Poor accuracy and sustainability of the first-step FIB4 EASL pathway for stratifying steatotic liver disease risk in the general population.

BACKGROUND AND AIMS: The European Association for the Study of the Liver introduced a clinical pathway (EASL CP) for screening significant/advanced fibrosis in people at risk of steatotic liver disease (SLD). We assessed the performance of the first-step FIB4 EASL CP in the general population across different SLD risk groups (MASLD, Met-ALD and ALD) and various age classes. METHODS: We analysed a total of 3372 individuals at risk of SLD from the 2017-2018 National Health and Nutrition Examination Survey (NHANES17-18), projected to 152.3 million U.S. adults, 300,329 from the UK Biobank (UKBB) and 57,644 from the Biobank Japan (BBJ). We assessed liver stiffness measurement (LSM) ≥8 kPa and liver-related events occurring within 3 and 10 years (3/10 year-LREs) as outcomes. We defined MASLD, MetALD, and ALD according to recent international recommendations. RESULTS: FIB4 sensitivity for LSM ≥ 8 kPa was low (27.7%), but it ranged approximately 80%-90% for 3-year LREs. Using FIB4, 22%-57% of subjects across the three cohorts were identified as candidates for vibration-controlled transient elastography (VCTE), which was mostly avoidable (positive predictive value of FIB4 ≥ 1.3 for LSM ≥ 8 kPa ranging 9.5%-13% across different SLD categories). Sensitivity for LSM ≥ 8 kPa and LREs increased with increasing alcohol intake (ALD>MetALD>MASLD) and age classes. For individuals aged ≥65 years, using the recommended age-adjusted FIB4 cut-off (≥2) substantially reduced sensitivity for LSM ≥ 8 kPa and LREs. CONCLUSIONS: The first-step FIB4 EASL CP is poorly accurate and feasible for individuals at risk of SLD in the general population. It is crucial to enhance the screening strategy with a first-step approach able to reduce unnecessary VCTEs and optimise their yield.

Novel ancestry-specific primary open-angle glaucoma loci and shared biology with vascular mechanisms and cell proliferation.

Primary open-angle glaucoma (POAG), a leading cause of irreversible blindness globally, shows disparity in prevalence and manifestations across ancestries. We perform meta-analysis across 15 biobanks (of the Global Biobank Meta-analysis Initiative) (n = 1,487,441: cases = 26,848) and merge with previous multi-ancestry studies, with the combined dataset representing the largest and most diverse POAG study to date (n = 1,478,037: cases = 46,325) and identify 17 novel significant loci, 5 of which were ancestry specific. Gene-enrichment and transcriptome-wide association analyses implicate vascular and cancer genes, a fifth of which are primary ciliary related. We perform an extensive statistical analysis of SIX6 and CDKN2B-AS1 loci in human GTEx data and across large electronic health records showing interaction between SIX6 gene and causal variants in the chr9p21.3 locus, with expression effect on CDKN2A/B. Our results suggest that some POAG risk variants may be ancestry specific, sex specific, or both, and support the contribution of genes involved in programmed cell death in POAG pathogenesis.

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

Genetic architecture of alcohol consumption identified by a genotype-stratified GWAS and impact on esophageal cancer risk in Japanese people.

An East Asian-specific variant on aldehyde dehydrogenase 2 (ALDH2 rs671, G>A) is the major genetic determinant of alcohol consumption. We performed an rs671 genotype-stratified genome-wide association study meta-analysis of alcohol consumption in 175,672 Japanese individuals to explore gene-gene interactions with rs671 behind drinking behavior. The analysis identified three genome-wide significant loci (GCKR, KLB, and ADH1B) in wild-type homozygotes and six (GCKR, ADH1B, ALDH1B1, ALDH1A1, ALDH2, and GOT2) in heterozygotes, with five showing genome-wide significant interaction with rs671. Genetic correlation analyses revealed ancestry-specific genetic architecture in heterozygotes. Of the discovered loci, four (GCKR, ADH1B, ALDH1A1, and ALDH2) were suggested to interact with rs671 in the risk of esophageal cancer, a representative alcohol-related disease. Our results identify the genotype-specific genetic architecture of alcohol consumption and reveal its potential impact on alcohol-related disease risk.

Extracting immunological and clinical heterogeneity across autoimmune rheumatic diseases by cohort-wide immunophenotyping.

OBJECTIVE: Extracting immunological and clinical heterogeneity across autoimmune rheumatic diseases (AIRDs) is essential towards personalised medicine. METHODS: We conducted large-scale and cohort-wide immunophenotyping of 46 peripheral immune cells using Human Immunology Protocol of comprehensive 8-colour flow cytometric analysis. Dataset consisted of >1000 Japanese patients of 11 AIRDs with deep clinical information registered at the FLOW study, including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). In-depth clinical and immunological characterisation was conducted for the identified RA patient clusters, including associations of inborn human genetics represented by Polygenic Risk Score (PRS). RESULTS: Multimodal clustering of immunophenotypes deciphered underlying disease-cell type network in immune cell, disease and patient cluster resolutions. This provided immune cell type specificity shared or distinct across AIRDs, such as close immunological network between mixed connective tissue disease and SLE. Individual patient-level clustering dissected patients with AIRD into several clusters with different immunological features. Of these, RA-like or SLE-like clusters were exclusively dominant, showing immunological differentiation between RA and SLE across AIRDs. In-depth clinical analysis of RA revealed that such patient clusters differentially defined clinical heterogeneity in disease activity and treatment responses, such as treatment resistance in patients with RA with SLE-like immunophenotypes. PRS based on RA case-control and within-case stratified genome-wide association studies were associated with clinical and immunological characteristics. This pointed immune cell type implicated in disease biology such as dendritic cells for RA-interstitial lung disease. CONCLUSION: Cohort-wide and cross-disease immunophenotyping elucidate clinically heterogeneous patient subtypes existing within single disease in immune cell type-specific manner.

Optimization of extreme ultra-violet light emitted from the CO2 laser-irradiated tin plasmas using 2D radiation hydrodynamic simulations.

We studied Extreme Ultra-Violet (EUV) emission characteristics of the 13.5 nm wavelength from CO2 laser-irradiated pre-formed tin plasmas using 2D radiation hydrodynamic simulations. Our results indicate that when a CO2 laser irradiates pre-formed tin plasma, the heated plasma expands towards the surrounding plasma, steepening the density at the ablation front and lowering the density near the laser axis due to the transverse motion of the plasma. Consequently, the laser absorption fraction decreases, and the contribution to EUV output from the ablation front becomes dominant over that from the low-density plasmas. We estimated that an EUV conversion efficiency of 10% from laser to EUV emission could be achieved with a larger laser spot size, shortened laser pulse width, and longer pre-formed plasma density scale length. Our results offer one optimizing solution to achieve an efficient and powerful EUV light source for the next-generation semiconductors.

Multifaceted analysis of cross-tissue transcriptomes reveals phenotype-endotype associations in atopic dermatitis.

Atopic dermatitis (AD) is a skin disease that is heterogeneous both in terms of clinical manifestations and molecular profiles. It is increasingly recognized that AD is a systemic rather than a local disease and should be assessed in the context of whole-body pathophysiology. Here we show, via integrated RNA-sequencing of skin tissue and peripheral blood mononuclear cell (PBMC) samples along with clinical data from 115 AD patients and 14 matched healthy controls, that specific clinical presentations associate with matching differential molecular signatures. We establish a regression model based on transcriptome modules identified in weighted gene co-expression network analysis to extract molecular features associated with detailed clinical phenotypes of AD. The two main, qualitatively differential skin manifestations of AD, erythema and papulation are distinguished by differential immunological signatures. We further apply the regression model to a longitudinal dataset of 30 AD patients for personalized monitoring, highlighting patient heterogeneity in disease trajectories. The longitudinal features of blood tests and PBMC transcriptome modules identify three patient clusters which are aligned with clinical severity and reflect treatment history. Our approach thus serves as a framework for effective clinical investigation to gain a holistic view on the pathophysiology of complex human diseases.

Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores.

Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits. We also present a two-stage meta-analysis strategy whereby, in contributing cohorts, a PGS-adjusted GWAS is rerun using PGSs derived from a first round of a standard meta-analysis. On average, across traits, this approach yields a 1.26-fold increase in the number of detected associations (range 1.07- to 1.76-fold increase). Altogether, our study demonstrates the value of using PGSs to increase the power of GWASs in underrepresented populations and promotes such an analytical strategy for future GWAS meta-analyses.

Water-window x-ray emission from laser-produced Au plasma under optimal target thickness and focus conditions.

Optimal laser irradiation conditions for water-window (WW) x-ray emission (2.3-4.4 nm) from an Au plasma are investigated to develop a laboratory-scale WW x-ray source. A minimum Au target thickness of 1 µm is obtained for a laser intensity of ∼10^{13} W/cm^{2} by observing the intensity drop in the WW spectra. Au targets produced by thermal evaporation are found to have a higher conversion efficiency than commercial foil targets for WW x-ray radiation. In addition, optimal laser spots for fixed laser energies (240 and 650 mJ) are found for an Au target ∼1 mm in front of the focal point, where suitable conditions for plasma temperature and plume volume coupling are achieved. The mechanism of the optimal target thickness and spot size can be well explained using a radiation hydrodynamic simulation code.

Pan-cancer and cross-population genome-wide association studies dissect shared genetic backgrounds underlying carcinogenesis.

Integrating genomic data of multiple cancers allows de novo cancer grouping and elucidating the shared genetic basis across cancers. Here, we conduct the pan-cancer and cross-population genome-wide association study (GWAS) meta-analysis and replication studies on 13 cancers including 250,015 East Asians (Biobank Japan) and 377,441 Europeans (UK Biobank). We identify ten cancer risk variants including five pleiotropic associations (e.g., rs2076295 at DSP on 6p24 associated with lung cancer and rs2525548 at TRIM4 on 7q22 nominally associated with six cancers). Quantifying shared heritability among the cancers detects positive genetic correlations between breast and prostate cancer across populations. Common genetic components increase the statistical power, and the large-scale meta-analysis of 277,896 breast/prostate cancer cases and 901,858 controls identifies 91 newly genome-wide significant loci. Enrichment analysis of pathways and cell types reveals shared genetic backgrounds across said cancers. Focusing on genetically correlated cancers can contribute to enhancing our insights into carcinogenesis.

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts.

Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.

Common Germline Risk Variants Impact Somatic Alterations and Clinical Features across Cancers.

Aggregation of genome-wide common risk variants, such as polygenic risk score (PRS), can measure genetic susceptibility to cancer. A better understanding of how common germline variants associate with somatic alterations and clinical features could facilitate personalized cancer prevention and early detection. We constructed PRSs from 14 genome-wide association studies (median n = 64,905) for 12 cancer types by multiple methods and calibrated them using the UK Biobank resources (n = 335,048). Meta-analyses across cancer types in The Cancer Genome Atlas (n = 7,965) revealed that higher PRS values were associated with earlier cancer onset and lower burden of somatic alterations, including total mutations, chromosome/arm somatic copy-number alterations (SCNA), and focal SCNAs. This contrasts with rare germline pathogenic variants (e.g., BRCA1/2 variants), showing heterogeneous associations with somatic alterations. Our results suggest that common germline cancer risk variants allow early tumor development before the accumulation of many somatic alterations characteristic of later stages of carcinogenesis. SIGNIFICANCE: Meta-analyses across cancers show that common germline risk variants affect not only cancer predisposition but the age of cancer onset and burden of somatic alterations, including total mutations and copy-number alterations.

Genetic footprints of assortative mating in the Japanese population.

Assortative mating (AM) is a pattern characterized by phenotypic similarities between mating partners. Detecting the evidence of AM has been challenging due to the lack of large-scale datasets that include phenotypic data on both partners, especially in populations of non-European ancestries. Gametic phase disequilibrium between trait-associated alleles is a signature of parental AM on a polygenic trait, which can be detected even without partner data. Here, using polygenic scores for 81 traits in the Japanese population using BioBank Japan Project genome-wide association studies data (n = 172,270), we found evidence of AM on the liability to type 2 diabetes and coronary artery disease, as well as on dietary habits. In cross-population comparison using United Kingdom Biobank data (n = 337,139) we found shared but heterogeneous impacts of AM between populations.

Interleukin-1ß triggers matrix metalloprotease-3 expression through p65/RelA activation in melanoma cells.

Melanoma shows highly aggressive behavior (i.e., local invasion and metastasis). Matrix metalloprotease-3 (MMP-3), a zinc-dependent endopeptidase, degrades several extracellular substrates and contributes to local invasion by creating a microenvironment suitable for tumor development. Here, we report that interleukin-1ß (IL-1ß) triggers the MMP-3 expression in canine melanoma cells. The activity of MMP-3 in the culture supernatant was increased in IL-1ß-treated melanoma cells. IL-1ß time- and dose-dependently provoked the mRNA expression of MMP-3. IL-1ß induced the migration of melanoma cells; however, this migration was attenuated by UK356618, an MMP-3 inhibitor. When the cells were treated with the nuclear factor-κB (NF-κB) inhibitor TPCA-1, the inhibition of MMP-3 expression was observed. In IL-1ß-treated cells, the phosphorylation both of p65/RelA and p105 was detected, indicating NF-κB pathway activation. In p65/RelA-depleted melanoma cells, IL-1ß-mediated mRNA expression of MMP-3 was inhibited, whereas this reduction was not observed in p105-depleted cells. These findings suggest that MMP-3 expression in melanoma cells is regulated through IL-1ß-mediated p65/RelA activation, which is involved in melanoma cell migration.

Stroke genetics informs drug discovery and risk prediction across ancestries.

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

Multi-trait and cross-population genome-wide association studies across autoimmune and allergic diseases identify shared and distinct genetic component.

OBJECTIVES: Autoimmune and allergic diseases are outcomes of the dysregulation of the immune system. Our study aimed to elucidate differences or shared components in genetic backgrounds between autoimmune and allergic diseases. METHODS: We estimated genetic correlation and performed multi-trait and cross-population genome-wide association study (GWAS) meta-analysis of six immune-related diseases: rheumatoid arthritis, Graves' disease, type 1 diabetes for autoimmune diseases and asthma, atopic dermatitis and pollinosis for allergic diseases. By integrating large-scale biobank resources (Biobank Japan and UK biobank), our study included 105 721 cases and 433 663 controls. Newly identified variants were evaluated in 21 778 cases and 712 767 controls for two additional autoimmune diseases: psoriasis and systemic lupus erythematosus. We performed enrichment analyses of cell types and biological pathways to highlight shared and distinct perspectives. RESULTS: Autoimmune and allergic diseases were not only mutually classified based on genetic backgrounds but also they had multiple positive genetic correlations beyond the classifications. Multi-trait GWAS meta-analysis newly identified six allergic disease-associated loci. We identified four loci shared between the six autoimmune and allergic diseases (rs10803431 at PRDM2, OR=1.07, p=2.3×10-8, rs2053062 at G3BP1, OR=0.90, p=2.9×10-8, rs2210366 at HBS1L, OR=1.07, p=2.5×10-8 in Japanese and rs4529910 at POU2AF1, OR=0.96, p=1.9×10-10 across ancestries). Associations of rs10803431 and rs4529910 were confirmed at the two additional autoimmune diseases. Enrichment analysis demonstrated link to T cells, natural killer cells and various cytokine signals, including innate immune pathways. CONCLUSION: Our multi-trait and cross-population study should elucidate complex pathogenesis shared components across autoimmune and allergic diseases.

Polygenic risk scores for prediction of breast cancer risk in Asian populations.

PURPOSE: Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups. METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases). RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk. CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.