GWAS Analysis Research Articles

GWAS and transcriptome analysis reveal key loci associated with drought tolerance in soybean

Genome-wide association and gene expression studies were conducted to identify key genes and markers associated with drought tolerance. GWAS panel consisting around 300 diverse soybean accessions were phenotyped for morpho-physiological traits under control and drought stress condition for three years during 2019-2021. Genotyping by Sequencing (GBS) of GWAS panel identified 66300 SNPs distributed over all the 20 chromosomes and were used for association analysis. GWAS analysis revealed closely located significant SNPs on chromosome 4 (50500762, 52098616 and 53008801) and chromosome 16 (32371663, 33082976 and 33283177). Key candidate genes related to MYB family, cell signaling gene (GPCR), salicylic acid synthesis, oxidative stress, auxin and ABA synthesis pathway were identified. Further few tolerant and susceptible haplotypes were also identified for real-time based expression analysis under drought stress condition.

Genome wide association studies reveals genetic loci associated with water logging tolerance in Soybean [Glycine max (L.) Merr.

In this investigation, a GWAS analysis was performed for four water logging tolerance traits in a panel of 265 soybean germplasm accessions with 66719 SNPs. A total of 29 SNPs and some candidate genes associated with different water logging tolerance traits were identified. This study also identified some soybean accessions, having superior water logging tolerance ability at vegetative and reproductive stages, which may be used as potential donors in soybean improvement programs.

Word-based GWAS harnesses the rich potential of genomic data for E. coli quinolone resistance.

Quinolone resistance presents a growing global health threat. We employed word-based GWAS to explore genomic data, aiming to enhance our understanding of this phenomenon. Unlike traditional variant-based GWAS analyses, this approach simultaneously captures multiple genomic factors, including single and interacting resistance mutations and genes. Analyzing a dataset of 92 genomic E. coli samples from a wastewater treatment plant in Dresden, we identified 54 DNA unitigs significantly associated with quinolone resistance. Remarkably, our analysis not only validated known mutations in gyrA and parC genes and the results of our variant-based GWAS but also revealed new (mutated) genes such as mdfA, the AcrEF-TolC multidrug efflux system, ptrB, and hisI, implicated in antibiotic resistance. Furthermore, our study identified joint mutations in 14 genes including the known gyrA gene, providing insights into potential synergistic effects contributing to quinolone resistance. These findings showcase the exceptional capabilities of word-based GWAS in unraveling the intricate genomic foundations of quinolone resistance.

Comparative Application of Terminal Restriction Fragment Analysis Tools to Large-Scale Genomic Assays.

The analysis of telomere length is an important component of many studies aiming to characterize the role of telomere maintenance mechanisms in cellular lifespan, disease, or in general chromosome protection and DNA replication pathways. Several powerful methods to accurately measure the telomere length from Southern blots have been developed, but their utility for large-scale genomic studies has not been previously evaluated. Here, we performed a comparative analysis of two recently developed programs, TeloTool and WALTER, for the extraction of mean telomere length values from Southern blots. Using both software packages, we measured the telomere length in two extensive experimental datasets for the model plant Arabidopsis thaliana, consisting of 537 natural accessions and 65 T-DNA (transfer DNA for insertion mutagenesis) mutant lines in the reference Columbia (Col-0) genotype background. We report that TeloTool substantially overestimates the telomere length in comparison to WALTER, especially for values over 4500 bp. Importantly, the TeloTool- and WALTER-calculated telomere length values correlate the most in the 2100-3500 bp range, suggesting that telomeres in this size interval can be estimated by both programs equally well. We further show that genome-wide association studies using datasets from both telomere length analysis tools can detect the most significant SNP candidates equally well. However, GWAS analysis with the WALTER dataset consistently detects fewer significant SNPs than analysis with the TeloTool dataset, regardless of the GWAS method used. These results imply that the telomere length data generated by WALTER may represent a more stringent approach to GWAS and SNP selection for the downstream molecular screening of candidate genes. Overall, our work reveals the unanticipated impact of the telomere length analysis method on the outcomes of large-scale genomic screens.

Isoform characterisation & splicing signatures of AD‐risk genes using long‐read sequencing

AbstractBackgroundAn increasing number of studies implicate a role for alternative splicing in development and neuropathology of Alzheimer’s disease (AD). However, it has been historically challenging to characterise splicing events, due to the inherent limitations of traditional RNA‐sequencing (RNA‐Seq) to capture full‐length transcripts critical for transcriptome assembly. In this study, we use two complementary targeted long‐read sequencing approaches, Pacific Biosciences (PacBio) isoform sequencing (Iso‐Seq) and Oxford Nanopore Technologies (ONT) nanopore cDNA sequencing, to profile the cortex of a mouse model of tau pathology (rTg4510) with ultra‐deep sequencing of a panel of 20 genes robustly implicated in AD.MethodTargeted PacBio Iso‐Seq and targeted ONT profiling were performed on RNA isolated from 24 female rTg4510 transgenic and wild‐type mice, aged 2, 4, 6 and 8 months. Following successful enrichment for target genes using custom‐designed probes (IDT), library preparation were performed for subsequent sequencing on Sequel and MinION. The panel of genes selected for enrichment included genes (i.e. App, Mapt, Snca) and dementia risk genes identified from GWAS analyses. Raw sequence data was processed using a customised bioinformatics, and full‐length reads were merged and annotated with our developed custom scripts (FICLE).ResultWe identify thousands of novel transcripts across the panel of 20 AD‐ and dementia‐associated genes. We reveal unprecedented diversity of alternatively‐spliced isoforms with widespread usage of alternative novel 5’ and 3’ splice sites. We further robust transcriptional and splicing differences in these AD‐risk genes associated with the development of tau pathology. Among these changes, we observed global up‐regulation of Trem2‐associated isoforms and isoform switches in Bin1, further supporting a role for the dysregulation of the immune response in the development of AD pathology.ConclusionThis represents the first study to comprehensively assess variable AS associated with the development of tau pathology using both PacBio Iso‐Seq and ONT nanopore sequencing. Our analyses confirm the importance of alternative RNA splicing in AD and identify evidence of differential transcript usage, even in the absence of gene‐level expression alterations. Further work will be undertaken to validate and functionally characterise these novel isoforms, and to extend these analyses to human post‐mortem AD brain samples.

Integration of multiple single cell microglial datasets reveals radial differentiation into long‐lived substates associated with Alzheimer’s pathology

AbstractBackgroundUnsupervised classification of brain cell types can be readily achieved through analysis of gene expression patterns in multidimensional space. However, the small transcriptional differences between microglia subtypes require more principled, robust, and reproducible approaches to expose and distinguish biological differences from noise.MethodHere we leverage Fokker‐Planck diffusion maps [1,2] to examine the dynamics of microglia subtypes by finding a low dimensional representation of the underlying stochastic dynamical system responsible for generating these transcriptional states. Clustering directly on this projection allows us to reduce noise, assign time scales to these substates, and generate a hierarchy of microglial cell states. Once these subtypes have been defined, we apply pseudobulk differential expression analysis to identify marker genes, and use those genes to build a boosted tree model to classify cells states. We then apply Shapley additive explanations (SHAP) to identify which genes are most important for distinguishing between cell states.ResultWe observe a radial transition pattern emanating, with a subtype that appears homeostatic, inactivated, and poised for transition. This is consistent with the observation that microglia dynamics are sensitive to their microenvironment. Deconvolution of an independent bulk microglia dataset (n = 130) showed depletion in subtypes linked to protein misfolding and myelin phagocytosis, as well as enrichment in immunoreactive microglia in Alzheimer’s patients. SHAP reveals DUSP1, CD83, PLCG2, OLR1,CCL2, and JUN among the most important genes for differentiating into these AD‐associated clusters.ConclusionOur approach enables us to reproducibly identify microglial subtypes across sets of single cell‐resolution high dimensional molecular profile data, identifying likely drivers of subtype differentiation. With several of our driver genes already associated with Alzheimer’s via GWAS and other analyses, our results will enable us to elucidate the role of these genes in determining microglial subtypes.

Genetic Diversity and Genome-Wide Association Study for the Phenology Response of Winter Wheats of North America, Western Asia, and Europe

Wheat is a staple food in many areas around the World. In the 20th century, breeders and scientists were able to boost wheat yield considerably. However, a yield plateau has become a concern and is threatening food security. Investments in cutting-edge technologies, including genomics and precision phenology measurements, can provide valuable tools to drive crop improvement. The objectives of this study were to (i) investigate the genetic diversity in a set of winter wheat lines, (ii) characterize their phenological response under different vernalization and photoperiod conditions, and (iii) identify effective markers associated with the phenological traits. A total of 249 adapted genotypes of different geographical origin were genotyped using the 35K Axiom® Wheat Breeder’s Array. A total of 11,476 SNPs were used for genetic analysis. The set showed an average polymorphism information content of 0.37 and a genetic diversity of 0.43. A population structure analysis revealed three distinct subpopulations mainly related to their geographical origin (Europe, North America, and Western Asia). The lines of CGIAR origin showed the largest diversity and the lowest genetic distance to all other subpopulations. The phenology of the set was studied under controlled conditions using four combinations of long (19 h light) and short photoperiod (13 h light) and long vernalization (49 days at 5 °C) and no vernalization. With this, phenological traits such as earliness per se (Eps), relative response to vernalization (RRV), and relative response to photoperiod (RRP) were calculated. The phenotypic variation of growing degree days was significant in all phenology combinations. RRV ranged from 0 to 0.56, while RRP was higher with an overall average of 0.25. The GWAS analysis detected 30 marker-trait associations linked to five phenological traits. The highest significant marker was detected on chromosome 2D with a value of −log10(p) = 11.69. Only four loci known to regulate flowering exceeded the Bonferroni correction threshold of −log10(p) > 5.1. These results outline a solid foundation to address global food security and offer tremendous opportunities for advancing crop improvement strategies.

Identification and replication of gene‐by‐stress interaction associations with Alzheimer’s disease and related dementias

AbstractBackgroundSeveral mechanisms have been hypothesized for the pathogenesis of Alzheimer’s disease and related dementias (ADRD); however, we are still far from effective prevention and treatment of the disease, thus more basic research is needed to understand the etiological neuropathogenesis. We hypothesized that a part of increased ADRD‐risk could be due to a complex interplay of genes and daily‐life psychosocial stress.MethodWe used the Health and Retirement Study (HRS) surveys and Medicare‐linked data for the discovery analysis and the Long‐Life Family Study (LLFS) dataset for replication analysis, creating a synthetic stress measure using the algorithm based on stress proxy‐indicators, as described in Singh et al., 2015. The two datasets were compared by evaluating samples’ stress levels and socioeconomic status. We performed the HRS gene‐by‐stress discovery GWAS analyses on age‐at‐onset of ADRD using linear regression with SNP, STRESS, SEX, and ancestry principal components as other terms in model. We fitted the same regression model in the LLFS replication analysis, adjusting it additionally with field centers and Huber–White familial clustering.ResultThe HRS GWASs resulted in associations at p‐value of order 10−8 in both Blacks and Whites. Although most of the top 25 significant SNPs were mapped to non‐coding regions, we identified four characterized genes (BCR, MCC, KCNQ5, and DCP2) in Whites and three genes (EMCN, DPYD, and INSYN2A) in Blacks. Published literature from human and experimental studies suggested that five out of the eight genes were known for their association with neurodevelopmental disorders including Autism, intellectual disability, but also for cancers including colorectal carcinoma, gastric carcinoma, and leukemia. Although LLFS samples presented higher socioeconomic status and lower stress levels compared to HRS samples, the associations of one‐third tested SNPs from HRS Whites replicated in LLFS samples.ConclusionOur findings suggest that daily‐life stress may contribute to the risk of ADRD via complex interactions with genes. The associations with non‐coding genetic variants may indicate their influence through gene‐regulatory roles. In addition, the associations observed with cancer genes may possibly point towards the involvement of a common mechanistic feature, e.g., angiogenesis, which needs to be investigated further.

Impact of Genetic Variations on Thrombotic Risk in Saudis with Sickle Cell Disease

Background Sickle cell disease (SCD) is a Mendelian disease characterised by multigenic phenotypes. Previous reports indicated a higher rate of venous thromboembolism (VTE) in SCD patients. A number of candidate polymorphisms in certain genes (e.g. FVL, PRT, and MTHFR) were previously reported as risk factors for VTE in different clinical conditions. This study aimed to genotype these genes and other loci predicted to underlay VTE in SCD patients. Methodology A genome-wide association study involving Saudi SCD adult patients with a history of VTE (n=65) and control patients without VTE history (n=285) was performed. Genotyping used the 10x Affymetrix Axiom array which includes 683,030 markers. Results No associations were identified between the targeted single nucleotide polymorphisms (SNPs) [FVL (rs6025), PRT (rs1799963), and MTHFR (rs1801133)] and VTE episodes in SCD patients. In contrast, GWAS analysis showed two genome-wide significant signals (P<5×10 -8) on chromosome (Chr) 11. These SNPs, rs35390334 and rs331532, are in strong linkage equilibrium (LD, r 2=0.97). A total of 35 other markers had an association threshold of P<5×10 -6. Four of these variants are located in olfactory receptor genes [OR51B5 (rs147062602), OR51V1 (rs7933549), OR51A1P (rs80034548), and OR52A5 (rs2472530)]. Conclusion No association between FVL, PRT, and MTHFR genes and VTE episodes was seen in Saudis with SCD. In contrast, two markers (rs35390334 and rs331532) showed significant genome-wide associations and less significant associations (P<5×10 -6) were identified for 35 other variants (24 of them are located on Chr 11). Further replication of these findings is needed.

Mendelian randomization identifies sex differences in pain manifestation of coronary artery disease

Abstract Background and aim Clinical manifestation of atherogenic cardiovascular disease differs between men and women. Men often present with classical symptoms i.e., chest pain radiating to left arm and jaw. Women may show a wide range of symptoms considered atypical, including but not limited to back pain and nausea. Anatomical pathways feeding cardiac pain have not been properly characterized with respect to sex-related differences in human at population level. Methods We performed sex-stratified GWAS analysis on CAD as well as chest, neck and shoulder, back and facial pain using the UK Biobank cohort (men N = 203,823; women N = 239,631). To unravel given differences in pain manifestation of atherogenic cardiovascular disease in men and women, we performed Mendelian Randomization to approximate the causal associations between coronary artery disease (CAD) and a variety of pain locations. Results We identified 32 and 19 independent instrumental variables (R2< 0.001, p-value 5x10-6) associated with CAD for men and women, respectively. MR analysis revealed potential causality between CAD and self-reported chest pain for men (OR: 1.33, CI: 1.25 – 1.41) and women (OR: 1.44, CI: 1.20 – 1.73) as well as a link between CAD and clinical chest pain for both sexes (men OR: 1.22, CI: 1.17 — 1.26; women OR: 1.31, CI: 1.18 — 1.46). MR displayed a relationship between CAD and back pain in women (OR: 1.35, CI: 1.03 — 1.66) but not in men (OR: 0.99, CI: 0.90 — 1.11, p-value difference: 0.036). Manifestation of neck and shoulder pain revealed a suggestive difference in causality between men and women (p-value difference: 0.051). Discussion Our study provided evidence supporting a causal association between CAD with manifestation of chest pain in both men and women. Additionally, no stronger effect in men was found contrary to clinical observations suggesting pain perception of the chest at population level could be similar between the sexes. Manifestation of back pain with CAD, however, showed a more causal effect in women compared to men. Here we show that pain perception of the heart is not limited to the chest in women at population level. Future research is required to identify what drives these differences at multiple levels.

Abstract 18805: Large-Scale Genome-Wide Association Study of Dilated Cardiomyopathy Identifies Genes and Pathways Contributing to Pathology

Introduction: Dilated cardiomyopathy (DCM) is a primary heart muscle disease that has long been considered a Mendelian disorder, but recent evidence highlights the important role of common genetic variation. Better characterization of the genetic architecture will provide opportunities for improved diagnosis and risk stratification. Methods: We performed a GWAS meta-analysis of 14,256 DCM cases and 1,185,671 controls of European ancestry from 16 studies. To improve discovery power, we performed multi-trait analysis of GWAS (MTAG) with three genetically correlated cardiac imaging traits in 36,203 individuals. We performed gene-level burden analysis <0.1% for rare predicted truncating variants (PTV) with minor allele frequency <0.1% in prioritized genes against DCM and quantitative CMR traits in UK Biobank (UKB) and 100,000 Genomes Project (GeL). A polygenic score (PGS) generated using a Bayesian framework was assessed for association with the same outcomes in UKB participants. Results: We identified 80 independent genomic loci associated with DCM at a false discovery rate <1% in GWAS or at P < 5 x 10 -8 in MTAG, of which 65 were novel ( Figure ). We prioritized a single high-confidence gene at 61 loci, including established genes for Mendelian cardiomyopathies ( TTN , BAG3 , FLNC , MYBPC3 , FHOD3 , ALPK3 ). Rare variant analysis highlighted novel associations with DCM and quantitative traits for PTVs in NEDD4L and MAP3K7 in UKB that were replicated in GeL. PGS was associated with DCM, with a 4-fold increased risk for those at the top centile compared to the median distribution. Penetrance of rare variants were higher for those in the top quintile of PGS compared to bottom quintile (7.3% vs. 1.7%, P <0.005). Conclusion: We have performed the largest DCM GWAS, resulting in 80 significant loci (65 novel). We identify novel DCM-causing genes and generate a PGS that associates with DCM and modulates penetrance in carriers of Mendelian disease-causing rare variants.

Genetic analysis of phenotypic plasticity identifies BBX6 as the candidate gene for maize adaptation to temperate regions.

Climate changes pose a significant threat to crop adaptation and production. Dissecting the genetic basis of phenotypic plasticity and uncovering the responsiveness of regulatory genes to environmental factors can significantly contribute to the improvement of climate- resilience in crops. We established a BC1F3:4 population using the elite inbred lines Zheng58 and PH4CV and evaluated plant height (PH) across four environments characterized by substantial variations in environmental factors. Then, we quantified the correlation between the environmental mean of PH (the mean performance in each environment) and the environmental parameters within a specific growth window. Furthermore, we performed GWAS analysis of phenotypic plasticity, and identified QTLs and candidate gene that respond to key environment index. After that, we constructed the coexpression network involving the candidate gene, and performed selective sweep analysis of the candidate gene. We found that the environmental parameters demonstrated substantial variation across the environments, and genotype by environment interaction contributed to the variations of PH. Then, we identified PTT(35-48) (PTT is the abbreviation for photothermal units), the mean PTT from 35 to 48 days after planting, as the pivotal environmental index that closely correlated with environmental mean of PH. Leveraging the slopes of the response of PH to both the environmental mean and PTT(35-48), we successfully pinpointed QTLs for phenotypic plasticity on chromosomes 1 and 2. Notably, the PH4CV genotypes at these two QTLs exhibited positive contributions to phenotypic plasticity. Furthermore, our analysis demonstrated a direct correlation between the additive effects of each QTL and PTT(35-48). By analyzing transcriptome data of the parental lines in two environments, we found that the 1009 genes responding to PTT(35-48) were enriched in the biological processes related to environmental sensitivity. BBX6 was the prime candidate gene among the 13 genes in the two QTL regions. The coexpression network of BBX6 contained other genes related to flowering time and photoperiod sensitivity. Our investigation, including selective sweep analysis and genetic differentiation analysis, suggested that BBX6 underwent selection during maize domestication. Th is research substantially advances our understanding of critical environmental factors influencing maize adaptation while simultaneously provides an invaluable gene resource for the development of climate-resilient maize hybrid varieties.

A high-resolution haplotype-resolved Reference panel constructed from the China Kadoorie Biobank Study.

Precisionmedicine depends on high-accuracy individual-level genotype data. However, the whole-genome sequencing (WGS) is still not suitable for gigantic studies due to budget constraints. It is particularly important to construct highly accurate haplotype reference panel for genotype imputation. In this study, we used 10000 samples with medium-depth WGS to construct a reference panel that wenamed theCKB reference panel. By imputing microarray datasets, it showed that the CKB panel outperformed compared panels in terms of both the number of well-imputed variants and imputation accuracy. In addition, we have completed the imputation of 100 706 microarrays with the CKB panel, and the after-imputed data is the hitherto largest whole genome data of the Chinese population. Furthermore, in the GWAS analysis of real phenotype height, the number of tested SNPs tripled and the number of significant SNPs doubled after imputation. Finally, we developed an online server for offering free genotype imputation service based on the CKB reference panel (https://db.cngb.org/imputation/). We believe that the CKB panel is of great value for imputing microarray or low-coverage genotype data of Chinese population, and potentially mixed populations. The imputation-completed 100 706 microarray data are enormous and precious resources of population genetic studies for complex traits and diseases.

Genome-wide association analysis of heifer livability and early first calving in Holstein cattle

BackgroundThe survival and fertility of heifers are critical factors for the success of dairy farms. The mortality of heifers poses a significant challenge to the management and profitability of the dairy industry. In dairy farming, achieving early first calving of heifers is also essential for optimal productivity and sustainability. Recently, Council on Dairy Cattle Breeding (CDCB) and USDA have developed new evaluations of heifer health and fertility traits. However, the genetic basis of these traits has yet to be thoroughly studied.ResultsLeveraging the extensive U.S dairy genomic database maintained at CDCB, we conducted large-scale GWAS analyses of two heifer traits, livability and early first calving. Despite the large sample size, we found no major QTL for heifer livability. However, we identified a major QTL in the bovine MHC region associated with early first calving. Our GO analysis based on nearby genes detected 91 significant GO terms with a large proportion related to the immune system. This QTL in the MHC region was also confirmed in the analysis of 27 K bull with imputed sequence variants. Since these traits have few major QTL, we evaluated the genome-wide distribution of GWAS signals across different functional genomics categories. For heifer livability, we observed significant enrichment in promotor and enhancer-related regions. For early calving, we found more associations in active TSS, active Elements, and Insulator. We also identified significant enrichment of CDS and conserved variants in the GWAS results of both traits. By linking GWAS results and transcriptome data from the CattleGTEx project via TWAS, we detected four and 23 significant gene-trait association pairs for heifer livability and early calving, respectively. Interestingly, we discovered six genes for early calving in the Bovine MHC region, including two genes in lymph node tissue and one gene each in blood, adipose, hypothalamus, and leukocyte.ConclusionOur large-scale GWAS analyses of two heifer traits identified a major QTL in the bovine MHC region for early first calving. Additional functional enrichment and TWAS analyses confirmed the MHC QTL with relevant biological evidence. Our results revealed the complex genetic basis of heifer health and fertility traits and indicated a potential connection between the immune system and reproduction in cattle.

GWAS analysis of maize host plant resistance to western corn rootworm (Coleoptera: Chrysomelidae) reveals candidate small effect loci for resistance breeding.

Western corn rootworm, Diabrotica virgifera virgifera (LeConte) (Coleoptera: Chrysomelidae), is the most serious economic pest of maize, Zea mays (L.) (Poales: Poaceae), in the U.S. Corn Belt and also threatens production in Europe. Traditional management options have repeatedly failed over time as western corn rootworm rapidly develops resistance to insecticides, transgenic maize and even crop rotation. Traits that improve host plant resistance and tolerance are highly sought after by plant breeders for crop protection and pest management. However, maize resistance to western corn rootworm appears to be highly complex and despite over 75 yr of breeding efforts, there are no naturally resistant hybrids available commercially. Using phenotypic data from field and greenhouse experiments on a highly diverse collection of 282 inbred lines, we screened and genetically mapped western corn rootworm-related traits to identify genetic loci which may be useful for future breeding or genetic engineering efforts. Our results confirmed that western corn rootworm resistance is complex with relatively low heritability due in part to strong genotype by environment impacts and the inherent difficulties of phenotyping below ground root traits. The results of the Genome Wide Associated Study identified 29 loci that are potentially associated with resistance to western corn rootworm. Of these loci, 16 overlap with those found in previous transcription or mapping studies indicating a higher likelihood they are truly involved in maize western corn rootworm resistance. Taken together with previous studies, these results indicate that breeding for natural western corn rootworm resistance will likely require the stacking of multiple small effect loci.

OR12-02 NRF2 Is Essential For Expanding Pancreatic Beta-Cell Mass During Pregnancy

Abstract Disclosure: S. Baumel-Alterzon: None. A. Garcia-Ocana: None. D.K. Scott: None. The late stages of the mammalian pregnancy are accompanied with increased insulin resistance due to the increased glucose demand of the growing fetus. Therefore, as a compensatory response, in order to maintain the maternal normal blood glucose levels, maternal beta-cell mass expands leading to increased insulin release. Beta-cell proliferation, beta-cell neogenesis, and decreased beta-cell apoptosis, are major contributors for the beta-cell adaptive response during pregnancy. Defects in these cellular processes can lead to gestational diabetes mellitus (GDM). GDM, which occurs in ∼7-8% of the total pregnancy cases within the U.S, results in adverse outcomes for both the mother and newborn. This highlights the urgent need for exploring the yet undefined intracellular mechanisms that regulate functional beta-cell mass expansion during pregnancy. GWAS analysis revealed several mutations in the Nrf2 antioxidant pathway that are associated with diabetes. Additionally, we previously found that Nrf2 is required for adaptive beta-cell expansion after high fat feeding via stimulation of beta-cell proliferation, increased beta-cell survival, and maintenance of beta-cell identity. Interestingly, Nrf2 expression levels are increased by 4.3-fold (+/- 6.60, p<0.05, n=3-4) in maternal beta-cells during pregnancy, peaking at gestational day (GD)19, while returning to normal levels postpartum. Based on these observations, we hypothesize that Nrf2 might play an important role in expanding beta-cell mass during pregnancy and that disruption of Nrf2 expression or function might lead to GDM. In order to test our hypothesis, we generated tamoxifen (Tam)-induced beta cell-specific deletion of Nrf2 in female mice by crossing MIP-CreERTTAM with Nrf2lox/lox mice (βNrf2KO). In order to exclude any effect of Tam on pregnancy outcomes, females mice were injected with Tam (or vehicle control) a month before gestation. Pancreata were harvested at GD15 or GD19 and immunolabeled with Ki67 and insulin (proliferation assay), TUNEL and insulin (apoptotic assay) or insulin alone (beta-cell mass analysis). Our results show that βNrf2KO mice exhibit 70% reduction (+/- 0.25, p<0.01, n=4-6) in beta-cell proliferation and a 0.13% increase in beta-cell death (+/- 0.03, p<0.05, n=4-6) at GD15 compared to littermate controls. Importantly, βNrf2KO pregnant mice display a remarkable decrease in beta-cell mass at GD19 (50%) (+/- 0.68, p<0.05, n=4) compared with control mice, accompanied by a trending decrease in plasma insulin and increase in blood glucose. No changes were observed in the average number of embryos between βNrf2KO and control pregnant mice. We conclude that Nrf2 is required for beta-cell mass expansion during pregnancy by controlling beta-cell proliferation and survival and alterations in Nrf2 action could potentially lead to development of GDM. Presentation: Friday, June 16, 2023

OC 17.2 New Insights on the Genetics of Venous Thromboembolism Recurrence from a GWAS Analysis of 6,504 Patients Including 1,797 Recurrent Events

OC 17.2 New Insights on the Genetics of Venous Thromboembolism Recurrence from a GWAS Analysis of 6,504 Patients Including 1,797 Recurrent Events

Human Leukocyte Antigen Signatures as Pathophysiological Discriminants of Microscopic Colitis Subtypes.

Microscopic colitis [MC] is currently regarded as an inflammatory bowel disease that manifests as two subtypes: collagenous colitis [CC] and lymphocytic colitis [LC]. Whether these represent a clinical continuum or distinct entities is, however, an open question. Genetic investigations may contribute important insight into their respective pathophysiologies. We conducted a genome-wide association study [GWAS] meta-analysis in 1498 CC, 373 LC patients, and 13 487 controls from Europe and the USA, combined with publicly available MC GWAS data from UK Biobank and FinnGen [2599 MC cases and 552 343 controls in total]. Human leukocyte antigen [HLA] alleles and polymorphic residues were imputed and tested for association, including conditional analyses for the identification of key causative variants and residues. Genetic correlations with other traits and diagnoses were also studied. We detected strong HLA association with CC, and conditional analyses highlighted the DRB1*03:01 allele and its residues Y26, N77, and R74 as key to this association (best p = 1.4 × 10-23, odds ratio [OR] = 1.96). Nominally significant genetic correlations were detected between CC and pneumonia [rg = 0.77; p = 0.048] and oesophageal diseases [rg = 0.45, p = 0.023]. An additional locus was identified in MC GWAS analyses near the CLEC16A and RMI2 genes on chromosome 16 [rs35099084, p = 2.0 × 10-8, OR = 1.31]. No significant association was detected for LC. Our results suggest CC and LC have distinct pathophysiological underpinnings, characterised by an HLA predisposing role only in CC. This challenges existing classifications, eventually calling for a re-evaluation of the utility of MC umbrella definitions.

Heritability of amygdala reactivity to angry faces and its replicable association with the schizophrenia risk locus of miR-137.

Among healthy participants, the interindividual variability of brain response to facial emotions is associated with genetic variation, including common risk variants for schizophrenia, a heritable brain disorder characterized by anomalies in emotion processing. We aimed to identify genetic variants associated with heritable brain activity during processing of facial emotions among healthy participants and to explore the impact of these identified variants among patients with schizophrenia. We conducted a data-driven stepwise study including samples of healthy twins, unrelated healthy participants and patients with schizophrenia. Participants approached or avoided pictures of faces with negative emotional valence during functional magnetic resonance imaging (fMRI). We investigated 3 samples of healthy participants - including 28 healthy twin pairs, 289 unrelated healthy participants (genome-wide association study [GWAS] discovery sample) and 90 unrelated healthy participants (replication sample) - and 1 sample of 48 patients with schizophrenia. Among healthy twins, we identified the amygdala as the brain region with the highest heritability during processing of angry faces (heritability estimate 0.54, p < 0.001). Subsequent GWAS in both discovery and replication samples of healthy non-twins indicated that amygdala activity was associated with a polymorphism in the miR-137 locus (rs1198575), a micro-RNA strongly involved in risk for schizophrenia. A significant effect in the same direction was found among patients with schizophrenia (p = 0.03). The limited sample size available for GWAS analyses may require further replication of results. Our data-driven approach shows preliminary evidence that amygdala activity, as evaluated with our task, is heritable. Our genetic associations preliminarily suggest a role for miR-137 in brain activity during explicit processing of facial emotions among healthy participants and patients with schizophrenia, pointing to the amygdala as a brain region whose activity is related to miR-137.

KidneyGPS: a user-friendly web application to help prioritize kidney function genes and variants based on evidence from genome-wide association studies

BackgroundGenome-wide association studies (GWAS) have identified hundreds of genetic loci associated with kidney function. By combining these findings with post-GWAS information (e.g., statistical fine-mapping to identify independent association signals and to narrow down signals to causal variants; or different sources of annotation data), new hypotheses regarding physiology and disease aetiology can be obtained. These hypotheses need to be tested in laboratory experiments, for example, to identify new therapeutic targets. For this purpose, the evidence obtained from GWAS and post-GWAS analyses must be processed and presented in a way that they are easily accessible to kidney researchers without specific GWAS expertise.MainHere we present KidneyGPS, a user-friendly web-application that combines genetic variant association for estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics consortium with annotation of (i) genetic variants with functional or regulatory effects (“SNP-to-gene” mapping), (ii) genes with kidney phenotypes in mice or human (“gene-to-phenotype”), and (iii) drugability of genes (to support re-purposing). KidneyGPS adopts a comprehensive approach summarizing evidence for all 5906 genes in the 424 GWAS loci for eGFR identified previously and the 35,885 variants in the 99% credible sets of 594 independent signals. KidneyGPS enables user-friendly access to the abundance of information by search functions for genes, variants, and regions. KidneyGPS also provides a function (“GPS tab”) to generate lists of genes with specific characteristics thus enabling customizable Gene Prioritisation (GPS). These specific characteristics can be as broad as any gene in the 424 loci with a known kidney phenotype in mice or human; or they can be highly focussed on genes mapping to genetic variants or signals with particularly with high statistical support. KidneyGPS is implemented with RShiny in a modularized fashion to facilitate update of input data (https://kidneygps.ur.de/gps/).ConclusionWith the focus on kidney function related evidence, KidneyGPS fills a gap between large general platforms for accessing GWAS and post-GWAS results and the specific needs of the kidney research community. This makes KidneyGPS an important platform for kidney researchers to help translate in silico research results into in vitro or in vivo research.