Health care utilization of fine-scale identity by descent clusters in a Los Angeles biobank

Caggiano, Christa; Boudaie, Arya; Shemirani, Ruhollah; Petter, Ella; Chiu, Alec; Johnson, Ruth; Ercelen, Defne; Paşaniuc, Bogdan; Shortt, Jonathan A.; Gignoux, Christopher R.; Balliu, Brunilda; Arboleda, Valerie A.; Belbin, Gillian M.; Zaitlen, Noah

doi:10.1101/2022.07.12.22277520

Cited by 3 publications

(4 citation statements)

References 113 publications

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“…These techniques can then be combined to divide a population into more descriptive subgroups. A more in-depth IBD analyses within ATLAS is described in additional work [57].…”

Section: Ibd Sharing Reveals Communities Of Recent Shared Ancestry Wi...mentioning

confidence: 99%

Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative

Johnson

Ding²,

Venkateswaran³

et al. 2022

Genome Med

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Background Large medical centers in urban areas, like Los Angeles, care for a diverse patient population and offer the potential to study the interplay between genetic ancestry and social determinants of health. Here, we explore the implications of genetic ancestry within the University of California, Los Angeles (UCLA) ATLAS Community Health Initiative—an ancestrally diverse biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients (N=36,736). Methods We quantify the extensive continental and subcontinental genetic diversity within the ATLAS data through principal component analysis, identity-by-descent, and genetic admixture. We assess the relationship between genetically inferred ancestry (GIA) and >1500 EHR-derived phenotypes (phecodes). Finally, we demonstrate the utility of genetic data linked with EHR to perform ancestry-specific and multi-ancestry genome and phenome-wide scans across a broad set of disease phenotypes. Results We identify 5 continental-scale GIA clusters including European American (EA), African American (AA), Hispanic Latino American (HL), South Asian American (SAA) and East Asian American (EAA) individuals and 7 subcontinental GIA clusters within the EAA GIA corresponding to Chinese American, Vietnamese American, and Japanese American individuals. Although we broadly find that self-identified race/ethnicity (SIRE) is highly correlated with GIA, we still observe marked differences between the two, emphasizing that the populations defined by these two criteria are not analogous. We find a total of 259 significant associations between continental GIA and phecodes even after accounting for individuals’ SIRE, demonstrating that for some phenotypes, GIA provides information not already captured by SIRE. GWAS identifies significant associations for liver disease in the 22q13.31 locus across the HL and EAA GIA groups (HL p-value=2.32×10−16, EAA p-value=6.73×10−11). A subsequent PheWAS at the top SNP reveals significant associations with neurologic and neoplastic phenotypes specifically within the HL GIA group. Conclusions Overall, our results explore the interplay between SIRE and GIA within a disease context and underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping linked with EHR-based phenotyping.

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“…These techniques can then be combined to divide a population into more descriptive subgroups. A more in-depth IBD analyses within ATLAS is described in additional work [57].…”

Section: Ibd Sharing Reveals Communities Of Recent Shared Ancestry Wi...mentioning

confidence: 99%

Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative

Johnson

Ding²,

Venkateswaran³

et al. 2022

Genome Med

Self Cite

View full text Add to dashboard Cite

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“…characterizing demographic history in [42] and identifying selection within populations in [43]). An IBD-based approach in ATLAS, for example, recently identified associations between genetic clusters and genetic, clinical, and environmental data [44]. The ability of IBD clustering to identify fine-scale structure can be due to two effects.…”

Section: Discussionmentioning

confidence: 99%

“…The structure of a typical biobank is more similar to the UKB than the 1KGP, as the recruitment methodology is often based on residence within a jurisdiction. Examples include municipal (ATLAS in Los Angeles [44], BioMe in New York City [46]), regional (CARTa-GENE in Quebec [20]) and national (Million Veterans Project (MVP), [47], CANPATH [48]) biobanks. Leveraging these diverse cohorts can improve variant discovery [49,50].…”

Section: Applicationsmentioning

confidence: 99%

Topological stratification of continuous genetic variation in large biobanks

Diaz-Papkovich

Zabad

Ben-Eghan

et al. 2023

Preprint

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Biobanks now contain genetic data from millions of individuals. Dimensionality reduction, visualization and stratification are standard when exploring data at these scales; while efficient and tractable methods exist for the first two, stratification remains challenging because of uncertainty about sources of population structure. In practice, stratification is commonly performed by drawing shapes around dimensionally reduced data or assuming populations have a "type" genome. We propose a method of stratifying data with topological analysis that is fast, easy to implement, and integrates with existing pipelines. The approach is robust to the presence of sub-populations of varying sizes and wide ranges of population structure patterns. We demonstrate its effectiveness on genotypes from three biobanks and illustrate how topological genetic strata can help us understand structure within biobanks, evaluate distributions of genotypic and phenotypic data, examine polygenic score transferability, identify potential influential alleles, and perform quality control.

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“…ATLAS is a diverse biobank that includes patients from a variety of genetic ancestries that live across the greater Los Angeles region. 59 Registered ATLAS researchers can access deidentified electronic health record data for patients, consisting of outpatient and inpatient encounters, including information on diagnoses, procedure orders, laboratory orders, and prescription orders. As of 2022, there were approximately 50,000 participants enrolled in ATLAS.…”

Section: Electronic Medical Record Validation Cohortmentioning

confidence: 99%

Cell type deconvolution of bulk blood RNA-Seq to reveal biological insights of neuropsychiatric disorders

Boltz

Schwarz

Bot

et al. 2023

Preprint

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Genome-wide association studies (GWAS) have uncovered susceptibility loci associated with psychiatric disorders like bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome with unknown causal mechanisms of the link between genetic variation and disease risk. Expression quantitative trait loci (eQTL) analysis of bulk tissue is a common approach to decipher underlying mechanisms, though this can obscure cell-type specific signals thus masking trait-relevant mechanisms. While single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell type proportions and cell type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-Seq from 1,730 samples derived from whole blood in a cohort ascertained for individuals with BP and SCZ this study estimated cell type proportions and their relation with disease status and medication. We found between 2,875 and 4,629 eGenes for each cell type, including 1,211 eGenes that are not found using bulk expression alone. We performed a colocalization test between cell type eQTLs and various traits and identified hundreds of associations between cell type eQTLs and GWAS loci that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on cell type expression regulation and found examples of genes that are differentially regulated dependent on lithium use. Our study suggests that computational methods can be applied to large bulk RNA-Seq datasets of non-brain tissue to identify disease-relevant, cell type specific biology of psychiatric disorders and psychiatric medication.

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Health care utilization of fine-scale identity by descent clusters in a Los Angeles biobank

Cited by 3 publications

References 113 publications

Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative

Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative

Topological stratification of continuous genetic variation in large biobanks

Cell type deconvolution of bulk blood RNA-Seq to reveal biological insights of neuropsychiatric disorders

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