Christopher H Arehart1, Michelle Daya1, Monica Campbell1, Meher Preethi Boorgula1, Nicholas Rafaels1, Sameer Chavan1, Gloria David2, Jon Hanifin3, Mark K Slifka3, Richard L Gallo4, Tissa Hata4, Lynda C Schneider5, Amy S Paller6, Peck Y Ong7, Jonathan M Spergel8, Emma Guttman-Yassky9, Donald Y M Leung10, Lisa A Beck11, Christopher R Gignoux1, Rasika A Mathias12, Kathleen C Barnes13. 1. Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colo. 2. Rho, Inc, Durham, NC. 3. Department of Dermatology, Oregon Health and Science University, Portland, Ore. 4. Department of Dermatology, University of California San Diego, San Diego, Calif. 5. Division of Immunology, Boston Children's Hospital, Boston, Mass. 6. Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, Ill; Department of Pediatrics (Dermatology), Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Ill. 7. Division of Clinical Immunology and Allergy, Children's Hospital Los Angeles, Los Angeles, Calif; Keck School of Medicine, University of Southern California, Los Angeles, Calif. 8. Department of Pediatrics, Perelman School of Medicine at University of Pennsylvania, Philadelphia, Pa. 9. Icahn School of Medicine at Mount Sinai, New York, NY. 10. Division of Allergy and Immunology, Department of Pediatrics, National Jewish Health, Denver, Colo. 11. Department of Dermatology, Medicine and Pathology, University of Rochester Medical Center, Rochester, NY. 12. Department of Medicine, Johns Hopkins University Department of Medicine, Baltimore, Md. 13. Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colo. Electronic address: Kathleen.Barnes@cuanschutz.edu.
Abstract
BACKGROUND: While numerous genetic loci associated with atopic dermatitis (AD) have been discovered, to date, work leveraging the combined burden of AD risk variants across the genome to predict disease risk has been limited. OBJECTIVES: This study aims to determine whether polygenic risk scores (PRSs) relying on genetic determinants for AD provide useful predictions for disease occurrence and severity. It also explicitly tests the value of including genome-wide association studies of related allergic phenotypes and known FLG loss-of-function (LOF) variants. METHODS: AD PRSs were constructed for 1619 European American individuals from the Atopic Dermatitis Research Network using an AD training dataset and an atopic training dataset including AD, childhood onset asthma, and general allergy. Additionally, whole genome sequencing data were used to explore genetic scoring specific to FLG LOF mutations. RESULTS: Genetic scores derived from the AD-only genome-wide association studies were predictive of AD cases (PRSAD: odds ratio [OR], 1.70; 95% CI, 1.49-1.93). Accuracy was first improved when PRSs were built off the larger atopy genome-wide association studies (PRSAD+: OR, 2.16; 95% CI, 1.89-2.47) and further improved when including FLG LOF mutations (PRSAD++: OR, 3.23; 95% CI, 2.57-4.07). Importantly, while all 3 PRSs correlated with AD severity, the best prediction was from PRSAD++, which distinguished individuals with severe AD from control subjects with OR of 3.86 (95% CI, 2.77-5.36). CONCLUSIONS: This study demonstrates how PRSs for AD that include genetic determinants across atopic phenotypes and FLG LOF variants may be a promising tool for identifying individuals at high risk for developing disease and specifically severe disease.
BACKGROUND: While numerous genetic loci associated with atopic dermatitis (AD) have been discovered, to date, work leveraging the combined burden of AD risk variants across the genome to predict disease risk has been limited. OBJECTIVES: This study aims to determine whether polygenic risk scores (PRSs) relying on genetic determinants for AD provide useful predictions for disease occurrence and severity. It also explicitly tests the value of including genome-wide association studies of related allergic phenotypes and known FLG loss-of-function (LOF) variants. METHODS: AD PRSs were constructed for 1619 European American individuals from the Atopic Dermatitis Research Network using an AD training dataset and an atopic training dataset including AD, childhood onset asthma, and general allergy. Additionally, whole genome sequencing data were used to explore genetic scoring specific to FLG LOF mutations. RESULTS: Genetic scores derived from the AD-only genome-wide association studies were predictive of AD cases (PRSAD: odds ratio [OR], 1.70; 95% CI, 1.49-1.93). Accuracy was first improved when PRSs were built off the larger atopy genome-wide association studies (PRSAD+: OR, 2.16; 95% CI, 1.89-2.47) and further improved when including FLG LOF mutations (PRSAD++: OR, 3.23; 95% CI, 2.57-4.07). Importantly, while all 3 PRSs correlated with AD severity, the best prediction was from PRSAD++, which distinguished individuals with severe AD from control subjects with OR of 3.86 (95% CI, 2.77-5.36). CONCLUSIONS: This study demonstrates how PRSs for AD that include genetic determinants across atopic phenotypes and FLG LOF variants may be a promising tool for identifying individuals at high risk for developing disease and specifically severe disease.
Authors: Maxwell M Tran; Diana L Lefebvre; Christoffer Dharma; David Dai; Wendy Y W Lou; Padmaja Subbarao; Allan B Becker; Piush J Mandhane; Stuart E Turvey; Malcolm R Sears Journal: J Allergy Clin Immunol Date: 2017-11-15 Impact factor: 10.793
Authors: Zelma C Chiesa Fuxench; Julie K Block; Mark Boguniewicz; John Boyle; Luz Fonacier; Joel M Gelfand; Mitchell H Grayson; David J Margolis; Lynda Mitchell; Jonathan I Silverberg; Lawrence Schwartz; Eric L Simpson; Peck Y Ong Journal: J Invest Dermatol Date: 2018-10-30 Impact factor: 8.551
Authors: E Krapohl; H Patel; S Newhouse; C J Curtis; S von Stumm; P S Dale; D Zabaneh; G Breen; P F O'Reilly; R Plomin Journal: Mol Psychiatry Date: 2017-08-08 Impact factor: 15.992
Authors: Joanne R Chalmers; Rachel H Haines; Lucy E Bradshaw; Alan A Montgomery; Kim S Thomas; Sara J Brown; Matthew J Ridd; Sandra Lawton; Eric L Simpson; Michael J Cork; Tracey H Sach; Carsten Flohr; Eleanor J Mitchell; Richard Swinden; Stella Tarr; Susan Davies-Jones; Nicola Jay; Maeve M Kelleher; Michael R Perkin; Robert J Boyle; Hywel C Williams Journal: Lancet Date: 2020-02-19 Impact factor: 202.731