Predicting risk for incident HF with Omega-3 Fatty Acids: from MESA

Abstract

Background:

Clinical trials suggest omega-3 polyunsatured fatty acids (ω3 PUFAs) prevent sudden death in coronary heart disease (CHD) and heart failure (HF), but this is controversial. In mice, we demonstrated that the ω3 PUFA, eicosapentaenoic acid (EPA), prevents contractile dysfunction and fibrosis in a HF model, but whether this extends to humans is unclear.

Objective:

To determine if plasma EPA abundance (%EPA) is associated with reduced hazards for primary HF events in the Multi-Ethnic Study of Atherosclerosis (MESA) trial.

Methods:

In the MESA cohort, we tested if plasma phospholipid EPA predicts primary HF incidence including, HF with reduced ejection fraction (HFrEF; EF<45%), and HF with preserved ejection fraction (HFpEF, EF≥ 45%) using Cox proportional hazards modeling.

Results:

6,562 participants aged 45–84 years had EPA measured at baseline (1794 black, 794 Chinese, 1442 Hispanic, and 2532 white; 52% female). Over a median follow-up of 13.0 years, 292 HF events occurred; 128 HFrEF, 110 HFpEF, and 54 with unknown EF status. Percent EPA in HF-free participants was 0.76% (0.75, 0.77), but lower in HF participants 0.69% (0.64, 0.74), P=0.005. Log-%EPA was associated with lower HF incidence; hazard ratio 0.73 (0.60, 0.91) per log-unit difference in %EPA, P=0.001. Adjusting for age, sex, race, BMI, smoking, diabetes mellitus, blood pressure, lipids and lipid-lowering drugs, albuminuria, and the lead FA for each cluster did not change this relationship. Sensitivity analyses showed no dependence on HF type.

Conclusions:

Higher plasma EPA was significantly associated with reduced risk for HF, both HFrEF and HFpEF.

INTRODUCTION

Heart failure (HF) is a leading cause of hospitalization in the United States (1). Its incidence increases with age, and is higher in men than women (2,3). Currenly, 26 million individuals globally suffer from HF, with >1 million annual hospitalizations in the United States and Europe, accounting for 1–2% of total health expenditures (4,5).

Clinically, HF manifests in two modes defined by ventricular function; reduced ejection fraction, ≤ 45%, (HFrEF), or preserved ejection fraction, >45%, (HFpEF) (6). Half of all current diagnoses are HFpEF (7), and HFpEF incidence rate has surpassed HFrEF (8). The survival for HFpEF is marginally higher than HFrEF, but is only 35% at 5-years (6,9). Generally, patients with HFpEF are older, female, and more likely to have hypertension, renal disease, atrial fibrillation, and/or pulmonary disease (10). Unfortunately, standard pharmacologic therapies for HFrEF show no efficacy in HFpEF (6).

In humans, the omega-3 polyunsatureated fatty acids (ω3 PUFAs) eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are important regulators of cardiovascular health (11–13). Several clinical trials have demonstrated that ω3-PUFAs confer a survival benefit in CHD by preventing sudden death (14–18), and clinical trials have indicated ω3-PUFAs might improve outcomes in HF (19–23). Despite these potential benefits, the use of ω3-PUFAs in CHD and HF remains controversial. A recent meta-analysis involving over 77,000 participants reported no evidence supporting supplemental ω3-PUFAs in CHD (24) but did not evaluate either HF as an endpoint or studies using doses sufficient to achieve protective concentrations in animals (25) or humans (26,27).

We have shown that dietary ω3-PUFAs at supra-physiologic levels preserves left ventricular function and prevent interstitial fibrosis in a mouse model of pressure overload induced heart failure (28). Follow-up with a diet designed to achieve ω3-PUFA levels closer to those achieved in patients treated with high dose prescription omega-3 acid ethyl esters showed only EPA was protective (13,25).

The Multi-Ethnic Study of Atherosclerosis (MESA) is a longitudinal cohort study of adults who are African-American, Hispanic, Asian, and whites in the United States. Due to its population, baseline plasma phospholipid fatty acid measurements, and HF outcomes, we used this cohort to determine whether higher levels of EPA predict reduced risk for HF. Our goal was to test the hypotheses: 1) in humans, plasma %EPA is inversely associated with all HF incidence; 2) high plasma %EPA is inversely associated with incidence of HFpEF; 3) the inverse association of high plasma %EPA with HF incidence is unique among ω3-PUFAs.

METHODS

Study Participants

MESA is a prospective, population-based study designed to investigate the prevalence, risk factors, and progression of subclinical cardiovascular disease in a multi-ethnic cohort in the United States (29,30). Its study design, population, and methods have been described (29). Between July 2000 and July 2002, 6,814 participants aged 45–84 years were recruited from 6 U.S. communities. The MESA study was approved by the institutional review board from all participating study sites. All participants gave informed consent.

Plasma Fatty Acid Measurements

Fasting blood was drawn, and serum and EDTA-anticoagulant tubes were collected and processed at the first (baseline) study visit using a standardized protocol as previously described (31).

HF Events

Participants completed study visits approximately every other year after the baseline examination (32,33). HF events were adjudicated by physicians based on medical records (34). We used EF reported in the hospital record to define HFrEF < 45% vs. HFpEF ≥ 45%.

Statistical Analyses

Descriptive statistics were used to compare the baseline characteristics of participants (Table 1). All covariates were measuerd at the baseline visit. Only the first HF event was accounted for in our analyses and each person’s data were only included once. Four ejection fraction status groups exist in the MESA dataset: 1) people free of heart failure during the study; 2) HFrEF ; 3) HFpEF ; and 4) patients with heart failure but unmeasured ejection fraction (HF_unk). For continuous variable comparisons, the two-sample t-test was used. For categorical variables, χ2 test was used (Supplemental Table 1). Statistical significance was defined as α<0.05.

Table 1.

Descriptive Statistics Of Demographic Variables By Heart Failure (HF) Status

		No HFa (N=6270)	All HF (N=292)	HF Subtypes Defined By Ejection Fraction Status
Variable, Mean (SD) or %				HFrEF (N=128)	HFpEF (N=110)	HFunk (N=54)
Age (years)		62 (1O)	69 (9)*	67 (9)*	69 (8)*	70 (9)*
BMI (kg/m 2 )		28.3 (5.4)	29.8 (5.9)*	29.4 (5.4)*	29.6 (5.6)*	31.0 (7.4)*
LDL Cholesterol (mg/dL)		117 (31)	114 (33)	114 (34)	112 (31)	114 (33)
Non-HDL Cholesterol (mg/dL)		143 (35.88)	141 (36)	142 (37)	139 (35)	142 (34)
HDL Cholesterol (mg/dL)		51.1 (14.9)	48.6 (13.9)*	47.6 (12.8)*	49.9 (14.1)	48.6 (15.8)
Triglycerides (mg/dL)		131 (88)	142 (113)	136 (78)	146 (154)	145 (84)
eGFR (ml/min/1.73 m2)		78.4 (16.1)	71.9 (18.5)*	71.4 (18.2)*	72.6 (18.4)*	71.7 (19.3)*
Gender	Male %	46.6	58.9*	69.5*	49.1	53.7
Site	WFU%	15.4	24.0	20.3	30.9	18.5
	COL%	16.0	17.5	17.2	16.4	20.4
	JHU%	15.7	12.0	13.3	8.2	16.7
	UMN%	15.7	18.5	21.9	18.2	11.1
	NWU%	17.5	12.7	14.8	10.9	11.1
	UCLA%	19.7	15.4	12.5	15.5	22.2
Race /Ethnicity	White %	38.5	39.7	37.5	46.4	31.5
Chinese American %		12.3	7.2	3.1	10.9	9.3
	Black %	27.1	31.9	39.8	22.7	31.5
	Hispanic %	22.0	21.2	19.5	20.0	27.8
Hypertension	Yes %	43.5	70.6*	68.0*	72.7*	72.2*
ACE Inhibitor	Yes %	12.2	29.2*	25.8*	32.1*	31.5*
Alpha Blocker	Yes %	3.8	6.2	7.8*	4.6	5.6
Beta Blocker	Yes %	9.4	13.1	12.5	13.8	13
Loop Diuretic	Yes %	1.7	6.9*	7.0*	4.6*	11.1*
Any Lipid Lowering		16	18.6	21.9	15.6	16.7
Medication	Yes %
Statin Medication	Yes%	14.7	17.8	20.3	14.6	18.5
Urine: albuminuria		91.2	72.7*	72.4*	72.5*	73.6*
Normal %
Microalbuminuria %		7.6	20.4	22.1	19.3	18.9
Macroalbuminuria %		1.2	6.9	5.5	8.3	7.6
Smoking Status		90.4	90.2	83.6*	90	88.9
Never %
	Former %	7.3	7.4	11.7	5.5	9.3
Current %		1.8	1.9	3.9	4.6	1.9
Diabetes		74.5	57.9*	60.9*	54.6*	57.4*
Normal %
Impaired Fasting Glycemia %		13.9	13.4	14.8	14.6	7.4
Untreated Diabetes %		2.5	5.1	4.7	4.6	7.4
Treated Diabetes %		9.1	23.6	19.5	26.4	27.8
EPA (mass%)		0.76 (0.75, 0.77)	0.69 (0.64, 0.74)*	0.68 (0.61, 0.76)*	0.69 (0.61, 0.76)	0.71 (0.60, 0.84)
DHA (mass%)		3.75 (3.71, 3.78)	3.50 (3.35, 3.66)*	3.45 (3.21, 3.70)*	3.44 (3.21, 3.69)*	3.76 (3.39, 4.17)
EPA+DHA (mass%)		4.58 (4.54, 4.63)	4.25 (4.06, 4.45)*	4.18 (3.89, 4.5)*	4.19 (3.9, 4.5)*	4.54 (4.08, 5.05)

Note:

No HF^a : free from heart failure

HF_unk : heart failure with ejection fraction unmeasured

An * indicates a statistically significant (p<0.05) difference between the category and those in the No HF group

Some values of heptadecanoic acid were non-physiologic (>1.0%) and likely resulted from methylation artifacts. Fatty acids were log-transformed to improve normality and clustered to identify groups of fatty acids with high collinearity. For adjustors, the fatty acid with the largest within-cluster correlation was identified as the “lead” fatty acid and used as an adjustor (Supplemental Table 2). This approach maximized independence and interpretability. %EPA was the lead member of a cluster of three PUFAs that also included DHA and ω3 DPA.

Participants who did not develop HF were censored at the last attended follow-up examination. Cox proportional hazard modeling was used to estimate hazard ratios (HRs) associated with continuous plasma phospholipid %EPA on log scale. We developed hazard models in blocks by including: %EPA first, as a univariate predictor; second, after adjustment for age, sex, race, and study center; third, after adjusting for other lead FAs; and fourth, after full adjustment for all factors considered, including BMI, blood pressure (systolic), pulse pressure, heart rate, fasting glucose, non-HDL-cholesterol, fasting triglycerides, diabetes mellitus status, use of hypertension medication, use of oral hypoglycemic medication, smoking status, and albuminuria status. In the final two blocks, we employed backward stepwise elimination, using the likelihood ratio method. Assumptions for proportional hazard were confirmed using time-dependent covariates approach. Consideration was given to the pattern of missing values when deciding which adjustors would be used in the models. We conducted subgroup analyses on outcomes by evaluating when only HFpEF or only HFrEF participants were included. Statistical analyses were conducted using SAS version 9.4, SPSS v24, and JMP 13.2.1.

RESULTS

Participant Baseline Demographics

The inclusion and exclusion of study participants for our analysis is outlined in Figure 1. Of the 6,814 total MESA participants, 6,562 (96%) were included. During a median follow-up of 4,774 days (13.0 years), 292 participants had a positive HF evaluation, including 128 with HFrEF, 110 with HFpEF, and 54 participants with unknown EF status (HF_unk). Baseline descriptive characteristics for each group are reported in Table 1. Details of post-hoc tests are in Supplemental Table 1, and details for differneces among ethnic groups are in Supplemental Table 2. HF-free participants had higher baseline plasma phospholipid %EPA, %DHA, and %EPA+ %DHA. Age, body mass index (BMI), diabetes mellitus, glomerular filtration rate (eGFR), hypertension (HTN), taking a loop diuretic, urine microalbuminuria, and taking an ACE inhibitor were different (p<0.05) between HF-free versus HF participants.

Figure 1:

Derivation of the data analysis cohort after using exclusion criteria.

Participant Plasma Phospholipid EPA Levels

We first evaluated the distribution of %EPA (Figure 2A and Supplemental Table 3). Median %EPA was 0.70% for all MESA participants. Participant %EPA status was defined as insufficient (<1.0%), marginal (1.0%≤ level ≤2.5%), or sufficient (>2.5%) to prevent HF based on prior definition of EPA levels that prevent HF in animal models (13); 73.1% of participants had insufficient plasma EPA, 2.4% had marginal levels, and 4.5% had sufficient levels (Figure 2A). Hispanic participants had the lowest %EPA levels with only 1.4% having sufficient EPA (Figure 2B), followed by blacks (4.4%), white (4.9%), and finally Chinese participants (9.8%). Variance among Chinese participants was greater than the other three races, which were each nearly identical. We evaluated the distribution of other PUFAs (Supplemental Figure 1). Plasma %EPA was highly skewed, %ω3 DPA and %DHA were moderately skewed, and %AA was least skewed; all fit better to a log-normal distribution than a normal distribution (Supplemental Table 3).

Figure 2:

The distribution of %EPA among MESA participants and their grouping by EPA sufficiency based on Eclov et al. (25). Top: Total population. Bottom: by race/ethnicity. See Supplemental Figure 1 for distributions of other ω3-PUFAs.

Fatty Acid Clustering

Twenty-five FAs were measured in all participants. Strong collinearities existed among %fatty acids, making it difficult to distinguish between direct and replacement effects on FA levels. Plasma %EPA and %DHA were strongly correlated since they co-occur in food products; both typically replace other PUFAs such as AA, hence increased %EPA can also report the replacement of AA. Eight FA clusters were identified (Supplemental Table 4), explaining 63% of the total variability. The marine ω3-PUFAs clustered together with EPA as the most representative. The remaining PUFAs clustered together with AA as the lead PUFA. Lead fatty acids in each cluster were used as adjustors in developing hazard models, which allowed us to preserve interpretability and avoid collinearity.

Proportional Hazard Models for EPA and other ω3 PUFAs

We tested for associations of EPA with HF risk using a four step approach: 1) testing a univariate association; 2) adjusting for age, sex, race, and study center; 3) adjusting for other lead fatty acids; and 4) adjusting for other known risk factors. This approach allowed us to evaluate the independence and robustness of associations. At each step we performed sensitivity analyses in which we included only participants with HFrEF or HFpEF in order to evaluate the associations by HF type. In step 1, high plasma phospholipid %EPA at visit 1 was associated with reduced HF risk, regardless of HF type. Figure 3A shows the HR [95%CIs] from proportional hazard models for log%EPA with each successive adjustment block. Sensitivity analyses demonstrated that the association was not dependent on HF type. For step 2, we adjsuted for age, sex, race, and study center. %EPA remained significantly associated with risk without any change in the strength of association indicating that age, sex, race, and study center did not mediate the association. Each successive model included these adjustors. In step 3, fatty acid cluster leads were entered and backwards stepwise selection eliminated those unrelated to risk. Only %behenic-acid was selected, but it did not change the association of %EPA. In step 4, all other HF-related adjustors were entered into the model and subjected to backwards selection: BMI, heart rate, fasting glucose, use of hypertensive medication, smoking status, pulse pressure, and urinary albuminuria status were selected; systolic blood pressure, non-HDL cholesterol, log-triglycerides, and diabetes mellitus status were not selected. The final, adjusted HR was a 0.73 (0.60, 0.91), P=0.004 fold reduction in risk per unit increase in log(%EPA), which was not dependent on HF type. In summary, %EPA was inversely related to HF risk, the relationship was robust and independent to adjustment, and this association was present among all participants including HFrEF and HFpEF participants (see Suppplemental Table 5).

Figure 3: Hazard Ratios for %EPA and other marine ω3-PUFAs by adjustment and sensitivity.

The HR [mean, 95% CI] for models of %EPA (A), %DHA (B), %ω3 DPA (C), and %EPA+%DHA (D) with successive blocks of adjustments are shown in bold along compared with sensitivity analyses including HFpEF (dark square) or HFrEF (light square) participants. ASRC: age, sex, race, study center. %EPA and ASRC were entered into all models. For FA cluster leads see Supplemental Table 3. Lead FAs were selected backwards using the likelihood ratio method. In the fully adjusted model %EPA, ASRC, and Behenic acid were entered into the model, and remaining adjustors subjected using the same method. See results for adjustors. Supplemental Table 5 lists HRs [95% CIs]. Missing values in some adjustors reduced the number of events.

To evaluate associations with other ω3-PUFAs, we employed the same four step approach as for %EPA, with senstitivity analyses. As univariate predictors, %DHA, and %EPA+%DHA were both associated with reduced risk for HF; %ω3 DPA was not. The HR [95%CIs] and sensitivity analyses for each are shown in Figure 3B-D (also Suppplemental Table 5). After step 2, %ω3 DPA became significant. Adjustment in step 3 again showed only the cluster represented by %behenic-acid was significantly associated but again, the ω3-PUFA HRs were unchanged and independent. Final adjustment not did not substantially alter the HRs, indicating that other %ω3-PUFAs are also significant and independent predictors of HF risk. The final adjusted HR for %DHA was 0.51 (0.38, 0.70), P<0.0001; for %ω3 DPA it was 0.59 (0.37, 0.95), P=0.03; and for %EPA+%DHA it was 0.54 (0.39, 0.73). Across all ω3-PUFAs, sensitivity analyses showed no substantial differences when only HFrEF or only HFpEF participants were included. Because HRs derived from log-transformed predictors are difficult to interpret, Figure 4 plots hazards for all HF relative to median across the entire observed PUFA ranges.

Figure 4: Marine ω3-PUFAs predict hazards for all heart failure.

The relationship between EPA (blue), DHA (purple), ω3 DPA (red), and the %EPA+DHA (yellow) are plotted in relationship to the relative risk (left y-axis) for HF, referencing median values. The PUFA distribution across the participant population is plotted (right y-axis) for comparison. Note axes scales.

DISCUSSION

Here we show in the MESA study that high plasma phospholipid EPA is associated with reduced risk for all HF, including both HFrEF and HFpEF, confirming our primary hypothesis. In addition, we found that high plasma DHA, ω3 DPA, and EPA+DHA are similarly associated indicating that unlike mice, humans may benefit from marine ω3-PUFAs generally. The findings were true in univariate analysis; after adjusting for age, sex, race, and study center; after accounting for replacement effects of other fatty acids; and after further selective adjustment for covariate factors known to predict HF. Finally, the protective associations remained evident after sensitivity analyses in which only HFpEF or only HFrEF participants were included.

Previous clinical trials have demonstrated that combined EPA and DHA administration improve HF outcomes. The Cardiovascular Health Study (CHS), a prospective cohort study from 1992 to 2006 also found an association between plasma phospholipid %EPA and a reduction in incident HF, 50% lower in the highest versus the lowest quartile (18). In our analysis, we estimated a more modest contrast, likely reflective of other care-related improvements since the CHS report.

In GISSI-HF, low-dose ω3-PUFAs (0.84 g/day) reduced hazards for total mortality (0.91 (0.83–0.99) and HF hospitalizations when added to standard therapy (35). Red blood cell EPA+DHA was measured in a subset of participants, and found an increase from 4.8% to 6.7% (36), indicating the participants did not achieve the proposed cardioprotective level of 8.0% (37,38). The final erythrocyte EPA was 1.2%, corresponding to 0.9% plasma phospholipid EPA (39), indicating that the dose did not achieved sufficient levels. In another smaller HF trial in patients with LV insufficiency, combined EPA+DHA (1.7 g/d) improved systolic and diastolic dysfunction (20). We estimate the dose would increase red blood cell %EPA+%DHA from the Italian average of 4.7% (40) to 6.7% in three months, again still not reaching optimal levels. Furthermore in OMEGA-REMODEL high dose ω3-PUFA therapy (3.4 g/day) for 6 months post-myocardial infarction reduced infarct size, improved ventricular systolic function, and reduced non-infarct myocardial fibrosis (26). Treatment increased the %EPA+%DHA, from 5.5±1.8 to approximately 10%. A number of smaller studies also show ω3-PUFA therapy improves systolic and diastolic function (21,22). In each study, the beneficial effects of ω3-PUFAs were observed in patients with HFrEF. Therefore, evidence from one major heart failure trial (GISSI-HF), several smaller trials, and one trial examining post MI remodeling all suggest that ω3 PUFAs prevent HF even when optimal tissue enrichment is not acheived.

We found high plasma EPA is associated with reduced risk for HFpEF, a condition for which there are currently no FDA-approved therapies which reduce mortality or hospitalizations. Our prior studies in mice indicated a concentration-dependent effect for EPA to prevent pathologic remodeling, preserving diastolic function and preventing interstitial fibrosis, in a pressure-overload model of HF that resembles HFpEF remodeling (13,25,28). We did not find strong evidence for the EPA cardioprotective threshold that exists in animals, but only 301 participants had %EPA levels with minimal sufficiency or greater (>2.5%), with only 6 HF events among them. To our knowledge this is the first clinical study to suggest a specific benefit for EPA or ω3 PUFAs in HFpEF.

Recently, the VITAL study reported low-dose ω3 PUFAs failed to prevent composite CV death, nonfatal MI, and stroke over 5-years follow-up; a secondary outcome suggested a reduced risk of MI (41). VITAL was preceded by a meta-analysis suggesting low-dose ω3-PUFAs does not prevent CHD (24). Neither study directly reported heart failure outcomes. These results stand in contrast to results from the REDUCE-IT trial, which demonstrated that high-dose icosapent ethyl (an EPA precursor) at 4 g/d produced a 25% reduction in the risk for composite CV death, non-fatal MI, nonfatal stroke, coronary revascularization, and unstable angina (27). These results are supported by OMEGA-REMODEL results, which indicate high-dose ω3-PUFAs (4 g/d) prevent post-MI remodeling (26). Consistently, subjects achieving the highest red blood cell %EPA+%DHA levels were associated with the greatest treatment benefits (26). These newer trials examining the effects of high-dose ω3-PUFA intake suggest a concentraction-dependent cardioprotective effect as previously suggested (13). REDUCE-IT reported no difference in HF incidence (4.1% placebo vs 4.3% EPA) (27), however the HF incidence was modest and could not exclude an large range of effects ( +17% risk to −23%). MESA had a broader age range, a longer follow-up, and broader diversity. Furthermore, REDUCE-IT included only hypertriglyceridemic subjects on statin therapy, with known cardiovascular disease or equivalents (27).

The overall HF rate observed in MESA was similar to other observational cohorts. HF occured in 4.4 percent of PREVEND participants during a median of 11.5 years (42), similar to 4.5% incidence in 13 years for MESA. The Physicians’ Health Study I (1982–2008) reported a lifetime HF risk of 13.8% over a much longer 22.4 years (43).

Clinical Implications:

We propose three clinical implications for our findings. 1) based on prior work in animals and related findings in humans, it is reasonable to expect this finding translates to ω3-PUFA intervention. In the interventional setting each unit change in log-%DHA would yield a greater risk-reduction than each unit change in log-%EPA, however this does not take into account that in the typical interventional setting, each g/d of EPA proportionally increases %EPA more than each g/d of DHA increases %DHA. Each g/d of DHA increases the absolute erythrocyte %DHA more than EPA raises %EPA. However, when considered on the proportional, or log-scale, each g/d of EPA is more effective than each g/d of DHA is (44). The latter expectation conforms better to our analysis, however more studies are required to determine which, if any, ω3-PUFA is superior. 2) HF patients, regardless of EF status would benefit from safe, effective therapies, with no adverse interactions with current medications and ω3 PUFAs appear to meet these criteria (45). 3) The differences among ethnicities in ω3 PUFAs could explain a component of HF health disparities (46).

Strengths and limitations:

Strengths of this study include large sample size, ethnic diversity, long duration of follow-up, modern medical therapy and accounting for the competing effects of other fatty acids. No published articles exist in which a clinical trial of ω3-PUFAs in primary prevention of HF incidence has occurred (47) making this observation relevant. Limitations include a population with few patients having HFpEF and few participants with protective levels of EPA, by our animal models. In addition, only baseline data were available and we could not account for changes in ω3-PUFAs and other risk factors. We consider this study to strongly determine a benefit of EPA exists, but insufficient to determine whether a threshold for %EPA exists near 3%. In our discussion, we used red blood cell and plasma phospholipid abundance somewhat interchangeably. The analytical answers are valid, but the enrichment of red blood cells is 0.71-fold lower for EPA and 1.13-fold higher for DHA (39).

Conclusion:

We show here that plasma phospholipid %EPA is inversely associated with all HF incidence, both HFpEF and HFrEF. In contrast to findings in animals, the inverse association was also found for other ω3-PUFAs and was strongest for the combined %EPA+%DHA.

Central Illustration: Eiscosapentaenoic acid predict hazards for all heart failure.

EPA as a precent total plasma phospholipid fatty acids is plotted in relationship to relative risk for HF (left y-axis), referencing media %EPA. The PUFA distribution across the participant population is plotted (right y-axis) for comparison.

CLINICAL PERSPECTIVES.

Competency in Medical Knowledge:

This study is the first to determine the ability of plasma phospholipid %EPA to predict heart failure outcomes in white, African-American, Asian and Hispanic populations.

Competency in Patient Care:

Given that plasma %EPA can be increased by the ingestion of seafood or fish oil capsules while being safe and relatively inexpensive; this prevention measure is limited in the response it produces, but is quite feasible.

Translational Outlook 1:

The study provides evidence for measuring plasma phospholipid ω3-PUFAs as an approach to estimating HF risk in adults.

Translational Outlook 2:

A follow-up study should be considered that includes participants with higher levels of %EPA. Such a study would be better powered to detect a threshold for protective effect at high (%EPA > 4.0%) levels.

Translational Outlook 3:

An interventional study should be considered that includes a dose of EPA or EPA derivative capable of increasing %EPA from 0.70% to >4.0%.