DOI: 10.35407/bag.2022.33.02.01

ARTÍCULOS ORIGINALES

Variability of PDYN and OPRK1 genes in four argentinian populations and its genetic association with clinical variables related to acute postsurgical pain

Variabilidad de los genes PDYN y OPRK1 en cuatro poblaciones argentinas y su asociación con variables clínicas relacionadas al dolor agudo post-quirúrgico

 

Di Santo Meztler G.P.^1,2

Schiaffi J. ³

Rigalli A. ⁴

Esteban Torné M.E. ⁵

Martina P.F. ⁶

Catanesi C.I. ^{2,7 *}  

 

¹ CIProVe-Centro Asociado CICPBA-UNLP,  Depto. de Cs. Biológicas, Facultad de Cs.  Exactas, UNLP, La Plata, Argentina. 

² Laboratorio de Diversidad Genetica,  Instituto Multidisciplinario de Biología  Celular- IMBICE (CONICET CCT-La Plata;  CICPBA; UNLP), La Plata, Argentina. 

³ Servicio de Ginecología del Hospital General de Agudos Bernardino Rivadavia,  Ciudad Autonoma de Buenos Aires,  Argentina. 

⁴ Centro Universitario de estudios  Medioambientales, Facultad de Ciencias  Médicas, Universidad Nacional de Rosario,  Rosario, Santa Fe, Argentina. 

⁵ Section of Zoology and Biological  Anthropology, Department of Evolutionary  Biology, Ecology, and Environmental Sciences, and Biodiversity Research Institute, University of Barcelona,  Barcelona. 

⁶ Facultad de Cs. Exactas, Químicas  y Naturales, Universidad Nacional de Misiones, Posadas, Misiones, Argentina.  

⁷ Facultad de Cs. Naturales y Museo, Universidad Nacional de La Plata (UNLP),  La Plata, Buenos Aires. 

 

* Corresponding author: Catanesi, Cecilia Ines  ccatanesi@imbice.gov.ar  ORCID 0000-0002-5970-5027 

 

ABSTRACT

Several population studies showed an association between variation in pain sensitivity and genetic  polymorphisms located in Prodynorphin (PDYN) and Kappa Opioid Receptor (OPRK1) human genes.  We analysed polymorphisms of these two genes to characterise their variation in Argentinian  populations, as well as to evaluate their association with acute pain sensitivity. We studied 11  genetic markers in individuals from four locations in Argentina (Ciudad Autónoma de Buenos  Aires, La Plata, Resistencia, and Misión Nueva Pompeya), calculated the population parameters,  and evaluated the possible association among pain sensitivity, clinical, and genetic variables  through a Generalised Estimating Equation model. High linkage disequilibrium was observed in  the four populations for both genes, and significant differences were found among frequencies of  Argentinian populations and those from other continents reported in the 1000 Genomes Project.  Four PDYN gene polymorphisms from 3´ untranslated region and exon 4 showed association  with acute pain sensitivity. One genotype of each of these polymorphisms was associated with a  higher pain sensitivity, probably related with the activation of the N-methyl-D-aspartate (NMDA)  receptors. We found a strong association with acute pain for the following clinical variables: 1)  time after surgery, 2) intravenous klosidol supplied every 8 h, and 3) type of incision. Our results  highlight the importance of a regional study of genetic variants which influence pain sensitivity  and analgesic response. 

Key words: Human populations, Pain sensitivity, Acute pain, Genetic polymorphisms, Genetic structure 

 

RESUMEN

La asociación entre la sensibilidad al dolor y los polimorfismos que presentan los genes humanos  de prodinorfina (PDYN) y receptor opioide kappa (OPRK1) se ha evidenciado en distintos estudios  poblacionales. Con el objetivo de caracterizar la variación de estos genes y evaluar su asociación con  dolor agudo en la población argentina, analizamos 11 polimorfismos en individuos provenientes de  cuatro localidades argentinas (Ciudad Autónoma de Buenos Aires, La Plata, Resistencia, y Misión  Nueva Pompeya). Calculamos los parámetros poblacionales y evaluamos la posible asociación entre  sensibilidad al dolor, variables clínicas y variables genéticas a través de un modelo de ecuación  generalizada de estimación. Se observó alto desequilibrio de ligamiento para ambos genes en las  cuatro poblaciones analizadas, y se encontraron diferencias significativas entre las frecuencias de  poblaciones argentinas y las reportadas en el Proyecto 1000 Genomes para poblaciones de otros  continentes. Cuatro polimorfismos de la región 3´UTR y el exón 4 de PDYN mostraron asociación  con la sensibilidad al dolor agudo. En cada uno de estos polimorfismos, un genotipo resultó  asociado con alta sensibilidad al dolor, probablemente en relación con la activación de receptores  N-metil-D-aspartato (NMDA). Encontramos una fuerte asociación con dolor agudo para las  siguientes variables clínicas: 1) tiempo post-cirugía, 2) administración intravenosa de klosidol  cada 8 h, y 3) tipo de incisión. Nuestros resultados resaltan la importancia de realizar estudios  regionales de variables genéticas que influyen en la sensibilidad al dolor y la respuesta analgésica. 

Palabras clave: Poblaciones humanas, Sensibilidad al dolor, Dolor agudo, Polimorfismos genéticos, Estructura genética

 

Received: 08/20/2021

Revised version received: 02/04/2022 

Accepted: 05/03/2022 

 

General Editor: Elsa Camadro 

 

 

INTRODUCTION

 

 

The available information on the human genome gives  a starting point for searching in different populations  and among individuals for genome variability related  to pain sensitivity and to the effectiveness of different  drugs in pain relief (Owusu Obeng et al., 2017; Crews  et al. 2021). The human prodynorphin gene (PDYN),  located on chromosome 20, encodes α-neoendorphin,  β-neoendorphin, dynorphin A and dynorphin B. These  molecules selectively activate kappa opioid receptors  (KOR), encoded by OPRK1 gene, which is located on  chromosome 8 (Schwarzer, 2009; Hashemi et al., 2018).  Genetic association studies gave evidence of a link  among certain DNA sequence variants of both genes  and various pathologies, including cognitive disorders  and drug abuse, as well as variations in pain sensitivity  (Clarke et al., 2012; Hashemi et al., 2018; Nosova et al.,  2021). 

It has been reported that an efficient management  of postoperative acute pain is essential not only for  improving the wellness of the patient, but also for  reducing the risk of chronicity of pain, morbidity  and mortality (Carr and Goudas, 1999). Genetic  polymorphisms can explain some of the variation in  response to analgesics, while other important variables  also involved are the sex of the patient, the intensity and  kind of pain, the environmental influences, and several  psychological aspects including among others, anxiety  and somatization (Stamer and Stüber, 2007; Schreiber  et al., 2014). 

The challenge is to decipher the biological basis of  such a complex phenotype, considering pain perception  and response to analgesic drugs, both showing clear  differences among populations of distinct origins. In  Argentina, the current population is the result of several  generations of intermixing among various groups at  different times, including indigenous (Amerindian)  communities, Spanish conquerors (early 1500s), Africans  (arriving as slaves since the late 1500s until the end of  slavery), and a large European immigrant population  (arriving between 1870 and 1950) (Avena et al., 2006).  In this work we analyse four different populations from  Argentina, namely from Ciudad Autónoma de Buenos  Aires (CABA), La Plata, Resistencia, and Misión Nueva  Pompeya (MNP).  Historical events  Ciudad Autónoma de Buenos Aires (CABA) is the  capital city of Argentina and it has by far the largest  population in the country. During the second half of  the 20th century, a significant demographic increment  occurred in Argentina, mainly due to migratory flows  (Gallo and Cortés Conde, 1967). From 1940 onwards,  the industrial development encouraged people to move  to CABA from other provinces of Argentina and from  bordering countries bringing their indigenous genetic  component (Torrado, 1992). While the European  migratory contribution declined after 1930, immigrants  from bordering countries are currently increasing the  foreigner’s contribution to the city (Avena et al., 2001).  La Plata is the capital city of Buenos Aires province.  Located 56 km southeast from CABA, it is the fourth  most populous city in the country. As in CABA, an  important European contribution in the past century is  currently complemented by the arrival of populations  from bordering countries looking for employment  (Cerrutti, 2009).  In the case of Chaco province, it was originally  inhabited by native people until 1528, when the first  Europeans arrived. In 1872, a group of people from the  province of Corrientes and Italian immigrants settled in  this region. The city of Resistencia was then founded, and  in 1884 it was assigned as the capital of the province of  Chaco (De Pompert de Valenzuela, 2008; Tissera, 2008).  At the end of the 19th century, European immigration to  Resistencia was in order to promote urbanization and  agricultural development (Maeder, 2012). 

In 1900, the Franciscan missionaries founded the  location of Misión Nueva Pompeya (MNP) in the western  region of this province known as the Impenetrable  Chaqueño. Currently, an important number of Native  American people of the Wichí community still live in this  inner region (Franceschi, 2010).  A previous report on the urban people living in MNP  estimated a native contribution of 25% uniparental  genetic markers (Sevini et al., 2013). In fact, within  the province of Chaco, Native American people from  different communities live nearby several cities, and  they still retain their traditional semi nomadic habits.  The numerical importance of these native communities  puts Chaco at present among the provinces with the  highest number of living Native American people in  Argentina (Instituto Nacional de Asuntos Indígenas,  2005).  Previous studies have shown genetic differences  between these four populations using non coding X  chromosome markers (SNPs, INDELs and STRs) (Di  Santo Meztler, 2018; Di Santo Meztler et al., 2019). Also,  differences between a native Wichí community of Chaco  and the population of Resistencia were found in the  OPRK1 gene (Raggio et al., 2018). 

In this work, our aim was to analyse whether  interpopulation differences observed for non-coding  genetic markers are also noticeable in coding regions,  particularly for two genes of the opioid system and,  therefore, to understand whether those differences  have influence on the perception of pain. In particular,  we focused on the genetic variability of PDYN and OPRK1  in four Argentinian populations. Genetic association  with clinical variants influencing pain sensitivity was  analysed for one of the populations, particularly after a  surgical intervention.

 

 

MATERIALS AND METHODS

 

 

Populations

 

 

Between 2009-2012 we collected a total of 286 samples  from adult, unrelated persons from four different  locations in Argentina: the capital city of Argentina,  CABA (n=106), the capital city of Buenos Aires province,  La Plata (n=33), the capital city of Chaco province,  Resistencia (n=96), and a small city of Chaco province,  MNP (n=54). Figure 1 shows a map indicating these  locations. Samples from La Plata, Resistencia and  MNP consisted of both male and female donors, and  were collected during three field trips. Samples from  CABA were only female donors, which were collected  at Gynecology Service´s Breast Pathology Section of  the Hospital General de Agudos Bernardino Rivadavia.  The intensity of perceived pain and the requirement  of analgesia after gynecological surgery were recorded  for 50 out of 106 females from CABA. After discarding  individuals with one or more missing data, the genetic  association study was performed for a sample size of 35  females.  DNA was isolated from buccal and blood cells  following protocols described in Gemmel and Akiyama (1996). OPRK1 data for the population of Resistencia  were previously reported in Raggio et al. (2018) and  were included in this work for comparison. All biological  samples were genotyped by author G. P. Di Santo Meztler  at the Instituto Multidisciplinario de Biología Celular  (IMBICE).  This study was part of a project previously approved  by the Ethics Committee of the IMBICE, and all donors  gave written consent for participation in the study. 

 

Figure 1. Location of the Argentinian populations analysed in this work.  1 = Ciudad Autónoma de Buenos Aires, 2 = La Plata, 3 = Resistencia,  4 = Misión Nueva Pompeya.

 

 

Genetic determinations

 

 

Eight polymorphisms (rs35286281, rs1997794,  rs2235751, rs6045819, rs10485703, rs910080, rs910079,  and rs2235749) were genotyped for PDYN gene, and  three polymorphisms (rs35566036, rs3808627 and  rs6985606) for OPRK1 gene (Table 1). Genotyping was  performed by PCR and separation of amplified fragments  in 1.8% agarose gels, except for rs10485703, rs910080,  rs910079 and rs2235749, which were amplified together  in a fragment by PCR and then sequenced. For rs35286281  VNTR polymorphism, alleles were designated as  1(271pb), 2(339pb), 3(407pb) or 4(475pb) based on  the number of repeated elements that were identified.  Such elements contain a transcription factor binding  site that is associated with transcriptional efficiency of  the human PDYN gene, and higher gene expression is  associated with repeated alleles 3 or 4 (Zimprich et al.,  2000). Therefore, the alleles 1 and 2 were categorised  as low (L), and the alleles 3 and 4 as high (H) gene  expression. 

 

Table 1. Change and location of the analysed polymorphisms

 

Primers for PDYN VNTR were obtained from  Nikoshkov et al. (2008), primers for the SNPs located  in the 3´ untranslated region (3´-UTR) of the gene were  obtained from Yuferov et al. (2009), and primers for  rs1997794, rs2235751 and rs6045819 were designed for  this work (Supplementary Table 1).  Primers for OPRK1 INDEL (rs35566036) were obtained  from Edenberg et al. (2008) and allele specific primers  for OPRK1 SNPs were designed in our lab and reported in  Raggio et al. (2018). 

 

 

Statistical analysis

 

 

Population study

 

 

For the genetic polymorphisms, allele frequencies  were calculated using R v. 3.6.3 program (R Core Team,  2021). Heterozygosity, Hardy-Weinberg equilibrium  (HWE) and genetic distance (as pairwise Fst values)  were calculated through the program ARLEQUIN v.3.5  (Excoffier and Lischer, 2010), and linkage disequilibrium  (LD) was calculated using the webtool SNPStats (Solé  et al., 2006) for obtaining both D´ and r values. In the  case of repetitive polymorphism rs35286281, the alleles  were pooled into short (271 and 339) and long (407 and 475) given that extreme alleles (271 and 475) are very  infrequent, so that pooling them would produce no  bias. The adaptation of the tables for R program and  ARLEQUIN was made using GA-TA program (https://github.com/santimda/GA-TA) (Gamboa Lerena et  al., 2020). For population comparisons, data of four  populations from 1000 Genomes database were included:  Japanese in Tokyo (JPT); Mexican ancestry from Los  Angeles (MXL), California, USA; residents of Utah with  North and Western European ancestry (CEU) and Yoruba  in Ibadan, Nigeria (YRI). Allele frequencies of these  reference populations are detailed in Supplementary  Table 2.  Association study  For the association study we considered only females  from the sample of CABA without missing data (n=35).  We analysed the variation of pain informed by the  physicians in a follow-up of 1, 2, 12 and 24 h after  surgery; although the observations were informed by  different surgeons, all pain reports were registered  under supervision of author J. Schiaffi. For this analysis  two models were evaluated: in one case the dependent  variable was the pain scale reported by the physician, who  considered wound palpation, analgesia requirement,  possibility of walking, and pain escalation according to  medical impression (model M); while in the other model  the scale was reported by the patient according to selfperception  (model P).  The independent variables used in both models were  the above mentioned polymorphisms of PDYN and  OPRK1 genes (Table 1), and the clinical variables time  after surgery, age of the patient, dose of intravenous  Klosidol (Bagó Laboratory, Argentina) -which consists  of a combination of dextropropoxyphene hydrochloride and dipyrone, supplied every 8 h according to pain  intensity-, associated pathologies, and type of incision  (Table 2). The type of incision depended on the type  of surgery, which was either gynecological surgery  (Median Infraumbilical laparotomy, and Pfannenstiel  laparotomy incisions) or breast surgery (Radian,  Arcuate, and Stewart mastectomy -Orr type- incisions).  The analyses were made using R v.3.6.3, and GEE  (Generalised Estimating Equation) model fitting was  performed with the geepack library (Halekoh et al., 2006). 

 

Table 2. Clinical variables included in the analysis

 

 

RESULTS

 

 

Population genetic analysis

 

 

Allele frequencies for the PDYN and OPRK1  polymorphisms are detailed in Table 3, and genotype  frequencies in Supplementary Table 3. In the case  of MNP, for rs35286281 the frequency of genotype  339/407 was higher than in the other populations,  and for rs6045819 genotype G/G was absent. In none  of the populations the genotype C/C was observed for  rs10485703. In the case of Resistencia, for rs35566036  the frequency of genotype del/del was higher and  that of the genotype in/del was lower than in the other  populations.  For MNP, all the polymorphisms fitted HWE  (p-value>0.05), but for the other three populations  some of the markers did not fit HWE (Table 3). As we  expected, linkage disequilibrium for PDYN gene was  considerably high in all the populations. CABA and  Resistencia showed higher LD than La Plata and MNP.  For OPRK1 the LD was lower in Resistencia and La Plata,  while in CABA and MNP there were significant values of  LD for all the markers (Supplementary Table 4).   

 

Table 3. Allele frequencies and Hardy-Weinberg Equilibrium p-values for the polymorphisms analysed. For biallelic polymorphisms, one of the allele  frequencies is showed.

 

Table 4. Pairwise genetic distances (Fst values) for SNP markers among the analysed populations and data from the 1000  Genomes Project. Above the diagonal: Fst values for OPRK markers; and below the diagonal: Fst values for PDYN markers.  Significant Fst values (p-value <0.05) are highlighted in bold.

 

The genetic distances were calculated for all the  populations, and Fst with p-values lower than 0.05  were considered as significant (Tables 4 and 5). All four  Argentinian populations showed significant differences  with Africans from the Yoruba tribe in both genes, and  also with Asians from Japan in PDYN, but differences in  OPRK1 resulted only significant for Resistencia. On the  contrary, OPRK1 resulted in significant values in the  comparison with Europeans, while no differences were  found when comparing with Mexicans for these two  genes. Within Argentina, no differences were found for  the SNPs comparisons (Table 4), whereas rs35566036  INDEL of OPRK1 showed a differentiation among  Resistencia and the other three Argentine populations,  and rs5286281 VNTR of PDYN resulted significant only  for CABA-MNP (Table 5). 

 

 Table 5. Genetic differentiation (pairwise Fst values) for OPRK1 INDEL (rs35566036) and PDYN VNTR  (rs35286281), among the analysed populations, and in comparison to data from other reports.  Significant values (p<0.05) are in bold.

 

 

Association Study

 

 

GEE analysis

Two GEE models were used to evaluate the association  of the reported pain scale with the following variables:  age of the patient (Age), dose of intravenous  dextropropoxyphene hydrochloride + dipyrone every 8  hrs (Ke8), associated pathologies (AP), type of incision  (I), time after surgery (Time) and the genotypes for each  polymorphism. Model M was based on the pain scale  reported by the physician (MScale) and Model P on the  pain reported by the patient (PScale). Thus, 

• Model M-->MScale(Time, Age, AP, Ke8, I, genetic  polymorphisms)

• Model P-->PScale(Time, Age, AP, Ke8, I, genetic  polymorphisms) 

 

For this study we used 7 out of 11 genetic  polymorphisms that fitted HWE (p-value>0.05). We only  focused on these polymorphisms for the association  study in order to avoid statistical artifacts of markers out  of HWE, probably given by the sample size, so that we can  reach an accurate association between genetic markers  and pain. The ANOVA p-values obtained with the GEE  models are shown in Table 6, where p-values<0.01 were  considered as significant values. 

 

Table 6 A. ANOVA p-values obtained for two  models of Generalised Estimating Equation. Model  M uses the pain scale reported by the physician  as a dependent variable, while Model P uses the  pain scale reported by the patient. Significant  p-values (p<0.01) indicate the clinical variables  and/or genetic variants that influence pain  susceptibility.

 

Table 6 B. Influence of clinical variables (Time, Ke8, I, AP and Age) on the pain scale reported  by the physician or the patient. Coefficients, deviation standard and p-values of the  generalised estimating equation (GEE). For each variable, the influence of the levels in the  sensitivity to pain is shown. Negative coefficients for a level indicates lower pain respect to  the reference level (coefficient for reference equals to zero).

 

After analysing the results of the previous GEE  models, three clinical variables presented a strong  association with pain (p-value<0.01) for the model M:  Time, Ke8, and I, while for Model P only Time and I were  significant. Regarding genetic polymorphisms, 5 out of  7 were significant for model M while 2 out of 7 resulted  significant for Model P (Table 6A). Once the variables  influencing pain sensation were identified, the analysis was focused within each level of the clinical variables  and polymorphisms, taking into account one level per  variable as a reference.  The reference level were 1 h after surgery (Time1),  no analgesia rescue (Ke8(No)), Median Infraumbilical  Laparotomy (I1), and no associated pathology (AP(No)),  which were set at a coefficient value of zero (Table 6B).  Thus, negative coefficients indicate pain decrease in  comparison to the reference case. Postsurgical acute  pain intensity was found to decrease as time increased  in hours in both models, showing negative coefficients:  Time 2(-1), Time 12(-1.556), Time 24(-2.259) for model  M. The action of analgesia rescue (Ke8Yes) resulted in  the same direction, showing a high negative coefficient.  Additionally, an ANOVA analysis was performed  considering Time separately for one surgical incision  at a time. ANOVA results for the first and second  hours after the intervention were non-significant, but  differences emerged for the reports at 12 and 24 h after  incision (data not shown). The Pfannenstiel, Radian,  Arcuate, and Orr surgery incisions showed a higher  decrease of pain scale, with respect to the reference type  of incision (Median Infraumbilical Laparotomy), being  Pfannenstiel, Radian and Orr, the types of incision that  presented the most important decrease in pain scale in  both models.  Regarding genetic polymorphisms, in Model M the  associated genotypes with lower pain sensitivity were  rs6045819-A/G, rs10485703-C/T, rs910080-C/C,  rs910079-C/C, and rs2235749-T/T, while for Model P  the associated genotypes with lower pain sensitivity  were rs6045819-A/G and rs35566036-del/del.    

 

 

 DISCUSSION

 

 

The genetic basis influencing postoperative pain  through the screening for variations in the expression  of genes coding for endogenous opioid system is a field  of interest for improving pain therapies (Stamer and  Stüber, 2007; Montes et al., 2015; Owusu Obeng et al.,  2017; Crews et al., 2021).  In this work we analysed the genetic diversity of PDYN  and OPRK1 in Argentinian populations from different  geographic locations, and the relationship between  the genetic polymorphisms and the postsurgical pain,  considering variables such as the use of analgesia and  the different types of incisions.  Our results show that the genetic background of  the Argentinian population differs in some aspects  from that of other countries and continents (Avena et  al., 2006; Hohl et al., 2018). In a previous report, the  variation of OPRM1 gene of the opioid system allowed  to group Argentinians with other populations according  to their ancestry, with 12.8% of differentiation among  Africans, Asians, and European-Americans for this gene  (López Soto and Catanesi, 2015).  Genetic differences have also been found among  different regions or provinces within Argentina, for  several genetic polymorphisms, whether they were  coding or non-coding markers (Corach et al., 2006;  Avena et al., 2012; Di Santo Meztler et al., 2018; Muzzio  et al., 2018; Sala et al., 2018; Caputo et al., 2021, among  others). Interestingly, some differences emerged even  when comparing Resistencia and MNP, which are  located in the same province and only 425 km apart,  as it was previously reported for non-coding markers  (Di Santo Meztler et al., 2019). Our results showed less  genetic differentiation among Argentinian populations,  probably because the polymorphisms here analyzed  are located in coding regions, having less chances for  displaying variability. However, a significant Fst value  was found between populations from CABA and MNP  for the PDYN VNTR. This differentiation could be caused  by the heterogeneous origin of immigrants from other  continents, mainly Europeans from various countries  who have settled in the past in particular locations along  the territory of Argentina, as in CABA (Junta de Estudios  Históricos del Municipio de Eldorado, 2015, 2016; Di  Santo Meztler et al., 2018). As opposed, MNP is somehow  isolated due to hard weather conditions and floods that  discourage immigration. 

 

 

Clinical variables

 

 

 As several aspects of a surgical intervention can  influence pain sensitivity, in this work we considered  the interaction of both clinical variables and genetic  variants.  When considering the evaluation of pain scale, the  physician integrated the knowledge of the patient and the  type of surgery performed, the questioning, the medical  examination, and the data of the medical record (such as  use of analgesics, calls to the nurse, rescue medication,  etc.). Therefore, we considered that an evaluation by the  professional (pain scale reported by the physician) is  more trustworthy, and, in fact, significant associations  of three clinical variables were found when analysing  the medical pain scale.  Among the clinical variables to be taken into account,  significant differences in reported pain scores were  found according to the type of surgery. Although in the  first two hours after the surgical intervention there  were no differences between types of incision for pain  scores, differences emerged as time increased, likely  as a consequence of the severity of incision, being  additionally influenced by biological factors as the  genetic polymorphisms here analysed. Specifically,  laparotomy incisions usually caused much higher pain  scores on the first and second day after surgery than  breast surgery incisions (either conservative or radical  breast surgery). The results obtained in this work are  in accordance with the grade of aggressivity of each  incision. Pfannenstiel laparotomy involves the handling  of the aponeurosis, thus giving a high pain sensation  at the beginning but recovering faster in comparison  to Radian, and even faster in comparison to Arcuate,  and Orr incisions, which are less aggressive and usually  cause a lower level of pain sensation from the beginning.  On the contrary, Median laparotomy is the more  aggressive, and the level of pain sensation likely persists  more constantly along the first two days after surgery.  Concerning the analgesic rescues, in general Klosidol  was known to be well-tolerated as analgesia of choice  for postsurgical pain in Latin American populations  from Bolivia and Argentina, with a good balance cost/  benefit when it was prescribed for relief of postsurgical  pain treatment (Daza Calderón et al., 2010). However,  this combination of dextropropoxyphene and dipyrone  was discontinued more recently because of some  serious adverse effects that were reported for European  populations (ANMAT, 2008). As expected, the analgesic  rescues indicated in our study had a significant effect  in decreasing the pain sensation during the first hours  after surgery. 

 

 

Genetic variables

 

 

Antinociception mediated by dynorphin and kappa  receptors is known to be influenced by the sex of the  patient, among other biological factors (Liu et al., 2013).  Moreover, the effect of certain PDYN polymorphisms  has been reported showing sexual dimorphism, with a  higher impact on females (Clarke et al., 2012). Therefore,  analysing genotype-phenotype association only in  females avoids confounding results in this sense.  Among the genetic variants that we analysed, an  association with pain sensitivity in the physician model  was observed for one SNP (rs6045819) in the exon  4 and four SNPs (rs10485703, rs910080, rs910079,  and rs2235749) in the 3´-UTR of PDYN. Genotypes  associated with higher pain sensitivity were GG for  rs6045819 and TT, TT, TT and CC respectively for 3´-  UTR polymorphisms. There is evidence that exon 4  could be involved in PDYN splicing. This is supported  by the significant association of the risk allele G (SNP  rs6045819) with alcohol and/or cocaine dependence  (Xuei et al., 2006; Yuferov et al., 2009). This risk allele  could form a non-canonical E-box, which is a target  of binding transcription factors that could modulate  PDYN transcription, thus increasing the expression  levels (Taqui, 2011). Regarding SNPs in the 3´-UTR of  the gene, they are located close to each other, resulting  in a significant LD among them (Supplementary Table  4). This genetic linkage is stronger among rs910080,  rs910079 and rs2235749, likely transmitted in a block.  This result is consistent with the finding that rs910079  can be chosen as a reporter of the block (Yuferov et  al., 2009). In addition, the haplotype rs910080-C /  rs910079-C / rs2235749-T has been proposed to be  associated with a lower level of gene expression (Yuferov  et al., 2009).  Several works show that dynorphins inhibit  nociceptive transmission in the spinal cord via interaction  with the kappa opioid receptor (Werz and Macdonald,  1985; Randic et al., 1995; Rusin et al., 1997; Wiley et al.,  1997; Zachariou and Goldstein, 1997; Ogura and Kita,  2000). However, other authors have found evidence of  dynorphin A having pronociceptive functions (Draisci  et al., 1991; Dubner and Ruda, 1992; Riley et al., 1996;  Vanderah et al., 1996et al., 1996; Wagner and Deleo, 1996;  Laughlin et al., 1997; Malan et al., 2000; Laughlin et al.,  2001). The switch between anti or pronociceptive effects  of dynorphin A may depend on peptide concentrations,  and kinetics of peptide interactions with either opioid or  NMDA (N-methyl-D-aspartate) receptors. Dynorphins  at physiological concentrations may be antinociceptive  through the opioid receptors, typically playing an  inhibitory role in acute pain conditions, whereas elevated  pathophysiological levels may be pronociceptive and can  interact with the NMDA receptors (Hauser et al., 1999;  Tan-No et al., 2009). During peripheral inflammation,  dynorphin induces its own synthesis through interaction  with NMDA receptors, generating a regenerative, feedforward  process (Laughlin et al., 2001).  In our work, we found genotypes that are associated  with a high pain sensitivity and, according to  bibliography, induce the expression of PDYN. We  suggest that an overexpression of PDYN after surgery, in  particular in patients with these genotypes, is giving rise  to an activation of NMDA receptors, causing increased  sensitivity to pain. 

Concerning OPRK1 gene, due to its wide presence in the  central nervous system, its expression has been related  to pain perception and behavioral traits as depression  and drug abuse (Edenberg et al., 2008; Bruchas et al.,  2010). The INDEL of OPRK1, rs35566036, was nearly  significant for the model M. Different authors arrived  to dissimilar conclusions on the importance of this  polymorphism, either reporting a lack of association  of this INDEL with the requirement of analgesia (Chatti  et al., 2017), or finding a regulatory effect on gene  expression in vitro for the longer allele (insertion), thus  acting as a transcriptional promoter with effect on a  complex phenotype of alcohol dependence (Edenberg et  al., 2008). Our results are not conclusive for this matter,  although the p-value near significance is suggestive  of an influence of OPRK1 INDEL on pain sensitivity.  Increasing the sample number is probably needed in  order to obtain a more accurate result. 

Several previous reports on PDYN and OPRK1 variation  refer in general to dependence either on alcohol or  drugs of abuse, given the abundance of dynorphin and  kappa receptors on brain connections related to the  formation of habits (Edenberg et al., 2008; Zhang et  al., 2008; Dahl et al., 2018; Hashemi et al., 2018) and to  emotional processing (Xu et al., 2013). Other reports  consider the influence of PDYN and OPRK1 variants on  pain modulation, mainly focused on chronic pain (Rosen  et al., 2000; Wang et al., 2001; Podvin et al., 2016; Tian et  al., 2018). Our results give an approach to the influence  of the variation of both genes in pain, and suggest an  association with levels of acute pain sensitivity and  hyperalgesia after surgical intervention.   

 

 

Concluding remarks

 

 

This is the first report on Argentinian population for  PDYN variation, while information available on OPRK1  variation and pain sensitivity in the same population  is scarce (Raggio et al., 2018), an unfavorable scene  given the geographic extent and the heterogeneity of  Argentinian people.  The results presented in this work show differences  between Argentinians and populations from other  continents, even in the comparison to Europeans,  suggesting that a component of admixture with Native  American people probably reinforce the differences.  This, however, cannot be confirmed due to the scarce  available information for Native Americans on variation  of the genes of the endogenous opioid system (Ehlers et  al., 1998; Raggio et al., 2018) and other genes related to  pain perception (Catanesi and Glesmann, 2015; López-  Cortés et al., 2020). For this reason, an analysis on other  populations of the region with known admixture with  Native communities is needed. Although the number of  individuals included in the analysis needs to be further  increased, a genetic association with postsurgical acute  pain phenotype has been found.  These findings highlight the importance of a regional  study of genetic variants influencing pain sensitivity and  analgesic response, in tune with the current tendency of  a personal therapy medicine.  

 

ACKNOWLEDGEMENTS 

This research was supported by  grants from Consejo Nacional  de Investigaciones Científicas y  Técnicas (CONICET, Argentina,  PIP 2015-2017/0930), Agencia Nacional de Promoción Científica y Tecnológica (PICT  -2020-SERIEA-01075), and from  Universidad Nacional de La Plata  (UNLP, Argentina, PID 2019-  2020/N895). We would like to  acknowledge Dr. Laura Angela  Glesmann, MSc. Raúl Jorge Bridi  and Dr. María Celeste Raggio for  being part of the field trips for  sample collection. We also thank  Mr. Eduardo César Bauzá for the  English language revision, and  two anonymous reviewers of the  manuscript. 

 

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