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      Prioritizing Parkinson’s disease genes using population-scale transcriptomic data

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          Abstract

          Genome-wide association studies (GWAS) have identified over 41 susceptibility loci associated with Parkinson’s Disease (PD) but identifying putative causal genes and the underlying mechanisms remains challenging. Here, we leverage large-scale transcriptomic datasets to prioritize genes that are likely to affect PD by using a transcriptome-wide association study (TWAS) approach. Using this approach, we identify 66 gene associations whose predicted expression or splicing levels in dorsolateral prefrontal cortex (DLFPC) and peripheral monocytes are significantly associated with PD risk. We uncover many novel genes associated with PD but also novel mechanisms for known associations such as MAPT, for which we find that variation in exon 3 splicing explains the common genetic association. Genes identified in our analyses belong to the same or related pathways including lysosomal and innate immune function. Overall, our study provides a strong foundation for further mechanistic studies that will elucidate the molecular drivers of PD.

          Abstract

          GWAS have identified over 41 susceptibility loci for Parkinson’s disease (PD). Here, the authors integrate PD GWAS summary statistics with transcriptome data from monocytes and DLFPC tissue in a TWAS approach and find 66 significant associations with PD risk highlighting lysosomal and innate immune functions.

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          Most cited references23

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          A human phenome-interactome network of protein complexes implicated in genetic disorders.

          We performed a systematic, large-scale analysis of human protein complexes comprising gene products implicated in many different categories of human disease to create a phenome-interactome network. This was done by integrating quality-controlled interactions of human proteins with a validated, computationally derived phenotype similarity score, permitting identification of previously unknown complexes likely to be associated with disease. Using a phenomic ranking of protein complexes linked to human disease, we developed a Bayesian predictor that in 298 of 669 linkage intervals correctly ranks the known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type 2 diabetes and coronary heart disease. Our publicly available draft of protein complexes associated with pathology comprises 506 complexes, which reveal functional relationships between disease-promoting genes that will inform future experimentation.
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            Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes.

            To extend our understanding of the genetic basis of human immune function and dysfunction, we performed an expression quantitative trait locus (eQTL) study of purified CD4(+) T cells and monocytes, representing adaptive and innate immunity, in a multi-ethnic cohort of 461 healthy individuals. Context-specific cis- and trans-eQTLs were identified, and cross-population mapping allowed, in some cases, putative functional assignment of candidate causal regulatory variants for disease-associated loci. We note an over-representation of T cell-specific eQTLs among susceptibility alleles for autoimmune diseases and of monocyte-specific eQTLs among Alzheimer's and Parkinson's disease variants. This polarization implicates specific immune cell types in these diseases and points to the need to identify the cell-autonomous effects of disease susceptibility variants.
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              CD33 Alzheimer’s disease locus: Altered monocyte function and amyloid biology

              In our functional dissection of the CD33 Alzheimer’s disease susceptibility locus, we find that the rs3865444C risk allele is associated with greater cell surface expression of CD33 in monocytes (t 50 = 10.06, pjoint=1.3×10–13) of young and older individuals. It is also associated with (1) diminished internalization of Aβ42) (2) accumulation of neuritic amyloid pathology and fibrillar amyloid on in vivo imaging and (3), increased numbers of activated human microglia.
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                Author and article information

                Contributors
                towfique.raj@mssm.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                1 March 2019
                1 March 2019
                2019
                : 10
                Affiliations
                [1 ]ISNI 0000 0004 1936 7822, GRID grid.170205.1, Section of Genetic Medicine, Department of Medicine, and Department of Human Genetics, , University of Chicago, ; Chicago, 60637 IL USA
                [2 ]ISNI 0000 0001 0670 2351, GRID grid.59734.3c, Departments of Neuroscience, and Genetics and Genomic Sciences, Ronald M. Loeb Center for Alzheimer’s disease, , Icahn School of Medicine at Mount Sinai, ; New York, 10029 NY USA
                [3 ]ISNI 0000000121901201, GRID grid.83440.3b, UCL Genetics Institute, ; Gower Street, London, WC1E 6BT UK
                [4 ]ISNI 0000000121901201, GRID grid.83440.3b, Department of Neurodegenerative Disease, , UCL Institute of Neurology, ; London, WC1E 6BT UK
                Article
                8912
                10.1038/s41467-019-08912-9
                6397174
                30824768
                6067780b-9cc7-4681-9098-5c0733e4581a
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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