March, 2014, San Francisco, Annual Meeting of the American Psychosomatic Society
Parallel session: The genetic basis of quality of life in healthy Swedish women - a candidate gene approach.
Authors: Schoormans D, Li JM, Darabi H, Brandberg Y, Sprangers M, Eriksson M, Zwinderman K, Hall P.
Background:Quality of life (QoL) is an increasingly important parameter in clinical practice as it predicts mortality and poor health outcomes. It is hypothesized that one may have a genetic predisposition for QoL. We therefore related 139 candidate genes, selected through a literature search, to QoL in healthy females.
Methods:In 5,142 healthy females, background characteristics (i.e. demographic,clinical, lifestyle, and psychological factors) were assessed. QoL was measured by the EORTC QLQ-C30, which consists of 15 domains. For all women genotype
information was available. For each candidate gene, single nucleotide polymorphisms (SNPs) were identified based on their functional (n=2,663) and physical annotation (n=10,649). SNPs were related to each QoL-domain, while controlling for background characteristics. Finally, gene-based analyses were performed relating the 10,649 SNPs selected based on physical annotation, to QoL using the statistical software package VEGAS.
Results:Overall, we found no relation between genetic variations (SNPs and genes)and 14 out of 15 QoL-domains. For cognitive functioning a near significant
association was found with the top SNP rs1468951 (p=9.79E-06) in the GSTZ1 gene, independent of background characteristics. Furthermore, results of the genebased
test showed that the combined effect of SNPs within the GSTZ1 gene is significantly associated with cognitive functioning (p=2.20E-05).
Conclusion:If validated, the involvement of GSTZ1 in cognitive functioning underscores its heritability which is likely the result of differences in the dopamine pathway, as GSTZ1 contributes to the equilibrium between dopamine and its
neurotoxic metabolites via the glutathione redox cycle.
ISOQOL Symposium 2013
Symposium: Genes, Cells and Symptom Clusters - What’s the Story?
Moderator: Madeleine T. King, PhD, Psycho-oncology Cooperative Research Group (PoCoG), University of Sydney, Sydney, Australia
Discussant: Donald Patrick, PhD MSPH, Seattle Quality of Life Group, Seattle, WA, United States
Presenters: Donald Patrick, PhD MSPH, Seattle Quality of Life Group, Seattle, WA, United States; Xin Shelley Wang, MD MPH, MD Anderson Cancer Center, Houston, TX, United States; Annemeike Kavelaars, PhD, MD Anderson Cancer Center, Houston, TX, United States; Mirjam AG Sprangers, PhD, Academic Medical Center, University of Amsterdam, The Netherlands
Background: Tantalizing evidence is emerging of “symptom clusters” in cancer. A common cause could point to more effective treatment of symptoms via the underlying cause. As individualized medicine emerges as the new treatment paradigm, informed by genetic profiling, it is both timely and important to explore possible causal pathways between biological parameters (such as gene expression, DNA methylation, genotypes and cytokines) and patient-reported outcomes including symptoms and other aspects of quality of life (QOL), not only in cancer but in all health conditions.
Objective: To frame a research agenda which will illuminate the genetic and biomolecular underpinnings of symptom clusters and HRQOL.
Content: The symposium will start with a brief exposition of a conceptual model of potential biological pathways, genetic and biomolecular variants, characteristics of the afflicted person and his/her environment (social and medical), symptom experience, treatment (benefits and harms), and QOL (health-related and more broadly). Three speakers will then present cutting-edge knowledge about potential biological pathways (e.g. inflammatory, immunologic), and other genetic and biomolecular linkages. The session will end with a panel discussion of future research directions.
Topics and Speakers:
(1) Conceptual model: Donald Patrick will present conceptual models of potential biological pathways, genetic and biomolecular variants, person and environment characteristics, symptom experience, treatment (benefits and harms), and quality of life (health-related and more broadly). (2) Clinical evidence: Xin Shelley Wang will present evidence about cancer symptom clusters and inflammatory response, explain the nature of each and their relationship, and implications for therapy (e.g. dosing and adherence). (3) Preclinical biological basis: Annemeike Kavelaars will describe the use of rat models to test underlying mechanism(s) linking inflammatory cell-level responses with symptom clusters in cancer. (4) GeneQol consortium: Mirjam Sprangers will present examples from the GeneQol consortium’s research portfolio, which aims to identify the biological foundations of HRQOL. This will include known biological pathways and genetic variants involved in a range of HRQOL domains (e.g. fatigue, pain, emotional well-being, social functioning) based on reviews of the literature and recent empirical data. (5) Panel Discussion: all speakers, facilitated by co-chairs, with focus on future research directions.
ISOQOL Symposium 2010
Recent advances in the genetic underpinnings of QoL from the GeneQoL Consortium
Co-Chairs: Jeff Sloan, Health Sciences Research, Mayo Clinic, Rochester, MN; Ailko H. Zwinderman, Medical Epidemiology and Biostatistics, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands; Sarah M. Rausch, Health Outcomes and Behavior, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL. Presenter: Jeff Sloan, Health Sciences Research, Mayo Clinic, Rochester, MN
The purpose of this session is to provide updates of three different confirmatory studies that indicate the genetic pathways that were theorized by the GENEQOL consortium roughly one year ago have been successfully completed with positive results. This session will present each of the three studies turn indicating: 1) the importance of the inflammatory pathways for cytokines as a contributing factor to overall QOL and fatigue; 2) the importance of the COMT opium expression pathways for pain 3) the TYMSDPYD cell structural pathway for fatigue and overall QOL The implications of these findings for genetic research, the relationship of these findings to other biomarker laboratory-based variables, and the future plans for the consortium will be provided.
Genes selected for their relevance to pain are also associated with fatigue and dyspnea: Evidence of the European Pharmacogenetic Opioid Study
Ailko H. Zwinderman, Medical Epidemiology and Biostatistics, Mirjam A. Sprangers, Medical Psychology, Frank Baas, Neurogenetics, Cornelis J. Van Noorden, Cell Biology and Histology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands, Lukas Radbruch, Palliative Medicine, University Clinic, Aachen, Germany, Andrew Davies, Palliative Medicine, Royal Marsden NHS Foundation Trust, Sutton, United Kingdom, Dick F. Swaab, -, Netherlands Institute for Neuroscience, Amsterdam, Netherlands, Jeff Sloan, Health Sciences Research, Mayo Clinic, Rochester, MN, Stein Kaasa, Intensive Care Medicine, Frank Skorpen, Laboratory Medicine, Pal Klepstad, Intensive Care Medicine, Norwegian University of Science and Technology, Trondheim, Norway.
Aims: There is emerging evidence for a genetic basis of quality of life (QL). However, research into the direct associations between QL outcomes and genes is sparse. The objective is to determine the association between a selected set of QL domains with a selected set of candidate genes.
Methods: A group of 2294 patients with advanced cancer, heterogenous to cancer site, using an opioid for pain were recruited from 17 medical centers in 11 European countries. Overall QL, physical, role, and social functioning, fatigue and dyspnea were assessed with the EORTC QLQ-C30. Sociodemographic and clinical variables were used as covariates. DNA was extracted from blood. A total of 359 polymorphisms (SNPs; differences in one base-pair order between one portion of the population and another), belonging to 149 genes, were selected for their relevance to pain and opioid pharmacology. Univariate regression analyses were conducted between QL scale scores and SNPs, using Bonferroni corrections, and controlling for covariates. Canonical correlation analysis of the QL scores and the SNPs was performed with an elastic net penalty to account for the multicollinearity among the SNPs.
Results: On average, patients reported poor QL, but the variation was large, e.g., Fatigue: Mean = 63.8; sd = 25.0; Dyspnea: Mean = 32.9, sd = 33.9. Analyses of the association between the QL scores and the SNPs revealed significant associations for Fatigue and Dyspnea (p = 0.00014). SNPs in the COMT and OPRM1 genes were related to fatigue (effect size 0.20) and SNPs in the COMT and HTR3B genes were associated with dyspnea (effect size 0.29).
Conclusions: Genes selected for their relevance to pain were also found to be associated with fatigue and dyspnea, suggesting a common underlying biological substrate. Whereas these findings need to be replicated, such meaningful results may help identifying future patients who are susceptible to fatigue and dyspnea, to better target preventive strategies and/or specific support.
A genetic link to QoL: The relationship between cytokine gene single nucleotide polymorphisms and symptom burden and quality of life in lung cancer survivors
Sarah M. Rausch, Health Outcomes and Behavior, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, Matthew M. Clark, Christi Patten, Psychiatry and Psychology, Jeff Sloan, Biostatistics, Ping Yang, Epidemiology, Mayo Clinic, Rochester, MN.
Aims: Previous research has demonstrated that many lung cancer survivors will report difficulties with symptom control and will experience a poor quality of life (QOL). Although recent studies have suggested a relationship between single nucleotide polymorphisms (SNPs) in several cytokine genes with cancer susceptibility and prognosis, associations with symptom burden and QOL have not been examined. Therefore, the primary aim of this study is to identify SNPs related to symptom burden and QOL outcomes in lung cancer survivors.
Methods: All participants were enrolled in the Mayo Clinic Lung Cancer Cohort upon diagnosis of their lung cancer. 1149 Caucasian lung cancer survivors, (440 surviving < 3 years; 354 surviving 3-5 years; and 355 surviving> 5 years) completed questionnaires and had genetic samples available. Outcomes included symptom burden (pain, fatigue, appetite, cough, dyspnea, hemoptysis) as measured by the Lung Cancer Symptom Scale (LCSS) and health related quality of life as measured by the SF-8.
Results: Twenty-one single nucleotide polymorphisms in cytokine genes were associated with symptom burden and QOL outcomes. Our results suggested both specificity and consistency of cytokine gene SNPs in predicting outcomes.
Conclusions: These results provide support for genetic predisposition to QOL and symptom burden and may aid in identification of lung cancer survivors at high risk for symptom management and QOL difficulties.
Expansion of the Wilson & Cleary theoretical model to incorporate genetic influences on quality of life
Jeff Sloan, Health Sciences Research, Mayo Clinic, Rochester, MN, Mirjam Sprangers, Psychology, Amsterdam Medical Center, Amsterdam, Netherlands
Aims: We expand the widely used theoretical model ofWilson and Cleary that links biological and patient-reported QOL to incorporate genetic influences.Wilson and Cleary acknowledged that the most fundamental biological determinants of health status are molecular and genetic factors. However, they had chosen not to incorporate these explicitly in their model because at the time these were not commonly measured and applied in routine clinical practice.
Methods: We present the original and revisedWilson and Cleary model. We describe multiple examples involving pain, fatigue and overall QOL in terms of how the theoretical framework for each of these patient-reported outcomes can be expanded to include genetic influences. We identify the physiological pathways for each of the three endpoints and recent data from the GENEQOL consortium that indicates confirmatory findings of specific genetic components for these three endpoints in studies involving cancer patients.
Results: Datasets involving colorectal and lung cancer patients demonstrate that genetic single-nucleotide polymorphisms involving the inflammatory pathway(SNPs) have been identified for fatigue including DPYD, TYMS, and cytokines. These are consistent with the biological pathways and variables previously identified by the GENEQOL consortium as being credible mechanistic models to explain a potential relationship between genetic influences and patient-reported outcomes.
Conclusions: The expanded Wilson & Cleary theoretical framework can be used in combination with wstablished biological pathways to facilitat ethe exploration of genetic influences of patient-reported health-related quality of life.
ISOQOL Symposium 2009
The genetic disposition of patient-reported quality-of-life outcomes
Co-Chairs: Jeff Sloan, Mayo Clinic, Rochester, MN, USA; Mirjam A. G. Sprangers, Academic Medical Center, University of Amsterdam, the Netherlands.
Presenters: Jeff Sloan; Mirjam A. G. Sprangers; Quiling Shi, University of Texas M.D. Anderson Cancer Center, Houston, US; Michele Halyard, Mayo Clinic, Scottsdale, AZ, USA; Amylou Dueck, Mayo Clinic, Scottsdale, AZ; Hein Raat, Erasmus University, Rotterdam, the Netherlands.
The field of patient-reported quality of life (QL) has never focused on that which is innate to the person. Research on twins has provided ample empirical evidence that, for example, self-rated health is, in part, heritable. Thus, there is a compelling need to reveal the genetic variables that play a role in QL. Clearly, this path is complex, considering the potential number of genes, gene interactions, and QL variables that may be involved. We have therefore established the international and interdisciplinary GENEQOL Consortium to provide the requisite foundation and research culture to stimulate the development of this field. This symposium aims to present the establishment of the GENEQOL Consortium, to provide a summary of its first results, and to highlight methodological challenges facing this novel line of research.
Paper 1 describes the establishment of the GENEQOL Consortium, which purports to translate and plan clinically relevant research to identify and investigate potential biological pathways, genes and genetic variants involved in QL. The subsequent papers describe the biological pathways and genetic variables involved in negative as well as positive affect (paper 2), pain (paper 3) and fatigue (paper 4). Paper 5 outlines the statistical challenges and paper 6 presents an ongoing genetic study into the QL of young children and their mothers. This symposium addresses a groundbreaking initiative to investigate the novel question about the genetic disposition of QL. Insight into the genetic versus environmental components of QL will ultimately allow us to explore new pathways for improving patient care. If we can identify patients who are susceptible to poor QL, we will be able to better target specific support to enhance their QL.
The establishment of the GeneQoL Consortium to investigate the genetic disposition of patient-reported quality-of-life (QL) outcomes
Jeff Sloan, Mayo Clinic, Rochester, MN USA; Mirjam A. G. Sprangers, Academic Medical Center, University of Amsterdam, The Netherlands; on behalf of the GENEQOL Consortium.
Aims: To our knowledge, no comprehensive, interdisciplinary initiatives have been taken to examine the role of genetic variants on QL outcomes and their relevance to disease. We therefore established the GENEQOL Consortium. The overall objective of this Consortium is to establish strong collaborative and interdisciplinary relationships to translate and plan clinically relevant research to identify and investigate potential genes and genetic variants involved in QL. We have identified five primary QL outcomes as initial targets: negative and positive affect, self-rated physical health, pain, and fatigue. The specific objectives are: (1) to develop a list of potential biological pathways, genes and genetic variants involved in the five QL outcomes, by reviewing current genetic knowledge; and (2) to design a research agenda to investigate and validate those genes and genetic variants of QL.
Methods: We brought together an international and interdisciplinary team of 28 experts who were combined to form five interdisciplinary teams related to the five identified QL outcomes. The teams were asked to prepare draft summary documents addressing the two objectives, which were presented and discussed during a two-day meeting.
Results: A considerable degree of biological and genetic overlap was found among the target QL components. We set out a research agenda by outlining a range of research objectives (e.g., to test the genetic differences in subjects with extreme values for a single symptom, to test the QL differences in subjects grouped according to a particular genetic makeup), by identifying large-scale data sets of general and disease populations that include both genetic and QL variables, and by delineating the analytical approach (e.g., genome wide association versus candidate gene approach).
Conclusions: With the establishment of the GENEQOL Consortium, it is our hope that the intriguing questions surrounding the genetic disposition of QL will be set on the research agenda and be studied widely. We therefore actively welcome new, contributing members.
Biological pathways and genetic variables involved in negative and positive affect
Mirjam Sprangers, Academic Medical Center, University of Amsterdam, The Netherlands; Meike Bartels, VU University, Amsterdam, The Netherlands; Ruut Veenhoven, Erasmus University Rotterdam, The Netherlands; Frank Baas, Academic Medical Center, Amsterdam, The Netherlands; Dorret Boomsma, VU University, Amsterdam, The Netherlands; Nick Martin, University of Queensland, Brisbane, Australia; Benjamin Movsas, Henry Ford Health System, Detroit, MI, USA; Miriam Mosing, University of Queensland, Brisbane, Australia; Mary Ropka, Fox Chase Cancer Center, Cheltenham, USA; Gen Shinozaki, Mayo Clinic, Rochester, MN, USA
Aims: Research on twin families has provided ample empirical evidence of a genetic disposition for negative emotional states (e.g., depression, anxiety, and psychosocial distress) and positive emotional states (e.g., subjective well-being and life satisfaction). Heritability estimates range between 40% and 50%. The objective is to identify the biological pathways, genes and genetic variants involved in negative and positive affect.
Methods: We reviewed genetic knowledge by studying the literature and ongoing research.
Results: The Hypothalamo-Pituitary-Adrenal (HPA) axis is considered to be the ‘final common pathway’ for most depressive symptoms. Additionally, an impaired dopamine system, decreased levels of serotonin, and changes of sex hormone levels may play important roles in the vulnerability to mood disorders. A large set of genes have been identified that are related to these biological pathways (e.g., Oxytocin, COMT). The prefrontal cortex is the candidate brain area for happiness and positive emotional states that may be related to taste, smell or other input via the somatosensory system. Dopamine has also been found to modulate positive affect states. Few candidate genes have been proposed for positive affect.
Conclusions: Whereas negative affect has been widely investigated, genetic research into positive affect is scarce. The overarching question arising from this study is the extent to which negative and positive affect are genetically distinct or opposite ends of the same continuum. Another question is whether different operationalizations of the same emotional state affect the findings. In other words, can we pool data sets that include different measures of affect? These and other intriguing questions will be addressed during the presentation.
Biological pathways and genetic variables involved in pain
Quiling Shi, U.T.M.D. Anderson Cancer Center, Houston, TX, USA; Charles Cleeland, U.T.M.D. Anderson Cancer Center, Houston, TX, USA; Pal Klepstad, St. Olav University Hospital, Trondheim, Norway; Christine Miaskowski, UCSF School of Nursing, San Francisco, CA, USA; Nancy Pedersen, Karolinska Institutet, Stockholm, Sweden
Aims: Research has established that genetic polymorphisms account for individual variations in perception of pain and response to analgesics. We reviewed the current knowledge of pain- and analgesic-related pathways, genes, and genetic variants involved in pain.
Methods: We searched the literature in PubMed by using “pain”, “gene”, and “polymorphism” as key words, and summarized this literature.
Results: A total of 397 references on genetic variation of pain perception and response to analgesics in human beings were obtained. We identified three categories of potential genetic pathways for pain perception: (a) modulators of central nervous system activity, (b) modulators of peripheral pain pathways, and (c) mechanisms that affect inflammation. Genes related to pharmacodynamics (receptor interaction, intracellular signaling, modulation of opioid effects) and pharmacokinetics (metabolism and transport) were identified for response to analgesics. Genes and genetic variations involved in these pathways were proposed as candidate genetic markers for pain perception (e.g. COMT, TNF-alpha, IL1-RN, IL-6,) and for individual sensitivity to analgesics (e.g. OPMR1, UGT2B6, CYP2D9, ABCB1).
Conclusions: Candidate gene association studies have been widely conducted to study the genetic modulation of pain perception and response to analgesics. However, the nature and range of genetic modulation of pain are still not well addressed due to the limited number of genes and genetic variants investigated in studies to date. Moreover, personalized analgesic treatment will require a more completed understanding of the effects of genetic variants and gene-gene interaction in response to analgesics.
Biologic and genetic mechanisms of cancer-related fatigue
Michele Halyard, Mayo Clinic, Scottsdale, AZ, USA; Marlene Frost, Rochester, MN, USA; Per Hall, Stockholm Sweden; Aeilko H. Zwinderman, Amsterdam, the Netherlands; Andrea Barsevick, Cheltenham, PA, USA.
Aims: Cancer-related fatigue is a significant symptom affecting over 50% of cancer patients. The pathophysiologic mechanisms involved in cancer-related fatigue are not completely understood.
Methods: As part of the 2009 GENEQOL Consortium meeting, a review of the potential factors associated with a genetic disposition of cancer-related fatigue was undertaken. Potential biological pathways and genes and genetic variants were explored related to cancer-related fatigue.
Results: Evidence indicates that increased inflammatory marker levels are related to increased levels of fatigue. Several cytokine genes and their polymorphisms have been proposed as candidate markers for the study of cancer-related fatigue, including interleukins 1B, 2, 6, 8 and tumor necrosis factor alpha. Gene polymorphisms in the promoter regions of genes that encode proinflammatory cytokines have been identified which could influence susceptibility to cancer-related fatigue. To date, there have been no genome-wide association studies of cancer-related fatigue.
Conclusions: Because cancer-related fatigue is complex, it is likely influenced by several genetic polymorphisms. The potential biologic and genetic factors related to cancer-related fatigue will be discussed.
Challenges in the statistical analysis of quality-of-life and genetic variables
Amylou C. Dueck, Ailko H. Zwinderman, Jeff A. Sloan
Aims: The aim of this presentation is to highlight the statistical challenges associated with genetic studies that incorporate quality-of-life (QL) data and to present available strategies for handling these challenges.
Methods: The lessons learned from ongoing and completed statistical analyses involving QL and genetic data conducted by GENEQOL Consortium members, were compiled. The statistical genetics literature was also reviewed to identify potential challenges and solutions.
Results: The advantages and disadvantages of genetic studies that accrue related (e.g., twins) versus unrelated (e.g., cases and controls) subjects will be described, as will be the required general statistical methods. The main statistical issues to be addressed are multiplicity and validation. In this context, the advantages and disadvantages of a targeted, candidate gene versus a genome-wide approach will be described. Power considerations and examples of required sample sizes in the various designs will be presented. Finally, the multidimensional and longitudinal aspects of QL data require additional analytical strategies in the context of genetic studies, with suggested methods deriving from the realm of multivariate statistical analysis.
Conclusions: Analytical challenges of QL and genetic variables can be overcome with available methods. Such methods should be applied to mine existing QL and genetic data. Further, studies can be designed with reasonable sample sizes and power to prospectively test hypotheses regarding the association between specific genetic and QL variables.
Candidate gene studies and genome wide association studies on health-related quality of life of mothers and young children; the generation R study
Hein Raat, Dept. of Public Health; Vincent Jaddoe, Generation R; Cornelia van Duijn, Dept. Epidemiology, Albert Hofman, Dept. Epidemiology, Andre Uitterlinden, Dept. of Internal Medicine, Erasmus MC – University Medical Center Rotterdam, The Netherlands; Jeanne M. Landgraf, HealthActCHQ, Boston, MA, USA
Aims: Current technology and available data form large birth cohort studies allow disentangling the genetic and environmental factors and biological pathways involved in quality of life (QL) of young children. Since assessment of young childrens’ QL relies on proxy reports, mostly the mothers, and since QL of the mother herself may be related to reported QL of the child, we will conduct candidate gene and genome wide association (GWA) studies on both QL of mother and child, using the dataset of the Generation R birth cohort study.
Methods: Generation R is a population-based prospective cohort study from fetal life onwards inRotterdam. Children were born in 2002-2006. Blood from mothers and placenta cord blood was sampled. Mothers’ QL was measured 4 times during pregnancy and after birth using SF-12 and EQ-5D. Child QL was measured at 1 year (ITQOL), 2 years (subset ITQOL), 3 years (HSCS-preschool), and 4 and 5 years (CHQ-PF28).
Results: Of the 7.893 mothers and their children, DNA is available for 6.000 children. Genotyping has been performed for 25 candidate genes relevant for obesity, diabetes mellitus type2, cortisol, and psychiatric conditions. Currently, a genome wide association scan (Illumina 610K) of child DNA is being undertaken. DNA of mothers will be assessed in the future. Genetic associations will be analyzed in strata of ethnicity and (pooled) as whole cohort.
Conclusions: In collaboration with the GENEQOL Consortium, Generation R will start with candidate gene studies on QL of both mothers and young children. Gene-environment interaction and interaction with medical indicators of health status will be explored. In the next stage GWA studies on the main physical health and psychosocial QL domains will be performed. This study will be one of the first to provide insight into the genetic background of the QL of young children and their mothers.