. 2023 Aug;10(2):e002382.

doi: 10.1136/openhrt-2023-002382.

Ancestral diversity in lipoprotein(a) studies helps address evidence gaps

Moa P Lee¹, Sofia F Dimos¹, Laura M Raffield², Zhe Wang³, Anna F Ballou¹, Carolina G Downie¹, Christopher H Arehart⁴, Adolfo Correa⁵, Paul S de Vries⁶, Zhaohui Du⁷, Christopher R Gignoux⁴, Penny Gordon-Larsen⁸, Xiuqing Guo⁹, Jeffrey Haessler⁷, Annie Green Howard¹⁰, Yao Hu⁷, Helina Kassahun¹¹, Shia T Kent¹², J Antonio G Lopez¹¹, Keri L Monda¹², Kari E North¹, Ulrike Peters⁷, Michael H Preuss³, Stephen S Rich¹³, Shannon L Rhodes¹², Jie Yao⁹, Rina Yarosh¹, Michael Y Tsai¹⁴, Jerome I Rotter⁹, Charles L Kooperberg⁷, Ruth J F Loos^{3

15}, Christie Ballantyne¹⁶, Christy L Avery^#¹⁷, Mariaelisa Graff^#¹

Affiliations

¹ Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
² Department of Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
³ The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
⁴ Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
⁵ Department of Population Health Science, The University of Mississippi Medical Center, Jackson, Mississippi, USA.
⁶ Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
⁷ Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
⁸ Department of Nutrition, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
⁹ Department of Pediatrics, UCLA Medical Center, Los Angeles, California, USA.
¹⁰ Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
¹¹ Global Development, Amgen Inc, Thousand Oaks, California, USA.
¹² Center for Observational Research, Amgen Inc, Thousand Oaks, California, USA.
¹³ University of Virginia School of Medicine, Charlottesville, Virginia, USA.
¹⁴ Department of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, Minnesota, USA.
¹⁵ Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Kobenhavn, Denmark.
¹⁶ Department of Medicine, Section of Cardiology, Baylor College of Medicine, Houston, Texas, USA.
¹⁷ Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA christy_avery@unc.edu.

^# Contributed equally.

PMID: 37648373
PMCID: PMC10471864
DOI: 10.1136/openhrt-2023-002382

Ancestral diversity in lipoprotein(a) studies helps address evidence gaps

Moa P Lee et al. Open Heart. 2023 Aug.

. 2023 Aug;10(2):e002382.

doi: 10.1136/openhrt-2023-002382.

Authors

Affiliations

¹ Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
² Department of Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
³ The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
⁴ Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
⁵ Department of Population Health Science, The University of Mississippi Medical Center, Jackson, Mississippi, USA.
⁶ Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
⁷ Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
⁸ Department of Nutrition, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
⁹ Department of Pediatrics, UCLA Medical Center, Los Angeles, California, USA.
¹⁰ Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
¹¹ Global Development, Amgen Inc, Thousand Oaks, California, USA.
¹² Center for Observational Research, Amgen Inc, Thousand Oaks, California, USA.
¹³ University of Virginia School of Medicine, Charlottesville, Virginia, USA.
¹⁴ Department of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, Minnesota, USA.
¹⁵ Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Kobenhavn, Denmark.
¹⁶ Department of Medicine, Section of Cardiology, Baylor College of Medicine, Houston, Texas, USA.
¹⁷ Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA christy_avery@unc.edu.

^# Contributed equally.

PMID: 37648373
PMCID: PMC10471864
DOI: 10.1136/openhrt-2023-002382

Abstract

Introduction: The independent and causal cardiovascular disease risk factor lipoprotein(a) (Lp(a)) is elevated in >1.5 billion individuals worldwide, but studies have prioritised European populations.

Methods: Here, we examined how ancestrally diverse studies could clarify Lp(a)'s genetic architecture, inform efforts examining application of Lp(a) polygenic risk scores (PRS), enable causal inference and identify unexpected Lp(a) phenotypic effects using data from African (n=25 208), East Asian (n=2895), European (n=362 558), South Asian (n=8192) and Hispanic/Latino (n=8946) populations.

Results: Fourteen genome-wide significant loci with numerous population specific signals of large effect were identified that enabled construction of Lp(a) PRS of moderate (R²=15% in East Asians) to high (R²=50% in Europeans) accuracy. For all populations, PRS showed promise as a 'rule out' for elevated Lp(a) because certainty of assignment to the low-risk threshold was high (88.0%-99.9%) across PRS thresholds (80th-99th percentile). Causal effects of increased Lp(a) with increased glycated haemoglobin were estimated for Europeans (p value =1.4×10^-6), although inverse effects in Africans and East Asians suggested the potential for heterogeneous causal effects. Finally, Hispanic/Latinos were the only population in which known associations with coronary atherosclerosis and ischaemic heart disease were identified in external testing of Lp(a) PRS phenotypic effects.

Conclusions: Our results emphasise the merits of prioritising ancestral diversity when addressing Lp(a) evidence gaps.

Keywords: biomarkers; epidemiology; genetic association studies; genome-wide association study.

PubMed Disclaimer

Conflict of interest statement

Competing interests: None declared.

Figures

**Figure 1**
Distributions of lipoprotein(a) by ancestry in n=3 57 096 UK Biobank participants at study baseline.

**Figure 2**
Genome wide-significant (p<5×10⁻⁹) loci discovered in ancestry-specific lipoprotein(a) genome-wide association studies of African (n=19 333), East Asian (n=2895), European (n=354 843) and South Asian (n=8192) Population Architecture through Genomics and Environment study and UK Biobank participants.

**Figure 3**
Performance of lipoprotein(a) polygenic risk scores (PRS) by methods across study populations in n=385 263 participants of African (n=19 333), East Asian (n=2895), European (n=3 54 843) and South Asian (n=8192) ancestry from the Population Architecture through Genomics and Environment study and UK Biobank.

See this image and copyright information in PMC

References

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Ancestral diversity in lipoprotein(a) studies helps address evidence gaps

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Ancestral diversity in lipoprotein(a) studies helps address evidence gaps

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