Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia
Schizophrenia (SCZ) is a devastating genetic mental disorder. Identification of the SCZ risk genes in brains is helpful to understand this disease. Thus, we first used the minimum Redundancy-Maximum Relevance (mRMR) approach to integrate the genome-wide sequence analysis results on SCZ and the expression quantitative trait locus (eQTL) data from ten brain tissues to identify the genes related to SCZ. Second, we adopted the variance inflation factor regression algorithm to identify their interacting genes in brains. Third, using multiple analysis methods, we explored and validated their roles. By means of the aforementioned procedures, we have found that (1) the cerebellum may play a crucial role in the pathogenesis of SCZ and (2) ITIH4 may be utilized as a clinical biomarker for the diagnosis of SCZ. These interesting findings may stimulate novel strategy for developing new drugs against SCZ. It has not escaped our notice that the approach reported here is of use for studying many other genome diseases as well. Keywords: schizophrenia, eQTL, mRMR, SNP, GTEx, brain, GO, YWHA, EIF2, ITIH4.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2018 |
|---|---|
| Erschienen: |
2018 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
|---|---|
| Enthalten in: |
Molecular Therapy: Nucleic Acids - 12(2018), Seite 433-442 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Lei Cai [VerfasserIn] |
|---|
| Links: |
doi.org [kostenfrei] |
|---|
| Themen: |
|---|
| doi: |
10.1016/j.omtn.2018.05.026 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
DOAJ01947413X |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | DOAJ01947413X | ||
| 003 | DE-627 | ||
| 005 | 20230501174742.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230226s2018 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.omtn.2018.05.026 |2 doi | |
| 035 | |a (DE-627)DOAJ01947413X | ||
| 035 | |a (DE-599)DOAJ124d69454d8f4fc0b6fec5db10e44d89 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 050 | 0 | |a RM1-950 | |
| 100 | 0 | |a Lei Cai |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia |
| 264 | 1 | |c 2018 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Schizophrenia (SCZ) is a devastating genetic mental disorder. Identification of the SCZ risk genes in brains is helpful to understand this disease. Thus, we first used the minimum Redundancy-Maximum Relevance (mRMR) approach to integrate the genome-wide sequence analysis results on SCZ and the expression quantitative trait locus (eQTL) data from ten brain tissues to identify the genes related to SCZ. Second, we adopted the variance inflation factor regression algorithm to identify their interacting genes in brains. Third, using multiple analysis methods, we explored and validated their roles. By means of the aforementioned procedures, we have found that (1) the cerebellum may play a crucial role in the pathogenesis of SCZ and (2) ITIH4 may be utilized as a clinical biomarker for the diagnosis of SCZ. These interesting findings may stimulate novel strategy for developing new drugs against SCZ. It has not escaped our notice that the approach reported here is of use for studying many other genome diseases as well. Keywords: schizophrenia, eQTL, mRMR, SNP, GTEx, brain, GO, YWHA, EIF2, ITIH4 | ||
| 653 | 0 | |a Therapeutics. Pharmacology | |
| 700 | 0 | |a Tao Huang |e verfasserin |4 aut | |
| 700 | 0 | |a Jingjing Su |e verfasserin |4 aut | |
| 700 | 0 | |a Xinxin Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Wenzhong Chen |e verfasserin |4 aut | |
| 700 | 0 | |a Fuquan Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Lin He |e verfasserin |4 aut | |
| 700 | 0 | |a Kuo-Chen Chou |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i In |t Molecular Therapy: Nucleic Acids |d Elsevier, 2013 |g 12(2018), Seite 433-442 |w (DE-627)DOAJ000101176 |x 21622531 |7 nnns |
| 773 | 1 | 8 | |g volume:12 |g year:2018 |g pages:433-442 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.omtn.2018.05.026 |z kostenfrei |
| 856 | 4 | 0 | |u https://doaj.org/article/124d69454d8f4fc0b6fec5db10e44d89 |z kostenfrei |
| 856 | 4 | 0 | |u http://www.sciencedirect.com/science/article/pii/S2162253118301264 |z kostenfrei |
| 856 | 4 | 2 | |u https://doaj.org/toc/2162-2531 |y Journal toc |z kostenfrei |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_DOAJ | ||
| 912 | |a SSG-OLC-PHA | ||
| 951 | |a AR | ||
| 952 | |d 12 |j 2018 |h 433-442 | ||