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Liang, Liming

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Liming

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Liang, Liming
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Now showing 1 - 10 of 47
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    An Epigenome-Wide Association Study of Total Serum Immunoglobulin E Concentration
    (2014) Liang, Liming; Willis-Owen, Saffron A.G.; Laprise, Catherine; Wong, Kenny C.C.; Davies, Gwyneth A.; Hudson, Thomas J.; Binia, Aristea; Hopkin, Julian M.; Yang, Ivana V.; Grundberg, Elin; Busche, Stephan; Hudson, Marie; Rönnblom, Lars; Pastinen, Tomi M.; Schwartz, David A.; Lathrop, G. Mark; Moffatt, Miriam F.; Cookson, William O.C.M.
    Immunoglobulin E (IgE) is a central mediator of allergic (atopic) inflammation. Therapies directed against IgE benefit hay fever1 and allergic asthma1,2. Genetic association studies have not yet identified novel therapeutic targets or pathways underlying IgE regulation3-6. We therefore surveyed epigenetic association between serum IgE concentrations and methylation at loci concentrated in CpG islands (CGI) genome-wide in 95 nuclear pedigrees, using DNA from peripheral blood leukocytes (PBL). We validated positive results in additional families and in subjects from the general population. We show here replicated associations with a meta-analysis false discovery rate <10−4 between IgE and low methylation at 36 loci. Genes annotated to these loci encode known eosinophil products, and also implicate phospholipid inflammatory mediators, specific transcription factors, and mitochondrial proteins. We confirmed that methylation at these loci differed significantly in isolated eosinophils from subjects with and without high IgE levels. The top three loci accounted for 13% of IgE variation in the primary subject panel, explaining 10 fold higher variance than that derived from large SNP GWAS3,4. The study identifies novel therapeutic targets and biomarkers for patient stratification for allergic diseases.
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    Expression Quantitative Trait Loci Information Improves Predictive Modeling of Disease Relevance of Non-Coding Genetic Variation
    (Public Library of Science, 2015) Croteau-Chonka, Damien; Rogers, Angela J.; Raj, Towfique; McGeachie, Michael; Qiu, Weiliang; Ziniti, John P.; Stubbs, Benjamin J.; Liang, Liming; Martinez, Fernando D.; Strunk, Robert C.; Lemanske, Robert F.; Liu, Andrew H.; Stranger, Barbara E.; Carey, Vincent; Raby, Benjamin
    Disease-associated loci identified through genome-wide association studies (GWAS) frequently localize to non-coding sequence. We and others have demonstrated strong enrichment of such single nucleotide polymorphisms (SNPs) for expression quantitative trait loci (eQTLs), supporting an important role for regulatory genetic variation in complex disease pathogenesis. Herein we describe our initial efforts to develop a predictive model of disease-associated variants leveraging eQTL information. We first catalogued cis-acting eQTLs (SNPs within 100kb of target gene transcripts) by meta-analyzing four studies of three blood-derived tissues (n = 586). At a false discovery rate < 5%, we mapped eQTLs for 6,535 genes; these were enriched for disease-associated genes (P < 10−04), particularly those related to immune diseases and metabolic traits. Based on eQTL information and other variant annotations (distance from target gene transcript, minor allele frequency, and chromatin state), we created multivariate logistic regression models to predict SNP membership in reported GWAS. The complete model revealed independent contributions of specific annotations as strong predictors, including evidence for an eQTL (odds ratio (OR) = 1.2–2.0, P < 10−11) and the chromatin states of active promoters, different classes of strong or weak enhancers, or transcriptionally active regions (OR = 1.5–2.3, P < 10−11). This complete prediction model including eQTL association information ultimately allowed for better discrimination of SNPs with higher probabilities of GWAS membership (6.3–10.0%, compared to 3.5% for a random SNP) than the other two models excluding eQTL information. This eQTL-based prediction model of disease relevance can help systematically prioritize non-coding GWAS SNPs for further functional characterization.
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    Height, height-related SNPs, and risk of non-melanoma skin cancer
    (Nature Publishing Group, 2016) Li, Xin; Liang, Liming; Feng, Yen-Chen Anne; De Vivo, Immaculata; Giovannucci, Edward; Tang, Jean Y; Han, Jiali
    Background: Adult height has been associated with risk of several site-specific cancers, including melanoma. However, less attention has been given to non-melanoma skin cancer (NMSC). Methods: We prospectively examined the risk of squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) in relation to adult height in the Nurses' Health Study (NHS, n=117 863) and the Health Professionals Follow-up Study (HPFS, n=51 111). We also investigated the relationships between height-related genetic markers and risk of BCC and SCC in the genetic data sets of the NHS and HPFS (3898 BCC cases, and 8530 BCC controls; 527 SCC cases, and 8962 SCC controls). Results: After controlling for potential confounding factors, the hazard ratios were 1.09 (95% CI: 1.02, 1.15) and 1.10 (95% CI: 1.07, 1.13) for the associations between every 10 cm increase in height and risk of SCC and BCC respectively. None of the 687 height-related single-nucleotide polymorphisms (SNPs) was significantly associated with the risk of SCC or BCC, nor were the genetic scores combining independent height-related loci. Conclusions: Our data from two large cohorts provide further evidence that height is associated with an increased risk of NMSC. More studies on height-related genetic loci and early-life exposures may help clarify the underlying mechanisms.
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    A genome-wide cross-trait analysis from UK Biobank highlights the shared genetic architecture of asthma and allergic diseases
    (Springer Science and Business Media LLC, 2018-05-21) Zhu, Zhaozhong; Lee, Phil; Chaffin, Mark; Chung, Wonil; Loh, Po-Ru; Lu, Quan; Christiani, David; Liang, Liming
    Clinical and epidemiological data suggest that asthma and allergic diseases are associated and may share a common genetic etiology. We analyzed genome-wide SNP data for asthma and allergic diseases in 33,593 cases and 76,768 controls of European ancestry from UK Biobank. Two publicly available independent genome-wide association studies were used for replication. We have found a strong genome-wide genetic correlation between asthma and allergic diseases (rg = 0.75, P = 6.84 × 10−62). Cross-trait analysis identified 38 genome-wide significant loci, including 7 novel shared loci. Computational analysis showed that shared genetic loci are enriched in immune/inflammatory systems and tissues with epithelium cells. Our work identifies common genetic architectures shared between asthma and allergy and will help to advance understanding of the molecular mechanisms underlying co-morbid asthma and allergic diseases.
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    Whole blood microRNA markers are associated with acute respiratory distress syndrome
    (Springer International Publishing, 2017) Zhu, Zhaozhong; Liang, Liming; Zhang, Ruyang; Wei, Yongyue; Su, Li; Tejera, Paula; Guo, Yichen; Wang, Zhaoxi; Lu, Quan; Baccarelli, Andrea; Zhu, Xi; Bajwa, Ednan; Taylor Thompson, B.; Shi, Guo-Ping; Christiani, David
    Background: MicroRNAs (miRNAs) can play important roles in inflammation and infection, which are common manifestations of acute respiratory distress syndrome (ARDS). We assessed if whole blood miRNAs were potential diagnostic biomarkers for human ARDS. Methods: This nested case-control study (N = 530) examined a cohort of ARDS patients and critically ill at-risk controls. Whole blood miRNA profiles and logistic regression analyses identified miRNAs correlated with ARDS. Stratification analysis also assessed selected miRNA markers for their role in sepsis and pneumonia associated with ARDS. Receiver operating characteristic (ROC) analysis evaluated miRNA diagnostic performance, along with Lung Injury Prediction Score (LIPS). Results: Statistical analyses were performed on 294 miRNAs, selected from 754 miRNAs after quality control screening. Logistic regression identified 22 miRNAs from a 156-patient discovery cohort as potential risk or protective markers of ARDS. Three miRNAs—miR-181a, miR-92a, and miR-424—from the discovery cohort remained significantly associated with ARDS in a 373-patient independent validation cohort (FDR q < 0.05) and meta-analysis (p < 0.001). ROC analyses demonstrated a LIPS baseline area-under-the-curve (AUC) value of ARDS of 0.708 (95% CI 0.651–0.766). Addition of miR-181a, miR-92a, and miR-424 to LIPS increased baseline AUC to 0.723 (95% CI 0.667–0.778), with a relative integrated discrimination improvement of 2.40 (p = 0.005) and a category-free net reclassification index of 27.21% (p = 0.01). Conclusions: miR-181a and miR-92a are risk biomarkers for ARDS, whereas miR-424 is a protective biomarker. Addition of these miRNAs to LIPS can improve the risk estimate for ARDS. Electronic supplementary material The online version of this article (10.1186/s40635-017-0155-0) contains supplementary material, which is available to authorized users.
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    Multiancestry association study identifies new asthma risk loci that colocalize with immune cell enhancer marks
    (2018) Demenais, Florence; Margaritte-Jeannin, Patricia; Barnes, Kathleen C; Cookson, William OC; Altmüller, Janine; Ang, Wei; Barr, R Graham; Beaty, Terri H; Becker, Allan B; Beilby, John; Bisgaard, Hans; Bjornsdottir, Unnur Steina; Bleecker, Eugene; Bønnelykke, Klaus; Boomsma, Dorret I; Bouzigon, Emmanuelle; Brightling, Christopher E; Brossard, Myriam; Brusselle, Guy G; Burchard, Esteban; Burkart, Kristin M; Bush, Andrew; Chan-Yeung, Moira; Chung, Kian Fan; Alves, Alexessander Couto; Curtin, John A; Custovic, Adnan; Daley, Denise; de Jongste, Johan C; Del-Rio-Navarro, Blanca E; Donohue, Kathleen M; Duijts, Liesbeth; Eng, Celeste; Eriksson, Johan G; Farrall, Martin; Fedorova, Yuliya; Feenstra, Bjarke; Ferreira, Manuel A; Freidin, Maxim B; Gajdos, Zofia; Gauderman, Jim; Gehring, Ulrike; Geller, Frank; Genuneit, Jon; Gharib, Sina A; Gilliland, Frank; Granell, Raquel; Graves, Penelope E; Gudbjartsson, Daniel F; Haahtela, Tari; Heckbert, Susan R; Heederik, Dick; Heinrich, Joachim; Heliövaara, Markku; Henderson, John; Himes, Blanca E; Hirose, Hiroshi; Hirschhorn, Joel; Hofman, Albert; Holt, Patrick; Hottenga, Jouke Jan; Hudson, Thomas J; Hui, Jennie; Imboden, Medea; Ivanov, Vladimir; Jaddoe, Vincent WV; James, Alan; Janson, Christer; Jarvelin, Marjo-Riitta; Jarvis, Deborah; Jones, Graham; Jonsdottir, Ingileif; Jousilahti, Pekka; Kabesch, Michael; Kähönen, Mika; Kantor, David; Karunas, Alexandra S; Khusnutdinova, Elza; Koppelman, Gerard H; Kozyrskyj, Anita L; Kreiner, Eskil; Kubo, Michiaki; Kumar, Rajesh; Kumar, Ashish; Kuokkanen, Mikko; Lahousse, Lies; Laitinen, Tarja; Laprise, Catherine; Lathrop, Mark; Lau, Susanne; Lee, Young-Ae; Lehtimäki, Terho; Letort, Sébastien; Levin, Albert M; Li, Guo; Liang, Liming; Loehr, Laura R; London, Stephanie J; Loth, Daan W; Manichaikul, Ani; Marenholz, Ingo; Martinez, Fernando J; Matheson, Melanie C; Mathias, Rasika A; Matsumoto, Kenji; Mbarek, Hamdi; McArdle, Wendy L; Melbye, Mads; Melén, Erik; Meyers, Deborah; Michel, Sven; Mohamdi, Hamida; Musk, Arthur W; Myers, Rachel A; Nieuwenhuis, Maartje AE; Noguchi, Emiko; O'Connor, George T; Ogorodova, Ludmila M; Palmer, Cameron D; Palotie, Aarno; Park, Julie E; Pennell, Craig E; Pershagen, Göran; Polonikov, Alexey; Postma, Dirkje S; Probst-Hensch, Nicole; Puzyrev, Valery P; Raby, Benjamin; Raitakari, Olli T; Ramasamy, Adaikalavan; Rich, Stephen S; Robertson, Colin F; Romieu, Isabelle; Salam, Muhammad T; Salomaa, Veikko; Schlünssen, Vivi; Scott, Robert; Selivanova, Polina A; Sigsgaard, Torben; Simpson, Angela; Siroux, Valérie; Smith, Lewis J; Solodilova, Maria; Standl, Marie; Stefansson, Kari; Strachan, David P; Stricker, Bruno H; Takahashi, Atsushi; Thompson, Philip J; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Tiesler, Carla MT; Torgerson, Dara G; Tsunoda, Tatsuhiko; Uitterlinden, André G; van der Valk, Ralf JP; Vaysse, Amaury; Vedantam, Sailaja; Von Berg, Andrea; Von Mutius, Erika; Vonk, Judith M; Waage, Johannes; Wareham, Nick J; Weiss, Scott; White, Wendy B; Wickman, Magnus; Widén, Elisabeth; Willemsen, Gonneke; Williams, L Keoki; Wouters, Inge M; Yang, James J; Zhao, Jing Hua; Moffatt, Miriam F; Ober, Carole; Nicolae, Dan L
    We examined common variation in asthma risk by conducting a meta-analysis of worldwide asthma genome-wide association studies (23,948 cases, 118,538 controls) from ethnically-diverse populations. We identified five new asthma loci, uncovered two additional novel associations at two known asthma loci, established asthma associations at two loci implicated previously in comorbidity of asthma plus hay fever, and confirmed nine known loci. Investigation of pleiotropy showed large overlaps in genetic variants with autoimmune and inflammatory diseases. Enrichment of asthma risk loci in enhancer marks, especially in immune cells, suggests a major role of these loci in the regulation of immune-related mechanisms.
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    Perfluoroalkyl substances and changes in body weight and resting metabolic rate in response to weight-loss diets: A prospective study
    (Public Library of Science, 2018) Liu, Gang; Dhana, Klodian; Furtado, Jeremy; Rood, Jennifer; Zong, Geng; Liang, Liming; Qi, Lu; Bray, George A.; DeJonge, Lilian; Coull, Brent; Grandjean, Philippe; Sun, Qi
    Background: The potential endocrine-disrupting effects of perfluoroalkyl substances (PFASs) have been demonstrated in animal studies, but whether PFASs may interfere with body weight regulation in humans is largely unknown. This study aimed to examine the associations of PFAS exposure with changes in body weight and resting metabolic rate (RMR) in a diet-induced weight-loss setting. Methods and findings In the 2-year POUNDS Lost randomized clinical trial based in Boston, Massachusetts, and Baton Rouge, Louisiana, that examined the effects of energy-restricted diets on weight changes, baseline plasma concentrations of major PFASs were measured among 621 overweight and obese participants aged 30–70 years. Body weight was measured at baseline and 6, 12, 18, and 24 months. RMR and other metabolic parameters, including glucose, lipids, thyroid hormones, and leptin, were measured at baseline and 6 and 24 months. Participants lost an average of 6.4 kg of body weight during the first 6 months (weight-loss period) and subsequently regained an average of 2.7 kg of body weight during the period of 6–24 months (weight regain period). After multivariate adjustment, baseline PFAS concentrations were not significantly associated with concurrent body weight or weight loss during the first 6 months. In contrast, higher baseline levels of PFASs were significantly associated with a greater weight regain, primarily in women. In women, comparing the highest to the lowest tertiles of PFAS concentrations, the multivariate-adjusted mean weight regain (SE) was 4.0 (0.8) versus 2.1 (0.9) kg for perfluorooctanesulfonic acid (PFOS) (Ptrend = 0.01); 4.3 (0.9) versus 2.2 (0.8) kg for perfluorooctanoic acid (PFOA) (Ptrend = 0.007); 4.7 (0.9) versus 2.5 (0.9) kg for perfluorononanoic acid (PFNA) (Ptrend = 0.006); 4.9 (0.9) versus 2.7 (0.8) kg for perfluorohexanesulfonic acid (PFHxS) (Ptrend = 0.009); and 4.2 (0.8) versus 2.5 (0.9) kg for perfluorodecanoic acid (PFDA) (Ptrend = 0.03). When further adjusted for changes in body weight or thyroid hormones during the first 6 months, results remained similar. Moreover, higher baseline plasma PFAS concentrations, especially for PFOS and PFNA, were significantly associated with greater decline in RMR during the weight-loss period and less increase in RMR during the weight regain period in both men and women. Limitations of the study include the possibility of unmeasured or residual confounding by socioeconomic and psychosocial factors, as well as possible relapse to the usual diet prior to randomization, which could have been rich in foods contaminated by PFASs through food packaging and also dense in energy. Conclusions: In this diet-induced weight-loss trial, higher baseline plasma PFAS concentrations were associated with a greater weight regain, especially in women, possibly explained by a slower regression of RMR levels. These data illustrate a potential novel pathway through which PFASs interfere with human body weight regulation and metabolism. The possible impact of environmental chemicals on the obesity epidemic therefore deserves attention. Trial registration ClinicalTrials.gov NCT00072995
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    Comprehensive Metabolomic Profiling and Incident Cardiovascular Disease: A Systematic Review
    (John Wiley and Sons Inc., 2017) Ruiz‐Canela, Miguel; Hruby, Adela; Clish, Clary B.; Liang, Liming; Martínez‐González, Miguel A.; Hu, Frank
    Background: Metabolomics is a promising tool of cardiovascular biomarker discovery. We systematically reviewed the literature on comprehensive metabolomic profiling in association with incident cardiovascular disease (CVD). Methods and Results: We searched MEDLINE and EMBASE from inception to January 2016. Studies were eligible if they pertained to adult humans; followed an agnostic and/or comprehensive approach; used serum or plasma (not urine or other biospecimens); conducted metabolite profiling at baseline in the context of examining prospective disease; and included myocardial infarction, stroke, and/or CVD death in the CVD outcome definition. We identified 12 original articles (9 cohort and 3 nested case‐control studies); participant numbers ranged from 67 to 7256. Mass spectrometry was the predominant analytical method. The number and chemical diversity of metabolites were very heterogeneous, ranging from 31 to >10 000 features. Four studies used untargeted profiling. Different types of metabolites were associated with CVD risk: acylcarnitines, dicarboxylacylcarnitines, and several amino acids and lipid classes. Only tiny improvements in CVD prediction beyond traditional risk factors were observed using these metabolites (C index improvement ranged from 0.006 to 0.05). Conclusions: There are a limited number of longitudinal studies assessing associations between comprehensive metabolomic profiles and CVD risk. Quantitatively synthesizing the literature is challenging because of the widely varying analytical tools and the diversity of methodological and statistical approaches. Although some results are promising, more research is needed, notably standardization of metabolomic techniques and statistical approaches. Replication and combinations of novel and holistic methodological approaches would move the field toward the realization of its promise.
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    Plasma Metabolites From Choline Pathway and Risk of Cardiovascular Disease in the PREDIMED (Prevention With Mediterranean Diet) Study
    (John Wiley and Sons Inc., 2017) Guasch‐Ferré, Marta; Hu, Frank; Ruiz‐Canela, Miguel; Bulló, Mònica; Toledo, Estefanía; Wang, Dong; Corella, Dolores; Gómez‐Gracia, Enrique; Fiol, Miquel; Estruch, Ramon; Lapetra, José; Fitó, Montserrat; Arós, Fernando; Serra‐Majem, Lluís; Ros, Emilio; Dennis, Courtney; Liang, Liming; Clish, Clary B.; Martínez‐González, Miguel A.; Salas‐Salvadó, Jordi
    Background: The relationship between plasma concentrations of betaine and choline metabolism and major cardiovascular disease (CVD) end points remains unclear. We have evaluated the association between metabolites from the choline pathway and risk of incident CVD and the potential modifying effect of Mediterranean diet interventions. Methods and Results: We designed a case‐cohort study nested within the PREDIMED (Prevention With Mediterranean Diet) trial, including 229 incident CVD cases and 751 randomly selected participants at baseline, followed up for 4.8 years. We used liquid chromatography–tandem mass spectrometry to measure, at baseline and at 1 year of follow‐up, plasma concentrations of 5 metabolites in the choline pathway: trimethylamine N‐oxide, betaine, choline, phosphocholine, and α‐glycerophosphocholine. We have calculated a choline metabolite score using a weighted sum of these 5 metabolites. We used weighted Cox regression models to estimate CVD risk. The multivariable hazard ratios (95% confidence intervals) per 1‐SD increase in choline and α‐glycerophosphocholine metabolites were 1.24 (1.05–1.46) and 1.24 (1.03–1.50), respectively. The baseline betaine/choline ratio was inversely associated with CVD. The baseline choline metabolite score was associated with a 2.21‐fold higher risk of CVD across extreme quartiles (95% confidence interval, 1.36–3.59; P<0.001 for trend) and a 2.27‐fold higher risk of stroke (95% confidence interval, 1.24–4.16; P<0.001 for trend). Participants in the higher quartiles of the score who were randomly assigned to the control group had a higher risk of CVD compared with participants in the lower quartile and assigned to the Mediterranean diet groups (P=0.05 for interaction). No significant associations were observed for 1‐year changes in individual plasma metabolites and CVD. Conclusions: A metabolite score combining plasma metabolites from the choline pathway was associated with an increased risk of CVD in a Mediterranean population at high cardiovascular risk. Clinical Trial Registration URL: http://www.controlled-trials.com. Unique identifier: ISRCTN35739639.
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    Performance of Polygenic Scores for Predicting Phobic Anxiety
    (Public Library of Science, 2013) Walter, Stefan; Glymour, M. Maria; Koenen, Karestan; Liang, Liming; Tchetgen Tchetgen, Eric; Cornelis, Marilyn; Chang, Shun-Chiao; Rimm, Eric; Kawachi, Ichiro; Kubzansky, Laura
    Context Anxiety disorders are common, with a lifetime prevalence of 20% in the U.S., and are responsible for substantial burdens of disability, missed work days and health care utilization. To date, no causal genetic variants have been identified for anxiety, anxiety disorders, or related traits. Objective: To investigate whether a phobic anxiety symptom score was associated with 3 alternative polygenic risk scores, derived from external genome-wide association studies of anxiety, an internally estimated agnostic polygenic score, or previously identified candidate genes. Design: Longitudinal follow-up study. Using linear and logistic regression we investigated whether phobic anxiety was associated with polygenic risk scores derived from internal, leave-one out genome-wide association studies, from 31 candidate genes, and from out-of-sample genome-wide association weights previously shown to predict depression and anxiety in another cohort. Setting and Participants: Study participants (n = 11,127) were individuals from the Nurses' Health Study and Health Professionals Follow-up Study. Main Outcome Measure: Anxiety symptoms were assessed via the 8-item phobic anxiety scale of the Crown Crisp Index at two time points, from which a continuous phenotype score was derived. Results: We found no genome-wide significant associations with phobic anxiety. Phobic anxiety was also not associated with a polygenic risk score derived from the genome-wide association study beta weights using liberal p-value thresholds; with a previously published genome-wide polygenic score; or with a candidate gene risk score based on 31 genes previously hypothesized to predict anxiety. Conclusion: There is a substantial gap between twin-study heritability estimates of anxiety disorders ranging between 20–40% and heritability explained by genome-wide association results. New approaches such as improved genome imputations, application of gene expression and biological pathways information, and incorporating social or environmental modifiers of genetic risks may be necessary to identify significant genetic predictors of anxiety.