Dataset Information

Mendelian Randomization Using the Druggable Genome Reveals Genetically Supported Drug Targets for Psychiatric Disorders.

ABSTRACT:

Background and hypothesis

Psychiatric disorders impose a huge health and economic burden on modern society. However, there is currently no proven completely effective treatment available, partly owing to the inefficiency of drug target identification and validation. We aim to identify therapeutic targets relevant to psychiatric disorders by conducting Mendelian randomization (MR) analysis.

Study design

We performed genome-wide MR analysis by integrating expression quantitative trait loci (eQTL) of 4479 actionable genes that encode druggable proteins and genetic summary statistics from genome-wide association studies of psychiatric disorders. After conducting colocalization analysis on the brain MR findings, we employed protein quantitative trait loci (pQTL) data as genetic proposed instruments for intersecting the colocalized genes to provide further genetic evidence.

Study results

By performing MR and colocalization analysis with eQTL genetic instruments, we obtained 31 promising drug targets for psychiatric disorders, including 21 significant genes for schizophrenia, 7 for bipolar disorder, 2 for depression, 1 for attention deficit and hyperactivity (ADHD) and none for autism spectrum disorder. Combining MR results using pQTL genetic instruments, we finally proposed 8 drug-targeting genes supported by the strongest MR evidence, including gene ACE, BTN3A3, HAPLN4, MAPK3 and NEK4 for schizophrenia, gene NEK4 and HAPLN4 for bipolar disorder, and gene TIE1 for ADHD.

Conclusions

Our findings with genetic support were more likely to be to succeed in clinical trials. In addition, our study prioritizes approved drug targets for the development of new therapies and provides critical drug reuse opportunities for psychiatric disorders.

SUBMITTER: Li X

PROVIDER: S-EPMC10483453 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

Mendelian Randomization Using the Druggable Genome Reveals Genetically Supported Drug Targets for Psychiatric Disorders.

Li Xiaoyan X Shen Aotian A Zhao Yiran Y Xia Junfeng J

Schizophrenia bulletin 20230901 5

<h4>Background and hypothesis</h4>Psychiatric disorders impose a huge health and economic burden on modern society. However, there is currently no proven completely effective treatment available, partly owing to the inefficiency of drug target identification and validation. We aim to identify therapeutic targets relevant to psychiatric disorders by conducting Mendelian randomization (MR) analysis.<h4>Study design</h4>We performed genome-wide MR analysis by integrating expression quantitative tra ...[more]

PMID: 37418754

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Project description:ImportanceObservational studies have reported associations between antihypertensive medication and psychiatric disorders, although the reported direction of association appears to be dependent on drug class.ObjectiveTo estimate the potential effect of different antihypertensive drug classes on schizophrenia, bipolar disorder, and major depressive disorder.Design, setting, and participantsThis 2-sample mendelian randomization study assessed the association between a single-nucleotide variant (SNV) and drug target gene expression derived from existing expression quantitative trait loci (eQTL) data in blood (sample 1) and the SNV-disease association from published case-control genome-wide association studies (sample 2). Significant associations were corroborated using published brain eQTL and protein QTL data. Participants included 40 675 patients with schizophrenia and 64 643 controls, 20 352 patients with bipolar disorder and 31 358 controls, and 135 458 patients with major depressive disorder and 344 901 controls. Blood eQTL levels were measured in 31 684 individuals from 37 cohorts (eQTLGen consortium); prefrontal cortex eQTLs were measured from the PsychENCODE resource in 1387 individuals; and protein QTLs were measured in cerebral spinal fluid from 544 individuals and plasma from 818 individuals. Data were collected from October 4, 2019, to June 1, 2020, and analyzed from October 14, 2019, to June 6, 2020.ExposuresExpression levels of antihypertensive drug target genes as proxies for drug exposure, and genetic variants robustly associated with the expression of these genes as mendelian randomization instruments.Main outcomes and measuresRisk for schizophrenia, bipolar disorder, and major depressive disorder.ResultsA 1-SD lower expression of the angiotensin-converting enzyme (ACE) gene in blood was associated with lower systolic blood pressure of 4.0 (95% CI, 2.7-5.3) mm Hg, but increased risk of schizophrenia (odds ratio [OR], 1.75; 95% CI, 1.28-2.38; P = 3.95 × 10-4). A concordant direction of association was also observed between ACE expression in prefrontal cortex (OR, 1.33; 95% CI, 1.13-1.56) and ACE protein levels in cerebral spinal fluid (OR per 1-SD decrease, 1.12; 95% CI, 1.05-1.19) and plasma (OR per 1-SD decrease, 1.04; 95% CI, 1.01-1.07). We found no evidence for an association between genetically estimated SBP and schizophrenia risk.Conclusions and relevanceFindings suggest an adverse association of lower ACE messenger RNA and protein levels with schizophrenia risk. These findings warrant greater pharmacovigilance and further investigation into the effect of ACE inhibitors, particularly those that are centrally acting, on psychiatric symptoms in patients with schizophrenia, as well as the role of ACE inhibitor use in late-onset schizophrenia.

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Project description:BackgroundPrevious researches have demonstrated a connection between psychiatric disorders and cardiovascular diseases (CVDs), but the cause-and-effect relationship is still unclear. To that goal, the mendelian randomization (MR) method was used to study the causal link between psychiatric disorders and CVDs.MethodsGenome-wide association studies (GWAS) data were collected for four CVDs, including coronary artery disease (n = 547,261), atrial fibrillation (n = 537,409), heart failure (n = 977,323) and ischemic stroke (n = 440,328). Summary data for four psychiatric disorders, including bipolar disorder (n = 51,710), major depressive disorder (n = 480,359), schizophrenia (n = 127,906) and attention deficit hyperactivity disorder (n = 55,374), came from the Psychiatric Genomics Consortium (PGC). All participants were European. The IVW method was mainly used, and the reliability of the results was increased using sensitivity analyses such as MR-Egger, Cochrane's Q test, MR-PRESSO and leave-one-out.ResultsMR revealed that the attention deficit hyperactivity disorder was linked to an increased risk of atrial fibrillation (OR, 1.085; 95% CI, 1.021-1.153; P = 0.008), heart failure (OR, 1.117; 95% CI, 1.044-1.195; P = 0.001), and ischemic stroke (OR, 1.146; 95% CI, 1.052-1.248; P = 0.002). The schizophrenia was linked to an increased risk of heart failure (OR, 1.035; 95% CI, 1.006-1.066; P = 0.017), but was found to be suggestively inverse associated with coronary artery disease (OR, 0.969; 95% CI, 0.941-0.997; P = 0.03). The major depressive disorder was associated with higher odds of coronary artery disease (OR, 1.109; 95% CI, 1.018-1.208; P = 0.018), while the bipolar disorder was linked to a reduced incidence of coronary artery disease (OR, 0.894; 95% CI, 0.831-0.961; P = 0.002) and heart failure (OR, 0.889; 95% CI, 0.829-0.955; P = 0.001). There were no clear relationships between other psychiatric disorders and CVDs.ConclusionThe results provide genetic proof of a possible causal relationship between psychiatric disorders and CVDs. These results imply that psychiatric disorders may be the cause of some CVDs, and that some abnormal mental states may increase or reduce the likelihood of CVDs, providing guidance for the CVDs prevention.

Dataset Information

Mendelian Randomization Using the Druggable Genome Reveals Genetically Supported Drug Targets for Psychiatric Disorders.

Background and hypothesis

Study design

Study results

Conclusions

Publications

Mendelian Randomization Using the Druggable Genome Reveals Genetically Supported Drug Targets for Psychiatric Disorders.

Similar Datasets

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