Wellbeing, a key aspect of mental health, is defined as a state of positive subjective experience and optimal psychological functioning. This thesis presents a series of studies devised to comprehensively explore phenotypic, genetic, and neural correlates of wellbeing. The first study (Chapter 2) aimed to compare the heritability and stability of different wellbeing measures in the TWIN-E dataset (N~1600) to discern the most suitable approach for measuring wellbeing for subsequent gene discovery efforts. This twin-based study concluded that multi-item measures of wellbeing such as the COMPAS-W scale, were more heritable and stable than single-item measures. Wellbeing-associated variants were identified via genome-wide association studies (GWAS) and highlighted the need for larger sample size. The subsequent studies were conducted using population-scale data from the UK Biobank comprising ~130,000 participants with phenotypic and genetic data. Thus, in Chapter 3, I constructed a multi-item “wellbeing index” measure using UK Biobank data to investigate its relationship phenotypically and genetically (using GWAS, polygenic scores and LD score regression) with negative mental health indicators (e.g., neuroticism and loneliness), childhood maltreatment and psychiatric illness. I confirmed that SNP-heritability of wellbeing index was higher than both single-item measures and estimates previously reported (SNP-h2 = 8.6%). Moreover, I provide an overview of phenotypic and genetic correlations between wellbeing index and negative mental health indicators. In addition, childhood maltreatment and psychiatric illnesses were associated with reduced wellbeing, with evidence that genetic factors may influence their correlations. In Chapter 4, I investigated the genetic and phenotypic associations between wellbeing index and brain structure, using magnetic resonance image-derived phenotypes from the UK Biobank. This study found associations between wellbeing and volumes of brainstem, cerebellum and subcortical regions, and structural morphology of various cortical regions. Thus, wellbeing is associated with complex structural variations, each with a small effect. Together, this thesis explores the multifaceted nature of wellbeing, elucidating its phenotypic and genetic relationships with related phenotypes, childhood maltreatment, and psychiatric outcomes, and provides novel insights into the associations between wellbeing, its genetic signatures and brain structure.