Genome-wide association with bone mass and geometry in the Framingham Heart Study

Background

Osteoporosis is defined as the loss of bone mineral density that leads to bone fragility with aging. Population-based case-control studies have identified polymorphisms in many candidate genes that have been associated with bone mass maintenance or osteoporotic fracture. To investigate single nucleotide polymorphisms (SNPs) that are associated with osteoporosis, we examined the genetic variation among Koreans by analyzing 81 genes according to their function in bone formation and resorption during bone remodeling.

Methods

We resequenced all the exons, splice junctions and promoter regions of candidate osteoporosis genes using 24 unrelated Korean individuals. Using the common SNPs from our study and the HapMap database, a statistical analysis of deviation in heterozygosity depicted.

Results

We identified 942 variants, including 888 SNPs, 43 insertion/deletion polymorphisms, and 11 microsatellite markers. Of the SNPs, 557 (63%) had been previously identified and 331 (37%) were newly discovered in the Korean population. When compared SNPs in the Korean population with those in HapMap database, 1% (or less) of SNPs in the Japanese and Chinese subpopulations and 20% of those in Caucasian and African subpopulations were significantly differentiated from the Hardy-Weinberg expectations. In addition, an analysis of the genetic diversity showed that there were no significant differences among Korean, Han Chinese and Japanese populations, but African and Caucasian populations were significantly differentiated in selected genes. Nevertheless, in the detailed analysis of genetic properties, the LD and Haplotype block patterns among the five sub-populations were substantially different from one another.

Conclusion

Through the resequencing of 81 osteoporosis candidate genes, 118 unknown SNPs with a minor allele frequency (MAF) > 0.05 were discovered in the Korean population. In addition, using the common SNPs between our study and HapMap, an analysis of genetic diversity and deviation in heterozygosity was performed and the polymorphisms of the above genes among the five populations were substantially differentiated from one another. Further studies of osteoporosis could utilize the polymorphisms identified in our data since they may have important implications for the selection of highly informative SNPs for future association studies.     

Genome-wide association with bone mass and geometry in the Framingham Heart Study

Background

Osteoporosis is characterized by low bone mass and compromised bone structure, heritable traits that contribute to fracture risk. There have been no genome-wide association and linkage studies for these traits using high-density genotyping platforms.

Methods

We used the Affymetrix 100K SNP GeneChip marker set in the Framingham Heart Study (FHS) to examine genetic associations with ten primary quantitative traits: bone mineral density (BMD), calcaneal ultrasound, and geometric indices of the hip. To test associations with multivariable-adjusted residual trait values, we used additive generalized estimating equation (GEE) and family-based association tests (FBAT) models within each sex as well as sexes combined. We evaluated 70,987 autosomal SNPs with genotypic call rates ≥80%, HWE p ≥ 0.001, and MAF ≥10% in up to 1141 phenotyped individuals (495 men and 646 women, mean age 62.5 yrs). Variance component linkage analysis was performed using 11,200 markers.

Results

Heritability estimates for all bone phenotypes were 30–66%. LOD scores ≥3.0 were found on chromosomes 15 (1.5 LOD confidence interval: 51,336,679–58,934,236 bp) and 22 (35,890,398–48,603,847 bp) for femoral shaft section modulus. The ten primary phenotypes had 12 associations with 100K SNPs in GEE models at p < 0.000001 and 2 associations in FBAT models at p < 0.000001. The 25 most significant p-values for GEE and FBAT were all less than 3.5 × 10^-6 and 2.5 × 10^-5, respectively. Of the 40 top SNPs with the greatest numbers of significantly associated BMD traits (including femoral neck, trochanter, and lumbar spine), one half to two-thirds were in or near genes that have not previously been studied for osteoporosis. Notably, pleiotropic associations between BMD and bone geometric traits were uncommon. Evidence for association (FBAT or GEE p < 0.05) was observed for several SNPs in candidate genes for osteoporosis, such as rs1801133 in MTHFR; rs1884052 and rs3778099 in ESR1; rs4988300 in LRP5; rs2189480 in VDR; rs2075555 in COLIA1; rs10519297 and rs2008691 in CYP19, as well as SNPs in PPARG (rs10510418 and rs2938392) and ANKH (rs2454873 and rs379016). All GEE, FBAT and linkage results are provided as an open-access results resource at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.

Conclusion

The FHS 100K SNP project offers an unbiased genome-wide strategy to identify new candidate loci and to replicate previously suggested candidate genes for osteoporosis.

     

Electrocardiographic abnormalities of left ventricular repolarization: Prognostic implications in hypertensive post-menopausal women

Background

Although repolarization abnormalities on ECG are frequent in post-menopausal hypertensive women, their prognostic value in these women is uncertain.

Methods

We analyzed 908 hypertensive post-menopausal women consecutively included in the PIUMA (Progetto Ipertensione Umbria Monitoraggio Ambulatoriale) study. The median duration of follow-up was 8.6 years (range: 1–21). All women were untreated at entry. Drug treatment during follow-up was adjusted to single individuals. Standard 12-lead ECG was carried out at entry. The Minnesota Coding was used to define minor and major (“typical strain”) repolarization abnormalities.

Design

prospective observational study in essential hypertension.

Results

Mean age at entry was 60 years. At baseline, ECG was normal in 707 women, minor ST-T changes were noted in 152 women, and a typical strain pattern was present in 49 subjects. Predictors of typical strain were age, diabetes and systolic blood pressure (BP). During follow-up there were 119 new cardiovascular (CV) events and 75 all-cause deaths. Typical strain was associated with a threefold higher risk of CV disease (HR: 3.16; 95% CI: 1.59–6.31; p = 0.001) after adjustment for the significant influence of age, diabetes, serum creatinine, systolic BP and HDL-cholesterol. Women with minor LV repolarization abnormalities showed a non-significant excess risk of CV disease when compared with women with normal LV repolarization (HR: 1.25; 95% CI: 0.69–2.26; p = 0.467). Similar results were obtained for all-cause mortality.

Conclusions

Typical strain pattern, an easily detectable marker of altered LV repolarization, identifies post-menopausal hypertensive women at increased risk of CV disease and all-cause mortality.     

Genome-wide association with diabetes-related traits in the Framingham Heart Study

Background

Susceptibility to type 2 diabetes may be conferred by genetic variants having modest effects on risk. Genome-wide fixed marker arrays offer a novel approach to detect these variants.

Methods

We used the Affymetrix 100K SNP array in 1,087 Framingham Offspring Study family members to examine genetic associations with three diabetes-related quantitative glucose traits (fasting plasma glucose (FPG), hemoglobin A1c, 28-yr time-averaged FPG (tFPG)), three insulin traits (fasting insulin, HOMA-insulin resistance, and 0–120 min insulin sensitivity index); and with risk for diabetes. We used additive generalized estimating equations (GEE) and family-based association test (FBAT) models to test associations of SNP genotypes with sex-age-age²-adjusted residual trait values, and Cox survival models to test incident diabetes.

Results

We found 415 SNPs associated (at p < 0.001) with at least one of the six quantitative traits in GEE, 242 in FBAT (18 overlapped with GEE for 639 non-overlapping SNPs), and 128 associated with incident diabetes (31 overlapped with the 639) giving 736 non-overlapping SNPs. Of these 736 SNPs, 439 were within 60 kb of a known gene. Additionally, 53 SNPs (of which 42 had r² < 0.80 with each other) had p < 0.01 for incident diabetes AND (all 3 glucose traits OR all 3 insulin traits, OR 2 glucose traits and 2 insulin traits); of these, 36 overlapped with the 736 other SNPs. Of 100K SNPs, one (rs7100927) was in moderate LD (r² = 0.50) with TCF7L2 (rs7903146), and was associated with risk of diabetes (Cox p-value 0.007, additive hazard ratio for diabetes = 1.56) and with tFPG (GEE p-value 0.03). There were no common (MAF > 1%) 100K SNPs in LD (r² > 0.05) with ABCC8 A1369S (rs757110), KCNJ11 E23K (rs5219), or SNPs in CAPN10 or HNFa. PPARG P12A (rs1801282) was not significantly associated with diabetes or related traits.

Conclusion

Framingham 100K SNP data is a resource for association tests of known and novel genes with diabetes and related traits posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. Framingham 100K data replicate the TCF7L2 association with diabetes.

     

Genome-wide association to body mass index and waist circumference: the Framingham Heart Study 100K project

Background

Obesity is related to multiple cardiovascular disease (CVD) risk factors as well as CVD and has a strong familial component. We tested for association between SNPs on the Affymetrix 100K SNP GeneChip and measures of adiposity in the Framingham Heart Study.

Methods

A total of 1341 Framingham Heart Study participants in 310 families genotyped with the Affymetrix 100K SNP GeneChip had adiposity traits measured over 30 years of follow up. Body mass index (BMI), waist circumference (WC), weight change, height, and radiographic measures of adiposity (subcutaneous adipose tissue, visceral adipose tissue, waist circumference, sagittal height) were measured at multiple examination cycles. Multivariable-adjusted residuals, adjusting for age, age-squared, sex, smoking, and menopausal status, were evaluated in association with the genotype data using additive Generalized Estimating Equations (GEE) and Family Based Association Test (FBAT) models. We prioritized mean BMI over offspring examinations (1–7) and cohort examinations (10, 16, 18, 20, 22, 24, 26) and mean WC over offspring examinations (4–7) for presentation. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, Hardy-Weinberg equilibrium p ≥ 0.001, and call rates of at least 80%.

Results

The top SNPs to be associated with mean BMI and mean WC by GEE were rs110683 (p-value 1.22*10^-7) and rs4471028 (p-values 1.96*10^-7). Please see http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 for the complete set of results. We were able to validate SNPs in known genes that have been related to BMI or other adiposity traits, including the ESR1 Xba1 SNP, PPARG, and ADIPOQ.

Conclusion

Adiposity traits are associated with SNPs on the Affymetrix 100K SNP GeneChip. Replication of these initial findings is necessary. These data will serve as a resource for replication as more genes become identified with BMI and WC.

     

Genome-wide association to body mass index and waist circumference: the Framingham Heart Study 100K project

Background

The FABP2 gene encodes for the intestinal FABP (IFABP) protein, which is expressed only in intestinal enterocytes. A polymorphism at codon 54 in exon 2 of the FABP2 gene exchanges an Alanine (Ala), in the small helical region of the protein, for Threonine (Thr). Given the potential physiological role of the Ala54Thr FABP2 polymorphism, we assess in this study the local population frequency and analyze possible associations with five selected markers, i.e. glycemia, total cholesterol, body mass index (BMI), hypertension, and high Cardiovascular Risk Index (CVR index).

Methods

We studied 86 men and 116 women. DNA was extracted from a blood drop for genotype analysis. Allele frequencies were calculated by direct counting. Hardy Weinberg Equilibrium was evaluated using a Chi-square goodness of fit test. For the polymorphism association analysis, five markers were selected, i.e. blood pressure, Framingham Risk Index, total cholesterol, BMI, and glycemia. For each marker, the Odds Ratio (OR) was calculated by an online statistic tool.

Results

Our results reveal a similar population polymorphism frequency as in previous European studies, with q = 0.277 (95% confidence limits 0.234–0.323). No significant association was found with any of the tested markers in the context of our Argentine nutritional and cultural habits. We did, however, observe a tendency for increased Cholesterol and high BMI in Thr54 carriers.

Conclusion

This is the first study to look at the population frequency of the Thr54 allele in Argentina. The obtained result does not differ from previously reported frequencies in European populations. Moreover, we found no association between the Thr54 allele and any of the five selected markers. The observed tendency to increased total cholesterol and elevated BMI in Thr54 carriers, even though not significant for p < 0.1 could be worth of further investigation to establish whether the Thr54 variant should be taken into consideration in cardiovascular prevention strategies.     

Fat-free mass as a determinant of left ventricular mass in children: The Muscatine Study

To assess the relationship of somatic growth to heart growth, associations were examined among body composition, blood pressure, androgens, sexual maturation, and left ventricular mass (LVM) during early puberty in 123 children, 7–12 years of age. All subjects underwent anthropometry, random-zero blood pressure measurements, hormone determination of androgens, physician's examination to determine sexual maturation, and echocardiographic examinations. Subjects then repeated these procedures 1 year later. Data were examined cross-sectionally (year 1, year 2) and longitudinally (Δ = year 2 minus year 1). The strongest correlations with LVM were among weight and fat-free mass (FFM) (r = 0.60 to 0.83). In males, cross-sectional predictors of LVM were FFM and stage of sexual maturation (r² = 0.49 to 0.65). Δ LVM was best predicted in males by Δ testosterone and Δ weight (r² = 0.22). In females, FFM was the strongest cross-sectional predictor of LVM (r² = 0.70). Δ LVM was best predicted in females by Δ FFM and Δ height (r² = 0.27). When males and females were pooled, gender did not predict LVM in any of the models. The results suggest that FFM is an important predictor of LVM in circumpubertal children. Boys and girls do not significantly differ in LVM once normalized for FFM. © 1996 Wiley-Liss, Inc.     

Genome-wide association with select biomarker traits in the Framingham Heart Study

Background

Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations.

Methods

We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 ± 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507–1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency ≥ 10%, call rate ≥ 80% and Hardy-Weinberg equilibrium p ≥ 0.001.

Results

With GEE, 58 SNPs had p < 10^-6: the top SNPs were rs2494250 (p = 1.00*10^-14) and rs4128725 (p = 3.68*10^-12) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10^-8) and rs2808629 (p = 3.19*10^-8) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10^-6: the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10^-8, and rs2494250, p = 3.55*10^-8), and also included B-type natriuretic peptide (rs437021, p = 1.01*10^-6) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10^-6). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.

Conclusion

The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.

     

Prognostic value of left ventricular apical tissue removed for HeartMate II left ventricular assist device placement

BackgroundWith the increasing use of left ventricular assist devices, the left ventricular apical core has become a more frequently encountered surgical pathology tissue. We investigated the prognostic value of this cardiac tissue in short-term patient mortality. Previous studies have shown that the degree of cardiac fibrosis correlates with improvements in ejection fraction and the likelihood of weaning from an assist device.MethodsLeft ventricular apical core tissues from 29 sequential subjects who received a HeartMate II continuous axial flow left ventricular assist device were studied retrospectively to determine whether interstitial fibrosis, replacement fibrosis (scar), the presence of mural thrombus, or other histopathologic findings were associated with hemodynamic changes or mortality in this population. Patients received left ventricular assist devices as bridges to transplantation or as destination therapy. Interstitial fibrosis was determined by observer scoring and digital scoring methods. Before and after left ventricular assist device procedure, right heart catheterizations were reviewed for clinical cardiac data.ResultsThe presence of replacement fibrosis in the apical core tissue significantly correlated with decreased improvement in pulmonary capillary wedge pressure after left ventricular assist device placement (P=.02). Ten subjects died over the course of this study. No specimen variables, including scar, interstitial fibrosis, and the presence of mural thrombosis, correlated with patient mortality.ConclusionsPathologic findings in left ventricular apical cores have little prognostic utility in guiding patient management as related to overall 1-year mortality, but may indicate patients who are more likely to positively remodel their hearts.     

Association between SNP Heterozygosity and Quantitative Traits in the Framingham Heart Study

Associations between multilocus heterozygosity and fitness traits, also termed heterozygosity and fitness correlations (HFCs), have been reported in numerous organisms. These studies, in general, indicate a positive relationship between heterozygosity and fitness traits. We studied the association between genome-wide heterozygosity at 706 non-synonymous and synonymous SNPs and 19 quantitative traits, including morphological, biochemical and fitness traits in the Framingham Heart Study. Statistically significant association was found between heterozygosity and systolic and diastolic blood pressures as well as left ventricular diameter and wall thickness. These results suggest that heterozygosity may be associated with traits, such as blood pressure that closely track environmental variations. Balancing selection may be operating in the maintenance of heterozygosity and the major components of blood pressure and hypertension. Genome wide SNP heterozygosity may be used to understand the phenomenon of dominance as well as the evolutionary basis of many quantitative traits in humans.     

Use of vectorcardiography in determination of the left ventricular muscle mass

Many studies have investigated different ECG and vectorcardiographic (VCG): criteria for diagnosis of left ventricular hypertrophy (LVH). In some investigations VCG was more sensitive than ECG in this respect. This study was performed to elucidate whether it is possible also to determine the degree of LVH using VCG. Eighty cardiovascularly healthy subjects aged 15-39 were investigated with ECG, VCG (Frank system) and echocardiography. The echocardiographic left ventricular (LV) mass has been shown by others to correlate closely to the anatomical and the angiographically determined LV mass and was used as reference standard. Thirty-eight of the subjects were endurance sportsmen and had a LV mass above standard reference limits. The measured ECG variables were R-amplitude in a VL, I, V5, V6, S-amplitude in V1 and SV1 + RV5/V6 and the VCG variables were QRS spatial area and circumference and left maximal spatial vector. The sensitivity and specificity of single criteria tested were similar for ECG and VCG in the quantitative determination of LVH. The correlations between ECG-amplitudes and the magnitude of the LV mass were weak. The correlations were higher with the VCG-variables, QRS spatial circumference being superior to the others, but not good enough to permit an estimation of the LV mass in individual subjects. In conclusion, normal VCG variables were highly specific for a normal LV mass but in individuals with LVH, VCG was not useful for the estimation of the LV mass.     

Realistic three-dimensional left ventricular ejection determined from computational fluid dynamics

A realistic model of the left ventricle of the human heart was constructed using a cast from a dog heart which was in diastole. A coordinate measuring machine was used to measure and digitize the coordinates of the left ventricle. From the complex measured left ventricle shape values, a three-dimensional finite volume representation was constructed using a simulation package. The left ventricular walls moved towards the centre of the aortic outlet in order to study the effects of time-varying left ventricular ejection. The left ventricular wall motion was assumed to follow the blood flow and the wall grid was reformed 25 times during the calculation. The 25.8 cm³ ventricular volume was reduced by 75% in 0.25 s. Centreline and cross-sectional velocity vectors greatly increased in magnitude at the aortic outlet, and most of the pressure occurred in the top 15% of the heart. The computational method should make it possible to compare simulation results with important measurement techniques such as ultrasound and magnetic resonance imaging, and this should allow a finer detail of flow understanding than is presently available using either a modelling or imaging method alone.     

A genome-wide association study for blood lipid phenotypes in the Framingham Heart Study

Background

Blood lipid levels including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) are highly heritable. Genome-wide association is a promising approach to map genetic loci related to these heritable phenotypes.

Methods

In 1087 Framingham Heart Study Offspring cohort participants (mean age 47 years, 52% women), we conducted genome-wide analyses (Affymetrix 100K GeneChip) for fasting blood lipid traits. Total cholesterol, HDL-C, and TG were measured by standard enzymatic methods and LDL-C was calculated using the Friedewald formula. The long-term averages of up to seven measurements of LDL-C, HDL-C, and TG over a ~30 year span were the primary phenotypes. We used generalized estimating equations (GEE), family-based association tests (FBAT) and variance components linkage to investigate the relationships between SNPs (on autosomes, with minor allele frequency ≥10%, genotypic call rate ≥80%, and Hardy-Weinberg equilibrium p ≥ 0.001) and multivariable-adjusted residuals. We pursued a three-stage replication strategy of the GEE association results with 287 SNPs (P < 0.001 in Stage I) tested in Stage II (n ~1450 individuals) and 40 SNPs (P < 0.001 in joint analysis of Stages I and II) tested in Stage III (n~6650 individuals).

Results

Long-term averages of LDL-C, HDL-C, and TG were highly heritable (h² = 0.66, 0.69, 0.58, respectively; each P < 0.0001). Of 70,987 tests for each of the phenotypes, two SNPs had p < 10^-5 in GEE results for LDL-C, four for HDL-C, and one for TG. For each multivariable-adjusted phenotype, the number of SNPs with association p < 10^-4 ranged from 13 to 18 and with p < 10^-3, from 94 to 149. Some results confirmed previously reported associations with candidate genes including variation in the lipoprotein lipase gene (LPL) and HDL-C and TG (rs7007797; P = 0.0005 for HDL-C and 0.002 for TG). The full set of GEE, FBAT and linkage results are posted at the database of Genotype and Phenotype (dbGaP). After three stages of replication, there was no convincing statistical evidence for association (i.e., combined P < 10^-5 across all three stages) between any of the tested SNPs and lipid phenotypes.

Conclusion

Using a 100K genome-wide scan, we have generated a set of putative associations for common sequence variants and lipid phenotypes. Validation of selected hypotheses in additional samples did not identify any new loci underlying variability in blood lipids. Lack of replication may be due to inadequate statistical power to detect modest quantitative trait locus effects (i.e., <1% of trait variance explained) or reduced genomic coverage of the 100K array. GWAS in FHS using a denser genome-wide genotyping platform and a better-powered replication strategy may identify novel loci underlying blood lipids.