DNA and IQ: Big deal or much ado about nothing? – A meta-analysis DOI
Florence A R Oxley, Kirsty Wilding, Sophie von Stumm

et al.

Intelligence, Journal Year: 2024, Volume and Issue: 107, P. 101871 - 101871

Published: Oct. 19, 2024

Language: Английский

Timing of lifespan influences on brain and cognition DOI Creative Commons
Kristine B. Walhovd, Martin Lövdén, Anders M. Fjell

et al.

Trends in Cognitive Sciences, Journal Year: 2023, Volume and Issue: 27(10), P. 901 - 915

Published: Aug. 8, 2023

Modifiable risk and protective factors for boosting brain cognitive development preventing neurodegeneration decline are embraced in neuroimaging studies. We call sobriety regarding the timing quantity of such influences on cognition. Individual differences level cognition, many which present already at birth early development, appear stable, larger, more pervasive than change across lifespan. Incorporating early-life factors, including genetics, investigating both will reduce ascribing undue importance causality to proximate adulthood older age. This has implications mechanistic understanding prevention.

Language: Английский

Citations

61

Behavioural genetics methods DOI
Emily A. Willoughby, Tinca J. C. Polderman, Brian B. Boutwell

et al.

Nature Reviews Methods Primers, Journal Year: 2023, Volume and Issue: 3(1)

Published: Feb. 9, 2023

Language: Английский

Citations

28

Three legs of the missing heritability problem DOI
Lucas J. Matthews, Eric Turkheimer

Studies in History and Philosophy of Science Part A, Journal Year: 2022, Volume and Issue: 93, P. 183 - 191

Published: May 7, 2022

Language: Английский

Citations

36

The impact of assortative mating, participation bias and socioeconomic status on the polygenic risk of behavioural and psychiatric traits DOI
Brenda Cabrera‐Mendoza, Frank R. Wendt, Gita A. Pathak

et al.

Nature Human Behaviour, Journal Year: 2024, Volume and Issue: 8(5), P. 976 - 987

Published: Feb. 16, 2024

Language: Английский

Citations

7

Taking the risk. A systematic review of ethical reasons and moral arguments in the clinical use of polygenic risk scores DOI
Lara Andreoli, Hilde Peeters, Kristel Van Steen

et al.

American Journal of Medical Genetics Part A, Journal Year: 2024, Volume and Issue: 194(7)

Published: March 7, 2024

Debates about the prospective clinical use of polygenic risk scores (PRS) have grown considerably in last years. The potential benefits PRS to improve patient care at individual and population levels been extensively underlined. Nonetheless, contexts presents a number unresolved ethical challenges consequent normative gaps that hinder their optimal implementation. Here, we conducted systematic review reasons literature discussing issues moral arguments related for prevention treatment common complex diseases. In total, included analyzed 34 records, spanning from 2013 2023. findings organized three major themes: first theme, consider harms individuals kin. theme "Threats health equity," concerns social relevance, with focus on justice issues. Finally, "Towards best practices" collects series research priorities provisional recommendations be considered an translation PRS. We conclude reinvigorates old debates matters justice; however, open questions, regarding practices counseling, suggest considerations applicable monogenic settings will not sufficient face emerging challenges.

Language: Английский

Citations

7

Celebrating a Century of Research in Behavioral Genetics DOI Creative Commons
Robert Plomin

Behavior Genetics, Journal Year: 2023, Volume and Issue: 53(2), P. 75 - 84

Published: Jan. 20, 2023

Abstract A century after the first twin and adoption studies of behavior in 1920s, this review looks back on journey celebrates milestones behavioral genetic research. After a whistle-stop tour early quantitative research parallel molecular genetics, travelogue focuses last fifty years. Just as discoveries were beginning to slow down 1990s, genetics made it possible assess DNA variation directly. From rocky start with candidate gene association research, by 2005 technological advance microarrays enabled genome-wide studies, which have successfully identified some variants that contribute ubiquitous heritability traits. The ability aggregate effects thousands polygenic scores has created revolution sciences making use predict individual differences from life.

Language: Английский

Citations

15

Infrastructuring Educational Genomics: Associations, Architectures, and Apparatuses DOI Creative Commons
Ben Williamson, Dimitra Kotouza, Martyn Pickersgill

et al.

Postdigital Science and Education, Journal Year: 2024, Volume and Issue: 6(4), P. 1143 - 1172

Published: Feb. 3, 2024

Technoscientific transformations in molecular genomics have begun to influence knowledge production education. Interdisciplinary scientific consortia are seeking identify 'genetic influences' on 'educationally relevant' traits, behaviors, and outcomes. This article examines the emerging 'knowledge infrastructure' of educational genomics, attending assembly choreography organizational associations, epistemic architecture, technoscientific apparatuses implicated generation genomic understandings from masses bioinformation. As an infrastructure datafied production, is embedded data-centered epistemologies practices which recast problems terms genetic associations-insights about deemed discoverable digital bioinformation potentially open genetically informed interventions policy practice. While scientists claim be 'opening black box genome' its association with outcomes, we itself as a source authority. Data-intensive does not straightforwardly 'discover' biological bases educationally relevant behaviors Rather, this also experimental 'ontological supporting particular ways knowing, understanding, explaining, intervening education, recasting human subjects education being surveyable predictable through algorithmic processing

Language: Английский

Citations

5

DeepGAMI: deep biologically guided auxiliary learning for multimodal integration and imputation to improve genotype–phenotype prediction DOI Creative Commons
Pramod Chandrashekar, Sayali Alatkar, Jiebiao Wang

et al.

Genome Medicine, Journal Year: 2023, Volume and Issue: 15(1)

Published: Oct. 31, 2023

Abstract Background Genotypes are strongly associated with disease phenotypes, particularly in brain disorders. However, the molecular and cellular mechanisms behind this association remain elusive. With emerging multimodal data for these mechanisms, machine learning methods can be applied phenotype prediction at different scales, but due to black-box nature of learning, integrating modalities interpreting biological challenging. Additionally, partial availability presents a challenge developing predictive models. Method To address challenges, we developed DeepGAMI, an interpretable neural network model improve genotype–phenotype from data. DeepGAMI leverages functional genomic information, such as eQTLs gene regulation, guide connections. it includes auxiliary layer cross-modal imputation allowing latent features missing thus predicting phenotypes single modality. Finally, uses integrated gradient prioritize various phenotypes. Results We several datasets including genotype bulk cell-type expression diseases, electrophysiology mouse neuronal cells. Using cross-validation independent validation, outperformed existing classifying types, clinical even using (e.g., AUC score 0.79 Schizophrenia 0.73 cognitive impairment Alzheimer’s disease). Conclusion demonstrated that improves prioritizes phenotypic networks multiple complex brains diseases. Also, prioritized disease-associated variants, genes, regulatory linked providing novel insights into interpretation mechanisms. is open-source available general use.

Language: Английский

Citations

12

Notes from Beethoven’s genome DOI Creative Commons
Laura W. Wesseldijk, Tara Lynn Henechowicz, David Baker

et al.

Current Biology, Journal Year: 2024, Volume and Issue: 34(6), P. R233 - R234

Published: March 1, 2024

Rapid advances over the last decade in DNA sequencing and statistical genetics enable us to investigate genomic makeup of individuals throughout history. In a recent notable study, Begg et al.

Language: Английский

Citations

4

Gene–environment interaction using polygenic scores: Do polygenic scores for psychopathology moderate predictions from environmental risk to behavior problems? DOI Creative Commons
Robert Plomin, Agnieszka Gidziela, Margherita Malanchini

et al.

Development and Psychopathology, Journal Year: 2022, Volume and Issue: 34(5), P. 1816 - 1826

Published: Sept. 23, 2022

Abstract The DNA revolution has energized research on interactions between genes and environments (GxE) by creating indices of G (polygenic scores) that are powerful predictors behavioral traits. Here, we test the extent to which polygenic scores for attention-deficit/hyperactivity disorder neuroticism moderate associations parent reports their children’s environmental risk (E) at ages 3 4 teacher ratings behavior problems (hyperactivity/inattention, conduct problems, emotional symptoms, peer relationship problems) 7, 9 12. sampling frame included up 6687 twins from Twins Early Development Study. Our analyses focused relative effect sizes G, E GxE in predicting problems. predicted 2%, 2% 0.4%, respectively, variance externalizing (hyperactivity/inattention across 12, with no clear developmental trends. predictions symptoms were weaker. A quarter (12 48) our tests nominally significant ( p = .05). Increasing predictive power would enhance search GxE.

Language: Английский

Citations

19