Felicia Gomez

Identifying Darwinian Selection Acting on Different Human APOL1 Variants among Diverse African Populations

Disease susceptibility can arise as a consequence of adaptation to infectious disease. Recent findings have suggested that higher rates of chronic kidney disease (CKD) in individuals with recent African ancestry might be attributed to two risk alleles (G1 and G2) at the serum-resistance-associated (SRA)-interacting-domain-encoding region of APOL1. These two alleles appear to have arisen adaptively, possibly as a result of their protective effects against human African trypanosomiasis (HAT), or African sleeping sickness. In order to explore the distribution of potential functional variation at APOL1, we studied nucleotide variation in 187 individuals across ten geographically and genetically diverse African ethnic groups with exposure to two Trypanosoma brucei subspecies that cause HAT. We observed unusually high levels of nonsynonymous polymorphism in the regions encoding the functional domains that are required for lysing parasites. Whereas allele frequencies of G2 were similar across all populations (3%-8%), the G1 allele was only common in the Yoruba (39%). Additionally, we identified a haplotype (termed G3) that contains a nonsynonymous change at the membrane-addressing-domain-encoding region of APOL1 and is present in all populations except for the Yoruba. Analyses of long-range patterns of linkage disequilibrium indicate evidence of recent selection acting on the G3 haplotype in Fulani from Cameroon. Our results indicate that the G1 and G2 variants in APOL1 are geographically restricted and that there might be other functional variants that could play a role in HAT resistance and CKD risk in African populations.

Novel approach identifies SNPs in SLC2A10 and KCNK9 with evidence for parent-of-origin effect on body mass index

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.

Genetic Variation and Adaptation in Africa: Implications for Human Evolution and Disease

Because modern humans originated in Africa and have adapted to diverse environments, African populations have high levels of genetic and phenotypic diversity. Thus, genomic studies of diverse African ethnic groups are essential for understanding human evolutionary history and how this leads to differential disease risk in all humans. Comparative studies of genetic diversity within and between African ethnic groups creates an opportunity to reconstruct some of the earliest events in human population history and are useful for identifying patterns of genetic variation that have been influenced by recent natural selection. Here we describe what is currently known about genetic variation and evolutionary history of diverse African ethnic groups. We also describe examples of recent natural selection in African genomes and how these data are informative for understanding the frequency of many genetic traits, including those that cause disease susceptibility in African populations and populations of recent African descent.

Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations

Meta-analyses of European populations has successfully identified genetic variants in over 100 loci associated with lipid levels, but our knowledge in other ethnicities remains limited. To address this, we performed dense genotyping of ∼2,000 candidate genes in 7,657 African Americans, 1,315 Hispanics and 841 East Asians, using the IBC array, a custom ∼50,000 SNP genotyping array. Meta-analyses confirmed 16 lipid loci previously established in European populations at genome-wide significance level, and found multiple independent association signals within these lipid loci. Initial discovery and in silico follow-up in 7,000 additional African American samples, confirmed two novel loci: rs5030359 within ICAM1 is associated with total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) (p = 8.8×10−7 and p = 1.5×10−6 respectively) and a nonsense mutation rs3211938 within CD36 is associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 13.5×10−12). The rs3211938-G allele, which is nearly absent in European and Asian populations, has been previously found to be associated with CD36 deficiency and shows a signature of selection in Africans and African Americans. Finally, we have evaluated the effect of SNPs established in European populations on lipid levels in multi-ethnic populations and show that most known lipid association signals span across ethnicities. However, differences between populations, especially differences in allele frequency, can be leveraged to identify novel signals, as shown by the discovery of ICAM1 and CD36 in the current report.

Recurrent somatic mutations affecting B-cell receptor signaling pathway genes in follicular lymphoma

Follicular lymphoma (FL) is the most common form of indolent non-Hodgkin lymphoma, yet it remains only partially characterized at the genomic level. To improve our understanding of the genetic underpinnings of this incurable and clinically heterogeneous disease, whole-exome sequencing was performed on tumor/normal pairs from a discovery cohort of 24 patients with FL. Using these data and mutations identified in other B-cell malignancies, 1716 genes were sequenced in 113 FL tumor samples from 105 primarily treatment-naive individuals. We identified 39 genes that were mutated significantly above background mutation rates. CREBBP mutations were associated with inferior PFS. In contrast, mutations in previously unreported HVCN1, a voltage-gated proton channel-encoding gene and B-cell receptor signaling modulator, were associated with improved PFS. In total, 47 (44.8%) patients harbor mutations in the interconnected B-cell receptor (BCR) and CXCR4 signaling pathways. Histone gene mutations were more frequent than previously reported (identified in 43.8% of patients) and often co-occurred (17.1% of patients). A novel, recurrent hotspot was identified at a posttranslationally modified residue in the histone H2B family. This study expands the number of mutated genes described in several known signaling pathways and complexes involved in lymphoma pathogenesis (BCR, Notch, SWitch/sucrose nonfermentable (SWI/SNF), vacuolar ATPases) and identified novel recurrent mutations (EGR1/2, POU2AF1, BTK, ZNF608, HVCN1) that require further investigation in the context of FL biology, prognosis, and treatment.

Selection of Models for the Analysis of Risk-factor Trees: Leveraging biological knowledge to mine large sets of risk factors with application to microbiome data

MOTIVATION Establishment of a statistical association between microbiome features and clinical outcomes is of growing interest because of the potential for yielding insights into biological mechanisms and pathogenesis. Extracting microbiome features that are relevant for a disease is challenging and existing variable selection methods are limited due to large number of risk factor variables from microbiome sequence data and their complex biological structure. RESULTS We propose a tree-based scanning method, Selection of Models for the Analysis of Risk factor Trees (referred to as SMART-scan), for identifying taxonomic groups that are associated with a disease or trait. SMART-scan is a model selection technique that uses a predefined taxonomy to organize the large pool of possible predictors into optimized groups, and hierarchically searches and determines variable groups for association test. We investigate the statistical properties of SMART-scan through simulations, in comparison to a regular single-variable analysis and three commonly-used variable selection methods, stepwise regression, least absolute shrinkage and selection operator (LASSO) and classification and regression tree (CART). When there are taxonomic group effects in the data, SMART-scan can significantly increase power by using bacterial taxonomic information to split large numbers of variables into groups. Through an application to microbiome data from a vervet monkey diet experiment, we demonstrate that SMART-scan can identify important phenotype-associated taxonomic features missed by single-variable analysis, stepwise regression, LASSO and CART.

Single-agent ibrutinib in relapsed or refractory follicular lymphoma: A phase 2 consortium trial

Most patients with follicular lymphoma (FL) experience multiple relapses necessitating subsequent lines of therapy. Ibrutinib, a Bruton tyrosine kinase (BTK) inhibitor approved for the treatment of several B-cell malignancies, showed promising activity in FL in a phase 1 study. We report the results of a phase 2 trial evaluating ibrutinib in recurrent FL. Forty patients with recurrent FL were treated with ibrutinib 560 mg/d until progression or intolerance. The primary end point was overall response rate (ORR). Exploratory analyses included correlations of outcome with recurrent mutations identified in a cancer gene panel that used next-generation sequencing in pretreatment biopsies from 31 patients and results of early interim positron emission tomography/computed tomography scans in 20 patients. ORR was 37.5% with a complete response rate of 12.5%, median progression-free survival (PFS) of 14 months, and 2-year PFS of 20.4%. Response rates were significantly higher among patients whose disease was sensitive to rituximab (52.6%) compared with those who were rituximab refractory (16.7%) (P = .04). CARD11 mutations were present in 16% of patients (5 of 31) and predicted resistance to ibrutinib with only wild-type patients responding (P = .002). Maximum standardized uptake value at cycle 1 day 8 correlated with response and PFS. Ibrutinib was well-tolerated with a toxicity profile similar to labeled indications. Ibrutinib is a well-tolerated treatment with modest activity in relapsed FL. Evaluation of BTK inhibitors in earlier lines of therapy may be warranted on the basis of improved response rates in rituximab-sensitive disease. Somatic mutations such as CARD11 may have an impact on response to ibrutinib, may inform clinical decisions, and should be evaluated in larger data sets. This trial was registered at www.clinicaltrials.gov as #NCT01849263.

Admixture mapping of coronary artery calcification in African Americans from the NHLBI family heart study

BackgroundCoronary artery calcification (CAC) is an imaging biomarker of coronary atherosclerosis. In European Americans, genome-wide association studies (GWAS) have identified several regions associated with coronary artery disease. However, few large studies have been conducted in African Americans. The largest meta-analysis of CAC in African Americans failed to identify genome-wide significant variants despite being powered to detect effects comparable to effects identified in European Americans. Because CAC is different in prevalence and severity in African Americans and European Americans, admixture mapping is a useful approach to identify loci missed by GWAS.ResultsWe applied admixture mapping to the African American cohort of the Family Heart Study and identified one genome-wide significant region on chromosome 12 and three potential regions on chromosomes 6, 15, and 19 that are associated with CAC. Follow-up studies using previously reported GWAS meta-analysis data suggest that the regions identified on chromosome 6 and 15 contain variants that are possibly associated with CAC. The associated region on chromosome 6 contains the gene for BMP-6, which is expressed in vascular calcific lesions.ConclusionsOur results suggest that admixture mapping can be a useful hypothesis-generating tool to identify genomic regions that contribute to complex diseases in genetically admixed populations.

Patterns of nucleotide and haplotype diversity at ICAM-1 across global human populations with varying levels of malaria exposure

Malaria is one of the strongest selective pressures in recent human evolution. African populations have been and continue to be at risk for malarial infections. However, few studies have re-sequenced malaria susceptibility loci across geographically and genetically diverse groups in Africa. We examined nucleotide diversity at Intercellular adhesion molecule-1 (ICAM-1), a malaria susceptibility candidate locus, in a number of human populations with a specific focus on diverse African ethnic groups. We used tests of neutrality to assess whether natural selection has impacted this locus and tested whether SNP variation at ICAM-1 is correlated with malaria endemicity. We observe differing patterns of nucleotide and haplotype variation in global populations and higher levels of diversity in Africa. Although we do not observe a deviation from neutrality based on the allele frequency distribution, we do observe several alleles at ICAM-1, including the ICAM-1Kilifi allele, that are correlated with malaria endemicity. We show that the ICAM-1Kilifi allele, which is common in Africa and Asia, exists on distinct haplotype backgrounds and is likely to have arisen more recently in Asia. Our results suggest that correlation analyses of allele frequencies and malaria endemicity may be useful for identifying candidate functional variants that play a role in malaria resistance and susceptibility.

Impact of Natural Selection Due to Malarial Disease on Human Genetic Variation

Malaria is an important selective pressure in modern human evolution. The dynamic relationship between human hosts and Plasmodium parasites has left numerous “footprints” of natural selection within the genomes of both the host and the parasite. In this chapter we describe the evolutionary impact of malaria, caused by Plasmodium infection, on human genetic diversity. Specifically, we focus on patterns of genetic variation that alter hemoglobin structure and red blood cell function. We also discuss patterns of nucleotide variation at loci involved in malaria pathogenesis and immune defense. We describe different types of natural selection that could underlie the observed nucleotide diversity at each locus. Finally, this chapter also discusses future directions for the study of human host/pathogen coevolution. These include departure from single-gene studies and the growing application of genomic methodologies for the identification of novel genetic loci and functional variants that play a role in malarial infection.