scholarly journals Functionalization of the TMEM175 p.M393T variant as a risk factor for Parkinson disease

2019 ◽  
Vol 28 (19) ◽  
pp. 3244-3254 ◽  
Author(s):  
Sarah Jinn ◽  
Cornelis Blauwendraat ◽  
Dawn Toolan ◽  
Cheryl A Gretzula ◽  
Robert E Drolet ◽  
...  
Keyword(s):  
Parkinson Disease ◽  
Therapeutic Strategy ◽  
Association Studies ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Wild Type ◽  
Lysosomal Ph ◽  
Genome Wide ◽  
Attractive Candidate ◽  
Lysosomal Gene

Abstract Multiple genome-wide association studies (GWAS) in Parkinson disease (PD) have identified a signal at chromosome 4p16.3; however, the causal variant has not been established for this locus. Deep investigation of the region resulted in one identified variant, the rs34311866 missense SNP (p.M393T) in TMEM175, which is 20 orders of magnitude more significant than any other SNP in the region. Because TMEM175 is a lysosomal gene that has been shown to influence α-synuclein phosphorylation and autophagy, the p.M393T variant is an attractive candidate, and we have examined its effect on TMEM175 protein and PD-related biology. After knocking down each of the genes located under the GWAS peak via multiple shRNAs, only TMEM175 was found to consistently influence accumulation of phosphorylated α-synuclein (p-α-syn). Examination of the p.M393T variant showed effects on TMEM175 function that were intermediate between the wild-type (WT) and knockout phenotypes, with reduced regulation of lysosomal pH in response to starvation and minor changes in clearance of autophagy substrates, reduced lysosomal localization, and increased accumulation of p-α-syn. Finally, overexpression of WT TMEM175 protein reduced p-α-syn, while overexpression of the p.M393T variant resulted in no change in α-synuclein phosphorylation. These results suggest that the main signal in the chromosome 4p16.3 PD risk locus is driven by the TMEM175 p.M393T variant. Modulation of TMEM175 may impact α-synuclein biology and therefore may be a rational therapeutic strategy for PD.

scholarly journals Functional genomics of autoimmune diseases

2021 ◽  
pp. annrheumdis-2019-216794
Author(s):  
Akari Suzuki ◽  
Matteo Maurizio Guerrini ◽  
Kazuhiko Yamamoto
Keyword(s):  
Autoimmune Diseases ◽  
Association Studies ◽  
Linkage Disequilibrium Block ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Coding Region ◽  
Risk Variants ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Long Non Coding Rna

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.

Impaired adhesion of neutrophils expressing Slc44a2/HNA-3b to VWF protects against NETosis under venous shear rate

Blood ◽  
2021 ◽  
Author(s):  
Gaia Zirka ◽  
Philippe Robert ◽  
Julia Tilburg ◽  
Victoria Tishkova ◽  
Chrissta X Maracle ◽  
...  
Keyword(s):  
Transmembrane Protein ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Wild Type ◽  
Shear Rates ◽  
Extracellular Traps ◽  
Genome Wide ◽  
Healthy Donors ◽  
Von Willebrand ◽  
Willebrand Factor

Genome wide association studies linked expression of the human neutrophil antigen 3b (HNA-3b) epitope on the Slc44a2 protein with a 30% decreased risk of venous thrombosis (VT) in humans. Slc44a2 is a ubiquitous transmembrane protein identified as a receptor for Von Willebrand factor (VWF). To explain the link between Slc44a2 and VT we wanted to determine how Slc44a2 expressing either HNA-3a or HNA-3b on neutrophils could modulate their adhesion and activation on VWF under flow. Transfected HEK293T cells or neutrophils homozygous for the HNA-3a- or the HNA-3b-coding allele were purified from healthy donors and perfused in flow chambers coated with VWF at venous shear rates (100s-1). HNA-3a expression was required for Slc44a2-mediated neutrophil adhesion to VWF at 100s-1. This adhesion could occur independently of β2 integrin and was enhanced when neutrophils are preactivated with lipopolysaccharide (LPS). Moreover, specific shear conditions with high neutrophil concentration could act as a "second hit", inducing the formation of neutrophil extracellular traps. Neutrophil mobilization was also measured by intravital microscopy in venules from SLC44A2-knockout and wild-type mice after histamine-induced endothelial degranulation. Mice lacking Slc44a2 showed a massive reduction in neutrophil recruitment in inflamed mesenteric venules. Our results show that Slc44a2/HNA-3a is important for the adhesion and activation of neutrophils in veins under inflammation and when submitted to specific shears. Neutrophils expressing Slc44a2/HNA-3b not being associated with these observations, these results could thus explain the association between HNA-3b and a reduced risk for VT in humans.

scholarly journals Genome-wide association and multi-omic analyses reveal new mechanisms for Heart Failure

2019 ◽  
Author(s):  
Marios Arvanitis ◽  
Yanxiao Zhang ◽  
Wei Wang ◽  
Adam Auton ◽  
Ali Keramati ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cardiac Muscle ◽  
Association Studies ◽  
Meta Analysis ◽  
Regulatory Region ◽  
Causal Variant ◽  
Left Ventricular ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractHeart failure is a major medical and economic burden in the healthcare system affecting over 23 million people worldwide. Although recent pedigree studies estimate heart failure heritability around 26%, genome-wide association studies (GWAS) have had limited success in explaining disease pathogenesis. We conducted the largest meta-analysis of heart failure GWAS to-date and replicated our findings in a comparable sized cohort to identify one known and two novel variants associated with heart failure. Leveraging heart failure sub-phenotyping and fine-mapping, we reveal a putative causal variant found in a cardiac muscle specific regulatory region that binds to the ACTN2 cardiac sarcolemmal gene and affects left ventricular adverse remodeling and clinical heart failure in response to different initial cardiac muscle insults. Via genetic correlation, we show evidence of broadly shared heritability between heart failure and multiple musculoskeletal traits. Our findings extend our understanding of biological mechanisms underlying heart failure.

scholarly journals A unifying framework for summary statistic imputation

2018 ◽  
Author(s):  
Yue Wu ◽  
Eleazar Eskin ◽  
Sriram Sankararaman
Keyword(s):  
Association Studies ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Multivariate Normal ◽  
Summary Statistic ◽  
Computationally Efficient ◽  
Imputation Methods ◽  
Individual Level ◽  
Genome Wide ◽  
Level Data

AbstractImputation has been widely utilized to aid and interpret the results of Genome-Wide Association Studies(GWAS). Imputation can increase the power to identify associations when the causal variant was not directly observed or typed in the GWAS. There are two broad classes of methods for imputation. The first class imputes the genotypes at the untyped variants given the genotypes at the typed variants and then performs a statistical test of association at the imputed variants. The second class of methods, summary statistic imputation, directly imputes the association statics at the untyped variants given the association statistics observed at the typed variants. This second class of methods is appealing as it tends to be computationally efficient while only requiring the summary statistics from a study while the former class requires access to individual-level data that can be difficult to obtain. The statistical properties of these two classes of imputation methods have not been fully understood. In this paper, we show that the two classes of imputation methods are equivalent, i.e., have identical asymptotic multivariate normal distributions with zero mean and minor variations in the covariance matrix, under some reasonable assumptions. Using this equivalence, we can understand the effect of imputation methods on power. We show that a commonly employed modification of summary statistic imputation that we term summary statistic imputation with variance re-weighting generally leads to a loss in power. On the other hand, our proposed method, summary statistic imputation without performing variance re-weighting, fully accounts for imputation uncertainty while achieving better power.

scholarly journals A 16q22.1 variant confers susceptibility to colorectal cancer as a distal regulator of ZFP90

Oncogene ◽  
2019 ◽  
Vol 39 (6) ◽  
pp. 1347-1360
Author(s):  
Chen-Yang Yu ◽  
Ji-Xuan Han ◽  
Junfang Zhang ◽  
Penglei Jiang ◽  
Chaoqin Shen ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Genetic Manipulation ◽  
Association Studies ◽  
Transcript Level ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Single Nucleotide ◽  
Enhancer Element ◽  
Oncogenic Pathways ◽  
Genome Wide

Abstract Genome-wide association studies (GWASs) implicate 16q22.1 locus in risk for colorectal cancer (CRC). However, the underlying oncogenic mechanisms remain unknown. Here, through comprehensive filtration, we prioritized rs7198799, a common SNP in the second intron of the CDH1, as the putative causal variant. In addition, we found an association of CRC-risk allele C of rs7198799 with elevated transcript level of biological plausible candidate gene ZFP90 via expression quantitative trait loci analysis. Mechanistically, causal variant rs7198799 resides in an enhancer element and remotely regulate ZFP90 expression by targeting the transcription factor NFATC2. Remarkably, CRISPR/Cas9-guided single-nucleotide editing demonstrated the direct effect of rs7198799 on ZFP90 expression and CRC cellular malignant phenotype. Furthermore, ZFP90 affects several oncogenic pathways, including BMP4, and promotes carcinogenesis in patients and in animal models with ZFP90 specific genetic manipulation. Taken together, these findings reveal a risk SNP-mediated long-range regulation on the NFATC2-ZFP90-BMP4 pathway underlying the initiation of CRC.

scholarly journals RACER: A data visualization strategy for exploring multiple genetic associations

2018 ◽  
Author(s):  
Olivia L. Sabik ◽  
Charles R. Farber
Keyword(s):  
Association Studies ◽  
Causal Variant ◽  
Visual Exploration ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Genome Wide ◽  
Causal Genes ◽  
Visualization Strategy ◽  
The Relationship

SummaryGenome-wide association studies (GWASs) have identified thousands of loci associated with risk of various diseases; however, the genes responsible for the majority of loci have not been identified. One means of uncovering potential causal genes is the identification of expression quantitative trait loci (eQTL) that colocalize with disease loci. Statistical methods have been developed to assess the likelihood that two associations (e.g. disease locus and eQTL) share a common causal variant, however, visualization of the two loci is often a crucial step in determining if a locus is pleiotropic. While the current convention is to plot two associations side-by-side, it is difficult to compare across two x-axes, even if they are identical. Thus, we have developed the Regional Association ComparER (RACER) package, which creates “mirror plots”, in which the two associations are plotted on a shared x-axis. Mirror plots provide an effective tool for the visual exploration and presentation of the relationship between two genetic associations.Availability and ImplementationRACER is provided under the GNU General Public License version 3 (GPL-3.0). Source code is available at https://github.com/oliviasabik/[email protected] informationSupplementary data are available online with the paper, see the Supplemental Data Manifest.

scholarly journals Discovery and fine-mapping of kidney function loci in first genome-wide association study in Africans

2020 ◽  
Author(s):  
Segun Fatumo ◽  
Tinashe Chikowore ◽  
Robert Kalyesubula ◽  
Rebecca N Nsubuga ◽  
Gershim Asiki ◽  
...  
Keyword(s):  
Kidney Function ◽  
Fine Mapping ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Causal Variant ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractGenome-wide association studies (GWAS) for kidney function have uncovered hundreds of risk loci, primarily in populations of European ancestry. We conducted the first GWAS of estimated glomerular filtration rate (eGFR) in Africa in 3288 Ugandans and replicated the findings in 8224 African Americans. We identified two loci associated with eGFR at genome-wide significance (p<5×10−8). The most significantly associated variant (rs2433603, p=2.4×10−9) in GATM was distinct from previously reported signals. A second association signal mapping near HBB (rs141845179, p=3.0×10−8) was not significant after conditioning on a previously reported SNP (rs334) for eGFR. However, fine-mapping analyses highlighted rs141845179 to be the most likely causal variant at the HBB locus (posterior probability of 0.61). A trans-ethnic GRS of eGFR constructed from previously reported lead SNPs was not predictive into the Ugandan population, indicating that additional large-scale efforts in Africa are necessary to gain further insight into the genetic architecture of kidney disease.

scholarly journals A more accurate method for colocalisation analysis allowing for multiple causal variants

2021 ◽  
Author(s):  
Chris Wallace
Keyword(s):  
Association Studies ◽  
Accurate Method ◽  
Causal Variant ◽  
Genomic Region ◽  
Genome Wide Association Studies ◽  
Novel Approach ◽  
Genome Wide ◽  
Close Proximity ◽  
Regression Framework ◽  
Causal Variants

AbstractIn genome-wide association studies (GWAS) it is now common to search for, and find, multiple causal variants located in close proximity. It has also become standard to ask whether different traits share the same causal variants, but one of the popular methods to answer this question, coloc, makes the simplifying assumption that only a single causal variant exists for any given trait in any genomic region. Here, we examine the potential of the recently proposed Sum of Single Effects (SuSiE) regression framework, which can be used for fine-mapping genetic signals, for use with coloc. SuSiE is a novel approach that allows evidence for association at multiple causal variants to be evaluated simultaneously, whilst separating the statistical support for each variant conditional on the causal signal being considered. We show this results in more accurate coloc inference than other proposals to adapt coloc for multiple causal variants based on conditioning or masking. We therefore recommend that coloc be used in combination with SuSiE to optimise accuracy of colocalisation analyses when multiple causal variants exist.

Data Mining in Genome Wide Association Studies

2011 ◽  
pp. 465-471
Author(s):  
Tom Burr
Keyword(s):  
Data Mining ◽  
Genetic Basis ◽  
Association Studies ◽  
Causal Variant ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Common Diseases ◽  
Genome Wide ◽  
Genomic Regions

The genetic basis for some human diseases, in which one or a few genome regions increase the probability of acquiring the disease, is fairly well understood. For example, the risk for cystic fibrosis is linked to particular genomic regions. Identifying the genetic basis of more common diseases such as diabetes has proven to be more difficult, because many genome regions apparently are involved, and genetic effects are thought to depend in unknown ways on other factors, called covariates, such as diet and other environmental factors (Goldstein and Cavalleri, 2005). Genome-wide association studies (GWAS) aim to discover the genetic basis for a given disease. The main goal in a GWAS is to identify genetic variants, single nucleotide polymorphisms (SNPs) in particular, that show association with the phenotype, such as “disease present” or “disease absent” either because they are causal, or more likely, because they are statistically correlated with an unobserved causal variant (Goldstein and Cavalleri, 2005). A GWAS can analyze “by DNA site” or “by multiple DNA sites. ” In either case, data mining tools (Tachmazidou, Verzilli, and De Lorio, 2007) are proving to be quite useful for understanding the genetic causes for common diseases.

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