Multi-omics Studies of Childhood Complex Traits in Diverse Populations

National Human Genome Research Institute

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Abstract

Overview The overall approach of the lab is to apply modern-day human genomics and genetics tools to population based childhood disease cohorts in order to better understand the pathophysiology of disease. This approach includes the recruitment of cohorts through international, national, and internal collaborators; the application of DNA sequencing technologies, including whole genome-, RNA-, bisulfite-, long-read-, and single cell sequencing; and the application of analytical frameworks that span genetic epidemiology, population genetics, and computational biology. Associations derived from this approach are then functionally validated to develop therapeutic hypotheses for the diseases in question. The 6 months covered by this annual report have included varying applications of the above in three main contexts: Childhood Severe Acute Malnutrition (SAM) Our previous studies found that DNA from children with the more-deadly edematous form of SAM (known as ESAM) was hypomethylated relative to those with the non-edematous form (NESAM). Collaborative metabolomic studies of ESAM have confirmed differences in one-carbon metabolism (1CM) between the two forms. During this most recent reporting period, using our recruited cohort of 800 DNA samples from Jamaica and Malawi, evenly split between ESAM and NESAM, we identify qualitative differences in DNA methylation between ESAM and NESAM that reflect disruptions in the normal architecture of correlation between highly methylated sites. We extended this observation to develop a systematic way of scanning the genome to characterize correlation patterns in different tissues. We also demonstrated that genetic variation in genes involved in 1CM are significantly associated with ESAM. The effects of the associated variants differ between the two countries surveyed, and we show that this is the result of ancestral differences in genetic admixture that mirror differences in the prevalence of the diseases in the two populations. We also find evidence that the associated variants may have been selected for in the recent past. We have developed a cellular model of starvation-induced fatty liver, which is a major pathological feature of SAM that is seen much more often in ESAM. This model will be used to functionally validate our genetic findings. Modifiers of Sickle Cell Disease (SCD) In this reporting period, our search for genetic modifiers of SCD has focused on cis-modifiers of fetal-hemoglobin (HbF) production. HbF is well known to ameliorate the severity of SCD and previous studies have identified genetic modifiers of HbF production and delineated regulatory motifs in the beta-globin cluster on chromosome 11, which houses and controls developmental switches in the production of beta-globin, including that from fetal to adult hemoglobin. These motifs are now targets for gene editing therapeutic approaches. To date, however, none of these studies have been performed in African populations, which have the highest global burden of SCD and a complex genetic ancestry. We performed targeted long-read sequencing across the beta-globin locus to define the complete genetic landscape of the region in 40 African individuals from Nigeria, Cameroon, Kenya, and USA, representing nine ethnolinguistic groups. We identify >4,000 structural variants (SVs) in the region, most of which are not currently characterized in public databases. Some of these SVs are found in almost all samples, likely a result of biases in the existing DNA reference sequence. We also find population-specific enrichment of SVs in groups that are not well-represented in existing public databases. Our results also identify an SV adjacent to the fetal hemoglobin gene that is unique to individuals with high levels of fetal hemoglobin and overlies a known regulatory motif. Genomic characterization of African populations Through our interactions with the H3Africa Consortium, we have contributed to ongoing efforts to delineate the landscape of African genetic variation. This includes a population-based genome-sequencing plan that seeks to use whole-genome sequences from approximately 2,000 individuals recruited from the major ethnolinguistic population groups across the continent to fill in gaps in our knowledge of human genetic variation. We completed analyses of unmapped genome and exome sequencing reads in populations from Botswana and Uganda. We have also developed a framework for leveraging data from the 40,000 individuals across the consortium who have had microarray-based genome-wide genotyping to explore the prevalence and co-inheritance of disease variants across the continent. This data will be integrated with institute-sponsored efforts to develop polygenic disease risk scores for diverse populations.