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Henson, R. N., Suri, S., Knights, E., Rowe, J. B., Kievit, R. A., Lyall, D. M., Chan, D., Eising, E., & Fisher, S. E. (2020). Effect of apolipoprotein E polymorphism on cognition and brain in the Cambridge Centre for Ageing and Neuroscience cohort. Brain and Neuroscience Advances, 4: 2398212820961704. doi:10.1177/2398212820961704.
Abstract
Polymorphisms in the apolipoprotein E (APOE) gene have been associated with individual differences in cognition, brain structure and brain function. For example, the ε4 allele has been associated with cognitive and brain impairment in old age and increased risk of dementia, while the ε2 allele has been claimed to be neuroprotective. According to the ‘antagonistic pleiotropy’ hypothesis, these polymorphisms have different effects across the lifespan, with ε4, for example, postulated to confer benefits on cognitive and brain functions earlier in life. In this stage 2 of the Registered Report – https://osf.io/bufc4, we report the results from the cognitive and brain measures in the Cambridge Centre for Ageing and Neuroscience cohort (www.cam-can.org). We investigated the antagonistic pleiotropy hypothesis by testing for allele-by-age interactions in approximately 600 people across the adult lifespan (18–88 years), on six outcome variables related to cognition, brain structure and brain function (namely, fluid intelligence, verbal memory, hippocampal grey-matter volume, mean diffusion within white matter and resting-state connectivity measured by both functional magnetic resonance imaging and magnetoencephalography). We found no evidence to support the antagonistic pleiotropy hypothesis. Indeed, Bayes factors supported the null hypothesis in all cases, except for the (linear) interaction between age and possession of the ε4 allele on fluid intelligence, for which the evidence for faster decline in older ages was ambiguous. Overall, these pre-registered analyses question the antagonistic pleiotropy of APOE polymorphisms, at least in healthy adults.Additional information
supplementary material -
Thompson, P. A., Bishop, D. V. M., Eising, E., Fisher, S. E., & Newbury, D. F. (2020). Generalized Structured Component Analysis in candidate gene association studies: Applications and limitations [version 2; peer review: 3 approved]. Wellcome Open Research, 4: 142. doi:10.12688/wellcomeopenres.15396.2.
Abstract
Background: Generalized Structured Component Analysis (GSCA) is a component-based alternative to traditional covariance-based structural equation modelling. This method has previously been applied to test for association between candidate genes and clinical phenotypes, contrasting with traditional genetic association analyses that adopt univariate testing of many individual single nucleotide polymorphisms (SNPs) with correction for multiple testing.
Methods: We first evaluate the ability of the GSCA method to replicate two previous findings from a genetics association study of developmental language disorders. We then present the results of a simulation study to test the validity of the GSCA method under more restrictive data conditions, using smaller sample sizes and larger numbers of SNPs than have previously been investigated. Finally, we compare GSCA performance against univariate association analysis conducted using PLINK v1.9.
Results: Results from simulations show that power to detect effects depends not just on sample size, but also on the ratio of SNPs with effect to number of SNPs tested within a gene. Inclusion of many SNPs in a model dilutes true effects.
Conclusions: We propose that GSCA is a useful method for replication studies, when candidate SNPs have been identified, but should not be used for exploratory analysis.Additional information
data via OSF -
Van der Meer, D., Sønderby, I. E., Kaufmann, T., Walters, G. B., Abdellaoui, A., Ames, D., Amunts, K., Andersson, M., Armstrong, N. J., Bernard, M., Blackburn, N. B., Blangero, J., Boomsma, D. I., Brodaty, H., Brouwer, R. M., Bülow, R., Cahn, W., Calhoun, V. D., Caspers, S., Cavalleri, G. L. and 112 moreVan der Meer, D., Sønderby, I. E., Kaufmann, T., Walters, G. B., Abdellaoui, A., Ames, D., Amunts, K., Andersson, M., Armstrong, N. J., Bernard, M., Blackburn, N. B., Blangero, J., Boomsma, D. I., Brodaty, H., Brouwer, R. M., Bülow, R., Cahn, W., Calhoun, V. D., Caspers, S., Cavalleri, G. L., Ching, C. R. K., Cichon, S., Ciufolini, S., Corvin, A., Crespo-Facorro, B., Curran, J. E., Dalvie, S., Dazzan, P., De Geus, E. J. C., De Zubicaray, G. I., De Zwarte, S. M. C., Delanty, N., Den Braber, A., Desrivieres, S., Di Forti, M., Doherty, J. L., Donohoe, G., Ehrlich, S., Eising, E., Espeseth, T., Fisher, S. E., Fladby, T., Frei, O., Frouin, V., Fukunaga, M., Gareau, T., Glahn, D. C., Grabe, H. J., Groenewold, N. A., Gústafsson, Ó., Haavik, J., Haberg, A. K., Hashimoto, R., Hehir-Kwa, J. Y., Hibar, D. P., Hillegers, M. H. J., Hoffmann, P., Holleran, L., Hottenga, J.-J., Hulshoff Pol, H. E., Ikeda, M., Jacquemont, S., Jahanshad, N., Jockwitz, C., Johansson, S., Jönsson, E. G., Kikuchi, M., Knowles, E. E. M., Kwok, J. B., Le Hellard, S., Linden, D. E. J., Liu, J., Lundervold, A., Lundervold, A. J., Martin, N. G., Mather, K. A., Mathias, S. R., McMahon, K. L., McRae, A. F., Medland, S. E., Moberget, T., Moreau, C., Morris, D. W., Mühleisen, T. W., Murray, R. M., Nordvik, J. E., Nyberg, L., Olde Loohuis, L. M., Ophoff, R. A., Owen, M. J., Paus, T., Pausova, Z., Peralta, J. M., Pike, B., Prieto, C., Quinlan, E. B., Reinbold, C. S., Reis Marques, T., Rucker, J. J. H., Sachdev, P. S., Sando, S. B., Schofield, P. R., Schork, A. J., Schumann, G., Shin, J., Shumskaya, E., Silva, A. I., Sisodiya, S. M., Steen, V. M., Stein, D. J., Strike, L. T., Tamnes, C. K., Teumer, A., Thalamuthu, A., Tordesillas-Gutiérrez, D., Uhlmann, A., Úlfarsson, M. Ö., Van 't Ent, D., Van den Bree, M. B. M., Vassos, E., Wen, W., Wittfeld, K., Wright, M. J., Zayats, T., Dale, A. M., Djurovic, S., Agartz, I., Westlye, L. T., Stefánsson, H., Stefánsson, K., Thompson, P. M., & Andreassen, O. A. (2020). Association of copy number variation of the 15q11.2 BP1-BP2 region with cortical and subcortical morphology and cognition. JAMA Psychiatry, 77(4), 420-430. doi:10.1001/jamapsychiatry.2019.3779.
Abstract
Importance Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities.
Objective To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance.
Design, Setting, and Participants In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019.
Main Outcomes and Measures The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort.
Results Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = −0.41; SE, 0.08; P = 4.9 × 10−8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10−7), and a smaller nucleus accumbens (Cohen d = −0.27; SE, 0.07; P = 7.3 × 10−5). There was also a significant negative dose response on cortical thickness (β = −0.24; SE, 0.05; P = 6.8 × 10−7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks.
Conclusions and Relevance These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders. -
Winsvold, B. S., Palta, P., Eising, E., Page, C. M., The International Headache Genetics Consortium, Van den Maagdenberg, A. M. J. M., Palotie, A., & Zwart, J.-A. (2018). Epigenetic DNA methylation changes associated with headache chronification: A retrospective case-control study. Cephalalgia, 38(2), 312-322. doi:10.1177/0333102417690111.
Abstract
Background
The biological mechanisms of headache chronification are poorly understood. We aimed to identify changes in DNA methylation associated with the transformation from episodic to chronic headache.
Methods
Participants were recruited from the population-based Norwegian HUNT Study. Thirty-six female headache patients who transformed from episodic to chronic headache between baseline and follow-up 11 years later were matched against 35 controls with episodic headache. DNA methylation was quantified at 485,000 CpG sites, and changes in methylation level at these sites were compared between cases and controls by linear regression analysis. Data were analyzed in two stages (Stages 1 and 2) and in a combined meta-analysis.
Results
None of the top 20 CpG sites identified in Stage 1 replicated in Stage 2 after multiple testing correction. In the combined meta-analysis the strongest associated CpG sites were related to SH2D5 and NPTX2, two brain-expressed genes involved in the regulation of synaptic plasticity. Functional enrichment analysis pointed to processes including calcium ion binding and estrogen receptor pathways.
Conclusion
In this first genome-wide study of DNA methylation in headache chronification several potentially implicated loci and processes were identified. The study exemplifies the use of prospectively collected population cohorts to search for epigenetic mechanisms of disease -
Eising, E., Huisman, S. M., Mahfouz, A., Vijfhuizen, L. S., Anttila, V., Winsvold, B. S., Kurth, T., Ikram, M. A., Freilinger, T., Kaprio, J., Boomsma, D. I., van Duijn, C. M., Järvelin, M.-R.-R., Zwart, J.-A., Quaye, L., Strachan, D. P., Kubisch, C., Dichgans, M., Davey Smith, G., Stefansson, K. and 9 moreEising, E., Huisman, S. M., Mahfouz, A., Vijfhuizen, L. S., Anttila, V., Winsvold, B. S., Kurth, T., Ikram, M. A., Freilinger, T., Kaprio, J., Boomsma, D. I., van Duijn, C. M., Järvelin, M.-R.-R., Zwart, J.-A., Quaye, L., Strachan, D. P., Kubisch, C., Dichgans, M., Davey Smith, G., Stefansson, K., Palotie, A., Chasman, D. I., Ferrari, M. D., Terwindt, G. M., de Vries, B., Nyholt, D. R., Lelieveldt, B. P., van den Maagdenberg, A. M., & Reinders, M. J. (2016). Gene co‑expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS‑based study using the Allen Human Brain Atlas. Human Genetics, 135(4), 425-439. doi:10.1007/s00439-016-1638-x.
Abstract
Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology. -
Eising, E., De Leeuw, C., Min, J. L., Anttila, V., Verheijen, M. H. G., Terwindt, G. M., Dichgans, M., Freilinger, T., Kubisch, C., Ferrari, M. D., Smit, A. B., De Vries, B., Palotie, A., Van Den Maagdenberg, A. M. J. M., & Posthuma, D. (2016). Involvement of astrocyte and oligodendrocyte gene sets in migraine. Cephalalgia, 36(7), 640-647. doi:10.1177/0333102415618614.
Abstract
Migraine is a common episodic brain disorder characterized by recurrent attacks of severe unilateral headache and additional neurological symptoms. Two main migraine types can be distinguished based on the presence of aura symptoms that can accompany the headache: migraine with aura and migraine without aura. Multiple genetic and environmental factors confer disease susceptibility. Recent genome-wide association studies (GWAS) indicate that migraine susceptibility genes are involved in various pathways, including neurotransmission, which have already been implicated in genetic studies of monogenic familial hemiplegic migraine, a subtype of migraine with aura. Methods To further explore the genetic background of migraine, we performed a gene set analysis of migraine GWAS data of 4954 clinic-based patients with migraine, as well as 13,390 controls. Curated sets of synaptic genes and sets of genes predominantly expressed in three glial cell types (astrocytes, microglia and oligodendrocytes) were investigated. Discussion Our results show that gene sets containing astrocyte- and oligodendrocyte-related genes are associated with migraine, which is especially true for gene sets involved in protein modification and signal transduction. Observed differences between migraine with aura and migraine without aura indicate that both migraine types, at least in part, seem to have a different genetic background. -
Zhao, H., Eising, E., de Vries, B., Vijfhuizen, L. S., Anttila, V., Winswold, B. S., Kurth, T., Stefansson, H., Kallela, M., Malik, R., Stam, A. H., Afran Ikram, M., Ligthart, L., Freilinger, T., Alexander, M., Müller-Myhsok, B., Schreiber, S., Meilinger, T., Aromas, A., Eriksson, J. G. and 15 moreZhao, H., Eising, E., de Vries, B., Vijfhuizen, L. S., Anttila, V., Winswold, B. S., Kurth, T., Stefansson, H., Kallela, M., Malik, R., Stam, A. H., Afran Ikram, M., Ligthart, L., Freilinger, T., Alexander, M., Müller-Myhsok, B., Schreiber, S., Meilinger, T., Aromas, A., Eriksson, J. G., Boomsma, D. I., van Duijn, C. M., Anker Zwart, J., Quaye, L., Kubisch, C., Dichgans, M., Wessman, M., Stefansson, K., Chasman, D. I., Palotie, A., Martin, N. G., Montgomery, G. W., Ferrari, M. D., van den Maagdenberg, A. M., & Nyholt, D. R. (2016). Gene-based pleiotropy across migraine with aura and migraine without aura patient groups. Cephalalgia, 36(7), 648-657. doi:10.1177/0333102415591497.
Abstract
Introduction It is unclear whether patients diagnosed according to International Classification of Headache Disorders criteria for migraine with aura (MA) and migraine without aura (MO) experience distinct disorders or whether their migraine subtypes are genetically related. Aim Using a novel gene-based (statistical) approach, we aimed to identify individual genes and pathways associated both with MA and MO. Methods Gene-based tests were performed using genome-wide association summary statistic results from the most recent International Headache Genetics Consortium study comparing 4505 MA cases with 34,813 controls and 4038 MO cases with 40,294 controls. After accounting for non-independence of gene-based test results, we examined the significance of the proportion of shared genes associated with MA and MO. Results We found a significant overlap in genes associated with MA and MO. Of the total 1514 genes with a nominally significant gene-based p value (pgene-based ≤ 0.05) in the MA subgroup, 107 also produced pgene-based ≤ 0.05 in the MO subgroup. The proportion of overlapping genes is almost double the empirically derived null expectation, producing significant evidence of gene-based overlap (pleiotropy) (pbinomial-test = 1.5 × 10–4). Combining results across MA and MO, six genes produced genome-wide significant gene-based p values. Four of these genes (TRPM8, UFL1, FHL5 and LRP1) were located in close proximity to previously reported genome-wide significant SNPs for migraine, while two genes, TARBP2 and NPFF separated by just 259 bp on chromosome 12q13.13, represent a novel risk locus. The genes overlapping in both migraine types were enriched for functions related to inflammation, the cardiovascular system and connective tissue. Conclusions Our results provide novel insight into the likely genes and biological mechanisms that underlie both MA and MO, and when combined with previous data, highlight the neuropeptide FF-amide peptide encoding gene (NPFF) as a novel candidate risk gene for both types of migraine.
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