Migraine, Human Genetics and a Passion for Science

2020 ◽  
Vol 23 (2) ◽  
pp. 105-106
Author(s):  
Dale R. Nyholt
Keyword(s):  
Genetic Architecture ◽  
Latent Class ◽  
Human Genetics ◽  
Polygenic Risk Score ◽  
Association Analyses ◽  
Polygenic Risk ◽  
The Past ◽  
Risk Variants ◽  
Genome Wide ◽  
Wide Range

AbstractThis note reflects on my collaborations with Nick Martin and the GenEpi group over the past 20 years. Over the past two decades, our work together has focused on gene mapping and understanding the genetic architecture of a wide range of traits with particular foci on migraine and common baldness. Our migraine research has included latent class and twin analyses cumulating in genome-wide association analyses which had identified 44 (34 new) risk variants for migraine. Leveraging these results through polygenic risk score analyses identified subgroups of patients likely to respond to triptans (an acute migraine drug), providing the first step toward precision medicine in migraine [Kogelman et al. (2019) Neurology Genetics, 5, e364].

scholarly journals Role of Common Genetic Variants for Drug-Resistance to Specific Anti-Seizure Medications

2021 ◽  
Vol 12 ◽  
Author(s):  
Stefan Wolking ◽  
Ciarán Campbell ◽  
Caragh Stapleton ◽  
Mark McCormack ◽  
Norman Delanty ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Genetic Variants ◽  
Neuropsychiatric Disorders ◽  
Polygenic Risk Score ◽  
Specific Response ◽  
Association Analyses ◽  
Polygenic Risk ◽  
Risk Variants ◽  
Genome Wide ◽  
Common Genetic Variants

Objective: Resistance to anti-seizure medications (ASMs) presents a significant hurdle in the treatment of people with epilepsy. Genetic markers for resistance to individual ASMs could support clinicians to make better-informed choices for their patients. In this study, we aimed to elucidate whether the response to individual ASMs was associated with common genetic variation.Methods: A cohort of 3,649 individuals of European descent with epilepsy was deeply phenotyped and underwent single nucleotide polymorphism (SNP)-genotyping. We conducted genome-wide association analyses (GWASs) on responders to specific ASMs or groups of functionally related ASMs, using non-responders as controls. We performed a polygenic risk score (PRS) analyses based on risk variants for epilepsy and neuropsychiatric disorders and ASM resistance itself to delineate the polygenic burden of ASM-specific drug resistance.Results: We identified several potential regions of interest but did not detect genome-wide significant loci for ASM-specific response. We did not find polygenic risk for epilepsy, neuropsychiatric disorders, and drug-resistance associated with drug response to specific ASMs or mechanistically related groups of ASMs.Significance: This study could not ascertain the predictive value of common genetic variants for ASM responder status. The identified suggestive loci will need replication in future studies of a larger scale.

scholarly journals Polygenic Risk Score of Sporadic late Onset Alzheimer Disease Reveals a Shared Architecture with the Familial and Early Onset Forms

2017 ◽  
Author(s):  
Jorge L Del-Aguila ◽  
Benjamin Saef ◽  
Kathleen Black ◽  
Maria Victoria Fernandez ◽  
John Budde ◽  
...  
Keyword(s):  
Early Onset ◽  
Genetic Architecture ◽  
Late Onset ◽  
Age At Onset ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Risk Variants ◽  
Genome Wide ◽  
Load Risk

AbstractObjective:To determine whether the genetic architecture of sporadic late-onset Alzheimer’s Disease (sLOAD) has an effect on familial late-onset AD (fLOAD), sporadic early-onset (sEOAD) and autosomal dominant early-onset (eADAD).Methods:Polygenic risk scores (PRS) were constructed using previously identified 21 genome-wide significant loci for LOAD risk.Results:We found that there is an overlap in the genetic architecture among sEOAD, fLOAD, and sLOAD. sEOAD showed the highest odds for the PRS (OR=2.27; p=1.29×10-7), followed by fLOAD (OR=1.75; p=1.12×10-7) and sLOAD (OR=1.40; p=1.21×10-3). PRS is associated with cerebrospinal fluid ptau181-Aβ42on eADAD.Conclusion:Our analysis confirms that the genetic factors identified for sLOAD also modulate risk in fLOAD and sEOAD cohorts. Furthermore, our results suggest that the burden of these risk variants is associated with familial clustering and earlier-onset of AD. Although these variants are not associated with risk in the eADAD, they may be modulating age at onset.

scholarly journals Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

2018 ◽  
Vol 50 (5) ◽  
pp. 668-681 ◽  
Author(s):  
Naomi R. Wray ◽  
◽  
Stephan Ripke ◽  
Manuel Mattheisen ◽  
Maciej Trzaskowski ◽  
...  
Keyword(s):  
Major Depression ◽  
Genetic Architecture ◽  
Genome Wide Association ◽  
Association Analyses ◽  
Risk Variants ◽  
Genome Wide

scholarly journals A polygenic risk score for multiple myeloma risk prediction

2021 ◽  
Author(s):  
Federico Canzian ◽  
Chiara Piredda ◽  
Angelica Macauda ◽  
Daria Zawirska ◽  
Niels Frost Andersen ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Risk Score ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Epidemiologic Evidence ◽  
Risk Variants ◽  
Genome Wide ◽  
Weighted Score

AbstractThere is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53–4.69, p = 3.55 × 10−15 for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34–4.33, p = 1.62 × 10−13 for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.

scholarly journals Global genetic heterogeneity in adaptive traits

2021 ◽  
Author(s):  
William Andres Lopez-Arboleda ◽  
Stephan Reinert ◽  
Magnus Nordborg ◽  
Arthur Korte
Keyword(s):  
Genetic Heterogeneity ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Human Genetics ◽  
Association Studies ◽  
Local Environment ◽  
Genome Wide Association Studies ◽  
Major Objective ◽  
Genome Wide ◽  
Wide Range

AbstractUnderstanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS for a variety of phenotypes in the model plant species Arabididopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, while others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be incredibly sensitive to sampling and population structure.

scholarly journals Elucidating the Joint Genetic Architecture of Mood Disorder and Schizophrenia

2020 ◽  
Author(s):  
Max Lam ◽  
Meiling Thompson ◽  
Baijia Li ◽  
Alexis C Edwards ◽  
Chia-Yen Chen ◽  
...  
Keyword(s):  
Mood Disorder ◽  
Genetic Architecture ◽  
East Asian ◽  
Genetic Correlations ◽  
Chromatin Interaction ◽  
Polygenic Risk Score ◽  
Eqtl Analysis ◽  
European Descent ◽  
Polygenic Risk ◽  
Genome Wide

Introduction: Recent advances in psychiatric genomics have enabled large-scale genome-wide scans that elucidated genetic architecture both in mood disorder and schizophrenia across individuals of East Asian and European descent. Investigating joint genetic architecture of these psychiatric traits enables the identification of common and diverging etiological mechanisms underlying these psychiatric illnesses. Here, we leverage on the largest GWAS of schizophrenia and mood disorder conducted to date in East Asian and European descent samples to elucidate the joint genetic architecture that underlie these psychiatric disorders. Methodology: We carried out GWAS meta-analysis on both European (EUR) and East Asian (EAS) Ancestry summary statistics for Major Depressive Disorder (MDD) and Schizophrenia via Multi-Trait Analysis of GWAS. Downstream pathway, eQTL, chromatin interaction analysis were carried out to characterize genome-wide results. In addition we carried out genetic correlations and polygenic risk prediction analysis to further study the joint genetic architectures of mood disorder and schizophrenia. Results: There were 308 loci that was significantly associated with at least one trait. Specifically, there were 98 independent loci in EUR-MDD, 5 loci for MTAGx-EAS-MDD, 121 loci for MTAGx-EUR-MDD, 8 independent loci for EAS-SZ, 171 independent loci for EUR-SZ, 124 independent loci for MTAGx-EAS-SZ, and 159 independent loci for MTAGx-EUR-SZ. In all, 61 loci were novel across traits. SOAT1 and FOXO3 genes were implicated based on genome-wide associations. 114 gene(s) were implicated in eQTL analysis of gene expression in brain tissue. Gene-set analysis show support for GABA-egic pathways implicated in MDD, driven by several GABA-alpha receptor genes as well as more peripheral PLCL1 and NISCH genes that are responsible for endocytosis and neuronal trafficking. Cross-Ancestry genetic correlations ascertained that the CONVERGE MDD phenotype generally holds higher SNP based heritability and is likely driven by case-ascertainment procedures. Finally, polygenic risk score modelling indicates that MTAGx procedures were effective in enriching GWAS signals in the EAS-MDD for prediction in an independent case-control sample. Discussion: Here we are able to demonstrate that cross-trait cross-ancestry approaches in schizophrenia and MDD not only yields new discoveries to the genetic architecture of these illnesses; we were able to identify new biological underpinnings within the GABA pathways for depressive disorders. The evidence in the current report underscores the importance of taking into consideration both phenotype and ancestry complexities in genome-wide studies.

scholarly journals Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis

2016 ◽  
Vol 48 (9) ◽  
pp. 1043-1048 ◽  
Author(s):  
Wouter van Rheenen ◽  
◽  
Aleksey Shatunov ◽  
Annelot M Dekker ◽  
Russell L McLaughlin ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Genetic Architecture ◽  
Genome Wide Association ◽  
Association Analyses ◽  
Risk Variants ◽  
Genome Wide ◽  
Lateral Sclerosis
Sign in / Sign up

Export Citation Format

Share Document