• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of ajhgLink to Publisher's site
Am J Hum Genet. Nov 2001; 69(5): 1080–1094.
Published online Oct 5, 2001. doi:  10.1086/323922
PMCID: PMC1274377

Markers for Mapping by Admixture Linkage Disequilibrium in African American and Hispanic Populations

Abstract

Population linkage disequilibrium occurs as a consequence of mutation, selection, genetic drift, and population substructure produced by admixture of genetically distinct ethnic populations. African American and Hispanic ethnic groups have a history of significant gene flow among parent groups, which can be of value in affecting genome scans for disease-gene discovery in the case-control and transmission/disequilibrium test designs. Disease-gene discovery using mapping by admixture linkage disequilibrium (MALD) requires a map of polymorphic markers that differentiate between the founding populations, along with differences in disease-gene allele frequencies. We describe markers appropriate for MALD mapping by assessing allele frequencies of 744 short tandem repeats (STRs) in African Americans, Hispanics, European Americans, and Asians, by choosing STR markers that have large differences in composite δ, log-likelihood ratios, and/or I*(2) for MALD. Additional markers can be added to this MALD map by utilization of the rapidly growing single-nucleotide–polymorphism databases and the literature, to achieve a 3–10-cM scanning scale. The map will be useful for studies of diseases, including prostate and breast cancer, diabetes, hypertension, and end-stage renal disease, that have large differences in incidence between the founding populations of either Hispanics or African Americans.

Introduction

The analysis of complex human diseases requires novel genetic strategies and approaches as we enter the known genomic sequence era. Approaches that involve the use of traditional family linkage analysis have yielded the locations of many genes, especially those that are highly penetrant and encode simple Mendelian disease phenotypes. More recently, use of sib-pair analysis, the transmission/disequilibrium test (TDT), and homozygosity mapping have made the identification of the genes involved in complex diseases more tractable (Risch and Merikangas 1996; Risch 2000). Whole-genome scans have identified genetic regions and genes involved in many diseases, including type I diabetes, asthma, prostate cancer, and others (e.g., Smith et al. 1996; Mein et al. 1998; Arngrimsson et al. 1999; The Tourette Syndrome Association International Consortium for Genetics 1999; Bellamy et al. 2000; Walder et al. 2000; Wiggs et al. 2000). Although these family-based approaches are powerful and make possible the identification of genes involved in many complex diseases, some diseases in which environmental and viral factors are important components may be best addressed by approaches that center around a case-control and TDT design.

The detection of polymorphic genes that influence quantitative traits, disease states, and other characters is the goal of population genetic association studies, but it depends upon the persistence of measurable linkage disequilibrium (i.e., haplotype allele association) between markers and undiscovered loci. In white populations, the extent and usefulness of linkage disequilibrium is generally limited to regions smaller than ~100 kb, because of recent population history (Bodmer 1986; Laan and Pääbo 1997; Huttley et al. 1999; Reich et al. 2001). The power of this approach depends upon how far linkage disequilibrium extends over a chromosomal interval which, in turn, determines the spacing and number of markers required for a genome scan.

One promising approach is mapping by admixture linkage disequilibrium (MALD), where the samples are collected from an admixed population in patient cohorts (Briscoe et al. 1994; Stephens et al. 1994; McKeigue 1997, 1998; Kaplan et al. 1998; Zheng and Elston 1999). These theoretical treatments and simulations point out that recent admixture generates linkage disequilibrium that can extend for many centimorgans and can persist for as many as 20 generations. We have recently detected admixture linkage disequilibrium (ALD) across tens of centimorgans around the FY (Duffy) gene in African Americans (Lautenberger et al. 2000).

African Americans and Hispanics seem ideal for MALD-based association ascertainment. Studies have shown that African Americans represent an admixed population with significant genetic contributions from both African and European ancestors (Chakraborty and Weiss 1988; Chakraborty et al. 1991). Recent estimates of the proportion of European genes in African American populations range from 6.8% for Sapelo Island in Georgia to 26% for Chicago (Long 1991; Chakraborty et al. 1992; Parra et al. 1998; Destro-Bisol et al. 1999). Hispanics—a complex U.S. ethnic group that includes Puerto Ricans, Cubans, Mexican Americans, and Spanish Americans—also constitute an admixed population of primarily European, 18%–31% Native American, and 3%–31% African origins (Hanis et al. 1991; Long et al. 1991), which is promising for MALD analysis.

Earlier studies of RFLPs suggested that establishing a collection of differentiating markers would be difficult to achieve with single-nucleotide polymorphisms (SNPs), where at most only 20% of 257 markers had large enough differences to be informative for MALD mapping (Dean et al. 1994), whereas subsequent work on short tandem repeat polymorphisms (STRs) suggested that about half had large differences (Bowcock et al. 1994). Current efforts of the SNP consortium (Altshuler et al. 2000) are likely to bring these biallelic markers to the forefront for MALD mapping in a case-control and TDT setting. However, the more-polymorphic STRs provide higher information content for TDT and case-control approaches, and, given the current state of genotyping technology, an STR-based MALD map provides a valuable gene-mapping resource.

In the present study, we sought to identify markers appropriate for MALD analysis, by genotyping of African Americans, Europeans, Hispanics, and Asians, using 421 STR loci and supplementing the data set with data from 323 markers from an asthma genome scan (Collaborative Study on the Genetics of Asthma 1997). These data were used to estimate allele frequencies and the usefulness of the loci for MALD mapping. Since MALD assessment provides remarkable potential for the discovery of novel genes involved in common diseases, the comprehensive set of markers with large differences between the founding populations for African Americans and Hispanics provides a foundation for future MALD gene localization studies.

Subjects and Methods

Patient DNAs were obtained from collections of human DNAs at the Laboratory of Genomic Diversity and included 45 African Americans, 45 Europeans, 45 Hispanics, and 40 Asians (Dean et al. 1994; Smith et al. 1997; O'Brien 2000; O'Brien et al. 2000). Early in the study, a different set of patients was used with fewer individuals (37 African Americans, 25 European Americans, 21 Hispanics, and 21 Asians), with the African American samples containing 18 parent/offspring pairs. DNAs from lymphoblastoid or fibroblast cell lines were extracted using methods we have published elsewhere (Dean et al. 1994). Some of the allele-frequency data have been reported elsewhere as part of an HIV-1/AIDS candidate gene analysis (Shin et al. 2000) or an asthma genetics genome scan (Collaborative Study on the Genetics of Asthma 1997).

STR locus primers were obtained from a variety of sources, including (1) commercial STR panels that were in development (Applied Biosystems), (2) the Applied Biosystems X chromosome STR kit, (3) ongoing HIV-1/AIDS projects (O'Brien et al. 2000; Shin et al. 2000), (4) work around the FY gene (Lautenberger et al. 2000), and (5) experiments designed to fill gaps in the MALD map with additional STR loci. Amplification was performed with Perkin-Elmer 9600 thermal cyclers. Loci were amplified with AmpliTaq DNA polymerase under the following conditions: 2 min at 95°C; 10 cycles of 30 s at 94°C, 15 s at 55°C, and 15 s at 72°C; 20 cycles with a lowered (89°C) denaturation temperature, followed by a 72°C final extension for 10 min. In addition, a Taq gold (PE Biosystems) touchdown protocol was also used later in the project; this protocol consisted of 10 min at 95°C; 10 cycles of 30 s at 94°C, 30 s at 65°C, and 30 s at 72°C; 20 cycles of the same conditions but dropping the annealing temperature by 0.5°C, to 55°C; 15 cycles of annealing at 55°C; and a 72°C final extension for 10 min. Loci that yielded banding patterns characteristic of +A addition were tried again, using a 90-min final extension, no final extension, and/or by redesigning the unlabeled reverse primer to add a guanine or to finish with the sequence of GTTT (G/A/C) at the 5′ end (Brownstein et al. 1996; Magnuson et al. 1996). Primer sequences and allele size ranges for the primers we designed are available at the Laboratory of Genomic Diversity Web site. Fluorescently labeled PCR products (FAM, HEX, TET, and NED) were separated on Applied Biosystems 373 and 377 sequencers. Gels were analyzed with Genescan collection and analysis software, and genotypes were called using Genotyper software (Applied Biosystems). Alleles were binned using linear regression, visual examination, and Genotyper software. Data were analyzed using the Statistical Analysis System (SAS) (SAS Institute, Inc.). Estimates of composite δ (δc) and log-likelihood allelic ratio (LLAR) values (Shriver et al. 1997; Stephens et al. 1999) were computed by SAS. The δc value is defined as the sum of the absolute value of all n allelic frequency (fi) differences divided by 2:

equation image

where fiA and fiB are the frequencies of the ith allele in the two groups, A and B, being compared at a locus. The LLAR statistic was calculated over all n alleles as

equation image

A program written in Pascal was used to calculate the MALD-TDT (transmission/disequilibrium test) allele-collapsing statistic, I*(2) (Kaplan et al. 1998). Regression analysis of these comparison measures were first examined as linear models, and then curvilinear terms were added to better fit the residuals. Autocorrelation of δc values for the comparison of European Americans versus both African Americans and Hispanics was examined using longitudinal data analysis techniques (Diggle et al. 1994).

Results

Estimated allele frequencies from the 744 STR loci examined are available at the Laboratory of Genomic Diversity Web site. Those allele frequency estimates were used to determine differences between the four racial/ethnic groups. Comparisons of African Americans versus Asians, African Americans versus European Americans, African Americans versus Hispanics, Asians versus European Americans, Asians versus Hispanics, and Hispanics versus European Americans were calculated as (1) δc, one-half the sum of the absolute value of the allele frequency differences (Shriver et al. 1997; Stephens et al. 1999; Lautenberger et al. 2000) and (2) the LLAR estimate of the discrimination power of each locus derived from some of our previous work (Shriver et al. 1997). The comparisons of African Americans versus European Americans and of European Americans versus Hispanics were evaluated as the optimal I*(2) (Kaplan et al. 1998). Values of δc for the African American versus European American and the European American versus Hispanic comparisons are plotted by chromosome position in figure 1.

Figure  1
δc values for the loci examined across the human genome, in comparisons between European Americans and African Americans (shaded triangles) and between European Americans and Hispanics (white circles). δc values are shown on the Y-axis, ...

A comparison of the behavior of the three MALD statistics—δc, LLAR, and I*(2)—shows a high level of correlation. For example, in the comparison of 724 loci between African Americans and European Americans, the correlation coefficient of LLAR versus δc was .88, with Y=0.12×e5.98X (fig. 2a). Similar results were obtained from the regression of I*(2) versus δc in the same ethnic group comparison (r2=.81; Y=0.044×e7.38X; fig. 2b). Some of the strengths and limitations of these different MALD statistics have been discussed elsewhere (Shriver et al. 1997; Kaplan et al. 1998; Stephens et al. 1999).

Figure  2
Relationship between differences seen at individual markers in δc and LLAR (A) and STR I*(2) (B) in African Americans, along with African American versus Hispanic δc values (C).

The distribution of δc was examined by chromosome and as a function of distance. No depression or elevation of all six δc comparisons was seen by chromosome in an analysis of variance (results not shown). An autocorrelation analysis of markers spaced at [less-than-or-eq, slant]50 cM showed no evidence of closely spaced markers having similar δc values in either admixed population in variograms. A representative comparison for African American versus European American differences in δc of marker pairs [less-than-or-eq, slant]10 cM apart is shown in figure 3. The lack of upward trend in the kernel smoothing line, which is flat in both populations out to 50 cM (not shown), indicates that the δc values of closely spaced marker pairs are no more similar than those of distantly spaced ones. The sample autocorrelation functions estimated with intrapair distances categorized into 1-cM-wide bins also displayed no evidence of positive autocorrelation in either population (analysis not shown).

Figure  3
Variograms of marker δc in African Americans. For each point, the X and Y coordinates represent the map distance between markers j and k on chromosome i (map location of j > map location of k) and half the squared difference of δ ...

The distribution of allelic differences conforms to our expectations, which are based upon the natural history of admixed Hispanics and African Americans (both including gene flow from Europeans) and nonadmixed Asian and European groups (fig. 4). Thus, the greatest difference is seen in the comparison between Asians and African Americans (who share little recent admixture), whereas the smallest differences occur between Hispanics and European Americans. For populations where MALD analysis would be feasible, appreciable divergence is apparent. In the comparison of African Americans versus Europeans, 44% of STR loci show δc>.3, and 74% of loci show δc>.2. For the Hispanic-European comparison, 17% of loci have δc>.3, and 45% have δc>.2. These differences are critical, insofar as the size of δ and δc are the principal determinants of linkage-disequilibrium detection in admixed populations (Chakraborty and Weiss 1988; Chakraborty et al. 1991; Stephens et al. 1994, 1999). The operative δc for Hispanics and African Americans is almost certainly underestimated here, since our comparison utilized admixed populations and not the actual parent population—native Africans, in the case of African Americans. To illustrate this underestimation, consider the comparison of African Americans versus Asians (fig. 4A, B), which shows the greatest δc, since these populations do not share any recent gene flow. This comparison shows 80% of STR loci with δc>.3 and 95% of the loci with δc>.2. These values are a plausible surrogate estimator of similar mean distances between native African and European population structure. However, it is not expected that the same loci with high δc in the Asian versus African American comparison would be the same as those with high δc in other comparisons. This discordance is illustrated in figure 2C, where the correlation between STR δc values in comparisons of different ethnic groups is low (r2=.25), considering that both comparisons are with the same European American reference group.

Figure  4
Cumulative frequency distributions of differences between African Americans, Asians, Hispanics, and European Americans are shown as δc (A), LLAR (B), and optimized STR allele-collapsing statistic I*(2) (C) (Kaplan et al. 1998).

Discussion

The development of allele frequency data for MALD mapping is critical to the advancement of the methodology for gene mapping studies. The theoretical basis of MALD mapping is now well established (Chakraborty and Weiss 1988; Chakraborty et al. 1991; Briscoe et al. 1994; Stephens et al. 1994; McKeigue 1997, 1998; Stephens et al. 1999; Zheng and Elston 1999). Empirical studies have also found MALD over large distances of as much as 30 cM around the FY gene in African Americans, and strong linkage disequilibrium was found with STRs in an 8-cM core around the FY gene (Parra et al. 1998; Hamblin and Di Rienzo 2000; Lautenberger et al. 2000; Wilson and Goldstein 2000). There is ample evidence that ongoing and differential levels of admixture across populations must be taken into account in any disease gene identification efforts (Parra et al. 2001; Pfaff et al. 2001). Others have attempted to identify markers appropriate for MALD (Dean et al. 1994; Collins et al. 2000), but the present study represents the largest to date. Taken together, these results suggest that the ~10-cM map of markers presented here makes a good foundation for MALD-based gene mapping in the African American and Hispanic populations.

The present study examines 744 markers, to identify those that are best able to differentiate between founding populations; such markers would be appropriate for MALD analysis in Hispanics or African Americans. Only weak correlations were found between δc, LLAR, or I*(2) in the European American versus African American and the European American versus Hispanic comparisons (fig. 4C and analyses not shown), so that the two groups of markers for MALD are nearly randomly overlapping. Those markers (n=315) with a δc of [gt-or-equal, slanted].30 have an average spacing of 11 cM in African Americans, and those with δc[gt-or-equal, slanted].25 (n=214 markers) in Hispanics have an average spacing of 16 cM; these two groups share 153 markers in common (indicated in table 1). There is some concern that these STR-based markers will be supplanted by SNP; however, several factors work to the advantage of STRs. They are relatively easy to assay via direct PCR amplification and separation on commercial sequencers. In MALD-TDT applications, the diversity of alleles seen at STRs will make TDT trios more generally informative than biallelic SNP markers (Spielman et al. 1993; McKeigue 1997, 1998). Those multiallelic advantages of STRs could be counterbalanced by multiallelic haplotypes based on SNPs. However, STR technology is in hand and works quite well, whereas SNP genotyping technology is currently in a state of flux (Kristensen et al. 2001).

Table 1
STR Markers Examined, Map Locations, δc, and MALD Map Status of Markers for European American versus African American and European American versus Hispanic Comparisons[Note]

We have examined genomewide marker frequency data to explore the possibility of autocorrelation of marker δc values in African-Americans and Hispanics. This analysis was undertaken because the existence of positive autocorrelation could influence both historical inferences and the search for genetic regions that contribute to ethnic differences in phenotype distribution. Positive autocorrelation between closely spaced pairs of markers would have occurred if nearby markers tended to have similar δc values, yet neighbors are as similar as randomly selected loci in δc differences (fig. 3).

Biologically speaking, appropriate MALD markers depend on the disease model. In the case of African Americans, at least 30 diseases with a likely hereditary component have a higher prevalence in this minority group than in European Americans (Williams 1999). Thus, although searching for a European disease allele in African Americans has, theoretically, the most power, the empirical approach is to search for an African one. Markers most appropriate for this case have alleles with high frequencies in African Americans that are absent in European Americans.

Acknowledgments

We thank Drs. J. Coresh, M. Dean, G. Huttley, and G. Nelson, for their helpful discussions. We are grateful to G. Washburn for assistance in designing multiplex STR primer sets. We thank Dr. Stephen Rich and the Collaborative Study of Asthma Genetics for sharing their allele frequency data. Some computations used resources of the Advanced Biomedical Computing Center (Frederick, MD). The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. government. This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under contract NO1-CO-56000.

Electronic-Database Information

The URL for data in this article is as follows:

Laboratory of Genomic Diversity Web site, http://lgd.nci.nih.gov (for additional allele frequency data for each locus, a full set of difference statistics between the groups, and primer sequences)

References

Altshuler D, Pollara VJ, Cowles CR, Van Etten WJ, Baldwin J, Linton L, Lander ES (2000) An SNP map of the human genome generated by reduced representation shotgun sequencing. Nature 407:513–516 [PubMed]
Arngrimsson R, Sigurard ttir S, Frigge ML, Bjarnadttir RI, Jonsson T, Stefansson H, Baldursdottir A, Einarsdottir AS, Palsson B, Snorradottir S, Lachmeijer AM, Nicolae D, Kong A, Bragason BT, Gulcher JR, Geirsson RT, Stefansson K (1999) A genome-wide scan reveals a maternal susceptibility locus for pre-eclampsia on chromosome 2p13. Hum Mol Genet 8:1799–1805 [PubMed]
Bellamy R, Beyers N, McAdam KP, Ruwende C, Gie R, Samaai P, Bester D, Meyer M, Corrah T, Collin M, Camidge DR, Wilkinson D, Hoal-Van Helden E, Whittle HC, Amos W, van Helden P, Hill AV (2000) Genetic susceptibility to tuberculosis in Africans: a genome-wide scan. Proc Natl Acad Sci USA 97:8005–8009 [PMC free article] [PubMed]
Bodmer WF (1986) Human genetics: the molecular challenge. Cold Spring Harbor Symposium. Quant Genet 51:1–13 [PubMed]
Bowcock AM, Ruiz-Linares A, Tomfohrde J, Minch E, Kidd JR, Cavalli-Sforza LL (1994) High resolution of human evolutionary trees with polymorphic microsatellites. Nature 368:455–457 [PubMed]
Briscoe D, Stephens JC, O'Brien SJ (1994) Linkage disequilibrium in admixed populations: applications in gene mapping. J Hered 85:59–63 [PubMed]
Brownstein MJ, Carpten JD, Smith JR (1996) Modulation of non-templated nucleotide addition by Taq DNA polymerase: primer modifications that facilitate genotyping. BioTechniques 20:1004-1006, 1008–1010 [PubMed]
Chakraborty R, Kamboh MI, Ferrell RE (1991) `Unique' alleles in admixed populations: a strategy for determining `hereditary' population differences of disease frequencies. Ethn Dis 1:245–256 [PubMed]
Chakraborty R, Kamboh MI, Nwankwo M, Ferrell RE (1992) Caucasian genes in American blacks: new data. Am J Hum Genet 50:145–155 [PMC free article] [PubMed]
Chakraborty R, Weiss KM (1988) Admixture as a tool for finding linked genes and detecting that difference from allelic association between loci. Proc Natl Acad Sci USA 85:9119–9123 [PMC free article] [PubMed]
Collaborative Study on the Genetics of Asthma (1997) A genome-wide search for asthma susceptibility loci in ethnically diverse populations. Nat Genet 15:389–392 [PubMed]
Collins HE, Li H, Inda SE, Anderson J, Laiho K, Tuomilehto J, Seldin MF (2000) A simple and accurate method for determination of microsatellite total allele content differences between DNA pools. Hum Genet 106:218–226 [PubMed]
Dean M, Stephens JC, Winkler C, Lomb DA, Ramsburg M, Boaze R, Stewart C, Charbonneau L, Goldman D, Albaugh BJ, Goedert JJ, Beasley RP, Hwang L-Y, Buchbinder S, Weedon M, Johnson PA, Eichelberger M, O'Brien SJ (1994) Polymorphic admixture typing in human ethnic populations. Am J Hum Genet 55:788–808 [PMC free article] [PubMed]
Destro-Bisol G, Maviglia R, Caglia A, Boschi I, Spedini G, Pascali V, Clark A, Tishkoff S (1999) Estimating European admixture in African Americans by using microsatellites and a microsatellite haplotype (CD4/Alu). Hum Genet 104:149–157 [PubMed]
Diggle PJ, Liang K-Y, Zeger SL (1994) Analysis of longitudinal data. Oxford Statistical Science Series. Vol 13. Oxford University Press, Oxford
Hamblin MT, Di Rienzo A (2000) Detection of the signature of natural selection in humans: evidence from the Duffy blood group locus. Am J Hum Genet 66:1669–1679 [PMC free article] [PubMed]
Hanis CL, Hewett-Emmett D, Bertin TK, Schull WJ (1991) Origins of US Hispanics. Implications for diabetes. Diabetes Care 14:618–627 [PubMed]
Huttley GA, Smith MW, Carrington M, O'Brien SJ (1999) A scan for linkage disequilibrium across the human genome. Genetics 152:1711–1722 [PMC free article] [PubMed]
Kaplan NL, Martin ER, Morris RW, Weir BS (1998) Marker selection for the transmission/disequilibrium test, in recently admixed populations. Am J Hum Genet 62:703–712 [PMC free article] [PubMed]
Kristensen VN, Kelefiotis D, Kristensen T, Borresen-Dale A-L (2001) High-throughput methods for detection of genetic variation. BioTechniques 30:318–332 [PubMed]
Laan M, Pääbo S (1997) Demographic history and linkage disequilibrium in human populations. Nat Genet 17:435–438 [PubMed]
Lautenberger JA, Stephens JC, O'Brien SJ, Smith MW (2000) Significant admixture linkage disequilibrium across 30 cM around the FY locus in African Americans. Am J Hum Genet 66:969–978 [PMC free article] [PubMed]
Long JC (1991) The genetic structure of admixed populations. Genetics 127:417–428 [PMC free article] [PubMed]
Long JC, Williams RC, McAuley JE, Medis R, Partel R, Tregellas WM, South SF, Rea AE, McCormick SB, Iwaniec U (1991) Genetic variation in Arizona Mexican Americans: estimation and interpretation of admixture proportions. Am J Phys Anthropol 84:141–157 [PubMed]
Magnuson VL, Ally DS, Nylund SJ, Karanjawala ZE, Rayman JB, Knapp JI, Lowe AL, Ghosh S, Collins FS (1996) Substrate nucleotide-determined non-templated addition of adenine by Taq DNA polymerase: implications for PCR-based genotyping and cloning. BioTechniques 21:700–709 [PubMed]
McKeigue PM (1997) Mapping genes underlying ethnic differences in disease risk by linkage disequilibrium in recently admixed populations. Am J Hum Genet 60:188–196 [PMC free article] [PubMed]
——— (1998) Mapping genes that underlie ethnic differences in disease risk: methods for detecting linkage in admixed populations, by conditioning on parental admixture. Am J Hum Genet 63:241–251 [PMC free article] [PubMed]
Mein CA, Esposito L, Dunn MG, Johnson GC, Timms AE, Goy JV, Smith AN, Sebag-Montefiore L, Merriman ME, Wilson AJ, Pritchard LE, Cucca F, Barnett AH, Bain SC, Todd JA (1998) A search for type 1 diabetes susceptibility genes in families from the United Kingdom. Nat Genet 19:297–300 [PubMed]
O'Brien SJ (2000) Human genetic factors that impact HIV infection and progression. In: Phair JP, King E (eds) Medscape HIV/AIDS annual update 2000. Medscape, New York, pp 19–28
O'Brien SJ, Nelson GW, Winkler CA, Smith MW (2000) Polygenic and multifactorial disease gene association in man: lessons from AIDS. Annu Rev Genet 34:563–591 [PubMed]
Parra EJ, Kittles RA, Argyropoulos G, Pfaff CL, Hiester K, Bonilla C, Sylvester N, Parrish-Gause D, Garvey WT, Jin L, McKeigue PM, Kamboh MI, Ferrell RE, Pollitzer WS, Shriver MD (2001) Ancestral proportions and admixture dynamics in geographically defined African Americans living in South Carolina. Am J Phys Anthropol 114:18–29 [PubMed]
Parra EJ, Marcini A, Akey J, Martinson J, Batzer MA, Cooper R, Forrester T, Allison DB, Deka R, Ferrell RE, Shriver MD (1998) Estimating African American admixture proportions by use of population-specific alleles. Am J Hum Genet 63:1839–1851 [PMC free article] [PubMed]
Pfaff CL, Parra EJ, Bonilla C, Hiester K, McKeigue PM, Kamboh MI, Hutchinson RG, Ferrell RE, Boerwinkle E, Shriver MD (2001) Population structure in admixed populations: effect of admixture dynamics on the pattern of linkage disequilibrium. Am J Hum Genet 68:198–207 [PMC free article] [PubMed]
Reich DE, Cargill M, Bolk S, Ireland J, Sabeti PC, Richter DJ, Lavery T, Kouyoumjian R, Farhadian SF, Ward R, Lander ES (2001) Linkage disequilibrium in the human genome. Nature 411:199–204 [PubMed]
Risch NJ (2000) Searching for genetic determinants in the new millennium. Nature 405:847–856 [PubMed]
Risch N, Merikangas K (1996) The future of genetic studies of complex human diseases. Science 273:1516–1517 [PubMed]
Shin HD, Winkler C, Stephens JC, Bream J, Young H, Goedert JJ, O'Brien TR, Vlahov D, Buchbinder S, Giorgi J, Rinaldo C, Donfield S, Willoughby A, O'Brien SJ, Smith MW (2000) Genetic restriction of HIV-1 infection and AIDS by promoter alleles of interleukin 10. Proc Natl Acad Sci USA 97:14467–14472 [PMC free article] [PubMed]
Shriver MD, Smith MW, Jin L, Marcini A, Akey JM, Deka R, Ferrell RE (1997) Ethnic-affiliation estimation by use of population-specific DNA markers. Am J Hum Genet 60:957–964 [PMC free article] [PubMed]
Smith JR, Freije D, Carpten JD, Gronberg H, Xu J, Isaacs SD, Brownstein MJ, Bova GS, Guo H, Bujnovszky P, Nusskern DR, Damber JE, Bergh A, Emanuelsson M, Kallioniemi OP, Walker-Daniels J, Bailey-Wilson JE, Beaty TH, Meyers DA, Walsh PC, Collins FS, Trent JM, Isaacs WB (1996) Major susceptibility locus for prostate cancer on chromosome 1 suggested by a genome-wide search. Science 274:1371–1374 [PubMed]
Smith MW, Dean M, Carrington M, Winkler C, Huttley GA, Lomb DA, Goedert JJ, O'Brien TR, Jacobson LP, Kaslow R, Buchbinder S, Vittinghoff E, Vlahov D, Hoots K, Hilgartner MW, O'Brien SJ (1997) Contrasting genetic influence of CCR2 and CCR5 variants on HIV-1 infection and disease progression. Science 277:959–965 [PubMed]
Spielman RS, McGinnis RE, Ewens WJ (1993) Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet 52:506–516 [PMC free article] [PubMed]
Stephens JC, Briscoe D, O'Brien SJ (1994) Mapping by admixture linkage disequilibrium in human populations: limits and guidelines. Am J Hum Genet 55:809–824 [PMC free article] [PubMed]
Stephens JC, Smith MW, Shin HD, O'Brien SJ (1999) Tracking linkage disequilibrium in admixed populations with MALD using microsatellite loci. In: Goldstein DB, Schlötterer C (eds) Microsatellites: evolution and applications. Oxford University Press, Oxford, pp 211–224
Tourette Syndrome Association International Consortium for Genetics, The (1999) A complete genome screen in sib pairs affected by Gilles de la Tourette syndrome. Am J Hum Genet 65:1428–1436 [PMC free article] [PubMed]
Walder K, Hanson RL, Kobes S, Knowler WC, Ravussin E (2000) An autosomal genomic scan for loci linked to plasma leptin concentration in Pima Indians. Int J Obes Relat Metab Disord 24:559–565 [PubMed]
Wiggs JL, Allingham RR, Hossain A, Kern J, Auguste J, DelBono EA, Broomer B, Graham FL, Hauser M, Pericak-Vance M, Haines JL (2000) Genome-wide scan for adult onset primary open angle glaucoma. Hum Mol Genet 9:1109–1117 [PubMed]
Williams DR (1999) Race, socioeconomic status, and health. The added effects of racism and discrimination. Ann NY Acad Sci 896:173–188 [PubMed]
Wilson JF, Goldstein DB (2000) Consistent long-range linkage disequilibrium generated by admixture in a Bantu-Semitic hybrid population. Am J Hum Genet 67:926–935 [PMC free article] [PubMed]
Zheng C, Elston RC (1999) Multipoint linkage disequilibrium mapping with particular reference to the African-American population. Genet Epidemiol 17:79–101 [PubMed]

Articles from American Journal of Human Genetics are provided here courtesy of American Society of Human Genetics
PubReader format: click here to try

Formats: