B4767 - Enhancing Genetic Insights Through Longitudinal Analysis and Novel Statistical Tools - 06/12/2024

B number: 
B4767
Principal applicant name: 
Ole A. Andreassen | Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo, Oslo, Norway (Norway)
Co-applicants: 
Jakub Kopal
Title of project: 
Enhancing Genetic Insights Through Longitudinal Analysis and Novel Statistical Tools
Proposal summary: 

Complex human genetic disorders are major contributors to global morbidity and mortality. Understanding their underlying pathophysiology is essential for advancing treatment and prevention. These disorders have heritability estimates between 40-80% and are considered polygenic, involving the interplay of multiple genes alongside environmental influences. This complexity complicates efforts to understand causal factors and disease mechanisms, predict individual susceptibility and uncover the molecular mechanisms involved, both of which are critical to improving treatment options. Genome-wide association studies (GWAS) have uncovered numerous trait-associated single nucleotide polymorphisms (SNPs) in diverse complex phenotypes. However, existing methods largely overlook the dynamic interactions between genetic and environmental factors over time, limiting our ability to fully understand and predict the progression of complex human disorders. This proposal aims to utilize ALSPAC data to investigate the genetic architecture of human traits, with a focus on the complex interplay among genetic factors and environmental influences, in mental disorders and co-morbid conditions. Leveraging ALSPAC’s rich longitudinal data, we will analyze SNPs linked to both baseline and longitudinal phenotypes and their changes over time, advancing our understanding of the dynamic genetic and environmental contributions to the development and progression of these traits.

Impact of research: 
The likely impact of this research will be significant in advancing our understanding of causal factors and disease mechanisms, as well as genetic risk prediction and understanding the progression of complex human disorders. This will provide valuable insights into the dynamic nature of genetic and environmental contributions to mental health and other complex traits, leading to earlier and more tailored interventions. Clinically, this work could pave the way for implementing age-specific risk assessments, allowing healthcare providers to make more informed, personalized decisions in managing mental health and related co-morbid conditions.
Date proposal received: 
Thursday, 5 December, 2024
Date proposal approved: 
Thursday, 5 December, 2024
Keywords: 
Genetics, Addiction - e.g. alcohol, illicit drugs, smoking, gambling, etc., Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Developmental disorders - autism, Cognitive impairment, Hypertension, Mental health, Computer simulations/modelling/algorithms, Gene mapping, GWAS, Medical imaging, Metabolomics, Statistical methods, Biomarkers - e.g. cotinine, fatty acids, haemoglobin, etc., Cohort studies - attrition, bias, participant engagement, ethics, Environment - enviromental exposure, pollution, Genetics, Genome wide association study, Methods - e.g. cross cohort analysis, data mining, mendelian randomisation, etc.