scholarly journals Novel Genetic Risk factors for Asthma in African American Children: Precision Medicine and The SAGE II Study

2016 ◽  
Author(s):  
MJ White ◽  
O Risse-Adams ◽  
P Goddard ◽  
MG Contreras ◽  
J Adams ◽  
...  

AbstractBackgroundAsthma, an inflammatory disorder of the airways, is the most common chronic disease of children worldwide. There are significant racial/ethnic disparities in asthma prevalence, morbidity and mortality among U.S. children. This trend is mirrored in obesity, which may share genetic and environmental risk factors with asthma. The majority of asthma biomedical research has been performed in populations of European decent.ObjectiveWe sought to identify genetic risk factors for asthma in African American children. We also assessed the generalizability of genetic variants associated with asthma in European and Asian populations to African American children.MethodsOur study population consisted of 1227 (812 asthma cases, 415 controls) African American children with genome-wide single nucleotide polymorphism (SNP) data. Logistic regression was used to identify associations between SNP genotype and asthma status.ResultsWe identified a novel variant in the PTCHD3 gene that is significantly associated with asthma (rs660498, p = 2.2 x10−7) independent of obesity status. Approximately 5% of previously reported asthma genetic associations identified in European populations replicated in African Americans.ConclusionsOur identification of novel variants associated with asthma in African American children, coupled with our inability to replicate the majority of findings reported in European Americans, underscores the necessity for including diverse populations in biomedical studies of asthma.

2016 ◽  
Vol 68 (6-7) ◽  
pp. 391-400 ◽  
Author(s):  
Marquitta J. White ◽  
O. Risse-Adams ◽  
P. Goddard ◽  
M. G. Contreras ◽  
J. Adams ◽  
...  

2001 ◽  
Vol 38 (7) ◽  
pp. 555-564 ◽  
Author(s):  
Jodi von Maffei ◽  
William S. Beckett ◽  
Kathleen Belanger ◽  
Elizabeth Triche ◽  
Heping Zhang ◽  
...  

2010 ◽  
Vol 7 (1) ◽  
pp. 10 ◽  
Author(s):  
Sushma Sharma ◽  
Lindsay S Roberts ◽  
Robert H Lustig ◽  
Sharon E Fleming

2020 ◽  
Author(s):  
Benjamin Meir Jacobs ◽  
Alastair Noyce ◽  
Jonathan Bestwick ◽  
Daniel Belete ◽  
Gavin Giovannoni ◽  
...  

AbstractImportanceMultiple Sclerosis (MS) is a neuro-inflammatory disorder caused by a combination of environmental exposures and genetic risk factors. We sought to determine whether genetic risk modifies the effect of environmental MS risk factors.MethodsPeople with MS were identified within UK Biobank using ICD10-coded MS or self-report. Associations between environmental risk factors and MS risk were quantified with a case-control design using multivariable logistic regression. Polygenic risk scores (PRS) were derived using the clumping-and-thresholding approach with external weights from the largest genome-wide association study of MS. Separate scores were created including (PRSMHC) and excluding (PRSNon-MHC) the MHC locus. The best performing PRS were identified in 30% of the cohort and validated in the remaining 70%. Interaction between environmental and genetic risk factors was quantified using the Attributable Proportion due to interaction (AP) and multiplicative interaction.ResultsData were available for 2250 people with MS and 486,000 controls. Childhood obesity, earlier age at menarche, and smoking were associated with MS. The optimal PRS were strongly associated with MS in the validation cohort (PRSMHC: Nagelkerke’s Pseudo-R2 0.033, p=3.92×10−111; PRSNon-MHC: Nagelkerke’s Pseudo-R2 0.013, p=3.73×10−43). There was strong evidence of interaction between polygenic risk for MS and childhood obesity (PRSMHC: AP=0.17, 95% CI 0.06 - 0.25, p=0.004; PRSNon-MHC: AP=0.17, 95% CI 0.06 - 0.27, p=0.006).Conclusions and RelevanceThis study provides novel evidence for an interaction between childhood obesity and a high burden of autosomal genetic risk. These findings may have significant implications for our understanding of MS biology and inform targeted prevention strategies.


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