Inherited causes of clonal haematopoiesis in 97,691 whole genomes.

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

DLRAPom: a hybrid pipeline of Optimized XGBoost-guided integrative multiomics analysis for identifying targetable disease-related lncRNA-miRNA-mRNA regulatory axes.

The lack of a reliable and easy-to-operate screening pipeline for disease-related noncoding RNA regulatory axis is a problem that needs to be solved urgently. To address this, we designed a hybrid pipeline, disease-related lncRNA-miRNA-mRNA regulatory axis prediction from multiomics (DLRAPom), to identify risk biomarkers and disease-related lncRNA-miRNA-mRNA regulatory axes by adding a novel machine learning model on the basis of conventional analysis and combining experimental validation. The pipeline consists of four parts, including selecting hub biomarkers by conventional bioinformatics analysis, discovering the most essential protein-coding biomarkers by a novel machine learning model, extracting the key lncRNA-miRNA-mRNA axis and validating experimentally. Our study is the first one to propose a new pipeline predicting the interactions between lncRNA and miRNA and mRNA by combining WGCNA and XGBoost. Compared with the methods reported previously, we developed an Optimized XGBoost model to reduce the degree of overfitting in multiomics data, thereby improving the generalization ability of the overall model for the integrated analysis of multiomics data. With applications to gestational diabetes mellitus (GDM), we predicted nine risk protein-coding biomarkers and some potential lncRNA-miRNA-mRNA regulatory axes, which all correlated with GDM. In those regulatory axes, the MALAT1/hsa-miR-144-3p/IRS1 axis was predicted to be the key axis and was identified as being associated with GDM for the first time. In short, as a flexible pipeline, DLRAPom can contribute to molecular pathogenesis research of diseases, effectively predicting potential disease-related noncoding RNA regulatory networks and providing promising candidates for functional research on disease pathogenesis.

Cross-phenotype relationship between opioid use disorder and suicide attempts: new evidence from polygenic association and Mendelian randomization analyses.

Clinical epidemiological studies have found high co-occurrence between suicide attempts (SA) and opioid use disorder (OUD). However, the patterns of correlation and causation between them are still not clear due to psychiatric confounding. To investigate their cross-phenotype relationship, we utilized raw phenotypes and genotypes from >150,000 UK Biobank samples, and genome-wide association summary statistics from >600,000 individuals with European ancestry. Pairwise association and a potential bidirectional relationship between OUD and SA were evaluated with and without controlling for major psychiatric disease status (e.g., schizophrenia, major depressive disorder, and alcohol use disorder). Multiple statistical and genetics tools were used to perform epidemiological association, genetic correlation, polygenic risk score prediction, and Mendelian randomizations (MR) analyses. Strong associations between OUD and SA were observed at both the phenotypic level (overall samples [OR = 2.94, P = 1.59 ×10-14]; non-psychiatric subgroup [OR = 2.15, P = 1.07 ×10-3]) and the genetic level (genetic correlation rg = 0.38 and 0.5 with or without conditioning on psychiatric traits, respectively). Consistently, increasing polygenic susceptibility to SA is associated with increasing risk of OUD (OR = 1.08, false discovery rate [FDR] =1.71 ×10-3), and similarly, increasing polygenic susceptibility to OUD is associated with increasing risk of SA (OR = 1.09, FDR = 1.73 ×10-6). However, these polygenic associations were much attenuated after controlling for comorbid psychiatric diseases. A combination of MR analyses suggested a possible causal association from genetic liability for SA to OUD risk (2-sample univariable MR: OR = 1.14, P = 0.001; multivariable MR: OR = 1.08, P = 0.001). This study provided new genetic evidence to explain the observed OUD-SA comorbidity. Future prevention strategies for each phenotype needs to take into consideration of screening for the other one.

The interactions between host genome and gut microbiome increase the risk of psychiatric disorders: Mendelian randomization and biological annotation.

BACKGROUND: The correlation between human gut microbiota and psychiatric diseases has long been recognized. Based on the heritability of the microbiome, genome-wide association studies on human genome and gut microbiome (mbGWAS) have revealed important host-microbiome interactions. However, establishing causal relationships between specific gut microbiome features and psychological conditions remains challenging due to insufficient sample sizes of previous studies of mbGWAS. METHODS: Cross-cohort meta-analysis (via METAL) and multi-trait analysis (via MTAG) were used to enhance the statistical power of mbGWAS for identifying genetic variants and genes. Using two large mbGWAS studies (7,738 and 5,959 participants respectively) and12 disease-specific studies from the Psychiatric Genomics Consortium (PGC), we performed bidirectional two-sample mendelian randomization (MR) analyses between microbial features and psychiatric diseases (up to 500,199 individuals). Additionally, we conducted downstream gene- and gene-set-based analyses to investigate the shared biology linking gut microbiota and psychiatric diseases. RESULTS: METAL and MTAG conducted in mbGWAS could boost power for gene prioritization and MR analysis. Increases in the number of lead SNPs and mapped genes were witnessed in 13/15 species and 5/10 genera after using METAL, and MTAG analysis gained an increase in sample size equivalent to expanding the original samples from 7% to 63%. Following METAL use, we identified a positive association between Bacteroides faecis and ADHD (OR, 1.09; 95 %CI, 1.02-1.16; P = 0.008). Bacteroides eggerthii and Bacteroides thetaiotaomicron were observed to be positively associated with PTSD (OR, 1.11; 95 %CI, 1.03-1.20; P = 0.007; OR, 1.11; 95 %CI, 1.01-1.23; P = 0.03). These findings remained stable across statistical models and sensitivity analyses. No genetic liabilities to psychiatric diseases may alter the abundance of gut microorganisms.Using biological annotation, we identified that those genes contributing to microbiomes (e.g., GRIN2A and RBFOX1) are expressed and enriched in human brain tissues. CONCLUSIONS: Our statistical genetics strategy helps to enhance the power of mbGWAS, and our genetic findings offer new insights into biological pleiotropy and causal relationship between microbiota and psychiatric diseases.

Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction.

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Survival Association of Angiotensin Inhibitors in Heart Failure With Reduced Ejection Fraction: Comparisons Using Self-Identified Race and Genomic Ancestry.

BACKGROUND: It remains unclear whether there is a racial disparity in the response to angiotensin inhibitors in patients with heart failure with reduced ejection fraction (HFrEF) and whether the role of genomic ancestry plays a part. Therefore, we compared survival rates associated with angiotensin inhibitors in patients with HFrEF by self-identified race and proportion of West African genomic ancestry. METHODS: Three datasets totaling 1153 and 1480 self-identified Black and White patients, respectively, with HFrEF were meta-analyzed (random effects model) for race-based analyses. One dataset had genomic data for ancestry analyses (416 and 369 self-identified Black and White patients, respectively). Cox proportional hazards regression, adjusted for propensity scores, assessed the association of angiotensin inhibitor exposure with all-cause mortality by self-identified race or proportion of West African genomic ancestry. RESULTS: In meta-analysis of self-identified race, adjusted hazard ratios (95% CI) for exposure to angiotensin inhibitors were similar in self-identified Black and White patients with HFrEF: 0.52 (0.31-0.85) P = 0.006 and 0.54 (0.42-0.71) P = 0.001, respectively. Results were similar when the proportion of West African genomic ancestry was > 80% or < 5%: 0.66 (0.34-1.25) P = 0.200 and 0.56 (0.26-1.23) P = 0.147, respectively. CONCLUSIONS: Among self-identified Black and White patients with HFrEF, reduction in all-cause mortality associated with exposure to angiotensin inhibitors was similar regardless of self-identified race or proportion of West African genomic ancestry.

Mapping the 17q12-21.1 Locus for Variants Associated with Early-Onset Asthma in African Americans.

Rationale: The 17q12-21.1 locus is one of the most highly replicated genetic associations with asthma. Individuals of African descent have lower linkage disequilibrium in this region, which could facilitate identifying causal variants.Objectives: To identify functional variants at 17q12-21.1 associated with early-onset asthma among African American individuals.Methods: We evaluated African American participants from SAPPHIRE (Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity) (n = 1,940), SAGE II (Study of African Americans, Asthma, Genes and Environment) (n = 885), and GCPD-A (Study of the Genetic Causes of Complex Pediatric Disorders-Asthma) (n = 2,805). Associations with asthma onset at ages under 5 years were meta-analyzed across cohorts. The lead signal was reevaluated considering haplotypes informed by genetic ancestry (i.e., African vs. European). Both an expression-quantitative trait locus analysis and a phenome-wide association study were performed on the lead variant.Measurements and Main Results: The meta-analyzed results from SAPPHIRE, SAGE II, and the GCPD-A identified rs11078928 as the top association for early-onset asthma. A haplotype analysis suggested that the asthma association partitioned most closely with the rs11078928 genotype. Genetic ancestry did not appear to influence the effect of this variant. In the expression-quantitative trait locus analysis, rs11078928 was related to alternative splicing of GSDMB (gasdermin-B) transcripts. The phenome-wide association study of rs11078928 suggested that this variant was predominantly associated with asthma and asthma-associated symptoms.Conclusions: A splice-acceptor polymorphism appears to be a causal variant for asthma at the 17q12-21.1 locus. This variant appears to have the same magnitude of effect in individuals of African and European descent.

Genetics of heart rate in heart failure patients (GenHRate).

BACKGROUND: Elevated resting heart rate (HR) is a risk factor and therapeutic target in patients with heart failure (HF) and reduced ejection fraction (HFrEF). Previous studies indicate a genetic contribution to HR in population samples but there is little data in patients with HFrEF. METHODS: Patients who met Framingham criteria for HF and had an ejection fraction < 50% were prospectively enrolled in a genetic HF registry (2007-2015, n = 1060). All participants donated blood for DNA and underwent genome-wide genotyping with additional variants called via imputation. We performed testing of previously identified variant "hits" (43 loci) as well as a genome-wide association (GWAS) of HR, adjusted for race, using Efficient Mixed-Model Association Expedited (EMMAX). RESULTS: The cohort was 35% female, 51% African American, and averaged 68 years of age. There was a 2 beats per minute (bpm) difference in HR by race, AA being slightly higher. Among 43 candidate variants, 4 single nucleotide polymorphisms (SNPs) in one gene (GJA1) were significantly associated with HR. In genome-wide testing, one statistically significant association peak was identified on chromosome 22q13, with strongest SNP rs535263906 (p = 3.3 × 10-8). The peak is located within the gene Cadherin EGF LAG Seven-Pass G-Type Receptor 1 (CELSR1), encoding a cadherin super-family cell surface protein identified in GWAS of other phenotypes (e.g., stroke). The highest associated SNP was specific to the African American population. CONCLUSIONS: These data confirm GJA1 association with HR in the setting of HFrEF and identify novel candidate genes for HR in HFrEF patients, particularly CELSR1. These associations should be tested in additional cohorts.

Integrative approach identifies corticosteroid response variant in diverse populations with asthma.

BACKGROUND: Although inhaled corticosteroid (ICS) medication is considered the cornerstone treatment for patients with persistent asthma, few ICS pharmacogenomic studies have involved nonwhite populations. OBJECTIVE: We sought to identify genetic predictors of ICS response in multiple population groups with asthma. METHODS: The discovery group comprised African American participants from the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) who underwent 6 weeks of monitored ICS therapy (n = 244). A genome-wide scan was performed to identify single nucleotide polymorphism (SNP) variants jointly associated (ie, the combined effect of the SNP and SNP × ICS treatment interaction) with changes in asthma control. Top associations were validated by assessing the joint association with asthma exacerbations in 3 additional groups: African Americans (n = 803 and n = 563) and Latinos (n = 1461). RNA sequencing data from 408 asthmatic patients and 405 control subjects were used to examine whether genotype was associated with gene expression. RESULTS: One variant, rs3827907, was significantly associated with ICS-mediated changes in asthma control in the discovery set (P = 7.79 × 10-8) and was jointly associated with asthma exacerbations in 3 validation cohorts (P = .023, P = .029, and P = .041). RNA sequencing analysis found the rs3827907 C-allele to be associated with lower RNASE2 expression (P = 6.10 × 10-4). RNASE2 encodes eosinophil-derived neurotoxin, and the rs3827907 C-allele appeared to particularly influence ICS treatment response in the presence of eosinophilic inflammation (ie, high pretreatment eosinophil-derived neurotoxin levels or blood eosinophil counts). CONCLUSION: We identified a variant, rs3827907, that appears to influence response to ICS treatment in multiple population groups and likely mediates its effect through eosinophils.

Association of Regulatory Genetic Variants for Protein Kinase Cα with Mortality and Drug Efficacy in Patients with Heart Failure.

PURPOSE: Protein kinase C alpha (gene: PRKCA) is a key regulator of cardiac contractility. Two genetic variants have recently been discovered to regulate PRKCA expression in failing human heart tissue (rs9909004 [T → C] and rs9303504 [C → G]). The association of those variants with clinical outcomes in patients with heart failure (HF), and their interaction with HF drug efficacy, is unknown. METHODS: Patients with HF in a prospective registry starting in 2007 were genotyped by whole genome array (n = 951). The primary outcome was all-cause mortality. Cox proportional hazards models adjusted for established clinical risk factors and genomic ancestry tested the independent association of rs9909004 or rs9303504 and the variant interactions with cornerstone HF pharmacotherapies (beta-blockers or angiotensin-converting enzyme inhibitors/angiotensin receptor blockers) in additive genetic models. RESULTS: The minor allele of rs9909004, but not of rs9303504, was independently associated with a decreased risk for all-cause mortality: adjusted HR = 0.81 (95% CI = 0.67-0.98), p = 0.032. The variants did not significantly interact with mortality benefit associated with cornerstone HF pharmacotherapies (p > 0.1 for all). CONCLUSIONS: A recently discovered cardiac-specific regulatory variant for PRKCA (rs9909004) was independently associated with a decreased risk for all-cause mortality in patients with HF. The variant did not interact with mortality benefit associated with cornerstone HF pharmacotherapies.

Trans-ethnic meta-analysis of genome-wide association studies for Hirschsprung disease.

Hirschsprung disease (HSCR) is the most common cause of neonatal intestinal obstruction. It is characterized by the absence of ganglia in the nerve plexuses of the lower gastrointestinal tract. So far, three common disease-susceptibility variants at the RET, SEMA3 and NRG1 loci have been detected through genome-wide association studies (GWAS) in Europeans and Asians to understand its genetic etiologies. Here we present a trans-ethnic meta-analysis of 507 HSCR cases and 1191 controls, combining all published GWAS results on HSCR to fine-map these loci and narrow down the putatively causal variants to 99% credible sets. We also demonstrate that the effects of RET and NRG1 are universal across European and Asian ancestries. In contrast, we detected a European-specific association of a low-frequency variant, rs80227144, in SEMA3 [odds ratio (OR) = 5.2, P = 4.7 × 10-10]. Conditional analyses on the lead SNPs revealed a secondary association signal, corresponding to an Asian-specific, low-frequency missense variant encoding RET p.Asp489Asn (rs9282834, conditional OR = 20.3, conditional P = 4.1 × 10-14). When in trans with the RET intron 1 enhancer risk allele, rs9282834 increases the risk of HSCR from 1.1 to 26.7. Overall, our study provides further insights into the genetic architecture of HSCR and has profound implications for future study designs.

Correction of Hirschsprung-Associated Mutations in Human Induced Pluripotent Stem Cells Via Clustered Regularly Interspaced Short Palindromic Repeats/Cas9, Restores Neural Crest Cell Function.

BACKGROUND & AIMS: Hirschsprung disease is caused by failure of enteric neural crest cells (ENCCs) to fully colonize the bowel, leading to bowel obstruction and megacolon. Heterozygous mutations in the coding region of the RET gene cause a severe form of Hirschsprung disease (total colonic aganglionosis). However, 80% of HSCR patients have short-segment Hirschsprung disease (S-HSCR), which has not been associated with genetic factors. We sought to identify mutations associated with S-HSCR, and used the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene editing system to determine how mutations affect ENCC function. METHODS: We created induced pluripotent stem cell (iPSC) lines from 1 patient with total colonic aganglionosis (with the G731del mutation in RET) and from 2 patients with S-HSCR (without a RET mutation), as well as RET+/- and RET-/- iPSCs. IMR90-iPSC cells were used as the control cell line. Migration and differentiation capacities of iPSC-derived ENCCs were analyzed in differentiation and migration assays. We searched for mutation(s) associated with S-HSCR by combining genetic and transcriptome data from patient blood- and iPSC-derived ENCCs, respectively. Mutations in the iPSCs were corrected using the CRISPR/Cas9 system. RESULTS: ENCCs derived from all iPSC lines, but not control iPSCs, had defects in migration and neuronal lineage differentiation. RET mutations were associated with differentiation and migration defects of ENCCs in vitro. Genetic and transcriptome analyses associated a mutation in the vinculin gene (VCL M209L) with S-HSCR. CRISPR/Cas9 correction of the RET G731del and VCL M209L mutations in iPSCs restored the differentiation and migration capacities of ENCCs. CONCLUSIONS: We identified mutations in VCL associated with S-HSCR. Correction of this mutation in iPSC using CRISPR/Cas9 editing, as well as the RET G731del mutation that causes Hirschsprung disease with total colonic aganglionosis, restored ENCC function. Our study demonstrates how human iPSCs can be used to identify disease-associated mutations and determine how they affect cell functions and contribute to pathogenesis.

Genetic overlap between epilepsy and schizophrenia: Evidence from cross phenotype analysis in Hong Kong Chinese population.

Epilepsy and schizophrenia are common and typical neurological or mental illness respectively, and sometimes they comorbid in the same patients, however the underlying genetic relationship between the two brain diseases is still not fully understood. To investigate the possible genetic contribution to their comorbidity, we performed polygenic risk score (PRS) analyses and genetic correlation estimation so as to identify the overall genetic overlap between the two diseases. The global schizophrenia PRS is strongly associated with schizophrenia phenotype in Hong Kong population (odds ratio = 1.7, p = 2.26E-16), and focal epilepsy PRS is moderately associated with epilepsy phenotype in Hong Kong population (odds ratio = 1.14, p = 0.013). However the disease-specific PRS can only predict its own well-matched phenotype but not the other ones (p > 0.05). This pattern is further supported by non-significant pairwise genetic correlation and insufficient statistical power for PRS association from the cross-phenotype analyses. Our study reveals there's limited shared genetic aetiology between schizophrenia and epilepsy, and thus supports a model of shared environmental factors to explain the comorbidity between the two phenotypes.

Identification of GLI Mutations in Patients With Hirschsprung Disease That Disrupt Enteric Nervous System Development in Mice.

BACKGROUND & AIMS: Hirschsprung disease is characterized by a deficit in enteric neurons, which are derived from neural crest cells (NCCs). Aberrant hedgehog signaling disrupts NCC differentiation and might cause Hirschsprung disease. We performed genetic analyses to determine whether hedgehog signaling is involved in pathogenesis. METHODS: We performed deep-target sequencing of DNA from 20 patients with Hirschsprung disease (16 men, 4 women), and 20 individuals without (controls), and searched for mutation(s) in GLI1, GLI2, GLI3, SUFU, and SOX10. Biological effects of GLI mutations were tested in luciferase reporter assays using HeLa or neuroblastoma cell lines. Development of the enteric nervous system was studied in Sufu(f/f), Gli3(Δ699), Wnt1-Cre, and Sox10(NGFP) mice using immunohistochemical and whole-mount staining procedures to quantify enteric neurons and glia and analyze axon fasciculation, respectively. NCC migration was studied using time-lapse imaging. RESULTS: We identified 3 mutations in GLI in 5 patients with Hirschsprung disease but no controls; all lead to increased transcription of SOX10 in cell lines. SUFU, GLI, and SOX10 form a regulatory loop that controls the neuronal vs glial lineages and migration of NCCs. Sufu mutants mice had high Gli activity, due to loss of Sufu, disrupting the regulatory loop and migration of enteric NCCs, leading to defective axonal fasciculation, delayed gut colonization, or intestinal hypoganglionosis. The ratio of enteric neurons to glia correlated inversely with Gli activity. CONCLUSIONS: We identified mutations that increase GLI activity in patients with Hirschsprung disease. Disruption of the SUFU-GLI-SOX10 regulatory loop disrupts migration of NCCs and development of the enteric nervous system in mice.

Targeted next-generation sequencing on Hirschsprung disease: a pilot study exploits DNA pooling.

To adopt an efficient approach of identifying rare variants possibly related to Hirschsprung disease (HSCR), a pilot study was set up to evaluate the performance of a newly designed protocol for next generation targeted resquencing. In total, 20 Chinese HSCR patients and 20 Chinese sex-matched individuals with no HSCR were included, for which coding sequences (CDS) of 62 genes known to be in signaling pathways relevant to enteric nervous system development were selected for capture and sequencing. Blood DNAs from eight pools of five cases or controls were enriched by PCR-based RainDance technology (RDT) and then sequenced on a 454 FLX platform. As technical validation, five patients from case Pool-3 were also independently enriched by RDT, indexed with barcode and sequenced with sufficient coverage. Assessment for CDS single nucleotide variants showed DNA pooling performed well (specificity/sensitivity at 98.4%/83.7%) at the common variant level; but relatively worse (specificity/sensitivity at 65.5%/61.3%) at the rare variant level. Further Sanger sequencing only validated five out of 12 rare damaging variants likely involved in HSCR. Hence more improvement at variant detection and sequencing technology is needed to realize the potential of DNA pooling for large-scale resequencing projects.

GATES: a rapid and powerful gene-based association test using extended Simes procedure.

The gene has been proposed as an attractive unit of analysis for association studies, but a simple yet valid, powerful, and sufficiently fast method of evaluating the statistical significance of all genes in large, genome-wide datasets has been lacking. Here we propose the use of an extended Simes test that integrates functional information and association evidence to combine the p values of the single nucleotide polymorphisms within a gene to obtain an overall p value for the association of the entire gene. Our computer simulations demonstrate that this test is more powerful than the SNP-based test, offers effective control of the type 1 error rate regardless of gene size and linkage-disequilibrium pattern among markers, and does not need permutation or simulation to evaluate empirical significance. Its statistical power in simulated data is at least comparable, and often superior, to that of several alternative gene-based tests. When applied to real genome-wide association study (GWAS) datasets on Crohn disease, the test detected more significant genes than SNP-based tests and alternative gene-based tests. The proposed test, implemented in an open-source package, has the potential to identify additional novel disease-susceptibility genes for complex diseases from large GWAS datasets.

A comprehensive framework for prioritizing variants in exome sequencing studies of Mendelian diseases.

Exome sequencing strategy is promising for finding novel mutations of human monogenic disorders. However, pinpointing the casual mutation in a small number of samples is still a big challenge. Here, we propose a three-level filtration and prioritization framework to identify the casual mutation(s) in exome sequencing studies. This efficient and comprehensive framework successfully narrowed down whole exome variants to very small numbers of candidate variants in the proof-of-concept examples. The proposed framework, implemented in a user-friendly software package, named KGGSeq (http://statgenpro.psychiatry.hku.hk/kggseq), will play a very useful role in exome sequencing-based discovery of human Mendelian disease genes.