Ancient genomes reveal complex patterns of population movement, interaction, and replacement in sub-Saharan Africa

Africa hosts the greatest human genetic diversity globally, but legacies of ancient population interactions and dispersals across the continent remain understudied. Here, we report genome-wide data from 20 ancient sub-Saharan African individuals, including the first reported ancient DNA from the DRC, Uganda, and Botswana. These data demonstrate the contraction of diverse, once contiguous hunter-gatherer populations, and suggest the resistance to interaction with incoming pastoralists of delayed-return foragers in aquatic environments. We refine models for the spread of food producers into eastern and southern Africa, demonstrating more complex trajectories of admixture than previously suggested. In Botswana, we show that Bantu ancestry post-dates admixture between pastoralists and foragers, suggesting an earlier spread of pastoralism than farming to southern Africa. Our findings demonstrate how processes of migration and admixture have markedly reshaped the genetic map of sub-Saharan Africa in the past few millennia and highlight the utility of combined archaeological and archaeogenetic approaches

Facile whole mitochondrial genome resequencing from nipple aspirate fluid using MitoChip v2.0

<p>Abstract</p> <p>Background</p> <p>Mutations in the mitochondrial genome (mtgenome) have been associated with many disorders, including breast cancer. Nipple aspirate fluid (NAF) from symptomatic women could potentially serve as a minimally invasive sample for breast cancer screening by detecting somatic mutations in this biofluid. This study is aimed at 1) demonstrating the feasibility of NAF recovery from symptomatic women, 2) examining the feasibility of sequencing the entire mitochondrial genome from NAF samples, 3) cross validation of the Human mitochondrial resequencing array 2.0 (MCv2), and 4) assessing the somatic mtDNA mutation rate in benign breast diseases as a potential tool for monitoring early somatic mutations associated with breast cancer.</p> <p>Methods</p> <p>NAF and blood were obtained from women with symptomatic benign breast conditions, and we successfully assessed the mutation load in the entire mitochondrial genome of 19 of these women. DNA extracts from NAF were sequenced using the mitochondrial resequencing array MCv2 and by capillary electrophoresis (CE) methods as a quality comparison. Sequencing was performed independently at two institutions and the results compared. The germline mtDNA sequence determined using DNA isolated from the patient's blood (control) was compared to the mutations present in cellular mtDNA recovered from patient's NAF.</p> <p>Results</p> <p>From the cohort of 28 women recruited for this study, NAF was successfully recovered from 23 participants (82%). Twenty two (96%) of the women produced fluids from both breasts. Twenty NAF samples and corresponding blood were chosen for this study. Except for one NAF sample, the whole mtgenome was successfully amplified using a single primer pair, or three pairs of overlapping primers. Comparison of MCv2 data from the two institutions demonstrates 99.200% concordance. Moreover, MCv2 data was 99.999% identical to CE sequencing, indicating that MCv2 is a reliable method to rapidly sequence the entire mtgenome. Four NAF samples contained somatic mutations.</p> <p>Conclusion</p> <p>We have demonstrated that NAF is a suitable material for mtDNA sequence analysis using the rapid and reliable MCv2. Somatic mtDNA mutations present in NAF of women with benign breast diseases could potentially be used as risk factors for progression to breast cancer, but this will require a much larger study with clinical follow up.</p

Cry the beloved country : multi-layered vulnerability and trauma for Africa’s children

Abstract: The maxim that history repeats itself will loom over the developmental trajectory of the continent as its broken citizens grow up in a broken world with untold nightmares and a paucity of dreams and hopes about a future beyond their childhood memories. This is a future Africa cannot afford

Association between depression, glycaemic control and the prevalence of diabetic retinopathy in a diabetic population in Cameroon

Purpose: The prevalence of diabetes mellitus is increasing especially in low- and middle- income countries in which 75% of the world’s diabetic population reside. The macro- and microvascular complications of diabetes such as diabetic retinopathy are also set to increase in these populations. The relationship between depression and glycaemic control has been established in high- income countries, but evidence from low- and middle-income countries is scarce. This research aimed to determine an association between depression and glycaemic control and record the prevalence of diabetic retinopathy in a diabetic population in Cameroon. Methods: Analysis of cross-sectional data from the ‘Improving access to HbA1c measurements in sub-Saharan Africa’ study was used. Primary data were collected from six diabetic care facilities in Yaoundé, Cameroon. Participants were aged ≥ 18 years with at least a 6-month history of diabetes. Depression was assessed using the Centre for Epidemiological Studies Depression Scale (CES-D). A CES-D score ≥ 16 was used to identify the presence of clinically significant depressive symptoms. Data on glycaemic control were measured using HbA1c measurements at baseline. The presence of diabetic retinopathy was established through ophthalmoscopy and angiography using the Early Treatment Diabetic Retinopathy Study classification. Results: A total of 261 participants were included in the study, and information on depressive symptoms at baseline (CES-D score) were available for 240 participants. The results of the data analysis found that 60% of the study participants had clinically significant depressive symptoms (CES-D > 16). A weak non-significant positive correlation was found between CES-D score and HbA1c level (p = 0.46, r = 0.05) using the Pearson’s correlation co-efficient. Gender and attendance to a patient support group were significantly associated with the presence of clinically significant depressive symptoms. Poor glycaemic control (HbA1c > 7%) was found in 72.8% of the population. Educational level and insulin use were significantly associated with glycaemic control. The prevalence of diabetic retinopathy was 27.2% (23.4% non-proliferative, 2.5% pre- proliferative and 3.2% proliferative), and the prevalence of diabetic maculopathy was 10.0%. Conclusion: The study found that a large proportion of diabetic patients may be experiencing depressive symptoms for which they are currently not receiving treatment or support. We also found a large proportion to have poor glycaemic control that is known to worsen the vascular complications of diabetes. In light of the increasing epidemic of type 2 diabetes in sub-Saharan Africa, it is important that the recognition of depressive symptoms becomes integrated into future healthcare policies in the nations of sub-Saharan Africa. This research suggests that individuals experiencing depressive symptoms may be more likely to engage in patient support groups. These groups can be beneficial in providing patients with diabetes valuable information, which could lead to better glycaemic control

Predicting Outcomes of Hormone and Chemotherapy in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) Study by Biochemically-inspired Machine Learning [version 3; referees: 2 approved]

Genomic aberrations and gene expression-defined subtypes in the large METABRIC patient cohort have been used to stratify and predict survival. The present study used normalized gene expression signatures of paclitaxel drug response to predict outcome for different survival times in METABRIC patients receiving hormone (HT) and, in some cases, chemotherapy (CT) agents. This machine learning method, which distinguishes sensitivity vs. resistance in breast cancer cell lines and validates predictions in patients; was also used to derive gene signatures of other HT  (tamoxifen) and CT agents (methotrexate, epirubicin, doxorubicin, and 5-fluorouracil) used in METABRIC. Paclitaxel gene signatures exhibited the best performance, however the other agents also predicted survival with acceptable accuracies. A support vector machine (SVM) model of paclitaxel response containing genes ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2, SLCO1B3, TUBB1, TUBB4A, and TUBB4B was 78.6% accurate in predicting survival of 84 patients treated with both HT and CT (median survival ≥ 4.4 yr). Accuracy was lower (73.4%) in 304 untreated patients. The performance of other machine learning approaches was also evaluated at different survival thresholds. Minimum redundancy maximum relevance feature selection of a paclitaxel-based SVM classifier based on expression of genes BCL2L1, BBC3, FGF2, FN1, and TWIST1 was 81.1% accurate in 53 CT patients. In addition, a random forest (RF) classifier using a gene signature (ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2,SLCO1B3, TUBB1, TUBB4A, and TUBB4B) predicted >3-year survival with 85.5% accuracy in 420 HT patients. A similar RF gene signature showed 82.7% accuracy in 504 patients treated with CT and/or HT. These results suggest that tumor gene expression signatures refined by machine learning techniques can be useful for predicting survival after drug therapies

Poor glycemic control in type 2 diabetes in the South of the Sahara: the issue of limited access to an HbA1c test

International audienceBackgroundManagement of type 2 diabetes remains a challenge in Africa. The objective of this study was to evaluate the prevalence and predictors of poor glycemic control in patients with type 2 diabetes living in sub-Saharan.Patients and methodsThis was a cross-sectional study involving 1267 people (61% women) with type 2 diabetes (mean age 58 years) recruited across health facilities in Cameroon and Guinea. Predictors of poor glycemic control (HbA1c ≥7.0% (53 mmol/mol)) were investigated via logistic regressions.ResultsThe mean body mass index was 27.4 ± 5.8 kg/m2, and 74% of patients had poor glycemic control. Predictors of poor glycemic control in multivariable regression models were recruitment in Guinea [odd ratio: 2.91 (95% confidence interval 2.07 to 4.11)], age <65 years [1.40 (1.04 to 1.88)], diabetes duration ≥3 years [2.36 (1.74 to 3.21)], treatment with: oral glucose control agents [3.46 (2.28 to 5.26)], insulin alone or with oral glucose control agents [7.74 (4.70 to 12.74)] and absence of a previous HbA1c measurement in Guinea [2.96 (1.30 to 6.75)].ConclusionPoor control of blood glucose is common in patients with type 2 diabetes in these two countries. Limited access to HbA1c appears to be a key factor associated with poor glycemic control in Guinea, and should be addressed by health policies targeting improvement in the outcomes of diabetes care

The global response to the COVID-19 pandemic: how have immunology societies contributed?

The COVID-19 pandemic is shining a spotlight on the field of immunology like never before. To appreciate the diverse ways in which immunologists have contributed, Nature Reviews Immunology invited the president of the International Union of Immunological Societies and the presidents of 15 other national immunology societies to discuss how they and their members responded following the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).</p