In PNAS, Song et al. (1) conduct a genome-wide association study (GWAS) for leadership phenotypes (leadership position and managing demands). They identify nine genome-wide significant single-nucleotide polymorphism (SNP) signals for leadership phenotypes (P < 5E-08), and find several top signals overlapping with known loci for bipolar disorder (miR-2113/POUSF2 and LINC01239) and schizophrenia (ZSWIM6) (1). Although the findings of them are encouraging, how these top SNPs influence leadership phenotypes remains unknown.
Substantial studies have shown that many genetic variants affect complex traits by modulating gene expression (2–5). These variants may regulate the expression of certain genes in the brain region, leading to stronger leadership. Here, we test our hypothesis from two aspects. First, we investigate the cis-regulated effects of the nine top SNPs in the genes (1) they located in 13 types of normal brain tissues from Genotype-Tissue Expression (GTEx, version 8) (amygdala, anterior cingulate cortex, caudate basal ganglia, cerebellar hemisphere, cerebellum, cortex, hippocampus, hypothalamus, frontal cortex, nucleus accumbens basal ganglia, putamen basal ganglia, spinal cord cervical, and substantia nigra) (6). In the GTEx dataset, eQTL (expression quantitative trait loci) analysis was performed by applying linear regression based on an additive model. The statistically significant association after multiple testing is defined as P < 0.05/(number of loci * number of tissues). Second, integrating GWAS data for leadership phenotypes with gene expression measurements for brain tissues in GTEx, we implement a transcriptome-wide association scan (TWAS) to identify genes whose cis-regulated expression was associated with leadership phenotypes (1, 2, 6). The significant association after multiple testing is defined as P < 0.05/(number of genes).
As a result, we found that seven of the nine genome-wide significant SNPs (rs7035099, rs4665237, rs9848497, rs7719676, rs1487441, rs4977839, and rs76915478) are involved in regulating the expression of leadership-related genes in brain regions. However, only the P values for the regulation of rs7035099 on ZNF618 expression and rs9848497 on MST1R expression passed multiple testing (Table 1). Specifically, rs7035099 significantly up-regulated ZNF618 expression in the cerebellar hemisphere and cerebellum, and rs9848497 significantly up-regulated MST1R expression in the anterior cingulate cortex, caudate, cerebellar hemisphere, cerebellum, cortex, nucleus accumbens, and spinal cord. Furthermore, by integrating GWAS data for leadership phenotypes with eQTL data for brain tissues, we identify six gene candidates (MST1, MST1R, RNF123, UBA7, FAM212A, and APEH) whose expression is significantly associated with managing demands after multiple testing (Table 2). These significant association signals are all located in chromosome 3p21.3. Interestingly, MST1R replicates the significant signal in the original GWAS, and is also the most significant signal in TWAS (ZCerebellar hemisphere = −6.30, PCerebellar hemisphere = 3.02E-10) (1). However, none of the genes for leadership position passed multiple testing. Similar to the results of Song et al. (1), the genes we identify are also involved in brain function or psychiatric disorders. For instance, down-regulation of MST1 protects against stress-induced depression-like behaviors (7, 8). RNF123, a biomarker of depression, is overexpressed in the cingulate cortex of depressed patients (9, 10).
Table 1.
Leadership-related genetic variants and gene expression in brain tissues
| SNP | Gene | Beta | P value | Tissue |
|---|---|---|---|---|
| rs7035099 | ZNF618 | 0.34 | 0.000014 | Cerebellar hemisphere |
| rs7035099 | ZNF618 | 0.31 | 0.000019 | Cerebellum |
| rs9848497 | MST1R | 0.39 | 0.000023 | Anterior cingulate cortex |
| rs9848497 | MST1R | 0.34 | 5.70E-06 | Caudate |
| rs9848497 | MST1R | 0.49 | 2.30E-13 | Cerebellar hemisphere |
| rs9848497 | MST1R | 0.54 | 5.00E-19 | Cerebellum |
| rs9848497 | MST1R | 0.42 | 1.10E-08 | Cortex |
| rs9848497 | MST1R | 0.40 | 2.50E-09 | Nucleus accumbens |
| rs9848497 | MST1R | 0.47 | 0.000025 | Spinal cord |
Beta is the regression coefficient of the SNP on gene expression. Beta > 0 and Beta < 0 mean that this effect allele of SNP regulates increased and reduced gene expression, respectively. The statistically significant association after multiple testing is defined as P < 0.05/(10 * 13) = 0.000385. Only variants and their expression levels that passed multiple testing are shown in the table.
Table 2.
Cis-regulated genes associated with managing demands based on TWAS in brain tissues
| Tissue | Gene | Chr | HSQ | Z | P value |
|---|---|---|---|---|---|
| Amygdala | RNF123 | 3 | 0.16 | −4.87 | 1.13E-06 |
| Anterior cingulate cortex | RNF123 | 3 | 0.12 | −5.11 | 3.29E-07 |
| MST1R | 3 | 0.19 | −5.74 | 9.64E-09 | |
| Caudate basal ganglia | UBA7 | 3 | 0.06 | 5.91 | 3.43E-09 |
| MST1R | 3 | 0.11 | −4.95 | 7.3E-07 | |
| Cerebellar hemisphere | FAM212A | 3 | 0.35 | −4.88 | 1.06E-06 |
| RNF123 | 3 | 0.27 | −4.88 | 1.08E-06 | |
| MST1R | 3 | 0.37 | −6.30 | 3.02E-10 | |
| Cerebellum | RNF123 | 3 | 0.41 | −5.45 | 4.97E-08 |
| FAM212A | 3 | 0.47 | −4.9 | 9.79E-07 | |
| Cortex | RNF123 | 3 | 0.18 | −5.26 | 1.45E-07 |
| MST1R | 3 | 0.13 | −5.97 | 2.31E-09 | |
| Hypothalamus | MST1 | 3 | 0.18 | 4.54 | 5.69E-06 |
| MST1R | 3 | 0.09 | −5.42 | 6.07E-08 | |
| RNF123 | 3 | 0.17 | −5.41 | 6.24E-08 | |
| Frontal cortex | RNF123 | 3 | 0.13 | −4.87 | 1.13E-06 |
| MST1R | 3 | 0.15 | −4.56 | 5.21E-06 | |
| MST1 | 3 | 0.21 | 4.91 | 8.99E-07 | |
| Nucleus accumbens basal ganglia | MST1R | 3 | 0.15 | −5.72 | 1.09E-08 |
| RNF123 | 3 | 0.17 | −4.87 | 1.13E-06 | |
| MST1 | 3 | 0.19 | 4.90 | 9.4E-07 | |
| RNF123 | 3 | 0.10 | −5.31 | 1.1E-07 | |
| Spinal cord cervical | RNF123 | 3 | 0.15 | −5.15 | 2.57E-07 |
| APEH | 3 | 0.13 | 5.13 | 2.97E-07 | |
| MST1R | 3 | 0.10 | −5.79 | 6.83E-09 |
Chr, chromosome; HSQ, heritability of the gene; Z, Z score of TWAS test. The statistically significant association after adjusting for multiple testing is defined as PAmygdala < 0.05/2633 = 1.90E-05, PAnterior cingulate cortex < 0.05/3482 = 1.44E-05, PCaudate basal ganglia < 0.05/5078 = 9.85E-06, PCerebellar hemisphere < 0.05/6141 = 8.14E-06, PCerebellum < 0.05/7330 = 6.82E-06, PCortex < 0.05/5645 = 8.86E-06, PHippocampus < 0.05/3576 = 1.40E-05, PHypothalamus < 0.05/3581 = 1.40E-05, PFrontal cortex < 0.05/4557 = 1.10E-05, PNucleus accumbens basal ganglia < 0.05/5039 = 9.92E-06, PPutamen basal ganglia < 0.05/4325 = 1.16E-05, PSpinal cord cervical < 0.05/3148 = 1.59E-05, and PSubstantia nigra < 0.05/2278 = 2.19E-05.
In summary, our findings highlight that rs9848497 influences leadership phenotypes by modulating MST1R expression, which may provide important information about the biological mechanism of rs9848497 in leadership phenotypes.
Acknowledgments
We gratefully acknowledge GTEx (https://www.gtexportal.org/home/) for providing eQTL data. This work was supported by funding from the National Natural Science Foundation of China (Grants 82071212 and 81901181), Beijing Natural Science Foundation (Grant JQ21022), the Mathematical Tianyuan Fund of the National Natural Science Foundation of China (Grant 12026414), and Beijing Ten Thousand Talents Project (Grant 2020A15).
Footnotes
The authors declare no competing interest.
References
- 1.Song Z., et al. , Genetics, leadership position, and well-being: An investigation with a large-scale GWAS. Proc. Natl. Acad. Sci. U.S.A. 119, 10.1073/pnas.2114271119 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Gusev A., et al. , Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245–252 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Albert F. W., Kruglyak L., The role of regulatory variation in complex traits and disease. Nat. Rev. Genet. 16, 197–212 (2015). [DOI] [PubMed] [Google Scholar]
- 4.Zhang X., et al. , Identification of common genetic variants controlling transcript isoform variation in human whole blood. Nat. Genet. 47, 345–352 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Zhu Z., et al. , Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016). [DOI] [PubMed] [Google Scholar]
- 6.Battle A., Brown C. D., Engelhardt B. E., Montgomery S. B.; GTEx Consortium; Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group; Statistical Methods groups—Analysis Working Group; Enhancing GTEx (eGTEx) groups; NIH Common Fund; NIH/NCI; NIH/NHGRI; NIH/NIMH; NIH/NIDA; Biospecimen Collection Source Site—NDRI; Biospecimen Collection Source Site—RPCI; Biospecimen Core Resource—VARI; Brain Bank Repository—University of Miami Brain Endowment Bank; Leidos Biomedical—Project Management; ELSI Study; Genome Browser Data Integration &Visualization—EBI; Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz; Lead analysts; Laboratory, Data Analysis &Coordinating Center (LDACC); NIH program management; Biospecimen collection; Pathology; eQTL manuscript working group, Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).29022597 [Google Scholar]
- 7.Chen B., Zhang Q., Yan Y., Zhang T., MST1-knockdown protects against impairment of working memory via regulating neural activity in depression-like mice. Genes Brain Behav. 21, e12782 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Yan Y., et al. , Down-regulation of MST1 in hippocampus protects against stress-induced depression-like behaviours and synaptic plasticity impairments. Brain Behav. Immun. 94, 196–209 (2021). [DOI] [PubMed] [Google Scholar]
- 9.Teyssier J. R., Rey R., Ragot S., Chauvet-Gelinier J. C., Bonin B., Correlative gene expression pattern linking RNF123 to cellular stress-senescence genes in patients with depressive disorder: Implication of DRD1 in the cerebral cortex. J. Affect. Disord. 151, 432–438 (2013). [DOI] [PubMed] [Google Scholar]
- 10.Glahn D. C., et al. , High dimensional endophenotype ranking in the search for major depression risk genes. Biol. Psychiatry 71, 6–14 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
