Shi-Dong Chen

Large-scale proteomics studies can refine our understanding of health and disease and enable precision medicine. Here, we provide a detailed atlas of 2,920 plasma proteins linking to diseases (406 prevalent and 660 incident) and 986 health-related traits in 53,026 individuals (median follow-up: 14.8 years) from the UK Biobank, representing the most comprehensive proteome profiles to date. This atlas revealed 168,100 protein-disease associations and 554,488 protein-trait associations. Over 650 proteins were shared among at least 50 diseases, and over 1,000 showed sex and age heterogeneity. Furthermore, proteins demonstrated promising potential in disease discrimination (area under the curve [AUC] > 0.80 in 183 diseases). Finally, integrating protein quantitative trait locus data determined 474 causal proteins, providing 37 drug-repurposing opportunities and 26 promising targets with favorable safety profiles. These results provide an open-access comprehensive proteome-phenome resource (https://proteome-phenome-atlas.com/) to help elucidate the biological mechanisms of diseases and accelerate the development of disease biomarkers, prediction models, and therapeutic targets.

BACKGROUND: Recent studies had explored that gut microbiota was associated with neurodegenerative diseases (including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS)) through the gut-brain axis, among which metabolic pathways played an important role. However, the underlying causality remained unclear. OBJECTIVE: Our study aimed to evaluate potential causal relationships between gut microbiota, metabolites, and neurodegenerative diseases through Mendelian randomization (MR) approach. METHODS: We selected genetic variants associated with gut microbiota traits (N = 18,340) and gut microbiota-derived metabolites (N = 7,824) from genome-wide association studies. Summary statistics of neurodegenerative diseases were obtained from IGAP (AD, 17,008 cases; 37,154 controls), IPDGC (PD, 37,688 cases; 141,779 controls), and IALSC (ALS, 20,806 cases; 59,804 controls) respectively. RESULTS: Greater abundance of Ruminococcus (OR, 1.245; 95% CI, 1.103-1.405; p = 0.0004) was found significantly related to higher risk of ALS. Besides, our study found suggestive associations of Actinobacteria, Lactobacillaceae, Faecalibacterium, Ruminiclostridium, and Lachnoclostridium with AD, of Lentisphaerae, Lentisphaeria, Oxalobacteraceae, Victivallales, Bacillales, Eubacteriumhalliigroup, Anaerostipes, and Clostridiumsensustricto1 with PD, and of Lachnospira, Fusicatenibacter, Catenibacterium, and Ruminococcusgnavusgroup with ALS. Our study also revealed suggestive associations between 12 gut microbiome-dependent metabolites and neurodegenerative diseases. Glutamine was related to lower risk of AD. For the serotonin pathway, serotonin was found as a protective factor of PD, while kynurenine as a risk factor for ALS. CONCLUSION: Our study firstly applied a two-sample MR approach to detect causal relationships among gut microbiota, gut metabolites, and neurodegenerative diseases. Our findings may provide new targets for treatments and may offer valuable insights for further studies on the underlying mechanisms.