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.

Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis.

Genetic studies have identified ≥240 loci associated with the risk of type 2 diabetes (T2D), yet most of these loci lie in non-coding regions, masking the underlying molecular mechanisms. Recent studies investigating mRNA expression in human pancreatic islets have yielded important insights into the molecular drivers of normal islet function and T2D pathophysiology. However, similar studies investigating microRNA (miRNA) expression remain limited. Here, we present data from 63 individuals, the largest sequencing-based analysis of miRNA expression in human islets to date. We characterized the genetic regulation of miRNA expression by decomposing the expression of highly heritable miRNAs into cis- and trans-acting genetic components and mapping cis-acting loci associated with miRNA expression [miRNA-expression quantitative trait loci (eQTLs)]. We found i) 84 heritable miRNAs, primarily regulated by trans-acting genetic effects, and ii) 5 miRNA-eQTLs. We also used several different strategies to identify T2D-associated miRNAs. First, we colocalized miRNA-eQTLs with genetic loci associated with T2D and multiple glycemic traits, identifying one miRNA, miR-1908, that shares genetic signals for blood glucose and glycated hemoglobin (HbA1c). Next, we intersected miRNA seed regions and predicted target sites with credible set SNPs associated with T2D and glycemic traits and found 32 miRNAs that may have altered binding and function due to disrupted seed regions. Finally, we performed differential expression analysis and identified 14 miRNAs associated with T2D status-including miR-187-3p, miR-21-5p, miR-668, and miR-199b-5p-and 4 miRNAs associated with a polygenic score for HbA1c levels-miR-216a, miR-25, miR-30a-3p, and miR-30a-5p.

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal remains challenging. In this study, we describe a deep learning (DL) method to analyze the impact of sequence variants on enhancers. Focusing on pancreatic islets, a T2D relevant tissue, we show that our model learns islet-specific transcription factor (TF) regulatory patterns and can be used to prioritize candidate causal variants. At 101 genetic signals associated with T2D and related glycemic traits where multiple variants occur in linkage disequilibrium, our method nominates a single causal variant for each association signal, including three variants previously shown to alter reporter activity in islet-relevant cell types. For another signal associated with blood glucose levels, we biochemically test all candidate causal variants from statistical fine-mapping using a pancreatic islet beta cell line and show biochemical evidence of allelic effects on TF binding for the model-prioritized variant. To aid in future research, we publicly distribute our model and islet enhancer perturbation scores across ~67 million genetic variants. We anticipate that DL methods like the one presented in this study will enhance the prioritization of candidate causal variants for functional studies.

Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 h.

AIMS/HYPOTHESIS: Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycaemia, beta cell glucotoxicity and subsequently type 2 diabetes. In this study, we explored the effects of in vitro hyperglycaemic conditions on human pancreatic islet gene expression across 24 h in six pancreatic cell types: alpha; beta; gamma; delta; ductal; and acinar. We hypothesised that genes associated with hyperglycaemic conditions may be relevant to the onset and progression of diabetes. METHODS: We exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 h in vitro. To assess the transcriptome, we performed single-cell RNA-seq (scRNA-seq) at seven time points. We modelled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterised the effect on insulin production and secretion using CRISPR interference to knock down gene expression in EndoC-ßH1 cells, followed by a glucose-stimulated insulin secretion assay. RESULTS: In the discrete time models, we identified 1344 genes associated with time and 668 genes associated with glucose exposure across all cell types and time points. In the continuous time models, we identified 1311 genes associated with time, 345 genes associated with glucose exposure and 418 genes associated with interaction effects between time and glucose across all cell types. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2449 candidate effector genes for type 2 diabetes, HbA1c, random blood glucose and fasting blood glucose. Of these candidate effector genes, we showed that three (ERO1B, HNRNPA2B1 and RHOBTB3) exhibited an effect on glucose-stimulated insulin production and secretion in EndoC-ßH1 cells. CONCLUSIONS/INTERPRETATION: The findings of our study provide an in-depth characterisation of the 24 h transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production. DATA AVAILABILITY: The scRNA-seq data from the 24 h glucose exposure experiment performed in this study are available in the database of Genotypes and Phenotypes (dbGap; https://www.ncbi.nlm.nih.gov/gap/ ) with accession no. phs001188.v3.p1. Study metadata and summary statistics for the differential expression, gene set enrichment and candidate effector gene prediction analyses are available in the Zenodo data repository ( https://zenodo.org/ ) under accession number 11123248. The code used in this study is publicly available at https://github.com/CollinsLabBioComp/publication-islet_glucose_timecourse .

Biallelic TLR4 deficiency in humans.

BACKGROUND: Toll-like receptors (TLRs) mediate functions for host defense and inflammatory responses. TLR4 recognizes LPS, a component of gram-negative bacteria as well as host-derived endogenous ligands such as S100A8 and S100A9 proteins. OBJECTIVE: We sought to report phenotype and cellular function of individuals with complete TLR4 deficiency. METHODS: We performed genome sequencing and investigated exome and genome sequencing databases. Cellular responses were studied on primary monocytes, macrophages, and neutrophils, as well as cell lines using flow cytometry, reporter, and cytokine assays. RESULTS: We identified 2 individuals in a family of Qatari origin carrying a homozygous stop codon variant p.Q188X in TLR4 presenting with a variable phenotype (asymptomatic and inflammatory bowel disease consistent with severe perianal Crohn disease). A third individual with homozygous p.Y794X was identified in a population database. In contrast to hypomorphic polymorphisms p.D299G and p.T399I, the variants p.Q188X and p.Y794X completely abrogated LPS-induced cytokine responses whereas TLR2 response was normal. TLR4 deficiency causes a neutrophil CD62L shedding defect, whereas antimicrobial activity toward intracellular Salmonella was intact. CONCLUSIONS: Biallelic TLR4 deficiency in humans causes an inborn error of immunity in responding to LPS. This complements the spectrum of known primary immunodeficiencies, in particular myeloid differentiation primary response 88 (MYD88) or the IL-1 receptor-associated kinase 4 (IRAK4) deficiency that are downstream of TLR4 and TLR2 signaling.

mTOR inhibitors reduce enteropathy, intestinal bleeding and colectomy rate in patients with juvenile polyposis of infancy with PTEN-BMPR1A deletion.

Ultra-rare genetic disorders can provide proof of concept for efficacy of targeted therapeutics and reveal pathogenic mechanisms relevant to more common conditions. Juvenile polyposis of infancy (JPI) is caused by microdeletions in chromosome 10 that result in haploinsufficiency of two tumor suppressor genes: phosphatase and tensin homolog deleted on chromosome 10 (PTEN) and bone morphogenetic protein receptor type IA (BMPR1A). Loss of PTEN and BMPR1A results in a much more severe phenotype than deletion of either gene alone, with infantile onset pan-enteric polyposis and a high mortality rate. No effective pharmacological therapy exists. A multi-center cohort analysis was performed to characterize phenotype and investigate the therapeutic effect of mammalian target of rapamycin (mTOR) inhibition (adverse events, disease progression, time to colectomy and mortality) in patients with JPI. Among 25 JPI patients identified (mean age of onset 13 months), seven received mTOR inhibitors (everolimus, n = 2; or sirolimus, n = 5). Treatment with an mTOR inhibitor reduced the risk of colectomy (hazard ratio = 0.27, 95% confidence interval = 0.07-0.954, P = 0.042) and resulted in significant improvements in the serum albumin level (mean increase = 16.3 g/l, P = 0.0003) and hemoglobin (mean increase = 2.68 g/dl, P = 0.0077). Long-term mTOR inhibitor treatment was well tolerated over an accumulated follow-up time of 29.8 patient years. No serious adverse events were reported. Early therapy with mTOR inhibitors offers effective, pathway-specific and personalized treatment for patients with JPI. Inhibition of the phosphoinositol-3-kinase-AKT-mTOR pathway mitigates the detrimental synergistic effects of combined PTEN-BMPR1A deletion. This is the first effective pharmacological treatment identified for a hamartomatous polyposis syndrome.

Biallelic PI4KA variants cause neurological, intestinal and immunological disease.

Phosphatidylinositol 4-kinase IIIα (PI4KIIIα/PI4KA/OMIM:600286) is a lipid kinase generating phosphatidylinositol 4-phosphate (PI4P), a membrane phospholipid with critical roles in the physiology of multiple cell types. PI4KIIIα's role in PI4P generation requires its assembly into a heterotetrameric complex with EFR3, TTC7 and FAM126. Sequence alterations in two of these molecular partners, TTC7 (encoded by TTC7A or TCC7B) and FAM126, have been associated with a heterogeneous group of either neurological (FAM126A) or intestinal and immunological (TTC7A) conditions. Here we show that biallelic PI4KA sequence alterations in humans are associated with neurological disease, in particular hypomyelinating leukodystrophy. In addition, affected individuals may present with inflammatory bowel disease, multiple intestinal atresia and combined immunodeficiency. Our cellular, biochemical and structural modelling studies indicate that PI4KA-associated phenotypical outcomes probably stem from impairment of PI4KIIIα-TTC7-FAM126's organ-specific functions, due to defective catalytic activity or altered intra-complex functional interactions. Together, these data define PI4KA gene alteration as a cause of a variable phenotypical spectrum and provide fundamental new insight into the combinatorial biology of the PI4KIIIα-FAM126-TTC7-EFR3 molecular complex.

Letters Lost: Capturing Appearance in Crowded Peripheral Vision Reveals a New Kind of Masking.

Peripheral vision is strongly limited by crowding, the deleterious influence of flanking items on target perception. Distinguishing what is seen from what is merely inferred in crowding is difficult because task demands and prior knowledge may influence observers' reports. Here, we used a standard identification task in which participants were susceptible to these influences, and to minimize them, we used a free-report-and-drawing paradigm. Three letters were presented in the periphery. In Experiment 1, 10 participants were asked to identify the central target letter. In Experiment 2, 25 participants freely named and drew what they saw. When three identical letters were presented, performance was almost perfect in Experiment 1, but it was very poor in Experiment 2, in which most participants reported only two letters. Our study reveals limitations of standard crowding paradigms and uncovers a hitherto unrecognized effect that we call redundancy masking.

A systematic review of sudden unexpected death in epilepsy (SUDEP) in childhood.

BACKGROUND: Sudden Unexpected Death in Epilepsy (SUDEP) is a significant cause of death in childhood epilepsy, and causes considerable concern to patients and their families. Despite this, the condition remains poorly understood. This systematic review investigates the risk factors, pathophysiology, and circumstances associated with childhood SUDEP. It aimed to explore the etiology of SUDEP and inform clinicians approaching SUDEP risk disclosure. METHODS: A structured electronic database search of MEDLINE, CENTRAL, EMBASE, and ISI web of science was conducted. Studies were included if they described clinical details of one or more patients, aged 18 years of age and below, who had SUDEP. Two reviewers independently reviewed each article for data extraction and quality assessment. RESULTS: Information on 108 cases of pediatric SUDEP was extracted from 22 included studies. These comprised five cohort studies, four retrospective case control studies, seven case series, and five case reports. Factors that appeared to be linked to pediatric SUDEP included those associated with severe epilepsy (early age of onset, high seizure frequency, intellectual impairment and developmental delay, multiple antiepileptic drug therapy, and structural abnormalities). The majority of included studies was noncomparative and had significant risk of bias. CONCLUSIONS: There is currently insufficient evidence to determine the etiology of pediatric SUDEP. Current best practice to prevent pediatric SUDEP is to optimize the management of epilepsy. A national SUDEP registry would provide invaluable high-quality data and insights into modifiable risk factors, genetic predispositions, and novel prevention strategies.

Gun violence revictimization in New York State: What increases the risk of being shot again?

BACKGROUND: While gun injuries are more likely to occur in in urban settings and affect people of color, factors associated with gun violence revictimization-suffering multiple incidents of gun violence-are unknown. We examined victim demographics and environmental factors associated with gun violence revictimization in New York state (NYS). METHODS: The 2005-2020 NYS hospital discharge database was queried for patients aged 12-65 years with firearm-related hospital encounters. Patient and environmental variables were extracted. Patient home zip code was used to determine the Social Deprivation Index (SDI) for each patient's area of residence. We conducted bivariate and multivariate analyses among patients who suffered a single incident of gun violence or gun violence revictimization. RESULTS: We identified 38,974 gun violence victims among whom 2,243 (5.8%) suffered revictimization. The proportion of revictimization rose from 4% in 2008 to 8% in 2020 (p < 0.01). The median [IQR] time from first to second incident among those who suffered revictimization was 359 [81-1,167] days. Revictimization was more common among Blacks (75.0% vs 65.1%, p < 0.01), patients with Medicaid (54.9% vs 43.2%, p < 0.01), and in areas of higher deprivation (84.8 percentile vs 82.1 percentile, p < 0.01). CONCLUSIONS: Gun violence revictimization is on the rise. People of color and those residing in areas with high social deprivation are more likely to be re-injured. Our findings emphasize the importance of community-level over individual-level interventions for prevention of gun violence revictimization. LEVEL OF EVIDENCE: Epidemiological, Level III.

Multi-omics characterization of type 2 diabetes associated genetic variation.

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date. Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657 cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of these cis- and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D. These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.

Guided preparedness planning with lay communities: enhancing capacity of rural emergency response through a systems-based partnership.

INTRODUCTION: Community disaster preparedness plans, particularly those with content that would mitigate the effects of psychological trauma on vulnerable rural populations, are often nonexistent or underdeveloped. The purpose of the study was to develop and evaluate a model of disaster mental health preparedness planning involving a partnership among three, key stakeholders in the public health system. METHODS: A one-group, post-test, quasi-experimental design was used to assess outcomes as a function of an intervention designated Guided Preparedness Planning (GPP). The setting was the eastern-, northern-, and mid-shore region of the state of Maryland. Partner participants were four local health departments (LHDs), 100 faith-based organizations (FBOs), and one academic health center (AHC)-the latter, collaborating entities of the Johns Hopkins University and the Johns Hopkins Health System. Individual participants were 178 community residents recruited from counties of the above-referenced geographic area. Effectiveness of GPP was based on post-intervention assessments of trainee knowledge, skills, and attitudes supportive of community disaster mental health planning. Inferences about the practicability (feasibility) of the model were drawn from pre-defined criteria for partner readiness, willingness, and ability to participate in the project. Additional aims of the study were to determine if LHD leaders would be willing and able to generate post-project strategies to perpetuate project-initiated government/faith planning alliances (sustainability), and to develop portable methods and materials to enhance model application and impact in other health jurisdictions (scalability). RESULTS: The majority (95%) of the 178 lay citizens receiving the GPP intervention and submitting complete evaluations reported that planning-supportive objectives had been achieved. Moreover, all criteria for inferring model feasibility, sustainability, and scalability were met. CONCLUSIONS: Within the span of a six-month period, LHDs, FBOs, and AHCs can work effectively to plan, implement, and evaluate what appears to be an effective, practical, and durable model of capacity building for public mental health emergency planning.

Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 hours.

Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycemia, beta cell glucotoxicity, and ultimately type 2 diabetes (T2D). In this study, we sought to explore the effects of hyperglycemia on human pancreatic islet (HPI) gene expression by exposing HPIs from two donors to low (2.8mM) and high (15.0mM) glucose concentrations over 24 hours, assaying the transcriptome at seven time points using single-cell RNA sequencing (scRNA-seq). We modeled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Across all cell types, we identified 1,528 genes associated with time, 1,185 genes associated with glucose exposure, and 845 genes associated with interaction effects between time and glucose. We clustered differentially expressed genes across cell types and found 347 modules of genes with similar expression patterns across time and glucose conditions, including two beta cell modules enriched in genes associated with T2D. Finally, by integrating genomic features from this study and genetic summary statistics for T2D and related traits, we nominate 363 candidate effector genes that may underlie genetic associations for T2D and related traits.

An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals.

Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased ß cell apoptosis. Additionally, pancreatic ß cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased ß cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- ß-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived ß-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.

Functional interrogation of twenty type 2 diabetes-associated genes using isogenic human embryonic stem cell-derived ß-like cells.

Genetic studies have identified numerous loci associated with type 2 diabetes (T2D), but the functional roles of many loci remain unexplored. Here, we engineered isogenic knockout human embryonic stem cell lines for 20 genes associated with T2D risk. We examined the impacts of each knockout on ß cell differentiation, functions, and survival. We generated gene expression and chromatin accessibility profiles on ß cells derived from each knockout line. Analyses of T2D-association signals overlapping HNF4A-dependent ATAC peaks identified a likely causal variant at the FAIM2 T2D-association signal. Additionally, the integrative association analyses identified four genes (CP, RNASE1, PCSK1N, and GSTA2) associated with insulin production, and two genes (TAGLN3 and DHRS2) associated with ß cell sensitivity to lipotoxicity. Finally, we leveraged deep ATAC-seq read coverage to assess allele-specific imbalance at variants heterozygous in the parental line and identified a single likely functional variant at each of 23 T2D-association signals.

Functional interrogation of twenty type 2 diabetes-associated genes using isogenic hESC-derived ß-like cells.

Genetic studies have identified numerous loci associated with type 2 diabetes (T2D), but the functional role of many loci has remained unexplored. In this study, we engineered isogenic knockout human embryonic stem cell (hESC) lines for 20 genes associated with T2D risk. We systematically examined ß-cell differentiation, insulin production and secretion, and survival. We performed RNA-seq and ATAC-seq on hESC-ß cells from each knockout line. Analyses of T2D GWAS signals overlapping with HNF4A-dependent ATAC peaks identified a specific SNP as a likely causal variant. In addition, we performed integrative association analyses and identified four genes ( CP, RNASE1, PCSK1N and GSTA2 ) associated with insulin production, and two genes ( TAGLN3 and DHRS2 ) associated with sensitivity to lipotoxicity. Finally, we leveraged deep ATAC-seq read coverage to assess allele-specific imbalance at variants heterozygous in the parental hESC line, to identify a single likely functional variant at each of 23 T2D GWAS signals.

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.

A community-university run conference as a catalyst for addressing health disparities in an urban community.

The African American population of Buffalo, New York experiences striking race-based health disparities due to adverse social determinants of health. A team of community leaders and university faculty determined that a community dialogue was needed to focus research and advocacy on the root causes of these disparities. In response, we organized the annual Igniting Hope conference series that has become the premier conference on health disparities in the region. The series, now supported by an R13 conference grant from NCATS, has been held four times (2018-2021) and has attracted community members, community leaders, university faculty, and trainees. The agenda includes talks by national leaders and breakout/working groups that led to a new state law that has reduced disproportionate traffic-ticketing and drivers' license suspensions in Black neighborhoods; mitigation of the disproportionate COVID-19 fatalities in Black communities; and the launching of a university-supported institute. We describe the key elements of success for a conference series designed by a community-university partnership to catalyze initiatives that are having an impact on social determinants of health in Buffalo.

Imaging Modality and Frequency in Surveillance of Stage I Seminoma Testicular Cancer: Results From a Randomized, Phase III, Noninferiority Trial (TRISST).

PURPOSE: Survival in stage I seminoma is almost 100%. Computed tomography (CT) surveillance is an international standard of care, avoiding adjuvant therapy. In this young population, minimizing irradiation is vital. The Trial of Imaging and Surveillance in Seminoma Testis (TRISST) assessed whether magnetic resonance images (MRIs) or a reduced scan schedule could be used without an unacceptable increase in advanced relapses. METHODS: A phase III, noninferiority, factorial trial. Eligible participants had undergone orchiectomy for stage I seminoma with no adjuvant therapy planned. Random assignment was to seven CTs (6, 12, 18, 24, 36, 48, and 60 months); seven MRIs (same schedule); three CTs (6, 18, and 36 months); or three MRIs. The primary outcome was 6-year incidence of Royal Marsden Hospital stage ≥ IIC relapse (> 5 cm), aiming to exclude increases ≥ 5.7% (from 5.7% to 11.4%) with MRI (v CT) or three scans (v 7); target N = 660, all contributing to both comparisons. Secondary outcomes include relapse ≥ 3 cm, disease-free survival, and overall survival. Intention-to-treat and per-protocol analyses were performed. RESULTS: Six hundred sixty-nine patients enrolled (35 UK centers, 2008-2014); mean tumor size was 2.9 cm, and 358 (54%) were low risk (< 4 cm, no rete testis invasion). With a median follow-up of 72 months, 82 (12%) relapsed. Stage ≥ IIC relapse was rare (10 events). Although statistically noninferior, more events occurred with three scans (nine, 2.8%) versus seven scans (one, 0.3%): 2.5% absolute increase, 90% CI (1.0 to 4.1). Only 4/9 could have potentially been detected earlier with seven scans. Noninferiority of MRI versus CT was also shown; fewer events occurred with MRI (two [0.6%] v eight [2.6%]), 1.9% decrease (-3.5 to -0.3). Per-protocol analyses confirmed noninferiority. Five-year survival was 99%, with no tumor-related deaths. CONCLUSION: Surveillance is a safe management approach-advanced relapse is rare, salvage treatment successful, and outcomes excellent, regardless of imaging frequency or modality. MRI can be recommended to reduce irradiation; and no adverse impact on long-term outcomes was seen with a reduced schedule.