Bayesian colocalization of GWAS and eQTL signals reveals cell type-specific genes and regulatory variants for susceptibility to subtypes of ischemic stroke.

A colocalization analysis of genome-wide association study (GWAS) signals and expression quantitative trait loci (eQTL) was conducted to pinpoint target genes and their regulatory nucleotide variants for subtypes of ischemic stroke. We utilized GWAS data from prominent meta-analysis consortia (MEGASTROKE and GIGASTROKE) and single-cell eQTL data in brain and blood tissues to enhance accuracy and minimize noise inherent in bulk RNA-seq. Employing Bayesian colocalization methods, we identified ten shared loci between GWAS and eQTL signals, targeting five eGenes. Specifically, RAPH1 and ICA1L were discovered for small vessel stroke (SVS), whereas SCYL3, CAV1, and CAV2 were for cardioembolic stroke (CS). However, no findings have been made for large artery stroke. The exploration and subsequent functional analysis of causal variants within the colocalized regions revealed their regulatory roles, particularly as enhancer variants (e.g., rs144505847 and rs72932755 targeting ICA1L; rs629234 targeting SCYL3; rs3807989 targeting CAV1 and CAV2). Notably, our study unveiled that all eQTL for CS were identified in oligodendrocytes, while those for SVS were across excitatory neurons, astrocytes, and oligodendrocyte precursor cells. This underscores the heterogeneous tissue-specific genetic factors by subtypes of ischemic stroke. The study emphasizes the need for intensive research efforts to discover causative genes and variants, unravelling the cell type-specific genetic architecture of ischemic stroke subtypes. This knowledge is crucial for advancing our understanding of the underlying pathophysiology and paving the way for precision neurology applications.

RNA Polymerase Subunits and Ribosomal Proteins: An Overview and Their Genetic Impact on Complex Human Traits.

Accurate gene expression is fundamental for sustaining life, enabling adaptive responses to routine tasks and management of urgent cellular environments. RNA polymerases (RNAP I, RNAP II, and RNAP III) and ribosomal proteins (RPs) play pivotal roles in the precise synthesis of proteins from DNA sequences. In this review, we briefly examined the structure and function of their constituent proteins and explored to characterize these proteins and the genes encoding them, particularly in terms of their expression quantitative trait loci (eQTL) associated with complex human traits. We gathered a comprehensive set of 4007 genome-wide association study (GWAS) signal-eQTL pairs, aligning GWAS Catalog signals with eQTLs across various tissues for the genes involved. These pairs spanned 16 experimental factor ontology (EFO) parent terms defined in European Bioinformatics Institute (EBI). A substantial majority (83.4%) of the pairs were attributed to the genes encoding RPs, especially RPS26 (32.9%). This large proportion was consistent across all tissues (15.5~81.9%), underscoring its extensive impact on complex human traits. Notably, these proportions of EFO terms differed significantly (p < 0.0031) from those for RNAPs. Brain-specific pairs for POLR3H, a component of RNAP III, were implicated in neurological disorders. The largest number of pairs in RNAP I was found for POLR1H, encoding RPA12, a built-in transcription factor essential for high transcriptional efficiency of RNAP I. RNAP II-related pairs were less abundant, with unique structural organization featuring minimal subunits for flexible transcription of a diverse range of genes with customized dissociable subunits. For instance, RPB4 encoded by POLR2D, the RNAP II gene with the most pairs, forms its dissociable stalk module with RPB7. This study provides insightful genetic characteristics of RPs and RNAPs, with a priority emphasis on RPS26, POLR1H, POLR2D, and POLR3H, for future studies on the impact of individual genetic variation on complex human traits.

Generating PET scan patterns in Alzheimer's by a mathematical model.

Alzheimer disease (AD) is the most common form of dementia. The cause of the disease is unknown, and it has no cure. Symptoms include cognitive decline, memory loss, and impairment of daily functioning. The pathological hallmarks of the disease are aggregation of plaques of amyloid-ß (Aß) and neurofibrillary tangles of tau proteins (τ), which can be detected in PET scans of the brain. The disease can remain asymptomatic for decades, while the densities of Aß and τ continue to grow. Inflammation is considered an early event that drives the disease. In this paper, we develop a mathematical model that can produce simulated patterns of (Aß,τ) seen in PET scans of AD patients. The model is based on the assumption that early inflammations, R and [Formula: see text], drive the growth of Aß and τ, respectively. Recently approved drugs can slow the progression of AD in patients, provided treatment begins early, before significant damage to the brain has occurred. In line with current longitudinal studies, we used the model to demonstrate how to assess the efficacy of such drugs when given years before the disease becomes symptomatic.

Anti-Melanogenic Activity of Undecylprodigiosin, a Red Pigment Isolated from a Marine Streptomyces sp. SNA-077.

Bioassay and HPLC-UV guided fractionations of the crude extract of marine-derived Streptomyces sp. SNA-077 have led to the isolation of a red pigment, undecylprodigiosin (1). The chemical structure of undecylprodigiosin (1) was revealed by the interpretation of NMR and mass spectroscopic (MS) data. Further, anti-melanogenic effects of undecylprodigiosin (1) were investigated. First, the melanin contents of undecylprodigiosin (1)-treated B16 cells were evaluated. Furthermore, undecylprodigiosin (1) significantly inhibited the key enzymes involved in melanogenesis, including tyrosinase, tyrosinase related protein-1 (TYRP-1), and dopachrome tautomerase (DCT). The mRNA and protein expression levels of Microphthalmia-associated transcriptian factor (MiTF), a critical transcription factor for tyrosinase gene expression, were also suppressed by undecylprodigiosin (1) treatment in B16 analyses. Collectively, our results suggest for the first time that undecylprodigiosin (1), a potent component isolated from an extract of marine Streptomyces sp. SNA-077, critically exerts the anti-melanogenic ability for melanin synthesis.

The discovery of an anti-inflammatory monoterpenoid, neoroseoside from the Zea mays.

A new monoterpenoid, neoroseoside (1), along with two previously reported compounds, 2″-O-α-l-rhamnosyl-6-C-fucosylluteolin (2) and farobin A (3) were isolated from the Zea mays. The structure of compound 1 was determined through the analysis spectroscopic data, including mass spectrometry (MS), infrared (IR) spectroscopy, and nuclear magnetic resonance (NMR) data. The absolute configurations of 1 were deduced from the comparing the values of optical rotations and from the interpretation of electronic circular dichroism (ECD) spectra. Compounds 2 and 3 displayed moderate antibacterial activity against Streptococcus mutans ATCC 25175 (inhibition rates 24 % and 28 %, respectively) and Streptococcus sobrinus ATCC 33478 (inhibition rate of 26 %), at a concentration of 100 µg/mL, whereas compound 1 did not have any significant antibacterial activities. The compounds 1-3 also showed anti-inflammatory activity on cytokine IL-6 and TNF-α.

Investigating the safety profiles of exogenous melatonin and associated adverse events: A pharmacovigilance study using WHO-VigiBase.

Melatonin, a pineal hormone that modulates circadian rhythms, sleep, and neurotransmitters, is widely used to treat sleep disorders. However, there are limited studies on the safety of melatonin. Therefore, we aimed to present the overall patterns of adverse events (AEs) following melatonin administration and identify potential safety signals associated with melatonin. Using VigiBase, a global individual case safety report (ICSRs) database managed by the World Health Organization (WHO), we conducted a retrospective, observational, pharmacovigilance study of melatonin between January 1996 and September 2022. Disproportionality analysis was conducted using two comparator settings: all other drugs and other sleep medications. We used multivariable logistic regression to estimate reporting odds ratios (RORs) with 95% confidence intervals (CIs) to compare the frequencies of AEs reporting between melatonin and each comparator setting. Furthermore, we assessed adverse events of special interests (AESIs) that could potentially be associated with melatonin. Signals were identified when the following criteria were met: cases ≥3, x2 ≥ 4, IC025 ≥ 0, and the lower end of the 95% CI of ROR > 2. These signals were then compared with the AE information on the drug labels provided by regulatory bodies. A total of 35 479 AE reports associated with melatonin were identified, with a higher proportion of reports from females (57.1%) and individuals aged 45-64 years (20.8%). We identified 21 AEs that were commonly detected as safety signals in the disproportionality analyses, including tic, educational problems, disturbance in social behavior, body temperature fluctuation, and growth retardation. In AESI analyses, accidents and injuries (adjusted ROR 2.97; 95% CI, 2.80-3.16), fall (2.24; 2.12-2.37), nightmare (4.90; 4.37-5.49), and abnormal dreams (3.68; 3.19-4.25) were detected as a signal of melatonin when compared to all other drugs, whereas those signals were not detected when compared to other sleep medications. In this pharmacovigilance study, exogenous melatonin showed safety profiles comparable to other sleep medications. However, several unexpected potential safety signals were identified, underscoring the need for further investigation at the population level.

Predicting Driver's mental workload using physiological signals: A functional data analysis approach.

This study investigates the impact of advanced driver-assistance systems on drivers' mental workload. Using a combination of physiological signals including ECG, EMG, EDA, EEG (af4 and fc6 channels from the theta band), and eye diameter data, this study aims to predict and categorize drivers' mental workload into low, adequate, and high levels. Data were collected from five different driving situations with varying cognitive demands. A functional linear regression model was employed for prediction, and the accuracy rate was calculated. Among the 31 tested combinations of physiological variables, 9 combinations achieved the highest accuracy result of 90%. These results highlight the potential benefits of utilizing raw physiological signal data and employing functional data analysis methods to understand and assess driver mental workload. The findings of this study have implications for the design and improvement of driver-assistance systems to optimize safety and performance.

Sustainable production of natural products using synthetic biology: Ginsenosides.

Synthetic biology approaches offer potential for large-scale and sustainable production of natural products with bioactive potency, including ginsenosides, providing a means to produce novel compounds with enhanced therapeutic properties. Ginseng, known for its non-toxic and potent qualities in traditional medicine, has been used for various medical needs. Ginseng has shown promise for its antioxidant and neuroprotective properties, and it has been used as a potential agent to boost immunity against various infections when used together with other drugs and vaccines. Given the increasing demand for ginsenosides and the challenges associated with traditional extraction methods, synthetic biology holds promise in the development of therapeutics. In this review, we discuss recent developments in microorganism producer engineering and ginsenoside production in microorganisms using synthetic biology approaches.

Synergistic toxicity with copper contributes to NAT2-associated isoniazid toxicity.

Anti-tuberculosis (AT) medications, including isoniazid (INH), can cause drug-induced liver injury (DILI), but the underlying mechanism remains unclear. In this study, we aimed to identify genetic factors that may increase the susceptibility of individuals to AT-DILI and to examine genetic interactions that may lead to isoniazid (INH)-induced hepatotoxicity. We performed a targeted sequencing analysis of 380 pharmacogenes in a discovery cohort of 112 patients (35 AT-DILI patients and 77 controls) receiving AT treatment for active tuberculosis. Pharmacogenome-wide association analysis was also conducted using 1048 population controls (Korea1K). NAT2 and ATP7B genotypes were analyzed in a replication cohort of 165 patients (37 AT-DILI patients and 128 controls) to validate the effects of both risk genotypes. NAT2 ultraslow acetylators (UAs) were found to have a greater risk of AT-DILI than other genotypes (odds ratio [OR] 5.6 [95% confidence interval; 2.5-13.2], P = 7.2 × 10-6). The presence of ATP7B gene 832R/R homozygosity (rs1061472) was found to co-occur with NAT2 UA in AT-DILI patients (P = 0.017) and to amplify the risk in NAT2 UA (OR 32.5 [4.5-1423], P = 7.5 × 10-6). In vitro experiments using human liver-derived cell lines (HepG2 and SNU387 cells) revealed toxic synergism between INH and Cu, which were strongly augmented in cells with defective NAT2 and ATP7B activity, leading to increased mitochondrial reactive oxygen species generation, mitochondrial dysfunction, DNA damage, and apoptosis. These findings link the co-occurrence of ATP7B and NAT2 genotypes to the risk of INH-induced hepatotoxicity, providing novel mechanistic insight into individual AT-DILI susceptibility. Yoon et al. showed that individuals who carry NAT2 UAs and ATP7B 832R/R genotypes are at increased risk of developing isoniazid hepatotoxicity, primarily due to the increased synergistic toxicity between isoniazid and copper, which exacerbates mitochondrial dysfunction-related apoptosis.

Hedgehog signalling is involved in acquired resistance to KRASG12C inhibitors in lung cancer cells.

Although KRASG12C inhibitors have shown promising activity in lung adenocarcinomas harbouring KRASG12C, acquired resistance to these therapies eventually occurs in most patients. Re-expression of KRAS is thought to be one of the main causes of acquired resistance. However, the mechanism through which cancer cells re-express KRAS is not fully understood. Here, we report that the Hedgehog signal is induced by KRASG12C inhibitors and mediates KRAS re-expression in cancer cells treated with a KRASG12C inhibitor. Further, KRASG12C inhibitors induced the formation of primary cilia and activated the Hedgehog-GLI-1 pathway. GLI-1 binds to the KRAS promoter region, enhancing KRAS promoter activity and KRAS expression. Inhibition of GLI using siRNA or the smoothened (Smo) inhibitor suppressed re-expression of KRAS in cells treated with a KRASG12C inhibitor. In addition, we demonstrate that KRASG12C inhibitors decreased Aurora kinase A (AURKA) levels in cancer cells, and inhibition of AURKA using siRNA or inhibitors led to increased expression levels of GLI-1 and KRAS even in the absence of KRAS inhibitor. Ectopic expression of AURKA attenuated the effect of KRASG12C inhibitors on the expression of GLI-1 and re-expression of KRAS. Together, these findings demonstrate the important role of AURKA, primary cilia, and Hedgehog signals in the re-expression of KRAS and therefore the induction of acquired resistance to KRASG12C inhibitors, and provide a rationale for targeting Hedgehog signalling to overcome acquired resistance to KRASG12C inhibitors.

Breast cancer malignancy is governed by regulation of the macroH2A2/TM4SF1 axis, the AKT/NF-κB pathway, and elevated MMP13 expression.

The histone variant, macroH2A (mH2A) influences gene expression through epigenetic regulation. Tumor suppressive function of mH2A isoforms has been reported in various cancer types, but few studies have investigated the functional role of mH2A2 in breast cancer pathophysiology. This study aimed to determine the significance of mH2A2 in breast cancer development and progression by exploring its downstream regulatory mechanisms. Knockdown of mH2A2 facilitated the migration and invasion of breast cancer cells, whereas its overexpression exhibited the opposite effect. In vivo experiments revealed that augmenting mH2A2 expression reduced tumor growth and lung metastasis. Microarray analysis showed that TM4SF1 emerged as a likely target linked to mH2A2 owing to its significant suppression in breast cancer cell lines where mH2A2 was overexpressed among the genes that exhibited over twofold upregulation upon mH2A2 knockdown. Suppressing TM4SF1 reduced the migration, invasion, tumor growth, and metastasis of breast cancer cells in vitro and in vivo. TM4SF1 depletion reversed the increased aggressiveness triggered by mH2A2 knockdown, suggesting a close interplay between mH2A2 and TM4SF1. Our findings also highlight the role of the mH2A2/TM4SF1 axis in activating the AKT/NF-κB pathway. Consequently, activated NF-κB signaling leads to increased expression and secretion of MMP13, a potent promoter of metastasis. In summary, we propose that the orchestrated regulation of the mH2A2/TM4SF1 axis in conjunction with the AKT/NF-κB pathway and the subsequent elevation in MMP13 expression constitute pivotal factors governing the malignancy of breast cancer.

Low-Dose Ionizing Radiation-Crosslinking Immunoprecipitation (LDIR-CLIP) Identified Irradiation-Sensitive RNAs for RNA-Binding Protein HuR-Mediated Decay.

Although ionizing radiation (IR) is widely used for therapeutic and research purposes, studies on low-dose ionizing radiation (LDIR) are limited compared with those on other IR approaches, such as high-dose gamma irradiation and ultraviolet irradiation. High-dose IR affects DNA damage response and nucleotide-protein crosslinking, among other processes; however, the molecular consequences of LDIR have been poorly investigated. Here, we developed a method to profile RNA species crosslinked to an RNA-binding protein, namely, human antigen R (HuR), using LDIR and high-throughput RNA sequencing. The RNA fragments isolated via LDIR-crosslinking and immunoprecipitation sequencing were crosslinked to HuR and protected from RNase-mediated digestion. Upon crosslinking HuR to target mRNAs such as PAX6, ZFP91, NR2F6, and CAND2, the transcripts degraded rapidly in human cell lines. Additionally, PAX6 and NR2F6 downregulation mediated the beneficial effects of LDIR on cell viability. Thus, our approach provides a method for investigating post-transcriptional gene regulation using LDIR.

Health-promoting behavior among undergraduate students in the COVID-19 era: Its association with problematic use of social media, social isolation, and online health information-seeking behavior.

OBJECTIVE: To examine the association between problematic use of social media, online health information-seeking, social isolation, and health-promoting behaviors among Korean undergraduate students. METHODS: In total, 178 undergraduate students participated in this study. A multiple linear regression analysis was performed. RESULTS: Predictors of health-promoting behaviors included overall time spent on social media, problematic social media use, social isolation, and online information-seeking, explaining 33.5 % of the variance in health-promoting behaviors. CONCLUSION: Prolonged social media use and social isolation negatively affected undergraduate students' health-promoting behaviors, while online information-seeking positively affected them. Nurses should assist young adults in improving health-promoting behaviors by preventing problematic social media uses, reducing social isolation, and strengthening their online health information-seeking ability.

Identification and Interpretation of eQTL and eGenes for Hodgkin Lymphoma Susceptibility.

Genome-wide association studies (GWAS) have revealed approximately 100 genomic signals associated with Hodgkin lymphoma (HL); however, their target genes and underlying mechanisms causing HL susceptibility remain unclear. In this study, transcriptome-wide analysis of expression quantitative trait loci (eQTL) was conducted to identify target genes associated with HL GWAS signals. A mixed model, which explains polygenic regulatory effects by the genomic covariance among individuals, was implemented to discover expression genes (eGenes) using genotype data from 462 European/African individuals. Overall, 80 eGenes were identified to be associated with 20 HL GWAS signals. Enrichment analysis identified apoptosis, immune responses, and cytoskeletal processes as functions of these eGenes. The eGene of rs27524 encodes ERAP1 that can cleave peptides attached to human leukocyte antigen in immune responses; its minor allele may help Reed-Sternberg cells to escape the immune response. The eGene of rs7745098 encodes ALDH8A1 that can oxidize the precursor of acetyl-CoA for the production of ATP; its minor allele may increase oxidization activity to evade apoptosis of pre-apoptotic germinal center B cells. Thus, these minor alleles may be genetic risk factors for HL susceptibility. Experimental studies on genetic risk factors are needed to elucidate the underlying mechanisms of HL susceptibility and improve the accuracy of precision oncology.

Estimation of Total Cost Required in Controlling COVID-19 Outbreaks by Financial Incentives.

In this article, we present a Monte Carlo simulation (MCS) to estimate the total cost required to control the spread of the COVID-19 pandemic by financial incentives. One of the greatest difficulties in controlling the spread of the COVID-19 pandemic is that most infected people are not identified and can transmit the virus to other people. Therefore, there is an urgent need to rapidly identify and isolate the infected people to avoid the further spread of COVID-19. To achieve this, we can consider providing a financial incentive for the people who voluntarily take the COVID-19 test and test positive. To prevent the abuse of the financial incentive policy, several conditions should be satisfied to receive the incentive. For example, an incentive is offered only if the recipients know who infected them. Based on the data obtained from epidemiological investigations, we calculated an estimated total cost of financial incentives for the policy by generating various possible infection routes using the estimated parameters and MCS. These results would help public health policymakers implement the proposed method to prevent the spread of the COVID-19 pandemic. In addition, the incentive policy can support various preparations such as hospital bed preparation, vaccine development, and so forth.

Role of senescent tumor cells in building a cytokine shield in the tumor microenvironment: mathematical modeling.

Cellular senescence can induce dual effects (promotion or inhibition) on cancer progression. While immune cells naturally respond and migrate toward various chemotactic sources from the tumor mass, various factors including senescent tumor cells (STCs) in the tumor microenvironment may affect this chemotactic movement. In this work, we investigate the mutual interactions between the tumor cells and the immune cells that either inhibit or facilitate tumor growth by developing a mathematical model that consists of taxis-reaction-diffusion equations and receptor kinetics for the key players in the interaction network. We apply a mathematical model to a transwell Boyden chamber invasion assay used in the experiments to illustrate that STCs can play a pivotal role in negating immune attack through tight regulation of intra- and extra-cellular signaling molecules. In particular, we show that senescent tumor cells in cell cycle arrest can block intratumoral infiltration of CD8+ T cells by secreting a high level of CXCL12, which leads to significant reduction its receptors, CXCR4, on T cells, and thus impaired chemotaxis. The predictions of nonlinear responses to CXCL12 were in good agreement with experimental data. We tested several hypotheses on immune-tumor interactions under various biochemical conditions in the tumor microenvironment and developed new concepts for anti-tumor strategies targeting senescence induced immune impairment.

Exploration of deep learning models for real-time monitoring of state and performance of anaerobic digestion with online sensors.

The immediate response to the state disturbances of anaerobic digestion is essential to prevent anaerobic digestion failure. However, frequent monitoring of the state and performance of anaerobic digestion is challenging. Thus, deep learning models were investigated to predict the state and performance variables from online sensor data. The online sensor data, including pH, electric conductivity, and oxidation-reduction potential, were used as the input features to build deep learning models. The state and performance data measured offline were used as the labels. The model performance was compared for several deep learning models of convolutional neural network (CNN), long short-term memory (LSTM), dense layer, and their combinations. The combined model of CNN and bidirectional LSTM was robust and well-generalized in predicting the state and performance variables (R2 = 0.978, root mean square error = 0.031). The combined model is an excellent soft sensor for monitoring the state and performance of anaerobic digestion from electrochemical sensors.

An Explicit Adaptive Finite Difference Method for the Cahn-Hilliard Equation.

In this study, we propose an explicit adaptive finite difference method (FDM) for the Cahn-Hilliard (CH) equation which describes the process of phase separation. The CH equation has been successfully utilized to model and simulate diverse field applications such as complex interfacial fluid flows and materials science. To numerically solve the CH equation fast and efficiently, we use the FDM and time-adaptive narrow-band domain. For the adaptive grid, we define a narrow-band domain including the interfacial transition layer of the phase field based on an undivided finite difference and solve the numerical scheme on the narrow-band domain. The proposed numerical scheme is based on an alternating direction explicit (ADE) method. To make the scheme conservative, we apply a mass correction algorithm after each temporal iteration step. To demonstrate the superior performance of the proposed adaptive FDM for the CH equation, we present two- and three-dimensional numerical experiments and compare them with those of other previous methods.

Antagonistic regulatory effects of a single cis-acting expression quantitative trait locus between transcription and translation of the MRPL43 gene.

BACKGROUND: Heterogeneity of expression quantitative trait locus (eQTL) effects have been shown across gene expression processes. Knowledge on how to produce the heterogeneity is quite limited. This study aims to examine fluctuations in differential gene expression by alleles of sequence variants across expression processes. RESULTS: Genome-wide eQTL analyses with transcriptome-wide gene expression data revealed 20 cis-acting eQTLs associated simultaneously with mRNA expression, ribosome occupancy, and protein abundance. A 97 kb-long eQTL signal for mitochondrial ribosomal protein L43 (MRPL43) covered the gene, showing a heterogeneous effect size on gene products across expression stages. One allele of the eQTL was associated with increased mRNA expression and ribosome occupancy but decreased protein abundance. We examined the heterogeneity and found that the eQTL can be attributed to the independent functions of three nucleotide variants, with a strong linkage. NC_000010.11:g.100987606G > T, upstream of MRPL43, may regulate the binding affinity of transcription factors. NC_000010.11:g.100986746C > G, 3 bp from an MRPL43 splice donor site, may alter the splice site. NC_000010.11:g.100978794A > G, in the isoform with a long 3'-UTR, may strengthen the binding affinity of the microRNA. Individuals with the TGG haplotype at these three variants had higher levels of mRNA expression and ribosome occupancy than individuals with the GCA haplotype but lower protein levels, producing the flipped effect throughout the expression process. CONCLUSIONS: These findings suggest that multiple functional variants in a linkage exert their regulatory functions at different points in the gene expression process, producing a complexity of single eQTLs.

Mixed model-based eQTL analysis reveals lncRNAs associated with regulation of genes involved in sex determination and spermatogenesis: The key to understanding human gender imbalance.

BACKGROUND: An imbalance in the prenatal sex ratio in humans may be due to several factors affecting sperm physiology, including genetic features. In this study, we conducted a transcriptome-wide analysis of expression quantitative trait loci (eQTLs) to identify target genes associated with previously described QTLs associated with gender imbalance. METHODS: A mixed model explaining polygenic effects by genomic covariance among individuals was used to identify the eQTLs using gene expression and genotype data from 462 European/African individuals. RESULTS: Eight eGenes were associated with four QTLs (P < 4.00 × 10-5), with strong associations found (P < 4.00 × 10-8) between rs2485007 and eGenes ANKRD26P3 (P = 3.40 × 10-9) and LINC00421 (P = 1.35 × 10-9). ANKRD26P3 and LINC00421 are both lncRNAs associated with the control of testis-dominant genes PELP1, TAF15, NANOG, TEX14, TCF3, ZNF433, ZNF555, TEX37, FATE1, TCP11, and CYLC2 and Y-linked genes SRY and ZFY, as well as several genes with roles in spermatogenesis (ODF1, SPATC1, SPATA3, SPATA31E1, SPERT, SPATA16, MOSPD1, SPATA24, and SPO11) and sex determination (SOX family genes). CONCLUSIONS: The above eGenes contribute directly or indirectly to gene regulation for sex determination and spermatogenesis, thereby serving as important functional clues for gender-biased selection.