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. 2023 Feb 1;8(3):258–267. doi: 10.1001/jamacardio.2022.5271

Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease

Jacqueline S Dron 1,2, Aniruddh P Patel 1,2,3,4, Yiyi Zhang 5, Sean J Jurgens 2,6, Dimitri J Maamari 1,2,3, Minxian Wang 7,8, Eric Boerwinkle 9, Alanna C Morrison 9, Paul S de Vries 9, Myriam Fornage 9,10, Lifang Hou 11, Donald M Lloyd-Jones 11, Bruce M Psaty 12,13,14, Russell P Tracy 15,16, Joshua C Bis 12, Ramachandran S Vasan 17,18,19, Daniel Levy 19,20, Nancy Heard-Costa 19,21, Stephen S Rich 22, Xiuqing Guo 23, Kent D Taylor 23, Richard A Gibbs 24, Jerome I Rotter 23, Cristen J Willer 25, Elizabeth C Oelsner 5, Andrew E Moran 5, Gina M Peloso 26, Pradeep Natarajan 2,3,4, Amit V Khera 1,2,3,27,✉
PMCID: PMC9996405  PMID: 36723951

Key Points

Question

What is the prevalence of protein-truncating variants (PTVs) in the apolipoprotein B (APOB) or proprotein convertase subtilisin/kexin type 9 (PCSK9) genes and their association with low-density lipoprotein (LDL) cholesterol levels and coronary heart disease (CHD)?

Findings

In this genetic association study including 19 073 US participants and 190 464 UK participants, a PTV was identified in 0.4% of individuals. Estimated untreated LDL cholesterol concentrations were 32% to 37% lower in PTV carriers vs noncarriers, and PTVs were associated with a 49% reduction in CHD risk.

Meaning

In this study, PTVs in either APOB or PCSK9 were associated with significantly lower exposure to atherogenic LDL cholesterol and risk of CHD.

This genetic association study evaluates the association of protein-truncating variants in APOB and PCSK9 with low-density lipoprotein (LDL) cholesterol levels and coronary heart disease.

Abstract

Importance

Protein-truncating variants (PTVs) in apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are associated with significantly lower low-density lipoprotein (LDL) cholesterol concentrations. The association of these PTVs with coronary heart disease (CHD) warrants further characterization in large, multiracial prospective cohort studies.

Objective

To evaluate the association of PTVs in APOB and PCSK9 with LDL cholesterol concentrations and CHD risk.

Design, Setting, and Participants

This studied included participants from 5 National Heart, Lung, and Blood Institute (NHLBI) studies and the UK Biobank. NHLBI study participants aged 5 to 84 years were recruited between 1971 and 2002 across the US and underwent whole-genome sequencing. UK Biobank participants aged 40 to 69 years were recruited between 2006 and 2010 in the UK and underwent whole-exome sequencing. Data were analyzed from June 2021 to October 2022.

Exposures

PTVs in APOB and PCSK9.

Main Outcomes and Measures

Estimated untreated LDL cholesterol levels and CHD.

Results

Among 19 073 NHLBI participants (10 598 [55.6%] female; mean [SD] age, 52 [17] years), 139 (0.7%) carried an APOB or PCSK9 PTV, which was associated with 49 mg/dL (95% CI, 43-56) lower estimated untreated LDL cholesterol level. Over a median (IQR) follow-up of 21.5 (13.9-29.4) years, incident CHD was observed in 12 of 139 carriers (8.6%) vs 3029 of 18 934 noncarriers (16.0%), corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.28-0.89; P = .02). Among 190 464 UK Biobank participants (104 831 [55.0%] female; mean [SD] age, 57 [8] years), 662 (0.4%) carried a PTV, which was associated with 45 mg/dL (95% CI, 42-47) lower estimated untreated LDL cholesterol level. Estimated CHD risk by age 75 years was 3.7% (95% CI, 2.0-5.3) in carriers vs 7.0% (95% CI, 6.9-7.2) in noncarriers, corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.32-0.81; P = .004).

Conclusions and Relevance

Among 209 537 individuals in this study, 0.4% carried an APOB or PCSK9 PTV that was associated with less exposure to LDL cholesterol and a 49% lower risk of CHD.

Introduction

Low-density lipoprotein (LDL) cholesterol is a leading and modifiable risk factor for coronary heart disease (CHD), a leading cause of global mortality.1 Initial human genetic studies of individuals with increased LDL cholesterol concentrations due to rare inactivating DNA variants in the low-density lipoprotein receptor gene (LDLR) noted accelerated progression of atherosclerosis.1 More recently, genetic analyses have provided 2 additional insights: first, mendelian randomization studies based on common variants indicated that the potential reduction in CHD risk per 38.6-mg/dL (1-mmol/L) reduction in LDL cholesterol was as high as 54%, substantially higher than the 22% reduction observed in short-term clinical trials.1,2,3 Second, a small subset of the population inherits a protective variant associated with reduced LDL cholesterol and CHD risk.4,5

Rare protein-truncating variants (PTVs) in either the apolipoprotein B gene (APOB) or proprotein convertase subtilisin/kexin type 9 gene (PCSK9) are associated with lower LDL cholesterol levels, mediated by decreased hepatic production and accelerated clearance, respectively.6,7,8,9 A seminal observation in 2006 extended the association between PCSK9 PTVs to associated protection from CHD among Black participants of the Atherosclerosis Risk in Communities (ARIC) study, noting an 89% decreased risk.10 Another study also considering PCSK9 PTVs also showed a range of associated CHD risk reductions, ranging from 29% to 61% across 4 studies that included Black individuals.11 More recently, a large case-control study noted an up to 72% reduction (95% CI, 36-88) in CHD among APOB PTV carriers.9 While informative, these and subsequent similar studies have potential limitations based on the focus of only a single gene,9,10,11 restriction to specific variants,10,12 lack of assessment across multiple ancestries,3,10,13 and case-control rather than prospective study designs, which prevents the follow-up and accurate assessment of how variants in APOB and PCSK9 affect cumulative lifetime LDL cholesterol exposure and the associated effect on CHD risk.9,11,13

To confirm and extend these prior studies, this study aggregated and harmonized genetic data and clinical phenotypes of more than 200 000 participants from 5 National Heart, Lung, and Blood Institute (NHLBI) prospective cohorts—the ARIC study, the Cardiovascular Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study (CHS), the Framingham Offspring Study (FHS-O), and the Multi-Ethnic Study of Atherosclerosis (MESA)—and the UK Biobank to better understand the prevalence of rare PTVs in APOB or PCSK9 and their association with LDL cholesterol and CHD.

Methods

Study Populations

Five NHLBI study cohorts were analyzed: ARIC, CARDIA, CHS, FHS-O, and MESA studies.14,15,16,17,18 A description of each cohort and its original design is provided in the eMethods in Supplement 1. Briefly, participants aged 5 to 84 years were recruited between 1971 and 2002 from multiple US enrollment sites. After excluding individuals with prevalent CHD and those with missing LDL cholesterol or genetic data, 19 073 individuals with whole-genome sequence data were analyzed.19 Clinical variables from the NHLBI cohorts were curated and harmonized across studies, as reported previously.14,15,16,17,18,20 This study followed the Strengthening the Reporting of Genetic Association Studies (STREGA) reporting guidelines.

The UK Biobank is a large-scale prospective cohort study that enrolled participants aged 40 and 69 years between 2006 and 2010.21,22 A total of 190 464 participants with whole-exome sequencing and LDL cholesterol measurement at enrollment were analyzed. Definitions of self-reported race are provided in the eMethods in Supplement 1.

Participants provided informed consent for their originating studies. Analyses related to NHLBI and UK Biobank data were performed with application numbers 11628 and 7089, respectively, and approved by the Massachusetts General Brigham Institutional Review Board.

Traits and Clinical End Points of Interest

In both the NHLBI cohorts and the UK Biobank, LDL cholesterol was measured from serum or plasma samples and adjusted to reflect estimated untreated values in participants taking lipid-lowering medications. As described previously, LDL cholesterol measurements were adjusted by dividing values by 0.7, 0.8, 0.85, 0.9, 0.9, or 0.7 when an individual was taking a statin, ezetimibe, bile acid sequestrant, fibrate, niacin, or when the lipid-lowering medication was not specified, respectively (eTable 1 in Supplement 1).23

Incident CHD was assessed within the NHLBI cohorts using a harmonized end point across the 5 studies, as previously described.24 Briefly, in the ARIC, CARDIA, and FHS-O studies, CHD was defined as myocardial infarction or fatal CHD. In MESA, CHD was defined as myocardial infarction, fatal CHD, or resuscitated cardiac arrest. In the CHS, CHD was defined as myocardial infarction, angina, coronary revascularization, or fatal CHD. In the UK Biobank, CHD event ascertainment was based on self-report of myocardial infarction; hospital or procedural records indicating acute myocardial infarction, ischemic heart disease, or coronary revascularization; or death registry data listing myocardial infarction or ischemic heart disease as cause of death, as previously reported.25

Gene Sequencing and Variant Annotation

The Freeze 8 release of the whole-genome sequence data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program and the 200 000 whole-exome sequence data release from the UK Biobank were used in this study.19,26 Details on sequencing methods, variant calling, quality control procedures, and calculation of principal components of ancestry are provided in the eMethods in Supplement 1.

DNA variants in APOB (ENSG00000084674) and PCSK9 (ENSG00000169174) designated as PTVs were identified using gene sequencing data. In addition to the PCSK9 p.Y142X and p.C679X premature stop variants previously characterized,10 the Loss-Of-Function Transcript Effect Estimator (LOFTEE) plugin for the Ensembl Variant Effect Predictor was used to identify additional high-confidence loss-of-function variants in either gene predicted to inactivate its function,27 including substitutions that lead to premature protein truncation due to early introduction of a stop codon (nonsense), insertions or deletions that alter protein translation (frameshift), and substitutions at sites of pre–messenger RNA splicing that alter the splicing process (splice site).

Statistical Analysis

Estimated untreated LDL cholesterol levels between PTV carriers and noncarriers both at time of enrollment and at different age intervals using measurements taken across all clinical visits were compared using adjusted linear regression models. Hazard ratios (HRs) for incident CHD events between carriers and noncarriers were evaluated using adjusted Cox proportional hazard models after excluding individuals with prevalent CHD at enrollment. Unless otherwise indicated, covariates included in regression analyses for NHLBI cohorts were age, sex, the first 5 principal components of ancestry, and an indicator variable for the original study cohort. For the UK Biobank, covariates included in regression analyses were age, sex, and the first 5 principal components of ancestry.

In the NHLBI cohorts, the 10-year risk for CHD between carriers and noncarriers was estimated using adjusted Cox proportional hazard models, stratified by the presence or absence of a traditional risk factor—type 2 diabetes, hypertension, male sex, or smoking—and standardized to the mean of each covariate, excluding original study cohort. In the UK Biobank, age-dependent probabilities for cumulative incidence of CHD in carriers and noncarriers were determined using Cox proportional hazard models adjusted for sex and the first 5 principal components of ancestry. The model was standardized to the mean of each covariate, as described previously.25

Statistical significance was defined as a 2-tailed P value less than .05. All analyses were performed using R version 4.0.5 (The R Foundation). Analyses were conducted from June 2021 to October 2022.

Results

Protective PTVs in NHLBI Study Participants

Among 19 073 participants from the NHLBI study cohorts, 10 598 participants (55.6%) were female, and the mean (SD) age at enrollment was 52 (17) years. A total of 636 participants (3.3%) were Asian, 4554 (23.9%) were Black, 1090 (5.7%) were Hispanic, 12 781 (67.0%) were White, and 8 (<0.1%) were another race (including American Indian and Alaska Native and other races). Self-reported race classifications were generally concordant with genetic ancestry as quantified by principal components (eFigure 1 in Supplement 1). A median (range) of 5 (1-9) study visits were available for study participants. Additional details of demographic and clinical characteristics are provided in eTable 2 in Supplement 1.

A total of 139 participants (0.7%) carried a PTV in either APOB (28 [0.2%]) or PCSK9 (111 [0.6%]); there were no homozygous carriers. Demographic and clinical characteristics are provided in eTable 3 in Supplement 1, and information on each PTV is summarized in eTable 4 in Supplement 1. Mean (SD) estimated untreated LDL cholesterol concentrations were 80 (33) mg/dL in carriers and 128 (38) mg/dL in noncarriers, corresponding to an adjusted difference of 49 mg/dL (95% CI, 43-56; P < .001) (Figure 1A; Table 1); a sensitivity analysis excluding individuals taking lipid-lowering medications revealed nearly identical results. This difference in estimated untreated LDL cholesterol levels between carriers and noncarriers was stable over time (Figure 1B).

Figure 1. Estimated Untreated Low-density Lipoprotein (LDL) Cholesterol Levels in APOB or PCSK9 Protein-Truncating Variant (PTV) Carriers and Noncarriers in National Heart, Lung, and Blood Institute Study Cohorts.

Figure 1.

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A, Box plots show the estimated untreated LDL cholesterol levels for PTV carriers (n = 139) and noncarriers (n = 18 934) at enrollment. The midline indicates the median; the bottom and top of the box indicate the first and third quartiles; and the whiskers indicate 1.5 × IQR. B, Assessed across multiple study visits, age-stratified estimated untreated LDL cholesterol levels are shown with box plots for PTV carriers and noncarriers. This difference was stable over time (P < .05 for each decade). The midline indicates the median; the bottom and top of the box indicate the first and third quartiles; and the whiskers indicate 1.5 × IQR.

aP < .001.

Table 1. Comparison of Characteristics at Enrollment Between Protein-Truncating Variant Carriers and Noncarriers in National Heart, Lung, and Blood Institute Study Cohorts.

Characteristic No. (%)
Carriers Noncarriers
Total, No. 139 18 934
Age, mean (SD), y 53.7 (16.4) 52.1 (16.7)
Sex
Female 74 (53.2) 10 524 (55.6)
Male 65 (46.8) 8410 (44.4)
Race and ethnicitya
Asian 0 636 (3.4)
Black 99 (71.2) 4455 (23.5)
Hispanic 5 (3.6) 1085 (5.7)
American Indian or Alaska Native 0 4 (0.02)
White 34 (24.5) 12 747 (67.3)
Other race 1 (0.7) 7 (0.04)
BMI, mean (SD)b 27.9 (4.9) 26.8 (5.2)
Cholesterol, mean (SD), mg/dL
Total 153.6 (36.2) 200.6 (39.3)
LDL 78.0 (33.2) 125.1 (35.6)
HDL 56.0 (15.1) 52.4 (15.5)
Triglycerides, median (IQR), mg/dL 84.0 (59.5-112.0) 110.0 (75.0-170.0)
Estimated untreated LDL cholesterol, mean (SD), mg/dL 80.3 (33.4) 128.0 (37.9)
Cholesterol medication 1 (0.7) 1070 (5.7)
Type 2 diabetes 8 (5.8) 1198 (6.3)
Hypertension 64 (46.0) 7289 (38.5)
Current smoker 29 (20.9) 4314 (22.8)
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Abbreviations: BMI, body-mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein.

SI conversion factor: To convert cholesterol to mmol/L, multiply by 0.0259; triglycerides to mmol/L, multiply by 0.0113.

a

Race and ethnicity were self-reported. The other race category included those who did not identify with the provided categories of American Indian or Alaska Native, Asian, Black, Hispanic, or White. Definitions of self-reported race are provided in the eMethods in Supplement 1.

b

Calculated as weight in kilograms divided by height in meters squared.

The associated reduction in estimated untreated LDL cholesterol was somewhat more pronounced in carriers of an APOB PTV compared with those with a PCSK9 PTV, with adjusted differences vs noncarriers of 74 mg/dL (95% CI, 60-87) and 43 mg/dL (95% CI, 36-50), respectively. Consistent with prior reports,10 prevalence of PCSK9 PTVs was significantly higher in Black participants (2.1%) than in other races (range, 0.4%-0.9%) (eTable 3 in Supplement 1), but no difference in the prevalence of APOB PTVs according to race classification was observed. Additional information on the associations between carrier status and estimated untreated LDL cholesterol levels stratified by race and gene are shown in eTable 5 and eFigure 3 in Supplement 1, respectively.

Over a median (IQR) follow-up time of 21.5 (13.9-29.4) years, an incident CHD event was observed in 12 of 139 carriers (8.6%) vs 3029 of 18 934 noncarriers (16.0%), corresponding to an adjusted HR of 0.51 (95% CI, 0.29-0.89; P = .02) (Figure 2A); a sensitivity analysis that excluded individuals taking lipid-lowering medications showed nearly identical results, with an adjusted HR of 0.51; (95% CI, 0.29-0.90; P = .02). After additional adjustment for the single estimated untreated LDL cholesterol measurement at enrollment, the association was no longer significant (HR, 0.63; 95% CI, 0.36-1.12; P = .11).28,29

Figure 2. Cumulative Incidence and Estimated 10-Year Coronary Heart Disease (CHD) Risk in Protein-Truncating Variant (PTV) Carriers and Noncarriers in National Heart, Lung, and Blood Institute Study Cohorts.

Figure 2.

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A, Cumulative incidence of CHD stratified by PTV carriers (n = 139) and noncarriers (n = 18 934). B, Each bar shows the estimated 10-year risk of CHD for carriers vs noncarriers, stratified by the presence or absence of traditional risk factors at enrollment, including diabetes, hypertension, male sex, and current smoking. Risk for CHD was estimated using a Cox proportional hazard model, stratified by the presence or absence of a traditional risk factor, and standardized to the mean age at enrollment and the first 5 principal components of ancestry. The 95% CI for each estimate is displayed. HR indicates hazard ratio.

To put the magnitude of the 49% reduced CHD risk associated with carrier status into context, the effect sizes were additionally calculated for traditional risk factors, noting an adjusted HR of 0.47 (95% CI, 0.42-0.52) for absence of diabetes, 0.75 (95% CI, 0.69-0.81) for absence of hypertension, 0.57 (95% CI, 0.52-0.62) for absence of current smoking, and 0.59 (95% CI, 0.55-0.64) for female sex. Joint modeling of each traditional risk factor along with PTV carrier status was used to determine predicted 10-year risk of incident CHD (Figure 2B). Taking hypertension as an example, the estimated 10-year risk was 2.4% (95% CI, 1.0-3.7) for a PTV carrier with hypertension and 2.8% (95% CI, 2.6-3.0) for a noncarrier without hypertension. Similarly, for smoking, the estimated 10-year risk was 2.7% (95% CI, 1.2-4.2) for a PTV carrier who smoked vs 3.0% (95% CI, 2.8-3.3) for a noncarrier who does not smoke.

Modeling Risk Estimates of CHD in the UK Biobank

Among 190 464 UK Biobank participants, 104 831 participants (55.0%) were female, and the mean (SD) age at enrollment was 57 (8) years. A total of 4632 participants were Asian (including 4026 [2.1%] who were South Asian and 606 [0.3%] who were East Asian), 3016 (1.6%) were Black, 178 821 (93.9%) were White, and 3995 (2.1%) self-identified as having a mixed racial background, an unknown background, or did not identify with any of the other provided categories. Self-reported race classifications were generally concordant with genetic ancestry as quantified by principal components (eFigure 2 in Supplement 1). Additional details of demographic and clinical characteristics are provided in eTable 6 in Supplement 1.

A total of 662 participants (0.4%) carried a PTV in either APOB only (276 [0.1%]), PCSK9 only (382 [0.2%]), or both APOB and PCSK9 (4 [0.002%]); there were no homozygous carriers. Demographic and clinical characteristics are summarized in eTable 7 in Supplement 1. Mean (SD) estimated untreated LDL cholesterol concentrations were 100 (37) mg/dL in carriers and 146 (33) mg/dL in noncarriers, corresponding to an adjusted difference of 45 mg/dL (95% CI, 42-47; P < .001) (Table 2). Results for gene-specific estimated untreated LDL cholesterol comparisons are illustrated in eFigure 4 in Supplement 1.

Table 2. Comparison of Characteristics at Enrollment Between Protein-Truncating Variant Carriers and Noncarriers in UK Biobank.

Characteristic No. (%)
Carriers Noncarriers
Total, No. 662 189 802
Age, mean (SD), y 56.4 (8.4) 57.0 (8.1)
Sex
Female 397 (60.0) 104 434 (55.0)
Male 265 (40.0) 85 368 (45.0)
Race and ethnicitya
Black 82 (12.4) 2934 (1.5)
East Asian 3 (0.5) 603 (0.3)
South Asian 18 (2.7) 4008 (2.1)
White 528 (79.8) 178 293 (93.9)
Other race 31 (4.7) 3964 (2.1)
BMI, mean (SD)b 27.7 (5.2) 27.4 (4.8)
Prevalent CHD 4 (0.6) 5158 (2.7)
Cholesterol, mean (SD), mg/dL
Total 173.3 (47.2) 220.6 (44.0)
LDL 97.1 (34.7) 137.8 (33.4)
HDL 59.5 (17.2) 56.3 (14.8)
Triglycerides, median (IQR), mg/dL 93.3 (62.8-148.2) 130.9 (92.4-189.0)
Estimated untreated LDL cholesterol, mean (SD), mg/dL 99.6 (36.7) 145.6 (33.0)
Lipoprotein(a), median (IQR), mg/dL 7.04 (2.79-29.17) 8.17 (3.17-30.96)
Statin 39 (5.9) 29 960 (15.8)
Cholesterol medication 60 (9.1) 36 264 (19.1)
Type 2 diabetes 18 (2.7) 4529 (2.4)
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Abbreviations: BMI, body-mass index; CHD, coronary heart disease; HDL, high-density lipoprotein; LDL, low-density lipoprotein.

SI conversion factor: To convert cholesterol to mmol/L, multiply by 0.0259; triglycerides to mmol/L, multiply by 0.0113.

a

Race and ethnicity were self-reported. The other race category included those with a mixed racial background, those who did not know their racial background, those who did not identify with any of the other provided categories, or those who chose not to answer. Definitions of self-reported race are provided in the eMethods in Supplement 1.

b

Calculated as weight in kilograms divided by height in meters squared.

Similar to what was observed in the NHLBI cohorts, the associated reduction in estimated untreated LDL cholesterol was somewhat more pronounced in carriers of an APOB PTV compared with those with a PCSK9 PTV, with adjusted differences vs noncarriers of 60 mg/dL (95% CI, 56-64) and 34 mg/dL (95% CI, 31-37), respectively, and the prevalence of PCSK9 PTVs was significantly higher in Black participants (2.7%) than in other races (range, 0.2%-0.5%) (eTable 7 in Supplement 1). No difference in the prevalence of APOB PTVs according to race classification was observed. Additional information on the association between carrier status and estimated untreated LDL cholesterol levels stratified by race is shown in eTable 8 in Supplement 1.

An incident CHD event was observed in 18 of 662 PTV carriers (2.7%) vs 10 990 of 189 802 noncarriers (5.8%), corresponding to an adjusted HR of 0.51 (95% CI, 0.32-0.82; P = .004). Age-specific risk estimates for the absolute incidence of CHD were next evaluated using standardized Cox proportional hazard models (Figure 3). The estimated probability of developing CHD by age 55 years was 0.47% (95% CI, 0.25-0.68) in carriers and 0.91% (95% CI, 0.87-0.95) in noncarriers. By age 65 years, the estimated probability of developing CHD was 1.7% (95% CI, 0.9-2.5) in carriers and 3.3% (95% CI, 3.2-3.4) in noncarriers. By age 75 years, the estimated probability of developing CHD was 3.7% (95% CI, 2.0-5.3) in carriers and 7.0% (95% CI, 6.9-7.2) in noncarriers.

Figure 3. Coronary Heart Disease (CHD) Risk Estimates in Protein-Truncating Variant (PTV) Carriers and Noncarriers in the UK Biobank.

Figure 3.

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Each bar shows the estimated risk of CHD by ages 55, 65, and 75 years based on carrier status. Disease risk was estimated for carriers and noncarriers using a Cox proportional hazard model standardized to the mean of the first 5 genetic principal components and prevalence of male sex. The 95% CIs for each estimate is displayed.

Discussion

In this study, rare naturally occurring DNA variants that inactivate APOB or PCSK9 were used to understand the association between the lifelong lowering of estimated untreated LDL cholesterol and CHD risk. Such variants were identified in 0.4% sequenced individuals (801 of 209 537) and were associated with 45 to 49 mg/dL lower estimated untreated LDL cholesterol levels and a 49% reduction in risk of CHD. These results have at least 4 implications.

First, these findings confirm and extend results of a seminal 2006 article that first documented a lower rate of CHD events in those who inherited a PCSK9 PTV in several ways.10 In this original report, 3363 Black participants from the ARIC study were studied, and an up to 89% decrease in CHD risk was observed in PTV carriers; however, this estimate was based on only a single CHD event among carriers, resulting in a 95% CI estimating risk reduction from 19% to 98%. Here, we studied 7570 Black participants across multiple studies with follow-ups of up to 31 years, including 176 PCSK9 PTV carriers, providing considerably increased precision. We further expanded our analysis to 201 967 additional participants of different racial groups, demonstrating race-specific effects on LDL cholesterol and a second genetic mechanism of lower LDL cholesterol, APOB PTVs. Lastly, we provided additional clarity into the likely mechanism of CHD protection by systematically exploring the associations with reduced LDL cholesterol levels in individuals across the age span of 5 to 84 years.

Second, our results based on genetic variants present at the time of birth reinforce the growing recognition that CHD risk reductions are dependent on both duration and extent of LDL cholesterol lowering.3,24,30,31 When considering cumulative exposure to LDL cholesterol expressed in so called mg/dL–years as a primary driver of CHD, one proposed threshold is 5000 mg/dL–years.3,30,31 In the UK Biobank, assuming the estimated untreated LDL cholesterol observed at enrollment is consistent starting from birth, this suggests that individuals who inherit a PTV may reach the 5000 mg/dL–years threshold at age 50 years vs 34 years in noncarriers, possibly leading to a delay in onset of atherosclerosis by as much as 16 years. This idea extends a previous analysis that extrapolated data from common variants in various genes known to have individually modest associated effects on LDL cholesterol level and estimated an up to 54.5% reduction in CHD risk per 39–mg/dL reduction in LDL cholesterol.12 More recently, an analysis of 21 clinical trials of lipid-lowering therapies arrived at a similar conclusion, with relative risk reductions per 39 mg/dL of LDL cholesterol reduction of 12% at year 1 but 23% at year 5 and 29% in year 7.32 This benefit of early initiation of lipid-lowering therapies is likely to be of particular use to patients with familial hypercholesterolemia. In a 20-year follow-up study of patients with familial hypercholesterolemia, initiation of statin therapy at a mean age of 13 years appeared to normalize rates of cardiovascular disease and progression of subclinical atherosclerosis compared with unaffected siblings.33

Third, beyond the traditional approach of identifying genetic variants driving associated risk of disease, emphasis on pathways conferring resistance will likely be of increasing value in informing drug development efforts. Taking APOB as an example, PTVs were initially discovered in 1989, based on the study of a family with hypobetalipoproteinemia, a condition characterized by low LDL cholesterol levels.34 Early studies demonstrated the cooccurrence of very low LDL cholesterol levels and hepatic fat accumulation.35,36 Subsequent sequencing efforts confirmed rare APOB PTVs were associated with lower LDL cholesterol levels and CHD risk but increased risk of liver steatosis.9,37,38 These potential benefits and toxicities were demonstrated in clinical trials of mipomersen, which reduced LDL cholesterol levels by up to 47%39 but ultimately was not used widely in clinical practice, owing to an increase in risk of steatosis.40 By contrast, inactivating variants in PCSK9 that were associated with lower LDL cholesterol levels and CHD risk were identified without detectable adverse outcomes.12,41 While the focus of the present analysis was on the association of PTVs in APOB or PCSK9 with LDL cholesterol concentrations, future studies could explore the expanded phenotypic effects of rare variants—especially those that include large populations of Black participants known to inherit PCSK9 PTVs at much higher rates—are of interest.42 Beyond CHD, we and others have identified rare variants associated with protection against several important diseases, including CHD, obesity, and nonalcoholic fatty liver disease.37,43,44,45,46,47,48,49

Fourth, CHD risk reductions reported here for heterozygous carriers of a PTV in APOB or PCSK9 may underestimate what might be achieved with potent pharmacologic suppression. In the current study, preferential use of lipid-lowering therapies in noncarriers according to clinical practice guidelines likely mitigated the difference in rates of CHD observed. Among participants of the NHLBI cohorts, 16.3% of noncarriers reported initiation of a lipid-lowering medication during follow-up compared with only 2.9% of carriers. Moreover, pharmacologic therapies allow for considerably more suppression of a given target compared with the approximately 50% reduction conferred in those who are heterozygous PTV carriers. For example, inclisiran—a recently approved small interfering RNA targeting PCSK9 led to a more than 60% reduction in circulating PCSK9 and 40% to 52% lowering of LDL cholesterol levels.50,51 Recently reported results from preclinical or early-phase clinical trials of other PCSK9-focused therapies suggest suppression of up to 90% may be achievable.52,53,54,55

Limitations

The results of this study should be interpreted within the context of potential limitations. First, while nearly one-third of the NHLBI cohorts consisted of racial and ethnic minority group individuals—with nearly one-quarter of all individuals reported as Black—most participants in the UK Biobank were White. Increasing the number of racial and ethnic minority group participants in future studies will allow for more race-specific estimates of PTV prevalence and effects, providing a more nuanced understanding of the possible difference in associated reductions in CHD risk. Second, because of the independent study design of each cohort, there were differences in recruitment criteria and definition for CHD between groups. Third, individuals in the UK Biobank tend to be healthier than the general population, which may have deflated CHD risk estimations.56 Fourth, the framework used to estimate lifelong LDL cholesterol exposure does not capture the variability in individuals’ LDL cholesterol levels over time, suggesting that the cumulative exposure to untreated LDL cholesterol presented here would be improved with a more comprehensive framework that models variability in LDL cholesterol levels over the lifespan.24,28,29,57,58 Fifth, the present analysis focused on PTVs predicted to fully inactivate the given gene and thus provides a clinically interpretable assessment of the phenotypic consequences of inherited haploinsufficiency. However, additional coding and noncoding variants near APOB and PCSK9 have also been shown to affect LDL cholesterol—albeit with smaller effect sizes.59,60 Future studies integrating both rare PTVs and common variants may be of interest.

Conclusions

By studying clinical and genetic data from large and multiethnic prospective study cohorts, this study demonstrated that PTVs in either APOB or PCSK9 were associated with lower LDL cholesterol levels and a substantial reduction in CHD risk. This inherited reduction in LDL cholesterol provides additional evidence to support recommendations to maintain low LDL cholesterol levels as early as possible, as lifetime cumulative exposure is a primary driver of risk for CHD.

Supplement 1.

eMethods.

eTable 1. Adjustment for LDL cholesterol levels based on different lipid-lowering medications

eTable 2. Comparison of characteristics at enrollment in NHLBI study cohort participants

eTable 3. Comparison of characteristics at enrollment for gene-specific PTV carriers and noncarriers in NHLBI study cohorts

eTable 4. Summary of APOB and PCSK9 PTVs identified in the NHLBI study cohorts and UK Biobank

eTable 5. Impact and association of APOB and PCSK9 PTVs on estimated untreated LDL cholesterol levels across race subsets in the NHLBI study cohorts

eTable 6. Characteristics at enrollment for UK Biobank participants

eTable 7. Comparison of characteristics at enrollment for gene-specific PTV carriers and noncarriers in UK Biobank

eTable 8. Impact and association of APOB and PCSK9 PTVs on estimated untreated LDL cholesterol levels across race subsets in the UK Biobank

eFigure 1. Principal component analysis of participants in the NHLBI study cohorts

eFigure 2. Principal component analysis of participants in the UK Biobank

eFigure 3. Comparison of estimated untreated LDL cholesterol levels between carriers and noncarriers of PTVs in either APOB or PCSK9, stratified by originating NHLBI study cohort

eFigure 4. Comparison of estimated untreated LDL cholesterol levels between carriers and noncarriers of PTVs in either APOB or PCSK9 in the UK Biobank

eReferences.

Click here for additional data file. (936.8KB, pdf)
Supplement 2.

Data Sharing Statement

Click here for additional data file. (16.5KB, pdf)

References

  • 1.Ference BA, Ginsberg HN, Graham I, et al. Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1. evidence from genetic, epidemiologic, and clinical studies. a consensus statement from the European Atherosclerosis Society Consensus Panel. Eur Heart J. 2017;38(32):2459-2472. doi: 10.1093/eurheartj/ehx144 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Silverman MG, Ference BA, Im K, et al. Association between lowering LDL-C and cardiovascular risk reduction among different therapeutic interventions: a systematic review and meta-analysis. JAMA. 2016;316(12):1289-1297. doi: 10.1001/jama.2016.13985 [DOI] [PubMed] [Google Scholar]
  • 3.Ference BA, Bhatt DL, Catapano AL, et al. Association of genetic variants related to combined exposure to lower low-density lipoproteins and lower systolic blood pressure with lifetime risk of cardiovascular disease. JAMA. 2019;322(14):1381-1391. doi: 10.1001/jama.2019.14120 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Defesche JC, Gidding SS, Harada-Shiba M, Hegele RA, Santos RD, Wierzbicki AS. Familial hypercholesterolaemia. Nat Rev Dis Primers. 2017;3:17093. doi: 10.1038/nrdp.2017.93 [DOI] [PubMed] [Google Scholar]
  • 5.Dron JS, Hegele RA. Genetics of lipid and lipoprotein disorders and traits. Curr Genet Med Rep. 2016;4(3):130-141. doi: 10.1007/s40142-016-0097-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Burnett JR, Hooper AJ. Common and rare gene variants affecting plasma LDL cholesterol. Clin Biochem Rev. 2008;29(1):11-26. [PMC free article] [PubMed] [Google Scholar]
  • 7.Burke AC, Dron JS, Hegele RA, Huff MW. PCSK9: regulation and target for drug development for dyslipidemia. Annu Rev Pharmacol Toxicol. 2017;57:223-244. doi: 10.1146/annurev-pharmtox-010716-104944 [DOI] [PubMed] [Google Scholar]
  • 8.Dron JS, Hegele RA. Complexity of mechanisms among human proprotein convertase subtilisin-kexin type 9 variants. Curr Opin Lipidol. 2017;28(2):161-169. doi: 10.1097/MOL.0000000000000386 [DOI] [PubMed] [Google Scholar]
  • 9.Peloso GM, Nomura A, Khera AV, et al. Rare protein-truncating variants in APOB, lower low-density lipoprotein cholesterol, and protection against coronary heart disease. Circ Genom Precis Med. 2019;12(5):e002376. doi: 10.1161/CIRCGEN.118.002376 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Cohen JC, Boerwinkle E, Mosley TH Jr, Hobbs HH. Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. N Engl J Med. 2006;354(12):1264-1272. doi: 10.1056/NEJMoa054013 [DOI] [PubMed] [Google Scholar]
  • 11.Kent ST, Rosenson RS, Avery CL, et al. PCSK9 loss-of-function variants, low-density lipoprotein cholesterol, and risk of coronary heart disease and stroke: data from 9 studies of Blacks and Whites. Circ Cardiovasc Genet. 2017;10(4):e001632. doi: 10.1161/CIRCGENETICS.116.001632 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Ference BA, Yoo W, Alesh I, et al. Effect of long-term exposure to lower low-density lipoprotein cholesterol beginning early in life on the risk of coronary heart disease: a mendelian randomization analysis. J Am Coll Cardiol. 2012;60(25):2631-2639. doi: 10.1016/j.jacc.2012.09.017 [DOI] [PubMed] [Google Scholar]
  • 13.Rao AS, Lindholm D, Rivas MA, Knowles JW, Montgomery SB, Ingelsson E. Large-scale phenome-wide association study of PCSK9 variants demonstrates protection against ischemic stroke. Circ Genom Precis Med. 2018;11(7):e002162. doi: 10.1161/CIRCGEN.118.002162 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Wright JD, Folsom AR, Coresh J, et al. The ARIC (Atherosclerosis Risk In Communities) study: JACC Focus Seminar 3/8. J Am Coll Cardiol. 2021;77(23):2939-2959. doi: 10.1016/j.jacc.2021.04.035 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Friedman GD, Cutter GR, Donahue RP, et al. CARDIA: study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol. 1988;41(11):1105-1116. doi: 10.1016/0895-4356(88)90080-7 [DOI] [PubMed] [Google Scholar]
  • 16.Fried LP, Borhani NO, Enright P, et al. The Cardiovascular Health Study: design and rationale. Ann Epidemiol. 1991;1(3):263-276. doi: 10.1016/1047-2797(91)90005-W [DOI] [PubMed] [Google Scholar]
  • 17.Feinleib M, Kannel WB, Garrison RJ, McNamara PM, Castelli WP. The Framingham Offspring study. design and preliminary data. Prev Med. 1975;4(4):518-525. doi: 10.1016/0091-7435(75)90037-7 [DOI] [PubMed] [Google Scholar]
  • 18.Bild DE, Bluemke DA, Burke GL, et al. Multi-Ethnic Study of Atherosclerosis: objectives and design. Am J Epidemiol. 2002;156(9):871-881. doi: 10.1093/aje/kwf113 [DOI] [PubMed] [Google Scholar]
  • 19.Taliun D, Harris DN, Kessler MD, et al. ; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium . Sequencing of 53,831 diverse genomes from the NHLBI TOPMed program. Nature. 2021;590(7845):290-299. doi: 10.1038/s41586-021-03205-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Oelsner EC, Balte PP, Cassano PA, et al. Harmonization of respiratory data from 9 US population-based cohorts: the NHLBI Pooled Cohorts study. Am J Epidemiol. 2018;187(11):2265-2278. doi: 10.1093/aje/kwy139 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Bycroft C, Freeman C, Petkova D, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562(7726):203-209. doi: 10.1038/s41586-018-0579-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Sudlow C, Gallacher J, Allen N, et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779. doi: 10.1371/journal.pmed.1001779 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Patel AP, Wang M, Fahed AC, et al. Association of rare pathogenic DNA variants for familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and lynch syndrome with disease risk in adults according to family history. JAMA Netw Open. 2020;3(4):e203959. doi: 10.1001/jamanetworkopen.2020.3959 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Zhang Y, Pletcher MJ, Vittinghoff E, et al. Association between cumulative low-density lipoprotein cholesterol exposure during young adulthood and middle age and risk of cardiovascular events. JAMA Cardiol. 2021;6(12):1406-1413. doi: 10.1001/jamacardio.2021.3508 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Fahed AC, Wang M, Homburger JR, et al. Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions. Nat Commun. 2020;11(1):3635. doi: 10.1038/s41467-020-17374-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Szustakowski JD, Balasubramanian S, Kvikstad E, et al. ; UKB-ESC Research Team . Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank. Nat Genet. 2021;53(7):942-948. doi: 10.1038/s41588-021-00885-0 [DOI] [PubMed] [Google Scholar]
  • 27.Karczewski KJ, Francioli LC, Tiao G, et al. ; Genome Aggregation Database Consortium . The mutational constraint spectrum quantified from variation in 141,456 humans. Nature. 2020;581(7809):434-443. doi: 10.1038/s41586-020-2308-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Khera AV, Won HH, Peloso GM, et al. Diagnostic yield and clinical utility of sequencing familial hypercholesterolemia genes in patients with severe hypercholesterolemia. J Am Coll Cardiol. 2016;67(22):2578-2589. doi: 10.1016/j.jacc.2016.03.520 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Clarke SL, Tcheandjieu C, Hilliard AT, et al. ; VA Million Veteran Program . Coronary artery disease risk of familial hypercholesterolemia genetic variants independent of clinically observed longitudinal cholesterol exposure. Circ Genom Precis Med. 2022;15(2):e003501. doi: 10.1161/CIRCGEN.121.003501 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Domanski MJ, Tian X, Wu CO, et al. Time course of LDL cholesterol exposure and cardiovascular disease event risk. J Am Coll Cardiol. 2020;76(13):1507-1516. doi: 10.1016/j.jacc.2020.07.059 [DOI] [PubMed] [Google Scholar]
  • 31.Braunwald E. How to live to 100 before developing clinical coronary artery disease: a suggestion. Eur Heart J. 2022;43(4):249-250. doi: 10.1093/eurheartj/ehab532 [DOI] [PubMed] [Google Scholar]
  • 32.Wang N, Woodward M, Huffman MD, Rodgers A. Compounding benefits of cholesterol-lowering therapy for the reduction of major cardiovascular events: systematic review and meta-analysis. Circ Cardiovasc Qual Outcomes. 2022;15(6):e008552. doi: 10.1161/CIRCOUTCOMES.121.008552 [DOI] [PubMed] [Google Scholar]
  • 33.Luirink IK, Wiegman A, Kusters DM, et al. 20-Year follow-up of statins in children with familial hypercholesterolemia. N Engl J Med. 2019;381(16):1547-1556. doi: 10.1056/NEJMoa1816454 [DOI] [PubMed] [Google Scholar]
  • 34.Krul ES, Kinoshita M, Talmud P, et al. Two distinct truncated apolipoprotein B species in a kindred with hypobetalipoproteinemia. Arteriosclerosis. 1989;9(6):856-868. doi: 10.1161/01.ATV.9.6.856 [DOI] [PubMed] [Google Scholar]
  • 35.Tarugi P, Lonardo A, Ballarini G, et al. Fatty liver in heterozygous hypobetalipoproteinemia caused by a novel truncated form of apolipoprotein B. Gastroenterology. 1996;111(4):1125-1133. doi: 10.1016/S0016-5085(96)70082-3 [DOI] [PubMed] [Google Scholar]
  • 36.Schonfeld G. Familial hypobetalipoproteinemia: a review. J Lipid Res. 2003;44(5):878-883. doi: 10.1194/jlr.R300002-JLR200 [DOI] [PubMed] [Google Scholar]
  • 37.Dewey FE, Gusarova V, O’Dushlaine C, et al. Inactivating variants in ANGPTL4 and risk of coronary artery disease. N Engl J Med. 2016;374(12):1123-1133. doi: 10.1056/NEJMoa1510926 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Haas ME, Pirruccello JP, Friedman SN, et al. Machine learning enables new insights into genetic contributions to liver fat accumulation. Cell Genom. 2021;1(3):100066. doi: 10.1016/j.xgen.2021.100066 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Visser ME, Wagener G, Baker BF, et al. Mipomersen, an apolipoprotein B synthesis inhibitor, lowers low-density lipoprotein cholesterol in high-risk statin-intolerant patients: a randomized, double-blind, placebo-controlled trial. Eur Heart J. 2012;33(9):1142-1149. doi: 10.1093/eurheartj/ehs023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Fogacci F, Ferri N, Toth PP, Ruscica M, Corsini A, Cicero AFG. Efficacy and safety of mipomersen: a systematic review and meta-analysis of randomized clinical trials. Drugs. 2019;79(7):751-766. doi: 10.1007/s40265-019-01114-z [DOI] [PubMed] [Google Scholar]
  • 41.Cohen J, Pertsemlidis A, Kotowski IK, Graham R, Garcia CK, Hobbs HH. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat Genet. 2005;37(2):161-165. doi: 10.1038/ng1509 [DOI] [PubMed] [Google Scholar]
  • 42.Jurgens SJ, Choi SH, Morrill VN, et al. ; Regeneron Genetics Center . Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank. Nat Genet. 2022;54(3):240-250. doi: 10.1038/s41588-021-01011-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.The TG and HDL Working Group of the Exome Sequencing Project, National Heart, Lung, and Blood Institute . Loss-of-function mutations in APOC3, triglycerides, and coronary disease. N Engl J Med. 2014;371(1):22-31. doi: 10.1056/NEJMoa1307095 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Stitziel NO, Khera AV, Wang X, et al. ; PROMIS and Myocardial Infarction Genetics Consortium Investigators . ANGPTL3 deficiency and protection against coronary artery disease. J Am Coll Cardiol. 2017;69(16):2054-2063. doi: 10.1016/j.jacc.2017.02.030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Stitziel NO, Won HH, Morrison AC, et al. ; Myocardial Infarction Genetics Consortium Investigators . Inactivating mutations in NPC1L1 and protection from coronary heart disease. N Engl J Med. 2014;371(22):2072-2082. doi: 10.1056/NEJMoa1405386 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Khera AV, Kathiresan S. Genetics of coronary artery disease: discovery, biology and clinical translation. Nat Rev Genet. 2017;18(6):331-344. doi: 10.1038/nrg.2016.160 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Akbari P, Gilani A, Sosina O, et al. ; Regeneron Genetics Center; DiscovEHR Collaboration . Sequencing of 640,000 exomes identifies GPR75 variants associated with protection from obesity. Science. 2021;373(6550):eabf8683. doi: 10.1126/science.abf8683 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Emdin CA, Khera AV, Chaffin M, et al. Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease. Nat Commun. 2018;9(1):1613. doi: 10.1038/s41467-018-03911-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Emdin CA, Haas ME, Khera AV, et al. ; Million Veteran Program . A missense variant in mitochondrial amidoxime reducing component 1 gene and protection against liver disease. PLoS Genet. 2020;16(4):e1008629. doi: 10.1371/journal.pgen.1008629 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Raal FJ, Kallend D, Ray KK, et al. ; ORION-9 Investigators . Inclisiran for the treatment of heterozygous familial hypercholesterolemia. N Engl J Med. 2020;382(16):1520-1530. doi: 10.1056/NEJMoa1913805 [DOI] [PubMed] [Google Scholar]
  • 51.Ray KK, Wright RS, Kallend D, et al. ; ORION-10 and ORION-11 Investigators . Two phase 3 trials of inclisiran in patients with elevated LDL cholesterol. N Engl J Med. 2020;382(16):1507-1519. doi: 10.1056/NEJMoa1912387 [DOI] [PubMed] [Google Scholar]
  • 52.American Heart Association . Oral PCSK9 inhibitor found to be safe, effective to lower cholesterol, in first human trial. Accessed May 3, 2022. https://newsroom.heart.org/news/oral-pcsk9-inhibitor-found-to-be-safe-effective-to-lower-cholesterol-in-first-human-trial
  • 53.Ionis . Ionis announces positive data for ETESIAN phase 2b study of antisense medicine targeting PCSK9 at 2022. American College of Cardiology Scientific Session. Accessed May 3, 2022. https://ir.ionispharma.com/news-releases/news-release-details/ionis-announces-positive-data-etesian-phase-2b-study-antisense
  • 54.Musunuru K, Chadwick AC, Mizoguchi T, et al. In vivo CRISPR base editing of PCSK9 durably lowers cholesterol in primates. Nature. 2021;593(7859):429-434. doi: 10.1038/s41586-021-03534-y [DOI] [PubMed] [Google Scholar]
  • 55.Lee RG, Mazzola AM, Braun MC, et al. Efficacy and safety of an investigational single-course CRISPR base editing therapy targeting PCSK9 in non-human primate and mouse models. Circulation. Published online October 31, 2022. doi: 10.1161/CIRCULATIONAHA.122.062132 [DOI] [PubMed] [Google Scholar]
  • 56.Fry A, Littlejohns TJ, Sudlow C, et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am J Epidemiol. 2017;186(9):1026-1034. doi: 10.1093/aje/kwx246 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Inaraja V, Thuissard I, Andreu-Vazquez C, Jodar E. Lipid profile changes during the menopausal transition. Menopause. 2020;27(7):780-787. doi: 10.1097/GME.0000000000001532 [DOI] [PubMed] [Google Scholar]
  • 58.Feng L, Nian S, Tong Z, et al. Age-related trends in lipid levels: a large-scale cross-sectional study of the general Chinese population. BMJ Open. 2020;10(3):e034226. doi: 10.1136/bmjopen-2019-034226 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Graham SE, Clarke SL, Wu KH, et al. ; VA Million Veteran Program; Global Lipids Genetics Consortium . The power of genetic diversity in genome-wide association studies of lipids. Nature. 2021;600(7890):675-679. doi: 10.1038/s41586-021-04064-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Liu DJ, Peloso GM, Yu H, et al. ; Charge Diabetes Working Group; EPIC-InterAct Consortium; EPIC-CVD Consortium; GOLD Consortium; VA Million Veteran Program . Exome-wide association study of plasma lipids in >300,000 individuals. Nat Genet. 2017;49(12):1758-1766. doi: 10.1038/ng.3977 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eMethods.

eTable 1. Adjustment for LDL cholesterol levels based on different lipid-lowering medications

eTable 2. Comparison of characteristics at enrollment in NHLBI study cohort participants

eTable 3. Comparison of characteristics at enrollment for gene-specific PTV carriers and noncarriers in NHLBI study cohorts

eTable 4. Summary of APOB and PCSK9 PTVs identified in the NHLBI study cohorts and UK Biobank

eTable 5. Impact and association of APOB and PCSK9 PTVs on estimated untreated LDL cholesterol levels across race subsets in the NHLBI study cohorts

eTable 6. Characteristics at enrollment for UK Biobank participants

eTable 7. Comparison of characteristics at enrollment for gene-specific PTV carriers and noncarriers in UK Biobank

eTable 8. Impact and association of APOB and PCSK9 PTVs on estimated untreated LDL cholesterol levels across race subsets in the UK Biobank

eFigure 1. Principal component analysis of participants in the NHLBI study cohorts

eFigure 2. Principal component analysis of participants in the UK Biobank

eFigure 3. Comparison of estimated untreated LDL cholesterol levels between carriers and noncarriers of PTVs in either APOB or PCSK9, stratified by originating NHLBI study cohort

eFigure 4. Comparison of estimated untreated LDL cholesterol levels between carriers and noncarriers of PTVs in either APOB or PCSK9 in the UK Biobank

eReferences.

Click here for additional data file. (936.8KB, pdf)
Supplement 2.

Data Sharing Statement

Click here for additional data file. (16.5KB, pdf)

Articles from JAMA Cardiology are provided here courtesy of American Medical Association

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