Genetic Risk Scores for Cardiometabolic Traits in Sub-Saharan African Populations

AbstractThere is growing support for the use of genetic risk scores (GRS) in routine clinical settings. Due to the limited diversity of current genomic discovery samples, there are concerns that the predictive power of GRS will be limited in non-European ancestry populations. Here, we evaluated the predictive utility of GRS for 12 cardiometabolic traits in sub-Saharan Africans (AF; n=5200), African Americans (AA; n=9139), and European Americans (EA; n=9594). GRS were constructed as weighted sums of the number of risk alleles. Predictive utility was assessed using the additional phenotypic variance explained and increase in discriminatory ability over traditional risk factors (age, sex and BMI), with adjustment for ancestry-derived principal components. Across all traits, GRS showed upto a 5-fold and 20-fold greater predictive utility in EA relative to AA and AF, respectively. Predictive utility was most consistent for lipid traits, with percent increase in explained variation attributable to GRS ranging from 10.6% to 127.1% among EA, 26.6% to 65.8% among AA, and 2.4% to 37.5% among AF. These differences were recapitulated in the discriminatory power, whereby the predictive utility of GRS was 4-fold greater in EA relative to AA and up to 44-fold greater in EA relative to AF. Obesity and blood pressure traits showed a similar pattern of greater predictive utility among EA. This work demonstrates the poorer performance of GRS in AF and highlights the need to improve representation of multiethnic populations in genomic studies to ensure equitable clinical translation of GRS.Key MessagesGenetic Risk Score (GRS) prediction is markedly poorer in sub-Saharan Africans compared with African Americans and European AmericansTo ensure equitable clinical translation of GRS, there is need need to improve representation of multiethnic populations in genomic studies

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Genetic risk scores for cardiometabolic traits in sub-Saharan African populations

International Journal of Epidemiology ◽

10.1093/ije/dyab046 ◽

2021 ◽

Author(s):

Kenneth Ekoru ◽

Adebowale A Adeyemo ◽

Guanjie Chen ◽

Ayo P Doumatey ◽

Jie Zhou ◽

...

Keyword(s):

African Americans ◽

Genetic Risk ◽

European Ancestry ◽

Risk Scores ◽

Weighted Sums ◽

Predictive Utility ◽

Genetic Risk Scores ◽

European Americans ◽

Sub Saharan ◽

Cardiometabolic Traits

Abstract Background There is growing support for the use of genetic risk scores (GRS) in routine clinical settings. Due to the limited diversity of current genomic discovery samples, there are concerns that the predictive power of GRS will be limited in non-European ancestry populations. GRS for cardiometabolic traits were evaluated in sub-Saharan Africans in comparison with African Americans and European Americans. Methods We evaluated the predictive utility of GRS for 12 cardiometabolic traits in sub-Saharan Africans (AF; n = 5200), African Americans (AA; n = 9139) and European Americans (EUR; n = 9594). GRS were constructed as weighted sums of the number of risk alleles. Predictive utility was assessed using the additional phenotypic variance explained and the increase in discriminatory ability over traditional risk factors [age, sex and body mass index (BMI)], with adjustment for ancestry-derived principal components. Results Across all traits, GRS showed up to a 5-fold and 20-fold greater predictive utility in EUR relative to AA and AF, respectively. Predictive utility was most consistent for lipid traits, with percentage increase in explained variation attributable to GRS ranging from 10.6% to 127.1% among EUR, 26.6% to 65.8% among AA and 2.4% to 37.5% among AF. These differences were recapitulated in the discriminatory power, whereby the predictive utility of GRS was 4-fold greater in EUR relative to AA and up to 44-fold greater in EUR relative to AF. Obesity and blood pressure traits showed a similar pattern of greater predictive utility among EUR. Conclusions This work demonstrates the poorer performance of GRS in AF and highlights the need to improve representation of multiple ethnic populations in genomic studies to ensure equitable clinical translation of GRS.

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Genetics and geography of leukocyte telomere length in sub-Saharan Africans

Human Molecular Genetics ◽

10.1093/hmg/ddaa187 ◽

2020 ◽

Vol 29 (18) ◽

pp. 3014-3020

Author(s):

Steven C Hunt ◽

Matthew E B Hansen ◽

Simon Verhulst ◽

Michael A McQuillan ◽

William Beggs ◽

...

Keyword(s):

Cardiovascular Disease ◽

Genetic Variation ◽

African Americans ◽

Telomere Length ◽

Leukocyte Telomere Length ◽

Associated Diseases ◽

European Americans ◽

Sub Saharan

Abstract Leukocyte telomere length (LTL) might be causal in cardiovascular disease and major cancers. To elucidate the roles of genetics and geography in LTL variability across humans, we compared LTL measured in 1295 sub-Saharan Africans (SSAs) with 559 African–Americans (AAms) and 2464 European–Americans (EAms). LTL differed significantly across SSAs (P = 0.003), with the San from Botswana (with the oldest genomic ancestry) having the longest LTL and populations from Ethiopia having the shortest LTL. SSAs had significantly longer LTL than AAms [P = 6.5(e-16)] whose LTL was significantly longer than EAms [P = 2.5(e-7)]. Genetic variation in SSAs explained 52% of LTL variance versus 27% in AAms and 34% in EAms. Adjustment for genetic variation removed the LTL differences among SSAs. LTL genetic variation among SSAs, with the longest LTL in the San, supports the hypothesis that longer LTL was ancestral in humans. Identifying factors driving LTL variation in Africa may have important ramifications for LTL-associated diseases.

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Multiple distinct CHRNB3-CHRNA6 variants are genetic risk factors for nicotine dependence in African Americans and European Americans

Addiction ◽

10.1111/add.12478 ◽

2014 ◽

Vol 109 (5) ◽

pp. 814-822 ◽

Cited By ~ 28

Author(s):

Robert C. Culverhouse ◽

Eric O. Johnson ◽

Naomi Breslau ◽

Dorothy K. Hatsukami ◽

Brooke Sadler ◽

...

Keyword(s):

Risk Factors ◽

African Americans ◽

Nicotine Dependence ◽

Genetic Risk ◽

Genetic Risk Factors ◽

European Americans

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Imputed Gene Expression Risk Scores: A Functionally Informed Component of Polygenic Risk

10.1101/2020.12.01.369462 ◽

2020 ◽

Author(s):

Oliver Pain ◽

Kylie P. Glanville ◽

Saskia Hagenaars ◽

Saskia Selzam ◽

Anna Fürtjes ◽

...

Keyword(s):

Gene Expression ◽

Genetic Risk ◽

Elastic Net ◽

Risk Scores ◽

Future Research ◽

Functional Genomic ◽

Predictive Utility ◽

Polygenic Risk ◽

Regulated Gene Expression ◽

Gene Expression Levels

AbstractBackgroundIntegration of functional genomic annotations when estimating polygenic risk scores (PRS) can provide insight into aetiology and improve risk prediction. This study explores the predictive utility of gene expression risk scores (GeRS), calculated using imputed gene expression and transcriptome-wide association study (TWAS) results.MethodsThe predictive utility of GeRS was evaluated using 12 neuropsychiatric and anthropometric outcomes measured in two target samples: UK Biobank and the Twins Early Development Study (TEDS). GeRS were calculated based on imputed gene expression levels and TWAS results, using 53 gene expression-genotype panels, termed SNP-weight sets, capturing expression across a range of tissues. We compare the predictive utility of elastic net models containing GeRS within and across SNP-weight sets, and models containing both GeRS and PRS. We estimate the proportion of SNP-based heritability attributable to cis-regulated gene expression.ResultsGeRS significantly predicted a range of outcomes, with elastic net models combining GeRS across SNP-weight sets improving prediction. GeRS were less predictive than PRS, but models combining GeRS and PRS improved prediction for several outcomes, with relative improvements ranging from 0.3% for Height (p=0.023) to 4% for Rheumatoid Arthritis (p=5.9×10-8). The proportion of SNP-based heritability attributable to cis-regulated expression was modest for most outcomes, even when restricting GeRS to colocalised genes.ConclusionGeRS represent a component of PRS and could be useful for functional stratification of genetic risk. Only in specific circumstances can GeRS substantially improve prediction over PRS alone. Future research considering functional genomic annotations when estimating genetic risk is warranted.

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Multiple Metabolic Genetic Risk Scores and Type 2 Diabetes Risk in Three Racial/Ethnic Groups

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jc.2014-1818 ◽

2014 ◽

Vol 99 (9) ◽

pp. E1814-E1818 ◽

Cited By ~ 13

Author(s):

Yann C. Klimentidis ◽

Nathan E. Wineinger ◽

Ana I. Vazquez ◽

Gustavo de los Campos

Keyword(s):

Genetic Risk ◽

Association Studies ◽

Risk Scores ◽

Genome Wide Association Studies ◽

Racial Groups ◽

European Americans ◽

Genome Wide ◽

Meta Analyses ◽

Racial Ethnic

Context/Rationale: Meta-analyses of genome-wide association studies have identified many single-nucleotide polymorphisms associated with various metabolic and cardiovascular traits, offering us the opportunity to learn about and capitalize on the links between cardiometabolic traits and type 2 diabetes (T2D). Design: In multiple datasets comprising over 30 000 individuals and 3 ethnic/racial groups, we calculated 17 genetic risk scores (GRSs) for glycemic, anthropometric, lipid, hemodynamic, and other traits, based on the results of recent trait-specific meta-analyses of genome-wide association studies, and examined associations with T2D risk. Using a training-testing procedure, we evaluated whether additional GRSs could contribute to risk prediction. Results: In European Americans, we find that GRSs for T2D, fasting glucose, fasting insulin, and body mass index are associated with T2D risk. In African Americans, GRSs for T2D, fasting insulin, and waist-to-hip ratio are associated with T2D. In Hispanic Americans, GRSs for T2D and body mass index are associated with T2D. We observed a trend among European Americans suggesting that genetic risk for hyperlipidemia is inversely associated with T2D risk. The use of additional GRSs resulted in only small changes in prediction accuracy in multiple independent validation datasets. Conclusions: The analysis of multiple GRSs can shed light on T2D etiology and how it varies across ethnic/racial groups. Our findings using multiple GRSs are consistent with what is known about the differences in T2D pathogenesis across racial/ethnic groups. However, further work is needed to understand the putative inverse correlation of genetic risk for hyperlipidemia and T2D risk and to develop ethnic-specific GRSs.

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Type 2 Diabetes Genetic Risk Scores Are Associated With Increased Type 2 Diabetes Risk Among African Americans by Cardiometabolic Status

Clinical Medicine Insights Endocrinology and Diabetes ◽

10.1177/1179551417748942 ◽

2018 ◽

Vol 11 ◽

pp. 117955141774894 ◽

Cited By ~ 7

Author(s):

Jill Layton ◽

Xiaochen Li ◽

Changyu Shen ◽

Mary de Groot ◽

Leslie Lange ◽

...

Keyword(s):

Type 2 Diabetes ◽

African Americans ◽

Genetic Risk ◽

Genetic Risk Score ◽

Diabetes Risk ◽

Risk Scores ◽

Genetic Risk Scores ◽

Normal Ranges ◽

Increased Risk

The relationship between genetic risk variants associated with glucose homeostasis and type 2 diabetes risk has yet to be fully explored in African American populations. We pooled data from 4 prospective studies including 4622 African Americans to assess whether β-cell dysfunction (BCD) and/or insulin resistance (IR) genetic variants were associated with increased type 2 diabetes risk. The BCD genetic risk score (GRS) and combined BCD/IR GRS were significantly associated with increased type 2 diabetes risk. In cardiometabolic-stratified models, the BCD and IR GRS were associated with increased type 2 diabetes risk among 5 cardiometabolic strata: 3 clinically healthy strata and 2 clinically unhealthy strata. Genetic risk scores related to BCD and IR were associated with increased risk of type 2 diabetes in African Americans. Notably, the GRSs were significant predictors of type 2 diabetes among individuals in clinically normal ranges of cardiometabolic traits.

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Imputed gene expression risk scores: a functionally informed component of polygenic risk

Human Molecular Genetics ◽

10.1093/hmg/ddab053 ◽

2021 ◽

Author(s):

Oliver Pain ◽

Kylie P Glanville ◽

Saskia Hagenaars ◽

Saskia Selzam ◽

Anna Fürtjes ◽

...

Keyword(s):

Gene Expression ◽

Genetic Risk ◽

Elastic Net ◽

Risk Scores ◽

Future Research ◽

Functional Genomic ◽

Predictive Utility ◽

Polygenic Risk ◽

Regulated Gene Expression ◽

Gene Expression Levels

Abstract Integration of functional genomic annotations when estimating polygenic risk scores (PRS) can provide insight into aetiology and improve risk prediction. This study explores the predictive utility of gene expression risk scores (GeRS), calculated using imputed gene expression and transcriptome-wide association study (TWAS) results. The predictive utility of GeRS was evaluated using 12 neuropsychiatric and anthropometric outcomes measured in two target samples: UK Biobank and the Twins Early Development Study. GeRS were calculated based on imputed gene expression levels and TWAS results, using 53 gene expression–genotype panels, termed single nucleotide polymorphism (SNP)-weight sets, capturing expression across a range of tissues. We compare the predictive utility of elastic net models containing GeRS within and across SNP-weight sets, and models containing both GeRS and PRS. We estimate the proportion of SNP-based heritability attributable to cis-regulated gene expression. GeRS significantly predicted a range of outcomes, with elastic net models combining GeRS across SNP-weight sets improving prediction. GeRS were less predictive than PRS, but models combining GeRS and PRS improved prediction for several outcomes, with relative improvements ranging from 0.3% for height (P = 0.023) to 4% for rheumatoid arthritis (P = 5.9 × 10−8). The proportion of SNP-based heritability attributable to cis-regulated expression was modest for most outcomes, even when restricting GeRS to colocalized genes. GeRS represent a component of PRS and could be useful for functional stratification of genetic risk. Only in specific circumstances can GeRS substantially improve prediction over PRS alone. Future research considering functional genomic annotations when estimating genetic risk is warranted.

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Genetic risk scores across multiple cardiometabolic traits predict patterns of cardiometabolic risk in Filipino women

The FASEB Journal ◽

10.1096/fasebj.27.1_supplement.630.13 ◽

2013 ◽

Vol 27 (S1) ◽

Author(s):

Niha Zubair ◽

Linda Adair

Keyword(s):

Genetic Risk ◽

Cardiometabolic Risk ◽

Risk Scores ◽

Genetic Risk Scores ◽

Filipino Women ◽

Cardiometabolic Traits

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The genetic diversity of multiple sclerosis risk among Hispanic and African American populations living in the United States

Multiple Sclerosis Journal ◽

10.1177/1352458519863764 ◽

2019 ◽

Vol 26 (11) ◽

pp. 1329-1339 ◽

Cited By ~ 2

Author(s):

AH Beecham ◽

L Amezcua ◽

A Chinea ◽

CP Manrique ◽

C Rubi ◽

...

Keyword(s):

United States ◽

Multiple Sclerosis ◽

African American ◽

African Americans ◽

Genetic Risk ◽

Statistical Power ◽

Genetic Risk Score ◽

The United States ◽

European Ancestry ◽

Risk Scores

Background: Substantial progress has been made toward unraveling the genetic architecture of multiple sclerosis (MS) within populations of European ancestry, but few genetic studies have focused on Hispanic and African American populations within the United States. Objective: We sought to test the relevance of common European MS risk variants outside of the major histocompatibility complex ( n = 200) within these populations. Methods: Genotype data were available on 2652 Hispanics (1298 with MS, 1354 controls) and 2435 African Americans (1298 with MS, 1137 controls). We conducted single variant, pathway, and cumulative genetic risk score analyses. Results: We found less replication than statistical power suggested, particularly among African Americans. This could be due to limited correlation between the tested and causal variants within the sample or alternatively could indicate allelic and locus heterogeneity. Differences were observed between pathways enriched among the replicating versus all 200 variants. Although these differences should be examined in larger samples, a potential role exists for gene–environment or gene–gene interactions which alter phenotype differentially across racial and ethnic groups. Cumulative genetic risk scores were associated with MS within each study sample but showed limited diagnostic capability. Conclusion: These findings provide a framework for fine-mapping efforts in multi-ethnic populations of MS.

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