Variants associated with common disease are not unusually differentiated in frequency across populations

Unveiling recent and ongoing adaptive selection in human populations

Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.

Risk variants of obesity associated genes demonstrate BMI raising effect in a large cohort

Obesity is highly polygenic disease where several genetic variants have been reportedly associated with obesity in different ethnicities of the world. In the current study, we identified the obesity risk or protective association and BMI raising effect of the minor allele of adiponectin, C1Q and collagen domain containing (ADIPOQ), cholesteryl ester transfer protein (CEPT), FTO alpha-ketoglutarate dependent dioxygenase (FTO), leptin (LEP), and leptin receptor (LEPR) genes in a large cohort stratified into four BMI-based body weight categories i.e., normal weight, lean, over-weight, and obese. Based on selected candidate genetic markers, the genotyping of all study subjects was performed by PCR assays, and genotypes and allele frequencies were calculated. The minor allele frequencies (MAFs) of all genetic markers were computed for total and BMI-based body weight categories and compared with MAFs of global and South Asian (SAS) populations. Genetic associations of variants with obesity risk were calculated and BMI raising effect per copy of the minor allele were estimated. The genetic variants with higher MAFs in obese BMI group were; rs2241766 (G = 0.43), rs17817449 (G = 0.54), rs9939609 (A = 0.51), rs1421085 (C = 0.53), rs1558902 (A = 0.63), and rs1137101 (G = 0.64) respectively. All these variants were significantly associated with obesity (OR = 1.03–4.42) and showed a high BMI raising effect (β = 0.239–0.31 Kg/m²) per copy of the risk allele. In contrast, the MAFs of three variants were higher in lean-normal BMI groups; rs3764261 A = 0.38, rs9941349 T = 0.43, and rs7799039 G = 0.40–0.43). These variants showed obesity protective associations (OR = 0.68–0.76), and a BMI lowering effect per copy of the protective allele (β = -0.103–0.155 Kg/m²). The rs3764261 variant also showed significant and positive association with lean body mass (OR = 2.38, CI = 1.30–4.34). Overall, we report six genetic variants of ADIPOQ, FTO and LEPR genes as obesity-risk markers and a CETP gene variant as lean mass/obesity protective marker in studied Pakistani cohort.

Leveraging genetic ancestry to study health disparities

Research to understand human genomic variation and its implications in health has great potential to contribute in the reduction of health disparities. Biological anthropology can play important roles in genomics and health disparities research using a biocultural approach. This paper argues that racial/ethnic categories should not be used as a surrogate for sociocultural factors or global genomic clusters in biomedical research or clinical settings, because of the high genetic heterogeneity that exists within traditional racial/ethnic groups. Genetic ancestry is used to show variation in ancestral genomic contributions to recently admixed populations in the United States, such as African Americans and Hispanic/Latino Americans. Genetic ancestry estimates are also used to examine the relationship between ancestry-related biological and sociocultural factors affecting health disparities. To localize areas of genomes that contribute to health disparities, admixture mapping and genome-wide association studies (GWAS) are often used. Recent GWAS have identified many genetic variants that are highly differentiated among human populations that are associated with disease risk. Some of these are population-specific variants. Many of these variants may impact disease risk and help explain a portion of the difference in disease burden among racial/ethnic groups. Genetic ancestry is also of particular interest in precision medicine and disparities in drug efficacy and outcomes. By using genetic ancestry, we can learn about potential biological differences that may contribute to the heterogeneity observed across self-reported racial groups.

Ethnic differences in prevalence of Dupuytren disease can partly be explained by known genetic risk variants

Dupuytren disease (DD), a fibroproliferative disorder of the palmar fascia that causes flexion contractures in the fingers, is prevalent in people of North-Western European descent and less so in other ethnicities. DD is a complex disorder, influenced by genetic risk variants. We aimed to study if the marked differences in prevalences in DD between ethnic (sub)groups could be explained by differences in allele frequencies of the 26 known genetic risk variants of DD. Therefore, genetic risk scores (GRS) composed of the 26 DD risk variants were calculated for the 26 populations from the 1000 Genomes database and correlated to observed DD prevalences from literature. For comparison, GRSs were generated for 10,000 sets of 26 random SNPs and also correlated to the observed DD prevalences to determine the significance of the observed correlation. To determine whether differences in allele frequencies between ethnicities were caused by natural selection, fixation indices (Fst) were calculated from the 26 SNPs and from the sets of 26 random SNPs for comparison. Observed prevalences could be determined from literature for 10 populations. Their correlation with the GRS composed of DD SNPs proved to be 0.60 (p = 0.0003). The Fsts between British and other populations were low for European, ad mixed American, and South-Asian populations, and moderate for East-Asians. African populations were significantly different from expected values determined from the random sets. In conclusion, the 26 known genetic risk variants associated with DD explain for a substantial part (R2 = 0.36) the differing DD prevalences observed between ethnicities.

Significant association of DRD2 enhancer variant rs12364283 with heroin addiction in a Pakistani population

The dopamine D2 receptor encoded by DRD2 has been implicated in multiple psychiatric disorders, mediated at least in part by two intronic variants affecting mRNA splicing, rs1076560 and rs2283265, and a less frequent enhancer variant, rs12364283, which increases DRD2 mRNA expression. This study tests whether these functionally validated variants confer susceptibility toward heroin addiction in a Pakistani population. A total of 540 heroin addicts and 467 healthy controls were genotyped, basic allele and genotype tests were performed. Neither rs1076560 nor rs2283265 significantly associated with heroin addiction. The enhancer rs12364283 occurs more frequently in heroin-dependent cases than controls (MAF 13% vs. 7%, respectively), revealing significant association with heroin addiction (p = 3.0E-06, OR 2.1). This study identifies rs12364283 of DRD2 as a potential risk factor for heroin addiction in the Pakistani study population. This enhancer variant had been shown to increase DRD2 mRNA expression, a possible factor in increased vulnerability to heroin addiction. Further studies are needed to validate this association of rs12364283.

Leveraging GWAS for complex traits to detect signatures of natural selection in humans

Natural selection can shape the genetic architecture of complex traits. In human populations, signals of positive selection at genetic loci have been detected through a variety of genome-wide scanning approaches without the knowledge of how genes affect traits or fitness. In the past decade, genome-wide association studies (GWAS) have provided unprecedented insights into the genetic basis of quantitative variation in complex traits. Summary statistics generated from these GWAS have been shown to be an extraordinary data source that can be utilized to detect and quantify natural selection in the genetic architecture of complex traits. In this review, we focus on recent discoveries about selection on genetic variants associated with human complex traits based on GWAS-facilitated methods.

Type 2 diabetes mellitus: distribution of genetic markers in Kazakh population

Background

Ethnic differences exist in the frequencies of genetic variations that contribute to the risk of common disease. This study aimed to analyse the distribution of several genes, previously associated with susceptibility to type 2 diabetes and obesity-related phenotypes, in a Kazakh population.

Methods

A total of 966 individuals belonging to the Kazakh ethnicity were recruited from an outpatient clinic. We genotyped 41 common single nucleotide polymorphisms (SNPs) previously associated with type 2 diabetes in other ethnic groups and 31 of these were in Hardy–Weinberg equilibrium. The obtained allele frequencies were further compared to publicly available data from other ethnic populations. Allele frequencies for other (compared) populations were pooled from the haplotype map (HapMap) database. Principal component analysis (PCA), cluster analysis, and multidimensional scaling (MDS) were used for the analysis of genetic relationship between the populations.

Results

Comparative analysis of allele frequencies of the studied SNPs showed significant differentiation among the studied populations. The Kazakh population was grouped with Asian populations according to the cluster analysis and with the Caucasian populations according to PCA. According to MDS, results of the current study show that the Kazakh population holds an intermediate position between Caucasian and Asian populations.

Conclusion

A high percentage of population differentiation was observed between Kazakh and world populations. The Kazakh population was clustered with Caucasian populations, and this result may indicate a significant Caucasian component in the Kazakh gene pool.

Estimating the mutational load for cardiovascular diseases in Pakistani population

The deleterious genetic variants contributing to certain diseases may differ in terms of number and allele frequency from population to population depending on their evolutionary background. Here, we prioritize the deleterious variants from Pakistani population in manually curated gene list already reported to be associated with common, Mendelian, and congenital cardiovascular diseases (CVDs) using the genome/exome sequencing data of Pakistani individuals publically available in 1000 Genomes Project (PJL), and Exome Aggregation Consortium (ExAC) South Asia. By applying a set of tools such as Combined Annotation Dependent Depletion (CADD), ANNOVAR, and Variant Effect Predictor (VEP), we highlighted 561 potentially detrimental variants from PJL data, and 7374 variants from ExAC South Asian data. Likewise, filtration from ClinVar for CVDs revealed 03 pathogenic and 02 likely pathogenic variants from PJL and 112 pathogenic and 42 likely pathogenic variants from ExAC South Asians. The comparison of derived allele frequencies (DAF) revealed many of these prioritized variants having two fold and higher DAF in Pakistani individuals than in other populations. The highest number of deleterious variants contributing to common CVDs in descending order includes hypertension, atherosclerosis, heart failure, aneurysm, and coronary heart disease, and for Mendelian and congenital CVDs cardiomyopathies, cardiac arrhythmias, and atrioventricular septal defects.

Allelic Spectra of Risk SNPs Are Different for Environment/Lifestyle Dependent versus Independent Diseases

Genome-wide association studies (GWAS) have generated sufficient data to assess the role of selection in shaping allelic diversity of disease-associated SNPs. Negative selection against disease risk variants is expected to reduce their frequencies making them overrepresented in the group of minor (<50%) alleles. Indeed, we found that the overall proportion of risk alleles was higher among alleles with frequency <50% (minor alleles) compared to that in the group of major alleles. We hypothesized that negative selection may have different effects on environment (or lifestyle)-dependent versus environment (or lifestyle)-independent diseases. We used an environment/lifestyle index (ELI) to assess influence of environmental/lifestyle factors on disease etiology. ELI was defined as the number of publications mentioning "environment" or "lifestyle" AND disease per 1,000 disease-mentioning publications. We found that the frequency distributions of the risk alleles for the diseases with strong environmental/lifestyle components follow the distribution expected under a selectively neutral model, while frequency distributions of the risk alleles for the diseases with weak environmental/lifestyle influences is shifted to the lower values indicating effects of negative selection. We hypothesized that previously selectively neutral variants become risk alleles when environment changes. The hypothesis of ancestrally neutral, currently disadvantageous risk-associated alleles predicts that the distribution of risk alleles for the environment/lifestyle dependent diseases will follow a neutral model since natural selection has not had enough time to influence allele frequencies. The results of our analysis suggest that prediction of SNP functionality based on the level of evolutionary conservation may not be useful for SNPs associated with environment/lifestyle dependent diseases.

Signatures of natural selection on genetic variants affecting complex human traits

It has recently been hypothesized that polygenic adaptation, resulting in modest allele frequency changes at many loci, could be a major mechanism behind the adaptation of complex phenotypes in human populations. Here we leverage the large number of variants that have been identified through genome-wide association (GWA) studies to comprehensively study signatures of natural selection on genetic variants associated with complex traits. Using population differentiation based methods, such as FST and phylogenetic branch length analyses, we systematically examined nearly 1300 SNPs associated with 38 complex phenotypes. Instead of detecting selection signatures at individual variants, we aimed to identify combined evidence of natural selection by aggregating signals across many trait associated SNPs. Our results have revealed some general features of polygenic selection on complex traits associated variants. First, natural selection acting on standing variants associated with complex traits is a common phenomenon. Second, characteristics of selection for different polygenic traits vary both temporarily and geographically. Third, some studied traits (e.g. height and urate level) could have been the primary targets of selection, as indicated by the significant correlation between the effect sizes and the estimated strength of selection in the trait associated variants; however, for most traits, the allele frequency changes in trait associated variants might have been driven by the selection on other correlated phenotypes. Fourth, the changes in allele frequencies as a result of selection can be highly stochastic, such that, polygenic adaptation may accelerate differentiation in allele frequencies among populations, but generally does not produce predictable directional changes. Fifth, multiple mechanisms (pleiotropy, hitchhiking, etc) may act together to govern the changes in allele frequencies of genetic variants associated with complex traits.

Analysis of the genetic basis of disease in the context of worldwide human relationships and migration

Genetic diversity across different human populations can enhance understanding of the genetic basis of disease. We calculated the genetic risk of 102 diseases in 1,043 unrelated individuals across 51 populations of the Human Genome Diversity Panel. We found that genetic risk for type 2 diabetes and pancreatic cancer decreased as humans migrated toward East Asia. In addition, biliary liver cirrhosis, alopecia areata, bladder cancer, inflammatory bowel disease, membranous nephropathy, systemic lupus erythematosus, systemic sclerosis, ulcerative colitis, and vitiligo have undergone genetic risk differentiation. This analysis represents a large-scale attempt to characterize genetic risk differentiation in the context of migration. We anticipate that our findings will enable detailed analysis pertaining to the driving forces behind genetic risk differentiation.

The environment humans inhabit has changed many times in the last 100,000 years. Migration and dynamic local environments can lead to genetic adaptations favoring beneficial traits. Many genes responsible for these adaptations can alter disease susceptibility. Genes can also affect disease susceptibility by varying randomly across different populations. We have studied genetic variants that are known to modify disease susceptibility in the context of worldwide migration. We found that variants associated with 11 diseases have been affected to an extent that is not explained by random variation. We also found that the genetic risk of type 2 diabetes has steadily decreased along the worldwide human migration trajectory from Africa to America.

Purifying selection modulates the estimates of population differentiation and confounds genome-wide comparisons across single-nucleotide polymorphisms

An improved understanding of the biological and numerical properties of measures of population differentiation across loci is becoming increasingly more important because of their growing use in analyzing genome-wide polymorphism data for detecting population structures, inferring the rates of migration, and identifying local adaptations. In a genome-wide analysis, we discovered that the estimates of population differentiation (e.g., F(ST), θ, and Jost's D) calculated for human single-nucleotide polymorphisms (SNPs) are strongly and positively correlated to the position-specific evolutionary rates measured from multispecies alignments. That is, genomic positions (loci) experiencing higher purifying selection (lower evolutionary rates) produce lower values for the degree of population differentiation than those evolving with faster rates. We show that this pattern is completely mediated by the negative effects of purifying selection on the minor allele frequency (MAF) at individual loci. Our results suggest that inferences and methods relying on the comparison of population differentiation estimates (F(ST), θ, and Jost's D) based on SNPs across genomic positions should be restricted to loci with similar MAFs and/or the rates of evolution in genome scale surveys.

Race-ethnic differences in the association of genetic loci with HbA1c levels and mortality in U.S. adults: the third National Health and Nutrition Examination Survey (NHANES III)

BACKGROUND

Hemoglobin A1c (HbA1c) levels diagnose diabetes, predict mortality and are associated with ten single nucleotide polymorphisms (SNPs) in white individuals. Genetic associations in other race groups are not known. We tested the hypotheses that there is race-ethnic variation in 1) HbA1c-associated risk allele frequencies (RAFs) for SNPs near SPTA1, HFE, ANK1, HK1, ATP11A, FN3K, TMPRSS6, G6PC2, GCK, MTNR1B; 2) association of SNPs with HbA1c and 3) association of SNPs with mortality.

METHODS

We studied 3,041 non-diabetic individuals in the NHANES (National Health and Nutrition Examination Survey) III. We stratified the analysis by race/ethnicity (NHW: non-Hispanic white; NHB: non-Hispanic black; MA: Mexican American) to calculate RAF, calculated a genotype score by adding risk SNPs, and tested associations with SNPs and the genotype score using an additive genetic model, with type 1 error = 0.05.

RESULTS

RAFs varied widely and at six loci race-ethnic differences in RAF were significant (p < 0.0002), with NHB usually the most divergent. For instance, at ATP11A, the SNP RAF was 54% in NHB, 18% in MA and 14% in NHW (p < .0001). The mean genotype score differed by race-ethnicity (NHW: 10.4, NHB: 11.0, MA: 10.7, p < .0001), and was associated with increase in HbA1c in NHW (β = 0.012 HbA1c increase per risk allele, p = 0.04) and MA (β = 0.021, p = 0.005) but not NHB (β = 0.007, p = 0.39). The genotype score was not associated with mortality in any group (NHW: OR (per risk allele increase in mortality) = 1.07, p = 0.09; NHB: OR = 1.04, p = 0.39; MA: OR = 1.03, p = 0.71).

CONCLUSION

At many HbA1c loci in NHANES III there is substantial RAF race-ethnic heterogeneity. The combined impact of common HbA1c-associated variants on HbA1c levels varied by race-ethnicity, but did not influence mortality.

Genetic variation and its role in malignancy

Genetic variation has long been thought associated with common complex disease and has therefore been widely studied. Genetic variation in the human genome is present in many forms and have been summarised in this review. The potential role of DNA damage, DNA repair and environmental influence on genetic variation in the development of cancer will be discussed, before significant genome projects are reviewed. All the various forms of genetic variation have been associated with malignancies and have been extensively studied and this is a review of the state of the field. We also discuss the road ahead in fulfilling the ultimate goal in all cancer genetic studies, which is decreasing deaths caused by cancer.

Geographic differences in allele frequencies of susceptibility SNPs for cardiovascular disease

BACKGROUND

We hypothesized that the frequencies of risk alleles of SNPs mediating susceptibility to cardiovascular diseases differ among populations of varying geographic origin and that population-specific selection has operated on some of these variants.

METHODS

From the database of genome-wide association studies (GWAS), we selected 36 cardiovascular phenotypes including coronary heart disease, hypertension, and stroke, as well as related quantitative traits (eg, body mass index and plasma lipid levels). We identified 292 SNPs in 270 genes associated with a disease or trait at P < 5 × 10⁻⁸. As part of the Human Genome-Diversity Project (HGDP), 158 (54.1%) of these SNPs have been genotyped in 938 individuals belonging to 52 populations from seven geographic areas. A measure of population differentiation, F(ST), was calculated to quantify differences in risk allele frequencies (RAFs) among populations and geographic areas.

RESULTS

Large differences in RAFs were noted in populations of Africa, East Asia, America and Oceania, when compared with other geographic regions. The mean global F(ST) (0.1042) for 158 SNPs among the populations was not significantly higher than the mean global F(ST) of 158 autosomal SNPs randomly sampled from the HGDP database. Significantly higher global F(ST) (P < 0.05) was noted in eight SNPs, based on an empirical distribution of global F(ST) of 2036 putatively neutral SNPs. For four of these SNPs, additional evidence of selection was noted based on the integrated Haplotype Score.

CONCLUSION

Large differences in RAFs for a set of common SNPs that influence risk of cardiovascular disease were noted between the major world populations. Pairwise comparisons revealed RAF differences for at least eight SNPs that might be due to population-specific selection or demographic factors. These findings are relevant to a better understanding of geographic variation in the prevalence of cardiovascular disease.

Recent human evolution has shaped geographical differences in susceptibility to disease

Background

Searching for associations between genetic variants and complex diseases has been a very active area of research for over two decades. More than 51,000 potential associations have been studied and published, a figure that keeps increasing, especially with the recent explosion of array-based Genome-Wide Association Studies. Even if the number of true associations described so far is high, many of the putative risk variants detected so far have failed to be consistently replicated and are widely considered false positives. Here, we focus on the world-wide patterns of replicability of published association studies.

Results

We report three main findings. First, contrary to previous results, genes associated to complex diseases present lower degrees of genetic differentiation among human populations than average genome-wide levels. Second, also contrary to previous results, the differences in replicability of disease associated-loci between Europeans and East Asians are highly correlated with genetic differentiation between these populations. Finally, highly replicated genes present increased levels of high-frequency derived alleles in European and Asian populations when compared to African populations.

Conclusions

Our findings highlight the heterogeneous nature of the genetic etiology of complex disease, confirm the importance of the recent evolutionary history of our species in current patterns of disease susceptibility and could cast doubts on the status as false positives of some associations that have failed to replicate across populations.

Genome-wide association study SNPs in the human genome diversity project populations: does selection affect unlinked SNPs with shared trait associations?

Genome-wide association studies (GWAS) have identified more than 2,000 trait-SNP associations, and the number continues to increase. GWAS have focused on traits with potential consequences for human fitness, including many immunological, metabolic, cardiovascular, and behavioral phenotypes. Given the polygenic nature of complex traits, selection may exert its influence on them by altering allele frequencies at many associated loci, a possibility which has yet to be explored empirically. Here we use 38 different measures of allele frequency variation and 8 iHS scores to characterize over 1,300 GWAS SNPs in 53 globally distributed human populations. We apply these same techniques to evaluate SNPs grouped by trait association. We find that groups of SNPs associated with pigmentation, blood pressure, infectious disease, and autoimmune disease traits exhibit unusual allele frequency patterns and elevated iHS scores in certain geographical locations. We also find that GWAS SNPs have generally elevated scores for measures of allele frequency variation and for iHS in Eurasia and East Asia. Overall, we believe that our results provide evidence for selection on several complex traits that has caused changes in allele frequencies and/or elevated iHS scores at a number of associated loci. Since GWAS SNPs collectively exhibit elevated allele frequency measures and iHS scores, selection on complex traits may be quite widespread. Our findings are most consistent with this selection being either positive or negative, although the relative contributions of the two are difficult to discern. Our results also suggest that trait-SNP associations identified in Eurasian samples may not be present in Africa, Oceania, and the Americas, possibly due to differences in linkage disequilibrium patterns. This observation suggests that non-Eurasian and non-East Asian sample populations should be included in future GWAS.

Disease-associated alleles in genome-wide association studies are enriched for derived low frequency alleles relative to HapMap and neutral expectations

Background

Genome-wide association studies give insight into the genetic basis of common diseases. An open question is whether the allele frequency distributions and ancestral vs. derived states of disease-associated alleles differ from the rest of the genome. Characteristics of disease-associated alleles can be used to increase the yield of future studies.

Methods

The set of all common disease-associated alleles found in genome-wide association studies prior to January 2010 was analyzed and compared with HapMap and theoretical null expectations. In addition, allele frequency distributions of different disease classes were assessed. Ages of HapMap and disease-associated alleles were also estimated.

Results

The allele frequency distribution of HapMap alleles was qualitatively similar to neutral expectations. However, disease-associated alleles were more likely to be low frequency derived alleles relative to null expectations. 43.7% of disease-associated alleles were ancestral alleles. The mean frequency of disease-associated alleles was less than randomly chosen CEU HapMap alleles (0.394 vs. 0.610, after accounting for probability of detection). Similar patterns were observed for the subset of disease-associated alleles that have been verified in multiple studies. SNPs implicated in genome-wide association studies were enriched for young SNPs compared to randomly selected HapMap loci. Odds ratios of disease-associated alleles tended to be less than 1.5 and varied by frequency, confirming previous studies.

Conclusions

Alleles associated with genetic disease differ from randomly selected HapMap alleles and neutral expectations. The evolutionary history of alleles (frequency and ancestral vs. derived state) influences whether they are implicated in genome-wide assocation studies.

Worldwide distribution of the MYH9 kidney disease susceptibility alleles and haplotypes: evidence of historical selection in Africa

MYH9 was recently identified as renal susceptibility gene (OR 3-8, p < 10(-8)) for major forms of kidney disease disproportionately affecting individuals of African descent. The risk haplotype (E-1) occurs at much higher frequencies in African Americans (> or = 60%) than in European Americans (< 4%), revealing a genetic basis for a major health disparity. The population distributions of MYH9 risk alleles and the E-1 risk haplotype and the demographic and selective forces acting on the MYH9 region are not well explored. We reconstructed MYH9 haplotypes from 4 tagging single nucleotide polymorphisms (SNPs) spanning introns 12-23 using available data from HapMap Phase II, and by genotyping 938 DNAs from the Human Genome Diversity Panel (HGDP). The E-1 risk haplotype followed a cline, being most frequent within sub-Saharan African populations (range 50-80%), less frequent in populations from the Middle East (9-27%) and Europe (0-9%), and rare or absent in Asia, the Americas, and Oceania. The fixation indexes (F(ST)) for pairwise comparisons between the risk haplotypes for continental populations were calculated for MYH9 haplotypes; F(ST) ranged from 0.27-0.40 for Africa compared to other continental populations, possibly due to selection. Uniquely in Africa, the Yoruba population showed high frequency extended haplotype length around the core risk allele (C) compared to the alternative allele (T) at the same locus (rs4821481, iHs = 2.67), as well as high population differentiation (F(ST(CEU vs. YRI)) = 0.51) in HapMap Phase II data, also observable only in the Yoruba population from HGDP (F(ST) = 0.49), pointing to an instance of recent selection in the genomic region. The population-specific divergence in MYH9 risk allele frequencies among the world's populations may prove important in risk assessment and public health policies to mitigate the burden of kidney disease in vulnerable populations.

Patterns of population structure and environmental associations to aridity across the range of loblolly pine (Pinus taeda L., Pinaceae)

Natural populations of forest trees exhibit striking phenotypic adaptations to diverse environmental gradients, thereby making them appealing subjects for the study of genes underlying ecologically relevant phenotypes. Here, we use a genome-wide data set of single nucleotide polymorphisms genotyped across 3059 functional genes to study patterns of population structure and identify loci associated with aridity across the natural range of loblolly pine (Pinus taeda L.). Overall patterns of population structure, as inferred using principal components and Bayesian cluster analyses, were consistent with three genetic clusters likely resulting from expansions out of Pleistocene refugia located in Mexico and Florida. A novel application of association analysis, which removes the confounding effects of shared ancestry on correlations between genetic and environmental variation, identified five loci correlated with aridity. These loci were primarily involved with abiotic stress response to temperature and drought. A unique set of 24 loci was identified as F(ST) outliers on the basis of the genetic clusters identified previously and after accounting for expansions out of Pleistocene refugia. These loci were involved with a diversity of physiological processes. Identification of nonoverlapping sets of loci highlights the fundamental differences implicit in the use of either method and suggests a pluralistic, yet complementary, approach to the identification of genes underlying ecologically relevant phenotypes.

Are "functionally related polymorphisms" of renin-angiotensin-aldosterone system gene polymorphisms associated with hypertension?

Background

Genotype-phenotype association studies are typically based upon polymorphisms or haplotypes comprised of multiple polymorphisms within a single gene. It has been proposed that combinations of polymorphisms in distinct genes, which functionally impact the same phenotype, may have stronger phenotype associations than those within a single gene. We have tested this hypothesis using genes encoding components of the renin-angiotensin-aldosterone system and the high blood pressure phenotype.

Methods

Our analysis is based on 1379 participants of the cross-sectional SUNSET study randomly selected from the population register of Amsterdam. Each subject was genotyped for the angiotensinogen M235T, the angiotensin-converting enzyme insertion/deletion and the angiotensin II type 1 receptor A1166C polymorphism. The phenotype high blood pressure was defined either as a categorical variable comparing hypertension versus normotension as in most previous studies or as a continuous variable using systolic, diastolic and mean blood pressure in a multiple regression analysis with gender, ethnicity, age, body-mass-index and antihypertensive medication as covariates.

Results

Genotype-phenotype relationships were explored for each polymorphism in isolation and for double and triple polymorphism combinations. At the single polymorphism level, only the A allele of the angiotensin II type 1 receptor was associated with a high blood pressure phenotype. Using combinations of polymorphisms of two or all three genes did not yield stronger/more consistent associations.

Conclusions

We conclude that combinations of physiologically related polymorphisms of multiple genes, at least with regard to the renin-angiotensin-aldosterone system and the hypertensive phenotype, do not necessarily offer additional benefit in analyzing genotype/phenotype associations.

Genome-wide scan for signatures of human population differentiation and their relationship with natural selection, functional pathways and diseases

Genetic differences both between individuals and populations are studied for their evolutionary relevance and for their potential medical applications. Most of the genetic differentiation among populations are caused by random drift that should affect all loci across the genome in a similar manner. When a locus shows extraordinary high or low levels of population differentiation, this may be interpreted as evidence for natural selection. The most used measure of population differentiation was devised by Wright and is known as fixation index, or F_ST. We performed a genome-wide estimation of F_ST on about 4 millions of SNPs from HapMap project data. We demonstrated a heterogeneous distribution of F_ST values between autosomes and heterochromosomes. When we compared the F_ST values obtained in this study with another evolutionary measure obtained by comparative interspecific approach, we found that genes under positive selection appeared to show low levels of population differentiation. We applied a gene set approach, widely used for microarray data analysis, to detect functional pathways under selection. We found that one pathway related to antigen processing and presentation showed low levels of F_ST, while several pathways related to cell signalling, growth and morphogenesis showed high F_ST values. Finally, we detected a signature of selection within genes associated with human complex diseases. These results can help to identify which process occurred during human evolution and adaptation to different environments. They also support the hypothesis that common diseases could have a genetic background shaped by human evolution.

Disparities in allele frequencies and population differentiation for 101 disease-associated single nucleotide polymorphisms between Puerto Ricans and non-Hispanic whites

Background

Variations in gene allele frequencies can contribute to differences in the prevalence of some common complex diseases among populations. Natural selection modulates the balance in allele frequencies across populations. Population differentiation (F_ST) can evidence environmental selection pressures. Such genetic information is limited in Puerto Ricans, the second largest Hispanic ethnic group in the US, and a group with high prevalence of chronic disease. We determined allele frequencies and population differentiation for 101 single nucleotide polymorphisms (SNPs) in 30 genes involved in major metabolic and disease-relevant pathways in Puerto Ricans (n = 969, ages 45–75 years) and compared them to similarly aged non-Hispanic whites (NHW) (n = 597).

Results

Minor allele frequency (MAF) distributions for 45.5% of the SNPs assessed in Puerto Ricans were significantly different from those of NHW. Puerto Ricans carried risk alleles in higher frequency and protective alleles in lower frequency than NHW. Patterns of population differentiation showed that Puerto Ricans had SNPs with exceptional F_ST values in intronic, non-synonymous and promoter regions. NHW had exceptional F_ST values in intronic and promoter region SNPs only.

Conclusion

These observations may serve to explain and broaden studies on the impact of gene polymorphisms on chronic diseases affecting Puerto Ricans.

Heroin addiction in African Americans: a hypothesis-driven association study

Heroin addiction is a chronic complex disease with a substantial genetic contribution. This study was designed to identify gene variants associated with heroin addiction in African Americans. The emphasis was on genes involved in reward modulation, behavioral control, cognitive function, signal transduction and stress response. We have performed a case-control association analysis by screening with 1350 variants of 130 genes. The sample consisted of 202 former severe heroin addicts in methadone treatment and 167 healthy controls with no history of drug abuse. Single nucleotide polymorphism (SNP), haplotype and multi-SNP genotype pattern analyses were performed. Seventeen SNPs showed point-wise significant association with heroin addiction (nominal P< 0.01). These SNPs are from genes encoding several receptors: adrenergic (ADRA1A), arginine vasopressin (AVPR1A), cholinergic (CHRM2), dopamine (DRD1), GABA-A (GABRB3), glutamate (GRIN2A) and serotonin (HTR3A) as well as alcohol dehydrogenase (ADH7), glutamic acid decarboxylase (GAD1 and GAD2), the nucleoside transporter (SLC29A1) and diazepam-binding inhibitor (DBI). The most significant result of the analyses was obtained for the GRIN2A haplotype G-A-T (rs4587976-rs1071502-rs1366076) with protective effect (P(uncorrected) = 9.6E- 05, P(corrected) = 0.058). This study corroborates several reported associations with alcohol and drug addiction as well as other related disorders and extends the list of variants that may affect the development of heroin addiction. Further studies will be necessary to replicate these associations and to elucidate the roles of these variants in drug addiction vulnerability.

Signals of recent positive selection in a worldwide sample of human populations

Genome-wide scans for recent positive selection in humans have yielded insight into the mechanisms underlying the extensive phenotypic diversity in our species, but have focused on a limited number of populations. Here, we present an analysis of recent selection in a global sample of 53 populations, using genotype data from the Human Genome Diversity-CEPH Panel. We refine the geographic distributions of known selective sweeps, and find extensive overlap between these distributions for populations in the same continental region but limited overlap between populations outside these groupings. We present several examples of previously unrecognized candidate targets of selection, including signals at a number of genes in the NRG-ERBB4 developmental pathway in non-African populations. Analysis of recently identified genes involved in complex diseases suggests that there has been selection on loci involved in susceptibility to type II diabetes. Finally, we search for local adaptation between geographically close populations, and highlight several examples.

Natural selection on genes that underlie human disease susceptibility

What evolutionary forces shape genes that contribute to the risk of human disease? Do similar selective pressures act on alleles that underlie simple versus complex disorders [1-3]? Answers to these questions will shed light onto the origin of human disorders (e.g., [4]) and help to predict the population frequencies of alleles that contribute to disease risk, with important implications for the efficient design of mapping studies [5-7]. As a first step toward addressing these questions, we created a hand-curated version of the Mendelian Inheritance in Man database (OMIM). We then examined selective pressures on Mendelian-disease genes, genes that contribute to complex-disease risk, and genes known to be essential in mouse by analyzing patterns of human polymorphism and of divergence between human and rhesus macaque. We found that Mendelian-disease genes appear to be under widespread purifying selection, especially when the disease mutations are dominant (rather than recessive). In contrast, the class of genes that influence complex-disease risk shows little signs of evolutionary conservation, possibly because this category includes targets of both purifying and positive selection.

Worldwide population differentiation at disease-associated SNPs

BACKGROUND

Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs).

METHODS

We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals.

RESULTS

On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations.

CONCLUSION

Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.

Genetic variants of Y chromosome are associated with a protective lipid profile in black men

OBJECTIVE

Gender and ethnicity modulate the phenotypic expression of cardiovascular risk factors. In particular, men are at higher risk of developing cardiovascular diseases compared to women, whereas black populations of African origin display reduced mortality from coronary heart disease (CHD) as compared to both whites and South Asians. Because the male-specific region (MSY) of the human Y chromosome is an obvious candidate for gender-related differences in the development of cardiovascular diseases, we aimed to identify genetic variants of MSY influencing cardiovascular risk profile in different ethnic groups.

METHODS AND RESULTS

We genotyped 4 polymorphisms of MSY (HindIII+/-, rs768983 of TBL1Y, rs3212292 of USP9Y, and rs9341273 of UTY genes) in 579 men of different ethnic groups (blacks, South Asians, and whites) from UK and in 301 whites in Italy. We found that the TBL1Y(A) USP9Y(A) haplotype, present only in blacks in whom it represents the most frequent allelic combinations (AA: n=125; all other combinations: n=45), was associated with lower levels of triglycerides (P=0.025) and higher levels of HDL-cholesterol (P=0.005) as compared to the other haplotypes.

CONCLUSIONS

The TBL1Y(A) USP9Y(A) haplotype of the Y chromosome, present only in black people of African origin, attributes a favorable lipoprotein pattern, likely to contribute to their reduced susceptibility to coronary heart disease.

Association of vitamin D receptor gene 3'-variants with Hashimoto's thyroiditis in the Croatian population

Hashimoto's thyroiditis (HT) is the most frequent autoimmune thyroid disease with strong genetic background. Vitamin D receptor (VDR) endocrine system affects immunosuppressive, regulatory and tolerogenic decisions required for induction and maintenance of peripheral immune tolerance. With respect to the biological function of the VDR and functionally plausible gene-expression data, we sought to test whether particular 3'-restriction fragment length polymorphisms (RFLP) and haplotypes previously directly or indirectly associated with VDR mRNA 3'-allelic imbalance phenotype and differences in total VDR mRNA expression are implicated in HT susceptibility. Thus, 145 Croatian HT patients and 145 age-, sex- and ethnically matched euthyroid controls were genotyped for VDR rs1544410 (BsmI), rs7975232 (ApaI) and rs731236 (TaqI) polymorphisms by polymerase chain reaction-RFLP method. Covariate-adjusted single-locus and haplotype-phenotype regression analyses were performed. Permutation corrections (P(c)) and Akaike Information Criteria were used for model comparisons. The best-fit [global P(c) = 7.2 x 10(-4)]BsmI-TaqI BT haplotype was found significantly more often in subjects without HT [12.2% vs. 3.7%; odds ratio (OR, 95% confidence intervals) = 0.28 (0.14-0.56), P(c) = 8 x 10(-4)], whereas the bT haplotype was significantly more frequent in individuals with HT [45.7% vs. 61.8%; OR = 1.91 (1.37-2.65), P(c) = 4 x 10(-4)]. Two extended BsmI-ApaI-TaqI RFLP haplotypes, the common baT [35.7 vs. 47.3%, OR = 1.63 (1.17-2.27), P(c) = 0.012] and rare BaT variants [6.5 vs. 1.2%, OR = 0.17 (0.06-0.55), P(c) = 1.2 x 10(-3)] were associated with HT, representing predisposing and protective haplotypes, respectively. In single-RFLP association analyses, only rs1544410 polymorphism was associated with HT phenotype (allelic P(c) = 0.0078) and appeared to function under the recessive model, with decreased risk of HT among the BB homozygotes [OR = 0.39 (0.21-0.7), P(c) = 0.0052] when compared to the reference b(+)-genotypes. These data suggest that common haplotypic variants within the VDR gene 3'-region previously linked to VDR mRNA expression and allelic imbalance could be associated with HT in the general population, and thus, may be involved in the pathogenesis of HT.

The structure of common genetic variation in United States populations

The common-variant/common-disease model predicts that most risk alleles underlying complex health-related traits are common and, therefore, old and found in multiple populations, rather than being rare or population specific. Accordingly, there is widespread interest in assessing the population structure of common alleles. However, such assessments have been confounded by analysis of data sets with bias toward ascertainment of common alleles (e.g., HapMap and Perlegen) or in which a relatively small number of genes and/or populations were sampled. The aim of this study was to examine the structure of common variation ascertained in major U.S. populations, by resequencing the exons and flanking regions of 3,873 genes in 154 chromosomes from European, Latino/Hispanic, Asian, and African Americans generated by the Genaissance Resequencing Project. The frequency distributions of private and common single-nucleotide polymorphisms (SNPs) were measured, and the extent to which common SNPs were shared across populations was analyzed using several different estimators of population structure. Most SNPs that were common in one population were present in multiple populations, but SNPs common in one population were frequently not common in other populations. Moreover, SNPs that were common in two or more populations often differed significantly in frequency from one population to another, particularly in comparisons of African Americans versus other U.S. populations. These findings indicate that, even if the bulk of alleles underlying complex health-related traits are common SNPs, geographic ancestry might well be an important predictor of whether a person carries a risk allele.

Genetic polymorphisms in xenobiotic clearance genes and their influence on disease expression in hereditary nonpolyposis colorectal cancer patients

BACKGROUND

Hereditary nonpolyposis colorectal cancer (HNPCC) is associated with germ-line mutations in DNA mismatch repair genes. There is considerable variation in disease expression that cannot be explained by genotype/phenotype correlation, which is likely to be the result of polymorphic modifier genes. One candidate group of modifiers is the xenobiotic clearance enzyme genes that encode CYP1A1, GSTM1, GSTT1, GSTP1, and NAT2. Alterations in these xenobiotic clearance genes can potentially influence the host response to carcinogen exposure and thereby alter cancer risk. We have investigated eight polymorphisms in xenobiotic clearance genes to assess the effect on the risk of disease in mutation positive HNPCC patients.

METHODS

DNA samples from 220 mutation-positive HNPCC participants (86 Australian and 134 Polish) were genotyped for single nucleotide polymorphisms (SNP) in CYP1A1, GSTM1, GSTT1, GSTP1, and NAT2. The association between the SNPs and disease characteristics, disease expression and age of diagnosis of colorectal cancer (CRC), was tested with Pearson's chi(2) and Kaplan-Meier survival analysis.

RESULTS

The HNPCC population displays a significant difference in the genotype frequency distribution between CRC patients and unaffected mismatch repair gene mutation carriers for the CYP1A1 SNP where the CRC patients harbor more of the mutant genotype.

CONCLUSIONS

Evidence from this study is not conclusive, but our data suggest that the CYP1A1 influences disease expression in individuals with HNPCC.

Lack of association between genetic polymorphisms in cytokine genes and disease expression in patients with hereditary non-polyposis colorectal cancer

OBJECTIVE

Hereditary non-polyposis colorectal cancer (HNPCC) is caused by germline mutations in DNA mismatch repair (MMR) genes and is characterized by familial aggregations of early-onset epithelial cancers. Inflammatory cells produce an attractive environment for tumour growth since reactive oxygen and nitrogen species generated by inflammatory cytokine induction can cause damage to DNA and proteins. In this study the objective was to investigate single nucleotide polymorphisms (SNPs) in cytokine genes to assess their impact on disease expression in individuals diagnosed with HNPCC.

MATERIAL AND METHODS

DNA samples from 220 participants diagnosed with HNPCC were genotyped for SNPs in IL-6, IL-1beta, TNF-alpha, IFN-gamma, IL-10, IL-4 and IL-1RN. The association between the polymorphisms and disease characteristics, i.e. affected or unaffected with colorectal cancer (CRC) and age of diagnosis of CRC, was tested with the Pearson chi2 test and by Kaplan-Meier survival analysis.

RESULTS

There was no significant difference between CRC patients and unaffected MMR gene mutation carriers for any of the SNPs studied and the Kaplan-Meier survival analysis showed no significant difference between age of diagnosis of CRC and genotype.

CONCLUSIONS

The SNPs selected for this study do not appear to modify disease expression in HNPCC. Given the complexity of the inflammatory response, the limited number of SNPs studied does not rule out the notion that other cytokine polymorphisms could act as disease modifiers of disease expression in HNPCC.

Genetic similarities within and between human populations

The proportion of human genetic variation due to differences between populations is modest, and individuals from different populations can be genetically more similar than individuals from the same population. Yet sufficient genetic data can permit accurate classification of individuals into populations. Both findings can be obtained from the same data set, using the same number of polymorphic loci. This article explains why. Our analysis focuses on the frequency, omega, with which a pair of random individuals from two different populations is genetically more similar than a pair of individuals randomly selected from any single population. We compare omega to the error rates of several classification methods, using data sets that vary in number of loci, average allele frequency, populations sampled, and polymorphism ascertainment strategy. We demonstrate that classification methods achieve higher discriminatory power than omega because of their use of aggregate properties of populations. The number of loci analyzed is the most critical variable: with 100 polymorphisms, accurate classification is possible, but omega remains sizable, even when using populations as distinct as sub-Saharan Africans and Europeans. Phenotypes controlled by a dozen or fewer loci can therefore be expected to show substantial overlap between human populations. This provides empirical justification for caution when using population labels in biomedical settings, with broad implications for personalized medicine, pharmacogenetics, and the meaning of race.

MDM2 SNP309 T>G alone or in combination with the TP53 R72P polymorphism does not appear to influence disease expression and age of diagnosis of colorectal cancer in HNPCC patients

Disease expression in hereditary nonpolyposis colorectal cancer (HNPCC) cannot be readily explained by mutation site in the respective DNA mismatch repair genes associated with this disorder. One explanation is the role of modifying genes that can either promote or prevent disease development on a background of increased risk. Two single nucleotide polymorphisms in MDM2 and TP53 have been shown to be associated with younger ages of disease onset in HNPCC (TP53) and Li-Fraumeni syndrome (MDM2). In this study 220 HNPCC patients were examined, from Australia and Poland, all characterized at the molecular level to determine the frequency of the MDM2 SNP309 T>G and to assess its influence on disease expression. The results were then pooled with the results of a previous study to assess the combined influence of the MDM2 SNP309 T>G and TP53 SNP R72P. A significant difference was observed between CRC patients and unaffected MMR gene mutation carriers over the age of 45 years (p = 0.01). The unaffected MMR gene mutation carriers over the age of 45 years who carry the G allele have a reduced risk of developing CRC. The results indicate that the MDM2 SNP309, alone or in combination with TP53 R72P, does not influence age of diagnosis of CRC in individuals with HNPCC. In conclusion, the data indicates the G allele of MDM2 SNP309 might have a protective effect on disease development in HNPCC patients and that age of diagnosis of CRC is not associated with MDM2 SNP309 or TP53 R72P either as single SNPs or combined.