CLINICAL PERSPECTIVE

This Article Abstract Full Text (PDF) All Versions of this Article: 116/1/10    most recent CIRCULATIONAHA.106.676783v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Aarnoudse, A.-J. L.H.J. Articles by Stricker, B. H.C. Search for Related Content PubMed PubMed Citation Articles by Aarnoudse, A.-J. L.H.J. Articles by Stricker, B. H.C. Related Collections Clinical genetics Arrhythmias, clinical electrophysiology, drugs Epidemiology Genetics of cardiovascular disease Genomics

(Circulation. 2007;116:10-16.)
© 2007 American Heart Association, Inc.

Arrhythmia/Electrophysiology

Common NOS1AP Variants Are Associated With a Prolonged QTc Interval in the Rotterdam Study

Albert-Jan L.H.J. Aarnoudse, MD^*; Christopher Newton-Cheh, MD, MPH^*; Paul I.W. de Bakker, PhD; Sabine M.J.M. Straus, MD, PhD; Jan A. Kors, PhD; Albert Hofman, MD, PhD; André G. Uitterlinden, PhD; Jacqueline C.M. Witteman, PhD; Bruno H.C. Stricker, PhD

From the Departments of Epidemiology and Biostatistics (A.L.H.J.A., S.M.J.M.S, A.H., A.G.U., J.C.M.W., B.H.C.S.), Internal Medicine (A.G.U., B.H.C.S.), and Medical Informatics (J.A.K.), Erasmus Medical Center, Rotterdam, the Netherlands; Cardiology Division (C.N.-C.), Department of Molecular Biology (P.I.W.d.B.), and Center for Human Genetics Research (P.I.W.d.B.), Massachusetts General Hospital, Boston; Program in Medical and Population Genetics (C.N.-C., P.I.W.d.B.), Broad Institute of Harvard and MIT, Cambridge, Mass; National Heart, Lung, and Blood Institute’s Framingham Heart Study (C.N.-C.), Framingham, Mass; Department of Genetics, Harvard Medical School (P.I.W.d.B.), Boston, Mass; Inspectorate for Health Care (A.L.H.J.A., B.H.C.S.), the Hague, the Netherlands; and Dutch Medicines Evaluation Board (S.M.J.M.S), the Hague, the Netherlands.

Correspondence to Bruno H.C. Stricker, PhD, Department of Epidemiology and Biostatistics, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands. E-mail b.stricker{at}erasmusmc.nl

Received November 16, 2006; accepted May 1, 2007.

	Abstract

Top Abstract Introduction Methods Results Discussion Conclusions References

 
Background— QT prolongation is an important risk factor for sudden cardiac death. About 35% of QT-interval variation is heritable. In a recent genome-wide association study, a common variant (rs10494366) in the nitric oxide synthase 1 adaptor protein (NOS1AP) gene was found to be associated with QT-interval variation. We tested for association of 2 NOS1AP variants with QT duration and sudden cardiac death.

Methods and Results— The Rotterdam Study is a population-based, prospective cohort study of individuals 55 years of age. The NOS1AP variants rs10494366 T>G and rs10918594 C>G were genotyped in 6571 individuals. Heart rate–corrected QT interval (QTc) was determined with ECG analysis software on up to 3 digital ECGs per individual (total, 11 108 ECGs from 5374 individuals). The association with QTc duration was estimated with repeated-measures analyses, and the association with sudden cardiac death was estimated by Cox proportional-hazards analyses. The rs10494366 G allele (36% frequency) was associated with a 3.8-ms (95% confidence interval, 3.0 to 4.6; P=7.8x10^–20) increase in QTc interval duration for each additional allele copy, and the rs10918594 G allele (31% frequency) was associated with a 3.6-ms (95% confidence interval, 2.7 to 4.4; P=6.9x10^–17) increase per additional allele copy. None of the inferred NOS1AP haplotypes showed a stronger effect than the individual single-nucleotide polymorphisms. There were 233 sudden cardiac deaths over 11.9 median years of follow-up. No significant association was observed with sudden cardiac death risk.

Conclusions— Common variants in NOS1AP are strongly associated with QT-interval duration in an elderly population. Larger sample sizes are needed to confirm or exclude an effect on sudden cardiac death risk.

Key Words: arrhythmia • death, sudden • electrocardiography • genetics • long-QT syndrome

	Introduction

Top Abstract Introduction Methods Results Discussion Conclusions References

 
Sudden cardiac death (SCD) claims 300 000 lives annually in the United States.¹ Although certain high-risk groups have been identified,² most SCD occurs in individuals unrecognized to be at risk.³

Clinical Perspective p 16

Familial aggregation of SCD suggests a substantial contribution of genetic variation to SCD risk,^4–7 but mendelian mutations identified to date individually explain little of the population burden of SCD.^8,9 Until recently, the search for sequence variants contributing to SCD risk has been restricted to candidate genes known for their role in arrhythmogenesis.¹⁰ The recent development of large single-nucleotide polymorphism (SNP) databases,¹¹ genotyping arrays of great accuracy and genome-wide coverage of common variation,¹² together with analytical methods,¹³ has enabled unbiased surveys of most of the common variation in the human genome. Still, the relatively small size of existing SCD collections and etiologic heterogeneity limit the statistical power to detect causal variants; therefore, initial attention has focused on quantitative SCD risk factors in large cohorts.

The electrocardiographic QT interval is a noninvasive measure of ventricular repolarization. About 35% of the variation in QT-interval duration in unselected community-based samples is heritable.^14,15 Mendelian congenital long- and short-QT syndromes are both characterized by SCD from ventricular arrhythmias. Moreover, nonsyndromal long QT interval^16–19 and short QT interval²⁰ impart increased risk of SCD in unselected populations. In addition, medication-induced prolonged QT interval and ventricular arrhythmias have led to the withdrawal of many noncardiac medications,²¹ making the QT interval an important phenotype to study.

Previously, we identified a locus on chromosome 3 with suggestive evidence of linkage to QT-interval duration, but the genomic interval was large, and the finding has yet to be confirmed.¹⁵ More recently, Arking et al²² reported the finding from a genome-wide association study that a common variant (rs10494366; minor allele frequency, 38%) in the NOS1AP gene was reproducibly associated with QT-interval variation in several large population samples. The NOS1AP gene, encoding the nitric oxide synthase 1 adaptor protein, has been found to regulate neuronal nitric oxide synthase activation²³ and to enhance Dexras1 activation by neuronal nitric oxide synthase through a ternary complex.²⁴ Neuronal nitric oxide synthase–knockout mice have been found to have altered cardiac contractility, which suggests a role for NOS1AP in cardiac depolarization.^25–27 Furthermore, NOS1AP is capable of interaction with ion channels through its PDZ domain.^28–30 Nevertheless, the involvement of NOS1AP in myocardial repolarization was not known until the initial report of the association.

The impact of NOS1AP variants on QT-interval duration in older populations, in whom nongenetic factors might play a stronger role than heritable factors, is unknown.

The goal of the present study was to test for association of the NOS1AP variant with QT duration and to test for its association with SCD in the Rotterdam Study.

	Methods

Top Abstract Introduction Methods Results Discussion Conclusions References

 
Study Population
The Rotterdam Study is a prospective population-based cohort study of chronic diseases in the elderly. All inhabitants of Ommoord, a Rotterdam suburb, 55 years of age (n=10 278), were ascertained from the municipal register and invited to participate. Of them, 78% (n=7983; 58% female, 98% white) took part in the baseline examination from March 1990 through July 1993. Second and third examinations were conducted from September 1993 to August 1996 and from April 1997 to December 1999, respectively. Objectives and methods of the Rotterdam Study have been described in detail.³¹ The medical ethics committee of Erasmus Medical Center (Rotterdam, the Netherlands) approved the study, and all participants provided signed informed consent for participation, including retrieval of medical records, use of blood and DNA for scientific purposes, and publication of data. DNA for genotyping is available for 6571 participants (82%) from the baseline visit.

Clinical characteristics, including smoking, body mass index, hypertension, diabetes mellitus, heart failure, and myocardial infarction, were ascertained as previously described.^19,32–36 Active surveillance for incident diabetes mellitus, heart failure, and myocardial infarction is conducted continuously between exams. In addition, exposure of study participants to medications has been gathered continuously from January 1, 1991, to the present through computerized pharmacy records of the pharmacies in the study area.

Genotyping
All participants were genotyped for the NOS1AP SNP rs10494366 T>G, previously shown to be associated with QT interval in 3 independent samples.²² The correlated SNP rs10918594 C>G, which had evidence of association with QT interval in one of the original samples,²² also was genotyped (see the Figure). Both were genotyped with Taqman assays C_1777074_10 and C_1777009_10 (Applied Biosystems, Foster City, Calif) in 1 ng genomic DNA extracted from leukocytes, as previously reported.³⁷

View larger version (4K): [in this window] [in a new window]   NOS1AP and location of rs10494366 and rs10918594. The ruler indicates the physical position on chromosome 1. Thick horizontal lines indicate genes in the region; thick vertical lines, NOS1AP exons; and arrows, the direction of transcription. Thick vertical lines on the ruler indicate the positions of rs10918594 and rs10494366, which are 55 kb apart. The 2 SNPs were in linkage disequilibrium, with an r2 of 0.63 and D' of 0.89.

Assessment of QTc Interval and Other Electrocardiographic Measurements
The electrocardiography (ECG) phenotype studied was the heart rate–corrected QT interval (QTc) in milliseconds using Bazett’s formula (QTc=QT/RR).³⁸ As in previous studies of QTc in the Rotterdam Study¹⁹ we used a 10-second resting 12-lead ECG (average of 8 to 10 beats), which was recorded on an ACTA ECG (ESAOTE, Florence, Italy) at a sampling frequency of 500 Hz and stored digitally. All ECGs were processed by the Modular ECG Analysis System (MEANS) to obtain ECG measurements.^39–41 MEANS determines the QT interval from the start of the QRS complex until the end of the T wave. MEANS also determines the presence of right or left bundle-branch block and left ventricular hypertrophy. To study the association between NOS1AP variants and QTc duration, all eligible ECGs from subjects with DNA available were used. ECGs with right or left bundle-branch block were excluded from analyses. In addition, to minimize confounding by nongenetic influences on QT duration, all ECGs taken while the subject was on any QT-altering drugs were excluded from analyses. Drugs were considered possibly QT prolonging if they appeared on any of lists 1 through 4 at www.qtdrugs.org.⁴² We also excluded ECGs if subjects were on flupentixol, levomepromazine, mefloquine, olanzapine, or sertindole, which may prolong QT interval, or digoxin, which shortens the QT interval. Up to 3 QTc measurements were recorded across the 3 examination cycles.

Finally, in additional analyses, the mean QTc interval per individual was divided into 3 gender-specific categories as previously described. For women, the cut points were 450 ms (normal), 451 to 470 ms (borderline), and >470 ms (prolonged); for men, the cut points were 430 ms (normal), 431 to 450 ms (borderline), and >450 ms (prolonged).^19,43

Adjudication of SCD
For the SCD analyses, all genotyped subjects were included. The ascertainment of SCD cases in the Rotterdam Study has been described previously.¹⁹ SCDs were defined operationally as a witnessed natural death attributable to cardiac causes, heralded by abrupt loss of consciousness, within 1 hour of onset of acute symptoms, or as an unwitnessed, unexpected death of someone seen in a stable medical condition <24 hours previously with no evidence of a noncardiac cause.^44,45

Statistical Analysis
Genotype frequencies were tested for Hardy-Weinberg equilibrium with a ² test.

Because the QTc in subsequent ECGs of the same subject are correlated, we used repeated-measures analyses implemented in PROC MIXED (SAS 8.2, SAS Institute, Cary, NC). Both allelic and general genotype models were tested for the 2 polymorphisms, although the allelic model was considered primary because of the previously reported rs10494366–QT relationship.²² Haplotypes were estimated with the expectation-maximization algorithm implemented in PHASE 2.0 (University of Washington, Seattle),^46,47 and only individuals with successful genotyping for both SNPs and a posterior probability of P>0.95 for assigned haplotypes were included in haplotype analyses. In total, we identified 2245 double heterozygotes, all of whom were phased as heterozygous haplotype TC-GG because these are the major haplotypes, with posterior probabilities in excess of 0.95. In haplotype analyses, the haplotype with major alleles for both SNPs was considered the reference to which the other 3 haplotypes were compared individually. QTc was tested for association with genotype as the sole predictor (crude) and with adjustment for age and gender (multivariable). To compare the outcomes of haplotype analysis with individual SNP analysis, the latter analyses also were performed restricting the analysis to subjects in whom genotyping was successful for both SNPs. Finally, a sensitivity analysis was carried out, excluding ECGs with an abnormally prolonged QTc and using gender-specific cutoff points of >450 ms for men and >470 ms for women. Jonckheere-Terpstra tests were used to test whether individuals carrying NOS1AP minor alleles had an increased frequency of borderline and abnormal mean QTc.

Hazard ratios for time to SCD from baseline were estimated with Cox proportional-hazards models. Again, both allelic and general genotype models were tested for the 2 polymorphisms. In addition to NOS1AP genotype, known SCD risk factors—including age, gender, body mass index, smoking, hypertension, diabetes mellitus, heart failure, and myocardial infarction at baseline and time-dependent incident diabetes mellitus, heart failure, and myocardial infarction—were included as predictors. To minimize misclassification of SCD, we additionally performed a subanalysis restricting the case definition to witnessed deaths only. As we have previously shown, the risk of SCD for increasing QTc is stronger in the younger than in the older age group,¹⁹ so we determined the hazard ratios for time to SCD separately in groups stratified by age above and below the median age at baseline. Finally, we performed a sensitivity analysis, excluding subjects with a history of myocardial infarction at baseline from the analysis. All Cox proportional hazards analyses were performed with SPSS for Windows, version 11.0 (SPSS Inc, Chicago, Ill).

The authors had full access to and take full responsibility for the integrity of the data. All authors have read and agree to the manuscript as written.

	Results

Top Abstract Introduction Methods Results Discussion Conclusions References

 
Study Subjects
Baseline characteristics for the total study population, consisting of all genotyped subjects from the Rotterdam Study (n=6571), are summarized in Table 1. Within the study population, 12 967 ECGs were available from 6052 subjects across up to 3 examination cycles. After exclusion of ECGs with right or left bundle-branch block (n=640) and those performed in individuals taking QT-prolonging or -shortening drugs (n=1334) or both, a total of 11 108 ECGs from 5374 subjects remained (on average, 2.1 ECGs per individual). The 5374 subjects included in the QTc analyses were 1.3 years younger at baseline, reflecting exclusions among older participants (Table 1). Women had an 8.9-ms-longer age-adjusted QTc interval (431.4 versus 422.5 ms; P<0.0001), as previously shown,^38,48 and were 2.2 years older than men (70.4 versus 68.2 years at baseline; P<0.0001). The numbers of abnormally prolonged QTc in men and women of our study population were slightly higher than expected on the basis of numbers from reference populations.^48,49 However, our study population was on average already considerably older at baseline (69.5 versus 53 and 61 years, respectively), and this mean further increased when follow-up ECGs were taken.

View this table: [in this window] [in a new window]   TABLE 1. Baseline Characteristics

Genotyping
The G-allele (minor) frequency of rs10494366 T>G was 36.4% and of rs10918594 C>G was 31.4%. Successful genotype calls were made in 95.8% and 95.9% of subjects, respectively. Both SNPs were in Hardy-Weinberg equilibrium (P=0.32 for rs10494366 and P=0.89 for rs10918594). The 2 SNPs were in linkage disequilibrium, with an r² of 0.63 and D' of 0.89. On phasing, we observed 2 common 2-SNP haplotypes, TC (61.4%) and GG (29.1%), consisting of the 2 major and 2 minor alleles, respectively, and 2 remaining haplotypes containing 1 major and 1 minor allele each, GC (7.2%) and TG (2.3%). Genotype distributions did not differ between men and women and between quartiles of age at baseline.

NOS1AP Polymorphisms and QTc
Minor alleles of both NOS1AP SNPs were significantly associated with an increase in QTc duration. SNP rs10494366 T>G was associated with a 3.8-ms increase in multivariable-adjusted QTc interval for each additional G allele, and SNP rs10918594 C>G was associated with a 3.6-ms increase per additional G allele (Table 2). Additional adjustment for ECG left ventricular hypertrophy did not alter the results (data not shown). We observed no difference in effect of the SNPs between men and women. A sensitivity analysis excluding ECGs with an abnormally prolonged QTc (using gender-specific cut points) resulted in slightly lower estimates (2.9 and 2.7 ms for the allelic models); however, the association of NOS1AP genotypes with QTc duration remained highly significant (all P<10^–11).

View this table: [in this window] [in a new window]   TABLE 2. Difference in QTc by NOS1AP Genotype

All 3 haplotypes containing 1 (GC and TG) or 2 (GG) minor alleles for the 2 SNPs were associated with increased QTc compared with the homozygous TC reference haplotype. The GG haplotype was associated with a 4.1-ms-longer multivariable-adjusted QTc per additional GG haplotype copy (P=2.0x10^–18) using the TC haplotype as reference. The GC and TG haplotypes were associated with a 3.2-ms-longer (P=7.0x10^–4) and 4.1-ms-longer (P=0.01) multivariable-adjusted QT interval per additional copy, respectively. None of the haplotypes had a more significant effect than the individual SNPs.

Furthermore, rs10494366 and rs10918594 were associated with a larger proportion of borderline and prolonged QTc intervals using gender-specific cut points¹⁹ (test for trend, both P<0.0001; Table 3).

View this table: [in this window] [in a new window]   TABLE 3. Number of Individuals With Normal, Borderline, and Abnormal Mean QTc per Genotype Group Using Gender-Specific Cut Points

NOS1AP Polymorphisms and SCD
Within the study population (n=6571), we identified 233 sudden cardiac deaths, 121 of which were witnessed. Baseline characteristics of all adjudicated SCD cases are shown in Table 1. After adjustment for known risk factors, the NOS1AP polymorphisms rs10494366 T>G and rs10918594 C>G showed nonsignificant trends in the direction of increased hazard of SCD, with hazard ratios per additional minor allele for time to SCD of 1.09 (95% confidence interval, 0.90 to 1.33) and 1.10 (95% confidence interval, 0.90 to 1.34), respectively. In the subset of 121 adjudicated SCD cases that were witnessed, a similar nonsignificant trend toward increased SCD risk was found (Table 4). Stratification for baseline age above and below the median showed no difference between age groups (data not shown). Finally, a sensitivity analysis excluding 767 subjects with a history of myocardial infarction at baseline did not result in a substantial change of the effect estimates or confidence intervals (data not shown).

View this table: [in this window] [in a new window]   TABLE 4. Hazard Ratio of All Adjudicated SCD and Witnessed SCD per NOS1AP Genotype or Allele

	Discussion

Top Abstract Introduction Methods Results Discussion Conclusions References

 
We observed strong replication in the Rotterdam Study, a large, well-phenotyped cohort of European ancestry, of the finding from a prior genome-wide association study²² that common NOS1AP variants are associated with increased age-, gender-, and heart rate–adjusted QT-interval duration. None of the haplotypes showed a more significant effect than the individual SNPs, which were not specifically selected to characterize haplotype variation at the locus. The 2 SNPs, which are 55 kb apart, are not known to be functional, nor are they highly correlated with any known functional SNP. These results support the existence of a causal untyped SNP that is correlated with both rs10494366 and rs10918594.

The association with SCD was not statistically significant. Although we cannot fully exclude survival bias because of the older age of our study population, we did not find that the genotype distribution differed between different age groups at baseline, making this less likely. The modest QTc prolongation associated with NOS1AP variation, despite the strong effect of prolonged QTc on SCD risk, suggests that a much larger study is needed to definitively confirm or rule out an increased risk of SCD by NOS1AP variants. At least 510 cases would be needed to detect an odds ratio of 1.2 per minor allele with 80% power. Even if no association with SCD is ultimately identified, the 7.2-ms increase in QTc interval in minor homozygotes compared with major homozygotes approximates the effect of medications that delay myocardial repolarization and increase liability to ventricular arrhythmias.

The mechanism by which a common variation in NOS1AP affects QTc interval duration is unknown at present. However, the statistical evidence supporting the association with QTc interval of rs10494366 (P<10^–19) and rs10918594 (P<10^–16) in 5374 individuals confirms that this is a genuine association, consistent with evidence from 4 independent cohorts totaling >13 000 individuals of European ancestry. Our study examined the relationship of genetic variation, present at birth, in an elderly cohort in whom one might assume that genetic factors play a smaller role than in younger cohorts. However, these results demonstrate that genetic factors continue to play a role even at older age.

One major advantage of our study was the availability of up to 3 ECGs per subject at regular intervals during follow-up, resulting in more precise long-term ECG measures. Furthermore, the use of digital ECG recordings all measured with the MEANS system likely reduced systematic differences in assessment of the QTc interval. In addition, the intersection of the Rotterdam Study with detailed pharmacy exposure data allowed us to exclude ECGs recorded in individuals on QT-prolonging or -shortening drugs, which could have attenuated the power to detect the association. Although no information on long-QT syndrome cases was available, the number of relatives in the Rotterdam Study is low, and the sensitivity analysis excluding abnormally prolonged QTc further minimized influence of potential familial long-QT syndrome cases. Another advantage of the Rotterdam Study is the prospective ascertainment of risk factors and the active surveillance for SCD events over a relatively long period of follow-up. Thus, extensive information surrounding SCD events was available, including the time between start of symptoms and death, which enabled rigorous adjudication of SCD events.

One limitation of the study resides in the variety of competing causes of abrupt death at increasing age, which may have led to misclassification, especially in cases in which death was unwitnessed. Because SCD coding was blinded to NOS1AP genotype, this would likely have biased our study to detect no effect. This might explain our finding of a slightly increased, but still nonsignificant, hazard ratio when the analyses were restricted to witnessed sudden cardiac deaths. Our results and those of the prior study by Arking et al²² were restricted to population samples of European ancestry. Further testing in samples of African and Asian ancestry is needed to establish the role of genetic variation at the NOS1AP locus in myocardial repolarization in these population groups. Moreover, substantial frequency differences are observed among European, African, and Asian HapMap samples, which raises the possibility of natural selection in the region.⁵⁰ Attempts to validate the NOS1AP association in recently admixed populations, such as African Americans, will need to account for global and local chromosomal differences in ancestry because of the strong association with continental ancestry and the risk of population stratification.

	Conclusions

Top Abstract Introduction Methods Results Discussion Conclusions References

 
We have strongly confirmed the association of NOS1AP variants with QT-interval duration. With the limited number of SCD cases in our cohort, it was not possible to demonstrate that this association translates into an influence on risk of SCD, although the point estimates suggest that such a risk increase may truly exist. Additional larger studies are required to determine whether NOS1AP genotype is associated with SCD.

	Acknowledgments

 
We thank Rowena Utberg for genotyping and Cornelis van der Hooft and Charlotte van Noord for their help with adjudication of SCD cases.

Sources of Funding

Dr Newton-Cheh and the genotyping were supported by a Doris Duke Charitable Foundation Clinical Scientist Development Award and NIH K23 (HL80025).

Disclosures

None.

	References

Top Abstract Introduction Methods Results Discussion Conclusions References

 

1. Thom T, Haase N, Rosamond W, Howard VJ, Rumsfeld J, Manolio T, Zheng ZJ, Flegal K, O’Donnell C, Kittner S, Lloyd-Jones D, Goff DC Jr, Hong Y, Adams R, Friday G, Furie K, Gorelick P, Kissela B, Marler J, Meigs J, Roger V, Sidney S, Sorlie P, Steinberger J, Wasserthiel-Smoller S, Wilson M, Wolf P. Heart disease and stroke statistics: 2006 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2006; 113: e85–e151.[Free Full Text]
   
2. Moss AJ, Zareba W, Hall WJ, Klein H, Wilber DJ, Cannom DS, Daubert JP, Higgins SL, Brown MW, Andrews ML. Prophylactic implantation of a defibrillator in patients with myocardial infarction and reduced ejection fraction. N Engl J Med. 2002; 346: 877–883.[Abstract/Free Full Text]
   
3. Myerburg RJ, Castellanos A. Emerging paradigms of the epidemiology and demographics of sudden cardiac arrest. Heart Rhythm. 2006; 3: 235–239.[CrossRef][Medline] [Order article via Infotrieve]
   
4. Jouven X, Desnos M, Guerot C, Ducimetiere P. Predicting sudden death in the population: the Paris Prospective Study I. Circulation. 1999; 99: 1978–1983.[Abstract/Free Full Text]
   
5. Friedlander Y, Siscovick DS, Arbogast P, Psaty BM, Weinmann S, Lemaitre RN, Raghunathan TE, Cobb LA. Sudden death and myocardial infarction in first degree relatives as predictors of primary cardiac arrest. Atherosclerosis. 2002; 162: 211–216.[CrossRef][Medline] [Order article via Infotrieve]
   
6. Dekker LR, Bezzina CR, Henriques JP, Tanck MW, Koch KT, Alings MW, Arnold AE, de Boer MJ, Gorgels AP, Michels HR, Verkerk A, Verheugt FW, Zijlstra F, Wilde AA. Familial sudden death is an important risk factor for primary ventricular fibrillation: a case-control study in acute myocardial infarction patients. Circulation. 2006; 114: 1140–1145.[Abstract/Free Full Text]
   
7. Kaikkonen KS, Kortelainen ML, Linna E, Huikuri HV. Family history and the risk of sudden cardiac death as a manifestation of an acute coronary event. Circulation. 2006; 114: 1462–1467.[Abstract/Free Full Text]
   
8. Splawski I, Shen J, Timothy KW, Lehmann MH, Priori S, Robinson JL, Moss AJ, Schwartz PJ, Towbin JA, Vincent GM, Keating MT. Spectrum of mutations in long-QT syndrome genes: KVLQT1, HERG, SCN5A, KCNE1, and KCNE2. Circulation. 2000; 102: 1178–1185.[Abstract/Free Full Text]
   
9. Mohler PJ, Schott JJ, Gramolini AO, Dilly KW, Guatimosim S, duBell WH, Song LS, Haurogne K, Kyndt F, Ali ME, Rogers TB, Lederer WJ, Escande D, Le Marec H, Bennett V. Ankyrin-B mutation causes type 4 long-QT cardiac arrhythmia and sudden cardiac death. Nature. 2003; 421: 634–639.[CrossRef][Medline] [Order article via Infotrieve]
   
10. Splawski I, Timothy KW, Tateyama M, Clancy CE, Malhotra A, Beggs AH, Cappuccio FP, Sagnella GA, Kass RS, Keating MT. Variant of SCN5A sodium channel implicated in risk of cardiac arrhythmia. Science. 2002; 297: 1333–1336.[Abstract/Free Full Text]
    
11. International HapMap Consortium. A haplotype map of the human genome. Nature. 2005; 437: 1299–1320.[CrossRef][Medline] [Order article via Infotrieve]
    
12. de Bakker PI, Yelensky R, Pe’er I, Gabriel SB, Daly MJ, Altshuler D. Efficiency and power in genetic association studies. Nat Genet. 2005; 37: 1217–1223.[CrossRef][Medline] [Order article via Infotrieve]
    
13. Skol AD, Scott LJ, Abecasis GR, Boehnke M. Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet. 2006; 38: 209–213.[CrossRef][Medline] [Order article via Infotrieve]
    
14. Hong Y, Rautaharju PM, Hopkins PN, Arnett DK, Djousse L, Pankow JS, Sholinsky P, Rao DC, Province MA. Familial aggregation of QT-interval variability in a general population: results from the NHLBI Family Heart Study. Clin Genet. 2001; 59: 171–177.[CrossRef][Medline] [Order article via Infotrieve]
    
15. Newton-Cheh C, Larson MG, Corey DC, Benjamin EJ, Herbert AG, Levy D, D’Agostino RB, O’Donnell CJ. QT interval is a heritable quantitative trait with evidence of linkage to chromosome 3 in a genome-wide linkage analysis: the Framingham Heart Study. Heart Rhythm. 2005; 2: 277–284.[CrossRef][Medline] [Order article via Infotrieve]
    
16. Schouten EG, Dekker JM, Meppelink P, Kok FJ, Vandenbroucke JP, Pool J. QT interval prolongation predicts cardiovascular mortality in an apparently healthy population. Circulation. 1991; 84: 1516–1523.[Abstract/Free Full Text]
    
17. Siscovick DS, Raghunathan TE, Rautaharju P, Psaty BM, Cobb LA, Wagner EH. Clinically silent electrocardiographic abnormalities and risk of primary cardiac arrest among hypertensive patients. Circulation. 1996; 94: 1329–1333.[Abstract/Free Full Text]
    
18. Karjalainen J, Reunanen A, Ristola P, Viitasalo M. QT interval as a cardiac risk factor in a middle aged population. Heart. 1997; 77: 543–548.[Abstract/Free Full Text]
    
19. Straus SM, Kors JA, De Bruin ML, van der Hooft CS, Hofman A, Heeringa J, Deckers JW, Kingma JH, Sturkenboom MC, Stricker BH, Witteman JC. Prolonged QTc interval and risk of sudden cardiac death in a population of older adults. J Am Coll Cardiol. 2006; 47: 362–367.[Abstract/Free Full Text]
    
20. Algra A, Tijssen JG, Roelandt JR, Pool J, Lubsen J. QT interval variables from 24 hour electrocardiography and the two year risk of sudden death. Br Heart J. 1993; 70: 43–48.[Abstract/Free Full Text]
    
21. Yap YG, Camm AJ. Drug induced QT prolongation and torsades de pointes. Heart. 2003; 89: 1363–1372.[Free Full Text]
    
22. Arking DE, Pfeufer A, Post W, Kao WH, Newton-Cheh C, Ikeda M, West K, Kashuk C, Akyol M, Perz S, Jalilzadeh S, Illig T, Gieger C, Guo CY, Larson MG, Wichmann HE, Marban E, O’Donnell CJ, Hirschhorn JN, Kaab S, Spooner PM, Meitinger T, Chakravarti A. A common genetic variant in the NOS1 regulator NOS1AP modulates cardiac repolarization. Nat Genet. 2006; 38: 644–651.[CrossRef][Medline] [Order article via Infotrieve]
    
23. Jaffrey SR, Snowman AM, Eliasson MJ, Cohen NA, Snyder SH. CAPON: a protein associated with neuronal nitric oxide synthase that regulates its interactions with PSD95. Neuron. 1998; 20: 115–124.[CrossRef][Medline] [Order article via Infotrieve]
    
24. Fang M, Jaffrey SR, Sawa A, Ye K, Luo X, Snyder SH. Dexras1: a G protein specifically coupled to neuronal nitric oxide synthase via CAPON. Neuron. 2000; 28: 183–193.[CrossRef][Medline] [Order article via Infotrieve]
    
25. Massion PB, Pelat M, Belge C, Balligand JL. Regulation of the mammalian heart function by nitric oxide. Comp Biochem Physiol A Mol Integr Physiol. 2005; 142: 144–150.[CrossRef][Medline] [Order article via Infotrieve]
    
26. Ashley EA, Sears CE, Bryant SM, Watkins HC, Casadei B. Cardiac nitric oxide synthase 1 regulates basal and beta-adrenergic contractility in murine ventricular myocytes. Circulation. 2002; 105: 3011–3016.[Abstract/Free Full Text]
    
27. Barouch LA, Harrison RW, Skaf MW, Rosas GO, Cappola TP, Kobeissi ZA, Hobai IA, Lemmon CA, Burnett AL, O’Rourke B, Rodriguez ER, Huang PL, Lima JA, Berkowitz DE, Hare JM. Nitric oxide regulates the heart by spatial confinement of nitric oxide synthase isoforms. Nature. 2002; 416: 337–339.[Medline] [Order article via Infotrieve]
    
28. Murata M, Buckett PD, Zhou J, Brunner M, Folco E, Koren G. SAP97 interacts with Kv1.5 in heterologous expression systems. Am J Physiol Heart Circ Physiol. 2001; 281: H2575–H2584.[Abstract/Free Full Text]
    
29. Leonoudakis D, Mailliard W, Wingerd K, Clegg D, Vandenberg C. Inward rectifier potassium channel Kir2.2 is associated with synapse-associated protein SAP97. J Cell Sci. 2001; 114: 987–998.[Abstract]
    
30. Kim E, Sheng M. Differential K+ channel clustering activity of PSD-95 and SAP97, two related membrane-associated putative guanylate kinases. Neuropharmacology. 1996; 35: 993–1000.[CrossRef][Medline] [Order article via Infotrieve]
    
31. Hofman A, Grobbee DE, de Jong PT, van den Ouweland FA. Determinants of disease and disability in the elderly: the Rotterdam Elderly Study. Eur J Epidemiol. 1991; 7: 403–422.[CrossRef][Medline] [Order article via Infotrieve]
    
32. Diabetes mellitus. In: Technical Reports Series 894. Geneva, Switzerland: World Health Organization; 1985.
    
33. Bots ML, Hoes AW, Koudstaal PJ, Hofman A, Grobbee DE. Common carotid intima-media thickness and risk of stroke and myocardial infarction: the Rotterdam Study. Circulation. 1997; 96: 1432–1437.[Abstract/Free Full Text]
    
34. Mosterd A, Hoes AW, de Bruyne MC, Deckers JW, Linker DT, Hofman A, Grobbee DE. Prevalence of heart failure and left ventricular dysfunction in the general population: the Rotterdam Study. Eur Heart J. 1999; 20: 447–455.[Abstract/Free Full Text]
    
35. 1999 World Health Organization–International Society of Hypertension guidelines for the management of hypertension: Guidelines Subcommittee. J Hypertens. 1999; 17: 151–183.[Medline] [Order article via Infotrieve]
    
36. Bleumink GS, Knetsch AM, Sturkenboom MC, Straus SM, Hofman A, Deckers JW, Witteman JC, Stricker BH. Quantifying the heart failure epidemic: prevalence, incidence rate, lifetime risk and prognosis of heart failure: the Rotterdam Study. Eur Heart J. 2004; 25: 1614–1619.[Abstract/Free Full Text]
    
37. Fang Y, van Meurs JB, d’Alesio A, Jhamai M, Zhao H, Rivadeneira F, Hofman A, van Leeuwen JP, Jehan F, Pols HA, Uitterlinden AG. Promoter and 3'-untranslated-region haplotypes in the vitamin D receptor gene predispose to osteoporotic fracture: the Rotterdam Study. Am J Hum Genet. 2005; 77: 807–823.[CrossRef][Medline] [Order article via Infotrieve]
    
38. Bazett H. An analysis of time relations of the electrocardiogram. Heart. 1920; 7: 353–370.
    
39. van Bemmel JH, Kors JA, van Herpen G. Methodology of the modular ECG analysis system MEANS. Methods Inf Med. 1990; 29: 346–353.[Medline] [Order article via Infotrieve]
    
40. Willems JL, Abreu-Lima C, Arnaud P, van Bemmel JH, Brohet C, Degani R, Denis B, Gehring J, Graham I, van Herpen G, Machado H, Macfarlane PW, Michaelis J, Moulopoulos SD, Rubel P, Zywietz C. The diagnostic performance of computer programs for the interpretation of electrocardiograms. N Engl J Med. 1991; 325: 1767–1773.[Abstract]
    
41. de Bruyne MC, Kors JA, Hoes AW, Kruijssen DA, Deckers JW, Grosfeld M, van Herpen G, Grobbee DE, van Bemmel JH. Diagnostic interpretation of electrocardiograms in population-based research: computer program research physicians, or cardiologists? J Clin Epidemiol. 1997; 50: 947–952.[CrossRef][Medline] [Order article via Infotrieve]
    
42. Drugs That Prolong the QT Interval and/or Induce Torsades de Pointes Ventricular Arrhythmia. Tucson, Ariz: University of Arizona Center for Education and Research on Therapeutics, Arizona Health Sciences Center. Available at: http://www.qtdrugs.org/medical-pros/drug-lists/drug-lists.htm. Accessed November 8, 2006.
    
43. The Assessment of the Potential for QT Interval Prolongation by Non-Cardiovascular Medicinal Products. London, UK: Committee for Proprietary Medicinal Products; 1997.
    
44. Myerburg RJ, Castellanos A. Cardiac arrest and sudden cardiac death. In: Zipes DP, Libby P, Bonow RO, Braunwald E, eds. Heart Disease: A Text Book of Cardiovascular Medicine. 7th ed. Philadelphia, Pa: Elsevier Saunders Co; 2004: 865–908.
    
45. Priori SG, Aliot E, Blomstrom-Lundqvist C, Bossaert L, Breithardt G, Brugada P, Camm AJ, Cappato R, Cobbe SM, Di Mario C, Maron BJ, McKenna WJ, Pedersen AK, Ravens U, Schwartz PJ, Trusz-Gluza M, Vardas P, Wellens HJ, Zipes DP. Task Force on Sudden Cardiac Death of the European Society of Cardiology. Eur Heart J. 2001; 22: 1374–1450.[Free Full Text]
    
46. Stephens M, Smith NJ, Donnelly P. A new statistical method for haplotype reconstruction from population data. Am J Hum Genet. 2001; 68: 978–989.[CrossRef][Medline] [Order article via Infotrieve]
    
47. Stephens M, Donnelly P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet. 2003; 73: 1162–1169.[CrossRef][Medline] [Order article via Infotrieve]
    
48. Vitelli LL, Crow RS, Shahar E, Hutchinson RG, Rautaharju PM, Folsom AR. Electrocardiographic findings in a healthy biracial population: Atherosclerosis Risk in Communities (ARIC) Study Investigators. Am J Cardiol. 1998; 81: 453–459.[CrossRef][Medline] [Order article via Infotrieve]
    
49. Rautaharju PM, Prineas RJ, Kadish A, Larson JC, Hsia J, Lund B. Normal standards for QT and QT subintervals derived from a large ethnically diverse population of women aged 50 to 79 years (the Women’s Health Initiative [WHI]). Am J Cardiol. 2006; 97: 730–737.[CrossRef][Medline] [Order article via Infotrieve]
    
50. International HapMap Project. Available at: www.hapmap.org/cgi-perl/gbrowse/hapmap21_B35. Accessed November 6, 2006.
    

---

 

CLINICAL PERSPECTIVE

Sudden cardiac death (SCD) claims 300 000 lives annually in the United States. The ECG QT interval is a noninvasive measure of ventricular repolarization, and prolongation of the QT interval is an important risk factor for SCD and drug-induced arrhythmias. Approximately 35% of the variation in QT-interval duration is attributable to heritable factors. Until recently, the search for sequence variants contributing to QT-interval duration and SCD risk has been restricted to candidate genes known for their role in arrhythmogenesis. However, in a recent genome-wide association study, a common variant in the nitric oxide synthase 1 adaptor protein (NOS1AP) gene was found to be associated with QT-interval variation. NOS1AP was not previously known to play a role in repolarization. In the present study, we have strongly confirmed the association of NOS1AP variants and QT-interval duration with a difference between minor homozygotes and major homozygotes of 7.2 ms (P<10^–19). We did not find an association of NOS1AP variants with SCD cases in our cohort, but with 228 SCD events, our study was underpowered to demonstrate such an effect. Even if no association with SCD is ultimately identified, the 7.2-ms increase in QTc interval in minor allele homozygotes compared with major homozygotes approximates the effect of medications that delay myocardial repolarization and increase liability to ventricular arrhythmias. The study underscores the power of association methods to identify novel genes and pathways involved in myocardial repolarization and to identify genetic variants that could contribute to the risk of cardiac arrhythmias.

	Footnotes

 
*The first 2 authors contributed equally to this work.

This article has been cited by other articles:

				M. D Tobin, M. Kahonen, P. Braund, T. Nieminen, C. Hajat, M. Tomaszewski, J. Viik, R. Lehtinen, G A. Ng, P. W Macfarlane, et al. Gender and effects of a common genetic variant in the NOS1 regulator NOS1AP on cardiac repolarization in 3761 individuals from two independent populations Int. J. Epidemiol., May 29, 2008; (2008) dyn091v1. [Abstract] [Full Text] [PDF]

				A. B. Lehtinen, C. Newton-Cheh, J. T. Ziegler, C. D. Langefeld, B. I. Freedman, K. R. Daniel, D. M. Herrington, and D. W. Bowden Association of NOS1AP Genetic Variants With QT Interval Duration in Families From the Diabetes Heart Study Diabetes, April 1, 2008; 57(4): 1108 - 1114. [Abstract] [Full Text] [PDF]

				K.-C. Chang, A. S. Barth, T. Sasano, E. Kizana, Y. Kashiwakura, Y. Zhang, D. B. Foster, and E. Marban CAPON modulates cardiac repolarization via neuronal nitric oxide synthase signaling in the heart PNAS, March 18, 2008; 105(11): 4477 - 4482. [Abstract] [Full Text] [PDF]

				N. Herring and D. J Paterson Letter by Herring and Paterson Regarding Article, "Common NOS1AP Variants Are Associated With a Prolonged QTc Interval in the Rotterdam Study" Circulation, December 11, 2007; 116(24): e564 - e564. [Full Text] [PDF]

				A.-J. L.H.J. Aarnoudse, S. M.J.M. Straus, A. Hofman, A. G. Uitterlinden, J. C.M. Witteman, B. H.C. Stricker, C. Newton-Cheh, J. A. Kors, and P. I.W. de Bakker Response to Letter Regarding Article, "Common NOS1AP Variants Are Associated With a Prolonged QTc Interval in the Rotterdam Study" Circulation, December 11, 2007; 116(24): e565 - e565. [Full Text] [PDF]

				F. Cambien and L. Tiret Genetics of Cardiovascular Diseases: From Single Mutations to the Whole Genome Circulation, October 9, 2007; 116(15): 1714 - 1724. [Full Text] [PDF]

				C. Newton-Cheh, C.-Y. Guo, M. G. Larson, S. L. Musone, A. Surti, A. L. Camargo, J. A. Drake, E. J. Benjamin, D. Levy, R. B. D'Agostino Sr, et al. Common Genetic Variation in KCNH2 Is Associated With QT Interval Duration: The Framingham Heart Study Circulation, September 4, 2007; 116(10): 1128 - 1136. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) All Versions of this Article: 116/1/10    most recent CIRCULATIONAHA.106.676783v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Aarnoudse, A.-J. L.H.J. Articles by Stricker, B. H.C. Search for Related Content PubMed PubMed Citation Articles by Aarnoudse, A.-J. L.H.J. Articles by Stricker, B. H.C. Related Collections Clinical genetics Arrhythmias, clinical electrophysiology, drugs Epidemiology Genetics of cardiovascular disease