Which patient will feel down, which will be happy? The need to study the genetic disposition of emotional states.
ABSTRACT In quality-of-life (QL) research, the genetic susceptibility of negative and positive emotions is frequently ignored, taken for granted, or treated as noise. The objectives are to describe: (1) the major findings of studies addressing the heritable and environmental causes of variation in negative and positive emotional states and (2) the major biological pathways of and genetic variants involved in these emotional states.
The heritability estimates for anxiety and depression are 30-40%. Related traits as neuroticism and loneliness are also highly heritable. The hypothalamo-pituitary-adrenal axis is the 'final common pathway' for most depressive symptoms. The many findings of investigated genes are promising but not definitive. Heritability estimates of positive emotional states range between 40 and 50%. Life satisfaction and mental health share common genetic factors with optimism and self-esteem. The prefrontal cortex is a candidate brain area for positive emotional states. Biological and genetic research into positive emotional states is scarce.
Genetically informative studies may provide insights into a wide variety of complex questions that traditional QL studies cannot deliver. This insight in turn will help us to design more effective supportive programs that could moderate the outcomes of genetically based predispositions.
- SourceAvailable from: Juan R Ordoñana[Show abstract] [Hide abstract]
ABSTRACT: There is compelling evidence of a genetic foundation of patient-reported quality of life (QOL). Given the rapid development of substantial scientific advances in this area of research, the current paper updates and extends reviews published in 2010. The objective was to provide an updated overview of the biological pathways, candidate genes, and molecular markers involved in fatigue, pain, negative (depressed mood) and positive (well-being/happiness) emotional functioning, social functioning, and overall QOL. We followed a purposeful search algorithm of existing literature to capture empirical papers investigating the relationship between biological pathways and molecular markers and the identified QOL domains. Multiple major pathways are involved in each QOL domain. The inflammatory pathway has the strongest evidence as a controlling mechanism underlying fatigue. Inflammation and neurotransmission are key processes involved in pain perception, and the catechol-O-methyltransferase (COMT) gene is associated with multiple sorts of pain. The neurotransmitter and neuroplasticity theories have the strongest evidence for their relationship with depression. Oxytocin-related genes and genes involved in the serotonergic and dopaminergic pathways play a role in social functioning. Inflammatory pathways, via cytokines, also play an important role in overall QOL. Whereas the current findings need future experiments and replication efforts, they will provide researchers supportive background information when embarking on studies relating candidate genes and/or molecular markers to QOL domains. The ultimate goal of this area of research is to enhance patients' QOL.Quality of Life Research 03/2014; · 2.86 Impact Factor
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ABSTRACT: PURPOSE: To describe the major findings in the literature regarding associations between biological and genetic factors and social functioning, paying special attention to: (1) heritability studies on social functioning and related concepts; (2) hypothesized biological pathways and genetic variants that could be involved in social functioning, and (3) the implications of these results for quality-of-life research. METHODS: A search of Web of Science and PubMed databases was conducted using combinations of the following keywords: genetics, twins, heritability, social functioning, social adjustment, social interaction, and social dysfunction. RESULTS: Variability in the definitions and measures of social functioning was extensive. Moderate to high heritability was reported for social functioning and related concepts, including prosocial behavior, loneliness, and extraversion. Disorders characterized by impairments in social functioning also show substantial heritability. Genetic variants hypothesized to be involved in social functioning are related to the network of brain structures and processes that are known to affect social cognition and behavior. CONCLUSIONS: Better knowledge and understanding about the impact of genetic factors on social functioning is needed to help us to attain a more comprehensive view of health-related quality-of-life (HRQOL) and will ultimately enhance our ability to identify those patients who are vulnerable to poor social functioning.Quality of Life Research 10/2012; · 2.86 Impact Factor
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ABSTRACT: Quality of life (QoL) in patients with chronic disease is impaired and cannot be solely explained by disease severity. We explored whether genetic variability and activity contributes to QoL in patients with Marfan syndrome (MFS), a genetic connective tissue disorder. In 121 MFS patients, patient characteristics (i.e. demographics and MFS-related symptoms) were assessed. Patients completed the SF-36 to measure QoL. In addition, transcriptome wide gene expression and 484 Single Nucleotide Polymorphysms (SNPs) in cytokine genes were available. QoL was first analyzed and associated with patient characteristics. Patients' physical QoL was impaired and weakly related with age and scoliosis, whereas mental quality of life (MCS) was normal. To explain a largely lacking correlation between disease severity and QoL, we related genome wide gene expression to QoL. Patients with lower MCS scores had high expression levels of CXCL9 and CXCL11 cytokine-related genes (p = 0.001; p = 0.002); similarly, patients with low vitality scores had high expression levels of CXCL9, CXCL11 and IFNA6 cytokine-related genes (p = 0.02; p = 0.02; p = 0.04), independent of patient characteristics. Subsequently, we associated cytokine related SNPs to mental QoL (MCS and vitality). SNP-cluster in the IL4R gene showed a weak association with MCS and vitality (strongest association p = 0.0017). Although overall mental QoL was normal, >10% of patients had low scores for MCS and vitality. Post-hoc analysis of systemic inflammatory mediators showed that patients with lowest MCS and vitality scores had high levels of CCL11 cytokine (p = 0.03; p = 0.04). Variation in the cytokine genetic pathway and its activation is related to mental QoL. These findings might allow us to identify and, ultimately, treat patients susceptible to poor QoL.PLoS ONE 01/2012; 7(9):e45126. · 3.53 Impact Factor
Which patient will feel down, which will be happy? The need
to study the genetic disposition of emotional states
Mirjam A. G. Sprangers•Meike Bartels•Ruut Veenhoven•Frank Baas•
Nicholas G. Martin•Miriam Mosing•Benjamin Movsas•Mary E. Ropka•
Gen Shinozaki•Dick Swaab•The GENEQOL Consortium
Accepted: 1 April 2010/Published online: 24 April 2010
? The Author(s) 2010. This article is published with open access at Springerlink.com
susceptibility of negative and positive emotions is fre-
quently ignored, taken for granted, or treated as noise. The
objectives are to describe: (1) the major findings of studies
addressing the heritable and environmental causes of var-
iation in negative and positive emotional states and (2) the
major biological pathways of and genetic variants involved
in these emotional states.
depression are 30–40%. Related traits as neuroticism and
loneliness are also highly heritable. The hypothalamo–
pituitary–adrenal axis is the ‘final common pathway’ for
most depressive symptoms. The many findings of investi-
gated genes are promising but not definitive. Heritability
In quality-of-life (QL) research, the genetic
estimates of positive emotional states range between 40
and 50%. Life satisfaction and mental health share com-
mon genetic factors with optimism and self-esteem. The
prefrontal cortex is a candidate brain area for positive
emotional states. Biological and genetic research into
positive emotional states is scarce.
Genetically informative studies may provide
insights into a wide variety of complex questions that tra-
ditional QL studies cannot deliver. This insight in turn will
help us to design more effective supportive programs that
could moderate the outcomes of genetically based
Negative emotional states ? Biological pathways ?
Review ? Positive emotional states ?
Department of Radiation Oncology, Henry Ford Health System,
Detroit, MI, USA
M. E. Ropka
Cancer Prevention and Control Program, Fox Chase Cancer
Center, Cheltenham, PA, USA
Department of Psychiatry and Psychology, Mayo Clinic,
Rochester, MN, USA
Department Neuropsychiatric Disorders, Netherlands Institute
for Neuroscience, An Institute of the Royal Netherlands
Academy of Arts and Sciences, Amsterdam, The Netherlands
M. A. G. Sprangers (&)
Department of Medical Psychology/J3-211, Academic Medical
Center, University of Amsterdam, Meibergdreef 15, 1105
AZ Amsterdam, The Netherlands
Department of Biological Psychology, VU University,
Amsterdam, The Netherlands
Faculty of Social Sciences, Erasmus University Rotterdam,
Rotterdam, The Netherlands
Laboratory of Neurogenetics, Academic Medical Center,
University of Amsterdam, Amsterdam, The Netherlands
N. G. Martin ? M. Mosing
Queensland Institute of Medical Research, Brisbane, Australia
Qual Life Res (2010) 19:1429–1437
Hypothalamic paraventricular nucleus
Psychological or mental functioning is one of the key
components of quality of life (QL) and encompasses the
entire spectrum of psychological well-being: from anxiety
and depression on the one hand to happiness and life sat-
isfaction on the other. Since being confronted with a dis-
ease is one of the major stressors in life, it is
understandable that patient-based QL research has focused
primarily on the negative end of this range. Frequently
used QL questionnaires, such as the European Organisation
for Research and Treatment of Cancer QL questionnaire
(EORTC QLQ-C30), exclusively inquire about negative
emotions (e.g., being tense, worried, irritable, depressed)
. In the area of health psychology, the stress process has
also been described predominantly in terms of negative
emotions. This focus may have stemmed from the
acknowledgment that negative emotions have adaptive
value as they mobilize the fight/flight response and focus
attention on the problem at hand .
However, there is mounting evidence that positive
emotions co-occur with negative emotions during intensely
stressful periods of life [2, 3]. Positive emotions have also
been found to have adaptive significance as they may
broaden the individual’s attentional focus and behavioral
repertoire, thereby increasing the person’s intellectual,
social, and physical resources . There is a growing
empirical body of research showing that positive emotions
have a salutary impact on health, particularly regarding the
immune system response and pain tolerance [5, 6]. In other
words, happy people are in general healthier. The World
Health Organization has started to emphasize happiness as
a component of health , and the British Medical Journal
has recently published an article on the dynamic spread of
happiness along connections in a large social network and
the implications for healthcare .
The balance between negative and positive emotions
may differ within persons over time, e.g. immediately after
the diagnosis of a disease, negative emotions will likely
prevail. The balance between negative and positive emo-
tions also differs across individuals. We all know persons
whose view on life is gloomy and somber irrespective of
happy and fortunate circumstances. Conversely, we can all
name people who persist in a sunny and cheerful view on
life despite setbacks and mayhem. In patient-based QL
research, this inborn nature is frequently ignored, taken for
granted, or treated as noise. The field of QL research would
benefit from taking this genetic component into account.
Insight into the genetic and environmental components of
patient-reported emotional states will ultimately allow us to
explore new pathways for improving patient care. If we can
identify patients who have a high risk of experiencing poor
psychological functioning, we will be able to better target
psychological support and/or pharmacological treatment.
In other words, we will be able to direct our limited
resources in a timely fashion to those who are most likely
to need them.
Research on twins, multi-generational families, and
population-based cohorts has provided ample empirical
evidence of a genetic predisposition for negative emotional
states, such as depression, anxiety, and loneliness. Addi-
tionally, an increasing number of studies showed sub-
stantial heritability of positive emotional states, such as
subjective well-being, happiness, and life satisfaction. The
objectives of this paper are first to describe the major
findings of the studies addressing the heritable and envi-
ronmental causes of variation in individual differences in
negative and positive emotional states. Second, we will
describe the major biological pathways of and genetic
variants involved in these emotional states. We will thus
describe those biological pathways and genetic variants
that affect QL, which is consistent with the adapted theo-
retical model of Wilson and Cleary  as described by
Sprangers et al. . Since more biological and genetic
research has been conducted in negative than in positive
emotional states, the paper will reflect this imbalance.
Negative and positive emotional states are commonly
reported in separate papers. We purposefully bring these
findings together as helping patients to achieve a high level
of well-being requires targeting both negative and positive
Negative emotional states
Causes of individual differences
Genetic as well as environmental factors play a role in the
etiology of negative emotional states, such as anxiety and
depression. The heritability estimates for both anxiety and
depression disorders range between 30 and 40%. These
percentages most likely represent the lower bound. Actual
heritability may be higher when measurement error could
be ruled out and depression could be perfectly reliably
assessed [11, 12]. The remaining variance can be attrib-
uted to individual-specific environmental influences, as
1430 Qual Life Res (2010) 19:1429–1437
indicated by two meta-analyses [11, 12]. It should be noted
that the environmental influence already starts in the womb
. According to twin and family studies, anxiety and
depression have a common genetic background. They also
share a common genetic factor with neuroticism. Thus, it is
likely that neuroticism is the personality trait underlying
these disorders [14, 15]. Neuroticism refers to the tendency
to experience negative emotions such as fear, sadness, and
anger. This trait is also being referred to as negative
affectivity or emotionality . The heritability estimates
of neuroticism have also been found to range around
30–40% . Findings in adolescents generally support
findings in adults and young children that neuroticism is
influenced principally by genetic and unique, non-shared
environmental factors .
Many patients may also experience the pain of loneli-
ness that a chronic or disabling disease may induce.
Loneliness can be described as feelings of social isolation
and dissatisfaction with one’s social relationships. There is
robust evidence that loneliness plays a pivotal role in
emotional states, such as mood, anxiety, anger, pessimism,
and dysphoria . Loneliness also has a significant
genetic component. In a cross-sectional study of adult
twins, the heritability estimate for variation in loneliness
scores averaged over items and measurement occasions
was found to be around 50% . In a longitudinal analysis
of two individual items (‘‘I feel lonely’’ and ‘‘Nobody loves
me’’), the heritability in young adults (below 35 years) was
found to be 77 and 70% respectively and 41 and 54% in
older adults . This finding of a heritability of around
50% is replicated in children, using an average score of
loneliness over ages 7, 10, and 12 . The longitudinal
analyses in this study show, however, that heritability is
58% at age 7, 56% at age 10 but drops to 26% at age 12. A
parallel increase in influences of shared family environ-
ment is observed, explaining 6% of the variance at age 7,
8% at age 10, and 35% at age 12. The remaining variance
is explained by relatively stable influences of non-shared
environmental factors. Stability in loneliness is high with
correlations over time ranging between 0.51 and 0.69,
indicating that individuals who score high on loneliness at
a young age have a substantial chance to stay lonely
throughout childhood, whereas gregarious youngsters have
a small chance of suddenly becoming lonely.
In this section and the next section on genetic variants, we
will focus primarily on anxiety and depression, as these
negative emotional states elicited a great deal of biological
and genetic research. The hypothalamo–pituitary–adrenal
(HPA) axis is considered to be the ‘final common pathway’
for most depressive symptoms  and thus may be
important for patient-reported distress. Indeed, a large part
of the environmental and genetic risk factors for depression
appear to correlate with increased HPA-axis activity in
adults. Figure 1 illustrates the pathogenesis of depression
as formulated by Bao et al. . In depressed patients,
stress acting on the HPA axis results in a disproportionately
high activity of this system due to a deficient cortisol
feedback effect. Such an impaired negative feedback
mechanism and overreaction of the HPA-axis to stress may
be based on genetic factors and environmental factors,
including placental dysfunction, smoking of the pregnant
mother, or child abuse. High corticotropin-releasing hor-
mone (CRH) and cortisol levels contribute to symptoms of
depression by their central effects. The set point of the
HPA-axis is at least partly genetically determined. For
example, the heritability estimate of basal cortisol levels
was found to be 62%, as indicated by a simultaneous
analysis of five comparable twin studies .
Fig. 1 Schematic illustration of the pathogenesis of depression
(reprinted with permission from Bao et al., 2008 , p. 541). The
schematic figure illustrates the impaired interaction among the
decreased activity of vasopressin neurons (AVP) in the suprachias-
matic nucleus (SCN), the increased activity of corticotropin-releasing
hormone (CRH) neurons in the paraventricular nucleus (PVN), the
increased release of adrenocorticotropin (ACTH) into the blood
stream by the pituitary gland, and the increased release of cortisol by
the adrenal gland. Normally, cortisol exerts a negative feedback effect
to shut down the stress response when the threat has passed. In
depressed patients, the cortisol feedback mechanism is deficient due
to the presence of glucocorticoid resistance, which may be caused
either by polymorphisms of the corticosteroid receptor or by early
(intra-uterine or childhood) developmental disorders. Both, increased
CRH and increased cortisol levels may induce mood disorders by
their central effects. The increased cortisol levels also affect the
vasopressin (AVP) neurons in the suprachiasmatic nucleus (SCN) as
they subsequently fail to inhibit sufficiently the CRH neurons in the
hypothalamic paraventricular nucleus (PVN). Such an impaired
negative feedback mechanism may lead to a further increase in the
activity of the HPA system 
Qual Life Res (2010) 19:1429–14371431
High cortisol levels in depression may result in an
impaired dopamine system , resulting in anhedonia
(insensitiveness to pleasure or incapacity for experiencing
happiness). Additionally, decreased levels of serotonin in
the brain are thought to be of importance in anxiety dis-
orders , panic disorders , and mood disorders,
although this latter relation is most probably reflecting a
vulnerability to suffer from depressive disorders .
Furthermore, sex hormone levels and particularly fluc-
tuations in sex hormone levels may play an important role
in the vulnerability to mood disorders . Finally, the
suprachiasmatic nucleus, i.e. the biological clock, which
regulates circadian and circannual variations in neuronal,
hormonal, and behavioral activity, is also involved. It is
supposed to be related to circadian and circannual fluctu-
ations in mood and to sleeping disturbances in depression
and to hyperactivity of the HPA-axis .
The genetic liability of a common familial disorder like
major depression involves multiple genes. Potentially
important genes have emerged that are related to the HPA
axis, e.g., those that affect AVP, CRH, or cortisol synthesis
as well as the production of their respective receptors.
Another frequently studied gene is catechol-o-methyl-
transferase (COMT) that is related to the monoamine
catabolism. Many other candidate genes have been pro-
posed and investigated.
To date, the genetic underpinning of depression has been
basically studied in three ways. First, linkage studies of
informative families have been conducted to identify
chromosomal regions (loci) likely to contain genes that
contribute to susceptibility of depression. For example,
several genome-wide linkage studies have identified
regions of chromosomes 15q [26–28], 17p, and 8p  to be
related to depression. Second, candidate gene association
studies have focused on functional polymorphisms (DNA
sequence variations that alter the expression and/or func-
tioning of the gene product) in previously identified and
new loci encoding for potentially relevant genes, as exem-
plified above. Many findings of this candidate gene
approach can be considered promising but not definitive.
The multiple genes involved in depression each exerts a
small effect, making genetic linkage and association studies
challenging . Some consistent patterns have only
recently emerged. For example, the following five genes
were significantly associated with major depressive disor-
der in meta-analyses of polymorphisms that had been
investigated in at least three studies : apolipoprotein E
(APOE), guanine nucleotide-binding protein (GNB3),
methylenetetrahydrofolate reductase (MTHFR), dopamine
transporter (SLC6A3), and serotonin transporter (SLC6A4).
Third, genome-wide association studies examine many
polymorphisms simultaneously in large samples of unre-
lated, population-based cases (those with depression) and
controls (those without depression). The first genome-wide
association study of depression examined more than
430,000 single nucleotide polymorphisms (SNPs) in 1,738
cases of major depression and 1,802 controls and suggested
preliminary evidence for the involvement of the pre-
synaptic protein piccolo (PCLO) on chromosome 7 .
The results from multiple replication cohorts (6,079 inde-
pendent cases with major depressive disorder and 5,893
controls) remained inconclusive. However, reanalysis of
the PCLO replication study indicated that there was con-
vincing evidence for the potentially causal association of
major depressive disorder with one particular SNP,
rs2522833, in PCLO . Interestingly, the second gen-
ome-wide association study based on two large, indepen-
dent data sets and a further combined analysis using a
meta-analytical approach  failed to identify any SNP
that achieved significance. The authors concluded that
SNPs with substantial odds ratio are unlikely to exist for
major depression disorder, at least among the studied SNPs
A consistent, negative finding is worth mentioning.
According to the monoamine-deficiency hypothesis, defi-
cits in serotonin were thought to play a predominant role in
the pathophysiology of depression . However, antide-
pressant drugs made to replenish the lack of these neuro-
transmitters, like serotonin reuptake inhibitors (SSRIs),
were shown not to be effective in large groups of patients
suffering from depression . In addition, there is no
simple relationship between serotonin levels in the brain
and mood . Moreover, the fact that SSRIs take weeks
to become effective makes also clear that the serotoniner-
gic system cannot play a primary role in mood disorders.
Finally, a recent meta-analysis was conducted of the
(5-HTTLPR) and stressful life events on depression using a
total sample of 14,250 participants divided into cases and
transporter gene alone or in interaction with stressful life
events is associated with an elevated risk of depression .
Positive emotional states
Causes of individual differences
An increasing number of twin studies showed substantial
heritability of positive emotional states, such as subjective
well-being and life satisfaction. Heritability estimates
ranged between 40 and 50%, whereas the remaining
1432Qual Life Res (2010) 19:1429–1437
variance was accounted for by environmental influences
unique to an individual. No effects of environmental
influences shared by members of the same family were
found [36–44]. Bartels and Boomsma  examined the
etiology of different operationalizations of positive emo-
tional states: quality of life in general, satisfaction with life,
quality of life at present, and subjective happiness. Multi-
variate analyses with over 5,000 genetically related indi-
viduals revealed that the four measures all loaded on
similar sets of genes. Genetic factors specific to the four
measures were negligible.
A recent study by Boardman et al.  addressing the
heritability of resilience merits attention because of its op-
erationalization. Resilience was measured by a six-item
positive emotional measure (‘‘During the past 30 days, how
much of the time did you feel … cheerful? in good spirits?’’
etc.). They used the residual variance of this positive
emotional measure, after adjusting for an exhaustive list of
social and interpersonal stressors. In a sample of 527 twin
pairs, aged 25–74, the heritability of resilience for men was
found to be 52% and for women 38%. Thus, the residual
variance of positive affect or resilience was also found to be
heritable, albeit more for men than for women.
Personality characteristics such as optimism, self-
esteem, autonomy, mastery, personal growth, and self-
acceptance play important roles in mental health status
and subjective well-being [46–49]. For example, opti-
mism as defined in terms of positive generalized outcome
expectancies  may serve as a protective buffer against
mental as well as physical health impairments. Optimism
has been found to enhance, for example, adjustment to
heart disease  and cancer  (for a brief review of
such studies, see 49).
Recent twin studies indicate that these traits are not only
associated within individuals, but also tend to share com-
mon genetic factors with positive emotional states. For
example, multivariate genetic modeling of data derived
from 428 twin pairs, aged 23–24, indicated that genes
influencing optimism (measured with the Life Orientation
Test), self-esteem (measured with the Rosenberg scale),
and life satisfaction are largely overlapping . The
largest study to date, using 3,053 twin individuals over
50 years, also found that the same set of genes was found
to be involved in optimism (also measured with the revised
Life Orientation Test), overall health (measured by a single
item: ‘‘how would you describe your health at present’’),
and mental health (measured with the General Health
Questionnaire, GHQ-12) . Thus, these factors share a
genetic core that might represent the heritable mechanism
behind an individual’s positive orientation . Never-
theless, a substantial amount of the variance in these traits
is still explained by non-shared, specific environmental
Biological pathways and genetic variants
Several studies suggest that the prefrontal cortex is a can-
didate brain area for happiness and positive emotional
states that may be related to taste , smell  or other
inputs via the somatosensory system . Some electro-
encephalographic (EEG) studies suggest that positive
emotional states are associated with increased left cortical
power in the alpha frequency compared to the right
hemisphere [56, 57]. There is also evidence that dopamine
modulates positive emotional states , indicating a role
for the ventral tegmental area. At the subcortical level, a
number of neuropeptide systems have been implicated in
positive emotional states, e.g., neurotensin and cocaine-
and amphetamine-regulated transcript (CART) (both clo-
sely associated with dopamine), neuropeptide Y, and
oxytocin . Finally, reduced activity of the neuroendo-
crine [59–61] and cardiovascular systems , as well as
increased activity of the immune system , may all be
involved in positive emotional states. However, genes or
genomic regions of interest for positive emotional states
have not been published at the time of paper writing.
We have described the major results of the studies
addressing the heritability of and biological pathways and
genetic variants involved in negative and positive emo-
tional states, respectively. These affect states are to a
substantial degree heritable, with positive states being
slightly more heritable (40–50%) than negative states
(30–40%). The remaining variances can be attributed to
environmental influences unique to the individual, in which
the intrauterine period may play an important role. Perhaps
contrary to some people’s expectation, emotional states are
not affected by environmental influences shared by family
members. Another finding is that these mood states share
common genetic factors with related personality traits, such
as neuroticism for negative emotional states and optimism
and self-esteem for positive emotional states. An abun-
dance of studies have focused on the delineation of the
biological pathways of negative affect, with the HPA axis
considered as the ‘final common pathway’ of depressive
symptoms. By contrast, biological and genetic research
into positive emotional states is scarce. Multiple genes are
involved in emotional states, each exerting a small effect.
While the rate of progress is dazzling, particularly for
negative affect, the biological complexities do not allow
definitive answers yet.
A note of caution is warranted. The studies reviewed
employed very different samples, study designs, measures,
and analyses thereby potentially limiting their comparability.
Qual Life Res (2010) 19:1429–14371433
Particularly, the highly divergent self-report measures across
ignore these different sources. The question arises whether
such collapsing of data is warranted. The cited study by Bar-
tels and Boomsma  examining the etiology of four dif-
ferent operationalizations of positive affect is enlightening.
They found that the four measures were explained by one
underlying genetic factor and genetic factors specific to the
is that distinct measures of subjective well-being are not dis-
tinct at the genetic level and represent biological overlapping
constructs. Thus, different studies that collect distinct mea-
pooling data across measures is acceptable, at least for these
four measures of positive emotional state. Whereas this find-
ing is heartening, further research is needed to examine the
extent to which different measures assessing similar emo-
tional states, or QL domains, also share a similar genetic
An intriguing and pressing question is the extent to
which negative and positive emotional states share the
same biological and genetic substrate. There is evidence of
some common biological mechanism. For example, the
dopamine system is involved in negative as well as positive
affect. However, the relatively recent finding that high
levels of distress can co-occur with high levels of well-
being plead for, at least partly, independent biological
mechanisms. Clearly, further studies are needed to disen-
tangle the biological and genetic substrates of negative and
positive affect, using data sets that include information on
To avoid a possible misunderstanding about the impli-
cations of heritability studies, we would like to call atten-
tion to the fact that a high level of heritability does not
mean that environmental influences are unimportant. Genes
only influence phenotypes within an environment . For
example, experimental manipulations of loneliness were
found to have powerful effects on mood, shyness, anxiety,
and self-esteem [in 18]. Moreover, interventions based on
simple and popular concepts such as committing acts of
thoughtful self-reflection had the power to induce a sus-
tainable increase in levels of happiness .
At this point, QL researchers may wonder why we need
to know the genes if we can examine the presence and
severity of depression, extent, and level of happiness, as
well as the related personality characteristics by self-report?
Molecular genetic studies may provide insights into a wide
variety of complex questions that traditional QL studies
cannot deliver. For example, how can we identify patients
who are vulnerable to long-lasting distress following a
diagnosis? How can we predict which patients will suffer
from mood disturbances when taking a specific chemo-
therapeutic regimen? Why do some pharmacotherapeutic
treatments not work in all patients with the ‘same’ level of
distress? Which patients would benefit from simple inter-
ventions to sustainably increase happiness? Why are some
psychotherapies not effective in comparable patients with
the same ‘problem’? Why do supportive interventions,
which one would expect to benefit all patients, often help
only a few? Delineation of biological pathways through
which various genetic predispositions propel people toward
negative or away from positive emotions is needed. More-
over, insight into which patients will respond to which
interventions can only be provided by studies assessing the
patients’ relative risk for negative and likelihood of positive
emotions using family and molecular genetic approaches in
combination with assessments of the risk and protective
environmental factors. This insight in turn will help us to
design more effective supportive programs that could
moderate the outcomes of genetically based predispositions.
For example, if we can identify which patients are
genetically predisposed to experience intense negative or
extreme positive affect, preventive measures such as self-
help programs or cognitive behavioral therapy can be
implemented. Further, if the patient is entering into a phase
of life where unavoidable stressors are present, such as a
diagnosis of a chronic disease, supportive care interven-
tions targeted at negative and positive affect or pharma-
cotherapy can be used concurrently with other treatments
that can ultimately lead to better treatment outcomes,
including survival. The individual, genetic profile would
thus help indicating which treatment or support would be
most helpful for a particular patient.
In sum, the combination of the prognostic value of
genetic, environmental risk and protective factors ulti-
mately enables appropriate and effective support .
Clearly, molecular genetic testing is a long way from being
implemented in clinical settings, and to some, the previ-
ously sketched vision might seem science fiction. However,
to realize this vision, we believe that QL research should
embrace the study of the genetic and environmental influ-
ences of both negative and positive affects as the resulting
insight will ultimately help our patients to become not only
happier but also healthier.
Sloan for helpful comments to earlier drafts of this article.
We are indebted to Carolyn Schwartz and Jeff
Creative Commons Attribution Noncommercial License which per-
mits any noncommercial use, distribution, and reproduction in any
medium, provided the original author(s) and source are credited.
This article is distributed under the terms of the
1434 Qual Life Res (2010) 19:1429–1437
Appendix: glossary [cited from 64]
Chromosome: Structure that is composed mainly of
chromatin, which contains DNA and resides in the nucleus
DNA (deoxyribonucleic acid): The-stranded molecule
that encodes genetic information.
Family study: Assessing the resemblance between
genetically related parents and offspring and between sib-
lings living together. Resemblance can be due to heredity
or to shared family environment.
Gene: The basic unit of inheritance. A sequence of
DNA bases that codes for a particular product.
Genome: All the DNA sequences of an organism.
Genotype: The genetic constitution of an individual.
Heritability: The proportion of the phenotypic differ-
ences that can be attributed to genetic differences in a
Linkage: Close proximity of loci on a chromosome.
Linkage analysis: A technique that detects linkage
between DNA markers and traits used to map genes to
Locus (plural, loci): The site of a specific gene on a
Mapping: Linkage of DNA markers to a chromosome
and to specific regions of chromosomes.
Nucleus: Thepart of
Phenotype: An observed characteristic of an individual
that results from the combined effects of genotype and
Polymorphism: A locus with two or more alleles
(alternative forms of a gene at a locus). (Functional poly-
morphism: DNA sequence variations that alter the
expression and/or functioning of the gene product)
Single nucleotide polymorphism (SNP): Sequences in
the genome that differ by a single nucleotide between one
portion of the population and another.
Twin study: Comparing the resemblance of identical
and fraternal twins to estimate genetic and environmental
components of variance.
GENEQOL Consortium participants per March 2009
Amy P. Abertnethy, Duke Cancer Care Research Program,
Duke University Medical Center, Durham, NC, US; Frank
Baas, Laboratory of Neurogenetics, Academic Medical
Center, University of Amsterdam, Amsterdam, The Neth-
erlands; Andrea M. Barsevick, Nursing Research and
Education, Fox Chase Cancer Center, Philadelphia, PA,
US; Meike Bartels, Department of Biological Psychology,
VU University, Amsterdam, the Netherlands; Dorret I.
Boomsma, Department of Biological Psychology, VU
University, Amsterdam, the Netherlands; Cynthia Chau-
han, Cancer Advocay, Wichita, KS, US; Charles S. Clee-
land, Department of Symptom Research, The University of
Texas M. D. Anderson Cancer Center, Houston, TX, US;
Amylou C. Dueck, Section of Biostatistics, Mayo Clinic,
Scottsdale, AZ, US; Marlene H. Frost, Women’s Cancer
Program, Mayo Clinic, Rochester, MN, US; Per Hall,
Department of Medical Epidemiology and Biostatistics,
Karolinska Institute, Stockholm, Sweden; Michele Y.
Halyard, Department of Radiation Oncology, Mayo Clinic,
Scottsdale, AZ, US; Pa ˚l Klepstad, Department of Intensive
Care Medicine, St Olavs University Hospital, Norwegian
University of Technology and Science, Trondheim, Nor-
way; Nicholas G. Martin, Queensland Institute of Medical
Research, Brisbane, Australia; Christine Miaskowski,
School of Nursing, University of California, San Fran-
cisco, CA, US; Miriam Mosing, Queensland Institute of
Medical Research, Brisbane, Australia; Benjamin Movsas,
Department of Radiation Oncology, Henry Ford Health
System, Detroit, MI, US; Cornelis J. F. Van Noorden,
Department of Cell Biology and Histology, Academic
Medical Center, University of Amsterdam, Amsterdam,
The Netherlands; Donald L. Patrick, Department of Health
Services, University of Washington, Seattle, WA, US;
Nancy L. Pedersen, Department of Medical Epidemiology
and Biostatistics, Karolinska; Institute, Stockholm, Swe-
den; Mary E. Ropka, Cancer Prevention and Control Pro-
gram, Fox Chase Cancer Center, Cheltenham, PA, US;
Quiling Shi, Department of Symptom Research, The
University of Texas M. D. Anderson Cancer Center,
Houston, TX, US; Gen Shinozaki, Department of Psychi-
atry and Psychology, Mayo Clinic, Rochester, MN, US;
Jasvinder A. Singh, Minneapolis Veterans Affairs Medical
Center and University of Minnesota, Minneapolis, MN and
Mayo Clinic College of Medicine, Rochester, MN, US; Jeff
A. Sloan, Department of Health Sciences Research, Mayo
Clinic, Rochester, MN, US; Mirjam A. G. Sprangers,
Department of Medical Psychology, Academic Medical
Center, University of Amsterdam, Amsterdam, The Neth-
erlands; Ruut Veenhoven, Faculty of Social Sciences,
Erasmus University Rotterdam, Rotterdam, The Nether-
lands; Ping Yang, Department of Genetic Epidemiology,
Mayo Clinic, Rochester, MN, US; Ailko H. Zwinderman,
Department of Clinical Epidemiology and Biostatistics,
Academic Medical Center, University of Amsterdam,
Amsterdam, The Netherlands.
Qual Life Res (2010) 19:1429–14371435
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