available, can guide combination treatments with anti-inflammatory agents (e.g., selective COX-2 inhibitors) reversing treatment resistance. We focus on established and emerging test procedures, potential biomarkers and non-biologic assessments and interventions to apply personalized medicine to effectively manage treatment resistance in general and TRD specifically.

The Challenge of Assessing Mild Neuroinflammation in Severe Mental Disorders

Recent psychoneuroimmunology research has provided new insight into the etiology and pathogenesis of severe mental disorders (SMDs). The mild encephalitis (ME) hypothesis was developed with the example of human Borna disease virus infection years ago and proposed, that a subgroup SMD patients, mainly from the broad schizophrenic and affective spectrum, could suffer from mild neuroinflammation, which remained undetected because hard to diagnose with available diagnostic methods. Recently, in neurology an emerging new subgroup of autoimmune encephalitis (AE) cases suffering from various neurological syndromes was described in context with the discovery of an emerging list of Central Nervous System (CNS) autoantibodies. Similarly in psychiatry, consensus criteria of autoimmune psychosis (AP) were developed for patients presenting with CNS autoantibodies together with isolated psychiatric symptoms and paraclinical findings of (mild) neuroinflammation, which in fact match also the previously proposed ME criteria. Nevertheless, identifying mild neuroinflammation in vivo in the individual SMD case remains still a major clinical challenge and the possibility that further cases of ME remain still under diagnosed appears an plausible possibility. In this paper a critical review of recent developments and remaining challenges in the research and clinical diagnosis of mild neuroinflammation in SMDs and in general and in transdisciplinary perspective to psycho-neuro-immunology and neuropsychiatry is given. Present nosological classifications of neuroinflammatory disorders are reconsidered with regard to findings from experimental and clinical research. A refined grading list of clinical states including "classical" encephalitis, AE, AP/ME,and newly proposed terms like parainflammation, stress-induced parainflammation and neuroprogression, and their respective relation to neurodegeneration is presented, which may be useful for further research on the possible causative role of mild neuroinflammation in SMDs. Beyond, an etiology-focused subclassification of ME subtypes, like autoimmune ME or infectious ME, appears to be required for differential diagnosis and individualized treatment. The present status of the clinical diagnosis of mild neuroinflammatory mechanisms involved in SMDs is outlined with the example of actual diagnosis and therapy in AP. Ideas for future research to unravel the contribution of mild neuroinflammation in the causality of SMDs and the difficulties expected to come to novel immune modulatory, anti-infectious or anti-inflammatory therapeutic principles in the sense of precision medicine are discussed.

Effects of adjunctive inflammatory modulation on IL-1β in treatment resistant bipolar depression

BACKGROUND

Adjunctive inflammatory modulation improved remission rates in treatment-resistant bipolar depression (TRBDD), but reliable biomarkers must be established to characterize the biosignature of TRBDD and the mechanisms underlying treatment response. In this molecular profiling study, we describe TRBDD and treatment response from the standpoint of interleukin-1 Beta (IL-1β) and KYN/TRP.

METHODS

47 TRBDD patients with moderately severe HAMD-17 scores were randomized to receive either escitalopram (ESC) (10 mg-40 mg daily dose range) + celecoxib (CBX) (200 mg twice daily), or ESC (10 mg-40 mg daily dose range) + placebo (PBO) (twice daily). Plasma cytokine levels were measured in both treatment arms at baseline and week 8, and in a healthy control (HC) group of subjects (N = 43) once. A linear mixed model (LMM) was applied to evaluate whether clinical outcome is related to CBX and changes to biomarkers throughout treatment. A binary logistic regression model was formulated from this series to predict both the primary outcome of treatment response to CBX, and the secondary outcome of diagnosis of TRBDD using age, BMI, gender, and IL-1β at baseline.

RESULTS

Patients receiving ESC + CBX had 4.278 greater odds of responding (p = 0.021) with NNT = 3, and 15.300 times more likely to remit (p < 0.001) with NNT = 2, compared with ESC + PBO patients. Patient BMI (p = 0.003), baseline IL-1β (p = 0.004), and baseline KYN/TRP (p = 0.001) were most predictive of TRBDD diagnosis. By Week 8, responders showed a downtrend in IL-1β compared to non-responders in the ESC + CBX treatment arm. However, there was no statistical difference in the IL-1β or KYN/TRP change after treatment between placebo and ESC + CBX group responders/non-responders (p = 0.239, and p = 0.146, respectively). While baseline IL-1β was elevated in TRBDD compared to HC (p < 0.001), there was no difference in IL-1β between treatment responders at Week 8 compared to HC (p = 0.067).

CONCLUSIONS

Elevated IL-1β and low KYN/TRP at baseline are components of the TRBDD molecular signature. CBX but not baseline IL-1β or KYN/TRP predict treatment response. Change in IL-1β and KYN/TRP did not predict treatment response.