Bio-Social Pathways to Poor Mental Health in The UK Population: Using Blood Samples to Index Neurobiological Factors

Poor mental health results from a complex interplay between genetic and environmental factors across the life course, and can be triggered by stressful life events (SLEs). A comprehensive understanding of these interactions could help identify risk and protective factors. Our ability to remain resilient may be influenced by the gene-environment interaction (GxE) which takes place during brain development and maturation in childhood and adolescence. Furthermore, some epigenetic and proteomic biomarkers measured in the blood may hold clues as to how resilient we are at a given moment, by their ability to measure neurobiological factors. This thesis will integrate genetic, epigenetic and proteomic biomarkers, along with SLEs, to understand how these interact on the pathway to poor mental health and resilience.

The thesis will generate three research papers. The first two papers will assess the face validity of genetic, epigenetic and proteomic biomarkers by their association with mental health symptoms, and the third will integrate significant biomarkers into a more comprehensive longitudinal model which incorporates SLEs and protective and risk factors.

Paper 1: A range of GxE will be modelled in relation to mental health outcomes. For "E", three early life exposures will be used: socioeconomic position (maternal education and father's occupation) and family disruption (intact family, parent moved out, or parent died). For "G", 28x polygenic indices which proxy structural, functional and molecular brain measurements will be generated: 6x subcortical brain regional volumes which are genetically correlated with depressive symptoms, bipolar disorder and/or neuroticism, 19x functional connectivity traits which are genetically correlated with schizophrenia, bipolar disorder, major depressive disorder and/or a cross-disorder trait, and 3x based on gene expression studies of the glucocorticoid receptor (NR3C1, a key stress response protein) in human brain tissue. These GxEs represent neurodevelopmental processes which take place during childhood and adolescence. The primary outcomes will be binary measures based on exceeding established thresholds for GHQ-12 or SF12-MCS.

Paper 2: DNA methylation (DNAm) data and proteomic data will be used to derive a range of biomarkers: a) DNAm biomarkers of five well-studied genes related to psychosocial stress: two stress response proteins NR3C1 and FKBP5, serotonin transporter (SLC6A4), oxytocin receptor (OXTR), and brain-derived neurotrophic factor (BDNF), and b) two proteomic biomarkers: a post-traumatic stress disorder (PTSD) risk score, and a hippocampal volume score. These biomarkers will be tested for prospective associations with the aforementioned mental health outcomes, and for associations with any significant GxE interacting factors from the first paper. These analyses could suggest that the DNAm and proteomic biomarkers act as mediators between neurodevelopmental factors and mental health outcomes, and may indicate their utility as measures of stress exposure, or as risk biomarkers.

Paper 3: Path modelling will incorporate mental health outcomes with significant early life exposures and biomarkers (genetic, epigenetic and proteomic) identified in the first two papers, longitudinal measures of SLEs, and risk and protective factors, which may include income, social support, chronic stressors (work quality, neighbourhood-level factors), exercise, education and prosocial behaviour. By modelling these pathways, this paper aims to aid our understanding of resilience and vulnerability to poor mental health, including genetic factors, and factors which may be modifiable at the policy level and at the individual level. It also aims to underscore the importance of a range of neurobiological factors in poor mental health, and to demonstrate their measurability in peripheral blood.