scholarly journals Associations between polygenic risk for schizophrenia and brain function during probabilistic learning in healthy individuals

2015 ◽  
Vol 37 (2) ◽  
pp. 491-500 ◽  
Author(s):  
Thomas M. Lancaster ◽  
Niklas Ihssen ◽  
Lisa M. Brindley ◽  
Katherine E. Tansey ◽  
Kiran Mantripragada ◽  
...  
Keyword(s):  
Brain Function ◽  
Healthy Individuals ◽  
Probabilistic Learning ◽  
Polygenic Risk

scholarly journals Brain function during probabilistic learning in relation to IQ and level of education

2012 ◽  
Vol 2 ◽  
pp. S78-S89 ◽  
Author(s):  
Wouter van den Bos ◽  
Eveline A. Crone ◽  
Berna Güroğlu
Keyword(s):  
Brain Function ◽  
Probabilistic Learning ◽  
Level Of Education

Individualized Prediction of Follicular Lymphoma Risk Using a Combination of Blood t(14;18) Frequency Years before Diagnosis and a Polygenic Risk Score (PRS) of 9 SNPs Associated with Follicular Lymphoma Susceptibility

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2775-2775
Author(s):  
Herve Ghesquieres ◽  
Youenn Drouet ◽  
Manon Zala ◽  
Paolo Vineis ◽  
Gilles A. Salles ◽  
...  
Keyword(s):  
High Risk ◽  
Follicular Lymphoma ◽  
Board Of Directors ◽  
Roc Curve ◽  
Genetic Variants ◽  
Epidemiological Studies ◽  
Polygenic Risk Score ◽  
Healthy Individuals ◽  
Advisory Committees ◽  
Polygenic Risk

Introduction: The risk of developing a follicular lymphoma (FL) begins to be better understood with the identification in large epidemiological studies of familial predisposition, some occupational exposures and genetic factors. Genome wide-association studies (GWAS) identified constitutional single nucleotide polymorphisms (SNPs) at risk of FL in HLA region (rs12195582), in 11q23.3 (near CXCR5), in 11q24.3 (near ETS1), in 3q28 (near LPP), in 18q21.33 (near BCL2), and 8q24 (near PVT1); three suggestive loci are localized at 17q25.3 (near CYBC1), 3q13.33 (CD86), 18q12.3 (SLC14A2) (Skibola, Am J Hum Genet. 2014). High t(14;18) frequency in blood years before diagnosis from healthy individuals was also defined as a predictive biomarker for FL (Roulland, J Clin Oncol 2014). It is currently unknown whether any relationship exists between inherited genetic variants associated with FL susceptibility and t(14;18) frequency and if the combination of the two biomarkers could be useful for a better stratification of risk of FL development in healthy individuals. Methods: We used quantitative PCR assays to estimate t(14;18) frequency in prediagnostic blood samples from 105 individuals that were obtained on average 6.4 years before FL diagnosis (pre-FL group) together with 236 age and gender-matched individuals (control group) that were issued from the participants in the EPIC cohort ( European Prospective Investigation Into Cancer and Nutrition). Constitutional DNA was analyzed for the genotyping of the nine SNPs associated with FL risk (HLA, rs12195582; CXCR5, rs4938573; ETS1, rs4937362; LPP, rs6444305; BCL2, rs17749561; PVT1, rs13254990; CYBC1, rs3751913; CD86, rs2681416; SLC14A2, rs11082438). Genotyping were performed in duplicate using TaqMan® assays on Fluidigm platform. The nine SNPs were analyzed individually and combined in a polygenic risk score (PRS). PRS is a weighted average of the number of risk alleles with the weights being the log of the odds-ratio (OR) reported in the FL GWAS (Skibola, Am J Hum Genet. 2014). A model for FL risk was developed using multivariable logistic regression. Predictive ability was assessed by area under Receiver Operating Characteristic (ROC) curve, with 10-fold cross-validation. This work is supported by the French NCI (INCA, PRT-K16-167). Results: t(14;18) frequency as a log-transformed continuous variable is predictive of FL risk (OR: 1.50; 95%CI: 1.29-1.78, P<0.001); PRS is also strongly associated with FL risk (OR: 3.31; 95%CI: 2.01-5.62, P<0.001). Age at screening (OR: 0.98; 95%CI: 0.95-1.01, P=0.24) did not influence FL risk. A weak but statistically significant correlation between t(14; 18) frequency and PRS was observed (Pearson correlation=0.18, P=0.002). In multivariable analysis, both PRS (OR: 2.84, 95%CI: 1.66-4.99, P<0.001) and t(14;18) frequency (OR: 1.45, 95%CI: 1.18-1.84, P<0.001) remained statistically significant. No departure from log-linear effect was observed in the modeling nor statistical interaction between PRS and log-transformed t(14;18), confirming that t(14; 18) frequency and genetic markers (PRS) were two independent factors of FL risk. Sensitivity analyses showed that these results were not influenced by the delay between the date of the screening and the FL diagnosis. Combining t(14;18) frequency and the PRS in a prediction model allowed the identification of some individuals at very high risk of developing FL and a shiny web application was developed to provide an easy-to-use tool to obtain individualized risk predictions for new patients (Figure). Area under ROC curve (AUC) showed that the model that integrated t(14;18) frequency and PRS (AUC: 0.69, 95%CI: 0.62-0.76) had a better prediction of FL risk than t(14;18) frequency (AUC: 0.62, 95%CI: 0.55-0.70) and PRS alone (AUC: 0.68, 95%CI: 0.61-0.75). Conclusions: Genetic variants combined in PRS and t(14;18) frequency allowed the identification of individuals at high-risk of FL development and provided a better way, when these two biomarkers were combined, to discriminate healthy individuals from pre-FL cases many years before malignant transformation. These findings could be used for screening test of populations with some environmental exposures positively associated with FL development in epidemiological studies and may contribute in the future to monitoring or early intervention. Figure Disclosures Salles: Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Amgen: Honoraria, Other: Educational events; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Epizyme: Consultancy, Honoraria.

The Neuroscientific Study of Music: A Burgeoning Discipline

2018 ◽  
pp. 1-16 ◽  
Author(s):  
Donald A. Hodges ◽  
Michael H. Thaut
Keyword(s):  
Eighteenth Century ◽  
Brain Function ◽  
Research Literature ◽  
Neural Responses ◽  
Healthy Individuals ◽  
Developmental Issues ◽  
Cultural Contexts ◽  
Early Twenty ◽  
Franz Joseph Gall ◽  
The Brain

Numerous pioneers laid the groundwork for current neuromusical research. Beginning with Franz Joseph Gall in the eighteenth century, and continuing with John Hughlings Jackson, August Knoblauch, Richard Wallaschek, and others, these early forerunners were interested in localizing musicality in the brain and learning more about how music is processed in both healthy individuals and those with dysfunctions of various kinds. Since then, research literature has mushroomed, especially in the latter part of the twentieth and early twenty-first centuries. The current volume features the work of fifty-four authors who have contributed over 350,000 words in thirty-three chapters. These chapters are organized into sections on music, the brain, and cultural contexts; music processing in the human brain; neural responses to music; musicianship and brain function; developmental issues in music and the brain; music, the brain, and health; and the future.

PW01-153 - Effect of DAAO on regional brain function in healthy individuals and patients with schizophrenia and bipolar disorder

2010 ◽  
Vol 25 ◽  
pp. 1569
Author(s):  
S.A. Papagni ◽  
A. Mechelli ◽  
D. Prata ◽  
J. Kambeitz ◽  
M. Picchioni ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Brain Function ◽  
Healthy Individuals ◽  
Regional Brain

Genetic Variation in Serotonin Transporter Alters Resting Brain Function in Healthy Individuals

2007 ◽  
Vol 62 (6) ◽  
pp. 600-606 ◽  
Author(s):  
Hengyi Rao ◽  
Seth J. Gillihan ◽  
Jiongjiong Wang ◽  
Marc Korczykowski ◽  
Geena Mary V. Sankoorikal ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Serotonin Transporter ◽  
Brain Function ◽  
Healthy Individuals

scholarly journals Sex-specific effects of polygenic risk for schizophrenia on lifespan cognitive functioning in healthy individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Elise Koch ◽  
Lars Nyberg ◽  
Anders Lundquist ◽  
Sara Pudas ◽  
Rolf Adolfsson ◽  
...  
Keyword(s):  
Sex Differences ◽  
Cognitive Decline ◽  
Cognitive Functioning ◽  
Cognitive Ability ◽  
Cognitive Change ◽  
Polygenic Risk Score ◽  
Healthy Individuals ◽  
Polygenic Risk ◽  
Specific Effects ◽  
Male Specific

AbstractPolygenic risk for schizophrenia has been associated with lower cognitive ability and age-related cognitive change in healthy individuals. Despite well-established neuropsychological sex differences in schizophrenia patients, genetic studies on sex differences in schizophrenia in relation to cognitive phenotypes are scarce. Here, we investigated whether the effect of a polygenic risk score (PRS) for schizophrenia on childhood, midlife, and late-life cognitive function in healthy individuals is modified by sex, and if PRS is linked to accelerated cognitive decline. Using a longitudinal data set from healthy individuals aged 25–100 years (N = 1459) spanning a 25-year period, we found that PRS was associated with lower cognitive ability (episodic memory, semantic memory, visuospatial ability), but not with accelerated cognitive decline. A significant interaction effect between sex and PRS was seen on cognitive task performance, and sex-stratified analyses showed that the effect of PRS was male-specific. In a sub-sample, we observed a male-specific effect of the PRS on school performance at age 12 (N = 496). Our findings of sex-specific effects of schizophrenia genetics on cognitive functioning across the lifespan indicate that the effects of underlying disease genetics on cognitive functioning is dependent on biological processes that differ between the sexes.

F132. The Effect of Telomere Length and Their Polygenic Risk Scores on Emotional Brain Function and Connectivity

2018 ◽  
Vol 83 (9) ◽  
pp. S289
Author(s):  
Danai Dima ◽  
Simone de Jong ◽  
Gerome Breen ◽  
Cathryn Lewis ◽  
Sophia Frangou ◽  
...  
Keyword(s):  
Telomere Length ◽  
Brain Function ◽  
Risk Scores ◽  
Polygenic Risk

scholarly journals A critical role of brain network architecture in a continuum model of autism spectrum disorders spanning from healthy individuals with genetic liability to individuals with ASD

2021 ◽  
Author(s):  
Budhachandra Khundrakpam ◽  
Neha Bhutani ◽  
Uku Vainik ◽  
Noor B Al-Sharif ◽  
Alain Dagher ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Network Architecture ◽  
Continuum Model ◽  
Critical Role ◽  
Autism Spectrum ◽  
Brain Network ◽  
Healthy Individuals ◽  
Polygenic Risk ◽  
Spectrum Disorders

Studies have shown cortical alterations in individuals with autism spectrum disorders (ASD) as well as in individuals with high polygenic risk for ASD. An important addition to the study of altered cortical anatomy is the investigation of the underlying brain network architecture that may reveal brain-wide mechanisms in ASD and in polygenic risk for ASD. Such an approach has been proven useful in other psychiatric disorders by revealing that brain network architecture shapes (to an extent) the disorder-related cortical alterations. This study uses data from a clinical dataset: 560 male subjects (266 individuals with ASD and 294 healthy individuals, CTL, mean age at 17.2 years) from the Autism Brain Imaging Data Exchange database, and data of 391 healthy individuals (207 males, mean age at 12.1 years) from the Pediatric Imaging, Neurocognition and Genetics database. ASD-related cortical alterations (group difference, ASD-CTL, in cortical thickness) and cortical correlates of polygenic risk for ASD were assessed, and then statistically compared with structural connectome-based network measures (such as hubs) using spin permutation tests. Next, we investigated whether polygenic risk for ASD could be predicted by network architecture by building machine-learning based prediction models, and whether the top predictors of the model were identified as disease epicenters of ASD. We observed that ASD-related cortical alterations as well as cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. We also observed that age progression of ASD-related cortical alterations and cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. Further investigation revealed that structural connectomes predicted polygenic risk for ASD (r=0.30, p<0.0001), and two brain regions (the left inferior parietal and left suparmarginal) with top predictive connections were identified as disease epicenters of ASD. Our study highlights a critical role of network architecture in a continuum model of ASD spanning from healthy individuals with genetic risk to individuals with ASD. Our study also highlights the strength of investigating polygenic risk scores in addition to multi-modal neuroimaging measures to better understand the interplay between genetic risk and brain alterations associated with ASD.

Genetic variation in CNTNAP2 alters brain function during linguistic processing in healthy individuals

2011 ◽  
Vol 156 (8) ◽  
pp. 941-948 ◽  
Author(s):  
Heather C. Whalley ◽  
Garret O'Connell ◽  
Jessika E. Sussmann ◽  
Anna Peel ◽  
Andrew C. Stanfield ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Brain Function ◽  
Healthy Individuals ◽  
Linguistic Processing
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