Person:
Kathiresan, Sekar

Profile Picture

Email Address

AA Acceptance Date

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Kathiresan

First Name

Sekar

Name

Kathiresan, Sekar
Author's Publications: search.filters.isAuthorOfPublication.64d3cc58-2b20-4af6-abb1-9fc523996495

Search Results

Now showing 1 - 7 of 7
  • Thumbnail Image
    Publication
    Best Practices and Joint Calling of the HumanExome BeadChip: The CHARGE Consortium
    (Public Library of Science, 2013) Grove, Megan L.; Yu, Bing; Cochran, Barbara J.; Haritunians, Talin; Bis, Joshua C.; Taylor, Kent D.; Hansen, Mark; Borecki, Ingrid B.; Cupples, L. Adrienne; Fornage, Myriam; Gudnason, Vilmundur; Harris, Tamara B.; Kathiresan, Sekar; Kraaij, Robert; Launer, Lenore J.; Levy, Daniel; Liu, Yongmei; Mosley, Thomas; Peloso, Gina M; Psaty, Bruce M.; Rich, Stephen S.; Rivadeneira, Fernando; Siscovick, David S.; Smith, Albert V.; Uitterlinden, Andre; van Duijn, Cornelia M.; Wilson, James G.; O’Donnell, Christopher J.; Rotter, Jerome I.; Boerwinkle, Eric
    Genotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77% were concordant, 0.14% had missing data, and 0.09% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip.
  • Thumbnail Image
    Publication
    Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits
    (Public Library of Science, 2013) Randall, Joshua C.; Winkler, Thomas W.; Kutalik, Zoltán; Berndt, Sonja I.; Jackson, Anne U.; Monda, Keri L.; Kilpeläinen, Tuomas O.; Esko, Tõnu; Mägi, Reedik; Li, Shengxu; Workalemahu, Tsegaselassie; Feitosa, Mary F.; Croteau-Chonka, Damien C.; Day, Felix R.; Fall, Tove; Ferreira, Teresa; Gustafsson, Stefan; Locke, Adam E.; Mathieson, Iain; Scherag, Andre; Vedantam, Sailaja; Wood, Andrew R.; Liang, Liming; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Dermitzakis, Emmanouil T.; Dimas, Antigone S.; Karpe, Fredrik; Min, Josine L.; Nicholson, George; Clegg, Deborah J.; Person, Thomas; Krohn, Jon P.; Bauer, Sabrina; Buechler, Christa; Eisinger, Kristina; Bonnefond, Amélie; Froguel, Philippe; Hottenga, Jouke-Jan; Prokopenko, Inga; Waite, Lindsay L.; Harris, Tamara B.; Smith, Albert Vernon; Shuldiner, Alan R.; McArdle, Wendy L.; Caulfield, Mark J.; Munroe, Patricia B.; Grönberg, Henrik; Chen, Yii-Der Ida; Li, Guo; Beckmann, Jacques S.; Johnson, Toby; Thorsteinsdottir, Unnur; Teder-Laving, Maris; Khaw, Kay-Tee; Wareham, Nicholas J.; Zhao, Jing Hua; Amin, Najaf; Oostra, Ben A.; Kraja, Aldi T.; Province, Michael A.; Cupples, L. Adrienne; Heard-Costa, Nancy L.; Kaprio, Jaakko; Ripatti, Samuli; Surakka, Ida; Collins, Francis S.; Saramies, Jouko; Tuomilehto, Jaakko; Jula, Antti; Salomaa, Veikko; Erdmann, Jeanette; Hengstenberg, Christian; Loley, Christina; Schunkert, Heribert; Lamina, Claudia; Wichmann, H. Erich; Albrecht, Eva; Gieger, Christian; Hicks, Andrew A.; Johansson, Åsa; Pramstaller, Peter P.; Kathiresan, Sekar; Speliotes, Elizabeth K.; Penninx, Brenda; Hartikainen, Anna-Liisa; Jarvelin, Marjo-Riitta; Gyllensten, Ulf; Boomsma, Dorret I.; Campbell, Harry; Wilson, James F.; Chanock, Stephen J.; Farrall, Martin; Goel, Anuj; Medina-Gomez, Carolina; Rivadeneira, Fernando; Estrada, Karol; Uitterlinden, André G.; Hofman, Albert; Zillikens, M. Carola; den Heijer, Martin; Kiemeney, Lambertus A.; Maschio, Andrea; Hall, Per; Tyrer, Jonathan; Teumer, Alexander; Völzke, Henry; Kovacs, Peter; Tönjes, Anke; Mangino, Massimo; Spector, Tim D.; Hayward, Caroline; Rudan, Igor; Hall, Alistair S.; Samani, Nilesh J.; Attwood, Antony Paul; Sambrook, Jennifer G.; Hung, Joseph; Palmer, Lyle J.; Lokki, Marja-Liisa; Sinisalo, Juha; Boucher, Gabrielle; Huikuri, Heikki; Lorentzon, Mattias; Ohlsson, Claes; Eklund, Niina; Eriksson, Johan G.; Barlassina, Cristina; Rivolta, Carlo; Nolte, Ilja M.; Snieder, Harold; Van der Klauw, Melanie M.; Van Vliet-Ostaptchouk, Jana V.; Gejman, Pablo V.; Shi, Jianxin; Jacobs, Kevin B.; Wang, Zhaoming; Bakker, Stephan J. L.; Mateo Leach, Irene; Navis, Gerjan; van der Harst, Pim; Martin, Nicholas G.; Medland, Sarah E.; Montgomery, Grant W.; Yang, Jian; Chasman, Daniel; Ridker, Paul; Rose, Lynda M.; Lehtimäki, Terho; Raitakari, Olli; Absher, Devin; Iribarren, Carlos; Basart, Hanneke; Hovingh, Kees G.; Hyppönen, Elina; Power, Chris; Anderson, Denise; Beilby, John P.; Hui, Jennie; Jolley, Jennifer; Sager, Hendrik; Bornstein, Stefan R.; Schwarz, Peter E. H.; Kristiansson, Kati; Perola, Markus; Lindström, Jaana; Swift, Amy J.; Uusitupa, Matti; Atalay, Mustafa; Lakka, Timo A.; Rauramaa, Rainer; Bolton, Jennifer L.; Fowkes, Gerry; Fraser, Ross M.; Price, Jackie F.; Fischer, Krista; KrjutÅ¡kov, Kaarel; Metspalu, Andres; Mihailov, Evelin; Langenberg, Claudia; Luan, Jian'an; Ong, Ken K.; Chines, Peter S.; Keinanen-Kiukaanniemi, Sirkka M.; Saaristo, Timo E.; Edkins, Sarah; Franks, Paul W.; Hallmans, Göran; Shungin, Dmitry; Morris, Andrew David; Palmer, Colin N. A.; Erbel, Raimund; Moebus, Susanne; Nöthen, Markus M.; Pechlivanis, Sonali; Hveem, Kristian; Narisu, Narisu; Hamsten, Anders; Humphries, Steve E.; Strawbridge, Rona J.; Tremoli, Elena; Grallert, Harald; Thorand, Barbara; Illig, Thomas; Koenig, Wolfgang; Müller-Nurasyid, Martina; Peters, Annette; Boehm, Bernhard O.; Kleber, Marcus E.; März, Winfried; Winkelmann, Bernhard R.; Kuusisto, Johanna; Laakso, Markku; Arveiler, Dominique; Cesana, Giancarlo; Kuulasmaa, Kari; Virtamo, Jarmo; Yarnell, John W. G.; Kuh, Diana; Wong, Andrew; Lind, Lars; de Faire, Ulf; Gigante, Bruna; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Dedoussis, George; Dimitriou, Maria; Kolovou, Genovefa; Kanoni, Stavroula; Stirrups, Kathleen; Bonnycastle, Lori L.; Njølstad, Inger; Wilsgaard, Tom; Ganna, Andrea; Rehnberg, Emil; Hingorani, Aroon; Kivimaki, Mika; Kumari, Meena; Assimes, Themistocles L.; Barroso, Inês; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; Fox, Caroline S.; Frayling, Timothy; Groop, Leif C.; Haritunians, Talin; Hunter, David; Ingelsson, Erik; Kaplan, Robert; Mohlke, Karen L.; O'Connell, Jeffrey R.; Schlessinger, David; Strachan, David P.; Stefansson, Kari; van Duijn, Cornelia M.; Abecasis, Gonçalo R.; McCarthy, Mark I.; Hirschhorn, Joel; Qi, Lu; Loos, Ruth J. F.; Lindgren, Cecilia M.; North, Kari E.; Heid, Iris M.
    Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
  • Thumbnail Image
    Publication
    From Noncoding Variant to Phenotype via SORT1 at the 1p13 Cholesterol Locus
    (Springer Nature, 2010) Musunuru, Kiran; Strong, Alanna; Frank-Kamenetsky, Maria; Lee, Noemi E.; Ahfeldt, Tim; Sachs, Katherine V.; Li, Xiaoyu; Li, Hui; Kuperwasser, Nicolas; Ruda, Vera M.; Pirruccello, James; Muchmore, Brian; Prokunina-Olsson, Ludmila; Hall, Jennifer L.; Schadt, Eric E.; Morales, Carlos R.; Lund-Katz, Sissel; Phillips, Michael C.; Wong, Jamie; Cantley, William; Racie, Timothy; Ejebe, Kenechi G.; Orho-Melander, Marju; Melander, Olle; Koteliansky, Victor; Fitzgerald, Kevin; Krauss, Ronald M.; Cowan, Chad; Kathiresan, Sekar; Rader, Daniel J.
    Recent genome-wide association studies (GWASs) have identified a locus on chromosome 1p13 strongly associated with both plasma low-density lipoprotein cholesterol (LDL-C) and myocardial infarction (MI) in humans. Here we show through a series of studies in human cohorts and human-derived hepatocytes that a common noncoding polymorphism at the 1p13 locus, rs12740374, creates a C/EBP (CCAAT/enhancer binding protein) transcription factor binding site and alters the hepatic expression of the SORT1 gene. With small interfering RNA (siRNA) knockdown and viral overexpression in mouse liver, we demonstrate that Sort1 alters plasma LDL-C and very low-density lipoprotein (VLDL) particle levels by modulating hepatic VLDL secretion. Thus, we provide functional evidence for a novel regulatory pathway for lipoprotein metabolism and suggest that modulation of this pathway may alter risk for MI in humans. We also demonstrate that common noncoding DNA variants identified by GWASs can directly contribute to clinical phenotypes.
  • Thumbnail Image
    Publication
    Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis
    (Springer Nature, 2015) Wagschal, Alexandre; Najafi-Shoushtari, S Hani; Wang, Lifeng; Goedeke, Leigh; Sinha, Sumita; deLemos, Andrew S; Black, Josh C; Ramírez, Cristina M; Li, Yingxia; Tewhey, Ryan; Hatoum, Ida; Shah, Naisha; Lu, Yong; Kristo, Fjoralba; Psychogios, Nikolaos; Vrbanac, Vladimir; Lu, Yi-Chien; Hla, Timothy; de Cabo, Rafael; Tsang, John S; Schadt, Eric; Sabeti, Pardis; Kathiresan, Sekar; Cohen, David E.; Whetstine, Johnathan; Chung, Raymond; Fernández-Hernando, Carlos; Kaplan, Lee; Bernards, Andre; Gerszten, Robert; Naar, Anders
    Genome-wide association studies (GWASs) have linked genes to various pathological traits. However, the potential contribution of regulatory noncoding RNAs, such as microRNAs (miRNAs), to a genetic predisposition to pathological conditions has remained unclear. We leveraged GWAS meta-analysis data from >188,000 individuals to identify 69 miRNAs in physical proximity to single-nucleotide polymorphisms (SNPs) associated with abnormal levels of circulating lipids. Several of these miRNAs (miR-128-1, miR-148a, miR-130b, and miR-301b) control the expression of key proteins involved in cholesterol-lipoprotein trafficking, such as the low-density lipoprotein (LDL) receptor (LDLR) and the ATP-binding cassette A1 (ABCA1) cholesterol transporter. Consistent with human liver expression data and genetic links to abnormal blood lipid levels, overexpression and antisense targeting of miR-128-1 or miR-148a in high-fat diet–fed C57BL/6J and Apoe-null mice resulted in altered hepatic expression of proteins involved in lipid trafficking and metabolism, and in modulated levels of circulating lipoprotein-cholesterol and triglycerides. Taken together, these findings support the notion that altered expression of miRNAs may contribute to abnormal blood lipid levels, predisposing individuals to human cardiometabolic disorders.
  • Thumbnail Image
    Publication
    An eMERGE Clinical Center at Partners Personalized Medicine
    (MDPI AG, 2016) Smoller, Jordan; Karlson, Elizabeth; Green, Robert; Kathiresan, Sekar; MacArthur, Daniel; Talkowski, Michael; Murphy, Shawn; Weiss, Scott
    The integration of electronic medical records (EMRs) and genomic research has become a major component of efforts to advance personalized and precision medicine. The Electronic Medical Records and Genomics (eMERGE) network, initiated in 2007, is an NIH-funded consortium devoted to genomic discovery and implementation research by leveraging biorepositories linked to EMRs. In its most recent phase, eMERGE III, the network is focused on facilitating implementation of genomic medicine by detecting and disclosing rare pathogenic variants in clinically relevant genes. Partners Personalized Medicine (PPM) is a center dedicated to translating personalized medicine into clinical practice within Partners HealthCare. One component of the PPM is the Partners Healthcare Biobank, a biorepository comprising broadly consented DNA samples linked to the Partners longitudinal EMR. In 2015, PPM joined the eMERGE Phase III network. Here we describe the elements of the eMERGE clinical center at PPM, including plans for genomic discovery using EMR phenotypes, evaluation of rare variant penetrance and pleiotropy, and a novel randomized trial of the impact of returning genetic results to patients and clinicians.
  • No Thumbnail Available
    Publication
    Genetic Risk, Coronary Heart Disease Events, and the Clinical Benefit of Statin Therapy: An Analysis of Primary and Secondary Prevention Trials
    (Elsevier BV, 2015-06-06) Mega, Jessica L.; Stitziel, Nathan O.; Smith, J. Gustav; Chasman, Daniel; Caulfield, Mark; Devlin, James J.; Nordio, Francesco; Hyde, Craig L.; Cannon, Christopher; Sacks, Frank; Poulter, Neil; Sever, Peter S.; Ridker, Paul; Braunwald, Eugene; Melander, Olle; Kathiresan, Sekar; Sabatine, Marc
    Background Genetic variants have been associated with the risk of coronary heart disease (CHD). We tested whether a composite of these variants could identify the risk of both incident as well as recurrent CHD events and distinguish individuals who derived greater clinical benefit from statin therapy. Methods A community-based cohort and four randomized controlled trials of both primary (JUPITER and ASCOT) and secondary (CARE and PROVE IT-TIMI 22) prevention with statin therapy totaling 48,421 individuals and 3,477 events were included in these analyses. We examined the association of a genetic risk score based on 27 genetic variants with incident or recurrent CHD, adjusting for established clinical predictors. We then investigated the relative and absolute risk reductions in CHD events with statin therapy stratified by genetic risk. Data from studies were combined using meta-analysis. Findings When individuals were divided into low (quintile 1), intermediate (quintiles 2-4), and high (quintile 5) genetic risk categories, a significant gradient of risk for incident or recurrent CHD was demonstrated with the multivariable-adjusted HRs (95% CI) for CHD for the intermediate and high genetic risk categories vs. low genetic risk category being 1.32 (1.20-1.46, P<0.0001) and 1.71 (1.54-1.91, P<0.0001), respectively. In terms of the benefit of statin therapy in the four randomized trials, there was a significant gradient of increasing relative risk reduction across the low, intermediate, and high genetic risk categories (13%, 29%, and 48%, P=0.0277). Similarly, greater absolute risk reductions were seen in those individuals in higher genetic risk categories (P=0.0101), resulting in an approximate three-fold gradient in the number needed to treat (NNT) in the primary prevention trials. Specifically, in the primary prevention trials, the NNT to prevent one MACE over 10 years for the low, intermediate, and high GRS individuals was 66, 42, and 25 in JUPITER and 57, 47, and 20 in ASCOT. Interpretation A genetic risk score identified individuals at increased risk for both incident and recurrent CHD events. Individuals with the highest burden of genetic risk derived the largest relative and absolute clinical benefit with statin therapy.
  • No Thumbnail Available
    Publication
    Inherited Causes of Clonal Haematopoiesis in 97,691 Whole Genomes
    (Springer Science and Business Media LLC, 2020-10-14) Bick, Alexander; Weinstock, Joshua S.; Nandakumar, Satish K.; Fulco, Charles P.; Bao, Erik; Zekavat, Seyedeh M.; Szeto, Mindy D.; Liao, Xiaotian; Leventhal, Matthew J.; Nasser, Joseph; Chang, Kyle; Laurie, Cecelia; Burugula, Bala Bharathi; Gibson, Christopher J.; Niroula, Abhishek; Lin, Amy; Taub, Margaret A.; Aguet, Francois; Ardlie, Kristin; Mitchell, Braxton D.; Barnes, Kathleen C.; Moscati, Arden; Fornage, Myriam; Redline, Susan; Psaty, Bruce M.; Silverman, Edwin; Weiss, Scott; Palmer, Nicholette D.; Vasan, Ramachandran S.; Burchard, Esteban G.; Kardia, Sharon L. R.; He, Jiang; Kaplan, Robert C.; Smith, Nicholas L.; Arnett, Donna K.; Schwartz, David A.; Correa, Adolfo; de Andrade, Mariza; Guo, Xiuqing; Konkle, Barbara A.; Custer, Brian; Peralta, Juan M.; Gui, Hongsheng; Meyers, Deborah A.; McGarvey, Stephen T.; Chen, Ida Yii-Der; Shoemaker, M. Benjamin; Peyser, Patricia A.; Broome, Jai G.; Gogarten, Stephanie M.; Wang, Fei Fei; Wong, Quenna; Montasser, May E.; Daya, Michelle; Kenny, Eimear E.; North, Kari E.; Launer, Lenore J.; Cade, Brian; Bis, Joshua C.; Cho, Michael; Lasky-Su, Jessica; Bowden, Donald W.; Cupples, L. Adrienne; Mak, Angel C. Y.; Becker, Lewis C.; Smith, Jennifer A.; Kelly, Tanika N.; Aslibekyan, Stella; Heckbert, Susan R.; Tiwari, Hemant K.; Yang, Ivana V.; Heit, John A.; Lubitz, Steven; Johnsen, Jill M.; Curran, Joanne E.; Wenzel, Sally E.; Weeks, Daniel E.; Rao, Dabeeru C.; Darbar, Dawood; Moon, Jee-Young; Tracy, Russell P.; Buth, Erin J.; Rafaels, Nicholas; Loos, Ruth J. F.; Durda, Peter; Liu, Yongmei; Hou, Lifang; Lee, Jiwon; Kachroo, Priyadarshini; Freedman, Barry I.; Levy, Daniel; Bielak, Lawrence F.; Hixson, James E.; Floyd, James S.; Whitsel, Eric A.; Ellinor, Patrick; Irvin, Marguerite R.; Fingerlin, Tasha E.; Raffield, Laura M.; Armasu, Sebastian M.; Wheeler, Marsha M.; Sabino, Ester C.; Blangero, John; Williams, L. Keoki; Levy, Bruce; Sheu, Wayne Huey-Herng; Roden, Dan M.; Boerwinkle, Eric; Manson, JoAnn; Mathias, Rasika A.; Desai, Pinkal; Taylor, Kent D.; Johnson, Andrew D.; Auer, Paul L.; Kooperberg, Charles; Laurie, Cathy C.; Blackwell, Thomas W.; Smith, Albert V.; Zhao, Hongyu; Lange, Ethan; Lange, Leslie; Rich, Stephen S.; Rotter, Jerome I.; Wilson, James G.; Scheet, Paul; Kitzman, Jacob O.; Lander, Eric; Engreitz, Jesse; Ebert, Benjamin; Reiner, Alexander P.; Jaiswal, Siddhartha; Abecasis, Gonçalo; Sankaran, Vijay; Kathiresan, Sekar; Natarajan, Pradeep
    Age is the dominant risk factor for most chronic human diseases; yet the mechanisms by which aging confers this risk are largely unknown. Recently, the age-related acquisition of somatic mutations in regenerating hematopoietic stem cell populations leading to clonal expansion was associated with both hematologic cancer and coronary heart disease5, a phenomenon termed ‘Clonal Hematopoiesis of Indeterminate Potential’ (CHIP). Simultaneous germline and somatic whole genome sequence analysis now provides the opportunity to identify root causes of CHIP. Here, we analyze high-coverage whole genome sequences from 97,691 participants of diverse ancestries in the NHLBI TOPMed program and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid, and inflammatory traits specific to different CHIP genes. Association of a genome-wide set of germline genetic variants identified three genetic loci associated with CHIP status, including one locus at TET2 that was African ancestry specific. In silico-informed in vitro evaluation of the TET2 germline locus identified a causal variant that disrupts a TET2 distal enhancer resulting in increased hematopoietic stem cell self-renewal. Overall, we observe that germline genetic variation shapes hematopoietic stem cell function leading to CHIP through mechanisms that are both specific to clonal hematopoiesis and shared mechanisms leading to somatic mutations across tissues.