Population specific reference panels are crucial for the genetic analyses of Native Hawai’ians: an example of the<i>CREBRF</i>locus

Lin, Meng; Caberto, Christian; Wan, Peggy; Li, Yuqing; Lum-Jones, Annette; Tiirikainen, Maarit; Pooler, Loreall; Nakamura, Brooke N.; Sheng, Xin; Porcel, Jacqueline; Lim, Unhee; Setiawan, Veronica Wendy; Marchand, Loı̈c Le; Wilkens, Lynne R.; Haiman, Christopher A.; Cheng, Iona; Chiang, Charleston W. K.

doi:10.1101/789073

Cited by 8 publications

(13 citation statements)

References 44 publications

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“…These values are similar to previous estimates of proportions of genetic ancestry from MEC using ancestry informative markers [44]. The summed PNS ancestry from RFMix is highly concordant with that inferred from ADMIX-TURE [25], and is thus used for phenotype association and covariate adjustments in admixture mapping (below).…”

Section: Global and Local Ancestry Inferencesupporting

confidence: 83%

“…The strong associations between global ancestry and disease risks or related quantitative phenotypes suggest the presence of population-specific variants that could contribute to the increased risk observed in these populations. For example, a recently reported, Polynesian-specific, CREBRF variant discovered in Samoans was strongly associated with the odds of obesity, a finding that we previously replicated in Native Hawaiians [25]. However, we should also stress that an association with global ancestry would also in theory capture any non-genetic cultural or environmental effects that are correlated with ancestry.…”

Section: Plos Geneticsmentioning

confidence: 77%

“…Quality control of MEGA array was previously described [25]. In general, individual and genotype level quality control filters were previously applied as part of PAGE, and additionally we applied the following steps: All variant names were updated to dbSNP v144; duplicated loci and indels were removed; triallelic variants or variants with non-matching alleles to 1000 Genomes Project phase 3 (1KGP) were discarded; loci with unique positions not found in 1KGP were removed from the dataset; alleles were standardized to the positive strand by comparing to 1KGP.…”

Section: Study Populationmentioning

confidence: 99%

“…In order to define individual genetic ancestry, whether locally or globally, we needed a reference panel for the Polynesian component of the Native Hawaiian ancestry. As such a reference panel does not exist, we sought to construct an internal reference panel by identifying MEC-NH individuals with the largest amount of global Polynesian ancestry as previously described [25]. Briefly, we combined all MEC individuals genotyped on the same MEGA array (3,940 Native Hawaiians, 3,465 Japanese, 30 Hispanic/Latinos, 5,325 African Americans) and all individuals from 1000 genomes Project, pruned SNPs with r 2 > 0.1 (using window sizes of 50 SNPs with steps of 10 SNPs across the genome), and partitioned the samples to two groups of related (up to and including 2 nd degree) and unrelated individuals by KING (default threshold used).…”

Section: Global and Local Ancestry Inferencementioning

confidence: 99%

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The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians

et al. 2021

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Epidemiological studies of obesity, Type-2 diabetes (T2D), cardiovascular diseases and several common cancers have revealed an increased risk in Native Hawaiians compared to European- or Asian-Americans living in the Hawaiian islands. However, there remains a gap in our understanding of the genetic factors that affect the health of Native Hawaiians. To fill this gap, we studied the genetic risk factors at both the chromosomal and sub-chromosomal scales using genome-wide SNP array data on ~4,000 Native Hawaiians from the Multiethnic Cohort. We estimated the genomic proportion of Native Hawaiian ancestry (“global ancestry,” which we presumed to be Polynesian in origin), as well as this ancestral component along each chromosome (“local ancestry”) and tested their respective association with binary and quantitative cardiometabolic traits. After attempting to adjust for non-genetic covariates evaluated through questionnaires, we found that per 10% increase in global Polynesian genetic ancestry, there is a respective 8.6%, and 11.0% increase in the odds of being diabetic (P = 1.65×10−4) and having heart failure (P = 2.18×10−4), as well as a 0.059 s.d. increase in BMI (P = 1.04×10−10). When testing the association of local Polynesian ancestry with risk of disease or biomarkers, we identified a chr6 region associated with T2D. This association was driven by an uniquely prevalent variant in Polynesian ancestry individuals. However, we could not replicate this finding in an independent Polynesian cohort from Samoa due to the small sample size of the replication cohort. In conclusion, we showed that Polynesian ancestry, which likely capture both genetic and lifestyle risk factors, is associated with an increased risk of obesity, Type-2 diabetes, and heart failure, and that larger cohorts of Polynesian ancestry individuals will be needed to replicate the putative association on chr6 with T2D.

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Section: Global and Local Ancestry Inferencesupporting

confidence: 83%

Section: Plos Geneticsmentioning

confidence: 77%

Section: Study Populationmentioning

confidence: 99%

Section: Global and Local Ancestry Inferencementioning

confidence: 99%

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The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians

et al. 2021

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“…Users should ensure good LAI performance in their target cohorts. A major determinant of accurate LAI calls is a comprehensive and well-matched reference panel 49,83 . Of relevance is that reference panels are more plentiful for Eurasian populations than for other groups, underscoring the need to expand sequencing efforts in more global populations.…”

Section: Discussionmentioning

confidence: 99%

Tractor: A framework allowing for improved inclusion of admixed individuals in large-scale association studies

Atkinson

Kanai

et al. 2020

Preprint

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38Admixed populations are routinely excluded from medical genomic studies due to concerns over 39 population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the 40 inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with 41 simulations and empirical data focused on admixed African-European individuals. Tractor generates ancestry-42 specific effect size estimates, can boost GWAS power, and improves the resolution of association signals. 43Using a local ancestry aware regression model, we replicate known hits for blood lipids in admixed 44 populations, discover novel hits missed by standard GWAS procedures, and localize signals closer to putative 45 causal variants. 46 47 48 Introduction 49Admixed groups, whose genomes contain more than one ancestral population such as African 50American and Hispanic/Latino individuals, make up more than a third of the US populace, and the population 51 is becoming increasingly mixed over time 1 . Many common, heritable, diseases including prostate cancer 2-5 , 52 asthma 6-9 , and several cardiovascular disorders such as atherosclerosis 10,11 are enriched in admixed 53 populations of the US. However, only a minute proportion of association studies address the genetic 54 architecture of complex traits in such groups 12,13 ; admixed individuals are systematically removed from many 55 studies due to the lack of methods and pipelines to effectively account for their ancestry such that population 56 substructure can infiltrate analyses and bias results [14][15][16][17][18][19][20][21] . Large-scale efforts to collect genetic data alongside 57 medically-relevant phenotypes are beginning to focus more on non-Eurasian ethnic groups that contain higher 58 amounts of admixture 22-27 , motivating the timely development of scalable methods to allow well-calibrated 59 statistical genomic work on these populations. If not addressed, this inability to analyze admixed people will 60 limit the clinical utility of large-scale data-collection efforts for minorities, exacerbating the concerning health 61 disparities that already exist 28-32 . 62In GWAS, the specific concern regarding including admixed participants is obtaining false positive hits due 63 to alleles being at different frequencies across populations. Most studies currently attempt to control for this by 64 using Principle Components (PCs) in a linear or linear mixed model framework. However, PCs capture broader 65 admixture fractions, and individuals' local ancestry makeup may differ between case and control cohorts even 66 if their global fractions are identical. Even including PCs as covariates, then, still leaves open the possibility for 67 false positive associations, as well as absorbing power. 68Studying diverse populations in gene discovery efforts not only reduces disparities but also benefits 69 genetic analysis for individuals of all ancestries. Perhaps the most notable example of this is in multi-ethnic 70 fine-mapping, which ca...

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Multivariate analysis of a missense variant in CREBRF reveals associations with measures of adiposity in people of Polynesian ancestries

Zhang

Heinsberg

Krishnan

et al. 2022

Genetic Epidemiology

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The minor allele of rs373863828, a missense variant in CREB3 Regulatory Factor, is associated with several cardiometabolic phenotypes in Polynesian peoples. To better understand the variant, we tested the association of rs373863828 with a panel of correlated phenotypes (body mass index [BMI], weight, height, HDL cholesterol, triglycerides, and total cholesterol) using multivariate Bayesian association and network analyses in a Samoa cohort (n = 1632), Aotearoa New Zealand cohort (n = 1419), and combined cohort (n = 2976). An expanded set of phenotypes (adding estimated fat and fat‐free mass, abdominal circumference, hip circumference, and abdominal‐hip ratio) was tested in the Samoa cohort (n = 1496). In the Samoa cohort, we observed significant associations (log10 Bayes Factor [BF] ≥ 5.0) between rs373863828 and the overall phenotype panel (8.81), weight (8.30), and BMI (6.42). In the Aotearoa New Zealand cohort, we observed suggestive associations (1.5 < log10BF < 5) between rs373863828 and the overall phenotype panel (4.60), weight (3.27), and BMI (1.80). In the combined cohort, we observed concordant signals with larger log10BFs. In the Samoa‐specific expanded phenotype analyses, we also observed significant associations between rs373863828 and fat mass (5.65), abdominal circumference (5.34), and hip circumference (5.09). Bayesian networks provided evidence for a direct association of rs373863828 with weight and indirect associations with height and BMI.

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Population specific reference panels are crucial for the genetic analyses of Native Hawai’ians: an example of theCREBRFlocus

Cited by 8 publications

References 44 publications

The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians

The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians

Tractor: A framework allowing for improved inclusion of admixed individuals in large-scale association studies

Multivariate analysis of a missense variant in CREBRF reveals associations with measures of adiposity in people of Polynesian ancestries

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