Evidence for an Epistatic Effect between <i>TP53</i> R72P and <i>MDM2</i> T309G SNPs in HIV Infection: A Cross-Sectional Study in Women from South Brazil

<div><p>Objective</p><p>To investigate the associations of <i>TP53</i> R72P and <i>MDM2</i> T309G SNPs with HPV infection status, HPV oncogenic risk and HIV infection status.</p><p>Design</p><p>Cross-sectional study combining two groups (150 HIV-negative and 100 HIV-positive) of women.</p><p>Methods</p><p>Data was collected using a closed questionnaire. DNA was extracted from cervical samples. HPV infection status was determined by nested-PCR, and HPV oncogenic risk group by Sanger sequencing. Both SNPS were genotyped by PCR-RFLP. Crude and adjusted associations involving each exposure (R72P and T309G SNPs, as well as 13 models of epistasis) and each outcome (HPV status, HPV oncogenic risk group and HIV infection) were assessed using logistic regression.</p><p>Results</p><p>R72P SNP was protectively associated with HPV status (overdominant model), as well as T309G SNP with HPV oncogenic risk (strongest in the overdominant model). No epistatic model was associated with HPV status, but a dominant (R72P over T309G) protective epistatic effect was observed for HPV oncogenic risk. HIV status was strongly associated (risk factor) with different epistatic models, especially in models based on a visual inspection of the results. Moreover, HIV status was evidenced to be an effect mediator of the associations involving HPV oncogenic risk.</p><p>Conclusions</p><p>We found evidence for a role of R72P and T309G SNPs in HPV status and HPV oncogenic risk (respectively), and strong associations were found for an epistatic effect in HIV status. Prospective studies in larger samples are warranted to validate our findings, which point to a novel role of these SNPs in HIV infection.</p></div

Associations between 11 epistatic models and HPV status.

<p>^*The epistatic models were numbered as described previously <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089489#pone.0089489-Hartwig1" target="_blank">[46]</a>.</p>†<p>The “_” indicates that the effect is irrespective of the allele. E.g., R72P G309_ represents the genotypic combinations R72P T309G - R72P G309G.</p>¥<p>Other: <b>3.1</b>:_72_ T309_ - R72R _309_. <b>3.2</b>: R72_ _309_ - _72_ T309T. <b>4</b>: P72_ _309_ - _72_ G309_. <b>5</b>: P72P _309_ - _72_ G309G. <b>6</b>: R72R G309_ - P72_ T309T. <b>7</b>: P72P T309_ - R72_ G309G.</p

OR (with 95% CI) for the association (adjusted for skin color and age) between combined genotypes of the two SNPs and HIV status.

<p>OR (with 95% CI) for the association (adjusted for skin color and age) between combined genotypes of the two SNPs and HIV status.</p

Associations between 11 epistatic models and HPV oncogenic risk.

<p>^*The epistatic models were numbered as described previously <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089489#pone.0089489-Hartwig1" target="_blank">[46]</a>.</p>†<p>The “_” indicates that the effect is irrespective of the allele. E.g., R72P G309_ represents the genotypic combinations R72P T309G - R72P G309G.</p>¥<p>Other: <b>3.1</b>: _72_ T309_ - R72R _309_. <b>3.2</b>: R72_ _309_ - _72_ T309T. <b>4</b>: P72_ _309_ - _72_ G309_. <b>5</b>: P72P _309_ - _72_ G309G. <b>6</b>: R72R G309_ - P72_ T309T. <b>7</b>: P72P T309_ - R72_ G309G.</p

Crude and adjusted associations [showing OR (95% CI) and p-values] between R72P and T309G SNPs and HPV status.

<p>^*“A” and “a” correspond to wild-type (i.e., either R72 or T309) and variant alleles (i.e., either P72 or G309), respectively.</p

Associations between 11 epistatic models and HIV status.

<p>^*The epistatic models were numbered as described previously <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089489#pone.0089489-Hartwig1" target="_blank">[46]</a>.</p>†<p>The “_” indicates that the effect is irrespective of the allele. E.g., R72P G309_ represents the genotypic combinations R72P T309G - R72P G309G.</p>¥<p>Other: <b>3.1</b>: _72_ T309_ - R72R _309_. <b>3.2</b>: R72_ _309_ - _72_ T309T. <b>4</b>: P72_ _309_ - _72_ G309_. <b>5</b>: P72P _309_ - _72_ G309G. <b>6</b>: R72R G309_ - P72_ T309T. <b>7</b>: P72P T309_ - R72_ G309G.</p

Crude and adjusted associations [showing OR (95% CI) and p-values] between R72P and T309G SNPs and HPV oncogenic risk.

<p>^*“A” and “a” correspond to wild-type (i.e., either R72 or T309) and variant alleles (i.e., either P72 or G309), respectively.</p

Descriptive analyses of the sample, comparing the HIV groups.

<p>^*Fisher's exact test.</p>†<p>Chi-square test.</p

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21 août 19321932/08/21 (A12,N4236)-1932/08/21

Table1.docx

<p>Some mammalian reference genes, which are widely used to normalize the qRT-PCR, could not be used for this purpose due to its high expression variation. The normalization with false reference genes leads to misinterpretation of results. The silversides (Odontesthes spp.) has been used as models for evolutionary, osmoregulatory and environmental pollution studies but, up to now, there are no studies about reference genes in any Odontesthes species. Furthermore, many studies on silversides have used reference genes without previous validations. Thus, present study aimed to was to clone and sequence potential reference genes, thereby identifying the best ones in Odontesthes humensis considering different tissues, ages and conditions. For this purpose, animals belonging to three ages (adults, juveniles, and immature) were exposed to control, Roundup®, and seawater treatments for 24 h. Blood samples were subjected to flow-cytometry and other collected tissues to RNA extraction; cDNA synthesis; molecular cloning; DNA sequencing; and qRT-PCR. The candidate genes tested included 18s, actb, ef1a, eif3g, gapdh, h3a, atp1a, and tuba. Gene expression results were analyzed using five algorithms that ranked the candidate genes. The flow-cytometry data showed that the environmental challenges could trigger a systemic response in the treated fish. Even during this systemic physiological disorder, the consensus analysis of gene expression revealed h3a to be the most stable gene expression when only the treatments were considered. On the other hand, tuba was the least stable gene in the control and gapdh was the least stable in both Roundup® and seawater groups. In conclusion, the consensus analyses of different tissues, ages, and treatments groups revealed that h3a is the most stable gene whereas gapdh and tuba are the least stable genes, even being considered two constitutive genes.</p