Post-GWAS knowledge gap: the how, where, and when

Abstract Genetic risk for complex diseases very rarely reflects only Mendelian-inherited phenotypes where single-gene mutations can be followed in families by linkage analysis. More commonly, a large set of low-penetrance, small effect-size variants combine to confer risk; they are normally revealed in genome-wide association studies (GWAS), which compare large population groups. Whereas Mendelian inheritance points toward disease mechanisms arising from the mutated genes, in the case of GWAS signals, the effector proteins and even general risk mechanism are mostly unknown. Instead, the utility of GWAS currently lies primarily in predictive and diagnostic information. Although an amazing body of GWAS-based knowledge now exists, we advocate for more funding towards the exploration of the fundamental biology in post-GWAS studies; this research will bring us closer to causality and risk gene identification. Using Parkinson’s Disease as an example, we ask, how, where, and when do risk loci contribute to disease?

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Genetics and Management of the Patient with Orofacial Cleft

Plastic Surgery International ◽

10.1155/2012/782821 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 5

Author(s):

Luciano Abreu Brito ◽

Joanna Goes Castro Meira ◽

Gerson Shigeru Kobayashi ◽

Maria Rita Passos-Bueno

Keyword(s):

Cleft Lip ◽

Association Studies ◽

Single Gene ◽

Gene Mutations ◽

Deletion Syndrome ◽

Genome Wide Association Studies ◽

Genetic Causes ◽

Complex Disorder ◽

Facial Defect ◽

Genome Wide

Cleft lip or palate (CL/P) is a common facial defect present in 1 : 700 live births and results in substantial burden to patients. There are more than 500 CL/P syndromes described, the causes of which may be single-gene mutations, chromosomopathies, and exposure to teratogens. Part of the most prevalent syndromic CL/P has known etiology. Nonsyndromic CL/P, on the other hand, is a complex disorder, whose etiology is still poorly understood. Recent genome-wide association studies have contributed to the elucidation of the genetic causes, by raising reproducible susceptibility genetic variants; their etiopathogenic roles, however, are difficult to predict, as in the case of the chromosomal region 8q24, the most corroborated locus predisposing to nonsyndromic CL/P. Knowing the genetic causes of CL/P will directly impact the genetic counseling, by estimating precise recurrence risks, and the patient management, since the patient, followup may be partially influenced by their genetic background. This paper focuses on the genetic causes of important syndromic CL/P forms (van der Woude syndrome, 22q11 deletion syndrome, and Robin sequence-associated syndromes) and depicts the recent findings in nonsyndromic CL/P research, addressing issues in the conduct of the geneticist.

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Genetics and pain in childhood

Oxford Textbook of Pediatric Pain ◽

10.1093/med/9780198818762.003.0009 ◽

2021 ◽

pp. 79-86

Author(s):

Jeffrey S. Mogil

Keyword(s):

Candidate Gene ◽

Association Studies ◽

Single Gene ◽

Gene Mutations ◽

Twin Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Pediatric Pain ◽

Genome Wide ◽

Pediatric Populations

Genomic and other “omic” approaches are now routinely applied to the study of pain. Some of these investigations have utilized pediatric populations. This review describes what is currently known about the heritability of pain in children (from twin studies), genes relevant to pain in children (from single-gene mutations, candidate gene, and genome-wide association studies), and the application of newer techniques, such as epigenomics, to pediatric pain.

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Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases

10.1101/2020.09.08.20190561 ◽

2020 ◽

Cited By ~ 1

Author(s):

Elle M Weeks ◽

Jacob C Ulirsch ◽

Nathan Y Cheng ◽

Brian L Trippe ◽

Rebecca S Fine ◽

...

Keyword(s):

Complex Traits ◽

Association Studies ◽

Gene Prioritization ◽

Protein Interaction Data ◽

Large Set ◽

Genome Wide Association Studies ◽

Protein Protein Interaction ◽

Genome Wide ◽

Causal Genes ◽

Red Blood Cell Count

Genome-wide association studies (GWAS) are a valuable tool for understanding the biology of complex traits, but the associations found rarely point directly to causal genes. Here, we introduce a new method to identify the causal genes by integrating GWAS summary statistics with gene expression, biological pathway, and predicted protein-protein interaction data. We further propose an approach that effectively leverages both polygenic and locus-specific genetic signals by combining results across multiple gene prioritization methods, increasing confidence in prioritized genes. Using a large set of gold standard genes to evaluate our approach, we prioritize 8,402 unique gene-trait pairs with greater than 75% estimated precision across 113 complex traits and diseases, including known genes such as SORT1 for LDL cholesterol, SMIM1 for red blood cell count, and DRD2 for schizophrenia, as well as novel genes such as TTC39B for cholelithiasis. Our results demonstrate that a polygenic approach is a powerful tool for gene prioritization and, in combination with locus-specific signal, improves upon existing methods.

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Genetic Data Analysis

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning - Advances in Medical Diagnosis, Treatment, and Care ◽

10.4018/978-1-7998-2742-9.ch017 ◽

2021 ◽

pp. 358-372

Author(s):

M. Shamila ◽

Amit Kumar Tyagi

Keyword(s):

Data Analysis ◽

Association Studies ◽

Single Gene ◽

Genetic Data ◽

Building Blocks ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Human Beings ◽

Genome Wide ◽

Genetic Data Analysis

Genome-wide association studies (GWAS) or genetic data analysis is used to discover common genetic factors which influence the health of human beings and become a part of a disease. The concept of using genomics has increased in recent years, especially in e-healthcare. Today there is huge improvement required in this field or genomics. Note that the terms genomics and genetics are not similar terms here. Basically, the human genome is made up of DNA, which consists of four different chemical building blocks (called bases and abbreviated A, T, C, and G). Based on this, we differentiate each and every human being living on earth. The term ‘genetics' originated from the Greek word ‘genetikos'. It means ‘origin'. In simple terms, genetics can be defined as a branch of biology, which deals with the study of the functionalities and composition of a single gene in an organism. There are mainly three branches of genetics, which include classical genetics, molecular genetics, and population genetics.

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Genomic Variations in Susceptibility to Intracranial Aneurysm in the Korean Population

Journal of Clinical Medicine ◽

10.3390/jcm8020275 ◽

2019 ◽

Vol 8 (2) ◽

pp. 275 ◽

Cited By ~ 8

Author(s):

Eun Hong ◽

Bong Kim ◽

Steve Cho ◽

Jin Yang ◽

Hyuk Choi ◽

...

Keyword(s):

Intracranial Aneurysm ◽

Association Studies ◽

Large Population ◽

Genome Wide Association ◽

Korean Population ◽

Genome Wide Association Studies ◽

Medicine Research ◽

Genome Wide ◽

A Genome ◽

Significant Difference

Genome-wide association studies found genetic variations with modulatory effects for intracranial aneurysm (IA) formations in European and Japanese populations. We aimed to identify the susceptibility of single nucleotide polymorphisms (SNPs) to IA in a Korean population consisting of 250 patients, and 294 controls using the Asian-specific Axiom Precision Medicine Research Array. Twenty-nine SNPs reached a genome-wide significance threshold (5 × 10−8). The rs371331393 SNP, with a stop-gain function of ARHGAP32 (11q24.3), showed the most significant association with the risk of IA (OR = 43.57, 95% CI: 21.84–86.95; p = 9.3 × 10−27). Eight out of 29 SNPs—GBA (rs75822236), TCF24 (rs112859779), OLFML2A (rs79134766), ARHGAP32 (rs371331393), CD163L1 (rs138525217), CUL4A (rs74115822), LOC102724084 (rs75861150), and LRRC3 (rs116969723)—demonstrated sufficient statistical power greater than or equal to 0.8. Two previously reported SNPs, rs700651 (BOLL, 2q33.1) and rs6841581 (EDNRA, 4q31.22), were validated in our GWAS (Genome-wide association study). In a subsequent analysis, three SNPs showed a significant difference in expressions: the rs6741819 (RNF144A, 2p25.1) was down-regulated in the adrenal gland tissue (p = 1.5 × 10−6), the rs1052270 (TMOD1. 9q22.33) was up-regulated in the testis tissue (p = 8.6 × 10−10), and rs6841581 (EDNRA, 4q31.22) was up-regulated in both the esophagus (p = 5.2 × 10−12) and skin tissues (1.2 × 10−6). Our GWAS showed novel candidate genes with Korean-specific variations in IA formations. Large population based studies are thus warranted.

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The genetics of axial spondyloarthritis

10.1093/med/9780198755296.003.0004 ◽

2016 ◽

Author(s):

Stefan Siebert ◽

Sengupta Raj ◽

Alexander Tsoukas

Keyword(s):

Axial Spondyloarthritis ◽

Association Studies ◽

Single Gene ◽

Twin Studies ◽

Genome Wide Association Studies ◽

Functional Importance ◽

Unfolded Protein ◽

Genome Wide ◽

Arthritogenic Peptide ◽

Protein Response

Family and twin studies have long suggested a large genetic component in ankylosing spondylitis (AS). The genetic association with HLA-B27 remains one of the strongest single gene variant associations reported in any complex polygenic disease. The exact mechanism by which HLA-B27 contributes to AS remains unknown, with three main theories proposed: the arthritogenic peptide, endoplasmic reticulum stress with unfolded protein response, and homodimerization theories. Genome-wide association studies have identified a number of other important susceptibility genes for AS, several of which overlap with other spondyloarthritis conditions. Of these, ERAP1 and IL-23R, are covered in more detail, highlighting their functional importance.

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Molecular Variants in Human Trace Amine-Associated Receptors and Their Implications in Mental and Metabolic Disorders

Cellular and Molecular Neurobiology ◽

10.1007/s10571-019-00743-y ◽

2019 ◽

Vol 40 (2) ◽

pp. 239-255 ◽

Cited By ~ 3

Author(s):

Grazia Rutigliano ◽

Riccardo Zucchi

Keyword(s):

Genetic Variants ◽

Affective Disorders ◽

Metabolic Disorders ◽

Association Studies ◽

Single Gene ◽

Genome Wide Association Studies ◽

Complex Disorders ◽

Linkage Analyses ◽

Genome Wide ◽

Trace Amine

Abstract We provide a comprehensive review of the available evidence on the pathophysiological implications of genetic variants in the human trace amine-associated receptor (TAAR) superfamily. Genes coding for trace amine-associated receptors (taars) represent a multigene family of G-protein-coupled receptors, clustered to a small genomic region of 108 kb located in chromosome 6q23, which has been consistently identified by linkage analyses as a susceptibility locus for schizophrenia and affective disorders. Most TAARs are expressed in brain areas involved in emotions, reward and cognition. TAARs are activated by endogenous trace amines and thyronamines, and evidence for a modulatory action on other monaminergic systems has been reported. Therefore, linkage analyses were followed by fine mapping association studies in schizophrenia and affective disorders. However, none of these reports has received sufficient universal replication, so their status remains uncertain. Single nucleotide polymorphisms in taars have emerged as susceptibility loci from genome-wide association studies investigating migraine and brain development, but none of the detected variants reached the threshold for genome-wide significance. In the last decade, technological advances enabled single-gene or whole-exome sequencing, thus allowing the detection of rare genetic variants, which may have a greater impact on the risk of complex disorders. Using these approaches, several taars (especially taar1) variants have been detected in patients with mental and metabolic disorders, and in some cases, defective receptor function has been demonstrated in vitro. Finally, with the use of transcriptomic and peptidomic techniques, dysregulations of TAARs (especially TAAR6) have been identified in brain disorders characterized by cognitive impairment.

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On the Number of Siblings and p-th Cousins in a Large Population Sample

10.1101/145599 ◽

2017 ◽

Cited By ~ 5

Author(s):

Vladimir Shchur ◽

Rasmus Nielsen

Keyword(s):

Association Studies ◽

Large Population ◽

Population Sample ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Asymptotic Expressions ◽

Fisher Model ◽

Sampling Fraction ◽

Close Relatives ◽

Number Of Individuals

1.AbstractThe number of individuals in a random sample with close relatives in the sample is a quantity of interest when designing Genome Wide Association Studies (GWAS) and other cohort based genetic, and non-genetic, studies. In this paper, we develop expressions for the distribution and expectation of the number of p-th cousins in a sample from a population of size N under two diploid Wright-Fisher models. We also develop simple asymptotic expressions for large values of N. For example, the expected proportion of individuals with at least one p-th cousin in a sample of K individuals, for a diploid dioecious Wright-Fisher model, is approximately 1 − e−(22p−1)K/N. Our results show that a substantial fraction of individuals in the sample will have at least a second cousin if the sampling fraction (K/N) is on the order of 10−2. This confirms that, for large cohort samples, relatedness among individuals cannot easily be ignored.

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

10.1101/2021.07.16.21260608 ◽

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.

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VarGen: an R package for disease-associated variant discovery and annotation

Bioinformatics ◽

10.1093/bioinformatics/btz930 ◽

2019 ◽

Vol 36 (8) ◽

pp. 2626-2627

Author(s):

Corentin Molitor ◽

Matt Brember ◽

Fady Mohareb

Keyword(s):

Association Studies ◽

Genetic Disorders ◽

R Package ◽

Tissue Expression ◽

Mendelian Inheritance ◽

Supplementary Information ◽

Genome Wide Association Studies ◽

Variant Discovery ◽

Genome Wide ◽

High Quality Information

Abstract Summary Over the past decade, there has been an exponential increase in the amount of disease-related genomic data available in public databases. However, this high-quality information is spread across independent sources and researchers often need to access these separately. Hence, there is a growing need for tools that gather and compile this information in an easy and automated manner. Here, we present ‘VarGen’, an easy-to-use, customizable R package that fetches, annotates and rank variants related to diseases and genetic disorders, using a collection public databases (viz. Online Mendelian Inheritance in Man, the Functional Annotation of the Mammalian genome 5, the Genotype-Tissue Expression and the Genome Wide Association Studies catalog). This package is also capable of annotating these variants to identify the most impactful ones. We expect that this tool will benefit the research of variant-disease relationships. Availability and implementation VarGen is open-source and freely available via GitHub: https://github.com/MCorentin/VarGen. The software is implemented as an R package and is supported on Linux, MacOS and Windows. Supplementary information Supplementary data are available at Bioinformatics online.

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