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Rossin, Elizabeth

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Rossin

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Elizabeth

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Rossin, Elizabeth
Author's Publications: search.filters.isAuthorOfPublication.24c03274-87cb-4949-b6ab-7aade9ef657e

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    Genome-wide meta-analysis identifies new susceptibility loci for migraine
    (2014) Anttila, Verneri; Winsvold, Bendik S.; Gormley, Padhraig; Kurth, Tobias; Bettella, Francesco; McMahon, George; Kallela, Mikko; Malik, Rainer; de Vries, Boukje; Terwindt, Gisela; Medland, Sarah E.; Todt, Unda; McArdle, Wendy L.; Quaye, Lydia; Koiranen, Markku; Ikram, M. Arfan; Lehtimäki, Terho; Stam, Anine H.; Ligthart, Lannie; Wedenoja, Juho; Dunham, Ian; Neale, Benjamin; Palta, Priit; Hamalainen, Eija; Schürks, Markus; Rose, Lynda M; Buring, Julie; Ridker, Paul; Steinberg, Stacy; Stefansson, Hreinn; Jakobsson, Finnbogi; Lawlor, Debbie A.; Evans, David M.; Ring, Susan M.; Färkkilä, Markus; Artto, Ville; Kaunisto, Mari A; Freilinger, Tobias; Schoenen, Jean; Frants, Rune R.; Pelzer, Nadine; Weller, Claudia M.; Zielman, Ronald; Heath, Andrew C.; Madden, Pamela A.F.; Montgomery, Grant W.; Martin, Nicholas G.; Borck, Guntram; Göbel, Hartmut; Heinze, Axel; Heinze-Kuhn, Katja; Williams, Frances M.K.; Hartikainen, Anna-Liisa; Pouta, Anneli; van den Ende, Joyce; Uitterlinden, Andre G.; Hofman, Albert; Amin, Najaf; Hottenga, Jouke-Jan; Vink, Jacqueline M.; Heikkilä, Kauko; Alexander, Michael; Muller-Myhsok, Bertram; Schreiber, Stefan; Meitinger, Thomas; Wichmann, Heinz Erich; Aromaa, Arpo; Eriksson, Johan G.; Traynor, Bryan; Trabzuni, Daniah; Rossin, Elizabeth; Lage, Kasper; Jacobs, Suzanne B.R.; Gibbs, J. Raphael; Birney, Ewan; Kaprio, Jaakko; Penninx, Brenda W.; Boomsma, Dorret I.; van Duijn, Cornelia; Raitakari, Olli; Jarvelin, Marjo-Riitta; Zwart, John-Anker; Cherkas, Lynn; Strachan, David P.; Kubisch, Christian; Ferrari, Michel D.; van den Maagdenberg, Arn M.J.M.; Dichgans, Martin; Wessman, Maija; Smith, George Davey; Stefansson, Kari; Daly, Mark; Nyholt, Dale R.; Chasman, Daniel; Palotie, Aarno
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    Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization
    (2014) Arking, Dan E.; Pulit, Sara L.; Crotti, Lia; van der Harst, Pim; Munroe, Patricia B.; Koopmann, Tamara T.; Sotoodehnia, Nona; Rossin, Elizabeth; Morley, Michael; Wang, Xinchen; Johnson, Andrew D.; Lundby, Alicia; Gudbjartsson, Daníel F.; Noseworthy, Peter A.; Eijgelsheim, Mark; Bradford, Yuki; Tarasov, Kirill V.; Dörr, Marcus; Müller-Nurasyid, Martina; Lahtinen, Annukka M.; Nolte, Ilja M.; Smith, Albert Vernon; Bis, Joshua C.; Isaacs, Aaron; Newhouse, Stephen J.; Evans, Daniel S.; Post, Wendy S.; Waggott, Daryl; Lyytikäinen, Leo-Pekka; Hicks, Andrew A.; Eisele, Lewin; Ellinghaus, David; Hayward, Caroline; Navarro, Pau; Ulivi, Sheila; Tanaka, Toshiko; Tester, David J.; Chatel, Stéphanie; Gustafsson, Stefan; Kumari, Meena; Morris, Richard W.; Naluai, Åsa T.; Padmanabhan, Sandosh; Kluttig, Alexander; Strohmer, Bernhard; Panayiotou, Andrie G.; Torres, Maria; Knoflach, Michael; Hubacek, Jaroslav A.; Slowikowski, Kamil; Raychaudhuri, Soumya; Kumar, Runjun D.; Harris, Tamara B.; Launer, Lenore J.; Shuldiner, Alan R.; Alonso, Alvaro; Bader, Joel S.; Ehret, Georg; Huang, Hailiang; Kao, W.H. Linda; Strait, James B.; Macfarlane, Peter W.; Brown, Morris; Caulfield, Mark J.; Samani, Nilesh J.; Kronenberg, Florian; Willeit, Johann; Smith, J. Gustav; Greiser, Karin H.; zu Schwabedissen, Henriette Meyer; Werdan, Karl; Carella, Massimo; Zelante, Leopoldo; Heckbert, Susan R.; Psaty, Bruce M.; Rotter, Jerome I.; Kolcic, Ivana; Polašek, Ozren; Wright, Alan F.; Griffin, Maura; Daly, Mark; Arnar, David O.; Hólm, Hilma; Thorsteinsdottir, Unnur; Denny, Joshua C.; Roden, Dan M.; Zuvich, Rebecca L.; Emilsson, Valur; Plump, Andrew S.; Larson, Martin G.; O'Donnell, Christopher; Yin, Xiaoyan; Bobbo, Marco; D'Adamo, Adamo P.; Iorio, Annamaria; Sinagra, Gianfranco; Carracedo, Angel; Cummings, Steven R.; Nalls, Michael A.; Jula, Antti; Kontula, Kimmo K.; Marjamaa, Annukka; Oikarinen, Lasse; Perola, Markus; Porthan, Kimmo; Erbel, Raimund; Hoffmann, Per; Jöckel, Karl-Heinz; Kälsch, Hagen; Nöthen, Markus M.; consortium, HRGEN; den Hoed, Marcel; Loos, Ruth J.F.; Thelle, Dag S.; Gieger, Christian; Meitinger, Thomas; Perz, Siegfried; Peters, Annette; Prucha, Hanna; Sinner, Moritz F.; Waldenberger, Melanie; de Boer, Rudolf A.; Franke, Lude; van der Vleuten, Pieter A.; Beckmann, Britt Maria; Martens, Eimo; Bardai, Abdennasser; Hofman, Nynke; Wilde, Arthur A.M.; Behr, Elijah R.; Dalageorgou, Chrysoula; Giudicessi, John R.; Medeiros-Domingo, Argelia; Barc, Julien; Kyndt, Florence; Probst, Vincent; Ghidoni, Alice; Insolia, Roberto; Hamilton, Robert M.; Scherer, Stephen W.; Brandimarto, Jeffrey; Margulies, Kenneth; Moravec, Christine E.; Fabiola Del, Greco M.; Fuchsberger, Christian; O'Connell, Jeffrey R.; Lee, Wai K.; Watt, Graham C.M.; Campbell, Harry; Wild, Sarah H.; El Mokhtari, Nour E.; Frey, Norbert; Asselbergs, Folkert W.; Leach, Irene Mateo; Navis, Gerjan; van den Berg, Maarten P.; van Veldhuisen, Dirk J.; Kellis, Manolis; Krijthe, Bouwe P.; Franco, Oscar H.; Hofman, Albert; Kors, Jan A.; Uitterlinden, André G.; Witteman, Jacqueline C.M.; Kedenko, Lyudmyla; Lamina, Claudia; Oostra, Ben A.; Abecasis, Gonçalo R.; Lakatta, Edward G.; Mulas, Antonella; Orrú, Marco; Schlessinger, David; Uda, Manuela; Markus, Marcello R.P.; Völker, Uwe; Snieder, Harold; Spector, Timothy D.; Ärnlöv, Johan; Lind, Lars; Sundström, Johan; Syvänen, Ann-Christine; Kivimaki, Mika; Kähönen, Mika; Mononen, Nina; Raitakari, Olli T.; Viikari, Jorma S.; Adamkova, Vera; Kiechl, Stefan; Brion, Maria; Nicolaides, Andrew N.; Paulweber, Bernhard; Haerting, Johannes; Dominiczak, Anna F.; Nyberg, Fredrik; Whincup, Peter H.; Hingorani, Aroon; Schott, Jean-Jacques; Bezzina, Connie R.; Ingelsson, Erik; Ferrucci, Luigi; Gasparini, Paolo; Wilson, James F.; Rudan, Igor; Franke, Andre; Mühleisen, Thomas W.; Pramstaller, Peter P.; Lehtimäki, Terho J.; Paterson, Andrew D.; Parsa, Afshin; Liu, Yongmei; van Duijn, Cornelia; Siscovick, David S.; Gudnason, Vilmundur; Jamshidi, Yalda; Salomaa, Veikko; Felix, Stephan B.; Sanna, Serena; Ritchie, Marylyn D.; Stricker, Bruno H.; Stefansson, Kari; Boyer, Laurie A.; Cappola, Thomas P.; Olsen, Jesper V.; Lage, Kasper; Schwartz, Peter J.; Kääb, Stefan; Chakravarti, Aravinda; Ackerman, Michael J.; Pfeufer, Arne; de Bakker, Paul I.W.; Newton-Cheh, Christopher
    The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.
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    Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics
    (2014) Lundby, Alicia; Rossin, Elizabeth; Steffensen, Annette B.; Rav Acha, Moshe; Newton-Cheh, Christopher; Pfeufer, Arne; Lynch, Stacey N.; Olesen, Søren-Peter; Brunak, Søren; Ellinor, Patrick; Jukema, J.Wouter; Trompet, Stella; Ford, Ian; Macfarlane, Peter W.; Krijthe, Bouwe P.; Hofman, Albert; Uitterlinden, Andre G.; Stricker, Bruno H.; Nathoe, Hendrik M.; Spiering, Wilko; Daly, Mark; Asselbergs, Folkert W.; van der Harst, Pim; Milan, David; de Bakker, Paul I.W.; Lage, Kasper; Olsen, Jesper V.
    Genome-wide association studies (GWAS) have identified thousands of loci associated wtih complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes involved in the Mendelian disorder long QT syndrome (LQTS). We integrated the LQTS network with GWAS loci from the corresponding common complex trait, QT interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LQTS protein network to filter weak GWAS signals by identifying single nucleotide polymorphisms (SNPs) in proximity to genes in the network supported by strong proteomic evidence. Three SNPs passing this filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy to propose candidates in GWAS loci for functional studies and to systematically filter subtle association signals using tissue-specific quantitative interaction proteomics.
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    Patterns and rates of exonic de novo mutations in autism spectrum disorders
    (2013) Neale, Benjamin; Kou, Yan; Liu, Li; Ma'ayan, Avi; Samocha, Kaitlin E.; Sabo, Aniko; Lin, Chiao-Feng; Stevens, Christine; Wang, Li-San; Makarov, Vladimir; Polak, Paz; Yoon, Seungtai; Maguire, Jared; Crawford, Emily L.; Campbell, Nicholas G.; Geller, Evan T.; Valladares, Otto; Shafer, Chad; Liu, Han; Zhao, Tuo; Cai, Guiqing; Lihm, Jayon; Dannenfelser, Ruth; Jabado, Omar; Peralta, Zuleyma; Nagaswamy, Uma; Muzny, Donna; Reid, Jeffrey G.; Newsham, Irene; Wu, Yuanqing; Lewis, Lora; Han, Yi; Voight, Benjamin F.; Lim, Elaine; Rossin, Elizabeth; Kirby, Andrew; Flannick, Jason; Fromer, Menachem; Shakir, Khalid; Fennell, Tim; Garimella, Kiran; Banks, Eric; Poplin, Ryan; Gabriel, Stacey; DePristo, Mark; Wimbish, Jack R.; Boone, Braden E.; Levy, Shawn E.; Betancur, Catalina; Sunyaev, Shamil; Boerwinkle, Eric; Buxbaum, Joseph D.; Cook, Edwin H.; Devlin, Bernie; Gibbs, Richard A.; Roeder, Kathryn; Schellenberg, Gerard D.; Sutcliffe, James S.; Daly, Mark
    Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified1,2. To identify further genetic risk factors, we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n= 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant and the overall rate of mutation is only modestly higher than the expected rate. In contrast, there is significantly enriched connectivity among the proteins encoded by genes harboring de novo missense or nonsense mutations, and excess connectivity to prior ASD genes of major effect, suggesting a subset of observed events are relevant to ASD risk. The small increase in rate of de novo events, when taken together with the connections among the proteins themselves and to ASD, are consistent with an important but limited role for de novo point mutations, similar to that documented for de novo copy number variants. Genetic models incorporating these data suggest that the majority of observed de novo events are unconnected to ASD, those that do confer risk are distributed across many genes and are incompletely penetrant (i.e., not necessarily causal). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5 to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case-control study provide strong evidence in favor of CHD8 and KATNAL2 as genuine autism risk factors.
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    Human Genetics in Rheumatoid Arthritis Guides a High-Throughput Drug Screen of the CD40 Signaling Pathway
    (Public Library of Science, 2013) Li, Gang; Diogo, Dorothee; Wu, Di; Spoonamore, Jim; Dancik, Vlado; Franke, Lude; Kurreeman, Fina; Rossin, Elizabeth; Duclos, Grant; Hartland, Cathy; Zhou, Xuezhong; Li, Kejie; Liu, Jun; De Jager, Philip; Siminovitch, Katherine A.; Zhernakova, Alexandra; Raychaudhuri, Soumya; Bowes, John; Eyre, Steve; Padyukov, Leonid; Gregersen, Peter K.; Worthington, Jane; Gupta, Namrata; Clemons, Paul A.; Stahl, Eli; Tolliday, Nicola; Plenge, Robert M.
    Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association \((rs4810485, P = 1.4×10^{−9})\). Second, we demonstrate that subjects homozygous for the RA risk allele have \(\sim33\%\) more CD40 on the surface of primary human \(CD19^+\) B lymphocytes than subjects homozygous for the non-risk allele \((P = 10^{−9})\), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the \(NF-\kappa B\) transcription factor. Finally, we develop a high-throughput \(NF-\kappa B\) luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA–approved drugs. After a series of counter-screens and testing in primary human \(CD19^+\) B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated \(NF-\kappa B\) signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA.
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    Large-Scale Association Analysis Provides Insights into the Genetic Architecture and Pathophysiology of Type 2 Diabetes
    (Nature Publishing Group, 2012) Morris, Andrew P; Voight, Benjamin F; Teslovich, Tanya M; Ferreira, Teresa; Segré, Ayellet V; Steinthorsdottir, Valgerdur; Strawbridge, Rona J; Khan, Hassan; Grallert, Harald; Mahajan, Anubha; Prokopenko, Inga; Kang, Hyun Min; Dina, Christian; Esko, Tonu; Fraser, Ross M; Kanoni, Stavroula; Kumar, Ashish; Lagou, Vasiliki; Langenberg, Claudia; Luan, Jian’an; Lindgren, Cecilia M; Müller-Nurasyid, Martina; Pechlivanis, Sonali; Rayner, N William; Scott, Laura J; Wiltshire, Steven; Yengo, Loic; Kinnunen, Leena; Rossin, Elizabeth; Raychaudhuri, Soumya; Johnson, Andrew D; Dimas, Antigone S; Loos, Ruth J F; Vedantam, Sailaja; Chen, Han; Florez, Jose; Fox, Caroline; Liu, Ching-Ti; Rybin, Denis; Couper, David J; Kao, Wen Hong L; Li, Man; Cornelis, Marilyn; Kraft, Peter; Sun, Qi; Van Dam, Rob; Stringham, Heather M; Chines, Peter S; Fischer, Krista; Fontanillas, Pierre; Holmen, Oddgeir L; Hunt, Sarah E; Jackson, Anne U; Kong, Augustine; Lawrence, Robert; Meyer, Julia; Perry, John R B; Platou, Carl G P; Potter, Simon; Rehnberg, Emil; Robertson, Neil; Sivapalaratnam, Suthesh; Stančáková, Alena; Stirrups, Kathleen; Thorleifsson, Gudmar; Tikkanen, Emmi; Wood, Andrew R; Almgren, Peter; Atalay, Mustafa; Benediktsson, Rafn; Bonnycastle, Lori L; Burtt, Noël; Carey, Jason; Charpentier, Guillaume; Crenshaw, Andrew T; Doney, Alex S F; Dorkhan, Mozhgan; Edkins, Sarah; Emilsson, Valur; Eury, Elodie; Forsen, Tom; Gertow, Karl; Gigante, Bruna; Grant, George B; Groves, Christopher J; Guiducci, Candace; Herder, Christian; Hreidarsson, Astradur B; Hui, Jennie; James, Alan; Jonsson, Anna; Rathmann, Wolfgang; Klopp, Norman; Kravic, Jasmina; Krjutškov, Kaarel; Langford, Cordelia; Leander, Karin; Lindholm, Eero; Lobbens, Stéphane; Männistö, Satu; Mirza, Ghazala; Mühleisen, Thomas W; Musk, Bill; Parkin, Melissa Ann; Rallidis, Loukianos; Saramies, Jouko; Sennblad, Bengt; Shah, Sonia; Sigurðsson, Gunnar; Silveira, Angela; Steinbach, Gerald; Thorand, Barbara; Trakalo, Joseph; Veglia, Fabrizio; Wennauer, Roman; Winckler, Wendy; Zabaneh, Delilah; Campbell, Harry; van Duijn, Cornelia; Uitterlinden, Andre G; Hofman, Albert; Sijbrands, Eric; Abecasis, Goncalo R; Owen, Katharine R; Zeggini, Eleftheria; Trip, Mieke D; Forouhi, Nita G; Syvänen, Ann-Christine; Eriksson, Johan G; Peltonen, Leena; Nöthen, Markus M; Balkau, Beverley; Palmer, Colin N A; Lyssenko, Valeriya; Tuomi, Tiinamaija; Isomaa, Bo; Hunter, David; Qi, Lu; Shuldiner, Alan R; Roden, Michael; Barroso, Ines; Wilsgaard, Tom; Beilby, John; Hovingh, Kees; Price, Jackie F; Wilson, James F; Rauramaa, Rainer; Lakka, Timo A; Lind, Lars; Dedoussis, George; Njølstad, Inger; Pedersen, Nancy L; Khaw, Kay-Tee; Wareham, Nicholas J; Keinanen-Kiukaanniemi, Sirkka M; Saaristo, Timo E; Korpi-Hyövälti, Eeva; Saltevo, Juha; Laakso, Markku; Kuusisto, Johanna; Metspalu, Andres; Collins, Francis S; Mohlke, Karen L; Bergman, Richard N; Tuomilehto, Jaakko; Boehm, Bernhard O; Gieger, Christian; Hveem, Kristian; Cauchi, Stephane; Froguel, Philippe; Baldassarre, Damiano; Tremoli, Elena; Humphries, Steve E; Saleheen, Danish; Danesh, John; Ingelsson, Erik; Ripatti, Samuli; Salomaa, Veikko; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Peters, Annette; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Morris, Andrew D; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; Boerwinkle, Eric; Melander, Olle; Kathiresan, Sekar; Nilsson, Peter M; Deloukas, Panos; Thorsteinsdottir, Unnur; Groop, Leif C; Stefansson, Kari; Hu, Frank; Pankow, James S; Dupuis, Josée; Meigs, James; Altshuler, David; Boehnke, Michael; McCarthy, Mark I
    To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.
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    The Proteomic Landscape of Human Disease: Construction and Evaluation of Networks Associated to Complex Traits
    (2012-11-15) Rossin, Elizabeth; Daly, Mark Joseph; Hirschhorn, Joel Naom; Regev, Aviv; Stranger, Barbara; Kraft, Peter
    Genetic mapping of complex traits has been successful over the last decade, with over 2,000 regions in the genome associated to disease. Yet, the translation of these findings into a better understanding of disease biology is not straightforward. The true promise of human genetics lies in its ability to explain disease etiology, and the need to translate genetic findings into a better understanding of biological processes is of great relevance to the community. We hypothesized that integrating genetics and protein- protein interaction (PPI) networks would shed light on the relationship among genes associated to complex traits, ultimately to help guide understanding of disease biology. First, we discuss the design, testing and implementation of a novel in silico approach (“DAPPLE”) to rigorously ask whether loci associated to complex traits code for proteins that form significantly connected networks. Using a high-confidence set of publically available physical interactions, we show that loci associated to autoimmune diseases code for proteins that assemble into significantly connected networks and that these networks are predictive of new genetic variants associated to the phenotypes in question. Next, we study variation in the electrocardiographic QT-interval, a heritable phenotype that when prolonged is a risk factor for cardiac arrhythmia and sudden cardiac death. We show that a large proportion of QT-associated loci encode proteins that are members of complexes identified by immunoprecipitations in mouse cardiac tissue of proteins known to be causal of Mendelian long-QT syndrome. For several of the identified proteins, we show they affect cardiac ion channel currents in model organisms. Using replication genotyping in 17,500 individuals, we use the complexes to identify genome-wide significant loci that would have otherwise been missed. Finally, we consider whether PPIs can be used to interpret rare and de novo variation discovered through recent technological advances in exome-sequencing. We report a highly connected network underlying de novo variants discovered in an autism trio exome-sequencing effort, and we design, test and implement a novel statistical framework (“DAPPLE/SEQ”) to analyze rare inherited variants in the context of PPIs in a way that significantly boosts power to detect association.