Specific immune-inflammatory profiles and neurocognitive deficits predict illness trajectories in people with type 2 diabetes mellitus or psychiatric disorders
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Bibliographic record
Abstract
Psychiatric disorders and type 2 diabetes mellitus (T2DM) are chronic conditions that are often comorbid with each other. Neurocognitive and functional impairments are associated with numerous clinical changes during the course of illness. Immune-inflammatory dysfunction is emerging as a critical factor in the progression of these disorders. This study aimed to identify neurocognitive deficits and immune-inflammatory biomarkers that are suitable for signaling different illness trajectories from transdiagnostic and longitudinal perspectives. Clinical status, neurocognitive and functional performance, and peripheral blood biomarkers of immune-inflammation were assessed twice a year in 165 individuals, including 30 with schizophrenia (SZ), 42 with bipolar disorder (BD), 35 with major depressive disorder (MDD), 30 with T2DM, and 28 healthy controls (HCs). Participants with chronic illness (n = 137) were stratified into quartiles, taking their years of illness duration at baseline as a reference into categories of short illness duration (SD; n = 37), middle illness duration (MD; n = 36), long illness duration (LD; n = 32), and very long illness duration (VLD; n = 32). The illness duration was used to measure the illness trajectory, and the exposure of interest was clinical progression, calculated as the difference between clinical severity at baseline (T1) and after 1 year (T2). Neurocognitive impairment was more significant in the VLD group than in the other groups, with small–moderate effect sizes (F = 2.9 to 9.3; p < 0.05−0.0001; η 2 p = 0.06−0.24). Moreover, the HC group showed significantly higher functional outcomes than the other groups (F = 5.8 to 6.0; p < 0.0001; η 2 p = 0.13−0.16). On the contrary, the HC group showed lower levels of immune-inflammatory markers (white blood cell count, absolute neutrophils, absolute monocytes, absolute basophiles, neutrophils/lymphocyte ratio, and platelets/lymphocyte ratio [PLR]) (F = 2.9 to 6.7; p < 0.05−0.0001; η 2 p = 0.07−0.18). In all groups, significant prospective associations were observed between cognitive function (short-term memory and processing speed), global functional scores, immune-inflammatory biomarkers (monocyte/lymphocyte ratio [MLR] and PLR), and clinical status (p < 0.05). Furthermore, a similar combination of neurocognitive deficits and immune-inflammatory alterations compounded the transdiagnostic model that best discriminated the different illness trajectories (χ 2 = 67.4 to 78.7; p < 0.05−0.01). Neurocognitive dysfunction and systemic inflammation are associated with prolonged illness trajectories in individuals with psychiatric disorders and T2DM. An immune-inflammatory profile and neurocognitive and functional performance may be valuable to differentiate individuals with different illness trajectories. These findings have potential translational utility for early transdiagnostic interventions targeting these groups. • Individuals with very long illness trajectory are characterized by increase of systemic inflammation and overall impairment in neurocognitive performance. • Short-term memory, processing speed, global functional score, monocyte/lymphocyte ratio, platelets/lymphocyte ratio compounded an useful transdiagnostic model for predicting clinical progression across chronic illness groups, regardless of illness duration. • Systemic inflammation is a key common factor in identifying individuals with stable disease trajectories from those with worsening/improving. • Neurocognitive and functional performance is relevant in differentiating individuals with opposing disease trajectories, while its role in differentiating clinical stability from worsening or improvement is less significant.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it