| Title: | Comorbidities between addiction and mental disorders ? association of genetics, biomarkers and environment (e.g. lifestyle) with mental health and cognitive function |
| Lead Institution: | Uppsala University |
| Principal investigator: | Professor Helgi Schioth |
Application 30172
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About
We aim to investigate interactions between genetics and environmental factors e.g. lifestyle in relation to mental health and addiction. We will examine whether environmental and other risk factors (psychiatric comorbidities) influence addiction besides having overlapping genetic risk factors crucial for prevention and treatment strategies, study genetic variants with known associations to addictions and psychiatric disorders and perform genome-wide exploratory analyses for novel variants. We will investigate the association and modulating effects of genetic variation between mental health and addiction, including pharmacogenetics, known and novel biomarkers, SNPs role in drug effects and cognitive function to understand susceptibility to addiction. Addictions and drug abuse are severe common psychiatric disorders, among the leading causes of morbidity and preventable mortality, and often linked with other psychiatric diseases as consequences or potential cause of addictive behavior (Agrawal, 2012). We will evaluate the impact of genetic and environmental risk factors on comorbidities of addiction and common psychiatric disorders. Better understanding how neural circuitry, genetics and environmental factors interact in the etiology of addiction and other psychiatric diseases offer better treatment strategies. Novel insights into molecular biology, genetic, pharmacogenetics and epigenetic mechanisms underlying these associations will improve public-health related decisions for health professionals. Statistical models will be utilized to analyze associations between genotype, cognitive function and mental health while controlling for demographics such as age, gender, medications, personality traits, physical activity, etc. as well as comorbidities. To examine causal effects of these genes, Mendelian randomization will be applied. Novel genetic variants will be derived from two-thirds of the cohort and validated in the remaining third. Linear models will be used to study the association between environmental factors, cognitive function and addictive behavior. Modifying effects of biomarkers on cognitive function and mental health will be assessed by incorporating it through generalized linear models. To maximize power, the full cohort will be included in the project. We would also like to include the new data from additional participants (still to be released).4 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 8978 | A deep learning model for brain age prediction using minimally preprocessed T1w images as input | Caroline Dartora (+15) | 2024 | Frontiers in Aging Neuroscience |
| 9288 | Higher fresh fruit intake relates to larger grey matter volumes in areas involved in dementia and depression: A UK Biobank study | Santino Gaudio (+5) | 2023 | NeuroImage |
| 10258 | The Effects of Statins on Cognitive Performance Are Mediated by Low-Density Lipoprotein, C-Reactive Protein, and Blood Glucose Concentrations | Mélissa Gentreau (+6) | 2023 | The Journals of Gerontology Series A |
| 9729 | Well-being spectrum traits are associated with polygenic scores for autism | Salahuddin Mohammad (+5) | 2023 | Autism Research |
Enabling scientific discoveries that improve human health