Review article
Twin studies of the covariation of pain with depression and anxiety: A systematic review and re-evaluation of critical needs

https://doi.org/10.1016/j.neubiorev.2020.01.015Get rights and content

Highlights

  • Covariation of pain with depression-anxiety is due to both genetic and environmental factors.

  • There is lack of longitudinal studies examining these covariations.

  • More standardized measurement tools and child and adolescent cohorts are needed.

Abstract

Pain often co-occurs with depression and anxiety, and together cause considerable social and economic burden. Twin studies have investigated the aetiology of these covariations. However, to our knowledge, no systematic review examining the covariation between these conditions has been conducted. We searched the Cochrane Database of Systematic Reviews, EMBASE, MEDLINE, and PsychInfo for twin studies examining the covariation between pain with depression and/or anxiety published from inception to May 16, 2019. Included studies reported: original data on twin samples using the classical twin or co-twin control designs; investigated the association between pain and depression and/or anxiety; were published in peer-reviewed journals; used validated measures; included ≥100 twin pairs. Of 359 retrieved articles, 23 met our inclusion criteria. Most studies found that the covariation of pain with depression and/or anxiety was explained by genetic (n = 6) or both genetic and environmental (n = 16) factors. Most studies were cross-sectional, and all were led in adult populations. Future research requires the use of more standardized measurement tools, including quantitative sensory testing as well as assess child-adolescent cohorts.

Introduction

Pain is a major global health concern that can affect all people regardless of age, sex, income, ethnicity, or geography. Studies found that 20 % of adults worldwide suffer from pain, and 10 % are newly diagnosed with a chronic form (lasting 3 or more months) each year (Goldberg and McGee, 2011; Treede et al., 2015; N. MHB, 1994). Pain begins early in life with approximately 8–12 % of adolescents and 16 % of youth/young adults experiencing chronic pain at one or more sites of the body (King et al., 2011; H R-MPG, 2020; Dunn et al., 2011). Pain, especially when chronic, creates considerable burden on individuals and their loved ones by negatively affecting their ability to perform daily activities and have relationships with others (Reid et al., 2011; Froud et al., 2014). According to the World Health Organization’s (WHO) Global Burden of Disease Study, pain (lower back, neck, musculoskeletal, migraine, and falls) account for 5 of the top 10 conditions that cause significant health burden in terms of years lived with disability (Vos et al., 2012). The financial burden of chronic pain on patients, caregivers, healthcare systems, and economies is also substantial. Roughly, 1.5–3.0 % of Europe’s gross domestic product (GDP) is spent on chronic pain, $6 billion is spent annually in Canada, and $560-635 billion is spent in the United States of America (USA) (Henschke et al., 2015; D PCS, 2008; Lynch, 2011). Annually, the USA’s healthcare spending relating to pain is greater than heart disease ($309 billion), cancer ($243 billion), and diabetes ($188 billion) (Gaskin and Richard, 2012).

One of the unique features of studying pain is that it is based on personal perceptions and experiences. While the amount of pressure or temperature applied to a limb assessed in a laboratory-controlled context can be measured, the intensity and affective experience of pain remains highly subjective. This subjectivity can create a challenge for standardising research methodologies. While only a portion of the population suffers from chronic pain, all individuals can be characterized on a continuum of nociception. Nociception refers to the nervous system's response to a variety of potentially harmful stimuli and is often at the origin of a painful experience (Prescott et al., 2014). Signals from diverse peripheral stimuli (e.g., thermal or mechanical) reach the central nervous system and trigger physiological and behavioural responses that result in the experience of pain. One tool for standardizing the type and intensity of pain-evoking stimuli is Quantitative Sensory Testing (QST). This tool allows one to map the construct of nociception as well as quantify chronic pain in healthy individuals and clinical research participants (Yarnitsky and Granot, 2006).

Chronic pain often co-occurs with mental health conditions, such as anxiety, depression, and substance use disorders. This co-occurrence might be due to the overlapping neurobiology of these conditions (Hooten, 2016; Bair et al., 2003; Gallagher and Verma, 1999; McWilliams et al., 2003). Anxiety, depression, and chronic pain can also coexist in individuals and together are associated with poorer health status when compared to the presence of one condition alone (Lovibond and Lovibond, 1995; Krishnan et al., 1985; Bair et al., 2008; Moussavi et al., 2007). Similar to pain, anxiety and depression cause substantial societal and economic burden. Across the 36 largest countries in the world, an estimated 12 billion days of lost productivity (costing roughly $925 billion USD) occurs annually due to these conditions (Chisholm et al., 2016). According to the WHO, the number of people suffering from these mental health conditions increased from 416 million to 615 million worldwide between 1990 and 2013, a growth of nearly 50 % (Organization WH., 2019).

A complex relationship exists between pain, depression, and anxiety (Bair et al., 2003; McWilliams et al., 2004; Tham et al., 2016; Patten et al., 2015; Crow et al., 2013). However, most research examining the covariation between these conditions was conducted in clinical populations with relatively small and skewed cohorts. Since co-occurring symptoms of these conditions can begin early in life and persist over time, investigating pain, depression, and anxiety in population-based longitudinal studies can provide a better understanding of their covariation (King et al., 2011; H R-MPG, 2020; Dunn et al., 2011). A recent longitudinal Canadian cohort study found a significant association between childhood trajectories of high separation anxiety and headache (Battaglia et al., 2016, 2017a). Analyses of the National Longitudinal Survey of Children and Youth (NLSCY) further found longitudinal associations between anxiety/depression and headache, stomach-ache, and backache (H R-MPG, 2020; Stanford et al., 2008).

The complex relationship between pain, anxiety and depression resonates also in prescription patterns. In the USA, approximately 115 million opioid prescriptions are distributed each year with 51.4 % (60 million prescriptions) dispensed to adults with depression or anxiety (Davis et al., 2017). More concerning, 16 % of individuals who have mental health conditions receive over half of all opioids prescribed in the USA. This further illustrates the need to better understand the covariation between pain with anxiety and depression as it can help improve pain management and reduce the national opioid crisis (Davis et al., 2017) Among adolescents in the USA, anxiety disorders and benzodiazepine prescriptions are amongst the strongest predictors of transitioning from a first opioid prescription to long-term opioid treatment. Furthermore, the presence of chronic pain (without cancer) doubles the cumulative incidence of long-term opioid treatment within 3 years of filling the first prescription (Quinn et al., 2018). Currently, opioid treatment of chronic pain has had serious health implications and its improper use is implicated in the epidemic of addictions and overdose deaths (Volkow and McLellan, 2016).

The co-occurrence between pain, anxiety, and depression may partly be explained by the overlapping biological underpinnings of these conditions. One way to assess the shared factors underlying the association is to examine them using a genetically-informative study design. This, in turn, can address epidemiological questions (e.g. the role of anxiety/depression as risk factors for pain) and clarify the co-occurrence between two or more phenotypes (e.g., anxiety and pain) due to shared genetic and environmental factors.

Twin studies are a special type of genetically informative investigation designed to measure the contribution of genetic and environmental sources to individual differences for a given trait (Rende et al., 1990; Calais-Ferreira et al., 2018). In the classical twin design, monozygotic (MZ) twin pairs are compared with dizygotic (DZ) twin pairs for one or more co-existing traits. In this model, it is assumed that MZ twin pairs share 100 % of their genetic additive variation, while DZ twin pairs share 50 %. Moreover, the shared environment (i.e. rearing environment that makes individuals in the same family alike) is assumed equal for MZ and DZ pairs (Calais-Ferreira et al., 2018). By modelling the difference between the similarity of MZ and DZ pairs for a given trait, it is possible to estimate the influence of genetic factors (often symbolized as A, hence a2 = heritability) as well as the influences of shared (C) and non-shared, or unique, (E) environment (Calais-Ferreira et al., 2018). Shared environmental influences refer to experiences shared by twins in the same family that enhance their similarity, such as socioeconomic status or diet. Non-shared environmental influences refer to events that each twin in the same pair experience differently (e.g., different relationships with peers and parents) and result in increased dissimilarity (Calais-Ferreira et al., 2018; Rijsdijk and Sham, 2002). Non-shared effects also includes measurement error. 37 Moreover, when the cross-twin/within-trait correlation between MZ pairs exceeds twice the correlation between DZ pairs, this suggests dominance (D) effects, which classical twin studies can estimate along with additive genetic effects and non-shared environmental effects (Rijsdijk and Sham, 2002; Sahu and Prasuna, 2016).

The classical twin study design can be used to examine the genetic and environmental factors contributing to the association (i.e. phenotypic correlation) between two or more traits. This allows one to examine the degree of overlap between the genetic, shared environmental, and unique environmental effects influencing two or more traits (i.e., their genetic correlation, rG; shared environmental, rC; and unique environmental, rE) simultaneously. It can further estimate the extent to which a phenotypic correlation between two traits is accounted by genetic and environmental factors effects shared between two phenotypes. In the co-twin control study design, discordant ‘affected’ and ‘healthy control’ twins are matched within twin pairs for several potential confounding variables (genes, shared environmental factors, age, sex when using same-sex pairs), and is especially valuable when comparing MZ twins (Calais-Ferreira et al., 2018; Sahu and Prasuna, 2016). In the co-twin control study design, one can investigate whether the phenotypic association between two or more traits is better accounted for by a direct causal effect (phenotype A causes B, or vice-versa). Moreover, one can assess if the association remains significant when repeating analyses in discordant DZ and MZ pairs, by unmeasured familial (genetic + shared environmental) confounding effects (if the association becomes non-significant in discordant DZ and MZ pairs), or by unmeasured genetic effects (if the association becomes non-significant only in discordant MZ pairs) (De Moor et al., 2008).

Finally, clinical pain and internalizing mental disorders (e.g., anxiety and depression) are more prevalent in women than in men (Reid et al., 2011; McWilliams et al., 2003; Canada S., 2020). Twin studies can test for sex differences by estimating if the sources of variation/covariation differ in magnitude between sexes, and whether the same or different sets of genes and environmental factors explain individual differences in males vs. females when DZ twins of opposite sex are included (Meier et al., 2011).

Overall, the social and economic burden caused by pain, depression, and anxiety warrants an assessment of their co-variation by examining aetiological models, diagnostic reformulations, and treatment strategies. Twin studies can contribute significantly to establishing formative evidence needed to improve scientific investigations and clinical practice. However, to our knowledge, no synthesis of the twin literature on the co-occurrence of pain with anxiety and depression exists. A previous review summarized results from twin studies of pain and identified 3 major limitations in the literature: the extended use of dichotomous outcome measures, lack of adoption of pain intensity as a continuous key phenotype, and paucity of experimental twin studies of pain proclivity (i.e. assessing pain via quantitative sensory testing, QST) (Nielsen et al., 2012). The objective of this systematic review is to summarise and evaluate studies that explored the covariation between pain, depression, and/or anxiety using a twin study design.

Section snippets

Methods

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al., 2009). Institutional review board approval was waived as no patient data were accessed for the study.

Study selection

A total of 359 articles that matched the search criteria were retrieved across all databases, with 247 references remaining after duplicates were removed. Although no a priori language restriction was applied in the literature search, all studies were in English. After reading the abstracts, 211 studies were excluded for not presenting original or relevant data and 36 articles underwent a full-text review. Thirteen articles were excluded for the following reasons: cohort size less than 100 twin

Summary and explanation of the systematic review findings

This is the first systematic review, to our knowledge, to synthesize available twin data examining the covariation between pain with depression and anxiety. Our findings indicate that multiple mechanisms, including shared genetic influences, explain the association between these health conditions. Specifically, classical twin studies found genetic correlations between different forms of pain and anxiety, depression, or anxiety-depression that ranged between 0.27 and 0.65. Shared and non-shared

Declaration of Competing Interest

The authors have no conflicts of interest relevant to the content of this report.

Acknowledgment

This research was supported by a Cundill Foundation bursary to WUK

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