SNP2TFBS - a database of regulatory SNPs affecting predicted transcription factor binding site affinity

Susceptibility to acute myeloid leukemia: Influence of genetic variants of interleukins 37 and 38

Interleukin (IL)-37 and IL-38 are anti-inflammatory cytokines encoded by IL37 and IL1F10 genes, respectively. Recently, it has been proposed that missense single nucleotide polymorphisms (SNPs) of IL37 (rs3811046 G/T and rs3811047 A/G) and 5'-untranslated region SNPs of IL1F10 (rs3811050 C/T and rs3811051 T/G) may influence susceptibility to some inflammatory disorders. Inflammation has also been shown to play a key role in pathogenesis of acute myeloid leukemia (AML). Therefore, it is reasonable to hypothesize that rs3811046, rs3811047, rs3811050, and rs3811051 may have a role in susceptibility to AML. A case-control study was conducted on 131 AML patients and 169 controls to investigate the association of these SNPs with AML risk. SNP genotypes were determined using TaqMan allelic discrimination, a real-time PCR-based method. Results revealed that mutant alleles (T, G, and T) and corresponding homozygous genotypes (TT, GG, and TT) of rs3811046, rs3811047, and rs3811050, respectively, were significantly associated with an increased risk of AML, while rs3811051 showed no association. Four-locus haplotype analysis (rs3811046-rs3811047-rs3811050-rs3811051) demonstrated that T-A-C-G haplotype was associated a 2.47-fold increased risk of AML. SNP-SNP interaction analysis showed significant genetic interactions between rs3811046 and rs3811047, rs3811046 and rs3811050, and rs3811047 and rs3811050. Rs3811046 and rs3811047 did not affect IL37 gene expression. Some laboratory and clinical variables of AML may be influenced by IL37 and IL1F10 SNPs. In conclusion, rs3811046, rs3811047, and rs3811050 were associated with AML susceptibility in terms of allele, genotype, and haplotype, while rs3811051 showed no association. Three SNPs (rs3811046, rs3811047, and rs3811050) showed a significant gene-gene interaction.

Functional insights into PTGS2 rs689466 polymorphism associated to asthma in West Bengal, India

BACKGROUND

Asthma is characterized by bronchoconstriction and airway hyperresponsiveness. Interplay of environmental and genetic factors led to significant rise in asthma prevalence in India during past decades.

OBJECTIVE

This study investigated functional insights of prostaglandin-endoperoxide synthase 2 (PTGS2) rs689466 polymorphism among 155 pollen-induced patients and 155 controls in West Bengal population, India.

METHODS

Genotyping was performed using Polymerase chain reaction-Restriction fragment length polymorphism. Transcription Factors (TFs) for promoter region corresponding to the polymorphism location were searched by SNP2TFBS. DNA structures were docked with TFs in HDOCK. Protein-DNA interface was analysed by DNAproDB. Relative abundance of PTGS2 mRNA in controls and different polymorphic genotypes was obtained using Real time PCR. Protein expression was analyzed by western blot.

RESULTS

Genotype and allele frequencies differed significantly between study groups (P = 0.01 and 0.03 respectively). Frequency of GG and AG genotype was significantly higher in patients (P = 0.02 and 0.04 respectively). Significant differences in FEV1/FVC were obtained in different polymorphic genotypes of patients (P < 0.0001) whereas no difference was found in controls (P = 0.08). It was predicted PTGS2 expression decreased due to altered interactions between DNA and TFs in promoter region harbouring the polymorphism. PTGS2 mRNA expression was upregulated in patients bearing AA genotype whereas downregulated in patients with AG and GG genotypes. Protein expression was reduced in AG and GG carrying patients compared to patients bearing AA genotype.

CONCLUSION

This study is the first one to report association of PTGS2 rs689466 polymorphism in Indian population. This will help in gene-based therapy for improved asthma management in future.

A 3D Genome Atlas of Genetic Variants and Their Pathological Effects in Cancer

The hierarchical organization of the eukaryotic genome is crucial for nuclear activities and cellular development. Genetic aberrations can disrupt this 3D genomic architecture, potentially driving oncogenesis. However, current research often lacks a comprehensive perspective, focusing on specific mutation types and singular 3D structural levels. Here, pathological changes from chromosomes to nucleotides are systematically cataloged, including 10 789 interchromosomal translocations (ICTs), 18 863 structural variants (SVs), and 162 769 single nucleotide polymorphisms (SNPs). The multilayered analysis reveals that fewer than 10% of ICTs disrupt territories via potent 3D interactions, and only a minimal fraction of SVs disrupt compartments or intersect topologically associated domain structures, yet these events significantly influence gene expression. Pathogenic SNPs typically show reduced interactions within the 3D genomic space. To investigate the effects of variants in the context of 3D organization, a two-phase scoring algorithm, 3DFunc, is developed to evaluate the pathogenicity of variant-gene pairs in cancer. Using 3DFunc, IGHV3-23's critical role in chronic lymphocytic leukemia is identified and it is found that three pathological SNPs (rs6605578, rs7814783, rs2738144) interact with DEFA3. Additionally, 3DGAtlas is introduced, which provides a highly accessible 3D genome atlas and a valuable resource for exploring the pathological effects of genetic mutations in cancer.

Sex-differentiated placental methylation and gene expression regulation has implications for neonatal traits and adult diseases

Sex differences in physiological and disease traits are pervasive and begin during early development, but the genetic architecture of these differences is largely unknown. Here, we leverage the human placenta, a transient organ during pregnancy critical to fetal development, to investigate the impact of sex in the regulatory landscape of placental autosomal methylome and transcriptome, and its relevance to health and disease. We find that placental methylation and its genetic regulation are extensively impacted by fetal sex, whereas sex differences in placental gene expression and its genetic regulation are limited. We identify molecular processes and regulatory targets that are enriched in a sex-specific manner, and find enrichment of imprinted genes in sex-differentiated placental methylation, including female-biased methylation within the well-known KCNQ1OT1/CDKN1C imprinting cluster of genes expressed in a parent-of-origin dependent manner. We establish that several sex-differentiated genetic effects on placental methylation and gene expression colocalize with birthweight and adult disease genetic associations, facilitating mechanistic insights on early life origins of health and disease outcomes shaped by sex.

Toll-like receptors polymorphisms and COVID-19: a systematic review

COVID-19 is a disease caused by SARS-CoV-2. It became a health problem affecting the lives of millions of people. Toll-like receptors are responsible for recognizing viral particles and activating the innate immune system. The genetic factors associated with COVID-19 remain unclear. Thus, this study aims to assess the association between the polymorphism in Toll-like receptors and susceptibility to COVID-19. We searched the electronic databases (Science Direct, PUBMED, Web of Science, and Scopus) for studies assessing the association between Toll-like receptor polymorphisms and susceptibility to COVID-19. The quality of the studies was assessed using the Q-Genie tool. Thirteen studies were included in this systematic review. The studies analyzed polymorphisms in TLR2, TLR3, TLR4, TLR7, TLR8 and TLR9. We used SNP2TFBS bioinformatic analysis to identify the variants influencing transcription factor binding sites. The Ensembl Genome Browser was used to assess the allele and genotype frequencies in different populations. The bioinformatic analysis revealed that the variant rs5743836 of TLR9 affects the transcription factor binding sites NFKB1 and RELA. The genotype frequency of the variants rs3775291, rs3853839, rs3764880 were higher in East Asian population compared to the other populations. The frequency of the rs3775290 variant was higher in East and South Asian populations. The rs179008 variant was higher in the European population, and the rs5743836 was higher in the African population. Toll-like receptors play an important role in COVID-19 susceptibility. Further studies in different populations are necessary to elucidate the role of Toll-like receptors polymorphisms in SARS-CoV-2 infection.

Identification of blood eQTLs in older adults

Genome-wide association studies (GWAS) have been successful in identifying genetic variation associated with a wide range of phenotypes. However, more detailed knowledge of their functional significance is required to provide insights into the molecular mechanisms involved. Single Nucleotide Polymorphisms (SNPs) that influence gene expression (Expression Quantitative Trait Loci-eQTLs) may be one such functional mechanism. As gene expression may change over the lifespan, it is important to identify eQTLs for specific age groups. In this study, we aimed to identify blood eQTLs in older adults. Peripheral blood was collected from participants of the Sydney Memory and Ageing Study (Sydney MAS, N = 445, mean age ± SD = 83.38 ± 4.31) and RNA extracted. Gene expression and SNP genotyping were assessed using arrays. Genome-wide eQTL analyses were undertaken using linear mixed-models. Replication was undertaken in the Older Australian Twins Study (OATS, N = 283, mean age = 75.86 ± 5.28). In the discovery cohort (Sydney MAS), a total of 10,468 unique eQTLs were identified influencing the expression of 1402 probes (1229 genes). A total of 6554 eQTLs were replicated in OATS, out of the 7339 that were available for analysis. We have identified, replicated, and described a catalogue of blood eQTLs in older adults. Noting that replication of these results in independent samples of older adults is required given our modest sample size. However, this information will be a useful resource for further studies, particularly in assessing the potential functions of SNPs identified in GWAS focussing on age-related traits.

Improving genetic variant identification for quantitative traits using ensemble learning-based approaches

BACKGROUND

Genome-wide association studies (GWAS) are rapidly advancing due to the improved resolution and completeness provided by Telomere-to-Telomere (T2T) and pangenome assemblies. While recent advancements in GWAS methods have primarily focused on identifying genetic variants associated with discrete phenotypes, approaches for quantitative traits (QTs) remain underdeveloped. This has often led to significant variants being overlooked due to biases from genotype multicollinearity and strict p-value thresholds.

RESULTS

We propose an enhanced ensemble learning approach for QT analysis that integrates regularized variant selection with machine learning-based association methods, validated through comprehensive biological enrichment analysis. We benchmarked four widely recognized single nucleotide polymorphism (SNP) feature selection methods-least absolute shrinkage and selection operator, ridge regression, elastic-net, and mutual information-alongside four association methods: linear regression, random forest, support vector regression (SVR), and XGBoost. Our approach is evaluated on simulated datasets and validated using a subset of the PennCATH real dataset, including imputed versions, focusing on low-density lipoprotein (LDL)-cholesterol levels as a QT. The combination of elastic-net with SVR outperformed other methods across all datasets. Functional annotation of top 100 SNPs identified through this superior ensemble method revealed their expression in tissues involved in LDL cholesterol regulation. We also confirmed the involvement of six known genes (APOB, TRAPPC9, RAB2A, CCL24, FCHO2, and EEPD1) in cholesterol-related pathways and identified potential drug targets, including APOB, PTK2B, and PTPN12.

CONCLUSIONS

In conclusion, our ensemble learning approach effectively identifies variants associated with QTs, and we expect its performance to improve further with the integration of T2T and pangenome references in future GWAS.

reg-eQTL: Integrating transcription factor effects to unveil regulatory variants

Regulatory single-nucleotide variants (rSNVs) in noncoding regions of the genome play a crucial role in gene transcription by altering transcription factor (TF) binding, chromatin states, and other epigenetic modifications. Existing expression quantitative trait locus (eQTL) methods identify genomic loci associated with gene-expression changes, but they often fall short in pinpointing causal variants. We introduce reg-eQTL, a computational method that incorporates TF effects and interactions with genetic variants into eQTL analysis. This approach provides deeper insights into the regulatory mechanisms, bringing us one step closer to identifying potential causal variants by uncovering how TFs interact with SNVs to influence gene expression. This method defines a trio consisting of a genetic variant, a target gene, and a TF and tests its impact on gene transcription. In comprehensive simulations, reg-eQTL shows improved power of detecting rSNVs with low population frequency, weak effects, and synergetic interaction with TF as compared to traditional eQTL methods. Application of reg-eQTL to GTEx data from lung, brain, and whole-blood tissues uncovered regulatory trios that include eQTLs and increased the number of eQTLs shared across tissue types. Regulatory networks constructed on the basis of these trios reveal intricate gene regulation across tissue types.

An Investigation of the Structures of [(Glycine)(1-Methyluracil)]M+ Complexes (M=H, Li, Na, K) in the Gas Phase by IRMPD Spectroscopy and Theoretical Methods

The presence of ions in the complexation of molecules can profoundly affect the structure, resulting in changes to functionality and stability. These non-covalent interactions drive many biological processes both necessary and inimical and require extensive research to understand and predict their effects. Protonated and alkali metalated complexes of glycine (Gly) and 1-methyluracil (1-mUra) were studied using infrared multiphoton dissociation (IRMPD) spectroscopy and density functional theory (DFT) calculations. The experimental and simulated vibrational spectra were compared to help elucidate the structure of each complex. The lowest energy structure for [(Gly)(1-mUra)]H+ consists of amine protonated Gly bound to O4 of canonical 1-mUra through a single ionic hydrogen bond with another, intraglycine ionic hydrogen bond between the protonated amine group and the carbonyl oxygen. For [(Gly)(1-mUra)]Li+, [(Gly)(1-mUra)]Na+ and [(Gly)(1-mUra)]K+, the experimental spectra are most consistent with the metal cations binding in a trigonal planar geometry with 1-mUra bound to the metal cation via the O4 carbonyl. In [(Gly)(1-mUra)]Li+ and [(Gly)(1-mUra)]Na+, the metal cation is bound to canonical Gly via the carbonyl oxygen and amine nitrogen, but in [(Gly)(1-mUra)]K+, Gly is bound through both oxygens and contains an intraglycine hydrogen bond from the hydroxyl to the amine nitrogen. It was found that the B3LYP/6-31+G(d,p) vibrational spectra are most consistent with the experimental spectra, but M062X was better than B3LYP at determining the lowest-energy structures.

Comprehensive mapping of genetic variation at Epromoters reveals pleiotropic association with multiple disease traits

There is growing evidence that a wide range of human diseases and physiological traits are influenced by genetic variation of cis-regulatory elements. We and others have shown that a subset of promoter elements, termed Epromoters, also function as enhancer regulators of distal genes. This opens a paradigm in the study of regulatory variants, as single nucleotide polymorphisms (SNPs) within Epromoters might influence the expression of several (distal) genes at the same time, which could disentangle the identification of disease-associated genes. Here, we built a comprehensive resource of human Epromoters using newly generated and publicly available high-throughput reporter assays. We showed that Epromoters display intrinsic and epigenetic features that distinguish them from typical promoters. By integrating Genome-Wide Association Studies (GWAS), expression Quantitative Trait Loci (eQTLs) and 3D chromatin interactions, we found that regulatory variants at Epromoters are concurrently associated with more disease and physiological traits, as compared with typical promoters. To dissect the regulatory impact of Epromoter variants, we evaluated their impact on regulatory activity by analyzing allelic-specific high-throughput reporter assays and provided reliable examples of pleiotropic Epromoters. In summary, our study represents a comprehensive resource of regulatory variants supporting the pleiotropic role of Epromoters.

Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants

Kidney dysfunction is a major cause of mortality, but its genetic architecture remains elusive. In this study, we conducted a multiancestry genome-wide association study in 2.2 million individuals and identified 1026 (97 previously unknown) independent loci. Ancestry-specific analysis indicated an attenuation of newly identified signals on common variants in European ancestry populations and the power of population diversity for further discoveries. We defined genotype effects on allele-specific gene expression and regulatory circuitries in more than 700 human kidneys and 237,000 cells. We found 1363 coding variants disrupting 782 genes, with 601 genes also targeted by regulatory variants and convergence in 161 genes. Integrating 32 types of genetic information, we present the "Kidney Disease Genetic Scorecard" for prioritizing potentially causal genes, cell types, and druggable targets for kidney disease.

Massively parallel variant-to-function mapping determines functional regulatory variants of non-small cell lung cancer

Genome-wide association studies have identified thousands of genetic variants associated with non-small cell lung cancer (NSCLC), however, it is still challenging to determine the causal variants and to improve disease risk prediction. Here, we applied massively parallel reporter assays to perform NSCLC variant-to-function mapping at scale. A total of 1249 candidate variants were evaluated, and 30 potential causal variants within 12 loci were identified. Accordingly, we proposed three genetic architectures underlying NSCLC susceptibility: multiple causal variants in a single haplotype block (e.g. 4q22.1), multiple causal variants in multiple haplotype blocks (e.g. 5p15.33), and a single causal variant (e.g. 20q11.23). We developed a modified polygenic risk score using the potential causal variants from Chinese populations, improving the performance of risk prediction in 450,821 Europeans from the UK Biobank. Our findings not only augment the understanding of the genetic architecture underlying NSCLC susceptibility but also provide strategy to advance NSCLC risk stratification.

In Silico Prediction of Functional SNPs Interrupting Antioxidant Defense Genes in Relation to COVID-19 Progression

The excessive production of reactive oxygen species and weakening of antioxidant defense system play a pivotal role in the pathogenesis of different diseases. Extensive differences observed among individuals in terms of affliction with cancer, cardiovascular disorders, diabetes, bacterial, and viral infections, as well as response to treatments can be partly due to their genomic variations. In this work, we attempted to predict the effect of SNPs of the key genes of antioxidant defense system on their structure, function, and expression in relation to COVID-19 pathogenesis using in silico tools. In addition, the effect of SNPs on the target site binding efficiency of SNPs was investigated as a factor with potential to change drug response or susceptibility to COVID-19. According to the predicted results, only six missense SNPs with minor allele frequency (MAF) ≥ 0.1 in the coding region of genes GPX7, GPX8, TXNRD2, GLRX5, and GLRX were able to strongly affect their structure and function. Our results predicted that 39 SNPs with MAF ≥ 0.1 led to the generation or destruction of miRNA-binding sites on target antioxidant genes from GPX, PRDX, GLRX, TXN, and SOD families. The results obtained from comparing the expression profiles of mild vs. severe COVID-19 patients using GEO2R demonstrated a significant change in the expression of approximately 250 miRNAs. The binding efficiency of 21 of these miRNAs was changed due to the elimination or generation of target sites in these genes. Altogether, this study reveals the fundamental role of the SNPs of antioxidant defense genes in COVID-19 progression and susceptibility of individuals to this virus. In addition, different responses of COVID-19 patients to antioxidant defense system enhancement drugs may be due to presence of these SNPs in different individuals.

A genome-wide association study of European advanced cancer patients treated with opioids identifies regulatory variants on chromosome 20 associated with pain intensity

BACKGROUND

Opioids in step III of the WHO analgesic ladder are the standard of care for treating cancer pain. However, a significant minority of patients do not benefit from therapy. Genetics might play a role in predisposing patients to a good or poor response to opioids. Here, we investigated this issue by conducting a genome-wide association study (GWAS).

METHODS

We genotyped 2057 European advanced cancer patients treated with morphine, buprenorphine, fentanyl and oxycodone. We carried out a whole-genome regression model (using REGENIE software) between genotypes and the opioid response phenotype, defined as a numerical score measuring patient pain intensity.

RESULTS

The GWAS identified five non-coding variants on chromosome 20 with a p-value <5.0 × 10-8. For all of them, the minor allele was associated with lower pain intensity. These variants were intronic to the PCMTD2 gene and were 200 kbp downstream of OPRL1, the opioid related nociceptin receptor 1. Notably according to the eQTLGen database, these variants act as expression quantitative trait loci, modulating the expression mainly of PCMTD2 but also of OPRL1. Variants in the same chromosomal region were recently reported to be significantly associated with pain intensity in a GWAS conducted in subjects with different chronic pain conditions.

CONCLUSIONS

Our results support the role of genetics in the opioid response in advanced cancer patients. Further functional analyses are needed to understand the biological mechanism underlying the observed association and lead to the development of individualized pain treatment plans, ultimately improving the quality of life for cancer patients.

SIGNIFICANCE STATEMENT

This genome-wide association study on European advanced cancer patients treated with opioids identifies novel regulatory variants on chromosome 20 (near PCMTD2 and OPRL1 genes) associated with pain intensity. These findings enhance our understanding of the genetic basis of opioid response, suggesting new potential markers for opioid efficacy. The study is a significant advancement in pharmacogenomics, providing a robust dataset and new insights into the genetic factors influencing pain intensity, which could lead to personalized cancer pain management.

The melanocortin receptor genes are linked to and associated with the risk of polycystic ovary syndrome in Italian families

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder occurring in women of reproductive age. The disease is caused by a complex interplay of genetic and environmental factors including genes encoding components of the hypothalamic-pituitary-adrenal (HPA) axis. We have recently reported the association of melanocortin receptor genes (MC1R, MC2R, MC3R, MC4R, and MC5R) with the risk of type 2 diabetes (T2D) and/or major depressive disorder (MDD). The latter 2 disorders are comorbid with PCOS. In this study, we used microarray to test 12 single nucleotide polymorphisms (SNPs) in the MC1R gene, 10 SNPs in the MC2R gene, 5 SNPs in the MC3R gene, 6 SNPs in the MC4R gene, and 4 SNPs in the MC5R gene in 212 original Italian families with PCOS. We identified 1 SNP in MC1R, 1 SNP in MC2R, 2 SNPs in MC3R, and 2 SNPs in MC5R significantly linked and/or associated to/with the risk of PCOS in Italian families. This is the first study to report the novel implication of melanocortin receptor genes (MC1R, MC2R, and MC5R) in PCOS. MC3R and MC4R were previously reported in PCOS. However, functional studies are needed to validate these results.

Linking Iris Cis-Regulatory Variants to Primary Angle-Closure Glaucoma Via Clinical Imaging and Multiomics

Purpose

To elucidate the genetic basis of primary angle-closure glaucoma (PACG) by identifying pathogenic tissue and critical tissue-specific variants.

Methods

The correlations among PACG susceptibility, axial length (AL), and anterior chamber depth (ACD) were evaluated using meta-analyses. Propensity score matching was utilized on 2161 participants from the Handan Eye Study to determine the risk factors independent of ACD and AL for PACG. Subsequently, we employed the assay for transposase-accessible chromatin with sequencing (ATAC-seq) and allele-specific self-transcribing active regulatory region sequencing (STARR-seq) to screen 202 PACG genome-wide association study (GWAS) variants for chromatin accessibility and functional roles.

Results

The meta-analysis found that PACG susceptibility loci are not associated with ACD or AL. However, abnormal iris phenotypes emerged as significant independent risk factors for primary angle-closure disease (PACD), unrelated to ACD and AL. Substantial enrichment of PACG heritability was observed in the open chromatin regions of the human iris. Within the iris-relevant cellular context, 22 out of the 202 PACG GWAS variants could influence enhancer activity. Two variants in the iris open chromatin regions were implicated in the modulation of PLEKHA7 and C10orf53 expression. The downregulation of these two genes affects cytoskeletal organization.

Conclusions

Our findings underscore the importance of the iris in the pathogenesis of PACG and identified iris-specific, enhancer-modulating variants that may influence disease risk. Our approach also provides a generalizable framework for studying ocular diseases from the perspective of enhancer-modulating variants.

Implication of vasopressin receptor genes (AVPR1A and AVPR1B) in the susceptibility to polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is a complex heterogenous disorder manifesting with various reproductive, endocrine, and metabolic derangements such as insulin resistance and hyperglycemia. The arginine vasopressin peptide (AVP), also called or antidiuretic hormone (ADH), modulates metabolic functions such as glucose hemostasis, insulin sensitivity, and lipid metabolism via binding to two central and peripheral receptors (AVPR1A and AVPR1B). In the present study, we aimed to detect whether the AVPR1A and AVPR1B genes confer risk for PCOS.

METHODS

In peninsular Italian families, we tested 7 variants in the AVPR1B gene and 2 variants in the AVPR1A gene via Pseudomarker for linkage and linkage joint to association (i.e.., linkage disequilibrium) with PCOS.

RESULTS

We identified two risk variants in each gene, significantly associated with the risk of PCOS.

CONCLUSION

To the best of our knowledge, this is the first study to report risk variants in AVPR1A and AVPR1B genes in association with PCOS. However, replication in other ethnic groups as well as functional studies are needed to confirm these results.

Tracing ALS Degeneration: Insights from Spinal Cord and Cortex Transcriptomes

BACKGROUND/OBJECTIVES

Amyotrophic Lateral Sclerosis is a progressive neurodegenerative disorder characterized by the loss of upper and lower motor neurons. Key factors contributing to neuronal death include mitochondrial energy damage, oxidative stress, and excitotoxicity. The frontal cortex is crucial for action initiation, planning, and voluntary movements whereas the spinal cord facilitates communication with the brain, walking, and reflexes. By investigating transcriptome data from the frontal cortex and spinal cord, we aim to elucidate common pathological mechanisms and pathways involved in ALS for understanding the disease progression and identifying potential therapeutic targets.

METHODS

In this study, we quantified gene and transcript expression patterns, predicted variants, and assessed their functional effects using computational tools. It also includes predicting variant-associated regulatory effects, constructing functional interaction networks, and performing a gene enrichment analysis.

RESULTS

We found novel genes for the upregulation of immune response, and the downregulation of metabolic-related and defective degradation processes in both the spinal cord and frontal cortex. Additionally, we observed the dysregulation of histone regulation and blood pressure-related genes specifically in the frontal cortex.

CONCLUSIONS

These results highlight the distinct and shared molecular disruptions in ALS, emphasizing the critical roles of immune response and metabolic dysfunction in neuronal degeneration. Targeting these pathways may provide new therapeutic avenues to combat neurodegeneration and preserve neuronal health.

An in-silico study to determine susceptibility to cancer by evaluating the coding and non-coding non-synonymous single nucleotide variants in the SOCS3 gene

Single Nucleotide Variant (SNVs) affect gene expression as well as protein structure and activity, leading to reduced signaling capabilities and ultimately, increasing cancer risk. SOCS3 (suppressor of cytokine signaling 3), a critical tumor suppressor providing a substantial part in the feedback loop of the JAK/STAT pathway, is abnormally suppressed in various cancer. This study aims to screen non-coding and potentially deleterious coding SNVs in the SOCS3 gene. We performed six programs: PredictSNP1.0 (predicting Deleterious nsSNVs), ConSurf (analyzing sequence conservation), ModPred (analyzing SNVS in PTMs sites), I-Mutant and MUpro (to analyze SNVs effecting protein stability), and molecular docking and molecular dynamics (MD) (to assess the consequences of SOCS3 genetic variations on JAK interactions) for coding regions and three programs (UTRSite, SNP2TFBS, miRNA SNP) (to analyze SNVs effecting the gene expression) in non-coding regions, respectively. After screening 2786 SOCS3 SNVs, we found 10 SNVs, as well as 49 SNPs that change the function of non-coding areas. Out of 10 selected nsSNVs, 3 SNVs (W48R, R71C, N198S) predicted to be the most damaging by all the software programs, as well as one nsSNV (R194W) could be highly deleterious from Molecular Docking analysis combined with MD Simulations. Our findings propose a procedure for studying the structure-related consequences of SNVs on protein function in the future.Communicated by Ramaswamy H. Sarma.

Biological sex affects functional variation across the human genome

Humans display sexual dimorphism across many traits, but little is known about underlying genetic mechanisms and impacts on disease. We utilized single-cell RNA-seq of 480 lymphoblastoid cell lines to reveal that the vast majority (79%) of sex-biased genes are targets of transcription factors that display sex-biased expression. Further, we developed a two-step regression method that identified sex-biased expression quantitative trait loci (sb-eQTL) across the genome. In contrast to previous work, these sb-eQTL are abundant (n=10,754; FDR 5%) and reproducible (replication up to π1=0.56). These sb-eQTL are enriched in over 600 GWAS phenotypes, including 120 sb-eQTL associated with the female-biased autoimmune disease multiple sclerosis. Our results demonstrate widespread genetic impacts on sexual dimorphism and identify possible mechanisms and clinical targets for sex differences in diverse diseases.

Epigenomic partitioning of a polygenic risk score for asthma reveals distinct genetically driven disease pathways

BACKGROUND

Individual differences in susceptibility to developing asthma, a heterogeneous chronic inflammatory lung disease, are poorly understood. Whether genetics can predict asthma risk and how genetic variants modulate the complex pathophysiology of asthma are still debated.

AIM

To build polygenic risk scores for asthma risk prediction and epigenomically link predictive genetic variants to pathophysiological mechanisms.

METHODS

Restricted polygenic risk scores were constructed using single nucleotide variants derived from genome-wide association studies and validated using data generated in the Rotterdam Study, a Dutch prospective cohort of 14 926 individuals. Outcomes used were asthma, childhood-onset asthma, adulthood-onset asthma, eosinophilic asthma and asthma exacerbations. Genome-wide chromatin analysis data from 19 disease-relevant cell types were used for epigenomic polygenic risk score partitioning.

RESULTS

The polygenic risk scores obtained predicted asthma and related outcomes, with the strongest associations observed for childhood-onset asthma (2.55 odds ratios per polygenic risk score standard deviation, area under the curve of 0.760). Polygenic risk scores allowed for the classification of individuals into high-risk and low-risk groups. Polygenic risk score partitioning using epigenomic profiles identified five clusters of variants within putative gene regulatory regions linked to specific asthma-relevant cells, genes and biological pathways.

CONCLUSIONS

Polygenic risk scores were associated with asthma(-related traits) in a Dutch prospective cohort, with substantially higher predictive power observed for childhood-onset than adult-onset asthma. Importantly, polygenic risk score variants could be epigenomically partitioned into clusters of regulatory variants with different pathophysiological association patterns and effect estimates, which likely represent distinct genetically driven disease pathways. Our findings have potential implications for personalised risk mitigation and treatment strategies.

Identification of an Allele-Specific Transcription Factor Binding Interaction that May Regulate PLA2G2A Gene Expression

The secreted phospholipase A2 (sPLA2) isoform, sPLA2-IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA2-IIA. The work in the manuscript leveraged 4 publicly available datasets to investigate the mechanism by which rs11573156 influences sPLA2-IIA levels via bioinformatics and modeling analysis. Through genotype-tissue expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA2-IIA, PLA2G2A. SNP2TFBS was used to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified eQTL SNPs. Subsequently, candidate TF-SNP interactions were cross-referenced with the ChIP-seq results in matched tissues from ENCODE. SP1-rs11573156 emerged as the significant TF-SNP pair in the liver. Further analysis revealed that the upregulation of PLA2G2A transcript levels through the rs11573156 variant was likely affected by tissue SP1 protein levels. Using an ordinary differential equation based on Michaelis-Menten kinetic assumptions, we modeled the dependence of PLA2G2A transcription on SP1 protein levels, incorporating the SNP influence. Collectively, our analysis strongly suggests that the difference in the binding dynamics of SP1 to different rs11573156 alleles may underlie the allele-specific PLA2G2A expression in different tissues, a mechanistic model that awaits future direct experimental validation. This mechanism likely contributes to the variation in circulating sPLA2-IIA protein levels in the human population, with implications for a wide range of human diseases.

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

Integrated analysis of blood DNA methylation, genetic variants, circulating proteins, microRNAs, and kidney failure in type 1 diabetes

Variation in DNA methylation (DNAmet) in white blood cells and other cells/tissues has been implicated in the etiology of progressive diabetic kidney disease (DKD). However, the specific mechanisms linking DNAmet variation in blood cells with risk of kidney failure (KF) and utility of measuring blood cell DNAmet in personalized medicine are not clear. We measured blood cell DNAmet in 277 individuals with type 1 diabetes and DKD using Illumina EPIC arrays; 51% of the cohort developed KF during 7 to 20 years of follow-up. Our epigenome-wide analysis identified DNAmet at 17 CpGs (5'-cytosine-phosphate-guanine-3' loci) associated with risk of KF independent of major clinical risk factors. DNAmet at these KF-associated CpGs remained stable over a median period of 4.7 years. Furthermore, DNAmet variations at seven KF-associated CpGs were strongly associated with multiple genetic variants at seven genomic regions, suggesting a strong genetic influence on DNAmet. The effects of DNAmet variations at the KF-associated CpGs on risk of KF were partially mediated by multiple KF-associated circulating proteins and KF-associated circulating miRNAs. A prediction model for risk of KF was developed by adding blood cell DNAmet at eight selected KF-associated CpGs to the clinical model. This updated model significantly improved prediction performance (c-statistic = 0.93) versus the clinical model (c-statistic = 0.85) at P = 6.62 × 10-14. In conclusion, our multiomics study provides insights into mechanisms through which variation of DNAmet may affect KF development and shows that blood cell DNAmet at certain CpGs can improve risk prediction for KF in T1D.

Estrogen receptor 1 chromatin profiling in human breast tumors reveals high inter-patient heterogeneity with enrichment of risk SNPs and enhancer activity at most-conserved regions

Estrogen Receptor 1 (ESR1; also known as ERα, encoded by ESR1 gene) is the main driver and prime drug target in luminal breast cancer. ESR1 chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ESR1 chromatin action, along with its biological implications. Here, we use a large set of ESR1 ChIP-seq data from 70 ESR1+ breast cancers to explore inter-patient heterogeneity in ESR1 DNA binding to reveal a striking inter-tumor heterogeneity of ESR1 action. Of note, commonly shared ESR1 sites show the highest estrogen-driven enhancer activity and are most engaged in long-range chromatin interactions. In addition, the most commonly shared ESR1-occupied enhancers are enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ESR1 and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we can confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ESR1-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ESR1 landscape, with the most common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

Deconvolution of polygenic risk score in single cells unravels cellular and molecular heterogeneity of complex human diseases

Polygenic risk scores (PRSs) are commonly used for predicting an individual's genetic risk of complex diseases. Yet, their implication for disease pathogenesis remains largely limited. Here, we introduce scPRS, a geometric deep learning model that constructs single-cell-resolved PRS leveraging reference single-cell chromatin accessibility profiling data to enhance biological discovery as well as disease prediction. Real-world applications across multiple complex diseases, including type 2 diabetes (T2D), hypertrophic cardiomyopathy (HCM), and Alzheimer's disease (AD), showcase the superior prediction power of scPRS compared to traditional PRS methods. Importantly, scPRS not only predicts disease risk but also uncovers disease-relevant cells, such as hormone-high alpha and beta cells for T2D, cardiomyocytes and pericytes for HCM, and astrocytes, microglia and oligodendrocyte progenitor cells for AD. Facilitated by a layered multi-omic analysis, scPRS further identifies cell-type-specific genetic underpinnings, linking disease-associated genetic variants to gene regulation within corresponding cell types. We substantiate the disease relevance of scPRS-prioritized HCM genes and demonstrate that the suppression of these genes in HCM cardiomyocytes is rescued by Mavacamten treatment. Additionally, we establish a novel microglia-specific regulatory relationship between the AD risk variant rs7922621 and its target genes ANXA11 and TSPAN14. We further illustrate the detrimental effects of suppressing these two genes on microglia phagocytosis. Our work provides a multi-tasking, interpretable framework for precise disease prediction and systematic investigation of the genetic, cellular, and molecular basis of complex diseases, laying the methodological foundation for single-cell genetics.

Genetic mapping across autoimmune diseases reveals shared associations and mechanisms

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.

Multimodal cell atlas of the ageing human skeletal muscle

Muscle atrophy and functional decline (sarcopenia) are common manifestations of frailty and are critical contributors to morbidity and mortality in older people1. Deciphering the molecular mechanisms underlying sarcopenia has major implications for understanding human ageing2. Yet, progress has been slow, partly due to the difficulties of characterizing skeletal muscle niche heterogeneity (whereby myofibres are the most abundant) and obtaining well-characterized human samples3,4. Here we generate a single-cell/single-nucleus transcriptomic and chromatin accessibility map of human limb skeletal muscles encompassing over 387,000 cells/nuclei from individuals aged 15 to 99 years with distinct fitness and frailty levels. We describe how cell populations change during ageing, including the emergence of new populations in older people, and the cell-specific and multicellular network features (at the transcriptomic and epigenetic levels) associated with these changes. On the basis of cross-comparison with genetic data, we also identify key elements of chromatin architecture that mark susceptibility to sarcopenia. Our study provides a basis for identifying targets in the skeletal muscle that are amenable to medical, pharmacological and lifestyle interventions in late life.

Deep learning modeling of rare noncoding genetic variants in human motor neurons defines CCDC146 as a therapeutic target for ALS

Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease caused by the selective and progressive death of motor neurons (MNs). Understanding the genetic and molecular factors influencing ALS survival is crucial for disease management and therapeutics. In this study, we introduce a deep learning-powered genetic analysis framework to link rare noncoding genetic variants to ALS survival. Using data from human induced pluripotent stem cell (iPSC)-derived MNs, this method prioritizes functional noncoding variants using deep learning, links cis-regulatory elements (CREs) to target genes using epigenomics data, and integrates these data through gene-level burden tests to identify survival-modifying variants, CREs, and genes. We apply this approach to analyze 6,715 ALS genomes, and pinpoint four novel rare noncoding variants associated with survival, including chr7:76,009,472:C>T linked to CCDC146. CRISPR-Cas9 editing of this variant increases CCDC146 expression in iPSC-derived MNs and exacerbates ALS-specific phenotypes, including TDP-43 mislocalization. Suppressing CCDC146 with an antisense oligonucleotide (ASO), showing no toxicity, completely rescues ALS-associated survival defects in neurons derived from sporadic ALS patients and from carriers of the ALS-associated G4C2-repeat expansion within C9ORF72. ASO targeting of CCDC146 may be a broadly effective therapeutic approach for ALS. Our framework provides a generic and powerful approach for studying noncoding genetics of complex human diseases.

A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools

Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.

Sex-biased genetic regulation of inflammatory proteins in the Dutch population

BACKGROUND

Significant differences in immune responses, prevalence or susceptibility of diseases and treatment responses have been described between males and females. Despite this, sex-differentiation analysis of the genetic architecture of inflammatory proteins is largely unexplored. We performed sex-stratified meta-analysis after protein quantitative trait loci (pQTL) mapping using inflammatory biomarkers profiled using targeted proteomics (Olink inflammatory panel) of two population-based cohorts of Europeans.

RESULTS

Even though, around 67% of the pQTLs demonstrated shared effect between sexes, colocalization analysis identified two loci in the males (LINC01135 and ITGAV) and three loci (CNOT10, SRD5A2, and LILRB5) in the females with evidence of sex-dependent modulation by pQTL variants. Furthermore, we identified pathways with relevant functions in the sex-biased pQTL variants. We also showed through cross-validation that the sex-specific pQTLs are linked with sex-specific phenotypic traits.

CONCLUSION

Our study demonstrates the relevance of genetic sex-stratified analysis in the context of genetic dissection of protein abundances among individuals and reveals that, sex-specific pQTLs might mediate sex-linked phenotypes. Identification of sex-specific pQTLs associated with sex-biased diseases can help realize the promise of individualized treatment.

Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk

Genome-wide association studies (GWAS) are a powerful tool for detecting variants associated with complex traits and can help risk stratification and prevention strategies against pancreatic ductal adenocarcinoma (PDAC). However, the strict significance threshold commonly used makes it likely that many true risk loci are missed. Functional annotation of GWAS polymorphisms is a proven strategy to identify additional risk loci. We aimed to investigate single-nucleotide polymorphisms (SNP) in regulatory regions [transcription factor binding sites (TFBSs) and enhancers] that could change the expression profile of multiple genes they act upon and thereby modify PDAC risk. We analyzed a total of 12,636 PDAC cases and 43,443 controls from PanScan/PanC4 and the East Asian GWAS (discovery populations), and the PANDoRA consortium (replication population). We identified four associations that reached study-wide statistical significance in the overall meta-analysis: rs2472632(A) (enhancer variant, OR 1.10, 95%CI 1.06,1.13, p = 5.5 × 10-8), rs17358295(G) (enhancer variant, OR 1.16, 95%CI 1.10,1.22, p = 6.1 × 10-7), rs2232079(T) (TFBS variant, OR 0.88, 95%CI 0.83,0.93, p = 6.4 × 10-6) and rs10025845(A) (TFBS variant, OR 1.88, 95%CI 1.50,1.12, p = 1.32 × 10-5). The SNP with the most significant association, rs2472632, is located in an enhancer predicted to target the coiled-coil domain containing 34 oncogene. Our results provide new insights into genetic risk factors for PDAC by a focused analysis of polymorphisms in regulatory regions and demonstrating the usefulness of functional prioritization to identify loci associated with PDAC risk.

The glucocorticoid receptor gene (NR3C1) is linked to and associated with polycystic ovarian syndrome in Italian families

OBJECTIVES

Components of the hypothalamic-pituitary axis (HPA) pathway are potential mediators of the genetic risk of polycystic ovarian syndrome (PCOS). Impaired glucocorticoid receptor (NR3C1) expression and function may underlie impaired HPA-axis cortisol activity, thereby also contributing to the increased adrenal cortisol and androgen production present in women with PCOS. In this study, we aimed to identify whether NR3C1 is linked or in linkage disequilibrium (LD), that is, linkage joint to association, with PCOS in Italian peninsular families.

METHOD

In 212 Italian families with type 2 diabetes (T2D) from the Italian peninsula, previously recruited for a T2D study and phenotyped for PCOS, we used microarray to genotype 25 variants in the NR3C1 gene. We analyzed the 25 NR3C1 variants by Pseudomarker parametric linkage and LD analysis.

RESULTS

We found the novel implication in PCOS risk of two intronic variants located within the NR3C1 gene (rs10482672 and rs11749561), thereby extending the phenotypic implication related to impaired glucocorticoid receptor.

CONCLUSIONS

To the best of our knowledge, this is the first study to report NR3C1 as a risk gene in PCOS.

Deep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer's Disease

Background

There are various molecular hypotheses regarding Alzheimer's disease (AD) like amyloid deposition, tau propagation, neuroinflammation, and synaptic dysfunction. However, detailed molecular mechanism underlying AD remains elusive. In addition, genetic contribution of these molecular hypothesis is not yet established despite the high heritability of AD.

Objective

The study aims to enable the discovery of functionally connected multi-omic features through novel integration of multi-omic data and prior functional interactions.

Methods

We propose a new deep learning model MoFNet with improved interpretability to investigate the AD molecular mechanism and its upstream genetic contributors. MoFNet integrates multi-omic data with prior functional interactions between SNPs, genes, and proteins, and for the first time models the dynamic information flow from DNA to RNA and proteins.

Results

When evaluated using the ROS/MAP cohort, MoFNet outperformed other competing methods in prediction performance. It identified SNPs, genes, and proteins with significantly more prior functional interactions, resulting in three multi-omic subnetworks. SNP-gene pairs identified by MoFNet were mostly eQTLs specific to frontal cortex tissue where gene/protein data was collected. These molecular subnetworks are enriched in innate immune system, clearance of misfolded proteins, and neurotransmitter release respectively. We validated most findings in an independent dataset. One multi-omic subnetwork consists exclusively of core members of SNARE complex, a key mediator of synaptic vesicle fusion and neurotransmitter transportation.

Conclusions

Our results suggest that MoFNet is effective in improving classification accuracy and in identifying multi-omic markers for AD with improved interpretability. Multi-omic subnetworks identified by MoFNet provided insights of AD molecular mechanism with improved details.

HTNpedia: A Knowledge Base for Hypertension Research

BACKGROUND

Hypertension is notably a serious public health concern due to its high prevalence and strong association with cardiovascular disease and renal failure. It is reported to be the fourth leading disease that leads to death worldwide.

OBJECTIVES

Currently, there is no active operational knowledge base or database for hypertension or cardiovascular illness.

METHODS

The primary data source was retrieved from the research outputs obtained from our laboratory team working on hypertension research. We have presented a preliminary dataset and external links to the public repository for detailed analysis to readers.

RESULTS

As a result, HTNpedia was created to provide information regarding hypertension-related proteins and genes.

CONCLUSION

The complete webpage is accessible via www.mkarthikeyan.bioinfoau.org/HTNpedia.

Identification of an allele-specific transcription factor binding interaction that regulates PLA2G2A gene expression

The secreted phospholipase A 2 (sPLA 2 ) isoform, sPLA 2 -IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA 2 -IIA. Through Genotype-Tissue Expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA 2 -IIA, PLA2G2A . SNP2TFBS ( https://ccg.epfl.ch/snp2tfbs/ ) was utilized to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified SNPs. Subsequently, ChIP-seq peaks highlighted the TF combinations that specifically bind to the SNP, rs11573156. SP1 emerged as a significant TF/SNP pair in liver cells, with rs11573156/SP1 interaction being most prominent in liver, prostate, ovary, and adipose tissues. Further analysis revealed that the upregulation of PLA2G2A transcript levels through the rs11573156 variant was affected by tissue SP1 protein levels. By leveraging an ordinary differential equation, structured upon Michaelis-Menten enzyme kinetics assumptions, we modeled the PLA2G2A transcription's dependence on SP1 protein levels, incorporating the SNP's influence. Collectively, these data strongly suggest that the binding affinity differences of SP1 for the different rs11573156 alleles can influence PLA2G2A expression. This, in turn, can modulate sPLA2-IIA levels, impacting a wide range of human diseases.

The prolactin receptor gene (PRLR) is linked and associated with the risk of polycystic ovarian syndrome

The prolactin receptor gene (PRLR) may contribute to polycystic ovarian syndrome (PCOS) since it plays important roles in physiological ovarian functions. PRLR-knockout mice have irregular cycles and subfertility and variants in or around the PRLR gene were associated in humans with female testosterone levels and recurrent miscarriage. We tested 40 variants in the PRLR gene in 212 Italian families phenotyped by type 2 diabetes (T2D) and PCOS and found two intronic PRLR-variants (rs13436213 and rs1604428) significantly linked to and/or associated with the risk of PCOS. This is the first study to report PRLR as a novel risk gene in PCOS. Functional studies are needed to confirm these results.

Breast cancer risk SNPs converge on estrogen receptor binding sites commonly shared between breast tumors to locally alter estrogen signalling output

Estrogen Receptor alpha (ERα) is the main driver and prime drug target in luminal breast. ERα chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ERα chromatin action, along with its biological implications. Here, we use a large set of ERα ChIP-seq data from 70 ERα+ breast cancers to explore inter-patient heterogeneity in ERα DNA binding, to reveal a striking inter-tumor heterogeneity of ERα action. Interestingly, commonly-shared ERα sites showed the highest estrogen-driven enhancer activity and were most-engaged in long-range chromatin interactions. In addition, the most-commonly shared ERα-occupied enhancers were enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ERα and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we could confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ERα-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ERα landscape, with the most-common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

Genome-wide study of genetic polymorphisms predictive for outcome from first-line oxaliplatin-based chemotherapy in colorectal cancer patients

We conducted the first large genome-wide association study to identify novel genetic variants that predict better (or poorer) prognosis in colorectal cancer patients receiving standard first-line oxaliplatin-based chemotherapy vs chemotherapy without oxaliplatin. We used data from two phase III trials, NCCTG N0147 and NCCTG N9741 and a population-based patient cohort, DACHS. Multivariable Cox proportional hazards models were employed, including an interaction term between each SNP and type of treatment for overall survival (OS) and progression-free survival. The analysis was performed for studies individually, and the results were combined using fixed-effect meta-analyses separately for resected stage III colon cancer (3098 patients from NCCTG N0147 and 549 patients from DACHS) and mCRC (505 patients from NCCTG N9741 and 437 patients from DACHS). We further performed gene-based analysis as well as in silico bioinformatics analysis for CRC-relevant functional genomic annotation of identified loci. In stage III colon cancer patients, a locus on chr22 (rs11912167) was associated with significantly poorer OS after oxaliplatin-based chemotherapy vs chemotherapy without oxaliplatin (Pinteraction  < 5 × 10-8 ). For mCRC patients, three loci on chr1 (rs1234556), chr12 (rs11052270) and chr15 (rs11858406) were found to be associated with differential OS (P < 5 × 10-7 ). The locus on chr1 located in the intronic region of RCSD1 was replicated in an independent cohort of 586 mCRC patients from ALGB/SWOG 80405 (Pinteraction  = .04). The GWA gene-based analysis yielded for RCSD1 the most significant association with differential OS in mCRC (P = 6.6 × 10-6 ). With further investigation into its biological mechanisms, this finding could potentially be used to individualize first-line treatment and improve clinical outcomes.

Genetic regulators of cytokine responses upon BCG vaccination in children from West Africa

Genetic variation is a key factor influencing cytokine production capacity, but which genetic loci regulate cytokine production before and after vaccination, particularly in African population is unknown. Here, we aimed to identify single-nucleotide polymorphisms (SNPs) controlling cytokine responses after microbial stimulation in infants of West-African ancestry, comprising of low-birth-weight neonates randomized to bacillus Calmette-Guérin (BCG) vaccine-at-birth or to the usual delayed BCG. Genome-wide cytokine cytokine quantitative trait loci (cQTL) mapping revealed 12 independent loci, of which the LINC01082-LINC00917 locus influenced more than half of the cytokine-stimulation pairs assessed. Furthermore, nine distinct cQTLs were found among infants randomized to BCG. Functional validation confirmed that several complement genes affect cytokine response after BCG vaccination. We observed a limited overlap of common cQTLs between the West-African infants and cohorts of Western European individuals. These data reveal strong population-specific genetic effects on cytokine production and may indicate new opportunities for therapeutic intervention and vaccine development in African populations.

Novel Risk Variants in the Oxytocin Receptor Gene (OXTR) Possibly Linked to and Associated with Familial Type 2 Diabetes

The oxytocin system is well-known for its role in social bonding and reproduction. Recently, the oxytocin system was found to play other metabolic roles such as regulation of food intake, peripheral glucose uptake, and insulin sensitivity. Variants in OXTR gene have been associated with overeating, increased cardiovascular risk, and type 2 diabetes (T2D). We tested 20 microarray-derived single nucleotide polymorphisms in the OXTR gene in 212 Italian families with rich family history for T2D and found four novel and one previously reported variant suggestively significant for linkage and association with the risk of T2D. Our study has shed some light into the genetics of susceptibility to T2D at least in Italian families.

Disease-associated non-coding variants alter NKX2-5 DNA-binding affinity

Genome-wide association studies (GWAS) have mapped over 90 % of disease- or trait-associated variants within the non-coding genome, like cis-regulatory elements (CREs). Non-coding single nucleotide polymorphisms (SNPs) are genomic variants that can change how DNA-binding regulatory proteins, like transcription factors (TFs), interact with the genome and regulate gene expression. NKX2-5 is a TF essential for proper heart development, and mutations affecting its function have been associated with congenital heart diseases (CHDs). However, establishing a causal mechanism between non-coding genomic variants and human disease remains challenging. To address this challenge, we identified 8475 SNPs predicted to alter NKX2-5 DNA-binding using a position weight matrix (PWM)-based predictive model. Five variants were prioritized for in vitro validation; four of them are associated with traits and diseases that impact cardiovascular health. The impact of these variants on NKX2-5 binding was evaluated with electrophoretic mobility shift assay (EMSA) using purified recombinant NKX2-5 homeodomain. Binding curves were constructed to determine changes in binding between variant and reference alleles. Variants rs7350789, rs7719885, rs747334, and rs3892630 increased binding affinity, whereas rs61216514 decreased binding by NKX2-5 when compared to the reference genome. Our findings suggest that differential TF-DNA binding affinity can be key in establishing a causal mechanism of pathogenic variants.

Genetic Regulation of SMC Gene Expression and Splicing Predict Causal CAD Genes

BACKGROUND

Coronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies have identified over 175 loci associated with CAD. The majority of these loci are in noncoding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we aimed to identify the subset of the CAD loci associated with the regulation of transcription in distinct SMC phenotypes.

METHODS

We measured gene expression in SMCs isolated from the ascending aortas of 151 heart transplant donors of various genetic ancestries in quiescent or proliferative conditions and calculated the association of their expression and splicing with ~6.3 million imputed single-nucleotide polymorphism markers across the genome.

RESULTS

We identified 4910 expression and 4412 splicing quantitative trait loci (sQTLs) representing regions of the genome associated with transcript abundance and splicing. A total of 3660 expression quantitative trait loci (eQTLs) had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 eQTLs were SMC-specific and sex-biased, respectively. We made these results available for public query on a user-friendly website. To identify the effector transcript(s) regulated by CAD loci, we used 4 distinct colocalization approaches. We identified 84 eQTL and 164 sQTL that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. One CAD locus colocalized with a sex-specific eQTL (TERF2IP), and another locus colocalized with SMC-specific eQTL (ALKBH8). The most significantly associated CAD locus, 9p21, was an sQTL for the long noncoding RNA CDKN2B-AS1, also known as ANRIL, in proliferative SMCs.

CONCLUSIONS

Collectively, our results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.

Integrative Meta-Analysis of Huntington's Disease Transcriptome Landscape

Huntington's disease (HD) is a neurodegenerative disorder with autosomal dominant inheritance caused by glutamine expansion in the Huntingtin gene (HTT). Striatal projection neurons (SPNs) in HD are more vulnerable to cell death. The executive striatal population is directly connected with the Brodmann Area (BA9), which is mainly involved in motor functions. Analyzing the disease samples from BA9 from the SRA database provides insights related to neuron degeneration, which helps to identify a promising therapeutic strategy. Most gene expression studies examine the changes in expression and associated biological functions. In this study, we elucidate the relationship between variants and their effect on gene/downstream transcript expression. We computed gene and transcript abundance and identified variants from RNA-seq data using various pipelines. We predicted the effect of genome-wide association studies (GWAS)/novel variants on regulatory functions. We found that many variants affect the histone acetylation pattern in HD, thereby perturbing the transcription factor networks. Interestingly, some variants affect miRNA binding as well as their downstream gene expression. Tissue-specific network analysis showed that mitochondrial, neuroinflammation, vasculature, and angiogenesis-related genes are disrupted in HD. From this integrative omics analysis, we propose that abnormal neuroinflammation acts as a two-edged sword that indirectly affects the vasculature and associated energy metabolism. Rehabilitation of blood-brain barrier functionality and energy metabolism may secure the neuron from cell death.

Contribution of TEX15 genetic variants to the risk of developing severe non-obstructive oligozoospermia

Background: Severe spermatogenic failure (SPGF) represents one of the most relevant causes of male infertility. This pathological condition can lead to extreme abnormalities in the seminal sperm count, such as severe oligozoospermia (SO) or non-obstructive azoospermia (NOA). Most cases of SPGF have an unknown aetiology, and it is known that this idiopathic form of male infertility represents a complex condition. In this study, we aimed to evaluate whether common genetic variation in TEX15, which encodes a key player in spermatogenesis, is involved in the susceptibility to idiopathic SPGF. Materials and Methods: We designed a genetic association study comprising a total of 727 SPGF cases (including 527 NOA and 200 SO) and 1,058 unaffected men from the Iberian Peninsula. Following a tagging strategy, three tag single-nucleotide polymorphisms (SNPs) of TEX15 (rs1362912, rs323342, and rs323346) were selected for genotyping using TaqMan probes. Case-control association tests were then performed by logistic regression models. In silico analyses were also carried out to shed light into the putative functional implications of the studied variants. Results: A significant increase in TEX15-rs1362912 minor allele frequency (MAF) was observed in the group of SO patients (MAF = 0.0842) compared to either the control cohort (MAF = 0.0468, OR = 1.90, p = 7.47E-03) or the NOA group (MAF = 0.0472, OR = 1.83, p = 1.23E-02). The genotype distribution of the SO population was also different from those of both control (p = 1.14E-02) and NOA groups (p = 4.33-02). The analysis of functional annotations of the human genome suggested that the effect of the SO-associated TEX15 variants is likely exerted by alteration of the binding affinity of crucial transcription factors for spermatogenesis. Conclusion: Our results suggest that common variation in TEX15 is involved in the genetic predisposition to SO, thus supporting the notion of idiopathic SPGF as a complex trait.

The complex, dynamic SpliceOme of the small GTPase transcripts altered by technique, sex, genetics, tissue specificity, and RNA base editing

The small GTPase family is well-studied in cancer and cellular physiology. With 162 annotated human genes, the family has a broad expression throughout cells of the body. Members of the family have multiple exons that require splicing. Yet, the role of splicing within the family has been underexplored. We have studied the splicing dynamics of small GTPases throughout 41,671 samples by integrating Nanopore and Illumina sequencing techniques. Within this work, we have made several discoveries. 1). Using the GTEx long read data of 92 samples, each small GTPase gene averages two transcripts, with 83 genes (51%) expressing two or more isoforms. 2). Cross-tissue analysis of GTEx from 17,382 samples shows 41 genes (25%) expressing two or more protein-coding isoforms. These include protein-changing transcripts in genes such as RHOA, RAB37, RAB40C, RAB4B, RAB5C, RHOC, RAB1A, RAN, RHEB, RAC1, and KRAS. 3). The isolation and library technique of the RNAseq influences the abundance of non-sense-mediated decay and retained intron transcripts of small GTPases, which are observed more often in genes than appreciated. 4). Analysis of 16,243 samples of "Blood PAXgene" identified seven genes (3.7%; RHOA, RAB40C, RAB4B, RAB37, RAB5B, RAB5C, RHOC) with two or more transcripts expressed as the major isoform (75% of the total gene), suggesting a role of genetics in altering splicing. 5). Rare (ARL6, RAB23, ARL13B, HRAS, NRAS) and common variants (GEM, RHOC, MRAS, RAB5B, RERG, ARL16) can influence splicing and have an impact on phenotypes and diseases. 6). Multiple genes (RAB9A, RAP2C, ARL4A, RAB3A, RAB26, RAB3C, RASL10A, RAB40B, and HRAS) have sex differences in transcript expression. 7). Several exons are included or excluded for small GTPase genes (RASEF, KRAS, RAC1, RHEB, ARL4A, RHOA, RAB30, RHOBTB1, ARL16, RAP1A) in one or more forms of cancer. 8). Ten transcripts are altered in hypoxia (SAR1B, IFT27, ARL14, RAB11A, RAB10, RAB38, RAN, RIT1, RAB9A) with RHOA identified to have a transient 3'UTR RNA base editing at a conserved site found in all of its transcripts. Overall, we show a remarkable and dynamic role of splicing within the small GTPase family that requires future explorations.

Pharmacogenomics deliberations of 2-deoxy-d-glucose in the treatment of COVID-19 disease: an in silico approach

The outbreak of COVID-19 caused by the coronavirus (SARS-CoV-2) prompted number of computational and laboratory efforts to discover molecules against the virus entry or replication. Simultaneously, due to the availability of clinical information, drug-repurposing efforts led to the discovery of 2-deoxy-d-glucose (2-DG) for treating COVID-19 infection. 2-DG critically accumulates in the infected cells to prevent energy production and viral replication. As there is no clarity on the impact of genetic variations on the efficacy and adverse effects of 2-DG in treating COVID-19 using in silico approaches, we attempted to extract the genes associated with the 2-DG pathway using the Comparative Toxicogenomics Database. The interaction between selected genes was assessed using ClueGO, to identify the susceptible gene loci for SARS-CoV infections. Further, SNPs that were residing in the distinct genomic regions were retrieved from the Ensembl genome browser and characterized. A total of 80 SNPs were retrieved using diverse bioinformatics resources after assessing their (a) detrimental influence on the protein stability using Swiss-model, (b) miRNA regulation employing miRNASNP3, PolymiRTS, MirSNP databases, (c) binding of transcription factors by SNP2TFBS, SNPInspector, and (d) enhancers regulation using EnhancerDB and HaploReg reported A2M rs201769751, PARP1 rs193238922 destabilizes protein, six polymorphisms of XIAP effecting microRNA binding sites, EGFR rs712829 generates 15 TFBS, BECN1 rs60221525, CASP9 rs4645980, SLC2A2 rs5393 impairs 14 TFBS, STK11 rs3795063 altered 19 regulatory motifs. These data may provide the relationship between genetic variations and drug effects of 2-DG which may further assist in assigning the right individuals to benefit from the treatment.

A 5′ UTR Mutation Contributes to Down-Regulation of Bbs7 in the Berlin Fat Mouse

The Bardet–Biedl Syndrome 7 (Bbs7) gene was identified as the most likely candidate gene causing juvenile obesity in the Berlin Fat Mouse Inbred (BFMI) line. Bbs7 expression is significantly lower in the brain, adipose tissue, and liver of BFMI mice compared to lean C57BL/6NCrl (B6N) mice. A DNA sequence comparison between BFMI and B6N revealed 16 sequence variants in the Bbs7 promoter region. Here, we tested if these mutations contribute to the observed differential expression of Bbs7. In a cell-based dual-luciferase assay, we compared the effects of the BFMI and the B6N haplotypes of different regions of the Bbs7 promotor on the reporter gene expression. A single-nucleotide polymorphism (SNP) was identified causing a significant reduction in the reporter gene expression. This SNP (rs29947545) is located in the 5′ UTR of Bbs7 at Chr3:36.613.350. The SNP is not unique to BFMI mice but also occurs in several other mouse strains, where the BFMI allele is not associated with lower Bbs7 transcript amounts. Thus, we suggest a compensatory mutation in the other mouse strains that keeps Bbs7 expression at the normal level. This compensatory mechanism is missing in BFMI mice and the cell lines tested.

In silico analysis of upstream variants in Brazilian patients with Familial Hypercholesterolemia

Familial hypercholesterolemia (FH) is a prevalent autosomal genetic disease associated with increased risk of early cardiovascular events and death due to chronic exposure to very high levels of low-density lipoprotein cholesterol (LDL-c). Pathogenic variants in the coding regions of LDLR, APOB and PCSK9 account for most FH cases, and variants in non-coding regions maybe involved in FH as well. Variants in the upstream region of LDLR, APOB and PCSK9 were screened by targeted next-generation sequencing and their effects were explored using in silico tools. Twenty-five patients without pathogenic variants in FH-related genes were selected. 3 kb upstream regions of LDLR, APOB and PCSK9 were sequenced using the AmpliSeq (Illumina) and Miseq Reagent Nano Kit v2 (Illumina). Sequencing data were analyzed using variant discovery and functional annotation tools. Potentially regulatory variants were selected by integrating data from public databases, published data and context-dependent regulatory prediction score. Thirty-four single nucleotide variants (SNVs) in upstream regions were identified (6 in LDLR, 15 in APOB, and 13 in PCSK9). Five SNVs were prioritized as potentially regulatory variants (rs934197, rs9282606, rs36218923, rs538300761, g.55038486A>G). APOB rs934197 was previously associated with increased rate of transcription, which in silico analysis suggests that could be due to reducing binding affinity of a transcriptional repressor. Our findings highlight the importance of variant screening outside of coding regions of all relevant genes. Further functional studies are necessary to confirm that prioritized variants could impact gene regulation and contribute to the FH phenotype.

Functional regulatory variants implicate distinct transcriptional networks in dementia

Predicting the function of noncoding variation is a major challenge in modern genetics. In this study, we used massively parallel reporter assays to screen 5706 variants identified from genome-wide association studies for both Alzheimer's disease (AD) and progressive supranuclear palsy (PSP), identifying 320 functional regulatory variants (frVars) across 27 loci, including the complex 17q21.31 region. We identified and validated multiple risk loci using CRISPR interference or excision, including complement 4 (C4A) and APOC1 in AD and PLEKHM1 and KANSL1 in PSP. Functional variants disrupt transcription factor binding sites converging on enhancers with cell type-specific activity in PSP and AD, implicating a neuronal SP1-driven regulatory network in PSP pathogenesis. These analyses suggest that noncoding genetic risk is driven by common genetic variants through their aggregate activity on specific transcriptional programs.