PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-10 (10)
 

Clipboard (0)
None

Select a Filter Below

Journals
Year of Publication
Document Types
1.  Extending Admixture Mapping to Nuclear Pedigrees: Application to Sarcoidosis 
Genetic epidemiology  2013;37(3):256-266.
We describe statistical methods that extend the application of admixture mapping from unrelated individuals to nuclear pedigrees, allowing existing pedigree-based collections to be fully exploited. Computational challenges have been overcome by developing a fast algorithm that exploits the factorial structure of the underlying model of ancestry transitions. This has been implemented as an extension of the program ADMIXMAP. We demonstrate the application of the method to a study of sarcoidosis in African Americans that has previously been analyzed only as an admixture mapping study restricted to unrelated individuals. Although the ancestry signals detected in this pedigree analysis are generally similar to those detected in the earlier analysis of unrelated cases, we are able to extract more information and this yields a much sharper exclusion map; using the classical criterion of an LOD score of minus 2, the pedigree analysis is able to exclude a risk ratio of 2 or more associated with African ancestry over 96% of the genome, compared with only 83% in the earlier analysis of unrelated individuals only. Although the pedigree extension of ADMIXMAP can use ancestry-informative markers only at relatively low density, it can use imputed ancestry states from programs such as WINPOP or HAPMIX that use dense SNP marker genotypes for admixture mapping. This extends both the efficiency and the range of application of this powerful gene mapping method.
doi:10.1002/gepi.21710
PMCID: PMC3756835  PMID: 23371909
admixture; ancestry; pedigrees; linkage; sarcoidosis; African American; hidden Markov models
2.  Genetic influences on plasma CFH and CFHR1 concentrations and their role in susceptibility to age-related macular degeneration 
Human Molecular Genetics  2013;22(23):4857-4869.
It is a longstanding puzzle why non-coding variants in the complement factor H (CFH) gene are more strongly associated with age-related macular degeneration (AMD) than functional coding variants that directly influence the alternative complement pathway. The situation is complicated by tight genetic associations across the region, including the adjacent CFH-related genes CFHR3 and CFHR1, which may themselves influence the alternative complement pathway and are contained within a common deletion (CNP147) which is associated with protection against AMD. It is unclear whether this association is mediated through a protective effect of low plasma CFHR1 concentrations, high plasma CFH or both. We examined the triangular relationships of CFH/CFHR3/CFHR1 genotype, plasma CFH or CFHR1 concentrations and AMD susceptibility in combined case–control (1256 cases, 1020 controls) and cross-sectional population (n = 1004) studies and carried out genome-wide association studies of plasma CFH and CFHR1 concentrations. A non-coding CFH SNP (rs6677604) and the CNP147 deletion were strongly correlated both with each other and with plasma CFH and CFHR1 concentrations. The plasma CFH-raising rs6677604 allele and raised plasma CFH concentration were each associated with AMD protection. In contrast, the protective association of the CNP147 deletion with AMD was not mediated by low plasma CFHR1, since AMD-free controls showed increased plasma CFHR1 compared with cases, but it may be mediated by the association of CNP147 with raised plasma CFH concentration. The results are most consistent with a regulatory locus within a 32 kb region of the CFH gene, with a major effect on plasma CFH concentration and AMD susceptibility.
doi:10.1093/hmg/ddt336
PMCID: PMC3820139  PMID: 23873044
3.  Genome-wide association study of genetic determinants of LDL-c response to atorvastatin therapy: importance of Lp(a) [S] 
Journal of Lipid Research  2012;53(5):1000-1011.
We carried out a genome-wide association study (GWAS) of LDL-c response to statin using data from participants in the Collaborative Atorvastatin Diabetes Study (CARDS; n = 1,156), the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT; n = 895), and the observational phase of ASCOT (n = 651), all of whom were prescribed atorvastatin 10 mg. Following genome-wide imputation, we combined data from the three studies in a meta-analysis. We found associations of LDL-c response to atorvastatin that reached genome-wide significance at rs10455872 (P = 6.13 × 10−9) within the LPA gene and at two single nucleotide polymorphisms (SNP) within the APOE region (rs445925; P = 2.22 × 10−16 and rs4420638; P = 1.01 × 10−11) that are proxies for the ϵ2 and ϵ4 variants, respectively, in APOE. The novel association with the LPA SNP was replicated in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial (P = 0.009). Using CARDS data, we further showed that atorvastatin therapy did not alter lipoprotein(a) [Lp(a)] and that Lp(a) levels accounted for all of the associations of SNPs in the LPA gene and the apparent LDL-c response levels. However, statin therapy had a similar effect in reducing cardiovascular disease (CVD) in patients in the top quartile for serum Lp(a) levels (HR = 0.60) compared with those in the lower three quartiles (HR = 0.66; P = 0.8 for interaction). The data emphasize that high Lp(a) levels affect the measurement of LDL-c and the clinical estimation of LDL-c response. Therefore, an apparently lower LDL-c response to statin therapy may indicate a need for measurement of Lp(a). However, statin therapy seems beneficial even in those with high Lp(a).
doi:10.1194/jlr.P021113
PMCID: PMC3329377  PMID: 22368281
genetics; low density lipoprotein; LDL/metabolism; lipoprotein(a); statins
4.  The Relationship Between Metabolic Risk Factors and Incident Cardiovascular Disease in Europeans, South Asians, and African Caribbeans 
Objectives
This study sought to determine whether ethnic differences in diabetes, dyslipidemia, and ectopic fat deposition account for ethnic differences in incident cardiovascular disease.
Background
Coronary heart disease risks are elevated in South Asians and are lower in African Caribbeans compared with Europeans. These ethnic differences map to lipid patterns and ectopic fat deposition.
Methods
Cardiovascular risk factors were assessed in 2,049 Europeans, 1,517 South Asians, and 630 African Caribbeans from 1988 through 1991 (mean age: 52.4 ± 6.9 years). Fatal and nonfatal events were captured over a median 20.5-year follow-up. Subhazard ratios (SHR) were calculated using competing risks regression.
Results
Baseline diabetes prevalence was more than 3 times greater in South Asians and African Caribbeans than in Europeans. South Asians were more and African Caribbeans were less centrally obese and dyslipidemic than Europeans. Compared with Europeans, coronary heart disease incidence was greater in South Asians and less in African Caribbeans. The age- and sex-adjusted South Asian versus European SHR was 1.70 (95% confidence interval [CI]: 1.52 to 1.91, p < 0.001) and remained significant (1.45, 95% CI: 1.28 to 1.64, p < 0.001) when adjusted for waist-to-hip ratio. The African Caribbean versus European age- and sex-adjusted SHR of 0.64 (95% CI: 0.52 to 0.79, p < 0.001) remained significant when adjusted for high-density lipoprotein and low-density lipoprotein cholesterol (0.74, 95% CI: 0.60 to 0.92, p = 0.008). Compared with Europeans, South Asians and African Caribbeans experienced more strokes (age- and sex-adjusted SHR: 1.45 [95% CI: 1.17 to 1.80, p = 0.001] and 1.50 [95% CI: 1.13 to 2.00, p = 0.005], respectively), and this differential was more marked in those with diabetes (age-adjusted SHR: 1.97 [95% CI: 1.16 to 3.35, p = 0.038 for interaction] and 2.21 [95% CI: 1.14 to 4.30, p = 0.019 for interaction]).
Conclusions
Ethnic differences in measured metabolic risk factors did not explain differences in coronary heart disease incidence. The apparently greater association between diabetes and stroke risk in South Asians and African Caribbeans compared with Europeans merits further study.
doi:10.1016/j.jacc.2012.12.046
PMCID: PMC3677086  PMID: 23500273
coronary heart disease; ethnicity; incidence; stroke; CHD, coronary heart disease; CVD, cardiovascular disease; HDL, high-density lipoprotein; ICD, International Classification of Diseases; IR, insulin resistance; LDL, low-density lipoprotein; SHR, subhazard ratio
6.  Insulin Resistance and Truncal Obesity as Important Determinants of the Greater Incidence of Diabetes in Indian Asians and African Caribbeans Compared With Europeans 
Diabetes Care  2013;36(2):383-393.
OBJECTIVE
To determine the extent of, and reasons for, ethnic differences in type 2 diabetes incidence in the U.K.
RESEARCH DESIGN AND METHODS
Population-based triethnic cohort. Participants were without diabetes, aged 40–69 at baseline (1989–1991), and followed-up for 20 years. Baseline measurements included fasting and postglucose bloods, anthropometry, and lifestyle questionnaire. Incident diabetes was identified from medical records and participant recall. Ethnic differences in diabetes incidence were examined using competing risks regression.
RESULTS
Incident diabetes was identified in 196 of 1,354 (14%) Europeans, 282 of 839 (34%) Indian Asians, and 100 of 335 (30%) African Caribbeans. All Indian Asians and African Caribbeans were first-generation migrants. Compared with Europeans, age-adjusted subhazard ratios (SHRs [95% CI]) for men and women, respectively, were 2.88 (95%, 2.36–3.53; P < 0.001) and 1.91 (1.18–3.10; P = 0.008) in Indian Asians, and 2.23 (1.64–3.03; P < 0.001) and 2.51 (1.63–3.87; P < 0.001) in African Caribbeans. Differences in baseline insulin resistance and truncal obesity largely attenuated the ethnic minority excess in women (adjusted SHRs: Indian Asians 0.77 [0.49–1.42]; P = 0.3; African Caribbeans 1.48 [0.89–2.45]; P = 0.13), but not in men (adjusted SHRs: Indian Asians 1.98 [1.52–2.58]; P < 0.001 and African Caribbeans, 2.05 [1.46–2.89; P < 0.001]).
CONCLUSIONS
Insulin resistance and truncal obesity account for the twofold excess incidence of diabetes in Indian Asian and African Caribbean women, but not men. Explanations for the excess diabetes risk in ethnic minority men remains unclear. Further study requires more precise measures of conventional risk factors and identification of novel risk factors.
doi:10.2337/dc12-0544
PMCID: PMC3554271  PMID: 22966089
7.  Admixture mapping of lung cancer in 1812 African-Americans 
Carcinogenesis  2010;32(3):312-317.
Lung cancer continues to be the leading cause of cancer death in the USA and the best example of a cancer with undisputed evidence of environmental risk. However, a genetic contribution to lung cancer has also been demonstrated by studies of familial aggregation, family-based linkage, candidate gene studies and most recently genome-wide association studies (GWAS). The African-American population has been underrepresented in these genetic studies and has patterns of cigarette use and linkage disequilibrium that differ from patterns in other populations. Therefore, studies in African-Americans can provide complementary data to localize lung cancer susceptibility genes and explore smoking dependence-related genes. We used admixture mapping to further characterize genetic risk of lung cancer in a series of 837 African-American lung cancer cases and 975 African-American controls genotyped at 1344 ancestry informative single-nucleotide polymorphisms. Both case-only and case–control analyses were conducted using ADMIXMAP adjusted for age, sex, pack-years of smoking, family history of lung cancer, history of emphysema and study site. In case-only analyses, excess European ancestry was observed over a wide region on chromosome 1 with the largest excess seen at rs6587361 for non-small-cell lung cancer (NSCLC) (Z-score = −4.33; P = 1.5 × 10−5) and for women with NSCLC (Z-score = −4.82; P = 1.4 × 10−6). Excess African ancestry was also observed on chromosome 3q with a peak Z-score of 3.33 (P = 0.0009) at rs181696 among ever smokers with NSCLC. These results add to the findings from the GWAS in Caucasian populations and suggest novel regions of interest.
doi:10.1093/carcin/bgq252
PMCID: PMC3047238  PMID: 21115650
8.  Genomic Runs of Homozygosity Record Population History and Consanguinity 
PLoS ONE  2010;5(11):e13996.
The human genome is characterised by many runs of homozygous genotypes, where identical haplotypes were inherited from each parent. The length of each run is determined partly by the number of generations since the common ancestor: offspring of cousin marriages have long runs of homozygosity (ROH), while the numerous shorter tracts relate to shared ancestry tens and hundreds of generations ago. Human populations have experienced a wide range of demographic histories and hold diverse cultural attitudes to consanguinity. In a global population dataset, genome-wide analysis of long and shorter ROH allows categorisation of the mainly indigenous populations sampled here into four major groups in which the majority of the population are inferred to have: (a) recent parental relatedness (south and west Asians); (b) shared parental ancestry arising hundreds to thousands of years ago through long term isolation and restricted effective population size (Ne), but little recent inbreeding (Oceanians); (c) both ancient and recent parental relatedness (Native Americans); and (d) only the background level of shared ancestry relating to continental Ne (predominantly urban Europeans and East Asians; lowest of all in sub-Saharan African agriculturalists), and the occasional cryptically inbred individual. Moreover, individuals can be positioned along axes representing this demographic historic space. Long runs of homozygosity are therefore a globally widespread and under-appreciated characteristic of our genomes, which record past consanguinity and population isolation and provide a distinctive record of the demographic history of an individual's ancestors. Individual ROH measures will also allow quantification of the disease risk arising from polygenic recessive effects.
doi:10.1371/journal.pone.0013996
PMCID: PMC2981575  PMID: 21085596
9.  Bayesian methods for instrumental variable analysis with genetic instruments (‘Mendelian randomization’): example with urate transporter SLC2A9 as an instrumental variable for effect of urate levels on metabolic syndrome 
The ‘Mendelian randomization’ approach uses genotype as an instrumental variable to distinguish between causal and non-causal explanations of biomarker–disease associations. Classical methods for instrumental variable analysis are limited to linear or probit models without latent variables or missing data, rely on asymptotic approximations that are not valid for weak instruments and focus on estimation rather than hypothesis testing. We describe a Bayesian approach that overcomes these limitations, using the JAGS program to compute the log-likelihood ratio (lod score) between causal and non-causal explanations of a biomarker–disease association. To demonstrate the approach, we examined the relationship of plasma urate levels to metabolic syndrome in the ORCADES study of a Scottish population isolate, using genotype at six single-nucleotide polymorphisms in the urate transporter gene SLC2A9 as an instrumental variable. In models that allow for intra-individual variability in urate levels, the lod score favouring a non-causal over a causal explanation was 2.34. In models that do not allow for intra-individual variability, the weight of evidence against a causal explanation was weaker (lod score 1.38). We demonstrate the ability to test one of the key assumptions of instrumental variable analysis—that the effects of the instrument on outcome are mediated only through the intermediate variable—by constructing a test for residual effects of genotype on outcome, similar to the tests of ‘overidentifying restrictions’ developed for classical instrumental variable analysis. The Bayesian approach described here is flexible enough to deal with any instrumental variable problem, and does not rely on asymptotic approximations that may not be valid for weak instruments. The approach can easily be extended to combine information from different study designs. Statistical power calculations show that instrumental variable analysis with genetic instruments will typically require combining information from moderately large cohort and cross-sectional studies of biomarkers with information from very large genetic case–control studies.
doi:10.1093/ije/dyp397
PMCID: PMC2878456  PMID: 20348110
Bayesian analysis; biomarkers; uric acid; human SLC2A9 protein; Monte Carlo method; causality; randomization; genetics
10.  Reduced fetal growth rate and increased risk of death from ischaemic heart disease: cohort study of 15 000 Swedish men and women born 1915-29 
BMJ : British Medical Journal  1998;317(7153):241-245.
Objective: To establish whether fetal growth rate (as distinct from size at birth) is associated with mortality from ischaemic heart disease.
Design: Cohort study based on uniquely detailed obstetric records with 97% follow up over the entire life course and linkage to census data in adult life.
Subjects: All 14 611 babies delivered at the Uppsala Academic Hospital, Sweden, during 1915-29 followed up to end of 1995.
Main outcome measures: Mortality from ischaemic heart disease and other causes.
Results: Cardiovascular disease showed an inverse association with birth weight for both men and women, although this was significant only for men. In men a 1000 g increase in birth weight was associated with a proportional reduction in the rate of ischaemic heart disease of 0.77 (95% confidence interval 0.67 to 0.90). Adjustment for socioeconomic circumstances at birth and in adult life led to slight attenuation of this effect. Relative to the lowest fourth of birth weight for gestational age, mortality from ischaemic heart disease in men in the second, third, and fourth fourths was 0.81 (0.66 to 0.98), 0.63 (0.50 to 0.78), and 0.67 (0.54 to 0.82), respectively. The inclusion of birth weight per se and birth weight for gestational age in the same model strengthened the association with birth weight for gestational age but removed the association with birth weight.
Conclusion: This study provides by far the most persuasive evidence of a real association between size at birth and mortality from ischaemic heart disease in men, which cannot be explained by methodological artefact or socioeconomic confounding. It strongly suggests that it is variation in fetal growth rate rather than size at birth that is aetiologically important.
Key messages Adult mortality from ischaemic heart disease increases as size at birth declines This association cannot be explained by artefact including selection bias or socioeconomic confounding The effect of size at birth (birth weight, ponderal index) is explained by the more fundamental association of reduced fetal growth rate with increased mortality from ischaemic heart disease The relevant determinants of fetal growth rate that drive this association have yet to be identified
PMCID: PMC28614  PMID: 9677213

Results 1-10 (10)