What's the role of SNP (Single Nucleotide Polymorphism) in a disease when there is no gene associated to that SNP

What's the role of SNP (Single Nucleotide Polymorphism) in a disease when there is no gene associated to that SNP

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I am quite new to the field of GWAS (genome-wide association studies), and I'm combining GWAS results and single cell analysis on type-1 diabetes (T1D), to see the role of cell specificity on the disease.

However, I don't understand one aspect about GWAS results. The GWAS results lists all the significant SNPs (low p-value) from a certain study on a particular disease. After that, those SNPs are mapped to genes using either positional mapping (using windows), eQTL mapping, or even both.

However, some SNPs do not map to any genes using both positional and eQTL mapping procedure. Some removed SNPs even have a lower p-value than those which are mapped to genes.

Here is my question: since all the listed SNPs are supposed to be significant (tiny p-value), how can those SNPs which are highly correlated to the disease also show no association towards any gene. How do these SNPs give rise to the disease?

I would like to thank you in advance. Sorry if I'm using wrong jargon or anything, and please let me know, if you want any further clarification.

SNPs do not signify anything about the functionality of a particular piece of DNA. You can think of a SNP as just a sign that says "hey, something in my neighborhood might be interesting!!" In this respect many GWAS SNPs are so-called "tag SNPs", that have been selected specifically to give the minimal number of SNPs that can be linked to all of the genome (e.g. every 1 centimorgan there is a SNP, or whatever).

So: SNPs do not say anything about biology, or about genes. The only thing that they signify is linkage to something that is possibly interesting.

Your issue seems to be that you are coming up with GWAS SNPs that do not show apparent linkage or statistical associations (e.g. eQTLs) to anything that you think should be interesting.

There are a lot of ways in which this could be the case:

  1. There actually is a gene in that part of the sequence, and we just haven't annotated it properly.

  2. The reference genome is wrong in that SNP's location, or is missing an interesting piece of sequence (i.e. a gene) that exists in your population.

  3. That SNP has a population structure signal (i.e. it is more common in one population than another) that is associated with your trait of interest, which you have not properly corrected for.

  4. That SNP is spuriously linked (for whatever reason) to a more distant part of the genome.

  5. That SNP was mis-mapped and is actually in the wrong part of the genome somehow.

  6. There is technical interference due to high similarity to some other part of the genome, which your procedure has not corrected for.

  7. Sometimes frequentist p-values are not actually informative and a thing that looks interesting according to p-values is simply not interesting.

  8. Though there are no genes, there is a long-range enhancer in the region of the SNP that affects a distant gene.

  9. Though there are no genes, there is repetitive DNA linked to the SNP that leads to a complicated regulatory feedback that affects something about your character of interest.

  10. Something about microRNAs?

  11. Your SNP doesn't have any genes nearby, but it is linked to a TAD boundary that affects overall chromatin architecture.

  12. There is a long non-coding RNA there.

  13. Your eQTL significance threshold is too stringent.

  14. Your eQTL association analysis missed an important isoform or transcript.

… and many other hypotheses! Many of these are very hand-wavey or unlikely, but sometimes biology is just weird.

However, in general I would default to an explanation in which there is some kind of technical or statistical artifact. Even when nothing is obviously wrong, there is usually some kind of technical problem in genomic datasets.

The Role of Single Nucleotide Polymorphisms in Predicting Prostate Cancer Risk and Therapeutic Decision Making

Prostate cancer (PCa) is a major health care problem because of its high prevalence, health-related costs, and mortality. Epidemiological studies have suggested an important role of genetics in PCa development. Because of this, an increasing number of single nucleotide polymorphisms (SNPs) had been suggested to be implicated in the development and progression of PCa. While individual SNPs are only moderately associated with PCa risk, in combination, they have a stronger, dose-dependent association, currently explaining 30% of PCa familial risk. This review aims to give a brief overview of studies in which the possible role of genetic variants was investigated in clinical settings. We will highlight the major research questions in the translation of SNP identification into clinical practice.

1. Introduction

Prostate cancer (PCa) is a major health care problem because of its high prevalence, health-related costs, and mortality. Even though most patients have clinically localized and indolent tumors at diagnosis, worldwide, this disease still holds second place in the leading causes of cancer deaths [1]. Despite its prevalence, lethality, and socioeconomic burden, there are still many diagnostic and therapeutic challenges in the PCa field. This is mainly due to the lack of cancer- and/or patient-specific biomarkers, currently limiting patient-tailored diagnostics/therapeutics in PCa.

Age, race, and family history remain primary risk factors for the development of PCa. It has been shown that PCa is one of the most heritable cancers with epidemiological studies suggesting the role of genetics in PCa development [2, 3].

Due to the latter, there has been an increasing focus on the role of single nucleotide polymorphisms (SNPs) in the development and progression of PCa but also on their role in diagnostics and risk prediction. A SNP is a DNA sequence variation occurring when a single nucleotide (A, T, C, or G) in the genome differs from the normally expected nucleotide. These SNPs are known to underlie differences in our susceptibility to diseases. SNPs need to be determined only once and are easy to determine, making them interesting biomarkers. The rising interest in the role of SNPs in PCa development and progression is illustrated by the number of studies being published on SNPs in the PCa field.

In 2008, an extensive genome-wide association study (GWAS) compared SNPs between PCa cases and controls. Since then, numerous GWAS studies have been conducted [4–26]. While many SNPs were only moderately associated with PCa risk, in combination, they had a stronger, dose-dependent (i.e., cumulative effect of number of SNPs) association. A total of 77 susceptibility loci are currently explaining approximately 30% of the familial risk [6]. With ongoing GWAS, we could expect that more genetic variants will be found, explaining more of the PCa familial risk. However, the question has been raised whether finding more PCa risk-associated SNPs will have added value over the currently known ones [27].

Many SNPs are connected to each other through “linkage disequilibrium,” which is a nonrandom association of alleles at two or more loci, descendant from a single, ancestral chromosome. However, the SNPs detected through GWAS studies are mostly limited to “index SNPs,” excluding other SNPs which are in linkage disequilibrium. Clearly, these index SNPs are not necessarily the SNPs causative for its associated phenotype (i.e., PCa risk, risk of progression, etc). Therefore, molecular analyses will be needed to identify the exact SNP within each linkage domain which is the causative SNP. SNPs that lie within an open reading frame can lead to changes in messenger RNA stability or translation efficiency, as well as changes in structure/activity of the encoded proteins. However, most SNPs are located outside of the genes and are suspected to affect gene expression levels and genome/chromatin organization. Therefore, it is interesting to determine the role of these SNPs in the clinical field. This review aims to give a selected overview of studies on the possible role of genetic variants in clinical practice. We will highlight diagnostic and therapeutic obstacles which are currently major issues in clinical practice.

2. Evidence Synthesis

2.1. Early Detection

To detect PCa in its early stages, currently, clinicians are limited to serum PSA level measurements as a marker, which lacks sensitivity and specificity. Therefore, PSA screening (defined as mass screening of asymptomatic men) has been heavily debated. Two prospective studies (The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial and The European Randomized Study of Screening for Prostate Cancer (ERSPC)) have contributed greatly to this discussion. The PLCO study concluded that PCa-related mortality did not significantly differ between patients being screened or not [3]. The ERSPC study inferred that, based on PSA-based PCa detection, 1410 men would need to be screened and 48 additional cases of PCa would need to be treated to prevent one death from PCa, resulting in a high rate of over diagnosis [28].

In reaction to these recent results, the US Preventive Services Task Force has radically recommended against PSA-based screening [29]. However, they ignored the 50% reduction in PCa-specific mortality since the introduction of PSA [28, 30]. Moreover, without PSA testing, most men would only be diagnosed when they become symptomatic, when the disease is often too far advanced to cure. Therefore, the current EAU guidelines recommend opportunistic screening to the well-informed man [31]. Furthermore, there is an urgent need for the development of novel biomarkers.

2.1.1. Opportunistic Screening

Despite the EAU guidelines’ recommendation on opportunistic PSA screening, the question remains which patients would benefit the most? Rephrased, we could ask ourselves which men are at an elevated risk of PCa? Since epidemiological studies have suggested a role of genetics in PCa development, it seems tempting to speculate that genetic variations could be of interest in predicting patients’ risk of PCa in clinical practice [3]. Using this, clinicians could determine which patients would benefit from PSA screening or in which patient group they should have a low threshold of performing prostate biopsies. Currently, these risk associations, detected by GWAS studies, are of limited clinical utility because the risk prediction is based on comparing groups of people. This allows for patient stratification into “risk groups,” having an x-fold greater PCa risk relative to the population average. However, for the clinician, it is of greater interest to be able to calculate a patient’s absolute risk to develop PCa at a certain given point based on an individual’s information.

Evaluating the efficiency of detecting PCa using a model based on family history, age, and genetic variation, Zheng et al. suggested comparable efficiency in detecting PCa when compared to the predictive power of PSA level cutoff of 4.1 ng/mL (see Table 1 for an overview of all SNPs cited in this paper) [32]. At first sight, this would seem irrelevant, since the efficiency of PSA testing itself is low. However, the economic burden of genetic testing could potentially be much lower, since this should only be determined once, whereas PSA levels fluctuate over time and often require multiple testing. The combined predictive performance of PSA plus genetic testing on PCa diagnostics unfortunately did not improve diagnostics once age, PSA level, and family history were known [32, 33].

Indeed, it was argued that SNPs are not good at discriminating cases from controls but might be of better use in identifying men at high risk of PCa [34]. In light of this, Xu et al. developed a prediction model of absolute risk for PCa at a specific age based on the sum of 14 SNPs and family history [35]. Using this model, one could identify a small subset (0.5–1%) of individuals at very high risk (41% and 52% absolute risk in a US and Swedish population) of developing PCa between 55 and 74 years of age. Sun et al. studied the performance of three sets of PCa risk SNPs in predicting PCa, showing that they are efficient at discriminating men who have a considerably elevated risk for PCa (a two- and threefold increase when compared to the population median risk) [36].

These risk predictions seem to have the highest impact in young patients with a family history of PCa [37, 38]. This seems logical, since one is born with a certain inheritable subset of SNPs, which do not change throughout one’s life. Therefore, it could be expected that their effects would present in the earlier stages of life. Macinnis et al. developed a risk prediction algorithm for familial PCa, using 26 common variants, predicting the cumulative PCa risk depending on family history (from incidental PCa to highly burdened PCa families) and the number of SNPs (expressed in percentile of a SNP profile) [38].

Generalized, the future role of SNP genotyping in PCa screening seems to lie in detecting men at high risk of (aggressive) disease. Men with a higher likelihood of (aggressive) PCa may choose to begin PCa screening at an earlier age and/or more frequently. They may also pursue preventative measures, including diet/lifestyle intervention and chemoprevention.

It has been estimated that, when compared to age-specific screening, personalized screening would result in 16% fewer men being eligible for screening at a cost of 3% fewer screen-detectable cases [39]. Importantly, SNPs can be determined with high accuracy, at low cost and at any age, which make them attractive candidates to predict an individual’s risk for PCa.

2.1.2. SNPs in Interpreting (Novel) Biomarkers Levels

SNP genotyping can result in a risk prediction, that is, estimating the likelihood of developing PCa. Currently, they have no role as true diagnostic markers. However, as Klein et al. have already stated, there might be other clinical uses for SNPs [40]. Hypothetically, they could be used in combination with PSA levels, increasing its predictive role [41, 42].

Furthermore, a profound knowledge on SNPs influencing novel biomarker levels would be of great interest, since this could play a crucial role in the interpretation of novel biomarkers. Fundamental research has already identified multiple SNPs playing a role in expression and/or function of hK2, β-MSP, TMPRSS2, and so forth [43–45], which could potentially have an important impact on their interpretation.

Recent evidence has suggested that PSA levels are subject to genetic variation as well, explaining 40–45% of variability in PSA levels in the general population [46]. This variability plays an important role in the low sensitivity and specificity of PSA testing, because of which there is no generalizable threshold at which men should undergo prostate biopsies.

Attempting to explain this variability, Gudmundsson et al. detected six loci associated with PSA levels, of which four had a combined relative effect on PSA level variation [47]. Other groups have validated this work. One group suggested that genetic correction could influence the risk of PCa per unit increased/decreased PSA [48]. Another group suggested that genetic correction could alter the number of men with an abnormal PSA (based on general biopsy thresholds), preventing up to 15 to 20% of prostatic biopsies, in this way reducing complications and costs and improving quality of life [49].

With the exponentially increasing interest and development of novel biomarkers in PCa, we should keep in mind that SNPs can clearly alter biomarker levels, which is crucial for correct interpretation. If these SNPs are not taken into account, we could foresee similar obstacles as we are seeing now with PSA testing.

2.2. Localized Disease

In treating localized PCa, defined as N0 M0 disease [31], there are multiple viable treatment options, each with its indications and contraindications. Based on clinical stage of the disease, age, and comorbidities, clinicians decide to enroll a patient in an active surveillance program or to start active treatment.

2.2.1. Active Surveillance

Active surveillance (defined as close monitoring of PSA levels combined with periodic imaging and repeat biopsies) is currently the golden standard for treating PCa with the lowest risk of cancer progression (cT1-2a, PSA < 10 ng/mL, biopsy Gleason score <6 (at least 10 cores), <2 positive biopsies, minimal biopsy core involvement (<50% cancer per biopsy)).

Although active surveillance has shown to be a viable option with excellent survival rates, reported conversion rates to active treatment range from 14% to 41%. This delayed treatment, however, has no effect on survival rates [50]. Biomarker research in the “active surveillance group” should therefore mainly focus on detecting high-risk disease with high specificity, avoiding under- and overtreatment and making prevention and early intervention possible. This topic has already been discussed in the paragraph “early detection” (see Section 2.1).

2.2.2. Active Therapy

As it has become clear that, in patients with low-risk disease, active therapy can be delayed based on active surveillance protocols, it is clear as well that therapy is required in patients with intermediate and especially in patients with high-risk disease, as defined by the EAU guidelines.

In light of this, there are two large retrospective studies, determining 15-year mortality rates in men with PCa treated with noncurative intent. Firstly, Rider et al. found that PCa mortality is low in all men diagnosed with localized low- and intermediate-risk PCa. However, death rates are much higher in all men with localized high-risk disease with a 31% mortality rate [51]. Similar results were published by Akre et al., who have shown that in men with locally advanced PCa with a Gleason score of 7–10, where the PCa is managed with noncurative intent, PCa-specific mortality rates range between 41 and 64% [52].

Reported incidence rates of high-risk PCa vary between 17% and 31%, depending on how the disease was defined [53]. After primary treatment, patients with high-risk PCa have a higher risk of disease recurrence and progression, requiring multimodality treatment [31]. Currently, the two most established treatment options with curative intent are surgery and radiotherapy, each with its obstacles.

Radical Prostatectomy. In treating patients with intermediate- and high-risk PCa, radical prostatectomy can be curative for some patients, whilst others need a multidisciplinary approach. For clinicians, it is therefore of great interest to be able to define a patient’s risk for persistence or relapse of disease before they start treatment. Based on these predictions, clinicians could decide to start with or withhold from adjuvant therapy, leading to a more personalized medicine.

At this moment, these predictions are based on nomograms, integrating preoperative clinical parameters, optimizing their prognostic value [54–56]. However, current clinical parameters still lack sufficient accuracy. Therefore, there is an enormous interest in developing novel biomarkers to optimize pretreatment risk stratification [57]. Regarding this, SNPs are especially interesting, since their use avoids PCa heterogeneity in a single specimen, limiting its pathological parameter accuracy [58, 59]. Again, SNPs are not age-dependent and only need to be determined once, reducing patient burden and costs.

Multiple groups have identified SNPs that might be associated with higher rates of biochemical recurrence and/or shorter periods of biochemical-recurrence-free survival after radical prostatectomy. These polymorphisms are located in genes involved in steroid hormone biotransformation [60–62], immune response [63], Wnt [64] and IGF1 [65] signaling pathways, and other genes associated with oncogenesis [66–68]. However, conflicting results have already been reported by Bachman et al., who found that the AA genotype of the 938 BCL2 promotor polymorphism was an independent prognostic marker of relapse-free and overall survival in a Caucasian patient group [69]. This contrasted with results published by Hirata et al., who found the CC variant of the same promotor to be predictive for biochemical recurrence in a Japanese population [70].

Despite the numerous investigations on the role of SNPs in predicting biochemical recurrence after radical prostatectomy, only a few have been developed into a clinically applicable model, integrating clinicopathological data and genetic information [71, 72].

Radiotherapy. External beam radiotherapy (EBRT) is a second treatment option with curative intent for localized PCa. Currently, there is no solid evidence suggesting superiority of surgery or radiotherapy over the other. With the development of new techniques (IMRT, tomotherapy, and so forth) with escalating radiation doses, there has been an increase in patients being treated with EBRT for localized PCa.

Still, toxicities in neighboring normal tissues remain the major limiting factor for delivering optimal tumoricidal doses [73]. Normal-tissue radiation sensitivity mainly depends on treatment-related factors, which are defined as the total irradiation dose, the fractionated regimen, the total treatment time, and the irradiated volume. However, even for similar or identical treatment protocols, the extent of side effects shows substantial variation. This interindividual variation can be explained by patient-related factors [74].

Since patients with higher rates of side effects show no specific phenotypic trait, this suggests that subclinical genetic variations could explain these interindividual differences. Therefore, there has been an increasing interest in identifying the role of genetic variation and SNPs on treatment efficacy and normal-tissue radiosensitivity, termed “radiogenomics.” Detecting these genetic variations could lead to the identification of subgroups of patients at risk for developing severe radiation-induced toxicity [75].

Based on a mechanistic understanding of the radiation pathogenesis, there has been a major interest in understanding the role of genetic variation in genes involved in DNA damage sensing (e.g., ATM), fibrogenesis (e.g., TGFB1), oxidative stress (e.g., SOD1), and major DNA repair pathways (e.g., XRCC1, XRCC3, ERCC2, and MLH1), showing conflicting results [73, 76–83]. Comparable studies have been performed in patients treated with brachytherapy [84–88].

These results are of great interest, since long-term genitourinary, sexual, and gastrointestinal quality of life are major issues guiding decision making with respect to curative management of PCa. In 2012, Barnett et al. aimed to prospectively validate SNPs which were at that time reported to be associated with radiation toxicity in a population of 637 patients treated with radical prostate radiotherapy. Despite previous evidence, none of the 92 investigated SNPs were associated with late normal tissue toxicity [89].

2.3. Metastatic Prostate Cancer

Since androgens have a pivotal role in the development of PCa, the androgen receptor is the main target of systemic therapy for PCa. Androgen deprivation therapy (ADT) is the mainstay of treatment for patients with metastatic PCa, of which chemical or surgical castration is the first-line treatment. Because of comparable efficacy between chemical and surgical castration, the latter generally has been replaced by chemical castration [90–92].

2.3.1. Genetic Polymorphisms and ADT

Despite the efficiency of hormonal therapy in metastatic disease, eventually every patient will relapse, developing castration-resistant PCa (CRPC) [93]. Clinicians use well-studied clinicopathologic parameters (PSA kinetics and Gleason Score and so forth) to predict which patients will not respond well to ADT and which patients have poor prognosis [94–96]. Still, these parameters are insufficient for prediction, which is suggested by the recommendation of the EAU guidelines that LHRH agonists should be continued, even in a castration-resistant state [31]. In light of this, genetic markers could be an attractive way to improve risk stratification, predicting which patients will respond less to ADT and have poor prognosis, warranting closer follow-up.

Ross et al. underlined the importance of pharmacogenomics on an individuals’ response to ADT [97]. They associated three SNPs located in/close to CYP19A1 (encodes for aromatase, a key enzyme that converts testosterone to estrogen in men), HSD3B1 (associated with PCa susceptibility) [98], and HSD17B4 (overexpression associated with higher Gleason grade) [99]. These SNPs were significantly associated with time to progression, having an additive effect when combined.

Later on, SNPs in multiple other loci have shown to be correlated with earlier relapse in patients treated with ADT. Currently known loci of interest are situated in the EGF gene [100] (known to activate several prooncogenic signaling pathways), in two androgen transporter genes (SLCO2B1 and SLCO1B3) [101] and in the TGFβR2 gene. The latter codes for a receptor involved in TGFβ signaling pathway, playing a role in carcinogenesis and tumor progression [102]. In contrast to these, some SNPs associated with time to progression under ADT, are located in genes of which the function is still unknown [103].

Moreover, a Taiwanese group developed a DNA library of 601 men with “advanced prostate cancer” treated with ADT, in which they detected 5 SNPs that were correlated with progression and 14 SNPs correlated with PCa-specific mortality under ADT [104–107]. Bao et al. detected four SNPs within miRNAs and miRNA target sites that were associated with disease progression [104]. Furthermore, Huang et al. systematically investigated 55 and 49 common SNPs in androgen- and estrogen-receptor-binding sites, after which they withheld one SNP (located in BNC2) which is correlated with progression and 5 SNPs (located in ARRDC3, FLT1, SKAP1, BNC2, and TACC2), which are correlated with PCa-specific mortality [105, 106]. Finally, Huang et al. associated a SNP in the BMP5 and IRS2 gene with survival [107]. The latter encodes a member of a family of intracellular signaling adaptor proteins that coordinate numerous biologically key extracellular signals within the cell, including insulin-like growth factor 1 (IGF1), of which the genotype seems to be correlated with survival in metastatic PCa as well [108]. This only shows how complex and interwoven the clinical effects of genetic variation can be.

Although these results are very interesting, it should be noted that the investigated patient group is very heterogeneous. In this population with “advanced PCa,” tumor characteristics show that 33% of patients have a Gleason score ranging from 2 to 6 and 31.7% of patients have T1/T2 tumors. Furthermore, the setting in which ADT was given was very heterogeneous, ranging from ADT in neoadjuvant setting to ADT for biochemical failure after radical prostatectomy. This heterogeneity limits the interpretation of genetic variation in clinical situations such as these.

Hypothetically, there are multiple potential clinical benefits of SNP genotyping with respect to ADT therapy. Firstly, it could play a prognostic role in identifying patients at high risk of therapeutic failure. This could help identify a subset of patients who may benefit from a more aggressive initial treatment strategy than ADT alone, including combinations with novel drugs [103]. Secondly, polymorphisms with functional implications on enzyme activity could be targeted with novel therapeutics, improving ADT efficacy [97].

2.3.2. Genetic Polymorphisms in the Castrate-Resistant PCa

In the castrate-resistant setting, taxane-based chemotherapy (docetaxel) has been the only treatment option for many years, based on two multicenter phase III randomized clinical trials, showing a moderate increase in overall survival [109, 110]. Over the last few years, numerous novel therapeutics have been developed in this setting. However, equally many questions regarding the optimal treatment regimen remain. Clinical evidence showing superiority to one treatment option over the other is severely lacking, keeping clinicians in the dark on the optimal treatment.

When treatment with docetaxel is started, there is a high variability in the clinical response [111]. Therefore, it would be of great interest to be able to predict this response rate before treatment is started. Based on this, the clinician could decide to withhold from docetaxel as first-line treatment and choose another treatment option.

Genetic variation in the CYP1B1 gene has shown to predict outcome in CRPC patients receiving first-line docetaxel. Pastina et al. showed that patients, carrying the CYP1B1 4326 GG genotype, had significantly shorter overall survival rates when compared to patients carrying CYP1B1 4326 GC or CC. Even after correcting for other risk factors (e.g., demographics, pathological, and biochemical characteristics), this genotype remained an independent predictive parameter of risk of death. This suggests that the 4326GG genotype might be a good pharmacogenetic marker of lower prevalence of response to docetaxel in CRPC patients [112]. It is suggested that its role probably lies in the effect it has on the levels of 4-hydroxyestradiol, which is the major CYP1B1 metabolite. The metabolite interferes with the chemotherapy-induced microtubule stabilization and structurally alters docetaxel [113]. Another gene of interest is the ABCB1 gene, which is responsible for a large portion of the systemic efflux of docetaxel. Within this gene, a combination of ABCB1 1236, 2677, and 3435 genotypes seems to be correlated with survival in CRPC patients receiving docetaxel and time to developing neuropathy in patients receiving a combination of docetaxel and thalidomide. The latter is probably due to cumulative effects on toxicity [114].

With the growing number of new treatment options, these results are very interesting for future clinical use. Using these, clinicians could individualize treatment regimens based on a patient’s genotype. Similarly, the role of SNPs in predicting therapeutic efficacy of novel therapeutic agents like abiraterone and enzalutamide awaits to be assessed.

3. Conclusions

Since the definition of the human genome, the basis for genetic variations that can lead to individual risks for diseases has become more and more clear. Genome-wide association studies (GWAS) have defined groups of SNPs which partially predict increased risk for PCa. As suggested in this review, SNPs have a great potential in predicting patients’ risk for PCa and/or therapy response, which could have an important impact in every day clinic.

Although many authors have suggested that genetic information can improve risk prediction and therefore be useful in clinical practice, there are several studies showing contradicting results, limiting their current clinical use. These contradicting results could be explained by multiple reasons. First, studies performed on small, heterogeneous populations might result in high rates of false positive and negative data. Secondly, most conducted studies are based on SNPs which have been correlated with PCa in GWAS studies. Since PCa phenotypes are probably determined by a spectrum of genetic variation (ranging from highly penetrant to low penetrant variations), with possible interdependencies of SNPs, GWAS studies are probably not sufficient to develop a full understanding of these variations in PCa.

Throughout this review, it has become clear that some challenges still remain for translational research on the role of SNPs in PCa. Firstly, clinical studies on SNPs should be performed in well-powered studies, which could give more conclusive results. Secondly, the important challenge for further basic research is to identify the causative SNPs within each linkage equilibrium. Hopefully, these SNPs will not only function as predictors but also give clues to important pathways in PCa development, which could be therapeutic targets.

It will only be after the enrichment of GWAS data by detailed SNP mapping and functional SNP testing that the most relevant SNPs can be analyzed in clinical research. In the future, we expect them to become critical to interpret individualized PCa risk, interindividual biomarker variation, and therapeutic response.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.


The authors gratefully acknowledge financial support from the company Ravago Distribution Center NV (LUOR fonds). This study was further financially supported by the Fundacion Federico, Grant OT/09/035 from the Katholieke Universiteit Leuven, and Grant nos. G.0684.12 and G.0830.13 of the Fund for Scientific Research Flanders, Belgium (FWO-Vlaanderen). Steven Joniau is holder of a grant from the Klinisch Onderzoeksfonds (KOF) from UZ Leuven.


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Copyright © 2014 Thomas Van den Broeck et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Radiation therapy in prostate cancer, either external beam or brachytherapy, is an effective therapy for men with early-stage, organ confined prostate cancer (1, 2). However, not all patients are cured, some because of occult metastases at the time of treatment and others because of failure of local control of cancer. In either scenario, cure or failure to cure may be driven by both host and somatic factors. More specifically, the role of inherited genetic variation to predict outcome after radiation therapy is biologically plausible and has been investigated somewhat in radiation therapy (3𠄵). Most studies have focused on polymorphisms in DNA damage response genes and examined toxicity outcomes (6𠄹). In contrast, data regarding the effects of genetic variation on treatment-specific cancer outcomes are more limited.

Ribonuclease L (RNASEL) is compelling as a potential modulator of response to radiation therapy in prostate cancer given its role in inflammation and response to infection. RNASEL is a putative tumor-suppressing enzyme that may inhibit growth and proliferation and induce apoptosis (10�), and is implicated in the cleavage of viral RNA and the interferon-mediated immune response (13). Polymorphisms in RNASEL, located on chromosome 1q25, have been inconsistently linked to hereditary and general prostate cancer risk (14�). In particular, the minor variant of single nucleotide polymorphism (SNP) rs12757998, located immediately downstream of the RNASEL coding region, was recently associated with an increased risk of prostate cancer and specifically higher-grade tumors (19), and was associated with elevated serum levels of the inflammatory markers C-reactive protein (CRP) and interleukin (IL)-6 (19).

The role of inflammation and the immune system in radiation-induced cancer cell death is complex and incompletely defined (27, 28). Preclinical data suggest that, at least under certain circumstances, the immune system may augment cytotoxic effects of radiation therapy and may even be required for tumor eradication (29, 30). Conformal radiation therapy given to prostate cancer patients induces a local inflammatory response and has been demonstrated to increase circulating IL-6 levels (31�). Therefore, we hypothesized that by modulating this response, inherited variation in RNASEL could affect prostate cancer outcomes following definitive radiation therapy for early-stage prostate cancer and sought to explore this association among men with prostate cancer in the US Health Professionals Follow-Up Study.

Single Nucleotide Polymorphisms in the NOD2/CARD15 Gene Are Associated With an Increased Risk of Relapse and Death for Patients With Acute Leukemia After Hematopoietic Stem-Cell Transplantation With Unrelated Donors

Hematopoietic stem cell transplantation (HSCT) is an important option in the management of acute leukemia, but the risk of disease relapse and death remains appreciable. Recent studies have suggested that nucleotide-binding oligomerization domain 2 (NOD2)/caspase recruitment domain 15 (CARD15) gene single nucleotide polymorphisms (SNPs), implicated in innate immunity and Crohn's disease, may also affect immune function post-HSCT.

NOD2/CARD15 genotypes were analyzed in 196 patients diagnosed with acute leukemia and their unrelated donors. The pairs are part of a previously well-characterized cohort with a median follow-up of 2.2 years (range, 0.42 to 6.61 years). T-cell depletion was used in 83% of pairs.

NOD2/CARD15 SNPs were associated with a reduction in overall survival (44% v 22% log-rank P = .0087) due to an increase in disease relapse (32% v 54% Gray's test P = .001) as compared with wild-type pairs. In multivariate analyses, the two most significant factors impacting outcome were transplantation in relapse and the presence of SNPs. The incidence of acute graft-versus-host disease was low and there was no significant difference due to the presence of SNPs.

These data indicate an unrecognized role for the NOD2/CARD15 gene in unrelated donor HSCT for acute leukemia. The increased risk of disease relapse suggests that the wild-type gene product may contribute to a graft-versus-leukemia effect. These data suggest that NOD2/CARD15 genotyping before transplantation may contribute to prognosis and influence clinical management.

Hematopoietic stem-cell transplantation (HSCT) is currently the only curative treatment for certain individuals diagnosed with acute leukemia who are considered to be high risk. 1 While the use of unrelated donors is well accepted, it is known that some complications may be increased. 2 Although HLA matching improves outcomes, recipients remain susceptible to life-threatening post-transplantation complications, including disease relapse and the development of graft-versus-host disease (GVHD). 3 Therefore, defining variables that predispose to either of these events is of critical importance.

Several recent studies have described a significant correlation between transplantation outcome and three single nucleotide polymorphisms (SNPs) in the caspase recruitment domain 15 (CARD15) gene (also known as the nucleotide-binding oligomerisation domain 2 [NOD2] gene). 4-7 Holler et al 5,6 associated increases in the incidence and severity of acute GVHD (aGVHD) and a reduction in overall survival (OS) with the presence of SNPs in two separate patient cohorts. A subsequent study also reported an association with these SNPs and the incidence of aGVHD, but failed to find any significant correlations with OS. 4 Conversely, Granell et al 7 have demonstrated that in a T-cell depleted setting, there was no impact of SNPs on aGVHD but a significant effect was reported on disease-free survival (DFS). The majority of patients reported received transplants from sibling donors.

The NOD2/CARD15 gene encodes the NOD2 protein, a member of a newly defined family of intracellular proteins 8,9 that are critical mediators of inflammation and participate in the formation of a protein complex termed the inflammasome, which has widespread effects on innate immunity, cytokine secretion, cell survival, and apoptosis. 10,11 NOD2 is expressed in circulating monocytes, in Paneth cells located in the epithelial crypts of the small intestine, and has also been identified in dendritic cells. 8,12 The cellular function of NOD2 is still uncertain and its physiological role is as yet undefined. SNPs within the NOD2/CARD15 gene have, however, been associated with functional defects 13-15 and with the occurrence of inflammatory bowel disorders. 16

We report herein the findings of an investigation into the impact of NOD2/CARD15 gene SNPs on the outcomes of acute leukemia HSCT pairs using an unrelated donor. Our data show that pairs with NOD2/CARD15 gene SNPs have a highly significant reduction in OS when compared with wild-type (WT) pairs. The reduced survival is attributable to a significant increase in disease relapse. The data also show that NOD2/CARD15 SNPs may offer a protective effect toward aGVHD. They suggest that NOD2 plays an important role in protection against recurrence of leukemia after HSCT.

NOD2/CARD15 genotyping was performed on 196 recipients and their Anthony Nolan Trust volunteer unrelated donors, who underwent an HSCT at one of 25 transplant centers in the United Kingdom between 1996 and 2003. These individuals formed part of a well-characterized cohort for whom high resolution HLA typing and long-term clinical data had been collated. Diagnoses were acute myeloid leukemia (AML 98 of 196 50%) and acute lymphoblastic leukemia (ALL 98 of 196 50% Table 1). Recipients were defined as having early-stage disease if in first complete remission. All others were designated as late-stage disease. The majority of recipients had myeloablative conditioning (78%). Eighty-three percent of recipients had T-cell depletion (TCD) included in their pretransplantation conditioning, with in vivo alemtuzumab (Campath Schering Health Care Ltd, West Sussex, United Kingdom) being the preferred method. Bone marrow was used as a source of stem cells in 81% of transplantations with the remaining 19% using peripheral blood stem cells as a graft. Two forms of post-transplantation immunosuppression predominated, cyclosporine A combined with methotrexate (47%) and cyclosporine A alone (31%).

Ethical approval was obtained from the central office for research ethics committees. Written consent for molecular studies of this nature was obtained from all recipients and their donors at the time of transplantation. The project was approved by the Anthony Nolan Trust Medical and Scientific Committees.

Recipients and donors were previously HLA typed to an allele-level resolution, with 64% (125 of 196) being matched at HLA-A, -B, -C, -DRB1 and -DQB1 (ie, 10 of 10 match). Of these, 16% (20 of 125) were also matched at HLA-DPB1 (ie, 12 of 12 match Table 1).

Donor and recipient genomic DNA was extracted from whole blood using the salting out technique. 17 Three SNPs were analyzed, namely, SNP 8 (p.R702W), SNP 12 (p.G908R) and SNP 13 (p.L1007fs numbering according to European Molecular Biology Laboratory accession number AJ303140 Appendix Table A1, online only). All genotyping was carried out by polymerase chain reaction (PCR) using sequence specific primers (SSP). DNA samples with a known NOD2/CARD15 genotype determined by the Taqman (Applied Biosystems, Foster City, CA) protocol 16 were used for optimizing PCR-SSP experiments. The primer sequences for exon 4 genotyping were a sense WT primer 5′-CATCTGAGAAGGCCCTGCTCC, a sense SNP 8 primer 5′-CATCTGAGAAGGCCCTGCTCT, each of which were used in an individual reaction with the antisense primer 5′-GTGCCCAACATTCAGGCCAC. For exon 8, the common sense primer 5′-GATGGAGGCAGGTCCACTTTGC was used with either the antisense WT 5′-TCGTCACCCACTCTGTTGCC or SNP 12 5′-TCGTCACCCACTCTGTTGCG. Exon 11 WT and SNP 13 analysis were performed simultaneously in a multiplex reaction. The primers were adapted from Ogura et al. 18 Briefly, the long sense primer 5′-TGGTACTGAGCCTTTGTTGATGAGCTC forms a product with the long antisense primer 5′-CATTCTTCAACCACATCCCCATTCCT. These in turn form additional products with either the antisense WT primer 5′-CAGAAGCCCTCCTGCAGGCCCT or the sense SNP 13 primer 5′-CGCGTGTCATTCCTTTCATGGGGC, respectively.

A proportion of samples were sequenced to confirm their genotype and to ensure the validity of the PCR-SSP system. All PCR-SSP results correlated with those obtained by sequencing.

Data were compiled and maintained on a Filemaker Pro database (Filemaker Inc, Santa Clara, CA). Analysis was performed using SPSS version 11.4 (SPSS Inc, Chicago, IL) and R version 2.2.1 ( The probabilities of OS and DFS were compared using log-rank statistics and calculated by the Kaplan-Meier method as there were no competing events. The probabilities of transplant related mortality (TRM), disease relapse, and chronic GVHD (cGVHD) were compared using Gray's test and analyzed using the cumulative incidence method. Competing events included in the cumulative incidence analysis for TRM, disease relapse, and cGVHD were relapse, death without relapse, and death without cGVHD, respectively. Of the 196 pairs in the study, four pairs had to be omitted from the TRM and disease relapse analysis due to a lack of data. The χ 2 test was used to analyze data on aGVHD and the achievement of neutrophil engraftment. aGVHD was defined as occurring up to 100 days post-transplantation. cGVHD was defined as occurring after 100 days post-transplantation.

Multivariate analysis was performed using Cox-regression analysis. Factors found to be significant in univariate analyses (α ≤ .2) were included in the model. These included recipient age, disease stage at transplantation, and HLA-DPB1 matching status in all three outcomes, donor age, cytomegalovirus serostatus of the recipient in OS and DFS, and stem cell source in disease relapse. For both univariate and multivariate analysis, P values were two sided and outcomes were considered to be significant with an α level of ≤ .05. A trend was identified when alpha levels were α = .05 to .1.

Three NOD2/CARD15 variants (SNPs 8, 12, and 13) were analyzed for 196 unrelated donor–HSCT pairs. The occurrence of any SNP in a recipient of an unrelated donor HSCT was found to be 13% and 17.3% in donors, resulting in an overall frequency of 27.6% (Table 2). The frequency of the individual SNPs were comparable in donors and recipients (Appendix Table A2, online only) and was similar to that previously published. 4,6

The median time of follow-up of surviving recipients in the cohort was 2.2 years, ranging from 0.42 to 6.61 years. The estimated three-year OS was 44% in WT pairs and 22% in pairs with SNPs of the NOD2/CARD15 gene (log-rank P = .0087 Fig 1A ). We investigated the reasons for the inferior OS. The presence of NOD2/CARD15 SNPs led to a significant increase in the incidence of disease relapse. The estimated 2-year incidence of disease relapse in SNP pairs was 54% compared with 32% of WT pairs (Gray test P = .001 Fig 1C ). The increase in disease relapse was reflected in a significantly worse DFS. The estimated 2-year DFS in WT pairs was 40% DFS as compared with a DFS of 19% in NOD2/CARD15 SNP pairs (log-rank P = .0047 Fig 1B ). These effects were significant in ALL but not AML ( Fig 2 ).

There were no significant differences in the impact of NOD2/CARD15 SNPs on TRM, neutrophil engraftment, aGVHD, or cGVHD. The incidence of clinically significant aGVHD in the group was low overall (grade 2 to 4: 43 of 171, 25% grade 3/4: 8 of 171, 5%).

Further analyses were performed to establish whether the effect of recipient or donor genotype was individually significant in transplantation outcome ( Fig 3 ). The presence of a NOD2/CARD15 SNP in the recipient genotype resulted in a reduced OS (log-rank, P = .01 Fig 3A ) and an increased incidence of disease relapse (Gray test, P = .005 Fig 3C ) when compared with those with a WT genotype. There was no significant impact of donor genotype on either of these variables ( Figs 3B and 3D ). Matching for NOD2/CARD15 genotype in a graft-versus-host direction also had similar effects on OS and relapse (P = .05 and P < .001, respectively) while matching in a host-versus-graft direction resulted in no significant differences (data not shown).

The impact of NOD2/CARD15 SNPs remained statistically significant in multivariate analyses for OS, DFS, and disease relapse (Table 3). Factors found to be significant in univariate analyses were included in the model (including stage at transplantation and HLA-DPB1 matching status in all three outcomes, donor age in OS, and stem cell source in relapse). The presence of a NOD2/CARD15 SNP within an unrelated donor-HSCT pair resulted in worse OS (relative risk [RR], 1.617 95% CI, 1.080 to 2.421 P = .02), reduced DFS (RR, 1.603 95% CI, 1.079 to 2.381 P = .02), and an increase in disease relapse (RR, 2.579 95% CI, 1.538 to 4.323 P < .001) when adjusted for the other factors in the models.

The NOD2 protein is known to function in innate immunity and SNPs in the NOD2/CARD15 gene have been linked to the occurrence of inflammatory bowel disorders. 16,19 Recent studies in HSCT identified significant associations between NOD2/CARD15 SNPs and reduced survival due to increased TRM, DFS, and the incidence of clinically significant aGVHD. 4-7 We have analyzed a large cohort of unrelated donor-HSCT pairs where recipients were diagnosed with acute leukemia. The primary and novel findings of this study are a highly significant impact of NOD2/CARD15 SNPs on disease relapse resulting in a significantly reduced survival for patients receiving transplantation from unrelated donors.

It has been shown by this study, and indeed by numerous others, that SNPs of the NOD2/CARD15 gene are implicated in immunological phenomena that affect either the onset or progression of malignant diseases. 20,21 The impact of the SNPs on relapse post-allograft is marked, but the exact mechanism of this effect is currently unknown. A second finding, although less marked, is that the presence of a SNP leads to a reduction in the occurrence of aGVHD. It is therefore possible that recipients with NOD2/CARD15 SNPs are incapable of mounting an efficient graft-versus-leukemia or GVHD response, resulting in increased disease relapse and protection from aGVHD. The graft-versus-leukemia effect is a complex series of events that involve the generation of tumor-specific cells targeting leukemic cells post-HSCT. The cells involved in this process are thought to be of T-cell origin although recent evidence points to a role for natural killer cells 22 and even possibly natural killer T cells. 23 It is thought to be caused by an immune reaction to genetic disparity, not unlike GVHD. In fact, certain theories propose that the two events stem from a common phenomenon, namely the cytokine storm, 24-26 an extreme increase in the production of cytokines that occurs during the early post-transplantation stages.

With this in mind, we postulate three possible mechanisms that may explain these data. Firstly, recent data have suggested that NOD2/CARD15 gene SNPs prevent its expression on the surface of epithelial cells. 27 This suggests that WT NOD2 is expressed on the surface of cells where cytosolic expression has been detected and also potentially on further, as yet unidentified, cell types. It is possible that the failure of leukemic cells to express NOD2 in recipients with NOD2/CARD15 variant genotype may lead to their evasion of the immune system, resulting in disease relapse. A second, indirect mechanism, is the inability of the NOD2 variant protein to initiate cytokine production. NOD2 is known to function as a regulator of cytokine production and a mediator of pro-inflammatory responses on recognition of the bacterial ligand muramyl dipeptide. While the effect of NOD2 SNPs are not yet known, numerous theories have been proposed that appear to argue for a loss or gain of function mechanism. 28-30 It is generally accepted that the NOD2/CARD15 SNPs downregulate expression of cytokines via the nuclear factor κB pathway (ie, cause a loss of function). 31 However, there is much controversy over what impact the SNPs have on the synergistic relationship with toll-like receptor 2, 32,33 and more specifically what subsequent impact this has on the production of interleukin-12 (IL-12). Recent studies have suggested SNPs of the NOD2/CARD15 genes actually result in either reduced or depleted levels of IL-12. 13 Interestingly, it has been reported that low levels of IL-12 are associated with an increase in disease relapse post-HSCT, 34 but without an increased incidence of aGVHD. 34,35 A third potential mechanism is that NOD2 acts as a minor histocompatibility antigen. We have been able to demonstrate that the impact of NOD2/CARD15 SNPs on transplantation outcome causes a more potent effect in a graft-versus-host direction. This may suggest that the mutated NOD2 protein initiates an immune response in the event of nonrecognition of host antigens.

The reduced incidence of both graft-versus-leukemia and GVHD responses in pairs with NOD2/CARD15 SNPs appear to be due predominantly to the recipient's genotype. The noticeable impact of recipient genotype suggests that expression of NOD2 protein in long-lived tissue cells that may survive conditioning chemotherapy, such as tissue macrophages, dendritic cells, and Paneth cells, is of critical importance particularly when other elements of the adaptive and innate immune systems have been compromised or inactivated by conditioning regimens and/or post-transplantation immunosuppression. These findings are further substantiated by evidence that host dendritic cells, which are known to express NOD2, are capable of causing aGVHD post-HSCT. 36 NOD2/CARD15 SNPs may directly affect antigen presentation on leukemic cells, which in turn would reduce graft-versus-leukemia and graft-versus-host responses. The near universal use of TCD, specifically in vivo alemtuzumab, in this cohort explains the low incidence of GVHD seen, and hence may mask a profound effect due to the NOD2/CARD15 SNPs.

We analyzed the data in AML and ALL separately. Interestingly, all of the results were highly significant in ALL but showed only trends in AML. A possible explanation may be that the number of AML cases in the study are insufficient to uncover an effect. Alternately, this may suggest that the mechanism and/or threshold for the graft-versus-leukemia effect differs between these two diseases. There were a greater number of transplantations performed in a late stage of disease in the ALL subgroup than in AML, 67% and 50%, respectively. This suggests that the effect of NOD2/CARD15 SNPs may be more prominent in high-risk disease. Cytogenetics are known to impact on transplantation outcome. 37 Unfortunately, cytogenetic data were not available in this cohort and future studies should aim to collect this data.

The data presented is in contrast to that published previously. 4-7 The reasons for this may be the numerous differences in the demographics of the cohorts, particularly that this study includes only unrelated donor and a high proportion of patients receiving bone marrow as the source of stem cells, both of which have been associated with a worse outcome in high-risk recipients. 38 Analysis was performed in order to establish whether there was a biased effect of SNPs in the different risk groups of recipients (ie, their stage of disease at transplant, bone marrow v peripheral blood stem cell). The presence of a SNP resulted in similar significant associations in all of these subgroups (data not shown). Another difference in this cohort was the high proportion of patients receiving TCD in conditioning regimens. This may in part explain the lack of significance between the presence of SNPs and aGVHD as the use of TCD is well known to result in significant reductions in GVHD. This theory is substantiated by data published by Granell et al 7 who also found no correlation between SNPs and the incidence of clinically significant aGVHD in T-cell depleted sibling transplantations. In concordance with the data presented, this group also noted a significant reduction in DFS in pairs with NOD2/CARD15 SNPs.

Recent studies have highlighted the importance of gastrointestinal decontamination protocols in the prediction of clinically significant GVHD and TRM attributable to NOD2/CARD15 SNPs. 4,5 The clinical data evaluated for this study did not include details on decontamination methods and therefore we are unable to make any correlations between them and the results observed. However, as mentioned previously, both this study and that by Granel et al 7 both reported a lack of association between NOD2/CARD15 SNPs and GVHD, which was attributed to a high use of TCD. It is possible that any association with gastrointestinal decontamination may have been masked again by the use of TCD.

The data presented confirm that the NOD2 protein is critically involved in the biology of transplantation. Further studies are required to ascertain whether the findings of this study can be extended to other disease groups or non-TCD transplantation protocols. In addition, recently identified SNPs 39,40 will require further studies to identify their relevance. We suggest that the prospective genotyping of recipients and donors will have a beneficial effect on transplantation outcome, not only reducing disease relapse, but also improving the chance of survival. Thus, genotyping may play a critical role in selecting donors and in the planning and administering conditioning regimens and post-transplantation immunosuppression.


As shown in Table 1, the frequency of major IL12B SNP allele (A rs3212227) was 81.4% in patients with breast cancer compared with 72.4% in healthy women (P = 0.003 OR = 1.67, 95% CI: 1.17–2.38 χ 2 : 8.75). This difference implies an association with 67% higher predisposition to the disease. On the other hand, carriers of the minor allele (C) had an association with 40% reduced disease risk, as it had a frequency of 18.6% in patients, compared with 27.6% in controls (P = 0.003 OR = 0.60 95% CI: 0.42–0.86).

IL12B b rs3212227 Patients a Controls a P OR Association
SNP (A>C) n = 382 n = 388
Allelic frequencies and number
1 A 0.814 (311) 0.724 (281) 0.003 1.67 (1.17–2.38) Predisposition
2 C 0.186 (71) 0.276 (107) 0.003 0.60 (0.42–0.86) Protection
  • SNP, single nucleotide polymorphism.
  • a Frequency (number).
  • b Allele designation (1 – major, 2 – minor allele).

The genotypic analysis of IL12B SNP frequencies showed also significant differences between cases and controls. As shown in Table 2, individuals homozygous for the major allele (AA) had an association with higher risk for breast cancer (P = 0.013 OR = 1.68, 95% CI: 1.09–2.59). High risk was also found for all carriers of the major allele (AA and AC), as 96.9% women with breast cancer (185/191) had the major allele compared with 91.2% women in healthy population (177/194), which was a statistically significant difference (P = 0.020 OR = 2.96, 95% CI: 1.07–8.62). In contrast, those that were homozygous for the minor allele (CC) had an association with protection from disease (P = 0.02 OR = 0.36, 95% CI: 0.13–0.94). However, heterozygous individuals had no significant association with either of the risks (P < 0.16), perhaps because both alleles neutralized each other’s association.

IL12B b,c rs3212227 Patients a Controls a P OR Association
SNP (A>C) n = 191 n = 194
Genotypic frequencies and number
1/1 A/A 0.660 (126) 0.536 (104) 0.013 1.68 (1.09–2.59) Predisposition
1/2 A/C 0.309 (59) 0.376 (73) 0.16
2/2 C/C 0.031 (6) 0.088 (17) 0.02 0.36 (0.13–0.94) Protection
  • SNP, single nucleotide polymorphism.
  • a Frequency (number).
  • b Allele designation (1 – major 2 – minor allele).
  • c Genotype designation.


Both coronary artery disease (CAD) and ischemic stroke (IS) are the major causes of morbidity and death in the developed countries, and are also the leading cause of long-term disability in survivors [1, 2]. Atherogenic dyslipidemia characterized by low levels of high-density lipoprotein cholesterol (HDL-C) and apolipoprotein (Apo) A1, high levels of total cholesterol (TC), triglyceride (TG) and low-density lipoprotein (LDL) particle number is highly associated with increased incidence of the cardiovascular disease [3] and IS [4, 5]. In addition, genetic factors are estimated to account for about 50–80% of the variation in serum lipid levels [6], and 30–60% of the incidence of CAD and IS [7]. Therefore, single nucleotide polymorphisms (SNPs) in the lipid-related genes may have some associations with serum lipid levels, and the risk of CAD and IS [8].

A few previous GWASes have proved that the breast cancer susceptibility gene 2 (BRCA2 Also knows as: FAD FACD FAD1 GLM3 BRCC2 FANCD PNCA2 FANCD1 XRCC11 BROVCA2, Gene ID: 675, HGNC ID: 1101, synonyms: “BRCA1/BRCA2-containing complex, subunit 2”, BRCC2, FAD, FAD1, XRCC11, locus type: gene with protein product, chromosomal location: 13q13.1) mutation can cause an increased risk for breast cancer [9]. Women carrying BRCA mutations have metabolic deregulations in their breast tissue that may be precursors to malignant transformation, and also lead to exhibit a reduction of 79% in metabolite level, while both lipid unsaturation and TG levels increased by 19%. Besides these, women carrying BRCA2 mutations showed an increased lipid unsaturation of 21% and the metabolic changes in women carrying BRCA1 mutations were different from those in women carrying BRCA2 mutations, with a 47% increase in cholesterol level recorded in those with BRCA2 mutations [10]. The mechanism was supposed to have a connection with lipid metabolism [11]. A previous GWAS on plasma lipid levels has identified the rs9534275 SNP near the BRCA2 as hyperlipidemic locus in European. And, several previous studies have shown that the BRCA2 rs9534275 may have an effect on TC, low-density lipoprotein cholesterol (LDL-C), and serum lipid levels might have ethnic- and/or sex-specificity [12, 13].

To our knowledge, the genetic evidence on the association between BRCA2 variants and atherosclerosis in humans is poor. In a previous study, we have found that the BRCA2 rs9534275 SNP modulated serum TC, LDL-C, ApoB concentrations, and the ApoA1/ApoB ratio in the hypercholesterolemic subjects [14], suggesting that the rs9534275 SNP plays an important role in the formation of atherosclerosis. Therefore, the present study aimed to determine whether the BRCA2 rs9534275 SNP is associated with the risk of CAD and IS in the Guangxi Han population.

References and Resources

The National Genographic Project uses SNPs to determine the earliest patterns of human migration.

The International HapMap Project is using SNPs to learn more about genetic variation in humans, and what implications this variation has for medicine.

A haplotype map of the human genome, based on information from SNPs, was published in Nature in 2005. Genomics: Understanding Human Diversity is a more accessible description of this publication.



Material on this page is offered under a Creative Commons license unless otherwise noted below.

Association between single nucleotide polymorphism of the CYP19A1 and ESR2 genes and endometriosis

Endometriosis is a frequent gynaecological condition, both in Poland and in the world. The development of this disease is supported by hormonal, immunological and environmental factors. During the recent years, a particular attention has been focused on the genetic polymorphisms which may be of particular significance for the increased incidence rates of endometriosis. According to literature data, Oestrogen Receptor 2 (ESR2) and Cytochrome P450 Family 19 Subfamily A Member 1 (CYP19A1) genes may be accounted to the potential risk factors of infertility associated with endometriosis. The reported research was aimed to evaluate the association between single nucleotide polymorphisms (SNPs) rs17179740 of ESR2 and rs2899470 of CYP19A1 genes and the incidence of endometriosis.


The study material included blood specimens, collected from patients (n = 200) with endometriosis. Blood samples from age-matched, endometriosis-free women (n = 200) served as control. The High-Resolution Melter (HRM) technique was applied for polymorphism analysis.


Regarding rs2899470 polymorphism TT homozygotes was significantly more prevalent among the patients with endometriosis than in the controls (OR 2.19 p = 0.04). In case of rs17179740, GG homozygotes, as well as AG-AA genotypes, were significantly more prevalent among the endometriosis patients (OR 2.48, p = 0.04 and OR 2.36, p = 0.04, respectively).


Summing up, the investigated polymorphisms of ESR2 and CYP19A1 gene are associated with the observed incidence of endometriosis.


In this acromegaly case-control study, we compared the rs2854744 genotype frequency in 102 acromegalic patients and 143 control group patients. In addition, we evaluated the association of the common polymorphism of IGFBP3 with the susceptibility to acromegaly, as well as with the susceptibility in subgroups of acromegaly. We found that IGFBP3 genetic variants were significantly correlated with an altered risk of acromegaly and that allele C of rs2854744 was strongly correlated with a decreased risk of acromegaly in the Han Chinese population.

IGFBP3 is the major transport protein for IGF-1, with IGFBP3 modulating the half-life and biological activities of IGF-1. Some cell culture studies have shown that IGFBP3 plays a vital role in cell survival or apoptosis in various microenvironments meanwhile, several clinical studies have indicated that variations in IGFBP3 levels are associated with an altered risk for certain common cancers [14]. More than half of the changes in IGFBP3 levels were identified to be genetically determined by the gene polymorphism at the − 202 locus of IGFBP3 [9]. Therefore, we attempted to identify whether polymorphic variation at the − 202 site constitutes a risk factor for acromegaly, an important type of pituitary tumour disorder.

The rs2854744 polymorphism is situated 202 base pairs (bp) upstream of the transcription start site of IGFBP3 and has been reported to control promoter activity. The A allele has been proven to be correlated with higher promoter activity. The AA genotype was associated with higher IGFBP-3 circulating levels, which have been previously shown to be associated with a decreased risk of most cancers [15, 16]. This is because IGFBP3 commonly displays growth inhibition and pro-apoptosis properties, and IGFBP3 has been recognized as an inhibitor of IGF activity by blocking the binding of IGF to its receptor. In our study, we found that the AA genotype showed a tendency for an association with higher IGFBP3 serum levels, although the difference was not statistically significant (P = 0.331), which may be explained by the small sample size. At first, we hypothesized that the AA genotype at the − 202 site of the IGFBP-3 gene might be associated with a decreased risk of acromegaly. However, our results showed that the C allele was actually correlated with a decreased acromegaly risk. Using the A allele as a reference, the OR for the C allele was 0.594 (95% CI 0.388–0.909). The multivariate analysis showed that this association was still significant after adjusting for age, sex, and smoking and drinking status. This may be because IGFBP3 has been identified as being able to enhance the activity of IGF by protecting IGF from degradation under certain circumstances [17, 18]. In addition, IGFBP3 is capable of acting via an IGF-independent mechanism to promote cell growth and survival, such as by binding the 78 kDa glucose-regulated protein (GRP78), by inducing autography, and by promoting non-homologous end-joining (NHEJ) repair during genotoxic stress [14]. These results might explain why the acromegaly risk was decreased with the C allele in the current study.

Additionally, the varying allele frequencies among different ethnicities, geographies and populations may yield conflicting results regarding IGFBP3 polymorphisms and cancer risk. A large-scale urinary bladder cancer study based on a multiethnic population residing in Germany and Hungary demonstrated that the C allele (55%) was slightly more frequent than the A allele (45%) at the − 202 site of the IGFBP-3 gene [19], which was significantly different from our participants’ allele distributions. However, a cancer study involving Korean and Japanese [20] adults indicated that the A allele (65–80%) was appreciably more frequent than the C allele (20–35%) and that the C allele was correlated with a reduced non-small cell lung cancer risk [21]. The genotypic distribution and study results of the Asian population were similar to those of our population.

Furthermore, our results showed that the association between the C allele of rs2854744 and a decreased risk of acromegaly was more significant in females, those with large tumours and those treated with monotherapy. IGFBP3 levels have been reported to be correlated with the stage and prognosis of cancer [6, 22, 23]. Several studies have found that some SNPs have different effects on cancer susceptibility between genders [24, 25]. We analysed genetic polymorphism and acromegaly risk in different subgroups. The results of our study were in some accordance with the results of the previously mentioned studies.

Our study had a few advantages. First, this was one of the first acromegaly case-control studies examining the relationship between the IGFBP3 -202A/C polymorphism and acromegaly risk. Second, we conducted an analysis of subgroups according to sex, treatment method and adenoma size, since pituitary adenomas possess diverse clinical manifestations, and the IGFBP3 gene may be associated with a specific subtype.

However, several limitations existed in the present study. First, we only selected acromegaly inpatients confirmed by postoperative pathology from Beijing Tiantan Hospital, which might have led to a selection bias. Second, as the groups with a CC genotype had fewer participants, comparisons with the AA group had limited statistical significance. Third, we did not perform functional research to confirm our findings.


Population genetic parameter, LD among SNP markers, identification of non-synonymous mutations in candidate genes, differences in relative gene expression between resistant and susceptible goats, and associations with FEC involving both individual SNP genotypes and SNP haplotypes can be used to advance our understanding of options to utilize selective breeding and molecular markers to improve resistance to H. contortus and other GIN in goats. Ten SNP within six candidate genes were associated with FEC and provided a suite of potential molecular markers for further study and possible use in screening individuals for resistance to H. contortus.

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