Risk Single Nucleotide Polymorphisms Research Articles

Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.

Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The quest for the identification of MCI individuals has highlighted the importance of comprehending the underlying mechanisms of disease causation. Integrated analysis of brain imaging and genomics offers a promising avenue for predicting MCI risk before clinical symptom onset. However, most existing methods face challenges in: 1) mining the brain network-specific topological structure and addressing the single nucleotide polymorphisms (SNPs)-related noise contamination and 2) extracting the discriminative properties of brain imaging genomics, resulting in limited accuracy for MCI diagnosis. To this end, a modality-aware discriminative fusion network (MA-DFN) is proposed to integrate the complementary information from brain imaging genomics to diagnose MCI. Specifically, we first design two modality-specific feature extraction modules: the graph convolutional network with edge-augmented self-attention module (GCN-EASA) and the deep adversarial denoising autoencoder module (DAD-AE), to capture the topological structure of brain networks and the intrinsic distribution of SNPs. Subsequently, a discriminative-enhanced fusion network with correlation regularization module (DFN-CorrReg) is employed to enhance inter-modal consistency and between-class discrimination in brain imaging and genomics. Compared to other state-of-the-art approaches, MA-DFN not only exhibits superior performance in stratifying cognitive normal (CN) and MCI individuals but also identifies disease-related brain regions and risk SNPs locus, which hold potential as putative biomarkers for MCI diagnosis.

The association between the single-nucleotide polymorphism of site rs1333040 in region 9p21 and the risk of coronary heart disease in Chinese population

Background Rs1333040 is the single-nucleotide polymorphisms (SNP) related with coronary heart disease (CHD). The aim of the present study is to examine the association between rs1333040 polymorphism genotypes and CHD and to further explore the molecular mechanism in Chinese population. Methods A case-control study was used in this study, including 500 CHD patients and 500 control subjects. CHD patients and controls were distinguished by coronary angiography. Genotypes of rs1333040 were determined on the Agena MassARRAY system. Statistical analysis was conducted by SPSS (Ver 16.0) and plink (Ver. 1.07, Shaun Purcell). Results Fisher’s exact test by plink indicated a significant difference in the allele distribution between cases and controls, the allele T may be associated with a higher risk of CHD (p = 0.012, odds ratio (OR) = 1.258). The serum levels of low-density lipoprotein cholesterol (LDL-C) (p = 0.029) and Gensini score (p = 0.008) distributed differently in patients with various alleles. In the recessive model, the levels of high-density lipoprotein (HDL) and apolipoprotein A (ApoA) were higher in the TC + CC genotype than in the TT genotype. The TC + TT genotype was found to be risk factors against CHD in a dominant model (OR = 1.278, p = 0.014). The TC + TT genotype along with multiple risk factors significantly positively correlated with the risk of CHD. Conclusions The present study investigates the association between the rs1333040 polymorphism genotypes and CHD. The T allele of rs1333040 is the susceptibility site of CHD. The interaction between SNP and various risk factors plays an important role in the development of CHD.

Association of the rs1042522 SNP with prostate cancer risk: a study of cancer tissues, primary tumor cultures, and serum samples from a Spanish Caucasian population.

Prostate cancer (PCa) is a leading cause of cancer-related deaths in European men, emphasizing the urgent need for effective risk assessment strategies. The TP53 gene, a tumor suppressor gene frequently mutated in cancer, commonly harbors the rs1042522 single nucleotide polymorphism (SNP), known as the P72R SNP, which may influence PCa susceptibility. This study investigated the prevalence of the P72R SNP in European Caucasian PCa samples and its association with PCa risk. Genotyping was conducted on 12 hormone-naïve aggressive PCa cultures (hnPCs) from untreated patients (Gleason ≥8), 11 radical prostatectomies (RP), and 94 serum samples using DNA Sanger sequencing and melting curve analysis. Comparative analysis utilized data from the GnomAD database's European Caucasian non-cancer population. Our results demonstrate a significantly higher frequency of the P72R SNP in PCa samples and serums compared to the general European non-cancer population. A robust and statistically significant association (p < 0.0001) between the SNP and prostate cancer risk was identified, with an odds ratio of 7.937 (95% CI 5.37-11.00). Notably, the G allele (R72) showed a pronounced prevalence in high Gleason score (≥8) patients, although statistical significance was not reached. These results highlight a potential association with undifferentiated and malignant PCa lesions. The compelling association between the P72R SNP and prostate cancer risk underscores the potential utility of this marker for the early identification of patients at risk of aggressive metastatic prostate cancer. This insight could empower further research to intervene at an early stage by offering enhanced opportunities for timely and targeted interventions.

Machine learning uncovers manganese as a key nutrient associated with reduced risk of steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 20%-30% of the general population and is linked to high-caloric western style diet. However, there are little data that specific nutrients might help to prevent steatosis. We analysed the UK Biobank (ID 71300) 24 h-nutritional assessments and investigated the association between nutrient intake calculated from food questionnaires and hepatic steatosis indicated by imaging or ICD10-coding. The effect of manganese (Mn) on subgroups with risk single nucleotide polymorphism carriage as well as the effect on metabolomics was investigated. All analyses are corrected for age, sex, body mass index, Townsend index for socioeconomic status, kcal, alcohol, protein intake, fat intake, carbohydrate intake, energy from beverages, diabetes, physical activity and for multiple testing. We used a random forest classifier to analyse the feature importance of 63 nutrients and imaging-proven steatosis in a cohort of over 25 000 UK Biobank participants. Increased dietary Mn intake was associated with a lower likelihood of MRI-diagnosed steatosis. Subsequently, we conducted a cohort study in over 200 000 UK Biobank participants to explore the relationship between Mn intake and hepatic or cardiometabolic outcomes and found that higher Mn intake was associated with a lower risk of ICD-10 coded steatosis (OR = .889 [.838-.943], p < .001), independent of other potential confounders. Our study provides evidence that higher Mn intake may be associated with lower odds of steatosis in a large population-based sample. These findings underline the potential role of Mn in the prevention of steatosis, but further research is needed to confirm these findings and to elucidate the underlying mechanisms.

Minor Genetic Overlap Among Rheumatoid Arthritis, Myocardial Infarction, and Myocardial Infarction Risk Determinants.

The aim of this study was to investigate whether a shared genetic susceptibility exists between individuals with rheumatoid arthritis (RA) and individuals with myocardial infarction (MI)-including major MI risk factors-and to quantify the degree of any such overlap. Genome-wide association study (GWAS) data for individuals with RA were constructed from a sample of 26,637 Swedish patients with RA and controls without RA. For patients with MI, GWAS data were obtained from a previously published meta-analysis. Genome-wide genetic correlation was estimated via linkage disequilibrium score regression. LAVA was employed to estimate local genetic correlations in ~2,500 nonoverlapping loci, including the major histocompatibility complex. The controls without RA were used for reference panel data. We also assessed stratified estimates of both genome-wide and local genetic correlation based on subsamples of individuals with seropositive RA and those with seronegative RA. Furthermore, genome-wide genetic correlation was estimated between RA and selected cardiovascular risk factors to elucidate pleiotropic relationships. Following quality control, our GWAS of patients with RA consisted of 25,826 individuas. Genome-wide genetic correlation between patients with RA and MI was estimated to 0.13 (95% confidence interval -0.03 to 0.29). Six regions exhibited significant local genetic correlation, though none harbored any known risk single-nucleotide polymorphisms for either of the two traits. Estimates were similar in both individuals with seropositive RA and those with seronegative RA. No statistically significant genetic correlations were observed between RA risk factors and any of the MI risk factors. Our findings indicate that genetic overlap between patients with RA and MI is minor. Furthermore, genetic overlap between RA and MI risk factors seem unlikely to provide a major contribution to the increased risk of MI observed in patients with RA.

Interaction between Risk Single-Nucleotide Polymorphisms of Developmental Dyslexia and Parental Education on Reading Ability: Evidence for Differential Susceptibility Theory.

While genetic and environmental factors have been shown as predictors of children's reading ability, the interaction effects of identified genetic risk susceptibility and the specified environment for reading ability have rarely been investigated. The current study assessed potential gene-environment (G×E) interactions on reading ability in 1477 school-aged children. The gene-environment interactions on character recognition were investigated by an exploratory analysis between the risk single-nucleotide polymorphisms (SNPs), which were discovered by previous genome-wide association studies of developmental dyslexia (DD), and parental education (PE). The re-parameterized regression analysis suggested that this G×E interaction conformed to the strong differential susceptibility model. The results showed that rs281238 exhibits a significant interaction with PE on character recognition. Children with the "T" genotype profited from high PE, whereas they performed worse in low PE environments, but "CC" genotype children were not malleable in different PE environments. This study provided initial evidence for how the significant SNPs in developmental dyslexia GWA studies affect children's reading performance by interacting with the environmental factor of parental education.

Transcriptional network analysis of peripheral blood leukocyte subsets in multiple sclerosis identifies a pathogenic role for a cytotoxicity-associated gene network in myeloid cells.

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system affecting predominantly adults. It is a complex disease associated with both environmental and genetic risk factors. Although over 230 risk single-nucleotide polymorphisms have been associated with MS, all are common human variants. The mechanisms by which they increase the risk of MS, however, remain elusive. We hypothesized that a complex genetic phenotype such as MS could be driven by coordinated expression of genes controlled by transcriptional regulatory networks. We, therefore, constructed a gene coexpression network from microarray expression analyses of five purified peripheral blood leukocyte subsets of 76 patients with relapsing remitting MS and 104 healthy controls. These analyses identified a major network (or module) of expressed genes associated with MS that play key roles in cell-mediated cytotoxicity which was downregulated in monocytes of patients with MS. Manipulation of the module gene expression was achieved in vitro through small interfering RNA gene knockdown of identified drivers. In a mouse model, network gene knockdown modulated the autoimmune inflammatory MS model disease-experimental autoimmune encephalomyelitis. This research implicates a cytotoxicity-associated gene network in myeloid cells in the pathogenesis of MS.

Deletion of the Murine Ortholog of the Human 9p21.3 Locus Leads to Insulin Resistance and Obesity in Hypercholesterolemic Mice.

The 9p21.3 genomic locus is a hot spot for disease-associated single-nucleotide polymorphisms (SNPs), and its strongest associations are with coronary artery disease (CAD). The disease-associated SNPs are located within the sequence of a long noncoding RNA ANRIL, which potentially contributes to atherogenesis by regulating vascular cell stress and proliferation, but also affects pancreatic β-cell proliferation. Altered expression of a neighboring gene, CDKN2B, has been also recognized to correlate with obesity and hepatic steatosis in people carrying the risk SNPs. In the present study, we investigated the impact of 9p21.3 on obesity accompanied by hyperlipidemia in mice carrying a deletion of the murine ortholog for the 9p21.3 (Chr4Δ70/Δ70) risk locus in hyperlipidemic Ldlr-/-ApoB100/100 background. The Chr4Δ70/Δ70 mice showed decreased mRNA expression of insulin receptors in white adipose tissue already at a young age, which developed into insulin resistance and obesity by aging. In addition, the Sirt1-Ppargc1a-Ucp2 pathway was downregulated together with the expression of Cdkn2b, specifically in the white adipose tissue in Chr4Δ70/Δ70 mice. These results suggest that the 9p21.3 locus, ANRIL lncRNA, and their murine orthologues may regulate the key energy metabolism pathways in a white adipose tissue-specific manner in the presence of hypercholesterolemia, thus contributing to the pathogenesis of metabolic syndrome.

Multi-feature next-generation liquid biopsy for diagnosis and prognosis in HPV-associated head and neck cancer.

6064 Background: Human papillomavirus-associated head and neck squamous cell carcinoma (HPV+HNSCC) releases circulating tumor HPV DNA (ctHPVDNA) into the blood which is a highly accurate biomarker of disease status. Existing approaches based on droplet digital PCR (ddPCR) have limitations in sensitivity, genotype coverage, and do not annotate additional prognostic genomic features. In this study, we tested the diagnostic and prognostic performance of a custom HPV whole-genome next-generation sequencing (NGS) liquid biopsy, termed HPV-DeepSeek, at the time of diagnosis with HPV+HNSCC, compared to ctHPVDNA ddPCR, HPV serology, and clinical work-up. Methods: 304 participants (152 untreated HPV+HNSCC patients, 152 population-level controls) were prospectively enrolled in this single-center prospective cohort study. Plasma samples were analyzed using HPV-DeepSeek, a multiplexed serology assay, single-plex ddPCR, and a 5-genotype multiplexed ddPCR assay. We tested the hypothesis that HPV-DeepSeek would have the highest diagnostic accuracy. We secondarily examined the accuracy of HPV-DeepSeek for prognostic feature annotation including high-risk HPV16 single nucleotide polymorphisms (SNPs), integration events, and PIK3CA mutations. Results: Of 152 cases, 114 (75%) were AJCC stage 1 and 138/152 (91%) were oropharynx primary site cancers. The sensitivity (98.7%), specificity (98.7%), and diagnostic accuracy (0.974) of HPV-DeepSeek was superior (P&lt;0.001) to singleplex ddPCR (94.2%, 98.6%, 0.928), multiplex ddPCR (90.6%, 96.3%, 0.869), HPV serology (86.4%, 96.3%, 0.827), and first attempt clinical diagnostic biopsy (78% sensitive). Utilizing HPV-DeepSeek, 8 different genotypes were detected. 4 patients were found to have multi-genotype infections. 137/152 cases were classified as HPV16, with A1 the most common sub-lineage (90/137). 21 of 137 HPV+HNSCC HPV16 cases (15%) displayed high risk SNPs. Head-to-head comparison of HPV SNP genotyping by HPV-DeepSeek, with the gold-standard tissue-based HPV whole genome sequencing assay, demonstrated 89% concordance in tissue and 85% in blood. The internal concordance rate for HPV-DeepSeek between tissue and blood was 91%. 48 of 152 cases (32%) had at least one viral integration event detected and 36 of 152 cases (24%) had a PIK3CA mutation detected by HPV-DeepSeek. Fragmentomic analysis demonstrated a mean ctHPVDNA fragment size of 148bp for ctHPVDNA versus 167bp for human cell free (cf)DNA from HPV+HNSCC patients and 168bp for control patient cfDNA. Baseline ctHPVDNA quantity was strongly correlated with viral integration status, T stage and N stage (P&lt;0.001). Conclusions: HPV-DeepSeek has improved diagnostic accuracy relative to ddPCR, HPV serology and clinical work-up at the time of diagnosis and demonstrates detection of prognostic features including high-risk HPV16 SNPs, viral integration events, and PIK3CA mutations.

Association of single nucleotide polymorphisms (SNPs) in inflammatory pathways with breast cancer (BC) risk: A multi-ethnic scoping review.

1617 Background: Breast cancer is the most prevalent cancer affecting women of every ethnic group in the United States. This is a scoping review assessing SNPs in inflammatory pathways posited to modify BC risk by ethnicity. Methods: We followed PRISMA guidelines for scoping reviews. PubMed, Medline, and OVID databases were interrogated for publications between 1/2000-12/2023 using search terms “breast cancer” AND [BMI OR “body mass index” OR elevated BMI OR obesity] AND [SNP OR “single nucleotide polymorphism” OR polymorphism OR mutation] AND [inflammation OR cytokines OR IL-1 OR IL-2 OR IL-4 OR IL-6 OR IL-8 OR IL-10 OR IL-12 OR TNF-A or TGFB OR CRP] AND [Asian, Black or Hispanic]. A single reviewer assessed 72 unique publications and determined that 42 met inclusion criteria. Two reviewers extracted the following data: demographics, SNP, number of cases and controls by ethnicity. Disagreements were resolved by consensus with a third reviewer. Results: Data were extractable from 42 studies, all case controls. In analyses stratified by ethnicity, we detected effects of SNPs on BC risk (Table). IL-1β rs1143634 and IL-10 (1082 A/G) had a significantly increased BC risk in Asian populations but insignificant in white populations. There were minimal publications for Black and Hispanic populations. Conclusions: The association of inflammatory SNPs and BC risk is complex and can be both protective and predisposing to BC, with ethnicity modifying SNP risk. Future research can be directed at assessment of SNPs and BC risk in diverse populations. [Table: see text]

Impact of PD-L1 Gene Polymorphisms and Interactions with Cooking with Solid Fuel Exposure on Tuberculosis

Introduction: Given that PD-L1 is a crucial immune checkpoint in regulating T-cell responses, the aim of this study was to explore the impact of PD-L1 gene polymorphisms and the interaction with cooking with solid fuel on susceptibility to tuberculosis (TB) in Chinese Han populations. Methods: A total of 503 TB patients and 494 healthy controls were enrolled in this case-control study. Mass spectrometry technology was applied to genotype rs2297136 and rs4143815 of PD-L1 genes. The associations between single nucleotide polymorphism (SNPs) and TB were assessed using unconditional logistic regression analysis. Marginal structural linear odds models were used to estimate the gene-environment interactions. Results: Compared with genotype CC, genotypes GG and CG+GG at rs4143815 locus were significantly associated with susceptibility to TB (OR: 3.074 and 1.506, respectively, p < 0.05). However, no statistical association was found between rs2297136 SNP and TB risk. Moreover, the relative excess risk of interaction between rs4143815 of the PD-L1 gene and cooking with solid fuel was 2.365 (95% CI: 1.922–2.809), suggesting positive interactions with TB susceptibility. Conclusion: The rs4143815 polymorphism of the PD-L1 gene was associated with susceptibility to TB in Chinese Han populations. There were significantly positive interactions between rs4143815 and cooking with solid fuel.

Exploring the relationship between admixture and genetic susceptibility to attention deficit hyperactivity disorder in two Latin American cohorts

Contemporary research on the genomics of Attention Deficit Hyperactivity Disorder (ADHD) often underrepresents admixed populations of diverse genomic ancestries, such as Latin Americans. This study explores the relationship between admixture and genetic associations for ADHD in Colombian and Mexican cohorts. Some 546 participants in two groups, ADHD and Control, were genotyped with Infinium PsychArray®. Global ancestry levels were estimated using overall admixture proportions and principal component analysis, while local ancestry was determined using a method to estimate ancestral components along the genome. Genome-wide association analysis (GWAS) was conducted to identify significant associations. Differences between Colombia and Mexico were evaluated using appropriate statistical tests. 354 Single-nucleotide polymorphisms (SNPs) and Single-nucleotide variants (SNVs) related to some genes and intergenic regions exhibited suggestive significance (p-value < 5*10e−5) in the GWAS. None of the variants revealed genome-wide significance (p-value < 5*10e−8). The study identified a significant relationship between risk SNPs and the European component of admixture, notably observed in the LOC105379109 gene. Despite differences in risk association loci, such as FOXP2, our findings suggest a possible homogeneity in genetic variation’s impact on ADHD between Colombian and Mexican populations. Current reference datasets for ADHD predominantly consist of samples with high European ancestry, underscoring the need for further research to enhance the representation of reference populations and improve the identification of ADHD risk traits in Latin Americans.

Abstract PO3-29-02: Single Nucleotide Polymorphisms (SNPs) in Inflammatory Pathways Associated with Body Mass Index (BMI) and Breast Cancer (BC) Risk: A Scoping Review

Abstract Background: BMI is a risk for BC, with inflammation as a possible link. We conducted a scoping review assessing SNPs in inflammatory pathways posited to modify BC risk by BMI. Design: We followed PRISMA guidelines for scoping reviews. Pubmed, Medline and OVID databases were interrogated for publications between 1/2000-12/2023 using search terms “breast cancer” AND [BMI OR “body mass index” OR elevated BMI OR obesity] AND [SNP OR “single nucleotide polymorphism” OR polymorphism OR mutation] AND [inflammation OR cytokines OR IL-1 OR IL-2 OR IL-4 OR IL-6 OR IL-8 OR IL-10 OR IL-12 OR TNF-A or TGFB OR CRP]. A single reviewer assessed 67 unique publications and determined that 17 met inclusion criteria as a case control or cohort study. Two reviewers extracted the following data: demographics, SNP, number of cases and controls by BMI. Disagreements were resolved by consensus with a third reviewer. High BMI was defined by each study using accepted levels within their population: ≥25 (United States, Mexico) or ≥22 (Korea). Unadjusted odds ratios (OR) for BC risk were calculated by SNP stratified by BMI. Results: Data were extractable from 5 studies, all case controls. We requested patient level data for 12 studies from the corresponding author, without response. When stratified by BMI, we detected heterogenous effects of SNPs on BC risk (Table 1, only significant or trending correlations presented). With high BMI, IL-1β-31 TT (OR 2.19, 0.86-5.59) and GC/CC (OR 0.81, 0.68-0.97) correlated with BC risk (p &amp;lt; 0.05). With normal BMI, STAT3 rs1026916 GA (OR 0.78, 0.62-0.96) and JAK2 rs1536800 TT (OR 1.93, 1.07-3.48) correlated with BC risk. Additional SNPs trended to correlate with BC risk (0.05 &amp;lt; mo &amp;gt;≤&amp;lt;/mo &amp;gt;&amp;lt;/math &amp;gt;"&amp;gt;≤ p &amp;lt; mo &amp;gt;≤&amp;lt;/mo &amp;gt;&amp;lt;/math &amp;gt;"&amp;gt;≤ 0.10) by BMI. Conclusion: The association of inflammatory SNPs and BC risk is complex and can be both protective and predisposing to BC risk, with BMI modifying SNP risk. Future research can assess SNPs and BC risk in more diverse populations. Citation Format: Erina Quinn, Braelyn Wekwerth, Maya Doyle, Ruth Carlos. Single Nucleotide Polymorphisms (SNPs) in Inflammatory Pathways Associated with Body Mass Index (BMI) and Breast Cancer (BC) Risk: A Scoping Review [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-29-02.

Impact of Family History and Germline Genetic Risk Single Nucleotide Polymorphisms on Long-Term Outcomes of Favorable-Risk Prostate Cancer.

Family history and germline genetic risk single nucleotide polymorphisms (SNPs) have been separately shown to stratify lifetime risk of prostate cancer. Here, we evaluate the combined prognostic value of family history of prostate and other related cancers and germline risk SNPs among patients with favorable-risk prostate cancer. A total of 1367 participants from the prospective Health Professionals Follow-up Study diagnosed with low- or favorable intermediate-risk prostate cancer from 1986 to 2017 underwent genome-wide SNP genotyping. Multivariable Cox regression was used to estimate the association between family history, specific germline risk variants, and a 269 SNP polygenic risk score with prostate cancer‒specific death. Family history of prostate, breast, and/or pancreatic cancer was observed in 489 (36%) participants. With median follow-up from diagnosis of 14.9 years, participants with favorable-risk prostate cancer with a positive family history had a significantly higher risk of prostate cancer‒specific death (HR 1.95, 95% CI 1.15-3.32, P = .014) compared to those without any family history. The rs2735839 (19q13) risk allele was associated with prostate cancer‒specific death (HR 1.81 per risk allele, 95% CI 1.04-3.17, P = .037), whereas the polygenic risk score was not. Combined family history and rs2735839 risk allele were each associated with an additive risk of prostate cancer‒specific death (HR 1.78 per risk factor, 95% CI 1.25-2.53, P = .001). Family history of prostate, breast, or pancreatic cancer and/or a 19q13 germline risk allele are associated with an elevated risk of prostate cancer‒specific death among favorable-risk patients. These findings have implications for how family history and germline genetic risk SNPs should be factored into clinical decision-making around favorable-risk prostate cancer.

Abstract 3791: A prognostic signature based on inherited genetic polymorphisms for patients with uveal melanoma

Abstract Introduction: Uveal melanoma (UM) is the most frequent eye malignancy in adults. Two UM subtypes exist, defined by Gene Expression Profiling or by genomic status: GEP class 1/disomy 3 [D3] and GEP class 2/monosomy 3 [M3] defining low-risk or high-risk of developing metastasis, respectively. However, these prognostic signatures require tumor samples, which may be difficult to obtain. We previously identified by a genome-wide association study (GWAS) frequent single nucleotide polymorphisms (SNP) in IRF4 and HERC2 associated with risk for D3 or M3 UM, respectively (1). Here, we aim to design a prognostic signature for the D3 and M3 UM subtypes based on these constitutive polymorphisms, available from blood samples. Experimental Procedures: We used the GWAS cohort of 1476 UM patients genotyped on GSA or Omni5. Risk SNPs coupled with clinical variables were used on a cohort of 497 UM patients (191 D3, 306 M3) in a statistical machine learning process to define a predictive signature of UM subtype. A cohort of 852 UM patients was used for validation. Results: We retained two SNPs, rs12203592 (in IRF4) and rs12913832 (in HERC2), tumor diameter and thickness, age at diagnosis and gender. We validated the predictive model in the validation cohort. The predicted high-risk group showed a decrease in time to relapse (TR) (HR: 3.72 [2.57 - 5.41], logrank p-value = 1.35E-15), overall survival (OS) (HR: 3.85 [2.58 - 5.73], logrank p-value = 1.24E-14) and progression-free-survival (PFS) (HR: 3.61 [2.32 - 5.61], logrank p-value = 6.55E-11), compared with the predicted low-risk group. Conclusion: Common germline polymorphisms contribute to the prediction of metastatic risk in patients with localized uveal melanoma. This information could be especially useful when access to the tumor is problematic. 1. Mobuchon et al, J Natl Cancer Inst, 114, 2, (2022) Citation Format: Thibault Verrier, Anaïs Le Ven, Alexandre Houy, Agathe Garcia, Pierron Gaelle, Nathalie Cassoux, Manuel Rodrigues, Josselin Noirel, Marc-Henri Stern. A prognostic signature based on inherited genetic polymorphisms for patients with uveal melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3791.

Investigating the shared genetic architecture between frailty and insomnia.

The epidemiological association between frailty and insomnia is well established, yet the presence of a common genetic etiology is still uncertain. Further exploration is needed to ascertain the causal relationship between frailty and insomnia. Utilizing data obtained from genome-wide association studies (GWAS) summaries, we utilized the linkage disequilibrium score regression (LDSC) to determine the genetic correlation existing between frailty and insomnia. The determination of causality was achieved through the application of two-sample Mendelian randomization. We investigated the enrichment of single nucleotide polymorphism (SNP) at various tissue types utilizing stratified LD score regression (S-LDSC) and multimarker analysis of genome annotation (MAGMA). Common risk SNPs were identified using Multi-Trait Analysis of GWAS (MTAG) and Cross-Phenotype Association (CPASSOC). We further investigated the expression profiles of risk genes in tissues using Summary-data-based Mendelian randomization(SMR) based on pooled data, to explore potential functional genes. Our findings indicated a significant genetic correlation between frailty and insomnia, highlighting SNPs sharing risk (rs34290943, rs10865954), with a pronounced correlation in the localized genomic region 3p21.31. Partitioned genetic analysis revealed 24 functional elements significantly associated with both frailty and insomnia. Furthermore, mendelian randomization revealed a causal connection between frailty and insomnia. The genetic correlation between frailty and insomnia showed enrichment in 11 brain regions (S-LDSC) and 9 brain regions (MAGMA), where four functional genes (RMB6, MST1R, RF123, and FAM212A) were identified. This study suggests the existence of a genetic correlation and common risk genes between frailty and insomnia, contributing to a deeper comprehension of their pathogenesis and assists in identifying potential therapeutic targets.

Enhanced osteoporotic fracture prediction in postmenopausal women using Bayesian optimization of machine learning models with genetic risk score.

This study aimed to enhance the fracture risk prediction accuracy in major osteoporotic fractures (MOFs) and hip fractures (HFs) by integrating genetic profiles, machine learning (ML) techniques, and Bayesian optimization. The genetic risk score (GRS), derived from 1,103 risk single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS), was formulated for 25,772 postmenopausal women from the Women's Health Initiative dataset. We developed four ML models: Support Vector Machine (SVM), Random Forest, XGBoost, and Artificial Neural Network (ANN) for binary fracture outcome and 10-year fracture risk prediction. GRS and FRAX clinical risk factors (CRFs) were used as predictors. Death as a competing risk was accounted for in ML models for time-to-fracture data. ML models were subsequently fine-tuned through Bayesian optimization, which displayed marked superiority over traditional grid search. Evaluation of the models' performance considered an array of metrics such as accuracy, weighted F1 Score, the area under the precision-recall curve (PRAUC), and the area under the receiver operating characteristic curve (AUC) for binary fracture predictions, and the C-index, Brier score, and dynamic mean AUC over a 10-year follow-up period for fracture risk predictions. We found that GRS-integrated XGBoost with Bayesian optimization is the most effective model, with an accuracy of 91.2% (95% CI: 90.4-92.0%) and an AUC of 0.739 (95% CI: 0.731-0.746) in MOF binary predictions. For 10-year fracture risk modeling, the XGBoost model attained a C-index of 0.795 (95% CI: 0.783-0.806) and a mean dynamic AUC of 0.799 (95% CI: 0.788-0.809). Compared to FRAX, the XGBoost model exhibited a categorical net reclassification improvement (NRI) of 22.6% (P= .004). A sensitivity analysis, which included BMD but lacked GRS, reaffirmed these findings. Furthermore, portability tests in diverse non-European groups, including Asians and African Americans, underscored the model's robustness and adaptability. This study accentuates the potential of combining genetic insights and optimized ML in strengthening fracture predictions, heralding new preventive strategies for postmenopausal women.

P709 Role of NOD2 single nucleotide polymorphisms on ustekinumab drug durability in adult patients with Crohn’s disease

Abstract Background Ustekinumab (UST), a monoclonal antibody targeting the p19 subunit of the pro-inflammatory Interleukins 12 and 23, is a therapeutic option in patients with Crohn’s disease (CD) with high efficacy, although some patients will have to cease therapy with UST due to primary non-response, secondary loss of response, or adverse events. Single nucleotide polymorphisms (SNPs) in the Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) gene have been proposed as a prognostic factor in CD. Whether these NOD2 SNPs have an impact on UST drug durability among adult CD patients remains unclear. Methods CD patients were genotyped for the three most common NOD2 SNPs (rs2066844, rs2066845, and rs2066847). Hazard ratios (HR) for risk of NOD2 SNPs on UST durability were calculated using univariable and multivariable cox proportional hazard regression adjusting for age at first UST prescription, previous surgery, Montreal A, L, and B classification, present perianal disease, and previous anti-TNF exposure. Statistical analysis was conducted using SPSS. A two-tailed P value &amp;lt; 0.05 was considered statistically significant. All patients provided written informed consent. Results 92 CD patients were included in the analysis. Of those, 72 continued receiving UST until the end of the study. In univariable and multivariable analyses, NOD2 SNPs were not independent prognostic factors for UST drug durability (P&amp;gt;0.05 for all three NOD2 SNPs). However, age at first UST prescription (adjusted HR [aHR] 0.96, 95% confidence interval [CI] 0.93-1.00, P=0.028 for all tested NOD2 SNPs) and present perianal disease (aHR 2.65, 95% CI 1.11-6.31, P=0.028 for all tested NOD2 SNPs) were independent predictors of ustekinumab drug durability. Conclusion Among adult Crohn’s disease patients being treated with ustekinumab, the presence of NOD2 SNPs did not have a significant impact on ustekinumab drug durability.

P1199 An Inflammatory Bowel Diseases Integrated Resources Portal (IBDIRP)

Abstract Background Inflammatory bowel disease (IBD), including ulcerative colitis and Crohn's disease (CD), is a chronic and debilitating gastrointestinal disorder that affects millions of people worldwide. Research on IBD has generated massive amounts of data, including literature, metagenomics, metabolism, bioresources, and databases. We aim to create an IBD Integrated Resources Portal (IBDIRP) that provides the most comprehensive resources for IBD. Methods An integrated platform was developed that provides information on different aspects of IBD research resources, such as single nucleotide polymorphism, genes, transcriptomics, microbiota, metabolism, single cells, and other resources. Valuable and comprehensive IBD-related data were collected from PubMed, Google, GMrepo, gutMega, gutMDisorder, Single-cell Portal, and other sources. Then, the data were systematically sorted, and these resources were manually curated. Results We systematically sorted and cataloged more than 312 unique risk single nucleotide polymorphism associated with IBD in the single nucleotide polymorphism section. We presented over 890 IBD-related genes based on the database collection in the gene section. We also obtained 153 manually curated IBD transcriptomics data, including 12,388 samples, on the GEO database. The sorted IBD-related microbiota data from three primary microbiome databases (GMrepo, gutMega, and gutMDisorder) were available for download. We selected 23,149 IBD-related taxonomic records from these databases. Additionally, we collected 24 IBD metabolism studies with 2,896 participants in the metabolism section. We introduced two interactive single-cell data plug-in units that provided data visualization based on cells and genes. Finally, we listed 18 significant IBD web resources, such as the official ECCO and IOIBD websites, IBD scoring tools, IBD genetic and multi-omics resources, IBD biobanks, and other useful research resources. Conclusion The IBDIRP website is the first integrated resource for global IBD researchers. This portal will help researchers by providing comprehensive knowledge and enabling them to reinforce the multi-dimensional impression of IBD. The IBDIRP website is accessible via www.ibdirp.com.

HiPSC-derived cardiomyocytes as a model to study the role of small-conductance Ca2+-activated K+ (SK) ion channel variants associated with atrial fibrillation.

Atrial fibrillation (AF), the most common arrhythmia, has been associated with different electrophysiological, molecular, and structural alterations in atrial cardiomyocytes. Therefore, more studies are required to elucidate the genetic and molecular basis of AF. Various genome-wide association studies (GWAS) have strongly associated different single nucleotide polymorphisms (SNPs) with AF. One of these GWAS identified the rs13376333 risk SNP as the most significant one from the 1q21 chromosomal region. The rs13376333 risk SNP is intronic to the KCNN3 gene that encodes for small conductance calcium-activated potassium channels type 3 (SK3). However, the functional electrophysiological effects of this variant are not known. SK channels represent a unique family of K+ channels, primarily regulated by cytosolic Ca2+ concentration, and different studies support their critical role in the regulation of atrial excitability and consequently in the development of arrhythmias like AF. Since different studies have shown that both upregulation and downregulation of SK3 channels can lead to arrhythmias by different mechanisms, an important goal is to elucidate whether the rs13376333 risk SNP is a gain-of-function (GoF) or a loss-of-function (LoF) variant. A better understanding of the functional consequences associated with these SNPs could influence clinical practice guidelines by improving genotype-based risk stratification and personalized treatment. Although research using native human atrial cardiomyocytes and animal models has provided useful insights, each model has its limitations. Therefore, there is a critical need to develop a human-derived model that represents human physiology more accurately than existing animal models. In this context, research with human induced pluripotent stem cells (hiPSC) and subsequent generation of cardiomyocytes derived from hiPSC (hiPSC-CMs) has revealed the underlying causes of various cardiovascular diseases and identified treatment opportunities that were not possible using in vitro or in vivo studies with animal models. Thus, the ability to generate atrial cardiomyocytes and atrial tissue derived from hiPSCs from human/patients with specific genetic diseases, incorporating novel genetic editing tools to generate isogenic controls and organelle-specific reporters, and 3D bioprinting of atrial tissue could be essential to study AF pathophysiological mechanisms. In this review, we will first give an overview of SK-channel function, its role in atrial fibrillation and outline pathophysiological mechanisms of KCNN3 risk SNPs. We will then highlight the advantages of using the hiPSC-CM model to investigate SNPs associated with AF, while addressing limitations and best practices for rigorous hiPSC studies.