TSPO PET BRAIN INFLAMMATION IMAGING: A TRANSDIAGNOSTIC SYSTEMATIC REVIEW AND META-ANALYSIS OF 156 CASE-CONTROL STUDIES
Bibliographic record
Abstract
Abstract Introduction The 18-kDa translocator protein (TSPO) is increasingly recognized as a molecular target for PET imaging of inflammatory responses in various CNS disorders, but its usefulness appears to vary greatly across disorders, disease stages, and applied quantification methods. To advance TSPO PET as a potential biomarker to evaluate brain inflammation and anti-inflammatory therapies, a better understanding of its applicability across disorders is needed. We conducted a transdiagnostic systematic review and meta-analysis of all in vivo human TSPO PET imaging case-control studies in the CNS. Specifically, we investigated the direction, strength, and heterogeneity associated with the TSPO PET signal across disorders in pre-specified brain regions, and explored the demographic and methodological sources of heterogeneity. Methods We performed a systematic search for studies reporting in vivo human case-control TSPO PET differences. A random-effects meta-analysis was applied to estimate case-control standardized mean differences (SMD) of the TSPO PET signal in the lobar/whole-brain cortical grey matter (cGM), thalamus, and cortico-limbic circuitry between different illness categories. Heterogeneity was evaluated with the I² statistic and explored using subgroup and meta-regression analyses for radioligand generation, PET quantification method, age, sex, and publication year. Results 156 individual case-control studies were included in the systematic review, incorporating data for 2381 healthy controls and 2626 patients. 139 studies documented meta-analysable data and were grouped into 11 illness categories. Across all the illness categories, we observed a significantly higher TSPO PET signal in cases compared to controls for the cGM (n=121 studies, SMD=0.358, PFDR<0.001, I²=68%), with a significant difference between the illness categories (P=0.004). cGM increases were only significant for Alzheimer’ s disease and other neurodegenerative disorders. Cortico-limbic increases (n=97 studies, SMD=0.541, P<0.001, I²=67%) were most prominent for Alzheimer’ s dementia, mild cognitive impairment, other neurodegenerative disorders, mood disorders and multiple sclerosis. Thalamic involvement (n=79 studies, SMD=0.393, P<0.001, I²=71%) was observed for Alzheimer’ s disease, other neurodegenerative disorders, multiple sclerosis, and chronic pain and functional disorders (all PFDR<0.05). Main outcomes for immunological disorders, viral infections, substance use disorders, schizophrenia and traumatic brain injury were not significant. We identified multiple sources of between-study variance to the TSPO PET signal including a strong transdiagnostic effect of the quantification method (explaining 25% of between-study variance; VT-based SMD=0.000 versus reference tissue-based studies SMD=0.630; F=20.49, df=1;103, P<0.001), patient age (9% of variance), and radioligand generation (5% of variance). Conclusion We observed robust increases in the TSPO signal for specific types of disorders, which were widespread or focal depending on illness category. We also found a large and transdiagnostic positive shift of the effect estimates of reference tissue-based compared to VT-based studies. Our results can support future studies to optimize experimental design and power calculations, by taking into account the type of disorder, brain region-of-interest, radioligand, and quantification method. References De Picker LJ, Morrens M, Branchi I, Haarman BCM, Terada T, Kang MS, Boche D, Tremblay ME, Leroy C, Bottlaender M, Ottoy J. TSPO PET brain inflammation imaging: A transdiagnostic systematic review and meta-analysis of 156 case-control studies. Brain Behav Immun. 2023 Oct;113:415-431. doi: 10.1016/j.bbi.2023.07.023. Epub 2023 Aug 3. PMID: 37543251.
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How this classification was reachedexpand
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".