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1. Heritable influences on amygdala and orbitofrontal cortex contribute to genetic variation in core dimensions of personality

Author

Lewis, GJ, Panizzon, MS, Eyler, L, Fennema-Notestine, C, Chen, C-H, Neale, MC, Jernigan, TL, Lyons, MJ, Dale, AM, Kremen, WS, and Franz, CE

Subjects
Biomedical and Clinical Sciences, Health Sciences, Neurosciences, Genetics, 1.1 Normal biological development and functioning, Mental health, Amygdala, Female, Frontal Lobe, Genetic Variation, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Organ Size, Personality, Phenotype, MPQ, MRI, Orbitofrontal cortex, Twins, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

While many studies have reported that individual differences in personality traits are genetically influenced, the neurobiological bases mediating these influences have not yet been well characterized. To advance understanding concerning the pathway from genetic variation to personality, here we examined whether measures of heritable variation in neuroanatomical size in candidate regions (amygdala and medial orbitofrontal cortex) were associated with heritable effects on personality. A sample of 486 middle-aged (mean=55 years) male twins (complete MZ pairs=120; complete DZ pairs=84) underwent structural brain scans and also completed measures of two core domains of personality: positive and negative emotionality. After adjusting for estimated intracranial volume, significant phenotypic (r(p)) and genetic (r(g)) correlations were observed between left amygdala volume and positive emotionality (r(p)=.16, p

Published
2014

2. A multivariate twin study of hippocampal volume, self‐esteem and well‐being in middle‐aged men

Author

Kubarych, TS, Prom‐Wormley, EC, Franz, CE, Panizzon, MS, Dale, AM, Fischl, B, Eyler, LT, Fennema‐Notestine, C, Grant, MD, Hauger, RL, Hellhammer, DH, Jak, AJ, Jernigan, TL, Lupien, SJ, Lyons, MJ, Mendoza, SP, Neale, MC, Seidman, LJ, Tsuang, MT, and Kremen, WS

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Neurosciences, Genetics, Prevention, Mental Health, Aging, Hippocampus, Humans, Male, Middle Aged, Models, Psychological, Organ Size, Personal Satisfaction, Self Concept, heritability, hippocampus, self-esteem, twins, well-being, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Self-esteem and well-being are important for successful aging, and some evidence suggests that self-esteem and well-being are associated with hippocampal volume, cognition and stress responsivity. Whereas most of this evidence is based on studies on older adults, we investigated self-esteem, well-being and hippocampal volume in 474 male middle-aged twins. Self-esteem was significantly positively correlated with hippocampal volume (0.09, P = 0.03 for left hippocampus, 0.10, P = 0.04 for right). Correlations for well-being were not significant (Ps > 0.05). There were strong phenotypic correlations between self-esteem and well-being (0.72, P < 0.001) and between left and right hippocampal volume (0.72, P < 0.001). In multivariate genetic analyses, a two-factor additive genetic and unique environmental (AE) model with well-being and self-esteem on one factor and left and right hippocampal volumes on the other factor fits the data better than Cholesky, independent pathway or common pathway models. The correlation between the two genetic factors was 0.12 (P = 0.03); the correlation between the environmental factors was 0.09 (P > 0.05). Our results indicate that largely different genetic and environmental factors underlie self-esteem and well-being on one hand and hippocampal volume on the other.

Published
2012

3. Presence of ApoE ε4 allele associated with thinner frontal cortex in middle age

Author

Fennema-Notestine, C, Panizzon, MS, Thompson, WR, Chen, CH, Eyler, LT, Fischl, B, Franz, CE, Grant, MD, Jak, AJ, Jernigan, TL, Lyons, MJ, Neale, MC, Seidman, LJ, Tsuang, MT, Xian, H, Dale, AM, and Kremen, WS

Abstract

The presence of an ApoE ε4 allele (ε4+) increases the risk of developing Alzheimer's disease (AD). Previous studies support an adverse relationship between ε4+ status and brain structure and function in mild cognitive impairment and AD; in contrast, the presence of an ε2 allele may be protective. Whether these findings reflect disease-related effects or pre-existing endophenotypes, however, remains unclear. The present study examined the influence of ApoE allele status on brain structure solely during middle-age in a large, national sample. Participants were 482 men, ages 51-59, from the Vietnam Era Twin Study of Aging (VETSA). T1-weighted images were used in volumetric segmentation and cortical surface reconstruction methods to measure regional volume and thickness. Primary linear mixed effects models predicted structural measures with ApoE status (ε3/3, ε2/3, ε3/4) and control variables for effects of site, non-independence of twin data, age, and average cranial vault or cortical thickness. Relative to the ε3/3 group, the ε3/4 group demonstrated significantly thinner cortex in superior frontal and left rostral and right caudal midfrontal regions; there were no significant effects of ε4 status on any temporal lobe measures. The ε2/3 group demonstrated significantly thicker right parahippocampal cortex relative to the ε3/3 group. The ApoE ε4 allele may influence cortical thickness in frontal areas, which are later developing regions thought to be more susceptible to the natural aging process. Previous conflicting findings for mesial temporal regions may be driven by the inclusion of older individuals, who may evidence preclinical manifestations of disease, and by unexamined moderators of ε4-related effects. The presence of the ε2 allele was related to thicker cortex, supporting a protective role. Ongoing follow-up of the VETSA sample may shed light on the potential for age-and disease-related mediation of the influence of ApoE allele status. © 2011 The authors and IOS Press. All rights reserved.

Published
2011

4. Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information

Author

Maihofer, AX, Choi, KW, Coleman, JR, Daskalakis, NP, Denckla, CA, Ketema, E, Morey, RA, Polimanti, R, Ratanatharathorn, A, Torres, K, Wingo, AP, Zai, CC, Aiello, AE, Almli, LM, Amstadter, AB, Andersen, SB, Andreassen, OA, Arbisi, PA, Ashley-Koch, AE, Austin, SB, Avdibegovic, E, Borglum, AD, Babic, D, Baekvad-Hansen, M, Baker, DG, Beckham, JC, Bierut, LJ, Bisson, J, Boks, MP, Bolger, EA, Bradley, B, Brashear, M, Breen, G, Bryant, RA, Bustamante, AC, Bybjerg-Grauholm, J, Calabrese, JR, Caldas-de-Almeida, JM, Chen, C-Y, Dale, AM, Dalvie, S, Deckert, J, Delahanty, DL, Dennis, MF, Disner, SG, Domschke, K, Duncan, LE, Kulenovic, AD, Erbes, CR, Evans, A, Farrer, LA, Feeny, NC, Flory, JD, Forbes, D, Franz, CE, Galea, S, Garrett, ME, Gautam, A, Gelaye, B, Gelernter, J, Geuze, E, Gillespie, CF, Goci, A, Gordon, SD, Guffanti, G, Hammamieh, R, Hauser, MA, Heath, AC, Hemmings, SMJ, Hougaard, DM, Jakovljevic, M, Jett, M, Johnson, EO, Jones, I, Jovanovic, T, Qin, X-J, Karstoft, K-I, Kaufman, ML, Kessler, RC, Khan, A, Kimbrel, NA, King, AP, Koen, N, Kranzler, HR, Kremen, WS, Lawford, BR, Lebois, LAM, Lewis, C, Liberzon, I, Linnstaedt, SD, Logue, MW, Lori, A, Lugonja, B, Luykx, JJ, Lyons, MJ, Maples-Keller, JL, Marmar, C, Martin, NG, Maurer, D, Mavissakalian, MR, McFarlane, A, McGlinchey, RE, McLaughlin, KA, McLean, SA, Mehta, D, Mellor, R, Michopoulos, V, Milberg, W, Miller, MW, Morris, CP, Mors, O, Mortensen, PB, Nelson, EC, Nordentoft, M, Norman, SB, O'Donnell, M, Orcutt, HK, Panizzon, MS, Peters, ES, Peterson, AL, Peverill, M, Pietrzak, RH, Polusny, MA, Rice, JP, Risbrough, VB, Roberts, AL, Rothbaum, AO, Rothbaum, BO, Roy-Byrne, P, Ruggiero, KJ, Rung, A, Rutten, BPF, Saccone, NL, Sanchez, SE, Schijven, D, Seedat, S, Seligowski, A, Seng, JS, Sheerin, CM, Silove, D, Smith, AK, Smoller, JW, Sponheim, SR, Stein, DJ, Stevens, JS, Teicher, MH, Thompson, WK, Trapido, E, Uddin, M, Ursano, RJ, van den Heuvel, LL, Van Hooff, M, Vermetten, E, Vinkers, CH, Voisey, J, Wang, Y, Wang, Z, Werge, T, Williams, MA, Williamson, DE, Winternitz, S, Wolf, C, Wolf, EJ, Yehuda, R, Young, KA, Young, RM, Zhao, H, Zoellner, LA, Haas, M, Lasseter, H, Provost, AC, Salem, RM, Sebat, J, Shaffer, RA, Wu, T, Ripke, S, Daly, MJ, Ressler, KJ, Koenen, KC, Stein, MB, Nievergelt, CM, Maihofer, AX, Choi, KW, Coleman, JR, Daskalakis, NP, Denckla, CA, Ketema, E, Morey, RA, Polimanti, R, Ratanatharathorn, A, Torres, K, Wingo, AP, Zai, CC, Aiello, AE, Almli, LM, Amstadter, AB, Andersen, SB, Andreassen, OA, Arbisi, PA, Ashley-Koch, AE, Austin, SB, Avdibegovic, E, Borglum, AD, Babic, D, Baekvad-Hansen, M, Baker, DG, Beckham, JC, Bierut, LJ, Bisson, J, Boks, MP, Bolger, EA, Bradley, B, Brashear, M, Breen, G, Bryant, RA, Bustamante, AC, Bybjerg-Grauholm, J, Calabrese, JR, Caldas-de-Almeida, JM, Chen, C-Y, Dale, AM, Dalvie, S, Deckert, J, Delahanty, DL, Dennis, MF, Disner, SG, Domschke, K, Duncan, LE, Kulenovic, AD, Erbes, CR, Evans, A, Farrer, LA, Feeny, NC, Flory, JD, Forbes, D, Franz, CE, Galea, S, Garrett, ME, Gautam, A, Gelaye, B, Gelernter, J, Geuze, E, Gillespie, CF, Goci, A, Gordon, SD, Guffanti, G, Hammamieh, R, Hauser, MA, Heath, AC, Hemmings, SMJ, Hougaard, DM, Jakovljevic, M, Jett, M, Johnson, EO, Jones, I, Jovanovic, T, Qin, X-J, Karstoft, K-I, Kaufman, ML, Kessler, RC, Khan, A, Kimbrel, NA, King, AP, Koen, N, Kranzler, HR, Kremen, WS, Lawford, BR, Lebois, LAM, Lewis, C, Liberzon, I, Linnstaedt, SD, Logue, MW, Lori, A, Lugonja, B, Luykx, JJ, Lyons, MJ, Maples-Keller, JL, Marmar, C, Martin, NG, Maurer, D, Mavissakalian, MR, McFarlane, A, McGlinchey, RE, McLaughlin, KA, McLean, SA, Mehta, D, Mellor, R, Michopoulos, V, Milberg, W, Miller, MW, Morris, CP, Mors, O, Mortensen, PB, Nelson, EC, Nordentoft, M, Norman, SB, O'Donnell, M, Orcutt, HK, Panizzon, MS, Peters, ES, Peterson, AL, Peverill, M, Pietrzak, RH, Polusny, MA, Rice, JP, Risbrough, VB, Roberts, AL, Rothbaum, AO, Rothbaum, BO, Roy-Byrne, P, Ruggiero, KJ, Rung, A, Rutten, BPF, Saccone, NL, Sanchez, SE, Schijven, D, Seedat, S, Seligowski, A, Seng, JS, Sheerin, CM, Silove, D, Smith, AK, Smoller, JW, Sponheim, SR, Stein, DJ, Stevens, JS, Teicher, MH, Thompson, WK, Trapido, E, Uddin, M, Ursano, RJ, van den Heuvel, LL, Van Hooff, M, Vermetten, E, Vinkers, CH, Voisey, J, Wang, Y, Wang, Z, Werge, T, Williams, MA, Williamson, DE, Winternitz, S, Wolf, C, Wolf, EJ, Yehuda, R, Young, KA, Young, RM, Zhao, H, Zoellner, LA, Haas, M, Lasseter, H, Provost, AC, Salem, RM, Sebat, J, Shaffer, RA, Wu, T, Ripke, S, Daly, MJ, Ressler, KJ, Koenen, KC, Stein, MB, and Nievergelt, CM

Abstract

BACKGROUND: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). METHODS: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. RESULTS: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. CONCLUSIONS: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

Published
2022

5. Smoking remains associated with education after controlling for social background and genetic factors in a study of 18 twin cohorts

Author

Silventoinen, K, Piirtola, M, Jelenkovic, A, Sund, R, Tarnoki, AD, Tarnoki, DL, Medda, E, Nistico, L, Toccaceli, V, Honda, C, Inui, F, Tomizawa, R, Watanabe, M, Sakai, N, Gatz, M, Butler, DA, Lee, J, Lee, SJ, Sung, J, Franz, CE, Kremen, WS, Lyons, MJ, Derom, CA, Vlietinck, RF, Loos, RJF, Tynelius, P, Rasmussen, F, Martin, NG, Medland, SE, Montgomery, GW, Brandt, I, Nilsen, TS, Harris, JR, Tyler, J, Hopper, JL, Magnusson, PKE, Pedersen, NL, Aslan, AKD, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Rebato, E, Zhang, D, Pang, Z, Tan, Q, Silberg, JL, Maes, HH, Boomsma, D, Sorensen, TIA, Korhonen, T, Kaprio, J, Silventoinen, K, Piirtola, M, Jelenkovic, A, Sund, R, Tarnoki, AD, Tarnoki, DL, Medda, E, Nistico, L, Toccaceli, V, Honda, C, Inui, F, Tomizawa, R, Watanabe, M, Sakai, N, Gatz, M, Butler, DA, Lee, J, Lee, SJ, Sung, J, Franz, CE, Kremen, WS, Lyons, MJ, Derom, CA, Vlietinck, RF, Loos, RJF, Tynelius, P, Rasmussen, F, Martin, NG, Medland, SE, Montgomery, GW, Brandt, I, Nilsen, TS, Harris, JR, Tyler, J, Hopper, JL, Magnusson, PKE, Pedersen, NL, Aslan, AKD, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Rebato, E, Zhang, D, Pang, Z, Tan, Q, Silberg, JL, Maes, HH, Boomsma, D, Sorensen, TIA, Korhonen, T, and Kaprio, J

Abstract

We tested the causality between education and smoking using the natural experiment of discordant twin pairs allowing to optimally control for background genetic and childhood social factors. Data from 18 cohorts including 10,527 monozygotic (MZ) and same-sex dizygotic (DZ) twin pairs discordant for education and smoking were analyzed by linear fixed effects regression models. Within twin pairs, education levels were lower among the currently smoking than among the never smoking co-twins and this education difference was larger within DZ than MZ pairs. Similarly, education levels were higher among former smoking than among currently smoking co-twins, and this difference was larger within DZ pairs. Our results support the hypothesis of a causal effect of education on both current smoking status and smoking cessation. However, the even greater intra-pair differences within DZ pairs, who share only 50% of their segregating genes, provide evidence that shared genetic factors also contribute to these associations.

Published
2022

6. Rare copy number variation in posttraumatic stress disorder.

Author

Maihofer, AX, Engchuan, W, Huguet, G, Klein, M, MacDonald, JR, Shanta, O, Thiruvahindrapuram, B, Jean-Louis, M, Saci, Z, Jacquemont, S, Scherer, SW, Ketema, E, Aiello, AE, Amstadter, AB, Avdibegović, E, Babic, D, Baker, DG, Bisson, JI, Boks, MP, Bolger, EA, Bryant, RA, Bustamante, AC, Caldas-de-Almeida, JM, Cardoso, G, Deckert, J, Delahanty, DL, Domschke, K, Dunlop, BW, Dzubur-Kulenovic, A, Evans, A, Feeny, NC, Franz, CE, Gautam, A, Geuze, E, Goci, A, Hammamieh, R, Jakovljevic, M, Jett, M, Jones, I, Kaufman, ML, Kessler, RC, King, AP, Kremen, WS, Lawford, BR, Lebois, LAM, Lewis, C, Liberzon, I, Linnstaedt, SD, Lugonja, B, Luykx, JJ, Lyons, MJ, Mavissakalian, MR, McLaughlin, KA, McLean, SA, Mehta, D, Mellor, R, Morris, CP, Muhie, S, Orcutt, HK, Peverill, M, Ratanatharathorn, A, Risbrough, VB, Rizzo, A, Roberts, AL, Rothbaum, AO, Rothbaum, BO, Roy-Byrne, P, Ruggiero, KJ, Rutten, BPF, Schijven, D, Seng, JS, Sheerin, CM, Sorenson, MA, Teicher, MH, Uddin, M, Ursano, RJ, Vinkers, CH, Voisey, J, Weber, H, Winternitz, S, Xavier, M, Yang, R, McD Young, R, Zoellner, LA, Psychiatric Genomics Consortium PTSD Working Group, Psychiatric Genomics Consortium CNV Working Group, Salem, RM, Shaffer, RA, Wu, T, Ressler, KJ, Stein, MB, Koenen, KC, Sebat, J, Nievergelt, CM, Maihofer, AX, Engchuan, W, Huguet, G, Klein, M, MacDonald, JR, Shanta, O, Thiruvahindrapuram, B, Jean-Louis, M, Saci, Z, Jacquemont, S, Scherer, SW, Ketema, E, Aiello, AE, Amstadter, AB, Avdibegović, E, Babic, D, Baker, DG, Bisson, JI, Boks, MP, Bolger, EA, Bryant, RA, Bustamante, AC, Caldas-de-Almeida, JM, Cardoso, G, Deckert, J, Delahanty, DL, Domschke, K, Dunlop, BW, Dzubur-Kulenovic, A, Evans, A, Feeny, NC, Franz, CE, Gautam, A, Geuze, E, Goci, A, Hammamieh, R, Jakovljevic, M, Jett, M, Jones, I, Kaufman, ML, Kessler, RC, King, AP, Kremen, WS, Lawford, BR, Lebois, LAM, Lewis, C, Liberzon, I, Linnstaedt, SD, Lugonja, B, Luykx, JJ, Lyons, MJ, Mavissakalian, MR, McLaughlin, KA, McLean, SA, Mehta, D, Mellor, R, Morris, CP, Muhie, S, Orcutt, HK, Peverill, M, Ratanatharathorn, A, Risbrough, VB, Rizzo, A, Roberts, AL, Rothbaum, AO, Rothbaum, BO, Roy-Byrne, P, Ruggiero, KJ, Rutten, BPF, Schijven, D, Seng, JS, Sheerin, CM, Sorenson, MA, Teicher, MH, Uddin, M, Ursano, RJ, Vinkers, CH, Voisey, J, Weber, H, Winternitz, S, Xavier, M, Yang, R, McD Young, R, Zoellner, LA, Psychiatric Genomics Consortium PTSD Working Group, Psychiatric Genomics Consortium CNV Working Group, Salem, RM, Shaffer, RA, Wu, T, Ressler, KJ, Stein, MB, Koenen, KC, Sebat, J, and Nievergelt, CM

Abstract

Posttraumatic stress disorder (PTSD) is a heritable (h2 = 24-71%) psychiatric illness. Copy number variation (CNV) is a form of rare genetic variation that has been implicated in the etiology of psychiatric disorders, but no large-scale investigation of CNV in PTSD has been performed. We present an association study of CNV burden and PTSD symptoms in a sample of 114,383 participants (13,036 cases and 101,347 controls) of European ancestry. CNVs were called using two calling algorithms and intersected to a consensus set. Quality control was performed to remove strong outlier samples. CNVs were examined for association with PTSD within each cohort using linear or logistic regression analysis adjusted for population structure and CNV quality metrics, then inverse variance weighted meta-analyzed across cohorts. We examined the genome-wide total span of CNVs, enrichment of CNVs within specified gene-sets, and CNVs overlapping individual genes and implicated neurodevelopmental regions. The total distance covered by deletions crossing over known neurodevelopmental CNV regions was significant (beta = 0.029, SE = 0.005, P = 6.3 × 10-8). The genome-wide neurodevelopmental CNV burden identified explains 0.034% of the variation in PTSD symptoms. The 15q11.2 BP1-BP2 microdeletion region was significantly associated with PTSD (beta = 0.0206, SE = 0.0056, P = 0.0002). No individual significant genes interrupted by CNV were identified. 22 gene pathways related to the function of the nervous system and brain were significant in pathway analysis (FDR q < 0.05), but these associations were not significant once NDD regions were removed. A larger sample size, better detection methods, and annotated resources of CNV are needed to explore this relationship further.

Published
2022

7. Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume.

Author

Zheng, Y, Garrett, ME, Sun, D, Clarke-Rubright, EK, Haswell, CC, Maihofer, AX, Elman, JA, Franz, CE, Lyons, MJ, Kremen, WS, Peverill, M, Sambrook, K, McLaughlin, KA, Davenport, ND, Disner, S, Sponheim, SR, Andrew, E, Korgaonkar, M, Bryant, R, Varkevisser, T, Geuze, E, Coleman, J, Beckham, JC, Kimbrel, NA, Sullivan, D, Miller, M, Hayes, J, Verfaellie, M, Wolf, E, Salat, D, Spielberg, JM, Milberg, W, McGlinchey, R, Dennis, EL, Thompson, PM, Medland, S, Jahanshad, N, Nievergelt, CM, Ashley-Koch, AE, Logue, MW, Morey, RA, Zheng, Y, Garrett, ME, Sun, D, Clarke-Rubright, EK, Haswell, CC, Maihofer, AX, Elman, JA, Franz, CE, Lyons, MJ, Kremen, WS, Peverill, M, Sambrook, K, McLaughlin, KA, Davenport, ND, Disner, S, Sponheim, SR, Andrew, E, Korgaonkar, M, Bryant, R, Varkevisser, T, Geuze, E, Coleman, J, Beckham, JC, Kimbrel, NA, Sullivan, D, Miller, M, Hayes, J, Verfaellie, M, Wolf, E, Salat, D, Spielberg, JM, Milberg, W, McGlinchey, R, Dennis, EL, Thompson, PM, Medland, S, Jahanshad, N, Nievergelt, CM, Ashley-Koch, AE, Logue, MW, and Morey, RA

Abstract

The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10-20), thalamus (p = 7.46 × 10-10), caudate (p = 1.97 × 10-18), putamen (p = 1.7 × 10-12), and nucleus accumbens (p = 1.99 × 10-7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = -0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p < 1 × 10-19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10-7) or PTSD (rs10861272; p = 1.78 × 10-6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.

Published
2021

8. CSNK2B: A broad spectrum of neurodevelopmental disability and epilepsy severity

Author

Ernst, ME, Baugh, EH, Thomas, A, Bier, L, Lippa, N, Stong, N, Mulhern, MS, Kushary, S, Akman, CI, Heinzen, EL, Yeh, R, Bi, W, Hanchard, NA, Burrage, LC, Leduc, MS, Chong, JSC, Bend, R, Lyons, MJ, Lee, JA, Suwannarat, P, Brilstra, E, Simon, M, Koopmans, M, van Binsbergen, E, Groepper, D, Fleischer, J, Nava, C, Keren, B, Mignot, C, Mathieu, S, Mancini, GMS, Madan-Khetarpal, S, Infante, EM, Bluvstein, J, Seeley, A, Bachman, K, Klee, EW, Schultz-Rogers, LE, Hasadsri, L, Barnett, S, Ellingson, MS, Ferber, MJ, Narayanan, V, Ramsey, K, Rauch, A, Joset, P, Steindl, K, Sheehan, T, Poduri, A, Vasquez, A, Ruivenkamp, C, White, SM, Pais, L, Monaghan, KG, Goldstein, DB, Sands, TT, Aggarwal, V, Ernst, ME, Baugh, EH, Thomas, A, Bier, L, Lippa, N, Stong, N, Mulhern, MS, Kushary, S, Akman, CI, Heinzen, EL, Yeh, R, Bi, W, Hanchard, NA, Burrage, LC, Leduc, MS, Chong, JSC, Bend, R, Lyons, MJ, Lee, JA, Suwannarat, P, Brilstra, E, Simon, M, Koopmans, M, van Binsbergen, E, Groepper, D, Fleischer, J, Nava, C, Keren, B, Mignot, C, Mathieu, S, Mancini, GMS, Madan-Khetarpal, S, Infante, EM, Bluvstein, J, Seeley, A, Bachman, K, Klee, EW, Schultz-Rogers, LE, Hasadsri, L, Barnett, S, Ellingson, MS, Ferber, MJ, Narayanan, V, Ramsey, K, Rauch, A, Joset, P, Steindl, K, Sheehan, T, Poduri, A, Vasquez, A, Ruivenkamp, C, White, SM, Pais, L, Monaghan, KG, Goldstein, DB, Sands, TT, and Aggarwal, V

Abstract

CSNK2B has recently been implicated as a disease gene for neurodevelopmental disability (NDD) and epilepsy. Information about developmental outcomes has been limited by the young age and short follow-up for many of the previously reported cases, and further delineation of the spectrum of associated phenotypes is needed. We present 25 new patients with variants in CSNK2B and refine the associated NDD and epilepsy phenotypes. CSNK2B variants were identified by research or clinical exome sequencing, and investigators from different centers were connected via GeneMatcher. Most individuals had developmental delay and generalized epilepsy with onset in the first 2 years. However, we found a broad spectrum of phenotypic severity, ranging from early normal development with pharmacoresponsive seizures to profound intellectual disability with intractable epilepsy and recurrent refractory status epilepticus. These findings suggest that CSNK2B should be considered in the diagnostic evaluation of patients with a broad range of NDD with treatable or intractable seizures.

Published
2021

9. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults

Author

Hofer, E, Roshchupkin, GV, Adams, HHH, Knol, MJ, Lin, H, Li, S, Zare, H, Ahmad, S, Armstrong, NJ, Satizabal, CL, Bernard, M, Bis, JC, Gillespie, NA, Luciano, M, Mishra, A, Scholz, M, Teumer, A, Xia, R, Jian, X, Mosley, TH, Saba, Y, Pirpamer, L, Seiler, S, Becker, JT, Carmichael, O, Rotter, JI, Psaty, BM, Lopez, OL, Amin, N, van der Lee, SJ, Yang, Q, Himali, JJ, Maillard, P, Beiser, AS, Decarli, C, Karama, S, Lewis, L, Harris, M, Bastin, ME, Deary, IJ, Witte, AV, Beyer, F, Loeffler, M, Mather, KA, Schofield, PR, Thalamuthu, A, Kwok, JB, Wright, MJ, Ames, D, Trollor, J, Jiang, J, Brodaty, H, Wen, W, Vernooij, MW, Hofman, A, Uitterlinden, AG, Niessen, WJ, Wittfeld, K, Bülow, R, Völker, U, Pausova, Z, Pike, GB, Maingault, S, Crivello, F, Tzourio, C, Amouyel, P, Mazoyer, B, Neale, MC, Franz, CE, Lyons, MJ, Panizzon, MS, Andreassen, OA, Dale, AM, Logue, M, Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Stein, JL, Thompson, PM, Medland, SE, Sachdev, PS, Kremen, WS, Wardlaw, JM, Villringer, A, van Duijn, CM, Grabe, HJ, Longstreth, WT, Fornage, M, Paus, T, Debette, S, Ikram, MA, Schmidt, H, Schmidt, R, Seshadri, S, Ching, CRK, Hofer, E, Roshchupkin, GV, Adams, HHH, Knol, MJ, Lin, H, Li, S, Zare, H, Ahmad, S, Armstrong, NJ, Satizabal, CL, Bernard, M, Bis, JC, Gillespie, NA, Luciano, M, Mishra, A, Scholz, M, Teumer, A, Xia, R, Jian, X, Mosley, TH, Saba, Y, Pirpamer, L, Seiler, S, Becker, JT, Carmichael, O, Rotter, JI, Psaty, BM, Lopez, OL, Amin, N, van der Lee, SJ, Yang, Q, Himali, JJ, Maillard, P, Beiser, AS, Decarli, C, Karama, S, Lewis, L, Harris, M, Bastin, ME, Deary, IJ, Witte, AV, Beyer, F, Loeffler, M, Mather, KA, Schofield, PR, Thalamuthu, A, Kwok, JB, Wright, MJ, Ames, D, Trollor, J, Jiang, J, Brodaty, H, Wen, W, Vernooij, MW, Hofman, A, Uitterlinden, AG, Niessen, WJ, Wittfeld, K, Bülow, R, Völker, U, Pausova, Z, Pike, GB, Maingault, S, Crivello, F, Tzourio, C, Amouyel, P, Mazoyer, B, Neale, MC, Franz, CE, Lyons, MJ, Panizzon, MS, Andreassen, OA, Dale, AM, Logue, M, Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Stein, JL, Thompson, PM, Medland, SE, Sachdev, PS, Kremen, WS, Wardlaw, JM, Villringer, A, van Duijn, CM, Grabe, HJ, Longstreth, WT, Fornage, M, Paus, T, Debette, S, Ikram, MA, Schmidt, H, Schmidt, R, Seshadri, S, and Ching, CRK

Abstract

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

Published
2020

10. Clinical spectrum of individuals with pathogenic NF1 missense variants affecting p.Met1149, p.Arg1276, and p.Lys1423: genotype-phenotype study in neurofibromatosis type 1

Author

Koczkowska, M, Callens, T, Chen, Y, Gomes, A, Hicks, AD, Sharp, A, Johns, E, Uhas, KA, Armstrong, L, Bosanko, KA, Babovic-Vuksanovic, D, Baker, L, Basel, DG, Bengala, M, Bennett, JT, Chambers, C, Clarkson, LK, Clementi, M, Cortes, FM, Cunningham, M, D'Agostino, MD, Delatycki, MB, Digilio, MC, Dosa, L, Esposito, S, Fox, S, Freckmann, M-L, Fauth, C, Giugliano, T, Giustini, S, Goetsch, A, Goldberg, Y, Greenwood, RS, Griffis, C, Gripp, KW, Gupta, P, Haan, E, Hachen, RK, Haygarth, TL, Hernandez-Chico, C, Hodge, K, Hopkin, RJ, Hudgins, L, Janssens, S, Keller, K, Kelly-Mancuso, G, Kochhar, A, Korf, BR, Lewis, AM, Liebelt, J, Lichty, A, Listernick, RH, Lyons, MJ, Maystadt, I, Ojeda, MM, McDougall, C, McGregor, LK, Melis, D, Mendelsohn, N, Nowaczyk, MJM, Ortenberg, J, Panzer, K, Pappas, JG, Pierpont, ME, Piluso, G, Pinna, V, Pivnick, EK, Pond, DA, Powell, CM, Rogers, C, Shahar, NR, Rutledge, SL, Saletti, V, Sandaradura, SA, Santoro, C, Schatz, UA, Schreiber, A, Scott, DA, Sellars, EA, Sheffer, R, Siqveland, E, Slopis, JM, Smith, R, Spalice, A, Stockton, DW, Streff, H, Theos, A, Tomlinson, GE, Tran, G, Trapane, PL, Trevisson, E, Ullrich, NJ, Van den Ende, J, Vergano, SAS, Wallace, SE, Wangler, MF, Weaver, DD, Yohay, KH, Zackai, E, Zonana, J, Zurcher, V, Claes, KBM, Eoli, M, Martin, Y, Wimmer, K, De Luca, A, Legius, E, Messiaen, LM, Koczkowska, M, Callens, T, Chen, Y, Gomes, A, Hicks, AD, Sharp, A, Johns, E, Uhas, KA, Armstrong, L, Bosanko, KA, Babovic-Vuksanovic, D, Baker, L, Basel, DG, Bengala, M, Bennett, JT, Chambers, C, Clarkson, LK, Clementi, M, Cortes, FM, Cunningham, M, D'Agostino, MD, Delatycki, MB, Digilio, MC, Dosa, L, Esposito, S, Fox, S, Freckmann, M-L, Fauth, C, Giugliano, T, Giustini, S, Goetsch, A, Goldberg, Y, Greenwood, RS, Griffis, C, Gripp, KW, Gupta, P, Haan, E, Hachen, RK, Haygarth, TL, Hernandez-Chico, C, Hodge, K, Hopkin, RJ, Hudgins, L, Janssens, S, Keller, K, Kelly-Mancuso, G, Kochhar, A, Korf, BR, Lewis, AM, Liebelt, J, Lichty, A, Listernick, RH, Lyons, MJ, Maystadt, I, Ojeda, MM, McDougall, C, McGregor, LK, Melis, D, Mendelsohn, N, Nowaczyk, MJM, Ortenberg, J, Panzer, K, Pappas, JG, Pierpont, ME, Piluso, G, Pinna, V, Pivnick, EK, Pond, DA, Powell, CM, Rogers, C, Shahar, NR, Rutledge, SL, Saletti, V, Sandaradura, SA, Santoro, C, Schatz, UA, Schreiber, A, Scott, DA, Sellars, EA, Sheffer, R, Siqveland, E, Slopis, JM, Smith, R, Spalice, A, Stockton, DW, Streff, H, Theos, A, Tomlinson, GE, Tran, G, Trapane, PL, Trevisson, E, Ullrich, NJ, Van den Ende, J, Vergano, SAS, Wallace, SE, Wangler, MF, Weaver, DD, Yohay, KH, Zackai, E, Zonana, J, Zurcher, V, Claes, KBM, Eoli, M, Martin, Y, Wimmer, K, De Luca, A, Legius, E, and Messiaen, LM

Abstract

We report 281 individuals carrying a pathogenic recurrent NF1 missense variant at p.Met1149, p.Arg1276, or p.Lys1423, representing three nontruncating NF1 hotspots in the University of Alabama at Birmingham (UAB) cohort, together identified in 1.8% of unrelated NF1 individuals. About 25% (95% confidence interval: 20.5-31.2%) of individuals heterozygous for a pathogenic NF1 p.Met1149, p.Arg1276, or p.Lys1423 missense variant had a Noonan-like phenotype, which is significantly more compared with the "classic" NF1-affected cohorts (all p < .0001). Furthermore, p.Arg1276 and p.Lys1423 pathogenic missense variants were associated with a high prevalence of cardiovascular abnormalities, including pulmonic stenosis (all p < .0001), while p.Arg1276 variants had a high prevalence of symptomatic spinal neurofibromas (p < .0001) compared with "classic" NF1-affected cohorts. However, p.Met1149-positive individuals had a mild phenotype, characterized mainly by pigmentary manifestations without externally visible plexiform neurofibromas, symptomatic spinal neurofibromas or symptomatic optic pathway gliomas. As up to 0.4% of unrelated individuals in the UAB cohort carries a p.Met1149 missense variant, this finding will contribute to more accurate stratification of a significant number of NF1 individuals. Although clinically relevant genotype-phenotype correlations are rare in NF1, each affecting only a small percentage of individuals, together they impact counseling and management of a significant number of the NF1 population.

Published
2020

11. Genetic and environmental influences on human height from infancy through adulthood at different levels of parental education

Author

Jelenkovic, A, Sund, R, Yokoyama, Y, Latvala, A, Sugawara, M, Tanaka, M, Matsumoto, S, Freitas, DL, Maia, JA, Knafo-Noam, A, Mankuta, D, Abramson, L, Ji, F, Ning, F, Pang, Z, Rebato, E, Saudino, KJ, Cutler, TL, Hopper, JL, Ullemar, V, Almqvist, C, Magnusson, PKE, Cozen, W, Hwang, AE, Mack, TM, Nelson, TL, Whitfield, KE, Sung, J, Kim, J, Lee, J, Lee, S, Llewellyn, CH, Fisher, A, Medda, E, Nistico, L, Toccaceli, V, Baker, LA, Tuvblad, C, Corley, RP, Huibregtse, BM, Derom, CA, Vlietinck, RF, Loos, RJF, Burt, SA, Klump, KL, Silberg, JL, Maes, HH, Krueger, RF, McGue, M, Pahlen, S, Gatz, M, Butler, DA, Harris, JR, Brandt, I, Nilsen, TS, Harden, KP, Tucker-Drob, EM, Franz, CE, Kremen, WS, Lyons, MJ, Lichtenstein, P, Bartels, M, van Beijsterveldt, CEM, Willemsen, G, Oncel, SY, Aliev, F, Jeong, H-U, Hur, Y-M, Turkheimer, E, Boomsma, D, Srensen, TIA, Kaprio, J, Silventoinen, K, Jelenkovic, A, Sund, R, Yokoyama, Y, Latvala, A, Sugawara, M, Tanaka, M, Matsumoto, S, Freitas, DL, Maia, JA, Knafo-Noam, A, Mankuta, D, Abramson, L, Ji, F, Ning, F, Pang, Z, Rebato, E, Saudino, KJ, Cutler, TL, Hopper, JL, Ullemar, V, Almqvist, C, Magnusson, PKE, Cozen, W, Hwang, AE, Mack, TM, Nelson, TL, Whitfield, KE, Sung, J, Kim, J, Lee, J, Lee, S, Llewellyn, CH, Fisher, A, Medda, E, Nistico, L, Toccaceli, V, Baker, LA, Tuvblad, C, Corley, RP, Huibregtse, BM, Derom, CA, Vlietinck, RF, Loos, RJF, Burt, SA, Klump, KL, Silberg, JL, Maes, HH, Krueger, RF, McGue, M, Pahlen, S, Gatz, M, Butler, DA, Harris, JR, Brandt, I, Nilsen, TS, Harden, KP, Tucker-Drob, EM, Franz, CE, Kremen, WS, Lyons, MJ, Lichtenstein, P, Bartels, M, van Beijsterveldt, CEM, Willemsen, G, Oncel, SY, Aliev, F, Jeong, H-U, Hur, Y-M, Turkheimer, E, Boomsma, D, Srensen, TIA, Kaprio, J, and Silventoinen, K

Abstract

Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.

Published
2020

12. Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts

Author

Silventoinen, K, Jelenkovic, A, Sund, R, Latvala, A, Honda, C, Inui, F, Tomizawa, R, Watanabe, M, Sakai, N, Rebato, E, Busjahn, A, Tyler, J, Hopper, JL, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Calais-Ferreira, L, Oliveira, VC, Ferreira, PH, Medda, E, Nistico, L, Toccaceli, V, Derom, CA, Vlietinck, RF, Loos, RJF, Siribaddana, SH, Hotopf, M, Sumathipala, A, Rijsdijk, F, Duncan, GE, Buchwald, D, Tynelius, P, Rasmussen, F, Tan, Q, Zhang, D, Pang, Z, Magnusson, PKE, Pedersen, NL, Aslan, AKD, Hwang, AE, Mack, TM, Krueger, RF, McGue, M, Pahlen, S, Brandt, I, Nilsen, TS, Harris, JR, Martin, NG, Medland, SE, Montgomery, GW, Willemsen, G, Bartels, M, van Beijsterveldt, CEM, Franz, CE, Kremen, WS, Lyons, MJ, Silberg, JL, Maes, HH, Kandler, C, Nelson, TL, Whitfield, KE, Corley, RP, Huibregtse, BM, Gatz, M, Butler, DA, Tarnoki, AD, Tarnoki, DL, Park, HA, Lee, J, Lee, SJ, Sung, J, Yokoyama, Y, Sorensen, TIA, Boomsma, D, Kaprio, J, Silventoinen, K, Jelenkovic, A, Sund, R, Latvala, A, Honda, C, Inui, F, Tomizawa, R, Watanabe, M, Sakai, N, Rebato, E, Busjahn, A, Tyler, J, Hopper, JL, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Calais-Ferreira, L, Oliveira, VC, Ferreira, PH, Medda, E, Nistico, L, Toccaceli, V, Derom, CA, Vlietinck, RF, Loos, RJF, Siribaddana, SH, Hotopf, M, Sumathipala, A, Rijsdijk, F, Duncan, GE, Buchwald, D, Tynelius, P, Rasmussen, F, Tan, Q, Zhang, D, Pang, Z, Magnusson, PKE, Pedersen, NL, Aslan, AKD, Hwang, AE, Mack, TM, Krueger, RF, McGue, M, Pahlen, S, Brandt, I, Nilsen, TS, Harris, JR, Martin, NG, Medland, SE, Montgomery, GW, Willemsen, G, Bartels, M, van Beijsterveldt, CEM, Franz, CE, Kremen, WS, Lyons, MJ, Silberg, JL, Maes, HH, Kandler, C, Nelson, TL, Whitfield, KE, Corley, RP, Huibregtse, BM, Gatz, M, Butler, DA, Tarnoki, AD, Tarnoki, DL, Park, HA, Lee, J, Lee, SJ, Sung, J, Yokoyama, Y, Sorensen, TIA, Boomsma, D, and Kaprio, J

Abstract

We investigated the heritability of educational attainment and how it differed between birth cohorts and cultural-geographic regions. A classical twin design was applied to pooled data from 28 cohorts representing 16 countries and including 193,518 twins with information on educational attainment at 25 years of age or older. Genetic factors explained the major part of individual differences in educational attainment (heritability: a2 = 0.43; 0.41-0.44), but also environmental variation shared by co-twins was substantial (c2 = 0.31; 0.30-0.33). The proportions of educational variation explained by genetic and shared environmental factors did not differ between Europe, North America and Australia, and East Asia. When restricted to twins 30 years or older to confirm finalized education, the heritability was higher in the older cohorts born in 1900-1949 (a2 = 0.44; 0.41-0.46) than in the later cohorts born in 1950-1989 (a2 = 0.38; 0.36-0.40), with a corresponding lower influence of common environmental factors (c2 = 0.31; 0.29-0.33 and c2 = 0.34; 0.32-0.36, respectively). In conclusion, both genetic and environmental factors shared by co-twins have an important influence on individual differences in educational attainment. The effect of genetic factors on educational attainment has decreased from the cohorts born before to those born after the 1950s.

Published
2020

13. The CODATwins Project: The Current Status and Recent Findings of COllaborative Project of Development of Anthropometrical Measures in Twins

Author

Silventoinen, K, Jelenkovic, A, Yokoyama, Y, Sund, R, Sugawara, M, Tanaka, M, Matsumoto, S, Bogl, LH, Freitas, DL, Maia, JA, Hjelmborg, JVB, Aaltonen, S, Piirtola, M, Latvala, A, Calais-Ferreira, L, Oliveira, VC, Ferreira, PH, Ji, F, Ning, F, Pang, Z, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Burt, SA, Klump, KL, Martin, NG, Medland, SE, Montgomery, GW, Kandler, C, McAdams, TA, Eley, TC, Gregory, AM, Saudino, KJ, Dubois, L, Boivin, M, Brendgen, M, Dionne, G, Vitaro, F, Tarnoki, AD, Tarnoki, DL, Haworth, CMA, Plomin, R, Oncel, SY, Aliev, F, Medda, E, Nistico, L, Toccaceli, V, Craig, JM, Saffery, R, Siribaddana, SH, Hotopf, M, Sumathipala, A, Rijsdijk, F, Jeong, H-U, Spector, T, Mangino, M, Lachance, G, Gatz, M, Butler, DA, Gao, W, Yu, C, Li, L, Bayasgalan, G, Narandalai, D, Harden, KP, Tucker-Drob, EM, Christensen, K, Skytthe, A, Kyvik, KO, Derom, CA, Vlietinck, RF, Loos, RJF, Cozen, W, Hwang, AE, Mack, TM, He, M, Ding, X, Silberg, JL, Maes, HH, Cutler, TL, Hopper, JL, Magnusson, PKE, Pedersen, NL, Dahl Aslan, AK, Baker, LA, Tuvblad, C, Bjerregaard-Andersen, M, Beck-Nielsen, H, Sodemann, M, Ullemar, V, Almqvist, C, Tan, Q, Zhang, D, Swan, GE, Krasnow, R, Jang, KL, Knafo-Noam, A, Mankuta, D, Abramson, L, Lichtenstein, P, Krueger, RF, McGue, M, Pahlen, S, Tynelius, P, Rasmussen, F, Duncan, GE, Buchwald, D, Corley, RP, Huibregtse, BM, Nelson, TL, Whitfield, KE, Franz, CE, Kremen, WS, Lyons, MJ, Ooki, S, Brandt, I, Nilsen, TS, Harris, JR, Sung, J, Park, HA, Lee, J, Lee, SJ, Willemsen, G, Bartels, M, Van Beijsterveldt, CEM, Llewellyn, CH, Fisher, A, Rebato, E, Busjahn, A, Tomizawa, R, Inui, F, Watanabe, M, Honda, C, Sakai, N, Hur, Y-M, Sorensen, TIA, Boomsma, DI, Kaprio, J, Silventoinen, K, Jelenkovic, A, Yokoyama, Y, Sund, R, Sugawara, M, Tanaka, M, Matsumoto, S, Bogl, LH, Freitas, DL, Maia, JA, Hjelmborg, JVB, Aaltonen, S, Piirtola, M, Latvala, A, Calais-Ferreira, L, Oliveira, VC, Ferreira, PH, Ji, F, Ning, F, Pang, Z, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Burt, SA, Klump, KL, Martin, NG, Medland, SE, Montgomery, GW, Kandler, C, McAdams, TA, Eley, TC, Gregory, AM, Saudino, KJ, Dubois, L, Boivin, M, Brendgen, M, Dionne, G, Vitaro, F, Tarnoki, AD, Tarnoki, DL, Haworth, CMA, Plomin, R, Oncel, SY, Aliev, F, Medda, E, Nistico, L, Toccaceli, V, Craig, JM, Saffery, R, Siribaddana, SH, Hotopf, M, Sumathipala, A, Rijsdijk, F, Jeong, H-U, Spector, T, Mangino, M, Lachance, G, Gatz, M, Butler, DA, Gao, W, Yu, C, Li, L, Bayasgalan, G, Narandalai, D, Harden, KP, Tucker-Drob, EM, Christensen, K, Skytthe, A, Kyvik, KO, Derom, CA, Vlietinck, RF, Loos, RJF, Cozen, W, Hwang, AE, Mack, TM, He, M, Ding, X, Silberg, JL, Maes, HH, Cutler, TL, Hopper, JL, Magnusson, PKE, Pedersen, NL, Dahl Aslan, AK, Baker, LA, Tuvblad, C, Bjerregaard-Andersen, M, Beck-Nielsen, H, Sodemann, M, Ullemar, V, Almqvist, C, Tan, Q, Zhang, D, Swan, GE, Krasnow, R, Jang, KL, Knafo-Noam, A, Mankuta, D, Abramson, L, Lichtenstein, P, Krueger, RF, McGue, M, Pahlen, S, Tynelius, P, Rasmussen, F, Duncan, GE, Buchwald, D, Corley, RP, Huibregtse, BM, Nelson, TL, Whitfield, KE, Franz, CE, Kremen, WS, Lyons, MJ, Ooki, S, Brandt, I, Nilsen, TS, Harris, JR, Sung, J, Park, HA, Lee, J, Lee, SJ, Willemsen, G, Bartels, M, Van Beijsterveldt, CEM, Llewellyn, CH, Fisher, A, Rebato, E, Busjahn, A, Tomizawa, R, Inui, F, Watanabe, M, Honda, C, Sakai, N, Hur, Y-M, Sorensen, TIA, Boomsma, DI, and Kaprio, J

Abstract

The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural-geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.

Published
2019

14. International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci

Author

Nievergelt, CM, Maihofer, AX, Klengel, T, Atkinson, EG, Chen, C-Y, Choi, KW, Coleman, JR, Dalvie, S, Duncan, LE, Gelernter, J, Levey, DF, Logue, MW, Polimanti, R, Provost, AC, Ratanatharathorn, A, Stein, MB, Torres, K, Aiello, AE, Almli, LM, Amstadter, AB, Andersen, SB, Andreassen, OA, Arbisi, PA, Ashley-Koch, AE, Austin, SB, Avdibegovic, E, Babic, D, Baekvad-Hansen, M, Baker, DG, Beckham, JC, Bierut, LJ, Bisson, J, Boks, MP, Bolger, EA, Brglum, AD, Bradley, B, Brashear, M, Breen, G, Bryant, RA, Bustamante, AC, Bybjerg-Grauholm, J, Calabrese, JR, Caldas-de-Almeida, JM, Dale, AM, Daly, MJ, Daskalakis, NP, Deckert, J, Delahanty, DL, Dennis, MF, Disner, SG, Domschke, K, Dzubur-Kulenovic, A, Erbes, CR, Evans, A, Farrer, LA, Feeny, NC, Flory, JD, Forbes, D, Franz, CE, Galea, S, Garrett, ME, Gelaye, B, Geuze, E, Gillespie, C, Uka, AG, Gordon, SD, Guffanti, G, Hammamieh, R, Harnal, S, Hauser, MA, Heath, AC, Hemmings, SMJ, Hougaard, DM, Jakovljevic, M, Jett, M, Johnson, EO, Jones, I, Jovanovic, T, Qin, X-J, Junglen, AG, Karstoft, K-I, Kaufman, ML, Kessler, RC, Khan, A, Kimbrel, NA, King, AP, Koen, N, Kranzler, HR, Kremen, WS, Lawford, BR, Lebois, LAM, Lewis, CE, Linnstaedt, SD, Lori, A, Lugonja, B, Luykx, JJ, Lyons, MJ, Maples-Keller, J, Marmar, C, Martin, AR, Martin, NG, Maurer, D, Mavissakalian, MR, McFarlane, A, McGlinchey, RE, McLaughlin, KA, McLean, SA, McLeay, S, Mehta, D, Milberg, WP, Miller, MW, Morey, RA, Morris, CP, Mors, O, Mortensen, PB, Neale, BM, Nelson, EC, Nordentoft, M, Norman, SB, O'Donnell, M, Orcutt, HK, Panizzon, MS, Peters, ES, Peterson, AL, Peverill, M, Pietrzak, RH, Polusny, MA, Rice, JP, Ripke, S, Risbrough, VB, Roberts, AL, Rothbaum, AO, Rothbaum, BO, Roy-Byrne, P, Ruggiero, K, Rung, A, Rutten, BPF, Saccone, NL, Sanchez, SE, Schijven, D, Seedat, S, Seligowski, A, Seng, JS, Sheerin, CM, Silove, D, Smith, AK, Smoller, JW, Sponheim, SR, Stein, DJ, Stevens, JS, Sumner, JA, Teicher, MH, Thompson, WK, Trapido, E, Uddin, M, Ursano, RJ, van den Heuvel, LL, Van Hooff, M, Vermetten, E, Vinkers, CH, Voisey, J, Wang, Y, Wang, Z, Werge, T, Williams, MA, Williamson, DE, Winternitz, S, Wolf, C, Wolf, EJ, Wolff, JD, Yehuda, R, Young, RM, Young, KA, Zhao, H, Zoellner, LA, Liberzon, I, Ressler, KJ, Haas, M, Koenen, KC, Nievergelt, CM, Maihofer, AX, Klengel, T, Atkinson, EG, Chen, C-Y, Choi, KW, Coleman, JR, Dalvie, S, Duncan, LE, Gelernter, J, Levey, DF, Logue, MW, Polimanti, R, Provost, AC, Ratanatharathorn, A, Stein, MB, Torres, K, Aiello, AE, Almli, LM, Amstadter, AB, Andersen, SB, Andreassen, OA, Arbisi, PA, Ashley-Koch, AE, Austin, SB, Avdibegovic, E, Babic, D, Baekvad-Hansen, M, Baker, DG, Beckham, JC, Bierut, LJ, Bisson, J, Boks, MP, Bolger, EA, Brglum, AD, Bradley, B, Brashear, M, Breen, G, Bryant, RA, Bustamante, AC, Bybjerg-Grauholm, J, Calabrese, JR, Caldas-de-Almeida, JM, Dale, AM, Daly, MJ, Daskalakis, NP, Deckert, J, Delahanty, DL, Dennis, MF, Disner, SG, Domschke, K, Dzubur-Kulenovic, A, Erbes, CR, Evans, A, Farrer, LA, Feeny, NC, Flory, JD, Forbes, D, Franz, CE, Galea, S, Garrett, ME, Gelaye, B, Geuze, E, Gillespie, C, Uka, AG, Gordon, SD, Guffanti, G, Hammamieh, R, Harnal, S, Hauser, MA, Heath, AC, Hemmings, SMJ, Hougaard, DM, Jakovljevic, M, Jett, M, Johnson, EO, Jones, I, Jovanovic, T, Qin, X-J, Junglen, AG, Karstoft, K-I, Kaufman, ML, Kessler, RC, Khan, A, Kimbrel, NA, King, AP, Koen, N, Kranzler, HR, Kremen, WS, Lawford, BR, Lebois, LAM, Lewis, CE, Linnstaedt, SD, Lori, A, Lugonja, B, Luykx, JJ, Lyons, MJ, Maples-Keller, J, Marmar, C, Martin, AR, Martin, NG, Maurer, D, Mavissakalian, MR, McFarlane, A, McGlinchey, RE, McLaughlin, KA, McLean, SA, McLeay, S, Mehta, D, Milberg, WP, Miller, MW, Morey, RA, Morris, CP, Mors, O, Mortensen, PB, Neale, BM, Nelson, EC, Nordentoft, M, Norman, SB, O'Donnell, M, Orcutt, HK, Panizzon, MS, Peters, ES, Peterson, AL, Peverill, M, Pietrzak, RH, Polusny, MA, Rice, JP, Ripke, S, Risbrough, VB, Roberts, AL, Rothbaum, AO, Rothbaum, BO, Roy-Byrne, P, Ruggiero, K, Rung, A, Rutten, BPF, Saccone, NL, Sanchez, SE, Schijven, D, Seedat, S, Seligowski, A, Seng, JS, Sheerin, CM, Silove, D, Smith, AK, Smoller, JW, Sponheim, SR, Stein, DJ, Stevens, JS, Sumner, JA, Teicher, MH, Thompson, WK, Trapido, E, Uddin, M, Ursano, RJ, van den Heuvel, LL, Van Hooff, M, Vermetten, E, Vinkers, CH, Voisey, J, Wang, Y, Wang, Z, Werge, T, Williams, MA, Williamson, DE, Winternitz, S, Wolf, C, Wolf, EJ, Wolff, JD, Yehuda, R, Young, RM, Young, KA, Zhao, H, Zoellner, LA, Liberzon, I, Ressler, KJ, Haas, M, and Koenen, KC

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.

Published
2019

15. Parental Education and Genetics of BMI from Infancy to Old Age: A Pooled Analysis of 29 Twin Cohorts

Author

Silventoinen, K, Jelenkovic, A, Latvala, A, Yokoyama, Y, Sund, R, Sugawara, M, Tanaka, M, Matsumoto, S, Aaltonen, S, Piirtola, M, Freitas, DL, Maia, JA, Oncel, SY, Aliev, F, Ji, F, Ning, F, Pang, Z, Rebato, E, Saudino, KJ, Cutler, TL, Hopper, JL, Ullemar, V, Almqvist, C, Magnusson, PKE, Cozen, W, Hwang, AE, Mack, TM, Willemsen, G, Bartels, M, van Beijsterveldt, CEM, Nelson, TL, Whitfield, KE, Sung, J, Kim, J, Lee, J, Lee, S, Llewellyn, CH, Fisher, A, Medda, E, Nistico, L, Toccaceli, V, Baker, LA, Tuvblad, C, Corley, RP, Huibregtse, BM, Derom, CA, Vlietinck, RF, Loos, RJF, Knafo-Noam, A, Mankuta, D, Abramson, L, Burt, SA, Klump, KL, Silberg, JL, Maes, HH, Krueger, RF, McGue, M, Pahlen, S, Gatz, M, Butler, DA, Harris, JR, Nilsen, TS, Harden, KP, Tucker-Drob, EM, Franz, CE, Kremen, WS, Lyons, MJ, Lichtenstein, P, Jeong, H-U, Hur, Y-M, Boomsma, DI, Sorensen, TIA, Kaprio, J, Silventoinen, K, Jelenkovic, A, Latvala, A, Yokoyama, Y, Sund, R, Sugawara, M, Tanaka, M, Matsumoto, S, Aaltonen, S, Piirtola, M, Freitas, DL, Maia, JA, Oncel, SY, Aliev, F, Ji, F, Ning, F, Pang, Z, Rebato, E, Saudino, KJ, Cutler, TL, Hopper, JL, Ullemar, V, Almqvist, C, Magnusson, PKE, Cozen, W, Hwang, AE, Mack, TM, Willemsen, G, Bartels, M, van Beijsterveldt, CEM, Nelson, TL, Whitfield, KE, Sung, J, Kim, J, Lee, J, Lee, S, Llewellyn, CH, Fisher, A, Medda, E, Nistico, L, Toccaceli, V, Baker, LA, Tuvblad, C, Corley, RP, Huibregtse, BM, Derom, CA, Vlietinck, RF, Loos, RJF, Knafo-Noam, A, Mankuta, D, Abramson, L, Burt, SA, Klump, KL, Silberg, JL, Maes, HH, Krueger, RF, McGue, M, Pahlen, S, Gatz, M, Butler, DA, Harris, JR, Nilsen, TS, Harden, KP, Tucker-Drob, EM, Franz, CE, Kremen, WS, Lyons, MJ, Lichtenstein, P, Jeong, H-U, Hur, Y-M, Boomsma, DI, Sorensen, TIA, and Kaprio, J

Abstract

OBJECTIVE: The objective of this study was to analyze how parental education modifies the genetic and environmental variances of BMI from infancy to old age in three geographic-cultural regions. METHODS: A pooled sample of 29 cohorts including 143,499 twin individuals with information on parental education and BMI from age 1 to 79 years (299,201 BMI measures) was analyzed by genetic twin modeling. RESULTS: Until 4 years of age, parental education was not consistently associated with BMI. Thereafter, higher parental education level was associated with lower BMI in males and females. Total and additive genetic variances of BMI were smaller in the offspring of highly educated parents than in those whose parents had low education levels. Especially in North American and Australian children, environmental factors shared by co-twins also contributed to the higher BMI variation in the low education level category. In Europe and East Asia, the associations of parental education with mean BMI and BMI variance were weaker than in North America and Australia. CONCLUSIONS: Lower parental education level is associated with higher mean BMI and larger genetic variance of BMI after early childhood, especially in the obesogenic macro-environment. The interplay among genetic predisposition, childhood social environment, and macro-social context is important for socioeconomic differences in BMI.

Published
2019

17. Association of current and former smoking with body mass index: A study of smoking discordant twin pairs from 21 twin cohorts

Author

Remuzzi, G, Piirtola, M, Jelenkovic, A, Latvala, A, Sund, R, Honda, C, Inui, F, Watanabe, M, Tomizawa, R, Iwatani, Y, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Tarnoki, AD, Tarnoki, DL, Martin, NG, Montgomery, GW, Medland, SE, Rasmussen, F, Tynelius, P, Tan, Q, Zhang, D, Pang, Z, Rebato, E, Stazi, MA, Fagnani, C, Brescianini, S, Busjahn, A, Harris, JR, Brandt, I, Nilsen, TS, Cutler, TL, Hopper, JL, Corley, RP, Huibregtse, BM, Sung, J, Kim, J, Lee, J, Lee, S, Gatz, M, Butler, DA, Franz, CE, Kremen, WS, Lyons, MJ, Magnusson, PKE, Pedersen, NL, Aslan, AKD, Oncel, SY, Aliev, F, Derom, CA, Vlietinck, RF, Loos, RJF, Silberg, JL, Maes, HH, Boomsma, D, Sorensen, TIA, Korhonen, T, Kaprio, J, Silventoinen, K, Remuzzi, G, Piirtola, M, Jelenkovic, A, Latvala, A, Sund, R, Honda, C, Inui, F, Watanabe, M, Tomizawa, R, Iwatani, Y, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Tarnoki, AD, Tarnoki, DL, Martin, NG, Montgomery, GW, Medland, SE, Rasmussen, F, Tynelius, P, Tan, Q, Zhang, D, Pang, Z, Rebato, E, Stazi, MA, Fagnani, C, Brescianini, S, Busjahn, A, Harris, JR, Brandt, I, Nilsen, TS, Cutler, TL, Hopper, JL, Corley, RP, Huibregtse, BM, Sung, J, Kim, J, Lee, J, Lee, S, Gatz, M, Butler, DA, Franz, CE, Kremen, WS, Lyons, MJ, Magnusson, PKE, Pedersen, NL, Aslan, AKD, Oncel, SY, Aliev, F, Derom, CA, Vlietinck, RF, Loos, RJF, Silberg, JL, Maes, HH, Boomsma, D, Sorensen, TIA, Korhonen, T, Kaprio, J, and Silventoinen, K

Abstract

BACKGROUND: Smokers tend to weigh less than never smokers, while successful quitting leads to an increase in body weight. Because smokers and non-smokers may differ in genetic and environmental family background, we analysed data from twin pairs in which the co-twins differed by their smoking behaviour to evaluate if the association between smoking and body mass index (BMI) remains after controlling for family background. METHODS AND FINDINGS: The international CODATwins database includes information on smoking and BMI measured between 1960 and 2012 from 156,593 twin individuals 18-69 years of age. Individual-based data (230,378 measurements) and data of smoking discordant twin pairs (altogether 30,014 pairwise measurements, 36% from monozygotic [MZ] pairs) were analysed with linear fixed-effects regression models by 10-year periods. In MZ pairs, the smoking co-twin had, on average, 0.57 kg/m2 lower BMI in men (95% confidence interval (CI): 0.49, 0.70) and 0.65 kg/m2 lower BMI in women (95% CI: 0.52, 0.79) than the never smoking co-twin. Former smokers had 0.70 kg/m2 higher BMI among men (95% CI: 0.63, 0.78) and 0.62 kg/m2 higher BMI among women (95% CI: 0.51, 0.73) than their currently smoking MZ co-twins. Little difference in BMI was observed when comparing former smoking co-twins with their never smoking MZ co-twins (0.13 kg/m2, 95% CI 0.04, 0.23 among men; -0.04 kg/m2, 95% CI -0.16, 0.09 among women). The associations were similar within dizygotic pairs and when analysing twins as individuals. The observed series of cross-sectional associations were independent of sex, age, and measurement decade. CONCLUSIONS: Smoking is associated with lower BMI and smoking cessation with higher BMI. However, the net effect of smoking and subsequent cessation on weight development appears to be minimal, i.e. never more than an average of 0.7 kg/m2.

Published
2018

20. Genetic and environmental influences on adult human height across birth cohorts from 1886 to 1994

Author

Jelenkovic, A, Hur, Y-M, Sund, R, Yokoyama, Y, Siribaddana, SH, Hotopf, M, Sumathipala, A, Rijsdijk, F, Tan, Q, Zhang, D, Pang, Z, Aaltonen, S, Heikkila, K, Oncel, SY, Aliev, F, Rebato, E, Tarnoki, AD, Tarnoki, DL, Christensen, K, Skytthe, A, Kyvik, KO, Silberg, JL, Eaves, LJ, Maes, HH, Cutler, TL, Hopper, JL, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Cozen, W, Hwang, AE, Mack, TM, Sun, J, Song, Y-M, Yang, S, Lee, K, Franz, CE, Kremen, WS, Lyons, MJ, Busjahn, A, Nelson, TL, Whitfield, KE, Kandler, C, Jang, KL, Gatz, M, Butler, DA, Stazi, MA, Fagnani, C, D'Ippolito, C, Duncan, GE, Buchwald, D, Derom, CA, Vlietinck, RF, Loos, RJF, Martin, NG, Medland, SE, Montgomery, GW, Jeong, H-U, Swan, GE, Krasnow, R, Magnusson, PKE, Pedersen, NL, Dahl-Aslan, AK, McAdams, TA, Eley, TC, Gregory, AM, Tynelius, P, Baker, LA, Tuvblad, C, Bayasgalan, G, Narandalai, D, Lichtenstein, P, Spector, TD, Mangino, M, Lachance, G, Bartels, M, van Beijsterveldt, TCEM, Willemsen, G, Burt, SA, Klump, KL, Harris, JR, Brandt, I, Nilsen, TS, Krueger, RF, McGue, M, Pahlen, S, Corley, RP, Hjelmborg, JVB, Goldberg, JH, Iwatani, Y, Watanabe, M, Honda, C, Inui, F, Rasmussen, F, Huibregtse, BM, Boomsma, DI, Sorensen, TIA, Kaprio, J, Silventoinen, K, Jelenkovic, A, Hur, Y-M, Sund, R, Yokoyama, Y, Siribaddana, SH, Hotopf, M, Sumathipala, A, Rijsdijk, F, Tan, Q, Zhang, D, Pang, Z, Aaltonen, S, Heikkila, K, Oncel, SY, Aliev, F, Rebato, E, Tarnoki, AD, Tarnoki, DL, Christensen, K, Skytthe, A, Kyvik, KO, Silberg, JL, Eaves, LJ, Maes, HH, Cutler, TL, Hopper, JL, Ordonana, JR, Sanchez-Romera, JF, Colodro-Conde, L, Cozen, W, Hwang, AE, Mack, TM, Sun, J, Song, Y-M, Yang, S, Lee, K, Franz, CE, Kremen, WS, Lyons, MJ, Busjahn, A, Nelson, TL, Whitfield, KE, Kandler, C, Jang, KL, Gatz, M, Butler, DA, Stazi, MA, Fagnani, C, D'Ippolito, C, Duncan, GE, Buchwald, D, Derom, CA, Vlietinck, RF, Loos, RJF, Martin, NG, Medland, SE, Montgomery, GW, Jeong, H-U, Swan, GE, Krasnow, R, Magnusson, PKE, Pedersen, NL, Dahl-Aslan, AK, McAdams, TA, Eley, TC, Gregory, AM, Tynelius, P, Baker, LA, Tuvblad, C, Bayasgalan, G, Narandalai, D, Lichtenstein, P, Spector, TD, Mangino, M, Lachance, G, Bartels, M, van Beijsterveldt, TCEM, Willemsen, G, Burt, SA, Klump, KL, Harris, JR, Brandt, I, Nilsen, TS, Krueger, RF, McGue, M, Pahlen, S, Corley, RP, Hjelmborg, JVB, Goldberg, JH, Iwatani, Y, Watanabe, M, Honda, C, Inui, F, Rasmussen, F, Huibregtse, BM, Boomsma, DI, Sorensen, TIA, Kaprio, J, and Silventoinen, K

Abstract

Human height variation is determined by genetic and environmental factors, but it remains unclear whether their influences differ across birth-year cohorts. We conducted an individual-based pooled analysis of 40 twin cohorts including 143,390 complete twin pairs born 1886-1994. Although genetic variance showed a generally increasing trend across the birth-year cohorts, heritability estimates (0.69-0.84 in men and 0.53-0.78 in women) did not present any clear pattern of secular changes. Comparing geographic-cultural regions (Europe, North America and Australia, and East Asia), total height variance was greatest in North America and Australia and lowest in East Asia, but no clear pattern in the heritability estimates across the birth-year cohorts emerged. Our findings do not support the hypothesis that heritability of height is lower in populations with low living standards than in affluent populations, nor that heritability of height will increase within a population as living standards improve.

Published
2016

34. Measuring and comparing civil societies

Author

Lyons, MJ and Lyons, MJ

Abstract

In most countries (Australia is an exception) the term `civil society is widely used by social researchers, activists and government officials. However its analytical value is limited by its great variety of meanings. The article proposes that if `civil society is to be of any use analytically it should be capable of being measured. It outlines two related efforts to measure civil society and to compare it cross nationally and identifies several problems with those approaches.

Published
2009

38. Capital Access of Nonprofit Organisations

Author

Lyons, MJ, North-Samardzic, A, Young, AL, Lyons, MJ, North-Samardzic, A, and Young, AL

Abstract

The recent sales by the Salvation Armys Southern Territory and the St Vincent de Paul Society in NSW of their nursing homes point to a wider problem faced by many parts of Australias nonprofit sector. Faced with the need for considerable new capital investment to ensure their accommodation met new aged care standards to be introduced in 2008, and recognising the challenges that such capital raising would entail, these two leading nonprofit organisations chose to pass the problem to others that could handle it in the case of the Salvation Army a consortium containing Macquarie Bank and a large for-profit aged care provider (Macquarie Bank, 2005; Horin, 2006). Many other nonprofit organisations that over the past fifty years have built facilities such as hospitals, aged accommodation, child care and schools face similar needs to refurbish or reposition these assets and similar challenges in accessing the capital needed for the task. Capital is either difficult to raise or is inaccessible. Of greater importance perhaps, many successful nonprofits are constrained from expansion by difficulties in raising capital and many potentially important social innovations are strangled by their inability to raise start-up capital.

Published
2007

45. Educational attainment, smoking initiation and lifetime nicotine dependence among male Vietnam-era twins.

Author

McCaffery JM, Papandonatos GD, Lyons MJ, Koenen KC, Tsuang MT, and Niaura R

Abstract

BACKGROUND: Smoking initiation and persistence are clearly associated with factors commonly thought to be environmental in origin, including socio-economic status. However, twin models that incorporate gene-environment correlation and gene x environment interaction have not been applied to elucidate the genetic or environmental role that socio-economic status plays in smoking initiation and nicotine dependence. METHOD: Twin structural equation modelling was used to examine gene-environment correlation and gene x environment interaction of one index of socio-economic status, educational attainment, with smoking initiation and nicotine dependence among 5119 monozygotic and 4295 dizygotic male-male Vietnam-era twins from the Vietnam Era Twin Registry, a national registry of twin pairs who served in the military during the Vietnam era. RESULTS: Educational attainment correlated significantly with smoking initiation (r=-0.27, p<0.001). Additive genetic (p=0.011), shared environment (p=0.002) and unique environment (p=0.027) components contributed to the correlation between educational attainment and smoking initiation. Educational attainment also significantly moderated the variance in smoking initiation (p<0.001), suggestive of gene x environment interaction, although the interaction with the additive genetic, shared environmental and unique environmental components could not be resolved due to multi-collinearity. In contrast, educational attainment neither correlated with nor moderated nicotine dependence, once smokers had initiated. CONCLUSIONS: Our study suggests that educational attainment is associated with smoking initiation, in part due to gene-environment correlation and gene x environment interaction. However, once smoking initiation is taken into account, there are no effects--be they gene-environment correlation or gene x environmental interaction--of educational attainment on nicotine dependence. [ABSTRACT FROM AUTHOR]

Published
2008
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50. Vietnam service, combat, and lifetime educational attainment: preliminary results from the Vietnam Era Twin Study of Aging.

Author

Lyons MJ, Kremen WS, Franz C, Grant MD, Brenner HT, Boake C, and Eisen S

Abstract

Combat experiences early in adulthood may have lifelong ramifications. In the Vietnam Era Twin Study of Aging (VETSA), the authors studied lifetime educational attainment (LEA) in 236 male twins from the Vietnam Era Twin Registry. Twins who served in Vietnam had completed significantly fewer years of education by their 50s. Level of combat exposure was negatively correlated with LEA. To control for variables that might confound the relationship between combat and LEA, the authors compared twin pairs discordant for Vietnam service (n = 44 pairs); the twins who served in Vietnam had significantly lower LEA than their cotwins. Greater cognitive ability at military induction and older age at induction both predicted higher LEA, but after statistically controlling for these variables, the relationship between combat exposure and LEA remained significant. The VETSA results demonstrate that combat experience and entering military service at a younger age may reduce lifelong educational prospects, even after cognitive ability is controlled. [ABSTRACT FROM AUTHOR]

Published
2006
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