Characteristics of inflammation-related depression
Bibliographic record
Abstract
Background: Depression is a serious mental disorder with a lifetime prevalence of about 10-20%. As is typically the case with chronic illnesses, depression is a multifactorial condition, with influences from both genetic and environmental factors. One factor of increasing interest in recent literature is that of systemic inflammation. There is consistent evidence for increased peripheral blood and cerebrospinal fluid concentrations of C-reactive protein (CRP) and proinflammatory cytokines, like interleukin-6 (IL-6), in patients with acute depression, compared to healthy controls [1,2]. Evidence from longitudinal and Mendelian randomisation studies suggest that these associations are likely to be causal, and not solely attributable to reverse causality or residual confounding. For instance, elevated concentrations of serum IL-6 in childhood was associated with an increased risk of depression in early-adulthood in a dose-response manner [3]. Genetic variants regulating levels/activity of IL-6 are associated risk for depression [4]. Meta-analysis suggests a quarter of depressed patients have evidence of elevated CRP [5]. Inflammation-related depression could be a novel phenotype potentially amenable to immunotherapy currently subject to a number of randomised controlled trials (RCTs). To understand the characteristics of inflammation-related depression we have conducted a study of sociodemographic, clinical and other factors in depressed patients with and without evidence of low-grade inflammation. Methods: Case-control design involving 84 participants meeting the International Classification of Diseases 10th revision (ICD-10) diagnosis of depression recruited through NHS services and self-referral in the East of England. Groups were defined according to serum high-sensitivity CRP (hs-CRP) levels: (1) those with evidence of low-grade inflammation, i.e. “inflamed depression” (hs-CRP≥3mg/L), and (2) those without evidence of low-grade inflammation, i.e. “non-inflamed depression” (hs-CRP<3mg/L). All participants provided blood samples and completed questionnaires for sociodemographic and lifestyle information, clinical history, neuropsychiatric symptoms and quality of life. Psychiatric questionnaires included Beck Depression Inventory-II (BDI-II), Clinical Interview Schedule-Revised (CIS-R), Patient Health Questionnaire-9 (PHQ-9), Snaith-Hamilton Pleasure Scale (SHAPS), State-Trait Anxiety Inventory (STAI), Multidimensional Fatigue Inventory (MFI), Perceived Stress Scale (PSS), Self-Compassion Scale (SCS), Visual Analogue Scale for Subjective Wellbeing (VAS-W) and the 3-level version of the EuroQol 5-Dimensional (EQ-5D-3L) questionnaire. Mean values for continuous variables were compared between groups using independent samples t-tests, whilst for categorical variables, proportion of participants between groups were compared using Chi-squared tests. Results: Compared with non-inflamed depression (n=54), inflamed depression (n=30) was associated with higher BMI (P<0.01), waist circumference (P<0.01) and diastolic blood pressure (P<0.01). The inflamed group had higher depression severity, as reflected by higher total scores on the BDI-II (P<0.01). This group also had higher somatic symptoms (P<0.01), increased fatigue (P<0.01), and poorer quality of life (P<0.01). The inflamed group also presented with higher total scores on the CIS-R scale, higher PHQ-9 total score, increased state anxiety, perceived stress, and lower frequency of alcohol use, but these were not statistically significant. Conclusions: Inflammation-related depression is associated with a number of characteristics including increased cardio-metabolic risk factors, depression severity, somatic symptoms particularly fatigue, and poor quality of life. These findings could inform patient selection in future RCTs. Future research should focus on replicating these results in larger samples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".