Familial hypercholesterolemia (FH) is a genetic disorder characterized by markedly elevated low-density lipoprotein cholesterol (LDL‐C) from birth that often causes premature coronary heart disease (CHD).1 FH can be diagnosed with established clinical criteria such as the Dutch Lipid Clinic Network (DLCN) criteria with or without genetic testing.1 This study sought to quantify the risks for incident CHD events associated with severe hypercholesterolemia (LDL-C ≥190 mg/dL) with or without an FH genotype.
This analysis used data from six population-based prospective cohort studies: (1) Atherosclerosis Risk in Communities Study; (2) Cardiovascular Risk Development in Young Adults Study; (3) Cardiovascular Health Study; (4) Framingham Heart Study Offspring Cohort; (5) Jackson Heart Study; and (6) Multi-Ethnic Study of Atherosclerosis Study. All study protocols were approved by the Institutional Review Boards at participating institutions and all participants provided written informed consent. The analysis was restricted to 21,426 participants without existing CHD at baseline and who underwent whole-genome sequencing. Because of the sensitive nature of the data collected for this study, requests to access the dataset from qualified researchers trained in human subject confidentiality protocols may be sent to the coordinating center of each study cohort.
Demographic characteristics, LDL-C, and other cardiovascular risk factors were measured using standardized protocols in each study. For individuals reporting use of lipid-lowering therapy at the time of LDL-C measurements, detreated LDL-C values were estimated by applying a 30% increase in LDL-C.2 We analyzed gene sequences of 3 FH genes (low-density lipoprotein receptor [LDLR], apolipoprotein B [APOB], and proprotein convertase subtilisin/kexin type 9 [PCSK9]).3 Variant annotations based on the American College of Medical Genetics and Genomics criteria and reports from the ClinGen and ClinVar expert panels were used to determine a variant’s pathogenicity.
Cox proportional hazards models were used to estimate the associations of LDL-C and FH genotype with incident CHD events. Age was used as the time scale and models were stratified by study cohort and adjusted for race/ethnicity, sex, smoking status, body mass index, high-density lipoprotein cholesterol, systolic blood pressure, diabetes, use of lipid-lowering medications, and use of anti-hypertensive medications.
The mean (SD) age of study participants at the baseline visit was 52.1 (15.5) years, 56.2% were women, and 64.2% self-identified as non-Hispanic White. Of the 21,426 individuals included, 1,334 (6.2%) had severe hypercholesterolemia with detreated LDL-C ≥190 mg/dL at baseline, 63 (0.3%) had an FH mutation, and 30 (0.1%) had both detreated LDL-C ≥190 mg/dL and an FH mutation. Mean (SD) detreated LDL-C levels were 197.0 (58.0) mg/dL among FH mutation carriers vs. 128.5 (38.5) mg/dL among noncarriers.
During a median follow-up of 20 years, there were a total of 3,091 incident CHD events. Compared with individuals with LDL-C <190 mg/dL and no FH mutation, the adjusted hazard ratios for incident CHD were 1.4 (95% CI, 1.2–1.6) for those with LDL-C ≥190 mg/dL alone, 2.8 (95% CI, 1.3–5.9) for those with FH mutation alone, and 4.3 (95% CI, 2.3–7.8) for those with both LDL-C ≥190 mg/dL and an FH mutation (Figure). Sensitivity analysis restricted to 15,409 participants not taking lipid-lowering medication found similar results.
Figure. Adjusted hazard ratios (95% CI) for coronary heart disease (CHD) associated with LDL-C and FH mutation status.
Models were adjusted for race/ethnicity, sex, smoking status, body mass index, high-density lipoprotein cholesterol, systolic blood pressure, diabetes, use of lipid-lowering medications, and use of anti-hypertensive medications, and stratified by study cohort. Crude incidence rates were calculated as event per 1,000 person-years. APOB: apolipoprotein B; FH: familial hypercholesterolemia; LDL-C: low-density lipoprotein cholesterol; LDLR: low-density lipoprotein receptor; PCSK9: proprotein convertase subtilisin/kexin type 9.
Although the diagnosis of FH can be made based on severely high LDL-C alone, the current study demonstrated that assessing for FH based on severely high LDL-C alone may miss a significant number of FH mutation carriers with LDL-C <190 mg/dL, and that these individuals have very high risk of CHD. Several commonly used FH diagnostic criteria (DLCN, Simon Broome, and AHA criteria) include presence of known FH mutation as a key criterion for FH diagnosis, yet genetic testing for FH is rarely utilized in the US, and typically only in individuals already demonstrating severely elevated LDL-C.1 In contrast, genetic testing for FH has been implemented following positive phenotypic screening and as part of cascade screening in routine primary care in the Netherlands, Norway, United Kingdom, Australia, and New Zealand.4 While this analysis found the relative impact of FH mutation on CHD was high, the absolute population health benefit of genetic testing in unselected individuals is likely low given the relatively low prevalence of FH mutation in the general population. Current out-of-pocket cost of FH genetic testing is about $500 or lower.4 As the costs of next-generation sequencing continue to decrease, further research is needed to assess the cost-effectiveness of universal vs. selected genetic testing to determine the optimal FH screening approach.4
Main strength of the study includes the use of data from six landmark prospective cohorts with one of the largest numbers of non-Hispanic black individuals sequenced for FH mutations. This study also has several limitations. Because we studied incident CHD events, participants with preexisting CHD at baseline were excluded. This approach may underestimate the true population prevalence of genetically confirmed FH. Additionally, since detailed lipid-lowering medication information was not available in many participants, for those self-reported lipid-lowering medication use, we estimated detreated LDL-C values by conservatively applying a standard 30% increase in LDL-C to account for the effect of a moderate-dose statin.2 This approach does not account for different medication classes and doses, or heterogeneity in adherence and drug dose-response.2,5 However, sensitivity analyses restricting to individuals not taking lipid-lowering medication found consistent results.
In conclusion, presence of FH mutation is associated with a higher risk of CHD, even when LDL-C levels are only modestly elevated. Further practical research is needed to assess the incremental prognostic value and cost-effectiveness of including genetic testing for FH as a complement to standard phenotypic FH screening in usual clinical care.
ACKNOWLEDGEMENT
The authors thank the investigators, staff, and participants of all six cohorts as well as the TOPMed Consortium (https://topmed.nhlbi.nih.gov/topmed-banner-authorship) for their valuable contributions. We also gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. In addition, the authors would like to thank the Cross-Cohort Collaboration Consortium (CCC) for their promotion and support of this multi-cohort effort. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
The Atherosclerosis Risk in Communities (ARIC) study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I). The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the NHLBI in collaboration with the University of Alabama at Birmingham (HHSN268201800005I & HHSN268201800007I), Northwestern University (HHSN268201800003I), University of Minnesota (HHSN268201800006I), and Kaiser Foundation Research Institute (HHSN268201800004I). CARDIA was also partially supported by the Intramural Research Program of the National Institute on Aging (NIA) and an intra‐agency agreement between NIA and NHLBI (AG0005). The Cardiovascular Health Study (CHS) was supported by contracts HHSN268201200036C, HHSN268200800007C, HHSN268201800001C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, 75N92021D00006, and grants U01HL080295, R01HL105756, and U01HL130114 from the NHLBI, with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by R01AG023629 from the NIA. A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The Framingham Heart Study (FHS) was supported by contracts NO1-HC-25195, HHSN268201500001I and 75N92019D00031 from the NHLBI and grant supplement R01 HL092577-06S1. The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute on Minority Health and Health Disparities (NIMHD). The authors also wish to thank the staffs and participants of the JHS. The MESA projects are conducted and supported by the NHLBI in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1TR001881, DK063491, and R01HL105756. Phenotype harmonization, data management, sample-identity QC, and general study coordination, were provided by the TOPMed Data Coordinating Center (3R01HL-120393-02S1), and TOPMed MESA Multi-Omics (HHSN2682015000031/HSN26800004). A fill list of participating MESA investigators and institutes can be found at http://www.mesa-nhlbi.org. Molecular data for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the NHLBI. Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity QC, and general program coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I).
FUNDING
This work was primarily supported by NIH R01HL141823 (Moran, de Ferranti). Funding support was also provided by grants K08HG010155 and U01HG011719 (Khera) from the National Human Genome Research Institute, and by grants K23HL130627 and R21HL129924 (Oelsner) to support the harmonization of phenotypic data across the TOPMed cohorts.
ROLE OF FUNDER/SPONSOR STATEMENT
The funder/sponsor had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.
DISCLOSURES
The spouse of CJW works at Regeneron Pharmaceuticals. APC previously received research support for investigator-initiated work from Amgen, Inc. BMP serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. CMB receives research support from Abbott Diagnostic, Akcea, Amgen, Arrowhead, Esperion, Ionis, Novartis, Regeneron, Roche Diagnostic, NIH, AHA, ADA, and serves as consultant to Abbott Diagnostics, Althera, Amarin, Amgen, Arrowhead, Astra Zeneca, Denka Seiken*, Esperion, Genentech, Gilead, Illumina, Matinas BioPharma Inc, Merck, New Amsterdam, Novartis, Novo Nordisk, Pfizer, Regeneron, Roche Diagnostic, Sanofi-Synthelabo.
Non-standard Abbreviations and Acronym
- CHD
coronary heart disease
- DLCN
Dutch Lipid Clinic Network
- FH
familial hypercholesterolemia
- LDL-C
low-density lipoprotein cholesterol
- PCSK9
proprotein convertase subtilisin/kexin type 9
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