Specific Genetic Influences on Nighttime Blood Pressure

Abstract

OBJECTIVES

Nighttime blood pressure (BP) has been shown to be superior to daytime BP in predicting hypertension related target organ damage and cardiac mortality. In our Georgia Cardiovascular Twin Study, we showed that apart from the genes that also influence daytime BP, specific genetic determinants explained 44% and 67% of the nighttime systolic BP (SBP) and diastolic BP (DBP) heritabilities, respectively. Here, we determined whether these results could be confirmed in a much larger twin cohort of young adults with 24-hour ambulatory BP measurements.

METHODS

Ambulatory BP was available in 703 white twins (308 pairs and 87 singletons, aged 18–34 years, 50% males) from the Prenatal Programming Twin Study. A bivariate quantitative genetic twin model was used to analyze daytime and nighttime BP. We conducted a meta-analysis to compare and integrate results from the 2 twin cohorts.

RESULTS

Model fitting showed no sex differences for any of the measures. Heritabilities were 0.60 and 0.51 for SBP and 0.54 and 0.46 for DBP at daytime and nighttime. The specific heritability due to novel genetic effects emerging during the nighttime was 0.21 for SBP and 0.26 for DBP, which comprised 41% and 57% of the total nighttime heritability for SBP and DBP, respectively. Meta-analysis confirmed absence of cohort differences with very similar combined results.

CONCLUSIONS

In addition to genes that influence both daytime and nighttime BP, a large part of the heritability is explained by genes that specifically influence BP at night.

High blood pressure (BP) has become one of the most important components of global health and is the single most important risk factor for cardiovascular events.¹ Ambulatory 24-hour BP, including daytime and nighttime BP, has been widely used as a predictor for hypertension-related cardiovascular risk.² Recently, nighttime BP recorded by 24-hour BP monitoring has been shown to be superior to daytime BP as a predictor of hypertension-related target organ damage and cardiac mortality.³ As such, it is of great interest to know whether the genetic regulation of nighttime BP is also different from daytime BP. For the first time, we explored this question in 430 twins (187 pairs and 56 singletons aged 11.9–30 years) from the Georgia Cardiovascular Twin Study and found that, in addition to the genes that also influence daytime BP, nighttime BP has its own specific genetic determinants.⁴

In the current study, we aimed to extend and replicate our findings in the Prenatal Programming Twin Study (PPTS), a larger twin cohort with ambulatory BP recordings. We further conducted a metaanalysis to compare and integrate results for these 2 cohorts.

METHODS

Study population

The PPTS is a study nested in the East Flanders Prospective Twin Survey (EFPTS), which is a population-based survey conducted in a homogenous white population in the Belgian province of East Flanders.⁵ The EFPTS started in 1964 and continues today. It is characterized by its extensive collection of perinatal data at birth and placental examination within 24 hours after delivery. Zygosity was determined at birth according to sequential analysis based on sex, fetal membranes, umbilical cord blood groups, placental alkaline phosphatase, and DNA fingerprints. Dizygotic (DZ) twins were defined as either unlike-sex twins or same-sex twins with at least 1 different genetic marker. Remaining pairs were classified as monozygotic (MZ) twins. Furthermore, a lod-score method was used to calculate a probability of monozygosity for all the same-sex dichorionic twins with the same genetic markers. All MZ dichorionic twins reached a probability of monozygosity of at least 0.99.^5–7

The PPTS randomly contacted 803 pairs out of 2,141 twin pairs registered in EFPTS between 1964 and 1982. Details of the selection process have been described previously.⁷ Exclusion criteria included 1 or both twin pairs had died or suffered from a major congenital malformation, 1 or both twin pairs had moved out of the area, participants taking any medication affecting BP, female participants getting pregnant before the start of the study, or twin pairs lacking accurate zygosity information. Eventually, 768 twins of 418 pairs (overall response, 52.1%) aged 18–34 years participated in the PPTS conducted from 1997 to 2000. The local medical ethics committee approved the study, and all participants gave signed written informed consents. A total of 703 twin participants from the PPTS (308 pairs and 87 singletons, aged 18–34 years, 50% males) with valid 24-hour ambulatory blood pressure recordings were included in the current study.

In addition, we also used the ambulatory 24-hour BP data from the Georgia Cardiovascular Twin Study for the metaanalysis, including 242 white twins (108 pairs and 26 singletons) and 188 black twins (79 pairs and 30 singletons), aged 12–30 years (47% males).⁴ Details of the participants of these 2 twin studies have been provided elsewhere (reference 8, Table 1).⁸

Table 1.

Heritability estimates of best–fitting bivariate models for daytime and nighttime blood pressure

Blood pressure		Prenatal Programming Twin Study (n = 703)		Meta-analysis (n = 1,133)
		SBP	DBP	SBP	DBP
Variance components
Daytime	h 2 (95% CI)	0.60 (0.52–0.68)	0.54 (0.44–0.63)	0.63 (0.56–0.69)	0.59 (0.52–0.66)
	e 2 (95% CI)	0.40 (0.32–0.48)	0.46 (0.37–0.56)	0.37 (0.31–0.44)	0.41 (0.34–0.48)
Nighttime	h 2 (95% CI)	0.51 (0.41–0.60)	0.46 (0.39–0.55)	0.56 (0.48–0.63)	0.53 (0.45–0.60)
	e 2 (95% CI)	0.49 (0.40–0.59)	0.54 (0.45–0.65)	0.44 (0.37–0.52)	0.47 (0.40–0.55)
Nighttime-specific	h 2 (95% CI)	0.21 (0.13–0.29)	0.26 (0.17–0.34)	0.22 (0.16–0.28)	0.30 (0.23–0.37)
	e 2 (95% CI)	0.40 (0.33–0.48)	0.44 (0.37–0.53)	0.35 (0.30–0.41)	0.40 (0.34–0.47)
Correlations
Daytime-nighttime	r g (95% CI)	0.77 (0.68–0.86)	0.66 (0.53–0.77)	0.78 (0.71–0.84)	0.66 (0.57–0.74)
	r e (95% CI)	0.43 (0.32–0.53)	0.43 (0.32–0.53)	0.45 (0.36–0.53)	0.40 (0.30–0.49)

Abbreviations: CI, confidence interval; h ², heritability, variance explained by additive genetics; e ², variance explained by unique environment; r _g, genetic correlation; r _e, unique environmental correlation.

Measurements

For the PPTS, details on clinical measurements such as office BP, 24-hour BP, and other characteristics have been reported previously.⁶ All participants underwent a 2-hour examination in the morning between February 1997 and April 2000. Two trained researchers measured clinical characteristics according to established protocols. The 24-hour ambulatory BP monitoring device (SpaceLabs, Inc., Redmond, WA) was worn for 1 complete 24-hour period, starting in the morning (06:00am to 08:00am) until they awoke the next day. The frequency of ambulatory BP measurements was every 15 minutes from 08:00am to 10:00pm and every 30 minutes from 10:00pm to 08:00am. Similar to the Georgia Cardiovascular Twin Study, daytime was defined as from 08:00am to 10:00pm and nighttime was defined as 00:00am to 06:00am.⁴ Data cleaning followed the same criteria described previously.⁴ Daytime BP and nighttime BP were calculated as the average levels of qualified BP records during the day and night, respectively.

Statistical analysis

Our aim was to determine whether genetic (and environmental) influences on nighttime BP were different from those on daytime BP and to what extent they depend on sex, race, and cohort.

Prior to all analyses, daytime and nighttime BP were log-transformed and the age effect was regressed out. Structural equation modeling was used to compare the variance–covariance matrices in MZ and DZ twins. The observed phenotypic variance was then separated into additive (A) or nonadditive (D) genetic components, shared (C) environmental components, and unique (E) environmental components. Although the heritability (h ²) was defined as the proportion of the total variance attributable to the additive genetic variation.

A bivariate twin model was used for the current study (see Supplementary Figure 1). With the so-called Cholesky decomposition model, we were able to estimate the heritability of daytime BP (h ² _day = a₁₁ ²/(a₁₁ ² + c₁₁ ² + e₁₁ ²)) and nighttime BP (h ² _{nigh t}= (a₂₁ ² + a₂₂ ²)/(a₂₁ ² + a₂₂ ² + c₂₁ ² + c₂₂ ² + e₂₁ ² + e₂₂ ²)) and also further test whether the genes influencing nighttime BP are the same (i.e., a₂₂ = 0?), partly the same (i.e., a₂₁ ≠ 0 and a₂₂ ≠ 0?), or entirely different (i.e., a₂₁ = 0?) from daytime BP. If they are partly the same, this bivariate model allows further determination of the amount of overlap between genes influencing daytime and nighttime BP by calculating the genetic correlation between the 2 BP levels (r_g = COV_A(day, night)/√ (V_A day * V_A night)). Shared and unique environmental correlations can be calculated in a similar fashion.

The sex differences in the PPTS were examined by comparing a full model in which parameter estimates were allowed to differ in magnitude between male and female, with a reduced model in which the parameter estimates were constrained to be equal across the sexes. The meta-analysis between the PPTS and the Georgia Cardiovascular Twin Study was based on individual records and was similar to the analysis for testing sex differences. That is, we first examined differences between studies by comparing a full model in which parameter estimates are allowed to differ between the 2 studies, with a reduced model in which parameter estimates are constrained to be equal across studies.⁸

All quantitative genetic modeling was carried out using OpenMx, version 1.2, an open source R-based package for analysis of twin data.⁹

RESULTS

Twin correlations of MZ twin pairs were larger than those of DZ twin pairs (daytime SBP, r_MZ = 0.66, r_DZ = 0.25; daytime DBP, r_MZ = 0.61, r_DZ = 0.31; nighttime SBP, r_MZ = 0.53, r_DZ = 0.28; nighttime DBP, r_MZ = 0.50, r_DZ = 0.25). Strong positive correlations between daytime and nighttime BP values were observed for both SBP (r = 0.65) and DBP (r = 0.58).

Table 1 presents the heritability estimates of best-fitting bivariate models for daytime and nighttime BP. Bivariate twin analysis showed that the AE model, including an additive genetic component (A) plus a unique environmental component (E), was the best-fitting model for both SBP and DBP because shared environment (C) could be dropped from the models without a significant loss in fit (SBP: ACE vs. AE model, χ² ₍₃₎ = 2.41, P = 0.49; DBP: ACE vs. AE model, χ² ₍₃₎ = 0.84, P = 0.84), but A could not (SBP: ACE vs. CE model, χ² ₍₃₎ = 16.52, P < 0.001; DBP: ACE vs. CE model, χ² ₍₃₎ = 16.41, P < 0.001). Based on the best-fitting AE model, we conducted additional testing in order to determine the extent to which the additive genetic and unique environmental influences were different between daytime and nighttime BP. Similar to our previous findings in the Georgia Cardiovascular Twin cohort, our results indicated that we could significantly (P < 0.001) reject a model assuming no genetic sharing at all between daytime and nighttime BP (e.g., SBP: a₂₁ ≠ 0 model vs. a₂₁ = 0 model, χ² ₍₁₎ = 78.59, P < 0.001) as well as a model assuming complete sharing of genes between daytime and nighttime BP (e.g., SBP: a₂₂ ≠ 0 model vs. a_{2 2}= 0 model, χ² ₍₁₎ = 24.01, P < 0.001). That is, the genes influencing BP at nighttime are partly shared with those of daytime BP. The genetic correlations (95% confidence interval (CI)) were 0.77 (0.68–0.86) between daytime and nighttime SBP and 0.66 (0.53–0.77) between daytime and nighttime DBP. As shown in Table 1, the specific heritability (95% CI) due to novel genetic effects emerging during the nighttime was 0.21 (0.13–0.29) for SBP and 0.26 (0.17–0.34) for DBP, indicating that 41% of nighttime SBP heritability (0.21/0.51) and 57% of nighttime DBP heritability (0.26/0.46) could be attributed to genes that only influence the nighttime levels. Meta-analysis showed that there were no race or cohort differences allowing the combination of the results of both twin cohorts, which were very similar to those for PPTS (Table 1).

The results also suggest an essential role of the unique environmental component in BP regulation during the day and the night. The unique environmental influences on BP at night are also partially shared with those during the day. However, the environmental correlations (r_e) were lower compared with the genetic correlations (e.g., Table 1, in metaanalysis, r_e 0.45 vs. r_g 0.78 for SBP, r_e 0.40 vs. r_g 0.66 for DBP).

DISCUSSION

In this study, we used a larger white twin cohort and successfully replicated and expanded our previous findings for the Georgia Cardiovascular Twin Study,⁴ firmly confirming that, in addition to the genes that influence daytime BP, nighttime BP has its own specific genetic determinants. Combined analysis of the 2 databases indicated that heritability estimates did not show any differences between whites and blacks or males and females or between the 2 twin cohorts.

There is compelling evidence that nighttime BP is superior to daytime BP in predicting outcome.¹⁰ Given the limited reproducibility of daytime BP levels, which were due to interference by individual daytime activities, it has been suggested that cardiovascular risk stratification might be more accurate if based on nighttime BP levels.¹¹ In this case, it is crucial to understand the potential mechanisms that underlie BP regulation at night. In line with our previous findings, in this independent twin cohort we demonstrated that, in addition to the genes that also influence daytime BP, nighttime BP has its own specific genetic determinants. The similarity and differences between daytime BP and nighttime BP genetic components raise the possibility that the underlying mechanisms for BP regulation partly change with the day–night shift, either via switching on or off of relevant genes or via a change in the amplitude of their expression. Our results also implied a partial change from daytime to nighttime in the environmental determinants of BP regulation as indicated by the moderate r_e between daytime and nighttime.

This observation has important implications for gene finding studies. The genes recently identified by the genome-wide association studies on daytime office BP need to be specifically tested for their effects on nighttime BP. In addition, some pathological conditions such as obstructive sleep apnea and glaucoma are associated with changes in nighttime BP levels. The genes responsible for these pathological conditions might also contribute to nighttime BP regulation. Identification of genes that specifically influence nighttime BP will provide new insights into the mechanisms of BP regulation at night. It may also help us to better understand the pathophysiology and clinical consequences of nighttime BP and to develop more accurate prediction of individuals at risk for cardiovascular disease as well as to develop new therapeutic strategies for normalizing nighttime BP levels.

SUPPLEMENTARY MATERIALS

Supplementary materials are available at American Journal of Hypertension (http://ajh.oxfordjournals.org).

DISCLOSURE

The authors declared no conflict of interest.