Smoking History and Higher Pack Years Predict Brain Atrophy in 9646 Healthy Individuals
Bibliographic record
Abstract
Abstract Background Smoking is a risk factor for both Alzheimer and vascular dementia. Understanding this risk requires an investigation of how smoking influences brain volume loss on MRI, a biomarker for neurodegeneration. Method In total, 9646 healthy participants from 4 sites were scanned on 1.5T MR with a whole‐body MR imaging protocol. Core whole body sequences included whole body coronal T1, STIR from vertex to feet, whole‐body axial DWI from vertex to proximal‐thighs and axial T2 TSE without fat suppression from skull base to pelvis. Brain sequences were T1 MPRAGE and 2D FLAIR. Deep learning volumetric software, FastSurfer, trained on over 134 participants age 27‐66, segmented 96 brain volumes. Smokers versus non‐smokers were compared by gray and white matter volumes normalized to total intracranial volume using a two tailed t‐test. Partial correlation analysis was done between pack years and brain volumes, controlling for age, sex, and total intracranial volume (TIV). The Benjamini Hochberg False Discovery Rate of 5% accounted for multiple comparisons. Result Overall, the sample had an average age of 52.9±13.1 years with 3123 individuals (32.3%) self‐reporting a history of smoking with 3.72±10.08 pack years. The remaining 6523 persons (67.7%) were non‐smokers. Participants who smoked were older than non‐smokers (p = 0.024) and 51.55% were men versus 52.8% in the non‐smoker group (p = .218). Individuals with a history of smoking had lower normalized gray and white matter volumes compared to non‐smokers (t = 8.95, p = 4.39e‐19). Adjusting for age, sex, and TIV co‐variates and multiple comparisons, higher pack years of smoking predicted brain volume loss in: total gray matter volume (Partial R = ‐0.06, p = 2.19e‐8), total white matter volume (Partial R = ‐0.06, p = 4.26e‐9), hippocampus (Partial R = ‐0.05, p = 6.26e‐6), frontal cortex (Partial R = ‐0.06, p = 1.34e‐10), temporal lobes (Partial R = ‐0.06, p = 3.24e‐8), parietal lobe (Partial R = ‐0.04, p = 0.0008), orbital frontal cortex (Partial R = ‐0.05, p = 2.19e‐8), posterior cingulate gyrus (Partial R = ‐0.05, p = 2.97e‐7). Conclusion Both smoking history and pack years are related to lower whole brain and regional volumes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".