Correlation between neurotransmitter levels and cognitive function in patients with comorbid Alzheimer's disease and chronic obstructive pulmonary disease
Bibliographic record
Abstract
BackgroundWith the intensification of population aging， the prevalence of Alzheimer's disease （AD） has been increasing， and 10% to 20% of AD patients also suffer from chronic obstructive pulmonary disease （COPD）. Compared to patients with a single disease， those with comorbid AD and COPD show more severe cognitive impairment， reduced quality of life， and a greater disease burden. Both AD and COPD patients exhibit abnormal levels of neurotransmitters， which affect cognitive function. However， the alterations in neurotransmitter levels in patients with comorbid AD and COPD and their association with cognitive function remain unclear.ObjectiveTo analyze the relationship between neurotransmitter levels and cognitive function in patients with AD combined with COPD， and to provide references for improving the cognitive function in this population.MethodsA total of 120 patients who were hospitalized at The Third Hospital of Mianyang from January to September 2024 were divided into three groups： 40 patients meeting the International Classification of Diseases， tenth edition （ICD-10） diagnostic criteria for AD were defined as AD group， 40 patients meeting the diagnostic criteria for COPD according to the Global Initiative for Chronic Obstructive Lung Disease （GOLD） 2023 guidelines were defined as COPD group， another 40 patients meeting the diagnostic criteria for both conditions were defined as AD combined with COPD group. Additionally， 40 healthy individuals undergoing physical examination at the same hospital during the same period were selected as the control group. Encephalofluctuograph was used to detect the levels of γ-aminobutyric acid （GABA）， glutamate （Glu）， norepinephrine （NE）， 5-hydroxytryptamin （5-HT）， acetylcholine （Ach）， and dopamine （DA）. Cognitive function of the subjects was assessed using the Mini-Mental State Examination （MMSE） and the Montreal Cognitive Assessment （MoCA）. Spearman correlation analysis was used to investigate the correlation between neurotransmitter levels and cognitive function in AD combined with COPD patients. Multiple linear regression analysis was adopted to investigate the influencing factors of cognitive function in this population.Results①Significant differences were observed in MMSE and MoCA scores across all four groups （H=126.323， 128.489， P<0.01）. The AD combined with COPD group demonstrated significantly lower MMSE and MoCA scores compared with COPD group， AD group， and control group （P<0.05）. ②Statistically significant differences were found in the levels of GABA， Glu， Ach， NE，and DA among the four groups （H=61.094， 46.665， 135.289， 15.089， 129.636， P<0.01）. Compared with the COPD group， AD group， and control group， the AD combined with COPD group showed significantly lower levels of GABA， Ach， and DA， but higher Glu levels， with all differences being statistically significant （P<0.05）. ③In the AD combined with COPD group， the levels of GABA， Ach， and DA showed positive correlations with MMSE scores （r=0.633， 0.876， 0.580， P<0.05）， while Glu levels were negatively correlated with MMSE scores （r=-0.377， P=0.013）. ④The levels of Ach （B=0.253， 95% CI： 0.153–0.352）， GABA （B=0.137， 95% CI： 0.013–0.261）， age （B=-0.212， 95% CI： -0.356–-0.069） and education duration （B=-0.367， 95% CI： -0.608–-0.126） were the influencing factors of cognitive function in patients with AD combined with COPD.ConclusionCompared with the COPD group， AD group， and control group， patients with AD combined with COPD exhibited more severe cognitive impairment， along with lower levels of GABA， ACh， and DA， but higher Glu levels. Ach and GABA levels are potential influencing factors of cognitive function in AD combined with COPD patients.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".