Brain Proteome-Wide and Transcriptome-Wide Asso-ciation Studies, Bayesian Colocalization, and Mendelian Randomization Analyses Reveal Causal Genes of Parkinson's Disease.

How genome-wide associated loci confer risk for Parkinson's disease is unclear. We aim to reveal causal genes through effects on brain proteins to provide new pathogenesis insights for Parkinson's disease. Proteome-wide and transcriptome-wide associations were determined by functional summary-based imputation leveraging data from genome-wide association summary (56 306 Europeans, 1.4 million controls), brain proteomes (528 cases from 2 separate data sets), and transcriptome (452 cases), followed by Mendelian randomization, Bayesian colocalization, cell-type-specific and brain regional expression, and drug-gene interaction analyses. As a result, genetically regulated protein abundances of 11 genes were associated with Parkinson's disease. Five genes (CD38, GPNMB, TMEM175, RAB7L1, and HIP1R) were colocalized. Four genes (GPNMB, SEC23IP, CD38, and DGKQ) demonstrated Mendelian randomized correlations (p < 8.10 × 10-5). Higher GPNMB level (1.47, 1.28-1.68) and lower CD38 level (0.319, 0.24-0.43) were causally associated with higher risk of Parkinson's disease, consistent with transcriptomic evaluations. CD38 and GPNMB were preferentially enriched in astrocytes and oligodendrocyte precursor cells, respectively. And CD38 and GPNMB were suggested to be the targets of many oncological drugs from Drug-Gene Interaction database. In conclusion, utilizing multidimensional data, GPNMB and CD38 were prioritized as the causal genes of Parkinson's disease, crucial for mechanistic and therapeutic investigations.

Zhou S ，Tian Y ，Song X ，Xiong J ，Cheng G ... -  《-》

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes.

Shi JJ ，Mao CY ，Guo YZ ，Fan Y ，Hao XY ，Li SJ ，Tian J ，Hu ZW ，Li MJ ，Li JD ，Ma DR ，Guo MN ，Zuo CY ，Liang YY ，Xu YM ，Yang J ，Shi CH ... -  《Aging-US》

Identifying causal genes for stroke via integrating the proteome and transcriptome from brain and blood.

Genome-wide association studies (GWAS) have revealed numerous loci associated with stroke. However, the underlying mechanisms at these loci in the pathogenesis of stroke and effective stroke drug targets are elusive. Therefore, we aimed to identify causal genes in the pathogenesis of stroke and its subtypes. Utilizing multidimensional high-throughput data generated, we integrated proteome-wide association study (PWAS), transcriptome-wide association study (TWAS), Mendelian randomization (MR), and Bayesian colocalization analysis to prioritize genes that contribute to stroke and its subtypes risk via affecting their expression and protein abundance in brain and blood. Our integrative analysis revealed that ICA1L was associated with small-vessel stroke (SVS), according to robust evidence at both protein and transcriptional levels based on brain-derived data. We also identified NBEAL1 that was causally related to SVS via its cis-regulated brain expression level. In blood, we identified 5 genes (MMP12, SCARF1, ABO, F11, and CKAP2) that had causal relationships with stroke and stroke subtypes. Together, via using an integrative analysis to deal with multidimensional data, we prioritized causal genes in the pathogenesis of SVS, which offered hints for future biological and therapeutic studies.

Wu BS ，Chen SF ，Huang SY ，Ou YN ，Deng YT ，Chen SD ，Dong Q ，Yu JT ... -  《Journal of Translational Medicine》

Prioritization of Drug Targets for Neurodegenerative Diseases by Integrating Genetic and Proteomic Data From Brain and Blood.

Neurodegenerative diseases are among the most prevalent and devastating neurological disorders, with few effective prevention and treatment strategies. We aimed to integrate genetic and proteomic data to prioritize drug targets for neurodegenerative diseases. We screened human proteomes through Mendelian randomization to identify causal mediators of Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, multiple sclerosis, frontotemporal dementia, and Lewy body dementia. For instruments, we used brain and blood protein quantitative trait loci identified from one genome-wide association study with 376 participants and another with 3301 participants, respectively. Causal associations were subsequently validated by sensitivity analyses and colocalization. The safety and druggability of identified targets were also evaluated. Our analyses showed targeting BIN1, GRN, and RET levels in blood as well as ACE, ICA1L, MAP1S, SLC20A2, and TOM1L2 levels in brain might reduce Alzheimer's disease risk, while ICA1L, SLC20A2, and TOM1L2 were not recommended as prioritized drugs due to the identified potential side effects. Brain CD38, DGKQ, GPNMB, and SEC23IP were candidate targets for Parkinson's disease. Among them, GPNMB was the most promising target for Parkinson's disease with their causal relationship evidenced by studies on both brain and blood tissues. Interventions targeting FCRL3, LMAN2, and MAPK3 in blood and DHRS11, FAM120B, SHMT1, and TSFM in brain might affect multiple sclerosis risk. The risk of amyotrophic lateral sclerosis might be reduced by medications targeting DHRS11, PSMB3, SARM1, and SCFD1 in brain. Our study prioritized 22 proteins as targets for neurodegenerative diseases and provided preliminary evidence for drug development. Further studies are warranted to validate these targets.

Ge YJ ，Ou YN ，Deng YT ，Wu BS ，Yang L ，Zhang YR ，Chen SD ，Huang YY ，Dong Q ，Tan L ，Yu JT ，International FTD-Genomics Consortium ... -  《-》

Mendelian Randomization and Bayesian Colocalization Analysis Implicate Glycoprotein VI as a Potential Drug Target for Cardioembolic Stroke in South Asian Populations.

Wu S ，Meena D ，Yarmolinsky J ，Gill D ，Smith A ，Dib MJ ，Chauhan G ，Rohatgi A ，Dehghan A ，Tzoulaki I ... -  《Journal of the American Heart Association》