Evaluation of imputation performance of multiple reference panels in a Pakistani population.

Genotype imputation is crucial for genome-wide association studies (GWASs), but reference panels and existing benchmarking studies prioritize European individuals. Consequently, it is unclear which publicly available reference panel should be used for Pakistani individuals, and whether ancestry composition or sample size of the panel matters more for imputation accuracy. Our study compared different reference panels to impute genotype data in 1,814 Pakistani individuals, finding the best performance balancing accuracy and coverage with meta-imputation with TOPMed and the expanded 1000 Genomes (ex1KG) reference.

BMI Interacts with the Genome to Regulate Gene Expression Globally, with Emphasis in the Brain and Gut.

Genome-wide association studies identify common genomic variants associated with disease across a population. Individual environmental effects are often not included, despite evidence that environment mediates genomic regulation of higher order biology. Body mass index (BMI) is associated with complex disorders across clinical specialties, yet has not been modeled as a genomic environment.

Decoding the transcriptomic signatures of psychological trauma in human cortex and amygdala.

Psychological trauma has profound effects on brain function and precipitates psychiatric disorders in vulnerable individuals, however, the molecular mechanisms linking trauma with psychiatric risk remain incompletely understood. Using RNA-seq data postmortem brain tissue of a cohort of 304 donors (N=136 with trauma exposure), we investigated transcriptional signatures of trauma exposures in two cortical regions (dorsolateral prefrontal cortex, and dorsal anterior cingulate cortex) and two amygdala regions (medial amygdala and basolateral amygdala) associated with stress processing and regulation. We focused on dissecting heterogeneity of traumatic experiences in these transcriptional signatures by investigating exposure to several trauma types (childhood, adulthood, complex, single acute, combat, and interpersonal traumas) and interactions with sex.

Critical reasoning on the co-expression module QTL in the dorsolateral prefrontal cortex.

Expression quantitative trait locus (eQTL) analysis is a popular method of gaining insight into the function of regulatory variation. While cis-eQTL resources have been instrumental in linking genome-wide association study variants to gene function, complex trait heritability may be additionally mediated by other forms of gene regulation. Toward this end, novel eQTL methods leverage gene co-expression (module-QTL) to investigate joint regulation of gene modules by single genetic variants.

Evaluation of imputation performance of multiple reference panels in a Pakistani population.

Genotype imputation is crucial for GWAS, but reference panels and existing benchmarking studies prioritize European individuals. Consequently, it is unclear which publicly available reference panel should be used for Pakistani individuals, and whether ancestry composition or sample size of the panel matters more for imputation accuracy. Our study compared different reference panels to impute genotype data in 1814 Pakistani individuals, finding the best performance balancing accuracy and coverage with meta-imputation with TOPMed and the expanded 1000 Genomes (ex1KG) reference.

Genetically Regulated Gene Expression in the Brain Associated With Chronic Pain: Relationships With Clinical Traits and Potential for Drug Repurposing.

Background: Chronic pain is a common, poorly understood condition. Genetic studies including genome-wide association studies have identified many relevant variants, which have yet to be translated into full understanding of chronic pain. Transcriptome-wide association studies using transcriptomic imputation methods such as S-PrediXcan can help bridge this genotype-phenotype gap.

Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings.

Major depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD.

Mapping anorexia nervosa genes to clinical phenotypes.

Background: Anorexia nervosa (AN) is a psychiatric disorder with complex etiology, with a significant portion of disease risk imparted by genetics. Traditional genome-wide association studies (GWAS) produce principal evidence for the association of genetic variants with disease. Transcriptomic imputation (TI) allows for the translation of those variants into regulatory mechanisms, which can then be used to assess the functional outcome of genetically regulated gene expression (GReX) in a broader setting through the use of phenome-wide association studies (pheWASs) in large and diverse clinical biobank populations with electronic health record phenotypes.

Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits.

One mechanism by which genetic factors influence complex traits and diseases is altering gene expression. Direct measurement of gene expression in relevant tissues is rarely tenable; however, genetically regulated gene expression (GReX) can be estimated using prediction models derived from large multi-omic datasets. These approaches have led to the discovery of many gene-trait associations, but whether models derived from predominantly European ancestry (EA) reference panels can map novel associations in ancestrally diverse populations remains unclear.

Comparison of confound adjustment methods in the construction of gene co-expression networks.

Adjustment for confounding sources of expression variation is an important preprocessing step in large gene expression studies, but the effect of confound adjustment on co-expression network analysis has not been well-characterized. Here, we demonstrate that the choice of confound adjustment method can have a considerable effect on the architecture of the resulting co-expression network. We compare standard and alternative confound adjustment methods and provide recommendations for their use in the construction of gene co-expression networks from bulk tissue RNA-seq datasets.

Corrigendum: Evaluation of Wearable Technology in Dementia: A Systematic Review and Meta-Analysis.

[This corrects the article DOI: 10.3389/fmed.2020.

Evaluation of Wearable Technology in Dementia: A Systematic Review and Meta-Analysis.

The objective of this analysis was to systematically review studies employing wearable technology in patients with dementia by quantifying differences in digitally captured physiological endpoints. This systematic review and meta-analysis was based on web searches of Cochrane Database, PsycInfo, Pubmed, Embase, and IEEE between October 25-31st, 2017. Observational studies providing physiological data measured by wearable technology on participants with dementia with a mean age ≥50.

A chromosomal connectome for psychiatric and metabolic risk variants in adult dopaminergic neurons.

Background: Midbrain dopaminergic neurons (MDN) represent 0.0005% of the brain's neuronal population and mediate cognition, food intake, and metabolism. MDN are also posited to underlay the neurobiological dysfunction of schizophrenia (SCZ), a severe neuropsychiatric disorder that is characterized by psychosis as well as multifactorial medical co-morbidities, including metabolic disease, contributing to markedly increased morbidity and mortality.

Evaluation of the use of the Scale for the Assessment and Rating of Ataxia (SARA) in healthy volunteers and patients with schizophrenia.

Objective: The Scale for the Assessment and Rating of Ataxia (SARA) is a semi-quantitative assessment used to evaluate ataxia. The goal of these studies was to assess and evaluate the utility of this instrument in a Healthy Volunteer (HV) group and subjects with Schizophrenia (SCZ).

Methods: Two studies were completed to collect SARA data, in a HV group and in a stable SCZ group.