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Objective: To evaluate changes in insulin pump use over two decades in a national U.S. sample. Research Design and Methods: We used data from the SEARCH for Diabetes in Youth study to perform a serial cross-sectional analysis to evaluate changes in insulin pump use in participants

BackgroundStratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested.MethodsWe present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning.FindingsWe found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems.InterpretationSemantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.FundingNIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.

We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P

IntroductionAPOL1 G1 and G2 nephropathy-risk variants cause mitochondrial dysfunction and contribute to kidney disease. Analyses were performed to determine the genetic regulation of APOL1 and elucidate potential mechanisms in APOL1-nephropathy.MethodsA global gene expression analysis was performed in human primary renal tubule cell lines derived from 50 African American individuals. Follow-up gene knock out, cell-based rescue, and microscopy experiments were performed.ResultsAPOL1 genotypes did not alter APOL1 expression levels in the global gene expression analysis. Expression quantitative trait locus (eQTL) analysis in polyinosinic-polycytidylic acid (poly IC)-stimulated renal tubule cells revealed that single nucleotide polymorphism (SNP) rs513349 adjacent to BAK1 was a trans eQTL for APOL1 and a cis eQTL for BAK1; APOL1 and BAK1 were co-expressed in cells. BAK1 knockout in a human podocyte cell line resulted in diminished APOL1 protein, supporting a pivotal effect for BAK1 on APOL1 expression. Because BAK1 is involved in mitochondrial dynamics, mitochondrial morphology was examined in primary renal tubule cells and HEK293 Tet-on cells of various APOL1 genotypes. Mitochondria in APOL1 wild-type (G0G0) tubule cells maintained elongated morphology when stimulated by low-dose poly IC, whereas those with G1G1, G2G2, and G1G2 genotypes appeared to fragment. HEK293 Tet-on cells overexpressing APOL1 G0, G1, and G2 were created; G0 cells appeared to promote mitochondrial fusion, whereas G1 and G2 induced mitochondrial fission. The mitochondrial dynamic regulator Mdivi-1 significantly preserved cell viability and mitochondrial cristae structure and reversed mitochondrial fission induced by overexpression of G1 and G2.ConclusionResults suggest the mitochondrial fusion/fission pathway may be a therapeutic target in APOL1-nephropathy.

IntroductionMuch of the higher risk for end-stage kidney disease (ESKD) in African American individuals relates to ancestry-specific variation in the apolipoprotein L1 gene (APOL1). Relative to kidneys from European American deceased-donors, kidneys from African American deceased-donors have shorter allograft survival and African American living-kidney donors more often develop ESKD. The National Institutes of Health (NIH)-sponsored APOL1 Long-term Kidney Transplantation Outcomes Network (APOLLO) is prospectively assessing kidney allograft survival from donors with recent African ancestry based on donor and recipient APOL1 genotypes.MethodsAPOLLO will evaluate outcomes from 2614 deceased kidney donor-recipient pairs, as well as additional living-kidney donor-recipient pairs and unpaired deceased-donor kidneys.ResultsThe United Network for Organ Sharing (UNOS), Association of Organ Procurement Organizations, American Society of Transplantation, American Society for Histocompatibility and Immunogenetics, and nearly all U.S. kidney transplant programs, organ procurement organizations (OPOs), and histocompatibility laboratories are participating in this observational study. APOLLO employs a central institutional review board (cIRB) and maintains voluntary partnerships with OPOs and histocompatibility laboratories. A Community Advisory Council composed of African American individuals with a personal or family history of kidney disease has advised the NIH Project Office and Steering Committee since inception. UNOS is providing data for outcome analyses.ConclusionThis article describes unique aspects of the protocol, design, and performance of APOLLO. Results will guide use of APOL1 genotypic data to improve the assessment of quality in deceased-donor kidneys and could increase numbers of transplanted kidneys, reduce rates of discard, and improve the safety of living-kidney donation.

Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria.

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.

ObjectiveGenetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS.Research design and methodsWe generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant (P < 5.0 × 10-8) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci (P < 2.79 × 10-5).ResultsAfrican-specific (HLA-DQA1*03:01-HLA-DQB1*02:01) and known European-ancestry HLA haplotypes (HLA-DRB1*03:01-HLA-DQA1*05:01-HLA-DQB1*02:01, HLA-DRB1*04:01-HLA-DQA1*03:01-HLA-DQB1*03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts.ConclusionsGenetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.

PurposeTo describe the study protocol and baseline characteristics of the African Descent and Glaucoma Evaluation Study (ADAGES) III.DesignCross-sectional, case-control study.ParticipantsThree thousand two hundred sixty-six glaucoma patients and control participants without glaucoma of African or European descent were recruited from 5 study centers in different regions of the United States.MethodsIndividuals of African descent (AD) and European descent (ED) with primary open-angle glaucoma (POAG) and control participants completed a detailed demographic and medical history interview. Standardized height, weight, and blood pressure measurements were obtained. Saliva and blood samples to provide serum, plasma, DNA, and RNA were collected for standardized processing. Visual fields, stereoscopic disc photographs, and details of the ophthalmic examination were obtained and transferred to the University of California, San Diego, Data Coordinating Center for standardized processing and quality review.Main outcome measuresParticipant gender, age, race, body mass index, blood pressure, history of smoking and alcohol use in POAG patients and control participants were described. Ophthalmic measures included intraocular pressure, visual field mean deviation, central corneal thickness, glaucoma medication use, or past glaucoma surgery. Ocular conditions, including diabetic retinopathy, age-related macular degeneration, and past cataract surgery, were recorded.ResultsThe 3266 ADAGES III study participants in this report include 2146 AD POAG patients, 695 ED POAG patients, 198 AD control participants, and 227 ED control participants. The AD POAG patients and control participants were significantly younger (both, 67.4 years) than ED POAG patients and control participants (73.4 and 70.2 years, respectively). After adjusting for age, AD POAG patients had different phenotypic characteristics compared with ED POAG patients, including higher intraocular pressure, worse visual acuity and visual field mean deviation, and thinner corneas (all P < 0.001). Family history of glaucoma did not differ between AD and ED POAG patients.ConclusionsWith its large sample size, extensive specimen collection, and deep phenotyping of AD and ED glaucoma patients and control participants from different regions in the United States, the ADAGES III genomics study will address gaps in our knowledge of the genetics of POAG in this high-risk population.

PurposeTo find genetic contributions to glaucoma in African Americans.DesignCross-sectional, case-control study.ParticipantsOne thousand eight hundred seventy-five primary open-angle glaucoma (POAG) patients and 1709 controls, self-identified as being of African descent (AD), from the African Descent and Glaucoma Evaluation Study (ADAGES) III and Wake Forest School of Medicine.MethodsMegaChip genotypes were imputed to Thousand Genomes data. Association of single nucleotide polymorphisms (SNPs) with POAG and advanced POAG was tested by linear mixed model correcting for relatedness and population stratification. Genetic risk scores were tested by receiver operator characteristic curves (ROC-AUCs).Main outcome measuresPrimary open-angle glaucoma defined by visual field loss without other nonocular conditions (n = 1875). Advanced POAG was defined by age-based mean deviation of visual field (n = 946).ResultsEighteen million two hundred eighty-one thousand nine hundred twenty SNPs met imputation quality of r2 > 0.7 and minor allele frequency > 0.005. Association of a novel locus, EN04, was observed for advanced POAG (rs185815146 β, 0.36; standard error, 0.065; P < 3×10-8). For POAG, an AD signal was observed at the 9p21 European descent (ED) POAG signal (rs79721419; P < 6.5×10-5) independent of the previously observed 9p21 ED signal (rs2383204; P < 2.3×10-5) by conditional analyses. An association with POAG in FNDC3B (rs111698934; P < 3.9×10-5) was observed, not in linkage disequilibrium (LD) with the previously reported ED SNP. Additional previously identified loci associated with POAG in persons of AD were: 8q22, AFAP1, and TMC01. An AUC of 0.62 was observed with an unweighted genetic risk score comprising 11 SNPs in candidate genes. Two additional risk scores were studied by using a penalized matrix decomposition with cross-validation; risk scores of 50 and 400 SNPs were identified with ROC of AUC = 0.74 and AUC = 0.94, respectively.ConclusionsA novel association with advanced POAG in the EN04 locus was identified putatively in persons of AD. In addition to this finding, this genome-wide association study in POAG patients of AD contributes to POAG genetics by identification of novel signals in prior loci (9p21), as well as advancing the fine mapping of regions because of shorter average LD (FNDC3B). Although not useful without confirmation and clinical trials, the use of genetic risk scores demonstrated that considerable AD-specific genetic information remains in these data.

Background: This study aimed to examine the prevalence of inappropriate tight glycemic control in older adults with type 2 diabetes and other chronic conditions in New York City, and to identify factors associated with this practice. Methods: We conducted a retrospective cohort study using the INSIGHT Clinical Research Network. The study population included 11,728 and 15,196 older adults in New York City (age ≥ 75 years) with a diagnosis of type 2 diabetes, and at least one other chronic medical condition, in 2017 and 2022, respectively. The main outcome of interest was inappropriate tight glycemic control, defined as HbA1c <7.0% (<53 mmol/mol) with prescription of at least one high‐risk agent (insulin or insulin secretagogue). Results: The proportion of older adults with inappropriate tight glycemic control decreased by nearly 19% over a five‐year period (19.4% in 2017 to 15.8% in 2022). There was a significant decrease in insulin (27.8% in 2017; 24.3% in 2022) and sulfonylurea (29.4% in 2017; 21.7% in 2022) medication prescription, and increase in use of GLP‐1 agonists (1.8% in 2017; 11.4% in 2022) and SGLT‐2 inhibitors (5.8% in 2017; 25.1% in 2022), among the total population. Factors associated with inappropriate tight glycemic control in 2022 included history of heart failure (adjusted odds ratio [aOR] 1.38), chronic kidney disease ([aOR] 1.93), colorectal cancer ([aOR] 1.38), acute myocardial infarction ([aOR] 1.28), "other" ([aOR] 0.72) or "unknown" ([aOR] 0.72) race, and a point increase in BMI ([aOR] 0.98). Conclusions: We found an encouraging trend toward less use of high‐risk medication strategies for older adults with type 2 diabetes and multiple chronic conditions. However, one in six patients in 2022 still had inappropriate tight glycemic control, indicating a need for continued efforts to optimize diabetes management in this population. [ABSTRACT FROM AUTHOR]

Background and Purpose- White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods- In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results- At 17q25, we confirmed the association of multiple common variants in TRIM65, FBF1, and ACOX1 ( P

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

BackgroundThe presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample.ResultsA fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy.ConclusionsThe identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations.

BACKGROUND Medicare supplement insurance, or Medigap, covers 21% of Medicare beneficiaries. Despite offsetting some out-of-pocket (OOP) expenses, remaining OOP costs may pose a barrier to medication adherence. This study aims to evaluate how OOP costs and insurance plan types influence medication adherence among beneficiaries covered by Medicare supplement plans. METHODS We conducted a retrospective analysis of the Merative MarketScan Medicare Supplement Database (2017–2019) in Medigap enrollees (≥65 years) with hypertension. The proportion of days covered (PDC) was a continuous measure of medication adherence and was also dichotomized (PDC ≥0.8) to quantify adequate adherence. Beta-binomial and logistic regression models were used to estimate associations between these outcomes and insurance plan type and log-transformed OOP costs, adjusting for patient characteristics. RESULTS Among 27,407 patients with hypertension, the average PDC was 0.68 ± 0.31; 47.5% achieved adequate adherence. A mean $1 higher in 30-day OOP costs were associated with a 0.06 (95% confidence intervals [CIs]: −0.09 to −0.03) lower probability of adequate adherence, or a 5% (95% CI: 4%–7%) decrease in PDC. Compared with comprehensive plan enrollees, the odds of adequate adherence were lower among those with point-of-service plans (odds ratio [OR]: 0.69, 95% CI: 0.62–0.77), but higher among those with preferred provider organization (PPO) plans (OR: 1.08, 95% CI: 1.01–1.15). Moreover, the association between OOP costs and PDC was significantly greater for PPO enrollees. CONCLUSIONS While Medicare supplement insurance alleviates some OOP costs, different insurance plans and remaining OOP costs influence medication adherence. Reducing patient cost-sharing may improve medication adherence. [ABSTRACT FROM AUTHOR]

Objectives. Cardiovascular disease (CVD) is the leading cause of death and disability among persons with diabetes. Early intervention on cardiovascular risk factors (CRFs) is important in reducing CVD burden. The SEARCH for Diabetes in Youth study assessed CRFs in incident cohorts of youth aged <20 years established from 2002 to 2016. Research Design and Methods. Regression models assessed trends over each incident year for lipids (total cholesterol (TC), HDL‐c, LDL‐c, triglycerides (TG), VLDL‐c, and non‐HDL‐c), kidney function (albumin/creatinine ratio (ACR) ≥30 and ≥300, cystatin C, serum creatinine and estimated glomerular filtration rate (eGFR)), systolic and diastolic blood pressure (BP) z‐scores, BMI z‐score, waist circumference (WC), and an inflammatory marker (C‐reactive protein (CRP)). Models were stratified by diabetes type (type 1 diabetes (T1D), N = 4,600; type 2 diabetes (T2D), N = 932) and adjusted for age at diagnosis, sex, race/ethnicity, and diabetes duration. An interaction analysis assessed differential time trends by type. Results. For youth with T1D, all CRFs significantly improved over time, with the exception of ACR > 300, cystatin C, serum creatinine, eGFR, and CRP. For youth with T2D, TC, LDL‐c, and non‐HDL‐c significantly improved, while eGFR, BMI z‐score, and CRP significantly worsened. Significant differences in trends over time by type were seen for TC, HDL‐c, BMI z‐score, BP z‐scores, WC, and CRP. Conclusions. Overall, improvements in CRFs were more often observed in youth with T1D. Youth with T2D had worsening trends over time in BMI z‐score, CRP, and kidney function. Further research is needed to better understand these trends and their implications for long‐term CVD risk. [ABSTRACT FROM AUTHOR]

In this study we examined the association between payor type, a proxy for health-care affordability, and presenting COVID-19 disease severity among 2108 polymerase chain reaction–positive nonelderly patients admitted to an acute-care hospital between March 1 and June 30, 2020. The adjacent-category logit model was used to fit pairwise odds of individuals' having (1) an asymptomatic-to-mild modified sequential organ failure assessment (mSOFA) score (0-3) versus a moderate-to-severe mSOFA score (4-7) and (2) a moderate-to-severe mSOFA score (4-7) versus a critical mSOFA score (>7). Despite representing the smallest population, Medicare recipients experienced the highest in-hospital death rate (19%), a rate twice that of the privately insured. The uninsured had the highest rate of critical mSOFA score on admission and had twice the odds of presenting with a critical illness when compared with the privately insured (odds ratio = 2.08, P =.03). Because payor type was statistically related to the most severe presentations of COVID-19, we question whether policy changes affecting health-care affordability might have prevented deaths and rationing of scarce resources, such as intensive care unit beds and ventilators. [ABSTRACT FROM AUTHOR]

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.

Apolipoprotein L1 gene (APOL1) G1 and G2 coding variants are strongly associated with chronic kidney disease (CKD) in African Americans (AAs). Here APOL1 association was tested with baseline estimated glomerular filtration rate (eGFR), urine albumin:creatinine ratio (UACR), and prevalent cardiovascular disease (CVD) in 2571 AAs from the Systolic Blood Pressure Intervention Trial (SPRINT), a trial assessing effects of systolic blood pressure reduction on renal and CVD outcomes. Logistic regression models that adjusted for potentially important confounders tested for association between APOL1 risk variants and baseline clinical CVD (myocardial infarction, coronary, or carotid artery revascularization) and CKD (eGFR under 60 ml/min per 1.73 m(2) and/or UACR over 30 mg/g). AA SPRINT participants were 45.3% female with a mean (median) age of 64.3 (63) years, mean arterial pressure 100.7 (100) mm Hg, eGFR 76.3 (77.1) ml/min per 1.73 m(2), and UACR 49.9 (9.2) mg/g, and 8.2% had clinical CVD. APOL1 (recessive inheritance) was positively associated with CKD (odds ratio 1.37, 95% confidence interval 1.08-1.73) and log UACR estimated slope (β) 0.33) and negatively associated with eGFR (β -3.58), all significant. APOL1 risk variants were not significantly associated with prevalent CVD (1.02, 0.82-1.27). Thus, SPRINT data show that APOL1 risk variants are associated with mild CKD but not with prevalent CVD in AAs with a UACR under 1000 mg/g.

Objectives To characterize the complex interplay between multiple clinical conditions in a time-to-event analysis framework using data from multiple hospitals, we developed two novel one-shot distributed algorithms for competing risk models (ODACoR). By applying our algorithms to the EHR data from eight national children's hospitals, we quantified the impacts of a wide range of risk factors on the risk of post-acute sequelae of SARS-COV-2 (PASC) among children and adolescents. Materials and Methods Our ODACoR algorithms are effectively executed due to their devised simplicity and communication efficiency. We evaluated our algorithms via extensive simulation studies as applications to quantification of the impacts of risk factors for PASC among children and adolescents using data from eight children's hospitals including the Children's Hospital of Philadelphia, Cincinnati Children's Hospital Medical Center, Children's Hospital of Colorado covering over 6.5 million pediatric patients. The accuracy of the estimation was assessed by comparing the results from our ODACoR algorithms with the estimators derived from the meta-analysis and the pooled data. Results The meta-analysis estimator showed a high relative bias (∼40%) when the clinical condition is relatively rare (∼0.5%), whereas ODACoR algorithms exhibited a substantially lower relative bias (∼0.2%). The estimated effects from our ODACoR algorithms were identical on par with the estimates from the pooled data, suggesting the high reliability of our federated learning algorithms. In contrast, the meta-analysis estimate failed to identify risk factors such as age, gender, chronic conditions history, and obesity, compared to the pooled data. Discussion Our proposed ODACoR algorithms are communication-efficient, highly accurate, and suitable to characterize the complex interplay between multiple clinical conditions. Conclusion Our study demonstrates that our ODACoR algorithms are communication-efficient and can be widely applicable for analyzing multiple clinical conditions in a time-to-event analysis framework. [ABSTRACT FROM AUTHOR]