Miaoxin Li

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.

Predicting Mendelian Disease-Causing Non-Synonymous Single Nucleotide Variants in Exome Sequencing Studies

Exome sequencing is becoming a standard tool for mapping Mendelian disease-causing (or pathogenic) non-synonymous single nucleotide variants (nsSNVs). Minor allele frequency (MAF) filtering approach and functional prediction methods are commonly used to identify candidate pathogenic mutations in these studies. Combining multiple functional prediction methods may increase accuracy in prediction. Here, we propose to use a logit model to combine multiple prediction methods and compute an unbiased probability of a rare variant being pathogenic. Also, for the first time we assess the predictive power of seven prediction methods (including SIFT, PolyPhen2, CONDEL, and logit) in predicting pathogenic nsSNVs from other rare variants, which reflects the situation after MAF filtering is done in exome-sequencing studies. We found that a logit model combining all or some original prediction methods outperforms other methods examined, but is unable to discriminate between autosomal dominant and autosomal recessive disease mutations. Finally, based on the predictions of the logit model, we estimate that an individual has around 5% of rare nsSNVs that are pathogenic and carries ∼22 pathogenic derived alleles at least, which if made homozygous by consanguineous marriages may lead to recessive diseases.

Uncovering the Total Heritability Explained by All True Susceptibility Variants in a Genome-Wide Association Study

Genome‐wide association studies (GWAS) have become increasingly popular recently and contributed to the discovery of many susceptibility variants. However, a large proportion of the heritability still remained unexplained. This observation raises queries regarding the ability of GWAS to uncover the genetic basis of complex diseases. In this study, we propose a simple and fast statistical framework to estimate the total heritability explained by all true susceptibility variants in a GWAS. It is expected that many true risk variants will not be detected in a GWAS due to limited power. The proposed framework aims at recovering the “hidden” heritability. Importantly, only the summary z‐statistics are required as input and no raw genotype data are needed. The strategy is to recover the true effect sizes from the observed z‐statistics. The methodology does not rely on any distributional assumptions of the effect sizes of variants. Both binary and quantitative traits can be handled and covariates may be included. Population‐based or family‐based designs are allowed as long as the summary statistics are available. Simulations were conducted and showed satisfactory performance of the proposed approach. Application to real data (Crohns disease, HDL, LDL, and triglycerides) reveals that at least around 10–20% of variance in liability or phenotype can be explained by GWAS panels. This translates to around 10–40% of the total heritability for the studied traits. Genet. Epidemiol. 2011.

Genetic determination and correlation of body mass index and bone mineral density at the spine and hip in Chinese Han ethnicity

The purpose of the present study was to evaluate the magnitude of genetic determination of spine and hip bone mineral density (BMD) and body mass index (BMI), and to explore the genetic, environmental, and phenotypic correlations among the above phenotypes in Chinese Han ethnicity. The sample was composed of at least 217 complete nuclear families in Chinese Han ethnicity. BMD at the spine and hip was measured using a dual-energy X-ray absorptiometry scanner. The heritability ( h 2) of BMI and BMD at the spine and hip, the genetic correlation ( ρ G) and environmental correlation ( ρ E) among the three phenotypes were evaluated via variance analysis, with age, sex, and age-by-sex interaction as covariates. The phenotypic correlation ( ρ P) and the bivariate heritability ρG2 were also calculated. The heritability for BMD and BMI was ~0.70 and ~0.50, respectively ( p <0.0001). The common environment shared by household members (household effect) is significant for BMI variation ( p =0.0004). Significant genetic, environmental, and phenotypic correlation was observed. The ρG2 values were 0.13 for BMI/spine BMD, 0.18 for BMI/hip BMD, and 0.58 for the spine BMD/hip BMD. While BMD at the spine and hip have significant genetic determination, BMI is more likely to be affected by environmental factors than BMD. In addition, BMD at the spine and hip shares more genetic effect (pleiotropy) than BMI and BMD do in Chinese Han ethnicity, though the effects are significant for both.

Heritability of variation in glycaemic response to metformin: a genome-wide complex trait analysis

Summary Background Metformin is a first-line oral agent used in the treatment of type 2 diabetes, but glycaemic response to this drug is highly variable. Understanding the genetic contribution to metformin response might increase the possibility of personalising metformin treatment. We aimed to establish the heritability of glycaemic response to metformin using the genome-wide complex trait analysis (GCTA) method. Methods In this GCTA study, we obtained data about HbA1c concentrations before and during metformin treatment from patients in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) study, which includes a cohort of patients with type 2 diabetes and is linked to comprehensive clinical databases and genome-wide association study data. We applied the GCTA method to estimate heritability for four definitions of glycaemic response to metformin: absolute reduction in HbA1c; proportional reduction in HbA1c; adjusted reduction in HbA1c; and whether or not the target on-treatment HbA1c of less than 7% (53 mmol/mol) was achieved, with adjustment for baseline HbA1c and known clinical covariates. Chromosome-wise heritability estimation was used to obtain further information about the genetic architecture. Findings 5386 individuals were included in the final dataset, of whom 2085 had enough clinical data to define glycaemic response to metformin. The heritability of glycaemic response to metformin varied by response phenotype, with a heritability of 34% (95% CI 1–68; p=0·022) for the absolute reduction in HbA1c, adjusted for pretreatment HbA1c. Chromosome-wise heritability estimates suggest that the genetic contribution is probably from individual variants scattered across the genome, which each have a small to moderate effect, rather than from a few loci that each have a large effect. Interpretation Glycaemic response to metformin is heritable, thus glycaemic response to metformin is, in part, intrinsic to individual biological variation. Further genetic analysis might enable us to make better predictions for stratified medicine and to unravel new mechanisms of metformin action. Funding Wellcome Trust.

Comparisons of seven algorithms for pathway analysis using the WTCCC Crohn's Disease dataset

BackgroundThough rooted in genomic expression studies, pathway analysis for genome-wide association studies (GWAS) has gained increasing popularity, since it has the potential to discover hidden disease pathogenic mechanisms by combining statistical methods with biological knowledge. Generally, algorithms or programs proposed recently can be categorized by different types of input data, null hypothesis or counts of analysis stages. Due to complexity caused by SNP, gene and pathway relationships, re-sampling strategies like permutation are always utilized to derive an empirical distribution for test statistics for evaluating the significance of candidate pathways. However, evaluation of these algorithms on real GWAS datasets and real biological pathway databases needs to be addressed before we apply them widely with confidence.FindingsTwo algorithms which use summary statistics from GWAS as input were implemented in KGG, a novel and user-friendly software tool for GWAS pathway analysis. Comparisons of these two algorithms as well as the other five selected algorithms were conducted by analyzing the WTCCC Crohns Disease dataset utilizing the MsigDB canonical pathways. As a result of using permutation to obtain empirical p-value, most of these methods could control Type I error rate well, although some are conservative. However, the methods varied greatly in terms of power and running time, with the PLINK truncated set-based test being the most powerful and KGG being the fastest.ConclusionsRaw data-based algorithms, such as those implemented in PLINK, are preferable for GWAS pathway analysis as long as computational capacity is available. It may be worthwhile to apply two or more pathway analysis algorithms on the same GWAS dataset, since the methods differ greatly in their outputs and might provide complementary findings for the studied complex disease.

The p.Ser267Phe variant in SLC10A1 is associated with resistance to chronic hepatitis B

In the past 50 years there have been considerable efforts to identify the cellular receptor of hepatitis B virus (HBV). Recently, in vitro evidence from several groups has shown that the sodium–taurocholate cotransporting polypeptide (NTCP, which is encoded by SLC10A1 and transports bile acids into hepatic cells in enterohepatic recirculation) is a strong candidate. In particular, in vitro the p.Ser267Phe variation of SLC10A1 results in loss of HBV receptor function. We tested the role of NTCP as a receptor for HBV in chronic hepatitis B patients using a genetic association study. We selected SLC10A1 variants from 189 exomes. We used Sanger sequencing to follow up the association of the various SLC10A1 variants in a Han Chinese cohort of 1899 chronic hepatitis B patients and 1828 healthy controls. We further investigated the potential impact of the p.Ser267Phe variant on NTCP function using structural analysis. The p.Ser267Phe variant was associated with healthy status (P = 5.7 × 10−23, odds ratio = 0.36) irrespective of hepatitis B virus surface antibody status (P = 6.2 × 10−21 and 1.5 × 10−10, respectively, when the cases were compared with hepatitis B virus surface antibody–positive and –negative controls). The variation was also associated with a lower incidence of acute‐on‐chronic liver failure (P = 0.007). The estimated heritability explained by this single variation was ∼3.2%. The population prevented fraction was around 13.0% among the southern Chinese. Our structural modeling showed that the p.Ser267Phe variant might interfere with ligand binding, thereby preventing HBV from cellular entry. Conclusion: The p.Ser267Phe NTCP variant is significantly associated with resistance to chronic hepatitis B and a lower incidence of acute‐on‐chronic liver failure. Our results support that NTCP is a cellular receptor for HBV in human infection. (Hepatology 2015;61:1251–1260)

Estrogen Receptor α Gene Polymorphisms and Peak Bone Density in Chinese Nuclear Families

PBD is an important determinant of osteoporotic fractures. Few studies were performed to search for genes underlying PBD variation in Chinese populations. We tested linkage and/or association of the estrogen receptor α gene polymorphism with PBD in 401 Chinese nuclear families. This study suggests the ER‐α gene may have some minor effects on PBM variation in the Chinese population.

Common Variants on Xq28 Conferring Risk of Schizophrenia in Han Chinese

Schizophrenia is a highly heritable, severe psychiatric disorder affecting approximately 1% of the world population. A substantial portion of heritability is still unexplained and the pathophysiology of schizophrenia remains to be elucidated. To identify more schizophrenia susceptibility loci, we performed a genome-wide association study (GWAS) on 498 patients with schizophrenia and 2025 controls from the Han Chinese population, and a follow-up study on 1027 cases and 1005 controls. In the follow-up study, we included 384 single nucleotide polymorphisms (SNPs) which were selected from the top hits in our GWAS (130 SNPs) and from previously implicated loci for schizophrenia based on the SZGene database, NHGRI GWAS Catalog, copy number variation studies, GWAS meta-analysis results from the international Psychiatric Genomics Consortium (PGC) and candidate genes from plausible biological pathways (254 SNPs). Within the chromosomal region Xq28, SNP rs2269372 in RENBP achieved genome-wide significance with a combined P value of 3.98 × 10(-8) (OR of allele A = 1.31). SNPs with suggestive P values were identified within 2 genes that have been previously implicated in schizophrenia, MECP2 (rs2734647, P combined = 8.78 × 10(-7), OR = 1.28; rs2239464, P combined = 6.71 × 10(-6), OR = 1.26) and ARHGAP4 (rs2269368, P combined = 4.74 × 10(-7), OR = 1.25). In addition, the patient sample in our follow-up study showed a significantly greater burden for pre-defined risk alleles based on the SNPs selected than the controls. This indicates the existence of schizophrenia susceptibility loci among the SNPs we selected. This also further supports multigenic inheritance in schizophrenia. Our findings identified a new schizophrenia susceptibility locus on Xq28, which harbor the genes RENBP, MECP2, and ARHGAP4.