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Petrovska J, Coynel D, Freytag V, de Quervain DJF, Papassotiropoulos A. Polygenic susceptibility for multiple sclerosis is associated with working memory in low-performing young adults. J Neurol Sci 2024; 463:123138. [PMID: 39059048 DOI: 10.1016/j.jns.2024.123138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 07/11/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024]
Abstract
BACKGROUND Multiple sclerosis (MS) is a complex disease with substantial heritability estimates. Besides typical clinical manifestations such as motor and sensory deficits, MS is characterized by structural and functional brain abnormalities, and by cognitive impairment such as decreased working memory (WM) performance. OBJECTIVES We investigated the possible link between the polygenic risk for MS and WM performance in healthy adults (18-35 years). Additionally, we addressed the relationship between polygenic risk for MS and white matter fractional anisotropy (FA). METHODS We generated a polygenic risk score (PRS) of MS susceptibility and investigated its association with WM performance in 3282 healthy adults (two subsamples, N1 = 1803, N2 = 1479). The association between MS-PRS and FA was studied in the second subsample. MS severity PRS associations were also investigated for the WM and FA measurements. RESULTS MS-PRS was significantly associated with WM performance within the 10% lowest WM-performing individuals (p = 0.001; pFDR = 0.018). It was not significantly associated with any of the investigated FA measurements. MS severity PRS was significantly associated with brain-wide mean FA (p = 0.041) and showed suggestive associations with additional FA measurements. CONCLUSIONS By identifying a genetic link between MS and WM performance this study contributes to the understanding of the genetic complexity of MS, and hopefully to the possible identification of molecular pathways linked to cognitive deficits in MS. It also contributes to the understanding of genetic associations with MS severity, as these associations seem to involve distinct biological pathways compared to genetic variants linked to the overall risk of developing MS.
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Affiliation(s)
- J Petrovska
- Division of Molecular Neuroscience, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland.
| | - D Coynel
- Division of Cognitive Neuroscience, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland
| | - V Freytag
- Division of Molecular Neuroscience, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland
| | - D J-F de Quervain
- Division of Cognitive Neuroscience, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland
| | - A Papassotiropoulos
- Division of Molecular Neuroscience, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, CH-4055 Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland
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Lin Z, Si Y, Kang J. LATENT SUBGROUP IDENTIFICATION IN IMAGE-ON-SCALAR REGRESSION. Ann Appl Stat 2024; 18:468-486. [PMID: 38846637 PMCID: PMC11156244 DOI: 10.1214/23-aoas1797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024]
Abstract
Image-on-scalar regression has been a popular approach to modeling the association between brain activities and scalar characteristics in neuroimaging research. The associations could be heterogeneous across individuals in the population, as indicated by recent large-scale neuroimaging studies, for example, the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD data can inform our understanding of heterogeneous associations and how to leverage the heterogeneity and tailor interventions to increase the number of youths who benefit. It is of great interest to identify subgroups of individuals from the population such that: (1) within each subgroup the brain activities have homogeneous associations with the clinical measures; (2) across subgroups the associations are heterogeneous, and (3) the group allocation depends on individual characteristics. Existing image-on-scalar regression methods and clustering methods cannot directly achieve this goal. We propose a latent subgroup image-on-scalar regression model (LASIR) to analyze large-scale, multisite neuroimaging data with diverse sociode-mographics. LASIR introduces the latent subgroup for each individual and group-specific, spatially varying effects, with an efficient stochastic expectation maximization algorithm for inferences. We demonstrate that LASIR outperforms existing alternatives for subgroup identification of brain activation patterns with functional magnetic resonance imaging data via comprehensive simulations and applications to the ABCD study. We have released our reproducible codes for public use with the software package available on Github.
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Affiliation(s)
- Zikai Lin
- Department of Biostatistics, University of Michigan
| | - Yajuan Si
- Survey Research Center, Institute for Social Research, University of Michigan
| | - Jian Kang
- Department of Biostatistics, University of Michigan
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Geissmann L, Coynel D, Papassotiropoulos A, de Quervain DJF. Neurofunctional underpinnings of individual differences in visual episodic memory performance. Nat Commun 2023; 14:5694. [PMID: 37709747 PMCID: PMC10502056 DOI: 10.1038/s41467-023-41380-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 09/01/2023] [Indexed: 09/16/2023] Open
Abstract
Episodic memory, the ability to consciously recollect information and its context, varies substantially among individuals. While prior fMRI studies have identified certain brain regions linked to successful memory encoding at a group level, their role in explaining individual memory differences remains largely unexplored. Here, we analyze fMRI data of 1,498 adults participating in a picture encoding task in a single MRI scanner. We find that individual differences in responsivity of the hippocampus, orbitofrontal cortex, and posterior cingulate cortex account for individual variability in episodic memory performance. While these regions also emerge in our group-level analysis, other regions, predominantly within the lateral occipital cortex, are related to successful memory encoding but not to individual memory variation. Furthermore, our network-based approach reveals a link between the responsivity of nine functional connectivity networks and individual memory variability. Our work provides insights into the neurofunctional correlates of individual differences in visual episodic memory performance.
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Affiliation(s)
- Léonie Geissmann
- Division of Cognitive Neuroscience, Department of Biomedicine, University of Basel, Basel, Switzerland.
- Research Cluster Molecular and Cognitive Neurosciences, University of Basel, Basel, Switzerland.
| | - David Coynel
- Division of Cognitive Neuroscience, Department of Biomedicine, University of Basel, Basel, Switzerland
- Research Cluster Molecular and Cognitive Neurosciences, University of Basel, Basel, Switzerland
| | - Andreas Papassotiropoulos
- Research Cluster Molecular and Cognitive Neurosciences, University of Basel, Basel, Switzerland
- Division of Molecular Neuroscience, Department of Biomedicine, University of Basel, Basel, Switzerland
- University Psychiatric Clinics, University of Basel, Basel, Switzerland
| | - Dominique J F de Quervain
- Division of Cognitive Neuroscience, Department of Biomedicine, University of Basel, Basel, Switzerland.
- Research Cluster Molecular and Cognitive Neurosciences, University of Basel, Basel, Switzerland.
- University Psychiatric Clinics, University of Basel, Basel, Switzerland.
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4
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Oscoz-Irurozqui M, Almodóvar-Payá C, Guardiola-Ripoll M, Guerrero-Pedraza A, Hostalet N, Salvador R, Carrión MI, Maristany T, Pomarol-Clotet E, Fatjó-Vilas M. Cannabis Use and Endocannabinoid Receptor Genes: A Pilot Study on Their Interaction on Brain Activity in First-Episode Psychosis. Int J Mol Sci 2023; 24:ijms24087501. [PMID: 37108689 PMCID: PMC10142622 DOI: 10.3390/ijms24087501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 04/29/2023] Open
Abstract
The role of both cannabis use and genetic background has been shown in the risk for psychosis. However, the effect of the interplay between cannabis and variability at the endocannabinoid receptor genes on the neurobiological underpinnings of psychosis remains inconclusive. Through a case-only design, including patients with a first-episode of psychosis (n = 40) classified as cannabis users (50%) and non-users (50%), we aimed to evaluate the interaction between cannabis use and common genetic variants at the endocannabinoid receptor genes on brain activity. Genetic variability was assessed by genotyping two Single Nucleotide Polymorphisms (SNP) at the cannabinoid receptor type 1 gene (CNR1; rs1049353) and cannabinoid receptor type 2 gene (CNR2; rs2501431). Functional Magnetic Resonance Imaging (fMRI) data were obtained while performing the n-back task. Gene × cannabis interaction models evidenced a combined effect of CNR1 and CNR2 genotypes and cannabis use on brain activity in different brain areas, such as the caudate nucleus, the cingulate cortex and the orbitofrontal cortex. These findings suggest a joint role of cannabis use and cannabinoid receptor genetic background on brain function in first-episode psychosis, possibly through the impact on brain areas relevant to the reward circuit.
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Affiliation(s)
- Maitane Oscoz-Irurozqui
- FIDMAG Germanes Hospitalàries Research Foundation, Av Jordà 8, 08035 Barcelona, Spain
- Centro de Salud Mental Errenteria-Osakidetza, Av Galtzaraborda 69-75, 20100 Errenteria, Guipúzcoa, Spain
| | - Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, Av Jordà 8, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av Monforte de Lemos, 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | - Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, Av Jordà 8, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av Monforte de Lemos, 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Av Jordà 8, 08035 Barcelona, Spain
- Hospital Benito Menni CASM, C/Doctor Antoni Pujadas 38, 08830 Sant Boi de Llobregat, Barcelona, Spain
| | - Noemí Hostalet
- FIDMAG Germanes Hospitalàries Research Foundation, Av Jordà 8, 08035 Barcelona, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Av Jordà 8, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av Monforte de Lemos, 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | | | - Teresa Maristany
- Diagnostic Imaging Department, Hospital Sant Joan de Déu Research Foundation, Passeig de Sant Joan de Déu, 2, 08950 Esplugues de Llobregat, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Av Jordà 8, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av Monforte de Lemos, 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, Av Jordà 8, 08035 Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Av Monforte de Lemos, 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Avinguda Diagonal, 643, 08028 Barcelona, Spain
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5
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Guardiola-Ripoll M, Almodóvar-Payá C, Lubeiro A, Sotero A, Salvador R, Fuentes-Claramonte P, Salgado-Pineda P, Papiol S, Ortiz-Gil J, Gomar JJ, Guerrero-Pedraza A, Sarró S, Maristany T, Molina V, Pomarol-Clotet E, Fatjó-Vilas M. A functional neuroimaging association study on the interplay between two schizophrenia genome-wide associated genes (CACNA1C and ZNF804A). Eur Arch Psychiatry Clin Neurosci 2022; 272:1229-1239. [PMID: 35796825 DOI: 10.1007/s00406-022-01447-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 06/07/2022] [Indexed: 12/23/2022]
Abstract
The CACNA1C and the ZNF804A genes are among the most relevant schizophrenia GWAS findings. Recent evidence shows that the interaction of these genes with the schizophrenia diagnosis modulates brain functional response to a verbal fluency task. To better understand how these genes might influence the risk for schizophrenia, we aimed to study the interplay between CACNA1C and ZNF804A on working memory brain functional correlates. The analyses included functional and behavioural N-back task data (obtained from an fMRI protocol) and CACNA1C-rs1006737 and ZNF804A-rs1344706 genotypes for 78 healthy subjects and 78 patients with schizophrenia (matched for age, sex and premorbid IQ). We tested the effects of the epistasis between these genes as well as of the three-way interaction (CACNA1C × ZNAF804A × diagnosis) on working memory-associated activity (N-back: 2-back vs 1-back). We detected a significant CACNA1C × ZNAF804A interaction on working memory functional response in regions comprising the ventral caudate medially and within the left hemisphere, the superior and inferior orbitofrontal gyrus, the superior temporal pole and the ventral-anterior insula. The individuals with the GWAS-identified risk genotypes (CACNA1C-AA/AG and ZNF804A-AA) displayed a reduced working memory modulation response. This genotypic combination was also associated with opposite brain activity patterns between patients and controls. While further research will help to comprehend the neurobiological mechanisms of this interaction, our data highlight the role of the epistasis between CACNA1C and ZNF804A in the functional mechanisms underlying the pathophysiology of schizophrenia.
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Affiliation(s)
- Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Alba Lubeiro
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
| | - Alejandro Sotero
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Sergi Papiol
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry, University Hospital, Ludwig Maximilian University, Munich, Germany
| | - Jordi Ortiz-Gil
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
- Hospital General de Granollers, Barcelona, Spain
| | - Jesús J Gomar
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- The Litwin-Zucker Alzheimer's Research Center, Manhasset, NY, USA
| | | | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Teresa Maristany
- Diagnostic Imaging Department, Hospital Sant Joan de Déu Research Foundation, Barcelona, Spain
| | - Vicente Molina
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
- Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain
- Psychiatry Service, University Hospital of Valladolid, Valladolid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain.
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain.
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain.
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona, Barcelona, Spain.
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6
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Almodóvar-Payá C, Guardiola-Ripoll M, Giralt-López M, Gallego C, Salgado-Pineda P, Miret S, Salvador R, Muñoz MJ, Lázaro L, Guerrero-Pedraza A, Parellada M, Carrión MI, Cuesta MJ, Maristany T, Sarró S, Fañanás L, Callado LF, Arias B, Pomarol-Clotet E, Fatjó-Vilas M. NRN1 Gene as a Potential Marker of Early-Onset Schizophrenia: Evidence from Genetic and Neuroimaging Approaches. Int J Mol Sci 2022; 23:ijms23137456. [PMID: 35806464 PMCID: PMC9267632 DOI: 10.3390/ijms23137456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 12/10/2022] Open
Abstract
Included in the neurotrophins family, the Neuritin 1 gene (NRN1) has emerged as an attractive candidate gene for schizophrenia (SZ) since it has been associated with the risk for the disorder and general cognitive performance. In this work, we aimed to further investigate the association of NRN1 with SZ by exploring its role on age at onset and its brain activity correlates. First, we developed two genetic association analyses using a family-based sample (80 early-onset (EO) trios (offspring onset ≤ 18 years) and 71 adult-onset (AO) trios) and an independent case–control sample (120 healthy subjects (HS), 87 EO and 138 AO patients). Second, we explored the effect of NRN1 on brain activity during a working memory task (N-back task; 39 HS, 39 EO and 39 AO; matched by age, sex and estimated IQ). Different haplotypes encompassing the same three Single Nucleotide Polymorphisms(SNPs, rs3763180–rs10484320–rs4960155) were associated with EO in the two samples (GCT, TCC and GTT). Besides, the GTT haplotype was associated with worse N-back task performance in EO and was linked to an inefficient dorsolateral prefrontal cortex activity in subjects with EO compared to HS. Our results show convergent evidence on the NRN1 association with EO both from genetic and neuroimaging approaches, highlighting the role of neurotrophins in the pathophysiology of SZ.
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Affiliation(s)
- Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Maria Giralt-López
- Departament de Psiquiatria, Hospital Universitari Germans Trias i Pujol (HUGTP), 08916 Badalona, Barcelona, Spain;
- Departament de Psiquiatria i Medicina Legal, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Barcelona, Spain
| | - Carme Gallego
- Department of Cell Biology, Molecular Biology Institute of Barcelona (IBMB-CSIC), 08028 Barcelona, Barcelona, Spain;
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Salvador Miret
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Centre de Salut Mental d’Adults de Lleida, Servei de Psiquiatria, Salut Mental i Addiccions, Hospital Universitari Santa Maria de Lleida, 25198 Lleida, Lleida, Spain
- Institut de Recerca Biomèdica (IRB), 25198 Lleida, Lleida, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - María J. Muñoz
- Complex Assistencial en Salut Mental Benito Menni, 08830 Sant Boi de Llobregat, Barcelona, Spain;
| | - Luisa Lázaro
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic de Barcelona, 08036 Barcelona, Barcelona, Spain
- Departament de Medicina, Universitat de Barcelona (UB), 08036 Barcelona, Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Barcelona, Spain
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Complex Assistencial en Salut Mental Benito Menni, 08830 Sant Boi de Llobregat, Barcelona, Spain;
| | - Mara Parellada
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Servicio de Psiquiatría del Niño y del Adolescente, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Madrid, Spain
- Instituto de Investigación Sanitaria del Hospital Gregorio Marañón (IiSGM), 28007 Madrid, Madrid, Spain
- Departamento de Psiquiatría, Facultad de Medicina, Universidad Complutense, 28040 Madrid, Madrid, Spain
| | | | - Manuel J. Cuesta
- Servicio de Psiquiatría, Hospital Universitario de Navarra, 31008 Pamplona, Navarra, Spain;
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), 31008 Pamplona, Navarra, Spain
| | - Teresa Maristany
- Departament de Diagnòstic per la Imatge, Hospital Sant Joan de Déu Fundació de Recerca, 08950 Esplugues de Llobregat, Barcelona, Spain;
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Lourdes Fañanás
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028 Barcelona, Barcelona, Spain
| | - Luis F. Callado
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Department of Pharmacology, University of the Basque Country, UPV/EHU, 48940 Leioa, Bizkaia, Spain
- Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Bizkaia, Spain
| | - Bárbara Arias
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028 Barcelona, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Correspondence: (E.P.-C.); (M.F.-V.)
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Correspondence: (E.P.-C.); (M.F.-V.)
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7
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Guardiola-Ripoll M, Almodóvar-Payá C, Lubeiro A, Salvador R, Salgado-Pineda P, Gomar JJ, Guerrero-Pedraza A, Sarró S, Maristany T, Fernández-Linsenbarth I, Hernández-García M, Papiol S, Molina V, Pomarol-Clotet E, Fatjó-Vilas M. New insights of the role of the KCNH2 gene in schizophrenia: An fMRI case-control study. Eur Neuropsychopharmacol 2022; 60:38-47. [PMID: 35635995 DOI: 10.1016/j.euroneuro.2022.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 04/14/2022] [Accepted: 04/19/2022] [Indexed: 11/04/2022]
Abstract
The KCNH2 gene, encoding for a subunit of a voltage-gated potassium channel, has been identified as a key element of neuronal excitability and a promising novel therapeutic target for schizophrenia (SZ). Nonetheless, evidence highlighting the role of KCNH2 on cognitive and brain activity phenotypes comes mainly from studies based on healthy controls (HC). Therefore, we aimed to study the role of KCNH2 on the brain functional differences between patients with SZ and HC. The fMRI sample comprised 78 HC and 79 patients with SZ (matched for age, sex and premorbid IQ). We studied the effect of the polymorphism KCNH2-rs3800779 on attention and working memory-related brain activity, evaluated through the N-back task, in regions with detected diagnostic differences (regression model, controlled for age, sex and premorbid IQ, FEAT-FSL). We report a significant diagnosis x KCNH2 interaction on brain activity (1-back vs baseline contrast) at the medial superior prefrontal cortex (Zmax=3.55, p = 0.00861). In this region, patients with SZ carrying the risk genotype (AA) show a deactivation failure, while HC depict the opposite pattern towards deactivation. The brain region with significant diagnosis x KCNH2 interaction has been previously associated with SZ. The results of this study, in which the role of KCNH2 on fMRI response is analysed for the first time in patients, suggest that KCNH2 variability contributes to inefficient brain activity modulation during the N-back task in affected subjects. These data may pave the way to further understand how KCNH2 genetic variability is related to the pathophysiological mechanisms underlying schizophrenia.
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Affiliation(s)
- Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Alba Lubeiro
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Jesús J Gomar
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; The Litwin-Zucker Alzheimer's Research Center, NY, United States
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital Benito Menni-CASM, Sant Boi de Llobregat, Barcelona, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Teresa Maristany
- Diagnostic Imaging Department, Hospital Sant Joan de Déu Research Foundation, Barcelona, Spain
| | | | - Marta Hernández-García
- Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain
| | - Sergi Papiol
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain; Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany; Department of Psychiatry, University Hospital, Ludwig Maximilian University, Munich Germany
| | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain; Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain; Psychiatry Service, University Hospital of Valladolid, Valladolid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain.
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain; Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona; Barcelona, Spain.
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8
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Combining fMRI and DISC1 gene haplotypes to understand working memory-related brain activity in schizophrenia. Sci Rep 2022; 12:7351. [PMID: 35513527 PMCID: PMC9072540 DOI: 10.1038/s41598-022-10660-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 04/11/2022] [Indexed: 11/30/2022] Open
Abstract
The DISC1 gene is one of the most relevant susceptibility genes for psychosis. However, the complex genetic landscape of this locus, which includes protective and risk variants in interaction, may have hindered consistent conclusions on how DISC1 contributes to schizophrenia (SZ) liability. Analysis from haplotype approaches and brain-based phenotypes can contribute to understanding DISC1 role in the neurobiology of this disorder. We assessed the brain correlates of DISC1 haplotypes associated with SZ through a functional neuroimaging genetics approach. First, we tested the association of two DISC1 haplotypes, the HEP1 (rs6675281-1000731-rs999710) and the HEP3 (rs151229-rs3738401), with the risk for SZ in a sample of 138 healthy subjects (HS) and 238 patients. This approach allowed the identification of three haplotypes associated with SZ (HEP1-CTG, HEP3-GA and HEP3-AA). Second, we explored whether these haplotypes exerted differential effects on n-back associated brain activity in a subsample of 70 HS compared to 70 patients (diagnosis × haplotype interaction effect). These analyses evidenced that HEP3-GA and HEP3-AA modulated working memory functional response conditional to the health/disease status in the cuneus, precuneus, middle cingulate cortex and the ventrolateral and dorsolateral prefrontal cortices. Our results are the first to show a diagnosis-based effect of DISC1 haplotypes on working memory-related brain activity, emphasising its role in SZ.
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Dimitriadis SI, Lancaster TM, Perry G, Tansey KE, Jones DK, Singh KD, Zammit S, Smith GD, Hall J, O'Donovan MC, Owen MJ, Linden DE. Global Brain Flexibility During Working Memory Is Reduced in a High-Genetic-Risk Group for Schizophrenia. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 6:1176-1184. [PMID: 33524599 PMCID: PMC7613444 DOI: 10.1016/j.bpsc.2021.01.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 01/07/2021] [Accepted: 01/09/2021] [Indexed: 10/22/2022]
Abstract
BACKGROUND Altered functional brain connectivity has been proposed as an intermediate phenotype between genetic risk loci and clinical expression of schizophrenia. Genetic high-risk groups of healthy subjects are particularly suited for the investigation of this proposition because they can be tested in the absence of medication or other secondary effects of schizophrenia. METHODS Here, we applied dynamic functional connectivity analysis to functional magnetic resonance imaging data to reveal the reconfiguration of brain networks during a cognitive task. We recruited healthy carriers of common risk variants using the recall-by-genotype design. We assessed 197 individuals: 99 individuals (52 female, 47 male) with low polygenic risk scores (schizophrenia risk profile scores [SCZ-PRSs]) and 98 individuals (52 female, 46 male) with high SCZ-PRSs from both tails of the SCZ-PRS distribution from a genotyped population cohort, the Avon Longitudinal Study of Parents and Children (N = 8169). We compared groups both on conventional brain activation profiles, using the general linear model of the experiment, and on the neural flexibility index, which quantifies how frequent a brain region's community affiliation changes over experimental time. RESULTS Behavioral performance and standard brain activation profiles did not differ significantly between groups. High SCZ-PRS was associated with reduced flexibility index and network modularity across n-back levels. The whole-brain flexibility index and that of the frontoparietal working memory network was associated with n-back performance. We identified a dynamic network phenotype related to high SCZ-PRS. CONCLUSIONS Such neurophysiological markers can become important for the elucidation of biological mechanisms of schizophrenia and, particularly, the associated cognitive deficit.
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Affiliation(s)
- Stavros I Dimitriadis
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom; Neuroinformatics Group, School of Psychology, Cardiff University, Cardiff, United Kingdom.
| | - Thomas M Lancaster
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom; School of Psychology, Bath University, Bath, United Kingdom
| | - Gavin Perry
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Katherine E Tansey
- MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Krish D Singh
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Stanley Zammit
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jeremy Hall
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michael C O'Donovan
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michael J Owen
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - David E Linden
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom; MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, United Kingdom; School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
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10
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The role of neural load effects in predicting individual differences in working memory function. Neuroimage 2021; 245:118656. [PMID: 34678433 PMCID: PMC8880845 DOI: 10.1016/j.neuroimage.2021.118656] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 09/18/2021] [Accepted: 10/11/2021] [Indexed: 12/02/2022] Open
Abstract
Studies of working memory (WM) function have tended to adopt either a within-subject approach, focusing on effects of load manipulations, or a between-subjects approach, focusing on individual differences. This dichotomy extends to WM neuroimaging studies, with different neural correlates being identified for within- and between-subjects variation in WM. Here, we examined this issue in a systematic fashion, leveraging the large-sample Human Connectome Project dataset, to conduct a well-powered, whole-brain analysis of the N-back WM task. We first demonstrate the advantages of parcellation schemes for dimension reduction, in terms of load-related effect sizes. This parcel-based approach is then utilized to directly compare the relationship between load-related (within-subject) and behavioral individual differences (between-subject) effects through both correlational and predictive analyses. The results suggest a strong linkage of within-subject and between-subject variation, with larger load-effects linked to stronger brain-behavior correlations. In frontoparietal cortex no hemispheric biases were found towards one type of variation, but the Dorsal Attention Network did exhibit greater sensitivity to between over within-subjects variation, whereas in the Somatomotor network, the reverse pattern was observed. Cross-validated predictive modeling capitalizing on this tight relationship between the two effects indicated greater predictive power for load-activated than load-deactivated parcels, while also demonstrating that load-related effect size can serve as an effective guide to feature (i.e., parcel) selection, in maximizing predictive power while maintaining interpretability. Together, the findings demonstrate an important consistency across within- and between-subjects approaches to identifying the neural substrates of WM, which can be effectively harnessed to develop more powerful predictive models.
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11
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Petrovska J, Loos E, Coynel D, Egli T, Papassotiropoulos A, de Quervain DJF, Milnik A. Recognition memory performance can be estimated based on brain activation networks. Behav Brain Res 2021; 408:113285. [PMID: 33819531 DOI: 10.1016/j.bbr.2021.113285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 03/11/2021] [Accepted: 03/30/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Recognition memory is an essential ability for functioning in everyday life. Establishing robust brain networks linked to recognition memory performance can help to understand the neural basis of recognition memory itself and the interindividual differences in recognition memory performance. METHODS We analysed behavioural and whole-brain fMRI data from 1'410 healthy young adults during the testing phase of a picture-recognition task. Using independent component analysis (ICA), we decomposed the fMRI contrast for previously seen vs. new (old-new) pictures into networks of brain activity. This was done in two independent samples (training sample: N = 645, replication sample: N = 665). Next, we investigated the relationship between the identified brain networks and interindividual differences in recognition memory performance by conducting a prediction analysis. We estimated the prediction accuracy in a third independent sample (test sample: N = 100). RESULTS We identified 12 robust and replicable brain networks using two independent samples. Based on the activity of those networks we could successfully estimate interindividual differences in recognition memory performance with high accuracy in a third independent sample (r = 0.5, p = 1.29 × 10-07). CONCLUSION Given the robustness of the ICA decomposition as well as the high prediction estimate, the identified brain networks may be considered as potential biomarkers of recognition memory performance in healthy young adults and can be further investigated in the context of health and disease.
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Affiliation(s)
- Jana Petrovska
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland.
| | - Eva Loos
- Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland
| | - David Coynel
- Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland
| | - Tobias Egli
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland
| | - Andreas Papassotiropoulos
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland; Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056 Basel, Switzerland
| | - Dominique J-F de Quervain
- Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland
| | - Annette Milnik
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055 Basel, Switzerland; Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, CH-4055 Basel, Switzerland; Psychiatric University Clinics, University of Basel, CH-4055 Basel, Switzerland.
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12
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Han H. A method to adjust a prior distribution in Bayesian second-level fMRI analysis. PeerJ 2021; 9:e10861. [PMID: 33604196 PMCID: PMC7866892 DOI: 10.7717/peerj.10861] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 01/08/2021] [Indexed: 01/14/2023] Open
Abstract
Previous research has shown the potential value of Bayesian methods in fMRI (functional magnetic resonance imaging) analysis. For instance, the results from Bayes factor-applied second-level fMRI analysis showed a higher hit rate compared with frequentist second-level fMRI analysis, suggesting greater sensitivity. Although the method reported more positives as a result of the higher sensitivity, it was able to maintain a reasonable level of selectivity in term of the false positive rate. Moreover, employment of the multiple comparison correction method to update the default prior distribution significantly improved the performance of Bayesian second-level fMRI analysis. However, previous studies have utilized the default prior distribution and did not consider the nature of each individual study. Thus, in the present study, a method to adjust the Cauchy prior distribution based on a priori information, which can be acquired from the results of relevant previous studies, was proposed and tested. A Cauchy prior distribution was adjusted based on the contrast, noise strength, and proportion of true positives that were estimated from a meta-analysis of relevant previous studies. In the present study, both the simulated images and real contrast images from two previous studies were used to evaluate the performance of the proposed method. The results showed that the employment of the prior adjustment method resulted in improved performance of Bayesian second-level fMRI analysis.
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Affiliation(s)
- Hyemin Han
- Educational Psychology Program, University of Alabama - Tuscaloosa, Tuscaloosa, AL, United States of America
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13
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A Comprehensive Meta-analysis on Short-term and Working Memory Dysfunction in Parkinson's Disease. Neuropsychol Rev 2021; 31:288-311. [PMID: 33523408 DOI: 10.1007/s11065-021-09480-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 01/05/2021] [Indexed: 12/29/2022]
Abstract
A previous meta-analysis demonstrated short-term memory (STM) and working memory (WM) dysfunction in patients with Parkinson's disease (PD). However, considerable research on the topic that calls into question the extent of such impairments in PD has since been published. The aim of the present quantitative review was to provide the largest statistical overview on STM and WM dysfunction in Parkinson's disease (PD), while simultaneously providing novel insights on moderating factors of effect size heterogeneity in PD. The systematic literature search in PubMed, PsycINFO, PsycArticles, Scopus and Web of Science databases allowed us to estimate 350 effect sizes from 145 empirical studies that reported STM and WM scores for patients with PD against healthy controls. The outcomes indicated general dysfunction in the visuospatial domain and poor verbal WM in PD. Subgroup analyses suggested that mild cognitive impairment is associated with STM and WM difficulties in PD. Furthermore, meta-regression analyses revealed that disease duration accounted for more than 80% of the visuospatial STM effect size variance (β = 0.136, p < .001, R2 = .8272), larger daily levodopa equivalent dose was associated with WM dysfunction (verbal: β = -0.001, p = .016, R2 = .1812; visuospatial: β = 0.003, p = .069, R2 = .2340), and years of education partially explained the verbal STM effect size variance (β = -0.027, p = .040, R2 = .1171). Collectively, these findings advance our understanding of underlying factors that influence STM and WM functioning in PD, while at the same time providing novel directions for future research.
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14
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Large-scale brain networks underlying non-spatial attention updating: Towards understanding the function of the temporoparietal junction. Cortex 2020; 133:247-265. [PMID: 33157345 DOI: 10.1016/j.cortex.2020.09.023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 06/19/2020] [Accepted: 09/21/2020] [Indexed: 12/12/2022]
Abstract
The temporoparietal junction (TPJ) and related areas are activated when a target stimulus appears at unexpected locations in Posner's spatial-cueing paradigm, and also when deviant stimuli are presented within a series of standard events in oddball paradigms. This type of activation corresponds to the ventral attention network (VAN), for regions defined on the basis of the spatial task. However, involvement of the VAN in object-based updating of attention has rarely been examined. In the present study, we used functional magnetic resonance imaging to investigate brain responses to (i) invalid targets after category-cueing and (ii) neutrally cued targets deviating in category from the background series of pictures. Bilateral TPJ activation was observed in response to invalidly cued targets, as compared to neutrally cued targets. Reference to the main large-scale brain networks showed that peaks of this activation located in the angular gyrus and inferior parietal lobule belonged to the default mode (DMN) and fronto-parietal networks (FPN), respectively. We found that VAN regions were involved only for simple detection activity. We conclude that spatial and non-spatial reorienting of attention rely on different network underpinnings. Our data suggest that DMN and FPN activity may support the ability to disengage from contextually irrelevant information.
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15
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Bakulin I, Zabirova A, Kopnin P, Sinitsyn D, Poydasheva A, Fedorov M, Gnedovskaya E, Suponeva N, Piradov M. Cerebral cortex activation during the Sternberg verbal working memory task. BULLETIN OF RUSSIAN STATE MEDICAL UNIVERSITY 2020. [DOI: 10.24075/brsmu.2020.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Despite intensive study, the data regarding functional role of specific brain regions in the working memory processes still remain controversial. The study was aimed to determine the activation of cerebral cortex regions at different stages of the working memory task (information encoding, maintenance and retrieval). Functional magnetic resonance imaging (fMRI) with the modified Sternberg task was applied to 19 healthy volunteers. The objective of the task was to memorize and retain in memory the sequence of 7 letters with the subsequent comparison of one letter with the sequence. Activation was analyzed during three periods of the task compared to the rest period, as well as temporal dynamics of changes in BOLD signal intensity in three regions: left dorsolateral prefrontal, left posterior parietal and left occipital cortex. According to the results, significant activation of the regions in prefrontal and posterior parietal cortex was observed during all periods of the task (p < 0.05), but there were changes in its localization and lateralization. The activation pattern during the maintenance period corresponded to the fronto-parietal control network components. According to the analysis of temporal dynamics of changes in BOLD signal intensity, the most prominent activation of the dorsolateral prefrontal cortex and parietal cortex was observed in the end of the encoding period, during the maintenance period and in the beginning of the retrieval period, which confirmed the role of those areas in the working memory processes. The maximum of occipital cortex activation was observed during encoding period. The study confirmed the functional role of the dorsolateral prefrontal cortex and posterior parietal cortex in the working memory mechanisms during all stages of the Sternberg task.
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Affiliation(s)
| | | | - P.N. Kopnin
- Research Center of Neurology, Moscow, Russia
| | | | | | | | - E.V. Gnedovskaya
- Research Center of Neurology, Moscow, Russia; Skoltech, Moscow, Russia
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16
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Lamichhane B, Westbrook A, Cole MW, Braver TS. Exploring brain-behavior relationships in the N-back task. Neuroimage 2020; 212:116683. [PMID: 32114149 DOI: 10.1016/j.neuroimage.2020.116683] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 02/17/2020] [Accepted: 02/24/2020] [Indexed: 12/22/2022] Open
Abstract
Working memory (WM) function has traditionally been investigated in terms of two dimensions: within-individual effects of WM load, and between-individual differences in task performance. In human neuroimaging studies, the N-back task has frequently been used to study both. A reliable finding is that activation in frontoparietal regions exhibits an inverted-U pattern, such that activity tends to decrease at high load levels. Yet it is not known whether such U-shaped patterns are a key individual differences factor that can predict load-related changes in task performance. The current study investigated this question by manipulating load levels across a much wider range than explored previously (N = 1-6), and providing a more comprehensive examination of brain-behavior relationships. In a sample of healthy young adults (n = 57), the analysis focused on a distinct region of left lateral prefrontal cortex (LPFC) identified in prior work to show a unique relationship with task performance and WM function. In this region it was the linear slope of load-related activity, rather than the U-shaped pattern, that was positively associated with individual differences in target accuracy. Comprehensive supplemental analyses revealed the brain-wide selectivity of this pattern. Target accuracy was also independently predicted by the global resting-state connectivity of this LPFC region. These effects were robust, as demonstrated by cross-validation analyses and out-of-sample prediction, and also critically, were primarily driven by the high-load conditions. Together, the results highlight the utility of high-load conditions for investigating individual differences in WM function.
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Affiliation(s)
- Bidhan Lamichhane
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, 1 Brookings Drive, Saint Louis, MO, 63130, USA.
| | - Andrew Westbrook
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Kapittelweg 29, 6525 EN, Nijmegen, the Netherlands; Department of Cognitive, Linguistics, and Psychological Sciences, Brown University, 190 Thayer Street, Providence, RI, 02912, USA
| | - Michael W Cole
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA
| | - Todd S Braver
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, 1 Brookings Drive, Saint Louis, MO, 63130, USA
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17
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Bakulin I, Zabirova A, Lagoda D, Poydasheva A, Cherkasova A, Pavlov N, Kopnin P, Sinitsyn D, Kremneva E, Fedorov M, Gnedovskaya E, Suponeva N, Piradov M. Combining HF rTMS over the Left DLPFC with Concurrent Cognitive Activity for the Offline Modulation of Working Memory in Healthy Volunteers: A Proof-of-Concept Study. Brain Sci 2020; 10:brainsci10020083. [PMID: 32033106 PMCID: PMC7071618 DOI: 10.3390/brainsci10020083] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 01/31/2020] [Accepted: 02/03/2020] [Indexed: 01/28/2023] Open
Abstract
It has been proposed that the effectiveness of non-invasive brain stimulation (NIBS) as a cognitive enhancement technique may be enhanced by combining the stimulation with concurrent cognitive activity. However, the benefits of such a combination in comparison to protocols without ongoing cognitive activity have not yet been studied. In the present study, we investigate the effects of fMRI-guided high-frequency repetitive transcranial magnetic stimulation (HF rTMS) over the left dorsolateral prefrontal cortex (DLPFC) on working memory (WM) in healthy volunteers, using an n-back task with spatial and verbal stimuli and a spatial span task. In two combined protocols (TMS + WM + (maintenance) and TMS + WM + (rest)) trains of stimuli were applied in the maintenance and rest periods of the modified Sternberg task, respectively. We compared them to HF rTMS without a cognitive load (TMS + WM −) and control stimulation (TMS − WM + (maintenance)). No serious adverse effects appeared in this study. Among all protocols, significant effects on WM were shown only for the TMS + WM − with oppositely directed influences of this protocol on storage and manipulation in spatial WM. Moreover, there was a significant difference between the effects of TMS + WM − and TMS + WM + (maintenance), suggesting that simultaneous cognitive activity does not necessarily lead to an increase in TMS effects.
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Affiliation(s)
- Ilya Bakulin
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
- Correspondence: ; Tel.: +7-495-490-2010
| | - Alfiia Zabirova
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Dmitry Lagoda
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Alexandra Poydasheva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Anastasiia Cherkasova
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Nikolay Pavlov
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Peter Kopnin
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Dmitry Sinitsyn
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Elena Kremneva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Maxim Fedorov
- Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, Territory of Innovation Center «Skolkovo», Moscow 121205, Russia;
| | - Elena Gnedovskaya
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
- Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, Territory of Innovation Center «Skolkovo», Moscow 121205, Russia;
| | - Natalia Suponeva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
| | - Michael Piradov
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.Z.); (D.L.); (A.P.); (A.C.); (N.P.); (P.K.); (D.S.); (E.K.); (E.G.); (N.S.); (M.P.)
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Loos E, Egli T, Coynel D, Fastenrath M, Freytag V, Papassotiropoulos A, de Quervain DJF, Milnik A. Predicting emotional arousal and emotional memory performance from an identical brain network. Neuroimage 2019; 189:459-467. [DOI: 10.1016/j.neuroimage.2019.01.028] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2018] [Revised: 01/07/2019] [Accepted: 01/10/2019] [Indexed: 12/17/2022] Open
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