Projects per year
Abstract / Description of output
Background
General cognitive function predicts psychiatric illness across the life course. This study examines the role of pleiotropy in explaining the link between cognitive function and psychiatric disorder.
Methods
We use two large genome-wide association study (GWAS) data sets on cognitive function. One from older age, n=53,949, and one from childhood, n=12,441. We also GWAS data on educational attainment, n = 95,427, to examine the validity of its use as a proxy phenotype for cognitive function. Using a new method, linkage disequilibrium (LD) regression, we derive genetic correlations, free from the confounding of clinical state between psychiatric illness and cognitive function.
Results
We find a genetic correlation of 0.711, (p=2.26e-12) across the life course for general cognitive function. We also show a positive genetic correlation between Autism Spectrum Disorder (ASD) and cognitive function in childhood (rg = 0.360, p = 0.0009), for educational attainment (rg = 0.322, p=1.37e-5), but not in older age. In schizophrenia we find a negative genetic correlation between older age cognitive function (rg =-0.231, p=3.81e-12) but not in childhood or for educational attainment. For Alzheimer’s disease we find negative genetic correlations with childhood cognitive function (rg = -0.341, p = 0.001), educational attainment (rg = -0.324, p=1.15e-5), and with older age cognitive function (rg = -0.324, p=1.78e-5).
Conclusions
The pleiotropy exhibited between cognitive function and psychiatric disorders was changes across the life course. These age-dependent associations might explain why negative selection has not removed variants causally associated with ASD or schizophrenia.
General cognitive function predicts psychiatric illness across the life course. This study examines the role of pleiotropy in explaining the link between cognitive function and psychiatric disorder.
Methods
We use two large genome-wide association study (GWAS) data sets on cognitive function. One from older age, n=53,949, and one from childhood, n=12,441. We also GWAS data on educational attainment, n = 95,427, to examine the validity of its use as a proxy phenotype for cognitive function. Using a new method, linkage disequilibrium (LD) regression, we derive genetic correlations, free from the confounding of clinical state between psychiatric illness and cognitive function.
Results
We find a genetic correlation of 0.711, (p=2.26e-12) across the life course for general cognitive function. We also show a positive genetic correlation between Autism Spectrum Disorder (ASD) and cognitive function in childhood (rg = 0.360, p = 0.0009), for educational attainment (rg = 0.322, p=1.37e-5), but not in older age. In schizophrenia we find a negative genetic correlation between older age cognitive function (rg =-0.231, p=3.81e-12) but not in childhood or for educational attainment. For Alzheimer’s disease we find negative genetic correlations with childhood cognitive function (rg = -0.341, p = 0.001), educational attainment (rg = -0.324, p=1.15e-5), and with older age cognitive function (rg = -0.324, p=1.78e-5).
Conclusions
The pleiotropy exhibited between cognitive function and psychiatric disorders was changes across the life course. These age-dependent associations might explain why negative selection has not removed variants causally associated with ASD or schizophrenia.
Original language | English |
---|---|
Pages (from-to) | 266-273 |
Journal | Biological Psychiatry |
Volume | 80 |
Issue number | 4 |
Early online date | 4 Sept 2015 |
DOIs | |
Publication status | Published - 15 Aug 2016 |
Fingerprint
Dive into the research topics of 'Age-dependent pleiotropy between general cognitive function and major psychiatric disorders'. Together they form a unique fingerprint.Projects
- 7 Finished
-
Stratifying Resilience and Depression Longitudinally
McIntosh, A., Deary, I., Evans, K., Haley, C. & Porteous, D.
1/01/15 → 30/06/21
Project: Research
-
-
RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.
Deary, I., Gale, C., Holmes, M., Logie, P., Maclullich, A., Porteous, D., Seckl, J., Starr, J., Wardlaw, J. & Okely, J.
1/09/13 → 31/08/19
Project: Research