Collagen structures of demineralized bone paper direct mineral metabolism.

Bone is a dynamic mineralized tissue that undergoes continuous turnover throughout life. While the general mechanism of bone mineral metabolism is documented, the role of underlying collagen structures in regulating osteoblastic mineral deposition and osteoclastic mineral resorption remains an active research area, partly due to the lack of biomaterial platforms supporting accurate and analytical investigation. The recently introduced osteoid-inspired demineralized bone paper (DBP), prepared by 20-µm thin sectioning of demineralized bovine compact bone, holds promise in addressing this challenge as it preserves the intrinsic bony collagen structure and retains semi-transparency. Here, we report on the impact of collagen structures on modulating osteoblast and osteoclast-driven bone mineral metabolism using vertical and transversal DBPs that exhibit a uniaxially aligned and a concentric ring collagen structure, respectively. Translucent DBP reveals these collagen structures and facilitates longitudinal tracking of mineral deposition and resorption under brightfield microscopy for at least 3 wk. Genetically labeled primary osteogenic cells allow fluorescent monitoring of these cellular processes. Osteoblasts adhere and proliferate following the underlying collagen structures of DBPs. Osteoblastic mineral deposition is significantly higher in vertical DBP than in transversal DBP. Spatiotemporal analysis reveals notably more osteoblast adhesion and faster mineral deposition in vascular regions than in bone regions. Subsequent osteoclastic resorption follows these mineralized collagen structures, directing distinct trench and pit-type resorption patterns. In vertical DBP, trench-type resorption occurs at an 80% frequency, whereas transversal DBP shows 35% trench-type and 65% pit-type resorption. Our studies substantiate the importance of collagen structures in regulating mineral metabolism by osteogenic cells. DBP is expected to serve as an enabling biomaterial platform for studying various aspects of cellular and extracellular bone remodeling biology.

Dual add-on therapy of gemigliptin and dapagliflozin in patients with type 2 diabetes inadequately controlled with metformin alone: The SOLUTION 2 study.

AIM: To evaluate the efficacy and safety of gemigliptin and dapagliflozin dual add-on therapy (GEMI + DAPA) to metformin in type 2 diabetes (T2D) patients who had inadequate glycaemic control on metformin alone, compared with a single add-on of either gemigliptin (GEMI) or dapagliflozin (DAPA) to metformin. MATERIALS AND METHODS: In this randomized, double-blind, double-dummy, active-controlled, parallel-group, phase 3 study, 469 T2D patients treated with a stable dose of metformin for 8 weeks or longer were randomized to receive GEMI + DAPA (n = 157) and either GEMI (n = 156) or DAPA (n = 156). The primary endpoint was change in HbA1c levels from baseline at week 24. RESULTS: Baseline characteristics including body mass index and T2D duration were similar among groups. At week 24, the least square mean changes in HbA1c from baseline were -1.34% with GEMI + DAPA, -0.90% with GEMI (difference between GEMI + DAPA vs. GEMI -0.44% [95% confidence interval {CI}: -0.58% to -0.31%], P < .01) and -0.78% with DAPA (difference between GEMI + DAPA vs. DAPA -0.56% [95% CI: -0.69% to -0.42%], P < .01). Both upper CIs were less than 0, demonstrating the superiority of GEMI + DAPA for lowering HbA1c. The rates of responders achieving HbA1c less than 7% and less than 6.5% were greater with GEMI + DAPA (84.9%, 56.6%) than with GEMI (55.3%, 32.2%) and DAPA (49.3%, 15.3%). The incidence rate of adverse events was similar across groups, with low incidence rates of hypoglycaemia, urinary tract infection and genital infection. CONCLUSIONS: These results suggest that the addition of GEMI + DAPA to metformin as triple combination therapy was effective, safe and well-tolerated, especially for T2D patients who experienced poor glycaemic control on metformin alone.

High remnant-cholesterol levels increase the risk for end-stage renal disease: a nationwide, population-based, cohort study.

BACKGROUND: The effect of remnant-cholesterol (remnant-C) on incident end-stage renal disease (ESRD) has not been studied longitudinally. This retrospective cohort study evaluated the association between remnant-C and the development of ESRD in a nationwide Korean cohort. METHODS: Participants in a National Health Insurance Service health examination (n = 3,856,985) were followed up until the onset of ESRD. The median duration of follow-up was 10.3 years. The Martin-Hopkins equation was used to determine low-density lipoprotein cholesterol (LDL-C) levels from directly measured triglyceride, high-density lipoprotein cholesterol (HDL-C), and total cholesterol levels. Remnant-C levels were determined by subtracting HDL-C and LDL-C from total cholesterol. The risk for incident ESRD was calculated for each quartile of remnant-C, adjusting for conventional risk factors such as baseline renal function, comorbidities, and total cholesterol levels. RESULTS: ESRD developed in 11,073 (0.29%) participants. The risk for ESRD exhibited a gradual increase according to higher levels of remnant-C, with a 61% increased risk in the highest quartile than in the lowest (hazard ratio [HR] 1.61 [95% confidence interval (CI) 1.50-1.72]). The elevated risk for ESRD in the highest quartile versus the lowest quartile was more prominent in younger than in older subjects (20-29 years, HR 4.07 [95% CI 2.85-5.83]; 30-39 years, HR 2.39 [95% CI 1.83-3.13]; ≥ 70 years, HR 1.32 [95% CI 1.16-1.51]). In addition, the increased risk for ESRD related to higher remnant-C levels was greater in females than in males. CONCLUSIONS: Independent of conventional risk factors, remnant-C levels were positively associated with incident ESRD, particularly in younger populations and adult females. Reducing remnant-C levels may be a novel preventive strategy against ESRD.

X-linked genetic associations in sporadic thoracic aortic dissection.

The male predominance in sporadic thoracic aortic aneurysm and dissection (TAD) suggests that the X chromosome contributes to TAD, but this has not been tested. We investigated whether X-linked variation-common (minor allele frequency [MAF] ≥0.01) and rare (MAF <0.01)-was associated with sporadic TAD in three cohorts of European descent (Discovery: 364 cases, 874 controls; Replication: 516 cases, 440,131 controls, and ARIC [Atherosclerosis Risk in Communities study]: 753 cases, 2247 controls). For analysis of common variants, we applied a sex-stratified logistic regression model followed by a meta-analysis of sex-specific odds ratios. Furthermore, we conducted a meta-analysis of overlapping common variants between the Discovery and Replication cohorts. For analysis of rare variants, we used a sex-stratified optimized sequence kernel association test model. Common variants results showed no statistically significant findings in the Discovery cohort. An intergenic common variant near SPANXN1 was statistically significant in the Replication cohort (p = 1.81 × 10-8). The highest signal from the meta-analysis of the Discovery and Replication cohorts was a ZNF182 intronic common variant (p = 3.5 × 10-6). In rare variants results, RTL9 reached statistical significance (p = 5.15 × 10-5). Although most of our results were statistically insignificant, our analysis is the most comprehensive X-chromosome association analysis of sporadic TAD to date.

Seq-Scope Protocol: Repurposing Illumina Sequencing Flow Cells for High-Resolution Spatial Transcriptomics.

Spatial transcriptomics (ST) technologies represent a significant advance in gene expression studies, aiming to profile the entire transcriptome from a single histological slide. These techniques are designed to overcome the constraints faced by traditional methods such as immunostaining and RNA in situ hybridization, which are capable of analyzing only a few target genes simultaneously. However, the application of ST in histopathological analysis is also limited by several factors, including low resolution, a limited range of genes, scalability issues, high cost, and the need for sophisticated equipment and complex methodologies. Seq-Scope-a recently developed novel technology-repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, thereby overcoming these limitations. Here we provide a detailed step-by-step protocol to implement Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell that allows for the profiling of multiple tissue sections in an area of 7 mm × 7 mm or larger. In addition to detailing how to prepare a frozen tissue section for both histological imaging and sequencing library preparation, we provide comprehensive instructions and a streamlined computational pipeline to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology.

High-Resolution Spatial Transcriptomic Atlas of Mouse Soleus Muscle: Unveiling Single Cell and Subcellular Heterogeneity in Health and Denervation.

Skeletal muscle is essential for both movement and metabolic processes, characterized by a complex and ordered structure. Despite its importance, a detailed spatial map of gene expression within muscle tissue has been challenging to achieve due to the limitations of existing technologies, which struggle to provide high-resolution views. In this study, we leverage the Seq-Scope technique, an innovative method that allows for the observation of the entire transcriptome at an unprecedented submicron spatial resolution. By applying this technique to the mouse soleus muscle, we analyze and compare the gene expression profiles in both healthy conditions and following denervation, a process that mimics aspects of muscle aging. Our approach reveals detailed characteristics of muscle fibers, other cell types present within the muscle, and specific subcellular structures such as the postsynaptic nuclei at neuromuscular junctions, hybrid muscle fibers, and areas of localized expression of genes responsive to muscle injury, along with their histological context. The findings of this research significantly enhance our understanding of the diversity within the muscle cell transcriptome and its variation in response to denervation, a key factor in the decline of muscle function with age. This breakthrough in spatial transcriptomics not only deepens our knowledge of muscle biology but also sets the stage for the development of new therapeutic strategies aimed at mitigating the effects of aging on muscle health, thereby offering a more comprehensive insight into the mechanisms of muscle maintenance and degeneration in the context of aging and disease.

C-Reactive Protein Levels Correlate with Measures of Dysglycemia and Gut Microbiome Profiles.

C-reactive protein (CRP) is a commonly used marker of low-grade inflammation as well as a marker of acute infection. CRP levels are elevated in those with diabetes and increased CRP concentrations are a risk factor for developing type 2 diabetes. Gut microbiome effects on metabolism and immune responses can impact chronic inflammation, including affecting CRP levels, that in turn can lead to the development and maintenance of dysglycemia. Using a high-sensitivity C-reactive protein (hsCRP) assay capable of detecting subtle changes in C-reactive protein, we show that higher hsCRP levels specifically correlate with worsening glycemia, reduced microbial richness and evenness, and with a reduction in the Firmicutes/Bacteroidota ratio. These data demonstrate a pivotal role for CRP not only in the context of worsening glycemia and changes to the gut microbiota, but also highlight CRP as a potential target for mitigating type 2 diabetes progression or as a therapeutic target that could be manipulated through the microbiome. Understanding these processes will provide insights into the etiology of type 2 diabetes in addition to opening doors leading to possible novel diagnostic strategies and therapeutics.

FICTURE: Scalable segmentation-free analysis of submicron resolution spatial transcriptomics.

Spatial transcriptomics (ST) technologies have advanced to enable transcriptome-wide gene expression analysis at submicron resolution over large areas. Analysis of high-resolution ST data relies heavily on image-based cell segmentation or gridding, which often fails in complex tissues due to diversity and irregularity of cell size and shape. Existing segmentation-free analysis methods scale only to small regions and a small number of genes, limiting their utility in high-throughput studies. Here we present FICTURE, a segmentation-free spatial factorization method that can handle transcriptome-wide data labeled with billions of submicron resolution spatial coordinates. FICTURE is orders of magnitude more efficient than existing methods and it is compatible with both sequencing- and imaging-based ST data. FICTURE reveals the microscopic ST architecture for challenging tissues, such as vascular, fibrotic, muscular, and lipid-laden areas in real data where previous methods failed. FICTURE's cross-platform generality, scalability, and precision make it a powerful tool for exploring high-resolution ST.

Cholecystectomy increases the risk of metabolic syndrome in the Korean population: a longitudinal cohort study.

Background: Cholecystectomy is a common surgical procedure to treat symptomatic gallstones; however, the long-term outcomes after cholecystectomy are unknown. Therefore, we aimed to investigate whether incident metabolic syndrome (MetS) is associated with cholecystectomy through a large, population-based, longitudinal study. Methods: Subjects aged ≥20 years who underwent cholecystectomy from 2010 to 2014 (n=76,485) and controls (n=76,485), matched for age and sex, were identified from the Korean National Health Insurance Corporation. Cox proportional hazards analyses were performed to evaluate the association between cases and incident MetS, and hazard ratios and 95% confidence intervals (CIs) were calculated. Results: A total of 152,970 patients were included. Mean age was 52.47±12.76 years, and 50.65% of participants were male. During the follow-up period, there were 38,979 (25.48%) newly diagnosed MetS cases in the study participants. The risk of MetS in the cholecystectomy group was approximately 20% higher than that in the control group [adjusted odds ratio (OR), 1.20; 95% CI: 1.17-1.23]. In the fully adjusted models, the corresponding ORs for new-onset high waist circumference (WC), low high-density lipoprotein cholesterol (HDL-C) levels, high triglycerides (TG) levels, high blood pressure (BP), and high blood glucose levels were 1.16 (1.13-1.19), 1.19 (1.16-1.22), 1.25 (1.22-1.28), 1.27 (1.23-1.31), and 1.21 (1.18-1.24), respectively. Cholecystectomy was an independent risk factor of incident MetS, after adjusting for potential confounding factors. In the subgroup analyses, the cholecystectomy group had a higher risk of MetS than the control group in subjects without hypertension or dyslipidemia, respectively. Conclusions: In this large, population-based study, cholecystectomy was associated with an increased risk of developing MetS, independent of other confounding factors. Therefore, careful monitoring of metabolic variables and long-term follow-up are required to evaluate MetS risk after cholecystectomy.

Arsenic metabolism, diabetes prevalence, and insulin resistance among Mexican Americans: A mendelian randomization approach.

Background: Differences in arsenic metabolism capacity may influence risk for type 2 diabetes, but the mechanistic drivers are unclear. We evaluated the associations between arsenic metabolism with overall diabetes prevalence and with static and dynamic measures of insulin resistance among Mexican Americans living in Starr County, Texas. Methods: We utilized data from cross-sectional studies conducted in Starr County, Texas, from 2010-2014. A Mendelian randomization approach was utilized to evaluate the associations between arsenic metabolism and type 2 diabetes prevalence using the intronic variant in the arsenic methylating gene, rs9527, as the instrumental variable for arsenic metabolism. To further assess mechanisms for diabetes pathogenesis, proportions of the urinary arsenic metabolites were employed to assess the association between arsenic metabolism and insulin resistance among participants without diabetes. Urinary biomarkers of arsenic metabolites were modeled as individual proportions of the total. Arsenic metabolism was evaluated both with a static outcome of insulin resistance, homeostatic measure of assessment (HOMA-IR), and a dynamic measure of insulin sensitivity, Matsuda Index. Results: Among 475 Mexican American participants from Starr County, higher metabolism capacity for arsenic is associated with higher diabetes prevalence driven by worse insulin resistance. Presence of the minor T allele of rs9527 is independently associated with an increase in the proportion of monomethylated arsenic (MMA%) and is associated with an odds ratio of 0.50 (95% CI: 0.24, 0.90) for type 2 diabetes. This association was conserved after potential covariate adjustment. Furthermore, among participants without type 2 diabetes, the highest quartile of MMA% was associated with 22% (95% CI: -33.5%, -9.07%) lower HOMA-IR and 56% (95% CI: 28.3%, 91.3%) higher Matsuda Index for insulin sensitivity. Conclusions: Arsenic metabolism capacity, indicated by a lower proportion of monomethylated arsenic, is associated with increased diabetes prevalence driven by an insulin resistant phenotype among Mexican Americans living in Starr County, Texas.

Efficacy of Gemigliptin Add-on to Dapagliflozin and Metformin in Type 2 Diabetes Patients: A Randomized, Double-Blind, Placebo-Controlled Study (SOLUTION).

BACKGRUOUND: This study evaluated the efficacy and safety of add-on gemigliptin in patients with type 2 diabetes mellitus (T2DM) who had inadequate glycemic control with metformin and dapagliflozin. METHODS: In this randomized, placebo-controlled, parallel-group, double-blind, phase III study, 315 patients were randomized to receive either gemigliptin 50 mg (n=159) or placebo (n=156) with metformin and dapagliflozin for 24 weeks. After the 24-week treatment, patients who received the placebo were switched to gemigliptin, and all patients were treated with gemigliptin for an additional 28 weeks. RESULTS: The baseline characteristics were similar between the two groups, except for body mass index. At week 24, the least squares mean difference (standard error) in hemoglobin A1c (HbA1c) changes was -0.66% (0.07) with a 95% confidence interval of -0.80% to -0.52%, demonstrating superior HbA1c reduction in the gemigliptin group. After week 24, the HbA1c level significantly decreased in the placebo group as gemigliptin was administered, whereas the efficacy of HbA1c reduction was maintained up to week 52 in the gemigliptin group. The safety profiles were similar: the incidence rates of treatment-emergent adverse events up to week 24 were 27.67% and 29.22% in the gemigliptin and placebo groups, respectively. The safety profiles after week 24 were similar to those up to week 24 in both groups, and no new safety findings, including hypoglycemia, were noted. CONCLUSION: Add-on gemigliptin was well tolerated, providing comparable safety profiles and superior efficacy in glycemic control over placebo for long-term use in patients with T2DM who had poor glycemic control with metformin and dapagliflozin.

Bone Marrow Adipocytes Contribute to Tumor Microenvironment-Driven Chemoresistance via Sequestration of Doxorubicin.

Chemoresistance is a significant problem in the effective treatment of bone metastasis. Adipocytes are a major stromal cell type in the bone marrow and may play a crucial role in developing microenvironment-driven chemoresistance. However, detailed investigation remains challenging due to the anatomical inaccessibility and intrinsic tissue complexity of the bone marrow microenvironment. In this study, we developed 2D and 3D in vitro models of bone marrow adipocytes to examine the mechanisms underlying adipocyte-induced chemoresistance. We first established a protocol for the rapid and robust differentiation of human bone marrow stromal cells (hBMSCs) into mature adipocytes in 2D tissue culture plastic using rosiglitazone (10 µM), a PPARγ agonist. Next, we created a 3D adipocyte culture model by inducing aggregation of hBMSCs and adipogenesis to create adipocyte spheroids in porous hydrogel scaffolds that mimic bone marrow sinusoids. Simulated chemotherapy treatment with doxorubicin (2.5 µM) demonstrated that mature adipocytes sequester doxorubicin in lipid droplets, resulting in reduced cytotoxicity. Lastly, we performed direct coculture of human multiple myeloma cells (MM1.S) with the established 3D adipocyte model in the presence of doxorubicin. This resulted in significantly accelerated multiple myeloma proliferation following doxorubicin treatment. Our findings suggest that the sequestration of hydrophobic chemotherapeutics by mature adipocytes represents a potent mechanism of bone marrow microenvironment-driven chemoresistance.

StocSum: stochastic summary statistics for whole genome sequencing studies.

Genomic summary statistics, usually defined as single-variant test results from genome-wide association studies, have been widely used to advance the genetics field in a wide range of applications. Applications that involve multiple genetic variants also require their correlations or linkage disequilibrium (LD) information, often obtained from an external reference panel. In practice, it is usually difficult to find suitable external reference panels that represent the LD structure for underrepresented and admixed populations, or rare genetic variants from whole genome sequencing (WGS) studies, limiting the scope of applications for genomic summary statistics. Here we introduce StocSum, a novel reference-panel-free statistical framework for generating, managing, and analyzing stochastic summary statistics using random vectors. We develop various downstream applications using StocSum including single-variant tests, conditional association tests, gene-environment interaction tests, variant set tests, as well as meta-analysis and LD score regression tools. We demonstrate the accuracy and computational efficiency of StocSum using two cohorts from the Trans-Omics for Precision Medicine Program. StocSum will facilitate sharing and utilization of genomic summary statistics from WGS studies, especially for underrepresented and admixed populations.

Association between Sleep Duration and Incident Diabetes Mellitus in Healthy Subjects: A 14-Year Longitudinal Cohort Study.

BACKGROUND: This study aimed to investigate whether sleep duration and/or quality are associated with incident diabetes mellitus (DM). METHODS: A total of 8816 of 10,030 healthy participants were enrolled in a prospective cohort study. Sleep duration and quality questionnaires were completed. Sleep quality was assessed using the Epworth Sleepiness Scale (ESS), which measures excessive daytime sleepiness in individuals. RESULTS: During the 14-year follow-up period, 18% (1630/8816) were diagnosed with DM. A U-shaped relationship was observed between sleep duration and incident DM, with the highest risk observed when sleep duration was ≥10 h/day (hazard ratios (HR) 1.65 [1.25-2.17]). This group exhibited decreased insulin glycogenic index, a marker of insulin secretory function, during the study period. Among study participants who slept less than 10 h/day, the risk of incident DM increased when the ESS score was >10. CONCLUSIONS: We found that the association between sleep duration and incident DM was U-shaped; both short (≤5 h) and long (≥10 h) sleep durations were associated with an increased risk for the occurrence of incident DM. When sleep duration was 10 h or longer per day, there was a tendency to develop DM due to decreased insulin secretory function.

Efficacy and safety of enavogliflozin, a novel SGLT2 inhibitor, in Korean people with type 2 diabetes: A 24-week, multicentre, randomized, double-blind, placebo-controlled, phase III trial.

AIMS: To evaluate the efficacy and safety of a novel sodium-glucose cotransporter 2 inhibitor, enavogliflozin 0.3 mg monotherapy, in Korean people with type 2 diabetes mellitus (T2DM) inadequately controlled with diet and exercise. MATERIALS AND METHODS: This study was a randomized, double-blind, placebo-controlled trial conducted in 23 hospitals. Individuals with haemoglobin A1c (HbA1c) of 7.0%-10.0% after at least 8 weeks of diet and exercise modification were randomized to receive enavogliflozin 0.3 mg (n = 83) or placebo (n = 84) for 24 weeks. The primary outcome was a change in HbA1c at week 24 from baseline. Secondary outcomes included the proportion of participants achieving HbA1c <7.0%, change in fasting glucose, body weight and lipid levels. Adverse events were investigated throughout the study. RESULTS: At week 24, the placebo-adjusted mean change in HbA1c from baseline in the enavogliflozin group was -0.99% (95% confidence interval -1.24%, -0.74%). The proportions of patients achieving HbA1c <7.0% (71% vs. 24%) at week 24 was significantly higher in the enavogliflozin group (p < .0001). Placebo-adjusted mean changes in fasting plasma glucose (-40.1 mg/dl) and body weight (-2.5 kg) at week 24 were statistically significant (p < .0001). In addition, a significant decrease in blood pressure, low-density lipoprotein cholesterol, triglyceride, and homeostasis model assessment of insulin resistance were observed, along with a significant increase in high-density lipoprotein cholesterol. No significant increase in treatment-related adverse events was observed for enavogliflozin. CONCLUSIONS: Monotherapy with enavogliflozin 0.3 mg improved glycaemic control in people with T2DM. Enavogliflozin therapy also exerted beneficial effects on body weight, blood pressure and lipid profile.

Efficacy and safety of enavogliflozin versus dapagliflozin added to metformin plus gemigliptin treatment in patients with type 2 diabetes: A double-blind, randomized, comparator-active study: ENHANCE-D study.

AIMS: This study evaluated the efficacy and safety of enavogliflozin, a novel sodium-glucose cotransporter 2 inhibitor, versus dapagliflozin in Korean patients with type 2 diabetes mellitus (T2DM) inadequately controlled with metformin and gemigliptin. METHODS: In this multicenter, double-blind, randomized study, patients with inadequate response to metformin (≥ 1000 mg/day) plus gemigliptin (50 mg/day) were randomized to receive enavogliflozin 0.3 mg/day (n = 134) or dapagliflozin 10 mg/day (n = 136) in addition to the metformin plus gemigliptin therapy. The primary endpoint was change in HbA1c from baseline to week 24. RESULTS: Both treatments significantly reduced HbA1c at week 24 (-0.92% in enavogliflozin group, -0.86% in dapagliflozin group). The enavogliflozin and dapagliflozin groups did not differ in terms of changes in HbA1c (between-group difference: -0.06%, 95% confidence interval [CI]: -0.19, 0.06) and fasting plasma glucose (between-group difference: -3.49 mg/dl [-8.08;1.10]). An increase in urine glucose-creatinine ratio was significantly greater in the enavogliflozin group than in the dapagliflozin group (60.2 g/g versus 43.5 g/g, P < 0.0001). The incidence of treatment-emergent adverse events was similar between the groups (21.64% versus 23.53%). CONCLUSIONS: Enavogliflozin, added to metformin plus gemigliptin, was well tolerated and as effective as dapagliflozin in the treatment of patients with T2DM.

Structural variation across 138,134 samples in the TOPMed consortium.

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hemotologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.

Structural variation across 138,134 samples in the TOPMed consortium.

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hematologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.