An update on the genetics of atopic dermatitis: Scratching the surface in 2009

Article Outline

• Abstract
• • Discovery of atopic dermatitis genes with traditional approaches: Genome-wide linkage and candidate gene association studies
    • Genome-wide linkage studies on AD
    • Candidate genes in select pathways of AD
    • Adaptive and innate immune response genes
    • Skin barrier dysfunction genes
    • New approaches on the horizon: The genome-wide approach
      • GWASs
      • High-throughput gene profiling
  • Confounders and complexities
    • It's not all about the genes
    • Ethnic diversity and underrepresentation
• Summary
• Acknowledgment
• Table E1. 
• References
• References
• Copyright

A genetic basis for atopic dermatitis (AD) has long been recognized. Historic documents allude to family history of disease as a risk factor. Before characterization of the human genome, heritability studies combined with family-based linkage studies supported the definition of AD as a complex trait in that interactions between genes and environmental factors and the interplay between multiple genes contribute to disease manifestation. A summary of more than 100 published reports on genetic association studies through mid-2009 implicates 81 genes, in 46 of which at least 1 positive association with AD has been demonstrated. Of these, the gene encoding filaggrin (FLG) has been most consistently replicated. Most candidate gene studies to date have focused on adaptive and innate immune response genes, but there is increasing interest in skin barrier dysfunction genes. This review examines the methods that have been used to identify susceptibility genes for AD and how the underlying pathology of this disease has been used to select candidate genes. Current challenges and the potential effect of new technologies are discussed.

Key words: Atopic dermatitis, genetics, IgE-mediated response, innate immunity, skin barrier dysfunction, genetic association, gene-environment interaction, ethnicity

Abbreviations used: AD, Atopic dermatitis, cM, Centimorgans, EDC, Epidermal differentiation complex, FLG, Filaggrin gene, GWAS, Genome-wide association study, NOD, Nucleotide-binding oligomerization domain, OR, Odds ratio, SC, Stratum corneum, SNP, Single nucleotide polymorphism, TJ, Tight junction, TLR, Toll-like receptor

More than 2,500 years ago, Hippocrates described a condition of an undetermined cause characterized as “itching over [a patient's] whole body.”¹ During the 18th and 19th centuries, what was believed to be this nondescript pruritic state was termed “eczema” or “prurigo diathésique.”² The condition received increasing attention in the dermatologic literature in the late 19th and early 20th centuries, especially as a component of the allergic diathesis, as Coca noted that “every recognized category of allergic disease affects the skin,” suggesting that, “among the diseases of the skin the familial allergy (hay fever-asthma group) is represented by atopic eczema.”³ The term was ultimately replaced with the descriptive term “atopic dermatitis” (AD) by Coca.³

A common theme from the most ancient descriptions of this syndrome to more recent observations is that allergy in general and AD in particular has a profound capacity to run in families. That is, AD, even more so than other atopic disorders, is highly heritable. For example, in the Munich Asthma and Allergy Study, it was demonstrated that the risk of a child having AD if one or both parents have AD is higher (odds ratio [OR], 3.4; 95% CI, 2.6-4.4) compared with the risk if 1 or both parents have asthma (OR, 1.5; 95% CI, 1.0-2.2) or allergic rhinitis (OR, 1.4; 95% CI, 1.1-1.8),⁴ supporting the notion that although generic atopy genes might be responsible for the manifestation of AD, there are likely to be phenotype-specific genes as well. Early observations of a strong family history of allergy, eczema, and asthma⁵, ⁶ contributed not only to an understanding of at least one of the underlying causes of AD (ie, an allergic response to “environmental inhalant factors” in addition to “hereditary factors”⁵) but also promoted the next stage of heritability investigations. A number of twin studies suggested wide ranges of concordance rates of between 0.23 and 0.86 for monozygotic twins and 0.15 and 0.5 for dizygotic twins.⁷, ⁸, ⁹, ¹⁰, ¹¹ These wide ranges can probably be explained in part by heterogeneity of the phenotype and phenotype definition across studies, but as suggested by the relatively low concordance in some studies, even for identical twins, the environment is also influencing disease risk and manifestation. Parent-of-origin effects, or maternal heritability, has also been attributed to AD,¹² an observation that has subsequently been supported by genetic association studies (ie, maternally transmitted alleles in the Kazal-type serine protease inhibitor 5 [SPINK5] gene).¹³

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Discovery of atopic dermatitis genes with traditional approaches: Genome-wide linkage and candidate gene association studies 

Given the long-standing recognition of the role of heritability in the manifestation of AD and the characteristic early age of disease onset, AD is a trait highly amenable to the genome-wide linkage approach for identifying novel genes. The genome-wide linkage method is a family-based approach relying on a collection of affected individuals (probands) and their parents (ie, case-parent trio design) or affected sibling pairs and their parents (and often additional family members) for which the inheritance pattern of a trait is compared with the inheritance pattern of chromosomal regions using highly polymorphic genetic (microsatellite) markers evenly spaced across all chromosomes (Fig 1, A). There are several advantages of genome-wide linkage mapping, such as that it is hypothesis independent because the entire genome is scanned without regard to specific candidates. Because of the polymorphic nature of microsatellite markers, genome-wide linkage mapping is cost-effective because it requires a relatively small number of markers (approximately 350); as a result, a significant linkage peak requires a much lower correction of the P value (eg, an LOD score of 3.6 or P = 2 × 10⁻⁵)¹⁴ compared with study designs involving thousands or tens of thousands of markers. Because linkage cannot detect genes with minimal or modest disease effect, linkage peaks that reach statistical significance are generally indicative of a locus (loci) with substantial effect on disease risk.

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• Fig 1. 

  Methods for detecting disease susceptibility genes. A, Genome-wide linkage method relying on polymorphic microsatellites referred to as short tandem repeat polymorphisms (STRPs) evenly spaced across the chromosomes, typically including approximately 350 STRPs. B, Candidate gene approach whereby genetic markers, usually easily typed substitutions (ie, SNPs) or structural variants (ie, insertions/deletions), are selected within and flanking a candidate gene of interest. C, GWASs using hundreds of thousands and up to 1 million SNPs to fully cover a subject's genome represent a hypothesis-free systematic search across the genome to identify novel associations with common diseases using a set of haplotype-tagging SNPs (htSNPs), which are indicated as blue arrows. htSNPs represent a relatively small subset of SNPs of the potential 2.5 million SNPs in the public database (ie, needed to uniquely identify a complete haplotype). The premise behind htSNPs is the observation that when SNPs are in linkage disequilibrium with each other and form haplotypes, there is redundant information contained within the haplotype because several of the SNPs will always occur together. Thus a marker at one locus can reasonably predict a marker or markers that will occur at the linked locus nearby.

To date, there have been 5 genome-wide linkage studies performed on AD, plus a genome-wide linkage screen originally designed for asthma with analyses repeated for the AD outcome (Fig 2). All but one of these screens were performed on families of European ancestry: (1) 199 German and Scandinavian,¹⁵ (2) 148 British,¹⁶ (3) 109 Swedish,¹⁷ (4) 100 Danish,¹⁸ and (5) 295 French¹⁹ families, of which 62 affected sib pairs for AD were available for reanalysis. The non-European study was performed on 77 Japanese families selected through 111 sib pairs with AD (287 individuals) and relied on a linkage mapping panel of 5,861 single nucleotide polymorphisms (SNPs) rather than the microsatellite panel traditionally used for linkage screens.²⁰

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• Fig 2. 

  Summary of genome-wide linkage studies of AD: representation of the 23 human chromosomes, highlighting those loci for which genome screens have identified linkage to AD. Loci are mapped to short or long chromosomal arms and color coded according to the studies listed in the legend.¹⁵, ¹⁶, ¹⁷, ¹⁸, ¹⁹, ²⁰ See Table E1 in this article's Online Repository for a complete summary of 111 published studies.

Underscoring the heterogeneity commonly observed in complex diseases, which, in addition to genetic heterogeneity, reflects heterogeneity of nongenetic factors, including differences in family ascertainment schemes, definition of the phenotype, and analytic approaches, there has been limited overlap of signals among these genome-wide linkage studies. Only the 3p24 locus has been truly replicated, with significant LOD scores observed for microsatellite markers in chromosome 3p24-p22 in the Swedish¹⁷ families and chromosome 3p26-p24 in the Danish¹⁸ families. Under a more relaxed threshold of a maximum distance of 25 centimorgans (cM) between linkage peaks, replication can be considered for the chromosome 3q13-q21 locus in the German/Scandinavian¹⁵ and Swedish¹⁷ samples and chromosome 18q11-q21 in the Danish¹⁸ and Swedish¹⁷ samples.

In the French study the linkage screen was originally designed to study asthma and allergic rhinitis in a sample of 295 families ascertained through asthmatic probands, but analyses were repeated for the outcome of eczema and demonstrated linkage at 5q13 and 11p14. Follow-up fine mapping of 8 markers in the 11p14 locus suggested a pleiotropic effect for the 3 allergic diseases of AD, asthma and allergic rhinitis. More recently, the Danish team followed up on their previous evidence for linkage at the 3 p, 4q, and 18q loci, in addition to previous evidence for linkage at 3q, in an independent sample of 130 AD sib-pair families and concluded the strongest evidence for linkage was to 3p34, 3q21, and 4q22.²¹ From these follow-ups, however, conclusions are speculative at best, given that each of the regions in which significant evidence of linkage has been identified contains multiple candidate genes. The best evidence for linkage in any one of these regions tends to extend over relatively large portions of the chromosome, rendering pinpointing of any specific locus (or gene) very difficult.

Although the genome-wide linkage approach represented one of the most sophisticated technologies in genetic epidemiology just over a decade ago, inherent challenges in this approach, including the considerable cost to follow-up genotyping of unwieldy and large chromosomal loci and the difficulties ascertaining sufficient numbers of complete families, has been, in part, an impetus for pursuing alternative approaches in gene hunting. After an initial genome-wide linkage analysis, positional cloning usually follows, whereby extra microsatellite markers at a density of 0.5 to 1.5 cM are genotyped over the linkage peaks that are suggestive or significant in the initial scan until the precise locus contributing to linkage is identified. However, even at this level of fine mapping, with an aim of localizing a gene to a region less of than 1 cM (1 cM ≈ 1 million base pairs), the region of peak linkage score might still include hundreds of genes. In none of the AD genome-wide linkage studies shown in Fig 1 was a candidate gene identified with positional cloning.

With the publication of initial efforts in sequencing the human genome²² (http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml), the opportunity to genotype markers directly in genes of interest was greatly expanded as polymorphisms were identified in the approximately 20,000 to 25,000 genes across the 3 billion chemical base pairs that make up human DNA. Relying on one of the simplest of these polymorphisms, SNPs, and relatively simple structural variants, such as insertions/deletions and repeats, this advancement allowed researchers to expand genetic studies beyond linkage toward the genetic association study design (Fig 1, B). Because many more biallelic markers are required compared with microsatellites to detect linkage and association across the genome, a candidate gene approach was adopted whereby investigators have focused on a specific gene or set of genes believed to be causally involved in the underlying pathology of a certain disease. An advantage of the candidate gene approach is that it is not limited to families and can be applied to case-control study designs, which possess certain advantages over family-based studies. For example, although association studies based on case-control designs are sensitive to confounding due to population stratification (ie, ethnic/racial admixture),²³ they are generally considered to be more powerful in detecting true associations once the gene has been identified.²⁴ Moreover, it is considerably easier (requires less effort and has lower costs in recruitment) to amass reasonably powered groups of patients with AD and healthy control subjects without AD than it is to collect complete case-parent trios or nuclear families.

For these reasons, there has been considerable effort in conducting association studies on AD and related phenotypes in independent populations in the post–genome-wide linkage era. In a search of the public database (http://www.ncbi.nlm.nih.gov/pubmed/) through June 2009, using key words including “association,” “atopic dermatitis,” “eczema,” “gene,” “polymorphism,” “mutation,” and “variant,” 111 studies were identified for which results of tests for association for AD were reported on a candidate gene (see Table E1 in this article's Online Repository at www.jacionline.org). The major outcome was limited to AD as a qualitative trait or AD severity. A significant association was defined liberally as any association at a P value of less than .05 without regard to effect size or weaknesses in the study design. Limitations in this exercise include the sometimes missing information on the precise variant for which association was (or was not) demonstrated and the unfortunate reality that negative association studies are rarely published and are therefore underrepresented in Table E1. In most instances the only information available on genes for which association was sought but for which the result was negative are those studies for which the negative results are included in manuscripts reporting positively associated genes/variants. In other words, there are undoubtedly more genes for which associations have been tested but failed but for which the information is not available in the public arena.

It is critical to note that there are several biases in this summary. First, there is the bias of reporting associations in studies for which either type I error (false-positive result) or type II error (false-negative result) is possible (and in many cases likely) because of the limited power in the original study design. Other biases are related to potential study design weaknesses, such as a failure to adjust for population stratification in the case-control studies and consideration of Hardy-Weinberg proportions. There is a general assumption that for risk variants with common allele frequencies of greater than 20%, the ORs will range from 1.1 to 1.5, and for rarer risk allele frequencies (ie, <0.20), the ORs can be approximately 3.0. Based on these assumptions, there is a requirement of at least 1,000 cases and 1,000 control subjects to detect ORs of approximately 1.5 with at least 80% power, although the required sample size is dependent on multiple additional factors. Regardless, according to the summary in Table E1, in barely 2 dozen of the reported studies have sample sizes reached even 250 in each group. Another important consideration is the extreme heterogeneity of the phenotype definition from study to study, wherein some studies consider early-onset AD versus studies that combine pediatric populations with adult populations, variations in means for determining disease severity, and so on. Variation in the phenotype renders replication of associations especially difficult.

A critical bias in this exercise is that replication was considered at the level of the gene rather than the specific variant/mutation. Elsewhere, there has been extensive discussion regarding the merit of this approach, including the comprehensive review of asthma genetics by Ober and Hoffjan,²³ in which the authors refer to advocacy of a gene-centric approach because the more conventional SNP-for-SNP approach is predicated on the assumption that allele frequencies and haplotype structure at a specific locus is identical in 2 (or more) populations, which is unlikely.²⁵ Elsewhere, the pitfalls of this “loose” replication have been cautioned.²⁶ However, a major outcome from the International Haplotype Map Project²⁷ is the observation that a large portion of the human genome is arranged into blocks of common polymorphisms (SNPs) in strong linkage disequilibrium with one another, and there is considerable diversity within these haplotype blocks. Because much of this diversity is driven by mutation and given our knowledge that the functional properties of protein products (eg, candidate genes) can depend on specific combinations of multiple polymorphisms within a gene or interactions with polymorphisms in other genes,²⁸ it is not surprising that a single-locus approach might fail to detect association a priori, much less fail to replicate across studies in different sets of populations. The recent report by Rogers et al,²⁹ wherein they combined SNP data from the Ober and Hoffjan review²³ supplemented by their own review of the asthma genetics literature with SNP data from their genome-wide association study (GWAS) on more than 1,000 asthmatic children and family members in the Childhood Asthma Management Program study and more than 500,000 SNPs, underscores the unlikely success in replication at the SNP level because the group only identified 10 significantly associated SNPs in 6 genes that were on the commercial SNP chip and that overlapped with 160 SNPs in 39 genes previously associated with asthma in the literature.²⁹

Finally, another area of potential controversy has to do with common versus rare variants. A perspective on the scientific value of GWASs³⁰ suggested that (assuming currently available commercial chips capture the bulk of common genetic variation) SNPs with large effects might have already been discovered (implying there is no need for additional genome wide scans) and that the focus should therefore shift toward detailed search for rare variants. Although the application of both conventional candidate gene studies and GWASs has lead to the discovery of hundreds of loci conferring risk of common diseases, it has been noted that the risk variants identified by GWASs in particular explain only a small fraction of the disease-specific heritability. One explanation that is beginning to emerge is that much of the remaining heritable disease risk is associated with rare variants (usually defined as those with a frequency of <5% to ≤1%).³¹ For example, rare alleles of at least 10 loci contribute to the risk for breast cancer, and more than 40 loci underlie the risk of type 1 diabetes. Importantly, in contrast to common variants, rare nonsynonymous variants in the human genome might be deleterious and therefore of significance because they influence protein function, phenotypic variation, or both. Most of these variants are probably only mildly deleterious, segregate at low frequencies, and are not pathogenic. However, a subset of these variants have more modest effects and are rare but could collectively explain a substantial fraction of the heritable variability of common disease phenotypes.

Although rare coding variants might have a greater functional effect than common variants, their analysis must consider the low frequency of any variant because it will reduce the power to infer statistical associations and therefore require very large populations of cases and control subjects or affected families. This complication can be overcome by evaluating the collective frequency of rare nonsynonymous variants within 1 or more genes or for a pathway or pathways and the functional effect of the discovered variations. As described further below, however, with the exception of studies focused on mutations in the gene encoding filaggrin (FLG), few if any other studies in patients with AD have specifically focused on rare variants or have been designed with sufficient power to be able to detect rare variants.

Despite the biases and potential pitfalls described above, several interesting conclusions can be inferred from this comprehensive review of the literature on the genetics of AD. In the 14 years since the first published report on an association between a genetic variant and AD, more than a third of the studies have been reported in the past 2½ years, and already in the first half of 2009, more reports have been published than in all of 2008. From these 111 published studies, there are reports on 81 genes, of which more than half (46 genes) had at least 1 positive association study reported (Fig 3). Of these 46 genes, 15 studies failed to replicate associations, and 13 were positively associated in at least 1 other independent study. One of these genes, FLG, has been associated with AD in 20 different reports (details below). There are 35 additional genes studied for which there has been no evidence for a positive association to date.

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• Fig 3. 

  Genes associated with AD in at least 1 published study. Genes are grouped according to how many positive association studies have been reported (see Table E1 in this article's Online Repository for a complete summary of 111 published studies). The y-axis indicates the number of genes (corresponding to the yellow boxes) for each time that a positive association was reported.

The well-established comorbidities of the other 2 allergic diseases that constitute the atopic triad (ie, asthma and allergic rhinitis), in addition to the sensitization to common aeroallergens that is commonly observed in patients with AD, has guided researchers toward selection of candidate genes that fall within the broad category of dysregulation of the adaptive and innate immune response and a heightened IgE-mediated, systemic T_H2 response plus a combined T_H1 and T_H2 response in the skin. This selection bias is evident in Table E1.

For complex diseases, such as AD, that involve a dense network of immune response proteins, it is anticipated that many genes will be involved and that multiple genetic variants will contribute to the alteration of gene function and expression. Because the effect of a single gene/polymorphism in a complex disease, such as AD, is anticipated to be relatively modest, it can be assumed that variants in multiple genes will cooperate in an additive or synergistic manner to affect disease risk, a phenomenon referred to as epistasis. A major difficulty in testing for epistasis is power: not only will fewer subjects in a sample possess both polymorphisms (or a set of polymorphisms) associated with risk of disease compared with the number of subjects with only 1 of the polymorphisms but also the correction factor for additional (multiple) comparisons (ie, tests for association) is quite large. Consider the example of 100,000 genetic markers, wherein there are a total of 5 × 10 + 9 2-locus combinations, requiring a (Bonferroni) correction factor of P = 1 × 10⁻¹¹ for a GWAS significance level of .05.³²

One approach toward characterizing potential gene-gene interactions and systematically evaluating the role of candidate genes/polymorphisms in AD susceptibility for which there is compelling evidence for association is to implement the program Ingenuity Pathways Analysis (Ingenuity Systems, Inc, Redwood City, Calif; www.analysis.ingenuity.com). The Ingenuity Pathways knowledge base is a Web-based entry tool developed by Ingenuity Systems, Inc, to characterize genes according to the predefined canonical pathway or pathways into which they fit and also to investigate the extent to which genes are in shared networks and might cooperate in a synergistic or additive manner to affect the risk of disease. As a proof of concept, we evaluated the 81 genes summarized in Fig 3 using the Ingenuity Pathway Analysis. Slightly more than half (n = 48) of the 81 genes studied to date clustered in 2 major networks, both of which are associated with immune dysregulation, specifically the pathway associated with antigen presentation and cell-mediated and humoral immune response and the pathway associated with cell signaling and interaction, cellular movement, and hematologic system development and function. Six genes (monocyte differentiation antigen CD14 [CD14], GATA-binding protein 3 [GATA3], interleukin 4 [IL4], IL18, nucleotide-binding oligomerization domain 1 [NOD1], and Toll-like receptor 2 [TLR2]), which have previously been significantly associated with AD, were clustered into the antigen presentation and immune response pathway, and 9 previously associated genes (BCL2-related protein A1 [BCL2A1], brain-derived neutrophilic factor [BDNF], Regulated upon Activation, Normally T-Expressed, and presumably Secreted [RANTES], colony-stimulating factor 2 [CSF2], glutathione S-transferase, 1 [GSTP1], IL5, interleukin 12 beta [IL12B], interleukin 12 receptor beta 1 [IL12RB1], and suppressor of cytokine signaling 3 [SOCS3]) were clustered into the cell-signaling/movement pathway. Although the studies for which these candidate genes were evaluated did not specifically test for gene-gene interaction, this interrogation of the potential for interaction serves as an example of the power of this approach in selecting optimal candidates for genetic association studies.

In addition to immune dysregulation manifested as IgE-mediated sensitization to numerous allergens, AD is also characterized as a common, chronic, pruritic, inflammatory skin disease complicated by recurrent bacterial and viral skin infections (ie, Staphylococcus aureus and herpes simplex virus).³³, ³⁴ More seriously, patients with AD are at greater risk for severe and generalized viral infections caused by herpes simplex virus (eg, eczema herpeticum), molluscum contagiosum virus (eg, eczema molluscatum), and eczema vaccinatum, which occurs after exposure to the smallpox vaccine.³⁵

Increased susceptibility to infections and cutaneous colonization implicate several of the immune function genes listed in Fig 4, A, specifically those genes associated with a dysfunctional host defense (or innate immune) response. These candidates include the pattern-recognition receptor type I transmembrane, TLRs,³⁶ the NOD–leucine rich–containing protein family (NOD1 and NOD2),³⁷, ³⁸ and CD14.³⁹, ⁴⁰, ⁴¹ Antimicrobial peptides, including S100 proteins, human defensin α and β, and sphingosine, exert potent antimicrobial activity by directly killing bacteria, fungi, and certain viruses.⁴² Natural killer cells, a critically important population of lymphocytes for innate immune responses against viral infection,⁴³ are dependent on transcription factors, such as IFN regulatory factor 2, for efficient cell development. (For an extensive review on innate immunity in AD, see McGirt and Beck⁴⁴ and De Benedetto et al.⁴⁵) Genetic association studies on AD to date in fact support a number of these candidates (ie, TLR2, NOD1, NOD2, CD14, and defensin beta 1 [DEFB1]; Fig 3). In addition to the direct effect of genetic modifications in innate immune response molecules and their role in susceptibility to infection, the attenuation of upregulation of the normal antimicrobial response to bacterial and viral stimuli because of an overabundance of T_H2 cytokines in the skin appears to be especially relevant in patients with AD.⁴⁶, ⁴⁷ For example, it has been demonstrated that increased T_H2 cytokine levels can inhibit mobilization of potent innate immunity molecules, such as human β-defensin 3, in epidermal keratinocytes.⁴⁸ Alternatively, persistent S aureus infections can also mediate inflammatory cascades by staphylococcal toxins acting in a superantigen-driven fashion to activate T cells⁴⁹ or by induction of a state of glucocorticoid resistance.⁵⁰ This observation further underscores the potential relevance of gene-gene interactions, as shown in Fig 4, A.

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• Fig 4. 

  Networks revealed through the Ingenuity Pathways Analysis based on 81 AD genes established in genetic association studies. Forty-eight genes clustered into 2 major networks associated with immune dysregulation. A, Antigen presentation and cell-mediated and humoral immune response pathway. Significantly associated genes are highlighted in dark blue. B, Cell signaling and interaction, cellular movement, and hematologic system development and function pathway. Significantly associated genes are highlighted in dark green. For both panels, genes or gene products are represented as nodes (shapes; see legend) that represent the functional class of the gene product. The relationship between genes is presented as solid lines with arrows (direct activation), and arrows point to the element on which an action is performed. All relationships (or lines) are supported by at least 1 reference (numbers of references in parentheses). Annotation of relationship (labels) between the nodes: A, Activation; E, expression; I, inhibition; MB, group/complex membership; PD, protein-DNA binding; PP, protein-protein binding. See Table E1 in this article's Online Repository for a complete summary of 111 published studies.

Notably, the candidates described above and summarized in Fig 4, as well as Table E1, are not all unique to AD; in fact, many AD candidate genes overlap with not only other atopic phenotypes (eg, asthma and allergic rhinitis) but also other diseases of inflammation and immune dysfunction. The common disease/common variant hypothesis⁴¹ has been put forth as one explanation for why many complex diseases are so common and why disease-associated variants occur at such a high frequency in the population. The common variant/multiple disease hypothesis, which is an extension of the common disease/common variant hypothesis, suggests that certain disease genes might not be disease specific and might contribute to related clinical phenotypes.⁵¹ One possibility is that the functional effects of certain alleles manifest in multiple disorders, presumably because they are involved in basic underlying immune regulatory pathways. Multiple examples of genetic association of the same gene (or allele) to diverse but related disorders abound (see the Genetic Association Database at http://geneticassociationdb.nih.gov). For example, in addition to AD, genetic associations have been observed in DEFB1 for asthma,⁵² chronic obstructive pulmonary disease,⁵³ and infectious diseases, including HIV⁵⁴ and sepsis.⁵⁵ NOD2 polymorphisms, in addition to AD, have also been associated with Crohn disease⁵⁶ and sarcoidosis.⁵⁷ Associations with RANTES polymorphisms are especially diverse, including phenotypes associated with immune response, infection, reproduction, and metabolic disorders (http://geneticassociationdb.nih.gov/). Given the prominent role that certain pathways, such as host defense, play in susceptibility to AD, it is likely that many more coassociations will be observed in the near future.

It is increasingly appreciated that both genetic and environmental factors that affect skin barrier function contribute to AD susceptibility⁵⁸ and that barrier dysfunction is an essential feature of AD and allergic diseases in general.⁵⁹, ⁶⁰, ⁶¹, ⁶², ⁶³ A disrupted barrier would allow penetration of microbes and allergens and other environmental insults, such as toxins, irritants, and pollutants, with consequences including inflammation, allergen sensitization, and bacterial colonization. This might explain why 55% to 90% of patients with AD are colonized with S aureus compared with only 5% of subjects without AD.⁶⁴, ⁶⁵, ⁶⁶, ⁶⁷, ⁶⁸ Although the epidermis functions as the primary defense to the external environment, considerable barrier function is regulated by the stratum corneum (SC) and by the tight junctions (TJ), which reside at the level of the stratum granulosum. When the SC is compromised, either by reduced levels of SC lipids,²⁹, ³⁰, ³¹ mechanical trauma resulting from extensive scratching that is precipitated by intensive itch (the hallmark of AD), or as a result of genetic defects in SC proteins (ie, FLG), TJs are the next line of defense. Currently, there is considerable interest in the more than 40 proteins that comprise TJs, which include the claudin family members, occludin, cingulin, tricellin, and the cytoplasmic plaque proteins,⁶⁹ which bind to actin and myosin,⁷⁰ and their role in human disease in general⁷¹ and specifically in AD.

As described earlier, linkage screens performed on AD to date have not elucidated specific candidate genes per se, but they have implicated loci harboring clusters of genes associated with skin barrier dysfunction. Specifically, one of the earliest screens indicated linkage at the epidermal differentiation complex (EDC) locus on chromosome 1q2116, which contains a very large and diverse family of genes associated with skin barrier dysfunction, including loricrin, involucrin, members of the S100 gene family, a large group of the late cornified envelope gene family, many of the small proline-rich proteins, peptidoglycan recognition proteins (ie, PGLYRP3 and PGLYRP4) and, most notably, FLG.⁷² Linkage has also been reported in 17q2117, where the gene encoding one of the keratins (KRT16) is localized.

Association studies on genes related to the EDC cluster and other barrier dysfunction candidates have, to date, been largely restricted to FLG, also known as filament-aggregating protein, and within FLG, most associations have been limited to 2 null mutations (R501X and 2282del4). In fact, FLG is the most consistently associated gene with risk of AD⁷³; as shown in Fig 3, by mid-2009, there were 20 positive reports on genetic associations between FLG mutations and AD. The gene encoding human FLG was first cloned in 1989, when it was found to contain numerous tandem FLG repeats localized to chromosome 1q21, and because of its tight regulation at the transcriptional level in terminally differentiating epidermis, it was postulated to be an important candidate for disorders of keratinization.⁷⁴ It was subsequently evaluated for its function in the formation of the SC and found to be a critical protein involved in epidermal differentiation and in maintaining barrier function.⁷⁵ Smith et al⁷⁶ developed long-range PCR conditions for a 12-kb genomic fragment covering exon 3 of FLG and identified a homozygous nonsense mutation (R501X) near the start of repeat 1 and a second mutation (2282del4) that similarly stops protein translation within the first FLG repeat in 3 patients with ichthyosis vulgaris. They demonstrated that these relatively rare mutations (a combined allele frequency of approximately 4% in the European population studied) are semidominant, with heterozygotes exhibiting mild disease with incomplete penetrance. Shortly thereafter, the same group showed that these 2 loss-of-function variants were associated with AD⁷⁷ and that they are ancestral European variants carried on conserved haplotypes.⁷⁸

Full sequencing of the FLG gene by the same team has revealed multiple additional polymorphisms with varying frequency across ethnic groups⁷⁸; however, with a combined allele frequency among patients with AD of 18% and 48% for the R501X and 2282del4 mutations, respectively, the 2 null mutations represent the strongest and most compelling genetic risk factors for AD. In the largest meta-analysis performed thus far on the R501X and 2282del4 mutations, Rodriguez et al⁷⁹ analyzed data from 24 independent studies, which included 6,448 cases, 26,787 control subjects, and 1,993 families (all selected for AD) and determined that the effect size for risk of eczema caused by the 2 FLG null mutations is not dissimilar to previous reports at an OR of just over 3.

The FLG mutations have also been consistently associated with risk of other atopic traits, including asthma, hay fever, rhinoconjunctivitis, and allergen-specific IgE.⁷⁹, ⁸⁰, ⁸¹, ⁸², ⁸³, ⁸⁴, ⁸⁵, ⁸⁶ Recently, Gao et al (unpublished data) evaluated whether FLG polymorphisms contribute to the serious complication of AD resulting from disseminated cutaneous herpes simplex virus infections (eczema herpeticum) and determined that the frequency of the R501X mutation was 3 times higher (24% vs 8%, respectively) and the relative risk for disease nearly double for patients with eczema herpeticum compared with those with AD without eczema herpeticum (OR, 11.8 vs 6.2; P = .0008). The authors speculate that the relationship between FLG null mutations and disease is most likely related to an increased propensity for disseminated viral skin infection resulting from skin barrier dysfunction rather than disease severity per se and provide the first insight into the genetic underpinnings of AD complications, such as viral dissemination.

GWASs 

A major limitation in the candidate gene approach is that selection of candidates is often based on limited knowledge,⁸⁷ and moreover, each potentially causal variant at each candidate gene can only make a modest contribution to overall heritability. Data from the Haplotype Map Project combined with more accurate approaches in selecting tagging markers sufficiently dense to capture most of the common variation in the human genome (Fig 1, C) have recently allowed GWASs to replace candidate gene studies as an unbiased approach to search for genes controlling the risk for complex diseases. At the time of this review, results have been published on 1 GWAS for AD in which investigators in Germany genotyped a set of AD cases and control subjects and an independent set of 270 nuclear families on the Affymetrix Human mapping 500 K and 5.0 arrays (resulting in 342,303 successfully typed markers).⁸⁸ Although none of the markers analyzed were significantly associated with AD at the genome-wide significance level (P < 1.46 × 10⁻⁷), the group genotyped 54 SNPs associated with AD at a modest P value in an independent German group and observed replication in markers in chromosomal regions 1q21, 9p21, and 11q13, with further replication in an additional European group for a marker (rs7927894) in an intergenic region near chromosome 11 open reading frame 30 (C11orf30) on chromosome 11q13.5, which is the same marker that has been associated with Crohn disease.⁸⁹ An additional European-based GWAS is in the replication phase. It will be of interest to determine the extent to which the Esparza-Gordillo et al⁸⁸ findings will be replicated.

High-throughput gene profiling 

Expression profiling of all known genes in the human genome is an ideal strategy for characterizing disease mechanisms and defining the transcriptome of complex diseases, such as AD. Indeed, genome-wide microarray technology has the potential to identify molecular signatures of clinical disease impossible to identify by using a gene-by-gene approach, and there are many examples whereby this technology can be highly predictive of clinical outcome. Although relatively few genome-wide expression studies have been performed for AD, which is likely due to the difficulties in ascertaining sufficient numbers of selected cell types of the epidermis and other relevant tissue samples, limitations related to the size of biopsied tissue, and challenges in ensuring collection of representative samples, it is anticipated that integration of this technology into gene discovery for AD will increase, especially as the cost for performing a genome-wide microarray continues to decrease.

Sugiura et al⁹⁰ performed high-throughput expression profiling of biopsy specimens from skin lesions of patients with AD compared with those from healthy control subjects and observed that several of the most significantly differentially expressed genes (ie, S100A8 and S100A7, upregulated; loricrin and FLG, downregulated) were epidermal differentiation genes localized in chromosome 1q21, a region previously linked with AD. (Note: results were similar in comparisons between affected and unaffected skin among the patients with AD.) Similar findings have been observed by Beck et al (personal communication), who compared nonlesional skin of patients with extrinsic AD with the skin of nonatopic healthy control subjects (Fig 5, B). The Sugiura et al group also observed that keratin 16, localized on chromosome 17q21, another linkage hotspot, was upregulated. In addition to validating genes, high-throughput expression studies have led to novel discoveries. One example is the work by Lu et al,⁹¹ in which they relied on primary cultured keratinocytes from patients with AD and healthy control subjects to identify a number of novel candidates. Significant findings included 2 extracellular matrix–associated factors, matrix metalloproteinase 1 and 10, for which ELISA studies of sera from patients with intrinsic AD showed that both proteins were upregulated nearly 2-fold compared with levels seen in healthy subjects and patients with extrinsic AD. In a differentiated keratinocyte model, FLG2 (or ifapsoriasin), also localized in the EDC, was identified, as well as 3 novel lipase genes, suggesting that these genes might also play a key role in the skin barrier and are worthy of further study.⁹² Thus, high-throughput expression profiling has already proved useful in supporting the hypothesis that defects in epidermal genes play a critical role in the development of AD, and it is also a tool for validating genetic findings and gene discovery.

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• Fig 5. 

  Genetic epidemiologic approaches toward identification of genes conferring AD susceptibility. In this summary of approaches used to date to identify candidate genes for AD, the first consideration is the complex pathology of AD (A), which includes defects and damage at the epithelial barrier and penetration of allergens, microbes, pollutants, and irritants into the epidermis and dermis, ultimately interacting with antigen-presenting cells (ie, Langerhans cells and dermal dendritic cells). The brick wall–like structure of the SC is compromised, possibly by defects in genes residing in the EDC, including FLG, loricrin (LOR), LCEs, S100s, SPRRs, SCTE, and SCCE. Additional candidates include TJs, proteins that constitute the “gate” to the passage of water, ions, and solutes through the paracellular pathway in the stratum granulosum (ie, CLDN1). A defective innate immune response (involving, for example, the TLRs, CD14, NOD1, NOD2, DEFB1, and IRF2) might contribute to a heightened, IgE-mediated, systemic T_H2 response. Combining a candidate gene approach with robust, genome-wide gene expression profiling has the potential of both elucidating novel candidates and validating suspected candidates, as shown in B, in which genes in the EDC on chromosome 1q21 are significantly differentially expressed in skin biopsy specimens taken from patients with AD compared with those from healthy nonatopic control subjects (courtesy of L. A. Beck). Candidate genes are selected, substitutions (ie, SNPs) and simple structural variants (ie, insertions/deletions and repeats) are genotyped in large populations selected for AD, and tests for association are performed.

Confounders and complexities 

The role of the environment. In the same year that Watson and Crick reported their structure of the DNA molecule in the journal Nature,⁹³ Senior Registrar at the Manchester and Salford Hospital for Skin Diseases, Dr J. K. Morgan, made the following observation: “In theory, in every case in which there is an eczematous reaction in the skin, there are two prime factors involved. The first, and the more important, is a constitutional or internal factor, relating to the individual himself. The second in an external factor. It is upon the relative balance and interplay between these two that the appellation of the disease is based.”⁹⁴

In the years of heritability studies that followed (described above), the consistent observation that concordance rates for AD among monozygotic twins raised together are higher than those among dizygotic twins supported the role of a genetic cause, but the relatively low concordance rates in both groups also supported the earliest suppositions that differences in exposure to certain environmental triggers might account for a considerable proportion of disease expression.

The challenge in the genetic epidemiology of AD in terms of interrogating gene-environment interactions is precisely which environmental factors should be considered. For example, at the core of the innate immune response are the ubiquitous fragments of bacterial LPS, or endotoxin, and many studies focusing on endotoxin exposure early in life suggest a protective effect in the development of allergic disease in general⁹⁵, ⁹⁶ by skewing the T_H profile toward T_H1, as purported by the hygiene hypothesis.⁹⁷ Interestingly, there is some support for the role of the hygiene hypothesis in susceptibility to AD.⁹⁸ Alternatively, the effect of exogenous substances, such as irritants (ie, soap and detergents), allergens (ie, exogenous proteases derived from house dust mites), and drugs (ie, topical corticosteroids) on patients with AD with genetic alterations in skin barrier genes has also been considered.⁵⁸

Very few of the genetic association studies summarized in Table E1 have considered evidence of association between genetic polymorphisms in the context of exposure to certain environmental factors. Perhaps the best example is the study by Bisgaard et al,⁹⁹ in which it was hypothesized that a compromised skin barrier among patients with AD who are FLG deficient might enhance the effect of exposure to certain aeroallergens, such as house dust mite and pet allergen. The group confirmed previous observations that the risk of eczema was considerably higher among children with the FLG mutations (hazard ratio,¹⁰⁰ 2.26; P = .0005) but that the risk increased considerably if children were exposed to cat allergen at birth (hazard ratio, 11.11; P < .0001). Important considerations in similar studies performed in the future will be the ability to detect such interactions for variants with smaller effect sizes, the temporal relationship between environmental exposure and risk of disease (ie, perinatal exposure vs exposure later in childhood), and the generalizability of such findings across populations.

As described previously, failure to replicate associations between genetic markers and a complex trait, such as AD, in independent populations can be due to several factors, including chance, misclassification of the phenotype, environmental heterogeneity, inadequate sample sizes, and population stratification.¹⁰¹, ¹⁰², ¹⁰³ An important factor contributing to failure to replicate associations is also related to population diversity. For example, it is possible that certain genetic markers might contribute to disease risk in a particular (ie, ethnic or racial) population but not in others, either because of differences in frequencies of the risk allele or alleles or because of specific gene-gene interactions. It is difficult to evaluate the effect of ethnicity on genetic associations of AD, however, because there is relatively little diversity in the populations that have been studied thus far. As shown in Table E1, the overwhelming majority (n = 70) of association studies have been performed in populations of European descent, followed by 42 studies performed in Asian populations. A single study was performed in a Mexican cohort, and none of the reported studies have been performed in groups considered underserved minorities, such as African Americans. Sadly, this statistic does not reflect the actual prevalence of AD because African Americans and Asian/Pacific Islanders reportedly have more AD than US whites.¹⁰⁴

Perhaps the best example of a candidate gene for which ethnicity likely influences the extent to which a polymorphism confers risk is FLG. Palmer et al⁷⁷ observed differences in the R501X and 2282del4 FLG null mutation frequencies in diverse cohorts and suggested that different populations will have different FLG mutation profiles. Indeed, this group and others have demonstrated that in populations in which the R501X and 2282del4 mutations are not present, other mutations are prevalent and confer risk of AD, such as the 3321delA and S2554X mutations among Japanese patients.¹⁰⁵ In unpublished data our group observed a complete absence of the R501X mutation and very low frequency (1%) of the 2282del4 mutation among healthy African Americans compared with a frequency of 9% of the R501X mutation and 0% of the 2282del4 mutation among patients with AD. The low frequency and even absence of this mutation is not novel; elsewhere, the prevalence of the R501X mutation among subjects without AD has ranged from 0.8% to 3.0% among European populations and has been found to be absent in southern European (ie, Italian)¹⁰⁶ and Asian⁷⁷, ¹⁰⁵ groups. In the only summary data available on the frequency of this mutation in African populations, it was absent in a cohort of 124 North Africans.⁷⁷ Collectively, the distribution of these alleles suggests a latitude-dependent distribution with a decreasing north-south gradient of frequency and suggests that polymorphisms other than the relatively common R501X and 2282del4 mutations might be more important in non-Northern European groups.

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Summary 

To recapitulate, AD is a chronic inflammatory disease of the skin characterized by dysregulation of the adaptive and innate immune response and a heightened IgE-mediated, systemic T_H2 response. Extreme T_H2 polarization and primary defects in the innate immune response, including epithelial barrier defects, in conjunction with mechanical damage to the epidermis as a consequence of the intense pruritus that is the hallmark feature of AD likely contribute to the more severe sequelae, including chronic bacterial colonization (ie, S aureus infection) and viral dissemination (ie, eczema herpeticum). This scenario can be summarized in Fig 5, whereby the damaged epidermal surface is penetrated by a host of exogenous substances, including allergens, irritants, microbes, pollutants, and even topical drugs. The brick wall–like structure of the SC, which normally creates a barrier that maintains water within the body and prevents the entrance of pathogens and allergens, is further compromised. The EDC, the DNA region in which a large number of genes encoding many of the cornified cell envelope precursor proteins, small proline-rich proteins, members of the S100 family, and intermediate filament-associated protein precursors (ie, profilaggrin) are localized, is an important target of candidate genes associated with barrier dysfunction at the level of the SC. The last line of defense is the stratum granulosum, containing TJs, proteins that constitute the “gate” to the passage of water, ions, and solutes through the paracellular pathway. Systemically, a dysfunctional immune response resulting in an imbalanced innate and adaptive milieu further aggravates the system. Early genome-wide linkage studies, association studies, and high-throughput expression profiling studies have supported the role of skin barrier dysfunction candidate genes in conjunction with innate and adaptive immune response genes. A comprehensive evaluation of all candidate gene studies published to date on AD shows the importance of both sets of genes, and a pathway analysis of the genes studied thus far supports a more thorough approach toward gene-gene and gene-environment interactions.

There are considerable challenges in the field: expanded analyses of skin barrier dysfunction genes to include not only those residing in the SC but also TJ genes at the level of the stratum granulosum; an expanded focus on both rare and common variants; expansion of population studies to include more ethnically diverse groups that are adequately powered; and a better integration of higher-throughput technology in addition to analyses that consider the interactive effects of common environmental factors. Each of these efforts will require greatly expanded sample sizes of carefully phenotyped patients and rigorous statistical approaches. None of these goals are achievable in the absence of a multidisciplinary approach, which will require the equal contributions of expert clinicians, geneticists, statistical analysts, and molecular biologists.

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I thank Drs Li Gao, Peisong Gao, and Candelaria Vergara; Nicholas Rafaels; and Pat Oldewurtel for technical assistance and Mr Boyd Jacobson for his artistic contributions, as well as Drs Donald Leung and Stephan Weidinger for invaluable discussions and comments. A special thanks to Dr Lisa A. Beck, who shared critical preliminary data and contributed to important discussions. I also acknowledge the contributions of the Atopic Dermatitis Vaccinia Network (ADVN) in generating much of the data used in this review.

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Table E1. 

Genes associated with atopic dermatitis in at least one study

ADAM33, A disintegrin and metalloproteinase domain 33; BDNF, brain-derived neurotrophic factor; BFL1, BCL2-related protein A1; C3, complement component 3; CARD12, caspase recruitment domain–containing protein 12; CARD15, caspase recruitment domain–containing protein 15; CCR4, chemokine, CC motif receptor 4; CD14, monocyte differentiation antigen CD14; CMA1, chymase 1; COL29A1, collagen, type XXIX, α-1; CSF2, colony-stimulating factor 2; CSTA, cystatin A; CTLA4, cytotoxic T lymphocyte–associated 4; CYSLTR1, cysteinyl leukotriene receptor 1; DEFA4, defensin α 4; DEFA5, defensin α 5; DEFA6, defensin α 6; DEFB1, defensin β 1; EOTAXIN, chemokine, CC motif, ligand 11; FCER1B, Fc fragment of IgE, high affinity I, receptor for, β subunit; FLG, filaggrin; GATA3, GATA-binding protein 3; GPRA, neuropeptide S receptor 1; GSTP1, Glutathione S-transferase, PI; GSTT1, glutathione S-transferase, θ-1; HNMT, histamine N-methyltransferase; IFNG, Interferon γ; IL1B, IL-1 β; IL1RN, IL-1 receptor antagonist; IL4, IL-4; IL4RA, IL-4 receptor; IL5, IL-5; IL5R, IL-5 receptor α; IL6, IL-6; IL8, IL-8; IL8RA, IL-8 receptor α; IL8RB, IL-8 receptor β; IL10, IL-10; IL12B, IL-12 β; IL12RB1, IL-12 receptor β1; IL13, IL-13; IL13RA, IL-13 receptor α1; IL18, IL-18; IRAKM, IL-1 receptor–associated kinase 3; IRF2, IFN regulatory factor 2; KLK7, kallikrein-related peptidase 7; LMP2, large multifunctional protease 2; LMP7, large multifunctional protease 7; MCP1, monocyte chemotactic protein 1; MHC2TA, MHC class II transactivator; MIP1A, macrophage inflammatory protein 1-α; NALP1, Nacht domain–, leucine-rich repeat–, and PVD-containing protein 1; NALP3, Nacht domain–, leucine-rich repeat–, and pyd-containing protein 3; NALP12, Nacht domain–, leucine-rich repeat–, and pyd-containing protein 12; NAT2, arylamine-N-acetyltransferase 2; NGFB, nerve growth factor β; NPSR1, neuropeptide S receptor 1 gene; PDYN, prodynorphin; PHF11, PHD finger protein 11; RANTES, regulated on activation, normally T-expressed, and presumably secreted; SCCE, stratum corneum chymotryptic enzyme; SETDB2, SET domain protein, bifurcated, 2; SMPD2, sphingomyelinase 2; SOCS3, suppressor of cytokine signaling 3; SPINK5, Kazal-type serine protease inhibitor 5; ST2, suppressor of tumorigenicity 2; STAT6, signal transducer and activator of transcription 6; TAP1, transporter, ATP-binding cassette, major histocompatibility complex, 1; TAP2, transporter, ATP-binding cassette, MHC, 2; TARC, thymus and activation-regulated chemokine; TGFB1, TGF-β1; TIM1, timeless, Drosophila, homolog of; TIM3, T-cell immunoglobulin and mucin domains–containing protein 3; TIM4, T-cell immunoglobulin and mucin domains–containing protein 4; TNFA, TNF-α; TOLLIP, Toll-interacting protein; UTR, untranslated region; VEGF, vascular endothelial growth factor.

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