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Featured researches published by Kari E. North.


The New England Journal of Medicine | 2014

Loss-of-Function Mutations in APOC3, Triglycerides, and Coronary Disease

Jacy R. Crosby; Gina M. Peloso; Paul L. Auer; David R. Crosslin; Nathan O. Stitziel; Leslie A. Lange; Yingchang Lu; Zheng-zheng Tang; He Zhang; George Hindy; Nicholas G. D. Masca; Kathleen Stirrups; Stavroula Kanoni; Ron Do; Goo Jun; Youna Hu; Hyun Min Kang; Chenyi Xue; Anuj Goel; Martin Farrall; Stefano Duga; Pier Angelica Merlini; Rosanna Asselta; Domenico Girelli; Nicola Martinelli; Wu Yin; Dermot F. Reilly; Elizabeth K. Speliotes; Caroline S. Fox; Kristian Hveem

BACKGROUND Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype. METHODS We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons. RESULTS An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)). CONCLUSIONS Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).


Nature Genetics | 2010

Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function

Dana B. Hancock; Mark Eijgelsheim; Jemma B. Wilk; Sina A. Gharib; Laura R. Loehr; Kristin D. Marciante; Nora Franceschini; Yannick M.T.A. van Durme; Ting Hsu Chen; R. Graham Barr; Matthew B. Schabath; David Couper; Guy Brusselle; Bruce M. Psaty; Cornelia M. van Duijn; Jerome I. Rotter; André G. Uitterlinden; Albert Hofman; Naresh M. Punjabi; Fernando Rivadeneira; Alanna C. Morrison; Paul L. Enright; Kari E. North; Susan R. Heckbert; Thomas Lumley; Bruno H. Stricker; George T. O'Connor; Stephanie J. London

Spirometric measures of lung function are heritable traits that reflect respiratory health and predict morbidity and mortality. We meta-analyzed genome-wide association studies for two clinically important lung-function measures: forced expiratory volume in the first second (FEV1) and its ratio to forced vital capacity (FEV1/FVC), an indicator of airflow obstruction. This meta-analysis included 20,890 participants of European ancestry from four CHARGE Consortium studies: Atherosclerosis Risk in Communities, Cardiovascular Health Study, Framingham Heart Study and Rotterdam Study. We identified eight loci associated with FEV1/FVC (HHIP, GPR126, ADAM19, AGER-PPT2, FAM13A, PTCH1, PID1 and HTR4) and one locus associated with FEV1 (INTS12-GSTCD-NPNT) at or near genome-wide significance (P < 5 × 10−8) in the CHARGE Consortium dataset. Our findings may offer insights into pulmonary function and pathogenesis of chronic lung disease.


PLOS Genetics | 2009

NRXN3 Is a Novel Locus for Waist Circumference: A Genome-Wide Association Study from the CHARGE Consortium

Nancy L. Heard-Costa; M. Carola Zillikens; Keri L. Monda; Åsa Johansson; Tamara B. Harris; Mao Fu; Talin Haritunians; Mary F. Feitosa; Thor Aspelund; Gudny Eiriksdottir; Melissa Garcia; Lenore J. Launer; Albert V. Smith; Braxton D. Mitchell; Patrick F. McArdle; Alan R. Shuldiner; Suzette J. Bielinski; Eric Boerwinkle; Fred Brancati; Ellen W. Demerath; James S. Pankow; Alice M. Arnold; Yii-Der I. Chen; Nicole L. Glazer; Barbara McKnight; Bruce M. Psaty; Jerome I. Rotter; Najaf Amin; Harry Campbell; Ulf Gyllensten

Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4×10−7)]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3×10−8 for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4×10−6, 0.024 z-score units (0.10 kg/m2) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07–1.19; p = 3.2×10−5 per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.


European Heart Journal | 2015

Mendelian randomization of blood lipids for coronary heart disease.

Michael V. Holmes; Folkert W. Asselbergs; Tom Palmer; Fotios Drenos; Matthew B. Lanktree; Christopher P. Nelson; Caroline Dale; Sandosh Padmanabhan; Chris Finan; Daniel I. Swerdlow; Vinicius Tragante; Erik P A Van Iperen; Suthesh Sivapalaratnam; Sonia Shah; Clara C. Elbers; Tina Shah; Jorgen Engmann; Claudia Giambartolomei; Jon White; Delilah Zabaneh; Reecha Sofat; Stela McLachlan; Pieter A. Doevendans; Anthony J. Balmforth; Alistair S. Hall; Kari E. North; Berta Almoguera; Ron C. Hoogeveen; Mary Cushman; Myriam Fornage

Aims To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. Methods and results We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10−6); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). Conclusion The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.


Diabetes | 2011

A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium

Aldi T. Kraja; Dhananjay Vaidya; James S. Pankow; Mark O. Goodarzi; Themistocles L. Assimes; Iftikhar J. Kullo; Ulla Sovio; Rasika A. Mathias; Yan V. Sun; Nora Franceschini; Devin Absher; Guo Li; Qunyuan Zhang; Mary F. Feitosa; Nicole L. Glazer; Talin Haritunians; Anna Liisa Hartikainen; Joshua W. Knowles; Kari E. North; Carlos Iribarren; Brian G. Kral; Lisa R. Yanek; Paul F. O'Reilly; Mark McCarthy; David Couper; Aravinda Chakravarti; Bruce M. Psaty; Lewis C. Becker; Michael A. Province; Eric Boerwinkle

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.


WOS | 2011

A Bivariate Genome-Wide Approach to Metabolic Syndrome STAMPEED Consortium

Aldi T. Kraja; Dhananjay Vaidya; James S. Pankow; Mark O. Goodarzi; Themistocles L. Assimes; Iftikhar J. Kullo; Ulla Sovio; Rasika A. Mathias; Yan V. Sun; Nora Franceschini; Devin Absher; Guo Li; Qunyuan Zhang; Mary F. Feitosa; Nicole L. Glazer; Talin Haritunians; Anna-Liisa Hartikainen; Joshua W. Knowles; Kari E. North; Carlos Iribarren; Brian G. Kral; Lisa R. Yanek; Mark McCarthy; David Couper; Aravinda Chakravarti; Bruce M. Psaty; Lewis C. Becker; Michael A. Province; Eric Boerwinkle; Thomas Quertermous

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.


Human Molecular Genetics | 2013

Exploring the genetic basis of chronic periodontitis: a genome-wide association study

Kimon Divaris; Keri L. Monda; Kari E. North; Andrew F. Olshan; Lindsay M. Reynolds; Wen Chi Hsueh; Ethan M. Lange; Kevin Moss; Silvana P. Barros; Robert J. Weyant; Yongmei Liu; Anne B. Newman; James D. Beck; Steven Offenbacher

Chronic periodontitis (CP) is a common oral disease that confers substantial systemic inflammatory and microbial burden and is a major cause of tooth loss. Here, we present the results of a genome-wide association study of CP that was carried out in a cohort of 4504 European Americans (EA) participating in the Atherosclerosis Risk in Communities (ARIC) Study (mean age—62 years, moderate CP—43% and severe CP—17%). We detected no genome-wide significant association signals for CP; however, we found suggestive evidence of association (P < 5 × 10−6) for six loci, including NIN, NPY, WNT5A for severe CP and NCR2, EMR1, 10p15 for moderate CP. Three of these loci had concordant effect size and direction in an independent sample of 656 adult EA participants of the Health, Aging, and Body Composition (Health ABC) Study. Meta-analysis pooled estimates were severe CP (n = 958 versus health: n = 1909)—NPY, rs2521634 [G]: odds ratio [OR = 1.49 (95% confidence interval (CI = 1.28–1.73, P = 3.5 × 10−7))]; moderate CP (n = 2293)—NCR2, rs7762544 [G]: OR = 1.40 (95% CI = 1.24–1.59, P = 7.5 × 10−8), EMR1, rs3826782 [A]: OR = 2.01 (95% CI = 1.52–2.65, P = 8.2 × 10−7). Canonical pathway analysis indicated significant enrichment of nervous system signaling, cellular immune response and cytokine signaling pathways. A significant interaction of NUAK1 (rs11112872, interaction P = 2.9 × 10−9) with smoking in ARIC was not replicated in Health ABC, although estimates of heritable variance in severe CP explained by all single nucleotide polymorphisms increased from 18 to 52% with the inclusion of a genome-wide interaction term with smoking. These genome-wide association results provide information on multiple candidate regions and pathways for interrogation in future genetic studies of CP.


Human Molecular Genetics | 2015

Epigenome-wide Association Study (EWAS) of BMI, BMI Change, and Waist Circumference in African American Adults Identifies Multiple Replicated Loci

Ellen W. Demerath; Weihua Guan; Megan L. Grove; Stella Aslibekyan; Michael M. Mendelson; Yi Hui Zhou; Åsa K. Hedman; Johanna K. Sandling; Li An Li; Marguerite R. Irvin; Degui Zhi; Panos Deloukas; Liming Liang; Chunyu Liu; Jan Bressler; Tim D. Spector; Kari E. North; Yun Li; Devin Absher; Daniel Levy; Donna K. Arnett; Myriam Fornage; James S. Pankow; Eric Boerwinkle

Obesity is an important component of the pathophysiology of chronic diseases. Identifying epigenetic modifications associated with elevated adiposity, including DNA methylation variation, may point to genomic pathways that are dysregulated in numerous conditions. The Illumina 450K Bead Chip array was used to assay DNA methylation in leukocyte DNA obtained from 2097 African American adults in the Atherosclerosis Risk in Communities (ARIC) study. Mixed-effects regression models were used to test the association of methylation beta value with concurrent body mass index (BMI) and waist circumference (WC), and BMI change, adjusting for batch effects and potential confounders. Replication using whole-blood DNA from 2377 White adults in the Framingham Heart Study and CD4+ T cell DNA from 991 Whites in the Genetics of Lipid Lowering Drugs and Diet Network Study was followed by testing using adipose tissue DNA from 648 women in the Multiple Tissue Human Expression Resource cohort. Seventy-six BMI-related probes, 164 WC-related probes and 8 BMI change-related probes passed the threshold for significance in ARIC (P < 1 × 10(-7); Bonferroni), including probes in the recently reported HIF3A, CPT1A and ABCG1 regions. Replication using blood DNA was achieved for 37 BMI probes and 1 additional WC probe. Sixteen of these also replicated in adipose tissue, including 15 novel methylation findings near genes involved in lipid metabolism, immune response/cytokine signaling and other diverse pathways, including LGALS3BP, KDM2B, PBX1 and BBS2, among others. Adiposity traits are associated with DNA methylation at numerous CpG sites that replicate across studies despite variation in tissue type, ethnicity and analytic approaches.


American Journal of Epidemiology | 2011

The Next PAGE in Understanding Complex Traits: Design for the Analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study

Tara C. Matise; José Luis Ambite; Steven Buyske; Christopher S. Carlson; Shelley A. Cole; Dana C. Crawford; Christopher A. Haiman; Gerardo Heiss; Charles Kooperberg; Loic Le Marchand; Teri A. Manolio; Kari E. North; Ulrike Peters; Marylyn D. Ritchie; Lucia A. Hindorff; Jonathan L. Haines

Genetic studies have identified thousands of variants associated with complex traits. However, most association studies are limited to populations of European descent and a single phenotype. The Population Architecture using Genomics and Epidemiology (PAGE) Study was initiated in 2008 by the National Human Genome Research Institute to investigate the epidemiologic architecture of well-replicated genetic variants associated with complex diseases in several large, ethnically diverse population-based studies. Combining DNA samples and hundreds of phenotypes from multiple cohorts, PAGE is well-suited to address generalization of associations and variability of effects in diverse populations; identify genetic and environmental modifiers; evaluate disease subtypes, intermediate phenotypes, and biomarkers; and investigate associations with novel phenotypes. PAGE investigators harmonize phenotypes across studies where possible and perform coordinated cohort-specific analyses and meta-analyses. PAGE researchers are genotyping thousands of genetic variants in up to 121,000 DNA samples from African-American, white, Hispanic/Latino, Asian/Pacific Islander, and American Indian participants. Initial analyses will focus on single nucleotide polymorphisms (SNPs) associated with obesity, lipids, cardiovascular disease, type 2 diabetes, inflammation, various cancers, and related biomarkers. PAGE SNPs are also assessed for pleiotropy using the “phenome-wide association study” approach, testing each SNP for associations with hundreds of phenotypes. PAGE data will be deposited into the National Center for Biotechnology Informations Database of Genotypes and Phenotypes and made available via a custom browser.


PLOS Genetics | 2011

Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study

Logan Dumitrescu; Cara L. Carty; Kira C. Taylor; Fredrick R. Schumacher; Lucia A. Hindorff; José Luis Ambite; Garnet L. Anderson; Lyle G. Best; Kristin Brown-Gentry; Petra Bůžková; Christopher S. Carlson; Barbara Cochran; Shelley A. Cole; Richard B. Devereux; Dave Duggan; Charles B. Eaton; Myriam Fornage; Nora Franceschini; Jeff Haessler; Barbara V. Howard; Karen C. Johnson; Sandra Laston; Laurence N. Kolonel; Elisa T. Lee; Jean W. MacCluer; Teri A. Manolio; Sarah A. Pendergrass; Miguel Quibrera; Ralph V. Shohet; Lynne R. Wilkens

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.

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Nora Franceschini

University of North Carolina at Chapel Hill

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Eric Boerwinkle

University of Texas Health Science Center at Houston

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Lucia A. Hindorff

National Institutes of Health

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Gerardo Heiss

University of North Carolina at Chapel Hill

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Shelley A. Cole

Texas Biomedical Research Institute

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Lyle G. Best

Turtle Mountain Community College

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Mariaelisa Graff

University of North Carolina at Chapel Hill

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Jean W. MacCluer

Texas Biomedical Research Institute

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Alex P. Reiner

University of Washington

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