Pericardial fat is a localized fat depot associated with coronary artery calcium and myocardial infarction. We hypothesized that genetic loci would be associated with pericardial fat independent of other body fat depots. Pericardial fat was quantified in 5,487 individuals of European ancestry from the Framingham Heart Study (FHS) and the Multi-Ethnic Study of Atherosclerosis (MESA). Genotyping was performed using standard arrays and imputed to ∼2. 5 million Hapmap SNPs. Each study performed a genome-wide association analysis of pericardial fat adjusted for age, sex, weight, and height. A weighted z-score meta-analysis was conducted, and validation was obtained in an additional 3,602 multi-ethnic individuals from the MESA study. We identified a genome-wide significant signal in our primary meta-analysis at rs10198628 near TRIB2 (MAF 0. 49, p = 2. 7×10-08). This SNP was not associated with visceral fat (p = 0. 17) or body mass index (p = 0. 38), although we observed direction-consistent, nominal significance with visceral fat adjusted for BMI (p = 0. 01) in the Framingham Heart Study. Our findings were robust among African ancestry (n = 1,442, p = 0. 001), Hispanic (n = 1,399, p = 0. 004), and Chinese (n = 761, p = 0. 007) participants from the MESA study, with a combined p-value of 5. 4E-14. We observed TRIB2 gene expression in the pericardial fat of mice. rs10198628 near TRIB2 is associated with pericardial fat but not measures of generalized or visceral adiposity, reinforcing the concept that there are unique genetic underpinnings to ectopic fat distribution.
Obesity is a heterogeneous condition, and its attendant metabolic sequelae may not be adequately captured by using traditional metrics of generalized adiposity [1]. In part, this is because different fat depots may be associated with differential metabolic risk. For example, visceral abdominal fat is thought to be a unique pathogenic fat depot [2], [3]. Ectopic fat depots, defined as fat depots in non-classical locations [4], may mediate vascular disease due to their local toxic effect on nearby anatomic structures. We and others have shown that pericardial fat, defined as fat surrounding the heart and attendant structures, but not visceral fat, is associated with coronary artery calcification and coronary heart disease [5], [6]. The hypothesized local toxic effect of pericardial fat is supported by experimental research demonstrating perivascular inflammation [7] and smooth muscle cell proliferation [8]. Prior studies have shown that measures of generalized adiposity, including body mass index, are heritable [9]. In addition, more recent work has demonstrated that markers of body fat distribution, including waist-hip-ratio [10], subcutaneous and abdominal visceral fat [3], and fatty liver [11] also have a heritable component. Recent large scale genome-wide association studies (GWAS) have identified genomic loci for indices of body fat distribution that are independent of BMI [11]–[13], further supporting the concept that unique genetic variants exist that are associated with ectopic fat depots. To explore this further, we conducted a GWAS of pericardial fat to determine whether genetic loci are associated with the propensity to store fat around the heart.
The study sample characteristics are shown in Table 1 and Table S1. The mean age ranged from 55 years in the Framingham Heart Study to 62 years in MESA. In the MESA cohort, mean pericardial fat differed significantly between race/ethnicity groups. Compared to European Americans, mean pericardial fat was significantly lower in African Americans (P = 1. 1E-38) and Chinese Americans (P = 4. 8E-11), and was higher in Hispanic Americans (p = 0. 02). The heritability (h2) of pericardial fat in the Framingham Heart Study was 50%. Upon additional adjustment for height and weight, the h2 was 52%. We also calculated genetic correlations between pericardial fat, visceral fat (VAT), and BMI in the Framingham Heart Study. Genetic correlations between pericardial fat and VAT were 0. 57; between pericardial fat and BMI 0. 41, and between VAT and BMI 0. 75. In all cases, we confirmed that there are genes that are associated with pair-wise comparisons of all three traits (all p-values<1. 7*10E-15 for overlapping genetic correlations), although our results also suggest that not all genes are shared (all p-values<1. 4*10E-22 for non-overlapping genetic correlations). The quantile-quantile plot (Figure S1) of GWAS of 5487 individuals of European ancestry demonstrated deviation from the null with no evidence of population stratification (lambda 0. 99). The Manhattan plot (Figure S2) shows a genome-wide significant locus on chromosome 2 (p = 2. 7E-08). The lead SNP (MAF 0. 49) is rs10198628 located ∼80 kb upstream from the TRIB2 gene. Per copy of the A allele, pericardial fat volumes were 4. 4 cm3 lower in the Framingham Heart Study and 3. 6 cm3 lower in MESA. All SNPs with p-values<1E-04 are shown in Table S2. We observed no evidence for a sex interaction for rs10198628 (p = 0. 33). The variance of pericardial fat explained by the lead SNP in the Framingham Heart Study was 0. 5% and 0. 3% in MESA. We performed validation in a multi-ethnic sample of African ancestry (n = 1442, β = 3. 31, p = 0. 001), Hispanic (n = 1399, β = 3. 62, p = 0. 004), and Chinese (n = 761, β = 4. 56, p = 0. 007) participants from the MESA study, with a combined Stage 1 and Stage 2 p-value of 5. 4E-14 (Figure 1A and Figure 1B). To assess whether rs10198628 is specific to pericardial fat, we assessed its associations with other fat depots (Table 2). We observed no association with body mass index from the GIANT consortium (p = 0. 38) [14] or with visceral or subcutaneous fat from the Framingham Heart Study (p = 0. 17 and 0. 34, respectively). We observed nominal direction-consistent associations with waist-hip-ratio adjusted for body mass index from the GIANT consortium (p = 0. 01) [12] and with visceral fat adjusted for body mass index in the Framingham Heart Study (p = 0. 01). We tested whether previously published SNPs in association with waist-hip-ratio adjusted for BMI [12] and BMI [14] are associated with pericardial fat in our meta-analysis dataset (Tables S4 and S5). Among the 14 well-validated SNPs for body fat distribution, we observed direction-consistent associations with CPEB4, a gene involved in cell survival [15]. Among SNPs associated with BMI, we observed nominal direction-consistent associations with FTO; no other associations were observed. Because of the proposed locally toxic effect of pericardial fat and cardiovascular disease outcomes, we evaluated the association of rs10198628 with several CVD phenotypes. We observed nominal, direction-consistent associations with carotid intimal medial thickness from the MESA individuals of European ancestry (n = 2505, p = 0. 04), but we observed no association with myocardial infarction from the CARDIoGRAM consortium (p = 0. 37, OR 1. 01 [95% CI 0. 985–1. 04], n = 81929) [16] or with coronary artery calcification from the MESA study (p = 0. 25, n = 2527). We performed a look-up of 25 validated SNPs for coronary heart disease from the CARDIoGRAM consortium (Table S3) [16], and found that rs12190287 at TCF21 was associated with pericardial fat in a direction-consistent fashion (p = 0. 0019). No additional SNPs met the bonferroni corrected p-value threshold of p<0. 002 (0. 05/25). We queried available human gene expression genetics data (see Methods) and identified eQTL associations with TRB2 in omental adipose (rs890069,1. 79e-9) [42] and two independent subcutaneous adipose samples (rs4669887,3. 62e-9; rs12616457,1. 28e-6) [41], [42]. All of these variants are in LD with our lead SNP rs10198628 (rs890069, rs4669887, rs1261657 have r2 0. 38,0. 38 and 0. 51 with rs10198629, respectively). Next, we tested for gene expression in multiple subcutaneous (inguinal, axillary, and gluteal) and visceral (epididymal, retroperitoneal, mesenteric, omental) adipose depots as well as classical brown, pericardial, and perivascular adipose tissue which were dissected from high-fat fed male mice. mRNA expression levels of the adipocyte markers aP2 and PPARγ2 were comparable across all adipose depots. Trib2 was expressed in pericardial adipose tissue, as well as all of the other adipose depots surveyed (Figure S3). Expression in pericardial adipose tissue was comparable to that in other adipose depots. Lipin 1 is another annotated gene near our lead SNP. It was also expressed in pericardial adipose tissue, as well as all other depots surveyed. Furthermore, expression in pericardial adipose tissue was comparable to that in other adipose depots.
We have identified a SNP near the TRIB2 locus that is associated with pericardial fat but not with body mass index or visceral abdominal fat. This SNP is also associated with pericardial fat in a multi-ethnic sample consisting of individuals of European, African, Hispanic, and Chinese ancestry. Finally, we identified a nearby eQTL, suggesting the potential for altered gene expression associated with our top SNP, or a correlated variant. An important question of our work is whether rs10198628 is uniquely associated with pericardial fat, or merely represents a manifestation of generalized adiposity. Our results suggest that this SNP is unique in its association with pericardial fat, given its strong association with pericardial fat in our stage 1 and stage 2 analysis. In contrast, this SNP was not associated with visceral abdominal fat, an ectopic fat depot that is correlated with pericardial fat. Further, we observed no association with our lead SNP and body mass index in more than 100,000 individuals from the GIANT consortium. We note that we observed nominal significance with our lead SNP with VAT-adjusted-for-BMI and waist-hip-ratio-adjusted for BMI, traits representing fat distribution. Gene expression analysis in mice showed that Trb2 is expressed in all adipose depots. Expression was not enriched in any depot. Confirmation that Trb2 is expressed in adipose tissue supports a functional role for this gene product in this tissue. Future studies are needed to investigate the specific function of Trb2 in adipose tissue, and in particular in pericardial fat. Finally, although our lead SNP is closest to Trb2, it is also possible that this is part of a regulatory region for another gene. Prior genome-wide association studies have primarily used easily-obtainable anthropometric measurements to estimate body fat distribution [12], [13]. While these studies benefit from concomitant enhanced power, the lack of detailed phenotyping renders the precise meaning of the measurement uncertain. In the current study, we have made use of well-validated measurements of pericardial fat that have been previously associated with coronary artery calcium [5], [17], myocardial infarction [6], [18], measurements of left ventricular structure and function [19], and carotid intimal medial thickness [20]. In this context, we sought to examine our lead SNP with coronary calcium, coronary heart disease, and carotid intimal medial thickness. Given the modest epidemiologic associations that have been observed in concert with the relatively small genetic effect sizes that are typical of GWAS, it is not surprising that we observed only nominal associations with carotid intimal medial thickness. Our findings are also notable for some enrichment of association with a SNP in TCF21, previously identified in association with coronary heart disease in CARDIoGRAM [16]. TCF21 encodes a transcription factor of the basic helix-loop-helix family and is a molecular marker of white adipose tissue [21]. TCF21 is expressed in the epicardium of the developing zebrafish, and is associated with perivascular cells but not cardiomyocytes [22]. This is relevant given the anatomic location of pericardial fat and thus rendering it a form of perivascular fat surrounding the coronary arteries. Our lead SNP is located about 80 kb downstream from TRIB2. TRIB2 is the tribbles homolog 2 gene, part of the Tribbles gene family. TRIB2 expression has been shown to be elevated in lung cancer, and has been found to induce apoptosis through downregulation of the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα) [23]. Via this mechanism, TRIB2 may also suppress adipocyte differentiation via AKt inhibition and C/EBPα degradation [24]. TRIB2 has also been associated with hematologic abnormalities including acute myelogenous leukemia [25]. TRIB2 has also been shown to be a regulator of the inflammatory activity of monocytes [26], suggesting a possible mechanism by which it may link low density lipoprotein cholesterol to plaque formation. TRB1 and TRB3 have both been linked to obesity and related phenotypes, with TRIB1 gene expression linked to adipose tissue inflammation [27] and TRB3 gene expression associated with insulin resistance [28]. Our lead SNP also lies near the LPIN1 gene, a compelling candidate gene that has previously been identified in association with lipodystrophy syndromes [29]. While it is tempting to implicate this gene in our association analyses, it is notable that only rare, not common variants have been detected in human populations in association with lipodystrophic phenotypes [30]. In addition, our best SNP in the LIPN1 gene has a p-value = 0. 03, rendering it less likely. Finally, our lead SNP is ∼1 MB from LPIN1. Strengths of our study include the well-characterized pericardial fat data present in both the Framingham Heart Study and the MESA Study. An additional strength is the extension of our findings to multi-ethnic populations, underscoring the generalizability of this finding. Typical of GWAS, we have identified an associated locus, but the causal variant and gene remains unidentified. Limitations include the relatively modest sample size of our study, leading to relatively low power to detect small effects. While our finding that rs12190287 at TCF21 was associated with pericardial fat in a direction-consistent fashion, we are unable to perform a formal mediation analysis. These findings support the concept that unique genetic variants exist in association with different ectopic fat depots. These findings are important because they suggest that different ectopic fat depots may each have their own unique genetic signature that is independent of generalized adiposity. Future work should focus on identifying the molecular mechanisms that link these genomic loci to ectopic fat depots, as this could ultimately lead to the identification of novel pathways and new therapeutic targets. A SNP near TRIB2 is associated with pericardial fat but not measures of generalized or visceral adiposity, reinforcing the concept that there are unique genetic underpinnings to ectopic fat distribution.
Pericardial fat was measured on CT using protocols determined by the participating studies, as described in the Study-Specific Methods. Sex-specific residuals were created, with adjustment for age, height, and weight, as well as principal components derived from genotypes denoting population stratification where necessary. Heritability of pericardial fat was calculated in the Framingham Heart Study using standard methods. Sex-and-cohort specific residuals were created and then pooled for analysis using variance components analysis (SOLAR) [31]. We used SOLAR [31] to calculate pair-wise genetic correlations between pericardial fat, visceral fat, and BMI in the Framingham Heart Study. We used residuals adjusted for age and sex. We tested two separate hypotheses: RhoG = 0 is the test for overlapping genetic correlations, whereas RhoG = 1 is the test for non-overlapping genetic correlations. Table S1 and the study specific methods describe the genotyping that was conducted. Quality-control filters were used to exclude low-quality samples or SNPs. Each study imputed ∼2. 5 million Phase 2 HapMap SNPs based on CEU samples; allelic dosage was used in the analysis. Each cohort separately conducted the regression analysis, using an additive genetic effect model with accounting for family structure when necessary. Next, we conducted a fixed effects weighted Z-score meta-analysis given possible differences in phenotype scaling between the participating studies using METAL [32]. Statistical significance was considered when SNPs reached a meta-analysis P value≤5×10−8 [33]. Discovery analyses were performed on European ancestry participants. SNPs were filtered at a minor allele frequency<2% and an imputation quality score<0. 3. We conducted Stage 2 validation using non-white ethnic samples from the MESA study. Statistical significance was achieved when a direction-consistent p-value was at least p<0. 05. For our lead SNP, we performed look-up in the publically available GIANT datasets [12], [14]. We also obtained specific look-up results in the CARDIoGRAM (for coronary heart disease) [16] and MESA (for coronary artery calcification and carotid intimal medial thickness). We also tested whether the 25 previously-identified SNPs for coronary heart disease from the CARDIoGRAM consortium [16] were associated with pericardial fat. To determine statistical significance, we used the false discovery rate q-value; SNPs with q-value<0. 05 were considered statistically significant using the QVALUE package in R [34]. We tested for a formal sex interaction of rs10198628. Each study computed the interaction regression coefficient, standard error, and p-value. For the sex interaction, we included, age, height, weight, and any principal components (and study center) that were used in the original discovery analysis. We additionally added rs10198628 and the cross-product rs10198628*sex. Interaction terms were meta-analyzed using the weighted z-score approach. We calculated the variance explained using the following formula: 2*MAF* (1−MAF) * ( ( (beta) ∧2) / ( (SD) ∧2) ). We searched for eQTLs in a region bounded by the LIPN1 and TRIB2 genes using expression SNP (eSNP) datasets availably publically or via collaboration including lymphocytes [35], leukocytes [36], leukocytes from patients with Celiac disease [37], lymphoblastoid cell lines (LCL) from children with asthma [38], HapMap LCL from 3 populations [39], a separate study on HapMap CEU LCL [40], peripheral blood monocytes [41], [42], subcutaneous and omental adipose tissue [43], [44], and blood samples [43], 2 studies on brain cortex [41], [45], three large studies of brain regions including prefrontal cortex, visual cortex and cerebellum (Emilsson, personal communication), liver [44], [46], osteoblasts [47], skin [48], and additional fibroblast, T cell and LCL samples [49]. Statistical significance was considered using the association with gene transcript levels as originally described. Adipose tissue was dissected from male C57Bl/6J mice (Jackson Labs) (n = 4) following 20 weeks of ad libitum feeding with a 60% high-fat diet (Research Diets, New Brunswick NJ). High fat feeding was used because many adipose depots (such as pericardial fat) are either not visible or extremely limited in size in standard chow fed mice. Animals were sacrificed and adipose tissues were dissected and frozen in liquid nitrogen. The following adipose depots were dissected: inguinal, axillary, gluteal, brown adipose, epididymal, retroperitoneal, mesenteric, omental, pericardial, and perivascular. All animal experiments were done according to procedures approved by the Institutional Animal Care and Use Committee of Beth Israel Deaconess Medical Center. Total RNA was isolated using TRIzol (Invitrogen, Carlsbad, CA) combined with RNeasy mini-columns, (Qiagen, Valencia, CA) according to the manufacturer' s instructions. For real-time PCR analysis, cDNA was synthesized from RNA using the high capacity cDNA synthesis kit (ABI, Carlsbad, CA). cDNA was used in quantitative PCR containing SYBR-green dye (ABI). mRNA expression levels for each gene were normalized to TBP. Quantitative PCR was performed using an ABI-7900HT PCR machine. In addition to Lipin 1 and Trb2, the expression of the adipocyte markers aP2 and PPARγ2 were also measured. The primer sequences were as follows: aP2, forward 5′ CAT CAG CGT AAA TGG GGA TT 3′ reverse 5′ CCG CCA TCT AGG GTT ATG AT 3′; Lipin 1, forward 5′ CGT ACG TGC GGC TCT GCG AA 3′ reverse 5′ GCT CGG TCG CGT CAA GCT GA 3′; PPARγ2, forward 5′ GCA TGG TGC CTT CGC TGA 3′ reverse 5′ TGG CAT CTC TGT GTC AAC CAT G 3′; TBP, forward 5′ CCC CTT GTA CCC TTC ACC AAT 3′ reverse 5′ GAA GCT GCG GTA CAA TTC CAG 3′; Trib2, forward 5′ CCC GCC CGA GAC TCC GAA CT 3′ reverse 5′ GCA CAG CGC GGA AAA CGT GG 3′.
Pericardial fat is a localized fat depot associated with coronary artery calcium and myocardial infarction. To test whether genetic loci are associated with pericardial fat independent of other body fat depots, we measured pericardial fat in 5,487 individuals of European ancestry. After performing an unbiased screen using genome-wide association, we identified a genome-wide significant signal in our primary meta-analysis at rs10198628 near TRIB2 (MAF 0. 49, p = 2. 7×10-08). This SNP was not associated with visceral fat (p = 0. 17) or body mass index (p = 0. 38). Our findings were robust among multi-ethnic participants from the MESA study, with a combined p-value of 5. 4E-14. We observed TRIB2 gene expression in the pericardial fat of mice. rs10198628 near TRIB2 is associated with pericardial fat but not measures of generalized or visceral adiposity, reinforcing the concept that there are unique genetic underpinnings to ectopic fat distribution.
medicine
myocardial infarction
clinical genetics
genetics and genomics
cardiovascular
Genome-Wide Association of Pericardial Fat Identifies a Unique Locus for Ectopic Fat