Metasubtract: an R‐package to analytically produce leave‐one‐out meta‐analysis GWAS summary statistics

SUMMARY: statistics from a meta-analysis of genome-wide association studies (meta-GWAS) can be used for many follow-up analyses. One valuable application is the creation of polygenic scores. However, if polygenic scores are calculated in a validation cohort that was part of the meta-GWAS consortium, this cohort is not independent and analyses will therefore yield inflated results. The R package 'MetaSubtract' was developed to subtract the results of the validation cohort from meta-GWAS summary statistics analytically. The statistical formulas for a meta-analysis were inverted to compute corrected summary statistics of a meta-GWAS leaving one (or more) cohort(s) out. These formulas have been implemented in MetaSubtract for different meta-analyses methods (fixed effects inverse variance or square root sample size weighted z-score) accounting for no, single or double genomic control correction. Results obtained by MetaSubtract correlate very well to those calculated using the traditional way, i.e. by performing a meta-analysis leaving out the validation cohort. In conclusion, MetaSubtract allows researchers to compute meta-GWAS summary statistics that are independent of the GWAS results of the validation cohort without requiring access to the cohort level GWAS results of the corresponding meta-GWAS consortium. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/web/packages/MetaSubtract. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Genetic pre-screening for glaucoma in population-based epidemiology:protocol for a double-blind prospective screening study within Lifelines (EyeLife)

BACKGROUND: Early detection of glaucoma is paramount to maintain patients' eyesight, however glaucomatous vision loss tends to begin in the periphery with up to 50% of patients unaware they are affected. Because glaucomatous vision loss is permanent, screening appears attractive, but currently is not cost-effective. Therefore we aim to investigate the utility of genetic pre-screening for glaucoma in a population-based setting, called EyeLife. METHODS: EyeLife adopts a double blind prospective design with contrasting groups. Selected participants (n = 1600) from the Lifelines cohort are 55 years of age or older, and of either the highest or lowest 20% of the genetic risk distribution for glaucoma. We obtained a highly curated list of genetic variants from the literature to obtain each participants' genetic risk for glaucoma. Participants will undergo comprehensive ophthalmic screening. The primary outcome is the relative risk of glaucoma given a high genetic risk compared to a low genetic risk. DISCUSSION: If genetic pre-screening is successful, it will increase the yield of a glaucoma screening program by focusing on high-risk individuals. This, in turn, may improve long-term visual health of middle-aged and elderly people. TRIAL REGISTRATION: Ethics approval was obtained on January 31, 2019, and the study was retrospectively registered with the Netherlands Trial Register ( NL8718 ) on the 17th of June, 2020

Ethnic differences in prevalence of Dupuytren disease can partly be explained by known genetic risk variants

Dupuytren disease (DD), a fibroproliferative disorder of the palmar fascia that causes flexion contractures in the fingers, is prevalent in people of North-Western European descent and less so in other ethnicities. DD is a complex disorder, influenced by genetic risk variants. We aimed to study if the marked differences in prevalences in DD between ethnic (sub)groups could be explained by differences in allele frequencies of the 26 known genetic risk variants of DD. Therefore, genetic risk scores (GRS) composed of the 26 DD risk variants were calculated for the 26 populations from the 1000 Genomes database and correlated to observed DD prevalences from literature. For comparison, GRSs were generated for 10,000 sets of 26 random SNPs and also correlated to the observed DD prevalences to determine the significance of the observed correlation. To determine whether differences in allele frequencies between ethnicities were caused by natural selection, fixation indices (Fst) were calculated from the 26 SNPs and from the sets of 26 random SNPs for comparison. Observed prevalences could be determined from literature for 10 populations. Their correlation with the GRS composed of DD SNPs proved to be 0.60 (p = 0.0003). The Fsts between British and other populations were low for European, ad mixed American, and South-Asian populations, and moderate for East-Asians. African populations were significantly different from expected values determined from the random sets. In conclusion, the 26 known genetic risk variants associated with DD explain for a substantial part (R-2 = 0.36) the differing DD prevalences observed between ethnicities

Novel genes for QTc interval. How much heritability is explained, and how much is left to find?

The corrected QT (QTc) interval is a complex quantitative trait, believed to be influenced by several genetic and environmental factors. It is a strong prognostic indicator of cardiovascular mortality in patients with and without cardiac disease. More than 700 mutations have been described in 12 genes (LQT1-LQT12) involved in congenital long QT syndrome. However, the heritability (genetic contribution) of QTc interval in the general population cannot be adequately explained by these long QT syndrome genes. In order to further investigate the genetic architecture underlying QTc interval in the general population, genome-wide association studies, in which up to one million single nucleotide polymorphisms are assayed in thousands of individuals, are now being employed and have already led to the discovery of variants in seven novel loci and five loci that are known to cause congenital long or short QT syndrome. Here we show that a combined risk score using 11 of these loci explains about 10% of the heritability of QTc. Additional discovery of both common and rare variants will yield further etiological insight and accelerate clinical applications

Validating the doubly weighted genetic risk score for the prediction of type 2 diabetes in the Lifelines and Estonian Biobank cohorts

As many cases of type 2 diabetes (T2D) are likely to remain undiagnosed, better tools for early detection of high-risk individuals are needed to prevent or postpone the disease. We investigated the value of the doubly weighted genetic risk score (dwGRS) for the prediction of incident T2D in the Lifelines and Estonian Biobank (EstBB) cohorts. The dwGRS uses an additional weight for each single nucleotide polymorphism in the risk score, to correct for “Winner's curse” bias in the effect size estimates. The traditional (single-weighted genetic risk score; swGRS) and dwGRS were calculated for participants in Lifelines (n = 12,018) and EstBB (n = 34,129). The dwGRS was found to have stronger association with incident T2D (hazard ratio [HR] = 1.26 [95% confidence interval: 1.10–1.43] and HR = 1.35 [1.28–1.42]) compared to the swGRS (HR = 1.21 [1.07–1.38] and HR = 1.25 [1.19–1.32]) in Lifelines and EstBB, respectively. Comparing the 5-year predicted risks from the models with and without the dwGRS, the continuous net reclassification index was 0.140 (0.034–0.243; p =.009 Lifelines), and 0.257 (0.194–0.319; p < 2 × 10−16 EstBB). The dwGRS provided incremental value to the T2D prediction model with established phenotypic predictors. It clearly distinguished the risk groups for incident T2D in both biobanks thereby showing its clinical relevance

Polygenic risk for aggressive behavior from late childhood through early adulthood

Twin studies suggest a substantial role for genes in explaining individual differences in aggressive behavior across development. It is unclear, however, how directly measured genetic risk is associated with aggressive behavior at different moments across adolescence and how genes might distinguish developmental trajectories of aggressive behavior. Here, a polygenic risk score derived from the EAGLE-Consortium genome-wide association study of aggressive behavior in children was tested as predictor of latent growth classes derived from those measures in an adolescent population (n = 2229, of which n = 1246 with genetic information) and a high-risk sample (n = 543, of which n = 335 with genetic information). In the population sample, the polygenic risk score explained variation in parent-reported aggressive behavior at all ages and distinguished between stable low aggressive behavior and moderate and high-decreasing trajectories based on parent-report. In contrast, the polygenic risk score was not associated with self- and teacher-reported aggressive behavior, and no associations were found in the high-risk sample. This pattern of results suggests that methodological choices made in genome-wide association studies impact the predictive strength of polygenic risk scores, not just with respect to power but likely also in terms of generalizability and specificity.</p

The associations of CNR1 SNPs and haplotypes with vulnerability and treatment response phenotypes in Han Chinese with major depressive disorder:A case-control association study

BACKGROUND: Understanding how genetic polymorphisms are associated with the pathophysiology of major depressive disorder (MDD) may aid in diagnosis and the development of personalized treatment strategies. CNR1 is the gene coding Cannabinoid type 1 receptor which is highly involved in emotional processing and in regulating neurotransmitter releases. We aimed to investigate the associations of CNR1 single‐nucleotide polymorphisms (SNPs) with MDD susceptibility and treatment response. METHODS: The study reported data on 181 Han Chinese with MDD and 80 healthy controls. The associations of CNR1 genetic polymorphisms with MDD susceptibility and treatment response were examined, wherein the MDD patients were subgrouped further by responding to antidepressant treatment, compared with healthy controls separately. RESULTS: The CNR1 SNPs rs806367 and rs6454674 and haplotype C‐T‐T‐C of rs806366, rs806367, rs806368, and rs806370 were associated with increased susceptibility for MDD and antidepressant treatment resistance, but the association was not detected in other SNPs or the haplotype block of rs806368 and rs806370. CONCLUSION: The CNR1 is a promising candidate for the genetic association study of MDD. Larger and well‐characterized samples are required to confirm the genetic association of CNR1 with MDD because of the limitations such as relatively small sample size and lack of information for correcting confounding factors

GWASinspector:comprehensive quality control of genome-wide association study results

Quality control (QC) of genome wide association study (GWAS) result files has become increasingly difficult due to advances in genomic technology. The main challenges include continuous increases in the number of polymorphic genetic variants contained in recent GWASs and reference panels, the rising number of cohorts participating in a GWAS consortium, and inclusion of new variant types. Here, we present GWASinspector, a flexible R package for comprehensive QC of GWAS results. This package is compatible with recent imputation reference panels, handles insertion/deletion and multi-allelic variants, provides extensive QC reports and efficiently processes big data files. Reference panels covering three human genome builds (NCBI36, GRCh37 and GRCh38) are available. GWASinspector has a user friendly design and allows easy set-up of the QC pipeline through a configuration file. In addition to checking and reporting on individual files, it can be used in preparation of a meta-analysis by testing for systemic differences between studies and generating cleaned, harmonized GWAS files. Comparison with existing GWAS QC tools shows that the main advantages of GWASinspector are its ability to more effectively deal with insertion/deletion and multi-allelic variants and its relatively low memory use

Development and validation of a questionnaire-based myopia proxy in adults:the LifeLines Cohort Study

Aims To build a questionnaire-based myopia proxy and to validate the proxy by confirming its association with educational attainment and a Polygenic Risk Score (PRS) for myopia. Methods Data were collected between 2014 and 2017 from 88 646 Dutch adults from the LifeLines Cohort. First, we performed principal component analysis (PCA) to responses of five refraction-status questions. Second, we measured the refractive state in a subset of LifeLines participants (n=326) and performed logistic regression using myopia (mean spherical equivalent</p