Biomedical subjects

Bamidele Tayo

Publications and source records attributed to Bamidele Tayo.

4 recordsLinked to original sources

PubMed2026

Long-read Sequences Mapped to a Complete Reference Genome Uncover Uncaptured Structural Variants across the Beta-globin Cluster in Africans with Sickle Cell Disease.

African genomes are marked by extensive complexity in the number and distribution of variants, yet remain under-represented in genetic databases and the human reference genome. This gap in representation limits the broad application of genomic medicine. Sickle cell disease (SCD) - one of the most common monogenic diseases - has its highest prevalence in Africa, and variation in disease severity has consistently been linked to the beta-globin locus, including levels of fetal hemoglobin (HbF). Modulation of HbF is central to current SCD gene therapies; however, the inherent complexity and variation at the locus in African genomes presents a challenge to translating these advances to Africa. Here, we align long-read single molecule sequences (LRS) targeted to the beta-globin region to the hg38 and T2T-CHM13v2 genome references in 40 individuals with SCD, predominantly recruited from three African countries. We demonstrate that the expanded T2T-CHM13v2 reference sequence at this locus reduces Structural Variant (SV) calls by 70% and uncovers uncaptured single nucleotide variants (SNVs). Across the cluster we report 343 SVs and 196 SNVs that have not been previously reported, including in LRS data from the All of Us project. By including African populations from ethnolinguistic groups that have not been previously surveyed we improve variant resolution and bolster evidence for observed variation. Finally, we identify a common ∼4kb insertion locus overlapping the HBB promoter among individuals with high HbF. These results demonstrate the utility of combining a comprehensive reference genome with LRS in African populations to uncover genomic variation at disease-associated loci.

SNV↗

PubMed2006

Positive association between resting energy expenditure and weight gain in a lean adult population.

BACKGROUND: Weight gain in adulthood is common, from modest gains in developing countries to substantial increases in Western societies. Evidence of the importance of energy expenditure in adult weight change has been limited to studies conducted in Pima Indians, in whom resting energy expenditure (REE) was found to be inversely associated with weight gain. OBJECTIVE: The aim was to determine whether REE was predictive of weight change in lean Nigerian adults. DESIGN: Weight was measured in 744 adults on 2-4 occasions over 5.5 y. REE was measured in the second follow-up examination. Sex-specific, mixed-effects models with REE, fat-free mass, and age as fixed effects were used to test the association between REE and weight change. RESULTS: Adults aged >19 y (n = 352 men and 392 women) were included in these analyses. At baseline, the mean (+/-SD) age was 45.9 +/- 16.1 y for the whole population; the mean weight was 61.4 +/- 10.7 and 58.1 +/- 12.1 kg and body mass index (in kg/m(2)) was 21.4 +/- 3.2 and 23.1 +/- 4.0 for men and women, respectively. Over a mean 5.5 y of follow-up, the age-adjusted weight gain was 0.42 kg/y for the men and 0.59 kg/y for the women. In mixed-effects models, REE was positively associated with weight gain in both men and women (P < 0.001). No significant association was observed in participants who lost weight. CONCLUSIONS: In contrast with observations in overweight Pima Indians, REE adjusted for body size and composition was positively associated with weight gain in lean Nigerian adults. This suggests either that the potential for differential regulation of body weight in lean compared with overweight populations exists or that the increased REE in this population was the result, rather than cause, of weight gain.

Adult↗

PubMed2005

Differential and trajectory methods for time course gene expression data.

MOTIVATION: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differentiation approaches can reduce the dimensions of data, help to remove redundant genes and noises, and highlight the most relevant genes that are major players in the development of certain diseases or the effect of drug treatment. The purpose of this study is to investigate the efficiency of parametric (including Bayesian and non-Bayesian, linear and non-linear), non-parametric and semi-parametric gene filtering methods through the application of time course microarray data from multiple sclerosis patients being treated with interferon-beta-1a. The analysis of variance with bootstrapping (parametric), class dispersion (semi-parametric) and Pareto (non-parametric) with permutation methods are presented and compared for filtering and finding differentially expressed genes. The Bayesian linear correlated model, the Bayesian non-linear model the and non-Bayesian mixed effects model with bootstrap were also developed to characterize the differential expression patterns. Furthermore, trajectory-clustering approaches were developed in order to investigate the dynamic patterns and inter-dependency of drug treatment effects on gene expression. RESULTS: Results show that the presented methods performed significant differently but all were adequate in capturing a small number of the potentially relevant genes to the disease. The parametric method, such as the mixed model and two Bayesian approaches proved to be more conservative. This may because these methods are based on overall variation in expression across all time points. The semi-parametric (class dispersion) and non-parametric (Pareto) methods were appropriate in capturing variation in expression from time point to time point, thereby making them more suitable for investigating significant monotonic changes and trajectories of changes in gene expressions in time course microarray data. Also, the non-linear Bayesian model proved to be less conservative than linear Bayesian correlated growth models to filter out the redundant genes, although the linear model showed better fit than non-linear model (smaller DIC). We also report the trajectories of significant genes-since we have been able to isolate trajectories of genes whose regulations appear to be inter-dependent.

Computer Simulation↗

PubMed2003

A genome-wide scan for body mass index among Nigerian families.

OBJECTIVE: Interest in mapping genetic variants that are associated with obesity remains high because of the increasing prevalence of obesity and its complications worldwide. Data on genetic determinants of obesity in African populations are rare. RESEARCH METHODS AND PROCEDURES: We have undertaken a genome-wide scan for body mass index (BMI) in 182 Nigerian families that included 769 individuals. RESULTS: The prevalence of obesity was only 5%, yet polygenic heritability for BMI was in the expected range (0.46 +/- 0.07). Tandem repeat markers (402) were typed across the genome with an average map density of 9 cM. Pedigree-based analysis using a variance components linkage model demonstrated evidence for linkage on chromosome 7 (near marker D7S817 at 7p14) with a logarithm of odds (LOD) score of 3.8 and on chromosome 11 (marker D11S2000 at 11q22) with an LOD score of 3.3. Weaker evidence for linkage was found on chromosomes 1 (1q21, LOD = 2.2) and 8 (8p22, LOD = 2.3). Several candidate genes, including neuropeptide Y, DRD2, APOA4, lamin A/C, and lipoprotein lipase, lie in or close to the chromosomal regions where strong linkage signals were found. DISCUSSION: The findings of this study suggest that, as in other populations with higher prevalences of obesity, positive linkage signals can be found on genome scans for obesity-related traits. Follow-up studies may be warranted to investigate these linkages, especially the one on chromosome 11, which has been reported in a population at the opposite end of the BMI distribution.

Adult↗