Biology subjects

Ganjgahi, H.

Publications and source records attributed to Ganjgahi, H..

3 recordsLinked to original sources

bioRxiv2017

Fast and Powerful Genome Wide Association Analysis of Dense Genetic Data with High Dimensional Imaging Phenotypes

Genome wide association (GWA) analysis of brain imaging phenotypes can advance our understanding of the genetic basis of normal and disorder-related variation in the brain. GWA approaches typically use linear mixed effect models to account for non-independence amongst subjects due to factors such as family relatedness and population structure. The use of these models with high-dimensional imaging phenotypes presents enormous challenges in terms of computational intensity and the need to account multiple testing in both the imaging and genetic domain. Here we present method that makes mixed models practical with high-dimensional traits by a combination of a transformation applied to the data and model, and the use of a non-iterative variance component estimator. With such speed enhancements permutation tests are feasible, which allows inference on powerful spatial tests like the cluster size statistic.

genetics↗

bioRxiv2017

Do Candidate Genes Affect the Brain’s White Matter Microstructure? Large-Scale Evaluation of 6,165 Diffusion MRI Scans

AbstractSusceptibility genes for psychiatric and neurological disorders - including APOE, BDNF, CLU,CNTNAP2, COMT, DISC1, DTNBP1, ErbB4, HFE, NRG1, NTKR3, and ZNF804A - have been reported to affect white matter (WM) microstructure in the healthy human brain, as assessed through diffusion tensor imaging (DTI). However, effects of single nucleotide polymorphisms (SNPs) in these genes explain only a small fraction of the overall variance and are challenging to detect reliably in single cohort studies. To date, few studies have evaluated the reproducibility of these results. As part of the ENIGMA-DTI consortium, we pooled regional fractional anisotropy (FA) measures for 6,165 subjects (CEU ancestry N=4,458) from 11 cohorts worldwide to evaluate effects of 15 candidate SNPs by examining their associations with WM microstructure. Additive association tests were conducted for each SNP. We used several meta-analytic and mega-analytic designs, and we evaluated regions of interest at multiple granularity levels. The ENIGMA-DTI protocol was able to detect single-cohort findings as originally reported. Even so, in this very large sample, no significant associations remained after multiple-testing correction for the 15 SNPs investigated. Suggestive associations (1.3x10-4 < p < 0.05, uncorrected) were found for BDNF, COMT, and ZNF804A in specific tracts. Meta-and mega-analyses revealed similar findings. Regardless of the approach, the previously reported candidate SNPs did not show significant associations with WM microstructure in this largest genetic study of DTI to date; the negative findings are likely not due to insufficient power. Genome-wide studies, involving large-scale meta-analyses, may help to discover SNPs robustly influencing WM microstructure.

neuroscience↗

bioRxiv2016

fMRI Correlates of Reaction Time Prolongation during intentional False Responding; an inter-individual difference study

Reaction time (RT) is chiefly longer when people lie. However, the baseline speed in answering questions and the amount of RT prolongation during lying show considerable amount of inter-individual variability. In the current study, we exploited this fact to glean insights on the contribution of each lie-related brain region to hampering of response speeds when people try to be deceitful. In an event-related fMRI session, participants were interrogated by yes-no autobiographical questions and were instructed to intentionally provide false responses to a pre-selected subset of questions. Data from twenty healthy volunteers were analyzed. Baseline speed [RTtruth] and relative appended lie RT [(RTlie - RTtruth) / RTtruth] measures were calculated for each participant and were included in the group level analysis of [lie > truth] BOLD contrasts. Lying RTs were significantly longer than truth telling RTs. Lie-related increase in activity of right ventrolateral prefrontal cortex (VLPFC) and bilateral paracingulate cortex correlated with the baseline speed of participants, while the increase in activity of Left VLPFC, left lateral occipital cortex and bilateral anterior cingulate areas directly correlated with the amount of lying reaction time cost. Activity within bilateral posterior cingulate cortex and right insular cortex inversely correlated with lying RT-cost. Bilateral supplementary motor areas, internal capsule white matter and left angular gyrus showed lie-related increase in activity but did not correlate with either of behavioral measures. Provisional implications regarding the contribution of these regions to RT prolongation and their cognitive role in deceitful behavior are discussed.

neuroscience↗