Evidence map›Paper›PMID 38076954›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Insights into Ancestral Diversity in Parkinsons Disease Risk: A Comparative Assessment of Polygenic Risk Scores.

Paula Saffie Awad, Mary B Makarious, Inas Elsayed, Arinola Sanyaolu, Peter Wild Crea, Artur F Schumacher Schuh, Kristin S Levine, Dan Vitale, Mathew J Korestky, Jeffrey Kim and 20 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

30 authors.

Paula Saffie AwadORCID 0000-0002-8056-365X
Artur F Schumacher SchuhORCID 0000-0002-8722-0908
Kristin S Levine
Mathew J KorestkyORCID 0000-0003-4341-3991
Thiago Peixoto LealORCID 0000-0002-5829-6452
Maria Teresa PerinanORCID 0000-0001-7412-7440
Sumit Dey
Armando Reyes-PalomaresORCID 0000-0002-0289-6889
Noela Rodriguez-LosadaORCID 0000-0003-3629-4883
Lucy Norcliffe-KaufmannORCID 0000-0003-0702-1333
23andMe Research Team
Njideka OkubadejoORCID 0000-0003-2975-8803
Mike Nalls
Cornelis BlauwendraatORCID 0000-0001-9358-8111
Sara Bandres CigaORCID 0000-0003-0056-1361
Global Parkinsons Genetics Program (GP2)

Funding

Harmonized Data-Derived Resources for the Alzheimer's Disease and Related Dementias CommunityZIAAG000534 · NIA · NATIONAL INSTITUTE ON AGING · PI COOKSON, MARK · 2019 to 2025
$85.1M
Research Education ComponentP30AG019610 · NIA · SUN HEALTH RESEARCH INSTITUTE · PI GONZALEZ HERNANDEZ, GRACIELA · 2001 to 2020
$32.5M
Research Education ComponentP30AG072980 · NIA · BANNER HEALTH · PI HEATHER Allyson BIMONTE-NELSON · 2021 to 2026
$24.9M
National Brain and Tissue Resource for Parkinson's Disease and Related DisordersU24NS072026 · NINDS · BANNER SUN HEALTH RESEARCH INSTITUTE · PI BEACH, THOMAS G · 2011 to 2015
$7.8M
Modeling the impact of Women's Specific Health Factors in PD outcomes in LatinasR01NS112499 · NINDS · CLEVELAND CLINIC LERNER COM-CWRU · PI FERNANDEZ MATA, IGNACIO · 2020 to 2024
$3.3M
Intramural NIH HHS ZIA AG000534NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG072980NINDS NIH HHS R01 NS112499NINDS NIH HHS U24 NS072026
6 · The paper itself

Abstract

Objectives To evaluate and compare different polygenic risk score (PRS) models in predicting Parkinsons disease (PD) across diverse ancestries, focusing on identifying the most suitable approach for each population and potentially contributing to equitable advancements in precision medicine. Methods We constructed a total of 105 PRS across individual level data from seven diverse ancestries. First, a cross-ancestry conventional PRS comparison was implemented by utilizing the 90 known European risk loci with weighted effects from four independent summary statistics including European, East Asian, Latino/Admixed American, and African/Admixed. These models were adjusted by sex, age, and principal components (28 PRS) and by sex, age, and percentage of admixture (28 PRS) for comparison. Secondly, a novel and refined multi-ancestry best-fit PRS approach was then applied across the seven ancestries by leveraging multi-ancestry meta-analyzed summary statistics and using a p-value thresholding approach (49 PRS) to enhance prediction applicability in a global setting. Results European-based PRS models predicted disease status across all ancestries to differing degrees of accuracy. Ashkenazi Jewish had the highest Odds Ratio (OR): 1.96 (95% CI: 1.69-2.25, p < 0.0001) with an AUC (Area Under the Curve) of 68%. Conversely, the East Asian population, despite having fewer predictive variants (84 out of 90), had an OR of 1.37 (95% CI: 1.32-1.42) and an AUC of 62%, illustrating the cross-ancestry transferability of this model. Lower OR alongside broader confidence intervals were observed in other populations, including Africans (OR =1.38, 95% CI: 1.12-1.63, p=0.001). Adjustment by percentage of admixture did not outperform principal components. Multi-ancestry best-fit PRS models improved risk prediction in European, Ashkenazi Jewish, and African ancestries, yet didn't surpass conventional PRS in admixed populations such as Latino/American admixed and African admixed populations. Interpretation The present study represents a novel and comprehensive assessment of PRS performance across seven ancestries in PD, highlighting the inadequacy of a 'one size fits all' approach in genetic risk prediction. We demonstrated that European based PD PRS models are partially transferable to other ancestries and could be improved by a novel best-fit multi-ancestry PRS, especially in non-admixed populations.

Identifiers

PMID38076954
PMCPMC10705647

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.