scholarly journals Structural Brain MRI Trait Polygenic Score Prediction of Cognitive Abilities

2015 ◽  
Vol 18 (6) ◽  
pp. 738-745 ◽  
Author(s):  
Michelle Luciano ◽  
Riccardo E. Marioni ◽  
Maria Valdés Hernández ◽  
Susana Muñoz Maniega ◽  
Iona F. Hamilton ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Brain Mri ◽  
Phenotypic Traits ◽  
Intracranial Volume ◽  
Birth Cohorts ◽  
Polygenic Score ◽  
Cognitive Measure ◽  
Polygenic Scores ◽  
Cognitive Traits ◽  
Structural Brain

Structural brain magnetic resonance imaging (MRI) traits share part of their genetic variance with cognitive traits. Here, we use genetic association results from large meta-analytic studies of genome-wide association (GWA) for brain infarcts (BI), white matter hyperintensities, intracranial, hippocampal, and total brain volumes to estimate polygenic scores for these traits in three Scottish samples: Generation Scotland: Scottish Family Health Study (GS:SFHS), and the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921). These five brain MRI trait polygenic scores were then used to: (1) predict corresponding MRI traits in the LBC1936 (numbers ranged 573 to 630 across traits), and (2) predict cognitive traits in all three cohorts (in 8,115–8,250 persons). In the LBC1936, all MRI phenotypic traits were correlated with at least one cognitive measure, and polygenic prediction of MRI traits was observed for intracranial volume. Meta-analysis of the correlations between MRI polygenic scores and cognitive traits revealed a significant negative correlation (maximal r = 0.08) between the HV polygenic score and measures of global cognitive ability collected in childhood and in old age in the Lothian Birth Cohorts. The lack of association to a related general cognitive measure when including the GS:SFHS points to either type 1 error or the importance of using prediction samples that closely match the demographics of the GWA samples from which prediction is based. Ideally, these analyses should be repeated in larger samples with data on both MRI and cognition, and using MRI GWA results from even larger meta-analysis studies.

scholarly journals Comparing within- and between-family polygenic score prediction

2019 ◽  
Author(s):  
Saskia Selzam ◽  
Stuart J. Ritchie ◽  
Jean-Baptiste Pingault ◽  
Chandra A. Reynolds ◽  
Paul F. O’Reilly ◽  
...  
Keyword(s):  
Assortative Mating ◽  
Complex Traits ◽  
Population Stratification ◽  
Educational Achievement ◽  
Economic Status ◽  
Life Outcomes ◽  
Polygenic Score ◽  
Family Effects ◽  
Polygenic Scores ◽  
Cognitive Traits

AbstractPolygenic scores are a popular tool for prediction of complex traits. However, prediction estimates in samples of unrelated participants can include effects of population stratification, assortative mating and environmentally mediated parental genetic effects, a form of genotype-environment correlation (rGE). Comparing genome-wide polygenic score (GPS) predictions in unrelated individuals with predictions between siblings in a within-family design is a powerful approach to identify these different sources of prediction. Here, we compared within- to between-family GPS predictions of eight life outcomes (anthropometric, cognitive, personality and health) for eight corresponding GPSs. The outcomes were assessed in up to 2,366 dizygotic (DZ) twin pairs from the Twins Early Development Study from age 12 to age 21. To account for family clustering, we used mixed-effects modelling, simultaneously estimating within- and between-family effects for target- and cross-trait GPS prediction of the outcomes. There were three main findings: (1) DZ twin GPS differences predicted DZ differences in height, BMI, intelligence, educational achievement and ADHD symptoms; (2) target and cross-trait analyses indicated that GPS prediction estimates for cognitive traits (intelligence and educational achievement) were on average 60% greater between families than within families, but this was not the case for non-cognitive traits; and (3) this within- and between-family difference for cognitive traits disappeared after controlling for family socio-economic status (SES), suggesting that SES is a source of between-family prediction through rGE mechanisms. These results provide novel insights into the patterns by which rGE contributes to GPS prediction, while ruling out confounding due to population stratification and assortative mating.

scholarly journals The nature of nurture: effects of parental genotypes

2017 ◽  
Author(s):  
Augustine Kong ◽  
Gudmar Thorleifsson ◽  
Michael L. Frigge ◽  
Bjarni J. Vilhjálmsson ◽  
Alexander I. Young ◽  
...  
Keyword(s):  
Educational Attainment ◽  
Meta Analysis ◽  
Genetic Component ◽  
Sequence Variants ◽  
Genetic Studies ◽  
Polygenic Score ◽  
Polygenic Scores

AbstractSequence variants in the parental genomes that are not transmitted to a child/proband are often ignored in genetic studies. Here we show that non-transmitted alleles can impact a child through their effects on the parents and other relatives, a phenomenon we call genetic nurture. Using results from a meta-analysis of educational attainment, the polygenic score computed for the non-transmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% (P = 1.6×10−14) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition/heath related traits.One Sentence SummaryNurture has a genetic component, i.e. alleles in the parents affect the parents’ phenotypes and through that influence the outcomes of the child.

Abstract MP24: Sedentary Behavior (SB) In Mid-life And Structural Brain Magnetic Resonance Imaging (MRI) Markers Of Cerebrovascular Disease And Neurodegeneration In Late-life: The Atherosclerosis Risk In Communities Neurocognitive Study (ARIC-NCS)

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Kelley Pettee Gabriel ◽  
Keith Diaz ◽  
Aarti Kumar ◽  
A Richey Sharrett ◽  
Kelly R Evenson ◽  
...  
Keyword(s):  
Grey Matter ◽  
Television Viewing ◽  
Brain Mri ◽  
Late Life ◽  
Intracranial Volume ◽  
Inverse Association ◽  
Sampling Weights ◽  
Cerebrovascular Lesions ◽  
Deep Grey Matter ◽  
Structural Brain

Introduction: Few prospective studies have examined the associations of SB on brain MRI markers. We tested the hypotheses that higher levels of, and persistence of mid-life television viewing, a cognitively passive SB, are associated with structural brain MRI markers in late-life, and that these associations are independent from physical activity (PA). Methods: ARIC participants (n=1,601, mean age: 76.2 years, 60.5% female, 27.2% Black) with reported television viewing at visits 1 (1987-89) and 3 (1993-95), and brain MRI in 2011-13 were included. Participants were categorized as low [never/seldom], medium [sometimes], or high [often/very often] television viewing. Persistent pattern of television viewing was quantified as the same frequency of reported television viewing at visits 1 and 3 (n=971). Imaging using 3T brain MRI quantified the presence of cerebrovascular lesions, white matter microstructural integrity and disease, and grey matter volumes using a standardized protocol. Models were adjusted for age, race-center, sex, education, APOE-ε4, smoking status, and total intracranial volume in volumetric analysis. Sampling weights were included to generalize MRI sample to the visit 5 cohort. Interactions by meeting (or not) 2018 PA guidelines were tested. Results: Compared to low television viewing, medium and high television viewing in midlife was significantly associated with smaller deep grey matter volumes in late-life after multivariable adjustment; associations were stronger for persistent television viewing ( Table ). All other associations of midlife, or persistent midlife, television viewing with structural brain MRI markers were statistically null. Interactions with meeting PA guidelines were also non-significant. Conclusions: Findings suggest an inverse association of mid-life television viewing with later-life deep grey matter volumes. Studies examining the associations of daily accumulated SB, and differences by SB type (active versus passive), with brain MRI markers are needed.

scholarly journals Stop Meta-Analyzing, Start Instrumenting: Maximizing the Predictive Power of Polygenic Scores

2021 ◽  
Author(s):  
Hans van Kippersluis ◽  
Pietro Biroli ◽  
Titus J. Galama ◽  
Stephanie von Hinke ◽  
S. Fleur W. Meddens ◽  
...  
Keyword(s):  
Sample Size ◽  
Statistical Power ◽  
Predictive Power ◽  
Association Studies ◽  
Meta Analysis ◽  
Ordinary Least Squares ◽  
Genome Wide Association Studies ◽  
Finite Sample ◽  
Polygenic Score ◽  
Polygenic Scores

Polygenic scores have become the workhorse for empirical analyses in social-science genetics. Because a polygenic score is constructed using the results of finite-sample Genome-Wide Association Studies (GWASs), it is a noisy approximation of the true latent genetic predisposition to a certain trait. The conventional way of boosting the predictive power of polygenic scores is to increase the GWAS sample size by meta-analyzing GWAS results of multiple cohorts. In this paper we challenge this convention. Through simulations, we show that Instrumental Variable (IV) regression using two polygenic scores from independent GWAS samples outperforms the typical Ordinary Least Squares (OLS) model employing a single meta-analysis based polygenic score in terms of bias, root mean squared error, and statistical power. We verify the empirical validity of these simulations by predicting educational attainment (EA) and height in a sample of siblings from the UK Biobank. We show that IV regression between-families approaches the SNP-based heritabilities, while compared to meta-analysis applying IV regression within-families provides a tighter lower bound on the direct genetic effect. IV estimation improves the predictive power of polygenic scores by 12% (height) to 22% (EA). Our findings suggest that measurement error is a key explanation for hidden heritability (i.e., the difference between SNP-based and GWAS-based heritability), and that it can be overcome using IV regression. We derive the practical rule of thumb that IV outperforms OLS when the correlation between the two polygenic scores used in IV regression is larger than √(10 / (N+10)), with N the sample size of the prediction sample.

scholarly journals Smaller total brain volume but not subcortical structure volume related to common genetic risk for ADHD

2020 ◽  
pp. 1-10 ◽  
Author(s):  
Michael A. Mooney ◽  
Priya Bhatt ◽  
Robert J. M. Hermosillo ◽  
Peter Ryabinin ◽  
Molly Nikolas ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Brain Volume ◽  
Process Models ◽  
Intracranial Volume ◽  
Subcortical Structures ◽  
Total Brain Volume ◽  
Brain Volumes ◽  
Polygenic Score ◽  
Total Brain ◽  
Polygenic Scores

Abstract Background Mechanistic endophenotypes can inform process models of psychopathology and aid interpretation of genetic risk factors. Smaller total brain and subcortical volumes are associated with attention-deficit hyperactivity disorder (ADHD) and provide clues to its development. This study evaluates whether common genetic risk for ADHD is associated with total brain volume (TBV) and hypothesized subcortical structures in children. Methods Children 7–15 years old were recruited for a case–control study (N = 312, N = 199 ADHD). Children were assessed with a multi-informant, best-estimate diagnostic procedure and motion-corrected MRI measured brain volumes. Polygenic scores were computed based on discovery data from the Psychiatric Genomics Consortium (N = 19 099 ADHD, N = 34 194 controls) and the ENIGMA + CHARGE consortium (N = 26 577). Results ADHD was associated with smaller TBV, and altered volumes of caudate, cerebellum, putamen, and thalamus after adjustment for TBV; however, effects were larger and statistically reliable only in boys. TBV was associated with an ADHD polygenic score [β = −0.147 (−0.27 to −0.03)], and mediated a small proportion of the effect of polygenic risk on ADHD diagnosis (average ACME = 0.0087, p = 0.012). This finding was stronger in boys (average ACME = 0.019, p = 0.008). In addition, we confirm genetic variation associated with whole brain volume, via an intracranial volume polygenic score. Conclusion Common genetic risk for ADHD is not expressed primarily as developmental alterations in subcortical brain volumes, but appears to alter brain development in other ways, as evidenced by TBV differences. This is among the first demonstrations of this effect using molecular genetic data. Potential sex differences in these effects warrant further examination.

scholarly journals Independent evolution towards larger body size in the distinctive Faroe Island mice

2021 ◽  
Author(s):  
Ricardo Wilches ◽  
William H Beluch ◽  
Ellen McConnell ◽  
Diethard Tautz ◽  
Yingguang Frank Chan
Keyword(s):  
Body Size ◽  
Meta Analysis ◽  
Small Body ◽  
Laboratory Mouse ◽  
Large Body ◽  
Natural Populations ◽  
Size Variation ◽  
Phenotypic Traits ◽  
Island Population ◽  
Multiple Loci

Abstract Most phenotypic traits in nature involve the collective action of many genes. Traits that evolve repeatedly are particularly useful for understanding how selection may act on changing trait values. In mice, large body size has evolved repeatedly on islands and under artificial selection in the laboratory. Identifying the loci and genes involved in this process may shed light on the evolution of complex, polygenic traits. Here, we have mapped the genetic basis of body size variation by making a genetic cross between mice from the Faroe Islands, which are among the largest and most distinctive natural populations of mice in the world, and a laboratory mouse strain selected for small body size, SM/J. Using this F2 intercross of 841 animals, we have identified 111 loci controlling various aspects of body size, weight and growth hormone levels. By comparing against other studies, including the use of a joint meta-analysis, we found that the loci involved in the evolution of large size in the Faroese mice were largely independent from those of a different island population or other laboratory strains. We hypothesize that colonization bottleneck, historical hybridization, or the redundancy between multiple loci have resulted in the Faroese mice achieving an outwardly similar phenotype through a distinct evolutionary path.

scholarly journals IN THIS ISSUE

2005 ◽  
Vol 35 (4) ◽  
pp. 465-465
Keyword(s):  
Brain Mri ◽  
Structural Brain

This issue features groups of papers dealing with nosology of depression and psychoses, biology of depression, structural brain MRI in schizophrenia and autism, together with papers on other topics.

Abstract MP100: Arterial Stiffness and Pressure Amplification Associated with Markers of Cerebral Microvascular Disease: The Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS)

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Priya Palta ◽  
Jingkai Wei ◽  
Michelle Meyer ◽  
Melinda C Power ◽  
Jennifer A Deal ◽  
...  
Keyword(s):  
Older Adults ◽  
Arterial Stiffness ◽  
Pulse Pressure ◽  
Aortic Stiffness ◽  
Brain Mri ◽  
Intracranial Volume ◽  
Sampling Weights ◽  
Arterial Stiffening ◽  
Lacunar Infarcts ◽  
Pressure Amplification

Introduction: Small vessel disease is associated with decreased cognitive function, possibly differential by race. Age-related central arterial stiffening increases pulsatility resulting in hypoperfusion, microvascular damage and remodeling in the brain, potentially impairing cognition. We examined if arterial stiffness and pressure amplification are associated with lacunar infarcts and greater volumes of white matter hyperintensities (WMH) in a sample of Caucasian and African American (AA) older adults. Methods: We analyzed a cross-sectional sample of ARIC participants aged 67-90 years (n=1486) from visit 5 (2011-2013), with brain magnetic resonance imaging (MRI). The Omron VP-1000 Plus was used to measure aortic stiffness (carotid-femoral pulse wave velocity [cfPWV]) and pressure amplification measures (pulse pressure amplification [PPA], central pulse pressure [cPP], and estimated central systolic blood pressure [cSBP]). Aortic stiffness and pressure amplification were dichotomized at race-specific 25th percentile cut points. Brain MRI using 3D-1.5T equipment quantified the presence of lacunar infarcts and volumes of WMH following a standardized protocol. Logistic regression, adjusted for age, sex, education, ApoE4, heart rate, smoking and body mass index, was used to quantify the odds of lacunar infarcts in participants with high vs. low cfPWV, cPP, cSBP, and low vs. high PPA. Linear regression models, additionally adjusted for intracranial volume, estimated the difference in log-transformed volumes of WMH among participants with high vs. low cfPWV, cPP, cSBP, and low vs. high PPA. Probability sampling weights for an MRI were included to allow for generalizability to the full visit 5 cohort. Results: Among the 1486 participants with a brain MRI (mean age: 76, 41% male, 26% AA), measures of aortic stiffness and pressure amplification were associated with lacunar infarcts in Caucasians, but not in AAs. Caucasian participants with a high cfPWV had greater odds of lacunar infarcts (Odds Ratio [OR] =2.02, 95% confidence interval [CI]: 1.23, 2.20). Caucasians with high cSBP had higher odds of lacunar infarcts (OR=1.72, 95% CI: 1.10, 2.69). In Caucasians, high cfPWV was associated with a 21% (95% CI: 6, 38) greater volume of WMH as compared to a low cfPWV; high cSBP was associated with a 28% (95% CI: 14, 45) greater volume of WMH compared to a low cSBP. In AAs, high cfPWV was associated with a 32% (95% CI: 7, 62) greater volume of WMH as compared to low cfPWV. Cerebral microvascular imaging markers did not differ quantitatively with measures of PPA and cPP. Conclusions: Central arterial stiffening and pressure amplification are plausible microvascular contributors to cognitive aging, providing new information on modifiable pathways for previously observed associations between cardiovascular disease risk factors and the rates of cognitive decline and dementia among older adults.

Sign in / Sign up

Export Citation Format

Share Document