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1. Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Author

Shrine, Nick, Izquierdo, Abril G, Chen, Jing, Packer, Richard, Hall, Robert J, Guyatt, Anna L, Batini, Chiara, Thompson, Rebecca J, Pavuluri, Chandan, Malik, Vidhi, Hobbs, Brian D, Moll, Matthew, Kim, Wonji, Tal-Singer, Ruth, Bakke, Per, Fawcett, Katherine A, John, Catherine, Coley, Kayesha, Piga, Noemi Nicole, Pozarickij, Alfred, Lin, Kuang, Millwood, Iona Y, Chen, Zhengming, Li, Liming, China Kadoorie Biobank Collaborative Group, Wijnant, Sara RA, Lahousse, Lies, Brusselle, Guy, Uitterlinden, Andre G, Manichaikul, Ani, Oelsner, Elizabeth C, Rich, Stephen S, Barr, R Graham, Kerr, Shona M, Vitart, Veronique, Brown, Michael R, Wielscher, Matthias, Imboden, Medea, Jeong, Ayoung, Bartz, Traci M, Gharib, Sina A, Flexeder, Claudia, Karrasch, Stefan, Gieger, Christian, Peters, Annette, Stubbe, Beate, Hu, Xiaowei, Ortega, Victor E, Meyers, Deborah A, Bleecker, Eugene R, Gabriel, Stacey B, Gupta, Namrata, Smith, Albert Vernon, Luan, Jian'an, Zhao, Jing-Hua, Hansen, Ailin F, Langhammer, Arnulf, Willer, Cristen, Bhatta, Laxmi, Porteous, David, Smith, Blair H, Campbell, Archie, Sofer, Tamar, Lee, Jiwon, Daviglus, Martha L, Yu, Bing, Lim, Elise, Xu, Hanfei, O'Connor, George T, Thareja, Gaurav, Albagha, Omar ME, Qatar Genome Program Research (QGPR) Consortium, Suhre, Karsten, Granell, Raquel, Faquih, Tariq O, Hiemstra, Pieter S, Slats, Annelies M, Mullin, Benjamin H, Hui, Jennie, James, Alan, Beilby, John, Patasova, Karina, Hysi, Pirro, Koskela, Jukka T, Wyss, Annah B, Jin, Jianping, Sikdar, Sinjini, Lee, Mikyeong, May-Wilson, Sebastian, Pirastu, Nicola, Kentistou, Katherine A, Joshi, Peter K, Timmers, Paul RHJ, Williams, Alexander T, Free, Robert C, Wang, Xueyang, Morrison, John L, Gilliland, Frank D, Chen, Zhanghua, Wang, Carol A, Foong, Rachel E, Harris, Sarah E, Taylor, Adele, Redmond, Paul, Cook, James P, Mahajan, Anubha, Lind, Lars, Palviainen, Teemu, Lehtimäki, Terho, Raitakari, Olli T, Kaprio, Jaakko, Rantanen, Taina, Pietiläinen, Kirsi H, Cox, Simon R, Pennell, Craig E, Hall, Graham L, Gauderman, W James, Brightling, Chris, Wilson, James F, Vasankari, Tuula, Laitinen, Tarja, Salomaa, Veikko, Mook-Kanamori, Dennis O, Timpson, Nicholas J, Zeggini, Eleftheria, Dupuis, Josée, Hayward, Caroline, Brumpton, Ben, Langenberg, Claudia, Weiss, Stefan, Homuth, Georg, Schmidt, Carsten Oliver, Probst-Hensch, Nicole, Jarvelin, Marjo-Riitta, Morrison, Alanna C, Polasek, Ozren, Rudan, Igor, Lee, Joo-Hyeon, Sayers, Ian, Rawlins, Emma L, Dudbridge, Frank, Silverman, Edwin K, Strachan, David P, Walters, Robin G, Morris, Andrew P, London, Stephanie J, Cho, Michael H, Wain, Louise V, Hall, Ian P, Tobin, Martin D, Shrine, Nick [0000-0003-3641-4371], Chen, Jing [0000-0003-1287-1930], Guyatt, Anna L. [0000-0003-1860-6337], Hobbs, Brian D. [0000-0001-9564-0745], Kim, Wonji [0000-0002-1249-797X], Coley, Kayesha [0000-0003-4951-6799], Chen, Zhengming [0000-0001-6423-105X], Li, Liming [0000-0001-5873-7089], Lahousse, Lies [0000-0002-3494-4363], Uitterlinden, Andre G. [0000-0002-7276-3387], Oelsner, Elizabeth C. [0000-0002-7481-9671], Rich, Stephen S. [0000-0003-3872-7793], Kerr, Shona M. [0000-0002-4137-1495], Vitart, Veronique [0000-0002-4991-3797], Jeong, Ayoung [0000-0003-1542-0756], Gharib, Sina A. [0000-0002-2480-4367], Gieger, Christian [0000-0001-6986-9554], Peters, Annette [0000-0001-6645-0985], Hu, Xiaowei [0000-0001-7804-7392], Smith, Albert Vernon [0000-0003-1942-5845], Luan, Jian’an [0000-0003-3137-6337], Langhammer, Arnulf [0000-0001-5296-6673], Willer, Cristen [0000-0001-5645-4966], Porteous, David [0000-0003-1249-6106], Smith, Blair H. [0000-0002-5362-9430], Campbell, Archie [0000-0003-0198-5078], Sofer, Tamar [0000-0001-8520-8860], Lee, Jiwon [0000-0002-4079-7494], Lim, Elise [0000-0001-8967-8464], Thareja, Gaurav [0000-0003-2277-6400], Albagha, Omar M. E. [0000-0001-5916-5983], Suhre, Karsten [0000-0001-9638-3912], Granell, Raquel [0000-0002-4890-4012], Faquih, Tariq O. [0000-0001-8026-2251], Hiemstra, Pieter S. [0000-0002-0238-5982], Hysi, Pirro [0000-0001-5752-2510], Koskela, Jukka T. [0000-0002-0154-7222], Jin, Jianping [0000-0002-3774-1609], Sikdar, Sinjini [0000-0003-1230-5162], Lee, Mikyeong [0000-0002-3036-3684], May-Wilson, Sebastian [0000-0003-2668-5717], Joshi, Peter K. [0000-0002-6361-5059], Timmers, Paul R. H. J. [0000-0002-5197-1267], Gilliland, Frank D. [0000-0002-9033-7269], Wang, Carol A. [0000-0002-4301-3974], Harris, Sarah E. [0000-0002-4941-5106], Mahajan, Anubha [0000-0001-5585-3420], Palviainen, Teemu [0000-0002-7847-8384], Kaprio, Jaakko [0000-0002-3716-2455], Pietiläinen, Kirsi H. [0000-0002-8522-1288], Cox, Simon R. [0000-0003-4036-3642], Pennell, Craig E. [0000-0002-0937-6165], Wilson, James F. [0000-0001-5751-9178], Vasankari, Tuula [0000-0002-1413-8970], Salomaa, Veikko [0000-0001-7563-5324], Timpson, Nicholas J. [0000-0002-7141-9189], Dupuis, Josée [0000-0003-2871-3603], Brumpton, Ben [0000-0002-3058-1059], Langenberg, Claudia [0000-0002-5017-7344], Weiss, Stefan [0000-0002-3553-4315], Homuth, Georg [0000-0001-6839-0605], Jarvelin, Marjo-Riitta [0000-0002-2149-0630], Morrison, Alanna C. [0000-0001-6381-4296], Rudan, Igor [0000-0001-6993-6884], Lee, Joo-Hyeon [0000-0002-7364-6422], Sayers, Ian [0000-0001-5601-5410], Rawlins, Emma L. [0000-0001-7426-3792], Dudbridge, Frank [0000-0002-8817-8908], Strachan, David P. [0000-0001-7854-1366], Walters, Robin G. [0000-0002-9179-0321], Morris, Andrew P. [0000-0002-6805-6014], London, Stephanie J. [0000-0003-4911-5290], Cho, Michael H. [0000-0002-4907-1657], Wain, Louise V. [0000-0003-4951-1867], Hall, Ian P. [0000-0001-9933-3216], Tobin, Martin D. [0000-0002-3596-7874], Apollo - University of Cambridge Repository, Tampere University, Department of Clinical Chemistry, Clinical Medicine, Department of General Administration, Guyatt, Anna L [0000-0003-1860-6337], Hobbs, Brian D [0000-0001-9564-0745], Uitterlinden, Andre G [0000-0002-7276-3387], Oelsner, Elizabeth C [0000-0002-7481-9671], Rich, Stephen S [0000-0003-3872-7793], Kerr, Shona M [0000-0002-4137-1495], Gharib, Sina A [0000-0002-2480-4367], Luan, Jian'an [0000-0003-3137-6337], Smith, Blair H [0000-0002-5362-9430], Albagha, Omar ME [0000-0001-5916-5983], Faquih, Tariq O [0000-0001-8026-2251], Hiemstra, Pieter S [0000-0002-0238-5982], Koskela, Jukka T [0000-0002-0154-7222], Joshi, Peter K [0000-0002-6361-5059], Timmers, Paul RHJ [0000-0002-5197-1267], Gilliland, Frank D [0000-0002-9033-7269], Wang, Carol A [0000-0002-4301-3974], Harris, Sarah E [0000-0002-4941-5106], Pietiläinen, Kirsi H [0000-0002-8522-1288], Cox, Simon R [0000-0003-4036-3642], Pennell, Craig E [0000-0002-0937-6165], Wilson, James F [0000-0001-5751-9178], Timpson, Nicholas J [0000-0002-7141-9189], Morrison, Alanna C [0000-0001-6381-4296], Rawlins, Emma L [0000-0001-7426-3792], Strachan, David P [0000-0001-7854-1366], Walters, Robin G [0000-0002-9179-0321], Morris, Andrew P [0000-0002-6805-6014], London, Stephanie J [0000-0003-4911-5290], Cho, Michael H [0000-0002-4907-1657], Wain, Louise V [0000-0003-4951-1867], Hall, Ian P [0000-0001-9933-3216], Tobin, Martin D [0000-0002-3596-7874], Epidemiology, and Internal Medicine

Subjects
Smoking, 631/208/205/2138, 45/43, article, 692/699/1785, Polymorphism, Single Nucleotide, 3142 Public health care science, environmental and occupational health, Pulmonary Disease, Chronic Obstructive, Genetics, Humans, 1182 Biochemistry, cell and molecular biology, Genetic Predisposition to Disease, Lung, Genome-Wide Association Study
Abstract

Funder: British Lung Foundation, Funder: National Institute for Health Research (NIHR), Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

Published
2023

2. Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Author

Shrine, Nick, Izquierdo, Abril G, Chen, Jing, Packer, Richard, Hall, Robert J, Guyatt, Anna L, Batini, Chiara, Thompson, Rebecca J, Pavuluri, Chandan, Malik, Vidhi, Hobbs, Brian D, Moll, Matthew, Kim, Wonji, Tal-Singer, Ruth, Bakke, Per, Fawcett, Katherine A, John, Catherine, Coley, Kayesha, Piga, Noemi Nicole, Pozarickij, Alfred, Lin, Kuang, Millwood, Iona Y, Chen, Zhengming, Li, Liming, Wijnant, Sara RA, Lahousse, Lies, Brusselle, Guy, Uitterlinden, Andre G, Manichaikul, Ani, Oelsner, Elizabeth C, Rich, Stephen S, Barr, R Graham, Kerr, Shona M, Vitart, Veronique, Brown, Michael R, Wielscher, Matthias, Imboden, Medea, Jeong, Ayoung, Bartz, Traci M, Gharib, Sina A, Flexeder, Claudia, Karrasch, Stefan, Gieger, Christian, Peters, Annette, Stubbe, Beate, Hu, Xiaowei, Ortega, Victor E, Meyers, Deborah A, Bleecker, Eugene R, Gabriel, Stacey B, Gupta, Namrata, Smith, Albert Vernon, Luan, Jian’an, Zhao, Jing-Hua, Hansen, Ailin F, Langhammer, Arnulf, Willer, Cristen, Bhatta, Laxmi, Porteous, David, Smith, Blair H, Campbell, Archie, Sofer, Tamar, Lee, Jiwon, Daviglus, Martha L, Yu, Bing, Lim, Elise, Xu, Hanfei, O’Connor, George T, Thareja, Gaurav, Albagha, Omar ME, Ismail, Said I, Al-Muftah, Wadha, Badji, Radja, Mbarek, Hamdi, Darwish, Dima, Fadl, Tasnim, Yasin, Heba, Ennaifar, Maryem, Abdellatif, Rania, Alkuwari, Fatima, Alvi, Muhammad, Al-Sarraj, Yasser, Saad, Chadi, Althani, Asmaa, Fethnou, Eleni, Qafoud, Fatima, Alkhayat, Eiman, Afifi, Nahla, Tomei, Sara, Liu, Wei, Lorenz, Stephan, Syed, Najeeb, Almabrazi, Hakeem, Vempalli, Fazulur Rehaman, Temanni, Ramzi, Saqri, Tariq Abu, Khatib, Mohammedhusen, Hamza, Mehshad, Zaid, Tariq Abu, El Khouly, Ahmed, Pathare, Tushar, Poolat, Shafeeq, Al-Ali, Rashid, Al-Khodor, Souhaila, Alshafai, Mashael, Badii, Ramin, Chouchane, Lotfi, Estivill, Xavier, Fakhro, Khalid, Mokrab, Younes, Puthen, Jithesh V, Tatari, Zohreh, Suhre, Karsten, Granell, Raquel, Faquih, Tariq O, Hiemstra, Pieter S, Slats, Annelies M, Mullin, Benjamin H, Hui, Jennie, James, Alan, Beilby, John, Patasova, Karina, Hysi, Pirro, Koskela, Jukka T, Wyss, Annah B, Jin, Jianping, Sikdar, Sinjini, Lee, Mikyeong, May-Wilson, Sebastian, Pirastu, Nicola, Kentistou, Katherine A, Joshi, Peter K, Timmers, Paul RHJ, Williams, Alexander T, Free, Robert C, Wang, Xueyang, Morrison, John L, Gilliland, Frank D, Chen, Zhanghua, Wang, Carol A, Foong, Rachel E, Harris, Sarah E, Taylor, Adele, Redmond, Paul, Cook, James P, Mahajan, Anubha, Lind, Lars, Palviainen, Teemu, Lehtimäki, Terho, Raitakari, Olli T, Kaprio, Jaakko, Rantanen, Taina, Pietiläinen, Kirsi H, Cox, Simon R, Pennell, Craig E, Hall, Graham L, Gauderman, W James, Brightling, Chris, Wilson, James F, Vasankari, Tuula, Laitinen, Tarja, Salomaa, Veikko, Mook-Kanamori, Dennis O, Timpson, Nicholas J, Zeggini, Eleftheria, Dupuis, Josée, Hayward, Caroline, Brumpton, Ben, Langenberg, Claudia, Weiss, Stefan, Homuth, Georg, Schmidt, Carsten Oliver, Probst-Hensch, Nicole, Jarvelin, Marjo-Riitta, Morrison, Alanna C, Polasek, Ozren, Rudan, Igor, Lee, Joo-Hyeon, Sayers, Ian, Rawlins, Emma L, Dudbridge, Frank, Silverman, Edwin K, Strachan, David P, Walters, Robin G, Morris, Andrew P, London, Stephanie J, Cho, Michael H, Wain, Louise V, Hall, Ian P, Tobin, Martin D, Shrine, Nick [0000-0003-3641-4371], Chen, Jing [0000-0003-1287-1930], Guyatt, Anna L [0000-0003-1860-6337], Hobbs, Brian D [0000-0001-9564-0745], Kim, Wonji [0000-0002-1249-797X], Coley, Kayesha [0000-0003-4951-6799], Chen, Zhengming [0000-0001-6423-105X], Li, Liming [0000-0001-5873-7089], Lahousse, Lies [0000-0002-3494-4363], Uitterlinden, Andre G [0000-0002-7276-3387], Oelsner, Elizabeth C [0000-0002-7481-9671], Rich, Stephen S [0000-0003-3872-7793], Kerr, Shona M [0000-0002-4137-1495], Vitart, Veronique [0000-0002-4991-3797], Jeong, Ayoung [0000-0003-1542-0756], Gharib, Sina A [0000-0002-2480-4367], Gieger, Christian [0000-0001-6986-9554], Peters, Annette [0000-0001-6645-0985], Hu, Xiaowei [0000-0001-7804-7392], Smith, Albert Vernon [0000-0003-1942-5845], Luan, Jian’an [0000-0003-3137-6337], Langhammer, Arnulf [0000-0001-5296-6673], Willer, Cristen [0000-0001-5645-4966], Porteous, David [0000-0003-1249-6106], Smith, Blair H [0000-0002-5362-9430], Campbell, Archie [0000-0003-0198-5078], Sofer, Tamar [0000-0001-8520-8860], Lee, Jiwon [0000-0002-4079-7494], Lim, Elise [0000-0001-8967-8464], Thareja, Gaurav [0000-0003-2277-6400], Albagha, Omar ME [0000-0001-5916-5983], Suhre, Karsten [0000-0001-9638-3912], Granell, Raquel [0000-0002-4890-4012], Faquih, Tariq O [0000-0001-8026-2251], Hiemstra, Pieter S [0000-0002-0238-5982], Hysi, Pirro [0000-0001-5752-2510], Koskela, Jukka T [0000-0002-0154-7222], Jin, Jianping [0000-0002-3774-1609], Sikdar, Sinjini [0000-0003-1230-5162], Lee, Mikyeong [0000-0002-3036-3684], May-Wilson, Sebastian [0000-0003-2668-5717], Joshi, Peter K [0000-0002-6361-5059], Timmers, Paul RHJ [0000-0002-5197-1267], Gilliland, Frank D [0000-0002-9033-7269], Wang, Carol A [0000-0002-4301-3974], Harris, Sarah E [0000-0002-4941-5106], Mahajan, Anubha [0000-0001-5585-3420], Palviainen, Teemu [0000-0002-7847-8384], Kaprio, Jaakko [0000-0002-3716-2455], Pietiläinen, Kirsi H [0000-0002-8522-1288], Cox, Simon R [0000-0003-4036-3642], Pennell, Craig E [0000-0002-0937-6165], Wilson, James F [0000-0001-5751-9178], Vasankari, Tuula [0000-0002-1413-8970], Salomaa, Veikko [0000-0001-7563-5324], Timpson, Nicholas J [0000-0002-7141-9189], Dupuis, Josée [0000-0003-2871-3603], Brumpton, Ben [0000-0002-3058-1059], Langenberg, Claudia [0000-0002-5017-7344], Weiss, Stefan [0000-0002-3553-4315], Homuth, Georg [0000-0001-6839-0605], Jarvelin, Marjo-Riitta [0000-0002-2149-0630], Morrison, Alanna C [0000-0001-6381-4296], Rudan, Igor [0000-0001-6993-6884], Lee, Joo-Hyeon [0000-0002-7364-6422], Sayers, Ian [0000-0001-5601-5410], Rawlins, Emma L [0000-0001-7426-3792], Dudbridge, Frank [0000-0002-8817-8908], Strachan, David P [0000-0001-7854-1366], Walters, Robin G [0000-0002-9179-0321], Morris, Andrew P [0000-0002-6805-6014], London, Stephanie J [0000-0003-4911-5290], Cho, Michael H [0000-0002-4907-1657], Wain, Louise V [0000-0003-4951-1867], Hall, Ian P [0000-0001-9933-3216], Tobin, Martin D [0000-0002-3596-7874], and Apollo - University of Cambridge Repository

Subjects
hengityselimet, genome-wide association studies, perimä, 631/208/205/2138, 45/43, article, keuhkosairaudet, hengityselinten taudit, riskitekijät, 692/699/1785, keuhkot, perinnöllisyys, respiratory tract diseases
Abstract

Funder: British Lung Foundation (BLF); doi: https://doi.org/10.13039/501100000351, Funder: DH | National Institute for Health Research (NIHR); doi: https://doi.org/10.13039/501100000272, Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

Published
2023

3. Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

Author

Qiyun Zhu, Shi Huang, Antonio Gonzalez, Imran McGrath, Daniel McDonald, Niina Haiminen, George Armstrong, Yoshiki Vázquez-Baeza, Julian Yu, Justin Kuczynski, Gregory D. Sepich-Poore, Austin D. Swafford, Promi Das, Justin P. Shaffer, Franck Lejzerowicz, Pedro Belda-Ferre, Aki S. Havulinna, Guillaume Méric, Teemu Niiranen, Leo Lahti, Veikko Salomaa, Ho-Cheol Kim, Mohit Jain, Michael Inouye, Jack A. Gilbert, Rob Knight, Sharpton, Thomas J, Zhu, Qiyun [0000-0002-3568-6271], Huang, Shi [0000-0002-7529-2269], McGrath, Imran [0000-0001-8791-4398], McDonald, Daniel [0000-0003-0876-9060], Haiminen, Niina [0000-0002-8663-1019], Armstrong, George [0000-0002-1061-3295], Vázquez-Baeza, Yoshiki [0000-0001-6014-2009], Sepich-Poore, Gregory D [0000-0002-3443-3715], Swafford, Austin D [0000-0001-5655-8300], Das, Promi [0000-0001-6733-2059], Shaffer, Justin P [0000-0002-9371-6336], Lejzerowicz, Franck [0000-0002-3195-032X], Belda-Ferre, Pedro [0000-0001-6532-1161], Havulinna, Aki S [0000-0002-4787-8959], Méric, Guillaume [0000-0001-6288-9958], Niiranen, Teemu [0000-0002-7394-7487], Lahti, Leo [0000-0001-5537-637X], Salomaa, Veikko [0000-0001-7563-5324], Kim, Ho-Cheol [0000-0003-0464-4340], Jain, Mohit [0000-0001-8628-2069], Inouye, Michael [0000-0001-9413-6520], Gilbert, Jack A [0000-0001-7920-7001], Knight, Rob [0000-0002-0975-9019], Apollo - University of Cambridge Repository, Medicum, Institute for Molecular Medicine Finland, Complex Disease Genetics, University of Helsinki, and Helsinki Institute of Life Science HiLIFE

Subjects
BACTERIAL, 16S, operational genomic unit, DATABASE, Physiology, DIVERSITY, Biochemistry, Microbiology, supervised learning, reference phylogeny, RNA, Ribosomal, 16S, Genetics, UniFrac, Humans, Molecular Biology, Life Below Water, taxonomy independent, TREE, Ecology, Evolution, Behavior and Systematics, Phylogeny, 11832 Microbiology and virology, Ribosomal, metagenomics, Ecology, Microbiota, Human Genome, READ ALIGNMENT, Computer Science Applications, Modeling and Simulation, FOS: Biological sciences, RNA, Metagenome, Biotechnology
Abstract

Funder: Emil Aaltosen Säätiö, Funder: Emerald Foundation, Funder: Sydäntutkimussäätiö, Funder: Suomen Lääketieteen Säätiö, Funder: Suomen Lääketieteen Säätiö (Finnish Medical Foundation), Funder: Sydäntutkimussäätiö (Finnish Foundation for Cardiovascular Research), Funder: Emil Aaltosen Säätiö (Emil Aaltonen Foundation), We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.

Published
2022
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4. The gut microbiome is a significant risk factor for future chronic lung disease

Author

Yang Liu, Shu Mei Teo, Guillaume Meric, Howard H.F. Tang, Qiyun Zhu, Jon G Sanders, Yoshiki Vazquez-Baeza, Karin Verspoor, Ville A Vartiainen, Pekka Jousilahti, Leo Lahti, Teemu Niiranen, Aki S. Havulinna, Rob Knight, Veikko Salomaa, Michael Inouye, Teo, Shu Mei [0000-0002-4563-7836], Meric, Guillaume [0000-0001-6288-9958], Tang, Howard HF [0000-0001-6422-0270], Zhu, Qiyun [0000-0002-3568-6271], Sanders, Jon G [0000-0001-6077-4014], Vazquez-Baeza, Yoshiki [0000-0001-6014-2009], Verspoor, Karin [0000-0002-8661-1544], Vartiainen, Ville A [0000-0002-9833-6965], Lahti, Leo [0000-0001-5537-637X], Niiranen, Teemu [0000-0002-7394-7487], Havulinna, Aki S [0000-0002-4787-8959], Knight, Rob [0000-0002-0975-9019], Salomaa, Veikko [0000-0001-7563-5324], Inouye, Michael [0000-0001-9413-6520], Apollo - University of Cambridge Repository, HUS Heart and Lung Center, Clinicum, INDIVIDRUG - Individualized Drug Therapy, Keuhkosairauksien yksikkö, Medicum, Institute for Molecular Medicine Finland, Complex Disease Genetics, and Helsinki Institute of Life Science HiLIFE

Subjects
Adult, Chronic Obstructive, metagenomics, Allergy, Chronic Obstructive Pulmonary Disease, Prevention, Immunology, microbiome, asthma, Gastrointestinal Microbiome, respiratory tract diseases, Pulmonary Disease, Pulmonary Disease, Chronic Obstructive, Clinical Research, Risk Factors, 3121 General medicine, internal medicine and other clinical medicine, Respiratory, Immunology and Allergy, COPD, Humans, Gut, Prospective Studies, Lung
Abstract

BackgroundThe gut-lung axis is generally recognized, but there are few large studies of the gut microbiome and incident respiratory disease in adults.Objectives3To investigate the associations between gut microbiome and respiratory disease and to construct predictive models from baseline gut microbiome profiles for incident asthma or chronic obstructive pulmonary disease (COPD).MethodsShallow metagenomic sequencing was performed for stool samples from a prospective, population-based cohort (FINRISK02; N=7,115 adults) with linked national administrative health register derived classifications for incident asthma and COPD up to 15 years after baseline. Generalised linear models and Cox regressions were utilised to assess associations of microbial taxa and diversity with disease occurrence. Predictive models were constructed using machine learning with extreme gradient boosting. Models considered taxa abundances individually and in combination with other risk factors, including sex, age, body mass index and smoking status.ResultsA total of 695 and 392 significant microbial associations at different taxonomic levels were found with incident asthma and COPD, respectively. Gradient boosting decision trees of baseline gut microbiome predicted incident asthma and COPD with mean area under the curves of 0.608 and 0.780, respectively. For both incident asthma and COPD, the baseline gut microbiome had C-indices of 0.623 for asthma and 0.817 for COPD, which were more predictive than other conventional risk factors. The integration of gut microbiome and conventional risk factors further improved prediction capacities. Subgroup analyses indicated gut microbiome was significantly associated with incident COPD in both current smokers and non-smokers, as well as in individuals who reported never smoking.ConclusionsThe gut microbiome is a significant risk factor for incident asthma and incident COPD and is largely independent of conventional risk factors.

Published
2022

5. A plasma metabolite score of three eicosanoids predicts incident type 2 diabetes: a prospective study in three independent cohorts

Author

Karolina Tuomisto, Joonatan Palmu, Tao Long, Jeramie D Watrous, Kysha Mercader, Kim A Lagerborg, Allen Andres, Marko Salmi, Sirpa Jalkanen, Ramachandran S Vasan, Michael Inouye, Aki S Havulinna, Jaakko Tuomilehto, Pekka Jousilahti, Teemu J Niiranen, Susan Cheng, Mohit Jain, Veikko Salomaa, Tuomisto, Karolina [0000-0002-1281-2749], Palmu, Joonatan [0000-0003-0059-3347], Salomaa, Veikko [0000-0001-7563-5324], Apollo - University of Cambridge Repository, Department of Public Health, University of Helsinki, Medicum, Institute for Molecular Medicine Finland, and Complex Disease Genetics

Subjects
Adult, Male, Metabolic Syndrome, INSULIN-RESISTANCE, TARGETING INFLAMMATION, Endocrinology, Diabetes and Metabolism, Genetics/Genomes/Proteomics/Metabolomics, Middle Aged, eicosanoids, BETA-CELL FUNCTION, Diabetes Mellitus, Type 2, inflammation, Risk Factors, 3121 General medicine, internal medicine and other clinical medicine, Humans, epidemiology, Female, Prospective Studies, OXIDATIVE STRESS, Aged
Abstract

IntroductionPeptide markers of inflammation have been associated with the development of type 2 diabetes. The role of upstream, lipid-derived mediators of inflammation such as eicosanoids, remains less clear. The aim of this study was to examine whether eicosanoids are associated with incident type 2 diabetes.Research design & methodsIn the FINRISK (Finnish Cardiovascular Risk Study) 2002 study, a population-based sample of Finnish men and women aged 25–74 years, we used directed, non-targeted liquid chromatography-mass spectrometry to identify 545 eicosanoids and related oxylipins in the participants’ plasma samples (n=8292). We used multivariable-adjusted Cox regression to examine associations between eicosanoids and incident type 2 diabetes. The significant independent findings were replicated in the Framingham Heart Study (FHS, n=2886) and DIetary, Lifestyle and Genetic determinants of Obesity and Metabolic syndrome (DILGOM) 2007 (n=3905). Together, these three cohorts had 1070 cases of incident type 2 diabetes.ResultsIn the FINRISK 2002 cohort, 76 eicosanoids were associated individually with incident type 2 diabetes. We identified three eicosanoids independently associated with incident type 2 diabetes using stepwise Cox regression with forward selection and a Bonferroni-corrected inclusion threshold. A three-eicosanoid risk score produced an HR of 1.56 (95% CI 1.41 to 1.72) per 1 SD increment for risk of incident diabetes. The HR for comparing the top quartile with the lowest was 2.80 (95% CI 2.53 to 3.07). In the replication analyses, the three-eicosanoid risk score was significant in FHS (HR 1.24 (95% CI 1.10 to 1.39, pConclusionsPlasma eicosanoid profiles predict incident type 2 diabetes and the clearest signals replicate in three independent cohorts. Our findings give new information on the biology underlying type 2 diabetes and suggest opportunities for early identification of people at risk.

Published
2022

6. Taxonomic signatures of cause-specific mortality risk in human gut microbiome

Author

Salosensaari, Aaro, Laitinen, Ville, Havulinna, Aki S, Meric, Guillaume, Cheng, Susan, Perola, Markus, Valsta, Liisa, Alfthan, Georg, Inouye, Michael, Watrous, Jeramie D, Long, Tao, Salido, Rodolfo A, Sanders, Karenina, Brennan, Caitriona, Humphrey, Gregory C, Sanders, Jon G, Jain, Mohit, Jousilahti, Pekka, Salomaa, Veikko, Knight, Rob, Lahti, Leo, Niiranen, Teemu, Salosensaari, Aaro [0000-0001-6698-6093], Laitinen, Ville [0000-0002-2653-1673], Havulinna, Aki S [0000-0002-4787-8959], Meric, Guillaume [0000-0001-6288-9958], Cheng, Susan [0000-0002-4977-036X], Sanders, Jon G [0000-0001-6077-4014], Salomaa, Veikko [0000-0001-7563-5324], Knight, Rob [0000-0002-0975-9019], Lahti, Leo [0000-0001-5537-637X], Apollo - University of Cambridge Repository, Medicum, Institute for Molecular Medicine Finland, Complex Disease Genetics, Helsinki Institute of Life Science HiLIFE, Havulinna, Aki S. [0000-0002-4787-8959], and Sanders, Jon G. [0000-0001-6077-4014]

Subjects
Adult, Male, 16S, Adolescent, IMPACT, Science, 45/23, Cohort Studies, Feces, Young Adult, Enterobacteriaceae, Clinical Research, Risk Factors, RNA, Ribosomal, 16S, Cause of Death, 692/53/2422, Genetics, 2.1 Biological and endogenous factors, Humans, Aetiology, 631/326/2565/2142, POPULATION, Finland, Aged, Ribosomal, 631/326/107, Prevention, Human Genome, article, Middle Aged, humanities, Gastrointestinal Microbiome, Good Health and Well Being, Cross-Sectional Studies, INFECTIONS, 3121 General medicine, internal medicine and other clinical medicine, Population Surveillance, RNA, Female, 2.4 Surveillance and distribution
Abstract

The collection of fecal material and developments in sequencing technologies have enabled standardised and non-invasive gut microbiome profiling. Microbiome composition from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterised due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a well-phenotyped and representative population cohort from Finland (n=7211). We report robust taxonomic and functional microbiome signatures related to the Enterobacteriaceae family that are associated with mortality risk during a 15-year follow-up. Our results extend previous cross-sectional studies, and help to establish the basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status. Gut microbiome composition has a role in health and disease. Here the authors show that microbiome signatures related to the Enterobacteriaceae family are associated with cause-specific mortality risk in a well phenotyped Finish population over a 15-year follow-up.

Published
2021

7. Lipoprotein signatures of cholesteryl ester transfer protein and HMG-CoA reductase inhibition

Author

Qin Wang, Marjo-Riitta Järvelin, Terho Lehtimäki, Veikko Salomaa, Michael V. Holmes, Mika Ala-Korpela, Clare Oliver-Williams, Emanuele Di Angelantonio, Therese Tillin, Adam S. Butterworth, Elias Allara, Mika Kähönen, Johannes Kettunen, Nish Chaturvedi, George Davey Smith, Pauli Ohukainen, Markus Perola, John Danesh, Olli T. Raitakari, Jorma Viikari, Alun D. Hughes, Olga Anufrieva, Research Programs Unit, CAMM - Research Program for Clinical and Molecular Metabolism, University of Helsinki, Lääketieteen ja terveysteknologian tiedekunta - Faculty of Medicine and Health Technology, Tampere University, Holmes, Michael V [0000-0001-6617-0879], Allara, Elias [0000-0002-1634-8330], Ohukainen, Pauli [0000-0002-0919-7204], Oliver-Williams, Clare [0000-0002-3573-2426], Hughes, Alun D [0000-0001-5432-5271], Salomaa, Veikko [0000-0001-7563-5324], Järvelin, Marjo-Riitta [0000-0002-2149-0630], Davey Smith, George [0000-0002-1407-8314], Butterworth, Adam S [0000-0002-6915-9015], Ala-Korpela, Mika [0000-0001-5905-1206], Apollo - University of Cambridge Repository, UNIVERSITY OF OULU, Holmes, Michael V. [0000-0001-6617-0879], Hughes, Alun D. [0000-0001-5432-5271], and Butterworth, Adam S. [0000-0002-6915-9015]

Subjects
Life Sciences & Biomedicine - Other Topics, Male, 0301 basic medicine, Very low-density lipoprotein, Apolipoprotein B, LOCI, Coronary Disease, Biochemistry, Vascular Medicine, DISEASE, Cohort Studies, chemistry.chemical_compound, 0302 clinical medicine, Medicine and Health Sciences, Coronary Heart Disease, EPIDEMIOLOGY, Biology (General), Genetics of disease, 11 Medical and Health Sciences, education.field_of_study, biology, PLASMA, General Neuroscience, CARDIOVASCULAR RISK, Middle Aged, Lipids, Coronary heart disease, Cholesterol, HMG-CoA reductase, Female, lipids (amino acids, peptides, and proteins), General Agricultural and Biological Sciences, Life Sciences & Biomedicine, Research Article, Adult, Biochemistry & Molecular Biology, medicine.medical_specialty, Adolescent, Biolääketieteet - Biomedicine, QH301-705.5, Lipoproteins, Population, Cardiology, General Biochemistry, Genetics and Molecular Biology, LDL, Young Adult, 03 medical and health sciences, MAGNETIC-RESONANCE METABOLOMICS, 07 Agricultural and Veterinary Sciences, Internal medicine, Cholesterylester transfer protein, REVEALS, medicine, Genetics, Humans, GENOME-WIDE ASSOCIATION, education, Biology, Triglycerides, Alleles, Apolipoproteins B, Science & Technology, General Immunology and Microbiology, Triglyceride, Genetic Variation, Biology and Life Sciences, Proteins, Cholesterol, LDL, 06 Biological Sciences, Cholesterol Ester Transfer Proteins, Medical risk factors, 030104 developmental biology, Endocrinology, Apolipoproteins, chemistry, Genetic Loci, Medical Risk Factors, Genetics of Disease, biology.protein, COHORT PROFILE, 1182 Biochemistry, cell and molecular biology, Hydroxymethylglutaryl CoA Reductases, 3111 Biomedicine, Hydroxymethylglutaryl-CoA Reductase Inhibitors, 030217 neurology & neurosurgery, Follow-Up Studies, Developmental Biology, Lipoprotein
Abstract

Cholesteryl ester transfer protein (CETP) inhibition reduces vascular event risk, but confusion surrounds its effects on low-density lipoprotein (LDL) cholesterol. Here, we clarify associations of genetic inhibition of CETP on detailed lipoprotein measures and compare those to genetic inhibition of 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR). We used an allele associated with lower CETP expression (rs247617) to mimic CETP inhibition and an allele associated with lower HMGCR expression (rs12916) to mimic the well-known effects of statins for comparison. The study consists of 65,427 participants of European ancestries with detailed lipoprotein subclass profiling from nuclear magnetic resonance spectroscopy. Genetic associations were scaled to 10% reduction in relative risk of coronary heart disease (CHD). We also examined observational associations of the lipoprotein subclass measures with risk of incident CHD in 3 population-based cohorts totalling 616 incident cases and 13,564 controls during 8-year follow-up. Genetic inhibition of CETP and HMGCR resulted in near-identical associations with LDL cholesterol concentration estimated by the Friedewald equation. Inhibition of HMGCR had relatively consistent associations on lower cholesterol concentrations across all apolipoprotein B-containing lipoproteins. In contrast, the associations of the inhibition of CETP were stronger on lower remnant and very-low-density lipoprotein (VLDL) cholesterol, but there were no associations on cholesterol concentrations in LDL defined by particle size (diameter 18–26 nm) (−0.02 SD LDL defined by particle size; 95% CI: −0.10 to 0.05 for CETP versus −0.24 SD, 95% CI −0.30 to −0.18 for HMGCR). Inhibition of CETP was strongly associated with lower proportion of triglycerides in all high-density lipoprotein (HDL) particles. In observational analyses, a higher triglyceride composition within HDL subclasses was associated with higher risk of CHD, independently of total cholesterol and triglycerides (strongest hazard ratio per 1 SD higher triglyceride composition in very large HDL 1.35; 95% CI: 1.18–1.54). In conclusion, CETP inhibition does not appear to affect size-specific LDL cholesterol but is likely to lower CHD risk by lowering concentrations of other atherogenic, apolipoprotein B-containing lipoproteins (such as remnant and VLDLs). Inhibition of CETP also lowers triglyceride composition in HDL particles, a phenomenon reflecting combined effects of circulating HDL, triglycerides, and apolipoprotein B-containing particles and is associated with a lower CHD risk in observational analyses. Our results reveal that conventional composite lipid assays may mask heterogeneous effects of emerging lipid-altering therapies., Inhibition of cholesteryl ester transfer protein does not affect size-specific low-density lipoprotein cholesterol, but may lower coronary heart disease risk by lowering cholesterol concentrations in other apolipoprotein-B containing atherogenic lipoproteins, and by lowering triglyceride content of high-density lipoprotein particles.

Published
2020
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