Large-scale cross-ancestry genome-wide meta-analysis of serum urate

Hyperuricemia is an essential causal risk factor for gout and is associated with cardiometabolic diseases. Given the limited contribution of East Asian ancestry to genome-wide association studies of serum urate, the genetic architecture of serum urate requires exploration. A large-scale cross-ancestry genome-wide association meta-analysis of 1,029,323 individuals and ancestry-specific meta-analysis identifies a total of 351 loci, including 17 previously unreported loci. The genetic architecture of serum urate control is similar between European and East Asian populations. A transcriptome-wide association study, enrichment analysis, and colocalization analysis in relevant tissues identify candidate serum urate-associated genes, including CTBP1, SKIV2L, and WWP2. A phenome-wide association study using polygenic risk scores identifies serum urate-correlated diseases including heart failure and hypertension. Mendelian randomization and mediation analyses show that serum urate-associated genes might have a causal relationship with serum urate-correlated diseases via mediation effects. This study elucidates our understanding of the genetic architecture of serum urate control.

The Clinical Validity of Urinary Pellet DNA Monitoring for the Diagnosis of Recurrent Bladder Cancer

The aim of this study was to evaluate the clinical validity of monitoring urine pellet DNA (upDNA) of bladder cancer (BC) by digital PCR (dPCR) as a biomarker for early recurrence prediction, treatment efficacy evaluation, and no-recurrence corroboration. Tumor panel sequencing was first performed to select patient-unique somatic mutations to monitor both upDNA and circulating tumor DNA (ctDNA) by dPCR. For longitudinal monitoring using upDNA as well as plasma ctDNA, an average of 7.2 (range, 2 to 12) time points per case were performed with the dPCR assay for 32 previously treated and untreated patients with BC. Clinical recurrence based on imaging and urine cytology was compared using upDNA variant allele frequency (VAF) dynamics. A continuous increasing trend of upDNA VAF ≥1% was considered to indicate molecular recurrence. Most (30/32; 93.8%) cases showed at least one traceable somatic mutation. In 5 of 7 cases (71.4%) with clinical recurrence, upDNA VAF >1% was detected 7 to 15 months earlier than the imaging diagnosis. The upDNA VAF remained high after initial treatment for locally recurrent cases. The clinical validity of upDNA monitoring was confirmed with the observation that 26 of 30 cases (86.7%) were traceable. Local recurrences were not indicated by ctDNA alone. The results support the clinical validity of upDNA monitoring in the management of recurrent BC.

Implication of Pre- and Post-radiotherapy ctDNA Dynamics in Patients with Residual Triple-Negative Breast Cancer at Surgery after Neoadjuvant Chemotherapy: Findings from a Prospective Observational Study

PURPOSE

This study aims to determine the association between pre- and postoperative radiotherapy (PORT) circulating tumor DNA (ctDNA) dynamics and oncological outcomes in patients with residual triple-negative breast cancer who underwent surgery after neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

Between March 2019 and July 2020, 11 nonmetastatic patients with residual disease who underwent surgery after NAC were prospectively enrolled. In each patient, tumor specimens obtained during surgery and blood samples collected at three time points during PORT (T0: pre-PORT, T1: 3 weeks after PORT, T2: 1 month after PORT) were sequenced, targeting 38 cancer-related genes. Disease-free survival (DFS) was evaluated and the association between DFS and ctDNA dynamics was analyzed.

RESULTS

At T0, ctDNA was detected in three (27.2%) patients. The ctDNA dynamics were as follows: two showed a decreasing ctDNA variant allele frequency (VAF) and reached zero VAF at T2, while one patient exhibited an increasing VAF during PORT and maintained an elevated VAF at T2. After a median follow-up of 48 months, two patients experienced distant metastasis without any locoregional failures. All failures occurred in patients with ctDNA positivity at T0 and a decreased VAF after PORT. The 4-year DFS rates according to the T0 ctDNA status were 67% (positive ctDNA) and 100% (negative ctDNA) (p=0.032).

CONCLUSION

More than a quarter of the patients with residual disease after post-NAC surgery exhibited pre-PORT ctDNA positivity, and ctDNA positivity was associated with poor DFS. For patients with pre-PORT ctDNA positivity, the administration of a more effective systemic treatment should be considered.

Association between genetic risk and adherence to healthy lifestyle for developing age-related hearing loss

BACKGROUND

Previous studies have shown that lifestyle/environmental factors could accelerate the development of age-related hearing loss (ARHL). However, there has not yet been a study investigating the joint association among genetics, lifestyle/environmental factors, and adherence to healthy lifestyle for risk of ARHL. We aimed to assess the association between ARHL genetic variants, lifestyle/environmental factors, and adherence to healthy lifestyle as pertains to risk of ARHL.

METHODS

This case-control study included 376,464 European individuals aged 40 to 69 years, enrolled between 2006 and 2010 in the UK Biobank (UKBB). As a replication set, we also included a total of 26,523 individuals considered of European ancestry and 9834 individuals considered of African-American ancestry through the Penn Medicine Biobank (PMBB). The polygenic risk score (PRS) for ARHL was derived from a sensorineural hearing loss genome-wide association study from the FinnGen Consortium and categorized as low, intermediate, high, and very high. We selected lifestyle/environmental factors that have been previously studied in association with hearing loss. A composite healthy lifestyle score was determined using seven selected lifestyle behaviors and one environmental factor.

RESULTS

Of the 376,464 participants, 87,066 (23.1%) cases belonged to the ARHL group, and 289,398 (76.9%) individuals comprised the control group in the UKBB. A very high PRS for ARHL had a 49% higher risk of ARHL than those with low PRS (adjusted OR, 1.49; 95% CI, 1.36-1.62; P < .001), which was replicated in the PMBB cohort. A very poor lifestyle was also associated with risk of ARHL (adjusted OR, 3.03; 95% CI, 2.75-3.35; P < .001). These risk factors showed joint effects with the risk of ARHL. Conversely, adherence to healthy lifestyle in relation to hearing mostly attenuated the risk of ARHL even in individuals with very high PRS (adjusted OR, 0.21; 95% CI, 0.09-0.52; P < .001).

CONCLUSIONS

Our findings of this study demonstrated a significant joint association between genetic and lifestyle factors regarding ARHL. In addition, our analysis suggested that lifestyle adherence in individuals with high genetic risk could reduce the risk of ARHL.

Polygenic risk score-based phenome-wide association study of head and neck cancer across two large biobanks

BACKGROUND

Numerous observational studies have highlighted associations of genetic predisposition of head and neck squamous cell carcinoma (HNSCC) with diverse risk factors, but these findings are constrained by design limitations of observational studies. In this study, we utilized a phenome-wide association study (PheWAS) approach, incorporating a polygenic risk score (PRS) derived from a wide array of genomic variants, to systematically investigate phenotypes associated with genetic predisposition to HNSCC. Furthermore, we validated our findings across heterogeneous cohorts, enhancing the robustness and generalizability of our results.

METHODS

We derived PRSs for HNSCC and its subgroups, oropharyngeal cancer and oral cancer, using large-scale genome-wide association study summary statistics from the Genetic Associations and Mechanisms in Oncology Network. We conducted a comprehensive investigation, leveraging genotyping data and electronic health records from 308,492 individuals in the UK Biobank and 38,401 individuals in the Penn Medicine Biobank (PMBB), and subsequently performed PheWAS to elucidate the associations between PRS and a wide spectrum of phenotypes.

RESULTS

We revealed the HNSCC PRS showed significant association with phenotypes related to tobacco use disorder (OR, 1.06; 95% CI, 1.05-1.08; P = 3.50 × 10-15), alcoholism (OR, 1.06; 95% CI, 1.04-1.09; P = 6.14 × 10-9), alcohol-related disorders (OR, 1.08; 95% CI, 1.05-1.11; P = 1.09 × 10-8), emphysema (OR, 1.11; 95% CI, 1.06-1.16; P = 5.48 × 10-6), chronic airway obstruction (OR, 1.05; 95% CI, 1.03-1.07; P = 2.64 × 10-5), and cancer of bronchus (OR, 1.08; 95% CI, 1.04-1.13; P = 4.68 × 10-5). These findings were replicated in the PMBB cohort, and sensitivity analyses, including the exclusion of HNSCC cases and the major histocompatibility complex locus, confirmed the robustness of these associations. Additionally, we identified significant associations between HNSCC PRS and lifestyle factors related to smoking and alcohol consumption.

CONCLUSIONS

The study demonstrated the potential of PRS-based PheWAS in revealing associations between genetic risk factors for HNSCC and various phenotypic traits. The findings emphasized the importance of considering genetic susceptibility in understanding HNSCC and highlighted shared genetic bases between HNSCC and other health conditions and lifestyles.

Genome-wide association analyses using machine learning-based phenotyping reveal genetic architecture of occupational creativity and overlap with psychiatric disorders

Creativity is known to be heritable and exhibits familial aggregation with psychiatric disorders; however, the complex nature of their relationship has not been well-established. In the present study, we demonstrate that using an expanded and validated machine learning (ML)-based phenotyping of occupational creativity (OC) can allow us to further understand the trait of creativity, which was previously difficult to define and study. We conducted the largest genome-wide association study (GWAS) on OC with 241,736 participants from the UK Biobank and identified 25 lead variants that have not yet been reported and three candidate causal genes that were previously associated with educational attainment and psychiatric disorders. We found extensive genetic overlap between OC and psychiatric disorders with mixed effect direction through various post-GWAS analyses, including the bivariate causal mixture model. In addition, we discovered a strongly genetic correlation between our original GWAS and the GWAS adjusted for education years (rg = 0.95). Our GWAS analysis via ML-based phenotyping contributes to the understanding of the genetic architecture of creativity, which may inform genetic discovery and genetic prediction in human cognition and psychiatric disorders.

Shared genetic architectures of educational attainment in East Asian and European populations

Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.

Transdiagnostic clustering and network analysis for questionnaire-based symptom profiling and drug recommendation in the UK Biobank and a Korean cohort

Clinical decision support systems (CDSSs) play a critical role in enhancing the efficiency of mental health care delivery and promoting patient engagement. Transdiagnostic approaches that utilize raw psychological and biological data enable personalized patient profiling and treatment. This study introduces a CDSS incorporating symptom profiling and drug recommendation for mental health care. Among the UK Biobank cohort, we analyzed 157,348 participants for symptom profiling and 14,358 participants with a drug prescription history for drug recommendation. Among the 1307 patients in the Samsung Medical Center cohort, 842 were eligible for analysis. Symptom profiling utilized demographic and questionnaire data, employing conventional clustering and community detection methods. Identified clusters were explored using diagnostic mapping, feature importance, and scoring. For drug recommendation, we employed cluster- and network-based approaches. The analysis identified nine clusters using k-means clustering and ten clusters with the Louvain method. Clusters were annotated for distinct features related to depression, anxiety, psychosis, drug addiction, and self-harm. For drug recommendation, drug prescription probabilities were retrieved for each cluster. A recommended list of drugs, including antidepressants, antipsychotics, mood stabilizers, and sedative-hypnotics, was provided to individual patients. This CDSS holds promise for efficient personalized mental health care and requires further validation and refinement with larger datasets, serving as a valuable tool for mental healthcare providers.

Biomarker-driven phase 2 umbrella trial: Clinical efficacy of olaparib monotherapy and combination with ceralasertib (AZD6738) in small cell lung cancer

BACKGROUND

Based on a high incidence of genomic alteration in the cell cycle and DNA damage and response (DDR)-related pathways in small cell lung cancer (SCLC), the clinical efficacy of the DDR-targeting agent olaparib (PARP inhibitor) as monotherapy and in combination with ceralasertib (ATR inhibitor) in relapsed or refractory SCLC was evaluated.

METHODS

As part of a phase 2 biomarker driven umbrella study, patients with SCLC and predefined DDR gene alterations who failed to benefit from prior platinum-based regimens were allocated to the olaparib monotherapy arm and nonbiomarker-selected patients were allocated to the olaparib and ceralasertib combination arm.

RESULTS

In the olaparib monotherapy arm (n = 15), the objective response rate was 6.7% (one partial response), and the disease control rate was 33.3%, including three patients with stable disease. The median progression-free survival was 1.3 months (95% CI, 1.2-NA). In the combination arm (n = 26), the objective response rate and disease control rate were 3.8% and 42.3%, respectively, with one partial response and 10 patients with stable disease. The median progression-free survival was 2.8 months (95% CI, 1.8-5.4). Treatment was generally well tolerated except for one fatal case of neutropenic fever in the combination arm.

CONCLUSIONS

Targeting DDR pathways with olaparib as a single agent or in combination with ceralasertib did not meet the predefined efficacy end point. However, disease stabilization was more evident in the combination arm. Further investigation of the combination of olaparib in SCLC should be performed with diverse combinations and patient selection strategies to maximize efficacy.

Early immune remodeling steers clinical response to frontline chemoimmunotherapy in advanced gastric cancer

Adding anti-PD1 to 5-FU/platinum improves survival in some advanced gastroesophageal adenocarcinomas (GEA). To understand the effects of chemotherapy and immunotherapy we conducted a phase II frontline trial (n = 47) sequentially adding pembrolizumab to 5-FU/platinum in advanced GEA. Using serial biopsy of the primary tumor at baseline, after one cycle of 5-FU/platinum, and after the addition of pembrolizumab we transcriptionally profiled 358,067 single cells to identify evolving multicellular TME networks. Chemotherapy induced early on-treatment multicellular hubs with tumor-reactive T-cell and M1-like macrophage interactions in slow progressors. Faster progression featured increased MUC5A and MSLN containing treatment-resistance programs in tumor cells and M2-like macrophages with immunosuppressive stromal interactions. After pembrolizumab we observed increased CD8 T-cell infiltration and development of an immunity hub involving tumor-reactive CXCL13 T-cell program and epithelial interferon-stimulated gene programs. Strategies to drive increases in anti-tumor immune hub formation could expand the portion of patients benefiting from anti-PD1 approaches.

Comprehensive profiling of DNA methylation in Korean patients with colorectal cancer

Alterations in DNA methylation play an important pathophysiological role in the development and progression of colorectal cancer. We comprehensively profiled DNA methylation alterations in 165 Korean patients with colorectal cancer (CRC), and conducted an in-depth investigation of cancer-specific methylation patterns. Our analysis of the tumor samples revealed a significant presence of hypomethylated probes, primarily within the gene body regions; few hypermethylated sites were observed, which were mostly enriched in promoter-like and CpG island regions. The CpG Island Methylator PhenotypeHigh (CIMP-H) exhibited notable enrichment of microsatellite instability-high (MSI-H). Additionally, our findings indicated a significant correlation between methylation of the MLH1 gene and MSI-H status. Furthermore, we found that the CIMP-H had a higher tendency to affect the right-side of the colon tissues and was slightly more prevalent among older patients. Through our methylome profile analysis, we successfully verified the thylation patterns and clinical characteristics of Korean patients with CRC. This valuable dataset lays a strong foundation for exploring novel molecular insights and potential therapeutic targets for the treatment of CRC. [BMB Reports 2024; 57(2): 110-115].

Machine learning model for circulating tumor DNA detection in chronic obstructive pulmonary disease patients with lung cancer

Background

Patients with chronic obstructive pulmonary disease (COPD) have a high risk of developing lung cancer. Due to the high rates of complications from invasive diagnostic procedures in this population, detecting circulating tumor DNA (ctDNA) as a non-invasive method might be useful. However, clinical characteristics that are predictive of ctDNA mutation detection remain incompletely understood. This study aimed to investigate factors associated with ctDNA detection in COPD patients with lung cancer.

Methods

Herein, 177 patients with COPD and lung cancer were prospectively recruited. Plasma ctDNA was genotyped using targeted deep sequencing. Comprehensive clinical variables were collected, including the emphysema index (EI), using chest computed tomography. Machine learning models were constructed to predict ctDNA detection.

Results

At least one ctDNA mutation was detected in 54 (30.5%) patients. After adjustment for potential confounders, tumor stage, C-reactive protein (CRP) level, and milder emphysema were independently associated with ctDNA detection. An increase of 1% in the EI was associated with a 7% decrease in the odds of ctDNA detection (adjusted odds ratio =0.933; 95% confidence interval: 0.857-0.999; P=0.047). Machine learning models composed of multiple clinical factors predicted individuals with ctDNA mutations at high performance (AUC =0.774).

Conclusions

ctDNA mutations were likely to be observed in COPD patients with lung cancer who had an advanced clinical stage, high CRP level, or milder emphysema. This was validated in machine learning models with high accuracy. Further prospective studies are required to validate the clinical utility of our findings.

Potential Role of Macrophage Polarization in the Progression of Hunner-Type Interstitial Cystitis

BACKGROUND

Hunner-type interstitial cystitis (HIC) is a chronic inflammatory condition of the bladder. However, it remains unclear whether there is a causal relationship between the presence of Hunner lesions and seemingly normal-appearing areas in the bladder (non-Hunner lesions). This study aimed to investigate the fundamental aspects of HIC by examining potential genetic differences between Hunner and non-Hunner lesions and elucidate their role as potential markers in the progression and suppression of the disease.

METHODS

This cross-sectional study enrolled patients with HIC (n = 10) who underwent supratrigonal cystectomy along with augmentation cystoplasty. Full-thickness bladder tissue was collected from Hunner and non-Hunner lesions in the same patient. Normal bladder tissue biopsies were also obtained as controls. Whole transcriptome analysis was performed to analyze the gene expression patterns and immune cell populations.

RESULTS

The mucosal layers of patients exhibited similar pathway dysregulation across Hunner and non-Hunner lesions, with immunerelated pathways being prominently affected. In the mucosal layer, genes related to anti-inflammatory and immune suppression were downregulated in Hunner lesions compared to non-Hunner lesions. Moreover, in Hunner lesions, genes related to macrophage differentiation and polarization, such as VSIG4, CD68, MAFB, and LIRB4, were downregulated. The cell fraction of M2 macrophages was found to decrease in Hunner lesions. Immunohistochemical staining revealed an elevated fraction of M1 macrophages and a reduced fraction of M2 macrophages in Hunner lesions compared to those in non-Hunner lesions. In the muscular layer, transcriptomic evidence of muscle thickness was observed in both Hunner and non-Hunner lesions; however, the difference was not significant.

CONCLUSION

Hunner lesions showed a reduced expression of anti-inflammatory and immunosuppressive factors compared to non-Hunner lesions, along with alterations in immune cell populations. This study suggests the possibility that macrophage polarization is related to the progression from non-Hunner lesions to Hunner lesions, suggesting its relevance to the characteristics of autoimmune diseases.

Effects of poly (ADP-ribose) polymerase inhibitor treatment on the repair process of ischemic acute kidney injury

Excessive activation of poly (ADP-ribose) polymerase (PARP) contributes to ischemic acute kidney injury (AKI). PARP inhibition has been shown to be beneficial in renal ischemia-reperfusion injury (IRI) in the early phase, but its role in the repair process remains unclear. The effects of JPI-289, a novel PARP inhibitor, during the healing phase after renal IRI were investigated. IRI was performed on 9-week-old male C57BL/6 mice. Saline or JPI-289 100 mg/kg was intraperitoneally administered once at 24 h or additionally at 48 h after IRI. Hypoxic HK-2 cells were treated with JPI-289. Renal function and fibrosis extent were comparable between groups. JPI-289 treatment caused more prominent tubular atrophy and proinflammatory intrarenal leukocyte phenotypes and cytokines/chemokines changes at 12 weeks after unilateral IRI. JPI-289 treatment enhanced gene expressions associated with collagen formation, toll-like receptors, and the immune system in proximal tubules and endothelial cells after IRI. JPI-289 treatment at 3 or 6 h after hypoxia facilitated proliferation of hypoxic HK-2 cells, whereas further treatment after 24 h suppressed proliferation. Delayed inhibition of PARP after renal IRI did not facilitate the repair process during the early healing phase but rather may aggravate renal tubular atrophy during the late healing phase in ischemic AKI.

Short-term effects of ambient temperature on acute exacerbation of inflammatory bowel disease: A nationwide case-crossover study with external validation

Inflammatory bowel disease (IBD) is an idiopathic inflammatory disorder characterized by chronic and relapsing manifestations. Several environmental factors are known as triggers for exacerbation of IBD. However, an association between exacerbation of IBD and ambient temperature is uncertain. This study aimed to estimate the risk of acute exacerbation of IBD due to ambient temperature. We performed a bidirectional case-crossover study using a nationwide claim data from South Korea. The external validation was conducted with a large prospective cohort in the United Kingdom. We confirmed significant associations between acute exacerbation of IBD and the short-term ambient temperature changes toward severe temperatures, in the cold weather (-19.4°C-4.3°C) (odd ratio [OR] = 1.13, 95% confidence interval [CI]: 1.13-1.14) and in the hot weather (21.3°C-33.5°C) (OR = 1.16, 95% CI: 1.15-1.17). However, the association was not significant in the moderate weather (4.3°C-21.3°C). The external validation suggested consistent results with additional elevation of acute exacerbation risk in the colder weather (-13.4°C to 2.6°C) (OR = 1.90, 95% CI: 1.62-2.22) and in the hotter weather (15.7°C-28.4°C) (OR = 1.41, 95% CI: 1.32-1.51). We observed and validated that the short-term ambient temperature changes were associated with acute exacerbation of IBD in the cold and hot weathers. Our findings provide evidence that temperature changes are associated with the acute exacerbation of IBD.

Single cell dynamics of tumor specificity vs bystander activity in CD8+ T cells define the diverse immune landscapes in colorectal cancer

CD8+ T cell activation via immune checkpoint blockade (ICB) is successful in microsatellite instable (MSI) colorectal cancer (CRC) patients. By comparison, the success of immunotherapy against microsatellite stable (MSS) CRC is limited. Little is known about the most critical features of CRC CD8+ T cells that together determine the diverse immune landscapes and contrasting ICB responses. Hence, we pursued a deep single cell mapping of CRC CD8+ T cells on transcriptomic and T cell receptor (TCR) repertoire levels in a diverse patient cohort, with additional surface proteome validation. This revealed that CRC CD8+ T cell dynamics are underscored by complex interactions between interferon-γ signaling, tumor reactivity, TCR repertoire, (predicted) TCR antigen-specificities, and environmental cues like gut microbiome or colon tissue-specific 'self-like' features. MSI CRC CD8+ T cells showed tumor-specific activation reminiscent of canonical 'T cell hot' tumors, whereas the MSS CRC CD8+ T cells exhibited tumor unspecific or bystander-like features. This was accompanied by inflammation reminiscent of 'pseudo-T cell hot' tumors. Consequently, MSI and MSS CRC CD8+ T cells showed overlapping phenotypic features that differed dramatically in their TCR antigen-specificities. Given their high discriminating potential for CD8+ T cell features/specificities, we used the single cell tumor-reactive signaling modules in CD8+ T cells to build a bulk tumor transcriptome classification for CRC patients. This "Immune Subtype Classification" (ISC) successfully distinguished various tumoral immune landscapes that showed prognostic value and predicted immunotherapy responses in CRC patients. Thus, we deliver a unique map of CRC CD8+ T cells that drives a novel tumor immune landscape classification, with relevance for immunotherapy decision-making.

Single-cell mapping of combinatorial target antigens for CAR switches using logic gates

Identification of optimal target antigens that distinguish cancer cells from normal surrounding tissue cells remains a key challenge in chimeric antigen receptor (CAR) cell therapy for tumors with intratumoral heterogeneity. In this study, we dissected tissue complexity to the level of individual cells through the construction of a single-cell expression atlas that integrates ~1.4 million tumor, tumor-infiltrating normal and reference normal cells from 412 tumors and 12 normal organs. We used a two-step screening method using random forest and convolutional neural networks to select gene pairs that contribute most to discrimination between individual malignant and normal cells. Tumor coverage and specificity are evaluated for the AND, OR and NOT logic gates based on the combinatorial expression pattern of the pairing genes across individual single cells. Single-cell transcriptome-coupled epitope profiling validates the AND, OR and NOT switch targets identified in ovarian cancer and colorectal cancer.

Comparative analysis of batch correction methods for FDG PET/CT using metabolic radiogenomic data of lung cancer patients

In radiomics research, the issue of different instruments being used is significant. In this study, we compared three correction methods to reduce the batch effects in radiogenomic data from fluorodeoxyglucose (FDG) PET/CT images of lung cancer patients. Texture features of the FDG PET/CT images and genomic data were retrospectively obtained. The features were corrected with different methods: phantom correction, ComBat method, and Limma method. Batch effects were estimated using three analytic tools: principal component analysis (PCA), the k-nearest neighbor batch effect test (kBET), and the silhouette score. Finally, the associations of features and gene mutations were compared between each correction method. Although the kBET rejection rate and silhouette score were lower in the phantom-corrected data than in the uncorrected data, a PCA plot showed a similar variance. ComBat and Limma methods provided correction with low batch effects, and there was no significant difference in the results of the two methods. In ComBat- and Limma-corrected data, more texture features exhibited a significant association with the TP53 mutation than in those in the phantom-corrected data. This study suggests that correction with ComBat or Limma methods can be more effective or equally as effective as the phantom method in reducing batch effects.

Pan-cancer analysis reveals multifaceted roles of retrotransposon-fusion RNAs

Transposon-derived transcripts are abundant in RNA sequences, yet their landscape and function, especially for fusion transcripts derived from unannotated or somatically acquired transposons, remains underexplored. Here, we developed a new bioinformatic tool to detect transposon-fusion transcripts in RNA-sequencing data and performed a pan-cancer analysis of 10,257 cancer samples across 34 cancer types as well as 3,088 normal tissue samples. We identified 52,277 cancer-specific fusions with ~30 events per cancer and hotspot loci within transposons vulnerable to fusion formation. Exonization of intronic transposons was the most prevalent genic fusions, while somatic L1 insertions constituted a small fraction of cancer-specific fusions. Source L1s and HERVs, but not Alus showed decreased DNA methylation in cancer upon fusion formation. Overall cancer-specific L1 fusions were enriched in tumor suppressors while Alu fusions were enriched in oncogenes, including recurrent Alu fusions in EZH2 predictive of patient survival. We also demonstrated that transposon-derived peptides triggered CD8+ T-cell activation to the extent comparable to EBV viruses. Our findings reveal distinct epigenetic and tumorigenic mechanisms underlying transposon fusions across different families and highlight transposons as novel therapeutic targets and the source of potent neoantigens.

Whole exome sequencing and clinical investigation of young onset dystonia: What can we learn?

BACKGROUND

Dystonia is a heterogeneous movement disorder involving various genetic backgrounds, and the implication of whole exome sequencing (WES) has yet to be clearly elucidated. In this study, we performed WES in Korean patients with young-onset dystonia.

METHODS

We recruited patients with young-onset dystonia based on the new MDS dystonia classification at Samsung Medical Centre from 2015 to 2019. We excluded subjects diagnosed by single gene tests (GCH1, TOR1A, PANK2, PRRT2, and SGCE) or levodopa trials and subjects with focal or possible secondary dystonia. We performed WES in all enrolled subjects and confirmed the results with Sanger sequencing.

RESULTS

Of the 43 patients, we detected 11 disease-causing variants, classified as either pathogenic or likely pathogenic, in 9 patients (20.9%). Generalized dystonia, infancy-childhood-onset dystonia, and other combined neurologic manifestations were related with PV/LPV. When we retrospectively reviewed the patients with PV/LPV, brain imaging was diagnostic in 3 subjects (HTRA1, SCL20A, and WDR45), clinical characteristics of paroxysmal presentation were observed in 2 (ADCY5 and ATP1A3), and microcephaly was noted in 1 patient (KMT2B).

CONCLUSION

Clinical exome sequencing is helpful for the diagnosis of dystonia, especially for that with infancy-childhood onset, and generalized dystonia with other neurologic manifestations. Additionally, careful evaluations and examinations could provide information for selecting candidates for genetic testing.

Definitive Radiotherapy in Patients with Clinical T1N0M0 Esophageal Squamous Cell Carcinoma: A Multicenter Retrospective Study

PURPOSE/OBJECTIVE(S)

In this study, we aimed to assess the failure pattern and survival outcomes and to analyze the optimal treatment field of definitive RT for T1N0M0 esophageal squamous cell carcinoma (ESCC).

MATERIALS/METHODS

We performed a retrospective analysis in a multi-institutional cohort of patients with histologically confirmed T1N0M0 ESCC. We included patients who underwent RT with definitive aim from 2010 to 2019. Patterns of failure were demonstrated as in-field locoregional, out-field locoregional and distant metastasis. In the survival analysis, freedom from locoregional recurrence and their association with clinicopathologic risk factors were analyzed. We performed a propensity score matching in the cT1b patients to adjust for the heterogeneity of radiation technique, radiation dose and the use of concurrent chemotherapy.

RESULTS

A total of 168 patients were included with a median follow-up of 34.0 months, and there were 20 cT1a, 94 cT1b and 24 cT1x, (cT1, not otherwise specified) patients. The rates of all and locoregional failure were 26.9% and 23.1% for cT1a and 25.0% and 22.4% for cT1b patients. 10 (10.6%) patients experienced grade ≥ 3 adverse events. Among 116 cT1b patients, 69 patients received elective nodal irradiation (ENI) and 47 patients received involved field irradiation (IFI). After propensity score matching, the 3-year FFLRR rate was 84.5% (95% Confidence Interval, 71.0 - 92.1%). There was no significant difference between the ENI and IFI patients in FFLRR (Log-rank P = 0.831). In the multivariate analysis, the use of concurrent chemotherapy was the only factor marginally associated with FFLRR (Hazard ratio, 0.17; 95% CI, 0.02 - 1.13; P = 0.067).

CONCLUSION

cT1a patients who cannot receive endoscopic resection, showed similar rates of failure compared with cT1b patients, which questioned the accuracy of the staging and raised the need for through treatment such as chemoradiotherapy. In cT1b patients, IFI using dose of 50 to 60 Gy with concurrent chemotherapy could be a reasonable treatment option.

Defining a TCF1-expressing progenitor allogeneic CD8+ T cell subset in acute graft-versus-host disease

Graft-versus-host disease (GvHD) is a severe complication of hematopoietic stem cell transplantation driven by activated allogeneic T cells. Here, we identify a distinct subset of T cell factor-1 (TCF1)+ CD8+ T cells in mouse allogeneic and xenogeneic transplant models of acute GvHD. These TCF1+ cells exhibit distinct characteristics compared to TCF1- cells, including lower expression of inhibitory receptors and higher expression of costimulatory molecules. Notably, the TCF1+ subset displays exclusive proliferative potential and could differentiate into TCF1- effector cells upon antigenic stimulation. Pathway analyses support the role of TCF1+ and TCF1- subsets as resource cells and effector cells, respectively. Furthermore, the TCF1+ CD8+ T cell subset is primarily present in the spleen and exhibits a resident phenotype. These findings provide insight into the differentiation of allogeneic and xenogeneic CD8+ T cells and have implications for the development of immunotherapeutic strategies targeting acute GvHD.

Single-nucleotide variant calling in single-cell sequencing data with Monopogen

Single-cell omics technologies enable molecular characterization of diverse cell types and states, but how the resulting transcriptional and epigenetic profiles depend on the cell's genetic background remains understudied. We describe Monopogen, a computational tool to detect single-nucleotide variants (SNVs) from single-cell sequencing data. Monopogen leverages linkage disequilibrium from external reference panels to identify germline SNVs and detects putative somatic SNVs using allele cosegregating patterns at the cell population level. It can identify 100 K to 3 M germline SNVs achieving a genotyping accuracy of 95%, together with hundreds of putative somatic SNVs. Monopogen-derived genotypes enable global and local ancestry inference and identification of admixed samples. It identifies variants associated with cardiomyocyte metabolic levels and epigenomic programs. It also improves putative somatic SNV detection that enables clonal lineage tracing in primary human clonal hematopoiesis. Monopogen brings together population genetics, cell lineage tracing and single-cell omics to uncover genetic determinants of cellular processes.

Longitudinal multi-omics study of palbociclib resistance in HR-positive/HER2-negative metastatic breast cancer

BACKGROUND

Cyclin-dependent kinase 4/6 inhibitor (CDK4/6) therapy plus endocrine therapy (ET) is an effective treatment for patients with hormone receptor-positive/human epidermal receptor 2-negative metastatic breast cancer (HR+/HER2- MBC); however, resistance is common and poorly understood. A comprehensive genomic and transcriptomic analysis of pretreatment and post-treatment tumors from patients receiving palbociclib plus ET was performed to delineate molecular mechanisms of drug resistance.

METHODS

Tissue was collected from 89 patients with HR+/HER2- MBC, including those with recurrent and/or metastatic disease, receiving palbociclib plus an aromatase inhibitor or fulvestrant at Samsung Medical Center and Seoul National University Hospital from 2017 to 2020. Tumor biopsy and blood samples obtained at pretreatment, on-treatment (6 weeks and/or 12 weeks), and post-progression underwent RNA sequencing and whole-exome sequencing. Cox regression analysis was performed to identify the clinical and genomic variables associated with progression-free survival.

RESULTS

Novel markers associated with poor prognosis, including genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four prognostic clusters with distinct molecular features were identified. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly to palbociclib plus ET. Comparisons of paired pre- and post-treatment samples revealed that tumors became enriched in APOBEC mutation signatures, and many switched to aggressive molecular subtypes with estrogen-independent characteristics. We identified frequent genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C.

CONCLUSIONS

We identified novel molecular features associated with poor prognosis and molecular mechanisms that could be targeted to overcome resistance to CKD4/6 plus ET.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03401359. The trial was posted on 18 January 2018 and registered prospectively.

Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders

Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.

Symmetry Breaking of Human Pluripotent Stem Cells (hPSCs) in Micropattern Generates a Polarized Spinal Cord-Like Organoid (pSCO) with Dorsoventral Organization

Axis formation and related spatial patterning are initiated by symmetry breaking during development. A geometrically confined culture of human pluripotent stem cells (hPSCs) mimics symmetry breaking and cell patterning. Using this, polarized spinal cord organoids (pSCOs) with a self-organized dorsoventral (DV) organization are generated. The application of caudalization signals promoted regionalized cell differentiation along the radial axis and protrusion morphogenesis in confined hPSC colonies. These detached colonies grew into extended spinal cord-like organoids, which established self-ordered DV patterning along the long axis through the spontaneous expression of polarized DV patterning morphogens. The proportions of dorsal/ventral domains in the pSCOs can be controlled by the changes in the initial size of micropatterns, which altered the ratio of center-edge cells in 2D. In mature pSCOs, highly synchronized neural activity is separately detected in the dorsal and ventral side, indicating functional as well as structural patterning established in the organoids. This study provides a simple and precisely controllable method to generate spatially ordered organoids for the understanding of the biological principles of cell patterning and axis formation during neural development.

Genetic network structure of 13 psychiatric disorders in the general population

Psychiatric disorders frequently co-occur and share common symptoms and genetic backgrounds. Previous research has used genome-wide association studies to identify the interrelationships among psychiatric disorders and identify clusters of disorders; however, these methods have limitations in terms of their ability to examine the relationships among disorders as a network structure and their generalizability to the general population. In this study, we explored the network structure of the polygenic risk score (PRS) for 13 psychiatric disorders in a general population (276,249 participants of European ancestry from the UK Biobank) and identified communities and the centrality of the network. In this network, the nodes represented a PRS for each psychiatric disorder and the edges represented the connections between nodes. The psychiatric disorders comprised four robust communities. The first community included attention-deficit hyperactivity disorder, autism spectrum disorder, major depressive disorder, and anxiety disorder. The second community consisted of bipolar I and II disorders, schizophrenia, and anorexia nervosa. The third group included Tourette's syndrome and obsessive-compulsive disorder. Cannabis use disorder, alcohol use disorder, and post-traumatic stress disorder make up the fourth community. The PRS of schizophrenia had the highest values for the three metrics (strength, betweenness, and closeness) in the network. Our findings provide a comprehensive genetic network of psychiatric disorders and biological evidence for the classification of psychiatric disorders.

ICD2Vec: Mathematical representation of diseases

BACKGROUND

The International Classification of Diseases (ICD) codes represent the global standard for reporting disease conditions. The current ICD codes connote direct human-defined relationships among diseases in a hierarchical tree structure. Representing the ICD codes as mathematical vectors helps to capture nonlinear relationships in medical ontologies across diseases.

METHODS

We propose a universally applicable framework called "ICD2Vec" designed to provide mathematical representations of diseases by encoding corresponding information. First, we present the arithmetical and semantic relationships between diseases by mapping composite vectors for symptoms or diseases to the most similar ICD codes. Second, we investigated the validity of ICD2Vec by comparing the biological relationships and cosine similarities among the vectorized ICD codes. Third, we propose a new risk score called IRIS, derived from ICD2Vec, and demonstrate its clinical utility with large cohorts from the UK and South Korea.

RESULTS

Semantic compositionality was qualitatively confirmed between descriptions of symptoms and ICD2Vec. For example, the most diseases most similar to COVID-19 were found to be the common cold (ICD-10: J00), unspecified viral hemorrhagic fever (ICD-10: A99), and smallpox (ICD-10: B03). We show the significant associations between the cosine similarities derived from ICD2Vec and the biological relationships using disease-to-disease pairs. Furthermore, we observed significant adjusted hazard ratios (HR) and area under the receiver operating characteristics (AUROC) between IRIS and risks for eight diseases. For instance, the higher IRIS for coronary artery disease (CAD) can be the higher probability for the incidence of CAD (HR: 2.15 [95% CI 2.02-2.28] and AUROC: 0.587 [95% CI 0.583-0.591]). We identified individuals at substantially increased risk of CAD using IRIS and 10-year atherosclerotic cardiovascular disease risk (adjusted HR, 4.26, 95% CI, 3.59-5.05).

CONCLUSIONS

ICD2Vec, a proposed universal framework for converting qualitatively measured ICD codes into quantitative vectors containing semantic relationships between diseases, exhibited a significant correlation with actual biological significance. In addition, the IRIS was a significant predictor of major diseases in a prospective study using two large-scale Biobank EHR datasets. Based on this clinical validity and utility evidence, we suggest that publicly available ICD2Vec can be used in diverse research and clinical practices and has important clinical implications.

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

BACKGROUND

Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application.

METHODS

We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy.

RESULTS

In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e-4 for progression-free survival (PFS) and 3.63e-4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher's exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e-4 for PFS and 3.66e-4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient using in vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage ( http://www.wang-lab-hkust.com:3838/TMZEP ).

CONCLUSIONS

We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs.

Clonal expansion of resident memory T cells in peripheral blood of patients with non-small cell lung cancer during immune checkpoint inhibitor treatment

BACKGROUND

Immune checkpoint inhibitors (ICIs) are an essential treatment for non-small cell lung cancer (NSCLC). Currently, the tumor-related intrinsic factors in response to ICIs have mostly been elucidated in tissue samples. However, tissue immune status and changes in the immune microenvironment can also be reflected and monitored through peripheral blood.

METHODS

Single-cell RNA and T cell receptor (scTCR) sequencing were conducted using peripheral blood mononuclear cells (PBMCs) from 60 patients with stage IV NSCLC. Those samples were prospectively acquired from patients treated with anti-PD(L)-1 therapy for advanced lung cancer. Based on the clinical outcomes, samples were classified as durable clinical benefit (DCB) and non-durable clinical benefit (NCB). The samples constituted paired longitudinal samples, consisting of pre-treatment and on-treatment. Additionally, PBMC samples from 60 healthy donors from the Asian Immune Diversity Atlas project were used as a control.

RESULTS

The dynamic changes in major cell types between pre-treatment and on-treatment PBMCs were associated with an increase in proliferating T cells and NK cells in both DCB and NCB groups. Among T cell subtypes, effector memory CD8⁺ T cells (CD8⁺ T_EM_GZMK_PDCD1) were increased after ICI treatment in both DCB and NCB. From the lineage trajectory analysis, effector memory CD8⁺ T cells resided at the bifurcation point, which has the potential to differentiate into lineages with precursor exhausted CD8⁺ T cells (CD8⁺ T_CM cells) assumed to be related to the ICI response. From the scTCR-seq, effector memory CD8⁺ T cells along with T cells recognizing unknown antigen expanded and composed of novel clones skewed toward dysfunctional status, especially in on-treatment samples of the DCB group. The extent of immunophenotype conversion capabilities of the TCR with effector memory CD8⁺ T cells showed remarkable variation in the on-treatment sample in the DCB group.

CONCLUSION

A transitioning T cell subtype identified in PBMCs might be related to the prolonged ICI response. From our study, expansion of effector memory CD8⁺ T cells with novel TCRs in PBMCs after ICI treatment could contribute to a better clinical outcome in patients with NSCLC. This proof-of-concept research strengthens the use of non-invasive PBMCs in studying systemic changes of immune reactions related to the ICI treatment.

Single Cell Analysis of Human Thyroid Reveals the Transcriptional Signatures of Aging

The thyroid gland plays a critical role in the maintenance of whole-body metabolism. However, aging frequently impairs homeostatic maintenance by thyroid hormones due to increased prevalence of subclinical hypothyroidism associated with mitochondrial dysfunction, inflammation, and fibrosis. To understand the specific aging-related changes of endocrine function in thyroid epithelial cells, we performed single-cell RNA sequencing (RNA-seq) of 54 726 cells derived from pathologically normal thyroid tissues from 7 patients who underwent thyroidectomy. Thyroid endocrine epithelial cells were clustered into 5 distinct subpopulations, and a subset of cells was found to be particularly vulnerable with aging, showing functional deterioration associated with the expression of metallothionein (MT) and major histocompatibility complex class II genes. We further validated that increased expression of MT family genes are highly correlated with thyroid gland aging in bulk RNAseq datasets. This study provides evidence that aging induces specific transcriptomic changes across multiple cell populations in the human thyroid gland.

G-RANK: an equivariant graph neural network for the scoring of protein-protein docking models

Motivation

Protein complex structure prediction is important for many applications in bioengineering. A widely used method for predicting the structure of protein complexes is computational docking. Although many tools for scoring protein-protein docking models have been developed, it is still a challenge to accurately identify near-native models for unknown protein complexes. A recently proposed model called the geometric vector perceptron-graph neural network (GVP-GNN), a subtype of equivariant graph neural networks, has demonstrated success in various 3D molecular structure modeling tasks.

Results

Herein, we present G-RANK, a GVP-GNN-based method for the scoring of protein-protein docking models. When evaluated on two different test datasets, G-RANK achieved a performance competitive with or better than the state-of-the-art scoring functions. We expect G-RANK to be a useful tool for various applications in biological engineering.

Availability and implementation

Source code is available at https://github.com/ha01994/grank.

Contact

kds@kaist.ac.kr.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Multimodal deep learning of fundus abnormalities and traditional risk factors for cardiovascular risk prediction

Cardiovascular disease (CVD), the leading cause of death globally, is associated with complicated underlying risk factors. We develop an artificial intelligence model to identify CVD using multimodal data, including clinical risk factors and fundus photographs from the Samsung Medical Center (SMC) for development and internal validation and from the UK Biobank for external validation. The multimodal model achieves an area under the receiver operating characteristic curve (AUROC) of 0.781 (95% confidence interval [CI] 0.766-0.798) in the SMC and 0.872 (95% CI 0.857-0.886) in the UK Biobank. We further observe a significant association between the incidence of CVD and the predicted risk from at-risk patients in the UK Biobank (hazard ratio [HR] 6.28, 95% CI 4.72-8.34). We visualize the importance of individual features in photography and traditional risk factors. The results highlight that non-invasive fundus photography can be a possible predictive marker for CVD.

Framework for Adoption of Next-Generation Sequencing (NGS) Globally in the Oncology Area

Radical new possibilities of improved treatment of cancer are on offer from an advanced medical technology already demonstrating its significance: next-generation sequencing (NGS). This refined testing provides unprecedentedly precise diagnoses and permits the use of focused and highly personalized treatments. However, across regions globally, many cancer patients will continue to be denied the benefits of NGS as long as some of the yawning gaps in its implementation remain unattended. The challenges at the regional and national levels are linked because putting the solutions into effect is highly dependent on cooperation between regional- and national-level cooperation, which could be hindered by shortfalls in interpretation or understanding. The aim of the paper was to define and explore the necessary conditions for NGS and make recommendations for effective implementation based on extensive exchanges with policy makers and stakeholders. As a result, the European Alliance for Personalised Medicine (EAPM) developed a maturity framework structured around demand-side and supply-side issues to enable interested stakeholders in different countries to self-evaluate according to a common matrix. A questionnaire was designed to identify the current status of NGS implementation, and it was submitted to different experts in different institutions globally. This revealed significant variability in the different aspects of NGS uptake. Within different regions globally, to ensure those conditions are right, this can be improved by linking efforts made at the national level, where patients have needs and where care is delivered, and at the global level, where major policy initiatives in the health field are underway or in preparation, many of which offer direct or indirect pathways for building those conditions. In addition, in a period when consensus is still incomplete and catching up is needed at a political level to ensure rational allocation of resources-even within individual countries-to enable the best ways to make the necessary provisions for NGS, a key recommendation is to examine where closer links between national and regional actions could complement, support, and mutually reinforce efforts to improve the situation for patients.

Discovering comorbid diseases using an inter-disease interactivity network based on biobank-scale PheWAS data

MOTIVATION

Understanding comorbidity is essential for disease prevention, treatment and prognosis. In particular, insight into which pairs of diseases are likely or unlikely to co-occur may help elucidate the potential relationships between complex diseases. Here, we introduce the use of an inter-disease interactivity network to discover/prioritize comorbidities. Specifically, we determine disease associations by accounting for the direction of effects of genetic components shared between diseases, and categorize those associations as synergistic or antagonistic. We further develop a comorbidity scoring algorithm to predict whether diseases are more or less likely to co-occur in the presence of a given index disease. This algorithm can handle networks that incorporate relationships with opposite signs.

RESULTS

We finally investigate inter-disease associations among 427 phenotypes in UK Biobank PheWAS data and predict the priority of comorbid diseases. The predicted comorbidities were verified using the UK Biobank inpatient electronic health records. Our findings demonstrate that considering the interaction of phenotype associations might be helpful in better predicting comorbidity.

AVAILABILITY AND IMPLEMENTATION

The source code and data of this study are available at https://github.com/dokyoonkimlab/DiseaseInteractiveNetwork.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Elevated IFNA1 and suppressed IL12p40 associated with persistent hyperinflammation in COVID-19 pneumonia

Introduction

Despite of massive endeavors to characterize inflammation in COVID-19 patients, the core network of inflammatory mediators responsible for severe pneumonia stillremain remains elusive.

Methods

Here, we performed quantitative and kinetic analysis of 191 inflammatory factors in 955 plasma samples from 80 normal controls (sample n = 80) and 347 confirmed COVID-19 pneumonia patients (sample n = 875), including 8 deceased patients.

Results

Differential expression analysis showed that 76% of plasmaproteins (145 factors) were upregulated in severe COVID-19 patients comparedwith moderate patients, confirming overt inflammatory responses in severe COVID-19 pneumonia patients. Global correlation analysis of the plasma factorsrevealed two core inflammatory modules, core I and II, comprising mainly myeloid cell and lymphoid cell compartments, respectively, with enhanced impact in a severity-dependent manner. We observed elevated IFNA1 and suppressed IL12p40, presenting a robust inverse correlation in severe patients, which was strongly associated with persistent hyperinflammation in 8.3% of moderate pneumonia patients and 59.4% of severe patients.

Discussion

Aberrant persistence of pulmonary and systemic inflammation might be associated with long COVID-19 sequelae. Our comprehensive analysis of inflammatory mediators in plasmarevealed the complexity of pneumonic inflammation in COVID-19 patients anddefined critical modules responsible for severe pneumonic progression.

Circulating Tumor DNA-Based Genotyping and Monitoring for Predicting Disease Relapses of Patients with Peripheral T-Cell Lymphomas

PURPOSE

Plasma circulating tumor DNA (ctDNA) could reflect the genetic alterations present in tumor tissues. However, there is little information about the clinical relevance of cell-free DNA genotyping in peripheral T-cell lymphoma (PTCL).

MATERIALS AND METHODS

After targeted sequencing plasma cell-free DNA of patients with various subtypes of PTCL (n=94), we analyzed the mutation profiles of plasma ctDNA samples and their predictive value of dynamic ctDNA monitoring for treatment outcomes.

RESULTS

Plasma ctDNA mutations were detected in 53 patients (56%, 53/94), and the detection rate of somatic mutations was highest in angioimmunoblastic T-cell lymphoma (24/31, 77%) and PTCL, not otherwise specified (18/29, 62.1%). Somatic mutations were detected in 51 of 66 genes that were sequenced, including the following top 10 ranked genes: RHOA, CREBBP, KMT2D, TP53, IDH2, ALK, MEF2B, SOCS1, CARD11, and KRAS. In the longitudinal assessment of ctDNA mutation, the difference in ctDNA mutation volume after treatment showed a significant correlation with disease relapse or progression. Thus, a ≥ 1.5-log decrease in genome equivalent (GE) between baseline and the end of treatment showed a significant association with better survival outcomes than a < 1.5-log decrease in GE.

CONCLUSION

Our results suggest the clinical relevance of plasma ctDNA analysis in patients with PTCL. However, our findings should be validated by a subsequent study with a larger study population and using a broader gene panel.

Empowering quality data - the gordian knot of bringing real innovation into healthcare system

OBJECTIVES

The introduction of Personalised Medicine (PM) into healthcare systems could benefit from a clearer understanding of the distinct national and regional frameworks around the world. Recent engagement by international regulators on maximising the use of real-world evidence (RWE) has highlighted the scope for improving the exploitation of the treasure-trove of health data that is currently largely neglected in many countries. The European Alliance for Personalised Medicine (EAPM) led an international study aimed at identifying the current status of conditions.

METHODS

A literature review examined how far such frameworks exist, with a view to identifying conducive factors - and crucial gaps. This extensive review of key factors across 22 countries and 5 regions revealed a wide variety of attitudes, approaches, provisions and conditions, and permitted the construction of a comprehensive overview of the current status of PM. Based on seven key pillars identified from the literature review and expert panels, the data was quantified, and on the basis of further analysis, an index was developed to allow comparison country by country and region by region.

RESULTS

The results show that United States of America is leading according to overall outcome whereas Kenya scored the least in the overall outcome.

CONCLUSIONS

Still, common approaches exist that could help accelerate take-up of opportunities even in the less prosperous parts of the world.

Comparison of cell type distribution between single-cell and single-nucleus RNA sequencing: enrichment of adherent cell types in single-nucleus RNA sequencing

Single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) is an effective technique for estimating the cellular composition and transcriptional profiles of individual cells from fresh tissue. Single-nucleus RNA sequencing (snRNA-seq) is necessary to perform this type of analysis in frozen or difficult-to-dissociate tissues, which cannot be subjected to scRNA-seq. This difference in the state of tissues leads to variation in cell-type distributions among each platform. To identify the characteristics of these methods and their differences, scRNA-seq and snRNA-seq were performed in parallel for colon and liver tissues. The two platforms revealed similar diversity but different proportions of cell types in matched tissues. The proportions of epithelial cells in the colon and hepatocytes in the liver were relatively high in snRNA-seq and that of immune cells was relatively high in scRNA-seq. This difference could be explained by variations in the expression scores of adhesion genes due to the disruption of the cytoplasmic contents during scRNA-seq. The enrichment of epithelial cells in the colon resulted in a discrepancy in the differentiation of epithelial cells. This enrichment was also well matched with the images of hematoxylin and eosin staining and the estimated distribution of cell types in bulk RNA sequencing. These results showed that snRNA-seq could be used to analyze tissues that cannot be subjected to scRNA-seq and provides more information in specific cell type analysis.

A database of 5305 healthy Korean individuals reveals genetic and clinical implications for an East Asian population

Despite substantial advances in disease genetics, studies to date have largely focused on individuals of European descent. This limits further discoveries of novel functional genetic variants in other ethnic groups. To alleviate the paucity of East Asian population genome resources, we established the Korean Variant Archive 2 (KOVA 2), which is composed of 1896 whole-genome sequences and 3409 whole-exome sequences from healthy individuals of Korean ethnicity. This is the largest genome database from the ethnic Korean population to date, surpassing the 1909 Korean individuals deposited in gnomAD. The variants in KOVA 2 displayed all the known genetic features of those from previous genome databases, and we compiled data from Korean-specific runs of homozygosity, positively selected intervals, and structural variants. In doing so, we found loci, such as the loci of ADH1A/1B and UHRF1BP1, that are strongly selected in the Korean population relative to other East Asian populations. Our analysis of allele ages revealed a correlation between variant functionality and evolutionary age. The data can be browsed and downloaded from a public website ( https://www.kobic.re.kr/kova/ ). We anticipate that KOVA 2 will serve as a valuable resource for genetic studies involving East Asian populations.

Fighting Cancer around the World: A Framework for Action

Tackling cancer is a major challenge right on the global level. Europe is only the tip of an iceberg of cancer around the world. Prosperous developed countries share the same problems besetting Europe-and the countries and regions with fewer resources and less propitious conditions are in many cases struggling often heroically against a growing tide of disease. This paper offers a view on these geographically wider, but essentially similar, challenges, and on the prospects for and barriers to better results in this ceaseless battle. A series of panels have been organized by the European Alliance for Personalised Medicine (EAPM) to identify different aspects of cancer care around the globe. There is significant diversity in key issues such as NGS, RWE, molecular diagnostics, and reimbursement in different regions. In all, it leads to disparities in access and diagnostics, patients' engagement, and efforts for a better understanding of cancer.

A Phase II Study of Nivolumab plus Gemcitabine in Patients with Recurrent or Metastatic Nasopharyngeal Carcinoma (KCSG HN17-11)

PURPOSE

Although programmed death 1/programmed death ligand 1 (PD-1/PD-L1) inhibitors are promising agents for recurrent or metastatic nasopharyngeal carcinoma (NPC), PD-1/PD-L1 inhibitor monotherapy has shown modest efficacy. This study evaluated the efficacy and safety of nivolumab plus gemcitabine in patients with NPC who failed prior platinum-based chemotherapy.

PATIENTS AND METHODS

This is a phase II, multicenter, open-label, single-arm study. Patients with recurrent or metastatic NPC received nivolumab 3 mg/kg and gemcitabine 1,250 mg/m2 every 2 weeks until disease progression or intolerable toxicity. The primary endpoint was progression-free survival (PFS). The secondary endpoints included objective response rate (ORR), overall survival (OS), and safety. To identify potential biomarkers, whole-exome sequencing, whole-transcriptome sequencing, and immune phenotype analysis based on Lunit SCOPE IO, an artificial intelligence-powered spatial tumor-infiltrating lymphocyte analyzer, were performed.

RESULTS

Thirty-six patients were enrolled between June 2018 and June 2019. The ORR was 36.1% and disease control rate was 97.2%. With median follow-up of 22.0 months, median PFS was 13.8 months [95% confidence interval (CI), 8.6-16.8 months]. Median OS was not reached, and OS rate at 6 months was 97.0% (95% CI, 80.4%-99.6%). The grade ≥3 treatment-related adverse events were hypertension (2.8%) and anemia (2.8%). In multivariate analysis of mutation of chromatin modifier gene, tumor mutational burden (≥ 2.1 mut/Mb), and somatic copy-number alteration (SCNA) level, the group with high SCNA (> 3 points; HR, 7.0; 95% CI, 1.3-37.9; P = 0.02) had independently associated with poor PFS. Immune phenotype analysis showed that tumors with high proportion of immune-excluded immune phenotype was significantly correlated with poor PFS (HR, 4.4; 95% CI, 1.2-16.2; P = 0.018).

CONCLUSIONS

Nivolumab plus gemcitabine showed promising efficacy with favorable toxicity profiles in patients with advanced NPC in whom platinum-based combination chemotherapy failed.

Clinical, Pathologic, and Molecular Prognostic Factors in Patients with Early-Stage EGFR-Mutant NSCLC

PURPOSE

In early-stage, EGFR mutation-positive (EGFR-M+) non-small cell lung cancer (NSCLC), surgery remains the primary treatment, without personalized adjuvant treatments. We aimed to identify risk factors for recurrence-free survival (RFS) to suggest personalized adjuvant strategies in resected early-stage EGFR-M+ NSCLC.

EXPERIMENTAL DESIGN

From January 2008 to August 2020, a total of 2,340 patients with pathologic stage (pStage) IB-IIIA, non-squamous NSCLC underwent curative surgery. To identify clinicopathologic risk factors, 1,181 patients with pStage IB-IIIA, common EGFR-M+ NSCLC who underwent surgical resection were analyzed. To identify molecular risk factors, comprehensive genomic analysis was conducted in 56 patients with matched case-controls (pStage II and IIIA and type of EGFR mutation).

RESULTS

Median follow-up duration was 38.8 months (0.5-156.2). Among 1,181 patients, pStage IB, II, and IIIA comprised 577 (48.9%), 331 (28.0%), and 273 (23.1%) subjects, respectively. Median RFS was 73.5 months [95% confidence interval (CI), 62.1-84.9], 48.7 months (95% CI, 41.2-56.3), and 22.7 months (95% CI, 19.4-26.0) for pStage IB, II, and IIIA, respectively (P < 0.001). In multivariate analysis of clinicopathologic risk factors, pStage, micropapillary subtype, vascular invasion, and pleural invasion, and pathologic classification by cell of origin (type II pneumocyte-like tumor cell vs. bronchial surface epithelial cell-like tumor cell) were associated with RFS. As molecular risk factors, the non-terminal respiratory unit (non-TRU) of the RNA subtype (HR, 3.49; 95% CI, 1.72-7.09; P < 0.01) and TP53 mutation (HR, 2.50; 95% CI, 1.24-5.04; P = 0.01) were associated with poor RFS independent of pStage II or IIIA. Among the patients with recurrence, progression-free survival of EGFR-tyrosine kinase inhibitor (TKI) in those with the Apolipoprotein B mRNA Editing Catalytic Polypeptide-like (APOBEC) mutation signature was inferior compared with that of patients without this signature (8.6 vs. 28.8 months; HR, 4.16; 95% CI, 1.28-13.46; P = 0.02).

CONCLUSIONS

The low-risk group with TRU subtype and TP53 wild-type without clinicopathologic risk factors might not need adjuvant EGFR-TKIs. In the high-risk group, with non-TRU subtype and/or TP 53 mutation, or clinicopathologic risk factors, a novel adjuvant strategy of EGFR-TKI with others, e.g., chemotherapy or antiangiogenic agents needs to be investigated. Given the poor outcome to EGFR-TKIs after recurrence in patients with the APOBEC mutation signature, an alternative adjuvant strategy might be needed.

Gene Expression Profile Changes in the Stimulated Rat Brain Cortex After Repetitive Transcranial Magnetic Stimulation

Repetitive transcranial magnetic stimulation (rTMS) is gaining popularity as a research tool in neuroscience; however, little is known about its molecular mechanisms of action. The present study aimed to investigate the rTMS-induced transcriptomic changes; we performed microarray messenger RNA, micro RNA, and integrated analyses to explore these molecular events. Eight adult male Sprague-Dawley rats were subjected to a single session of unilateral rTMS at 1 Hz (n = 4) or sham (n = 4). The left hemisphere was stimulated for 20 minutes. To evaluate the cumulative effect of rTMS, eight additional rats were assigned to the 1-Hz (n = 4) or sham (n = 4) rTMS groups. The left hemisphere was stimulated for 5 consecutive days using the same protocol. Microarray analysis revealed differentially expressed genes in the rat cortex after rTMS treatment. The overrepresented gene ontology categories included the positive regulation of axon extension, axonogenesis, intracellular transport, and synaptic plasticity after repeated sessions of rTMS. A single session of rTMS primarily induced changes in the early genes, and several miRNAs were significantly related to the mRNAs. Future studies are required to validate the functional significance of selected genes and refine the therapeutic use of rTMS.

Establishment of the large-scale longitudinal multi-omics dataset in COVID-19 patients: data profile and biospecimen

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of large-scale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment.

Single-cell transcriptomics reveal cellular diversity of aortic valve and the immunomodulation by PPARγ during hyperlipidemia

Valvular inflammation triggered by hyperlipidemia has been considered as an important initial process of aortic valve disease; however, cellular and molecular evidence remains unclear. Here, we assess the relationship between plasma lipids and valvular inflammation, and identify association of low-density lipoprotein with increased valvular lipid and macrophage accumulation. Single-cell RNA sequencing analysis reveals the cellular heterogeneity of leukocytes, valvular interstitial cells, and valvular endothelial cells, and their phenotypic changes during hyperlipidemia leading to recruitment of monocyte-derived MHC-II^hi macrophages. Interestingly, we find activated PPARγ pathway in Cd36⁺ valvular endothelial cells increased in hyperlipidemic mice, and the conservation of PPARγ activation in non-calcified human aortic valves. While the PPARγ inhibition promotes inflammation, PPARγ activation using pioglitazone reduces valvular inflammation in hyperlipidemic mice. These results show that low-density lipoprotein is the main lipoprotein accumulated in the aortic valve during hyperlipidemia, leading to early-stage aortic valve disease, and PPARγ activation protects the aortic valve against inflammation.

Identifying the mechanisms underlying the early inflammatory phase of aortic valve disease is crucial for disease prevention. Here the authors perform single-cell RNA sequencing to show the immunomodulatory role of PPARγ in valvular endothelial cells during hyperlipidemia.

Establishment of the large-scale longitudinal multi-omics dataset in COVID-19 patients: data profile and biospecimen

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of largescale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment. [BMB Reports 2022; 55(9): 465-471].

Associations between polygenic risk of coronary artery disease and type 2 diabetes, lifestyle, and cardiovascular mortality: A prospective UK Biobank study

Background

Previous studies primarily targeted the ability of polygenic risk scores (PRSs) to predict a specific disease, and only a few studies have investigated the association between genetic risk scores and cardiovascular (CV) mortality. We assessed PRSs for coronary artery disease (CAD) and type 2 diabetes (T2DM) as the predictive factors for CV mortality, independent of traditional risk factors, and further investigated the additive effect between lifestyle behavior and PRS on CV mortality.

Methods

We used genetic and phenotypic data from UK Biobank participants aged 40–69 years at baseline, collected with standardized procedures. Genome-wide PRSs were constructed using >6 million genetic variants. Cox proportional hazard models were used to analyze the relationship between PRS and CV mortality with stratification by age, sex, disease status, and lifestyle behavior.

Results

Of 377,909 UK Biobank participants having European ancestry, 3,210 (0.8%) died due to CV disease during a median follow-up of 8.9 years. CV mortality risk was significantly associated with CAD PRS [low vs. very high genetic risk groups, CAD PRS hazard ratio (HR) 2.61 (2.02–3.36)] and T2DM PRS [HR 2.08 (1.58–2.73)], respectively. These relationships remained significant even after an adjustment for a comprehensive range of demographic and clinical factors. In the very high genetic risk group, adherence to an unfavorable lifestyle was further associated with a substantially increased risk of CV mortality [favorable vs. unfavorable lifestyle with very high genetic risk for CAD PRS, HR 8.31 (5.12–13.49); T2DM PRS, HR 5.84 (3.39–10.04)]. Across all genetic risk groups, 32.1% of CV mortality was attributable to lifestyle behavior [population attributable fraction (PAF) 32.1% (95% CI 28.8–35.3%)] and 14.1% was attributable to smoking [PAF 14.1% (95% CI 12.4–15.7%)]. There was no evidence of significant interaction between PRSs and age, sex, or lifestyle behavior in predicting the risk of CV mortality.

Conclusion

PRSs for CAD or T2DM and lifestyle behaviors are the independent predictive factors for future CV mortality in the white, middle-aged population. PRS-based risk assessment could be useful to identify the individuals who need intensive behavioral or therapeutic interventions to reduce the risk of CV mortality.