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1.  Effect of Five Genetic Variants Associated with Lung Function on the Risk of Chronic Obstructive Lung Disease, and Their Joint Effects on Lung Function 
Rationale: Genomic loci are associated with FEV1 or the ratio of FEV1 to FVC in population samples, but their association with chronic obstructive pulmonary disease (COPD) has not yet been proven, nor have their combined effects on lung function and COPD been studied.
Objectives: To test association with COPD of variants at five loci (TNS1, GSTCD, HTR4, AGER, and THSD4) and to evaluate joint effects on lung function and COPD of these single-nucleotide polymorphisms (SNPs), and variants at the previously reported locus near HHIP.
Methods: By sampling from 12 population-based studies (n = 31,422), we obtained genotype data on 3,284 COPD case subjects and 17,538 control subjects for sentinel SNPs in TNS1, GSTCD, HTR4, AGER, and THSD4. In 24,648 individuals (including 2,890 COPD case subjects and 13,862 control subjects), we additionally obtained genotypes for rs12504628 near HHIP. Each allele associated with lung function decline at these six SNPs contributed to a risk score. We studied the association of the risk score to lung function and COPD.
Measurements and Main Results: Association with COPD was significant for three loci (TNS1, GSTCD, and HTR4) and the previously reported HHIP locus, and suggestive and directionally consistent for AGER and TSHD4. Compared with the baseline group (7 risk alleles), carrying 10–12 risk alleles was associated with a reduction in FEV1 (β = –72.21 ml, P = 3.90 × 10−4) and FEV1/FVC (β = –1.53%, P = 6.35 × 10−6), and with COPD (odds ratio = 1.63, P = 1.46 × 10−5).
Conclusions: Variants in TNS1, GSTCD, and HTR4 are associated with COPD. Our highest risk score category was associated with a 1.6-fold higher COPD risk than the population average score.
doi:10.1164/rccm.201102-0192OC
PMCID: PMC3398416  PMID: 21965014
FEV1; FVC; genome-wide association study; modeling risk
2.  Detailed Physiologic Characterization Reveals Diverse Mechanisms for Novel Genetic Loci Regulating Glucose and Insulin Metabolism in Humans 
Diabetes  2010;59(5):1266-1275.
OBJECTIVE
Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action.
RESEARCH DESIGN AND METHODS
We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084).
RESULTS
The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 × 10−71). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction.
CONCLUSIONS
Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes.
doi:10.2337/db09-1568
PMCID: PMC2857908  PMID: 20185807
3.  Evaluating the Role of LPIN1 Variation in Insulin Resistance, Body Weight, and Human Lipodystrophy in U.K. Populations 
Diabetes  2008;57(9):2527-2533.
OBJECTIVE— Loss of lipin 1 activity causes lipodystrophy and insulin resistance in the fld mouse, and LPIN1 expression and common genetic variation were recently suggested to influence adiposity and insulin sensitivity in humans. We aimed to conduct a comprehensive association study to clarify the influence of common LPIN1 variation on adiposity and insulin sensitivity in U.K. populations and to examine the role of LPIN1 mutations in insulin resistance syndromes.
RESEARCH DESIGN AND METHOD— Twenty-two single nucleotide polymorphisms tagging common LPIN1 variation were genotyped in Medical Research Council (MRC) Ely (n = 1,709) and Hertfordshire (n = 2,901) population-based cohorts. LPIN1 exons, exon/intron boundaries, and 3′ untranslated region were sequenced in 158 patients with idiopathic severe insulin resistance (including 23 lipodystrophic patients) and 48 control subjects.
RESULTS— We found no association between LPIN1 single nucleotide polymorphisms and fasting insulin but report a nominal association between rs13412852 and BMI (P = 0.042) in a meta-analysis of 8,504 samples from in-house and publicly available studies. Three rare nonsynonymous variants (A353T, R552K, and G582R) were detected in severely insulin-resistant patients. However, these did not cosegregate with disease in affected families, and Lipin1 protein expression and phosphorylation in patients with variants were indistinguishable from those in control subjects.
CONCLUSIONS— Our data do not support a major effect of common LPIN1 variation on metabolic traits and suggest that mutations in LPIN1 are not a common cause of lipodystrophy in humans. The nominal associations with BMI and other metabolic traits in U.K. cohorts require replication in larger cohorts.
doi:10.2337/db08-0422
PMCID: PMC2518506  PMID: 18591397
4.  Correction: Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution 
Lindgren, Cecilia M. | Heid, Iris M. | Randall, Joshua C. | Lamina, Claudia | Steinthorsdottir, Valgerdur | Qi, Lu | Speliotes, Elizabeth K. | Thorleifsson, Gudmar | Willer, Cristen J. | Herrera, Blanca M. | Jackson, Anne U. | Lim, Noha | Scheet, Paul | Soranzo, Nicole | Amin, Najaf | Aulchenko, Yurii S. | Chambers, John C. | Drong, Alexander | Luan, Jian'an | Lyon, Helen N. | Rivadeneira, Fernando | Sanna, Serena | Timpson, Nicholas J. | Zillikens, M. Carola | Zhao, Jing Hua | Almgren, Peter | Bandinelli, Stefania | Bennett, Amanda J. | Bergman, Richard N. | Bonnycastle, Lori L. | Bumpstead, Suzannah J. | Chanock, Stephen J. | Cherkas, Lynn | Chines, Peter | Coin, Lachlan | Cooper, Cyrus | Crawford, Gabriel | Doering, Angela | Dominiczak, Anna | Doney, Alex S. F. | Ebrahim, Shah | Elliott, Paul | Erdos, Michael R. | Estrada, Karol | Ferrucci, Luigi | Fischer, Guido | Forouhi, Nita G. | Gieger, Christian | Grallert, Harald | Groves, Christopher J. | Grundy, Scott | Guiducci, Candace | Hadley, David | Hamsten, Anders | Havulinna, Aki S. | Hofman, Albert | Holle, Rolf | Holloway, John W. | Illig, Thomas | Isomaa, Bo | Jacobs, Leonie C. | Jameson, Karen | Jousilahti, Pekka | Karpe, Fredrik | Kuusisto, Johanna | Laitinen, Jaana | Lathrop, G. Mark | Lawlor, Debbie A. | Mangino, Massimo | McArdle, Wendy L. | Meitinger, Thomas | Morken, Mario A. | Morris, Andrew P. | Munroe, Patricia | Narisu, Narisu | Nordström, Anna | Nordström, Peter | Oostra, Ben A. | Palmer, Colin N. A. | Payne, Felicity | Peden, John F. | Prokopenko, Inga | Renström, Frida | Ruokonen, Aimo | Salomaa, Veikko | Sandhu, Manjinder S. | Scott, Laura J. | Scuteri, Angelo | Silander, Kaisa | Song, Kijoung | Yuan, Xin | Stringham, Heather M. | Swift, Amy J. | Tuomi, Tiinamaija | Uda, Manuela | Vollenweider, Peter | Waeber, Gerard | Wallace, Chris | Walters, G. Bragi | Weedon, Michael N. | Witteman, Jacqueline C. M. | Zhang, Cuilin | Zhang, Weihua | Caulfield, Mark J. | Collins, Francis S. | Davey Smith, George | Day, Ian N. M. | Franks, Paul W. | Hattersley, Andrew T. | Hu, Frank B. | Jarvelin, Marjo-Riitta | Kong, Augustine | Kooner, Jaspal S. | Laakso, Markku | Lakatta, Edward | Mooser, Vincent | Morris, Andrew D. | Peltonen, Leena | Samani, Nilesh J. | Spector, Timothy D. | Strachan, David P. | Tanaka, Toshiko | Tuomilehto, Jaakko | Uitterlinden, André G. | van Duijn, Cornelia M. | Wareham, Nicholas J. | Watkins for the PROCARDIS consortia, Hugh | Waterworth, Dawn M. | Boehnke, Michael | Deloukas, Panos | Groop, Leif | Hunter, David J. | Thorsteinsdottir, Unnur | Schlessinger, David | Wichmann, H.-Erich | Frayling, Timothy M. | Abecasis, Gonçalo R. | Hirschhorn, Joel N. | Loos, Ruth J. F. | Stefansson, Kari | Mohlke, Karen L. | Barroso, Inês | McCarthy for the GIANT consortium, Mark I.
PLoS Genetics  2009;5(7):10.1371/annotation/b6e8f9f6-2496-4a40-b0e3-e1d1390c1928.
doi:10.1371/annotation/b6e8f9f6-2496-4a40-b0e3-e1d1390c1928
PMCID: PMC2722420
5.  Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution 
Lindgren, Cecilia M. | Heid, Iris M. | Randall, Joshua C. | Lamina, Claudia | Steinthorsdottir, Valgerdur | Qi, Lu | Speliotes, Elizabeth K. | Thorleifsson, Gudmar | Willer, Cristen J. | Herrera, Blanca M. | Jackson, Anne U. | Lim, Noha | Scheet, Paul | Soranzo, Nicole | Amin, Najaf | Aulchenko, Yurii S. | Chambers, John C. | Drong, Alexander | Luan, Jian'an | Lyon, Helen N. | Rivadeneira, Fernando | Sanna, Serena | Timpson, Nicholas J. | Zillikens, M. Carola | Zhao, Jing Hua | Almgren, Peter | Bandinelli, Stefania | Bennett, Amanda J. | Bergman, Richard N. | Bonnycastle, Lori L. | Bumpstead, Suzannah J. | Chanock, Stephen J. | Cherkas, Lynn | Chines, Peter | Coin, Lachlan | Cooper, Cyrus | Crawford, Gabriel | Doering, Angela | Dominiczak, Anna | Doney, Alex S. F. | Ebrahim, Shah | Elliott, Paul | Erdos, Michael R. | Estrada, Karol | Ferrucci, Luigi | Fischer, Guido | Forouhi, Nita G. | Gieger, Christian | Grallert, Harald | Groves, Christopher J. | Grundy, Scott | Guiducci, Candace | Hadley, David | Hamsten, Anders | Havulinna, Aki S. | Hofman, Albert | Holle, Rolf | Holloway, John W. | Illig, Thomas | Isomaa, Bo | Jacobs, Leonie C. | Jameson, Karen | Jousilahti, Pekka | Karpe, Fredrik | Kuusisto, Johanna | Laitinen, Jaana | Lathrop, G. Mark | Lawlor, Debbie A. | Mangino, Massimo | McArdle, Wendy L. | Meitinger, Thomas | Morken, Mario A. | Morris, Andrew P. | Munroe, Patricia | Narisu, Narisu | Nordström, Anna | Nordström, Peter | Oostra, Ben A. | Palmer, Colin N. A. | Payne, Felicity | Peden, John F. | Prokopenko, Inga | Renström, Frida | Ruokonen, Aimo | Salomaa, Veikko | Sandhu, Manjinder S. | Scott, Laura J. | Scuteri, Angelo | Silander, Kaisa | Song, Kijoung | Yuan, Xin | Stringham, Heather M. | Swift, Amy J. | Tuomi, Tiinamaija | Uda, Manuela | Vollenweider, Peter | Waeber, Gerard | Wallace, Chris | Walters, G. Bragi | Weedon, Michael N. | Witteman, Jacqueline C. M. | Zhang, Cuilin | Zhang, Weihua | Caulfield, Mark J. | Collins, Francis S. | Davey Smith, George | Day, Ian N. M. | Franks, Paul W. | Hattersley, Andrew T. | Hu, Frank B. | Jarvelin, Marjo-Riitta | Kong, Augustine | Kooner, Jaspal S. | Laakso, Markku | Lakatta, Edward | Mooser, Vincent | Morris, Andrew D. | Peltonen, Leena | Samani, Nilesh J. | Spector, Timothy D. | Strachan, David P. | Tanaka, Toshiko | Tuomilehto, Jaakko | Uitterlinden, André G. | van Duijn, Cornelia M. | Wareham, Nicholas J. | Watkins for the PROCARDIS consortia, Hugh | Waterworth, Dawn M. | Boehnke, Michael | Deloukas, Panos | Groop, Leif | Hunter, David J. | Thorsteinsdottir, Unnur | Schlessinger, David | Wichmann, H.-Erich | Frayling, Timothy M. | Abecasis, Gonçalo R. | Hirschhorn, Joel N. | Loos, Ruth J. F. | Stefansson, Kari | Mohlke, Karen L. | Barroso, Inês | McCarthy for the GIANT consortium, Mark I. | Allison, David B.
PLoS Genetics  2009;5(6):e1000508.
To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist–hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9×10−11) and MSRA (WC, P = 8.9×10−9). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6×10−8). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
Author Summary
Here, we describe a meta-analysis of genome-wide association data from 38,580 individuals, followed by large-scale replication (in up to 70,689 individuals) designed to uncover variants influencing anthropometric measures of central obesity and fat distribution, namely waist circumference (WC) and waist–hip ratio (WHR). This work complements parallel efforts that have been successful in defining variants impacting overall adiposity and focuses on the visceral fat accumulation which has particularly strong relationships to metabolic and cardiovascular disease. Our analyses have identified two loci (TFAP2B and MSRA) associated with WC, and a further locus, near LYPLAL1, which shows gender-specific relationships with WHR (all to levels of genome-wide significance). These loci vary in the strength of their associations with overall adiposity, and LYPLAL1 in particular appears to have a specific effect on patterns of fat distribution. All in all, these three loci provide novel insights into human physiology and the development of obesity.
doi:10.1371/journal.pgen.1000508
PMCID: PMC2695778  PMID: 19557161
6.  Evaluating the role of LPIN1 variation on insulin resistance, body weight and human lipodystrophy in UK populations 
Diabetes  2008;57(9):2527-2533.
OBJECTIVE:
Loss of Lpin1 activity causes lipodystrophy and insulin resistance in the fld mouse, and LPIN1 expression and common genetic variation were recently suggested to influence adiposity and insulin sensitivity in humans. We aimed to conduct a comprehensive association study to clarify the influence of LPIN1 common variation on adiposity and insulin sensitivity in UK populations, and to examine the role of LPIN1 mutations in insulin resistance syndromes.
RESEARCH DESIGN AND METHOD:
Twenty-two SNPs tagging LPIN1 common variation were genotyped in MRC Ely (N = 1709) and Hertfordshire (N = 2901) population-based cohorts. LPIN1 exons, exon/intron boundaries and 3′UTR were sequenced in 158 patients with idiopathic severe insulin resistance (including 23 lipodystrophic patients), and 48 controls.
RESULTS:
We found no association between LPIN1 SNPs and fasting insulin, but report a nominal association between rs13412852 and BMI (P = 0.042) in a meta-analysis of 8504 samples from in-house and publicly available studies. Three rare nonsynonymous variants (A353T, R552K and G582R) were detected in severely insulin resistant patients. However, these did not co-segregate with disease in affected families and Lipin1 protein expression and phosphorylation in patients with variants was indistinguishable from controls.
CONCLUSIONS:
Our data do not support a major effect of LPIN1 common variation on metabolic traits and suggest that mutations in LPIN1 are not a common cause of lipodystrophy in humans. The nominal associations with BMI and other metabolic traits in UK cohorts require replication in larger cohorts.
doi:10.2337/db08-0422
PMCID: PMC2518506  PMID: 18591397

Results 1-6 (6)