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Ying Y, Li X, Chen Y. Hypomethylation of the opioid receptor delta 1 gene combined with high opioid receptor delta 1 protein levels indicates increased risk of gout. J Clin Lab Anal 2022; 36:e24634. [PMID: 35908776 PMCID: PMC9459328 DOI: 10.1002/jcla.24634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 07/12/2022] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
Background The purpose of this study was to identify biomarkers for the diagnosis of gout in Chinese Han males using methylation microarray profiling. Methods We screened for differentially methylated genes (DMGs) in gout using a methylation microarray and analyzed the functions of the DMGs using gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. We verified gene methylation levels by pyrosequencing and protein levels by enzyme‐linked immunosorbent assays (ELISAs). Statistical analyses were performed using SPSS. Two‐sided p values <0.05 were deemed to be statistically significant for all analyses. Results We identified 20,426 significant differential methylation sites (5719 high‐methylation sites and 14,707 low‐methylation sites). Bioinformatics analysis showed that the DMGs were mainly involved in 43 biological functions, 13 cellular components, 18 molecular functions, and 35 KEGG pathways. We selected opioid receptor delta 1 (OPRD1) for verification of methylation levels between 50 gout patients and 50 controls. The methylation levels of OPRD1 (Chr1:29,139,121) were significantly lower in the gout group (p < 0.05), while OPRD1 protein levels were significantly higher in the gout group (p < 0.05). In addition, the AUC of the combination of OPRD1 (Chr1:29,139,121) methylation and OPRD1 protein levels was 0.796 (0.710, 0.883) with a high sensitivity of 82% and a specificity of 68% (p < 0.001). Conclusions The combination of OPRD1 (Chr1:29,139,121) hypomethylation and high levels of OPRD1 protein is a potential biomarker for gout diagnosis.
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Affiliation(s)
- Ying Ying
- Department of Rheumatology, Hwa Mei Hospital, University of Chinese Academy of Sciences (Ningbo No. 2 Hospital), Ningbo, Zhejiang, China
| | - Xiaoke Li
- Medical School, Ningbo University, Ningbo, Zhejiang, China
| | - Yong Chen
- Department of Rheumatology, Hwa Mei Hospital, University of Chinese Academy of Sciences (Ningbo No. 2 Hospital), Ningbo, Zhejiang, China
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Zhang Q, Yang J, Yang C, Yang X, Chen Y. Eucommia ulmoides Oliver- Tribulus terrestris L. Drug Pair Regulates Ferroptosis by Mediating the Neurovascular-Related Ligand-Receptor Interaction Pathway- A Potential Drug Pair for Treatment Hypertension and Prevention Ischemic Stroke. Front Neurol 2022; 13:833922. [PMID: 35345408 PMCID: PMC8957098 DOI: 10.3389/fneur.2022.833922] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 02/08/2022] [Indexed: 01/04/2023] Open
Abstract
Background In this study, we used the network pharmacology approach to explore the potential disease targets of the Eucommia ulmoides Oliver (EUO)-Tribulus terrestris L. (TT) drug pair in the treatment of hypertension-associated neurovascular lesions and IS via the ferroptosis pathway. Methods We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform to search for the key active compounds and targets of the drug pair. Based on the GeneCards database, the relevant targets for the drug pair were obtained. Then, we performed the molecular docking of the screened core active ingredients and proteins using the DAVID database and the R AutoDock Vina software. Based on the GSE22255 dataset, these screened target proteins were used to build random forest (RF) and support vector machine (SVM) models. Finally, a new IS nomogram prediction model was constructed and evaluated. Results There were 36 active compounds in the EUO-TT drug pair. CHRM1, NR3C1, ADRB2, and OPRD1 proteins of the neuroactive ligand-receptor interaction pathway interacted with the proteins related to the ferroptosis pathway. Molecular docking experiments identified 12 active ingredients of the drug pair that may tightly bind to those target proteins. We constructed a visual IS nomogram prediction model using four genes (CHRM1, NR3C1, ADRB2, and OPRD1). The calibration curve, DCA, and clinical impact curves all indicated that the nomogram model is clinically applicable and diagnostically capable. CHRM1, NR3C1, ADRB2, and OPRD1, the target genes of the four effective components of the EUO-TT drug pair, were considered as risk markers for IS. Conclusions The active ingredients of EUO-TT drug pair may act on proteins associated with the neuroactive ligand-receptor interaction pathway to regulate ferroptosis in vascular neurons cells, ultimately affecting the onset and progression of hypertension.
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Affiliation(s)
- Qian Zhang
- Department of Science and Technology Office, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jie Yang
- Department of Cardiology, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Chuanhua Yang
- Department of Cardiology, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Xuesong Yang
- Department of Vascular Surgery, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Yongzhi Chen
- Department of Cardiology, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
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Crist RC, Arauco-Shapiro G, Zhang A, Reiner BC, Berrettini WH, Doyle GA. Differential expression and transcription factor binding associated with genotype at a pharmacogenetic variant in OPRD1. THE AMERICAN JOURNAL OF DRUG AND ALCOHOL ABUSE 2021; 47:581-589. [PMID: 34407719 DOI: 10.1080/00952990.2021.1954189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
BACKGROUND The functional mechanism is unknown for many genetic variants associated with substance use disorder phenotypes. Rs678849, an intronic variant in the delta-opioid receptor gene (OPRD1), has been found to predict regional brain volume, addiction risk, and the efficacy of buprenorphine/naloxone in treating opioid use disorder. The variant has also been implicated as an expression quantitative trait locus (eQTL) for several genes. OBJECTIVES The objective of this study was to identify functional differences between the two alleles of rs678849 in vitro. We hypothesized that the two alleles of rs678849 would have different effects on transcriptional activity due to differential interactions with transcription factors. METHODS 15bp regions containing the C or T alleles of rs678849 were cloned into luciferase constructs and transfected into BE(2)C neuroblastoma cells to test the effect on transcription. Electrophoretic mobility shift assays (EMSA) using nuclear lysates from BE(2)C cell or human postmortem medial prefrontal cortex were used to identify proteins that differentially bound the two alleles. RESULTS At 24 hours post-transfection, the C allele construct had significantly lower luciferase expression than the T allele construct and empty vector control (ANOVA p < .001). Proteomic analysis and supershift assays identified XRCC6 as a transcription factor specifically binding the C allele, whereas hnRNP D0 was found to specifically bind the T allele. CONCLUSION These functional differences between the C and T alleles may help explain the psychiatric and neurological phenotype differences predicted by rs678849 genotype and the potential role of the variant as an eQTL.
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Affiliation(s)
- Richard C Crist
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Gabriella Arauco-Shapiro
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Alexander Zhang
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin C Reiner
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Wade H Berrettini
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Geisinger Clinic, Danville, PA, USA
| | - Glenn A Doyle
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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Abstract
After participating in this activity, learners should be better able to:• Identify the effects of dysregulated opioid signalling in depression• Evaluate the use of opioid compounds and ketamine in patients with depression ABSTRACT: Major depressive disorder (MDD) remains one of the leading causes of disability and functional impairment worldwide. Current antidepressant therapeutics require weeks to months of treatment prior to the onset of clinical efficacy on depressed mood but remain ineffective in treating suicidal ideation and cognitive impairment. Moreover, 30%-40% of individuals fail to respond to currently available antidepressant medications. MDD is a heterogeneous disorder with an unknown etiology; novel strategies must be developed to treat MDD more effectively. Emerging evidence suggests that targeting one or more of the four opioid receptors-mu (MOR), kappa (KOR), delta (DOR), and the nociceptin/orphanin FQ receptor (NOP)-may yield effective therapeutics for stress-related psychiatric disorders. Furthermore, the effects of the rapidly acting antidepressant ketamine may involve opioid receptors. This review highlights dysregulated opioid signaling in depression, evaluates clinical trials with opioid compounds, and considers the role of opioid mechanisms in rapidly acting antidepressants.
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Macedo A, Gómez C, Rebelo MÂ, Poza J, Gomes I, Martins S, Maturana-Candelas A, Pablo VGD, Durães L, Sousa P, Figueruelo M, Rodríguez M, Pita C, Arenas M, Álvarez L, Hornero R, Lopes AM, Pinto N. Risk Variants in Three Alzheimer's Disease Genes Show Association with EEG Endophenotypes. J Alzheimers Dis 2021; 80:209-223. [PMID: 33522999 PMCID: PMC8075394 DOI: 10.3233/jad-200963] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background: Dementia due to Alzheimer’s disease (AD) is a complex neurodegenerative disorder, which much of heritability remains unexplained. At the clinical level, one of the most common physiological alterations is the slowing of oscillatory brain activity, measurable by electroencephalography (EEG). Relative power (RP) at the conventional frequency bands (i.e., delta, theta, alpha, beta-1, and beta-2) can be considered as AD endophenotypes. Objective: The aim of this work is to analyze the association between sixteen genes previously related with AD: APOE, PICALM, CLU, BCHE, CETP, CR1, SLC6A3, GRIN2
β, SORL1, TOMM40, GSK3
β, UNC5C, OPRD1, NAV2, HOMER2, and IL1RAP, and the slowing of the brain activity, assessed by means of RP at the aforementioned frequency bands. Methods: An Iberian cohort of 45 elderly controls, 45 individuals with mild cognitive impairment, and 109 AD patients in the three stages of the disease was considered. Genomic information and brain activity of each subject were analyzed. Results: The slowing of brain activity was observed in carriers of risk alleles in IL1RAP (rs10212109, rs9823517, rs4687150), UNC5C (rs17024131), and NAV2 (rs1425227, rs862785) genes, regardless of the disease status and situation towards the strongest risk factors: age, sex, and APOE ɛ4 presence. Conclusion: Endophenotypes reduce the complexity of the general phenotype and genetic variants with a major effect on those specific traits may be then identified. The found associations in this work are novel and may contribute to the comprehension of AD pathogenesis, each with a different biological role, and influencing multiple factors involved in brain physiology.
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Affiliation(s)
- Ana Macedo
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,JTA: The Data Scientists, Porto, Portugal
| | - Carlos Gómez
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
| | - Miguel Ângelo Rebelo
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Jesús Poza
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain.,Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, Valladolid, Spain
| | - Iva Gomes
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Sandra Martins
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | | | | | - Luis Durães
- Associação Portuguesa de Familiares e Amigos de Doentes de Alzheimer, Lavra, Portugal
| | - Patrícia Sousa
- Associação Portuguesa de Familiares e Amigos de Doentes de Alzheimer, Lavra, Portugal
| | - Manuel Figueruelo
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, Zamora, Spain
| | - María Rodríguez
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, Zamora, Spain
| | - Carmen Pita
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, Zamora, Spain
| | - Miguel Arenas
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,CINBIO (Biomedical Research Center), University of Vigo, Vigo, Spain.,Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo, Spain
| | - Luis Álvarez
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,Adeneas, Valencia, Spain
| | - Roberto Hornero
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain.,Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, Valladolid, Spain
| | - Alexandra M Lopes
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Nádia Pinto
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,Centro de Matemática da Universidade do Porto, Porto, Portugal
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Shukla M, Vincent B. The multi-faceted impact of methamphetamine on Alzheimer's disease: From a triggering role to a possible therapeutic use. Ageing Res Rev 2020; 60:101062. [PMID: 32304732 DOI: 10.1016/j.arr.2020.101062] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 03/05/2020] [Accepted: 03/28/2020] [Indexed: 12/15/2022]
Abstract
Although it has been initially synthesized for therapeutic purposes and currently FDA-approved and prescribed for obesity, attention-deficit/hyperactivity disorder, narcolepsy and depression, methamphetamine became a recreational drug that is nowadays massively manufactured illegally. Because it is a powerful and extremely addictive psychotropic agent, its abuse has turned out to become a major health problem worldwide. Importantly, the numerous effects triggered by this drug induce neurotoxicity in the brain ultimately leading to serious neurological impairments, tissue damage and neuropsychological disturbances that are reminiscent to most of the symptoms observed in Alzheimer's disease and other pathological manifestations in aging brain. In this context, there is a growing number of compelling evidence linking methamphetamine abuse with a higher probability of developing premature Alzheimer's disease and consequent neurodegeneration. This review proposes to establish a broad assessment of the effects that this drug can generate at the cellular and molecular levels in connection with the development of the age-related Alzheimer's disease. Altogether, the objective is to warn against the long-term effects that methamphetamine abuse may convey on young consumers and the increased risk of developing this devastating brain disorder at later stages of their lives, but also to discuss a more recently emerging concept suggesting a possible use of methamphetamine for treating this pathology under proper and strictly controlled conditions.
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Lemche E. Early Life Stress and Epigenetics in Late-onset Alzheimer's Dementia: A Systematic Review. Curr Genomics 2018; 19:522-602. [PMID: 30386171 PMCID: PMC6194433 DOI: 10.2174/1389202919666171229145156] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Revised: 07/27/2017] [Accepted: 12/12/2017] [Indexed: 11/22/2022] Open
Abstract
Involvement of life stress in Late-Onset Alzheimer's Disease (LOAD) has been evinced in longitudinal cohort epidemiological studies, and endocrinologic evidence suggests involvements of catecholamine and corticosteroid systems in LOAD. Early Life Stress (ELS) rodent models have successfully demonstrated sequelae of maternal separation resulting in LOAD-analogous pathology, thereby supporting a role of insulin receptor signalling pertaining to GSK-3beta facilitated tau hyper-phosphorylation and amyloidogenic processing. Discussed are relevant ELS studies, and findings from three mitogen-activated protein kinase pathways (JNK/SAPK pathway, ERK pathway, p38/MAPK pathway) relevant for mediating environmental stresses. Further considered were the roles of autophagy impairment, neuroinflammation, and brain insulin resistance. For the meta-analytic evaluation, 224 candidate gene loci were extracted from reviews of animal studies of LOAD pathophysiological mechanisms, of which 60 had no positive results in human LOAD association studies. These loci were combined with 89 gene loci confirmed as LOAD risk genes in previous GWAS and WES. Of the 313 risk gene loci evaluated, there were 35 human reports on epigenomic modifications in terms of methylation or histone acetylation. 64 microRNA gene regulation mechanisms were published for the compiled loci. Genomic association studies support close relations of both noradrenergic and glucocorticoid systems with LOAD. For HPA involvement, a CRHR1 haplotype with MAPT was described, but further association of only HSD11B1 with LOAD found; however, association of FKBP1 and NC3R1 polymorphisms was documented in support of stress influence to LOAD. In the brain insulin system, IGF2R, INSR, INSRR, and plasticity regulator ARC, were associated with LOAD. Pertaining to compromised myelin stability in LOAD, relevant associations were found for BIN1, RELN, SORL1, SORCS1, CNP, MAG, and MOG. Regarding epigenetic modifications, both methylation variability and de-acetylation were reported for LOAD. The majority of up-to-date epigenomic findings include reported modifications in the well-known LOAD core pathology loci MAPT, BACE1, APP (with FOS, EGR1), PSEN1, PSEN2, and highlight a central role of BDNF. Pertaining to ELS, relevant loci are FKBP5, EGR1, GSK3B; critical roles of inflammation are indicated by CRP, TNFA, NFKB1 modifications; for cholesterol biosynthesis, DHCR24; for myelin stability BIN1, SORL1, CNP; pertaining to (epi)genetic mechanisms, hTERT, MBD2, DNMT1, MTHFR2. Findings on gene regulation were accumulated for BACE1, MAPK signalling, TLR4, BDNF, insulin signalling, with most reports for miR-132 and miR-27. Unclear in epigenomic studies remains the role of noradrenergic signalling, previously demonstrated by neuropathological findings of childhood nucleus caeruleus degeneration for LOAD tauopathy.
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Affiliation(s)
- Erwin Lemche
- Section of Cognitive Neuropsychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
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Replication of the pharmacogenetic effect of rs678849 on buprenorphine efficacy in African-Americans with opioid use disorder. THE PHARMACOGENOMICS JOURNAL 2018; 19:260-268. [PMID: 30368523 PMCID: PMC6486881 DOI: 10.1038/s41397-018-0065-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 08/24/2018] [Accepted: 09/27/2018] [Indexed: 01/01/2023]
Abstract
Many patients with opioid use disorder do not have successful outcomes during treatment but the underlying reasons are not well understood. An OPRD1 variant (rs678849) was previously associated with methadone and buprenorphine efficacy in African-Americans with opioid use disorder. The objective of this study was to determine if the effect of rs678849 on opioid use disorder treatment outcome could be replicated in an independent population. Participants were recruited from African-American patients who had participated in previous studies of methadone or buprenorphine treatment at the outpatient treatment research clinic of the NIDA Intramural Research Program in Baltimore, MD, USA between 2000 and 2017. Rs678849 was genotyped retrospectively, and genotypes were compared with urine drug screen results from the previous studies for opioids other than the one prescribed for treatment. Genotypes were available for 24 methadone patients and 55 buprenorphine patients. After controlling for demographics, the effect of rs678849 genotype was significant in the buprenorphine treatment group (RR = 1.69, 95% confidence interval (CI) 1.59-1.79, p = 0.021). Buprenorphine patients with the C/C genotype were more likely to have opioid-positive drug screens than individuals with the C/T or T/T genotypes, replicating the original pharmacogenetic finding. The effect of genotype was not significant in the methadone group (p = 0.087). Thus, the genotype at rs678849 is associated with buprenorphine efficacy in African-Americans being treated for opioid use disorder. This replication suggests that rs678849 genotype may be a valuable pharmacogenetic marker for deciding which opioid use disorder medication to prescribe in this population.
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Abstract
Increased physician prescribing of opioids to treat chronic nonprogressive pain has been accompanied by an increase in opioid addiction. Twin studies of opioid addiction are consistent with an inherited component of risk, approximately 50%. Several genome-wide association study (GWAS) reports indicate that genetic risk for opioid addiction is conveyed by many alleles of small effect (odds ratios <1.5). These reports have detected alleles in potassium-ion-channel genes (KCNC1 and KCNG2) and in a glutamate receptor auxiliary protein (CNIH3). Additionally, a variant at the µ-opioid receptor gene (OPRM1), which regulates OPRM1 expression appears promising. In pharmacogenetics of opioid addictions, methadone dose may be regulated by variants in cytochrome P450 2B6 (CYP2B6), a methadone-metabolizing enzyme, and by a locus 300 kb 5' to OPRM1. A δ-opioid-receptor gene single-nucleotide polymorphism may predict treatment response to methadone versus buprenorphine. To achieve better progress, larger sample sizes are needed for GWAS research, including controls with chronic opioid exposure, but no addiction. Large clinical trials comparing effective pharmacotherapies for opioid addiction (naltrexone, methadone, and buprenorphine) are needed for pharmacogenetic progress.
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Affiliation(s)
- Wade Berrettini
- Karl E. Rickels Professor of Psychiatry, Perelman School of Medicine, University of Pennsylvania, USA
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10
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Analysis of natural product regulation of opioid receptors in the treatment of human disease. Pharmacol Ther 2018; 184:51-80. [DOI: 10.1016/j.pharmthera.2017.10.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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11
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Abstract
Alzheimer's disease (AD), the main form of dementia in the elderly, is the most common progressive neurodegenerative disease characterized by rapidly progressive cognitive dysfunction and behavior impairment. AD exhibits a considerable heritability and great advances have been made in approaches to searching the genetic etiology of AD. In AD genetic studies, methods have developed from classic linkage-based and candidate-gene-based association studies to genome-wide association studies (GWAS) and next generation sequencing (NGS). The identification of new susceptibility genes has provided deeper insights to understand the mechanisms underlying AD. In addition to searching novel genes associated with AD in large samples, the NGS technologies can also be used to shed light on the 'black matter' discovery even in smaller samples. The shift in AD genetics between traditional studies and individual sequencing will allow biomaterials of each patient as the central unit of genetic studies. This review will cover genetic findings in AD and consequences of AD genetic findings. Firstly, we will discuss the discovery of mutations in APP, PSEN1, PSEN2, APOE, and ADAM10. Then we will summarize and evaluate the information obtained from GWAS of AD. Finally, we will outline the efforts to identify rare variants associated with AD using NGS.
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Albonaim A, Fazel H, Sharafshah A, Omarmeli V, Rezaei S, Ajamian F, Keshavarz P. Association of OPRK1 gene polymorphisms with opioid dependence in addicted men undergoing methadone treatment in an Iranian population. J Addict Dis 2017; 36:227-235. [DOI: 10.1080/10550887.2017.1361724] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Ali Albonaim
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences/University of Guilan, Rasht, Iran
| | - Hedyeh Fazel
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Alireza Sharafshah
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences/University of Guilan, Rasht, Iran
| | - Vahid Omarmeli
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences/University of Guilan, Rasht, Iran
| | - Sajjad Rezaei
- Department of Psychology, University of Guilan, Rasht, Iran
| | - Farzam Ajamian
- Department of Biology, Faculty of Sciences, University of Guilan, Rasht, Iran
| | - Parvaneh Keshavarz
- Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Guilan, Rasht, Iran
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Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Green RC, Harvey D, Jack CR, Jagust W, Morris JC, Petersen RC, Saykin AJ, Shaw LM, Toga AW, Trojanowski JQ. Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials. Alzheimers Dement 2017; 13:e1-e85. [PMID: 28342697 DOI: 10.1016/j.jalz.2016.11.007] [Citation(s) in RCA: 165] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 11/21/2016] [Accepted: 11/28/2016] [Indexed: 01/31/2023]
Abstract
INTRODUCTION The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015. METHODS We used standard searches to find publications using ADNI data. RESULTS (1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers. DISCUSSION Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.
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Affiliation(s)
- Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA
| | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - John C Morris
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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14
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Sharafshah A, Fazel H, Albonaim A, Omarmeli V, Rezaei S, Mirzajani E, Ajamian F, Keshavarz P. Association of OPRD1 Gene Variants with Opioid Dependence in Addicted Male Individuals Undergoing Methadone Treatment in the North of Iran. J Psychoactive Drugs 2017. [DOI: 10.1080/02791072.2017.1290303] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Alireza Sharafshah
- Master’s Student, Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
- Master’s Student, Genetic Laboratory, Department of Biology, Faculty of Sciences, University of Guilan, Rasht, Iran
| | - Hedyeh Fazel
- Master’s Student, Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Ali Albonaim
- Master’s Student, Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
- Master’s Student, Genetic Laboratory, Department of Biology, Faculty of Sciences, University of Guilan, Rasht, Iran
| | - Vahid Omarmeli
- Master’s Student, Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
- Master’s Student, Genetic Laboratory, Department of Biology, Faculty of Sciences, University of Guilan, Rasht, Iran
| | - Sajjad Rezaei
- Assistant Professor, Department of Psychology, University of Guilan, Rasht, Iran
| | - Ebrahim Mirzajani
- Assistant Professor, Department of Biochemistry and Biophysics, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Farzam Ajamian
- Assistant Professor in Molecular Genetics and Engineering, Department of Biology, Faculty of Sciences (FA), University of Guilan, Rasht, Iran
| | - Parvaneh Keshavarz
- Associate Professor, Cellular and Molecular Research Center, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran
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15
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Crist RC, Clarke TK. OPRD1 Genetic Variation and Human Disease. Handb Exp Pharmacol 2016; 247:131-145. [PMID: 28035534 DOI: 10.1007/164_2016_112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
The OPRD1 gene encodes the delta-opioid receptor, which has multiple functions including regulating reward pathways. The gene contains more than 2,000 verified genetic variants but only 2 currently have evidence for specific functions: rs1042114 disrupts maturation of the receptor and rs569356 affects OPRD1 expression. These polymorphisms and others in the gene have been found to be associated with human diseases. The most reproducible data are associations between opioid addiction and three variants in intron 1 (rs2236861, rs2236857, and rs3766951), which have been described in a number of independent populations. Several publications also point toward an association between anorexia and a haplotype block containing rs569356 and rs533123. Unfortunately the mechanisms underlying these two effects are currently unknown. In contrast, rs1042114 has been linked to Alzheimer's disease through an increasingly well-defined mechanism by which the variant allele reduces production of the beta-amyloid plaques associated with the disease. Additional studies of OPRD1 variants are necessary to replicate current findings and to delineate the functional roles of relevant polymorphisms.
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Affiliation(s)
- Richard C Crist
- Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania School of Medicine, 125 South 31st Street, Room 2207, Philadelphia, PA, 19104, USA.
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
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16
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A delta-opioid receptor genetic variant is associated with abstinence prior to and during cocaine dependence treatment. Drug Alcohol Depend 2016; 166:268-71. [PMID: 27449273 PMCID: PMC4983478 DOI: 10.1016/j.drugalcdep.2016.07.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Revised: 06/28/2016] [Accepted: 07/11/2016] [Indexed: 11/20/2022]
Abstract
INTRODUCTION An intronic polymorphism in the delta-opioid receptor gene (OPRD1) was previously associated with cocaine dependence in African-Americans. However, it is not known if the polymorphism (rs678849) is associated with dependence-related phenotypes within the cocaine dependent population. METHODS Cocaine and alcohol dependent subjects were randomized to either topiramate or placebo. Abstinence from cocaine use was confirmed by urine drug screens for benzoylecgonine three times per week. Cocaine withdrawal and craving were assessed at randomization using the Cocaine Selective Severity Assessment (CSSA) and Minnesota Cocaine Craving Scale (MCCS), respectively. Subjects were also interviewed using the Addiction Severity Index (ASI). Genotype at rs678849 was determined for 105 African-American subjects and compared to cocaine abstinence, as well as scores for CSSA, MCCS, and ASI. RESULTS African-American patients with the C/T or T/T genotypes (n=40) were more likely to be abstinent at the first urine drug screen and more likely to be abstinent for the week prior to randomization compared to patients with the C/C genotype (n=65). Subjects carrying the T allele were also more likely to have abstinent weeks over the course of the trial compared to those with the C/C genotype (RR=1.88, 95% CI=1.59-2.22, p=0.0035). No effects of rs678849 genotype on withdrawal, craving, or addiction severity were observed. CONCLUSIONS A polymorphism in OPRD1 appears to be associated with both cocaine dependence and cocaine use during treatment in African-Americans. Follow-up studies to confirm the effect on cocaine use are warranted.
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Tadayon SH, Vaziri-Pashkam M, Kahali P, Ansari Dezfouli M, Abbassian A. Common Genetic Variant in VIT Is Associated with Human Brain Asymmetry. Front Hum Neurosci 2016; 10:236. [PMID: 27252636 PMCID: PMC4877381 DOI: 10.3389/fnhum.2016.00236] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Accepted: 05/04/2016] [Indexed: 11/22/2022] Open
Abstract
Brain asymmetry varies across individuals. However, genetic factors contributing to this normal variation are largely unknown. Here we studied variation of cortical surface area asymmetry in a large sample of subjects. We performed principal component analysis (PCA) to capture correlated asymmetry variation across cortical regions. We found that caudal and rostral anterior cingulate together account for a substantial part of asymmetry variation among individuals. To find SNPs associated with this subset of brain asymmetry variation we performed a genome-wide association study followed by replication in an independent cohort. We identified one SNP (rs11691187) that had genome-wide significant association (PCombined = 2.40e-08). The rs11691187 is in the first intron of VIT. In a follow-up analysis, we found that VIT gene expression is associated with brain asymmetry in six donors of the Allen Human Brain Atlas. Based on these findings we suggest that VIT contributes to normal brain asymmetry variation. Our results can shed light on disorders associated with altered brain asymmetry.
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Affiliation(s)
- Sayed H Tadayon
- School of Cognitive Sciences, Institute for Research in Fundamental SciencesTehran, Iran; School of Mathematics, Institute for Research in Fundamental SciencesTehran, Iran
| | - Maryam Vaziri-Pashkam
- Vision Sciences Laboratory, Department of Psychology, Harvard University Cambridge, MA, USA
| | - Pegah Kahali
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences Tehran, Iran
| | - Mitra Ansari Dezfouli
- Department of Cell and Molecular Biology, School of Biology, College of Science, University of Tehran Tehran, Iran
| | - Abdolhossein Abbassian
- School of Cognitive Sciences, Institute for Research in Fundamental SciencesTehran, Iran; School of Mathematics, Institute for Research in Fundamental SciencesTehran, Iran
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18
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Jack CR, Barnes J, Bernstein MA, Borowski BJ, Brewer J, Clegg S, Dale AM, Carmichael O, Ching C, DeCarli C, Desikan RS, Fennema-Notestine C, Fjell AM, Fletcher E, Fox NC, Gunter J, Gutman BA, Holland D, Hua X, Insel P, Kantarci K, Killiany RJ, Krueger G, Leung KK, Mackin S, Maillard P, Malone IB, Mattsson N, McEvoy L, Modat M, Mueller S, Nosheny R, Ourselin S, Schuff N, Senjem ML, Simonson A, Thompson PM, Rettmann D, Vemuri P, Walhovd K, Zhao Y, Zuk S, Weiner M. Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2. Alzheimers Dement 2016; 11:740-56. [PMID: 26194310 DOI: 10.1016/j.jalz.2015.05.002] [Citation(s) in RCA: 109] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2015] [Revised: 04/28/2015] [Accepted: 05/05/2015] [Indexed: 01/18/2023]
Abstract
INTRODUCTION Alzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders. METHODS We review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3. RESULTS Contributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials. DISCUSSION Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future.
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Affiliation(s)
| | - Josephine Barnes
- Department of Neurodegenerative Disease, Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | | | | | - James Brewer
- Department of Neuroscience, University of California at San Diego, La Jolla, CA, USA
| | - Shona Clegg
- Department of Neurodegenerative Disease, Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Anders M Dale
- Department of Neuroscience, University of California at San Diego, La Jolla, CA, USA
| | - Owen Carmichael
- Department of Neurology, University of California at Davis, Davis, CA, USA
| | - Christopher Ching
- Department of Neurology, Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, USA
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Davis, CA, USA; Center for Neuroscience, University of California at Davis, Davis, CA, USA
| | - Rahul S Desikan
- Department of Radiology, University of California at San Diego, La Jolla, CA, USA
| | - Christine Fennema-Notestine
- Department of Radiology, University of California at San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California at San Diego, La Jolla, CA, USA
| | - Anders M Fjell
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Evan Fletcher
- Department of Neurology, University of California at Davis, Davis, CA, USA; Center for Neuroscience, University of California at Davis, Davis, CA, USA
| | - Nick C Fox
- Department of Neurodegenerative Disease, Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Jeff Gunter
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Boris A Gutman
- Department of Neurology, Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, USA
| | - Dominic Holland
- Department of Neuroscience, University of California at San Diego, La Jolla, CA, USA
| | - Xue Hua
- Department of Neurology, Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, USA
| | - Philip Insel
- Department of Radiology and Biomedical Imaging, Center for Imaging of Neurodegenerative Diseases, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Ron J Killiany
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | | | - Kelvin K Leung
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Scott Mackin
- Department of Radiology and Biomedical Imaging, Center for Imaging of Neurodegenerative Diseases, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Department of Psychiatry, University of California at San Francisco, San Francisco, CA, USA
| | - Pauline Maillard
- Department of Neurology, University of California at Davis, Davis, CA, USA; Center for Neuroscience, University of California at Davis, Davis, CA, USA
| | - Ian B Malone
- Department of Neurodegenerative Disease, Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Niklas Mattsson
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
| | - Linda McEvoy
- Department of Radiology, University of California at San Diego, La Jolla, CA, USA
| | - Marc Modat
- Department of Neurodegenerative Disease, Dementia Research Centre, Institute of Neurology, University College London, London, UK; Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Susanne Mueller
- Department of Radiology and Biomedical Imaging, Center for Imaging of Neurodegenerative Diseases, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Department of Radiology, University of California at San Francisco, San Francisco, CA, USA
| | - Rachel Nosheny
- Department of Radiology and Biomedical Imaging, Center for Imaging of Neurodegenerative Diseases, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Department of Radiology, University of California at San Francisco, San Francisco, CA, USA
| | - Sebastien Ourselin
- Department of Neurodegenerative Disease, Dementia Research Centre, Institute of Neurology, University College London, London, UK; Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Norbert Schuff
- Department of Radiology and Biomedical Imaging, Center for Imaging of Neurodegenerative Diseases, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Department of Radiology, University of California at San Francisco, San Francisco, CA, USA
| | | | - Alix Simonson
- Department of Radiology and Biomedical Imaging, Center for Imaging of Neurodegenerative Diseases, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Paul M Thompson
- Department of Neurology, Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, USA
| | - Dan Rettmann
- MR Applications and Workflow, GE Healthcare, Rochester, MN, USA
| | | | | | | | - Samantha Zuk
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Michael Weiner
- Department of Radiology and Biomedical Imaging, Center for Imaging of Neurodegenerative Diseases, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Department of Psychiatry, University of California at San Francisco, San Francisco, CA, USA; Department of Radiology, University of California at San Francisco, San Francisco, CA, USA; Department of Medicine, University of California at San Francisco, San Francisco, CA, USA; Department of Neurology, University of California at San Francisco, San Francisco, CA, USA
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Roussotte FF, Jahanshad N, Hibar DP, Thompson PM. Altered regional brain volumes in elderly carriers of a risk variant for drug abuse in the dopamine D2 receptor gene (DRD2). Brain Imaging Behav 2016; 9:213-22. [PMID: 24634060 DOI: 10.1007/s11682-014-9298-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Dopamine D2 receptors mediate the rewarding effects of many drugs of abuse. In humans, several polymorphisms in DRD2, the gene encoding these receptors, increase our genetic risk for developing addictive disorders. Here, we examined one of the most frequently studied candidate variant for addiction in DRD2 for association with brain structure. We tested whether this variant showed associations with regional brain volumes across two independent elderly cohorts, totaling 1,032 subjects. We first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI1). We hypothesized that this addiction-related polymorphism would be associated with structural brain differences in regions previously implicated in familial vulnerability for drug dependence. Then, we assessed the generalizability of our findings by testing this polymorphism in a non-overlapping replication sample of 294 elderly subjects from a continuation of the first ADNI project (ADNI2) to minimize the risk of reporting false positive results. In both cohorts, the minor allele-previously linked with increased risk for addiction-was associated with larger volumes in various brain regions implicated in reward processing. These findings suggest that neuroanatomical phenotypes associated with familial vulnerability for drug dependence may be partially mediated by DRD2 genotype.
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Affiliation(s)
- Florence F Roussotte
- Imaging Genetics Center, Institute for Neuroimaging and Informatics Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
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Abstract
This paper is the thirty-seventh consecutive installment of the annual review of research concerning the endogenous opioid system. It summarizes papers published during 2014 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior (endogenous opioids and receptors), and the roles of these opioid peptides and receptors in pain and analgesia (pain and analgesia); stress and social status (human studies); tolerance and dependence (opioid mediation of other analgesic responses); learning and memory (stress and social status); eating and drinking (stress-induced analgesia); alcohol and drugs of abuse (emotional responses in opioid-mediated behaviors); sexual activity and hormones, pregnancy, development and endocrinology (opioid involvement in stress response regulation); mental illness and mood (tolerance and dependence); seizures and neurologic disorders (learning and memory); electrical-related activity and neurophysiology (opiates and conditioned place preferences (CPP)); general activity and locomotion (eating and drinking); gastrointestinal, renal and hepatic functions (alcohol and drugs of abuse); cardiovascular responses (opiates and ethanol); respiration and thermoregulation (opiates and THC); and immunological responses (opiates and stimulants). This paper is the thirty-seventh consecutive installment of the annual review of research concerning the endogenous opioid system. It summarizes papers published during 2014 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior (endogenous opioids and receptors), and the roles of these opioid peptides and receptors in pain and analgesia (pain and analgesia); stress and social status (human studies); tolerance and dependence (opioid mediation of other analgesic responses); learning and memory (stress and social status); eating and drinking (stress-induced analgesia); alcohol and drugs of abuse (emotional responses in opioid-mediated behaviors); sexual activity and hormones, pregnancy, development and endocrinology (opioid involvement in stress response regulation); mental illness and mood (tolerance and dependence); seizures and neurologic disorders (learning and memory); electrical-related activity and neurophysiology (opiates and conditioned place preferences (CPP)); general activity and locomotion (eating and drinking); gastrointestinal, renal and hepatic functions (alcohol and drugs of abuse); cardiovascular responses (opiates and ethanol); respiration and thermoregulation (opiates and THC); and immunological responses (opiates and stimulants).
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Affiliation(s)
- Richard J Bodnar
- Department of Psychology and Neuropsychology Doctoral Sub-Program, Queens College, City University of New York, Flushing, NY 11367, United States.
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21
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In-vivo brain neuroimaging provides a gateway for integrating biological and clinical biomarkers of Alzheimer's disease. Curr Opin Neurol 2015; 28:351-7. [DOI: 10.1097/wco.0000000000000225] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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22
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Saykin AJ, Shen L, Yao X, Kim S, Nho K, Risacher SL, Ramanan VK, Foroud TM, Faber KM, Sarwar N, Munsie LM, Hu X, Soares HD, Potkin SG, Thompson PM, Kauwe JSK, Kaddurah-Daouk R, Green RC, Toga AW, Weiner MW. Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans. Alzheimers Dement 2015; 11:792-814. [PMID: 26194313 PMCID: PMC4510473 DOI: 10.1016/j.jalz.2015.05.009] [Citation(s) in RCA: 202] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2015] [Revised: 05/08/2015] [Accepted: 05/08/2015] [Indexed: 01/01/2023]
Abstract
INTRODUCTION Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. METHODS Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated. RESULTS ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD. DISCUSSION Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.
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Affiliation(s)
- Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Li Shen
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xiaohui Yao
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; School of Informatics and Computing, Indiana University, Purdue University - Indianapolis, Indianapolis, IN, USA
| | - Sungeun Kim
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Vijay K Ramanan
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tatiana M Foroud
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kelley M Faber
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | | | - Xiaolan Hu
- Bristol-Myers Squibb, Wallingford, CT, USA
| | | | - Steven G Potkin
- Department of Psychiatry and Human Behavior, University of California - Irvine, Irvine, CA, USA
| | - Paul M Thompson
- Department of Neurology, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA; Imaging Genetics Center, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA
| | - John S K Kauwe
- Department of Biology, Brigham Young University, Provo, UT, USA; Department of Neuroscience, Brigham Young University, Provo, UT, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - Robert C Green
- Partners Center for Personalized Genetic Medicine, Boston, MA, USA; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute for Neuroimaging and Neuroinformatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Michael W Weiner
- Department of Radiology, University of California-San Francisco, San Francisco, CA, USA; Department of Medicine, University of California-San Francisco, San Francisco, CA, USA; Department of Psychiatry, University of California-San Francisco, San Francisco, CA, USA; Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center, San Francisco, CA, USA
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23
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Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Cedarbaum J, Green RC, Harvey D, Jack CR, Jagust W, Luthman J, Morris JC, Petersen RC, Saykin AJ, Shaw L, Shen L, Schwarz A, Toga AW, Trojanowski JQ. 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception. Alzheimers Dement 2015; 11:e1-120. [PMID: 26073027 PMCID: PMC5469297 DOI: 10.1016/j.jalz.2014.11.001] [Citation(s) in RCA: 203] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 04/18/2013] [Indexed: 01/18/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.
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Affiliation(s)
- Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA
| | - Paul S Aisen
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Jesse Cedarbaum
- Neurology Early Clinical Development, Biogen Idec, Cambridge, MA, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Johan Luthman
- Neuroscience Clinical Development, Neuroscience & General Medicine Product Creation Unit, Eisai Inc., Philadelphia, PA, USA
| | - John C Morris
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li Shen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adam Schwarz
- Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Strike LT, Couvy-Duchesne B, Hansell NK, Cuellar-Partida G, Medland SE, Wright MJ. Genetics and Brain Morphology. Neuropsychol Rev 2015; 25:63-96. [DOI: 10.1007/s11065-015-9281-1] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Accepted: 02/08/2015] [Indexed: 12/17/2022]
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Roussotte FF, Daianu M, Jahanshad N, Leonardo CD, Thompson PM. Neuroimaging and genetic risk for Alzheimer's disease and addiction-related degenerative brain disorders. Brain Imaging Behav 2014; 8:217-233. [PMID: 24142306 PMCID: PMC3992278 DOI: 10.1007/s11682-013-9263-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Neuroimaging offers a powerful means to assess the trajectory of brain degeneration in a variety of disorders, including Alzheimer's disease (AD). Here we describe how multi-modal imaging can be used to study the changing brain during the different stages of AD. We integrate findings from a range of studies using magnetic resonance imaging (MRI), positron emission tomography (PET), functional MRI (fMRI) and diffusion weighted imaging (DWI). Neuroimaging reveals how risk genes for degenerative disorders affect the brain, including several recently discovered genetic variants that may disrupt brain connectivity. We review some recent neuroimaging studies of genetic polymorphisms associated with increased risk for late-onset Alzheimer's disease (LOAD). Some genetic variants that increase risk for drug addiction may overlap with those associated with degenerative brain disorders. These common associations offer new insight into mechanisms underlying neurodegeneration and addictive behaviors, and may offer new leads for treating them before severe and irreversible neurological symptoms appear.
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Affiliation(s)
- Florence F Roussotte
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Madelaine Daianu
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Cassandra D Leonardo
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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Roussotte FF, Gutman BA, Hibar DP, Jahanshad N, Madsen SK, Jack CR, Weiner MW, Thompson PM. A single nucleotide polymorphism associated with reduced alcohol intake in the RASGRF2 gene predicts larger cortical volumes but faster longitudinal ventricular expansion in the elderly. Front Aging Neurosci 2013; 5:93. [PMID: 24409144 PMCID: PMC3867747 DOI: 10.3389/fnagi.2013.00093] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2013] [Accepted: 11/30/2013] [Indexed: 11/23/2022] Open
Abstract
A recent genome-wide association meta-analysis showed a suggestive association between alcohol intake in humans and a common single nucleotide polymorphism in the ras-specific guanine nucleotide releasing factor 2 gene. Here, we tested whether this variant – associated with lower alcohol consumption – showed associations with brain structure and longitudinal ventricular expansion over time, across two independent elderly cohorts, totaling 1,032 subjects. We first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI1). Then, we assessed the generalizability of the findings by testing this polymorphism in a replication sample of 294 elderly subjects from a continuation of the first ADNI project (ADNI2) to minimize the risk of reporting false positive results. The minor allele – previously linked with lower alcohol intake – was associated with larger volumes in various cortical regions, notably the medial prefrontal cortex and cingulate gyrus in both cohorts. Intriguingly, the same allele also predicted faster ventricular expansion rates in the ADNI1 cohort at 1- and 2-year follow up. Despite a lack of alcohol consumption data in this study cohort, these findings, combined with earlier functional imaging investigations of the same gene, suggest the existence of reciprocal interactions between genes, brain, and drinking behavior.
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Affiliation(s)
- Florence F Roussotte
- Imaging Genetics Center, University of Southern California Los Angeles, CA, USA ; Departments of Neurology and Psychiatry, David Geffen School of Medicine at University of California Los Angeles Los Angeles, CA, USA
| | - Boris A Gutman
- Imaging Genetics Center, University of Southern California Los Angeles, CA, USA
| | - Derrek P Hibar
- Imaging Genetics Center, University of Southern California Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, University of Southern California Los Angeles, CA, USA
| | - Sarah K Madsen
- Imaging Genetics Center, University of Southern California Los Angeles, CA, USA
| | | | - Michael W Weiner
- Departments of Radiology, Medicine, Psychiatry, University of California San Francisco San Francisco, CA, USA ; Department of Veterans Affairs Medical Center San Francisco, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, University of Southern California Los Angeles, CA, USA ; Departments of Neurology and Psychiatry, David Geffen School of Medicine at University of California Los Angeles Los Angeles, CA, USA ; Departments of Neurology, Psychiatry, Pediatrics, Engineering, Radiology, and Ophthalmology, Keck University of Southern California School of Medicine, University of Southern California , Los Angeles, CA, USA
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27
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Thompson PM, Ge T, Glahn DC, Jahanshad N, Nichols TE. Genetics of the connectome. Neuroimage 2013; 80:475-88. [PMID: 23707675 PMCID: PMC3905600 DOI: 10.1016/j.neuroimage.2013.05.013] [Citation(s) in RCA: 132] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2013] [Revised: 05/05/2013] [Accepted: 05/08/2013] [Indexed: 11/24/2022] Open
Abstract
Connectome genetics attempts to discover how genetic factors affect brain connectivity. Here we review a variety of genetic analysis methods--such as genome-wide association studies (GWAS), linkage and candidate gene studies--that have been fruitfully adapted to imaging data to implicate specific variants in the genome for brain-related traits. Studies that emphasized the genetic influences on brain connectivity. Some of these analyses of brain integrity and connectivity using diffusion MRI, and others have mapped genetic effects on functional networks using resting state functional MRI. Connectome-wide genome-wide scans have also been conducted, and we review the multivariate methods required to handle the extremely high dimension of the genomic and network data. We also review some consortium efforts, such as ENIGMA, that offer the power to detect robust common genetic associations using phenotypic harmonization procedures and meta-analysis. Current work on connectome genetics is advancing on many fronts and promises to shed light on how disease risk genes affect the brain. It is already discovering new genetic loci and even entire genetic networks that affect brain organization and connectivity.
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Affiliation(s)
- Paul M Thompson
- Imaging Genetics Center, Laboratory of NeuroImaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA.
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