| Application: | 12505, Dissecting the genetic basis of relationships between early-life and later-life events |
| Title: | Association Between Population Density and Genetic Risk for Schizophrenia |
| Size: | 90.7 MB |
| Archived: | 11 Mar 2021 |
| Stability: | Complete |
| Personal: | Contains individual-level data |
Return 3201
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Notes
We showed that the genetic risk for schizophrenia was not randomly distributed across the UK (England, Wales and Scotland) and in particular that risk alleles were more common in urban/densely populated areas, consistent with the reporter higher rates of schizophrenia observed in urban area. We identified a handful of genetic variants associated with living in a populated environment that do not allow do predict much at an individual level. We found that the genetic risk for schizophrenia likely causes people to live in more densely populated area, though it does not preclude anything about the reverse relationship (which we could not test). Our work raises important questions about the selection of certain (individuals with) risk alleles by the urban environment, or on the contrary about the possible causal effect of city living on psychiatric risk. Note that those hypotheses are not mutually exclusive.Application 12505
Dissecting the genetic basis of relationships between early-life and later-life events
Differences among individuals in distinct changes in their physiology as they age lead to differences in their susceptibility to negative later-life outcomes, and ultimately to differences in lifespan. This proposal aims to test whether genetic differences among individuals influence changes in cognition and physiological function in later life, to identify the genomic regions and biochemical pathways associated with these changes, and to test for genetic associations between early-life reproduction and later-life outcomes. This is crucial to understanding and predicting transitions across different human life stages. Understanding the genetic basis of relationships between early-life phenotypes, reproductive events, and later-life outcomes is of considerable research and public health interest. This proposal will identify new genetic relationships among physiological and cognitive functions, identify genomic regions of age-specific effect, estimate genetic relationships among life stages, and test the effects of genetic homozygosity in the genome in humans across life. It will lead to a better understanding of the genetic factors and biochemical pathways underlying cognitive and physiological decline in people as they age. Establishing robust genetic links between early and later-life health outcomes is challenging as (i) it usually requires studying people across their lives, and, when using families, (ii) relationships are confounded by other factors, such as shared environment between relatives. A novel design for studying the genetics of ageing will be used, so that even when different traits are measured on different individuals, the genetic basis of changes across life can be studied unbiased of shared environment. This enables an assessment of the genomic basis of multiple later-life phenotypes across different ages, testing theories for the genetics of ageing. For sufficient power to accurately estimate genetic relationships between characters, we require access to the full cohort. Even though individuals in the UKBiobank sample are measured across different ages, we can utilize the estimated genetic relationships among them to ask whether the genetic basis of characters is consistent across later life. We can then assess whether variation in genetic effects across life alters genetic relationships among characters throughout life (i.e., do the impacts of early-life on cognitive or physiological function only become apparent in individuals over 65). This requires data on all individuals recorded across all ages.
| Lead investigator: | Professor Peter Visscher |
| Lead institution: | University of Queensland |
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1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 3202 | Association Between Population Density and Genetic Risk for Schizophrenia | Colodro-Conde L et al. | 2018 | JAMA Psychiatry |
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