current understanding of human genetics and genetic analysis of psoriasis

doi: 10.1111/j.1346-8138.2012.01504.x Journal of Dermatology 2012; 39: 231–241

INVITED ARTICLE

Current understanding of human genetics and geneticanalysis of psoriasis

Akira OKA,1 Tomotaka MABUCHI,2 Akira OZAWA,2 Hidetoshi INOKO3

1The Institute of Medical Science, Tokai University, and Departments of 2Dermatology and 3Molecular Life Sciences, Division of Basic

Medical Science and Molecular Medicine, Tokai University School of Medicine, Isehara, Kanagawa, Japan

ABSTRACT

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During the past 5 years, genome-wide association studies (GWAS), primarily based on single nucleotide polymorphism

markers, have identified many loci as potential psoriasis susceptibility regions. These studies appeared to provide strong

evidence because the susceptibility genes are involved in the interleukin-23 ⁄ T-helper 17 axis of psoriasis immunopatho-

genesis and ⁄ or skin barrier functions. However, the ‘‘identified’’ genes only explained a small proportion of psoriasis heri-

tability, although it is known to be comparatively higher than that of other common diseases. GWAS are based on the

hypothesis that disease-causing variants are high frequency variants within populations. However, this hypothesis is

problematic because deleterious variants such as those predisposing to specific diseases will generally not be main-

tained by selection pressure throughout human evolution. This issue also affects psoriasis studies. Here, we review the

current paradigm shift in human genetic analyses and its implications for detection of psoriasis-causing variants based

on linkage analysis and GWAS, except the well-known psoriasis susceptibility locus HLA-C.

Key words: common disease–common variant, genome-wide association study, missing heritability, psoriasis,

rare variant.

INTRODUCTION

Psoriasis is a complex and multifactorial disease involving envi-

ronmental factors and has a high prevalence in those with Euro-

pean ancestry. Psoriasis displays a relatively high heritability, and

thus, genetic analysis via linkage and ⁄ or association studies have

been undertaken worldwide to explore its causative genes. Initial

genetic studies have demonstrated a strong association between

the HLA-Cw6 allele and psoriasis in various races, although the

HLA-C locus only explains part of the genetic predisposition to

psoriasis. Recently, genome-wide association studies (GWAS)

have been used to identify causative genes of psoriasis and

other common diseases. Probably, these genes were involved in

a predisposition to psoriasis because the susceptibility genes are

involved in the interleukin (IL)-23 ⁄ T-helper (Th)17 axis of psoriasis

immunopathogenesis and ⁄ or skin barrier functions. However,

these observations have never completely explained psoriasis

pathogenesis or directly contributed to medical diagnosis and

treatment for psoriasis. In this review, we analyze this problem

by investigating the implications of current human genetics for

disease and genetic analysis of psoriasis by linkage analysis and

GWAS, except the well-known psoriasis susceptibility locus

HLA-C.

orrespondence: Akira Oka, Ph.D., The Institute of Medical Science, To

ail: [email protected]

eceived 25 December 2011; accepted 28 December 2011.

2012 Japanese Dermatological Association

WHAT IS GWAS?

Researchers have recently begun to reassess the outcomes of

GWAS in relation to common diseases. A major issue in recent

GWAS is whether the implicated variants and ⁄ or genes actually pre-

dispose individuals to these diseases. However, the conclusions of

researchers are inconsistent. The initial hypothesis known as the

common disease–common variant (CDCV) hypothesis requires

understanding of the recent history of human genetics.

Linkage analysis traces the concordance between genotypes

and phenotypes in a disease pedigree and provides a powerful tool

for discovering causative genes, especially for Mendelian diseases,

even if a researcher does not have a complete dataset of human

genome sequences. A causative gene can be found for a Mendelian

disease because the concordance between genotypes and pheno-

types throughout disease transmission is not an estimation but

strong evidence in itself. In fact, causative genes have been discov-

ered using linkage analysis for many Mendelian diseases, such as

cystic fibrosis1 and Duchenne’s muscular dystrophy,2 and the total

number of diseases caused by known gene mutations is now over

2600.3 These diseases are rarely observed throughout the world

and only account for a minority of all human diseases. Researchers

have attempted to apply this method to common diseases, which

kai University, 143 Shimokasuya, Isehara, Kanagawa 259-1193, Japan.

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A. Oka et al.

could potentially elevate medical costs and burden the health ser-

vices in each country, but it has proved difficult to find the causative

genes for these diseases. There have been few successes with

human diseases. It is easy to explain this problem. Common dis-

eases that do not exhibit obvious Mendelian recessive or dominant

inheritance usually have complex traits that are related to environ-

mental factors, which are associated with locus heterogeneity and

low penetrance. Moreover, the risk of a locus contributing to the

onset of a common disease is generally much lower than with Men-

delian diseases. Thus, the statistical detection power for complex

diseases using linkage analysis is insufficient.

But was there a better method than linkage analysis for discover-

ing causative genes of complex diseases? During the mid-1990s,

the concept of whole-genome association studies was proposed

based on affected familial subjects and unaffected individuals in a

population. However, researchers had to wait for the completion of

human genome sequencing before pursuing such research. Associ-

ation studies were not new at that time because research of this

type was already conducted by using polymorphic markers in

human leukocyte antigen (HLA) genes and other genes of interest.

GWAS is simply an expanded version of these earlier studies. The

purpose of association studies was to find statistical differences in

allele frequencies between case and control individuals within the

same population. Even if a variant with the strongest disease asso-

ciation in GWAS did not predispose individuals to a disease, it was

predicted that a true causative variant would lie in a region that was

physically close to the associated variant. This ‘‘proxy’’ variant

would exhibit a different allele frequency, if there was linkage dis-

equilibrium (LD) between both loci. However, it was observed that

any conclusions obtained from such studies were only estimates

rather than evidence. Lander et al.4–6 argued that a disease suscep-

tibility allele would have a high frequency in a common disease,

based on results that were mainly obtained from analyses of Alzhei-

mer’s disease and simulations. This is known as the CDCV hypo-

thesis (minor allele frequency >0.01). Lander5 suggested that a

comprehensive catalog of variants in whole genomes could be cre-

ated if hundreds subjects were investigated by sequencing analysis

using the human genome sequence. Moreover, Risch and Merikan-

gas7 argued that future genetic analysis of complex diseases was

likely to require large-scale examination using association studies

and that many genetic effects that were too weak to be identified by

linkage would be detected using association studies to statistically

estimate their feasibility. The International HapMap Project was

established in the early 2000s to create a dataset of common

genetic variants found in humans.8 To date, the International Hap-

Map consortium has genotyped 1.6 million common single nucleo-

tide polymorphisms (SNP) in 1184 reference individuals from 11

global populations.9

OUTCOMES OF GWAS OF COMMONDISEASES

The New York Times published the following in an article in June

2010:10 ‘‘Ten years after President Bill Clinton announced that the

first draft of the human genome was complete, medicine has yet to

see any large part of the promised benefits […] Indeed, after

232

10 years of effort, geneticists are almost back to square one in

knowing where to look for the roots of common disease.’’ Many

researchers and other stakeholders had hoped that the use of

GWAS for discovery of causative alleles and genes would lead to

novel inventions for diagnosis, prevention and treatment of human

diseases. But why was this comment published? It is apparent that

most of this optimism was misplaced.

Hundreds of SNP were found to be associated with common

diseases by GWAS, but the median OR for modest effect sizes

was only 1.33.11 Moreover, 88% of these SNP were located in

intronic or intergenic regions.11 A large part of the genetic variance

(proportion of heritability) in each disease was not explained even

when the entire locus discovered by GWAS was assembled.12,13

Like psoriasis, Crohn’s disease is an autoimmune disease that has

also been investigated by GWAS, mainly in Caucasian populations

where many susceptibility loci were identified. However, an analysis

based on a liability threshold model using the 32 loci discovered by

GWAS demonstrated that only 13.43% of the total proportion of

heritability for Crohn’s disease could be explained.14–18 Similarly,

only 13.20% of the proportion was explained by the same analysis

of 23 susceptibility loci for systemic lupus erythematosus (SLE).14

GWAS of neuropsychiatric disorders has been even less successful

in explaining heritability. Although the heritability of attention deficit

hyperactivity disorder (ADHD) was high (76%),19 the variants dis-

covered by GWAS explained less than 1% of its genetic vari-

ance.20,21 Some researchers have referred to the undiscovered

variance as ‘‘missing heritability’’12 and have attempted to use

alternative methods to find disease-causing variants with a higher

effect size. Thus, the validity of the CDCV hypothesis is being

increasingly questioned.

A SERIOUS PROBLEM WITH GWAS

The CDCV hypothesis has a serious problem. Deleterious alleles

that contribute to diseases must be rapidly eliminated under evolu-

tionary pressure so as to preserve and expand human species.

Therefore, these deleterious alleles will not be maintained at a high

frequency in a population. Furthermore, if a common allele directly

influences the phenotype, the element surrounding the variant must

be essential for viability, indicating that the allele frequency must be

maintained by positive selection. Archeological evidence is gener-

ally considered to support the initial spread of humans throughout

Africa with an East African origin during the first half of the last

100 000 years, followed by their expansion from this point of origin

across the world approximately 50 000–60 000 years ago.22

Ancient alleles derived from this African source share most of the

alleles of common variants, including those currently used in

GWAS.23 Consequently, any deleterious alleles with high frequency

must have been supported by evolutionary forces for a long time.

This clearly suggests a discrepancy of some sort. However, Lander

et al.6,24 explained this discrepancy using simulations where mildly

deleterious alleles can emerge to have a moderate frequency, par-

ticularly in populations that have undergone a recent human expan-

sion. Klein et al.25 also suggested that the rapid acceleration of

human development in the recent evolutionary timeframe has

led to numerous environmental changes that increase the risk of

� 2012 Japanese Dermatological Association

Genetic analysis of psoriasis

complex common diseases. In contrast, Raychaudhuri simulated

de novo mutations propagating in a general population. Even if the

mutations had no impact on evolutionary fitness and did not influ-

ence the survival of individual organisms carrying the mutations,

none of the de novo mutations achieved an allele frequency of

more than 1% within 200 generations, and over half of the de novomutations were eliminated from the population after only two

generations.26

EXCEPTIONAL CONDITIONS THAT ALLOWCOMMON VARIANTS TO CAUSE COMMONDISEASES

Common variants with large effect sizes have been detected by

association studies, although these cases represent a minority of all

studies. These cases have the following patterns:

1 Late-onset disease: exfoliation glaucoma is the second most

common cause of blindness worldwide and is a late-onset dis-

ease. GWAS demonstrated that the OR of a common variant

associated with this disease was 20.1.27 Alzheimer’s disease,

which was used by Lander et al.4–6 as the basis for the CDCV

hypothesis, is also a late-onset disease. Clearly, it is reasonable

that a common variant can be a causal variant of late-onset dis-

eases because such diseases do not negatively influence repro-

ductive fitness.28

2 Balancing selection: under balancing selection a gene shows

more variation than expected, because an individual with two

different versions of it – heterozygotes – have an advantage

over those who carry two copies of the same allele.29 In human

evolution, a number of alleles that are pathogenic in the homozy-

gous state can confer significant selective advantages in the

heterozygous state.30 For example, glucose-6-phosphate dehy-

drogenase (G6PD) deficiency is the most common enzymopathy

in humans and the most common deficiency allele in Africa

(G6PD A)), where it has been shown to confer some resistance

to malaria.31

3 Normal traits: common variants may understandably influence

normal traits in organisms. GWAS of hair, skin and eye color,

which are highly heritable and visible traits in humans, demon-

strated that a common variant in OCA2 was strongly associated

with eye color (OR = 35.42) and the variant was under the influ-

ence of positive selection.32

4 Pharmacogenomics: the antimicrobial agent flucloxacillin is a

common cause of drug-induced liver injury (DILI), which is an

important cause of serious liver disease.33 GWAS of cases and a

separate drug-exposed control group indicated that HLA-B*5701had a highly significant association with DILI, where possession

of this allele was associated with an 80-fold increase in the risk of

developing the disease (OR = 80.6).33 The allele frequency must

be maintained because humans have never been exposed chron-

ically to flucloxacillin throughout their evolution and HLA genes

are influenced by balancing selection.34

5 Modifier: b-thalassemia and sickle cell disease are defined as

simple Mendelian diseases, but a common variant in BCL11Awas discovered by GWAS rather than linkage analysis, and it was

found to contribute to both diseases as a modifier.35–37


These examples clearly show how common variants can influ-

ence phenotypes and be maintained, but they are exceptional

cases in GWAS. Even under neutral evolution, in the absence of

natural selection, polymorphisms will eventually vanish, as allele

frequencies slowly fluctuate because of genetic drift until one allele

becomes fixed.30 Goldstein also suggested that the apparently

modest effect of common variation on most human diseases and

related traits probably reflects the efficiency of natural selection in

prohibiting increases in disease-associated variants in the popu-

lation.38 Most GWAS results have shown that deleterious alleles

are not maintained as common variants during human evolution.

Thus, even if a common allele is associated with a disease and is

truly the causative variant, the effect sizes are too small to reveal

the role of genetic functionality in disease pathogenesis, thereby

excluding any applications in diagnosis, prevention and treatment.

Moreover, the majority of variants detected by GWAS have no

demonstrable biological significance.24 Thus, it is obvious that

GWAS based on the CDCV hypothesis cannot be applied to all

common diseases.

A PARADIGM SHIFT IN HUMAN GENETICS

At the time the CDCV hypothesis was proposed39 by other

researchers, Pritchard suggested that multiple and recent rare vari-

ants could both contribute to common diseases. Pritchard referred

to studies on Crohn’s disease as examples of rare variants that influ-

ence a disease, in which rare frame-shift and missense variants in

NOD2 were found to be associated with this disease that displayed

high effect sizes.40,41 Goldstein et al.42 argued that much of the

genetic control of common diseases is due to rare and generally

deleterious variants that have a strong influence on the risk of dis-

ease in individual patients. Rare variants are typically more recent

and may yet be subjected to negative selection pressure, which

means they could include some relatively deleterious mutations.26

Some researchers have pursued rare variants in common diseases

and accumulated empirical evidence based on a common disease–

rare variant (minor allele frequency <0.01) hypothesis. However, it is

difficult to explore rare variants for each individual in a whole gen-

ome. However, new sequencing technology and the CDCV hypothe-

sis shed light on research regarding common diseases in human

genetics. Next-generation sequencing (NGS) rapidly produces huge

amounts of sequence data, allowing human genetic researchers to

analyze a personal genome.43 Moreover, the targeted sequencing of

all protein-coding regions (‘‘exomes’’) using NGS could reduce

costs, while increasing the rate of discovery of highly penetrant vari-

ants.44 The first report of exome sequencing in a Mendelian disease

suggested that this strategy could be extended to diseases with

more complex genetics by using larger sample sizes and appropri-

ate weighting of non-synonymous variants based on their predicted

functional effect.44 For common neuropsychiatric diseases, several

studies using exome sequencing and a few family subjects or unre-

lated subjects with schizophrenia,45,46 autism,47 epilepsy,48 cogni-

tive disorder49 and mental retardation50 revealed that rare variants of

de novo mutations including insertion ⁄ deletion polymorphisms with

missense and frame-shift mutations showed a large effect size in

each disease. Furthermore, rare de novo copy number variations

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A. Oka et al.

(CNV) with high penetrance were found in schizophrenia,51–56 aut-

ism,57,58 epilepsy59–61 and ADHD62 using array comparative geno-

mic hybridization and ⁄ or genome-wide SNP genotyping. In addition

to these neuropsychiatric diseases and Crohn’s disease, there have

only been a few reports of rare variants linked with a predisposition

to common diseases. Hypertension is another highly prevalent dis-

ease where GWAS have found many associated variants that have

small effect sizes.18,63–66 However, multiple rare variants that con-

tribute to blood pressure were discovered using a candidate gene

approach by re-sequencing, which demonstrated that many rare

alleles influenced renal salt handling during blood pressure variation

and that alleles with health benefits were nonetheless under negative

selection.67 Rare variants predisposing to pathogenesis of common

diseases have been reported for type 1 diabetes,68 low plasma high-

density lipoprotein cholesterol levels,69 hypertriglyceridemia70 and

severe early-onset obesity.71 These successful studies are not rare

cases. The recent and rapid expansion of human populations

has resulted in the presence of many rare variants, and rare variants

are often more evident when they are more likely to have dramatic

functional consequences.26

Based on available results, it is obvious that rare variants are

more highly penetrant for most common diseases than common

variants. Lander et al.6,24 suggested that mildly deleterious alleles

can have a moderate frequency, particularly in populations that

have undergone recent expansion. However, there is no available

evidence to support this assumption.

SYNTHETIC ASSOCIATIONS

What are the implications of the common variants detected by

GWAS in terms of the CDCV hypothesis? A new interpretation of

the results of GWAS is suggested. Variants much less common than

the associated one may create ‘‘synthetic associations’’ by occur-

ring, stochastically, more often in association with one of the alleles

at the common site versus the other allele.72 In other words, it is pre-

sumed that rare causative variants with high effect size lie on a chro-

mosome of which chromosomes were identified as a chromosome

with low effect size in GWAS. Thus, rare variants can easily lead to

genome-wide significant associations attributed to more common

variants, given the sample sizes being considered.42,72–74 Moreover,

the causal variants may be megabases away from the common

variants that provide a signal of the association and can show the

several-fold stronger real risk effects than what is credited to a com-

mon variant.42 Because rare causal variants arose recently, they

often exist on long-range haplotypes spanning multiple blocks of

high LD (as observed in control populations), which recombination

has not yet had a chance to further fragment. Several lines of evi-

dences that support this hypothesis have already been recog-

nized,42,74 although some researchers have suggested that

synthetic associations are unlikely to account for many common

disease GWAS signals,75,76 In contrast, Goldstein proposed the

synthetic association hypothesis and argued that the proportion of

GWAS signals that are synthetic in origin depends on the genetic

architecture of human traits, and this architecture remains largely

unknown. Hence, it is uncertain how many GWAS signals may be

due to synthetic associations.42,73 This is currently a limitation of

234

human genetics. Goldstein observed that ‘‘time will tell’’ in the reso-

lution of this issue.73

EPIDEMIOLOGY OF PSORIASIS

Psoriasis is one of the most common human skin diseases. It is

characterized by excessive growth and aberrant differentiation of

keratinocytes, but it can be completely reversed with appropriate

treatment.77 The abnormal production of inflammatory mediators is

believed to play an important role in psoriasis pathogenesis. Emerg-

ing data from mice and human studies has highlighted a new subset

of Th cells that are partially characterized by their production of

IL-17, leading to them being known as Th17 cells.78 Considerable

overlap is apparent between the molecular pathways involved in

psoriasis and those leading to other inflammatory or autoimmune

diseases such as Crohn’s disease, SLE, rheumatoid arthritis and

Behcet’s disease.79 The clinical manifestations collectively known

as psoriasis are a result of complex interactions between different

cell types and molecules with multiple environmental triggers such

as physical trauma, drugs, infection and stress.80 The familial nature

of this disease, which affects almost 2–3% of Caucasians, has

long been recognized.81 However, a lower incidence82 has been

observed in the Japanese population where most psoriasis cases

are sporadic. Psoriasis patients are found in most countries

throughout the world, although it is extremely rare or absent in

Aborigines, pre-Colombians, Andean Indians, Amerindians in the

remote villages of the Amazon–Orinoco forest, Alaskans, Canadi-

ans, and Native Americans of the USA.83 The concordance of psori-

asis in monozygotic twins is 35–72%, while it is 12–30% in dizygotic

twins.84,85 Psoriasis heritability has been estimated at 60–90%,

which is among the highest of all multifactorial genetic diseases.86

For example, twin studies in other diseases have indicated that heri-

tability is 30–50% for hypertension,87 50% for Crohn’s disease88

and 40–60% for rheumatoid arthritis.89 Psoriasis in concordant

monozygotic twin pairs appears to be similar with respect to age

onset, distribution pattern, severity and course, whereas this pattern

was not found in concordant dizygotic twin pairs.90 The age of

psoriasis onset shows a bimodal distribution with one peak at

20–30 years and another at 50–60 years.91 Moreover, the HLA-Cw*0602 allele is strongly associated with the early-onset type of

psoriasis in various races.92–97 In addition to having a lower age of

onset, HLA-Cw*0602-positive patients present more severe clinical

symptoms.98 Thus, psoriasis has complex multifactorial features,

genetic heterogeneity, high heritability, a broad range of onset age

and different prevalence in various populations, suggesting that

psoriasis is comparatively similar to other common diseases. With

the exception of HLA, there is no reason why deleterious variants

predisposing to psoriasis should endure any selection pressures.

Taking recent human genetics into consideration, it is unlikely that

deleterious common variants for psoriasis, other than for HLA, exist

in the human genome.

LINKAGE ANALYSIS OF PSORIASIS

Although linkage analysis has been used for investigation of causa-

tive genes of psoriasis, no causative genes that predisposed to


Table 1. Susceptibility locations detected by linkage analysis in pso-riasis family

Location

HGNC*

approvedgene symbol

Candidategene Reference

1q21 PSORS4 LCE3B andLCE3C

110,111

1p PSORS7 128

3q21 PSORS5 SLC12A8 113,1144q PSORS3 129

4q31-q34 PSORS9 130

6p21.33 PSORS1 HLA-C 102,103,109,113,

126,128,130,13116q PSORS8 103,131

17q25 PSORS2 SLC9A3R1and RAPTOR

99,102–104,131

18p11.23 PSORS10 13219p13 PSORS6 TYK2? 126

*HUGO Gene Nomenclature Committee.


psoriasis with a large effect were revealed apart from HLA-C. Ten

loci have been identified as psoriasis susceptibility regions by link-

age analysis (Table 1). Fine mapping has been performed in four of

these regions. We review the following three loci identified as psori-

asis susceptibility regions by previous linkage studies.

17q25A psoriasis susceptibility region was localized to the distal region of

the human chromosome 17q as a result of the first genome-wide

linkage analysis using polymorphic microsatellites in eight multi-

affected psoriasis families with Caucasian ancestry.99 There was

also evidence of genetic heterogeneity, and although none of the

related families showed any association with HLA-Cw6, two unre-

lated families showed weak association levels. Nevertheless,

D17S784 showed strong evidence for linkage,99 although two other

linkage studies did not confirm this linkage.100,101 On the other

hand, two independent studies provided evidence for linkage in the

same region of 17q.102,103 To further refine this location, the group

that first found this linkage focused on chromosome 17q23–25

(physical distance = 11.5 Mb) surrounding the D17S784 locus and

they conducted non-parametric genetic linkage analysis and asso-

ciation studies using microsatellites and SNP.104 As a result, a

microsatellite (D17S1301) with linkage and two SNP haplotypes

associated with psoriasis were observed in a segment located

512 kb away from D17S784.104 The same group then conducted a

family-based association study and found two loci associated with

psoriasis where the regions were separated by 6 Mb.105 One locus

was an SNP (rs734232) located 84.7 kb distal to D17S1301, which

was identified as a putative binding site for the runt-related tran-

scription factor RUNX1 and a causal variant influencing SLC9A3R1expression, whereas the other peak was in the third intron of

RAPTOR located 852 kb distal to D17S784.106,107 The frequency of

risk allele in rs734232 was 48% compared with 42% in the

controls,105 indicating that the proportion of heritability of this

locus would be very low, even if this locus was truly linked with a


predisposition to psoriasis. However, other studies have indicated a

lack of evidence for a genetic association with the RUNX1-binding

site and RAPTOR,107,108 while all recent GWAS have failed to repli-

cate these associations with psoriasis. A consistent result that

explained a relationship between SLC9A3R1 expression and the

‘‘risk’’ allele was provided by electrophoretic mobility supershift and

luciferase assays.105 It was unlikely that this observation explained a

skin abnormality such as psoriasis because the frequency of the risk

allele was high in control subjects. However, this locus has been

supported in independent families and studies, although there are

several cases of negative data. The concepts of genetic linkage in

families and a genetic association between cases and controls are

entirely different. Linkage analysis is effective for finding a causative

gene under allelic heterogeneity and is not effective under locus het-

erogeneity; however, association study is the opposite. If this link-

age is real and multiple rare variants that predispose to psoriasis are

found in this region, some discrepancies in these genetic data might

be disclosed because multiple rare variants would emerge due to

allelic heterogeneity.

1q21Chromosome 1q21 was mapped as a psoriasis-susceptibility locus

by linkage analysis109 and subsequent fine mapping in an associa-

tion study110 conducted by the same group. An associated haplo-

type was detected using microsatellites in the association study,

which segregated in only one of the 22 psoriasis families where link-

age to the 1q21 region was originally demonstrated.109,110 This indi-

cated that the causative allele frequency in this region should be

relatively low in populations. In fact, the haplotype was found at an

increased frequency among disease chromosomes compared with

that in control chromosomes (6.9% vs 1.9%).110 This region was

subsequently supported by GWAS using SNP117 and a genome-

wide search for CNV,111 but we cannot understand in detail whether

these associations might explain the findings of previous linkage

analysis and association studies of psoriasis. However, we can at

least speculate regarding this issue. The researchers who analyzed

CNV concluded that a susceptibility variant of psoriasis was a dele-

tion of the late cornified envelope LCE3B and LCE3C genes.111 Fre-

quencies of the ‘‘risk’’ deletion in European cases and controls

were 69.6% and 64.2% (OR = 1.21), respectively.112 The physical

distance between the haplotype associated with psoriasis in a previ-

ous fine mapping109,110 and LCE3B discovered by GWAS was

583 kb. If this deletion actually predisposes to psoriasis, these

results in the linkage analysis and the association studies must be

independent. The chromosome harboring the risk deletion allele

could not maintain a long-range LD to the linkage region for long if

genetic events such as recombination occur normally. This com-

mon deletion allele emerged in a very old chromosome; hence,

the region surrounding the deletion site must have had frequent

opportunities for recombination in every generation. In contrast, the

rare haplotype detected by linkage analysis and subsequent fine

mapping may have emerged recently and contain a relatively

longer haplotype. Thus, if both results are true, the CNV associa-

tion observed by GWAS may have attributed to the rare causative

variants in the same region based on synthetic associations.

LCE expression is upregulated in psoriatic and normal skin that is

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A. Oka et al.

stimulated by tape stripping, while it is not detected in uninvolved

psoriatic and normal skin. Thus, the expression of this gene can be

induced in the normal epidermis by disruption of the skin barrier.111

A significant correlation was found between normalized LCE3Cexpression and copy number.111 However, the conclusion that this

deletion is a deleterious variant in the epidermis cannot explain why

42% of healthy individuals of European ancestry112 who do not

express these genes will not be psoriasis patients. Interactions with

the other proteins may explain this discrepancy, but this deletion

cannot be a major psoriasis-predisposing event.

3q21A linkage analysis in Swedish families identified chromosome 3q21

as a psoriasis susceptibility locus.113 Subsequent fine mapping by

the same group isolated the locus to a 250-kb interval mainly by

using SNP markers and suggested SLC12A8 as a plausible candi-

date gene.114,115 However, genetic evidence was not strong and it

has not been replicated by other studies including recent GWAS.

We suggest that results of previous linkage analysis must also be

reconsidered because GWAS cannot detect causative variants with

large effects, while linkage analysis is inadequate for common dis-

eases such as psoriasis. Family subjects with psoriasis investigated

by some researchers are important and they will be informative for

future sequence-based genotyping.

WHAT HAVE GWAS OF PSORIASIS TOLD US?

In the past 5 years, 10 GWAS of psoriasis based on the CDCV

hypothesis have been published, indicating that 24 loci have

associations with psoriasis (Table 2).116 These GWAS identified

many genes involved with skin barrier functions (LCE3E and

LCE3C),15,111,117 IL-23 signaling (IL23A, IL23R and IL12B),117–122

nuclear factor-jB and interferon signaling (NFKBIA, REL, TYK2,

IFIH1, IL28RA, TNIP1 and TNFAIP3)118,121,123 and IL-17 cell

responses (TRAF3IP2, TYK2 and IL23R),118,120–122 in addition to

HLA-C as psoriasis susceptibility genes. In general, these results

appeared to indicate the IL-23 ⁄ Th17 axis in psoriasis immunopatho-

genesis. However, what does ‘‘identify’’ mean in these studies?

Most variants associated with psoriasis are located in intergenic or

intronic regions. Thus, GWAS have not identified psoriasis suscepti-

bility genes and merely identified variants that were statistically

associated with psoriasis. These genes are involved in IL-23 ⁄ Th17

pathway and are physically close to variants associated with psoria-

sis, which cannot prove that they predispose to psoriasis. Further-

more, few studies have completely explained the relationship

between genetic data in GWAS and gene expression.

Were there any important findings in GWAS of psoriasis? King

et al. argued that most of the signals with small size effects

(OR < 1.5) detected in GWAS are false positive, regardless of the

P-value associated with them.28,124 In a risk allele which demon-

strated an OR of over 1.5 and lay in a coding region of a functional

gene (excluding HLA-Cw*0602), the only SNP was rs33980500 in

TRAF3IP2 which encoded ACT1, a signaling adaptor involved in the

regulation of adaptive immunity (Table 2).122,124 These studies of

European populations also indicated that the association with

‘‘psoriatic arthritis’’ was stronger than ‘‘psoriasis vulgaris’’.120,122

236

This SNP is a missense variant that causes a mutation from aspartic

acid to asparagine in the protein sequence, resulting in a change in

charge (a negative electric charge to nonpolar).120 It is interesting

that the variant is located in a region that is more than 90% con-

served among different species, which further indicates a possible

functional consequence of this change.120 In fact, functional assays

have clearly shown that a protein derived from a transcript harboring

the risk allele could reduce the efficiency of the interaction with

tumor necrosis factor receptor-associated factor 6.124 These results

are strong evidence, but may explain only a small proportion of heri-

tability. In contrast, it seems unlikely that the other ‘‘associated’’

variants were causative and they predispose to psoriasis. Even if

the variants associated with psoriasis were due to synthetic associ-

ations from multiple rare variants, we could not evaluate whether

synthetic associations are expected in most psoriasis GWAS with-

out additional evidence such as linkage analysis.

Linkage analysis in German families identified chromosome

19p13 as a psoriasis susceptibility locus.125 This region harbored

the TYK2 locus discovered in a GWAS with European ancestry.110

However, we could not evaluate whether the concordance between

both studies was due to any genetic factor because the linkage

study left a vast region (>20 Mb).

Where is the ‘‘missing heritability’’ in GWAS of psoriasis? Chen

et al.126 estimated the genetic variance using a liability threshold

model for 10 selected loci from GWAS of psoriasis, indicating that

these loci could explain only 11.6% of the proportion. The locus with

the largest genetic variance, other than the well-known susceptibility

locus HLA-C, was IL12B (rs3213094), and this locus could explain

1.27% of the genetic variance in psoriasis.126 Despite spending vast

amounts of funds and collecting huge numbers of subjects, recent

GWAS of psoriasis have a very large amount of missing heritability,

as is found with other GWAS of other common diseases. Most of

the 10 published GWAS of psoriasis indicated that functional study,

fine mapping and additional association studies are needed to con-

firm these results, and they leave the identification of causal variants

for future studies. Thus, important and informative results have not

been reported and they fail to address this fundamental issue of

missing heritability. Some researchers indicate that elevating the

OR by interactions between variants associated with psoriasis could

account for missing heritability. Two studies suggested that the risk

allele of rs27524 was found in an intron of ERAP1, and the risk

deletion of LCE3D statistically interacted with HLA-C, respec-

tively.111,121 However, it was unlikely that the evidence was strong

or that the interactions would be supported by biological and exper-

imental data. In general, interactions are theoretically possible but

there are few clear examples of common variants identified in

GWAS that interact strongly with each other or the environment to

affect a complex trait.42 Thus, even if we conduct more GWAS with

larger sample sizes to capture all the remaining unidentified variants

influencing psoriasis, numerous variants would be required to

explain missing heritability.38

FUTURE OF PSORIASIS GENETICS

Common diseases are often complex because they are genetically

heterogeneous, where many different genetic defects can result in


Tab

le2.

Susc

eptib

ility

locatio

ns

dete

cte

dby

genom

e-w

ide

ass

ocia

tion

studie

sin

pso

riasi

s

Lo

catio

n

Overlap

reg

ion

dete

cte

db

y

linkag

eanaly

sis

Rep

ort

ed

gene(s

)

Str

ong

est

SN

P

risk

alle

leC

onte

xt

Ris

kalle

le

freq

uency

inco

ntr

ol

OR

95%

CI

P-v

alu

eA

ncestr

yR

efe

rence

1p

36.1

1IL

28R

Ars

4649203-A

Inte

rgenic

0.7

30

1.1

31.0

5–1.2

27.0

E-0

8E

uro

pean

121

1p

31.3

IL23

Rrs

11209026-?

Mis

sense

NR

1.4

91.2

7–1.7

47.0

E-0

7E

uro

pean

121

1p

31.3

IL23

Rrs

2201841-G

Intr

on

0.3

00

1.1

3N

R3.0

E-0

8E

uro

pean

118

1q

21.3

PS

OR

S4

LCE

3B,

LCE

3Crs

4112788-C

Inte

rgenic

0.4

40

1.4

11.2

5–1.5

86.5

E–09

Euro

pean

111

1q

21.3

PS

OR

S4

LCE

3Drs

4112788-?

Inte

rgenic

NR

1.2

91.1

9–1.4

03.0

E-1

0E

uro

pean

121

1q

21.3

PS

OR

S4

LCE

3D,

LCE

3Ars

4085613-A

Inte

rgenic

0.4

30

1.3

21.2

5–1.3

97.0

E-3

0C

hin

ese

117

2p

16.1

RE

Lrs

702873-G

Inte

rgenic

0.5

60

1.1

21.0

4–1.2

04.0

E-0

9E

uro

pean

121

2p

16.1

NR

rs842636-G

Inte

rgenic

0.5

60

1.1

5N

R6.0

E-0

6E

uro

pean

123

2q

24.2

IFIH

1rs

17716942-A

Intr

on

0.8

60

1.2

91.1

7–1.4

31.0

E-1

3E

uro

pean

121

3p

24.3

Inte

rgen

icrs

6809854-G

Inte

rgenic

0.1

90

1.1

41.0

4–1.2

61.0

E-0

7E

uro

pean

121

5q

15

ER

AP

1rs

27524-A

Intr

on

0.3

60

1.1

31.0

5–1.2

23.0

E-1

1E

uro

pean

121

5q

33.3

IL12

Brs

3212227-C

UT

R0.5

17

0.6

40.5

6–0.9

07.9

E-1

0E

uro

pean

119

5q

33.3

IL12

Brs

2546890-A

Inte

rgenic

0.5

60

1.5

41.3

2–1.7

9(P

anelA

)1.0

E-2

0E

uro

pean

120

5q

33.3

IL12

Brs

12188300-T

Inte

rgenic

0.0

80

1.7

01.5

0–1.9

37.0

E-1

7E

uro

pean

122

5q

33.3

IL12

Brs

3213094-?

Intr

on

NR

1.3

91.2

6–1.5

35.0

E-1

1E

uro

pean

121

5q

33.3

IL12

Brs

2082412-G

Inte

rgenic

0.8

00

1.4

4N

R2.0

E-2

8E

uro

pean

118

5q

33.3

IL12

Brs

3213094-A

Intr

on

0.4

50

1.2

81.2

3–1.3

53.0

E-2

6C

hin

ese

117

5q

33.1

TNIP

1rs

17728338-A

Inte

rgenic

0.0

54

1.5

9N

R1.0

E-2

0E

uro

pean

118

5q

31.1

IL13

rs20541-G

Mis

sense

0.7

90

1.2

7N

R5.0

E-1

5E

uro

pean

118

6p

21.3

3P

SO

RS

1H

LA-C

rs1265181-?

Inte

rgenic

NR

22.6

NR

1.9

E-2

08

Chin

ese

117

6p

21.3

3P

SO

RS

1H

LA-C

rs12191877-?

Inte

rgenic

NR

2.7

92.3

5–3.3

3

(PanelA

)

4.0

E-3

2E

uro

pean

120

6p

21.3

3P

SO

RS

1H

LA-C

rs13191343-T

nearG

ene-5

0.1

30

2.3

72.1

6–2.6

12.0

E-7

2E

uro

pean

122

6p

21.3

3P

SO

RS

1H

LA-C

rs10484554-?

Inte

rgenic

NR

4.6

64.2

3–5.1

34.0

E-2

14

Euro

pean

121

6p

21.3

3P

SO

RS

1H

LA-C

rs12191877-T

Inte

rgenic

0.1

50

2.6

4N

R1.0

E-1

00

Euro

pean

118

6p

21.3

3P

SO

RS

1H

LA-C

rs2395029-C

Mis

sense

0.0

30

4.1

03.1

0–5.3

02.0

E-2

6E

uro

pean

133

6p

21.3

3P

SO

RS

1H

LA-C

rs10484554-T

Inte

rgenic

0.1

50

2.8

02.4

0–3.3

02.0

E-3

9E

uro

pean

133

6p

21.3

3P

SO

RS

1H

LA-C

rs3134792-?

Inte

rgenic

NR

NR

NR

1.0

E-0

9E

uro

pean

134

6q

23.3

TNFA

IP3

rs610604-?

Intr

on

NR

1.2

21.1

3–1.3

27.0

E-0

7E

uro

pean

121

6q

23.3

TNFA

IP3

rs610604-G

Intr

on

0.3

20

1.1

9N

R9.0

E-1

2E

uro

pean

118

6q

21*

TRA

F3IP

2rs

33980500-T

Mis

sense

0.0

80

1.5

71.3

8–1.7

81.0

E-1

6E

uro

pean

120

6q

21*

TRA

F3IP

2rs

33980500-T

Mis

sense

0.0

70

1.9

51.6

9–2.2

41.0

E-2

0E

uro

pean

122

6q

21

TRA

F3IP

2rs

240993-A

Intr

on

0.2

50

1.2

51.1

6–1.3

45.0

E-2

0E

uro

pean

121

9q

34.1

3TS

C1

rs1076160-T

Intr

on

0.4

80

1.0

9N

R6.0

E-0

6E

uro

pean

118

12q

13.3

IL23

Ars

2066808-?

Intr

on

NR

1.4

91.2

8–1.7

32.0

E-0

7E

uro

pean

121

12q

13.3

IL23

A,

STA

T2rs

2066808-A

Intr

on

0.9

30

1.3

4N

R1.0

E-0

9E

uro

pean

118

12q

13.2

RP

S26

rs12580100-A

Inte

rgenic

0.9

00

1.1

7N

R1.0

E-0

6E

uro

pean

123

13q

14.1

1C

OG

6rs

7993214-?

Intr

on

0.6

50

1.4

11.2

2–1.6

12.0

E-0

6E

uro

pean

133

� 2012 Japanese Dermatological Association 237


Tab

le2.

(Con

tinue

d)

Lo

catio

n

Overlap

reg

ion

dete

cte

db

y

linkag

eanaly

sis

Rep

ort

ed

gene(s

)

Str

ong

est

SN

P

risk

alle

leC

onte

xt

Ris

kalle

lefr

eq

uency

inco

ntr

ol

OR

95%

CI

P-v

alu

eA

ncestr

yR

efe

rence

14q

13.2

NFK

BIA

rs8016947-C

Inte

rgenic

0.5

70

1.1

91.1

1–1.2

72.0

E-1

1E

uro

pean

121

14q

13.2

NFK

BIA

,P

SM

A6

rs12586317-T

Intr

on

0.7

50

1.1

5N

R2.0

E-0

8E

uro

pean

123

16p

11.2

FBX

L19,

PO

L3S

rs10782001-G

Intr

on

0.3

70

1.1

6N

R9.0

E-1

0E

uro

pean

123

17p

11.2

NR

rs1975974-G

Inte

rgenic

0.2

30

1.1

7N

R1.0

E-0

7E

uro

pean

123

17q

11.2

NO

S2

rs4795067-G

Intr

on

0.3

50

1.1

9N

R4.0

E-1

1E

uro

pean

123

19p

13.2

PS

OR

S6

TYK

2rs

12720356-A

Mis

sense

0.9

00

1.4

01.2

3–1.6

14.0

E-1

1E

uro

pean

121

20q

13.1

3R

NF1

14,S

PA

TA2,

SLC

9A8,

SN

AI1

rs495337-G

cd

s-s

yno

n0.5

70

1.2

1N

R2.0

E-0

7E

uro

pean

123

20q

13.1

3S

PA

TA2

rs495337-?

cd

s-s

yno

nN

R1.2

51.1

2–1.3

91.0

E-0

8E

uro

pean

134

20q

13.1

2S

DC

4rs

1008953-C

Inte

rgenic

0.7

90

1.1

4N

R1.0

E-0

7E

uro

pean

123

*Pso

riatic

art

hritis

str

atified

analy

sis

.C

I,co

nfid

ence

inte

rval;

NR

,no

tre

po

rted

;O

R,

od

ds

ratio

,S

NP

,sin

gle

nucle

otid

ep

oly

mo

rphis

ms;

UT

R,

untr

ansla

ted

reg

ion.

238

A. Oka et al.

clinically indistinguishable phenotypes.49 Thus, even if the disease

in every affected individual emerges from a different specific cause,

each will nonetheless share the disruption of related key biological

processes.28 Studies of common diseases in populations may not

be appropriate for finding disease causative variants with large

effect sizes. The genetic heterogeneity of populations and their bio-

logy may be more complex than our expectations. We usually prefer

to consider a hypothesis that simplifies the results of a study. The

estimated total number of human genes in the human genome data-

base was 26 473 on 7 September 2011.127 However, many scien-

tists estimated that the number would be vastly more before human

genome sequencing is complete. A large part of the human pheno-

type cannot be explained using simple hypotheses, such as the

‘‘central dogma’’. Therefore, identifying disease susceptibility genes

one by one based on a conventional method and hypothesis may

not lead to a complete understanding of the pathogenesis of each

common disease.

None of the available methods or theories of human genetics can

comprehensively reveal the genetic factors underlying the patho-

genesis of common diseases. However, future studies of psoriasis

can only try to find rare variants that predispose to psoriasis and

that have large effect sizes, using sequencing-based genotyping by

NGS of familial subjects and ⁄ or sporadic subjects that are carefully

screened based on strict criteria. Thus, we may need to re-evaluate

the global epidemiology and the features of psoriasis in detail and

construct a novel hypothesis for disclosing the genetic architecture

of psoriasis by carefully selecting the optimal methods and without

blindly applying new technology.

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