Conclusiones específicas de cada estudio

5.2.1.1. Genetics of CRS

The study of DNA via the Human Genome Project in the late 1990s was supposed to revolutionise medicine genes, allowing new understandings of implicated mechanisms and identifying new drug targets, with future treatments based on personalised genetic makeup⁽⁹⁸⁾. However, despite the considerable advances in technology and radical cost reductions of genotyping, early experience with use of association genetics was disappointing.

Monogenic gene disorders, where transmission of variation(s) in the makeup of a single gene produce disease via well-described mechanisms (such as the Cystic Fibrosis Transmembrane Con-ductance Regulator (CFTR) gene responsible for cystic fibrosis), were almost never found. Instead, for complex traits (such as height, intelligence, creativity), and traits for complex diseases (such as schizophrenia, diabetes and asthma) were found to be associated with a dizzying number of variations in wide variety of genes, all offering minor contributions to the observed

phe-notype⁽⁹⁹⁾. Indeed, for schizophrenia, a well described disease entity with distinctive symptoms, was found to be associated with variations in almost one hundred different genes⁽¹⁰⁰⁾. Compounding this difficulty was the genes identified are often at first glance difficult to integrate into mechanistic models – for example, one of the main associations in schizophrenia was with a gene coding for C4, an element of the complement

casca-de⁽¹⁰¹⁾. Additionally, identified genetic factors may not so much

modify the structure of an organ or a cellular organelle, but may instead increase susceptibility to an environmental influence, such as infection or colonisation with undesirable bacteria⁽¹⁰²⁾. It may then be the bacterial presence that contributes to persis-tence or maintenance of disease. While this complicates the direct transposition of genetic results to the clinic, the field of genomics is again progressing, and mathematical approa-ches being developed to make predictions based on multiple variations, rather than relying on a single one. A glimpse into the future is afforded by a recent commercial venture which analy-ses combinations of SNPSs from the DNA of fertilised embryos to predict the fittest ones for implantation in vitro fertilisation (https://genomicprediction.com). This nevertheless may be of limited usefulness, as a simulation exercise using real GWAS data from large families showed that simulated embryos selected to be the smartest and tallest were only around 2.5 IQ points and 2.5 centimetres above average. Screening human embryos for polygenic traits has limited utility⁽¹⁰³⁾.

CRS is nevertheless benefitting from the ‘genetics revolution’. For example, in studies from the group of Desrosiers identification of candidate genes associated with epithelial and basement membrane structure and function led to exploration of barrier function in epithelial cells from CRS patients. This culminated in the recent identification of a defect in tissue repair in CRS⁽¹⁰⁴⁾, opening up the possibility of new drug treatments, confirming that there is value in the genetics arena. Other insights still wai-ting to bear fruit may become clearer as we better understand the role and functions of identified putative candidate genes.

5.2.1.2. Genetics: an overview

The term ‘genetics’ encompasses transmissible gene variations causing or predisposing to development of disease or pheno-type in question. Transmissible variations in gene function may also be induced by exposure to outside agents in a process ter-med epigenetic regulation, or epigenetics. In a newer challenge, previously ignored short sequences of the genome called ‘mi-croRNAs’ have been found to play important roles in regulation of gene function, and transmission of de-novo genetic material via bacterial viruses termed ‘bacteriophages’ may also modulate genetic makeup.

The identification of a genetic basis to a disease may be dif-ficult. Sinus physiology is a complex system, with multiple steps involved in even a single process such as pathogen recognition

comparisons between two or more groups, usually separated according to the element under study. Markers of genetic variation (‘microsatellites’ or single nucleotide polymorphisms (SNP)), single genes or multiple genes of a pathway are compa-red to identify differences in frequency of identified traits. The modern era was ushered in by the introduction of ‘chips’ which allowed the simultaneous analysis of 100,000+ SNPs simulta-neously, interrogating the entire genome in a hypothesis-free fashion (Genome wide association study (GWAS)). More recently, whole-genome sequencing has been used, however, bioin-formatic analysis of results remains a rate-limiting step. For validation, find ings must be validated via replication in a second population and/or associated with genotype-specific variation in a biologic mechanism or in outcome. For a number of genetic findings, biological plausibility may not be evident as the role these genes play in normal function may not yet be described.

One particular problem for CRS is difficulties with statistical methods required in genetic association studies; the size of re-quired populations and the cost of studies. Analysing the typical one million different genetic variations simultaneously increases the risk of spurious association. Thus large, well-characterised populations (1,000-10,000 subjects) are required, with their at-tendant costs. Caution must be thus be used when interpreting the results from CRS genetic studies in the literature.

5.2.1.3. Implications of genetic association studies of CRS Despite these challenges, genetic assessments of CRS are sug-gesting links with exiting concepts of pathophysiology and extending the tantalizing promise of future results down the road. Published genetic association studies in CRS have incre-ased in number over the past decade, increasing the number of potential gene candidates (Table 5.2.1.), and also repeatedly implicating certain genes, supporting their relevance to disease (Table 5.2.2.). Increased numbers allowed us to categorise gene candidates according to location or function. In both groups, candidate genes group loosely into regulation of immune tion, barrier function, and a variety of SNPs in genes whose func-tions are unknown or difficult to integrate into our current vision of CRS pathophysiology. Note that the high percentages of iden-tified genes related to immune function may reflect a selection bias of candidate genes studied rather than their actual level of implication. As an example, barrier structure and function genes were not suspected in CRS, but were identified with ‘agnostic’ or

‘hypothesis-free’ genome-wide approaches. Subsequently, dys-function of the epithelial barrier has been confirmed in in vitro models as a novel pathway for CRS development and persisten-ce. This improves our understanding of the disease process and opens potential new targets and approaches for therapy.

5.2.1.4. Epigenetics in CRS

Epigenetics deals with changes in organisms brought about by and initiation of initial defensive responses. Variations in

func-tion of a number of different genes or regulatory elements may lead to dysfunction within this system, ultimately yielding the same common disease phenotype. In addition, different genetic variations within a same gene may produce variable degrees of dysfunction.

The earliest identified genetic disorders were discovered because they showed a clear pattern of heritability, with well-defined disease phenotype or by using markers such as the sweat chloride test used in cystic fibrosis (CF). These well-cha-racterised genetic disorders implicated a single gene with a high penetrance and strong effects, which made the search for the genetic underpinnings of the disease much simpler. In contrast, most chronic disease such as asthma and CRS are considered

‘complex diseases’ where multiple genes are believed to parti-cipate in disease development, with each genetic factor having weak effects and thereby making only a partial contribution. In addition, the genetic basis may not be immediately obvious. For example, while it may seem obvious that an immune deficiency may predispose to chronic infection with bacteria, a defect in a gene involved of the epithelial barrier may lead to poor epithelial regeneration following viral insult, thereby facilitating bacterial sub-epithelially and thereby yielding the same result.

Despite the considerable difficulties posed by the multiplicity of factors implicated in CRS pathogenesis, strong evidence nevertheless supports that there is nonetheless a hereditary component to CRS. A classic example is CF, where homozygous mutations in the CFTR gene lead to defects in chloride transport and yield the clinical manifestations of the disease. CRS, prefe-rentially affecting the maxillary sinuses, is a consistent feature of CF. Other examples of well-characterised genetic diseases which include CRS in their phenotype include the forms of ciliary dyskinesia which can be coded for by at least 31 different genes implicated in coding a different portion of the structural arm of the cilia⁽¹⁰⁵⁾.

More recent work by Oakley et al. assesses the heritability of CRSwNP and CRSsNP in a more general population. In a study of 1638 patients with CRSwNP and 24,200 CRSsNP patients, they identify that first-degree family members of affected subjects are 4.1 times more likely to develop CRSwNP and 2.4 times more likely to develop CRSsNP⁽¹⁰⁶⁾. However, despite the demonstration of a heritable component, they still suggest an environmental factor as spouses of an affected patient are also 2.0 times more likely to develop CRSsNP as well. This is comple-mented by work from Sweden. Relatives of patients with nasal polyposis were screened for CRSwNP. 13.4% of the relatives had nasal polyps (compared to 2.7% in a control group randomly selected from the Swedish population). Thus the relative risk of the first-degree relatives having nasal polyps when compared to the control group was 4.9⁽¹⁰⁷⁾.

Techniques used to identify the genetic basis of disease involve

modifications in gene expression not resulting directly from al-teration of DNA sequences⁽¹⁰⁸⁾. This can lead to the modification of gene expression which can then be transmitted both intra-generationally and inter-intra-generationally. “Epigenetics” denote the way that genes interact with the environment in order to produce each individual phenotype. It is of significant interest that factors associated with increased risk of severity of disease such as cigarette smoking or Staphylococcus aureus are both implicated in epigenetic modification.

Evidence of epigenetics in vivo is still limited, but nevertheless, the concepts suggested by these studies are intriguing and hold promise for the future^(109-113). Most studies assessing blood or nasal epithelia obtained from brushing or raised nasal epithelial cultures derived from patients have identified that epigenetic changes are more pronounced in epithelium than in circulating blood, supporting the importance of contact with the external environment for their development. This suggests that patho-gens might be playing a role in adapting the environment for evolutionary advantage, and underlines that genetics co-exist with environment, compounding the difficulties in finding a

‘single-gene’ solution to the problem of CRS.

5.2.1.5. Clinical uses of genetics and genotyping in CRS

5.2.1.5.1. Characterisation of unexplained immune deficien-cies

Immune deficiencies frequently present as a clinical portrait or phenotype, where an immune defect is suspected but which may not be specifically elucidated by common blood tests⁽¹¹⁴⁾. However, sequencing suspect genes may identify the nature of the defect and allow for specific corrective therapy. A recent example of this has been the novel description of TLR3 receptor dysfunction first identified by sequencing patients with herpes simplex encephalitis⁽¹¹⁵⁾.

5.2.1.5.2. Assessment and selection of therapy for cystic fibrosis (CF)

CFTR genotyping is not recommended routinely in CRS patients but is instead performed only following demonstration of CFTR gene function impairment via sweat testing. In patients with positive test (high sweat chloride), this will be followed by gene testing for a panel of standard mutations then possibly gene sequencing. Type of mutation identified does not predict evo-a. Immune system

Gene Reference

ALOX5AP Al-Shemari et al. 2008⁽⁸⁰⁴⁾; Henmyr et al. 2014⁽⁸⁰⁵⁾ AOAH Bossé et al. 2009⁽⁸⁰⁶⁾; Zhang et al. 2012⁽⁸⁰⁷⁾

IL1A Karjalainen et al. 2003⁽⁸⁴⁶⁾; Erbek et al. 2007⁽⁸⁰⁸⁾; Mfuna Endam et al. 2010⁽⁸⁰⁹⁾ IL1B Erbek et al. 2007⁽⁸⁰⁸⁾; Bernstein et al. 2009⁽⁸¹⁰⁾

IL10 Kim et al. 2009⁽⁸¹¹⁾; Bernstein et al. 2009⁽⁸¹⁰⁾; Zhang 2012⁽⁸¹²⁾ IL22RA1 Endam 2009⁽⁸¹³⁾; Henmyr 2014⁽⁸⁰⁵⁾

IL33 Buysschaert 2010⁽⁸¹⁴⁾; Kristjansson 2019(⁴³⁶⁾ IRAK-4 Tewfik et al. 2009⁽⁸¹⁵⁾; Zhang et al. 2011⁽⁸¹⁶⁾

NOS1 Castano et al. 2009⁽⁸¹⁷⁾; Zhang et al. 2011⁽⁸¹⁶⁾; Henmyr et al. 2014⁽⁸⁰⁵⁾ NOS1AP Zhang et al. 2011⁽⁸¹⁶⁾; Henmyr et al. 2014⁽⁸⁰⁵⁾

TAS2R38 Adappa et al. 2014⁽¹¹⁶⁾; Mfuna Endam et al. 2014⁽¹¹¹⁾; Purnell et al. 2019⁽¹¹⁷⁾

TGFB1 Henmyr et al. 2014⁽⁸⁰⁵⁾

TNFA Erbek et al. 2007⁽⁸⁰⁸⁾; Bernstein et al. 2009⁽⁸¹⁰⁾; Batikhan et al. 2010⁽⁸¹⁸⁾ b. Barrier and structural

Gene Reference

None None

c. Not easily categorised

Gene Reference

DCBLD2 Pasaje et al. 2012⁽⁸¹⁹⁾; Henmyr et al. 2014⁽⁸⁰⁵⁾ PARS2 Bossé et al. 2009⁽⁸⁰⁶⁾; Henmyr et al. 2014⁽⁸⁰⁵)

RYBP Bossé et al. 2009⁽⁸⁰⁶⁾; Zhang et al. 2011⁽⁸¹⁶⁾; Cormier et al. 2014⁽¹⁰²⁾

Table 5.2.1. List of genes associated with CRS in more than one study. Genes are grouped according to putative biological role: a. immune system related; b. epithelial barrier related; c. difficult to categorize.

5.2.1.5.3. Predictive genetics in CRS

Given the multiplicity of implicated factors, it is unclear that genetic polymorphisms alone will allow planning of success vs. failure following therapy. However, a number of markers are already predicting type of bacteria likely to be recovered, which offers a beginning of a classification of CRS patients.

lution, as the overall clinical picture is believed to be secondary to other ‘modifier’ genes. However, certain genotypes may predict response to Ivacaflor, a new drug enhancing CFTR gene function.

Table 5.2.2. Genes reported in a single study. Genes are grouped according to putative biological role: a. immune system-related; b. epithelial barrier related; c. difficult to categorize.

a. Immune system

Gene Reference

ALOX15 Kristjansson et al. 2019⁽⁴³⁶⁾

ALOX5 Al-Shemari et al. 2008⁽⁸⁰⁴⁾

BDKRB2 Cormier et al. 2014⁽¹⁰²⁾

CD58 Pasaje et al. 2011⁽⁸¹⁹⁾

CD8A Alromaih et al. 2013⁽⁸²⁰⁾

CIITA Bae et al. 2013⁽⁸²¹⁾

CNTN5 Cormier et al. 2014⁽¹⁰²⁾

COX2 Sitarek et al. 2012⁽⁸²²⁾

CYSLTR1 (X)* Al-Shemari et al. 2008⁽⁸⁰⁴⁾

FOXP1 Kristjansson et al. 2019⁽⁴³⁶⁾

HLA-DQA1 Kristjansson et al. 2019⁽⁴³⁶⁾

HLA-DQB1 Schubert et al. 2004⁽⁸²³⁾

HLA-DRA Bohman et al. 2017⁽⁸²⁴⁾

IGFBP7 Cormier et al. 2014⁽¹⁰²⁾

IL1RL1 Castano et al. 2009⁽⁸¹⁷⁾

IL1RN Cheng et al. 2006⁽⁸²⁵⁾

IL18R1 Kristjansson et al. 2019⁽⁴³⁶⁾

IL4 Zhang et al. 2012⁽⁸⁰⁷⁾

MET Sitarek et al. 2012⁽⁸²²⁾

MET1 Castano et al. 2010⁽⁸²⁶⁾

OSF-2 (POSTN) Zielinska-Blizniewska et al. 2012⁽⁸²⁷⁾

PDGFD Cormier et al. 2014⁽¹⁰²⁾

PRKCH Cormier et al. 2014⁽¹⁰²⁾

RAC1 Cormier et al. 2014⁽¹⁰²⁾

SERPINA1 Kilty et al. 2010⁽⁸²⁸⁾

TAS2R19 Purnell et al. 2019⁽¹¹⁷⁾

TNFAIP3 Cormier et al. 2009⁽⁸²⁹⁾

TP73 Tournas et al. 2010⁽⁸³⁰⁾

TSLP Kristjansson et al. 2019⁽⁴³⁶⁾

VSIR Bohman et al. 2017⁽⁸²⁴⁾

b. Barrier and structural

Gene Reference

BICD2 Bohman et al. 2017⁽⁸²⁴⁾

CACNA1I Bossé et al. 2009⁽⁸⁰⁶⁾

CACNA2D1 Cormier et al. 2014⁽¹⁰²⁾

CACNG6 Lee et al. 2010⁽⁸³¹⁾

CDH23 Cormier et al. 2014⁽¹⁰²⁾

K6IRS2 Cormier et al. 2014⁽¹⁰²⁾

KCNAM1 Purkey et al. 2014⁽⁷⁸⁶⁾

KCNQ5 Purkey et al. 2014⁽⁷⁸⁶⁾

K6IRS4 Cormier et al. 2014⁽¹⁰²⁾

LAMA2 Bossé et al. 2009⁽⁸⁰⁶⁾

LAMB1 Bossé et al. 2009⁽⁸⁰⁶⁾

LF Zielinska-Blizniewska et al. 2012⁽⁸²⁷⁾

MMP9 Wang et al. 2010⁽⁸³²⁾

MSRA Bossé et al. 2009⁽⁸⁰⁶⁾

MUSK Bossé et al. 2009⁽⁸⁰⁶⁾

NARF Cormier et al. 2014⁽¹⁰²⁾

NAV3 Bossé et al. 2009⁽⁸⁰⁶⁾

RPGR Bukowy-Bieryłło et al. 2013⁽⁸³³⁾

c. Not easily categorised

Gene Reference

C13orf7 Cormier et al. 2014⁽¹⁰²⁾

CYP2S1 Kristjansson et al. 2019⁽⁴³⁶⁾

DPP10 Kim et al. 2015⁽⁸³⁴⁾

FAM79B Cormier et al. 2014⁽¹⁰²⁾

GFRA1 Cormier et al. 2014⁽¹⁰²⁾

GNB2 Purnell et al. 2019⁽¹¹⁷⁾

HLCS Bohman et al. 2017⁽⁸²⁴⁾

KIAA1456 Bossé et al. 2009⁽⁸⁰⁶⁾

MYRF Kristjansson et al. 2019⁽⁴³⁶⁾

PHF14 Cormier et al. 2014⁽¹⁰²⁾

PIGT Cormier et al. 2014⁽¹⁰²⁾

SLC13A3 Cormier et al. 2014⁽¹⁰²⁾

SLC22A4 Kristjansson et al. 2019⁽⁴³⁶⁾

SLC5A1 Bohman et al. 2017⁽⁸²⁴⁾

TOMM34 Cormier et al. 2014⁽¹⁰²⁾

TRHDE Cormier et al. 2014⁽¹⁰²⁾

TRIP12 Bossé et al. 2009⁽⁸⁰⁶⁾

UBE3A Cormier et al. 2014⁽¹⁰²⁾

UBE3C Pasaje et al. 2011⁽⁸¹⁹⁾

10p14 Kristjansson et al. 2019⁽⁴³⁶⁾

5.2.1.5.4. Taste receptors: predicting Gram-negative carri-age

TAS2R38 polymorphisms have been associated with CRS⁽¹¹⁶⁾. TAS2R38 codes for a type of bitter taste receptor, which is expressed in the airway and is implicated in innate immune defence. Activation of T2Rs by bitter stimuli are followed by se-cretion of antimicrobial peptides, production of nitric oxide, and increased ciliary beat frequency. The protective genotype codes for ability to detect phenylthiocarbamide (PTC), which can be assessed by simple taste testing. Interestingly, in CRSsNP, the non-tasting (or non-protective) TAS2R38 genotype is associated with a higher rate of gram-negative bacterial carriage and a poor outcome. To this end, many physicians now profile taste as part of patient assessment, however, this does not yet identify optimal therapy. Additionally, there is a concern that the effect may not be similar in patients with CRSwNP. Also, taste receptors Table 5.2.3. Genetic polymorphisms associated with S. aureus carriage in CRSwNP patients⁽¹⁰²⁾.

a. Immune system Gene

BDKRB2 CNTN5 IGFBP7 PDGFD PRKCH RAC1

b. Barrier and structural Gene

CACNA2D1 CDH23 GFRA1 K6IRS2 K6IRS4 TOMM34

c. Not easily categorised Gene

C13orf7 FAM79B NARF PHF14 PIGT RYBP SLC13A3 TRHDE UBE3A

may also play role or have predictive value in CRS, notably the taste receptor TAS2R19 (rs10772420)^{(111, 117)}. This remains to be validated and replicated in other populations.

5.2.1.6. Staphyloccus aureus carriage in CRSwNP

Genes associated with culture-positivity for S. aureus in CRSwNP patients has been assessed in an agnostic ‘hypothesis-free’

fashion using a pooling-based Genome-wide Association study

(102). Presence of S. aureus in CRSwNP patients is associated with

a number of genes loosely organised along reduced engulfment of bacteria, modulation of inflammatory response, and genes of barrier elements (Table 5.2.3.). This supports that CRS patients colonised with S. aureus may be subject to immune impairment and dysfunction of the epithelial barrier and may thus be exqui-sitely sensitive to low level chronic bacterial infection with S. au-reus. Attempts to predict S. aureus carriage in individual patients implicates several genes acting together to provide additive effects (Figure 5.2.1.). This supports the concept of multiple ge-nes in a pathway interacting to yield a common final phenotype (S. aureus carriage) and aligns well with our current concepts of disease pathogenesis. Given the ubiquity of S. aureus in CRS and its association with a difficult evolution, having the capacity to identify patients at risk of S. aureus carriage prospectively might allow selection of patients for specific anti-S. aureus therapy.

5.2.1.7. Summary and future perspectives

The current knowledge base in genomics of CRS disease of-fers the tantalizing promise of identifying new mechanisms of disease development and of markers predicting optimal response to available therapies. However, for the moment, genetics do not allow prediction of disease or outcome and its uses are currently restricted to extreme cases to understand the molecular underpinnings of disease. Nevertheless, simultaneous ongoing revolutions in our understanding of CRS and the dis-section of implicated mechanisms will complement increased appreciation of genetic changes. Diagnosis of particular forms of disease or identification of particular predisposing factors may help predict evolution and better tailor therapy. Identification of novel pathogenic mechanism may lead to increased scrutiny of genes in unsuspected novel pathways.

As knowledge regarding and our appreciation of interactions of immune system / microbiome / epithelial barrier improves, we may be able to develop multi component predictive models that integrate all of the interaction components and allow more rational administration of therapy and improved clinical care.

It will be essential to continue to collect genetic material as a component of clinical trials to be able to verify whether iden-tified factors and factors remaining to be discovered influence response to therapy and can be used for pharmacogenomic purposes.

In document El impacto de las instrucciones de relevancia y de la interrogación elaborativa en el procesamiento de textos expositivos: evidencias desde los movimientos oculares (página 163-169)