Contribution of the APOE Genotype to Cognitive Impairment in Individuals With NOTCH3 Cysteine-Altering Variants

BACKGROUND

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the most prevalent monogenic cerebral small-vessel disease. Phenotype variability in CADASIL suggests the possible role of genetic modifiers. We aimed to investigate the contributions of the APOE genotype and Neurogenic locus notch homolog protein 3 (NOTCH3) variant position to cognitive impairment associated with CADASIL.

METHODS AND RESULTS

Patients with the cysteine-altering NOTCH3 variant were enrolled in a cross-sectional study, including the Mini-Mental State Examination (MMSE), brain magnetic resonance imaging, and APOE genotyping. Cognitive impairment was defined as an MMSE score <24. The associations between the MMSE score and genetic factors were assessed using linear regression models. Bayesian adjustment for confounding was used to identify clinical confounders. A total of 246 individuals were enrolled, among whom 210 (85%) harbored the p.R544C variant, 96 (39%) had cognitive impairment, and 150 (61%) had a history of stroke. The APOE ɛ2 allele was associated with a lower MMSE score (adjusted B, -4.090 [95% CI, -6.708 to -1.473]; P=0.023), whereas the NOTCH3 p.R544C variant was associated with a higher MMSE score (adjusted B, 2.854 [95% CI, 0.603-5.105]; P=0.0132) after adjustment for age, education, and history of ischemic stroke. Mediation analysis suggests that the associations between the APOE ɛ2 allele and MMSE score and between the NOTCH3 p.R544C variant and MMSE score are mediated by mesial temporal atrophy and white matter hyperintensity, respectively.

CONCLUSIONS

APOE genotype may modify cognitive impairment in CADASIL, whereby individuals carrying the APOE ɛ2 allele may present a more severe cognitive impairment.

Phenome-wide analysis of Taiwan Biobank reveals novel glycemia-related loci and genetic risks for diabetes

To explore the complex genetic architecture of common diseases and traits, we conducted comprehensive PheWAS of ten diseases and 34 quantitative traits in the community-based Taiwan Biobank (TWB). We identified 995 significantly associated loci with 135 novel loci specific to Taiwanese population. Further analyses highlighted the genetic pleiotropy of loci related to complex disease and associated quantitative traits. Extensive analysis on glycaemic phenotypes (T2D, fasting glucose and HbA_1c) was performed and identified 115 significant loci with four novel genetic variants (HACL1, RAD21, ASH1L and GAK). Transcriptomics data also strengthen the relevancy of the findings to metabolic disorders, thus contributing to better understanding of pathogenesis. In addition, genetic risk scores are constructed and validated for absolute risks prediction of T2D in Taiwanese population. In conclusion, our data-driven approach without a priori hypothesis is useful for novel gene discovery and validation on top of disease risk prediction for unique non-European population.

Patient-Derived Organoid Serves as a Platform for Personalized Chemotherapy in Advanced Colorectal Cancer Patients

Background

Addition of oxaliplatin to adjuvant 5-FU has significantly improved the disease-free survival and served as the first line adjuvant chemotherapy in advanced colorectal cancer (CRC) patients. However, a fraction of patients remains refractory to oxaliplatin-based treatment. It is urgent to establish a preclinical platform to predict the responsiveness toward oxaliplatin in CRC patients as well as to improve the efficacy in the resistant patients.

Methods

A living biobank of organoid lines were established from advanced CRC patients. Oxaliplatin sensitivity was assessed in patient-derived tumor organoids (PDOs) in vitro and in PDO-xenografted tumors in mice. Based on in vitro oxaliplatin IC₅₀ values, PDOs were classified into either oxaliplatin-resistant (OR) or oxaliplatin-sensitive (OS) PDOs. The outcomes of patients undergone oxaliplatin-based treatment was followed. RNA-sequencing and bioinformatics tools were performed for molecular profiling of OR and OS PDOs. Oxaliplatin response signatures were submitted to Connectivity Map algorithm to identify perturbagens that may antagonize oxaliplatin resistance.

Results

Oxaliplatin sensitivity in PDOs was shown to correlate to oxaliplatin-mediated inhibition on PDO xenograft tumors in mice, and parallelled clinical outcomes of CRC patients who received FOLFOX treatment. Molecular profiling of transcriptomes revealed oxaliplatin-resistant and -sensitive PDOs as two separate entities, each being characterized with distinct hallmarks and gene sets. Using Leave-One-Out Cross Validation algorithm and Logistic Regression model, 18 gene signatures were identified as predictive biomarkers for oxaliplatin response. Candidate drugs identified by oxaliplatin response signature-based strategies, including inhibitors targeting c-ABL and Notch pathway, DNA/RNA synthesis inhibitors, and HDAC inhibitors, were demonstrated to potently and effectively increase oxaliplatin sensitivity in the resistant PDOs.

Conclusions

PDOs are useful in informing decision-making on oxaliplatin-based chemotherapy and in designing personalized chemotherapy in CRC patients.

Hepatitis B virus persistent infection-related single nucleotide polymorphisms in HLA regions are associated with viral load in hepatoma families

BACKGROUND

Genome-wide association studies from Asia indicate that HLA-DP and HLA-DQ loci are important in persistent hepatitis B virus (HBV) infections. One of the key elements for HBV-related carcinogenesis is persistent viral replication and inflammation.

AIM

To examine genetic and nongenetic factors with persistent HBV infection and viral load in families with hepatocellular carcinoma (HCC).

METHODS

The HCC families included 301 hepatitis B surface antigen (HBsAg) carriers and 424 noncarriers born before the nationwide vaccination program was initiated in 1984. Five HBV-related single nucleotide polymorphisms (SNPs) — rs477515, rs9272105, rs9276370, rs7756516, and rs9277535 — were genotyped. Factors associated with persistent HBV infection and viral load were analyzed by a generalized estimating equation.

RESULTS

In the first-stage persistent HBV study, all SNPs except rs9272105 were associated with persistent infection. A significantly higher area under the reciprocal operating characteristic curve for nongenetic factors vs genetic factors (P < 0.001) suggests that the former play a major role in persistent HBV infection. In the second-stage viral load study, we added 8 HBsAg carriers born after 1984. The 309 HBsAg carriers were divided into low (n = 162) and high viral load (n = 147) groups with an HBV DNA cutoff of 10⁵ cps/mL. Sex, relationship to the index case, rs477515, rs9272105, and rs7756516 were associated with viral load. Based on the receiver operating characteristic curve analysis, genetic and nongenetic factors affected viral load equally in the HCC family cohort (P = 0.3117).

CONCLUSION

In these east Asian adults, the mechanism of persistent HBV infection-related SNPs was a prolonged viral replication phase.

Genetic Association of Hepatitis C-Related Mixed Cryoglobulinemia: A 10-Year Prospective Study of Asians Treated with Antivirals

Genetic profiles of hepatitis C virus (HCV)-associated mixed cryoglobulinemia (MC) in Asians remain elusive. A 10-year prospective cohort study was conducted with 1043 consecutive HCV Ab-positive Taiwanese surveyed with 13 single nucleotide polymorphisms (SNPs). Of 1043, 589 (56.5%) had baseline MC, 934 (89.5%) had positive HCV RNA, 796 completed anti-HCV therapy, and 715 had sustained virological responses (SVRs). SNP associations were surveyed withgenotypic, allelic, trend, permutation and multivariate analyses. At baseline, higher male sex and MC rates were noted in HCV RNA-positive than RNA-negative patients; higher female sex and positive HCV RNA rates but lower HCV RNA levels were noted in patients with than those without MC. Baseline associations were: HLA II-rs9461776 A allele, IFNL3-rs12979860 T allele, SERPINE1-rs6976053 C allele and MC with HCV RNA positivity; IFNL3-rs12979860 C allele, ARNTL-rs6486122 T allele and HCV RNA positivity with baseline MC. In SVR patients, RETN-rs1423096 C allele and SERPINE1-rs6976053 T allele were associated with 24-week and 10-year post-therapy MC, respectively. Conclusions: HCV RNA, IFNL3-rs12979860 and ARNTL-rs6486122 were associated with baseline MC; RETN-rs1423096 and SERPINE1-rs6976053 were associated with short- and long-term post-therapy MC in SVR patients, respectively. Links with HCV RNA and immune-associated SNPs suggest MC an immune reaction to expel HCV.

Shared genomic segment analysis with equivalence testing

An important aspect of disease gene mapping is replication, that is, a putative finding in one group of individuals is confirmed in another set of individuals. As it can happen by chance that individuals share an estimated disease position, we developed a statistical approach to determine the p‐value for multiple individuals or families to share a possibly small number of candidate susceptibility variants. Here, we focus on candidate variants for dominant traits that have been obtained by our previously developed heterozygosity analysis, and we are testing the sharing of candidate variants obtained for different individuals. Our approach allows for multiple pathogenic variants in a gene to contribute to disease, and for estimated disease variant positions to be imprecise. Statistically, the method developed here falls into the category of equivalence testing, where the classical null and alternative hypotheses of homogeneity and heterogeneity are reversed. The null hypothesis situation is created by permuting genomic locations of variants for one individual after another. We applied our methodology to the ALSPAC data set of 1,927 whole‐genome sequenced individuals, where some individuals carry a pathogenic variant for the BRCA1 gene, but no two individuals carry the same variant. Our shared genomic segment analysis found significant evidence for BRCA1 pathogenic variants within ±5 kb of a given DNA variant.

Maximal Segmental Score Method for Localizing Recessive Disease Variants Based on Sequence Data

Background

Due to the affordability of whole-genome sequencing, the genetic association design can now address rare diseases. However, some common statistical association methods only consider homozygosity mapping and need several criteria, such as sliding windows of a given size and statistical significance threshold setting, such as P-value < 0.05 to achieve good power in rare disease association detection.

Methods

Our region-specific method, called expanded maximal segmental score (eMSS), converts p-values into continuous scores based on the maximal segmental score (MSS) (Lin et al., 2014) for detecting disease-associated segments. Our eMSS considers the whole genome sequence data, not only regions of homozygosity in candidate genes. Unlike sliding window methods of a given size, eMSS does not need predetermined parameters, such as window size or minimum or maximum number of SNPs in a segment. The performance of eMSS was evaluated by simulations and real data analysis for autosomal recessive diseases multiple intestinal atresia (MIA) and osteogenesis imperfecta (OI), where the number of cases is extremely small. For the real data, the results by eMSS were compared with a state-of-the-art method, HDR-del (Imai et al., 2016).

Results

Our simulation results show that eMSS had higher power as the number of non-causal haplotype blocks decreased. The type I error for eMSS under different scenarios was well controlled, p < 0.05. For our observed data, the bone morphogenetic protein 1 (BMP1) gene on chromosome 8, the Violaxanthin de-epoxidase-related chloroplast (VDR) gene on chromosome 12 associated with OI, and the tetratricopeptide repeat domain 7A (TTC7A) gene on chromosome 2 associated with MIA have previously been identified as harboring the relevant pathogenic mutations.

Conclusions

When compared to HDR-del, our eMSS is powerful in analyzing even small numbers of recessive cases, and the results show that the method can further reduce numbers of candidate variants to a very small set of susceptibility pathogenic variants underlying OI and MIA. When we conduct whole-genome sequence analysis, eMSS used 3/5 the computation time of HDR-del. Without additional parameters needing to be set in the segment detection, the computational burden for eMSS is lower compared with that in other region-specific approaches.

Genome-wide association analysis in host genetic characteristics of progression to high-grade cervical intraepithelial neoplasia or higher for women with human papillomavirus infection and normal cytology

6033

Background: Human papillomavirus (HPV) testing is widely used for cervical cancer screening. The hazard ratio of developing cervical intraepithelial neoplasia grade 2 or higher (CIN2+) in HPV-positive/ normal cytology women is 20–34 fold as compared to those with HPV-negative/normal cytology. HPV-positivity would cause substantial anxiety. Apart from viral factors such as high-risk (hr) types, it is important to identify host characteristics for predicting outcome. Methods: An initial genome-wide association study (GWAS) of single nucleotide polymorphisms (SNPs) by Affymetrix Axiom™ Genome-Wide Human Arrays was conducted on 505 cases with histological diagnosis of CIN2+ (group D1) versus 920 female controls. An additional set of 2315 female controls from the Taiwan Biobank genotype array were added in the discovery stage. The identified 29 CIN2+ -associated SNPs from GWAS (p < 5 x 10−6) were verified in an independent cohort (group D2 [n = 306] versus group N [n = 600]). Group N were HPV-negative/normal cytology women from a population-based cervical cytology and HPV co-test study. A cohort with HPV-positive/normal cytology (group P, n = 755) underwent follow-up and was served as the prediction set. The predictive validity was analyzed by logistic regression and receiver operating characteristic (ROC) curve analysis. Results: Thirty-three individuals of the group P progressed to CIN2+ (median follow-up: 23.7 months, range 4.0–122.1). A risk-predictive panel of 8 SNPs rs3097662, rs35979982, rs7763822, rs4282438, rs3128927, rs7759943, rs213194, rs17835649 which were significant in the replication (p < 0.05) was used to train models for disease risk prediction using the combination of GWAS and verification sets. Two prediction models were finalized and determined using 7 SNPs for hr- and low-risk (lr) HPV groups respectively (sensitivity 0.72 and 0.75, specificity 0.651 and 0.884, area under the ROC curve 0.703 and 0.701). Among group P with hr-HPV, those carried < 6 risk-alleles had significantly decreased hazard (log-rank p < 0·001) of progression to CIN2+ than those with ≧6 risk-alleles, while among group P with lr-HPV, those with predictive probability of ≥ 0·095 had a cumulative risk of progression of 10% at 3 years. Conclusions: Two risk-predictive SNP panels including 7 SNPs with hr- or lr-HPV groups can assist risk stratification among HPV-positive/ normal cytology women. These panels could be further tested in other ethnic populations.

Source identification of HIV-1 transmission in three lawsuits Using Ultra-Deep pyrosequencing and phylogenetic analysis

BACKGROUND/PURPOSE

Intentional transmission of HIV-1 is a crime. Identifying the source of transmission between HIV-1 infected cases using phylogenetic analysis has limitations, including delayed examinations after the initiation of infection and ambiguity of phyletic relationships. This study was the first to introduce phylogenetic tree Results as forensic evidence in a trial in Taiwan.

METHODS

Three lawsuit cases from different district courts in Taiwan were chosen for this study. We identified the source of transmission between individuals in each lawsuit based on the maximum likelihood and Bayesian phylogenetic tree analyses using the HIV-1 sequences from molecular cloning and ultra-deep pyrosequencing (UDPS). Two gene regions of the HIV genome, env and gag, were involved.

RESULTS

The results of phylogenetic analysis using sequences from molecular cloning were clear and evidential enough in lawsuits 1 and 3. Due to the delayed sampling time, the result of sequences from molecular cloning in lawsuit 2 was ambiguous. Combined with the analyzed result of sequences from UDPS and epidemiological information, the source of transmission in lawsuit 2 was further identified.

CONCLUSION

Hence phylogenetic analyses cannot exclude the possibility of unsampled intermediaries, the data interpretation should be more careful and conservative, and it should not be considered as the only evidence for the source identification in a trial without epidemiological or serological information. The evaluation of the introduced UDPS method in the identification of transmission source has shown that the validity and evidential effects were still limited and need further optimization.

Heterozygosity mapping for human dominant trait variants

Homozygosity mapping is a well-known technique to identify runs of homozygous variants that are likely to harbor genes responsible for autosomal recessive disease, but a comparable method for autosomal dominant traits has been lacking. We developed an approach to map dominant disease genes based on heterozygosity frequencies of sequence variants in the immediate vicinity of a dominant trait. We demonstrate through theoretical analysis that DNA variants surrounding an inherited dominant disease variant tend to have increased heterozygosity compared with variants elsewhere in the genome. We confirm existence of this phenomenon in sequence data with known dominant pathogenic variants obtained on family members and in unrelated population controls. A computer-based approach to estimating empirical significance levels associated with our test statistics shows genome-wide p-values smaller than 0.05 for many but not all of the individuals carrying a pathogenic variant.

A non-threshold region-specific method for detecting rare variants in complex diseases

A region-specific method, NTR (non-threshold rare) variant detection method, was developed—it does not use the threshold for defining rare variants and accounts for directions of effects. NTR also considers linkage disequilibrium within the region and accommodates common and rare variants simultaneously. NTR weighs variants according to minor allele frequency and odds ratio to combine the effects of common and rare variants on disease occurrence into a single score and provides a test statistic to assess the significance of the score. In the simulations, under different effect sizes, the power of NTR increased as the effect size increased, and the type I error of our method was controlled well. Moreover, NTR was compared with several other existing methods, including the combined multivariate and collapsing method (CMC), weighted sum statistic method (WSS), sequence kernel association test (SKAT), and its modification, SKAT-O. NTR yields comparable or better power in simulations, especially when the effects of linkage disequilibrium between variants were at least moderate. In an analysis of diabetic nephropathy data, NTR detected more confirmed disease-related genes than the other aforementioned methods. NTR can thus be used as a complementary tool to help in dissecting the etiology of complex diseases.

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets.

Methods for identifying differentially methylated regions for sequence- and array-based data

DNA methylation is one of the most important epigenetic mechanisms, and participates in the pathogenic processes of many diseases. Differentially methylated regions (DMRs) in the genome have been reported and implicated in a number of different diseases, tissues and cell types, and are associated with gene expression levels. Therefore, identification of DMRs is one of the most critical and fundamental issues in dissecting the disease etiologies. Based on bisulfite conversion, advances in sequence- and array-based technologies have helped investigators study genome-wide DNA methylation. Many methods have been developed to detect DMRs, and they have revolutionized our understanding of DNA methylation and provided new insights into its role in diverse biological functions. According to data and region types, we discuss various methods in detecting DMRs, their utility and limitations comprehensively. We recommend using a few of the methods in the same data and region type to detect DMRs because they could be complementary to one another.

Using propensity score adjustment method in genetic association studies

BACKGROUND

The statistical tests for single locus disease association are mostly under-powered. If a disease associated causal single nucleotide polymorphism (SNP) operates essentially through a complex mechanism that involves multiple SNPs or possible environmental factors, its effect might be missed if the causal SNP is studied in isolation without accounting for these unknown genetic influences. In this study, we attempt to address the issue of reduced power that is inherent in single point association studies by accounting for genetic influences that negatively impact the detection of causal variant in single point association analysis. In our method we use propensity score (PS) to adjust for the effect of SNPs that influence the marginal association of a candidate marker. These SNPs might be in linkage disequilibrium (LD) and/or epistatic with the target-SNP and have a joint interactive influence on the disease under study. We therefore propose a propensity score adjustment method (PSAM) as a tool for dimension reduction to improve the power for single locus studies through an estimated PS to adjust for influence from these SNPs while regressing disease status on the target-genetic locus. The degree of freedom of such a test is therefore always restricted to 1.

RESULTS

We assess PSAM under the null hypothesis of no disease association to affirm that it correctly controls for the type-I-error rate (<0.05). PSAM displays reasonable power (>70%) and shows an average of 15% improvement in power as compared with commonly-used logistic regression method and PLINK under most simulated scenarios. Using the open-access multifactor dimensionality reduction dataset, PSAM displays improved significance for all disease loci. Through a whole genome study, PSAM was able to identify 21 SNPs from the GAW16 NARAC dataset by reducing their original trend-test p-values from within 0.001 and 0.05 to p-values less than 0.0009, and among which 6 SNPs were further found to be associated with immunity and inflammation.

CONCLUSIONS

PSAM improves the significance of single-locus association of causal SNPs which have had marginal single point association by adjusting for influence from other SNPs in a dataset. This would explain part of the missing heritability without increasing the complexity of the model due to huge multiple testing scenarios. The newly reported SNPs from GAW16 data would provide evidences for further research to elucidate the etiology of rheumatoid arthritis. PSAM is proposed as an exploratory tool that would be complementary to other existing methods. A downloadable user friendly program, PSAM, written in SAS, is available for public use.

Use of a failure probability constraint to suggest an initial dose in a phase I cancer clinical trial

The primary objective of a Phase I cancer clinical trial is to determine the maximum tolerated dose of a drug. The “failure probability” was proposed and used as a constraint to help identify a suitable initial dose range. The maximum tolerated dose was then determined based on a 3 + 3 cohort-based escalation scheme. Multiple simulations were conducted, and the method was evaluated according to the required sample size and accuracy and precision of maximum tolerated dose estimate. The results indicated that the median of the initial dose range suggested using a failure probability is a suitable initial dose regardless of the dose escalation sequence used for a cancer Phase I study. This initial dose required a smaller sample size and resulted in less bias of the estimated maximum tolerated dose compared with a commonly used initial dose, that is, 10% of the lethal dose. We tested our approach using real dose and toxicity outcome data from two published Phase I studies. These results indicate that adding a failure probability constraint into the calculation of the initial dose range will improve the efficiency of Phase I cancer trials.

Genetic polymorphisms and tissue expression of interleukin-22 associated with risk and therapeutic response of gastric mucosa-associated lymphoid tissue lymphoma

Chronic Helicobacter pylori-stimulated immune reactions determine the pathogenesis of gastric mucosa-associated lymphoid tissue (MALT) lymphoma. We aimed to explore the genetic predisposition to this lymphoma and its clinical implication. A total of 68 patients and 140 unrelated controls were genotyped for 84 single-nucleotide polymorphisms in genes encoding cytokines, chemokines and related receptors that play important roles in T cell-mediated gastrointestinal immunity. Five genotypes in IL-22, namely CC at rs1179246, CC at rs2227485, AA at rs4913428, AA at rs1026788 and TT at rs7314777, were associated with disease susceptibility. The former four genotypes resided in the same linkage disequilibrium block (r(2)=0.99) that conferred an approximately threefold higher risk. In vitro experiments demonstrated that co-culturing peripheral mononuclear cells or CD4(+) T cells with H. pylori stimulated the secretion of interleukin-22 (IL-22), and that IL-22 induced the expression of antimicrobial proteins, RegIIIα and lipocalin-2, in gastric epithelial cells. Furthermore, patients with gastric tissue expressing IL-22 were more likely to respond to H. pylori eradication (14/22 vs 4/19, P<0.006). We conclude that susceptibility of gastric MALT lymphoma is influenced by genetic polymorphisms in IL-22, the product of which is involved in mucosal immunity against H. pylori and associated with tumor response to H. pylori eradication.

Identifying rare and common disease associated variants in genomic data using Parkinson's disease as a model

BACKGROUND

Genome-wide association studies have been successful in identifying common genetic variants for human diseases. However, much of the heritable variation associated with diseases such as Parkinson's disease remains unknown suggesting that many more risk loci are yet to be identified. Rare variants have become important in disease association studies for explaining missing heritability. Methods for detecting this type of association require prior knowledge on candidate genes and combining variants within the region. These methods may suffer from power loss in situations with many neutral variants or causal variants with opposite effects.

RESULTS

We propose a method capable of scanning genetic variants to identify the region most likely harbouring disease gene with rare and/or common causal variants. Our method assigns a score at each individual variant based on our scoring system. It uses aggregate scores to identify the region with disease association. We evaluate performance by simulation based on 1000 Genomes sequencing data and compare with three commonly used methods. We use a Parkinson's disease case-control dataset as a model to demonstrate the application of our method. Our method has better power than CMC and WSS and similar power to SKAT-O with well-controlled type I error under simulation based on 1000 Genomes sequencing data. In real data analysis, we confirm the association of α-synuclein gene (SNCA) with Parkinson's disease (p = 0.005). We further identify association with hyaluronan synthase 2 (HAS2, p = 0.028) and kringle containing transmembrane protein 1 (KREMEN1, p = 0.006). KREMEN1 is associated with Wnt signalling pathway which has been shown to play an important role for neurodegeneration in Parkinson's disease.

CONCLUSIONS

Our method is time efficient and less sensitive to inclusion of neutral variants and direction effect of causal variants. It can narrow down a genomic region or a chromosome to a disease associated region. Using Parkinson's disease as a model, our method not only confirms association for a known gene but also identifies two genes previously found by other studies. In spite of many existing methods, we conclude that our method serves as an efficient alternative for exploring genomic data containing both rare and common variants.

A novel method for identification and quantification of consistently differentially methylated regions

Advances in biotechnology have resulted in large-scale studies of DNA methylation. A differentially methylated region (DMR) is a genomic region with multiple adjacent CpG sites that exhibit different methylation statuses among multiple samples. Many so-called “supervised” methods have been established to identify DMRs between two or more comparison groups. Methods for the identification of DMRs without reference to phenotypic information are, however, less well studied. An alternative “unsupervised” approach was proposed, in which DMRs in studied samples were identified with consideration of nature dependence structure of methylation measurements between neighboring probes from tiling arrays. Through simulation study, we investigated effects of dependencies between neighboring probes on determining DMRs where a lot of spurious signals would be produced if the methylation data were analyzed independently of the probe. In contrast, our newly proposed method could successfully correct for this effect with a well-controlled false positive rate and a comparable sensitivity. By applying to two real datasets, we demonstrated that our method could provide a global picture of methylation variation in studied samples. R source codes to implement the proposed method were freely available at http://www.csjfann.ibms.sinica.edu.tw/eag/programlist/ICDMR/ICDMR.html.

The DAO gene is associated with schizophrenia and interacts with other genes in the Taiwan Han Chinese population

BACKGROUND

Schizophrenia is a highly heritable disease with a polygenic mode of inheritance. Many studies have contributed to our understanding of the genetic underpinnings of schizophrenia, but little is known about how interactions among genes affect the risk of schizophrenia. This study aimed to assess the associations and interactions among genes that confer vulnerability to schizophrenia and to examine the moderating effect of neuropsychological impairment.

METHODS

We analyzed 99 SNPs from 10 candidate genes in 1,512 subject samples. The permutation-based single-locus, multi-locus association tests, and a gene-based multifactorial dimension reduction procedure were used to examine genetic associations and interactions to schizophrenia.

RESULTS

We found that no single SNP was significantly associated with schizophrenia. However, a risk haplotype, namely A-T-C of the SNP triplet rsDAO7-rsDAO8-rsDAO13 of the DAO gene, was strongly associated with schizophrenia. Interaction analyses identified multiple between-gene and within-gene interactions. Between-gene interactions including DAO*DISC1 , DAO*NRG1 and DAO*RASD2 and a within-gene interaction for CACNG2 were found among schizophrenia subjects with severe sustained attention deficits, suggesting a modifying effect of impaired neuropsychological functioning. Other interactions such as the within-gene interaction of DAO and the between-gene interaction of DAO and PTK2B were consistently identified regardless of stratification by neuropsychological dysfunction. Importantly, except for the within-gene interaction of CACNG2, all of the identified risk haplotypes and interactions involved SNPs from DAO.

CONCLUSIONS

These results suggest that DAO, which is involved in the N-methyl-d-aspartate receptor regulation, signaling and glutamate metabolism, is the master gene of the genetic associations and interactions underlying schizophrenia. Besides, the interaction between DAO and RASD2 has provided an insight in integrating the glutamate and dopamine hypotheses of schizophrenia.

Fine-mapping angiotensin-converting enzyme gene: separate QTLs identified for hypertension and for ACE activity

Angiotensin-converting enzyme (ACE) has been implicated in multiple biological system, particularly cardiovascular diseases. However, findings associating ACE insertion/deletion polymorphism with hypertension or other related traits are inconsistent. Therefore, in a two-stage approach, we aimed to fine-map ACE in order to narrow-down the function-specific locations. We genotyped 31 single nucleotide polymorphisms (SNPs) of ACE from 1168 individuals from 305 young-onset (age ≤40) hypertension pedigrees, and found four linkage disequilibrium (LD) blocks. A tag-SNP, rs1800764 on LD block 2, upstream of and near the ACE promoter, was significantly associated with young-onset hypertension (p = 0.04). Tag-SNPs on all LD blocks were significantly associated with ACE activity (p-value: 10^–16 to <10^–33). The two regions most associated with ACE activity were found between exon13 and intron18 and between intron 20 and 3′UTR, as revealed by measured haplotype analysis. These two major QTLs of ACE activity and the moderate effect variant upstream of ACE promoter for young-onset hypertension were replicated by another independent association study with 842 subjects.

Using maximal segmental score in genome-wide association studies

Genome-wide association studies (GWAS) have become the method of choice for identifying disease susceptibility genes in common disease genetics research. Despite successes in these studies, much of the heritability remains unexplained due to lack of power and low resolution. High-density genotyping arrays can now screen more than 5 million genetic markers. As a result, multiple comparison has become an important issue especially in the era of next-generation sequencing. We propose to use a two-stage maximal segmental score procedure (MSS) which uses region-specific empirical P-values to identify genomic segments most likely harboring the disease gene. We develop scoring systems based on Fisher's P-value combining method to convert locus-specific significance levels into region-specific scores. Through simulations, our result indicated that MSS increased the power to detect genetic association as compared with conventional methods provided type I error was at 5%. We demonstrated the application of MSS on a publicly available case-control dataset of Parkinson's disease and replicated the findings in the literature. MSS provides an efficient exploratory tool for high-density association data in the current era of next-generation sequencing. R source codes to implement the MSS procedure are freely available at http://www.csjfann.ibms.sinica.edu.tw/EAG/program/programlist.htm.

Constructing endophenotypes of complex diseases using non-negative matrix factorization and adjusted rand index

Complex diseases are typically caused by combinations of molecular disturbances that vary widely among different patients. Endophenotypes, a combination of genetic factors associated with a disease, offer a simplified approach to dissect complex trait by reducing genetic heterogeneity. Because molecular dissimilarities often exist between patients with indistinguishable disease symptoms, these unique molecular features may reflect pathogenic heterogeneity. To detect molecular dissimilarities among patients and reduce the complexity of high-dimension data, we have explored an endophenotype-identification analytical procedure that combines non-negative matrix factorization (NMF) and adjusted rand index (ARI), a measure of the similarity of two clusterings of a data set. To evaluate this procedure, we compared it with a commonly used method, principal component analysis with k-means clustering (PCA-K). A simulation study with gene expression dataset and genotype information was conducted to examine the performance of our procedure and PCA-K. The results showed that NMF mostly outperformed PCA-K. Additionally, we applied our endophenotype-identification analytical procedure to a publicly available dataset containing data derived from patients with late-onset Alzheimer's disease (LOAD). NMF distilled information associated with 1,116 transcripts into three metagenes and three molecular subtypes (MS) for patients in the LOAD dataset: MS1 (n1=80), MS2 (n2=73), and MS3 (n3=23). ARI was then used to determine the most representative transcripts for each metagene; 123, 89, and 71 metagene-specific transcripts were identified for MS1, MS2, and MS3, respectively. These metagene-specific transcripts were identified as the endophenotypes. Our results showed that 14, 38, 0, and 28 candidate susceptibility genes listed in AlzGene database were found by all patients, MS1, MS2, and MS3, respectively. Moreover, we found that MS2 might be a normal-like subtype. Our proposed procedure provides an alternative approach to investigate the pathogenic mechanism of disease and better understand the relationship between phenotype and genotype.

Meta-analysis identifies common variants associated with body mass index in east Asians

Multiple genetic loci associated with obesity or body mass index (BMI) have been identified through genome-wide association studies conducted predominantly in populations of European ancestry. We conducted a meta-analysis of associations between BMI and approximately 2.4 million SNPs in 27,715 East Asians, followed by in silico and de novo replication in 37,691 and 17,642 additional East Asians, respectively. We identified ten BMI-associated loci at the genome-wide significance level (P<5.0×10⁻⁸), including seven previously identified loci (FTO, SEC16B, MC4R, GIPR/QPCTL, ADCY3/RBJ, BDNF, and MAP2K5) and three novel loci in or near the CDKAL1,PCSK1, and GP2 genes. Three additional loci nearly reached the genome-wide significance threshold, including two previously identified loci in the GNPDA2 and TFAP2B genes and a new locus near PAX6, which all had P<5.0×10⁻⁷. Findings from this study may shed light on new pathways involved in obesity and demonstrate the value of conducting genetic studies in non-European populations.

A genome-wide association study identifies susceptibility variants for type 2 diabetes in Han Chinese

To investigate the underlying mechanisms of T2D pathogenesis, we looked for diabetes susceptibility genes that increase the risk of type 2 diabetes (T2D) in a Han Chinese population. A two-stage genome-wide association (GWA) study was conducted, in which 995 patients and 894 controls were genotyped using the Illumina HumanHap550-Duo BeadChip for the first genome scan stage. This was further replicated in 1,803 patients and 1,473 controls in stage 2. We found two loci not previously associated with diabetes susceptibility in and around the genes protein tyrosine phosphatase receptor type D (PTPRD) (P = 8.54×10⁻¹⁰; odds ratio [OR] = 1.57; 95% confidence interval [CI] = 1.36–1.82), and serine racemase (SRR) (P = 3.06×10⁻⁹; OR = 1.28; 95% CI = 1.18–1.39). We also confirmed that variants in KCNQ1 were associated with T2D risk, with the strongest signal at rs2237895 (P = 9.65×10⁻¹⁰; OR = 1.29, 95% CI = 1.19–1.40). By identifying two novel genetic susceptibility loci in a Han Chinese population and confirming the involvement of KCNQ1, which was previously reported to be associated with T2D in Japanese and European descent populations, our results may lead to a better understanding of differences in the molecular pathogenesis of T2D among various populations.

Type 2 diabetes (T2D) is a complex disease that involves many genes and environmental factors. Genome-wide and candidate-gene association studies have thus far identified at least 19 regions containing genes that may confer a risk for T2D. However, most of these studies were conducted with patients of European descent. We studied Chinese patients with T2D and identified two genes, PTPRD and SRR, that were not previously known to be involved in diabetes and are involved in biological pathways different from those implicated in T2D by previous association reports. PTPRD is a protein tyrosine phosphatase and may affect insulin signaling on its target cells. SRR encodes a serine racemase that synthesizes D-serine from L-serine. Both D-serine (coagonist) and the neurotransmitter glutamate bind to NMDA receptors and trigger excitatory neurotransmission in the brain. Glutamate signaling also regulates insulin and glucagon secretion in pancreatic islets. Thus, SRR and D-serine, in addition to regulating insulin and glucagon secretion, may play a role in the etiology of T2D. Our study suggests that, in different patient populations, different genes may confer risks for diabetes. Our findings may lead to a better understanding of the molecular pathogenesis of T2D.

A genome-wide association study identifies new loci for ACE activity: potential implications for response to ACE inhibitor

Because angiotensin-converting enzyme (ACE) activity is implicated widely in biological systems, we aimed to identify its novel quantitative trait loci for the purposes of understanding ACE activity regulation and pharmacogenetics relating to ACE inhibitor (ACEI). We performed a two-stage genome-wide association study: (1) from 400 young-onset hypertension (YOH) subjects and (2) a confirmation study with an additional 623 YOH subjects. In the first stage, eight single nucleotide polymorphisms (SNPs) of the ACE structural gene and one SNP of ABO genes were significantly associated with ACE activity. SNP rs4343 in exon17 near the well-known insertion/deletion polymorphism had the strongest association. We confirmed in the second stage that three SNPs: rs4343 in ACE gene (P=3.0 x 10⁻²⁵), rs495828 (P=3.5 x 10⁻⁸) and rs8176746 (P=9.3 x 10⁻⁵) in ABO gene were significantly associated with ACE activity. We further replicated the association between ABO genotype/blood types and ACE activity in an independent YOH family study (428 hypertension pedigrees), and showed a potential differential blood pressure response to ACEI in subjects with varied numbers of ACE-activity-raising alleles. These findings may broaden our understanding of the mechanisms controlling ACE activity and advance our pharmacogenetic knowledge on ACEI.

Severe obesity is associated with novel single nucleotide polymorphisms of the ESR1 and PPARgamma locus in Han Chinese

BACKGROUND

A large number of potential obesity loci have been reported. At least 18 genes have been replicated in a minimum of 5 studies on obesity-related phenotypes. Fourteen additional genes have been associated with obesity in Asians.

OBJECTIVES

Our objectives were to examine how many common variants of these candidate genes are associated with severe obesity in Han Chinese and how they are combined to exert their effects.

DESIGN

In total, 304 severely obese patients [body mass index (BMI; in kg/m(2)) > or =39] and 304 control subjects (BMI < or = 24) participated in a 2-staged association study. Subsequently, 220 additional severely obese patients (BMI > or = 35) and 338 controls (BMI < or = 24) were recruited to replicate the results. All of the controls were age-, sex-, education- and residence-matched. Finally, a pooled analysis was carried out based on all 514 cases and 606 controls with complete information.

RESULTS

The first-stage association analysis in 94 cases and 94 controls found 18 potentially associated single nucleotide polymorphisms (SNPs) (P = 0.01-0.1). The significance of 3 novel common SNPs, 1 on ESR1 and 2 on PPARgamma, were confirmed in the second stage and replicated further with odds ratios ranging from 1.89 to 2.24. The combined effect of these 3 genes was stronger (odds ratio: 5.27; 95% CI: 2.25, 12.32) than that from any individual gene.

CONCLUSIONS

Severe obesity in Han Chinese was associated with 3 novel common SNPs for ESR1 and PPARgamma. These 2 genes collectively result in a >5-fold risk of severe obesity. This information may contribute to the assessment of risk of severe obesity.

A genome-wide survey of copy number variations in Han Chinese residing in Taiwan

Copy number variation (CNV) is a form of DNA sequence variation in the human genome. CNVs can affect expression of nearby and distant genes, and some of them might cause certain phenotypic differences. CNVs vary slightly in location and frequency among different populations. Because currently-available CNV information from Asian population was limited to fewer small-scale studies with only dozens of subjects, a high-resolution CNV survey was conducted using a large number of Han Chinese in this study. The Illumina HumanMap550K single-nucleotide polymorphism array was used to identify CNVs from 813 unrelated Han Chinese residing in Taiwan. A total of 365 CNV regions were identified in this population, and the average size of the CNV regions was 235 kb (covering a total of 2.86% of the human genome), and 67 (18.4%) were newly-discovered CNV regions. Two hundred and seventy-nine CNV regions (76%) were verified from 304 randomly-selected samples by Affymetrix 500K GeneChip and qPCR experiments. These regions contain 1029 genes, some of which are associated with diseases. Consistent with previous studies, most CNVs were rare structural variations in the human genome, and only 64 regions (17.5%) had a CNV allele frequency greater than 1%. Our discovery of 67 new CNV regions indicates that previous CNV coverage of the human genome is incomplete and there is diversity among different ethnic populations. The comprehensive knowledge of CNVs in the human genome is very important and useful in further genetic studies.

Genome-wide association study of young-onset hypertension in the Han Chinese population of Taiwan

Young-onset hypertension has a stronger genetic component than late-onset counterpart; thus, the identification of genes related to its susceptibility is a critical issue for the prevention and management of this disease. We carried out a two-stage association scan to map young-onset hypertension susceptibility genes. The first-stage analysis, a genome-wide association study, analyzed 175 matched case-control pairs; the second-stage analysis, a confirmatory association study, verified the results at the first stage based on a total of 1,008 patients and 1,008 controls. Single-locus association tests, multilocus association tests and pair-wise gene-gene interaction tests were performed to identify young-onset hypertension susceptibility genes. After considering stringent adjustments of multiple testing, gene annotation and single-nucleotide polymorphism (SNP) quality, four SNPs from two SNP triplets with strong association signals (-log(10)(p)>7) and 13 SNPs from 8 interactive SNP pairs with strong interactive signals (-log(10)(p)>8) were carefully re-examined. The confirmatory study verified the association for a SNP quartet 219 kb and 495 kb downstream of LOC344371 (a hypothetical gene) and RASGRP3 on chromosome 2p22.3, respectively. The latter has been implicated in the abnormal vascular responsiveness to endothelin-1 and angiotensin II in diabetic-hypertensive rats. Intrinsic synergy involving IMPG1 on chromosome 6q14.2-q15 was also verified. IMPG1 encodes interphotoreceptor matrix proteoglycan 1 which has cation binding capacity. The genes are novel hypertension targets identified in this first genome-wide hypertension association study of the Han Chinese population.

Lipoprotein lipase variants associated with an endophenotype of hypertension: hypertension combined with elevated triglycerides

Previously, we observed that young-onset hypertension was independently associated with elevated plasma triglyceride(s) (TG) levels to a greater extent than other metabolic risk factors. Thus, focusing on the endophenotype--hypertension combined with elevated TG--we designed a family-based haplotype association study to explore its genetic connection with novel genetic variants of lipoprotein lipase gene (LPL), which encodes a major lipid metabolizing enzyme. Young-onset hypertension probands and their families were recruited, numbering 1,002 individuals from 345 families. Single-nucleotide polymorphism discovery for LPL, linkage disequilibrium (LD) analysis, transmission disequilibrium tests (TDT), bin construction, haplotype TDT association and logistic regression analysis were performed. We found that the CC- haplotype (i) spanning from intron 2 to intron 4 and the ACATT haplotype (ii) spanning from intron 5 to intron 6 were significantly associated with hypertension-related phenotypes: hypertension (ii, P=0.05), elevated TG (i, P=0.01), and hypertension combined with elevated TG (i, P=0.001; ii, P<0.0001), according to TDT. The risk of this hypertension subtype increased with the number of risk haplotypes in the two loci, using logistic regression model after adjusting within-family correlation. The relationships between LPL variants and hypertension-related disorders were also confirmed by an independent association study. Finally, we showed a trend that individuals with homozygous risk haplotypes had decreased LPL expression after a fatty meal, as opposed to those with protective haplotypes. In conclusion, this study strongly suggests that two LPL intronic variants may be associated with development of the hypertension endophenotype with elevated TG.

A large-scale survey of genetic copy number variations among Han Chinese residing in Taiwan

BACKGROUND

Copy number variations (CNVs) have recently been recognized as important structural variations in the human genome. CNVs can affect gene expression and thus may contribute to phenotypic differences. The copy number inferring tool (CNIT) is an effective hidden Markov model-based algorithm for estimating allele-specific copy number and predicting chromosomal alterations from single nucleotide polymorphism microarrays. The CNIT algorithm, which was constructed using data from 270 HapMap multi-ethnic individuals, was applied to identify CNVs from 300 unrelated Han Chinese individuals in Taiwan.

RESULTS

Using stringent selection criteria, 230 regions with variable copy numbers were identified in the Han Chinese population; 133 (57.83%) had been reported previously, 64 displayed greater than 1% CNV allele frequency. The average size of the CNV regions was 322 kb (ranging from 1.48 kb to 5.68 Mb) and covered a total of 2.47% of the human genome. A total of 196 of the CNV regions were simple deletions and 27 were simple amplifications. There were 449 genes and 5 microRNAs within these CNV regions; some of these genes are known to be associated with diseases.

CONCLUSION

The identified CNVs are characteristic of the Han Chinese population and should be considered when genetic studies are conducted. The CNV distribution in the human genome is still poorly characterized, and there is much diversity among different ethnic populations.

Genome-wide copy number analysis using copy number inferring tool (CNIT) and DNA pooling

Copy number variation (CNV) has become an important genomic structure element in the human population, and some CNVs are related to specific traits and diseases. Moreover, analysis of human genomes has been potentiated by the use of high-resolution microarrays that assess single nucleotide polymorphisms (SNPs). Although many programs have been designed to analyze data from Affymetrix SNP microarrays, they all have high false-positive rates (FPRs) in copy number (CN) analyses. Copy number analysis tool (CNAT) 4.0 is a recently developed program that offers improved CN estimation, but small amplifications and deletions are lost when using the smoothing procedure. Here, we propose a copy number inferring tool (CNIT) algorithm for the 100K SNP microarray to investigate CNVs at 29.6-kb resolution. CNIT estimated SNP allelic and total CN with reliable P values based on intensity data. In addition, the hidden Markov model (HMM) method was applied to predict regions having altered CN by considering contiguous SNPs. Based on a CN analysis of 23 unrelated Taiwanese and 30 HapMap Centre d'Etude du Polymorphisme Humain (CEPH) trios, CNIT showed higher accuracy and power than other programs. The FPRs and false-negative rates (FNRs) of CNIT were 0.1% and 0.16%, respectively. CNIT also showed better sensitivity for detecting small amplifications and deletions. Furthermore, DNA pooling of 10 and 30 normal unrelated individuals were applied to the 100K SNP microarray, respectively, and 12 common CN-variable regions were identified, suggesting that DNA pooling can be applied to discover common CNVs.

Kernel-based association test

Association mapping (i.e., linkage disequilibrium mapping) is a powerful tool for positional cloning of disease genes. We propose a kernel-based association test (KBAT), which is a composite function of "P-values of single-locus association tests" and "kernel weights related to intermarker distances and/or linkage disequilibria." The KBAT is a general form of some current test statistics. This method can be applied to the study of candidate genes and can scan each chromosome using a moving average procedure. We evaluated the performance of the KBAT through simulation studies that considered evolutionary parameters, disease models, sample sizes, kernel functions, test statistics, window attributes, empirical P-value estimations, and genetic/physical maps. The results showed that the KBAT had a well-controlled false positive rate and high power compared to existing methods. In addition, the KBAT was also applied to analyze a genomewide data set from the Collaborative Study on the Genetics of Alcoholism. Important genes associated with alcoholism dependence were identified. In summary, the merits of the KBAT are multifold: the KBAT is robust against the inclusion of nuisance markers, is invariant to the map scale, and accommodates different types of genomic data, study designs, and study purposes. The proposed methods are packaged in the user-friendly software, KBAT, available at http://www.stat.sinica.edu.tw/hsinchou/genetics/association/KBAT.htm.

Using the longest significance run to estimate region-specific p-values in genetic association mapping studies

BACKGROUND

Association testing is a powerful tool for identifying disease susceptibility genes underlying complex diseases. Technological advances have yielded a dramatic increase in the density of available genetic markers, necessitating an increase in the number of association tests required for the analysis of disease susceptibility genes. As such, multiple-tests corrections have become a critical issue. However the conventional statistical corrections on locus-specific multiple tests usually result in lower power as the number of markers increases. Alternatively, we propose here the application of the longest significant run (LSR) method to estimate a region-specific p-value to provide an index for the most likely candidate region.

RESULTS

An advantage of the LSR method relative to procedures based on genotypic data is that only p-value data are needed and hence can be applied extensively to different study designs. In this study the proposed LSR method was compared with commonly used methods such as Bonferroni's method and FDR controlling method. We found that while all methods provide good control over false positive rate, LSR has much better power and false discovery rate. In the authentic analysis on psoriasis and asthma disease data, the LSR method successfully identified important candidate regions and replicated the results of previous association studies.

CONCLUSION

The proposed LSR method provides an efficient exploratory tool for the analysis of sequences of dense genetic markers. Our results show that the LSR method has better power and lower false discovery rate comparing with the locus-specific multiple tests.

MPDA: microarray pooled DNA analyzer

BACKGROUND

Microarray-based pooled DNA experiments that combine the merits of DNA pooling and gene chip technology constitute a pivotal advance in biotechnology. This new technique uses pooled DNA, thereby reducing costs associated with the typing of DNA from numerous individuals. Moreover, use of an oligonucleotide gene chip reduces costs related to processing various DNA segments (e.g., primers, reagents). Thus, the technique provides an overall cost-effective solution for large-scale genomic/genetic research. However, few publicly shared tools are available to systematically analyze the rapidly accumulating volume of whole-genome pooled DNA data.

RESULTS

We propose a generalized concept of pooled DNA and present a user-friendly tool named Microarray Pooled DNA Analyzer (MPDA) that we developed to analyze hybridization intensity data from microarray-based pooled DNA experiments. MPDA enables whole-genome DNA preferential amplification/hybridization analysis, allele frequency estimation, association mapping, allelic imbalance detection, and permits integration with shared data resources online. Graphic and numerical outputs from MPDA support global and detailed inspection of large amounts of genomic data. Four whole-genome data analyses are used to illustrate the major functionalities of MPDA. The first analysis shows that MPDA can characterize genomic patterns of preferential amplification/hybridization and provide calibration information for pooled DNA data analysis. The second analysis demonstrates that MPDA can accurately estimate allele frequencies. The third analysis indicates that MPDA is cost-effective and reliable for association mapping. The final analysis shows that MPDA can identify regions of chromosomal aberration in cancer without paired-normal tissue.

CONCLUSION

MPDA, the software that integrates pooled DNA association analysis and allelic imbalance analysis, provides a convenient analysis system for extensive whole-genome pooled DNA data analysis. The software, user manual and illustrated examples are freely available online at the MPDA website listed in the Availability and requirements section.

A promoter sequence variant of ZNF750 is linked with familial psoriasis

We previously mapped a psoriasis-susceptibility gene to a 3.8-Mb region of the 17q terminus in a five-generation Chinese family with autosomal-dominant psoriasis. To identify the mutations responsible for the psoriasis in this family, we sequenced 78 genes within the region and found four gene variants, p.Ala201Val in CD7, c.-625A>C in zinc-finger protein 750 (ZNF750), p.Asp189Asn in C17orf56, and p.Ala568Thr in AATK cosegregated with the disease. The latter two variants were not studied further in the absence of disease segregation in other familial psoriasis and presence of variants in normal subjects. Functional analyses of CD7 did not support CD7 as a disease-causing gene. In contrast, the c.-625A>C mutation in ZNF750 resulted in a 42% reduction of the promoter activity, and the electrophoretic mobility shift assay showed binding of nuclear protein(s) to the mutant C allele. The c.-625A>C mutation was found in another sporadic psoriasis patient but was absent in 188 normal controls. Together, the mutation accounts for 1.7% (confidence interval: 0.2-5.84%) of psoriasis in the Chinese population. This report suggests that ZNF750 mutations could contribute to psoriasis susceptibility.

Association mapping using pooled DNA

The genetic dissection of complex disorders via genetic marker data has gained popularity in the postgenome era. Methods for typing genetic markers on human chromosomes continue to improve. Compared with the popular individual genotyping experiment, a pooled-DNA experiment (alleotyping experiment) is more cost effective when carrying out genetic typing. This chapter provides an overview of association mapping using pooled DNA and describes a five-stage study design including the preliminary calibration of peak intensities, estimation of allele frequency, single-locus association mapping, multilocus association mapping, and a confirmation study. Software and an analysis of authentic data are presented. The strengths and weaknesses of pooled-DNA analyses, as well as possible future applications for this method, are discussed.

More evidence supports the association of PPP3CC with schizophrenia

Calcineurin is a calcium/calmodulin-dependent protein phosphatase composed of two subunits, a regulatory subunit of calcineurin B (CNB) and a catalytic subunit of calcineurin A (CNA). PPP3CC is the gamma isoform of CNA located at the chromosome 8p21.3 region. To evaluate the association between PPP3CC and schizophrenia in the Taiwanese population, 10 single nucleotide polymorphism (SNP) markers across the gene were genotyped by the method of MALDI-TOF in 218 schizophrenia families with at least two affected siblings. One SNP (rs2272080) located around the exon 1 untranslated region was nominally associated with schizophrenia (P=0.024) and significantly associated with the expression of PPP3CC in lymphoblast cell line; the TT and TG genotype had significantly higher relative expression levels than the GG genotype (P=0.0012 and 0.015, respectively). In further endophenotype stratification, the single locus of rs2272080 and the haplotypes of both two-SNP haplotype (rs7833266-rs2272080) and seven-SNP haplotype (rs2461491-rs2469758-rs2461489-rs2469770-rs2449340-rs1482337-rs2252471) showed significant associations with the subgroup of schizophrenia with deficits of the sustained attention as tested by the continuous performance test (CPT, P<0.05) and the executive functioning as tested by the Wisconsin Card Sorting Test (WCST, P<0.05). The results suggest that PPP3CC gene may be a true susceptibility gene for schizophrenia.

Genome-wide scan for quantitative ACE activity in Taiwan young-onset hypertension study

OBJECTIVES

Angiotensin converting enzyme (ACE) plays major roles in the pathogenesis of cardiovascular diseases (CVD). However, findings on the relations between ACE variants and CVD have not been consistent. The purpose of this study was to map quantitative trait loci (QTL) for serum ACE activity, a heritable endophenotype of cardiovascular diseases (estimated heritability = 0.58).

METHODS

With 1,271 individuals from 373 young-onset (age <or=40) hypertension pedigrees, 479 deCODE microsatellite markers were genotyped.

RESULTS

We identified a previously unknown loci on chromosomes 9 at 149.4 cM (LOD = 3.00) in addition to a strong linkage peak near the ACE structural locus on chromosome 17 at 89.6 cM (LOD = 4.60).

CONCLUSIONS

These results not only indicate that the ACE gene or nearby loci on 17q was among the strongest QTL influencing ACE activity, but also reveal a potential ACE QTL in human genome, pointing to the complexity of ACE regulation.

Genomewide suggestive linkage of opioid dependence to chromosome 14q

The genetic predisposition to addiction to opioids and other substances is transmitted as a complex genetic trait, which investigators are attempting to characterize using genetic linkage and association. We now report a high-density genome-wide linkage study of opioid dependence. We ascertained 305 DSM-IV opioid dependent affected sibling pairs from an ethnically mixed population of methadone maintained subjects and genotyped their DNA using Affymetrix 10K v2 arrays. Analysis with MERLIN identified a region on chromosome 14q with a non-parametric lod (NPL) of 3.30. Secondary analyses indicated that this locus was relatively specific to the self-identified Puerto Rican subset, as the NPL increased from 3.30 to 5.00 (NPL(Caucasian) = 0.05 and NPL(African Amer.) = 0.15). The 14q peak encompasses the NRXN3 gene (neurexin 3), which was previously identified as a potential candidate gene for addiction. Secondary analyses also identified several regions with gender-specific NPL scores greater than 2.00. The most significant was a peak on (10q) that increased from 0.90 to 3.22 when only males were considered (NPL(female) = 0.05). Our linkage data suggest specific chromosomal loci for future fine-mapping genetic analysis and support the hypothesis that ethnic and gender specific genes underlie addiction susceptibility.

A comparison of individual genotyping and pooled DNA analysis for polymorphism validation prior to large-scale genetic studies

Polymorphism validation is an important issue in genetic studies because only polymorphic markers provide useful information. We analyzed genetic data for 180 SNPs in the human major histocompatibility complex region in Caucasian and Taiwanese populations, and evaluated ethnic heterogeneity between these populations to illustrate the importance of polymorphism validation. An initial individual genotyping experiment (IGE) with 95 samples was compared with a DNA pooling allele-typing experiment (PAE) of 630 individuals for polymorphism validation based on authentic data sets. Afterwards, all samples were genotyped individually in a confirmation study. Under narrow (broad) polymorphism criteria, 24 (41) polymorphic SNPs in Caucasians could not be validated in the Taiwanese population, suggesting a 13% (23%) inconsistency rate and revealing a strong discrepancy between genetic backgrounds, probably due to ethnic heterogeneity. IGE yielded high sensitivity and specificity for polymorphism validation, but may be sensitive to sampling variation. PAE showed high sensitivity (97%) and specificity (100%) using a narrow polymorphism criterion, but reduced specificity (83%) using a broad criterion. Public domain polymorphism databases should therefore be used with caution and polymorphism validation should be performed routinely prior to conducting large-scale genetic studies. PAE is a cost-saving, reliable alternative to IGE for polymorphism validation, especially for a stringent polymorphism criterion.

Nasopharyngeal shedding of severe acute respiratory syndrome-associated coronavirus is associated with genetic polymorphisms

Background. A high initial or peak severe acute respiratory syndrome (SARS)—associated coronavirus (SARS-CoV) load in nasopharyngeal specimens was shown to be associated with a high mortality rate. Because all infected individuals were devoid of preeexisting protective immunity against SARS-CoV, the biological basis for the variable virus burdens in different patients remains elusive.

Methods. The nationwide SARS database in Taiwan was analyzed, and genotyping of 281 single-nucleotide polymorphisms (SNPs) of 65 genes was performed for 94 patients with SARS, to identify SNPs for which distribution between patients with or without detectable nasopharyngeal shedding of SARS-CoV was biased.

Results. Titers of SARS-CoV shed in nasopharyngeal specimens varied widely, ranging from nondetectable to 10⁸ SARS-CoV RNA copies/mL, and they were correlated positively with a high mortality rate (P < .0001, by trend test) and with early death (i.e., death occurring within 2 weeks of the onset of illness) (P = .0015, by trend test). Virus shedding was found to be higher among male patients (P = .0014, by multivariate logistic regression) and among older patients (P = .015, by multivariate logistic regression). Detectable nasopharyngeal shedding of SARS-CoV was associated with polymorphic alleles of interleukins 18 (P = .014) and 1A (P = .031) and a member of NFκB complex (reticuloendotheliosis viral oncogene homolog B [RelB]) (P = .034), all of which are proinflammatory in nature, as well as the procoagulation molecule fibrinogen-like protein 2 (P = .008).

Conclusion. The SARS-CoV load is a determinant of clinical outcomes of SARS, and it is associated with polymorphisms of genes involved in innate immunity, which might be regulated in an age- and sex-dependent manner. The findings of the present study provided leads to genes involved in the host response to SARS-CoV infection; if substantiated with functional studies, these findings may be applicable to other newly emerged respiratory viruses (e.g., the influenza pandemic strain).

A comparison of major histocompatibility complex SNPs in Han Chinese residing in Taiwan and Caucasians

Genetic dissection of complex diseases is both important and challenging. The human major histocompatibility complex is involved in many human diseases and genetic mechanisms. This highly polymorphic chromosome region has been extensively studied in Caucasians but not as well in Asians. Thus, we compared genotypic distributions, linkage disequilibria and haplotype blocks between Caucasian and Taiwan's Han Chinese populations. Moreover, we investigated the population admixture and phylogenetic system in Han Chinese residing in Taiwan. The results show that Taiwan's Han Chinese differ drastically in genotypic information compared with Caucasians but are relatively homogeneous among the three major ethnic subgroups, Minnan, Hakka and Mainlanders. Differences in allele frequency (AF) between Taiwanese and Caucasians in some disease-associated loci may reveal clues to differences in disease prevalence. The results of ethnic heterogeneity imply that public databases should be used with caution in cases where the study population(s) differs from the population characterized in the database. The high homogeneity we observed among the Taiwanese subpopulations mitigates the possibility of spurious association caused by ignoring population stratification in Taiwanese disease gene association studies. These results are useful for understanding our genetic background and designing future disease gene mapping studies.

A sliding-window weighted linkage disequilibrium test

Multilocus linkage disequilibrium (LD) tests that consider inter-marker (LD) are more powerful than single-locus tests when disease etiology is contributed simultaneously by several linked and correlated loci. However, inclusion of redundant non-informative markers may result in reduced testing power and/or inflated false-positive rate, therefore selection of proper marker sets is important in such tests. We introduce a unified LD test based on a convenient marker-selection procedure (sliding window) combined with an adjustment approach (marker weighting) to dilute the impact of nuisance markers on tests. The proposed procedure includes several conventional p-value combination methods as its special cases. Simulation studies were performed to evaluate the impact of inclusion of nuisance markers and performance of the procedure. The results showed that testing power was often inversely proportional to the quantity of nuisance markers. Among a class of p-value combination methods, the product p-value method had the highest testing power. P-value truncation somewhat reduced the testing power but controlled the false-positive rate well. Compared with conventional unweighted approaches, the weighted strategy alleviated the false-positive rate and/or increased testing power when nuisance markers were included. Analyses of two authentic data sets for psoriasis and Alzheimer's disease using our proposed method confirmed previous findings.

Lipoprotein Lipase Gene is Linked and Associated with Hypertension in Taiwan Young-onset Hypertension Genetic Study

Hypertriglyceridemia has been extensively associated with hypertension. However, the mechanism behind it is poorly understood. A positive linkage signal between Lipoprotein lipase (LPL) and young-onset hypertension has been identified by us as the strongest among 18 candidate genes. Here we report our fine mapping works with seven microsatellite markers flanking LPL, sequencing results for its promoter and exons, and an extended association study with the identified single nucleotide polymorphisms(SNP). First, using data from 213 individuals in 59 nuclear families of young-onset hypertension, multipoint analysis revealed a NPL score of 3.02 for the LPL (GZ-14/GZ-15) marker in intron 6. LPL marker (p < 10(-12)) and the haplotypes containing its allele 1 (p < 0.0001) were also significantly associated with young hypertension by transmission disequilibrium test. In-depth sequencing revealed no mutation in promoter and exon regions, except two cSNP: 7754C--> A (C/A: 0.91/0.09), a silent mutation in exon 8 and S447X (C/G: 0.92/0.08), a stop codon mutation in exon 9. Other 11 cSNPs documented in NCBI GenBank are absent in our sample. Constructed from the above 2 cSNPs, haplotype AC showed a moderate TDT association with elevated triglyceride (p = 0.02) and with hypertension and elevated triglyceride combined (p = 0.06). Again, in an extended case-control study, a significant association was found between S447X and patients with persistent hypertension and elevated triglyceride (p = 0.02). We conclude that LPL variants may play a causal role in the development of hypertension in Taiwan Han Chinese. The moderate association with SNP haplotype suggests that other regulatory LPL variant may exist.

New adjustment factors and sample size calculation in a DNA-pooling experiment with preferential amplification

In the post-genome era, disease gene mapping using dense genetic markers has become an important tool for dissecting complex inheritable diseases. Locating disease susceptibility genes using DNA-pooling experiments is a potentially economical alternative to those involving individual genotyping. The foundation of a successful DNA-pooling association test is a precise and accurate estimation of allele frequency. In this article, we propose two new adjustment methods that correct for preferential amplification of nucleotides when estimating the allele frequency of single-nucleotide polymorphisms. We also discuss the effect of sample size when calibrating unequal allelic amplification. We conducted simulation studies to assess the performance of different adjustment procedures and found that our proposed adjustments are more reliable with respect to the estimation bias and root mean square error compared with the current approach. The improved performance not only improves the accuracy and precision of allele frequency estimations but also leads to more powerful disease gene mapping.

Type II collagen gene variants and inherited osteonecrosis of the femoral head

BACKGROUND

Avascular necrosis of the femoral head (ANFH) causes disability that often requires surgical intervention. Most cases of ANFH are sporadic, but we identified three families in which there was autosomal dominant inheritance of the disease and mapped the chromosomal position of the gene to 12q13.

METHODS

We carried out haplotype analysis in the families, selected candidate genes from the critical interval for ANFH on 12q13, and sequenced the promoter and exonic regions of the type II collagen gene (COL2A1) from persons with inherited and sporadic forms of ANFH.

RESULTS

We identified a G-->A transition in exon 50 of COL2A1 in affected members of a four-generation family with ANFH. This transition predicts the replacement of glycine with serine at codon 1170 in a GXY repeat of type II collagen. Another pedigree was shown to harbor the same transition, but the mutant allele occurred on a different haplotype background. In a third family, a G-->A transition in exon 33 of the gene, causing a glycine-to-serine change at codon 717, was detected. No mutation was found in the COL2A1 coding region in sporadic cases of ANFH.

CONCLUSIONS

All the patients with familial ANFH whom we studied carried COL2A1 mutations. In families with ANFH, haplotype and sequence analysis of the COL2A1 gene can be used to identify carriers of the mutant allele before the onset of clinical symptoms, allowing the initiation of measures that may delay progression of the disease.

Linkage evidence of schizophrenia to loci near neuregulin 1 gene on chromosome 8p21 in Taiwanese families

Positive linkage of schizophrenia to chromosome 8p22-21 loci had been reported in the Caucasian samples. This study was designed to replicate this finding by using eleven microsatellite markers on chromosome 8p22-21 in 52 Taiwanese schizophrenic families with at least two affected siblings. Two phenotype models (narrow: DSM-IV schizophrenia only; and broad: including schizophrenia, schizoaffective, and other non-affective psychotic disorders) were used to define the disease phenotype. Maximum non-parametric linkage scores (NPL score) of 2.45 (P = 0.008) and 1.89 (P = 0.02) were obtained for the marker D8S1222 under the broad and narrow models, respectively. Positive linkage was found across about a 4-cM region. The marker D8S1222 was about 400 kbp distal to the exon 1 of glial growth factor 2 (GGF2), an isoform of Neuregulin 1 gene (NRG1), which has been highly suggested to be a candidate gene for schizophrenia. The results provide suggestive linkage evidence of schizophrenia to loci near NRG1 on chromosome 8p21 in an ethnically distinct Taiwanese sample. Further exploration of the candidate gene and nearby chromosome regions is warranted.