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Biomedical subjects

Diogo Meyer

Publications and source records attributed to Diogo Meyer.

6 recordsLinked to original sources

Genomic landscape of autism spectrum disorder in Brazil.

Genomic studies of autism spectrum disorder (ASD) have largely excluded admixed populations. To address this gap, we characterized the genomic landscape of ASD in Brazil by combining a systematic literature review with whole-exome sequencing analysis of 441 Brazilian individuals and their families. Our analysis revealed a conclusive molecular diagnosis in 13.1% of probands. The diagnostic yield was higher among individuals with clinical features, particularly comorbid signs of intellectual disability, hypotonia, and seizures, providing a basis for prioritizing genetic testing. The sample presented a diverse ancestry, with major European, African, and Native American contributions. Notably, more than half of the identified rare risk variants were located on non-European haplotypes. Both de novo and inherited variants contributed to ASD risk, and we reinforce NPAS3 as a candidate ASD risk gene. This study provides the first comprehensive genomic overview of ASD in a large Brazilian cohort, reinforcing the critical need to include diversely admixed populations in genomic research to expand the understanding of ASD architecture and improve diagnostic strategies in resource-limited settings.

Journal Article↗

Signatures of demographic history and natural selection in the human major histocompatibility complex Loci.

Many lines of evidence show that several HLA loci have experienced balancing selection. However, distinguishing among demographic and selective explanations for patterns of variation observed with HLA genes remains a challenge. In this study we address this issue using data from a diverse set of human populations at six classical HLA loci and, employing a comparative genomics approach, contrast results for HLA loci to those for non-HLA markers. Using a variety of analytic methods, we confirm and extend evidence for selection acting on several HLA loci. We find that allele frequency distributions for four of the six HLA loci deviate from neutral expectations and show that this is unlikely to be explained solely by demographic factors. Other features of HLA variation are explained in part by demographic history, including decreased heterozygosity and increased LD for populations at greater distances from Africa and a similar apportionment of genetic variation for HLA loci compared to putatively neutral non-HLA loci. On the basis of contrasts among different HLA loci and between HLA and non-HLA loci, we conclude that HLA loci bear detectable signatures of both natural selection and demographic history.

Evolution, Molecular↗

The molecular signature of selection underlying human adaptations.

In the last decade, advances in human population genetics and comparative genomics have resulted in important contributions to our understanding of human genetic diversity and genetic adaptation. For the first time, we are able to reliably detect the signature of natural selection from patterns of DNA polymorphism. Identifying the effects of natural selection in this way provides a crucial piece of evidence needed to support hypotheses of human adaptation. This review provides a detailed description of the theory and analytical approaches used to detect signatures of natural selection in the human genome. We discuss these methods in relation to four classic human traits--skin color, the Duffy blood group, bitter-taste sensation, and lactase persistence. By highlighting these four traits we are able to discuss the ways in which analyses of DNA polymorphism can lead to inferences regarding past histories of selection. Specifically, we can infer the importance of specific regimes of selection (i.e. directional selection, balancing selection, and purifying selection) in the evolution of a trait because these different types of selection leave different patterns of DNA polymorphism. In addition, we demonstrate how these types of data can be used to estimate the time frame in which selection operated on a trait. As the field has advanced, a general issue that has come to the forefront is how specific demographic events in human history, such as population expansions, bottlenecks, and subdivision of populations, have also left a signature across the genome that can interfere with our detection of the footprint of selection at particular genes. Therefore, we discuss this general problem with respect to the four traits reviewed here, and describe the ways in which the signature of selection can be teased from a background signature of demographic history. Finally, we move from a discussion of analyses of selection motivated by a "candidate-gene" approach, in which a priori information led to the analysis of specific gene, to discussion of "genome-scanning" approaches that are directed at discovering new genes that have been under positive selection. Such scans can be designed to detect those genes that have been positively selected in our divergence from chimpanzees, as well as those genes that have been under selection as human populations have migrated, differentiated, and adapted to specific geographic environments. We predict that both approaches will be applied in the future, enabling a greater insight into human species-wide adaptations, as well as the specific adaptations of human populations.

Animals↗

High resolution HLA-DRB1 identification of a Caucasian population.

Polymerase chain reaction-sequence-specific oligonucleotide probes typing methods have been applied to 1000 individuals from the Northern Ireland population to give human leukocyte antigen DRB1 (HLA-DRB1) allele assignment. HLA-DRB1 allele frequencies and four-locus haplotypes (A/B/C/DR) for this Caucasian population, based on HLA class I and class II allele assignment, are now presented. No significant deviations from Hardy-Weinberg proportions were observed. The HLA-C locus exhibited marginal evidence of selection (p<0.03, uncorrected one-sided test) in the direction of balancing selection; the HLA-A, -B, and -DRB1 allele frequency distributions were compatible with expectations under a neutral model (which does not mean that selection is not operating). Evidence for selection was seen on haplotypes HLA-A*010101-B*0801-DRB1*030101 and HLA-A*290201-B*440301-DRB1*070101 based on their patterns of linkage disequilibrium.

Alleles↗

PyPop: a software framework for population genomics: analyzing large-scale multi-locus genotype data.

Software to analyze multi-locus genotype data for entire populations is useful for estimating haplotype frequencies, deviation from Hardy-Weinberg equilibrium and patterns of linkage disequilibrium. These statistical results are important to both those interested in human genome variation and disease predisposition as well as evolutionary genetics. As part of the 13th International Histocompatibility and Immunogenetics Working Group (IHWG), we have developed a software framework (PyPop). The primary novelty of this package is that it allows integration of statistics across large numbers of data-sets by heavily utilizing the XML file format and the R statistical package to view graphical output, while retaining the ability to inter-operate with existing software. Largely developed to address human population data, it can, however, be used for population based data for any organism. We tested our software on the data from the 13th IHWG which involved data sets from at least 50 laboratories each of up to 1000 individuals with 9 MHC loci (both class I and class II) and found that it scales to large numbers of data sets well.

Computational Biology↗

Haplotype frequency estimation in patient populations: the effect of departures from Hardy-Weinberg proportions and collapsing over a locus in the HLA region.

Haplotype analyses are an important area in the study of the genetic components of human disease. Associations between markers and disease loci that are not evident with a single marker locus may be identified in multi-locus marker analyses using estimated haplotype frequencies (HFs). Procedures that make use of the expectation-maximization (EM) algorithm to estimate HFs from unphased genotype data are in common use in genetic studies. The EM algorithm uses these unphased genotype frequencies along with the assumption of Hardy-Weinberg proportions (HWP) to converge on HF estimates. In this paper, we assess the accuracy of EM estimates of HFs in patients with type I diabetes for whom the true haplotypes are known, but the data are analyzed ignoring family information to allow comparison between estimated and true frequencies. The data consist of six HLA loci with high levels of polymorphism and a range of departures from HWP and linkage equilibrium. While the overall accuracy of the EM estimates is good, there can be large over- and underestimates of particular HFs, even for common haplotypes, especially when the loci involved deviate significantly from HWP. Estimating HFs for three or more loci and then collapsing over loci so as to generate two locus haplotypes can improve the accuracy of the estimation. The collapsing procedure is most beneficial when one of the loci in the two-locus haplotype of interest deviates significantly from HWP and the locus collapsed over is in linkage disequilibrium with the other loci.

Algorithms↗