Examining the shared genetic liability between late‐life onset psychosis and major psychiatric, cognitive and personality phenotypes
Bibliographic record
Abstract
BACKGROUND: When assessed in the Mild Behavioral Impairment (MBI) framework, late-life onset psychotic like symptoms (MBI-psychosis) are associated with incident cognitive decline and dementia. One approach to examining the genetic basis of this association, is to use Polygenic Risk Scores (PRS) to determine whether genetic propensity for late-life onset psychosis is shared with other traits. We aimed to elucidate the shared genetic liability between Educational Attainment, Intelligence, Reasoning, Memory, Neuroticism, Alzheimer's Disease, Major Depression, Schizophrenia and Bipolar Disorder and Mild Behavioral Impairment (MBI)-Psychosis in later life. METHOD: A total of 7,307 older adults without dementia were included in the analytical sample. MBI-Psychosis status (present or absent) was determined by the Mild Behavioral Impairment Checklist (MBI-C) rated by participants and study partners (that is 'self' and 'informant' ratings). Each PRS was tested in a logistic regression model with MBI-Psychosis status as the dependent variable, and with age, sex and ancestry as covariates. RESULT: Higher PRS for Major Depression, Schizophrenia and Neuroticism were all associated with an higher odds of MBI-Psychosis. PRS for schizophrenia was only associated with self-reported MBI-psychosis, not informant reported MBI-psychosis (see Figure 1). Higher PRS for Educational Attainment and Intelligence were both associated with lower odds of MBI-Psychosis. In analysis stratified by self-reported education level, the relationship between higher PRS for educational attainment and lower odds of MBI-psychosis was only present in those we left school at 16. CONCLUSION: In early life, psychosis is known to overall with cognitive, psychiatric and personality traits. These data extend this observation to later-life psychosis. The significance of the differences between self and informant reported symptoms are yet to be determined but may be a mix of measurement error and the different respondents having a propensity to report symptoms which reflect different etiologies. We also show that established protective factors against cognitive decline, like educational attainment, in later life may also extend to late life neuropsychiatric syndrome.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".