Optimal population-specific HLA imputation with dimension reduction.

Human genomics has quickly evolved, powering genome-wide association studies (GWASs). SNP-based GWASs cannot capture the intense polymorphism of HLA genes, highly associated with disease susceptibility. There are methods to statistically impute HLA genotypes from SNP-genotypes data, but lack of diversity in reference panels hinders their performance. We evaluated the accuracy of the 1000 Genomes data as a reference panel for imputing HLA from admixed individuals of African and European ancestries, focusing on (a) the full dataset, (b) 10 replications from 6 populations, and (c) 19 conditions for the custom reference panels. The full dataset outperformed smaller models, with a good F1-score of 0.66 for HLA-B. However, custom models outperformed the multiethnic or population models of similar size (F1-scores up to 0.53, against up to 0.42). We demonstrated the importance of using genetically specific models for imputing populations, which are currently underrepresented in public datasets, opening the door to HLA imputation for every genetic population.

18th International HLA and Immunogenetics Workshop: Report on the SNP-HLA Reference Consortium (SHLARC) component.

The SNP-HLA Reference Consortium (SHLARC), a component of the 18th International HLA and Immunogenetics Workshop, is aimed at collecting diverse and extensive human leukocyte antigen (HLA) data to create custom reference panels and enhance HLA imputation techniques. Genome-wide association studies (GWAS) have significantly contributed to identifying genetic associations with various diseases. The HLA genomic region has emerged as the top locus in GWAS, particularly in immune-related disorders. However, the limited information provided by single nucleotide polymorphisms (SNPs), the hallmark of GWAS, poses challenges, especially in the HLA region, where strong linkage disequilibrium (LD) spans several megabases. HLA imputation techniques have been developed using statistical inference in response to these challenges. These techniques enable the prediction of HLA alleles from genotyped GWAS SNPs. Here we present the SHLARC activities, a collaborative effort to create extensive, and multi-ethnic reference panels to enhance HLA imputation accuracy.

The HLA-B*57:01 allele corresponds to a very large MHC haploblock likely explaining its massive effect for HIV-1 elite control.

Introduction: We have reanalyzed the genomic data of the International Collaboration for the Genomics of HIV (ICGH), centering on HIV-1 Elite Controllers. Methods: We performed a genome-wide Association Study comparing 543 HIV Elite Controllers with 3,272 uninfected controls of European descent. Using the latest database for imputation, we analyzed 35,552 Single Nucleotide Polymorphisms (SNPs) within the Major Histocompatibility Complex (MHC) region. Results: Our analysis identified 2,626 SNPs significantly associated (p<5. 10-8) with elite control of HIV-1 infection, including well-established MHC signals such as the rs2395029-G allele which tags HLA-B*57:01. A thorough investigation of SNPs in linkage disequilibrium with rs2395029 revealed an extensive haploblock spanning 1.9 megabases in the MHC region tagging HLA-B*57:01, comprising 379 SNP alleles impacting 72 genes. This haploblock contains damaging variations in proteins like NOTCH4 and DXO and is also associated with a strong differential pattern of expression of multiple MHC genes such as HLA-B, MICB, and ZBTB12. The study was expanded to include two cohorts of seropositive African-American individuals, where a haploblock tagging the HLA-B*57:03 allele was similarly associated with control of viral load. The mRNA expression profile of this haploblock in African Americans closely mirrored that in the European cohort. Discussion: These findings suggest that additional molecular mechanisms beyond the conventional antigen-presenting role of class I HLA molecules may contribute to the observed influence of HLA-B*57:01/B*57:03 alleles on HIV-1 elite control. Overall, this study has uncovered a large haploblock associated with HLA-B*57 alleles, providing novel insights into their massive effect on HIV-1 elite control.

Immunogenetics of HLA-B: SNP, allele, and haplotype diversity in populations from different continents and ancestry backgrounds.

HLA-B is among the most variable gene in the human genome. This gene encodes a key molecule for antigen presentation to CD8+ T lymphocytes and NK cell modulation. Despite the myriad of studies evaluating its coding region (with an emphasis on exons 2 and 3), few studies evaluated introns and regulatory sequences in real population samples. Thus, HLA-B variability is probably underestimated. We applied a bioinformatics pipeline tailored for HLA genes on 5347 samples from 80 different populations, which includes more than 1000 admixed Brazilians, to evaluate the HLA-B variability (SNPs, indels, MNPs, alleles, and haplotypes) in exons, introns, and regulatory regions. We observed 610 variable sites throughout HLA-B; the most frequent variants are shared worldwide. However, the haplotype distribution is geographically structured. We detected 920 full-length haplotypes (exons, introns, and untranslated regions) encoding 239 different protein sequences. HLA-B gene diversity is higher in admixed populations and Europeans while lower in African ancestry individuals. Each HLA-B allele group is associated with specific promoter sequences. This HLA-B variation resource may improve HLA imputation accuracy and disease-association studies and provide evolutionary insights regarding HLA-B genetic diversity in human populations.

Patient-centric synthetic data generation, no reason to risk re-identification in biomedical data analysis.

While nearly all computational methods operate on pseudonymized personal data, re-identification remains a risk. With personal health data, this re-identification risk may be considered a double-crossing of patients' trust. Herein, we present a new method to generate synthetic data of individual granularity while holding on to patients' privacy. Developed for sensitive biomedical data, the method is patient-centric as it uses a local model to generate random new synthetic data, called an "avatar data", for each initial sensitive individual. This method, compared with 2 other synthetic data generation techniques (Synthpop, CT-GAN), is applied to real health data with a clinical trial and a cancer observational study to evaluate the protection it provides while retaining the original statistical information. Compared to Synthpop and CT-GAN, the Avatar method shows a similar level of signal maintenance while allowing to compute additional privacy metrics. In the light of distance-based privacy metrics, each individual produces an avatar simulation that is on average indistinguishable from 12 other generated avatar simulations for the clinical trial and 24 for the observational study. Data transformation using the Avatar method both preserves, the evaluation of the treatment's effectiveness with similar hazard ratios for the clinical trial (original HR = 0.49 [95% CI, 0.39-0.63] vs. avatar HR = 0.40 [95% CI, 0.31-0.52]) and the classification properties for the observational study (original AUC = 99.46 (s.e. 0.25) vs. avatar AUC = 99.84 (s.e. 0.12)). Once validated by privacy metrics, anonymous synthetic data enable the creation of value from sensitive pseudonymized data analyses by tackling the risk of a privacy breach.

KiT-GENIE, the French genetic biobank of kidney transplantation.

KiT-GENIE is a monocentric DNA biobank set up to consolidate the very rich and homogeneous DIVAT French cohort of kidney donors and recipients (D/R) in order to explore the molecular factors involved in kidney transplantation outcomes. We collected DNA samples for kidney transplantations performed in Nantes, and we leveraged GWAS genotyping data for securing high-quality genetic data with deep SNP and HLA annotations through imputations and for inferring D/R genetic ancestry. Overall, the biobank included 4217 individuals (n = 1945 D + 2,272 R, including 1969 D/R pairs), 7.4 M SNPs and over 200 clinical variables. KiT-GENIE represents an accurate snapshot of kidney transplantation clinical practice in Nantes between 2002 and 2018, with an enrichment in living kidney donors (17%) and recipients with focal segmental glomerulosclerosis (4%). Recipients were predominantly male (63%), of European ancestry (93%), with a mean age of 51yo and 86% experienced their first graft over the study period. D/R pairs were 93% from European ancestry, and 95% pairs exhibited at least one HLA allelic mismatch. The mean follow-up time was 6.7 years with a hindsight up to 25 years. Recipients experienced biopsy-proven rejection and graft loss for 16.6% and 21.3%, respectively. KiT-GENIE constitutes one of the largest kidney transplantation genetic cohorts worldwide to date. It includes homogeneous high-quality clinical and genetic data for donors and recipients, hence offering a unique opportunity to investigate immunogenetic and genetic factors, as well as donor-recipient interactions and mismatches involved in rejection, graft survival, primary disease recurrence and other comorbidities.

Identification of Novel Genetic Risk Factors for Focal Segmental Glomerulosclerosis in Children: Results From the Chronic Kidney Disease in Children (CKiD) Cohort.

RATIONALE & OBJECTIVE: Focal segmental glomerulosclerosis (FSGS) is a major cause of pediatric nephrotic syndrome, and African Americans exhibit an increased risk for developing FSGS compared with other populations. Predisposing genetic factors have previously been described in adults. Here we performed genomic screening of primary FSGS in a pediatric African American population. STUDY DESIGN: Prospective cohort with case-control genetic association study design. SETTING & PARTICIPANTS: 140 African American children with chronic kidney disease from the Chronic Kidney Disease in Children (CKiD) cohort, including 32 cases with FSGS. PREDICTORS: Over 680,000 common single-nucleotide polymorphisms (SNPs) were tested for association. We also ran a pathway enrichment analysis and a human leucocyte antigen (HLA)-focused association study. OUTCOME: Primary biopsy-proven pediatric FSGS. ANALYTICAL APPROACH: Multivariate logistic regression models. RESULTS: The genome-wide association study revealed 169 SNPs from 14 independent loci significantly associated with FSGS (false discovery rate [FDR]<5%). We observed notable signals for genetic variants within the APOL1 (P=8.6×10-7; OR, 25.8 [95% CI, 7.1-94.0]), ALMS1 (P=1.3×10-7; 13.0% in FSGS cases vs 0% in controls), and FGFR4 (P=4.3×10-6; OR, 24.8 [95% CI, 6.3-97.7]) genes, all of which had previously been associated with adult FSGS, kidney function, or chronic kidney disease. We also highlighted novel, functionally relevant genes, including GRB2 (which encodes a slit diaphragm protein promoting podocyte structure through actin polymerization) and ITGB1 (which is linked to renal injuries). Our results suggest a major role for immune responses and antigen presentation in pediatric FSGS through (1) associations with SNPs in PTPRJ (or CD148, P=3.5×10-7), which plays a role in T-cell receptor signaling, (2) HLA-DRB1∗11:01 association (P=6.1×10-3; OR, 4.5 [95% CI, 1.5-13.0]), and (3) signaling pathway enrichment (P=1.3×10-6). LIMITATIONS: Sample size and no independent replication cohort with genomic data readily available. CONCLUSIONS: Our genetic study has identified functionally relevant risk factors and the importance of immune regulation for pediatric primary FSGS, which contributes to a better description of its molecular pathophysiological mechanisms. PLAIN-LANGUAGE SUMMARY: We assessed the genetic risk factors for primary focal segmental glomerulosclerosis (FSGS) by simultaneously testing over 680,000 genetic markers spread across the genome in 140 children, including 32 with FSGS lesions. Fourteen independent genetic regions were significantly associated with pediatric FSGS, including APOL1 and ALMS1-NAT8, which were previously found to be associated with FSGS and chronic kidney diseases in adults. Novel genes with relevant biological functions were also highlighted, such as GRB2 and FGFR4, which play a role in the kidney filtration barrier and in kidney cell differentiation, respectively. Finally, we revealed the importance of immune regulation in pediatric FSGS through associations involving cell surface proteins presenting antigens to the immune system and interacting with T-cell receptors.

A Phase I/IIa study of autologous tolerogenic dendritic cells immunotherapy in kidney transplant recipients.

Kidney transplant survival is shortened by chronic rejection and side effects of standard immunosuppressive drugs. Cell-based immunotherapy with tolerogenic dendritic cells has long been recognized as a promising approach to reduce general immunosuppression. Published trials report the safety and the absence of therapy-related adverse reactions in patients treated with tolerogenic dendritic cells suffering from several inflammatory diseases. Here, we present the first phase I clinical trial results using human autologous tolerogenic dendritic cells (ATDC) in kidney transplantation. Eight patients received ATDC the day before transplantation in conjunction with standard steroids, mycophenolate mofetil and tacrolimus immunosuppression with an option to taper mycophenolate mofetil. ATDC preparations were manufactured in a Good Manufacturing Practice-compliant facility and fulfilled cell count, viability, purity and identity criteria for release. A control group of nine patients received the same standard immunosuppression, except basiliximab induction replaced ATDC therapy and mycophenolate tapering was not allowed. During the three-year follow-up, no deaths occurred and there was 100% graft survival. No significant increase of adverse events was associated with ATDC infusion. Episodes of rejection were observed in two patients from the ATDC group and one patient from the control group. However, all rejections were successfully treated by glucocorticoids. Mycophenolate was successfully reduced/stopped in five patients from the ATDC group, allowing tacrolimus monotherapy for two of them. Regarding immune monitoring, reduced CD8 T cell activation markers and increased Foxp3 expression were observed in the ATDC group. Thus, our results demonstrate ATDC administration safety in kidney-transplant recipients.

Multiple sclerosis clinical decision support system based on projection to reference datasets.

OBJECTIVE: Multiple sclerosis (MS) is a multifactorial disease with increasingly complicated management. Our objective is to use on-demand computational power to address the challenges of dynamically managing MS. METHODS: A phase 3 clinical trial data (NCT00906399) were used to contextualize the medication efficacy of peg-interferon beta-1a vs placebo on patients with relapsing-remitting MS (RRMS). Using a set of reference patients (PORs), selected based on adequate features similar to those of an individual patient, we visualize disease activity by measuring the percentage of relapses, accumulation of new T2 lesions on MRI, and worsening EDSS during the clinical trial. RESULTS: We developed MS Vista, a functional prototype of clinical decision support system (CDSS), with a user-centered design and distributed infrastructure. MS Vista shows the medication efficacy of peginterferon beta-1a versus placebo for each individual patient with RRMS. In addition, MS Vista initiated the integration of a longitudinal magnetic resonance imaging (MRI) viewer and interactive dual physician-patient data display to facilitate communication. INTERPRETATION: The pioneer use of PORs for each individual patient enables personalized analytics sustaining the dialog between neurologists, patients and caregivers with quantified evidence.

APOL1 Renal Risk Variants and Sickle Cell Trait Associations With Reduced Kidney Function in a Large Congolese Population-Based Study.

Introduction: APOL1, GSTM1 risk variants, and sickle cell trait (SCT) are associated with chronic kidney disease (CKD) among African Americans (AAs). Nevertheless, such evidence remains scarce in sub-Saharan Africa (SSA) populations. Methods: In a cross-sectional study, we evaluated the prevalence of these risk variants and their association with estimated glomerular filtration rate (eGFR), albuminuria, and CKD in urban (n = 587) and rural (n = 730) adults from South-Kivu, DR Congo (DRC). Furthermore, we evaluated APOL1 recessive model (high risk [HR] vs. low risk [LR]), SCT carriage, and the active versus inactive GSTM1 genotypes. Results: The frequencies of the APOL1 G1 and G2 alleles were 8.7% and 9.1%, respectively, and 3.2% carried the HR genotype. SCT and GSTM1 null allele frequencies were 3.8% and 51.2%, respectively. APOL1 HR was associated with lower eGFR (P = 0.047, odds ratio [OR] = 4). Individuals with SCT exhibited lower eGFR (P = 0.018), higher albuminuria (P = 0.032), and 2.4× increased risk of CKD (P = 0.031). APOL1 HR and SCT were synergistically associated with lower eGFR (P interaction = 0.012). The GSTM1 null allele was not significantly associated with any renal outcomes. Conclusion: Our study highlighted the impact of APOL1 and SCT variants on poorer renal outcomes in the DRC and advocates for further genetic studies in SSA settings.

APOL1 Renal Risk Variants and Kidney Function in HIV-1-Infected People From Sub-Saharan Africa.

Introduction: APOL1 G1 and G2 alleles have been associated with kidney-related outcomes in people living with HIV (PLHIV) of Black African origin. No APOL1-related kidney risk data have yet been reported in PLHIV in West Africa, where high APOL1 allele frequencies have been observed. Methods: We collected clinical data from PLHIV followed in Burkina Faso (N = 413) and in the ANRS-12169/2LADY trial (Cameroon, Senegal, Burkina Faso, N = 369). APOL1 G1 and G2 risk variants were genotyped using TaqMan assays, and APOL1 high-risk (HR) genotype was defined by the carriage of 2 risk alleles. Results: In West Africa (Burkina Faso and Senegal), the G1 and G2 allele frequencies were 13.3% and 10.7%, respectively. In Cameroon (Central Africa), G1 and G2 frequencies were 8.7% and 8.9%, respectively. APOL1 HR prevalence was 4.9% in West Africa and 3.4% in Cameroon. We found no direct association between APOL1 HR and estimated glomerular filtration rate (eGFR) change over time. Nevertheless, among the 2LADY cohort participants, those with both APOL1 HR and high baseline viral load had a faster eGFR progression (ß = -3.9[-7.7 to -0.1] ml/min per 1.73 m2 per year, P < 0.05) than those with low-risk (LR) genotype and low viral load. Conclusion: Overall, the APOL1 risk allele frequencies in PLHIV were higher in the West African countries than in Cameroon, but much lower than previously reported in some Nigeria ethnic groups, which strongly advocates for further investigation in the African continent. This study suggested that the virological status could modulate the APOL1 impact on kidney function, hence reinforcing the need for early therapeutic interventions.

HLA-EPI: A new EPIsode in exploring donor/recipient epitopic compatibilities.

The HLA system plays a pivotal role both in transplantation and immunology. While classical HLA genotypes matching is made at the allelic level, recent progresses were developed to explore antibody-antigen recognition by studying epitopes. Donor to recipient matching at the epitopic level is becoming a trending topic in the transplantation research field because anti-HLA antibodies are epitope-specific rather than allele-specific. Indeed, different HLA alleles often share common epitopes. We present the HLA-Epi tool (hla.univ-nantes.fr) to study an HLA genotype at the epitope level. Using the international HLA epitope registry (Epregistry.com.br) as a reference, we developed HLA-Epi to easily determine epitopic and allelic compatibility levels between several HLA genotypes. The epitope database covers the most common HLA alleles (N = 2976 HLA alleles), representing more than 99% of the total observed frequency of HLA alleles. The freely accessible web tool HLA-Epi calculates an epitopic mismatch load between different sets of potential recipient-donor pairs at different resolution levels. We have characterized the epitopic mismatches distribution in a cohort of more than 10,000 kidney transplanted pairs from European ancestry, which showed low number of epitopic mismatches: 56.9 incompatibilities on average. HLA-Epi allows the exploration of epitope pairing matching to better understand epitopes contribution to immune responses regulation, particularly during transplantation. This free and ready-to-use bioinformatics tool not only addresses limitations of other related tools, but also offers a cost-efficient and reproducible strategy to analyze HLA epitopes as an alternative to HLA allele compatibility. In the future, this could improve sensitization prevention for allograft allocation decisions and reduce the risk of alloreactivity.

Surfing the Big Data Wave: Omics Data Challenges in Transplantation.

In both research and care, patients, caregivers, and researchers are facing a leap forward in the quantity of data that are available for analysis and interpretation, marking the daunting "big data era." In the biomedical field, this quantitative shift refers mostly to the -omics that permit measuring and analyzing biological features of the same type as a whole. Omics studies have greatly impacted transplantation research and highlighted their potential to better understand transplant outcomes. Some studies have emphasized the contribution of omics in developing personalized therapies to avoid graft loss. However, integrating omics data remains challenging in terms of analytical processes. These data come from multiple sources. Consequently, they may contain biases and systematic errors that can be mistaken for relevant biological information. Normalization methods and batch effects have been developed to tackle issues related to data quality and homogeneity. In addition, imputation methods handle data missingness. Importantly, the transplantation field represents a unique analytical context as the biological statistical unit is the donor-recipient pair, which brings additional complexity to the omics analyses. Strategies such as combined risk scores between 2 genomes taking into account genetic ancestry are emerging to better understand graft mechanisms and refine biological interpretations. The future omics will be based on integrative biology, considering the analysis of the system as a whole and no longer the study of a single characteristic. In this review, we summarize omics studies advances in transplantation and address the most challenging analytical issues regarding these approaches.

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research.

The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics. Research in genetics investigated HLA association with COVID-19 based on in silico, population, and individual data. However, they were conducted with variable scale and success; convincing results were mostly obtained with broader whole-genome association studies. Here, we propose a technical review of HLA analysis, including basic HLA knowledge as well as available tools and advice. We notably describe recent algorithms to infer and call HLA genotypes from GWAS SNPs and NGS data, respectively, which opens the possibility to investigate HLA from large datasets without a specific initial focus on this region. We thus hope this overview will empower geneticists who were unfamiliar with HLA to run MHC-focused analyses following the footsteps of the Covid-19|HLA & Immunogenetics Consortium.

Current HLA Investigations on SARS-CoV-2 and Perspectives.

The rapid, global spread of the SARS-CoV-2 virus during the current pandemic has triggered numerous efforts in clinical and research settings to better understand the host genetics' interactions and the severity of COVID-19. Due to the established major role played by MHC/HLA polymorphism in infectious disease course and susceptibility, immunologists and geneticists have teamed up to investigate its contribution to the SARS-CoV-2 infection and COVID-19 progression. A major goal of the Covid-19|HLA & Immunogenetics Consortium is to support and unify these efforts. Here, we present a review of HLA immunogenomics studies in the SARS-CoV-2 pandemic and reflect on the role of various HLA data, their limitation and future perspectives.

Impact of rural versus urban setting on kidney markers: a cross-sectional study in South-Kivu, DRCongo.

BACKGROUND: Most studies of chronic kidney disease (CKD) in Sub-Saharan Africa (SSA) have been conducted in urban settings. They relied on GFR estimated from serum creatinine alone and on the inexpensive, convenient urinary dipstick to assess proteinuria. The dipstick for proteinuria has not been directly compared with the gold standard albumin-to-creatinine ratio (ACR) in a large-sized study in SSA. We hereby assessed the influence of rural versus urban location on the level, interpretation, and diagnostic performance of proteinuria dipstick versus ACR. METHODS: In a cross-sectional population-based study of CKD in both urban (n = 587) and rural (n = 730) settings in South-Kivu, Democratic Republic of Congo (DRC), we assessed the prevalence, performance (sensitivity, specificity, positive predictive value and negative predictive value) and determinants of a positive dipstick proteinuria as compared with albuminuria (ACR). Albuminuria was subdivided into: A1 (< 30 mg/g creatinine), A2 (30 to 299 mg/g creatinine) and A3 (≥ 300 mg/g creatinine). RESULTS: The overall prevalence of positive dipstick proteinuria (≥ 1+) was 9.6 % (95 % CI, 7.9-11.3) and was higher in rural than in urban residents (13.1 % vs. 4.8 %, p < 0.001), whereas the prevalence of albuminuria (A2 or A3) was similar in both sites (6 % rural vs. 7.6 % urban, p = 0.31). In both sites, dipstick proteinuria ≥ 1 + had a poor sensitivity (< 50 %) and positive predictive value (< 11 %) for the detection of A2 or A3. The negative predictive value was 95 %. Diabetes [aOR 6.12 (1.52-24.53)] was a significant predictor of A3 whereas alkaline [aOR 7.45 (3.28-16.93)] and diluted urine [aOR 2.19 (1.35-3.57)] were the main predictors of positive dipstick proteinuria. CONCLUSIONS: ACR and dipstick proteinuria have similar positivity rates in the urban site whereas, in the rural site, dipstick was 2-fold more often positive than ACR. The poor sensitivity and positive predictive value of the dipstick as compared with ACR makes it unattractive as a screening tool in community studies of CKD in SSA.

APOL1 variant alleles associate with reduced risk for opportunistic infections in HIV infection.

Apolipoprotein L1 (APOL1), an innate immune factor against African trypanosoma brucei, inhibits HIV-1 in vitro. The impact of APOL1 G1-G2 variants on HIV-1-associated opportunistic infections (OIs) is unknown. Here, we report findings from a metaanalysis of four HIV/AIDS prospective cohorts (ALIVE, LSOCA, MACS, and WIHS) including 2066 African American participants. Using a global test combining all four cohorts, carriage of two APOL1 variant alleles is associated with a 50% reduction in odds of OI (combined OR 0.50, 95% CI 0.33-0.76). Subgroup analysis of OI etiological categories (viral, parasitic, fungal and Mycobacterial) suggests the possibility of specific protection from fungal infections (OR 0.54. 95% CI 0.32-0.93; PBonferroni corrected = 0.08). We observe an association of APOL1 variant alleles with host protection against OI in HIV-positive individuals. The study suggests a broader role of APOL1 variant alleles in innate immunity in vivo.

Prevalence and Risk Factors of CKD in South Kivu, Democratic Republic of Congo: A Large-Scale Population Study.

BACKGROUND: The prevalence of chronic kidney disease (CKD) in African American individuals is high but whether this applies to native populations in sub-Saharan Africa is unclear. METHODS: In a cross-sectional study, we assessed the prevalence and risk factors of CKD in rural and urban adults in South Kivu, Democratic Republic of Congo. Glomerular filtration rate (GFR) was estimated using the CKD-Epidemiology Collaboration (CKD-EPI) equations based on serum creatinine (eGFRcr), cystatin C (eGFRcys), or both markers (eGFRcr-cys), without ethnic correction factor. CKD was defined as an eGFR <60 ml/min per 1.73 m2 and/or albuminuria (albumin-to-creatinine ratio ≥30 mg/g). RESULTS: A total of 1317 participants aged 41.1 ± 17.1 years (730 rural, 587 urban) were enrolled. The prevalence of hypertension (20.2%; 95% confidence interval [CI], 18-22.3), diabetes mellitus (4.3%; 95% CI, 3.2-5.4) and obesity (8.9%; 95% CI, 7.4-10.5) was higher in urban than rural participants (all P < 0.05). HIV infection prevalence was 0.41% (95% CI, 0.05-0.78). The prevalence of eGFRcr <60 ml/min per 1.73 m2 was 5.4% (95% CI, 4.2-6.7). The prevalence of albuminuria was 6.6% (95 % CI, 5.1-8.1). The overall prevalence of CKD was 12.2% (95% CI, 10.2-14.2) according to CKD-EPIcr. Factors independently associated with CKD-EPIcr were older age (adjusted odds ratio [aOR], 1.05 [1.04-1.07]), urban residence (aOR 1.86 [1.18-2.95]), female sex (aOR 1.66 [1.04-2.66]), hypertension (aOR 1.90 [1.15-3.12]), diabetes (aOR 2.03 [1.02-4.06]), and HIV infection (10.21 [2.75-37.85]). The results based on eGFRcys or eGFRcr-cys were largely consistent with the preceding. CONCLUSION: Overall, the burden of CKD is substantial (>11%), predominantly in the urban area, and largely driven by classic risk factors (gender, aging, HIV, hypertension, and diabetes).

SNP-HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC-centric analyses in genomics.

Genome-wide associations studies have repeatedly identified the major histocompatibility complex genomic region (6p21.3) as key in immune pathologies. Researchers have also aimed to extend the biological interpretation of associations by focusing directly on human leukocyte antigen (HLA) polymorphisms and their combination as haplotypes. To circumvent the effort and high costs of HLA typing, statistical solutions have been developed to infer HLA alleles from single-nucleotide polymorphism (SNP) genotyping data. Though HLA imputation methods have been developed, no unified effort has yet been undertaken to share large and diverse imputation models, or to improve methods. By training the HIBAG software on SNP + HLA data generated by the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) to create reference panels, we highlighted the importance of (a) the number of individuals in reference panels, with a twofold increase in accuracy (from 10 to 100 individuals) and (b) the number of SNPs, with a 1.5-fold increase in accuracy (from 500 to 24,504 SNPs). Results showed improved accuracy with CAAPA compared to the African American models available in HIBAG, highlighting the need for precise population-matching. The SNP-HLA Reference Consortium is an international endeavor to gather data, enhance HLA imputation and broaden access to highly accurate imputation models for the immunogenomics community.

Transcriptional meta-analysis of regulatory B cells.

Regulatory B cells (Bregs) have the ability to regulate inflammation in various pathological situations, making them key players in immune regulation. Several mechanisms have been described and we recently identified a GZMB expressing Breg population in kidney transplanted patients who tolerate a kidney graft. To further investigate their biology and mechanisms, we conducted a transcriptomic analysis by RNAseq of these cells and we performed the first weighted meta-analysis of publicly available transcriptomic data from published Breg studies both in humans and mice. We identified two distinct and unique transcriptional signatures of 126 and 93 genes, respectively, associated with these Bregs. While we highlighted genes coding for proteins with potent involvement in regulatory functions, proliferation, and coding for transcription factors, the comparison between humans and mice did not allow identifying a common pattern. Thus, our results suggest distinct species-restricted Breg transcriptional signatures in humans and mice.