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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
JAMA. Author manuscript; available in PMC May 24, 2011.
Published in final edited form as:
PMCID: PMC3073054
NIHMSID: NIHMS275343

Association between Familial Atrial Fibrillation and Risk of New-onset Atrial Fibrillation

Steven A. Lubitz, MD, MPH,1,2 Xiaoyan Yin, PhD,3 João D. Fontes, MD,3,4 Jared W. Magnani, MD,3,4 Michiel Rienstra, MD, PhD,1,5 Manju Pai, MD,6 Mark L. Villalon, MD,6 Ramachandran S. Vasan, MD,3,4,7 Michael J. Pencina, PhD,3,8 Daniel Levy, MD,3,9 Martin G. Larson, SD,3,8,10 Patrick T. Ellinor, MD, PhD,1,11 and Emelia J. Benjamin, MD, ScM3,4,7,12

Abstract

Context

Although the heritability of atrial fibrillation (AF) is established, the contribution of familial AF to predicting new-onset AF remains unknown.

Objective

To determine whether familial occurrence of AF is associated with new-onset AF beyond established risk factors.

Design, Setting, and Participants

The Framingham Heart Study, a prospective population-based cohort study started in 1948. Original and Offspring Cohort participants were age at least 30 years, free of AF at the baseline examination, and had at least one parent or sibling enrolled in the study.

Main outcome measures

The incremental predictive value of incorporating different features of familial AF (any familial AF, premature familial AF [onset ≤65 years], number of affected relatives, and youngest age of onset in a relative) into a risk model for new-onset AF.

Results

Of 4421 participants (11971 person-examinations, mean age 54±13 years, 54% women), 440 developed AF during follow-up. Familial AF occurred in 1185 participants (26.8%) and premature familial AF occurred in 351 (7.9%) participants. AF occurred more frequently among participants with familial AF than without familial AF (unadjusted absolute event rates of 5.8% and 3.1%, respectively). The association was not attenuated by adjustment for AF risk factors (multivariable-adjusted HR 1.40, 95% CI 1.13–1.74) or reported AF-related genetic variants. Among the different features of familial AF examined, premature familial AF was associated with improved discrimination beyond traditional risk factors to the greatest extent (c-statistic 0.842; 95% CI, 0.826–0.858 to 0.846; 95%CI, 0.831–0.862; P=.004). Modest changes in integrated discrimination improvement were observed with premature familial AF (2.1%). Net reclassification improvement (assessed using eight-year risk thresholds of <5%, 5–10%, >10%) did not change significantly with premature familial AF (0.011; 95% CI, −0.021–0.042; P=.51), although category-less net reclassification was improved (0.127; 95% CI, 0.064–0.189; P=.009).

Conclusions

Familial AF was associated with an increased risk of AF that was not attenuated by adjustment for AF risk factors including genetic variants. Assessment of premature familial AF was associated with a very slight increase in predictive accuracy compared with traditional risk factors.

A heritable component underlying atrial fibrillation (AF) has been well-demonstrated,16 and it is now evident that genetic variants are associated with AF risk.710 However, the role of familial occurrence across and within generations has received little attention.

Several gaps in knowledge exist regarding the association between familial AF and AF risk. Although AF risk appears greater with younger age of AF onset in relatives,1,2 the magnitude of risk attributable to familial AF has not been characterized across a wide range of AF onset ages in family members. Whereas occurrence of AF in a first-degree relative is associated with new-onset AF, only parental AF has been demonstrated to confer risk independently of other AF risk factors.1 The association between sibling AF and AF risk after accounting for parental disease has not been examined. Importantly, the extent to which risk conferred by familial AF is mediated by common AF susceptibility loci identified in genome-wide association studies on chromosomes 4q25, 16q22, and 1q21710 is unknown.

Furthermore, familial AF has not been formally examined as a risk factor for AF using conventional metrics that assess discrimination and risk reclassification. Investigators from the Framingham Heart Study recently developed a clinical risk score for predicting AF,11 but familial AF was not assessed as a potential risk factor. We examined the association between AF occurrence in a first-degree relative and AF risk, and hypothesized that considering familial AF would enhance prediction of new-onset AF.

METHODS

Participants

We identified participants from the Framingham Heart Study who were age at least 30 years, free of AF at one or more of the following examinations: Original cohort12 cycles 11 (1968–71, n=934), 18 (1983–85, n=621), 22 (1990–94, n=353), and 26 (1999–2001, n=148), and Offspring cohort13 cycles 1 (1971–75, n=2326), 3 (1984–87, n=2622), 5 (1991–95, n=2600), and 7 (1998–2001, n=2367). All included participants had at least one parent or sibling enrolled in the study. Since examinations were conducted two to eight years apart, we examined the eight-year occurrence of AF. Participants in this analysis were followed through December 31, 2007. Study protocols for examination cycles received ethics approval from the Boston University Medical Center Institutional Review Board, and participants signed consent forms.

Assessment of AF

At each Framingham Heart Study clinic examination, participants’ medical histories, physical examinations, and electrocardiograms were obtained to ascertain symptoms and findings suggestive of cardiovascular disease. Records of all interim hospitalizations for cardiovascular disease were sought for review. Participants were classified as having AF if either atrial flutter or fibrillation were present on an electrocardiogram obtained at a Framingham Heart Study clinic visit, an electrocardiogram during an encounter with an external clinician, Holter monitoring, or noted in hospital records.14 Familial AF was defined as the occurrence of AF in a first-degree relative prior to an examination commencing an eight-year follow-up period (baseline examination). A priori, we defined familial AF as premature when the first-detected occurrence was at age 65 years or younger in a first-degree relative in keeping with prior analyses of early-onset AF.4,10 Two physicians unaware of familial AF status adjudicated AF events.

Statistical analysis

Participant characteristics were ascertained at Framingham Heart Study clinic examinations. Potential risk factors for AF, other than familial AF, were derived from a published prediction model and included age, sex, body mass index, systolic blood pressure, treatment for hypertension, PR interval, significant heart murmur (≥grade three of six systolic or any diastolic), and heart failure (eMethods).11 In 477 participants from the Original cohort, neither treatment for hypertension nor heart murmur were available at examination 11 (1968–71), and both were carried forward from examination cycle 10 (1966–70). Heart murmur status was not measured in 148 Original cohort participants who attended examination 26 (1999–2001) and was carried over from earlier examinations.

We examined associations between risk factors and incident AF using proportional hazards regression with robust variance estimators to account for relatedness among participants.15 We restricted our model to risk factors with multivariable-adjusted two-sided P values <.05 in our sample, and forced in treatment for hypertension (eMethods).11 Follow-up began at baseline examinations and participants were censored at death, loss to follow-up, or the earliest of either the next baseline examination or eight-years. Follow-up windows were pooled.16 Proportional hazards assumptions were verified with multiplicative interaction terms between covariates and survival time. To account for potentially differing baseline hazards of AF during different cohorts and eras, we stratified models by cohort and examination.

We estimated the cumulative incidence of AF among those with or without familial AF using the Kaplan-Meier method, adjusting for the competing risk of death.17 We calculated unadjusted absolute event rates by dividing the number of events by the number of person-examinations, where the total number of person-examinations is the sum of the number of baseline examinations that all participants attended. We modeled familial AF in several ways, including treating the presence of familial AF as a dichotomous variable; treating the number of first-degree relatives with AF as a continuous dosage; and introducing separate indicators for AF in fathers, mothers, and siblings. Since the number of informative family members differs across participants, we explored associations between familial and incident AF in models stratified by family size; presence of fathers, mothers, or siblings in the study; presence of any parent versus sibling in the study; and in non-stratified models. In models that included terms for maternal, paternal, and sibling AF, we used contrasts among parameter estimates to test equality of effects among different sources of familial AF with the Wald chi-squared statistic.

We examined whether the effect estimate for familial AF differed according to participant age by modeling AF risk in different groups of participant age (30–49, 50–59, 60–69, 70–79, and 80–99 years). We also examined the relations between AF onset age in the youngest affected relative and incident AF compared to participants without familial AF by including indicators for familial AF and familial age of onset in the same model. We examined linearity of the association with a restricted cubic spline model among those with familial AF (knots at 50, 60, 70, 80, and 90 years).18,19

In a subset of genotyped participants, we assessed the degree to which risk associated with familial AF was mediated by AF-associated genetic loci by examining the change in effect estimate for familial AF after adjusting for genotypes of four common single nucleotide polymorphisms (SNPs) tagging validated genome-wide significant (P<5×10−8) AF susceptibility signals ([chromosomal locus-dbSNP rsID] 4q25-rs2200733 and 4q25-rs100334647 [r2 0.015 HapMap Phase III CEU20], 16q22-rs2106261,8,9 and 1q21-rs13376333).10 See eMethods for genotyping and imputation details. Minor alleles for SNPs were modeled assuming an additive genetic effect.

After exploring the relations between familial AF and AF risk, we assessed model fit statistics with the addition of various features of familial AF into an AF prediction model. For discrimination and reclassification analyses we estimated risk at 8 years. We examined the incremental utility of each of the tested features of familial AF by assessing discrimination using the c-statistic for time-to-event data,21 and reclassification of predicted AF risk with integrated discrimination and net reclassification improvement indices.22 We used risk thresholds of <5%, 5–10%, >10%11 for the net reclassification improvement index. We also assessed category-less net reclassification improvement, which assesses any upward or downward reclassification; values >0 correspond to improved reclassification (eMethods).23 The a priori significance threshold was P<.05 using two-sided tests. Model calibration was assessed with the Hosmer-Lemeshow chi-squared statistic. Statistical analyses were performed using SAS version 9.2.15

RESULTS

Eight-year windows from 4455 participants were pooled. After excluding 156 baseline examinations with incomplete covariate data, 4421 participants and 11,971 baseline examinations remained for analysis. The average age at examination was 53.9±13.3 years and 54% were female participants (Table 1). AF developed in 440 participants during eight-year follow-up windows.

Table 1
Characteristics of participants at the 11971 baseline examinations included in the analysis.a

The number of first-degree relatives per participant varied from one to ten (median three). Familial AF occurred in 1185 participants (26.8%) and premature familial AF occurred in 351 (7.9%) participants. Of the 2393 baseline examinations at which familial AF was present, sources included fathers (n=1163), mothers (n=1068), and siblings (n=404). The sum exceeds the number of participants with familial AF because multiple affected relatives could contribute to familial AF in any given individual. Among participants with familial AF, the number of affected relatives ranged from one to five (median one). Approximately 98% of participants with familial AF had two or fewer affected relatives.

Association between familial AF and incident AF

The cumulative incidence of AF according to the presence of familial AF accounting for competing risk is plotted in Figure 1. The unadjusted absolute event rates among participants with and without familial AF were 5.8% (139 events out of 2393 person-examinations) and 3.1% (301 events out of 9578 person-examinations), respectively. Familial AF was associated with new-onset AF in age- and sex-adjusted models (HR 1.39; 95% confidence interval [CI], 1.12–1.73; P=.003), and remained associated after multivariable-adjustment (HR 1.40; 95% CI, 1.13–1.74; P=.002; Table 2). Removing PR interval from the model, a variable that is genetically-related to AF24,25 and that may not always be available in the clinical setting, did not substantively alter the association for familial AF (Table 2). Similarly, the effect estimate for familial AF was not materially altered when the original AF risk prediction model and coefficients11 were used or when diabetes mellitus, another heritable condition26 associated with AF,27,28 was included in the model (eTable 1).

Figure 1
Cumulative AF incidence by presence or absence of antecedent AF in a first-degree relative accounting for competing risk of death.
Table 2
Association between first-degree familial AF and incident AF.a

AF risk was associated with increasing number of affected first-degree relatives (HR 1.24; 95% CI, 1.05–1.46 per affected member, Table 2). The association was not substantially affected by adjustment for family size (eTable 2).

Effect estimates for familial AF were similar in subsets of participants with parent(s) only, sibling(s) only, and both parent(s) and sibling(s) in the study; little heterogeneity was seen in the risk conferred by familial AF across sources (eTable 3). Sibling AF was associated with AF after adjusting for maternal and paternal AF (HR 1.39; 95% CI, 1.02–1.91; P=.04). We did not observe a difference in AF risk according to familial relationship when maternal, paternal, and sibling AF were included in the same model (HR 1.37; 1.15 and 1.39 respectively, χ2 = 0.66, 2df, P=.72).

Relations of participant age and familial age of AF onset

The risk of new-onset AF associated with familial AF may vary in a non-linear fashion with increasing participant age at examination (Figure 2A). The relations between familial age of AF onset and AF risk are displayed in Figure 2B. Among participants with familial AF, we observed a log-linear increase in AF risk as the age of the youngest affected relative decreased (HR for each decreasing decade of age 1.32, 95% CI 1.12–1.56, P<.001).

Figure 2
Association between familial AF and AF risk according to participant age or familial age of AF onset.

Adjustment for genetic AF susceptibility loci

In a subset of 2861 previously genotyped participants, familial AF was associated with increased risk of AF similar to that observed in the full sample, with unadjusted absolute event rates of 5.8% (116 events out of 2005 person-examinations) and 2.3% (207 out of 7168 person-examinations) for those with and without familial AF, respectively (multivariable-adjusted HR 1.43; 95% CI, 1.13–1.83; P=.003). After further adjustment for genotypes of four SNPs tagging AF susceptibility loci, the effect estimate for familial AF remained essentially unchanged (HR 1.38; 95% CI, 1.08–1.75; P=.01; eTable 4).

Incremental utility of familial AF for AF risk prediction

Each of the assessed features of familial AF improved model fit beyond traditional risk factors alone (Table 3). The c-statistic indicated slightly improved discrimination with each familial AF feature. The largest improvement was observed with premature familial AF (0.842; 95% CI, 0.826–0.858 to 0.846; 95%CI, 0.831–0.862; P=.004).

Table 3
Models assessed for discrimination and risk reclassification.

Integrated discrimination improvement estimates were similar for each familial AF feature, though the standard errors, and hence, P values differed (Table 3). The relative integrated discrimination improvement values (1.0–2.1%) indicate weaker performance of each familial AF feature than the average of variables already in the model.

Net reclassification improvement using eight-year risk thresholds of <5%, 5–10%, and >10% was not enhanced by familial AF (premature familial AF 0.011; 95% CI, −0.021–0.042; P=.51; any familial AF −0.029; 95% CI, −0.057– −0.000; P=.05; Table 3 and eTable 5). Notably, only 12% of our sample had predicted eight-year risks that exceeded 10%. In contrast, category-less net reclassification improvement indicated weak to moderate improvement in risk reclassification with premature familial (0.127; 95% CI, 0.064–0.189; P=.009) and any familial AF (0.253; 95% CI, 0.164–0.341; P<.001). The significant improvement in category-less net reclassification was driven by the downward classification of non-events (proportion correctly classified down = 94% for premature and 80% for any familial AF).

The Hosmer-Lemeshow statistic indicated adequate calibration between observed and predicted AF risk in models without (X2=14.9, 9 df; P=.11) and with familial AF (X2=16.1, 9 df; P=.08).

DISCUSSION

We report an association between the occurrence of AF in a first-degree relative and AF risk in 4,421 individuals of European descent. Familial AF was associated with AF after multivariable adjustment for commonly accepted AF risk factors, including genetic variants at AF susceptibility loci. Consideration of familial AF, particularly when premature in onset, slightly improved prediction of new-onset AF beyond conventional AF risk factors.

Our findings support and extend previous reports of AF heritability.16 The observation that AF risk is inversely related to the age at which a first-degree relative develops AF is consistent with reports of an increased risk of AF in individuals with relatives affected before the age of 602 or parents before age 75 years.1 We further demonstrate that the estimated hazard of AF diminishes log-linearly with increasing age of an affected family member. We also found that AF risk is associated with an increasing number of affected first-degree relatives. Sibling AF conferred a similar magnitude of risk as parental AF and was informative even after considering parental AF status, similar to observations of risk in cardiovascular disease.29

Unexpectedly, the magnitude of risk associated with familial AF varied by participant age in a nonlinear fashion. Our precision to determine the nature of the relation was limited owing to the small number of person-examinations and events in each stratum of participant age. Future investigation of the observed U-shaped relation between an individual’s age and the association between familial AF and AF risk will require larger samples.

The estimated 40% increase in the hazard for new-onset AF associated with familial AF was not attenuated by adjustment for traditional AF risk factors or genetic variants at AF susceptibility loci, demonstrating that risk associated with familial AF was not substantially mediated by known risk factors in our sample. The concept of “missing heritability” has received much attention in the current era of genome-wide association studies.30 Our results justify future efforts to identify novel genetic variants, unmeasured environmental factors, as well as potential joint effects of genetic and environmental factors involved in the pathogenesis of AF.

We demonstrated that consideration of easily ascertained clinical factors at the bedside results in excellent discrimination of AF risk. Familial AF improves discrimination, particularly when familial AF is premature or when familial age of AF onset is taken into account. Premature familial AF discriminates AF risk better than considering any occurrence of familial AF, perhaps because premature AF is a less heterogeneous disorder. The small magnitude of improvement in discrimination attributable to various familial AF variables is consistent with reports in which family history was examined in the context of cardiovascular disease,31,32 and reflects the difficulty of assessing novel risk factors for incremental benefit beyond established risk factors.

The absence of significant benefit with the category-based net reclassification improvement may have arisen because few participants in our sample were in the highest category of predicted AF risk, and because clinically meaningful risk thresholds for AF are uncertain. The fact that category-less net reclassification improvement with premature familial AF was driven by correct downward classification of individuals that did not develop AF may provide reassurance to patients without familial AF. Generally, the small magnitude of improvement in the c-statistic, integrated discrimination improvement, and category-less net reclassification improvement indices with each of the assessed features of familial AF suggest that meaningful enhancement of AF prediction beyond traditional risk factors by considering familial AF may require large samples. Assessment of familial AF in larger samples might lead to improved prediction of AF risk in more individuals in absolute terms, but may not be expected to enhance the magnitudes of effect we observed in our sample.

Our selected age threshold of ≤65 years may not be the optimal cutoff for defining premature familial AF, and the number of participants with premature familial AF was limited. We submit that a systematic analysis of various definitions of premature familial AF based on different age thresholds, and potential variation by sex, is warranted in larger samples. Indeed, the association between parental myocardial infarction and offspring cardiovascular disease risk has been shown to differ according to parental age and sex.33

Strengths and Limitations

Strengths of our study include the multi-generational nature of the Framingham Heart Study, which allowed us to examine documented and adjudicated occurrences of AF within families. In contrast, self-reported AF or family history of AF would likely result in less robust results because of the inherent inaccuracy of such information. Other strengths include that physicians without knowledge of familial occurrence status adjudicated AF events, and risk factors were systematically and routinely ascertained.

Our study has several limitations. First, our analysis was limited to a single sample of European ancestry and the results may not be generalizable to other populations. Second, not all family members participated in the Framingham Heart Study. Such family members were not included in our analysis and may bias our results. However, we assume that nonparticipation is random and unlikely to result in meaningful bias. Third, we acknowledge that there may be other genetic susceptibility loci for AF that mediate the risk conferred by familial AF.24,25 We included only replicated loci that were beyond genome-wide significance. Fourth, we had low power to detect differences in the magnitude of risk conferred by maternal and paternal AF. Larger samples will be necessary to examine whether these associations differ, and perhaps whether specific parent-of-origin allelic effects modify associations between genetic variants and AF. Fifth, the occurrence of AF beyond first-degree relatives is associated with AF risk2,4 and may be clinically informative. However, we submit that ascertainment of first-degree rather than extended family history information is most practical in the clinical setting. Sixth, although our risk model included systolic blood pressure and treatment for hypertension, it is not clear to what extent successful treatment of blood pressure during follow-up may impact AF risk. Moreover, whereas heart murmur was ascertained routinely at Framingham Heart Study examinations, we have insufficient echocardiographic data in our sample to determine the impact of echocardiographic valvular disease on the risk of familial AF, or to compare the reliability of heart murmur with echocardiography.

Conclusions

The occurrence of AF in first-degree relatives was associated with AF risk after adjustment for established AF risk factors and AF-related genetic variants. Assessment of familial AF enhanced risk prediction slightly beyond traditional risk factors, particularly when familial AF occurred prematurely. Future efforts should attempt to discern the factors that mediate the association between familial AF and AF risk, further explore the relations between premature familial AF and risk prediction, and determine whether incorporating genetic variants into an AF prediction model enhances its performance.

Supplementary Material

Supplemental materials

Acknowledgments

Funding support:

Dr. Lubitz is supported by an NIH training grant in the Epidemiology of Cardiovascular Disease (T32HL007575). Dr. Magnani is supported by AHA grant 09FTF2190028. Dr. Rienstra is supported by a Rubicon grant from the Netherlands Organization for Scientific Research (825.09.020). This work was supported by grants from the NIH to Drs. Benjamin and Ellinor (HL092577), Dr. Benjamin (RO1AG028321, RC1-HL01056, 1R01HL102214) and Dr. Ellinor (DA027021, HL104156).

Role of the sponsors: The sponsors did not have any input into the study design or conduct; data collection, management, analysis, or interpretation; nor did they influence the preparation, review, or approval of the manuscript.

Footnotes

Financial disclosures: None.

Author contributions:

EJB had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design: Lubitz, Yin, Fontes, Larson, Ellinor, Benjamin

Acquisition of data: Lubitz, Yin, Fontes, Magnani, Pai, Villalon, Vasan, Levy, Larson, Benjamin

Interpretation of data: Lubitz, Yin, Fontes, Magnani, Rienstra, Vasan, Pencina, Levy, Larson, Ellinor, Benjamin

Drafting of the manuscript: Lubitz, Yin, Larson, Ellinor, Benjamin

Critical revision of the manuscript for important intellectual content: Lubitz, Yin, Fontes, Magnani, Rienstra, Pai, Villalon, Vasan, Pencina, Levy, Larson, Ellinor, Benjamin

Statistical analysis: Lubitz, Yin, Pencina, Larson

Obtaining funding: Levy, Larson, Benjamin

Supervision: Levy, Ellinor, Benjamin

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