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.

     

Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham study

Background

Brain magnetic resonance imaging (MRI) and cognitive tests can identify heritable endophenotypes associated with an increased risk of developing stroke, dementia and Alzheimer's disease (AD). We conducted a genome-wide association (GWA) and linkage analysis exploring the genetic basis of these endophenotypes in a community-based sample.

Methods

A total of 705 stroke- and dementia-free Framingham participants (age 62 +9 yrs, 50% male) who underwent volumetric brain MRI and cognitive testing (1999–2002) were genotyped. We used linear models adjusting for first degree relationships via generalized estimating equations (GEE) and family based association tests (FBAT) in additive models to relate qualifying single nucleotide polymorphisms (SNPs, 70,987 autosomal on Affymetrix 100K Human Gene Chip with minor allele frequency ≥ 0.10, genotypic call rate ≥ 0.80, and Hardy-Weinberg equilibrium p-value ≥ 0.001) to multivariable-adjusted residuals of 9 MRI measures including total cerebral brain (TCBV), lobar, ventricular and white matter hyperintensity (WMH) volumes, and 6 cognitive factors/tests assessing verbal and visuospatial memory, visual scanning and motor speed, reading, abstract reasoning and naming. We determined multipoint identity-by-descent utilizing 10,592 informative SNPs and 613 short tandem repeats and used variance component analyses to compute LOD scores.

Results

The strongest gene-phenotype association in FBAT analyses was between SORL1 (rs1131497; p = 3.2 × 10^-6) and abstract reasoning, and in GEE analyses between CDH4 (rs1970546; p = 3.7 × 10^-8) and TCBV. SORL1 plays a role in amyloid precursor protein processing and has been associated with the risk of AD. Among the 50 strongest associations (25 each by GEE and FBAT) were other biologically interesting genes. Polymorphisms within 28 of 163 candidate genes for stroke, AD and memory impairment were associated with the endophenotypes studied at p < 0.001. We confirmed our previously reported linkage of WMH on chromosome 4 and describe linkage of reading performance to a marker on chromosome 18 (GATA11A06), previously linked to dyslexia (LOD scores = 2.2 and 5.1).

Conclusion

Our results suggest that genes associated with clinical neurological disease also have detectable effects on subclinical phenotypes. These hypothesis generating data illustrate the use of an unbiased approach to discover novel pathways that may be involved in brain aging, and could be used to replicate observations made in other studies.

     

A genome-wide association study of breast and prostate cancer in the NHLBI's Framingham Heart Study

Background

Cutaneous Malignant Melanoma causes over 75% of skin cancer-related deaths, and it is clear that many factors may contribute to the outcome. Matrix Metalloproteinases (MMPs) play an important role in the degradation and remodeling of the extracellular matrix and basement membrane that, in turn, modulate cell division, migration and angiogenesis. Some polymorphisms are known to influence gene expression, protein activity, stability, and interactions, and they were shown to be associated with certain tumor phenotypes and cancer risk.

Methods

We tested seven polymorphisms within the MMP-9 gene in 1002 patients with melanoma in order to evaluate germline genetic variants and their association with progression and known risk factors of melanoma. The polymorphisms were selected based on previously published reports and their known or potential functional relevance using in-silico methods. Germline DNA was then genotyped using pyrosequencing, melting temperature profiles, heteroduplex analysis, and fragment size analysis.

Results

We found that reference alleles were present in higher frequency in patients who tend to sunburn, have family history of melanoma, higher melanoma stage, intransit metastasis and desmoplastic melanomas among others. However, after adjustment for age, sex, phenotypic index, moles, and freckles only Q279R, P574R and R668Q had significant associations with intransit metastasis, propensity to tan/sunburn and primary melanoma site.

Conclusion

This study does not provide strong evidence for further investigation into the role of the MMP-9 SNPs in melanoma progression.     

A genome-wide association study of breast and prostate cancer in the NHLBI's Framingham Heart Study

Background

Breast and prostate cancer are two commonly diagnosed cancers in the United States. Prior work suggests that cancer causing genes and cancer susceptibility genes can be identified.

Methods

We conducted a genome-wide association study (Affymetrix 100K SNP GeneChip) of cancer in the community-based Framingham Heart Study. We report on 2 cancer traits – prostate cancer and breast cancer – in up to 1335 participants from 330 families (54% women, mean entry age 33 years). Multivariable-adjusted residuals, computed using Cox proportional hazards models, were tested for association with qualifying SNPs (70, 987 autosomal SNPs with genotypic call rate ≥80%, minor allele frequency ≥10%, Hardy-Weinberg test p ≥ 0.001) using generalized estimating equations (GEE) models and family based association tests (FBAT).

Results

There were 58 women with breast cancer and 59 men with prostate cancer. No SNP associations attained genome-wide significance. The top SNP associations in GEE models for each trait were as follows: breast cancer, rs2075555, p = 8.0 × 10^-8 in COL1A1; and prostate cancer, rs9311171, p = 1.75 × 10^-6 in CTDSPL. In analysis of selected candidate cancer susceptibility genes, two MSR1 SNPs (rs9325782, GEE p = 0.008 and rs2410373, FBAT p = 0.021) were associated with prostate cancer and three ERBB4 SNPs (rs905883 GEE p = 0.0002, rs7564590 GEE p = 0.003, rs7558615 GEE p = 0.0078) were associated with breast cancer. The previously reported risk SNP for prostate cancer, rs1447295, was not included on the 100K chip. Results of cancer phenotype-genotype associations for all autosomal SNPs are web posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.

Conclusion

Although no association attained genome-wide significance, several interesting associations emerged for breast and prostate cancer. These findings can serve as a resource for replication in other populations to identify novel biologic pathways contributing to cancer susceptibility.

     

Framingham Heart Study genome-wide association: results for pulmonary function measures

Background

Pulmonary function measures obtained by spirometry are used to diagnose chronic obstructive pulmonary disease (COPD) and are highly heritable. We conducted genome-wide association (GWA) analyses (Affymetrix 100K SNP GeneChip) for measures of lung function in the Framingham Heart Study.

Methods

Ten spirometry phenotypes including percent of predicted measures, mean spirometry measures over two examinations, and rates of change based on forced expiratory volume in one second (FEV₁), forced vital capacity (FVC), forced expiratory flow from the 25^th to 75^th percentile (FEF_25–75), the FEV₁/FVC ratio, and the FEF_25–75/FVC ratio were examined. Percent predicted phenotypes were created using each participant's latest exam with spirometry. Predicted lung function was estimated using models defined in the set of healthy never-smokers, and standardized residuals of percent predicted measures were created adjusting for smoking status, pack-years, and body mass index (BMI). All modeling was performed stratified by sex and cohort. Mean spirometry phenotypes were created using data from two examinations and adjusting for age, BMI, height, smoking and pack-years. Change in pulmonary function over time was studied using two to four examinations with spirometry to calculate slopes, which were then adjusted for age, height, smoking and pack-years.

Results

Analyses were restricted to 70,987 autosomal SNPs with minor allele frequency ≥ 10%, genotype call rate ≥ 80%, and Hardy-Weinberg equilibrium p-value ≥ 0.001. A SNP in the interleukin 6 receptor (IL6R) on chromosome 1 was among the best results for percent predicted FEF_25–75. A non-synonymous coding SNP in glutathione S-transferase omega 2 (GSTO2) on chromosome 10 had top-ranked results studying the mean FEV₁ and FVC measurements from two examinations. SNPs nearby the SOD3 and vitamin D binding protein genes, candidate genes for COPD, exhibited association to percent predicted phenotypes.

Conclusion

GSTO2 and IL6R are credible candidate genes for association to pulmonary function identified by GWA. These and other observed associations warrant replication studies. This resource of GWA results for pulmonary function measures is publicly available at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.

     

Pathway-based analysis of genome-wide association study of circadian phenotypes

Sleepiness affects normal social life, which attracts more and more attention. Circadian phenotypes contribute to obvious individual differences in susceptibility to sleepiness. We aimed to identify candidate single nucleotide polymorphisms (SNPs) which may cause circadian phenotypes, elucidate the potential mechanisms, and generate corresponding SNP-gene-pathways. A genome-wide association studies (GWAS) dataset of circadian phenotypes was utilized in the study. Then, the Identify Candidate Causal SNPs and Pathways analysis was employed to the GWAS dataset after quality control filters. Furthermore, genotype-phenotype association analysis was performed with HapMap database. Four SNPs in three different genes were determined to correlate with usual weekday bedtime, totally providing seven hypothetical mechanisms. Eleven SNPs in six genes were identified to correlate with usual weekday sleep duration, which provided six hypothetical pathways. Our results demonstrated that fifteen candidate SNPs in eight genes played vital roles in six hypothetical pathways implicated in usual weekday bedtime and six potential pathways involved in usual weekday sleep duration.     

A genome-wide association study for age-related hearing impairment in the Saami

This study aimed at contributing to the elucidation of the genetic basis of age-related hearing impairment (ARHI), a common multifactorial disease with an important genetic contribution as demonstrated by heritability studies. We conducted a genome-wide association study (GWAS) in the Finnish Saami, a small, ancient, genetically isolated population without evidence of demographic expansion. The choice of this study population was motivated by its anticipated higher extent of LD, potentially offering a substantial power advantage for association mapping. DNA samples and audiometric measurements were collected from 352 Finnish Saami individuals, aged between 50 and 75 years. To reduce the burden of multiple testing, we applied principal component (PC) analysis to the multivariate audiometric phenotype. The first three PCs captured 80% of the variation in hearing thresholds, while maintaining biologically important audiometric features. All subjects were genotyped with the Affymetrix 100 K chip. To account for multiple levels of relatedness among subjects, as well as for population stratification, association testing was performed using a mixed model. We summarised the top-ranking association signals for the three traits under study. The top-ranked SNP, rs457717 (P-value 3.55 × 10⁻⁷), was associated with PC3 and was localised in an intron of the IQ motif-containing GTPase-activating-like protein (IQGAP2). Intriguingly, the SNP rs161927 (P-value 0.000149), seventh-ranked for PC1, was positioned immediately downstream from the metabotropic glutamate receptor-7 gene (GRM7). As a previous GWAS of a European and Finnish sample set already suggested a role for GRM7 in ARHI, this study provides further evidence for the involvement of this gene.     

A genome-wide association for kidney function and endocrine-related traits in the NHLBI's Framingham Heart Study

Background

Glomerular filtration rate (GFR) and urinary albumin excretion (UAE) are markers of kidney function that are known to be heritable. Many endocrine conditions have strong familial components. We tested for association between the Affymetrix GeneChip Human Mapping 100K single nucleotide polymorphism (SNP) set and measures of kidney function and endocrine traits.

Methods

Genotype information on the Affymetrix GeneChip Human Mapping 100K SNP set was available on 1345 participants. Serum creatinine and cystatin-C (cysC; n = 981) were measured at the seventh examination cycle (1998–2001); GFR (n = 1010) was estimated via the Modification of Diet in Renal Disease (MDRD) equation; UAE was measured on spot urine samples during the sixth examination cycle (1995–1998) and was indexed to urinary creatinine (n = 822). Thyroid stimulating hormone (TSH) was measured at the third and fourth examination cycles (1981–1984; 1984–1987) and mean value of the measurements were used (n = 810). Age-sex-adjusted and multivariable-adjusted residuals for these measurements were used in association with genotype data using generalized estimating equations (GEE) and family-based association tests (FBAT) models. We presented the results for association tests using additive allele model. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, Hardy-Weinberg Equilibrium p-value ≥ 0.001, and call rates of at least 80%.

Results

The top SNPs associated with these traits using the GEE method were rs2839235 with GFR (p-value 1.6*10^-05), rs1158167 with cysC (p-value 8.5*10^-09), rs1712790 with UAE (p-value 1.9*10^-06), and rs6977660 with TSH (p-value 3.7*10^-06), respectively. The top SNPs associated with these traits using the FBAT method were rs6434804 with GFR(p-value 2.4*10^-5), rs563754 with cysC (p-value 4.7*10^-5), rs1243400 with UAE (p-value 4.8*10^-6), and rs4128956 with TSH (p-value 3.6*10^-5), respectively. Detailed association test results can be found at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. Four SNPs in or near the CST3 gene were highly associated with cysC levels (p-value 8.5*10^-09 to 0.007).

Conclusion

Kidney function traits and TSH are associated with SNPs on the Affymetrix GeneChip Human Mapping 100K SNP set. These data will serve as a valuable resource for replication as more SNPs associated with kidney function and endocrine traits are identified.

     

Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study

Background

Increased circulating levels of hemostatic factors as well as anemia have been associated with increased risk of cardiovascular disease (CVD). Known associations between hemostatic factors and sequence variants at genes encoding these factors explain only a small proportion of total phenotypic variation. We sought to confirm known putative loci and identify novel loci that may influence either trait in genome-wide association and linkage analyses using the Affymetrix GeneChip 100K single nucleotide polymorphism (SNP) set.

Methods

Plasma levels of circulating hemostatic factors (fibrinogen, factor VII, plasminogen activator inhibitor-1, von Willebrand factor, tissue plasminogen activator, D-dimer) and hematological phenotypes (platelet aggregation, viscosity, hemoglobin, red blood cell count, mean corpuscular volume, mean corpuscular hemoglobin concentration) were obtained in approximately 1000 Framingham Heart Study (FHS) participants from 310 families. Population-based association analyses using the generalized estimating equations (GEE), family-based association test (FBAT), and multipoint variance components linkage analyses were performed on the multivariable adjusted residuals of hemostatic and hematological phenotypes.

Results

In association analysis, the lowest GEE p-value for hemostatic factors was p = 4.5*10^-16 for factor VII at SNP rs561241, a variant located near the F7 gene and in complete linkage disequilibrium (LD) (r² = 1) with the Arg353Gln F7 SNP previously shown to account for 9% of total phenotypic variance. The lowest GEE p-value for hematological phenotypes was 7*10^-8 at SNP rs2412522 on chromosome 4 for mean corpuscular hemoglobin concentration. We presented top 25 most significant GEE results with p-values in the range of 10^-6 to 10^-5 for hemostatic or hematological phenotypes. In relating 100K SNPs to known candidate genes, we identified two SNPs (rs1582055, rs4897475) in erythrocyte membrane protein band 4.1-like 2 (EPB41L2) associated with hematological phenotypes (GEE p < 10^-3). In linkage analyses, the highest linkage LOD score for hemostatic factors was 3.3 for factor VII on chromosome 10 around 15 Mb, and for hematological phenotypes, LOD 3.4 for hemoglobin on chromosome 4 around 55 Mb. All GEE and FBAT association and variance components linkage results can be found at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007

Conclusion

Using genome-wide association methodology, we have successfully identified a SNP in complete LD with a sequence variant previously shown to be strongly associated with factor VII, providing proof of principle for this approach. Further study of additional strongly associated SNPs and linked regions may identify novel variants that influence the inter-individual variability in hemostatic factors and hematological phenotypes.

     

Phenomics: the systematic study of phenotypes on a genome-wide scale

Phenomics is an emerging transdiscipline dedicated to the systematic study of phenotypes on a genome-wide scale. New methods for high-throughput genotyping have changed the priority for biomedical research to phenotyping, but the human phenome is vast and its dimensionality remains unknown. Phenomics research strategies capable of linking genetic variation to public health concerns need to prioritize development of mechanistic frameworks that relate neural systems functioning to human behavior. New approaches to phenotype definition will benefit from crossing neuropsychiatric syndromal boundaries, and defining phenotypic features across multiple levels of expression from proteome to syndrome. The demand for high throughput phenotyping may stimulate a migration from conventional laboratory to web-based assessment of behavior, and this offers the promise of dynamic phenotyping—the iterative refinement of phenotype assays based on prior genotype-phenotype associations. Phenotypes that can be studied across species may provide greatest traction, particularly given rapid development in transgenic modeling. Phenomics research demands vertically integrated research teams, novel analytic strategies and informatics infrastructure to help manage complexity. The Consortium for Neuropsychiatric Phenomics at UCLA has been supported by the National Institutes of Health Roadmap Initiative to illustrate these principles, and is developing applications that may help investigators assemble, visualize, and ultimately test multi-level phenomics hypotheses. As the transdiscipline of phenomics matures, and work is extended to large-scale international collaborations, there is promise that systematic new knowledge bases will help fulfill the promise of personalized medicine and the rational diagnosis and treatment of neuropsychiatric syndromes.     

Genetic variation associated with chromosomal aberration frequency: A genome-wide association study

Chromosomal aberrations (CAs) in human peripheral blood lymphocytes (PBL) measured with the conventional cytogenetic assay have been used for human biomonitoring of genotoxic exposure for decades. CA frequency in peripheral blood is a marker of cancer susceptibility. Previous studies have shown associations between genetic variants in metabolic pathway, DNA repair and major mitotic checkpoint genes and CAs. We conducted a genome-wide association study on 576 individuals from the Czech Republic and Slovakia followed by a replication in two different sample sets of 482 (replication 1) and 1288 (replication 2) samples. To have a broad look at the genetic susceptibility associated with CA frequency, the sample sets composed of individuals either differentially exposed to smoking, occupational/environmental hazards, or they were untreated cancer patients. Phenotypes were divided into chromosome- and chromatid-type aberrations (CSAs and CTAs, respectively) and total chromosomal aberrations (CAtot). The arbitrary cutoff point between individuals with high and low CA frequency was 2% for CAtot and 1% for CSA and CTA. The data were analyzed using age, sex, occupation/cancer and smoking history as covariates. Altogether 11 loci reached the P-value of 10⁻⁵ in the GWAS. Replication 1 supported the association of rs1383997 (8q13.3) and rs2824215 (21q21.1) in CAtot and rs983889 (5p15.1) in CTA analysis. These loci were found to be associated with genes involved in mitosis, response to environmental and chemical factors and genes involved in syndromes linked to chromosomal abnormalities. Identification of new genetic variants for the frequency of CAs offers prediction tools for cancer risk in future. Environ. Mol. Mutagen. 60:17–28, 2019. © 2018 Wiley Periodicals, Inc.     

Genome-wide association study of electrocardiographic and heart rate variability traits: the Framingham Heart Study

Background

Heritable electrocardiographic (ECG) and heart rate variability (HRV) measures, reflecting pacemaking, conduction, repolarization and autonomic function in the heart have been associated with risks for cardiac arrhythmias. Whereas several rare monogenic conditions with extreme phenotypes have been noted, few common genetic factors contributing to interindividual variability in ECG and HRV measures have been identified. We report the results of a community-based genomewide association study of six ECG and HRV intermediate traits.

Methods

Genotyping using Affymetrix 100K GeneChip was conducted on 1345 related Framingham Heart Study Original and Offspring cohort participants. We analyzed 1175 Original and Offspring participants with ECG data (mean age 52 years, 52% women) and 548 Offspring participants with HRV data (mean age 48 years, 51% women), in relation to 70,987 SNPs with minor allele frequency ≥ 0.10, call rate ≥ 80%, Hardy-Weinberg p-value ≥ 0.001. We used generalized estimating equations to test association of SNP alleles with multivariable-adjusted residuals for QT, RR, and PR intervals, the ratio of low frequency to high frequency power (LF/HFP), total power (TP) and the standard deviation of normal RR intervals (SDNN).

Results

Associations at p < 10^-3 were found for 117 (QT), 105 (RR), 111 (PR), 102 (LF/HF), 121 (TP), and 102 (SDNN) SNPs. Several common variants in NOS1AP (4 SNPs with p-values < 10^-3; lowest p-value, rs6683968, p = 1 × 10^-4) were associated with adjusted QT residuals, consistent with our previously reported finding for NOS1AP in an unrelated sample of FHS Offspring and other cohorts. All results are publicly available at NCBI's dbGaP at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.

Conclusion

In the community-based Framingham Heart Study none of the ECG and HRV results individually attained genomewide significance. However, the presence of bona fide QT-associated SNPs among the top 117 results for QT duration supports the importance of efforts to validate top results from the reported scans. Finding genetic variants associated with ECG and HRV quantitative traits may identify novel genes and pathways implicated in arrhythmogenesis and allow for improved recognition of individuals at high risk for arrhythmias in the general population.

     

A look at the basic correlates of longevity: is longevity a superficial trait?

Nature appears to have distributed life spans, whether long or short, entirely upon the possession or non-possession of a few physiologically superficial characteristics, namely, immunity of mature, full-sized specimens from the effects of: (1) predation, (2) competition, (3) fire, (4) disease, and (5) the existence of a definite usefulness for long life spans in bridging lengthy periods unfavorable to the reproduction and/or maturation of offspring. Extremely strong correlations are presented in proof of the above relationships. Since longevity mechanisms can closely correlate to superficial traits, it is unlikely that they comprise an integral part of basic structural or biochemical processes. In the case of trees, all five of the above traits are apparently required for the achievement of potential life spans in excess of 1000 years. By contrast, the longest live animal species appear to fully possess only (1) and (3) of the five prerequisite traits above. This observation may fully account for the fact that maximum life spans of trees are 30-40 times greater than those of the longest lived animals.     

Replication of past candidate loci for common diseases and phenotypes in 100 genome-wide association studies

Genome-wide association studies (GWASs) have created a paradigm shift in discovering genetic associations for common diseases and phenotypes, but it is unclear whether the thousands of candidate genetic association studies performed in the pre-GWAS era had found any reliable associations for common diseases and phenotypes. We aimed to systematically evaluate whether loci proposed to harbor candidate associations before the advent of GWASs are replicated in GWASs. The GWAS data published through August, 2008 and included in the NHGRI catalog were screened and variants in candidate loci were selected on the basis of statistical significance (P<0.05) to create a list of independent, non-redundant associations. Altogether, 159 articles on GWASs were evaluated, 100 of which addressed past proposed candidate loci. A total of 291 independent, nominally significant (P<0.05) candidate gene associations were assembled after keeping only the SNP with lowest P-value for each locus and each phenotype; 108 of those had P<10⁻³ for association and 41 had P<10⁻⁷. A total of 22 of these 41 candidate gene associations pertained to binary phenotypes with a median odds ratio=2.91 (IQR: 1.82–4.6) and median minor allele frequency=0.17 (IQR: 0.12–0.29) in Caucasians; for comparison, 60 new associations of binary outcomes with P<10⁻⁷ discovered in the same GWASs had much smaller effects (median odds ratio 1.30, IQR: 1.18–1.58) and modestly larger minor allele frequencies (median 0.27, IQR: 0.15–0.43). Overall, few of the numerous genetic associations proposed in the candidate gene era have been replicated in GWASs, but those that have been conclusively replicated have large genetic effects that should not be discarded.     

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.

     

Pharmacogenomics in Alzheimer's disease: a genome-wide association study of response to cholinesterase inhibitors

We conducted a genome-wide association study in a cohort of 176 Italian Alzheimer's disease (AD) patients with extreme phenotype of response to cholinesterase inhibitors. Patients were classified into responders in case of positive, stable, or ≤1 worsening of mini-mental state examination score and into nonresponders if >3 points worsening during a median follow-up of 0.85 years of treatment. Forty-eight single-nucleotide polymorphisms were selected for replication in 198 additional AD-treated patients. By using the dichotomous response trait and a quantitative trait approach (change of mini-mental state examination), a nominal replication and evidence of association when combining data were achieved for 2 single-nucleotide polymorphisms associated with response to treatment: rs6720975_A (p_combined = 2.9 × 10⁻⁵, beta regression coefficient: 1.61) and rs17798800_A (p_combined = 6.8 × 10⁻⁶, odds ratio = 0.38, 95% confidence interval = 0.25–0.58). Rs6720975 maps in the intronic region of PRKCE, a protein kinase involved in several cellular functions, whereas rs17798800 is intergenic and, according to expression quantitative trait locus (eQTL) analysis, it acts as a cis-regulator of NBEA, an A kinase–anchoring protein playing a substantial role in the maturation of the nervous system. Despite its limitations, this project paves the way for the application of personalized medicine in AD patients and for collaborative efforts in this field.     

Framingham Heart Study 100K Project: genome-wide associations for blood pressure and arterial stiffness

Background

About one quarter of adults are hypertensive and high blood pressure carries increased risk for heart disease, stroke, kidney disease and death. Increased arterial stiffness is a key factor in the pathogenesis of systolic hypertension and cardiovascular disease. Substantial heritability of blood-pressure (BP) and arterial-stiffness suggests important genetic contributions.

Methods

In Framingham Heart Study families, we analyzed genome-wide SNP (Affymetrix 100K GeneChip) associations with systolic (SBP) and diastolic (DBP) BP at a single examination in 1971–1975 (n = 1260), at a recent examination in 1998–2001 (n = 1233), and long-term averaged SBP and DBP from 1971–2001 (n = 1327, mean age 52 years, 54% women) and with arterial stiffness measured by arterial tonometry (carotid-femoral and carotid-brachial pulse wave velocity, forward and reflected pressure wave amplitude, and mean arterial pressure; 1998–2001, n = 644). In primary analyses we used generalized estimating equations in models for an additive genetic effect to test associations between SNPs and phenotypes of interest using multivariable-adjusted residuals. A total of 70,987 autosomal SNPs with minor allele frequency ≥ 0.10, genotype call rate ≥ 0.80, and Hardy-Weinberg equilibrium p ≥ 0.001 were analyzed. We also tested for association of 69 SNPs in six renin-angiotensin-aldosterone pathway genes with BP and arterial stiffness phenotypes as part of a candidate gene search.

Results

In the primary analyses, none of the associations attained genome-wide significance. For the six BP phenotypes, seven SNPs yielded p values < 10^-5. The lowest p-values for SBP and DBP respectively were rs10493340 (p = 1.7 × 10^-6) and rs1963982 (p = 3.3 × 10^-6). For the five tonometry phenotypes, five SNPs had p values < 10^-5; lowest p-values were for reflected wave (rs6063312, p = 2.1 × 10^-6) and carotid-brachial pulse wave velocity (rs770189, p = 2.5 × 10^-6) in MEF2C, a regulator of cardiac morphogenesis. We found only weak association of SNPs in the renin-angiotensin-aldosterone pathway with BP or arterial stiffness.

Conclusion

These results of genome-wide association testing for blood pressure and arterial stiffness phenotypes in an unselected community-based sample of adults may aid in the identification of the genetic basis of hypertension and arterial disease, help identify high risk individuals, and guide novel therapies for hypertension. Additional studies are needed to replicate any associations identified in these analyses.

     

Framingham Heart Study 100K Project: genome-wide associations for blood pressure and arterial stiffness

Background

Genes implicated in common complex disorders such as obesity, type 2 diabetes mellitus (T2DM) or cardiovascular diseases are not disease specific, since clinically related disorders also share genetic components. Cysteine protease Calpain 10 (CAPN10) has been associated with T2DM, hypertension, hypercholesterolemia, increased body mass index (BMI) and polycystic ovary syndrome (PCOS), a reproductive disorder of women in which isunlin resistance seems to play a pathogenic role. The calpain 5 gene (CAPN5) encodes a protein homologue of CAPN10. CAPN5 has been previously associated with PCOS by our group. In this new study, we have analysed the association of four CAPN5 gene variants(rs948976A>G, rs4945140G>A, rs2233546C>T and rs2233549G>A) with several cardiovascular risk factors related to metabolic syndrome in general population.

Methods

Anthropometric measurements, blood pressure, insulin, glucose and lipid profiles were determined in 606 individuals randomly chosen from a cross-sectional population-based epidemiological survey in the province of Segovia in Central Spain (Castille), recruited to investigate the prevalence of anthropometric and physiological parameters related to obesity and other components of the metabolic syndrome. Genotypes at the four polymorphic loci in CAPN5 gene were detected by polymerase chain reaction (PCR).

Results

Genotype association analysis was significant for BMI (p ≤ 0.041), diastolic blood pressure (p = 0.015) and HDL-cholesterol levels (p = 0.025). Different CAPN5 haplotypes were also associated with diastolic blood pressure (DBP) (0.0005 ≤ p ≤ 0.006) and total cholesterol levels (0.001 ≤ p ≤ 0.029). In addition, the AACA haplotype, over-represented in obese individuals, is also more frequent in individuals with metabolic syndrome defined by ATPIII criteria (p = 0.029).

Conclusion

As its homologue CAPN10, CAPN5 seems to influence traits related to increased risk for cardiovascular diseases. Our results also may suggest CAPN5 as a candidate gene for metabolic syndrome.