The number of new cases of type 1 and type 2 diabetes in U.S. children and adolescents increased at constant rates from 2002 through 2015, and the rates of increase were generally higher in racial/ethnic minority populations than in whites.
Background Two apolipoprotein L1 gene (APOL1) renal-risk variants in donors and African American (AA) recipient race are associated with worse allograft survival in deceased-donor kidney transplantation (DDKT) from AA donors. To detect other factors impacting allograft survival from deceased AA kidney donors, APOL1 renal-risk variants were genotyped in additional AA kidney donors. Methods The APOL1 genotypes were linked to outcomes in 478 newly analyzed DDKTs in the Scientific Registry of Transplant Recipients. Multivariate analyses accounting for recipient age, sex, race, panel-reactive antibody level, HLA match, cold ischemia time, donor age, and expanded criteria donation were performed. These 478 transplantations and 675 DDKTs from a prior report were jointly analyzed. Results Fully adjusted analyses limited to the new 478 DDKTs replicated shorter renal allograft survival in recipients of APOL1 2-renal-risk-variant kidneys (hazard ratio [HR], 2.00; P = 0.03). Combined analysis of 1153 DDKTs from AA donors revealed donor APOL1 high-risk genotype (HR, 2.05; P = 3 × 10−4), older donor age (HR, 1.18; P = 0.05), and younger recipient age (HR, 0.70; P = 0.001) adversely impacted allograft survival. Although prolonged allograft survival was seen in many recipients of APOL1 2-renal-risk-variant kidneys, follow-up serum creatinine concentrations were higher than that in recipients of 0/1 APOL1 renal-risk-variant kidneys. A competing risk analysis revealed that APOL1 impacted renal allograft survival, but not recipient survival. Interactions between donor age and APOL1 genotype on renal allograft survival were nonsignificant. Conclusions Shorter renal allograft survival is reproducibly observed after DDKT from APOL1 2-renal-risk-variant donors. Younger recipient age and older donor age have independent adverse effects on renal allograft survival.
Background Stratification 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. Methods We 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. Findings We 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. Interpretation Semantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC. Funding NIH (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.
Much 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. APOLLO will evaluate outcomes from 2614 deceased kidney donor-recipient pairs, as well as additional living-kidney donor-recipient pairs and unpaired deceased-donor kidneys. The 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. This 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.
Transcriptomic studies hold great potential towards understanding the human aging process. Previous transcriptomic studies have identified many genes with age-associated expression levels; however, small samples sizes and mixed cell types often make these results difficult to interpret. Using transcriptomic profiles in CD14+ monocytes from 1,264 participants of the Multi-Ethnic Study of Atherosclerosis (aged 55–94 years), we identified 2,704 genes differentially expressed with chronological age (false discovery rate, FDR ≤ 0.001). We further identified six networks of co-expressed genes that included prominent genes from three pathways: protein synthesis (particularly mitochondrial ribosomal genes), oxidative phosphorylation, and autophagy, with expression patterns suggesting these pathways decline with age. Expression of several chromatin remodeler and transcriptional modifier genes strongly correlated with expression of oxidative phosphorylation and ribosomal protein synthesis genes. 17% of genes with age-associated expression harbored CpG sites whose degree of methylation significantly mediated the relationship between age and gene expression (p < 0.05). Lastly, 15 genes with age-associated expression were also associated (FDR ≤ 0.01) with pulse pressure independent of chronological age. Comparing transcriptomic profiles of CD14+ monocytes to CD4+ T cells from a subset (n = 423) of the population, we identified 30 age-associated (FDR < 0.01) genes in common, while larger sets of differentially expressed genes were unique to either T cells (188 genes) or monocytes (383 genes). At the pathway level, a decline in ribosomal protein synthesis machinery gene expression with age was detectable in both cell types. An overall decline in expression of ribosomal protein synthesis genes with age was detected in CD14+ monocytes and CD4+ T cells, demonstrating that some patterns of aging are likely shared between different cell types. Our findings also support cell-specific effects of age on gene expression, illustrating the importance of using purified cell samples for future transcriptomic studies. Longitudinal work is required to establish the relationship between identified age-associated genes/pathways and aging-related diseases.
Coronary artery calcified atherosclerotic plaque (CAC) predicts cardiovascular disease (CVD). Despite exposure to more severe conventional CVD risk factors, African Americans (AAs) are less likely to develop CAC, and when they do, have markedly lower levels than European Americans. Genetic factors likely contribute to the observed ethnic differences. To identify genes associated with CAC in AAs with type 2 diabetes (T2D), a genome-wide association study (GWAS) was performed using the Illumina 5 M chip in 691 African American-Diabetes Heart Study participants (AA-DHS), with replication in 205 Jackson Heart Study (JHS) participants with T2D. Genetic association tests were performed on the genotyped and 1000 Genomes-imputed markers separately for each study, and combined in a meta-analysis. Single nucleotide polymorphisms (SNPs), rs11353135 (2q22.1), rs16879003 (6p22.3), rs5014012, rs58071836 and rs10244825 (all on chromosome 7), rs10918777 (9q31.2), rs13331874 (16p13.3) and rs4459623 (18q12.1) were associated with presence and/or quantity of CAC in the AA-DHS and JHS, with meta-analysis p-values ≤8.0 × 10−7. The strongest result in AA-DHS alone was rs6491315 in the 13q32.1 region (parameter estimate (SE) = −1.14 (0.20); p-value = 9.1 × 10−9). This GWAS peak replicated a previously reported AA-DHS CAC admixture signal (rs7492028, LOD score 2.8). Genetic association between SNPs on chromosomes 2, 6, 7, 9, 16 and 18 and CAC were detected in AAs with T2D from AA-DHS and replicated in the JHS. These data support a role for genetic variation on these chromosomes as contributors to CAC in AAs with T2D, as well as to variation in CAC between populations of African and European ancestry.