David L. Duffy

Bio: David L. Duffy is an academic researcher from QIMR Berghofer Medical Research Institute. The author has contributed to research in topics: Population & Genome-wide association study. The author has an hindex of 73, co-authored 311 publications receiving 19867 citations. Previous affiliations of David L. Duffy include University of Queensland & Tianjin University.

A genome-wide search for asthma susceptibility loci in ethnically diverse populations

Abstract: Asthma is an inflammatory airwaysdisease associated with intermittent respiratory symptoms, bronchial hyperresponsiveness (BHR) and reversible airflow obstruction and is phenotypically heterogeneous1,2. Patterns of clustering and segregation analyses in asthma families have suggested a genetic component to asthma3–6. Previous studies reported linkage of BHR and atopy to chromosomes 5q (refs 7–9), 6p (refs 10–12), 11q (refs 13–15), 14q (ref. 16), and 12q (ref. 17) using candidate gene approaches. However, the relative roles of these genes in the pathogenesis of asthma or atopy are difficult to assess outside of the context of a genome-wide search. One genome-wide search in atopic sib pairs has been reported18, however, only 12% of their subjects had asthma. We conducted a genome-wide search in 140 families with ≥2 asthmatic sibs, from three racial groups and report evidence for linkage to six novel regions: 5p15 (P= 0.0008) and 17p11.1–q11.2 (/> = 0.0015) in African Americans; 11p15 (P = 0.0089) and 19q13 (P = 0.0013) in Caucasians; 2q33 (P = 0.0005) and 21q21 (P = 0.0040) in Hispanics. Evidence for linkage was also detected in five regions previously reported to be linked to asthma-associated phenotypes: 5q23–31 (P = 0.0187), 6p21.3–23 (P = 0.0129), 12q14–24.2 (P = 0.0042), 13q21.3–qter (P = 0.0014), and 14q11.2–13 (P = 0.0062) in Caucasians and 12q14–24.2 (P = 0.0260) in Hispanics.

A method for meta-analysis of molecular association studies.

Abstract: Although population-based molecular association studies are becoming increasingly popular, methodology for the meta-analysis of these studies has been neglected, particularly with regard to two issues: testing Hardy-Weinberg equilibrium (HWE), and pooling results in a manner that reflects a biological model of gene effect We propose a process for pooling results from population-based molecular association studies which consists of the following steps: (1) checking HWE using chi-square goodness of fit; we suggest performing sensitivity analysis with and without studies that are in HWE (2) Heterogeneity is then checked, and if present, possible causes are explored (3) If no heterogeneity is present, regression analysis is used to pool data and to determine the gene effect (4) If there is a significant gene effect, pairwise group differences are analysed and these data are allowed to 'dictate' the best genetic model (5) Data may then be pooled using this model This method is easily performed using standard software, and has the advantage of not assuming an a priori genetic model

Dating the Origin of the CCR5-Δ32 AIDS-Resistance Allele by the Coalescence of Haplotypes

Abstract: The CCR5-Delta32 deletion obliterates the CCR5 chemokine and the human immunodeficiency virus (HIV)-1 coreceptor on lymphoid cells, leading to strong resistance against HIV-1 infection and AIDS. A genotype survey of 4,166 individuals revealed a cline of CCR5-Delta32 allele frequencies of 0%-14% across Eurasia, whereas the variant is absent among native African, American Indian, and East Asian ethnic groups. Haplotype analysis of 192 Caucasian chromosomes revealed strong linkage disequilibrium between CCR5 and two microsatellite loci. By use of coalescence theory to interpret modern haplotype genealogy, we estimate the origin of the CCR5-Delta32-containing ancestral haplotype to be approximately 700 years ago, with an estimated range of 275-1,875 years. The geographic cline of CCR5-Delta32 frequencies and its recent emergence are consistent with a historic strong selective event (e.g. , an epidemic of a pathogen that, like HIV-1, utilizes CCR5), driving its frequency upward in ancestral Caucasian populations.

Genetics of asthma and hay fever in Australian twins.

Abstract: The occurrence of self-reported asthma/wheezing and hay fever among 3,808 pairs of twins from the Australian National Health and Medical Research Council Twin Registry was examined for evidence of genetic transmission by path analytic methods. The cumulative prevalence of asthma or wheezing was 13.2% and of hay fever, 32%. There were significant correlations in liability to reported disease among twins, and these were higher in monozygotic twins (MZ) (r = 0.65) than in dizygotic twins (DZ) (r = 0.25), and in male MZ twins (r = 0.75) compared with female MZ twins (r = 0.60). Analysis under the assumptions of the classic twin model suggested that there were genetic factors common to asthma and hay fever, with a correlation in genetic liability to the traits of 0.52 for men and 0.65 for women. These genes acted substantially in a nonadditive fashion in men but not in women. As the genetic correlation was significantly less than unity, this implied additional genetic factors influencing either or both diseases individually. The estimated heritability of these diseases was 60 to 70% in this population. Environmental causes of both diseases also were correlated (r = 0.53 for men and 0.33 for women). Cigarette smoking was only weakly associated with wheezing.

Melanocortin-1 Receptor Polymorphisms and Risk of Melanoma: Is the Association Explained Solely by Pigmentation Phenotype?

Abstract: Risk of cutaneous malignant melanoma (CMM) is increased in sun-exposed whites, particularly those with a pale complexion. This study was designed to investigate the relationship of the melanocortin-1 receptor (MC1R) genotype to CMM risk, controlled for pigmentation phenotype. We report the occurrence of five common MC1R variants in an Australian population-based sample of 460 individuals with familial and sporadic CMM and 399 control individuals—and their relationship to such other risk factors as skin, hair, and eye color; freckling; and nevus count. There was a strong relationship between MC1R variants and hair color and skin type. Moreover, MC1R variants were found in 72% of the individuals with CMM, whereas only 56% of the control individuals carried at least one variant (P<.001), a finding independent of strength of family history of melanoma. Three active alleles (Arg151Cys, Arg160Trp, and Asp294His), previously associated with red hair, doubled CMM risk for each additional allele carried (odds ratio 2.0; 95% confidence interval 1.6–2.6). No such independent association could be demonstrated with the Val60Leu and Asp84Glu variants. Among pale-skinned individuals alone, this association between CMM and MC1R variants was absent, but it persisted among those reporting a medium or olive/dark complexion. We conclude that the effect that MC1R variant alleles have on CMM is partly mediated via determination of pigmentation phenotype and that these alleles may also negate the protection normally afforded by darker skin coloring in some members of this white population.

Human biochemical genetics

Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm.

Abstract: The effect of genetic mutation on phenotype is of significant interest in genetics. The type of genetic mutation that causes a single amino acid substitution (AAS) in a protein sequence is called a non-synonymous single nucleotide polymorphism (nsSNP). An nsSNP could potentially affect the function of the protein, subsequently altering the carrier's phenotype. This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function. To assess the effect of a substitution, SIFT assumes that important positions in a protein sequence have been conserved throughout evolution and therefore substitutions at these positions may affect protein function. Thus, by using sequence homology, SIFT predicts the effects of all possible substitutions at each position in the protein sequence. The protocol typically takes 5–20 min, depending on the input. SIFT is available as an online tool ( http://sift-dna.org ).

Integrative analysis of 111 reference human epigenomes

Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.