Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Ioanna Ntalla is active.

Publication


Featured researches published by Ioanna Ntalla.


The Lancet Respiratory Medicine | 2015

Novel insights into the genetics of smoking behaviour, lung function, and chronic obstructive pulmonary disease (UK BiLEVE): a genetic association study in UK Biobank.

Louise V. Wain; Nick Shrine; Suzanne Miller; Victoria E. Jackson; Ioanna Ntalla; María Soler Artigas; Charlotte K. Billington; Abdul Kader Kheirallah; Richard J. Allen; James P. Cook; Kelly Probert; Ma'en Obeidat; Yohan Bossé; Ke Hao; Dirkje S. Postma; Peter D. Paré; Adaikalavan Ramasamy; Reedik Mägi; Evelin Mihailov; Eva Reinmaa; Erik Melén; Jared O'Connell; Eleni Frangou; Olivier Delaneau; Colin Freeman; Desislava Petkova; Mark I. McCarthy; Ian Sayers; Panos Deloukas; Richard Hubbard

Summary Background Understanding the genetic basis of airflow obstruction and smoking behaviour is key to determining the pathophysiology of chronic obstructive pulmonary disease (COPD). We used UK Biobank data to study the genetic causes of smoking behaviour and lung health. Methods We sampled individuals of European ancestry from UK Biobank, from the middle and extremes of the forced expiratory volume in 1 s (FEV1) distribution among heavy smokers (mean 35 pack-years) and never smokers. We developed a custom array for UK Biobank to provide optimum genome-wide coverage of common and low-frequency variants, dense coverage of genomic regions already implicated in lung health and disease, and to assay rare coding variants relevant to the UK population. We investigated whether there were shared genetic causes between different phenotypes defined by extremes of FEV1. We also looked for novel variants associated with extremes of FEV1 and smoking behaviour and assessed regions of the genome that had already shown evidence for a role in lung health and disease. We set genome-wide significance at p<5 × 10−8. Findings UK Biobank participants were recruited from March 15, 2006, to July 7, 2010. Sample selection for the UK BiLEVE study started on Nov 22, 2012, and was completed on Dec 20, 2012. We selected 50 008 unique samples: 10 002 individuals with low FEV1, 10 000 with average FEV1, and 5002 with high FEV1 from each of the heavy smoker and never smoker groups. We noted a substantial sharing of genetic causes of low FEV1 between heavy smokers and never smokers (p=2·29 × 10−16) and between individuals with and without doctor-diagnosed asthma (p=6·06 × 10−11). We discovered six novel genome-wide significant signals of association with extremes of FEV1, including signals at four novel loci (KANSL1, TSEN54, TET2, and RBM19/TBX5) and independent signals at two previously reported loci (NPNT and HLA-DQB1/HLA-DQA2). These variants also showed association with COPD, including in individuals with no history of smoking. The number of copies of a 150 kb region containing the 5′ end of KANSL1, a gene that is important for epigenetic gene regulation, was associated with extremes of FEV1. We also discovered five new genome-wide significant signals for smoking behaviour, including a variant in NCAM1 (chromosome 11) and a variant on chromosome 2 (between TEX41 and PABPC1P2) that has a trans effect on expression of NCAM1 in brain tissue. Interpretation By sampling from the extremes of the lung function distribution in UK Biobank, we identified novel genetic causes of lung function and smoking behaviour. These results provide new insight into the specific mechanisms underlying airflow obstruction, COPD, and tobacco addiction, and show substantial shared genetic architecture underlying airflow obstruction across individuals, irrespective of smoking behaviour and other airway disease. Funding Medical Research Council.


Nature Genetics | 2017

Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk.

Helen R. Warren; Evangelos Evangelou; Claudia P. Cabrera; He Gao; Meixia Ren; Borbala Mifsud; Ioanna Ntalla; Praveen Surendran; Chunyu Liu; James P. Cook; Aldi T. Kraja; Fotios Drenos; Marie Loh; Niek Verweij; Jonathan Marten; Ibrahim Karaman; Marcelo Segura Lepe; Paul F. O'Reilly; Joanne Knight; Harold Snieder; Norihiro Kato; Jiang He; E. Shyong Tai; M. Abdullah Said; David J. Porteous; Maris Alver; Neil Poulter; Martin Farrall; Ron T. Gansevoort; Sandosh Padmanabhan

Elevated blood pressure is the leading heritable risk factor for cardiovascular disease worldwide. We report genetic association of blood pressure (systolic, diastolic, pulse pressure) among UK Biobank participants of European ancestry with independent replication in other cohorts, and robust validation of 107 independent loci. We also identify new independent variants at 11 previously reported blood pressure loci. In combination with results from a range of in silico functional analyses and wet bench experiments, our findings highlight new biological pathways for blood pressure regulation enriched for genes expressed in vascular tissues and identify potential therapeutic targets for hypertension. Results from genetic risk score models raise the possibility of a precision medicine approach through early lifestyle intervention to offset the impact of blood pressure–raising genetic variants on future cardiovascular disease risk.


Diabetes | 2011

Association of Genetic Loci With Glucose Levels in Childhood and Adolescence: A Meta-Analysis of Over 6,000 Children

Adam Barker; Stephen J. Sharp; Nicholas J. Timpson; Nabila Bouatia-Naji; Nicole M. Warrington; Stavroula Kanoni; Lawrence J. Beilin; Soren Brage; Panos Deloukas; David Evans; Anders Grøntved; Neelam Hassanali; Debbie A. Lawlor; Cécile Lecoeur; Ruth J. F. Loos; Stephen J. Lye; Mark McCarthy; Trevor A. Mori; Ndeye Coumba Ndiaye; John P. Newnham; Ioanna Ntalla; Craig E. Pennell; Beate St Pourcain; Inga Prokopenko; Susan M. Ring; Naveed Sattar; Sophie Visvikis-Siest; George Dedoussis; Lyle J. Palmer; Philippe Froguel

OBJECTIVE To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents. RESEARCH DESIGN AND METHODS A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9–16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose. RESULTS Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021–0.031) for each unit increase in the score. CONCLUSIONS Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.


Diabetic Medicine | 2011

Association of genetic Loci with glucose levels in childhood and adolescence

Adam Barker; Stephen J. Sharp; Nicholas J. Timpson; Nabila Bouatia-Naji; Nicole M. Warrington; Stavroula Kanoni; Lawrence J. Beilin; Soren Brage; Panos Deloukas; David Evans; Anders Grøntved; Neelam Hassanali; Debbie A. Lawlor; Cécile Lecoeur; Ruth J. F. Loos; Stephen J. Lye; Mark McCarthy; Trevor A. Mori; Ndeye Coumba Ndiaye; John P. Newnham; Ioanna Ntalla; Craig E. Pennell; M U B St Pourcain; Inga Prokopenko; Susan M. Ring; Naveed Sattar; Sophie Visvikis-Siest; George Dedoussis; Lyle J. Palmer; Philippe Froguel

OBJECTIVE To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents. RESEARCH DESIGN AND METHODS A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9–16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose. RESULTS Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021–0.031) for each unit increase in the score. CONCLUSIONS Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.


American Journal of Epidemiology | 2013

Meta-Analysis Investigating Associations Between Healthy Diet and Fasting Glucose and Insulin Levels and Modification by Loci Associated With Glucose Homeostasis in Data From 15 Cohorts

Jennifer A. Nettleton; Marie-France Hivert; Rozenn N. Lemaitre; Nicola M. McKeown; Dariush Mozaffarian; Toshiko Tanaka; Mary K. Wojczynski; Adela Hruby; Luc Djoussé; Julius S. Ngwa; Jack L. Follis; Maria Dimitriou; Andrea Ganna; Denise K. Houston; Stavroula Kanoni; Vera Mikkilä; Ani Manichaikul; Ioanna Ntalla; Frida Renström; Emily Sonestedt; Frank J. A. van Rooij; Stefania Bandinelli; Lawrence de Koning; Ulrika Ericson; Neelam Hassanali; Jessica C. Kiefte-de Jong; Kurt Lohman; Olli T. Raitakari; Constantina Papoutsakis; Per Sjögren

Whether loci that influence fasting glucose (FG) and fasting insulin (FI) levels, as identified by genome-wide association studies, modify associations of diet with FG or FI is unknown. We utilized data from 15 U.S. and European cohort studies comprising 51,289 persons without diabetes to test whether genotype and diet interact to influence FG or FI concentration. We constructed a diet score using study-specific quartile rankings for intakes of whole grains, fish, fruits, vegetables, and nuts/seeds (favorable) and red/processed meats, sweets, sugared beverages, and fried potatoes (unfavorable). We used linear regression within studies, followed by inverse-variance-weighted meta-analysis, to quantify 1) associations of diet score with FG and FI levels and 2) interactions of diet score with 16 FG-associated loci and 2 FI-associated loci. Diet score (per unit increase) was inversely associated with FG (β = -0.004 mmol/L, 95% confidence interval: -0.005, -0.003) and FI (β = -0.008 ln-pmol/L, 95% confidence interval: -0.009, -0.007) levels after adjustment for demographic factors, lifestyle, and body mass index. Genotype variation at the studied loci did not modify these associations. Healthier diets were associated with lower FG and FI concentrations regardless of genotype at previously replicated FG- and FI-associated loci. Studies focusing on genomic regions that do not yield highly statistically significant associations from main-effect genome-wide association studies may be more fruitful in identifying diet-gene interactions.


Journal of Nutrition | 2013

Higher Magnesium Intake Is Associated with Lower Fasting Glucose and Insulin, with No Evidence of Interaction with Select Genetic Loci, in a Meta-Analysis of 15 CHARGE Consortium Studies

Adela Hruby; Julius S. Ngwa; Frida Renström; Mary K. Wojczynski; Andrea Ganna; Göran Hallmans; Denise K. Houston; Paul F. Jacques; Stavroula Kanoni; Terho Lehtimäki; Rozenn N. Lemaitre; Ani Manichaikul; Kari E. North; Ioanna Ntalla; Emily Sonestedt; Toshiko Tanaka; Frank J. A. van Rooij; Stefania Bandinelli; Luc Djoussé; Efi Grigoriou; Ingegerd Johansson; Kurt Lohman; James S. Pankow; Olli T. Raitakari; Ulf Risérus; Mary Yannakoulia; M. Carola Zillikens; Neelam Hassanali; Yongmei Liu; Dariush Mozaffarian

Favorable associations between magnesium intake and glycemic traits, such as fasting glucose and insulin, are observed in observational and clinical studies, but whether genetic variation affects these associations is largely unknown. We hypothesized that single nucleotide polymorphisms (SNPs) associated with either glycemic traits or magnesium metabolism affect the association between magnesium intake and fasting glucose and insulin. Fifteen studies from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided data from up to 52,684 participants of European descent without known diabetes. In fixed-effects meta-analyses, we quantified 1) cross-sectional associations of dietary magnesium intake with fasting glucose (mmol/L) and insulin (ln-pmol/L) and 2) interactions between magnesium intake and SNPs related to fasting glucose (16 SNPs), insulin (2 SNPs), or magnesium (8 SNPs) on fasting glucose and insulin. After adjustment for age, sex, energy intake, BMI, and behavioral risk factors, magnesium (per 50-mg/d increment) was inversely associated with fasting glucose [β = -0.009 mmol/L (95% CI: -0.013, -0.005), P < 0.0001] and insulin [-0.020 ln-pmol/L (95% CI: -0.024, -0.017), P < 0.0001]. No magnesium-related SNP or interaction between any SNP and magnesium reached significance after correction for multiple testing. However, rs2274924 in magnesium transporter-encoding TRPM6 showed a nominal association (uncorrected P = 0.03) with glucose, and rs11558471 in SLC30A8 and rs3740393 near CNNM2 showed a nominal interaction (uncorrected, both P = 0.02) with magnesium on glucose. Consistent with other studies, a higher magnesium intake was associated with lower fasting glucose and insulin. Nominal evidence of TRPM6 influence and magnesium interaction with select loci suggests that further investigation is warranted.


Diabetes | 2015

Dietary Intake, FTO genetic variants, and adiposity: A combined analysis of over 16,000 children and adolescents

Qibin Qi; Mary K. Downer; Tuomas O. Kilpeläinen; H. Rob Taal; Sheila J. Barton; Ioanna Ntalla; Marie Standl; Vesna Boraska; Ville Huikari; Jessica C. Kiefte-de Jong; Antje Körner; Timo A. Lakka; Gaifen Liu; Jessica Magnusson; Masayuki Okuda; Olli T. Raitakari; Rebecca C Richmond; Robert A. Scott; Mark E.S. Bailey; Kathrin Scheuermann; John W. Holloway; Hazel Inskip; Carmen R. Isasi; Yasmin Mossavar-Rahmani; Vincent W. V. Jaddoe; Jaana Laitinen; Virpi Lindi; Erik Melén; Yannis Pitsiladis; Niina Pitkänen

The FTO gene harbors variation with the strongest effect on adiposity and obesity risk. Previous data support a role for FTO variation in influencing food intake. We conducted a combined analysis of 16,094 boys and girls aged 1–18 years from 14 studies to examine the following: 1) the association between the FTO rs9939609 variant (or a proxy) and total energy and macronutrient intake; and 2) the interaction between the FTO variant and dietary intake, and the effect on BMI. We found that the BMI-increasing allele (minor allele) of the FTO variant was associated with increased total energy intake (effect per allele = 14.3 kcal/day [95% CI 5.9, 22.7 kcal/day], P = 6.5 × 10−4), but not with protein, carbohydrate, or fat intake. We also found that protein intake modified the association between the FTO variant and BMI (interactive effect per allele = 0.08 SD [0.03, 0.12 SD], P for interaction = 7.2 × 10−4): the association between FTO genotype and BMI was much stronger in individuals with high protein intake (effect per allele = 0.10 SD [0.07, 0.13 SD], P = 8.2 × 10−10) than in those with low intake (effect per allele = 0.04 SD [0.01, 0.07 SD], P = 0.02). Our results suggest that the FTO variant that confers a predisposition to higher BMI is associated with higher total energy intake, and that lower dietary protein intake attenuates the association between FTO genotype and adiposity in children and adolescents.


Nature Communications | 2015

Sixteen new lung function signals identified through 1000 Genomes Project reference panel imputation.

María Soler Artigas; Louise V. Wain; Suzanne Miller; Abdul Kader Kheirallah; Jennifer E. Huffman; Ioanna Ntalla; Nick Shrine; Ma’en Obeidat; Holly Trochet; Wendy L. McArdle; Alexessander Couto Alves; Jennie Hui; Jing Hua Zhao; Peter K. Joshi; Alexander Teumer; Eva Albrecht; Medea Imboden; Rajesh Rawal; Lorna M. Lopez; Jonathan Marten; Stefan Enroth; Ida Surakka; Ozren Polasek; Leo-Pekka Lyytikäinen; Raquel Granell; Pirro G. Hysi; Claudia Flexeder; Anubha Mahajan; John Beilby; Yohan Bossé

Lung function measures are used in the diagnosis of chronic obstructive pulmonary disease. In 38,199 European ancestry individuals, we studied genome-wide association of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC with 1000 Genomes Project (phase 1)-imputed genotypes and followed up top associations in 54,550 Europeans. We identify 14 novel loci (P<5 × 10−8) in or near ENSA, RNU5F-1, KCNS3, AK097794, ASTN2, LHX3, CCDC91, TBX3, TRIP11, RIN3, TEKT5, LTBP4, MN1 and AP1S2, and two novel signals at known loci NPNT and GPR126, providing a basis for new understanding of the genetic determinants of these traits and pulmonary diseases in which they are altered.


American Journal of Medical Genetics | 2012

Genome-Wide Association Analysis of Eating Disorder-Related Symptoms, Behaviors, and Personality Traits

Vesna Boraska; Oliver S. P. Davis; Lynn Cherkas; Sietske G. Helder; Juliette Harris; Isabel Krug; Thomas Pei-Chi Liao; Janet Treasure; Ioanna Ntalla; Leila Karhunen; Anna Keski-Rahkonen; Danai Christakopoulou; Anu Raevuori; So-Youn Shin; George V. Dedoussis; Jaakko Kaprio; Nicole Soranzo; Tim D. Spector; David A. Collier; Eleftheria Zeggini

Eating disorders (EDs) are common, complex psychiatric disorders thought to be caused by both genetic and environmental factors. They share many symptoms, behaviors, and personality traits, which may have overlapping heritability. The aim of the present study is to perform a genome‐wide association scan (GWAS) of six ED phenotypes comprising three symptom traits from the Eating Disorders Inventory 2 [Drive for Thinness (DT), Body Dissatisfaction (BD), and Bulimia], Weight Fluctuation symptom, Breakfast Skipping behavior and Childhood Obsessive‐Compulsive Personality Disorder trait (CHIRP). Investigated traits were derived from standardized self‐report questionnaires completed by the TwinsUK population‐based cohort. We tested 283,744 directly typed SNPs across six phenotypes of interest in the TwinsUK discovery dataset and followed‐up signals from various strata using a two‐stage replication strategy in two independent cohorts of European ancestry. We meta‐analyzed a total of 2,698 individuals for DT, 2,680 for BD, 2,789 (821 cases/1,968 controls) for Bulimia, 1,360 (633 cases/727 controls) for Childhood Obsessive‐Compulsive Personality Disorder trait, 2,773 (761 cases/2,012 controls) for Breakfast Skipping, and 2,967 (798 cases/2,169 controls) for Weight Fluctuation symptom. In this GWAS analysis of six ED‐related phenotypes, we detected association of eight genetic variants with P < 10−5. Genetic variants that showed suggestive evidence of association were previously associated with several psychiatric disorders and ED‐related phenotypes. Our study indicates that larger‐scale collaborative studies will be needed to achieve the necessary power to detect loci underlying ED‐related traits.


Nature Communications | 2014

Genetic characterization of Greek population isolates reveals strong genetic drift at missense and trait-associated variants

Kalliope Panoutsopoulou; Konstantinos Hatzikotoulas; Dionysia K. Xifara; Vincenza Colonna; Aliki-Eleni Farmaki; Graham R. S. Ritchie; Lorraine Southam; Arthur Gilly; Ioanna Tachmazidou; Segun Fatumo; Angela Matchan; Nigel W. Rayner; Ioanna Ntalla; Massimo Mezzavilla; Yuan Chen; Chrysoula Kiagiadaki; Eleni Zengini; Vasiliki Mamakou; Antonis Athanasiadis; Margarita Giannakopoulou; Vassiliki-Eirini Kariakli; Rebecca N. Nsubuga; Alex Karabarinde; Manjinder S. Sandhu; Gil McVean; Chris Tyler-Smith; Emmanouil Tsafantakis; Maria Karaleftheri; Yali Xue; George Dedoussis

Isolated populations are emerging as a powerful study design in the search for low-frequency and rare variant associations with complex phenotypes. Here we genotype 2,296 samples from two isolated Greek populations, the Pomak villages (HELIC-Pomak) in the North of Greece and the Mylopotamos villages (HELIC-MANOLIS) in Crete. We compare their genomic characteristics to the general Greek population and establish them as genetic isolates. In the MANOLIS cohort, we observe an enrichment of missense variants among the variants that have drifted up in frequency by more than fivefold. In the Pomak cohort, we find novel associations at variants on chr11p15.4 showing large allele frequency increases (from 0.2% in the general Greek population to 4.6% in the isolate) with haematological traits, for example, with mean corpuscular volume (rs7116019, P=2.3 × 10−26). We replicate this association in a second set of Pomak samples (combined P=2.0 × 10−36). We demonstrate significant power gains in detecting medical trait associations.

Collaboration


Dive into the Ioanna Ntalla's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar

Kalliope Panoutsopoulou

Wellcome Trust Sanger Institute

View shared research outputs
Top Co-Authors

Avatar

Stavroula Kanoni

Queen Mary University of London

View shared research outputs
Top Co-Authors

Avatar

Eleftheria Zeggini

Wellcome Trust Sanger Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Mary Yannakoulia

National and Kapodistrian University of Athens

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

John Perry

University of Cambridge

View shared research outputs
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge