Biomedical subjects

Adebowale Adeyemo

Publications and source records attributed to Adebowale Adeyemo.

3 recordsLinked to original sources

PubMed2026

Post-colonial human admixture and natural selection: disentangling signals in complex demographic contexts.

Natural selection and admixture are defining population genetic features of modern human populations, yet their interaction has only recently emerged as a major focus in human evolutionary genomics. While the influence of natural selection on population structure and trait diversity is well established, the ways in which selective pressures operate after admixture have historically received far less attention. In this review, we synthesise the latest progress in understanding post-admixture selection and highlight case studies that illustrate how novel environments, pathogen exposure, dietary shifts and socio-historical transformations have driven genomic adaptation. We conclude by identifying key gaps that remain in the field with the aim of motivating future research and facilitating new insights into how admixture and selection jointly shape human diversity.

Journal Article↗

PubMed2026

The relationships between figure rating scale, anthropometric measures, and cardiometabolic outcomes: the AADM study.

INTRODUCTION: Direct measurement of anthropometrics can be impractical in research. Validated Figure Rating Scales (FRS) offer an alternative, but their validity across populations remains limited. OBJECTIVES: This study aimed to analyze the relationships between figure rating scale (FRS) and anthropometric measures (body mass index (BMI); waist circumference (WC), and waist-to-hip ratio (WHR)) and to specifically evaluate FRS at the time of enrollment and lifetime body size, an FRS-derived score as risk factors for cardiometabolic traits including type 2 diabetes (T2D). METHODS: Participants consisted of 650 adults from the America Africa Diabetes Mellitus study. Kendall's tau coefficient (τ) was used to analyze correlations between FRS at the time of enrollment, overall obesity, and abdominal obesity. Regression models were used to evaluate FRS at the time of enrollment and lifetime body size as risk factors for T2D, and related traits. RESULTS: BMI and WHR increased monotonically with increasing body size. FRS at the time of enrollment showed a stronger correlation with BMI (τ = 0.48, p < 0.0001) than with WHR (τ = 0.17, p < 0.0001) in women. Lifetime body size was significantly associated with T2D (OR = 1.044, 95% Confidence Limit: [1.006, 1.08]; both FRS at the time of enrollment and lifetime body size were associated with insulin resistance. Diastolic blood pressure was associated with FRS at the time of enrollment. CONCLUSIONS: FRS at the time of enrollment is significantly associated with BMI and WHR in this population and lifetime body size, a novel composite score, shows promising utility as a predictor of T2D.

Humans↗

PubMed2025

Polygenic Risk Scores and HLA Class II Variants are Biomarkers of Corticosteroid Response in Childhood Nephrotic Syndrome.

INTRODUCTION: Nephrotic syndrome (NS), a common glomerular disease in children, is classified based on response to corticosteroid therapy as either steroid-sensitive nephrotic syndrome (SSNS), or steroid-resistant nephrotic syndrome (SRNS). However, there are currently no reliable predictors of therapy response at initial clinical presentation. METHODS: We conducted genome-wide association studies, developed polygenic risk scores (PRS) for therapy response and analyzed classical HLA alleles in 1,997 (994 discovery and 1,003 replication/validation cohorts) previously unstudied children with NS and 3,558 ancestry-matched controls. RESULTS: A significant association with HLA loci defined by variants in HLA-DQB1, HLA-DRB1, and HLA-DQA1 were found for SSNS (but not SRNS), along with a second immune-related SSNS locus: CLEC16A. A PRS that discriminates between SSNS and SRNS was validated in two independent cohorts. The HLA haplotype HLA- DRB1*07:01~DQA1*02:01~DQB1*02:02 was associated with ~4 times the risk of developing SSNS. A model incorporating HLA haplotype, PRS score, and age at onset of the disease was the best predictor of steroid responsiveness with an AUC of 0.68-0.70 and an overall classification accuracy of SSNS versus SRNS of 67-71%. CONCLUSIONS: Our findings confirm that SSNS (unlike SRNS) is an immune-mediated HLA-associated disorder. The PRS for therapy response and HLA haplotype can serve as biomarkers and provide a foundation for more accurate diagnoses and tailored and individualized treatment.

HLA haplotype↗