%0 Journal Article %J J Am Soc Nephrol %D 2016 %T SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function. %A Li, Man %A Li, Yong %A Weeks, Olivia %A Mijatovic, Vladan %A Teumer, Alexander %A Huffman, Jennifer E %A Tromp, Gerard %A Fuchsberger, Christian %A Gorski, Mathias %A Lyytikäinen, Leo-Pekka %A Nutile, Teresa %A Sedaghat, Sanaz %A Sorice, Rossella %A Tin, Adrienne %A Yang, Qiong %A Ahluwalia, Tarunveer S %A Arking, Dan E %A Bihlmeyer, Nathan A %A Böger, Carsten A %A Carroll, Robert J %A Chasman, Daniel I %A Cornelis, Marilyn C %A Dehghan, Abbas %A Faul, Jessica D %A Feitosa, Mary F %A Gambaro, Giovanni %A Gasparini, Paolo %A Giulianini, Franco %A Heid, Iris %A Huang, Jinyan %A Imboden, Medea %A Jackson, Anne U %A Jeff, Janina %A Jhun, Min A %A Katz, Ronit %A Kifley, Annette %A Kilpeläinen, Tuomas O %A Kumar, Ashish %A Laakso, Markku %A Li-Gao, Ruifang %A Lohman, Kurt %A Lu, Yingchang %A Mägi, Reedik %A Malerba, Giovanni %A Mihailov, Evelin %A Mohlke, Karen L %A Mook-Kanamori, Dennis O %A Robino, Antonietta %A Ruderfer, Douglas %A Salvi, Erika %A Schick, Ursula M %A Schulz, Christina-Alexandra %A Smith, Albert V %A Smith, Jennifer A %A Traglia, Michela %A Yerges-Armstrong, Laura M %A Zhao, Wei %A Goodarzi, Mark O %A Kraja, Aldi T %A Liu, Chunyu %A Wessel, Jennifer %A Boerwinkle, Eric %A Borecki, Ingrid B %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Braga, Daniele %A Brandslund, Ivan %A Brody, Jennifer A %A Campbell, Archie %A Carey, David J %A Christensen, Cramer %A Coresh, Josef %A Crook, Errol %A Curhan, Gary C %A Cusi, Daniele %A de Boer, Ian H %A de Vries, Aiko P J %A Denny, Joshua C %A Devuyst, Olivier %A Dreisbach, Albert W %A Endlich, Karlhans %A Esko, Tõnu %A Franco, Oscar H %A Fulop, Tibor %A Gerhard, Glenn S %A Glümer, Charlotte %A Gottesman, Omri %A Grarup, Niels %A Gudnason, Vilmundur %A Harris, Tamara B %A Hayward, Caroline %A Hocking, Lynne %A Hofman, Albert %A Hu, Frank B %A Husemoen, Lise Lotte N %A Jackson, Rebecca D %A Jørgensen, Torben %A Jørgensen, Marit E %A Kähönen, Mika %A Kardia, Sharon L R %A König, Wolfgang %A Kooperberg, Charles %A Kriebel, Jennifer %A Launer, Lenore J %A Lauritzen, Torsten %A Lehtimäki, Terho %A Levy, Daniel %A Linksted, Pamela %A Linneberg, Allan %A Liu, Yongmei %A Loos, Ruth J F %A Lupo, Antonio %A Meisinger, Christine %A Melander, Olle %A Metspalu, Andres %A Mitchell, Paul %A Nauck, Matthias %A Nürnberg, Peter %A Orho-Melander, Marju %A Parsa, Afshin %A Pedersen, Oluf %A Peters, Annette %A Peters, Ulrike %A Polasek, Ozren %A Porteous, David %A Probst-Hensch, Nicole M %A Psaty, Bruce M %A Qi, Lu %A Raitakari, Olli T %A Reiner, Alex P %A Rettig, Rainer %A Ridker, Paul M %A Rivadeneira, Fernando %A Rossouw, Jacques E %A Schmidt, Frank %A Siscovick, David %A Soranzo, Nicole %A Strauch, Konstantin %A Toniolo, Daniela %A Turner, Stephen T %A Uitterlinden, André G %A Ulivi, Sheila %A Velayutham, Dinesh %A Völker, Uwe %A Völzke, Henry %A Waldenberger, Melanie %A Wang, Jie Jin %A Weir, David R %A Witte, Daniel %A Kuivaniemi, Helena %A Fox, Caroline S %A Franceschini, Nora %A Goessling, Wolfram %A Köttgen, Anna %A Chu, Audrey Y %X

Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium (nStage1: 111,666; nStage2: 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea (PPM1J, EDEM3, ACP1, SPEG, EYA4, CYP1A1, and ATXN2L; PStage1<3.7×10(-7)), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 (P=5.4×10(-8) by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2-knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation.

%B J Am Soc Nephrol %8 2016 Dec 05 %G eng %R 10.1681/ASN.2016020131 %0 Journal Article %J JAMA Oncol %D 2017 %T Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study. %A Haycock, Philip C %A Burgess, Stephen %A Nounu, Aayah %A Zheng, Jie %A Okoli, George N %A Bowden, Jack %A Wade, Kaitlin Hazel %A Timpson, Nicholas J %A Evans, David M %A Willeit, Peter %A Aviv, Abraham %A Gaunt, Tom R %A Hemani, Gibran %A Mangino, Massimo %A Ellis, Hayley Patricia %A Kurian, Kathreena M %A Pooley, Karen A %A Eeles, Rosalind A %A Lee, Jeffrey E %A Fang, Shenying %A Chen, Wei V %A Law, Matthew H %A Bowdler, Lisa M %A Iles, Mark M %A Yang, Qiong %A Worrall, Bradford B %A Markus, Hugh Stephen %A Hung, Rayjean J %A Amos, Chris I %A Spurdle, Amanda B %A Thompson, Deborah J %A O'Mara, Tracy A %A Wolpin, Brian %A Amundadottir, Laufey %A Stolzenberg-Solomon, Rachael %A Trichopoulou, Antonia %A Onland-Moret, N Charlotte %A Lund, Eiliv %A Duell, Eric J %A Canzian, Federico %A Severi, Gianluca %A Overvad, Kim %A Gunter, Marc J %A Tumino, Rosario %A Svenson, Ulrika %A van Rij, Andre %A Baas, Annette F %A Bown, Matthew J %A Samani, Nilesh J %A van t'Hof, Femke N G %A Tromp, Gerard %A Jones, Gregory T %A Kuivaniemi, Helena %A Elmore, James R %A Johansson, Mattias %A Mckay, James %A Scelo, Ghislaine %A Carreras-Torres, Robert %A Gaborieau, Valerie %A Brennan, Paul %A Bracci, Paige M %A Neale, Rachel E %A Olson, Sara H %A Gallinger, Steven %A Li, Donghui %A Petersen, Gloria M %A Risch, Harvey A %A Klein, Alison P %A Han, Jiali %A Abnet, Christian C %A Freedman, Neal D %A Taylor, Philip R %A Maris, John M %A Aben, Katja K %A Kiemeney, Lambertus A %A Vermeulen, Sita H %A Wiencke, John K %A Walsh, Kyle M %A Wrensch, Margaret %A Rice, Terri %A Turnbull, Clare %A Litchfield, Kevin %A Paternoster, Lavinia %A Standl, Marie %A Abecasis, Goncalo R %A SanGiovanni, John Paul %A Li, Yong %A Mijatovic, Vladan %A Sapkota, Yadav %A Low, Siew-Kee %A Zondervan, Krina T %A Montgomery, Grant W %A Nyholt, Dale R %A van Heel, David A %A Hunt, Karen %A Arking, Dan E %A Ashar, Foram N %A Sotoodehnia, Nona %A Woo, Daniel %A Rosand, Jonathan %A Comeau, Mary E %A Brown, W Mark %A Silverman, Edwin K %A Hokanson, John E %A Cho, Michael H %A Hui, Jennie %A Ferreira, Manuel A %A Thompson, Philip J %A Morrison, Alanna C %A Felix, Janine F %A Smith, Nicholas L %A Christiano, Angela M %A Petukhova, Lynn %A Betz, Regina C %A Fan, Xing %A Zhang, Xuejun %A Zhu, Caihong %A Langefeld, Carl D %A Thompson, Susan D %A Wang, Feijie %A Lin, Xu %A Schwartz, David A %A Fingerlin, Tasha %A Rotter, Jerome I %A Cotch, Mary Frances %A Jensen, Richard A %A Munz, Matthias %A Dommisch, Henrik %A Schaefer, Arne S %A Han, Fang %A Ollila, Hanna M %A Hillary, Ryan P %A Albagha, Omar %A Ralston, Stuart H %A Zeng, Chenjie %A Zheng, Wei %A Shu, Xiao-Ou %A Reis, Andre %A Uebe, Steffen %A Hüffmeier, Ulrike %A Kawamura, Yoshiya %A Otowa, Takeshi %A Sasaki, Tsukasa %A Hibberd, Martin Lloyd %A Davila, Sonia %A Xie, Gang %A Siminovitch, Katherine %A Bei, Jin-Xin %A Zeng, Yi-Xin %A Försti, Asta %A Chen, Bowang %A Landi, Stefano %A Franke, Andre %A Fischer, Annegret %A Ellinghaus, David %A Flores, Carlos %A Noth, Imre %A Ma, Shwu-Fan %A Foo, Jia Nee %A Liu, Jianjun %A Kim, Jong-Won %A Cox, David G %A Delattre, Olivier %A Mirabeau, Olivier %A Skibola, Christine F %A Tang, Clara S %A Garcia-Barcelo, Merce %A Chang, Kai-Ping %A Su, Wen-Hui %A Chang, Yu-Sun %A Martin, Nicholas G %A Gordon, Scott %A Wade, Tracey D %A Lee, Chaeyoung %A Kubo, Michiaki %A Cha, Pei-Chieng %A Nakamura, Yusuke %A Levy, Daniel %A Kimura, Masayuki %A Hwang, Shih-Jen %A Hunt, Steven %A Spector, Tim %A Soranzo, Nicole %A Manichaikul, Ani W %A Barr, R Graham %A Kahali, Bratati %A Speliotes, Elizabeth %A Yerges-Armstrong, Laura M %A Cheng, Ching-Yu %A Jonas, Jost B %A Wong, Tien Yin %A Fogh, Isabella %A Lin, Kuang %A Powell, John F %A Rice, Kenneth %A Relton, Caroline L %A Martin, Richard M %A Davey Smith, George %K Adult %K Aged %K Aged, 80 and over %K Cardiovascular Diseases %K Female %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Germ-Line Mutation %K Humans %K Male %K Mendelian Randomization Analysis %K Middle Aged %K Neoplasms %K Polymorphism, Single Nucleotide %K Risk Assessment %K Telomere %K Telomere Homeostasis %X

Importance: The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.

Objective: To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.

Data Sources: Genomewide association studies (GWAS) published up to January 15, 2015.

Study Selection: GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.

Data Extraction and Synthesis: Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.

Main Outcomes and Measures: Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.

Results: Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).

Conclusions and Relevance: It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

%B JAMA Oncol %V 3 %P 636-651 %8 2017 May 01 %G eng %N 5 %R 10.1001/jamaoncol.2016.5945 %0 Journal Article %J BioData Min %D 2017 %T Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals. %A Holzinger, Emily R %A Verma, Shefali S %A Moore, Carrie B %A Hall, Molly %A De, Rishika %A Gilbert-Diamond, Diane %A Lanktree, Matthew B %A Pankratz, Nathan %A Amuzu, Antoinette %A Burt, Amber %A Dale, Caroline %A Dudek, Scott %A Furlong, Clement E %A Gaunt, Tom R %A Kim, Daniel Seung %A Riess, Helene %A Sivapalaratnam, Suthesh %A Tragante, Vinicius %A van Iperen, Erik P A %A Brautbar, Ariel %A Carrell, David S %A Crosslin, David R %A Jarvik, Gail P %A Kuivaniemi, Helena %A Kullo, Iftikhar J %A Larson, Eric B %A Rasmussen-Torvik, Laura J %A Tromp, Gerard %A Baumert, Jens %A Cruickshanks, Karen J %A Farrall, Martin %A Hingorani, Aroon D %A Hovingh, G K %A Kleber, Marcus E %A Klein, Barbara E %A Klein, Ronald %A Koenig, Wolfgang %A Lange, Leslie A %A Mӓrz, Winfried %A North, Kari E %A Charlotte Onland-Moret, N %A Reiner, Alex P %A Talmud, Philippa J %A van der Schouw, Yvonne T %A Wilson, James G %A Kivimaki, Mika %A Kumari, Meena %A Moore, Jason H %A Drenos, Fotios %A Asselbergs, Folkert W %A Keating, Brendan J %A Ritchie, Marylyn D %X

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.

%B BioData Min %V 10 %P 25 %8 2017 %G eng %R 10.1186/s13040-017-0145-5