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author:("Zhai, gwangju")
1.  Classification of osteoarthritis phenotypes by metabolomics analysis 
BMJ Open  2014;4(11):e006286.
To identify metabolic markers that can classify patients with osteoarthritis (OA) into subgroups.
A case-only study design was utilised.
Patients were recruited from those who underwent total knee or hip replacement surgery due to primary OA between November 2011 and December 2013 in St. Clare's Mercy Hospital and Health Science Centre General Hospital in St. John's, capital of Newfoundland and Labrador (NL), Canada. 38 men and 42 women were included in the study. The mean age was 65.2±8.7 years.
Outcome measures
Synovial fluid samples were collected at the time of their joint surgeries. Metabolic profiling was performed on the synovial fluid samples by the targeted metabolomics approach, and various analytic methods were utilised to identify metabolic markers for classifying subgroups of patients with OA. Potential confounders such as age, sex, body mass index (BMI) and comorbidities were considered in the analysis.
Two distinct patient groups, A and B, were clearly identified in the 80 patients with OA. Patients in group A had a significantly higher concentration on 37 of 39 acylcarnitines, but the free carnitine was significantly lower in their synovial fluids than in those of patients in group B. The latter group was further subdivided into two subgroups, that is, B1 and B2. The corresponding metabolites that contributed to the grouping were 86 metabolites including 75 glycerophospholipids (6 lysophosphatidylcholines, 69 phosphatidylcholines), 9 sphingolipids, 1 biogenic amine and 1 acylcarnitine. The grouping was not associated with any known confounders including age, sex, BMI and comorbidities. The possible biological processes involved in these clusters are carnitine, lipid and collagen metabolism, respectively.
The study demonstrated that OA consists of metabolically distinct subgroups. Identification of these distinct subgroups will help to unravel the pathogenesis and develop targeted therapies for OA.
PMCID: PMC4244434  PMID: 25410606
2.  Association of Adiposity Genetic Variants With Menarche Timing in 92,105 Women of European Descent 
Fernández-Rhodes, Lindsay | Demerath, Ellen W. | Cousminer, Diana L. | Tao, Ran | Dreyfus, Jill G. | Esko, Tõnu | Smith, Albert V. | Gudnason, Vilmundur | Harris, Tamara B. | Launer, Lenore | McArdle, Patrick F. | Yerges-Armstrong, Laura M. | Elks, Cathy E. | Strachan, David P. | Kutalik, Zoltán | Vollenweider, Peter | Feenstra, Bjarke | Boyd, Heather A. | Metspalu, Andres | Mihailov, Evelin | Broer, Linda | Zillikens, M. Carola | Oostra, Ben | van Duijn, Cornelia M. | Lunetta, Kathryn L. | Perry, John R. B. | Murray, Anna | Koller, Daniel L. | Lai, Dongbing | Corre, Tanguy | Toniolo, Daniela | Albrecht, Eva | Stöckl, Doris | Grallert, Harald | Gieger, Christian | Hayward, Caroline | Polasek, Ozren | Rudan, Igor | Wilson, James F. | He, Chunyan | Kraft, Peter | Hu, Frank B. | Hunter, David J. | Hottenga, Jouke-Jan | Willemsen, Gonneke | Boomsma, Dorret I. | Byrne, Enda M. | Martin, Nicholas G. | Montgomery, Grant W. | Warrington, Nicole M. | Pennell, Craig E. | Stolk, Lisette | Visser, Jenny A. | Hofman, Albert | Uitterlinden, André G. | Rivadeneira, Fernando | Lin, Peng | Fisher, Sherri L. | Bierut, Laura J. | Crisponi, Laura | Porcu, Eleonora | Mangino, Massimo | Zhai, Guangju | Spector, Tim D. | Buring, Julie E. | Rose, Lynda M. | Ridker, Paul M. | Poole, Charles | Hirschhorn, Joel N. | Murabito, Joanne M. | Chasman, Daniel I. | Widen, Elisabeth | North, Kari E. | Ong, Ken K. | Franceschini, Nora
American Journal of Epidemiology  2013;178(3):451-460.
Obesity is of global health concern. There are well-described inverse relationships between female pubertal timing and obesity. Recent genome-wide association studies of age at menarche identified several obesity-related variants. Using data from the ReproGen Consortium, we employed meta-analytical techniques to estimate the associations of 95 a priori and recently identified obesity-related (body mass index (weight (kg)/height (m)2), waist circumference, and waist:hip ratio) single-nucleotide polymorphisms (SNPs) with age at menarche in 92,116 women of European descent from 38 studies (1970–2010), in order to estimate associations between genetic variants associated with central or overall adiposity and pubertal timing in girls. Investigators in each study performed a separate analysis of associations between the selected SNPs and age at menarche (ages 9–17 years) using linear regression models and adjusting for birth year, site (as appropriate), and population stratification. Heterogeneity of effect-measure estimates was investigated using meta-regression. Six novel associations of body mass index loci with age at menarche were identified, and 11 adiposity loci previously reported to be associated with age at menarche were confirmed, but none of the central adiposity variants individually showed significant associations. These findings suggest complex genetic relationships between menarche and overall obesity, and to a lesser extent central obesity, in normal processes of growth and development.
PMCID: PMC3816344  PMID: 23558354
adiposity; body mass index; genetic association studies; menarche; obesity; waist circumference; waist:hip ratio; women's health
3.  SMAD3 Is Associated with the Total Burden of Radiographic Osteoarthritis: The Chingford Study 
PLoS ONE  2014;9(5):e97786.
A newly-described syndrome called Aneurysm-Osteoarthritis Syndrome (AOS) was recently reported. AOS presents with early onset osteoarthritis (OA) in multiple joints, together with aneurysms in major arteries, and is caused by rare mutations in SMAD3. Because of the similarity of AOS to idiopathic generalized OA (GOA), we hypothesized that SMAD3 is also associated with GOA and tested the hypothesis in a population-based cohort.
Study participants were derived from the Chingford study. Kellgren-Lawrence (KL) grades and the individual features of osteophytes and joint space narrowing (JSN) were scored from radiographs of hands, knees, hips, and lumbar spines. The total KL score, osteophyte score, and JSN score were calculated and used as indicators of the total burden of radiographic OA. Forty-one common SNPs within SMAD3 were genotyped using the Illumina HumanHap610Q array. Linear regression modelling was used to test the association between the total KL score, osteophyte score, and JSN score and each of the 41 SNPs, with adjustment for patient age and BMI. Permutation testing was used to control the false positive rate.
A total of 609 individuals were included in the analysis. All were Caucasian females with a mean age of 60.9±5.8. We found that rs3825977, with a minor allele (T) frequency of 20%, in the last intron of SMAD3, was significantly associated with total KL score (β = 0.14, Ppermutation = 0.002). This association was stronger for the total JSN score (β = 0.19, Ppermutation = 0.002) than for total osteophyte score (β = 0.11, Ppermutation = 0.02). The T allele is associated with a 1.47-fold increased odds for people with 5 or more joints to be affected by radiographic OA (Ppermutation = 0.046).
We found that SMAD3 is significantly associated with the total burden of radiographic OA. Further studies are required to reveal the mechanism of the association.
PMCID: PMC4031234  PMID: 24852296
4.  Interrogating causal pathways linking genetic variants, small molecule metabolites, and circulating lipids 
Genome Medicine  2014;6(3):25.
Emerging technologies based on mass spectrometry or nuclear magnetic resonance enable the monitoring of hundreds of small metabolites from tissues or body fluids. Profiling of metabolites can help elucidate causal pathways linking established genetic variants to known disease risk factors such as blood lipid traits.
We applied statistical methodology to dissect causal relationships between single nucleotide polymorphisms, metabolite concentrations, and serum lipid traits, focusing on 95 genetic loci reproducibly associated with the four main serum lipids (total-, low-density lipoprotein-, and high-density lipoprotein- cholesterol and triglycerides). The dataset used included 2,973 individuals from two independent population-based cohorts with data for 151 small molecule metabolites and four main serum lipids. Three statistical approaches, namely conditional analysis, Mendelian randomization, and structural equation modeling, were compared to investigate causal relationship at sets of a single nucleotide polymorphism, a metabolite, and a lipid trait associated with one another.
A subset of three lipid-associated loci (FADS1, GCKR, and LPA) have a statistically significant association with at least one main lipid and one metabolite concentration in our data, defining a total of 38 cross-associated sets of a single nucleotide polymorphism, a metabolite and a lipid trait. Structural equation modeling provided sufficient discrimination to indicate that the association of a single nucleotide polymorphism with a lipid trait was mediated through a metabolite at 15 of the 38 sets, and involving variants at the FADS1 and GCKR loci.
These data provide a framework for evaluating the causal role of components of the metabolome (or other intermediate factors) in mediating the association between established genetic variants and diseases or traits.
PMCID: PMC4062056  PMID: 24678845
5.  Human metabolic individuality in biomedical and pharmaceutical research 
Nature  2011;477(7362):10.1038/nature10354.
Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 exhibit effect sizes that are unusually high for GWAS and account for 10-60% of metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism, and Crohn’s disease. Taken together our study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.
PMCID: PMC3832838  PMID: 21886157
6.  A genomewide perspective of genetic variation in human metabolism 
Nature genetics  2009;42(2):137-141.
Serum metabolite concentrations provide a direct readout of biological processes in the human body, and are associated with disorders such as cardiovascular and metabolic diseases. Here we present a genome-wide association study with 163 metabolic traits using 1809 participants from the KORA population, followed up in the TwinsUK cohort with 422 participants. In eight out of nine replicated loci (FADS1, ELOVL2, ACADS, ACADM, ACADL, SPTLC3, ETFDH, SLC16A9) the genetic variant is located in or near enzyme or solute carrier coding genes, where the associating metabolic traits match the proteins’ function. Many of these loci are located in rate limiting steps of important enzymatic reactions. Use of metabolite concentration ratios as proxies for enzymatic reaction rates reduces the variance and yields robust statistical associations with p-values between 3×10−24 and 6.5×10−179. These loci explained 5.6% to 36.3% of the observed variance. For several loci, associations with clinically relevant parameters have previously been reported.
PMCID: PMC3773904  PMID: 20037589
7.  Variants near TERC are associated with mean telomere length. 
Nature genetics  2010;42(3):197-199.
We conducted genome-wide association analyses of mean leukocyte telomere length in 2,917 subjects and follow-up replication analyses in 9,492 and identified a locus on 3q26 encompassing the telomerase RNA component TERC, with compelling evidence for association (rs12696304, combined P value 3.72×10−14). Each copy of the minor allele of rs12696304 was associated with ≈75 base pairs shorter mean telomere length equivalent to ≈3.6 years of age-related attrition of mean telomere length.
PMCID: PMC3773906  PMID: 20139977
8.  Food Addiction: Its Prevalence and Significant Association with Obesity in the General Population 
PLoS ONE  2013;8(9):e74832.
‘Food addiction’ shares a similar neurobiological and behavioral framework with substance addiction. However whether, and to what degree, ‘food addiction’ contributes to obesity in the general population is unknown.
to assess 1) the prevalence of ‘food addiction’ in the Newfoundland population; 2) if clinical symptom counts of ‘food addiction’ were significantly correlated with the body composition measurements; 3) if food addicts were significantly more obese than controls, and 4) if macronutrient intakes are associated with ‘food addiction’.
A total of 652 adults (415 women, 237 men) recruited from the general population participated in this study. Obesity was evaluated by Body Mass Index (BMI) and Body Fat percentage measured by dual-energy X-ray absorptiometry. ‘Food addiction’ was assessed using the Yale Food Addiction Scale and macronutrient intake was determined from the Willet Food Frequency Questionnaire.
The prevalence of ‘food addiction’ was 5.4% (6.7% in females and 3.0% in males) and increased with obesity status. The clinical symptom counts of ‘food addiction’ were positively correlated with all body composition measurements across the entire sample (p<0.001). Obesity measurements were significantly higher in food addicts than controls; Food addicts were 11.7 (kg) heavier, 4.6 BMI units higher, and had 8.2% more body fat and 8.5% more trunk fat. Furthermore, food addicts consumed more calories from fat and protein compared with controls.
Our results demonstrated that ‘food addiction’ contributes to severity of obesity and body composition measurements from normal weight to obese individuals in the general population with higher rate in women as compared to men.
PMCID: PMC3762779  PMID: 24023964
9.  Meta-analysis of genome-wide association studies confirms a susceptibility locus for knee osteoarthritis on chromosome 7q22 
Evangelou, Evangelos | Valdes, Ana M. | Kerkhof, Hanneke J.M | Styrkarsdottir, Unnur | Zhu, YanYan | Meulenbelt, Ingrid | Lories, Rik J. | Karassa, Fotini B. | Tylzanowski, Przemko | Bos, Steffan D. | Akune, Toru | Arden, Nigel K. | Carr, Andrew | Chapman, Kay | Cupples, L. Adrienne | Dai, Jin | Deloukas, Panos | Doherty, Michael | Doherty, Sally | Engstrom, Gunnar | Gonzalez, Antonio | Halldorsson, Bjarni V. | Hammond, Christina L. | Hart, Deborah J. | Helgadottir, Hafdis | Hofman, Albert | Ikegawa, Shiro | Ingvarsson, Thorvaldur | Jiang, Qing | Jonsson, Helgi | Kaprio, Jaakko | Kawaguchi, Hiroshi | Kisand, Kalle | Kloppenburg, Margreet | Kujala, Urho M. | Lohmander, L. Stefan | Loughlin, John | Luyten, Frank P. | Mabuchi, Akihiko | McCaskie, Andrew | Nakajima, Masahiro | Nilsson, Peter M. | Nishida, Nao | Ollier, William E.R. | Panoutsopoulou, Kalliope | van de Putte, Tom | Ralston, Stuart H. | Rivadeneira, Fernado | Saarela, Janna | Schulte-Merker, Stefan | Slagboom, P. Eline | Sudo, Akihiro | Tamm, Agu | Tamm, Ann | Thorleifsson, Gudmar | Thorsteinsdottir, Unnur | Tsezou, Aspasia | Wallis, Gillian A. | Wilkinson, J. Mark | Yoshimura, Noriko | Zeggini, Eleftheria | Zhai, Guangju | Zhang, Feng | Jonsdottir, Ingileif | Uitterlinden, Andre G. | Felson, David T | van Meurs, Joyce B. | Stefansson, Kari | Ioannidis, John P.A. | Spector, Timothy D.
Annals of the rheumatic diseases  2010;70(2):349-355.
Osteoarthritis (OA) is the most prevalent form of arthritis and accounts for substantial morbidity and disability, particularly in the elderly. It is characterized by changes in joint structure including degeneration of the articular cartilage and its etiology is multifactorial with a strong postulated genetic component. We performed a meta-analysis of four genome-wide association (GWA) studies of 2,371 knee OA cases and 35,909 controls in Caucasian populations. Replication of the top hits was attempted with data from additional ten replication datasets. With a cumulative sample size of 6,709 cases and 44,439 controls, we identified one genome-wide significant locus on chromosome 7q22 for knee OA (rs4730250, p-value=9.2×10−9), thereby confirming its role as a susceptibility locus for OA. The associated signal is located within a large (500kb) linkage disequilibrium (LD) block that contains six genes; PRKAR2B (protein kinase, cAMP-dependent, regulatory, type II, beta), HPB1 (HMG-box transcription factor 1), COG5 (component of oligomeric golgi complex 5), GPR22 (G protein-coupled receptor 22), DUS4L (dihydrouridine synthase 4-like), and BCAP29 (the B-cell receptor-associated protein 29). Gene expression analyses of the (six) genes in primary cells derived from different joint tissues confirmed expression of all the genes in the joint environment.
PMCID: PMC3615180  PMID: 21068099
10.  A Meta-Analysis of Thyroid-Related Traits Reveals Novel Loci and Gender-Specific Differences in the Regulation of Thyroid Function 
Porcu, Eleonora | Medici, Marco | Pistis, Giorgio | Volpato, Claudia B. | Wilson, Scott G. | Cappola, Anne R. | Bos, Steffan D. | Deelen, Joris | den Heijer, Martin | Freathy, Rachel M. | Lahti, Jari | Liu, Chunyu | Lopez, Lorna M. | Nolte, Ilja M. | O'Connell, Jeffrey R. | Tanaka, Toshiko | Trompet, Stella | Arnold, Alice | Bandinelli, Stefania | Beekman, Marian | Böhringer, Stefan | Brown, Suzanne J. | Buckley, Brendan M. | Camaschella, Clara | de Craen, Anton J. M. | Davies, Gail | de Visser, Marieke C. H. | Ford, Ian | Forsen, Tom | Frayling, Timothy M. | Fugazzola, Laura | Gögele, Martin | Hattersley, Andrew T. | Hermus, Ad R. | Hofman, Albert | Houwing-Duistermaat, Jeanine J. | Jensen, Richard A. | Kajantie, Eero | Kloppenburg, Margreet | Lim, Ee M. | Masciullo, Corrado | Mariotti, Stefano | Minelli, Cosetta | Mitchell, Braxton D. | Nagaraja, Ramaiah | Netea-Maier, Romana T. | Palotie, Aarno | Persani, Luca | Piras, Maria G. | Psaty, Bruce M. | Räikkönen, Katri | Richards, J. Brent | Rivadeneira, Fernando | Sala, Cinzia | Sabra, Mona M. | Sattar, Naveed | Shields, Beverley M. | Soranzo, Nicole | Starr, John M. | Stott, David J. | Sweep, Fred C. G. J. | Usala, Gianluca | van der Klauw, Melanie M. | van Heemst, Diana | van Mullem, Alies | H.Vermeulen, Sita | Visser, W. Edward | Walsh, John P. | Westendorp, Rudi G. J. | Widen, Elisabeth | Zhai, Guangju | Cucca, Francesco | Deary, Ian J. | Eriksson, Johan G. | Ferrucci, Luigi | Fox, Caroline S. | Jukema, J. Wouter | Kiemeney, Lambertus A. | Pramstaller, Peter P. | Schlessinger, David | Shuldiner, Alan R. | Slagboom, Eline P. | Uitterlinden, André G. | Vaidya, Bijay | Visser, Theo J. | Wolffenbuttel, Bruce H. R. | Meulenbelt, Ingrid | Rotter, Jerome I. | Spector, Tim D. | Hicks, Andrew A. | Toniolo, Daniela | Sanna, Serena | Peeters, Robin P. | Naitza, Silvia
PLoS Genetics  2013;9(2):e1003266.
Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3) and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2). Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2) show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64% and 2.30% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism.
Author Summary
Levels of thyroid hormones are tightly regulated by TSH produced in the pituitary, and even mild alterations in their concentrations are strong indicators of thyroid pathologies, which are very common worldwide. To identify common genetic variants associated with the highly heritable markers of thyroid function, TSH and FT4, we conducted a meta-analysis of genome-wide association studies in 26,420 and 17,520 individuals, respectively, of European ancestry with normal thyroid function. Our analysis identified 26 independent genetic variants regulating these traits, several of which are new, and confirmed previously detected polymorphisms affecting TSH (within the PDE8B gene and near CAPZB, MAF/LOC440389, and NR3C2) and FT4 (within DIO1) levels. Gender-specific differences in the genetic effects of several variants for TSH and FT4 levels were identified at several loci, which offer clues to understand the known sexual dimorphism in thyroid function and pathology. Of particular clinical interest, we show that TSH-associated loci contribute not only to normal variation, but also to TSH values outside reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings add to the developing landscape of the regulation of thyroid homeostasis and the consequences of genetic variation for thyroid related diseases.
PMCID: PMC3567175  PMID: 23408906
11.  Genome-Wide Joint Meta-Analysis of SNP and SNP-by-Smoking Interaction Identifies Novel Loci for Pulmonary Function 
Hancock, Dana B. | Artigas, María Soler | Gharib, Sina A. | Henry, Amanda | Manichaikul, Ani | Ramasamy, Adaikalavan | Loth, Daan W. | Imboden, Medea | Koch, Beate | McArdle, Wendy L. | Smith, Albert V. | Smolonska, Joanna | Sood, Akshay | Tang, Wenbo | Wilk, Jemma B. | Zhai, Guangju | Zhao, Jing Hua | Aschard, Hugues | Burkart, Kristin M. | Curjuric, Ivan | Eijgelsheim, Mark | Elliott, Paul | Gu, Xiangjun | Harris, Tamara B. | Janson, Christer | Homuth, Georg | Hysi, Pirro G. | Liu, Jason Z. | Loehr, Laura R. | Lohman, Kurt | Loos, Ruth J. F. | Manning, Alisa K. | Marciante, Kristin D. | Obeidat, Ma'en | Postma, Dirkje S. | Aldrich, Melinda C. | Brusselle, Guy G. | Chen, Ting-hsu | Eiriksdottir, Gudny | Franceschini, Nora | Heinrich, Joachim | Rotter, Jerome I. | Wijmenga, Cisca | Williams, O. Dale | Bentley, Amy R. | Hofman, Albert | Laurie, Cathy C. | Lumley, Thomas | Morrison, Alanna C. | Joubert, Bonnie R. | Rivadeneira, Fernando | Couper, David J. | Kritchevsky, Stephen B. | Liu, Yongmei | Wjst, Matthias | Wain, Louise V. | Vonk, Judith M. | Uitterlinden, André G. | Rochat, Thierry | Rich, Stephen S. | Psaty, Bruce M. | O'Connor, George T. | North, Kari E. | Mirel, Daniel B. | Meibohm, Bernd | Launer, Lenore J. | Khaw, Kay-Tee | Hartikainen, Anna-Liisa | Hammond, Christopher J. | Gläser, Sven | Marchini, Jonathan | Kraft, Peter | Wareham, Nicholas J. | Völzke, Henry | Stricker, Bruno H. C. | Spector, Timothy D. | Probst-Hensch, Nicole M. | Jarvis, Deborah | Jarvelin, Marjo-Riitta | Heckbert, Susan R. | Gudnason, Vilmundur | Boezen, H. Marike | Barr, R. Graham | Cassano, Patricia A. | Strachan, David P. | Fornage, Myriam | Hall, Ian P. | Dupuis, Josée | Tobin, Martin D. | London, Stephanie J.
PLoS Genetics  2012;8(12):e1003098.
Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV1), and its ratio to forced vital capacity (FEV1/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV1 and FEV1/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest PJMA = 5.00×10−11), HLA-DQB1 and HLA-DQA2 (smallest PJMA = 4.35×10−9), and KCNJ2 and SOX9 (smallest PJMA = 1.28×10−8) were associated with FEV1/FVC or FEV1 in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.
Author Summary
Measures of pulmonary function provide important clinical tools for evaluating lung disease and its progression. Genome-wide association studies have identified numerous genetic risk factors for pulmonary function but have not considered interaction with cigarette smoking, which has consistently been shown to adversely impact pulmonary function. In over 50,000 study participants of European descent, we applied a recently developed joint meta-analysis method to simultaneously test associations of gene and gene-by-smoking interactions in relation to two major clinical measures of pulmonary function. Using this joint method to incorporate genetic main effects plus gene-by-smoking interaction, we identified three novel gene regions not previously related to pulmonary function: (1) DNER, (2) HLA-DQB1 and HLA-DQA2, and (3) KCNJ2 and SOX9. Expression analyses in human lung tissue from ours or prior studies indicate that these regions contain genes that are plausibly involved in pulmonary function. This work highlights the utility of employing novel methods for incorporating environmental interaction in genome-wide association studies to identify novel genetic regions.
PMCID: PMC3527213  PMID: 23284291
12.  Targeted metabolomics profiles are strongly correlated with nutritional patterns in women 
Metabolomics  2012;9(2):506-514.
Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targeted metabolomic analyses of serum samples using the Biocrates Absolute-IDQ™ Kit p150 (163 metabolites). We analyzed seven nutritional parameters: coffee intake, garlic intake and nutritional scores derived from the FFQs summarizing fruit and vegetable intake, alcohol intake, meat intake, hypo-caloric dieting and a “traditional English” diet. We studied the correlation between metabolite levels and dietary intake patterns in the larger population and identified for each trait between 14 and 20 independent monozygotic twins pairs discordant for nutritional intake and replicated results in this set. Results from both analyses were then meta-analyzed. For the metabolites associated with nutritional patterns, we calculated heritability using structural equation modelling. 42 metabolite nutrient intake associations were statistically significant in the discovery samples (Bonferroni P < 4 × 10−5) and 11 metabolite nutrient intake associations remained significant after validation. We found the strongest associations for fruit and vegetables intake and a glycerophospholipid (Phosphatidylcholine diacyl C38:6, P = 1.39 × 10−9) and a sphingolipid (Sphingomyeline C26:1, P = 6.95 × 10−13). We also found significant associations for coffee (confirming a previous association with C10 reported in an independent study), garlic intake and hypo-caloric dieting. Using the twin study design we find that two thirds the metabolites associated with nutritional patterns have a significant genetic contribution, and the remaining third are solely environmentally determined. Our data confirm the value of metabolomic studies for nutritional epidemiologic research.
Electronic supplementary material
The online version of this article (doi:10.1007/s11306-012-0469-6) contains supplementary material, which is available to authorized users.
PMCID: PMC3608890  PMID: 23543136
Metabolomics; Twins; Dietary pattern; Nutrition habits; Food questionnaires
13.  Meta-analyses identify 13 novel loci associated with age at menopause and highlights DNA repair and immune pathways 
Stolk, Lisette | Perry, John RB | Chasman, Daniel I | He, Chunyan | Mangino, Massimo | Sulem, Patrick | Barbalic, Maja | Broer, Linda | Byrne, Enda M | Ernst, Florian | Esko, Tõnu | Franceschini, Nora | Gudbjartsson, Daniel F | Hottenga, Jouke-Jan | Kraft, Peter | McArdle, Patick F | Porcu, Eleonora | Shin, So-Youn | Smith, Albert V | van Wingerden, Sophie | Zhai, Guangju | Zhuang, Wei V | Albrecht, Eva | Alizadeh, Behrooz Z | Aspelund, Thor | Bandinelli, Stefania | Lauc, Lovorka Barac | Beckmann, Jacques S | Boban, Mladen | Boerwinkle, Eric | Broekmans, Frank J | Burri, Andrea | Campbell, Harry | Chanock, Stephen J | Chen, Constance | Cornelis, Marilyn C | Corre, Tanguy | Coviello, Andrea D | d’Adamo, Pio | Davies, Gail | de Faire, Ulf | de Geus, Eco JC | Deary, Ian J | Dedoussis, George VZ | Deloukas, Panagiotis | Ebrahim, Shah | Eiriksdottir, Gudny | Emilsson, Valur | Eriksson, Johan G | Fauser, Bart CJM | Ferreli, Liana | Ferrucci, Luigi | Fischer, Krista | Folsom, Aaron R | Garcia, Melissa E | Gasparini, Paolo | Gieger, Christian | Glazer, Nicole | Grobbee, Diederick E | Hall, Per | Haller, Toomas | Hankinson, Susan E | Hass, Merli | Hayward, Caroline | Heath, Andrew C | Hofman, Albert | Ingelsson, Erik | Janssens, A Cecile JW | Johnson, Andrew D | Karasik, David | Kardia, Sharon LR | Keyzer, Jules | Kiel, Douglas P | Kolcic, Ivana | Kutalik, Zoltán | Lahti, Jari | Lai, Sandra | Laisk, Triin | Laven, Joop SE | Lawlor, Debbie A | Liu, Jianjun | Lopez, Lorna M | Louwers, Yvonne V | Magnusson, Patrik KE | Marongiu, Mara | Martin, Nicholas G | Klaric, Irena Martinovic | Masciullo, Corrado | McKnight, Barbara | Medland, Sarah E | Melzer, David | Mooser, Vincent | Navarro, Pau | Newman, Anne B | Nyholt, Dale R | Onland-Moret, N. Charlotte | Palotie, Aarno | Paré, Guillaume | Parker, Alex N | Pedersen, Nancy L | Peeters, Petra HM | Pistis, Giorgio | Plump, Andrew S | Polasek, Ozren | Pop, Victor JM | Psaty, Bruce M | Räikkönen, Katri | Rehnberg, Emil | Rotter, Jerome I | Rudan, Igor | Sala, Cinzia | Salumets, Andres | Scuteri, Angelo | Singleton, Andrew | Smith, Jennifer A | Snieder, Harold | Soranzo, Nicole | Stacey, Simon N | Starr, John M | Stathopoulou, Maria G | Stirrups, Kathleen | Stolk, Ronald P | Styrkarsdottir, Unnur | Sun, Yan V | Tenesa, Albert | Thorand, Barbara | Toniolo, Daniela | Tryggvadottir, Laufey | Tsui, Kim | Ulivi, Sheila | van Dam, Rob M | van der Schouw, Yvonne T | van Gils, Carla H | van Nierop, Peter | Vink, Jacqueline M | Visscher, Peter M | Voorhuis, Marlies | Waeber, Gérard | Wallaschofski, Henri | Wichmann, H Erich | Widen, Elisabeth | Gent, Colette JM Wijnands-van | Willemsen, Gonneke | Wilson, James F | Wolffenbuttel, Bruce HR | Wright, Alan F | Yerges-Armstrong, Laura M | Zemunik, Tatijana | Zgaga, Lina | Zillikens, M. Carola | Zygmunt, Marek | Arnold, Alice M | Boomsma, Dorret I | Buring, Julie E. | Crisponi, Laura | Demerath, Ellen W | Gudnason, Vilmundur | Harris, Tamara B | Hu, Frank B | Hunter, David J | Launer, Lenore J | Metspalu, Andres | Montgomery, Grant W | Oostra, Ben A | Ridker, Paul M | Sanna, Serena | Schlessinger, David | Spector, Tim D | Stefansson, Kari | Streeten, Elizabeth A | Thorsteinsdottir, Unnur | Uda, Manuela | Uitterlinden, André G | van Duijn, Cornelia M | Völzke, Henry | Murray, Anna | Murabito, Joanne M | Visser, Jenny A | Lunetta, Kathryn L
Nature Genetics  2012;44(3):260-268.
To identify novel loci for age at natural menopause, we performed a meta-analysis of 22 genome-wide association studies in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 new age at natural menopause loci (P < 5 × 10−8). The new loci included genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG, PRIM1) and immune function (IL11, NLRP11, BAT2). Gene-set enrichment pathway analyses using the full GWAS dataset identified exodeoxyribonuclease, NFκB signalling and mitochondrial dysfunction as biological processes related to timing of menopause.
PMCID: PMC3288642  PMID: 22267201
14.  A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation 
Coviello, Andrea D. | Haring, Robin | Wellons, Melissa | Vaidya, Dhananjay | Lehtimäki, Terho | Keildson, Sarah | Lunetta, Kathryn L. | He, Chunyan | Fornage, Myriam | Lagou, Vasiliki | Mangino, Massimo | Onland-Moret, N. Charlotte | Chen, Brian | Eriksson, Joel | Garcia, Melissa | Liu, Yong Mei | Koster, Annemarie | Lohman, Kurt | Lyytikäinen, Leo-Pekka | Petersen, Ann-Kristin | Prescott, Jennifer | Stolk, Lisette | Vandenput, Liesbeth | Wood, Andrew R. | Zhuang, Wei Vivian | Ruokonen, Aimo | Hartikainen, Anna-Liisa | Pouta, Anneli | Bandinelli, Stefania | Biffar, Reiner | Brabant, Georg | Cox, David G. | Chen, Yuhui | Cummings, Steven | Ferrucci, Luigi | Gunter, Marc J. | Hankinson, Susan E. | Martikainen, Hannu | Hofman, Albert | Homuth, Georg | Illig, Thomas | Jansson, John-Olov | Johnson, Andrew D. | Karasik, David | Karlsson, Magnus | Kettunen, Johannes | Kiel, Douglas P. | Kraft, Peter | Liu, Jingmin | Ljunggren, Östen | Lorentzon, Mattias | Maggio, Marcello | Markus, Marcello R. P. | Mellström, Dan | Miljkovic, Iva | Mirel, Daniel | Nelson, Sarah | Morin Papunen, Laure | Peeters, Petra H. M. | Prokopenko, Inga | Raffel, Leslie | Reincke, Martin | Reiner, Alex P. | Rexrode, Kathryn | Rivadeneira, Fernando | Schwartz, Stephen M. | Siscovick, David | Soranzo, Nicole | Stöckl, Doris | Tworoger, Shelley | Uitterlinden, André G. | van Gils, Carla H. | Vasan, Ramachandran S. | Wichmann, H.-Erich | Zhai, Guangju | Bhasin, Shalender | Bidlingmaier, Martin | Chanock, Stephen J. | De Vivo, Immaculata | Harris, Tamara B. | Hunter, David J. | Kähönen, Mika | Liu, Simin | Ouyang, Pamela | Spector, Tim D. | van der Schouw, Yvonne T. | Viikari, Jorma | Wallaschofski, Henri | McCarthy, Mark I. | Frayling, Timothy M. | Murray, Anna | Franks, Steve | Järvelin, Marjo-Riitta | de Jong, Frank H. | Raitakari, Olli | Teumer, Alexander | Ohlsson, Claes | Murabito, Joanne M. | Perry, John R. B.
PLoS Genetics  2012;8(7):e1002805.
Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×10−106), PRMT6 (rs17496332, 1p13.3, p = 1.4×10−11), GCKR (rs780093, 2p23.3, p = 2.2×10−16), ZBTB10 (rs440837, 8q21.13, p = 3.4×10−09), JMJD1C (rs7910927, 10q21.3, p = 6.1×10−35), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×10−08), NR2F2 (rs8023580, 15q26.2, p = 8.3×10−12), ZNF652 (rs2411984, 17q21.32, p = 3.5×10−14), TDGF3 (rs1573036, Xq22.3, p = 4.1×10−14), LHCGR (rs10454142, 2p16.3, p = 1.3×10−07), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×10−08), and UGT2B15 (rs293428, 4q13.2, p = 5.5×10−06). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×10−08, women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.
Author Summary
Sex hormone-binding globulin (SHBG) is the key protein responsible for binding and transporting the sex steroid hormones, testosterone and estradiol, in the circulatory system. SHBG regulates their bioavailability and therefore their effects in the body. SHBG has been linked to chronic diseases including type 2 diabetes and to hormone-sensitive cancers such as breast and prostate cancer. SHBG concentrations are approximately 50% heritable in family studies, suggesting SHBG concentrations are under significant genetic control; yet, little is known about the specific genes that influence SHBG. We conducted a large study of the association of SHBG concentrations with markers in the human genome in ∼22,000 white men and women to determine which loci influence SHBG concentrations. Genes near the identified genomic markers in addition to the SHBG protein coding gene included PRMT6, GCKR, ZBTB10, JMJD1C, SLCO1B1, NR2F2, ZNF652, TDGF3, LHCGR, BAIAP2L1, and UGT2B15. These genes represent a wide range of biologic pathways that may relate to SHBG function and sex steroid hormone biology, including liver function, lipid metabolism, carbohydrate metabolism and type 2 diabetes, and the development and progression of sex steroid hormone-responsive cancers.
PMCID: PMC3400553  PMID: 22829776
15.  A Genome-Wide Association Study identifies a locus on chromosome 7q22 to influence susceptibility for osteoarthritis 
Arthritis and Rheumatism  2010;62(2):499-510.
To identify genes involved in osteoarthritis (OA), the most prevalent form of joint disease, we performed a genome-wide association study (GWAS) in which we tested 500,510 Single Nucelotide Polymorphisms (SNPs) in 1341 OA cases and 3496 Dutch Caucasian controls. SNPs associated with at least two OA-phenotypes were analysed in 14,938 OA cases and approximately 39,000 controls. The C-allele of rs3815148 on chromosome 7q22 (MAF 23%, 172 kb upstream of the GPR22 gene) was consistently associated with a 1.14-fold increased risk (95%CI: 1.09–1.19) for knee- and/or hand-OA (p=8×10−8), and also with a 30% increased risk for knee-OA progression (95%CI: 1.03–1.64, p=0.03). This SNP is in almost complete linkage disequilibrium with rs3757713 (located 68 kb upstream of GPR22) which is associated with GPR22 expression levels in lymphoblast cell lines (p=4×10−12). GPR22 encodes an G-protein coupled receptor with unkown ligand (orphan receptor). Immunohistochemistry experiments showed absence of GPR22 in normal mouse articular cartilage or synovium. However, GPR22 positive chondrocytes were found in the upper layers of the articular cartilage of mouse knee joints that were challenged by in vivo papain treatment or in the presence of interleukin-1 driven inflammation. GRP22 positive chondrocyte-like cells were also found in osteophytes in instability-induced OA. In addition, GPR22 is also present in areas of the brain involved in locomotor function. Our findings reveal a novel common variant on chromosome 7q22 to influence susceptibility for prevalence and progression of OA.
PMCID: PMC3354739  PMID: 20112360
16.  Genome-wide association and large scale follow-up identifies 16 new loci influencing lung function 
Artigas, María Soler | Loth, Daan W | Wain, Louise V | Gharib, Sina A | Obeidat, Ma’en | Tang, Wenbo | Zhai, Guangju | Zhao, Jing Hua | Smith, Albert Vernon | Huffman, Jennifer E | Albrecht, Eva | Jackson, Catherine M | Evans, David M | Cadby, Gemma | Fornage, Myriam | Manichaikul, Ani | Lopez, Lorna M | Johnson, Toby | Aldrich, Melinda C | Aspelund, Thor | Barroso, Inês | Campbell, Harry | Cassano, Patricia A | Couper, David J | Eiriksdottir, Gudny | Franceschini, Nora | Garcia, Melissa | Gieger, Christian | Gislason, Gauti Kjartan | Grkovic, Ivica | Hammond, Christopher J | Hancock, Dana B | Harris, Tamara B | Ramasamy, Adaikalavan | Heckbert, Susan R | Heliövaara, Markku | Homuth, Georg | Hysi, Pirro G | James, Alan L | Jankovic, Stipan | Joubert, Bonnie R | Karrasch, Stefan | Klopp, Norman | Koch, Beate | Kritchevsky, Stephen B | Launer, Lenore J | Liu, Yongmei | Loehr, Laura R | Lohman, Kurt | Loos, Ruth JF | Lumley, Thomas | Al Balushi, Khalid A | Ang, Wei Q | Barr, R Graham | Beilby, John | Blakey, John D | Boban, Mladen | Boraska, Vesna | Brisman, Jonas | Britton, John R | Brusselle, Guy G | Cooper, Cyrus | Curjuric, Ivan | Dahgam, Santosh | Deary, Ian J | Ebrahim, Shah | Eijgelsheim, Mark | Francks, Clyde | Gaysina, Darya | Granell, Raquel | Gu, Xiangjun | Hankinson, John L | Hardy, Rebecca | Harris, Sarah E | Henderson, John | Henry, Amanda | Hingorani, Aroon D | Hofman, Albert | Holt, Patrick G | Hui, Jennie | Hunter, Michael L | Imboden, Medea | Jameson, Karen A | Kerr, Shona M | Kolcic, Ivana | Kronenberg, Florian | Liu, Jason Z | Marchini, Jonathan | McKeever, Tricia | Morris, Andrew D | Olin, Anna-Carin | Porteous, David J | Postma, Dirkje S | Rich, Stephen S | Ring, Susan M | Rivadeneira, Fernando | Rochat, Thierry | Sayer, Avan Aihie | Sayers, Ian | Sly, Peter D | Smith, George Davey | Sood, Akshay | Starr, John M | Uitterlinden, André G | Vonk, Judith M | Wannamethee, S Goya | Whincup, Peter H | Wijmenga, Cisca | Williams, O Dale | Wong, Andrew | Mangino, Massimo | Marciante, Kristin D | McArdle, Wendy L | Meibohm, Bernd | Morrison, Alanna C | North, Kari E | Omenaas, Ernst | Palmer, Lyle J | Pietiläinen, Kirsi H | Pin, Isabelle | Polašek, Ozren | Pouta, Anneli | Psaty, Bruce M | Hartikainen, Anna-Liisa | Rantanen, Taina | Ripatti, Samuli | Rotter, Jerome I | Rudan, Igor | Rudnicka, Alicja R | Schulz, Holger | Shin, So-Youn | Spector, Tim D | Surakka, Ida | Vitart, Veronique | Völzke, Henry | Wareham, Nicholas J | Warrington, Nicole M | Wichmann, H-Erich | Wild, Sarah H | Wilk, Jemma B | Wjst, Matthias | Wright, Alan F | Zgaga, Lina | Zemunik, Tatijana | Pennell, Craig E | Nyberg, Fredrik | Kuh, Diana | Holloway, John W | Boezen, H Marike | Lawlor, Debbie A | Morris, Richard W | Probst-Hensch, Nicole | Kaprio, Jaakko | Wilson, James F | Hayward, Caroline | Kähönen, Mika | Heinrich, Joachim | Musk, Arthur W | Jarvis, Deborah L | Gläser, Sven | Järvelin, Marjo-Riitta | Stricker, Bruno H Ch | Elliott, Paul | O’Connor, George T | Strachan, David P | London, Stephanie J | Hall, Ian P | Gudnason, Vilmundur | Tobin, Martin D
Nature Genetics  2011;43(11):1082-1090.
Pulmonary function measures reflect respiratory health and predict mortality, and are used in the diagnosis of chronic obstructive pulmonary disease (COPD). We tested genome-wide association with the forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) in 48,201 individuals of European ancestry, with follow-up of top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P<5×10−8) with pulmonary function, in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1, and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.
PMCID: PMC3267376  PMID: 21946350
17.  Epigenome-Wide Scans Identify Differentially Methylated Regions for Age and Age-Related Phenotypes in a Healthy Ageing Population 
PLoS Genetics  2012;8(4):e1002629.
Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype–phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes.
Author Summary
Epigenetic patterns vary during healthy ageing and development. Age-related DNA methylation changes have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To understand the biological mechanisms involved in potential longevity and rate of healthy ageing, we performed genome-wide association of epigenetic and genetic variation with both chronological age and age-related phenotypes. We identified hundreds of DNA methylation variants significantly associated with age and replicated these in an independent sample of young adult twins. Only a small proportion of these variants were also associated with age-related phenotypes. Therefore, the majority of age-related epigenetic changes do not contribute to rate of healthy ageing at later stages in life. Our results suggest that age-related changes in methylation occur throughout an individual's lifespan and that a proportion of these may be initiated from an early age. Intriguingly, a fraction of the age differentially methylated regions also associated with genetic variants in our sample, suggesting that DNA methylation may be a candidate mechanism of mediating not only environmental but also genetic effects on age-related phenotypes.
PMCID: PMC3330116  PMID: 22532803
18.  Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies 
Elks, Cathy E. | Perry, John R.B. | Sulem, Patrick | Chasman, Daniel I. | Franceschini, Nora | He, Chunyan | Lunetta, Kathryn L. | Visser, Jenny A. | Byrne, Enda M. | Cousminer, Diana L. | Gudbjartsson, Daniel F. | Esko, Tõnu | Feenstra, Bjarke | Hottenga, Jouke-Jan | Koller, Daniel L. | Kutalik, Zoltán | Lin, Peng | Mangino, Massimo | Marongiu, Mara | McArdle, Patrick F. | Smith, Albert V. | Stolk, Lisette | van Wingerden, Sophie W. | Zhao, Jing Hua | Albrecht, Eva | Corre, Tanguy | Ingelsson, Erik | Hayward, Caroline | Magnusson, Patrik K.E. | Smith, Erin N. | Ulivi, Shelia | Warrington, Nicole M. | Zgaga, Lina | Alavere, Helen | Amin, Najaf | Aspelund, Thor | Bandinelli, Stefania | Barroso, Ines | Berenson, Gerald S. | Bergmann, Sven | Blackburn, Hannah | Boerwinkle, Eric | Buring, Julie E. | Busonero, Fabio | Campbell, Harry | Chanock, Stephen J. | Chen, Wei | Cornelis, Marilyn C. | Couper, David | Coviello, Andrea D. | d’Adamo, Pio | de Faire, Ulf | de Geus, Eco J.C. | Deloukas, Panos | Döring, Angela | Smith, George Davey | Easton, Douglas F. | Eiriksdottir, Gudny | Emilsson, Valur | Eriksson, Johan | Ferrucci, Luigi | Folsom, Aaron R. | Foroud, Tatiana | Garcia, Melissa | Gasparini, Paolo | Geller, Frank | Gieger, Christian | Gudnason, Vilmundur | Hall, Per | Hankinson, Susan E. | Ferreli, Liana | Heath, Andrew C. | Hernandez, Dena G. | Hofman, Albert | Hu, Frank B. | Illig, Thomas | Järvelin, Marjo-Riitta | Johnson, Andrew D. | Karasik, David | Khaw, Kay-Tee | Kiel, Douglas P. | Kilpeläinen, Tuomas O. | Kolcic, Ivana | Kraft, Peter | Launer, Lenore J. | Laven, Joop S.E. | Li, Shengxu | Liu, Jianjun | Levy, Daniel | Martin, Nicholas G. | McArdle, Wendy L. | Melbye, Mads | Mooser, Vincent | Murray, Jeffrey C. | Murray, Sarah S. | Nalls, Michael A. | Navarro, Pau | Nelis, Mari | Ness, Andrew R. | Northstone, Kate | Oostra, Ben A. | Peacock, Munro | Palmer, Lyle J. | Palotie, Aarno | Paré, Guillaume | Parker, Alex N. | Pedersen, Nancy L. | Peltonen, Leena | Pennell, Craig E. | Pharoah, Paul | Polasek, Ozren | Plump, Andrew S. | Pouta, Anneli | Porcu, Eleonora | Rafnar, Thorunn | Rice, John P. | Ring, Susan M. | Rivadeneira, Fernando | Rudan, Igor | Sala, Cinzia | Salomaa, Veikko | Sanna, Serena | Schlessinger, David | Schork, Nicholas J. | Scuteri, Angelo | Segrè, Ayellet V. | Shuldiner, Alan R. | Soranzo, Nicole | Sovio, Ulla | Srinivasan, Sathanur R. | Strachan, David P. | Tammesoo, Mar-Liis | Tikkanen, Emmi | Toniolo, Daniela | Tsui, Kim | Tryggvadottir, Laufey | Tyrer, Jonathon | Uda, Manuela | van Dam, Rob M. | van Meurs, Joyve B.J. | Vollenweider, Peter | Waeber, Gerard | Wareham, Nicholas J. | Waterworth, Dawn M. | Weedon, Michael N. | Wichmann, H. Erich | Willemsen, Gonneke | Wilson, James F. | Wright, Alan F. | Young, Lauren | Zhai, Guangju | Zhuang, Wei Vivian | Bierut, Laura J. | Boomsma, Dorret I. | Boyd, Heather A. | Crisponi, Laura | Demerath, Ellen W. | van Duijn, Cornelia M. | Econs, Michael J. | Harris, Tamara B. | Hunter, David J. | Loos, Ruth J.F. | Metspalu, Andres | Montgomery, Grant W. | Ridker, Paul M. | Spector, Tim D. | Streeten, Elizabeth A. | Stefansson, Kari | Thorsteinsdottir, Unnur | Uitterlinden, André G. | Widen, Elisabeth | Murabito, Joanne M. | Ong, Ken K. | Murray, Anna
Nature genetics  2010;42(12):1077-1085.
To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P=5.4×10−60) and 9q31.2 (P=2.2×10−33), we identified 30 novel menarche loci (all P<5×10−8) and found suggestive evidence for a further 10 loci (P<1.9×10−6). New loci included four previously associated with BMI (in/near FTO, SEC16B, TRA2B and TMEM18), three in/near other genes implicated in energy homeostasis (BSX, CRTC1, and MCHR2), and three in/near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and MAGENTA pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing.
PMCID: PMC3140055  PMID: 21102462
19.  Association between DHEAS and Bone Loss in Postmenopausal Women: A 15-Year Longitudinal Population-Based Study 
Calcified Tissue International  2011;89(4):295-302.
Our aim was to examine the association between serum dehydroepiandrosterone sulfate (DHEAS) at baseline and BMD change at the femoral neck (FN) and lumbar spine (LS) in postmenopausal women during a 15-year follow-up. All participants were from the Chingford Study. BMD at the FN and LS were measured eight times during the 15-year follow-up by dual-energy X-ray absorptiometry. DHEAS at baseline was measured using radioimmunoassay. Data on height, weight, and hormone-replacement therapy (HRT) status were obtained at each visit. Multilevel linear regression modeling was used to examine the association between longitudinal BMD change at the FN and LS and DHEAS at baseline. Postmenopausal women (n = 1,003) aged 45–68 years (mean 54.7) at baseline were included in the study. After adjustment for baseline age, estradiol, HRT, and BMI, BMD at the FN decreased on average 0.49% (95% CI 0.31–0.71%) per year; and the decline was slowed down by 0.028% per squared year. Increase of DHEAS (each micromole per liter) was associated with 0.49% less bone loss at the FN (95% CI 0.21–0.71%, P = 0.001). However, this strong association became slightly weaker over time. Similar but weaker results were obtained for LS BMD. Our data suggest that high serum DHEAS at baseline is associated with less bone loss at both FN and LS and this association diminishes over time. The nature of the association is unclear, but such an association implies that, in managing BMD loss, women might benefit from maintaining a high level of DHEAS.
PMCID: PMC3175043  PMID: 21789637
BMD; DHEAS; Osteoporosis; Longitudinal study; Postmenopausal
20.  Common genetic determinants of vitamin D insufficiency: a genome-wide association study 
Wang, Thomas J. | Zhang, Feng | Richards, J. Brent | Kestenbaum, Bryan | van Meurs, Joyce B. | Berry, Diane | Kiel, Douglas | Streeten, Elizabeth A. | Ohlsson, Claes | Koller, Daniel L. | Palotie, Leena | Cooper, Jason D. | O'Reilly, Paul F. | Houston, Denise K. | Glazer, Nicole L. | Vandenput, Liesbeth | Peacock, Munro | Shi, Julia | Rivadeneira, Fernando | McCarthy, Mark I. | Anneli, Pouta | de Boer, Ian H. | Mangino, Massimo | Kato, Bernet | Smyth, Deborah J. | Booth, Sarah L. | Jacques, Paul F. | Burke, Greg L. | Goodarzi, Mark | Cheung, Ching-Lung | Wolf, Myles | Rice, Kenneth | Goltzman, David | Hidiroglou, Nick | Ladouceur, Martin | Hui, Siu L. | Wareham, Nicholas J. | Hocking, Lynne J. | Hart, Deborah | Arden, Nigel K. | Cooper, Cyrus | Malik, Suneil | Fraser, William D. | Hartikainen, Anna-Liisa | Zhai, Guangju | Macdonald, Helen | Forouhi, Nita G. | Loos, Ruth J.F. | Reid, David M. | Hakim, Alan | Dennison, Elaine | Liu, Yongmei | Power, Chris | Stevens, Helen E. | Jaana, Laitinen | Vasan, Ramachandran S. | Soranzo, Nicole | Bojunga, Jörg | Psaty, Bruce M. | Lorentzon, Mattias | Foroud, Tatiana | Harris, Tamara B. | Hofman, Albert | Jansson, John-Olov | Cauley, Jane A. | Uitterlinden, Andre G. | Gibson, Quince | Järvelin, Marjo-Riitta | Karasik, David | Siscovick, David S. | Econs, Michael J. | Kritchevsky, Stephen B. | Florez, Jose C. | Todd, John A. | Dupuis, Josee | Hypponen, Elina | Spector, Timothy D.
Lancet  2010;376(9736):180-188.
Vitamin D is crucial for maintaining musculoskeletal health. Recently, vitamin D insufficiency has been linked to a number of extraskeletal disorders, including diabetes, cancer, and cardiovascular disease. Determinants of circulating 25-hydroxyvitamin D (25-OH D) include sun exposure and dietary intake, but its high heritability suggests that genetic determinants may also play a role.
We performed a genome-wide association study of 25-OH D among ∼30,000 individuals of European descent from 15 cohorts. Five cohorts were designated as discovery cohorts (n=16,125), five as in silico replication cohorts (n=9,366), and five as de novo replication cohorts (n=8,378). Association results were combined using z-score-weighted meta-analysis. Vitamin D insufficiency was defined as 25-OH D <75 nmol/L or <50 nmol/L.
Variants at three loci reached genome-wide significance in the discovery cohorts, and were confirmed in the replication cohorts: 4p12 (overall P=1.9 × 10-109 for rs2282679, in GC); 11q12 (P=2.1 × 10-27 for rs12785878, near DHCR7); 11p15 (P=3.3 × 10-20 for rs10741657, near CYP2R1). Variants at an additional locus (20q13, CYP24A1) were genome-wide significant in the pooled sample (P=6.0 × 10-10 for rs6013897). A genotype score was constructed using the three confirmed variants. Those in the top quartile of genotype scores had 2- to 2.5-fold elevated odds of vitamin D insufficiency (P≤1 × 10-26).
Variants near genes involved in cholesterol synthesis (DHCR7), hydroxylation (CYP2R1, CYP24A1), and vitamin D transport (GC) influence vitamin D status. Genetic variation at these loci identifies individuals of European descent who have substantially elevated risk of vitamin D insufficiency.
PMCID: PMC3086761  PMID: 20541252
21.  A Comprehensive Evaluation of Potential Lung Function Associated Genes in the SpiroMeta General Population Sample 
PLoS ONE  2011;6(5):e19382.
Lung function measures are heritable traits that predict population morbidity and mortality and are essential for the diagnosis of chronic obstructive pulmonary disease (COPD). Variations in many genes have been reported to affect these traits, but attempts at replication have provided conflicting results. Recently, we undertook a meta-analysis of Genome Wide Association Study (GWAS) results for lung function measures in 20,288 individuals from the general population (the SpiroMeta consortium).
To comprehensively analyse previously reported genetic associations with lung function measures, and to investigate whether single nucleotide polymorphisms (SNPs) in these genomic regions are associated with lung function in a large population sample.
We analysed association for SNPs tagging 130 genes and 48 intergenic regions (+/−10 kb), after conducting a systematic review of the literature in the PubMed database for genetic association studies reporting lung function associations.
The analysis included 16,936 genotyped and imputed SNPs. No loci showed overall significant association for FEV1 or FEV1/FVC traits using a carefully defined significance threshold of 1.3×10−5. The most significant loci associated with FEV1 include SNPs tagging MACROD2 (P = 6.81×10−5), CNTN5 (P = 4.37×10−4), and TRPV4 (P = 1.58×10−3). Among ever-smokers, SERPINA1 showed the most significant association with FEV1 (P = 8.41×10−5), followed by PDE4D (P = 1.22×10−4). The strongest association with FEV1/FVC ratio was observed with ABCC1 (P = 4.38×10−4), and ESR1 (P = 5.42×10−4) among ever-smokers.
Polymorphisms spanning previously associated lung function genes did not show strong evidence for association with lung function measures in the SpiroMeta consortium population. Common SERPINA1 polymorphisms may affect FEV1 among smokers in the general population.
PMCID: PMC3098839  PMID: 21625484
22.  Eight Common Genetic Variants Associated with Serum DHEAS Levels Suggest a Key Role in Ageing Mechanisms 
PLoS Genetics  2011;7(4):e1002025.
Dehydroepiandrosterone sulphate (DHEAS) is the most abundant circulating steroid secreted by adrenal glands—yet its function is unknown. Its serum concentration declines significantly with increasing age, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. We conducted a meta-analysis of genome-wide association data with 14,846 individuals and identified eight independent common SNPs associated with serum DHEAS concentrations. Genes at or near the identified loci include ZKSCAN5 (rs11761528; p = 3.15×10−36), SULT2A1 (rs2637125; p = 2.61×10−19), ARPC1A (rs740160; p = 1.56×10−16), TRIM4 (rs17277546; p = 4.50×10−11), BMF (rs7181230; p = 5.44×10−11), HHEX (rs2497306; p = 4.64×10−9), BCL2L11 (rs6738028; p = 1.72×10−8), and CYP2C9 (rs2185570; p = 2.29×10−8). These genes are associated with type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins. Several SNPs were associated with changes in gene expression levels, and the related genes are connected to biological pathways linking DHEAS with ageing. This study provides much needed insight into the function of DHEAS.
Author Summary
Dehydroepiandrosterone sulphate (DHEAS), mainly secreted by the adrenal gland, is the most abundant circulating steroid in humans. It shows a significant physiological decline after the age of 25 and diminishes about 95% by the age of 85 years, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. Twin- and family-based studies have shown that there is a substantial genetic effect with heritability estimate of 60%, but no specific genes regulating serum DHEAS concentration have been identified to date. Here we take advantage of recent technical and methodological advances to examine the effects of common genetic variants on serum DHEAS concentrations. By examining 14,846 Caucasian individuals, we show that eight common genetic variants are associated with serum DHEAS concentrations. Genes at or near these genetic variants include BCL2L11, ARPC1A, ZKSCAN5, TRIM4, HHEX, CYP2C9, BMF, and SULT2A1. These genes have various associations with steroid hormone metabolism—co-morbidities of ageing including type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins—suggesting a wider functional role for DHEAS than previously thought.
PMCID: PMC3077384  PMID: 21533175
23.  Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study 
Fox, Ervin R. | Young, J. Hunter | Li, Yali | Dreisbach, Albert W. | Keating, Brendan J. | Musani, Solomon K. | Liu, Kiang | Morrison, Alanna C. | Ganesh, Santhi | Kutlar, Abdullah | Ramachandran, Vasan S. | Polak, Josef F. | Fabsitz, Richard R. | Dries, Daniel L. | Farlow, Deborah N. | Redline, Susan | Adeyemo, Adebowale | Hirschorn, Joel N. | Sun, Yan V. | Wyatt, Sharon B. | Penman, Alan D. | Palmas, Walter | Rotter, Jerome I. | Townsend, Raymond R. | Doumatey, Ayo P. | Tayo, Bamidele O. | Mosley, Thomas H. | Lyon, Helen N. | Kang, Sun J. | Rotimi, Charles N. | Cooper, Richard S. | Franceschini, Nora | Curb, J. David | Martin, Lisa W. | Eaton, Charles B. | Kardia, Sharon L.R. | Taylor, Herman A. | Caulfield, Mark J. | Ehret, Georg B. | Johnson, Toby | Chakravarti, Aravinda | Zhu, Xiaofeng | Levy, Daniel | Munroe, Patricia B. | Rice, Kenneth M. | Bochud, Murielle | Johnson, Andrew D. | Chasman, Daniel I. | Smith, Albert V. | Tobin, Martin D. | Verwoert, Germaine C. | Hwang, Shih-Jen | Pihur, Vasyl | Vollenweider, Peter | O'Reilly, Paul F. | Amin, Najaf | Bragg-Gresham, Jennifer L. | Teumer, Alexander | Glazer, Nicole L. | Launer, Lenore | Zhao, Jing Hua | Aulchenko, Yurii | Heath, Simon | Sõber, Siim | Parsa, Afshin | Luan, Jian'an | Arora, Pankaj | Dehghan, Abbas | Zhang, Feng | Lucas, Gavin | Hicks, Andrew A. | Jackson, Anne U. | Peden, John F. | Tanaka, Toshiko | Wild, Sarah H. | Rudan, Igor | Igl, Wilmar | Milaneschi, Yuri | Parker, Alex N. | Fava, Cristiano | Chambers, John C. | Kumari, Meena | JinGo, Min | van der Harst, Pim | Kao, Wen Hong Linda | Sjögren, Marketa | Vinay, D.G. | Alexander, Myriam | Tabara, Yasuharu | Shaw-Hawkins, Sue | Whincup, Peter H. | Liu, Yongmei | Shi, Gang | Kuusisto, Johanna | Seielstad, Mark | Sim, Xueling | Nguyen, Khanh-Dung Hoang | Lehtimäki, Terho | Matullo, Giuseppe | Wu, Ying | Gaunt, Tom R. | Charlotte Onland-Moret, N. | Cooper, Matthew N. | Platou, Carl G.P. | Org, Elin | Hardy, Rebecca | Dahgam, Santosh | Palmen, Jutta | Vitart, Veronique | Braund, Peter S. | Kuznetsova, Tatiana | Uiterwaal, Cuno S.P.M. | Campbell, Harry | Ludwig, Barbara | Tomaszewski, Maciej | Tzoulaki, Ioanna | Palmer, Nicholette D. | Aspelund, Thor | Garcia, Melissa | Chang, Yen-Pei C. | O'Connell, Jeffrey R. | Steinle, Nanette I. | Grobbee, Diederick E. | Arking, Dan E. | Hernandez, Dena | Najjar, Samer | McArdle, Wendy L. | Hadley, David | Brown, Morris J. | Connell, John M. | Hingorani, Aroon D. | Day, Ian N.M. | Lawlor, Debbie A. | Beilby, John P. | Lawrence, Robert W. | Clarke, Robert | Collins, Rory | Hopewell, Jemma C. | Ongen, Halit | Bis, Joshua C. | Kähönen, Mika | Viikari, Jorma | Adair, Linda S. | Lee, Nanette R. | Chen, Ming-Huei | Olden, Matthias | Pattaro, Cristian | Hoffman Bolton, Judith A. | Köttgen, Anna | Bergmann, Sven | Mooser, Vincent | Chaturvedi, Nish | Frayling, Timothy M. | Islam, Muhammad | Jafar, Tazeen H. | Erdmann, Jeanette | Kulkarni, Smita R. | Bornstein, Stefan R. | Grässler, Jürgen | Groop, Leif | Voight, Benjamin F. | Kettunen, Johannes | Howard, Philip | Taylor, Andrew | Guarrera, Simonetta | Ricceri, Fulvio | Emilsson, Valur | Plump, Andrew | Barroso, Inês | Khaw, Kay-Tee | Weder, Alan B. | Hunt, Steven C. | Bergman, Richard N. | Collins, Francis S. | Bonnycastle, Lori L. | Scott, Laura J. | Stringham, Heather M. | Peltonen, Leena | Perola, Markus | Vartiainen, Erkki | Brand, Stefan-Martin | Staessen, Jan A. | Wang, Thomas J. | Burton, Paul R. | SolerArtigas, Maria | Dong, Yanbin | Snieder, Harold | Wang, Xiaoling | Zhu, Haidong | Lohman, Kurt K. | Rudock, Megan E. | Heckbert, Susan R. | Smith, Nicholas L. | Wiggins, Kerri L. | Shriner, Daniel | Veldre, Gudrun | Viigimaa, Margus | Kinra, Sanjay | Prabhakaran, Dorairajan | Tripathy, Vikal | Langefeld, Carl D. | Rosengren, Annika | Thelle, Dag S. | MariaCorsi, Anna | Singleton, Andrew | Forrester, Terrence | Hilton, Gina | McKenzie, Colin A. | Salako, Tunde | Iwai, Naoharu | Kita, Yoshikuni | Ogihara, Toshio | Ohkubo, Takayoshi | Okamura, Tomonori | Ueshima, Hirotsugu | Umemura, Satoshi | Eyheramendy, Susana | Meitinger, Thomas | Wichmann, H.-Erich | Cho, Yoon Shin | Kim, Hyung-Lae | Lee, Jong-Young | Scott, James | Sehmi, Joban S. | Zhang, Weihua | Hedblad, Bo | Nilsson, Peter | Smith, George Davey | Wong, Andrew | Narisu, Narisu | Stančáková, Alena | Raffel, Leslie J. | Yao, Jie | Kathiresan, Sekar | O'Donnell, Chris | Schwartz, Steven M. | Arfan Ikram, M. | Longstreth, Will T. | Seshadri, Sudha | Shrine, Nick R.G. | Wain, Louise V. | Morken, Mario A. | Swift, Amy J. | Laitinen, Jaana | Prokopenko, Inga | Zitting, Paavo | Cooper, Jackie A. | Humphries, Steve E. | Danesh, John | Rasheed, Asif | Goel, Anuj | Hamsten, Anders | Watkins, Hugh | Bakker, Stephan J.L. | van Gilst, Wiek H. | Janipalli, Charles S. | Radha Mani, K. | Yajnik, Chittaranjan S. | Hofman, Albert | Mattace-Raso, Francesco U.S. | Oostra, Ben A. | Demirkan, Ayse | Isaacs, Aaron | Rivadeneira, Fernando | Lakatta, Edward G. | Orru, Marco | Scuteri, Angelo | Ala-Korpela, Mika | Kangas, Antti J. | Lyytikäinen, Leo-Pekka | Soininen, Pasi | Tukiainen, Taru | Würz, Peter | Twee-Hee Ong, Rick | Dörr, Marcus | Kroemer, Heyo K. | Völker, Uwe | Völzke, Henry | Galan, Pilar | Hercberg, Serge | Lathrop, Mark | Zelenika, Diana | Deloukas, Panos | Mangino, Massimo | Spector, Tim D. | Zhai, Guangju | Meschia, James F. | Nalls, Michael A. | Sharma, Pankaj | Terzic, Janos | Kranthi Kumar, M.J. | Denniff, Matthew | Zukowska-Szczechowska, Ewa | Wagenknecht, Lynne E. | Fowkes, Gerald R. | Charchar, Fadi J. | Schwarz, Peter E.H. | Hayward, Caroline | Guo, Xiuqing | Bots, Michiel L. | Brand, Eva | Samani, Nilesh J. | Polasek, Ozren | Talmud, Philippa J. | Nyberg, Fredrik | Kuh, Diana | Laan, Maris | Hveem, Kristian | Palmer, Lyle J. | van der Schouw, Yvonne T. | Casas, Juan P. | Mohlke, Karen L. | Vineis, Paolo | Raitakari, Olli | Wong, Tien Y. | Shyong Tai, E. | Laakso, Markku | Rao, Dabeeru C. | Harris, Tamara B. | Morris, Richard W. | Dominiczak, Anna F. | Kivimaki, Mika | Marmot, Michael G. | Miki, Tetsuro | Saleheen, Danish | Chandak, Giriraj R. | Coresh, Josef | Navis, Gerjan | Salomaa, Veikko | Han, Bok-Ghee | Kooner, Jaspal S. | Melander, Olle | Ridker, Paul M. | Bandinelli, Stefania | Gyllensten, Ulf B. | Wright, Alan F. | Wilson, James F. | Ferrucci, Luigi | Farrall, Martin | Tuomilehto, Jaakko | Pramstaller, Peter P. | Elosua, Roberto | Soranzo, Nicole | Sijbrands, Eric J.G. | Altshuler, David | Loos, Ruth J.F. | Shuldiner, Alan R. | Gieger, Christian | Meneton, Pierre | Uitterlinden, Andre G. | Wareham, Nicholas J. | Gudnason, Vilmundur | Rettig, Rainer | Uda, Manuela | Strachan, David P. | Witteman, Jacqueline C.M. | Hartikainen, Anna-Liisa | Beckmann, Jacques S. | Boerwinkle, Eric | Boehnke, Michael | Larson, Martin G. | Järvelin, Marjo-Riitta | Psaty, Bruce M. | Abecasis, Gonçalo R. | Elliott, Paul | van Duijn , Cornelia M. | Newton-Cheh, Christopher
Human Molecular Genetics  2011;20(11):2273-2284.
The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10−8) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10−8). The top IBC association for SBP was rs2012318 (P= 6.4 × 10−6) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10−6) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexity.
PMCID: PMC3090190  PMID: 21378095
24.  New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk 
Dupuis, Josée | Langenberg, Claudia | Prokopenko, Inga | Saxena, Richa | Soranzo, Nicole | Jackson, Anne U | Wheeler, Eleanor | Glazer, Nicole L | Bouatia-Naji, Nabila | Gloyn, Anna L | Lindgren, Cecilia M | Mägi, Reedik | Morris, Andrew P | Randall, Joshua | Johnson, Toby | Elliott, Paul | Rybin, Denis | Thorleifsson, Gudmar | Steinthorsdottir, Valgerdur | Henneman, Peter | Grallert, Harald | Dehghan, Abbas | Hottenga, Jouke Jan | Franklin, Christopher S | Navarro, Pau | Song, Kijoung | Goel, Anuj | Perry, John R B | Egan, Josephine M | Lajunen, Taina | Grarup, Niels | Sparsø, Thomas | Doney, Alex | Voight, Benjamin F | Stringham, Heather M | Li, Man | Kanoni, Stavroula | Shrader, Peter | Cavalcanti-Proença, Christine | Kumari, Meena | Qi, Lu | Timpson, Nicholas J | Gieger, Christian | Zabena, Carina | Rocheleau, Ghislain | Ingelsson, Erik | An, Ping | O’Connell, Jeffrey | Luan, Jian'an | Elliott, Amanda | McCarroll, Steven A | Payne, Felicity | Roccasecca, Rosa Maria | Pattou, François | Sethupathy, Praveen | Ardlie, Kristin | Ariyurek, Yavuz | Balkau, Beverley | Barter, Philip | Beilby, John P | Ben-Shlomo, Yoav | Benediktsson, Rafn | Bennett, Amanda J | Bergmann, Sven | Bochud, Murielle | Boerwinkle, Eric | Bonnefond, Amélie | Bonnycastle, Lori L | Borch-Johnsen, Knut | Böttcher, Yvonne | Brunner, Eric | Bumpstead, Suzannah J | Charpentier, Guillaume | Chen, Yii-Der Ida | Chines, Peter | Clarke, Robert | Coin, Lachlan J M | Cooper, Matthew N | Cornelis, Marilyn | Crawford, Gabe | Crisponi, Laura | Day, Ian N M | de Geus, Eco | Delplanque, Jerome | Dina, Christian | Erdos, Michael R | Fedson, Annette C | Fischer-Rosinsky, Antje | Forouhi, Nita G | Fox, Caroline S | Frants, Rune | Franzosi, Maria Grazia | Galan, Pilar | Goodarzi, Mark O | Graessler, Jürgen | Groves, Christopher J | Grundy, Scott | Gwilliam, Rhian | Gyllensten, Ulf | Hadjadj, Samy | Hallmans, Göran | Hammond, Naomi | Han, Xijing | Hartikainen, Anna-Liisa | Hassanali, Neelam | Hayward, Caroline | Heath, Simon C | Hercberg, Serge | Herder, Christian | Hicks, Andrew A | Hillman, David R | Hingorani, Aroon D | Hofman, Albert | Hui, Jennie | Hung, Joe | Isomaa, Bo | Johnson, Paul R V | Jørgensen, Torben | Jula, Antti | Kaakinen, Marika | Kaprio, Jaakko | Kesaniemi, Y Antero | Kivimaki, Mika | Knight, Beatrice | Koskinen, Seppo | Kovacs, Peter | Kyvik, Kirsten Ohm | Lathrop, G Mark | Lawlor, Debbie A | Le Bacquer, Olivier | Lecoeur, Cécile | Li, Yun | Lyssenko, Valeriya | Mahley, Robert | Mangino, Massimo | Manning, Alisa K | Martínez-Larrad, María Teresa | McAteer, Jarred B | McCulloch, Laura J | McPherson, Ruth | Meisinger, Christa | Melzer, David | Meyre, David | Mitchell, Braxton D | Morken, Mario A | Mukherjee, Sutapa | Naitza, Silvia | Narisu, Narisu | Neville, Matthew J | Oostra, Ben A | Orrù, Marco | Pakyz, Ruth | Palmer, Colin N A | Paolisso, Giuseppe | Pattaro, Cristian | Pearson, Daniel | Peden, John F | Pedersen, Nancy L. | Perola, Markus | Pfeiffer, Andreas F H | Pichler, Irene | Polasek, Ozren | Posthuma, Danielle | Potter, Simon C | Pouta, Anneli | Province, Michael A | Psaty, Bruce M | Rathmann, Wolfgang | Rayner, Nigel W | Rice, Kenneth | Ripatti, Samuli | Rivadeneira, Fernando | Roden, Michael | Rolandsson, Olov | Sandbaek, Annelli | Sandhu, Manjinder | Sanna, Serena | Sayer, Avan Aihie | Scheet, Paul | Scott, Laura J | Seedorf, Udo | Sharp, Stephen J | Shields, Beverley | Sigurðsson, Gunnar | Sijbrands, Erik J G | Silveira, Angela | Simpson, Laila | Singleton, Andrew | Smith, Nicholas L | Sovio, Ulla | Swift, Amy | Syddall, Holly | Syvänen, Ann-Christine | Tanaka, Toshiko | Thorand, Barbara | Tichet, Jean | Tönjes, Anke | Tuomi, Tiinamaija | Uitterlinden, André G | van Dijk, Ko Willems | van Hoek, Mandy | Varma, Dhiraj | Visvikis-Siest, Sophie | Vitart, Veronique | Vogelzangs, Nicole | Waeber, Gérard | Wagner, Peter J | Walley, Andrew | Walters, G Bragi | Ward, Kim L | Watkins, Hugh | Weedon, Michael N | Wild, Sarah H | Willemsen, Gonneke | Witteman, Jaqueline C M | Yarnell, John W G | Zeggini, Eleftheria | Zelenika, Diana | Zethelius, Björn | Zhai, Guangju | Zhao, Jing Hua | Zillikens, M Carola | Borecki, Ingrid B | Loos, Ruth J F | Meneton, Pierre | Magnusson, Patrik K E | Nathan, David M | Williams, Gordon H | Hattersley, Andrew T | Silander, Kaisa | Salomaa, Veikko | Smith, George Davey | Bornstein, Stefan R | Schwarz, Peter | Spranger, Joachim | Karpe, Fredrik | Shuldiner, Alan R | Cooper, Cyrus | Dedoussis, George V | Serrano-Ríos, Manuel | Morris, Andrew D | Lind, Lars | Palmer, Lyle J | Hu, Frank B. | Franks, Paul W | Ebrahim, Shah | Marmot, Michael | Kao, W H Linda | Pankow, James S | Sampson, Michael J | Kuusisto, Johanna | Laakso, Markku | Hansen, Torben | Pedersen, Oluf | Pramstaller, Peter Paul | Wichmann, H Erich | Illig, Thomas | Rudan, Igor | Wright, Alan F | Stumvoll, Michael | Campbell, Harry | Wilson, James F | Hamsten, Anders | Bergman, Richard N | Buchanan, Thomas A | Collins, Francis S | Mohlke, Karen L | Tuomilehto, Jaakko | Valle, Timo T | Altshuler, David | Rotter, Jerome I | Siscovick, David S | Penninx, Brenda W J H | Boomsma, Dorret | Deloukas, Panos | Spector, Timothy D | Frayling, Timothy M | Ferrucci, Luigi | Kong, Augustine | Thorsteinsdottir, Unnur | Stefansson, Kari | van Duijn, Cornelia M | Aulchenko, Yurii S | Cao, Antonio | Scuteri, Angelo | Schlessinger, David | Uda, Manuela | Ruokonen, Aimo | Jarvelin, Marjo-Riitta | Waterworth, Dawn M | Vollenweider, Peter | Peltonen, Leena | Mooser, Vincent | Abecasis, Goncalo R | Wareham, Nicholas J | Sladek, Robert | Froguel, Philippe | Watanabe, Richard M | Meigs, James B | Groop, Leif | Boehnke, Michael | McCarthy, Mark I | Florez, Jose C | Barroso, Inês
Nature genetics  2010;42(2):105-116.
Circulating glucose levels are tightly regulated. To identify novel glycemic loci, we performed meta-analyses of 21 genome-wide associations studies informative for fasting glucose (FG), fasting insulin (FI) and indices of β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 non-diabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with FG/HOMA-B and two associated with FI/HOMA-IR. These include nine new FG loci (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and FAM148B) and one influencing FI/HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB/TMEM195 with type 2 diabetes (T2D). Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify T2D risk loci, as well as loci that elevate FG modestly, but do not cause overt diabetes.
PMCID: PMC3018764  PMID: 20081858
25.  Bone marrow lesions predict site-specific cartilage defect development and volume loss: a prospective study in older adults 
Arthritis Research & Therapy  2010;12(6):R222.
Recent evidence suggests that bone marrow lesions (BMLs) play a pivotal role in knee osteoarthritis (OA). The aims of this study were to determine: 1) whether baseline BML presence and/or severity predict site-specific cartilage defect progression and cartilage volume loss; and 2) whether baseline cartilage defects predict site-specific BML progression.
A total of 405 subjects (mean age 63 years, range 52 to 79) were measured at baseline and approximately 2.7 years later. Magnetic resonance imaging (MRI) of the right knee was performed to measure knee cartilage volume, cartilage defects (0 to 4), and BMLs (0 to 3) at the medial tibial (MT), medial femoral (MF), lateral tibial (LT), and lateral femoral (LF) sites. Logistic regression and generalized estimating equations were used to examine the relationship between BMLs and cartilage defects and cartilage volume loss.
At all four sites, baseline BML presence predicted defect progression (odds ratio (OR) 2.4 to 6.4, all P < 0.05), and cartilage volume loss (-0.9 to -2.9% difference per annum, all P < 0.05) at the same site. In multivariable analysis, there was a significant relationship between BML severity and defect progression at all four sites (OR 1.8 to 3.2, all P < 0.05) and BML severity and cartilage volume loss at the MF, LT, and LF sites (β -22.1 to -42.0, all P < 0.05). Additionally, baseline defect severity predicted BML progression at the MT and LF sites (OR 3.3 to 3.7, all P < 0.01). Lastly, there was a greater increase in cartilage volume loss at the MT and LT sites when both larger defects and BMLs were present at baseline (all P < 0.05).
Baseline BMLs predicted site-specific defect progression and cartilage volume loss in a dose-response manner suggesting BMLs may have a local effect on cartilage homeostasis. Baseline defects predicted site-specific BML progression, which may represent increased bone loading adjacent to defects. These results suggest BMLs and defects are interconnected and play key roles in knee cartilage volume loss; thus, both should be considered targets for intervention.
PMCID: PMC3046535  PMID: 21190554

Results 1-25 (38)