The Gloomy Prospect Wins: Statistical Significance and Population Stratification in Genome Wide Association Studies

This one-hour lecture by Dr. Eric Turkheimer of the University of Virginia's Department of Psychology explored the following:

The contemporary era has seen a convergence of genomic technology and traditional social scientific concerns with complex human individual differences. Rather than finally turning social science into a replicable hard-scientific enterprise, genomics has gotten bogged down in the long-standing frustrations of social science. A recent report of an extensive genome wide association study of human height demonstrates the profound difficulties of explaining uncontrolled human variation at a genomic level. The statistical technologies that have been brought to bear on the problem of genomic association are simply modifications of similar methods that have been used by social scientists for decades, with little success. The motivation for the statistical methods in genomics is the same as it is in traditional social science: An attempt to discern linear causation in complex systems when experimental control is not possible.

For an audio recording of Dr. Turkheimer's lecture, please visit "http://cirge.stanford.edu/activities/events.html.":http://cirge.stanford.edu/activities/events.htm

Optimally Stabilized PET Image Denoising Using Trilateral Filtering

Low-resolution and signal-dependent noise distribution in positron emission tomography (PET) images makes denoising process an inevitable step prior to qualitative and quantitative image analysis tasks. Conventional PET denoising methods either over-smooth small-sized structures due to resolution limitation or make incorrect assumptions about the noise characteristics. Therefore, clinically important quantitative information may be corrupted. To address these challenges, we introduced a novel approach to remove signal-dependent noise in the PET images where the noise distribution was considered as Poisson-Gaussian mixed. Meanwhile, the generalized Anscombe's transformation (GAT) was used to stabilize varying nature of the PET noise. Other than noise stabilization, it is also desirable for the noise removal filter to preserve the boundaries of the structures while smoothing the noisy regions. Indeed, it is important to avoid significant loss of quantitative information such as standard uptake value (SUV)-based metrics as well as metabolic lesion volume. To satisfy all these properties, we extended bilateral filtering method into trilateral filtering through multiscaling and optimal Gaussianization process. The proposed method was tested on more than 50 PET-CT images from various patients having different cancers and achieved the superior performance compared to the widely used denoising techniques in the literature.Comment: 8 pages, 3 figures; to appear in the Lecture Notes in Computer Science (MICCAI 2014

MENGA: a new comprehensive tool for the integration of neuroimaging data and the Allen human brain transcriptome atlas

Brain-wide mRNA mappings offer a great potential for neuroscience research as they can provide information about system proteomics. In a previous work we have correlated mRNA maps with the binding patterns of radioligands targeting specific molecular systems and imaged with positron emission tomography (PET) in unrelated control groups. This approach is potentially applicable to any imaging modality as long as an efficient procedure of imaging-genomic matching is provided. In the original work we considered mRNA brain maps of the whole human genome derived from the Allen human brain database (ABA) and we performed the analysis with a specific region-based segmentation with a resolution that was limited by the PET data parcellation. There we identified the need for a platform for imaging-genomic integration that should be usable with any imaging modalities and fully exploit the high resolution mapping of ABA dataset.In this work we present MENGA (Multimodal Environment for Neuroimaging and Genomic Analysis), a software platform that allows the investigation of the correlation patterns between neuroimaging data of any sort (both functional and structural) with mRNA gene expression profiles derived from the ABA database at high resolution.We applied MENGA to six different imaging datasets from three modalities (PET, single photon emission tomography and magnetic resonance imaging) targeting the dopamine and serotonin receptor systems and the myelin molecular structure. We further investigated imaging-genomic correlations in the case of mismatch between selected proteins and imaging targets

An Exploratory Analysis of Father Involvement in Low-Income Families

Using data from the Fragile Families study, this paper explores factors that influence paternal involvement in low-income families. 4873 fathers from the Fragile Families study were classified using CART (Classification and Regression Tree Analysis). CART is a nonparametric technique that allows many different factors to be combined in order to classify homogeneous subgroups within a sample. The CART analysis distinguished between residential and non-residential fathers. In addition, among residential fathers, race emerged as the distinguishing factor. For White men, residential status was the only factor to affect involvement. For African American and Hispanic men however, interactions among several sociodemographic characteristics revealed that both contextual and individual factors affect paternal involvement. Results suggest that an ecological approach is necessary in the investigation of paternal involvement.

A role for TSPO in mitochondrial Ca2+ homeostasis and redox stress signaling

The 18 kDa translocator protein TSPO localizes on the outer mitochondrial membrane (OMM). Systematically overexpressed at sites of neuroinflammation it is adopted as a biomarker of brain conditions. TSPO inhibits the autophagic removal of mitochondria by limiting PARK2-mediated mitochondrial ubiquitination via a peri-organelle accumulation of reactive oxygen species (ROS). Here we describe that TSPO deregulates mitochondrial Ca2+ signaling leading to a parallel increase in the cytosolic Ca2+ pools that activate the Ca2+-dependent NADPH oxidase (NOX) thereby increasing ROS. The inhibition of mitochondrial Ca2+ uptake by TSPO is a consequence of the phosphorylation of the voltage-dependent anion channel (VDAC1) by the protein kinase A (PKA), which is recruited to the mitochondria, in complex with the Acyl-CoA binding domain containing 3 (ACBD3). Notably, the neurotransmitter glutamate, which contributes neuronal toxicity in age-dependent conditions, triggers this TSPO-dependent mechanism of cell signaling leading to cellular demise. TSPO is therefore proposed as a novel OMM-based pathway to control intracellular Ca2+ dynamics and redox transients in neuronal cytotoxicity

TSPO expression in brain tumours: is TSPO a target for brain tumour imaging?

Positron emission tomography (PET) alone or in combination with MRI is increasingly assuming a central role in the development of diagnostic and therapeutic strategies for brain tumours with the aim of addressing tumour heterogeneity, assisting in patient stratification, and contributing to predicting treatment response. The 18 kDa translocator protein (TSPO) is expressed in high-grade gliomas, while its expression is comparatively low in normal brain. In addition, the evidence of elevated TSPO in neoplastic cells has led to studies investigating TSPO as a transporter of anticancer drugs for brain delivery and a selective target for tumour tissue. The TSPO therefore represents an ideal candidate for molecular imaging studies. Knowledge of the biology of TSPO in normal brain cells, in-depth understanding of TSPO functions and biodistribution in neoplastic cells, accurate methods for quantification of uptake of TSPO tracers and pharmacokinetic data regarding TSPO-targeted drugs are required before introducing TSPO PET and TSPO-targeted treatment in clinical practice. In this review, we will discuss the impact of preclinical PET studies and the application of TSPO imaging in human brain tumours, the advantages and disadvantages of TSPO imaging compared to other imaging modalities and other PET tracers, and pathology studies on the extent and distribution of TSPO in gliomas. The suitability of TSPO as molecular target for treatment of brain tumours will also be the appraised

Self-similar correlation function in brain resting-state fMRI

Adaptive behavior, cognition and emotion are the result of a bewildering variety of brain spatiotemporal activity patterns. An important problem in neuroscience is to understand the mechanism by which the human brain's 100 billion neurons and 100 trillion synapses manage to produce this large repertoire of cortical configurations in a flexible manner. In addition, it is recognized that temporal correlations across such configurations cannot be arbitrary, but they need to meet two conflicting demands: while diverse cortical areas should remain functionally segregated from each other, they must still perform as a collective, i.e., they are functionally integrated. Here, we investigate these large-scale dynamical properties by inspecting the character of the spatiotemporal correlations of brain resting-state activity. In physical systems, these correlations in space and time are captured by measuring the correlation coefficient between a signal recorded at two different points in space at two different times. We show that this two-point correlation function extracted from resting-state fMRI data exhibits self-similarity in space and time. In space, self-similarity is revealed by considering three successive spatial coarse-graining steps while in time it is revealed by the 1/f frequency behavior of the power spectrum. The uncovered dynamical self-similarity implies that the brain is spontaneously at a continuously changing (in space and time) intermediate state between two extremes, one of excessive cortical integration and the other of complete segregation. This dynamical property may be seen as an important marker of brain well-being both in health and disease.Comment: 14 pages 13 figures; published online before print September 2

Altered dynamical integration/segregation balance during anesthesia-induced loss of consciousness

In recent years, brain imaging studies have begun to shed light on the neural correlates of physiologically-reversible altered states of consciousness such as deep sleep, anesthesia, and psychedelic experiences. The emerging consensus is that normal waking consciousness requires the exploration of a dynamical repertoire enabling both global integration i.e., long-distance interactions between brain regions, and segregation, i.e., local processing in functionally specialized clusters. Altered states of consciousness have notably been characterized by a tipping of the integration/segregation balance away from this equilibrium. Historically, functional MRI (fMRI) has been the modality of choice for such investigations. However, fMRI does not enable characterization of the integration/segregation balance at sub-second temporal resolution. Here, we investigated global brain spatiotemporal patterns in electrocorticography (ECoG) data of a monkey (Macaca fuscata) under either ketamine or propofol general anesthesia. We first studied the effects of these anesthetics from the perspective of band-specific synchronization across the entire ECoG array, treating individual channels as oscillators. We further aimed to determine whether synchrony within spatially localized clusters of oscillators was differently affected by the drugs in comparison to synchronization over spatially distributed subsets of ECoG channels, thereby quantifying changes in integration/segregation balance on physiologically-relevant time scales. The findings reflect global brain dynamics characterized by a loss of long-range integration in multiple frequency bands under both ketamine and propofol anesthesia, most pronounced in the beta (13–30 Hz) and low-gamma bands (30–80 Hz), and with strongly preserved local synchrony in all bands

Item response theory analysis of the cognitive ability test in TwinLife

Carroll S, Turkheimer E. Item response theory analysis of the cognitive ability test in TwinLife. TwinLife Working Paper Series. Vol 02. Bielefeld: Project TwinLife "Genetic and social causes of life chances" (Universität Bielefeld / Universität des Saarlandes); 2018.TwinLife, an ongoing German study of twins and their families, investigates cognitive performance as one factor among many that contribute to the development of social inequality. Participants completed the CFT 20-R, a nonverbal intelligence assessment. The current analysis applied a two-parameter logistic item response theory model using Mplus software to subtest results from twin pairs in the three oldest birth cohorts, ranging in age from 10 to 25 years old. The findings indicated that the 2PL model fit the data considerably better than the one-parameter logistic model did for all four of the CFT 20-R subtests used in TwinLife. Results from the 2PL model, including item and person parameters and test information, are discussed. In addition, the items were assessed for measurement invariance across age cohort and gender. Fit statistics reveal little difference in item function according to these demographic factors, meaning that the CFT 20-R may be valid in heterogeneous samples