scholarly journals The Epidemiology and Genetics of Hyperuricemia and Gout across Major Racial Groups: A Literature Review and Population Genetics Secondary Database Analysis

2021 ◽  
Vol 11 (3) ◽  
pp. 231
Author(s):  
Faven Butler ◽  
Ali Alghubayshi ◽  
Youssef Roman
Keyword(s):  
Literature Review ◽  
Risk Allele ◽  
Statistical Significance ◽  
Elevated Serum ◽  
The United States ◽  
Allele Frequencies ◽  
Racial Groups ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Risk Alleles

Gout is an inflammatory condition caused by elevated serum urate (SU), a condition known as hyperuricemia (HU). Genetic variations, including single nucleotide polymorphisms (SNPs), can alter the function of urate transporters, leading to differential HU and gout prevalence across different populations. In the United States (U.S.), gout prevalence differentially affects certain racial groups. The objective of this proposed analysis is to compare the frequency of urate-related genetic risk alleles between Europeans (EUR) and the following major racial groups: Africans in Southwest U.S. (ASW), Han-Chinese (CHS), Japanese (JPT), and Mexican (MXL) from the 1000 Genomes Project. The Ensembl genome browser of the 1000 Genomes Project was used to conduct cross-population allele frequency comparisons of 11 SNPs across 11 genes, physiologically involved and significantly associated with SU levels and gout risk. Gene/SNP pairs included: ABCG2 (rs2231142), SLC2A9 (rs734553), SLC17A1 (rs1183201), SLC16A9 (rs1171614), GCKR (rs1260326), SLC22A11 (rs2078267), SLC22A12 (rs505802), INHBC (rs3741414), RREB1 (rs675209), PDZK1 (rs12129861), and NRXN2 (rs478607). Allele frequencies were compared to EUR using Chi-Square or Fisher’s Exact test, when appropriate. Bonferroni correction for multiple comparisons was used, with p < 0.0045 for statistical significance. Risk alleles were defined as the allele that is associated with baseline or higher HU and gout risks. The cumulative HU or gout risk allele index of the 11 SNPs was estimated for each population. The prevalence of HU and gout in U.S. and non-US populations was evaluated using published epidemiological data and literature review. Compared with EUR, the SNP frequencies of 7/11 in ASW, 9/11 in MXL, 9/11 JPT, and 11/11 CHS were significantly different. HU or gout risk allele indices were 5, 6, 9, and 11 in ASW, MXL, CHS, and JPT, respectively. Out of the 11 SNPs, the percentage of risk alleles in CHS and JPT was 100%. Compared to non-US populations, the prevalence of HU and gout appear to be higher in western world countries. Compared with EUR, CHS and JPT populations had the highest HU or gout risk allele frequencies, followed by MXL and ASW. These results suggest that individuals of Asian descent are at higher HU and gout risk, which may partly explain the nearly three-fold higher gout prevalence among Asians versus Caucasians in ambulatory care settings. Furthermore, gout remains a disease of developed countries with a marked global rising.

scholarly journals The Epidemiology and Genetics of Hyperuricemia and Gout Across Major Racial Groups: A literature Review and Population Genetics Secondary Data Analysis

2021 ◽  
Author(s):  
Faven Butler ◽  
Ali Alghubayshi ◽  
Youssef Malak Roman
Keyword(s):  
Literature Review ◽  
Risk Allele ◽  
Statistical Significance ◽  
Elevated Serum ◽  
The United States ◽  
Allele Frequencies ◽  
Racial Groups ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Risk Alleles

Abstract BackgroundGout is an inflammatory condition caused by elevated serum urate (SU), a condition known as hyperuricemia (HU). Genetic variations, including single nucleotide polymorphisms (SNPs), can alter the function of urate transporters, leading to differential HU and gout prevalence across different populations. In the United States (U.S.)., gout prevalence differentially affects certain racial groups. The objective of this proposed analysis is to compare the frequency of urate-related genetic risk alleles between Europeans (EUR) and the following major racial groups: Africans in Southwest U.S. (ASW), Han-Chinese (CHS), Japanese (JPT), and Mexican (MXL) from the 1000 Genomes Project. MethodsEnsembl genome browser of the 1000 Genomes Project was used to conduct cross-population allele frequency comparisons of 11 SNPs across 11 genes, physiologically involved and significantly associated with SU levels and gout risk. Gene/SNP pairs included: ABCG2 (rs2231142), SLC2A9 (rs734553), SLC17A1 (rs1183201), SLC16A9 (rs1171614), GCKR (rs1260326), SLC22A11 (rs2078267), SLC22A12 (rs505802), INHBC (rs3741414), RREB1 (rs675209), PDZK1 (rs12129861), and NRXN2 (rs478607). Allele frequencies were compared to EUR using Chi-Square or Fisher's Exact test, when appropriate. Bonferroni correction for multiple comparisons was used, with p<0.005 for statistical significance. Risk alleles were defined as the allele that is associated with baseline or higher HU and gout risks. The cumulative HU or gout risk allele index of the 11 SNPs was estimated for each population. The prevalence of HU and gout in U.S. and non-US populations was evaluated using a literature review.ResultsCompared with EUR, the SNP frequencies of 7/11 in ASW, 9/11 in MXL, 9/11 JPT, and 11/11 CHS were significantly different. HU or gout risk allele indices were 5, 6, 9, and 11 in ASW, MXL, CHS, and JPT, respectively. Out of the 11 SNPs, the percentage of risk alleles in CHS and JPT was 100%. Compared to non-US populations, the prevalence of HU and gout appear to be higher in western world countries.ConclusionsCompared with EUR, CHS and JPT populations had the highest HU or gout risk allele frequencies, followed by MXL and ASW. These results suggest that individuals of Asian descent are at higher HU and gout risk, which may partly explain the 2.7-fold higher gout prevalence among Asians versus Caucasians in ambulatory care settings. Furthermore, gout remains a disease of developed countries with a marked global rising.

scholarly journals Efficient analysis of large datasets and sex bias with ADMIXTURE

2016 ◽  
Author(s):  
Suyash S. Shringarpure ◽  
Carlos D. Bustamante ◽  
Kenneth L. Lange ◽  
David H. Alexander
Keyword(s):  
Large Datasets ◽  
Allele Frequencies ◽  
Sex Bias ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Males And Females ◽  
Related Individuals ◽  
Using Data ◽  
Human Ancestry ◽  
Individual Ancestry

Background: A number of large genomic datasets are being generated for studies of human ancestry and diseases. The ADMIXTURE program is commonly used to infer individual ancestry from genomic data. Results: We describe two improvements to the ADMIXTURE software. The first enables ADMIXTURE to infer ancestry for a new set of individuals using cluster allele frequencies from a reference set of individuals. Using data from the 1000 Genomes Project, we show that this allows ADMIXTURE to infer ancestry for 10,920 individuals in a few hours (a 5x speedup). This mode also allows ADMIXTURE to correctly estimate individual ancestry and allele frequencies from a set of related individuals. The second modification allows ADMIXTURE to correctly handle X-chromosome (and other haploid) data from both males and females. We demonstrate increased power to detect sex-biased admixture in African-American individuals from the 1000 Genomes project using this extension. Conclusions: These modifications make ADMIXTURE more efficient and versatile, allowing users to extract more information from large genomic datasets.

scholarly journals How genetic disease risks can be misestimated across global populations

2017 ◽  
Author(s):  
Michelle S Kim ◽  
Kane P Patel ◽  
Andrew K Teng ◽  
Ali J Berens ◽  
Joseph Lachance
Keyword(s):  
Genetic Disease ◽  
Risk Allele ◽  
Association Studies ◽  
Allele Frequencies ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Risk Alleles ◽  
Disease Associations ◽  
Disease Risks

AbstractBackgroundAccurate assessment of health disparities requires unbiased knowledge of genetic risks in different populations. Unfortunately, most genome-wide association studies use genotyping arrays and European samples. Here, we integrate whole genome sequence data from global populations, results from thousands of GWAS, and extensive computer simulations to identify how genetic disease risks can be misestimated.ResultsIn contrast to null expectations, we find that risk allele frequencies at known disease loci are significantly different for African populations compared to other continents. Strikingly, ancestral risk alleles are found at 9.51% higher frequency in Africa and derived risk alleles are found at 5.40% lower frequency in Africa. By simulating GWAS with different study populations, we find that non-African cohorts yield disease associations that have biased allele frequencies and that African cohorts yield disease associations that are relatively free of bias. We also find empirical evidence that genotyping arrays and SNP ascertainment bias contribute to continental differences in risk allele frequencies. Because of these causes, polygenic risk scores can be grossly misestimated for individuals of African descent. Importantly, continental differences in risk allele frequencies are only moderately reduced if GWAS use whole genome sequences and hundreds of thousands of cases and controls. Finally, comparisons between uncorrected and corrected genetic risk scores reveal the benefits of considering whether risk alleles are ancestral or derived.ConclusionsOur results imply that caution must be taken when extrapolating GWAS results from one population to predict disease risks in another population.

scholarly journals Open-Access STRS Database Of Populations From The 1000 Genomes Project Using High Coverage Phase 3 Data

2021 ◽  
Author(s):  
Tamara Soledad Frontanilla ◽  
Guilherme Valle Silva ◽  
Jesus Ayala ◽  
Celso Teixeira Mendes
Keyword(s):  
Open Access ◽  
Forensic Genetics ◽  
Allele Frequencies ◽  
Equilibrium Analysis ◽  
1000 Genomes Project ◽  
Phase 3 ◽  
Principal Coordinates Analysis ◽  
High Coverage ◽  
1000 Genomes ◽  
Principal Coordinates

Accurate STR genotyping from next-generation sequencing (NGS) data has been challenging. Haplotype inference and phasing for STRs (HipSTR) was specifically developed to deal with genotyping errors and obtain reliable STR genotypes from whole-genome sequencing datasets. The objective of this investigation was to perform a comprehensive genotyping analysis of a set of STRs of broad forensic interest from the 1000 Genomes populations and release a reliable open-access STR database to the forensic genetics community. A set of 22 STR markers were analyzed using the CRAM files of the 1000 Genomes Project Phase 3 high-coverage (30x) dataset generated by the New York Genome Center (NYGC). HipSTR was used to call genotypes from 2,504 samples from 26 populations organized into five groups: African, East Asian, European, South Asian, and admixed American. The D21S11 marker could not be detected in the present study. Moreover, the Hardy-Weinberg equilibrium analysis, coupled with a comprehensive analysis of allele frequencies, revealed that HipSTR could not identify longer Penta E (and Penta D at a lesser extent) alleles. This issue is probably due to the limited length of sequencing reads available for genotype calling, resulting in heterozygote deficiency. Notwithstanding that, AMOVA, a clustering analysis using STRUCTURE, and a Principal Coordinates Analysis revealed a clear-cut separation between the four major ancestries sampled by the 1000 Genomes Consortium (AFR, EUR, EAS, SAS). Meanwhile, the AMOVA results corroborated previous reports that most of the variance is (97.12%) observed within populations. This set of analyses revealed that except for larger Penta D and Penta E alleles, allele frequencies and genotypes defined by HipSTR from the 1000 Genomes Project phase 3 data and offered as an open-access database are consistent and highly reliable.

Abstract 537: Higher Prevalence of Risk Alleles for Hyperuricemia Parallels Elevated Incidence of Gout and Growing Risk for Cardiovascular Diseases in a Hmong Population

2014 ◽  
Vol 34 (suppl_1) ◽  
Author(s):  
Youssef M Roman ◽  
Jenny D Xiong ◽  
Jeremiah S Menk ◽  
Kathleen Culhane-Pera ◽  
Robert J Straka
Keyword(s):  
Elevated Serum ◽  
Asian Population ◽  
Allele Frequencies ◽  
Fisher Exact Test ◽  
Snp Analysis ◽  
Cvd Risk ◽  
Significance Level ◽  
Exact Test ◽  
Risk Alleles ◽  
Increased Risk

Introduction: Hyperuricemia (HU) is the strongest predictor of gout and highly associated with major CVD including hypertension, HF, and CKD. The Hmong, a unique Asian population numbering > 60,000 in Minnesota, have a two-fold increased risk of gout compared to non-Hmong, rising prevalence of CVD, and may differ from other Asian populations in these regards. A genetic predisposition to elevated Serum Uric Acid (SUA) may help identify individuals at risk for gout and CVD. We quantified the Minor Allele Frequencies (MAFs) of known genetic variants (SNPs) associated with HU and compared the MAFs between our Hmong sample and both a reference (HapMap) population of Caucasian (CEU) as well as Han-Chinese (CHB). Methods: Salivary DNA from 235 self-identified Hmong was genotyped using either a Sequenom (iPLEX Gold) or TaqMan approach. MAFs for seven SNPs within candidate genes ( SLC2A9, SLC22A12, PDZK1, and ABCG2 ) identified by GWAS, were determined in our Hmong sample. Associations between HU and genotype were examined for 57/235 Hmong with known SUA levels. A Chi-Square or Fisher exact test with a Bonferroni corrected significance level (<0.007) was used to evaluate MAF differences. Mean SUA concentrations were compared by genotype using one-way ANOVA. Results: Our Hmong participant's age [mean (±SD)] was 30.2 (15.4) years, with >61% overweight or obese and a mean (±SD) SUA of 6.3 (1.7) mg/dL. Although the frequency of risk alleles in the Hmong were significantly higher compared to CEU (6/7) and CHB (3/7) populations, independent SNP by SNP analysis did not show a clear association with SUA. Risk allele frequencies were always more frequent in the Hmong versus comparator groups. Conclusion: MAFs of selected SNPs for HU are not independent of race. The higher prevalence of risk alleles for HU in the Hmong versus CEU and CHB populations may partly explain the clinically observed higher prevalence of gout and CVD risk in the Hmong. Although sample size precludes a robust assessment of an association between genotype and SUA, to our knowledge this is the first study to examine the genetic basis of HU in the Hmong.

scholarly journals Major sex differences in allele frequencies for X chromosome variants in the 1000 Genomes Project data

2021 ◽  
Author(s):  
Zhong Wang ◽  
Lei Sun ◽  
Andrew D Paterson
Keyword(s):  
Sex Differences ◽  
X Chromosome ◽  
Association Studies ◽  
Allele Frequencies ◽  
Whole Genome Sequence ◽  
P Value ◽  
1000 Genomes Project ◽  
Phase 3 ◽  
High Coverage ◽  
1000 Genomes

An unexpectedly high proportion of SNPs on the X chromosome in the 1000 Genomes Project phase 3 data were identified with significant sex differences in minor allele frequencies (sdMAF). sdMAF persisted for many of these SNPs in the recently released high coverage whole genome sequence, and it was consistent between the five super-populations. Among the 245,825 common biallelic SNPs in phase 3 data presumed to be high quality, 2,039 have genome-wide significant sdMAF (p-value <5e-8). sdMAF varied by location: (NPR)=0.83%, pseudo-autosomal region (PAR1)=0.29%, PAR2=13.1%, and PAR3=0.85% of SNPs had sdMAF, and they were clustered at the NPR-PAR boundaries, among others. sdMAF at the NPR-PAR boundaries are biologically expected due to sex-linkage, but have generally been ignored in association studies. For comparison, similar analyses found only 6, 1 and 0 SNPs with significant sdMAF on chromosomes 1, 7 and 22, respectively. Future X chromosome analyses need to take sdMAF into account.

scholarly journals Mapping Bias Overestimates Reference Allele Frequencies at theHLAGenes in the 1000 Genomes Project Phase I Data

2015 ◽  
Vol 5 (5) ◽  
pp. 931-941 ◽  
Author(s):  
Débora Y. C. Brandt ◽  
Vitor R. C. Aguiar ◽  
Bárbara D. Bitarello ◽  
Kelly Nunes ◽  
Jérôme Goudet ◽  
...  
Keyword(s):  
Phase I ◽  
Allele Frequencies ◽  
1000 Genomes Project ◽  
Reference Allele ◽  
1000 Genomes ◽  
Mapping Bias

scholarly journals The frequencies of autoimmunity risk alleles of some genes in Belarus population

2010 ◽  
Vol 8 (1) ◽  
pp. 50-58
Author(s):  
Elena A Aksenova ◽  
Tatiana N Pokladok ◽  
Dina V Boiko ◽  
Nina G Danilenko
Keyword(s):  
T Lymphocyte ◽  
Protein Tyrosine Phosphatase ◽  
Risk Allele ◽  
Cytotoxic T Lymphocyte ◽  
Tyrosine Phosphatase ◽  
Allele Frequencies ◽  
Protective Allele ◽  
Risk Alleles ◽  
Genotype And Allele Frequencies ◽  
Allele Combination

The population genotype and allele frequencies of +49A/G cytotoxic T-lymphocyte-associated antigen-4 (CTLA4); C1858T protein tyrosine phosphatase gene (PTPN22); –23HphIА/T insulin gene (INS) loci in native Belarusians from 6 ethnogeographic regions were estimated. The frequencies of risk allele homozygotes were: +49G CTLA4 — 17,3%; –23HphIА INS 50,7% — 1858Т PTPN22 — 4,1%. 5 individuals out of 662 investigated were risk homozygotes for all three genes, 21 were homozygotes with protective allele combination. The uniformity of genotypes and alleles distribution of investigated locuses across Belarus regions was demonstrated. 

Sign in / Sign up

Export Citation Format

Share Document