Copeptin,a Marker of Vasopressin,Predicts Vascular Dementia but not Alzheimer’s Disease

Abstract

Background: Copeptin is a reliable surrogate marker for the neurohypophyseal hormone vasopressin. Elevated plasma level of copeptin has been associated with cardiovascular and metabolic disease risk.

Objective: To investigate the association between copeptin and risk of dementia.

Methods: In all, 18,240 individuals from Malmö, Sweden, were examined between 2002 and 2006 (mean age 69.3 years, 69.8% men). Incident cases of dementia until 31 December 2009 were identified by linkage with the Swedish National Patient Register. To validate the dementia diagnoses, medical records as well as laboratory and neuroimaging data were carefully reviewed. Baseline level of copeptin was measured in frozen plasma in: (1) all participants who were diagnosed with dementia during follow-up, (2) a random sample of 5100 individuals of the cohort.

Results: During a median follow-up of 4.2 years, there were 374 incident dementia cases (age range 60–83 years at baseline): 120 were classified as Alzheimer’s disease (AD), 84 as vascular dementia (VaD), and 102 as mixed dementia. In logistic regressions adjusted for cardiovascular risk factors, baseline level of copeptin predicted incident VaD (Odds ratio (OR) 1.30 per 1 SD increase in log copeptin, 95% CI 1.03–1.64). Copeptin did not predict incidence of all-cause dementia (OR 1.05, 95% CI 0.94–1.18), AD (OR 0.97, 95% CI 0.79–1.18), or mixed dementia (OR 0.85, 95% CI 0.68–1.05).

Conclusion: Elevated plasma level of copeptin is a risk marker for incident VaD, but not for incident AD. This suggests that the vasopressin hormonal system might be involved in the development of VaD.

Keywords

Alzheimer’s disease copeptin dementia vascular dementia

INTRODUCTION

Alzheimer’s disease (AD), vascular dementia (VaD), and mixed AD and VaD are considered to be the most common subtypes of dementia [1]. Increasing evidence supports that vascular factors are involved in the etiology not only of VaD, but also of AD [1]. This implies that the relationship between vascular factors and dementia is more complex than previously believed. One approach in studying this complex relationship is to examine how different dementia subtypes are associated with biomarkers considered to be involved in the pathogenesis of cardiovascular disease.

The vasopressin hormonal system could be of substantial interest in this context. Arginine vasopressin (AVP), also known as antidiuretic hormone, is aneurohypophyseal hormone involved in osmoregulation, control of vascular tone, stress response, and glucose metabolism [2]. Due to its short half-life and other pre-analytical factors, AVP is cumbersome to measure in plasma [3]. Copeptin, the stable C-terminal part of the AVP precursor peptide, is secreted in equimolar amounts to AVP, and is considered to be a reliable surrogate marker for AVP [3].

Recent studies have recognized plasma copeptin as an important risk marker for cardiovascular and metabolic disease risk. In population-based studies, elevated level of copeptin has been associated with the metabolic syndrome [4, 5], with an increased incidence of diabetes mellitus [6, 7], and with diabetes-related cardiovascular disease [8]. In clinical studies based on patients, elevated level has been associated with a worse prognosis in many diseases, including stroke [9], and heart failure [10, 11]. In the acute setting, copeptin has been used to rule out acute myocardial infarction [12].

We recently reported that elevated baseline plasma copeptin predicted worse results on “A Quick Test of cognitive speed” (AQT) [13], a test of attention, executive function, and cognitive speed, after 16 years of follow-up [14]. The association between copeptin and risk of dementia has not previously been reported. Therefore, the aim of the present large population-based study was to investigate if baseline level of copeptin is associated with incident all-cause dementia, incident AD, and incident VaD, respectively.

MATERIALS AND METHODS

Study population

The Malmö Preventive Project (MPP) is a population-based cohort study in the city of Malmö, Sweden. With the initial aims of screening for cardiovascular risk factors and alcohol abuse, baseline examinations were conducted between 1974 and 1992. A total of 33,346 individuals with a mean age of 45.7 years were screened (age range 27–61 years, participation rate 71%). Details of the procedure have been described previously [15]. A reexamination of 18 240 surviving baseline participants from MPP was conducted between 2002 and 2006 (age range 56–85 years, 63.4% men), giving a participation rate of 72% [16]. This reexamination represents the baseline time point in the present study. Levels of copeptin were measured in frozen plasma from the reexamination in: (1) all participants who were diagnosed with dementia until 31 December 2009 (see section “Ascertainment of dementia diagnosis”), (2) a random sample of 5,100 individuals who participated in the MPP reexamination, but not in the Malmö Diet and Cancer Study, another large population-based cohort study in Malmö with about 25% overlap with MPP [17]. After exclusion of 54 individuals with prevalent dementia at the time for the MPP reexamination, copeptin was available in 5,356 individuals, and they constitute the study population.

All participants signed an informed consent. The study was approved by the Ethical Committee of Lund University, Lund, Sweden.

Procedures

The MPP reexamination included anthropometric and clinical measurements, a self-administered questionnaire, and blood sampling. Blood pressure was measured twice with a mercury-column sphygmomanometer after five minutes of supine rest, and the mean values were calculated (mmHg). Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Smoking and anti-hypertensive treatment were assessed with a self-administered questionnaire. Diabetes mellitus was defined as a self-reported physician’s diagnosis of diabetes, use of antidiabetic medication, or fasting plasma glucose of ≥7.0 mmol/l. Information about prevalent stroke (history of clinical stroke) at the MPP reexamination was obtained from national and regional registers [18]. Only approximately 2/3 of the participants reported about educational level in the MPP questionnaire. Therefore, we acquired information about education (≤8 or >9 years) from the Swedish national census 1970 (in Swedish: Folk- och Bostadsrä kning, FoB). Fasting serum total cholesterol, high-density lipoprotein (HDL), and triglycerides were analyzed according to the standard procedures at the Department of Clinical Chemistry, University Hospital Malmö. Low-density lipoprotein (LDL) was estimated using the Friedewald formula [19]. Copeptin was measured in fasting plasma samples stored at –80°C with a commercially available assay in the chemiluminescence/coated tube format (B.R.A.H.M.S. AG, Henningsdorf, Germany) as described previously [3].

Ascertainment of dementia diagnosis

Cases of dementia were identified by linkage with the Swedish National Patient Register. This is a register that covers more than 99% of all hospital discharge diagnoses, as well as diagnoses from hospital-based outpatient care [20]. The diagnoses in the register are coded according to the International Classification of Diseases (ICD), and we retrieved all dementia diagnoses (ICD 8th, 9th, and 10th revisions) until 31 December 2009. Thereafter, in order to validate the dementia diagnoses, medical records (providing data on cognitive decline) as well as laboratory and neuroimaging data from both hospitals and primary care were reviewed. The final diagnosis was adjudicated by a research physician, and a geriatrician specialized in memory disorders was consulted in unclear cases. All-cause dementia was diagnosed according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition, revised (DSM-IIIR) [21]. The DSM-IV criteria [22] were applied for the AD and VaD diagnoses. AD and VaD diagnoses were established when the clinical presentation, cognitive profile, and neuroimaging findings all were congruent with either of these diagnostic categories. The diagnosis of mixed dementia was used when the patient had a clinical presentation and neuroimaging findings suggesting that both Alzheimer and cerebrovascular pathology significantly contributed to thedisorder.

A total of 471 dementia cases were identified in the Swedish National Patient Register. Of these, 428 retained a dementia diagnosis after the validation process described above (54 prevalent cases at the time of the MPP reexamination, and 374 incident cases during follow-up). The 54 prevalent cases were excluded from further analyses since our aim was to study incident dementia.

Statistical analyses

Copeptin was skewed to the right and therefore log-transformed with the natural logarithm. Differences between groups were tested with the independent samples t-test, the Mann Whitney test, and chi-square tests, as appropriate. Logistic regressions (Enter) were used to assess the association between copeptin and incident dementia. We report multivariable-adjusted odds ratios (OR) per 1 standard deviation (SD) increase in log copeptin, as well as for quartiles of copeptin with quartile 1 considered as the reference. In model 1, adjustments were made for age, sex, and educational level. In model 2, further adjustments were made for systolic blood pressure (SBP), BMI, LDL, HDL, current smoking, anti-hypertensive treatment, prevalent diabetes, and prevalent stroke. Logistic regressions were used rather than Cox regressions because there is a significant and varying timespan between the time point when the individual fulfills the criteria of dementia, and when dementia is diagnosed. All analyses were performed in SPSS version 22.0 (SPSS Inc., Chicago, Illinois, USA). A p-value of less than 0.05 was considered statistically significant.

RESULTS

Characteristics of the study population are presented in Table 1. During a median follow-up period of 4.2 years (interquartile range, IQR, 3.4–5.2), there were 374 incident dementia cases (age range 60–83 years at baseline): 120 AD, 84 VaD, 102 mixed dementia, and 68 other dementias. The median copeptin concentration in those who developed dementia compared with those who did not was 7.3 pmol/l (IQR 4.2–12.9) versus 7.1 pmol/l (IQR 4.2–11.8), p = 0.67. The median copeptin concentration was significantly higher in the incident VaD group compared with the incident AD group (9.9 pmol/l (IQR 5.2–21.9) versus 6.3 pmol/l (IQR 3.8–10.1), p < 0.001), and compared with those who did not develop VaD (p < 0.001). The median copeptin concentration in the incident “other dementias” group was 8.2 pmol/l (IQR 4.8–14.1).

In logistic regression adjusted for covariates in model 1, copeptin predicted incident VaD (OR 1.41 per 1 SD increase in log copeptin, 95% CI 1.12–1.77, p = 0.003) (Table 2). The association was attenuated but remained statistically significant after further adjustment for model 2 covariates (OR 1.30, 95% CI 1.03–1.64, p = 0.03). Copeptin did not predict incidence of all-cause dementia or AD (Table 2). In model 1, there was a borderline significant trend of lower copeptin predicting incident mixed dementia, but this trend was attenuated after full adjustment (Table 2). When copeptin was analyzed in quartiles, increasing quartiles of copeptin predicted incident VaD, with participants in the highest quartile having an OR of 2.43 (95% CI 1.11–5.30, p = 0.03), compared with participants in the lowest quartile, after full adjustment (Table 2). Table 3 shows all the covariates that were significantly associated with the dementia outcomes in the fully adjusted logistic regressions.

During the follow-up period, 532 (9.8%) of the participants died. They were excluded in secondary analyses, but this did not change the main results (data not shown). In further secondary analyses individuals with prevalent stroke were excluded, and SBP were replaced by diastolic blood pressure, but this did not affect the results (data not shown).

To examine the relationship between copeptin and the other covariates studied, we performed a linear regression with log copeptin as the dependent variable, and the other covariates in model 2 as independent variables. Copeptin was significantly and independently associated with most other markers of cardiovascular risk (age: β= 0.02, p < 0.001, male sex: β= 0.48, p < 0.001, systolic blood pressure: β= 0.01, p = 0.002, BMI: β= 0.01, p < 0.001, HDL: β= –0.11, p < 0.001, LDL: β= –0.02, p = 0.042, current smoking: β= 0.08, p = 0.001, anti-hypertensive treatment: β= 0.07, p = 0.001, prevalent diabetes: β= 0.11, p < 0.001, and prevalent stroke: β= 0.13, p = 0.006).

DISCUSSION

This large observational study examined the association between baseline plasma copeptin, a marker of AVP, and incident dementia over 3–7 years follow-up in an urban population. After adjustments for traditional cardiovascular risk factors, we found that copeptin predicted VaD, but not AD, mixed dementia, or all-cause dementia. Participants in the top quartile of copeptin had a 2.5-fold increased risk of incident VaD compared to those in the lowest quartile.

To the best of our knowledge, this is the first study to explore the association between copeptin and dementia. In another Swedish population-based sample, we recently found that elevated copeptin levels at baseline predicted worse results on the cognitive test AQT [13], but not on the Mini-Mental State Examination (MMSE) [23], after 16 years of follow-up [14]. AQT is a measure of attention, executive function, and cognitive speed; i.e., cognitive domains that are considered to be more affected in VaD than in AD [24]. MMSE, on the other hand, is mainly a measure of orientation, language skills, and memory function [25]. We interpret these findings as being in line with the results of our present study.

Several pathophysiological hypotheses linking higher copeptin with an increased risk of VaD could be formulated. The neurohypophyseal hormone AVP, which copeptin is a surrogate marker for, is involved in a variety of physiological functions, including osmoregulation, control of vascular tone, stress response, and glucose metabolism [2, 6]. AVP also acts locally as a neuropeptide in the brain, where it seems to be involved in behavior and social interaction [26], and has been suggested to affect learning and memory [27]. However, only a small fraction of AVP passes the blood-brain barrier [26], why peripheral levels do not reflect levels in the brain.

Elevated copeptin has been associated with diabetes mellitus [6, 7] and the metabolic syndrome [4, 5]. In a Swedish population-based sample, Enhörning et al. found that baseline copeptin predicted incident diabetes during 15.8 years follow-up [7]. Diabetes and glucose metabolism disturbances are well-recognized risk factors for dementia [1, 28], and the increase in risk is higher for VaD than for AD [28]. Disturbances in glucose metabolism could thus, at least partly, explain our finding of an association of copeptin with VaD, but not with AD. Diabetes could also act as an effect modifier of the association between copeptin and dementia. To examine this was beyond the scope of the present study, but this interesting question could be addressed in future studies.

Copeptin has been reported to be higher in individuals with prevalent cardiovascular diseases compared with healthy individuals [29]. In our study, we found that copeptin was independently associated with most other markers of cardiovascular risk. Furthermore, it has been reported that level of copeptin predicts prognosis in patients with heart failure [10, 11], myocardial infarction [30], and stroke [9]. Thus, copeptin seems to be a marker of cardiovascular disease severity and risk. In this context, our finding of an association between copeptin and VaD seems plausible, even though it should be noted that vascular factors have been suggested to be involved in the etiology of AD as well [1]. Interestingly, we did not find an independent association between copeptin and mixed dementia. A potential explanation for this could be that the dementias in those individuals are predominantly caused by Alzheimer, and not cerebrovascular, pathology.

Copeptin was the main focus of the present study, but some of the other covariates are worth mentioning. Age is known to be the strongest risk factor for dementia, and, in line with this, we found a highly significant association between age and all outcomes studied. Higher SBP, higher BMI, and higher LDL were associated with a lower incidence of all-cause dementia (SBP and BMI), AD (BMI), mixed dementia (BMI), and VaD (LDL). This might seem counterintuitive since these are all known risk factors for dementia [1]. However, observational studies have shown that they are mainly risk factors when measured in mid-life [31]. In elderly populations, theassociations reported are more diverse. It is well known that demented patients lose weight and that their blood pressure decreases [31]. Since our follow-up time was rather short, the dementing process had probably already started when the covariates were measured. Therefore, a reverse causation (i.e., dementia affecting the levels of the covariates, and not the other way around) seems plausible. This underlines the importance of finding markers of cardiovascular risk that are unaffected by the dementing process per se. Copeptin might be such a biomarker, although this can only be a matter of speculation based on the present observational study.

Strengths and weaknesses of the study

The strengths of our study include the large sample size and the population-based setting. Some limitations merit attention. First, the dementia diagnoses were retrieved from the Swedish National Patient Register. This register covers more than 99% of all hospital discharge diagnoses in Sweden, as well as diagnoses from hospital-based outpatient care [20]. Individuals treated only in primary care during the follow-up period were not covered. Therefore, the incidence rates are underestimates. Two previous Swedish studies have examined the degree of this underestimation [32, 33]. However, these studies were only based on hospital discharge diagnoses, not on diagnoses from hospital-based outpatient care, which make their numbers lower than ours. They found that the register had a sensitivity of 23 to 55% regarding identification of dementia cases in the population [32, 33]. To overcome validity problems of the diagnoses from the register, we applied a thorough validation process.

Second, a health selection bias has probably occurred with less people in the study sample having cardiovascular and cognitive diseases compared with the general population. The bias that this might have introduced would probably be towards null. Third, we did not have information on the exact number of years of education, and therefore could not adjust for education as a continuous variable. Finally, we cannot rule out residual confounding. For example, we could not adjust for renal function or heart disease.

Conclusion

We found that elevated baseline copeptin was an independent risk marker for incident VaD, but not for incident AD, mixed dementia, or all-cause dementia. This suggests that the AVP hormonal system might be involved in the development of VaD. Our findings apply to the population level. Future studies should elucidate if copeptin adds diagnostic and prognostic information for the individual patient in the clinical setting. Since our study is the first reporting on the association between copeptin and dementia, the results should be replicated by others before firmer conclusions can be drawn.

Footnotes

ACKNOWLEDGMENTS

This study was supported by the Swedish Research Council, ERC St-282255, the Swedish Heart and Lung Foundation, the Ernhold Lundström Foundation, and the Regional agreement on medical training and clinical research (ALF) between Skåne County Council and Lund University.

Authors’ disclosures available online ().

References

Gorelick

, Scuteri

, Black

, Decarli

, Greenberg

, Iadecola

, Launer

, Laurent

, Lopez

, Nyenhuis

, Petersen

, Schneider

, Tzourio

, Arnett

, Bennett

, Chui

, Higashida

, Lindquist

, Nilsson

, Roman

, Sellke

, Seshadri

(2011) Vascular contributions to cognitive impairment and dementia: A statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 42, 2672–2713.

Barrett

, Singer

, Clapp

(2007) Vasopressin: Mechanisms of action on the vasculature in health and in septic shock Crit Care Med 35, 33–40.

Morgenthaler

, Struck

, Alonso

, Bergmann

(2006) Assay for the measurement of copeptin, a stable peptide derived from the precursor of vasopressin. Clin Chem 52, 112–119.

Saleem

, Khaleghi

, Morgenthaler

, Bergmann

, Struck

, Mosley

Jr , Kullo

(2009) Plasma carboxy-terminal provasopressin (copeptin): A novel marker of insulin resistance and metabolic syndrome. J Clin Endocrinol Metab 94, 2558–2564.

Enhorning

, Struck

, Wirfalt

, Hedblad

, Morgenthaler

, Melander

(2011) Plasma copeptin, a unifying factor behind the metabolic syndrome. J Clin Endocrinol Metab 96, E1065–E1072.

Enhorning

, Wang

, Nilsson

, Almgren

, Hedblad

, Berglund

, Struck

, Morgenthaler

, Bergmann

, Lindholm

, Groop

, Lyssenko

, Orho-Melander

, Newton-Cheh

, Melander

(2010) Plasma copeptin and the risk of diabetes mellitus. Circulation 121, 2102–2108.

Enhorning

, Bankir

, Bouby

, Struck

, Hedblad

, Persson

, Morgenthaler

, Nilsson

, Melander

(2013) Copeptin, a marker of vasopressin, in abdominal obesity, diabetes and microalbuminuria: The prospective Malmo Diet and Cancer Study cardiovascular cohort. Int J Obes (Lond) 37, 598–603.

Enhorning

, Hedblad

, Nilsson

, Engstrom

, Melander

(2015) Copeptin is an independent predictor of diabetic heart disease and death. Am Heart J 169, 549–556.

De Marchis

, Katan

, Weck

, Fluri

, Foerch

, Findling

, Schuetz

, Buhl

, El-Koussy

, Gensicke

, Seiler

, Morgenthaler

, Mattle

, Mueller

, Christ-Crain

, Arnold

(2013) Copeptin adds prognostic information after ischemic stroke: Results from the CoRisk study. Neurology 80, 1278–1286.

10.

Maisel

, Xue

, Shah

, Mueller

, Nowak

, Peacock

, Ponikowski

, Mockel

, Hogan

, Wu

, Richards

, Clopton

, Filippatos

, Di Somma

, Anand

, Ng

, Daniels

, Neath

, Christenson

, Potocki

, McCord

, Terracciano

, Kremastinos

, Hartmann

, von Haehling

, Bergmann

, Morgenthaler

, Anker

(2011) Increased 90-daymortality in patients with acute heart failure with elevated copeptin: Secondary results from the Biomarkers in Acute Heart Failure (BACH) study Circ Heart Fail 4, 613–620.

11.

Tentzeris

, Jarai

, Farhan

, Perkmann

, Schwarz

, Jakl

, Wojta

, Huber

(2011) Complementary role of copeptin and high-sensitivity troponin in predicting outcome in patients with stable chronic heart failure. Eur J Heart Fail 13, 726–733.

12.

Lipinski

, Escarcega

, D’Ascenzo

, Magalhaes

, Baker

, Torguson

, Chen

, Epstein

, Miro

, Llorens

, Giannitsis

, Lotze

, Lefebvre

, Sebbane

, Cristol

, Chenevier-Gobeaux

, Meune

, Eggers

, Charpentier

, Twerenbold

, Mueller

, Biondi-Zoccai

, Waksman

(2014) A systematic review and collaborative meta-analysis to determine the incremental value of copeptin for rapid rule-out of acute myocardial infarction. Am J Cardiol 113, 1581–1591.

13.

Wiig

, Nielsen

, Minthon

, Warkentin

(2002) , Pearson/Psych Corp, San Antonio, TX. A quick test of cognitive speed (AQT).

14.

Tufvesson

, Melander

, Minthon

, Persson

, Nilsson

, Struck

, Nagga

(2013) Diabetes mellitus and elevated copeptin levels in middle age predict low cognitive speed after long-term follow-up. Dement Geriatr Cogn Disord 35, 67–76.

15.

Berglund

, Nilsson

, Eriksson

, Nilsson

, Hedblad

, Kristenson

, Lindgarde

(2000) Long-term outcome of the Malmo preventive project: Mortality and cardiovascular morbidity. J Intern Med 247, 19–29.

16.

Leosdottir

, Willenheimer

, Persson

, Nilsson

(2011) The association between glucometabolic disturbances, traditional cardiovascular risk factors and self-rated health by age and gender: A cross-sectional analysis within the Malmo Preventive Project. Cardiovasc Diabetol 10, 118.

17.

Mokhtari

, Bellinetto-Ford

, Melander

, Nilsson

(2008) Determinants of increasing pulse pressure during 23 years’ follow-up as a marker of arterial stiffness and vascular ageing. Blood Press 17, 291–297.

18.

Persson

, Hedblad

, Nelson

, Berglund

(2007) Elevated Lp-PLA2 levels add prognostic information to the metabolic syndrome on incidence of cardiovascular events among middle-aged nondiabetic subjects. Arterioscler Thromb Vasc Biol 27, 1411–1416.

19.

Friedewald

, Levy

, Fredrickson

(1972) Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 18, 499–502.

20.

Ludvigsson

, Andersson

, Ekbom

, Feychting

, Kim

, Reuterwall

, Heurgren

, Olausson

(2011) External review and validation of the Swedish national inpatient register. BMC Public Health 11, 450.

21.

Amercian Psychiatric Association (1987) Diagnostic and Statistical Manual of Mental disorders, 3rd rev. ed., American Psychiatric Association, Washington, DC.

22.

Amercian Psychiatric Association (1994) Diagnostic and Statistical Manual of Mental disorders, 4th ed., American Psychiatric Association, Washington, DC.

23.

Folstein

, Folstein

, McHugh

(1975) “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12, 189–198.

24.

Tzourio

, Laurent

, Debette

(2014) Is hypertension associated with an accelerated aging of the brain? . Hypertension 63, 894–903.

25.

Tombaugh

, McIntyre

(1992) The mini-mental state examination: A comprehensive review. J Am Geriatr Soc 40, 922–935.

26.

Meyer-Lindenberg

, Domes

, Kirsch

, Heinrichs

(2011) Oxytocin and vasopressin in the human brain: Social neuropeptides for translational medicine Nat Rev Neurosci 12, 524–538.

27.

Born

, Pietrowsky

, Fehm

(1998) Neuropsychological effects of vasopressin in healthy humans. Prog Brain Res 119, 619–643.

28.

Middleton

, Yaffe

(2010) Targets for the prevention of dementia. J Alzheimers Dis 20, 915–924.

29.

Wannamethee

, Welsh

, Whincup

, Lennon

, Papacosta

, Sattar

(2014) N-terminal pro brain natriuretic peptide but not copeptin improves prediction of heart failure over other routine clinical risk parameters in older men with and without cardiovascular disease: Population-based study. Eur J Heart Fail 16, 25–32.

30.

Khan

, Dhillon

, O’Brien

, Struck

, Quinn

, Morgenthaler

, Squire

, Davies

, Bergmann

, Ng

(2007) C-terminal provasopressin (copeptin) as a novel and prognostic marker in acute myocardial infarction: Leicester Acute Myocardial Infarction Peptide (LAMP) study. Circulation 115, 2103–2110.

31.

Kerola

, Kettunen

, Nieminen

(2011) The complex interplay of cardiovascular system and cognition: How to predict dementia in the elderly? . Int J Cardiol 150, 123–129.

32.

Dahl

, Berg

, Nilsson

(2007) Identification of dementia in epidemiological research: A study on the usefulness of various data sources. Aging Clin Exp Res 19, 381–389.

33.

Jin

, Gatz

, Johansson

, Pedersen

(2004) Sensitivity and specificity of dementia coding in two Swedish disease registries. Neurology 63, 739–741.