A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons.
BMI GWAS
Dopamine
Euclidean hot spots
Metabolic syndrome
Neurons
Obesity
Schizophrenia
Schizophrenia GWAS
Shared nuclear territories
Spatial genome
chrom3D
Journal
Genome medicine
ISSN: 1756-994X
Titre abrégé: Genome Med
Pays: England
ID NLM: 101475844
Informations de publication
Date de publication:
19 02 2020
19 02 2020
Historique:
received:
10
05
2019
accepted:
30
01
2020
entrez:
21
2
2020
pubmed:
23
2
2020
medline:
5
1
2021
Statut:
epublish
Résumé
Midbrain dopaminergic neurons (MDN) represent 0.0005% of the brain's neuronal population and mediate cognition, food intake, and metabolism. MDN are also posited to underlay the neurobiological dysfunction of schizophrenia (SCZ), a severe neuropsychiatric disorder that is characterized by psychosis as well as multifactorial medical co-morbidities, including metabolic disease, contributing to markedly increased morbidity and mortality. Paradoxically, however, the genetic risk sequences of psychosis and traits associated with metabolic disease, such as body mass, show very limited overlap. We investigated the genomic interaction of SCZ with medical conditions and traits, including body mass index (BMI), by exploring the MDN's "spatial genome," including chromosomal contact landscapes as a critical layer of cell type-specific epigenomic regulation. Low-input Hi-C protocols were applied to 5-10 × 10 The Hi-C-reconstructed MDN spatial genome revealed 11 "Euclidean hot spots" of clustered chromatin domains harboring risk sequences for SCZ and elevated BMI. Inter- and intra-chromosomal contacts interconnecting SCZ and BMI risk sequences showed massive enrichment for brain-specific expression quantitative trait loci (eQTL), with gene ontologies, regulatory motifs and proteomic interactions related to adipogenesis and lipid regulation, dopaminergic neurogenesis and neuronal connectivity, and reward- and addiction-related pathways. We uncovered shared nuclear topographies of cognitive and metabolic risk variants. More broadly, our PsychENCODE sponsored Hi-C study offers a novel genomic approach for the study of psychiatric and medical co-morbidities constrained by limited overlap of their respective genetic risk architectures on the linear genome.
Sections du résumé
BACKGROUND
Midbrain dopaminergic neurons (MDN) represent 0.0005% of the brain's neuronal population and mediate cognition, food intake, and metabolism. MDN are also posited to underlay the neurobiological dysfunction of schizophrenia (SCZ), a severe neuropsychiatric disorder that is characterized by psychosis as well as multifactorial medical co-morbidities, including metabolic disease, contributing to markedly increased morbidity and mortality. Paradoxically, however, the genetic risk sequences of psychosis and traits associated with metabolic disease, such as body mass, show very limited overlap.
METHODS
We investigated the genomic interaction of SCZ with medical conditions and traits, including body mass index (BMI), by exploring the MDN's "spatial genome," including chromosomal contact landscapes as a critical layer of cell type-specific epigenomic regulation. Low-input Hi-C protocols were applied to 5-10 × 10
RESULTS
The Hi-C-reconstructed MDN spatial genome revealed 11 "Euclidean hot spots" of clustered chromatin domains harboring risk sequences for SCZ and elevated BMI. Inter- and intra-chromosomal contacts interconnecting SCZ and BMI risk sequences showed massive enrichment for brain-specific expression quantitative trait loci (eQTL), with gene ontologies, regulatory motifs and proteomic interactions related to adipogenesis and lipid regulation, dopaminergic neurogenesis and neuronal connectivity, and reward- and addiction-related pathways.
CONCLUSIONS
We uncovered shared nuclear topographies of cognitive and metabolic risk variants. More broadly, our PsychENCODE sponsored Hi-C study offers a novel genomic approach for the study of psychiatric and medical co-morbidities constrained by limited overlap of their respective genetic risk architectures on the linear genome.
Identifiants
pubmed: 32075678
doi: 10.1186/s13073-020-0715-x
pii: 10.1186/s13073-020-0715-x
pmc: PMC7031924
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
19Subventions
Organisme : National Institute of Health (NIH)
ID : R01MH106056
Pays : International
Organisme : NIMH NIH HHS
ID : R01 MH106056
Pays : United States
Organisme : NIDA NIH HHS
ID : RF1 DA048810
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA047880
Pays : United States
Organisme : National Institute of Health (NIH)
ID : U01MH116442
Pays : International
Organisme : NIH HHS
ID : S10 OD018522
Pays : United States
Organisme : NIH HHS
ID : S10 OD026880
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH117790
Pays : United States
Organisme : NIDA NIH HHS
ID : U01 DA048279
Pays : United States
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