Open Access
Open access
Scientific Reports, volume 13, issue 1, publication number 2139

Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia

Kopylov Arthur T. 1
, 
Stepanov Alexander A. 1
, 
Butkova Tatiana V 1
, 
Malsagova Kristina A 1
, 
Zakharova Natalia V. 2
, 
Kostyuk Georgy P 2
, 
Elmuratov Artem U 1, 3
, 
Kaysheva Anna L. 1
1
 
2
 
Alexeev N.A. 1St Clinics for Mental Health, Moscow, Russian Federation | 
3
 
Center for Medical Genetics “Genotek”, Moscow, Russian Federation | 
Publication type: Journal Article
Publication date: 2023-02-06
Quartile SCImago
Q1
Quartile WOS
Q2
Impact factor: 4.6
ISSN: 20452322
Multidisciplinary
Abstract

Despite of multiple systematic studies of schizophrenia based on proteomics, metabolomics, and genome-wide significant loci, reconstruction of underlying mechanism is still a challenging task. Combination of the advanced data for quantitative proteomics, metabolomics, and genome-wide association study (GWAS) can enhance the current fundamental knowledge about molecular pathogenesis of schizophrenia. In this study, we utilized quantitative proteomic and metabolomic assay, and high throughput genotyping for the GWAS study. We identified 20 differently expressed proteins that were validated on an independent cohort of patients with schizophrenia, including ALS, A1AG1, PEDF, VTDB, CERU, APOB, APOH, FASN, GPX3, etc. and almost half of them are new for schizophrenia. The metabolomic survey revealed 18 group-specific compounds, most of which were the part of transformation of tyrosine and steroids with the prevalence to androgens (androsterone sulfate, thyroliberin, thyroxine, dihydrotestosterone, androstenedione, cholesterol sulfate, metanephrine, dopaquinone, etc.). The GWAS assay mostly failed to reveal significantly associated loci therefore 52 loci with the smoothened p < 10−5 were fractionally integrated into proteome-metabolome data. We integrated three omics layers and powered them by the quantitative analysis to propose a map of molecular events associated with schizophrenia psychopathology. The resulting interplay between different molecular layers emphasizes a strict implication of lipids transport, oxidative stress, imbalance in steroidogenesis and associated impartments of thyroid hormones as key interconnected nodes essential for understanding of how the regulation of distinct metabolic axis is achieved and what happens in the conditioned proteome and metabolome to produce a schizophrenia-specific pattern.

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Citations by journals

1
Critical Reviews in Clinical Laboratory Sciences
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Critical Reviews in Clinical Laboratory Sciences
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Taylor & Francis
Taylor & Francis, 1, 33.33%
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1 publication, 33.33%
Elsevier
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Elsevier
1 publication, 33.33%
Springer Nature
Springer Nature, 1, 33.33%
Springer Nature
1 publication, 33.33%
1
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Kopylov A. T. et al. Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia // Scientific Reports. 2023. Vol. 13. No. 1. 2139
GOST all authors (up to 50) Copy
Kopylov A. T., Stepanov A. A., Butkova T. V., Malsagova K. A., Zakharova N. V., Kostyuk G. P., Elmuratov A. U., Kaysheva A. L. Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia // Scientific Reports. 2023. Vol. 13. No. 1. 2139
RIS |
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RIS Copy
TY - JOUR
DO - 10.1038/s41598-023-29117-7
UR - https://doi.org/10.1038%2Fs41598-023-29117-7
TI - Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia
T2 - Scientific Reports
AU - Kopylov, Arthur T.
AU - Stepanov, Alexander A.
AU - Butkova, Tatiana V
AU - Malsagova, Kristina A
AU - Zakharova, Natalia V.
AU - Kostyuk, Georgy P
AU - Elmuratov, Artem U
AU - Kaysheva, Anna L.
PY - 2023
DA - 2023/02/06 00:00:00
PB - Springer Nature
IS - 1
VL - 13
SN - 2045-2322
ER -
BibTex
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BibTex Copy
@article{2023_Kopylov,
author = {Arthur T. Kopylov and Alexander A. Stepanov and Tatiana V Butkova and Kristina A Malsagova and Natalia V. Zakharova and Georgy P Kostyuk and Artem U Elmuratov and Anna L. Kaysheva},
title = {Consolidation of metabolomic, proteomic, and GWAS data in connective model of schizophrenia},
journal = {Scientific Reports},
year = {2023},
volume = {13},
publisher = {Springer Nature},
month = {feb},
url = {https://doi.org/10.1038%2Fs41598-023-29117-7},
number = {1},
doi = {10.1038/s41598-023-29117-7}
}
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