Toward a fine-scale population health monitoring system.

Understanding population health disparities is an essential component of equitable precision health efforts. Epidemiology research often relies on definitions of race and ethnicity, but these population labels may not adequately capture disease burdens and environmental factors impacting specific sub-populations. Here, we propose a framework for repurposing data from electronic health records (EHRs) in concert with genomic data to explore the demographic ties that can impact disease burdens. Using data from a diverse biobank in New York City, we identified 17 communities sharing recent genetic ancestry. We observed 1,177 health outcomes that were statistically associated with a specific group and demonstrated significant differences in the segregation of genetic variants contributing to Mendelian diseases. We also demonstrated that fine-scale population structure can impact the prediction of complex disease risk within groups. This work reinforces the utility of linking genomic data to EHRs and provides a framework toward fine-scale monitoring of population health.

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

The Polygenic and Monogenic Basis of Blood Traits and Diseases.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

An integrative framework to prioritize genes in more than 500 loci associated with body mass index.

Obesity is a major risk factor for a myriad of diseases, affecting >600 million people worldwide. Genome-wide association studies (GWASs) have identified hundreds of genetic variants that influence body mass index (BMI), a commonly used metric to assess obesity risk. Most variants are non-coding and likely act through regulating genes nearby. Here, we apply multiple computational methods to prioritize the likely causal gene(s) within each of the 536 previously reported GWAS-identified BMI-associated loci. We performed summary-data-based Mendelian randomization (SMR), FINEMAP, DEPICT, MAGMA, transcriptome-wide association studies (TWASs), mutation significance cutoff (MSC), polygenic priority score (PoPS), and the nearest gene strategy. Results of each method were weighted based on their success in identifying genes known to be implicated in obesity, ranking all prioritized genes according to a confidence score (minimum: 0; max: 28). We identified 292 high-scoring genes (≥11) in 264 loci, including genes known to play a role in body weight regulation (e.g., DGKI, ANKRD26, MC4R, LEPR, BDNF, GIPR, AKT3, KAT8, MTOR) and genes related to comorbidities (e.g., FGFR1, ISL1, TFAP2B, PARK2, TCF7L2, GSK3B). For most of the high-scoring genes, however, we found limited or no evidence for a role in obesity, including the top-scoring gene BPTF. Many of the top-scoring genes seem to act through a neuronal regulation of body weight, whereas others affect peripheral pathways, including circadian rhythm, insulin secretion, and glucose and carbohydrate homeostasis. The characterization of these likely causal genes can increase our understanding of the underlying biology and offer avenues to develop therapeutics for weight loss.

Inherited causes of clonal haematopoiesis in 97,691 whole genomes.

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

Life is pain: Fibromyalgia as a nexus of multiple liability distributions.

Fibromyalgia is a complex disease of unclear etiology that is complicated by difficulties in diagnosis, treatment, and clinical heterogeneity. To clarify this etiology, healthcare-based data are leveraged to assess the influences on fibromyalgia in several domains. Prevalence is less than 1% of females in our population register data, and about 1/10th that in males. Fibromyalgia often presents with co-occurring conditions including back pain, rheumatoid arthritis, and anxiety. More comorbidities are identified with hospital-associated biobank data, falling into three broad categories of pain-related, autoimmune, and psychiatric disorders. Selecting representative phenotypes with published genome-wide association results for polygenic scoring, we confirm genetic predispositions to psychiatric, pain sensitivity, and autoimmune conditions show associations with fibromyalgia, although these may differ by ancestry group. We conduct a genome-wide association analysis of fibromyalgia in biobank samples, which did not result in any genome-wide significant loci; further studies with increased sample size are necessary to identify specific genetic effects on fibromyalgia. Overall, fibromyalgia appears to have strong clinical and likely genetic links to several disease categories, and could usefully be understood as a composite manifestation of these etiological sources.

Whole-Genome Sequencing Association Analyses of Stroke and Its Subtypes in Ancestrally Diverse Populations From Trans-Omics for Precision Medicine Project.

BACKGROUND AND PURPOSE: Stroke is the leading cause of death and long-term disability worldwide. Previous genome-wide association studies identified 51 loci associated with stroke (mostly ischemic) and its subtypes among predominantly European populations. Using whole-genome sequencing in ancestrally diverse populations from the Trans-Omics for Precision Medicine (TOPMed) Program, we aimed to identify novel variants, especially low-frequency or ancestry-specific variants, associated with all stroke, ischemic stroke and its subtypes (large artery, cardioembolic, and small vessel), and hemorrhagic stroke and its subtypes (intracerebral and subarachnoid). METHODS: Whole-genome sequencing data were available for 6833 stroke cases and 27 116 controls, including 22 315 European, 7877 Black, 2616 Hispanic/Latino, 850 Asian, 54 Native American, and 237 other ancestry participants. In TOPMed, we performed single variant association analysis examining 40 million common variants and aggregated association analysis focusing on rare variants. We also combined TOPMed European populations with over 28 000 additional European participants from the UK BioBank genome-wide array data through meta-analysis. RESULTS: In the single variant association analysis in TOPMed, we identified one novel locus 13q33 for large artery at whole-genome-wide significance (P<5.00×10-9) and 4 novel loci at genome-wide significance (P<5.00×10-8), all of which need confirmation in independent studies. Lead variants in all 5 loci are low-frequency but are more common in non-European populations. An aggregation of synonymous rare variants within the gene C6orf26 demonstrated suggestive evidence of association for hemorrhagic stroke (P<3.11×10-6). By meta-analyzing European ancestry samples in TOPMed and UK BioBank, we replicated several previously reported stroke loci including PITX2, HDAC9, ZFHX3, and LRCH1. CONCLUSIONS: We represent the first association analysis for stroke and its subtypes using whole-genome sequencing data from ancestrally diverse populations. While our findings suggest the potential benefits of combining whole-genome sequencing data with populations of diverse genetic backgrounds to identify possible low-frequency or ancestry-specific variants, they also highlight the need to increase genome coverage and sample sizes.

Inflamed Ulcerative Colitis Regions Associated With MRGPRX2-Mediated Mast Cell Degranulation and Cell Activation Modules, Defining a New Therapeutic Target.

BACKGROUND & AIMS: Recent literature has implicated a key role for mast cells in murine models of colonic inflammation, but their role in human ulcerative colitis (UC) is not well established. A major advance has been the identification of mrgprb2 (human orthologue, MRGPX2) as mediating IgE-independent mast cell activation. We sought to define mechanisms of mast cell activation and MRGPRX2 in human UC. METHODS: Colon tissues were collected from patients with UC for bulk RNA sequencing and lamina propria cells were isolated for MRGPRX2 activation studies and single-cell RNA sequencing. Genetic association of all protein-altering G-protein coupled receptor single-nucleotide polymorphism was performed in an Ashkenazi Jewish UC case-control cohort. Variants of MRGPRX2 were transfected into Chinese hamster ovary (CHO) and human mast cell (HMC) 1.1 cells to detect genotype-dependent effects on ß-arrestin recruitment, IP-1 accumulation, and phosphorylated extracellular signal-regulated kinase. RESULTS: Mast cell-specific mediators and adrenomedullin (proteolytic precursor of PAMP-12, an MRGPRX2 agonist) are up-regulated in inflamed compared to uninflamed UC. MRGPRX2 stimulation induces carboxypeptidase secretion from inflamed UC. Of all protein-altering GPCR alleles, a unique variant of MRGPRX2, Asn62Ser, was most associated with and was bioinformatically predicted to alter arrestin recruitment. We validated that the UC protective serine allele enhances ß-arrestin recruitment, decreases IP-1, and increases phosphorylated extracellular signal-regulated kinase with MRGPRX2 agonists. Single-cell RNA sequencing defines that adrenomedullin is expressed by activated fibroblasts and epithelial cells and that interferon gamma is a key upstream regulator of mast cell gene expression. CONCLUSION: Inflamed UC regions are distinguished by MRGPRX2-mediated activation of mast cells, with decreased activation observed with a UC-protective genetic variant. These results define cell modules of UC activation and a new therapeutic target.

Common and Rare Variant Prediction and Penetrance of IBD in a Large, Multi-ethnic, Health System-based Biobank Cohort.

BACKGROUND AND AIMS: Polygenic risk scores (PRS) may soon be used to predict inflammatory bowel disease (IBD) risk in prevention efforts. We leveraged exome-sequence and single nucleotide polymorphism (SNP) array data from 29,358 individuals in the multiethnic, randomly ascertained health system-based BioMe biobank to define effects of common and rare IBD variants on disease prediction and pathophysiology. METHODS: PRS were calculated from European, African American, and Ashkenazi Jewish (AJ) reference case-control studies, and a meta-GWAS run using all three association datasets. PRS were then combined using regression to assess which combination of scores best predicted IBD status in European, AJ, Hispanic, and African American cohorts in BioMe. Additionally, rare variants were assessed in genes associated with very early-onset IBD (VEO-IBD), by estimating genetic penetrance in each BioMe population. RESULTS: Combining risk scores based on association data from distinct ancestral populations improved IBD prediction for every population in BioMe and significantly improved prediction among European ancestry UK Biobank individuals. Lower predictive power for non-Europeans was observed, reflecting in part substantially lower African IBD case-control reference sizes. We replicated associations for two VEO-IBD genes, ADAM17 and LRBA, with high dominant model penetrance in BioMe. Autosomal recessive LRBA risk alleles are associated with severe, early-onset autoimmunity; we show that heterozygous carriage of an African-predominant LRBA protein-altering allele is associated with significantly decreased LRBA and CTLA-4 expression with T-cell activation. CONCLUSIONS: Greater genetic diversity in African populations improves prediction across populations, and generalizes some VEO-IBD genes. Increasing African American IBD case-collections should be prioritized to reduce health disparities and enhance pathophysiological insight.