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Genome-wide association study identified INSC gene associated with Trail Making Test Part A and Alzheimer's disease related cognitive phenotypes. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110393. [PMID: 34224794 DOI: 10.1016/j.pnpbp.2021.110393] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 06/14/2021] [Accepted: 06/29/2021] [Indexed: 12/27/2022]
Abstract
BACKGROUND The Trail Making Test (TMT) Part A (TMT-A) is a good measure of performance on cognitive processing speed. This study aimed to perform a genome-wide association study of TMT-A in Alzheimer's disease (AD). METHODS A total of 757 individuals with TMT-A phenotypes and 620,901 single nucleotide polymorphisms (SNPs) were extracted from the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) cohort. AD related cognitive phenotypes include TMT-A, TMT-B, Functional Activities Questionnaire (FAQ), Clinical Dementia Rating Sum of Boxes (CDR-SB), and Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 (ADAS13). Multivariable linear regression analysis of TMT-A was conducted using PLINK software. The most TMT-A associated gene was tested with Color Trails Test 1 Form A (CTTA), a culturally fair analog of the TMT-A. Functional annotation of SNPs was performed using the RegulomeDB and Genotype-Tissue Expression (GTEx) databases. RESULTS The best signal with TMT-A was rs1108010 (p = 4.34 × 10-8) at 11p15.2 within INSC gene, which was also associated with TMT-B, FAQ, CDR-SB, and ADAS13 (p = 2.47 × 10-4, 8.56 × 10-3, 0.0127 and 0.0188, respectively). Furthermore, suggestive loci were identified such as FOXD2 and CLTA with TMT-A, GBP1/GBP3 with TMT-B, GRIK2 with FAQ, BAALC and CCDC146 with CDR-SB, BAALC and NKAIN2 with ADAS13. Additionally, the best SNP within INSC associated with CTTA was rs7931705 (p = 6.15 × 10-5). Several SNPs had significant eQTLs using GTEx. CONCLUSIONS We identified several genes/loci associated with TMT-A and AD related phenotypes. These findings offer the potential for new insights into the pathogenesis of cognitive function and Alzheimer's disease.
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Broomfield C, Stedal K, Touyz S. The Neuropsychological Profile of Severe and Enduring Anorexia Nervosa: A Systematic Review. Front Psychol 2021; 12:708536. [PMID: 34408714 PMCID: PMC8365190 DOI: 10.3389/fpsyg.2021.708536] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 06/30/2021] [Indexed: 11/13/2022] Open
Abstract
Characteristics of Severe and Enduring Anorexia Nervosa (SE-AN) are being investigated to differentiate the patients experiencing SE-AN from those at earlier stages of the AN disease. The current systematic review was the first step in exploring neuropsychological functioning as a potentially identifying characteristic for long-term presentations. With a subgroup of AN patients reflecting a unique neuropsychological profile that is proportionate to the quantity of patients that go on to develop SE-AN, it was the aim of this review to assess neuropsychological functioning in the later stage of the disease. In accordance with PRISMA guidelines, a literature search was conducted using four electronic databases (PsycINFO, MEDLINE, Web of Science, and Scopus) for neuropsychological research on AN participants with a seven or more year illness duration. Datasets that met inclusion criteria were screened for SE-AN participants (N = 166) and neuropsychological data extracted together with potentially confounding variables and information required to conduct a quality assessment. In research investigating decision-making, participants with a SE-AN presentation demonstrated significantly lower functioning compared to healthy controls. There was conflicting evidence for differences in intellectual functioning and set-shifting abilities with no variability indicated in central coherence, memory, attention, reasoning, or processing speed. If findings from this preliminary analysis are confirmed through empirical research, implications include earlier identification of SE-AN patients and more effective treatment development.
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Affiliation(s)
| | - Kristin Stedal
- Regional Department for Eating Disorders, Oslo University Hospital, Ullevål, Norway
| | - Stephen Touyz
- Inside Out Institute, Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
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Chakraborty N, Hammamieh R, Gautam A, Miller SA, Condlin ML, Jett M, Scrimgeour AG. TBI weight-drop model with variable impact heights differentially perturbs hippocampus-cerebellum specific transcriptomic profile. Exp Neurol 2020; 335:113516. [PMID: 33172833 DOI: 10.1016/j.expneurol.2020.113516] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 09/28/2020] [Accepted: 10/21/2020] [Indexed: 01/14/2023]
Abstract
The degree of brain injury is the governing factor for the magnitude of the patient's psycho- and physiological deficits post-injury, and the associated long-term consequences. The present scaling method used to segregate the patients among mild, moderate and severe phases of traumatic brain injury (TBI) has major limitations; however, a more continuous stratification of TBI is still elusive. With the anticipation that differentiating molecular markers could be the backbone of a robust method to triage TBI, we used a modified closed-head injury (CHI) Marmarou model with two impact heights (IH). By definition, IH directly correlates with the impact force causing TBI. In our modified CHI model, the rat skull was fitted with a helmet to permit a diffuse axonal injury. With the frontal cortex as the focal point of injury, the adjacent brain regions (hippocampus, HC and cerebellum, CB) were susceptible to diffuse secondary shock injury. At 8 days post injury (po.i.), rats impacted by 120 cm IH (IH120) took a longer time to find an escape route in the Barnes maze as compared to those impacted by 100 cm IH (IH100). Using a time-resolved interrogation of the transcriptomic landscape of HC and CB tissues, we mined those genes that altered their regulations in correlation with the variable IHs. At 14 days po.i., when all rats demonstrated nearly normal visuomotor performance, the bio-functional analysis suggested an advanced healing mechanism in the HC of IH100 group. In contrast, the HC of IH120 group displayed a delayed healing with evidence of active cell death networks. Combining whole genome rat microarrays with behavioral analysis provided the insight of neuroprotective signals that could be the foundation of the next generation triage for TBI patients.
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Affiliation(s)
- Nabarun Chakraborty
- Geneva Foundation, Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD 20910, United States of America; Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD 20910, United States of America.
| | - Rasha Hammamieh
- Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD 20910, United States of America
| | - Aarti Gautam
- Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD 20910, United States of America
| | - Stacy-Ann Miller
- Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD 20910, United States of America; ORISE, Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD 20910, United States of America
| | - Michelle L Condlin
- Military Nutrition Division, US Army Research Institute of Environmental Medicine, 10 General Greene Ave, Bldg 42, Natick, MA 01760, United States of America
| | - Marti Jett
- Medical Readiness Systems Biology, Walter Reed Army Institute of Research, Silver Spring, MD 20910, United States of America
| | - Angus G Scrimgeour
- Military Nutrition Division, US Army Research Institute of Environmental Medicine, 10 General Greene Ave, Bldg 42, Natick, MA 01760, United States of America
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Chen C, Chen C, Xue G, Dong Q, Zhao L, Zhang S. Parental warmth interacts with several genes to affect executive function components: a genome-wide environment interaction study. BMC Genet 2020; 21:11. [PMID: 32019487 PMCID: PMC7001336 DOI: 10.1186/s12863-020-0819-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2019] [Accepted: 01/29/2020] [Indexed: 12/20/2022] Open
Abstract
Background Executive function (EF) is vital to human beings. It has been linked to many genes and family environmental factors in separate studies, but few studies have examined the potential interactions between gene(s) and environmental factor(s). The current study explored the whole genome to identify SNPs, genes, and pathways that interacted with parental warmth (PW) on EF. Results Nine EF tasks were used to measure its three components (common EF, updating, shifting) based on the model proposed by Miyake et al. (2000). We found that rs111605473, LAMP5, SLC4A7, and LRRK1 interacted significantly with PW to affect the updating component of EF, and the GSE43955 pathway interacted significantly with PW to affect the common EF component. Conclusions The current study is the first to identify genes that interacted with PW to affect EF. Further studies are needed to reveal the underlying mechanism.
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Affiliation(s)
- Chunhui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Chuansheng Chen
- Department of Psychological Science, University of California, Irvine, CA, USA
| | - Gui Xue
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Libo Zhao
- Department of Psychology, BeiHang University, Beijing, 100191, China
| | - Shudong Zhang
- Faculty of Education, Beijing Normal University, Beijing, China.
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Alfimova MV, Kondratiev NV, Golimbet VE. [Results and promises of genetics of cognitive impairment in schizophrenia: molecular-genetic approaches]. Zh Nevrol Psikhiatr Im S S Korsakova 2018. [PMID: 28635752 DOI: 10.17116/jnevro2016116111137-144] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
This review highlights the basic paradigms and directions of molecular genetic studies of cognitive deficits in schizophrenia. Along with the traditional approach based on functional candidate genes, it covers genome-wide association studies (GWAS) for cognition in general population and schizophrenic patients, attempts to integrate GWAS results in polygenic profiles that can be used in personalized care of schizophrenic patients, and a search for biological pathways implicated in the development of cognitive impairments with bioinformatics methods. However, despite significant advances in understanding the genetic basis of the disease and a rapidly growing amount of data on genes associated with cognitive functions, most of the variability of cognitive impairments in patients remains unexplained. The data on the functional complexity of the genome accumulated in the fields of molecular biology and genetics underscore the importance of studying epigenetic mechanisms of cognitive deficits in schizophrenia.
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Knowles EEM, Mathias SR, Mollon J, Rodrigue A, Koenis MMG, Dyer TD, Goring HHH, Curran JE, Olvera RL, Duggirala R, Almasy L, Blangero J, Glahn DC. A QTL on chromosome 3q23 influences processing speed in humans. GENES BRAIN AND BEHAVIOR 2018; 18:e12530. [PMID: 30379395 DOI: 10.1111/gbb.12530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 09/24/2018] [Accepted: 10/18/2018] [Indexed: 10/28/2022]
Abstract
Processing speed is a psychological construct that refers to the speed with which an individual can perform any cognitive operation. Processing speed correlates strongly with general cognitive ability, declines sharply with age and is impaired across a number of neurological and psychiatric disorders. Thus, identifying genes that influence processing speed will likely improve understanding of the genetics of intelligence, biological aging and the etiologies of numerous disorders. Previous genetics studies of processing speed have relied on simple phenotypes (eg, mean reaction time) derived from single tasks. This strategy assumes, erroneously, that processing speed is a unitary construct. In the present study, we aimed to characterize the genetic architecture of processing speed by using a multidimensional model applied to a battery of cognitive tasks. Linkage and QTL-specific association analyses were performed on the factors from this model. The randomly ascertained sample comprised 1291 Mexican-American individuals from extended pedigrees. We found that performance on all three distinct processing-speed factors (Psychomotor Speed; Sequencing and Shifting and Verbal Fluency) were moderately and significantly heritable. We identified a genome-wide significant quantitative trait locus (QTL) on chromosome 3q23 for Psychomotor Speed (LOD = 4.83). Within this locus, we identified a plausible and interesting candidate gene for Psychomotor Speed (Z = 2.90, P = 1.86 × 10-03 ).
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Affiliation(s)
- Emma E M Knowles
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Samuel R Mathias
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Josephine Mollon
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Amanda Rodrigue
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Marinka M G Koenis
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Thomas D Dyer
- South Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas of the Rio Grande Valley School of Medicine, Brownsville, Texas
| | - Harald H H Goring
- South Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas of the Rio Grande Valley School of Medicine, Brownsville, Texas
| | - Joanne E Curran
- South Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas of the Rio Grande Valley School of Medicine, Brownsville, Texas
| | - Rene L Olvera
- Department of Psychiatry, University of Texas Health Science Center at San Antonio, San Antonio, Texas
| | - Ravi Duggirala
- South Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas of the Rio Grande Valley School of Medicine, Brownsville, Texas
| | - Laura Almasy
- Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - John Blangero
- South Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas of the Rio Grande Valley School of Medicine, Brownsville, Texas
| | - David C Glahn
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.,Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital, Hartford, Connecticut
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Woods DL, Wyma JM, Herron TJ, Yund EW. The Effects of Aging, Malingering, and Traumatic Brain Injury on Computerized Trail-Making Test Performance. PLoS One 2015; 10:e0124345. [PMID: 26060999 PMCID: PMC4465490 DOI: 10.1371/journal.pone.0124345] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Accepted: 02/27/2015] [Indexed: 12/18/2022] Open
Abstract
The trail making test (TMT) is widely used to assess speed of processing and executive function. However, normative data sets gathered at different sites show significant inconsistencies. Here, we describe a computerized version of the TMT (C-TMT) that increases the precision and replicability of the TMT by permitting a segment-by-segment analysis of performance and separate analyses of dwell-time, move-time, and error time. Experiment 1 examined 165 subjects of various ages and found that completion times on both the C-TMT-A (where subjects connect successively numbered circles) and the C-TMT-B (where subjects connect circles containing alternating letters and numbers) were strongly influenced by age. Experiment 2 examined 50 subjects who underwent three test sessions. The results of the first test session were well fit by the normative data gathered in Experiment 1. Sessions 2 and 3 demonstrated significant learning effects, particularly on the C-TMT-B, and showed good test-retest reliability. Experiment 3 examined performance in subjects instructed to feign symptoms of traumatic brain injury: 44% of subjects produced abnormal completion times on the C-TMT-A, and 18% on the C-TMT-B. Malingering subjects could be distinguished from abnormally slow controls based on (1) disproportionate increases in dwell-time on the C-TMT-A, and (2) greater deficits on the C-TMT-A than on the C-TMT-B. Experiment 4 examined the performance of 28 patients with traumatic brain injury: C-TMT-B completion times were slowed, and TBI patients showed reduced movement velocities on both tests. The C-TMT improves the reliability and sensitivity of the trail making test of processing speed and executive function.
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Affiliation(s)
- David L. Woods
- Human Cognitive Neurophysiology Laboratory, Veterans Affairs Northern California Heath Care System, 150 Muir Rd., Martinez, CA, 95553, United States of America
- University of California Davis, Department of Neurology, 4860 Y St., Suite 3700, Sacramento, CA, 95817, United States of America
- Center for Neurosciences, University of California Davis, 1544 Newton Ct., Davis, CA, 95616, United States of America
- Center for Mind and Brain, University of California Davis, 202 Cousteau Place, Suite 201, Davis, CA, 95616, United States of America
- * E-mail:
| | - John M. Wyma
- Human Cognitive Neurophysiology Laboratory, Veterans Affairs Northern California Heath Care System, 150 Muir Rd., Martinez, CA, 95553, United States of America
| | - Timothy J. Herron
- Human Cognitive Neurophysiology Laboratory, Veterans Affairs Northern California Heath Care System, 150 Muir Rd., Martinez, CA, 95553, United States of America
| | - E. William Yund
- Human Cognitive Neurophysiology Laboratory, Veterans Affairs Northern California Heath Care System, 150 Muir Rd., Martinez, CA, 95553, United States of America
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