Multiple testing correction in linear mixed models

Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data

Biosensors, such as microelectrode arrays that record in vitro neuronal activity, provide powerful platforms for studying neuroactive substances. This study presents a machine learning workflow to analyze drug-induced changes in neuronal biosensor data using complex network measures from graph theory. Microelectrode array recordings of neuronal networks exposed to bicuculline, a GABA[Formula: see text] receptor antagonist known to induce hypersynchrony, demonstrated the workflow's ability to detect and characterize pharmacological effects. The workflow integrates network-based features with synchrony, optimizing preprocessing parameters, including spike train bin sizes, segmentation window sizes, and correlation methods. It achieved high classification accuracy (AUC up to 90%) and used Shapley Additive Explanations to interpret feature importance rankings. Significant reductions in network complexity and segregation, hallmarks of epileptiform activity induced by bicuculline, were revealed. While bicuculline's effects are well established, this framework is designed to be broadly applicable for detecting both strong and subtle network alterations induced by neuroactive compounds. The results demonstrate the potential of this methodology for advancing biosensor applications in neuropharmacology and drug discovery.

MARSweb: a fully automated web service for set-based association testing

BACKGROUND

Despite the successes in GWAS, there is still a large gap between the known heritability and the part explained by the SNPs identified by GWAS. Set-based analysis is one of the approaches that has tried to identify associations between multiple variants in a locus a trait, leveraging allelic heterogeneity to increase power in association testing. MARS is a set-based analysis method that integrates likelihood ratio test with a recently developed fine mapping technique to accurately account for causal status of variants in a risk locus. Unfortunately, due to its complex running process, time complexity, and the requirement of high-performance computing resources, it is not widely used.

RESULTS

To address these issues, we proposed a fully automated web-based analysis service, MARSweb. By providing a web service, we minimized the effort required for initial configuration. Additionally, users can perform analyses by simply uploading their data without needing to familiarize themselves with intricate analysis procedures. Furthermore, it facilitates easier interpretation of results by integrating advanced visualization tools. We confirmed the performance of MARSweb by detecting eGenes and performing pathway analysis of the genes using a Yeast Dataset.

CONCLUSIONS

MARSweb is a web-based analysis service that fully automates set-based analysis. It offers an intuitive user interface, making complex analyses more accessible while significantly reducing processing time for enhanced efficiency. MARSweb is available for use at http://cblab.dongguk.edu/MARSweb and its source code is available at https://github.com/DGU-CBLAB/MARSweb .

FlexLMM: a Nextflow linear mixed model framework for GWAS

SUMMARY

Linear mixed models (LMMs) are a commonly used statistical approach in genome-wide association studies when population structure is present. However, naive permutations of the phenotype to empirically estimate the null distribution of a statistic of interest are not appropriate in the presence of population structure or covariates. This is because the samples are not exchangeable with each other under the null hypothesis, and because permuting the phenotypes breaks the relationship among those and eventual covariates. For this reason, we developed FlexLMM, a Nextflow pipeline that can perform appropriate permutations in LMMs while allowing for flexibility in the definition of the exact statistical model to be used. FlexLMM can set a significance threshold via permutations, thanks to a two-step process where the population structure is first regressed out, and only then are the permutations performed on the uncorrelated residuals. We envision this pipeline will be particularly useful for researchers working on multi-parental crosses among inbred lines of model organisms or farm animals and plants.

AVAILABILITY AND IMPLEMENTATION

The source code and documentation for the FlexLMM is available at https://github.com/birneylab/flexlmm.

Schizophrenia polygenic risk scores, clinical variables and genetic pathways as predictors of phenotypic traits of bipolar I disorder

AIM

We investigated the predictive value of polygenic risk scores (PRS) derived from the schizophrenia GWAS (Trubetskoy et al., 2022) (SCZ3) for phenotypic traits of bipolar disorder type-I (BP-I) in 1878 BP-I cases and 2751 controls from Romania and UK.

METHODS

We used PRSice-v2.3.3 and PRS-CS for computing SCZ3-PRS for testing the predictive power of SCZ3-PRS alone and in combination with clinical variables for several BP-I subphenotypes and for pathway analysis. Non-linear predictive models were also used.

RESULTS

SCZ3-PRS significantly predicted psychosis, incongruent and congruent psychosis, general age-of-onset (AO) of BP-I, AO-depression, AO-Mania, rapid cycling in univariate regressions. A negative correlation between the number of depressive episodes and psychosis, mainly incongruent and an inverse relationship between increased SCZ3-SNP loading and BP-I-rapid cycling were observed. In random forest models comparing the predictive power of SCZ3-PRS alone and in combination with nine clinical variables, the best predictions were provided by combinations of SCZ3-PRS-CS and clinical variables closely followed by models containing only clinical variables. SCZ3-PRS performed worst. Twenty-two significant pathways underlying psychosis were identified.

LIMITATIONS

The combined RO-UK sample had a certain degree of heterogeneity of the BP-I severity: only the RO sample and partially the UK sample included hospitalized BP-I cases. The hospitalization is an indicator of illness severity. Not all UK subjects had complete subphenotype information.

CONCLUSION

Our study shows that the SCZ3-PRS have a modest clinical value for predicting phenotypic traits of BP-I. For clinical use their best performance is in combination with clinical variables.

Quantitative genomics-enabled selection for simultaneous improvement of lint yield and seed traits in cotton (Gossypium hirsutum L.)

KEY MESSAGE

A Bayesian linkage disequilibrium-based multiple-locus mixed model identified QTLs for fibre, seed and oil traits and predicted breeding worthiness of test lines, enabling their simultaneous improvement in cotton. Improving cotton seed and oil yields has become increasingly important while continuing to breed for higher lint yield. In this study, a novel Bayesian linkage disequilibrium-based multiple-locus mixed model was developed for QTL identification and genomic prediction (GP). A multi-parent population consisting of 256 recombinant inbred lines, derived from four elite cultivars with distinct combinations of traits, was used in the analysis of QTLs for lint percentage, seed index, lint index and seed oil content and their interrelations. All four traits were moderately heritable and correlated but with no large influence of genotype × environment interactions across multiple seasons. Seven to ten major QTLs were identified for each trait with many being adjacent or overlapping for different trait pairs. A fivefold cross-validation of the model indicated prediction accuracies of 0.46-0.62. GP results based on any two-season phenotypes were strongly correlated with phenotypic means of a pooled analysis of three-season experiments (r = 0.83-0.92). When used for selection of improvement in lint, seed and oil yields, GP captured 40-100% of individuals with comparable lint yields of those selected based on the three-season phenotypic results. Thus, this quantitative genomics-enabled approach can not only decipher the genomic variation underlying lint, seed and seed oil traits and their interrelations, but can provide predictions for their simultaneous improvement. We discuss future breeding strategies in cotton that will enhance the entire value of the crop, not just its fibre.

Ankle-targeted exosuit resistance increases paretic propulsion in people post-stroke

BACKGROUND

Individualized, targeted, and intense training is the hallmark of successful gait rehabilitation in people post-stroke. Specifically, increasing use of the impaired ankle to increase propulsion during the stance phase of gait has been linked to higher walking speeds and symmetry. Conventional progressive resistance training is one method used for individualized and intense rehabilitation, but often fails to target paretic ankle plantarflexion during walking. Wearable assistive robots have successfully assisted ankle-specific mechanisms to increase paretic propulsion in people post-stroke, suggesting their potential to provide targeted resistance to increase propulsion, but this application remains underexamined in this population. This work investigates the effects of targeted stance-phase plantarflexion resistance training with a soft ankle exosuit on propulsion mechanics in people post-stroke.

METHODS

We conducted this study in nine individuals with chronic stroke and tested the effects of three resistive force magnitudes on peak paretic propulsion, ankle torque, and ankle power while participants walked on a treadmill at their comfortable walking speeds. For each force magnitude, participants walked for 1 min while the exosuit was inactive, 2 min with active resistance, and 1 min with the exosuit inactive, in sequence. We evaluated changes in gait biomechanics during the active resistance and post-resistance sections relative to the initial inactive section.

RESULTS

Walking with active resistance increased paretic propulsion by more than the minimal detectable change of 0.8 %body weight at all tested force magnitudes, with an average increase of 1.29 ± 0.37 %body weight at the highest force magnitude. This improvement corresponded to changes of 0.13 ± 0.03 N m kg- 1 in peak biological ankle torque and 0.26 ± 0.04 W kg- 1 in peak biological ankle power. Upon removal of resistance, propulsion changes persisted for 30 seconds with an improvement of 1.49 ± 0.58 %body weight after the highest resistance level and without compensatory involvement of the unresisted joints or limb.

CONCLUSIONS

Targeted exosuit-applied functional resistance of paretic ankle plantarflexors can elicit the latent propulsion reserve in people post-stroke. After-effects observed in propulsion highlight the potential for learning and restoration of propulsion mechanics. Thus, this exosuit-based resistive approach may offer new opportunities for individualized and progressive gait rehabilitation.

Novel insights into genome-wide associations in Bos indicus reveal genetic linkages between fertility and growth

Bos indicus breed Sahiwal, famous for its optimum performance, has so far been genetically improved for performance traits based on phenotypic records and the genomic knowhow regarding genes, regions and biological processes underlying the complex quantitative traits is lacking. In this context, a Genome-wide Association Study was performed for fertility and growth traits in Sahiwal cattle to shed light on its genomic profile. A total of 46 SNPs were found associated with the traits at genome-wide suggestive threshold of P ≤ 10^-4. USP32, LRPPRC, PLA2G10, RRN3 and ASAP1 were identified as putative candidate genes for body weight at different ages. However, several genes mapped for growth traits like GREB1, PLA2G10, RAD51C, BIRC6, TEX14 and PEBP4 had significant physiological underpinnings in determining fertility of the animals. Moreover, Quantitative trait loci (QTL) identification revealed potential overlaps with the already reported QTLs for both fertility and growth for most of the traits. Further, candidate SNP enrichment analysis revealed an enriched biological process for birth weight with a significant reproductive role. Based on the findings, genetic linkages underlying fertility and growth could be discerned in Sahiwal population and may be utilized for improving fertility traits in future.

Interactions between genetic and lifestyle factors on cardiometabolic disease-related outcomes in Latin American and Caribbean populations: A systematic review

Introduction

The prevalence of cardiometabolic diseases has increased in Latin American and the Caribbean populations (LACP). To identify gene-lifestyle interactions that modify the risk of cardiometabolic diseases in LACP, a systematic search using 11 search engines was conducted up to May 2022.

Methods

Eligible studies were observational and interventional studies in either English, Spanish, or Portuguese. A total of 26,171 publications were screened for title and abstract; of these, 101 potential studies were evaluated for eligibility, and 74 articles were included in this study following full-text screening and risk of bias assessment. The Appraisal tool for Cross-Sectional Studies (AXIS) and the Risk Of Bias In Non-Randomized Studies-of Interventions (ROBINS-I) assessment tool were used to assess the methodological quality and risk of bias of the included studies.

Results

We identified 122 significant interactions between genetic and lifestyle factors on cardiometabolic traits and the vast majority of studies come from Brazil (29), Mexico (15) and Costa Rica (12) with FTO, APOE, and TCF7L2 being the most studied genes. The results of the gene-lifestyle interactions suggest effects which are population-, gender-, and ethnic-specific. Most of the gene-lifestyle interactions were conducted once, necessitating replication to reinforce these results.

Discussion

The findings of this review indicate that 27 out of 33 LACP have not conducted gene-lifestyle interaction studies and only five studies have been undertaken in low-socioeconomic settings. Most of the studies were cross-sectional, indicating a need for longitudinal/prospective studies. Future gene-lifestyle interaction studies will need to replicate primary research of already studied genetic variants to enable comparison, and to explore the interactions between genetic and other lifestyle factors such as those conditioned by socioeconomic factors and the built environment. The protocol has been registered on PROSPERO, number CRD42022308488.

Systematic review registration

https://clinicaltrials.gov, identifier CRD420223 08488.

Identification of biomarkers to stratify response to B-cell-targeted therapies in systemic lupus erythematosus: an exploratory analysis of a randomised controlled trial

Background

Systemic lupus erythematosus (SLE) is a complex autoimmune disease associated with widespread immune dysregulation and diverse clinical features. Immune abnormalities might be differentially associated with specific organ involvement or response to targeted therapies. We aimed to identify biomarkers of response to belimumab after rituximab to facilitate a personalised approach to therapy.

Methods

In this exploratory analysis of a randomised controlled trial (BEAT-LUPUS), we investigated immune profiles of patients with SLE recruited to the 52-week clinical trial, which tested the combination of rituximab plus belimumab versus rituximab plus placebo. We used machine learning and conventional statistics to investigate relevant laboratory and clinical biomarkers associated with major clinical response. BEAT LUPUS is registered at ISRCTN, 47873003, and is now complete.

Findings

Between Feb 2, 2017, and March 28, 2019, 52 patients were recruited to BEAT-LUPUS, of whom 44 provided clinical data at week 52 and were included in this analysis. 21 (48%) of 44 participants were in the belimumab group (mean age 39·5 years [SD 12·1]; 17 [81%] were female, four [19%] were male, 13 [62%] were White) and 23 (52%) were in the placebo group (mean age 42·1 years [SD 10·5]; 21 [91%] were female, two [9%] were male, 16 [70%] were White). Ten (48%) of 21 participants who received belimumab after rituximab and eight (35%) of 23 who received placebo after rituximab had a major clinical response at 52 weeks (between-group difference of 13% [95% CI -15 to 38]). We found a predictive association between baseline serum IgA2 anti-double stranded DNA (dsDNA) antibody concentrations and clinical response to belimumab after rituximab, with a between-group difference in major clinical response of 48% (95% CI 10 to 70) in patients with elevated baseline serum IgA2 anti-dsDNA antibody concentrations. Moreover, among those who had a major clinical response, serum IgA2 anti-dsDNA antibody concentrations significantly decreased from baseline only in the belimumab group. Increased circulating IgA2 (but not total) plasmablast numbers, and T follicular helper cell numbers predicted clinical response and were both reduced only in patients who responded to belimumab after rituximab. Serum IgA2 anti-dsDNA antibody concentrations were also associated with active renal disease, whereas serum IgA1 anti-dsDNA antibody and IFN-α concentrations were associated with mucocutaneous disease activity but did not predict response to B-cell targeted therapy. Patients with a high baseline serum interleukin-6 concentration were less likely to have a major clinical response, irrespective of therapy.

Interpretation

This exploratory study revealed the presence of distinct molecular networks associated with renal and mucocutaneous involvement, and response to B-cell-targeted therapies, which, if confirmed, could guide precision targeting of advanced therapies for this heterogenous disease.

Funding

Versus Arthritis, UCLH Biomedical Research Centre, LUPUS UK, and GSK.

Admixture Mapping of Alzheimer's disease in Caribbean Hispanics identifies a new locus on 22q13.1

Late-onset Alzheimer's disease (LOAD) is significantly more frequent in Hispanics than in non-Hispanic Whites. Ancestry may explain these differences across ethnic groups. To this end, we studied a large cohort of Caribbean Hispanics (CH, N = 8813) and tested the association between Local Ancestry (LA) and LOAD ("admixture mapping") to identify LOAD-associated ancestral blocks, separately for ancestral components (European [EUR], African [AFR], Native American[NA]) and jointly (AFR + NA). Ancestral blocks significant after permutation were fine-mapped employing multi-ethnic whole-exome sequencing (WES) to identify rare variants associated with LOAD (SKAT-O) and replicated in the UK Biobank WES dataset. Candidate genes were validated studying (A) protein expression in human LOAD and control brains; (B) two animal AD models, Drosophila and Zebrafish. In the joint AFR + NA model, we identified four significant ancestral blocks located on chromosomes 1 (p value = 8.94E-05), 6 (p value = 8.63E-05), 21 (p value = 4.64E-05) and 22 (p value = 1.77E-05). Fine-mapping prioritized the GCAT gene on chromosome 22 (SKAT-O p value = 3.45E-05) and replicated in the UK Biobank (SKAT-O p value = 0.05). In LOAD brains, a decrease of 28% in GCAT protein expression was observed (p value = 0.038), and GCAT knockdown in Amyloid-β42 Drosophila exacerbated rough eye phenotype (68% increase, p value = 4.84E-09). In zebrafish, gcat expression increased after acute amyloidosis (34%, p value = 0.0049), and decreased upon anti-inflammatory Interleukin-4 (39%, p value = 2.3E-05). Admixture mapping uncovered genomic regions harboring new LOAD-associated loci that might explain the observed different frequency of LOAD across ethnic groups. Our results suggest that the inflammation-related activity of GCAT is a response to amyloid toxicity, and reduced GCAT expression exacerbates AD pathology.

Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies

Sprague Dawley (SD) rats are among the most widely used outbred laboratory rat populations. Despite this, the genetic characteristics of SD rats have not been clearly described, and SD rats are rarely used for experiments aimed at exploring genotype-phenotype relationships. In order to use SD rats to perform a genome-wide association study (GWAS), we collected behavioral data from 4,625 SD rats that were predominantly obtained from two commercial vendors, Charles River Laboratories and Harlan Sprague Dawley Inc. Using double-digest genotyping-by-sequencing (ddGBS), we obtained dense, high-quality genotypes at 291,438 SNPs across 4,061 rats. This genetic data allowed us to characterize the variation present in Charles River vs. Harlan SD rats. We found that the two populations are highly diverged (F_ST > 0.4). Furthermore, even for rats obtained from the same vendor, there was strong population structure across breeding facilities and even between rooms at the same facility. We performed multiple separate GWAS by fitting a linear mixed model that accounted for population structure and using meta-analysis to jointly analyze all cohorts. Our study examined Pavlovian conditioned approach (PavCA) behavior, which assesses the propensity for rats to attribute incentive salience to reward-associated cues. We identified 46 significant associations for the various metrics used to define PavCA. The surprising degree of population structure among SD rats from different sources has important implications for their use in both genetic and non-genetic studies.

Outbred Sprague Dawley rats are among the most commonly used rats for neuroscience, physiology and pharmacological research; in the year 2020, 4,188 publications contained the keyword “Sprague Dawley”. Rats identified as “Sprague Dawley” are sold by several commercial vendors, including Charles River Laboratories and Harlan Sprague Dawley Inc. (now Envigo). Despite their widespread use, little is known about the genetic diversity of SD. We genotyped more than 4,000 SD rats, which we used for a genome-wide association study (GWAS) and to characterize genetic differences between SD rats from Charles River Laboratories and Harlan. Our analysis revealed extensive population structure both between and within vendors. The GWAS for Pavlovian conditioned approach (PavCA) identified a number of genome-wide significant loci for that complex behavioral trait. Our results demonstrate that, despite sharing an identical name, SD rats that are obtained from different vendors are very different. Future studies should carefully define the exact source of SD rats being used and may exploit their genetic diversity for genetic studies of complex traits.

Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.

Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits

While large-scale, genome-wide association studies (GWAS) have identified hundreds of loci associated with brain-related traits, identification of the variants, genes and molecular mechanisms underlying these traits remains challenging. Integration of GWAS with expression quantitative trait loci (eQTLs) and identification of shared genetic architecture have been widely adopted to nominate genes and candidate causal variants. However, this approach is limited by sample size, statistical power and linkage disequilibrium. We developed the multivariate multiple QTL approach and performed a large-scale, multi-ancestry eQTL meta-analysis to increase power and fine-mapping resolution. Analysis of 3,983 RNA-sequenced samples from 2,119 donors, including 474 non-European individuals, yielded an effective sample size of 3,154. Joint statistical fine-mapping of eQTL and GWAS identified 329 variant-trait pairs for 24 brain-related traits driven by 204 unique candidate causal variants for 189 unique genes. This integrative analysis identifies candidate causal variants and elucidates potential regulatory mechanisms for genes underlying schizophrenia, bipolar disorder and Alzheimer's disease.

EXPRESS: An eye-tracking investigation of the cognitive processes involved in the comprehension of simple and complex communicative acts

Indirect speech acts communicate more than their literal meaning, and their comprehension relies on the listener's ability to draw the appropriate inferences in a given context. We used eye-tracking to investigate the cognitive processing involved in the comprehension of simple (direct) and complex (unconventional indirect) communicative acts, a more general distinction that applies not only to sincere speech acts, but also to irony and deceit. We recorded the eye movements of 40 participants while they read 60 stories (20 sincere, 20 deceitful, 20 ironic) consisting of a context and a target answer. For each story, we created two different contexts so that the same identical target answer was a simple (direct) and a complex (unconventional indirect) communicative act, respectively. We also assessed the indirectness of simple and complex communicative acts, as well as participants' working memory (WM) and Theory of Mind (ToM). Eye-pattern analysis showed that complex communicative acts were more difficult to understand than simple acts; differences between simple and complex acts held for all the pragmatic phenomena investigated, though processing differences were greater for sincere acts than for irony and deceit. We found a role of indirectness and ToM in the pragmatic processing of simple and complex acts, whereas the role of WM was modest. The present findings underscore the importance of adopting an encompassing theory that can account for different types of indirect speech acts, such as sincere, deceitful and ironic acts; they also suggest the importance of assessing individual differences in inferential and cognitive abilities.

Study protocol for iSIPsmarter: A randomized-controlled trial to evaluate the efficacy, reach, and engagement of a technology-based behavioral intervention to reduce sugary beverages among rural Appalachian adults

Sugar-sweetened beverage (SSB) consumption is disproportionately high among rural Appalachian adults, with intakes double the national average and nearly four times the recommended amount. This trial targets this major dietary risk factor and addresses notable gaps in the rural digital health intervention literature. iSIPsmarter is a technology-based behavior and health literacy intervention aimed at improving SSB behaviors. It is comprised of six Internet-delivered, interactive Cores delivered weekly, an integrated short message service (SMS) strategy to engage users in tracking and reporting SSB behaviors, and a cellular-enabled scale for in-home weighing. iSIPsmarter is adapted from an evidence-based intervention and is grounded by the Theory of Planned Behavior and health literacy, numeracy, and media literacy concepts. The RCT is guided by the RE-AIM framework and targets 244 rural Appalachian adults. The goal is to examine the efficacy of iSIPsmarter to reduce SSB in a two-group design [iSIPsmarter vs. static Participant Education website] with four assessment points. Changes in secondary outcomes (e.g., diet quality, weight, quality of life) and maintenance of outcomes will also be evaluated. Additional secondary aims are to examine reach and representativeness, patterns of user engagement, and cost. Two tertiary aims are exploratory mediation analyses and a systems-level, participatory evaluation to understand context for future organizational-level adoption of iSIPsmarter. The long-term goal is to sustain an effective, scalable, and high reach behavioral intervention to reduce SSB-related health inequities and related chronic conditions (i.e., obesity, diabetes, some obesity-related cancers, heart disease, hypertension, dental decay) in rural Appalachia and beyond. ClinicalTrial registry: NCT05030753.

The monologue of the double: Allocentric reduplication of the own voice alters bodily self-perception

During autoscopic phenomena, people perceive a double of themselves in extrapersonal space. Such clinical allocentric self-experiences sometimes co-occur with auditory hallucinations, yet experimental setups to induce similar illusions in healthy participants have generally neglected acoustic cues. We investigated whether feeling the presence of an auditory double could be provoked experimentally by recording healthy participants' own versus another person's voice and movements using binaural headphones from an egocentric (the participants' own) and an allocentric (a dummy head located elsewhere) perspective. When hearing themselves allocentrically, participants reported feeling a self-identified presence extracorporeally, an arguably distinct quality of autoscopy. Our results suggest that participants without hallucinatory experiences localized their own voice closer to themselves compared to that of another person. Explorative findings suggest that distinct patterns for hallucinators should be further investigated. This study suggests a successful induction of the feeling of an acoustic doppelganger, bridging clinical phenomena and experimental work.

Evidence for the butyrate metabolism as key pathway improving ulcerative colitis in both pediatric and adult patients

Accumulating evidence has shown many similarities and differences of gene profiles and pathways between pediatric and adult ulcerative colitis (UC) patients. In this study, we aimed to investigate the shared genes and pathways in intestinal tissues of pediatric and adult UC. Differentially expressed genes (DEGs) between pediatric and adult UC were identified via bioinformatic analysis of Gene Expression Omnibus datasets GSE87473 and GSE126124. Gene Ontology and pathway enrichment were used to analyze overlapped and distinguished DEGs. Gene Set Variation Analysis (GSVA) was utilized for contrast consistency. Mice colitis models were induced by dextran sulfate sodium (DSS) and Citrobacter rodentium. 2616 DEGs were screened out in intestinal tissues of adult UC compared with those of adult healthy controls, and 1195 DEGs in pediatrics. Same pathways between pediatric and adult UC were enriched using overlapped DEGs, mainly related to immune responses and metabolic processes, including butyrate metabolism, which was also identified by GSVA analysis. Of note, butyrate metabolism was the exclusive down-regulated pathway enriched by these two analyses, indicating that butyrate metabolism is one of the key pathways associated with both pediatric and adult UC. In addition, butyrate suppressed DSS-induced and Citrobacter rodentium-induced intestinal inflammation in mice. Therefore, the study revealed that butyrate metabolism was critical in both pediatric and adult UC. And butyrate suppressed colitis in mice, which provided a theoretical basis for the potential treatment of butyrate for UC patients.

Abbreviations: UC, Ulcerative colitis; IBD, Inflammatory bowel disease; DEGs, Differentially expressed genes; GEO, Gene Expression Omnibus; SVA, Spatial variant apodization; LIMMA, Linear models for the microarray data; FC, Fold change; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; GSVA, Gene Set Variation Analysis; MSigDB, Molecular Signatures Database; WT, Wild-type; DSS, Dextran sulfate sodium; HC, Healthy control; SD, Standard deviation; SNHG5, Small nucleolar RNA host gene 5; GLP-2, Glucagon-like peptide 2; GSE, Gene set enrichment; ECM, Extracellular matrix; TCA, Tricarboxylic acid cycle; NA, Not available.

Estimating the effective sample size in association studies of quantitative traits

The effective sample size (ESS) is a metric used to summarize in a single term the amount of correlation in a sample. It is of particular interest when predicting the statistical power of genome-wide association studies (GWAS) based on linear mixed models. Here, we introduce an analytical form of the ESS for mixed-model GWAS of quantitative traits and relate it to empirical estimators recently proposed. Using our framework, we derived approximations of the ESS for analyses of related and unrelated samples and for both marginal genetic and gene-environment interaction tests. We conducted simulations to validate our approximations and to provide a quantitative perspective on the statistical power of various scenarios, including power loss due to family relatedness and power gains due to conditioning on the polygenic signal. Our analyses also demonstrate that the power of gene-environment interaction GWAS in related individuals strongly depends on the family structure and exposure distribution. Finally, we performed a series of mixed-model GWAS on data from the UK Biobank and confirmed the simulation results. We notably found that the expected power drop due to family relatedness in the UK Biobank is negligible.

Status and prospects of genome-wide association studies in plants

Genome-wide association studies (GWAS) have developed into a powerful and ubiquitous tool for the investigation of complex traits. In large part, this was fueled by advances in genomic technology, enabling us to examine genome-wide genetic variants across diverse genetic materials. The development of the mixed model framework for GWAS dramatically reduced the number of false positives compared with naïve methods. Building on this foundation, many methods have since been developed to increase computational speed or improve statistical power in GWAS. These methods have allowed the detection of genomic variants associated with either traditional agronomic phenotypes or biochemical and molecular phenotypes. In turn, these associations enable applications in gene cloning and in accelerated crop breeding through marker assisted selection or genetic engineering. Current topics of investigation include rare-variant analysis, synthetic associations, optimizing the choice of GWAS model, and utilizing GWAS results to advance knowledge of biological processes. Ongoing research in these areas will facilitate further advances in GWAS methods and their applications.

Iterative epigenomic analyses in the same single cell

Gene expression in individual cells is epigenetically regulated by DNA modifications, histone modifications, transcription factors, and other DNA-binding proteins. It has been shown that multiple histone modifications can predict gene expression and reflect future responses of bulk cells to extracellular cues. However, the predictive ability of epigenomic analysis is still limited for mechanistic research at a single cell level. To overcome this limitation, it would be useful to acquire reliable signals from multiple epigenetic marks in the same single cell. Here, we propose a new approach and a new method for analysis of several components of the epigenome in the same single cell. The new method allows reanalysis of the same single cell. We found that reanalysis of the same single cell is feasible, provides confirmation of the epigenetic signals, and allows application of statistical analysis to identify reproduced reads using data sets generated only from the single cell. Reanalysis of the same single cell is also useful to acquire multiple epigenetic marks from the same single cells. The method can acquire at least five epigenetic marks: H3K27ac, H3K27me3, mediator complex subunit 1, a DNA modification, and a DNA-interacting protein. We can predict active signaling pathways in K562 single cells using the epigenetic data and confirm that the predicted results strongly correlate with actual active signaling pathways identified by RNA-seq results. These results suggest that the new method provides mechanistic insights for cellular phenotypes through multilayered epigenome analysis in the same single cells.

Central Auditory Tests to Track Cognitive Function in People With HIV: Longitudinal Cohort Study

Background

The development of neurocognitive deficits in people infected with HIV is a significant public health problem. Previous cross-sectional studies have shown that performance on central auditory tests (CATs) correlates with cognitive test results in those with HIV, but no longitudinal data exist for confirmation. We have been performing longitudinal assessments of central auditory and cognitive function on a cohort of HIV-positive and HIV-negative individuals in Dar es Salaam, Tanzania to understand how the central auditory system could be used to study and track the progress of central nervous system dysfunction.

Objective

The goal of the project was to determine if CATs can track the trajectory of cognitive function over time in people diagnosed with HIV.

Methods

Tests of peripheral and central auditory function as well as cognitive performance were performed on 382 individuals over the course of 3.5 years. Visits were scheduled every 6 months. CATs included tests of auditory temporal processing (gap detection) and speech perception in noise (Hearing in Noise Test and Triple Digit Test). Cognitive tests included the Montreal Cognitive Assessment (MoCA), Test of Variables of Attention (TOVA), and subtests from the Cogstate battery. HIV-positive subjects were divided into groups based on their CAT results at their final visit (bottom 20%, top 20%, middle 60%). Primary analyses focused on the comparison between HIV-positive individuals that performed worse on CATs (bottom 20%) and the overall HIV-positive group (middle 60%). Data were analyzed using linear mixed-effect models with time as the main fixed effect.

Results

The group with the worst (bottom 20%) CAT performance showed a difference in trajectory for the MoCA (P=.003), TOVA (P<.048), and Cogstate (P<.046) over the course of the study period compared to the overall HIV-positive group. A battery of three CATs showed a significant difference in cognitive trajectory over a relatively short study period of 3.5 years independent of age (bottom 20% vs HIV-positive group).

Conclusions

The results of this study support the ability for CATs to track cognitive function over time, suggesting that central auditory processing can provide a window into central nervous system performance. CATs can be simple to perform, and are relatively insensitive to education and socioeconomic status because they only require repeating sentences, numbers, or detecting gaps in noise. These tests could potentially provide a time-efficient, low-cost method to screen for and monitor cognitive decline in patients with HIV, making them a useful surveillance tool for this major public health problem.

Gene-level quantitative trait mapping in Caenorhabditis elegans

The Caenorhabditis elegans multiparental experimental evolution (CeMEE) panel is a collection of genome-sequenced, cryopreserved recombinant inbred lines useful for mapping the evolution and genetic basis of quantitative traits. We have expanded the resource with new lines and new populations, and here report the genotype and haplotype composition of CeMEE version 2, including a large set of putative de novo mutations, and updated additive and epistatic mapping simulations. Additive quantitative trait loci explaining 4% of trait variance are detected with >80% power, and the median detection interval approaches single-gene resolution on the highly recombinant chromosome arms. Although CeMEE populations are derived from a long-term evolution experiment, genetic structure is dominated by variation present in the ancestral population.

Longitudinal analysis of regional cerebellum volumes during normal aging

Some cross-sectional studies suggest reduced cerebellar volumes with aging, but there have been few longitudinal studies of age changes in cerebellar subregions in cognitively healthy older adults. In this work, 2,023 magnetic resonance (MR) images of 822 cognitively normal participants from the Baltimore Longitudinal Study of Aging (BLSA) were analyzed. Participants ranged in age from 50 to 95 years (mean 70.7 years) at the baseline assessment. Follow-up intervals were 1-9 years (mean 3.7 years) for participants with two or more visits. We used a recently developed cerebellum parcellation algorithm based on convolutional neural networks to divide the cerebellum into 28 subregions. Linear mixed effects models were applied to the volume of each cerebellar subregion to investigate cross-sectional and longitudinal age effects, as well as effects of sex and their interactions, after adjusting for intracranial volume. Our findings suggest spatially varying atrophy patterns across the cerebellum with respect to age and sex both cross-sectionally and longitudinally.

Effects of Aerobic Training Versus Breathing Exercises on Asthma Control: A Randomized Trial

BACKGROUND

Aerobic training and breathing exercises are interventions that improve asthma control. However, the outcomes of these 2 interventions have not been compared.

OBJECTIVE

To compare the effects of aerobic training versus breathing exercises on clinical control (primary outcome), quality of life, exercise capacity, and airway inflammation in outpatients with moderate-to-severe asthma.

METHODS

Fifty-four asthmatics were randomized into either the aerobic training group (AG, n = 29) or the breathing exercise group (BG, n = 25). Both interventions lasted for 24 sessions (2/week, 40 minutes/session). Asthma clinical control (Asthma Control Questionnaire [ACQ]), quality of life (Asthma Quality of Life Questionnaire), asthma symptom-free days (ASFD), airway inflammation, exercise capacity, psychological distress (Hospital Anxiety and Depression Scale), daily-life physical activity (DLPA), and pulmonary function were evaluated before, immediately after, and 3 months after the intervention.

RESULTS

Both interventions presented similar results regarding the ACQ score, psychological distress, ASFD, DLPA, and airway inflammation (P > .05). However, participants in the AG were 2.6 times more likely to experience clinical improvement at the 3-month follow-up than participants in the BG (P = .02). A greater proportion of participants in the AG also presented a reduction in the number of days without rescue medication use compared with BG (34% vs 8%; P = .04).

CONCLUSIONS

Outpatients with moderate-to-severe asthma who participated in aerobic training or breathing exercise programs presented similar results in asthma control, quality of life, asthma symptoms, psychological distress, physical activity, and airway inflammation. However, a greater proportion of participants in the AG presented improvement in asthma control and reduced use of rescue medication.

Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity

There has been extensive discussion of the "Replication Crisis" in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner's Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.

Last-Generation Genome-Environment Associations Reveal the Genetic Basis of Heat Tolerance in Common Bean (Phaseolus vulgaris L.)

Genome-environment associations (GEAs) are a powerful strategy for the study of adaptive traits in wild plant populations, yet they still lack behind in the use of modern statistical methods as the ones suggested for genome-wide association studies (GWASs). In order to bridge this gap, we couple GEA with last-generation GWAS algorithms in common bean to identify novel sources of heat tolerance across naturally heterogeneous ecosystems. Common bean (Phaseolus vulgaris L.) is the most important legume for human consumption, and breeding it for resistance to heat stress is key because annual increases in atmospheric temperature are causing decreases in yield of up to 9% for every 1°C. A total of 78 geo-referenced wild accessions, spanning the two gene pools of common bean, were genotyped by sequencing (GBS), leading to the discovery of 23,373 single-nucleotide polymorphism (SNP) markers. Three indices of heat stress were developed for each accession and inputted in last-generation algorithms (i.e. SUPER, FarmCPU, and BLINK) to identify putative associated loci with the environmental heterogeneity in heat stress. Best-fit models revealed 120 significantly associated alleles distributed in all 11 common bean chromosomes. Flanking candidate genes were identified using 1-kb genomic windows centered in each associated SNP marker. Some of these genes were directly linked to heat-responsive pathways, such as the activation of heat shock proteins (MED23, MED25, HSFB1, HSP40, and HSP20). We also found protein domains related to thermostability in plants such as S1 and Zinc finger A20 and AN1. Other genes were related to biological processes that may correlate with plant tolerance to high temperature, such as time to flowering (MED25, MBD9, and PAP), germination and seedling development (Pkinase_Tyr, Ankyrin-B, and Family Glicosil-hydrolase), cell wall stability (GAE6), and signaling pathway of abiotic stress via abscisic acid (histone-like transcription factors NFYB and phospholipase C) and auxin (Auxin response factor and AUX_IAA). This work offers putative associated loci for marker-assisted and genomic selection for heat tolerance in common bean. It also demonstrates that it is feasible to identify genome-wide environmental associations with modest sample sizes by using a combination of various carefully chosen environmental indices and last-generation GWAS algorithms.

Comprehensive Multiple eQTL Detection and Its Application to GWAS Interpretation

Expression QTL (eQTL) detection has emerged as an important tool for unraveling the relationship between genetic risk factors and disease or clinical phenotypes. Most studies are predicated on the assumption that only a single causal variant explains the association signal in each interval. This greatly simplifies the statistical modeling, but is liable to biases in scenarios where multiple local causal-variants are responsible. Here, our primary goal was to address the prevalence of secondary cis-eQTL signals regulating peripheral blood gene expression locally, utilizing two large human cohort studies, each >2500 samples with accompanying whole genome genotypes. The CAGE (Consortium for the Architecture of Gene Expression) dataset is a compendium of Illumina microarray studies, and the Framingham Heart Study is a two-generation Affymetrix dataset. We also describe Bayesian colocalization analysis of the extent of sharing of cis-eQTL detected in both studies as well as with the BIOS RNAseq dataset. Stepwise conditional modeling demonstrates that multiple eQTL signals are present for ∼40% of over 3500 eGenes in both microarray datasets, and that the number of loci with additional signals reduces by approximately two-thirds with each conditioning step. Although <20% of the peak signals across platforms fine map to the same credible interval, the colocalization analysis finds that as many as 50-60% of the primary eQTL are actually shared. Subsequently, colocalization of eQTL signals with GWAS hits detected 1349 genes whose expression in peripheral blood is associated with 591 human phenotype traits or diseases, including enrichment for genes with regulatory functions. At least 10%, and possibly as many as 40%, of eQTL-trait colocalized signals are due to nonprimary cis-eQTL peaks, but just one-quarter of these colocalization signals replicated across the gene expression datasets. Our results are provided as a web-based resource for visualization of multi-site regulation of gene expression and its association with human complex traits and disease states.

Genome-wide Significance Thresholds for Admixture Mapping Studies

Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 × 10-5 and 4.5 × 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.

Replication and discovery of musculoskeletal QTLs in LG/J and SM/J advanced intercross lines

The genetics underlying variation in health‐related musculoskeletal phenotypes can be investigated in a mouse model. Quantitative trait loci (QTLs) affecting musculoskeletal traits in the LG/J and SM/J strain lineage remain to be refined and corroborated. The aim of this study was to map muscle and bone traits in males (n = 506) of the 50th filial generation of advanced intercross lines (LG/SM AIL) derived from the two strains. Genetic contribution to variation in all musculoskeletal traits was confirmed; the SNP heritability of muscle mass ranged between 0.46 and 0.56; and the SNP heritability of tibia length was 0.40. We used two analytical software, GEMMA and QTLRel, to map the underlying QTLs. GEMMA required substantially less computation and recovered all the QTLs identified by QTLRel. Seven significant QTLs were identified for muscle weight (Chr 1, 7, 11, 12, 13, 15, and 16), and two for tibia length, (Chr 1 and 13). Each QTL explained 4–5% of phenotypic variation. One muscle and both bone loci replicated previous findings; the remaining six were novel. Positional candidates for the replicated QTLs were prioritized based on in silico analyses and gene expression in muscle tissue. In summary, we replicated existing QTLs and identified novel QTLs affecting muscle weight, and replicated bone length QTLs in LG/SM AIL males. Heritability estimates substantially exceed the cumulative effect of the QTLs, hence a richer genetic architecture contributing to muscle and bone variability could be uncovered with a larger sample size.

Genome wide association analysis in a mouse advanced intercross line

The LG/J x SM/J advanced intercross line of mice (LG x SM AIL) is a multigenerational outbred population. High minor allele frequencies, a simple genetic background, and the fully sequenced LG and SM genomes make it a powerful population for genome-wide association studies. Here we use 1,063 AIL mice to identify 126 significant associations for 50 traits relevant to human health and disease. We also identify thousands of cis- and trans-eQTLs in the hippocampus, striatum, and prefrontal cortex of ~200 mice. We replicate an association between locomotor activity and Csmd1, which we identified in an earlier generation of this AIL, and show that Csmd1 mutant mice recapitulate the locomotor phenotype. Our results demonstrate the utility of the LG x SM AIL as a mapping population, identify numerous novel associations, and shed light on the genetic architecture of mammalian behavior.

Infant diet and maternal gestational weight gain predict early metabolic maturation of gut microbiomes

Commensal gut bacterial communities (microbiomes) are predicted to influence human health and disease1,2. Neonatal gut microbiomes are colonized with maternal and environmental flora and mature toward a stable composition over 2-3 years3,4. To study pre- and postnatal determinants of infant microbiome development, we analyzed 402 fecal metagenomes from 60 infants aged 0-8 months, using longitudinal generalized linear mixed models (GLMMs). Distinct microbiome signatures correlated with breastfeeding, formula ingredients, and maternal gestational weight gain (GWG). Amino acid synthesis pathway accretion in breastfed microbiomes complemented normative breastmilk composition. Prebiotic oligosaccharides, designed to promote breastfed-like microflora5, predicted functional pathways distinct from breastfed infant microbiomes. Soy formula in six infants was positively associated with Lachnospiraceae and pathways suggesting a short-chain fatty acid (SCFA)-rich environment, including glycerol to 1-butanol fermentation, which is potentially dysbiotic. GWG correlated with altered carbohydrate degradation and enriched vitamin synthesis pathways. Maternal and postnatal antibiotics predicted microbiome alterations, while delivery route had no persistent effects. Domestic water source correlates suggest water may be an underappreciated determinant of microbiome acquisition. Clinically important microbial pathways with statistically significant dietary correlates included dysbiotic markers6,7, core enterotype features8, and synthesis pathways for enteroprotective9 and immunomodulatory10,11 metabolites, epigenetic mediators1, and developmentally critical vitamins12, warranting further investigation.

Genome-wide association study for intramuscular fat content in Chinese Lulai black pigs

Objective

Intramuscular fat (IMF) content plays an important role in meat quality. Identification of single nucleotide polymorphisms (SNPs) and genes related to pig IMF, especially using pig populations with high IMF content variation, can help to establish novel molecular breeding tools for optimizing IMF in pork and unveil the mechanisms that underlie fat metabolism.

Methods

We collected muscle samples of 453 Chinese Lulai black pigs, measured IMF content by Soxhlet petroleum-ether extraction method, and genotyped genome-wide SNPs using GeneSeek Genomic Profiler Porcine HD BeadChip. Then a genome-wide association study was performed using a linear mixed model implemented in the GEMMA software.

Results

A total of 43 SNPs were identified to be significantly associated with IMF content by the cutoff p<0.001. Among these significant SNPs, the greatest number of SNPs (n = 19) were detected on Chr.9, and two linkage disequilibrium blocks were formed among them. Additionally, 17 significant SNPs are mapped to previously reported quantitative trait loci (QTLs) of IMF and confirmed previous QTLs studies. Forty-two annotated genes centering these significant SNPs were obtained from Ensembl database. Overrepresentation test of pathways and gene ontology (GO) terms revealed some enriched reactome pathways and GO terms, which mainly involved regulation of basic material transport, energy metabolic process and signaling pathway.

Conclusion

These findings improve our understanding of the genetic architecture of IMF content in pork and facilitate the follow-up study of fine-mapping genes that influence fat deposition in muscle.

Wild GWAS-association mapping in natural populations

The increasing affordability of sequencing and genotyping technologies has transformed the field of molecular ecology in recent decades. By correlating marker variants with trait variation using association analysis, large-scale genotyping and phenotyping of individuals from wild populations has enabled the identification of genomic regions that contribute to phenotypic differences among individuals. Such "gene mapping" studies are enabling us to better predict evolutionary potential and the ability of populations to adapt to challenges, such as changing environment. These studies are also allowing us to gain insight into the evolutionary processes maintaining variation in natural populations, to better understand genotype-by-environment and epistatic interactions and to track the dynamics of allele frequency change at loci contributing to traits under selection. Gene mapping in the wild using genomewide association scans (GWAS) do, however, come with a number of methodological challenges, not least the population structure in space and time inherent to natural populations. We here provide an overview of these challenges, summarize the exciting methodological advances and applications of association mapping in natural populations reported in this special issue and provide some guidelines for future "wild GWAS" research.

Applying meta-analysis to genotype-tissue expression data from multiple tissues to identify eQTLs and increase the number of eGenes

Motivation

There is recent interest in using gene expression data to contextualize findings from traditional genome-wide association studies (GWAS). Conditioned on a tissue, expression quantitative trait loci (eQTLs) are genetic variants associated with gene expression, and eGenes are genes whose expression levels are associated with genetic variants. eQTLs and eGenes provide great supporting evidence for GWAS hits and important insights into the regulatory pathways involved in many diseases. When a significant variant or a candidate gene identified by GWAS is also an eQTL or eGene, there is strong evidence to further study this variant or gene. Multi-tissue gene expression datasets like the Gene Tissue Expression (GTEx) data are used to find eQTLs and eGenes. Unfortunately, these datasets often have small sample sizes in some tissues. For this reason, there have been many meta-analysis methods designed to combine gene expression data across many tissues to increase power for finding eQTLs and eGenes. However, these existing techniques are not scalable to datasets containing many tissues, like the GTEx data. Furthermore, these methods ignore a biological insight that the same variant may be associated with the same gene across similar tissues.

Results

We introduce a meta-analysis model that addresses these problems in existing methods. We focus on the problem of finding eGenes in gene expression data from many tissues, and show that our model is better than other types of meta-analyses.

Availability and Implementation

Source code is at https://github.com/datduong/RECOV.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genome-wide association across Saccharomyces cerevisiae strains reveals substantial variation in underlying gene requirements for toxin tolerance

Cellulosic plant biomass is a promising sustainable resource for generating alternative biofuels and biochemicals with microbial factories. But a remaining bottleneck is engineering microbes that are tolerant of toxins generated during biomass processing, because mechanisms of toxin defense are only beginning to emerge. Here, we exploited natural diversity in 165 Saccharomyces cerevisiae strains isolated from diverse geographical and ecological niches, to identify mechanisms of hydrolysate-toxin tolerance. We performed genome-wide association (GWA) analysis to identify genetic variants underlying toxin tolerance, and gene knockouts and allele-swap experiments to validate the involvement of implicated genes. In the process of this work, we uncovered a surprising difference in genetic architecture depending on strain background: in all but one case, knockout of implicated genes had a significant effect on toxin tolerance in one strain, but no significant effect in another strain. In fact, whether or not the gene was involved in tolerance in each strain background had a bigger contribution to strain-specific variation than allelic differences. Our results suggest a major difference in the underlying network of causal genes in different strains, suggesting that mechanisms of hydrolysate tolerance are very dependent on the genetic background. These results could have significant implications for interpreting GWA results and raise important considerations for engineering strategies for industrial strain improvement.

Understanding the genetic architecture of complex traits is important for elucidating the genotype-phenotype relationship. Many studies have sought genetic variants that underlie phenotypic variation across individuals, both to implicate causal variants and to inform on architecture. Here we used genome-wide association analysis to identify genes and processes involved in tolerance of toxins found in plant-biomass hydrolysate, an important substrate for sustainable biofuel production. We found substantial variation in whether or not individual genes were important for tolerance across genetic backgrounds. Whether or not a gene was important in a given strain background explained more variation than the alleleic differences in the gene. These results suggest substantial variation in gene contributions, and perhaps underlying mechanisms, of toxin tolerance.

Cis-SNPs Set Testing and PrediXcan Analysis for Gene Expression Data using Linear Mixed Models

Understanding the functional mechanism of SNPs identified in GWAS on complex diseases is currently a challenging task. The studies of expression quantitative trait loci (eQTL) have shown that regulatory variants play a crucial role in the function of associated SNPs. Detecting significant genes (called eGenes) in eQTL studies and analyzing the effect sizes of cis-SNPs can offer important implications on the genetic architecture of associated SNPs and interpretations of the molecular basis of diseases. We applied linear mixed models (LMM) to the gene expression level and constructed likelihood ratio tests (LRT) to test for eGene in the Geuvadis data. We identified about 11% genes as eGenes in the Geuvadis data and found some eGenes were enriched in approximately independent linkage disequilibrium (LD) blocks (e.g. MHC). We further performed PrediXcan analysis for seven diseases in the WTCCC data with weights estimated using LMM and identified 64, 5, 21 and 1 significant genes (p < 0.05 after Bonferroni correction) associated with T1D, CD, RA and T2D. We found most of the significant genes of T1D and RA were also located within the MHC region. Our results provide strong evidence that gene expression plays an intermediate role for the associated variants in GWAS.

Widespread Allelic Heterogeneity in Complex Traits

Recent successes in genome-wide association studies (GWASs) make it possible to address important questions about the genetic architecture of complex traits, such as allele frequency and effect size. One lesser-known aspect of complex traits is the extent of allelic heterogeneity (AH) arising from multiple causal variants at a locus. We developed a computational method to infer the probability of AH and applied it to three GWASs and four expression quantitative trait loci (eQTL) datasets. We identified a total of 4,152 loci with strong evidence of AH. The proportion of all loci with identified AH is 4%-23% in eQTLs, 35% in GWASs of high-density lipoprotein (HDL), and 23% in GWASs of schizophrenia. For eQTLs, we observed a strong correlation between sample size and the proportion of loci with AH (R2 = 0.85, p = 2.2 × 10-16), indicating that statistical power prevents identification of AH in other loci. Understanding the extent of AH may guide the development of new methods for fine mapping and association mapping of complex traits.

Strategy-based reasoning training modulates cortical thickness and resting-state functional connectivity in adults with chronic traumatic brain injury

INTRODUCTION

Prior studies have demonstrated training-induced changes in the healthy adult brain. Yet, it remains unclear how the injured brain responds to cognitive training months-to-years after injury.

METHODS

Sixty individuals with chronic traumatic brain injury (TBI) were randomized into either strategy-based (N = 31) or knowledge-based (N = 29) training for 8 weeks. We measured cortical thickness and resting-state functional connectivity (rsFC) before training, immediately posttraining, and 3 months posttraining.

RESULTS

Relative to the knowledge-based training group, the cortical thickness of the strategy-based training group showed diverse temporal patterns of changes over multiple brain regions (pvertex < .05, pcluster < .05): (1) increases followed by decreases, (2) monotonic increases, and (3) monotonic decreases. However, network-based statistics (NBS) analysis of rsFC among these regions revealed that the strategy-based training group induced only monotonic increases in connectivity, relative to the knowledge-based training group (|Z| > 1.96, pNBS < 0.05). Complementing the rsFC results, the strategy-based training group yielded monotonic improvement in scores for the trail-making test (p < .05). Analyses of brain-behavior relationships revealed that improvement in trail-making scores were associated with training-induced changes in cortical thickness (pvertex < .05, pcluster < .05) and rsFC (pvertex < .05, pcluster < .005) within the strategy-based training group.

CONCLUSIONS

These findings suggest that training-induced brain plasticity continues through chronic phases of TBI and that brain connectivity and cortical thickness may serve as markers of plasticity.

Colocalization of GWAS and eQTL Signals Detects Target Genes

The vast majority of genome-wide association study (GWAS) risk loci fall in non-coding regions of the genome. One possible hypothesis is that these GWAS risk loci alter the individual's disease risk through their effect on gene expression in different tissues. In order to understand the mechanisms driving a GWAS risk locus, it is helpful to determine which gene is affected in specific tissue types. For example, the relevant gene and tissue could play a role in the disease mechanism if the same variant responsible for a GWAS locus also affects gene expression. Identifying whether or not the same variant is causal in both GWASs and expression quantitative trail locus (eQTL) studies is challenging because of the uncertainty induced by linkage disequilibrium and the fact that some loci harbor multiple causal variants. However, current methods that address this problem assume that each locus contains a single causal variant. In this paper, we present eCAVIAR, a probabilistic method that has several key advantages over existing methods. First, our method can account for more than one causal variant in any given locus. Second, it can leverage summary statistics without accessing the individual genotype data. We use both simulated and real datasets to demonstrate the utility of our method. Using publicly available eQTL data on 45 different tissues, we demonstrate that eCAVIAR can prioritize likely relevant tissues and target genes for a set of glucose- and insulin-related trait loci.

Sex-dichotomous effects of NOS1AP promoter DNA methylation on intracranial aneurysm and brain arteriovenous malformation

The goal of this study was to investigate the contribution of NOS1AP-promoter DNA methylation to the risk of intracranial aneurysm (IA) and brain arteriovenous malformation (BAVM) in a Han Chinese population. A total of 48 patients with IAs, 22 patients with BAVMs, and 26 control individuals were enrolled in the study. DNA methylation was tested using bisulfite pyrosequencing technology. We detected significantly higher DNA methylation levels in BAVM patients than in IA patients based on the multiple testing correction (CpG4-5 methylation: 5.86±1.04% vs. 4.37±2.64%, P=0.006). In women, CpG4-5 methylation levels were much lower in IA patients (3.64±1.97%) than in BAVM patients (6.11±1.20%, P<0.0001). However, in men, CpG1-3 methylation levels were much higher in the controls (6.92±0.78%) than in BAVM patients (5.99±0.70%, P=0.008). Additionally, there was a gender-based difference in CpG1 methylation within the controls (men vs. women: 5.75±0.50% vs. 4.99±0.53%, P=0.003) and BAVM patients (men vs. women: 4.70±0.74% vs. 5.50±0.87%, P=0.026). A subgroup analysis revealed significantly higher CpG3 methylation in patients who smoked than in those who did not (P=0.041). Our results suggested that gender modulated the interaction between NOS1AP promoter DNA methylation in IA and BAVM patients. Our results also confirmed that regular tobacco smoking was associated with increased NOS1AP methylation in humans. Additional studies with larger sample sizes are required to replicate and extend these findings.