Results 71 to 80 of about 8,166 (222)

Embracing polygenicity: a review of methods and tools for psychiatric genetics research. [PDF]

, 2017
The availability of genome-wide genetic data on hundreds of thousands of people has led to an equally rapid growth in methodologies available to analyse these data.
Maier, R.M., Robinson, M.R., Visscher, P.M., Wray, N.R.   +3 more
core   +2 more sources

Transcriptome-Wide Association Study Provides Insights Into the Genetic Component of Gene Expression in Anxiety

Frontiers in Genetics, 2021
Anxiety disorders are common mental disorders that often result in disability. Recently, large-scale genome-wide association studies (GWASs) have identified several novel risk variants and loci for anxiety disorders (or anxiety traits). Nevertheless, how
Xi Su, Xi Su, Wenqiang Li, Wenqiang Li, Luxian Lv, Luxian Lv, Xiaoyan Li, Jinfeng Yang, Jinfeng Yang, Xiong-Jian Luo, Xiong-Jian Luo, Xiong-Jian Luo, Xiong-Jian Luo, Jiewei Liu   +13 more
doaj   +1 more source

Gene expression imputation identifies candidate genes and susceptibility loci associated with cutaneous squamous cell carcinoma

Nature Communications, 2018
Genetic loci linked to susceptibility for the common skin cancer cutaneous squamous cell carcinoma (cSCC) have been identified by genome wide association studies (GWAS).
Nilah M. Ioannidis, Wei Wang, Nicholas A. Furlotte, David A. Hinds, 23andMe Research Team, Carlos D. Bustamante, Eric Jorgenson, Maryam M. Asgari, Alice S. Whittemore   +8 more
doaj   +1 more source

Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions [PDF]

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 ...
Aben, Katja KH, Anton-Culver, Hoda, Antonenkova, Natalia N, AOCS, Group, Aravantinos, Gerasimos, Bandera, Elisa V, Beane Freeman, Laura E, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Berchuck, Andrew, Bernardini, Marcus Q, Bjorge, Line, Black, Amanda, Bogdanova, Natalia V, Bolton, Kelly L, Brenton, James D, Budzilowska, Agnieszka, Butzow, Ralf, Cai, Hui, Campbell, Ian, Cannioto, Rikki, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Kexin, Chen, Stephanie, Chenevix-Trench, Georgia, Chiew, Yoke-Eng, Coetzee, Simon G, Cook, Linda S, Dareng, Eileen O, Davis, Brian D, DeFazio, Anna, Dennis, Joe, Dezem, Felipe Segato, Doherty, Jennifer A, du Bois, Andreas, Dörk, Thilo, Dürst, Matthias, Eccles, Diana M, Edwards, Digna Velez, Ene, Gabrielle, Fasching, Peter A, Flanagan, James M, Fortner, Renée T, Fostira, Florentia, Freedman, Matthew L, Gayther, Simon A, Gentry-Maharaj, Aleksandra, Giles, Graham G, Goode, Ellen L, Goodman, Marc T, Gronwald, Jacek, Haiman, Christopher A, Hazelett, Dennis, Heitz, Florian, Hildebrandt, Michelle AT, Huang, Ruea-Yea, Huntsman, David G, Håkansson, Niclas, Høgdall, Claus K, Høgdall, Estrid, Jensen, Allan, Jones, Michael E, Jones, Michelle R, Kang, Daehee, Kar, Siddhartha, Karlan, Beth Y, Karnezis, Anthony N, Kelemen, Linda E, Kennedy, Catherine J, Khusnutdinova, Elza K, Kiemeney, Lambertus A, Kjaer, Susanne K, Kupryjanczyk, Jolanta, Labrie, Marilyne, Lambrechts, Diether, Larson, Melissa C, Lawrenson, Kate, Le, Nhu D, Lester, Jenny, Li, Lian, Lubiński, Jan, Lush, Michael, Marks, Jeffrey R, Matsuo, Keitaro, May, Taymaa, McLaughlin, John R, McNeish, Iain A, Menon, Usha, Missmer, Stacey, Modugno, Francesmary, Moffitt, Melissa, Monteiro, Alvaro N, Moysich, Kirsten B, Nameki, Robbin, Narod, Steven A, Nguyen-Dumont, Tu, Odunsi, Kunle, Olsson, Håkan, Onland-Moret, N Charlotte, OPAL Study, Group, Ovarian Cancer Association Consortium, (OCAC), Park, Sue K, Pearce, Celeste L, Pejovic, Tanja, Peng, Pei-Chen, Permuth, Jennifer B, Pharoah, Paul DP, Piskorz, Anna, Plummer, Jasmine T, Prokofyeva, Darya, Ramus, Susan J, Reyes, Alberto L, Riggan, Marjorie J, Risch, Harvey A, Rodríguez-Antona, Cristina, Rosenow, Will, Rossing, Mary Anne, Sandler, Dale P, Schildkraut, Joellen M, Sellers, Thomas A, Seo, Ji-Heui, Setiawan, V Wendy, Shan, Kang, Song, Honglin, Southey, Melissa C, Steed, Helen, Sutphen, Rebecca, Swerdlow, Anthony J, Teo, Soo Hwang, Terry, Kathryn L, Thompson, Pamela J, Titus, Linda, Trabert, Britton, Travis, Ruth, Tworoger, Shelley S, Tyrer, Jonathan P, Valen, Ellen, Van Nieuwenhuysen, Els, Vestrheim Thomsen, Liv Cecilie, Vierkant, Robert A, Webb, Penelope M, Weinberg, Clarice R, Weise, Rayna Matsuno, Wentzensen, Nicolas, White, Emily, Winham, Stacey J, Wolk, Alicja, Woo, Yin-Ling, Wu, Anna H, Yan, Li, Yannoukakos, Drakoulis, Zeinomar, Nur, Zheng, Wei, Ziogas, Argyrios   +155 more
core   +4 more sources

Identification of candidate genes and chemicals associated with osteoarthritis by transcriptome-wide association study and chemical-gene interaction analysis

Arthritis Research & Therapy, 2023
Background Osteoarthritis (OA) is a common degenerative joint disease and causes chronic pain and disability to the elderly. Several risk factors are involved, such as aging, obesity, genetic susceptibility, and environmental factors.
Lin Mei, Zhiming Zhang, Ruiqi Chen, Zhongyue Liu, Xiaolei Ren, Zhihong Li   +5 more
doaj   +1 more source

Novel insight into the etiology of autism spectrum disorder gained by integrating expression data with genome-wide association statistics [PDF]

, 2019
Background A recent genome-wide association study (GWAS) of autism spectrum disorders (ASD) (Ncases=18,381, Ncontrols=27,969) has provided novel opportunities for investigating the aetiology of ASD. Here, we integrate the ASD GWAS summary statistics with
Anney, Richard, Bray, Nichloas J., Hall, Lynsey S., Holmans, Peter A., O'Brian, Heath E., O'Donovan, Michael C., Owen, Michael J., Pain, Oliver, Pardinas, Antonio F., Pocklington, Andrew J.   +9 more
core   +2 more sources

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Biological insights into systemic lupus erythematosus through an immune cell-specific transcriptome-wide association study [PDF]

, 2022
Objective: Genome-wide association studies (GWAS) have identified >100 risk loci for systemic lupus erythematosus (SLE), but the disease genes at most loci remain unclear, hampering translation of these genetic discoveries.
박용범
core   +1 more source

Integrating transcriptome-wide study and mRNA expression profiles yields novel insights into the biological mechanism of chondropathies

Arthritis Research & Therapy, 2019
Background Chondropathies are a group of cartilage diseases, which share some common pathogenetic features. The etiology of chondropathies is still largely obscure now.
Ping Li, Yujie Ning, Xiong Guo, Yan Wen, Bolun Cheng, Mei Ma, Lu Zhang, Shiqiang Cheng, Sen Wang, Feng Zhang   +9 more
doaj   +1 more source

Identification of candidate genes and pathways associated with juvenile idiopathic arthritis by integrative transcriptome-wide association studies and mRNA expression profiles

Arthritis Research & Therapy, 2023
Aim Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease of childhood, with genetic susceptibility and pathological processes such as autoimmunity and autoinflammation, but its pathogenesis is unclear.
Ruoyang Feng, Mengnan Lu, Chunyan Yin, Ke Xu, Lin Liu, Peng Xu   +5 more
doaj   +1 more source