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1. Genome-wide association study of Tourettes syndrome.

Author

Neale, B, Stewart, S, Fagerness, J, Evans, P, Gamazon, E, Edlund, C, Service, S, Tikhomirov, A, Osiecki, L, Illmann, C, Pluzhnikov, A, Konkashbaev, A, Davis, L, Han, B, Crane, J, Scharf, J, Yu, D, Rangel-Lugo, M, Chouinard, S, Dion, Y, Girard, S, Cath, D, Smit, J, King, R, Fernandez, T, Leckman, J, Kidd, K, Kidd, J, Pakstis, A, Herrera, L, Romero, R, Fournier, E, Sandor, P, Barr, C, Phan, N, Gross-Tsur, V, Benarroch, F, Pollak, Y, Budman, C, Bruun, R, Erenberg, G, Naarden, A, Lee, P, Weiss, N, Kremeyer, B, Berrío, G, Campbell, D, Cardona Silgado, J, Ochoa, W, Mesa Restrepo, S, Muller, H, Valencia Duarte, A, Lyon, G, Leppert, M, Morgan, J, Weiss, R, Grados, M, Anderson, K, Davarya, S, Singer, H, Walkup, J, Jankovic, J, Tischfield, J, Heiman, G, Gilbert, D, Hoekstra, P, Robertson, M, Kurlan, R, Liu, C, Gibbs, J, Singleton, A, Hardy, J, Strengman, E, Crenshaw, A, Parkin, M, Wagner, M, Moessner, R, Mirel, D, Posthuma, D, Sabatti, C, Conti, D, Knowles, J, Ruiz-Linares, A, Rouleau, G, Purcell, S, Heutink, P, Oostra, B, McMahon, W, Cox, N, Pauls, D, Reus, Victor, State, Matthew, Eskin, Eleazar, Mathews, Carol, Lowe, Thomas, Freimer, Nelson, Ophoff, Roel, and Moorjani, Priya

Subjects
Adolescent, Adult, Attention Deficit Disorder with Hyperactivity, Case-Control Studies, Chromosomes, Human, Pair 9, Female, Fibrillar Collagens, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, International Cooperation, Male, Meta-Analysis as Topic, Obsessive-Compulsive Disorder, Polymorphism, Single Nucleotide, Tourette Syndrome, White People, Young Adult
Abstract

Tourettes syndrome (TS) is a developmental disorder that has one of the highest familial recurrence rates among neuropsychiatric diseases with complex inheritance. However, the identification of definitive TS susceptibility genes remains elusive. Here, we report the first genome-wide association study (GWAS) of TS in 1285 cases and 4964 ancestry-matched controls of European ancestry, including two European-derived population isolates, Ashkenazi Jews from North America and Israel and French Canadians from Quebec, Canada. In a primary meta-analysis of GWAS data from these European ancestry samples, no markers achieved a genome-wide threshold of significance (P

Published
2013

2. Genome-wide association study of Tourette's syndrome.

Author

Scharf, JM, Yu, D, Mathews, CA, Neale, BM, Stewart, SE, Fagerness, JA, Evans, P, Gamazon, E, Edlund, CK, Service, SK, Tikhomirov, A, Osiecki, L, Illmann, C, Pluzhnikov, A, Konkashbaev, A, Davis, LK, Han, B, Crane, J, Moorjani, P, Crenshaw, AT, Parkin, MA, Reus, VI, Lowe, TL, Rangel-Lugo, M, Chouinard, S, Dion, Y, Girard, S, Cath, DC, Smit, JH, King, RA, Fernandez, TV, Leckman, JF, Kidd, KK, Kidd, JR, Pakstis, AJ, State, MW, Herrera, LD, Romero, R, Fournier, E, Sandor, P, Barr, CL, Phan, N, Gross-Tsur, V, Benarroch, F, Pollak, Y, Budman, CL, Bruun, RD, Erenberg, G, Naarden, AL, Lee, PC, Weiss, N, Kremeyer, B, Berrío, GB, Campbell, DD, Cardona Silgado, JC, Ochoa, WC, Mesa Restrepo, SC, Muller, H, Valencia Duarte, AV, Lyon, GJ, Leppert, M, Morgan, J, Weiss, R, Grados, MA, Anderson, K, Davarya, S, Singer, H, Walkup, J, Jankovic, J, Tischfield, JA, Heiman, GA, Gilbert, DL, Hoekstra, PJ, Robertson, MM, Kurlan, R, Liu, C, Gibbs, JR, Singleton, A, North American Brain Expression Consortium, Hardy, J, UK Human Brain Expression Database, Strengman, E, Ophoff, RA, Wagner, M, Moessner, R, Mirel, DB, Posthuma, D, Sabatti, C, Eskin, E, Conti, DV, Knowles, JA, Ruiz-Linares, A, Rouleau, GA, Purcell, S, Heutink, P, Oostra, BA, McMahon, WM, Freimer, NB, Cox, NJ, and Pauls, DL

Subjects
North American Brain Expression Consortium, UK Human Brain Expression Database, Chromosomes, Human, Pair 9, Humans, Tourette Syndrome, Genetic Predisposition to Disease, Fibrillar Collagens, Case-Control Studies, Obsessive-Compulsive Disorder, Attention Deficit Disorder with Hyperactivity, Genotype, Polymorphism, Single Nucleotide, International Cooperation, Adolescent, Adult, Female, Male, Meta-Analysis as Topic, Genome-Wide Association Study, Young Adult, White People, Genetics, Human Genome, Mental Health, Brain Disorders, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, genetics, GWAS, neurodevelopmental disorder, tics, Tourette's syndrome, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Tourette's syndrome (TS) is a developmental disorder that has one of the highest familial recurrence rates among neuropsychiatric diseases with complex inheritance. However, the identification of definitive TS susceptibility genes remains elusive. Here, we report the first genome-wide association study (GWAS) of TS in 1285 cases and 4964 ancestry-matched controls of European ancestry, including two European-derived population isolates, Ashkenazi Jews from North America and Israel and French Canadians from Quebec, Canada. In a primary meta-analysis of GWAS data from these European ancestry samples, no markers achieved a genome-wide threshold of significance (P

Published
2013

3. A genome-wide meta-analysis of association studies of Cloninger's Temperament Scales.

Author

Service, SK, Verweij, KJH, Lahti, J, Congdon, E, Ekelund, J, Hintsanen, M, Räikkönen, K, Lehtimäki, T, Kähönen, M, Widen, E, Taanila, A, Veijola, J, Heath, AC, Madden, PAF, Montgomery, GW, Sabatti, C, Järvelin, M-R, Palotie, A, Raitakari, O, Viikari, J, Martin, NG, Eriksson, JG, Keltikangas-Järvinen, L, Wray, NR, and Freimer, NB

Subjects
Humans, Cohort Studies, Longitudinal Studies, Reproducibility of Results, Personality, Temperament, Personality Inventory, Psychometrics, Twins, Genotype, Linkage Disequilibrium, Phenotype, Genetic Heterogeneity, Polymorphism, Single Nucleotide, Adult, Middle Aged, Australia, Finland, Female, Male, Genome-Wide Association Study, association, genetics, genome-wide, meta-analysis, personality, temperament, Polymorphism, Single Nucleotide, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Temperament has a strongly heritable component, yet multiple independent genome-wide studies have failed to identify significant genetic associations. We have assembled the largest sample to date of persons with genome-wide genotype data, who have been assessed with Cloninger's Temperament and Character Inventory. Sum scores for novelty seeking, harm avoidance, reward dependence and persistence have been measured in over 11,000 persons collected in four different cohorts. Our study had >80% power to identify genome-wide significant loci (P

Published
2012

4. The dysbindin-containing complex (BLOC-1) in brain: developmental regulation, interaction with SNARE proteins and role in neurite outgrowth

Author

Ghiani, CA, Starcevic, M, Rodriguez-Fernandez, IA, Nazarian, R, Cheli, VT, Chan, LN, Malvar, JS, de Vellis, J, Sabatti, C, and Dell'Angelica, EC

Subjects
Schizophrenia, Mental Health, Brain Disorders, Genetics, Neurosciences, 1.1 Normal biological development and functioning, Underpinning research, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Analysis of Variance, Animals, Animals, Newborn, Carrier Proteins, Cattle, Cells, Cultured, Dysbindin, Dystrophin-Associated Proteins, Embryo, Mammalian, Gene Expression Regulation, Developmental, Hippocampus, Mice, Mice, Inbred C57BL, Mice, Knockout, Mutation, Nerve Tissue Proteins, Neurites, Neurons, Protein Binding, Protein Transport, Qa-SNARE Proteins, Recombinant Proteins, SNARE Proteins, Synaptosomal-Associated Protein 25, Vesicle-Associated Membrane Protein 2, schizophrenia, DTNBP1, pallidin, synaptosomal-associated protein, biological plausibility, neurite extension, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Previous studies have implicated DTNBP1 as a schizophrenia susceptibility gene and its encoded protein, dysbindin, as a potential regulator of synaptic vesicle physiology. In this study, we found that endogenous levels of the dysbindin protein in the mouse brain are developmentally regulated, with higher levels observed during embryonic and early postnatal ages than in young adulthood. We obtained biochemical evidence indicating that the bulk of dysbindin from brain exists as a stable component of biogenesis of lysosome-related organelles complex-1 (BLOC-1), a multi-subunit protein complex involved in intracellular membrane trafficking and organelle biogenesis. Selective biochemical interaction between brain BLOC-1 and a few members of the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) superfamily of proteins that control membrane fusion, including SNAP-25 and syntaxin 13, was demonstrated. Furthermore, primary hippocampal neurons deficient in BLOC-1 displayed neurite outgrowth defects. Taken together, these observations suggest a novel role for the dysbindin-containing complex, BLOC-1, in neurodevelopment, and provide a framework for considering potential effects of allelic variants in DTNBP1--or in other genes encoding BLOC-1 subunits--in the context of the developmental model of schizophrenia pathogenesis.

Published
2010

10. Disruption of the neurexin 1 gene is associated with schizophrenia

Author

Toulopoulou, T, Wiersma, D, Murray, R, Ruggeri, M, Tosato, S, Bonetto, C, Steinberg, S, Sigurdsson, E, Sigmundsson, T, Petursson, H, Gylfason, A, Olason, PI, Hardarsson, G, Jonsdottir, GA, Cahn, W, de Haan, L, Krabbendam, L, MyinGermeys, I, Werge, T, Kiemeney, LA, Franke, B, Pietiläinen, OPH, Picchioni, M, Vassos, E, Ettinger, U, Rietschel, M, Gustafsson, O, BuizerVoskamp, JE, Fossdal, R, Giegling, I, Sabatti, C, Ophoff, RA, Möller, HJ, Hartmann, AM, Hoffmann, P, Crombie, C, Rujescu, D, Veltman, J, Fraser, G, St Clair, D, Peltonen, L, Stefansson, K, Barnes, MR, Ingason, A, Stefansson, H, Nöthen, MM, Walker, N, Lonnqvist, J, Suvisaari, J, TuulioHenriksson, A, Djurovic, S, Collier, DA, Kahn, RS, Melle, I, Andreassen, OA, Hansen, T, Linszen, D, von Os, J, Bramon, E, Cichon, S, Bruggeman, R, ANS - Amsterdam Neuroscience, Adult Psychiatry, Germeys, Inez, Clinical Child and Family Studies, LEARN! - Brain, learning and development, and Faculteit Medische Wetenschappen/UMCG

Subjects
Male, Genetics and epigenetic pathways of disease [NCMLS 6], Gene Dosage, Aetiology, screening and detection [ONCOL 5], CARDIO-FACIAL SYNDROME, 0302 clinical medicine, Gene Duplication, Gene duplication, Perception and Action [DCN 1], HUMAN GENOME, Copy-number variation, European Continental Ancestry Group/genetics, Neural Cell Adhesion Molecules, POPULATION, Genetics (clinical), RISK, Genetics, 0303 health sciences, education.field_of_study, Schizophrenia/*genetics, REARRANGEMENTS, General Medicine, Exons, Nerve Tissue Proteins/*genetics, Penetrance, 3. Good health, Female, Molecular Sequence Numbers, Functional Neurogenomics [DCN 2], Adult, Psychosis, Adolescent, Cell Adhesion Molecules, Neuronal, Population, European Continental Ancestry Group, Nerve Tissue Proteins, COPY-NUMBER VARIATION, Biology, Gene dosage, Article, White People, STRUCTURAL VARIANTS, Genomic disorders and inherited multi-system disorders [IGMD 3], Molecular epidemiology [NCEBP 1], 03 medical and health sciences, Young Adult, Translational research [ONCOL 3], mental disorders, medicine, Humans, MICRODELETION, Genetic Predisposition to Disease, Gene Silencing, education, Molecular Biology, 030304 developmental biology, Genetic association, Hereditary cancer and cancer-related syndromes [ONCOL 1], AUTISM SPECTRUM DISORDER, Calcium-Binding Proteins, Case-Control Studies, Gene Deletion, Breakpoint, ADVANCING PATERNAL AGE, medicine.disease, Schizophrenia, 030217 neurology & neurosurgery
Abstract

Deletions within the neurexin 1 gene (NRXN1; 2p16.3) are associated with autism and have also been reported in two families with schizophrenia. We examined NRXN1, and the closely related NRXN2 and NRXN3 genes, for copy number variants (CNVs) in 2977 schizophrenia patients and 33 746 controls from seven European populations (Iceland, Finland, Norway, Germany, The Netherlands, Italy and UK) using microarray data. We found 66 deletions and 5 duplications in NRXN1, including a de novo deletion: 12 deletions and 2 duplications occurred in schizophrenia cases (0.47%) compared to 49 and 3 (0.15%) in controls. There was no common breakpoint and the CNVs varied from 18 to 420 kb. No CNVs were found in NRXN2 or NRXN3. We performed a Cochran-Mantel-Haenszel exact test to estimate association between all CNVs and schizophrenia (P = 0.13; OR = 1.73; 95% CI 0.81-3.50). Because the penetrance of NRXN1 CNVs may vary according to the level of functional impact on the gene, we next restricted the association analysis to CNVs that disrupt exons (0.24% of cases and 0.015% of controls). These were significantly associated with a high odds ratio (P = 0.0027; OR 8.97, 95% CI 1.8-51.9). We conclude that NRXN1 deletions affecting exons confer risk of schizophrenia. © The Author 2008. Published by Oxford University Press. All rights reserved., link_to_OA_fulltext

Published
2009

11. Large recurrent microdeletions associated with schizophrenia

Author

Toulopoulou, T, Franke, B, Crombie, C, Fossdal, R, Sigmundsson, T, BuizerVoskamp, JE, Hansen, T, Jakobsen, KD, Muglia, P, Francks, C, Matthews, PM, Murray, R, Ruggeri, M, Sabatti, C, Gylfason, A, Halldorsson, BV, Vassos, E, Tosato, S, Walshe, M, Freimer, NB, Gulcher, JR, Gudbjartsson, D, Thorsteinsdottir, U, Kong, A, Thorgeirsson, TE, Olesen, J, Vasilescu, C, Andreassen, OA, Melle, I, Mühleisen, TW, Wang, AG, Ullum, H, Need, AC, Sigurdsson, A, Jonasdottir, A, Djurovic, S, Ophoff, RA, Georgi, A, Rietschel, M, Werge, T, Bjornsson, A, Mattiasdottir, S, Blondal, T, Haraldsson, M, Petursson, H, MyinGermeys, I, Krabbendam, L, De Haan, L, Cahn, W, Bruggeman, R, Wiersma, D, Goldstein, DB, Nöthen, MM, Peltonen, L, Van Os, J, Linszen, DH, Kahn, RS, Stefansson, K, Magnusdottir, BB, Di Forti, M, Bramon, E, Paunio, T, TuulioHenriksson, A, Giegling, I, Möller, HJ, Suvisaari, J, Hartmann, A, Shianna, KV, Ge, D, Lonnqvist, J, Collier, DA, Walker, N, Li, T, Fraser, G, Ingason, A, Steinberg, S, Sigurdsson, E, St Clair, D, Kiemeney, LA, Stefansson, H, Rujescu, D, Cichon, S, Pietiläinen, OPH, ANS - Amsterdam Neuroscience, and Adult Psychiatry

Subjects
Schizophrenia/genetics, Genetics and epigenetic pathways of disease [NCMLS 6], Loss of Heterozygosity, Aetiology, screening and detection [ONCOL 5], Bioinformatics, China, Chromosomes, Human, Pair 1/genetics, Pair 15/genetics, Europe, Gene Dosage/genetics, Genetic Predisposition to Disease/genetics, Genome, Human/genetics, Genotype, Models, Genetic, Polymorphism, Single Nucleotide/genetics, Psychotic Disorders/genetics, Sequence Deletion/genetics, Perception and Action [DCN 1], Determinants in Health and Disease [EBP 1], Copy-number variation, Molecular diagnosis, prognosis and monitoring [UMCN 1.2], Genetics, education.field_of_study, Multidisciplinary, biology, CHRNA7, Fragile X syndrome, References (31) View In Table Layout, Schizophrenia, Functional Neurogenomics [DCN 2], Psychosis, Population, Single-nucleotide polymorphism, Article, Genomic disorders and inherited multi-system disorders [IGMD 3], Molecular epidemiology [NCEBP 1], Cognitive neurosciences [UMCN 3.2], Translational research [ONCOL 3], mental disorders, medicine, education, Hereditary cancer and cancer-related syndromes [ONCOL 1], medicine.disease, Genetic defects of metabolism [UMCN 5.1], biology.protein, Autism
Abstract

Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia. ©2008 Macmillan Publishers Limited. All rights reserved., link_to_OA_fulltext

Published
2008

12. Large recurrent microdeletions associated with schizophrenia [Letter to Nature]

Author

Stefansson, H., Rujescu, D., Cichon, S., Pietilainen, O., Ingason, A., Steinberg, S., Fossdal, R., Sigurdsson, E., Sigmundsson, T., Buizer-Voskamp, J., Hansen, T., Jakobsen, K., Muglia, P., Francks, C., Matthews, P., Gylfason, A., Halldorsson, B., Gudbjartsson, D., Thorgeirsson, T., Sigurdsson, A., Jonasdottir, A., Bjornsson, A., Mattiasdottir, S., Blondal, T., Haraldsson, M., Magnusdottir, B., Giegling, I., Möller, H., Hartmann, A., Shianna, K., Ge, D., Need, A., Crombie, C., Fraser, G., Walker, N., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Paunio, T., Toulopoulou, T., Bramon, E., Forti, M., Murray, R., Ruggeri, M., Vassos, E., Tosato, S., Walshe, M., Li, T., Vasilescu, C., Muhleisen, T., Wang, A., Ullum, H., Djurovic, S., Melle, I., Olesen, J., Kiemeney, L., Franke, B., Sabatti, C., Freimer, N., Gulcher, J., Thorsteinsdottir, U., Kong, A., Andreassen, O., Ophoff, R., Georgi, A., Rietschel, M., Werge, T., Petursson, H., Goldstein, D., Nothen, M., Peltonen, L., Collier, D., St. Clair, D., and Stefansson, K.

Subjects
mental disorders
Abstract

Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.

Published
2008

13. Increased paternal age and the influence on burden of genomic copy number variation in the general population

Author

Buizer-Voskamp, J.E., Blauw, H.M., Boks, M.P., Eijk, K.R. van, Veldink, J.H., Hennekam, E.A., Vorstman, J.A., Mulder, F., Tiemeier, H., Uitterlinden, A.G., Kiemeney, L.A.L.M., Berg, L.H. van den, Kahn, R.S., Sabatti, C., Ophoff, R.A., Buizer-Voskamp, J.E., Blauw, H.M., Boks, M.P., Eijk, K.R. van, Veldink, J.H., Hennekam, E.A., Vorstman, J.A., Mulder, F., Tiemeier, H., Uitterlinden, A.G., Kiemeney, L.A.L.M., Berg, L.H. van den, Kahn, R.S., Sabatti, C., and Ophoff, R.A.

Abstract

Item does not contain fulltext, Genomic copy number variations (CNVs) and increased parental age are both associated with the risk to develop a variety of clinical neuropsychiatric disorders such as autism, schizophrenia and bipolar disorder. At the same time, it has been shown that the rate of transmitted de novo single nucleotide mutations is increased with paternal age. To address whether paternal age also affects the burden of structural genomic deletions and duplications, we examined various types of CNV burden in a large population sample from the Netherlands. Healthy participants with parental age information (n = 6,773) were collected at different University Medical Centers. CNVs were called with the PennCNV algorithm using Illumina genome-wide SNP array data. We observed no evidence in support of a paternal age effect on CNV load in the offspring. Our results were negative for global measures as well as several proxies for de novo CNV events in this unique sample. While recent studies suggest de novo single nucleotide mutation rate to be dominated by the age of the father at conception, our results strongly suggest that at the level of global CNV burden there is no influence of increased paternal age. While it remains possible that local genomic effects may exist for specific phenotypes, this study indicates that global CNV burden and increased father's age may be independent disease risk factors.

Published
2013

14. A genome-wide meta-analysis of association studies of Cloninger's Temperament Scales

Author

Service, S.K., Verweij, K.J.H., Lahti, J., Congdon, E., Ekelund, J., Hintsanen, M., Raikkonen, K., Lehtimaki, T., Kahonen, M., Widen, E., Taanila, A., Veijola, J., Heath, A.C., Madden, P.A.F., Montgomery, G.W., Sabatti, C., Jarvelin, M.R., Palotie, A., Raitakari, O., Viikari, J., Martin, N.G., Eriksson, J.G., Keltikangas-Jarvinen, L., Wray, N.R., Freimer, N.B., Service, S.K., Verweij, K.J.H., Lahti, J., Congdon, E., Ekelund, J., Hintsanen, M., Raikkonen, K., Lehtimaki, T., Kahonen, M., Widen, E., Taanila, A., Veijola, J., Heath, A.C., Madden, P.A.F., Montgomery, G.W., Sabatti, C., Jarvelin, M.R., Palotie, A., Raitakari, O., Viikari, J., Martin, N.G., Eriksson, J.G., Keltikangas-Jarvinen, L., Wray, N.R., and Freimer, N.B.

Abstract

Contains fulltext : 156129.pdf (publisher's version ) (Open Access), Temperament has a strongly heritable component, yet multiple independent genome-wide studies have failed to identify significant genetic associations. We have assembled the largest sample to date of persons with genome-wide genotype data, who have been assessed with Cloninger's Temperament and Character Inventory. Sum scores for novelty seeking, harm avoidance, reward dependence and persistence have been measured in over 11 000 persons collected in four different cohorts. Our study had >80% power to identify genome-wide significant loci (P < 1.25 x 10(-8), with correction for testing four scales) accounting for >= 0.4% of the phenotypic variance in temperament scales. Using meta-analysis techniques, gene-based tests and pathway analysis we have tested over 1.2 million single-nucleotide polymorphisms (SNPs) for association to each of the four temperament dimensions. We did not discover any SNPs, genes, or pathways to be significantly related to the four temperament dimensions, after correcting for multiple testing. Less than 1% of the variability in any temperament dimension appears to be accounted for by a risk score derived from the SNPs showing strongest association to the temperament dimensions. Elucidation of genetic loci significantly influencing temperament and personality will require potentially very large samples, and/or a more refined phenotype. Item response theory methodology may be a way to incorporate data from cohorts assessed with multiple personality instruments, and might be a method by which a large sample of a more refined phenotype could be acquired.

Published
2012

15. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Author

DIAGRAM+ Consortium, MAGIC Consortium, GLGC Investigators, MuTHER Consortium, DIAGRAM Consortium, GIANT Consortium, Global B Pgen Consortium, Procardis Consortium, MAGIC investigators, GLGC Consortium, Olson, J., Kronmal, R., Robbins, J., Chaves, PH., Burke, G., Kuller, LH., Tracy, R., Gottdiener, J., Prineas, R., Becker, JT., Enright, P., Klein, R., O'Leary, DH., Dastani, Z., Hivert, M.F., Timpson, N., Perry, J.R., Yuan, X., Scott, R.A., Henneman, P., Heid, I.M., Kizer, J.R., Lyytikäinen, L.P., Fuchsberger, C., Tanaka, T., Morris, A.P., Small, K., Isaacs, A., Beekman, M., Coassin, S., Lohman, K., Qi, L., Kanoni, S., Pankow, J.S., Uh, H.W., Wu, Y., Bidulescu, A., Rasmussen-Torvik, L.J., Greenwood, C.M., Ladouceur, M., Grimsby, J., Manning, A.K., Liu, C.T., Kooner, J., Mooser, V.E., Vollenweider, P., Kapur, K.A., Chambers, J., Wareham, N.J., Langenberg, C., Frants, R., Willems-Vandijk, K., Oostra, B.A., Willems, S.M., Lamina, C., Winkler, T.W., Psaty, B.M., Tracy, R.P., Brody, J., Chen, I., Viikari, J., Kähönen, M., Pramstaller, P.P., Evans, D.M., St Pourcain, B., Sattar, N., Wood, A.R., Bandinelli, S., Carlson, O.D., Egan, J.M., Böhringer, S., van Heemst, D., Kedenko, L., Kristiansson, K., Nuotio, M.L., Loo, B.M., Harris, T., Garcia, M., Kanaya, A., Haun, M., Klopp, N., Wichmann, H.E., Deloukas, P., Katsareli, E., Couper, D.J., Duncan, B.B., Kloppenburg, M., Adair, L.S., Borja, J.B., Wilson, J.G., Musani, S., Guo, X., Johnson, T., Semple, R., Teslovich, T.M., Allison, M.A., Redline, S., Buxbaum, S.G., Mohlke, K.L., Meulenbelt, I., Ballantyne, C.M., Dedoussis, G.V., Hu, F.B., Liu, Y., Paulweber, B., Spector, T.D., Slagboom, P.E., Ferrucci, L., Jula, A., Perola, M., Raitakari, O., Florez, J.C., Salomaa, V., Eriksson, J.G., Frayling, T.M., Hicks, A.A., Lehtimäki, T., Smith, G.D., Siscovick, D.S., Kronenberg, F., van Duijn, C., Loos, R.J., Waterworth, D.M., Meigs, J.B., Dupuis, J., Richards, J.B., Voight, B.F., Scott, L.J., Steinthorsdottir, V., Dina, C., Welch, R.P., Zeggini, E., Huth, C., Aulchenko, Y.S., Thorleifsson, G., McCulloch, L.J., Ferreira, T., Grallert, H., Amin, N., Wu, G., Willer, C.J., Raychaudhuri, S., McCarroll, S.A., Hofmann, O.M., Segrè, A.V., van Hoek, M., Navarro, P., Ardlie, K., Balkau, B., Benediktsson, R., Bennett, A.J., Blagieva, R., Boerwinkle, E., Bonnycastle, L.L., Boström, K.B., Bravenboer, B., Bumpstead, S., Burtt, N.P., Charpentier, G., Chines, P.S., Cornelis, M., Crawford, G., Doney, A.S., Elliott, K.S., Elliott, A.L., Erdos, M.R., Fox, C.S., Franklin, C.S., Ganser, M., Gieger, C., Grarup, N., Green, T., Griffin, S., Groves, C.J., Guiducci, C., Hadjadj, S., Hassanali, N., Herder, C., Isomaa, B., Jackson, A.U., Johnson, P.R., Jørgensen, T., Kao, W.H., Kong, A., Kraft, P., Kuusisto, J., Lauritzen, T., Li, M., Lieverse, A., Lindgren, C.M., Lyssenko, V., Marre, M., Meitinger, T., Midthjell, K., Morken, M.A., Narisu, N., Nilsson, P., Owen, K.R., Payne, F., Petersen, A.K., Platou, C., Proença, C., Prokopenko, I., Rathmann, W., Rayner, N.W., Robertson, N.R., Rocheleau, G., Roden, M., Sampson, M.J., Saxena, R., Shields, B.M., Shrader, P., Sigurdsson, G., Sparsø, T., Strassburger, K., Stringham, H.M., Sun, Q., Swift, A.J., Thorand, B., Tichet, J., Tuomi, T., van Dam, R.M., van Haeften, T.W., van Herpt, T., van Vliet-Ostaptchouk, J.V., Walters, G.B., Weedon, M.N., Wijmenga, C., Witteman, J., Bergman, R.N., Cauchi, S., Collins, F.S., Gloyn, A.L., Gyllensten, U., Hansen, T., Hide, W.A., Hitman, G.A., Hofman, A., Hunter, D.J., Hveem, K., Laakso, M., Morris, A.D., Palmer, C.N., Rudan, I., Sijbrands, E., Stein, L.D., Tuomilehto, J., Uitterlinden, A., Walker, M., Watanabe, R.M., Abecasis, G.R., Boehm, B.O., Campbell, H., Daly, M.J., Hattersley, A.T., Pedersen, O., Barroso, I., Groop, L., Sladek, R., Thorsteinsdottir, U., Wilson, J.F., Illig, T., Froguel, P., van Duijn, C.M., Stefansson, K., Altshuler, D., Boehnke, M., McCarthy, M.I., Soranzo, N., Wheeler, E., Glazer, N.L., Bouatia-Naji, N., Mägi, R., Randall, J., 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Consortium, GLGC Investigators, MuTHER Consortium, DIAGRAM Consortium, GIANT Consortium, Global B Pgen Consortium, Procardis Consortium, MAGIC investigators, GLGC Consortium, Olson, J., Kronmal, R., Robbins, J., Chaves, PH., Burke, G., Kuller, LH., Tracy, R., Gottdiener, J., Prineas, R., Becker, JT., Enright, P., Klein, R., O'Leary, DH., Dastani, Z., Hivert, M.F., Timpson, N., Perry, J.R., Yuan, X., Scott, R.A., Henneman, P., Heid, I.M., Kizer, J.R., Lyytikäinen, L.P., Fuchsberger, C., Tanaka, T., Morris, A.P., Small, K., Isaacs, A., Beekman, M., Coassin, S., Lohman, K., Qi, L., Kanoni, S., Pankow, J.S., Uh, H.W., Wu, Y., Bidulescu, A., Rasmussen-Torvik, L.J., Greenwood, C.M., Ladouceur, M., Grimsby, J., Manning, A.K., Liu, C.T., Kooner, J., Mooser, V.E., Vollenweider, P., Kapur, K.A., Chambers, J., Wareham, N.J., Langenberg, C., Frants, R., Willems-Vandijk, K., Oostra, B.A., Willems, S.M., Lamina, C., Winkler, T.W., Psaty, B.M., Tracy, R.P., Brody, J., Chen, I., Viikari, J., Kähönen, M., Pramstaller, P.P., Evans, D.M., St Pourcain, B., Sattar, N., Wood, A.R., Bandinelli, S., Carlson, O.D., Egan, J.M., Böhringer, S., van Heemst, D., Kedenko, L., Kristiansson, K., Nuotio, M.L., Loo, B.M., Harris, T., Garcia, M., Kanaya, A., Haun, M., Klopp, N., Wichmann, H.E., Deloukas, P., Katsareli, E., Couper, D.J., Duncan, B.B., Kloppenburg, M., Adair, L.S., Borja, J.B., Wilson, J.G., Musani, S., Guo, X., Johnson, T., Semple, R., Teslovich, T.M., Allison, M.A., Redline, S., Buxbaum, S.G., Mohlke, K.L., Meulenbelt, I., Ballantyne, C.M., Dedoussis, G.V., Hu, F.B., Liu, Y., Paulweber, B., Spector, T.D., Slagboom, P.E., Ferrucci, L., Jula, A., Perola, M., Raitakari, O., Florez, J.C., Salomaa, V., Eriksson, J.G., Frayling, T.M., Hicks, A.A., Lehtimäki, T., Smith, G.D., Siscovick, D.S., Kronenberg, F., van Duijn, C., Loos, R.J., Waterworth, D.M., Meigs, J.B., Dupuis, J., Richards, J.B., Voight, B.F., Scott, L.J., Steinthorsdottir, V., Dina, C., Welch, R.P., Zeggini, E., Huth, C., Aulchenko, Y.S., Thorleifsson, G., McCulloch, L.J., Ferreira, T., Grallert, H., Amin, N., Wu, G., Willer, C.J., Raychaudhuri, S., McCarroll, S.A., Hofmann, O.M., Segrè, A.V., van Hoek, M., Navarro, P., Ardlie, K., Balkau, B., Benediktsson, R., Bennett, A.J., Blagieva, R., Boerwinkle, E., Bonnycastle, L.L., Boström, K.B., Bravenboer, B., Bumpstead, S., Burtt, N.P., Charpentier, G., Chines, P.S., Cornelis, M., Crawford, G., Doney, A.S., Elliott, K.S., Elliott, A.L., Erdos, M.R., Fox, C.S., Franklin, C.S., Ganser, M., Gieger, C., Grarup, N., Green, T., Griffin, S., Groves, C.J., Guiducci, C., Hadjadj, S., Hassanali, N., Herder, C., Isomaa, B., Jackson, A.U., Johnson, P.R., Jørgensen, T., Kao, W.H., Kong, A., Kraft, P., Kuusisto, J., Lauritzen, T., Li, M., Lieverse, A., Lindgren, C.M., Lyssenko, V., Marre, M., Meitinger, T., Midthjell, K., Morken, M.A., Narisu, N., Nilsson, P., Owen, K.R., Payne, F., Petersen, A.K., Platou, C., Proença, C., Prokopenko, I., Rathmann, W., Rayner, N.W., Robertson, N.R., Rocheleau, G., Roden, M., Sampson, M.J., Saxena, R., Shields, B.M., Shrader, P., Sigurdsson, G., Sparsø, T., Strassburger, K., Stringham, H.M., Sun, Q., Swift, A.J., Thorand, B., Tichet, J., Tuomi, T., van Dam, R.M., van Haeften, T.W., van Herpt, T., van Vliet-Ostaptchouk, J.V., Walters, G.B., Weedon, M.N., Wijmenga, C., Witteman, J., Bergman, R.N., Cauchi, S., Collins, F.S., Gloyn, A.L., Gyllensten, U., Hansen, T., Hide, W.A., Hitman, G.A., Hofman, A., Hunter, D.J., Hveem, K., Laakso, M., Morris, A.D., Palmer, C.N., Rudan, I., Sijbrands, E., Stein, L.D., Tuomilehto, J., Uitterlinden, A., Walker, M., Watanabe, R.M., Abecasis, G.R., Boehm, B.O., Campbell, H., Daly, M.J., Hattersley, A.T., Pedersen, O., Barroso, I., Groop, L., Sladek, R., Thorsteinsdottir, U., Wilson, J.F., Illig, T., Froguel, P., van Duijn, C.M., Stefansson, K., Altshuler, D., Boehnke, M., McCarthy, M.I., Soranzo, N., Wheeler, E., Glazer, N.L., Bouatia-Naji, N., Mägi, R., Randall, J., Elliott, P., Rybin, D., Dehghan, A., Hottenga, J.J., Song, K., Goel, A., Lajunen, T., Doney, A., Cavalcanti-Proença, C., Kumari, M., Timpson, N.J., Zabena, C., Ingelsson, E., An, P., O'Connell, J., Luan, J., Elliott, A., Roccasecca, R.M., Pattou, F., Sethupathy, P., Ariyurek, Y., Barter, P., Beilby, J.P., Ben-Shlomo, Y., Bergmann, S., Bochud, M., Bonnefond, A., Borch-Johnsen, K., Böttcher, Y., Brunner, E., Bumpstead, S.J., Chen, Y.D., Chines, P., Clarke, R., Coin, L.J., Cooper, M.N., Crisponi, L., Day, I.N., de Geus, E.J., Delplanque, J., Fedson, A.C., Fischer-Rosinsky, A., Forouhi, N.G., Franzosi, M.G., Galan, P., Goodarzi, M.O., Graessler, J., Grundy, S., Gwilliam, R., Hallmans, G., Hammond, N., Han, X., Hartikainen, A.L., Hayward, C., Heath, S.C., Hercberg, S., Hillman, D.R., Hingorani, A.D., Hui, J., Hung, J., Kaakinen, M., Kaprio, J., Kesaniemi, Y.A., Kivimaki, M., Knight, B., Koskinen, S., Kovacs, P., Kyvik, K.O., Lathrop, G.M., Lawlor, D.A., Le Bacquer, O., Lecoeur, C., Li, Y., Mahley, R., Mangino, M., Martínez-Larrad, M.T., McAteer, J.B., McPherson, R., Meisinger, C., Melzer, D., Meyre, D., Mitchell, B.D., Mukherjee, S., Naitza, S., Neville, M.J., Orrù, M., Pakyz, R., Paolisso, G., Pattaro, C., Pearson, D., Peden, J.F., Pedersen, N.L., Pfeiffer, A.F., Pichler, I., Polasek, O., Posthuma, D., Potter, S.C., Pouta, A., Province, M.A., Rice, K., Ripatti, S., Rivadeneira, F., Rolandsson, O., Sandbaek, A., Sandhu, M., Sanna, S., Sayer, A.A., Scheet, P., Seedorf, U., Sharp, S.J., Shields, B., Sigurðsson, G., Sijbrands, E.J., Silveira, A., Simpson, L., Singleton, A., Smith, N.L., Sovio, U., Swift, A., Syddall, H., Syvänen, A.C., Tönjes, A., Uitterlinden, A.G., van Dijk, K.W., Varma, D., Visvikis-Siest, S., Vitart, V., Vogelzangs, N., Waeber, G., Wagner, P.J., Walley, A., Ward, K.L., Watkins, H., Wild, S.H., Willemsen, G., Witteman, J.C., Yarnell, J.W., Zelenika, D., Zethelius, B., Zhai, G., Zhao, J.H., Zillikens, M.C., Borecki, I.B., Meneton, P., Magnusson, P.K., Nathan, D.M., Williams, G.H., Silander, K., Bornstein, S.R., Schwarz, P., Spranger, J., Karpe, F., Shuldiner, A.R., Cooper, C., Serrano-Ríos, M., Lind, L., Palmer, L.J., Franks, P.W., Ebrahim, S., Marmot, M., Wright, A.F., Stumvoll, M., Hamsten, A., Buchanan, T.A., Valle, T.T., Rotter, J.I., Penninx, B.W., Boomsma, D.I., Cao, A., Scuteri, A., Schlessinger, D., Uda, M., Ruokonen, A., Jarvelin, M.R., Peltonen, L., Mooser, V., Musunuru, K., Smith, A.V., Edmondson, A.C., Stylianou, I.M., Koseki, M., Pirruccello, J.P., Chasman, D.I., Johansen, C.T., Fouchier, S.W., Peloso, G.M., Barbalic, M., Ricketts, S.L., Bis, J.C., Feitosa, M.F., Orho-Melander, M., Melander, O., Li, X., Cho, Y.S., Go, M.J., Kim, Y.J., Lee, J.Y., Park, T., Kim, K., Sim, X., Ong, R.T., Croteau-Chonka, D.C., Lange, L.A., Smith, J.D., Ziegler, A., Zhang, W., Zee, R.Y., Whitfield, J.B., Thompson, J.R., Surakka, I., Smit, J.H., Sinisalo, J., Scott, J., Saharinen, J., Sabatti, C., Rose, L.M., Roberts, R., Rieder, M., Parker, A.N., Pare, G., O'Donnell, C.J., Nieminen, M.S., Nickerson, D.A., Montgomery, G.W., McArdle, W., Masson, D., Martin, N.G., Marroni, F., Lucas, G., Luben, R., Lokki, M.L., Lettre, G., Launer, L.J., Lakatta, E.G., Laaksonen, R., König, I.R., Khaw, K.T., Kaplan, L.M., Johansson, Å., Janssens, A.C., Igl, W., Hovingh, G.K., Hengstenberg, C., Havulinna, A.S., Hastie, N.D., Harris, T.B., Haritunians, T., Hall, A.S., Groop, L.C., Gonzalez, E., Freimer, N.B., Erdmann, J., Ejebe, K.G., Döring, A., Dominiczak, A.F., Demissie, S., de Faire, U., Caulfield, M.J., Boekholdt, S.M., Assimes, T.L., Quertermous, T., Seielstad, M., Wong, T.Y., Tai, E.S., Feranil, A.B., Kuzawa, C.W., Taylor, H.A., Gabriel, S.B., Holm, H., Gudnason, V., Krauss, R.M., Ordovas, J.M., Munroe, P.B., Kooner, J.S., Tall, A.R., Hegele, R.A., Kastelein, J.J., Schadt, E.E., Strachan, D.P., Reilly, M.P., Samani, N.J., Schunkert, H., Cupples, L.A., Sandhu, M.S., Ridker, P.M., Rader, D.J., and Kathiresan, S.

Abstract

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Published
2012

16. Genome-wide analysis shows increased frequency of copy number variation deletions in dutch schizophrenia patients

Author

Buizer-Voskamp, J.E., Muntjewerff, J.W., Strengman, E., Sabatti, C., Stefansson, H., Vorstman, J.A., Ophoff, R.A., Buizer-Voskamp, J.E., Muntjewerff, J.W., Strengman, E., Sabatti, C., Stefansson, H., Vorstman, J.A., and Ophoff, R.A.

Abstract

Item does not contain fulltext, BACKGROUND: Since 2008, multiple studies have reported on copy number variations (CNVs) in schizophrenia. However, many regions are unique events with minimal overlap between studies. This makes it difficult to gain a comprehensive overview of all CNVs involved in the etiology of schizophrenia. We performed a systematic CNV study on the basis of a homogeneous genome-wide dataset aiming at all CNVs >/= 50 kilobase pair. We complemented this analysis with a review of cytogenetic and chromosomal abnormalities for schizophrenia reported in the literature with the purpose of combining classical genetic findings and our current understanding of genomic variation. METHODS: We investigated 834 Dutch schizophrenia patients and 672 Dutch control subjects. The CNVs were included if they were detected by QuantiSNP (http://www.well.ox.ac.uk/QuantiSNP/) as well as PennCNV (http://www.neurogenome.org/cnv/penncnv/) and contain known protein coding genes. The integrated identification of CNV regions and cytogenetic loci indicates regions of interest (cytogenetic regions of interest [CROIs]). RESULTS: In total, 2437 CNVs were identified with an average number of 2.1 CNVs/subject for both cases and control subjects. We observed significantly more deletions but not duplications in schizophrenia cases versus control subjects. The CNVs identified coincide with loci previously reported in the literature, confirming well-established schizophrenia CROIs 1q42 and 22q11.2 as well as indicating a potentially novel CROI on chromosome 5q35.1. CONCLUSIONS: Chromosomal deletions are more prevalent in schizophrenia patients than in healthy subjects and therefore confer a risk factor for pathogenicity. The combination of our CNV data with previously reported cytogenetic abnormalities in schizophrenia provides an overview of potentially interesting regions for positional candidate genes.

Published
2011

17. Biological, clinical and population relevance of 95 loci for blood lipids

Author

Teslovich, T.M. (Tanya), Musunuru, K. (Kiran), Smith, A.V. (Albert Vernon), Edmondson, A.C. (Andrew), Stylianou, I.M. (Ioannis), Koseki, M. (Masahiro), Pirruccello, J.P. (James), Ripatti, S. (Samuli), Chasman, D.I. (Daniel), Willer, C.J. (Cristen), Johansen, C.T. (Christopher), Fouchier, S.W. (Sigrid), Isaacs, A.J. (Aaron), Peloso, G.M. (Gina), Barbalic, M. (maja), Ricketts, S.L. (Sally), Bis, J.C. (Joshua), Aulchenko, Y.S. (Yurii), Thorleifsson, G. (Gudmar), Feitosa, M.F. (Mary Furlan), Chambers, J. (John), Orho-Melander, M. (Marju), Melander, O. (Olle), Johnson, T. (Toby), Li, X. (Xiaohui), Guo, X. (Xiuqing), Shin Cho, Y. (Yoon), Jin Go, M. (Min), Jin Kim, Y. (Young), Lee, J.Y. (Jong Young), Park, T. (Taesung), Kim, Y-J. (Yong-Jin), Sim, X. (Xueling), Twee-Hee Ong, R. (Rick), Croteau-Chonka, D.C. (Damien), Lange, L.A. (Leslie), Song, K. (Kijoung), Zhao, J.H. (Jing Hua), Yuan, X. (Xin), Luan, J., Lamina, C. (Claudia), Ziegler, A. (Andreas), Zhang, W. (Weibo), Zee, R.Y.L. (Robert), Wright, A.F. (Alan), Witteman, J.C.M. (Jacqueline), Wilson, J.F. (James), Willemsen, G.A.H.M. (Gonneke), Wichmann, H.E. (Heinz Erich), Whitfield, J. (John), Waterworth, D. (Dawn), Wareham, N.J. (Nick), Waeber, G. (Gérard), Vollenweider, P. (Peter), Voight, B.F. (Benjamin), Vitart, V. (Veronique), Uitterlinden, A.G. (André), Uda, M. (Manuela), Tuomilehto, J. (Jaakko), Thompson, J.R. (John), Tanaka, T. (Toshiko), Surakka, I. (Ida), Stringham, H.M. (Heather), Spector, T.D. (Timothy), Soranzo, N. (Nicole), Smit, J.H. (Johannes), Sinisalo, J. (Juha), Silander, K. (Kaisa), Sijbrands, E.J.G. (Eric), Scuteri, A. (Angelo), Scott, J. (James), Schlessinger, D. (David), Sanna, S. (Serena), Salomaa, V. (Veikko), Saharinen, J. (Juha), Sabatti, C. (Chiara), Ruokonen, A. (Aimo), Rudan, I. (Igor), Rose, L.M. (Lynda), Roberts, R. (Robert), Rieder, M. (Mark), Psaty, B.M. (Bruce), Pramstaller, P.P. (Peter Paul), Pichler, I. (Irene), Perola, M. (Markus), Penninx, B.W.J.H. (Brenda), Pedersen, N.L. (Nancy), Pattaro, C. (Cristian), Parker, A.N. (Alex), Pare, G. (Guillaume), Oostra, B.A. (Ben), Nieminen, M.S. (Markku), Nickerson, D.A. (Deborah), Montgomery, G.W. (Grant), Meitinger, T. (Thomas), McPherson, R. (Ruth), McCarthy, M.I. (Mark), McArdle, W.L. (Wendy), Masson, D. (David), Martin, N.G. (Nicholas), Marroni, F. (Fabio), Mangino, M. (Massimo), Magnusson, P.K. (Patrik), Lucas, G. (Gavin), Luben, R.N. (Robert), Loos, R.J.F. (Ruth), Lokki, M.L., Lettre, G. (Guillaume), Langenberg, C. (Claudia), Launer, L.J. (Lenore), Lakatta, E. (Edward), Laaksonen, R. (Reijo), Kyvik, K.O. (Kirsten Ohm), Kronenberg, F. (Florian), König, I.R. (Inke), Khaw, K-T. (Kay-Tee), Kaprio, J. (Jaakko), Kaplan, R.C. (Robert), Johansson, A. (Åsa), Jarvelin, M.-R. (Marjo-Riitta), Cecile, A. (A.), Ingelsson, E. (Erik), Igl, W. (Wilmar), Hovingh, G.K. (Kees), Hottenga, J.J. (Jouke Jan), Hofman, A. (Albert), Hicks, A.A. (Andrew), Hengstenberg, C. (Christian), Heid, I.M. (Iris), Hayward, C. (Caroline), Havulinna, A.S. (Aki), Hastie, N. (Nick), Harris, T.B. (Tamara), Haritunians, T. (Talin), Hall, A.S. (Alistair), Gyllensten, U. (Ulf), Guiducci, C. (Candace), Groop, L. (Leif), Gonzalez, E. (Elena), Gieger, C. (Christian), Freimer, N.B. (Nelson), Ferrucci, L. (Luigi), Erdmann, J. (Jeanette), Elliott, P. (Paul), Ejebe, K.G. (Kenechi), Döring, A. (Angela), Dominiczak, A. (Anna), Demissie, S. (Serkalem), Deloukas, P. (Panagiotis), Geus, E.J.C. (Eco) de, Faire, U. (Ulf) de, Crawford, G. (Gabe), Collins, F.S. (Francis), Chen, C. (Chao), Caulfield, M. (Mark), Campbell, H. (Harry), Burtt, N.P. (Noël), Bonnycastle, L.L. (Lori), Boomsma, D.I. (Dorret), Boekholdt, S.M. (Matthijs), Bergman, R.N. (Richard), Barroso, I.E. (Inês), Bandinelli, S. (Stefania), Ballantyne, C. (Christie), Assimes, T.L. (Themistocles), Quertermous, T. (Thomas), Altshuler, D. (David), Seielstad, M. (Mark), Wong, T.Y. (Tien Yin), Tai, E.S. (Shyong), Feranil, A.B. (Alan), Kuzawa, C.W. (Christopher), Adair, L.S. (Linda), Taylor, H.A. (Herman), Borecki, I.B. (Ingrid), Gabriel, S.B. (Stacey), Holm, H. (Hilma), Thorsteinsdottir, U. (Unnur), Gudnason, V. (Vilmundur), Krauss, R.M. (Ronald), Mohlke, K.L. (Karen), Ordovas, J.M. (Jose), Munroe, P. (Patricia), Kooner, J.S. (Jaspal), Tall, A.R. (Alan), Hegele, R.A. (Robert), Kastelein, J.J.P. (John), Schadt, E.E. (Eric), Rotter, J.I. (Jerome), Boerwinkle, E.A. (Eric), Strachan, D.P. (David), Mooser, V. (Vincent), Zwart, J-A. (John-Anker), Reilly, M.P. (Muredach), Samani, N.J. (Nilesh), Schunkert, H. (Heribert), Cupples, L.A. (Adrienne), Sandhu, M.S. (Manjinder), Ridker, P.M. (Paul), Rader, D.J. (Daniel), Tikka-Kleemola, P. (Päivi), Peltonen, L. (Leena Johanna), Abecasis, G.R. (Gonçalo), Boehnke, M. (Michael), Kathiresan, S. (Sekar), O'Donnell, C.J. (Christopher), Teslovich, T.M. (Tanya), Musunuru, K. (Kiran), Smith, A.V. (Albert Vernon), Edmondson, A.C. (Andrew), Stylianou, I.M. (Ioannis), Koseki, M. (Masahiro), Pirruccello, J.P. (James), Ripatti, S. (Samuli), Chasman, D.I. (Daniel), Willer, C.J. (Cristen), Johansen, C.T. (Christopher), Fouchier, S.W. (Sigrid), Isaacs, A.J. (Aaron), Peloso, G.M. (Gina), Barbalic, M. (maja), Ricketts, S.L. (Sally), Bis, J.C. (Joshua), Aulchenko, Y.S. (Yurii), Thorleifsson, G. (Gudmar), Feitosa, M.F. (Mary Furlan), Chambers, J. (John), Orho-Melander, M. (Marju), Melander, O. (Olle), Johnson, T. (Toby), Li, X. (Xiaohui), Guo, X. (Xiuqing), Shin Cho, Y. (Yoon), Jin Go, M. (Min), Jin Kim, Y. (Young), Lee, J.Y. (Jong Young), Park, T. (Taesung), Kim, Y-J. (Yong-Jin), Sim, X. (Xueling), Twee-Hee Ong, R. (Rick), Croteau-Chonka, D.C. (Damien), Lange, L.A. (Leslie), Song, K. (Kijoung), Zhao, J.H. (Jing Hua), Yuan, X. (Xin), Luan, J., Lamina, C. (Claudia), Ziegler, A. (Andreas), Zhang, W. (Weibo), Zee, R.Y.L. (Robert), Wright, A.F. (Alan), Witteman, J.C.M. (Jacqueline), Wilson, J.F. (James), Willemsen, G.A.H.M. (Gonneke), Wichmann, H.E. (Heinz Erich), Whitfield, J. (John), Waterworth, D. (Dawn), Wareham, N.J. (Nick), Waeber, G. (Gérard), Vollenweider, P. (Peter), Voight, B.F. (Benjamin), Vitart, V. (Veronique), Uitterlinden, A.G. (André), Uda, M. (Manuela), Tuomilehto, J. (Jaakko), Thompson, J.R. (John), Tanaka, T. (Toshiko), Surakka, I. (Ida), Stringham, H.M. (Heather), Spector, T.D. (Timothy), Soranzo, N. (Nicole), Smit, J.H. (Johannes), Sinisalo, J. (Juha), Silander, K. (Kaisa), Sijbrands, E.J.G. (Eric), Scuteri, A. (Angelo), Scott, J. (James), Schlessinger, D. (David), Sanna, S. (Serena), Salomaa, V. (Veikko), Saharinen, J. (Juha), Sabatti, C. (Chiara), Ruokonen, A. (Aimo), Rudan, I. (Igor), Rose, L.M. (Lynda), Roberts, R. (Robert), Rieder, M. (Mark), Psaty, B.M. (Bruce), Pramstaller, P.P. (Peter Paul), Pichler, I. (Irene), Perola, M. (Markus), Penninx, B.W.J.H. (Brenda), Pedersen, N.L. (Nancy), Pattaro, C. (Cristian), Parker, A.N. (Alex), Pare, G. (Guillaume), Oostra, B.A. (Ben), Nieminen, M.S. (Markku), Nickerson, D.A. (Deborah), Montgomery, G.W. (Grant), Meitinger, T. (Thomas), McPherson, R. (Ruth), McCarthy, M.I. (Mark), McArdle, W.L. (Wendy), Masson, D. (David), Martin, N.G. (Nicholas), Marroni, F. (Fabio), Mangino, M. (Massimo), Magnusson, P.K. (Patrik), Lucas, G. (Gavin), Luben, R.N. (Robert), Loos, R.J.F. (Ruth), Lokki, M.L., Lettre, G. (Guillaume), Langenberg, C. (Claudia), Launer, L.J. (Lenore), Lakatta, E. (Edward), Laaksonen, R. (Reijo), Kyvik, K.O. (Kirsten Ohm), Kronenberg, F. (Florian), König, I.R. (Inke), Khaw, K-T. (Kay-Tee), Kaprio, J. (Jaakko), Kaplan, R.C. (Robert), Johansson, A. (Åsa), Jarvelin, M.-R. (Marjo-Riitta), Cecile, A. (A.), Ingelsson, E. (Erik), Igl, W. (Wilmar), Hovingh, G.K. (Kees), Hottenga, J.J. (Jouke Jan), Hofman, A. (Albert), Hicks, A.A. (Andrew), Hengstenberg, C. (Christian), Heid, I.M. (Iris), Hayward, C. (Caroline), Havulinna, A.S. (Aki), Hastie, N. (Nick), Harris, T.B. (Tamara), Haritunians, T. (Talin), Hall, A.S. (Alistair), Gyllensten, U. (Ulf), Guiducci, C. (Candace), Groop, L. (Leif), Gonzalez, E. (Elena), Gieger, C. (Christian), Freimer, N.B. (Nelson), Ferrucci, L. (Luigi), Erdmann, J. (Jeanette), Elliott, P. (Paul), Ejebe, K.G. (Kenechi), Döring, A. (Angela), Dominiczak, A. (Anna), Demissie, S. (Serkalem), Deloukas, P. (Panagiotis), Geus, E.J.C. (Eco) de, Faire, U. (Ulf) de, Crawford, G. (Gabe), Collins, F.S. (Francis), Chen, C. (Chao), Caulfield, M. (Mark), Campbell, H. (Harry), Burtt, N.P. (Noël), Bonnycastle, L.L. (Lori), Boomsma, D.I. (Dorret), Boekholdt, S.M. (Matthijs), Bergman, R.N. (Richard), Barroso, I.E. (Inês), Bandinelli, S. (Stefania), Ballantyne, C. (Christie), Assimes, T.L. (Themistocles), Quertermous, T. (Thomas), Altshuler, D. (David), Seielstad, M. (Mark), Wong, T.Y. (Tien Yin), Tai, E.S. (Shyong), Feranil, A.B. (Alan), Kuzawa, C.W. (Christopher), Adair, L.S. (Linda), Taylor, H.A. (Herman), Borecki, I.B. (Ingrid), Gabriel, S.B. (Stacey), Holm, H. (Hilma), Thorsteinsdottir, U. (Unnur), Gudnason, V. (Vilmundur), Krauss, R.M. (Ronald), Mohlke, K.L. (Karen), Ordovas, J.M. (Jose), Munroe, P. (Patricia), Kooner, J.S. (Jaspal), Tall, A.R. (Alan), Hegele, R.A. (Robert), Kastelein, J.J.P. (John), Schadt, E.E. (Eric), Rotter, J.I. (Jerome), Boerwinkle, E.A. (Eric), Strachan, D.P. (David), Mooser, V. (Vincent), Zwart, J-A. (John-Anker), Reilly, M.P. (Muredach), Samani, N.J. (Nilesh), Schunkert, H. (Heribert), Cupples, L.A. (Adrienne), Sandhu, M.S. (Manjinder), Ridker, P.M. (Paul), Rader, D.J. (Daniel), Tikka-Kleemola, P. (Päivi), Peltonen, L. (Leena Johanna), Abecasis, G.R. (Gonçalo), Boehnke, M. (Michael), Kathiresan, S. (Sekar), and O'Donnell, C.J. (Christopher)

Abstract

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P<-10-8), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Published
2010
Full Text
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18. Biological, clinical and population relevance of 95 loci for blood lipids

Author

Teslovich, TM, Musunuru, K, Smith, AV, Edmondson, AC, Stylianou, IM, Koseki, M, Pirruccello, JP, Ripatti, S, Chasman, DI, Willer, CJ, Johansen, CT, Fouchier, SW, Isaacs, A, Peloso, GM, Barbalic, M, Ricketts, SL, Bis, JC, Aulchenko, YS, Thorleifsson, G, Feitosa, MF, Chambers, J, Orho-Melander, M, Melander, O, Johnson, T, Li, X, Guo, X, Li, M, Cho, YS, Go, MJ, Kim, YJ, Lee, J-Y, Park, T, Kim, K, Sim, X, Ong, RT-H, Croteau-Chonka, DC, Lange, LA, Smith, JD, Song, K, Zhao, JH, Yuan, X, Luan, J, Lamina, C, Ziegler, A, Zhang, W, Zee, RYL, Wright, AF, Witteman, JCM, Wilson, JF, Willemsen, G, Wichmann, H-E, Whitfield, JB, Waterworth, DM, Wareham, NJ, Waeber, G, Vollenweider, P, Voight, BF, Vitart, V, Uitterlinden, AG, Uda, M, Tuomilehto, J, Thompson, JR, Tanaka, T, Surakka, I, Stringham, HM, Spector, TD, Soranzo, N, Smit, JH, Sinisalo, J, Silander, K, Sijbrands, EJG, Scuteri, A, Scott, J, Schlessinger, D, Sanna, S, Salomaa, V, Saharinen, J, Sabatti, C, Ruokonen, A, Rudan, I, Rose, LM, Roberts, R, Rieder, M, Psaty, BM, Pramstaller, PP, Pichler, I, Perola, M, Penninx, BWJH, Pedersen, NL, Pattaro, C, Parker, AN, Pare, G, Oostra, BA, O'Donnell, CJ, Nieminen, MS, Nickerson, DA, Montgomery, GW, Meitinger, T, McPherson, R, McCarthy, MI, McArdle, W, Masson, D, Martin, NG, Marroni, F, Mangino, M, Magnusson, PKE, Lucas, G, Luben, R, Loos, RJF, Lokki, M-L, Lettre, G, Langenberg, C, Launer, LJ, Lakatta, EG, Laaksonen, R, Kyvik, KO, Kronenberg, F, Koenig, IR, Khaw, K-T, Kaprio, J, Kaplan, LM, Johansson, A, Jarvelin, M-R, Janssens, ACJW, Ingelsson, E, Igi, W, Hovingh, GK, Hottenga, J-J, Hofman, A, Hicks, AA, Hengstenberg, C, Heid, IM, Hayward, C, Havulinna, AS, Hastie, ND, Harris, TB, Haritunians, T, Hall, AS, Gyllensten, U, Guiducci, C, Groop, LC, Gonzalez, E, Gieger, C, Freimer, NB, Ferrucci, L, Erdmann, J, Elliott, P, Ejebe, KG, Doering, A, Dominiczak, AF, Demissie, S, Deloukas, P, de Geus, EJC, de Faire, U, Crawford, G, Collins, FS, Chen, Y-DI, Caulfield, MJ, Campbell, H, Burtt, NP, Bonnycastle, LL, Boomsma, DI, Boekholdt, SM, Bergman, RN, Barroso, I, Bandinelli, S, Ballantyne, CM, Assimes, TL, Quertermous, T, Altshuler, D, Seielstad, M, Wong, TY, Tai, E-S, Feranil, AB, Kuzawa, CW, Adair, LS, Taylor, HA, Borecki, IB, Gabriel, SB, Wilson, JG, Holm, H, Thorsteinsdottir, U, Gudnason, V, Krauss, RM, Mohlke, KL, Ordovas, JM, Munroe, PB, Kooner, JS, Tall, AR, Hegele, RA, Kastelein, JJP, Schadt, EE, Rotter, JI, Boerwinkle, E, Strachan, DP, Mooser, V, Stefansson, K, Reilly, MP, Samani, NJ, Schunkert, H, Cupples, LA, Sandhu, MS, Ridker, PM, Rader, DJ, van Duijn, CM, Peltonen, L, Abecasis, GR, Boehnke, M, Kathiresan, S, Teslovich, TM, Musunuru, K, Smith, AV, Edmondson, AC, Stylianou, IM, Koseki, M, Pirruccello, JP, Ripatti, S, Chasman, DI, Willer, CJ, Johansen, CT, Fouchier, SW, Isaacs, A, Peloso, GM, Barbalic, M, Ricketts, SL, Bis, JC, Aulchenko, YS, Thorleifsson, G, Feitosa, MF, Chambers, J, Orho-Melander, M, Melander, O, Johnson, T, Li, X, Guo, X, Li, M, Cho, YS, Go, MJ, Kim, YJ, Lee, J-Y, Park, T, Kim, K, Sim, X, Ong, RT-H, Croteau-Chonka, DC, Lange, LA, Smith, JD, Song, K, Zhao, JH, Yuan, X, Luan, J, Lamina, C, Ziegler, A, Zhang, W, Zee, RYL, Wright, AF, Witteman, JCM, Wilson, JF, Willemsen, G, Wichmann, H-E, Whitfield, JB, Waterworth, DM, Wareham, NJ, Waeber, G, Vollenweider, P, Voight, BF, Vitart, V, Uitterlinden, AG, Uda, M, Tuomilehto, J, Thompson, JR, Tanaka, T, Surakka, I, Stringham, HM, Spector, TD, Soranzo, N, Smit, JH, Sinisalo, J, Silander, K, Sijbrands, EJG, Scuteri, A, Scott, J, Schlessinger, D, Sanna, S, Salomaa, V, Saharinen, J, Sabatti, C, Ruokonen, A, Rudan, I, Rose, LM, Roberts, R, Rieder, M, Psaty, BM, Pramstaller, PP, Pichler, I, Perola, M, Penninx, BWJH, Pedersen, NL, Pattaro, C, Parker, AN, Pare, G, Oostra, BA, O'Donnell, CJ, Nieminen, MS, Nickerson, DA, Montgomery, GW, Meitinger, T, McPherson, R, McCarthy, MI, McArdle, W, Masson, D, Martin, NG, Marroni, F, Mangino, M, Magnusson, PKE, Lucas, G, Luben, R, Loos, RJF, Lokki, M-L, Lettre, G, Langenberg, C, Launer, LJ, Lakatta, EG, Laaksonen, R, Kyvik, KO, Kronenberg, F, Koenig, IR, Khaw, K-T, Kaprio, J, Kaplan, LM, Johansson, A, Jarvelin, M-R, Janssens, ACJW, Ingelsson, E, Igi, W, Hovingh, GK, Hottenga, J-J, Hofman, A, Hicks, AA, Hengstenberg, C, Heid, IM, Hayward, C, Havulinna, AS, Hastie, ND, Harris, TB, Haritunians, T, Hall, AS, Gyllensten, U, Guiducci, C, Groop, LC, Gonzalez, E, Gieger, C, Freimer, NB, Ferrucci, L, Erdmann, J, Elliott, P, Ejebe, KG, Doering, A, Dominiczak, AF, Demissie, S, Deloukas, P, de Geus, EJC, de Faire, U, Crawford, G, Collins, FS, Chen, Y-DI, Caulfield, MJ, Campbell, H, Burtt, NP, Bonnycastle, LL, Boomsma, DI, Boekholdt, SM, Bergman, RN, Barroso, I, Bandinelli, S, Ballantyne, CM, Assimes, TL, Quertermous, T, Altshuler, D, Seielstad, M, Wong, TY, Tai, E-S, Feranil, AB, Kuzawa, CW, Adair, LS, Taylor, HA, Borecki, IB, Gabriel, SB, Wilson, JG, Holm, H, Thorsteinsdottir, U, Gudnason, V, Krauss, RM, Mohlke, KL, Ordovas, JM, Munroe, PB, Kooner, JS, Tall, AR, Hegele, RA, Kastelein, JJP, Schadt, EE, Rotter, JI, Boerwinkle, E, Strachan, DP, Mooser, V, Stefansson, K, Reilly, MP, Samani, NJ, Schunkert, H, Cupples, LA, Sandhu, MS, Ridker, PM, Rader, DJ, van Duijn, CM, Peltonen, L, Abecasis, GR, Boehnke, M, and Kathiresan, S

Abstract

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Published
2010

19. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts

Author

Aulchenko, Y.S. (Yurii), Ripatti, S. (Samuli), Lindqvist, I. (Ida), Boomsma, D.I. (Dorret), Heid, I.M. (Iris), Pramstaller, P.P. (Peter Paul), Penninx, B.W.J.H. (Brenda), Janssens, A.C.J.W. (Cécile), Wilson, J.F. (James), Spector, T.D. (Timothy), Martin, N.G. (Nicholas), Pedersen, N.L. (Nancy), Kyvik, K.O. (Kirsten Ohm), Kaprio, J. (Jaakko), Hofman, A. (Albert), Freimer, N.B. (Nelson), Jarvelin, M.-R. (Marjo-Riitta), Gyllensten, U. (Ulf), Campbell, H. (Harry), Rudan, I. (Igor), Johansson, A. (Åsa), Marroni, F. (Fabio), Hayward, C. (Caroline), Vitart, V. (Veronique), Jonasson, I. (Inger), Pattaro, C. (Cristian), Wright, A. (Alan), Hastie, N. (Nick), Pichler, I. (Irene), Hicks, A.A. (Andrew), Falchi, M. (Mario), Willemsen, G.A.H.M. (Gonneke), Hottenga, J.J. (Jouke Jan), Geus, E.J.C. (Eco) de, Montgomery, G.W. (Grant), Whitfield, J. (John), Magnusson, P. (Patrik), Saharinen, J. (Juha), Perola, M. (Markus), Silander, K. (Kaisa), Isaacs, A.J. (Aaron), Sijbrands, E.J.G. (Eric), Uitterlinden, A.G. (André), Witteman, J.C.M. (Jacqueline), Oostra, B.A. (Ben), Elliott, P. (Paul), Ruokonen, A. (Aimo), Sabatti, C. (Chiara), Gieger, C. (Christian), Meitinger, T. (Thomas), Kronenberg, F. (Florian), Döring, A. (Angela), Wichmann, H.E. (Erich), Smit, J.H. (Johannes), McCarthy, M.I. (Mark), Tikka-Kleemola, P. (Päivi), Peltonen, L. (Leena Johanna), Aulchenko, Y.S. (Yurii), Ripatti, S. (Samuli), Lindqvist, I. (Ida), Boomsma, D.I. (Dorret), Heid, I.M. (Iris), Pramstaller, P.P. (Peter Paul), Penninx, B.W.J.H. (Brenda), Janssens, A.C.J.W. (Cécile), Wilson, J.F. (James), Spector, T.D. (Timothy), Martin, N.G. (Nicholas), Pedersen, N.L. (Nancy), Kyvik, K.O. (Kirsten Ohm), Kaprio, J. (Jaakko), Hofman, A. (Albert), Freimer, N.B. (Nelson), Jarvelin, M.-R. (Marjo-Riitta), Gyllensten, U. (Ulf), Campbell, H. (Harry), Rudan, I. (Igor), Johansson, A. (Åsa), Marroni, F. (Fabio), Hayward, C. (Caroline), Vitart, V. (Veronique), Jonasson, I. (Inger), Pattaro, C. (Cristian), Wright, A. (Alan), Hastie, N. (Nick), Pichler, I. (Irene), Hicks, A.A. (Andrew), Falchi, M. (Mario), Willemsen, G.A.H.M. (Gonneke), Hottenga, J.J. (Jouke Jan), Geus, E.J.C. (Eco) de, Montgomery, G.W. (Grant), Whitfield, J. (John), Magnusson, P. (Patrik), Saharinen, J. (Juha), Perola, M. (Markus), Silander, K. (Kaisa), Isaacs, A.J. (Aaron), Sijbrands, E.J.G. (Eric), Uitterlinden, A.G. (André), Witteman, J.C.M. (Jacqueline), Oostra, B.A. (Ben), Elliott, P. (Paul), Ruokonen, A. (Aimo), Sabatti, C. (Chiara), Gieger, C. (Christian), Meitinger, T. (Thomas), Kronenberg, F. (Florian), Döring, A. (Angela), Wichmann, H.E. (Erich), Smit, J.H. (Johannes), McCarthy, M.I. (Mark), Tikka-Kleemola, P. (Päivi), and Peltonen, L. (Leena Johanna)

Abstract

Recent genome-wide association (GWA) studies of lipids have been conducted in samples ascertained for other phenotypes, particularly diabetes. Here we report the first GWA analysis of loci affecting total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglycerides sampled randomly from 16 population-based cohorts and genotyped using mainly the Illumina HumanHap300-Duo platform. Our study included a total of 17,797-22,562 persons, aged 18-104 years and from geographic regions spanning from the Nordic countries to Southern Europe. We established 22 loci associated with serum lipid levels at a genome-wide significance level (P < 5 × 10-8), including 16 loci that were identified by previous GWA studies. The six newly identified loci in our cohort samples are ABCG5 (TC, P = 1.5 × 10-11; LDL, P = 2.6 × 10-10), TMEM57 (TC, P = 5.4 × 10-10), CTCF-PRMT8 region (HDL, P = 8.3 × 10-16), DNAH11 (LDL, P = 6.1 × 10-9), FADS3-FADS2 (TC, P = 1.5 × 10-10; LDL, P = 4.4 × 10-13) and MADD-FOLH1 region (HDL, P = 6 × 10-11). For three loci, effect sizes differed significantly by sex. Genetic risk scores based on lipid loci explain up to 4.8% of variation in lipids and were also associated with increased intima media thickness (P = 0.001) and coronary heart disease incidence (P = 0.04). The genetic risk score improves the screening of high-risk groups of dyslipidemia over classical risk factors.

Published
2009
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20. Disruption of the neurexin 1 gene is associated with schizophrenia.

Author

Rujescu, D., Ingason, A., Cichon, S., Pietilainen, O.P.H., Barnes, M.R., Toulopoulou, T., Picchioni, M., Vassos, E., Ettinger, U., Bramon, E., Murray, R., Ruggeri, M., Tosato, S., Bonetto, C., Steinberg, S., Sigurdsson, E., Sigmundsson, T., Petursson, H., Gylfason, A, Olason, P., Hardarsson, G., Jonsdottir, G.A., Gustafsson, O., Fossdal, R., Giegling, I., Moller, H.J., Hartmann, A.M., Hoffmann, P., Crombie, C., Fraser, G., Walker, N., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Djurovic, S., Melle, I., Andreassen, O.A., Hansen, T., Werge, T., Kiemeney, L.A.L.M., Franke, B., Veltman, J.A., Buizer-Voskamp, J.E., Sabatti, C., Ophoff, R.A., Rietschel, M., Nothen, Markus, Stefansson, K., Peltonen, L., St Clair, D., Stefansson, H., Collier, D.A., Rujescu, D., Ingason, A., Cichon, S., Pietilainen, O.P.H., Barnes, M.R., Toulopoulou, T., Picchioni, M., Vassos, E., Ettinger, U., Bramon, E., Murray, R., Ruggeri, M., Tosato, S., Bonetto, C., Steinberg, S., Sigurdsson, E., Sigmundsson, T., Petursson, H., Gylfason, A, Olason, P., Hardarsson, G., Jonsdottir, G.A., Gustafsson, O., Fossdal, R., Giegling, I., Moller, H.J., Hartmann, A.M., Hoffmann, P., Crombie, C., Fraser, G., Walker, N., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Djurovic, S., Melle, I., Andreassen, O.A., Hansen, T., Werge, T., Kiemeney, L.A.L.M., Franke, B., Veltman, J.A., Buizer-Voskamp, J.E., Sabatti, C., Ophoff, R.A., Rietschel, M., Nothen, Markus, Stefansson, K., Peltonen, L., St Clair, D., Stefansson, H., and Collier, D.A.

Abstract

Contains fulltext : 80670.pdf (publisher's version ) (Closed access), Deletions within the neurexin 1 gene (NRXN1; 2p16.3) are associated with autism and have also been reported in two families with schizophrenia. We examined NRXN1, and the closely related NRXN2 and NRXN3 genes, for copy number variants (CNVs) in 2977 schizophrenia patients and 33 746 controls from seven European populations (Iceland, Finland, Norway, Germany, The Netherlands, Italy and UK) using microarray data. We found 66 deletions and 5 duplications in NRXN1, including a de novo deletion: 12 deletions and 2 duplications occurred in schizophrenia cases (0.47%) compared to 49 and 3 (0.15%) in controls. There was no common breakpoint and the CNVs varied from 18 to 420 kb. No CNVs were found in NRXN2 or NRXN3. We performed a Cochran-Mantel-Haenszel exact test to estimate association between all CNVs and schizophrenia (P = 0.13; OR = 1.73; 95% CI 0.81-3.50). Because the penetrance of NRXN1 CNVs may vary according to the level of functional impact on the gene, we next restricted the association analysis to CNVs that disrupt exons (0.24% of cases and 0.015% of controls). These were significantly associated with a high odds ratio (P = 0.0027; OR 8.97, 95% CI 1.8-51.9). We conclude that NRXN1 deletions affecting exons confer risk of schizophrenia.

Published
2009

21. Large recurrent microdeletions associated with schizophrenia.

Author

Stefansson, H., Rujescu, D., Cichon, S., Pietilainen, O.P.H., Ingason, A., Steinberg, S., Fossdal, R., Sigurdsson, E., Sigmundsson, T., Buizer-Voskamp, J.E., Hansen, T., Jakobsen, K.D., Muglia, P., Francks, C., Matthews, P.M., Gylfason, A, Halldorsson, B.V., Gudbjartsson, D.F., Thorgeirsson, T.E., Sigurdsson, A., Jonasdottir, A., Bjornsson, A., Mattiasdottir, S., Blondal, T., Haraldsson, M., Magnusdottir, B.B., Giegling, I., Moller, H.J., Hartmann, A., Shianna, K.V., Ge, D., Need, A.C., Crombie, C., Fraser, G., Walker, N., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Paunio, T., Toulopoulou, T., Bramon, E., Di Forti, M., Murray, R., Ruggeri, M., Vassos, E., Tosato, S., Walshe, M., Li, T., Vasilescu, C., Muhleisen, T.W., Wang, A.G., Ullum, H., Djurovic, S., Melle, I., Olesen, J., Kiemeney, B., Franke, B., Sabatti, C., Freimer, N.B., Gulcher, J.R., Thorsteinsdottir, U., Kong, A., Andreassen, O.A., Ophoff, R.A., Georgi, A., Rietschel, M., Werge, T., Petursson, H., Goldstein, D.B, Nothen, Markus, Peltonen, L., Collier, D.A., St Clair, D., Stefansson, K., Stefansson, H., Rujescu, D., Cichon, S., Pietilainen, O.P.H., Ingason, A., Steinberg, S., Fossdal, R., Sigurdsson, E., Sigmundsson, T., Buizer-Voskamp, J.E., Hansen, T., Jakobsen, K.D., Muglia, P., Francks, C., Matthews, P.M., Gylfason, A, Halldorsson, B.V., Gudbjartsson, D.F., Thorgeirsson, T.E., Sigurdsson, A., Jonasdottir, A., Bjornsson, A., Mattiasdottir, S., Blondal, T., Haraldsson, M., Magnusdottir, B.B., Giegling, I., Moller, H.J., Hartmann, A., Shianna, K.V., Ge, D., Need, A.C., Crombie, C., Fraser, G., Walker, N., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Paunio, T., Toulopoulou, T., Bramon, E., Di Forti, M., Murray, R., Ruggeri, M., Vassos, E., Tosato, S., Walshe, M., Li, T., Vasilescu, C., Muhleisen, T.W., Wang, A.G., Ullum, H., Djurovic, S., Melle, I., Olesen, J., Kiemeney, B., Franke, B., Sabatti, C., Freimer, N.B., Gulcher, J.R., Thorsteinsdottir, U., Kong, A., Andreassen, O.A., Ophoff, R.A., Georgi, A., Rietschel, M., Werge, T., Petursson, H., Goldstein, D.B, Nothen, Markus, Peltonen, L., Collier, D.A., St Clair, D., and Stefansson, K.

Abstract

Contains fulltext : 69527.pdf (publisher's version ) (Closed access)

Published
2008

22. Recurrent CNVs disrupt three candidate genes in schizophrenia patients.

Author

Vrijenhoek, T., Buizer-Voskamp, J.E., Stelt, I. van der, Strengman, E., Sabatti, C., Geurts van Kessel, A.H.M., Brunner, H.G., Ophoff, R.A., Veltman, J.A., Vrijenhoek, T., Buizer-Voskamp, J.E., Stelt, I. van der, Strengman, E., Sabatti, C., Geurts van Kessel, A.H.M., Brunner, H.G., Ophoff, R.A., and Veltman, J.A.

Abstract

Contains fulltext : 71232.pdf (publisher's version ) (Closed access), Schizophrenia is a severe psychiatric disease with complex etiology, affecting approximately 1% of the general population. Most genetics studies so far have focused on disease association with common genetic variation, such as single-nucleotide polymorphisms (SNPs), but it has recently become apparent that large-scale genomic copy-number variants (CNVs) are involved in disease development as well. To assess the role of rare CNVs in schizophrenia, we screened 54 patients with deficit schizophrenia using Affymetrix's GeneChip 250K SNP arrays. We identified 90 CNVs in total, 77 of which have been reported previously in unaffected control cohorts. Among the genes disrupted by the remaining rare CNVs are MYT1L, CTNND2, NRXN1, and ASTN2, genes that play an important role in neuronal functioning but--except for NRXN1--have not been associated with schizophrenia before. We studied the occurrence of CNVs at these four loci in an additional cohort of 752 patients and 706 normal controls from The Netherlands. We identified eight additional CNVs, of which the four that affect coding sequences were found only in the patient cohort. Our study supports a role for rare CNVs in schizophrenia susceptibility and identifies at least three candidate genes for this complex disorder.

Published
2008

26. Bayesian analysis of haplotypes for linkage disequilibrium mapping.

Author

Liu, J S, Sabatti, C, Teng, J, Keats, B J, and Risch, N

Abstract

Haplotype analysis of disease chromosomes can help identify probable historical recombination events and localize disease mutations. Most available analyses use only marginal and pairwise allele frequency information. We have developed a Bayesian framework that utilizes full haplotype information to overcome various complications such as multiple founders, unphased chromosomes, data contamination, and incomplete marker data. A stochastic model is used to describe the dependence structure among several variables characterizing the observed haplotypes, for example, the ancestral haplotypes and their ages, mutation rate, recombination events, and the location of the disease mutation. An efficient Markov chain Monte Carlo algorithm was developed for computing the estimates of the quantities of interest. The method is shown to perform well in both real data sets (cystic fibrosis data and Friedreich ataxia data) and simulated data sets. The program that implements the proposed method, BLADE, as well as the two real datasets, can be obtained from http://www.fas.harvard.edu/~junliu/TechRept/01folder/diseq_prog.tar.gz.

Published
2001
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27. Reconstructing DNA copy number by joint segmentation of multiple sequences

Author

Zhang Zhongyang, Lange Kenneth, and Sabatti Chiara

Subjects
Copy number variant, Copy number polymorphism, Fused lasso, Group fused lasso, MM algorithm, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Variations in DNA copy number carry information on the modalities of genome evolution and mis-regulation of DNA replication in cancer cells. Their study can help localize tumor suppressor genes, distinguish different populations of cancerous cells, and identify genomic variations responsible for disease phenotypes. A number of different high throughput technologies can be used to identify copy number variable sites, and the literature documents multiple effective algorithms. We focus here on the specific problem of detecting regions where variation in copy number is relatively common in the sample at hand. This problem encompasses the cases of copy number polymorphisms, related samples, technical replicates, and cancerous sub-populations from the same individual. Results We present a segmentation method named generalized fused lasso (GFL) to reconstruct copy number variant regions. GFL is based on penalized estimation and is capable of processing multiple signals jointly. Our approach is computationally very attractive and leads to sensitivity and specificity levels comparable to those of state-of-the-art specialized methodologies. We illustrate its applicability with simulated and real data sets. Conclusions The flexibility of our framework makes it applicable to data obtained with a wide range of technology. Its versatility and speed make GFL particularly useful in the initial screening stages of large data sets.

Published
2012
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28. Volume measures for linkage disequilibrium

Author

Lin Chia-Ho, Chen Yuguo, and Sabatti Chiara

Subjects
Genetics, QH426-470
Abstract

Abstract Background Defining measures of linkage disequilibrium (LD) that have good small sample properties and are applicable to multiallelic markers poses some challenges. The potential of volume measures in this context has been noted before, but their use has been hampered by computational challenges. Results We design a sequential importance sampling algorithm to evaluate volume measures on I × J tables. The algorithm is implemented in a C routine as a complement to exhaustive enumeration. We make the C code available as open source. We achieve fast and accurate evaluation of volume measures in two dimensional tables. Conclusion Applying our code to simulated and real datasets reinforces the belief that volume measures are a very useful tool for LD evaluation: they are not inflated in small samples, their definition encompasses multiallelic markers, and they can be computed with appreciable speed.

Published
2006
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29. Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette's Syndrome and OCD

Author

Mary M. Robertson, Peter Heutink, Leonhard Lennertz, Victor I. Reus, John Hardy, Mark A. Riddle, Beatriz Camarena, Helena Garrido, Robert A. King, Simon Girard, Christine Lochner, Michael H. Bloch, Patrick Evans, Anuar Konkashbaev, Jack Samuels, Priya Moorjani, Chiara Sabatti, Andrew J. Pakstis, Ying Wang, O. Joseph Bienvenu, Richard Delorme, David L. Pauls, Rainald Moessner, Gary A. Heiman, Daniel A. Geller, Marco A. Grados, Eric R. Gamazon, John Piacentini, Dan J. Stein, William Cornejo Ochoa, Maria Conceição do Rosário, Karin Egberts, Thomas L. Lowe, Christopher K. Edlund, Jan Smit, Christopher Pittenger, Denise A. Chavira, Marion Leboyer, Homero Vallada, Sandra Catalina Mesa Restrepo, Jacquelyn Crane, Donald W. Black, David V. Conti, Paul Sandor, Humberto Nicolini, Lisa Osiecki, Jeremy Veenstra-VanderWeele, Catherine Mayerfeld, Danielle Posthuma, Edna Grünblatt, Carolina Cappi, Robert B. Weiss, Cristina Barlassina, Sara Lupoli, Chunyu Liu, Sian M. J. Hemmings, Ben A. Oostra, D. Denys, Susanne Walitza, Lea K. Davis, Stephen A. Haddad, Luis Diego Herrera, Jubel Morgan, Hans Joergen Grabe, Benjamin M. Neale, Thomas V. Fernandez, Yehuda Pollak, Roel A. Ophoff, Gerald Nestadt, Harvey S. Singer, Stephan Ruhrmann, Bernadette Cullen, Michael Wagner, Nuria Lanzagorta, Jeremiah M. Scharf, Cathy L. Budman, Ruth D. Bruun, R. Kurlan, Valsama Eapen, Jesen Fagerness, Desmond Campbell, James L. Kennedy, Carlos N. Pato, Nancy J. Cox, Pieter J. Hoekstra, Joseph Jankovic, Cathy L. Barr, Peter Falkai, Donald L. Gilbert, Fortu Benarroch, Dianne M. Hezel, Maria Cristina Cavallini, Brooke Sheppard, Fabio Macciardi, William M. McMahon, Laura Bellodi, Maurizio Turiel, Wolfgang Maier, Varda Gross-Tsur, Helena Brentani, Dongmei Yu, Danielle C. Cath, Ana V. Valencia Duarte, Eduardo Fournier, James A. Knowles, Tobias J. Renner, Erika L. Nurmi, Guy A. Rouleau, Benjamin D. Greenberg, Nelson B. Freimer, Shaun Purcell, Patience J. Gallagher, Roxana Romero, Gregory L. Hanna, Paolo Manunta, Edwin H. Cook, Michele T. Pato, Sylvain Chouinard, Scott L. Rauch, James T. McCracken, Gloria Gerber, Carol A. Mathews, Jens R. Wendland, Sampath Arepalli, Dennis L. Murphy, Daniele Cusi, Barbara Kremeyer, Vladimir Coric, Aline S. Sampaio, Erika Salvi, Julio C. Cardona Silgado, Cornelia Illmann, James F. Leckman, Euripedes Constantino Miguel, H. Müller, Yin Yao Shugart, Eric Strengman, Ana Gabriela Hounie, Michael E. Weale, Gabriel Bedoya Berrió, Margaret A. Richter, Maurizio Marconi, Allan L. Naarden, Michael A. Jenike, M.R. Cookson, David R. Rosenberg, Andres Ruiz-Linares, S. Evelyn Stewart, Paul D. Arnold, H.G.M. Westenberg, Yves Dion, Jay A. Tischfield, Eske M. Derks, Lauren M. McGrath, Child and Adolescent Psychiatry / Psychology, Clinical Genetics, Yu, D., Mathews, C. A., Scharf, J. M., Neale, B. M., Davis, L. K., Gamazon, E. R., Derks, E. M., Evans, P., Edlund, C. K., Crane, J., Fagerness, J. A., Osiecki, L., Gallagher, P., Gerber, G., Haddad, S., Illmann, C., Mcgrath, L. M., Mayerfeld, C., Arepalli, S., Barlassina, C., Barr, C. L., Bellodi, L., Benarroch, F., Berrio, G. B., Bienvenu, O. J., Black, D., Bloch, M. H., Brentani, H., Bruun, R. D., Budman, C. L., Camarena, B., Campbell, D. D., Cappi, C., Cardona Silgado, J. C., Cavallini, M. C., Chavira, D. A., Chouinard, S., Cook, E. H., Cookson, M. R., Coric, V., Cullen, B., Cusi, D., Delorme, R., Denys, D., Dion, Y., Eapen, V., Egberts, K., Falkai, P., Fernandez, T., Fournier, E., Garrido, H., Geller, D., Gilbert, D., Girard, S. L., Grabe, H. J., Grados, M. A., Greenberg, B. D., Gross-Tsur, V., Grunblatt, E., Hardy, J., Heiman, G. A., Hemmings, S. M. J., Herrera, L. D., Hezel, D. M., Hoekstra, P. J., Jankovic, J., Kennedy, J. L., King, R. A., Konkashbaev, A. I., Kremeyer, B., Kurlan, R., Lanzagorta, N., Leboyer, M., Leckman, J. F., Lennertz, L., Liu, C., Lochner, C., Lowe, T. L., Lupoli, S., Macciardi, F., Maier, W., Manunta, P., Marconi, M., Mccracken, J. T., Mesa Restrepo, S. C., Moessner, R., Moorjani, P., Morgan, J., Muller, H., Murphy, D. L., Naarden, A. L., Ochoa, W. C., Ophoff, R. A., Pakstis, A. J., Pato, M. T., Pato, C. N., Piacentini, J., Pittenger, C., Pollak, Y., Rauch, S. L., Renner, T., Reus, V. I., Richter, M. A., Riddle, M. A., Robertson, M. M., Romero, R., Rosario, M. C., Rosenberg, D., Ruhrmann, S., Sabatti, C., Salvi, E., Sampaio, A. S., Samuels, J., Sandor, P., Service, S. K., Sheppard, B., Singer, H. S., Smit, J. H., Stein, D. J., Strengman, E., Tischfield, J. A., Turiel, M., Valencia Duarte, A. V., Vallada, H., Veenstra-VanderWeele, J., Walitza, S., Walkup, J., Wang, Y., Weale, M., Weiss, R., Wendland, J. R., Westenberg, H. G. M., Yao, Y., Hounie, A. G., Miguel, E. C., Nicolini, H., Wagner, M., Ruiz-Linares, A., Cath, D. C., Mcmahon, W., Posthuma, D., Oostra, B. A., Nestadt, G., Rouleau, G. A., Purcell, S., Jenike, M. A., Heutink, P., Hanna, G. L., Conti, D. V., Arnold, P. D., Freimer, N., Stewart, S. E., Knowles, J. A., Cox, N. J., Pauls, D. L., Netherlands Institute for Neuroscience (NIN), Sub String Theory Cosmology and ElemPart, Leerstoel Hout, Experimental psychopathology, Psychiatry, Human genetics, NCA - Neurobiology of mental health, EMGO - Mental health, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Other departments, ANS - Amsterdam Neuroscience, APH - Amsterdam Public Health, Adult Psychiatry, Complex Trait Genetics, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, and EMGO+ - Mental Health

Subjects
Adult, Male, Obsessive-Compulsive Disorder, diagnosis [Tourette Syndrome], Tics, Single-nucleotide polymorphism, Genome-wide association study, Comorbidity, VARIANTS, Tourette syndrome, Polymorphism, Single Nucleotide, Severity of Illness Index, ASSOCIATION SCANS, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Polymorphism (computer science), Severity of illness, mental disorders, medicine, TICS, Humans, ddc:610, Polymorphism, 030304 developmental biology, Genetics, Psychiatric Status Rating Scales, genetics [Obsessive-Compulsive Disorder], 0303 health sciences, GENERALIST GENES, Single Nucleotide, OBSESSIVE-COMPULSIVE DISORDER, epidemiology [Tourette Syndrome], medicine.disease, Genetic architecture, Psychiatry and Mental health, genetics [Tourette Syndrome], Female, epidemiology [Obsessive-Compulsive Disorder], Psychology, 030217 neurology & neurosurgery, diagnosis [Obsessive-Compulsive Disorder], Genome-Wide Association Study, Tourette Syndrome
Abstract

Objective: Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a combined genome-wide association study (GWAS) of Tourette's syndrome and OCD.Method: The authors conducted a GWAS in 2,723 cases (1,310 with OCD, 834 with Tourette's syndrome, 579 with OCD plus Tourette's syndrome/chronic tics), 5,667 ancestry-matched controls, and 290 OCD parent-child trios. GWAS summary statistics were examined for enrichment of functional variants associated with gene expression levels in brain regions. Polygenic score analyses were conducted to investigate the genetic architecture within and across the two disorders.Results: Although no individual single-nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels (expression quantitative loci, or eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders Polygenic score analyses identified a significant polygenic component for OCD (p=2x10(-4)), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, Tourette's syndrome had a smaller, nonsignificant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and co-occurring Tourette's syndrome/chronic tics were included in the analysis (p=0.01).Conclusions: Previous work has shown that Tourette's syndrome and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of these two disorders. Furthermore, OCD with co-occurring burette's syndrome/chronic tics may have different underlying genetic susceptibility compared with OCD alone.

Published
2015

30. Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals

Author

Seppo Koskinen, Christian Herder, Daniel I. Chasman, Andrew R. Wood, Jonna L. Grimsby, J.F. Wilson, Day Inm., Massimo Mangino, Gonneke Willemsen, Robert W. Mahley, Cristian Pattaro, Nicole L. Glazer, T.B. Harris, Irene Pichler, M S Sandhu, D. van Heemst, Christine Proença, Martha Ganser, Robert A. Hegele, Richa Saxena, Eleftheria Zeggini, Markku Laakso, Peter Kraft, Judith B. Borja, Karen L. Mohlke, J B Richards, de Geus Ejc., Robert Sladek, Cristen J. Willer, Samy Hadjadj, S.M. Boekholdt, Gina M. Peloso, Kijoung Song, Sutapa Mukherjee, Gudmar Thorleifsson, Winston Hide, Mark I. McCarthy, Ruth E. Pakyz, Marian Beekman, Ayellet V. Segrè, Inga Prokopenko, Ping An, George Dedoussis, Danielle Posthuma, Jeanette Erdmann, Simon J. Griffin, Nilesh J. Samani, Inke R. König, Frank B. Hu, Lokki M-L., David M. Evans, Xiaohui Li, Valgerdur Steinthorsdottir, Aimo Ruokonen, A Pouta, Kerrin S. Small, Cecilia M. Lindgren, O Le Bacquer, Xijing Han, Florian Kronenberg, E Katsareli, Christian Dina, S. Gabriel, Jochen Spranger, James S. Pankow, M. Kloppenburg, Penninx Bwjh., Torben Hansen, Josh Smith, Jennie Hui, Gordon H. Williams, Mark Seielstad, Ingrid B. Borecki, Weihua Zhang, Peter P. Pramstaller, Stephen J. Sharp, Neil R. Robertson, Zee Ryl., Mike Sampson, Angela Silveira, C.M. van Duijn, Anders Hamsten, Peter Shrader, Denis Rybin, Chen Y-Di., Gunnar Sigurdsson, Michael Stumvoll, Russel Tracy, Mark O. Goodarzi, Göran Hallmans, Michael R. Erdos, Valeriya Lyssenko, Juha Saharinen, Sven Bergmann, Jeffrey R. O'Connell, Debbie A Lawlor, Thomas Meitinger, Yvonne Böttcher, Jérôme Delplanque, Sarah G. Buxbaum, Silvia Naitza, Shah Ebrahim, Graham A. Hitman, Angelo Scuteri, Aroon D. Hingorani, Heribert Schunkert, François Pattou, Claudia Lamina, A L Elliott, Sekar Kathiresan, Dawn M. Waterworth, Jennifer A. Brody, Thomas Quertermous, Leena Peltonen, Josephine M. Egan, Daniel J. Rader, J F Peden, Yarnell Jwg., Daniel S. Pearson, Pfeiffer Afh., P S Chines, N Vogelzangs, Susan Redline, Alka M. Kanaya, T B Harris, J. V. van Vliet-Ostaptchouk, Ghislain Rocheleau, Rune R. Frants, Olga D. Carlson, James G. Wilson, Melissa Garcia, Ong Rt-H., Mark J. Caulfield, Tanya M. Teslovich, Loo B-M., Beatrice Knight, Andreas Ziegler, Claudia Langenberg, Yoon Shin Cho, Paul M. Ridker, Mark J. Rieder, Praveen Sethupathy, Bert Bravenboer, J. Viikari, Matt Neville, Ioannis M. Stylianou, Andrew Walley, Jarvelin M-R., Jarred B. McAteer, Ronald M. Krauss, Augustine Kong, Oluf Pedersen, Mark J. Daly, Andrew P. Morris, Anna F. Dominiczak, Stéphane Cauchi, Michael Boehnke, Christopher J. O'Donnell, Barbara Thorand, Peter M. Nilsson, Aaron Isaacs, Deborah A. Nickerson, Roza Blagieva, Mary F. Feitosa, Nicholas J. Wareham, Robert Roberts, J S Kooner, K W van Dijk, Tiinamaija Tuomi, Paul Scheet, Lynda M. Rose, Albert V. Smith, Rafn Benediktsson, Chiara Sabatti, Candace Guiducci, Lee M. Kaplan, Aki S. Havulinna, Toby Johnson, Samuli Ripatti, Erik Ingelsson, Mario A. Morken, Carl G. P. Platou, Anke Tönjes, Qi Sun, Narisu Narisu, S J Bumpstead, Jose M. Ordovas, Alan B. Feranil, L Groop, P Chines, Sara M. Willems, Perry Jrb., Matthew A. Allison, Jan Scott, Cécile Lecoeur, Kastelein Jjp., Herman A. Taylor, Anyuan Cao, Christopher J. Groves, Lincoln D. Stein, Laura J. Scott, John Beilby, Kristin G. Ardlie, Christopher S. Franklin, Yoav Ben-Shlomo, B M Shields, N J Timpson, Marco Orrù, Amélie Bonnefond, Kiran Musunuru, Murielle Bochud, Udo Seedorf, Yongmei Liu, Guillaume Lettre, Lee J-Y., Alan R. Shuldiner, Ryan P. Welch, David J. Hunter, John Whitfield, Klaus Strassburger, Khaw K-T., Hartikainen A-L., Gunnar Sigurðsson, Lu Qi, Richard N. Bergman, G M Lathrop, Sigrid W. Fouchier, T van Herpt, David S. Siscovick, Igor Rudan, Richard M. Watanabe, Themistocles L. Assimes, Nicholas G. Martin, Ozren Polasek, Dhiraj Varma, K Kim, Oliver Hofmann, Nicholas D. Hastie, S Bumpstead, Jose C. Florez, Fernando Rivadeneira, Katharine R. Owen, Braxton D. Mitchell, Alisa K. Manning, Abbas Dehghan, Bruce Bartholow Duncan, Cisca Wijmenga, Timo T. Valle, Jaakko Kaprio, Mika Kivimäki, B Shields, Laila Simpson, Tim D. Spector, Paul W. Franks, Guangju Zhai, María Teresa Martínez-Larrad, Janssens Acjw., Kim L. Ward, Inês Barroso, Xiuqing Guo, Rosa Maria Roccasecca, Zari Dastani, Reijo Laaksonen, Wilmar Igl, Vincent Mooser, Niels Grarup, Cornelia Huth, Christian Gieger, Fabio Marroni, Jaakko Tuomilehto, Doney Asf., Andrew C. Edmondson, Christian Fuchsberger, Meena Kumari, David M. Nathan, Reedik Mägi, Solomon K. Musani, U de Faire, Knut Borch-Johnsen, Masahiro Koseki, Giuseppe Paolisso, Norman Klopp, Caroline S. Fox, Nelson B. Freimer, Mika Kähönen, Peter Henneman, Diana Zelenika, K Willems-Vandijk, Steven A. McCarroll, Paul Elliott, Wichmann H-E., J. C. Bis, Nita G. Forouhi, Antti Jula, Witteman Jcm., Fredrik Karpe, Joseph Hung, Antje Fischer-Rosinsky, Eric J. Brunner, Elena Gonzalez, Soumya Raychaudhuri, Jian'an Luan, Josée Dupuis, Joshua C. Randall, Taesung Park, Francis S. Collins, Lori L. Bonnycastle, Andrew A. Hicks, Peter Kovacs, Thomas Illig, Maja Barbalić, David Couper, Jaspal S. Kooner, Damien C. Croteau-Chonka, Gavin Lucas, P J Wagner, Young-Jin Kim, Yurii S. Aulchenko, Aurelian Bidulescu, Ingrid Meulenbelt, Pilar Galan, Iris M. Heid, Michael N. Weedon, Serena Sanna, Sarah H. Wild, Hivert M-F., Patricia B. Munroe, Johan G. Eriksson, Teresa Ferreira, Robert A. Scott, A. Sandbaek, Kenneth Rice, Veronique Vitart, Xin Yuan, Leslie A. Lange, Hilma Holm, Jorge R. Kizer, Timothy M. Frayling, Marika Kaakinen, Liu C-T., Petersen A-K., Peter Schwarz, G B Walters, Palmer Cna., Jean Tichet, Bernhard Paulweber, Ying Wu, Alyson Hall, Christopher T. Johansen, David Masson, Martin Ladouceur, Christie M. Ballantyne, Tai E-S., Robert Luben, Guillaume Charpentier, Angela Döring, Philip J. Barter, Ruth McPherson, Benjamin F. Voight, Wolfgang Rathmann, Mark Walker, Markus Perola, M. A. Province, Veikko Salomaa, James B. Meigs, George Davey Smith, Robert Clarke, Gerard Waeber, Stefania Bandinelli, Sally L. Ricketts, Kaisa Silander, Loos Rjf., Amanda J. Bennett, John C. Chambers, Marilyn C. Cornelis, L A Cupples, Andrew T. Hattersley, M Sandhu, Marju Orho-Melander, C M van Duijn, Olli T. Raitakari, David Meyre, Ida Surakka, Jouke-Jan Hottenga, Uh H-W., Kari Stefansson, David Melzer, P E Slagboom, Kristian Midthjell, Robert K. Semple, James P. Pirruccello, Aloysius G Lieverse, Åsa Johansson, Michael Roden, Felicity Payne, Eric J.G. Sijbrands, N P Burtt, David R. Hillman, Michael Marmot, Todd Green, Eric E. Schadt, Sijbrands Ejg., Tien Yin Wong, Coin Ljm., K B Boström, Olov Rolandsson, A D Morris, David Altshuler, Harald Grallert, L C Groop, Alan F. Wright, Karen Kapur, Xueling Sim, Philippe Froguel, K O Kyvik, T. Lauritzen, Linda S. Adair, Yavuz Ariyurek, Talin Haritunians, Toshiko Tanaka, Albert Hofman, MariaGrazia Franzosi, Nicholas L. Smith, Laura Crisponi, Andrew B. Singleton, A Uitterlinden, Bo Isomaa, Y A Kesaniemi, Anne U. Jackson, Christa Meisinger, Holly E. Syddall, Dorret I. Boomsma, Harry Campbell, Gonçalo R. Abecasis, Lyudmyla Kedenko, Christine Cavalcanti-Proença, G Crawford, Scott M. Grundy, Johnson Prv., Nuotio M-L., I Chen, J.H. Smit, Anuj Goel, M Li, David P. Strachan, Kenechi Ejebe, Beverley Balkau, Neelam Hassanali, Kristian Hveem, Pierre Meneton, R. Gwilliam, A J Swift, Caroline Hayward, J. Graessler, Carina Zabena, B. St Pourcain, Michel Marre, Margot Haun, Lyytikäinen L-P., Ben A. Oostra, Stefan Coassin, M. van Hoek, Nigel W. Rayner, John R. Thompson, Kurt Lohman, Ulla Sovio, Unnur Thorsteinsdottir, Naveed Sattar, Lyle J. Palmer, Ulf Gyllensten, A Elliott, Muredach P. Reilly, A Swift, Luigi Ferrucci, Syvänen A-C., Simon C. Potter, T.W. van Haeften, G Wu, Stefan Böhringer, Grant W. Montgomery, Edward G. Lakatta, Serkalem Demissie, Alex S. F. Doney, Najaf Amin, Lenore J. Launer, Hugh Watkins, Johanna Kuusisto, Lars Lind, Stefan R. Bornstein, Laura J. Rasmussen-Torvik, Terho Lehtimäki, Guillaume Paré, Sophie Visvikis-Siest, S C Heath, David Schlessinger, Juha Sinisalo, Kao Whl., Mark E. Cooper, Kati Kristiansson, Thomas W. Winkler, Thomas Sparsø, Laura J. McCulloch, Taina K. Lajunen, Alex N. Parker, Nabila Bouatia-Naji, Markku S. Nieminen, Peter Vollenweider, Wendy L. McArdle, G K Hovingh, Thomas A. Buchanan, Avan Aihie Sayer, M C Zillikens, Jing Hua Zhao, Naomi Hammond, Vilmundur Gudnason, Björn Zethelius, Panos Deloukas, Jacqueline C. M. Witteman, Eric Boerwinkle, Manuel Serrano-Ríos, Anna L. Gloyn, Katherine S. Elliott, A C Fedson, Torben Jørgensen, Nicole Soranzo, Heather M. Stringham, Bruce M. Psaty, A G Uitterlinden, Stavroula Kanoni, Christian Hengstenberg, Yun Li, Olle Melander, Alan R. Tall, Manuela Uda, Magnusson Pke., Christopher W. Kuzawa, V Mooser, R. M. van Dam, Jerome I. Rotter, Greenwood Cmt., Cyrus Cooper, Pau Navarro, Min Jin Go, Nancy L. Pedersen, Serge Hercberg, Bernhard O. Boehm, Eleanor Wheeler, Epidemiology, Medical Microbiology & Infectious Diseases, Clinical Genetics, Dastani, Z, Hivert, Mf, Timpson, N, Perry, Jr, Yuan, X, Scott, Ra, Henneman, P, Heid, Im, Kizer, Jr, Lyytikäinen, Lp, Fuchsberger, C, Tanaka, T, Morris, Ap, Small, K, Isaacs, A, Beekman, M, Coassin, S, Lohman, K, Qi, L, Kanoni, S, Pankow, J, Uh, Hw, Wu, Y, Bidulescu, A, Rasmussen Torvik, Lj, Greenwood, Cm, Ladouceur, M, Grimsby, J, Manning, Ak, Liu, Ct, Kooner, J, Mooser, Ve, Vollenweider, P, Kapur, Ka, Chambers, J, Wareham, Nj, Langenberg, C, Frants, R, Willems Vandijk, K, Oostra, Ba, Willems, Sm, Lamina, C, Winkler, Tw, Psaty, Bm, Tracy, Rp, Brody, J, Chen, I, Viikari, J, Kähönen, M, Pramstaller, Pp, Evans, Dm, St Pourcain, B, Sattar, N, Wood, Ar, Bandinelli, S, Carlson, Od, Egan, Jm, Böhringer, S, van Heemst, D, Kedenko, L, Kristiansson, K, Nuotio, Ml, Loo, Bm, Harris, T, Garcia, M, Kanaya, A, Haun, M, Klopp, N, Wichmann, He, Deloukas, P, Katsareli, E, Couper, Dj, Duncan, Bb, Kloppenburg, M, Adair, L, Borja, Jb, DIAGRAM+, Consortium, Magic, Consortium, Glgc, Investigator, Muther, Consortium, Wilson, Jg, Musani, S, Guo, X, Johnson, T, Semple, R, Teslovich, Tm, Allison, Ma, Redline, S, Buxbaum, Sg, Mohlke, Kl, Meulenbelt, I, Ballantyne, Cm, Dedoussis, Gv, Hu, Fb, Liu, Y, Paulweber, B, Spector, Td, Slagboom, Pe, Ferrucci, L, Jula, A, Perola, M, Raitakari, O, Florez, Jc, Salomaa, V, Eriksson, Jg, Frayling, Tm, Hicks, Aa, Lehtimäki, T, Smith, Gd, Siscovick, D, Kronenberg, F, van Duijn, C, Loos, Rj, Waterworth, Dm, Meigs, Jb, Dupuis, J, Richards, Jb, Voight, Bf, Scott, Lj, Steinthorsdottir, V, Dina, C, Welch, Rp, Zeggini, E, Huth, C, Aulchenko, Y, Thorleifsson, G, Mcculloch, Lj, Ferreira, T, Grallert, H, Amin, N, Wu, G, Willer, Cj, Raychaudhuri, S, Mccarroll, Sa, Hofmann, Om, Segrè, Av, van Hoek, M, Navarro, P, Ardlie, K, Balkau, B, Benediktsson, R, Bennett, Aj, Blagieva, R, Boerwinkle, E, Bonnycastle, Ll, Boström, Kb, Bravenboer, B, Bumpstead, S, Burtt, Np, Charpentier, G, Chines, P, Cornelis, M, Crawford, G, Doney, A, Elliott, K, Elliott, Al, Erdos, Mr, Fox, C, Franklin, C, Ganser, M, Gieger, C, Grarup, N, Green, T, Griffin, S, Groves, Cj, Guiducci, C, Hadjadj, S, Hassanali, N, Herder, C, Isomaa, B, Jackson, Au, Johnson, Pr, Jørgensen, T, Kao, Wh, Kong, A, Kraft, P, Kuusisto, J, Lauritzen, T, Li, M, Lieverse, A, Lindgren, Cm, Lyssenko, V, Marre, M, Meitinger, T, Midthjell, K, Morken, Ma, Narisu, N, Nilsson, P, Owen, Kr, Payne, F, Petersen, Ak, Platou, C, Proença, C, Prokopenko, I, Rathmann, W, Rayner, Nw, Robertson, Nr, Rocheleau, G, Roden, M, Sampson, Mj, Saxena, R, Shields, Bm, Shrader, P, Sigurdsson, G, Sparsø, T, Strassburger, K, Stringham, Hm, Sun, Q, Swift, Aj, Thorand, B, Tichet, J, Tuomi, T, van Dam, Rm, van Haeften, Tw, van Herpt, T, van Vliet Ostaptchouk, Jv, Walters, Gb, Weedon, Mn, Wijmenga, C, Witteman, J, Bergman, Rn, Cauchi, S, Collins, F, Gloyn, Al, Gyllensten, U, Hansen, T, Hide, Wa, Hitman, Ga, Hofman, A, Hunter, Dj, Hveem, K, Laakso, M, Morris, Ad, Palmer, Cn, Rudan, I, Sijbrands, E, Stein, Ld, Tuomilehto, J, Uitterlinden, A, Walker, M, Watanabe, Rm, Abecasis, Gr, Boehm, Bo, Campbell, H, Daly, Mj, Hattersley, At, Pedersen, O, Barroso, I, Groop, L, Sladek, R, Thorsteinsdottir, U, Wilson, Jf, Illig, T, Froguel, P, van Duijn, Cm, Stefansson, K, Altshuler, D, Boehnke, M, Mccarthy, Mi, Soranzo, N, Wheeler, E, Glazer, Nl, Bouatia Naji, N, Mägi, R, Randall, J, Elliott, P, Rybin, D, Dehghan, A, Hottenga, Jj, Song, K, Goel, A, Lajunen, T, Cavalcanti Proença, C, Kumari, M, Timpson, Nj, Zabena, C, Ingelsson, E, An, P, O'Connell, J, Luan, J, Elliott, A, Roccasecca, Rm, Pattou, F, Sethupathy, P, Ariyurek, Y, Barter, P, Beilby, Jp, Ben Shlomo, Y, Bergmann, S, Bochud, M, Bonnefond, A, Borch Johnsen, K, Böttcher, Y, Brunner, E, Bumpstead, Sj, Chen, Yd, Clarke, R, Coin, Lj, Cooper, Mn, Crisponi, L, Day, In, de Geus, Ej, Delplanque, J, Fedson, Ac, Fischer Rosinsky, A, Forouhi, Ng, Franzosi, Mg, Galan, P, Goodarzi, Mo, Graessler, J, Grundy, S, Gwilliam, R, Hallmans, G, Hammond, N, Han, X, Hartikainen, Al, Hayward, C, Heath, Sc, Hercberg, S, Hillman, Dr, Hingorani, Ad, Hui, J, Hung, J, Kaakinen, M, Kaprio, J, Kesaniemi, Ya, Kivimaki, M, Knight, B, Koskinen, S, Kovacs, P, Kyvik, Ko, Lathrop, Gm, Lawlor, Da, Le Bacquer, O, Lecoeur, C, Li, Y, Mahley, R, Mangino, M, Martínez Larrad, Mt, Mcateer, Jb, Mcpherson, R, Meisinger, C, Melzer, D, Meyre, D, Mitchell, Bd, Mukherjee, S, Naitza, S, Neville, Mj, Orrù, M, Pakyz, R, Paolisso, Giuseppe, Pattaro, C, Pearson, D, Peden, Jf, Pedersen, Nl, Pfeiffer, Af, Pichler, I, Polasek, O, Posthuma, D, Potter, Sc, Pouta, A, Province, Ma, Rice, K, Ripatti, S, Rivadeneira, F, Rolandsson, O, Sandbaek, A, Sandhu, M, Sanna, S, Sayer, Aa, Scheet, P, Seedorf, U, Sharp, Sj, Shields, B, Sigurðsson, G, Sijbrands, Ej, Silveira, A, Simpson, L, Singleton, A, Smith, Nl, Sovio, U, Swift, A, Syddall, H, Syvänen, Ac, Tönjes, A, Uitterlinden, Ag, van Dijk, Kw, Varma, D, Visvikis Siest, S, Vitart, V, Vogelzangs, N, Waeber, G, Wagner, Pj, Walley, A, Ward, Kl, Watkins, H, Wild, Sh, Willemsen, G, Witteman, Jc, Yarnell, Jw, Zelenika, D, Zethelius, B, Zhai, G, Zhao, Jh, Zillikens, Mc, Diagram, Consortium, Giant, Consortium, Global B., Pgen Consortium, Borecki, Ib, Meneton, P, Magnusson, Pk, Nathan, Dm, Williams, Gh, Silander, K, Bornstein, Sr, Schwarz, P, Spranger, J, Karpe, F, Shuldiner, Ar, Cooper, C, Serrano Ríos, M, Lind, L, Palmer, Lj, Hu FB, 1st, Franks, Pw, Ebrahim, S, Marmot, M, Wright, Af, Stumvoll, M, Hamsten, A, Procardis, Consortium, Buchanan, Ta, Valle, Tt, Rotter, Ji, Penninx, Bw, Boomsma, Di, Cao, A, Scuteri, A, Schlessinger, D, Uda, M, Ruokonen, A, Jarvelin, Mr, Peltonen, L, Mooser, V, Magic, Investigator, Glgc, Consortium, Musunuru, K, Smith, Av, Edmondson, Ac, Stylianou, Im, Koseki, M, Pirruccello, Jp, Chasman, Di, Johansen, Ct, Fouchier, Sw, Peloso, Gm, Barbalic, M, Ricketts, Sl, Bis, Jc, Feitosa, Mf, Orho Melander, M, Melander, O, Li, X, Cho, Y, Go, Mj, Kim, Yj, Lee, Jy, Park, T, Kim, K, Sim, X, Ong, Rt, Croteau Chonka, Dc, Lange, La, Smith, Jd, Ziegler, A, Zhang, W, Zee, Ry, Whitfield, Jb, Thompson, Jr, Surakka, I, Smit, Jh, Sinisalo, J, Scott, J, Saharinen, J, Sabatti, C, Rose, Lm, Roberts, R, Rieder, M, Parker, An, Pare, G, O'Donnell, Cj, Nieminen, M, Nickerson, Da, Montgomery, Gw, Mcardle, W, Masson, D, Martin, Ng, Marroni, F, Lucas, G, Luben, R, Lokki, Ml, Lettre, G, Launer, Lj, Lakatta, Eg, Laaksonen, R, König, Ir, Khaw, Kt, Kaplan, Lm, Johansson, Å, Janssens, Ac, Igl, W, Hovingh, Gk, Hengstenberg, C, Havulinna, A, Hastie, Nd, Harris, Tb, Haritunians, T, Hall, A, Groop, Lc, Gonzalez, E, Freimer, Nb, Erdmann, J, Ejebe, Kg, Döring, A, Dominiczak, Af, Demissie, S, de Faire, U, Caulfield, Mj, Boekholdt, Sm, Assimes, Tl, Quertermous, T, Seielstad, M, Wong, Ty, Tai, E, Feranil, Ab, Kuzawa, Cw, Taylor HA, Jr, Gabriel, Sb, Holm, H, Gudnason, V, Krauss, Rm, Ordovas, Jm, Munroe, Pb, Tall, Ar, Hegele, Ra, Kastelein, Jj, Schadt, Ee, Strachan, Dp, Reilly, Mp, Samani, Nj, Schunkert, H, Cupples, La, Ridker, Pm, Rader, Dj, Kathiresan, S., Medical Research Council (MRC), Perry, John [0000-0001-6483-3771], Wareham, Nicholas [0000-0003-1422-2993], Langenberg, Claudia [0000-0002-5017-7344], Semple, Robert [0000-0001-6539-3069], Griffin, Simon [0000-0002-2157-4797], Barroso, Ines [0000-0001-5800-4520], Soranzo, Nicole [0000-0003-1095-3852], Wheeler, Eleanor [0000-0002-8616-6444], Luan, Jian'an [0000-0003-3137-6337], Forouhi, Nita [0000-0002-5041-248X], Sharp, Stephen [0000-0003-2375-1440], Sovio, Ulla [0000-0002-0799-1105], Zhao, Jing Hua [0000-0003-4930-3582], Luben, Robert [0000-0002-5088-6343], Khaw, Kay-Tee [0000-0002-8802-2903], Sandhu, Manjinder [0000-0002-2725-142X], Apollo - University of Cambridge Repository, Biological Psychology, Functional Genomics, Neuroscience Campus Amsterdam - Attention & Cognition, EMGO+ - Lifestyle, Overweight and Diabetes, Other departments, Experimental Vascular Medicine, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Cardiology, Human genetics, Psychiatry, NCA - Attention & Cognition, EMGO - Lifestyle, overweight and diabetes, Lääketieteen yksikkö - School of Medicine, University of Tampere, Institute for Molecular Medicine Finland, Hjelt Institute (-2014), Clinicum, Department of General Practice and Primary Health Care, Department of Public Health, Haartman Institute (-2014), Transplantation Laboratory, Biostatistics Helsinki, Quantitative Genetics, Complex Disease Genetics, Genetic Epidemiology, DIAGRAM+ Consortium, MAGIC Consortium, GLGC Investigators, MuTHER Consortium, DIAGRAM Consortium, GIANT Consortium, Global B Pgen Consortium, Procardis Consortium, MAGIC investigators, GLGC Consortium, Olson, J., Kronmal, R., Robbins, J., Chaves, PH., Burke, G., Kuller, LH., Tracy, R., Gottdiener, J., Prineas, R., Becker, JT., Enright, P., Klein, R., and O'Leary, DH.

Subjects
Netherlands Twin Register (NTR), Male, Insulin Resistance/genetics, VARIANTS, 0302 clinical medicine, POPULATION, African Americans, blood/genetics, 0303 health sciences, education.field_of_study, Adiponectin/blood, Adiponectin/genetics, Asian Continental Ancestry Group, Cholesterol, HDL/genetics, Diabetes Mellitus, Type 2/genetics, European Continental Ancestry Group, Female, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Glucose Tolerance Test, Humans, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide, Waist-Hip Ratio, Global B Pgen Consortium, MAGIC investigators, 3. Good health, Cholesterol, Medicine, Adiponectin, Type 2, medicine.medical_specialty, HDL, Biolääketieteet - Biomedicine, Single-nucleotide polymorphism, DIAGRAM Consortium, White People, Molecular Genetics, GLGC Consortium, 03 medical and health sciences, Asian People, SDG 3 - Good Health and Well-being, GIANT Consortium, Diabetes Mellitus, Genetics, DIAGRAM+ Consortium, GENOME-WIDE ASSOCIATION, Polymorphism, education, Biology, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 0604 Genetics, Science & Technology, GLGC Investigators, nutritional and metabolic diseases, ta3121, medicine.disease, Obesity, Black or African American, blood/genetics, African Americans, Asian Continental Ancestry Group, Cholesterol, genetics, Diabetes Mellitus, genetics, European Continental Ancestry Group, Female, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Glucose Tolerance Test, Humans, Insulin Resistance, genetics, Male, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide, Waist-Hip Ratio, Endocrinology, Diabetes Mellitus, Type 2, Developmental Biology, Type 2/genetics, Cancer Research, Type 2 diabetes, QH426-470, 030204 cardiovascular system & hematology, LIPID CONCENTRATIONS, GENETICS & HEREDITY, Genetics (clinical), RISK, 2. Zero hunger, INSULIN-RESISTANCE, Glucose tolerance test, medicine.diagnostic_test, MAGIC Consortium, Single Nucleotide, ADIPOSE-TISSUE, CORONARY-ARTERY-DISEASE, Life Sciences & Biomedicine, Research Article, Clinical Research Design, GENETIC-BASIS, Population, Insulin resistance, Internal medicine, Diabetes mellitus, medicine, ddc:610, 030304 developmental biology, RECEPTOR, Cholesterol, HDL, Human Genetics, HDL/genetics, 3121 General medicine, internal medicine and other clinical medicine, MuTHER Consortium, 3111 Biomedicine, Procardis Consortium, Insulin Resistance
Abstract

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8–1.2×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p, Author Summary Serum adiponectin levels are highly heritable and are inversely correlated with the risk of type 2 diabetes (T2D), coronary artery disease, stroke, and several metabolic traits. To identify common genetic variants associated with adiponectin levels and risk of T2D and metabolic traits, we conducted a meta-analysis of genome-wide association studies of 45,891 multi-ethnic individuals. In addition to confirming that variants at the ADIPOQ and CDH13 loci influence adiponectin levels, our analyses revealed that 10 new loci also affecting circulating adiponectin levels. We demonstrated that expression levels of several genes in these candidate regions are associated with serum adiponectin levels. Using a powerful novel method to assess the contribution of the identified variants with other traits using summary-level results from large-scale GWAS consortia, we provide evidence that the risk alleles for adiponectin are associated with deleterious changes in T2D risk and metabolic syndrome traits (triglycerides, HDL, post-prandial glucose, insulin, and waist-to-hip ratio), demonstrating that the identified loci, taken together, impact upon metabolic disease.

Published
2012

31. Second-order group knockoffs with applications to genome-wide association studies.

Author

Chu BB, Gu J, Chen Z, Morrison T, Candès E, He Z, and Sabatti C

Subjects
Humans, Polymorphism, Single Nucleotide, Genome-Wide Association Study methods, Algorithms, Software
Abstract

Motivation: Conditional testing via the knockoff framework allows one to identify-among a large number of possible explanatory variables-those that carry unique information about an outcome of interest and also provides a false discovery rate guarantee on the selection. This approach is particularly well suited to the analysis of genome-wide association studies (GWAS), which have the goal of identifying genetic variants that influence traits of medical relevance., Results: While conditional testing can be both more powerful and precise than traditional GWAS analysis methods, its vanilla implementation encounters a difficulty common to all multivariate analysis methods: it is challenging to distinguish among multiple, highly correlated regressors. This impasse can be overcome by shifting the object of inference from single variables to groups of correlated variables. To achieve this, it is necessary to construct "group knockoffs." While successful examples are already documented in the literature, this paper substantially expands the set of algorithms and software for group knockoffs. We focus in particular on second-order knockoffs, for which we describe correlation matrix approximations that are appropriate for GWAS data and that result in considerable computational savings. We illustrate the effectiveness of the proposed methods with simulations and with the analysis of albuminuria data from the UK Biobank., Availability and Implementation: The described algorithms are implemented in an open-source Julia package Knockoffs.jl. R and Python wrappers are available as knockoffsr and knockoffspy packages., (© The Author(s) 2024. Published by Oxford University Press.)

Published
2024
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32. A blended genome and exome sequencing method captures genetic variation in an unbiased, high-quality, and cost-effective manner.

Author

Boltz TA, Chu BB, Liao C, Sealock JM, Ye R, Majara L, Fu JM, Service S, Zhan L, Medland SE, Chapman SB, Rubinacci S, DeFelice M, Grimsby JL, Abebe T, Alemayehu M, Ashaba FK, Atkinson EG, Bigdeli T, Bradway AB, Brand H, Chibnik LB, Fekadu A, Gatzen M, Gelaye B, Gichuru S, Gildea ML, Hill TC, Huang H, Hubbard KM, Injera WE, James R, Joloba M, Kachulis C, Kalmbach PR, Kamulegeya R, Kigen G, Kim S, Koen N, Kwobah EK, Kyebuzibwa J, Lee S, Lennon NJ, Lind PA, Lopera-Maya EA, Makale J, Mangul S, McMahon J, Mowlem P, Musinguzi H, Mwema RM, Nakasujja N, Newman CP, Nkambule LL, O'Neil CR, Olivares AM, Olsen CM, Ongeri L, Parsa SJ, Pretorius A, Ramesar R, Reagan FL, Sabatti C, Schneider JA, Shiferaw W, Stevenson A, Stricker E, Stroud RE 2nd, Tang J, Whiteman D, Yohannes MT, Yu M, Yuan K, Akena D, Atwoli L, Kariuki SM, Koenen KC, Newton CRJC, Stein DJ, Teferra S, Zingela Z, Pato CN, Pato MT, Lopez-Jaramillo C, Freimer N, Ophoff RA, Olde Loohuis LM, Talkowski ME, Neale BM, Howrigan DP, and Martin AR

Abstract

We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4× mean depth) and deep whole exome (30-40× mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence >53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations. We evaluated the accuracy of BGE imputed genotypes against raw genotype calls from the Illumina Global Screening Array. All PUMAS cohorts had R 2 concordance ≥95% among SNPs with MAF≥1%, and never fell below ≥90% R 2 for SNPs with MAF<1%. Furthermore, concordance rates among local ancestries within two recently admixed cohorts were consistent among SNPs with MAF≥1%, with only minor deviations in SNPs with MAF<1%. We also benchmarked the discovery capacity of BGE to access protein-coding copy number variants (CNVs) against deep whole genome data, finding that deletions and duplications spanning at least 3 exons had a positive predicted value of ~90%. Our results demonstrate BGE scalability and efficacy in capturing SNPs, indels, and CNVs in the human genome at 28% of the cost of deep whole-genome sequencing. BGE is poised to enhance access to genomic testing and empower genomic discoveries, particularly in underrepresented populations.

Published
2024
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33. Beyond guilty by association at scale: searching for causal variants on the basis of genome-wide summary statistics.

Author

He Z, Chu B, Yang J, Gu J, Chen Z, Liu L, Morrison T, Belloy ME, Qi X, Hejazi N, Mathur M, Le Guen Y, Tang H, Hastie T, Ionita-Laza I, Sabatti C, and Candès E

Abstract

Understanding the causal genetic architecture of complex phenotypes is essential for future research into disease mechanisms and potential therapies. Here, we present a novel framework for genome-wide detection of sets of variants that carry non-redundant information on the phenotypes and are therefore more likely to be causal in a biological sense. Crucially, our framework requires only summary statistics obtained from standard genome-wide marginal association testing. The described approach, implemented in open-source software, is also computationally efficient, requiring less than 15 minutes on a single CPU to perform genome-wide analysis. Through extensive genome-wide simulation studies, we show that the method can substantially outperform usual two-stage marginal association testing and fine-mapping procedures in precision and recall. In applications to a meta-analysis of ten large-scale genetic studies of Alzheimer's disease (AD), we identified 82 loci associated with AD, including 37 additional loci missed by conventional GWAS pipeline. The identified putative causal variants achieve state-of-the-art agreement with massively parallel reporter assays and CRISPR-Cas9 experiments. Additionally, we applied the method to a retrospective analysis of 67 large-scale GWAS summary statistics since 2013 for a variety of phenotypes. Results reveal the method's capacity to robustly discover additional loci for polygenic traits and pinpoint potential causal variants underpinning each locus beyond conventional GWAS pipeline, contributing to a deeper understanding of complex genetic architectures in post-GWAS analyses., Competing Interests: Competing interests The Authors declare no competing interests.

Published
2024
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34. Second-order group knockoffs with applications to GWAS.

Author

Chu BB, Gu J, Chen Z, Morrison T, Candes E, He Z, and Sabatti C

Abstract

Conditional testing via the knockoff framework allows one to identify -- among large number of possible explanatory variables -- those that carry unique information about an outcome of interest, and also provides a false discovery rate guarantee on the selection. This approach is particularly well suited to the analysis of genome wide association studies (GWAS), which have the goal of identifying genetic variants which influence traits of medical relevance. While conditional testing can be both more powerful and precise than traditional GWAS analysis methods, its vanilla implementation encounters a difficulty common to all multivariate analysis methods: it is challenging to distinguish among multiple, highly correlated regressors. This impasse can be overcome by shifting the object of inference from single variables to groups of correlated variables. To achieve this, it is necessary to construct "group knockoffs." While successful examples are already documented in the literature, this paper substantially expands the set of algorithms and software for group knockoffs. We focus in particular on second-order knockoffs, for which we describe correlation matrix approximations that are appropriate for GWAS data and that result in considerable computational savings. We illustrate the effectiveness of the proposed methods with simulations and with the analysis of albuminuria data from the UK Biobank. The described algorithms are implemented in an open-source Julia package Knockoffs.jl, for which both R and Python wrappers are available.

Published
2024

35. Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders.

Author

Song J, Ramírez MC, Okano JT, Service SK, de la Hoz J, Díaz-Zuluaga AM, Upegui CV, Gallago C, Arias A, Sánchez AV, Teshiba T, Sabatti C, Gur RC, Bearden CE, Escobar JI, Reus VI, Jaramillo CL, Freimer NB, Olde Loohuis LM, and Blower S

Abstract

Background: Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas., Methods: We constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters., Results: We show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients., Conclusions: Our results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots., (© 2024. The Author(s).)

Published
2024
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36. Controlled Variable Selection from Summary Statistics Only? A Solution via GhostKnockoffs and Penalized Regression.

Author

Chen Z, He Z, Chu BB, Gu J, Morrison T, Sabatti C, and Candès E

Abstract

Identifying which variables do influence a response while controlling false positives pervades statistics and data science. In this paper, we consider a scenario in which we only have access to summary statistics, such as the values of marginal empirical correlations between each dependent variable of potential interest and the response. This situation may arise due to privacy concerns, e.g., to avoid the release of sensitive genetic information. We extend GhostKnockoffs He et al. [2022] and introduce variable selection methods based on penalized regression achieving false discovery rate (FDR) control. We report empirical results in extensive simulation studies, demonstrating enhanced performance over previous work. We also apply our methods to genome-wide association studies of Alzheimer's disease, and evidence a significant improvement in power.

Published
2024

37. Filtering the rejection set while preserving false discovery rate control.

Author

Katsevich E, Sabatti C, and Bogomolov M

Abstract

Scientific hypotheses in a variety of applications have domain-specific structures, such as the tree structure of the International Classification of Diseases (ICD), the directed acyclic graph structure of the Gene Ontology (GO), or the spatial structure in genome-wide association studies. In the context of multiple testing, the resulting relationships among hypotheses can create redundancies among rejections that hinder interpretability. This leads to the practice of filtering rejection sets obtained from multiple testing procedures, which may in turn invalidate their inferential guarantees. We propose Focused BH, a simple, flexible, and principled methodology to adjust for the application of any pre-specified filter. We prove that Focused BH controls the false discovery rate under various conditions, including when the filter satisfies an intuitive monotonicity property and the p -values are positively dependent. We demonstrate in simulations that Focused BH performs well across a variety of settings, and illustrate this method's practical utility via analyses of real datasets based on ICD and GO.

Published
2023
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38. GhostKnockoff inference empowers identification of putative causal variants in genome-wide association studies.

Author

He Z, Liu L, Belloy ME, Le Guen Y, Sossin A, Liu X, Qi X, Ma S, Gyawali PK, Wyss-Coray T, Tang H, Sabatti C, Candès E, Greicius MD, and Ionita-Laza I

Subjects
Phenotype, Causality, Chromosome Mapping, Genome-Wide Association Study methods, Polymorphism, Single Nucleotide
Abstract

Recent advances in genome sequencing and imputation technologies provide an exciting opportunity to comprehensively study the contribution of genetic variants to complex phenotypes. However, our ability to translate genetic discoveries into mechanistic insights remains limited at this point. In this paper, we propose an efficient knockoff-based method, GhostKnockoff, for genome-wide association studies (GWAS) that leads to improved power and ability to prioritize putative causal variants relative to conventional GWAS approaches. The method requires only Z-scores from conventional GWAS and hence can be easily applied to enhance existing and future studies. The method can also be applied to meta-analysis of multiple GWAS allowing for arbitrary sample overlap. We demonstrate its performance using empirical simulations and two applications: (1) a meta-analysis for Alzheimer's disease comprising nine overlapping large-scale GWAS, whole-exome and whole-genome sequencing studies and (2) analysis of 1403 binary phenotypes from the UK Biobank data in 408,961 samples of European ancestry. Our results demonstrate that GhostKnockoff can identify putatively functional variants with weaker statistical effects that are missed by conventional association tests., (© 2022. The Author(s).)

Published
2022
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39. False discovery rate control in genome-wide association studies with population structure.

Author

Sesia M, Bates S, Candès E, Marchini J, and Sabatti C

Subjects
Algorithms, Genome-Wide Association Study methods, Genotype, Humans, Linkage Disequilibrium genetics, Multifactorial Inheritance genetics, Phenotype, Software, Genome, Human genetics
Abstract

We present a comprehensive statistical framework to analyze data from genome-wide association studies of polygenic traits, producing interpretable findings while controlling the false discovery rate. In contrast with standard approaches, our method can leverage sophisticated multivariate algorithms but makes no parametric assumptions about the unknown relation between genotypes and phenotype. Instead, we recognize that genotypes can be considered as a random sample from an appropriate model, encapsulating our knowledge of genetic inheritance and human populations. This allows the generation of imperfect copies (knockoffs) of these variables that serve as ideal negative controls, correcting for linkage disequilibrium and accounting for unknown population structure, which may be due to diverse ancestries or familial relatedness. The validity and effectiveness of our method are demonstrated by extensive simulations and by applications to the UK Biobank data. These analyses confirm our method is powerful relative to state-of-the-art alternatives, while comparisons with other studies validate most of our discoveries. Finally, fast software is made available for researchers to analyze Biobank-scale datasets., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Published
2021
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40. Increased activation product of complement 4 protein in plasma of individuals with schizophrenia.

Author

Kalinowski A, Liliental J, Anker LA, Linkovski O, Culbertson C, Hall JN, Pattni R, Sabatti C, Noordsy D, Hallmayer JF, Mellins ED, Ballon JS, O'Hara R, Levinson DF, and Urban AE

Subjects
Complement C4a genetics, Endothelial Cells, Genetic Predisposition to Disease, Humans, Complement C4 genetics, Schizophrenia blood, Schizophrenia genetics
Abstract

Structural variation in the complement 4 gene (C4) confers genetic risk for schizophrenia. The variation includes numbers of the increased C4A copy number, which predicts increased C4A mRNA expression. C4-anaphylatoxin (C4-ana) is a C4 protein fragment released upon C4 protein activation that has the potential to change the blood-brain barrier (BBB). We hypothesized that elevated plasma levels of C4-ana occur in individuals with schizophrenia (iSCZ). Blood was collected from 15 iSCZ with illness duration < 5 years and from 14 healthy controls (HC). Plasma C4-ana was measured by radioimmunoassay. Other complement activation products C3-ana, C5-ana, and terminal complement complex (TCC) were also measured. Digital-droplet PCR was used to determine C4 gene structural variation state. Recombinant C4-ana was added to primary brain endothelial cells (BEC) and permeability was measured in vitro. C4-ana concentration was elevated in plasma from iSCZ compared to HC (mean = 654 ± 16 ng/mL, 557 ± 94 respectively, p = 0.01). The patients also carried more copies of the C4AL gene and demonstrated a positive correlation between plasma C4-ana concentrations and C4A gene copy number. Furthermore, C4-ana increased the permeability of a monolayer of BEC in vitro. Our findings are consistent with a specific role for C4A protein in schizophrenia and raise the possibility that its activation product, C4-ana, increases BBB permeability. Exploratory analyses suggest the novel hypothesis that the relationship between C4-ana levels and C4A gene copy number could also be altered in iSCZ, suggesting an interaction with unknown genetic and/or environmental risk factors., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Published
2021
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41. Selection-adjusted inference: an application to confidence intervals for cis-eQTL effect sizes.

Author

Panigrahi S, Zhu J, and Sabatti C

Subjects
Alleles, Confidence Intervals, Humans, Polymorphism, Single Nucleotide genetics, Sample Size, Genome-Wide Association Study, Quantitative Trait Loci genetics
Abstract

The goal of expression quantitative trait loci (eQTL) studies is to identify the genetic variants that influence the expression levels of the genes in an organism. High throughput technology has made such studies possible: in a given tissue sample, it enables us to quantify the expression levels of approximately 20 000 genes and to record the alleles present at millions of genetic polymorphisms. While obtaining this data is relatively cheap once a specimen is at hand, obtaining human tissue remains a costly endeavor: eQTL studies continue to be based on relatively small sample sizes, with this limitation particularly serious for tissues as brain, liver, etc.-often the organs of most immediate medical relevance. Given the high-dimensional nature of these datasets and the large number of hypotheses tested, the scientific community has adopted early on multiplicity adjustment procedures. These testing procedures primarily control the false discoveries rate for the identification of genetic variants with influence on the expression levels. In contrast, a problem that has not received much attention to date is that of providing estimates of the effect sizes associated with these variants, in a way that accounts for the considerable amount of selection. Yet, given the difficulty of procuring additional samples, this challenge is of practical importance. We illustrate in this work how the recently developed conditional inference approach can be deployed to obtain confidence intervals for the eQTL effect sizes with reliable coverage. The procedure we propose is based on a randomized hierarchical strategy with a 2-fold contribution: (1) it reflects the selection steps typically adopted in state of the art investigations and (2) it introduces the use of randomness instead of data-splitting to maximize the use of available data. Analysis of the GTEx Liver dataset (v6) suggests that naively obtained confidence intervals would likely not cover the true values of effect sizes and that the number of local genetic polymorphisms influencing the expression level of genes might be underestimated., (© The Author 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2021
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42. Progenitor identification and SARS-CoV-2 infection in human distal lung organoids.

Author

Salahudeen AA, Choi SS, Rustagi A, Zhu J, van Unen V, de la O SM, Flynn RA, Margalef-Català M, Santos AJM, Ju J, Batish A, Usui T, Zheng GXY, Edwards CE, Wagar LE, Luca V, Anchang B, Nagendran M, Nguyen K, Hart DJ, Terry JM, Belgrader P, Ziraldo SB, Mikkelsen TS, Harbury PB, Glenn JS, Garcia KC, Davis MM, Baric RS, Sabatti C, Amieva MR, Blish CA, Desai TJ, and Kuo CJ

Subjects
Alveolar Epithelial Cells cytology, Alveolar Epithelial Cells metabolism, Alveolar Epithelial Cells virology, COVID-19 metabolism, COVID-19 pathology, Cell Differentiation, Cell Division, Clone Cells cytology, Clone Cells metabolism, Clone Cells virology, Humans, In Vitro Techniques, Influenza A Virus, H1N1 Subtype growth & development, Influenza A Virus, H1N1 Subtype physiology, Integrin alpha6 analysis, Integrin beta4 analysis, Keratin-5 analysis, Organoids metabolism, Pneumonia, Viral metabolism, Pneumonia, Viral pathology, Pneumonia, Viral virology, SARS-CoV-2 growth & development, Single-Cell Analysis, TWEAK Receptor analysis, COVID-19 virology, Lung cytology, Models, Biological, Organoids cytology, Organoids virology, SARS-CoV-2 physiology, Tissue Culture Techniques
Abstract

The distal lung contains terminal bronchioles and alveoli that facilitate gas exchange. Three-dimensional in vitro human distal lung culture systems would strongly facilitate the investigation of pathologies such as interstitial lung disease, cancer and coronavirus disease 2019 (COVID-19) pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here we describe the development of a long-term feeder-free, chemically defined culture system for distal lung progenitors as organoids derived from single adult human alveolar epithelial type II (AT2) or KRT5 + basal cells. AT2 organoids were able to differentiate into AT1 cells, and basal cell organoids developed lumens lined with differentiated club and ciliated cells. Single-cell analysis of KRT5 + cells in basal organoids revealed a distinct population of ITGA6 + ITGB4 + mitotic cells, whose offspring further segregated into a TNFRSF12A hi subfraction that comprised about ten per cent of KRT5 + basal cells. This subpopulation formed clusters within terminal bronchioles and exhibited enriched clonogenic organoid growth activity. We created distal lung organoids with apical-out polarity to present ACE2 on the exposed external surface, facilitating infection of AT2 and basal cultures with SARS-CoV-2 and identifying club cells as a target population. This long-term, feeder-free culture of human distal lung organoids, coupled with single-cell analysis, identifies functional heterogeneity among basal cells and establishes a facile in vitro organoid model of human distal lung infections, including COVID-19-associated pneumonia.

Published
2020
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43. Causal inference in genetic trio studies.

Author

Bates S, Sesia M, Sabatti C, and Candès E

Subjects
Humans, Genetic Association Studies, Genetic Techniques, Genetic Variation, Heredity, Phenotype
Abstract

We introduce a method to draw causal inferences-inferences immune to all possible confounding-from genetic data that include parents and offspring. Causal conclusions are possible with these data because the natural randomness in meiosis can be viewed as a high-dimensional randomized experiment. We make this observation actionable by developing a conditional independence test that identifies regions of the genome containing distinct causal variants. The proposed digital twin test compares an observed offspring to carefully constructed synthetic offspring from the same parents to determine statistical significance, and it can leverage any black-box multivariate model and additional nontrio genetic data to increase power. Crucially, our inferences are based only on a well-established mathematical model of recombination and make no assumptions about the relationship between the genotypes and phenotypes. We compare our method to the widely used transmission disequilibrium test and demonstrate enhanced power and localization., Competing Interests: The authors declare no competing interest.

Published
2020
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45. Multi-resolution localization of causal variants across the genome.

Author

Sesia M, Katsevich E, Bates S, Candès E, and Sabatti C

Subjects
Algorithms, Chromosome Mapping methods, Datasets as Topic, Feasibility Studies, Humans, Multifactorial Inheritance genetics, Polymorphism, Single Nucleotide genetics, Quantitative Trait Loci genetics, Software, Genome, Human genetics, Genome-Wide Association Study methods, Genomics methods, Linkage Disequilibrium, Models, Genetic
Abstract

In the statistical analysis of genome-wide association data, it is challenging to precisely localize the variants that affect complex traits, due to linkage disequilibrium, and to maximize power while limiting spurious findings. Here we report on KnockoffZoom: a flexible method that localizes causal variants at multiple resolutions by testing the conditional associations of genetic segments of decreasing width, while provably controlling the false discovery rate. Our method utilizes artificial genotypes as negative controls and is equally valid for quantitative and binary phenotypes, without requiring any assumptions about their genetic architectures. Instead, we rely on well-established genetic models of linkage disequilibrium. We demonstrate that our method can detect more associations than mixed effects models and achieve fine-mapping precision, at comparable computational cost. Lastly, we apply KnockoffZoom to data from 350k subjects in the UK Biobank and report many new findings.

Published
2020
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46. Contribution of common and rare variants to bipolar disorder susceptibility in extended pedigrees from population isolates.

Author

Sul JH, Service SK, Huang AY, Ramensky V, Hwang SG, Teshiba TM, Park Y, Ori APS, Zhang Z, Mullins N, Olde Loohuis LM, Fears SC, Araya C, Araya X, Spesny M, Bejarano J, Ramirez M, Castrillón G, Gomez-Makhinson J, Lopez MC, Montoya G, Montoya CP, Aldana I, Escobar JI, Ospina-Duque J, Kremeyer B, Bedoya G, Ruiz-Linares A, Cantor RM, Molina J, Coppola G, Ophoff RA, Macaya G, Lopez-Jaramillo C, Reus V, Bearden CE, Sabatti C, and Freimer NB

Subjects
Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Pedigree, Polymorphism, Single Nucleotide, Bipolar Disorder genetics
Abstract

Current evidence from case/control studies indicates that genetic risk for psychiatric disorders derives primarily from numerous common variants, each with a small phenotypic impact. The literature describing apparent segregation of bipolar disorder (BP) in numerous multigenerational pedigrees suggests that, in such families, large-effect inherited variants might play a greater role. To identify roles of rare and common variants on BP, we conducted genetic analyses in 26 Colombia and Costa Rica pedigrees ascertained for bipolar disorder 1 (BP1), the most severe and heritable form of BP. In these pedigrees, we performed microarray SNP genotyping of 838 individuals and high-coverage whole-genome sequencing of 449 individuals. We compared polygenic risk scores (PRS), estimated using the latest BP1 genome-wide association study (GWAS) summary statistics, between BP1 individuals and related controls. We also evaluated whether BP1 individuals had a higher burden of rare deleterious single-nucleotide variants (SNVs) and rare copy number variants (CNVs) in a set of genes related to BP1. We found that compared with unaffected relatives, BP1 individuals had higher PRS estimated from BP1 GWAS statistics (P = 0.001 ~ 0.007) and displayed modest increase in burdens of rare deleterious SNVs (P = 0.047) and rare CNVs (P = 0.002 ~ 0.033) in genes related to BP1. We did not observe rare variants segregating in the pedigrees. These results suggest that small-to-moderate effect rare and common variants are more likely to contribute to BP1 risk in these extended pedigrees than a few large-effect rare variants.

Published
2020
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47. Genetic regulation of gene expression and splicing during a 10-year period of human aging.

Author

Balliu B, Durrant M, Goede O, Abell N, Li X, Liu B, Gloudemans MJ, Cook NL, Smith KS, Knowles DA, Pala M, Cucca F, Schlessinger D, Jaiswal S, Sabatti C, Lind L, Ingelsson E, and Montgomery SB

Subjects
Aged, Aged, 80 and over, Aging metabolism, Female, Humans, Male, Aging genetics, Alternative Splicing, Gene Expression Regulation
Abstract

Background: Molecular and cellular changes are intrinsic to aging and age-related diseases. Prior cross-sectional studies have investigated the combined effects of age and genetics on gene expression and alternative splicing; however, there has been no long-term, longitudinal characterization of these molecular changes, especially in older age., Results: We perform RNA sequencing in whole blood from the same individuals at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging at a population and individual level. We observe that individuals are more similar to their own expression profiles later in life than profiles of other individuals their own age. We identify 1291 and 294 genes differentially expressed and alternatively spliced with age, as well as 529 genes with outlying individual trajectories. Further, we observe a strong correlation of genetic effects on expression and splicing between the two ages, with a small subset of tested genes showing a reduction in genetic associations with expression and splicing in older age., Conclusions: These findings demonstrate that, although the transcriptome and its genetic regulation is mostly stable late in life, a small subset of genes is dynamic and is characterized by a reduction in genetic regulation, most likely due to increasing environmental variance with age.

Published
2019
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48. Author Correction: Exome sequencing of Finnish isolates enhances rare-variant association power.

Author

Locke AE, Steinberg KM, Chiang CWK, Service SK, Havulinna AS, Stell L, Pirinen M, Abel HJ, Chiang CC, Fulton RS, Jackson AU, Kang CJ, Kanchi KL, Koboldt DC, Larson DE, Nelson J, Nicholas TJ, Pietilä A, Ramensky V, Ray D, Scott LJ, Stringham HM, Vangipurapu J, Welch R, Yajnik P, Yin X, Eriksson JG, Ala-Korpela M, Järvelin MR, Männikkö M, Laivuori H, Dutcher SK, Stitziel NO, Wilson RK, Hall IM, Sabatti C, Palotie A, Salomaa V, Laakso M, Ripatti S, Boehnke M, and Freimer NB

Abstract

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019
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49. Exome sequencing of Finnish isolates enhances rare-variant association power.

Author

Locke AE, Steinberg KM, Chiang CWK, Service SK, Havulinna AS, Stell L, Pirinen M, Abel HJ, Chiang CC, Fulton RS, Jackson AU, Kang CJ, Kanchi KL, Koboldt DC, Larson DE, Nelson J, Nicholas TJ, Pietilä A, Ramensky V, Ray D, Scott LJ, Stringham HM, Vangipurapu J, Welch R, Yajnik P, Yin X, Eriksson JG, Ala-Korpela M, Järvelin MR, Männikkö M, Laivuori H, Dutcher SK, Stitziel NO, Wilson RK, Hall IM, Sabatti C, Palotie A, Salomaa V, Laakso M, Ripatti S, Boehnke M, and Freimer NB

Subjects
Alleles, Cholesterol, HDL genetics, Cluster Analysis, Endpoint Determination, Finland, Geographic Mapping, Humans, Multifactorial Inheritance genetics, Reproducibility of Results, Genetic Association Studies methods, Genetic Predisposition to Disease genetics, Genetic Variation genetics, Quantitative Trait Loci genetics, Exome Sequencing
Abstract

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.

Published
2019
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50. Genetic analyses of diverse populations improves discovery for complex traits.

Author

Wojcik GL, Graff M, Nishimura KK, Tao R, Haessler J, Gignoux CR, Highland HM, Patel YM, Sorokin EP, Avery CL, Belbin GM, Bien SA, Cheng I, Cullina S, Hodonsky CJ, Hu Y, Huckins LM, Jeff J, Justice AE, Kocarnik JM, Lim U, Lin BM, Lu Y, Nelson SC, Park SL, Poisner H, Preuss MH, Richard MA, Schurmann C, Setiawan VW, Sockell A, Vahi K, Verbanck M, Vishnu A, Walker RW, Young KL, Zubair N, Acuña-Alonso V, Ambite JL, Barnes KC, Boerwinkle E, Bottinger EP, Bustamante CD, Caberto C, Canizales-Quinteros S, Conomos MP, Deelman E, Do R, Doheny K, Fernández-Rhodes L, Fornage M, Hailu B, Heiss G, Henn BM, Hindorff LA, Jackson RD, Laurie CA, Laurie CC, Li Y, Lin DY, Moreno-Estrada A, Nadkarni G, Norman PJ, Pooler LC, Reiner AP, Romm J, Sabatti C, Sandoval K, Sheng X, Stahl EA, Stram DO, Thornton TA, Wassel CL, Wilkens LR, Winkler CA, Yoneyama S, Buyske S, Haiman CA, Kooperberg C, Le Marchand L, Loos RJF, Matise TC, North KE, Peters U, Kenny EE, and Carlson CS

Subjects
Body Height genetics, Cohort Studies, Female, Genetics, Medical methods, Health Equity trends, Health Status Disparities, Humans, Male, United States, Black or African American, Asian People genetics, Black People genetics, Genome-Wide Association Study methods, Hispanic or Latino genetics, Minority Groups, Multifactorial Inheritance genetics, Women's Health
Abstract

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry 1-3 . In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific 4-10 . Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations 11,12 . Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions 13 -the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

Published
2019
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