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Knowles EEM, Kent JW, McKay DR, Sprooten E, Mathias SR, Curran JE, Carless MA, de Almeida MAA, Harald HHG, Dyer TD, Olvera RL, Fox PT, Duggirala R, Almasy L, Blangero J, Glahn DC. Genome-wide linkage on chromosome 10q26 for a dimensional scale of major depression. J Affect Disord 2016; 191:123-31. [PMID: 26655122 PMCID: PMC4715913 DOI: 10.1016/j.jad.2015.11.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Revised: 10/27/2015] [Accepted: 11/09/2015] [Indexed: 12/28/2022]
Abstract
Major depressive disorder (MDD) is a common and potentially life-threatening mood disorder. Identifying genetic markers for depression might provide reliable indicators of depression risk, which would, in turn, substantially improve detection, enabling earlier and more effective treatment. The aim of this study was to identify rare variants for depression, modeled as a continuous trait, using linkage and post-hoc association analysis. The sample comprised 1221 Mexican-American individuals from extended pedigrees. A single dimensional scale of MDD was derived using confirmatory factor analysis applied to all items from the Past Major Depressive Episode section of the Mini-International Neuropsychiatric Interview. Scores on this scale of depression were subjected to linkage analysis followed by QTL region-specific association analysis. Linkage analysis revealed a single genome-wide significant QTL (LOD=3.43) on 10q26.13, QTL-specific association analysis conducted in the entire sample revealed a suggestive variant within an intron of the gene LHPP (rs11245316, p=7.8×10(-04); LD-adjusted Bonferroni-corrected p=8.6×10(-05)). This region of the genome has previously been implicated in the etiology of MDD; the present study extends our understanding of the involvement of this region by highlighting a putative gene of interest (LHPP).
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Olvera RL, Fisher-Hoch SP, Williamson DE, Vatcheva KP, McCormick JB. Depression in Mexican Americans with diagnosed and undiagnosed diabetes. Psychol Med 2016; 46:637-646. [PMID: 26511778 PMCID: PMC5836321 DOI: 10.1017/s0033291715002160] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Depression and diabetes commonly co-occur; however, the strength of the physiological effects of diabetes as mediating factors towards depression is uncertain. METHOD We analyzed extensive clinical, epidemiological and laboratory data from n = 2081 Mexican Americans aged 35-64 years, recruited from the community as part of the Cameron County Hispanic Cohort (CCHC) divided into three groups: Diagnosed (self-reported) diabetes (DD, n = 335), Undiagnosed diabetes (UD, n = 227) and No diabetes (ND, n = 1519). UD participants denied being diagnosed with diabetes, but on testing met the 2010 American Diabetes Association and World Health Organization definitions of diabetes. Depression was measured using the Center for Epidemiological Studies - Depression (CES-D) scale. Weighted data were analyzed using dimensional and categorical outcomes using univariate and multivariate models. RESULTS The DD group had significantly higher CES-D scores than both the ND and UD (p ⩽ 0.001) groups, whereas the ND and UD groups did not significantly differ from each other. The DD subjects were more likely to meet the CES-D cut-off score for depression compared to both the ND and UD groups (p = 0.001), respectively. The UD group was also less likely to meet the cut-off score for depression than the ND group (p = 0.003). Our main findings remained significant in models that controlled for socio-demographic and clinical confounders. CONCLUSIONS Meeting clinical criteria for diabetes was not sufficient for increased depressive symptoms. Our findings suggest that the 'knowing that one is ill' is associated with depressive symptoms in diabetic subjects.
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Sprooten E, Gupta CN, Knowles EEM, McKay DR, Mathias SR, Curran JE, Kent JW, Carless MA, Almeida MA, Dyer TD, Göring HHH, Olvera RL, Kochunov P, Fox PT, Duggirala R, Almasy L, Calhoun VD, Blangero J, Turner JA, Glahn DC. Genome-wide significant linkage of schizophrenia-related neuroanatomical trait to 12q24. Am J Med Genet B Neuropsychiatr Genet 2015; 168:678-86. [PMID: 26440917 PMCID: PMC4639444 DOI: 10.1002/ajmg.b.32360] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2014] [Accepted: 07/31/2015] [Indexed: 11/08/2022]
Abstract
The insula and medial prefrontal cortex (mPFC) share functional, histological, transcriptional, and developmental characteristics, and they serve higher cognitive functions of theoretical relevance to schizophrenia and related disorders. Meta-analyses and multivariate analysis of structural magnetic resonance imaging (MRI) scans indicate that gray matter density and volume reductions in schizophrenia are the most consistent and pronounced in a network primarily composed of the insula and mPFC. We used source-based morphometry, a multivariate technique optimized for structural MRI, in a large sample of randomly ascertained pedigrees (N = 887) to derive an insula-mPFC component and to investigate its genetic determinants. Firstly, we replicated the insula-mPFC gray matter component as an independent source of gray matter variation in the general population, and verified its relevance to schizophrenia in an independent case-control sample. Secondly, we showed that the neuroanatomical variation defined by this component is largely determined by additive genetic variation (h(2) = 0.59), and genome-wide linkage analysis resulted in a significant linkage peak at 12q24 (LOD = 3.76). This region has been of significant interest to psychiatric genetics as it contains the Darier's disease locus and other proposed susceptibility genes (e.g., DAO, NOS1), and it has been linked to affective disorders and schizophrenia in multiple populations. Thus, in conjunction with previous clinical studies, our data imply that one or more psychiatric risk variants at 12q24 are co-inherited with reductions in mPFC and insula gray matter concentration. © 2015 Wiley Periodicals, Inc.
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Mathias SR, Knowles EEM, Kent JW, McKay DR, Curran JE, de Almeida MAA, Dyer TD, Göring HHH, Olvera RL, Duggirala R, Fox PT, Almasy L, Blangero J, Glahn DC. Recurrent major depression and right hippocampal volume: A bivariate linkage and association study. Hum Brain Mapp 2015; 37:191-202. [PMID: 26485182 DOI: 10.1002/hbm.23025] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Accepted: 10/02/2015] [Indexed: 01/04/2023] Open
Abstract
Previous work has shown that the hippocampus is smaller in the brains of individuals suffering from major depressive disorder (MDD) than those of healthy controls. Moreover, right hippocampal volume specifically has been found to predict the probability of subsequent depressive episodes. This study explored the utility of right hippocampal volume as an endophenotype of recurrent MDD (rMDD). We observed a significant genetic correlation between the two traits in a large sample of Mexican American individuals from extended pedigrees (ρg = -0.34, p = 0.013). A bivariate linkage scan revealed a significant pleiotropic quantitative trait locus on chromosome 18p11.31-32 (LOD = 3.61). Bivariate association analysis conducted under the linkage peak revealed a variant (rs574972) within an intron of the gene SMCHD1 meeting the corrected significance level (χ(2) = 19.0, p = 7.4 × 10(-5)). Univariate association analyses of each phenotype separately revealed that the same variant was significant for right hippocampal volume alone, and also revealed a suggestively significant variant (rs12455524) within the gene DLGAP1 for rMDD alone. The results implicate right-hemisphere hippocampal volume as a possible endophenotype of rMDD, and in so doing highlight a potential gene of interest for rMDD risk.
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Olvera RL, Williamson DE, Fisher-Hoch SP, Vatcheva KP, McCormick JB. Depression, obesity, and metabolic syndrome: prevalence and risks of comorbidity in a population-based representative sample of Mexican Americans. J Clin Psychiatry 2015; 76:e1300-5. [PMID: 26528653 PMCID: PMC5836315 DOI: 10.4088/jcp.14m09118] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2014] [Accepted: 10/23/2014] [Indexed: 02/08/2023]
Abstract
INTRODUCTION We examined the prevalence of depression, obesity, and metabolic syndrome and associations between them in a population-based representative cohort of Mexican Americans living on the United States-Mexico border. METHOD The sample in this cross-sectional analysis consisted of 1,768 Mexican American adults (≥ 18 years of age) assessed between the years 2004 and 2010, with whom we tested our central hypothesis of a significant relationship between obesity and depression. Depression was measured using the Center for Epidemiologic Studies-Depression scale (CES-D) with a cutoff score of ≥ 16 for depression and a cutoff score of ≥ 27 for severe depression. We categorized body mass index (BMI) values as obese (≥ 30kg/m(2)) and later subdivided the obese subjects into obese (30-39 kg/m(2)[inclusive]) and morbidly obese (≥ 40 kg/m(2)). Metabolic syndrome was defined using the American Heart Association definition requiring at least 3 of the following: increased waist circumference, elevated triglycerides, reduced high-density lipoprotein (HDL) cholesterol, elevated blood pressure, and elevated fasting glucose. Weighted data were analyzed to establish prevalence of depression, obesity, and metabolic syndrome. Univariate and multivariable weighted regression models were used to test potential associations between these disorders. RESULTS Using weighted prevalence, we observed high rates of depression (30%), obesity (52%), and metabolic syndrome (45%). Univariate models revealed female gender (P = .0004), low education (P = .003), low HDL level (P = .009), and increased waist circumference (P = .03) were associated with depression. Female gender (P = .01), low education (P = .003), and morbid obesity (P = .002) were risk factors for severe depression and remained significant in multivariable models. CONCLUSIONS In this large cohort of Mexican Americans, obesity, female gender, and low education were identified risk factors for depression. These indicators may serve as targets for early detection, prevention, and intervention in this population.
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Vatcheva KP, Fisher-Hoch SP, Rahbar MH, Lee M, Olvera RL, Mccormick JB. ASSOCIATION OF TOTAL AND DIFFERENTIAL WHITE BLOOD CELL COUNTS TO DEVELOPMENT OF TYPE 2 DIABETES IN MEXICAN AMERICANS IN CAMERON COUNTY HISPANIC COHORT. DIABETES RESEARCH (EDINBURGH, SCOTLAND) 2015; 1:103-112. [PMID: 28090128 PMCID: PMC5226365 DOI: 10.17140/droj-1-117] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
OBJECTIVE To evaluate the relationship between total and differential White Blood Cell (WBC) counts with time to transition to type 2 diabetes in Mexican Americans using prospective data from the Cameron County Hispanic Cohort (CCHC). RESULTS Multivariable Cox proportional hazards regression models revealed that obese Mexican-American cohort participants whose total WBC or granulocyte count increased over time had 1.39 and 1.35 times higher risk respectively of transition to type 2 diabetes when compared to overweight participants. The granulocyte or total WBC count in participants with BMI≥35 were significant risk factors for transition to type 2 diabetes. CONCLUSIONS Increased total WBC and WBC differential counts, particularly lymphocytes and granulocytes, are associated with risk of transition to type 2 diabetes in obese Mexican Americans, after adjusting for other potential confounders. Screening and monitoring the WBC counts, including lymphocytes and granulocytes can help with monitoring potential transition to type 2 diabetes.
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Kochunov P, Jahanshad N, Marcus D, Winkler A, Sprooten E, Nichols TE, Wright SN, Hong LE, Patel B, Behrens T, Jbabdi S, Andersson J, Lenglet C, Yacoub E, Moeller S, Auerbach E, Ugurbil K, Sotiropoulos SN, Brouwer RM, Landman B, Lemaitre H, den Braber A, Zwiers MP, Ritchie S, vanHulzen K, Almasy L, Curran J, deZubicaray GI, Duggirala R, Fox P, Martin NG, McMahon KL, Mitchell B, Olvera RL, Peterson C, Starr J, Sussmann J, Wardlaw J, Wright M, Boomsma DI, Kahn R, de Geus EJC, Williamson DE, Hariri A, van t Ent D, Bastin ME, McIntosh A, Deary IJ, Hulshoff pol HE, Blangero J, Thompson PM, Glahn DC, Van Essen DC. Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data. Neuroimage 2015; 111:300-11. [PMID: 25747917 PMCID: PMC4387079 DOI: 10.1016/j.neuroimage.2015.02.050] [Citation(s) in RCA: 136] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2014] [Revised: 01/10/2015] [Accepted: 02/23/2015] [Indexed: 01/23/2023] Open
Abstract
The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p<10(-5)), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application.
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Ramage AE, Lin AL, Olvera RL, Fox PT, Williamson DE. Resting-state regional cerebral blood flow during adolescence: associations with initiation of substance use and prediction of future use disorders. Drug Alcohol Depend 2015; 149:40-8. [PMID: 25682478 PMCID: PMC4361292 DOI: 10.1016/j.drugalcdep.2015.01.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2014] [Revised: 01/09/2015] [Accepted: 01/12/2015] [Indexed: 11/28/2022]
Abstract
BACKGROUND Adolescence is a period of developmental flux when brain systems are vulnerable to influences of early substance use, which in turn relays increased risk for substance use disorders. Our study intent was to assess adolescent regional cerebral blood flow (rCBF) as it relates to current and future alcohol use. The aim was to identify brain-based predictors for initiation of alcohol use and onset of future substance use disorders. METHODS Quantitative rCBF was assessed in 100 adolescents (age 12-15). Prospective behavioral assessments were conducted annually over a three-year follow-up period to characterize onset of alcohol initiation, future drinking patterns and use disorders. Comparisons amongst use groups (i.e., current-, future-, and non-alcohol using adolescents) identified rCBF associated with initiation of alcohol use. Regression by future drinking patterns identified rCBF predictive of heavier drinking. Survival analysis determined whether or not baseline rCBF predicted later development of use disorders. RESULTS Baseline rCBF was decreased to the parietal cortex and increased to mesolimbic regions in adolescents currently using alcohol as well as those who would use alcohol in the future. Higher baseline rCBF to the left fusiform gyrus and lower rCBF to the right inferior parietal cortex and left cerebellum was associated with future drinking patterns as well as predicted the onset of alcohol and substance use disorders in this cohort. CONCLUSIONS Variations in resting rCBF to regions within reward and default mode or control networks appear to represent trait markers of alcohol use initiation and are predictive of future development of use disorders.
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Spieker EA, Kochunov P, Rowland LM, Sprooten E, Winkler AM, Olvera RL, Almasy L, Duggirala R, Fox PT, Blangero J, Glahn DC, Curran JE. Shared genetic variance between obesity and white matter integrity in Mexican Americans. Front Genet 2015; 6:26. [PMID: 25763009 PMCID: PMC4327744 DOI: 10.3389/fgene.2015.00026] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 01/19/2015] [Indexed: 01/01/2023] Open
Abstract
Obesity is a chronic metabolic disorder that may also lead to reduced white matter integrity, potentially due to shared genetic risk factors. Genetic correlation analyses were conducted in a large cohort of Mexican American families in San Antonio (N = 761, 58% females, ages 18–81 years; 41.3 ± 14.5) from the Genetics of Brain Structure and Function Study. Shared genetic variance was calculated between measures of adiposity [(body mass index (BMI; kg/m2) and waist circumference (WC; in)] and whole-brain and regional measurements of cerebral white matter integrity (fractional anisotropy). Whole-brain average and regional fractional anisotropy values for 10 major white matter tracts were calculated from high angular resolution diffusion tensor imaging data (DTI; 1.7 × 1.7 × 3 mm; 55 directions). Additive genetic factors explained intersubject variance in BMI (heritability, h2 = 0.58), WC (h2 = 0.57), and FA (h2 = 0.49). FA shared significant portions of genetic variance with BMI in the genu (ρG = −0.25), body (ρG = −0.30), and splenium (ρG = −0.26) of the corpus callosum, internal capsule (ρG = −0.29), and thalamic radiation (ρG = −0.31) (all p's = 0.043). The strongest evidence of shared variance was between BMI/WC and FA in the superior fronto-occipital fasciculus (ρG = −0.39, p = 0.020; ρG = −0.39, p = 0.030), which highlights region-specific variation in neural correlates of obesity. This may suggest that increase in obesity and reduced white matter integrity share common genetic risk factors.
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Hibar DP, Stein JL, Renteria ME, Arias-Vasquez A, Desrivières S, Jahanshad N, Toro R, Wittfeld K, Abramovic L, Andersson M, Aribisala BS, Armstrong NJ, Bernard M, Bohlken MM, Boks MP, Bralten J, Brown AA, Chakravarty MM, Chen Q, Ching CRK, Cuellar-Partida G, den Braber A, Giddaluru S, Goldman AL, Grimm O, Guadalupe T, Hass J, Woldehawariat G, Holmes AJ, Hoogman M, Janowitz D, Jia T, Kim S, Klein M, Kraemer B, Lee PH, Olde Loohuis LM, Luciano M, Macare C, Mather KA, Mattheisen M, Milaneschi Y, Nho K, Papmeyer M, Ramasamy A, Risacher SL, Roiz-Santiañez R, Rose EJ, Salami A, Sämann PG, Schmaal L, Schork AJ, Shin J, Strike LT, Teumer A, van Donkelaar MMJ, van Eijk KR, Walters RK, Westlye LT, Whelan CD, Winkler AM, Zwiers MP, Alhusaini S, Athanasiu L, Ehrlich S, Hakobjan MMH, Hartberg CB, Haukvik UK, Heister AJGAM, Hoehn D, Kasperaviciute D, Liewald DCM, Lopez LM, Makkinje RRR, Matarin M, Naber MAM, McKay DR, Needham M, Nugent AC, Pütz B, Royle NA, Shen L, Sprooten E, Trabzuni D, van der Marel SSL, van Hulzen KJE, Walton E, Wolf C, Almasy L, Ames D, Arepalli S, Assareh AA, Bastin ME, Brodaty H, Bulayeva KB, Carless MA, Cichon S, Corvin A, Curran JE, Czisch M, de Zubicaray GI, Dillman A, Duggirala R, Dyer TD, Erk S, Fedko IO, Ferrucci L, Foroud TM, Fox PT, Fukunaga M, Gibbs JR, Göring HHH, Green RC, Guelfi S, Hansell NK, Hartman CA, Hegenscheid K, Heinz A, Hernandez DG, Heslenfeld DJ, Hoekstra PJ, Holsboer F, Homuth G, Hottenga JJ, Ikeda M, Jack CR, Jenkinson M, Johnson R, Kanai R, Keil M, Kent JW, Kochunov P, Kwok JB, Lawrie SM, Liu X, Longo DL, McMahon KL, Meisenzahl E, Melle I, Mohnke S, Montgomery GW, Mostert JC, Mühleisen TW, Nalls MA, Nichols TE, Nilsson LG, Nöthen MM, Ohi K, Olvera RL, Perez-Iglesias R, Pike GB, Potkin SG, Reinvang I, Reppermund S, Rietschel M, Romanczuk-Seiferth N, Rosen GD, Rujescu D, Schnell K, Schofield PR, Smith C, Steen VM, Sussmann JE, Thalamuthu A, Toga AW, Traynor BJ, Troncoso J, Turner JA, Valdés Hernández MC, van 't Ent D, van der Brug M, van der Wee NJA, van Tol MJ, Veltman DJ, Wassink TH, Westman E, Zielke RH, Zonderman AB, Ashbrook DG, Hager R, Lu L, McMahon FJ, Morris DW, Williams RW, Brunner HG, Buckner RL, Buitelaar JK, Cahn W, Calhoun VD, Cavalleri GL, Crespo-Facorro B, Dale AM, Davies GE, Delanty N, Depondt C, Djurovic S, Drevets WC, Espeseth T, Gollub RL, Ho BC, Hoffmann W, Hosten N, Kahn RS, Le Hellard S, Meyer-Lindenberg A, Müller-Myhsok B, Nauck M, Nyberg L, Pandolfo M, Penninx BWJH, Roffman JL, Sisodiya SM, Smoller JW, van Bokhoven H, van Haren NEM, Völzke H, Walter H, Weiner MW, Wen W, White T, Agartz I, Andreassen OA, Blangero J, Boomsma DI, Brouwer RM, Cannon DM, Cookson MR, de Geus EJC, Deary IJ, Donohoe G, Fernández G, Fisher SE, Francks C, Glahn DC, Grabe HJ, Gruber O, Hardy J, Hashimoto R, Hulshoff Pol HE, Jönsson EG, Kloszewska I, Lovestone S, Mattay VS, Mecocci P, McDonald C, McIntosh AM, Ophoff RA, Paus T, Pausova Z, Ryten M, Sachdev PS, Saykin AJ, Simmons A, Singleton A, Soininen H, Wardlaw JM, Weale ME, Weinberger DR, Adams HHH, Launer LJ, Seiler S, Schmidt R, Chauhan G, Satizabal CL, Becker JT, Yanek L, van der Lee SJ, Ebling M, Fischl B, Longstreth WT, Greve D, Schmidt H, Nyquist P, Vinke LN, van Duijn CM, Xue L, Mazoyer B, Bis JC, Gudnason V, Seshadri S, Ikram MA, Martin NG, Wright MJ, Schumann G, Franke B, Thompson PM, Medland SE. Common genetic variants influence human subcortical brain structures. Nature 2015; 520:224-9. [PMID: 25607358 DOI: 10.1038/nature14101] [Citation(s) in RCA: 552] [Impact Index Per Article: 61.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2014] [Accepted: 11/19/2014] [Indexed: 12/11/2022]
Abstract
The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.
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Glahn DC, Williams JT, McKay DR, Knowles EE, Sprooten E, Mathias SR, Curran JE, Kent JW, Carless MA, Göring HHH, Dyer TD, Woolsey MD, Winkler AM, Olvera RL, Kochunov P, Fox PT, Duggirala R, Almasy L, Blangero J. Discovering schizophrenia endophenotypes in randomly ascertained pedigrees. Biol Psychiatry 2015; 77:75-83. [PMID: 25168609 PMCID: PMC4261014 DOI: 10.1016/j.biopsych.2014.06.027] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2014] [Revised: 06/08/2014] [Accepted: 06/15/2014] [Indexed: 01/21/2023]
Abstract
BACKGROUND Although case-control approaches are beginning to disentangle schizophrenia's complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member's risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. METHODS A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage. RESULTS Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. CONCLUSIONS With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.
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McKay DR, Knowles EEM, Winkler AAM, Sprooten E, Kochunov P, Olvera RL, Curran JE, Kent JW, Carless MA, Göring HHH, Dyer TD, Duggirala R, Almasy L, Fox PT, Blangero J, Glahn DC. Influence of age, sex and genetic factors on the human brain. Brain Imaging Behav 2014; 8:143-52. [PMID: 24297733 DOI: 10.1007/s11682-013-9277-5] [Citation(s) in RCA: 63] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
We report effects of age, age(2), sex and additive genetic factors on variability in gray matter thickness, surface area and white matter integrity in 1,010 subjects from the Genetics of Brain Structure and Function Study. Age was more strongly associated with gray matter thickness and fractional anisotropy of water diffusion in white matter tracts, while sex was more strongly associated with gray matter surface area. Widespread heritability of neuroanatomic traits was observed, suggesting that brain structure is under strong genetic control. Furthermore, our findings indicate that neuroimaging-based measurements of cerebral variability are sensitive to genetic mediation. Fundamental studies of genetic influence on the brain will help inform gene discovery initiatives in both clinical and normative samples.
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Dougherty DM, Charles NE, Mathias CW, Ryan SR, Olvera RL, Liang Y, Acheson A. Delay discounting differentiates pre-adolescents at high and low risk for substance use disorders based on family history. Drug Alcohol Depend 2014; 143:105-11. [PMID: 25096271 PMCID: PMC4161645 DOI: 10.1016/j.drugalcdep.2014.07.012] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2014] [Revised: 07/10/2014] [Accepted: 07/10/2014] [Indexed: 11/25/2022]
Abstract
BACKGROUND Youth with family histories of substance use disorders (FH+) are at increased risk for developing substance use disorders relative to those without such histories (FH-). FH+ individuals show deficits in impulse control that parallel those in individuals with substance use disorders. Elucidating how specific components of impulse control are affected in FH+ pre-adolescents would advance our understanding of how deficits in impulse control relate to risk of substance use disorders. METHOD A total of 386 children (305 FH+, 81 FH-; ages 10-12) with no histories of regular alcohol or other drug use were compared on measures of delay discounting (Kirby), response inhibition (GoStop Impulsivity Paradigm), and response initiation impulsivity (Immediate Memory Task). The independent associations between these three behavioral measures of impulsivity and FH status were analyzed using logistic regression models. RESULT FH+ pre-adolescents performed more impulsively on measures of delay discounting and response inhibition impulsivity, but there were no significant group differences on response initiation impulsivity. When the behavioral impulsivity measures were examined simultaneously, delay discounting was most robustly associated with FH status. CONCLUSIONS These results identify deficits in impulse control present in FH+ pre-adolescents before the onset of regular substance use, and suggest that increased delay discounting may be an important behavioral phenotype for pre-adolescents at risk for substance use involvement.
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Kochunov P, Jahanshad N, Sprooten E, Nichols TE, Mandl RC, Almasy L, Booth T, Brouwer RM, Curran JE, de Zubicaray GI, Dimitrova R, Duggirala R, Fox PT, Hong LE, Landman BA, Lemaitre H, Lopez LM, Martin NG, McMahon KL, Mitchell BD, Olvera RL, Peterson CP, Starr JM, Sussmann JE, Toga AW, Wardlaw JM, Wright MJ, Wright SN, Bastin ME, McIntosh AM, Boomsma DI, Kahn RS, den Braber A, de Geus EJC, Deary IJ, Hulshoff Pol HE, Williamson DE, Blangero J, van 't Ent D, Thompson PM, Glahn DC. Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling. Neuroimage 2014; 95:136-50. [PMID: 24657781 PMCID: PMC4043878 DOI: 10.1016/j.neuroimage.2014.03.033] [Citation(s) in RCA: 102] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2013] [Revised: 02/21/2014] [Accepted: 03/04/2014] [Indexed: 01/25/2023] Open
Abstract
Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.
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Thompson PM, Stein JL, Medland SE, Hibar DP, Vasquez AA, Renteria ME, Toro R, Jahanshad N, Schumann G, Franke B, Wright MJ, Martin NG, Agartz I, Alda M, Alhusaini S, Almasy L, Almeida J, Alpert K, Andreasen NC, Andreassen OA, Apostolova LG, Appel K, Armstrong NJ, Aribisala B, Bastin ME, Bauer M, Bearden CE, Bergmann Ø, Binder EB, Blangero J, Bockholt HJ, Bøen E, Bois C, Boomsma DI, Booth T, Bowman IJ, Bralten J, Brouwer RM, Brunner HG, Brohawn DG, Buckner RL, Buitelaar J, Bulayeva K, Bustillo JR, Calhoun VD, Cannon DM, Cantor RM, Carless MA, Caseras X, Cavalleri GL, Chakravarty MM, Chang KD, Ching CRK, Christoforou A, Cichon S, Clark VP, Conrod P, Coppola G, Crespo-Facorro B, Curran JE, Czisch M, Deary IJ, de Geus EJC, den Braber A, Delvecchio G, Depondt C, de Haan L, de Zubicaray GI, Dima D, Dimitrova R, Djurovic S, Dong H, Donohoe G, Duggirala R, Dyer TD, Ehrlich S, Ekman CJ, Elvsåshagen T, Emsell L, Erk S, Espeseth T, Fagerness J, Fears S, Fedko I, Fernández G, Fisher SE, Foroud T, Fox PT, Francks C, Frangou S, Frey EM, Frodl T, Frouin V, Garavan H, Giddaluru S, Glahn DC, Godlewska B, Goldstein RZ, Gollub RL, Grabe HJ, Grimm O, Gruber O, Guadalupe T, Gur RE, Gur RC, Göring HHH, Hagenaars S, Hajek T, Hall GB, Hall J, Hardy J, Hartman CA, Hass J, Hatton SN, Haukvik UK, Hegenscheid K, Heinz A, Hickie IB, Ho BC, Hoehn D, Hoekstra PJ, Hollinshead M, Holmes AJ, Homuth G, Hoogman M, Hong LE, Hosten N, Hottenga JJ, Hulshoff Pol HE, Hwang KS, Jack CR, Jenkinson M, Johnston C, Jönsson EG, Kahn RS, Kasperaviciute D, Kelly S, Kim S, Kochunov P, Koenders L, Krämer B, Kwok JBJ, Lagopoulos J, Laje G, Landen M, Landman BA, Lauriello J, Lawrie SM, Lee PH, Le Hellard S, Lemaître H, Leonardo CD, Li CS, Liberg B, Liewald DC, Liu X, Lopez LM, Loth E, Lourdusamy A, Luciano M, Macciardi F, Machielsen MWJ, MacQueen GM, Malt UF, Mandl R, Manoach DS, Martinot JL, Matarin M, Mather KA, Mattheisen M, Mattingsdal M, Meyer-Lindenberg A, McDonald C, McIntosh AM, McMahon FJ, McMahon KL, Meisenzahl E, Melle I, Milaneschi Y, Mohnke S, Montgomery GW, Morris DW, Moses EK, Mueller BA, Muñoz Maniega S, Mühleisen TW, Müller-Myhsok B, Mwangi B, Nauck M, Nho K, Nichols TE, Nilsson LG, Nugent AC, Nyberg L, Olvera RL, Oosterlaan J, Ophoff RA, Pandolfo M, Papalampropoulou-Tsiridou M, Papmeyer M, Paus T, Pausova Z, Pearlson GD, Penninx BW, Peterson CP, Pfennig A, Phillips M, Pike GB, Poline JB, Potkin SG, Pütz B, Ramasamy A, Rasmussen J, Rietschel M, Rijpkema M, Risacher SL, Roffman JL, Roiz-Santiañez R, Romanczuk-Seiferth N, Rose EJ, Royle NA, Rujescu D, Ryten M, Sachdev PS, Salami A, Satterthwaite TD, Savitz J, Saykin AJ, Scanlon C, Schmaal L, Schnack HG, Schork AJ, Schulz SC, Schür R, Seidman L, Shen L, Shoemaker JM, Simmons A, Sisodiya SM, Smith C, Smoller JW, Soares JC, Sponheim SR, Sprooten E, Starr JM, Steen VM, Strakowski S, Strike L, Sussmann J, Sämann PG, Teumer A, Toga AW, Tordesillas-Gutierrez D, Trabzuni D, Trost S, Turner J, Van den Heuvel M, van der Wee NJ, van Eijk K, van Erp TGM, van Haren NEM, van ‘t Ent D, van Tol MJ, Valdés Hernández MC, Veltman DJ, Versace A, Völzke H, Walker R, Walter H, Wang L, Wardlaw JM, Weale ME, Weiner MW, Wen W, Westlye LT, Whalley HC, Whelan CD, White T, Winkler AM, Wittfeld K, Woldehawariat G, Wolf C, Zilles D, Zwiers MP, Thalamuthu A, Schofield PR, Freimer NB, Lawrence NS, Drevets W. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav 2014; 8:153-82. [PMID: 24399358 PMCID: PMC4008818 DOI: 10.1007/s11682-013-9269-5] [Citation(s) in RCA: 507] [Impact Index Per Article: 50.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
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Chouinard-Decorte F, McKay DR, Reid A, Khundrakpam B, Zhao L, Karama S, Rioux P, Sprooten E, Knowles E, Kent JW, Curran JE, Göring HHH, Dyer TD, Olvera RL, Kochunov P, Duggirala R, Fox PT, Almasy L, Blangero J, Bellec P, Evans AC, Glahn DC. Heritable changes in regional cortical thickness with age. Brain Imaging Behav 2014; 8:208-16. [PMID: 24752552 PMCID: PMC4205107 DOI: 10.1007/s11682-014-9296-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2013] [Accepted: 02/05/2014] [Indexed: 01/15/2023]
Abstract
It is now well established that regional indices of brain structure such as cortical thickness, surface area or grey matter volume exhibit spatially variable patterns of heritability. However, a recent study found these patterns to change with age during development, a result supported by gene expression studies. Changes in heritability have not been investigated in adulthood so far and could have important implications in the study of heritability and genetic correlations in the brain as well as in the discovery of specific genes explaining them. Herein, we tested for genotype by age (G ×A) interactions, an extension of genotype by environment interactions, through adulthood and healthy aging in 902 subjects from the Genetics of Brain Structure (GOBS) study. A "jackknife" based method for the analysis of stable cortical thickness clusters (JASC) and scale selection is also introduced. Although additive genetic variance remained constant throughout adulthood, we found evidence for incomplete pleiotropy across age in the cortical thickness of paralimbic and parieto-temporal areas. This suggests that different genetic factors account for cortical thickness heritability at different ages in these regions.
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Sprooten E, Knowles EE, McKay DR, Göring HH, Curran JE, Kent JW, Carless MA, Dyer TD, Drigalenko EI, Olvera RL, Fox PT, Almasy L, Duggirala R, Kochunov P, Blangero J, Glahn DC. Common genetic variants and gene expression associated with white matter microstructure in the human brain. Neuroimage 2014; 97:252-61. [PMID: 24736177 DOI: 10.1016/j.neuroimage.2014.04.021] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2014] [Revised: 03/29/2014] [Accepted: 04/07/2014] [Indexed: 12/29/2022] Open
Abstract
Identifying genes that contribute to white matter microstructure should provide insights into the neurobiological processes that regulate white matter development, plasticity and pathology. We detected five significant SNPs using genome-wide association analysis on a global measure of fractional anisotropy in 776 individuals from large extended pedigrees. Genetic correlations and genome-wide association results indicated that the genetic signal was largely homogeneous across white matter regions. Using RNA transcripts derived from lymphocytes in the same individuals, we identified two genes (GNA13 and CCDC91) that are likely to be cis-regulated by top SNPs, and whose expression levels were also genetically correlated with fractional anisotropy. A transcript of HTR7 was phenotypically associated with FA, and was associated with an intronic genome-wide significant SNP. These results encourage further research in the mechanisms by which GNA13, HTR7 and CCDC91 influence brain structure, and emphasize a role for g-protein signaling in the development and maintenance of white matter microstructure in health and disease.
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Jahanshad N, Kochunov PV, Sprooten E, Mandl RC, Nichols TE, Almasy L, Blangero J, Brouwer RM, Curran JE, de Zubicaray GI, Duggirala R, Fox PT, Hong LE, Landman BA, Martin NG, McMahon KL, Medland SE, Mitchell BD, Olvera RL, Peterson CP, Starr JM, Sussmann JE, Toga AW, Wardlaw JM, Wright MJ, Pol HEH, Bastin ME, McIntosh AM, Deary IJ, Thompson PM, Glahn DC. Corrigendum to “Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA–DTI working group” [NeuroImage 81 (2013) 455–469]. Neuroimage 2014. [DOI: 10.1016/j.neuroimage.2013.12.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022] Open
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Curran JE, McKay DR, Winkler AM, Olvera RL, Carless MA, Dyer TD, Kent JW, Kochunov P, Sprooten E, Knowles EE, Comuzzie AG, Fox PT, Almasy L, Duggirala R, Blangero J, Glahn DC. Identification of pleiotropic genetic effects on obesity and brain anatomy. Hum Hered 2013; 75:136-43. [PMID: 24081229 DOI: 10.1159/000353953] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND/AIMS Obesity is a major contributor to the global burden of chronic disease and disability, though current knowledge of causal biologic underpinnings is lacking. Through the regulation of energy homeostasis and interactions with adiposity and gut signals, the brain is thought to play a significant role in the development of this disorder. While neuroanatomical variation has been associated with obesity, it is unclear if this relationship is influenced by common genetic mechanisms. In this study, we sought genetic components that influence both brain anatomy and body mass index (BMI) to provide further insight into the role of the brain in energy homeostasis and obesity. METHODS MRI images of brain anatomy were acquired in 839 Mexican American individuals from large extended pedigrees. Bivariate linkage and quantitative analyses were performed in SOLAR. RESULTS Genetic factors associated with an increased BMI were also associated with a reduced cortical surface area and subcortical volume. We identified two genome-wide quantitative trait loci that influenced BMI and the ventral diencephalon volume, and BMI and the supramarginal gyrus surface area, respectively. CONCLUSIONS This study represents the first genetic analysis seeking evidence of pleiotropic effects acting on both brain anatomy and BMI. Our results suggest that a region on chromosome 17 contributes to the development of obesity, potentially through leptin-induced signaling in the hypothalamus, and that a region on chromosome 3 appears to jointly influence the food-related reward circuitry and the supramarginal gyrus.
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Kochunov P, Charlesworth J, Winkler A, Hong LE, Nichols TE, Curran JE, Sprooten E, Jahanshad N, Thompson PM, Johnson MP, Kent JW, Landman BA, Mitchell B, Cole SA, Dyer TD, Moses EK, Goring HHH, Almasy L, Duggirala R, Olvera RL, Glahn DC, Blangero J. Transcriptomics of cortical gray matter thickness decline during normal aging. Neuroimage 2013; 82:273-83. [PMID: 23707588 DOI: 10.1016/j.neuroimage.2013.05.066] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2013] [Revised: 04/23/2013] [Accepted: 05/14/2013] [Indexed: 01/27/2023] Open
Abstract
INTRODUCTION We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging. METHODS Transcriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 μm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability. RESULTS Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT. CONCLUSION Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation.
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Zappitelli MC, Bordin IA, Hatch JP, Caetano SC, Zunta-Soares G, Olvera RL, Soares JC. Temperament and character traits in children and adolescents with major depressive disorder: a case-control study. Compr Psychiatry 2013; 54:346-53. [PMID: 23218681 DOI: 10.1016/j.comppsych.2012.10.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2012] [Revised: 10/14/2012] [Accepted: 10/23/2012] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVES To evaluate temperament and character traits using the Junior Temperament and Character Inventory (JTCI) in children and adolescents with major depressive disorder (MDD) in comparison with healthy control subjects (HC), and to verify if comorbidity with disruptive behavioral disorders and being currently depressed influence JTCI scores. METHODS A case-control study comprising 41 MDD children/adolescents matched to 40 HC by gender and age (8-17years). All participants were assessed diagnostically with the Kiddie Schedule for Affective Disorders and Schizophrenia - Present and Lifetime (K-SADS-PL). Temperament and character traits were measured with the parent and child versions of JTCI, and depression was evaluated with the Children's Depression Rating Scale (CDRS). RESULTS According to child and parent data, MDD subjects had significantly higher scores on harm avoidance and novelty seeking, and lower scores on reward dependence, persistence, self-directedness and cooperativeness compared with HC. According to parent data only, MDD subjects significantly differed from HC on self-transcendence (lower spirituality scores and higher fantasy scores). Comorbidity with disruptive behavioral disorders exerted influence on almost all dimensions, in general increasing the mean differences between MDD and HC subjects. Also, being currently depressed did not influence the results, except for reward dependence according to parent data. LIMITATIONS The cross-sectional nature of the study and its limited sample size. CONCLUSIONS MDD children/adolescents have a different temperament and character profile compared to HC subjects. This study supports previous findings of trait-like characteristics of harm avoidance and self-directedness.
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Jahanshad N, Kochunov PV, Sprooten E, Mandl RC, Nichols TE, Almasy L, Blangero J, Brouwer RM, Curran JE, de Zubicaray GI, Duggirala R, Fox PT, Hong LE, Landman BA, Martin NG, McMahon KL, Medland SE, Mitchell BD, Olvera RL, Peterson CP, Starr JM, Sussmann JE, Toga AW, Wardlaw JM, Wright MJ, Hulshoff Pol HE, Bastin ME, McIntosh AM, Deary IJ, Thompson PM, Glahn DC. Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group. Neuroimage 2013; 81:455-469. [PMID: 23629049 DOI: 10.1016/j.neuroimage.2013.04.061] [Citation(s) in RCA: 297] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2013] [Revised: 03/28/2013] [Accepted: 04/10/2013] [Indexed: 10/26/2022] Open
Abstract
The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).
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Kochunov P, Glahn DC, Rowland LM, Olvera RL, Winkler A, Yang YH, Sampath H, Carpenter WT, Duggirala R, Curran J, Blangero J, Hong LE. Testing the hypothesis of accelerated cerebral white matter aging in schizophrenia and major depression. Biol Psychiatry 2013; 73:482-91. [PMID: 23200529 PMCID: PMC3645491 DOI: 10.1016/j.biopsych.2012.10.002] [Citation(s) in RCA: 96] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2012] [Revised: 08/19/2012] [Accepted: 10/03/2012] [Indexed: 12/21/2022]
Abstract
BACKGROUND Elevated rate of aging-related biological and functional decline, termed "accelerated aging," is reported in patients with schizophrenia (SCZ) and major depressive disorder (MDD). We used diffusion tensor imaging derived fractional anisotropy (FA) as a biomarker of aging-related decline in white matter (WM) integrity to test the hypotheses of accelerated aging in SCZ and MDD. METHODS The SCZ cohort comprised 58 SCZ patients and 60 controls (aged 20-60 years). The MDD cohort comprised 136 MDD patients and 351 controls (aged 20-79 years). The main outcome measures were the diagnosis-by-age interaction on whole-brain-averaged WM FA values and FA values from 12 major WM tracts. RESULTS Diagnosis-by-age interaction for the whole-brain average FA was significant for the SCZ (p = .04) but not the MDD (p = .80) cohort. Diagnosis-by-age interaction was nominally significant (p<.05) for five WM tracts for SCZ and for none of the tracts in the MDD cohort. Tract-specific heterochronicity of the onset of age-related decline in SCZ demonstrated strong negative correlations with the age-of-peak myelination and the rates of age-related decline obtained from normative sample (r =-.61 and-.80, p<.05, respectively). No such trends existed for MDD cohort. CONCLUSIONS Cerebral WM showed accelerated aging in SCZ but not in MDD, suggesting some difference in the pathophysiology underlying their WM aging changes. Tract-specific heterochronicity of WM development modulated presentation of accelerated aging in SCZ: WM tracts that matured later in life appeared more sensitive to the pathophysiology of SCZ and demonstrated more susceptibility to disorder-related accelerated decline in FA values with age. This trend was not observed in MDD cohort.
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Kochunov P, Glahn DC, Hong LE, Lancaster J, Curran JE, Johnson MP, Winkler AM, Holcomb HH, Kent JW, Mitchell B, Kochunov V, Olvera RL, Cole SA, Dyer TD, Moses EK, Goring H, Almasy L, Duggirala R, Blangero J. P-selectin Expression Tracks Cerebral Atrophy in Mexican-Americans. Front Genet 2012; 3:65. [PMID: 22558002 PMCID: PMC3340599 DOI: 10.3389/fgene.2012.00065] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2011] [Accepted: 04/05/2012] [Indexed: 11/13/2022] Open
Abstract
Background and Purpose: We hypothesized that the P-selectin (SELP) gene, localized to a region on chromosome 1q24, pleiotropically contributes to increased blood pressure and cerebral atrophy. We tested this hypothesis by performing genetic correlation analyses for 13 mRNA gene expression measures from P-selectin and 11 other genes located in 1q24 region and three magnetic resonance imaging derived indices of cerebral integrity. Methods: The subject pool consisted of 369 (219F; aged 28–85, average = 47.1 ± 12.7 years) normally aging, community-dwelling members of large extended Mexican-American families. Genetic correlation analysis decomposed phenotypic correlation coefficients into genetic and environmental components among 13 leukocyte-based mRNA gene expressions and three whole-brain and regional measurements of cerebral integrity: cortical gray matter thickness, fractional anisotropy of cerebral white matter, and the volume of hyperintensive WM lesions. Results: From the 13 gene expressions, significant phenotypic correlations were only found for the P- and L-selectin expression levels. Increases in P-selectin expression levels tracked with decline in cerebral integrity while the opposite trend was observed for L-selectin expression. The correlations for the P-selectin expression were driven by shared genetic factors, while the correlations with L-selectin expression were due to shared environmental effects. Conclusion: This study demonstrated that P-selectin expression shared a significant variance with measurements of cerebral integrity and posits elevated P-selectin expression levels as a potential risk factor of hypertension-related cerebral atrophy.
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Stein JL, Medland SE, Vasquez AA, Hibar DP, Senstad RE, Winkler AM, Toro R, Appel K, Bartecek R, Bergmann Ø, Bernard M, Brown AA, Cannon DM, Chakravarty MM, Christoforou A, Domin M, Grimm O, Hollinshead M, Holmes AJ, Homuth G, Hottenga JJ, Langan C, Lopez LM, Hansell NK, Hwang KS, Kim S, Laje G, Lee PH, Liu X, Loth E, Lourdusamy A, Mattingsdal M, Mohnke S, Maniega SM, Nho K, Nugent AC, O'Brien C, Papmeyer M, Pütz B, Ramasamy A, Rasmussen J, Rijpkema M, Risacher SL, Roddey JC, Rose EJ, Ryten M, Shen L, Sprooten E, Strengman E, Teumer A, Trabzuni D, Turner J, van Eijk K, van Erp TGM, van Tol MJ, Wittfeld K, Wolf C, Woudstra S, Aleman A, Alhusaini S, Almasy L, Binder EB, Brohawn DG, Cantor RM, Carless MA, Corvin A, Czisch M, Curran JE, Davies G, de Almeida MAA, Delanty N, Depondt C, Duggirala R, Dyer TD, Erk S, Fagerness J, Fox PT, Freimer NB, Gill M, Göring HHH, Hagler DJ, Hoehn D, Holsboer F, Hoogman M, Hosten N, Jahanshad N, Johnson MP, Kasperaviciute D, Kent JW, Kochunov P, Lancaster JL, Lawrie SM, Liewald DC, Mandl R, Matarin M, Mattheisen M, Meisenzahl E, Melle I, Moses EK, Mühleisen TW, Nauck M, Nöthen MM, Olvera RL, Pandolfo M, Pike GB, Puls R, Reinvang I, Rentería ME, Rietschel M, Roffman JL, Royle NA, Rujescu D, Savitz J, Schnack HG, Schnell K, Seiferth N, Smith C, Steen VM, Valdés Hernández MC, Van den Heuvel M, van der Wee NJ, Van Haren NEM, Veltman JA, Völzke H, Walker R, Westlye LT, Whelan CD, Agartz I, Boomsma DI, Cavalleri GL, Dale AM, Djurovic S, Drevets WC, Hagoort P, Hall J, Heinz A, Jack CR, Foroud TM, Le Hellard S, Macciardi F, Montgomery GW, Poline JB, Porteous DJ, Sisodiya SM, Starr JM, Sussmann J, Toga AW, Veltman DJ, Walter H, Weiner MW, Bis JC, Ikram MA, Smith AV, Gudnason V, Tzourio C, Vernooij MW, Launer LJ, DeCarli C, Seshadri S, Andreassen OA, Apostolova LG, Bastin ME, Blangero J, Brunner HG, Buckner RL, Cichon S, Coppola G, de Zubicaray GI, Deary IJ, Donohoe G, de Geus EJC, Espeseth T, Fernández G, Glahn DC, Grabe HJ, Hardy J, Hulshoff Pol HE, Jenkinson M, Kahn RS, McDonald C, McIntosh AM, McMahon FJ, McMahon KL, Meyer-Lindenberg A, Morris DW, Müller-Myhsok B, Nichols TE, Ophoff RA, Paus T, Pausova Z, Penninx BW, Potkin SG, Sämann PG, Saykin AJ, Schumann G, Smoller JW, Wardlaw JM, Weale ME, Martin NG, Franke B, Wright MJ, Thompson PM. Identification of common variants associated with human hippocampal and intracranial volumes. Nat Genet 2012; 44:552-61. [PMID: 22504417 PMCID: PMC3635491 DOI: 10.1038/ng.2250] [Citation(s) in RCA: 524] [Impact Index Per Article: 43.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2011] [Accepted: 03/19/2012] [Indexed: 02/06/2023]
Abstract
Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10(-7)).
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