Larry D Atwood

Boston University, Boston, Massachusetts, United States

Are you Larry D Atwood?

Claim your profile

Publications (80)652.83 Total impact

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background The GIANT consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio adjusted for BMI (WHR). These loci are wide and narrowing the signals remains necessary.ResultsTwelve of 14 loci identified in GIANT EA samples retained strong associations with WHR in our joint EA/AA analysis (log-Bayes factor>6.1). Trans-ethnic analyses at five loci (TBX15-WARS2, LYPLAL1, ADAMTS9, LY86 and ITPR2-SSPN) substantially narrowed the signals to smaller sets of variants, some of which are in regions that have evidence of regulatory activity.Conclusion By leveraging varying linkage disequilibrium structures across different populations, SNPs with strong signals and narrower credible sets from trans-ethnic meta-analysis of central obesity provide more precise localizations of potential functional variants and suggest a possible regulatory role.Methods Meta-analysis results for WHR were obtained from 77,167 EA participants from GIANT and 23,564 African Ancestry (AA) participants from the African Ancestry Anthropometry Genetics Consortium. For fine mapping we interrogated SNPs within ±250 kb flanking regions of 14 previously reported index SNPs from loci discovered in EA populations by performing trans-ethnic meta-analysis of results from the EA and AA meta-analyses. We applied a Bayesian approach that leverages allelic heterogeneity across populations to combine meta-analysis results and aids in fine-mapping shared variants at these locations. We annotated variants using information from the ENCODE Consortium and Roadmap Epigenomics Project to prioritize variants for possible functionality.
    Human Molecular Genetics 04/2014; DOI:10.1093/hmg/ddu183 · 6.68 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Genetic loci forbodymassindex (BMI) in adolescenceandyoungadulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10-8) near FTO (P = 3.72 × 10-23), TMEM18 (P = 3.24 × 10-17), MC4R (P = 4.41 × 10-11), TNNI3K (P = 4.32 × 10-9), SEC16B (P = 6.24 × 10-8), GNPDA2 (P = 1.11 × 10-8) and POMC (P = 4.94 × 1028) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10-5 after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18-90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages. © The Author 2013. Published by Oxford University Press. All rights reserved.
    Human Molecular Genetics 09/2013; 22(17):3597-3607. DOI:10.1093/hmg/ddt205 · 6.68 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10-11) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10-10). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10-8). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10-7), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.
    Nature Genetics 04/2013; DOI:10.1038/ng.2608 · 29.65 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Recent genetic association studies have made progress in uncovering components of the genetic architecture of the body mass index (BMI). We used the ITMAT-Broad-Candidate Gene Association Resource (CARe) (IBC) array comprising up to 49 320 single nucleotide polymorphisms (SNPs) across ∼2100 metabolic and cardiovascular-related loci to genotype up to 108 912 individuals of European ancestry (EA), African-Americans, Hispanics and East Asians, from 46 studies, to provide additional insight into SNPs underpinning BMI. We used a five-phase study design: Phase I focused on meta-analysis of EA studies providing individual level genotype data; Phase II performed a replication of cohorts providing summary level EA data; Phase III meta-analyzed results from the first two phases; associated SNPs from Phase III were used for replication in Phase IV; finally in Phase V, a multi-ethnic meta-analysis of all samples from four ethnicities was performed. At an array-wide significance (P < 2.40E-06), we identify novel BMI associations in loci translocase of outer mitochondrial membrane 40 homolog (yeast) - apolipoprotein E - apolipoprotein C-I (TOMM40-APOE-APOC1) (rs2075650, P = 2.95E-10), sterol regulatory element binding transcription factor 2 (SREBF2, rs5996074, P = 9.43E-07) and neurotrophic tyrosine kinase, receptor, type 2 [NTRK2, a brain-derived neurotrophic factor (BDNF) receptor gene, rs1211166, P = 1.04E-06] in the Phase IV meta-analysis. Of 10 loci with previous evidence for BMI association represented on the IBC array, eight were replicated, with the remaining two showing nominal significance. Conditional analyses revealed two independent BMI-associated signals in BDNF and melanocortin 4 receptor (MC4R) regions. Of the 11 array-wide significant SNPs, three are associated with gene expression levels in both primary B-cells and monocytes; with rs4788099 in SH2B adaptor protein 1 (SH2B1) notably being associated with the expression of multiple genes in cis. These multi-ethnic meta-analyses expand our knowledge of BMI genetics.
    Human Molecular Genetics 01/2013; 22(1):184-201. DOI:10.1093/hmg/dds396 · 6.68 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
    Nature 09/2012; 490(7419):267-72. DOI:10.1038/nature11401 · 42.35 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Myopia is a complex genetic disorder and a common cause of visual impairment among working age adults. Genome-wide association studies have identified susceptibility loci on chromosomes 15q14 and 15q25 in Caucasian populations of European ancestry. Here, we present a confirmation and meta-analysis study in which we assessed whether these two loci are also associated with myopia in other populations. The study population comprised 31 cohorts from the Consortium of Refractive Error and Myopia (CREAM) representing 4 different continents with 55,177 individuals; 42,845 Caucasians and 12,332 Asians. We performed a meta-analysis of 14 single nucleotide polymorphisms (SNPs) on 15q14 and 5 SNPs on 15q25 using linear regression analysis with spherical equivalent as a quantitative outcome, adjusted for age and sex. We calculated the odds ratio (OR) of myopia versus hyperopia for carriers of the top-SNP alleles using a fixed effects meta-analysis. At locus 15q14, all SNPs were significantly replicated, with the lowest P value 3.87 × 10(-12) for SNP rs634990 in Caucasians, and 9.65 × 10(-4) for rs8032019 in Asians. The overall meta-analysis provided P value 9.20 × 10(-23) for the top SNP rs634990. The risk of myopia versus hyperopia was OR 1.88 (95 % CI 1.64, 2.16, P < 0.001) for homozygous carriers of the risk allele at the top SNP rs634990, and OR 1.33 (95 % CI 1.19, 1.49, P < 0.001) for heterozygous carriers. SNPs at locus 15q25 did not replicate significantly (P value 5.81 × 10(-2) for top SNP rs939661). We conclude that common variants at chromosome 15q14 influence susceptibility for myopia in Caucasian and Asian populations world-wide.
    Human Genetics 06/2012; 131(9):1467-80. DOI:10.1007/s00439-012-1176-0 · 4.52 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: [This corrects the article on p. e1002298 in vol. 7.].
    PLoS Genetics 11/2011; 7(11). DOI:10.1371/annotation/58c67154-3f10-4155-9085-dcd6e3689008 · 8.17 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.
    Nature Genetics 11/2011; 43(11):1131-8. DOI:10.1038/ng.970 · 29.65 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Adult height is a classic polygenic trait of high heritability (h(2) approximately 0.8). More than 180 single nucleotide polymorphisms (SNPs), identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain approximately10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA) results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P = 3.4×10(-12) and 2p14-rs4315565, P = 1.2×10(-8)). As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry (P = 1.7×10(-4) for overall replication). Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs (P<0.01). Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits.
    PLoS Genetics 10/2011; 7(10):e1002298. DOI:10.1371/journal.pgen.1002298 · 8.17 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: White matter hyperintensities (WMHs) detectable by magnetic resonance imaging are part of the spectrum of vascular injury associated with aging of the brain and are thought to reflect ischemic damage to the small deep cerebral vessels. WMHs are associated with an increased risk of cognitive and motor dysfunction, dementia, depression, and stroke. Despite a significant heritability, few genetic loci influencing WMH burden have been identified. We performed a meta-analysis of genome-wide association studies (GWASs) for WMH burden in 9,361 stroke-free individuals of European descent from 7 community-based cohorts. Significant findings were tested for replication in 3,024 individuals from 2 additional cohorts. We identified 6 novel risk-associated single nucleotide polymorphisms (SNPs) in 1 locus on chromosome 17q25 encompassing 6 known genes including WBP2, TRIM65, TRIM47, MRPL38, FBF1, and ACOX1. The most significant association was for rs3744028 (p(discovery) = 4.0 × 10(-9) ; p(replication) = 1.3 × 10(-7) ; p(combined) = 4.0 × 10(-15) ). Other SNPs in this region also reaching genome-wide significance were rs9894383 (p = 5.3 × 10(-9) ), rs11869977 (p = 5.7 × 10(-9) ), rs936393 (p = 6.8 × 10(-9) ), rs3744017 (p = 7.3 × 10(-9) ), and rs1055129 (p = 4.1 × 10(-8) ). Variant alleles at these loci conferred a small increase in WMH burden (4-8% of the overall mean WMH burden in the sample). This large GWAS of WMH burden in community-based cohorts of individuals of European descent identifies a novel locus on chromosome 17. Further characterization of this locus may provide novel insights into the pathogenesis of cerebral WMH.
    Annals of Neurology 06/2011; 69(6):928-39. DOI:10.1002/ana.22403 · 11.91 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.
    The American Journal of Human Genetics 01/2011; 88(1):6-18. DOI:10.1016/j.ajhg.2010.11.007 · 10.99 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10−9 to P = 1.8 × 10−40) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10−3 to P = 1.2 × 10−13). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
    Nature Genetics 01/2011; 43(11):1164. DOI:10.1038/ng1111-1164a · 29.65 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 x 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 x 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 x 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.
    The American Journal of Human Genetics 01/2011; 88(1):6-18. · 10.99 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
    Nature Genetics 10/2010; 42(11):949-60. DOI:10.1038/ng.685 · 29.65 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
    Nature Genetics 10/2010; 42(11):937-48. DOI:10.1038/ng.686 · 29.65 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
    Nature 09/2010; 467(7317):832-8. DOI:10.1038/nature09410 · 42.35 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Genome-wide association (GWA) studies that use population-based association approaches may identify spurious associations in the presence of population admixture. In this paper, we propose a novel three-stage approach that is computationally efficient and robust to population admixture and more powerful than the family-based association test (FBAT) for GWA studies with family data.We propose a three-stage approach for GWA studies with family data. The first stage is to perform linear regression ignoring phenotypic correlations among family members. SNPs with a first stage p-value below a liberal cut-off (e.g. 0.1) are then analyzed in the second stage that employs a linear mixed effects (LME) model that accounts for within family correlations. Next, SNPs that reach genome-wide significance (e.g. 10-6 for 34,625 genotyped SNPs in this paper) are analyzed in the third stage using FBAT, with correction of multiple testing only for SNPs that enter the third stage. Simulations are performed to evaluate type I error and power of the proposed method compared to LME adjusting for 10 principal components (PC) of the genotype data. We also apply the three-stage approach to the GWA analyses of uric acid in Framingham Heart Study's SNP Health Association Resource (SHARe) project. Our simulations show that whether or not population admixture is present, the three-stage approach has no inflated type I error. In terms of power, using LME adjusting PC is only slightly more powerful than the three-stage approach. When applied to the GWA analyses of uric acid in the SHARe project of FHS, the three-stage approach successfully identified and confirmed three SNPs previously reported as genome-wide significant signals. For GWA analyses of quantitative traits with family data, our three-stage approach provides another appealing solution to population admixture, in addition to LME adjusting for genetic PC.
    BMC Genetics 05/2010; 11:40. DOI:10.1186/1471-2156-11-40 · 2.36 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Extensive efforts have been aimed at understanding the genetic underpinnings of complex diseases that affect humans. Numerous genome-wide association studies have assessed the association of genes with human disease, including the Framingham Heart Study (FHS), which genotyped 550,000 SNPs in 9,000 participants. The success of such efforts requires high rates of consent by participants, which is dependent on ethical oversight, communications, and trust between research participants and investigators. To study this we calculated percentages of participants who consented to collection of DNA and to various uses of their genetic information in two FHS cohorts between 2002 and 2009. The data included rates of consent for providing a DNA sample, creating an immortalized cell line, conducting research on various genetic conditions including those that might be considered sensitive, and for notifying participants of clinically significant genetic findings were above 95%. Only with regard to granting permission to share DNA or genetic findings with for-profit companies was the consent rate below 95%. We concluded that the FHS has maintained high rates of retention and consent for genetic research that has provided the scientific freedom to establish collaborations and address a broad range of research questions. We speculate that our high rates of consent have been achieved by establishing frequent and open communications with participants that highlight extensive oversight procedures. Our approach to maintaining high consent rates via ethical oversight of genetic research and communication with study participants is summarized in this report and should be of help to other studies engaged in similar types of research. Published 2010 Wiley-Liss, Inc.
    American Journal of Medical Genetics Part A 05/2010; 152A(5):1250-6. DOI:10.1002/ajmg.a.33377 · 2.05 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Previous studies examining genetic associations with MRI-defined brain infarct have yielded inconsistent findings. We investigated genetic variation underlying covert MRI infarct in persons without histories of transient ischemic attack or stroke. We performed meta-analysis of genome-wide association studies of white participants in 6 studies comprising the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Using 2.2 million genotyped and imputed single nucleotide polymorphisms, each study performed cross-sectional genome-wide association analysis of MRI infarct using age- and sex-adjusted logistic regression models. Study-specific findings were combined in an inverse-variance-weighted meta-analysis, including 9401 participants with mean age 69.7 (19.4% of whom had >or=1 MRI infarct). The most significant association was found with rs2208454 (minor allele frequency, 20%), located in intron 3 of MACRO domain containing 2 gene and in the downstream region of fibronectin leucine-rich transmembrane protein 3 gene. Each copy of the minor allele was associated with lower risk of MRI infarcts (odds ratio, 0.76; 95% confidence interval, 0.68-0.84; P=4.64x10(-7)). Highly suggestive associations (P<1.0x10(-5)) were also found for 22 other single nucleotide polymorphisms in linkage disequilibrium (r(2)>0.64) with rs2208454. The association with rs2208454 did not replicate in independent samples of 1822 white and 644 black participants, although 4 single nucleotide polymorphisms within 200 kb from rs2208454 were associated with MRI infarcts in the black population sample. This first community-based, genome-wide association study on covert MRI infarcts uncovered novel associations. Although replication of the association with top single nucleotide polymorphisms failed, possibly because of insufficient power, results in the black population sample are encouraging, and further efforts at replication are needed.
    Stroke 02/2010; 41(2):210-7. DOI:10.1161/STROKEAHA.109.569194 · 6.02 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: ABSTRACT : Genetic Analysis Workshop 16 (GAW16) Problem 2 presented data from the Framingham Heart Study (FHS), an observational, prospective study of risk factors for cardiovascular disease begun in 1948. Data have been collected in three generations of family participants in the study and the data presented for GAW16 included phenotype data from all three generations, with four examinations of data collected repeatedly for the first two generations. The trait data consisted of information on blood pressure, hypertension treatment, lipid levels, diabetes and blood glucose, smoking, alcohol consumed, weight, and coronary heart disease incidence. Additionally, genotype data obtained through a genome-wide scan (FHS SHARe) of 550,000 single-nucleotide polymorphisms from Affymetrix chips were included with the GAW16 data. The genotype data were also used for GAW16 Problem 3, where simulated phenotypes were generated using the actual FHS genotypes. These data served to provide investigators with a rich resource to study the behavior of genome-wide scans with longitudinally collected family data and to develop and apply new procedures.
    BMC proceedings 12/2009; 3 Suppl 7(Suppl 7):S3. DOI:10.1186/1753-6561-3-s7-s3

Publication Stats

5k Citations
652.83 Total Impact Points

Institutions

  • 2003–2013
    • Boston University
      • • Department of Medicine
      • • Department of Neurology
      • • Department of Biostatistics
      Boston, Massachusetts, United States
  • 2007–2009
    • National Heart, Lung, and Blood Institute
      • Division of Cardiovascular Sciences (DCVS)
      Maryland, United States
  • 2003–2007
    • Beverly Hospital, Boston MA
      Beverly, Massachusetts, United States
  • 2002–2007
    • University of Massachusetts Boston
      • Clinical Epidemiology Research and Training Unit
      Boston, Massachusetts, United States
  • 2004
    • The Children's Hospital of Philadelphia
      Filadelfia, Pennsylvania, United States
    • University of Pittsburgh
      • Department of Human Genetics
      Pittsburgh, PA, United States
  • 1997–2002
    • University of Minnesota Duluth
      • Laboratory Medicine and Pathology
      Duluth, Minnesota, United States
  • 2001
    • University of Minnesota Medical Center, Fairview
      Minneapolis, Minnesota, United States
  • 1995
    • University of Texas at San Antonio
      San Antonio, Texas, United States
  • 1993–1995
    • Southwest Foundation For Biomedical Research
      San Antonio, Texas, United States