Network Analysis and Human Single Cell Brain Transcriptomics Reveal Novel Aspects of Alpha-Synuclein (SNCA) Biology

ABSTRACTAlpha-synuclein (SNCA) aggregates are pathological hallmarks of synucleinopathies, neurodegenerative disorders including Parkinson’s Disease (PD) and Lewy Body Dementia (LBD). Functional networks are not yet well-characterized for SNCA by CNS cell type. We investigated cell-specific differences in SNCA expression using Allen Brain Database single-nucleus RNA-seq data from human Middle Temporal Gyrus (MTG, 15,928 nuclei) and Anterior Cingulate Cortex (ACC, 7,258 nuclei). Weighted gene co-expression analysis (WGCNA) and hierarchical clustering identified a conserved SNCA co-expression module. Module genes were highly conserved (p < 10−10) and most highly expressed in excitatory neurons versus inhibitory neurons and other glial cells. SNCA co-expression module genes from ACC and MTG regions were then used to construct a protein-protein interaction (PPI) network, with SNCA empirically top hub. Genes in the SNCA PPI network were compared with genes nearest single nucleotide polymorphisms linked with PD risk in genome-wide association studies. 16 genes in our PPI network are nearest genes to PD risk loci (p < 0.0006) and 55 genes map within 100kb. Selected SNCA PPI network genes nearest PD risk loci were disrupted by CRISPR knock out gene editing for validation of network functional significance; disruption of STK39, GBA, and MBNL2 resulted in significantly elevated intracellular SNCA expression.

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Silencing of the tRNA Modification Enzyme Cdkal1 Effects Functional Insulin Synthesis in NIT-1 Cells: tRNALys3 Lacking ms2- (ms2t6A37) is Unable to Establish Sufficient Anticodon:Codon Interactions to Decode the Wobble Codon AAG

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2020.584228 ◽

2021 ◽

Vol 7 ◽

Author(s):

Amithi Narendran ◽

Sweta Vangaveti ◽

Srivathsan V. Ranganathan ◽

Emily Eruysal ◽

Miranda Craft ◽

...

Keyword(s):

Cell Line ◽

Association Studies ◽

Significant Risk ◽

Genome Wide Association Studies ◽

Trna Modification ◽

Nucleotide Polymorphisms ◽

Insulin Production ◽

Case Control Studies ◽

Knock Out ◽

Insulin Synthesis

Human Genome Wide Association Studies found a significant risk of Type 2 Diabetes Mellitus (T2DM) in single nucleotide polymorphisms in the cdkal1 gene. The cdkal1 gene is remote from the insulin gene and with the surprising function of a specific tRNA modification. Population studies and case control studies acquired evidences of the connection between Cdkal1 protein and insulin production over the years. To obtain biochemical proofs directly linking potential SNPs to their roles in insulin production and availability is challenging, but the development of Cdkal1 knock out mice and knock out cell lines made it possible to extend our knowledge towards therapeutic field of diabetic research. Supporting the evidences, here we show that knock down of the cdkal1 gene using small interfering and short hairpin RNA in the NIT-1 cell line, a β-cell line inducible for insulin resulted in reduced levels of cdkal1 and mature insulin mRNAs, increased the level of precursor insulin mRNA, decreased Cdkal1 and insulin proteins, and diminished modification of tRNALys3 from t6A37 to ms2t6A37, the specified function of Cdkal1. tRNALys3 lacking ms2- is incapable of establishing sufficient hydrogen bonding energy and hydrophobic stabilization to decode the wobble codon AAG.

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Multivariate Analysis of Potential Pleiotropic Genes For Breast, Ovarian And Cervical Cancers Using Gene-Based Association Analysis

10.21203/rs.3.rs-695526/v1 ◽

2021 ◽

Author(s):

XiaoCan Jia ◽

Nian Shi ◽

Yu Feng ◽

Huili Zhu ◽

Yuping Wang ◽

...

Keyword(s):

Network Analysis ◽

Association Studies ◽

Statistical Significance ◽

Enrichment Analysis ◽

Biological Pathways ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Ppi Network ◽

Cervical Cancers ◽

Protein Protein Interaction

Abstract Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery in gynecological malignancies, the single nucleotide polymorphisms (SNPs) identified by this prevailing univariate approach only explain a small percentage of heredity. The extensive previous studies have repeatedly shown breast, ovarian and cervical cancers have common genetic mechanisms and the overlapping pathophysiological pathways. Novel multivariate analytical methods are necessary to identify shared pleiotropic genes. In this study, a total of 40,859 SNPs mapped in 11,597 gene regions were performed to identify potential common variants by using metaCCA and VEGAS2 analysis. Gene enrichment and protein-protein interaction (PPI) network analysis were used to explore potential biological pathways and connectivity. After metaCCA analysis, 4,203 SNPs (P<1.22×10−6) and 1,886 pleotropic gene (P<4.31×10−6) were identified. By screening the results of gene-based P-values, the existence of 3 confirmed pleiotropic genes and 16 novel genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one cancer in the VEGAS2 analysis were identified. The enrichment analysis showed the biological pathways of these genes were mainly enriched in 4 signaling pathways and 11 differentially expressed genes were found to encode interacting proteins in PPI network analysis. Altogether, we identified novel genetic variants of breast, ovarian and cervical cancers and provided evidence of biological functions which developed new insights for the diagnosis and treatment of these cancers.

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Causal Association between Periodontitis and Parkinson’s Disease: A Bidirectional Mendelian Randomization Study

Genes ◽

10.3390/genes12050772 ◽

2021 ◽

Vol 12 (5) ◽

pp. 772

Author(s):

João Botelho ◽

Vanessa Machado ◽

José João Mendes ◽

Paulo Mascarenhas

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Instrumental Variables ◽

Mendelian Randomization ◽

Association Studies ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Genetic Liability ◽

Bidirectional Association

The latest evidence revealed a possible association between periodontitis and Parkinson’s disease (PD). We explored the causal relationship of this bidirectional association through two-sample Mendelian randomization (MR) in European ancestry populations. To this end, we used openly accessible data of genome-wide association studies (GWAS) on periodontitis and PD. As instrumental variables for periodontitis, seventeen single-nucleotide polymorphisms (SNPs) from a GWAS of periodontitis (1817 periodontitis cases vs. 2215 controls) and eight non-overlapping SNPs of periodontitis from an additional GWAS for validation purposes. Instrumental variables to explore for the reverse causation included forty-five SNPs from a GWAS of PD (20,184 cases and 397,324 controls). Multiple approaches of MR were carried-out. There was no evidence of genetic liability of periodontitis being associated with a higher risk of PD (B = −0.0003, Standard Error [SE] 0.0003, p = 0.26). The eight independent SNPs (B = −0.0000, SE 0.0001, p = 0.99) validated this outcome. We also found no association of genetically primed PD towards periodontitis (B = −0.0001, SE 0.0001, p = 0.19). These MR study findings do not support a bidirectional causal genetic liability between periodontitis and PD. Further GWAS studies are needed to confirm the consistency of these results.

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Pharmacogenomics of Lithium Response in Bipolar Disorder

Pharmaceuticals ◽

10.3390/ph14040287 ◽

2021 ◽

Vol 14 (4) ◽

pp. 287

Author(s):

Courtney M. Vecera ◽

Gabriel R. Fries ◽

Lokesh R. Shahani ◽

Jair C. Soares ◽

Rodrigo Machado-Vieira

Keyword(s):

Bipolar Disorder ◽

Association Studies ◽

Mood Stabilizer ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Non Coding Rna ◽

Genome Wide ◽

Lithium Response ◽

Genetic Loading ◽

Long Non Coding Rna

Despite being the most widely studied mood stabilizer, researchers have not confirmed a mechanism for lithium’s therapeutic efficacy in Bipolar Disorder (BD). Pharmacogenomic applications may be clinically useful in the future for identifying lithium-responsive patients and facilitating personalized treatment. Six genome-wide association studies (GWAS) reviewed here present evidence of genetic variations related to lithium responsivity and side effect expression. Variants were found on genes regulating the glutamate system, including GAD-like gene 1 (GADL1) and GRIA2 gene, a mutually-regulated target of lithium. In addition, single nucleotide polymorphisms (SNPs) discovered on SESTD1 may account for lithium’s exceptional ability to permeate cell membranes and mediate autoimmune and renal effects. Studies also corroborated the importance of epigenetics and stress regulation on lithium response, finding variants on long, non-coding RNA genes and associations between response and genetic loading for psychiatric comorbidities. Overall, the precision medicine model of stratifying patients based on phenotype seems to derive genotypic support of a separate clinical subtype of lithium-responsive BD. Results have yet to be expounded upon and should therefore be interpreted with caution.

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Investigation of gene–environment interactions in relation to tic severity

Journal of Neural Transmission ◽

10.1007/s00702-021-02396-y ◽

2021 ◽

Author(s):

Mohamed Abdulkadir ◽

Dongmei Yu ◽

Lisa Osiecki ◽

Robert A. King ◽

Thomas V. Fernandez ◽

...

Keyword(s):

Tourette Syndrome ◽

Association Studies ◽

Autism Spectrum ◽

Environment Interaction ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Linear Regression Models ◽

Compulsive Disorder ◽

Gene Environment ◽

Tic Severity

AbstractTourette syndrome (TS) is a neuropsychiatric disorder with involvement of genetic and environmental factors. We investigated genetic loci previously implicated in Tourette syndrome and associated disorders in interaction with pre- and perinatal adversity in relation to tic severity using a case-only (N = 518) design. We assessed 98 single-nucleotide polymorphisms (SNPs) selected from (I) top SNPs from genome-wide association studies (GWASs) of TS; (II) top SNPs from GWASs of obsessive–compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD); (III) SNPs previously implicated in candidate-gene studies of TS; (IV) SNPs previously implicated in OCD or ASD; and (V) tagging SNPs in neurotransmitter-related candidate genes. Linear regression models were used to examine the main effects of the SNPs on tic severity, and the interaction effect of these SNPs with a cumulative pre- and perinatal adversity score. Replication was sought for SNPs that met the threshold of significance (after correcting for multiple testing) in a replication sample (N = 678). One SNP (rs7123010), previously implicated in a TS meta-analysis, was significantly related to higher tic severity. We found a gene–environment interaction for rs6539267, another top TS GWAS SNP. These findings were not independently replicated. Our study highlights the future potential of TS GWAS top hits in gene–environment studies.

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Transcriptional Regulation of RUNX1: An Informatics Analysis

Genes ◽

10.3390/genes12081175 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1175

Author(s):

Amarni L. Thomas ◽

Judith Marsman ◽

Jisha Antony ◽

William Schierding ◽

Justin M. O’Sullivan ◽

...

Keyword(s):

Association Studies ◽

Regulatory Elements ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Genome Wide ◽

Runx1 Gene ◽

Gene Regulatory Elements ◽

Important Regulator ◽

Aml1 Gene ◽

Regulatory Landscape

The RUNX1/AML1 gene encodes a developmental transcription factor that is an important regulator of haematopoiesis in vertebrates. Genetic disruptions to the RUNX1 gene are frequently associated with acute myeloid leukaemia. Gene regulatory elements (REs), such as enhancers located in non-coding DNA, are likely to be important for Runx1 transcription. Non-coding elements that modulate Runx1 expression have been investigated over several decades, but how and when these REs function remains poorly understood. Here we used bioinformatic methods and functional data to characterise the regulatory landscape of vertebrate Runx1. We identified REs that are conserved between human and mouse, many of which produce enhancer RNAs in diverse tissues. Genome-wide association studies detected single nucleotide polymorphisms in REs, some of which correlate with gene expression quantitative trait loci in tissues in which the RE is active. Our analyses also suggest that REs can be variant in haematological malignancies. In summary, our analysis identifies features of the RUNX1 regulatory landscape that are likely to be important for the regulation of this gene in normal and malignant haematopoiesis.

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Common genetic variants with fetal effects on birth weight are enriched for proximity to genes implicated in rare developmental disorders

Human Molecular Genetics ◽

10.1093/hmg/ddab060 ◽

2021 ◽

Author(s):

Robin N Beaumont ◽

Isabelle K Mayne ◽

Rachel M Freathy ◽

Caroline F Wright

Keyword(s):

Birth Weight ◽

Statistical Power ◽

Developmental Disorders ◽

Association Studies ◽

Later Life ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Genome Wide ◽

Common Genetic Variants ◽

Causal Genes

Abstract Birth weight is an important factor in newborn survival; both low and high birth weights are associated with adverse later-life health outcomes. Genome-wide association studies (GWAS) have identified 190 loci associated with maternal or fetal effects on birth weight. Knowledge of the underlying causal genes is crucial to understand how these loci influence birth weight and the links between infant and adult morbidity. Numerous monogenic developmental syndromes are associated with birth weights at the extreme ends of the distribution. Genes implicated in those syndromes may provide valuable information to prioritize candidate genes at the GWAS loci. We examined the proximity of genes implicated in developmental disorders (DDs) to birth weight GWAS loci using simulations to test whether they fall disproportionately close to the GWAS loci. We found birth weight GWAS single nucleotide polymorphisms (SNPs) fall closer to such genes than expected both when the DD gene is the nearest gene to the birth weight SNP and also when examining all genes within 258 kb of the SNP. This enrichment was driven by genes causing monogenic DDs with dominant modes of inheritance. We found examples of SNPs in the intron of one gene marking plausible effects via different nearby genes, highlighting the closest gene to the SNP not necessarily being the functionally relevant gene. This is the first application of this approach to birth weight, which has helped identify GWAS loci likely to have direct fetal effects on birth weight, which could not previously be classified as fetal or maternal owing to insufficient statistical power.

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A nonparametric test for association with multiple loci in the retrospective case-control study

Statistical Methods in Medical Research ◽

10.1177/0962280219842892 ◽

2019 ◽

Vol 29 (2) ◽

pp. 589-602

Author(s):

Chan Wang ◽

Shufang Deng ◽

Leiming Sun ◽

Liming Li ◽

Yue-Qing Hu

Keyword(s):

Rare Variants ◽

Association Studies ◽

Nonparametric Test ◽

Case Control ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Retrospective Case ◽

Multiple Loci ◽

Common Diseases ◽

The Difference

The genome-wide association studies aim at identifying common or rare variants associated with common diseases and explaining more heritability. It is well known that common diseases are influenced by multiple single nucleotide polymorphisms (SNPs) that are usually correlated in location or function. In order to powerfully detect association signals, it is highly desirable to take account of correlations or linkage disequilibrium (LD) information among multiple SNPs in testing for association. In this article, we propose a test SLIDE that depicts the difference of the average multi-locus genotypes between cases and controls and derive its variance–covariance matrix in the retrospective design. This matrix is composed of the pairwise LD between SNPs. Thus SLIDE can borrow the strength from an external database in the population of interest with a few thousands to hundreds of thousands individuals to improve the power for detecting association. Extensive simulations show that SLIDE has apparent superiority over the existing methods, especially in the situation involving both common and rare variants, both protective and deleterious variants. Furthermore, the efficiency of the proposed method is demonstrated in the application to the data from the Wellcome Trust Case Control Consortium.

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Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2016.0569 ◽

2016 ◽

Vol 283 (1835) ◽

pp. 20160569 ◽

Cited By ~ 52

Author(s):

M. E. Goddard ◽

K. E. Kemper ◽

I. M. MacLeod ◽

A. J. Chamberlain ◽

B. J. Hayes

Keyword(s):

Complex Traits ◽

Genetic Architecture ◽

Quantitative Traits ◽

Association Studies ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Crop Breeding ◽

Single Nucleotide ◽

Genome Wide ◽

Phenotype Identification

Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.

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Upregulation of c-MYC in cis through a Large Chromatin Loop Linked to a Cancer Risk-Associated Single-Nucleotide Polymorphism in Colorectal Cancer Cells

Molecular and Cellular Biology ◽

10.1128/mcb.01384-09 ◽

2010 ◽

Vol 30 (6) ◽

pp. 1411-1420 ◽

Cited By ~ 177

Author(s):

Jason B. Wright ◽

Seth J. Brown ◽

Michael D. Cole

Keyword(s):

Cancer Risk ◽

Cancer Cells ◽

Association Studies ◽

Beta Catenin ◽

Genome Wide Association Studies ◽

Chromatin Loop ◽

Nucleotide Polymorphisms ◽

Distal Enhancer ◽

Enhancer Activity ◽

Single Nucleotide

ABSTRACT Genome-wide association studies have mapped many single-nucleotide polymorphisms (SNPs) that are linked to cancer risk, but the mechanism by which most SNPs promote cancer remains undefined. The rs6983267 SNP at 8q24 has been associated with many cancers, yet the SNP falls 335 kb from the nearest gene, c-MYC. We show that the beta-catenin-TCF4 transcription factor complex binds preferentially to the cancer risk-associated rs6983267(G) allele in colon cancer cells. We also show that the rs6983267 SNP has enhancer-related histone marks and can form a 335-kb chromatin loop to interact with the c-MYC promoter. Finally, we show that the SNP has no effect on the efficiency of chromatin looping to the c-MYC promoter but that the cancer risk-associated SNP enhances the expression of the linked c-MYC allele. Thus, cancer risk is a direct consequence of elevated c-MYC expression from increased distal enhancer activity and not from reorganization/creation of the large chromatin loop. The findings of these studies support a mechanism for intergenic SNPs that can promote cancer through the regulation of distal genes by utilizing preexisting large chromatin loops.

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