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Depression is a very prevalent disorder affecting between 2 to 21% of the world population. This thesis extends the knowledge on the biological aspects of depression, aiming to identify and validate markers of genetic, epigenetic, and gene expression origin.

In Study I, the main focus was depression-related gene MAD1L1 that was previously linked to depression by SNPs and frequently mentioned as a stress-related marker. We identified that depression-related SNPs in MAD1L1 affect DNA methylation levels at cg02825527, cg18302629, and cg19624444 that were associated with depressive phenotypes in independent cohorts.

In Study II, we investigated whether GWAS catalog depression SNPs located in Olink-detectable genes could be replicated in a UKBiobank cohort and whether these associations are supported by DNA methylation and transcriptome. We validated eight depression SNPs and found very weak evidence that TNXB may be related to depression.

Study III was based on comparison of different depression -OMIC layers, including genetics, DNA methylation, and transcriptome. We explored how the identified genes from different -OMICs overlap, are functionally related and if they could show patterns in drugs and clinical trials. Only three genes were supported by evidence at all three -OMIC levels and included: FOXP1, VPS41, and AKTIP. Different -OMIC levels showed involvement of multiple systems in depression.

In Study IV, we used the Neuro Exploratory panel (Olink) to identify depression proteomic changes in blood. We took antidepressant intake into the account and validated associations in the independent datasets. We identified several proteins that showed nominally different levels between depression risk groups in the adolescent cohort. Validation of identified markers yielded that only PPP3R1 was also differentially expressed in prefrontal cortex and whole blood in the independent open-access cohorts with matching association directions.

In Study V, we used the entire blood DNA methylation as a depression marker. We investigated stability of DNA-methylation in eight independent datasets with meta-analysis and compared common machine learning and deep learning strategies for the depression detection purposes. We found 1987 CpG sites related to depression in both mega- and meta-analysis at the nominal level. Random forest classifiers achieved the best performance in identifying depression based on DNA methylation data in blood (AUC 0.73 and 0.76) in CV and hold-out tests respectively on the batch-level processed data.

Overall, the thesis supports multiple depression genetic, epigenetic, and expression markers. However, identified individual and systemic depression changes show high variability, which is in agreement with previous studies and observations.

Psychiatric and neurological diseases present substantial challenges in healthcare, affecting millions of individuals worldwide. Conditions such as depression, trigeminal neuralgia (TN), and narcolepsy have a profound impact on the quality of life for both patients and their families. The complex nature of these conditions necessitates the development of innovative diagnostic and treatment strategies. In recent years, the importance of biomarkers in understanding, diagnosing, and managing psychiatric and neurological diseases has emerged as a promising field of research. In the current thesis, five studies were conducted to identify candidate biomarkers in depression, TN, and narcolepsy. Study I validated depression-associated genetic variants in the UK Biobank (UKB) cohort, with transcriptome and DNA methylation analyses in independent datasets. Eight single nucleotide polymorphisms corresponding to six protein-coding genes (TNXB, NCAM1, LTBP3, BTN3A2, DAG1, FHIT) were strongly linked to depression. Study II analyzed 92 proteins in cerebrospinal fluid and serum from TN patients, compared with multiple sclerosis patients and controls. Several proteins, including SFRP1, FKBP5, and TBCB, were elevated in TN, suggesting their relevance in disease mechanisms. Study III examined protein levels in adolescents assessed for depression in the domestic Psychiatric Health in Adolescent Study (PSY cohort) in Sweden, with transcriptome validation in independent cohorts. Key findings highlighted protein and transcriptomic differences, particularly in PPP3R1, implicating the calcineurin pathway and prefrontal cortex in depression. Study IV explored genetic evidence in the UKB to validate the role of 17 proteins from previous studies in TN. Novel associations were identified with C8B (complement system) and MFGE8 (neuroinflammation regulation), highlighting their roles in TN pathology. Finally, Study V assessed protein biomarkers in narcolepsy using Swedish and Finnish cohorts, with transcriptome validation in an independent dataset. The identified candidate proteins were indicative of neural development involving survival, growth, and differentiation (UNC5C, VWC2, GFR-alpha-1, ADAM23), oxidative stress (HAGH), immune response (CLEC10A), and cell cycle regulation (ILKAP). Collectively, these studies identify potential biomarkers across these conditions, offering insights into their underlying mechanisms. The findings expand our understanding of psychiatric and neurological health and may inform future research and therapeutic strategies.