scholarly journals Genome-wide association study of suicide death and polygenic prediction of clinical antecedents

2017 ◽  
Author(s):  
Anna R. Docherty ◽  
Andrey A. Shabalin ◽  
Emily DiBlasi ◽  
Eric Monson ◽  
Niamh Mullins ◽  
...  
Keyword(s):  
Autism Spectrum ◽  
Case Control ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Behavioral Disinhibition ◽  
Suicide Death ◽  
Polygenic Score ◽  
Death Case ◽  
Genome Wide ◽  
Polygenic Scores

ABSTRACTObjectiveSuicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort.MethodsThe analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression.ResultsGWAS identified two genome-wide significant loci (6 SNPs, p<5×10−8). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder.ConclusionsIn this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status.

scholarly journals Genome-wide Polygenic Scores for Multiple Psychiatric and Common Traits Identify Preadolescent Youth with Risk for Suicide

2021 ◽  
Author(s):  
Yoonjung Yoonie Joo ◽  
Seo-Yoon Moon ◽  
Hee-Hwan Wang ◽  
Hyeonjin Kim ◽  
Eun-Ji Lee ◽  
...  
Keyword(s):  
Machine Learning ◽  
Suicidal Ideation ◽  
Family Environment ◽  
Autism Spectrum ◽  
Cognitive Capacity ◽  
European Ancestry ◽  
Environment Interaction ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Preadolescent Youth

Abstract Importance. Suicide is the second leading cause of death in children worldwide but no available means exist to identify the risk in youth. Objective. To predict the risk of suicide in children and to investigate whether and to what extents genetic factors and a major environmental risk factor, early life stress(ELS), influence youth suicide. Design, Setting and Participants. We analyzed the genotype-phenotype data of 11,869 preadolescent children ages 9- to 10-year-old from the Adolescent Brain and Cognitive Development (ABCD) study. We estimated genome-wide polygenic scores (GPSs) of 25 complex traits to investigate their phenome-wide associations and predictive utility with suicidality (suicidal ideation and attempt) with machine learning approaches. Predictors. GPSs of 25 traits including psychiatric disorders, personality, cognitive capacity, and psychological traits. Parent Child Behavior Checklist to measure ELS in youth and Youth Family Environment Scale to assess family environment. Main outcomes and Measures. Records of suicidal ideation and attempt of the participants were derived from the computerized version of Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS). Results. We identified three GPSs associated with youth suicidality in multiethnic (n = 7,206) and European-ancestry (n = 5,749) participants: ADHD (P = 3.48x10− 4; odds ratio = 1.13 in multiethnic participants, P = 5.60x10− 5, OR = 1.25 in European-ancestry participants), general happiness (P = 1.43x10− 3; OR = 0.89 in multiethnic, P = 8.61x10− 4, OR = 0.89 in European) and autism spectrum disorder(ASD) (P = 1.81x10− 3; OR = 1.15 in multiethnic, P = 1.26x10− 3, OR = 1.18 in European). We also found a significant GPS-by-environment interaction between the effects of genetic risk factors for ASD and the level of ELS in increasing the risk for suicidal ideation (P = 1.36x10− 2, OR = 1.12 in multiethnic, P = 1.39x10− 3, OR = 1.19 in European). A machine learning model trained on the same data showed moderately accurate prediction of children with overall suicidal ideation with a test ROC-AUC of 0.727 (0.746 in European), and with suicidal attempts with a test ROC-AUC of 0.641 (0.975 in European) in held-out samples. Conclusions and Relevance. This study provides the first quantitative account of polygenic and environmental factors of suicidality in a large, representative population of preadolescent youth. It thus shows the potential utility of the GPSs in identifying a child with high risk for suicidality for early screening, intervention, and prevention.

scholarly journals Association between polygenic propensity for psychiatric disorders and nutrient intake

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Avina K. Hunjan ◽  
Christopher Hübel ◽  
Yuhao Lin ◽  
Thalia C. Eley ◽  
Gerome Breen
Keyword(s):  
Psychiatric Disorders ◽  
Nutrient Intake ◽  
Autism Spectrum ◽  
Dietary Behaviour ◽  
Obsessive Compulsive ◽  
Higher Alcohol ◽  
Polygenic Score ◽  
Compulsive Disorder ◽  
Genome Wide ◽  
Polygenic Scores

AbstractDespite the observed associations between psychiatric disorders and nutrient intake, genetic studies are limited. We examined whether polygenic scores for psychiatric disorders are associated with nutrient intake in UK Biobank (N = 163,619) using linear mixed models. We found polygenic scores for attention-deficit/hyperactivity disorder, bipolar disorder, and schizophrenia showed the highest number of associations, while a polygenic score for autism spectrum disorder showed no association. The relatively weaker obsessive-compulsive disorder polygenic score showed the greatest effect sizes suggesting its association with diet traits may become more apparent with larger genome-wide analyses. A higher alcohol dependence polygenic score was associated with higher alcohol intake and individuals with higher persistent thinness polygenic scores reported their food to weigh less, both independent of socioeconomic status. Our findings suggest that polygenic propensity for a psychiatric disorder is associated with dietary behaviour. Note, nutrient intake was self-reported and findings must therefore be interpreted mindfully.

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.

Abstract P359: A Sickle Cell Variant Associates With Urine Albumin Excretion in Genome Wide Association Study of Hispanics: The HCHS/SOL Study

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Nora Franceschini ◽  
Adrienne Stilp ◽  
Christina L Wassel ◽  
Holly J Mattix-Kramer ◽  
Michael F Flessner ◽  
...  
Keyword(s):  
Allele Frequency ◽  
Sickle Cell ◽  
Missense Variant ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Minority Population ◽  
Genome Wide Association Studies ◽  
Urine Albumin ◽  
Genome Wide ◽  
A Genome

Introduction: Genome wide association studies have identified genetic variants in the Cubillin gene ( CUBN ) that explain inter-individual variation in urine albumin-to-creatinine excretion (UACR) in populations. These studies have not included Hispanics/Latinos, the fast growing minority population in the U.S., who has also high prevalence of chronic kidney disease and its risk factors. Hypothesis: By leveraging on population admixture of Hispanics and using a genome wide association approach, we hypothesized that novel loci associated with UACR would be identified. Methods: We used data from 12,212 self-identified Hispanic individuals recruited in a community-based study, aged 18-74 years at screening (2008-2011), and randomly selected from households in four U.S. field centers (Chicago, IL; Miami, FL; Bronx, NY; San Diego, CA). Urine albumin (mg/dl) and creatinine (g/dl) were measured at the baseline exam. UACR was log-transformed for analysis. Individuals were excluded if reporting to have end-stage renal disease. Genotyping was performed using a custom Illumina Omni2.5M array. Imputation of variants was performed using 1000 Genome Project data from cosmopolitan HapMap samples. After quality control of imputed data, we performed mixed linear regression analyses that accounted for the sampling strategy and family relatedness, for variants with minor allele frequency (MAF) > 0.01 and imputation quality > 0.3. We used additive genetic models and adjusted for age, sex, and principal components which were estimated from the data. In a secondary analysis, we also examine the association of significant variants with kidney function using estimated glomerular filtration rate (eGFR) equations. Results: Among 12,212 participants, 41% were men, and mean age was 46 (SD =13). There was little evidence for genome wide inflation (lambda =1.024). We identified significant associations of single nucleotide polymorphisms (SNPs) with UACR at two loci: CUBN and HBB . The CUBN SNP (chr10:16966414, p=2.1x10-8) is an indel variant with MAF of 0.14, which was not in linkage disequilibrium with previously reported SNP rs1801239 (rsq=0.38, p=1.3x10-4) identified in individuals of European ancestry. The HBB SNP is a missense variant which results in an E [Glu] ⇒ A [Ala] substitution in the beta-globin chain of hemoglobin and a cause of the Mendelian disorder sickle cell anemia (rs334, T allele frequency =0.01, beta=0.44, SE=0.06, p=7.6x10-12). rs344 was not associated with eGFR in our data (p>0.05). Conclusion: This study identified a novel association of a sickle cell missense variant with UACR in Hispanics, and provided evidence for allelic heterogeneity at the CUBN locus. Our findings suggest a role for Mendelian gene variants in increased albuminuria in Hispanic populations with admixture.

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