@article {6568, title = {Mendelian randomization of blood lipids for coronary heart disease.}, journal = {Eur Heart J}, volume = {36}, year = {2015}, month = {2015 Mar 01}, pages = {539-50}, abstract = {
AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization.
METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 {\texttimes} 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P <= 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95\% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95\% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95\% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95\% CI: 1.24, 2.11 and 1.61; 95\% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95\% CI: 0.59, 1.75).
CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.
}, keywords = {Case-Control Studies, Cholesterol, HDL, Coronary Artery Disease, Female, Gene Frequency, Genotype, Genotyping Techniques, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Polymorphism, Single Nucleotide, Risk Assessment, Triglycerides}, issn = {1522-9645}, doi = {10.1093/eurheartj/eht571}, author = {Holmes, Michael V and Asselbergs, Folkert W and Palmer, Tom M and Drenos, Fotios and Lanktree, Matthew B and Nelson, Christopher P and Dale, Caroline E and Padmanabhan, Sandosh and Finan, Chris and Swerdlow, Daniel I and Tragante, Vinicius and van Iperen, Erik P A and Sivapalaratnam, Suthesh and Shah, Sonia and Elbers, Clara C and Shah, Tina and Engmann, Jorgen and Giambartolomei, Claudia and White, Jon and Zabaneh, Delilah and Sofat, Reecha and McLachlan, Stela and Doevendans, Pieter A and Balmforth, Anthony J and Hall, Alistair S and North, Kari E and Almoguera, Berta and Hoogeveen, Ron C and Cushman, Mary and Fornage, Myriam and Patel, Sanjay R and Redline, Susan and Siscovick, David S and Tsai, Michael Y and Karczewski, Konrad J and Hofker, Marten H and Verschuren, W Monique and Bots, Michiel L and van der Schouw, Yvonne T and Melander, Olle and Dominiczak, Anna F and Morris, Richard and Ben-Shlomo, Yoav and Price, Jackie and Kumari, Meena and Baumert, Jens and Peters, Annette and Thorand, Barbara and Koenig, Wolfgang and Gaunt, Tom R and Humphries, Steve E and Clarke, Robert and Watkins, Hugh and Farrall, Martin and Wilson, James G and Rich, Stephen S and de Bakker, Paul I W and Lange, Leslie A and Davey Smith, George and Reiner, Alex P and Talmud, Philippa J and Kivimaki, Mika and Lawlor, Debbie A and Dudbridge, Frank and Samani, Nilesh J and Keating, Brendan J and Hingorani, Aroon D and Casas, Juan P} } @article {7262, title = {52 Genetic Loci Influencing Myocardial~Mass.}, journal = {J Am Coll Cardiol}, volume = {68}, year = {2016}, month = {2016 Sep 27}, pages = {1435-48}, abstract = {BACKGROUND: Myocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death.
OBJECTIVES: This meta-analysis sought to gain insights into the genetic determinants of myocardial mass.
METHODS: We carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment.
RESULTS: We identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p~< 1~{\texttimes} 10(-8). These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67~candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in~vitro and in~vivo.
CONCLUSIONS: Taken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets.
}, issn = {1558-3597}, doi = {10.1016/j.jacc.2016.07.729}, author = {van der Harst, Pim and van Setten, Jessica and Verweij, Niek and Vogler, Georg and Franke, Lude and Maurano, Matthew T and Wang, Xinchen and Mateo Leach, Irene and Eijgelsheim, Mark and Sotoodehnia, Nona and Hayward, Caroline and Sorice, Rossella and Meirelles, Osorio and Lyytik{\"a}inen, Leo-Pekka and Polasek, Ozren and Tanaka, Toshiko and Arking, Dan E and Ulivi, Sheila and Trompet, Stella and M{\"u}ller-Nurasyid, Martina and Smith, Albert V and D{\"o}rr, Marcus and Kerr, Kathleen F and Magnani, Jared W and del Greco M, Fabiola and Zhang, Weihua and Nolte, Ilja M and Silva, Claudia T and Padmanabhan, Sandosh and Tragante, Vinicius and Esko, T{\~o}nu and Abecasis, Goncalo R and Adriaens, Michiel E and Andersen, Karl and Barnett, Phil and Bis, Joshua C and Bodmer, Rolf and Buckley, Brendan M and Campbell, Harry and Cannon, Megan V and Chakravarti, Aravinda and Chen, Lin Y and Delitala, Alessandro and Devereux, Richard B and Doevendans, Pieter A and Dominiczak, Anna F and Ferrucci, Luigi and Ford, Ian and Gieger, Christian and Harris, Tamara B and Haugen, Eric and Heinig, Matthias and Hernandez, Dena G and Hillege, Hans L and Hirschhorn, Joel N and Hofman, Albert and Hubner, Norbert and Hwang, Shih-Jen and Iorio, Annamaria and K{\"a}h{\"o}nen, Mika and Kellis, Manolis and Kolcic, Ivana and Kooner, Ishminder K and Kooner, Jaspal S and Kors, Jan A and Lakatta, Edward G and Lage, Kasper and Launer, Lenore J and Levy, Daniel and Lundby, Alicia and Macfarlane, Peter W and May, Dalit and Meitinger, Thomas and Metspalu, Andres and Nappo, Stefania and Naitza, Silvia and Neph, Shane and Nord, Alex S and Nutile, Teresa and Okin, Peter M and Olsen, Jesper V and Oostra, Ben A and Penninger, Josef M and Pennacchio, Len A and Pers, Tune H and Perz, Siegfried and Peters, Annette and Pinto, Yigal M and Pfeufer, Arne and Pilia, Maria Grazia and Pramstaller, Peter P and Prins, Bram P and Raitakari, Olli T and Raychaudhuri, Soumya and Rice, Ken M and Rossin, Elizabeth J and Rotter, Jerome I and Schafer, Sebastian and Schlessinger, David and Schmidt, Carsten O and Sehmi, Jobanpreet and Sillj{\'e}, Herman H W and Sinagra, Gianfranco and Sinner, Moritz F and Slowikowski, Kamil and Soliman, Elsayed Z and Spector, Timothy D and Spiering, Wilko and Stamatoyannopoulos, John A and Stolk, Ronald P and Strauch, Konstantin and Tan, Sian-Tsung and Tarasov, Kirill V and Trinh, Bosco and Uitterlinden, Andr{\'e} G and van den Boogaard, Malou and van Duijn, Cornelia M and van Gilst, Wiek H and Viikari, Jorma S and Visscher, Peter M and Vitart, Veronique and V{\"o}lker, Uwe and Waldenberger, Melanie and Weichenberger, Christian X and Westra, Harm-Jan and Wijmenga, Cisca and Wolffenbuttel, Bruce H and Yang, Jian and Bezzina, Connie R and Munroe, Patricia B and Snieder, Harold and Wright, Alan F and Rudan, Igor and Boyer, Laurie A and Asselbergs, Folkert W and van Veldhuisen, Dirk J and Stricker, Bruno H and Psaty, Bruce M and Ciullo, Marina and Sanna, Serena and Lehtim{\"a}ki, Terho and Wilson, James F and Bandinelli, Stefania and Alonso, Alvaro and Gasparini, Paolo and Jukema, J Wouter and K{\"a}{\"a}b, Stefan and Gudnason, Vilmundur and Felix, Stephan B and Heckbert, Susan R and de Boer, Rudolf A and Newton-Cheh, Christopher and Hicks, Andrew A and Chambers, John C and Jamshidi, Yalda and Visel, Axel and Christoffels, Vincent M and Isaacs, Aaron and Samani, Nilesh J and de Bakker, Paul I W} } @article {7566, title = {Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.}, journal = {BioData Min}, volume = {10}, year = {2017}, month = {2017}, pages = {25}, abstract = {BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG).
RESULTS: Our analysis consisted of a discovery phase using a merged dataset of five different cohorts (n~=~12,853 to n~=~16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of p~<~0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of p~<~0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing.
CONCLUSIONS: These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.
}, issn = {1756-0381}, doi = {10.1186/s13040-017-0145-5}, author = {Holzinger, Emily R and Verma, Shefali S and Moore, Carrie B and Hall, Molly and De, Rishika and Gilbert-Diamond, Diane and Lanktree, Matthew B and Pankratz, Nathan and Amuzu, Antoinette and Burt, Amber and Dale, Caroline and Dudek, Scott and Furlong, Clement E and Gaunt, Tom R and Kim, Daniel Seung and Riess, Helene and Sivapalaratnam, Suthesh and Tragante, Vinicius and van Iperen, Erik P A and Brautbar, Ariel and Carrell, David S and Crosslin, David R and Jarvik, Gail P and Kuivaniemi, Helena and Kullo, Iftikhar J and Larson, Eric B and Rasmussen-Torvik, Laura J and Tromp, Gerard and Baumert, Jens and Cruickshanks, Karen J and Farrall, Martin and Hingorani, Aroon D and Hovingh, G K and Kleber, Marcus E and Klein, Barbara E and Klein, Ronald and Koenig, Wolfgang and Lange, Leslie A and Mӓrz, Winfried and North, Kari E and Charlotte Onland-Moret, N and Reiner, Alex P and Talmud, Philippa J and van der Schouw, Yvonne T and Wilson, James G and Kivimaki, Mika and Kumari, Meena and Moore, Jason H and Drenos, Fotios and Asselbergs, Folkert W and Keating, Brendan J and Ritchie, Marylyn D} } @article {7579, title = {Genetic loci associated with heart rate variability and their effects on cardiac disease risk.}, journal = {Nat Commun}, volume = {8}, year = {2017}, month = {2017 Jun 14}, pages = {15805}, abstract = {Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6\% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74 BACKGROUND: Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data. An additional 100 variants yielded suggestive evidence of association. METHODS AND RESULTS: Here, we augment the sample with 140 886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, ≈475 000), and the other in the subset of individuals of European descent (≈423 000). Twenty-one SNVs were genome-wide significant (P<5{\texttimes}10-8) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant. CONCLUSIONS: We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up. Aims: Sudden cardiac arrest (SCA) accounts for 10\% of adult mortality in Western populations. We aim to identify potential loci associated with SCA and to identify risk factors causally associated with SCA. Methods and results: We carried out a large genome-wide association study (GWAS) for SCA (n = 3939 cases, 25~989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization (MR) methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA. No variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (i) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (ii) height and BMI, and (iii) electrical instability traits (QT and atrial fibrillation), suggesting aetiologic roles for these traits in SCA risk. Conclusions: Our findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in high-risk populations and the general community.