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1.  Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels 
van Leeuwen, Elisabeth M. | Karssen, Lennart C. | Deelen, Joris | Isaacs, Aaron | Medina-Gomez, Carolina | Mbarek, Hamdi | Kanterakis, Alexandros | Trompet, Stella | Postmus, Iris | Verweij, Niek | van Enckevort, David J. | Huffman, Jennifer E. | White, Charles C. | Feitosa, Mary F. | Bartz, Traci M. | Manichaikul, Ani | Joshi, Peter K. | Peloso, Gina M. | Deelen, Patrick | van Dijk, Freerk | Willemsen, Gonneke | de Geus, Eco J. | Milaneschi, Yuri | Penninx, Brenda W.J.H. | Francioli, Laurent C. | Menelaou, Androniki | Pulit, Sara L. | Rivadeneira, Fernando | Hofman, Albert | Oostra, Ben A. | Franco, Oscar H. | Leach, Irene Mateo | Beekman, Marian | de Craen, Anton J.M. | Uh, Hae-Won | Trochet, Holly | Hocking, Lynne J. | Porteous, David J. | Sattar, Naveed | Packard, Chris J. | Buckley, Brendan M. | Brody, Jennifer A. | Bis, Joshua C. | Rotter, Jerome I. | Mychaleckyj, Josyf C. | Campbell, Harry | Duan, Qing | Lange, Leslie A. | Wilson, James F. | Hayward, Caroline | Polasek, Ozren | Vitart, Veronique | Rudan, Igor | Wright, Alan F. | Rich, Stephen S. | Psaty, Bruce M. | Borecki, Ingrid B. | Kearney, Patricia M. | Stott, David J. | Adrienne Cupples, L. | Jukema, J. Wouter | van der Harst, Pim | Sijbrands, Eric J. | Hottenga, Jouke-Jan | Uitterlinden, Andre G. | Swertz, Morris A. | van Ommen, Gert-Jan B. | de Bakker, Paul I.W. | Eline Slagboom, P. | Boomsma, Dorret I. | Wijmenga, Cisca | van Duijn, Cornelia M.
Nature Communications  2015;6:6065.
Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10−4), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.
Frequencies of rare variants fluctuate over populations, hampering gene discovery. Here the authors use a population-specific reference panel, the Genome of the Netherlands, to discover four novel loci involved in lipid metabolism, including an exonic variant in ABCA6.
doi:10.1038/ncomms7065
PMCID: PMC4366498  PMID: 25751400
2.  Association between cognition and gene polymorphisms involved in thrombosis and haemostasis 
Age  2015;37(4):80.
An association between blood markers of thrombosis and haemostasis and cognitive decline has been described. These results may be confounded by lifestyle and environmental factors. We used a Mendelian randomisation approach to describe the association between thrombosis/haemostasis genotypes and cognition. We studied the genetic variants (single nucleotide polymorphisms) of circulating markers of thrombosis and haemostasis. Our chosen blood factors and associated polymorphisms were D-dimer [rs12029080], fibrinogen [rs1800789], plasminogen activator inhibitor [rs2227631], and von Willebrand factor [rs1063857]. We described association with multidomain cognitive test scores using data from the Scottish Family Health Study. Cognitive data were analysed for individual tests and combined to give a general cognitive factor. In 20,288 subjects, we found no evidence of association between cognitive function (individual tests and combined scores) and any of the above-mentioned single nucleotide polymorphisms. Lower scores on cognitive measures were associated with increasing age, socioeconomic deprivation, blood pressure, waist-hip ratio, smoking, and vascular comorbidity (all p < 0.001). In a post hoc sensitivity analysis restricted to those aged over 50 years, there was still no signal of association. Our data add to our understanding of determinants of cognition but are not definitive; the variation in blood levels explained by SNPs was modest and our sample size may have been insufficient to detect a modest association.
Electronic supplementary material
The online version of this article (doi:10.1007/s11357-015-9820-y) contains supplementary material, which is available to authorized users.
doi:10.1007/s11357-015-9820-y
PMCID: PMC5005822  PMID: 26228839
Cognition disorders; Dementia; Haemostasis; Genomics; Mendelian randomization analysis
3.  Genome-wide association analysis identifies six new loci associated with forced vital capacity 
Loth, Daan W. | Artigas, María Soler | Gharib, Sina A. | Wain, Louise V. | Franceschini, Nora | Koch, Beate | Pottinger, Tess | Smith, Albert Vernon | Duan, Qing | Oldmeadow, Chris | Lee, Mi Kyeong | Strachan, David P. | James, Alan L. | Huffman, Jennifer E. | Vitart, Veronique | Ramasamy, Adaikalavan | Wareham, Nicholas J. | Kaprio, Jaakko | Wang, Xin-Qun | Trochet, Holly | Kähönen, Mika | Flexeder, Claudia | Albrecht, Eva | Lopez, Lorna M. | de Jong, Kim | Thyagarajan, Bharat | Alves, Alexessander Couto | Enroth, Stefan | Omenaas, Ernst | Joshi, Peter K. | Fall, Tove | Viňuela, Ana | Launer, Lenore J. | Loehr, Laura R. | Fornage, Myriam | Li, Guo | Wilk, Jemma B. | Tang, Wenbo | Manichaikul, Ani | Lahousse, Lies | Harris, Tamara B. | North, Kari E. | Rudnicka, Alicja R. | Hui, Jennie | Gu, Xiangjun | Lumley, Thomas | Wright, Alan F. | Hastie, Nicholas D. | Campbell, Susan | Kumar, Rajesh | Pin, Isabelle | Scott, Robert A. | Pietiläinen, Kirsi H. | Surakka, Ida | Liu, Yongmei | Holliday, Elizabeth G. | Schulz, Holger | Heinrich, Joachim | Davies, Gail | Vonk, Judith M. | Wojczynski, Mary | Pouta, Anneli | Johansson, Åsa | Wild, Sarah H. | Ingelsson, Erik | Rivadeneira, Fernando | Völzke, Henry | Hysi, Pirro G. | Eiriksdottir, Gudny | Morrison, Alanna C. | Rotter, Jerome I. | Gao, Wei | Postma, Dirkje S. | White, Wendy B. | Rich, Stephen S. | Hofman, Albert | Aspelund, Thor | Couper, David | Smith, Lewis J. | Psaty, Bruce M. | Lohman, Kurt | Burchard, Esteban G. | Uitterlinden, André G. | Garcia, Melissa | Joubert, Bonnie R. | McArdle, Wendy L. | Musk, A. Bill | Hansel, Nadia | Heckbert, Susan R. | Zgaga, Lina | van Meurs, Joyce B.J. | Navarro, Pau | Rudan, Igor | Oh, Yeon-Mok | Redline, Susan | Jarvis, Deborah | Zhao, Jing Hua | Rantanen, Taina | O’Connor, George T. | Ripatti, Samuli | Scott, Rodney J. | Karrasch, Stefan | Grallert, Harald | Gaddis, Nathan C. | Starr, John M. | Wijmenga, Cisca | Minster, Ryan L. | Lederer, David J. | Pekkanen, Juha | Gyllensten, Ulf | Campbell, Harry | Morris, Andrew P. | Gläser, Sven | Hammond, Christopher J. | Burkart, Kristin M. | Beilby, John | Kritchevsky, Stephen B. | Gudnason, Vilmundur | Hancock, Dana B. | Williams, O. Dale | Polasek, Ozren | Zemunik, Tatijana | Kolcic, Ivana | Petrini, Marcy F. | Wjst, Matthias | Kim, Woo Jin | Porteous, David J. | Scotland, Generation | Smith, Blair H. | Viljanen, Anne | Heliövaara, Markku | Attia, John R. | Sayers, Ian | Hampel, Regina | Gieger, Christian | Deary, Ian J. | Boezen, H. Marike | Newman, Anne | Jarvelin, Marjo-Riitta | Wilson, James F. | Lind, Lars | Stricker, Bruno H. | Teumer, Alexander | Spector, Timothy D. | Melén, Erik | Peters, Marjolein J. | Lange, Leslie A. | Barr, R. Graham | Bracke, Ken R. | Verhamme, Fien M. | Sung, Joohon | Hiemstra, Pieter S. | Cassano, Patricia A. | Sood, Akshay | Hayward, Caroline | Dupuis, Josée | Hall, Ian P. | Brusselle, Guy G. | Tobin, Martin D. | London, Stephanie J.
Nature genetics  2014;46(7):669-677.
Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P < 5 × 10−8) with FVC in or near EFEMP1, BMP6, MIR-129-2/HSD17B12, PRDM11, WWOX, and KCNJ2. Two (GSTCD and PTCH1) loci previously associated with spirometric measures were related to FVC. Newly implicated regions were followed-up in samples of African American, Korean, Chinese, and Hispanic individuals. We detected transcripts for all six newly implicated genes in human lung tissue. The new loci may inform mechanisms involved in lung development and pathogenesis of restrictive lung disease.
doi:10.1038/ng.3011
PMCID: PMC4140093  PMID: 24929828
4.  Genome-wide association and large scale follow-up identifies 16 new loci influencing lung function 
Artigas, María Soler | Loth, Daan W | Wain, Louise V | Gharib, Sina A | Obeidat, Ma’en | Tang, Wenbo | Zhai, Guangju | Zhao, Jing Hua | Smith, Albert Vernon | Huffman, Jennifer E | Albrecht, Eva | Jackson, Catherine M | Evans, David M | Cadby, Gemma | Fornage, Myriam | Manichaikul, Ani | Lopez, Lorna M | Johnson, Toby | Aldrich, Melinda C | Aspelund, Thor | Barroso, Inês | Campbell, Harry | Cassano, Patricia A | Couper, David J | Eiriksdottir, Gudny | Franceschini, Nora | Garcia, Melissa | Gieger, Christian | Gislason, Gauti Kjartan | Grkovic, Ivica | Hammond, Christopher J | Hancock, Dana B | Harris, Tamara B | Ramasamy, Adaikalavan | Heckbert, Susan R | Heliövaara, Markku | Homuth, Georg | Hysi, Pirro G | James, Alan L | Jankovic, Stipan | Joubert, Bonnie R | Karrasch, Stefan | Klopp, Norman | Koch, Beate | Kritchevsky, Stephen B | Launer, Lenore J | Liu, Yongmei | Loehr, Laura R | Lohman, Kurt | Loos, Ruth JF | Lumley, Thomas | Al Balushi, Khalid A | Ang, Wei Q | Barr, R Graham | Beilby, John | Blakey, John D | Boban, Mladen | Boraska, Vesna | Brisman, Jonas | Britton, John R | Brusselle, Guy G | Cooper, Cyrus | Curjuric, Ivan | Dahgam, Santosh | Deary, Ian J | Ebrahim, Shah | Eijgelsheim, Mark | Francks, Clyde | Gaysina, Darya | Granell, Raquel | Gu, Xiangjun | Hankinson, John L | Hardy, Rebecca | Harris, Sarah E | Henderson, John | Henry, Amanda | Hingorani, Aroon D | Hofman, Albert | Holt, Patrick G | Hui, Jennie | Hunter, Michael L | Imboden, Medea | Jameson, Karen A | Kerr, Shona M | Kolcic, Ivana | Kronenberg, Florian | Liu, Jason Z | Marchini, Jonathan | McKeever, Tricia | Morris, Andrew D | Olin, Anna-Carin | Porteous, David J | Postma, Dirkje S | Rich, Stephen S | Ring, Susan M | Rivadeneira, Fernando | Rochat, Thierry | Sayer, Avan Aihie | Sayers, Ian | Sly, Peter D | Smith, George Davey | Sood, Akshay | Starr, John M | Uitterlinden, André G | Vonk, Judith M | Wannamethee, S Goya | Whincup, Peter H | Wijmenga, Cisca | Williams, O Dale | Wong, Andrew | Mangino, Massimo | Marciante, Kristin D | McArdle, Wendy L | Meibohm, Bernd | Morrison, Alanna C | North, Kari E | Omenaas, Ernst | Palmer, Lyle J | Pietiläinen, Kirsi H | Pin, Isabelle | Polašek, Ozren | Pouta, Anneli | Psaty, Bruce M | Hartikainen, Anna-Liisa | Rantanen, Taina | Ripatti, Samuli | Rotter, Jerome I | Rudan, Igor | Rudnicka, Alicja R | Schulz, Holger | Shin, So-Youn | Spector, Tim D | Surakka, Ida | Vitart, Veronique | Völzke, Henry | Wareham, Nicholas J | Warrington, Nicole M | Wichmann, H-Erich | Wild, Sarah H | Wilk, Jemma B | Wjst, Matthias | Wright, Alan F | Zgaga, Lina | Zemunik, Tatijana | Pennell, Craig E | Nyberg, Fredrik | Kuh, Diana | Holloway, John W | Boezen, H Marike | Lawlor, Debbie A | Morris, Richard W | Probst-Hensch, Nicole | Kaprio, Jaakko | Wilson, James F | Hayward, Caroline | Kähönen, Mika | Heinrich, Joachim | Musk, Arthur W | Jarvis, Deborah L | Gläser, Sven | Järvelin, Marjo-Riitta | Stricker, Bruno H Ch | Elliott, Paul | O’Connor, George T | Strachan, David P | London, Stephanie J | Hall, Ian P | Gudnason, Vilmundur | Tobin, Martin D
Nature genetics  2011;43(11):1082-1090.
Pulmonary function measures reflect respiratory health and predict mortality, and are used in the diagnosis of chronic obstructive pulmonary disease (COPD). We tested genome-wide association with the forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) in 48,201 individuals of European ancestry, with follow-up of top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P<5×10−8) with pulmonary function, in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1, and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.
doi:10.1038/ng.941
PMCID: PMC3267376  PMID: 21946350
5.  Genetic predictors of fibrin D-dimer levels in healthy adults 
Circulation  2011;123(17):1864-1872.
Background
Fibrin fragment D-dimer is one of several peptides produced when cross-linked fibrin is degraded by plasmin, and is the most widely-used clinical marker of activated blood coagulation. To identity genetic loci influencing D-dimer levels, we performed the first large-scale, genome-wide association search.
Methods and Results
A genome-wide investigation of the genomic correlates of plasma D-dimer levels was conducted among 21,052 European-ancestry adults. Plasma levels of D-dimer were measured independently in each of 13 cohorts. Each study analyzed the association between ~2.6 million genotyped and imputed variants across the 22 autosomal chromosomes and natural-log transformed D-dimer levels using linear regression in additive genetic models adjusted for age and sex. Among all variants, 74 exceeded the genome-wide significance threshold and marked 3 regions. At 1p22, rs12029080 (p-value 6.4×10−52) was 46.0 kb upstream from F3, coagulation factor III (tissue factor). At 1q24, rs6687813 (p-value 2.4×10−14) was 79.7 kb downstream of F5, coagulation factor V. At 4q32, rs13109457 (p-value 2.9×10−18) was located between 2 fibrinogen genes: 10.4 kb downstream from FGG and 3.0 kb upstream from FGA. Variants were associated with a 0.099, 0.096, and 0.061 unit difference, respectively, in natural-log transformed D-dimer and together accounted for 1.8% of the total variance. When adjusted for non-synonymous substitutions in F5 and FGA loci known to be associated with D-dimer levels, there was no evidence of an additional association at either locus.
Conclusions
Three genes were associated with fibrin D-dimer levels, of which the F3 association was the strongest and has not been previously reported.
doi:10.1161/CIRCULATIONAHA.110.009480
PMCID: PMC3095913  PMID: 21502573
genome-wide variation; D-dimer; epidemiology; meta-analysis; thrombosis; hemostasis
6.  Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis 
PLoS Medicine  2016;13(8):e1002090.
Background
Chronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD) is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the United Kingdom Biobank study.
Methods and Findings
Using family-based mixed-model analyses, we examined the contribution of genetics and shared family environment to chronic pain by spouse, sibling, and household relationships. These analyses were conducted in GS:SFHS (n = 23,960), a family- and population-based study of individuals recruited from the Scottish population through their general practitioners. We then examined and partitioned the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment in GS:SFHS. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. These analyses were conducted in GS:SFHS and repeated in UK Biobank, a study of 500,000 from the UK population, of whom 112,151 had genotyping and phenotypic data. Chronic pain is a moderately heritable trait (heritability = 38.4%, 95% CI 33.6% to 43.9%) that is significantly concordant in spouses (variance explained 18.7%, 95% CI 9.5% to 25.1%). Chronic pain is positively correlated with depression (ρ = 0.13, 95% CI 0.11 to 0.15, p = 2.72x10-68) and shows a tendency to cluster within families for genetic reasons (genetic correlation = 0.51, 95%CI 0.40 to 0.62, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, were associated with chronic pain in both GS:SFHS (maximum β = 6.18x10-2, 95% CI 2.84 x10-2 to 9.35 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 5.68 x 10−2, 95% CI 4.70x10-2 to 6.65x10-2, p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum β = 6.62x10-2, 95% CI 2.82 x10-2 to 9.76 x10-2, p = 4.3x10-4) and UK Biobank (maximum β = 2.56x10-2, 95% CI 1.62x10-2 to 3.63x10-2, p < 3x10-4). Limitations of the current study include the possibility that spouse effects may be due to assortative mating and the relatively small polygenic risk score effect sizes.
Conclusions
Genetic factors, as well as chronic pain in a partner or spouse, contribute substantially to the risk of chronic pain for an individual. Chronic pain is genetically correlated with MDD, has a polygenic architecture, and is associated with polygenic risk of MDD.
Andrew M. McIntosh and colleagues investigate the genetic and environmental factors associated with chronic pain and and major depressive disorder.
Author Summary
Why Was This Study Done?
Genetic factors and the environment you share with your nuclear family, siblings, or spouse may determine your risk of chronic pain.
Depression is also associated with chronic pain, but whether this relationship is explained by shared genetic factors, environment, or both is not known.
We sought to investigate these issues using genetic data and family environmental information from Generation Scotland: Scottish Family Health Study and UK Biobank.
What Did the Researchers Do and Find?
Using data from the family-based Generation Scotland study, we found that genetic factors and the environment you share with your partner/spouse are important risk factors for the development of chronic pain.
Shared genetic and environmental factors also partly explained the association between chronic pain and depression.
Finally, we found evidence showing that the genetic contribution to chronic pain arises through the combined effect of many different genetic risk factors and that the cumulative effects of genetic risk factors for depression increased an individual’s chance of having chronic pain.
What Do These Findings Mean?
Both genetic factors and chronic pain in a partner or spouse contribute to the risk of chronic pain for an individual.
Chronic pain is caused by an accumulation of many small genetic effects and is associated with some of the same genetic and environmental risk factors that confer risk of depression.
doi:10.1371/journal.pmed.1002090
PMCID: PMC4987025  PMID: 27529168
7.  Genome-wide association study identifies 74 loci associated with educational attainment 
Okbay, Aysu | Beauchamp, Jonathan P. | Fontana, Mark A. | Lee, James J. | Pers, Tune H. | Rietveld, Cornelius A. | Turley, Patrick | Chen, Guo-Bo | Emilsson, Valur | Meddens, S. Fleur W. | Oskarsson, Sven | Pickrell, Joseph K. | Thom, Kevin | Timshel, Pascal | de Vlaming, Ronald | Abdellaoui, Abdel | Ahluwalia, Tarunveer S. | Bacelis, Jonas | Baumbach, Clemens | Bjornsdottir, Gyda | Brandsma, Johannes H. | Concas, Maria Pina | Derringer, Jaime | Furlotte, Nicholas A. | Galesloot, Tessel E. | Girotto, Giorgia | Gupta, Richa | Hall, Leanne M. | Harris, Sarah E. | Hofer, Edith | Horikoshi, Momoko | Huffman, Jennifer E. | Kaasik, Kadri | Kalafati, Ioanna P. | Karlsson, Robert | Kong, Augustine | Lahti, Jari | van der Lee, Sven J. | de Leeuw, Christiaan | Lind, Penelope A. | Lindgren, Karl-Oskar | Liu, Tian | Mangino, Massimo | Marten, Jonathan | Mihailov, Evelin | Miller, Michael B. | van der Most, Peter J. | Oldmeadow, Christopher | Payton, Antony | Pervjakova, Natalia | Peyrot, Wouter J. | Qian, Yong | Raitakari, Olli | Rueedi, Rico | Salvi, Erika | Schmidt, Börge | Schraut, Katharina E. | Shi, Jianxin | Smith, Albert V. | Poot, Raymond A. | Pourcain, Beate | Teumer, Alexander | Thorleifsson, Gudmar | Verweij, Niek | Vuckovic, Dragana | Wellmann, Juergen | Westra, Harm-Jan | Yang, Jingyun | Zhao, Wei | Zhu, Zhihong | Alizadeh, Behrooz Z. | Amin, Najaf | Bakshi, Andrew | Baumeister, Sebastian E. | Biino, Ginevra | Bønnelykke, Klaus | Boyle, Patricia A. | Campbell, Harry | Cappuccio, Francesco P. | Davies, Gail | De Neve, Jan-Emmanuel | Deloukas, Panos | Demuth, Ilja | Ding, Jun | Eibich, Peter | Eisele, Lewin | Eklund, Niina | Evans68, David M. | Faul, Jessica D. | Feitosa, Mary F. | Forstner, Andreas J. | Gandin, Ilaria | Gunnarsson, Bjarni | Halldórsson, Bjarni V. | Harris, Tamara B. | Heath, Andrew C. | Hocking, Lynne J. | Holliday, Elizabeth G. | Homuth, Georg | Horan, Michael A. | Hottenga, Jouke-Jan | de Jager, Philip L. | Joshi, Peter K. | Jugessur, Astanand | Kaakinen, Marika A. | Kähönen, Mika | Kanoni, Stavroula | Keltigangas-Järvinen, Liisa | Kiemeney, Lambertus A.L.M. | Kolcic, Ivana | Koskinen, Seppo | Kraja, Aldi T. | Kroh, Martin | Kutalik, Zoltan | Latvala, Antti | Launer, Lenore J. | Lebreton, Maël P. | Levinson, Douglas F. | Lichtenstein, Paul | Lichtner, Peter | Liewald, David C.M. | Loukola, Anu | Madden, Pamela A. | Mägi, Reedik | Mäki-Opas, Tomi | Marioni, Riccardo E. | Marques-Vidal, Pedro | Meddens, Gerardus A. | McMahon, George | Meisinger, Christa | Meitinger, Thomas | Milaneschi, Yusplitri | Milani, Lili | Montgomery, Grant W. | Myhre, Ronny | Nelson, Christopher P. | Nyholt, Dale R. | Ollier, William E.R. | Palotie, Aarno | Paternoster, Lavinia | Pedersen, Nancy L. | Petrovic, Katja E. | Porteous, David J. | Räikkönen, Katri | Ring, Susan M. | Robino, Antonietta | Rostapshova, Olga | Rudan, Igor | Rustichini, Aldo | Salomaa, Veikko | Sanders, Alan R. | Sarin, Antti-Pekka | Schmidt, Helena | Scott, Rodney J. | Smith, Blair H. | Smith, Jennifer A. | Staessen, Jan A. | Steinhagen-Thiessen, Elisabeth | Strauch, Konstantin | Terracciano, Antonio | Tobin, Martin D. | Ulivi, Sheila | Vaccargiu, Simona | Quaye, Lydia | van Rooij, Frank J.A. | Venturini, Cristina | Vinkhuyzen, Anna A.E. | Völker, Uwe | Völzke, Henry | Vonk, Judith M. | Vozzi, Diego | Waage, Johannes | Ware, Erin B. | Willemsen, Gonneke | Attia, John R. | Bennett, David A. | Berger, Klaus | Bertram, Lars | Bisgaard, Hans | Boomsma, Dorret I. | Borecki, Ingrid B. | Bultmann, Ute | Chabris, Christopher F. | Cucca, Francesco | Cusi, Daniele | Deary, Ian J. | Dedoussis, George V. | van Duijn, Cornelia M. | Eriksson, Johan G. | Franke, Barbara | Franke, Lude | Gasparini, Paolo | Gejman, Pablo V. | Gieger, Christian | Grabe, Hans-Jörgen | Gratten, Jacob | Groenen, Patrick J.F. | Gudnason, Vilmundur | van der Harst, Pim | Hayward, Caroline | Hinds, David A. | Hoffmann, Wolfgang | Hyppönen, Elina | Iacono, William G. | Jacobsson, Bo | Järvelin, Marjo-Riitta | Jöckel, Karl-Heinz | Kaprio, Jaakko | Kardia, Sharon L.R. | Lehtimäki, Terho | Lehrer, Steven F. | Magnusson, Patrik K.E. | Martin, Nicholas G. | McGue, Matt | Metspalu, Andres | Pendleton, Neil | Penninx, Brenda W.J.H. | Perola, Markus | Pirastu, Nicola | Pirastu, Mario | Polasek, Ozren | Posthuma, Danielle | Power, Christine | Province, Michael A. | Samani, Nilesh J. | Schlessinger, David | Schmidt, Reinhold | Sørensen, Thorkild I.A. | Spector, Tim D. | Stefansson, Kari | Thorsteinsdottir, Unnur | Thurik, A. Roy | Timpson, Nicholas J. | Tiemeier, Henning | Tung, Joyce Y. | Uitterlinden, André G. | Vitart, Veronique | Vollenweider, Peter | Weir, David R. | Wilson, James F. | Wright, Alan F. | Conley, Dalton C. | Krueger, Robert F. | Smith, George Davey | Hofman, Albert | Laibson, David I. | Medland, Sarah E. | Meyer, Michelle N. | Yang, Jian | Johannesson, Magnus | Visscher, Peter M. | Esko, Tõnu | Koellinger, Philipp D. | Cesarini, David | Benjamin, Daniel J.
Nature  2016;533(7604):539-542.
Summary
Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease.
doi:10.1038/nature17671
PMCID: PMC4883595  PMID: 27225129
8.  Assessing the genetic overlap between BMI and cognitive function 
Molecular psychiatry  2016;21(10):1477-1482.
Obesity and low cognitive function are associated with multiple adverse health outcomes across the life-course. They have a small phenotypic correlation (r=−0.11; high BMI - low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6 815 unrelated, genotyped members of Generation Scotland - an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using: same-sample bivariate GCTA-GREML; independent samples bivariate GCTA-GREML utilising Generation Scotland for cognitive data, and four other samples (n=20 806) for BMI; and bivariate LDSC analysis utilising the largest GWAS summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of −0.51 (SE 0.15) was observed using the same-sample GCTA-GREML approach compared to −0.10 (SE 0.08) from the independent samples GCTA-GREML approach, and −0.22 (SE 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI, and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10−7) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10−5, which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function.
doi:10.1038/mp.2015.205
PMCID: PMC4863955  PMID: 26857597
BMI; cognitive function; genetics; polygenic score
9.  Shared Genetics and Couple-Associated Environment Are Major Contributors to the Risk of Both Clinical and Self-Declared Depression 
EBioMedicine  2016;14:161-167.
Background
Both genetic and environmental factors contribute to risk of depression, but estimates of their relative contributions are limited. Commonalities between clinically-assessed major depressive disorder (MDD) and self-declared depression (SDD) are also unclear.
Methods
Using data from a large Scottish family-based cohort (GS:SFHS, N = 19,994), we estimated the genetic and environmental variance components for MDD and SDD. The components representing the genetic effect associated with genome-wide common genetic variants (SNP heritability), the additional pedigree-associated genetic effect and non-genetic effects associated with common environments were estimated in a linear mixed model (LMM).
Findings
Both MDD and SDD had significant contributions from components representing the effect from common genetic variants, the additional genetic effect associated with the pedigree and the common environmental effect shared by couples. The estimate of correlation between SDD and MDD was high (r = 1.00, se = 0.20) for common-variant-associated genetic effect and lower for the additional genetic effect from the pedigree (r = 0.57, se = 0.08) and the couple-shared environmental effect (r = 0.53, se = 0.22).
Interpretation
Both genetics and couple-shared environmental effects were major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression.
Highlights
•Shared genetics and couple-associated environment are major contributors to the risk of depression.•The common-variant-associated genetic correlation between MDD and SDD was very high (r = 1.00, se = 0.20).•Lower correlations were detected for pedigree-associated genetics and couple-shared environmental components.
It is important to understand the differences between clinical depression (MDD) and self-declared depression (SDD) for which there has been recent genetics progress. We found major contributions from genetics and couple-shared environment to both traits. There is a very high correlation between the traits associated with common genetic variants but a lower correlation for other (probably rarer) genetic variation. MDD and SDD also likely differ in their shared environmental risk factors. Thus for studies of common genetic variation, SDD is a potential alternative to MDD. In clinical practice and research, the spousal depression status should also be considered a risk indicator.
doi:10.1016/j.ebiom.2016.11.003
PMCID: PMC5161419  PMID: 27838479
Major depressive disorder; Self-declared depression; SNP heritability; Couple effect; Family environment; Linear mixed modeling
10.  Rare Functional Variant in TM2D3 is Associated with Late-Onset Alzheimer's Disease 
PLoS Genetics  2016;12(10):e1006327.
We performed an exome-wide association analysis in 1393 late-onset Alzheimer’s disease (LOAD) cases and 8141 controls from the CHARGE consortium. We found that a rare variant (P155L) in TM2D3 was enriched in Icelanders (~0.5% versus <0.05% in other European populations). In 433 LOAD cases and 3903 controls from the Icelandic AGES sub-study, P155L was associated with increased risk and earlier onset of LOAD [odds ratio (95% CI) = 7.5 (3.5–15.9), p = 6.6x10-9]. Mutation in the Drosophila TM2D3 homolog, almondex, causes a phenotype similar to loss of Notch/Presenilin signaling. Human TM2D3 is capable of rescuing these phenotypes, but this activity is abolished by P155L, establishing it as a functionally damaging allele. Our results establish a rare TM2D3 variant in association with LOAD susceptibility, and together with prior work suggests possible links to the β-amyloid cascade.
Author Summary
Alzheimer’s disease (AD) is the most common cause of dementia in the older adult population. There is substantial evidence for an important genetic contribution to AD risk. While prior work has comprehensively evaluated the contribution of common genetic variants in large population-based cohorts, the role of rare variants remains to be defined. Here, we have used a newer genotyping array to characterize less common variants, including those likely to impact the function of encoded proteins, in a combined cohort of 1393 AD cases and 8141 control subjects without AD. Our results implicate a novel, amino acid-changing variant, P155L, in the TM2D3 gene. This variant was discovered to be more common in the Icelandic population, where it was significantly associated with both increased risk and earlier age of onset of AD. Lastly, in order to examine the potential functional impact of the implicated variant, we performed additional studies in the fruit fly. Our results suggest that P155L causes a loss-of-function in TM2D3, in the context of Notch-Presenilin signal transduction. In sum, we identify a novel, rare TM2D3 variant in association with AD risk and highlight functional connections with AD-relevant biology.
doi:10.1371/journal.pgen.1006327
PMCID: PMC5072721  PMID: 27764101
12.  Balanced translocation linked to psychiatric disorder, glutamate, and cortical structure/function 
NPJ Schizophrenia  2016;2:16024-.
Rare genetic variants of large effect can help elucidate the pathophysiology of brain disorders. Here we expand the clinical and genetic analyses of a family with a (1;11)(q42;q14.3) translocation multiply affected by major psychiatric illness and test the effect of the translocation on the structure and function of prefrontal, and temporal brain regions. The translocation showed significant linkage (LOD score 6.1) with a clinical phenotype that included schizophrenia, schizoaffective disorder, bipolar disorder, and recurrent major depressive disorder. Translocation carriers showed reduced cortical thickness in the left temporal lobe, which correlated with general psychopathology and positive psychotic symptom severity. They showed reduced gyrification in prefrontal cortex, which correlated with general psychopathology severity. Translocation carriers also showed significantly increased activation in the caudate nucleus on increasing verbal working memory load, as well as statistically significant reductions in the right dorsolateral prefrontal cortex glutamate concentrations. These findings confirm that the t(1;11) translocation is associated with a significantly increased risk of major psychiatric disorder and suggest a general vulnerability to psychopathology through altered cortical structure and function, and decreased glutamate levels.
doi:10.1038/npjschz.2016.24
PMCID: PMC4994153  PMID: 27602385
13.  APOE/TOMM 40 genetic loci, white matter hyperintensities, and cerebral microbleeds 
International Journal of Stroke  2015;10(8):1297-1300.
Background
Two markers of cerebral small vessel disease are white matter hyperintensities and cerebral microbleeds, which commonly occur in people with Alzheimer's disease.
Aim and/or hypothesis
To test for independent associations between two Alzheimer's disease‐susceptibility gene loci – APOE ε and the TOMM 40 ‘523’ poly‐T repeat – and white matter hyperintensities/cerebral microbleed burden in community‐dwelling older adults.
Methods
Participants in the Lothian Birth Cohort 1936 underwent genotyping for APOE ε and TOMM 40 523, and detailed structural brain magnetic resonance imaging at a mean age of 72·70 years (standard deviation = 0·7; range = 71–74).
Results
No significant effects of APOE ε or TOMM 40 523 genotypes on white matter hyperintensities or cerebral microbleed burden were found amongst 624 participants.
Conclusions
Lack of association between two Alzheimer's disease susceptibility gene loci and markers of cerebral small vessel disease may reflect the relative health of this population compared with those in other studies in the literature.
doi:10.1111/ijs.12615
PMCID: PMC4950052  PMID: 26310205
brain microbleeds; epidemiology; MRI; neurology; risk factors; vascular events
15.  Exome-wide analysis of rare coding variation identifies novel associations with COPD and airflow limitation in MOCS3, IFIT3 and SERPINA12 
Thorax  2016;71(6):501-509.
Background
Several regions of the genome have shown to be associated with COPD in genome-wide association studies of common variants.
Objective
To determine rare and potentially functional single nucleotide polymorphisms (SNPs) associated with the risk of COPD and severity of airflow limitation.
Methods
3226 current or former smokers of European ancestry with lung function measures indicative of Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2 COPD or worse were genotyped using an exome array. An analysis of risk of COPD was carried out using ever smoking controls (n=4784). Associations with %predicted FEV1 were tested in cases. We followed-up signals of interest (p<10−5) in independent samples from a subset of the UK Biobank population and also undertook a more powerful discovery study by meta-analysing the exome array data and UK Biobank data for variants represented on both arrays.
Results
Among the associated variants were two in regions previously unreported for COPD; a low frequency non-synonymous SNP in MOCS3 (rs7269297, pdiscovery=3.08×10−6, preplication=0.019) and a rare SNP in IFIT3, which emerged in the meta-analysis (rs140549288, pmeta=8.56×10−6). In the meta-analysis of % predicted FEV1 in cases, the strongest association was shown for a splice variant in a previously unreported region, SERPINA12 (rs140198372, pmeta=5.72×10−6). We also confirmed previously reported associations with COPD risk at MMP12, HHIP, GPR126 and CHRNA5. No associations in novel regions reached a stringent exome-wide significance threshold (p<3.7×10−7).
Conclusions
This study identified several associations with the risk of COPD and severity of airflow limitation, including novel regions MOCS3, IFIT3 and SERPINA12, which warrant further study.
doi:10.1136/thoraxjnl-2015-207876
PMCID: PMC4893124  PMID: 26917578
COPD epidemiology; Tobacco and the lung
16.  Differential effects of the APOE e4 allele on different domains of cognitive ability across the life-course 
The association between APOE genotype and cognitive function suggests a positive role for the e2 allele and a negative role for the e4 allele. Both alleles have relatively low frequencies in the general population; hence, meta-analyses have been based on many small, heterogeneous studies. Here, we report the APOE-cognition associations in the largest single analysis to date. APOE status and cognitive ability were measured in 18 337 participants from the Generation Scotland study between 2006 and 2011. The age range was 18–94 years with a mean of 47 (SD 15). Four cognitive domains were assessed: verbal declarative memory (paragraph recall), processing speed (digit symbol substitution), verbal fluency (phonemic verbal fluency), and vocabulary (Mill Hill synonyms). Linear regression was used to assess the associations between APOE genetic status and cognition. Possession of the e4 allele was associated with lower scores on the measures of memory and processing speed in subjects aged >60. Across all age ranges, the e4 allele was linked to better verbal fluency scores. In younger subjects (≤60 years) the e4 allele was linked to higher vocabulary scores. There were no associations between the e2 allele and cognitive ability. As seen in previous meta-analyses, the APOE e4 allele is linked to poorer cognitive performance in the domains of memory and processing speed. By contrast, positive associations were seen between the e4 allele and measures of verbal fluency and vocabulary. All associations were relatively small and, in many cases, nominally significant despite the very large sample size.
doi:10.1038/ejhg.2015.210
PMCID: PMC4705436  PMID: 26395552
17.  Identification of polymorphic and off-target probe binding sites on the Illumina Infinium MethylationEPIC BeadChip 
Genomics Data  2016;9:22-24.
Genome-wide analysis of DNA methylation has now become a relatively inexpensive technique thanks to array-based methylation profiling technologies. The recently developed Illumina Infinium MethylationEPIC BeadChip interrogates methylation at over 850,000 sites across the human genome, covering 99% of RefSeq genes. This array supersedes the widely used Infinium HumanMethylation450 BeadChip, which has permitted insights into the relationship between DNA methylation and a wide range of conditions and traits. Previous research has identified issues with certain probes on both the HumanMethylation450 BeadChip and its predecessor, the Infinium HumanMethylation27 BeadChip, which were predicted to affect array performance. These issues concerned probe-binding specificity and the presence of polymorphisms at target sites. Using in silico methods, we have identified probes on the Infinium MethylationEPIC BeadChip that are predicted to (i) measure methylation at polymorphic sites and (ii) hybridise to multiple genomic regions. We intend these resources to be used for quality control procedures when analysing data derived from this platform.
doi:10.1016/j.gdata.2016.05.012
PMCID: PMC4909830  PMID: 27330998
DNA methylation; Infinium MethylationEPIC BeadChip; Cross-hybridising probes; Polymorphic CpG; Quality control
18.  Polygenic risk for alcohol dependence associates with alcohol consumption, cognitive function and social deprivation in a population‐based cohort 
Addiction Biology  2015;21(2):469-480.
Abstract
Alcohol dependence is frequently co‐morbid with cognitive impairment. The relationship between these traits is complex as cognitive dysfunction may arise as a consequence of heavy drinking or exist prior to the onset of dependence. In the present study, we tested the genetic overlap between cognitive abilities and alcohol dependence using polygenic risk scores (PGRS). We created two independent PGRS derived from two recent genome‐wide association studies (GWAS) of alcohol dependence (SAGE GWAS: n = 2750; Yale‐Penn GWAS: n = 2377) in a population‐based cohort, Generation Scotland: Scottish Family Health Study (GS:SFHS) (n = 9863). Data on alcohol consumption and four tests of cognitive function [Mill Hill Vocabulary (MHV), digit symbol coding, phonemic verbal fluency (VF) and logical memory] were available. PGRS for alcohol dependence were negatively associated with two measures of cognitive function: MHV (SAGE: P = 0.009, β = −0.027; Yale‐Penn: P = 0.001, β = −0.034) and VF (SAGE: P = 0.0008, β = −0.036; Yale‐Penn: P = 0.00005, β = −0.044). VF remained robustly associated after adjustment for education and social deprivation; however, the association with MHV was substantially attenuated. Shared genetic variants may account for some of the phenotypic association between cognitive ability and alcohol dependence. A significant negative association between PGRS and social deprivation was found (SAGE: P = 5.2 × 10−7, β = −0.054; Yale‐Penn: P = 0.000012, β = −0.047). Individuals living in socially deprived regions were found to carry more alcohol dependence risk alleles which may contribute to the increased prevalence of problem drinking in regions of deprivation. Future work to identify genes which affect both cognitive impairment and alcohol dependence will help elucidate biological processes common to both disorders.
doi:10.1111/adb.12245
PMCID: PMC4600406  PMID: 25865819
Alcohol dependence; cognition; environment; genetics; polygenic; social deprivation
19.  Differential effects of the APOE e4 allele on different domains of cognitive ability across the life-course 
The association between APOE genotype and cognitive function suggests a positive role for the e2 allele and a negative role for the e4 allele. Both alleles have relatively low frequencies in the general population, hence meta-analyses have been based on many small, heterogeneous studies. Here we report the APOE-cognition associations in the largest single analysis to date. APOE status and cognitive ability were measured in 18,337 participants from the Generation Scotland study between 2006 and 2011. The age range was 18-94 years with a mean of 47 (SD 15). Four cognitive domains were assessed: verbal declarative memory (paragraph recall), processing speed (digit symbol substitution), verbal fluency (phonemic verbal fluency), and vocabulary (Mill Hill synonyms). Linear regression was used to assess the associations between APOE genetic status and cognition. Possession of the e4 allele was associated with lower scores on the measures of memory and processing speed in subjects aged >60. Across all age ranges, the e4 allele was linked to better verbal fluency scores. In younger subjects (≤60 years) the e4 allele was linked to higher vocabulary scores. There were no associations between the e2 allele and cognitive ability. As seen in previous meta-analyses, the APOE e4 allele is linked to poorer cognitive performance in the domains of memory and processing speed. By contrast, positive associations were seen between the e4 allele and measures of verbal fluency and vocabulary. All associations were relatively small and, in many cases, nominally significant despite the very large sample size.
doi:10.1038/ejhg.2015.210
PMCID: PMC4705436  PMID: 26395552
APOE; cognition; Generation Scotland
20.  Polygenic risk of ischemic stroke is associated with cognitive ability 
Neurology  2016;86(7):611-618.
Objectives:
We investigated the correlation between polygenic risk of ischemic stroke (and its subtypes) and cognitive ability in 3 relatively healthy Scottish cohorts: the Lothian Birth Cohort 1936 (LBC1936), the Lothian Birth Cohort 1921 (LBC1921), and Generation Scotland: Scottish Family Health Study (GS).
Methods:
Polygenic risk scores for ischemic stroke were created in LBC1936 (n = 1005), LBC1921 (n = 517), and GS (n = 6,815) using genome-wide association study summary data from the METASTROKE collaboration. We investigated whether the polygenic risk scores correlate with cognitive ability in the 3 cohorts.
Results:
In the largest cohort, GS, polygenic risk of all ischemic stroke, small vessel disease stroke, and large vessel disease stroke, but not cardioembolic stroke, were correlated with both fluid and crystallized cognitive abilities. The highest correlation was between a polygenic risk score for all ischemic stroke and general cognitive ability (r = −0.070, p = 1.95 × 10−8). Few correlations were identified in LBC1936 and LBC1921, but a meta-analysis of all 3 cohorts supported the correlation between polygenic risk of ischemic stroke and cognitive ability.
Conclusions:
The findings from this study indicate that even in the absence of stroke, being at high polygenic risk of ischemic stroke is associated with lower cognitive ability.
doi:10.1212/WNL.0000000000002306
PMCID: PMC4762420  PMID: 26695942
21.  Structural brain MRI trait polygenic score prediction of cognitive abilities 
Structural brain magnetic resonance imaging (MRI) traits share part of their genetic variance with cognitive traits. Here, we use genetic association results from large meta-analytic studies of genome-wide association for brain infarcts, white matter hyperintensities, intracranial, hippocampal and total brain volumes to estimate polygenic scores for these traits in three Scottish samples: Generation Scotland: Scottish Family Health Study (GS:SFHS), and the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921). These five brain MRI trait polygenic scores were then used to 1) predict corresponding MRI traits in the LBC1936 (numbers ranged 573 to 630 across traits) and 2) predict cognitive traits in all three cohorts (in 8,115 to 8,250 persons). In the LBC1936, all MRI phenotypic traits were correlated with at least one cognitive measure; and polygenic prediction of MRI traits was observed for intracranial volume. Meta-analysis of the correlations between MRI polygenic scores and cognitive traits revealed a significant negative correlation (maximal r=0.08) between the hippocampal volume polygenic score and measures of global cognitive ability collected in childhood and in old age in the Lothian Birth Cohorts. The lack of association to a related general cognitive measure when including the GS:SFHS points to either type 1 error or the importance of using prediction samples that closely match the demographics of the genome-wide association samples from which prediction is based. Ideally, these analyses should be repeated in larger samples with data on both MRI and cognition, and using MRI GWA results from even larger meta-analysis studies.
doi:10.1017/thg.2015.71
PMCID: PMC4747328  PMID: 26427786
Polygenic prediction; white matter hyperintensities; brain infarct; intracranial volume; hippocampal volume; total brain volume; general cognitive ability
22.  Genes from a translational analysis support a multifactorial nature of white matter hyperintensities 
Background and Purpose
White matter hyperintensities of presumed vascular origin (WMH) increase the risk of stroke and dementia. Despite strong WMH heritability, few gene associations have been identified. Relevant experimental models may be informative.
Methods
We tested associations between genes that were differentially-expressed in brains of young spontaneously-hypertensive stroke-prone rat (SHRSP) and human WMH (using volume and visual score) in 621 subjects from the Lothian Birth Cohort 1936 (LBC1936). We then attempted replication in 9,361 subjects from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE). We also tested the LBC1936 for previous genome-wide WMH associations found in CHARGE.
Results
Of 126 SHRSP genes, 10 were nominally associated with WMH volume or score in LBC1936, of which five [AFP, ALB, GNAI1, RBM8a, MRPL18] associated with both WMH volume and score (p<0.05); two of the 10 [XPNPEP1, p=6.7×10−5; FARP1, p=0.024] plus another SHRSP gene [USMG5, p=0.00014], on chromosomes 10, 13 and 10 respectively, associated with WMH in CHARGE. Gene set enrichment showed significant associations for down-regulated SHRSP genes with WMH in humans. In LBC1936, we replicated CHARGE’s genome-wide WMH associations on chromosomes 17 [TRIM65, TRIM47] and, for the first time, 1 [PMF1].
Conclusions
Despite not passing multiple testing thresholds individually, these genes collectively are relevant to known WMH associations, proposed WMH mechanisms or dementia: associations with Alzheimer’s disease, late life depression, ATP production, osmotic regulation, neuro-developmental abnormalities and cognitive impairment. If replicated further, they suggest a multifactorial nature for WMH and argue for more consideration of vascular contributions to dementia.
doi:10.1161/STROKEAHA.114.007649
PMCID: PMC4306534  PMID: 25586835
23.  Polygenic risk for coronary artery disease is associated with cognitive ability in older adults 
Background: Coronary artery disease (CAD) is associated with cognitive decrements and risk of later dementia, but it is not known if shared genetic factors underlie this association. We tested whether polygenic risk for CAD was associated with cognitive ability in community-dwelling cohorts of middle-aged and older adults.
Methods: Individuals from Generation Scotland: Scottish Family Health Study (GS:SFHS, N = 9865) and from the Lothian Birth Cohorts of 1921 (LBC1921, N = 517) and 1936 (LBC1936, N = 1005) provided cognitive data and genome-wide genotype data. Polygenic risk profile scores for CAD were calculated for all of the cohorts using the largest available genome-wide association studies (GWAS) data set, the CARDIoGRAM consortium (22 233 cases and 64 762 controls). Polygenic risk profile scores for CAD were then tested for their association with cognitive abilities in the presence and absence of manifest cardiovascular disease.
Results: A meta-analysis of all three cohorts showed a negative association between CAD polygenic risk and fluid cognitive ability (β = −0.022, P = 0.016), verbal intelligence (β = −0.024, P = 0.011) and memory (β = −0.021, P = 0.028).
Conclusions: Increased polygenic risk for CAD is associated with lower cognitive ability in older adults. Common genetic variants may underlie some of the association between age-related cognitive decrements and the risk for CAD.
doi:10.1093/ije/dyv354
PMCID: PMC4864876  PMID: 26822939
Coronary artery disease; polygenic traits; cognition; ageing; dementia; genetics
24.  Directional dominance on stature and cognition in diverse human populations 
Joshi, Peter K. | Esko, Tonu | Mattsson, Hannele | Eklund, Niina | Gandin, Ilaria | Nutile, Teresa | Jackson, Anne U. | Schurmann, Claudia | Smith, Albert V. | Zhang, Weihua | Okada, Yukinori | Stančáková, Alena | Faul, Jessica D. | Zhao, Wei | Bartz, Traci M. | Concas, Maria Pina | Franceschini, Nora | Enroth, Stefan | Vitart, Veronique | Trompet, Stella | Guo, Xiuqing | Chasman, Daniel I. | O’Connel, Jeffery R. | Corre, Tanguy | Nongmaithem, Suraj S. | Chen, Yuning | Mangino, Massimo | Ruggiero, Daniela | Traglia, Michela | Farmaki, Aliki-Eleni | Kacprowski, Tim | Bjonnes, Andrew | van der Spek, Ashley | Wu, Ying | Giri, Anil K. | Yanek, Lisa R. | Wang, Lihua | Hofer, Edith | Rietveld, Cornelius A. | McLeod, Olga | Cornelis, Marilyn C. | Pattaro, Cristian | Verweij, Niek | Baumbach, Clemens | Abdellaoui, Abdel | Warren, Helen R. | Vuckovic, Dragana | Mei, Hao | Bouchard, Claude | Perry, John R.B. | Cappellani, Stefania | Mirza, Saira S. | Benton, Miles C. | Broeckel, Ulrich | Medland, Sarah E. | Lind, Penelope A. | Malerba, Giovanni | Drong, Alexander | Yengo, Loic | Bielak, Lawrence F. | Zhi, Degui | van der Most, Peter J. | Shriner, Daniel | Mägi, Reedik | Hemani, Gibran | Karaderi, Tugce | Wang, Zhaoming | Liu, Tian | Demuth, Ilja | Zhao, Jing Hua | Meng, Weihua | Lataniotis, Lazaros | van der Laan, Sander W. | Bradfield, Jonathan P. | Wood, Andrew R. | Bonnefond, Amelie | Ahluwalia, Tarunveer S. | Hall, Leanne M. | Salvi, Erika | Yazar, Seyhan | Carstensen, Lisbeth | de Haan, Hugoline G. | Abney, Mark | Afzal, Uzma | Allison, Matthew A. | Amin, Najaf | Asselbergs, Folkert W. | Bakker, Stephan J.L. | Barr, R. Graham | Baumeister, Sebastian E. | Benjamin, Daniel J. | Bergmann, Sven | Boerwinkle, Eric | Bottinger, Erwin P. | Campbell, Archie | Chakravarti, Aravinda | Chan, Yingleong | Chanock, Stephen J. | Chen, Constance | Chen, Y.-D. Ida | Collins, Francis S. | Connell, John | Correa, Adolfo | Cupples, L. Adrienne | Smith, George Davey | Davies, Gail | Dörr, Marcus | Ehret, Georg | Ellis, Stephen B. | Feenstra, Bjarke | Feitosa, Mary F. | Ford, Ian | Fox, Caroline S. | Frayling, Timothy M. | Friedrich, Nele | Geller, Frank | Scotland, Generation | Gillham-Nasenya, Irina | Gottesman, Omri | Graff, Misa | Grodstein, Francine | Gu, Charles | Haley, Chris | Hammond, Christopher J. | Harris, Sarah E. | Harris, Tamara B. | Hastie, Nicholas D. | Heard-Costa, Nancy L. | Heikkilä, Kauko | Hocking, Lynne J. | Homuth, Georg | Hottenga, Jouke-Jan | Huang, Jinyan | Huffman, Jennifer E. | Hysi, Pirro G. | Ikram, M. Arfan | Ingelsson, Erik | Joensuu, Anni | Johansson, Åsa | Jousilahti, Pekka | Jukema, J. Wouter | Kähönen, Mika | Kamatani, Yoichiro | Kanoni, Stavroula | Kerr, Shona M. | Khan, Nazir M. | Koellinger, Philipp | Koistinen, Heikki A. | Kooner, Manraj K. | Kubo, Michiaki | Kuusisto, Johanna | Lahti, Jari | Launer, Lenore J. | Lea, Rodney A. | Lehne, Benjamin | Lehtimäki, Terho | Liewald, David C.M. | Lind, Lars | Loh, Marie | Lokki, Marja-Liisa | London, Stephanie J. | Loomis, Stephanie J. | Loukola, Anu | Lu, Yingchang | Lumley, Thomas | Lundqvist, Annamari | Männistö, Satu | Marques-Vidal, Pedro | Masciullo, Corrado | Matchan, Angela | Mathias, Rasika A. | Matsuda, Koichi | Meigs, James B. | Meisinger, Christa | Meitinger, Thomas | Menni, Cristina | Mentch, Frank D. | Mihailov, Evelin | Milani, Lili | Montasser, May E. | Montgomery, Grant W. | Morrison, Alanna | Myers, Richard H. | Nadukuru, Rajiv | Navarro, Pau | Nelis, Mari | Nieminen, Markku S. | Nolte, Ilja M. | O’Connor, George T. | Ogunniyi, Adesola | Padmanabhan, Sandosh | Palmas, Walter R. | Pankow, James S. | Patarcic, Inga | Pavani, Francesca | Peyser, Patricia A. | Pietilainen, Kirsi | Poulter, Neil | Prokopenko, Inga | Ralhan, Sarju | Redmond, Paul | Rich, Stephen S. | Rissanen, Harri | Robino, Antonietta | Rose, Lynda M. | Rose, Richard | Sala, Cinzia | Salako, Babatunde | Salomaa, Veikko | Sarin, Antti-Pekka | Saxena, Richa | Schmidt, Helena | Scott, Laura J. | Scott, William R. | Sennblad, Bengt | Seshadri, Sudha | Sever, Peter | Shrestha, Smeeta | Smith, Blair H. | Smith, Jennifer A. | Soranzo, Nicole | Sotoodehnia, Nona | Southam, Lorraine | Stanton, Alice V. | Stathopoulou, Maria G. | Strauch, Konstantin | Strawbridge, Rona J. | Suderman, Matthew J. | Tandon, Nikhil | Tang, Sian-Tsun | Taylor, Kent D. | Tayo, Bamidele O. | Töglhofer, Anna Maria | Tomaszewski, Maciej | Tšernikova, Natalia | Tuomilehto, Jaakko | Uitterlinden, Andre G. | Vaidya, Dhananjay | van Hylckama Vlieg, Astrid | van Setten, Jessica | Vasankari, Tuula | Vedantam, Sailaja | Vlachopoulou, Efthymia | Vozzi, Diego | Vuoksimaa, Eero | Waldenberger, Melanie | Ware, Erin B. | Wentworth-Shields, William | Whitfield, John B. | Wild, Sarah | Willemsen, Gonneke | Yajnik, Chittaranjan S. | Yao, Jie | Zaza, Gianluigi | Zhu, Xiaofeng | Project, The BioBank Japan | Salem, Rany M. | Melbye, Mads | Bisgaard, Hans | Samani, Nilesh J. | Cusi, Daniele | Mackey, David A. | Cooper, Richard S. | Froguel, Philippe | Pasterkamp, Gerard | Grant, Struan F.A. | Hakonarson, Hakon | Ferrucci, Luigi | Scott, Robert A. | Morris, Andrew D. | Palmer, Colin N.A. | Dedoussis, George | Deloukas, Panos | Bertram, Lars | Lindenberger, Ulman | Berndt, Sonja I. | Lindgren, Cecilia M. | Timpson, Nicholas J. | Tönjes, Anke | Munroe, Patricia B. | Sørensen, Thorkild I.A. | Rotimi, Charles N. | Arnett, Donna K. | Oldehinkel, Albertine J. | Kardia, Sharon L.R. | Balkau, Beverley | Gambaro, Giovanni | Morris, Andrew P. | Eriksson, Johan G. | Wright, Margie J. | Martin, Nicholas G. | Hunt, Steven C. | Starr, John M. | Deary, Ian J. | Griffiths, Lyn R. | Tiemeier, Henning | Pirastu, Nicola | Kaprio, Jaakko | Wareham, Nicholas J. | Pérusse, Louis | Wilson, James G. | Girotto, Giorgia | Caulfield, Mark J. | Raitakari, Olli | Boomsma, Dorret I. | Gieger, Christian | van der Harst, Pim | Hicks, Andrew A. | Kraft, Peter | Sinisalo, Juha | Knekt, Paul | Johannesson, Magnus | Magnusson, Patrik K.E. | Hamsten, Anders | Schmidt, Reinhold | Borecki, Ingrid B. | Vartiainen, Erkki | Becker, Diane M. | Bharadwaj, Dwaipayan | Mohlke, Karen L. | Boehnke, Michael | van Duijn, Cornelia M. | Sanghera, Dharambir K. | Teumer, Alexander | Zeggini, Eleftheria | Metspalu, Andres | Gasparini, Paolo | Ulivi, Sheila | Ober, Carole | Toniolo, Daniela | Rudan, Igor | Porteous, David J. | Ciullo, Marina | Spector, Tim D. | Hayward, Caroline | Dupuis, Josée | Loos, Ruth J.F. | Wright, Alan F. | Chandak, Giriraj R. | Vollenweider, Peter | Shuldiner, Alan | Ridker, Paul M. | Rotter, Jerome I. | Sattar, Naveed | Gyllensten, Ulf | North, Kari E. | Pirastu, Mario | Psaty, Bruce M. | Weir, David R. | Laakso, Markku | Gudnason, Vilmundur | Takahashi, Atsushi | Chambers, John C. | Kooner, Jaspal S. | Strachan, David P. | Campbell, Harry | Hirschhorn, Joel N. | Perola, Markus | Polašek, Ozren | Wilson, James F.
Nature  2015;523(7561):459-462.
Homozygosity has long been associated with rare, often devastating, Mendelian disorders1 and Darwin was one of the first to recognise that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity, ROH), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use ROH to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts and find statistically significant associations between summed runs of homozygosity (SROH) and four complex traits: height, forced expiratory lung volume in 1 second (FEV1), general cognitive ability (g) and educational attainment (nominal p<1 × 10−300, 2.1 × 10−6, 2.5 × 10−10, 1.8 × 10−10). In each case increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing convincing evidence for the first time that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
doi:10.1038/nature14618
PMCID: PMC4516141  PMID: 26131930
25.  Epidemiology and Heritability of Major Depressive Disorder, Stratified by Age of Onset, Sex, and Illness Course in Generation Scotland: Scottish Family Health Study (GS:SFHS) 
PLoS ONE  2015;10(11):e0142197.
The heritability of Major Depressive Disorder (MDD) has been estimated at 37% based largely on twin studies that rely on contested assumptions. More recently, the heritability of MDD has been estimated on large populations from registries such as the Swedish, Finnish, and Chinese cohorts. Family-based designs utilise a number of different relationships and provide an alternative means of estimating heritability. Generation Scotland: Scottish Family Health Study (GS:SFHS) is a large (n = 20,198), family-based population study designed to identify the genetic determinants of common diseases, including Major Depressive Disorder. Two thousand seven hundred and six individuals were SCID diagnosed with MDD, 13.5% of the cohort, from which we inferred a population prevalence of 12.2% (95% credible interval: 11.4% to 13.1%). Increased risk of MDD was associated with being female, unemployed due to a disability, current smokers, former drinkers, and living in areas of greater social deprivation. The heritability of MDD in GS:SFHS was between 28% and 44%, estimated from a pedigree model. The genetic correlation of MDD between sexes, age of onset, and illness course were examined and showed strong genetic correlations. The genetic correlation between males and females with MDD was 0.75 (0.43 to 0.99); between earlier (≤ age 40) and later (> age 40) onset was 0.85 (0.66 to 0.98); and between single and recurrent episodic illness course was 0.87 (0.72 to 0.98). We found that the heritability of recurrent MDD illness course was significantly greater than the heritability of single MDD illness course. The study confirms a moderate genetic contribution to depression, with a small contribution of the common family environment (variance proportion = 0.07, CI: 0.01 to 0.15), and supports the relationship of MDD with previously identified risk factors. This study did not find robust support for genetic differences in MDD due to sex, age of onset, or illness course. However, we found an intriguing difference in heritability between recurrent and single MDD illness course. These findings establish GS:SFHS as a valuable cohort for the genetic investigation of MDD.
doi:10.1371/journal.pone.0142197
PMCID: PMC4646689  PMID: 26571028

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