scholarly journals Genome-wide Association Study of Pediatric Obsessive-Compulsive Traits: Shared Genetic Risk between Traits and Disorder

2019 ◽  
Author(s):  
Christie L. Burton ◽  
Mathieu Lemire ◽  
Bowei Xiao ◽  
Elizabeth C. Corfield ◽  
Lauren Erdman ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Genetic Risk ◽  
Meta Analysis ◽  
Case Control ◽  
Genome Wide Association ◽  
Polygenic Risk Score ◽  
Obsessive Compulsive ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Shared Genetic

AbstractObjectiveTo identify genetic variants associated with obsessive-compulsive (OC) traits and test for sharing of genetic risks between OC traits and obsessive-compulsive disorder (OCD).MethodsWe conducted a genome-wide association analysis of OC traits using the Toronto Obsessive-Compulsive Scale (TOCS) in 5018 unrelated Caucasian children and adolescents from the community (Spit for Science sample). We tested the hypothesis that genetic variants associated with OC traits from the community would be associated with clinical OCD using a meta-analysis of three OCD case-controls samples (cases=3384, controls=8363). Shared genetic risk was examined between OC traits and OCD in the respective samples using polygenic risk score and genetic correlation analyses.ResultsA locus tagged by rs7856850 in an intron of PTPRD (protein tyrosine phosphatase δ) was significantly associated with OC traits at the genome-wide significance level (p=2.48×10−8). The rs7856850 locus was also associated with OCD in a meta-analysis of three independent OCD case/control genome-wide datasets (p=0.0069). Polygenic risk scores derived from OC traits were significantly associated with OCD in a sample of childhood-onset OCD and vice versa (p’s<0.01). OC traits were highly but not significantly genetically correlated with OCD (rg=0.83, p=0.07).ConclusionsWe report the first validated genome-wide significant variant for OC traits. OC traits measured in the community sample shared genetic risk with OCD case/control status. Our results demonstrate the importance of the type of measure used to measure traits as well as the feasibility and power of using trait-based approaches in community samples for genetic discovery.

scholarly journals Genome-wide association study of pediatric obsessive-compulsive traits: shared genetic risk between traits and disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Christie L. Burton ◽  
◽  
Mathieu Lemire ◽  
Bowei Xiao ◽  
Elizabeth C. Corfield ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Genetic Risk ◽  
Meta Analysis ◽  
Community Sample ◽  
Case Control ◽  
Genome Wide Association ◽  
Obsessive Compulsive ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Shared Genetic

Abstract Using a novel trait-based measure, we examined genetic variants associated with obsessive-compulsive (OC) traits and tested whether OC traits and obsessive-compulsive disorder (OCD) shared genetic risk. We conducted a genome-wide association analysis (GWAS) of OC traits using the Toronto Obsessive-Compulsive Scale (TOCS) in 5018 unrelated Caucasian children and adolescents from the community (Spit for Science sample). We tested the hypothesis that genetic variants associated with OC traits from the community would be associated with clinical OCD using a meta-analysis of all currently available OCD cases. Shared genetic risk was examined between OC traits and OCD in the respective samples using polygenic risk score and genetic correlation analyses. A locus tagged by rs7856850 in an intron of PTPRD (protein tyrosine phosphatase δ) was significantly associated with OC traits at the genome-wide significance level (p = 2.48 × 10−8). rs7856850 was also associated with OCD in a meta-analysis of OCD case/control genome-wide datasets (p = 0.0069). The direction of effect was the same as in the community sample. Polygenic risk scores from OC traits were significantly associated with OCD in case/control datasets and vice versa (p’s < 0.01). OC traits were highly, but not significantly, genetically correlated with OCD (rg = 0.71, p = 0.062). We report the first validated genome-wide significant variant for OC traits in PTPRD, downstream of the most significant locus in a previous OCD GWAS. OC traits measured in the community sample shared genetic risk with OCD case/control status. Our results demonstrate the feasibility and power of using trait-based approaches in community samples for genetic discovery.

scholarly journals A Genome-Wide Association Study and Polygenic Risk Score Analysis of Posttraumatic Stress Disorder and Metabolic Syndrome in a South African Population

2021 ◽  
Vol 15 ◽  
Author(s):  
Patricia C. Swart ◽  
Leigh L. van den Heuvel ◽  
Cathryn M. Lewis ◽  
Soraya Seedat ◽  
Sian M. J. Hemmings
Keyword(s):  
Metabolic Syndrome ◽  
South African ◽  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Stress Disorder ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Polygenic Risk ◽  
Genome Wide ◽  
A Genome

Posttraumatic stress disorder (PTSD) is a trauma-related disorder that frequently co-occurs with metabolic syndrome (MetS). MetS is characterized by obesity, dyslipidemia, and insulin resistance. To provide insight into these co-morbidities, we performed a genome-wide association study (GWAS) meta-analysis to identify genetic variants associated with PTSD, and determined if PTSD polygenic risk scores (PRS) could predict PTSD and MetS in a South African mixed-ancestry sample. The GWAS meta-analysis of PTSD participants (n = 260) and controls (n = 343) revealed no SNPs of genome-wide significance. However, several independent loci, as well as five SNPs in the PARK2 gene, were suggestively associated with PTSD (p &lt; 5 × 10–6). PTSD-PRS was associated with PTSD diagnosis (Nagelkerke’s pseudo R2 = 0.0131, p = 0.00786), PTSD symptom severity [as measured by CAPS-5 total score (R2 = 0.00856, p = 0.0367) and PCL-5 score (R2 = 0.00737, p = 0.0353)], and MetS (Nagelkerke’s pseudo R2 = 0.00969, p = 0.0217). These findings suggest an association between PTSD and PARK2, corresponding with results from the largest PTSD-GWAS conducted to date. PRS analysis suggests that genetic variants associated with PTSD are also involved in the development of MetS. Overall, the results contribute to a broader goal of increasing diversity in psychiatric genetics.

scholarly journals Association between substance use disorder and polygenic liability to schizophrenia

2017 ◽  
Author(s):  
Sarah M. Hartz ◽  
Amy Horton ◽  
Mary Oehlert ◽  
Caitlin E. Carey ◽  
Arpana Agrawal ◽  
...  
Keyword(s):  
Substance Use ◽  
Substance Use Disorder ◽  
Meta Analysis ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Individual Substance ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Individual Dataset ◽  
Shared Genetic

AbstractBackgroundThere are high levels of comorbidity between schizophrenia and substance use disorder, but little is known about the genetic etiology of this comorbidity.MethodsHere, we test the hypothesis that shared genetic liability contributes to the high rates of comorbidity between schizophrenia and substance use disorder. To do this, polygenic risk scores for schizophrenia derived from a large meta-analysis by the Psychiatric Genomics Consortium were computed in three substance use disorder datasets: COGEND (ascertained for nicotine dependence n=918 cases, 988 controls), COGA (ascertained for alcohol dependence n=643 cases, 384 controls), and FSCD (ascertained for cocaine dependence n=210 cases, 317 controls). Phenotypes were harmonized across the three datasets and standardized analyses were performed. Genome-wide genotypes were imputed to 1000 Genomes reference panel.ResultsIn each individual dataset and in the mega-analysis, strong associations were observed between any substance use disorder diagnosis and the polygenic risk score for schizophrenia (mega-analysis pseudo R2 range 0.8%-3.7%, minimum p=4×10-23).ConclusionsThese results suggest that comorbidity between schizophrenia and substance use disorder is partially attributable to shared polygenic liability. This shared liability is most consistent with a general risk for substance use disorder rather than specific risks for individual substance use disorders and adds to increasing evidence of a blurred boundary between schizophrenia and substance use disorder.

Genetic Background of Mesalamine-induced Fever and Diarrhea in Japanese Patients with Inflammatory Bowel Disease

2021 ◽  
Author(s):  
Kaoru Suzuki ◽  
Yoichi Kakuta ◽  
Takeo Naito ◽  
Tetsuya Takagawa ◽  
Hiroyuki Hanai ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Background ◽  
Association Studies ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Genome Wide Association ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

Abstract Background Some patients with inflammatory bowel disease (IBD) who were under mesalamine treatment develop adverse reactions called “mesalamine allergy,” which includes high fever and worsening diarrhea. Currently, there is no method to predict mesalamine allergy. Pharmacogenomic approaches may help identify these patients. Here we analyzed the genetic background of mesalamine intolerance in the first genome-wide association study of Japanese patients with IBD. Methods Two independent pharmacogenetic IBD cohorts were analyzed: the MENDEL (n = 1523; as a discovery set) and the Tohoku (n = 788; as a replication set) cohorts. Genome-wide association studies were performed in each population, followed by a meta-analysis. In addition, we constructed a polygenic risk score model and combined genetic and clinical factors to model mesalamine intolerance. Results In the combined cohort, mesalamine-induced fever and/or diarrhea was significantly more frequent in ulcerative colitis vs Crohn’s disease. The genome-wide association studies and meta-analysis identified one significant association between rs144384547 (upstream of RGS17) and mesalamine-induced fever and diarrhea (P = 7.21e-09; odds ratio = 11.2). The estimated heritability of mesalamine allergy was 25.4%, suggesting a significant correlation with the genetic background. Furthermore, a polygenic risk score model was built to predict mesalamine allergy (P = 2.95e-2). The combined genetic/clinical prediction model yielded a higher area under the curve than did the polygenic risk score or clinical model alone (area under the curve, 0.89; sensitivity, 71.4%; specificity, 90.8%). Conclusions Mesalamine allergy was more common in ulcerative colitis than in Crohn’s disease. We identified a novel genetic association with and developed a combined clinical/genetic model for this adverse event.

scholarly journals Association analysis of juvenile idiopathic arthritis genetic susceptibility factors in Estonian patients

2021 ◽  
Author(s):  
Tiit Nikopensius ◽  
Priit Niibo ◽  
Toomas Haller ◽  
Triin Jagomägi ◽  
Ülle Voog-Oras ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Juvenile Idiopathic Arthritis ◽  
Autoimmune Diseases ◽  
Genetic Risk ◽  
Association Studies ◽  
Control Sample ◽  
Case Control ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract Background Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic condition of childhood. Genetic association studies have revealed several JIA susceptibility loci with the strongest effect size observed in the human leukocyte antigen (HLA) region. Genome-wide association studies have augmented the number of JIA-associated loci, particularly for non-HLA genes. The aim of this study was to identify new associations at non-HLA loci predisposing to the risk of JIA development in Estonian patients. Methods We performed genome-wide association analyses in an entire JIA case–control sample (All-JIA) and in a case–control sample for oligoarticular JIA, the most prevalent JIA subtype. The entire cohort was genotyped using the Illumina HumanOmniExpress BeadChip arrays. After imputation, 16,583,468 variants were analyzed in 263 cases and 6956 controls. Results We demonstrated nominal evidence of association for 12 novel non-HLA loci not previously implicated in JIA predisposition. We replicated known JIA associations in CLEC16A and VCTN1 regions in the oligoarticular JIA sample. The strongest associations in the All-JIA analysis were identified at PRKG1 (P = 2,54 × 10−6), LTBP1 (P = 9,45 × 10−6), and ELMO1 (P = 1,05 × 10−5). In the oligoarticular JIA analysis, the strongest associations were identified at NFIA (P = 5,05 × 10−6), LTBP1 (P = 9,95 × 10−6), MX1 (P = 1,65 × 10−5), and CD200R1 (P = 2,59 × 10−5). Conclusion This study increases the number of known JIA risk loci and provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis. The reported loci are involved in molecular pathways of immunological relevance and likely represent genomic regions that confer susceptibility to JIA in Estonian patients. Key Points• Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease with heterogeneous presentation and genetic predisposition.• Present genome-wide association study for Estonian JIA patients is first of its kind in Northern and Northeastern Europe.• The results of the present study increase the knowledge about JIA risk loci replicating some previously described associations, so adding weight to their relevance and describing novel loci.• The study provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis.

scholarly journals Genome-wide association meta-analysis of childhood and adolescent internalising symptoms

2020 ◽  
Author(s):  
Eshim S Jami ◽  
Anke R Hammerschlag ◽  
Hill F Ip ◽  
Andrea G Allegrini ◽  
Beben Benyamin ◽  
...  
Keyword(s):  
Confidence Intervals ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genetic Effects ◽  
Childhood Aggression ◽  
Genome Wide Association ◽  
Childhood And Adolescence ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Genome Wide

Internalising symptoms in childhood and adolescence are as heritable as adult depression and anxiety, yet little is known of their molecular basis. This genome-wide association meta-analysis of internalising symptoms included repeated observations from 64,641 individuals, aged between 3 and 18. The N-weighted meta-analysis of overall internalising symptoms (INToverall) detected no genome-wide significant hits and showed low SNP heritability (1.66%, 95% confidence intervals 0.84-2.48%, Neffective=132,260). Stratified analyses showed rater-based heterogeneity in genetic effects, with self-reported internalising symptoms showing the highest heritability (5.63%, 95% confidence intervals 3.08-8.18%). Additive genetic effects on internalising symptoms appeared stable over age, with overlapping estimates of SNP heritability from early-childhood to adolescence. Gene-based analyses showed significant associations with three genes: WNT3 (p=1.13×10-06), CCL26 (p=1.88×10-06), and CENPO (p=2.54×10-06). Of these, WNT3 was previously associated with neuroticism, with which INToverall also shared a strong genetic correlation (rg=0.76). Genetic correlations were also observed with adult anxiety, depression, and the wellbeing spectrum (|rg|> 0.70), as well as with insomnia, loneliness, attention-deficit hyperactivity disorder, autism, and childhood aggression (range |rg|=0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Overall, childhood and adolescent internalising symptoms share substantial genetic vulnerabilities with adult internalising disorders and other childhood psychiatric traits, which could explain both the persistence of internalising symptoms over time, and the high comorbidity amongst childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

scholarly journals Cardiac Imaging of Aortic Valve Area From 34 287 UK Biobank Participants Reveals Novel Genetic Associations and Shared Genetic Comorbidity With Multiple Disease Phenotypes

2020 ◽  
Vol 13 (6) ◽  
Author(s):  
Aldo Córdova-Palomera ◽  
Catherine Tcheandjieu ◽  
Jason A. Fries ◽  
Paroma Varma ◽  
Vincent S. Chen ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Aortic Valve Disease ◽  
Valve Disease ◽  
Genome Wide Association ◽  
Aortic Valve Area ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Shared Genetic ◽  
Valve Area

Background: The aortic valve is an important determinant of cardiovascular physiology and anatomic location of common human diseases. Methods: From a sample of 34 287 white British ancestry participants, we estimated functional aortic valve area by planimetry from prospectively obtained cardiac magnetic resonance imaging sequences of the aortic valve. Aortic valve area measurements were submitted to genome-wide association testing, followed by polygenic risk scoring and phenome-wide screening, to identify genetic comorbidities. Results: A genome-wide association study of aortic valve area in these UK Biobank participants showed 3 significant associations, indexed by rs71190365 (chr13:50764607, DLEU1 , P =1.8×10 −9 ), rs35991305 (chr12:94191968, CRADD , P =3.4×10 −8 ), and chr17:45013271:C:T ( GOSR2 , P =5.6×10 −8 ). Replication on an independent set of 8145 unrelated European ancestry participants showed consistent effect sizes in all 3 loci, although rs35991305 did not meet nominal significance. We constructed a polygenic risk score for aortic valve area, which in a separate cohort of 311 728 individuals without imaging demonstrated that smaller aortic valve area is predictive of increased risk for aortic valve disease (odds ratio, 1.14; P =2.3×10 −6 ). After excluding subjects with a medical diagnosis of aortic valve stenosis (remaining n=308 683 individuals), phenome-wide association of >10 000 traits showed multiple links between the polygenic score for aortic valve disease and key health-related comorbidities involving the cardiovascular system and autoimmune disease. Genetic correlation analysis supports a shared genetic etiology with between aortic valve area and birth weight along with other cardiovascular conditions. Conclusions: These results illustrate the use of automated phenotyping of cardiac imaging data from the general population to investigate the genetic etiology of aortic valve disease, perform clinical prediction, and uncover new clinical and genetic correlates of cardiac anatomy.

scholarly journals Genome-wide association study of susceptibility to idiopathic pulmonary fibrosis

2019 ◽  
Author(s):  
Richard J Allen ◽  
Beatriz Guillen-Guio ◽  
Justin M Oldham ◽  
Shwu-Fan Ma ◽  
Amy Dressen ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Telomere Maintenance ◽  
Genome Wide Association ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

AbstractRationaleIdiopathic pulmonary fibrosis (IPF) is a complex lung disease characterised by scarring of the lung that is believed to result from an atypical response to injury of the epithelium. The mechanisms by which this arises are poorly understood and it is likely that multiple pathways are involved. The strongest genetic association with IPF is a variant in the promoter of MUC5B where each copy of the risk allele confers a five-fold risk of disease. However, genome-wide association studies have reported additional signals of association implicating multiple pathways including host defence, telomere maintenance, signalling and cell-cell adhesion.ObjectivesTo improve our understanding of mechanisms that increase IPF susceptibility by identifying previously unreported genetic associations.Methods and measurementsWe performed the largest genome-wide association study undertaken for IPF susceptibility with a discovery stage comprising up to 2,668 IPF cases and 8,591 controls with replication in an additional 1,467 IPF cases and 11,874 controls. Polygenic risk scores were used to assess the collective effect of variants not reported as associated with IPF.Main resultsWe identified and replicated three new genome-wide significant (P<5×10-8) signals of association with IPF susceptibility (near KIF15, MAD1L1 and DEPTOR) and confirm associations at 11 previously reported loci. Polygenic risk score analyses showed that the combined effect of many thousands of as-yet unreported IPF risk variants contribute to IPF susceptibility.ConclusionsNovel association signals support the importance of mTOR signalling in lung fibrosis and suggest a possible role of mitotic spindle-assembly genes in IPF susceptibility.

scholarly journals Polygenic risk score, genome-wide association, and gene set analyses of cognitive domain deficits in schizophrenia

2018 ◽  
Vol 201 ◽  
pp. 393-399 ◽  
Author(s):  
Soichiro Nakahara ◽  
Sarah Medland ◽  
Jessica A. Turner ◽  
Vince D. Calhoun ◽  
Kelvin O. Lim ◽  
...  
Keyword(s):  
Risk Score ◽  
Genome Wide Association ◽  
Cognitive Domain ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Gene Set ◽  
Genome Wide

Genome-Wide Association for HbA1c in Malay Identified Deletion on SLC4A1 that Influences HbA1c Independent of Glycemia

2020 ◽  
Vol 105 (12) ◽  
pp. 3854-3864
Author(s):  
Jin-Fang Chai ◽  
Shih-Ling Kao ◽  
Chaolong Wang ◽  
Victor Jun-Yu Lim ◽  
Ing Wei Khor ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Hba1c Level ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Specific Reference ◽  
Genetic Determinants ◽  
Genome Wide ◽  
Whole Exome ◽  
A Genome

Abstract Context Glycated hemoglobin A1c (HbA1c) level is used to screen and diagnose diabetes. Genetic determinants of HbA1c can vary across populations and many of the genetic variants influencing HbA1c level were specific to populations. Objective To discover genetic variants associated with HbA1c level in nondiabetic Malay individuals. Design and Participants We conducted a genome-wide association study (GWAS) analysis for HbA1c using 2 Malay studies, the Singapore Malay Eye Study (SiMES, N = 1721 on GWAS array) and the Living Biobank study (N = 983 on GWAS array and whole-exome sequenced). We built a Malay-specific reference panel to impute ethnic-specific variants and validate the associations with HbA1c at ethnic-specific variants. Results Meta-analysis of the 1000 Genomes imputed array data identified 4 loci at genome-wide significance (P &lt; 5 × 10-8). Of the 4 loci, 3 (ADAM15, LINC02226, JUP) were novel for HbA1c associations. At the previously reported HbA1c locus ATXN7L3-G6PC3, association analysis using the exome data fine-mapped the HbA1c associations to a 27-bp deletion (rs769664228) at SLC4A1 that reduced HbA1c by 0.38 ± 0.06% (P = 3.5 × 10-10). Further imputation of this variant in SiMES confirmed the association with HbA1c at SLC4A1. We also showed that these genetic variants influence HbA1c level independent of glucose level. Conclusion We identified a deletion at SLC4A1 associated with HbA1c in Malay. The nonglycemic lowering of HbA1c at rs769664228 might cause individuals carrying this variant to be underdiagnosed for diabetes or prediabetes when HbA1c is used as the only diagnostic test for diabetes.

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