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1.  A Genome-Wide Association Study of Monozygotic Twin-Pairs Suggests a Locus Related to Variability of Serum High-Density Lipoprotein Cholesterol 
Genome-wide association analysis on monozygotic twin pairs offers a route to discovery of gene–environment interactions through testing for variability loci associated with sensitivity to individual environment/lifestyle. We present a genome-wide scan of loci associated with intra-pair differences in serum lipid and apolipoprotein levels. We report data for 1,720 monozygotic female twin pairs from GenomEUtwin project with 2.5 million SNPs, imputed or genotyped, and measured serum lipid fractions for both twins. We found one locus associated with intra-pair differences in high density lipoprotein (HDL) cholesterol, rs2483058 in an intron of SRGAP2, where twins carrying the C allele are more sensitive to environmental factors (p = 3.98 × 10−8). We followed up the association in further genotyped monozygotic twins (N = 1 261) which showed a moderate association for the variant (p = .002, same direction of an effect). In addition, we report a new association on the level of apolipoprotein A-II (p = 4.03 × 10−8).
doi:10.1017/thg.2012.63
PMCID: PMC4333218  PMID: 23031429
twins; association; lipids; apolipoproteins; interaction
2.  Genome-wide association study identifies loci affecting blood copper, selenium and zinc 
Human Molecular Genetics  2013;22(19):3998-4006.
Genetic variation affecting absorption, distribution or excretion of essential trace elements may lead to health effects related to sub-clinical deficiency. We have tested for allelic effects of single-nucleotide polymorphisms (SNPs) on blood copper, selenium and zinc in a genome-wide association study using two adult cohorts from Australia and the UK. Participants were recruited in Australia from twins and their families and in the UK from pregnant women. We measured erythrocyte Cu, Se and Zn (Australian samples) or whole blood Se (UK samples) using inductively coupled plasma mass spectrometry. Genotyping was performed with Illumina chips and >2.5 m SNPs were imputed from HapMap data. Genome-wide significant associations were found for each element. For Cu, there were two loci on chromosome 1 (most significant SNPs rs1175550, P = 5.03 × 10−10, and rs2769264, P = 2.63 × 10−20); for Se, a locus on chromosome 5 was significant in both cohorts (combined P = 9.40 × 10−28 at rs921943); and for Zn three loci on chromosomes 8, 15 and X showed significant results (rs1532423, P = 6.40 × 10−12; rs2120019, P = 1.55 × 10−18; and rs4826508, P = 1.40 × 10−12, respectively). The Se locus covers three genes involved in metabolism of sulphur-containing amino acids and potentially of the analogous Se compounds; the chromosome 8 locus for Zn contains multiple genes for the Zn-containing enzyme carbonic anhydrase. Where potentially relevant genes were identified, they relate to metabolism of the element (Se) or to the presence at high concentration of a metal-containing protein (Cu).
doi:10.1093/hmg/ddt239
PMCID: PMC3766178  PMID: 23720494
3.  Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index 
Hoggart, Clive J. | Venturini, Giulia | Mangino, Massimo | Gomez, Felicia | Ascari, Giulia | Zhao, Jing Hua | Teumer, Alexander | Winkler, Thomas W. | Tšernikova, Natalia | Luan, Jian'an | Mihailov, Evelin | Ehret, Georg B. | Zhang, Weihua | Lamparter, David | Esko, Tõnu | Macé, Aurelien | Rüeger, Sina | Bochud, Pierre-Yves | Barcella, Matteo | Dauvilliers, Yves | Benyamin, Beben | Evans, David M. | Hayward, Caroline | Lopez, Mary F. | Franke, Lude | Russo, Alessia | Heid, Iris M. | Salvi, Erika | Vendantam, Sailaja | Arking, Dan E. | Boerwinkle, Eric | Chambers, John C. | Fiorito, Giovanni | Grallert, Harald | Guarrera, Simonetta | Homuth, Georg | Huffman, Jennifer E. | Porteous, David | Moradpour, Darius | Iranzo, Alex | Hebebrand, Johannes | Kemp, John P. | Lammers, Gert J. | Aubert, Vincent | Heim, Markus H. | Martin, Nicholas G. | Montgomery, Grant W. | Peraita-Adrados, Rosa | Santamaria, Joan | Negro, Francesco | Schmidt, Carsten O. | Scott, Robert A. | Spector, Tim D. | Strauch, Konstantin | Völzke, Henry | Wareham, Nicholas J. | Yuan, Wei | Bell, Jordana T. | Chakravarti, Aravinda | Kooner, Jaspal S. | Peters, Annette | Matullo, Giuseppe | Wallaschofski, Henri | Whitfield, John B. | Paccaud, Fred | Vollenweider, Peter | Bergmann, Sven | Beckmann, Jacques S. | Tafti, Mehdi | Hastie, Nicholas D. | Cusi, Daniele | Bochud, Murielle | Frayling, Timothy M. | Metspalu, Andres | Jarvelin, Marjo-Riitta | Scherag, André | Smith, George Davey | Borecki, Ingrid B. | Rousson, Valentin | Hirschhorn, Joel N. | Rivolta, Carlo | Loos, Ruth J. F. | Kutalik, Zoltán
PLoS Genetics  2014;10(7):e1004508.
The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.
Author Summary
Large genetic association studies have revealed many genetic factors influencing common traits, such as body mass index (BMI). These studies assume that the effect of genetic variants is the same regardless of whether they are inherited from the mother or the father. In our study, we have developed a new approach that allows us to investigate variants whose impact depends on their parental origin (parent-of-origin effects), in unrelated samples when the parental origin cannot be inferred. This is feasible because at genetic markers at which such effects occur there is increased variability of the trait among individuals who inherited different genetic codes from their mother and their father compared to individuals who inherited the same genetic code from both parents. We applied this methodology to discover genetic markers with parent-of-origin effects (POEs) on BMI. This resulted in six candidate markers showing strong POE association. We then attempted to replicate the POE effects of these markers in family studies (where one can infer the parental origin of the inherited variants). Two of our candidates showed significant association in the family studies, the paternal and maternal effects of these markers were in the opposite direction.
doi:10.1371/journal.pgen.1004508
PMCID: PMC4117451  PMID: 25078964
4.  Identification of heart rate–associated loci and their effects on cardiac conduction and rhythm disorders 
den Hoed, Marcel | Eijgelsheim, Mark | Esko, Tõnu | Brundel, Bianca J J M | Peal, David S | Evans, David M | Nolte, Ilja M | Segrè, Ayellet V | Holm, Hilma | Handsaker, Robert E | Westra, Harm-Jan | Johnson, Toby | Isaacs, Aaron | Yang, Jian | Lundby, Alicia | Zhao, Jing Hua | Kim, Young Jin | Go, Min Jin | Almgren, Peter | Bochud, Murielle | Boucher, Gabrielle | Cornelis, Marilyn C | Gudbjartsson, Daniel | Hadley, David | Van Der Harst, Pim | Hayward, Caroline | Heijer, Martin Den | Igl, Wilmar | Jackson, Anne U | Kutalik, Zoltán | Luan, Jian’an | Kemp, John P | Kristiansson, Kati | Ladenvall, Claes | Lorentzon, Mattias | Montasser, May E | Njajou, Omer T | O’Reilly, Paul F | Padmanabhan, Sandosh | Pourcain, Beate St. | Rankinen, Tuomo | Salo, Perttu | Tanaka, Toshiko | Timpson, Nicholas J | Vitart, Veronique | Waite, Lindsay | Wheeler, William | Zhang, Weihua | Draisma, Harmen H M | Feitosa, Mary F | Kerr, Kathleen F | Lind, Penelope A | Mihailov, Evelin | Onland-Moret, N Charlotte | Song, Ci | Weedon, Michael N | Xie, Weijia | Yengo, Loic | Absher, Devin | Albert, Christine M | Alonso, Alvaro | Arking, Dan E | de Bakker, Paul I W | Balkau, Beverley | Barlassina, Cristina | Benaglio, Paola | Bis, Joshua C | Bouatia-Naji, Nabila | Brage, Søren | Chanock, Stephen J | Chines, Peter S | Chung, Mina | Darbar, Dawood | Dina, Christian | Dörr, Marcus | Elliott, Paul | Felix, Stephan B | Fischer, Krista | Fuchsberger, Christian | de Geus, Eco J C | Goyette, Philippe | Gudnason, Vilmundur | Harris, Tamara B | Hartikainen, Anna-liisa | Havulinna, Aki S | Heckbert, Susan R | Hicks, Andrew A | Hofman, Albert | Holewijn, Suzanne | Hoogstra-Berends, Femke | Hottenga, Jouke-Jan | Jensen, Majken K | Johansson, Åsa | Junttila, Juhani | Kääb, Stefan | Kanon, Bart | Ketkar, Shamika | Khaw, Kay-Tee | Knowles, Joshua W | Kooner, Angrad S | Kors, Jan A | Kumari, Meena | Milani, Lili | Laiho, Päivi | Lakatta, Edward G | Langenberg, Claudia | Leusink, Maarten | Liu, Yongmei | Luben, Robert N | Lunetta, Kathryn L | Lynch, Stacey N | Markus, Marcello R P | Marques-Vidal, Pedro | Leach, Irene Mateo | McArdle, Wendy L | McCarroll, Steven A | Medland, Sarah E | Miller, Kathryn A | Montgomery, Grant W | Morrison, Alanna C | Müller-Nurasyid, Martina | Navarro, Pau | Nelis, Mari | O’Connell, Jeffrey R | O’Donnell, Christopher J | Ong, Ken K | Newman, Anne B | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P | Psaty, Bruce M | Rao, Dabeeru C | Ring, Susan M | Rossin, Elizabeth J | Rudan, Diana | Sanna, Serena | Scott, Robert A | Sehmi, Jaban S | Sharp, Stephen | Shin, Jordan T | Singleton, Andrew B | Smith, Albert V | Soranzo, Nicole | Spector, Tim D | Stewart, Chip | Stringham, Heather M | Tarasov, Kirill V | Uitterlinden, André G | Vandenput, Liesbeth | Hwang, Shih-Jen | Whitfield, John B | Wijmenga, Cisca | Wild, Sarah H | Willemsen, Gonneke | Wilson, James F | Witteman, Jacqueline C M | Wong, Andrew | Wong, Quenna | Jamshidi, Yalda | Zitting, Paavo | Boer, Jolanda M A | Boomsma, Dorret I | Borecki, Ingrid B | Van Duijn, Cornelia M | Ekelund, Ulf | Forouhi, Nita G | Froguel, Philippe | Hingorani, Aroon | Ingelsson, Erik | Kivimaki, Mika | Kronmal, Richard A | Kuh, Diana | Lind, Lars | Martin, Nicholas G | Oostra, Ben A | Pedersen, Nancy L | Quertermous, Thomas | Rotter, Jerome I | van der Schouw, Yvonne T | Verschuren, W M Monique | Walker, Mark | Albanes, Demetrius | Arnar, David O | Assimes, Themistocles L | Bandinelli, Stefania | Boehnke, Michael | de Boer, Rudolf A | Bouchard, Claude | Caulfield, W L Mark | Chambers, John C | Curhan, Gary | Cusi, Daniele | Eriksson, Johan | Ferrucci, Luigi | van Gilst, Wiek H | Glorioso, Nicola | de Graaf, Jacqueline | Groop, Leif | Gyllensten, Ulf | Hsueh, Wen-Chi | Hu, Frank B | Huikuri, Heikki V | Hunter, David J | Iribarren, Carlos | Isomaa, Bo | Jarvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kiemeney, Lambertus A | van der Klauw, Melanie M | Kooner, Jaspal S | Kraft, Peter | Iacoviello, Licia | Lehtimäki, Terho | Lokki, Marja-Liisa L | Mitchell, Braxton D | Navis, Gerjan | Nieminen, Markku S | Ohlsson, Claes | Poulter, Neil R | Qi, Lu | Raitakari, Olli T | Rimm, Eric B | Rioux, John D | Rizzi, Federica | Rudan, Igor | Salomaa, Veikko | Sever, Peter S | Shields, Denis C | Shuldiner, Alan R | Sinisalo, Juha | Stanton, Alice V | Stolk, Ronald P | Strachan, David P | Tardif, Jean-Claude | Thorsteinsdottir, Unnur | Tuomilehto, Jaako | van Veldhuisen, Dirk J | Virtamo, Jarmo | Viikari, Jorma | Vollenweider, Peter | Waeber, Gérard | Widen, Elisabeth | Cho, Yoon Shin | Olsen, Jesper V | Visscher, Peter M | Willer, Cristen | Franke, Lude | Erdmann, Jeanette | Thompson, John R | Pfeufer, Arne | Sotoodehnia, Nona | Newton-Cheh, Christopher | Ellinor, Patrick T | Stricker, Bruno H Ch | Metspalu, Andres | Perola, Markus | Beckmann, Jacques S | Smith, George Davey | Stefansson, Kari | Wareham, Nicholas J | Munroe, Patricia B | Sibon, Ody C M | Milan, David J | Snieder, Harold | Samani, Nilesh J | Loos, Ruth J F
Nature genetics  2013;45(6):621-631.
Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate–increasing and heart rate–decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
doi:10.1038/ng.2610
PMCID: PMC3696959  PMID: 23583979
5.  A genome wide association study of alcohol dependence symptom counts in extended pedigrees identifies C15orf53 
Molecular psychiatry  2012;18(11):10.1038/mp.2012.143.
Several studies have identified genes associated with alcohol use disorders, but the variation in each of these genes explains only a small portion of the genetic vulnerability. The goal of the present study was to perform a genome-wide association study (GWAS) in extended families from the Collaborative Study on the Genetics of Alcoholism (COGA) to identify novel genes affecting risk for alcohol dependence. To maximize the power of the extended family design we used a quantitative endophenotype, measured in all individuals: number of alcohol dependence symptoms endorsed (symptom count). Secondary analyses were performed to determine if the single nucleotide polymorphisms (SNPs) associated with symptom count were also associated with the dichotomous phenotype, DSM-IV alcohol dependence. This family-based GWAS identified SNPs in C15orf53 that are strongly associated with DSM-IV alcohol (p=4.5×10−8, inflation corrected p=9.4×10−7). Results with DSM-IV alcohol dependence in the regions of interest support our findings with symptom count, though the associations were less significant. Attempted replications of the most promising association results were conducted in two independent samples: non-overlapping subjects from the Study of Addiction: Genes and Environment (SAGE) and the Australian twin-family study of alcohol use disorders (OZALC). Nominal association of C15orf53 with symptom count was observed in SAGE. The variant that showed strongest association with symptom count, rs12912251 and its highly correlated variants (D′=1, r2≥ 0.95), has previously been associated with risk for bipolar disorder.
doi:10.1038/mp.2012.143
PMCID: PMC3752321  PMID: 23089632
DSM-IV alcohol dependence symptoms; Family-based GWAS; C15orf53; Quantitative traits
6.  Discovery and Refinement of Loci Associated with Lipid Levels 
Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Do, Ron | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian’an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O’Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Ingi Eyjolfsson, Gudmundur | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Kathiresan, Sekar | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Gonçalo R.
Nature genetics  2013;45(11):10.1038/ng.2797.
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
doi:10.1038/ng.2797
PMCID: PMC3838666  PMID: 24097068
7.  Metabolic and biochemical effects of low-to-moderate alcohol consumption 
Background
Alcohol consumption has multiple biochemical consequences. Only a few of these are useful as diagnostic markers but many reflect potentially harmful or beneficial effects of alcohol. Average consumption of two to four drinks per day is associated with lower overall or cardiovascular mortality risk than either lower or higher intake. We have analysed the dose-response relationships between reported alcohol consumption and 17 biomarkers, with emphasis on intake of up to three drinks per day.
Methods
Biochemical tests were performed on serum from 8396 study participants (3750 men and 4646 women, aged 51 ± 13 years, range 18–93) who had provided information on alcohol consumption in the week preceding blood collection.
Results
GGT, ALT, AST, CDT, urate, ferritin and bilirubin showed little or no change with alcohol consumption below two to three drinks per day, but increased with higher intake. HDL-C and albumin showed increasing results, and insulin showed decreasing results, across the entire range of alcohol use. Biphasic responses, where subjects reporting one to two drinks per day had lower results than those reporting either more or less alcohol use, occurred for triglycerides, glucose, C-reactive protein, alkaline phosphatase and butyrylcholinesterase. Increasing alcohol use was associated with decreasing LDL-C in younger women, but higher LDL-C in older men.
Conclusions
Some markers show threshold relationships with alcohol, others show continuous ones, and a third group show biphasic or U-shaped relationships. Overall the biochemical sequelae of low-to-moderate alcohol use are consistent with the epidemiological evidence on morbidity and mortality.
doi:10.1111/acer.12015
PMCID: PMC3568441  PMID: 23134229
Alcohol; Biomarkers; Dose-response curve; Population study
8.  Genetic Insights into Cardiometabolic Risk Factors 
Many biochemical traits are recognised as risk factors, which contribute to or predict the development of disease. Only a few are in widespread use, usually to assist with treatment decisions and motivate behavioural change. The greatest effort has gone into evaluation of risk factors for cardiovascular disease and/or diabetes, with substantial overlap as ‘cardiometabolic’ risk. Over the past few years many genome-wide association studies (GWAS) have sought to account for variation in risk factors, with the expectation that identifying relevant polymorphisms would improve our understanding or prediction of disease; others have taken the direct approach of genomic case-control studies for the corresponding diseases. Large GWAS have been published for coronary heart disease and Type 2 diabetes, and also for associated biomarkers or risk factors including body mass index, lipids, C-reactive protein, urate, liver function tests, glucose and insulin. Results are not encouraging for personal risk prediction based on genotyping, mainly because known risk loci only account for a small proportion of risk. Overlap of allelic associations between disease and marker, as found for low density lipoprotein cholesterol and heart disease, supports a causal association, but in other cases genetic studies have cast doubt on accepted risk factors. Some loci show unexpected effects on multiple markers or diseases. An intriguing feature of risk factors is the blurring of categories shown by the correlation between them and the genetic overlap between diseases previously thought of as distinct. GWAS can provide insight into relationships between risk factors, biomarkers and diseases, with potential for new approaches to disease classification.
PMCID: PMC3961996  PMID: 24659834
9.  Association between in vivo alcohol metabolism and genetic variation in pathways that metabolize the carbon skeleton of ethanol and NADH reoxidation in the Alcohol Challenge Twin Study 
Background
Variation in alcohol metabolism affects the duration of intoxication and alcohol use. While the majority of genetic association studies investigating variation in alcohol metabolism have focused on polymorphisms in alcohol or aldehyde dehydrogenases, we have now tested for association with genes in alternative metabolic pathways that catalyze the carbon skeleton of ethanol and NADH reoxidation.
Methods
950 single nucleotide polymorphisms (SNPs) spanning 14 genes (ACN9, ACSS1, ACSS2, ALDH1A1, CAT, CYP2E1, GOT1, GOT2, MDH1, MDH2, SLC25A10, SLC25A11, SLC25A12, SLC25A13) were genotyped in 352 young adults who participated in an alcohol challenge study. Traits tested were blood and breath alcohol concentration, peak alcohol concentration and rates of alcohol absorption and elimination. Allelic association was tested using quantitative univariate and multivariate methods.
Results
A CYP2E1 promoter SNP (rs4838767, minor allele frequency 0.008) exceeded the threshold for study-wide significance (4.01 × 10−5) for two early blood alcohol concentration (BAC), eight breath alcohol concentration (BrAC) measures and the peak BrAC. For each phenotype the minor C-allele was related to a lower alcohol concentration, most strongly for the fourth BrAC (P = 2.07 × 10−7) explaining ~8% of the phenotypic variance. We also observed suggestive patterns of association with variants in ALDH1A1 and on chromosome 17 near SLC25A11 for aspects of blood and breath alcohol metabolism. A SNP upstream of GOT1 (rs2490286) reached study-wide significance for multivariate BAC metabolism (P = 0.000040).
Conclusions
Overall, we did not find strong evidence that variation in genes coding for proteins that further metabolize the carbon backbone of acetaldehyde, or contribute to mechanisms for regenerating NAD from NADH, affects alcohol metabolism in our European-descent subjects. However, based on the breath alcohol data, variation in the promoter of CYP2E1 may play a role in pre-absorptive or early hepatic alcohol metabolism, but more samples are required to validate this finding.
doi:10.1111/j.1530-0277.2012.01829.x
PMCID: PMC3729587  PMID: 22577853
alcohol metabolism; association; genetics; CYP2E1; alcohol challenge
10.  Mining the Human Phenome Using Allelic Scores That Index Biological Intermediates 
PLoS Genetics  2013;9(10):e1003919.
It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.
Author Summary
The standard approach in genome-wide association studies is to analyse the relationship between genetic variants and disease one marker at a time. Significant associations between markers and disease are then used as evidence to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically only explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates than single markers, and then use these scores to data mine genome-wide association studies. We show how allelic scores derived from known variants as well as allelic scores derived from hundreds of thousands of genetic markers across the genome explain significant portions of the variance in body mass index, levels of C-reactive protein, and LDLc cholesterol, and many of these scores show expected correlations with disease. Power calculations confirm the feasibility of scaling our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. Our method represents a simple way in which tens of thousands of molecular phenotypes could be screened for potential causal relationships with disease.
doi:10.1371/journal.pgen.1003919
PMCID: PMC3814299  PMID: 24204319
11.  Genome-wide association analyses identify 18 new loci associated with serum urate concentrations 
Köttgen, Anna | Albrecht, Eva | Teumer, Alexander | Vitart, Veronique | Krumsiek, Jan | Hundertmark, Claudia | Pistis, Giorgio | Ruggiero, Daniela | O’Seaghdha, Conall M | Haller, Toomas | Yang, Qiong | Tanaka, Toshiko | Johnson, Andrew D | Kutalik, Zoltán | Smith, Albert V | Shi, Julia | Struchalin, Maksim | Middelberg, Rita P S | Brown, Morris J | Gaffo, Angelo L | Pirastu, Nicola | Li, Guo | Hayward, Caroline | Zemunik, Tatijana | Huffman, Jennifer | Yengo, Loic | Zhao, Jing Hua | Demirkan, Ayse | Feitosa, Mary F | Liu, Xuan | Malerba, Giovanni | Lopez, Lorna M | van der Harst, Pim | Li, Xinzhong | Kleber, Marcus E | Hicks, Andrew A | Nolte, Ilja M | Johansson, Asa | Murgia, Federico | Wild, Sarah H | Bakker, Stephan J L | Peden, John F | Dehghan, Abbas | Steri, Maristella | Tenesa, Albert | Lagou, Vasiliki | Salo, Perttu | Mangino, Massimo | Rose, Lynda M | Lehtimäki, Terho | Woodward, Owen M | Okada, Yukinori | Tin, Adrienne | Müller, Christian | Oldmeadow, Christopher | Putku, Margus | Czamara, Darina | Kraft, Peter | Frogheri, Laura | Thun, Gian Andri | Grotevendt, Anne | Gislason, Gauti Kjartan | Harris, Tamara B | Launer, Lenore J | McArdle, Patrick | Shuldiner, Alan R | Boerwinkle, Eric | Coresh, Josef | Schmidt, Helena | Schallert, Michael | Martin, Nicholas G | Montgomery, Grant W | Kubo, Michiaki | Nakamura, Yusuke | Tanaka, Toshihiro | Munroe, Patricia B | Samani, Nilesh J | Jacobs, David R | Liu, Kiang | D’Adamo, Pio | Ulivi, Sheila | Rotter, Jerome I | Psaty, Bruce M | Vollenweider, Peter | Waeber, Gerard | Campbell, Susan | Devuyst, Olivier | Navarro, Pau | Kolcic, Ivana | Hastie, Nicholas | Balkau, Beverley | Froguel, Philippe | Esko, Tõnu | Salumets, Andres | Khaw, Kay Tee | Langenberg, Claudia | Wareham, Nicholas J | Isaacs, Aaron | Kraja, Aldi | Zhang, Qunyuan | Wild, Philipp S | Scott, Rodney J | Holliday, Elizabeth G | Org, Elin | Viigimaa, Margus | Bandinelli, Stefania | Metter, Jeffrey E | Lupo, Antonio | Trabetti, Elisabetta | Sorice, Rossella | Döring, Angela | Lattka, Eva | Strauch, Konstantin | Theis, Fabian | Waldenberger, Melanie | Wichmann, H-Erich | Davies, Gail | Gow, Alan J | Bruinenberg, Marcel | Study, LifeLines Cohort | Stolk, Ronald P | Kooner, Jaspal S | Zhang, Weihua | Winkelmann, Bernhard R | Boehm, Bernhard O | Lucae, Susanne | Penninx, Brenda W | Smit, Johannes H | Curhan, Gary | Mudgal, Poorva | Plenge, Robert M | Portas, Laura | Persico, Ivana | Kirin, Mirna | Wilson, James F | Leach, Irene Mateo | van Gilst, Wiek H | Goel, Anuj | Ongen, Halit | Hofman, Albert | Rivadeneira, Fernando | Uitterlinden, Andre G | Imboden, Medea | von Eckardstein, Arnold | Cucca, Francesco | Nagaraja, Ramaiah | Piras, Maria Grazia | Nauck, Matthias | Schurmann, Claudia | Budde, Kathrin | Ernst, Florian | Farrington, Susan M | Theodoratou, Evropi | Prokopenko, Inga | Stumvoll, Michael | Jula, Antti | Perola, Markus | Salomaa, Veikko | Shin, So-Youn | Spector, Tim D | Sala, Cinzia | Ridker, Paul M | Kähönen, Mika | Viikari, Jorma | Hengstenberg, Christian | Nelson, Christopher P | Consortium, CARDIoGRAM | Consortium, DIAGRAM | Consortium, ICBP | Consortium, MAGIC | Meschia, James F | Nalls, Michael A | Sharma, Pankaj | Singleton, Andrew B | Kamatani, Naoyuki | Zeller, Tanja | Burnier, Michel | Attia, John | Laan, Maris | Klopp, Norman | Hillege, Hans L | Kloiber, Stefan | Choi, Hyon | Pirastu, Mario | Tore, Silvia | Probst-Hensch, Nicole M | Völzke, Henry | Gudnason, Vilmundur | Parsa, Afshin | Schmidt, Reinhold | Whitfield, John B | Fornage, Myriam | Gasparini, Paolo | Siscovick, David S | Polašek, Ozren | Campbell, Harry | Rudan, Igor | Bouatia-Naji, Nabila | Metspalu, Andres | Loos, Ruth J F | van Duijn, Cornelia M | Borecki, Ingrid B | Ferrucci, Luigi | Gambaro, Giovanni | Deary, Ian J | Wolffenbuttel, Bruce H R | Chambers, John C | März, Winfried | Pramstaller, Peter P | Snieder, Harold | Gyllensten, Ulf | Wright, Alan F | Navis, Gerjan | Watkins, Hugh | Witteman, Jacqueline C M | Sanna, Serena | Schipf, Sabine | Dunlop, Malcolm G | Tönjes, Anke | Ripatti, Samuli | Soranzo, Nicole | Toniolo, Daniela | Chasman, Daniel I | Raitakari, Olli | Kao, W H Linda | Ciullo, Marina | Fox, Caroline S | Caulfield, Mark | Bochud, Murielle | Gieger, Christian
Nature genetics  2012;45(2):145-154.
Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.
doi:10.1038/ng.2500
PMCID: PMC3663712  PMID: 23263486
12.  The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis 
Fall, Tove | Hägg, Sara | Mägi, Reedik | Ploner, Alexander | Fischer, Krista | Horikoshi, Momoko | Sarin, Antti-Pekka | Thorleifsson, Gudmar | Ladenvall, Claes | Kals, Mart | Kuningas, Maris | Draisma, Harmen H. M. | Ried, Janina S. | van Zuydam, Natalie R. | Huikari, Ville | Mangino, Massimo | Sonestedt, Emily | Benyamin, Beben | Nelson, Christopher P. | Rivera, Natalia V. | Kristiansson, Kati | Shen, Huei-yi | Havulinna, Aki S. | Dehghan, Abbas | Donnelly, Louise A. | Kaakinen, Marika | Nuotio, Marja-Liisa | Robertson, Neil | de Bruijn, Renée F. A. G. | Ikram, M. Arfan | Amin, Najaf | Balmforth, Anthony J. | Braund, Peter S. | Doney, Alexander S. F. | Döring, Angela | Elliott, Paul | Esko, Tõnu | Franco, Oscar H. | Gretarsdottir, Solveig | Hartikainen, Anna-Liisa | Heikkilä, Kauko | Herzig, Karl-Heinz | Holm, Hilma | Hottenga, Jouke Jan | Hyppönen, Elina | Illig, Thomas | Isaacs, Aaron | Isomaa, Bo | Karssen, Lennart C. | Kettunen, Johannes | Koenig, Wolfgang | Kuulasmaa, Kari | Laatikainen, Tiina | Laitinen, Jaana | Lindgren, Cecilia | Lyssenko, Valeriya | Läärä, Esa | Rayner, Nigel W. | Männistö, Satu | Pouta, Anneli | Rathmann, Wolfgang | Rivadeneira, Fernando | Ruokonen, Aimo | Savolainen, Markku J. | Sijbrands, Eric J. G. | Small, Kerrin S. | Smit, Jan H. | Steinthorsdottir, Valgerdur | Syvänen, Ann-Christine | Taanila, Anja | Tobin, Martin D. | Uitterlinden, Andre G. | Willems, Sara M. | Willemsen, Gonneke | Witteman, Jacqueline | Perola, Markus | Evans, Alun | Ferrières, Jean | Virtamo, Jarmo | Kee, Frank | Tregouet, David-Alexandre | Arveiler, Dominique | Amouyel, Philippe | Ferrario, Marco M. | Brambilla, Paolo | Hall, Alistair S. | Heath, Andrew C. | Madden, Pamela A. F. | Martin, Nicholas G. | Montgomery, Grant W. | Whitfield, John B. | Jula, Antti | Knekt, Paul | Oostra, Ben | van Duijn, Cornelia M. | Penninx, Brenda W. J. H. | Davey Smith, George | Kaprio, Jaakko | Samani, Nilesh J. | Gieger, Christian | Peters, Annette | Wichmann, H.-Erich | Boomsma, Dorret I. | de Geus, Eco J. C. | Tuomi, TiinaMaija | Power, Chris | Hammond, Christopher J. | Spector, Tim D. | Lind, Lars | Orho-Melander, Marju | Palmer, Colin Neil Alexander | Morris, Andrew D. | Groop, Leif | Järvelin, Marjo-Riitta | Salomaa, Veikko | Vartiainen, Erkki | Hofman, Albert | Ripatti, Samuli | Metspalu, Andres | Thorsteinsdottir, Unnur | Stefansson, Kari | Pedersen, Nancy L. | McCarthy, Mark I. | Ingelsson, Erik | Prokopenko, Inga
PLoS Medicine  2013;10(6):e1001474.
In this study, Prokopenko and colleagues provide novel evidence for causal relationship between adiposity and heart failure and increased liver enzymes using a Mendelian randomization study design.
Please see later in the article for the Editors' Summary
Background
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
Conclusions
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Editors' Summary
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a major cause of illness and death worldwide. In the US, for example, coronary heart disease—a CVD in which narrowing of the heart's blood vessels by fatty deposits slows the blood supply to the heart and may eventually cause a heart attack—is the leading cause of death, and stroke—a CVD in which the brain's blood supply is interrupted—is the fourth leading cause of death. Globally, both the incidence of CVD (the number of new cases in a population every year) and its prevalence (the proportion of the population with CVD) are increasing, particularly in low- and middle-income countries. This increasing burden of CVD is occurring in parallel with a global increase in the incidence and prevalence of obesity—having an unhealthy amount of body fat (adiposity)—and of metabolic diseases—conditions such as diabetes in which metabolism (the processes that the body uses to make energy from food) is disrupted, with resulting high blood sugar and damage to the blood vessels.
Why Was This Study Done?
Epidemiological studies—investigations that record the patterns and causes of disease in populations—have reported an association between adiposity (indicated by an increased body mass index [BMI], which is calculated by dividing body weight in kilograms by height in meters squared) and cardiometabolic traits such as coronary heart disease, stroke, heart failure (a condition in which the heart is incapable of pumping sufficient amounts of blood around the body), diabetes, high blood pressure (hypertension), and high blood cholesterol (dyslipidemia). However, observational studies cannot prove that adiposity causes any particular cardiometabolic trait because overweight individuals may share other characteristics (confounding factors) that are the real causes of both obesity and the cardiometabolic disease. Moreover, it is possible that having CVD or a metabolic disease causes obesity (reverse causation). For example, individuals with heart failure cannot do much exercise, so heart failure may cause obesity rather than vice versa. Here, the researchers use “Mendelian randomization” to examine whether adiposity is causally related to various cardiometabolic traits. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. It is known that a genetic variant (rs9939609) within the genome region that encodes the fat-mass- and obesity-associated gene (FTO) is associated with increased BMI. Thus, an investigation of the associations between rs9939609 and cardiometabolic traits can indicate whether obesity is causally related to these traits.
What Did the Researchers Do and Find?
The researchers analyzed the association between rs9939609 (the “instrumental variable,” or IV) and BMI, between rs9939609 and 24 cardiometabolic traits, and between BMI and the same traits using genetic and health data collected in 36 population-based studies of nearly 200,000 individuals of European descent. They then quantified the strength of the causal association between BMI and the cardiometabolic traits by calculating “IV estimators.” Higher BMI showed a causal relationship with heart failure, metabolic syndrome (a combination of medical disorders that increases the risk of developing CVD), type 2 diabetes, dyslipidemia, hypertension, increased blood levels of liver enzymes (an indicator of liver damage; some metabolic disorders involve liver damage), and several other cardiometabolic traits. All the IV estimators were similar to the BMI–cardiovascular trait associations (observational estimates) derived from the same individuals, with the exception of diabetes, where the causal estimate was higher than the observational estimate, probably because the observational estimate is based on a single BMI measurement, whereas the causal estimate considers lifetime changes in BMI.
What Do These Findings Mean?
Like all Mendelian randomization studies, the reliability of the causal associations reported here depends on several assumptions made by the researchers. Nevertheless, these findings provide support for many previously suspected and biologically plausible causal relationships, such as that between adiposity and hypertension. They also provide new insights into the causal effect of obesity on liver enzyme levels and on heart failure. In the latter case, these findings suggest that a one-unit increase in BMI might increase the incidence of heart failure by 17%. In the US, this corresponds to 113,000 additional cases of heart failure for every unit increase in BMI at the population level. Although additional studies are needed to confirm and extend these findings, these results suggest that global efforts to reduce the burden of obesity will likely also reduce the occurrence of CVD and metabolic disorders.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001474.
The American Heart Association provides information on all aspects of cardiovascular disease and tips on keeping the heart healthy, including weight management (in several languages); its website includes personal stories about stroke and heart attacks
The US Centers for Disease Control and Prevention has information on heart disease, stroke, and all aspects of overweight and obesity (in English and Spanish)
The UK National Health Service Choices website provides information about cardiovascular disease and obesity, including a personal story about losing weight
The World Health Organization provides information on obesity (in several languages)
The International Obesity Taskforce provides information about the global obesity epidemic
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
MedlinePlus provides links to other sources of information on heart disease, on vascular disease, on obesity, and on metabolic disorders (in English and Spanish)
The International Association for the Study of Obesity provides maps and information about obesity worldwide
The International Diabetes Federation has a web page that describes types, complications, and risk factors of diabetes
doi:10.1371/journal.pmed.1001474
PMCID: PMC3692470  PMID: 23824655
13.  Neuropeptide Y (NPY) 
Objectives
This study sought to understand whether genetic variation at the Neuropeptide Y (NPY) locus governs secretion and stress responses in vivo as well as NPY gene expression in sympathochromaffin cells.
Background
The NPY is a potent pressor peptide co-released with catecholamines during stress by sympathetic axons. Genome-wide linkage on NPY secretion identified a LOD (logarithm of the odds ratio) peak spanning the NPY locus on chromosome 7p15.
Methods
Our approach began with genomics (linkage and polymorphism determination), extended into NPY genetic control of heritable stress traits in twin pairs, established transcriptional mechanisms in transfected chromaffin cells, and concluded with observations on blood pressure (BP) in the population.
Results
Systematic polymorphism tabulation at NPY (by re-sequencing across the locus: promoter, 4 exons, exon/intron borders, and untranslated regions; on 2n = 160 chromosomes of diverse biogeographic ancestries) identified 16 variants, of which 5 were common. We then studied healthy twin/sibling pairs (n = 399 individuals), typing 6 polymorphisms spanning the locus. Haplotype and single nucleotide polymorphism analyses indicated that proximal promoter variant ∇−880Δ (2-bp TG/—, Ins/Del, rs3037354) minor/Δ allele was associated with several heritable (h2) stress traits: higher NPY secretion (h2 = 73 ± 4%) as well as greater BP response to environmental (cold) stress, and higher basal systemic vascular resistance. Association of ∇−880Δ and plasma NPY was replicated in an independent sample of 361 healthy young men, with consistent allelic effects; genetic variation at NPY also associated with plasma NPY in another independent series of 2,212 individuals derived from Australia twin pairs. Effects of allele −880Δ to increase NPY expression were directionally coordinate in vivo (on human traits) and in cells (transfected NPY promoter/luciferase reporter activity). Promoter −880Δ interrupts a novel glucocorticoid response element motif, an effect confirmed in chromaffin cells by site-directed mutagenesis on the transfected promoter, with differential glucocorticoid stimulation of the motif as well as alterations in electrophoretic mobility shifts. The same −880Δ allele also conferred risk for hypertension and accounted for approximately 4.5/approximately 2.1 mm Hg systolic BP/diastolic BP in a population sample from BP extremes.
Conclusions
We conclude that common genetic variation at the NPY locus, especially in proximal promoter ∇−880Δ, disrupts glucocorticoid signaling to influence NPY transcription and secretion, raising systemic vascular resistance and early heritable responses to environmental stress, eventuating in elevated resting BP in the population. The results point to new molecular strategies for probing autonomic control of the human circulation and ultimately susceptibility to and pathogenesis of cardiovascular and neuropsychiatric disease states.
doi:10.1016/j.jacc.2012.06.042
PMCID: PMC3687554  PMID: 23021333
genetics; glucocorticoid receptor; hypertension; neuropeptide Y
15.  Serum Iron Levels and the Risk of Parkinson Disease: A Mendelian Randomization Study 
PLoS Medicine  2013;10(6):e1001462.
In this study, Mendelian randomization was used to study genes known to modify iron levels, and the effect of iron on Parkinson's disease (PD) risk was estimated. Based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date, the findings suggest that increased iron levels in the blood are associated with a 3% reduction in the risk of Parkinson's disease for every 10 µg/dL increase in iron. The results of this analysis have potentially important implications for future research into the prevention of Parkinson's disease.
Please see later in the article for the Editors' Summary
Background
Although levels of iron are known to be increased in the brains of patients with Parkinson disease (PD), epidemiological evidence on a possible effect of iron blood levels on PD risk is inconclusive, with effects reported in opposite directions. Epidemiological studies suffer from problems of confounding and reverse causation, and mendelian randomization (MR) represents an alternative approach to provide unconfounded estimates of the effects of biomarkers on disease. We performed a MR study where genes known to modify iron levels were used as instruments to estimate the effect of iron on PD risk, based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date.
Methods and Findings
We used as instrumental variables three genetic variants influencing iron levels, HFE rs1800562, HFE rs1799945, and TMPRSS6 rs855791. Estimates of their effect on serum iron were based on a recent genome-wide meta-analysis of 21,567 individuals, while estimates of their effect on PD risk were obtained through meta-analysis of genome-wide and candidate gene studies with 20,809 PD cases and 88,892 controls. Separate MR estimates of the effect of iron on PD were obtained for each variant and pooled by meta-analysis. We investigated heterogeneity across the three estimates as an indication of possible pleiotropy and found no evidence of it. The combined MR estimate showed a statistically significant protective effect of iron, with a relative risk reduction for PD of 3% (95% CI 1%–6%; p = 0.001) per 10 µg/dl increase in serum iron.
Conclusions
Our study suggests that increased iron levels are causally associated with a decreased risk of developing PD. Further studies are needed to understand the pathophysiological mechanism of action of serum iron on PD risk before recommendations can be made.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Parkinson disease is a degenerative disorder of the central nervous system caused by the death of dopamine-generating cells in the substania nigra, a region of the midbrain. The earliest symptoms are usually movement-related and include tremor, slow movements, and difficulty walking, and later cognitive and behavioral problems may arise, with dementia commonly occurring in the advanced stages of the disease. Parkinson disease affects around ten million people world-wide and incidence increases with age, with men more affected than women. To date, the causes of Parkinson disease remain unknown although a combination of genetic and environmental factors is thought to play a role. Identifying possible modifiable risks is an important step in the possible prevention of Parkinson disease.
Why Was This Study Done?
Previous studies have shown a possible association between lower blood levels of iron in people with Parkinson disease compared with controls, although the quality of these studies makes this finding difficult to interpret. So in this study, the researchers used a mendelian randomization approach to investigate whether there was any evidence of an effect of blood iron levels on the risk of Parkinson disease and if so to further explore the direction and scale of any link. Mendelian randomization is a method of using measured variation in genes of known function to examine the causal effect of a modifiable exposure on disease in situations where it is inappropriate to perform a randomized controlled trial.
What Did the Researchers Do and Find?
The researchers estimated the effect of blood iron levels on the risk of Parkinson disease using three polymorphisms in two genes, HFE and TMPRSS6. For each polymorphism, they performed a meta-analysis combining the results of studies investigating the genetic effect on iron levels, which included almost 22,000 people from Europe and Australia, and a meta-analysis of studies investigating the genetic effect on the risk of Parkinson disease, which included a total of 20,809 people with Parkinson disease and 88,892 controls from Europe and North America. They then performed three separate mendelian randomization analyses to estimate the effect of iron on Parkinson disease for the three polymorphisms. By combining the three estimates, they obtained a statistically significant odds ratio of 0.97 for Parkinson disease per 10 µg/dl increase in iron, corresponding to a 3% reduction in the risk of Parkinson disease for every 10 µg/dl increase in blood iron. Since genotype influences on blood iron levels represent differences that generally persist throughout adult life, the combined mendelian randomization estimate reflects an effect of iron over the course of a lifetime.
What Do These Findings Mean?
These findings suggest that increased iron levels in the blood are associated with a 3% reduction in the risk of Parkinson disease for every 10 µg/dl increase in iron. This finding is important as it suggests that increased blood iron levels may have a protective effect against Parkinson disease, although the underlying mechanism remains unclear. Furthermore, although mendelian randomization is an increasingly used approach to address the issue of classical confounding, there may be remaining confounding factors specific of mendelian randomization that may influence the interpretation of this study. Nevertheless, the results of this analysis have potentially important implications for future research into the prevention of Parkinson disease. Further studies on the underlying mechanisms are needed before any specific treatment recommendations can be proposed.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001462.
The National Institutes of Neurological Disorder and Stroke, MedlinePlus, and NHS Choices have several pages with comprehensive information on Parkinson disease
Wikipedia gives an explanation of mendelian randomization (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001462
PMCID: PMC3672214  PMID: 23750121
16.  Genetic Variation Within a Metabolic Motif in the Chromogranin A Promoter: Pleiotropic Influence on Cardiometabolic Risk Traits in Twins 
BACKGROUND
The cardiometabolic syndrome comprised of multiple correlated traits, but its origin is incompletely understood. Chromogranin A (CHGA) is required for formation of the catecholamine secretory pathway in sympathochromaffin cells. In twin pair studies, we found that CHGA traits aggregated with body mass index (BMI), as well as its biochemical determinant leptin.
METHODS
Here we used the twin method to probe the role of heredity in generating such risk traits, and then investigated the role of risk-trait-associated CHGA promoter genetic variation in transfected chromaffin cells. Trait heritability (h2) and shared genetic determination among traits (pleiotropy, genetic covariance, ρG) were estimated by variance components in twin pairs.
RESULTS
CHGA, BMI, and leptin each displayed substantial h2, and the traits also aggregated with several features of the metabolic syndrome (e.g., insulin resistance, blood pressure (BP), hypertension, catecholamines, and C-reactive protein (CRP)). Twin studies demonstrated genetic covariance (pleiotropy, ρG) for CHGA, BMI, and leptin with other metabolic traits (insulin resistance, BP, and CRP). We therefore investigated the CHGA locus for mechanisms of codetermination with such metabolic traits. A common functional variant in the human CHGA promoter (G-462A, rs9658634, minor allele frequency ~21%) was associated with leptin and CRP secretion, as well as BMI, especially in women; marker-on-trait effects on BMI were replicated across twin populations on two continents. In CHGA promoter/luciferase reporter plasmids transfected into chromaffin cells, G-462A alleles differed markedly in reporter expression. The G-462A variant disrupted predicted transcriptional control by a PPARγ/RXRα motif and costimulation by PPARγ/RXRα and their cognate ligands, differentially activated the two alleles. During chromatin immunoprecipitation, endogenous PPARγ bound the motif.
CONCLUSIONS
Multiple features of the metabolic syndrome are thus under joint (pleiotropic) genetic determination, with CHGA as one such contributory locus: a common polymorphism in the promoter (G-462A) of CHGA predicts such heritable metabolic traits as BMI and leptin. CHGA promoter variant G-462A was not only associated with such metabolic traits but also disrupted a PPARγ/RXRα motif and responded differentially to characteristic trans-activators of that motif. The results suggest novel links between the catecholaminergic system and risk for the metabolic syndrome as well as systemic hypertension.
doi:10.1038/ajh.2011.163
PMCID: PMC3664223  PMID: 21918574
adrenal; blood pressure; BMI; C-reactive protein; catecholamine; chromaffin; chromogranin; hypertension; leptin; metabolic syndrome; twin study
17.  Seventy-five genetic loci influencing the human red blood cell 
van der Harst, Pim | Zhang, Weihua | Leach, Irene Mateo | Rendon, Augusto | Verweij, Niek | Sehmi, Joban | Paul, Dirk S. | Elling, Ulrich | Allayee, Hooman | Li, Xinzhong | Radhakrishnan, Aparna | Tan, Sian-Tsung | Voss, Katrin | Weichenberger, Christian X. | Albers, Cornelis A. | Al-Hussani, Abtehale | Asselbergs, Folkert W. | Ciullo, Marina | Danjou, Fabrice | Dina, Christian | Esko, Tõnu | Evans, David M. | Franke, Lude | Gögele, Martin | Hartiala, Jaana | Hersch, Micha | Holm, Hilma | Hottenga, Jouke-Jan | Kanoni, Stavroula | Kleber, Marcus E. | Lagou, Vasiliki | Langenberg, Claudia | Lopez, Lorna M. | Lyytikäinen, Leo-Pekka | Melander, Olle | Murgia, Federico | Nolte, Ilja M. | O’Reilly, Paul F. | Padmanabhan, Sandosh | Parsa, Afshin | Pirastu, Nicola | Porcu, Eleonora | Portas, Laura | Prokopenko, Inga | Ried, Janina S. | Shin, So-Youn | Tang, Clara S. | Teumer, Alexander | Traglia, Michela | Ulivi, Sheila | Westra, Harm-Jan | Yang, Jian | Zhao, Jing Hua | Anni, Franco | Abdellaoui, Abdel | Attwood, Antony | Balkau, Beverley | Bandinelli, Stefania | Bastardot, François | Benyamin, Beben | Boehm, Bernhard O. | Cookson, William O. | Das, Debashish | de Bakker, Paul I. W. | de Boer, Rudolf A. | de Geus, Eco J. C. | de Moor, Marleen H. | Dimitriou, Maria | Domingues, Francisco S. | Döring, Angela | Engström, Gunnar | Eyjolfsson, Gudmundur Ingi | Ferrucci, Luigi | Fischer, Krista | Galanello, Renzo | Garner, Stephen F. | Genser, Bernd | Gibson, Quince D. | Girotto, Giorgia | Gudbjartsson, Daniel Fannar | Harris, Sarah E. | Hartikainen, Anna-Liisa | Hastie, Claire E. | Hedblad, Bo | Illig, Thomas | Jolley, Jennifer | Kähönen, Mika | Kema, Ido P. | Kemp, John P. | Liang, Liming | Lloyd-Jones, Heather | Loos, Ruth J. F. | Meacham, Stuart | Medland, Sarah E. | Meisinger, Christa | Memari, Yasin | Mihailov, Evelin | Miller, Kathy | Moffatt, Miriam F. | Nauck, Matthias | Novatchkova, Maria | Nutile, Teresa | Olafsson, Isleifur | Onundarson, Pall T. | Parracciani, Debora | Penninx, Brenda W. | Perseu, Lucia | Piga, Antonio | Pistis, Giorgio | Pouta, Anneli | Puc, Ursula | Raitakari, Olli | Ring, Susan M. | Robino, Antonietta | Ruggiero, Daniela | Ruokonen, Aimo | Saint-Pierre, Aude | Sala, Cinzia | Salumets, Andres | Sambrook, Jennifer | Schepers, Hein | Schmidt, Carsten Oliver | Silljé, Herman H. W. | Sladek, Rob | Smit, Johannes H. | Starr, John M. | Stephens, Jonathan | Sulem, Patrick | Tanaka, Toshiko | Thorsteinsdottir, Unnur | Tragante, Vinicius | van Gilst, Wiek H. | van Pelt, L. Joost | van Veldhuisen, Dirk J. | Völker, Uwe | Whitfield, John B. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Wirnsberger, Gerald | Algra, Ale | Cucca, Francesco | d’Adamo, Adamo Pio | Danesh, John | Deary, Ian J. | Dominiczak, Anna F. | Elliott, Paul | Fortina, Paolo | Froguel, Philippe | Gasparini, Paolo | Greinacher, Andreas | Hazen, Stanley L. | Jarvelin, Marjo-Riitta | Khaw, Kay Tee | Lehtimäki, Terho | Maerz, Winfried | Martin, Nicholas G. | Metspalu, Andres | Mitchell, Braxton D. | Montgomery, Grant W. | Moore, Carmel | Navis, Gerjan | Pirastu, Mario | Pramstaller, Peter P. | Ramirez-Solis, Ramiro | Schadt, Eric | Scott, James | Shuldiner, Alan R. | Smith, George Davey | Smith, J. Gustav | Snieder, Harold | Sorice, Rossella | Spector, Tim D. | Stefansson, Kari | Stumvoll, Michael | Wilson Tang, W. H. | Toniolo, Daniela | Tönjes, Anke | Visscher, Peter M. | Vollenweider, Peter | Wareham, Nicholas J. | Wolffenbuttel, Bruce H. R. | Boomsma, Dorret I. | Beckmann, Jacques S. | Dedoussis, George V. | Deloukas, Panos | Ferreira, Manuel A. | Sanna, Serena | Uda, Manuela | Hicks, Andrew A. | Penninger, Josef Martin | Gieger, Christian | Kooner, Jaspal S. | Ouwehand, Willem H. | Soranzo, Nicole | Chambers, John C
Nature  2012;492(7429):369-375.
Anaemia is a chief determinant of globalill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P <10−8, which together explain 4–9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.
doi:10.1038/nature11677
PMCID: PMC3623669  PMID: 23222517
18.  Loci affecting gamma-glutamyl transferase in adults and adolescents show age × SNP interaction and cardiometabolic disease associations 
Human Molecular Genetics  2011;21(2):446-455.
Serum gamma-glutamyl transferase (GGT) activity is a marker of liver disease which is also prospectively associated with the risk of all-cause mortality, cardiovascular disease, type 2 diabetes and cancers. We have discovered novel loci affecting GGT in a genome-wide association study (rs1497406 in an intergenic region of chromosome 1, P = 3.9 × 10−8; rs944002 in C14orf73 on chromosome 14, P = 4.7 × 10−13; rs340005 in RORA on chromosome 15, P = 2.4 × 10−8), and a highly significant heterogeneity between adult and adolescent results at the GGT1 locus on chromosome 22 (maximum PHET = 5.6 × 10−12 at rs6519520). Pathway analysis of significant and suggestive single-nucleotide polymorphism associations showed significant overlap between genes affecting GGT and those affecting common metabolic and inflammatory diseases, and identified the hepatic nuclear factor (HNF) family as controllers of a network of genes affecting GGT. Our results reinforce the disease associations of GGT and demonstrate that control by the GGT1 locus varies with age.
doi:10.1093/hmg/ddr478
PMCID: PMC3276286  PMID: 22010049
19.  GWAS of butyrylcholinesterase activity identifies four novel loci, independent effects within BCHE and secondary associations with metabolic risk factors 
Human Molecular Genetics  2011;20(22):4504-4514.
Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from ∼2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 × 10−262, 7.8 × 10−47, 2.9 × 10−12) and at four other loci: RNPEP (P = 9.4 × 10−16), RAPH1-ABI2 (P = 4.1 × 10−18), UGT1A1 (P = 4.0 × 10−8) and an intergenic region on chromosome 8 (P = 1.4 × 10−8). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.
doi:10.1093/hmg/ddr375
PMCID: PMC3196893  PMID: 21862451
20.  Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma 
Chambers, John C | Zhang, Weihua | Sehmi, Joban | Li, Xinzhong | Wass, Mark N | Van der Harst, Pim | Holm, Hilma | Sanna, Serena | Kavousi, Maryam | Baumeister, Sebastian E | Coin, Lachlan J | Deng, Guohong | Gieger, Christian | Heard-Costa, Nancy L | Hottenga, Jouke-Jan | Kühnel, Brigitte | Kumar, Vinod | Lagou, Vasiliki | Liang, Liming | Luan, Jian’an | Vidal, Pedro Marques | Leach, Irene Mateo | O’Reilly, Paul F | Peden, John F | Rahmioglu, Nilufer | Soininen, Pasi | Speliotes, Elizabeth K | Yuan, Xin | Thorleifsson, Gudmar | Alizadeh, Behrooz Z | Atwood, Larry D | Borecki, Ingrid B | Brown, Morris J | Charoen, Pimphen | Cucca, Francesco | Das, Debashish | de Geus, Eco J C | Dixon, Anna L | Döring, Angela | Ehret, Georg | Eyjolfsson, Gudmundur I | Farrall, Martin | Forouhi, Nita G | Friedrich, Nele | Goessling, Wolfram | Gudbjartsson, Daniel F | Harris, Tamara B | Hartikainen, Anna-Liisa | Heath, Simon | Hirschfield, Gideon M | Hofman, Albert | Homuth, Georg | Hyppönen, Elina | Janssen, Harry L A | Johnson, Toby | Kangas, Antti J | Kema, Ido P | Kühn, Jens P | Lai, Sandra | Lathrop, Mark | Lerch, Markus M | Li, Yun | Liang, T Jake | Lin, Jing-Ping | Loos, Ruth J F | Martin, Nicholas G | Moffatt, Miriam F | Montgomery, Grant W | Munroe, Patricia B | Musunuru, Kiran | Nakamura, Yusuke | O’Donnell, Christopher J | Olafsson, Isleifur | Penninx, Brenda W | Pouta, Anneli | Prins, Bram P | Prokopenko, Inga | Puls, Ralf | Ruokonen, Aimo | Savolainen, Markku J | Schlessinger, David | Schouten, Jeoffrey N L | Seedorf, Udo | Sen-Chowdhry, Srijita | Siminovitch, Katherine A | Smit, Johannes H | Spector, Timothy D | Tan, Wenting | Teslovich, Tanya M | Tukiainen, Taru | Uitterlinden, Andre G | Van der Klauw, Melanie M | Vasan, Ramachandran S | Wallace, Chris | Wallaschofski, Henri | Wichmann, H-Erich | Willemsen, Gonneke | Würtz, Peter | Xu, Chun | Yerges-Armstrong, Laura M | Abecasis, Goncalo R | Ahmadi, Kourosh R | Boomsma, Dorret I | Caulfield, Mark | Cookson, William O | van Duijn, Cornelia M | Froguel, Philippe | Matsuda, Koichi | McCarthy, Mark I | Meisinger, Christa | Mooser, Vincent | Pietiläinen, Kirsi H | Schumann, Gunter | Snieder, Harold | Sternberg, Michael J E | Stolk, Ronald P | Thomas, Howard C | Thorsteinsdottir, Unnur | Uda, Manuela | Waeber, Gérard | Wareham, Nicholas J | Waterworth, Dawn M | Watkins, Hugh | Whitfield, John B | Witteman, Jacqueline C M | Wolffenbuttel, Bruce H R | Fox, Caroline S | Ala-Korpela, Mika | Stefansson, Kari | Vollenweider, Peter | Völzke, Henry | Schadt, Eric E | Scott, James | Järvelin, Marjo-Riitta | Elliott, Paul | Kooner, Jaspal S
Nature genetics  2011;43(11):1131-1138.
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10−8 to P = 10−190). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.
doi:10.1038/ng.970
PMCID: PMC3482372  PMID: 22001757
21.  Genome-wide association study identifies two loci strongly affecting transferrin glycosylation 
Human Molecular Genetics  2011;20(18):3710-3717.
Polysaccharide sidechains attached to proteins play important roles in cell–cell and receptor–ligand interactions. Variation in the carbohydrate component has been extensively studied for the iron transport protein transferrin, because serum levels of the transferrin isoforms asialotransferrin + disialotransferrin (carbohydrate-deficient transferrin, CDT) are used as biomarkers of excessive alcohol intake. We conducted a genome-wide association study to assess whether genetic factors affect CDT concentration in serum. CDT was measured in three population-based studies: one in Switzerland (CoLaus study, n = 5181) and two in Australia (n = 1509, n = 775). The first cohort was used as the discovery panel and the latter ones served as replication. Genome-wide single-nucleotide polymorphism (SNP) typing data were used to identify loci with significant associations with CDT as a percentage of total transferrin (CDT%). The top three SNPs in the discovery panel (rs2749097 near PGM1 on chromosome 1, and missense polymorphisms rs1049296, rs1799899 in TF on chromosome 3) were successfully replicated , yielding genome-wide significant combined association with CDT% (P = 1.9 × 10−9, 4 × 10−39, 5.5 × 10−43, respectively) and explain 5.8% of the variation in CDT%. These allelic effects are postulated to be caused by variation in availability of glucose-1-phosphate as a precursor of the glycan (PGM1), and variation in transferrin (TF) structure.
doi:10.1093/hmg/ddr272
PMCID: PMC3159549  PMID: 21665994
22.  A quantitative-trait genome-wide association study of alcoholism risk in the community: findings and implications 
Biological psychiatry  2011;70(6):513-518.
Background
Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50–60% heritability), with high correlation of genetic influences, we have conducted a quantitative trait genomewide association study for phenotypes related to alcohol use and dependence.
Methods
Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genomewide SNP genotyping was performed with 8754 individuals [2062 alcohol dependent cases] selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genomewide SNP data.
Results
No findings reached genomewide significance (p=8.4×10−8 for this study), with lowest p-value for primary phenotypes of 1.2×10−7. Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene (TMEM108) and for ANKS1A. The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk.
Conclusions
We conclude that (i) meta-analyses of consumption data may contribute usefully to gene-discovery; (ii) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging; (iii) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g. prospective high-risk or resilience studies).
doi:10.1016/j.biopsych.2011.02.028
PMCID: PMC3210694  PMID: 21529783
Alcoholism; genome-wide association; quantitative-trait; non-replication
23.  Genetic architecture of circulating lipid levels 
Serum concentrations of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TGs) and total cholesterol (TC) are important heritable risk factors for cardiovascular disease. Although genome-wide association studies (GWASs) of circulating lipid levels have identified numerous loci, a substantial portion of the heritability of these traits remains unexplained. Evidence of unexplained genetic variance can be detected by combining multiple independent markers into additive genetic risk scores. Such polygenic scores, constructed using results from the ENGAGE Consortium GWAS on serum lipids, were applied to predict lipid levels in an independent population-based study, the Rotterdam Study-II (RS-II). We additionally tested for evidence of a shared genetic basis for different lipid phenotypes. Finally, the polygenic score approach was used to identify an alternative genome-wide significance threshold before pathway analysis and those results were compared with those based on the classical genome-wide significance threshold. Our study provides evidence suggesting that many loci influencing circulating lipid levels remain undiscovered. Cross-prediction models suggested a small overlap between the polygenic backgrounds involved in determining LDL-C, HDL-C and TG levels. Pathway analysis utilizing the best polygenic score for TC uncovered extra information compared with using only genome-wide significant loci. These results suggest that the genetic architecture of circulating lipids involves a number of undiscovered variants with very small effects, and that increasing GWAS sample sizes will enable the identification of novel variants that regulate lipid levels.
doi:10.1038/ejhg.2011.21
PMCID: PMC3137496  PMID: 21448234
serum lipids; polygenic; genome-wide association; polygenic score; pathway analysis
24.  Heritability and Genome-Wide Linkage in US and Australian Twins Identify Novel Genomic Regions Controlling Chromogranin A 
Circulation  2008;118(3):247-257.
Background
Chromogranin A (CHGA) triggers catecholamine secretory granule biogenesis, and its catestatin fragment inhibits catecholamine release. We approached catestatin heritability using twin pairs, coupled with genome-wide linkage, in a series of twin and sibling pairs from 2 continents.
Methods and Results
Hypertensive patients had elevated CHGA coupled with reduction in catestatin, suggesting diminished conversion of precursor to catestatin. Heritability for catestatin in twins was 44% to 60%. Six hundred fifteen nuclear families yielded 870 sib pairs for linkage, with significant logarithm of odds peaks on chromosomes 4p, 4q, and 17q. Because acidification of catecholamine secretory vesicles determines CHGA trafficking and processing to catestatin, we genotyped at positional candidate ATP6N1, bracketed by peak linkage markers on chromosome 17q, encoding a subunit of vesicular H+-translocating ATPase. The minor allele diminished CHGA secretion and processing to catestatin. The ATP6N1 variant also influenced blood pressure in 1178 individuals with the most extreme blood pressure values in the population. In chromaffin cells, inhibition of H+-ATPase diverted CHGA from regulated to constitutive secretory pathways.
Conclusions
We established heritability of catestatin in twins from 2 continents. Linkage identified 3 regions contributing to catestatin, likely novel determinants of sympathochromaffin exocytosis. At 1 such positional candidate (ATP6N1), variation influenced CHGA secretion and processing to catestatin, confirming the mechanism of a novel trans-QTL for sympathochromaffin activity and blood pressure.
doi:10.1161/CIRCULATIONAHA.107.709105
PMCID: PMC2654229  PMID: 18591442
catecholamines; genes; genetics; hypertension; nervous system, autonomic
25.  The Brisbane Systems Genetics Study: Genetical Genomics Meets Complex Trait Genetics 
PLoS ONE  2012;7(4):e35430.
There is growing evidence that genetic risk factors for common disease are caused by hereditary changes of gene regulation acting in complex pathways. Clearly understanding the molecular genetic relationships between genetic control of gene expression and its effect on complex diseases is essential. Here we describe the Brisbane Systems Genetics Study (BSGS), a family-based study that will be used to elucidate the genetic factors affecting gene expression and the role of gene regulation in mediating endophenotypes and complex diseases.
BSGS comprises of a total of 962 individuals from 314 families, for which we have high-density genotype, gene expression and phenotypic data. Families consist of combinations of both monozygotic and dizygotic twin pairs, their siblings, and, for 72 families, both parents. A significant advantage of the inclusion of parents is improved power to disentangle environmental, additive genetic and non-additive genetic effects of gene expression and measured phenotypes. Furthermore, it allows for the estimation of parent-of-origin effects, something that has not previously been systematically investigated in human genetical genomics studies. Measured phenotypes available within the BSGS include blood phenotypes and biochemical traits measured from components of the tissue sample in which transcription levels are determined, providing an ideal test case for systems genetics approaches.
We report results from an expression quantitative trait loci (eQTL) analysis using 862 individuals from BSGS to test for associations between expression levels of 17,926 probes and 528,509 SNP genotypes. At a study wide significance level approximately 15,000 associations were observed between expression levels and SNP genotypes. These associations corresponded to a total of 2,081 expression quantitative trait loci (eQTL) involving 1,503 probes. The majority of identified eQTL (87%) were located within cis-regions.
doi:10.1371/journal.pone.0035430
PMCID: PMC3338511  PMID: 22563384

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