Candidate Causal Genes Research Articles

Functional and Practical Insights Into the Genetic Basis of Takayasu Arteritis.

Takayasu arteritis (TAK) is a rare vasculitis characterized by inflammation of large arteries. Although the exact etiology of TAK remains unclear, a genetic predisposition to the disease has been established. Large-scale genetic studies have significantly contributed to the identification of genetic variation associated with immune-mediated diseases. To date, five genome-wide association studies (GWAS) have been performed in TAK, identifying multiple genetic susceptibility loci across the genome. Here, we summarize the major findings from GWAS in TAK and provide an in silico functional evaluation of the associated loci (P < 5 × 10-8) and variants in high linkage disequilibrium with them (r2 > 0.8). By exploring gene expression and chromatin interaction data, we identified candidate causal genes in TAK, some of them with well-known functional implications. The analysis of transcription factor motifs within TAK-associated loci revealed enrichment of the STAT and RUNX families, both characterized by their role in immune functions and inflammatory responses. The enrichment in biological processes in susceptibility loci confirmed the involvement of specific immune-related pathways in TAK. Further, we devised and calculated a cumulative genetic risk score for TAK and confirmed differences in genetic risk for the disease among ancestries. Finally, we provide a practical guide to communicate genetic information for TAK to patients and families.

Prediction of causal genes at GWAS loci with pleiotropic gene regulatory effects using sets of correlated instrumental variables.

Multivariate Mendelian randomization (MVMR) is a statistical technique that uses sets of genetic instruments to estimate the direct causal effects of multiple exposures on an outcome of interest. At genomic loci with pleiotropic gene regulatory effects, that is, loci where the same genetic variants are associated to multiple nearby genes, MVMR can potentially be used to predict candidate causal genes. However, consensus in the field dictates that the genetic instruments in MVMR must be independent (not in linkage disequilibrium), which is usually not possible when considering a group of candidate genes from the same locus. Here we used causal inference theory to show that MVMR with correlated instruments satisfies the instrumental set condition. This is a classical result by Brito and Pearl (2002) for structural equation models that guarantees the identifiability of individual causal effects in situations where multiple exposures collectively, but not individually, separate a set of instrumental variables from an outcome variable. Extensive simulations confirmed the validity and usefulness of these theoretical results. Importantly, the causal effect estimates remained unbiased and their variance small even when instruments are highly correlated, while bias introduced by horizontal pleiotropy or LD matrix sampling error was comparable to standard MR. We applied MVMR with correlated instrumental variable sets at genome-wide significant loci for coronary artery disease (CAD) risk using expression Quantitative Trait Loci (eQTL) data from seven vascular and metabolic tissues in the STARNET study. Our method predicts causal genes at twelve loci, each associated with multiple colocated genes in multiple tissues. We confirm causal roles for PHACTR1 and ADAMTS7 in arterial tissues, among others. However, the extensive degree of regulatory pleiotropy across tissues and the limited number of causal variants in each locus still require that MVMR is run on a tissue-by-tissue basis, and testing all gene-tissue pairs with cis-eQTL associations at a given locus in a single model to predict causal gene-tissue combinations remains infeasible. Our results show that within tissues, MVMR with dependent, as opposed to independent, sets of instrumental variables significantly expands the scope for predicting causal genes in disease risk loci with pleiotropic regulatory effects. However, considering risk loci with regulatory pleiotropy that also spans across tissues remains an unsolved problem.

CCN3/NOV as a potential therapeutic target for diverticular disease: A proteome-wide Mendelian randomization study.

Genome-wide association studies (GWAS) identified over 100 susceptibility loci and candidate causal genes for diverticular disease (DD) at the transcriptional level. However, effective therapeutics or preventions based on underlying disease mechanisms remain to be elucidated. In this study, we explored potential causal genes for DD at the protein level. We used 2 GWAS summary statistics of DD; 1 was obtained from the United Kingdom Biobank (UKBB) with 31,917 cases and 419,135 controls, and the other from the FinnGen consortium with 30,649 cases and 301,931 controls. For the primary analysis, we employed proteome-wide Mendelian randomization (MR) studies using 738 cis-acting protein quantitative trait loci (pQTLs) for 735 plasma proteins from the 5 published studies. For external validation, we conducted 2-sample MR analyses using plasma pQTLs of the screened proteins from another study by deCODE genetics. Moreover, we performed a series of sensitivity analyses including reverse MR and Bayesian colocalization tests. The primary MR identified 4 plasma proteins that were associated with DD risk including CCN3/NOV (odds ratio [OR], 0.98; 95% confidence interval [CI], 0.97-0.99; P = 1.2 × 10-11 for UKBB. OR, 0.73; 95% CI, 0.66-0.81; P = 7.2 × 10-10 for FinnGen). The validation MR well replicated the primary result of CCN3/NOV (OR, 0.95; 95% CI, 0.93-0.96; P = 1.9 × 10-11 for UKBB. OR, 0.43; 95% CI, 0.33-0.56; P = 7.0 × 10-10 for FinnGen). Sensitivity analyses supported the causal association. We prioritized plasma CCN3/NOV protein as a protective factor for DD for follow-up functional studies to elucidate the disease mechanisms and therapeutics.

The orchestration of coding and non-coding genes at the CDH13 locus in coronary artery disease

Abstract Background The CDH13 locus was associated with coronary artery disease (CAD) by genome-wide association studies (GWAS). However, the causal gene(s) and underlying disease mechanisms at this locus remain undetermined. Purpose We intended to pinpoint and functionally validate the causal coding and non-coding genes at the CDH13 locus and delineate the underlying mechanisms for CAD. Methods and results We conducted the transcriptome-wide association analysis (TWAS) using nine types of CAD-relevant tissues from Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and Genotyped Tissue Expression (GTEx) projects and identified CDH13 (T-cadherin) and four long non-coding RNA (lncRNA) genes as candidate causal genes at The CDH13 locus. One of the antisense(AS) lncRNAs, CDH13-AS2, was predicted to bind on the 3’ untranslated region (UTR) of CDH13 using LncRRIsearch and RNAup servers. The binding interaction was validated by dCas13-medicated RNA immunoprecipitation. Weighted correlation network analysis (WGCNA) using transcriptomic data from CAD-relevant tissues of ~600 human subjects suggested a positive expression correlation between CDH13 and CDH13-AS2 in artery tissues. CRISPR/Cas9-based knockout (KO) of CDH13 or CDH13-AS2 in human umbilical vein endothelial cells (HUVECs) indicated synergistically atherogenic phenotypes, including reduced proliferation and migration, and increased apoptosis and monocyte adhesion. The data matched with the downregulation of CDH13 in artery samples of atherosclerosis patients. The cellular phenotypes were also in line with our in vivo data of Cdh13 and Apoe double-KO (Cdh13-/-/Apoe-/-) mice, which showed increased aortic lesion areas when fed on a high-fat diet compared to Apoe-/- mice. Furthermore, prediction using TargetScan, miRWalk, and scanMiRApp databases identified the potential binding of several EC-expression microRNAs (mir) on 3’UTR of CDH13. Several disease-associated variants were mapped to the predicted binding sites of a few microRNAs, including mir-let7, mir-30, and mir-125. The dual luciferase-based RNA interference (RNAi) assay confirmed the binding of mir-let7 on 3’UTR of CDH13. Transcriptional activation of CDH13-AS2 by the enzymatically inactivated Cas9 (dCas9) system diminished the binding of mir-let7 and increased CDH13 expression. Conclusions At the CDH13 locus, CDH13 and CDH13-AS2 are two causal genes, whose downregulation likely contributes to CAD. CDH13-AS2 bound and stabilized CDH13 partially by preventing mir-let7 mediated degradation of CDH13 mRNA, suggesting therapeutic potentials.

Genetic Testing of Japanese Patients with Serrated Polyposis Syndrome: A Multicentric Study.

Serrated polyposis syndrome (SPS) is a rare condition associated with an increased risk of colorectal cancer. However, the genetic basis of SPS in Japanese patients remains unclear. The present study therefore aimed to address this omission by identifying candidate causative genes of SPS in Japanese patients. The present study performed next-generation sequencing using a multigene panel to identify the causative genes in SPS. Whenever a candidate gene was detected, whole exome sequencing of the tumor tissue was performed. An analysis of 11 patients with SPS identified a germline pathogenic variant of BUB1 (c.1543G>T/p.Gly515Ter) in a 47-year-old, female patient with transverse colon cancer with more than 50 serrated polyps. She had no history of smoking. None of the canonical, causative genes in common colorectal cancer, such as APC, KRAS and TP53, were detected in her lesion. Most of the somatic variants detected in the cancer were transition substitutions (C>T). BUB1 was identified as a candidate causative gene in SPS in a non-smoker with the disease. These findings will hopefully contribute to understanding the genetic basis of SPS.

Cross-population enhancement of PrediXcan predictions with a gnomAD-based east Asian reference framework.

Over the past decade, genome-wide association studies have identified thousands of variants significantly associated with complex traits. For each locus, gene expression levels are needed to further explore its biological functions. To address this, the PrediXcan algorithm leverages large-scale reference data to impute the gene expression level from single nucleotide polymorphisms, and thus the gene-trait associations can be tested to identify the candidate causal genes. However, a challenge arises due to the fact that most reference data are from subjects of European ancestry, and the accuracy and robustness of predicted gene expression in subjects of East Asian (EAS) ancestry remains unclear. Here, we first simulated a variety of scenarios to explore the impact of the level of population diversity on gene expression. Population differentiated variants were estimated by using the allele frequency information from The Genome Aggregation Database. We found that the weights of a variants was the main factor that affected the gene expression predictions, and that ~70% of variants were significantly population differentiated based on proportion tests. To provide insights into this population effect on gene expression levels, we utilized the allele frequency information to develop a gene expression reference panel, Predict Asian-Population (PredictAP), for EAS ancestry. PredictAP can be viewed as an auxiliary tool for PrediXcan when using genotype data from EAS subjects.

Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy

Insulin resistance causes multiple epidemic metabolic diseases, including type 2 diabetes, cardiovascular disease, and fatty liver, but is not routinely measured in epidemiological studies. To discover novel insulin resistance genes in the general population, we conducted genome-wide association studies in 382,129 individuals for triglyceride to HDL-cholesterol ratio (TG/HDL), a surrogate marker of insulin resistance calculable from commonly measured serum lipid profiles. We identified 251 independent loci, of which 62 were more strongly associated with TG/HDL compared to TG or HDL alone, suggesting them as insulin resistance loci. Candidate causal genes at these loci were prioritized by fine mapping with directions-of-effect and tissue specificity annotated through analysis of protein coding and expression quantitative trait variation. Directions-of-effect were corroborated in an independent cohort of individuals with directly measured insulin resistance. We highlight two phospholipase encoding genes, PLA2G12A and PLA2G6, which liberate arachidonic acid and improve insulin sensitivity, and VGLL3, a transcriptional co-factor that increases insulin resistance partially through enhanced adiposity. Finally, we implicate the anti-apoptotic gene TNFAIP8 as a sex-dimorphic insulin resistance factor, which acts by increasing visceral adiposity, specifically in females. In summary, our study identifies several candidate modulators of insulin resistance that have the potential to serve as biomarkers and pharmacological targets.

Fibroblast Growth Factor (FGF) 13

Fibroblast Growth Factor (FGF) 13, also referred to as FGF homologous factor (FHF) 2, is a member of the FGF11 subfamily that is characterized as having sequence similarities to classical FGF receptor (FGFR)-binding FGFs, but functionally do not bind FGFRs. In this primer mini-review, we summarize current knowledge regarding FGF13 expression, mutant analyses, and gene and protein structure. Similar to other FHFs, FGF13 has been considered a non-secreted protein that lacks an amino signal and is prominently expressed in developing and mature neurons of the central and peripheral nervous systems, as well as the heart. The expression of FGF13 is not limited to early embryonic stages and has been shown to persist in adult tissues. As well, FGF13 is known to localize subcellularly, both within the cytoplasm and the nucleus. FGF13 is extremely adaptable, as it interacts with MAPK scaffolding protein islet brain 2 (IB2), stabilizes microtubules, or binds to voltage-gated sodium channels. Fgf13 mutant mouse lines display various neurological pathologies. Through sequence mapping, FGF13 is considered a candidate causative gene that is mutated in multiple human X-linked neurological diseases.

Deciphering the Genetic Basis of Kernel Composition in a Maize Association Panel.

The primary objective in contemporary maize breeding is to pursue high quality alongside high yield. Deciphering the genetic basis of natural variation in starch, protein, oil, and fiber contents is essential for manipulating kernel composition, thereby enhancing the kernel quality and meeting growing demands. Here, we identified 12 to 88 statistically significant loci associated with kernel composition traits through a genome-wide association study (GWAS) using a panel of 212 diverse inbred lines. A regional association study pinpointed numerous causal candidate genes at these loci. Coexpression and protein-protein interaction network analyses of candidate genes revealed several causal genes directly or indirectly involved in the metabolic processes related to kernel composition traits. Subsequent mutant experiment revealed that nonsense mutations in ZmTIFY12 affect starch, protein, and fiber content, whereas nonsense mutations in ZmTT12 affect starch, protein, and oil content. These findings provide valuable guidance for improving kernel quality in maize breeding efforts.

A variant in long noncoding RNA NORSF affects granulosa cells response to transcription factor RFX7.

NORSF is a nuclear long noncoding RNA (lncRNA) that contributes to the follicular atresia and restrains 17β-estradiol (E2) release by granulosa cells (GCs). Importantly, it is also a potential candidate gene in the quantitative trait locus (QTLs) for sow fertility traits. We identified NORSF as a candidate (causal) gene affecting sow fertility traits. A novel G-A variant was discovered at -478 nt of the NORSF promoter and termed as g.-478G>A. Association analysis revealed that this variant was associated with sow fertility traits (e.g., the total number of piglets born, the total number of piglets born alive, and the number of healthy piglets). Mechanistically, the g.-478G>A variant reduced the binding activity of the NORSF promoter to its transcription activator regulatory factor X7 (RFX7), leading to decreased NORSF promoter activity and transcription levels in sow GCs (sGCs), and weakened inhibitory effects on the transcription of CYP19A1, which encodes a rate-limiting enzyme for E2 synthesis and E2 release by sGCs. In addition, RFX7 is transcriptionally activated by P53, which restrains E2 release from sGCs via the RFX7/NORSF/CYP19A1 pathway. These findings indicate that the lncRNA NORSF is a causal gene in QTLs for sow fertility traits and define the P53/NORSF/CYP19A1 pathway as a new signaling pathway affecting sow reproduction, which provides a new target for improving female fertility.

IIIVmrMLM Provides New Insights into the Genetic Basis of the Agronomic Trait Variation in Chickpea

Chickpea is a staple crop for many nations worldwide. Modeling genotype-by-environment interactions and assessing the genotype’s ability to contribute adaptive alleles are crucial for chickpea breeding. In this study, we evaluated 12 agronomically important traits of 159 accessions from the N.I. Vavilov All Russian Institute for Plant Genetic Resources collection. These included 145 landraces and 13 cultivars grown in different climatic conditions in Kuban (45°18′ N and 40°52′ E) in both 2016 and 2022, as well as in Astrakhan (46°06′ N and 48°04′ E) in 2022. Using the IIIVmrMLM model in multi-environmental mode, we identified 161 quantitative trait nucleotides (QTNs) with stable genetic effects across different environments. Furthermore, we have observed 254 QTN-by-environment interactions with distinct environment-specific effects. Notably, five of these interactions manifested large effects, with R2 values exceeding 10%, while the highest R2 value for stable QTNs was 4.7%. Within the protein-coding genes and their 1 Kb flanking regions, we have discerned 22 QTNs and 45 QTN-by-environment interactions, most likely tagging the candidate causal genes. The landraces obtained from the N.I Vavilov All Russian Institute for Plant Genetic Resources collection exhibit numerous favorable alleles at quantitative trait nucleotide loci, showing stable effects in the Kuban and Astrakhan regions. Additionally, they possessed a significantly higher number of Kuban-specific favorable alleles of the QTN-by-environment interaction loci compared to the Astrakhan-specific ones. The environment-specific alleles found at the QTN-by-environment interaction loci have the potential to enhance chickpea adaptation to specific climatic conditions.

Cross-Phenotype GWAS Supports Shared Genetic Susceptibility to Systemic Sclerosis and Primary Biliary Cholangitis.

An increased risk of primary biliary cholangitis (PBC) has been reported in patients with systemic sclerosis (SSc). Our study aims to investigate the shared genetic susceptibility between the two disorders and to define candidate causal genes using cross-phenotype GWAS meta-analysis. We performed cross-phenotype GWAS meta-analysis and colocalization analysis for SSc and PBC. We performed both genome-wide and locus-based analysis, including tissue and pathway enrichment analyses, fine-mapping, colocalization analyses with expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) datasets, and phenome-wide association studies (PheWAS). Finally, we used an integrative approach to prioritize candidate causal genes from the novel loci. We detected a strong genetic correlation between SSc and PBC (rg = 0.84, p = 1.7 × 10-6). In the cross-phenotype GWAS meta-analysis, we identified 44 non-HLA loci that reached genome-wide significance (p < 5 × 10-8). Evidence of shared causal variants between SSc and PBC was found for nine loci, five of which were novel. Integrating multiple sources of evidence, we prioritized CD40, ERAP1, PLD4, SPPL3, and CCDC113 as novel candidate causal genes. The CD40 risk locus colocalized with trans-pQTLs of multiple plasma proteins involved in B cell function. Our study supports a strong shared genetic susceptibility between SSc and PBC. Through cross-phenotype analyses, we have prioritized several novel candidate causal genes and pathways for these disorders.

Identification of novel genetic loci and candidate genes for progressive ethanol consumption in diversity outbred mice.

Mouse behavioral genetic mapping studies can identify genomic intervals modulating complex traits under well-controlled environmental conditions and have been used to study ethanol behaviors to aid in understanding genetic risk and the neurobiology of alcohol use disorder (AUD). However, historically such studies have produced large confidence intervals, thus complicating identification of potential causal candidate genes. Diversity Outbred (DO) mice offer the ability to perform high-resolution quantitative trait loci (QTL) mapping on a very genetically diverse background, thus facilitating identification of candidate genes. Here, we studied a population of 636 male DO mice with four weeks of intermittent ethanol access via a three-bottle choice procedure, producing a progressive ethanol consumption phenotype. QTL analysis identified 3 significant (Chrs 3, 4, and 12) and 13 suggestive loci for ethanol-drinking behaviors with narrow confidence intervals (1-4 Mbp for significant QTLs). Results suggested that genetic influences on initial versus progressive ethanol consumption were localized to different genomic intervals. A defined set of positional candidate genes were prioritized using haplotype analysis, identified coding polymorphisms, prefrontal cortex transcriptomics data, human GWAS data and prior rodent gene set data for ethanol or other misused substances. These candidates included Car8, the lone gene with a significant cis-eQTL within a Chr 4 QTL for week four ethanol consumption. These results represent the highest-resolution genetic mapping of ethanol consumption behaviors in mice to date, providing identification of novel loci and candidate genes for study in relation to the neurobiology of AUD.

NASP gene contributes to autism by epigenetic dysregulation of neural and immune pathways

BackgroundEpigenetics makes substantial contribution to the aetiology of autism spectrum disorder (ASD) and may harbour a unique opportunity to prevent the development of ASD. We aimed to identify novel epigenetic...

A Novel Macrophage Subpopulation Conveys Increased Genetic Risk of Coronary Artery Disease.

Coronary artery disease (CAD), the leading cause of death worldwide, is influenced by both environmental and genetic factors. Although over 250 genetic risk loci have been identified through genome-wide association studies, the specific causal variants and their regulatory mechanisms are still largely unknown, particularly in disease-relevant cell types such as macrophages. We utilized single-cell RNA-seq and single-cell multiomics approaches in primary human monocyte-derived macrophages to explore the transcriptional regulatory network involved in a critical pathogenic event of coronary atherosclerosis-the formation of lipid-laden foam cells. The relative genetic contribution to CAD was assessed by partitioning disease heritability across different macrophage subpopulations. Meta-analysis of single-cell RNA-seq data sets from 38 human atherosclerotic samples was conducted to provide high-resolution cross-referencing to macrophage subpopulations in vivo. We identified 18 782 cis-regulatory elements by jointly profiling the gene expression and chromatin accessibility of >5000 macrophages. Integration with CAD genome-wide association study data prioritized 121 CAD-related genetic variants and 56 candidate causal genes. We showed that CAD heritability was not uniformly distributed and was particularly enriched in the gene programs of a novel CD52-hi lipid-handling macrophage subpopulation. These CD52-hi macrophages displayed significantly less lipoprotein accumulation and were also found in human atherosclerotic plaques. We investigated the cis-regulatory effect of a risk variant rs10488763 on FDX1, implicating the recruitment of AP-1 and C/EBP-β in the causal mechanisms at this locus. Our results provide genetic evidence of the divergent roles of macrophage subsets in atherogenesis and highlight lipid-handling macrophages as a key subpopulation through which genetic variants operate to influence disease. These findings provide an unbiased framework for functional fine-mapping of genome-wide association study results using single-cell multiomics and offer new insights into the genotype-environment interactions underlying atherosclerotic disease.

Loss of function variant in CIP2A associated with female infertility with early embryonic arrest and fragmentation

BackgroundEarly embryonic arrest and fragmentation (EEAF) is a common cause of female infertility, but the genetic causes remain to be largely unknown. CIP2A encodes the cellular inhibitor of PP2A, playing a crucial role in mitosis and mouse oocyte meiosis. MethodsExome sequencing and Sanger sequencing were performed to identify candidate causative genes in patients with EEAF. The pathogenicity of the CIP2A variant was assessed and confirmed in cultured cell lines and human oocytes through Western blotting, semi-quantitative RT-PCR, TUNEL staining, and fluorescence localization analysis. FindingsWe identified CIP2A (c.1510C > T, p.L504F) as a novel disease-causing gene in human EEAF from a consanguineous family. L504 is highly conserved throughout evolution. The CIP2A variant (c.1510C > T, p.L504F) reduced the expression level of the mutant CIP2A protein, leading to the abnormal aggregation of mutant CIP2A protein and cell apoptosis. Abnormal aggregation of CIP2A protein and chromosomal dispersion occurred in the patient's oocytes and early embryos. We further replicated the patient phenotype by knockdown CIP2A in human oocytes. Additionally, CIP2A deficiency resulted in decreased levels of phosphorylated ERK1/2. InterpretationWe first found that the CIP2A loss-of-function variant associate with female infertility characterized by EEAF. Our findings suggest the uniqueness and importance of CIP2A gene in human oocyte and early embryo development. FundingThis work was supported by National Key Research and Development Program of China (2023YFC2706302), the National Natural Science Foundation of China (81000079, 81170165, and 81870959), the HUST Academic Frontier Youth Team (2016QYTD02), and the Key Research of Huazhong University of Science and Technology, Tongji Hospital (2022A20).

Abstract PO5-09-03: Multi-tissue transcriptome-wide association studies identified genes for intrinsic subtypes of breast cancer

Abstract Background: Though several genome-wide association studies (GWAS) of breast cancer (BC) have identified common variants which differ between intrinsic subtypes, the genes through which these variants act through to impact BC risk have not been fully established. Furthermore, transcriptome-wide association studies (TWAS) have thus far been primarily employed to identify genes associated with overall BC risk, while overlooking how the influence of common variation on gene expression may contribute to subtype-specific differences. Methods: In this study, we performed two complementary multi-tissue TWASs for each of the following BC intrinsic subtypes: Luminal A-like, Luminal B-like, Luminal B/HER2-negative-like, HER2-enriched-like, Triple Negative BC. These two approaches included 1) an expression-based approach that collated TWAS signals from expression quantitative trait loci (eQTLs) across multiple tissues using the Aggregated Cauchy Association Test (ACAT) and 2) a splicing-based approach that utilized two applications of ACAT to collate splicing QTLs (sQTLs) for a given gene in a tissue and then across tissues. To perform these two TWASs, we utilized e/sQTL models trained in 11 tissues from the Genotype-Tissue Expression Project including breast, ovary, uterus, vagina, EBV-transformed lymphocytes, whole blood, spleen, liver, subcutaneous adipose, visceral adipose, and cell-cultured fibroblasts. GWAS summary statistics were previously generated from 133,384 BC cases and 113,789 controls who were participants in the Breast Cancer Association Consortium (BCAC). We further performed our TWAS while conditioning e/sQTL effect sizes on nearby GWAS index SNPs. Additionally, we utilized gene-based fine-mapping of eQTLs and sQTL to identify candidate causal genes for each intrinsic subtype. Results: Overall, we identified 164 genes in 69 loci that were associated with Luminal A-like, 19 genes in 9 loci with Luminal B-like, 18 genes in 11 loci with Luminal B/HER2-negative-like, 10 genes in 7 loci with HER2-enriched-like, and 29 genes in 12 loci with TNBC. Among these genes, 17 genes had not been reported in previous TWAS of BC, and 140 genes, 1 gene, 2 genes, 2 genes, and 16 genes were uniquely associated with each of the intrinsic subtypes, respectively. Additionally, we identified one gene associated with Luminal A-like and one gene with Luminal B-like BC that were each in a locus located at least 1.4 Mb from published GWAS hits. Furthermore, we identified 106, 11, 10, 5, and 21 candidate causal genes for each of the intrinsic subtypes, respectively, that had a posterior inclusion probability of 0.9 in at least one e/sQTL. Conclusion: In summary, our multi-tissue TWAS corroborated previous GWAS loci for overall BC risk and intrinsic subtypes, while underscoring how common variation impacts BC etiology by modulating the expression and splicing of genes in multiple tissue types. Citation Format: James Li, Julian McClellan, Haoyu Zhang, Guimin Gao, Dezheng Huo. Multi-tissue transcriptome-wide association studies identified genes for intrinsic subtypes of breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-09-03.

Abstract 150: Decoding The Variant-to-function Relationship For LIPA , A Risk Locus For Cad

Background: Genome-wide association studies (GWASs) link genetic variation in the LIPA (lysosomal acid lipase) gene to coronary artery disease (CAD). Quantitative Trait Loci (QTL) studies indicate higher LIPA mRNA and enzyme activity in the monocytes of risk alleles carriers. Yet, the mechanism whereby this locus confers disease etiology has not been fully established. Herein, we aim to establish the variant-to-function relationship and elucidate how increased LIPA impacts atherosclerosis. Methods: Employing post-GWAS pipelines (eQTL, enzyme activity-QTL, Tri-HiC, luciferase assay, allele-specific binding, motif analysis, and mobility shift assay), we connect functional variants to target genes in causal myeloid cells. Myeloid-specific Lipa overexpression mice ( Lipa Tg ) on Ldlr -/- background were generated and characterized. Results: Post-GWAS pipelines support LIPA as the candidate causal gene at this locus. In human monocyte-derived macrophages, risk allele carriers of GWAS CAD variants exhibit higher LIPA mRNA, protein, and enzyme activity. Tri-HiC and luciferase assay identified an intronic region within LIPA , housing GWAS CAD noncoding variants and exhibiting monocyte-specific enhancer activity. Within the enhancer region, 1412445 and rs1320496 were identified as the two potential causal variants, with the risk alleles having increased enhancer activity in luciferase assay and increased binding to PU.1 in mobility shift assay. Collectively, the above data suggest that the risk alleles of CAD variants lead to increased LIPA in monocytes/macrophages. Consistently, Lipa Tg , Ldlr -/- mice fed a Western diet showed significantly increased lesion size and lesion macrophage area compared to Ctl, Ldlr -/- mice. scRNA-seq analysis followed by functional validation demonstrated that Lipa Tg macrophages had higher free cholesterol yet lower neutral lipid accumulation, accompanied by a transcriptomic signature of increased interferon signaling. Lipa overexpression also increased monocyte infiltration into the plaque. Conclusions: We established that the risk alleles of common noncoding variants at the LIPA locus drive increased myeloid LIPA expression and aggravate atherosclerosis.

A novel QTL region for pH and meat color in Duroc pigs.

One of the most important processes that occur during the transformation of muscle to meat is the pH decline as a consequence of the post-mortem metabolism of muscle tissue. Abnormal pH declines lead to pork defects such as pale, soft, and exudative meat. There is genetic variance for ultimate pH and the role of some genes on this phenotype is well established. After conducting a genome-wide association study on ultimate pH using 526 purebred Duroc pigs, we identified associated regions on Sus scrofa chromosomes (SSC) 3, 8, and 15. Functional candidate genes in these regions included PRKAG3 and PHKG1. The SSC8 region, at 71.6 Mb, was novel and, although no candidate causative gene could be identified, it may have regulatory effects. Subsequent analysis on 828 pigs from the same population confirmed the impact of the three associated regions on pH and meat color. We detected no interaction between the three regions. Further investigations are necessary to unravel the functional significance of the novel genomic region at SSC8. These variants could be used as markers in marker-assisted selection for improving meat quality.

Integrative genomic analyses identify candidate causal genes for calcific aortic valve stenosis involving tissue-specific regulation.

There is currently no medical therapy to prevent calcific aortic valve stenosis (CAVS). Multi-omics approaches could lead to the identification of novel molecular targets. Here, we perform a genome-wide association study (GWAS) meta-analysis including 14,819 cases among 941,863 participants of European ancestry. We report 32 genomic loci, among which 20 are novel. RNA sequencing of 500 human aortic valves highlights an enrichment in expression regulation at these loci and prioritizes candidate causal genes. Homozygous genotype for a risk variant near TWIST1, a gene involved in endothelial-mesenchymal transition, has a profound impact on aortic valve transcriptomics. We identify five genes outside of GWAS loci by combining a transcriptome-wide association study, colocalization, and Mendelian randomization analyses. Using cross-phenotype and phenome-wide approaches, we highlight the role of circulating lipoproteins, blood pressure and inflammation in the disease process. Our findings pave the way for the development of novel therapies for CAVS.