Marilyn C Cornelis

Massachusetts Department of Public Health, Boston, Massachusetts, United States

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Publications (106)1046.34 Total impact

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    Peter K. Joshi, Tonu Esko, Hannele Mattsson, Niina Eklund, Ilaria Gandin, Teresa Nutile, Anne U. Jackson, Claudia Schurmann, Albert V. Smith, Weihua Zhang, [...], Vilmundur Gudnason, Atsushi Takahashi, John C. Chambers, Jaspal S. Kooner, David P. Strachan, Harry Campbell, Joel N. Hirschhorn, Markus Perola, Ozren Polašek, James F. Wilson
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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.
    Nature 07/2015; DOI:10.1038/nature14618 · 42.35 Impact Factor
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    ABSTRACT: b>Background: The observational relationship between obesity and periodontitis is widely known, yet causal evidence is lacking. Our objective was to investigate causal associations between periodontitis and body mass index (BMI). Methods: We performed Mendelian randomization analyses with BMI-associated loci combined in a genetic risk score (GRS) as the instrument for BMI. All analyses were conducted within the Gene-Lifestyle Interactions and Dental Endpoints (GLIDE) Consortium in 13 studies from Europe and the USA, including 49 066 participants with clinically assessed (seven studies, 42.1% of participants) and self-reported (six studies, 57.9% of participants) periodontitis and genotype data (17 672/31 394 with/without periodontitis); 68 761 participants with BMI and genotype data; and 57 871 participants (18 881/38 990 with/without periodontitis) with data on BMI and periodontitis. Results: In the observational meta-analysis of all participants, the pooled crude observational odds ratio (OR) for periodontitis was 1.13 [95% confidence interval (CI): 1.03, 1.24] per standard deviation increase of BMI. Controlling for potential confounders attenuated this estimate (OR = 1.08; 95% CI:1.03, 1.12). For clinically assessed periodontitis, corresponding ORs were 1.25 (95% CI: 1.10, 1.42) and 1.13 (95% CI: 1.10, 1.17), respectively. In the genetic association meta-analysis, the OR for periodontitis was 1.01 (95% CI: 0.99, 1.03) per GRS unit (per one effect allele) in all participants and 1.00 (95% CI: 0.97, 1.03) in participants with clinically assessed periodontitis. The instrumental variable meta-analysis of all participants yielded an OR of 1.05 (95% CI: 0.80, 1.38) per BMI standard deviation, and 0.90 (95% CI: 0.56, 1.46) in participants with clinical data. Conclusions: Our study does not support total adiposity as a causal risk factor for periodontitis, as the point estimate is very close to the null in the causal inference analysis, with wide confidence intervals.
    International Journal of Epidemiology 06/2015; DOI:10.1093/ije/dyv075 · 9.20 Impact Factor
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    ABSTRACT: Mendelian Randomization studies, which use genetic instrumental variables (IVs) as quasi-experiments to estimate causal effects, report inconsistent findings regarding effects of body mass index (BMI) on mental health. We used genetic IV to estimate effects of BMI on depression and evaluated validity of a commonly used IV. Female Nurse's Health Study participants (n = 6989, average age 56.4, [Standard Deviation 6.91] years at first depression assessment) self-reported BMI, which was averaged across eight reports prior to depression assessment (mean = 24.96, SD 4.50). Genetic instruments included fat mass and obesity-associated protein (FTO) alleles, melanocortin receptor 4 (MC4R) alleles, and polygenic risk scores based on 32 established polymorphisms for BMI. Depression was assessed using multiple symptom measures, scaled to the Geriatric Depression Scale 15, averaged across up to 7 biennial waves. We used over-identification tests to assess the validity of genetic IVs. In conventional estimates, each additional BMI point predicted 0.024 (95% Confidence Interval (CI): 0.020-0.029) higher average depression scores. Genetic IV estimates were not significant when based on FTO (beta: 0.064, CI: -0.014, 0.142), MC4R (beta: 0.005, CI: -0.146, 0.156), polygenic score excluding FTO (beta = -0.003, 95%-CI -0.051, 0.045), or mechanism-specific scores. The over-identification test comparing IV estimates based on FTO to estimates based on the polygenic score excluding FTO rejected equality of estimated effects (P = 0.014). Results provide no evidence against a null effect of BMI on depression and call into question validity of FTO as an instrument for BMI in Mendelian Randomization studies. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
    American Journal of Medical Genetics Part B Neuropsychiatric Genetics 02/2015; 168(2). DOI:10.1002/ajmg.b.32286 · 3.27 Impact Factor
  • Marilyn C Cornelis
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    ABSTRACT: Coffee is one of the most widely consumed beverages in the world and has been associated with many health conditions. This review examines the limitations of the classic epidemiological approach to studies of coffee and health, and describes the progress in systems epidemiology of coffee and its correlated constituent, caffeine. Implications and applications of this growing body of knowledge are also discussed. Population-based metabolomic studies of coffee replicate coffee-metabolite correlations observed in clinical settings but have also identified novel metabolites of coffee response, such as specific sphingomyelin derivatives and acylcarnitines. Genome-wide analyses of self-reported coffee and caffeine intake and serum levels of caffeine support an overwhelming role for caffeine in modulating the coffee consumption behavior. Interindividual variation in the physiological exposure or response to any of the many chemicals present in coffee may alter the persistence and magnitude of their effects. It is thus imperative that future studies of coffee and health account for this variation. Systems epidemiological approaches promise to inform causality, parse the constituents of coffee responsible for health effects, and identify the subgroups most likely to benefit from increasing or decreasing coffee consumption.
    Current Opinion in Lipidology 02/2015; 26(1):20-9. DOI:10.1097/MOL.0000000000000143 · 5.80 Impact Factor
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    ABSTRACT: Family history of diabetes is a major risk factor for type 2 diabetes (T2D), but whether this association derives from shared genetic or environmental factors is unclear. To address this question, we developed a statistical framework that models four components of variance, including known and unknown genetic and environmental factors, using a liability threshold model. Focusing on parental history, we simulated case-control studies with two first-degree relatives for each individual, assuming 50 % genetic similarity and a range of values of environmental similarity. By comparing the association of parental history with T2D in our simulations to case-control studies of T2D nested in the Nurses' Health Study and Health Professionals Follow-up Study, we estimate that first-degree relatives have a correlation of 23 % (95 % CI 15-27 %) in their environmental contribution to T2D liability and that this shared environment is responsible for 32 % (95 % CI 24-36 %) of the association between parental history and T2D, with the remainder due to shared genetics. Estimates are robust to varying model parameter values and our framework can be extended to different definitions of family history. In conclusion, we find that the association between parental history and T2D derives from predominately genetic but also environmental effects.
    Human Genetics 12/2014; 134(2). DOI:10.1007/s00439-014-1519-0 · 4.52 Impact Factor
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    ABSTRACT: Usual sleep duration is a heritable trait correlated with psychiatric morbidity, cardiometabolic disease and mortality, although little is known about the genetic variants influencing this trait. A genome-wide association study (GWAS) of usual sleep duration was conducted using 18 population-based cohorts totaling 47 180 individuals of European ancestry. Genome-wide significant association was identified at two loci. The strongest is located on chromosome 2, in an intergenic region 35- to 80-kb upstream from the thyroid-specific transcription factor PAX8 (lowest P=1.1 × 10(-9)). This finding was replicated in an African-American sample of 4771 individuals (lowest P=9.3 × 10(-4)). The strongest combined association was at rs1823125 (P=1.5 × 10(-10), minor allele frequency 0.26 in the discovery sample, 0.12 in the replication sample), with each copy of the minor allele associated with a sleep duration 3.1 min longer per night. The alleles associated with longer sleep duration were associated in previous GWAS with a more favorable metabolic profile and a lower risk of attention deficit hyperactivity disorder. Understanding the mechanisms underlying these associations may help elucidate biological mechanisms influencing sleep duration and its association with psychiatric, metabolic and cardiovascular disease.Molecular Psychiatry advance online publication, 2 December 2014; doi:10.1038/mp.2014.133.
    Molecular Psychiatry 12/2014; DOI:10.1038/mp.2014.133 · 15.15 Impact Factor
  • Marilyn C. Cornelis
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    ABSTRACT: Type 2 diabetes (T2D) is thought to arise from an interaction between susceptibility genes and a diabetogenic environment. This review summarizes progress pertaining specifically to gene-diet interactions. Recent efforts have been population-based and have focused on established genetic and dietary risk factors for T2D. TCF7L2 × carbohydrate-quality and IRS1 × macronutrient-composition interactions are promising factors, but most studies of gene-diet interactions are conflicting or need follow-up. T2D genetic risk scores are powerful predictors of developing T2D, but whether they can be combined with dietary risk factors merits further study. Lack of statistical power, imprecise diet measures, and conceptual issues surrounding replication all challenge our efforts to characterize interactions. Collaborations are needed for optimal study designs in both hypothesis-testing and hypothesis-generating contexts. Continued investment in studies of gene-diet interactions may lead to novel mechanistic insights into T2D, opportunities for risk stratification, and ultimately to personalized nutrition to prevent the disease.
    12/2014; 3(4). DOI:10.1007/s13668-014-0095-1
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    ABSTRACT: Selenium (Se) is an essential trace element in human nutrition, but its role in certain health conditions, particularly among Se sufficient populations, is controversial. A genome-wide association study (GWAS) of blood Se concentrations previously identified a locus at 5q14 near BHMT. We performed a GW meta-analysis of toenail Se concentrations, which reflect a longer duration of exposure than blood Se concentrations, including 4,162 European descendants from four U.S. cohorts. Toenail Se was measured using neutron activation analysis. We identified a GW-significant locus at 5q14 (P<1×10(-16)), the same locus identified in the published GWAS of blood Se based on independent cohorts. The lead SNP explained ∼1% of the variance in toenail Se concentrations. Using GW-summary statistics from both toenail and blood Se, we observed statistical evidence of polygenic overlap (P<0.001) and meta-analysis of results from studies of either trait (N=9,639) yielded a second GW-significant locus at 21q22.3, harboring CBS (P<4×10(-8)). Proteins encoded by genes at 5q14 and 21q22.3 function in homocysteine metabolism, and index SNPs for each have previously been associated with betaine and homocysteine levels in GWAS. Our findings show evidence of a genetic link between Se and homocysteine pathways, both involved in cardiometabolic disease.
    Human Molecular Genetics 10/2014; 24(5). DOI:10.1093/hmg/ddu546 · 6.68 Impact Factor
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    ABSTRACT: Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91 462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log10Bayes factor (BF)>5.64) with per-allele effect sizes of 0.03-0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P<5 × 10(-8)).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.Molecular Psychiatry advance online publication, 7 October 2014; doi:10.1038/mp.2014.107.
    Molecular Psychiatry 10/2014; DOI:10.1038/mp.2014.107 · 15.15 Impact Factor
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    ABSTRACT: While research has suggested that being married may confer a health advantage, few studies to date have investigated the role of marital status in the development of type 2 diabetes. We examined whether men who are not married have increased risk of incident type 2 diabetes in the Health Professionals Follow-up Study. Men (n = 41,378) who were free of T2D in 1986, were followed for ≤22 years with biennial reports of T2D, marital status and covariates. Cox proportional hazard models were used to compare risk of incident T2D by marital status (married vs unmarried and married vs never married, divorced/separated, or widowed). There were 2,952 cases of incident T2D. Compared to married men, unmarried men had a 16% higher risk of developing T2D (95%CI:1.04,1.30), adjusting for age, family history of diabetes, ethnicity, lifestyle and body mass index (BMI). Relative risks (RR) for developing T2D differed for divorced/separated (1.09 [95%CI: 0.94,1.27]), widowed (1.29 [95%CI:1.06,1.57]), and never married (1.17 [95%CI:0.91,1.52]) after adjusting for age, family history of diabetes and ethnicity. Adjusting for lifestyle and BMI, the RR for T2D associated with widowhood was no longer significant (RR:1.16 [95%CI:0.95,1.41]). When allowing for a 2-year lag period between marital status and disease, RRs of T2D for widowers were augmented and borderline significant (RR:1.24 [95%CI:1.00,1.54]) after full adjustment. In conclusion, not being married, and more specifically, widowhood was more consistently associated with an increased risk of type 2 diabetes in men and this may be mediated, in part, through unfavorable changes in lifestyle, diet and adiposity.
    PLoS ONE 09/2014; 9(9):e106720. DOI:10.1371/journal.pone.0106720 · 3.53 Impact Factor
  • Marilyn C. Cornelis
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    ABSTRACT: Coffee is one of the most widely consumed beverages in the world, and has been implicated in many health conditions. Coffee is a complex exposure with pleiotropic effects, and the physiological response to coffee varies among individuals. Epidemiological studies of gene-coffee interactions may inform causality, parse the constituents of coffee responsible for disease, and identify subgroups most likely to benefit from increasing or decreasing coffee consumption. Cancers, cardiovascular disease, Parkinson’s disease, and pregnancy outcomes have been the subject of gene-coffee interaction studies and have yielded promising preliminary results. Most studies have targeted the caffeine component of coffee and have examined only a limited number of genetic variants. Depending upon the disease of study, coffee appears to exert beneficial, adverse, or no effects, which may be more pronounced when accounting for genetics. With continued investment, studies of gene-coffee interactions promise to provide the necessary foundation for personalized coffee consumption recommendations.
    09/2014; 3(3):178-195. DOI:10.1007/s13668-014-0087-1
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    ABSTRACT: Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcomes should account for the case-control sampling scheme, or otherwise results may be biased. Often, one uses inverse probability weighted (IPW) estimators to estimate population effects in such studies. However, these estimators are inefficient relative to estimators that make additional assumptions about the data generating mechanism. We propose a class of estimators for the effect of risk factors on a secondary outcome in case-control studies, when the mean is modeled using either the identity or the log link. The proposed estimator combines IPW with a mean zero control function that depends explicitly on a model for the primary disease outcome. The efficient estimator in our class of estimators reduces to standard IPW when the model for the primary disease outcome is unrestricted, and is more efficient than standard IPW when the model is either parametric or semiparametric.
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    ABSTRACT: Obesity and anxiety are often linked but the direction of effects is not clear.
    Psychological Medicine 05/2014; DOI:10.1017/S0033291714001226 · 5.43 Impact Factor
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    ABSTRACT: Objective: Many confirmed genetic loci for obesity are expressed in regions of the brain that regulate energy intake and reward-seeking behavior. Whether these loci contribute to the development of specific eating behaviors has not been investigated. We examined the relationship between a genetic susceptibility to obesity and cognitive restraint, uncontrolled and emotional eating. Design and Methods: Eating behavior and body mass index (BMI) were determined by questionnaires for 1471 men and 2381 women from two U.S cohorts. Genotypes were extracted from genome-wide scans and a genetic-risk score (GRS) derived from 32 obesity-loci was calculated. Results: The GRS was positively associated with emotional and uncontrolled eating(P<0.002). In exploratory analysis, BMI-increasing variants of MTCH2,TNNI3K and ZC3H4 were positively associated with emotional eating and those of TNNI3K and ZC3H4 were positively associated with uncontrolled eating.The BMI-increasing variant of FTO was positively and those of LRP1B and TFAP2B were inversely associated with cognitive restraint.These associations for single SNPs were independent of BMI but were not significant after multiple-testing correction. Conclusions: An overall genetic susceptibility to obesity may also extend to eating behaviors. The link between specific loci and obesity may be mediated by eating behavior but larger studies are warranted to confirm these results.
    Obesity 05/2014; 22(5). DOI:10.1002/oby.20592 · 4.39 Impact Factor
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    ABSTRACT: We give critical attention to the assumptions underlying Mendelian randomization analysis and their biological plausibility. Several scenarios violating the Mendelian randomization assumptions are described, including settings with inadequate phenotype definition, the setting of time-varying exposures, the presence of gene-environment interaction, the existence of measurement error, the possibility of reverse causation, and the presence of linkage disequilibrium. Data analysis examples are given, illustrating that the inappropriate use of instrumental variable techniques when the Mendelian randomization assumptions are violated can lead to biases of enormous magnitude. To help address some of the strong assumptions being made, three possible approaches are suggested. First, the original proposal of Katan (Lancet. 1986;1:00-00) for Mendelian randomization was not to use instrumental variable techniques to obtain estimates but merely to examine genotype-outcome associations to test for the presence of an effect of the exposure on the outcome. We show that this more modest goal and approach can circumvent many, though not all, the potential biases described. Second, we discuss the use of sensitivity analysis in evaluating the consequences of violations in the assumptions and in attempting to correct for those violations. Third, we suggest that a focus on negative, rather than positive, Mendelian randomization results may turn out to be more reliable.
    Epidemiology (Cambridge, Mass.) 03/2014; DOI:10.1097/EDE.0000000000000081 · 6.18 Impact Factor
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    ABSTRACT: Prospective evidence regarding associations for exposures to bisphenol A (BPA) and phthalates with type 2 diabetes (T2D) is lacking. To prospectively examine urinary concentrations of BPA and phthalate metabolites with T2D risk. BPA and eight major phthalate metabolites were measured among 971 incident T2D case-control pairs from the Nurses' Health Study (NHS; mean age 65.6) and NHSII (mean age 45.6). In the NHSII, BPA levels were not associated with incident T2D in multivariate-adjusted analysis until body mass index was adjusted: odds ratio (OR) comparing extreme BPA quartiles increased from 1.40 (95% CI: 0.91, 2.15) to 2.08 (95% CI: 1.17, 3.69; Ptrend = 0.02) with such an adjustment. In contrast, BPA concentrations were not associated with T2D in the NHS (OR 0.81; 95% CI 0.48, 1.38; Ptrend = 0.45). Likewise, urinary concentrations of total phthalate metabolites were associated with T2D in the NHSII (OR comparing extreme quartiles 2.14; 95% CI 1.19, 3.85; Ptrend = 0.02), but not in the NHS (OR 0.87; 95% CI 0.49, 1.53; Ptrend = 0.29). Summed metabolites of butyl phthalates or di-(2-ethylhexyl) phthalates were significantly associated with T2D in the NHSII only; ORs comparing extreme quartiles were 3.16 (95% CI: 1.68, 5.95; Ptrend = 0.0002) and 1.91 (95% CI: 1.04, 3.49; Ptrend = 0.20), respectively. These results suggest that BPA and phthalate exposures may be associated with the risk of T2D among middle-aged women, but not older women. The divergent findings between the two cohorts might be explained by menopausal status or simply by chance. Clearly, these results need to be interpreted with caution and should be replicated in future studies, ideally with multiple urine samples collected prospectively to improve the measurement of these exposures with short half-lives.
    Environmental Health Perspectives 03/2014; 122(6). DOI:10.1289/ehp.1307201 · 7.03 Impact Factor
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    ABSTRACT: To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
    Nature Genetics 03/2014; 46(3):234-244. DOI:10.1038/ng.2897 · 29.65 Impact Factor
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    ABSTRACT: Background Despite moderate heritability estimates for depression-related phenotypes, few robust genetic predictors have been identified. Potential explanations for this discrepancy include the use of phenotypic measures taken from a single time point, rather than integrating information over longer time periods via multiple assessments, and the possibility that genetic risk is shaped by multiple loci with small effects. Methods We developed a 14-year long-term average depression measure based on 14 years of follow-up in the Nurses' Health Study (NHS; N = 6989 women). We estimated polygenic scores (PS) with internal whole-genome scoring (NHS-GWAS-PS). We also constructed PS by applying two external PS weighting algorithms from independent samples, one previously shown to predict depression (GAIN-MDD-PS) and another from the largest genome-wide analysis currently available (PGC-MDD-PS). We assessed the association of all three PS with our long-term average depression phenotype using linear, logistic, and quantile regressions. ResultsIn this study, the three PS approaches explained at most 0.2% of variance in the long-term average phenotype. Quantile regressions indicated PS had larger impacts at higher quantiles of depressive symptoms. Quantile regression coefficients at the 75th percentile were at least 40% larger than at the 25th percentile in all three polygenic scoring algorithms. The interquartile range comparison suggested the effects of PS significantly differed at the 25th and 75th percentiles of the long-term depressive phenotype for the PGC-MDD-PS (P = 0.03), and this difference also reached borderline statistical significance for the GAIN-MDD-PS (P = 0.05). Conclusions Integrating multiple phenotype assessments spanning 14 years and applying different polygenic scoring approaches did not substantially improve genetic prediction of depression. Quantile regressions suggested the effects of PS may be largest at high quantiles of depressive symptom scores, presumably among people with additional, unobserved sources of vulnerability to depression.
    03/2014; 4(2):298-311. DOI:10.1002/brb3.205
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    ABSTRACT: Functional impairment is one of the most enduring, intractable consequences of psychiatric disorders and is both familial and heritable. Previous studies have suggested that variation in functional impairment can be independent of symptom severity. Here we report the first genome-wide association study (GWAS) of functional impairment in the context of major mental illness. Participants of European-American descent (N = 2,246) were included from three large treatment studies of bipolar disorder (STEP-BD) (N = 765), major depressive disorder (STAR*D) (N = 1091), and schizophrenia (CATIE) (N = 390). At study entry, participants completed the SF-12, a widely used measure of health-related quality of life. We performed a GWAS and pathway analysis of the mental and physical components of health-related quality of life across diagnosis (∼1.6 million single nucleotide polymorphisms), adjusting for psychiatric symptom severity. Psychiatric symptom severity was a significant predictor of functional impairment, but it accounted for less than one-third of the variance across disorders. After controlling for diagnostic category and symptom severity, the strongest evidence of genetic association was between variants in ADAMTS16 and physical functioning (P = 5.87 × 10(-8) ). Pathway analysis did not indicate significant enrichment after correction for gene clustering and multiple testing. This study illustrates a phenotypic framework for examining genetic contributions to functional impairment across psychiatric disorders. © 2013 Wiley Periodicals, Inc.
    American Journal of Medical Genetics Part B Neuropsychiatric Genetics 12/2013; 162(8). DOI:10.1002/ajmg.b.32190 · 3.27 Impact Factor
  • Marilyn C Cornelis, Frank B Hu
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    ABSTRACT: Systems epidemiology applied to the field of nutrition has potential to provide new insight into underlying mechanisms and ways to study the health effects of specific foods more comprehensively. Human intervention and population-based studies have identified i) common genetic factors associated with several nutrition-related traits and ii) dietary factors altering the expression of genes and levels of proteins and metabolites related to inflammation, lipid metabolism and/or gut microbial metabolism, results of high relevance to metabolic disease. System-level tools applied type 2 diabetes and related conditions have revealed new pathways that are potentially modified by diet and thus offer additional opportunities for nutritional investigations. Moving forward, harnessing the resources of existing large prospective studies within which biological samples have been archived and diet and lifestyle have been measured repeatedly within individual will enable systems-level data to be integrated, the outcome of which will be improved personalized optimal nutrition for prevention and treatment of disease.
    12/2013; 2(4). DOI:10.1007/s13668-013-0052-4

Publication Stats

5k Citations
1,046.34 Total Impact Points

Institutions

  • 2010–2015
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States
    • Beverly Hospital, Boston MA
      Beverly, Massachusetts, United States
    • University Hospital Regensburg
      • Klinik und Poliklinik für Innere Medizin II
      Ratisbon, Bavaria, Germany
  • 2009–2015
    • Harvard Medical School
      • • Department of Medicine
      • • Division of Nutrition
      Boston, Massachusetts, United States
  • 2009–2014
    • Harvard University
      • Department of Nutrition
      Cambridge, Massachusetts, United States
  • 2013
    • Uppsala University
      Uppsala, Uppsala, Sweden
  • 2012
    • University of Oxford
      • Wellcome Trust Centre for Human Genetics
      Oxford, ENG, United Kingdom
  • 2004–2009
    • University of Toronto
      • Department of Nutritional Sciences
      Toronto, Ontario, Canada
  • 2005–2006
    • Hanyang University
      • • Major in Rehabilitation Medicine
      • • Major in Internal Medicine
      Ansan, Gyeonggi, South Korea