Biology subjects

Evans, L. M.

Publications and source records attributed to Evans, L. M..

11 recordsLinked to original sources

bioRxiv2025

Differential methylation clock ages across buffy coat (BC), peripheral blood mononuclear cells (PBMC), and saliva in individuals approaching midlife

Epigenetic aging prior to midlife is gaining interest as an intervenable period to address health and cognitive aging. Epigenetic changes may index DNA methylation aging rates, but methylation profiles may not be substitutable across tissues. We compared DNA methylation clocks and age acceleration in saliva, buffy coat (BC), and peripheral blood mononuclear cells (PBMC) collected in 91 individuals (7 unpaired, 20 siblings, 64 twins; 18 monozygotic (MZ), 14 dizygotic (DZ) pairs) from the Colorado Adoption/Twin Study of Lifespan behavioral development and cognitive aging (CATSLife1; Mean age=30.90 years [range=28.07-41.13]; 50.5% female). Across 15 DNA methylation clocks, chronological age and DNA methylation ages were moderately associated (mean Spearman correlations: r=0.37, Saliva; r=0.41, BC; r=0.38, PBMC). In mixed-effects models, saliva showed higher DNA methylation ages (B=3.83-16.46 years vs BC, p<0.001), whereas PBMC and BC were comparable (B=-0.06-0.39 years vs BC, p>0.447). The exception was the next-generation clock DunedinPace showing comparability (p=0.486). Similar patterns were observed for age acceleration estimates. Altogether, MZ pairs (meta-analytic r=0.49, 95%CI=0.32,0.66) and DZ pairs (meta-analytic r=0.38, 95%CI=0.25,0.52) were moderately correlated (Spearman), but MZ pairs showed heterogeneity across tissues (p<0.020): saliva was lower (mean r=0.33, SD=0.25) than BC (mean r=0.64, SD=0.10) and PBMC (mean r=0.49, SD=0.18). Next-generation PCGrimAge and DunedinPace clocks showed consistent zygosity correlations across tissues, while multi-tissue clocks (e.g., ZhangQ) showed comparable MZ-DZ correlations. While saliva-based DNA methylation is not a direct substitute for blood-based DNA methylation, BC and PBMC show comparability; nevertheless, all tissue types may be appropriate for DNA methylation aging studies when compared within tissues. Key Policy HighlightsO_LISaliva-based methylation is not a direct substitute for blood-based methylation. C_LIO_LISaliva-based DNA methylation clocks demonstrated relatively older methylation ages and faster age accelerations relative to blood-based DNA methylation clocks. C_LIO_LIBlood-based DNA methylation clocks were comparable across buffy coat and peripheral blood mononuclear cell tissues. C_LIO_LITwin similarity, particularly among identical twins, was higher for blood-based DNA methylation clocks and newer generation DNA methylation clocks. C_LIO_LIThree clocks (one first-generation multi-tissue and two next-generation) showed consistency and/or comparability across tissues and showed moderate to strong correlations among identical and fraternal twins, supporting the importance of tool development. C_LI

genetics↗

bioRxiv2025

Polygenetic Determinants of Azole Resistance, Tolerance, and Heteroresistance in Candida albicans

Azole antifungals are widely used to treat Candida infections, yet therapeutic failures are common. In addition to resistance, fungal populations can exhibit tolerance and heteroresistance, subpopulation-driven drug responses that can contribute to treatment failure. Here, we performed a genome-wide association study (GWAS) on 557 genetically diverse C. albicans isolates to identify genetic loci associated with fluconazole susceptibility, tolerance, and heteroresistance. We uncovered a complex, polygenic architecture underlying all three traits, involving novel loci linked to stress responses, cell cycle, and genome integrity. Notably, canonical resistance genes were absent from our top associations, reflecting either their low frequency or lineage specificity. Functional validation of several candidate genes confirmed distinct genetic determinants for each drug response. Heritability estimates and conditional analyses revealed that susceptibility and heteroresistance are governed by partially overlapping but largely independent loci, with some genetic variants displaying opposing effects on different traits. This limited overlap suggests that each phenotype represents a distinct evolutionary strategy for drug evasion, which may not be simultaneously addressed by a single therapeutic approach. Our findings underscore the polygenic nature of adaptation to antifungal drugs and expand our understanding of drug response mechanisms in C. albicans. SIGNIFICANCEDespite advances in antifungal therapies, treatment failures in Candida albicans infections remain common and poorly understood. Standard clinical diagnostic tools rely on susceptibility testing to predict treatment outcomes, yet many treatment-refractory infections are caused by strains that appear susceptible in laboratory tests. This study provides the first genome-wide dissection of three distinct drug responses - susceptibility, tolerance, and heteroresistance - across a global population of C. albicans isolates. By identifying novel genetic contributors beyond canonical resistance genes, our findings shift the current paradigm toward a more nuanced, polygenic model of antifungal adaptation. These results underscore the importance of integrating tolerance and heteroresistance into clinical and research frameworks and point to new molecular pathways that could be leveraged to enhance antifungal strategies.

microbiology↗

bioRxiv2022

Poly-omic risk scores predict inflammatory bowel disease diagnosis

Inflammatory Bowel Disease (IBD) is characterized by complex etiology and a disrupted colonic ecosystem. We provide a framework for the analysis of multi-omic data, which we apply to study the gut ecosystem in IBD. Specifically, we train and validate models using data on the metagenome metatranscriptome, virome, and metabolome from the Human Microbiome Project 2 IBD Multi-omics Database, with 1,785 repeated samples from 131 individuals (103 cases, 27 controls). After splitting the participants into training and testing groups, we used mixed effects least absolute shrinkage and selection operator (LASSO) regression to select features for each -omic. These features, with demographic covariates, were used to generate separate single-omic prediction scores. All four single-omic scores were then combined into a final regression to assess the relative importance of the individual -omics and the predictive benefits when considered together. We identified several species, pathways, and metabolites known to be associated with IBD risk, and we explored the connections between datasets. Individually, metabolomics and viromics scores were more predictive than metagenomics or metatranscriptomics, and when all four scores were combined, we predicted disease diagnosis with a Nagelkerkes R2 of 0.46 and an AUC of 0.80 [95% CI: 0.63, 0.98]. Our work suggests that some single-omic models for complex traits are more predictive than others, that incorporating multiple -omics datasets may improve prediction, and that each -omic data type provides a combination of unique and redundant information. This modeling framework can be extended to other complex traits and multi-omic datasets. ImportanceComplex traits are characterized by many biological and environmental factors, such that multi-omics datasets are well-positioned to help us understand their underlying etiologies. We applied a prediction framework across multiple -omics (metagenomics, metatranscriptomics, metabolomics, and viromics) from the gut ecosystem to predict inflammatory bowel disease (IBD) diagnosis. The predicted scores from our models highlighted key features and allowed us to compare the relative utility of each -omic dataset in single-omic versus multi-omics models. Our results emphasized the importance of metabolomics and viromics over metagenomics and metatranscriptomics for predicting IBD status. The greater predictive capability of metabolomics and viromics is likely because these -omics serve as markers of lifestyle factors such as diet. This study provides a modeling framework for multi-omic data, and our results show the utility of combining multiple -omic data types to disentangle complex disease etiologies and biological signatures.

bioinformatics↗

bioRxiv2022

Transcriptome-Wide Gene-Gene Interaction Association Study Elucidates Pathways and Functional Enrichment of Complex Traits

It remains unknown to what extent gene-gene interactions contribute to complex traits. Here, we introduce a new approach using predicted gene expression to perform exhaustive transcriptome-wide interaction studies (TWISs) for multiple traits across all pairs of genes expressed in several tissue types. Using imputed transcriptomes, we simultaneously reduce the computational challenge and improve interpretability and statistical power. We discover and replicate several interaction associations, and find several hub genes with numerous interactions. We also demonstrate that TWIS can identify novel associated genes because genes with many or strong interactions have smaller single-locus model effect sizes. Finally, we develop a method to test gene set enrichment of TWIS associations (E-TWIS), finding numerous pathways and networks enriched in interaction associations. Epistasis is likely widespread, and our procedure represents a tractable framework for beginning to explore gene interactions and identify novel genomic targets.

genetics↗

bioRxiv2022

Testing Human Anxiety Associations of Genes Previously Implicated by Mouse Anxiety Models

Anxiety disorders are common and can be debilitating, with effective treatments remaining hampered by an incomplete understanding of the underlying genetic etiology. Improvements have been made in understanding the genetic influences on mouse behavioral models of anxiety, yet it is unclear the extent to which genes identified in these experimental systems contribute to genetic variation in human anxiety phenotypes. Leveraging new and existing large-scale human genome-wide association studies, we tested whether sets of genes previously identified in mouse anxiety-like behavior studies contribute to a range of human anxiety disorders. When tested as individual genes, thirteen mouse-identified genes were associated with human anxiety phenotypes, suggesting an overlap of individual genes contributing to both mouse models of anxiety-like behaviors and human anxiety traits. When genes were tested as sets, we did identify fourteen significant associations between mouse gene sets and human anxiety, but the majority of gene sets showed no significant association with human anxiety phenotypes. These few significant associations indicate a need to identify and develop more translatable mouse models by identifying sets of genes that match between model systems and specific human phenotypes of interest. We suggest that continuing to develop improved behavioral paradigms and finer-scale experimental data, for instance from individual neuronal subtypes or cell-type-specific expression data, is likely to improve our understanding of the genetic etiology and underlying functional changes in anxiety disorders.

genetics↗

bioRxiv2021

Within-sibship GWAS improve estimates of direct genetic effects

Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.

genetics↗

bioRxiv2020

Sexual dimorphism and sex ratio bias in the dioecious willow Salix purpurea L.

PremiseSexual dimorphism in dioecious plant species is often not obvious or is absent. Dioecious species populations also often exhibit deviations from expected sex ratios. Previous studies on members of the Salicaceae family have shown strong, partial, and no sexual dimorphism. Some studies have shown sex-biased ratios in several Salix spp., however, S. purpurea has never been examined for evidence of sexual dimorphism or for the presence of sex-ratio bias, and therefore a comprehensive phenotypic study is needed to fill this knowledge gap. MethodsThis study examined a suite of morphological, phenological, physiological and wood composition traits from multi-environment and multi-year replicated field trials in a diversity panel of unrelated S. purpurea accessions and in full-sib F1 and F2 families produced through controlled cross pollinations to test for sexual dimorphism and sex ratio bias. Key ResultsSignificant evidence of sexual dimorphism was found in vegetative traits with greater means for many traits in male genotypes compared to females across three populations of S. purpurea, measured across multiple years that were highly predictive of biomass yield. Male plants exhibited greater nitrogen accumulation under fertilizer amendment as measured by SPAD in the diversity panel, and males showed greater susceptibility to fungal infection by Melampsora spp in the F2 family. There were also consistent female-biased sex ratios in both the F1 and F2 families. ConclusionsThese results provide the first evidence of sexual dimorphism in S. purpurea and also confirm the prevalence of female-biased sex ratios previously found in other Salix species.

plant biology↗

bioRxiv2019

The role of a priori-identified addiction and smoking gene sets in smoking behaviors.

IntroductionSmoking is a leading cause of death, and genetic variation contributes to smoking behaviors. Identifying genes and sets of genes that contribute to risk for addiction is necessary to prioritize targets for functional characterization and for personalized medicine.\n\nMethodsWe performed a gene set-based association and heritable enrichment study of two addiction-related gene sets, those on the Smokescreen Genotyping Array and the nicotinic acetylcholine receptors, using the largest available GWAS summary statistics. We assessed smoking initiation, cigarettes per day, smoking cessation, and age of smoking initiation.\n\nResultsIndividual genes within each gene set were significantly associated with smoking behaviors. Both sets of genes were significantly associated with cigarettes per day, smoking initiation, and smoking cessation. Age of initiation was only associated with the Smokescreen gene set. While both sets of genes were enriched for trait heritability, each accounts for only a small proportion of the SNP-based heritability (2-12%).\n\nConclusionsThese two gene sets are associated with smoking behaviors, but collectively account for a limited amount of the genetic and phenotypic variation of these complex traits, consistent with high polygenicity.\n\nImplicationsWe evaluated evidence for association and heritable contribution of expert-curated and bioinformatically identified sets of genes related to smoking. Although they impact smoking behaviors, these specifically targeted genes do not account for much of the heritability in smoking and will be of limited use for predictive purposes. Advanced genome-wide approaches and integration of other omics data will be needed to fully account for the genetic variation in smoking phenotypes.

genetics↗

bioRxiv2019

GWAS of Over 427,000 Individuals Establishes GABAergic and Synaptic Molecular Pathways as Key for Cognitive Executive Functions

Deficits in executive functions (EFs), cognitive processes that control goal-directed behaviors, are associated with psychopathology and neurological disorders. Little is known about the molecular bases of EF individual differences; existing EF genome-wide association studies (GWAS) used small sample sizes and/or focused on individual tasks that are imprecise measures of EF. We conducted a GWAS of a Common EF (cEF) factor based on multiple tasks in the UK Biobank (N=427,037 European-descent individuals), finding 129 independent genome-wide significant lead variants in 112 distinct loci. cEF was associated with fast synaptic transmission processes (synaptic, potassium channel, and GABA pathways) in gene-based analyses. cEF was genetically correlated with measures of intelligence (IQ) and cognitive processing speed, but cEF and IQ showed differential genetic associations with psychiatric disorders and educational attainment. Results suggest that cEF is a genetically distinct cognitive construct that is particularly relevant to understanding the genetic variance in psychiatric disorders.

neuroscience↗

bioRxiv2018

Relationships between estimated autozygosity and complex traits in the UK Biobank

Inbreeding increases the risk of certain Mendelian disorders in humans but may also reduce fitness through its effects on complex traits and diseases. Such inbreeding depression is thought to occur due to increased homozygosity at causal variants that are recessive with respect to fitness. Until recently it has been difficult to amass large enough sample sizes to investigate the effects of inbreeding depression on complex traits using genome-wide single nucleotide polymorphism (SNP) data in population-based samples. Further, it is difficult to infer causation in analyses that relate degree of inbreeding to complex traits because confounding variables (e.g., education) may influence both the likelihood for parents to outbreed and offspring trait values. The present study used runs of homozygosity in genome-wide SNP data in up to 400,000 individuals in the UK Biobank to estimate the proportion of the autosome that exists in autozygous tracts--stretches of the genome which are identical due to a shared common ancestor. After multiple testing corrections and controlling for possible sociodemographic confounders, we found significant relationships in the predicted direction between estimated autozygosity and three of the 26 traits we investigated: age at first sexual intercourse, fluid intelligence, and forced expiratory volume in 1 second. Our findings for fluid intelligence and forced expiratory volume corroborate those of several published studies while the finding for age at first sexual intercourse was novel. These results may suggest that these traits have been associated with Darwinian fitness over evolutionary time, although there are other possible explanations for these associations that cannot be eliminated. Some of the autozygosity-trait relationships were attenuated after controlling for background sociodemographic characteristics, suggesting that care needs to be taken in the design and interpretation of ROH studies in order to glean reliable information about the genetic architecture and evolutionary history of complex traits.\n\nAuthor SummaryInbreeding is well known to increase the risk of rare, monogenic diseases, and there has been some evidence that it also affects complex traits, such as cognition and educational attainment. However, difficulties can arise when inferring causation in these types of analyses because of the potential for confounding variables (e.g., socioeconomic status) to bias the observed relationships between distant inbreeding and complex traits. In this investigation, we used single-nucleotide polymorphism data in a very large (N > 400,000) sample of seemingly outbred individuals to quantify the degree to which distant inbreeding is associated with 26 complex traits. We found robust evidence that distant inbreeding is inversely associated with fluid intelligence and a measure of lung function, and is positively associated with age at first sex, while other trait associations with inbreeding were attenuated after controlling for background sociodemographic characteristics. Our findings are consistent with evolutionary predictions that fluid intelligence, lung function, and age at first sex have been under selection pressures over time; however, they also suggest that confounding variables must be accounted for in order to reliably interpret results from these types of analyses.

genetics↗

bioRxiv2017

Testing the moderation of quantitative gene by environment interactions in unrelated individuals

The environment can moderate the effect of genes - a phenomenon called gene-environment (GxE) interaction. There are two broad types of GxE modeled in human behavior - qualitative GxE, where the effects of individual genetic variants differ depending on some environmental moderator, and quantitative GxE, where the additive genetic variance changes as a function of an environmental moderator. Tests of both qualitative and quantitative GxE have traditionally relied on comparing the covariances between twins and close relatives, but recently there has been interest in testing such models on unrelated individuals measured on genomewide data. However, to date, there has been no ability to test quantitative GxE effects in unrelated individuals using genomewide data because standard software cannot solve nonlinear constraints. Here, we introduce a maximum likelihood approach with parallel constrained optimization to fit such models. We use simulation to estimate the accuracy, power, and type I error rates of our method and to gauge its computational performance, and then apply this method to IQ data measured on 40,172 individuals with whole-genome SNP data from the UK Biobank. We found that the additive genetic variation of IQ tagged by SNPs increases as socioeconomic status (SES) decreases, opposite the direction found by several twin studies conducted in the U.S. on adolescents, but consistent with several studies from Europe and Australia on adults.

bioinformatics↗