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》

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 ... -  《-》

Shared Genetics and Comorbid Genes of Amyotrophic Lateral Sclerosis and Parkinson's Disease.

Comorbidity exists between amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD), but the role of genetic factors is unclear. We aim to investigate genetic correlation, causal relationship, and comorbid genes between ALS and PD. Leveraging the largest genome-wide association study data (ALS: 27,205 cases, 110,881 controls; PDG: 33,674 cases, 449,056 controls), we used linkage disequilibrium score regression and Mendelian randomization analysis for genetic correlation and causal inference. We performed genome-wide cross-trait analysis via Multi-Trait Analysis of Genome-Wide Association Studies and Cross-Phenotype Association to identify specific single-nucleotide polymorphisms, followed by functional mapping and annotation. Integrating expression quantitative trait loci data from 13 brain regions, we conducted a transcriptome-wide association study via functional summary-based imputation and joint-tissue imputation to explore comorbid genes, followed by pathway enrichment analysis. We found that PD positively correlates with ALS (rg  = 0.144, P = 0.026) and confers a causal effect (odds ratio = 1.09, 95% confidence interval: 1.03-1.15, P = 3.00 × 10-3 ). We identified nine single-nucleotide polymorphisms (eight new), associating with three risk loci (chromosomes 4, 10, and 17) and seven genes (TMEM175, MAPT, NSF, LRRC37A2, ARHGAP27, GAK, and FGFRL1). In transcriptome-wide association study analysis, we showed six previously unreported pleiotropic genes (KANSL1, ARL17B, EFNA1, WNT3, ERCC8, and ADAM15), and we found these candidate genes are mainly enriched in negative regulation of neuron projection development (GO:0010977). Our work demonstrates shared genetic architecture between ALS and PD, reports new pleiotropic genes, and sheds light on the comorbid mechanism. © 2023 International Parkinson and Movement Disorder Society.

Tian Y ，Ma G ，Li H ，Zeng Y ，Zhou S ，Wang X ，Shan S ，Xu Y ，Xiong J ，Cheng G ... -  《-》

Identifying causal genes for migraine by integrating the proteome and transcriptome.

While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.

Li SJ ，Shi JJ ，Mao CY ，Zhang C ，Xu YF ，Fan Y ，Hu ZW ，Yu WK ，Hao XY ，Li MJ ，Li JD ，Ma DR ，Guo MN ，Zuo CY ，Liang YY ，Xu YM ，Wu J ，Sun SL ，Wang YG ，Shi CH ... -  《-》

Pinpointing novel risk loci for Lewy body dementia and the shared genetic etiology with Alzheimer's disease and Parkinson's disease: a large-scale multi-trait association analysis.

The current genome-wide association study (GWAS) of Lewy body dementia (LBD) suffers from low power due to a limited sample size. In addition, the genetic determinants underlying LBD and the shared genetic etiology with Alzheimer's disease (AD) and Parkinson's disease (PD) remain poorly understood. Using the largest GWAS summary statistics of LBD to date (2591 cases and 4027 controls), late-onset AD (86,531 cases and 676,386 controls), and PD (33,674 cases and 449,056 controls), we comprehensively investigated the genetic basis of LBD and shared genetic etiology among LBD, AD, and PD. We first conducted genetic correlation analysis using linkage disequilibrium score regression (LDSC), followed by multi-trait analysis of GWAS (MTAG) and association analysis based on SubSETs (ASSET) to identify the trait-specific SNPs. We then performed SNP-level functional annotation to identify significant genomic risk loci paired with Bayesian fine-mapping and colocalization analysis to identify potential causal variants. Parallel gene-level analysis including GCTA-fastBAT and transcriptome-wide association analysis (TWAS) was implemented to explore novel LBD-associated genes, followed by pathway enrichment analysis to understand underlying biological mechanisms. Pairwise LDSC analysis found positive genome-wide genetic correlations between LBD and AD (rg = 0.6603, se = 0.2001; P = 0.0010), between LBD and PD (rg = 0.6352, se = 0.1880; P = 0.0007), and between AD and PD (rg = 0.2136, se = 0.0860; P = 0.0130). We identified 13 significant loci for LBD, including 5 previously reported loci (1q22, 2q14.3, 4p16.3, 4q22.1, and 19q13.32) and 8 novel biologically plausible genetic associations (5q12.1, 5q33.3, 6p21.1, 8p23.1, 8p21.1, 16p11.2, 17p12, and 17q21.31), among which APOC1 (19q13.32), SNCA (4q22.1), TMEM175 (4p16.3), CLU (8p21.1), MAPT (17q21.31), and FBXL19 (16p11.2) were also validated by gene-level analysis. Pathway enrichment analysis of 40 common genes identified by GCTA-fastBAT and TWAS implicated significant role of neurofibrillary tangle assembly (GO:1902988, adjusted P = 1.55 × 10-2). Our findings provide novel insights into the genetic determinants of LBD and the shared genetic etiology and biological mechanisms of LBD, AD, and PD, which could benefit the understanding of the co-pathology as well as the potential treatment of these diseases simultaneously.

Guo P ，Gong W ，Li Y ，Liu L ，Yan R ，Wang Y ，Zhang Y ，Yuan Z ... -  《BMC Medicine》