Pharmacometabolomic study of drug response to antihypertensive medications for hypertension marker identification in Han Chinese individuals in Taiwan.

Various groups of antihypertensive drugs targeting different pathways have been developed; however, the pharmacometabolic responses to these drugs have rarely been compared to elucidate the common pathway of blood pressure regulation. Here, we performed a comparative multi-dimensional pharmacometabolic study on the four major lines of antihypertensive drugs, namely angiotensin-converting enzyme inhibitors (ACEis), angiotensin receptor blockers (ARBs), calcium channel blockers (CCBs), and diuretics (DIURs), through ultra-performance liquid chromatography coupled to quantum time-of-flight mass spectrometry. Two hundred fifty patients with young-onset hypertension, who were equally divided among five study groups: non-medicated, ACEi, ARB, CCB, and DIUR groups, were recruited. In a metabolome-wide association study conducted through analysis of covariance, 37 molecular features significantly associated with pharmacometabolic responses to antihypertensive drugs were identified. One-third of these features were shared by multiple medications. ACEis, ARBs, and DIURs shared more features than CCB, partially reflecting that ACEis, ARBs, and DIURs affect the renin-angiotensin-aldosterone system. Thirteen molecular features were consistently identified by all four models of the analysis of covariance. A tandem mass spectrometry (or MS/MS) experiment was performed to decipher the chemical structure of these 13 molecular features, including ARB-associated lysophosphatidylcholine (P4135), CCB-associated diacylglycerol(15:0/18:2) (P1175), and DIUR-associated oleamide (P1516). In addition, diacylglycerol(15:0/14:2) (P408) was significantly associated with the pharmacometabolic response to all four antihypertensive drugs. The identified metabolites provide insights into the mechanisms of blood pressure regulation and potential predictive markers of pharmacometabolic responses to antihypertensive drugs.

Evaluating statistical significance in a meta-analysis by using numerical integration.

Meta-analysis is a method for enhancing statistical power through the integration of information from multiple studies. Various methods for integrating p-values (i.e., statistical significance), including Fisher's method under an independence assumption, the permutation method, and the decorrelation method, have been broadly used in bioinformatics and computational biotechnology studies. However, these methods have limitations related to statistical assumption, computing efficiency, and accuracy of statistical significance estimation. In this study, we proposed a numerical integration method and examined its theoretical properties. Simulation studies were conducted to evaluate its Type I error, statistical power, computational efficiency, and estimation accuracy, and the results were compared with those of other methods. The results demonstrate that our proposed method performs well in terms of Type I error, statistical power, computing efficiency (regardless of sample size), and statistical significance estimation accuracy. P-value data from multiple large-scale genome-wide association studies (GWASs) and transcriptome-wise association studies (TWASs) were analyzed. The results demonstrate that our proposed method can be used to identify critical genomic regions associated with rheumatoid arthritis and asthma, increase statistical significance in individual GWASs and TWASs, and control for false-positives more effectively than can Fisher's method under an independence assumption. We created the software package Pbine, available at GitHub (https://github.com/Yinchun-Lin/Pbine).

PRAP1 is a novel lipid-binding protein that promotes lipid absorption by facilitating MTTP-mediated lipid transport.

Microsomal triglyceride transfer protein (MTTP) is an endoplasmic reticulum resident protein that is essential for the assembly and secretion of triglyceride (TG)-rich, apoB-containing lipoproteins. Although the function and structure of mammalian MTTP have been extensively studied, how exactly MTTP transfers lipids to lipid acceptors and whether there are other biomolecules involved in MTTP-mediated lipid transport remain elusive. Here we identify a role in this process for the poorly characterized protein PRAP1. We report that PRAP1 and MTTP are partially colocalized in the endoplasmic reticulum. We observe that PRAP1 directly binds to TG and facilitates MTTP-mediated lipid transfer. A single amino acid mutation at position 85 (E85V) impairs PRAP1's ability to form a ternary complex with TG and MTTP, as well as impairs its ability to facilitate MTTP-mediated apoB-containing lipoprotein assembly and secretion, suggesting that the ternary complex formation is required for PRAP1 to facilitate MTTP-mediated lipid transport. PRAP1 is detectable in chylomicron/VLDL-rich plasma fractions, suggesting that MTTP recognizes PRAP1-bound TG as a cargo and transfers TG along with PRAP1 to lipid acceptors. Both PRAP1-deficient and E85V knock-in mutant mice fed a chow diet manifested an increase in the length of their small intestines, likely to compensate for challenges in absorbing lipid. Interestingly, both genetically modified mice gained significantly less body weight and fat mass when on high-fat diets compared with littermate controls and were prevented from hepatosteatosis. Together, this study provides evidence that PRAP1 plays an important role in MTTP-mediated lipid transport and lipid absorption.

Integrated omics-based pathway analyses uncover CYP epoxygenase-associated networks as theranostic targets for metastatic triple negative breast cancer.

BACKGROUND: Current prognostic tools and targeted therapeutic approaches have limited value for metastatic triple negative breast cancer (TNBC). Building upon current knowledge, we hypothesized that epoxyeicosatrienoic acids (EETs) and related CYP450 epoxygenases may have differential roles in breast cancer signaling, and better understanding of which may uncover potential directions for molecular stratification and personalized therapy for TNBC patients. METHODS: We analyzed the oxylipin metabolome of paired tumors and adjacent normal mammary tissues from patients with pathologically confirmed breast cancer (N = 62). We used multivariate statistical analysis to identify important metabolite contributors and to determine the predictive power of tumor tissue metabolite clustering. In vitro functional assays using a panel of breast cancer cell lines were carried out to further confirm the crucial roles of endogenous and exogenous EETs in the metastasis transformation of TNBC cells. Deregulation of associated downstream signaling networks associated with EETs/CYPs was established using transcriptomics datasets from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). Comparative TNBC proteomics using the same tissue specimens subjected to oxylipin metabolomics analysis was used as validation set. RESULTS: Metabolite-by-metabolite comparison, tumor immunoreactivity, and gene expression analyses showed that CYP epoxygenases and arachidonic acid-epoxygenation products, EET metabolites, are strongly associated with TNBC metastasis. Notably, all the 4 EET isomers (5,6-, 8,9-, 11,12-, and 14,15-EET) was observed to profoundly drive the metastasis transformation of mesenchymal-like TNBC cells among the TNBC (basal- and mesenchymal-like), HER2-overexpressing and luminal breast cancer cell lines examined. Our pathway analysis revealed that, in hormone-positive breast cancer subtype, CYP epoxygenase overexpression is more related to immune cell-associated signaling, while EET-mediated Myc, Ras, MAPK, EGFR, HIF-1α, and NOD1/2 signaling are the molecular vulnerabilities of metastatic CYP epoxygenase-overexpressing TNBC tumors. CONCLUSIONS: This study suggests that categorizing breast tumors according to their EET metabolite ratio classifiers and CYP epoxygenase profiles may be useful for prognostic and therapeutic assessment. Modulation of CYP epoxygenase and EET-mediated signaling networks may offer an effective approach for personalized treatment of breast cancer, and may be an effective intervention option for metastatic TNBC patients.

Alkylphenol ethoxylate metabolites in coastal sediments off southwestern Taiwan: Spatiotemporal variations, possible sources, and ecological risk.

Alkylphenol ethoxylates (APEOs) are one of the most widely used classes of surfactants, but they are also ubiquitous environmental pollutants and known endocrin-disrupting chemicals. This study is the first to investigate the spatiotemporal variations and possible sources of APEOs and their metabolites, including nonylphenol ethoxylates (NPEOs) and octylphenol ethoxylates (OPEOs), in coastal sediments off southwestern Taiwan. The highest APEO concentration in the dry season was observed for the Kaohsiung coastal area, whereas the highest alkylphenol (AP) concentration in the wet season was found offshore at the Tainan Canal exit. No continuous accumulation of alkylphenol metabolites was evident in the area. One possible reason is that seasonal current and wind waves disperse the coastal pollutants. Application of multivariate statistical tools (hierarchical cluster analysis and principal component analysis) confirmed the role of rivers and the Tainan Canal in transporting contaminants to coastal environments, suggesting influences of industrial and human activities on APEO distribution. A further comparison with the predicted no-effect concentrations (PNECs) proposed by the European Union indicates that nonylphenol (NP) and octylphenol (OP) might pose potential ecological risks to the aquatic environment in the studied area. These findings provide useful information for environmental policy implementation and ecological assessments of different types of endocrine-disrupting chemicals and raise warnings about surfactant applications.

Vegetable Signatures Derived from Human Urinary Metabolomic Data in Controlled Feeding Studies.

Examination of changes in urinary metabolomic profiles after vegetable ingestion may lead to new methods of assessing plant food intake. To this regard, we developed a proof-of-principle methodology to identify urinary metabolomic signatures for spinach, celery, and onion. Three feeding studies were conducted. In the first study, healthy individuals were fed with spinach, celery, onion, and no vegetables in four separate experiments with pooled urinary samples for metabolite discovery. The same protocol was used to validate the finding at the individual level in the second study and when feeding all three vegetables simultaneously in the third study. An LC-MS-based metabolomics approach was adopted to search for indicative metabolites from urine samples collected during multiple time periods before and after the meal. Consequently, a total of 1, 9, and 3 nonoverlapping urinary metabolites were associated with the intake of spinach, celery, and onion, respectively. The PCA signature of these metabolites followed a similar "time cycle" pattern, which maximized at approximately 2-4 h after intake. In addition, the metabolite profiles for the same vegetable were consistent across samples, regardless of whether it was consumed individually or in combination. The developed methodology along with the identified urinary metabolomic signatures were potential tools for assessing plant food intake.

Postprandial Metabolomics Response to Various Cooking Oils in Humans.

Lipids account for a high proportion of dietary calories, which greatly affect human health. As a result of differences in composition of fatty acid of individual cooking oils, certain biological effects of these oils may vary. This study aimed to compare postprandial metabolomic profiles of six commonly consumed cooking oils/fats. Adopting a switch-over experimental design ( n = 15), we carried out a human feeding study with six groups (control without oils, soybean oil, olive oil, palm oil, camellia oil, and tallow) and collected fasting and postprandial serum samples. The metabolomic profile was measured by ultra-high-pressure liquid chromatography-quadrupole time of flight. We observed significant differences between the control group and experimental groups for 33 serum metabolites (false discovery rate; p < 0.05), which take part in lipid digestion, fatty acid metabolism, metabolism of pyrimidines and pyrimidine nucleosides, amino acid metabolism, neurobiology, and antioxidation. Sparse partial least squares discriminant analysis revealed distinct metabolomics patterns between monounsaturated fatty acid (MUFA) and saturated fatty acid oils, between soybean oil, olive oil, and palm oil, and between two MUFA-rich oils (olive and camellia oils). The present metabolomics study suggests shared and distinct metabolisms of various cooking oils/fats.

SMART: Statistical Metabolomics Analysis-An R Tool.

Metabolomics data provide unprecedented opportunities to decipher metabolic mechanisms by analyzing hundreds to thousands of metabolites. Data quality concerns and complex batch effects in metabolomics must be appropriately addressed through statistical analysis. This study developed an integrated analysis tool for metabolomics studies to streamline the complete analysis flow from initial data preprocessing to downstream association analysis. We developed Statistical Metabolomics Analysis-An R Tool (SMART), which can analyze input files with different formats, visually represent various types of data features, implement peak alignment and annotation, conduct quality control for samples and peaks, explore batch effects, and perform association analysis. A pharmacometabolomics study of antihypertensive medication was conducted and data were analyzed using SMART. Neuromedin N was identified as a metabolite significantly associated with angiotensin-converting-enzyme inhibitors in our metabolome-wide association analysis (p = 1.56 × 10(-4) in an analysis of covariance (ANCOVA) with an adjustment for unknown latent groups and p = 1.02 × 10(-4) in an ANCOVA with an adjustment for hidden substructures). This endogenous neuropeptide is highly related to neurotensin and neuromedin U, which are involved in blood pressure regulation and smooth muscle contraction. The SMART software, a user guide, and example data can be downloaded from http://www.stat.sinica.edu.tw/hsinchou/metabolomics/SMART.htm .

Impacts of emerging contaminants on surrounding aquatic environment from a youth festival.

The youth festival as we refer to Spring Scream, a large-scale pop music festival, is notorious for the problems of drug abuse and addiction. The origin, temporal magnitudes, potential risks and mass inputs of emerging contaminants (ECs) were investigated. Thirty targeted ECs were analyzed by solid-phase extraction and liquid chromatography coupled to tandem mass spectrometry (SPE-LC-MS/MS). Sampling strategy was designed to characterize EC behavior in different stages (before and after the youth festival), based on multivariate data analysis to explore the contributions of contaminants from normal condition to the youth festival. Wastewater influents and effluents were collected during the youth festival (approximately 600 000 pop music fans and youth participated). Surrounding river waters are also sampled to illustrate the touristic impacts during peak season and off-season. Seasonal variations were observed, with the highest concentrations in April (Spring Scream) and the lowest in October (off-season). Acetaminophen, diclofenac, codeine, ampicillin, tetracycline, erythromycin-H2O, and gemfibrozil have significant pollution risk quotients (RQs > 1), indicating ecotoxicological concerns. Principal component analysis (PCA) and weekly patterns provide a perspective in assessing the touristic impacts and address the dramatic changes in visitor population and drug consumption. The highest mass loads discharged into the aquatic ecosystem corresponded to illicit drugs/controlled substances such as ketamine and MDMA, indicating the high consumption of ecstasy during Spring Scream.

A three-stage genome-wide association study combining multilocus test and gene expression analysis for young-onset hypertension in Taiwan Han Chinese.

BACKGROUND: Although many large-scale genome-wide association studies (GWASs) have been performed, only a few studies have successfully identified replicable, large-impact hypertension loci; even fewer studies have been done on Chinese subjects. Young-onset hypertension (YOH) is considered to be a more promising target disorder to investigate than late-onset hypertension because of its stronger genetic component. METHODS: To map YOH genetic variants, we performed a 3-stage study combining 1st-stage multilocus GWASs, 2nd-stage gene expression analysis, and 3rd-stage multilocus confirmatory study. RESULTS: In the 1st stage, Illumina550K data from 400 case-control pairs were used, and 22 genes flanked by 14 single nucleotide polymorphism (SNP) septets (P values adjusted for false discovery rate (pFDR) < 3.16×10(-7)) were identified. In the 2nd stage, differential gene expression analysis was carried out for these genes, and 5 genes were selected (pFDR < 0.05). In the 3rd stage, we re-examined the finding with an independent set of 592 case-control pairs and with the joint samples (n = 992 case-control pairs). A total of 6 SNP septets flanking C1orf135, GSN, LARS, and ACTN4 remained significant in all 3 stages. Among them, the same septet flanking ACTN4 was also associated with blood pressure traits in the Hong Kong Hypertension Study (HKHS) and in the Wellcome Trust Case-Control Consortium Hypertension Study (WTCCCHS). LARS was detected in the HKHS, but not in the WTCCCHS. GSN may be specific to Taiwanese individuals because it was not found by either the HKHS or the WTCCCHS. CONCLUSIONS: Our study identified 4 previously unknown YOH loci in Han Chinese. Identification of these genes enriches the hypertension susceptibility gene list, thereby shedding light on the etiology of hypertension in Han Chinese.

Identification of IGF1, SLC4A4, WWOX, and SFMBT1 as hypertension susceptibility genes in Han Chinese with a genome-wide gene-based association study.

Hypertension is a complex disorder with high prevalence rates all over the world. We conducted the first genome-wide gene-based association scan for hypertension in a Han Chinese population. By analyzing genome-wide single-nucleotide-polymorphism data of 400 matched pairs of young-onset hypertensive patients and normotensive controls genotyped with the Illumina HumanHap550-Duo BeadChip, 100 susceptibility genes for hypertension were identified and also validated with permutation tests. Seventeen of the 100 genes exhibited differential allelic and expression distributions between patient and control groups. These genes provided a good molecular signature for classifying hypertensive patients and normotensive controls. Among the 17 genes, IGF1, SLC4A4, WWOX, and SFMBT1 were not only identified by our gene-based association scan and gene expression analysis but were also replicated by a gene-based association analysis of the Hong Kong Hypertension Study. Moreover, cis-acting expression quantitative trait loci associated with the differentially expressed genes were found and linked to hypertension. IGF1, which encodes insulin-like growth factor 1, is associated with cardiovascular disorders, metabolic syndrome, decreased body weight/size, and changes of insulin levels in mice. SLC4A4, which encodes the electrogenic sodium bicarbonate cotransporter 1, is associated with decreased body weight/size and abnormal ion homeostasis in mice. WWOX, which encodes the WW domain-containing protein, is related to hypoglycemia and hyperphosphatemia. SFMBT1, which encodes the scm-like with four MBT domains protein 1, is a novel hypertension gene. GRB14, TMEM56 and KIAA1797 exhibited highly significant differential allelic and expressed distributions between hypertensive patients and normotensive controls. GRB14 was also found relevant to blood pressure in a previous genetic association study in East Asian populations. TMEM56 and KIAA1797 may be specific to Taiwanese populations, because they were not validated by the two replication studies. Identification of these genes enriches the collection of hypertension susceptibility genes, thereby shedding light on the etiology of hypertension in Han Chinese populations.

A genome-wide homozygosity association study identifies runs of homozygosity associated with rheumatoid arthritis in the human major histocompatibility complex.

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with a polygenic mode of inheritance. This study examined the hypothesis that runs of homozygosity (ROHs) play a recessive-acting role in the underlying RA genetic mechanism and identified RA-associated ROHs. Ours is the first genome-wide homozygosity association study for RA and characterized the ROH patterns associated with RA in the genomes of 2,000 RA patients and 3,000 normal controls of the Wellcome Trust Case Control Consortium. Genome scans consistently pinpointed two regions within the human major histocompatibility complex region containing RA-associated ROHs. The first region is from 32,451,664 bp to 32,846,093 bp (-log10(p)>22.6591). RA-susceptibility genes, such as HLA-DRB1, are contained in this region. The second region ranges from 32,933,485 bp to 33,585,118 bp (-log10(p)>8.3644) and contains other HLA-DPA1 and HLA-DPB1 genes. These two regions are physically close but are located in different blocks of linkage disequilibrium, and ∼40% of the RA patients' genomes carry these ROHs in the two regions. By analyzing homozygote intensities, an ROH that is anchored by the single nucleotide polymorphism rs2027852 and flanked by HLA-DRB6 and HLA-DRB1 was found associated with increased risk for RA. The presence of this risky ROH provides a 62% accuracy to predict RA disease status. An independent genomic dataset from 868 RA patients and 1,194 control subjects of the North American Rheumatoid Arthritis Consortium successfully validated the results obtained using the Wellcome Trust Case Control Consortium data. In conclusion, this genome-wide homozygosity association study provides an alternative to allelic association mapping for the identification of recessive variants responsible for RA. The identified RA-associated ROHs uncover recessive components and missing heritability associated with RA and other autoimmune diseases.

Genome-wide gene-based association study.

Genome-wide association studies, which analyzes hundreds of thousands of single-nucleotide polymorphisms to identify disease susceptibility genes, are challenging because the work involves intensive computation and complex modeling. We propose a two-stage genome-wide association scanning procedure, consisting of a single-locus association scan for the first stage and a gene-based association scan for the second stage. Marginal effects of single-nucleotide polymorphisms are examined by using the exact Armitage trend test or logistic regression, and gene effects are examined by using a p-value combination method. Compared with some existing single-locus and multilocus methods, the proposed method has the following merits: 1) convenient for definition of biologically meaningful regions, 2) powerful for detection of minor-effect genes, 3) helpful for alleviation of a multiple-testing problem, and 4) convenient for result interpretation. The method was applied to study Genetic Analysis Workshop 16 Problem 1 rheumatoid arthritis data, and strong association signals were found. The results show that the human major histocompatibility complex region is the most important genomic region associated with rheumatoid arthritis. Moreover, previously reported genes including PTPN22, C5, and IL2RB were confirmed; novel genes including HLA-DRA, BTNL2, C6orf10, NOTCH4, TAP2, and TNXB were identified by our analysis.

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.

Construction of endophenotypes for complex diseases in the presence of heterogeneity.

Endophenotypes such as behavior disorders have been increasingly adopted in genetic studies for complex traits. For efficient gene mapping, it is essential that an endophenotype is associated with the disease of interest and is inheritable or co-segregating within families. In this study, we proposed a strategy to construct endophenotypes to analyze the Genetic Analysis Workshop 14 simulated dataset. Initially, generalized estimating equation models were employed to identify phenotypes that were correlated to the disease (affected status) in combination with the family structures in data. Endophenotypes were then constructed with consideration of heterogeneity as functions of the identified phenotypes. Genome scans on the constructed endophenotypes were carried out using family-based association analysis. For comparison, genome scans were also performed with the original affected status. The family-based association analysis using the endophenotypes correctly identified the same susceptible gene in about 80 of the 100 replicates.