Gene-based Tests Research Articles

Exome-wide screening identifies novel rare risk variants for major depression disorder.

Despite thousands of common genetic loci of major depression disorders (MDD) have been identified by GWAS to date, a large proportion of genetic variation predisposing to MDD remains unaccounted for. By utilizing the newly released UK Biobank 200,643 exome dataset, we conducted an exome-wide association study to identify rare risk variants contributing to MDD. After quality control, 120,033 participants with MDD polygenic risk scores (PRS) values were included. The individuals with lower 30% quantile of the PRS value were filtered for case and control selecting. Then the cases were set as the individuals with upper 10% quantile of the PHQ depression score and lower 10% quantile were set as controls. Finally, 1612 cases and 1612 controls were included in this study. The variants were annotated by ANNOVRA software. After exclusions, 34,761 qualifying variants, including 148 frameshift variant, 335 non-frameshift variant, 33,758 nonsynonymous, 91 start-loss, 393 stop-gain, 36 stop-loss variants were imported into the SKAT R-package to perform single variants, gene-based burden and robust burden tests with minor allele frequency (MAF) < 0.01. Single variant association testing identified one variant, rs4057749 (P = 5.39 × 10-9), within OR8B4 gene at an exome-wide significance level. The gene-based burden test of the exonic variants identified genome-wide significant associations in OR8B4 (PSKAT = 6.23 × 10-5, PSKAT Robust = 4.49 × 10-5), TRAPPC11 (PSKAT = 0.014, PSKAT Robust = 0.015), SBK3 (PSKAT = 0.020, PSKAT Robust = 0.025) and TNRC6B (PSKAT = 0.026, PSKAT Robust = 0.036). We identified multiple novel rare risk variants contributing to MDD in the individuals with lower PRS of MDD. The findings can help to broaden the genetic insights of the MDD pathogenesis.

Omnibus testing approach for gene-based gene-gene interaction.

Genetic interaction is considered as one of the main heritable component of complex traits. With the emergence of genome-wide association studies (GWAS), a collection of statistical methods dedicated to the identification of interaction at the SNP level have been proposed. More recently, gene-based gene-gene interaction testing has emerged as an attractive alternative as they confer advantage in both statistical power and biological interpretation. Most of the gene-based interaction methods rely on a multidimensional modeling of the interaction, thus facing a lack of robustness against the huge space of interaction patterns. In this paper, we study a global testing approaches to address the issue of gene-based gene-gene interaction. Based on a logistic regression modeling framework, all SNP-SNP interaction tests are combined to produce a gene-level test for interaction. We propose an omnibus test that takes advantage of (1) the heterogeneity between existing global tests and (2) the complementarity between allele-based and genotype-based coding of SNPs. Through an extensive simulation study, it is demonstrated that the proposed omnibus test has the ability to detect with high power the most common interaction genetic models with one causal pair as well as more complex genetic models where more than one causal pair is involved. On the other hand, the flexibility of the proposed approach is shown to be robust and improves power compared to single global tests in replication studies. Furthermore, the application of our procedure to real datasets confirms the adaptability of our approach to replicate various gene-gene interactions.

Examining the Association between Mitochondrial Genome Variation and Coronary Artery Disease.

Large-scale genome-wide association studies have identified hundreds of single-nucleotide variants (SNVs) significantly associated with coronary artery disease (CAD). However, collectively, these explain <20% of the heritability. Hypothesis: Here, we hypothesize that mitochondrial (MT)-SNVs might present one potential source of this “missing heritability”. Methods: We analyzed 265 MT-SNVs in ~500,000 UK Biobank individuals, exploring two different CAD definitions: a more stringent (myocardial infarction and/or revascularization; HARD = 20,405), and a more inclusive (angina and chronic ischemic heart disease; SOFT = 34,782). Results: In HARD cases, the most significant (p < 0.05) associations were for m.295C>T (control region) and m.12612A>G (ND5), found more frequently in cases (OR = 1.05), potentially related to reduced cardiorespiratory fitness in response to exercise, as well as for m.12372G>A (ND5) and m.11467A>G (ND4), present more frequently in controls (OR = 0.97), previously associated with lower ROS production rate. In SOFT cases, four MT-SNVs survived multiple testing corrections (at FDR < 5%), all potentially conferring increased CAD risk. Of those, m.11251A>G (ND4) and m.15452C>A (CYB) have previously shown significant associations with body height. In line with this, we observed that CAD cases were slightly less physically active, and their average body height was ~2.00 cm lower compared to controls; both traits are known to be related to increased CAD risk. Gene-based tests identified CO2 associated with HARD/SOFT CAD, whereas ND3 and CYB associated with SOFT cases (p < 0.05), dysfunction of which has been related to MT oxidative stress, obesity/T2D (CO2), BMI (ND3), and angina/exercise intolerance (CYB). Finally, we observed that macro-haplogroup I was significantly (p < 0.05) more frequent in HARD cases vs. controls (3.35% vs. 3.08%), potentially associated with response to exercise. Conclusions: We found only spurious associations between MT genome variation and HARD/SOFT CAD and conclude that more MT-SNV data in even larger study cohorts may be needed to conclusively determine the role of MT DNA in CAD.

Whole-genome sequencing reveals novel ethnicity-specific rare variants associated with Alzheimer’s disease

Alzheimer’s disease (AD) is the most common multifactorial neurodegenerative disease among elderly people. Genome-wide association studies (GWAS) have been highly successful in identifying genetic risk factors. However, GWAS investigate common variants, which tend to have small effect sizes, and rare variants with potentially larger phenotypic effects have not been sufficiently investigated. Whole-genome sequencing (WGS) enables us to detect those rare variants. Here, we performed rare-variant association studies by using WGS data from 140 individuals with probable AD and 798 cognitively normal elder controls (CN), as well as single-nucleotide polymorphism genotyping data from an independent large Japanese AD cohort of 1604 AD and 1235 CN subjects. We identified two rare variants as candidates for AD association: a missense variant in OR51G1 (rs146006146, c.815 G > A, p.R272H) and a stop-gain variant in MLKL (rs763812068, c.142 C > T, p.Q48X). Subsequent in vitro functional analysis revealed that the MLKL stop-gain variant can contribute to increases not only in abnormal cells that should die by programmed cell death but do not, but also in the ratio of Aβ42 to Aβ40. We further detected AD candidate genes through gene-based association tests of rare variants; a network-based meta-analysis using these candidates identified four functionally important hub genes (NCOR2, PLEC, DMD, and NEDD4). Our findings will contribute to the understanding of AD and provide novel insights into its pathogenic mechanisms that can be used in future studies.

Gene-based association tests using GWAS summary statistics and incorporating eQTL

Although genome-wide association studies (GWAS) have been successfully applied to a variety of complex diseases and identified many genetic variants underlying complex diseases via single marker tests, there is still a considerable heritability of complex diseases that could not be explained by GWAS. One alternative approach to overcome the missing heritability caused by genetic heterogeneity is gene-based analysis, which considers the aggregate effects of multiple genetic variants in a single test. Another alternative approach is transcriptome-wide association study (TWAS). TWAS aggregates genomic information into functionally relevant units that map to genes and their expression. TWAS is not only powerful, but can also increase the interpretability in biological mechanisms of identified trait associated genes. In this study, we propose a powerful and computationally efficient gene-based association test, called Overall. Using extended Simes procedure, Overall aggregates information from three types of traditional gene-based association tests and also incorporates expression quantitative trait locus (eQTL) information into a gene-based association test using GWAS summary statistics. We show that after a small number of replications to estimate the correlation among the integrated gene-based tests, the p values of Overall can be calculated analytically. Simulation studies show that Overall can control type I error rates very well and has higher power than the tests that we compared with. We also apply Overall to two schizophrenia GWAS summary datasets and two lipids GWAS summary datasets. The results show that this newly developed method can identify more significant genes than other methods we compared with.

Abstract 018: Whole Genome Sequence Analysis Of Apparent Treatment Resistant Hypertension Status In Participants From The Trans-omics For Precision Medicine Program

Background: Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive classes to achieve blood pressure (BP) control. The estimated prevalence of aTRH from population-based studies is ~12-15% among adults with hypertension (HTN). Individuals with aTRH have an increased risk for cardiovascular events compared to those individuals with controlled HTN. Hypothesis: We hypothesize that identifying the genetic contributors to aTRH may provide insight on its etiology. Methods: We conducted case-control single-variant and gene-based analyses of aTRH among individuals treated for HTN from 13 TOPMed cohorts with whole-genome sequencing data. Cases were defined as individuals treated for HTN taking three different antihypertensive classes, with average BP ≥ 140/90 mmHg, or four or more medications regardless of BP level (n=2,616; 68% African Ancestry, AA). A normotensive control group (n=6,062; 42% AA) was defined as individuals with BP &lt;140/90 mmHg. A second control group comprised individuals who were treatment responsive on one antihypertensive medication with BP &lt;140/90 mmHg (n=26,356; 29% AA). We performed logistic regression with kinship adjustment using the S calable and A ccurate Implementation of Ge neralized mixed models (SAIGE) and adjusted for age, sex, and genetic ancestry. We assessed variants using SKAT-O within EPACTS in a rare-variant, gene-based analysis. Gene-based tests were stratified by functional impact of variants (e.g. high or high-moderate), as well as race (AA, European Ancestry (EA), and race-combined) for each case-control model. We used a Bonferroni correction to correct for multiple testing. Results: An intronic variant (rs142681624) in ZFHX3 (p=2.44E-08) exceeded the significance threshold in the case vs treatment responsive control analysis in the AA stratum. The variant was replicated in AAs from the Genetics of Hypertension Associated Treatments (GenHAT) study (p=0.016) with the same direction of effect. In the gene-based analyses in the EA stratum, ERG was statistically significant in the case vs normotensive control analysis (32 variants/ 27 singletons, p=2.22E-14) and marginally significant in the case vs treatment responsive control analysis (16 singletons; p=7.69E-06). Conclusions: We identified and replicated a ZFHX3 v ariant from our single-variant analysis in AAs. ZFHX3 has been implicated in atrial fibrillation, systolic BP, hydrochlorothiazide-induced metabolic effects, and ischemic stroke. Gene-based tests in EAs identified ERG as a gene of interest. The ERG intronic variant rs117870289 has been previously associated with diastolic BP, pulse pressure, and coronary artery disease. The 16 singletons were not in LD with rs117870289. Additional work validating these loci is warranted to determine whether these regions influence the pathobiology of aTRH.

Polygenic risk impacts PDGFRA mutation penetrance in non-syndromic cleft lip and palate.

Non-syndromic cleft lip with or without cleft palate (NSCL/P) is a common, severe craniofacial malformation that imposes significant medical, psychosocial and financial burdens. NSCL/P is a multifactorial disorder with genetic and environmental factors playing etiologic roles. Currently, only 25% of the genetic variation underlying NSCL/P has been identified by linkage, candidate gene and genome-wide association studies. In this study, whole-genome sequencing and genome-wide genotyping followed by polygenic risk score (PRS) and linkage analyses were used to identify the genetic etiology of NSCL/P in a large three-generation family. We identified a rare missense variant in PDGFRA (c.C2740T; p.R914W) as potentially etiologic in a gene-based association test using pVAAST (P = 1.78×10-4) and showed decreased penetrance. PRS analysis suggested that variant penetrance was likely modified by common NSCL/P risk variants, with lower scores found among unaffected carriers. Linkage analysis provided additional support for PRS-modified penetrance, with a 7.4-fold increase in likelihood after conditioning on PRS. Functional characterization experiments showed that the putatively causal variant was null for signaling activity in vitro; further, perturbation of pdgfra in zebrafish embryos resulted in unilateral orofacial clefting. Our findings show that a rare PDGFRA variant, modified by additional common NSCL/P risk variants, have a profound effect on NSCL/P risk. These data provide compelling evidence for multifactorial inheritance long postulated to underlie NSCL/P and may explain some unusual familial patterns.

Potential Involvement of NSD1, KRT24 and ACACA in the Genetic Predisposition to Colorectal Cancer.

Simple SummaryMethods used for the identification of hereditary cancer genes have evolved in parallel to technological progress; however, much of the genetic predisposition to cancer remains unexplained. A new in silico method based on Knudson’s two-hit hypothesis recently identified ~50 putative cancer predisposing genes, but their actual association with cancer has not yet been validated. In our study, we aimed to assess the involvement of these genes in familial/early-onset colorectal cancer (CRC) using different lines of evidence. Our results indicated that most of those genes were not associated with a genetic predisposition to CRC, but suggested a possible association for NSD1, KRT24 and ACACA.The ALFRED (Allelic Loss Featuring Rare Damaging) in silico method was developed to identify cancer predisposition genes through the identification of somatic second hits. By applying ALFRED to ~10,000 tumor exomes, 49 candidate genes were identified. We aimed to assess the causal association of the identified genes with colorectal cancer (CRC) predisposition. Of the 49 genes, NSD1, HDAC10, KRT24, ACACA and TP63 were selected based on specific criteria relevant for hereditary CRC genes. Gene sequencing was performed in 736 patients with familial/early onset CRC or polyposis without germline pathogenic variants in known genes. Twelve (predicted) damaging variants in 18 patients were identified. A gene-based burden test in 1596 familial/early-onset CRC patients, 271 polyposis patients, 543 TCGA CRC patients and >134,000 controls (gnomAD, non-cancer), revealed no clear association with CRC for any of the studied genes. Nevertheless, (non-significant) over-representation of disruptive variants in NSD1, KRT24 and ACACA in CRC patients compared to controls was observed. A somatic second hit was identified in one of 20 tumors tested, corresponding to an NSD1 carrier. In conclusion, most genes identified through the ALFRED in silico method were not relevant for CRC predisposition, although a possible association was detected for NSD1, KRT24 and ACACA.

The genetics of glaucoma: Disease associations, personalised risk assessment and therapeutic opportunities-A review.

Glaucoma refers to a heterogenous group of disorders characterised by progressive loss of retinal ganglion cells and associated visual field loss. Both early-onset and adult-onset forms of the disease have a strong genetic component. Here, we summarise the known genetic associations for various forms of glaucoma and the possible functional roles for these genes in disease pathogenesis. We also discuss efforts to translate genetic knowledge into clinical practice, including gene-based tests for disease diagnosis and risk-stratification as well as gene-based therapies.

Precision management of gene-based tests not covered by the National Health Insurance system in Japan: a questionnaire-based study.

Precision management of gene-based tests not covered by the National Health Insurance system in Japan: a questionnaire-based study.

Associations of risk genes with onset age and plasma biomarkers of Alzheimer's disease: a large case-control study in mainland China.

Most genetic studies concerning risk genes in Alzheimer's disease (AD) are from Caucasian populations, whereas the data remain limited in the Chinese population. In this study, we systematically explored the relationship between AD and risk genes in mainland China. We sequenced 33 risk genes previously reported to be associated with AD in a total of 3604 individuals in the mainland Chinese population. Common variant (MAF ≥ 0.01) based association analysis and gene-based (MAF < 0.01) association test were performed by PLINK 1.9 and Sequence Kernel Association Test-Optimal, respectively. Polygenic risk score (PRS) was calculated, and receiver operating characteristic curve (AUC) was computed. Plasma Aβ42, Aβ40, total tau (T-tau), and neurofilament light chain (NFL) were tested in a subgroup, and their associations with PRS were conducted using the Spearman correlation test. Six common variants varied significantly between AD patients and cognitively normal controls after the adjustment of age, gender, and APOE ε4 status, including variants in ABCA7 (n = 5) and APOE (n = 1). Among them, four variants were novel and two were reported previously. The AUC of PRS was 0.71. The high PRS was significantly associated with an earlier age at onset (P = 4.30 × 10-4). PRS was correlated with plasma Aβ42, Aβ42/Aβ40 ratio, T-tau, and NFL levels. Gene-based association test revealed that ABCA7 and UNC5C reached statistical significance. The common variants in APOE and ABCA7, as well as rare variants in ABCA7 and UNC5C, may contribute to the etiology of AD. Moreover, the PRS, to some extent, could predict the risk, onset age, and biological changes of AD.

Contribution of Rare Genetic Variation to Disease Susceptibility in a Large Scandinavian Myositis Cohort.

Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of complex autoimmune conditions characterized by inflammation in skeletal muscle and extramuscular compartments, and interferon (IFN) system activation. We undertook this study to examine the contribution of genetic variation to disease susceptibility and to identify novel avenues for research in IIMs. Targeted DNA sequencing was used to mine coding and potentially regulatory single nucleotide variants from ~1,900 immune-related genes in a Scandinavian case-control cohort of 454 IIM patients and 1,024 healthy controls. Gene-based aggregate testing, together with rare variant- and gene-level enrichment analyses, was implemented to explore genotype-phenotype relations. Gene-based aggregate tests of all variants, including rare variants, identified IFI35 as a potential genetic risk locus for IIMs, suggesting a genetic signature of type I IFN pathway activation. Functional annotation of the IFI35 locus highlighted a regulatory network linked to the skeletal muscle-specific gene PTGES3L, as a potential candidate for IIM pathogenesis. Aggregate genetic associations with AGER and PSMB8 in the major histocompatibility complex locus were detected in the antisynthetase syndrome subgroup, which also showed a less marked genetic signature of the type I IFN pathway. Enrichment analyses indicated a burden of synonymous and noncoding rare variants in IIM patients, suggesting increased disease predisposition associated with these classes of rare variants. Our study suggests the contribution of rare genetic variation to disease susceptibility in IIM and specific patient subgroups, and pinpoints genetic associations consistent with previous findings by gene expression profiling. These features highlight genetic profiles that are potentially relevant to disease pathogenesis.

Rare coding variants in 35 genes associate with circulating lipid levels—A multi-ancestry analysis of 170,000 exomes

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

Genetic Variants Correlate With Better Processing Speed

Some cognitive abilities, such as vocabulary, are resilient to brain aging, while others such as conceptual reasoning, memory, and processing speed, decline with age and their rate of decline is genetically regulated. Despite the strong genetic heritability of processing speed assessed by the digit symbol substitution test (DSST), previous studies have failed to identify robust common genetic variants associated with this test. The Long Life Family Study (LLFS) includes long lived individuals and their family members who maintain good DSST scores as they age and who may carry variants associated with better DSST. We therefore conducted a genome-wide association study (GWAS) of DSST in LLFS using ~15M genetic variants imputed to the HRC panel of 64,940 haplotypes with 39,635,008 sites and replicated the findings using genetic data imputed to the 1000 Genomes phase 3 reference panel combining two Danish cohorts: the Middle Aged Danish Twins and the Longitudinal Study of Aging Danish Twins. The GWAS in LLFS discovered 20 rare genetic variants reaching genome-wide significance (p-value < 5x10-8), including 18 variants associated with better processing speed with large effect size. The genetic associations of rs7623455, rs9821776, rs9821587, rs78704059 in chromosome 3 were replicated in the combined Danish cohort. These genetic variants tagged two hormone receptor related genes, THRB and RARB, both related to cognitive aging. Further gene-based tests in LLFS confirmed that these two genes have protective variants associated with better processing speed.

Gene-Based Testing of Interactions Using XGBoost in Genome-Wide Association Studies.

Among the myriad of statistical methods that identify gene–gene interactions in the realm of qualitative genome-wide association studies, gene-based interactions are not only powerful statistically, but also they are interpretable biologically. However, they have limited statistical detection by making assumptions on the association between traits and single nucleotide polymorphisms. Thus, a gene-based method (GGInt-XGBoost) originated from XGBoost is proposed in this article. Assuming that log odds ratio of disease traits satisfies the additive relationship if the pair of genes had no interactions, the difference in error between the XGBoost model with and without additive constraint could indicate gene–gene interaction; we then used a permutation-based statistical test to assess this difference and to provide a statistical p-value to represent the significance of the interaction. Experimental results on both simulation and real data showed that our approach had superior performance than previous experiments to detect gene–gene interactions.

Testing Gene-Gene Interactions Based on a Neighborhood Perspective in Genome-wide Association Studies.

Unexplained genetic variation that causes complex diseases is often induced by gene-gene interactions (GGIs). Gene-based methods are one of the current statistical methodologies for discovering GGIs in case-control genome-wide association studies that are not only powerful statistically, but also interpretable biologically. However, most approaches include assumptions about the form of GGIs, which results in poor statistical performance. As a result, we propose gene-based testing based on the maximal neighborhood coefficient (MNC) called gene-based gene-gene interaction through a maximal neighborhood coefficient (GBMNC). MNC is a metric for capturing a wide range of relationships between two random vectors with arbitrary, but not necessarily equal, dimensions. We established a statistic that leverages the difference in MNC in case and in control samples as an indication of the existence of GGIs, based on the assumption that the joint distribution of two genes in cases and controls should not be substantially different if there is no interaction between them. We then used a permutation-based statistical test to evaluate this statistic and calculate a statistical p-value to represent the significance of the interaction. Experimental results using both simulation and real data showed that our approach outperformed earlier methods for detecting GGIs.

Molecular analysis and novel variation identification of Chinese pedigrees with mucopolysaccharidosis using targeted next-generation sequencing

BackgroundMucopolysaccharidosis (MPS) refers to a group of lysosomal storage disorders for which seven types and 11 subtypes are currently recognized. Targeted next-generation sequencing (NGS) offers an important method of disease typing, diagnosis, prenatal diagnosis, and treatment. MethodsGene variations in 48 Chinese MPS patients were evaluated using NGS, and the pathogenicity of the DNA alterations was evaluated using PolyPhen2, SIFT, and Mutation Taster. The effect of amino acid substitution on protein structure was also assessed. ResultsFour pedigrees with MPS I (8.3%), 28 with MPS II (58.3%), two with MPS IIIA (4.2%), two with MPS IIIB (4.2%), six with MPS IVA (12.5%), one with MPS IVB (2.1%), and five with MPS VI (10.4%) were identified. Of the 69 variations identified, 11 were novel variants (three in IDUA, five in IDS, and three in GALNS), all of which were predicted to be disease-causing except for one, and were associated with impaired protein structure and function. ConclusionsTargeted NGS technology is effective for the gene-based testing of MPS disorders, which show high allelic heterogeneity. MPS II was the predominant form in Chinese. Our study expands the existing variation spectrum of MPS, which is important for disease management and genetic counseling.

Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes

Gene-based tests are valuable techniques for identifying genetic factors in complex traits. Here, we propose a gene-based testing framework that incorporates data on long-range chromatin interactions, several recent technical advances for region-based tests, and leverages the knockoff framework for synthetic genotype generation for improved gene discovery. Through simulations and applications to genome-wide association studies (GWAS) and whole-genome sequencing data for multiple diseases and traits, we show that the proposed test increases the power over state-of-the-art gene-based tests in the literature, identifies genes that replicate in larger studies, and can provide a more narrow focus on the possible causal genes at a locus by reducing the confounding effect of linkage disequilibrium. Furthermore, our results show that incorporating genetic variation in distal regulatory elements tends to improve power over conventional tests. Results for UK Biobank and BioBank Japan traits are also available in a publicly accessible database that allows researchers to query gene-based results in an easy fashion.

Abstract 10479: Genome Wide Association Study For Acute Kidney Injury In Patients Undergoing Off-pump Coronary Artery Bypass Graft Surgery

Introduction: In this study, we evaluated the genetic predisposition to AKI using genome-wide association study (GWAS) in patients undergoing elective off-pump-CABG (OP-CABG). Methods: Patients of South Asian ancestry were categorized into four cohorts as follows: (A) patients with normal renal function undergoing OP-CABG (eGFR&gt;60ml/min/m2) (n=754; AKI - 81, Non-AKI-673); (B) patients with renal dysfunction (eGFR&lt;60ml/min/m2; not needing dialysis) undergoing OP-CABG (n=263; AKI-169, non-AKI-89); (C) patients with renal dysfunction with no symptomatic/known heart disease (n=92); (D) age-matched healthy control population (with normal kidney function, without symptomatic/known heart disease) (n=826). Renal function was considered to be normal, if the serum creatinine was less than 1.3mg% and/or estimated glomerular filtration rate was greater than 60ml/min/1.7 m 2 . Genotyping was performed using Infinium Global Screening Array-24 v3.0 BeadChip from Illumina, which included 6,54,027 markers. GWAS analysis was performed using age, genders and top10 principal components as covariates using logistic regression using PLINK 2.0. Postoperative AKI was defined based on Kidney Disease Improving Global Outcomes guidelines. Results: There were 754 participants with good renal function undergoing OP-CABG; among them, 81 subjects developed AKI postoperatively. The GWAS analysis revealed 607 markers with a suggestive significance p-value threshold of 1e-4. A modest signal was observed on chromosome 11 region, covering genes such as COX8A, NAA40, RCOR. The gene-based test in FUMA annotation revealed genes, MARCOD2, CNTN4, MAGI2 etc. as top hits. However, none of the markers remained significant after multiple testing corrections using Bonferroni and Benjamini-Hochberg. Conclusions: The GWAS revealed an association signal on chromosome 11, which is suggestive and needs to be pursued further in a larger sample set.

Precisely modeling zero-inflated count phenotype for rare variants.

Count data with excessive zeros are increasingly ubiquitous in genetic association studies, such as neuritic plaques in brain pathology for Alzheimer's disease. Here, we developed gene-based association tests to model such data by a mixture of two distributions, one for the structural zeros contributed by the Binomial distribution, and the other for the counts from the Poisson distribution. We derived the score statistics of the corresponding parameter of the rare variants in the zero-inflated Poisson regression model, and then constructed burden (ZIP-b) and kernel (ZIP-k) tests for the association tests. We evaluated omnibus tests that combined both ZIP-b and ZIP-k tests. Through simulated sequence data, we illustrated the potential power gain of our proposed method over a two-stage method that analyzes binary and non-zero continuous data separately for both burden and kernel tests. The ZIP burden test outperformed the kernel test as expected in all scenarios except for the scenario of variants with a mixture of directions in the genetic effects. We further demonstrated its applications to analyses of the neuritic plaque data in the ROSMAP cohort. We expect our proposed test to be useful in practice as more powerful than or complementary to the two-stage method.