Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix

Effect of serotonin receptor gene variants on substance use disorders

BACKGROUND

Substance use disorders are multifaceted conditions influenced by both genetic and environmental factors. Serotonergic pathways are known to be involved in substance use disorder susceptibility, with genetic markers within serotonin receptor genes identified as potential risk factors.

METHODS

To further explore this relationship, we conducted a study to investigate the association between several polymorphisms in five serotonin receptor genes (HTR1B, HTR2A/B, HTR3A/B) and substance use disorders (SUD) in Jordanian males by sequencing genotypes in 496 SUD patients and 496 healthy controls.

RESULTS

Our findings revealed an allelic association between rs9567735 in the HTR2A gene and rs17586428 in the HTR2B gene with SUD. Haplotype analysis also showed that one haplotype of the HTR2A gene and four haplotypes of the five included genes were significantly associated with SUD risk. Moreover, we found that motives for substance use were correlated with single nucleotide polymorphisms SNPs rs1923882 and rs1150226, with the latter SNP also being associated with smoking.

CONCLUSION

These findings suggest that genetic variants of human 5-HT receptor genes may affect individual susceptibility to SUD in Jordan. However, further studies with larger sample sizes and additional variants in the same or different genes must confirm these findings.

Multi-environment GWAS uncovers markers associated to biotic stress response and genotype-by-environment interactions in stone fruit trees

While breeding for improved immunity is essential to achieve sustainable fruit production, it also requires to account for genotype-by-environment interactions (G × E), which still represent a major challenge. To tackle this issue, we conducted a comprehensive study to identify genetic markers with main and environment-specific effects on pest and disease response in peach (Prunus persica) and apricot (Prunus armeniaca). Leveraging multienvironment trials (MET), we assessed the genetic architecture of resistance and tolerance to seven major pests and diseases through visual scoring of symptoms in naturally infected core collections, repeated within and between years and sites. We applied a series of genome-wide association models (GWAS) to both maximum of symptom severity and kinetic disease progression. These analyses lead to the identification of environment-shared quantitative trait loci (QTLs), environment-specific QTLs, and interactive QTLs with antagonist or differential effects across environments. We mapped 60 high-confidence QTLs encompassing a total of 87 candidate genes involved in both basal and host-specific responses, mostly consisting of the Leucine-Rich Repeat Containing Receptors (LRR-CRs) gene family. The most promising disease resistance candidate genes were found for peach leaf curl on LG4 and for apricot and peach rust on LG2 and LG4. These findings underscore the critical role of G × E in shaping the phenotypic response to biotic pressure, especially for blossom blight. Last, models including dominance effects revealed 123 specific QTLs, emphasizing the significance of non-additive genetic effects, therefore warranting further investigation. These insights will support the development of marker-assisted selection to improve the immunity of Prunus varieties in diverse environmental conditions.

Evaluation of plasma alpha-1-antichymotrypsin as a marker for pulmonary Kaposi sarcoma

Individuals with AIDS and Kaposi sarcoma (AIDS-KS) with pulmonary involvement have high-risk of poor outcomes but diagnosis of pulmonary KS in low-resource settings is difficult. We aimed to discover plasma proteins that distinguish individuals with pulmonary KS from those without pulmonary involvement. SomaScan proteomics screen measured 7288 plasma proteins in 22 cases and 17 controls selected from 181 participants with HIV-1 and cutaneous KS who underwent bronchoscopy. Cases had KS in the lower respiratory tract by bronchoscopy. Controls had no KS lesions detected by bronchoscopy. Results of the proteomics screen were confirmed by ELISA measurement of plasma alpha-1-antichymotrypsin (SERPINA3) in 18 cases and 13 controls and in an additional 162 individuals with AIDS-KS who were not included in the case-control analysis. Proteomics identified 12 plasma proteins with differential levels in controls and cases. Plasma alpha-1-antichymotrypsin (SERPINA3) complex was consistently higher in cases compared to controls in the proteomics assay. Measurement of plasma alpha-1-antichymotrypsin by ELISA confirmed higher levels in cases (median 399.4, IQR 95.77-766.4 μg/ml) versus controls (median 39.98, IQR 31.2-170.2 μg/ml; p = .001). Plasma alpha-1-antichymotrypsin correlated with the estimated burden of pulmonary KS in the respiratory tract (r = 0.439; p = .0002) and 234 μg/ml had 51% sensitivity and 94% specificity for detection of pulmonary KS by bronchoscopy. Measurement of plasma alpha-1-antichymotrypsin has potential for identifying persons with pulmonary AIDS-KS and estimating the burden of KS in the lower respiratory tract.

Preschool musicality is associated with school-age communication abilities through genes related to rhythmicity

Early-life abilities involved in perceiving, producing and engaging with music (musicality) may shape later (social) communication and language abilities. Here, we investigate phenotypic and genetic relationships linking musicality and communication abilities by studying information from preschool and school-aged children of the Avon Longitudinal Study of Parents and Children (N = 4169-6737 per measure, age 0.5-17 years). Using structural models, we identified relationships between latent musicality and speech- and cognition-related variables (r > 0.30). Consistently, polygenic scores for rhythmicity in adulthood (PGSrhythmicity) showed associations with preschool and school-age musicality (incremental-Nagelkerke-R2 = 0.006-0.011, p < 0.0025), as well as school-age communication and cognition-related measures (incremental-R2 = 0.04-1%, p < 0.0025). Studying the directionality of genetic effects using a mediation framework, we found evidence supporting a developmental pathway linking preschool musicality to school-age speech-/syntax-related abilities, as captured by PGSrhythmicity (shared effect: β = 0.0051(SE = 0.0021), p = 0.015). Associations were found conditional on general cognition and genetically unrelated to educational attainment, suggesting robust developmental links between early musicality and later speech-related communication performance.

Neuroimaging Predictors of Cognitive Resilience against Alzheimer's Disease Pathology

OBJECTIVE

Some individuals demonstrate greater cognitive resilience-the ability to maintain cognitive performance despite adverse brain-related changes-through as yet unknown mechanisms. We examined whether cortical thickness in several brain regions confers resilience against cognitive decline in amyloid-positive adults by moderating the effects of thinner cortex in Alzheimer's disease (AD)-related brain regions and of higher levels of tau.

METHODS

Amyloid-positive participants from the Alzheimer's Disease Neuroimaging Initiative with relevant imaging data were included (n = 160, observations = 473). Risk factors included an AD brain signature and cerebrospinal fluid phosphorylated tau. Cognitive measures were episodic memory and executive function composites. Mixed effects models tested whether region-specific cortical thickness moderated relationships between markers of AD risk and memory or executive function.

RESULTS

Cross-sectionally, thicker cortex in 8 regions minimized the negative impact of thinner cortex/smaller volume in AD signature regions on executive function. Longitudinally, higher baseline thickness in a composite of these 8 regions predicted less memory decline (p = 0.007) and weakened negative effects of phosphorylated tau on memory decline (p = 0.014), independent of baseline cognition and risk markers.

INTERPRETATION

We identified 8 cortical regions that appear to confer cognitive resilience cross-sectionally and longitudinally in the face of established indicators of AD pathology. Brain regions fostering executive function may enable compensation in later memory performance and confer cognitive resilience against effects of phosphorylated tau and AD-related cortical changes. These "resilience" regions suggest the value of focusing on brain regions beyond only those determined to be AD-related and may partially explain variability in AD-related cognitive trajectories. ANN NEUROL 2025;97:1038-1050.

Pleiotropic and sex-specific genetic mechanisms of circulating metabolic markers

Metabolites in plasma form biosignatures of a range of common complex human diseases. Discovering variants with pleiotropic effects across metabolites can reveal underlying biological mechanisms. We therefore performed uni- and multivariate genome-wide association studies (GWAS) on 249 circulating metabolic markers across 328,006 UK Biobank and Estonian Biobank participants. We investigated rare variation through whole exome sequencing gene burden tests, analysed the role of body mass index through Mendelian randomization, and performed genome-wide interaction analyses with sex. We discovered 15,585 loci summed over the univariate GWAS, with high pleiotropy across markers, linked to a wide range of disorders. Findings from common and rare variant gene tests converged on lipid homeostasis pathways. 31 loci interacted with sex, mapped to genes involved in cholesterol processing. The findings offer insights into the genetic architecture of circulating metabolites, revealing pleiotropic loci, highlighting the role of rare variation, and uncovering sex-specific molecular mechanisms of lipid metabolism.

Leaf Na+ effects and multi-trait GWAS point to salt exclusion as the key mechanism for reproductive stage salinity tolerance in rice

BACKGROUND AND AIMS

Since salinity stress may occur across stages of rice (Oryza sativa) crop growth, understanding the effects of salinity at the reproductive stage is important, although it has been much less studied than at the seedling stage.

METHODS

Lines from the Rice Diversity Panel 1 (RDP1) and the 3000 Rice Genomes (3KRG) were used to screen morphological and physiological traits, map loci controlling salinity tolerance through genome-wide association studies (GWAS), and identify favourable haplotypes associated with reproductive stage salinity tolerance.

KEY RESULTS

Salt exclusion was identified as the key tolerance mechanism in this study, based on reduced panicle length as flag leaf Na+ increased and a lack of effect of trimming the leaves on genotypic rankings in the salinity treatment. Since larger biomass showed a negative effect on the number of filled grains in multiple experiments, future studies should investigate the effect of whole-plant transpiration levels on salt uptake. In addition to genome-wide significant peaks identified in the single-trait GWAS analyses, six loci showed colocations for multiple traits across experiments. Among these colocating loci, three candidate loci that exhibited favourable haplotypes were also characterized to be involved in co-expression networks, among which apoplast and cell wall functions had been annotated, further highlighting the role of salt exclusion.

CONCLUSION

The loci identified here could be considered as potential sources for improving reproductive stage salinity tolerance in rice.

Human genetic variation determines 24-hour rhythmic gene expression and disease risk

24-hour biological rhythms are essential to maintain physiological homeostasis. Disruption of these rhythms increases the risks of multiple diseases. Biological rhythms are known to have a genetic basis formed by core clock genes, but how individual genetic variation shapes the oscillating transcriptome and contributes to human chronophysiology and disease risk is largely unknown. Here, we mapped interactions between temporal gene expression and genotype to identify quantitative trait loci (QTLs) contributing to rhythmic gene expression. These newly identified QTLs were termed as rhythmic QTLs (rhyQTLs), which determine previously unappreciated rhythmic genes in human subpopulations with specific genotypes. Functionally, rhyQTLs and their associated rhythmic genes contribute extensively to essential chronophysiological processes, including bile acid and lipid metabolism. The identification of rhyQTLs sheds light on the genetic mechanisms of gene rhythmicity, offers mechanistic insights into variations in human disease risk, and enables precision chronotherapeutic approaches for patients.

Multi-Omic Associations of Epigenetic Age Acceleration Are Heterogeneously Shaped by Genetic and Environmental Influences

Connections between the multi-ome and epigenetic age acceleration (EAA), and especially whether these are influenced by genetic or environmental factors, remain underexplored. We therefore quantified associations between the multi-ome comprising four layers-the proteome, metabolome, external exposome (here, sociodemographic factors), and specific exposome (here, lifestyle)-with six different EAA estimates. Two twin cohorts were used in a discovery-replication scheme, comprising, respectively, young (N = 642; mean age = 22.3) and older (N = 354; mean age = 62.3) twins. Within-pair twin designs were used to assess genetic and environmental effects on associations. We identified 40 multi-omic factors, of which 28 were proteins, associated with EAA in the young twins while adjusting for sex, smoking, and body mass index. Within-pair analyses revealed that genetic confounding influenced these associations heterogeneously, with six multi-omic factors -matrix metalloproteinase 9, complement component C6, histidine, glycoprotein acetyls, lactate, and neighborhood percentage of nonagenarians- remaining significantly associated with EAA, independent of genetic effects. Replication analyses showed that some associations assessed in young twins were consistent in older twins. Our study highlights the differential influence of genetic effects on the associations between the multi-ome and EAA and shows that some, but not all, of the associations persist into adulthood.

metacp: a versatile software package for combining dependent or independent p-values

BACKGROUND

We present metacp an open-source software package which implements an abundance of statistical methods for the combination of both independent p-values, with methods such as Fisher's, Stouffer's and Edgington's, and dependent p-values, with methods such as Brown's method and the Cauchy Combination Test.

RESULTS

The tool is available in Python and STATA, it is very fast, and it is easy to use, requiring only minimal input. It offers a useful resource for combining both independent and dependent p-values, responding to diverse analytical needs for practitioners performing meta-analyses and bioinformaticians developing tools for a variety of applications. Depending on the input data it can be used for gene-based testing, for analysis of multiple traits in GWAS, or for combining diverse multi-omics data such as those of a TWAS, a colocalization or an RNA-seq study.

CONCLUSIONS

Compared to other similar packages (like poolr or metap), metacp implements the largest collection of statistical methods for this problem, offering users the flexibility to choose from a wide variety of approaches. Being available both as a standalone Python tool and as a STATA command, metacp is accessible to a broad and diverse audience, including practitioners conducting meta-analyses across various fields and bioinformaticians developing new tools where p-value combination is a crucial component.

Identification of novel candidate genes for regulating oil composition in soybean seeds under environmental stresses

Introduction

A key objective of soybean breeding programs is to enhance nutritional quality for human and animal consumption, with improved fatty acid (FA) composition for health benefits, and expand soybean use for industrial applications.

Methods

We conducted a metabolite genome-wide association study (mGWAS) to identify genomic regions associated with changes in FA composition and FA ratios in soybean seeds influenced by environmental factors. This mGWAS utilized 218 soybean plant introductions (PIs) grown in two field locations in Virginia over two years.

Results

The mGWAS revealed that 20 SNPs were significantly associated with 21 FA ratios, while additional suggestive SNPs were found for 36 FA ratios, highlighting potential quantitative trait loci linked to FA composition.

Discussion

Many of these SNPs are located near or within the genes related to phytohormone-mediated biotic and abiotic stress responses, suggesting the involvement of environmental factors in modulating FA composition in soybean seeds. Our findings provide novel insights into the genetic and environmental factors influencing FA composition in oilseeds. This research also lays the foundation for developing stable markers to develop soybean cultivars with tailored FA profiles for different practical applications under variable growth conditions.

Periodic dietary restriction of animal products induces metabolic reprogramming in humans with effects on cardiometabolic health

Dietary interventions constitute powerful approaches for disease prevention and treatment. However, the molecular mechanisms through which diet affects health remain underexplored in humans. Here, we compare plasma metabolomic and proteomic profiles between dietary states for a unique group of individuals who alternate between omnivory and restriction of animal products for religious reasons. We find that short-term restriction drives reductions in levels of lipid classes and of branched-chain amino acids, not detected in a control group of individuals, and results in metabolic profiles associated with decreased risk for all-cause mortality. We show that 23% of proteins whose levels are affected by dietary restriction are druggable targets and reveal that pro-longevity hormone FGF21 and seven additional proteins (FOLR2, SUMF2, HAVCR1, PLA2G1B, OXT, SPP1, HPGDS) display the greatest magnitude of change. Through Mendelian randomization we demonstrate potentially causal effects of FGF21 and HAVCR1 on risk for type 2 diabetes, of HPGDS on BMI, and of OXT on risk for lacunar stroke. Collectively, we find that restriction-associated reprogramming improves metabolic health and emphasise high-value targets for pharmacological intervention.

High-Throughput Site-Specific N-Glycosylation Profiling of Human Fibrinogen in Atrial Fibrillation

Fibrinogen is a major plasma glycoprotein involved in blood coagulation and inflammatory responses. Alterations in its glycosylation have been implicated in various pathological conditions; yet, its site-specific N-glycosylation profile remains largely unexplored in a clinical context. Here, we present a high-throughput LC-MS workflow for site-specific analysis of fibrinogen N-glycosylation using a cost-effective ethanol precipitation enrichment method. The method demonstrated good intra- and interplate repeatability (CV: 5% and 12%, respectively) and was validated through the first assessment of intraindividual temporal stability in healthy individuals, revealing consistent glycosylation patterns within individuals. Application to 181 atrial fibrillation (AF) patients and 52 healthy controls identified three gamma chain glycoforms significantly associated with AF. Most notably, increased levels of the asialylated N4H5, known to enhance fibrin bundle thickness and promote clot formation, suggest a potential mechanism linking glycosylation changes to the prothrombotic state in AF. Furthermore, fibrinogen sialylation showed strong associations with cardiovascular risk factors, including triglycerides, BMI, and glucose levels. Longitudinal analysis of 108 AF patients six months postcatheter ablation showed stability in the AF-associated glycan profile. Our findings establish fibrinogen glycosylation as a potential biomarker for cardiovascular conditions and demonstrate the utility of site-specific glycosylation analysis for clinical applications.

Mutations in the bone morphogenetic protein signaling pathway sensitize zebrafish and humans to ethanol-induced jaw malformations

Fetal alcohol spectrum disorders (FASD) describe ethanol-induced developmental defects including craniofacial malformations. While ethanol-sensitive genetic mutations contribute to facial malformations, the impacted cellular mechanisms remain unknown. Signaling via bone morphogenetic protein (Bmp) is a key regulatory step of epithelial morphogenesis driving facial development, providing a possible ethanol-sensitive mechanism. We found that zebrafish carrying mutants for Bmp signaling components are ethanol-sensitive and affect anterior pharyngeal endoderm shape and gene expression, indicating that ethanol-induced malformations of the anterior pharyngeal endoderm cause facial malformations. By integrating FASD patient data, we provide the first evidence that variants of the human Bmp receptor gene BMPR1B associate with ethanol-related differences in jaw volume. Our results show that ethanol exposure disrupts proper morphogenesis of, and tissue interactions between, facial epithelia that mirror overall viscerocranial shape changes and are predictive for Bmp-ethanol associations in human jaw development. Our data provide a mechanistic paradigm linking ethanol to disrupted epithelial cell behaviors that underlie facial defects in FASD.

Scalable eQTL mapping using single-nucleus RNA-sequencing of recombined gametes from a small number of individuals

Phenotypic differences between individuals of a species are often caused by differences in gene expression, which are in turn caused by genetic variation. Expression quantitative trait locus (eQTL) analysis is a methodology by which we can identify such causal variants. Scaling eQTL analysis is costly due to the expense of generating mapping populations, and the collection of matched transcriptomic and genomic information. We developed a rapid eQTL analysis approach using single-cell/nucleus RNA sequencing of gametes from a small number of heterozygous individuals. Patterns of inherited polymorphisms are used to infer the recombinant genomes of thousands of individual gametes and identify how different haplotypes correlate with variation in gene expression. Applied to Arabidopsis pollen nuclei, our approach uncovers both cis- and trans-eQTLs, ultimately mapping variation in a master regulator of sperm cell development that affects the expression of hundreds of genes. This establishes snRNA-sequencing as a powerful, cost-effective method for the mapping of meiotic recombination, addressing the scalability challenges of eQTL analysis and enabling eQTL mapping in specific cell-types.

Low to Moderate Prenatal Alcohol Exposure and Facial Shape of Children at Age 6 to 8 Years

Importance

In addition to confirmed prenatal alcohol exposure and severe neurodevelopmental deficits, three cardinal facial features are included in the diagnostic criteria for fetal alcohol spectrum disorder. It is not understood whether subtle facial characteristics occur in children without a diagnosis but who were exposed to a range of common pregnancy drinking patterns and, if so, whether these persist throughout childhood.

Objective

To determine whether subtle changes in facial shape with prenatal alcohol exposure found in 12-month-old children were evident at age 6 to 8 years using extended phenotyping methods and, if so, whether facial characteristics were similar to those seen in fetal alcohol spectrum disorder.

Design, Setting, and Participants

In a prospective cohort study in Melbourne, Victoria, Australia, commencing in July 2011 with follow-up through April 2021, pregnant women were recruited in the first trimester from low-risk, metropolitan, public maternity clinics over a period of 12 months. Three-dimensional craniofacial images from 549 children of European descent taken at age 12 months (n = 421 images) and 6 to 8 years (n = 363) were included. Data analysis was performed from May 2021 to October 2024.

Exposures

Predominantly low to moderate prenatal alcohol exposure in the first trimester or throughout pregnancy compared with controls without prenatal alcohol exposure.

Main Outcomes and Measures

Following hierarchical facial segmentation, phenotype descriptors were computed. Hypothesis testing was performed for 63 facial modules to analyze different facial parts independently using principal component analysis and response-based imputed predictor (RIP) scores. Comparison was made with a clinical discovery sample of facial images of children with a confirmed diagnosis of partial or full fetal alcohol syndrome.

Results

A total of 549 children took part in the 3-dimensional craniofacial image analysis, of whom 235 (42.8%) contributed an image at both time points. Time 1 included 421 children, comprising 336 children (159 [47.3%] female) with any prenatal alcohol exposure and 85 control children (45 [52.9%] female); time 2 included 363 children, comprising 260 children with any prenatal alcohol exposure (125 [48.1%] female; mean [SD] age, 6.9 [0.7] years) and 103 control children (53 [51.5%] female; mean [SD] age, 6.8 [0.7] years). At both time points, there was consistent evidence for an association between prenatal alcohol exposure and the shape of the eyes (eg, module 15: RIP partial Spearman ρ, 0.19 [95% CI, 0.10-0.29; P < .001] at 6-8 years) and nose (eg, module 5: RIP partial Spearman ρ, 0.19 [95% CI, 0.09-0.27; P < .001] at 6-8 years), whether exposure occurred only in trimester 1 or throughout pregnancy. Facial variations observed differed from those in the clinical discovery sample.

Conclusions and Relevance

Low to moderate prenatal alcohol exposure was associated with characteristic changes in the face, which persisted until at least 6 to 8 years of age. A linear association between alcohol exposure levels and facial shape was not supported.

Overcoming the "feast or famine" effect: improved interaction testing in genome-wide association studies

In genetic association analysis of complex traits, detection of interaction (either GxG or GxE) can help to elucidate the genetic architecture and biological mechanisms underlying the trait. Detection of interaction in a genome-wide interaction study (GWIS) can be methodologically challenging for various reasons, including a high burden of multiple comparisons when testing for epistasis between all possible pairs of a set of genomewide variants, as well as heteroscedasticity effects occurring in the presence of GxG or GxE interaction. In this paper, we address the problem of an even more striking phenomenon that we call the "feast or famine" effect that occurs when testing interaction in a genomewide context. We show that in any given GxE GWIS, the type 1 error of standard interaction tests performed genomewide can vary widely from the nominal level, where the actual type 1 error in any given GWIS varies as a predictable function of the observed trait and environmental values. Using standard methods, some GWISs will have systematically underinflated p-values ("feast"), and others will have systematically overinflated p-values ("famine"), which can lead to false detection of interaction, reduced power, inconsistent results across studies, and failure to replicate true signal. This startling phenomenon is specific to detection of interaction in a GWIS, and it may partly explain why such detection has often proved challenging and difficult to replicate. We show that the feast or famine effect occurs across a wide range of GxE analysis methods, including but not limited to (1) testing interaction in a linear or linear mixed model (LMM) using standard approaches such as t-tests/Wald tests, likelihood ratio tests, or score tests; (2) doing a combined interaction-association test in a linear model or LMM using standard approaches; (3) testing interaction with multiple environments or multiple SNPs, where these are modeled as random effects in a LMM using standard approaches; (4) performing tests of interaction in a GWIS where significance is assessed using permutation of the trait residuals. We show theoretically that the key cause of this phenomenon is which variables are conditioned on in the analysis. Using this insight, we have developed (i) a diagnostic ratio to detect which GWASs are subject to a strong "feast or famine" effect and (ii) the TINGA method to adjust the interaction test statistics to make their p-values approximately uniform under the null hypothesis. In simulations we show that TINGA both controls type 1 error and improves power. TINGA allows for covariates and population structure through use of a linear mixed model and accounts for heteroscedasticity. We apply TINGA to detection of epistasis in a study of flowering time in Arabidopsis thaliana.

Twin modelling reveals partly distinct genetic pathways to music enjoyment

Humans engage with music for various reasons that range from emotional regulation and relaxation to social bonding. While there are large inter-individual differences in how much humans enjoy music, little is known about the origins of those differences. Here, we disentangle the genetic factors underlying such variation. We collect data on several facets of music reward sensitivity, as measured by the Barcelona Music Reward Questionnaire, plus music perceptual abilities and general reward sensitivity from a large sample of Swedish twins (N = 9169; 2305 complete pairs). We estimate that genetic effects contribute up to 54% of the variability in music reward sensitivity, with 70% of these effects being independent of music perceptual abilities and general reward sensitivity. Furthermore, multivariate analyses show that genetic and environmental influences on the different facets of music reward sensitivity are partly distinct, uncovering distinct pathways to music enjoyment and different patterns of genetic associations with objectively assessed music perceptual abilities. These results paint a complex picture in which partially distinct sources of variation contribute to different aspects of musical enjoyment.

Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction

Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.

An Entropy-Based Approach to Model Selection with Application to Single-Cell Time-Stamped Snapshot Data

Recent single-cell experiments that measure copy numbers of over 40 proteins in thousands of individual cells at different time points [time-stamped snapshot (TSS) data] exhibit cell-to-cell variability. Because the same cells cannot be tracked over time, TSS data provide key information about the statistical time-evolution of protein abundances in single cells, information that could yield insights into the mechanisms influencing the biochemical signaling kinetics of a cell. However, when multiple candidate models (i.e., mechanistic models applied to initial protein abundances) can potentially explain the same TSS data, selecting the best model (i.e., model selection) is often challenging. For example, popular approaches like Kullback-Leibler divergence and Akaike's Information Criterion are often difficult to implement largely because mathematical expressions for the likelihoods of candidate models are typically not available. To perform model selection, we introduce an entropy-based approach that uses split-sample techniques to exploit the availability of large data sets and uses (1) existing generalized method of moments (GMM) software to estimate model parameters, and (2) standard kernel density estimators and a Gaussian copula to estimate candidate models. Using simulated data, we show that our approach can select the "ground truth" from a set of competing mechanistic models. Then, to assess the relative support for a candidate model, we compute model selection probabilities using a bootstrap procedure.

Determinants and impact of postoperative atrial fibrillation burden during 2.5 years of continuous rhythm monitoring after cardiac surgery: Results from the RACE V prospective cohort study

BACKGROUND

Early postoperative atrial fibrillation (POAF) is common after cardiac surgery and is associated with late-POAF recurrences. However, little is known about the burden of POAF and its potential impact on long-term outcomes after cardiac surgery, particularly on the risk for late-POAF recurrences.

OBJECTIVE

The purpose of this study was to establish the distribution of POAF burden and to determine the association between early-POAF burden and late-POAF recurrences during 2.5 years of continuous rhythm monitoring after cardiac surgery in patients with and without preoperative history of atrial fibrillation (AF).

METHODS

Patients undergoing cardiac surgery were prospectively enrolled and postoperatively continuously monitored with an implantable loop recorder for 2.5 years. All patients underwent extensive clinical assessment at baseline. During follow-up, all AF episodes were registered, and AF associated metrics, such as burden, were calculated for different time intervals. Early-POAF was defined as AF within first 90 postoperative days and late-POAF as AF after this interval.

RESULTS

A total of 98 consecutive patients were included. POAF burden during the early postoperative phase was significantly higher compared to the late postoperative phase (P <.001). The longest individual POAF episode was strongly associated with increased POAF burden after adjusting for age, sex, and AF history (standardized Beta: 0.91, P <.001). Also, early-POAF burden was associated with late-POAF (re)occurrence after adjusting for age, sex, AF history (adjusted hazard ratio 1.93, 95% confidence interval 1.42-2.62, P <.001).

CONCLUSION

POAF burden was significantly associated with the longest individual POAF episode duration. Additionally, greater early-POAF burden was associated with increased late-POAF incidence, highlighting its potential in estimating the risk for long-term POAF recurrences.

Investigating the Genetic Association of Selected Candidate Loci with Alopecia Areata Susceptibility in Jordanian Patients

Background and Objectives: Alopecia areata (AA) is a common cell-mediated autoimmune disease of the hair follicle that results in hair loss patches, affecting males and females of all ages and ethnicities. Although its etiology is not fully understood, AA is hypothesized to have a multifactorial basis with a strong genetic association. This study aims to replicate the genetic association of several risk loci in the Jordanian population for the first time. Materials and Methods: Genomic DNA samples of 152 patients with AA and 150 control individuals were extracted from EDTA blood tubes collected from dermatology clinics, in addition to the clinical data of participants. Genetic sequencing of the 21 targeted risk loci was carried out using the Sequenom MassARRAY® system (iPLEX GOLD), and the results were statistically analyzed using the Statistical Package for the Social Sciences. Results: The results compared the distribution of alleles and genotypes and the association between control individuals and AA patients. However, our results do not support a significant association of all of the 21 SNPs in our AA cohort (p > 0.05). Conclusions: Our data emphasize that AA has a varied genetic component between ethnic groups and suggest that other additional environmental and psychological triggers may be involved.

Genome wide association study reveals novel associations with face morphology

Genome-wide association studies (GWAS) on the Middle Eastern population, including the United Arab Emirates (UAE), have been relatively limited. The present study aims to investigate genotype-face morphology associations in the UAE population through Genome Wide Association Studies (GWAS). Phenotypic data (44 face measurements) from 172 Emiratis was obtained through three-dimensional (3D) scanning technology and an automatic face landmarking technique. GWAS analysis revealed associations of 19 genetic loci with six face features, 14 of which are novel. The GWAS analysis revealed 11 significant relationships between 44 face parameters and 242 SNPs, exceeding the GWAS significance threshold. These phenotypes were previously associated with body height, craniofacial defects, and facial characters. The most significant associations of these genetic variations were related to six main facial features which were facial convexity, left orbital protrusion, mandibular contour, nasolabial angle D, inferior facial angle B, and inferior facial angle A. To the best of our knowledge, this is the first GWAS study to investigate the association of SNP variations with face morphology in the Middle Eastern population.

Autism common variants associated with white matter alterations at birth: cross-sectional fixel-based analyses of 221 European term-born neonates from the developing human connectome project

Increasing lines of evidence suggest white matter (WM) structural changes associated with autism can be detected in the first year of life. Despite the condition having high heritability, the relationship between autism common genetic variants and WM changes during this period remains unclear. By employing advanced regional and whole-brain fixel-based analysis, the current study investigated the association between autism polygenic scores (PS) and WM microscopic fibre density and macrostructural morphology in 221 term-born infants of European ancestry from the developing Human Connectome Project. The results suggest greater tract mean fibre-bundle cross-section of the left superior corona radiata is associated with higher autism PS. Subsequent exploratory enrichment analysis revealed that the autism risk single nucleotide polymorphisms most associated with the imaging phenotype may have roles in neuronal cellular components. Together, these findings suggest a possible link between autism common variants and early WM development.

Genomic Insights into Blood Pressure Regulation: Exploring Ion Channel and Transporter Gene Variations in Jordanian Hypertensive Individuals

Background and Objectives: Hypertension (HTN) constitutes a significant global health burden, yet the specific genetic variant responsible for blood pressure regulation remains elusive. This study investigates the genetic basis of hypertension in the Jordanian population, focusing on gene variants related to ion channels and transporters, including KCNJ1, WNK1, NPPA, STK39, LUC7L2, NEDD4L, NPHS1, BDKRB2, and CACNA1C. Materials and Methods: This research involved 200 hypertensive patients and 224 healthy controls. Whole blood samples were collected from each participant, and genomic DNA was extracted. The genetic distribution of the polymorphisms was analyzed. The haplotype frequencies were investigated using the SNPStats web tool, and the genotype and allele frequencies of the studied variants were assessed using the χ2 test. Results: Sixteen single nucleotide polymorphisms (SNPs) from nine genes were evaluated. A significant association was observed between the rs880054 variant of the WNK1 gene and hypertension susceptibility, with the T allele elevating the risk of hypertension. This association remained important in the codominant model (p = 0.049) and the dominant model (p = 0.029). In addition, rs880054 was associated with clinical characteristics such as triglyceride levels and cerebrovascular accidents (p-value > 0.05). Conclusions: Our findings reveal a significant link between the rs880054 SNP and an increased hypertension risk, suggesting that variations in WNK1 may be crucial in regulating blood pressure. This study provides new insights into the genetic factors contributing to hypertension and highlights the potential of WNK1 as a target for future therapeutic interventions.

DisCo P-ad: Distance-Correlation-Based p-Value Adjustment Enhances Multiple Testing Corrections for Metabolomics

BACKGROUND

Due to scientific advancements in high-throughput data production technologies, omics studies, such as genomics and metabolomics, often give rise to numerous measurements per sample/subject containing several noisy variables that potentially cloud the true signals relevant to the desired study outcome(s). Therefore, correcting for multiple testing is critical while performing any statistical test of significance to minimize the chances of false or missed discoveries. Such correction practice is commonplace in genome-wide association studies (GWAS) but is also becoming increasingly relevant to metabolome-wide association studies (MWAS). However, many existing procedures may be too conservative or too lenient, only assume a linear association between the features, or have not been evaluated on metabolomics data.

METHODS

One such multiple testing correction strategy is to estimate the number of statistically independent tests, called the effective number of tests, based on the eigen-analysis of the correlation matrix between the features. This effective number is then used for a subsequent single-step adjustment to obtain the pointwise significance level. We propose a modification to the p-value adjustment based on a more general measure of association between two predictors, the distance correlation, with a specific focus on MWAS.

RESULTS

We assessed common GWAS p-value adjustment procedures and one tailored for MWAS, which rely on eigen-analysis of the Pearson's correlation matrix. Our study, including varying sample size-to-feature ratios, response types, and metabolite groupings, highlights the superior performance of the distance correlation.

CONCLUSION

We propose the distance-correlation-based p-value adjustment (DisCo P-ad) as a novel modification that can enhance existing eigen-analysis-based multiple testing correction procedures by increasing power or reducing false positives. While our focus is on metabolomics, DisCo P-ad can also readily be applied to other high-dimensional omics studies.

PITX2 expression and Neanderthal introgression in HS3ST3A1 contribute to variation in tooth dimensions in modern humans

Dental morphology varies greatly throughout evolution, including in the human lineage, but little is known about the biology of this variation. Here, we use multiomics analyses to examine the genetics of variation in tooth crown dimensions. In a human cohort with mixed continental ancestry, we detected genome-wide significant associations at 18 genome regions. One region includes EDAR, a gene known to impact dental features in East Asians. Furthermore, we find that EDAR variants increase the mesiodistal diameter of all teeth, following an anterior-posterior gradient of decreasing strength. Among the 17 novel-associated regions, we replicate 7/13 in an independent human cohort and find that 4/12 orthologous regions affect molar size in mice. Two association signals point to compelling candidate genes. One is ∼61 kb from PITX2, a major determinant of tooth development. Another overlaps HS3ST3A1, a paralogous neighbor of HS3ST3B1, a tooth enamel knot factor. We document the expression of Pitx2 and Hs3st3a1 in enamel knot and dental epithelial cells of developing mouse incisors. Furthermore, associated SNPs in PITX2 and HS3ST3A1 overlap enhancers active in these cells, suggesting a role for these SNPs in gene regulation during dental development. In addition, we document that Pitx2 and Hs3st3a1/Hs3st3b1 knockout mice show alterations in dental morphology. Finally, we find that associated SNPs in HS3ST3A1 are in a DNA tract introgressed from Neanderthals, consistent with an involvement of HS3ST3A1 in tooth size variation during human evolution.

Mitochondrial DNA abundance and circulating metabolomic profiling: Multivariable-adjusted and Mendelian randomization analyses in UK Biobank

BACKGROUND

Low leukocyte mitochondrial DNA (mtDNA) abundance has been associated with a higher risk of atherosclerotic cardiovascular disease, but through unclear mechanisms. We aimed to investigate whether low mtDNA abundance is associated with worse metabolomic profiling, as being potential intermediate phenotypes, using cross-sectional and genetic studies.

METHODS

Among 61,186 unrelated European participants from UK Biobank, we performed multivariable-adjusted linear regression analyses to examine the associations between mtDNA abundance and 168 NMR-based circulating metabolomic measures and nine metabolomic principal components (PCs) that collectively covered 91.5% of the total variation of individual metabolomic measures. Subsequently, we conducted Mendelian randomization (MR) to approximate the causal effects of mtDNA abundance on the individual metabolomic measures and their metabolomic PCs.

RESULTS

After correction for multiple testing, low mtDNA abundance was associated with 130 metabolomic measures, predominantly lower concentrations of some amino acids and higher concentrations of lipids, lipoproteins and fatty acids; moreover, mtDNA abundance was associated with seven out of the nine metabolomic PCs. Using MR, genetically-predicted low mtDNA abundance was associated with lower lactate (standardized beta and 95% confidence interval: -0.17; -0.26, -0.08), and higher acetate (0.15; 0.07,0.23), and unsaturation degree (0.14; 0.08,0.20). Similarly, genetically-predicted low mtDNA abundance was associated with lower metabolomic PC2 (related to lower concentrations of lipids and fatty acids), and higher metabolomic PC9 (related to lower concentrations of glycolysis-related metabolites).

CONCLUSION

Low mtDNA abundance is associated with metabolomic perturbations, particularly reflecting a pro-atherogenic metabolomic profile, which potentially could link low mtDNA abundance to higher atherosclerosis risk.

Brain morphology mediating the effects of common genetic risk variants on Alzheimer's disease

Background

Late-onset Alzheimer's disease (LOAD) has been associated with alterations in the morphology of multiple brain structures, and it is likely that disease mechanisms differ between brain regions. Coupling genetic determinants of LOAD with measures of brain morphology could localize and identify primary causal neurobiological pathways.

Objective

To determine causal pathways from genetic risk variants of LOAD via brain morphology to LOAD.

Methods

Mediation and Mendelian randomization (MR) analysis were performed using common genetic variation, T1 MRI and clinical data collected by UK Biobank and Alzheimer's Disease Neuroimaging Initiative.

Results

Thickness of the entorhinal cortex and the volumes of the hippocampus, amygdala and inferior lateral ventricle mediated the effect of APOE ε4 on LOAD. MR showed that a thinner entorhinal cortex, a smaller hippocampus and amygdala, and a larger volume of the inferior lateral ventricles, increased the risk of LOAD as well as vice versa.

Conclusions

Combining neuroimaging and genetic data can give insight into the causal neuropathological pathways of LOAD.

Ambulatory autonomic nervous system activity in relation to hearing impairment

Previous research has demonstrated that hearing impairment is associated with heightened subjective experiences of listening effort, fatigue, and stress, impacting daily functioning. This study aimed to evaluate whether hearing impairment alters physiological stress systems and whether different aspects of hearing impairment could vary in predicting dysregulation in these systems. Hallmark measures of parasympathetic and sympathetic nervous system activity were derived from electrocardiography, impedance cardiography, and electrodermal activity recordings taken from 133 individuals, aged 37 to 73, over two 24-hr periods, including sleep. Using ecological momentary assessment (EMA), participants reported mood, listening effort, and fatigue seven times daily. Hearing impairment was quantified through pure tone thresholds, speech perception in noise testing, and the Amsterdam Inventory for Auditory Disability questionnaire (Amsterdam Inventory). Using mixed models, we compared average daytime and sleep values of physiological measures across the 2 days, and their daytime-to-sleep contrast, based on each hearing impairment assessment. Results indicated that all three hearing impairment assessments were strong predictors of EMA outcomes of listening effort and fatigue. Contrary to expectations, hearing impairment did not have a significant impact on parasympathetic activity in daily life or on skin sympathetic activity. However, individuals with higher impairment exhibited a larger change in a cardiac sympathetic measure, the pre-ejection period, during wakefulness compared to sleep. Overall, hearing impairment had a small impact on autonomic nervous system functioning in daily life, but the effects were potentially attenuated by reduced exposure to listening demand in those with hearing impairment.

Family-based whole-exome sequencing implicates a variant in lysyl oxidase like 4 in atypical femur fractures

Atypical femur fractures (AFFs) are rare adverse events associated with bisphosphonate use, having unclear pathophysiology. AFFs also cluster in families and have occurred in patients with monogenetic bone diseases sometimes without bisphosphonate use, suggesting an underlying genetic susceptibility. Our aim was to identify a genetic cause for AFF in a Caucasian family with 7 members affected by osteoporosis, including 3 siblings with bisphosphonate-associated AFFs. Using whole-exome sequencing, we identified a rare pathogenic variant c.G1063A (p.Gly355Ser) in lysyl oxidase like 4 (LOXL4) among 64 heterozygous rare, protein-altering variants shared by the 3 siblings with AFFs. The same variant was also found in a fourth sibling with a low-trauma femur fracture above the knee, not fulfilling all the ASBMR criteria of AFF and in 1 of 73 unrelated European AFF patients. LOXL4 is involved in collagen cross-linking and may be relevant for microcrack formation and bone repair mechanisms. Preliminary functional analysis showed that skin fibroblast-derived osteoblasts from the unrelated patient with the LOXL4 variant expressed less collagen type I and elastin, while osteogenic differentiation and mineralization were enhanced compared with 2 controls. In conclusion, this LOXL4 variant may underlie AFF susceptibility possibly due to abnormal collagen metabolism, leading to increased formation of microdamage or compromised healing of microcracks in the femur.

Identification of novel candidate genes for Ascochyta blight resistance in chickpea

Ascochyta blight, caused by the necrotrophic fungus Ascochyta rabiei, is a major threat to chickpea production worldwide. Resistance genes with broad-spectrum protection against virulent A. rabiei strains are required to secure chickpea yield in the US Northern Great Plains. Here, we performed a genome-wide association (GWA) study to discover novel sources of genetic variation for Ascochyta blight resistance using a worldwide germplasm collection of 219 chickpea lines. Ascochyta blight resistance was evaluated at 3, 9, 11, 13, and 14 days post-inoculation. Multiple GWA models revealed eight quantitative trait nucleotides (QTNs) across timepoints mapped to chromosomes 1, 3, 4, 6, and 7. Of these eight QTNs, only CM001767.1_28299946 on Chr 4 had previously been reported. QTN CM001766.1_36967269 on Chr 3 explained up to 33% of the variation in disease severity and was mapped to an exonic region of the pentatricopeptide repeat-containing protein At4g02750-like gene (LOC101506608). This QTN was confirmed across all models and timepoints. A total of 153 candidate genes, including genes with roles in pathogen recognition and signaling, cell wall biosynthesis, oxidative burst, and regulation of DNA transcription, were observed surrounding QTN-targeted regions. Further gene expression analysis on the QTNs identified in this study will provide insights into defense-related genes that can be further incorporated into breeding of new chickpea cultivars to minimize fungicide applications required for successful chickpea production in the US Northern Great Plains.

A proteogenomic analysis of the adiposity colorectal cancer relationship identifies GREM1 as a probable mediator

BACKGROUND

Adiposity is an established risk factor for colorectal cancer (CRC). The pathways underlying this relationship, and specifically the role of circulating proteins, are unclear.

METHODS

Utilizing two-sample univariable Mendelian randomization (UVMR), multivariable Mendelian randomization (MVMR), and colocalization, based on summary data from large sex-combined and sex-specific genetic studies, we estimated the univariable associations between: (i) body mass index (BMI) and waist-hip ratio (WHR) and overall and site-specific (colon, proximal colon, distal colon, and rectal) CRC risk, (ii) BMI and WHR and circulating proteins, and (iii) adiposity-associated circulating proteins and CRC risk. We used MVMR to investigate the potential mediating role of adiposity- and CRC-related circulating proteins in the adiposity-CRC association.

RESULTS

BMI and WHR were positively associated with CRC risk, with similar associations by anatomical tumor site. In total, 6591 adiposity-protein (2628 unique circulating proteins) and 33 protein-CRC (7 unique circulating proteins) associations were identified using UVMR and colocalization. One circulating protein, GREM1, was associated with BMI (only) and CRC outcomes in a manner that was consistent with a potential mediating role in sex-combined and female-specific analyses. In MVMR, adjusting the BMI-CRC association for GREM1, effect estimates were attenuated-suggestive of a potential mediating role-most strongly for the BMI-overall CRC association in women.

CONCLUSION

Results highlight the impact of adiposity on the plasma proteome and of adiposity-associated circulating proteins on the risk of CRC. Supported by evidence from UVMR and colocalization analyses using cis-single-nucleotide polymorphisms, GREM1 was identified as a potential mediator of the BMI-CRC association, particularly in women.

Genetic control of root/shoot biomass partitioning in barley seedlings

The process of allocating resources to different plant organs in the early stage of development can affect their adaptation to drought conditions, by influencing water uptake, transpiration, photosynthesis, and carbon storage. Early barley development can affect the response to drought conditions and mitigate yield losses. A distinct behavior of biomass partitioning between two Spanish barley landraces (SBCC073 and SBCC146) was observed in a previous rhizotron experiment. An RIL population of approximately 200 lines, derived from the cross of those lines, was advanced using speed breeding. We devised an experiment to test if seedling biomass partitioning was under genetic control, growing the seedlings in pots filled with silica sand, in a growth chamber under controlled conditions. After 1 week, the shoot and root were separated, oven dried, and weighted. There were genotypic differences for shoot dry weight, root dry weight, and root-to-shoot ratio. The population was genotyped with a commercial 15k SNP chip, and a genetic map was constructed with 1,353 SNP markers. A QTL analysis revealed no QTL for shoot or root dry weight. However, a clear single QTL for biomass partitioning (RatioRS) was found, in the long arm of chromosome 5H. By exploring the high-confidence genes in the region surrounding the QTL peak, five genes with missense mutations between SBCC146 and SBCC073, and differential expression in roots compared to other organs, were identified. We provide evidence of five promising candidate genes with a role in biomass partitioning that deserve further research.

Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population

Human craniofacial shape is highly variable yet highly heritable with numerous genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the general population. We compare three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores reveals a polygenic basis for facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples, both human and mouse, shows craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing insights into the genetic intersection of complex traits and Mendelian disorders.

Disentangling the consequences of type 2 diabetes on targeted metabolite profiles using causal inference and interaction QTL analyses

Circulating metabolite levels have been associated with type 2 diabetes (T2D), but the extent to which T2D affects metabolite levels and their genetic regulation remains to be elucidated. In this study, we investigate the interplay between genetics, metabolomics, and T2D risk in the UK Biobank dataset using the Nightingale panel composed of 249 metabolites, 92% of which correspond to lipids (HDL, IDL, LDL, VLDL) and lipoproteins. By integrating these data with large-scale T2D GWAS from the DIAMANTE meta-analysis through Mendelian randomization analyses, we find 79 metabolites with a causal association to T2D, all spanning lipid-related classes except for Glucose and Tyrosine. Twice as many metabolites are causally affected by T2D liability, spanning almost all tested classes, including branched-chain amino acids. Secondly, using an interaction quantitative trait locus (QTL) analysis, we describe four metabolites consistently replicated in an independent dataset from the Estonian Biobank, for which genetic loci in two different genomic regions show attenuated regulation in T2D cases compared to controls. The significant variants from the interaction QTL analysis are significant QTLs for the corresponding metabolites in the general population but are not associated with T2D risk, pointing towards consequences of T2D on the genetic regulation of metabolite levels. Finally, through differential level analyses, we find 165 metabolites associated with microvascular, macrovascular, or both types of T2D complications, with only a few discriminating between complication classes. Of the 165 metabolites, 40 are not causally linked to T2D in either direction, suggesting biological mechanisms specific to the occurrence of complications. Overall, this work provides a map of the consequences of T2D on Nightingale targeted metabolite levels and on their genetic regulation, enabling a better understanding of the T2D trajectory leading to complications.

Development of metabolic signatures of plant-rich dietary patterns using plant-derived metabolites

BACKGROUND

Diet is an important modifiable lifestyle factor for human health, and plant-rich dietary patterns are associated with lower risk of non-communicable diseases in numerous studies. However, objective assessment of plant-rich dietary exposure in nutritional epidemiology remains challenging.

OBJECTIVES

This study aimed to develop and evaluate metabolic signatures of the most widely used plant-rich dietary patterns using a targeted metabolomics method comprising 108 plant food metabolites.

METHODS

A total of 218 healthy participants were included, aged 51.5 ± 17.7 years, with 24 h urine samples measured using ultra-high-performance liquid chromatography-mass spectrometry. The validation dataset employed three sample types to test the robustness of the signature, including 24 h urine (n = 88), plasma (n = 195), and spot urine (n = 198). Adherence to the plant-rich diet was assessed using a priori plant-rich dietary patterns calculated using Food Frequency Questionnaires. A combination of metabolites evaluating the adherence to a specific diet was identified as metabolic signature. We applied linear regression analysis to select the metabolites significantly associated with dietary patterns (adjusting energy intake), and ridge regression to estimate penalized weights of each candidate metabolite. The correlation between metabolic signature and the dietary pattern was assessed by Spearman analysis (FDR < 0.05).

RESULTS

The metabolic signatures consisting of 42, 22, 35, 15, 33, and 33 predictive metabolites across different subclasses were found to be associated with adherence to Amended Mediterranean Score (A-MED), Original MED (O-MED), Dietary Approaches to Stop Hypertension (DASH), Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND), healthy Plant-based Diet Index (hPDI) and unhealthy PDI (uDPI), respectively. The overlapping and distinct predictive metabolites across six dietary patterns predominantly consisted of phenolic acids (n = 38), including 14 cinnamic acids, 14 hydroxybenzoic acids, seven phenylacetic acids, and three hippuric acids. Six metabolites were included in all signatures, including two lignans: enterolactone-glucuronide, enterolactone-sulfate, and four phenolic acids: cinnamic acid, cinnamic acid-4'-sulfate, 2'-hydroxycinnamic acid, and 4-methoxybenzoic acid-3-sulfate. The established signatures were robustly correlated with dietary patterns in the validation datasets (r = 0.13-0.40, FDR < 0.05).

CONCLUSIONS

We developed and evaluated a set of metabolic signatures that reflected the adherence to plant-rich dietary patterns, suggesting the potential of these signatures to serve as an objective assessment of free-living eating habits.

Capturing resilience from phenotypic deviations: a case study using feed consumption and whole genome data in pigs

BACKGROUND

In recent years, interest has grown in quantifying resilience in livestock by examining deviations in target phenotypes. This method is based on the idea that variability in these phenotypes reflects an animal's ability to adapt to external factors. By utilizing routinely collected time-series feed intake data in pigs, researchers can obtain a broad measure of resilience. This measure extends beyond specific conditions, capturing the impact of various unknown external factors that influence phenotype variations. Importantly, this method does not require additional phenotyping investments. Despite growing interest, the relationship between resilience indicators-calculated as deviations from longitudinally recorded target traits-and the mean of those traits remains largely unexplored. This gap raises the risk of inadvertently selecting for the mean rather than accurately capturing true resilience. Additionally, distinguishing between random phenotype fluctuations (white noise) and structural variations linked to resilience poses a challenge. With the aim of developing general resilience indicators applicable to commercial swine populations, we devised four resilience indicators utilizing daily feed consumption as the target trait. These include a canonical resilience indicator (BALnVar) and three novel ones (BAMaxArea, SPLnVar, and SPMaxArea), designed to minimize noise and ensure independence from daily feed consumption. We subsequently integrated these indicators with Whole Genome Sequencing using SLEMM algorithm, data from 1,250 animals to assess their efficacy in capturing resilience and their independence from the mean of daily feed consumption.

RESULTS

Our findings revealed that conventional resilience indicators failed to differentiate from the mean of daily feed consumption, underscoring potential limitations in accurately capturing true resilience. Notably, significant associations involving conventional resilience indicators were identified on chromosome 1, which is commonly linked to body weight.

CONCLUSION

We observed that deviations in feed consumption can effectively serve as indicators for selecting resilience in commercial pig farming, as confirmed by the identification of genes such as PKN1 and GYPC. However, the identification of other genes, such as RNF152, related to growth, suggests that common resilience quantification methods may be more closely related to the mean of daily feed consumption rather than capturing true resilience.

Gene-environment interactions in the influence of maternal education on adolescent neurodevelopment using ABCD study

Maternal education was strongly correlated with adolescent brain morphology, cognitive performances, and mental health. However, the molecular basis for the effects of maternal education on the structural neurodevelopment remains unknown. Here, we conducted gene-environment-wide interaction study using the Adolescent Brain Cognitive Development cohort. Seven genomic loci with significant gene-environment interactions (G×E) on regional gray matter volumes were identified, with enriched biological functions related to metabolic process, inflammatory process, and synaptic plasticity. Additionally, genetic overlapping results with behavioral and disease-related phenotypes indicated shared biological mechanism between maternal education modified neurodevelopment and related behavioral traits. Finally, by decomposing the multidimensional components of maternal education, we found that socioeconomic status, rather than family environment, played a more important role in modifying the genetic effects on neurodevelopment. In summary, our study provided analytical evidence for G×E effects regarding adolescent neurodevelopment and explored potential biological mechanisms as well as social mechanisms through which maternal education could modify the genetic effects on regional brain development.

Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction

Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.

Perceived Mistreatment and Professional Identity of Medical Students in China

Importance

Mistreatment is a common experience among medical students, with various negative consequences of such perceived mistreatment reported. However, few large-scale studies have investigated the association between perceived mistreatment and the formation of medical students' professional identities.

Objective

To investigate medical students' perceived mistreatment during medical school and its association with professional identity.

Design, Setting, and Participants

This repeated cross-sectional study included medical students graduating between 2019 and 2022 at 135 medical schools in China. Analyses were performed from July 25, 2023, to May 15, 2024.

Exposure

The China Medical Student Survey includes 5 items designed to measure students' perceived experiences of mistreatment.

Main Outcomes and Measures

Professional identity was measured using a validated 7-item scale adapted from the Macleod Clark Professional Identity Scale. Multivariate linear regression was used to determine the association between perceived mistreatment and medical students' professional identity.

Results

A total of 94 153 students (53 819 female [57.2%]; 83 548 Han ethnicity [88.7%]) were analyzed, representing 67.2% of the medical graduates enrolled in all responding medical schools. Most medical students reported having experienced at least 1 mistreatment incident (79 554 students [84.5%]). Medical students reported being required to perform personal service (57 455 students [61.0%]), experiencing mistreatment by patients (67 439 students [71.6%]), being publicly humiliated (24 348 students [25.9%]), being unjustly treated (35 926 students [38.2%]), and experiencing deliberate harassment (46 082 students [48.9%]). A negative association and saturation effect (where effect size plateaus after moderate exposure of mistreatment) were found between the degree of mistreatment and medical students' professional identity scores. Compared with students who had not reported mistreatment, students who reported single (β, -0.30; 95% CI, -0.33 to -0.28; P < .001), moderate (β, -0.66; 95% CI, -0.69 to -0.63; P < .001), and high (β, -0.62; 95% CI, -0.65 to -0.58; P < .001) frequency of mistreatment were more likely to have lower professional identity scores; this association persisted but was attenuated after adjusting for students' sociodemographic characteristics and was consistent across all the types of mistreatment.

Conclusions and Relevance

In this national, repeated cross-sectional study, a high prevalence of mistreatment among medical students in China and a negative association between perceived mistreatment and medical students' professional identity was found. Further research is needed to ensure that medical schools offer supportive and respectful learning environments.

Targeted plasma multi-omics propose glutathione, glycine and serine as biomarkers for abdominal aortic aneurysm growth on serial CT scanning

BACKGROUND AND AIMS

Abdominal aortic aneurysm (AAA) patients undergo uniform imaging surveillance until reaching the surgical threshold. In spite of the ongoing exploration of AAA pathophysiology, biomarkers for personalized surveillance are lacking. This study aims to identify potential circulating biomarkers for AAA growth on serial CT scans.

METHODS

Patients with an AAA (maximal diameter ≥40 mm) were included in this multicentre, prospective cohort study. Participants underwent baseline blood sampling and yearly CT-imaging to determine AAA diameter and volume. Proteins and metabolites were measured using proximity extension assay (Olink Cardiovascular III) or separate ELISA panels, and mass-spectrometry (LC-TQMS), respectively. Linear mixed-effects, orthogonal partial least squares, and Cox regression were used to explore biomarker associations with AAA volume growth rate and the risk of surpassing the surgical threshold, as formulated by current guidelines.

RESULTS

271 biomarkers (95 proteins, 176 metabolites) were measured in 109 (90.8 % male) patients with mean age 72. Median baseline maximal AAA diameter was 47.8 mm, volume 109 mL. Mean annual AAA volume growth rate was 11.5 %, 95 % confidence interval (CI) (10.4, 12.7). Median follow-up time was 23.2 months, 49 patients reached the surgical threshold. Patients with one standard deviation (SD) higher glutathione and glycine levels at baseline had an AAA volume growth rate that respectively was 1.97 %, 95%CI (0.97, 2.97) and 1.74 %, 95%CI (0.78, 2.71) larger, relative to the actual aneurysm size. Serine was associated with the risk of reaching the surgical threshold, independent of age and baseline AAA size (cause-specific hazard ratio per SD difference 1.78, 95%CI (1.30, 2.44)).

CONCLUSIONS

Among multiple intertwined biomarkers related to AAA pathophysiology and progression, glutathione, glycine and serine were most promising.

Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease

Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia. Genetic risk loci for white matter hyperintensities (WMH), the most common MRI-marker of cSVD in older age, were recently shown to be significantly associated with white matter (WM) microstructure on diffusion tensor imaging (signal-based) in young adults. To provide new insights into these early changes in WM microstructure and their relation with cSVD, we sought to explore the genetic underpinnings of cutting-edge tissue-based diffusion imaging markers across the adult lifespan. We conducted a genome-wide association study of neurite orientation dispersion and density imaging (NODDI) markers in young adults (i-Share study: N = 1 758, (mean[range]) 22.1[18-35] years), with follow-up in young middle-aged (Rhineland Study: N = 714, 35.2[30-40] years) and late middle-aged to older individuals (UK Biobank: N = 33 224, 64.3[45-82] years). We identified 21 loci associated with NODDI markers across brain regions in young adults. The most robust association, replicated in both follow-up cohorts, was with Neurite Density Index (NDI) at chr5q14.3, a known WMH locus in VCAN. Two additional loci were replicated in UK Biobank, at chr17q21.2 with NDI, and chr19q13.12 with Orientation Dispersion Index (ODI). Transcriptome-wide association studies showed associations of STAT3 expression in arterial and adipose tissue (chr17q21.2) with NDI, and of several genes at chr19q13.12 with ODI. Genetic susceptibility to larger WMH volume, but not to vascular risk factors, was significantly associated with decreased NDI in young adults, especially in regions known to harbor WMH in older age. Individually, seven of 25 known WMH risk loci were associated with NDI in young adults. In conclusion, we identified multiple novel genetic risk loci associated with NODDI markers, particularly NDI, in early adulthood. These point to possible early-life mechanisms underlying cSVD and to processes involving remyelination, neurodevelopment and neurodegeneration, with a potential for novel approaches to prevention.

Optimal Structured Matrix Approximation for Robustness to Incomplete Biosequence Data

We propose a general method for optimally approximating an arbitrary matrix by a structured matrix (circulant, Toeplitz/Hankel, etc.) and examine its use for estimating the spectra of genomic linkage disequilibrium matrices. This application is prototypical of a variety of genomic and proteomic problems that demand robustness to incomplete biosequence information. We perform a simulation study and corroborative test of our method using real genomic data from the Mouse Genome Database (Bult et al., 2019). The results confirm the predicted utility of the method and provide strong evidence of its potential value to a wide range of bioinformatics applications. Our optimal general matrix approximation method is expected to be of independent interest to an even broader range of applications in applied mathematics and engineering.

Identification of heat stress-related genomic regions by genome-wide association study in Solanum tuberosum

The climate crisis impairs yield and quality of crucial crops like potatoes. We investigated the effects of heat stress on five morpho-physiological parameters in a diverse panel of 178 potato cultivars under glasshouse conditions. Overall, heat stress increased shoot elongation and green fresh weight, but reduced tuber yield, starch content and harvest index. Genomic information was obtained from 258 tetraploid and three diploid cultivars by a genotyping-by-sequencing approach using methylation-sensitive restriction enzymes. This resulted in an enrichment of sequences in gene-rich regions. Population structure analyses using genetic distances and hierarchical clustering revealed strong kinship but weak overall population structure cultivars. A genome-wide association study (GWAS) was conducted with a subset of 20 K stringently filtered SNPs to identify quantitative trait loci (QTL) linked to heat tolerance. We identified 67 QTL and established haploblock boundaries to narrow down the number of candidate genes. Additionally, GO-enrichment analyses provided insights into gene functions. Heritability and genomic prediction were conducted to assess the usability of the collected data for selecting breeding material. The detected QTL might be exploited in marker-assisted selection to develop heat-resilient potato cultivars.

Networks of human milk microbiota are associated with host genomics, childhood asthma, and allergic sensitization

The human milk microbiota (HMM) is thought to influence the long-term health of offspring. However, its role in asthma and atopy and the impact of host genomics on HMM composition remain unclear. Through the CHILD Cohort Study, we followed 885 pregnant mothers and their offspring from birth to 5 years and determined that HMM was associated with maternal genomics and prevalence of childhood asthma and allergic sensitization (atopy) among human milk-fed infants. Network analysis identified modules of correlated microbes in human milk that were associated with subsequent asthma and atopy in preschool-aged children. Moreover, reduced alpha-diversity and increased Lawsonella abundance in HMM were associated with increased prevalence of childhood atopy. Genome-wide association studies (GWASs) identified maternal genetic loci (e.g., ADAMTS8, NPR1, and COTL1) associated with HMM implicated with asthma and atopy, notably Lawsonella and alpha-diversity. Thus, our study elucidates the role of host genomics on the HMM and its potential impact on childhood asthma and atopy.

Longitudinal association of depressive symptoms with cognition and neuroimaging biomarkers in cognitively unimpaired older adults, mild cognitive impairment, and Alzheimer's disease

We aimed to longitudinally examine the relationship between depression and cognitive function and investigate the mediating effects of imaging indicators in this relationship. 2,251 subjects with longitudinal assessment of geriatric depression scale, Mini-Mental State Examination, Montreal Cognitive Assessment, Clinical Dementia Rating-Sum of Boxes (CDRSB), Alzheimer's Disease Assessment Scale11, Alzheimer's Disease Assessment Scale13 and imaging of 3DT1, diffusion tensor imaging, fluid-attenuated inversion recovery, arterial spin labeling, fluorodeoxyglucose positron emission tomography, 18F-AV45-PET, and 18F-AV1451-PET were included from the Alzheimer's Disease Neuroimaging Initiative database. The multivariate mixed-effects models were employed to analyze the correlation between geriatric depression scale scores, cognitive function, and imaging indicators. The sgmediation software package was utilized to analyze the mediating effects of imaging indicators. The geriatric depression scale was negatively correlated with Mini-Mental State Examination and Montreal Cognitive Assessment, and positively correlated with CDRSB, Alzheimer's Disease Assessment Scale11, and Alzheimer's Disease Assessment Scale13 when the subjects were not grouped. The geriatric depression scale was negatively correlated with Montreal Cognitive Assessment and positively correlated with Alzheimer's Disease Assessment Scal13 in groups with baseline diagnosis of early mild cognitive impairment and late mild cognitive impairment. Furthermore, depression was associated with regional imaging indicators, while cognitive function was linked to broad imaging indicators. Some of these indicators were related to both depression and cognitive function, playing a mediating role in their relationship. Depression was related to cognitive function, especially in subjects with mild cognitive impairment. Some imaging indicators may represent the underlying basis for the association between depression and cognitive function.

Genetic Polymorphisms of Immunity Regulatory Genes and Alopecia Areata Susceptibility in Jordanian Patients

Background and Objectives: Alopecia areata (AA) is a tissue-specific immune-mediated disorder that affects hair follicles and the nail apparatus. Due to the collapse of hair follicle immune privilege in AA, hair loss ranges in severity from small, localized patches on the scalp to the loss of entire body hair. Although AA is of uncertain etiology, the disease has a common genetic basis with a number of other autoimmune diseases. Materials and Methods: To identify candidate genes that confer susceptibility to AA in the Jordanian population and further understand the disease background, we performed DNA genotyping using case-control samples of 152 patients and 150 healthy subjects. Results: While no significant result was observed in the ten single-nucleotide polymorphisms (SNPs), CLEC4D rs4304840 variants showed significant associations with AA development within our cohort (p = 0.02). The strongest associations were for the codominant and recessive forms of rs4304840 (p = 0.023 and p = 0.0061, respectively). Conclusions: These findings suggest that CLEC4D gene variants may contribute to AA pathogenesis among Jordanians. Further advanced genetic analysis and functional investigations are required to elucidate the genetic basis of the disease.

A multidimensional gender analysis of health technology self-efficacy among people with Parkinson's disease

BACKGROUND

Digital health technologies (DHT) enable self-tracking of bio-behavioral states and pharmacotherapy outcomes in various diseases. However, the role of gender, encompassing social roles, expectations, and relations, is often overlooked in their adoption and use. This study addresses this issue for persons with Parkinson's disease (PD), where DHT hold promise for remote evaluations.

METHODS

We conducted a cross-sectional survey study in the Netherlands, assessing the impact of gender identity, roles, and relations on health technology self-efficacy (HTSE) and attitude (HTA). An intersectional gender analysis was applied to explore how gender intersects with education, employment, disease duration, and severity in influencing HTSE and HTA.

RESULTS

Among 313 participants (40% women), no significant correlation was found between gender identity or relations and HTSE or HTA. However, individuals with an androgynous (non-binary) gender role orientation demonstrated better HTSE and HTA. The exploratory intersectional analysis suggested that sociodemographic and clinical factors might affect the influence of gender role orientations on HTSE and HTA, indicating complex and nuanced interactions.

CONCLUSION

This study highlights the importance of investigating gender as a multidimensional variable in PD research on health technology adoption and use. Considering gender as a behavioral construct, such as through gender roles and norms, shows more significant associations with HTSE and HTA, although effect sized were generally small. The impact of gender dimensions on these outcomes can be compounded by intersecting social and disease-specific factors. Future studies should consider multiple gender dimensions and intersecting factors to fully understand their combined effects on technology uptake and use among people with PD.

Prenatal Exposure to Per- and Polyfluoroalkyl Substances and ASD-Related Symptoms in Early Childhood: Mediation Role of Steroids

Previous studies regarding the associations between perfluoroalkyl and polyfluoroalkyl substances (PFAS) and autism spectrum disorder (ASD) have yielded inconsistent results, with the underlying mechanisms remaining unknown. In this study, we quantified 13 PFAS in cord serum samples from 396 neonates and followed the children at age 4 to assess ASD-related symptoms. Our findings revealed associations between certain PFAS and ASD-related symptoms, with a doubling of perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and perfluoroundecanoic acid (PFUnDA) concentrations associated with respective increases of 1.79, 1.62, and 1.45 units in language-related symptoms and PFDA exhibiting an association with higher score of sensory stimuli. Nonlinear associations were observed in the associations of 6:2 chlorinated polyfluorinated ether sulfonate (Cl-PFAES) and 8:2 Cl-PFAES with ASD-related symptoms. Employing weighted quantile sum (WQS) regression, we observed significant mixture effects of multiple PFAS on all domains of ASD-related symptoms, with PFNA emerging as the most substantial contributor. Assuming causality, we found that 39-40% of the estimated effect of long-chain PFAS (PFUnDA and PFDoDA) exposure on sensory stimuli was mediated by androstenedione. This study provides novel epidemiological data about prenatal PFAS mixture exposure and ASD-related symptoms.