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1. Interindividual Variability and Lateralization of μ-Opioid Receptors in the Human Brain

   Critiqued Article

   Kantonen, T., Karjalainen, T., Isojarvi, J., Nuutila, P., Tuisku, J., Rinne, J., Hietala, J., Kaasinen, V., Kalliokoski, K., Scheinin, H., Hirvonen, J., Vehtari, A., & Nummenmaa, L. (2020). Interindividual variability and lateralization of μ-opioid receptors in the human brain, NeuroImage, 217(116922), 1-8 . https://doi.org/10.1016/j.neuroimage.2020.116922  

    

   Date of Submission:

    

    

   Interindividual Variability and Lateralization of μ-Opioid Receptors in the Human Brain

   Summary

   Background and Rationale

               Alteration in μ-opioid receptor (MOR) system in the human brain is associated with development of various neuropsychiatric disorders. Availability of MOR is also found to vary significantly across different healthy individuals. Several epidemiological factors have been demonstrated to have an impact in influencing the MOR system; however, the magnitude of such influence was found to be inconclusive due to use of small sample sizes (Kantonen et al., 2020). The rationale for carry-out ¹¹C]carfentanil positron emission tomography (PET) study is that evidence from previous studies are not open for generalization due generally small sample sizes (20 to 40). [¹¹C]carfentanil is an agonist tracer that preferably binds to MORs in the high-affinitiy-state (Kantonen et al., 2020). Endogenous opioids tend to compete with [¹¹C]carfentanil for MOR binding sites. [¹¹C]carfentanil has been found to be proportional to density of MOR (Kantonen et al., 2020).

               Poorly replicable previous neuroimaging findings are attributed to uncertain measurements, inappropriate correction for multiple comparisons, ubiquitous ‘degrees of freedom’, and small sample size (Kantonen et al., 2020).  Stricter statistical thresholds and use of larger samples have been suggested as strategies for improving reproducibility of PET neuroimaging studies (Kantonen et al., 2020).

   Aim: To determine whether MOR density is lateralized in vivo in healthy individuals.

   Hypothesis and Research Methods

               The investigators compiled data from 204 individuals who had [¹¹C]carfentanil PET scans but had no psychiatric or neurologic disorders. The in vivo molecular images had been taken and hosted by Turku PET center. PET images of individuals who had no psychiatric or neurologic disorders have been scanned using [¹¹C]carfentanil PET scanning between 2003 and 2018 in baseline condition (Kantonen et al., 2020). [¹¹C]carfentanil PET scans from 204 individuals were taken from five PET scanners and 11 research projects. During the time of taking the PET scans no subject had abused illicit drugs, alcohol, or any medication that affects the central nervous system. Among 204 individuals whose data was used were 132 males and 72 females; in this 13 females were smokers, while none of the male subject was a smoker (Kantonen et al., 2020).  The effects of variables such as sex, smoking, and body mass index (BMI) on ¹¹C]carfentanil binding potential was estimated though utilization of between-subject regression analysis. The differences of MOR availability were examined in both hemispheres (Kantonen et al., 2020).

               The investigators used Bayesian hierarchical modeling so as to promote reproducibility of research findings by restricting the number of paths in which investigators took in their analyses as well as by eliminating the need to correct for multiple-comparisons (Kantonen et al., 2020). Bayesian hierarchical modeling with varying intercepts and slopes for various brain regions so as to estimate the effect of body mass index, age, smoking, and sex on availability of MOR in the cerebral cortex and cerebral lateralization of the MOR system (Kantonen et al., 2020). The investigators took into consideration confounding variables including handedness and smoking status in their study. Tracer binding of [¹¹C]carfentanil was quantified using an outcome measure referred to as binding potential. Binding potential is the ratio of specific-binding to non-displaceable-binding in tissue. Binding potential was estimated through the use of simplified reference-tissue model; whereby the occipital cortex served as the reference region (Kantonen et al., 2020). Binding potential is a product of affinity of the radioligand to the receptor and density of the target receptors, which is occupied by endogenous ligands (Kantonen et al., 2020).

               Ethical implications of the study also observed in the study. The investigators used data from human subjects but in a retrospective manner.  Since the study utilized retrospective data and was register-based, the need for informed consent was waived (Kantonen et al., 2020). However, the publication does not provide any identifiable information of the study subjects; thus, confidentiality and privacy were maintained. The study had been approved by the Turku University Hospital Clinical Research Services (Kantonen et al., 2020).

   Hypothesis:  Factors such as age, sex, body mass index, and smoking has a positive impact on determining MORs cerebral lateralization and variability in both brain hemispheres (Kantonen et al., 2020).

   Control Experiments and Key Results

               Age, sex, and smoking were found to have regionally-specific influence on the availability of human MOR in the brain. Besides, MOR availabilities were established to demonstrate regional asymmetries in both hemispheres; left hemisphere being less abundant in MORs compared with the right hemisphere (Kantonen et al., 2020). Across both male and female subjects in the study, it was evident the MORs were broadly expressed in the brain. Binding potential of [¹¹C]carfentanil decreased with age in thalamus, amygdala, cerebellum, and nucleus accumbens; conversely it increased with age in the frontal cortex and the temporal regions in the brain (Kantonen et al., 2020). The positive associations between [¹¹C]carfentanil binding potential and density of MORs was stronger in male subjects. In male subjects, it was also observed that [¹¹C]carfentanil binding potential tend to increase with age in the insula and putamen (Kantonen et al., 2020).

               In almost all regions of interest, the means binding potential was found to be higher among females who were 20 years old compared to males who were 20 years old. The binding potential of [¹¹C]carfentanil with age increases much faster in males than in females; however, sex differences tend to decrease up to 30 years of age, when binding potential in males surpasses that of females in most brain regions (Kantonen et al., 2020). In the study, brain regions such as the nucleus accumbens, thalamus, temporal pole, and amygdala did not demonstrated any notable sex difference at any age. Body mass index is not a relevant predictor of the availability of MORs (Kantonen et al., 2020).

               In most brain regions such as the caudate, thalamus, cingulate cortex, putamen, and orbitofrontal cortex, binding potential of [¹¹C]carfentanil on MORs was found to be higher in the right hemisphere. The binding potential of [¹¹C]carfentanil was only higher in the amygdala and the nucleus accumbens in the left hemisphere compared to the right hemisphere. Lateralization was found to be consistent in both sexes. Lateralization towards the right hemisphere is also consistent in right-handed and left-handed individuals (Kantonen et al., 2020).  

                                                                          Analysis

   Analysis of Application/Generalizability of Results

   As opposed to previous studies that used a small sample size (20 to 40 research participants), the investigators used a large sample size (collected data from 204 subjects retrospectively); thus, the findings from the study are open for generalization. However, generalizability is only limited to people aged between 20 years and 60 years (Kantonen et al., 2020). Besides, the investigators provided a precise methodology; thus, the study can be repeated to check for reproducibility of study results (Kantonen et al., 2020).

   The study is also important in informing smoking cessation efforts. This is because it was established that smokers ten to report decreased [¹¹C]carfentanil binding potential on MORs compared to non-smokers. [¹¹C]carfentanil binding potential reduces among smokers by 8% to 14% compared to non-smokers. The reduced [¹¹C]carfentanil binding potential on MORs was more prominent in subcortical regions such as striatum and amygdala. Therefore, smokers are likely to be administered opioid medications in slightly higher doses than non-smokers. Besides, smokers may experience increased risk of opioid overdose compared to non-smokers (Kantonen et al., 2020). 

   Critical Evaluation of Research Shortcoming

   Investigators retrieved data from AIVO database in a retrospective manner. Therefore, significant biases may have occurred in selection of potential research subjects. Subjects who whose PET scans were used in the study were recruited by convergence sampling approach; hence, findings may not be representative of the general population. But use of a large sample size may be used to justify generalizability of evidence but only to people aged between 20 and 60 years (Kantonen et al., 2020).  Besides, the investigators had not power to control PET scanning and outcome assessment but relied on others for accurate recordkeeping, which cannot be ascertained. For example, in the study, the investigators acknowledged that retrospective data was not detailed since the phase of menstrual cycle and possible menopause among female subjects were not recorded. Compared with prospective studies, retrospective studies may have inferior level of evidence (Kantonen et al., 2020).

   Another limitation is that the data was drawn from eleven different projects that used five different PET scanners; therefore, consistency of measurement cannot be guaranteed. PET scanners may generate different [¹¹C]carfentanil biding potential estimates, despite the fact the that the scanners were cross-calibrated. However, the investigators attempted to correct for potential scanner-associated biases in their analyses. There were only 13 female smokers, no male smoker and seven left-handed subjects; therefore, there are concerns that the findings may not be fully representative for all sub-groups (Kantonen et al., 2020).

   Ideas for Subsequent Experiments

   Findings tend to answer the original research question since factors such as age, sex, and smoking were found to have positive impact on determining MORs cerebral lateralization and variability in both brain hemispheres. However, body mass index had no significant impact on determining [¹¹C]carfentanil  binding on MOR (Kantonen et al., 2020). The study failed to explain age-related decrease [¹¹C]carfentanil  binding potential in amygdala, thalamus, and nucleus accumbens, thus, this need to be answered by the future studies (Kantonen et al., 2020).

   To improve generalizability and strength of evidence, a prospective study need to be conducted in which subjects need to be recruited in a random manner. Variables such as smoking, sex, and age have a significant influence on [¹¹C]carfentanil binding potential in MORs in the brain. However, body mass index does not seem to influence [¹¹C]carfentanil binding in the brain. A major finding is that [¹¹C]carfentanil binding potential is significantly higher in the right hemisphere compared with the left hemisphere in both sexes. On another hand, [¹¹C]carfentanil binding potential on MORs tend to reduce with age, in both sexes, in brain regions such as the nucleus accumbens, amygdala, thalamus, and  cerebellum; however, the mechanism of this observed change has not been described and need to be described in future studies. Besides, investigators recommended that future studies should examine how OPRM1A118G polymorphism influences/determines lateralization and expression of MORs (Kantonen et al., 2020).

   Personal Response

   Explanation and Justification of Personal Reaction

               This particular field of study is of interest to me since I would like to expand my knowledge and understanding on addiction research and the basis for development of neuropsychiatric disorders as well as chronic pain. Dysregulation of MOR system can lead to development of several disorders including post-traumatic stress disorder, schizophrenia, major depression, obesity, and drug addiction. Variability and density of MORs can significantly contribute to variation in response to treatment and development of different psychiatric conditions (Kantonen et al., 2020). 

   New Learning/ Understanding Acquired

               I have learnt that distribution and availability of MOR in the brain vary from one brain hemisphere to the other and may also vary with age of the individual. MORs has been described as important mediators for the reward system as well as for analgesia. Besides, endogenous opioids are important regulators for social behavior, mood, and endocrine function (Kantonen et al., 2020).   Age, smoking and sex influences cerebral MOR availability. Decreases availability of MOR in the amygdala and thalamus, can possible reflect age-related pain related changes in pain processes or neurodegeneration. On the other hand, increased availability of MORs in the frontotemporal regions may be due to the compensatory processes aimed at reducing endogenous opioid concentrations. Age-related increase in MOR density on [¹¹C]carfentanil PET can be explained by increase in receptor density but not due to increase in receptor affinity. MOR receptors are possibly up-regulated so as to compensate for reduced endogenous opioid drive (Kantonen et al., 2020).

               MOR availability tend to increase in males faster in males than in females and this may be explained by sex differences in hormonal modulation of the MOR system. Smoking can cause down-regulation of MOR receptors; possibly through continuous activation of MORs. Besides, another important point is that the MOR system tends to manifest with consistent but rather minor hemispheric asymmetry (Kantonen et al., 2020). Sex and age may, in part, help to explain variability of the MOR system. Neurobiological differences may help to explain as to why some individuals are susceptible to neurobiological disorders; particularly MOR-linked pathological states such as neuropsychiatric disorders and chronic pain (Kantonen et al., 2020).

   Personal Interest/ Application of Research Field

               A large sample size (204) and evidenced-based research methodology opens the way for generalizability of findings in the study. However, generalizability is only limited to people aged between 20 years and 60 years. Variability of MORs system provides a window into developing an understanding as to why some individuals are more vulnerable to neuropsychiatric disorders and chronic pain compared to others. Variation in terms of distribution and availability of MORs in the brain hemispheres is important since endogenous opioids tend to modular several homeostatic and physiological functions. I have also learned that body mass index and obesity have no significant influence on determining lateralization and expression of MORs; thus, these factors may not be taken into consideration when determining dosage of opioid medications.

               Differences in binding potential of [¹¹C]carfentanil in different brain regions may indicate changes in brain structure and function with age in terms of changes in MORs density. Besides, differences in [¹¹C]carfentanil binding potential in most brain regions in males and females across different age groups may indicate differences in MORs density in the brains of both sexes. Therefore, it is imperative that different approaches and understanding of the female and brain function is necessary in studies that aims to research on opioid addiction. Besides, similar approaches may be indicated in studies on neuropsychiatric disorders and chronic pain. Relevance of the article in my life experience is that density of MORs and lateralization seem to change with age in most brain regions; hence, understanding of opioid addition, chronic pain, and neuropsychiatric disorders may be different across different age groups as a result of MORs lateralization and changes in density with age.

    

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Answer

Assessing Risk and Reward

The Nissan Motor Company is one of the leading automobile makers in the world. The Japanese carmaker has primarily enjoyed a successful run, allowing it to enter various regional and international markets such as the United States. However, the changing business environment was not favorable to the company in 2019. Notably, the cooperation recorded losses amounting to 7.8%. The experience pushed the management into making tough decisions, requiring almost all of its North American workforce to go for unpaid leaves.

In late 2019, the company announced that the decline in sales necessitated a two-day unpaid leave for the North American workers. The stated days for the vacation were January 2 and 3^rd    (Chicago Tribune, 2019).  Notably, this move was a crucial decision for the company because of its conflicting impacts. Whereas on the positive side, it could help the firm minimize expenses, it threatened to affect the public perception of the company regarding employee welfare.

The rewards for the decision involved cutting expenses by not paying the workers on leave, which eventually would translate into reduced expenses. Another reward was that the decision could allow the company to optimize performance by evaluating employee performances then developing new milestones. However, on the low side, the company risked affecting its public image and brand name, especially in the North American market. As per Chakravorti (2010), the way an organization treats its employees influences the firm’s public perception. Thus, Nissan risked eliciting a negative public perception. With a distorted public image, the company could fail to revive its declining sales.

I would have advised the management of Nissan to utilize the Predictive Analytic perspective in determining the right decision to take. Ideally, the approach tries to predict what might happen in the future if particular decisions or actions are undertaken at the moment (Traymbak & Aggarwal, 2019). Looking at the situation at Nissan, the company needed to develop a goal such as increasing sales. After that, they would have made decisions aimed at realizing the set goal. In this regard, the predicted outcome could give the management an overview of whether more risks existed or significant rewards could be realized.

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