Biology subjects

Belbin, G. M.

Publications and source records attributed to Belbin, G. M..

10 recordsLinked to original sources

bioRxiv2023

The effects of reference panel perturbations on the accuracy of genotype imputation

Reference-based genotype imputation is a standard technique that has become increasingly popular in large-scale studies involving genomic data. The two key elements involved in the process of genotype imputation are (1) the haplotype reference panel to which a target individual is being imputed, and (2) the imputation algorithm used to infer missing genotypes in the target individual. The imputation literature has historically focused mainly on (2), with a typical comparative study investigating the relative performance of various imputation algorithms while holding the reference panel constant. However, the role of the reference panel itself (1) on overall imputation performance is equally, if not more, important than the choice among many high-performing algorithms. Even though it is intuitive that the quality of a reference panel should play a role in the accuracy of imputation, it is nonetheless unclear to what extent common errors during panel creation (e.g., genotyping and phase error) lead to suboptimal imputation performance. In this study, we investigate the effects of applying three distinct modes of perturbations to a widely used haplotype reference panel in human genetics on the resulting imputation accuracy. Specifically, we perturb the reference panel by (1) randomly introducing phase errors, (2) randomly introducing genotype errors, and (3) randomly pruning variants from the panel (all at varying magnitudes). We then impute a set of diverse individuals at various sequencing coverages (0.5x, 1.0x, and 2.0x) to these various perturbed panels and evaluate imputation accuracy using the r2 metric for the entire cohort as well as ancestry-stratified subsets. We observe that both phase- and genotype-perturbations can dramatically affect imputation accuracy, particularly at very low allele frequencies, while pruning variants has a far smaller effect. We then empirically verified that our simulations reliably predict the impact of potential filtering techniques in a real-world dataset. In the context of haplotype reference panels, these results suggest that phasing and genotyping accuracy are far more important than the density of a reference panel used for imputation.

genomics↗

bioRxiv2021

Selecting Clustering Algorithms for IBD Mapping

BackgroundGroups of distantly related individuals who share a short segment of their genome identical-by-descent (IBD) can provide insights about rare traits and diseases in massive biobanks via a process called IBD mapping. Clustering algorithms play an important role in finding these groups. We set out to analyze the fitness of commonly used, fast and scalable clustering algorithms for IBD mapping applications. We designed a realistic benchmark for local IBD graphs and utilized it to compare clustering algorithms in terms of statistical power. We also investigated the effectiveness of common clustering metrics as replacements for statistical power. ResultsWe simulated 3.4 million clusters across 850 experiments with varying cluster counts, false-positive, and false-negative rates. Infomap and Markov Clustering (MCL) community detection methods have high statistical power in most of the graphs, compared to greedy methods such as Louvain and Leiden. We demonstrate that standard clustering metrics, such as modularity, cannot predict statistical power of algorithms in IBD mapping applications, though they can help with simulating realistic benchmarks. We extend our findings to real datasets by analyzing 3 populations in the Population Architecture using Genomics and Epidemiology (PAGE) Study with 51,000 members and 2 million shared segments on Chromosome 1, resulting in the extraction of 39 million local IBD clusters across three different populations in PAGE. We used cluster properties derived in PAGE to increase the accuracy of our simulations and comparison. ConclusionsMarkov Clustering produces a 30% increase in statistical power compared to the current state-of-art approach, while reducing runtime by 3 orders of magnitude; making it computationally tractable in modern large-scale genetic datasets. We provide an efficient implementation to enable clustering at scale for IBD mapping and poplation-based linkage for various populations and scenarios.

bioinformatics↗

bioRxiv2019

Exome Sequencing Reveals a High Prevalence of BRCA1 and BRCA2 Founder Variants in a Diverse Population-Based Biobank

Pathogenic variants in BRCA1 and BRCA2 (BRCA1/2) lead to increased risk of breast, ovarian, and other cancers, but most variant positive individuals in the general population are unaware of their risk, and little is known about the prevalence of pathogenic BRCA1/2 variants in non-European populations. We investigated BRCA1/2 prevalence and impact using exome sequencing and electronic health record (EHR) data from 30,223 adult participants of the BioMe Biobank in New York City. There were 218 (0.7%) individuals harboring expected pathogenic variants, resulting in an overall prevalence of 1 in 139. In sub-populations defined by genetic ancestry, the highest prevalence was in individuals of Ashkenazi Jewish (AJ; 1 in 49), Filipino and Southeast Asian (1 in 81), and Non-AJ European (1 in 103) descent. Among 218 variant positive individuals, 112 (51.4%) harbored known founder variants: 80 had AJ founder variants (BRCA1 c.5266dupC and c.68_69delAG, and BRCA2 c.5946delT), 7 had a Puerto Rican founder variant (BRCA2 c.3922G>T), and 25 had one of 19 other founder variants. Non-European populations were more likely to harbor BRCA1/2 variants that were not classified in ClinVar, or that had uncertain or conflicting evidence for pathogenicity. Within mixed ancestry populations, such as Hispanic/Latinos with genetic ancestry from Africa, Europe, and the Americas, there was a strong correlation between the proportion African genetic ancestry and the likelihood of harboring a BRCA1/2 variant with uncertain or conflicting evidence for pathogenicity. Based on EHR and participant questionnaire data, [~]28% of variant positive individuals had a personal history, and [~]45% a personal or family history of BRCA1/2-associated cancers. Approximately 27% of variant positive individuals had evidence of prior clinical genetic testing for BRCA1/2. However, individuals with AJ founder variants were twice as likely to have had a clinical test (38%) than those with other pathogenic variants (19%). These findings deepen our knowledge about BRCA1/2 variants and associated cancer risk in diverse populations, indicate a gap in knowledge about potential cancer-related variants in non-European populations, and suggest that genomic screening in diverse patient populations may be an effective tool to identify at-risk individuals.

genomics↗

bioRxiv2019

Towards 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 specific to sub-populations. Here we propose a framework for repurposing data from Electronic Health Records (EHRs) in concert with genomic data to explore enrichment of disease within sub-populations. Using data from a diverse biobank in New York City, we genetically identified 17 sub-populations, and noted the presence of genetic founder effects in 7. By then linking community membership to the EHR, we were able to identify over 600 health outcomes that were statistically enriched within a specific population, with many representing known associations, and many others being novel. This work reinforces the utility of linking genomic data to EHRs, and provides a framework towards fine-scale monitoring of population health.

genomics↗

bioRxiv2019

Rapid detection of identity-by-descent tracts for mega-scale datasets

The ability to identify segments of genomes identical-by-descent (IBD) is a part of standard workflows in both statistical and population genetics. However, traditional methods for finding local IBD across all pairs of individuals scale poorly leading to a lack of adoption in very large-scale datasets. Here, we present iLASH, IBD by LocAlity-Sensitive Hashing, an algorithm based on similarity detection techniques that shows equal or improved accuracy in simulations compared to the current leading method and speeds up analysis by several orders of magnitude on genomic datasets, making IBD estimation tractable for hundreds of thousands to millions of individuals. We applied iLASH to the Population Architecture using Genomics and Epidemiology (PAGE) dataset of [~]52,000 multi-ethnic participants, including several founder populations with elevated IBD sharing, which identified IBD segments on a single machine in an hour ([~]3 minutes per chromosome compared to over 6 days per chromosome for a state-of-the-art algorithm). iLASH is able to efficiently estimate IBD tracts in very large-scale datasets, as demonstrated via IBD estimation across the entire UK Biobank ([~]500,000 individuals), detecting nearly 13 billion pairwise IBD tracts shared between [~]11% of participants. In summary, iLASH enables fast and accurate detection of IBD, an upstream step in applications of IBD for population genetics and trait mapping.

genomics↗

bioRxiv2019

Rapid response to the Alpha-1 Adrenergic Agent Phenylephrine in the Perioperative Period is Impacted by Genomics and Ancestry

BackgroundThe emergence of genomic data in biobanks and health systems offers new ways to derive medically important phenotypes, including acute phenotypes that occur during in-patient clinical care. We hypothesized that there is a genetic underpinning to the magnitude of the response to phenylephrine, an 1-adrenergic receptor agonist commonly used to treat hypotension during anesthesia and surgery.\n\nMethodsWe quantified the response to phenylephrine by determining the delta between the minimum blood pressure (BP) within five minutes before and the maximum BP within five minutes after bolus administration. We then performed a genome-wide association study (GWAS) adjusted for genetic ancestry, demographics, and relevant clinical covariates to investigate genetic factors underlying individual differences systolic BP response to phenylephrine ({Delta}SBP), as well as mean arterial pressure ({Delta}MAP) and diastolic BP ({Delta}DBP), for both the entire study cohort as well as for each of 3 ancestry sub-cohorts; European American(EA), African American(AA), and Hispanic American(HA).\n\nResults4,317 patients met inclusion criteria, of which 3,699 were genotyped. Average {Delta}BP values over the entire cohort were {Delta}SBP=17(+-25) mmHg, {Delta}MAP=14(+-18) mmHg, {Delta}DBP=11(+-14) mmHg. The largest difference between populations was observed for {Delta}SBP ({Delta}SBPEA=20(+-24) mmHg; {Delta}SBPHA=16(+-25) mmHg; {Delta}SBPAA=15(+-25) mmHg). The differences remained after adjusting for clinical covariates and ancestry (EA vs. HA: {Delta}SBP, p<0.032;{Delta}MAP, p<0.021;{Delta}DBP,p<0.008);(EA vs. AA:{Delta}SBP,p<5.13x10-5;{Delta}MAP,p<2.1x10-4;{Delta}DBP,p<3.3x10-4). GWAS revealed significant associations between loci and BP response in 5 different genome regions (p<5x10-8) in the entire cohort, and suggestive associations in 2 different regions in EAs (p<6x10-8,p<7x10-8). We observed non-random enrichment in association with SBP drug response in 165 loci previously reported to be associated with systolic blood pressure. Finally, we discovered rare variants, rs188427942 and rs147664194 present at [~]1% in EAs and rs146535276 present at [~]1% in AAs respectively, where patients carrying one copy of these variants show no response to phenylephrine.\n\nConclusionsIt is possible to derive a quantitative phenotype suited for comparative statistics and genome-wide association studies from routinely collected perioperative data. There are population differences in rapid response to phenylephrine, large effect alleles and novel genes affecting pharmaceutical response, and phenylephrine non-responders, with implications for personalized treatment during surgery.

genomics↗

bioRxiv2019

A positively selected, common, missense variant in FBN1 confers a 2.2 centimeter reduction of height in the Peruvian population

Peruvians are among the shortest people in the world. To understand the genetic basis of short stature in Peru, we examined an ethnically diverse group of Peruvians and identified a novel, population-specific, missense variant in FBN1 (E1297G) that is significantly associated with lower height in the Peruvian population. Each copy of the minor allele (frequency = 4.7%) reduces height by 2.2 cm (4.4 cm in homozygous individuals). This is the largest effect size known for a common height-associated variant. This variant shows strong evidence of positive selection within the Peruvian population and is significantly more frequent in Native American populations from coastal regions of Peru compared to populations from the Andes or the Amazon, suggesting that short stature in Peruvians is the result of adaptation to the coastal environment. One Sentence SummaryA mutation found in Peruvians has the largest known effect on height for a common variant. This variant is specific to Native American ancestry.

genomics↗

bioRxiv2018

Multiscale causal network models of Alzheimer’s disease identify VGF as a key regulator of disease

Though discovered over 100 years ago, the molecular foundation of sporadic Alzheimers disease (AD) remains elusive. To elucidate its complex nature, we constructed multiscale causal network models on a large human AD multi-omics dataset, integrating clinical features of AD, DNA variation, and gene and protein expression into probabilistic causal models that enabled detection and prioritization of high-confidence key drivers of AD, including the top predicted key driver VGF. Overexpression of neuropeptide precursor VGF in 5xFAD mice partially rescued beta-amyloid-mediated memory impairment and neuropathology. Molecular validation of network predictions downstream of VGF was achieved, with significant enrichment for homologous genes identified as differentially expressed in 5xFAD brains overexpressing VGF versus controls. Our findings support a causal and/or protective role for VGF in AD pathogenesis and progression.\n\nOne sentence summaryVGF protects against Alzheimers disease

genomics↗

bioRxiv2017

Genetic Diversity Turns a New PAGE in Our Understanding of Complex Traits

Summary/AbstractGenome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development, and clinical guidelines. However, the dominance of European-ancestry populations in GWAS creates a biased view of the role of human variation in disease, and hinders the equitable translation of genetic associations into clinical and public health applications. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioral phenotypes in 49,839 non-European individuals. Using strategies designed for analysis of multi-ethnic and admixed populations, we confirm 574 GWAS catalog variants across these traits, and find 38 secondary signals in known loci and 27 novel loci. Our data shows strong evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts, and insights into clinical implications. We strongly advocate for continued, large genome-wide efforts in diverse populations to reduce health disparities.

genetics↗

bioRxiv2017

Genetic Identification Of A Common Collagen Disease In Puerto Ricans Via Identity-By-Descent Mapping In A Health System

Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic BioMe biobank in New York City. By linking to medical records, we discover a locus associated with genetic relatedness that also underlies extreme short stature. We link the gene, COL27A1, with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.

genomics↗