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PubMed2005

ADH4 gene variation is associated with alcohol and drug dependence: results from family controlled and population-structured association studies.

We found strong associations between ADH4 gene variation and alcohol and drug dependence by the Hardy-Weinberg Disequilibrium (HWD) test and case-control association analysis in an initial study. The present study aimed to confirm these findings by controlling for population stratification and admixture effects to which the HWD test and case-control association methods may be vulnerable. In addition to 365 unrelated healthy controls and 560 unrelated cases in the initial study, we evaluated 104 small nuclear families with affected offspring who had diagnoses of alcohol and/or drug dependence. Seven single nucleotide polymorphisms (SNPs) at the ADH4 gene locus were genotyped in all subjects, and 38 unlinked ancestry-informative markers were also genotyped in unrelated cases and controls. Structured association analysis demonstrated that the genotypes of six ADH4 markers were associated with alcohol dependence, and all seven ADH4 markers were associated with drug dependence (P=10-0.047). Logistic regression analysis showed that: (i) the genotypes of SNP2 (rs1042363) were significantly associated with alcohol dependence and drug dependence (mainly cocaine dependence), and the genotypes of SNP3 (rs1126671) were also significantly associated with alcohol dependence and (ii) one seven-variant haplotype and one diplotype were significantly associated with alcohol dependence and other seven-variant diplotypes were significantly associated with drug dependence (including cocaine and opioid dependence). Transmission disequilibrium test, haplotype-based haplotype relative risk and genotype-based haplotype relative risk analyses all confirmed the association of the ADH4 markers with alcohol dependence and drug dependence. Using rigorous study designs that account for possible population stratification, these findings confirm and extend our original observations indicating that variation at ADH4 predisposes to alcohol and drug dependence.

Adult↗

PubMed2007

African Americans with asthma: genetic insights.

It has been well established that genetic factors strongly affect susceptibility to asthma and its associated traits. It is less clear to what extent genetic variation contributes to the ethnic disparities observed for asthma morbidity and mortality. Individuals of African descent with asthma have more severe asthma, higher IgE levels, a higher degree of steroid dependency, and more severe clinical symptoms than individuals of European descent with asthma but relatively few studies have focused on this particularly vulnerable ethnic group. Similar underrepresentation exists for other minorities, including Hispanics. In this review, a summary of linkage and association studies in populations of African descent is presented, and the role of linkage disequilibrium in the dissection of a complex trait such as asthma is discussed. Consideration for the impact of population stratification in recently admixed populations (i.e., European, African) is essential in genetic association studies focusing on African ancestry groups. With the most recent update on the International HapMap Project, efficient selection of haplotype tagging single nucleotide polymorphisms (htSNPs) for African Americans has accelerated and efficiency of htSNPs chosen from one population to represent other continental groups (e.g., African) has been demonstrated. Cutting-edge approaches, such as genomewide association studies, admixture mapping, and phylogenetic analyses, offer new opportunities for dissecting the genetic basis for asthma in populations of African descent.

Black or African American↗

PubMed2005

Genetic structure in four West African population groups.

BACKGROUND: Africa contains the most genetically divergent group of continental populations and several studies have reported that African populations show a high degree of population stratification. In this regard, it is important to investigate the potential for population genetic structure or stratification in genetic epidemiology studies involving multiple African populations. The presences of genetic sub-structure, if not properly accounted for, have been reported to lead to spurious association between a putative risk allele and a disease. Within the context of the Africa America Diabetes Mellitus (AADM) Study (a genetic epidemiologic study of type 2 diabetes mellitus in West Africa), we have investigated population structure or stratification in four ethnic groups in two countries (Akan and Gaa-Adangbe from Ghana, Yoruba and Igbo from Nigeria) using data from 372 autosomal microsatellite loci typed in 493 unrelated persons (986 chromosomes). RESULTS: There was no significant population genetic structure in the overall sample. The smallest probability is associated with an inferred cluster of 1 and little of the posterior probability is associated with a higher number of inferred clusters. The distribution of members of the sample to inferred clusters is consistent with this finding; roughly the same proportion of individuals from each group is assigned to each cluster with little variation between the ethnic groups. Analysis of molecular variance (AMOVA) showed that the between-population component of genetic variance is less than 0.1% in contrast to 99.91% for the within population component. Pair-wise genetic distances between the four ethnic groups were also very similar. Nonetheless, the small between-population genetic variance was sufficient to distinguish the two Ghanaian groups from the two Nigerian groups. CONCLUSION: There was little evidence for significant population substructure in the four major West African ethnic groups represented in the AADM study sample. Ethnicity apparently did not introduce differential allele frequencies that may affect analysis and interpretation of linkage and association studies. These findings, although not entirely surprising given the geographical proximity of these groups, provide important insights into the genetic relationships between the ethnic groups studied and confirm previous results that showed close genetic relationship between most studied West African groups.

Africa, Western↗

PubMed2004

False positive rates in association studies as a function of degree of stratification.

UNLABELLED: To explore the degree to which stratification can cause spurious positive association results, we tested for association between BMD and 373 genetic markers using 381 white and 126 black females. The rate of positive results doubled as the proportion of stratification increased, showing the importance of controlling for stratification in association studies. INTRODUCTION: Population-based association studies are commonly used to test the relationship between polymorphisms in a candidate gene and a disease or trait of interest. Although the collection of samples for this type of study design is relatively cost-effective, the statistical analysis may be susceptible to false positive results because of the effects of population stratification. Such results may occur when the underlying populations differ in both the polymorphism allele frequency and mean trait value. MATERIALS AND METHODS: To explore the degree to which stratification can cause spurious positive association results, we analyzed femoral neck BMD data from an unrelated sample of 381 white and 126 black premenopausal females. As part of a previous genome screen, 373 microsatellite markers had been genotyped for each individual. For simplicity of interpretation, each multiallelic marker was reduced to a biallelic marker, with the most common allele as one allele and all other alleles combined as the second allele. As expected, the black women differed substantially for marker allele frequencies and had significantly higher mean femoral neck BMD than their white counterparts. Random subsets of the white and black samples were sampled, with increasing proportions of stratification (0%, 1%, 2%, 5%, 10%, 15%, and 20% black subjects) in the total analyzed sample. ANOVA was used to test for association between the recoded marker and femoral neck BMD. RESULTS AND CONCLUSIONS: The rate of positive results for the association test were observed to double as the proportion of stratification increased, with substantial increases in the frequency of false positives even for stratification proportions as small as 2-5%. These results show the importance of controlling for stratification when the trait and the polymorphism allele frequency differ between the races.

Adult↗

PubMed2005

Practical population group assignment with selected informative markers: characteristics and properties of Bayesian clustering via STRUCTURE.

Population stratification, which is caused by population genetic substructure (PGS), is a critical issue for the design and interpretation of genetic association studies. Methods to address this problem have been devised, but little is known at this point about practical genotyping requirements for resolving PGS based on different marker characteristics. In this report, we seek to (1) identify a small, practical marker set to differentiate African Americans (AAs) from European Americans (EAs), and (2) assess the impact of marker efficiency and sample size on clustering individuals into subgroups by the methods of STRUCTURE (Pritchard et al., [2000a] Genetics 155:945-959). A panel of 37 markers was genotyped for 865 individuals (640 EAs and 225 AAs) from the Northeastern United States. Among EAs, the assignment accuracy reached >99% using only the 4 most efficient markers. Among AAs, the assignment accuracy exceeded 95% when using the 6 most informative markers. Smaller sample size increased the variance in population differentiation, rather than degrading the results consistently. We conclude that the use of marker-efficiency measures for marker selection yielded a relatively small set of STR markers that were effective at differentiating EA and AA populations. The number of markers required is much lower than has been suggested in previous studies.

Black or African American↗

PubMed2026

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n = 929), CARDIA (n = 1123), JHS (n = 1365), ARIC (n = 2338), and HCHS/SOL (n = 1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R² ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans↗

PubMed2005

A probabilistic approach to large-scale association scans: a semi-Bayesian method to detect disease-predisposing alleles.

Recent analytic and technological breakthroughs have set the stage for genome-wide linkage disequilibrium studies to map disease-susceptibility variants. This paper discusses a probabilistic methodology for making disease-mapping inferences in large-scale case-control genetic studies. The semi-Bayesian approach promoted compares the probability of the observed data under disease hypotheses to the probability of the data under a null hypothesis defined by data at all the markers interrogated in a large study. This method automatically adjusts for the effects of diffuse population stratification. It is claimed that this characterization of the evidence for or against disease models may facilitate more appropriate inductions for large-scale genetic studies. Results include (i) an analytic solution for the population stratification-adjusted Bayes' factor, (ii) the relationship between sample size and Bayes' factors, (iii) an extension to an approximate Bayes' factor calculated across closely-linked sites, and (iv) an extension across multiple studies. Although this paper deals exclusively with genetic studies, it is possible to generalize the approach to treat many different large-scale experiments including studies of gene expression and proteomics.

Journal Article↗

PubMed2006

Reliability of self-reported ancestry among siblings: implications for genetic association studies.

This study investigated the reliability of self-reported ancestry by comparing the interview responses of probands and their siblings. A total of 546 sibling pairs were ascertained in a family-based study of susceptibility genes for Parkinson's disease and asked to identify maternal and paternal countries of origin. Probands were recruited prospectively from the Department of Neurology of the Mayo Clinic in Rochester, Minnesota, from June 1, 1996, through May 31, 2005. Probands resided within Minnesota or one of the four surrounding states (Wisconsin, Iowa, South Dakota, North Dakota). Only 49 percent of these sibling pairs, primarily Caucasian, agreed completely on the countries of origin of both parents. The agreement increased to 68 percent when named countries were postcoded into six population genetic clusters (as previously defined by microsatellite markers). Self-reported ancestry may not be a reliable method to reduce the possible impact of population stratification in genetic association studies of outbred populations, such as in the United States.

Adult↗

PubMed1991

Effects of population structure on DNA fingerprint analysis in forensic science.

DNA fingerprints are used in forensic sciences to identify individuals. However, current analyses could underestimate the probability of two individuals sharing the same profile because the effect of population structure is not incorporated. An alternative analysis is proposed to take into account population stratification. The analysis uses studies of inbreeding in human populations to obtain an empirical upper bound on the magnitude of the effect.

Alleles↗

PubMed2006

Overview of the pharmacogenetics of asthma treatment.

Asthma affects approximately 300 million individuals worldwide. Medications comprise a substantial portion of asthma expenditures. Despite the availability of three primary therapeutic classes of medications, there are a significant number of nonresponders to therapy. Available data, as well as previous pharmacogenetic studies, suggest that genetics may contribute as much as 60-80% to the interindividual variability in treatment response. In this methodologic review, after providing a broad overview of the asthma pharmacogenetics literature to date, we describe the application of a novel family-based screening algorithm to the analysis of pharmacogenetic data and highlight our approach to identifying and verifying loci influencing asthma treatment response. This approach seeks to address issues related to multiple comparisons, statistical power, population stratification, and failure to replicate from which previous population-based or case-control pharmacogenetic association studies may suffer. Identification of such replicable loci is the next step towards the goal of 'individualized therapy' for asthma.

Adrenergic beta-Agonists↗

PubMed2005

Is variation in the GABA(B) receptor 1 gene associated with temporal lobe epilepsy?

PURPOSE: gamma-Aminobutyric acid (GABA)-receptor genes are prime candidates for a role in seizure susceptibility. An association between the c.1465G-->A variant in the GABA(B) receptor 1 gene (GABBR1) and susceptibility to temporal lobe epilepsy (TLE) has been reported in an Italian cohort. We sought to replicate this association in an independent Australian cohort. METHODS: The 234 patients with TLE and 164 healthy controls were genotyped for the c.1465G-->A variant, by using inclusion criteria identical to those of the first study. RESULTS: The c.1465G-->A variant was found in one TLE patient and one control subject. Genotype and allele frequencies did not differ between groups. CONCLUSIONS: We did not replicate the reported associations between the c.1465G-->A variant and susceptibility to TLE. We suggest that the initial positive association may be due to undetected population stratification; the importance of genomic control is emphasized. Population-specific effects also may play a role, and we highlight the need to demonstrate an in vitro functional effect to give biologic meaning to any proposed association.

Adolescent↗

PubMed2003

Number of SNPS loci needed to detect population structure.

The study of the association of polymorphic genetic markers with common diseases is one of the most powerful tools in modern genetics. Interest in single nucleotide polymorphisms (SNPs) has steadily grown over the last decade. SNPs are currently the most developed markers in the human genome because they have a number of advantages over other marker types. One of the critical problems responsible for 'spurious' association findings in case-control studies is population stratification. There are many statistical approaches developed for detecting population heterogeneity. However the power to detect population structure by known methods is highly dependent on the number of loci utilised. We performed an analysis of SNPs data available in the public domain from The Single Nucleotide Consortia Ltd. (TSCL). Three populations, Afro-American, Asian and Caucasian, were compared. Estimation of the minimum number of SNPs loci necessary for detection of the population structure was performed. Two clustering approaches, distance-based and model-based, were compared. The model-based approach was superior when compared with the distance-based method. We found more than 65 random SNPs loci are required for identifying distinct geographically separated populations. Increasing the number of markers to over 100 raises the probability of correct assignment of a particular individual to an origin group to over 90%, even with conventional clustering methods.

Genetic Markers↗

PubMed2002

Properties of the transmission-disequilibrium test in the presence of inbreeding.

Family-based association tests such as the transmission-disequilibrium test (TDT), which compare alleles transmitted and non-transmitted from parents to affected offspring, are widely used to detect the role of genetic risk factors in diseases. These methods have the advantage of being robust to population stratification and are thus believed to be valid whatever the population context. In different studies of the statistical properties of the TDT, parents of affected offspring are typically assumed to be neither inbred nor related. In many human populations, however, this assumption is false and parental alleles are then no longer independent. It is thus of interest to determine whether the TDT is a valid test of linkage and association in the presence of inbreeding. We present a method to derive the expected value of the TDT statistic under different disease models and for any relationship between the parents of affected offspring. Using this method, we show that in the presence of inbreeding, the TDT is still a valid test for linkage but not for association. The power of the test to detect linkage may, however, be increased in the presence of inbreeding under different modes of inheritance.

Consanguinity↗

PubMed2006

Human clock, PER1 and PER2 polymorphisms: lack of association with cocaine dependence susceptibility and cocaine-induced paranoia.

Considerable research points to the importance of genetic mechanisms in psychostimulant addiction. Behavioral sensitization, a well-documented response to repeated stimulant exposure, may be mechanistically important in clinical features of the disorder, including escalating patterns of drug use, craving and drug-induced paranoia. Basic studies in both Drosophila melanogaster and mice have suggested the importance of circadian rhythm genes in locomotor sensitization and reward. The primary objective of the current study was to assess the potential involvement of three human orthologs (CLOCK, PER1 and PER2) in clinical phenotypes of the disorder. Allelic associations of three single nucleotide polymorphisms (SNPs) were assessed for both cocaine dependence and cocaine-induced paranoia in 186 cases and 273 controls. Potential population stratification biases were controlled for by means of within-population comparisons, and by structured association methods (using all populations). No differences in allele frequencies were found for any of the three single nucleotide polymorphisms studied between cocaine dependent and control subjects or between paranoid and nonparanoid cocaine users. These results do not support the involvement of genetic variation in these three circadian gene SNPs for influencing risks for either of these cocaine phenotypes.

Animals↗

PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗

PubMed1999

Applicability of the case-parent design in the etiological research of Type 1 diabetes in Chile and other genetically mixed populations.

In case-control studies, spurious associations between Human Leukocyte Antigen (HLA) alleles and Type 1 diabetes could arise as a result of population stratification, if there are ethnic differences between cases and non-related controls. The Chilean population has several unique features which make it ideal for the study of the effect of stratification by ethnicity on genetic epidemiological research. The incidence rates of Type 1 diabetes in Chilean Aboriginal populations are very low compared to Caucasian populations, while the frequency of the alleles in HLA loci also vary across ethnic groups. In order to avoid the confounding effect of ethnicity, one possible remedy would be the use of cases and their parents in place of non-related controls. The case-parent design offers an adequate framework for the study of the association between HLA polymorphisms and Type 1 diabetes in the Chilean population and can also be applicable to other genetically mixed populations especially in the Americas.

Adolescent↗

PubMed2002

A functional neuropeptide Y Leu7Pro polymorphism associated with alcohol dependence in a large population sample from the United States.

BACKGROUND: Quantitative trait locus studies, and observations in animals manipulated for the neuropeptide Y (NPY) gene suggest that variation within this gene may contribute to alcoholism. A recent population study suggested that the Pro7 allele of a functional NPY polymorphism (Leu7Pro) may be associated with increased alcohol consumption. We tested whether the Pro7 allele is associated with alcohol dependence in European Americans (EA). METHODS: The design was a population study comparing the Leu7Pro allele frequencies in alcohol-dependent subjects and controls. Population stratification potential and diagnostic specificity was studied by genotyping individuals from additional populations and psychiatric diagnostic classes. We studied 2 independently collected samples of EA alcohol-dependent subjects (sample 1, n = 307; sample 2, n = 160) and a sample of psychiatrically screened EA controls (n = 202); 8 population samples, including African Americans and European Americans (total n = 551); and 4 samples of individuals with Alzheimer disease, schizophrenia, posttraumatic stress disorder, and major depression (total n = 502). The main outcome measure was the difference in Leu7Pro allele frequencies between alcohol-dependent subjects and controls. RESULTS: The frequency of the Pro7 allele was higher in the alcohol-dependent subjects (sample 1, 5.5%; sample 2, 5.0%) compared with the screened EA controls (2.0%) (sample 1 vs controls, P=.006; sample 2 vs controls, P=.03). The attributable fraction (excess morbidity) in similarly affected populations, owing to the Pro7 allele, was estimated to be 7.3%. The frequency of the Pro7 allele was equal or lower in the population samples, as compared with the screened EA controls (0%-2.2%), with 1 exception (Bedouins). We found no significant evidence that the association of the Pro7 allele with alcohol dependence was due to an association with a comorbid psychiatric disorder. CONCLUSIONS: These results suggest that the NPY Pro7 allele is a risk factor for alcohol dependence. This is only the second specific genetic mechanism ever identified that modulates risk for alcohol dependence.

Alcohol Drinking↗

PubMed1980

[Linkage disequilibrium].

The linkage disequilibrium which measures the association between linked genes is a temporary phenomenon in a population because of crossing over. But such associations persist in HLA system. These persistent linkage disequilibria may be due to the very small fraction of recombinaison between the loci but other explanations are possible: selection or migration. A linkage disequilibrium produces a phenotypic correlation in a population. A phenotypic correlation may be due to pleiotropic effect of a gene, or epistasie of two genes, or population stratification... On the same hand, if a correlation appears in an inter population study, it may be due to a migration or a subdivided population. In medical genetics the research of such association intra or inter population studies may permit to point out a defect gene. In particular, HLA system study has proved that many susceptibility genes of various diseases are linked to B or D alleles.

Female↗