Uncovering novel drug targets for bipolar disorder: a Mendelian randomization analysis of brain, cerebrospinal fluid, and plasma proteomes.

BACKGROUND: There is a clear demand for innovative therapeutics for bipolar disorder (BD). METHODS: We integrated the largest BD genome-wide association study (GWAS) dataset (NCase = 41 917, NControl = 371 549) with protein quantitative trait loci from brain, cerebrospinal fluid, and plasma. Using a range of integrative analyses, including Mendelian randomization (MR), Steiger filter analysis, Bayesian colocalization, and phenome-wide MR analysis, we prioritized novel drug targets for BD. Additionally, we incorporated data from the UK Biobank (NCase = 1064, NControl = 365 476) and the FinnGen study (NCase = 7006, NControl = 329 192) for robust biological validation. RESULTS: Through MR analysis, we found that in the brain, downregulation of DNM3, MCTP1, ABCB8 and elevation of DFNA5 and PDF were risk factors for BD. In cerebrospinal fluid, increased BD risk was associated with increased levels of FRZB, AGRP, and IL36A and decreased CTSF and LRP8. Plasma analysis revealed that decreased LMAN2L, CX3CL1, PI3, NCAM1, and TIMP4 correlated with increased BD risk, but ITIH1 did not. All these proteins passed Steiger filtering, and Bayesian colocalization confirmed that 12 proteins were colocalized with BD. Phenome-wide MR analysis revealed no significant side effects for potential drug targets, except for LRP8. External validation further underscored the concordance between the primary and validation cohorts, confirming MCTP1, DNM3, PDF, CTSF, AGRP, FRZB, LMAN2L, NCAM1, and TIMP4 are intriguing targets for BD. CONCLUSIONS: Our study identified druggable proteins for BD, including MCTP1, DNM3, and PDF in the brain; CTSF, AGRP, and FRZB in cerebrospinal fluid; and LMAN2L, NCAM1, and TIMP4 in plasma, delineating promising avenues to development of novel therapies.

Identification of novel proteins for lacunar stroke by integrating genome-wide association data and human brain proteomes.

BACKGROUND: Previous genome-wide association studies (GWAS) have identified numerous risk genes for lacunar stroke, but it is challenging to decipher how they confer risk for the disease. We employed an integrative analytical pipeline to efficiently transform genetic associations to identify novel proteins for lacunar stroke. METHODS: We systematically integrated lacunar stroke genome-wide association study (GWAS) (N=7338) with human brain proteomes (N=376) to perform proteome-wide association studies (PWAS), Mendelian randomization (MR), and Bayesian colocalization. We also used an independent human brain proteomic dataset (N=152) to annotate the new genes. RESULTS: We found that the protein abundance of seven genes (ICA1L, CAND2, ALDH2, MADD, MRVI1, CSPG4, and PTPN11) in the brain was associated with lacunar stroke. These seven genes were mainly expressed on the surface of glutamatergic neurons, GABAergic neurons, and astrocytes. Three genes (ICA1L, CAND2, ALDH2) were causal in lacunar stroke (P < 0.05/proteins identified for PWAS; posterior probability of hypothesis 4 ≥ 75 % for Bayesian colocalization), and they were linked with lacunar stroke in confirmatory PWAS and independent MR. We also found that ICA1L is related to lacunar stroke at the brain transcriptome level. CONCLUSIONS: Our present proteomic findings have identified ICA1L, CAND2, and ALDH2 as compelling genes that may give key hints for future functional research and possible therapeutic targets for lacunar stroke.

[Association Between SNP rs6007897 of CELSR1 and Acute Ischemic Stroke in Western China Han Population: a Case-control Study].

OBJECTIVE: To investigate the relationship between single nucleotide polymorphism (SNP) rs6007897 of CELSR1 and acute ischemic stroke in Western China Han population. METHODS: All subjects (759 acute ischemic stroke patients and 786 controls) were genotyped using ligation detection reaction (LDR). We analyzed the differences between SNP rs6007897 genotypes and allele frequencies between two groups. RESULTS: Two genotypes (AA, AG) of rs6007897 were found in both stroke and control group. There was no statistically significance between two groups about genotype and allele frequency. After adjusting for risk factors, we found there was no significant association between rs6007897 and ischemic stroke CP = 0.797, odds ratio (OR) = 0.886, 95% confidence interval (CI) = 0.352-2.227). CONCLUSION: SNP rs6007897 of CELSR1 was not significantly associated with ischemic stroke in Western China Han population.

Abnormal Brain Protein Abundance and Cross-tissue mRNA Expression in Amyotrophic Lateral Sclerosis.

Due to the limitations of the present risk genes in understanding the etiology of amyotrophic lateral sclerosis (ALS), it is necessary to find additional causative genes utilizing novel approaches. In this study, we conducted a two-stage proteome-wide association study (PWAS) using ALS genome-wide association study (GWAS) data (N = 152,268) and two distinct human brain protein quantitative trait loci (pQTL) datasets (ROSMAP N = 376 and Banner N = 152) to identify ALS risk genes and prioritized candidate genes with Mendelian randomization (MR) and Bayesian colocalization analysis. Next, we verified the aberrant expression of risk genes in multiple tissues, including lower motor neurons, skeletal muscle, and whole blood. Six ALS risk genes (SCFD1, SARM1, TMEM175, BCS1L, WIPI2, and DHRS11) were found during the PWAS discovery phase, and SARM1 and BCS1L were confirmed during the validation phase. The following MR (p = 2.10 × 10-7) and Bayesian colocalization analysis (ROSMAP PP4 = 0.999, Banner PP4 = 0.999) confirmed the causal association between SARM1 and ALS. Further differential expression analysis revealed that SARM1 was markedly downregulated in lower motor neurons (p = 7.64 × 10-3), skeletal muscle (p = 9.34 × 10-3), and whole blood (p = 1.94 × 10-3). Our findings identified some promising protein candidates for future investigation as therapeutic targets. The dysregulation of SARM1 in multiple tissues provides a new way to explain ALS pathology.

Brain proteome-wide association study linking-genes in multiple sclerosis pathogenesis.

OBJECTIVES: To identify genes that confer MS risk via the alteration of cis-regulated protein abundance and verify their aberrant expression in human brain. METHODS: Utilizing a two-stage proteome-wide association study (PWAS) design, MS GWAS data (N = 41,505) was respectively integrated with two distinct human brain proteomes from the dorsolateral prefrontal cortex, including ROSMAP (N = 376) in the discovery stage and Banner (N = 152) in the confirmation stage. In the following, Bayesian colocalization analysis was conducted for GWAS and protein quantitative trait loci signals to prioritize candidate genes. Differential expression analysis was then used to verify the dysregulation of risk genes in white matter and gray matter for evidence at the transcription level. RESULTS: A total of 51 genes whose protein abundance had association with the MS risk were identified, of which 18 genes overlapped in the discovery and confirmation PWAS. Bayesian colocalization indicated six causal genes with genetic risk variants for the MS risk. The differential expression analysis of SHMT1 (PFDR  = 4.82 × 10-2 ), FAM120B (PFDR  = 8.13 × 10-4 ) in white matter and ICA1L (PFDR  = 3.44 × 10-2 ) in gray matter confirmed the dysregulation at the transcription level. Further investigation of expression found SHMT1 significantly up-regulated in white matter lesion, and FAM120B up-regulated in both white matter lesion and normal appearing white matter. ICA1L was down-regulated in both gray matter lesion and normal appearing gray matter. INTERPRETATION: Dysregulation of SHMT1, FAM120B and ICA1L may confer MS risk. Our findings shed new light on the pathogenesis of MS and prioritized promising targets for future therapy research.

Fiscal Expenditure Structure, Vertical Fiscal Imbalance and Environmental Pollution.

Based on China's provincial panel data from 2007 to 2019, the authors of this paper conducted an empirical test on the direct effect of China's fiscal expenditure structure on the reduction in environmental pollution with the use of a fixed effect model. We also creatively added an interaction item comprising vertical fiscal imbalance and the expenditure structure to further study the impact of vertical fiscal imbalance on reducing environmental pollution and its effect on the fiscal expenditure structure. The study results show that a structure in favor of expenditure on people's welfare noticeably reduces environmental pollution. However, after the introduction of the vertical fiscal imbalance indicator, the pollution reduction effect decreases. That is, the vertical fiscal imbalance weakens and distorts the impact of the fiscal expenditure structure on the reduction in environmental pollution. Therefore, it is possible to further motivate local governments with incentive measures, such as fiscal decentralization and the centralization of administrative responsibilities, and regulate the environmental pollution of local governments through use of restrictive measures, such as the "green GDP" evaluation mechanism to further improve the fiscal expenditure structure of local governments, enhance the environmental pollution reduction capability of fiscal expenditure.

Economic Development, Fiscal Ecological Compensation, and Ecological Environment Quality.

Focusing on the exploration of the important role of fiscal ecological compensation in green development, this paper incorporates fiscal ecological compensation into the analytical framework of green development. Based on samples of data from county areas in China in 2017 and 2018, this paper empirically examines the shape of the green development routes in county areas in China. On this basis, this paper explores the impact and mechanism of fiscal ecological compensation on the green development path in China. The empirical results show that there is a nonlinear, N-shaped relationship between economic development and the ecological environment in China within the range of the sample examined. Fiscal ecological compensation has a direct governance effect on the ecological environment of deterring ecological damage and providing financial compensation. Fiscal ecological compensation has an indirect impact on the ecological management of different regions by influencing economic development. Therefore, while focusing on transforming the economic development model, local governments should adopt policy instruments such as expanding the coverage of financial ecological compensation, deepening the design of the financial ecological compensation system, and systematically evaluating the effects of financial ecological compensation policies. The government should further improve and optimize the fiscal eco-compensation system in order to help China's green and high-quality development.

Statin treatment reduces the risk of poststroke seizures.

OBJECTIVE: To examine the potential efficacy of statin treatment in reducing the risk of poststroke seizures. METHODS: In this cohort study, patients with a first-ever ischemic stroke and no history of epilepsy before stroke were enrolled. After a mean follow-up period of 2.5 years, a follow-up assessment was performed to identify poststroke epilepsy. Logistic regression and Cox regression analyses were used to assess the relationship between statin use and poststroke early-onset seizures or poststroke epilepsy. RESULTS: Of 1,832 enrolled patients, 63 (3.4%) patients had poststroke early-onset seizures and 91 (5.0%) patients had poststroke epilepsy. Statin use was associated with a lower risk of poststroke early-onset seizures (odds ratio [OR] 0.35, 95% confidence interval [CI] 0.20-0.60, p < 0.001), and this reduced risk was seen mainly in patients who used a statin only in the acute phase (OR 0.36, 95% CI 0.20-0.62, p < 0.001). No significant association was found between statin use and poststroke epilepsy (OR 0.81, 95% CI 0.52-1.26, p = 0.349). In 63 patients who presented with early-onset seizures, statin use was associated with reduced risk of poststroke epilepsy (OR 0.34, 95% CI 0.13-0.88, p = 0.026). CONCLUSIONS: Statin use, especially in the acute phase, may reduce the risk of poststroke early-onset seizures. In addition, statin treatment may prevent the progression of initial poststroke seizure-induced neurodegeneration into chronic epilepsy. Because of the observational nature of the study, more studies are needed to confirm the results. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that in patients with a first-ever ischemic stroke, the early use of statins reduces the risk of early poststroke seizures.