Biomedical subjects

Charles Rotimi

Publications and source records attributed to Charles Rotimi.

14 recordsLinked to original sources

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↗

PubMed2007

Refining the impact of TCF7L2 gene variants on type 2 diabetes and adaptive evolution.

We recently described an association between risk of type 2diabetes and variants in the transcription factor 7-like 2 gene (TCF7L2; formerly TCF4), with a population attributable risk (PAR) of 17%-28% in three populations of European ancestry. Here, we refine the definition of the TCF7L2 type 2diabetes risk variant, HapB(T2D), to the ancestral T allele of a SNP, rs7903146, through replication in West African and Danish type 2 diabetes case-control studies and an expanded Icelandic study. We also identify another variant of the same gene, HapA, that shows evidence of positive selection in East Asian, European and West African populations. Notably, HapA shows a suggestive association with body mass index and altered concentrations of the hunger-satiety hormones ghrelin and leptin in males, indicating that the selective advantage of HapA may have been mediated through effects on energy metabolism.

Asian People↗

PubMed2006

Podoconiosis: a tropical model for gene-environment interactions?

Podoconiosis (endemic non-filarial elephantiasis) is a geochemical disease occurring in individuals exposed to red clay soil derived from alkalic volcanic rock. It is a chronic, debilitating disorder and a considerable public health problem in at least 10 countries in tropical Africa, Central America and northern India. Only a small proportion of individuals exposed to red clay develop disease and familial clustering of cases occurs, so we tested the hypothesis that disease occurs in genetically susceptible individuals on exposure to an environmental element in soil. Using multiple statistical genetic techniques we estimated sibling recurrence risk ratio (lambda(s)) and heritability for podoconiosis, and conducted segregation analysis on 59 multigenerational affected families from Wolaitta Zone, southern Ethiopia. We estimated the lambda(s) to be 5.07. The heritability of podoconiosis was estimated to be 0.629 (SE 0.069, P=1x10(-7)). Segregation analysis showed that the most parsimonious model was that of an autosomal co-dominant major gene. Age and use of footwear were significant covariates in the final model. Host genetic factors are important determinants of susceptibility to podoconiosis. Identification of the gene(s) involved will lead to better understanding of the gene-environment interactions involved in the pathogenesis of podoconiosis and other complex multifactorial conditions.

Age of Onset↗

PubMed2006

Variance components model with disequilibria.

The variance components (VC) model has been popular for genetic analysis. It has received wide applications in a variety of genetic practices, and been extended to various forms for different settings. However, most of the existing VC models are, explicitly or implicitly, under the assumption of the Hardy-Weinberg and/or linkage equilibria, which is impractical in some realistic settings since more or less deviations from this assumption are common. We propose a new VC model that incorporates both these disequilibria, and includes the existing models as special cases. The corresponding variance components are computed for some commonly used relative pairs conditional on the observed marker identity-by-descent data. Parameters can be estimated by the traditional methods such as the maximum likelihood estimate. Simulation studies suggest that this extended model improves inference significantly over the existing models when deviations of these disequilibria are present.

Analysis of Variance↗

PubMed2005

Genome scan linkage analysis comparing microsatellites and single-nucleotide polymorphisms markers for two measures of alcoholism in chromosomes 1, 4, and 7.

BACKGROUND: We analyzed 143 pedigrees (364 nuclear families) in the Collaborative Study on the Genetics of Alcoholism (COGA) data provided to the participants in the Genetic Analysis Workshop 14 (GAW14) with the goal of comparing results obtained from genome linkage analysis using microsatellite and with results obtained using SNP markers for two measures of alcoholism (maximum number of drinks -MAXDRINK and an electrophysiological measure from EEG -TTTH1). First, we constructed haplotype blocks by using the entire set of single-nucleotide polymorphisms (SNP) in chromosomes 1, 4, and 7. These chromosomes have shown linkage signals for MAXDRINK or EEG-TTTH1 in previous reports. Second, we randomly selected one, two, three, four, and five SNPs from each block (referred to as Rep1 - Rep5, respectively) to conduct linkage analysis using variance component approach. Finally, results of all SNP analyses were compared with those obtained using microsatellite markers. RESULTS: The LOD scores obtained from SNPs were slightly higher but the curves were not radically different from those obtained from microsatellite analyses. The peaks of linkage regions from SNP sets were slightly shifted to the left when compared to those from microsatellite markers. The reduced sets of SNPs provide signals in the same linkage regions but with a smaller LOD score suggesting a significant impact of the decrease in information content on linkage results. The widths of 1 LOD support interval of linkage regions from SNP sets were smaller when compared to those of microsatellite markers. However, two linkage regions obtained from the microsatellite linkage analysis on chromosome 7 for LOG of TTTH1 were not detected in the SNP based analyses. CONCLUSION: The linkage results from SNPs showed narrower linkage regions and slightly higher LOD scores when compared to those of microsatellite markers. The different builds of the genetic maps used in microsatellite and SNPs markers or/and errors in genotyping may account for the microsatellite linkage signals on chromosome 7 that were not identified using SNPs. Also, unresolved map issues between SNPs and microsatellite markers may be partly responsible for the shifted linkage peaks when comparing the two types of markers.

Alcoholism↗

PubMed2005

Genetic structure in four West African population groups.

BACKGROUND: Africa contains the most genetically divergent group of continental populations and several studies have reported that African populations show a high degree of population stratification. In this regard, it is important to investigate the potential for population genetic structure or stratification in genetic epidemiology studies involving multiple African populations. The presences of genetic sub-structure, if not properly accounted for, have been reported to lead to spurious association between a putative risk allele and a disease. Within the context of the Africa America Diabetes Mellitus (AADM) Study (a genetic epidemiologic study of type 2 diabetes mellitus in West Africa), we have investigated population structure or stratification in four ethnic groups in two countries (Akan and Gaa-Adangbe from Ghana, Yoruba and Igbo from Nigeria) using data from 372 autosomal microsatellite loci typed in 493 unrelated persons (986 chromosomes). RESULTS: There was no significant population genetic structure in the overall sample. The smallest probability is associated with an inferred cluster of 1 and little of the posterior probability is associated with a higher number of inferred clusters. The distribution of members of the sample to inferred clusters is consistent with this finding; roughly the same proportion of individuals from each group is assigned to each cluster with little variation between the ethnic groups. Analysis of molecular variance (AMOVA) showed that the between-population component of genetic variance is less than 0.1% in contrast to 99.91% for the within population component. Pair-wise genetic distances between the four ethnic groups were also very similar. Nonetheless, the small between-population genetic variance was sufficient to distinguish the two Ghanaian groups from the two Nigerian groups. CONCLUSION: There was little evidence for significant population substructure in the four major West African ethnic groups represented in the AADM study sample. Ethnicity apparently did not introduce differential allele frequencies that may affect analysis and interpretation of linkage and association studies. These findings, although not entirely surprising given the geographical proximity of these groups, provide important insights into the genetic relationships between the ethnic groups studied and confirm previous results that showed close genetic relationship between most studied West African groups.

Africa, Western↗

PubMed2005

A genome wide quantitative trait linkage analysis for serum lipids in type 2 diabetes in an African population.

Lipid abnormalities are strongly linked with coronary heart disease and are common in type 2 diabetes. However, little is known about the genetic determinants of serum lipids in African populations. An autosomal genome scan was performed for linkage to five plasma lipid phenotypes (total cholesterol, triglycerides (TG), HDL-cholesterol (HDL-C), LDL-cholesterol (LDL-C) and VLDL-cholesterol (VLDL-C)) in the Africa-America Diabetes Mellitus (AADM) study. Two hundred and ninety-five affected sibling pairs with type 2 diabetes mellitus enrolled from Ghana and Nigeria were genotyped for 390 microsatellite markers with an average inter-marker distance of 9cM. Multipoint variance components linkage analysis showed that HDL-C had a LOD score of 4.34 near marker D7S3061 and 3.00 near marker D7S513. Some clustering of linkage evidence to several lipid phenotypes was observed on chromosomes 5 (LDL-C, total cholesterol, VLDL-C), chromosome 7 (HDL-C, TG) and chromosome 19 (total cholesterol, LDL-C, TG). Principal component analysis of the five phenotypes yielded two factors, one (TG, HDL-C and VLDL) of which was linked to QTLs on chromosomes 2, 5 and 7, while the other (total cholesterol and LDL-C) was linked to a different set of QTLs on chromosomes 2, 5 and 18. Several of these regions have been reported to be linked to lipids in other studies. Follow up investigations are warranted in view of the central role serum lipids play in the aetiopathogenesis of cardiovascular disease.

Adult↗

PubMed2005

A statistical framework for haplotype block inference.

The existence of haplotype blocks transmitted from parents to offspring has been suggested recently. This has created an interest in the inference of the block structure and length. The motivation is that haplotype blocks that are characterized well will make it relatively easier to quickly map all the genes carrying human diseases. To study the inference of haplotype block systematically, we propose a statistical framework. In this framework, the optimal haplotype block partitioning is formulated as the problem of statistical model selection; missing data can be handled in a standard statistical way; population strata can be implemented; block structure inference/hypothesis testing can be performed; prior knowledge, if present, can be incorporated to perform a Bayesian inference. The algorithm is linear in the number of loci, instead of NP-hard for many such algorithms. We illustrate the applications of our method to both simulated and real data sets.

Algorithms↗

PubMed2004

Identifying the susceptibility gene(s) in a set of trait-linked genes using genotype data.

There are generally three steps to isolate a disease linkage-susceptibility gene: genome-wide scan, fine mapping, and, last, positional cloning. The last step is time consuming and involves intensive laboratory work. In some cases, fine mapping cannot proceed further on a set of markers because they are tightly linked. For years, genetic statisticians have been trying different ways to narrow the fine-mapping results to provide some guidance for the next step of laboratory work. Although these methods are practical and efficient, most of them are based on IBD data, which usually can be inferred only from the genotype data with some uncertainty. The corresponding methods thus have no greater power than one using genotype data directly. Also, IBD-based methods apply only to relative pair data. Here, using genotype data, we have developed a statistical hypothesis-testing method to pinpoint a SNP, or SNPs, suspected of responsibility for a disease trait linkage among a set of SNPs tightly linked in a region. Our method uses genotype data of affected individuals or case-control studies, which are widely available in the laboratory. The testing statistic can be constructed using any genotype-based disease-marker disequilibrium measure and is asymptotically distributed as a chi-square mixture. This method can be used for singleton data, relative pair data, or general pedigree data. We have applied the method to simulated data as well as a real data set; it gives satisfactory results.

Chromosome Mapping↗

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↗

PubMed2003

Prevalence and determinants of diabetic retinopathy and cataracts in West African type 2 diabetes patients.

OBJECTIVE: To quantify the prevalence of, and risk factors for, diabetic retinopathy and cataracts in patients with type 2 diabetes, and their spouse controls, enrolled from 5 centers in 2 West African countries (Ghana and Nigeria). METHOD: The analysis cohort was made up of 840 subjects with type 2 diabetes, and their 191 unaffected spouse controls, who were enrolled and examined in Lagos, Enugu, and Ibadan, in Nigeria, and in Accra and Kumasi, in Ghana. A diagnosis of diabetic retinopathy was made only where a participant had a minimum of one microaneurysm in any field, as well as exhibiting hemorrhages (dot, blot, or flame shaped), and maculopathy (with or without clinically significant edema). RESULTS: Average duration of diabetes was 7.0 years, and mean age at diagnosis was 46.5 years. Prevalence of diabetic retinopathy was 17.9%. Cataracts were present in 44.9% of the patients with type 2 diabetes, and in 18.3% of spouse controls. The risk of developing retinopathy increased more than 3-fold for patients at the highest fasting plasma glucose (FPG) level (OR=3.4; 95% CI, 1.8-6.3), compared to patients at the lowest FPG level. The odds ratios for persons with diabetes for 10 years or more, compared to persons with diabetes for less than 5 years, was 7.3 (95% CI, 4.3-12.3) for retinopathy, and 2.6 (95% CI, 1.5-4.5) for cataracts. CONCLUSIONS: Cataracts were a more important cause of vision impairment than was diabetic retinopathy in this cohort. The prevalence of cataracts in patients with diabetes was more than twice that of their spouse controls, indicating that type 2 diabetes is an important risk factor for cataract formation. Individuals who developed type 2 diabetes at an earlier age were more likely to develop both diabetic retinopathy and cataracts. A strong positive association was observed between FPG level, duration of diabetes, and risk of retinopathy and cataracts. The low prevalence of retinopathy and cataracts observed within the first 5 years of diagnosis of diabetes in this cohort, suggests that intensive blood glucose control may reduce the risk of the development and progression of retinopathy and cataracts. In this regard, early eye examination, preferably at first presentation of elevated blood glucose, is highly recommended.

Adult↗

PubMed2002

The structure of haplotype blocks in the human genome.

Haplotype-based methods offer a powerful approach to disease gene mapping, based on the association between causal mutations and the ancestral haplotypes on which they arose. As part of The SNP Consortium Allele Frequency Projects, we characterized haplotype patterns across 51 autosomal regions (spanning 13 megabases of the human genome) in samples from Africa, Europe, and Asia. We show that the human genome can be parsed objectively into haplotype blocks: sizable regions over which there is little evidence for historical recombination and within which only a few common haplotypes are observed. The boundaries of blocks and specific haplotypes they contain are highly correlated across populations. We demonstrate that such haplotype frameworks provide substantial statistical power in association studies of common genetic variation across each region. Our results provide a foundation for the construction of a haplotype map of the human genome, facilitating comprehensive genetic association studies of human disease.

Africa↗

PubMed2002

Genome scan among Nigerians linking blood pressure to chromosomes 2, 3, and 19.

An understanding of the genetic influences on hypertension would help unravel the pathophysiology of this complex disorder and improve our understanding of causal mechanisms. Contemporary technology makes it possible to examine enough genetic markers to support a generalized search across the entire genome for candidate regions. In the present study, a family set was recruited from southwest Nigeria, and 378 microsatellite markers were typed on 792 individuals in 196 families. Multipoint variance component analysis identified linkage signals (logarithm of the odds [LOD] 1.74, P<0.0023) for systolic blood pressure on 19p (D19S714) and 19q (D19S246), whereas for diastolic blood pressure, linkage was observed on 2p (D2S1790), 3p (D3S1304), 5q (D5S1462), 7p (D7S3046), 7q (D7S821), and 10q (D10S1221). Other regions of interest (1.18<LOD<1.74, 0.0023<P<0.01) were found on chromosomes 1, 6, 8, 9, and 11. These results provide additional evidence of linkage between blood pressure and several genomic regions reported in previous studies. Some of these regions additionally harbor hypertension candidate genes. Although evidence of linkage for blood pressure has been very slow to accumulate, even in comparison to other complex traits, the sum of current evidence appears to implicate, in particular, 2p, 3p, and 19p. Study designs that make it possible to confirm these results with association analysis and narrow the genomic interval are needed in order to make progress in this field.

Adolescent↗