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author:("Guo, xiuning")
1.  A prevalent caveolin-1 gene variant is associated with the metabolic syndrome in Caucasians and Hispanics 
Metabolism: clinical and experimental  2015;64(12):1674-1681.
Context and objective
We examined whether a prevalent caveolin-1 gene (CAV1) variant, previously related to insulin resistance, is associated with metabolic syndrome (MetS).
Patients and methods
We included subjects genotyped for the CAV1 variant rs926198 from two cohorts: 735 Caucasians from the HyperPATH multicenter study, and 810 Hispanic participants from the HTN-IR cohort.
Minor allele carriers from HyperPATH cohort (57% of subjects) had higher Framingham risk scores, higher odds of diabetes (10.7% vs 5.7%, p=0.016), insulin resistance (44.3% vs 35.1%, p=0.022), low HDL (49.3% vs 39.6%, p=0.018) and MetS (33% vs 20.5%, p<0.001) but similar BMI. Consistently, minor allele carriers exhibited higher odds of MetS, even when adjusted for confounders and relatedness (OR 2.83 (1.73–4.63), p<0.001). The association with MetS was replicated in the Hispanic cohort HTN-IR (OR 1.61, [1.06–2.44], p=0.025). Exploratory analyses suggest that MetS risk is modified by a CAV1 variant - BMI status interaction, whereby the minor allele carrier status strongly predicted MetS (OR 3.86 [2.05–7.27], p<0.001) and diabetes (OR 2.27 [1.07–4.78], p=0.03) in non-obese, but not in obese subjects. In addition, we observed a familial aggregation for MetS diagnosis in minor allele carriers.
The prevalent CAV1 gene variant rs926198 is associated with MetS in separate Caucasian and Hispanic cohorts. These findings appear to be driven by an interaction between the genetic marker and obesity status, suggesting that the CAV1 variant may improve risk profiling in non-obese subjects. Additional studies are needed to confirm the clinical implications of our results.
PMCID: PMC4641791  PMID: 26475177
caveolin 1; metabolic syndrome; dyslipidemia; insulin resistance; diabetes; cardiovascular risk
2.  Insulin Clearance Is Associated with Hepatic Lipase Activity and Lipid and Adiposity Traits in Mexican Americans 
PLoS ONE  2016;11(11):e0166263.
Reduction in insulin clearance plays an important role in the compensatory response to insulin resistance. Given the importance of this trait to the pathogenesis of diabetes, a deeper understanding of its regulation is warranted. Our goal was to identify metabolic and cardiovascular traits that are independently associated with metabolic clearance rate of insulin (MCRI). We conducted a cross-sectional analysis of metabolic and cardiovascular traits in 765 participants from the Mexican-American Coronary Artery Disease (MACAD) project who had undergone blood sampling, oral glucose tolerance test, euglycemic-hyperinsulinemic clamp, dual-energy X-ray absorptiometry, and carotid ultrasound. We assessed correlations of MCRI with traits from seven domains, including anthropometry, biomarkers, cardiovascular, glucose homeostasis, lipase activity, lipid profile, and liver function tests. We found inverse independent correlations between MCRI and hepatic lipase (P = 0.0004), insulin secretion (P = 0.0002), alanine aminotransferase (P = 0.0045), total fat mass (P = 0.014), and diabetes (P = 0.03). MCRI and apolipoprotein A-I exhibited a positive independent correlation (P = 0.035). These results generate a hypothesis that lipid and adiposity associated traits related to liver function may play a role in insulin clearance.
PMCID: PMC5112869  PMID: 27846285
3.  Rare, low frequency, and common coding variants in CHRNA5 and their contribution to nicotine dependence in European and African Americans 
Molecular psychiatry  2015;21(5):601-607.
The common nonsynonymous variant rs16969968 in the α5 nicotinic receptor subunit gene (CHRNA5) is the strongest genetic risk factor for nicotine dependence in European Americans and contributes to risk in African Americans. To comprehensively examine whether other CHRNA5 coding variation influences nicotine dependence risk, we performed targeted sequencing on 1582 nicotine dependent cases (Fagerström Test for Nicotine Dependence score≥4) and 1238 non-dependent controls, with independent replication of common and low frequency variants using 12 studies with exome chip data. Nicotine dependence was examined using logistic regression with individual common variants (MAF≥0.05), aggregate low frequency variants (0.05>MAF≥0.005), and aggregate rare variants (MAF<0.005). Meta-analysis of primary results was performed with replication studies containing 12 174 heavy and 11 290 light smokers. Next-generation sequencing with 180X coverage identified 24 nonsynonymous variants and 2 frameshift deletions in CHRNA5, including 9 novel variants in the 2820 subjects. Meta-analysis confirmed the risk effect of the only common variant (rs16969968, European ancestry: OR=1.3, p=3.5×10−11; African ancestry: OR=1.3, p=0.01) and demonstrated that 3 low frequency variants contributed an independent risk (aggregate term, European ancestry: OR=1.3, p=0.005; African ancestry: OR=1.4, p=0.0006). The remaining 22 rare coding variants were associated with increased risk of nicotine dependence in the European American primary sample (OR=12.9, p=0.01) and in the same risk direction in African Americans (OR=1.5, p=0.37). Our results indicate that common, low frequency and rare CHRNA5 coding variants are independently associated with nicotine dependence risk. These newly identified variants likely influence risk for smoking-related diseases such as lung cancer.
PMCID: PMC4740321  PMID: 26239294
4.  Variant Discovery and Fine Mapping of Genetic Loci Associated with Blood Pressure Traits in Hispanics and African Americans 
PLoS ONE  2016;11(10):e0164132.
Despite the substantial burden of hypertension in US minority populations, few genetic studies of blood pressure have been conducted in Hispanics and African Americans, and it is unclear whether many of the established loci identified in European-descent populations contribute to blood pressure variation in non-European descent populations. Using the Metabochip array, we sought to characterize the genetic architecture of previously identified blood pressure loci, and identify novel cardiometabolic variants related to systolic and diastolic blood pressure in a multi-ethnic US population including Hispanics (n = 19,706) and African Americans (n = 18,744). Several known blood pressure loci replicated in African Americans and Hispanics. Fourteen variants in three loci (KCNK3, FGF5, ATXN2-SH2B3) were significantly associated with blood pressure in Hispanics. The most significant diastolic blood pressure variant identified in our analysis, rs2586886/KCNK3 (P = 5.2 x 10−9), also replicated in independent Hispanic and European-descent samples. African American and trans-ethnic meta-analysis data identified novel variants in the FGF5, ULK4 and HOXA-EVX1 loci, which have not been previously associated with blood pressure traits. Our identification and independent replication of variants in KCNK3, a gene implicated in primary hyperaldosteronism, as well as a variant in HOTTIP (HOXA-EVX1) suggest that further work to clarify the roles of these genes may be warranted. Overall, our findings suggest that loci identified in European descent populations also contribute to blood pressure variation in diverse populations including Hispanics and African Americans—populations that are understudied for hypertension genetic risk factors.
PMCID: PMC5063457  PMID: 27736895
5.  General Framework for Meta-analysis of Haplotype Association Tests 
Genetic epidemiology  2016;40(3):244-252.
For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta-analysis has emerged as the method of choice to combine results from multiple studies. Many meta-analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta-analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two-stage meta-analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta-analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype-specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type-I error rate, and our approach is more powerful than inverse-variance-weighted meta-anaysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose-associated locus (G6PC2) and fasting glucose in 7 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.
PMCID: PMC4869684  PMID: 27027517
meta-analysis; haplotype association tests; family samples; linear mixed effects model
6.  Set-based Tests for Genetic Association in Longitudinal Studies 
Biometrics  2015;71(3):606-615.
Genetic association studies with longitudinal markers of chronic diseases (e.g., blood pressure, body mass index) provide a valuable opportunity to explore how genetic variants affect traits over time by utilizing the full trajectory of longitudinal outcomes. Since these traits are likely influenced by the joint effect of multiple variants in a gene, a joint analysis of these variants considering linkage disequilibrium (LD) may help to explain additional phenotypic variation. In this article, we propose a longitudinal genetic random field model (LGRF), to test the association between a phenotype measured repeatedly during the course of an observational study and a set of genetic variants. Generalized score type tests are developed, which we show are robust to misspefication of within-subject correlation, a feature that is desirable for longitudinal analysis. In addition, a joint test incorporating gene-time interaction is further proposed. Computational advancement is made for scalable implementation of the proposed methods in large-scale genome-wide association studies (GWAS). The proposed methods are evaluated through extensive simulation studies and illustrated using data from the Multi-Ethnic Study of Atherosclerosis (MESA). Our simulation results indicate substantial gain in power using LGRF when compared with two commonly used existing alternatives: (i) single marker tests using longitudinal outcome and (ii) existing gene-based tests using the average value of repeated measurements as the outcome.
PMCID: PMC4601568  PMID: 25854837
Genetic association; Generalized estimating equations; Generalized score test; Longitudinal study; Multi-marker test; Random field
7.  Association of a 62 Variant Type 2 Diabetes Genetic Risk Score with Markers of Subclinical Atherosclerosis: A Transethnic, Multicenter Study 
Type 2 diabetes (T2D) and cardiovascular disease (CVD) share risk factors and subclinical atherosclerosis (SCA) predicts events in those with and without diabetes. T2D genetic risk may predict both T2D and SCA. We hypothesized that greater T2D genetic risk is associated with higher extent of SCA.
Methods and Results
In a cross-sectional analysis including up to 9,210 European Americans, 3,773 African Americans, 1,446 Hispanic Americans and 773 Chinese Americans without known CVD and enrolled in the FHS, CARDIA, MESA and GENOA studies, we tested a 62 T2D-loci genetic risk score (GRS62) for association with measures of SCA, including coronary artery (CACS) or abdominal aortic calcium score, common (CCA-IMT) and internal carotid artery intima-media thickness, and ankle-brachial index (ABI). We used ancestry-stratified linear regression models, with random effects accounting for family relatedness when appropriate, applying a genetic-only (adjusted for sex) and a full SCA risk factors adjusted model (significance = p<0.01 = 0.05/5, number of traits analyzed). An inverse association with CACS in MESA Europeans (fully-adjusted p=0.004) and with CCA-IMT in FHS (p=0.009) was not confirmed in other study cohorts, either separately or in meta-analysis. Secondary analyses showed no consistent associations with β-cell and insulin resistance sub-GRS in FHS and CARDIA.
SCA does not have a major genetic component linked to a burden of 62 T2D loci identified by large genome-wide association studies. A shared T2D-SCA genetic basis, if any, might become apparent from better functional information about both T2D and CVD risk loci.
PMCID: PMC4472563  PMID: 25805414
genetic association; risk assessment; subclinical atherosclerosis risk factor; type 2 diabetes mellitus; cardiovascular disease
8.  Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND) 
BMC Genomics  2016;17:325.
The presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample.
A fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy.
The identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations.
Electronic supplementary material
The online version of this article (doi:10.1186/s12864-016-2654-x) contains supplementary material, which is available to authorized users.
PMCID: PMC4855449  PMID: 27142425
Individual genetic ancestry; Population structure; SNP; Diabetic nephropathy
9.  Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium 
Diabetes  2014;64(5):1853-1866.
Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10−8) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D.
PMCID: PMC4407862  PMID: 25524916
10.  Large-scale genomic analyses link reproductive ageing to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair 
Day, Felix R. | Ruth, Katherine S. | Thompson, Deborah J. | Lunetta, Kathryn L. | Pervjakova, Natalia | Chasman, Daniel I. | Stolk, Lisette | Finucane, Hilary K. | Sulem, Patrick | Bulik-Sullivan, Brendan | Esko, Tõnu | Johnson, Andrew D. | Elks, Cathy E. | Franceschini, Nora | He, Chunyan | Altmaier, Elisabeth | Brody, Jennifer A. | Franke, Lude L. | Huffman, Jennifer E. | Keller, Margaux F. | McArdle, Patrick F. | Nutile, Teresa | Porcu, Eleonora | Robino, Antonietta | Rose, Lynda M. | Schick, Ursula M. | Smith, Jennifer A. | Teumer, Alexander | Traglia, Michela | Vuckovic, Dragana | Yao, Jie | Zhao, Wei | Albrecht, Eva | Amin, Najaf | Corre, Tanguy | Hottenga, Jouke-Jan | Mangino, Massimo | Smith, Albert V. | Tanaka, Toshiko | Abecasis, Goncalo | Andrulis, Irene L. | Anton-Culver, Hoda | Antoniou, Antonis C. | Arndt, Volker | Arnold, Alice M. | Barbieri, Caterina | Beckmann, Matthias W. | Beeghly-Fadiel, Alicia | Benitez, Javier | Bernstein, Leslie | Bielinski, Suzette J. | Blomqvist, Carl | Boerwinkle, Eric | Bogdanova, Natalia V. | Bojesen, Stig E. | Bolla, Manjeet K. | Borresen-Dale, Anne-Lise | Boutin, Thibaud S | Brauch, Hiltrud | Brenner, Hermann | Brüning, Thomas | Burwinkel, Barbara | Campbell, Archie | Campbell, Harry | Chanock, Stephen J. | Chapman, J. Ross | Chen, Yii-Der Ida | Chenevix-Trench, Georgia | Couch, Fergus J. | Coviello, Andrea D. | Cox, Angela | Czene, Kamila | Darabi, Hatef | De Vivo, Immaculata | Demerath, Ellen W. | Dennis, Joe | Devilee, Peter | Dörk, Thilo | dos-Santos-Silva, Isabel | Dunning, Alison M. | Eicher, John D. | Fasching, Peter A. | Faul, Jessica D. | Figueroa, Jonine | Flesch-Janys, Dieter | Gandin, Ilaria | Garcia, Melissa E. | García-Closas, Montserrat | Giles, Graham G. | Girotto, Giorgia G. | Goldberg, Mark S. | González-Neira, Anna | Goodarzi, Mark O. | Grove, Megan L. | Gudbjartsson, Daniel F. | Guénel, Pascal | Guo, Xiuqing | Haiman, Christopher A. | Hall, Per | Hamann, Ute | Henderson, Brian E. | Hocking, Lynne J. | Hofman, Albert | Homuth, Georg | Hooning, Maartje J. | Hopper, John L. | Hu, Frank B. | Huang, Jinyan | Humphreys, Keith | Hunter, David J. | Jakubowska, Anna | Jones, Samuel E. | Kabisch, Maria | Karasik, David | Knight, Julia A. | Kolcic, Ivana | Kooperberg, Charles | Kosma, Veli-Matti | Kriebel, Jennifer | Kristensen, Vessela | Lambrechts, Diether | Langenberg, Claudia | Li, Jingmei | Li, Xin | Lindström, Sara | Liu, Yongmei | Luan, Jian’an | Lubinski, Jan | Mägi, Reedik | Mannermaa, Arto | Manz, Judith | Margolin, Sara | Marten, Jonathan | Martin, Nicholas G. | Masciullo, Corrado | Meindl, Alfons | Michailidou, Kyriaki | Mihailov, Evelin | Milani, Lili | Milne, Roger L. | Müller-Nurasyid, Martina | Nalls, Michael | Neale, Ben M. | Nevanlinna, Heli | Neven, Patrick | Newman, Anne B. | Nordestgaard, Børge G. | Olson, Janet E. | Padmanabhan, Sandosh | Peterlongo, Paolo | Peters, Ulrike | Petersmann, Astrid | Peto, Julian | Pharoah, Paul D.P. | Pirastu, Nicola N. | Pirie, Ailith | Pistis, Giorgio | Polasek, Ozren | Porteous, David | Psaty, Bruce M. | Pylkäs, Katri | Radice, Paolo | Raffel, Leslie J. | Rivadeneira, Fernando | Rudan, Igor | Rudolph, Anja | Ruggiero, Daniela | Sala, Cinzia F. | Sanna, Serena | Sawyer, Elinor J. | Schlessinger, David | Schmidt, Marjanka K. | Schmidt, Frank | Schmutzler, Rita K. | Schoemaker, Minouk J. | Scott, Robert A. | Seynaeve, Caroline M. | Simard, Jacques | Sorice, Rossella | Southey, Melissa C. | Stöckl, Doris | Strauch, Konstantin | Swerdlow, Anthony | Taylor, Kent D. | Thorsteinsdottir, Unnur | Toland, Amanda E. | Tomlinson, Ian | Truong, Thérèse | Tryggvadottir, Laufey | Turner, Stephen T. | Vozzi, Diego | Wang, Qin | Wellons, Melissa | Willemsen, Gonneke | Wilson, James F. | Winqvist, Robert | Wolffenbuttel, Bruce B.H.R. | Wright, Alan F. | Yannoukakos, Drakoulis | Zemunik, Tatijana | Zheng, Wei | Zygmunt, Marek | Bergmann, Sven | Boomsma, Dorret I. | Buring, Julie E. | Ferrucci, Luigi | Montgomery, Grant W. | Gudnason, Vilmundur | Spector, Tim D. | van Duijn, Cornelia M | Alizadeh, Behrooz Z. | Ciullo, Marina | Crisponi, Laura | Easton, Douglas F. | Gasparini, Paolo P. | Gieger, Christian | Harris, Tamara B. | Hayward, Caroline | Kardia, Sharon L.R. | Kraft, Peter | McKnight, Barbara | Metspalu, Andres | Morrison, Alanna C. | Reiner, Alex P. | Ridker, Paul M. | Rotter, Jerome I. | Toniolo, Daniela | Uitterlinden, André G. | Ulivi, Sheila | Völzke, Henry | Wareham, Nicholas J. | Weir, David R. | Yerges-Armstrong, Laura M. | Price, Alkes L. | Stefansson, Kari | Visser, Jenny A. | Ong, Ken K. | Chang-Claude, Jenny | Murabito, Joanne M. | Perry, John R.B. | Murray, Anna
Nature genetics  2015;47(11):1294-1303.
Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ~70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two harbouring additional rare missense alleles of large effect. We found enrichment of signals in/near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses revealed a major association with DNA damage-response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomisation analyses supported a causal effect of later ANM on breast cancer risk (~6% risk increase per-year, P=3×10−14), likely mediated by prolonged sex hormone exposure, rather than DDR mechanisms.
PMCID: PMC4661791  PMID: 26414677
11.  Genetics of Coronary Artery Disease in Taiwan: A Cardiometabochip Study by the Taichi Consortium 
PLoS ONE  2016;11(3):e0138014.
By means of a combination of genome-wide and follow-up studies, recent large-scale association studies of populations of European descent have now identified over 46 loci associated with coronary artery disease (CAD). As part of the TAICHI Consortium, we have collected and genotyped 8556 subjects from Taiwan, comprising 5423 controls and 3133 cases with coronary artery disease, for 9087 CAD SNPs using the CardioMetaboChip. We applied penalized logistic regression to ascertain the top SNPs that contribute together to CAD susceptibility in Taiwan. We observed that the 9p21 locus contributes to CAD at the level of genome-wide significance (rs1537372, with the presence of C, the major allele, the effect estimate is -0.216, standard error 0.033, p value 5.8x10-10). In contrast to a previous report, we propose that the 9p21 locus is a single genetic contribution to CAD in Taiwan because: 1) the penalized logistic regression and the follow-up conditional analysis suggested that rs1537372 accounts for all of the CAD association in 9p21, and 2) the high linkage disequilibrium observed for all associated SNPs in 9p21. We also observed evidence for the following loci at a false discovery rate >5%: SH2B3, ADAMTS7, PHACTR1, GGCX, HTRA1, COL4A1, and LARP6-LRRC49. We also took advantage of the fact that penalized methods are an efficient approach to search for gene-by-gene interactions, and observed that two-way interactions between the PHACTR1 and ADAMTS7 loci and between the SH2B3 and COL4A1 loci contribute to CAD risk. Both the similarities and differences between the significance of these loci when compared with significance of loci in studies of populations of European descent underscore the fact that further genetic association of studies in additional populations will provide clues to identify the genetic architecture of CAD across all populations worldwide.
PMCID: PMC4794124  PMID: 26982883
12.  Empirical Characteristics of Family-Based Linkage to a Complex Trait: the ADIPOQ Region and Adiponectin Levels 
Human genetics  2014;134(2):203-213.
We previously identified a low frequency (1.1%) coding variant (G45R; rs200573126) in the adiponectin gene (ADIPOQ) which was the basis for a multipoint microsatellite linkage signal (LOD=8.2) for plasma adiponectin levels in Hispanic families. We have empirically evaluated the ability of data from targeted common variants, exome chip genotyping, and genome-wide association study (GWAS) data to detect linkage and association to adiponectin protein levels at this locus. Simple two-point linkage and association analyses were performed in 88 Hispanic families (1150 individuals) using 10,958 SNPs on chromosome 3. Approaches were compared for their ability to map the functional variant, G45R, which was strongly linked (two-point LOD=20.98) and powerfully associated (p-value=8.1×10−50). Over 450 SNPs within a broad 61 Mb interval around rs200573126 showed nominal evidence of linkage (LOD>3) but only four other SNPs in this region were associated with p-values<1.0×10−4. When G45R was accounted for, the maximum LOD score across the interval dropped to 4.39 and the best p-value was 1.1×10−5. Linked and/or associated variants ranged in frequency (0.0018 to 0.50) and type (coding, non-coding) and had little detectable linkage disequilibrium with rs200573126 (r2<0.20). In addition, the two-point linkage approach empirically outperformed multipoint microsatellite and multipoint SNP analysis. In the absence of data for rs200573126, family-based linkage analysis using a moderately dense SNP dataset, including both common and low frequency variants, resulted in stronger evidence for an adiponectin locus than association data alone. Thus, linkage analysis can be a useful tool to facilitate identification of high impact genetic variants.
PMCID: PMC4293344  PMID: 25447270
13.  Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels 
Kilpeläinen, Tuomas O. | Carli, Jayne F. Martin | Skowronski, Alicja A. | Sun, Qi | Kriebel, Jennifer | Feitosa, Mary F | Hedman, Åsa K. | Drong, Alexander W. | Hayes, James E. | Zhao, Jinghua | Pers, Tune H. | Schick, Ursula | Grarup, Niels | Kutalik, Zoltán | Trompet, Stella | Mangino, Massimo | Kristiansson, Kati | Beekman, Marian | Lyytikäinen, Leo-Pekka | Eriksson, Joel | Henneman, Peter | Lahti, Jari | Tanaka, Toshiko | Luan, Jian'an | Greco M, Fabiola Del | Pasko, Dorota | Renström, Frida | Willems, Sara M. | Mahajan, Anubha | Rose, Lynda M. | Guo, Xiuqing | Liu, Yongmei | Kleber, Marcus E. | Pérusse, Louis | Gaunt, Tom | Ahluwalia, Tarunveer S. | Ju Sung, Yun | Ramos, Yolande F. | Amin, Najaf | Amuzu, Antoinette | Barroso, Inês | Bellis, Claire | Blangero, John | Buckley, Brendan M. | Böhringer, Stefan | I Chen, Yii-Der | de Craen, Anton J. N. | Crosslin, David R. | Dale, Caroline E. | Dastani, Zari | Day, Felix R. | Deelen, Joris | Delgado, Graciela E. | Demirkan, Ayse | Finucane, Francis M. | Ford, Ian | Garcia, Melissa E. | Gieger, Christian | Gustafsson, Stefan | Hallmans, Göran | Hankinson, Susan E. | Havulinna, Aki S | Herder, Christian | Hernandez, Dena | Hicks, Andrew A. | Hunter, David J. | Illig, Thomas | Ingelsson, Erik | Ioan-Facsinay, Andreea | Jansson, John-Olov | Jenny, Nancy S. | Jørgensen, Marit E. | Jørgensen, Torben | Karlsson, Magnus | Koenig, Wolfgang | Kraft, Peter | Kwekkeboom, Joanneke | Laatikainen, Tiina | Ladwig, Karl-Heinz | LeDuc, Charles A. | Lowe, Gordon | Lu, Yingchang | Marques-Vidal, Pedro | Meisinger, Christa | Menni, Cristina | Morris, Andrew P. | Myers, Richard H. | Männistö, Satu | Nalls, Mike A. | Paternoster, Lavinia | Peters, Annette | Pradhan, Aruna D. | Rankinen, Tuomo | Rasmussen-Torvik, Laura J. | Rathmann, Wolfgang | Rice, Treva K. | Brent Richards, J | Ridker, Paul M. | Sattar, Naveed | Savage, David B. | Söderberg, Stefan | Timpson, Nicholas J. | Vandenput, Liesbeth | van Heemst, Diana | Uh, Hae-Won | Vohl, Marie-Claude | Walker, Mark | Wichmann, Heinz-Erich | Widén, Elisabeth | Wood, Andrew R. | Yao, Jie | Zeller, Tanja | Zhang, Yiying | Meulenbelt, Ingrid | Kloppenburg, Margreet | Astrup, Arne | Sørensen, Thorkild I. A. | Sarzynski, Mark A. | Rao, D. C. | Jousilahti, Pekka | Vartiainen, Erkki | Hofman, Albert | Rivadeneira, Fernando | Uitterlinden, André G. | Kajantie, Eero | Osmond, Clive | Palotie, Aarno | Eriksson, Johan G. | Heliövaara, Markku | Knekt, Paul B. | Koskinen, Seppo | Jula, Antti | Perola, Markus | Huupponen, Risto K. | Viikari, Jorma S. | Kähönen, Mika | Lehtimäki, Terho | Raitakari, Olli T. | Mellström, Dan | Lorentzon, Mattias | Casas, Juan P. | Bandinelli, Stefanie | März, Winfried | Isaacs, Aaron | van Dijk, Ko W. | van Duijn, Cornelia M. | Harris, Tamara B. | Bouchard, Claude | Allison, Matthew A. | Chasman, Daniel I. | Ohlsson, Claes | Lind, Lars | Scott, Robert A. | Langenberg, Claudia | Wareham, Nicholas J. | Ferrucci, Luigi | Frayling, Timothy M. | Pramstaller, Peter P. | Borecki, Ingrid B. | Waterworth, Dawn M. | Bergmann, Sven | Waeber, Gérard | Vollenweider, Peter | Vestergaard, Henrik | Hansen, Torben | Pedersen, Oluf | Hu, Frank B. | Eline Slagboom, P | Grallert, Harald | Spector, Tim D. | Jukema, J.W. | Klein, Robert J. | Schadt, Erik E | Franks, Paul W. | Lindgren, Cecilia M. | Leibel, Rudolph L. | Loos, Ruth J. F.
Nature Communications  2016;7:10494.
Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10−6 in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10−8) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
This meta-analysis of genome-wide association studies identifies four genetic loci associated with circulating leptin levels independent of adiposity. Examination in mouse adipose tissue explants provides functional support for the leptin-associated loci.
PMCID: PMC4740377  PMID: 26833098
14.  Directional dominance on stature and cognition in diverse human populations 
Joshi, Peter K. | Esko, Tonu | Mattsson, Hannele | Eklund, Niina | Gandin, Ilaria | Nutile, Teresa | Jackson, Anne U. | Schurmann, Claudia | Smith, Albert V. | Zhang, Weihua | Okada, Yukinori | Stančáková, Alena | Faul, Jessica D. | Zhao, Wei | Bartz, Traci M. | Concas, Maria Pina | Franceschini, Nora | Enroth, Stefan | Vitart, Veronique | Trompet, Stella | Guo, Xiuqing | Chasman, Daniel I. | O’Connel, Jeffery R. | Corre, Tanguy | Nongmaithem, Suraj S. | Chen, Yuning | Mangino, Massimo | Ruggiero, Daniela | Traglia, Michela | Farmaki, Aliki-Eleni | Kacprowski, Tim | Bjonnes, Andrew | van der Spek, Ashley | Wu, Ying | Giri, Anil K. | Yanek, Lisa R. | Wang, Lihua | Hofer, Edith | Rietveld, Cornelius A. | McLeod, Olga | Cornelis, Marilyn C. | Pattaro, Cristian | Verweij, Niek | Baumbach, Clemens | Abdellaoui, Abdel | Warren, Helen R. | Vuckovic, Dragana | Mei, Hao | Bouchard, Claude | Perry, John R.B. | Cappellani, Stefania | Mirza, Saira S. | Benton, Miles C. | Broeckel, Ulrich | Medland, Sarah E. | Lind, Penelope A. | Malerba, Giovanni | Drong, Alexander | Yengo, Loic | Bielak, Lawrence F. | Zhi, Degui | van der Most, Peter J. | Shriner, Daniel | Mägi, Reedik | Hemani, Gibran | Karaderi, Tugce | Wang, Zhaoming | Liu, Tian | Demuth, Ilja | Zhao, Jing Hua | Meng, Weihua | Lataniotis, Lazaros | van der Laan, Sander W. | Bradfield, Jonathan P. | Wood, Andrew R. | Bonnefond, Amelie | Ahluwalia, Tarunveer S. | Hall, Leanne M. | Salvi, Erika | Yazar, Seyhan | Carstensen, Lisbeth | de Haan, Hugoline G. | Abney, Mark | Afzal, Uzma | Allison, Matthew A. | Amin, Najaf | Asselbergs, Folkert W. | Bakker, Stephan J.L. | Barr, R. Graham | Baumeister, Sebastian E. | Benjamin, Daniel J. | Bergmann, Sven | Boerwinkle, Eric | Bottinger, Erwin P. | Campbell, Archie | Chakravarti, Aravinda | Chan, Yingleong | Chanock, Stephen J. | Chen, Constance | Chen, Y.-D. Ida | Collins, Francis S. | Connell, John | Correa, Adolfo | Cupples, L. Adrienne | Smith, George Davey | Davies, Gail | Dörr, Marcus | Ehret, Georg | Ellis, Stephen B. | Feenstra, Bjarke | Feitosa, Mary F. | Ford, Ian | Fox, Caroline S. | Frayling, Timothy M. | Friedrich, Nele | Geller, Frank | Scotland, Generation | Gillham-Nasenya, Irina | Gottesman, Omri | Graff, Misa | Grodstein, Francine | Gu, Charles | Haley, Chris | Hammond, Christopher J. | Harris, Sarah E. | Harris, Tamara B. | Hastie, Nicholas D. | Heard-Costa, Nancy L. | Heikkilä, Kauko | Hocking, Lynne J. | Homuth, Georg | Hottenga, Jouke-Jan | Huang, Jinyan | Huffman, Jennifer E. | Hysi, Pirro G. | Ikram, M. Arfan | Ingelsson, Erik | Joensuu, Anni | Johansson, Åsa | Jousilahti, Pekka | Jukema, J. Wouter | Kähönen, Mika | Kamatani, Yoichiro | Kanoni, Stavroula | Kerr, Shona M. | Khan, Nazir M. | Koellinger, Philipp | Koistinen, Heikki A. | Kooner, Manraj K. | Kubo, Michiaki | Kuusisto, Johanna | Lahti, Jari | Launer, Lenore J. | Lea, Rodney A. | Lehne, Benjamin | Lehtimäki, Terho | Liewald, David C.M. | Lind, Lars | Loh, Marie | Lokki, Marja-Liisa | London, Stephanie J. | Loomis, Stephanie J. | Loukola, Anu | Lu, Yingchang | Lumley, Thomas | Lundqvist, Annamari | Männistö, Satu | Marques-Vidal, Pedro | Masciullo, Corrado | Matchan, Angela | Mathias, Rasika A. | Matsuda, Koichi | Meigs, James B. | Meisinger, Christa | Meitinger, Thomas | Menni, Cristina | Mentch, Frank D. | Mihailov, Evelin | Milani, Lili | Montasser, May E. | Montgomery, Grant W. | Morrison, Alanna | Myers, Richard H. | Nadukuru, Rajiv | Navarro, Pau | Nelis, Mari | Nieminen, Markku S. | Nolte, Ilja M. | O’Connor, George T. | Ogunniyi, Adesola | Padmanabhan, Sandosh | Palmas, Walter R. | Pankow, James S. | Patarcic, Inga | Pavani, Francesca | Peyser, Patricia A. | Pietilainen, Kirsi | Poulter, Neil | Prokopenko, Inga | Ralhan, Sarju | Redmond, Paul | Rich, Stephen S. | Rissanen, Harri | Robino, Antonietta | Rose, Lynda M. | Rose, Richard | Sala, Cinzia | Salako, Babatunde | Salomaa, Veikko | Sarin, Antti-Pekka | Saxena, Richa | Schmidt, Helena | Scott, Laura J. | Scott, William R. | Sennblad, Bengt | Seshadri, Sudha | Sever, Peter | Shrestha, Smeeta | Smith, Blair H. | Smith, Jennifer A. | Soranzo, Nicole | Sotoodehnia, Nona | Southam, Lorraine | Stanton, Alice V. | Stathopoulou, Maria G. | Strauch, Konstantin | Strawbridge, Rona J. | Suderman, Matthew J. | Tandon, Nikhil | Tang, Sian-Tsun | Taylor, Kent D. | Tayo, Bamidele O. | Töglhofer, Anna Maria | Tomaszewski, Maciej | Tšernikova, Natalia | Tuomilehto, Jaakko | Uitterlinden, Andre G. | Vaidya, Dhananjay | van Hylckama Vlieg, Astrid | van Setten, Jessica | Vasankari, Tuula | Vedantam, Sailaja | Vlachopoulou, Efthymia | Vozzi, Diego | Vuoksimaa, Eero | Waldenberger, Melanie | Ware, Erin B. | Wentworth-Shields, William | Whitfield, John B. | Wild, Sarah | Willemsen, Gonneke | Yajnik, Chittaranjan S. | Yao, Jie | Zaza, Gianluigi | Zhu, Xiaofeng | Project, The BioBank Japan | Salem, Rany M. | Melbye, Mads | Bisgaard, Hans | Samani, Nilesh J. | Cusi, Daniele | Mackey, David A. | Cooper, Richard S. | Froguel, Philippe | Pasterkamp, Gerard | Grant, Struan F.A. | Hakonarson, Hakon | Ferrucci, Luigi | Scott, Robert A. | Morris, Andrew D. | Palmer, Colin N.A. | Dedoussis, George | Deloukas, Panos | Bertram, Lars | Lindenberger, Ulman | Berndt, Sonja I. | Lindgren, Cecilia M. | Timpson, Nicholas J. | Tönjes, Anke | Munroe, Patricia B. | Sørensen, Thorkild I.A. | Rotimi, Charles N. | Arnett, Donna K. | Oldehinkel, Albertine J. | Kardia, Sharon L.R. | Balkau, Beverley | Gambaro, Giovanni | Morris, Andrew P. | Eriksson, Johan G. | Wright, Margie J. | Martin, Nicholas G. | Hunt, Steven C. | Starr, John M. | Deary, Ian J. | Griffiths, Lyn R. | Tiemeier, Henning | Pirastu, Nicola | Kaprio, Jaakko | Wareham, Nicholas J. | Pérusse, Louis | Wilson, James G. | Girotto, Giorgia | Caulfield, Mark J. | Raitakari, Olli | Boomsma, Dorret I. | Gieger, Christian | van der Harst, Pim | Hicks, Andrew A. | Kraft, Peter | Sinisalo, Juha | Knekt, Paul | Johannesson, Magnus | Magnusson, Patrik K.E. | Hamsten, Anders | Schmidt, Reinhold | Borecki, Ingrid B. | Vartiainen, Erkki | Becker, Diane M. | Bharadwaj, Dwaipayan | Mohlke, Karen L. | Boehnke, Michael | van Duijn, Cornelia M. | Sanghera, Dharambir K. | Teumer, Alexander | Zeggini, Eleftheria | Metspalu, Andres | Gasparini, Paolo | Ulivi, Sheila | Ober, Carole | Toniolo, Daniela | Rudan, Igor | Porteous, David J. | Ciullo, Marina | Spector, Tim D. | Hayward, Caroline | Dupuis, Josée | Loos, Ruth J.F. | Wright, Alan F. | Chandak, Giriraj R. | Vollenweider, Peter | Shuldiner, Alan | Ridker, Paul M. | Rotter, Jerome I. | Sattar, Naveed | Gyllensten, Ulf | North, Kari E. | Pirastu, Mario | Psaty, Bruce M. | Weir, David R. | Laakso, Markku | Gudnason, Vilmundur | Takahashi, Atsushi | Chambers, John C. | Kooner, Jaspal S. | Strachan, David P. | Campbell, Harry | Hirschhorn, Joel N. | Perola, Markus | Polašek, Ozren | Wilson, James F.
Nature  2015;523(7561):459-462.
Homozygosity has long been associated with rare, often devastating, Mendelian disorders1 and Darwin was one of the first to recognise that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity, ROH), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use ROH to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts and find statistically significant associations between summed runs of homozygosity (SROH) and four complex traits: height, forced expiratory lung volume in 1 second (FEV1), general cognitive ability (g) and educational attainment (nominal p<1 × 10−300, 2.1 × 10−6, 2.5 × 10−10, 1.8 × 10−10). In each case increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing convincing evidence for the first time that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
PMCID: PMC4516141  PMID: 26131930
15.  Genome-wide association studies in East Asians identify new loci for waist-hip ratio and waist circumference 
Scientific Reports  2016;6:17958.
Sixty genetic loci associated with abdominal obesity, measured by waist circumference (WC) and waist-hip ratio (WHR), have been previously identified, primarily from studies conducted in European-ancestry populations. We conducted a meta-analysis of associations of abdominal obesity with approximately 2.5 million single nucleotide polymorphisms (SNPs) among 53,052 (for WC) and 48,312 (for WHR) individuals of Asian descent, and replicated 33 selected SNPs among 3,762 to 17,110 additional individuals. We identified four novel loci near the EFEMP1, ADAMTSL3 , CNPY2, and GNAS genes that were associated with WC after adjustment for body mass index (BMI); two loci near the NID2 and HLA-DRB5 genes associated with WHR after adjustment for BMI, and three loci near the CEP120, TSC22D2, and SLC22A2 genes associated with WC without adjustment for BMI. Functional enrichment analyses revealed enrichment of corticotropin-releasing hormone signaling, GNRH signaling, and/or CDK5 signaling pathways for those newly-identified loci. Our study provides additional insight on genetic contribution to abdominal obesity.
PMCID: PMC4726286  PMID: 26785701
17.  A Comprehensive Analysis of Common and Rare Variants to Identify Adiposity Loci in Hispanic Americans: The IRAS Family Study (IRASFS) 
PLoS ONE  2015;10(11):e0134649.
Obesity is growing epidemic affecting 35% of adults in the United States. Previous genome-wide association studies (GWAS) have identified numerous loci associated with obesity. However, the majority of studies have been completed in Caucasians focusing on total body measures of adiposity. Here we report the results from genome-wide and exome chip association studies focusing on total body measures of adiposity including body mass index (BMI), percent body fat (PBF) and measures of fat deposition including waist circumference (WAIST), waist-hip ratio (WHR), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) in Hispanic Americans (nmax = 1263) from the Insulin Resistance Atherosclerosis Family Study (IRASFS). Five SNPs from two novel loci attained genome-wide significance (P<5.00x10-8) in IRASFS. A missense SNP in the isocitrate dehydrogenase 1 gene (IDH1) was associated with WAIST (rs34218846, MAF = 6.8%, PDOM = 1.62x10-8). This protein is postulated to play an important role in fat and cholesterol biosynthesis as demonstrated in cell and knock-out animal models. Four correlated intronic SNPs in the Zinc finger, GRF-type containing 1 gene (ZGRF1; SNP rs1471880, MAF = 48.1%, PDOM = 1.00x10-8) were strongly associated with WHR. The exact biological function of ZGRF1 and the connection with adiposity remains unclear. SNPs with p-values less than 5.00x10-6 from IRASFS were selected for replication. Meta-analysis was computed across seven independent Hispanic-American cohorts (nmax = 4156) and the strongest signal was rs1471880 (PDOM = 8.38x10-6) in ZGRF1 with WAIST. In conclusion, a genome-wide and exome chip association study was conducted that identified two novel loci (IDH1 and ZGRF1) associated with adiposity. While replication efforts were inconclusive, when taken together with the known biology, IDH1 and ZGRF1 warrant further evaluation.
PMCID: PMC4658008  PMID: 26599207
18.  Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index 
Wen, Wanqing | Zheng, Wei | Okada, Yukinori | Takeuchi, Fumihiko | Tabara, Yasuharu | Hwang, Joo-Yeon | Dorajoo, Rajkumar | Li, Huaixing | Tsai, Fuu-Jen | Yang, Xiaobo | He, Jiang | Wu, Ying | He, Meian | Zhang, Yi | Liang, Jun | Guo, Xiuqing | Sheu, Wayne Huey-Herng | Delahanty, Ryan | Guo, Xingyi | Kubo, Michiaki | Yamamoto, Ken | Ohkubo, Takayoshi | Go, Min Jin | Liu, Jian Jun | Gan, Wei | Chen, Ching-Chu | Gao, Yong | Li, Shengxu | Lee, Nanette R. | Wu, Chen | Zhou, Xueya | Song, Huaidong | Yao, Jie | Lee, I-Te | Long, Jirong | Tsunoda, Tatsuhiko | Akiyama, Koichi | Takashima, Naoyuki | Cho, Yoon Shin | Ong, Rick TH | Lu, Ling | Chen, Chien-Hsiun | Tan, Aihua | Rice, Treva K | Adair, Linda S. | Gui, Lixuan | Allison, Matthew | Lee, Wen-Jane | Cai, Qiuyin | Isomura, Minoru | Umemura, Satoshi | Kim, Young Jin | Seielstad, Mark | Hixson, James | Xiang, Yong-Bing | Isono, Masato | Kim, Bong-Jo | Sim, Xueling | Lu, Wei | Nabika, Toru | Lee, Juyoung | Lim, Wei-Yen | Gao, Yu-Tang | Takayanagi, Ryoichi | Kang, Dae-Hee | Wong, Tien Yin | Hsiung, Chao Agnes | Wu, I-Chien | Juang, Jyh-Ming Jimmy | Shi, Jiajun | Choi, Bo Youl | Aung, Tin | Hu, Frank | Kim, Mi Kyung | Lim, Wei Yen | Wang, Tzung-Dao | Shin, Min-Ho | Lee, Jeannette | Ji, Bu-Tian | Lee, Young-Hoon | Young, Terri L. | Shin, Dong Hoon | Chun, Byung-Yeol | Cho, Myeong-Chan | Han, Bok-Ghee | Hwu, Chii-Min | Assimes, Themistocles L. | Absher, Devin | Yan, Xiaofei | Kim, Eric | Kuo, Jane Z. | Kwon, Soonil | Taylor, Kent D. | Chen, Yii-Der I. | Rotter, Jerome I. | Qi, Lu | Zhu, Dingliang | Wu, Tangchun | Mohlke, Karen L. | Gu, Dongfeng | Mo, Zengnan | Wu, Jer-Yuarn | Lin, Xu | Miki, Tetsuro | Tai, E. Shyong | Lee, Jong-Young | Kato, Norihiro | Shu, Xiao-Ou | Tanaka, Toshihiro
Human Molecular Genetics  2014;23(20):5492-5504.
Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488–47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10−13), ALDH2/MYL2 (rs671, P = 3.40 × 10−11; rs12229654, P = 4.56 × 10−9), ITIH4 (rs2535633, P = 1.77 × 10−10) and NT5C2 (rs11191580, P = 3.83 × 10−8) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10−8) and an additional 14 at P < 1.0 × 10−3 with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity.
PMCID: PMC4168820  PMID: 24861553
19.  Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND) 
PLoS Genetics  2015;11(8):e1005352.
Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.
Author Summary
Type 2 diabetes is the most common cause of severe kidney disease worldwide and diabetic kidney disease (DKD) associates with premature death. Individuals of non-European ancestry have the highest burden of type 2 DKD; hence understanding the causes of DKD remains critical to reducing health disparities. Family studies demonstrate that genes regulate the onset and progression of DKD; however, identifying these genes has proven to be challenging. The Family Investigation of Diabetes and Nephropathy consortium (FIND) recruited a large multi-ethnic collection of individuals with type 2 diabetes with and without kidney disease in order to detect genes associated with DKD. FIND discovered and replicated a DKD-associated genetic locus on human chromosome 6q25.2 (rs955333) between the SCAF8 and CNKSR genes. Findings were supported by significantly different expression of genes in this region from kidney tissue of subjects with, versus without DKD. The present findings identify a novel kidney disease susceptibility locus in individuals with type 2 diabetes which is consistent across subjects of differing ancestries. In addition, FIND results provide a rich catalogue of genetic variation in DKD patients for future research on the genetic architecture regulating this common and devastating disease.
PMCID: PMC4549309  PMID: 26305897
20.  Leptin-Mediated Increases in Catecholamine Signaling Reduce Adipose Tissue Inflammation via Activation of Macrophage HDAC4 
Cell metabolism  2014;19(6):1058-1065.
Obesity promotes systemic insulin resistance through inflammatory changes that lead to the release of cytokines from activated macrophages. Although the mechanism is unclear, the second messenger cAMP has been found to attenuate macrophage activity in response to a variety of hormonal signals. We show that, in the setting of acute over-nutrition, leptin triggers catecholamine-dependent increases in cAMP signaling that reduce inflammatory gene expression via the activation of the histone deacetylase HDAC4. cAMP stimulates HDAC4 activity through the PKA-dependent inhibition of the salt inducible kinases (SIKs), which otherwise phosphorylate and sequester HDAC4 in the cytoplasm. Following its dephosphorylation, HDAC4 shuttles to the nucleus where it inhibits NFkB activity over pro-inflammatory genes. As variants in the HDAC4 gene are associated with obesity in humans, our results indicate that the cAMP-HDAC4 pathway functions importantly in maintaining insulin sensitivity and energy balance via its effects on the innate immune system.
PMCID: PMC4207085  PMID: 24768298
21.  A novel method for testing association of multiple genetic markers with a multinomial trait 
We developed a multinomial probit model with singular value decomposition for testing a large number of single nucleotide polymorphisms (SNPs) simultaneously, using maximum likelihood estimation and permutation. The method was validated by simulation. We simulated 1000 SNPs, including 9 associated with disease states, and 8 of the 9 were successfully identified. Applying the method to study 32 genes in our Mexican-American samples for association with prediabetes through either impaired glucose tolerance (IGT) or impaired fasting glucose (IFG), we found 3 genes (SORCS1, AMPD1, PPAR) associated with both IGT and IFG, while 5 genes (AMPD2, PRKAA2, C5, TCF7L2, ITR) with the IGT mechanism only and 6 genes (CAPN10, IL4,NOS3, CD14, GCG, SORT1) with the IFG mechanism only. These data suggest that IGT and IFG may indicate different physiological mechanism to prediabetes, via different genetic determinants.
PMCID: PMC4439253  PMID: 26005397
22.  Identification and validation of N-acetyltransferase 2 as an insulin sensitivity gene 
The Journal of Clinical Investigation  2015;125(4):1739-1751.
Decreased insulin sensitivity, also referred to as insulin resistance (IR), is a fundamental abnormality in patients with type 2 diabetes and a risk factor for cardiovascular disease. While IR predisposition is heritable, the genetic basis remains largely unknown. The GENEticS of Insulin Sensitivity consortium conducted a genome-wide association study (GWAS) for direct measures of insulin sensitivity, such as euglycemic clamp or insulin suppression test, in 2,764 European individuals, with replication in an additional 2,860 individuals. The presence of a nonsynonymous variant of N-acetyltransferase 2 (NAT2) [rs1208 (803A>G, K268R)] was strongly associated with decreased insulin sensitivity that was independent of BMI. The rs1208 “A” allele was nominally associated with IR-related traits, including increased fasting glucose, hemoglobin A1C, total and LDL cholesterol, triglycerides, and coronary artery disease. NAT2 acetylates arylamine and hydrazine drugs and carcinogens, but predicted acetylator NAT2 phenotypes were not associated with insulin sensitivity. In a murine adipocyte cell line, silencing of NAT2 ortholog Nat1 decreased insulin-mediated glucose uptake, increased basal and isoproterenol-stimulated lipolysis, and decreased adipocyte differentiation, while Nat1 overexpression produced opposite effects. Nat1-deficient mice had elevations in fasting blood glucose, insulin, and triglycerides and decreased insulin sensitivity, as measured by glucose and insulin tolerance tests, with intermediate effects in Nat1 heterozygote mice. Our results support a role for NAT2 in insulin sensitivity.
PMCID: PMC4409020  PMID: 25798622
Cardiology; Endocrinology; Genetics; Metabolism
23.  Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility 
Wessel, Jennifer | Chu, Audrey Y. | Willems, Sara M. | Wang, Shuai | Yaghootkar, Hanieh | Brody, Jennifer A. | Dauriz, Marco | Hivert, Marie-France | Raghavan, Sridharan | Lipovich, Leonard | Hidalgo, Bertha | Fox, Keolu | Huffman, Jennifer E. | An, Ping | Lu, Yingchang | Rasmussen-Torvik, Laura J. | Grarup, Niels | Ehm, Margaret G. | Li, Li | Baldridge, Abigail S. | Stančáková, Alena | Abrol, Ravinder | Besse, Céline | Boland, Anne | Bork-Jensen, Jette | Fornage, Myriam | Freitag, Daniel F. | Garcia, Melissa E. | Guo, Xiuqing | Hara, Kazuo | Isaacs, Aaron | Jakobsdottir, Johanna | Lange, Leslie A. | Layton, Jill C. | Li, Man | Zhao, Jing Hua | Meidtner, Karina | Morrison, Alanna C. | Nalls, Mike A. | Peters, Marjolein J. | Sabater-Lleal, Maria | Schurmann, Claudia | Silveira, Angela | Smith, Albert V. | Southam, Lorraine | Stoiber, Marcus H. | Strawbridge, Rona J. | Taylor, Kent D. | Varga, Tibor V. | Allin, Kristine H. | Amin, Najaf | Aponte, Jennifer L. | Aung, Tin | Barbieri, Caterina | Bihlmeyer, Nathan A. | Boehnke, Michael | Bombieri, Cristina | Bowden, Donald W. | Burns, Sean M. | Chen, Yuning | Chen, Yii-Der I. | Cheng, Ching-Yu | Correa, Adolfo | Czajkowski, Jacek | Dehghan, Abbas | Ehret, Georg B. | Eiriksdottir, Gudny | Escher, Stefan A. | Farmaki, Aliki-Eleni | Frånberg, Mattias | Gambaro, Giovanni | Giulianini, Franco | III, William A. Goddard | Goel, Anuj | Gottesman, Omri | Grove, Megan L. | Gustafsson, Stefan | Hai, Yang | Hallmans, Göran | Heo, Jiyoung | Hoffmann, Per | Ikram, Mohammad K. | Jensen, Richard A. | Jørgensen, Marit E. | Jørgensen, Torben | Karaleftheri, Maria | Khor, Chiea C. | Kirkpatrick, Andrea | Kraja, Aldi T. | Kuusisto, Johanna | Lange, Ethan M. | Lee, I.T. | Lee, Wen-Jane | Leong, Aaron | Liao, Jiemin | Liu, Chunyu | Liu, Yongmei | Lindgren, Cecilia M. | Linneberg, Allan | Malerba, Giovanni | Mamakou, Vasiliki | Marouli, Eirini | Maruthur, Nisa M. | Matchan, Angela | McKean, Roberta | McLeod, Olga | Metcalf, Ginger A. | Mohlke, Karen L. | Muzny, Donna M. | Ntalla, Ioanna | Palmer, Nicholette D. | Pasko, Dorota | Peter, Andreas | Rayner, Nigel W. | Renström, Frida | Rice, Ken | Sala, Cinzia F. | Sennblad, Bengt | Serafetinidis, Ioannis | Smith, Jennifer A. | Soranzo, Nicole | Speliotes, Elizabeth K. | Stahl, Eli A. | Stirrups, Kathleen | Tentolouris, Nikos | Thanopoulou, Anastasia | Torres, Mina | Traglia, Michela | Tsafantakis, Emmanouil | Javad, Sundas | Yanek, Lisa R. | Zengini, Eleni | Becker, Diane M. | Bis, Joshua C. | Brown, James B. | Cupples, L. Adrienne | Hansen, Torben | Ingelsson, Erik | Karter, Andrew J. | Lorenzo, Carlos | Mathias, Rasika A. | Norris, Jill M. | Peloso, Gina M. | Sheu, Wayne H.-H. | Toniolo, Daniela | Vaidya, Dhananjay | Varma, Rohit | Wagenknecht, Lynne E. | Boeing, Heiner | Bottinger, Erwin P. | Dedoussis, George | Deloukas, Panos | Ferrannini, Ele | Franco, Oscar H. | Franks, Paul W. | Gibbs, Richard A. | Gudnason, Vilmundur | Hamsten, Anders | Harris, Tamara B. | Hattersley, Andrew T. | Hayward, Caroline | Hofman, Albert | Jansson, Jan-Håkan | Langenberg, Claudia | Launer, Lenore J. | Levy, Daniel | Oostra, Ben A. | O'Donnell, Christopher J. | O'Rahilly, Stephen | Padmanabhan, Sandosh | Pankow, James S. | Polasek, Ozren | Province, Michael A. | Rich, Stephen S. | Ridker, Paul M | Rudan, Igor | Schulze, Matthias B. | Smith, Blair H. | Uitterlinden, André G. | Walker, Mark | Watkins, Hugh | Wong, Tien Y. | Zeggini, Eleftheria | Scotland, Generation | Laakso, Markku | Borecki, Ingrid B. | Chasman, Daniel I. | Pedersen, Oluf | Psaty, Bruce M. | Tai, E. Shyong | van Duijn, Cornelia M. | Wareham, Nicholas J. | Waterworth, Dawn M. | Boerwinkle, Eric | Kao, WH Linda | Florez, Jose C. | Loos, Ruth J.F. | Wilson, James G. | Frayling, Timothy M. | Siscovick, David S. | Dupuis, Josée | Rotter, Jerome I. | Meigs, James B. | Scott, Robert A. | Goodarzi, Mark O.
Nature communications  2015;6:5897.
Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol L−1, p=3.4×10−12), T2D risk (OR[95%CI]=0.86[0.76-0.96], p=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose−1, p=0.048), but higher 2-h glucose (β=0.16±0.05 mmol L−1, p=4.3×10−4). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8×10−6) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol L−1, p=1.3×10−8). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
PMCID: PMC4311266  PMID: 25631608
24.  Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility 
Wessel, Jennifer | Chu, Audrey Y | Willems, Sara M | Wang, Shuai | Yaghootkar, Hanieh | Brody, Jennifer A | Dauriz, Marco | Hivert, Marie-France | Raghavan, Sridharan | Lipovich, Leonard | Hidalgo, Bertha | Fox, Keolu | Huffman, Jennifer E | An, Ping | Lu, Yingchang | Rasmussen-Torvik, Laura J | Grarup, Niels | Ehm, Margaret G | Li, Li | Baldridge, Abigail S | Stančáková, Alena | Abrol, Ravinder | Besse, Céline | Boland, Anne | Bork-Jensen, Jette | Fornage, Myriam | Freitag, Daniel F | Garcia, Melissa E | Guo, Xiuqing | Hara, Kazuo | Isaacs, Aaron | Jakobsdottir, Johanna | Lange, Leslie A | Layton, Jill C | Li, Man | Hua Zhao, Jing | Meidtner, Karina | Morrison, Alanna C | Nalls, Mike A | Peters, Marjolein J | Sabater-Lleal, Maria | Schurmann, Claudia | Silveira, Angela | Smith, Albert V | Southam, Lorraine | Stoiber, Marcus H | Strawbridge, Rona J | Taylor, Kent D | Varga, Tibor V | Allin, Kristine H | Amin, Najaf | Aponte, Jennifer L | Aung, Tin | Barbieri, Caterina | Bihlmeyer, Nathan A | Boehnke, Michael | Bombieri, Cristina | Bowden, Donald W | Burns, Sean M | Chen, Yuning | Chen, Yii-DerI | Cheng, Ching-Yu | Correa, Adolfo | Czajkowski, Jacek | Dehghan, Abbas | Ehret, Georg B | Eiriksdottir, Gudny | Escher, Stefan A | Farmaki, Aliki-Eleni | Frånberg, Mattias | Gambaro, Giovanni | Giulianini, Franco | Goddard, William A | Goel, Anuj | Gottesman, Omri | Grove, Megan L | Gustafsson, Stefan | Hai, Yang | Hallmans, Göran | Heo, Jiyoung | Hoffmann, Per | Ikram, Mohammad K | Jensen, Richard A | Jørgensen, Marit E | Jørgensen, Torben | Karaleftheri, Maria | Khor, Chiea C | Kirkpatrick, Andrea | Kraja, Aldi T | Kuusisto, Johanna | Lange, Ethan M | Lee, I T | Lee, Wen-Jane | Leong, Aaron | Liao, Jiemin | Liu, Chunyu | Liu, Yongmei | Lindgren, Cecilia M | Linneberg, Allan | Malerba, Giovanni | Mamakou, Vasiliki | Marouli, Eirini | Maruthur, Nisa M | Matchan, Angela | McKean-Cowdin, Roberta | McLeod, Olga | Metcalf, Ginger A | Mohlke, Karen L | Muzny, Donna M | Ntalla, Ioanna | Palmer, Nicholette D | Pasko, Dorota | Peter, Andreas | Rayner, Nigel W | Renström, Frida | Rice, Ken | Sala, Cinzia F | Sennblad, Bengt | Serafetinidis, Ioannis | Smith, Jennifer A | Soranzo, Nicole | Speliotes, Elizabeth K | Stahl, Eli A | Stirrups, Kathleen | Tentolouris, Nikos | Thanopoulou, Anastasia | Torres, Mina | Traglia, Michela | Tsafantakis, Emmanouil | Javad, Sundas | Yanek, Lisa R | Zengini, Eleni | Becker, Diane M | Bis, Joshua C | Brown, James B | Adrienne Cupples, L | Hansen, Torben | Ingelsson, Erik | Karter, Andrew J | Lorenzo, Carlos | Mathias, Rasika A | Norris, Jill M | Peloso, Gina M | Sheu, Wayne H.-H. | Toniolo, Daniela | Vaidya, Dhananjay | Varma, Rohit | Wagenknecht, Lynne E | Boeing, Heiner | Bottinger, Erwin P | Dedoussis, George | Deloukas, Panos | Ferrannini, Ele | Franco, Oscar H | Franks, Paul W | Gibbs, Richard A | Gudnason, Vilmundur | Hamsten, Anders | Harris, Tamara B | Hattersley, Andrew T | Hayward, Caroline | Hofman, Albert | Jansson, Jan-Håkan | Langenberg, Claudia | Launer, Lenore J | Levy, Daniel | Oostra, Ben A | O'Donnell, Christopher J | O'Rahilly, Stephen | Padmanabhan, Sandosh | Pankow, James S | Polasek, Ozren | Province, Michael A | Rich, Stephen S | Ridker, Paul M | Rudan, Igor | Schulze, Matthias B | Smith, Blair H | Uitterlinden, André G | Walker, Mark | Watkins, Hugh | Wong, Tien Y | Zeggini, Eleftheria | Laakso, Markku | Borecki, Ingrid B | Chasman, Daniel I | Pedersen, Oluf | Psaty, Bruce M | Shyong Tai, E | van Duijn, Cornelia M | Wareham, Nicholas J | Waterworth, Dawn M | Boerwinkle, Eric | Linda Kao, W H | Florez, Jose C | Loos, Ruth J.F. | Wilson, James G | Frayling, Timothy M | Siscovick, David S | Dupuis, Josée | Rotter, Jerome I | Meigs, James B | Scott, Robert A | Goodarzi, Mark O
Nature Communications  2015;6:5897.
Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=−0.09±0.01 mmol l−1, P=3.4 × 10−12), T2D risk (OR[95%CI]=0.86[0.76–0.96], P=0.010), early insulin secretion (β=−0.07±0.035 pmolinsulin mmolglucose−1, P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l−1, P=4.3 × 10−4). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10−6) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l−1, P=1.3 × 10−8). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
Both rare and common variants contribute to the aetiology of complex traits such as type 2 diabetes (T2D). Here, the authors examine the effect of coding variation on glycaemic traits and T2D, and identify low-frequency variation in GLP1R significantly associated with these traits.
PMCID: PMC4311266  PMID: 25631608
25.  Air Pollution and Percent Emphysema Identified by Computed Tomography in the Multi-Ethnic Study of Atherosclerosis 
Environmental Health Perspectives  2014;123(2):144-151.
Background: Air pollution is linked to low lung function and to respiratory events, yet little is known of associations with lung structure.
Objectives: We examined associations of particulate matter (PM2.5, PM10) and nitrogen oxides (NOx) with percent emphysema-like lung on computed tomography (CT).
Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) recruited participants (45–84 years of age) in six U.S. states. Percent emphysema was defined as lung regions < –910 Hounsfield Units on cardiac CT scans acquired following a highly standardized protocol. Spirometry was also conducted on a subset. Individual-level 1- and 20-year average air pollution exposures were estimated using spatiotemporal models that included cohort-specific measurements. Multivariable regression was conducted to adjust for traditional risk factors and study location.
Results: Among 6,515 participants, we found evidence of an association between percent emphysema and long-term pollution concentrations in an analysis leveraging between-city exposure contrasts. Higher concentrations of PM2.5 (5 μg/m3) and NOx (25 ppb) over the previous year were associated with 0.6 (95% CI: 0.1, 1.2%) and 0.5 (95% CI: 0.1, 0.9%) higher average percent emphysema, respectively. However, after adjustment for study site the associations were –0.6% (95% CI: –1.5, 0.3%) for PM2.5 and –0.5% (95% CI: –1.1, 0.02%) for NOx. Lower lung function measures (FEV1 and FVC) were associated with higher PM2.5 and NOx levels in 3,791 participants before and after adjustment for study site, though most associations were not statistically significant.
Conclusions: Associations between ambient air pollution and percentage of emphysema-like lung were inconclusive in this cross-sectional study, thus longitudinal analyses may better clarify these associations with percent emphysema.
Citation: Adar SD, Kaufman JD, Diez-Roux AV, Hoffman EA, D’Souza J, Stukovsky KH, Rich SS, Rotter JI, Guo X, Raffel LJ, Sampson PD, Oron AP, Raghunathan T, Barr RG. 2015. Air pollution and percent emphysema identified by computed tomography in the Multi-Ethnic Study of Atherosclerosis. Environ Health Perspect 123:144–151;
PMCID: PMC4314244  PMID: 25302408

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