Title page Individual multi-locus heterozygosity is associated with ...

Title page 1

Individual multi-locus heterozygosity is associated with lower morning plasma cortisol 2

concentration 3

Lina Zgaga1,2

, Veronique Vitart3, Caroline Hayward

3, Darko Kastelan

4, Ozren Polašek

5, Miro 4

Jakovljevic6, Ivana Kolcic

5, Zrinka Biloglav

2, Alan F Wright

3, Harry Campbell

1§, Brian R 5

Walker7§*

and Igor Rudan1§*

6

§ joint author in this position 7

8

1 Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK 9

2 Department of Medical statistics, Epidemiology and Medical Informatics, University of 10

Zagreb School of Medicine, 10000 Zagreb, Croatia 11

3 MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of 12

Edinburgh, Edinburgh EH4 2XU, UK 13

4 Department of Endocrinology, University of Zagreb School of Medicine, University 14

Hospital Center, 10000 Zagreb, Croatia 15

5 Department of Public Health, University of Split, 21000 Split, Croatia 16

6 Department of Psychiatry, University of Zagreb School of Medicine, University Hospital 17

Center, 10000 Zagreb, Croatia 18

7 University of Edinburgh/British Heart Foundation Centre for Cardiovascular Science, 19

Queen's Medical Research Institute, Edinburgh EH16 4TJ, UK 20

21

of 27 Accepted Preprint first posted on 1 May 2013 as Manuscript EJE-12-0916

Copyright © 2013 European Society of Endocrinology.

Correspondence about the manuscript: Lina Zgaga, Public Health Sciences, University of 22

Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK, Phone 0131 650 4332, e-mail: 23

[email protected] 24

25

* Corresponding authors: 26

Brian Walker, University of Edinburgh/British Heart Foundation Centre for Cardiovascular 27

Science, Queen's Medical Research Institute, Edinburgh EH16 4TJ, UK, Phone Tel +44 28

(0)131 242 6770, Fax +44 (0)131 242 6779, email: [email protected] 29

Igor Rudan, Centre for Population Health Sciences, University of Edinburgh, Teviot Place, 30

Edinburgh EH8 9AG, UK, Phone +44 (0)131 650 3210, Fax 0131 650 3037, e-mail: 31

[email protected] 32

33

Short title: Multi-locus heterozygosity and cortisol 34

Key words: cortisol, heterozygosity, psychological distress, inbreeding, GHQ, 35

heterozygosity-fitness correlation, heterozygote advantage, standardized multi-locus 36

heterozygosity 37

38

Word count: 2658 39

40

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Abstract 41

Objective. Stress is implicated as a risk factor for numerous illnesses in humans, putatively 42

in part mediated by biological responses to stress, such as elevated cortisol. The theory of 43

genetic homeostasis suggests that individual heterozygosity facilitates compensation for 44

environmental stresses. We hypothesized that heterozygosity ameliorates the biological 45

response to a given level of perceived stress, reflected in lower plasma cortisol 46

concentrations. 47

Design. We examine the role of heterozygosity on the association between perceived 48

psychological stress and morning cortisol concentrations in 854 individuals from the isolated 49

island of Vis, Croatia. 50

Methods. Cortisol was measured in morning plasma samples. 1184 autosomal microsatellite 51

markers were genotyped and individual multi-locus heterozygosity was calculated as the 52

proportion of heterozygous markers. General Health Questionnaire (GHQ-30) was used to 53

assess the degree of psychological distress. 54

Results. Mean multi-locus heterozygosity was 34.85±0.45% (range: 31.97-36.22%). 55

Psychological distress (GHQ Likert score >31) was more prevalent in women (37% versus 56

18% in men, p<0.0001), in less educated people (β=-0.35 per year in school, p<0.001) and in 57

lower socio-economic classes (β=-3.59, p<0.0001). Cortisol was positively associated with 58

psychological distress (β=2.20, p=0.01). In a regression model adjusting for age, BMI, 59

education and GHQ-30 score, multi-locus heterozygosity was independently and inversely 60

associated with morning plasma cortisol (p=0.005). 61

Conclusion. More heterozygous individuals, as measured by microsatellite markers, had 62

lower morning plasma cortisol concentrations for a given level of perceived psychological 63

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stress. This may be important, as higher cortisol concentrations may increase allostatic load 64

and be associated with higher risk of stress-related illness. 65

66

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Introduction 67

Stress has been implicated as a risk factor for numerous illnesses and for mortality in humans 68

1, 2. However, large inter-individual differences in perception of stress, response to stress and 69

stress-induced susceptibility to disease can alter the stress-to-illness pathway 3, 4

. Relevant 70

individual characteristics include both psychological factors such as personality or previous 71

experiences, and somatic differences including genetic makeup 5, 6

. 72

The biological response to stress includes activation of the hypothalamic-pituitary-adrenal 73

(HPA) axis which regulates release of cortisol. Elevated cortisol contributes to adaptive 74

changes in immune, cardiovascular and metabolic systems to maintain homeostasis, a process 75

called allostasis. However, sustained elevation of cortisol (as exaggerated in Cushing's 76

syndrome) results in maladaptive changes, representing 'allostatic load'. 77

In 1954 Lerner introduced the idea of genetic homeostasis, hypothesizing that individual 78

heterozygosity is important because it facilitates compensation for environmental stresses and 79

enhances an individual’s ability to maintain homeostasis in changing environments 7. 80

Advantages of increased locus and multi-locus heterozygosity for disease resistance, 81

longevity and fitness, especially when the organism is challenged, has been described for 82

several species including humans 8-10

. However, the underlying mechanism for this 83

“heterozygosity-fitness correlation” is not clear and reported associations with infectious 84

disease susceptibility and common complex disease risk factors are usually weak, perhaps 85

due to the fact that most human populations are outbred with nearly uniform and high 86

heterozygosity of individuals 11-14

. 87

A closely related and more frequently investigated research theme is inbreeding, which leads 88

to decreased heterozygosity in offspring. The phrase “inbreeding depression” reflects the 89

negative effects of inbreeding and the general inferiority of the inbred offspring. Besides the 90

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well-characterized role in monogenic conditions, negative effects of inbreeding and 91

decreased heterozygosity on fitness in humans have also been described for complex traits 92

and diseases 14-16

. Because its detrimental consequences are well-known among layman and 93

professionals, inbreeding is discouraged in most human societies and also in agricultural and 94

farming practices. Interestingly, it has been suggested that rural-to-urban migration and 95

progressive globalization in the past century has led to outbreeding and consequentially to an 96

increase in individual heterozygosity, that may have had a beneficial effect on a range of 97

human traits and could in part account for improved health and longevity 9, 15-18

. 98

We aimed to investigate the role of heterozygosity in the individual biological response to 99

perceived psychological stress. We did so by examining the associations between 100

psychological stress, morning cortisol concentration and heterozygosity. 101

102

103

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Methods 104

The Croatia-Vis study included 924 unselected individuals from the island of Vis, Croatia, 105

aged 18-93 years, who were phenotyped for over 50 disease-related quantitative traits 9, 15, 19

. 106

The study received appropriate ethical committee approval and all participants gave informed 107

written consent. A custom-made questionnaire was used to collect information on age, socio-108

economic status (self-reported, estimated in comparison to others as: “much worse”, “a bit 109

worse”, “same”, “a bit better” or “much better”), education (number of completed years of 110

education), medication, chronic illness and ancestry. Blood samples were taken between 8:30 111

and 9:30 am in the research centre, after overnight fast and were used for genetic and 112

biochemical analysis. Individual data on medication was screened to identify individuals on 113

corticosteroid treatment or hormone replacement therapy. 114

Twenty two participants were taking corticosteroid medication and were excluded from this 115

study. Genetic data has not passed the quality control procedures below for further nine, and 116

cortisol concentration was not available for further 32. Finally, we also excluded female 117

participants on hormone replacement therapy (N=7), yielding a final sample of 854 118

participants that were included in the analysis. 119

We used the General Health Questionnaire with 30 items (GHQ-30), a screening instrument 120

for minor psychological disorders, to assess the degree of psychological distress. It was 121

administered by a survey team with many years of experience. The Likert method was used 122

for scoring GHQ-30, where answers “better than usual”, “like usual”, “worse than usual” and 123

“much worse than usual” are scored with 0, 1, 2 and 3 points, respectively. A GHQ-30 score 124

above 31 is considered suggestive of psychological distress when applied to a general 125

population 20, 21

. We considered scores >2 SD above the mean in our study population (51 126

points) as indicative of severe psychological distress. 127

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Plasma cortisol was measured by radioimmunoassay (MP Biomedicals, Cambridge, UK) with 128

an intraassay coefficient of variation of 5.1-7.0%, interassay coefficient of variation of 6.0-129

7.9% and lower limit of detection of 40 nmol/L. In regression analyses, cortisol concentration 130

was corrected for relatedness, because our sample consisted of many related individuals, 131

violating the independence of observations assumption that is required for majority of 132

statistical tests due to shared genetic factors. The GenABEL package for R allows an easy 133

adjustment for relatedness by estimating pair-wise kinship coefficients from the genome-wide 134

data. 135

DNA extraction and genotyping 136

DNA was extracted from EDTA whole blood specimens by the salting out procedure, stored 137

at the MRC Human Genetics Unit in Edinburgh, UK, and genotyped at the Center for 138

Medical Genetics, Marshfield Medical Research Foundation, USA. Samples were analyzed 139

with 1,184 autosomal markers comprising the microsatellite markers taken from the 140

Marshfield Screening Set and indel markers (detailed at 141

http://research.marshfieldclinic.org/genetics). 142

Microsatellite markers were excluded from the analysis if genotyping failed in more than 143

10% of all samples and if the locus was homozygous for all participants. We also excluded 144

individuals for whom fewer than 750 markers were successfully genotyped, because 145

genotyping failure is more common for heterozygous markers 22

. 146

147

Multi-locus and standardized multi-locus heterozygosity 148

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Data on all microsatellite markers that passed quality control was used to calculate multi-149

locus heterozygosity for each individual (MLHi), i.e. the proportion of heterozygous 150

microsatellite loci among the ones that have been successfully genotyped: 151

152

Standardized multi-locus heterozygosity (SMLH) was calculated as MLHi divided by the 153

average MLH of all other n individuals, restricted to the set of loci successfully typed in the 154

individual i. 155

156

SMLH ranged from 0.9 – 1.1, with mean±SD = 1.00±0.03. Calculations were performed 157

using the Rhh application for R (available at http://cran.r-158

project.org/web/packages/Rhh/index.html). 159

160

Statistical analysis 161

Statistical analysis was performed using R (http://www.r-project.org/). χ2 test was used to 162

analyse categorical variables. A multivariate regression model was constructed and morning 163

cortisol concentration (as a continuous variable) corrected for relatedness was used as the 164

outcome. Predictor variables used in the model were: age, gender, BMI, GHQ-30 score, 165

standardized multi-locus heterozygosity. To enable comparison between β-coefficients, 166

variables were normalized to standard normal distribution and expressed as z-scores.167

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Results 168

A total of 854 (485 (57%) female) participants were included, 499 from the Komiza village 169

and 355 from the town of Vis. The mean age of participants was 56.56±15.67 y. Median 170

duration of education was 11 y (interquartile range, IQR: 8-12 y). Duration of education was 171

inversely associated with age (p<0.0001) and was significantly longer in males (p<0.0001). 172

The median GHQ-30 (Likert) score was 26 (IQR: 20-33). A total of 245 participants (179 173

(73%) female) were categorized as suffering psychological distress (GHQ-30 >31) and 35 174

participants (25 (71%) female) had severe psychological distress (GHQ-30 >51). In a 175

multivariate regression analysis we found that GHQ-30 score was significantly associated 176

with gender (prevalence of psychological distress was higher in females (36.9%) than in 177

males (17.9%), p<0.0001), age (β-coefficient=0.13, p<0.001), duration of education (among 178

those with 8 or less years in full-time education 137 individuals (40%) were distressed, in 179

contrast to 11 (17%) among those with 16 or more years in schooling, p<0.001) and with 180

socio-economic status (prevalence of psychological distress in 5 categories of worst to best 181

socio-economic status: 70%, 43%, 27%, 18% and 17%, p<0.0001). 182

Mean morning plasma cortisol concentration was 619.62±227.05 nmol/L. There was no 183

statistically significant difference in cortisol concentration between males (617.43±199.86 184

nmol/L) and females (621.28±245.92 nmol/L), p=0.1, but age (p=0.003) and BMI (p<0.001) 185

were inversely associated with morning cortisol concentration. 186

Mean multi-locus heterozygosity (including markers that passed quality control and were not 187

homozygous in all individuals) was 34.85±0.45%, range 31.97% to 36.22%; Figure 1). 188

Standardized multi-locus heterozygosity (mean=1.00 and SD=0.03) was used in regression 189

analysis. 190

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Descriptive data according to cortisol tertiles are shown in Table 1. Standardised multi-locus 191

heterozygosity was lowest in those with highest cortisol in one-way ANOVA analysis 192

(p=0.035) and when adjusted for age and sex (p=0.015). An association between higher 193

morning cortisol concentration (adjusted for relatedness) and lower SMLH (p=0.005) was 194

also found in a regression model adjusted for age, GHQ-30 score and BMI (Table 2). The 195

association remained largely unchanged after addition of adjustment variables sex and socio-196

economic status to the model. 197

198

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199

Discussion 200

In this study we have shown that heterozygosity, as measured by microsatellite markers, is 201

significantly and inversely associated with morning plasma cortisol concentration. The 202

association remained statistically significant after adjustment for perceived psychological 203

distress and other measured potential confounders. This raises the possibility that variations 204

in plasma cortisol, including its response to stressors and its contribution to allostatic load, is 205

a mediator for the protective effect of heterozygosity on health. 206

The effect size of heterozygosity on cortisol concentration was quite small (explaining 0.9% 207

of the variance), but comparable to the effect of psychological distress found here (1.5%) and 208

in previous studies 23-26

. Moreover, for other biological variables, the percentage of variance 209

explained by heterozygosity was typically in the range from 0.07% to 3.3%, and ~1% in 210

studies with microsatellite markers (as used here) 27-29

. Also, given the marked circadian 211

variation in plasma cortisol, which peaks on waking from sleep, morning cortisol values are 212

highly variable due to variations in time of waking, stress response to venepuncture and 213

precise time of sampling so it is all the more remarkable that variation attributable to 214

heterozygosity can be detected. 215

The characteristics of the cohort from the island of Vis may have contributed to the detection 216

of these small effects in modest numbers of participants. The GHQ-30 questionnaire has been 217

shown to be a valid measure of acute psychological distress in the general population 21, 30

218

and we observed a similarly wide range of GHQ-30 scores among study participants as in 219

other studies. However, The GHQ score is not a “general stress score” and other stressors 220

may have an effect on an individual. 221

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The distribution of morning plasma cortisol concentrations was also similar to that we have 222

observed in several other cohorts (unpublished data), and the association with GHQ-30 scores 223

31-33 and other covariates including body mass index

34 was as expected. However, most 224

human populations today are outbred and individual heterozygosity is regularly found to be 225

distributed in a narrow range of high values. Geographical isolation of the island of Vis and 226

the limited immigration throughout its history are reflected in the pedigree structure of the 227

study population 15, 35

. A limited choice of sexual partners may have led to a higher degree of 228

inbreeding in this isolated population, which is reflected in the varied levels of individual 229

multi-locus heterozygosity, increasing the power of the regression analysis when 230

heterozygosity is used as a covariate. Sharing of a similar environment and lifestyle typical 231

for island populations is also advantageous for the analysis, in that participants are naturally 232

“matched” for a range of hidden influences that could confound the analysis. 233

Given limited statistical power in this study, we have not been able to explore whether 234

heterozygosity contributes to the documented associations of plasma cortisol with well-235

known risk factors for disease such as blood pressure, blood glucose etc. 34

. However, both in 236

the current cohort 9 and in the Framingham heart study

11, heterozygosity was predictive of 237

blood pressure, blood glucose, lipid profile and urate levels as well as left ventricular 238

diameter and ventricular wall thickness. 239

The mechanism for the association of heterozygosity with cortisol is unknown. It is 240

reasonable to infer a direction of causality from genetic constitution to biological variation 241

rather than vice versa. Many mutations are recessive and exhibit effects only when 242

homozygous. An individual with low heterozygosity is more likely to be homozygous for a 243

number of deleterious recessive alleles. Recent genome-wide association studies show that 244

many common complex traits in humans are influenced by DNA sequence variants at 245

multiple genetic loci 36

. It therefore seems likely that homozygosity at numerous deleterious 246

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alleles (with individually small effects) may decrease the capacity to counterbalance stressors 247

and at increased “cost” in form of increased cortisol and increased allostatic load. 248

On the other hand, there is the advantage of heterozygotes, or “overdominance”, which 249

occurs when the heterozygote genotype has a higher relative fitness than either the 250

homozygote mutant or normal homozygote 37, 38

. An example is that of sickle cell anaemia in 251

regions with prevalent malaria: homozygotes for mutant S-allele often die prematurely from 252

sickle-cell disease, individuals with two normal alleles are susceptible to severe malaria often 253

with lethal outcome, but heterozygous individuals are resistant to severe malaria and suffer 254

none or mild symptoms of sickle-cell disease 39

. By definition, less heterozygous individuals 255

will have smaller proportion of heterozygous loci, which will also include loci where 256

advantage of heterozygotes occurs. It seems likely that heterozygosity at some of the many 257

loci likely to influence plasma cortisol levels is advantageous in this way. Identification of 258

those loci, even for small effects, has the potential to flag pathways and mechanisms involved 259

in the contribution of stress and cortisol to disease development. 260

261

Potential limitations of the study include the use of microsatellite markers to measure multi-262

locus heterozygosity as a proxy of true genome-wide heterozygosity. We followed previous 263

recommendations for studying heterozygosity-fitness correlations in taking SMLH as a 264

measure of heterozygosity and in investigating a fitness-related trait 41

. However, tandem 265

repeats are not thought to influence gene function directly (and are therefore not influenced 266

by selection pressure directly), so we infer that heterozygosity of other genetic variants is 267

mechanistically important in the protective effect but we have not investigated those here. 268

Another limitation is that it is unknown how much time passed between awakening and blood 269

sampling for our participants, so not all would have been sampled at their peak cortisol 270

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concentration (30-45 minutes after awakening) 40

and cortisol concentrations might have been 271

further elevated due to the stress related to the clinic visit and venepuncture. However, 272

psychological distress has been shown to be associated with “morning cortisol” measured in 273

this way and not just peak concentrations after wakening31, 32

. 274

275

We conclude that in this cohort, more heterozygous individuals had lower morning plasma 276

cortisol concentrations for a given level of perceived psychological distress. This may be 277

important as higher cortisol concentrations may increase allostatic load and be associated 278

with higher risk of stress-related illness. In the future, alternative tools to SMLH, such as 279

analysis of 'runs of homozygosity' may be used to explore the generalisability of these 280

findings in larger cohorts 42

.281

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Acknowledgements 282

We thank Rosa Bisset for invaluable administrative support. We would like to acknowledge 283

the staff of several institutions in Croatia that supported the field work, including but not 284

limited to The University of Zagreb Medical School and the Institute for Anthropological 285

Research in Zagreb. We are grateful to Jill Harrison for technical assistance with cortisol 286

measurements and to the British Heart Foundation and Chief Scientist Office of the Scottish 287

Government for research funding. 288

289

Conflict of interest 290

The authors declare that they have no conflict of interest.291

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292

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Figures and Tables

Figure Legends

Figure 1. Histogram of multi-locus heterozygosity in the study population.

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Table 1. Characteristics of participants by tertile of morning plasma cortisol concentration.

Data are number of participants (%) or mean ± SD values. BMI = body mass index; GHQ-30 = Generalized Health Questionnaire with 30 items;

SMLH = standardized multi-locus heterozygosity score.

Cortisol

All < 508 nmol/L 508 - 689 nmol/L ≥ 690 nmol/L

P a

(univariate)

Cortisol (nmol/L) 619.62 ± 227.05

400.36 ± 82.49 593.12 ± 51.16 865.94 ± 188.19

N (% female) 854

286 (61.5) 283 (52.7) 285 (56.1)

0.10 b

Age, y 56.6 ± 15.7

57.4 ± 14.7 58.2 ± 16.0 54.2 ± 16.1

0.003

GHQ-30 (Likert points) 28.1 ± 11.3

27.7 ± 10.7 27.3 ± 11.5 29.2 ± 11.5

0.014

SMLH 0.9995 ± 0.0268

0.9999 ± 0.0288 1.0009 ± 0.0251 0.9977 ± 0.0263

0.035

BMI 27.3 ± 4.2

27.7 ± 4.1 27.6 ± 4.2 26.5 ± 4.3

<0.001

Education duration (years) 10.0 ± 3.5

10.0 ± 3.5 10.0 ± 3.5 9.9 ± 3.6

<9 years (N) 348

116 111 121

9-12 years (N) 364

124 124 116

>12 years (N) 137

45 47 45

0.93 b

unknown 5

1 1 3

Socio-economic status

much worse than others 30

13 8 9

a bit worse than others 130

46 46 38

like others 500

160 168 172

a bit better than others 171

54 57 60

much better than others 19

10 3 6

0.53 b

unknown 4 3 1 0

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a P-value for the association from one-way ANOVA analysis (cortisol analysed as a continuous variable)

b χ

2 test P–value for categorical variables (cortisol analysed by tertiles)

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Table 2. A multivariate regression analysis of morning plasma cortisol concentration.

Beta-coefficients, p-values and percent of variance explained are presented for investigated

predictor variables. Prior to analysis covariates were normalized to standard normal

distribution, to enable comparison of β-coefficients.

β-coefficient P

variance

explained, %

Age -0.56 0.001 1.1

GHQ-30 0.39 0.009 1.5

BMI -0.5 0.001 1.3

Standardized multi-locus

heterozygosity (SMLH)

-0.41 0.005 0.9

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254x190mm (96 x 96 DPI)

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