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.

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.

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.

Comprehensive human leukocyte antigen genotyping of patients with type 1 diabetes mellitus in Taiwan.

BACKGROUND: Type 1 diabetes (T1D) mellitus is an autoimmune disorder involving both complex genetic and environmental factors. The incidence rates are low in Asian countries, and the specific, explanatory genetic factors underlying this have been investigated. The aim of this study was to elucidate the association of human leukocyte antigen (HLA) alleles/haplotypes with T1D in Taiwan. METHODS: We performed direct comprehensive genotyping of 6 classical HLA loci (HLA-A, -B, -C, -DPB1, -DQB1, and -DRB1) to 4-digit resolution in 104 unrelated T1D patients and 504 controls. Twenty-four of the 104 patients also exhibited thyroid autoimmunity. RESULTS: Three major susceptibility haplotypes were identified: DRB1*03:01-DQB1*02:01 (odds ratio [OR] = 5.39 under the dominant model, P = 2.3 × 10-13 ), DRB1*04:05-DQB1*04:01 (OR = 2.44, P = 5.0 × 10-4 ), and DRB1*09:01-DQB1*03:03 (OR = 2.02, P = 1.4 × 10-3 ); one protective haplotype was identified: DRB1*08:03-DQB1*06:01 (OR = 0.10, P = 1.6 × 10-3 ). DRB1*03:01-DQB1*02:01, the major T1D susceptibility haplotype, was found at a lower frequency in T1D patients with thyroid autoimmunity. The T1D protective allele DRB1*12:02 was shown to be protective against Graves' disease in our previous report. CONCLUSION: In addition to clarifying the roles of several known T1D HLA alleles and haplotypes, we discovered that the DRB1*08:03-DQB1*06:01 haplotype is protective against T1D. The DRB1*12:02 allele protected against both T1D and Graves' disease.

Susceptible genes of restless legs syndrome in migraine.

Objective Several genetic variants have been found to increase the risk of restless legs syndrome (RLS). The aim of the present study was to determine if these genetic variants were also associated with the comorbidity of RLS and migraine in patients. Methods Thirteen single-nucleotide polymorphisms (SNPs) at six RLS risk loci ( MEIS1, BTBD9, MAP2K5, PTPRD, TOX3, and an intergenic region on chromosome 2p14) were genotyped in 211 migraine patients with RLS and 781 migraine patients without RLS. Association analyses were performed for the overall cohort, as well as for the subgroups of patients who experienced migraines with and without aura and episodic migraines (EMs) vs. chronic migraines (CMs). In order to verify which genetic markers were potentially related to the incidence of RLS in migraine patients, multivariate regression analyses were also performed. Results Among the six tested loci, only MEIS1 was significantly associated with RLS. The most significant SNP of MEIS1, rs2300478, increased the risk of RLS by 1.42-fold in the overall cohort ( p = 0.0047). In the subgroup analyses, MEIS1 augmented the risk of RLS only in the patients who experienced EMs (odds ratio (OR) = 1.99, p = 0.0004) and not those experiencing CMs. Multivariate regression analyses further showed that rs2300478 in MEIS1 (OR = 1.39, p = 0.018), a CM diagnosis (OR = 1.52, p = 0.022), and depression (OR = 1.86, p = 0.005) were independent predictors of RLS in migraine. Conclusions MEIS1 variants were associated with an increased risk of RLS in migraine patients. It is possible that an imbalance in iron homeostasis and the dopaminergic system may represent a link between RLS incidence and migraines.

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.

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.

DRD2 haplotype associated with negative symptoms and sustained attention deficits in Han Chinese with schizophrenia in Taiwan.

Previous studies have reported significant associations between schizophrenia and the dopamine receptor D2 gene (DRD2) variants. The relationships between DRD2 and clinical phenotypes are of particular interest because DRD2 has been shown to associate with treatment response and prefrontal dopamine transmission. Glatt et al. reported significant associations between schizophrenia and DRD2 variants (two single-nucleotide polymorphisms (SNPs) rs1079727 and rs2283265, and two haplotypes, block 3 (rs1079727(A)-rs2440390(C)-rs2283265(G)) and block 4 (rs1801028(G)-rs1110977(A)-rs1124492(C)-rs2734841 (T))) in 2408 Han Chinese individuals in Taiwan. To further investigate the relationships between the SNPs/haplotypes of DRD2 and clinical symptoms and neuropsychological function, we compared the quantitative phenotypes in patients with risk alleles/haplotypes and those without. The results showed that the A allele of rs1079727, G allele of rs2283265, A allele of rs1124492 and the risk haplotype (A-C-G) of block 3 were associated with more severe negative symptoms. With regard to neuropsychological performance, the risk haplotype (G-A-C-T) of block 4 was associated with poorer performance in the sustained attention task. Our results imply that the genetic variants of DRD2 might not only have a role in susceptibility to schizophrenia, but also influence the phenotypes of negative symptoms and sustained attention in schizophrenia. This association warrants further validation.

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 = 8.54x10(-10); odds ratio [OR] = 1.57; 95% confidence interval [CI] = 1.36-1.82), and serine racemase (SRR) (P = 3.06x10(-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 = 9.65x10(-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.

Effects of insomnia and non-vasomotor menopausal symptoms on coronary heart disease risk: a mendelian randomization study.

Background: Previous studies suggested that vasomotor symptoms were associated with an increasing risk of coronary heart diseases (CHD) but not clear with menopausal symptoms other than vasomotor symptoms. Given the heterogeneity and interrelationship among menopausal symptoms, it is not easy to make causal inferences based on observational studies. We performed a Mendelian randomization (MR) to investigate the association of individual non-vasomotor menopausal symptoms and the risk of CHDs. Methods: A sample of 177,497 British women aged ≥51 years old (average age at menopause) without related cardiovascular diseases from the UK biobank is selected as our study population. Non-vasomotor menopausal symptoms, including anxiety, nervous, insomnia, urinary tract infection, fatigue, and vertigo, were selected as exposures based on the modified Kupperman index. Outcome variable is CHD. Results: In total, 54, 47, 24, 33, 22, and 81 instrumental variables were selected for anxiety, insomnia, fatigue, vertigo, urinary tract infection and nervous respectively. We conducted MR analyses of menopausal symptoms and CHD. Only insomnia symptoms increased the lifetime risk of CHD with OR 1.394 (p = 0.0003). There were no significant causal relationships with CHD and other menopausal symptoms. Insomnia near menopause age (45-50 years) does not increase the risk of CHD. However, postmenopausal (over 51) insomnia increases the risk of CHD. Conclusion: MR analyses support that among non-vasomotor menopausal symptoms, only insomnia symptoms may increase the lifetime risk of CHD. Insomnia at different ages near menopause has differential impacts on CHD risk.

Extracellular Nicotinamide Phosphoribosyltransferase as a Surrogate Marker of Prominent Malignant Potential in Colonic Polyps: A 2-Year Prospective Study.

BACKGROUND/AIMS: The implications of extracellular nicotinamide phosphoribosyltransferase (eNAMPT), a cancer metabokine, in colonic polyps remain uncertain. METHODS: A 2-year prospective cohort study of patients who underwent colonoscopy was conducted. Biochemical parameters and serum eNAMPT levels were analyzed at baseline and every 24 weeks postpolypectomy. NAMPT-associated single-nucleotide polymorphisms (SNPs), including rs61330082, rs2302559, rs10953502, and rs23058539, were assayed. RESULTS: Of 532 patients, 80 (15%) had prominent malignant potential (PMP) in colonic polyps, including villous adenomas (n = 18, 3.3%), adenomas with high-grade dysplasia (n = 33, 6.2%), and adenocarcinomas (n = 29, 5.5%). Baseline associations were as follows: colonic polyp pathology (p < 0.001), total cholesterol (p = 0.019), and neutrophil-to-lymphocyte ratio (p = 0.023) with eNAMPT levels; and age (p < 0.001), polyp size (p < 0.001), and eNAMPT levels (p < 0.001) with polyp pathology. Higher baseline eNAMPT levels were noted in patients harboring polyps with PMP than in patients without PMP (p < 0.001), and baseline eNAMPT levels significantly predicted PMP (cutoff: >4.238 ng/mL, p < 0.001). Proportions of eNAMPT-positive glandular and stromal cells were higher in polyps with PMP than in polyps without PMP (64.55 ± 11.94 vs. 14.82 ± 11.45%, p = 0.025). eNAMPT levels decreased within 48 weeks postpolypectomy (p = 0.01) and remained stable afterward regardless of PMP until 96 weeks postpolypectomy. However, those with PMP had a higher degree of eNAMPT decline within 24 weeks (p = 0.046). All investigated SNPs were in linkage disequilibrium with each other but were not associated with eNAMPT levels. CONCLUSION: With a link to inflammation and lipid metabolism, along with its decreasing trend after polypectomy, serum eNAMPT may serve as a surrogate marker of PMP in colonic polyps. In situ probing of the NAMPT-associated pathway holds promise in attenuating PMP, as much of the eNAMPT likely originates from colonic polyps.

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.

On the use of multifactor dimensionality reduction (MDR) and classification and regression tree (CART) to identify haplotype-haplotype interactions in genetic studies.

Haplotype-based approaches may have greater power than single-locus analyses when the SNPs are in strong linkage disequilibrium with the risk locus. To overcome potential complexities owing to large numbers of haplotypes in genetic studies, we evaluated two data mining approaches, multifactor dimensionality reduction (MDR) and classification and regression tree (CART), with the concept of haplotypes considering their haplotype uncertainty to detect haplotype-haplotype (HH) interactions. In evaluation of performance for detecting HH interactions, MDR had higher power than CART, but MDR gave a slightly higher type I error. Additionally, we performed an HH interaction analysis with a publicly available dataset of Parkinson's disease and confirmed previous findings that the RET proto-oncogene is associated with the disease. In this study, we showed that using HH interaction analysis is possible to assist researchers in gaining more insight into identifying genetic risk factors for complex diseases.

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.

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 HbA1c) 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.

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.

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.

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.

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.