Carolina Makowski

This study examines how BMI relates to brain microstructure across adolescence, finding nonlinear associations that intensify at higher BMI percentiles.

FEMA-Long enables efficient modeling of time-dependent effects in longitudinal data, discovering genetic variants with time-dependent effects on infant growth traits.

The paper uses the ABCD Study to determine optimal replication sample sizes for reproducible brain-behavior associations using neuroimaging data.

FEMA enables fast and efficient mixed-effects analyses of large-scale whole-brain imaging data, revealing distinct spatial patterns of brain maturation in early adolescence.

The paper investigates the genetic architecture of cortical expansion and regionalization by comparing genome-wide association studies of 24 cortical regions with and without adjustment for global measures, finding distinct genetic loci associated with different regions.

The paper evaluates the replication of genome-wide association loci discovered using MOSTest across different cohorts and finds higher replication yields and rates compared to min-P.

The paper examines genetic and familial risk factors for psychopathology in youth, finding shared and unique associations between polygenic risk scores and behavioral measures.

This study identifies 856 genetic loci associated with sulcal depth through a genome-wide association study using UK Biobank data, showing higher heritability and locus yield compared to cortical thickness and surface area.

The paper uses a multivariate GWAS approach to identify 780 genetic loci associated with cortical morphology, showing a 10-fold increase in loci compared to univariate methods.

This study uses multivariate GWAS on diffusion imaging data from two large datasets to identify 503 genetic loci affecting brain tissue composition and uncover molecular pathways related to axonal growth, synaptogenesis, and neuroinflammation.

This study links tissue volume loss in schizophrenia to structural and functional connectivity, finding that 25-35% of regional deformation variance is explained by these factors.

The paper describes neuroimaging processing methods for the ABCD Study to extract brain phenotypes from multimodal imaging data.