(2019-2.1.7-ERA-NET-2020-00005) Támogató: Nemzeti Kutatási, Fejlesztési és Innovációs
Hivatal
ERA PerMed(ERAPERMED2019-108)
(2017-1.2.1-NKP-2017-00002.)
(National Brain Programme 3.0(NAP2022-I-4/2022))
MILAB(RRF-2.3.1-21-2022-00004) Támogató: NKFIH
(ÚNKP-22-4-II-SE-1)
(ÚNKP-23-4-II-SE-2)
Most current approaches to establish subgroups of depressed patients for precision
medicine aim to rely on biomarkers that require highly specialized assessment. Our
present aim was to stratify participants of the UK Biobank cohort based on three readily
measurable common independent risk factors, and to investigate depression genomics
in each group to discover common and separate biological etiology. Two-step cluster
analysis was run separately in males ( n = 149,879) and females ( n = 174,572),
with neuroticism (a tendency to experience negative emotions), body fat percentage,
and years spent in education as input variables. Genome-wide association analyses
were implemented within each of the resulting clusters, for the lifetime occurrence
of either a depressive episode or recurrent depressive disorder as the outcome. Variant-based,
gene-based, gene set-based, and tissue-specific gene expression test were applied.
Phenotypically distinct clusters with high genetic intercorrelations in depression
genomics were found. A two-cluster solution was the best model in each sex with some
differences including the less important role of neuroticism in males. In females,
in case of a protective pattern of low neuroticism, low body fat percentage, and high
level of education, depression was associated with pathways related to olfactory function.
While also in females but in a risk pattern of high neuroticism, high body fat percentage,
and less years spent in education, depression showed association with complement system
genes. Our results, on one hand, indicate that alteration of olfactory pathways, that
can be paralleled to the well-known rodent depression models of olfactory bulbectomy,
might be a novel target towards precision psychiatry in females with less other risk
factors for depression. On the other hand, our results in multi-risk females may provide
a special case of immunometabolic depression.
