Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2015 Nov 1.
Published in final edited form as: Psychosom Med. 2014 Nov-Dec;76(9):732–738. doi: 10.1097/PSY.0000000000000117

Associations between Depression and Anxiety Symptoms with Retinal Vessel Caliber in Adolescents and Young Adults

Madeline H Meier 1, Nathan A Gillespie 2,3, Narelle K Hansell 3, Alex W Hewitt 4,5, Ian B Hickie 6, Yi Lu 3, Stuart MacGregor 3, Sarah E Medland 3, Cong Sun 7,8, Tien Y Wong 9,10,11, Margie Wright 3, Gu Zhu 3, Nicholas G Martin 3, David A Mackey 4,5
PMCID: PMC4290848  NIHMSID: NIHMS625974  PMID: 25373892

Abstract

Objective

Previous longitudinal studies suggest that depression and anxiety are associated with risk for cardiovascular disease. The aim of the present study was to test whether an association between depression and anxiety symptoms and retinal vessel caliber, an indicator of subclinical cardiovascular risk, is apparent as early as adolescence and young adulthood.

Methods

Participants were 865 adolescents and young adults who participated in the Brisbane Longitudinal Twin Study and the Twin Eye Study in Tasmania. Participants completed the Somatic and Psychological Health Report (SPHERE), including assessments of depression/anxiety and somatic symptom subscales, when they were M=16.5 years, and they underwent retinal imaging M=2.5 years later (range=2 years before to 7 years after the depression/anxiety assessment). Retinal vessel caliber was assessed using computer software.

Results: Depression and anxiety symptoms were associated with wider retinal arteriolar caliber in this sample of adolescents and young adults (β=0.09, p=.016), even after adjusting for other cardiovascular risk factors (β=0.08, p=.025). Multiple regression analyses revealed that affective symptoms of depression/anxiety were associated with retinal vessel caliber independently of somatic symptoms.

Conclusions

Depression and anxiety symptoms are associated with measurable signs in the retinal microvasculature in early life, suggesting that pathological microvascular mechanisms may be operative in the association between depression and anxiety with cardiovascular disease starting as early as adolescence.

Keywords: depression, anxiety, retinal vessel caliber, cardiovascular, adolescence, young adults

Longitudinal studies have shown that individuals with symptoms of depression and anxiety are at increased risk for developing cardiovascular disease, and this association persists after accounting for traditional cardiovascular risk factors (1–7). Depression has even been found to confer risk for coronary events up to 10 years later (2). This finding suggests that the pathophysiological mechanisms linking depression with cardiovascular disease may be operative years before the clinical manifestation of cardiovascular disease, and it highlights the need for studies of depression and anxiety and subclinical markers of cardiovascular disease in early life.

One increasingly recognized marker of early subclinical cardiovascular disease is the caliber of the retinal microvessels (8). Advances in digital retinal photography and retinal image computer analysis now allow for the accurate quantitative assessment of the condition of small retinal blood vessels in large population-based samples (8, 9). Retinal microvessels can be used to gauge the health of the microcirculation, because the retina shares anatomical and physiological features with other end organs (e.g., heart, brain, kidneys) (10, 11). Research has shown, for example, that retinal vessel caliber predicts risk of coronary heart disease, stroke, cerebral small vessel disease, cognitive impairment, and dementia (8, 12–15).

Fewer than a dozen studies have examined associations of depression and anxiety with retinal vessel caliber (16–25) (Table 1). These studies have generally shown that adults with depression and/or anxiety exhibit deviations in retinal vessel caliber, either wider or narrower arterioles or venules, suggesting that microvascular abnormality may underlie the association between depression and anxiety symptoms and cardiovascular disease. Yet these studies have primarily focused on older adults. Given mounting evidence that depression, anxiety, and cardiovascular disease have their roots in childhood (26–30), we tested whether an association between depression/anxiety symptoms and retinal vessel caliber is apparent as early as adolescence and young adulthood. In addition, because affective depression and anxiety symptoms often co-occur with somatic symptoms (i.e., fatigue and pain) (31) that may themselves be related to retinal vessel caliber, we differentiated between affective symptoms of depression/anxiety and somatic symptoms.

Table 1.

Extant Studies of Depression and Anxiety and Retinal Vessel Caliber. Studies are generally organized by date, with studies using the same sample appearing together.

Study Study Sample Analysis N Mean Age or
Age Range
(Years)		 Mental Health Index Finding
1. Sun et al., 2007 (16) Cardiovascular Health Study 2,420 78.5 Short version of the CES-D. No association.
2. Kim et al. 2011 (17) Cardiovascular Health Study 1,489 78.1 Short version of the CES-D. Depression associated with narrower arterioles.
3. Nguyen et al., 2008 (18) Clinic-based study of depressed (n=34) and non-depressed (n=27) individuals with Type 2 diabetes and healthy controls (n=38) 99 56.5 DSM-IV criteria, Hamilton Depression Rating Scale, and Mattis Dementia Rating Scale. Some evidence that depression was associated with wider arterioles and venules.
4. Nguyen et al. 2010 (19) Clinic-based study of depressed (n=43) and non-depressed (n=49) individuals with Type 2 diabetes and healthy controls (n=54) 146 57.8 DSM-IV criteria, Hamilton Depression Rating Scale, Mini Mental State Exam. Depression associated with wider arterioles.
5. Cheung et al 2009 (20) Atherosclerosis Risk in Communities Study 10,339 56.5 Vital exhaustion assessed with the Maastricht questionnaire. Vital exhaustion associated with wider venules.
6. Ikram et al., 2010 (21) Rotterdam Study 3,605 66.1 Various (CES-D or Hospital Anxiety and Depression Scale, structured interview, general practitioner and pharmacy records). No association.
7. Jensen et al 2010 (22) Multi-Ethnic Study of Atherosclerosis >6,000 45–84 CES-D, Spielberger trait anxiety. Anxiety (but not depression) associated with narrower arterioles.
8. Caspi et al 2013 (23) Dunedin Multidisciplinary Health and Development Study 1,000 38 Structured diagnostic interviews used to create an internalizing latent factor indicated by depression, generalized anxiety disorder, fears/phobias. Internalizing associated with wider venules.
9. Meier et al 2013 (24) Dunedin Multidisciplinary Health and Development Study. Subset of study members with persistent depression (n=188) versus healthy controls (n=412) 38 Structured diagnostic interviews used to diagnose persistent depression. Persistent depression associated with wider venules and narrower arterioles.
10. Li et al 2013 (25) Growing Up in Singapore Towards Healthy Outcomes Study & In Vitro Fertilization Study 472–786 30.6 (26 weeks gestation) Edinburgh Postnatal Depression Scale, State-Trait Anxiety Inventory, Pittsburg Sleeping Quality Index. Depression and poor sleep quality (but not anxiety) associated with wider arterioles.
Open in a new tab

Note. Analytic strategy and adjustment for other cardiovascular risks varied considerably across studies.

Methods

Participants

Participants were members of the population-based Brisbane Longitudinal Twin Study (BLTS), an ongoing longitudinal study of adolescent and young-adult monozygotic (MZ) and dizygotic (DZ) twin pairs and their siblings (32, 33). As described in detail elsewhere (32, 33), twins were initially recruited to the study from primary and secondary schools in South East Queensland in 1992, with new twins added at various intervals. All schools in South East Queensland were approached, and all regions in South East Queensland were represented. Comparisons of this sample with other population-based samples suggest that this sample is representative with respect to a variety of traits, including, for example, personality (34) and retinal vessel caliber (35, 36).

Mental health data were collected on up to four occasions between 2000 and 2013 as part of the study of skin mole development (37) as well as the study of cognition (32), and the study of health and well-being (32, 33). A subset of participants also completed an extensive eye examination in 2004–2008 as part of the Twins Eye Study of Tasmania (38, 39). Here were report on 865 participants for whom both mental health data (mean age across assessments=16.52, SD=2.96) and eye exam (mean age=19.07, SD=3.53) data were available. Though the eye exam was conducted M=2.55 (SD=1.57) years after the mental health assessment, the eye exam took place anywhere from 2 years before to as many as 7 years after the mental health assessment. The study was approved by the ethics committees of the Royal Victorian Eye and Ear Hospital, the Royal Hobart Hospital, and the QIMR Berghofer Medical Research Institute, as well as the Australian Twin Registry, and adhered to the tenets of the Declaration of Helsinki. Written informed consent was obtained from all of the participants or their legal guardians, with the participants’ assent before examination.

Measures

Depression/anxiety, somatization, and fatigue

The Somatic and Psychological Health Report (SPHERE) questionnaire is a 34-item self-report questionnaire that assesses common symptoms of depression, anxiety, and somatic distress (40–42). In addition to yielding a total score indexing overall mental health and well-being, the SPHERE yields subscale scores indexing primarily affective symptoms of depression/anxiety (14 items; e.g. “feeling irritable or cranky”, “feeling unhappy and depressed”, “everything getting on top of you”), somatization (10 items; e.g. “joint pain”, “weak muscles”), and fatigue (9 items; e.g. “poor sleep”, “prolonged tiredness after activity”, “poor concentration”). Participants indicated if they had been troubled by symptoms over the past few weeks.

The SPHERE has been shown to have adequate reliability and validity (33, 40, 41). Internal consistency reliability for the SPHERE and the depression/anxiety, somatization, and fatigue subscales was 0.89, 0.84, 0.70, and 0.75, respectively (40). A prior study showed that the SPHERE accurately identified 93% of individuals with current DSM depression, anxiety, or somatoform disorders (41). Moreover, the depression/anxiety subscale shows substantial heritability (40%) and correlates strongly with the personality trait of neuroticism (r=0.64) (40).

Item response theory (IRT) analysis of the SPHERE items was implemented in WINBUGS2 (43) to estimate latent liability scores reflecting (a) liability to depression/anxiety (based on the 14 items of the SPHERE depression/anxiety subscale; 1 item overlaps with somatization, and 3 items overlap with fatigue), (b) liability to somatization (based on the 10 items of the SPHERE somatization subscale, 1 item overlaps with fatigue), (c) liability to fatigue (based on the 9 items of the SPHERE fatigue subscale), and (d) poor overall mental health and well-being (based on all 34 items of the SPHERE). High scores on the latent liability indexes reflect that participants endorsed many symptoms. Liability to depression/anxiety was significantly correlated with liability to somatization (r=0.54) and fatigue (r=.70), and liability to somatization and fatigue were also significantly correlated (r=0.63). Each subscale was significantly correlated with poor overall mental health (0.90, 0.69, and 0.87, respectively).

Over half of the participants (n=479) had completed the SPHERE on more than one occasion as part of different studies (details published previously (40)). Data were collected only once for 386 participants (45%), twice for 152 (17%), three times for 233 (27%), and four times for 94 participants (11%). For participants who had completed the SPHERE on multiple occasions, we averaged the latent liability scores over occasions and took an ‘average age’ at assessment. Our rationale for aggregating the SPHERE data was that an aggregate estimate would be more reliable and accurate than an estimate from any single occasion.

Retinal vessel caliber

As described elsewhere (39, 44), all of the twins had 10° stereoscopic optic disc–centered photographs using a Nidek 3-Dx/F fundus camera (Nidek) after dilatation of the pupils with tropicamide 1% or cyclopentolate 1%. Photographs were digitalized, and retinal vessel caliber was measured with computer-assisted software (IVAN, University of Wisconsin, USA) according to a standardized protocol (45). Two trained graders, masked to participant characteristics, performed the vessel measurements on the optic disc–centered image for both eyes for all of the participants. The largest 6 arterioles and venules coursing through a zone between half to 1 disc diameter from the optic disc margin were measured. Estimates were summarized as the central retinal arteriolar equivalent (CRAE) and central retinal venular equivalent (CRVE), representing the average caliber (diameter) of arterioles and venules of the eye, respectively, using a revised Knudtson-Parr-Hubbard formula (46). Reliability of the retinal vessel measurement has been published elsewhere (44). Intragrader variation was assessed in 67 randomly selected retinal photographs. The intragrader intraclass correlation coefficient was 0.95 for CRAE and 0.99 for CRVE. Intergrader reliability was assessed in 52 randomly selected retinal images, and the interclass correlation coefficient was 0.93 for CRAE and 0.98 for CRVE. The correlation between CRAE and CRVE was 0.51 (p<.001).

Covariates

Smoking status and body mass index (BMI) were included as covariates, as they are associated with both retinal vessel caliber and mental health, in this sample and in others (8, 9, 47–50). Spherical equivalent and axial length were included as covariates in order to adjust for any potential effects of these parameters on retinal vessel caliber (45, 51). Table S1 (Supplemental Digital Content 1) shows correlations of these covariates with vessel caliber and mental health. All analyses also controlled for age and sex. Covariates were assessed at the time of the eye exam.

BMI was calculated as kilograms per meter squared. For participants who were missing either height or weight data or both (12%, n=102), we imputed the missing data using the multiple imputation procedure in SAS (SAS Institute, Inc., Cary, NC, USA). Axial length was measured using the IOL Master, and refractive errors were measured using a Humphrey-598 automatic refractor (Carl Zeiss Meditec, Inc., Miami, Florida, USA). Spherical equivalent was calculated using the standard formula of the algebraic sum of the dioptric powers of the sphere and half of the cylinder (38).

Statistical Analysis

To examine associations between mental health and retinal arteriolar caliber, we conducted separate linear regressions predicting arteriolar caliber from each mental health risk factor (i.e., we considered each predictor [depression/anxiety, somatization, fatigue, and overall mental health] individually). Associations between each predictor and retinal arteriolar caliber were initially adjusted for the effects of age and sex (Model 1) and then further adjusted for the effects of smoking status, BMI, sphericity, and axial length (Model 2). We then repeated these analyses with venular caliber as the outcome. We report standardized beta coefficients (β) from these analyses. To account for participants’ familial relatedness (the non-independence of observations), robust standard errors were computed using the SURVEYREG procedure in SAS (SAS Institute, Inc., Cary, NC, USA). This procedure downwardly adjusts the degrees of freedom based on the number of twin pairs in the analysis, taking into account that information obtained about one twin is related to information obtained about the co-twin.

Results

Descriptive statistics for measures of mental health and retinal vessel caliber are presented in Table 2.

Table 2.

Means and standard deviations for measures of mental health and retinal vessel caliber.

Full Sample
N=865		 Girls
N=495		 Boys
N=370
Measure M SD M SD M SD
SPHERE (range)
  Depression/Anxiety Subscale (0–14) 3.69 3.13 3.76 3.20 3.58 3.03
  Somatization Subscale (0–10) 1.62 1.59 1.63 1.66 1.61 1.50
  Fatigue Subscale (0–9) 2.95 1.98 2.83 1.95 3.10 2.01
  Overall Mental Health (0–34) 8.62 5.71 8.61 5.78 8.63 5.61
Retinal Vessel Caliber (in µm)
  Arterioles 165.27 12.94 165.27 13.69 165.28 11.89
  Venules 249.54 17.96 248.81 18.51 250.52 17.17
Open in a new tab

Note. Means for SPHERE (Somatic and Psychological Health Report) and retinal vessel caliber match published means for the larger studies from which these participants were drawn (38–40).

Table 3 shows associations between each mental health predictor and vessel caliber. Liability to depression/anxiety was associated with arteriolar (β=0.09, p=.016) but not venular caliber (β=0.00, p=.90) (Table 3, Model 1). Specifically, adolescents and young adults with a greater number of depression/anxiety symptoms showed wider arteriolar caliber (Figure 1). A similar pattern of associations was observed for somatization, fatigue, and overall mental health, though effects for somatization and fatigue did not reach statistical significance. Notably, associations were unchanged after controlling for smoking status, BMI, sphericity, and axial length (Table 3, Model 2).

Table 3.

Associations between measures of mental health and retinal vessel caliber.

Arterioles Venules
Model 1a Model 2b Model 1a Model 2b
SPHERE Liability Score β SE p β SE p β SE p β SE p
Depression/anxiety 0.09 .037 .016 0.08 .036 .025 0.00 .037 .90 −0.01 .035 .72
Somatization 0.06 .035 .072 0.06 .035 .090 0.04 .035 .22 0.02 .034 .63
Fatigue 0.06 .035 .099 0.05 .034 .11 0.00 .035 .94 −0.01 .033 .71
Overall Mental Health 0.08 .036 .024 0.08 .036 .028 0.00 .038 .99 −0.02 .036 .67
Open in a new tab

Note: Results are from ordinary least squares regressions predicting arteriolar and venular caliber from each SPHERE liability score, with separate regressions conducted for each SPHERE liability score.

a

. Model 1 controls for age and sex.

b

. Model 2 controls for age, sex, smoking status, BMI (body mass index), sphericity, and axial length. SPHERE = Somatic and Psychological Health Report. β=standardized beta coefficients. SE = robust standard error. Statistically significant associations are bolded.

Figure 1.

Figure 1

Open in a new tab

Association between depression/anxiety and retinal arteriolar caliber. Adolescents and young adults with a greater number of depression and anxiety symptoms showed wider arteriolar caliber. Note. Depression symptoms were grouped such that the first and third categories roughly correspond to the bottom and top deciles of the sample. Raw means, unadjusted for covariates, are presented. The p-value indicates the results of a t-test comparing the group with no symptoms to the group with 9+ symptoms. Error bars = robust standard errors.

As an additional check of these associations, we re-ran Model 2 analyses while also controlling for mean arterial blood pressure (MABP; calculated as 2/3 diastolic + 1/3 systolic blood pressure) in a subset of participants (n=291) who had their blood pressure taken as part of an earlier study (M age=14.27 years). MABP was associated with narrower arterioles (r=−0.18, p=.004), consistent with previous research, but was not associated with depression/anxiety (r=-.01), somatization (r=−0.01), or fatigue (0.03). As such, associations between mental health measures and arteriolar caliber were unchanged from before to after controlling for MABP. For example, the association between depression/anxiety and arteriolar caliber was β=0.08 before and after controlling for MABP.

Finally, in order to determine whether affective symptoms of depression/anxiety were associated with arteriolar caliber over and above somatic symptoms, we examined a model including depression/anxiety, somatization, and fatigue as simultaneous predictors of arteriolar caliber. (Smoking status, BMI, sphericity, axial length, age, and sex were included as covariates.) The association between depression/anxiety and arteriolar caliber was unchanged after additionally controlling for somatization and fatigue (β=0.08), though this association did not reach statistical significance (p=.099).

Discussion

We found that adolescents and young adults with symptoms of depression/anxiety had wider retinal arteriolar caliber. This is the first study, to our knowledge, to demonstrate an association between depression/anxiety and retinal vessel caliber in a young, otherwise healthy population. Our finding is of interest because while depression and anxiety first develop in adolescence (52), cardiovascular diseases are typically not apparent until years later. Our finding, therefore, adds to a small but growing body of literature suggesting that the pathophysiological mechanisms linking depression and anxiety with cardiovascular disease may be operative from a young age (53–56), possibly at the level of the microvasculature.

The specific pathophysiological mechanisms underlying wider arteriolar caliber are not entirely understood, but one hypothesized mechanism is endothelial dysfunction (impairment of nitric oxide-mediated vasodilation). Wider retinal arteriolar caliber is a sign of impaired autoregulation (57) and has been shown to be associated with reduced flicker-induced vasodilation (58). Notably, endothelial dysfunction is seen in individuals with depression and anxiety (5, 56, 59). For example, a meta-analysis reported a statistically significant overall correlation of 0.19 between depressed mood and reduced flow-mediated dilation in adults (59). Recent studies of children and adolescents have also shown an association between depression and anxiety and impaired endothelial function assessed using the EndoPAT device (54–56). Moreover, a study using arterial spin labeling technology demonstrated that adolescents diagnosed with depression showed altered cerebral perfusion (60), which could be consistent with impaired autoregulation. These findings further strengthen the possibility that abnormal vascular processes linking depression and anxiety to later cardiovascular disease may begin in childhood.

Our finding of an association between depression/anxiety and wider arteriolar caliber in adolescents and young adults is generally consistent with three other studies of adults (18, 19, 25), but findings in adults are inconsistent. A few studies of adults have shown an association between depression and narrower (rather than wider) arteriolar caliber and/or wider venular caliber (Table 1). The reasons for the discrepancies across studies of adults are uncertain, but inconsistent findings may be attributable to methodological differences between studies, such as the age and overall physical health of the sample. Older adults have a higher prevalence of vascular risk factors that exert opposing influences on the microvasculature. For example, hypertension-induced arteriolar narrowing and sclerosis in older adults could obscure the effects of pathological vascular processes that might cause wider arteriolar caliber. The relative healthiness of the adolescents and young adults in the current study reduces the chances of such confounding by other cardiovascular risks. Another possible explanation for the mixed findings is that wider arteriolar caliber might reflect an early emerging microvascular abnormality, whereas wider venular caliber could reflect a more entrenched pathological process. Prospective longitudinal studies are needed to address this question.

A limitation of the current study is that retinal vessel caliber was not assessed concurrently with depression/anxiety symptoms, which may have attenuated their association. We note, however, that the association between depression/anxiety and retinal arteriolar caliber was unchanged when we restricted the analyses to participants (n=345) for whom retinal imaging and depression/anxiety data were collected within 1 year of each other (β=0.09 in this subsample compared with the full sample estimate of β=0.09). A second limitation is that we only measured retinal vessel caliber at a single time point and, therefore, we cannot determine the temporal ordering of depression/anxiety symptoms and wider arteriolar caliber. The directional and causal nature of the association remains unclear. For example, wider arterioles may be a consequence of depression/anxiety. Conversely, depression/anxiety symptoms may result from wider arterioles or from shared mechanisms that contribute to both. A related limitation is that we did not use the twin design to determine whether common genetic or environmental factors contribute to the association between depression/anxiety and retinal vessel caliber. Studies from this sample (as well as others) have shown that genetic factors play a significant role in retinal vessel caliber (39) and depression/anxiety (40). Moreover, a study of adult twins found a modest genetic correlation between depression and coronary artery disease (61). Thus, a natural question is whether the genetic factors underlying depression/anxiety and retinal vessel caliber overlap. The cross-twin, cross-trait correlations were fairly similar for MZ and DZ twins in this sample (MZ=0.09, −0.01; DZ=0.10, 0.12), suggesting a role for shared-environmental influences in the association between depression/anxiety and arteriolar caliber. However, these correlations were too small to reliably parse genetic and environmental influences.

Third, we did not distinguish between depression and anxiety symptoms or assess clinically diagnosable depression and anxiety. Thus, it is unclear whether retinal vessel caliber may show differential associations with depression and anxiety symptoms or whether results will apply to those meeting diagnostic criteria for depression and anxiety disorders. Depression and anxiety disorders tap both affective and somatic symptoms, however, leaving some researchers to question whether somatic symptoms drive the association between depression and anxiety and cardiovascular disease (62, 63). A strength of our study is that we were able to distinguish between affective and somatic symptoms, and a multiple regression analysis suggested that affective symptoms of depression/anxiety may be useful indicators of cardiovascular risk. Nonetheless, ongoing data collection in our twins (33) will enable us to examine the association between retinal vessel caliber and clinical indices of depression and anxiety as well as provide a more powerful means of modeling direction of causation.

This study has a number of implications. First, our finding that generally healthy adolescents and young adults with depression/anxiety symptoms have wider arteriolar caliber suggests that depression/anxiety-associated cardiovascular risk may have its roots in childhood. Second, affective symptoms of depression/anxiety may identify youth at risk for cardiovascular disease. Therefore, routine screening for affective symptoms of depression and anxiety may be important for the cardiovascular health of young people as well as older adults (64). Third, retinal imaging is a simple, non-invasive, and cost-effective approach to assessing microvascular health in children, adolescents, and adults. Future research can use retinal imaging to address a variety of important questions. For example, longitudinal studies can address whether increases in depression and anxiety symptoms track with increases in retinal arteriolar caliber, and treatment studies can address whether improvement in depressive and anxiety symptoms is associated with changes in arteriolar caliber. In summary, we provide initial evidence that adolescents and young adults with depression/anxiety symptoms show microvascular abnormality, a finding that adds to a growing body of research suggesting that the link between depression/anxiety and cardiovascular disease dates back to childhood.

Supplementary Material

FINAL PRODUCTION FILE_ SDC

Acknowledgments

Sources of Funding

This work was supported by grants from the Australian Research Council (ARC); the National Health & Medical Research Council (NHMRC); Beyond Blue, Australia; and by the United States National Institute on Drug Abuse (R00DA023549). We also thank the following organizations for their financial support: Clifford Craig Medical Research Trust, Ophthalmic Research Institute of Australia (ORIA), American Health Assistance Foundation (AHAF), Peggy and Leslie Cranbourne Foundation, Foundation for Children, National Health and Medical Research Foundation Project Grant (2005–2007), NEI Project Grant (2007–2010).

The authors would like to thank Jane MacKinnon, Shayne Brown, Lisa Kearns, Jonathan Ruddle, Paul Sanfilippo, Fleur O’Hare, Sandra Staffieri, Johan Poulsen, Justin Sherwin, Robert Macmillan, Byoung Sung Chu, Katherine Smallcombe, Olivia Bigault, Colleen Wilkinson, Julie Barbour, Robin Wilkinson, Rachael Adams, Robyn Troutbeck, Jonathan Yeoh, Ya Ling Ma, Trent Roydhouse, Lindsey Scotter, Katarina Creese, Vischal Jhanji, Sonya Bennett, Christine Chen, Ann Eldridge, Marlene Grace, Yingfeng Zheng, Jian Zhang, Mingguang He and Amy Cohn for helping examine twins. In addition, we appreciate the assistance in recruiting twins from Thanuja Gunasekera, Allison McKenzie, Anne-Louise Ponsonby, Terry Dwyer, James Dilger, Palma Ragno, Jenny Boadle, Kim Dorrell, Shyamali Dharmage, John Hopper, Christopher Hammond, Terri Young and Jamie Craig.

ABBREVIATIONS

SPHERE

Somatic and Psychological Health Report

CRAE

central retinal arteriolar equivalent

CRVE

central retinal venular equivalent

BMI

body mass index

MABP

mean arterial blood pressure

MZ

monozygotic

DZ

dizygotic

BLTS

Brisbane Longitudinal Twin Study

DSM

Diagnostic and Statistical Manual of Mental Disorders

IRT

item response theory

Footnotes

Conflicts of Interest

No conflicts of interest to declare.

References

  • 1.Anda R, Williamson D, Jones D, Macera C, Eaker E, Glassman A, Marks J. Depressed affect, hopelessness, and the risk of ischemic-heart-disease in a cohort of United States adults. Epidemiology. 1993;4:285–293. doi: 10.1097/00001648-199307000-00003. [DOI] [PubMed] [Google Scholar]
  • 2.Ford DE, Mead LA, Chang PP, Cooper-Patrick L, Wang NY, Klag MJ. Depression is a risk factor for coronary artery disease in men - the Precursors Study. Arch Intern Med. 1998;158:1422–1426. doi: 10.1001/archinte.158.13.1422. [DOI] [PubMed] [Google Scholar]
  • 3.Pratt LA, Ford DE, Crum RM, Armenian HK, Gallo JJ, Eaten WW. Depression, psychotropic medication, and risk of myocardial infarction - prospective data from the Baltimore ECA Follow-Up. Circulation. 1996;94:3123–3129. doi: 10.1161/01.cir.94.12.3123. [DOI] [PubMed] [Google Scholar]
  • 4.Glassman AH, Shapiro PA. Depression and the course of coronary artery disease. Am J Psychiat. 1998;155:4–11. doi: 10.1176/ajp.155.1.4. [DOI] [PubMed] [Google Scholar]
  • 5.Nemeroff CB, Goldschmidt-Clermont PJ. Heartache and heartbreak-the link between depression and cardiovascular disease. Nat Rev Cardiol. 2012;9:526–539. doi: 10.1038/nrcardio.2012.91. [DOI] [PubMed] [Google Scholar]
  • 6.Suls J, Bunde J. Anger, anxiety, and depression as risk factors for cardiovascular disease: the problems and implications of overlapping affective dispositions. Psychol Bull. 2005;131:260–300. doi: 10.1037/0033-2909.131.2.260. [DOI] [PubMed] [Google Scholar]
  • 7.Jakobsen AH, Foldager L, Parker G, Munk-Jorgensen P. Quantifying links between acute myocardial infarction and depression, anxiety and schizophrenia using case register databases. J Affect Disorders. 2008;109:177–181. doi: 10.1016/j.jad.2007.10.012. [DOI] [PubMed] [Google Scholar]
  • 8.Ikram MK, Ong YT, Cheung CY, Wong TY. Retinal vascular caliber measurements: clinical significance, current knowledge and future perspectives. Ophthalmologica. 2012 doi: 10.1159/000342158. [DOI] [PubMed] [Google Scholar]
  • 9.Sun C, Wang JJ, Mackey DA, Wong TY. Retinal vascular caliber: systemic, environmental, and genetic associations. Surv Ophthalmol. 2009;54:74–95. doi: 10.1016/j.survophthal.2008.10.003. [DOI] [PubMed] [Google Scholar]
  • 10.Patton N, Aslam T, MacGillivray T, Pattie A, Deary IJ, Dhillon B. Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: a rationale based on homology between cerebral and retinal microvasculatures. J Anat. 2005;206:319–348. doi: 10.1111/j.1469-7580.2005.00395.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Cheung CYL, Ikram MK, Sabanayagam C, Wong TY. Retinal microvasculature as a model to study the manifestations of hypertension. Hypertension. 2012;60:1094-+. doi: 10.1161/HYPERTENSIONAHA.111.189142. [DOI] [PubMed] [Google Scholar]
  • 12.McGeechan K, Liew G, Macaskill P, Irwig L, Klein R, Klein BE, Wang JJ, Mitchell P, Vingerling JR, Dejong PT, Witteman JC, Breteler MM, Shaw J, Zimmet P, Wong TY. Meta-analysis: retinal vessel caliber and risk for coronary heart disease. Annals of Internal Medicine. 2009;151:404–413. doi: 10.7326/0003-4819-151-6-200909150-00005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.McGeechan K, Liew G, Macaskill P, Irwig L, Klein R, Klein BEK, Wang JJ, Mitchell P, Vingerling JR, de Jong PTVM, Witteman JCM, Breteler MMB, Shaw J, Zimmet P, Wong TY. Prediction of incident stroke events based on retinal vessel caliber: a systematic review and individual-participant meta-analysis. Am J Epidemiol. 2009;170:1323–1332. doi: 10.1093/aje/kwp306. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Shalev I, Moffitt TE, Wong TY, Meier MH, Houts RM, Ding J, Cheung CY, Ikram MK, Caspi A, Poulton R. Retinal vessel caliber and lifelong neuropsychological functioning: retinal imaging as an investigative tool for cognitive epidemiology. Psychol Sci. 2013;24:1198–1207. doi: 10.1177/0956797612470959. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.de Jong FJ, Schrijvers EMC, Ikram MK, Koudstaal PJ, de Jong PTVM, Hofman A, Vingerling JR, Breteler MMB. Retinal vascular caliber and risk of dementia: the Rotterdam Study. Neurology. 2011;76:816–821. doi: 10.1212/WNL.0b013e31820e7baa. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Sun C, Tikellis G, Klein R, Steffens DC, Larsen EK, Siscovick DS, Klein BE, Wong TY. Are microvascular abnormalities in the retina associated with depression symptoms? The Cardiovascular Health Study. The American Journal of Geriatric Psychiatry. 2007;15:335–343. doi: 10.1097/01.JGP.0000247161.98311.0f. [DOI] [PubMed] [Google Scholar]
  • 17.Kim DH, Newman AB, Hajjar I, Strotmeyer ES, Klein R, Newton E, Sarnak MJ, Burke GL, Lipsitz LA. Retinal microvascular signs and functional loss in older persons: the Cardiovascular Health Study. Stroke. 2011;42:1589–1595. doi: 10.1161/STROKEAHA.110.605261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Nguyen TT, Wong TY, Islam FM, Hubbard L, Miller J, Haroon E, Darwin C, Esser B, Kumar A. Is depression associated with microvascular disease in patients with type 2 diabetes? Depression and Anxiety. 2008;25:E158–E162. doi: 10.1002/da.20427. [DOI] [PubMed] [Google Scholar]
  • 19.Nguyen TT, Wong TY, Islam FMA, Hubbard L, Ajilore O, Haroon E, Darwin C, Esser B, Kumar A. Evidence of early retinal microvascular changes in patients with type 2 diabetes and depression. Psychosom Med. 2010;72:535–538. doi: 10.1097/PSY.0b013e3181da90f4. [DOI] [PubMed] [Google Scholar]
  • 20.Cheung N, Rogers S, Mosley TH, Klein R, Couper D, Wong TY. Vital exhaustion and retinal microvascular changes in cardiovascular disease: Atherosclerosis Risk in Communities Study. Psychosom Med. 2009;71:308–312. doi: 10.1097/PSY.0b013e318190f009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Ikram MK, Luijendijk HJ, Hofman A, de Jong PTVM, Breteler MMB, Vingerling JR, Tiemeier H. Retinal vascular calibers and risk of late-life depression: the Rotterdam Study. Am J Geriat Psychiat. 2010;18:452–455. doi: 10.1097/jgp.0b013e3181d69250. [DOI] [PubMed] [Google Scholar]
  • 22.Jensen RA, Shea S, Ranjit N, Diez-Roux A, Wong TY, Klein R, Klein BEK, Cotch MF, Siscovick DS. Psychosocial risk factors and retinal microvascular signs. Am J Epidemiol. 2010;171:522–531. doi: 10.1093/aje/kwp414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Caspi A, Houts RM, Belsky DW, Goldman-Mellor SJ, Harrington H, Israel S, Meier MH, Ramrakha S, Shalev I, Poulton R. The p factor one general psychopathology factor in the structure of psychiatric disorders? Clinical Psychological Science. 2014;2:119–137. doi: 10.1177/2167702613497473. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Meier MH, Shalev W, Moffitt TE, Kapur S, Keefe RSE, Wong TY, Belsky DW, Harrington HL, Hogan S, Houts R, Caspi A, Poulton R. Microvascular abnormality in schizophrenia as shown by retinal imaging. Am J Psychiat. 2013;170:1451–1459. doi: 10.1176/appi.ajp.2013.13020234. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Li LJ, Ikram MK, Broekman L, Cheung CY, Chen H, Gooley JJ, Soh SE, Gluckman P, Kwek K, Chong YS, Meaney M, Wong TY, Saw SM. Antenatal mental health and retinal vascular caliber in pregnant women. Translational Vision Science & Technology. 2013;2:2. doi: 10.1167/tvst.2.2.2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Barker DJP, Osmond C, Golding J, Kuh D, Wadsworth MEJ. Growth inutero, blood-pressure in childhood and adult life, and mortality from cardiovascular disease. Brit Med J. 1989;298:564–567. doi: 10.1136/bmj.298.6673.564. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Kavey REW, Daniels SR, Lauer RM, Atkins DL, Hayman LL, Taubert K. American heart association guidelines for primary prevention of atherosclerotic cardiovascular disease beginning in childhood. Circulation. 2003;107:1562–1566. doi: 10.1161/01.cir.0000061521.15730.6e. [DOI] [PubMed] [Google Scholar]
  • 28.Shonkoff JP, Boyce WT, McEwen BS. Neuroscience, molecular biology, and the childhood roots of health disparities: building a new framework for health promotion and disease prevention. JAMA. 2009;301:2252–2259. doi: 10.1001/jama.2009.754. [DOI] [PubMed] [Google Scholar]
  • 29.Maughan B, Kim-Cohen J. Continuities between childhood and adult life. Brit J Psychiat. 2005;187:301–303. doi: 10.1192/bjp.187.4.301. [DOI] [PubMed] [Google Scholar]
  • 30.Li SX, Chen W, Srinivasan SR, Bond MG, Tang R, Urbina EM, Berenson GS. Childhood cardiovascular risk factors and carotid vascular changes in adulthood - the Bogalusa Heart Study. JAMA. 2003;290:2271–2276. doi: 10.1001/jama.290.17.2271. [DOI] [PubMed] [Google Scholar]
  • 31.Vaccarino AL, Sills TL, Evans KR, Kalali AH. Multiple pain complaints in patients with major depressive disorder. Psychosom Med. 2009;71:159–162. doi: 10.1097/PSY.0b013e3181906572. [DOI] [PubMed] [Google Scholar]
  • 32.Wright MJ, Martin NG. Brisbane Adolescent Twin Study: outline of study methods and research projects. Aust J Psychol. 2004;56:65–78. [Google Scholar]
  • 33.Gillespie NA, Henders AK, Davenport TA, Hermens DF, Wright MJ, Martin NG, Hickie IB. The Brisbane Longitudinal Twin Study: pathways to cannabis use, abuse, and dependence project: current status, preliminary results, and future directions. Twin Research and Human Genetics. 2013;16:21–33. doi: 10.1017/thg.2012.111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.de Moor MHM, Costa PT, Terracciano A, Krueger RF, de Geus EJC, Toshiko T, Penninx BWJH, Esko T, Madden PAF, Derringer J, Amin N, Willemsen G, Hottenga JJ, Distel MA, Uda M, Sanna S, Spinhoven P, Hartman CA, Sullivan P, Realo A, Allik J, Heath AC, Pergadia ML, Agrawal A, Lin P, Grucza R, Nutile T, Ciullo M, Rujescu D, Giegling I, Konte B, Widen E, Cousminer DL, Eriksson JG, Palotie A, Peltonen L, Luciano M, Tenesa A, Davies G, Lopez LM, Hansell NK, Medland SE, Ferrucci L, Schlessinger D, Montgomery GW, Wright MJ, Aulchenko YS, Janssens ACJW, Oostra BA, Metspalu A, Abecasis GR, Deary IJ, Raikkonen K, Bierut LJ, Martin NG, van Duijn CM, Boomsma DI. Meta-analysis of genome-wide association studies for personality. Mol Psychiatr. 2012;17:337–349. doi: 10.1038/mp.2010.128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Ikram MK, Xueling S, Jensen RA, Cotch MF, Hewitt AW, Ikram MA, Wang JJ, Klein R, Klein BEK, Breteler MMB, Cheung N, Liew G, Mitchell P, Uitterlinden AG, Rivadeneira F, Hofman A, de Jong PTVM, van Duijn CM, Kao L, Cheng CY, Smith AV, Glazer NL, Lumley T, McKnight B, Psaty BM, Jonasson F, Eiriksdottir G, Aspelund T, Harris TB, Launer LJ, Taylor KD, Li XH, Iyengar SK, Xi QS, Sivakumaran TA, Mackey DA, MacGregor S, Martin NG, Young TL, Bis JC, Wiggins KL, Heckbert SR, Hammond CJ, Andrew T, Fahy S, Attia J, Holliday EG, Scott RJ, Islam FMA, Rotter JI, McAuley AK, Boerwinkle E, Tai ES, Gudnason V, Siscovick DS, Vingerling JR, Wong TY, Consortium GB. Four novel loci (19q13, 6q24, 12q24, and 5q14) influence the microcirculation in vivo. Plos Genet. 2010;6 doi: 10.1371/journal.pgen.1001184. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Mitchell P, Cheung N, de Haseth K, Taylor B, Rochtchina E, Islam FMA, Wang JJ, Saw SM, Wong TY. Blood pressure and retinal arteriolar narrowing in children. Hypertension. 2007;49:1156–1162. doi: 10.1161/HYPERTENSIONAHA.106.085910. [DOI] [PubMed] [Google Scholar]
  • 37.Aitken JF, Green A, Eldridge A, Green L, Pfitzner J, Battistutta D, Martin NG. Comparability of nevus counts between and within examiners, and comparison with computer image-analysis. British Journal of Cancer. 1994;69:487–491. doi: 10.1038/bjc.1994.88. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Mackey DA, MacKinnon JR, Brown SA, Kearns LS, Ruddle JB, Sanfilippo PG, Sun C, Hammond CJ, Young TL, Martin NG, Hewitt AW. Twins Eye Study in Tasmania (TEST): rationale and methodology to recruit and examine twins. Twin Research and Human Genetics. 2009;12:441–454. doi: 10.1375/twin.12.5.441. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Sun C, Zhu G, Wong TY, Hewitt AW, Ruddle JB, Hodgson L, Montgomery GW, Young TL, Hammond CJ, Craig JE, Martin NG, He MG, Mackey DA. Quantitative genetic analysis of the retinal vascular caliber: the Australian Twins Eye Study. Hypertension. 2009;54:788–U200. doi: 10.1161/HYPERTENSIONAHA.109.132902. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Hansell NK, Wright MJ, Medland SE, Davenport TA, Wray NR, Martin NG, Hickie IB. Genetic co-morbidity between neuroticism, anxiety/depression and somatic distress in a population sample of adolescent and young adult twins. Psychol Med. 2012;42:1249–1260. doi: 10.1017/S0033291711002431. [DOI] [PubMed] [Google Scholar]
  • 41.Hickie IB, Davenport TA, Hadzi-Pavlovic D, Koschera A, Naismith SL, Scott EM, Wilhelm KA. Development of a simple screening tool for common mental disorders in general practice. Med J Australia. 2001;175:S10–S17. doi: 10.5694/j.1326-5377.2001.tb143784.x. [DOI] [PubMed] [Google Scholar]
  • 42.Hickie IB, Davenport TA, Scott EM, Hadzi-Pavlovic D, Naismith SL, Koschera A. Unmet need for recognition of common mental disorders in Australian general practice. Med J Australia. 2001;175:S18–S24. doi: 10.5694/j.1326-5377.2001.tb143785.x. [DOI] [PubMed] [Google Scholar]
  • 43.Wray NR, Coventry WL, James MR, Montgomery GW, Eaves LJ, Martin NG. In Genetic Effects on Environmental Vulnerability to Disease: Novartis Foundation Symposium. Vol. 293. Wiley Online Library; 2008. Use of monozygotic twins to investigate the relationship between 5httlpr genotype, depression and stressful life events: an application of item response theory. [DOI] [PubMed] [Google Scholar]
  • 44.Sun C, Ponsonby AL, Wong TY, Brown SA, Kearns LS, Cochrane J, MacKinnon JR, Ruddle JB, Hewitt AW, Liew G, Dwyer T, Scurrah K, Mackey DA. Effect of birth parameters on retinal vascular caliber: the Twins Eye Study in Tasmania. Hypertension. 2009;53:487–493. doi: 10.1161/HYPERTENSIONAHA.108.125914. [DOI] [PubMed] [Google Scholar]
  • 45.Wong TY, Knudtson MD, Klein R, Klein BEK, Meuer SM, Hubbard LD. Computer-assisted measurement of retinal vessel diameters in the Beaver Dam Eye Study - methodology, correlation between eyes, and effect of refractive errors. Ophthalmology. 2004;111:1183–1190. doi: 10.1016/j.ophtha.2003.09.039. [DOI] [PubMed] [Google Scholar]
  • 46.Knudtson MD, Lee KE, Hubbard LD, Wong TY, Klein R, Klein BEK. Revised formulas for summarizing retinal vessel diameters. Curr Eye Res. 2003;27:143–149. doi: 10.1076/ceyr.27.3.143.16049. [DOI] [PubMed] [Google Scholar]
  • 47.Pine DS, Goldstein RB, Wolk S, Weissman MM. The association between childhood depression and adulthood body mass index. Pediatrics. 2001;107:1049–1056. doi: 10.1542/peds.107.5.1049. [DOI] [PubMed] [Google Scholar]
  • 48.Simon GE, Von Korff M, Saunders K, Miglioretti DL, Crane PK, van Belle G, Kessler RC. Association between obesity and psychiatric disorders in the US adult population. Arch Gen Psychiatry. 2006;63:824–830. doi: 10.1001/archpsyc.63.7.824. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Glassman AH, Helzer JE, Covey LS, Cottler LB, Stetner F, Tipp JE, Johnson J. Smoking, smoking cessation, and major depression. JAMA. 1990;264:1546–1549. [PubMed] [Google Scholar]
  • 50.Degenhardt L, Hall W, Lynskey M. Alcohol, cannabis and tobacco use among Australians: a comparison of their associations with other drug use and use disorders, affective and anxiety disorders, and psychosis. Addiction. 2001;96:1603–1614. doi: 10.1046/j.1360-0443.2001.961116037.x. [DOI] [PubMed] [Google Scholar]
  • 51.Cheung N, Tikellis G, Saw SM, Islam FMA, Mitchell P, Wang JJ, Wong TY. Relationship of axial length and retinal vascular caliber in children. Am J Ophthalmol. 2007;144:658–662. doi: 10.1016/j.ajo.2007.07.023. [DOI] [PubMed] [Google Scholar]
  • 52.Merikangas KR, He JP, Burstein M, Swanson SA, Avenevoli S, Cui LH, Benjet C, Georgiades K, Swendsen J. Lifetime prevalence of mental disorders in US adolescents: results from the National Comorbidity Survey Replication-Adolescent Supplement (NCS-A) J Am Acad Child Psy. 2010;49:980–989. doi: 10.1016/j.jaac.2010.05.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Dietz LJ, Matthews KA. Depressive symptoms and subclinical markers of cardiovascular disease in adolescents. J Adolescent Health. 2011;48:579–584. doi: 10.1016/j.jadohealth.2010.09.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Tomfohr LM, Martin TM, Miller GE. Symptoms of depression and impaired endothelial function in healthy adolescent women. J Behav Med. 2008;31:137–143. doi: 10.1007/s10865-007-9141-4. [DOI] [PubMed] [Google Scholar]
  • 55.Tomfohr LM, Murphy MLM, Miller GE, Puterman E. Multiwave associations between depressive symptoms and endothelial function in adolescent and young adult females. Psychosom Med. 2011;73:456–461. doi: 10.1097/PSY.0b013e3182228644. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Osika W, Montgomery SM, Dangardt F, Wahrborg P, Gan LM, Tideman E, Friberg P. Anger, depression and anxiety associated with endothelial function in childhood and adolescence. Arch Dis Child. 2011;96:38–43. doi: 10.1136/adc.2008.152777. [DOI] [PubMed] [Google Scholar]
  • 57.Gardiner TA, Archer DB, Curtis TM, Stitt AW. Arteriolar involvement in the microvascular lesions of diabetic retinopathy: implications for pathogenesis. Microcirculation. 2007;14:25–38. doi: 10.1080/10739680601072123. [DOI] [PubMed] [Google Scholar]
  • 58.Nguyen TT, Kawasaki R, Kreis AJ, Wang JJ, Shaw J, Vilser W, Wong TY. Correlation of light-flicker-induced retinal vasodilation and retinal vascular caliber measurements in diabetes. Invest Ophth Vis Sci. 2009;50:5609–5613. doi: 10.1167/iovs.09-3442. [DOI] [PubMed] [Google Scholar]
  • 59.Cooper DC, Tomfohr LM, Milic MS, Natarajan L, Bardwell WA, Ziegler MG, Dimsdale JE. Depressed mood and flow-mediated dilation: a systematic review and meta-analysis. Psychosom Med. 2011;73:360–369. doi: 10.1097/PSY.0b013e31821db79a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Ho TC, Wu J, Shin DD, Liu TT, Tapert SF, Yang G, Connolly CG, Frank GKW, Max JE, Wolkowitz O, Eisendrath S, Hoeft F, Banerjee D, Hood K, Hendren RL, Paulus MP, Simmons AN, Yang TT. Altered cerebral perfusion in executive, affective, and motor networks during adolescent depression. J Am Acad Child Psy. 2013;52:1076–1091. doi: 10.1016/j.jaac.2013.07.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Kendler KS, Gardner CO, Fiske A, Gatz M. Major depression and coronary artery disease in the Swedish Twin Registry: phenotypic, genetic, and environmental sources of comorbidity. Arch Gen Psychiatry. 2009;66:857–863. doi: 10.1001/archgenpsychiatry.2009.94. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Lee KS, Lennie TA, Heo S, Moser DK. Association of physical versus affective depressive symptoms with cardiac event-free survival in patients with heart failure. Psychosom Med. 2012;74:452–458. doi: 10.1097/PSY.0b013e31824a0641. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Kop WJ. Somatic depressive symptoms, vital exhaustion, and fatigue: divergent validity of overlapping constructs. Psychosom Med. 2012;74:442–445. doi: 10.1097/PSY.0b013e31825f30c7. [DOI] [PubMed] [Google Scholar]
  • 64.Colquhoun DM, Bunker SJ, Clarke DM, Glozier N, Hare DL, Hickie IB, Tatoulis J, Thompson DR, Tofler GH, Wilson A, Branagan MG. Screening, referral and treatment for depression in patients with coronary heart disease. Med J Australia. 2013;198:483–484. doi: 10.5694/mja13.10153. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

FINAL PRODUCTION FILE_ SDC
NIHMS625974-supplement-FINAL_PRODUCTION_FILE__SDC.docx (57.7KB, docx)

RESOURCES