Pravesh Parekh

Oct 1, 2024 | nature.com | Shahram Bahrami |Kaja Nordengen |Olav B. Smeland |Nadine Staples Parker |Pravesh Parekh |Torbjørn Elvsåshagen | +4 more

AbstractThe basal ganglia are subcortical brain structures involved in motor control, cognition, and emotion regulation. We conducted univariate and multivariate genome-wide association analyses (GWAS) to explore the genetic architecture of basal ganglia volumes using brain scans obtained from 34,794 Europeans with replication in 4,808 white and generalization in 5,220 non-white Europeans.

May 10, 2024 | biorxiv.org | Diana Smith |Pravesh Parekh |Joseph E. Kennedy |Robert Loughnan

AbstractThe relative contributions of genetic variation and experience in shaping the morphology of the adolescent brain are not fully understood. Using longitudinal data from 11,665 subjects in the ABCD Study®, we fit vertex-wise variance components including family effects, genetic effects, and subject-level effects using a computationally efficient framework.

Apr 18, 2024 | medrxiv.org | Pravesh Parekh |Laura Hegemann |Viktoria Birkenas |Nora Refsum Bakken

Prof. Andreassen has received speaker fees from Lundbeck, Janssen, Otsuka, and Sunovion and is aconsultant to Cortechs.ai. and Precision Health. None of the remaining authors have any conflicts ofinterest.

Jan 29, 2024 | onlinelibrary.wiley.com | Pravesh Parekh |Chun Chieh Fan |Oleksandr Frei |Clare Palmer

1 INTRODUCTION As neuroimaging studies have moved to large sample sizes, the size of datasets and the complexity of relationships among observations within these datasets pose several challenges to neuroimaging analysis. For example, in the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) (https://abcdstudy.org), the inclusion of twins and siblings, in addition to a longitudinal design, make it necessary to simultaneously consider multiple correlations among observations.

Dec 9, 2023 | biorxiv.org | Diana Smith |Pravesh Parekh |Joseph E. Kennedy |Robert Loughnan

AbstractThe heritability of cortical brain imaging phenotypes has been a subject of investigation for several years. Prior studies have employed both twin datasets1 and genome-wide association studies (GWAS) to estimate the contribution of genetic variation to variance in cortical morphometry at the region of interest (ROI) and vertex level. Longitudinal datasets that capture changes in brain structure over time can provide novel insights into the heritability of brain structure.