CAP Profiles

Bio

Academic Appointments

Professional Education

  • Postdoc, Harvard Medical School, Statistical Genetics (2016)
  • Internship, Harvard Medical School, Clinical Psychology (2011)
  • PhD, University of Colorado, PhDs Clinical Psychology & Neuroscience (2011)
  • MS, University of Georgia, Honors Interdisciplinary Studies (2003)

Contact

Links

Research & Scholarship

Current Research and Scholarly Interests

We study genetic and environmental effects on mental health. Much of our work is computational and it relies upon genetic data, collected from millions of individuals, from around the world. We use genetic approaches because the overall goal of the lab is to discover fundamental information about psychiatric disorders, and ultimately to build more rational approaches to classification, prevention, and treatment.

Teaching

2019-20 Courses

Publications

All Publications

  • How genome-wide association studies (GWAS) made traditional candidate gene studies obsolete NEUROPSYCHOPHARMACOLOGY Duncan, L. E., Ostacher, M., Ballon, J. 2019; 44 (9): 1518–23

    View details for DOI 10.1038/s41386-019-0389-5

    View details for Web of Science ID 000475474900003

  • Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nature genetics Watson, H. J., Yilmaz, Z., Thornton, L. M., Hubel, C., Coleman, J. R., Gaspar, H. A., Bryois, J., Hinney, A., Leppa, V. M., Mattheisen, M., Medland, S. E., Ripke, S., Yao, S., Giusti-Rodriguez, P., Anorexia Nervosa Genetics Initiative, Hanscombe, K. B., Purves, K. L., Eating Disorders Working Group of the Psychiatric Genomics Consortium, Adan, R. A., Alfredsson, L., Ando, T., Andreassen, O. A., Baker, J. H., Berrettini, W. H., Boehm, I., Boni, C., Perica, V. B., Buehren, K., Burghardt, R., Cassina, M., Cichon, S., Clementi, M., Cone, R. D., Courtet, P., Crow, S., Crowley, J. J., Danner, U. N., Davis, O. S., de Zwaan, M., Dedoussis, G., Degortes, D., DeSocio, J. E., Dick, D. M., Dikeos, D., Dina, C., Dmitrzak-Weglarz, M., Docampo, E., Duncan, L. E., Egberts, K., Ehrlich, S., Escaramis, G., Esko, T., Estivill, X., Farmer, A., Favaro, A., Fernandez-Aranda, F., Fichter, M. M., Fischer, K., Focker, M., Foretova, L., Forstner, A. J., Forzan, M., Franklin, C. S., Gallinger, S., Giegling, I., Giuranna, J., Gonidakis, F., Gorwood, P., Mayora, M. G., Guillaume, S., Guo, Y., Hakonarson, H., Hatzikotoulas, K., Hauser, J., Hebebrand, J., Helder, S. G., Herms, S., Herpertz-Dahlmann, B., Herzog, W., Huckins, L. M., Hudson, J. I., Imgart, H., Inoko, H., Janout, V., Jimenez-Murcia, S., Julia, A., Kalsi, G., Kaminska, D., Kaprio, J., Karhunen, L., Karwautz, A., Kas, M. J., Kennedy, J. L., Keski-Rahkonen, A., Kiezebrink, K., Kim, Y., Klareskog, L., Klump, K. L., Knudsen, G. P., La Via, M. C., Le Hellard, S., Levitan, R. D., Li, D., Lilenfeld, L., Lin, B. D., Lissowska, J., Luykx, J., Magistretti, P. J., Maj, M., Mannik, K., Marsal, S., Marshall, C. R., Mattingsdal, M., McDevitt, S., McGuffin, P., Metspalu, A., Meulenbelt, I., Micali, N., Mitchell, K., Monteleone, A. M., Monteleone, P., Munn-Chernoff, M. A., Nacmias, B., Navratilova, M., Ntalla, I., O'Toole, J. K., Ophoff, R. A., Padyukov, L., Palotie, A., Pantel, J., Papezova, H., Pinto, D., Rabionet, R., Raevuori, A., Ramoz, N., Reichborn-Kjennerud, T., Ricca, V., Ripatti, S., Ritschel, F., Roberts, M., Rotondo, A., Rujescu, D., Rybakowski, F., Santonastaso, P., Scherag, A., Scherer, S. W., Schmidt, U., Schork, N. J., Schosser, A., Seitz, J., Slachtova, L., Slagboom, P. E., Slof-Op 't Landt, M. C., Slopien, A., Sorbi, S., Swiatkowska, B., Szatkiewicz, J. P., Tachmazidou, I., Tenconi, E., Tortorella, A., Tozzi, F., Treasure, J., Tsitsika, A., Tyszkiewicz-Nwafor, M., Tziouvas, K., van Elburg, A. A., van Furth, E. F., Wagner, G., Walton, E., Widen, E., Zeggini, E., Zerwas, S., Zipfel, S., Bergen, A. W., Boden, J. M., Brandt, H., Crawford, S., Halmi, K. A., Horwood, L. J., Johnson, C., Kaplan, A. S., Kaye, W. H., Mitchell, J. E., Olsen, C. M., Pearson, J. F., Pedersen, N. L., Strober, M., Werge, T., Whiteman, D. C., Woodside, D. B., Stuber, G. D., Gordon, S., Grove, J., Henders, A. K., Jureus, A., Kirk, K. M., Larsen, J. T., Parker, R., Petersen, L., Jordan, J., Kennedy, M., Montgomery, G. W., Wade, T. D., Birgegard, A., Lichtenstein, P., Norring, C., Landen, M., Martin, N. G., Mortensen, P. B., Sullivan, P. F., Breen, G., Bulik, C. M. 2019

    Abstract

    Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness1, affecting 0.9-4% of women and 0.3% of men2-4, with twin-based heritability estimates of 50-60%5. Mortality rates are higher than those in other psychiatric disorders6, and outcomes are unacceptably poor7. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992cases of anorexia nervosa and 55,525controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.

    View details for DOI 10.1038/s41588-019-0439-2

    View details for PubMedID 31308545

  • A Network Mendelian Randomization Analysis of Neuroticism, Trauma, and Psychopathology Ratanatharathorn, A., Chen, C., Choi, K., Davie, S., Duncan, L., Maihofer, A., Nievergelt, C., Polimanti, R., Koenen, K. ELSEVIER SCIENCE INC. 2019: S64

    View details for DOI 10.1016/j.biopsych.2019.03.168

    View details for Web of Science ID 000472661000155

  • Taking a Closer Look at PTSD Genomics: Rare Copy Number Variants and Extended Phenotyping Maihofer, A., Coleman, J., Duncan, L., Ratanatharathorn, A., Liberzon, I., Ressler, K., Koenen, K., Nievergelt, C., PGC PTSD Workgrp ELSEVIER SCIENCE INC. 2019: S63

    View details for DOI 10.1016/j.biopsych.2019.03.166

    View details for Web of Science ID 000472661000153

  • Statistical inference and reproducibility in geobiology GEOBIOLOGY Sperling, E. A., Tecklenburg, S., Duncan, L. E. 2019; 17 (3): 261–71

    View details for DOI 10.1111/gbi.12333

    View details for Web of Science ID 000465014600003

  • Association of Economic Status and Educational Attainment With Posttraumatic Stress Disorder A Mendelian Randomization Study JAMA NETWORK OPEN Polimanti, R., Ratanatharathorn, A., Maihofer, A. X., Choi, K. W., Stein, M. B., Morey, R. A., Logue, M. W., Nievergelt, C. M., Stein, D. J., Koenen, K. C., Gelernter, J., Nievergelt, C. M., Maihofer, A. X., Klengel, T., Atkinson, E. G., Chen, C., Coleman, J. I., Dalvie, S., Duncan, L. E., Logue, M. W., Provost, A. C., Ratanatharathorn, A., Stein, M. B., Torres, K., Aiello, A. E., Almli, L. M., Amstadter, A. B., Andersen, S. B., Andreassen, O. A., Arbisi, P. A., Ashley-Koch, A. E., Austin, S., Avdibegovic, E., Babic, D., Baekvad-Hansen, M., Baker, D. G., Beckham, J. C., Bierut, L. J., Bisson, J. I., Boks, M. P., Bolger, E. A., Borglum, A. D., Bradley, B., Brashear, M., Breen, G., Bryant, R. A., Bustamante, A. C., Bybjerg-Grauholm, J., Calabrese, J. R., Caldas-de-Almeida, J. M., Dale, A. M., Daly, M. J., Daskalakis, N. P., Deckert, J., Delahanty, D. L., Dennis, M. F., Disner, S. G., Domschke, K., Dzubur-Kulenovic, A., Erbes, C. R., Evans, A., Farrer, L. A., Feeny, N. C., Flory, J. D., Forbes, D., Franz, C. E., Galea, S., Garrett, M. E., Gelaye, B., Gelernter, J., Geuze, E., Gillespie, C., Uka, A., Gordon, S. D., Guffanti, G., Hammamieh, R., Harnal, S., Hauser, M. A., Heath, A. C., Hemmings, S. J., Hougaard, D., Jakovljevic, M., Jett, M., Johnson, E., Jones, I., Jovanovic, T., Qin, X., Junglen, A. G., Karstoft, K., Kaufman, M. L., Kessler, R. C., Khan, A., Kimbrel, N. A., King, A. P., Koen, N., Kranzler, H. R., Kremen, W. S., Lawford, B. R., Lebois, L. M., Lewis, C. E., Linnstaedt, S. D., Lori, A., Lugonja, B., Luykx, J. J., Lyons, M. J., Maples-Keller, J., Marmar, C., Martin, A. R., Martin, N. G., Maurer, D., Mavissakalian, M. R., McFarlane, A., McGlinchey, R. E., McLaughlin, K. A., McLean, S. A., McLeay, S., Mehta, D., Milberg, W. P., Miller, M. W., Morris, C., Mors, O., Mortensen, P. B., Neale, B. M., Nelson, E. C., Nordentoft, M., Norman, S. B., O'Donnell, M., Orcutt, H. K., Panizzon, M. S., Peters, E. S., Peterson, A. L., Peverill, M., Pietrzak, R. H., Polusny, M. A., Rice, J. P., Ripke, S., Risbrough, V. B., Roberts, A. L., Rothbaum, A. O., Rothbaum, B. O., Roy-Byrne, P., Ruggiero, K., Rung, A., Rutten, B. F., Saccone, N. L., Sanchez, S. E., Schijven, D., Seedat, S., Seligowski, A. V., Seng, J. S., Sheerin, C. M., Silove, D., Smith, A. K., Smoller, J. W., Solovieff, N., Sponheim, S. R., Stein, D. J., Sumner, J. A., Teicher, M. H., Thompson, W. K., Trapido, E., Uddin, M., Ursano, R. J., van den Heuvel, L., van Hooff, M., Vermetten, E., Vinkers, C. H., Voisey, J., Wang, Y., Wang, Z., Werge, T., Williams, M. A., Williamson, D. E., Winternitz, S., Wolf, C., Wolf, E. J., Wolff, J. D., Yehuda, R., Young, K. A., Young, R., Zhao, H., Zoellner, L. A., Liberzon, I., Ressler, K. J., Haas, M., Koenen, K. C., Psychiat Genomics Consortium 2019; 2 (5): e193447

    Abstract

    There is a well-established negative association of educational attainment (EA) and other traits related to cognitive ability with posttraumatic stress disorder (PTSD), but the underlying mechanisms are poorly understood.To investigate the association of PTSD with traits related to EA.Genetic correlation, polygenic risk scoring, and mendelian randomization (MR) were conducted including 23 185 individuals with PTSD and 151 309 control participants from the Psychiatric Genomics Consortium for PTSD and up to 1 131 881 individuals assessed for EA and related traits from UK Biobank, 23andMe, and the Social Science Genetic Association Consortium. Data were analyzed from July 3 through November 19, 2018.Genetic correlation obtained from linkage disequilibrium score regression, phenotypic variance explained by polygenic risk scores, and association estimates from MR.Summary association data from multiple genome-wide association studies were available for a total of 1 180 352 participants (634 391 [53.7%] women). Posttraumatic stress disorder showed negative genetic correlations with EA (rg = -0.26; SE = 0.05; P = 4.60 × 10-8). Mendelian randomization analysis, conducting considering a random-effects inverse-variance weighted method, indicated that EA has a negative association with PTSD (β = -0.23; 95% CI, -0.07 to -0.39; P = .004). Investigating potential mediators of the EA-PTSD association, propensity for trauma exposure and risk-taking behaviors were observed as risk factors for PTSD independent of EA (trauma exposure: β = 0.37; 95% CI, 0.19 to 0.52; P = 2.57 × 10-5; risk-taking: β = 0.76; 95% CI, 0.38 to 1.13; P = 1.13 × 10-4), while income may mediate the association of EA with PSTD (MR income: β = -0.18; 95% CI, -0.29 to -0.07; P = .001; MR EA: β = -0.23; 95% CI, -0.39 to -0.07; P = .004; multivariable MR income: β = -0.32; 95% CI, -0.57 to 0.07; P = .02; multivariable MR EA: β = -0.04; 95% CI, -0.29 to 0.21; SE, 0.13; P = .79).Large-scale genomic data sets add further evidence to the negative association of EA with PTSD, also supporting the role of economic status as a mediator in the association observed.

    View details for DOI 10.1001/jamanetworkopen.2019.3447

    View details for Web of Science ID 000476806200031

    View details for PubMedID 31050786

    View details for PubMedCentralID PMC6503495

  • How genome-wide association studies (GWAS) made traditional candidate gene studies obsolete. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Duncan, L. E., Ostacher, M., Ballon, J. 2019

    View details for PubMedID 30982060

  • Statistical inference and reproducibility in geobiology. Geobiology Sperling, E. A., Tecklenburg, S., Duncan, L. E. 2019

    View details for PubMedID 30747493

  • International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci. Nature communications Nievergelt, C. M., Maihofer, A. X., Klengel, T., Atkinson, E. G., Chen, C. Y., Choi, K. W., Coleman, J. R., Dalvie, S., Duncan, L. E., Gelernter, J., Levey, D. F., Logue, M. W., Polimanti, R., Provost, A. C., Ratanatharathorn, A., Stein, M. B., Torres, K., Aiello, A. E., Almli, L. M., Amstadter, A. B., Andersen, S. B., Andreassen, O. A., Arbisi, P. A., Ashley-Koch, A. E., Austin, S. B., Avdibegovic, E., Babić, D., Bækvad-Hansen, M., Baker, D. G., Beckham, J. C., Bierut, L. J., Bisson, J. I., Boks, M. P., Bolger, E. A., Børglum, A. D., Bradley, B., Brashear, M., Breen, G., Bryant, R. A., Bustamante, A. C., Bybjerg-Grauholm, J., Calabrese, J. R., Caldas-de-Almeida, J. M., Dale, A. M., Daly, M. J., Daskalakis, N. P., Deckert, J., Delahanty, D. L., Dennis, M. F., Disner, S. G., Domschke, K., Dzubur-Kulenovic, A., Erbes, C. R., Evans, A., Farrer, L. A., Feeny, N. C., Flory, J. D., Forbes, D., Franz, C. E., Galea, S., Garrett, M. E., Gelaye, B., Geuze, E., Gillespie, C., Uka, A. G., Gordon, S. D., Guffanti, G., Hammamieh, R., Harnal, S., Hauser, M. A., Heath, A. C., Hemmings, S. M., Hougaard, D. M., Jakovljevic, M., Jett, M., Johnson, E. O., Jones, I., Jovanovic, T., Qin, X. J., Junglen, A. G., Karstoft, K. I., Kaufman, M. L., Kessler, R. C., Khan, A., Kimbrel, N. A., King, A. P., Koen, N., Kranzler, H. R., Kremen, W. S., Lawford, B. R., Lebois, L. A., Lewis, C. E., Linnstaedt, S. D., Lori, A., Lugonja, B., Luykx, J. J., Lyons, M. J., Maples-Keller, J., Marmar, C., Martin, A. R., Martin, N. G., Maurer, D., Mavissakalian, M. R., McFarlane, A., McGlinchey, R. E., McLaughlin, K. A., McLean, S. A., McLeay, S., Mehta, D., Milberg, W. P., Miller, M. W., Morey, R. A., Morris, C. P., Mors, O., Mortensen, P. B., Neale, B. M., Nelson, E. C., Nordentoft, M., Norman, S. B., O'Donnell, M., Orcutt, H. K., Panizzon, M. S., Peters, E. S., Peterson, A. L., Peverill, M., Pietrzak, R. H., Polusny, M. A., Rice, J. P., Ripke, S., Risbrough, V. B., Roberts, A. L., Rothbaum, A. O., Rothbaum, B. O., Roy-Byrne, P., Ruggiero, K., Rung, A., Rutten, B. P., Saccone, N. L., Sanchez, S. E., Schijven, D., Seedat, S., Seligowski, A. V., Seng, J. S., Sheerin, C. M., Silove, D., Smith, A. K., Smoller, J. W., Sponheim, S. R., Stein, D. J., Stevens, J. S., Sumner, J. A., Teicher, M. H., Thompson, W. K., Trapido, E., Uddin, M., Ursano, R. J., van den Heuvel, L. L., Van Hooff, M., Vermetten, E., Vinkers, C. H., Voisey, J., Wang, Y., Wang, Z., Werge, T., Williams, M. A., Williamson, D. E., Winternitz, S., Wolf, C., Wolf, E. J., Wolff, J. D., Yehuda, R., Young, R. M., Young, K. A., Zhao, H., Zoellner, L. A., Liberzon, I., Ressler, K. J., Haas, M., Koenen, K. C. 2019; 10 (1): 4558

    Abstract

    The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.

    View details for DOI 10.1038/s41467-019-12576-w

    View details for PubMedID 31594949

  • FINDINGS FROM PGC PTSD GENOME-WIDE ASSOCIATION STUDY OF OVER 200,000 SAMPLES Maihofer, A., Atkinson, E., Klengel, T., Ratanatharathorn, A., Coleman, J., Duncan, L., Daly, M., Ressler, K., Liberzon, I., Koenen, K., Nievergelt, C., PGC PTSD Working Grp ELSEVIER. 2019: 1054–55

    View details for DOI 10.1016/j.euroneuro.2018.07.070

    View details for Web of Science ID 000477708400070

  • PERFORMANCE OF POLYGENIC SCORES ACROSS ANCESTRALLY DIVERSE POPULATIONS: SCIENTIFIC AND ETHICAL CONSIDERATIONS Duncan, L., Shen, H., Pritchard, J., Feldman, M., Ressler, K., Harris, K., Domingue, B. ELSEVIER SCIENCE BV. 2019: S833–S834

    View details for DOI 10.1016/j.euroneuro.2017.08.094

    View details for Web of Science ID 000462156400223

  • LARGE-SCALE GENETIC CHARACTERIZATION OF PTSD ACROSS ANCESTRY, GENDER AND TRAUMA-TYPE Nievergelt, C., Maihofer, A., Dalvie, S., Ratanatharathorn, A., Duncan, L., Daly, M., Ressler, K., Liberzon, I., Koenen, K., Psychiatric Genomics Consortium ELSEVIER SCIENCE BV. 2019: S749–S750

    View details for DOI 10.1016/j.euroneuro.2017.06.091

    View details for Web of Science ID 000462156400075

  • Correction to: Robust Findings From 25Years of PTSD Genetics Research. Current psychiatry reports Duncan, L. E., Cooper, B. N., Shen, H. 2018; 20 (12): 119

    Abstract

    The original version of this article contained an error in the title. The correct title should read "Robust Findings From 25 Years of PTSD Genetics Research" as shown above. The original article has been corrected.

    View details for PubMedID 30474743

  • Robust Findings From 25Years of PSTD Genetics Research. Current psychiatry reports Duncan, L. E., Cooper, B. N., Shen, H. 2018; 20 (12): 115

    Abstract

    PURPOSE OF REVIEW: The purpose of this review is to contextualize findings from the first 25years of PTSD genetics research, focusing on the most robust findings and interpreting results in light of principles that have emerged from modern genetics studies.RECENT FINDINGS: Genome-wide association studies (GWAS) encompassing tens of thousands of participants enabled the first molecular genetic heritability and genetic correlation estimates for PTSD in 2017. In 2018, highly promising loci for PTSD were reported, including variants in and near the CAMKV, KANSL1, and TCF4 genes. Twin studies from 25years ago established that PTSD is genetically influenced and foreshadowed the molecular genetic findings of today. Discoveries that were impossible with smaller studies have been achieved via collaborative/team-science efforts. Most promisingly, individual genomic loci offer entirely novel clues about PTSD etiology, providing the raw material for transformative discoveries, and the future of PTSD research is bright.

    View details for PubMedID 30350223

  • Chromosomes to Social Contexts: Sex and Gender Differences in PTSD. Current psychiatry reports Kimerling, R., Allen, M. C., Duncan, L. E. 2018; 20 (12): 114

    Abstract

    PURPOSE OF REVIEW: This review highlights recent research on sex- and gender-related factors in the prevalence, symptom expression, and treatment of PTSD. Further discoveries about the underlying mechanisms of sex and gender effects have the potential to shape innovative directions for research.RECENT FINDINGS: The prevalence of PTSD is substantially higher among women, but women show a modest advantage with respect to treatment response. There is evidence of greater heritability among females. Women are more likely to experience sexual and intimate violence, childhood trauma exposure, and repeated trauma exposures. Specific characteristics of social contexts act as gender-linked risks for PTSD. Among individuals diagnosed with PTSD, men and women are similar in phenotypic expression. Though research has yet to fully account for the factors that explain sex- and gender- related effects on PTSD, emerging research suggests these effects occur across multiple levels. Shared risk factors for trauma exposure and PTSD merit further investigation. Both social and biological contexts merit investigation to understand sex-linked differences in heritability.

    View details for PubMedID 30345456

  • The Anorexia Nervosa Genetics Initiative (ANGI): Overview and methods. Contemporary clinical trials Thornton, L. M., Munn-Chernoff, M. A., Baker, J. H., Jureus, A., Parker, R., Henders, A. K., Larsen, J. T., Petersen, L., Watson, H. J., Yilmaz, Z., Kirk, K. M., Gordon, S., Leppa, V. M., Martin, F. C., Whiteman, D. C., Olsen, C. M., Werge, T. M., Pedersen, N. L., Kaye, W., Bergen, A. W., Halmi, K. A., Strober, M., Kaplan, A. S., Woodside, D. B., Mitchell, J., Johnson, C. L., Brandt, H., Crawford, S., Horwood, L. J., Boden, J. M., Pearson, J. F., Duncan, L. E., Grove, J., Mattheisen, M., Jordan, J., Kennedy, M. A., Birgegard, A., Lichtenstein, P., Norring, C., Wade, T. D., Montgomery, G. W., Martin, N. G., Landen, M., Mortensen, P. B., Sullivan, P. F., Bulik, C. M. 2018; 74: 61–69

    Abstract

    BACKGROUND: Genetic factors contribute to anorexia nervosa (AN); and the first genome-wide significant locus has been identified. We describe methods and procedures for the Anorexia Nervosa Genetics Initiative (ANGI), an international collaboration designed to rapidly recruit 13,000 individuals with AN and ancestrally matched controls. We present sample characteristics and the utility of an online eating disorder diagnostic questionnaire suitable for large-scale genetic and population research.METHODS: ANGI recruited from the United States (US), Australia/New Zealand (ANZ), Sweden (SE), and Denmark (DK). Recruitment was via national registers (SE, DK); treatment centers (US, ANZ, SE, DK); and social and traditional media (US, ANZ, SE). All cases had a lifetime AN diagnosis based on DSM-IV or ICD-10 criteria (excluding amenorrhea). Recruited controls had no lifetime history of disordered eating behaviors. To assess the positive and negative predictive validity of the online eating disorder questionnaire (ED100K-v1), 109 women also completed the Structured Clinical Interview for DSM-IV (SCID), Module H.RESULTS: Blood samples and clinical information were collected from 13,363 individuals with lifetime AN and from controls. Online diagnostic phenotyping was effective and efficient; the validity of the questionnaire was acceptable.CONCLUSIONS: Our multi-pronged recruitment approach was highly effective for rapid recruitment and can be used as a model for efforts by other groups. High online presence of individuals with AN rendered the Internet/social media a remarkably effective recruitment tool in some countries. ANGI has substantially augmented Psychiatric Genomics Consortium AN sample collection. ANGI is a registered clinical trial: clinicaltrials.govNCT01916538; https://clinicaltrials.gov/ct2/show/NCT01916538?cond=Anorexia+Nervosa&draw=1&rank=3.

    View details for PubMedID 30287268

  • Analysis of shared heritability in common disorders of the brain SCIENCE Anttila, V., Bulik-Sullivan, B., Finucane, H. K., Walters, R. K., Bras, J., Duncan, L., Escott-Price, V., Falcone, G. J., Gormley, P., Malik, R., Patsopoulos, N. A., Ripke, S., Wei, Z., Yu, D., Lee, P. H., Turley, P., Grenier-Boley, B., Chouraki, V., Kamatani, Y., Berr, C., Letenneur, L., Hannequin, D., Amouyel, P., Boland, A., Deleuze, J., Duron, E., Vardarajan, B. N., Reitz, C., Goate, A. M., Huentelman, M. J., Kamboh, M., Larson, E. B., Rogaeva, E., St George-Hyslop, P., Hakonarson, H., Kukull, W. A., Farrer, L. A., Barnes, L. L., Beach, T. G., Demirci, F., Head, E., Hulette, C. M., Jicha, G. A., Kauwe, J. K., Kaye, J. A., Leverenz, J. B., Levey, A. I., Lieberman, A. P., Pankratz, V. S., Poon, W. W., Quinn, J. F., Saykin, A. J., Schneider, L. S., Smith, A. G., Sonnen, J. A., Stern, R. A., Van Deerlin, V. M., Van Eldik, L. J., Harold, D., Russo, G., Rubinsztein, D. C., Bayer, A., Tsolaki, M., Proitsi, P., Fox, N. C., Hampel, H., Owen, M. J., Mead, S., Passmore, P., Morgan, K., Noethen, M. M., Rossor, M., Lupton, M. K., Hoffmann, P., Kornhuber, J., Lawlor, B., McQuillin, A., Al-Chalabi, A., Bis, J. C., Ruiz, A., Boada, M., Seshadri, S., Beiser, A., Rice, K., van der Lee, S. J., De Jager, P. L., Geschwind, D. H., Riemenschneider, M., Riedel-Heller, S., Rotter, J. I., Ransmayr, G., Hyman, B. T., Cruchaga, C., Alegret, M., Winsvold, B., Palta, P., Farh, K., Cuenca-Leon, E., Furlotte, N., Kurth, T., Ligthart, L., Terwindt, G. M., Freilinger, T., Ran, C., Gordon, S. D., Borck, G., Adams, H. H., Lehtimaki, T., Wedenoja, J., Buring, J. E., Schuerks, M., Hrafnsdottir, M., Hottenga, J., Penninx, B., Artto, V., Kaunisto, M., Vepsalainen, S., Martin, N. G., Montgomery, G. W., Kurki, M. I., Hamalainen, E., Huang, H., Huang, J., Sandor, C., Webber, C., Muller-Myhsok, B., Schreiber, S., Salomaa, V., Loehrer, E., Goebel, H., Macaya, A., Pozo-Rosich, P., Hansen, T., Werge, T., Kaprio, J., Metspalu, A., Kubisch, C., Ferrari, M. D., Belin, A. C., van den Maagdenberg, A. M., Zwart, J., Boomsma, D., Eriksson, N., Olesen, J., Chasman, D. I., Nyholt, D. R., Avbersek, A., Baum, L., Berkovic, S., Bradfield, J., Buono, R., Catarino, C. B., Cossette, P., De Jonghe, P., Depondt, C., Dlugos, D., Ferraro, T. N., French, J., Hjalgrim, H., Jamnadas-Khoda, J., Kalviainen, R., Kunz, W. S., Lerche, H., Leu, C., Lindhout, D., Lo, W., Lowenstein, D., McCormack, M., Moller, R. S., Molloy, A., Ng, P., Oliver, K., Privitera, M., Radtke, R., Ruppert, A., Sander, T., Schachter, S., Schankin, C., Scheffer, I., Schoch, S., Sisodiya, S. M., Smith, P., Sperling, M., Striano, P., Surges, R., Thomas, G., Visscher, F., Whelan, C. D., Zara, F., Heinzen, E. L., Marson, A., Becker, F., Stroink, H., Zimprich, F., Gasser, T., Gibbs, R., Heutink, P., Martinez, M., Morris, H. R., Sharma, M., Ryten, M., Mok, K. Y., Pulit, S., Bevan, S., Holliday, E., Attia, J., Battey, T., Boncoraglio, G., Thijs, V., Chen, W., Mitchell, B., Rothwell, P., Sharma, P., Sudlow, C., Vicente, A., Markus, H., Kourkoulis, C., Pera, J., Raffeld, M., Silliman, S., Perica, V., Thornton, L. M., Huckins, L. M., Rayner, N., Lewis, C. M., Gratacos, M., Rybakowski, F., Keski-Rahkonen, A., Raevuori, A., Hudson, J. I., Reichborn-Kjennerud, T., Monteleone, P., Karwautz, A., Mannik, K., Baker, J. H., O'Toole, J. K., Trace, S. E., Davis, O. P., Helder, S. G., Ehrlich, S., Herpertz-Dahlmann, B., Danner, U. N., van Elburg, A. A., Clementi, M., Forzan, M., Docampo, E., Lissowska, J., Hauser, J., Tortorella, A., Maj, M., Gonidakis, F., Tziouvas, K., Papezova, H., Yilmaz, Z., Wagner, G., Cohen-Woods, S., Herms, S., Julia, A., Rabionet, R., Dick, D. M., Ripatti, S., Andreassen, O. A., Espeseth, T., Lundervold, A. J., Steen, V. M., Pinto, D., Scherer, S. W., Aschauer, H., Schosser, A., Alfredsson, L., Padyukov, L., Halmi, K. A., Mitchell, J., Strober, M., Bergen, A. W., Kaye, W., Szatkiewicz, J., Cormand, B., Antoni Ramos-Quiroga, J., Sanchez-Mora, C., Ribases, M., Casas, M., Hervas, A., Jesus Arranz, M., Haavik, J., Zayats, T., Johansson, S., Williams, N., Dempfle, A., Rothenberger, A., Kuntsi, J., Oades, R. D., Banaschewski, T., Franke, B., Buitelaar, J. K., Arias Vasquez, A., Doyle, A. E., Reif, A., Lesch, K., Freitag, C., Rivero, O., Palmason, H., Romanos, M., Langley, K., Rietschel, M., Witt, S. H., Dalsgaard, S., Borglum, A. D., Waldman, I., Wilmot, B., Molly, N., Bau, C. D., Crosbie, J., Schachar, R., K., S., McGough, J. J., Grevet, E. H., Medland, S. E., Robinson, E., Weiss, L. A., Bacchelli, E., Bailey, A., Bal, V., Battaglia, A., Betancur, C., Bolton, P., Cantor, R., Celestino-Soper, P., Dawson, G., De Rubeis, S., Duque, F., Green, A., Klauck, S. M., Leboyer, M., Levitt, P., Maestrini, E., Mane, S., Moreno-De-Luca, D., Parr, J., Regan, R., Reichenberg, A., Sandin, S., Vorstman, J., Wassink, T., Wijsman, E., Cook, E., Santangelo, S., Delorme, R., Roge, B., Magalhaes, T., Arking, D., Schulze, T. G., Thompson, R. C., Strohmaier, J., Matthews, K., Melle, I., Morris, D., Blackwood, D., McIntosh, A., Bergen, S. E., Schalling, M., Jamain, S., Maaser, A., Fischer, S. B., Reinbold, C. S., Fullerton, J. M., Guzman-Parra, J., Mayoral, F., Schofield, P. R., Cichon, S., Muhleisen, T. W., Degenhardt, F., Schumacher, J., Bauer, M., Mitchell, P. B., Gershon, E. S., Rice, J., Potash, J. B., Zandi, P. P., Craddock, N., Ferrier, I., Alda, M., Rouleau, G. A., Turecki, G., Ophoff, R., Pato, C., Anjorin, A., Stahl, E., Leber, M., Czerski, P. M., Cruceanu, C., Jones, I. R., Posthuma, D., Andlauer, T. M., Forstner, A. J., Streit, F., Baune, B. T., Air, T., Sinnamon, G., Wray, N. R., MacIntyre, D. J., Porteous, D., Homuth, G., Rivera, M., Grove, J., Middeldorp, C. M., Hickie, I., Pergadia, M., Mehta, D., Smit, J. H., Jansen, R., de Geus, E., Dunn, E., Li, Q. S., Nauck, M., Schoevers, R. A., Beekman, A. F., Knowles, J. A., Viktorin, A., Arnold, P., Barr, C. L., Bedoya-Berrio, G., Bienvenu, O., Brentani, H., Burton, C., Camarena, B., Cappi, C., Cath, D., Cavallini, M., Cusi, D., Darrow, S., Denys, D., Derks, E. M., Dietrich, A., Fernandez, T., Figee, M., Freimer, N., Gerber, G., Grados, M., Greenberg, E., Hanna, G. L., Hartmann, A., Hirschtritt, M. E., Hoekstra, P. J., Huang, A., Huyser, C., Illmann, C., Jenike, M., Kuperman, S., Leventhal, B., Lochner, C., Lyon, G. J., Macciardi, F., Madruga-Garrido, M., Malaty, I. A., Maras, A., McGrath, L., Miguel, E. C., Mir, P., Nestadt, G., Nicolini, H., Okun, M. S., Pakstis, A., Paschou, P., Piacentini, J., Pittenger, C., Plessen, K., Ramensky, V., Ramos, E. M., Reus, V., Richter, M. A., Riddle, M. A., Robertson, M. M., Roessner, V., Rosario, M., Samuels, J. F., Sandor, P., Stein, D. J., Tsetsos, F., Van Nieuwerburgh, F., Weatherall, S., Wendland, J. R., Wolanczyk, T., Worbe, Y., Zai, G., Goes, F. S., McLaughlin, N., Nestadt, P. S., Grabe, H., Depienne, C., Konkashbaev, A., Lanzagorta, N., Valencia-Duarte, A., Bramon, E., Buccola, N., Cahn, W., Cairns, M., Chong, S. A., Cohen, D., Crespo-Facorro, B., Crowley, J., Davidson, M., DeLisi, L., Dinan, T., Donohoe, G., Drapeau, E., Duan, J., Haan, L., Hougaard, D., Karachanak-Yankova, S., Khrunin, A., Klovins, J., Kucinskas, V., Keong, J., Limborska, S., Loughland, C., Lonnqvist, J., Maher, B., Mattheisen, M., McDonald, C., Murphy, K. C., Nenadic, I., van Os, J., Pantelis, C., Pato, M., Petryshen, T., Quested, D., Roussos, P., Sanders, A. R., Schall, U., Schwab, S. G., Sim, K., So, H., Stoegmann, E., Subramaniam, M., Toncheva, D., Waddington, J., Walters, J., Weiser, M., Cheng, W., Cloninger, R., Curtis, D., Gejman, P. V., Henskens, F., Mattingsdal, M., Oh, S., Scott, R., Webb, B., Breen, G., Churchhouse, C., Bulik, C. M., Daly, M., Dichgans, M., Faraone, S. V., Guerreiro, R., Holmans, P., Kendler, K. S., Koeleman, B., Mathews, C. A., Price, A., Scharf, J., Sklar, P., Williams, J., Wood, N. W., Cotsapas, C., Palotie, A., Smoller, J. W., Sullivan, P., Rosand, J., Corvin, A., Neale, B. M., Brainstorm Consortium 2018; 360 (6395): 1313-+

    Abstract

    Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

    View details for PubMedID 29930110

  • Genetic Pathway Analysis to Characterize the Role of Glia in Psychosis Duncan, L., Holmans, P., O'Dushlaine, C., Lee, P., Smoller, J., Ongur, D., Cohen, B. ELSEVIER SCIENCE INC. 2018: S69

    View details for Web of Science ID 000432466300171

  • Large-Scale Genetic Characterization of PTSD: Addressing Heterogeneity Across Ancestry, Sex, and Trauma Nievergelt, C., Maihofer, A., Dalvie, S., Duncan, L., Ratanatharathorn, A., Ressler, K., Liberzon, I., Koenen, K., PGC PTSD Workgrp ELSEVIER SCIENCE INC. 2018: S64

    View details for Web of Science ID 000432466300158

  • THE PGC GWAS META-ANALYSIS OF ANOREXIA NERVOSA: SNP HERITABILITY, GENETIC CORRELATIONS, AND SNP RESULTS Bulik, C., Duncan, L., Breen, G., PGC AN Working Grp ELSEVIER SCIENCE BV. 2017: S360–S361

    View details for DOI 10.1016/j.euroneuro.2016.09.381

    View details for Web of Science ID 000413847300010

  • Largest GWAS of PTSD (N=20,070) Yields Genetic Overlap with Schizophrenia and Sex Differences in Heritability Molecular Psychiatry Duncan, L. E., Ratanatharathorn, A., Aiello, A., Almli, L., Amstadter, A., additional_authors, ., Koenen, K. 2017
  • Genetic Correlation Profile of Schizophrenia Mirrors Epidemiological Results and Suggests Link Between Polygenic and Rare Variant (22q11.2) Cases of Schizophrenia. Schizophrenia bulletin Duncan, L. E., Shen, H., Ballon, J. S., Hardy, K. V., Noordsy, D. L., Levinson, D. F. 2017

    Abstract

    New methods in genetics research, such as linkage disequilibrium score regression (LDSR), quantify overlap in the common genetic variants that influence diverse phenotypes. It is becoming clear that genetic effects often cut across traditional diagnostic boundaries. Here, we introduce genetic correlation analysis (using LDSR) to a nongeneticist audience and report transdisciplinary discoveries about schizophrenia. This analytical study design used publically available genome wide association study (GWAS) data from approximately 1.5 million individuals. Genetic correlations between schizophrenia and 172 medical, psychiatric, personality, and metabolomic phenotypes were calculated using LDSR, as implemented in LDHub in order to identify known and new genetic correlations. Consistent with previous research, the strongest genetic correlation was with bipolar disorder. Positive genetic correlations were also found between schizophrenia and all other psychiatric phenotypes tested, the personality traits of neuroticism and openness to experience, and cigarette smoking. Novel results were found with medical phenotypes: schizophrenia was negatively genetically correlated with serum citrate, positively correlated with inflammatory bowel disease, and negatively correlated with BMI, hip, and waist circumference. The serum citrate finding provides a potential link between rare cases of schizophrenia (strongly influenced by 22q11.2 deletions) and more typical cases of schizophrenia (with polygenic influences). Overall, these genetic correlation findings match epidemiological findings, suggesting that common variant genetic effects are part of the scaffolding underlying phenotypic comorbidity. The "genetic correlation profile" is a succinct report of shared genetic effects, is easily updated with new information (eg, from future GWAS), and should become part of basic disease knowledge about schizophrenia.

    View details for PubMedID 29294133

  • Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa American Journal of Psychiatry Duncan, L. E., Yilmaz, Z., Gaspar, H., Walters, R., Goldstein, J., Anttila, V., Bulik-Sullivan, B., Ripke, S., Eating Disorders Working Group of the Psychiatric Genomics Consortium, ., Thornton, L., Hinney, A., Daly, M., Sullivan, P., Zeggini, E., Breen, G., Bulk, C. 2017
  • Analysis of protein-coding genetic variation in 60,706 humans NATURE Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O'Donnell-Luria, A. H., Ware, J. S., Hill, A. J., Cummings, B. B., Tukiainen, T., Birnbaum, D. P., Kosmicki, J. A., Duncan, L. E., Estrada, K., Zhao, F., Zou, J., Pierce-Hollman, E., Berghout, J., Cooper, D. N., Deflaux, N., DePristo, M., Do, R., Flannick, J., Fromer, M., Gauthier, L., Goldstein, J., Gupta, N., Howrigan, D., Kiezun, A., Kurki, M. I., Moonshine, A. L., Natarajan, P., Orozeo, L., Peloso, G. M., Poplin, R., Rivas, M. A., Ruano-Rubio, V., Rose, S. A., Ruderfer, D. M., Shakir, K., Stenson, P. D., Stevens, C., Thomas, B. P., Tiao, G., Tusie-Luna, M. T., Weisburd, B., Won, H., Yu, D., Altshuler, D. M., Ardissino, D., Boehnke, M., Danesh, J., Donnelly, S., Elosua, R., Florez, J. C., Gabriel, S. B., Getz, G., Glatt, S. J., Hultman, C. M., Kathiresan, S., Laakso, M., NcCarroll, S., McCarthy, M. I., McGovern, D., McPherson, R., Neale, B. M., Palotie, A., Purcell, S. M., Saleheen, D., Scharf, J. M., Sklar, P., Sullivan, P. F., Tuomilehto, J., Tsuang, M. T., Watkins, H. C., Wilson, J. G., Daly, M. J., MacArthur, D. G. 2016; 536 (7616): 285-?

    Abstract

    Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

    View details for DOI 10.1038/nature19057

    View details for Web of Science ID 000381804900026

    View details for PubMedID 27535533

  • Research Letter: PTSD has shared polygenic contributions with bipolar disorder and schizophrenia in women PSYCHOLOGICAL MEDICINE Sumner, J. A., Duncan, L., Ratanatharathorn, A., Roberts, A. L., Koenen, K. C. 2016; 46 (3): 669-671

    View details for DOI 10.1017/S0033291715002135

    View details for Web of Science ID 000367172500020

    View details for PubMedID 26464113

  • An atlas of genetic correlations across human diseases and traits NATURE GENETICS Bulik-Sullivan, B., Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P., Duncan, L., Perry, J. R., Patterson, N., Robinson, E. B., Daly, M. J., Price, A. L., Neale, B. M. 2015; 47 (11): 1236-?

    Abstract

    Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual-level genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique-cross-trait LD Score regression-for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity, and educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

    View details for DOI 10.1038/ng.3406

    View details for Web of Science ID 000363988200006

    View details for PubMedID 26414676

  • Large Scale Genetic Research on Neuropsychiatric Disorders in African Populations is Needed. EBioMedicine Dalvie, S., Koen, N., Duncan, L., Abbo, C., Akena, D., Atwoli, L., Chiliza, B., Donald, K. A., Kinyanda, E., Lochner, C., Mall, S., Nakasujja, N., Newton, C. R., Ramesar, R., Sibeko, G., Teferra, S., Stein, D. J., Koenen, K. C. 2015; 2 (10): 1259-1261

    View details for DOI 10.1016/j.ebiom.2015.10.002

    View details for PubMedID 26629498

    View details for PubMedCentralID PMC4634677

  • The Psychiatric Genomics Consortium Posttraumatic Stress Disorder Workgroup: Posttraumatic Stress Disorder Enters the Age of Large-Scale Genomic Collaboration NEUROPSYCHOPHARMACOLOGY Logue, M. W., Amstadter, A. B., Baker, D. G., Duncan, L., Koenen, K. C., Liberzon, I., Miller, M. W., Morey, R. A., Nievergelt, C. M., Ressler, K. J., Smith, A. K., Smoller, J. W., Stein, M. B., Sumner, J. A., Uddin, M. 2015; 40 (10): 2287-2297

    Abstract

    The development of posttraumatic stress disorder (PTSD) is influenced by genetic factors. Although there have been some replicated candidates, the identification of risk variants for PTSD has lagged behind genetic research of other psychiatric disorders such as schizophrenia, autism, and bipolar disorder. Psychiatric genetics has moved beyond examination of specific candidate genes in favor of the genome-wide association study (GWAS) strategy of very large numbers of samples, which allows for the discovery of previously unsuspected genes and molecular pathways. The successes of genetic studies of schizophrenia and bipolar disorder have been aided by the formation of a large-scale GWAS consortium: the Psychiatric Genomics Consortium (PGC). In contrast, only a handful of GWAS of PTSD have appeared in the literature to date. Here we describe the formation of a group dedicated to large-scale study of PTSD genetics: the PGC-PTSD. The PGC-PTSD faces challenges related to the contingency on trauma exposure and the large degree of ancestral genetic diversity within and across participating studies. Using the PGC analysis pipeline supplemented by analyses tailored to address these challenges, we anticipate that our first large-scale GWAS of PTSD will comprise over 10 000 cases and 30 000 trauma-exposed controls. Following in the footsteps of our PGC forerunners, this collaboration-of a scope that is unprecedented in the field of traumatic stress-will lead the search for replicable genetic associations and new insights into the biological underpinnings of PTSD.

    View details for DOI 10.1038/npp.2015.118

    View details for Web of Science ID 000359493700001

    View details for PubMedID 25904361

  • The Evaluation of Tools Used to Predict the Impact of Missense Variants Is Hindered by Two Types of Circularity HUMAN MUTATION Grimm, D. G., Azencott, C., Aicheler, F., Gieraths, U., MacArthur, D. G., Samocha, K. E., Cooper, D. N., Stenson, P. D., Daly, M. J., Smoller, J. W., Duncan, L. E., Borgwardt, K. M. 2015; 36 (5): 513-523

    Abstract

    Prioritizing missense variants for further experimental investigation is a key challenge in current sequencing studies for exploring complex and Mendelian diseases. A large number of in silico tools have been employed for the task of pathogenicity prediction, including PolyPhen-2, SIFT, FatHMM, MutationTaster-2, MutationAssessor, Combined Annotation Dependent Depletion, LRT, phyloP, and GERP++, as well as optimized methods of combining tool scores, such as Condel and Logit. Due to the wealth of these methods, an important practical question to answer is which of these tools generalize best, that is, correctly predict the pathogenic character of new variants. We here demonstrate in a study of 10 tools on five datasets that such a comparative evaluation of these tools is hindered by two types of circularity: they arise due to (1) the same variants or (2) different variants from the same protein occurring both in the datasets used for training and for evaluation of these tools, which may lead to overly optimistic results. We show that comparative evaluations of predictors that do not address these types of circularity may erroneously conclude that circularity confounded tools are most accurate among all tools, and may even outperform optimized combinations of tools.

    View details for DOI 10.1002/humu.22768

    View details for Web of Science ID 000353357300004

    View details for PubMedID 25684150

    View details for PubMedCentralID PMC4409520

  • Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways NATURE NEUROSCIENCE O'Dushlaine, C., Rossin, L., Lee, P. H., Duncan, L., Parikshak, N. N., Newhouse, S., Ripke, S., Neale, B. M., Purcell, S. M., Posthuma, D., Nurnberger, J. I., Lee, S. H., Faraone, S. V., Perlis, R. H., Mowry, B. J., Thapar, A., Goddard, M. E., Witte, J. S., Absher, D., Agartz, I., Akil, H., Amin, F., Andreassen, O. A., Anjorin, A., Anney, R., Anttila, V., Arking, D. E., Asherson, P., Azevedo, M. H., Backlund, L., Badner, J. A., Bailey, A. J., Banaschewski, T., Barchas, J. D., Barnes, M. R., Barrett, T. B., Bass, N., Battaglia, A., Bauer, M., Bayes, M., Bellivier, F., Bergen, S. E., Berrettini, W., Betancur, C., Bettecken, T., Biederman, J., Binder, E. B., Black, D. W., Blackwood, D. H., Bloss, C. S., Boehnke, M., Boomsma, D. I., Breuer, R., Bruggeman, R., Cormican, P., Buccola, N. G., Buitelaar, J. K., Bunney, W. E., Buxbaum, J. D., Byerley, W. F., Byrne, E. M., Caesar, S., Cahn, W., Cantor, R. M., Casas, M., Chakravarti, A., Chambert, K., Choudhury, K., Cichon, S., Mattheisen, M., Cloninger, C. R., Collier, D. A., Cook, E. H., Coon, H., Cormand, B., Corvin, A., Coryell, W. H., Craig, D. W., Craig, I. W., Crosbie, J., Cuccaro, M. L., Curtis, D., Czamara, D., Datta, S., Dawson, G., Day, R., de Geus, E. J., Degenhardt, F., Djurovic, S., Donohoe, G. J., Doyle, A. E., Duan, J., Dudbridge, F., Duketis, E., Ebstein, R. P., Edenberg, H. J., Elia, J., Ennis, S., Etain, B., Fanous, A., Farmer, A. E., Ferrier, I. N., Flicldnger, M., Fombonne, E., Foroud, T., Frank, J., Franke, B., Fraser, C., Freedman, R., Freimer, N. B., Freitag, C. M., Friedl, M., Frisen, L., Gailagher, L., Gejman, P. V., Georgieva, L., Gershon, E. S., Giegling, I., Gill, M., Gordon, S. D., Gordon-Smith, K., Green, E. K., Greenwood, T. A., Grice, D. E., Gross, M., Grozeva, D., Guan, W., Gurling, H., de Haan, L., Haines, J. L., Hakonarson, H., Hallmayer, J., Hamilton, S. P., Hamshere, M. L., Hansen, T. F., Hartmann, A. M., Hautzinger, M., Heath, A. C., Henders, A. K., Herms, S., Hickie, I. B., Hipolito, M., Hoefels, S., Holsboer, F., Hoogendijk, W. J., Hottenga, J., Hultman, C. M., Hus, V., Ingason, A., Ising, M., Jamain, S., Jones, E. G., Jones, I., Jones, L., Tzeng, J., Kaehler, A. K., Kahn, R. S., Kandaswamy, R., Keller, M. C., Kennedy, J. L., Kenny, E., Kent, L., Kim, Y., Kirov, G. K., Klauck, S. M., Klei, L., Knowles, J. A., Kohli, M. A., Koller, D. L., Konte, B., Korszun, A., Krabbendam, L., Krasucki, R., Kuntsi, J., Kwan, P., Landen, M., Laengstroem, N., Lathrop, M., Lawrence, J., Lawson, W. B., Leboyer, M., Ledbetter, D. H., Lencz, T., Lesch, K., Levinson, D. F., Lewis, C. M., Li, J., Lichtenstein, P., Lieberman, J. A., Lin, D., Linszen, D. H., Liu, C., Lohoff, F. W., Loo, S. K., Lord, C., Lowe, J. K., Lucae, S., MacIntyre, D. J., Madden, P. A., Maestrini, E., Magnusson, P. K., Mahon, P. B., Maier, W., Malhotra, A. K., Mane, S. M., Martin, C. L., Martin, N. G., Matthews, K., Mattingsdal, M., McCarroll, S. A., McGhee, K. A., McGough, J. J., McGrath, P. J., McGuffin, P., McInnis, M. G., McIntosh, A., McKinney, R., McLean, A. W., McMahon, F. J., McMahon, W. M., McQuillin, A., Medeiros, H., Medland, S. E., Meier, S., Melle, I., Meng, F., Meyer, J., Middeldorp, C. M., Middleton, L., Milanova, V., Miranda, A., Monaco, A. P., Montgomery, G. W., Moran, J. L., Moreno-De-Luca, D., Morken, G., Morris, D. W., Morrow, E. M., Moskvina, V., Muglia, P., Muehleisen, T. W., Muir, W. J., Mueller-Myhsok, B., Murtha, M., Myers, R. M., Myin-Germeys, I., Neale, M. C., Nelson, S. F., Nievergelt, C. M., Nikolov, I., Nimgaonkar, V., Nolen, W. A., Noethen, M. M., Nwulia, E. A., Nyholt, D. R., Oades, R. D., Olincy, A., Oliveira, G., Olsen, L., Ophoff, R. A., Osby, U., Owen, M. J., Palotie, A., Parr, J. R., Paterson, A. D., Pato, C. N., Pato, M. T., Penninx, B. W., Pergadia, M. L., Pericak-Vance, M. A., Pickard, B. S., Pimm, J., Piven, J., Potash, J. B., Poustka, F., Propping, P., Puri, V., Quested, D. J., Quinn, E. M., Ramos-Quiroga, J. A., Rasmussen, H. B., Raychaudhuri, S., Rehnstroem, K., Reif, A., Ribases, M., Rice, J. P., Rietschel, M., Roeder, K., Roeyers, H., Rothenberger, A., Rouleau, G., Ruderfer, D., Rujescu, D., Sanders, A. R., Sanders, S. J., Santangelo, S. L., Sergeant, J. A., Schachar, R., Schalling, M., Schatzberg, A. F., Scheftner, W. A., Schellenberg, G. D., Scherer, S. W., Schork, N. J., Schulze, T. G., Schumacher, J., Schwarz, M., Scolnick, E., Scott, L. J., Shi, J., Shilling, P. D., Shyn, S. I., Silverman, J. M., Slager, S. L., Smalley, S. L., Smit, J. H., Smith, E. N., Sonuga-Barke, E. J., Cair, D. S., State, M., Steffens, M., Steinhausen, H., Strauss, J. S., Strohmaier, J., Stroup, T. S., Sutdiffe, J. S., Szatmari, P., Szelinger, S., Thirumalai, S., Thompson, R. C., Todorov, A. A., Tozzi, F., Treutlein, J., Uhr, M., van den Oord, E. J., Van Grootheest, G., van Os, J., Vicente, A. M., Vieland, V. J., Vincent, J. B., Visscher, P. M., Walsh, C. A., Wassink, T. H., Watson, S. J., Weissman, M. M., Werge, T., Wienker, T. F., Wijsman, E. M., Willemsen, G., Williams, N., Willsey, A. J., Witt, S. H., Xu, W., Young, A. H., Yu, T. W., Zammit, S., Zandi, P. P., Zhang, P., Zitman, F. G., Zoellner, S., Devlin, B., Kelsoe, J. R., Sklar, P., Daly, M. J., O'Donovan, M. C., Craddock, N., Kendler, K. S., Weiss, L. A., Wray, N. R., Zhao, Z., Geschwind, D. H., Sullivan, P. F., Smoller, J. W., Holmans, P. A., Breen, G. 2015; 18 (2): 199-209

    Abstract

    Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

    View details for DOI 10.1038/nn.3922

    View details for Web of Science ID 000348631800010

    View details for PubMedID 25599223

    View details for PubMedCentralID PMC4378867

  • The Human Ortholog of Acid-Sensing Ion Channel Gene ASIC1a Is Associated With Panic Disorder and Amygdala Structure and Function BIOLOGICAL PSYCHIATRY Smoller, J. W., Gallagher, P. J., Duncan, L. E., McGrath, L. M., Haddad, S. A., Holmes, A. J., Wolf, A. B., Hilker, S., Block, S. R., Weill, S., Young, S., Choi, E. Y., Rosenbaum, J. F., Biederman, J., Faraone, S. V., Roffman, J. L., Manfro, G. G., Blaya, C., Hirshfeld-Becker, D. R., Stein, M. B., Van Ameringen, M., Tolin, D. F., Otto, M. W., Pollack, M. H., Simon, N. M., Buckner, R. L., Oenguer, D., Cohen, B. M. 2014; 76 (11): 902-910

    Abstract

    Individuals with panic disorder (PD) exhibit a hypersensitivity to inhaled carbon dioxide, possibly reflecting a lowered threshold for sensing signals of suffocation. Animal studies have shown that carbon dioxide-mediated fear behavior depends on chemosensing of acidosis in the amygdala via the acid-sensing ion channel ASIC1a. We examined whether the human ortholog of the ASIC1a gene, ACCN2, is associated with the presence of PD and with amygdala structure and function.We conducted a case-control analysis (n = 414 PD cases and 846 healthy controls) of ACCN2 single nucleotide polymorphisms and PD. We then tested whether variants showing significant association with PD are also associated with amygdala volume (n = 1048) or task-evoked reactivity to emotional stimuli (n = 103) in healthy individuals.Two single nucleotide polymorphisms at the ACCN2 locus showed evidence of association with PD: rs685012 (odds ratio = 1.32, gene-wise corrected p = .011) and rs10875995 (odds ratio = 1.26, gene-wise corrected p = .046). The association appeared to be stronger when early-onset (age ≤ 20 years) PD cases and when PD cases with prominent respiratory symptoms were compared with controls. The PD risk allele at rs10875995 was associated with increased amygdala volume (p = .035) as well as task-evoked amygdala reactivity to fearful and angry faces (p = .0048).Genetic variation at ACCN2 appears to be associated with PD and with amygdala phenotypes that have been linked to proneness to anxiety. These results support the possibility that modulation of acid-sensing ion channels may have therapeutic potential for PD.

    View details for DOI 10.1016/j.biopsych.2013.12.018

    View details for Web of Science ID 000344733200013

    View details for PubMedID 24529281

  • Clozapine-induced agranulocytosis is associated with rare HLA-DQB1 and HLA-B alleles NATURE COMMUNICATIONS Goldstein, J. I., Jarskog, L. F., Hilliard, C., Alfirevic, A., Duncan, L., Fourches, D., Huang, H., Lek, M., Neale, B. M., Ripke, S., Shianna, K., Szatkiewicz, J. P., Tropsha, A., van den Oord, E. J., Cascorbi, I., Dettling, M., Gazit, E., Goff, D. C., Holden, A. L., Kelly, D. L., Malhotra, A. K., Nielsen, J., Pirmohamed, M., Rujescu, D., Werge, T., Levy, D. L., Josiassen, R. C., Kennedy, J. L., Lieberman, J. A., Daly, M. J., Sullivan, P. F. 2014; 5

    Abstract

    Clozapine is a particularly effective antipsychotic medication but its use is curtailed by the risk of clozapine-induced agranulocytosis/granulocytopenia (CIAG), a severe adverse drug reaction occurring in up to 1% of treated individuals. Identifying genetic risk factors for CIAG could enable safer and more widespread use of clozapine. Here we perform the largest and most comprehensive genetic study of CIAG to date by interrogating 163 cases using genome-wide genotyping and whole-exome sequencing. We find that two loci in the major histocompatibility complex are independently associated with CIAG: a single amino acid in HLA-DQB1 (126Q) (P=4.7 × 10(-14), odds ratio (OR)=0.19, 95% confidence interval (CI)=0.12-0.29) and an amino acid change in the extracellular binding pocket of HLA-B (158T) (P=6.4 × 10(-10), OR=3.3, 95% CI=2.3-4.9). These associations dovetail with the roles of these genes in immunogenetic phenotypes and adverse drug responses for other medications, and provide insight into the pathophysiology of CIAG.

    View details for DOI 10.1038/ncomms5757

    View details for Web of Science ID 000342927300001

    View details for PubMedID 25187353

  • Personality Pathology Factors Predict Recurrent Major Depressive Disorder in Emerging Adults JOURNAL OF CLINICAL PSYCHOLOGY Sheets, E. S., Duncan, L. E., Bjornsson, A. S., Craighead, L. W., Craighead, W. E. 2014; 70 (6): 536-545

    Abstract

    Prior investigations consistently indicate that personality pathology is a risk factor for recurrence of major depressive disorder (MDD). Lack of emipircal support, however, for the Diagnostic and Statistical Manual of Mental Disorders (DSM) Fourth Edition organization of Axis II disorders supports the investigation of empirically derived factors of personality pathology as predictors of recurrence.A sample of 130 previously depressed emerging adults (80% female; aged 18 to 21 years) were assessed for personality disorder symptoms at baseline. Participants were then followed for 18 months to identify MDD recurrence during the first 2 years of college.Based on a previous factor analysis of DSM personality disorder criteria, eight personality pathology factors were examined as predictors of MDD recurrence. Survival analysis indicated that factors of interpersonal hypersensitivity, antisocial conduct, and social anxiety were associated with increased risk of MDD recurrence.These findings suggest that an empirically based approach to personality pathology organization may yield useful predictors of MDD recurrence during emerging adulthood.

    View details for DOI 10.1002/jclp.22028

    View details for Web of Science ID 000334846400005

    View details for PubMedID 23852879

  • Mind the Gap Why Many Geneticists and Psychological Scientists Have Discrepant Views About Gene-Environment Interaction (GXE) Research AMERICAN PSYCHOLOGIST Duncan, L. E., Pollastri, A. R., Smoller, J. W. 2014; 69 (3): 249-268

    Abstract

    As our field seeks to elucidate the biopsychosocial etiologies of mental health disorders, many traditional psychological and social science researchers have added, or plan to add, genetic components to their programs of research. An understanding of the history, methods, and perspectives of the psychiatric genetics community is useful in this pursuit. In this article we provide a brief overview of psychiatric genetic methods and findings. This overview lays the groundwork for a more thorough review of gene-environment interaction (G×E) research and the candidate gene approach to G×E research that remains popular among many psychologists and social scientists. We describe the differences in perspective between psychiatric geneticists and psychological scientists that have contributed to a growing divide between the research cited and conducted by these two related disciplines. Finally, we outline a strategy for the future of research on gene-environment interactions that capitalizes on the relative strengths of each discipline. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

    View details for DOI 10.1037/a0036320

    View details for Web of Science ID 000334685500003

    View details for PubMedID 24750075

  • Pathway Analyses Implicate Glial Cells in Schizophrenia PLOS ONE Duncan, L. E., Holmans, P. A., Lee, P. H., O'Dushlaine, C. T., Kirby, A. W., Smoller, J. W., Oenguer, D., Cohen, B. M. 2014; 9 (2)

    Abstract

    The quest to understand the neurobiology of schizophrenia and bipolar disorder is ongoing with multiple lines of evidence indicating abnormalities of glia, mitochondria, and glutamate in both disorders. Despite high heritability estimates of 81% for schizophrenia and 75% for bipolar disorder, compelling links between findings from neurobiological studies, and findings from large-scale genetic analyses, are only beginning to emerge.Ten publically available gene sets (pathways) related to glia, mitochondria, and glutamate were tested for association to schizophrenia and bipolar disorder using MAGENTA as the primary analysis method. To determine the robustness of associations, secondary analyses were performed with: ALIGATOR, INRICH, and Set Screen. Data from the Psychiatric Genomics Consortium (PGC) were used for all analyses. There were 1,068,286 SNP-level p-values for schizophrenia (9,394 cases/12,462 controls), and 2,088,878 SNP-level p-values for bipolar disorder (7,481 cases/9,250 controls).The Glia-Oligodendrocyte pathway was associated with schizophrenia, after correction for multiple tests, according to primary analysis (MAGENTA p = 0.0005, 75% requirement for individual gene significance) and also achieved nominal levels of significance with INRICH (p = 0.0057) and ALIGATOR (p = 0.022). For bipolar disorder, Set Screen yielded nominally and method-wide significant associations to all three glial pathways, with strongest association to the Glia-Astrocyte pathway (p = 0.002).Consistent with findings of white matter abnormalities in schizophrenia by other methods of study, the Glia-Oligodendrocyte pathway was associated with schizophrenia in our genomic study. These findings suggest that the abnormalities of myelination observed in schizophrenia are at least in part due to inherited factors, contrasted with the alternative of purely environmental causes (e.g. medication effects or lifestyle). While not the primary purpose of our study, our results also highlight the consequential nature of alternative choices regarding pathway analysis, in that results varied somewhat across methods, despite application to identical datasets and pathways.

    View details for DOI 10.1371/journal.pone.0089441

    View details for Web of Science ID 000331880700045

    View details for PubMedID 24586781

    View details for PubMedCentralID PMC3933626

  • A polygenic burden of rare disruptive mutations in schizophrenia NATURE Purcell, S. M., Moran, J. L., Fromer, M., Ruderfer, D., Solovieff, N., Roussos, P., O'Dushlaine, C., Chambert, K., Bergen, S. E., Kahler, A., Duncan, L., Stahl, E., Genovese, G., Fernandez, E., Collins, M. O., Komiyama, N. H., Choudhary, J. S., Magnusson, P. K., Banks, E., Shakir, K., Garimella, K., Fennell, T., DePristo, M., Grant, S. G., Haggarty, S. J., Gabriel, S., Scolnick, E. M., Lander, E. S., Hultman, C. M., Sullivan, P. F., McCarroll, S. A., Sklar, P. 2014; 506 (7487): 185-?

    Abstract

    Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease.

    View details for DOI 10.1038/nature12975

    View details for Web of Science ID 000331107700030

    View details for PubMedID 24463508

    View details for PubMedCentralID PMC4136494

  • Genetic Predictors of Risk and Resilience in Psychiatric Disorders: A Cross-Disorder Genome-Wide Association Study of Functional Impairment in Major Depressive Disorder, Bipolar Disorder, and Schizophrenia AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS McGrath, L. M., Cornelis, M. C., Lee, P. H., Robinson, E. B., Duncan, L. E., Barnett, J. H., Huang, J., Gerber, G., Sklar, P., Sullivan, P., Perlis, R. H., Smoller, J. W. 2013; 162 (8): 779-788

    View details for DOI 10.1002/ajmg.b.32190

    View details for Web of Science ID 000326506700001

  • From Candidate Genes to Genome-wide Association: The Challenges and Promise of Posttraumatic Stress Disorder Genetic Studies BIOLOGICAL PSYCHIATRY Koenen, K. C., Duncan, L. E., Liberzon, I., Ressler, K. J. 2013; 74 (9): 634-636

    View details for DOI 10.1016/j.biopsych.2013.08.022

    View details for Web of Science ID 000325472900003

    View details for PubMedID 24120289

  • Paying Attention to All Results, Positive and Negative JOURNAL OF THE AMERICAN ACADEMY OF CHILD AND ADOLESCENT PSYCHIATRY Duncan, L. E. 2013; 52 (5): 462-465

    View details for DOI 10.1016/j.jaac.2013.02.007

    View details for Web of Science ID 000318395100004

    View details for PubMedID 23622847

  • Conceptual Issues in Psychiatric Gene-Environment Interaction Research Response AMERICAN JOURNAL OF PSYCHIATRY Duncan, L. E., Keller, M. C. 2012; 169 (2): 223-223

    View details for DOI 10.1176/appi.ajp.2011.11111614r

    View details for Web of Science ID 000300121100020

  • A Critical Review of the First 10 Years of Candidate Gene-by-Environment Interaction Research in Psychiatry AMERICAN JOURNAL OF PSYCHIATRY Duncan, L. E., Keller, M. C. 2011; 168 (10): 1041-1049

    Abstract

    Gene-by-environment interaction (G×E) studies in psychiatry have typically been conducted using a candidate G×E (cG×E) approach, analogous to the candidate gene association approach used to test genetic main effects. Such cG×E research has received widespread attention and acclaim, yet cG×E findings remain controversial. The authors examined whether the many positive cG×E findings reported in the psychiatric literature were robust or if, in aggregate, cG×E findings were consistent with the existence of publication bias, low statistical power, and a high false discovery rate.The authors conducted analyses on data extracted from all published studies (103 studies) from the first decade (2000-2009) of cG×E research in psychiatry.Ninety-six percent of novel cG×E studies were significant compared with 27% of replication attempts. These findings are consistent with the existence of publication bias among novel cG×E studies, making cG×E hypotheses appear more robust than they actually are. There also appears to be publication bias among replication attempts because positive replication attempts had smaller average sample sizes than negative ones. Power calculations using observed sample sizes suggest that cG×E studies are underpowered. Low power along with the likely low prior probability of a given cG×E hypothesis being true suggests that most or even all positive cG×E findings represent type I errors.In this new era of big data and small effects, a recalibration of views about groundbreaking findings is necessary. Well-powered direct replications deserve more attention than novel cG×E findings and indirect replications.

    View details for DOI 10.1176/appi.ajp.2011.11020191

    View details for Web of Science ID 000295481200011

    View details for PubMedID 21890791

  • Understanding the Complex Etiologies of Developmental Disorders: Behavioral and Molecular Genetic Approaches JOURNAL OF DEVELOPMENTAL AND BEHAVIORAL PEDIATRICS Willcutt, E. G., Pennington, B. F., Duncan, L., Smith, S. D., Keenan, J. M., Wadsworth, S., DeFries, J. C., Olson, R. K. 2010; 31 (7): 533-544

    Abstract

    This article has 2 primary goals. First, a brief tutorial on behavioral and molecular genetic methods is provided for readers without extensive training in these areas. To illustrate the application of these approaches to developmental disorders, etiologically informative studies of reading disability (RD), math disability (MD), and attention-deficit hyperactivity disorder (ADHD) are then reviewed. Implications of the results for these specific disorders and for developmental disabilities as a whole are discussed, and novel directions for future research are highlighted.Previous family and twin studies of RD, MD, and ADHD are reviewed systematically, and the extensive molecular genetic literatures on each disorder are summarized. To illustrate 4 novel extensions of these etiologically informative approaches, new data are presented from the Colorado Learning Disabilities Research Center, an ongoing twin study of the etiology of RD, ADHD, MD, and related disorders.RD, MD, and ADHD are familial and heritable, and co-occur more frequently than expected by chance. Molecular genetic studies suggest that all 3 disorders have complex etiologies, with multiple genetic and environmental risk factors each contributing to overall risk for each disorder. Neuropsychological analyses indicate that the 3 disorders are each associated with multiple neuropsychological weaknesses, and initial evidence suggests that comorbidity between the 3 disorders is due to common genetic risk factors that lead to slow processing speed.

    View details for DOI 10.1097/DBP.0b013e3181ef42a1

    View details for Web of Science ID 000281561700003

    View details for PubMedID 20814254

  • Are Extended Twin Family Designs Worth the Trouble? A Comparison of the Bias, Precision, and Accuracy of Parameters Estimated in Four Twin Family Models BEHAVIOR GENETICS Keller, M. C., Medland, S. E., Duncan, L. E. 2010; 40 (3): 377-393

    Abstract

    The classical twin design (CTD) uses observed covariances from monozygotic and dizygotic twin pairs to infer the relative magnitudes of genetic and environmental causes of phenotypic variation. Despite its wide use, it is well known that the CTD can produce biased estimates if its stringent assumptions are not met. By modeling observed covariances of twins' relatives in addition to twins themselves, extended twin family designs (ETFDs) require less stringent assumptions, can estimate many more parameters of interest, and should produce less biased estimates than the CTD. However, ETFDs are more complicated to use and interpret, and by attempting to estimate a large number of parameters, the precision of parameter estimates may suffer. This paper is a formal investigation into a simple question: Is it worthwhile to use more complex models such as ETFDs in behavioral genetics? In particular, we compare the bias, precision, and accuracy of estimates from the CTD and three increasingly complex ETFDs. We find the CTD does a decent job of estimating broad sense heritability, but CTD estimates of shared environmental effects and the relative importance of additive versus non-additive genetic variance can be biased, sometimes wildly so. Increasingly complex ETFDs, on the other hand, are more accurate and less sensitive to assumptions than simpler models. We conclude that researchers interested in characterizing the environment or the makeup of genetic variation should use ETFDs when possible.

    View details for DOI 10.1007/s10519-009-9320-x

    View details for Web of Science ID 000276603900011

    View details for PubMedID 20013306

  • Variation in brain-derived neurotrophic factor (BDNF) gene is associated with symptoms of depression JOURNAL OF AFFECTIVE DISORDERS Duncan, L. E., Hutchison, K. E., Carey, G., Craighead, W. E. 2009; 115 (1-2): 215-219

    Abstract

    Brain-derived neurotrophic factor (BDNF) is putatively involved in the pathophysiology of depression. This study examined associations between BDNF genotype at the Val66Met locus, depression symptoms, and serum BDNF levels.Twenty-eight subjects in the primary study (25 female, 3 male) completed diagnostic interviews, self-report questionnaires, and provided blood samples for serum BDNF quantification and buccal cell samples for genotyping. Data from a second sample of 189 subjects (94 female, 95 male) were also analyzed.The Val/Val genotype was associated with higher scores on the Cognitive-Affective factor of the Beck Depression Inventory-II (BDI-II) in the primary sample. No evidence was found for association between genotype and serum BDNF in this sample. Consistent with the primary study, Val/Val genotype was associated with higher total BDI-II scores, Cognitive-Affective factor scores, and Somatic-Vegetative factor scores, in the second sample. Serum BDNF measures were not available for the second sample.The mechanism through which BDNF genotype translates into (putative) differences in depression symptoms is not known.In contrast to case-control association studies, we demonstrate two changes in the operationalization of the phenotype. Additionally, we found an association between Val/Val genotype and higher levels of depression symptoms. This result is distinct from an association between BDNF genotype and diagnosis of depression, and it may help to clarify our understanding of genetic liability to depression, which will ultimately lead to more nuanced and effective treatment strategies.

    View details for DOI 10.1016/j.jad.2008.08.016

    View details for Web of Science ID 000265319900027

    View details for PubMedID 18842305

  • Modeling Extended Twin Family Data I: Description of the Cascade Model TWIN RESEARCH AND HUMAN GENETICS Keller, M. C., Medland, S. E., Duncan, L. E., Hatemi, P. K., Neale, M. C., Maes, H. H., Eaves, L. J. 2009; 12 (1): 8-18

    Abstract

    The classical twin design uses data on the variation of and covariation between monozygotic and dizygotic twins to infer underlying genetic and environmental causes of phenotypic variation in the population. By using data from additional relative classes, such as parents, extended twin family designs more comprehensively describe the causes of phenotypic variation. This article introduces an extension of previous extended twin family models, the Cascade model, which uses information on twins as well as their siblings, spouses, parents, and children to differentiate two genetic and six environmental sources of phenotypic variation. The Cascade also relaxes assumptions regarding mating and cultural transmission that existed in previous extended twin family designs. The estimation of additional parameters and relaxation of assumptions is potentially important, not only because it allows more fine-grained descriptions of the causes of phenotypic variation, but more importantly, because it can reduce the biases in parameter estimates that exist in earlier designs.

    View details for Web of Science ID 000263635000002

    View details for PubMedID 19210175

  • Experimental vesicular stomatitis virus infection in horses: Effect of route of inoculation and virus serotype VETERINARY PATHOLOGY Howerth, E. W., Mead, D. G., Mueller, P. O., Duncan, L., Murphy, M. D., Stallknecht, D. E. 2006; 43 (6): 943-955

    Abstract

    Horses were inoculated with Vesicular stomatitis New Jersey and Indiana viruses by routes simulating contact and vector transmission. Clinical signs, lesions, antibody development, viral shedding and persistence, and viremia were monitored. Horses were infected with both viruses by all routes as confirmed by seroconversion. Salivation, primary lesions at inoculation sites, and secondary oral lesions were the most common clinical findings. Viral shedding was most often from the oral cavity, followed by the nasal cavity; titers were highest from oral cavity samples. Virus was rarely isolated from the conjunctival sac and never from feces or blood. Development of neutralizing antibody coincided with cessation of lesion development and detection of virus by isolation. Circulating virus-specific IgM, IgG, IgA, and neutralizing antibodies developed in most animals postinoculation (PI) days 6 to 12, depending on the route of inoculation. At postmortem (PI days 12 to 15), lesions were healing, were not vesicular, and did not contain detectable virus by isolation, reverse transcriptase polymerase chain reaction, or immunohistochemistry. Numerous infiltrating lymphocytes and plasma cells suggested that lesion resolution was partially due to local immunity. Detection of viral RNA from tonsil and lymph nodes of head at necropsy suggests that these tissues play a role in the pathogenesis of the disease; molecular techniques targeting these tissues may be useful for confirming infection in resolving stages of disease. The routes of inoculation used in this study reflect the diversity of transmission routes that may occur during outbreaks and can be used to further study contact and vector transmission, vaccine development, and clarify pathogenesis of the disease in horses.

    View details for Web of Science ID 000242225800009

    View details for PubMedID 17099151