A.T. Sidibé’s research while affiliated with University of Bamako and other places

HLA genotyping was performed on 99 type 1 diabetes (T1D) patients and 200 controls from Mali. Next‐generation sequencing of the classical HLA‐A, ‐B, ‐C, ‐DRB1, ‐DRB3, ‐DRB4, ‐DRB5, ‐DQA1, ‐DQB1, ‐DPA1, and ‐DPB1 loci revealed strong T1D association for all loci except HLA‐C and ‐DPA1. Class II association is stronger than class I association, with most observed associations predisposing or protective as expected based on previous studies. For example, HLA‐DRB1*03:01, HLA‐DRB1*09:01, and HLA‐DRB1*04:05 predispose for T1D, whereas HLA‐DRB1*15:03 is protective. HLA‐DPB1*04:02 (OR = 12.73, p = 2.92 × 10⁻⁰⁵) and HLA‐B*27:05 (OR = 21.36, p = 3.72 × 10⁻⁰⁵) appear highly predisposing, although previous studies involving multiple populations have reported HLA‐DPB1*04:02 as T1D‐protective and HLA‐B*27:05 as neutral. This result may reflect the linkage disequilibrium between alleles on the extended HLA‐A*24:02~HLA‐B*27:05~HLA‐C*02:02~HLA‐DRB1*04:05~HLA‐DRB4*01:03~HLA‐DQB1*02:02~HLA‐DQA1*02:01~HLA‐DPB1*04:02~HLA‐DPA1*01:03 haplotype in this population rather than an effect of either allele itself. Individual amino acid (AA) analyses are consistent with most T1D association attributable to HLA class II rather than class I in this data set. AA‐level analyses reveal previously undescribed differences of the HLA‐C locus from the HLA‐A and HLA‐B loci, with more polymorphic positions, spanning a larger portion of the gene. This may reflect additional mechanisms for HLA‐C to influence T1D risk, for example, through expression differences or through its role as the dominant ligand for killer cell immunoglobulin‐like receptors (KIR). Comparison of these data to those from larger studies and on other populations may facilitate T1D prediction and help elucidate elusive mechanisms of how HLA contributes to T1D risk and autoimmunity.

Objective: Limited information is available regarding youth-onset diabetes in Mali. We investigated demographic, clinical, biochemical, and genetic features in new diabetes cases in children and adolescents. Research design and methods: The study was conducted at Hôpital du Mali in Bamako. A total of 132 recently-diagnosed cases <21 years were enrolled. Demographic characteristics, clinical information, biochemical parameters (blood glucose, HbA1c, C-peptide, glutamic acid decarboxylase-65 (GAD-65) and islet antigen-2 (IA2) autoantibodies) were assessed. DNA was genotyped for HLA-DRB1 using high-resolution genotyping technology. Results: A total of 130 cases were clinically diagnosed as type 1 diabetes (T1D), one with type 2 diabetes (T2D), and one with secondary diabetes. A total of 66 (50.8%) T1D cases were males and 64 (49.2%) females, with a mean age at diagnosis of 13.8 ± 4.4 years (range 0.8-20.7 years) peak onset of 15 years. 58 (44.6%) presented in diabetic ketoacidosis; with 28 (21.5%) IA2 positive, 76 (58.5%) GAD-65 positive, and 15 (11.5%) positive for both autoantibodies. HLA was also genotyped in 195 controls without diabetes. HLA-DRB1 genotyping of controls and 98 T1D cases revealed that DRB1*03:01, DRB1*04:05, and DRB1*09:01 alleles were predisposing for T1D (odds ratios [ORs]: 2.82, 14.76, and 3.48, p-values: 9.68E-5, 2.26E-10, and 8.36E-4, respectively), while DRB1*15:03 was protective (OR = 0.27; p-value = 1.73E-3). No significant differences were observed between T1D cases with and without GAD-65 and IA2 autoantibodies. Interestingly, mean C-peptide was 3.6 ± 2.7 ng/ml (1.2 ± 0.9 nmol/L) in T1D cases at diagnosis. Conclusions: C-peptide values were higher than expected in those diagnosed as T1D and autoantibody rates lower than in European populations. It is quite possible that some cases have an atypical form of T1D, ketosis-prone T2D, or youth-onset T2D. This study will help guide assessment and individual management of Malian diabetes cases, potentially enabling healthier outcomes.

Aims Determine incidence, prevalence and mortality of type 1 diabetes (T1D) in children and youth <25 years (y) in Mali during the first 10 years of the Santé Diabète/Life for a Child program. Methods Data were collected from the prospective program register. Diagnosis of T1D was clinical, based on presentation, clinical features, immediate requirement for insulin, and no suggestion of other diabetes types. Results 460 cases were diagnosed with T1D <25y in 2007‐2016. Male‐to‐female ratio was 1.04:1. Peak age at onset was 15‐16y (range 1.1‐24y). T1D incidence <25 years per 100,000 population/y increased from 0.12 in 2007 to 0.74 in 2016 (an 18% annualized increase, p<0.001). Incidence peaked at 0.80 in 2014, the year after an education campaign was conducted. Incidence <15y rose from 0.12 to 0.35 per 100,000/y in 2007 and 2016 respectively (14% annualized increase, p<0.001). There was a steep, consistent increase in prevalence (per 100,000) from 0.43 in 2007 to 2.90 in 2016 (p<0.001). Prevalence <15y was 0.34/100,000 in 2007 and 1.02/100,000 by 2016 (p<0.001). Overall crude mortality rate was 30.0/1,000 patient years, equating to a standardized mortality rate of 9.0, with vital status known for 99.8% of cases. Conclusions Known incidence and prevalence of diabetes in Mali increased rapidly from 2007 to 2016, contemporaneous with the introduction and development of the Santé Diabète/Life for a Child program. Improved diagnosis and care resulting in lower mortality are likely contributors. True incidence may still be underestimated, with some cases still dying undiagnosed and full study ascertainment being uncertain. This article is protected by copyright. All rights reserved.

Introduction Around 90% of all undiagnosed people with haemophilia (PWH) live in developing countries. In Mali, in sub-Saharan Africa, nearly 90% of potential PWH are not identified. We initiated a two-year study involving an integrated programme of training and awareness-raising with the aim of improving diagnosis and access to care for PWH, based on partnership with those who regularly interact with them. Methodology Our training programme focused on four regions of Mali and the district of Bamako, and included three types of health professionals from different districts and hospitals: medical doctor, nurse and laboratory technician. We also targeted traditional healers, who continue to be strongly involved in local healthcare, and provided training sessions for patients and their families on the symptoms, diagnosis, treatment and complications of haemophilia. A complementary programme of awareness-raising, including the national media, ran alongside the training sessions. Results Overall, the programme involved 495 participants: 213 health care professionals, 24 patients, 79 parents of patients, 126 traditional healers, and 53 media workers. A direct result was development of collaboration between these groups in identifying haemophilia, and the transfer of four patients from a traditional healer's office to hospital for diagnosis and treatment. The number of diagnosed PWH increased from 42 in 2016 to 126 in 2017. Conclusion The integrated haemophilia educational programme, which took into account the nature of the local environment and involved all relevant stakeholders, showed that taking a collaborative approach is a successful strategy for improving diagnosis and care for PWH in Mali. This approach could be relevant in other developing countries.