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1. The enhanced X-ray Timing and Polarimetry mission - eXTP

Author: Zhang, ShuangNan, Santangelo, Andrea, Feroci, Marco, Xu, YuPeng, Lu, FangJun, Chen, Yong, Feng, Hua, Zhang, Shu, Brandt, Søren, Hernanz, Margarita, Baldini, Luca, Bozzo, Enrico, Campana, Riccardo, De Rosa, Alessandra, Dong, YongWei, Evangelista, Yuri, Karas, Vladimir, Meidinger, Norbert, Meuris, Aline, Nandra, Kirpal, Pan, Teng, Pareschi, Giovanni, Orleanski, Piotr, Huang, QiuShi, Schanne, Stephane, Sironi, Giorgia, Spiga, Daniele, Svoboda, Jiri, Tagliaferri, Gianpiero, Tenzer, Christoph, Vacchi, Andrea, Zane, Silvia, Walton, Dave, Wang, ZhanShan, Winter, Berend, Wu, Xin, Zand, Jean J. M. in 't, Ahangarianabhari, Mahdi, Ambrosi, Giovanni, Ambrosino, Filippo, Barbera, Marco, Basso, Stefano, Bayer, Jörg, Bellazzini, Ronaldo, Bellutti, Pierluigi, Bertucci, Bruna, Bertuccio, Giuseppe, Borghi, Giacomo, Cao, XueLei, Cadoux, Franck, Ceraudo, Francesco, Chen, TianXiang, Chen, YuPeng, Chevenez, Jerome, Civitani, Marta, Cui, Wei, Cui, WeiWei, Dauser, Thomas, Del Monte, Ettore, Di Cosimo, Sergio, Diebold, Sebastian, Doroshenko, Victor, Dovciak, Michal, Du, YuanYuan, Ducci, Lorenzo, Fan, QingMei, Favre, Yannick, Fuschino, Fabio, Gálvez, José Luis, Gao, Min, Ge, MingYu, Gevin, Olivier, Grassi, Marco, Gu, QuanYing, Gu, YuDong, Han, DaWei, Hong, Bin, Hu, Wei, Ji, Long, Jia, ShuMei, Jiang, WeiChun, Kennedy, Thomas, Kreykenbohm, Ingo, Kuvvetli, Irfan, Labanti, Claudio, Latronico, Luca, Li, Gang, Li, MaoShun, Li, Xian, Li, Wei, Li, ZhengWei, Limousin, Olivier, Liu, HongWei, Liu, XiaoJing, Lu, Bo, Luo, Tao, Macera, Daniele, Malcovati, Piero, Martindale, Adrian, Michalska, Malgorzata, Meng, Bin, Minuti, Massimo, Morbidini, Alfredo, Muleri, Fabio, Paltani, Stephane, Perinati, Emanuele, Picciotto, Antonino, Piemonte, Claudio, Qu, JinLu, Rachevski, Alexandre, Rashevskaya, Irina, Rodriguez, Jerome, Schanz, Thomas, Shen, ZhengXiang, Sheng, LiZhi, Song, JiangBo, Song, LiMing, Sgro, Carmelo, Sun, Liang, Tan, Ying, Uttley, Phil, Wang, Juan, Wang, LangPing, Wang, YuSa, Watts, Anna L., Wen, XiangYang, Wilms, Jörn, Xiong, ShaoLin, Yang, JiaWei, Yang, Sheng, Yang, YanJi, Yu, Nian, Zhang, WenDa, Zampa, Gianluigi, Zampa, Nicola, Zdziarski, Andrzej A., Zhang, AiMei, Zhang, ChengMo, Zhang, Fan, Zhang, Long, Zhang, Tong, Zhang, Yi, Zhang, XiaoLi, Zhang, ZiLiang, Zhao, BaoSheng, Zheng, ShiJie, Zhou, YuPeng, Zorzi, Nicola, and Zwart, J. Frans
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract: In this paper we present the enhanced X-ray Timing and Polarimetry mission - eXTP. eXTP is a space science mission designed to study fundamental physics under extreme conditions of density, gravity and magnetism. The mission aims at determining the equation of state of matter at supra-nuclear density, measuring effects of QED, and understanding the dynamics of matter in strong-field gravity. In addition to investigating fundamental physics, eXTP will be a very powerful observatory for astrophysics that will provide observations of unprecedented quality on a variety of galactic and extragalactic objects. In particular, its wide field monitoring capabilities will be highly instrumental to detect the electro-magnetic counterparts of gravitational wave sources. The paper provides a detailed description of: (1) the technological and technical aspects, and the expected performance of the instruments of the scientific payload; (2) the elements and functions of the mission, from the spacecraft to the ground segment., Comment: Accepted for publication on Sci. China Phys. Mech. Astron. (2019)
Published: 2018
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2. The MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Survey

Author: Jarvis, Matt J., Taylor, A. R., Agudo, I., Allison, James R., Deane, R. P., Frank, B., Gupta, N., Heywood, I., Maddox, N., McAlpine, K., Santos, Mario G., Scaife, A. M. M., Vaccari, M., Zwart, J. T. L., Adams, E., Bacon, D. J., Baker, A. J., Bassett, Bruce. A., Best, P. N., Beswick, R., Blyth, S., Brown, Michael L., Bruggen, M., Cluver, M., Colafranceso, S., Cotter, G., Cress, C., Dave, R., Ferrari, C., Hardcastle, M. J., Hale, C., Harrison, I., Hatfield, P. W., Klockner, H. -R., Kolwa, S., Malefahlo, E., Marubini, T., Mauch, T., Moodley, K., Morganti, R., Norris, R., Peters, J. A., Prandoni, I., Prescott, M., Oliver, S., Oozeer, N., Rottgering, H. J. A., Seymour, N., Simpson, C., Smirnov, O., Smith, D. J. B., Spekkens, K., Stil, J., Tasse, C., van der Heyden, K., Whittam, I. H., and WIlliams, W. L.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The MIGHTEE large survey project will survey four of the most well-studied extragalactic deep fields, totalling 20 square degrees to $\mu$Jy sensitivity at Giga-Hertz frequencies, as well as an ultra-deep image of a single ~1 square degree MeerKAT pointing. The observations will provide radio continuum, spectral line and polarisation information. As such, MIGHTEE, along with the excellent multi-wavelength data already available in these deep fields, will allow a range of science to be achieved. Specifically, MIGHTEE is designed to significantly enhance our understanding of, (i) the evolution of AGN and star-formation activity over cosmic time, as a function of stellar mass and environment, free of dust obscuration; (ii) the evolution of neutral hydrogen in the Universe and how this neutral gas eventually turns into stars after moving through the molecular phase, and how efficiently this can fuel AGN activity; (iii) the properties of cosmic magnetic fields and how they evolve in clusters, filaments and galaxies. MIGHTEE will reach similar depth to the planned SKA all-sky survey, and thus will provide a pilot to the cosmology experiments that will be carried out by the SKA over a much larger survey volume., Comment: Proceedings of Science, "MeerKAT Science: On the Pathway to the SKA", Stellenbosch, 25-27 May 2016
Published: 2017

3. A MeerKAT view on galaxy clusters

Author: Bernardi, G., Venturi, T., Cassano, R., Brunetti, G., Dallacasa, D., Fanaroff, B., Hugo, B., Makhatini, S., Oozeer, N., Smirnov, O. M., and Zwart, J. T. L.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Almost two decades of observations of radio emission in galaxy clusters have proven the existence of relativistic particles and magnetic fields that generate extended synchrotron emission in the form of radio halos. In the current scenario, radio halos are generated through re--acceleration of relativistic electrons by turbulence generated by cluster mergers. Although this theoretical framework has received increasingly supporting observational evidence over the last ten years, observations of statistically complete samples are needed in order to fundamentally test model predictions. In this paper we briefly review our 7--element Karoo Radio Telescope observations of a sample of nearby clusters aimed to test the predictions of the turbulent re--acceleration model in small systems ($M_{500} > 4 \times 10^{14}$ M$_{\odot}$). We conclude by presenting two galaxy cluster surveys to be carried out with MeerKAT in order to provide crucial test of models of radio halo formation in nearby ($z < 0.1$) and high redshift ($z > 0.4$) systems respectively., Comment: 7 pages, 2 figures Accepted for publication, Proceedings of Science, Workshop on "MeerKAT Science: On the Pathway to the SKA", held in Stellenbosch 25-27 May, 2016
Published: 2017

4. The LOFAR Two-metre Sky Survey - I. Survey Description and Preliminary Data Release

Author: Shimwell, T. W., Röttgering, H. J. A., Best, P. N., Williams, W. L., Dijkema, T. J., de Gasperin, F., Hardcastle, M. J., Heald, G. H., Hoang, D. N., Horneffer, A., Intema, H., Mahony, E. K., Mandal, S., Mechev, A. P., Morabito, L., Oonk, J. B. R., Rafferty, D., Retana-Montenegro, E., Sabater, J., Tasse, C., van Weeren, R. J., Brüggen, M., Brunetti, G., Chyży, K. T., Conway, J. E., Haverkorn, M., Jackson, N., Jarvis, M. J., McKean, J. P., Miley, G. K., Morganti, R., White, G. J., Wise, M. W., van Bemmel, I. M., Beck, R., Brienza, M., Bonafede, A., Rivera, G. Calistro, Cassano, R., Clarke, A. O., Cseh, D., Deller, A., Drabent, A., van Driel, W., Engels, D., Falcke, H., Ferrari, C., Fröhlich, S., Garrett, M. A., Harwood, J. J., Heesen, V., Hoeft, M., Horellou, C., Israel, F. P., Kapińska, A. D., Kunert-Bajraszewska, M., McKay, D. J., Mohan, N. R., Orrú, E., Pizzo, R. F., Prandoni, I., Schwarz, D. J., Shulevski, A., Sipior, M., Smith, D. J. B., Sridhar, S. S., Steinmetz, M., Stroe, A., Varenius, E., van der Werf, P. P., Zensus, J. A., and Zwart, J. T. L.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The LOFAR Two-metre Sky Survey (LoTSS) is a deep 120-168 MHz imaging survey that will eventually cover the entire Northern sky. Each of the 3170 pointings will be observed for 8 hrs, which, at most declinations, is sufficient to produce ~5arcsec resolution images with a sensitivity of ~0.1mJy/beam and accomplish the main scientific aims of the survey which are to explore the formation and evolution of massive black holes, galaxies, clusters of galaxies and large-scale structure. Due to the compact core and long baselines of LOFAR, the images provide excellent sensitivity to both highly extended and compact emission. For legacy value, the data are archived at high spectral and time resolution to facilitate subarcsecond imaging and spectral line studies. In this paper we provide an overview of the LoTSS. We outline the survey strategy, the observational status, the current calibration techniques, a preliminary data release, and the anticipated scientific impact. The preliminary images that we have released were created using a fully-automated but direction-independent calibration strategy and are significantly more sensitive than those produced by any existing large-area low-frequency survey. In excess of 44,000 sources are detected in the images that have a resolution of 25arcsec, typical noise levels of less than 0.5 mJy/beam, and cover an area of over 350 square degrees in the region of the HETDEX Spring Field (right ascension 10h45m00s to 15h30m00s and declination 45d00m00s to 57d00m00s)., Comment: 23 pages, 15 figures, 3 tables, accepted for publication in A&A
Published: 2016
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5. Bayesian constraints on the global 21-cm signal from the Cosmic Dawn

Author: Bernardi, G., Zwart, J. T. L., Price, D., Greenhill, L. J., Mesinger, A., Dowell, J., Eftekhari, T., Ellingson, S. W., Kocz, J., and Schinzel, F.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The birth of the first luminous sources and the ensuing epoch of reionization are best studied via the redshifted 21-cm emission line, the signature of the first two imprinting the last. In this work we present a fully-Bayesian method, \textsc{hibayes}, for extracting the faint, global (sky-averaged) 21-cm signal from the much brighter foreground emission. We show that a simplified (but plausible), Gaussian model of the 21-cm emission from the Cosmic Dawn epoch ($15 \lesssim z \lesssim 30$), parameterized by an amplitude $A_{\rm HI}$, a frequency peak $\nu_{\rm HI}$ and a width $\sigma_{\rm HI}$, can be extracted even in the presence of a structured foreground frequency spectrum (parameterized as a $7^{\rm th}$-order polynomial), provided sufficient signal-to-noise (400~hours of observation with a single dipole). We apply our method to an early, 19-minute long observation from the Large aperture Experiment to detect the Dark Ages, constraining the 21-cm signal amplitude and width to be $-890 < A_{\rm HI} < 0$ mK and $\sigma_{\rm HI} > 6.5$ MHz (corresponding to $\Delta z > 1.9$ at redshift $z \simeq 20$) respectively at the 95-per-cent confidence level in the range $13.2 < z < 27.4$ ($100 > \nu > 50$ MHz)., Comment: 10 pages, 8 figures, MNRAS accepted
Published: 2016
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6. Engineering and Science Highlights of the KAT-7 Radio Telescope

Author: Foley, A. R., Alberts, T., Armstrong, R P., Barta, A., Bauermeister, E. F., Bester, H., Blose, S., Booth, R. S., Botha, D. H., Buchner, S. J., Carignan, C., Cheetham, T., Cloete, K., Coreejes, G., Crida, R. C., Cross, S. D., Curtolo, F., Dikgale, A., de Villiers, M. S., Toit, L. J. du, Esterhuyse, S. W. P., Fanaroff, B., Fender, R. P., Fijalkowski, M., Fourie, D., Frank, B., George, D., Gibbs, P., Goedhart, S., Grobbelaar, J., Gumede, S. C., Herselman, P., Hess, K. M., Hoek, N., Horrell, J., Jonas, J. L., Jordaan, J. D. B., Julie, R., Kapp, F., Kotzé, P., Kusel, T., Langman, A., Lehmensiek, R., Liebenberg, D., Liebenberg, I. J. V., Loots, A., Lord, R. T., Lucero, D. M., Ludick, J., Macfarlane, P., Madlavana, M., Magnus, L., Magozore, C., Malan, J. A., Manley, J. R., Marais, L., Marais, N., Marais, S. J., Maree, M., Martens, A., Mokone, O., Moss, V., Mthembu, S., New, W., Nicholson, G. D., van Niekerk, P. C., Oozeer, N., Passmoor, S. S., Peens-Hough, A., Pińska, A. B., Prozesky, P., Rajan, S., Ratcliffe, S., Renil, R., Richter, L. L., Rosekrans, D., Rust, A., Schröder, A. C., Schwardt, L. C., Seranyane, S., Serylak, M., Shepherd, D. S., Siebrits, R., Sofeya, L., Spann, R., Springbok, R., Swart, P. S., Thondikulam, Venkatasubramani L., Theron, I. P., Tiplady, A., Toruvanda, O., Tshongweni, S., Heever, L. van den, van der Merwe, C., van Rooyen, R., Wakhaba, S., Walker, A. L., Welz, M., Williams, L., Wolleben, M., Woudt, P. A., Young, N. J., and Zwart, J. T. L.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The construction of the KAT-7 array in the Karoo region of the Northern Cape in South Africa was intended primarily as an engineering prototype for technologies and techniques applicable to the MeerKAT telescope. This paper looks at the main engineering and scien- tific highlights from this effort, and discusses their applicability to both MeerKAT and other next-generation radio telescopes. In particular we found that the composite dish surface works well, but it becomes complicated to fabricate for a dish lacking circular symmetry; the Stir- ling cycle cryogenic system with ion pump to achieve vacuum works but demands much higher maintenance than an equivalent Gifford-McMahon cycle system; the ROACH (Recon- figurable Open Architecture Computing Hardware)-based correlator with SPEAD (Stream- ing Protocol for Exchanging Astronomical Data) protocol data transfer works very well and KATCP (Karoo Array Telescope Control Protocol) control protocol has proven very flexible and convenient. KAT-7 has also been used for scientific observations where it has a niche in mapping low surface-brightness continuum sources, some extended HI halos and OH masers in star-forming regions. It can also be used to monitor continuum source variability, observe pulsars, and make VLBI observations
Published: 2016
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7. LOFAR 150-MHz observations of the Bo\'otes field: Catalogue and Source Counts

Author: Williams, W. L., van Weeren, R. J., Röttgering, H. J. A., Best, P., Dijkema, T. J., de Gasperin, F., Hardcastle, M. J., Heald, G., Prandoni, I., Sabater, J., Shimwell, T. W., Tasse, C., van Bemmel, I. M., Brüggen, M., Brunetti, G., Conway, J. E., Enßlin, T., Engels, D., Falcke, H., Ferrari, C., Haverkorn, M., Jackson, N., Jarvis, M. J., Kapinska, A. D., Mahony, E. K., Miley, G. K., Morabito, L. K., Morganti, R., Orrú, E., Retana-Montenegro, E., Sridhar, S. S., Toribio, M. C., White, G. J., Wise, M. W., and Zwart, J. T. L.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We present the first wide area (19 deg$^2$), deep ($\approx120-150$ {\mu}Jy beam$^{-1}$), high resolution ($5.6 \times 7.4$ arcsec) LOFAR High Band Antenna image of the Bo\"otes field made at 130-169 MHz. This image is at least an order of magnitude deeper and 3-5 times higher in angular resolution than previously achieved for this field at low frequencies. The observations and data reduction, which includes full direction-dependent calibration, are described here. We present a radio source catalogue containing 6276 sources detected over an area of $19$\,deg$^2$, with a peak flux density threshold of $5\sigma$. As the first thorough test of the facet calibration strategy, introduced by van Weeren et al., we investigate the flux and positional accuracy of the catalogue. We present differential source counts that reach an order of magnitude deeper in flux density than previously achieved at these low frequencies, and show flattening at 150 MHz flux densities below 10 mJy associated with the rise of the low flux density star-forming galaxies and radio-quiet AGN., Comment: 29 pages, 27 figures, accepted for publication in MNRAS
Published: 2016
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8. Predicting the risks and recognizing the signs: a two-year prospective population-based study on pregnant women with uterine rupture in The Netherlands

Author: Arts-assistenten DV&B, MS Verloskunde, DV&B-MT-Medisch, Child Health, Overtoom, E. M., Huynh, T. N., Rosman, A. N., Zwart, J. J., Schaap, T. P., Vogelvang, T. E., van den Akker, T., Bloemenkamp, K. W.M., Arts-assistenten DV&B, MS Verloskunde, DV&B-MT-Medisch, Child Health, Overtoom, E. M., Huynh, T. N., Rosman, A. N., Zwart, J. J., Schaap, T. P., Vogelvang, T. E., van den Akker, T., and Bloemenkamp, K. W.M.
Published: 2024

9. The Q/U Imaging ExperimenT: Polarization Measurements of the Galactic Plane at 43 and 95 GHz

Author: QUIET Collaboration, Ruud, T. M., Fuskeland, U., Wehus, I. K., Vidal, M., Araujo, D., Bischoff, C., Buder, I., Chinone, Y., Cleary, K., Dumoulin, R. N., Kusaka, A., Monsalve, R., Naess, S. K., Newburgh, L. B., Reeves, R. A., Zwart, J. T. L., Bronfman, L., Davies, R. D., Davis, R., Dickinson, C., Eriksen, H. K., Gaier, T., Gundersen, J. O., Hasegawa, M., Hazumi, M., Huffenberger, K. M., Jones, M. E., Lawrence, C. R., Leitch, E. M., Limon, M., Miller, A. D., Pearson, T. J., Piccirillo, L., Radford, S. J. E., Readhead, A. C. S., Samtleben, D., Seiffert, M., Shepherd, M. C., Staggs, S. T., Tajima, O., and Thompson, K. L.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present polarization observations of two Galactic plane fields centered on Galactic coordinates (l,b)=(0 deg,0 deg) and (329 deg, 0 deg) at Q- (43 GHz) and W-band (95 GHz), covering between 301 and 539 square degrees depending on frequency and field. These measurements were made with the QUIET instrument between 2008 October and 2010 December, and include a total of 1263 hours of observations. The resulting maps represent the deepest large-area Galactic polarization observations published to date at the relevant frequencies with instrumental rms noise varying between 1.8 and 2.8 uK deg, 2.3-6 times deeper than corresponding WMAP and Planck maps. The angular resolution is 27.3' and 12.8' FWHM at Q- and W-band, respectively. We find excellent agreement between the QUIET and WMAP maps over the entire fields, and no compelling evidence for significant residual instrumental systematic errors in either experiment, whereas the Planck 44 GHz map deviates from these in a manner consistent with reported systematic uncertainties for this channel. We combine QUIET and WMAP data to compute inverse-variance-weighted average maps, effectively retaining small angular scales from QUIET and large angular scales from WMAP. From these combined maps, we derive constraints on several important astrophysical quantities, including a robust detection of polarized synchrotron spectral index steepening of ~0.2 off the plane, as well as the Faraday rotation measure toward the Galactic center (RM=-4000 +/- 200 rad m^-2), all of which are consistent with previously published results. Both the raw QUIET and the co-added QUIET+WMAP maps are made publicly available together with all necessary ancillary information., Comment: 22 pages, 18 figures; accepted for publication in ApJ; data are available on Lambda (http://lambda.gsfc.nasa.gov)
Published: 2015
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10. Doppler ultrasound of umbilical and middle cerebral artery in third trimester small‐for‐gestational age fetuses to decide on timing of delivery for suspected fetal growth restriction: A cohort with nested RCT (DRIGITAT).

Author: Marijnen, Mauritia C., Kamphof, Hester D., Damhuis, Stefanie E., Smies, Maddy, Leemhuis, Aleid G., Wolf, Hans, Gordijn, Sanne J., Ganzevoort, Wessel, Schaaf, J. M., de Boer, M. A., Zwart, J. J., Huisjes, A. J. M., Veerbeek, J. H. W., van Laar, J. O. E. H., Al‐Nasiry, S., Bremer, H. A., Hermsen, B. B. J., van de Nieuwenhof, H. P., Sueters, M., and van der Ham, D. P.
Subjects: FETAL growth retardation, DOPPLER ultrasonography, CEREBRAL arteries, SMALL for gestational age, FETUS
Abstract: Objective: To assess the association of the umbilicocerebral ratio (UCR) with adverse perinatal outcome in late preterm small‐for‐gestational age (SGA) fetuses and to investigate the effect on perinatal outcomes of immediate delivery. Design: Multicentre cohort study with nested randomised controlled trial (RCT). Setting: Nineteen secondary and tertiary care centres. Population: Singleton SGA pregnancies (estimated fetal weight [EFW] or fetal abdominal circumference [FAC] <10th centile) from 32 to 36+6 weeks. Methods: Women were classified: (1) RCT‐eligible: abnormal UCR twice consecutive and EFW below the 3rd centile at/or below 35 weeks or below the 10th centile at 36 weeks; (2) abnormal UCR once or intermittent; (3) never abnormal UCR. Consenting RCT‐eligible patients were randomised for immediate delivery from 34 weeks or expectant management until 37 weeks. Main outcome measures: A composite adverse perinatal outcome (CAPO), defined as perinatal death, birth asphyxia or major neonatal morbidity. Results: The cohort consisted of 690 women. The study was halted prematurely for low RCT‐inclusion rates (n = 40). In the RCT‐eligible group, gestational age at delivery, birthweight and birthweight multiple of the median (MoM) (0.66, 95% confidence interval [CI] 0.59–0.72) were significantly lower and the CAPO (n = 50, 44%, p < 0.05) was more frequent. Among patients randomised for immediate delivery there was a near‐significant lower birthweight (p = 0.05) and higher CAPO (p = 0.07). EFW MoM, pre‐eclampsia, gestational hypertension and Doppler classification were independently associated with the CAPO (area under the curve 0.71, 95% CI 0.67–0.76). Conclusions: Perinatal risk was effectively identified by low EFW MoM and UCR. Early delivery of SGA fetuses with an abnormal UCR at 34–36 weeks should only be performed in the context of clinical trials. [ABSTRACT FROM AUTHOR]
Published: 2024
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11. Development and validation of a prediction model for incident hand osteoarthritis in the HUNT study

Author: Johnsen, M.B., Magnusson, K., Børte, S., Gabrielsen, M.E., Winsvold, B.S., Skogholt, A.H., Thomas, L., Storheim, K., Hveem, K., and Zwart, J.-A.
Published: 2020
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12. Predicting the risks and recognizing the signs: a two-year prospective population-based study on pregnant women with uterine rupture in The Netherlands

Author: Overtoom, E. M., primary, Huynh, T. N., additional, Rosman, A. N., additional, Zwart, J. J., additional, Schaap, T. P., additional, Vogelvang, T. E., additional, van den Akker, T., additional, and Bloemenkamp, K. W. M., additional
Published: 2024
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13. The Q/U Imaging Experiment: Polarization Measurements of Radio Sources at 43 and 95 GHz

Author: QUIET Collaboration, Huffenberger, K. M., Araujo, D., Bischoff, C., Buder, I., Chinone, Y., Cleary, K., Kusaka, A., Monsalve, R., Næss, S. K., Newburgh, L. B., Reeves, R., Ruud, T. M., Wehus, I. K., Zwart, J. T. L., Dickinson, C., Eriksen, H. K., Gaier, T., Gundersen, J. O., Hasegawa, M., Hazumi, M., Miller, A. D., Radford, S. J. E., Readhead, A. C. S., Staggs, S. T., Tajima, O., and Thompson, K. L.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We present polarization measurements of extragalactic radio sources observed during the Cosmic Microwave Background polarization survey of the Q/U Imaging Experiment (QUIET), operating at 43 GHz (Q-band) and 95 GHz (W-band). We examine sources selected at 20 GHz from the public, $>$40 mJy catalog of the Australia Telescope (AT20G) survey. There are $\sim$480 such sources within QUIET's four low-foreground survey patches, including the nearby radio galaxies Centaurus A and Pictor A. The median error on our polarized flux density measurements is 30--40 mJy per Stokes parameter. At S/N $> 3$ significance, we detect linear polarization for seven sources in Q-band and six in W-band; only $1.3 \pm 1.1$ detections per frequency band are expected by chance. For sources without a detection of polarized emission, we find that half of the sources have polarization amplitudes below 90 mJy (Q-band) and 106 mJy (W-band), at 95% confidence. Finally, we compare our polarization measurements to intensity and polarization measurements of the same sources from the literature. For the four sources with WMAP and Planck intensity measurements $>1$ Jy, the polarization fraction are above 1% in both QUIET bands. At high significance, we compute polarization fractions as much as 10--20% for some sources, but the effects of source variability may cut that level in half for contemporaneous comparisons. Our results indicate that simple models---ones that scale a fixed polarization fraction with frequency---are inadequate to model the behavior of these sources and their contributions to polarization maps., Comment: 16 pages, 10 figures. Submitted to ApJ
Published: 2014
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14. Severe Hypertensive Disorders of Pregnancy in Eastern Ethiopia: Comparing the Original WHO and Adapted sub-Saharan African Maternal Near-Miss Criteria

Author: Tura AK, Scherjon S, Stekelenburg J, van Roosmalen J, van den Akker T, and Zwart J
Subjects: severe maternal outcomes, hypertensive disorders of pregnancy, maternal near miss, maternal mortality, sub-saharan africa, Gynecology and obstetrics, RG1-991
Abstract: Abera Kenay Tura,1,2 Sicco Scherjon,2 Jelle Stekelenburg,3,4 Jos van Roosmalen,5,6 Thomas van den Akker,5,6 Joost Zwart7 1School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia; 2Department of Obstetrics and Gynecology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands; 3Department of Health Sciences, Global Health, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands; 4Department of Obstetrics and Gynecology, Leeuwarden Medical Centre, Leeuwarden, The Netherlands; 5Athena Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; 6Department of Obstetrics and Gynaecology, Leiden University Medical Centre, Leiden, The Netherlands; 7Department of Obstetrics and Gynaecology, Deventer Ziekenhuis, Deventer, The NetherlandsCorrespondence: Abera Kenay TuraSchool of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, POB 235, Harar, EthiopaEmail a.k.tura@haramaya.edu.etObjectives: To assess life-threatening complications among women admitted with severe hypertensive disorders of pregnancy and compare applicability of World Health Organization (WHO) maternal near-miss (MNM) criteria and the recently adapted sub-Saharan African (SSA) MNM criteria in eastern Ethiopia.Methods: Of 1,054 women admitted with potentially life-threatening conditions between January 2016 and April 2017, 562 (53.3%) had severe preeclampsia/eclampsia. We applied the definition of MNM according to the WHO MNM criteria and the SSA MNM criteria. Logistic regression was performed to identify factors associated with severe maternal outcomes (MNMs and maternal deaths).Results: The SSA MNM criteria identified 285 cases of severe maternal outcomes: 271 MNMs and 14 maternal deaths (mortality index 4.9%). The WHO criteria identified 50 cases of severe maternal outcomes: 36 MNMs and 14 maternal deaths (mortality index 28%). The MNM ratio was 36.6 per 1,000 livebirths according to the SSA MNM criteria and 4.9 according to the WHO criteria. More than 80% of women in both groups had MNM events on arrival or within 12 hours after admission. Women without antenatal care, from rural areas, referred from other facilities, and with concomitant hemorrhage more often developed severe maternal outcomes.Conclusion: Regarding hypertensive disorders of pregnancy, the SSA tool is more inclusive than the WHO tool, while still maintaining a considerably high mortality index indicating severity of included cases. This may enable more robust audits. Strengthening the referral system and improving prevention and management of obstetric hemorrhage in women with hypertensive disorders of pregnancy are required to avert severe maternal outcomes.Keywords: severe maternal outcomes, hypertensive disorders of pregnancy, maternal near-miss, maternal mortality, sub-Saharan Africa
Published: 2020

15. The QUIET Instrument

Author: QUIET Collaboration, Bischoff, C., Brizius, A., Buder, I., Chinone, Y., Cleary, K., Dumoulin, R. N., Kusaka, A., Monsalve, R., Naess, S. K., Newburgh, L. B., Nixon, G., Reeves, R., Smith, K. M., Vanderlinde, K., Wehus, I. K., Bogdan, M., Bustos, R., Church, S. E., Davis, R., Dickinson, C., Eriksen, H. K., Gaier, T., Gundersen, J. O., Hasegawa, M., Hazumi, M., Holler, C., Huffenberger, K. M., Imbriale, W. A., Ishidoshiro, K., Jones, M. E., Kangaslahti, P., Kapner, D. J., Lawrence, C. R., Leitch, E. M., Limon, M., McMahon, J. J., Miller, A. D., Nagai, M., Nguyen, H., Pearson, T. J., Piccirillo, L., Radford, S. J. E., Readhead, A. C. S., Richards, J. L., Samtleben, D., Seiffert, M., Shepherd, M. C., Staggs, S. T., Tajima, O., Thompson, K. L., Williamson, R., Winstein, B., Wollack, E. J., and Zwart, J. T. L.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Q/U Imaging ExperimenT (QUIET) is designed to measure polarization in the Cosmic Microwave Background, targeting the imprint of inflationary gravitational waves at large angular scales (~ 1 degree). Between 2008 October and 2010 December, two independent receiver arrays were deployed sequentially on a 1.4 m side-fed Dragonian telescope. The polarimeters which form the focal planes use a highly compact design based on High Electron Mobility Transistors (HEMTs) that provides simultaneous measurements of the Stokes parameters Q, U, and I in a single module. The 17-element Q-band polarimeter array, with a central frequency of 43.1 GHz, has the best sensitivity (69 uK sqrt(s)) and the lowest instrumental systematic errors ever achieved in this band, contributing to the tensor-to-scalar ratio at r < 0.1. The 84-element W-band polarimeter array has a sensitivity of 87 uK sqrt(s) at a central frequency of 94.5 GHz. It has the lowest systematic errors to date, contributing at r < 0.01. The two arrays together cover multipoles in the range l= 25-975. These are the largest HEMT-based arrays deployed to date. This article describes the design, calibration, performance of, and sources of systematic error for the instrument.
Published: 2012
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16. Second Season QUIET Observations: Measurements of the CMB Polarization Power Spectrum at 95 GHz

Author: QUIET Collaboration, Araujo, D., Bischoff, C., Brizius, A., Buder, I., Chinone, Y., Cleary, K., Dumoulin, R. N., Kusaka, A., Monsalve, R., Næss, S. K., Newburgh, L. B., Reeves, R., Wehus, I. K., Zwart, J. T. L., Bronfman, L., Bustos, R., Church, S. E., Dickinson, C., Eriksen, H. K., Gaier, T., Gundersen, J. O., Hasegawa, M., Hazumi, M., Huffenberger, K. M., Ishidoshiro, K., Jones, M. E., Kangaslahti, P., Kapner, D. J., Kubik, D., Lawrence, C. R., Limon, M., McMahon, J. J., Miller, A. D., Nagai, M., Nguyen, H., Nixon, G., Pearson, T. J., Piccirillo, L., Radford, S. J. E., Readhead, A. C. S., Richards, J. L., Samtleben, D., Seiffert, M., Shepherd, M. C., Smith, K. M., Staggs, S. T., Tajima, O., Thompson, K. L., Vanderlinde, K., and Williamson, R.
Subjects: Astrophysics - Cosmology and Extragalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The Q/U Imaging ExperimenT (QUIET) has observed the cosmic microwave background (CMB) at 43 and 95GHz. The 43-GHz results have been published in QUIET Collaboration et al. (2011), and here we report the measurement of CMB polarization power spectra using the 95-GHz data. This data set comprises 5337 hours of observations recorded by an array of 84 polarized coherent receivers with a total array sensitivity of 87 uK sqrt(s). Four low-foreground fields were observed, covering a total of ~1000 square degrees with an effective angular resolution of 12.8', allowing for constraints on primordial gravitational waves and high-signal-to-noise measurements of the E-modes across three acoustic peaks. The data reduction was performed using two independent analysis pipelines, one based on a pseudo-Cl (PCL) cross-correlation approach, and the other on a maximum-likelihood (ML) approach. All data selection criteria and filters were modified until a predefined set of null tests had been satisfied before inspecting any non-null power spectrum. The results derived by the two pipelines are in good agreement. We characterize the EE, EB and BB power spectra between l=25 and 975 and find that the EE spectrum is consistent with LCDM, while the BB power spectrum is consistent with zero. Based on these measurements, we constrain the tensor-to-scalar ratio to r=1.1+0.9-0.8 (r<2.8 at 95% C.L.) as derived by the ML pipeline, and r=1.2+0.9-0.8 (r<2.7 at 95% C.L.) as derived by the PCL pipeline. In one of the fields, we find a correlation with the dust component of the Planck Sky Model, though the corresponding excess power is small compared to statistical errors. Finally, we derive limits on all known systematic errors, and demonstrate that these correspond to a tensor-to-scalar ratio smaller than r=0.01, the lowest level yet reported in the literature., Comment: 10 pages, 6 figures, 3 tables, submitted to ApJ, This paper should be cited as "QUIET Collaboration (2012)." v2: updated to reflect published version
Published: 2012
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17. The VISTA Deep Extragalactic Observations (VIDEO) Survey

Author: Jarvis, Matt J., Bonfield, D. G., Bruce, V. A., Geach, J. E., McAlpine, K., McLure, R. J., Gonzalez-Solares, E., Irwin, M., Lewis, J., Yoldas, A. Kupcu, Andreon, S., Cross, N. J. G., Emerson, J. P., Dalton, G., Dunlop, J. S., Hodgkin, S. T., Fevre, O. Le, Karouzos, M., Meisenheimer, K., Oliver, S., Rawlings, S., Simpson, C., Smail, I., Smith, D. J. B., Sullivan, M., Sutherland, W., White, S. V., and Zwart, J. T. L.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: In this paper we describe the first data release of the the Visible and Infrared Survey Telescope for Astronomy (VISTA) Deep Extragalactic Observations (VIDEO) survey. VIDEO is a ~12degree^2 survey in the near-infrared Z,Y,J,H and K_s bands, specifically designed to enable the evolution of galaxies and large structures to be traced as a function of both epoch and environment from the present day out to z=4, and active galactic nuclei (AGN) and the most massive galaxies up to and into the epoch of reionization. With its depth and area, VIDEO will be able to fully explore the period in the Universe where AGN and starburst activity were at their peak and the first galaxy clusters were beginning to virialize. VIDEO therefore offers a unique data set with which to investigate the interplay between AGN, starbursts and environment, and the role of feedback at a time when it was potentially most crucial. We provide data over the VIDEO-XMM3 tile, which also covers the Canada-France-Hawaii-Telescope Legacy Survey Deep-1 field (CFHTLS-D1). The released VIDEO data reach a 5-sigma AB-magnitude depth of Z=25.7, Y=24.5, J=24.4, H=24.1 and K_s=23.8 in 2 arcsec diameter apertures (the full depth of Y=24.6 will be reached within the full integration time in future releases). The data are compared to previous surveys over this field and we find good astrometric agreement with the Two-Micron All Sky Survey, and source counts in agreement with the recently released UltraVISTA survey data. The addition of the VIDEO data to the CFHTLS-D1 optical data increases the accuracy of photometric redshifts and significantly reduces the fraction of catastrophic outliers over the redshift range 0
Published: 2012
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18. A blind detection of a large, complex, Sunyaev--Zel'dovich structure

Author: Consortium, AMI, Shimwell, T. W., Barker, R. W., Biddulph, P., Bly, D., Boysen, R. C., Brown, A. R., Brown, M. L., Clementson, C., Crofts, M., Culverhouse, T. L., Czeres, J., Dace, R. J., Davies, M. L., D'Alessandro, R., Doherty, P., Duggan, K., Ely, J. A., Felvus, M., Feroz, F., Flynn, W., Franzen, T. M. O., Geisbusch, J., Genova-Santos, R., Grainge, K. J. B., Grainger, W. F., Hammett, D., Hobson, M. P., Holler, C. M., Hurley-Walker, N., Jilley, R., Kaneko, T., Kneissl, R., Lancaster, K., Lasenby, A. N., Marshall, P. J., Newton, F., Norris, O., Northrop, I., Odell, D. M., Olamaie, M., Pober, Y. C. Perrott J. C., Pooley, G. G., Pospieszalski, M. W., Quy, V., Rodriguez-Gonzalvez, C., Saunders, R. D. E., Scaife, A. M. M., Schammel, M. P., Schofield, J., Scott, P. F., Shaw, C., Smith, H., Titterington, D. J., Velic, M., Waldram, E. M., West, S., Wood, B. A., Yassin, G., and Zwart, J. T. L.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present an interesting Sunyaev-Zel'dovich (SZ) detection in the first of the Arcminute Microkelvin Imager (AMI) 'blind', degree-square fields to have been observed down to our target sensitivity of 100{\mu}Jy/beam. In follow-up deep pointed observations the SZ effect is detected with a maximum peak decrement greater than 8 \times the thermal noise. No corresponding emission is visible in the ROSAT all-sky X-ray survey and no cluster is evident in the Palomar all-sky optical survey. Compared with existing SZ images of distant clusters, the extent is large (\approx 10') and complex; our analysis favours a model containing two clusters rather than a single cluster. Our Bayesian analysis is currently limited to modelling each cluster with an ellipsoidal or spherical beta-model, which do not do justice to this decrement. Fitting an ellipsoid to the deeper candidate we find the following. (a) Assuming that the Evrard et al. (2002) approximation to Press & Schechter (1974) correctly gives the number density of clusters as a function of mass and redshift, then, in the search area, the formal Bayesian probability ratio of the AMI detection of this cluster is 7.9 \times 10^4:1; alternatively assuming Jenkins et al. (2001) as the true prior, the formal Bayesian probability ratio of detection is 2.1 \times 10^5:1. (b) The cluster mass is MT,200 = 5.5+1.2\times 10^14h-1M\odot. (c) Abandoning a physical model with num- -1.3 70 ber density prior and instead simply modelling the SZ decrement using a phenomenological {\beta}-model of temperature decrement as a function of angular distance, we find a central SZ temperature decrement of -295+36 {\mu}K - this allows for CMB primary anisotropies, receiver -15 noise and radio sources. We are unsure if the cluster system we observe is a merging system or two separate clusters., Comment: accepted MNRAS. 12 pages, 9 figures
Published: 2010
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19. First Season QUIET Observations: Measurements of CMB Polarization Power Spectra at 43 GHz in the Multipole Range 25 <= ell <= 475

Author: QUIET Collaboration, Bischoff, C., Brizius, A., Buder, I., Chinone, Y., Cleary, K., Dumoulin, R. N., Kusaka, A., Monsalve, R., Næss, S. K., Newburgh, L. B., Reeves, R., Smith, K. M., Wehus, I. K., Zuntz, J. A., Zwart, J. T. L., Bronfman, L., Bustos, R., Church, S. E., Dickinson, C., Eriksen, H. K., Ferreira, P. G., Gaier, T., Gundersen, J. O., Hasegawa, M., Hazumi, M., Huffenberger, K. M., Jones, M. E., Kangaslahti, P., Kapner, D. J., Lawrence, C. R., Limon, M., May, J., McMahon, J. J., Miller, A. D., Nguyen, H., Nixon, G. W., Pearson, T. J., Piccirillo, L., Radford, S. J. E., Readhead, A. C. S., Richards, J. L., Samtleben, D., Seiffert, M., Shepherd, M. C., Staggs, S. T., Tajima, O., Thompson, K. L., Vanderlinde, K., Williamson, R., and Winstein, B.
Subjects: Astrophysics - Cosmology and Extragalactic Astrophysics
Abstract: The Q/U Imaging ExperimenT (QUIET) employs coherent receivers at 43GHz and 95GHz, operating on the Chajnantor plateau in the Atacama Desert in Chile, to measure the anisotropy in the polarization of the CMB. QUIET primarily targets the B modes from primordial gravitational waves. The combination of these frequencies gives sensitivity to foreground contributions from diffuse Galactic synchrotron radiation. Between 2008 October and 2010 December, >10,000hours of data were collected, first with the 19-element 43GHz array (3458hours) and then with the 90-element 95GHz array. Each array observes the same four fields, selected for low foregrounds, together covering ~1000deg^2. This paper reports initial results from the 43GHz receiver which has an array sensitivity to CMB fluctuations of 69uK sqrt(s). The data were extensively studied with a large suite of null tests before the power spectra, determined with two independent pipelines, were examined. Analysis choices, including data selection, were modified until the null tests passed. Cross correlating maps with different telescope pointings is used to eliminate a bias. This paper reports the EE, BB and EB power spectra in the multipole range ell=25-475. With the exception of the lowest multipole bin for one of the fields, where a polarized foreground, consistent with Galactic synchrotron radiation, is detected with 3sigma significance, the E-mode spectrum is consistent with the LCDM model, confirming the only previous detection of the first acoustic peak. The B-mode spectrum is consistent with zero, leading to a measurement of the tensor-to-scalar ratio of r=0.35+1.06-0.87. The combination of a new time-stream double-demodulation technique, Mizuguchi-Dragone optics, natural sky rotation, and frequent boresight rotation leads to the lowest level of systematic contamination in the B-mode power so far reported, below the level of r=0.1, Comment: 19 pages, 14 figures, higher quality figures are available at http://quiet.uchicago.edu/results/index.html; Fixed a typo and corrected statistical error values used as a reference in Figure 14, showing our systematic uncertainties (unchanged) vs. multipole; Revision to ApJ accepted version, this paper should be cited as "QUIET Collaboration et al. (2011)"
Published: 2010
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20. An excess of emission in the dark cloud LDN 1111 with the Arcminute Microkelvin Imager

Author: Consortium, AMI, Scaife, A. M. M., Hurley-Walker, N., Green, D. A., Davies, M. L., Grainge, K. J. B., Hobson, M. P., Lasenby, A. N., Lopez-Caniego, M., Pooley, G. G., Saunders, R. D. E., Scott, P. F., Titterington, D. J., Waldram, E. M., and Zwart, J. T. L.
Subjects: Astrophysics
Abstract: We present observations of the Lynds' dark nebula LDN 1111 made at microwave frequencies between 14.6 and 17.2 GHz with the Arcminute Microkelvin Imager (AMI). We find emission in this frequency band in excess of a thermal free--free spectrum extrapolated from data at 1.4 GHz with matched uv-coverage. This excess is > 15 sigma above the predicted emission. We fit the measured spectrum using the spinning dust model of Drain & Lazarian (1998a) and find the best fitting model parameters agree well with those derived from Scuba data for this object by Visser et al. (2001)., Comment: accepted MNRAS
Published: 2008
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21. Bayesian modelling of clusters of galaxies from multi-frequency pointed Sunyaev--Zel'dovich observations

Author: Feroz, F., Hobson, M. P., Zwart, J. T. L., Saunders, R. D. E., and Grainge, K. J. B.
Subjects: Astrophysics
Abstract: We present a Bayesian approach to modelling galaxy clusters using multi-frequency pointed observations from telescopes that exploit the Sunyaev--Zel'dovich effect. We use the recently developed MultiNest technique (Feroz, Hobson & Bridges, 2008) to explore the high-dimensional parameter spaces and also to calculate the Bayesian evidence. This permits robust parameter estimation as well as model comparison. Tests on simulated Arcminute Microkelvin Imager observations of a cluster, in the presence of primary CMB signal, radio point sources (detected as well as an unresolved background) and receiver noise, show that our algorithm is able to analyse jointly the data from six frequency channels, sample the posterior space of the model and calculate the Bayesian evidence very efficiently on a single processor. We also illustrate the robustness of our detection process by applying it to a field with radio sources and primordial CMB but no cluster, and show that indeed no cluster is identified. The extension of our methodology to the detection and modelling of multiple clusters in multi-frequency SZ survey data will be described in a future work., Comment: 12 pages, 7 figures, submitted to MNRAS
Published: 2008
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22. The Arcminute Microkelvin Imager

Author: Consortium, AMI, Zwart, J. T. L., Barker, R. W., Biddulph, P., Bly, D., Boysen, R. C., Brown, A. R., Clementson, C., Crofts, M., Culverhouse, T. L., Czeres, J., Dace, R. J., Davies, M. L., D'Alessandro, R., Doherty, P., Duggan, K., Ely, J. A., Felvus, M., Feroz, F., Flynn, W., Franzen, T. M. O., Geisbüsch, J., Génova-Santos, R., Grainge, K. J. B., Grainger, W. F., Hammett, D., Hills, R. E., Hobson, M. P., Holler, C. M., Hurley-Walker, N., Jilley, R., Jones, M. E., Kaneko, T., Kneissl, R., Lancaster, K., Lasenby, A. N., Marshall, P. J., Newton, F., Norris, O., Northrop, I., Odell, D. M., Pober, J. C., Pooley, G. G., Quy, V., Rodríguez-Gonzálvez, C., Saunders, R. D. E., Scaife, A. M., Schofield, J., Scott, P. F., Shaw, C., Shimwell, T. W., Smith, H., Taylor, A. C., Titterington, D. J., Velić, M., Waldram, E. M., West, S., Wood, B. A., and Yassin, G.
Subjects: Astrophysics
Abstract: The Arcminute Microkelvin Imager is a pair of interferometer arrays operating with six frequency channels spanning 13.9-18.2 GHz, with very high sensitivity to angular scales 30''-10'. The telescope is aimed principally at Sunyaev-Zel'dovich imaging of clusters of galaxies. We discuss the design of the telescope and describe and explain its electronic and mechanical systems., Comment: 15 pages, 13 figures. Submitted to MNRAS
Published: 2008
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23. AMI limits on 15 GHz excess emission in northern HII regions

Author: Scaife, A. M. M., Hurley-Walker, N., Davies, M. L., Duffett-Smith, P. J., Feroz, F., Grainge, K. J. B., Green, D. A., Hobson, M. P., Kaneko, T., Lasenby, A. N., Pooley, G. G., Saunders, R. D. E., Scott, P. F., Titterington, D. J., Waldram, E. M., and Zwart, J.
Subjects: Astrophysics
Abstract: We present observations between 14.2 and 17.9 GHz of sixteen Galactic HII regions made with the Arcminute Microkelvin Imager (AMI). In conjunction with data from the literature at lower radio frequencies we investigate the possibility of a spinning dust component in the spectra of these objects. We conclude that there is no significant evidence for spinning dust towards these sources and measure an average spectral index of 0.15+/-0.07 between 1.4 and 17.9 GHz for the sample., Comment: accepted MNRAS
Published: 2007
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24. High-significance Sunyaev-Zel'dovich measurement: Abell 1914 seen with the Arcminute Microkelvin Imager

Author: AMI Collaboration, Barker, R., Biddulph, P., Bly, D., Boysen, R., Brown, A., Clementson, C., Crofts, M., Culverhouse, T., Czeres, J., Dace, R., D'Alessandro, R., Doherty, P., Duffett-Smith, P., Duggan, K., Ely, J., Felvus, M., Flynn, W., Geisbuesch, J., Grainge, K., Grainger, W., Hammet, D., Hills, R., Hobson, M., Holler, C., Jilley, R., Jones, M., Kaneko, T., Kneissl, R., Lancaster, K., Lasenby, A., Marshall, P., Newton, F., Norris, O., Northrop, I., Pooley, G., Quy, V., Saunders, R., Scaife, A., Schofield, J., Scott, P., Shaw, C., Taylor, A., Titterington, D., Velic, M., Waldram, E., West, S., Wood, B., Yassin, G., and Zwart, J.
Subjects: Astrophysics
Abstract: We report the first detection of a Sunyaev-Zel'dovich (S-Z) decrement with the Arcminute Microkelvin Imager (AMI). We have made commissioning observations towards the cluster A1914 and have measured an integrated flux density of -8.61 mJy in a uv-tapered map with noise level 0.19 mJy/beam. We find that the spectrum of the decrement, measured in the six channels between 13.5-18GHz, is consistent with that expected for a S-Z effect. The sensitivity of the telescope is consistent with the figures used in our simulations of cluster surveys with AMI., Comment: 5 pages, 6 figures, submitted to MNRAS Letters
Published: 2005
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25. Incidence and outcomes of uterine rupture in women with unscarred, preterm or prelabour uteri: data from the international network of obstetric survey systems

Author: Vandenberghe, G, Vierin, A, Bloemenkamp, K, Berlage, S, Colmorn, L, Deneux-Tharaux, C, Donati, S, Gissler, M, Knight, M, Langhoff-Roos, J, Lindqvist, PG, Maier, B, van Roosmalen, J, Zwart, J, Roelens, K, and Systems), INOSS (the International Network of Obstetrics Survey
Abstract: Objective Analysis of atypical cases of uterine rupture, namely, uterine rupture occurring in unscarred, preterm or prelabour uteri. Design Descriptive multi-country population-based study. Setting Ten high-income countries within the International Network of Obstetric Survey Systems. Population Women with unscarred, preterm or prelabour ruptured uteri. Methods We merged prospectively collected individual patient data in ten population-based studies of women with complete uterine rupture. In this analysis, we focused on women with uterine rupture of unscarred, preterm or prelabour ruptured uteri. Main Outcome Measures Incidence, women's characteristics, presentation and maternal and perinatal outcome. Results We identified 357 atypical uterine ruptures in 3 064 923 women giving birth. Estimated incidence was 0.2 per 10 000 women (95% CI 0.2–0.3) in the unscarred uteri, 0.5 (95% CI 0.5–0.6) in the preterm uteri, 0.7 (95% CI 0.6–0.8) in the prelabour uteri, and 0.5 (95% CI 0.4–0.5) in the group with no previous caesarean. Atypical uterine rupture resulted in peripartum hysterectomy in 66 women (18.5%, 95% CI 14.3–23.5%), three maternal deaths (0.84%, 95% CI 0.17–2.5%) and perinatal death in 62 infants (19.7%, 95% CI 15.1–25.3%). Conclusions Uterine rupture in preterm, prelabour or unscarred uteri are extremely uncommon but were associated with severe maternal and perinatal outcome. We found a mix of risk factors in unscarred uteri, most preterm uterine ruptures occurred in caesarean-scarred uteri and most prelabour uterine ruptures in ‘otherwise’ scarred uteri. This study may increase awareness among clinicians and raise suspicion of the possibility of uterine rupture under these less expected conditions.
Published: 2023

26. The International Network of Obstetric Survey Systems Study of Uterine Rupture: A Descriptive Multicountry Population-based Study

Author: Vandenberghe, G., Bloemenkamp, K., Berlage, S., Colmorn, L., Deneux-Tharaux, C., Gissler, M., Knight, M., Langhoff-Roos, J., Lindqvist, P.G., Oberaigner, W., Van Roosmalen, J., Zwart, J., and Roelens, K.
Published: 2019
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27. Binational confidential enquiry of maternal deaths due to postpartum hemorrhage in France and the Netherlands: Lessons learned through the perspective of a different context of care

Author: de Vries, P. L. M., primary, van den Akker, T., additional, Bloemenkamp, K. W. M., additional, Grossetti, E., additional, Rigouzzo, A., additional, Saucedo, M., additional, Verspyck, E., additional, Zwart, J., additional, and Deneux‐Tharaux, C., additional
Published: 2023
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28. Uitdagingen bij klimaatadaptatie vragen om zowel duidelijke normen als flexibiliteit : Technische concepten bieden uitkomst in stedelijke gebieden : case studie

Author: Zwart, J., Henckens, G., Tolk, L., Zwart, J., Henckens, G., and Tolk, L.
Abstract: De huidige trend in het klimaatbeleid is voor een belangrijk deel gericht op het optimaal benutten van de kansen om water zoveel mogelijk vast te houden. Dit verkleint de belasting van het riool- en oppervlaktewatersysteem tijdens hevige piekbuien. Tegelijkertijd kan het water worden gebruikt om het grondwater aan te vullen door middel van infiltratie. Een andere trend is het zoveel mogelijk vergroenen van de buitenruimte. Maar: zowel infiltreren als vergroenen kan in bepaalde situaties zeer ongewenste gevolgen hebben.
Published: 2023

29. Binational confidential enquiry of maternal deaths due to postpartum hemorrhage in France and the Netherlands: Lessons learned through the perspective of a different context of care

Author: MS Verloskunde, Child Health, de Vries, P L M, van den Akker, T, Bloemenkamp, K W M, Grossetti, E, Rigouzzo, A, Saucedo, M, Verspyck, E, Zwart, J, Deneux-Tharaux, C, MS Verloskunde, Child Health, de Vries, P L M, van den Akker, T, Bloemenkamp, K W M, Grossetti, E, Rigouzzo, A, Saucedo, M, Verspyck, E, Zwart, J, and Deneux-Tharaux, C
Published: 2023

30. Hacking Limnology Workshops and DSOS23: Growing a Workforce for the Nexus of Data Science, Open Science, and the Aquatic Sciences

Author: Meyer, M. F., Harlan, M. E., Hensley, R. T., Zhan, Q., Börekçi, N. S., Bucak, T., Cramer, A. N., Feldbauer, J., Ladwig, R., Mesman, J. P., Oleksy, I. A., Pilla, R. M., Zwart, J. A., Calamita, E., Gubbins, N. J., Lofton, M. E., Maciel, D. A., Marzolf, N. S., Olsson, F., Thellman, A. N., Thomas, R. Quinn, Vlah, M. J., Meyer, M. F., Harlan, M. E., Hensley, R. T., Zhan, Q., Börekçi, N. S., Bucak, T., Cramer, A. N., Feldbauer, J., Ladwig, R., Mesman, J. P., Oleksy, I. A., Pilla, R. M., Zwart, J. A., Calamita, E., Gubbins, N. J., Lofton, M. E., Maciel, D. A., Marzolf, N. S., Olsson, F., Thellman, A. N., Thomas, R. Quinn, and Vlah, M. J.
Published: 2023

31. Influence of ergonomic factors on peripheral neuropathy under HAV exposure

Author: Schulze, D G, primary, Nilsen, K B, additional, Clemm, T, additional, Grotle, M, additional, Zwart, J A, additional, Ulvestad, B, additional, and Nordby, K C, additional
Published: 2022
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32. Een zwangere vrouw met maagkanker en placentaire metastasen

Author: Kleijn, T. G., Scholten, I., Knol, H. M., Zwart, J. J., Hoogland, A. M., and Faculteit Medische Wetenschappen/UMCG
Abstract: BACKGROUND: About 200 pregnant women in the Netherlands are yearly diagnosed with cancer. Pregnant women with cancer are often diagnosed later than non-pregnant women because symptoms of cancer are common during pregnancy and may elude suspicion. We report a patient with gastric carcinoma masquerading as hyperemesis gravidarum. CASE DESCRIPTION: A 39-year-old pregnant woman was admitted at 25 weeks' gestation for the evaluation of persistent nausea, vomiting and weight loss (29 kg) since the beginning of her pregnancy. A presumptive diagnosis of hyperemesis gravidarum was made. Endoscopic examination was not performed. At 28 weeks' gestation caesarean was performed due to fetal distress and revealed a gastric tumour with abnormalities of the omentum. Microscopic examination of the omentum and placental specimen demonstrated poorly differentiated adenocarcinoma cells. CONCLUSION: This case illustrates that endoscopic examination should be conducted in pregnant patients presenting with persistent gastrointestinal symptoms for the differential diagnosis of hyperemesis gravidarum.
Published: 2022

33. Can machine learning accelerate process understanding and decision-relevant predictions of river water quality?

Author: Varadharajan, C, Varadharajan, C, Appling, AP, Arora, B, Christianson, DS, Hendrix, VC, Kumar, V, Lima, AR, Müller, J, Oliver, S, Ombadi, M, Perciano, T, Sadler, JM, Weierbach, H, Willard, JD, Xu, Z, Zwart, J, Varadharajan, C, Varadharajan, C, Appling, AP, Arora, B, Christianson, DS, Hendrix, VC, Kumar, V, Lima, AR, Müller, J, Oliver, S, Ombadi, M, Perciano, T, Sadler, JM, Weierbach, H, Willard, JD, Xu, Z, and Zwart, J
Abstract: The global decline of water quality in rivers and streams has resulted in a pressing need to design new watershed management strategies. Water quality can be affected by multiple stressors including population growth, land use change, global warming, and extreme events, with repercussions on human and ecosystem health. A scientific understanding of factors affecting riverine water quality and predictions at local to regional scales, and at sub-daily to decadal timescales are needed for optimal management of watersheds and river basins. Here, we discuss how machine learning (ML) can enable development of more accurate, computationally tractable, and scalable models for analysis and predictions of river water quality. We review relevant state-of-the art applications of ML for water quality models and discuss opportunities to improve the use of ML with emerging computational and mathematical methods for model selection, hyperparameter optimization, incorporating process knowledge into ML models, improving explainablity, uncertainty quantification, and model-data integration. We then present considerations for using ML to address water quality problems given their scale and complexity, available data and computational resources, and stakeholder needs. When combined with decades of process understanding, interdisciplinary advances in knowledge-guided ML, information theory, data integration, and analytics can help address fundamental science questions and enable decision-relevant predictions of riverine water quality.
Published: 2022

34. Lessons learned from the perinatal audit of uterine rupture in the Netherlands: A mixed-method study

Author: Rosman, Ageeth N., Dillen, J. van, Zwart, J., Overtoom, Evelien, Schaap, Timme, Bloemenkamp, Kitty, Akker, Thomas van den, Rosman, Ageeth N., Dillen, J. van, Zwart, J., Overtoom, Evelien, Schaap, Timme, Bloemenkamp, Kitty, and Akker, Thomas van den
Abstract: Contains fulltext : 253169.pdf (Publisher’s version ) (Open Access)
Published: 2022

35. Stroke genetics informs drug discovery and risk prediction across ancestries

Author: Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Lee, J-M, Cheng, Y-C, Meschia, JF, Chen, WM, Sale, MM, Zonderman, AB, Evans, MK, Wilson, JG, Correa, A, Traylor, M, Lewis, CM, Reiner, A, Haessler, J, Langefeld, CD, Gottesman, RF, Yaffe, K, Liu, YM, Kooperberg, C, Lange, LA, Furie, KL, Arnett, DK, Benavente, OR, Grewal, RP, Peddareddygari, LR, Hveem, K, Lindstrom, S, Wang, L, Smith, EN, Gordon, W, Vlieg, AVH, de Andrade, M, Brody, JA, Pattee, JW, Brumpton, BM, Suchon, P, Chen, M-H, Frazer, KA, Turman, C, Germain, M, MacDonald, J, Braekkan, SK, Armasu, SM, Pankratz, N, Jackson, RD, Nielsen, JB, Giulianin, F, Puurunen, MK, Ibrahim, M, Heckbert, SR, Bammler, TK, McCauley, BM, Taylor, KD, Pankow, JS, Reiner, AP, Gabrielsen, ME, Deleuze, J-F, O'Donnell, CJ, Kim, J, McKnight, B, Kraft, P, Hansen, J-B, Rosendaal, FR, Heit, JA, Tang, W, Morange, P-E, Johnson, AD, Kabrhel, C, van Dijk, EJ, Koudstaal, PJ, Luijckx, G-J, Nederkoorn, PJ, van Oostenbrugge, RJ, Visser, MC, Wermer, MJH, Kappelle, LJ, Esko, T, Metspalu, A, Magi, R, Nelis, M, Levi, CR, Maguire, J, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rannikmae, K, Schmidt, R, Slowik, A, Pera, J, Thijs, VNS, Lindgren, AG, Ilinca, A, Melander, O, Engstrom, G, Rexrode, KM, Rothwell, PM, Stanne, TM, Johnson, JA, Danesh, J, Butterworth, AS, Heitsch, L, Boncoraglio, GB, Kubo, M, Pezzini, A, Rolfs, A, Giese, A-K, Weir, D, Ross, OA, Lemmons, R, Soderholm, M, Cushman, M, Jood, K, McDonough, CW, Bell, S, Linkohr, B, Lee, T-H, Putaala, J, Lopez, OL, Carty, CL, Jian, X, Schminke, U, Cullell, N, Delgado, P, Ibanez, L, Krupinski, J, Lioutas, V, Matsuda, K, Montaner, J, Muino, E, Roquer, J, Sarnowski, C, Sattar, N, Sibolt, G, Teumer, A, Rutten-Jacobs, L, Kanai, M, Gretarsdottir, S, Rost, NS, Yusuf, S, Almgren, P, Ay, H, Bevan, S, Brown, RD, Carrera, C, Buring, JE, Chen, W-M, Cotlarciuc, I, de Bakker, PIW, DeStefano, AL, den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gustafsson, S, Hassan, A, Holliday, EG, Howard, G, Hsu, F-C, Ingelsson, E, Harris, TB, Kissela, BM, Kleindorfer, DO, Langenberg, C, Leys, D, Lin, W-Y, Lorentzen, E, Magnusson, PK, McArdle, PF, Pulit, SL, Rice, K, Sakaue, S, Sapkota, BR, Tanislav, C, Thorleifsson, G, Thorsteinsdottir, U, Tzourio, C, van Duijn, CM, Walters, M, Wareham, NJ, Amin, N, Aparicio, HJ, Attia, J, Beiser, AS, Berr, C, Bustamante, M, Caso, V, Choi, SH, Chowhan, A, Dartigues, J-F, Delavaran, H, Dorr, M, Ford, I, Gurpreet, WS, Hamsten, A, Hozawa, A, Ingelsson, M, Iwasaki, M, Kaffashian, S, Kalra, L, Kjartansson, O, Kloss, M, Labovitz, DL, Laurie, CC, Lind, L, Lindgren, CM, Makoto, H, Minegishi, N, Morris, AP, Mueller-Nurasyid, M, Norrving, B, Ogishima, S, Parati, EA, Pedersen, NL, Perola, M, Jousilahti, P, Pileggi, S, Rabionet, R, Riba-Llena, I, Ribases, M, Romero, JR, Rudd, AG, Sarin, A-P, Sarju, R, Satoh, M, Sawada, N, Sigurdsson, A, Smith, A, Stine, OC, Stott, DJ, Strauch, K, Takai, T, Tanaka, H, Touze, E, Tsugane, S, Uitterlinden, AG, Valdimarsson, EM, van der Lee, SJ, Wakai, K, Williams, SR, Wolfe, CDA, Wong, Q, Yamaji, T, Sanghera, DK, Stefansson, K, Martinez-Majander, N, Sobue, K, Soriano-Tarraga, C, Volzke, H, Akpa, O, Sarfo, FS, Akpalu, A, Obiako, R, Wahab, K, Osaigbovo, G, Owolabi, L, Komolafe, M, Jenkins, C, Arulogun, O, Ogbole, G, Adeoye, AM, Akinyemi, J, Agunloye, A, Fakunle, AG, Uvere, E, Olalere, A, Adebajo, OJ, Chen, J, Clarke, R, Collins, R, Guo, Y, Wang, C, Lv, J, Peto, R, Chen, Y, Fairhurst-Hunter, Z, Hill, M, Pozarickij, A, Schmidt, D, Stevens, B, Turnbull, I, Yu, C, Nagai, A, Murakami, Y, Shiroma, EJ, Sigurdsson, S, Ghanbari, M, Boerwinkle, E, Fongang, B, Wang, R, Ikram, MK, Volker, U, de Laat, KF, van Norden, AGW, de Kort, PL, Vermeer, SE, Brouwers, PJAM, Gons, RAR, den Heijer, T, van Dijk, GW, van Rooij, FGW, Aamodt, AH, Skogholt, AH, Willer, CJ, Heuch, I, Hagen, K, Fritsche, LG, Pedersen, LM, Ellekjaer, H, Zhou, W, Martinsen, AE, Kristoffersen, ES, Thomas, LF, Kleinschnitz, C, Frantz, S, Ungethum, K, Gallego-Fabrega, C, Lledos, M, Llucia-Carol, L, Sobrino, T, Campos, F, Castillo, J, Freijo, M, Arenillas, JF, Obach, V, Alvarez-Sabin, J, Molina, CA, Ribo, M, Munoz-Narbona, L, Lopez-Cancio, E, Millan, M, Diaz-Navarro, R, Vives-Bauza, C, Serrano-Heras, G, Segura, T, Dhar, R, Delgado-Mederos, R, Prats-Sanchez, L, Camps-Renom, P, Blay, N, Sumoy, L, Marti-Fabregas, J, Schnohr, P, Jensen, GB, Benn, M, Afzal, S, Kamstrup, PR, van Setten, J, van der Laan, SW, Vonk, JMJ, Kim, B-J, Curtze, S, Tiainen, M, Kinnunen, J, Menon, V, Sung, YJ, Saillour-Glenisson, F, Gravel, S, Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Lee, J-M, Cheng, Y-C, Meschia, JF, Chen, WM, Sale, MM, Zonderman, AB, Evans, MK, Wilson, JG, Correa, A, Traylor, M, Lewis, CM, Reiner, A, Haessler, J, Langefeld, CD, Gottesman, RF, Yaffe, K, Liu, YM, Kooperberg, C, Lange, LA, Furie, KL, Arnett, DK, Benavente, OR, Grewal, RP, Peddareddygari, LR, Hveem, K, Lindstrom, S, Wang, L, Smith, EN, Gordon, W, Vlieg, AVH, de Andrade, M, Brody, JA, Pattee, JW, Brumpton, BM, Suchon, P, Chen, M-H, Frazer, KA, Turman, C, Germain, M, MacDonald, J, Braekkan, SK, Armasu, SM, Pankratz, N, Jackson, RD, Nielsen, JB, Giulianin, F, Puurunen, MK, Ibrahim, M, Heckbert, SR, Bammler, TK, McCauley, BM, Taylor, KD, Pankow, JS, Reiner, AP, Gabrielsen, ME, Deleuze, J-F, O'Donnell, CJ, Kim, J, McKnight, B, Kraft, P, Hansen, J-B, Rosendaal, FR, Heit, JA, Tang, W, Morange, P-E, Johnson, AD, Kabrhel, C, van Dijk, EJ, Koudstaal, PJ, Luijckx, G-J, Nederkoorn, PJ, van Oostenbrugge, RJ, Visser, MC, Wermer, MJH, Kappelle, LJ, Esko, T, Metspalu, A, Magi, R, Nelis, M, Levi, CR, Maguire, J, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rannikmae, K, Schmidt, R, Slowik, A, Pera, J, Thijs, VNS, Lindgren, AG, Ilinca, A, Melander, O, Engstrom, G, Rexrode, KM, Rothwell, PM, Stanne, TM, Johnson, JA, Danesh, J, Butterworth, AS, Heitsch, L, Boncoraglio, GB, Kubo, M, Pezzini, A, Rolfs, A, Giese, A-K, Weir, D, Ross, OA, Lemmons, R, Soderholm, M, Cushman, M, Jood, K, McDonough, CW, Bell, S, Linkohr, B, Lee, T-H, Putaala, J, Lopez, OL, Carty, CL, Jian, X, Schminke, U, Cullell, N, Delgado, P, Ibanez, L, Krupinski, J, Lioutas, V, Matsuda, K, Montaner, J, Muino, E, Roquer, J, Sarnowski, C, Sattar, N, Sibolt, G, Teumer, A, Rutten-Jacobs, L, Kanai, M, Gretarsdottir, S, Rost, NS, Yusuf, S, Almgren, P, Ay, H, Bevan, S, Brown, RD, Carrera, C, Buring, JE, Chen, W-M, Cotlarciuc, I, de Bakker, PIW, DeStefano, AL, den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gustafsson, S, Hassan, A, Holliday, EG, Howard, G, Hsu, F-C, Ingelsson, E, Harris, TB, Kissela, BM, Kleindorfer, DO, Langenberg, C, Leys, D, Lin, W-Y, Lorentzen, E, Magnusson, PK, McArdle, PF, Pulit, SL, Rice, K, Sakaue, S, Sapkota, BR, Tanislav, C, Thorleifsson, G, Thorsteinsdottir, U, Tzourio, C, van Duijn, CM, Walters, M, Wareham, NJ, Amin, N, Aparicio, HJ, Attia, J, Beiser, AS, Berr, C, Bustamante, M, Caso, V, Choi, SH, Chowhan, A, Dartigues, J-F, Delavaran, H, Dorr, M, Ford, I, Gurpreet, WS, Hamsten, A, Hozawa, A, Ingelsson, M, Iwasaki, M, Kaffashian, S, Kalra, L, Kjartansson, O, Kloss, M, Labovitz, DL, Laurie, CC, Lind, L, Lindgren, CM, Makoto, H, Minegishi, N, Morris, AP, Mueller-Nurasyid, M, Norrving, B, Ogishima, S, Parati, EA, Pedersen, NL, Perola, M, Jousilahti, P, Pileggi, S, Rabionet, R, Riba-Llena, I, Ribases, M, Romero, JR, Rudd, AG, Sarin, A-P, Sarju, R, Satoh, M, Sawada, N, Sigurdsson, A, Smith, A, Stine, OC, Stott, DJ, Strauch, K, Takai, T, Tanaka, H, Touze, E, Tsugane, S, Uitterlinden, AG, Valdimarsson, EM, van der Lee, SJ, Wakai, K, Williams, SR, Wolfe, CDA, Wong, Q, Yamaji, T, Sanghera, DK, Stefansson, K, Martinez-Majander, N, Sobue, K, Soriano-Tarraga, C, Volzke, H, Akpa, O, Sarfo, FS, Akpalu, A, Obiako, R, Wahab, K, Osaigbovo, G, Owolabi, L, Komolafe, M, Jenkins, C, Arulogun, O, Ogbole, G, Adeoye, AM, Akinyemi, J, Agunloye, A, Fakunle, AG, Uvere, E, Olalere, A, Adebajo, OJ, Chen, J, Clarke, R, Collins, R, Guo, Y, Wang, C, Lv, J, Peto, R, Chen, Y, Fairhurst-Hunter, Z, Hill, M, Pozarickij, A, Schmidt, D, Stevens, B, Turnbull, I, Yu, C, Nagai, A, Murakami, Y, Shiroma, EJ, Sigurdsson, S, Ghanbari, M, Boerwinkle, E, Fongang, B, Wang, R, Ikram, MK, Volker, U, de Laat, KF, van Norden, AGW, de Kort, PL, Vermeer, SE, Brouwers, PJAM, Gons, RAR, den Heijer, T, van Dijk, GW, van Rooij, FGW, Aamodt, AH, Skogholt, AH, Willer, CJ, Heuch, I, Hagen, K, Fritsche, LG, Pedersen, LM, Ellekjaer, H, Zhou, W, Martinsen, AE, Kristoffersen, ES, Thomas, LF, Kleinschnitz, C, Frantz, S, Ungethum, K, Gallego-Fabrega, C, Lledos, M, Llucia-Carol, L, Sobrino, T, Campos, F, Castillo, J, Freijo, M, Arenillas, JF, Obach, V, Alvarez-Sabin, J, Molina, CA, Ribo, M, Munoz-Narbona, L, Lopez-Cancio, E, Millan, M, Diaz-Navarro, R, Vives-Bauza, C, Serrano-Heras, G, Segura, T, Dhar, R, Delgado-Mederos, R, Prats-Sanchez, L, Camps-Renom, P, Blay, N, Sumoy, L, Marti-Fabregas, J, Schnohr, P, Jensen, GB, Benn, M, Afzal, S, Kamstrup, PR, van Setten, J, van der Laan, SW, Vonk, JMJ, Kim, B-J, Curtze, S, Tiainen, M, Kinnunen, J, Menon, V, Sung, YJ, Saillour-Glenisson, F, and Gravel, S
Abstract: Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
Published: 2022

36. A saturated map of common genetic variants associated with human height

Author: Yengo, L, Vedantam, S, Marouli, E, Sidorenko, J, Bartell, E, Sakaue, S, Graff, M, Eliasen, AU, Jiang, Y, Raghavan, S, Miao, J, Arias, JD, Graham, SE, Mukamel, RE, Spracklen, CN, Yin, X, Chen, S-H, Ferreira, T, Highland, HH, Ji, Y, Karaderi, T, Lin, K, Lull, K, Malden, DE, Medina-Gomez, C, Machado, M, Moore, A, Rueger, S, Sim, X, Vrieze, S, Ahluwalia, TS, Akiyama, M, Allison, MA, Alvarez, M, Andersen, MK, Ani, A, Appadurai, V, Arbeeva, L, Bhaskar, S, Bielak, LF, Bollepalli, S, Bonnycastle, LL, Bork-Jensen, J, Bradfield, JP, Bradford, Y, Braund, PS, Brody, JA, Burgdorf, KS, Cade, BE, Cai, H, Cai, Q, Campbell, A, Canadas-Garre, M, Catamo, E, Chai, J-F, Chai, X, Chang, L-C, Chang, Y-C, Chen, C-H, Chesi, A, Choi, SH, Chung, R-H, Cocca, M, Concas, MP, Couture, C, Cuellar-Partida, G, Danning, R, Daw, EW, Degenhard, F, Delgado, GE, Delitala, A, Demirkan, A, Deng, X, Devineni, P, Dietl, A, Dimitriou, M, Dimitrov, L, Dorajoo, R, Ekici, AB, Engmann, JE, Fairhurst-Hunter, Z, Farmaki, A-E, Faul, JD, Fernandez-Lopez, J-C, Forer, L, Francescatto, M, Freitag-Wolf, S, Fuchsberger, C, Galesloot, TE, Gao, Y, Gao, Z, Geller, F, Giannakopoulou, O, Giulianini, F, Gjesing, AP, Goel, A, Gordon, SD, Gorski, M, Grove, J, Guo, X, Gustafsson, S, Haessler, J, Hansen, TF, Havulinna, AS, Haworth, SJ, He, J, Heard-Costa, N, Hebbar, P, Hindy, G, Ho, Y-LA, Hofer, E, Holliday, E, Horn, K, Hornsby, WE, Hottenga, J-J, Huang, H, Huang, J, Huerta-Chagoya, A, Huffman, JE, Hung, Y-J, Huo, S, Hwang, MY, Iha, H, Ikeda, DD, Isono, M, Jackson, AU, Jager, S, Jansen, IE, Johansson, I, Jonas, JB, Jonsson, A, Jorgensen, T, Kalafati, I-P, Kanai, M, Kanoni, S, Karhus, LL, Kasturiratne, A, Katsuya, T, Kawaguchi, T, Kember, RL, Kentistou, KA, Kim, H-N, Kim, YJ, Kleber, ME, Knol, MJ, Kurbasic, A, Lauzon, M, Le, P, Lea, R, Lee, J-Y, Leonard, HL, Li, SA, Li, X, Liang, J, Lin, H, Lin, S-Y, Liu, J, Liu, X, Lo, KS, Long, J, Lores-Motta, L, Luan, J, Lyssenko, V, Lyytikainen, L-P, Mahajan, A, Mamakou, V, Mangino, M, Manichaikul, A, Marten, J, Mattheisen, M, Mavarani, L, McDaid, AF, Meidtner, K, Melendez, TL, Mercader, JM, Milaneschi, Y, Miller, JE, Millwood, IY, Mishra, PP, Mitchell, RE, Mollehave, LT, Morgan, A, Mucha, S, Munz, M, Nakatochi, M, Nelson, CP, Nethander, M, Nho, CW, Nielsen, AA, Nolte, IM, Nongmaithem, SS, Noordam, R, Ntalla, I, Nutile, T, Pandit, A, Christofidou, P, Parna, K, Pauper, M, Petersen, ERB, Petersen, L, Pitkanen, N, Polasek, O, Poveda, A, Preuss, MH, Pyarajan, S, Raffield, LM, Rakugi, H, Ramirez, J, Rasheed, A, Raven, D, Rayner, NW, Riveros, C, Rohde, R, Ruggiero, D, Ruotsalainen, SE, Ryan, KA, Sabater-Lleal, M, Saxena, R, Scholz, M, Sendamarai, A, Shen, B, Shi, J, Shin, JH, Sidore, C, Sitlani, CM, Slieker, RKC, Smit, RAJ, Smith, A, Smith, JA, Smyth, LJ, Southam, LE, Steinthorsdottir, V, Sun, L, Takeuchi, F, Tallapragada, D, Taylor, KD, Tayo, BO, Tcheandjieu, C, Terzikhan, N, Tesolin, P, Teumer, A, Theusch, E, Thompson, DJ, Thorleifsson, G, Timmers, PRHJ, Trompet, S, Turman, C, Vaccargiu, S, van der Laan, SW, van der Most, PJ, van Klinken, JB, van Setten, J, Verma, SS, Verweij, N, Veturi, Y, Wang, CA, Wang, C, Wang, L, Wang, Z, Warren, HR, Wei, WB, Wickremasinghe, AR, Wielscher, M, Wiggins, KL, Winsvold, BS, Wong, A, Wu, Y, Wuttke, M, Xia, R, Xie, T, Yamamoto, K, Yang, J, Yao, J, Young, H, Yousri, NA, Yu, L, Zeng, L, Zhang, W, Zhang, X, Zhao, J-H, Zhao, W, Zhou, W, Zimmermann, ME, Zoledziewska, M, Adair, LS, Adams, HHH, Aguilar-Salinas, CA, Al-Mulla, F, Arnett, DK, Asselbergs, FW, Asvold, BO, Attia, J, Banas, B, Bandinelli, S, Bennett, DA, Bergler, T, Bharadwaj, D, Biino, G, Bisgaard, H, Boerwinkle, E, Boger, CA, Bonnelykke, K, Boomsma, D, Borglum, AD, Borja, JB, Bouchard, C, Bowden, DW, Brandslund, I, Brumpton, B, Buring, JE, Caulfield, MJ, Chambers, JC, Chandak, GR, Chanock, SJ, Chaturvedi, N, Chen, Y-DI, Chen, Z, Cheng, C-Y, Christophersen, IE, Ciullo, M, Cole, JW, Collins, FS, Cooper, RS, Cruz, M, Cucca, F, Cupples, LA, Cutler, MJ, Damrauer, SM, Dantoft, TM, de Borst, GJ, de Groot, LCPGM, De Jager, PL, de Kleijn, DP, de Silva, HJ, Dedoussis, G, den Hollander, A, Du, S, Easton, DF, Elders, PJM, Eliassen, AH, Ellinor, PT, Elmstahl, S, Erdmann, J, Evans, MK, Fatkin, D, Feenstra, B, Feitosa, MF, Ferrucci, L, Ford, I, Fornage, M, Franke, A, Franks, PW, Freedman, B, Gasparini, P, Gieger, C, Girotto, G, Goddard, ME, Golightly, YM, Gonzalez-Villalpando, C, Gordon-Larsen, P, Grallert, H, Grant, SFA, Grarup, N, Griffiths, L, Gudnason, V, Haiman, C, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayward, C, Heckbert, SR, Heng, C-K, Hengstenberg, C, Hewitt, AW, Hishigaki, H, Hoyng, CB, Huang, PL, Huang, W, Hunt, SC, Hveem, K, Hypponen, E, Iacono, WG, Ichihara, S, Ikram, MA, Isasi, CR, Jackson, RD, Jarvelin, M-R, Jin, Z-B, Jockel, K-H, Joshi, PK, Jousilahti, P, Jukema, JW, Kahonen, M, Kamatani, Y, Kang, KD, Kaprio, J, Kardia, SLR, Karpe, F, Kato, N, Kee, F, Kessler, T, Khera, A, Khor, CC, Kiemeney, LALM, Kim, B-J, Kim, EK, Kim, H-L, Kirchhof, P, Kivimaki, M, Koh, W-P, Koistinen, HA, Kolovou, GD, Kooner, JS, Kooperberg, C, Kottgen, A, Kovacs, P, Kraaijeveld, A, Kraft, P, Krauss, RM, Kumari, M, Kutalik, Z, Laakso, M, Lange, LA, Langenberg, C, Launer, LJ, Le Marchand, L, Lee, H, Lee, NR, Lehtimaki, T, Li, H, Li, L, Lieb, W, Lin, X, Lind, L, Linneberg, A, Liu, C-T, Loeffler, M, London, B, Lubitz, SA, Lye, SJ, Mackey, DA, Magi, R, Magnusson, PKE, Marcus, GM, Vidal, PM, Martin, NG, Marz, W, Matsuda, F, McGarrah, RW, McGue, M, McKnight, AJ, Medland, SE, Mellstrom, D, Metspalu, A, Mitchell, BD, Mitchell, P, Mook-Kanamori, DO, Morris, AD, Mucci, LA, Munroe, PB, Nalls, MA, Nazarian, S, Nelson, AE, Neville, MJ, Newton-Cheh, C, Nielsen, CS, Nothen, MM, Ohlsson, C, Oldehinkel, AJ, Orozco, L, Pahkala, K, Pajukanta, P, Palmer, CNA, Parra, EJ, Pattaro, C, Pedersen, O, Pennell, CE, Penninx, BWJH, Perusse, L, Peters, A, Peyser, PA, Porteous, DJ, Posthuma, D, Power, C, Pramstaller, PP, Province, MA, Qi, Q, Qu, J, Rader, DJ, Raitakari, OT, Ralhan, S, Rallidis, LS, Rao, DC, Redline, S, Reilly, DF, Reiner, AP, Rhee, SY, Ridker, PM, Rienstra, M, Ripatti, S, Ritchie, MD, Roden, DM, Rosendaal, FR, Rotter, J, Rudan, I, Rutters, F, Sabanayagam, C, Saleheen, D, Salomaa, V, Samani, NJ, Sanghera, DK, Sattar, N, Schmidt, B, Schmidt, H, Schmidt, R, Schulze, MB, Schunkert, H, Scott, LJ, Scott, RJ, Sever, P, Shiroma, EJ, Shoemaker, MB, Shu, X-O, Simonsick, EM, Sims, M, Singh, JR, Singleton, AB, Sinner, MF, Smith, JG, Snieder, H, Spector, TD, Stampfer, MJ, Stark, KJ, Strachan, DP, t' Hart, LM, Tabara, Y, Tang, H, Tardif, J-C, Thanaraj, TA, Timpson, NJ, Tonjes, A, Tremblay, A, Tuomi, T, Tuomilehto, J, Tusie-Luna, M-T, Uitterlinden, AG, van Dam, RM, van der Harst, P, Van der Velde, N, van Duijn, CM, van Schoor, NM, Vitart, V, Volker, U, Vollenweider, P, Volzke, H, Wacher-Rodarte, NH, Walker, M, Wang, YX, Wareham, NJ, Watanabe, RM, Watkins, H, Weir, DR, Werge, TM, Widen, E, Wilkens, LR, Willemsen, G, Willett, WC, Wilson, JF, Wong, T-Y, Woo, J-T, Wright, AF, Wu, J-Y, Xu, H, Yajnik, CS, Yokota, M, Yuan, J-M, Zeggini, E, Zemel, BS, Zheng, W, Zhu, X, Zmuda, JM, Zonderman, AB, Zwart, J-A, Chasman, D, Cho, YS, Heid, IM, McCarthy, M, Ng, MCY, O'Donnell, CJ, Rivadeneira, F, Thorsteinsdottir, U, Sun, Y, Tai, ES, Boehnke, M, Deloukas, P, Justice, AE, Lindgren, CM, Loos, RJF, Mohlke, KL, North, KE, Stefansson, K, Walters, RG, Winkler, TW, Young, KL, Loh, P-R, Esko, T, Assimes, TL, Auton, A, Abecasis, GR, Willer, CJ, Locke, AE, Berndt, S, Lettre, G, Frayling, TM, Okada, Y, Wood, AR, Visscher, PM, Hirschhorn, JN, Yengo, L, Vedantam, S, Marouli, E, Sidorenko, J, Bartell, E, Sakaue, S, Graff, M, Eliasen, AU, Jiang, Y, Raghavan, S, Miao, J, Arias, JD, Graham, SE, Mukamel, RE, Spracklen, CN, Yin, X, Chen, S-H, Ferreira, T, Highland, HH, Ji, Y, Karaderi, T, Lin, K, Lull, K, Malden, DE, Medina-Gomez, C, Machado, M, Moore, A, Rueger, S, Sim, X, Vrieze, S, Ahluwalia, TS, Akiyama, M, Allison, MA, Alvarez, M, Andersen, MK, Ani, A, Appadurai, V, Arbeeva, L, Bhaskar, S, Bielak, LF, Bollepalli, S, Bonnycastle, LL, Bork-Jensen, J, Bradfield, JP, Bradford, Y, Braund, PS, Brody, JA, Burgdorf, KS, Cade, BE, Cai, H, Cai, Q, Campbell, A, Canadas-Garre, M, Catamo, E, Chai, J-F, Chai, X, Chang, L-C, Chang, Y-C, Chen, C-H, Chesi, A, Choi, SH, Chung, R-H, Cocca, M, Concas, MP, Couture, C, Cuellar-Partida, G, Danning, R, Daw, EW, Degenhard, F, Delgado, GE, Delitala, A, Demirkan, A, Deng, X, Devineni, P, Dietl, A, Dimitriou, M, Dimitrov, L, Dorajoo, R, Ekici, AB, Engmann, JE, Fairhurst-Hunter, Z, Farmaki, A-E, Faul, JD, Fernandez-Lopez, J-C, Forer, L, Francescatto, M, Freitag-Wolf, S, Fuchsberger, C, Galesloot, TE, Gao, Y, Gao, Z, Geller, F, Giannakopoulou, O, Giulianini, F, Gjesing, AP, Goel, A, Gordon, SD, Gorski, M, Grove, J, Guo, X, Gustafsson, S, Haessler, J, Hansen, TF, Havulinna, AS, Haworth, SJ, He, J, Heard-Costa, N, Hebbar, P, Hindy, G, Ho, Y-LA, Hofer, E, Holliday, E, Horn, K, Hornsby, WE, Hottenga, J-J, Huang, H, Huang, J, Huerta-Chagoya, A, Huffman, JE, Hung, Y-J, Huo, S, Hwang, MY, Iha, H, Ikeda, DD, Isono, M, Jackson, AU, Jager, S, Jansen, IE, Johansson, I, Jonas, JB, Jonsson, A, Jorgensen, T, Kalafati, I-P, Kanai, M, Kanoni, S, Karhus, LL, Kasturiratne, A, Katsuya, T, Kawaguchi, T, Kember, RL, Kentistou, KA, Kim, H-N, Kim, YJ, Kleber, ME, Knol, MJ, Kurbasic, A, Lauzon, M, Le, P, Lea, R, Lee, J-Y, Leonard, HL, Li, SA, Li, X, Liang, J, Lin, H, Lin, S-Y, Liu, J, Liu, X, Lo, KS, Long, J, Lores-Motta, L, Luan, J, Lyssenko, V, Lyytikainen, L-P, Mahajan, A, Mamakou, V, Mangino, M, Manichaikul, A, Marten, J, Mattheisen, M, Mavarani, L, McDaid, AF, Meidtner, K, Melendez, TL, Mercader, JM, Milaneschi, Y, Miller, JE, Millwood, IY, Mishra, PP, Mitchell, RE, Mollehave, LT, Morgan, A, Mucha, S, Munz, M, Nakatochi, M, Nelson, CP, Nethander, M, Nho, CW, Nielsen, AA, Nolte, IM, Nongmaithem, SS, Noordam, R, Ntalla, I, Nutile, T, Pandit, A, Christofidou, P, Parna, K, Pauper, M, Petersen, ERB, Petersen, L, Pitkanen, N, Polasek, O, Poveda, A, Preuss, MH, Pyarajan, S, Raffield, LM, Rakugi, H, Ramirez, J, Rasheed, A, Raven, D, Rayner, NW, Riveros, C, Rohde, R, Ruggiero, D, Ruotsalainen, SE, Ryan, KA, Sabater-Lleal, M, Saxena, R, Scholz, M, Sendamarai, A, Shen, B, Shi, J, Shin, JH, Sidore, C, Sitlani, CM, Slieker, RKC, Smit, RAJ, Smith, A, Smith, JA, Smyth, LJ, Southam, LE, Steinthorsdottir, V, Sun, L, Takeuchi, F, Tallapragada, D, Taylor, KD, Tayo, BO, Tcheandjieu, C, Terzikhan, N, Tesolin, P, Teumer, A, Theusch, E, Thompson, DJ, Thorleifsson, G, Timmers, PRHJ, Trompet, S, Turman, C, Vaccargiu, S, van der Laan, SW, van der Most, PJ, van Klinken, JB, van Setten, J, Verma, SS, Verweij, N, Veturi, Y, Wang, CA, Wang, C, Wang, L, Wang, Z, Warren, HR, Wei, WB, Wickremasinghe, AR, Wielscher, M, Wiggins, KL, Winsvold, BS, Wong, A, Wu, Y, Wuttke, M, Xia, R, Xie, T, Yamamoto, K, Yang, J, Yao, J, Young, H, Yousri, NA, Yu, L, Zeng, L, Zhang, W, Zhang, X, Zhao, J-H, Zhao, W, Zhou, W, Zimmermann, ME, Zoledziewska, M, Adair, LS, Adams, HHH, Aguilar-Salinas, CA, Al-Mulla, F, Arnett, DK, Asselbergs, FW, Asvold, BO, Attia, J, Banas, B, Bandinelli, S, Bennett, DA, Bergler, T, Bharadwaj, D, Biino, G, Bisgaard, H, Boerwinkle, E, Boger, CA, Bonnelykke, K, Boomsma, D, Borglum, AD, Borja, JB, Bouchard, C, Bowden, DW, Brandslund, I, Brumpton, B, Buring, JE, Caulfield, MJ, Chambers, JC, Chandak, GR, Chanock, SJ, Chaturvedi, N, Chen, Y-DI, Chen, Z, Cheng, C-Y, Christophersen, IE, Ciullo, M, Cole, JW, Collins, FS, Cooper, RS, Cruz, M, Cucca, F, Cupples, LA, Cutler, MJ, Damrauer, SM, Dantoft, TM, de Borst, GJ, de Groot, LCPGM, De Jager, PL, de Kleijn, DP, de Silva, HJ, Dedoussis, G, den Hollander, A, Du, S, Easton, DF, Elders, PJM, Eliassen, AH, Ellinor, PT, Elmstahl, S, Erdmann, J, Evans, MK, Fatkin, D, Feenstra, B, Feitosa, MF, Ferrucci, L, Ford, I, Fornage, M, Franke, A, Franks, PW, Freedman, B, Gasparini, P, Gieger, C, Girotto, G, Goddard, ME, Golightly, YM, Gonzalez-Villalpando, C, Gordon-Larsen, P, Grallert, H, Grant, SFA, Grarup, N, Griffiths, L, Gudnason, V, Haiman, C, Hakonarson, H, Hansen, T, Hartman, CA, Hattersley, AT, Hayward, C, Heckbert, SR, Heng, C-K, Hengstenberg, C, Hewitt, AW, Hishigaki, H, Hoyng, CB, Huang, PL, Huang, W, Hunt, SC, Hveem, K, Hypponen, E, Iacono, WG, Ichihara, S, Ikram, MA, Isasi, CR, Jackson, RD, Jarvelin, M-R, Jin, Z-B, Jockel, K-H, Joshi, PK, Jousilahti, P, Jukema, JW, Kahonen, M, Kamatani, Y, Kang, KD, Kaprio, J, Kardia, SLR, Karpe, F, Kato, N, Kee, F, Kessler, T, Khera, A, Khor, CC, Kiemeney, LALM, Kim, B-J, Kim, EK, Kim, H-L, Kirchhof, P, Kivimaki, M, Koh, W-P, Koistinen, HA, Kolovou, GD, Kooner, JS, Kooperberg, C, Kottgen, A, Kovacs, P, Kraaijeveld, A, Kraft, P, Krauss, RM, Kumari, M, Kutalik, Z, Laakso, M, Lange, LA, Langenberg, C, Launer, LJ, Le Marchand, L, Lee, H, Lee, NR, Lehtimaki, T, Li, H, Li, L, Lieb, W, Lin, X, Lind, L, Linneberg, A, Liu, C-T, Loeffler, M, London, B, Lubitz, SA, Lye, SJ, Mackey, DA, Magi, R, Magnusson, PKE, Marcus, GM, Vidal, PM, Martin, NG, Marz, W, Matsuda, F, McGarrah, RW, McGue, M, McKnight, AJ, Medland, SE, Mellstrom, D, Metspalu, A, Mitchell, BD, Mitchell, P, Mook-Kanamori, DO, Morris, AD, Mucci, LA, Munroe, PB, Nalls, MA, Nazarian, S, Nelson, AE, Neville, MJ, Newton-Cheh, C, Nielsen, CS, Nothen, MM, Ohlsson, C, Oldehinkel, AJ, Orozco, L, Pahkala, K, Pajukanta, P, Palmer, CNA, Parra, EJ, Pattaro, C, Pedersen, O, Pennell, CE, Penninx, BWJH, Perusse, L, Peters, A, Peyser, PA, Porteous, DJ, Posthuma, D, Power, C, Pramstaller, PP, Province, MA, Qi, Q, Qu, J, Rader, DJ, Raitakari, OT, Ralhan, S, Rallidis, LS, Rao, DC, Redline, S, Reilly, DF, Reiner, AP, Rhee, SY, Ridker, PM, Rienstra, M, Ripatti, S, Ritchie, MD, Roden, DM, Rosendaal, FR, Rotter, J, Rudan, I, Rutters, F, Sabanayagam, C, Saleheen, D, Salomaa, V, Samani, NJ, Sanghera, DK, Sattar, N, Schmidt, B, Schmidt, H, Schmidt, R, Schulze, MB, Schunkert, H, Scott, LJ, Scott, RJ, Sever, P, Shiroma, EJ, Shoemaker, MB, Shu, X-O, Simonsick, EM, Sims, M, Singh, JR, Singleton, AB, Sinner, MF, Smith, JG, Snieder, H, Spector, TD, Stampfer, MJ, Stark, KJ, Strachan, DP, t' Hart, LM, Tabara, Y, Tang, H, Tardif, J-C, Thanaraj, TA, Timpson, NJ, Tonjes, A, Tremblay, A, Tuomi, T, Tuomilehto, J, Tusie-Luna, M-T, Uitterlinden, AG, van Dam, RM, van der Harst, P, Van der Velde, N, van Duijn, CM, van Schoor, NM, Vitart, V, Volker, U, Vollenweider, P, Volzke, H, Wacher-Rodarte, NH, Walker, M, Wang, YX, Wareham, NJ, Watanabe, RM, Watkins, H, Weir, DR, Werge, TM, Widen, E, Wilkens, LR, Willemsen, G, Willett, WC, Wilson, JF, Wong, T-Y, Woo, J-T, Wright, AF, Wu, J-Y, Xu, H, Yajnik, CS, Yokota, M, Yuan, J-M, Zeggini, E, Zemel, BS, Zheng, W, Zhu, X, Zmuda, JM, Zonderman, AB, Zwart, J-A, Chasman, D, Cho, YS, Heid, IM, McCarthy, M, Ng, MCY, O'Donnell, CJ, Rivadeneira, F, Thorsteinsdottir, U, Sun, Y, Tai, ES, Boehnke, M, Deloukas, P, Justice, AE, Lindgren, CM, Loos, RJF, Mohlke, KL, North, KE, Stefansson, K, Walters, RG, Winkler, TW, Young, KL, Loh, P-R, Esko, T, Assimes, TL, Auton, A, Abecasis, GR, Willer, CJ, Locke, AE, Berndt, S, Lettre, G, Frayling, TM, Okada, Y, Wood, AR, Visscher, PM, and Hirschhorn, JN
Abstract: Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.
Published: 2022

37. Stroke genetics informs drug discovery and risk prediction across ancestries (vol 611, pg 115, 2022)

Author: Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, IH, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, IH, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, and Debette, S
Published: 2022

38. Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles

Author: Hautakangas, H. (Heidi), Winsvold, B. S. (Bendik S.), Ruotsalainen, S. E. (Sanni E.), Bjornsdottir, G. (Gyda), Harder, A. V. (Aster V. E.), Kogelman, L. J. (Lisette J. A.), Thomas, L. F. (Laurent F.), Noordam, R. (Raymond), Benner, C. (Christian), Gormley, P. (Padhraig), Artto, V. (Ville), Banasik, K. (Karina), Bjornsdottir, A. (Anna), Boomsma, D. I. (Dorret, I), Brumpton, B. M. (Ben M.), Burgdorf, K. S. (Kristoffer Solvsten), Buring, J. E. (Julie E.), Chalmer, M. A. (Mona Ameri), de Boer, I. (Irene), Dichgans, M. (Martin), Erikstrup, C. (Christian), Färkkilä, M. (Markus), Garbrielsen, M. E. (Maiken Elvestad), Ghanbari, M. (Mohsen), Hagen, K. (Knut), Häppölä, P. (Paavo), Hottenga, J.-J. (Jouke-Jan), Hrafnsdottir, M. G. (Maria G.), Hveem, K. (Kristian), Johnsen, M. B. (Marianne Bakke), Kähönen, M. (Mika), Kristoffersen, E. S. (Espen S.), Kurth, T. (Tobias), Lehtimäki, T. (Terho), Lighart, L. (Lannie), Magnusson, S. H. (Sigurdur H.), Malik, R. (Rainer), Pedersen, O. B. (Ole Birger), Pelzer, N. (Nadine), Penninx, B. W. (Brenda W. J. H.), Ran, C. (Caroline), Ridker, P. M. (Paul M.), Rosendaal, F. R. (Frits R.), Sigurdardottir, G. R. (Gudrun R.), Skogholt, A. H. (Anne Heidi), Sveinsson, O. A. (Olafur A.), Thorgeirsson, T. E. (Thorgeir E.), Ullum, H. (Henrik), Vijfhuizen, L. S. (Lisanne S.), Widen, E. (Elisabeth), van Dijk, K. W. (Ko Willems), International Headache Genetics Consortium, HUNT All-in Headache, Danish Blood Donor Study Genomic Cohort, Aromaa, A. (Arpo), Belin, A. C. (Andrea Carmine), Freilinger, T. (Tobias), Ikram, M. A. (M. Arfan), Järvelin, M.-R. (Marjo-Riitta), Raitakari, O. T. (Olli T.), Terwindt, G. M. (Gisela M.), Kallela, M. (Mikko), Wessman, M. (Maija), Olesen, J. (Jes), Chasman, D. I. (Daniel, I), Nyholt, D. R. (Dale R.), Stefansson, H. (Hreinn), Stefansson, K. (Kari), van den Maagdenberg, A. M. (Arn M. J. M.), Hansen, T. F. (Thomas Folkmann), Ripatti, S. (Samuli), Zwart, J.-A. (John-Anker), Palotie, A. (Aarno), Pirinen, M. (Matti), Hautakangas, H. (Heidi), Winsvold, B. S. (Bendik S.), Ruotsalainen, S. E. (Sanni E.), Bjornsdottir, G. (Gyda), Harder, A. V. (Aster V. E.), Kogelman, L. J. (Lisette J. A.), Thomas, L. F. (Laurent F.), Noordam, R. (Raymond), Benner, C. (Christian), Gormley, P. (Padhraig), Artto, V. (Ville), Banasik, K. (Karina), Bjornsdottir, A. (Anna), Boomsma, D. I. (Dorret, I), Brumpton, B. M. (Ben M.), Burgdorf, K. S. (Kristoffer Solvsten), Buring, J. E. (Julie E.), Chalmer, M. A. (Mona Ameri), de Boer, I. (Irene), Dichgans, M. (Martin), Erikstrup, C. (Christian), Färkkilä, M. (Markus), Garbrielsen, M. E. (Maiken Elvestad), Ghanbari, M. (Mohsen), Hagen, K. (Knut), Häppölä, P. (Paavo), Hottenga, J.-J. (Jouke-Jan), Hrafnsdottir, M. G. (Maria G.), Hveem, K. (Kristian), Johnsen, M. B. (Marianne Bakke), Kähönen, M. (Mika), Kristoffersen, E. S. (Espen S.), Kurth, T. (Tobias), Lehtimäki, T. (Terho), Lighart, L. (Lannie), Magnusson, S. H. (Sigurdur H.), Malik, R. (Rainer), Pedersen, O. B. (Ole Birger), Pelzer, N. (Nadine), Penninx, B. W. (Brenda W. J. H.), Ran, C. (Caroline), Ridker, P. M. (Paul M.), Rosendaal, F. R. (Frits R.), Sigurdardottir, G. R. (Gudrun R.), Skogholt, A. H. (Anne Heidi), Sveinsson, O. A. (Olafur A.), Thorgeirsson, T. E. (Thorgeir E.), Ullum, H. (Henrik), Vijfhuizen, L. S. (Lisanne S.), Widen, E. (Elisabeth), van Dijk, K. W. (Ko Willems), International Headache Genetics Consortium, HUNT All-in Headache, Danish Blood Donor Study Genomic Cohort, Aromaa, A. (Arpo), Belin, A. C. (Andrea Carmine), Freilinger, T. (Tobias), Ikram, M. A. (M. Arfan), Järvelin, M.-R. (Marjo-Riitta), Raitakari, O. T. (Olli T.), Terwindt, G. M. (Gisela M.), Kallela, M. (Mikko), Wessman, M. (Maija), Olesen, J. (Jes), Chasman, D. I. (Daniel, I), Nyholt, D. R. (Dale R.), Stefansson, H. (Hreinn), Stefansson, K. (Kari), van den Maagdenberg, A. M. (Arn M. J. M.), Hansen, T. F. (Thomas Folkmann), Ripatti, S. (Samuli), Zwart, J.-A. (John-Anker), Palotie, A. (Aarno), and Pirinen, M. (Matti)
Abstract: Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.
Published: 2022

39. Global patterns and controls of nutrient immobilization on decomposing cellulose in riverine ecosystems

Author: Costello, D. M. (David M.), Tiegs, S. D. (Scott D.), Boyero, L. (Luz), Canhoto, C. (Cristina), Capps, K. A. (Krista A.), Danger, M. (Michael), Frost, P. C. (Paul C.), Gessner, M. O. (Mark O.), Griffiths, N. A. (Natalie A.), Halvorson, H. M. (Halvor M.), Kuehn, K. A. (Kevin A.), Marcarelli, A. M. (Amy M.), Royer, T. V. (Todd, V), Mathie, D. M. (Devan M.), Albarino, R. J. (Ricardo J.), Arango, C. P. (Clay P.), Aroviita, J. (Jukka), Baxter, C. V. (Colden, V), Bellinger, B. J. (Brent J.), Bruder, A. (Andreas), Burdon, F. J. (Francis J.), Callisto, M. (Marcos), Camacho, A. (Antonio), Colas, F. (Fanny), Cornut, J. (Julien), Crespo-Perez, V. (Veronica), Cross, W. F. (Wyatt F.), Derry, A. M. (Alison M.), Douglas, M. M. (Michael M.), Elosegi, A. (Arturo), Eyto, E. (Elvira), Ferreira, V. (Veronica), Ferriol, C. (Carmen), Fleituch, T. (Tadeusz), Shah, J. J. (Jennifer J. Follstad), Frainer, A. (Andre), Garcia, E. A. (Erica A.), Garcia, L. (Liliana), Garcia, P. E. (Pavel E.), Giling, D. P. (Darren P.), Gonzales-Pomar, R. K. (R. Karina), Graca, M. A. (Manuel A. S.), Grossart, H.-P. (Hans-Peter), Guerold, F. (Francois), Hepp, L. U. (Luiz U.), Higgins, S. N. (Scott N.), Hishi, T. (Takuo), Iniguez-Armijos, C. (Carlos), Iwata, T. (Tomoya), Kirkwood, A. E. (Andrea E.), Koning, A. A. (Aaron A.), Kosten, S. (Sarian), Laudon, H. (Hjalmar), Leavitt, P. R. (Peter R.), Lemes da Silva, A. L. (Aurea L.), Leroux, S. J. (Shawn J.), LeRoy, C. J. (Carri J.), Lisi, P. J. (Peter J.), Masese, F. O. (Frank O.), McIntyre, P. B. (Peter B.), McKie, B. G. (Brendan G.), Medeiros, A. O. (Adriana O.), Milisa, M. (Marko), Miyake, Y. (Yo), Mooney, R. J. (Robert J.), Muotka, T. (Timo), Nimptsch, J. (Jorge), Paavola, R. (Riku), Pardo, I. (Isabel), Parnikoza, I. Y. (Ivan Y.), Patrick, C. J. (Christopher J.), Peeters, E. T. (Edwin T. H. M.), Pozo, J. (Jesus), Reid, B. (Brian), Richardson, J. S. (John S.), Rincon, J. (Jose), Risnoveanu, G. (Geta), Robinson, C. T. (Christopher T.), Santamans, A. C. (Anna C.), Simiyu, G. M. (Gelas M.), Skuja, A. (Agnija), Smykla, J. (Jerzy), Sponseller, R. A. (Ryan A.), Teixeira-de Mello, F. (Franco), Vilbaste, S. (Sirje), Villanueva, V. D. (Veronica D.), Webster, J. R. (Jackson R.), Woelfl, S. (Stefan), Xenopoulos, M. A. (Marguerite A.), Yates, A. G. (Adam G.), Yule, C. M. (Catherine M.), Zhang, Y. (Yixin), Zwart, J. A. (Jacob A.), Costello, D. M. (David M.), Tiegs, S. D. (Scott D.), Boyero, L. (Luz), Canhoto, C. (Cristina), Capps, K. A. (Krista A.), Danger, M. (Michael), Frost, P. C. (Paul C.), Gessner, M. O. (Mark O.), Griffiths, N. A. (Natalie A.), Halvorson, H. M. (Halvor M.), Kuehn, K. A. (Kevin A.), Marcarelli, A. M. (Amy M.), Royer, T. V. (Todd, V), Mathie, D. M. (Devan M.), Albarino, R. J. (Ricardo J.), Arango, C. P. (Clay P.), Aroviita, J. (Jukka), Baxter, C. V. (Colden, V), Bellinger, B. J. (Brent J.), Bruder, A. (Andreas), Burdon, F. J. (Francis J.), Callisto, M. (Marcos), Camacho, A. (Antonio), Colas, F. (Fanny), Cornut, J. (Julien), Crespo-Perez, V. (Veronica), Cross, W. F. (Wyatt F.), Derry, A. M. (Alison M.), Douglas, M. M. (Michael M.), Elosegi, A. (Arturo), Eyto, E. (Elvira), Ferreira, V. (Veronica), Ferriol, C. (Carmen), Fleituch, T. (Tadeusz), Shah, J. J. (Jennifer J. Follstad), Frainer, A. (Andre), Garcia, E. A. (Erica A.), Garcia, L. (Liliana), Garcia, P. E. (Pavel E.), Giling, D. P. (Darren P.), Gonzales-Pomar, R. K. (R. Karina), Graca, M. A. (Manuel A. S.), Grossart, H.-P. (Hans-Peter), Guerold, F. (Francois), Hepp, L. U. (Luiz U.), Higgins, S. N. (Scott N.), Hishi, T. (Takuo), Iniguez-Armijos, C. (Carlos), Iwata, T. (Tomoya), Kirkwood, A. E. (Andrea E.), Koning, A. A. (Aaron A.), Kosten, S. (Sarian), Laudon, H. (Hjalmar), Leavitt, P. R. (Peter R.), Lemes da Silva, A. L. (Aurea L.), Leroux, S. J. (Shawn J.), LeRoy, C. J. (Carri J.), Lisi, P. J. (Peter J.), Masese, F. O. (Frank O.), McIntyre, P. B. (Peter B.), McKie, B. G. (Brendan G.), Medeiros, A. O. (Adriana O.), Milisa, M. (Marko), Miyake, Y. (Yo), Mooney, R. J. (Robert J.), Muotka, T. (Timo), Nimptsch, J. (Jorge), Paavola, R. (Riku), Pardo, I. (Isabel), Parnikoza, I. Y. (Ivan Y.), Patrick, C. J. (Christopher J.), Peeters, E. T. (Edwin T. H. M.), Pozo, J. (Jesus), Reid, B. (Brian), Richardson, J. S. (John S.), Rincon, J. (Jose), Risnoveanu, G. (Geta), Robinson, C. T. (Christopher T.), Santamans, A. C. (Anna C.), Simiyu, G. M. (Gelas M.), Skuja, A. (Agnija), Smykla, J. (Jerzy), Sponseller, R. A. (Ryan A.), Teixeira-de Mello, F. (Franco), Vilbaste, S. (Sirje), Villanueva, V. D. (Veronica D.), Webster, J. R. (Jackson R.), Woelfl, S. (Stefan), Xenopoulos, M. A. (Marguerite A.), Yates, A. G. (Adam G.), Yule, C. M. (Catherine M.), Zhang, Y. (Yixin), and Zwart, J. A. (Jacob A.)
Abstract: Microbes play a critical role in plant litter decomposition and influence the fate of carbon in rivers and riparian zones. When decomposing low-nutrient plant litter, microbes acquire nitrogen (N) and phosphorus (P) from the environment (i.e., nutrient immobilization), and this process is potentially sensitive to nutrient loading and changing climate. Nonetheless, environmental controls on immobilization are poorly understood because rates are also influenced by plant litter chemistry, which is coupled to the same environmental factors. Here we used a standardized, low-nutrient organic matter substrate (cotton strips) to quantify nutrient immobilization at 100 paired stream and riparian sites representing 11 biomes worldwide. Immobilization rates varied by three orders of magnitude, were greater in rivers than riparian zones, and were strongly correlated to decomposition rates. In rivers, P immobilization rates were controlled by surface water phosphate concentrations, but N immobilization rates were not related to inorganic N. The N:P of immobilized nutrients was tightly constrained to a molar ratio of 10:1 despite wide variation in surface water N:P. Immobilization rates were temperature-dependent in riparian zones but not related to temperature in rivers. However, in rivers nutrient supply ultimately controlled whether microbes could achieve the maximum expected decomposition rate at a given temperature. Collectively, we demonstrated that exogenous nutrient supply and immobilization are critical control points for decomposition of organic matter.
Published: 2022

40. Confidential enquiry into maternal deaths in the Netherlands, 2006–2018

Author: Kallianidis, A. F., Schutte, J. M., Schuringa, L. E. M., Beenakkers, I. C. M., Bloemenkamp, K. W. M., Braams-Lisman, B. A. M., Cornette, J., Kuppens, S. M., Rietveld, A. L., Schaap, T., Stekelenburg, J., Zwart, J. J., van den Akker, T., Kallianidis, A. F., Schutte, J. M., Schuringa, L. E. M., Beenakkers, I. C. M., Bloemenkamp, K. W. M., Braams-Lisman, B. A. M., Cornette, J., Kuppens, S. M., Rietveld, A. L., Schaap, T., Stekelenburg, J., Zwart, J. J., and van den Akker, T.
Abstract: Introduction: To calculate the maternal mortality ratio (MMR) for 2006–2018 in the Netherlands and compare this with 1993–2005, and to describe women’s characteristics, causes of death and improvable factors. Material and Methods: We performed a nationwide, cohort study of all maternal deaths between January 1, 2006 and December 31, 2018 reported to the Audit Committee Maternal Mortality and Morbidity. Main outcome measures were the national MMR and causes of death. Results: Overall MMR was 6.2 per 100 000 live births, a decrease from 12.1 in 1993–2005 (risk ratio [RR] 0.5). Women with a non-western ethnic background had an increased MMR compared with Dutch women (MMR 6.5 vs. 5.0, RR 1.3). The MMR was increased among women with a background from Surinam/Dutch Antilles (MMR 14.7, RR 2.9). Half of all women had an uncomplicated medical history (79/161, 49.1%). Of 171 pregnancy-related deaths within 1 year postpartum, 102 (60%) had a direct and 69 (40%) an indirect cause of death. Leading causes within 42 days postpartum were cardiac disease (n = 21, 14.9%), hypertensive disorders (n = 20, 14.2%) and thrombosis (n = 19, 13.5%). Up to 1 year postpartum, the most common cause of death was cardiac disease (n = 32, 18.7%). Improvable care factors were identified in 76 (47.5%) of all deaths. Conclusions: Maternal mortality halved in 2006–2018 compared with 1993–2005. Cardiac disease became the main cause. In almost half of all deaths, improvable factors were identified and women with a background from Surinam/Dutch Antilles had a threefold increased risk of death compared with Dutch women without a background of migration.
Published: 2022

41. SARS-CoV-2 infection in pregnancy during the first wave of COVID-19 in the Netherlands: a prospective nationwide population-based cohort study (NethOSS)

Author: MS Verloskunde, Geboortecentrum voorzitterschap, Child Health, Overtoom, E. M., Rosman, A. N., Zwart, J. J., Vogelvang, T. E., Schaap, T. P., van den Akker, T., Bloemenkamp, K. W.M., MS Verloskunde, Geboortecentrum voorzitterschap, Child Health, Overtoom, E. M., Rosman, A. N., Zwart, J. J., Vogelvang, T. E., Schaap, T. P., van den Akker, T., and Bloemenkamp, K. W.M.
Published: 2022

42. Effects of spatial fMRI resolution on the classification of naturalistic movies

Author: Mandelkow, H., de Zwart, J. A., and Duyn, J. H.
Published: 2017
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43. The Neck Disability Index (NDI) and its correlation with quality of life and mental health measures among patients with single-level cervical disc disease scheduled for surgery

Author: Sundseth, J., Kolstad, F., Johnsen, L. G., Pripp, A. H., Nygaard, O. P., Andresen, H., Fredriksli, O. A., Myrseth, E., Züchner, M., and Zwart, J. A.
Published: 2015
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44. Multi‐Task Deep Learning of Daily Streamflow and Water Temperature

Author: Sadler, J. M., primary, Appling, A. P., additional, Read, J. S., additional, Oliver, S. K., additional, Jia, X., additional, Zwart, J. A., additional, and Kumar, V., additional
Published: 2022
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45. Rare SLC13A1 variants associate with intervertebral disc disorder highlighting role of sulfate in disc pathology

Author: Bjornsdottir, G. Stefansdottir, L. Thorleifsson, G. Sulem, P. Norland, K. Ferkingstad, E. Oddsson, A. Zink, F. Lund, S.H. Nawaz, M.S. Bragi Walters, G. Skuladottir, A.T. Gudjonsson, S.A. Einarsson, G. Halldorsson, G.H. Bjarnadottir, V. Sveinbjornsson, G. Helgadottir, A. Styrkarsdottir, U. Gudmundsson, L.J. Pedersen, O.B. Hansen, T.F. Werge, T. Banasik, K. Troelsen, A. Skou, S.T. Thørner, L.W. Erikstrup, C. Nielsen, K.R. Mikkelsen, S. Andersen, S. Brunak, S. Burgdorf, K. Hjalgrim, H. Jemec, G. Jennum, P. Johansson, P.I. Nielsen, K.R. Nyegaard, M. Bruun, M.T. Pedersen, O.B. Dinh, K.M. Sørensen, E. Ostrowski, S. Johansson, P.I. Gudbjartsson, D. Stefánsson, H. Þorsteinsdóttir, U. Larsen, M.A.H. Didriksen, M. Sækmose, S. Zeggini, E. Hatzikotoulas, K. Southam, L. Gilly, A. Barysenka, A. van Meurs, J.B.J. Boer, C.G. Uitterlinden, A.G. Styrkársdóttir, U. Stefánsdóttir, L. Jonsson, H. Ingvarsson, T. Esko, T. Mägi, R. Teder-Laving, M. Ikegawa, S. Terao, C. Takuwa, H. Meulenbelt, I. Coutinho de Almeida, R. Kloppenburg, M. Tuerlings, M. Slagboom, P.E. Nelissen, R.R.G.H.H. Valdes, A.M. Mangino, M. Tsezou, A. Zengini, E. Alexiadis, G. Babis, G.C. Cheah, K.S.E. Wu, T.T. Samartzis, D. Cheung, J.P.Y. Sham, P.C. Kraft, P. Kang, J.H. Hveem, K. Zwart, J.-A. Luetge, A. Skogholt, A.H. Johnsen, M.B. Thomas, L.F. Winsvold, B. Gabrielsen, M.E. Lee, M.T.M. Zhang, Y. Lietman, S.A. Shivakumar, M. Smith, G.D. Tobias, J.H. Hartley, A. Gaunt, T.R. Zheng, J. Wilkinson, J.M. Steinberg, J. Morris, A.P. Jonsdottir, I. Bjornsson, A. Olafsson, I.H. Ulfarsson, E. Blondal, J. Vikingsson, A. Brunak, S. Ostrowski, S.R. Ullum, H. Thorsteinsdottir, U. Stefansson, H. Gudbjartsson, D.F. Thorgeirsson, T.E. Stefansson, K. DBDS Genetic Consortium GO Consortium
Abstract: Back pain is a common and debilitating disorder with largely unknown underlying biology. Here we report a genome-wide association study of back pain using diagnoses assigned in clinical practice; dorsalgia (119,100 cases, 909,847 controls) and intervertebral disc disorder (IDD) (58,854 cases, 922,958 controls). We identify 41 variants at 33 loci. The most significant association (ORIDD = 0.92, P = 1.6 × 10−39; ORdorsalgia = 0.92, P = 7.2 × 10−15) is with a 3’UTR variant (rs1871452-T) in CHST3, encoding a sulfotransferase enzyme expressed in intervertebral discs. The largest effects on IDD are conferred by rare (MAF = 0.07 − 0.32%) loss-of-function (LoF) variants in SLC13A1, encoding a sodium-sulfate co-transporter (LoF burden OR = 1.44, P = 3.1 × 10−11); variants that also associate with reduced serum sulfate. Genes implicated by this study are involved in cartilage and bone biology, as well as neurological and inflammatory processes. © 2022, The Author(s).
Published: 2022

46. Caesarean section rates in subgroups of women and perinatal outcomes

Author: Zhang, J, Geerts, C, Hukkelhoven, C, Offerhaus, P, Zwart, J, and de Jonge, A
Published: 2016
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47. Early menarche and chronic widespread musculoskeletal complaints- Results from the HUNT study

Author: Kvalheim, S., Sandvik, L., Winsvold, B., Hagen, K., and Zwart, J.-A.
Published: 2016
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48. Influence of ergonomic factors on peripheral neuropathy under HAV exposure.

Author: Schulze, D G, Nilsen, K B, Clemm, T, Grotle, M, Zwart, J A, Ulvestad, B, and Nordby, K C
Subjects: PERIPHERAL neuropathy, NERVE conduction studies, MEDIAN nerve, CARPAL tunnel syndrome, ULNAR nerve
Abstract: Background Hand–arm vibration (HAV) is a risk factor for carpal tunnel syndrome (CTS) and ulnar neuropathy at the elbow (UNE). It is unclear how ergonomic factors influence the relationship between HAV exposure and CTS and UNE. Aims We aimed to assess the relationship between cumulative HAV exposure and CTS and UNE in workers exposed to HAV from two tools with different ergonomic profiles. Methods We performed nerve conduction studies (NCSs) of the sensory and motor median and ulnar nerves and recorded symptoms indicating CTS and UNE in workers exposed to HAV from impact wrenches or from rock drills. Exposure was measured as cumulative lifetime exposure. We used linear regression adjusted for age and body mass index to assess linear relationships. Results Sixty-five workers participated (33 rock drill and 32 impact wrench operators). We found inverse linear associations between cumulative HAV exposure and median nerve sensory conduction velocity in impact wrench operators and ulnar nerve motor conduction velocity in rock drill operators (beta of 0.63 and 0.75). Based on NCS findings and symptoms, seven impact wrench operators had CTS and one UNE, and four rock drill operators had CTS and six UNE. Conclusions Our findings indicate that ergonomic factors influence the development of CTS and UNE under HAV exposure. The ergonomic profile seems to influence which type of neuropathy workers exposed to HAV will develop. Design of occupational exposure guidelines and future studies should be based on ergonomic profile and exposure characteristics for different tools and not merely HAV. [ABSTRACT FROM AUTHOR]
Published: 2023
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49. Aspirin versus placebo for the prevention of recurrent preterm labor: APRIL trial

Author: Landman, A., de Boer, M., Visser, L., Nijman, T., Hemels, M., Naaktgeboren, C., Jansen-van der Weide, M., Mol, B., van Laar, J., Papatsonis, D., Bekker, M., van Drongelen, J., van Pampus, M., Sueters, M., van der Ham, D., Sikkema, M., Zwart, J., Huisjes, A., van Huizen, M., Kleiverda, G., Boon, J., Franssen, M., Hermes, W., Visser, H., de Groot, C., Oudijk, M., Obstetrics and gynaecology, Pathology, Gastroenterology and hepatology, Urology, Internal medicine, and Amsterdam Reproduction & Development
Published: 2021

50. Blood pressure as a risk factor for headache and migraine: a prospective population-based study

Author: Fagernæs, C. F., Heuch, I., Zwart, J.-A., Winsvold, B. S., Linde, M., and Hagen, K.
Published: 2015
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