In this review, we provide an overview of food allergy genetics and epigenetics aimed at clinicians and researchers. This includes a brief review of the current understanding of genetic and epigenetic mechanisms, inheritance of food allergy, as well as a discussion of advantages and limitations of the different types of studies in genetic research. We specifically focus on the results of genome-wide association studies in food allergy, which have identified 16 genetic variants that reach genome-wide significance, many of which overlap with other allergic diseases, including asthma, atopic dermatitis, and allergic rhinitis. Identified genes for food allergy are mainly involved in epithelial barrier function (e.g., FLG, SERPINB7) and immune function (e.g., HLA, IL4). Epigenome-wide significant findings at 32 loci are also summarized as well as 14 additional loci with significance at a false discovery of < 1 × 10-4. Integration of epigenetic and genetic data is discussed in the context of disease mechanisms, many of which are shared with other allergic diseases. The potential utility of genetic and epigenetic discoveries is deliberated. In the future, genetic and epigenetic markers may offer ways to predict the presence or absence of clinical IgE-mediated food allergy among sensitized individuals, likelihood of development of natural tolerance, and response to immunotherapy.

Atopic dermatitis (AD) is characterized by a damaged skin barrier that allows allergens to penetrate the body, leading to sensitization and a higher risk of developing food allergies (relative risk [RR], 33.79), asthma (RR, 7.04), and/or rhinitis (RR, 11.75), all features of the atopic march.1Tran M.M. Lefebvre D.L. Dharma C. Dai D. Lou W.Y.W. Subbarao P. et al.Predicting the atopic march: results from the Canadian Healthy Infant Longitudinal Development Study.J Allergy Clin Immunol. 2018; 141: 601-607.e8Abstract Full Text Full Text PDF PubMed Scopus (79) Google Scholar Recent evidence has shown that the atopic march can be modified in high-risk infants with early interventions directed at reestablishing and/or maintaining skin barrier function with intense use of simple emollients, and introducing food allergens early into the diet.2Du Toit G. Sayre P.H. Roberts G. Sever M.L. Lawson K. Bahnson H.T. et al.Effect of avoidance on peanut allergy after early peanut consumption.N Engl J Med. 2016; 374: 1435-1443Crossref PubMed Scopus (272) Google Scholar, 3Horimukai K. Morita K. Narita M. Kondo M. Kitazawa H. Nozaki M. et al.Application of moisturizer to neonates prevents development of atopic dermatitis.J Allergy Clin Immunol. 2014; 134: 824-830.e6Abstract Full Text Full Text PDF PubMed Scopus (403) Google Scholar, 4Natsume O. Kabashima S. Nakazato J. Yamamoto-Hanada K. Narita M. Kondo M. et al.Two-step egg introduction for prevention of egg allergy in high-risk infants with eczema (PETIT): a randomised, double-blind, placebo-controlled trial.Lancet. 2017; 389: 276-286Abstract Full Text Full Text PDF PubMed Scopus (183) Google Scholar, 5Simpson E.L. Chalmers J.R. Hanifin J.M. Thomas K.S. Cork M.J. McLean W.H. et al.Emollient enhancement of the skin barrier from birth offers effective atopic dermatitis prevention.J Allergy Clin Immunol. 2014; 134: 818-823Abstract Full Text Full Text PDF PubMed Scopus (495) Google Scholar Although these constitute examples of low-intensity, high-impact interventions for health care systems, their successful and indiscriminate implementation in the whole population is neither feasible nor realistic. In this context, building a predictive tool to identify children at high risk of developing moderate to severe AD (MSAD) would allow targeted interventions with maximized impact. In this study, a polygenic risk score (PRS) with an area under the curve (AUC) of 88% and explaining 37% of MSAD variance was established for the Canadian population. Two scenarios for PRS were tested, one using genome-wide association study (GWAS) loci identified through existing literature and the other based on the strongest GWAS hits found in 2 Canadian cohorts (see Table E1 in this article's Online Repository at www.jacionline.org; for the detailed methodology, see this article's Methods section in the Online Repository at www.jacionline.org). The first scenario evaluated whether the best associations in the literature were suitable to build a PRS for AD with a good discriminative value in a specific population. The 25 best associations documented in GWASs of AD (see Tables E2 and E3 in this article's Online Repository at www.jacionline.org) were selected. For each of these, a region spanning ±100 kb was tested for the best associated genetic variant with MSAD (for clinical definitions, see this article's Online Repository at www.jacionline.org) in 80% of the unrelated cases and controls from the 2 Canadian cohorts (training cohort, n = 2688 individuals; see Fig E1 in this article's Online Repository at www.jacionline.org) using a general regression model to extract risk alleles and β estimates (= ln[odds ratio]).E7 The PRS was then built for each individual of the training and testing groups (the remaining 20% of individuals; n = 676) considering the number of risk alleles from genetic variants weighted by their β estimates. The discriminative value of PRS was assessed by a receiver-operating characteristic curve analysis and gave an AUC of 71% (Fig 1, A). According to Nagelkerke's pseudo-R2, 11% of MSAD variance was explained by PRS. Once covariates were added to the model (sex, age, and parents' ethnicity), an AUC of 86% was reached (Fig 1, A) and the model explained 31% of MSAD variance. These results highlight the dependence of the first scenario upon covariates to reach a good discriminative value (AUC between 80% and 89%).E12 The second scenario took advantage of 2 Canadian cohorts to build another PRS based on the best associations for AD in the Canadian population, which is ethnically diverse. The Saguenay–Lac-Saint-Jean asthma familial cohortE1 includes individuals of French descent from this region in northern Quebec, Canada, and the CHILD cohort studyE2 comprises both those of English descent and those of multiple other origins living in British Columbia (Vancouver), Alberta (Edmonton), Manitoba (Winnipeg, Morden, and Winkler), and Ontario (Toronto). Each site obtained local Research Ethics Board approval for the study, and each participating parent gave signed informed consent. The GWAS was performed on the training cohort using the Multiple Family-based Quasi-Likelihood Score (MFQLS) test,E10 and a PRS was built with the 25 best associations (see Table E4 and Fig E1 in this article's Online Repository at www.jacionline.org) after running a general regression model to extract their β estimates. The PRS obtained had an AUC of 85% (Fig 1, C) and explained 33% of MSAD variance. Adding the same covariates as for the first scenario, the AUC was 88% (Fig 1, C), corresponding to a sensitivity and specificity of both 84%, and the PRS explained 37% of MSAD variance. The 2 models of this second scenario demonstrate a good discriminative value.E12 In comparison, AUCs derived from PRSs in the literature range from 53% to 76%,6Do C.B. Hinds D.A. Francke U. Eriksson N. Comparison of family history and SNPs for predicting risk of complex disease.PLoS Genet. 2012; 8e1002973Crossref PubMed Scopus (75) Google Scholar and show relatively low percentages of explained variance (0.3% for brain tumor compared with 36% in this study).7Adel Fahmideh M. Lavebratt C. Tettamanti G. Schuz J. Roosli M. Kjaerheim K. et al.A weighted genetic risk score of adult glioma susceptibility loci associated with pediatric brain tumor risk.Sci Rep. 2019; 9: 18142Crossref PubMed Scopus (3) Google Scholar The PRS based on the Canadian cohorts also carried good predictive values for other allergic phenotypes (for clinical definitions, see this article's Online Repository at www.jacionline.org), with AUCs of 75% for food allergies, 71% for asthma, and 69% for allergic rhinitis (Fig 2, A and B). Interestingly, the discriminative value for asthma was similar than that reported using the Predicting Asthma Risk in Children clinical tool, based on respiratory symptoms occurring before school age (AUC = 77%), even though the predictive tool proposed in this study is designed to identify children at high risk of developing MSAD and not directly to detect those at high risk of developing asthma.8Pedersen E.S.L. Spycher B.D. de Jong C.C.M. Halbeisen F. Ramette A. Gaillard E.A. et al.The simple 10-item Predicting Asthma Risk in Children Tool to predict childhood asthma—an external validation.J Allergy Clin Immunol Pract. 2019; 7: 943-953.e4Abstract Full Text Full Text PDF PubMed Scopus (3) Google Scholar Results were validated in the testing cohort, with AUCs of 85% and 93% for the models for MSAD without and with covariates, respectively (with 31% and 49% of explained variability) and AUCs of 75%, 75%, and 77% for food allergies, asthma, and rhinitis (Fig 2, C and D). These results demonstrate that the second scenario, which used data from the targeted population to build the PRS, best explains the risk of developing MSAD even without considering any covariate. It is interesting to note that no locus was common between the 25 best associations from the 2 scenarios (Tables E2-E4). It confirms the need to characterize the genetic profile of each specific population before building a PRS in order to reach a good discriminative value. To be an efficient predictive tool, a cutoff value has to be established to distinguish between low- and high-risk individuals. When examining the progression of risk to develop MSAD on the basis of individuals' PRSs from the second scenario, there is a clear inflection in the curve at the 9th decile (OR, 17.5, compared with the first decile) with further progressing up to the 10th decile (OR, 39.0; Fig 1, D; see Table E5 in this article's Online Repository at www.jacionline.org). In contrast, risk progression was much more continuous with PRSs calculated from the first scenario, which is further evidence of its lower discriminative value (Fig 1, B, and Table E5). Using a binomial logistic regression with the above-mentioned covariates in the training cohort, being classified as high risk (defined as having a PRS between the 9th and 10th deciles) was strongly associated with the risk of developing AD (odds ratio [OR], 2.96; P = 2.62 × 10−07), MSAD (OR, 11.73; P = 1.27 × 10−21), food allergies (OR, 5.80; P = 2.96 × 10−19), asthma (OR, 3.96; P = 2.12 × 10−10), and rhinitis (OR, 2.29; P = .001; see Table E6 in this article's Online Repository at www.jacionline.org). For comparison, a PRS built from 4 selected genes (GSTP1, TNF, TLR2, and TLR4) was previously reported to have an OR of only 1.22 for AD.9Huls A. Klumper C. MacIntyre E.A. Brauer M. Melen E. Bauer M. et al.Atopic dermatitis: interaction between genetic variants of GSTP1, TNF, TLR2, and TLR4 and air pollution in early life.Pediatr Allergy Immunol. 2018; 29: 596-605Crossref PubMed Scopus (27) Google Scholar Analyses in the testing cohort also gave significant results for MSAD (OR, 5.67; P = .001), food allergies (OR, 3.27; P = .003), and asthma (OR, 3.15; P = .013) even though the cohort used was smaller. Moreover, AUCs for the binary PRS in the testing cohort had similar values than for the continuous PRS (Fig 2, E and F). These are interesting results for clinical applications because such a predictive tool based on only 25 genetic variants and basic covariates available at birth could be easily added to the test routines already established in Canada, which are performed on blood samples collected by a prick on the heels of newborns. Finally, to test whether a smaller number of genetic variants can be as efficient, a PRS was tested for genetic variants from the second scenario that were associated with P less than 1 × 10−10 (n = 8). The discriminative value was well preserved with a corresponding AUC of 86% (Fig E2). However, analyses using a cutoff value to identify children at high risk of developing MSAD in the testing cohort gave less interesting results than the ones for the PRS built from 25 genetic variants, showing a greater dependence on covariates (AUC for the model without covariates = 67% and with covariates = 92%). To conclude, the use of 2 independent multiethnic Canadian cohorts allowed development of a PRS with an AUC of 88% and explaining 37% of MSAD variance. Considering the accumulating body of evidence indicating the need to intervene early to prevent the development of AD and associated allergic comorbidities, discriminative PRS such as this one could prove helpful to guide interventions and direct investments toward those patients most likely to benefit, ensuring the cost-effectiveness and sustainability of early prevention programs. We thank the participants recruited in the Saguenay–Lac-Saint-Jean asthma cohort and the CHILD cohort for their valuable participation in this study. We also thank Dominique Fournier, scientific language expert, for the revision of this manuscript (http://www.serviceslinguistiquesdf.com/home). Fig E2View Large Image Figure ViewerDownload Hi-res image Download (PPT) Download .docx (.09 MB) Help with docx files Online Repository

Au cours des deux dernières décennies, la planète a vu une augmentation marquée du nombre de catastrophes naturelles et de leur impact sur les populations humaines. Les liens entre les changements climatiques, les évènements extrêmes et les vulnérabilités, ainsi que la résilience de divers groupes humains, sont explorés de façon croissante. Les catastrophes affectent de façon différentielle chacun des groupes de la société civile. Un groupe particulièrement affecté par les catastrophes est celui des personnes en situation de handicap. Le taux de mortalité de ce groupe en contexte de catastrophe est de deux à quatre fois celui de la population générale. Les situations de risque existantes se présentent sous des aspects à la fois généraux et spécifiques. Des opportunités existent également afin de répondre à ces problématiques et de mettre en place des stratégies inclusives et adaptées à la réalité des personnes en situation de handicap. Cet article désire donc explorer les concepts de continuum de gestion de crises humanitaires, de catastrophes, vulnérabilité et résilience. Des cadres d’analyse propres à aborder cette question seront définis afin de proposer des pistes d’exploration pour l’avenir afin de promouvoir les recherches académiques et leur application en pratique.

We thank the participants recruited in the Saguenay–Lac-Saint-Jean asthma cohort and the CHILD cohort for their valuable participation in this study. We also thank Dominique Fournier, scientific language expert, for the revision of this manuscript (http://www.serviceslinguistiquesdf.com/home). Mathieu Simard, BSc Anne-Marie Madore, PhD Simon Girard, PhD Susan Waserman, MD, MSc Qingling Duan, PhD Padmaja Subbarao, MD, MSc Malcolm R. Sears, MBChB Theo J. Moraes, MD, PhD Allan B. Becker, MD Stuart E. Turvey, MBBS, DPhil Piushkumar J. Mandhane, MD, PhD Charles Morin, MD Philippe B egin, MD, PhD Catherine Laprise, PhD From D epartement des sciences fondamentales and Centre intersectoriel en sant e durable, Universit e du Qu ebec a Chicoutimi, Saguenay, Quebec, the Division of Clinical Immunology and Allergy, McMaster University, Hamilton, the School of Computing and Department of Biomedical & Molecular Sciences, Queen’s University, Kingston, the Department of Pediatrics, Hospital for Sick Children, University of Toronto, Toronto, and the Division of Respirology, McMaster University, Hamilton, Ontario, the Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, Manitoba, the Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, the Department of Pediatrics, University of Alberta, Edmonton, Alberta, and the Department of Pediatrics, Centre int egr e universitaire de sant e et de services sociaux du Saguenay–Lac-Saint-Jean, Saguenay, the Department of Medicine, Centre hospitalier de l’Universit e de Montr eal, Montreal, and the Department of Pediatrics, CHU Sainte-Justine, Montreal, Quebec, Canada. E-mail: catherine.laprise@uqac.ca. M.S. is supported by a Fonds de recherche du Qu ebec Sant e (FRQS) Master’s Training Award. This study had support from the Quebec Respiratory Health Network (RHN; https://rsr-qc.ca/en/) pilot project grants and by the Canada Research Chair in the Environment and Genetics of Respiratory Disorders and Allergy. The Canadian Institutes of Health Research (CIHR), and the Allergy, Genes and Environment (AllerGen) Network of Centres of Excellence provided core support for the CHILD study. C.L. is part of the Quebec RHN, the investigator of the CHILD study, the director of the Centre intersectoriel en sant e durable de l’UQAC and the chairholder of the Canada Research Chair in the Environment and Genetics of Respiratory Disorders and Allergy (http://www.chairs.gc.ca). The GWAS data were made available by the European Commission as part of GABRIEL (A multidisciplinary study to identify the genetic and environmental causes of asthma in the European Community) contract number 018996 under the Integrated Program LSH-2004-1.2.5-1 (Post genomic approaches to understand the molecular basis of asthma aiming at a preventive or therapeutic control). This study makes use of data generated by the UK10K Consortium. A full list of the investigators who contributed to the generation of the data is available from www.UK10K.org. Funding for UK10K was provided by the Wellcome Trust under award WT091310. Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest.

BACKGROUND: The effect of maternal age at conception on various aspects of offspring health is well documented and often discussed. We seldom hear about the paternal age effect on offspring health, although the link is now almost as solid as with maternal age. The causes behind this, however, are drastically different between males and females.CONTENT: In this review article, we will first examine documented physiological changes linked to paternal age effect. We will start with all morphological aspects of the testis that have been shown to be altered with aging. We will then move on to all the parameters of spermatogenesis that are linked with paternal age at conception. The biggest part of this review will focus on genetic changes associated with paternal age effects. Several studies that have established a strong link between paternal age at conception and the rate of de novo mutations will be reviewed. We will next discuss paternal age effects associated with telomere length and try to better understand the seemingly contradictory results. Finally, severe diseases that affect brain functions and normal development have been associated with older paternal age at conception. In this context, we will discuss the cases of autism spectrum disorder and schizophrenia, as well as several childhood cancers.SUMMARY: In many Western civilizations, the age at which parents have their first child has increased substantially in recent decades. It is important to summarize major health issues associated with an increased paternal age at conception to better model public health systems. (c) 2018 American Association for Clinical Chemistry