South Asian Patient Population Genetics Reveal Strong Founder Effects and High Rates of Homozygosity – New Resources for Precision Medicine

Wall, Jeff; Sathirapongsasuti, J. Fah; Gupta, Ravi; Barik, Anamitra; Kumar, Rajesh; Rasheed, Awais; Radha, Venkatesan; Belsare, Saurabh; Menon, Ramesh; Phalke, Sameer; Mittal, Anuradha; Fang, John; Tanneeru, Deepak; Deshmukh, Manjari; Bassi, Akshi; Robinson, Jacqueline; Chaudhary, Ruchi; Asar, Zameer-ul; Saleem, Imran; Ishtiaq, Unzila; Fatima, Areej; Sheikh, Saqib Shafi; Hameed, Shahid; Ishaq, Mohammad; Rasheed, Syed Zahed; Memon, Fazal-ur-Rehman; Jalal, Anjum; Abbas, Shahid; Frossard, Philippe; Fuchsberger, Christian; Forer, Lukas; Schoenherr, Sebastian; Bei, Qixin; Bhangale, Tushar; Tom, Jennifer; Gadde, Santosh Gopi Krishna; Priya, B V; Naik, Naveen Kumar; Wang, Minxian; Kwok, Pui‐Yan; Khera, Amit V.; Lakshmi, B. R.; Butterworth, Adam S.; Chowdhury, Rajiv; Danesh, John; Angelantonio, Emanuele Di; Naheed, Aliya; Seshagiri, Somasekar; Kathiresan, Sekar; Ghosh, Arkasubhra; Mohan, Viswanathan; Chowdhury, Abhijit; Saleheen, Danish; Stawiski, Eric; Peterson, Andrew S.

doi:10.2139/ssrn.3728138

Cited by 3 publications

(2 citation statements)

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“…62 We and others have recently started to assess the relationship of a polygenic predictor of ASCVD in South Asian individuals and to establish larger reference populations that may identify common or rare genetic factors distinct to South Asian individuals. 63–66…”

Section: Discussionmentioning

confidence: 99%

Quantifying and Understanding the Higher Risk of Atherosclerotic Cardiovascular Disease Among South Asian Individuals

Patel

Wang

Kartoun³

et al. 2021

Circulation

107

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Background: Individuals of South Asian ancestry represent 23% of the global population, corresponding to 1.8 billion people, and have substantially higher risk of atherosclerotic cardiovascular disease compared with most other ethnicities. US practice guidelines now recognize South Asian ancestry as an important risk-enhancing factor. The magnitude of enhanced risk within the context of contemporary clinical care, the extent to which it is captured by existing risk estimators, and its potential mechanisms warrant additional study. Methods: Within the UK Biobank prospective cohort study, 8124 middle-aged participants of South Asian ancestry and 449 349 participants of European ancestry who were free of atherosclerotic cardiovascular disease at the time of enrollment were examined. The relationship of ancestry to risk of incident atherosclerotic cardiovascular disease—defined as myocardial infarction, coronary revascularization, or ischemic stroke—was assessed with Cox proportional hazards regression, along with examination of a broad range of clinical, anthropometric, and lifestyle mediators. Results: The mean age at study enrollment was 57 years, and 202 405 (44%) were male. Over a median follow-up of 11 years, 554 of 8124 (6.8%) individuals of South Asian ancestry experienced an atherosclerotic cardiovascular disease event compared with 19 756 of 449 349 (4.4%) individuals of European ancestry, corresponding to an adjusted hazard ratio of 2.03 (95% CI, 1.86–2.22; P <0.001). This higher relative risk was largely consistent across a range of age, sex, and clinical subgroups. Despite the >2-fold higher observed risk, the predicted 10-year risk of cardiovascular disease according to the American Heart Association/American College of Cardiology Pooled Cohort equations and QRISK3 equations was nearly identical for individuals of South Asian and European ancestry. Adjustment for a broad range of clinical, anthropometric, and lifestyle risk factors led to only modest attenuation of the observed hazard ratio to 1.45 (95% CI, 1.28–1.65, P <0.001). Assessment of variance explained by 18 candidate risk factors suggested greater importance of hypertension, diabetes, and central adiposity in South Asian individuals. Conclusions: Within a large prospective study, South Asian individuals had substantially higher risk of atherosclerotic cardiovascular disease compared with individuals of European ancestry, and this risk was not captured by the Pooled Cohort Equations.

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Section: Discussionmentioning

confidence: 99%

Quantifying and Understanding the Higher Risk of Atherosclerotic Cardiovascular Disease Among South Asian Individuals

Patel

Wang

Kartoun³

et al. 2021

Circulation

107

View full text Add to dashboard Cite

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“…For example, many marriages might occur between "cousins" who are actually quite distantly related. Alternatively, in many regions of the world, cousin marriage co-occurs with endogamy (marriage within defined subgroups such as castes) (Wall et al 2020). Since endogamy can itself lead to excess recessive disease burden (Nakatsuka et al 2017), the additional effect of consanguinity might be smaller.…”

Section: Simulationsmentioning

confidence: 99%

Long Runs of Homozygosity Are Correlated with Marriage Preferences across Global Population Samples

Sahoo¹,

Zaidi*²,

Anagol³

et al. 2021

Human Biology

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Children of consanguineous unions carry long runs of homozygosity (ROH) in their genomes, due to their parents' recent shared ancestry. This increases the burden of recessive disease in populations with high levels of consanguinity and has been heavily studied in some groups. However, there has been little investigation of the broader effect of consanguinity on patterns of genetic variation on a global scale. This study, which collected published genetic data and information about marriage practice from 395 worldwide populations, shows that reported preference for cousin marriage has a detectable association with the distribution of long ROH in this sample, increasing the expected number of ROH longer than 10 cM by a factor of 2.2. Variation in marriage practice and consequent rates of consanguinity are therefore an important aspect of demographic history for the purposes of modeling human genetic variation. However, reported marriage practices explain a relatively small proportion of the variation in ROH distribution, and consequently, population genetic data are only partially informative about cultural preferences.

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Novel genotyping algorithms for rare variants significantly improve the accuracy of Applied Biosystems ™ Axiom ™ array genotyping calls

Man

Woehrmann

Webster

et al. 2021

Preprint

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Objective: To significantly improve the positive predictive value (PPV) and sensitivity of Applied Biosystems™ Axiom™ array variant calling, by means of novel improvement to genotyping algorithms and careful quality control of array probesets. The improvement makes array genotyping more suitable for very rare variants. Design: Retrospective evaluation of UK Biobank array data re-genotyped with improved algorithms for rare variants. Participant: 488,359 people recruited to the UK Biobank with Axiom array genotyping data including 200,630 with exome sequencing data. Main Outcome Measures: A comparison of genotyping calls from array data to genotyping calls on a subset of variants with exome sequencing data. Results: Axiom genotyping [18] performed well, based on comparison to sequencing data, for over 100,000 common variants directly genotyped on the Axiom UK Biobank array and also exome sequenced by the UK Biobank Exome Sequencing Consortium. However, in a comparison to the initial exome sequencing results of the first 50K individuals, Weedon et al. [1] observed that when grouping these variants by the minor allele frequency (MAF) observed in UK Biobank, the concordance with sequencing and resulting positive predictive value (PPV) decreased with the number of heterozygous (Het) array calls per variant. An improved genotyping algorithm, Rare Heterozygous Adjustment (RHA) [16], released mid-2020 for genotyping on Axiom arrays, significantly improves PPV in all MAF ranges for the 50K data as well as when compared to the exome sequencing of 200K individuals, released after Weedon et al. [1] performed their comparison. The RHA algorithm improved PPVs in the 200K data in the lowest three frequency groups [0, 0.001%), [0.001%, 0.005%) and [0.005%, 0.01%) to 83%, 82% and 88%; respectively. PPV was above 95% for higher MAF ranges without algorithm improvement. PPVs are somewhat higher in the 200K dataset, due to a different "truth set" from exome sequencing and because monomorphic exome loci are not included in the joint genotyping calls for the 200K data set, as explained in the methods section. Sensitivity was higher in the 200K data set than in the original 50K data as well, especially for low MAF ranges. This increase is in part due to the larger data set over which sensitivity could be computed and in part due to the different WES algorithms used for the 200K data [7]. Filtering of a relatively small number of non-performing probesets (determined without reference to the exome sequencing data) significantly improved sensitivities for all MAF ranges, resulting in 70%, 88% and 94% respectively in the three lowest MAF ranges and greater than 98% and 99.9% for the two higher MAF ranges ([0.01%, 1%), [1%, 50%]). Conclusions: Improved algorithms for genotyping along with enhanced quality control of array probesets, significantly improve the positive predictive value and the sensitivity of array data, making it suitable for the detection of very rare variants. The probeset filtering methods developed have resulted in better probe designs for arrays and the new genotyping algorithm is part of the standard algorithm for all Axiom arrays since early 2020.

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South Asian Patient Population Genetics Reveal Strong Founder Effects and High Rates of Homozygosity – New Resources for Precision Medicine

Cited by 3 publications

References 0 publications

Quantifying and Understanding the Higher Risk of Atherosclerotic Cardiovascular Disease Among South Asian Individuals

Quantifying and Understanding the Higher Risk of Atherosclerotic Cardiovascular Disease Among South Asian Individuals

Long Runs of Homozygosity Are Correlated with Marriage Preferences across Global Population Samples

Novel genotyping algorithms for rare variants significantly improve the accuracy of Applied Biosystems ™ Axiom ™ array genotyping calls

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