👤 Charles N Rotimi

Variations in lipid levels are attributed partly to genetic factors. Genome-wide association studies (GWASs) mainly performed in European, African American and Asian cohorts have identified variants associated with LDL-C, HDL-C, total cholesterol (TC) and triglycerides (TG), but few studies have been performed in sub-Saharan Africans. This study evaluated the effect of single nucleotide variants (SNVs) in eight candidate loci ( Show less

Although highly heritable, few genes have been linked to spontaneous intracerebral hemorrhage (SICH), which does not currently have any evidence-based disease-modifying therapy. Individuals of African ancestry are especially susceptible to SICH, even more so for indigenous Africans. We systematically reviewed the genetic variants associated with SICH and examined opportunities for rapidly advancing SICH genomic research for precision medicine. We searched the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) Genome Wide Association Study (GWAS) catalog and PubMed for original research articles on genetic variants associated with SICH as of 15 June 2019 using the PRISMA guideline. Eight hundred and sixty-four articles were identified using pre-specified search criteria, of which 64 met the study inclusion criteria. Among eligible articles, only 9 utilized GWAS approach while the rest were candidate gene studies. Thirty-eight genetic loci were found to be variously associated with the risk of SICH, hematoma volume, functional outcome and mortality, out of which 8 were from GWAS including APOE, CR1, KCNK17, 1q22, CETP, STYK1, COL4A2 and 17p12. None of the studies included indigenous Africans. Given this limited information on the genetic contributors to SICH, more genomic studies are needed to provide additional insights into the pathophysiology of SICH, and develop targeted preventive and therapeutic strategies. This call for additional investigation of the pathogenesis of SICH is likely to yield more discoveries in the unexplored indigenous African populations which also have a greater predilection. Show less

The metabolically healthy obesity (MHO) phenotype is an important obesity subtype in which obesity is not accompanied by any metabolic comorbidity. However, the underlying molecular mechanisms remain elusive. In this study, a shotgun proteomics approach to identify circulating biomolecules and pathways associated with MHO was used. The subjects were 20 African-American women: 10 MHO cases and 10 metabolically abnormal individuals with obesity (MAO) controls. Serum proteins were detected and quantified using label-free proteomics. Differential expression of proteins between the two groups was analyzed, and the list of differentially expressed proteins was analyzed to determine enriched biological pathways. Twenty proteins were differentially expressed between MHO and controls. These proteins included: hemoglobin subunits (HBA1, P = 6.00 × 10(-18) ), haptoglobin-related protein (HPR, P = 1.2 × 10(-15) ), apolipoproteins (APOB-100, P = 1.50 × 10(-40) ; APOA4, P = 1.1 × 10(-14) ), retinol-binding protein 4 (RBP4, P = 7.1 × 10(-08) ), and CRP (P = 2.0 × 10(-04) ). MHO was associated with lower levels of proinflammatory and higher levels of anti-inflammatory biomarkers when compared with MAO. Pathway analysis showed enrichment of lipids and inflammatory pathways, including LXR/RXR and FXR/RXR activation, and acute phase response signaling. These findings suggested that protection from dysregulated inflammatory and lipid processes were primary molecular hallmarks of MHO. The candidate biomarkers (AHSG, RBP4, and APOA4) identified in this study are potential prognostic markers for MHO. Show less

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation. Show less

A recent, large genome-wide association study (GWAS) of European ancestry individuals has identified multiple genetic variants influencing serum lipids. Studies of the transferability of these associations to African Americans remain few, an important limitation given interethnic differences in serum lipids and the disproportionate burden of lipid-associated metabolic diseases among African Americans. We attempted to evaluate the transferability of 95 lipid-associated loci recently identified in European ancestry individuals to 887 non-diabetic, unrelated African Americans from a population-based sample in the Washington, DC area. Additionally, we took advantage of the generally reduced linkage disequilibrium among African ancestry populations in comparison to European ancestry populations to fine-map replicated GWAS signals. We successfully replicated reported associations for 10 loci (CILP2/SF4, STARD3, LPL, CYP7A1, DOCK7/ANGPTL3, APOE, SORT1, IRS1, CETP, and UBASH3B). Through trans-ethnic fine-mapping, we were able to reduce associated regions around 75% of the loci that replicated. Between this study and previous work in African Americans, 40 of the 95 loci reported in a large GWAS of European ancestry individuals also influence lipid levels in African Americans. While there is now evidence that the lipid-influencing role of a number of genetic variants is observed in both European and African ancestry populations, the still considerable lack of concordance highlights the importance of continued ancestry-specific studies to elucidate the genetic underpinnings of these traits. Show less

Hyperglycaemia disproportionately affects African-Americans (AfAs). We tested the transferability of 18 single-nucleotide polymorphisms (SNPs) associated with glycaemic traits identified in European ancestry (EuA) populations in 5,984 non-diabetic AfAs. We meta-analysed SNP associations with fasting glucose (FG) or insulin (FI) in AfAs from five cohorts in the Candidate Gene Association Resource. We: (1) calculated allele frequency differences, variations in linkage disequilibrium (LD), fixation indices (F(st)s) and integrated haplotype scores (iHSs); (2) tested EuA SNPs in AfAs; and (3) interrogated within ± 250 kb around each EuA SNP in AfAs. Allele frequency differences ranged from 0.6% to 54%. F(st) exceeded 0.15 at 6/16 loci, indicating modest population differentiation. All iHSs were <2, suggesting no recent positive selection. For 18 SNPs, all directions of effect were the same and 95% CIs of association overlapped when comparing EuA with AfA. For 17 of 18 loci, at least one SNP was nominally associated with FG in AfAs. Four loci were significantly associated with FG (GCK, p = 5.8 × 10(-8); MTNR1B, p = 8.5 × 10(-9); and FADS1, p = 2.2 × 10(-4)) or FI (GCKR, p = 5.9 × 10(-4)). At GCK and MTNR1B the EuA and AfA SNPs represented the same signal, while at FADS1, and GCKR, the EuA and best AfA SNPs were weakly correlated (r(2) <0.2), suggesting allelic heterogeneity for association with FG at these loci. Few glycaemic SNPs showed strict evidence of transferability from EuA to AfAs. Four loci were significantly associated in both AfAs and those with EuA after accounting for varying LD across ancestral groups, with new signals emerging to aid fine-mapping. Show less

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. We have undertaken a genome-wide scan for body mass index (BMI) in 182 Nigerian families that included 769 individuals. 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. 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. Show less