scholarly journals Genetic Risk for Rheumatoid Arthritis is Associated with Increased Striatal Volume in Healthy Young Adults

2019 ◽  
Author(s):  
Reut Avinun ◽  
Adam Nevo ◽  
Ahmad R. Hariri
Keyword(s):  
Rheumatoid Arthritis ◽  
Genetic Risk ◽  
Genome Wide Association Study ◽  
Morphological Changes ◽  
Disease Onset ◽  
Risk Scores ◽  
Intracranial Volume ◽  
Polygenic Risk ◽  
Genetic Components ◽  
A Genome

AbstractRheumatoid arthritis (RA), an autoimmune disease, has recently been associated with increased striatal volume and decreased intracranial volume (ICV) in longstanding patients. As inflammation has been shown to precede the clinical diagnosis of RA and it is a known moderator of neuro- and gliogenesis, we were interested in testing whether these brain morphological changes appear before the clinical onset of disease in healthy young adult volunteers, as a function of relative genetic risk for RA. Genetic and structural MRI data were available for 516 healthy non-Hispanic Caucasian university students (275 women, mean age 19.78±1.24 years). Polygenic risk scores were computed for each individual based on a genome-wide association study of RA, so that higher scores indicated higher risk. Striatal volume (sum of caudate, putamen, and nucleus accumbens volumes) and ICV were derived for each individual from high-resolution T1-weighted images. After controlling for sex, age, genetic components of ethnicity, socioeconomic status, and depressive symptoms, we found that higher RA polygenic risk scores were associated with increased striatal volume, but not decreased ICV. Our findings suggest that increased striatal volume may be linked to processes that precede disease onset, such as inflammation, while decreased ICV may relate to disease progression.

scholarly journals Polygenic risk modeling with latent trait-related genetic components

2019 ◽  
Author(s):  
Matthew Aguirre ◽  
Yosuke Tanigawa ◽  
Guhan Ram Venkataraman ◽  
Rob Tibshirani ◽  
Trevor Hastie ◽  
...  
Keyword(s):  
Fat Mass ◽  
Genetic Risk ◽  
Complex Traits ◽  
Fat Free Mass ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genetic Associations ◽  
Polygenic Risk ◽  
Genetic Components ◽  
Mass Component

AbstractPolygenic risk models have led to significant advances in understanding complex diseases and their clinical presentation. While models like polygenic risk scores (PRS) can effectively predict outcomes, they do not generally account for disease subtypes or pathways which underlie within-trait diversity. Here, we introduce a latent factor model of genetic risk based on components from Decomposition of Genetic Associations (DeGAs), which we call the DeGAs polygenic risk score (dPRS). We compute DeGAs using genetic associations for 977 traits in the UK Biobank and find that dPRS performs comparably to standard PRS while offering greater interpretability. We show how to decompose an individual’s genetic risk for a trait across DeGAs components, highlighting specific results for body mass index (BMI), myocardial infarction (heart attack), and gout in 337,151 white British individuals, with replication in a further set of 25,486 non-British white individuals from the Biobank. We find that BMI polygenic risk factorizes into components relating to fat-free mass, fat mass, and overall health indicators like physical activity measures. Most individuals with high dPRS for BMI have strong contributions from both a fat mass component and a fat-free mass component, whereas a few ‘outlier’ individuals have strong contributions from only one of the two components. Overall, our method enables fine-scale interpretation of the drivers of genetic risk for complex traits.

Orbitofrontal cortex volume links polygenic risk for smoking with tobacco use in healthy adolescents

2020 ◽  
pp. 1-8
Author(s):  
Jin Li ◽  
Bing Liu ◽  
Tobias Banaschewski ◽  
Arun L.W. Bokde ◽  
Erin Burke Quinlan ◽  
...  
Keyword(s):  
Tobacco Use ◽  
Tobacco Smoking ◽  
Orbitofrontal Cortex ◽  
Genetic Risk ◽  
Molecular Mechanisms ◽  
Self Report ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Cortical Volume ◽  
A Genome

Abstract Background Tobacco smoking remains one of the leading causes of preventable illness and death and is heritable with complex underpinnings. Converging evidence suggests a contribution of the polygenic risk for smoking to the use of tobacco and other substances. Yet, the underlying brain mechanisms between the genetic risk and tobacco smoking remain poorly understood. Methods Genomic, neuroimaging, and self-report data were acquired from a large cohort of adolescents from the IMAGEN study (a European multicenter study). Polygenic risk scores (PGRS) for smoking were calculated based on a genome-wide association study meta-analysis conducted by the Tobacco and Genetics Consortium. We examined the interrelationships among the genetic risk for smoking initiation, brain structure, and the number of occasions of tobacco use. Results A higher smoking PGRS was significantly associated with both an increased number of occasions of tobacco use and smaller cortical volume of the right orbitofrontal cortex (OFC). Furthermore, reduced cortical volume within this cluster correlated with greater tobacco use. A subsequent path analysis suggested that the cortical volume within this cluster partially mediated the association between the genetic risk for smoking and the number of occasions of tobacco use. Conclusions Our data provide the first evidence for the involvement of the OFC in the relationship between smoking PGRS and tobacco use. Future studies of the molecular mechanisms underlying tobacco smoking should consider the mediation effect of the related neural structure.

scholarly journals Maternal Psychological Problems During Pregnancy and Child Externalizing Problems: Moderated Mediation Model with Child Self-regulated Compliance and Polygenic Risk Scores for Aggression

2021 ◽  
Author(s):  
Mannan Luo ◽  
Irene Pappa ◽  
Charlotte A. M. Cecil ◽  
Philip Jansen ◽  
Marinus H. van IJzendoorn ◽  
...  
Keyword(s):  
Externalizing Problems ◽  
Genome Wide Association Study ◽  
Self Regulation ◽  
Psychological Problems ◽  
Risk Scores ◽  
Mediation Model ◽  
Polygenic Risk ◽  
Moderated Mediation Model ◽  
Genome Wide ◽  
A Genome

AbstractA potential pathway underlying the association between prenatal exposure to maternal psychological problems and childhood externalizing problems is child self-regulation. This prospective study (N = 687) examined whether self-regulated compliance mediates the relation between maternal affective problems and hostility during pregnancy and childhood externalizing problems, and explored moderation by child polygenic risk scores for aggression and sex. Self-regulated compliance at age 3 was observed in mother–child interactions, and externalizing problems at age 6 were reported by mothers and teachers. Polygenic risk scores were calculated based on a genome-wide association study of aggressive behavior. Self-regulated compliance mediated the associations between maternal psychological problems and externalizing problems. Aggression PRS was associated with higher externalizing problems reported by mothers. No evidence was found of moderation by aggression PRS or sex. These findings support the hypothesis that maternal psychological problems during pregnancy might influence externalizing problems through early self-regulation, regardless of child genetic susceptibility or sex.

scholarly journals Exceptional Longevity and Polygenic Risk for Cardiovascular Health

Genes ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 227 ◽  
Author(s):  
Mary Revelas ◽  
Anbupalam Thalamuthu ◽  
Christopher Oldmeadow ◽  
Tiffany-Jane Evans ◽  
Nicola J. Armstrong ◽  
...  
Keyword(s):  
Multiple Testing ◽  
Cardiovascular Health ◽  
Genome Wide Association Study ◽  
Hdl Cholesterol ◽  
Cholesterol Homeostasis ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Exceptional Longevity ◽  
A Genome ◽  
Artery Disease

Studies investigating exceptionally long-lived (ELL) individuals, including genetic studies, have linked cardiovascular-related pathways, particularly lipid and cholesterol homeostasis, with longevity. This study explored the genetic profiles of ELL individuals (cases: n = 294, 95–106 years; controls: n = 1105, 55–65 years) by assessing their polygenic risk scores (PRS) based on a genome wide association study (GWAS) threshold of p < 5 × 10−5. PRS were constructed using GWAS summary data from two exceptional longevity (EL) analyses and eight cardiovascular-related risk factors (lipids) and disease (myocardial infarction, coronary artery disease, stroke) analyses. A higher genetic risk for exceptional longevity (EL) was significantly associated with longevity in our sample (odds ratio (OR) = 1.19–1.20, p = 0.00804 and 0.00758, respectively). Two cardiovascular health PRS were nominally significant with longevity (HDL cholesterol, triglycerides), with higher PRS associated with EL, but these relationships did not survive correction for multiple testing. In conclusion, ELL individuals did not have significantly lower polygenic risk for the majority of the investigated cardiovascular health traits. Future work in larger cohorts is required to further explore the role of cardiovascular-related genetic variants in EL.

scholarly journals Pathway-specific Polygenic Risk Scores (PRS) identify OSA-related pathways differentially moderating genetic susceptibility to CAD

2021 ◽  
Author(s):  
Matthew O Goodman ◽  
Brian E Cade ◽  
Neomi Shah ◽  
Tianyi Huang ◽  
Hassan S Dashti ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Genome Wide Association Study ◽  
Risk Scores ◽  
Molecular Pathways ◽  
Environment Interaction ◽  
Dependent Manner ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Obstructive Sleep ◽  
Cad Risk

Background: Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia (IH), may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (e.g. inflammatory) and protective (e.g. increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner. Methods: We selected a cross-sectional sample of 471,877 participants from the UK Biobank, among whom we ascertained 4,974 to have OSA, 25,988 to have CAD, and 711 to have both. We calculated pathway-specific polygenic risk scores (PS-PRS) for CAD, based on 6.6 million common variants evaluated in the CARDIoGRAMplusC4D genome-wide association study (GWAS), annotated to specific genes and pathways using functional genomics databases. Based on evidence of involvement with IH and CAD, we tested PS-PRS for the HIF-1, VEGF, NFkB and TNF signaling pathways. Results: In a multivariable-adjusted logistic generalized additive model, elevated PS-PRSs for the KEGG VEGF pathway (39 genes) associated with protection for CAD in OSA (interaction odds ratio 0.86, p = 6E-04). By contrast, the genome-wide CAD PRS did not show evidence of statistical interaction with OSA. Conclusions: We find evidence that pathway-specific genetic risk of CAD differs between individuals with and without OSA in a qualitatively pathway-dependent manner, consistent with the previously studied phenomena whereby features of OSA may have both positive and negative effects on CAD. These results provide evidence that gene-by-environment interaction influences CAD risk in certain pathways among people with OSA, an effect that is not well-captured by the genome-wide PRS. These results can be followed up to study how OSA interacts with genetic risk at the molecular level, and potentially to personalize OSA treatment and reduce CAD risk according to individual pathway-specific genetic risk profiles.

scholarly journals Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity between ancestral groups

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yong-Fei Wang ◽  
Yan Zhang ◽  
Zhiming Lin ◽  
Huoru Zhang ◽  
Ting-You Wang ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Genome Wide Association Study ◽  
Age Of Onset ◽  
Treatment Options ◽  
Human Leukocyte ◽  
Risk Scores ◽  
Systemic Lupus ◽  
Disease Manifestation ◽  
A Genome

AbstractSystemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underlie the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertake a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture are identified. In addition to the human leukocyte antigen (HLA) region, nine disease loci show clear ancestral differences and implicate antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores perform significantly better when trained on ancestry-matched data sets. These analyses help to reveal the genetic basis for disparities in SLE among ancestral groups.

scholarly journals Genome-wide association study of psychiatric and substance use comorbidity in Mexican individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Jaime Martínez-Magaña ◽  
Alma Delia Genis-Mendoza ◽  
Jorge Ameth Villatoro Velázquez ◽  
Marycarmen Bustos-Gamiño ◽  
Isela Esther Juárez-Rojop ◽  
...  
Keyword(s):  
Substance Use ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Logistic Models ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Multinomial Models ◽  
Gamma Receptor ◽  
Genome Wide ◽  
A Genome

AbstractThe combination of substance use and psychiatric disorders is one of the most common comorbidities. The objective of this study was to perform a genome-wide association study of this comorbidity (Com), substance use alone (Subs), and psychiatric symptomatology alone (Psych) in the Mexican population. The study included 3914 individuals of Mexican descent. Genotyping was carried out using the PsychArray microarray and genome-wide correlations were calculated. Genome-wide associations were analyzed using multiple logistic models, polygenic risk scores (PRSs) were evaluated using multinomial models, and vertical pleiotropy was evaluated by generalized summary-data-based Mendelian randomization. Brain DNA methylation quantitative loci (brain meQTL) were also evaluated in the prefrontal cortex. Genome-wide correlation and vertical pleiotropy were found between all traits. No genome-wide association signals were found, but 64 single-nucleotide polymorphism (SNPs) reached nominal associations (p < 5.00e−05). The SNPs associated with each trait were independent, and the individuals with high PRSs had a higher prevalence of tobacco and alcohol use. In the multinomial models all of the PRSs (Subs-PRS, Com-PRS, and Psych-PRS) were associated with all of the traits. Brain meQTL of the Subs-associated SNPs had an effect on the genes enriched in insulin signaling pathway, and that of the Psych-associated SNPs had an effect on the Fc gamma receptor phagocytosis pathway.

scholarly journals Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

2021 ◽  
pp. 1-12
Author(s):  
Simon Schmitt ◽  
Tina Meller ◽  
Frederike Stein ◽  
Katharina Brosch ◽  
Kai Ringwald ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Mental Disorders ◽  
Cortical Thickness ◽  
Genetic Risk ◽  
Right Hemisphere ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Grey Matter Volume ◽  
Polygenic Risk ◽  
Risk For Depression

Abstract Background MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. Methods We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. Results The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. Conclusions Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Prediction Accuracy ◽  
Genetic Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Sample Mean ◽  
Polygenic Risk ◽  
Reliable Identification

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

Sign in / Sign up

Export Citation Format

Share Document