scholarly journals miRNAs in NMDA receptor-dependent synaptic plasticity and psychiatric disorders

2016 ◽  
Vol 130 (14) ◽  
pp. 1137-1146 ◽  
Author(s):  
Hongmei Shen ◽  
Zheng Li
Keyword(s):  
Synaptic Plasticity ◽  
Psychiatric Disorders ◽  
Molecular Mechanisms ◽  
Current Knowledge ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Aspartate Receptor ◽  
Genome Wide ◽  
Non Coding Rnas

The identification and functional delineation of miRNAs (a class of small non-coding RNAs) have added a new layer of complexity to our understanding of the molecular mechanisms underlying synaptic plasticity. Genome-wide association studies in conjunction with investigations in cellular and animal models, moreover, provide evidence that miRNAs are involved in psychiatric disorders. In the present review, we examine the current knowledge about the roles played by miRNAs in NMDA (N-methyl-D-aspartate) receptor-dependent synaptic plasticity and psychiatric disorders.

scholarly journals Current knowledge in hypertension genetics: mosaic theory, candidate genes and genome-wide association studies

2020 ◽  
Vol 26 (5) ◽  
pp. 490-500
Author(s):  
A. O. Konradi
Keyword(s):  
Candidate Genes ◽  
High Performance ◽  
New Technologies ◽  
Current Knowledge ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Modern Approach ◽  
Genome Wide

The article reviews monogenic forms of hypertension, data on the role of heredity of essential hypertension and candidate genes, as well as genome-wide association studies. Modern approach for the role of genetics is driven by implementation of new technologies and their productivity. High performance speed of new technologies like genome-wide association studies provide data for better knowledge of genetic markers of hypertension. The major goal nowadays for research is to reveal molecular pathways of blood pressure regulation, which can help to move from populational to individual level of understanding of pathogenesis and treatment targets.

scholarly journals Challenges and progress in interpretation of non-coding genetic variants associated with human disease

2017 ◽  
Vol 242 (13) ◽  
pp. 1325-1334 ◽  
Author(s):  
Yizhou Zhu ◽  
Cagdas Tazearslan ◽  
Yousin Suh
Keyword(s):  
Molecular Mechanisms ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Functional Interpretation ◽  
Genome Wide ◽  
Coding Variants

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.

scholarly journals Multivariate genome-wide association studies on the tissue compartments of human brain identify novel loci underpinning brain development and neuropsychiatric outcomes.

2021 ◽  
Author(s):  
Chun Chieh Fan ◽  
Robert Loughnan ◽  
Diliana Pechva ◽  
Chi-Hua Chen ◽  
Donald Hagler ◽  
...  
Keyword(s):  
Human Brain ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Risk Tolerance ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Imaging Features ◽  
Genome Wide ◽  
Neuropsychiatric Diseases ◽  
Tissue Compartments

It is important to understand the molecular determinants for microstructures of human brain. However, past genome-wide association studies (GWAS) on microstructures of human brain have had limited results due to methodological constraints. Here, we adopt advanced imaging processing methods and multivariate GWAS on two large scale imaging genetic datasets (UK Biobank and Adolescent Brain Cognitive Development study) to identify and validate key genetic association signals. We discovered 503 unique genetic loci that explained more than 50% of the average heritability across imaging features sensitive to tissue compartments. The genome-wide signals are strongly overlapped with neuropsychiatric diseases, cognitive functions, risk tolerance, and immune responses. Our results implicate the shared molecular mechanisms between tissue microstructures of brain and neuropsychiatric outcomes with astrocyte involvement in the early developmental stage.

scholarly journals Genome-wide association analysis reveals extensive genetic overlap between mood instability and psychiatric disorders but divergent patterns of genetic effects

2021 ◽  
Author(s):  
Guy Hindley ◽  
Kevin S O'Connell ◽  
Zillur Rahman ◽  
Oleksandr Frei ◽  
Shahram Bahrami ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Genetic Correlation ◽  
Association Studies ◽  
Single Gene ◽  
Genetic Effects ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Mood Instability ◽  
Genome Wide

Mood instability (MOOD) is a transdiagnostic phenomenon with a prominent neurobiological basis. Recent genome-wide association studies found significant positive genetic correlation between MOOD and major depression (DEP) and weak correlations with other psychiatric disorders. We investigated the polygenic overlap between MOOD and psychiatric disorders beyond genetic correlation to better characterize putative shared genetic determinants. Summary statistics for schizophrenia (SCZ, n=105,318), bipolar disorder (BIP, n=413,466), DEP (n=450,619), attention-deficit hyperactivity disorder (ADHD, n=53,293) and MOOD (n=363,705), were analysed using the bivariate causal mixture model and conjunctional false discovery rate methods to estimate the proportion of shared variants influencing MOOD and each disorder, and identify jointly associated genomic loci. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (rg=0.10-0.62). Of 10.4K genomic variants influencing MOOD, 4K-9.4K were estimated to influence psychiatric disorders. MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25, with consistent genetic effects in independent samples. Fifty-three jointly associated loci were overlapping across two or more disorders (transdiagnostic), seven of which had discordant effect directions on psychiatric disorders. Genes mapped to loci associated with MOOD and all four disorders were enriched in a single gene-set, synapse organization. The extensive polygenic overlap indicates shared molecular underpinnings across MOOD and psychiatric disorders. However, distinct patterns of genetic correlation and effect directions of shared loci suggest divergent effects on corresponding neurobiological mechanisms which may relate to differences in the core clinical features of each disorder.

scholarly journals Dissecting the phenotype in genome-wide association studies of psychiatric illness

2009 ◽  
Vol 195 (2) ◽  
pp. 97-99 ◽  
Keyword(s):  
Psychiatric Disorders ◽  
Psychiatric Illness ◽  
Genetic Architecture ◽  
Association Studies ◽  
Human Diseases ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
The Past ◽  
Genome Wide

SummaryOver the past 2 years genome-wide association studies have made major contributions to understanding the genetic architecture of many common human diseases. This editorial outlines the development of such studies in psychiatry and highlights the opportunities for advancing understanding of the biological underpinnings and nosological structure of psychiatric disorders.

Genetic contributions to anxiety disorders: where we are and where we are heading

2021 ◽  
pp. 1-16
Author(s):  
Helga Ask ◽  
Rosa Cheesman ◽  
Eshim S. Jami ◽  
Daniel F. Levey ◽  
Kirstin L. Purves ◽  
...  
Keyword(s):  
Anxiety Disorders ◽  
Psychiatric Disorders ◽  
Large Scale ◽  
Current Knowledge ◽  
Association Studies ◽  
Twin Studies ◽  
Future Research ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract Anxiety disorders are among the most common psychiatric disorders worldwide. They often onset early in life, with symptoms and consequences that can persist for decades. This makes anxiety disorders some of the most debilitating and costly disorders of our time. Although much is known about the synaptic and circuit mechanisms of fear and anxiety, research on the underlying genetics has lagged behind that of other psychiatric disorders. However, alongside the formation of the Psychiatric Genomic Consortium Anxiety workgroup, progress is rapidly advancing, offering opportunities for future research. Here we review current knowledge about the genetics of anxiety across the lifespan from genetically informative designs (i.e. twin studies and molecular genetics). We include studies of specific anxiety disorders (e.g. panic disorder, generalised anxiety disorder) as well as those using dimensional measures of trait anxiety. We particularly address findings from large-scale genome-wide association studies and show how such discoveries may provide opportunities for translation into improved or new therapeutics for affected individuals. Finally, we describe how discoveries in anxiety genetics open the door to numerous new research possibilities, such as the investigation of specific gene–environment interactions and the disentangling of causal associations with related traits and disorders. We discuss how the field of anxiety genetics is expected to move forward. In addition to the obvious need for larger sample sizes in genome-wide studies, we highlight the need for studies among young people, focusing on specific underlying dimensional traits or components of anxiety.

scholarly journals Inflammation-Related Risk Loci in Genome-Wide Association Studies of Coronary Artery Disease

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 440
Author(s):  
Carina Mauersberger ◽  
Heribert Schunkert ◽  
Hendrik B. Sager
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Genome Wide Association ◽  
Considerable Proportion ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Related Risk ◽  
Artery Disease

Although the importance of inflammation in atherosclerosis is now well established, the exact molecular processes linking inflammation to the development and course of the disease are not sufficiently understood. In this context, modern genetics—as applied by genome-wide association studies (GWAS)—can serve as a comprehensive and unbiased tool for the screening of potentially involved pathways. Indeed, a considerable proportion of loci discovered by GWAS is assumed to affect inflammatory processes. Despite many well-replicated association findings, however, translating genomic hits to specific molecular mechanisms remains challenging. This review provides an overview of the currently most relevant inflammation-related GWAS findings in coronary artery disease and explores their potential clinical perspectives.

scholarly journals Sex Differences in the Genetics of Sarcoidosis Across European and African Ancestry Populations

2021 ◽  
Author(s):  
Ying Xiong ◽  
Susanna Kullberg ◽  
Lori Garman ◽  
Nathan Pezant ◽  
David Ellinghaus ◽  
...  
Keyword(s):  
Sex Differences ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
The United States ◽  
Genetic Variations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
A Genome ◽  
Löfgren’S Syndrome

Abstract Background: Sex differences in the susceptibility of sarcoidosis are unknown. The study aims to identify sex-dependent genetic variations in two sarcoidosis clinical phenotypes: Löfgren's syndrome (LS) and non- Löfgren's syndrome (non-LS).Methods: A meta-analysis of genome-wide association studies was conducted in Europeans and African Americans, totaling 10,103 individuals from three population-based cohorts, Sweden (n = 3,843), Germany (n = 3,342), and the United States (n = 2,918), followed by replication look-up in the UK Biobank (n = 387,945). A genome-wide association study based on Immunochip data consisting of 141,000 single nucleotide polymorphisms (SNPs) was conducted in males and females in each cohort, respectively. The association test was based on logistic regression using the additive model in LS and non-LS independently. Additionally, gene-based analysis, expression quantitative trait loci (eQTL) assessments, and enrichment analysis were performed to discover functionally relevant mechanisms related to biological sex. Results: In LS sarcoidosis, we identified various sex-dependent genetic variations (798 SNPs in males and 703 SNPs in females). Genetic findings in sex groups were explicitly located in the extended major histocompatibility complex. In non-LS, we detected 16 SNPs in males and 38 in females, primarily localized to the MHC class II region. Additionally, the ANXA11 gene, a well-documented locus in sarcoidosis, was associated exclusively with non-LS males. Gene-based, eQTL assessment and enrichment analyses revealed distinct sex-dependent genomic loci and gene expression variation in the sex groups. Conclusions: Our findings provide new evidence of the existence of sex-dependent genetic variations underlying sarcoidosis genetic architecture. These findings suggest a sex bias in molecular mechanisms of sarcoidosis.

scholarly journals FINEMAP: Efficient variable selection using summary data from genome-wide association studies

2015 ◽  
Author(s):  
Christian Benner ◽  
Chris C.A. Spencer ◽  
Samuli Ripatti ◽  
Matti Pirinen
Keyword(s):  
Fine Mapping ◽  
Molecular Mechanisms ◽  
Search Algorithm ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Promising Tool ◽  
Genome Wide ◽  
Genomic Regions ◽  
Summary Data

Motivation: The goal of fine-mapping in genomic regions associated with complex diseases and traits is to identify causal variants that point to molecular mechanisms behind the associations. Recent fine-mapping methods using summary data from genome-wide association studies rely on exhaustive search through all possible causal configurations, which is computationally expensive. Results: We introduce FINEMAP, a software package to efficiently explore a set of the most important causal configurations of the region via a shotgun stochastic search algorithm. We show that FINEMAP produces accurate results in a fraction of processing time of existing approaches and is therefore a promising tool for analyzing growing amounts of data produced in genome-wide association studies. Availability: FINEMAP v1.0 is freely available for Mac OS X and Linux at http://www.christianbenner.com.

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