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419 results on '"Ollila, A. M"'

1. Genetic drivers and cellular selection of female mosaic X chromosome loss

Author

Liu, Aoxing, Genovese, Giulio, Zhao, Yajie, Pirinen, Matti, Zekavat, Seyedeh M., Kentistou, Katherine A., Yang, Zhiyu, Yu, Kai, Vlasschaert, Caitlyn, Liu, Xiaoxi, Brown, Derek W., Hudjashov, Georgi, Gorman, Bryan R., Dennis, Joe, Zhou, Weiyin, Momozawa, Yukihide, Pyarajan, Saiju, Tuzov, Valdislav, Pajuste, Fanny-Dhelia, Aavikko, Mervi, Sipilä, Timo P., Ghazal, Awaisa, Huang, Wen-Yi, Freedman, Neal D., Song, Lei, Gardner, Eugene J., Sankaran, Vijay G., Palotie, Aarno, Ollila, Hanna M., Tukiainen, Taru, Chanock, Stephen J., Mägi, Reedik, Natarajan, Pradeep, Daly, Mark J., Bick, Alexander, McCarroll, Steven A., Terao, Chikashi, Loh, Po-Ru, Ganna, Andrea, Perry, John R. B., and Machiela, Mitchell J.

Published
2024
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2. Intense alteration on early Mars revealed by high-aluminum rocks at Jezero crater

Author

Royer, C., Bedford, C. C., Johnson, J. R., Horgan, B. H. N., Broz, A., Forni, O., Connell, S., Wiens, R. C., Mandon, L., Kathir, B. S., Hausrath, E. M., Udry, A., Madariaga, J. M., Dehouck, E., Anderson, R. B., Beck, P., Beyssac, O., Clavé, É., Clegg, S. M., Cloutis, E., Fouchet, T., Gabriel, T. S. J., Garczynski, B. J., Klidaras, A., Manelski, H. T., Mayhew, L., Núñez, J., Ollila, A. M., Schröder, S., Simon, J. I., Wolf, U., Stack, K. M., Cousin, A., and Maurice, S.

Published
2024
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5. Author Correction: Genetic drivers and cellular selection of female mosaic X chromosome loss

Author

Liu, Aoxing, Genovese, Giulio, Zhao, Yajie, Pirinen, Matti, Zekavat, Seyedeh M., Kentistou, Katherine A., Yang, Zhiyu, Yu, Kai, Vlasschaert, Caitlyn, Liu, Xiaoxi, Brown, Derek W., Hudjashov, Georgi, Gorman, Bryan R., Dennis, Joe, Zhou, Weiyin, Momozawa, Yukihide, Pyarajan, Saiju, Tuzov, Valdislav, Pajuste, Fanny-Dhelia, Aavikko, Mervi, Sipilä, Timo P., Ghazal, Awaisa, Huang, Wen-Yi, Freedman, Neal D., Song, Lei, Gardner, Eugene J., Sankaran, Vijay G., Palotie, Aarno, Ollila, Hanna M., Tukiainen, Taru, Chanock, Stephen J., Mägi, Reedik, Natarajan, Pradeep, Daly, Mark J., Bick, Alexander, McCarroll, Steven A., Terao, Chikashi, Loh, Po-Ru, Ganna, Andrea, Perry, John R. B., and Machiela, Mitchell J.

Published
2024
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6. Narcolepsy risk loci outline role of T cell autoimmunity and infectious triggers in narcolepsy

Author

Ollila, Hanna M, Sharon, Eilon, Lin, Ling, Sinnott-Armstrong, Nasa, Ambati, Aditya, Yogeshwar, Selina M, Hillary, Ryan P, Jolanki, Otto, Faraco, Juliette, Einen, Mali, Luo, Guo, Zhang, Jing, Han, Fang, Yan, Han, Dong, Xiao Song, Li, Jing, Zhang, Jun, Hong, Seung-Chul, Kim, Tae Won, Dauvilliers, Yves, Barateau, Lucie, Lammers, Gert Jan, Fronczek, Rolf, Mayer, Geert, Santamaria, Joan, Arnulf, Isabelle, Knudsen-Heier, Stine, Bredahl, May Kristin Lyamouri, Thorsby, Per Medbøe, Plazzi, Giuseppe, Pizza, Fabio, Moresco, Monica, Crowe, Catherine, Van den Eeden, Stephen K, Lecendreux, Michel, Bourgin, Patrice, Kanbayashi, Takashi, Martínez-Orozco, Francisco J, Peraita-Adrados, Rosa, Benetó, Antonio, Montplaisir, Jacques, Desautels, Alex, Huang, Yu-Shu, Jennum, Poul, Nevsimalova, Sona, Kemlink, David, Iranzo, Alex, Overeem, Sebastiaan, Wierzbicka, Aleksandra, Geisler, Peter, Sonka, Karel, Honda, Makoto, Högl, Birgit, Stefani, Ambra, Coelho, Fernando Morgadinho, Mantovani, Vilma, Feketeova, Eva, Wadelius, Mia, Eriksson, Niclas, Smedje, Hans, Hallberg, Pär, Hesla, Per Egil, Rye, David, Pelin, Zerrin, Ferini-Strambi, Luigi, Bassetti, Claudio L, Mathis, Johannes, Khatami, Ramin, Aran, Adi, Nampoothiri, Sheela, Olsson, Tomas, Kockum, Ingrid, Partinen, Markku, Perola, Markus, Kornum, Birgitte R, Rueger, Sina, Winkelmann, Juliane, Miyagawa, Taku, Toyoda, Hiromi, Khor, Seik-Soon, Shimada, Mihoko, Tokunaga, Katsushi, Rivas, Manuel, Pritchard, Jonathan K, Risch, Neil, Kutalik, Zoltan, O’Hara, Ruth, Hallmayer, Joachim, Ye, Chun Jimmie, and Mignot, Emmanuel J

Subjects
Medical Microbiology, Biomedical and Clinical Sciences, Clinical Sciences, Biological Sciences, Prevention, Vaccine Related, Influenza, Autoimmune Disease, Immunization, Pneumonia & Influenza, Emerging Infectious Diseases, Infectious Diseases, 2.1 Biological and endogenous factors, Aetiology, Infection, Inflammatory and immune system, Good Health and Well Being, Humans, Autoimmunity, Influenza, Human, Influenza A Virus, H1N1 Subtype, Autoimmune Diseases, Influenza Vaccines, Narcolepsy, FinnGen
Abstract

Narcolepsy type 1 (NT1) is caused by a loss of hypocretin/orexin transmission. Risk factors include pandemic 2009 H1N1 influenza A infection and immunization with Pandemrix®. Here, we dissect disease mechanisms and interactions with environmental triggers in a multi-ethnic sample of 6,073 cases and 84,856 controls. We fine-mapped GWAS signals within HLA (DQ0602, DQB1*03:01 and DPB1*04:02) and discovered seven novel associations (CD207, NAB1, IKZF4-ERBB3, CTSC, DENND1B, SIRPG, PRF1). Significant signals at TRA and DQB1*06:02 loci were found in 245 vaccination-related cases, who also shared polygenic risk. T cell receptor associations in NT1 modulated TRAJ*24, TRAJ*28 and TRBV*4-2 chain-usage. Partitioned heritability and immune cell enrichment analyses found genetic signals to be driven by dendritic and helper T cells. Lastly comorbidity analysis using data from FinnGen, suggests shared effects between NT1 and other autoimmune diseases. NT1 genetic variants shape autoimmunity and response to environmental triggers, including influenza A infection and immunization with Pandemrix®.

Published
2023

8. Genome-wide association study identifies human genetic variants associated with fatal outcome from Lassa fever

Author

Kotliar, Dylan, Raju, Siddharth, Tabrizi, Shervin, Odia, Ikponmwosa, Goba, Augustine, Momoh, Mambu, Sandi, John Demby, Nair, Parvathy, Phelan, Eric, Tariyal, Ridhi, Eromon, Philomena E., Mehta, Samar, Robles-Sikisaka, Refugio, Siddle, Katherine J., Stremlau, Matt, Jalloh, Simbirie, Gire, Stephen K., Winnicki, Sarah, Chak, Bridget, Schaffner, Stephen F., Pauthner, Matthias, Karlsson, Elinor K., Chapin, Sarah R., Kennedy, Sharon G., Branco, Luis M., Kanneh, Lansana, Vitti, Joseph J., Broodie, Nisha, Gladden-Young, Adrianne, Omoniwa, Omowunmi, Jiang, Pan-Pan, Yozwiak, Nathan, Heuklom, Shannon, Moses, Lina M., Akpede, George O., Asogun, Danny A., Rubins, Kathleen, Kales, Susan, Happi, Anise N., Iruolagbe, Christopher O., Dic-Ijiewere, Mercy, Iraoyah, Kelly, Osazuwa, Omoregie O., Okonkwo, Alexander K., Kunz, Stefan, McCormick, Joseph B., Khan, S. Humarr, Honko, Anna N., Lander, Eric S., Oldstone, Michael B. A., Hensley, Lisa, Folarin, Onikepe A., Okogbenin, Sylvanus A., Günther, Stephan, Ollila, Hanna M., Tewhey, Ryan, Okokhere, Peter O., Schieffelin, John S., Andersen, Kristian G., Reilly, Steven K., Grant, Donald S., Garry, Robert F., Barnes, Kayla G., Happi, Christian T., and Sabeti, Pardis C.

Published
2024
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10. Genetic and functional analysis of Raynaud’s syndrome implicates loci in vasculature and immunity

Author

Tervi, Anniina, Ramste, Markus, Abner, Erik, Cheng, Paul, Lane, Jacqueline M., Maher, Matthew, Valliere, Jesse, Lammi, Vilma, Strausz, Satu, Riikonen, Juha, Nguyen, Trieu, Martyn, Gabriella E., Sheth, Maya U., Xia, Fan, Docampo, Mauro Lago, Gu, Wenduo, Esko, Tõnu, Saxena, Richa, Pirinen, Matti, Palotie, Aarno, Ripatti, Samuli, Sinnott-Armstrong, Nasa, Daly, Mark, Engreitz, Jesse M., Rabinovitch, Marlene, Heckman, Caroline A., Quertermous, Thomas, Jones, Samuel E., and Ollila, Hanna M.

Published
2024
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11. The impact of Mendelian sleep and circadian genetic variants in a population setting

Author

Weedon, Michael N, Jones, Samuel E, Lane, Jacqueline M, Lee, Jiwon, Ollila, Hanna M, Dawes, Amy, Tyrrell, Jess, Beaumont, Robin N, Partonen, Timo, Merikanto, Ilona, Rich, Stephen S, Rotter, Jerome I, Frayling, Timothy M, Rutter, Martin K, Redline, Susan, Sofer, Tamar, Saxena, Richa, and Wood, Andrew R

Subjects
Biological Sciences, Genetics, Sleep Research, Clinical Research, Neurosciences, Human Genome, 2.1 Biological and endogenous factors, Circadian Rhythm, Humans, Phenotype, Receptors, G-Protein-Coupled, Sleep, Sleep Wake Disorders, Developmental Biology
Abstract

Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants in these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. No carriers for variants reported in NPSR1 or PER2 were identified. We found no association between variants analyzed and extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being "definitely a morning person", P = 4x10-8; and had a 57-minute earlier midpoint sleep, P = 5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population.

Published
2022

12. Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer

Author

Reeve, Mary Pat, Vehviläinen, Mari, Luo, Shuang, Ritari, Jarmo, Karjalainen, Juha, Gracia-Tabuenca, Javier, Mehtonen, Juha, Padmanabhuni, Shanmukha Sampath, Kolosov, Nikita, Artomov, Mykyta, Siirtola, Harri, Ollila, Hanna M., Graham, Daniel, Partanen, Jukka, Xavier, Ramnik J., Daly, Mark J., Ripatti, Samuli, Salo, Tuula, and Siponen, Maria

Published
2024
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14. BMAL1 loss in oligodendroglia contributes to abnormal myelination and sleep

Author

Rojo, Daniela, Dal Cengio, Louisa, Badner, Anna, Kim, Samuel, Sakai, Noriaki, Greene, Jacob, Dierckx, Tess, Mehl, Lindsey C., Eisinger, Ella, Ransom, Julia, Arellano-Garcia, Caroline, Gumma, Mohammad E., Soyk, Rebecca L., Lewis, Cheyanne M., Lam, Mable, Weigel, Maya K., Damonte, Valentina Martinez, Yalçın, Belgin, Jones, Samuel E., Ollila, Hanna M., Nishino, Seiji, and Gibson, Erin M.

Published
2023
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15. Dark microbiome and extremely low organics in Atacama fossil delta unveil Mars life detection limits

Author

Azua-Bustos, Armando, Fairén, Alberto G., González-Silva, Carlos, Prieto-Ballesteros, Olga, Carrizo, Daniel, Sánchez-García, Laura, Parro, Victor, Fernández-Martínez, Miguel Ángel, Escudero, Cristina, Muñoz-Iglesias, Victoria, Fernández-Sampedro, Maite, Molina, Antonio, Villadangos, Miriam García, Moreno-Paz, Mercedes, Wierzchos, Jacek, Ascaso, Carmen, Fornaro, Teresa, Brucato, John Robert, Poggiali, Giovanni, Manrique, Jose Antonio, Veneranda, Marco, López-Reyes, Guillermo, Sanz-Arranz, Aurelio, Rull, Fernando, Ollila, Ann M., Wiens, Roger C., Reyes-Newell, Adriana, Clegg, Samuel M., Millan, Maëva, Johnson, Sarah Stewart, McIntosh, Ophélie, Szopa, Cyril, Freissinet, Caroline, Sekine, Yasuhito, Fukushi, Keisuke, Morida, Koki, Inoue, Kosuke, Sakuma, Hiroshi, and Rampe, Elizabeth

Published
2023
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16. FinnGen provides genetic insights from a well-phenotyped isolated population

Author

Kurki, Mitja I., Karjalainen, Juha, Palta, Priit, Sipilä, Timo P., Kristiansson, Kati, Donner, Kati M., Reeve, Mary P., Laivuori, Hannele, Aavikko, Mervi, Kaunisto, Mari A., Loukola, Anu, Lahtela, Elisa, Mattsson, Hannele, Laiho, Päivi, Della Briotta Parolo, Pietro, Lehisto, Arto A., Kanai, Masahiro, Mars, Nina, Rämö, Joel, Kiiskinen, Tuomo, Heyne, Henrike O., Veerapen, Kumar, Rüeger, Sina, Lemmelä, Susanna, Zhou, Wei, Ruotsalainen, Sanni, Pärn, Kalle, Hiekkalinna, Tero, Koskelainen, Sami, Paajanen, Teemu, Llorens, Vincent, Gracia-Tabuenca, Javier, Siirtola, Harri, Reis, Kadri, Elnahas, Abdelrahman G., Sun, Benjamin, Foley, Christopher N., Aalto-Setälä, Katriina, Alasoo, Kaur, Arvas, Mikko, Auro, Kirsi, Biswas, Shameek, Bizaki-Vallaskangas, Argyro, Carpen, Olli, Chen, Chia-Yen, Dada, Oluwaseun A., Ding, Zhihao, Ehm, Margaret G., Eklund, Kari, Färkkilä, Martti, Finucane, Hilary, Ganna, Andrea, Ghazal, Awaisa, Graham, Robert R., Green, Eric M., Hakanen, Antti, Hautalahti, Marco, Hedman, Åsa K., Hiltunen, Mikko, Hinttala, Reetta, Hovatta, Iiris, Hu, Xinli, Huertas-Vazquez, Adriana, Huilaja, Laura, Hunkapiller, Julie, Jacob, Howard, Jensen, Jan-Nygaard, Joensuu, Heikki, John, Sally, Julkunen, Valtteri, Jung, Marc, Junttila, Juhani, Kaarniranta, Kai, Kähönen, Mika, Kajanne, Risto, Kallio, Lila, Kälviäinen, Reetta, Kaprio, Jaakko, Kerimov, Nurlan, Kettunen, Johannes, Kilpeläinen, Elina, Kilpi, Terhi, Klinger, Katherine, Kosma, Veli-Matti, Kuopio, Teijo, Kurra, Venla, Laisk, Triin, Laukkanen, Jari, Lawless, Nathan, Liu, Aoxing, Longerich, Simonne, Mägi, Reedik, Mäkelä, Johanna, Mäkitie, Antti, Malarstig, Anders, Mannermaa, Arto, Maranville, Joseph, Matakidou, Athena, Meretoja, Tuomo, Mozaffari, Sahar V., Niemi, Mari E. K., Niemi, Marianna, Niiranen, Teemu, O´Donnell, Christopher J., Obeidat, Ma´en, Okafo, George, Ollila, Hanna M., Palomäki, Antti, Palotie, Tuula, Partanen, Jukka, Paul, Dirk S., Pelkonen, Margit, Pendergrass, Rion K., Petrovski, Slavé, Pitkäranta, Anne, Platt, Adam, Pulford, David, Punkka, Eero, Pussinen, Pirkko, Raghavan, Neha, Rahimov, Fedik, Rajpal, Deepak, Renaud, Nicole A., Riley-Gillis, Bridget, Rodosthenous, Rodosthenis, Saarentaus, Elmo, Salminen, Aino, Salminen, Eveliina, Salomaa, Veikko, Schleutker, Johanna, Serpi, Raisa, Shen, Huei-yi, Siegel, Richard, Silander, Kaisa, Siltanen, Sanna, Soini, Sirpa, Soininen, Hilkka, Sul, Jae Hoon, Tachmazidou, Ioanna, Tasanen, Kaisa, Tienari, Pentti, Toppila-Salmi, Sanna, Tukiainen, Taru, Tuomi, Tiinamaija, Turunen, Joni A., Ulirsch, Jacob C., Vaura, Felix, Virolainen, Petri, Waring, Jeffrey, Waterworth, Dawn, Yang, Robert, Nelis, Mari, Reigo, Anu, Metspalu, Andres, Milani, Lili, Esko, Tõnu, Fox, Caroline, Havulinna, Aki S., Perola, Markus, Ripatti, Samuli, Jalanko, Anu, Laitinen, Tarja, Mäkelä, Tomi P., Plenge, Robert, McCarthy, Mark, Runz, Heiko, Daly, Mark J., and Palotie, Aarno

Published
2023
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17. The public health impact of poor sleep on severe COVID-19, influenza and upper respiratory infections

Author

Palotie, Aarno, Daly, Mark, Riley-Gills, Bridget, Jacob, Howard, Paul, Dirk, Petrovski, Slavé, Runz, Heiko, John, Sally, Okafo, George, Lawless, Nathan, Salminen-Mankonen, Heli, Plenge, Robert, Maranville, Joseph, McCarthy, Mark, Ehm, Margaret G., Auro, Kirsi, Longerich, Simonne, Mälarstig, Anders, Klinger, Katherine, Chatelain, Clement, Gossel, Matthias, Estrada, Karol, Graham, Robert, Yang, Robert, O´Donnell, Chris, Mäkelä, Tomi P., Kaprio, Jaakko, Virolainen, Petri, Hakanen, Antti, Kilpi, Terhi, Perola, Markus, Partanen, Jukka, Pitkäranta, Anne, Raivio, Taneli, Tikkanen, Jani, Serpi, Raisa, Laitinen, Tarja, Kosma, Veli-Matti, Laukkanen, Jari, Hautalahti, Marco, Tuovila, Outi, Pakkanen, Raimo, Waring, Jeffrey, Riley-Gillis, Bridget, Rahimov, Fedik, Tachmazidou, Ioanna, Chen, Chia-Yen, Ding, Zhihao, Jung, Marc, Biswas, Shameek, Pendergrass, Rion, Pulford, David, Raghavan, Neha, Huertas-Vazquez, Adriana, Sul, Jae-Hoon, Hu, Xinli, Hedman, Åsa, Rivas, Manuel, Waterworth, Dawn, Renaud, Nicole, Obeidat, Ma´en, Ripatti, Samuli, Schleutker, Johanna, Arvas, Mikko, Carpén, Olli, Hinttala, Reetta, Kettunen, Johannes, Mannermaa, Arto, Aalto-Setälä, Katriina, Kähönen, Mika, Mäkelä, Johanna, Kälviäinen, Reetta, Julkunen, Valtteri, Soininen, Hilkka, Remes, Anne, Hiltunen, Mikko, Peltola, Jukka, Raivio, Minna, Tienari, Pentti, Rinne, Juha, Kallionpää, Roosa, Partanen, Juulia, Abbasi, Ali, Ziemann, Adam, Smaoui, Nizar, Lehtonen, Anne, Eaton, Susan, Lahdenperä, Sanni, Bowers, Natalie, Teng, Edmond, Xu, Fanli, Addis, Laura, Eicher, John, Li, Qingqin S., He, Karen, Khramtsova, Ekaterina, Färkkilä, Martti, Koskela, Jukka, Pikkarainen, Sampsa, Jussila, Airi, Kaukinen, Katri, Blomster, Timo, Kiviniemi, Mikko, Voutilainen, Markku, Lu, Tim, McCarthy, Linda, Hart, Amy, Guan, Meijian, Miller, Jason, Kalpala, Kirsi, Miller, Melissa, Eklund, Kari, Palomäki, Antti, Isomäki, Pia, Pirilä, Laura, Kaipiainen-Seppänen, Oili, Huhtakangas, Johanna, Mars, Nina, Lertratanakul, Apinya, Viollet, Coralie, Hochfeld, Marla, Gordillo, Jorge Esparza, Farias, Fabiana, Bing, Nan, Pelkonen, Margit, Kauppi, Paula, Kankaanranta, Hannu, Harju, Terttu, Lahesmaa, Riitta, Chen, Hubert, Betts, Joanna, Mishra, Rajashree, Mouded, Majd, Ngo, Debby, Niiranen, Teemu, Vaura, Felix, Salomaa, Veikko, Metsärinne, Kaj, Aittokallio, Jenni, Hernesniemi, Jussi, Gordin, Daniel, Sinisalo, Juha, Taskinen, Marja-Riitta, Tuomi, Tiinamaija, Hiltunen, Timo, Elliott, Amanda, Reeve, Mary Pat, Ruotsalainen, Sanni, Chu, Audrey, Reilly, Dermot, Mendelson, Mike, Parkkinen, Jaakko, Meretoja, Tuomo, Joensuu, Heikki, Mattson, Johanna, Salminen, Eveliina, Auranen, Annika, Karihtala, Peeter, Auvinen, Päivi, Elenius, Klaus, Pitkänen, Esa, Popovic, Relja, Fabre, Margarete, Schutzman, Jennifer, Kulkarni, Diptee, Porello, Alessandro, Loboda, Andrey, Lehtonen, Heli, McDonough, Stefan, Vuoti, Sauli, Kaarniranta, Kai, Turunen, Joni A., Ollila, Terhi, Uusitalo, Hannu, Karjalainen, Juha, Liu, Mengzhen, Loomis, Stephanie, Strauss, Erich, Chen, Hao, Tasanen, Kaisa, Huilaja, Laura, Hannula-Jouppi, Katariina, Salmi, Teea, Peltonen, Sirkku, Koulu, Leena, Choy, David, Wu, Ying, Pussinen, Pirkko, Salminen, Aino, Salo, Tuula, Rice, David, Nieminen, Pekka, Palotie, Ulla, Siponen, Maria, Suominen, Liisa, Mäntylä, Päivi, Gursoy, Ulvi, Anttonen, Vuokko, Sipilä, Kirsi, Laivuori, Hannele, Kurra, Venla, Kotaniemi-Talonen, Laura, Heikinheimo, Oskari, Kalliala, Ilkka, Aaltonen, Lauri, Jokimaa, Varpu, Vääräsmäki, Marja, Uimari, Outi, Morin-Papunen, Laure, Niinimäki, Maarit, Piltonen, Terhi, Kivinen, Katja, Widen, Elisabeth, Tukiainen, Taru, Välimäki, Niko, Laakkonen, Eija, Tyrmi, Jaakko, Silven, Heidi, Sliz, Eeva, Arffman, Riikka, Savukoski, Susanna, Laisk, Triin, Pujol, Natalia, Kumar, Janet, Hovatta, Iiris, Isometsä, Erkki, Ollila, Hanna, Suvisaari, Jaana, Als, Thomas Damm, Mäkitie, Antti, Bizaki-Vallaskangas, Argyro, Toppila-Salmi, Sanna, Willberg, Tytti, Saarentaus, Elmo, Aarnisalo, Antti, Rahikkala, Elisa, Aittomäki, Kristiina, Åberg, Fredrik, Kurki, Mitja, Havulinna, Aki, Mehtonen, Juha, Palta, Priit, Hassan, Shabbeer, Della Briotta Parolo, Pietro, Zhou, Wei, Maasha, Mutaamba, Lemmelä, Susanna, Liu, Aoxing, Lehisto, Arto, Ganna, Andrea, Llorens, Vincent, Heyne, Henrike, Rämö, Joel, Rodosthenous, Rodos, Strausz, Satu, Palotie, Tuula, Palin, Kimmo, Garcia-Tabuenca, Javier, Siirtola, Harri, Kiiskinen, Tuomo, Lee, Jiwoo, Tsuo, Kristin, Kristiansson, Kati, Hyvärinen, Kati, Ritari, Jarmo, Pylkäs, Katri, Karjalainen, Minna, Mantere, Tuomo, Kangasniemi, Eeva, Heikkinen, Sami, Pitkänen, Nina, Lessard, Samuel, Chatelain, Clément, Kallio, Lila, Wahlfors, Tiina, Punkka, Eero, Siltanen, Sanna, Kuopio, Teijo, Jalanko, Anu, Shen, Huei-Yi, Kajanne, Risto, Aavikko, Mervi, Leinonen, Rasko, Palin, Henna, Linna, Malla-Maria, Kanai, Masahiro, Zheng, Zhili, Lahtela, L. Elisa, Kaunisto, Mari, Kilpeläinen, Elina, Sipilä, Timo P., Dada, Oluwaseun Alexander, Ghazal, Awaisa, Kytölä, Anastasia, Weldatsadik, Rigbe, Donner, Kati, Loukola, Anu, Laiho, Päivi, Sistonen, Tuuli, Kaiharju, Essi, Laukkanen, Markku, Järvensivu, Elina, Lähteenmäki, Sini, Männikkö, Lotta, Wong, Regis, Toivola, Auli, Brunfeldt, Minna, Mattsson, Hannele, Koskelainen, Sami, Hiekkalinna, Tero, Paajanen, Teemu, Pärn, Kalle, Kals, Mart, Luo, Shuang, Padmanabhuni, Shanmukha Sampath, Niemi, Marianna, Gracia-Tabuenca, Javier, Helminen, Mika, Luukkaala, Tiina, Vähätalo, Iida, Tammerluoto, Jyrki, Smith, Sarah, Southerington, Tom, Lehto, Petri, Jones, Samuel E., Maisha, Fahrisa I., Strausz, Satu J., Lammi, Vilma, Cade, Brian E., Tervi, Anniina, Helaakoski, Viola, Broberg, Martin E., Lane, Jacqueline M., Redline, Susan, Saxena, Richa, and Ollila, Hanna M.

Published
2023
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20. Kleine-Levin syndrome is associated with birth difficulties and genetic variants in the TRANK1 gene loci

Author

Ambati, Aditya, Hillary, Ryan, Leu-Semenescu, Smaranda, Ollila, Hanna M., Lin, Ling, During, Emmanuel H., Farber, Neal, Rico, Thomas J., Faraco, Juliette, Leary, Eileen, Goldstein-Piekarski, Andrea N., Huang, Yu-Shu, Han, Fang, Sivan, Yakov, Lecendreux, Michel, Dodet, Pauline, Honda, Makoto, Gadoth, Natan, Nevsimalova, Sona, Pizza, Fabio, Kanbayashi, Takashi, Peraita-Adrados, Rosa, Leschziner, Guy D., Hasan, Rosa, Canellas, Francesca, Kume, Kazuhiko, Daniilidou, Makrina, Bourgin, Patrice, Ryec, David, Vicario, José L., Hogl, Birgit, Hong, Seung Chul, Plazzi, Guiseppe, Mayer, Geert, Landtblom, Anne Marie, Dauvilliers, Yves, Arnulf, Isabelle, and Mignot, Emmanuel Jean-Marie

Published
2021

22. 24-hour movement behaviours and cardiometabolic markers in women with polycystic ovary syndrome (PCOS): a compositional data analysis.

Author

Pesonen, E, Farrahi, V, Brakenridge, C J, Ollila, M M, Morin-Papunen, L C, Nurkkala, M, Jämsä, T, Korpelainen, R, Moran, L J, Piltonen, T T, and Niemelä, M

Subjects
POLYCYSTIC ovary syndrome, REGIONAL development, GLUCOSE tolerance tests, SEDENTARY behavior, INSULIN sensitivity
Abstract

STUDY QUESTION Are 24-h movement composition and time reallocations between the movement behaviours (moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behaviour (SB), and sleep) differentially associated with cardiometabolic markers in women with polycystic ovary syndrome (PCOS) relative to women without PCOS? SUMMARY ANSWER There was no difference in 24-h movement composition between the groups, although among women without PCOS, reducing SB time while increasing either MVPA or LPA time was associated with beneficial differences in cardiometabolic markers, whereas in women with PCOS beneficial differences were observed only when SB time was replaced with MVPA. WHAT IS KNOWN ALREADY Women with PCOS display lower levels of physical activity, higher sedentary time, and less total sleep than women without the syndrome. Exercise interventions among women with PCOS have shown improvements in body composition and insulin sensitivity, while the findings regarding blood pressure, insulin resistance, and lipid profiles are contradictory. STUDY DESIGN, SIZE, DURATION This study was part of a prospective, general population-based Northern Finland Birth Cohort 1966 (NFBC1966) (n = 5889 women). At the 31-year and 46-year follow-up, data collection was performed through postal and clinical examinations, including fasting blood samples and anthropometric measurements. Accelerometer data collection of 14 days (n = 2602 women) and a 2-h oral glucose tolerance test (n = 2780 women) were performed at the 46-year follow-up. Participants were identified as women with or without PCOS at age 31 (n = 1883), and the final study population included those who provided valid accelerometer data at age 46 (n = 857). PARTICIPANTS/MATERIALS, SETTING, METHODS Women with PCOS (n = 192) were identified based on the 2023 International Evidence-based Guideline, while those who exhibited no PCOS features were considered women without PCOS (controls; n = 665). Accelerometer-measured MVPA, LPA, and SB were combined with self-reported sleep to obtain 24-h compositions. Multivariable regression analysis based on compositional data analysis and isotemporal reallocations were performed to investigate the associations between 24-h movement composition and cardiometabolic markers. Isotemporal reallocations were expressed as differences (%Δ) from the sample's mean. MAIN RESULTS AND THE ROLE OF CHANCE There was no difference in overall 24-h movement composition between women with PCOS and controls in midlife. The 24-h movement composition was associated with waist circumference, triglycerides, fasting serum insulin, and Homeostatic Model Assessment–insulin resistance (HOMA-IR) in both controls and women with PCOS. Reallocating 15 min from SB to MVPA was associated with favourable differences in cardiometabolic markers in both controls (%Δ range from −1.7 to −4.9) and women with PCOS (%Δ range from −1.9 to −8.6). Reallocating 15 min from SB to LPA was also associated with favourable differences in cardiometabolic markers among controls (%Δ range from −0.5 to −1.6) but not among women with PCOS. LIMITATIONS, REASONS FOR CAUTION The substitution technique used in this study is theoretical, which can be considered as a limitation. Other limitations of this study are the use of self-reported sleeping time and the difference in the group sample sizes. WIDER IMPLICATIONS OF THE FINDINGS These findings suggest that women with PCOS should be targeted with interventions involving physical activity of at least moderate intensity to improve their cardiometabolic health and underline the importance of developing tailored activity guidelines for women with PCOS. STUDY FUNDING/COMPETING INTEREST(S) This study was funded by the Jenny and Antti Wihuri Foundation, Sigrid Juselius Foundation, Novo Nordisk (NNF21OC0070372), Research Council of Finland (315921/2018, 321763/2019, 6GESS 336449), Ministry of Education and Culture of Finland (OKM/54/626/2019, OKM/85/626/2019, OKM/1096/626/2020, OKM/20/626/2022, OKM/76/626/2022, and OKM/68/626/2023), and Roche Diagnostics International Ltd. L.J.M. is supported by a Veski Fellowship. M.Nu. has received funding from Fibrobesity-project, a strategic profiling project at the University of Oulu, which is supported by Research Council of Finland (Profi6 336449). NFBC1966 follow-ups received financial support from University of Oulu (Grant no. 65354, 24000692), Oulu University Hospital (Grant no. 2/97, 8/97, 24301140), Ministry of Health and Social Affairs (Grant no. 23/251/97, 160/97, 190/97), National Institute for Health and Welfare, Helsinki (Grant no. 54121), Regional Institute of Occupational Health, Oulu, Finland (Grant no. 50621, 54231), and ERDF European Regional Development Fund (Grant no. 539/2010 A31592). T.T.P. declares consulting fees from Gedeon Richter, Organon, Astellas, Roche; speaker's fees from Gedeon Richter, Exeltis, Roche, Stragen, Merck, Organon; and travel support from Gedeon Richter. The remaining authors declare no conflicts of interest. TRIAL REGISTRATION NUMBER N/A. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Excess of severe autoimmune diseases in women with premature ovarian insufficiency: a population-based study.

Author

Savukoski, S M, Silvén, H, Pesonen, P, Pukkala, E, Gissler, M, Suvanto, E, Ollila, M -M, and Niinimäki, M

Subjects
SYSTEMIC lupus erythematosus, INFLAMMATORY bowel diseases, PREMATURE ovarian failure, TYPE 1 diabetes, HORMONE therapy, SARCOIDOSIS, AUTOIMMUNE diseases
Abstract

STUDY QUESTION Is there an association between premature ovarian insufficiency (POI) and severe autoimmune diseases before and after POI diagnosis? SUMMARY ANSWER Women with POI had at least one hospital-treated autoimmune disorder preceding POI diagnosis 2.6 times more often compared with matched female controls, and a 2- to 3-fold risk for these diseases for several years after POI diagnosis. WHAT IS KNOWN ALREADY It has been suggested that autoimmunity is an important factor in the pathogenesis of POI. Estimations of the prevalence of POI cases with autoimmune origin have ranged from 4% to 50%. STUDY DESIGN, SIZE, DURATION This population-based registry study included 3972 women diagnosed with spontaneous POI between 1988 and 2017 and 15 708 female population controls and used both case–control and cohort analysis. Autoimmune disease diagnoses were evaluated from childhood until the end of the year 2017. PARTICIPANTS/MATERIALS, SETTING, METHODS Women with POI were identified from the reimbursement registry of the Finnish Social Insurance Institution by their right to hormone replacement therapy (HRT). Four female population controls matched by age and municipality of residence were searched for each POI case to form a reference cohort. Women with a history of cancer or bilateral oophorectomy were excluded. Severe autoimmune disorder diagnoses for the years 1970–2017 were identified from the Hospital Discharge Registry. Odds ratios (ORs) with 95% confidence intervals (CI) were calculated using binary logistic regression for cases of having any, or one or more, specific autoimmune diseases preceding the index date (the date when reimbursement for HRT was granted for the POI) among women with POI as compared to controls. Standardized incidence ratios (SIR) with 95% CIs for getting diagnosed with an autoimmune disease after the index date in 3-year follow-up periods among women with POI (who did not have these diseases prior to the index date) were also calculated. The expected numbers of autoimmune disease cases were based on the incidence of first-onset severe autoimmune disease among the controls. MAIN RESULTS AND THE ROLE OF CHANCE The prevalence of having at least one severe autoimmune disease in women with POI was 5.6% (n = 233), with an OR of 2.6 (95% CI 2.2, 3.1) when compared to population controls. Women with POI had an increased prevalence of several specific autoimmune diseases prior to the index date compared to controls: polyglandular autoimmune diseases (OR 25.8, 95% CI 9.0, 74.1), Addison's disease (OR 22.9, 95% CI 7.9, 66.1), vasculitis (OR 10.2, 95% 4.3, 24.5), systemic lupus erythematosus (OR 6.3 95% CI 4.2, 20.3), rheumatoid arthritis (OR 2.3, 95% CI 1.7, 3.2), sarcoidosis (OR 2.3, 95% CI 1.2, 4.5), inflammatory bowel diseases (OR 2.2, 95% CI 1.5, 3.3), and hyperthyroidism (OR 1.9, 95% CI 1.2, 3.1); whereas the prevalence of diabetes type 1 and ankylosing spondylitis did not differ between the women with POI and the reference cohort. The SIRs for being diagnosed for the first time with a severe autoimmune disease after POI diagnosis was 2.8 (95% CI 2.3, 3.4), during the first three years after POI diagnosis, decreasing gradually to 1.3 (1.1, 1.6) after 12 years. LIMITATIONS, REASONS FOR CAUTION This study only included autoimmune disorders diagnosed in specialized health care; hence, the overall prevalence of autoimmune disorders in women with POI may be higher. WIDER IMPLICATIONS OF THE FINDINGS Severe autoimmune diseases have a strong association with POI, suggesting that immunological mechanisms play a pivotal role in POI. Future studies should focus on specific autoimmune mechanisms behind POI, from both preventive and curative perspectives. STUDY FUNDING/COMPETING INTEREST(S) This work was financially supported by Oulu University Hospital. S.M.S. received grants from the Finnish Menopause Society, the Finnish Medical Foundation, and the Juho Vainio Foundation. H.S. received grants from the Finnish Menopause Society, the Oulu Medical Research Foundation, the Finnish Research Foundation of Gynecology and Obstetrics, UniOGS graduate school, The Finnish Medical Society Duodecim, Orion Research Foundation, and the University of Oulu Scholarship Fund. M.-M.O. received a grant from the Sakari Alhopuro Foundation and the Finnish Diabetes Research Foundation. None of the funders had any involvement in the study design or its execution or reporting. The authors do not have any competing interests to report. TRIAL REGISTRATION NUMBER N/A. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Author Correction: FinnGen provides genetic insights from a well-phenotyped isolated population

Author

Kurki, Mitja I., Karjalainen, Juha, Palta, Priit, Sipilä, Timo P., Kristiansson, Kati, Donner, Kati M., Reeve, Mary P., Laivuori, Hannele, Aavikko, Mervi, Kaunisto, Mari A., Loukola, Anu, Lahtela, Elisa, Mattsson, Hannele, Laiho, Päivi, Della Briotta Parolo, Pietro, Lehisto, Arto A., Kanai, Masahiro, Mars, Nina, Rämö, Joel, Kiiskinen, Tuomo, Heyne, Henrike O., Veerapen, Kumar, Rüeger, Sina, Lemmelä, Susanna, Zhou, Wei, Ruotsalainen, Sanni, Pärn, Kalle, Hiekkalinna, Tero, Koskelainen, Sami, Paajanen, Teemu, Llorens, Vincent, Gracia-Tabuenca, Javier, Siirtola, Harri, Reis, Kadri, Elnahas, Abdelrahman G., Sun, Benjamin, Foley, Christopher N., Aalto-Setälä, Katriina, Alasoo, Kaur, Arvas, Mikko, Auro, Kirsi, Biswas, Shameek, Bizaki-Vallaskangas, Argyro, Carpen, Olli, Chen, Chia-Yen, Dada, Oluwaseun A., Ding, Zhihao, Ehm, Margaret G., Eklund, Kari, Färkkilä, Martti, Finucane, Hilary, Ganna, Andrea, Ghazal, Awaisa, Graham, Robert R., Green, Eric M., Hakanen, Antti, Hautalahti, Marco, Hedman, Åsa K., Hiltunen, Mikko, Hinttala, Reetta, Hovatta, Iiris, Hu, Xinli, Huertas-Vazquez, Adriana, Huilaja, Laura, Hunkapiller, Julie, Jacob, Howard, Jensen, Jan-Nygaard, Joensuu, Heikki, John, Sally, Julkunen, Valtteri, Jung, Marc, Junttila, Juhani, Kaarniranta, Kai, Kähönen, Mika, Kajanne, Risto, Kallio, Lila, Kälviäinen, Reetta, Kaprio, Jaakko, Kerimov, Nurlan, Kettunen, Johannes, Kilpeläinen, Elina, Kilpi, Terhi, Klinger, Katherine, Kosma, Veli-Matti, Kuopio, Teijo, Kurra, Venla, Laisk, Triin, Laukkanen, Jari, Lawless, Nathan, Liu, Aoxing, Longerich, Simonne, Mägi, Reedik, Mäkelä, Johanna, Mäkitie, Antti, Malarstig, Anders, Mannermaa, Arto, Maranville, Joseph, Matakidou, Athena, Meretoja, Tuomo, Mozaffari, Sahar V., Niemi, Mari E. K., Niemi, Marianna, Niiranen, Teemu, O´Donnell, Christopher J., Obeidat, Ma´en, Okafo, George, Ollila, Hanna M., Palomäki, Antti, Palotie, Tuula, Partanen, Jukka, Paul, Dirk S., Pelkonen, Margit, Pendergrass, Rion K., Petrovski, Slavé, Pitkäranta, Anne, Platt, Adam, Pulford, David, Punkka, Eero, Pussinen, Pirkko, Raghavan, Neha, Rahimov, Fedik, Rajpal, Deepak, Renaud, Nicole A., Riley-Gillis, Bridget, Rodosthenous, Rodosthenis, Saarentaus, Elmo, Salminen, Aino, Salminen, Eveliina, Salomaa, Veikko, Schleutker, Johanna, Serpi, Raisa, Shen, Huei-yi, Siegel, Richard, Silander, Kaisa, Siltanen, Sanna, Soini, Sirpa, Soininen, Hilkka, Sul, Jae Hoon, Tachmazidou, Ioanna, Tasanen, Kaisa, Tienari, Pentti, Toppila-Salmi, Sanna, Tukiainen, Taru, Tuomi, Tiinamaija, Turunen, Joni A., Ulirsch, Jacob C., Vaura, Felix, Virolainen, Petri, Waring, Jeffrey, Waterworth, Dawn, Yang, Robert, Nelis, Mari, Reigo, Anu, Metspalu, Andres, Milani, Lili, Esko, Tõnu, Fox, Caroline, Havulinna, Aki S., Perola, Markus, Ripatti, Samuli, Jalanko, Anu, Laitinen, Tarja, Mäkelä, Tomi P., Plenge, Robert, McCarthy, Mark, Runz, Heiko, Daly, Mark J., and Palotie, Aarno

Published
2023
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25. Genetics of 35 blood and urine biomarkers in the UK Biobank

Author

Sinnott-Armstrong, Nasa, Tanigawa, Yosuke, Amar, David, Mars, Nina, Benner, Christian, Aguirre, Matthew, Venkataraman, Guhan Ram, Wainberg, Michael, Ollila, Hanna M., Kiiskinen, Tuomo, Havulinna, Aki S., Pirruccello, James P., Qian, Junyang, Shcherbina, Anna, Rodriguez, Fatima, Assimes, Themistocles L., Agarwala, Vineeta, Tibshirani, Robert, Hastie, Trevor, Ripatti, Samuli, Pritchard, Jonathan K., Daly, Mark J., and Rivas, Manuel A.

Published
2021
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26. How do clinicians use post-COVID syndrome diagnosis? Analysis of clinical features in a Swedish COVID-19 cohort with 18 months’ follow-up : a national observational cohort and matched cohort study

Author

Ollila, Hanna M, Fonseca Rodriguez, Osvaldo, Caspersen, Ida Henriette, Kalucza, Sebastian, Normark, Johan, Trogstad, Lill, Magnus, Per Minor, Rod, Naja Hulvej, Ganna, Andrea, Eriksson, Marie, Fors Connolly, Anne-Marie, Ollila, Hanna M, Fonseca Rodriguez, Osvaldo, Caspersen, Ida Henriette, Kalucza, Sebastian, Normark, Johan, Trogstad, Lill, Magnus, Per Minor, Rod, Naja Hulvej, Ganna, Andrea, Eriksson, Marie, and Fors Connolly, Anne-Marie

Abstract

Introduction: SARS-CoV-2 infection causes acute COVID-19 and may result in post-COVID syndrome (PCS). We aimed to investigate how clinicians diagnose PCS and identify associated clinical and demographic characteristics. Methods: We analysed multiregistry data of all SARS-CoV-2 test-positive individuals in Sweden (n=1 057 174) between 1 February 2020 and 25 May 2021. We described clinical characteristics that prompt PCS diagnosis in outpatient and inpatient settings. In total, there were 6389 individuals with a hospital inpatient or outpatient diagnosis for PCS. To understand symptomatology, we examined individuals diagnosed with PCS at least 3 months after COVID-19 onset (n=6389) and assessed factors associated with PCS diagnosis. Results: Mechanical ventilation correlated with PCS (OR 114.7, 95% CI 105.1 to 125.3) compared with no outpatient/inpatient contact during initial COVID-19. Dyspnoea (13.4%), malaise/fatigue (8%) and abnormal pulmonary diagnostic imaging findings (4.3%) were the most common features linked to PCS. We compared clinical features of PCS with matched controls (COVID-19 negative, n=23 795) and COVID-19 severity-matched patients (COVID-19 positive, n=25 556). Hypertension associated with PCS cohort (26.61%) than in COVID-19-negative (OR 17.16, 95% CI 15.23 to 19.3) and COVID-19-positive (OR 9.25, 95% CI 8.41 to 10.16) controls, although most individuals received this diagnosis before COVID-19. Dyspnoea was the second most common feature in the PCS cohort (17.2%), and new to the majority compared with COVID-19-negative (OR 54.16, 95% CI 42.86 to 68.45) and COVID-19-positive (OR 18.7, 95% CI 16.21 to 21.57) controls. Conclusions: Our findings highlight factors Swedish physicians associate with PCS.

Published
2024
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27. How do clinicians use post-COVID syndrome diagnosis? Analysis of clinical features in a Swedish COVID-19 cohort with 18 months’ follow-up: a national observational cohort and matched cohort study

Author

Ollila, Hanna M, primary, Fonseca-Rodríguez, Osvaldo, additional, Caspersen, Ida Henriette, additional, Kalucza, Sebastian, additional, Normark, Johan, additional, Trogstad, Lill, additional, Magnus, Per Minor, additional, Rod, Naja Hulvej, additional, Ganna, Andrea, additional, Eriksson, Marie, additional, and Fors Connolly, Anne-Marie, additional

Published
2024
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28. The SuperCam Instrument Suite on the Mars 2020 Rover: Science Objectives and Mast-Unit Description

Author

Maurice, S., Wiens, R. C., Bernardi, P., Caïs, P., Robinson, S., Nelson, T., Gasnault, O., Reess, J.-M., Deleuze, M., Rull, F., Manrique, J.-A., Abbaki, S., Anderson, R. B., André, Y., Angel, S. M., Arana, G., Battault, T., Beck, P., Benzerara, K., Bernard, S., Berthias, J.-P., Beyssac, O., Bonafous, M., Bousquet, B., Boutillier, M., Cadu, A., Castro, K., Chapron, F., Chide, B., Clark, K., Clavé, E., Clegg, S., Cloutis, E., Collin, C., Cordoba, E. C., Cousin, A., Dameury, J.-C., D’Anna, W., Daydou, Y., Debus, A., Deflores, L., Dehouck, E., Delapp, D., De Los Santos, G., Donny, C., Doressoundiram, A., Dromart, G., Dubois, B., Dufour, A., Dupieux, M., Egan, M., Ervin, J., Fabre, C., Fau, A., Fischer, W., Forni, O., Fouchet, T., Frydenvang, J., Gauffre, S., Gauthier, M., Gharakanian, V., Gilard, O., Gontijo, I., Gonzalez, R., Granena, D., Grotzinger, J., Hassen-Khodja, R., Heim, M., Hello, Y., Hervet, G., Humeau, O., Jacob, X., Jacquinod, S., Johnson, J. R., Kouach, D., Lacombe, G., Lanza, N., Lapauw, L., Laserna, J., Lasue, J., Le Deit, L., Le Mouélic, S., Le Comte, E., Lee, Q.-M., Legett, IV, C., Leveille, R., Lewin, E., Leyrat, C., Lopez-Reyes, G., Lorenz, R., Lucero, B., Madariaga, J. M., Madsen, S., Madsen, M., Mangold, N., Manni, F., Mariscal, J.-F., Martinez-Frias, J., Mathieu, K., Mathon, R., McCabe, K. P., McConnochie, T., McLennan, S. M., Mekki, J., Melikechi, N., Meslin, P.-Y., Micheau, Y., Michel, Y., Michel, J. M., Mimoun, D., Misra, A., Montagnac, G., Montaron, C., Montmessin, F., Moros, J., Mousset, V., Morizet, Y., Murdoch, N., Newell, R. T., Newsom, H., Nguyen Tuong, N., Ollila, A. M., Orttner, G., Oudda, L., Pares, L., Parisot, J., Parot, Y., Pérez, R., Pheav, D., Picot, L., Pilleri, P., Pilorget, C., Pinet, P., Pont, G., Poulet, F., Quantin-Nataf, C., Quertier, B., Rambaud, D., Rapin, W., Romano, P., Roucayrol, L., Royer, C., Ruellan, M., Sandoval, B. F., Sautter, V., Schoppers, M. J., Schröder, S., Seran, H.-C., Sharma, S. K., Sobron, P., Sodki, M., Sournac, A., Sridhar, V., Standarovsky, D., Storms, S., Striebig, N., Tatat, M., Toplis, M., Torre-Fdez, I., Toulemont, N., Velasco, C., Veneranda, M., Venhaus, D., Virmontois, C., Viso, M., Willis, P., and Wong, K. W.

Published
2021
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30. Causal Association Between Subtypes of Excessive Daytime Sleepiness and Risk of Cardiovascular Diseases

Author

Goodman, Matthew O., primary, Dashti, Hassan S., additional, Lane, Jacqueline M., additional, Windred, Daniel P., additional, Burns, Angus, additional, Jones, Samuel E., additional, Sofer, Tamar, additional, Purcell, Shaun M., additional, Zhu, Xiaofeng, additional, Ollila, Hanna M., additional, Kyle, Simon D., additional, Spiegelhalder, Kai, additional, Peker, Yuksel, additional, Huang, Tianyi, additional, Cain, Sean W., additional, Phillips, Andrew J. K., additional, Saxena, Richa, additional, Rutter, Martin K., additional, Redline, Susan, additional, and Wang, Heming, additional

Published
2023
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32. Characteristics of women with ischemic sudden cardiac death

Author

Hookana, I., primary, Holmström, L., additional, Eskuri, M. A. E., additional, Pakanen, L., additional, Ollila, M. M., additional, Kiviniemi, A. M., additional, Kenttä, T., additional, Vähätalo, J., additional, Tulppo, M., additional, Lepojärvi, E. S., additional, Piltonen, T., additional, Perkiömäki, J., additional, Tikkanen, J. T., additional, Huikuri, H. V., additional, and Junttila, M. J., additional

Published
2023
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33. The SuperCam Instrument Suite on the NASA Mars 2020 Rover: Body Unit and Combined System Tests

Author

Wiens, Roger C., Maurice, Sylvestre, Robinson, Scott H., Nelson, Anthony E., Cais, Philippe, Bernardi, Pernelle, Newell, Raymond T., Clegg, Sam, Sharma, Shiv K., Storms, Steven, Deming, Jonathan, Beckman, Darrel, Ollila, Ann M., Gasnault, Olivier, Anderson, Ryan B., André, Yves, Michael Angel, S., Arana, Gorka, Auden, Elizabeth, Beck, Pierre, Becker, Joseph, Benzerara, Karim, Bernard, Sylvain, Beyssac, Olivier, Borges, Louis, Bousquet, Bruno, Boyd, Kerry, Caffrey, Michael, Carlson, Jeffrey, Castro, Kepa, Celis, Jorden, Chide, Baptiste, Clark, Kevin, Cloutis, Edward, Cordoba, Elizabeth C., Cousin, Agnes, Dale, Magdalena, Deflores, Lauren, Delapp, Dorothea, Deleuze, Muriel, Dirmyer, Matthew, Donny, Christophe, Dromart, Gilles, George Duran, M., Egan, Miles, Ervin, Joan, Fabre, Cecile, Fau, Amaury, Fischer, Woodward, Forni, Olivier, Fouchet, Thierry, Fresquez, Reuben, Frydenvang, Jens, Gasway, Denine, Gontijo, Ivair, Grotzinger, John, Jacob, Xavier, Jacquinod, Sophie, Johnson, Jeffrey R., Klisiewicz, Roberta A., Lake, James, Lanza, Nina, Laserna, Javier, Lasue, Jeremie, Le Mouélic, Stéphane, Legett, IV, Carey, Leveille, Richard, Lewin, Eric, Lopez-Reyes, Guillermo, Lorenz, Ralph, Lorigny, Eric, Love, Steven P., Lucero, Briana, Madariaga, Juan Manuel, Madsen, Morten, Madsen, Soren, Mangold, Nicolas, Manrique, Jose Antonio, Martinez, J. P., Martinez-Frias, Jesus, McCabe, Kevin P., McConnochie, Timothy H., McGlown, Justin M., McLennan, Scott M., Melikechi, Noureddine, Meslin, Pierre-Yves, Michel, John M., Mimoun, David, Misra, Anupam, Montagnac, Gilles, Montmessin, Franck, Mousset, Valerie, Murdoch, Naomi, Newsom, Horton, Ott, Logan A., Ousnamer, Zachary R., Pares, Laurent, Parot, Yann, Pawluczyk, Rafal, Glen Peterson, C., Pilleri, Paolo, Pinet, Patrick, Pont, Gabriel, Poulet, Francois, Provost, Cheryl, Quertier, Benjamin, Quinn, Heather, Rapin, William, Reess, Jean-Michel, Regan, Amy H., Reyes-Newell, Adriana L., Romano, Philip J., Royer, Clement, Rull, Fernando, Sandoval, Benigno, Sarrao, Joseph H., Sautter, Violaine, Schoppers, Marcel J., Schröder, Susanne, Seitz, Daniel, Shepherd, Terra, Sobron, Pablo, Dubois, Bruno, Sridhar, Vishnu, Toplis, Michael J., Torre-Fdez, Imanol, Trettel, Ian A., Underwood, Mark, Valdez, Andres, Valdez, Jacob, Venhaus, Dawn, and Willis, Peter

Published
2021
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34. SuperCam Calibration Targets: Design and Development

Author

Manrique, J. A., Lopez-Reyes, G., Cousin, A., Rull, F., Maurice, S., Wiens, R. C., Madsen, M. B., Madariaga, J. M., Gasnault, O., Aramendia, J., Arana, G., Beck, P., Bernard, S., Bernardi, P., Bernt, M. H., Berrocal, A., Beyssac, O., Caïs, P., Castro, C., Castro, K., Clegg, S. M., Cloutis, E., Dromart, G., Drouet, C., Dubois, B., Escribano, D., Fabre, C., Fernandez, A., Forni, O., Garcia-Baonza, V., Gontijo, I., Johnson, J., Laserna, J., Lasue, J., Madsen, S., Mateo-Marti, E., Medina, J., Meslin, P.-Y., Montagnac, G., Moral, A., Moros, J., Ollila, A. M., Ortega, C., Prieto-Ballesteros, O., Reess, J. M., Robinson, S., Rodriguez, J., Saiz, J., Sanz-Arranz, J. A., Sard, I., Sautter, V., Sobron, P., Toplis, M., and Veneranda, M.

Published
2020
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35. Genetic Analysis of Obstructive Sleep Apnea and Its Relationship with Severe COVID-19.

Author

Strausz, Satu, Agafonova, Elizabete, Tiullinen, Varvara, Kiiskinen, Tuomo, Broberg, Martin, Ruotsalainen, Sanni E., Koskela, Jukka, Bachour, Adel, Sofer, Tamar, Gottlieb, Daniel J., Palotie, Aarno, Palotie, Tuula, Ripatti, Samuli, and Ollila, Hanna M.

Subjects
SLEEP apnea syndromes, COVID-19, GENOME-wide association studies, ELECTRONIC health records, BODY mass index
Abstract

Rationale: Although patients with obstructive sleep apnea (OSA) have a higher risk for coronavirus disease (COVID-19) hospitalization, the causal relationship has remained unexplored. Objectives: To understand the causal relationship between OSA and COVID-19 by leveraging data from vaccination and electronic health records, genetic risk factors from genome-wide association studies, and Mendelian randomization. Methods: We elucidated genetic risk factors for OSA using FinnGen (total N = 377,277), performing genome-wide association. We used the associated variants as instruments for univariate and multivariate Mendelian randomization (MR) analyses and computed absolute risk reduction against COVID-19 hospitalization with or without vaccination. Results: We identified nine novel loci for OSA and replicated our findings in the Million Veteran Program. Furthermore, MR analysis showed that OSA was a causal risk factor for severe COVID-19 (P = 9.41 × 10−4). Probabilistic modeling showed that the strongest genetic risk factor for OSA at the FTO locus reflected a signal of higher body mass index (BMI), whereas BMI-independent association was seen with the earlier reported SLC9A4 locus and a MECOM locus, which is a transcriptional regulator with 210-fold enrichment in the Finnish population. Similarly, multivariate MR analysis showed that the causality for severe COVID-19 was driven by BMI (multivariate MR P = 5.97 × 10−6, β = 0.47). Finally, vaccination reduced the risk for COVID-19 hospitalization more in the patients with OSA than in the non-OSA controls, with respective absolute risk reductions of 13.3% versus 6.3%. Conclusions: Our analysis identified novel genetic risk factors for OSA and showed that OSA is a causal risk factor for severe COVID-19. The effect is predominantly explained by higher BMI and suggests BMI-dependent effects at the level of individual variants and at the level of comorbid causality. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

Author

Wainberg, Michael, Jones, Samuel E., Beaupre, Lindsay Melhuish, Hill, Sean L., Felsky, Daniel, Rivas, Manuel A., Lim, Andrew S. P., Ollila, Hanna M., and Tripathy, Shreejoy J.

Subjects
Technology application, Diagnosis, Usage, Medical examination, Risk factors, Mentally ill persons -- Medical examination -- Technology application, Accelerometers -- Usage, Sleep disorders -- Diagnosis -- Risk factors, Mentally ill -- Medical examination -- Technology application
Abstract

Author(s): Michael Wainberg 1, Samuel E. Jones 2,3, Lindsay Melhuish Beaupre 4,5, Sean L. Hill 1,5,6,7, Daniel Felsky 1,5,6,8, Manuel A. Rivas 9, Andrew S. P. Lim 10,11, Hanna M. [...], Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures-bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration-were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was [beta] = -0.11 (95% confidence interval -0.13 to -0.10, p = 3 x 10.sup.-56, FDR = 6 x 10.sup.-55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

Published
2021
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38. The public health impact of poor sleep on severe COVID-19, influenza and upper respiratory infections

Author

Jones, Samuel E., primary, Maisha, Fahrisa I., additional, Strausz, Satu J., additional, Lammi, Vilma, additional, Cade, Brian E., additional, Tervi, Anniina, additional, Helaakoski, Viola, additional, Broberg, Martin E., additional, Lane, Jacqueline M., additional, Redline, Susan, additional, Saxena, Richa, additional, Ollila, Hanna M., additional, Palotie, Aarno, additional, Daly, Mark, additional, Riley-Gills, Bridget, additional, Jacob, Howard, additional, Paul, Dirk, additional, Petrovski, Slavé, additional, Runz, Heiko, additional, John, Sally, additional, Okafo, George, additional, Lawless, Nathan, additional, Salminen-Mankonen, Heli, additional, Plenge, Robert, additional, Maranville, Joseph, additional, McCarthy, Mark, additional, Ehm, Margaret G., additional, Auro, Kirsi, additional, Longerich, Simonne, additional, Mälarstig, Anders, additional, Klinger, Katherine, additional, Chatelain, Clement, additional, Gossel, Matthias, additional, Estrada, Karol, additional, Graham, Robert, additional, Yang, Robert, additional, O´Donnell, Chris, additional, Mäkelä, Tomi P., additional, Kaprio, Jaakko, additional, Virolainen, Petri, additional, Hakanen, Antti, additional, Kilpi, Terhi, additional, Perola, Markus, additional, Partanen, Jukka, additional, Pitkäranta, Anne, additional, Raivio, Taneli, additional, Tikkanen, Jani, additional, Serpi, Raisa, additional, Laitinen, Tarja, additional, Kosma, Veli-Matti, additional, Laukkanen, Jari, additional, Hautalahti, Marco, additional, Tuovila, Outi, additional, Pakkanen, Raimo, additional, Waring, Jeffrey, additional, Riley-Gillis, Bridget, additional, Rahimov, Fedik, additional, Tachmazidou, Ioanna, additional, Chen, Chia-Yen, additional, Ding, Zhihao, additional, Jung, Marc, additional, Biswas, Shameek, additional, Pendergrass, Rion, additional, Pulford, David, additional, Raghavan, Neha, additional, Huertas-Vazquez, Adriana, additional, Sul, Jae-Hoon, additional, Hu, Xinli, additional, Hedman, Åsa, additional, Rivas, Manuel, additional, Waterworth, Dawn, additional, Renaud, Nicole, additional, Obeidat, Ma´en, additional, Ripatti, Samuli, additional, Schleutker, Johanna, additional, Arvas, Mikko, additional, Carpén, Olli, additional, Hinttala, Reetta, additional, Kettunen, Johannes, additional, Mannermaa, Arto, additional, Aalto-Setälä, Katriina, additional, Kähönen, Mika, additional, Mäkelä, Johanna, additional, Kälviäinen, Reetta, additional, Julkunen, Valtteri, additional, Soininen, Hilkka, additional, Remes, Anne, additional, Hiltunen, Mikko, additional, Peltola, Jukka, additional, Raivio, Minna, additional, Tienari, Pentti, additional, Rinne, Juha, additional, Kallionpää, Roosa, additional, Partanen, Juulia, additional, Abbasi, Ali, additional, Ziemann, Adam, additional, Smaoui, Nizar, additional, Lehtonen, Anne, additional, Eaton, Susan, additional, Lahdenperä, Sanni, additional, Bowers, Natalie, additional, Teng, Edmond, additional, Xu, Fanli, additional, Addis, Laura, additional, Eicher, John, additional, Li, Qingqin S., additional, He, Karen, additional, Khramtsova, Ekaterina, additional, Färkkilä, Martti, additional, Koskela, Jukka, additional, Pikkarainen, Sampsa, additional, Jussila, Airi, additional, Kaukinen, Katri, additional, Blomster, Timo, additional, Kiviniemi, Mikko, additional, Voutilainen, Markku, additional, Lu, Tim, additional, McCarthy, Linda, additional, Hart, Amy, additional, Guan, Meijian, additional, Miller, Jason, additional, Kalpala, Kirsi, additional, Miller, Melissa, additional, Eklund, Kari, additional, Palomäki, Antti, additional, Isomäki, Pia, additional, Pirilä, Laura, additional, Kaipiainen-Seppänen, Oili, additional, Huhtakangas, Johanna, additional, Mars, Nina, additional, Lertratanakul, Apinya, additional, Viollet, Coralie, additional, Hochfeld, Marla, additional, Gordillo, Jorge Esparza, additional, Farias, Fabiana, additional, Bing, Nan, additional, Pelkonen, Margit, additional, Kauppi, Paula, additional, Kankaanranta, Hannu, additional, Harju, Terttu, additional, Lahesmaa, Riitta, additional, Chen, Hubert, additional, Betts, Joanna, additional, Mishra, Rajashree, additional, Mouded, Majd, additional, Ngo, Debby, additional, Niiranen, Teemu, additional, Vaura, Felix, additional, Salomaa, Veikko, additional, Metsärinne, Kaj, additional, Aittokallio, Jenni, additional, Hernesniemi, Jussi, additional, Gordin, Daniel, additional, Sinisalo, Juha, additional, Taskinen, Marja-Riitta, additional, Tuomi, Tiinamaija, additional, Hiltunen, Timo, additional, Elliott, Amanda, additional, Reeve, Mary Pat, additional, Ruotsalainen, Sanni, additional, Chu, Audrey, additional, Reilly, Dermot, additional, Mendelson, Mike, additional, Parkkinen, Jaakko, additional, Meretoja, Tuomo, additional, Joensuu, Heikki, additional, Mattson, Johanna, additional, Salminen, Eveliina, additional, Auranen, Annika, additional, Karihtala, Peeter, additional, Auvinen, Päivi, additional, Elenius, Klaus, additional, Pitkänen, Esa, additional, Popovic, Relja, additional, Fabre, Margarete, additional, Schutzman, Jennifer, additional, Kulkarni, Diptee, additional, Porello, Alessandro, additional, Loboda, Andrey, additional, Lehtonen, Heli, additional, McDonough, Stefan, additional, Vuoti, Sauli, additional, Kaarniranta, Kai, additional, Turunen, Joni A., additional, Ollila, Terhi, additional, Uusitalo, Hannu, additional, Karjalainen, Juha, additional, Liu, Mengzhen, additional, Loomis, Stephanie, additional, Strauss, Erich, additional, Chen, Hao, additional, Tasanen, Kaisa, additional, Huilaja, Laura, additional, Hannula-Jouppi, Katariina, additional, Salmi, Teea, additional, Peltonen, Sirkku, additional, Koulu, Leena, additional, Choy, David, additional, Wu, Ying, additional, Pussinen, Pirkko, additional, Salminen, Aino, additional, Salo, Tuula, additional, Rice, David, additional, Nieminen, Pekka, additional, Palotie, Ulla, additional, Siponen, Maria, additional, Suominen, Liisa, additional, Mäntylä, Päivi, additional, Gursoy, Ulvi, additional, Anttonen, Vuokko, additional, Sipilä, Kirsi, additional, Laivuori, Hannele, additional, Kurra, Venla, additional, Kotaniemi-Talonen, Laura, additional, Heikinheimo, Oskari, additional, Kalliala, Ilkka, additional, Aaltonen, Lauri, additional, Jokimaa, Varpu, additional, Vääräsmäki, Marja, additional, Uimari, Outi, additional, Morin-Papunen, Laure, additional, Niinimäki, Maarit, additional, Piltonen, Terhi, additional, Kivinen, Katja, additional, Widen, Elisabeth, additional, Tukiainen, Taru, additional, Välimäki, Niko, additional, Laakkonen, Eija, additional, Tyrmi, Jaakko, additional, Silven, Heidi, additional, Sliz, Eeva, additional, Arffman, Riikka, additional, Savukoski, Susanna, additional, Laisk, Triin, additional, Pujol, Natalia, additional, Kumar, Janet, additional, Hovatta, Iiris, additional, Isometsä, Erkki, additional, Ollila, Hanna, additional, Suvisaari, Jaana, additional, Als, Thomas Damm, additional, Mäkitie, Antti, additional, Bizaki-Vallaskangas, Argyro, additional, Toppila-Salmi, Sanna, additional, Willberg, Tytti, additional, Saarentaus, Elmo, additional, Aarnisalo, Antti, additional, Rahikkala, Elisa, additional, Aittomäki, Kristiina, additional, Åberg, Fredrik, additional, Kurki, Mitja, additional, Havulinna, Aki, additional, Mehtonen, Juha, additional, Palta, Priit, additional, Hassan, Shabbeer, additional, Della Briotta Parolo, Pietro, additional, Zhou, Wei, additional, Maasha, Mutaamba, additional, Lemmelä, Susanna, additional, Liu, Aoxing, additional, Lehisto, Arto, additional, Ganna, Andrea, additional, Llorens, Vincent, additional, Heyne, Henrike, additional, Rämö, Joel, additional, Rodosthenous, Rodos, additional, Strausz, Satu, additional, Palotie, Tuula, additional, Palin, Kimmo, additional, Garcia-Tabuenca, Javier, additional, Siirtola, Harri, additional, Kiiskinen, Tuomo, additional, Lee, Jiwoo, additional, Tsuo, Kristin, additional, Kristiansson, Kati, additional, Hyvärinen, Kati, additional, Ritari, Jarmo, additional, Pylkäs, Katri, additional, Karjalainen, Minna, additional, Mantere, Tuomo, additional, Kangasniemi, Eeva, additional, Heikkinen, Sami, additional, Pitkänen, Nina, additional, Lessard, Samuel, additional, Chatelain, Clément, additional, Kallio, Lila, additional, Wahlfors, Tiina, additional, Punkka, Eero, additional, Siltanen, Sanna, additional, Kuopio, Teijo, additional, Jalanko, Anu, additional, Shen, Huei-Yi, additional, Kajanne, Risto, additional, Aavikko, Mervi, additional, Leinonen, Rasko, additional, Palin, Henna, additional, Linna, Malla-Maria, additional, Kanai, Masahiro, additional, Zheng, Zhili, additional, Lahtela, L. Elisa, additional, Kaunisto, Mari, additional, Kilpeläinen, Elina, additional, Sipilä, Timo P., additional, Dada, Oluwaseun Alexander, additional, Ghazal, Awaisa, additional, Kytölä, Anastasia, additional, Weldatsadik, Rigbe, additional, Donner, Kati, additional, Loukola, Anu, additional, Laiho, Päivi, additional, Sistonen, Tuuli, additional, Kaiharju, Essi, additional, Laukkanen, Markku, additional, Järvensivu, Elina, additional, Lähteenmäki, Sini, additional, Männikkö, Lotta, additional, Wong, Regis, additional, Toivola, Auli, additional, Brunfeldt, Minna, additional, Mattsson, Hannele, additional, Koskelainen, Sami, additional, Hiekkalinna, Tero, additional, Paajanen, Teemu, additional, Pärn, Kalle, additional, Kals, Mart, additional, Luo, Shuang, additional, Padmanabhuni, Shanmukha Sampath, additional, Niemi, Marianna, additional, Gracia-Tabuenca, Javier, additional, Helminen, Mika, additional, Luukkaala, Tiina, additional, Vähätalo, Iida, additional, Tammerluoto, Jyrki, additional, Smith, Sarah, additional, Southerington, Tom, additional, and Lehto, Petri, additional

Published
2023
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39. Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes

Author

Wang, Heming, Lane, Jacqueline M., Jones, Samuel E., Dashti, Hassan S., Ollila, Hanna M., Wood, Andrew R., van Hees, Vincent T., Brumpton, Ben, Winsvold, Bendik S., Kantojärvi, Katri, Palviainen, Teemu, Cade, Brian E., Sofer, Tamar, Song, Yanwei, Patel, Krunal, Anderson, Simon G., Bechtold, David A., Bowden, Jack, Emsley, Richard, Kyle, Simon D., Little, Max A., Loudon, Andrew S., Scheer, Frank A. J. L., Purcell, Shaun M., Richmond, Rebecca C., Spiegelhalder, Kai, Tyrrell, Jessica, Zhu, Xiaofeng, Hublin, Christer, Kaprio, Jaakko A., Kristiansson, Kati, Sulkava, Sonja, Paunio, Tiina, Hveem, Kristian, Nielsen, Jonas B., Willer, Cristen J., Zwart, John-Anker, Strand, Linn B., Frayling, Timothy M., Ray, David, Lawlor, Deborah A., Rutter, Martin K., Weedon, Michael N., Redline, Susan, and Saxena, Richa

Published
2019
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40. Causal association between subtypes of excessive daytime sleepiness and risk of cardiovascular diseases

Author

Peker, Yüksel (ORCID 0000-0001-9067-6538 & YÖK ID 234103), Goodman, Matthew O.; Dashti, Hassan S.; Lane, Jacqueline M.; Windred, Daniel P.; Burns, Angus; Jones, Samuel E.; Sofer, Tamar; Purcell, Shaun M.; Zhu, Xiaofeng; Ollila, Hanna M.; Kyle, Simon D.; Spiegelhalder, Kai; Huang, Tianyi; Cain, Sean W.; Phillips, Andrew J. K.; Saxena, Richa; Rutter, Martin K.; Redline, Susan; Wang, Heming, School of Medicine, Peker, Yüksel (ORCID 0000-0001-9067-6538 & YÖK ID 234103), Goodman, Matthew O.; Dashti, Hassan S.; Lane, Jacqueline M.; Windred, Daniel P.; Burns, Angus; Jones, Samuel E.; Sofer, Tamar; Purcell, Shaun M.; Zhu, Xiaofeng; Ollila, Hanna M.; Kyle, Simon D.; Spiegelhalder, Kai; Huang, Tianyi; Cain, Sean W.; Phillips, Andrew J. K.; Saxena, Richa; Rutter, Martin K.; Redline, Susan; Wang, Heming, and School of Medicine

Abstract

Background: excessive daytime sleepiness (EDS), experienced in 10% to 20% of the population, has been associated with cardiovascular disease and death. However, the condition is heterogeneous and is prevalent in individuals having short and long sleep duration. We sought to clarify the relationship between sleep duration subtypes of EDS with cardiovascular outcomes, accounting for these subtypes. Methods and results: we defined 3 sleep duration subtypes of excessive daytime sleepiness: normal (6-9?hours), short (<6?hours), and long (>9?hours), and compared these with a nonsleepy, normal-sleep-duration reference group. We analyzed their associations with incident myocardial infarction (MI) and stroke using medical records of 355?901 UK Biobank participants and performed 2-sample Mendelian randomization for each outcome. Compared with healthy sleep, long-sleep EDS was associated with an 83% increased rate of MI (hazard ratio, 1.83 [95% CI, 1.21-2.77]) during 8.2-year median follow-up, adjusting for multiple health and sociodemographic factors. Mendelian randomization analysis provided supporting evidence of a causal role for a genetic long-sleep EDS subtype in MI (inverse-variance weighted ?=1.995, P=0.001). In contrast, we did not find evidence that other subtypes of EDS were associated with incident MI or any associations with stroke (P>0.05). Conclusions: our study suggests the previous evidence linking EDS with increased cardiovascular disease risk may be primarily driven by the effect of its long-sleep subtype on higher risk of MI. Underlying mechanisms remain to be investigated but may involve sleep irregularity and circadian disruption, suggesting a need for novel interventions in this population., This work was supported by the National Institute of Health grants R01HL153814 (to H.W.), National Heart, Lung, and Blood Institute R35HL135818 (to S.R.), and National Institute for Health and Care Research Manchester Biomedical Research Centre.

Published
2023

41. Polycystic ovary syndrome is associated with weight-loss attempts and perception of overweight independent of BMI:a population-based cohort study

Author

Pesonen, E. (Emilia), Nurkkala, M. (Marjukka), Niemelä, M. (Maisa), Morin-Papunen, L. (Laure), Tapanainen, J. S. (Juha S.), Jämsä, T. (Timo), Korpelainen, R. (Raija), Ollila, M.-M. (Meri-Maija), Piltonen, T. T. (Terhi T.), Pesonen, E. (Emilia), Nurkkala, M. (Marjukka), Niemelä, M. (Maisa), Morin-Papunen, L. (Laure), Tapanainen, J. S. (Juha S.), Jämsä, T. (Timo), Korpelainen, R. (Raija), Ollila, M.-M. (Meri-Maija), and Piltonen, T. T. (Terhi T.)

Abstract

Objectives: Up to 70% of women with polycystic ovary syndrome (PCOS) have pre-obesity or obesity. The aim of this study was to investigate whether women with PCOS have more weight-loss attempts than women without PCOS, regardless of BMI. Moreover, women's weight perceptions in relation to previous weight-loss attempts were evaluated. Methods: A population-based birth cohort study included women with (n = 278) and without PCOS (control individuals, n = 1560) who were examined at ages 31 and 46 years with questionnaires and clinical examinations. Results: Women with PCOS had more weight-loss attempts compared with control individuals at age 31 (47% vs. 34%, p <0.001) and 46 years (63% vs. 47%, p < 0.001). At age 46 years, PCOS was associated with multiple weight-loss attempts in the adjusted model (odds ratio: 1.43 [95% CI: 1.00‐2.03], p = 0.05). The perception of having overweight was more prevalent in those with PCOS, even among participants with normal weight, at age 31 (PCOS 47% vs. control 34%, p = 0.014) and 46 years (PCOS 60% vs. control 39%, p = 0.001). Conclusions: Women with PCOS were more likely to have experienced multiple weight-loss attempts and a perception of having overweight compared with control individuals, regardless of obesity status.

Published
2023

42. Narcolepsy risk loci outline role of T cell autoimmunity and infectious triggers in narcolepsy

Author

Ollila, Hanna M., Sharon, Eilon, Lin, Ling, Sinnott-Armstrong, Nasa, Ambati, Aditya, Yogeshwar, Selina M., Hillary, Ryan P., Jolanki, Otto, Faraco, Juliette, Einen, Mali, Luo, Guo, Zhang, Jing, Han, Fang, Yan, Han, Dong, Xiao Song, Li, Jing, Zhang, Jun, Hong, Seung-Chul, Kim, Tae Won, Dauvilliers, Yves, Barateau, Lucie, Lammers, Gert Jan, Fronczek, Rolf, Mayer, Geert, Santamaria, Joan, Arnulf, Isabelle, Knudsen-Heier, Stine, Bredahl, May Kristin Lyamouri, Thorsby, Per Medboe, Plazzi, Giuseppe, Pizza, Fabio, Moresco, Monica, Crowe, Catherine, Van den Eeden, Stephen K., Lecendreux, Michel, Bourgin, Patrice, Kanbayashi, Takashi, Martinez-Orozco, Francisco J., Peraita-Adrados, Rosa, Beneto, Antonio, Montplaisir, Jacques, Desautels, Alex, Huang, Yu-Shu, FinnGen, Poul Jennum, Jennum, Poul, Nevsimalova, Sona, Kemlink, David, Iranzo, Alex, Overeem, Sebastiaan, Wierzbicka, Aleksandra, Geisler, Peter, Sonka, Karel, Honda, Makoto, Högl, Birgit, Stefani, Ambra, Coelho, Fernando Morgadinho, Mantovani, Vilma, Feketeova, Eva, Wadelius, Mia, Eriksson, Niclas, Smedje, Hans, Hallberg, Pär, Hesla, Per Egil, Rye, David, Pelin, Zerrin, Ferini-Strambi, Luigi, Bassetti, Claudio L., Mathis, Johannes, Khatami, Ramin, Aran, Adi, Nampoothiri, Sheela, Olsson, Tomas, Kockum, Ingrid, Partinen, Markku, Perola, Markus, Kornum, Birgitte R., Rueger, Sina, Winkelmann, Juliane, Miyagawa, Taku, Toyoda, Hiromi, Khor, Seik-Soon, Shimada, Mihoko, Tokunaga, Katsushi, Rivas, Manuel, Pritchard, Jonathan K., Risch, Neil, Kutalik, Zoltan, O'Hara, Ruth, Hallmayer, Joachim, Ye, Chun Jimmie, Mignot, Emmanuel J., Ollila, Hanna M., Sharon, Eilon, Lin, Ling, Sinnott-Armstrong, Nasa, Ambati, Aditya, Yogeshwar, Selina M., Hillary, Ryan P., Jolanki, Otto, Faraco, Juliette, Einen, Mali, Luo, Guo, Zhang, Jing, Han, Fang, Yan, Han, Dong, Xiao Song, Li, Jing, Zhang, Jun, Hong, Seung-Chul, Kim, Tae Won, Dauvilliers, Yves, Barateau, Lucie, Lammers, Gert Jan, Fronczek, Rolf, Mayer, Geert, Santamaria, Joan, Arnulf, Isabelle, Knudsen-Heier, Stine, Bredahl, May Kristin Lyamouri, Thorsby, Per Medboe, Plazzi, Giuseppe, Pizza, Fabio, Moresco, Monica, Crowe, Catherine, Van den Eeden, Stephen K., Lecendreux, Michel, Bourgin, Patrice, Kanbayashi, Takashi, Martinez-Orozco, Francisco J., Peraita-Adrados, Rosa, Beneto, Antonio, Montplaisir, Jacques, Desautels, Alex, Huang, Yu-Shu, FinnGen, Poul Jennum, Jennum, Poul, Nevsimalova, Sona, Kemlink, David, Iranzo, Alex, Overeem, Sebastiaan, Wierzbicka, Aleksandra, Geisler, Peter, Sonka, Karel, Honda, Makoto, Högl, Birgit, Stefani, Ambra, Coelho, Fernando Morgadinho, Mantovani, Vilma, Feketeova, Eva, Wadelius, Mia, Eriksson, Niclas, Smedje, Hans, Hallberg, Pär, Hesla, Per Egil, Rye, David, Pelin, Zerrin, Ferini-Strambi, Luigi, Bassetti, Claudio L., Mathis, Johannes, Khatami, Ramin, Aran, Adi, Nampoothiri, Sheela, Olsson, Tomas, Kockum, Ingrid, Partinen, Markku, Perola, Markus, Kornum, Birgitte R., Rueger, Sina, Winkelmann, Juliane, Miyagawa, Taku, Toyoda, Hiromi, Khor, Seik-Soon, Shimada, Mihoko, Tokunaga, Katsushi, Rivas, Manuel, Pritchard, Jonathan K., Risch, Neil, Kutalik, Zoltan, O'Hara, Ruth, Hallmayer, Joachim, Ye, Chun Jimmie, and Mignot, Emmanuel J.

Abstract

Narcolepsy type 1 (NT1) is caused by a loss of hypocretin/orexin transmission. Risk factors include pandemic 2009 H1N1 influenza A infection and immunization with Pandemrix (R). Here, we dissect disease mechanisms and interactions with environmental triggers in a multi-ethnic sample of 6,073 cases and 84,856 controls. We fine-mapped GWAS signals within HLA (DQ0602, DQB1*03:01 and DPB1*04:02) and discovered seven novel associations (CD207, NAB1, IKZF4-ERBB3, CTSC, DENND1B, SIRPG, PRF1). Significant signals at TRA and DQB1*06:02 loci were found in 245 vaccination-related cases, who also shared polygenic risk. T cell receptor associations in NT1 modulated TRAJ*24, TRAJ*28 and TRBV*4-2 chain-usage. Partitioned heritability and immune cell enrichment analyses found genetic signals to be driven by dendritic and helper T cells. Lastly comorbidity analysis using data from FinnGen, suggests shared effects between NT1 and other autoimmune diseases. NT1 genetic variants shape autoimmunity and response to environmental triggers, including influenza A infection and immunization with Pandemrix (R).

Published
2023
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43. AMH as part of the diagnostic PCOS workup in large epidemiological studies

Author

Piltonen, T. T. (Terhi T.), Komsi, E. (Elina), Morin-Papunen, L. C. (Laure C.), Korhonen, E. (Elisa), Franks, S. (Stephen), Järvelin, M.-R. (Marjo-Riitta), Arffman, R. K. (Riikka K.), Ollila, M.-M. (Meri-Maija), Piltonen, T. T. (Terhi T.), Komsi, E. (Elina), Morin-Papunen, L. C. (Laure C.), Korhonen, E. (Elisa), Franks, S. (Stephen), Järvelin, M.-R. (Marjo-Riitta), Arffman, R. K. (Riikka K.), and Ollila, M.-M. (Meri-Maija)

Abstract

Objectives: Previous studies have shown good correlation between polycystic ovarian morphology (PCOM) and serum anti-Müllerian hormone (AMH) levels. We evaluated the utility of AMH as a surrogate for PCOM as a part of the polycystic ovary syndrome (PCOS) diagnosis by describing how the use of different AMH cut-off values would change the prevalence of PCOS. Methods: A general population-based birth cohort study. Anti-Müllerian hormone concentrations were measured from serum samples taken at age 31 years (n = 2917) using the electrochemiluminescence immunoassay (Elecsys). Anti-Müllerian hormone data were combined with data on oligo/amenorrhoea and hyperandrogenism to identify women with PCOS. Results: The addition of AMH as a surrogate marker for PCOM increased the number of women fulfilling at least two PCOS features in accordance with the Rotterdam criteria. The prevalence of PCOS was 5.9% when using the AMH cut-off based on the 97.5% quartile (10.35 ng/mL) and 13.6% when using the recently proposed cut-off of 3.2 ng/mL. When using the latter cut-off value, the distribution of PCOS phenotypes A, B, C, and D was 23.9%, 4.7%, 36.6%, and 34.8%, respectively. Compared with the controls, all PCOS groups with different AMH concentration cut-offs showed significantly elevated testosterone (T), free androgen index (FAI), luteinizing hormone (LH), LH/follicle-stimulating hormone (FSH) ratio, body mass index (BMI), waist circumference, and homoeostatic model assessment of insulin resistance (HOMA-IR) values, as well as significantly decreased sex hormone-binding globulin (SHBG) values. Conclusions: Anti-Müllerian hormone could be useful surrogate for PCOM in large data sets, where transvaginal ultrasound is not feasible, to aid the capturing of women with typical PCOS characteristics. Anti-Müllerian hormone measurement from archived samples enables retrospective PCOS diagnosis when combined with oligo/amenorrhoea or hyperandrogenism.

Published
2023

44. Women with PCOS have an increased risk for cardiovascular disease regardless of diagnostic criteria:a prospective population-based cohort study

Author

Ollila, M.-M. (Meri-Maija), Arffman, R. K. (Riikka K.), Korhonen, E. (Elisa), Morin-Papunen, L. (Laure), Franks, S. (Stephen), Junttila, J. (Juhani), Piltonen, T. T. (Terhi T.), Ollila, M.-M. (Meri-Maija), Arffman, R. K. (Riikka K.), Korhonen, E. (Elisa), Morin-Papunen, L. (Laure), Franks, S. (Stephen), Junttila, J. (Juhani), and Piltonen, T. T. (Terhi T.)

Abstract

Objective: Polycystic ovary syndrome (PCOS) is associated with many cardiovascular disease (CVD) risk factors, such as obesity, type 2 diabetes mellitus and hypertension. However, it remains debatable whether the presence of multiple CVD risk factors translates to increased CVD events. Desing: A prospective, population-based Northern Finland Birth Cohort 1966. Methods: Individuals with an expected date of birth in 1966 in Northern Finland have been followed from birth. Women in the cohort were classified as having PCOS according to either the National Institute of Health (NIH) criteria (n = 144) or the Rotterdam criteria (n = 386) at age 31, and they were compared to women without any PCOS features. The study population was re-examined at age 46, and the incidence of major adverse cardiovascular events (MACE), including myocardial infarction (MI), stroke, heart failure and cardiovascular mortality, was recorded up to age 53. Results: During the 22-year follow-up, both women with NIH-PCOS and women with Rotterdam-PCOS had a significantly higher risk for cardiovascular events than control women. The BMI-adjusted hazard ratio (HR) for MACE in the Rotterdam-PCOS group and the NIH-PCOS group was 2.33 (1.26–4.30) and 2.47 (1.18–5.17), respectively. The cumulative hazard curves in both diagnostic categories began to diverge at age 35. Regarding the individual CVD endpoints, MI was significantly more prevalent in both women with NIH-PCOS (P = 0.010) and women with Rotterdam-PCOS (P = 0.019), when compared to control women. Conclusions: PCOS should be considered a significant risk factor for CVD. Future follow-up will show how the risk of CVD events develops after menopausal age.

Published
2023

45. Dark microbiome and extremely low organics in Atacama fossil delta unveil Mars life detection limits

Author

European Commission, Ministerio de Economía y Competitividad (España), Comunidad de Madrid, Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), Azua-Bustos, Armando, Farién, Alberto G., González-Silva, Carlos, Prieto-Ballesteros, Olga, Carrizo, Daniel, Sánchez-García, Laura, Parro, Víctor, Fernández-Martínez, Miguel Ángel, Escudero, Cristina, Muñoz-Iglesias, Victoria, Fernández-Sampedro, Maite, Molina, Antonio, García Villadangos, Miriam, Moreno-Paz, Mercedes, Wierzchos, Jacek, Ascaso, Carmen, Fornaro, Teresa, Brucato, John Robert, Poggiali, Giovanni, Manrique, José Antonio, Veneranda, Marco, López-Reyes, Guilermo, Sanz-Arranz, Aurelio, Rull, Fernando, Ollila, Ann M., Wiens, Roger C., Reyes-Newell, Adriana, Clegg, Samuel M., Millán, Maëva, Stewart Johnson, Sarah, McIntosh, Ophélie, Szopa, Cyril, Freissinet, Caroline, Sekine, Yasuhito, Fukushi, Keisuke, Morida, Koki, Inoue, Kosuke, Sakuma, Hiroshi, Rampe, Elisabeth, European Commission, Ministerio de Economía y Competitividad (España), Comunidad de Madrid, Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), Azua-Bustos, Armando, Farién, Alberto G., González-Silva, Carlos, Prieto-Ballesteros, Olga, Carrizo, Daniel, Sánchez-García, Laura, Parro, Víctor, Fernández-Martínez, Miguel Ángel, Escudero, Cristina, Muñoz-Iglesias, Victoria, Fernández-Sampedro, Maite, Molina, Antonio, García Villadangos, Miriam, Moreno-Paz, Mercedes, Wierzchos, Jacek, Ascaso, Carmen, Fornaro, Teresa, Brucato, John Robert, Poggiali, Giovanni, Manrique, José Antonio, Veneranda, Marco, López-Reyes, Guilermo, Sanz-Arranz, Aurelio, Rull, Fernando, Ollila, Ann M., Wiens, Roger C., Reyes-Newell, Adriana, Clegg, Samuel M., Millán, Maëva, Stewart Johnson, Sarah, McIntosh, Ophélie, Szopa, Cyril, Freissinet, Caroline, Sekine, Yasuhito, Fukushi, Keisuke, Morida, Koki, Inoue, Kosuke, Sakuma, Hiroshi, and Rampe, Elisabeth

Abstract

Identifying unequivocal signs of life on Mars is one of the most important objectives for sending missions to the red planet. Here we report Red Stone, a 163-100 My alluvial fan–fan delta that formed under arid conditions in the Atacama Desert, rich in hematite and mudstones containing clays such as vermiculite and smectites, and therefore geologically analogous to Mars. We show that Red Stone samples display an important number of microorganisms with an unusual high rate of phylogenetic indeterminacy, what we refer to as “dark microbiome”, and a mix of biosignatures from extant and ancient microorganisms that can be barely detected with state-of-the-art laboratory equipment. Our analyses by testbed instruments that are on or will be sent to Mars unveil that although the mineralogy of Red Stone matches that detected by ground-based instruments on the red planet, similarly low levels of organics will be hard, if not impossible to detect in Martian rocks depending on the instrument and technique used. Our results stress the importance in returning samples to Earth for conclusively addressing whether life ever existed on Mars.

Published
2023

46. Large registry-based analysis of genetic predisposition to tuberculosis identifies genetic risk factors at HLA

Author

Massachusetts Institute of Technology. Department of Biological Engineering, Tervi, Anniina, Junna, Nella, Broberg, Martin, Jones, Samuel E, Partinen, Markku, Pirinen, Matti, Bryson, Bryan, Strausz, Satu, Kreivi, Hanna-Riikka, Heckman, Caroline A, Ollila, Hanna M, Massachusetts Institute of Technology. Department of Biological Engineering, Tervi, Anniina, Junna, Nella, Broberg, Martin, Jones, Samuel E, Partinen, Markku, Pirinen, Matti, Bryson, Bryan, Strausz, Satu, Kreivi, Hanna-Riikka, Heckman, Caroline A, and Ollila, Hanna M

Abstract

Abstract Tuberculosis is a significant public health concern resulting in the death of over 1 million individuals each year worldwide. While treatment options and vaccines exist, a substantial number of infections still remain untreated or are caused by treatment resistant strains. Therefore, it is important to identify mechanisms that contribute to risk and prognosis of tuberculosis as this may provide tools to understand disease mechanisms and provide novel treatment options for those with severe infection. Our goal was to identify genetic risk factors that contribute to the risk of tuberculosis and to understand biological mechanisms and causality behind the risk of tuberculosis. A total of 1895 individuals in the FinnGen study had International Classification of Diseases-based tuberculosis diagnosis. Genome-wide association study analysis identified genetic variants with statistically significant association with tuberculosis at the human leukocyte antigen (HLA) region (P < 5e−8). Fine mapping of the HLA association provided evidence for one protective haplotype tagged by HLA DQB1*05:01 (P = 1.82E−06, OR = 0.81 [CI 95% 0.74–0.88]), and predisposing alleles tagged by HLA DRB1*13:02 (P = 0.00011, OR = 1.35 [CI 95% 1.16–1.57]). Furthermore, genetic correlation analysis showed association with earlier reported risk factors including smoking (P < 0.05). Mendelian randomization supported smoking as a risk factor for tuberculosis (inverse-variance weighted P < 0.05, OR = 1.83 [CI 95% 1.15–2.93]) with no significant evidence of pleiotropy. Our findings indicate that specific HLA alleles associate with the risk of tuberculosis. In addition, lifestyle risk factors such as smoking contribute to the risk of developing tuberculosis.

Published
2023

47. Genome-wide association studies highlight novel risk loci for septal defects and left-sided congenital heart defects.

Author

Broberg, Martin, Ampuja, Minna, Jones, Samuel, Ojala, Tiina, Rahkonen, Otto, Kivelä, Riikka, Priest, James, Palotie, Aarno, Ollila, Hanna M., and Helle, Emmi

Subjects
CONGENITAL heart disease, GENOME-wide association studies, HEREDITY, LOCUS (Genetics)
Abstract

Background: Congenital heart defects (CHD) are structural defects of the heart affecting approximately 1% of newborns. They exhibit low penetrance and non-Mendelian patterns of inheritance as varied and complex traits. While genetic factors are known to play an important role in the development of CHD, the specific genetics remain unknown for the majority of patients. To elucidate the underlying genetic risk, we performed a genome wide association study (GWAS) of CHDs in general and specific CHD subgroups using the FinnGen Release 10 (R10) (N > 393,000), followed by functional fine-mapping through eQTL and co-localization analyses using the GTEx database. Results: We discovered three genome-wide significant loci associated with general CHD. Two of them were located in chromosome 17: 17q21.32 (rs2316327, intronic: LRRC37A2, Odds ratio (OR) [95% Confidence Interval (CI)] = 1.17[1.12–1.23], p = 1.5 × 10–9) and 17q25.3 (rs1293973611, nearest: BAHCC1, OR[95%CI] = 4.48[2.80–7.17], p = 7.0 × 10–10), respectively, and in addition to general CHD, the rs1293973611 locus was associated with the septal defect subtype. The third locus was in band 1p21.2 (rs35046143, nearest: PALMD, OR[95%CI] = 1.15[1.09–1.21], p = 7.1 × 10–9), and it was associated with general CHD and left-sided lesions. In the subgroup analysis, two additional loci were associated with septal defects (rs75230966 and rs6824295), and one with left-sided lesions (rs1305393195). In the eQTL analysis the variants rs2316327 (general CHD), and rs75230966 (septal defects) both located in 17q21.32 (with a LD r2 of 0.41) were both predicted to significantly associate with the expression of WNT9B in the atrial appendage tissue category. This effect was further confirmed by co-localization analysis, which also implicated WNT3 expression in the atrial appendage. A meta-analysis of general CHD together with the UK Biobank (combined N = 881,678) provided a different genome-wide significant locus in LRRC37A2; rs16941382 (OR[95%CI] = 1.15[1.11–1.20], p = 1.5 × 10–9) which is in significant LD with rs2316327. Conclusions: Our results of general CHD and different CHD subcategories identified a complex risk locus on chromosome 17 near BAHCC1 and LRRC37A2, interacting with the genes WNT9B, WNT3 and MYL4, may constitute potential novel CHD risk associated loci, warranting future experimental tests to determine their role. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Apatites in Gale Crater

Author

Forni, O, Meslin, P.-Y, Drouet, C, Cousin, A, David, G, Mangold, N, Dehouck, E, Rampe, E. B, Gasnault, O, Nachon, M, Newsom, H, Blaney, D. L, Clegg, S. M, Ollila, A. M, Lasue, J, Maurice, S, and Wiens, R.C

Subjects
Space Sciences (General)
Abstract

ChemCam is an active remote sensing instrument suite that has operated successfully on MSL since landing Aug. 6th, 2012. It uses laser pulses to remove dust and to analyze rocks up to 7 m away. Laser-induced breakdown spectroscopy (LIBS) obtains emission spectra of materials ablated from the samples in electronically excited states. The intensities of the emission lines scale with the abundances of the related element. ChemCam is sensitive to most major rock-forming elements as well as to a set of minor and trace elements such as F, Cl, Li, P, Sr, Ba, and Rb. The measured chemical composition can then be used to infer the mineralogical composition of the ablated material. Here, we report a summary of inferred apatite detections along the MSL traverse at Gale Crater. We present the geologic settings of these findings and derive some interpretations about the formation conditions of apatite in time and space.

Published
2020

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