Whole Exome Sequencing Data Research Articles

Diverse ancestral representation improves genetic intolerance metrics

The unprecedented scale of genomic databases has revolutionized our ability to identify regions in the human genome intolerant to variation—regions often implicated in disease. However, these datasets remain constrained by limited ancestral diversity. Here, we analyze whole-exome sequencing data from 460,551 UK Biobank and 125,748 Genome Aggregation Database (gnomAD) participants across multiple ancestries to test several key intolerance metrics, including the Residual Variance Intolerance Score (RVIS), Missense Tolerance Ratio (MTR), and Loss-of-Function Observed/Expected ratio (LOF O/E). We demonstrate that increasing ancestral representation, rather than sample size alone, critically drives their performance. Scores trained on variation observed in African and Admixed American ancestral groups show higher resolution in detecting haploinsufficient and neurodevelopmental disease risk genes compared to scores trained on European ancestry groups. Most strikingly, MTR trained on 43,000 multi-ancestry exomes demonstrates greater predictive power than when trained on a nearly 10-fold larger dataset of 440,000 non-Finnish European exomes. We further find that European ancestry group-based scores are likely approaching saturation. These findings highlight the need for enhanced population representation in genomic resources to fully realize the potential of precision medicine and drug discovery. Ancestry group-specific scores are publicly available through an interactive portal: http://intolerance.public.cgr.astrazeneca.com/.

Integrated Analysis of WES and scRNA-Seq Data Reveals the Genetic Basis of Immune Dysregulation in Unexplained Recurrent Pregnancy Loss.

This study aimed to identify genetic variants and their functional consequences underlying Unexplained Recurrent Pregnancy Loss (uRPL) through comprehensive genomic and transcriptomic analyses. We recruited 13 Chinese uRPL patients and performed Whole Exome Sequencing (WES) on chorionic villi samples from miscarriage tissues. Additionally, we conducted an integrative analysis using single-cell RNA sequencing data from decidual immune cells to examine expression patterns. WES analysis pinpointed variants in the four MUC genes (MUC4, MUC6, MUC16, and MUC17), six lipid metabolism genes in immune cells (ABCA4, ABCA7, ABCB5, ABCC8, ADGRV1, and ANK3), and two structural genes (PIEZO1 and PKD1), whose variants impair mucosal barriers and lipid homeostasis, thereby leading to immune dysregulation and contributing to uRPL. To delve deeper into the effects of these genetic variants on cellular expression patterns, we undertook an integrative analysis using a single-cell dataset from decidual immune cells in uRPL cases. We observed significant dysregulation of lipid metabolism within immune cells, reduced heat shock protein expression, and enhanced chemokine signaling in uRPL samples, indicating a pro-inflammatory state. In summary, our study reveals a complex interplay between genetic variants and immune cell dysfunctions in uRPL, emphasizing the role of identified genetic variants in driving pro-inflammatory states. These findings provide a comprehensive view of the molecular mechanisms underlying uRPL, opening paths for novel therapeutic interventions and improved clinical management.

Molecular subtyping of stage I lung adenocarcinoma via molecular alterations in pre-invasive lesion progression

BackgroundPatients with adenocarcinoma in situ (AIS) and minimally invasive (MIA) lung adenocarcinoma (LUAD) are curable by surgery, whereas 20% stage I patients die within five years after surgery. We hypothesize that poor-prognosis stage I patients may exhibit key molecular characteristics deviating from AIS/MIA. Therefore, we tried to reveal molecularly and prognostically distinct subtypes of stage I LUAD by applying key molecular alterations from AIS/MIA to invasive LUAD progression.MethodsThe RNA and whole-exome sequencing data of 197 tumor-normal matched samples from patients with AIS, MIA, and invasive LUAD were analyzed. ddPCR quantified 202 samples from 182 patients at the absolute expression level. Immunohistochemical quantified the protein expression levels of ACTA2. RNA-seq data from 954 LUAD patients, including 541 stage I patients, along with 12 published datasets comprising 1,331 stage I LUAD patients, were used to validate our findings.ResultsFocal adhesion (FA) was identified as the only pathway significantly perturbed at both genomic and transcriptomic levels by comparing 98 AIS/MIA and 99 LUAD. Then, two FA genes (COL11A1 and THBS2) were found strongly upregulated from AIS/MIA to stage I while steadily expressed from normal to AIS/MIA. Furthermore, unsupervised clustering separated stage I patients into two molecularly and prognostically distinct subtypes (S1 and S2) based on COL11A1 and THBS2 expressions (FA2). Subtype S1 resembled AIS/MIA, whereas S2 exhibited more somatic alterations and activated cancer-associated fibroblast. Immunohistochemistry on 73 samples also observed that CAF was more active in S2 compared to S1 and AIS/MIA. The prognostic value of these two genes identified from our knowledge-driven process was confirmed by 541 stage I patients in a prospective dataset, ddPCR and 12 published datasets.ConclusionsWe successfully revealed two molecularly and prognostically distinct subtypes of stage I LUAD by applying key molecular alterations from AIS/MIA to invasive LUAD progression. Our model may help reliably identify high-risk stage I patients for more intensive post-surgery treatment.

Clinical and Genomic Characterization of Secondary Rectal Cancer After Radiotherapy for Prostate Cancer.

Patients treated with radiotherapy (RT) for prostate cancer (PC) have increased risk of secondary rectal cancer (SRC) and more limited treatment options. To assess the tumor molecular profile, clinical characteristics, and oncologic outcomes of SRC after PC and compare them with those of primary rectal cancer (PRC). This case-control study included patients with SRC diagnosed 5 or more years after RT for PC and patients with PRC who were treated at Memorial Sloan Kettering Cancer Center in New York between February 1, 1994, and September 31, 2022. Clinical information and DNA sequencing data were analyzed. Oncologic outcomes were compared between patients with SRC and clinically matched patients with PRC using log-rank tests and Cox proportional hazards regression models. Numerical and categorical variables were compared using the Wilcoxon rank sum test and Fisher exact test, respectively. The analysis included 604 male patients with PRC (71.6%; median age, 55 [IQR, 46-66] years) and 64 male patients with SRC (median age, 78 [IQR, 72-82] years). Patients with SRC had more distal rectum (37 of 63 [58.7%] vs 131 of 581 [22.5%]; P < .001) and anterior rectal wall (20 of 57 [35.1%] vs 67 of 496 [13.5%]; P < .001) tumors, were less likely to receive neoadjuvant treatment (33 of 64 [51.6%] vs 570 of 604 [94.4%]), and had shorter 5-year overall survival (45.7% vs 64.9%; P = .01) and disease-free survival (40.3% vs 71.2%; P = .006) compared with clinically matched patients with PRC. Targeted DNA sequencing data from 31 SRC tumors identified lower mutational burden (median, 4.4 [IQR, 3.2-6.7] per megabase [Mb] vs 5.8 [IQR, 4.4-7.0] per Mb; P = .047), lower frequency of APC alterations (15 [48.4%] vs 432 [79.9%]; P < .001), and higher rates of SMAD4 inactivation (8 [25.8%] vs 54 [10.0%]; P = .01) compared with 541 PRC tumors. Whole-exome sequencing data from 17 SRC tumors identified a higher rate of frameshift deletions compared with 28 PRC tumors (median, 5.0 [IQR, 4.0-9.0] vs 2.5 [IQR, 1.0-4.2] variants; P < .001). In this case-control study, patients with SRC after RT for PC had worse survival and different molecular profiles than patients with PRC. These findings may help improve the clinical management of SRC.

Oligogenic analysis across broad phenotypes of 46,XY differences in sex development associated with NR5A1/SF-1 variants: findings from the international SF1next study.

Oligogenic inheritance has been suggested as a possible mechanism to explain the broad phenotype observed in individuals with differences of sex development (DSD) harbouring NR5A1/SF-1 variants. We investigated genetic patterns of possible oligogenicity in a cohort of 30 individuals with NR5A1/SF-1 variants and 46,XY DSD recruited from the international SF1next study, using whole exome sequencing (WES) on family trios whenever available. WES data were analysed using a tailored filtering algorithm designed to identify rare variants in DSD and SF-1-related genes. Identified variants were subsequently tested using the Oligogenic Resource for Variant Analysis (ORVAL) bioinformatics platform for a possible combined pathogenicity with the individual NR5A1/SF-1 variant. In 73% (22/30) of the individuals with NR5A1/SF-1 related 46,XY DSD, we identified one to seven additional variants, predominantly in known DSD-related genes, that might contribute to the phenotype. We found identical variants in eight unrelated individuals with DSD in DSD-related genes (e.g., TBCE, FLNB, GLI3 and PDGFRA) and different variants in eight genes frequently associated with DSD (e.g., CDH23, FLNB, GLI2, KAT6B, MYO7A, PKD1, SPRY4 and ZFPM2) in 15 index cases. Our study also identified combinations with NR5A1/SF-1 variants and variants in novel candidate genes. These findings highlight the complex genetic landscape of DSD associated with NR5A1/SF-1, where in several cases, the use of advanced genetic testing and filtering with specific algorithms and machine learning tools revealed additional genetic hits that may contribute to the phenotype. Swiss National Science Foundation and Boveri Foundation Zurich.

Comprehensive analysis of SLC17A5 variants in large European cohorts reveals no association with Parkinson's disease risk.

Comprehensive analysis of SLC17A5 variants in large European cohorts reveals no association with Parkinson's disease risk.

Rare variant association studies: Significance, methods, and applications in chronic pain studies.

Rare variant association studies: Significance, methods, and applications in chronic pain studies.

The contribution of coding variants to the heritability of multiple cancer types using UK Biobank whole-exome sequencing data

The contribution of coding variants to the heritability of multiple cancer types using UK Biobank whole-exome sequencing data

Meta-analysis of Germline Whole-exome Sequencing in 1435 Cases of Testicular Germ Cell Tumour to Evaluate Disruptive Mutations Under Dominant, Recessive, and X-linked Inheritance Models.

Meta-analysis of Germline Whole-exome Sequencing in 1435 Cases of Testicular Germ Cell Tumour to Evaluate Disruptive Mutations Under Dominant, Recessive, and X-linked Inheritance Models.

Family study of bipolar disorder with comorbid anxiety disorder points to THSD7A with possible role of parent-of-origin effect.

The aim of this study was to provide new insights into the genetics of bipolar disorder (BD) by analyzing BD comorbid with anxiety disorders. Structured interviews were conducted with BD patients and their parents. Cases were classified into those with comorbid anxiety spectrum (AS) and those without. The family history of patients with BD with comorbid AS was assessed. Focusing on parent-of-origin effects and genomic imprinting from the results, imprinted genes and tested single nucleotide polymorphisms (SNPs) in the identified genes were investigated for an association with BD by transmission disequilibrium test (TDT) using published whole-exome sequencing data. The incidence of comorbid AS among all the patients with BD analyzed in this study was 39.6%. Patients with BD whose fathers had AS or mood disorders exhibited a significantly higher rate of AS. Among the known imprinted genes, two were associated with BD: THSD7A and CACNA1C. By pruning SNPs, six variants of the THSD7A exons and four variants of the CACNA1C exons were included in the analysis. Among these, one variant of THSD7A, rs2074603, showed over-transmission from parents to patients with BD. Furthermore, it was nominally significant only for fathers when TDT was performed separately for fathers and mothers. THSD7A may play a role in BD with parent-of-origin effects. Further research is necessary to explore the mechanisms by which genomic imprinting is associated with BD. Clinical Trial Registration: N/A.

Sample size required for prognostic genes analysis in colorectal cancer

BackgroundDifferent colorectal cancer (CRC) studies rarely report overlapping prognostic genes. This study aimed to investigate the effects of sample size on prognostic genes analysis in CRC.MethodsWe included 418 CRC cases detected by whole-exome sequencing (WES) in the TCGA PanCancer cohort and 931 CRC cases detected by targeted sequencing in the MSK cohort. Prognostic genes analysis was repeated 200 times at each sample size level using a random resampling method.ResultsFor WES data, the number of prognostic genes increased in a power-law with increasing sample size in CRC cases with stage III and IV. This pattern also applied to CRC patients with stage II after the removal of patients with MSI-H or POLE mutations. However, for targeted sequencing data, the number of prognostic genes increased linearly with increasing sample size in CRC cases with stage III and IV. About 550 cases were required for stage IV CRC to reach the plateau of prognostic genes. In both cohorts, the proportion of true prognostic genes relative to sample size was consistent with a binomial distribution, indicating a significant effect of sample size on the reliability of prognostic genes. At the same sample size level, the number of prognostic genes from the WES data was higher than that from the targeted sequencing data, while the reliability of prognostic genes from the WES data was lower.ConclusionThis study shows the relationship between the number of prognostic genes and sample size in CRC and how mutation data affects this relationship. This will contribute to the trial design for prognostic genetic analysis in CRC.

High-Throughput Whole-Exome Sequencing and Large-Scale Computational Analysis to Identify the Genetic Biomarkers to Predict the Vedolizumab Response Status in Inflammatory Bowel Disease Patients from Saudi Arabia.

Background/Objectives: Vedolizumab (VDZ) is the new monoclonal drug targeting α4β7 integrin for patients with moderate/severe IBD. Between 30 and 45% of patients fail to respond to VDZ after 14-16 weeks of treatment. The aim of the study was to explore the genetic profile of vedolizumab-treated Arab IBD patients in Saudi Arabia to identify the potential biomarkers to differentiate the responders from non-responders. Methods: A cohort of 16 patients with IBD, including 4 with Crohn's disease and 12 with ulcerative colitis, were recruited. Following 16 weeks of VDZ treatment, nine were found to be responders and seven non-responders. Blood samples were collected for the whole exome sequencing of DNA from all patients. The variants in the whole-exome sequencing data were analyzed with a variety of bioinformatics tools and databases, such as Polyphen2, Mutation Taster, CADD, FATHMM, Open Target Platform, TOPPFun, STRING, and GTEx. Results: More than 1.6 million variants from 16 samples were analyzed. The rare variant analysis prioritized NOD2, IL23, IL10, IL27, and TRAF1 genes in non-responders. NOD2, IL23, IL10, IL27, and TRAF1 were found to be the significant IBD risk factors in multiple genome-wide association studies, and their pro-inflammatory activity might contribute to the inherent resistance to VDZ. Rare variants of CARD9, TYK2, IL4, and NLRP1 genes present in VDZ responders enhance the anti-inflammatory/immune modulation effects. Conclusions: This investigation is the first to apply whole-exome sequencing to identify the potential drug response biomarkers for the IBD drug VDZ in Saudi Arabia.

Clonal hematopoiesis of indeterminate potential, health indicators, and risk of cardiovascular diseases among patients with diabetes: a prospective cohort study

BackgroundClonal hematopoiesis of indeterminate potential (CHIP) was associated with diabetes and cardiovascular diseases (CVD). However, the effect of CHIP on CVD have not been evaluated among patients with diabetes, and whether maintaining the healthy indictors could mitigate the adverse influence was also unclear.MethodsA total of 22,239 adults from the UK Biobank with diabetes and available whole-exome sequence data, and free of CVD were included. Multivariable-adjusted Cox regressions were used to explore the associations of any CHIP (variant allele fraction ≥ 2%), large CHIP (variant allele fraction ≥ 10%), and the top 10 commonly mutated driver genes for CHIP and with risk of CVD. The joint associations between health indicators (body mass index [BMI], HbA1c, blood pressure [BP], and low-density lipoprotein cholesterol [LDL]) and CHIP were further investigated.ResultsOver a median follow-up of 13.2 years, 5366 participants with diabetes developed CVD events. The hazard ratios (HRs) (95% confidence intervals [CIs]) of any CHIP and large CHIP were (1.21, 1.08–1.36) and (1.25, 1.09–1.43) for incident CVD, respectively. Significant associations between any CHIP and coronary heart disease (HR, 95%CI: 1.18, 1.03–1.36) and heart failure (1.73, 1.46–2.06) were observed, but not for stroke (1.14, 0.89–1.48). Gene-specific analyses suggested that the greatest association were for SF3B1 (HR, 95%CI: 2.50, 1.25–5.01) and TET2 (HR, 95%CI: 1.36, 1.07–1.77) with risk of CVD. There was no significant interaction between the four health indicators and CHIP in relation to incident CVD. Compared to patients without CHIP, those with any CHIP and ideal health indicators still exhibited significantly or nonsignificantly higher HRs (BMI: 1.18, 0.82–1.68; HbA1c: 1.12, 0.96–1.30; BP: 1.24, 1.03–1.49; LDL: 1.29, 1.09–1.53). Similar results were demonstrated using large CHIP.ConclusionsCHIP is independently associated with an increased risk of CVD in patients with diabetes, regardless of health indicator levels. Diabetic patients with CHIP but ideal health indicators still exhibited higher CVD risk compared with diabetic patients without CHIP.Graphic abstract

Combined genomics and proteomics unveils elusive variants and vast aetiologic heterogeneity in dystonia.

Dystonia is a rare-disease trait for which large-scale genomic investigations are still underrepresented. Genetic heterogeneity among patients with unexplained dystonia warrants interrogation of entire genome sequences, but this has not yet been systematically evaluated. To significantly enhance our understanding of the genetic contribution to dystonia, we (re)analyzed 2,874 whole-exome sequencing (WES), 564 whole-genome sequencing (WGS), as well as 80 fibroblast-derived proteomics datasets, representing the output of high-throughput analyses in 1,990 patients and 973 unaffected relatives from 1,877 families. Recruitment and precision-phenotyping procedures were driven by long-term collaborations of international experts with access to overlooked populations. By exploring WES data, we found that continuous scaling of sample sizes resulted in steady gains in the number of associated disease genes without plateauing. On average, every second diagnosis involved a gene not previously implicated in our cohort. Second-line WGS focused on a subcohort of undiagnosed individuals with high likelihood of having monogenic forms of dystonia, comprising large proportions of patients with early onset (81.3%), generalized symptom distribution (50.8%) and/or coexisting features (68.9%). We undertook extensive searches for variants in nuclear and mitochondrial genomes to uncover 38 (ultra)rare diagnostic-grade findings in 37 of 305 index patients (12.1%), many of which had remained undetected due to methodological inferiority of WES or pipeline limitations. WGS-identified elusive variations included alterations in exons poorly covered by WES, RNA-gene variants, mitochondrial-DNA mutations, small copy-number variants, complex rearranged genome structure, and short tandem repeats. For improved variant interpretation in WGS-inconclusive cases, we employed systematic integration of quantitative proteomics. This aided in verifying diagnoses related to technically challenging variants and in upgrading a variant of uncertain significance (3 of 70 WGS-inconclusive index patients, 4.3%). Further, unsupervised proteomic outlier-analysis supplemented with transcriptome sequencing revealed pathological gene underexpression induced by transcript disruptions in three more index patients with underlying (deep) intronic variants (3/70, 4.3%), highlighting the potential for targeted antisense-oligonucleotide therapy development. Finally, trio-WGS prioritized a de-novo missense change in the candidate PRMT1, encoding a histone-methyltransferase. Data-sharing strategies supported the discovery of three distinct PRMT1 de-novo variants in four phenotypically similar patients, associated with loss-of-function effects in in-vitro assays. This work underscores the importance of continually expanding sequencing cohorts to characterize the extensive spectrum of gene aberrations in dystonia. We show that a pool of unresolved cases is amenable to WGS and complementary multi-omic studies, directing advanced etiopathological concepts and future diagnostic-practice workflows for dystonia.

Germline correlates of clinical outcomes in aggressive prostate cancer subtypes treated with radiation therapy.

418 Background: Research on the genetic profile of cribriform pattern (CP) and intraductal carcinoma (IDC) subtypes of aggressive prostate cancer (PCa) is limited. We evaluated germline mutations in CP/IDC PCa patients receiving radiation therapy (RT) to assess the role of familial high-risk (FHR) and DNA damage repair (DDR) mutations associated with these pathologies and clinical outcomes. Methods: This multi-institutional study included CP/IDC PCa patients treated with RT who consented to germline whole exome sequencing (WES). WES data was annotated using Ensembl Variant Predictor, ClinVar, and OncoKB to identify pathogenic/oncogenic mutations. Mutational frequencies were calculated in R. Clinical data and disease progression (biochemical recurrence [BCR], local relapse [LR], distant metastases [DM]) were assessed. Gene and clinical outcome associations were evaluated using the Kaplan-Meier method and log-rank test (p &lt; 0.05 for significance, Benjamini-Hochberg FDR of 0.1 used for multiple hypothesis testing). Results: Of 1,392 CP/IDC patients treated with RT between 2010-2024, 80 had germline sequencing, and 49 had WES data (12 CP, 24 IDC, 13 CP+IDC); 45 were localized at diagnosis (28 high-, 16 intermediate-, 1 low-risk). Median age at diagnosis was 64 years. 39 (80%) received RT post-radical prostatectomy (RP, salvage) and 10 (20%) for intact prostate (definitive). Median follow-up (FU, months) was 64.5 after diagnosis and 60.3 after RT. At last FU post-RT, 14 (29%) exhibited BCR, 12 (24%) had LR, and 9 (18%) had DM, with progression rates of 83% in CP and IDC, and 77% in CP+IDC. Five-year OS from diagnosis was 94.8% (95% CI, 80.4-98.7), and BCR-free survival (defined as no BCR post-salvage or post-definitive RT) was 69% (95% CI, 47.8-83). Of the 98 FHR and 280 DDR genes analyzed, 4 (8%) and 20 (40%) patients had confirmed mutations, respectively. Of the 24 patients with germline mutations, 20 (83%) had IDC pathology. DDR mutations associated with improved BCR-free survival, HR 0.14, 95%CI 0.03-0.70, p=0.007. Notably, 19 patients had a pathogenic MSH3 deletion, which was associated with improved BCR-free survival, HR 0.17, 95%CI 0.03-0.83, p=0.02. Additionally, 20 patients had pathogenic stop-gains/deletions, 17 (85%) of whom had IDC pathology. Five oncogene mutations were identified in DDR genes ATR, TP53 and ATM, and tumor suppressor genes SHDA and DPYS previously implicated in PCa, all in IDC samples. Conclusions: Pathogenic germline mutations, particularly DDR variants, are significantly associated with aggressive IDC pathology. Continued evaluation in non-CP/IDC patients undergoing RT is needed to examine associations between mutations, subtypes, and outcomes. Mutations in DDR genes, such as MSH3 deletion, were linked to improved BCR-free survival, highlighting the potential role of DDR alterations in therapeutic response of RT patients with aggressive PCa subtypes.

GenoCare Prognosticator Model: Host Genetics Predict Severity of Infectious Disease

Scientific community understanding of the variance in severity of infectious disease like COVID-19 across patients is an important area of focus. The article presents an innovative voting ensemble GenoCare Prognosticator (GCP) model that incorporates XGBoost and Random Forest classifiers, two cutting-edge machine learning approaches. A large dataset that incorporates medical covariates like gender and age along with biological WES (Whole Exome Sequencing) data was used to train these models. Five-fold stratified cross-validation was used to process the dataset in order to improve model stability and avoid overfitting. Two medical covariates and sixteen recognized candidate gene variants were among the eighteen major features on which our GCP model had been verified using data from earlier studies. Specific post-hoc clarification of the model’s predictions was provided by ExplainerDashboard, a Python open-source library, to improve interpretability. Furthermore, we utilized OpenTarget and Enrichr, two bioinformatic resources, to establish connections between the discovered variations in genetics and pertinent ontologies, biological pathways, and possible drug/disease relationships. Unsupervised clustering of SHAP key feature values was included in the analysis, which revealed intricate genetic interactions that affect the severity of the disease. Our results show that although gender and age are the main factors influencing the severity of COVID-19, complex genetic interactions cause severe symptoms in a specific subset of patients. This work contributes to our comprehension of the biological variables influencing the severity of COVID-19 and offers a reliable, comprehensible model that can help recognize patients at high risk and guide individualized treatment plans.

Research on genetic variant characteristics in ADME genes based on whole-exome sequencing in the Han Chinese population.

Research on genetic variant characteristics in ADME genes based on whole-exome sequencing in the Han Chinese population.

A polygenic risk score derived from common variants of monogenic diabetes genes is associated with young-onset type 2 diabetes and cardiovascular-kidney complications.

Monogenic diabetes is caused by rare mutations in genes usually implicated in beta cell biology. Common variants of monogenic diabetes genes (MDG) may jointly influence the risk of young-onset type 2 diabetes (YOD, diagnosed before the age of 40 years) and cardiovascular and kidney events. Using whole-exome sequencing data, we constructed a weighted polygenic risk score (wPRS) consisting of 135 common variants (minor allele frequency >0.01) of 34 MDG based on r2>0.2 for linkage disequilibrium in a discovery case-control cohort of 453 adults with YOD (median [IQR] age 39.7 [34.9-46.9] years) and 405 without YOD (median [IQR] age 56.7 [50.3-61.0] years), followed by validation in an independent cross-sectional cohort with array-based genotyping for YOD and a prospective cohort of individuals with type 2 diabetes for cardiovascular and kidney events. In the discovery cohort, the OR of the 135 common variants for YOD ranged from 1.00 to 2.61. In the validation cohort (920 YOD and 4910 non-YOD), top-10%-wPRS was associated with an OR of 1.42 (95% CI 1.03, 1.95, p=0.033) for YOD compared with bottom-10%-wPRS. In 2313 individuals with type 2 diabetes (median [IQR]: age 53.4 [45.4-61.7] years; disease duration 4.0 [1.0-9.0] years) observed for a median (IQR) of 17.5 (14.4-21.8) years, standardised wPRS was associated with increased HR for incident cardiovascular events (1.16 [95% CI 1.06, 1.27], p=0.001), kidney events (1.09 [95% CI 1.02, 1.16], p=0.013) and cardiovascular-kidney events (1.10 [95% CI 1.03, 1.16], p=0.003). Using the 'bottom-20%-wPRS plus baseline disease duration <5 years' group as referent, the 'top-20%-wPRS plus baseline disease duration 5 to <10 years' group had unadjusted and adjusted HR of 1.60 (95% CI 1.17, 2.19, p=0.003) and 1.62 (95% CI 1.16, 2.26, p=0.005), respectively, for cardiovascular-kidney events compared with 1.38 (95% CI 0.97, 1.98, p=0.075) and 1.06 (95% CI 0.72, 1.57, p=0.752) in the 'bottom-20%-wPRS plus baseline disease duration ≥10 years' group. Common variants of MDG increased risk for YOD and cardiovascular-kidney events.

A replication study of novel fetal hemoglobin-associated genetic variants in sickle cell disease-only cohorts.

Sickle cell disease (SCD) is the most common monogenic disease in the world and is caused by mutations in the β-globin gene (HBB). Notably, SCD is characterized by extreme clinical heterogeneity. Inter-individual variation in fetal hemoglobin (HbF) levels strongly contributes to this patient-to-patient variability, with high HbF levels associated with decreased morbidity and mortality. Genetic association studies have identified and replicated HbF levels-associated variants at three loci: BCL11A, HBS1L-MYB, and HBB. In SCD patients, genetic variation at these three loci accounts for ~ 50% of HbF heritability. Genome-wide association studies (GWAS) in non-anemic and SCD patients of multiple ancestries have identified 20 new HbF-associated variants. However, these genetic associations have yet to be replicated in independent SCD cohorts. Here, we validated the association between HbF levels and variants at five of these new loci (ASB3, BACH2, PFAS, ZBTB7A, and KLF1) in up to 3740 SCD patients. By combining CRISPR inhibition and single-cell transcriptomics, we also showed that sequences near non-coding genetic variants at BACH2 (rs4707609) and KLF1 (rs2242514, rs10404876) can control the production of the β-globin genes in erythroid HUDEP-2 cells. Finally, we analyzed whole-exome sequence data from 1354 SCD patients but could not identify rare genetic variants of large effect on HbF levels. Together, our results confirm five new HbF-associated loci that can be functionally studied to develop new strategies to induce HbF expression in SCD patients.

Clinicopathological and molecular features of HR + /HER2 - breast cancer patients with distinct endocrine resistance patterns.

Recurrence continues to be a pivotal challenge among hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancers. In the international consensus guidelines, HR+/HER2- breast cancer relapse patterns are divided into three distinct types: primary resistant, secondary resistant, and endocrine sensitive. However, owing to the lack of cohorts with treatment and follow-up data, the heterogeneity among different recurrence patterns remains uncharted. Current treatments still lack precision. This analysis included data from a large-scale multiomics study of a HR+/HER2- breast cancer cohort (n=314). Through the analysis of transcriptomics (n=312), proteomics (n=124), whole-exome sequencing (n=290), metabolomics (n=217), and digital pathology (n=228) data, we explored distinctive molecular features and identified putative therapeutic targets for patients experiencing recurrence. We explored distinct clinicopathological characteristics, biological heterogeneity, and potential therapeutic strategies for recurrence. Based on a shared relapse signature, we stratified patients into high- and low-recurrence-risk groups. Patients with different relapse patterns presented unique molecular features in primary tumors. Specifically, receptor tyrosine kinase (RTK) pathway activation in the primary resistant group suggested the utility of RTK inhibitors, whereas mammalian target of rapamycin (mTOR) and cell cycle pathway activation in the secondary resistant group highlighted the potential of mTOR and CDK4/6 inhibitors. Interestingly, the endocrine-sensitive group displayed a quiescent state and high genomic instability, suggesting that targeting quiescent cells and using poly-ADP-ribose polymerase (PARP) inhibitors could be effective strategies. These findings illuminate the clinicopathological and molecular landscape of HR+/HER2- breast cancer patients with distinct recurrence patterns, highlighting potential targeted therapies.