scholarly journals Evaluating the role of common risk variation in the recurrence risk of schizophrenia in multiplex schizophrenia families

2021 ◽  
Author(s):  
Mohammad Ahangari ◽  
Amanda Gentry ◽  
Tan Hoang Nguyen ◽  
Brian Verrelli ◽  
Silviu-Alin Bacanu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Random Effect ◽  
Recurrence Risk ◽  
Mixed Effects ◽  
Risk Scores ◽  
Continuous Increase ◽  
Polygenic Risk ◽  
Familial Cases ◽  
Multiplex Families

Importance: Multiplex schizophrenia families have higher recurrence risk of schizophrenia compared to the families of singleton cases in the population, but the source of increased familial recurrence risk is unknown. Determining the source of this observation is essential, as it will define the relative focus on common versus rare genetic variation in case-control and family studies of schizophrenia. Objective: To evaluate the role of common risk variation in the recurrence risk of schizophrenia, by comparing the polygenic risk scores in familial versus ancestry matched singleton cases of schizophrenia. Design: We used the latest genome-wide association study data of schizophrenia (N=166,464) to construct polygenic risk scores in multiplex family members, singleton cases and controls. To account for the high degree of relatedness in the samples, analyses were carried out using a mixed effects logistic regression model with the family structure modeled as a random effect. Setting: Population and family based. Participants: We used a large, homogenous sample of 1,005 individuals from 257 families from the Irish Study of High-Density Schizophrenia Families, 2,224 singleton cases and 2,284 population controls all from the population of the island of Ireland. Exposures: Polygenic risk scores, diagnostic categories, familial or singleton case status. Main outcomes and measures: The primary outcomes were the mixed effects logistic regression results generated from comparison between different groups. Results: Polygenic risk scores in singleton cases did not differ significantly from familial cases (p=0.49), rejecting the hypothesis that an increased burden of common risk variation can account for the higher recurrence risk of schizophrenia in multiplex families. Conclusions and relevance: This study suggests that a higher burden of common schizophrenia risk variation cannot account for the increased familial recurrence risk of schizophrenia in multiplex families. In the absence of elevated polygenic risk scores in multiplex schizophrenia families, segregation of rare variation in the genome and environmental exposures unique to the families may explain the increased multiplex familial recurrence risk of schizophrenia. These findings also further validate the concept of a genetically influenced psychosis spectrum in multiplex schizophrenia families as shown by a continuous increase of common risk variation burden from unaffected relatives to familial cases of schizophrenia in the families.

scholarly journals Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases

Stroke ◽  
2021 ◽  
Author(s):  
Gad Abraham ◽  
Loes Rutten-Jacobs ◽  
Michael Inouye
Keyword(s):  
Risk Prediction ◽  
Risk Scores ◽  
Future Research ◽  
Cvd Risk ◽  
Polygenic Risk ◽  
Monogenic Disorders ◽  
Current State ◽  
Common Genetic Variants ◽  
Artery Disease

Early prediction of risk of cardiovascular disease (CVD), including stroke, is a cornerstone of disease prevention. Clinical risk scores have been widely used for predicting CVD risk from known risk factors. Most CVDs have a substantial genetic component, which also has been confirmed for stroke in recent gene discovery efforts. However, the role of genetics in prediction of risk of CVD, including stroke, has been limited to testing for highly penetrant monogenic disorders. In contrast, the importance of polygenic variation, the aggregated effect of many common genetic variants across the genome with individually small effects, has become more apparent in the last 5 to 10 years, and powerful polygenic risk scores for CVD have been developed. Here we review the current state of the field of polygenic risk scores for CVD including stroke, and their potential to improve CVD risk prediction. We present findings and lessons from diseases such as coronary artery disease as these will likely be useful to inform future research in stroke polygenic risk prediction.

scholarly journals Efficient implementation of penalized regression for genetic risk prediction

2018 ◽  
Author(s):  
Florian Privé ◽  
Hugues Aschard ◽  
Michael G.B. Blum
Keyword(s):  
Logistic Regression ◽  
Genetic Risk ◽  
Association Studies ◽  
Predictive Performance ◽  
Penalized Regression ◽  
Risk Scores ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Penalized Logistic Regression

AbstractPolygenic Risk Scores (PRS) consist in combining the information across many single-nucleotide polymorphisms (SNPs) in a score reflecting the genetic risk of developing a disease. PRS might have a major impact on public health, possibly allowing for screening campaigns to identify high-genetic risk individuals for a given disease. The “Clumping+Thresholding” (C+T) approach is the most common method to derive PRS. C+T uses only univariate genome-wide association studies (GWAS) summary statistics, which makes it fast and easy to use. However, previous work showed that jointly estimating SNP effects for computing PRS has the potential to significantly improve the predictive performance of PRS as compared to C+T.In this paper, we present an efficient method to jointly estimate SNP effects, allowing for practical application of penalized logistic regression (PLR) on modern datasets including hundreds of thousands of individuals. Moreover, our implementation of PLR directly includes automatic choices for hyper-parameters. The choice of hyper-parameters for a predictive model is very important since it can dramatically impact its predictive performance. As an example, AUC values range from less than 60% to 90% in a model with 30 causal SNPs, depending on the p-value threshold in C+T.We compare the performance of PLR, C+T and a derivation of random forests using both real and simulated data. PLR consistently achieves higher predictive performance than the two other methods while being as fast as C+T. We find that improvement in predictive performance is more pronounced when there are few effects located in nearby genomic regions with correlated SNPs; for instance, AUC values increase from 83% with the best prediction of C+T to 92.5% with PLR. We confirm these results in a data analysis of a case-control study for celiac disease where PLR and the standard C+T method achieve AUC of 89% and of 82.5%.In conclusion, our study demonstrates that penalized logistic regression can achieve more discriminative polygenic risk scores, while being applicable to large-scale individual-level data thanks to the implementation we provide in the R package bigstatsr.

O-116 Genetic association analyses identify links between pelvic prolapse (PP) and connective tissue biology, cardiovascular and reproductive health

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
N Pujol Gualdo ◽  
K Läll ◽  
M Lepamets ◽  
R Arffman ◽  
T Piltonen ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Meta Analyses ◽  
Personalized Risk

Abstract Study question Can genome-wide association analysis unravel the biological underpinnings of PP and facilitate personalized risk assessment via genetic risk scores construction? Summary answer We unravel novel links with urogenital development and vascular health in PP and present polygenic risk score as a tool to stratify PP risk. What is known already Prolapse is characterized by a descent of the pelvic organs into the vaginal cavity. PP affects around 40% of women after menopause and is the main indication for major gynecological surgery, having an important health, social and economic burden. Although the etiology and biological mechanisms underlying PP remain poorly understood, prior studies suggest genetic factors might play a role. Recently, a genome-wide association study (GWAS) identified seven genome-wide significant loci, located in or near genes involved in connective tissue metabolism and estrogen exposure in the etiology of PP. Study design, size, duration We conducted a three-stage case-control genome-wide association study. Firstly, in the discovery phase, we meta-analyzed Icelandic, UK Biobank and the FinnGen R3 datasets, comprising a total of 20118 cases and 427426 controls of European ancestry. For replication we used an independent dataset from Estonian Biobank (7968 cases and 118895 controls). Finally, we conducted a joint meta-analysis, containing 28086 cases and 546321 controls, which is the largest GWAS of PP to date. Participants/materials, setting, methods We performed functional annotation on genetic variants unraveled by GWAS and integrated these with expression quantitative trait loci and chromatin interaction data. In addition, we looked at enrichment of association signal on gene-set, tissue and cell type level and analyzed associations with other phenotypes both on genetic and phenotypic level. Colocalisation analyses were conducted to help pinpoint causal genes. We further constructed polygenic risk scores to explore options for personalized risk assessment and prevention. Main results and the role of chance In the discovery phase, we identified 18 genetic loci and 20 genetic variants significantly associated with POP (p < 5 × 10−8) and 75% of the variants show nominal significance association (p < 0.05) in the replication. Notably, the joint meta-analyses detected 20 genetic loci significantly associated with POP, from which 13 loci were novel. Novel genetic variants are located in or near genes involved in gestational duration and preterm birth (rs2687728 p = 2.19x10-9, EEFSEC), cardiovascular health and pregnancy success (rs1247943 p = 5.83x10-18, KLF13), endometriosis (rs12325192 p = 3.72x10-18, CRISPLD2), urogenital tract development (rs7126322, p = 4.35x10-15, WT1 and rs42400, p = 4.8x10-10, ADAMTS16) and regulation of the oxytocin receptor (rs2267372, p = 4.49x10-13, MAFF). Further analyses demonstrated that POP GWAS signals colocalise with several eQTLS (including EEFSEC, MAFF, KLF13, etc.), providing further evidence for mapping associated genes. Tissue and cell enrichment analyses underlined the role of the urogenital system, muscle cells, myocytes and adipocytes (p < 0.00001, FDR<0.05). Furthermore, genetic correlation analyses supported a shared genetic background with gastrointestinal disorders, joint and musculoskeletal disorders and cardiovascular disease. Polygenic risk scores analyses included a total of 125551 people in the target dataset, with 5379 prevalent patients and 2517 incident patients. Analyzing the best GRS as a quintile showed association with incident disease (Harrell c-statistic= 0.603, SD = 0.006). Limitations, reasons for caution This GWAS meta-analyses focused on European ancestry populations, which challenges the generalizability of GWAS findings to non-European populations. Moreover, this study included women with PP from population-based biobanks identified using the ICD-10 code N81, which limits analyses considering different disease stages and severity. Wider implications of the findings Our study provides genetic evidence to improve the current understanding of PP pathogenesis and serves as basis for further functional studies. Moreover, we provide a genetic tool for personalized risk stratification, which could help prevent PP development and improve the quality of a vast quantity of women. Trial registration number not applicable

Examining the role of sex hormones in postpartum depression: Polygenic risk scores and adult hippocampal neurogenesis

2017 ◽  
Vol 83 ◽  
pp. 42-43 ◽  
Author(s):  
Demelza Smeeth ◽  
Alish Palmos ◽  
Thomas Bridge ◽  
Cathryn M. Lewis ◽  
Timothy R. Powell ◽  
...  
Keyword(s):  
Postpartum Depression ◽  
Sex Hormones ◽  
Hippocampal Neurogenesis ◽  
Adult Hippocampal Neurogenesis ◽  
Risk Scores ◽  
Polygenic Risk

scholarly journals Household overcrowding and risk of SARS-CoV-2: analysis of the Virus Watch prospective community cohort study in England and Wales

2021 ◽  
Author(s):  
Robert W Aldridge ◽  
Helen Pineo ◽  
Ellen Fragaszy ◽  
Max Eyre ◽  
Jana Kovar ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Fixed Effects ◽  
Respiratory Infections ◽  
Random Effect ◽  
Mixed Effects ◽  
P Value ◽  
England And Wales ◽  
Logistic Regression Models ◽  
Household Level ◽  
Increased Risk

Background: Household overcrowding is associated with increased risk of infectious diseases across cultures and countries. Limited data exist in England and Wales linking household overcrowding and risk of COVID-19. We used data collected from the Virus Watch cohort to examine the association between overcrowded households and infection to pandemic coronavirus SARS-CoV-2. Methods: The Virus Watch study is a household community cohort of acute respiratory infections in England & Wales that began recruitment in June 2020. We calculated the persons per room for each household and classified accommodation as overcrowded when the number of rooms was fewer than the number of people. We considered two primary outcomes - PCR-confirmed positive SARS-CoV-2 antigen tests and laboratory confirmed SARS-CoV-2 antibodies (Roche Elecsys anti-N total immunoglobulin assay). We used mixed effects logistic regression models that accounted for household structure to estimate the association between household overcrowding and SARS-CoV-2 infection. Results: The proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (6.6%; 73/1,102) and lowest in the under-occupied group (2.9%; 682/23,219). In a mixed effects logistic regression model that included age, sex, ethnicity, household income and geographical region as fixed effects, and a household-level random effect, we found strong evidence of an increased odds of having a positive PCR SARS-CoV-2 antigen result (Odds Ratio 3.67; 95% CI: 1.91, 7.06; p-value < 0.001) and increased odds of having a positive SARS-CoV-2 antigen result in individuals living in overcrowded houses (2.99; 95% CI: 1.14, 7.81; p-value =0.03) compared to people living in under-occupied houses. Discussion: Public health interventions to prevent and stop the spread of SARS-CoV-2 should consider the much greater risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission. There is an urgent need to better recognise housing as a leading determinant of health in the context of a pandemic and beyond.

scholarly journals Polygenic risk for psychiatric disorder reveals distinct association profiles across social behaviour in the general population

2021 ◽  
Author(s):  
Fenja Schlag ◽  
Andrea Giuseppe Allegrini ◽  
Jan Buitelaar ◽  
Ellen Verhoef ◽  
Marjolein van Donkelaar ◽  
...  
Keyword(s):  
General Population ◽  
Psychiatric Disorders ◽  
Social Behaviour ◽  
Negative Binomial ◽  
Random Effect ◽  
Population Based ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Shared Genetic

Many complex psychiatric disorders are characterised by a spectrum of social difficulties. These symptoms lie on a behavioural dimension that is shared with social behaviour in the general population, with substantial contributions of genetic factors. However, shared genetic links may vary across psychiatric disorders and social symptoms. Here, we systematically investigate heterogeneity in shared genetic liabilities with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), bipolar disorder (BP), major depression (MD) and schizophrenia, across a spectrum of different social symptoms. Specifically, longitudinally assessed low-prosociality and peer-problem scores in two UK population-based/community-based cohorts (ALSPAC, N ≤ 6174, 4-17 years; TEDS, N ≤ 7112, 4-16 years; parent- and teacher-reports) were regressed on polygenic risk scores for ADHD, ASD, BP, MD, and schizophrenia, as informed by genome-wide summary statistics from large consortia, using negative binomial regression models. Across ALSPAC and TEDS, we replicated univariate polygenic associations between social behaviour and risk for ADHD, MD, and schizophrenia. Modelling univariate genetic effects across both cohorts with random-effect meta-regression revealed evidence for polygenic links between social behaviour and ADHD, ASD, MD, and schizophrenia risk, but not BP, where differences in age, reporter and social trait captured 45-88% in univariate effect variation. For ADHD, MD, and ASD polygenic risk, we identified stronger association with peer problems than low prosociality, while schizophrenia polygenic risk was solely associated with low prosociality. The identified association profiles suggest marked differences in the social genetic architecture underlying different psychiatric disorders when investigating population-based social symptoms across 13 years of child and adolescent development.  

Abstract P879: Differences in Statistical Performance of Polygenic Risk Scores for Cardiovascular Disease Across Different Race/Ethnicities

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Julian N Acosta ◽  
Cameron Both ◽  
Natalia Szejko ◽  
Stacy Brown ◽  
Kevin N Sheth ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Logistic Regression ◽  
Genetic Risk ◽  
Regression Models ◽  
Risk Scores ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Logistic Regression Models ◽  
The Uk ◽  
Significant Health

Introduction: Genome-wide association studies have identified numerous genetic risk variants for stroke and myocardial infarction (MI) in Europeans. However, the limited applicability of these results to non-Europeans due to racial/ethnic differences in the genetic architecture of cardiovascular disease (CVD), coupled with the limited availability of genomic data in non-Europeans, may create significant health disparities now that genomic-based precision medicine is a reality. We tested the hypothesis that the performance of polygenic risk scores (PRS) for CVD differ in Europeans versus non-Europeans. Methods: We conducted a nested study within the UK Biobank, a prospective, population-based study that enrolled ~500,000 participants across the UK. For this study, we identified self-reported black participants and randomly matched them 1:1 by age and sex with white participants. We created a PRS using previously discovered loci for stroke and MI. We then tested whether this PRS representing the aggregate polygenic susceptibility to CVD yielded similar precision in black versus white participants in logistic regression models. Results: Of the 502,536 participants enrolled in the UK Biobank, 8,061 were self-reported blacks, with 7,644 having available data for our analyses. We randomly matched these participants with white individuals, leading to a total sample size of 15,288 (mean age 51.9 [SD 8.1], female 8,722 [57%]). The total number of events was 741 overall, with 363 happening in blacks and 378 happening in whites. In logistic regression models including age, sex, and 5 principal components, the statistical precision (e.g. narrower confidence intervals) for the PRS was substantially higher for whites (OR 1.22, 95%CI 1.08 - 1.37; p<0.0001) compared to blacks (OR 1.24, 95%CI 1.05-1.47; p=0.01). Secondary analyses using genetically-determined ancestry yielded similar results. Conclusion: Because CVD-related PRSs are derived mainly using genetic risk factors identified in populations of European ancestry, their statistical performance is lower in non-European populations. This asymmetry can lead to significant health disparities now that these tools are being evaluated in multiple precision medicine approaches.

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