Genome Association Research Articles

P109 Heterogeneity of 68Ga-PSMA PET/CT in metastatic castration-resistant prostate cancer: Genomic characteristics and association with new hormonal agent response, an international multi-center cohort study

P109 Heterogeneity of 68Ga-PSMA PET/CT in metastatic castration-resistant prostate cancer: Genomic characteristics and association with new hormonal agent response, an international multi-center cohort study

NF1 expression profiling in IDH-wildtype glioblastoma: genomic associations and survival outcomes

BackgroundNF1 inactivation is associated with sensitivity to MEK inhibitor targeted therapy in low-grade and some high-grade gliomas. NF1 loss may also be a harbinger of exploitable vulnerabilities in IDH-wildtype glioblastoma (GBM). Accurate and consistent detection of NF1 loss, however, is fraught given the large gene size, challenges with complete coverage and variant calling upon sequencing, and mechanisms of mRNA and protein regulation that result in early degradation in the absence of genomic alterations. Here, we seek to perform a composite analysis for NF1 loss accounting for genomic alterations and protein expression via immunohistochemistry. We also characterize the landscape of NF1 alterations in GBM.MethodsWe assembled a single-institution, retrospective cohort of 542 IDH-wildtype GBM with somatic next generation sequencing to investigate the frequency and nature of detected NF1 alterations. We selected 69 GBMs from which to build a tissue microarray (TMA) of 44 NF1-wildtype and 25 NF1-mutant cases. We performed NF1 immunohistochemistry using two different NF1 antibodies (NFC, Sigma-Aldrich; and iNF-07E, iNFixion Bioscience) and correlated results with clinical, genomic, and other immunohistochemical features.ResultsIn our retrospective cohort, we identified 88 IDH-wildtype GBM with NF1 alterations (16%). NF1 alterations were mutually exclusive with EGFR and MDM2 alterations (p-adj < 0.001, 0.05, respectively), but co-occurred with PIK3R1 alterations (Log2(OR) = − 1.6, p-adj = 0.03). Of the 63 scorable sporadic GBMs in the TMA, 14 harbored NF1 inactivating alterations and of those, 12 (86%) demonstrated minimal NF1 immunoreactivity by NFC antibody, compared to 8 (57%) by iNF-07E antibody. Among the 42 scorable NF1-wildtype GBM in the TMA, NF1 immunostaining was minimal in 18 (43%) by NFC antibody compared to 4 (10%) by iNF-07E antibody, potentially reflecting false positives or differential protein regulation. Minimal immunoreactivity by NFC antibody was associated with decreased median overall survival (8.5 vs. 16.4 months, p = 0.011). Cox proportional hazards model correcting for prognostic variables in this subset revealed HR 3.23 (95% CI 1.29–8.06, p = 0.01) associated with decreased NF1 expression by IHC.ConclusionNF1 immunostaining may serve as a sensitive surrogate marker of NF1 genomic inactivation and a valuable extension to next-generation sequencing for defining NF1 status. Minimal NF1 immunoreactivity is a poor prognostic marker, even in IDH-wildtype glioblastoma without apparent NF1 genomic alterations, but the underlying molecular mechanism requires further investigation.

Exploring the potential link between gut microbiota and chronic kidney disease in causality: A 2-sample Mendelian randomization study.

Increasing evidence indicates a significant correlation between gut microbiota (GM) and susceptibility to chronic kidney disease (CKD). However, causal relationship presence remains uncertain. Mendelian randomization (MR) was applied to evaluate potential causal relation from GM to CKD. Genomic association analysis aggregates publicly online databases, utilizing Genome-Wide Association Study (GWAS) database focused on GM and CKD. For examination of potential causal connection from GM to CKD, a 2-way, 2-sample Mendelian randomization (MR) method was applied. Sensitivity analyses were utilized to scrutinize for heterogeneity, horizontal pleiotropy, MR outcomes resilience. Result from inverse variance weighting (IVW) method revealed that 10 microbiotas such as Porphyromonadaceae (OR = 1.351, 95% CI: 1.114-1.638, P = .002), Dorea (OR = 1.236, 95% CI: 1.040-1.468, P = .016), Ruminococcus torques group (OR = 1.290, 95% CI: 1.035-1.608, P = .024) are potential CKD risk factors. Five microbiotas, including the Prevotellaceae (OR = 0.814, 95% CI: 0.719-0.922, P = .001) are potential CKD protective factors. Sensitivity analyses reveal no horizontal pleiotropy or heterogeneity. Additionally, reverse MR results unveiled potential relation between CKD and disorders in 3 microbiotas, including Senegalimassilia. According to the investigation, MR method was employed to delve into reciprocal causal connection from GM to CKD. Our findings identified 15 types of GM causally linked to CKD, as well as CKD demonstrating causal associations with 3 types of GM. Further exploration of these associated GM types is hopeful to raise novel insights, for CKD preventing and early monitoring.

Higher oxygen content and transport characterize high-altitude ethnic Tibetan women with the highest lifetime reproductive success

We chose the "natural laboratory" provided by high-altitude native ethnic Tibetan women who had completed childbearing to examine the hypothesis that multiple oxygen delivery traits were associated with lifetime reproductive success and had genomic associations. Four hundred seventeen (417) women aged 46 to 86 y residing at ≥3,500 m in Upper Mustang, Nepal, provided information on reproductive histories, sociocultural factors, physiological measurements, and DNA samples for this observational cohort study. Simultaneously assessing multiple traits identified combinations associated with lifetime reproductive success measured as the number of livebirths. Women with the most livebirths had distinctive hematological and cardiovascular traits. A hemoglobin concentration near the sample mode and a high percent of oxygen saturation of hemoglobin raised arterial oxygen concentration without risking elevated blood viscosity. We propose ongoing stabilizing selection on hemoglobin concentration because extreme values predicted fewer livebirths and directional selection favoring higher oxygen saturation because higher values had more predicted livebirths. EPAS1, an oxygen homeostasis locus with strong signals of positive natural selection and a high frequency of variants occurring only among populations indigenous to the Tibetan Plateau, associated with hemoglobin concentration. High blood flow into the lungs, wide left ventricles, and low hypoxic heart rate responses aided effective convective oxygen transport to tissues. Women with physiologies closer to unstressed, low altitude values had the highest lifetime reproductive success. This example of ethnic Tibetan women residing at high altitudes in Nepal links reproductive fitness with trait combinations increasing oxygen delivery under severe hypoxic stress and demonstrates ongoing natural selection.

Genomic association of SNPs rs4077582 of CYP11A1 and rs700519 of CYP19A1 genes with polycystic ovarian syndrome.

Polycystic Ovarian Syndrome (PCOS) is a complex endocrine disorder that affects women of reproductive age. Several candidate genes have been shown to be associated with PCOS. Previous studies have shown that variations in CYP11A1 and CYP19A1 genes are associated with hormonal dysregulation associated with PCOS in different ethnic populations. This study aims to investigate the genomic association between SNPs rs4077582 of CYP11A1 and rs700519 of CYP19A1 and the development of PCOS in Pakistani population. A total of 280 subjects were recruited for the study, including 142 PCOS cases diagnosed based on Rotterdam criteria and 138 age-matched controls. The anthropometric, hormonal and biochemical parameters of all subjects were analyzed. Genomic DNA was extracted and genotyping of the selected SNPs was performed using Sanger sequencing. Further, we also examined the genotypic-phenotypic correlation analysis for various clinical and biochemical parameters for SNP rs4077582 of CYP11A1. We found significant differences in allele frequency (OR = 0.42, 95% CI = 0.30-0.60, χ2 = 16.3693, p = 0.000052) and genotypic frequency (χ2 = 26.4376, p = 0.00001) between PCOS women and controls for SNP rs4077582 of CYP11A1. Genotype-phenotype correlation analysis showed a significant difference in FAI (p = 0.005), testosterone (p = 0.001), androstenedione (p = 0.005) and urea (p = 0.049) levels between the three genotypes. No association between SNP rs700519 of CYP19A1 and PCOS was observed. Our results suggest the role of SNP rs4077582 of CYP11A1 gene in the clinical manifestation of PCOS in Pakistani women.

Genome-wide studies define new genetic mechanisms of IgA vasculitis.

IgA vasculitis (IgAV) is a pediatric disease with skin and systemic manifestations. Here, we conducted genome, transcriptome, and proteome-wide association studies in 2,170 IgAV cases and 5,928 controls, generated IgAV-specific maps of gene expression and splicing from blood of 255 pediatric cases, and reconstructed myeloid-specific regulatory networks to define disease master regulators modulated by the newly identified disease driver genes. We observed significant association at the HLA - DRB1 (OR=1.55, P=1.1×10 -25 ) and fine-mapped specific amino-acid risk substitutions in DRβ1. We discovered two novel non-HLA loci: FCAR (OR=1.51, P=1.0×10 -20 ) encoding a myeloid IgA receptor FcαR, and INPP5D (OR=1.34, P=2.2×10 -09 ) encoding a known inhibitor of FcαR signaling. The FCAR risk locus co-localized with a cis-eQTL increasing FCAR expression; the risk alleles disrupted a PRDM1 binding motif within a myeloid enhancer of FCAR . Another risk locus was associated with a higher genetically predicted levels of plasma IL6R. The IL6R risk haplotype carried a missense variant contributing to accelerated cleavage of IL6R into a soluble form. Using systems biology approaches, we prioritized IgAV master regulators co-modulated by FCAR , INPP5D and IL6R in myeloid cells. We additionally identified 21 shared loci in a cross-phenotype analysis of IgAV with IgA nephropathy, including novel loci PAID4, WLS , and ANKRD55 .

Research on the genetic etiology of polycystic ovary syndrome in the post-GWAS era

Great progress has been made in the genetic research of PCOS, thanks to the application of genome association study (GWAS) technology. However, in the post-GWAS era, investigating the pathogenic mechanisms related to numerous genetic loci has become challenging, leading to the current generalized approach to treating PCOS. To address this issue, taking the significantly associated susceptibility gene THADA as an example, we share a series of advancements from the perspectives of genetic evolution, epigenetics, and gene function studies. Our aim is to provide guidance for a better understanding of the essence of PCOS.

Bacterial N-Acyl Homoserine Lactone Priming Enhances Leaf-Rust Resistance in Winter Wheat and Some Genomic Regions Are Associated with Priming Efficiency.

Leaf rust (Puccinia triticina) is a common disease that causes significant yield losses in wheat. The most frequently used methods to control leaf rust are the application of fungicides and the cultivation of resistant genotypes. However, high genetic diversity and associated adaptability of pathogen populations hamper achieving durable resistance in wheat. Emerging alternatives, such as microbial priming, may represent an effective measure to stimulate plant defense mechanisms and could serve as a means of controlling a broad range of pathogens. In this study, 175 wheat genotypes were inoculated with two bacterial strains: Ensifer meliloti strain expR+ch (producing N-acyl homoserine lactone (AHL)) or transformed E. meliloti carrying the lactonase gene attM (control). In total, 21 genotypes indicated higher resistance upon bacterial AHL priming. Subsequently, the phenotypic data of 175 genotypes combined with 9917 single-nucleotide polymorphisms (SNPs) in a genome-wide association study to identify quantitative trait loci (QTLs) and associated markers for relative infection under attM and expR+ch conditions and priming efficiency using the Genome Association and Prediction Integrated Tool (GAPIT). In total, 15 QTLs for relative infection under both conditions and priming efficiency were identified on chromosomes 1A, 1B, 2A, 3A, 3B, 3D, 6A, and 6B, which may represent targets for wheat breeding for priming and leaf-rust resistance.

A GWAS of ACE Inhibitor-Induced Angioedema in a South African Population.

Angiotensin-converting enzyme inhibitor-induced angioedema (AE-ACEI) is a life-threatening adverse event and, globally, the commonest cause of emergency presentations with angioedema. Several large genome-wide association studies (GWAS) have found genomic associations with AE-ACEI. However, despite African Americans having a 5-fold increased risk of AE-ACEI, there are no published GWAS from Africa. The aim of this study was to conduct a case-control GWAS of AE-ACEI in a South African population and perform a meta-analysis with an African American and European American population. The GWAS included 202 South African adults with a history of AE-ACEI and 513 controls without angioedema following angiotensin-converting enzyme inhibitor (ACEI) treatment for at least 2 years. A meta-analysis was conducted with GWAS summary statistics from an African American and European American cohort (from Vanderbilt/Marshfield with 174 cases and 489 controls). No SNPs attained genome-wide significance. However, 26 SNPs in the post-imputation standard GWAS of the South African cohort and 37 SNPs in the meta-analysis were associated to AE-ACEI with suggestive threshold(p-value<5.0×10-06). Some of these SNPs were found to be located close to the genes PRKCQ and RIMS1, previously linked with drug-induced angioedema, and also close to the CSMD1 gene linked to ACEI cough, providing replication at the gene level, but with novel lead SNPs. Our results highlight the importance of African populations to detect novel variants in replication studies. Further increased sampling across the continent and matched functional work are needed to confirm the importance of genetic variation in understanding the biology of AE-ACEI.

SARS-CoV-2 Omicron subvariant genomic variation associations with immune evasion in Northern California: A retrospective cohort study.

The possibility of association between SARS-CoV-2 genomic variation and immune evasion is not known among persons with Omicron variant SARS-CoV-2 infection. In a retrospective cohort, using Poisson regression adjusting for sociodemographic variables and month of infection, we examined associations between individual non-lineage defining mutations and SARS-CoV-2 immunity status, defined as a) no prior recorded infection, b) not vaccinated but with at least one prior recorded infection, c) complete primary series vaccination, and/or d) primary series vaccination and ≥ 1 booster. We identified all non-synonymous single nucleotide polymorphisms (SNPs), insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. We also examined correlations between the presence of SNPs with each other, with subvariants, and over time. Seventy-nine mutations met inclusion criteria. Among 15,566 persons infected with Omicron SARS-CoV-2, 1,825 (12%) were unvaccinated with no prior recorded infection, 360 (2%) were unvaccinated with a recorded prior infection, 13,381 (86%) had a complete primary series vaccination, and 9,172 (58%) had at least one booster. After examining correlation between SNPs, 79 individual non-lineage defining mutations were organized into 38 groups. After correction for multiple testing, no individual SNPs or SNP groups were significantly associated with immunity status levels. Genomic variation identified within SARS-CoV-2 Omicron specimens was not significantly associated with immunity status, suggesting that contribution of non-lineage defining SNPs to immune evasion is minimal. Larger-scale surveillance of SARS-CoV-2 genomes linked with clinical data can help provide information to inform future vaccine development.

Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modeling

Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modeling of postsynaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from postmortem RNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in the anterior cingulate cortex, lead to impaired protein kinase A (PKA)-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped electroencephalogram (EEG) dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.

Unfolding the leaf economics spectrum for wheat: Trait analysis and genomic associations across cultivars

The leaf economics spectrum (LES) is an ecophysiological concept that describes the trade-offs between leaf structural and physiological traits. It has been extensively studied across various scales. However, the coordination hypothesis has rarely been tested at the intraspecific scale, especially in crops, for understanding yield increases or predicting evolutionary trajectories. Here, we first tested the relationships among leaf traits and examined the genetic coordination among 209 wheat genotypes. Compared to non-crop grass species, wheat is a fast-growing species, and tends to have a higher value of photosynthetic rate, leaf nitrogen concentration and leaf respiration rate at a given leaf mass per area, although it does align with the predicted direction of the “fast-slow” spectrum. We conducted a principal component analysis (PCA) to compare different traits within wheat. The first axis from PCA (ranging from slow to fast of plant economic investment) is significantly positively associated with the agronomic traits, especially grain yield (R2=0.11, P<0.001). Partially independent changes in leaf nitrogen content and leaf mass per area may allow crops to maximize photosynthetic rates without sacrificing leaf lifespan. The results reveal that some loci are simultaneously associated with different traits, which may be the genetic basis for the formation of trait-trait relationships. The current study deepens the understanding of LES traits in wheat at the intraspecific and genetic levels, supporting the trait-based adaptation strategies to improve wheat productivity and resource-use efficiency.

Genome-wide association studies from spoken phenotypic descriptions: a proof of concept from maize field studies.

We present a novel approach to genome-wide association studies (GWAS) by leveraging unstructured, spoken phenotypic descriptions to identify genomic regions associated with maize traits. Utilizing the Wisconsin Diversity panel, we collected spoken descriptions of Zea mays ssp. mays traits, converting these qualitative observations into quantitative data amenable to GWAS analysis. First, we determined that visually striking phenotypes could be detected from unstructured spoken phenotypic descriptions. Next, we developed two methods to process the same descriptions to derive the trait plant height, a well-characterized phenotypic feature in maize: (1) a semantic similarity metric that assigns a score based on the resemblance of each observation to the concept of 'tallness' and (2) a manual scoring system that categorizes and assigns values to phrases related to plant height. Our analysis successfully corroborated known genomic associations and uncovered novel candidate genes potentially linked to plant height. Some of these genes are associated with gene ontology terms that suggest a plausible involvement in determining plant stature. This proof-of-concept demonstrates the viability of spoken phenotypic descriptions in GWAS and introduces a scalable framework for incorporating unstructured language data into genetic association studies. This methodology has the potential not only to enrich the phenotypic data used in GWAS and to enhance the discovery of genetic elements linked to complex traits but also to expand the repertoire of phenotype data collection methods available for use in the field environment.

Transcriptomic analysis reveals cross-talk genes between type 2 diabetes and recurrent benign paroxysmal positional vertigo

BackgroundBenign paroxysmal positional vertigo (BPPV) is a common neurological disorder with a high recurrence rate. Type 2 diabetes mellitus (T2DM) is recognized as a risk factor for BPPV recurrence. However, the genomic association between T2DM and BPPV recurrence remains understudied. MethodsDifferential gene expression analysis and weighted gene co-expression network analysis were used to identify shared genes between BPPV recurrence and T2DM. The MCC algorithm was employed to select hub genes from the protein-protein interaction network of the shared genes. The predictive efficacy of hub genes for BPPV recurrence and T2DM was assessed using ROC curve analysis. Genemania database was used to identify downstream targets of hub genes. The immune infiltration landscape of BPPV and T2DM was characterized using the CIBERSORT algorithm. Correlation analysis was performed to explore the relationship between hub genes and immune cells. The expression levels of hub genes in patient blood samples were validated using qPCR. ResultsThirteen shared genes were identified and a protein-protein interaction network was constructed for BPPV recurrence and T2DM. Subsequently, four hub genes were selected, and their expression levels effectively predicted the occurrence of BPPV recurrence and T2DM. These hub genes were highly correlated with immune cell infiltration, indicating a common mechanism underlying recurrent BPPV and T2DM. Finally, the upregulation of hub genes in patients with T2DM comorbid with BPPV recurrence was confirmed in blood samples. These hub genes may serve as predictive biomarkers for assessing the recurrence rate in BPPV patients with comorbid T2DM. ConclusionWe proposed shared gene characteristics between BPPV recurrence and T2DM, revealing an immune-mediated inflammatory regulation as a common pathway and identifying four immune-related biomarkers and potential therapeutic targets for T2DM comorbid with recurrent BPPV.

Variation to Biology: Optimizing Functional Analysis of Cancer Risk Variants.

Research conducted over the past 15+ years has identified hundreds of common germline genetic variants associated with cancer risk but understanding the biological impact of these primarily non-protein coding variants has been challenging [1]. The National Cancer Institute sought to better understand and address those challenges by requesting input from the scientific community via a survey and a 2-day virtual meeting, which focused on discussions among participants. Here, we discuss challenges identified through the survey as important to advancing functional analysis of common cancer risk variants: 1) When is a variant truly characterized; 2) Developing and standardizing databases and computational tools; 3) Optimization and implementation of high throughput assays; 4) Use of model organisms for understanding variant function; 5) Diversity in data and assays; and 6) Creating and improving large multidisciplinary collaborations. We define these six challenges, describe how success in addressing them may look, propose potential solutions, and note issues that span all the challenges. Implementation of these ideas could help develop a framework for methodically analyzing common cancer risk variants to understand their function and make effective and efficient use of the wealth of existing genomic association data.

Integrated single-cell and bulk RNA sequencing revealed an epigenetic signature predicts prognosis and tumor microenvironment colorectal cancer heterogeneity.

Colorectal cancer (CRC) prognosis prediction is currently a major challenge. Epigenetic regulation has been widely reported for its role in cancer development. To construct a robust prognostic signature, we used developed and validated across datasets. After constructing the signature, the prognostic value of the signature was evaluated in the TCGA cohort and six independent datasets (GSE17526, GSE17537, GSE33113, GSE37892, GSE39048 and GSE39582). The clinical, genomic and transcriptomic features related to the signature were identified. The correlations of the signature score with immune cell infiltration and cell-cell interactions were analyzed. The correlations between the signature score and the sensitivity to different drugs were also predicted. In the TCGA cohort, patients in the low-risk group according to the signature score had longer survival than those in the high-risk group, and this finding was validated in the validation datasets. The signature was a prognostic factor independent of age and sex and was correlated with stage and PD-1/PD-L1 expression. Area under the receiving operating characteristic curve was 0.72. Genomic association analyses revealed that samples from high-risk patients exhibited chromosomal instability. Transcriptomic analyses revealed that the signature score was significantly associated with multiple cellular pathways. Bulk RNA-seq and single-cell sequencing data revealed that the signature reflected differences in infiltrating immune cell-tumor cell interactions, especially for macrophages. The signature also predicted the putative drug sensitivity of CRC samples. The signature is a valuable biomarker for predicting CRC prognosis and reflects multiple features of CRC, especially macrophage infiltration in the microenvironment.

Genomic, immunologic, and prognostic associations of TROP2 (TACSTD2) expression in solid tumors.

TROP2 (TACSTD2) expression is associated with decreased overall survival (OS) in some solid tumors, and the TROP2-targeting antibody-drug conjugate (ADC) sacituzumab govitecan has been approved in breast and urothelial carcinomas. We aimed to explore the multi-omic landscape associated with TACSTD2 gene expression in various solid tumors to identify patients most likely to benefit from this approach. Breast (N = 11246), colorectal (N = 15425), hepatocellular (N = 433), pancreatic (N = 5488), and urothelial (N = 4125) tumors were stratified into quartiles by TACSTD2 gene expression, analyzed by next-generation DNA sequencing, whole transcriptome sequencing, and immunohistochemistry at Caris Life Sciences (Phoenix, AZ). Survival data were obtained from insurance claims, and Kaplan-Meier estimates were calculated for molecularly defined cohorts. Several pathogenic mutations were associated with TACSTD2-high tumors, including TP53 in breast, colorectal (CRC), pancreatic, and hepatocellular cancers; KRAS in pancreatic and CRC cancers; ARID1A and FGFR3 in urothelial cancer; and CTNNB1 in hepatocellular cancer. TACSTD2-low breast tumors were enriched for copy number amplifications in CCND1 and FGF/R family member genes. TACSTD2 high was generally associated with more immune cell infiltration and greater T-cell inflammation scores. Patients with TACSTD2-high breast, CRC, and pancreatic cancers demonstrated a significantly shorter OS than TACSTD2-low tumors. This was restricted to CRC with microsatellite stable tumors and patients with pancreatic cancer with KRAS-mutant tumors. Patients with breast cancer with TACSTD2-high tumors also experienced significantly worse OS following immune checkpoint inhibitors. TACSTD2 expression is associated with key driver alterations and a more active immune microenvironment, suggesting possible combinatorial strategies with TROP2-targeting ADCs plus immunotherapy in various solid tumors.

Genomic variants association with selective hypersensitivity reactions to amoxicillin and clavulanic acid.

Genomic variants association with selective hypersensitivity reactions to amoxicillin and clavulanic acid.

O-071 Stringent statistical analysis of 108,684 oocyte donation cycles identifies 2.6% of donors with specific oocyte/embryo developmental arrest phenotypes for genome association studies

Abstract Study question Can statistical modelling accurately identify an outlier group of presumed fertile donors with specific reduced embryological outcomes suggestive of an underlying infertility-related genomic condition? Summary answer Statistical modelling identified a highly specific group of donors as embryologically under-performing outliers across multiple treatment cycles for the optimisation of downstream genomic association studies. What is known already Female infertility has a wide range of clinical presentations. While some causes of infertility are well defined, the aetiology of most infertility remains unexplained. Since IVF allows for in vitro monitoring of oocyte and embryo, it is now possible to identify subtle infertility endophenotypes, characterized by specific developmental failure that would otherwise go undetected in natural conception. Currently, the lack of large and well-categorized datasets of infertility endophenotypes has limited research in the area. Therefore, a clear and methodological definition of infertility endophenotypes in IVF is the first crucial step towards a better understanding of their mechanism and biological/genetic aetiology. Study design, size, duration A retrospective analysis was performed on clinical and embryological data from 40497 egg donors, undergoing 108.684 stimulations, with 4.235.036 oocytes retrieved. The data also included information on the 85482 recipients and their 190996 oocyte reception cycles, spanning from 1999 to 2023. Infertility endophenotypes were able to be well categorized as oocyte donors are presumed fertile based on their young age and on normal ranges displayed for the parameters assessed during typical oocyte donation work-up. Participants/materials, setting, methods Donor performance was calculated according to: (I) oocyte maturation rate (MR); (ii) survival rate of cryopreserved oocytes (SR); (iii) oocyte fertilization rate (FR;2PN/Injected MII); and (iii) blastulation rate (BR;blastocyst/2PN). Donors with significantly impaired rates, considering ≥2 stimulations and/or recipients, were identified as outliers using probabilistic modelling (Binomial test, Bonferroni corrected P &amp;lt; 0.05). Outliers were computed for each rate on data subsets after applying this stringent filtering criteria and excluding inconsistent or missing data. Main results and the role of chance 2.6% of donors were identified as underperforming outliers when summing the rate observed for each embryological outcome using the stringent statistical modelling. The average MR was 79.8% (95%CI: 79.6-80). Taking into account the correlation of follicle size during ultrasound tracking and the number of mature oocytes collected, a total of 168/29768 (0.56%) donors with statistically lower MR (mean MR = 43% 95%CI:40.1-45.7) across ≥2 egg collection cycles were identified as outliers. The average SR was 88% (95%CI:87.9-88.2). A total of 176/18544 (0.95%) donors with ≥2 stimulations and ≥2 recipient cycles were deemed outliers, showing a statistically reduced SR (mean SR = 51% 95%CI:48.9-53.1). The average FR was 74% (95%CI: 73.8-74.2). 164/31657 (0.52%) donors were found to have statistically low FR (mean FR = 37% 95%CI:34.6-38.7) and deemed outliers when assessed over ≥2 stimulation cycles with ≥2 recipient cycles. The average BR was 53.4% (95%CI: 53.1-53.7). After considering only donors with ≥2 recipients and ≥2 stimulations, a total of 142/24716 (0.57%) donors with statistically low BR (mean BR = 14% 95%CI:12.4-15.3) were considered outliers. Limitations, reasons for caution The stringent criteria applied to our statistical modelling has likely resulted in underestimating the true level of outlier donors. This is also likely compounded by the selection bias associated with donor recruitment and the retention policies after the first stimulation cycle preventing the evaluation of recurrent patterns in some cases. Wider implications of the findings The analytical tools developed on this unprecedentedly large dataset are fundamental to define a methodological workflow for accurately identifying unexpectedly infertile individuals. This is crucial for investigating the genetic and biological mechanisms underlying infertility endophenotypes, leading to improvements in treatment and developing screening tool to predict infertility and related pathologies. Trial registration number not applicable

Leveraging genomics and temporal high-throughput phenotyping to enhance association mapping and yield prediction in sesame.

Sesame (Sesamum indicum) is an important oilseed crop with rising demand owing to its nutritional and health benefits. There is an urgent need to develop and integrate new genomic-based breeding strategies to meet these future demands. While genomic resources have advanced genetic research in sesame, the implementation of high-throughput phenotyping and genetic analysis of longitudinal traits remains limited. Here, we combined high-throughput phenotyping and random regression models to investigate the dynamics of plant height, leaf area index, and five spectral vegetation indices throughout the sesame growing seasons in a diversity panel. Modeling the temporal phenotypic and additive genetic trajectories revealed distinct patterns corresponding to the sesame growth cycle. We also conducted longitudinal genomic prediction and association mapping of plant height using various models and cross-validation schemes. Moderate prediction accuracy was obtained when predicting new genotypes at each time point, and moderate to high values were obtained when forecasting future phenotypes. Association mapping revealed three genomic regions in linkage groups 6, 8, and 11, conferring trait variation over time and growth rate. Furthermore, we leveraged correlations between the temporal trait and seed-yield and applied multi-trait genomic prediction. We obtained an improvement over single-trait analysis, especially when phenotypes from earlier time points were used, highlighting the potential of using a high-throughput phenotyping platform as a selection tool. Our results shed light on the genetic control of longitudinal traits in sesame and underscore the potential of high-throughput phenotyping to detect a wide range of traits and genotypes that can inform sesame breeding efforts to enhance yield.