Fast identification of biological pathways associated with a quantitative trait using group lasso with overlaps.

Where causal SNPs (single nucleotide polymorphisms) tend to accumulate within biological pathways, the incorporation of prior pathways information into a statistical model is expected to increase the power to detect true associations in a genetic association study. Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within pathways.We use a sparse regression model, with SNPs grouped into pathways, to identify causal pathways associated with a quantitative trait. Notable features of our "pathways group lasso with adaptive weights" (P-GLAW) algorithm include the incorporation of all pathways in a single regression model, an adaptive pathway weighting procedure that accounts for factors biasing pathway selection, and the use of a bootstrap sampling procedure for the ranking of important pathways. P-GLAW takes account of the presence of overlapping pathways and uses a novel combination of techniques to optimise model estimation, making it fast to run, even on whole genome datasets.In a comparison study with an alternative pathways method based on univariate SNP statistics, our method demonstrates high sensitivity and specificity for the detection of important pathways, showing the greatest relative gains in performance where marginal SNP effect sizes are small

Fast Identification of Biological Pathways Associated with a Quantitative Trait Using Group Lasso with Overlaps

Where causal SNPs (single nucleotide polymorphisms) tend to accumulate within biological pathways, the incorporation of prior pathways information into a statistical model is expected to increase the power to detect true associations in a genetic association study. Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within pathways. We use a sparse regression model, with SNPs grouped into pathways, to identify causal pathways associated with a quantitative trait. Notable features of our "pathways group lasso with adaptive weights" (P-GLAW) algorithm include the incorporation of all pathways in a single regression model, an adaptive pathway weighting procedure that accounts for factors biasing pathway selection, and the use of a bootstrap sampling procedure for the ranking of important pathways. P-GLAW takes account of the presence of overlapping pathways and uses a novel combination of techniques to optimise model estimation, making it fast to run, even on whole genome datasets. In a comparison study with an alternative pathways method based on univariate SNP statistics, our method demonstrates high sensitivity and specificity for the detection of important pathways, showing the greatest relative gains in performance where marginal SNP effect sizes are small.Comment: 29 page

Birth Weight and Adult IQ, but Not Anxious-Depressive Psychopathology, Are Associated with Cortical Surface Area: A Study in Twins

BACKGROUND: Previous research suggests that low birth weight (BW) induces reduced brain cortical surface area (SA) which would persist until at least early adulthood. Moreover, low BW has been linked to psychiatric disorders such as depression and psychological distress, and to altered neurocognitive profiles. AIMS: We present novel findings obtained by analysing high-resolution structural MRI scans of 48 twins; specifically, we aimed: i) to test the BW-SA association in a middle-aged adult sample; and ii) to assess whether either depression/anxiety disorders or intellectual quotient (IQ) influence the BW-SA link, using a monozygotic (MZ) twin design to separate environmental and genetic effects. RESULTS: Both lower BW and decreased IQ were associated with smaller total and regional cortical SA in adulthood. Within a twin pair, lower BW was related to smaller total cortical and regional SA. In contrast, MZ twin differences in SA were not related to differences in either IQ or depression/anxiety disorders. CONCLUSION: The present study supports findings indicating that i) BW has a long-lasting effect on cortical SA, where some familial and environmental influences alter both foetal growth and brain morphology; ii) uniquely environmental factors affecting BW also alter SA; iii) higher IQ correlates with larger SA; and iv) these effects are not modified by internalizing psychopathology.This work was supported by the Spanish SAF2008-05674, European Twins Study Network on Schizophrenia Research Training Network (grant number EUTwinsS; MRTN-CT-2006-035987), the Catalan 2014SGR1636 and the PIM2010-ERN- 00642 in frame of ERA-NET NEURON. A. Córdova- Palomera was funded by The National Council for Science and Technology (CONACyT, Mexico). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Functional connectivity response to acute pain assessed by fNIRS is associated with BDNF genotype in fibromyalgia : an exploratory study

Fibromyalgia is a heterogenous primary pain syndrome whose severity has been associated with descending pain modulatory system (DPMS) function and functional connectivity (FC) between pain processing areas. The brain-derived neurotrophic factor (BDNF) Val66Met single nucleotide polymorphism has been linked to vulnerability to chronic pain. In this cross-sectional imaging genetics study, we investigated fbromyalgia, the relationship between BDNF Val66Met heterozygous genotypes (Val/Met), and the functional connectivity (FC) response pattern to acute pain stimulus in the motor (MC) and prefrontal (PFC) cortex assessed by near-infrared spectroscopy (fNIRS) before and after a cold pressor test utilizing water (0–1 °C). Also, we assessed the relationship between this genotype with the DPMS function and quality of life. We included 42 women (Val/ Val = 30; Val/Met = 12) with fbromyalgia, ages 18–65. The MANCOVA comparing Val/Met to Val/Val genotypes showed higher ΔFC between left(l)-PFC—l-MC (β= 0.357, p = 0.048), l-PFC—right(r)-PFC (β= 0.249, p = 0.012), l-PFC—r-MC (β= 0.226, p = 0.022), and l-MC—r-PFC (β= 0.260, p = 0.016). Val/Met genotypes showed higher efciency of the DPMS and lower disability due to pain. Here we show that fbromyalgia patients carrying the Val/Met BDNF genotype presented an increased ΔFC across MC and PFC in response to acute pain associated with diferences in acute pain perception and fbromyalgia symptoms

Neuroimaging genomics in psychiatry—a translational approach

Neuroimaging genomics is a relatively new field focused on integrating genomic and imaging data in order to investigate the mechanisms underlying brain phenotypes and neuropsychiatric disorders. While early work in neuroimaging genomics focused on mapping the associations of candidate gene variants with neuroimaging measures in small cohorts, the lack of reproducible results inspired better-powered and unbiased large-scale approaches. Notably, genome-wide association studies (GWAS) of brain imaging in thousands of individuals around the world have led to a range of promising findings. Extensions of such approaches are now addressing epigenetics, gene-gene epistasis, and gene-environment interactions, not only in brain structure, but also in brain function. Complementary developments in systems biology might facilitate the translation of findings from basic neuroscience and neuroimaging genomics to clinical practice. Here, we review recent approaches in neuroimaging genomics-we highlight the latest discoveries, discuss advantages and limitations of current approaches, and consider directions by which the field can move forward to shed light on brain disorders

Serotonin transporter gene polymorphisms and brain function during emotional distraction from cognitive processing in posttraumatic stress disorder

BACKGROUND: Serotonergic system dysfunction has been implicated in posttraumatic stress disorder (PTSD). Genetic polymorphisms associated with serotonin signaling may predict differences in brain circuitry involved in emotion processing and deficits associated with PTSD. In healthy individuals, common functional polymorphisms in the serotonin transporter gene (SLC6A4) have been shown to modulate amygdala and prefrontal cortex (PFC) activity in response to salient emotional stimuli. Similar patterns of differential neural responses to emotional stimuli have been demonstrated in PTSD but genetic factors influencing these activations have yet to be examined. METHODS: We investigated whether SLC6A4 promoter polymorphisms (5-HTTLPR, rs25531) and several downstream single nucleotide polymorphisms (SNPs) modulated activity of brain regions involved in the cognitive control of emotion in post-9/11 veterans with PTSD. We used functional MRI to examine neural activity in a PTSD group (n = 22) and a trauma-exposed control group (n = 20) in response to trauma-related images presented as task-irrelevant distractors during the active maintenance period of a delayed-response working memory task. Regions of interest were derived by contrasting activation for the most distracting and least distracting conditions across participants. RESULTS: In patients with PTSD, when compared to trauma-exposed controls, rs16965628 (associated with serotonin transporter gene expression) modulated task-related ventrolateral PFC activation and 5-HTTLPR tended to modulate left amygdala activation. Subsequent to combat-related trauma, these SLC6A4 polymorphisms may bias serotonin signaling and the neural circuitry mediating cognitive control of emotion in patients with PTSD. CONCLUSIONS: The SLC6A4 SNP rs16965628 and 5-HTTLPR are associated with a bias in neural responses to traumatic reminders and cognitive control of emotions in patients with PTSD. Functional MRI may help identify intermediate phenotypes and dimensions of PTSD that clarify the functional link between genes and disease phenotype, and also highlight features of PTSD that show more proximal influence of susceptibility genes compared to current clinical categorizations

The relationship between genetic risk variants with brain structure and function in bipolar disorder: A systematic review of genetic-neuroimaging studies

Genetic-neuroimaging paradigms could provide insights regarding the pathophysiology of bipolar disorder (BD). Nevertheless, findings have been inconsistent across studies. A systematic review of gene-imaging studies involving individuals with BD was conducted across electronic major databases from inception until January 9th, 2017. Forty-four studies met eligibility criteria (N=2122 BD participants). Twenty-six gene variants were investigated across candidate gene studies and 4 studies used a genome-wide association approach. Replicated evidence (i.e. in >2 studies) suggests that individuals with BD carrying the BDNF Val66Met risk allele could have reduced hippocampal volumes compared to non-carriers. This review underscores the potential of gene-neuroimaging paradigms to provide mechanistic insights for BD. However, this systematic review found a single replicated finding. Suggestions to improve the reproducibility of this emerging field are provided, including the adoption of a trans-diagnostic approac

Grey and white matter microstructure is associated with polygenic risk for schizophrenia.

Funder: E.-M.S is supported by a PhD studentship awarded by the Friends of Peterhouse.Funder: DH | National Institute for Health Research (NIHR); doi: https://doi.org/10.13039/501100000272Recent discovery of approximately 270 common genetic variants associated with schizophrenia has enabled polygenic risk scores (PRS) to be measured in the population. We hypothesized that normal variation in PRS would be associated with magnetic resonance imaging (MRI) phenotypes of brain morphometry and tissue composition. We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (Nmax = 29,878) who had multiple micro- and macrostructural MRI metrics measured at each of 180 cortical areas, seven subcortical structures, and 15 major white matter tracts. Linear mixed-effect models were used to investigate associations between PRS and brain structure at global and regional scales, controlled for multiple comparisons. Polygenic risk was significantly associated with reduced neurite density index (NDI) at global brain scale, at 149 cortical regions, five subcortical structures, and 14 white matter tracts. Other microstructural parameters, e.g., fractional anisotropy, that were correlated with NDI were also significantly associated with PRS. Genetic effects on multiple MRI phenotypes were co-located in temporal, cingulate, and prefrontal cortical areas, insula, and hippocampus. Post-hoc bidirectional Mendelian randomization analyses provided preliminary evidence in support of a causal relationship between (reduced) thalamic NDI and (increased) risk of schizophrenia. Risk-related reduction in NDI is plausibly indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks. Cortical, subcortical, and white matter microstructure may be linked to the genetic mechanisms of schizophrenia.E.-M.S is supported by a PhD studentship awarded by the Friends of Peterhouse. This research was co-funded by the National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre and a Marmaduke Sheild grant to R.A.I.B. and V.W.. E.T.B is an NIHR Senior Investigator. R.R.G was funded by a Guarantors of Brain Fellowship. R.A.I.B. is supported by a British Academy Post-Doctoral fellowship and the Autism Research Trust. We wish to thank Dr Petra Vertes and Dr Lisa Ronan for their advice on research design and Dr Simon R White for his statistical advice and support. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. This research was possible due to an application to the UK Biobank (project 20904)