Expression Quantitative Trait Loci Research Articles

Powerful mapping of cis-genetic effects on gene expression across diverse populations reveals novel disease-critical genes.

While disease-associated variants identified by genome-wide association studies (GWAS) most likely regulate gene expression levels, linking variants to target genes is critical to determining the functional mechanisms of these variants. Genetic effects on gene expression have been extensively characterized by expression quantitative trait loci (eQTL) studies, yet data from non-European populations is limited. This restricts our understanding of disease to genes whose regulatory variants are common in European populations. While previous work has leveraged data from multiple populations to improve GWAS power and polygenic risk score (PRS) accuracy, multi-ancestry data has not yet been used to better estimate cis-genetic effects on gene expression. Here, we present a new method, Multi-Ancestry Gene Expression Prediction Regularized Optimization (MAGEPRO), which constructs robust genetic models of gene expression in understudied populations or cell types by fitting a regularized linear combination of eQTL summary data across diverse cohorts. In simulations, our tool generates more accurate models of gene expression than widely-used LASSO and the state-of-the-art multi-ancestry PRS method, PRS-CSx, adapted to gene expression prediction. We attribute this improvement to MAGEPRO's ability to more accurately estimate causal eQTL effect sizes (p < 3.98 × 10-4, two-sided paired t-test). With real data, we applied MAGEPRO to 8 eQTL cohorts representing 3 ancestries (average n = 355) and consistently outperformed each of 6 competing methods in gene expression prediction tasks. Integration with GWAS summary statistics across 66 complex traits (representing 22 phenotypes and 3 ancestries) resulted in 2,331 new gene-trait associations, many of which replicate across multiple ancestries, including PHTF1 linked to white blood cell count, a gene which is overexpressed in leukemia patients. MAGEPRO also identified biologically plausible novel findings, such as PIGB, an essential component of GPI biosynthesis, associated with heart failure, which has been previously evidenced by clinical outcome data. Overall, MAGEPRO is a powerful tool to enhance inference of gene regulatory effects in underpowered datasets and has improved our understanding of population-specific and shared genetic effects on complex traits.

Genetic Variation and Regulation of MICA Alters Natural Killer Cell-Mediated Immunosurveillance in Early-Onset Colorectal Cancer.

The incidence of colorectal cancer (CRC) among individuals under age 50, or early-onset CRC (EOCRC), has been rising over the past few decades for unclear reasons, and the etiology of the disease remains largely unknown. Known genetic risk factors do not explain this increase, pointing to possible environmental and as-yet unidentified genetic contributors and their interactions. Previous research linked genetic variation on chromosome 6 to increased CRC risk. This region harbors multiple immune genes, including the gene encoding Major Histocompatibility Complex (MHC) class I polypeptide-related sequence A (MICA). MICA is a polygenic ligand for the Natural Killer Group 2D receptor (NKG2D), a receptor expressed on Natural Killer (NK) cells and other lymphocytes. Given that intra-tumoral NK cell infiltration correlates with favorable CRC outcomes, we hypothesized that germline genetic variation in MICA could influence CRC risk. In a discovery set of 40,125 cases and controls, we show that the minor G allele at Chr6:31373718C>G (hg19) is associated with increased risk for CRC (odds ratio (OR) = 1.09, 95% confidence interval (CI) 1.04 - 1.15, p = 0.0009). The effect is stronger in EOCRC (OR = 1.26, 95% CI 1.08 - 1.44, p = 0.0023) than in those 50 and over (OR = 1.07, 95% CI 1.02 - 1.13; p = 0.012) (Ratio of ORs = 1.32, 95% CI 1.14 - 1.52, p = 0.0002). In an independent validation set of 77,983 cases and controls, the adjusted interaction by age-of-onset was significant at OR = 1.15 (95% CI 1.03 - 1.34, p = 0.0150) with a higher risk in EOCRC. Expression quantitative trait locus analysis in normal colonic epithelia showed that MICA RNA expression decreases linearly with each additional copy of the minor G allele (p = 3.345 × 10e-18). Bulk RNA analysis of the tumor immune microenvironment revealed that tumors from patients with CG or GG genotypes have lower resting and activated NK cell infiltration as compared to tumors from patients with CC genotype. Multiplex immunofluorescence analysis demonstrated that patients with a G allele (i.e. CG or GG genotype, but not CC genotype) have a statistically significant decrease in the number of NK cells in tumor compared to adjacent normal colonic mucosa. Taken together, population-based epidemiologic, molecular, genetic, cellular and immunologic evidence demonstrate that MICA genotype is associated with increased risk of EOCRC and reduced number of NK cells in colorectal tumors, suggesting that patients with a G allele have altered NK cell-mediated immunosurveillance. These novel findings suggest that EOCRC may have a previously unrecognized innate immune-mediated etiology which merits further investigation.

Integrating transcriptomics, eQTL, and Mendelian randomization to dissect monocyte roles in severe COVID-19 and gout flare.

There are considerable similarities between the pathophysiology of gout flare and the dysregulated inflammatory response in severe COVID-19 infection. Monocytes are the key immune cells involved in the pathogenesis of both diseases. Therefore, it is critical to elucidate the molecular basis of the function of monocytes in gout and COVID-19 in order to develop more effective therapeutic approaches. The single-cell RNA sequencing (scRNA-seq), large-scale genome-wide association studies (GWAS), and expression quantitative trait loci (eQTL) data of gout and severe COVID-19 were comprehensively analyzed. Cellular heterogeneity and intercellular communication were identified using the scRNA-seq datasets, and the monocyte-specific differentially expressed genes (DEGs) between COVID-19, gout and normal subjects were screened. In addition, the correlation of the DEGs with severe COVID-19 and gout flare was analyzed through GWAS statistics and eQTL data. The scRNA-seq analysis exhibited that the proportion of classical monocytes was increased in both severe COVID-19 and gout patient groups compared to healthy controls. Differential expression analysis and MR analysis showed that NLRP3 was positively associated with the risk of severe COVID-19 and involved 11 SNPs, of which rs4925547 was not significantly co-localized. In contrast, IER3 was positively associated with the risk of gout and involved 9 SNPs, of which rs1264372 was significantly co-localized. Monocytes have a complex role in gout flare and severe COVID-19, which underscores the potential mechanisms and clinical significance of the interaction between the two diseases.

Potentially functional variants of PARK7 and DDR2 in ferroptosis-related genes predict survival of non-small cell lung cancer patients.

Ferroptosis, a form of regulated cell death, is characterized by iron-dependent lipid peroxidation. It is recognized increasingly for its pivotal role in both cancer development and the response to cancer treatments. We assessed associations between 370,027 single-nucleotide polymorphisms (SNPs) within 467 ferroptosis-related genes and survival of non-small cell lung cancer (NSCLC) patients. Data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial served as our discovery dataset, while the Harvard Lung Cancer Susceptibility Study used as our validation dataset. For SNPs that remained statistically significantly associated with overall survival (OS) in both datasets, we employed a multivariable stepwise Cox proportional hazards regression model with the PLCO dataset. Ultimately, two independent SNPs, PARK7 rs225120 C>T and DDR2 rs881127 T>C, were identified with adjusted hazard ratios of 1.32 (95% confidence interval = 1.15-1.52, p = .0001) and 1.34 (95% confidence interval = 1.09-1.64, p = .006) for OS, respectively. We aggregated these two SNPs into a genetic score reflecting the number of unfavorable genotypes (NUG) in further multivariable analysis, revealing a noteworthy association between increased NUG and diminished OS (ptrend = .001). Additionally, an expression quantitative trait loci analysis indicated that PARK7 rs225120T genotypes were significantly associated with higher PARK7 mRNA expression levels in both whole blood and normal lung tissue. Conversely, DDR2 rs881127C genotypes were significantly associated with lower DDR2 mRNA expression levels in normal lung tissue. Our findings suggest that genetic variants in the ferroptosis-related genes PARK7 and DDR2 are associated with NSCLC survival, potentially through their influence on gene expression levels.

Clinical application of sparse canonical correlation analysis to detect genetic associations with cortical thickness in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by cerebral cortex atrophy. In this study, we used sparse canonical correlation analysis (SCCA) to identify associations between single nucleotide polymorphisms (SNPs) and cortical thickness in the Korean population. We also investigated the role of the SNPs in neurological outcomes, including neurodegeneration and cognitive dysfunction. We recruited 1125 Korean participants who underwent neuropsychological testing, brain magnetic resonance imaging, positron emission tomography, and microarray genotyping. We performed group-wise SCCA in Aβ negative (-) and Aβ positive (+) groups. In addition, we performed mediation, expression quantitative trait loci, and pathway analyses to determine the functional role of the SNPs. We identified SNPs related to cortical thickness using SCCA in Aβ negative and positive groups and identified SNPs that improve the prediction performance of cognitive impairments. Among them, rs9270580 was associated with cortical thickness by mediating Aβ uptake, and three SNPs (rs2271920, rs6859, rs9270580) were associated with the regulation of CHRNA2, NECTIN2, and HLA genes. Our findings suggest that SNPs potentially contribute to cortical thickness in AD, which in turn leads to worse clinical outcomes. Our findings contribute to the understanding of the genetic architecture underlying cortical atrophy and its relationship with AD.

Plasma proteomics reveals the potential causal impact of extracellular matrix proteins on abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is a common and life-threatening vascular disease. Genetic studies have identified numerous associated loci, many potentially encoding plasma proteins. However, the causal effects of plasma proteins on AAA have not been thoroughly studied. We used genetic causal inference approaches to identify plasma proteins that have a potential causal impact on AAA. Causal inference was performed using two-sample Mendelian randomization (MR). For AAA, we utilized recently published summary statistics from a multi-population genome-wide association (GWAS) meta-analysis including 39,221 individuals with, and 1,086,107 individuals without AAA from 14 cohorts. We used protein quantitative trait loci (pQTLs) identified in two large-scale plasma-proteomics studies (deCODE and UKB-PPP) to generate genetic instruments. We tested 2,783 plasma proteins for possible causal effects on AAA using two-sample MR with inverse variance weighting and common sensitivity analyses to evaluate the MR assumptions. Bayesian colocalization and gene ontology (GO) enrichment analyses provided additional insights. MR identified 90 plasma proteins associated with AAA at FDR<0.05, with 25 supported by colocalization analysis. Among those supported by both MR and colocalization were previously experimentally validated proteins such as PCSK9 (OR 1.3; 95%CI 1.2-1.4; P<1e-10), LTBP4 (OR 3.4; 95%CI 2.6-4.6; P<1e-10) and COL6A3 (OR 0.6; 95%CI 0.5-0.7; P<1e-6). GO analysis revealed enrichment of proteins found in extracellular matrix (ECM, OR 7.8; P<1e-4), some with maximal mRNA levels in aortic tissue. Bi-directional MR suggested plasma level changes were not caused by liability to AAA itself. We then investigated whether variants responsible for expression changes in the aorta also influenced plasma levels and AAA risk. Colocalization analysis showed that an aortic expression quantitative trait locus (eQTL) for COL6A3, and a splicing quantitative trait locus (sQTL) for LTBP4 colocalized with their respective plasma pQTLs and AAA signals (posterior probabilities 0.84 and 0.89, respectively). Our results highlight proteins and pathways with potential causal effects on AAA, providing a foundation for future functional experiments. These findings suggest a possible causal pathway whereby genetic variation affecting ECM proteins expressed in the aortic wall cause their levels to change in blood plasma, influencing development of AAA.

Abstract C051: Impact of population pharmacogenomics on cisplatin-induced neurotoxicities

Abstract Background: Studies have shown that taxane-treated breast cancer patients with African (AFR) ancestry experience worse peripheral sensory neuropathy (PSN), while African American vincristine-treated leukemia patients have less PSN than Europeans (EUR). We hypothesized that ancestral disparities may exist for cisplatin-induced neurotoxicities and may relate to differences in allele frequency and resultant gene expression of SNPs associated with these toxicities. Methods: In our Platinum Study of 1680 genotyped testicular cancer survivors (TCS), multidimensional scaling scores were anchored by the 1000 Genomes population to classify geographic ancestry. PSN (EORTC-CIPN20) and other toxicities plus clinical and lifestyle variables were examined for associations between geographic ancestry and phenotypes using logistic regression and Wilcoxon rank sum test. Genotyped SNPs with Fst &amp;gt; 0.25 in 1000 Genomes were identified and evaluated with GTEx data to find expression or splicing quantitative trait loci in nerve/brain tissue or for cisplatin-associated candidate genes, across all tissues. LDmatrix was used to find linkage disequilibrium. If a block of SNPs had R2 &amp;gt; 0.75, one independent SNP was kept for association analysis. Logistic regression with age at questionnaire completion and 10 genetic principal components as covariates was used to calculate the association between genotype and toxicity. Results: In an analysis of patients who received 400-450 mg/m2 of cisplatin including EUR (n=681), Asian (ASN) axis (n=44) and AFR (n=13), the odds ratio (OR) for any neuropathy vs. none in the AFR vs. EUR was 7.8 (P=0.049) and in the AFR vs. ASN axis (including East Asian 1000 Genomes populations) was 10.0 (P=0.034). TCS with AFR ancestry had significantly more vertigo. There were 19,874 SNPs for analysis from the genome-wide approach and 118 SNPs from the candidate gene approach. While associations between genotype and toxicity did not reach Bonferroni threshold, some SNPs had p-values in the 10-5 range. For PSN, one SNP had increased frequency of a risk allele in the AFR population while the other had increased frequency of a protective allele, while for vertigo, four SNPs had increased frequency of risk alleles in the AFR population. Of interest was rs34904346, in which the TT vs. AA genotype had an OR of 1.9 (p=2x10-5) for any vs. no PSN, with the T allele having 90% frequency in AFR ancestry patients versus ∼60% in other populations. This SNP and three other independent SNPs associated with PSN incidence (p∼10-3) are eQTLs for RNF24 in nerve tissue, which interacts with membrane proteins that regulate intracellular calcium levels. Conclusions: We show preliminary evidence for the role of differing risk allele frequencies across populations in explaining disparities in cisplatin-induced PSN and vertigo, likely in combination with structural and environmental factors. Genotyping risk alleles could customize dosing, treatment, and post-treatment monitoring to benefit all cisplatin-treated patients. Citation Format: Swetha Nakshatri, Paul C. Dinh, Darren R. Feldman, Robert J. Hamilton, Chunkit Fung, David J. Vaughn, Christian Kollmannsberger, Robert Huddart, Lawrence H. Einhorn, Nancy J. Cox, Lois B. Travis, Eileen Dolan. Impact of population pharmacogenomics on cisplatin-induced neurotoxicities [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C051.

GsQTL: Associating genetic risk variants with gene sets by exploiting their shared variability.

To investigate the functional significance of genetic risk loci identified through genome-wide association studies (GWASs), genetic loci are linked to genes based on their capacity to account for variation in gene expression, resulting in expression quantitative trait loci (eQTL). Following this, gene set analyses are commonly used to gain insights into functionality. However, the efficacy of this approach is hampered by small effect sizes and the burden of multiple testing. We propose an alternative approach: instead of examining the cumulative associations of individual genes within a gene set, we consider the collective variation of the entire gene set. We introduce the concept of gene set QTL (gsQTL), and show it to be more adept at identifying links between genetic risk variants and specific gene sets. Notably, gsQTL experiences less susceptibility to inflation or deflation of significant enrichments compared with conventional methods. Furthermore, we demonstrate the broader applicability of shared variability within gene sets. This is evident in scenarios such as the coordinated regulation of genes by a transcription factor or coordinated differential expression.

Allelic effects on KLHL17 expression likely mediated by JunB/D underlie a PDAC GWAS signal at chr1p36.33.

Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the U.S. Both rare and common germline variants contribute to PDAC risk. Here, we fine-map and functionally characterize a common PDAC risk signal at 1p36.33 (tagged by rs13303010) identified through a genome wide association study (GWAS). One of the fine-mapped SNPs, rs13303160 (r2=0.93 in 1000G EUR samples, OR=1.23, P value=2.74x10-9) demonstrated allele-preferential gene regulatory activity in vitro and allele-preferential binding of JunB and JunD in vitro and in vivo. Expression Quantitative Trait Locus (eQTL) analysis identified KLHL17 as a likely target gene underlying the signal. Proteomic analysis identified KLHL17 as a member of the Cullin-E3 ubiquitin ligase complex in PDAC-derived cells. In silico differential gene expression analysis of the GTExv8 pancreas data suggested an association between lower KLHL17 (risk associated) and pro-inflammatory pathways. We hypothesize that KLHL17 may mitigate inflammation by recruiting pro-inflammatory proteins for ubiquitination and degradation thereby influencing PDAC risk.

Deciphering the functional impact of Alzheimer's Disease-associated variants in resting and proinflammatory immune cells.

Genome-wide association studies have identified loci associated with Alzheimer's Disease (AD), but identifying the exact causal variants and genes at each locus is challenging due to linkage disequilibrium and their largely non-coding nature. To address this, we performed a massively parallel reporter assay of 3,576 AD-associated variants in THP-1 macrophages in both resting and proinflammatory states and identified 47 expression-modulating variants (emVars). To understand the endogenous chromatin context of emVars, we built an activity-by-contact model using epigenomic maps of macrophage inflammation and inferred condition-specific enhancer-promoter pairs. Intersection of emVars with enhancer-promoter pairs and microglia expression quantitative trait loci allowed us to connect 39 emVars to 76 putative AD risk genes enriched for AD-associated molecular signatures. Overall, systematic characterization of AD-associated variants enhances our understanding of the regulatory mechanisms underlying AD pathogenesis.

CD4+ Effective Memory T Cell Markers GBP2 and LAG3 Are Risk Factors for PTB and COVID-19 Infection: A Study Integrating Single-Cell Expression Quantitative Trait Locus and Mendelian Randomization Analyses.

Observational studies indicate that variations in peripheral blood mononuclear cell (PBMC) subsets are associated with an increased risk of pulmonary tuberculosis (PTB) and coronavirus disease 2019 (COVID-19), but causal validation is lacking. Here, we combined single-cell expression quantitative trait locus (sc-eQTL) and two-sample mendelian randomization (MR) analyses to elucidate the causal relationship between PBMC subsets and the occurrence of PTB and COVID-19 and verified by RT-qPCR. We observed an increase in the CD4+ Effective Memory T Cell (CD4+ TEM) cluster in both PTB and COVID-19 patients according to the single-cell transcriptional landscape of PBMC. Through MR analysis using an inverse variance weighted (IVW) method, we found strong evidence of positive correlations between CD4+ TEM cell markers (GBP2, TRAV1-2, and ODF2L) and PTB, and between markers (LAG3 and SLFN5) and COVID-19, especially highlighted by lead eQTL-SNPs of GBP2 (rs2256752, p = 4.76321 × 10-15) and LAG3 (rs67706382, p = 6.16× 10-16). Similar results were observed in validation sets, and no pleiotropy was detected in sensitivity analyses including weighted median (WM), MR-Egger, MR-pleiotropy residual sum and outlier, and leave-one-out analyses (all p > 0.05). We visualized the colocalization of marker-eQTLs and markers of PTB and COVID-19 genome-wide association study (GWAS) associations. Based on CellChat analyses, monocytes communicated predominantly with CD4+ TEM cells positively expressing PTB markers (GBP2, TRAV1-2, and ODF2L) and COVID-19 markers (LAG3 and SLFN5) in both PTB and COVID-19. Our data suggest a causal effect between two key CD4+ TEM cell markers (GBP2 and LAG3) and the risk for PTB and COVID-19 infection. Our findings provide novel insights into the biological mechanism for PTB and COVID-19 infection, but future single-cell studies are necessary to further enhance understanding of this find.

Genomic study of taste perception genes in African Americans reveals SNPs linked to Alzheimer’s disease

While previous research has shown the potential links between taste perception pathways and brain-related conditions, the area involving Alzheimer’s disease remains incompletely understood. Taste perception involves neurotransmitter signaling, including serotonin, glutamate, and dopamine. Disruptions in these pathways are implicated in neurodegenerative diseases. The integration of olfactory and taste signals in flavor perception may impact brain health, evident in olfactory dysfunction as an early symptom in neurodegenerative conditions. Shared immune response and inflammatory pathways may contribute to the association between altered taste perception and conditions like neurodegeneration, present in Alzheimer’s disease. This study consists of an exploration of expression-quantitative trait loci (eQTL), utilizing whole-blood transcriptome profiles, of 28 taste perception genes, from a combined cohort of 475 African American subjects. This comprehensive dataset was subsequently intersected with single-nucleotide polymorphisms (SNPs) identified in Genome-Wide Association Studies (GWAS) of Alzheimer’s Disease (AD). Finally, the investigation delved into assessing the association between eQTLs reported in GWAS of AD and the profiles of 741 proteins from the Olink Neurological Panel. The eQTL analysis unveiled 3,547 statistically significant SNP-Gene associations, involving 412 distinct SNPs that spanned all 28 taste genes. In 17 GWAS studies encompassing various traits, a total of 14 SNPs associated with 12 genes were identified, with three SNPs consistently linked to Alzheimer’s disease across four GWAS studies. All three SNPs demonstrated significant associations with the down-regulation of TAS2R41, and two of them were additionally associated with the down-regulation of TAS2R60. In the subsequent pQTL analysis, two of the SNPs linked to TAS2R41 and TAS2R60 genes (rs117771145 and rs10228407) were correlated with the upregulation of two proteins, namely EPHB6 and ADGRB3. Our investigation introduces a new perspective to the understanding of Alzheimer's disease, emphasizing the significance of bitter taste receptor genes in its pathogenesis. These discoveries set the stage for subsequent research to delve into these receptors as promising avenues for both intervention and diagnosis. Nevertheless, the translation of these genetic insights into clinical practice requires a more profound understanding of the implicated pathways and their pertinence to the disease's progression across diverse populations.

Genetic regulation of microRNAs in the older adult brain and their contribution to neuropsychiatric conditions.

MicroRNAs are essential post-transcriptional regulators of gene expression and involved in many biological processes; however, our understanding of their genetic regulation and role in brain illnesses is limited. Here, we mapped brain microRNA expression quantitative trait loci (miR-QTLs) using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex (dlPFC) samples of 604 older adult donors of European ancestry. miR-QTLs were identified for 224 miRNAs (48% of 470 tested miRNAs) at false discovery rate < 1%. We found that miR-QTLs were enriched in brain promoters and enhancers, and that intragenic miRNAs often did not share QTLs with their host gene. Additionally, we integrated the brain miR-QTLs with results from 16 GWAS of psychiatric and neurodegenerative diseases using multiple independent integration approaches and identified four miRNAs that contribute to the pathogenesis of bipolar disorder, major depression, post-traumatic stress disorder, schizophrenia, and Parkinson's disease. This study provides novel insights into the contribution of miRNAs to the complex biological networks that link genetic variation to disease.

Genome-Wide Analysis Reveals Copy Number Variant Gene TGFBR3 Regulates Pig Back Fat Deposition.

BFT is closely related to meat quality and lean meat percentage in pigs. The BFT traits of European LW pigs significantly differ from those of Chinese indigenous fatty MZ pigs. CNV is a prevalent genetic variation that plays an important role in economically important traits in pigs. However, the potential contribution of CNV to BFT in LW and MZ pigs remains unclear. In this study, whole-genome CNV detection was performed using next-generation sequencing data from LW and MZ pigs, and transcriptome data from back fat tissue of 180-day-old LW and MZ pigs were integrated for expression quantitative trait loci (eQTL) analysis. We identified a copy number variation in the TGFBR3 gene associated with BFT, showing a dose effect between the genome and transcriptome levels of the TGFBR3 gene. In porcine preadipocytes, TGFBR3 expression continuously increased during differentiation. Knockdown of TGFBR3 using specific siRNA inhibited preadipocyte differentiation and proliferation. Our study provides insights into the genetic regulation of pork quality and offers a theoretical basis for improving carcass quality by modulating BFT in pigs.

Validation and identification of new QTLs for plant and fruit developmental and composition traits in eggplant under low N conditions

Enhancing plant adaptation to low input conditions is a fundamental goal for implementing sustainable agriculture. In the present study, two eggplant (Solanum melongena) accessions (MEL1 and MEL5), two introgression lines (ILs) derived from eggplant wild relatives S. dasyphyllum (IL-M1-D1) and S. insanum (IL-M5-I9), and a heterozygous version of this last IL (ILHet-M5-I9), along with hybrids among them were evaluated under low N (LN) conditions. IL-M1-D1 carries an introgressed fragment of 4.9 Mb in homozygosis from S. dasyphyllum on chromosome 2, while IL-M5-I9 and ILHet-M5-I9 carry an introgression of 21.5 Mb on chromosome 9 in homozygosis and heterozygosis, respectively, from S. insanum. Multiple quantitative trait loci (QTLs) for several traits of interest were associated with both introgressions under LN conditions in a previous study with segregating advanced backcrosses. Here we evaluated the performance of these materials for 22 agronomic and developmental traits under low N fertilization (LN) conditions. Hybrids with the ILs enabled the study of genetic background effects on QTLs expression. The materials evaluated showed a significant phenotypic variation, particularly within hybrids segregating for the introgression from S. insanum in chromosome 9. Statistical analysis revealed no significant differences among hybrids carrying or not the introgression on chromosome 2 of S. dasyphyllum, and only slight differences were observed between the IL-M1-D1 and its recurrent parent S. melongena MEL1, suggesting a limited impact of this introgression on chromosome 2 on the phenotype variation. However, the differences observed between IL-M5-I9 and its recurrent parent S. melongena MEL5, together with the association between genotypic and phenotypic variation in hybrids segregating for this introgression, allowed the identification of 13 QTLs on chromosome 9. These results successfully validated the previously identified QTLs for flavonol content in leaves, nitrogen balanced index, fruit mean weight, and nitrogen content in leaves and, also revealed nine new QTLs associated with the introgressed genomic region in chromosome 9. This study emphasizes the influence of environmental conditions, genotypes, and genetic backgrounds on the phenotypic expression of eggplant QTLs introgressed from wild relatives and highlights the importance of QTL validation. These findings contribute valuable insights for developing new eggplant cultivars for a more sustainable agriculture, particularly with adaptation to LN conditions.

Identification of genetic association between mitochondrial dysfunction and knee osteoarthritis through integrating multi-omics: a summary data-based Mendelian randomization study

ObjectiveAssociation between mitochondrial dysfunction and osteoarthritis (OA) has been consistently investigated, yet their genetic association remains obscure. In this study, mitochondrial-related genes were used as instrumental variables to proxy for mitochondrial dysfunction, and summary data of knee OA (KOA) were used as outcome to examine their genetic association.MethodsWe obtained 1136 mitochondrial-related genes from the human MitoCarta3.0 database. Genetic proxy instruments for mitochondrial-related genes from studies of corresponding gene expression (n = 31,684) and protein (n = 35,559) quantitative trait locus (eQTLs and pQTLs), respectively. Aggregated data for KOA (62,497 KOA cases and 333,557 controls) were extracted from the largest OA genome-wide association study (GWAS). We integrated QTL data with KOA GWAS data to estimate their genetic association using summary data-based Mendelian randomization analysis (SMR). Additionally, we implemented Bayesian colocalization analysis to reveal whether suggestive mitochondrial-related genes and KOA were driven by a same genetic variant. Finally, to validate the primary findings, replication study (24,955 cases and 378,169 controls) and multi-SNP-based SMR (SMR-multi) test was performed.ResultsThrough SMR analysis, we found that the expression levels of 2 mitochondrial-related genes were associated with KOA risk. Specifically, elevated gene expression levels of the IMMP2L (odds ratio [OR] = 1.056; 95% confidence interval [CI] = 1.030–1.082; P-FDR = 0.004) increased the risk of KOA. Conversely, increased gene expression levels of AKAP10 decreased the risk of KOA (OR = 0.955; 95% CI, 0.934–0.977; P-FDR = 0.019). Colocalization analysis demonstrated that AKAP10 (PP.H4 = 0.84) and IMMP2L (PP.H4 = 0.91) shared the same genetic variant with KOA. In addition, consistent results were found in replication study and SMR-multi test, further demonstrating the reliability of our findings.ConclusionsIn summary, our analyses revealed the genetic association between mitochondrial dysfunction proxied by mitochondrial-related genes and KOA, providing new insight into potential pathogenesis of KOA. Furthermore, these identified candidate genes offer the possibility of clinical drug target development for KOA.Key points• This is the first SMR study to explore the genetic association between mitochondrial dysfunction proxied by mitochondrial-related genes and KOA.• Sufficient evidence to support genetic association between the expression levels of AKAP10 and IMMP2L, and KOA• Our MR analysis may provide novel new insight into potential pathogenesis of KOA.• These identified candidate genes offer the possibility of clinical drug target development for KOA

Direct targets of MEF2C are enriched for genes associated with schizophrenia and cognitive function and are involved in neuron development and mitochondrial function.

Myocyte Enhancer Factor 2C (MEF2C) is a transcription factor that plays a crucial role in neurogenesis and synapse development. Genetic studies have identified MEF2C as a gene that influences cognition and risk for neuropsychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia (SCZ). Here, we investigated the involvement of MEF2C in these phenotypes using human-derived neural stem cells (NSCs) and glutamatergic induced neurons (iNs), which represented early and late neurodevelopmental stages. For these cellular models, MEF2C function had previously been disrupted, either by direct or indirect mutation, and gene expression assayed using RNA-seq. We integrated these RNA-seq data with MEF2C ChIP-seq data to identify dysregulated direct target genes of MEF2C in the NSCs and iNs models. Several MEF2C direct target gene-sets were enriched for SNP-based heritability for intelligence, educational attainment and SCZ, as well as being enriched for genes containing rare de novo mutations reported in ASD and/or developmental disorders. These gene-sets are enriched in both excitatory and inhibitory neurons in the prenatal and adult brain and are involved in a wide range of biological processes including neuron generation, differentiation and development, as well as mitochondrial function and energy production. We observed a trans expression quantitative trait locus (eQTL) effect of a single SNP at MEF2C (rs6893807, which is associated with IQ) on the expression of a target gene, BNIP3L. BNIP3L is a prioritized risk gene from the largest genome-wide association study of SCZ and has a function in mitophagy in mitochondria. Overall, our analysis reveals that either direct or indirect disruption of MEF2C dysregulates sets of genes that contain multiple alleles associated with SCZ risk and cognitive function and implicates neuron development and mitochondrial function in the etiology of these phenotypes.

Genetic, transcriptomic, histological, and biochemical analysis of progressive supranuclear palsy implicates glial activation and novel risk genes

Progressive supranuclear palsy (PSP), a rare Parkinsonian disorder, is characterized by problems with movement, balance, and cognition. PSP differs from Alzheimer’s disease (AD) and other diseases, displaying abnormal microtubule-associated protein tau by both neuronal and glial cell pathologies. Genetic contributors may mediate these differences; however, the genetics of PSP remain underexplored. Here we conduct the largest genome-wide association study (GWAS) of PSP which includes 2779 cases (2595 neuropathologically-confirmed) and 5584 controls and identify six independent PSP susceptibility loci with genome-wide significant (P < 5 × 10−8) associations, including five known (MAPT, MOBP, STX6, RUNX2, SLCO1A2) and one novel locus (C4A). Integration with cell type-specific epigenomic annotations reveal an oligodendrocytic signature that might distinguish PSP from AD and Parkinson’s disease in subsequent studies. Candidate PSP risk gene prioritization using expression quantitative trait loci (eQTLs) identifies oligodendrocyte-specific effects on gene expression in half of the genome-wide significant loci, and an association with C4A expression in brain tissue, which may be driven by increased C4A copy number. Finally, histological studies demonstrate tau aggregates in oligodendrocytes that colocalize with C4 (complement) deposition. Integrating GWAS with functional studies, epigenomic and eQTL analyses, we identify potential causal roles for variation in MOBP, STX6, RUNX2, SLCO1A2, and C4A in PSP pathogenesis.

Role of the X Chromosome in Alzheimer Disease Genetics

The X chromosome has remained enigmatic in Alzheimer disease (AD), yet it makes up 5% of the genome and carries a high proportion of genes expressed in the brain, making it particularly appealing as a potential source of unexplored genetic variation in AD. To perform the first large-scale X chromosome-wide association study (XWAS) of AD. This was a meta-analysis of genetic association studies in case-control, family-based, population-based, and longitudinal AD-related cohorts from the US Alzheimer's Disease Genetics Consortium, the Alzheimer's Disease Sequencing Project, the UK Biobank, the Finnish health registry, and the US Million Veterans Program. Risk of AD was evaluated through case-control logistic regression analyses. Data were analyzed between January 2023 and March 2024. Genetic data available from high-density single-nucleotide variant microarrays and whole-genome sequencing and summary statistics for multitissue expression and protein quantitative trait loci available from published studies were included, enabling follow-up genetic colocalization analyses. A total of 1 629 863 eligible participants were selected from referred and volunteer samples, 477 596 of whom were excluded for analysis exclusion criteria. The number of participants who declined to participate in original studies was not available. Risk of AD, reported as odds ratios (ORs) with 95% CIs. Associations were considered at X chromosome-wide (P < 1 × 10-5) and genome-wide (P < 5 × 10-8) significance. Primary analyses are nonstratified, while secondary analyses evaluate sex-stratified effects. Analyses included 1 152 284 participants of non-Hispanic White, European ancestry (664 403 [57.7%] female and 487 881 [42.3%] male), including 138 558 individuals with AD. Six independent genetic loci passed X chromosome-wide significance, with 4 showing support for links between the genetic signal for AD and expression of nearby genes in brain and nonbrain tissues. One of these 4 loci passed conservative genome-wide significance, with its lead variant centered on an intron of SLC9A7 (OR, 1.03; 95% CI, 1.02-1.04) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes. Of these 6 loci, 4 displayed evidence for escape from X chromosome inactivation with regard to AD risk. This large-scale XWAS of AD identified the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid β accumulation. Overall, this study advances our knowledge of AD genetics and may provide novel biological drug targets. The results further provide initial insights into elucidating the role of the X chromosome in sex-based differences in AD.

Temporal Gene Expression Profiles From Pollination to Seed Maturity in Sorghum Provide Core Candidates for Engineering Seed Traits.

Sorghum (Sorghum bicolor (L.) Moench) is a highly nutritional multipurpose millet crop. However, the genetic and molecular regulatory mechanisms governing sorghum grain development and the associated agronomic traits remain unexplored. In this study, we performed a comprehensive transcriptomic analysis of pistils collected 1-2 days before pollination, and developing seeds collected -2, 10, 20 and 30 days after pollination of S. bicolor variety M35-1. Out of 31 337 genes expressed in these stages, 12 804 were differentially expressed in the consecutive stages of seed development. These exhibited 10 dominant expression patterns correlated with the distinct pathways and gene functions. Functional analysis, based on the pathway mapping, transcription factor enrichment and orthology, delineated the key patterns associated with pollination, fertilization, early seed development, grain filling and seed maturation. Furthermore, colocalization with previously reported quantitative trait loci (QTLs) for grain weight/size revealed 48 differentially expressed genes mapping to these QTL regions. Comprehensive literature mining integrated with QTL mapping and expression data shortlisted 25, 17 and 8 core candidates for engineering grain size, starch and protein content, respectively.