James B Meigs

Harvard University, Cambridge, Massachusetts, United States

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Publications (493)3656.43 Total impact

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    ABSTRACT: Insulin-like growth factor 1 (IGF-I) has been associated with insulin resistance. Genome-wide association studies (GWASs) of fasting insulin (FI) identified single-nucleotide variants (SNVs) near the IGF1 gene, raising two hypotheses: (1) these associations are mediated by IGF-I levels and (2) these noncoding variants either tag other functional variants in the region or are directly functional. In our study, analyses including 5141 individuals from population-based cohorts suggest that FI associations near IGF1 are not mediated by IGF-I. Analyses of targeted sequencing data in 3539 individuals reveal a large number of novel rare variants at the IGF1 locus and show a FI association with a subset of rare nonsynonymous variants (PSKAT=5.7 × 10(-4)). Conditional analyses suggest that this association is partly explained by the GWAS signal and the presence of a residual independent rare variant effect (Pconditional=0.019). Annotation using ENCODE data suggests that the GWAS variants may have a direct functional role in insulin biology. In conclusion, our study provides insight into variation present at the IGF1 locus and into the genetic architecture underlying FI levels, suggesting that FI associations of SNVs near IGF1 are not mediated by IGF-I and suggesting a role for both rare nonsynonymous and common functional variants in insulin biology.European Journal of Human Genetics advance online publication, 10 February 2016; doi:10.1038/ejhg.2016.4.
    No preview · Article · Feb 2016 · European journal of human genetics: EJHG
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    ABSTRACT: Although plasminogen activator inhibitor (PAI-1) plays a key regulatory role in fibrinolysis, it has not been clearly shown to independently predict cardiovascular disease (CVD) among individuals without prior CVD. We investigated, in the Framingham Heart Study offspring cohort, whether PAI-1 predicted CVD risk among individuals without prior CVD.
    No preview · Article · Feb 2016 · Thrombosis Research
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    ABSTRACT: Waist-to-hip ratio (WHR), a relative comparison of waist and hip circumferences, is an easily accessible measurement of body fat distribution, in particular central abdominal fat. A high WHR indicates more intra-abdominal fat deposition and is an established risk factor for cardiovascular disease and type 2 diabetes. Recent genome-wide association studies have identified numerous common genetic loci influencing WHR, but the contributions of rare variants have not been previously reported. We investigated rare variant associations with WHR in 1510 European-American and 1186 African-American women from the National Heart, Lung, and Blood Institute-Exome Sequencing Project. Association analysis was performed on the gene level using several rare variant association methods. The strongest association was observed for rare variants in IKBKB (P=4.0 × 10(-8)) in European-Americans, where rare variants in this gene are predicted to decrease WHRs. The activation of the IKBKB gene is involved in inflammatory processes and insulin resistance, which may affect normal food intake and body weight and shape. Meanwhile, aggregation of rare variants in COBLL1, previously found to harbor common variants associated with WHR and fasting insulin, were nominally associated (P=2.23 × 10(-4)) with higher WHR in European-Americans. However, these significant results are not shared between African-Americans and European-Americans that may be due to differences in the allelic architecture of the two populations and the small sample sizes. Our study indicates that the combined effect of rare variants contribute to the inter-individual variation in fat distribution through the regulation of insulin response.European Journal of Human Genetics advance online publication, 13 January 2016; doi:10.1038/ejhg.2015.272.
    Full-text · Article · Jan 2016 · European journal of human genetics: EJHG
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    ABSTRACT: Context: Though clinical trials have shown that hypoglycemia is associated with coronary artery disease (CAD), little is known whether hypoglycemia is a CAD risk factor in primary care. Objective: We sought to determine whether prior hypoglycemia was associated with incident CAD, and whether this association differed in patients of different underlying vascular risk. Design, setting and participants: This is a longitudinal cohort study of diabetes patients without CAD before 1/1/2006 (N=9,173) followed at an academic network of 13 primary care practices from 1/1/2006 to 6/30/2012. Hypoglycemic events before 1/1/2006 were identified via ICD-9 codes from emergency department, inpatient and outpatient visits. Main outcome measure: Patients were followed until incident CAD or 6/30/2012. Cox regression with time interaction was used to determine the association between hypoglycemia and CAD (significance set at P ≤0.05). We then tested the association among high vascular-risk patients (age≥55 years, Hemoglobin A1c≥7.5%, ≥2 risk factors [dyslipidemia, hypertension or obesity]), a subset of high vascular-risk patients aged ≥65 years, and the remaining patients with lower vascular risk. Results: Three percent of patients (N=285) had prior hypoglycemia. Hypoglycemia was associated with a twofold CAD risk [HR 2.15 (95%CI 1.24-3.74)], adjusting for time interaction and vascular risk factors. Among high vascular-risk patients, the risk was threefold [3.01 (1.15-7.91), N=1,823 (20% of cohort)], and over fourfold [4.62 (1.65-12.9), N=996] in the subset aged ≥65 years. No association was found in the remaining 80% of the cohort with lower vascular risk. Conclusions: Prior hypoglycemia was associated with CAD among high vascular-risk patients. Hypoglycemia may not be a CAD risk factor for the majority of primary care patients with lower underlying vascular risk.
    No preview · Article · Dec 2015 · The Journal of Clinical Endocrinology and Metabolism
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    Full-text · Dataset · Nov 2015
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    ABSTRACT: We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
    Full-text · Article · Nov 2015 · Nature Genetics
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    ABSTRACT: Loci identified in genome-wide association studies (GWAS) of cardio-metabolic traits account for a small proportion of the traits' heritability. To date, most association studies have not considered parent-of-origin effects (POEs). Here we report investigation of POEs on adiposity and glycemic traits in young adults. The Jerusalem Perinatal Family Follow-Up Study (JPS), comprising 1250 young adults and their mothers was used for discovery. Focusing on 18 genes identified by previous GWAS as associated with cardio-metabolic traits, we used linear regression to examine the associations of maternally- and paternally-derived offspring minor alleles with body mass index (BMI), waist circumference (WC), fasting glucose and insulin. We replicated and meta-analyzed JPS findings in individuals of European ancestry aged ≤50 belonging to pedigrees from the Framingham Heart Study, Family Heart Study and Erasmus Rucphen Family study (total N≅4800). We considered p<2.7x10-4 statistically significant to account for multiple testing. We identified a common coding variant in the 4th exon of APOB (rs1367117) with a significant maternally-derived effect on BMI (β = 0.8; 95%CI:0.4,1.1; p = 3.1x10-5) and WC (β = 2.7; 95%CI:1.7,3.7; p = 2.1x10-7). The corresponding paternally-derived effects were non-significant (p>0.6). Suggestive maternally-derived associations of rs1367117 were observed with fasting glucose (β = 0.9; 95%CI:0.3,1.5; p = 4.0x10-3) and insulin (ln-transformed, β = 0.06; 95%CI:0.03,0.1; p = 7.4x10-4). Bioinformatic annotation for rs1367117 revealed a variety of regulatory functions in this region in liver and adipose tissues and a 50% methylation pattern in liver only, consistent with allelic-specific methylation, which may indicate tissue-specific POE. Our findings demonstrate a maternal-specific association between a common APOB variant and adiposity, an association that was not previously detected in GWAS. These results provide evidence for the role of regulatory mechanisms, POEs specifically, in adiposity. In addition this study highlights the benefit of utilizing family studies for deciphering the genetic architecture of complex traits.
    Full-text · Article · Oct 2015 · PLoS Genetics
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    ABSTRACT: Background: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown. Objective: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus. Design: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations. Results: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance. Conclusion: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).
    Full-text · Article · Sep 2015 · American Journal of Clinical Nutrition
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    ABSTRACT: Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
    Full-text · Article · Jul 2015 · Nature
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    ABSTRACT: Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
    Full-text · Article · Jul 2015 · Nature

  • No preview · Conference Paper · Jun 2015
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    ABSTRACT: In observational studies, type-2 diabetes (T2D) is associated with an increased risk of coronary heart disease (CHD), yet interventional trials have shown no clear effect of glucose-lowering on CHD. Confounding may have therefore influenced these observational estimates. Here we use Mendelian randomization to obtain unconfounded estimates of the influence of T2D and fasting glucose (FG) on CHD risk. Using multiple genetic variants associated with T2D and FG, we find that risk of T2D increases CHD risk (odds ratio (OR)=1.11 (1.05-1.17), per unit increase in odds of T2D, P=8.8 × 10(-5); using data from 34,840/114,981 T2D cases/controls and 63,746/130,681 CHD cases/controls). FG in non-diabetic individuals tends to increase CHD risk (OR=1.15 (1.00-1.32), per mmol·per l, P=0.05; 133,010 non-diabetic individuals and 63,746/130,681 CHD cases/controls). These findings provide evidence supporting a causal relationship between T2D and CHD and suggest that long-term trials may be required to discern the effects of T2D therapies on CHD risk.
    Full-text · Article · May 2015 · Nature Communications
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    ABSTRACT: -Type 2 diabetes (T2D) and cardiovascular disease (CVD) share risk factors and subclinical atherosclerosis (SCA) predicts events in those with and without diabetes. T2D genetic risk may predict both T2D and SCA. We hypothesized that greater T2D genetic risk is associated with higher extent of SCA. -In a cross-sectional analysis including up to 9,210 European Americans, 3,773 African Americans, 1,446 Hispanic Americans and 773 Chinese Americans without known CVD and enrolled in the FHS, CARDIA, MESA and GENOA studies, we tested a 62 T2D-loci genetic risk score (GRS62) for association with measures of SCA, including coronary artery (CACS) or abdominal aortic calcium score, common (CCA-IMT) and internal carotid artery intima-media thickness, and ankle-brachial index (ABI). We used ancestry-stratified linear regression models, with random effects accounting for family relatedness when appropriate, applying a genetic-only (adjusted for sex) and a full SCA risk factors adjusted model (significance = p<0.01 = 0.05/5, number of traits analyzed). An inverse association with CACS in MESA Europeans (fully-adjusted p=0.004) and with CCA-IMT in FHS (p=0.009) was not confirmed in other study cohorts, either separately or in meta-analysis. Secondary analyses showed no consistent associations with β-cell and insulin resistance sub-GRS in FHS and CARDIA. -SCA does not have a major genetic component linked to a burden of 62 T2D loci identified by large genome-wide association studies. A shared T2D-SCA genetic basis, if any, might become apparent from better functional information about both T2D and CVD risk loci.
    Full-text · Article · Mar 2015 · Circulation Cardiovascular Genetics
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    ABSTRACT: Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
    Full-text · Article · Jan 2015 · Nature Communications
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    ABSTRACT: Type 2 diabetes mellitus in parents is a strong determinant of diabetes risk in their offspring. We hypothesise that offspring diabetes risk associated with parental diabetes is mediated by metabolic risk factors. We studied initially non-diabetic participants of the Framingham Offspring Study. Metabolic risk was estimated using beta cell corrected insulin response (CIR), HOMA-IR or a count of metabolic syndrome components (metabolic syndrome score [MSS]). Dietary risk and physical activity were estimated using questionnaire responses. Genetic risk score (GRS) was estimated as the count of 62 type 2 diabetes risk alleles. The outcome of incident diabetes in offspring was examined across levels of parental diabetes exposure, accounting for sibling correlation and adjusting for age, sex and putative mediators. The proportion mediated was estimated by comparing regression coefficients for parental diabetes with (β adj) and without (β unadj) adjustments for CIR, HOMA-IR, MSS and GRS (percentage mediated = 1 - β adj / β unadj). Metabolic factors mediated 11% of offspring diabetes risk associated with parental diabetes, corresponding to a reduction in OR per diabetic parent from 2.13 to 1.96. GRS mediated 9% of risk, corresponding to a reduction in OR per diabetic parent from 2.13 to 1.99. Metabolic risk factors partially mediated offspring type 2 diabetes risk conferred by parental diabetes to a similar magnitude as genetic risk. However, a substantial proportion of offspring diabetes risk associated with parental diabetes remains unexplained by metabolic factors, genetic risk, diet and physical activity, suggesting that important familial influences on diabetes risk remain undiscovered.
    No preview · Article · Jan 2015 · Diabetologia
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    ABSTRACT: Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5x10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.
    Full-text · Article · Jan 2015 · PLoS Genetics
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    ABSTRACT: Increasing access to care may be insufficient to improve the health of patients with diabetes mellitus and unmet basic needs (hereinafter referred to as material need insecurities). How specific material need insecurities relate to clinical outcomes and the use of health care resources in a setting of near-universal access to health care is unclear. To determine the association of food insecurity, cost-related medication underuse, housing instability, and energy insecurity with control of diabetes mellitus and the use of health care resources. Cross-sectional data were collected from June 1, 2012, through October 31, 2013, at 1 academic primary care clinic, 2 community health centers, and 1 specialty center for the treatment of diabetes mellitus in Massachusetts. A random sample of 411 patients, stratified by clinic, consisted of adults (aged ≥21 years) with diabetes mellitus (response rate, 62.3%). The prespecified primary outcome was a composite indicator of poor diabetes control (hemoglobin A1c level, >9.0%; low-density lipoprotein cholesterol level, >100 mg/dL; or blood pressure, >140/90 mm Hg). Prespecified secondary outcomes included outpatient visits and a composite of emergency department (ED) visits and acute care hospitalizations (ED/inpatient visits). Overall, 19.1% of respondents reported food insecurity; 27.6%, cost-related medication underuse; 10.7%, housing instability; 14.1%, energy insecurity; and 39.1%, at least 1 material need insecurity. Poor diabetes control was observed in 46.0% of respondents. In multivariable models, food insecurity was associated with a greater odds of poor diabetes control (adjusted odds ratio [OR], 1.97 [95% CI, 1.58-2.47]) and increased outpatient visits (adjusted incident rate ratio [IRR], 1.19 [95% CI, 1.05-1.36]) but not increased ED/inpatient visits (IRR, 1.00 [95% CI, 0.51-1.97]). Cost-related medication underuse was associated with poor diabetes control (OR, 1.91 [95% CI, 1.35-2.70]) and increased ED/inpatient visits (IRR, 1.68 [95% CI, 1.21-2.34]) but not outpatient visits (IRR, 1.07 [95% CI, 0.95-1.21]). Housing instability (IRR, 1.31 [95% CI, 1.14-1.51]) and energy insecurity (IRR, 1.12 [95% CI, 1.00-1.25]) were associated with increased outpatient visits but not with diabetes control (OR, 1.10 [95% CI, 0.60-2.02] and OR, 1.27 [95% CI, 0.96-1.69], respectively) or with ED/inpatient visits (IRR, 1.49 [95% CI, 0.81-2.73] and IRR, 1.31 [95% CI, 0.80-2.13], respectively). An increasing number of insecurities was associated with poor diabetes control (OR for each additional need, 1.39 [95% CI, 1.18-1.63]) and increased use of health care resources (IRR for outpatient visits, 1.09 [95% CI, 1.03-1.15]; IRR for ED/inpatient visits, 1.22 [95% CI, 0.99-1.51]). Material need insecurities were common among patients with diabetes mellitus and had varying but generally adverse associations with diabetes control and the use of health care resources. Material need insecurities may be important targets for improving care of diabetes mellitus.
    No preview · Article · Dec 2014 · JAMA Internal Medicine
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    ABSTRACT: -Cardiovascular disease (CVD) reflects a highly coordinated complex of traits. Although genome-wide association studies (GWAS) have reported numerous SNPs to be associated with CVD, the role of most of these variants in disease processes remains unknown. -We built a CVD network using 1,512 SNPs associated with 21 CVD traits in GWAS (at p≤5×10(-8)) and cross-linked different traits by virtue of their shared SNP associations. We then explored whole blood gene expression in relation to these SNPs in 5,257 participants in the Framingham Heart Study. At a false discovery rate <0.05, we identified 370 cis-eQTLs (SNPs associated with altered expression of nearby genes) and 44 trans-eQTLs (SNPs associated with altered expression of remote genes). The eQTL network revealed 13 CVD-related modules. Searching for association of eQTL genes with CVD risk factors (lipids, blood pressure, fasting blood glucose, and body mass index) in the same individuals, we found examples where the expression of eQTL genes was significantly associated with these CVD phenotypes. In addition, mediation tests suggested that a subset of SNPs previously associated with CVD phenotypes in GWAS, may exert their function by altering expression of eQTL genes (e.g. LDLR, and PCSK7) that in turn may promote inter-individual variation in phenotypes. -Using a network approach to analyze CVD traits, we identified complex networks of SNP-phenotype and SNP-transcript connections. Integrating the CVD network with phenotypic data, we identified biological pathways that may provide insights into potential drug targets for treatment or prevention of CVD.
    Full-text · Article · Dec 2014 · Circulation
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    ABSTRACT: Human immunodeficiency virus (HIV) infection is associated with increased risk of myocardial infarction (MI). The use of aspirin for primary and secondary MI prevention in HIV infection has not been extensively studied. We performed a cross-sectional study of 4037 patients infected with HIV and 36 338 demographics-matched control patients in the Partners HealthCare System HIV cohort. We developed an algorithm to ascertain rates of nonepisodic acetylsalicylic acid (ASA) use using medication and electronic health record free text data. We assessed rates of ASA use among HIV-infected and HIV-uninfected (negative) patients with and without coronary heart disease (CHD). Rates of ASA use were lower among HIV-infected compared with HIV-uninfected patients (12.4% vs 15.3%, P < .001), with a relatively greater difference among patients with ≥2 CHD risk factors (22.1% vs 42.4%, P < .001). This finding was present among men and among patients in the 30-39 and 40-49 age groups. Among patients with prevalent CHD using ASA for secondary prevention, rates of ASA use were also lower among HIV-infected patients compared with HIV-uninfected patients (51.6% vs 65.4%, P < .001). Rates of ASA use were lower among HIV-infected patients compared with controls, with a greater relative difference among those with elevated CHD risk and those with known CHD. Further studies are needed to investigate the optimal strategies for ASA use among patients infected with HIV.
    Full-text · Article · Dec 2014 · Open Forum Infectious Diseases
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    ABSTRACT: Heritability measures the proportion of phenotypic variation attributable to genetic factors. In addition to a shared nuclear genetic component, a number of additional variance components, such as spousal correlation, sibship, household and maternal effects, may have strong contributions to inter-individual phenotype variation. In humans, the confounding effects of these components on heritability have not been studied thoroughly. We sought to obtain unbiased heritability estimates for complex traits in the presence of multiple variance components and also to estimate the contributions of these variance components to complex traits. We compared regression and variance component methods to estimate heritability in simulations when additional variance components existed. We then revisited heritability for several traits in Framingham Heart Study (FHS) participants. Using simulations, we found that failure to account for or misclassification of necessary variance components yielded biased heritability estimates. The direction and magnitude of the bias varied depending on a variance structure and an estimation method. Using the best fitted models to account for necessary variance components, we found that heritability estimates for most FHS traits were overestimated, ranging from 4 to 47 %, when we compared models that considered necessary variance components to models that only considered familial relationships. Spousal correlation explained 14-36 % of phenotypic variation in several anthropometric and lifestyle traits. Maternal and sibling effects also contributed to phenotypic variation, ranging from 3 to 5 % and 4 to 7 %, respectively, in several anthropometric and metabolic traits. Our findings may explain, in part, the missing heritability for some traits.
    No preview · Article · Nov 2014 · Human Genetics

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49k Citations
3,656.43 Total Impact Points

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Institutions

  • 1999-2015
    • Harvard University
      • Department of Nutrition
      Cambridge, Massachusetts, United States
  • 1996-2015
    • Massachusetts General Hospital
      • • Center for Human Genetic Research
      • • Department of Medicine
      • • Department of Psychiatry
      • • Hospital Medicine Unit
      Boston, Massachusetts, United States
  • 2013
    • University of Lausanne
      Lausanne, Vaud, Switzerland
  • 2001-2013
    • Boston University
      • Department of Medicine
      Boston, Massachusetts, United States
  • 2005-2012
    • Beverly Hospital, Boston MA
      Beverly, Massachusetts, United States
    • Uppsala University
      • Department of Public Health and Caring Sciences
      Uppsala, Uppsala, Sweden
    • German Institute of Human Nutrition
      • Department of Epidemiology
      Potsdam, Brandenburg, Germany
    • Simmons College
      • Program in Nutrition and Dietetics
      Boston, Massachusetts, United States
  • 2002-2012
    • Harvard Medical School
      • Department of Medicine
      Boston, Massachusetts, United States
    • Columbia University
      New York, New York, United States
  • 2010
    • Karolinska Institutet
      • Institutionen för medicinsk epidemiologi och biostatistik
      Solna, Stockholm, Sweden
    • McMaster University
      Hamilton, Ontario, Canada
  • 2008
    • Johns Hopkins University
      • Welch Center for Prevention, Epidemiology, and Clinical Research
      Baltimore, Maryland, United States
    • American Heart Association
      Dallas, Texas, United States
  • 2002-2008
    • Tufts University
      • Department of Medicine
      Georgia, United States
  • 2004-2007
    • University of Verona
      Verona, Veneto, Italy
  • 2006
    • Beth Israel Deaconess Medical Center
      • Division of Endocrinology, Diabetes and Metabolism
      Boston, MA, United States