Applicability of Diagnostic Criteria and Prevalence of Familial Dysbetalipoproteinemia in Russia
Open accessPreprint — published as 10.3390/ijms241713159
Abstract
Familial dysbetalipoproteinemia (FD) is a highly atherogenic genetically-based lipid disorder with the underestimated actual prevalence. In the recent years, several biochemical algorithms have been developed to diagnose FD using available laboratory tests. However, there is not enough data on their use in real-world clinical implementation. We studied the applicability of the most accessible biochemical algorithms to diagnose FD in clinical practice. We also investi-gated the prevalence of FD in one of the European regions of Russia based on a population sample. In this study there was detected a high prevalence of FD: 1 in 151. We demonstrated that the diagnostic algorithms of FD including a diagnostic apoB levels require correction, taking into account the characteristics of the distribution of apoB levels in the population. At the same time a triglycerides cutoff ≥1.5 mmol/L may be a useful tool in identifying subjects with FD. We also analyzed the presence and pathogenicity of APOE variants associated with the autosomal dominant FD in a large research sample.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Frameshifts p.Glu63ArgfsTer15 and p.Gly145AlafsTer97 were previously described by our team as likely pathogenic for FD.
“Frameshifts p.Glu63ArgfsTer15 and p.Gly145AlafsTer97 were previously described by our team as likely pathogenic for FD [10].”
From Spectrum and Prevalence of Rare APOE Variants and Their Association with Familial Dysbetalipoproteinemia (2024) · cites this paper as [10]
Section 3.3 identifies both frameshift variants as newly found by the authors and associated with autosomal dominant FD. It classifies p.Gly145AlafsTer97 as likely pathogenic, but p.Glu63ArgfsTer15 as pathogenic—not likely pathogenic. (LLM, conf=0.90)
Experimental — accuracy not yet measuredPreviously developed FD diagnostic algorithms, including apoB level, could not be applied in Russian patients.
“Also, we could not apply previously developed FD diagnostic algorithms, including apoB level, in Russian patients, as we previously described [10].”
From Spectrum and Prevalence of Rare APOE Variants and Their Association with Familial Dysbetalipoproteinemia (2024) · cites this paper as [10]
Section 2.1 reports low specificity for the apoB level and some other criteria in the ESSE-Ivanovo sample, and Section 3.1 concludes that algorithms including apoB require correction for the population’s apoB distribution. But the paper did apply and evaluate the previously developed algorithms, and found some criteria useful; it does not say that none could be applied in Russian patients. Section 4.7 also limits generalization beyond the Ivanovo region. (LLM, conf=0.86)
Experimental — accuracy not yet measuredPrevious studies have shown that a TG cutoff of ≥1.5 mmol/L is optimal for identifying carriers of the ε2ε2 genotype and FD.
“Previous studies have shown that a TG cutoff of ≥1.5 mmol/L is optimal for identifying carriers of the ε2ε2 genotype and FD [10,51].”
From Spectrum and Prevalence of Rare APOE Variants and Their Association with Familial Dysbetalipoproteinemia (2024) · cites this paper as [10]
Section 3.1 reports that a TG cutoff of ≥1.5 mmol/L had sufficiently high sensitivity and specificity for identifying ε2ε2 carriers, and says a previous study found it optimal for identifying people with FD. The paper does not establish that this cutoff is optimal for identifying ε2ε2 carriers; its FD recommendation also pairs the cutoff with the ε2ε2 haplotype. (LLM, conf=0.82)
Experimental — accuracy not yet measuredFamilial dysbetalipoproteinemia (FD) is a highly atherogenic, prevalent, genetically based lipid disorder.
“Familial dysbetalipoproteinemia (FD) is a highly atherogenic, prevalent genetically based lipid disorder.”
From Spectrum and Prevalence of Rare APOE Variants and Their Association with Familial Dysbetalipoproteinemia (2024) · cites this paper as [10]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
No references could be resolved yet.
Research works printed but not linked: 44
- Blum, C.B. Type III hyperlipoproteinemia: Still worth considering? Prog. Cardiovasc. Dis. 2016, 59, 119-124. [CrossRef] · DOI · Paper page
- Marais, A.D.; Solomon, G.A.; Blom, D.J. Dysbetalipoproteinaemia: A mixed hyperlipidaemia of remnant lipoproteins due to mutations in apolipoprotein E. Crit. Rev. Clin. Lab. Sci. 2014, 51, 46-62. [CrossRef] [PubMed] · DOI · Paper page
- Smelt, A.H.M.; De Beer, F. Apolipoprotein E and familial dysbetalipoproteinemia: Clinical, biochemical, and genetic aspects. Semin. Vasc. Med. 2004, 4, 249-257. [CrossRef] · DOI · Paper page
- Mahley, R.W.; Weisgraber, K.H.; Huang, Y. Apolipoprotein E: Structure determines function, from atherosclerosis to Alzheimer's disease to AIDS. J. Lipid. Res. 2009, 50, 183-188. [CrossRef] · DOI · Paper page
- Blokhina, A.V.; Ershova, A.I.; Meshkov, A.N.; Drapkina, O.M. Familial dysbetalipoproteinemia: Highly atherogenic and underdiagnosed disorder. Cardiovasc. Ther. Prev. 2021, 20, 2893. [CrossRef] · DOI
- Koopal, C.; Marais, A.D.; Visseren, F.L.J. Familial dysbetalipoproteinemia: An underdiagnosed lipid disorder. Curr. Opin. Endocrinol. Diabetes Obes. 2017, 24, 133-139. [CrossRef] · DOI · Paper page
- De Beer, F.; Stalenhoef, A.F.H.; Hoogerbrugge, N.; Kastelein, J.J.P.; Gevers Leuven, J.A.; van Duijn, C.M.; Havekes, L.M.; Smelt, A.H. Expression of type III hyperlipoproteinemia in apolipoprotein E2 (Arg158 → Cys) homozygotes is associated with hyperinsulinemia. Arterioscler. Thromb. Vasc. Biol. 2002, 22, 294-299. [CrossRef] [PubMed] · DOI · Paper page
- Heidemann, B.E.; Wolters, F.J.; Kavousi, M.; Gruppen, E.G.; Dullaart, R.P.; Marais, A.D.; Visseren, F.L.; Koopal, C. Adiposity and the development of dyslipidemia in APOE ε2 homozygous subjects: A longitudinal analysis in two population-based cohorts. Atherosclerosis. 2021, 325, 57-62. [CrossRef] · DOI · Paper page
- Corsetti, J.P.; Love, T.M.; Sparks, C.E.; Bakker, S.J.L.; Dullaart, R.P.F. Insulin resistance involvement in prevalence of familial dysbetalipoproteinemia in ε2ε2 subjects by Bayesian network modeling. Clin. Biochem. 2018, 59, 31-36. [CrossRef] · DOI · Paper page
- Koopal, C.; Retterstøl, K.; Sjouke, B.; Hovingh, G.K.; Ros, E.; de Graaf, J.; Dullaart, R.P.; Bertolini, S.; Visseren, F.L. Vascular risk factors, vascular disease, lipids and lipid targets in patients with familial dysbetalipoproteinemia: A European cross-sectional study. Atherosclerosis 2015, 240, 90-97. [CrossRef] · DOI · Paper page
- Basaran, A. Pregnancy-induced hyperlipoproteinemia: Review of the literature. Reprod. Sci. 2009, 16, 431-437. [CrossRef] [PubMed] · DOI
- Chuang, T.Y.; Chao, C.L.; Lin, B.J.; Lu, S.C. Gestational hyperlipidemic pancreatitis caused by type III hyperlipoproteinemia with apolipoprotein E2/E2 homozygote. Pancreas 2009, 38, 716-717. [CrossRef] [PubMed] · DOI
- Koopal, C.; Marais, A.D.; Westerink, J.; Visseren, F.L.J. Autosomal dominant familial dysbetalipoproteinemia: A pathophysiologi- cal framework and practical approach to diagnosis and therapy. J. Clin. Lipidol. 2017, 11, 12-23. [CrossRef] [PubMed] · DOI · Paper page
- Abou, K.Y.; Rabes, J.P.; Boileau, C.; Varret, M. APOE gene variants in primary dyslipidemia. Atherosclerosis 2021, 328, 11-22. [CrossRef] · DOI · Paper page
- Heidemann, B.E.; Koopal, C.; Baass, A.; Defesche, J.C.; Zuurbier, L.; Mulder, M.T.; Roeters van Lennep, J.E.; Riksen, N.P.; Boot, C.; Marais, A.D.; et al. Establishing the relationship between familial dysbetalipoproteinemia and genetic variants in the APOE gene. Clin. Genet. 2022, 102, 253-261. [CrossRef] · DOI · Paper page
- Hopkins, P.N.; Nanjee, M.N.; Wu, L.L.; McGinty, M.G.; Brinton, E.A.; Hunt, S.C.; Anderson, J.L. Altered composition of triglyceride-rich lipoproteins and coronary artery disease in a large case-control study. Atherosclerosis 2009, 207, 559-566. [CrossRef] · DOI · Paper page
- Pallazola, V.A.; Sathiyakumar, V.; Park, J.; Vakil, R.M.; Toth, P.P.; Lazo-Elizondo, M.; Brown, E.; Quispe, R.; Guallar, E.; Banach, M.; et al. Modern prevalence of dysbetalipoproteinemia (Fredrickson-Levy-Lees type III hyperlipoproteinemia). Arch. Med. Sci. 2019, 16, 993-1003. [CrossRef] [PubMed] · DOI · Paper page
- Hopkins, P.N.; Brinton, E.A.; Nanjee, M.N. Hyperlipoproteinemia type 3: The forgotten phenotype. Curr. Atheroscler. Rep. 2014, 16, 440. [CrossRef] · DOI
- Boot, C.S.; Luvai, A.; Neely, R.D.G. The clinical and laboratory investigation of dysbetalipoproteinemia. Crit. Rev. Clin. Lab. Sci. 2020, 57, 458-469. [CrossRef] · DOI
- Sniderman, A.; Couture, P.; De Graaf, J. Diagnosis and treatment of apolipoprotein B dyslipoproteinemias. Nat. Rev. Endocrinol. 2010, 6, 335-346. [CrossRef] · DOI
- Paquette, M.; Bernard, S.; Blank, D.; Paré, G.; Baass, A. A simplified diagnosis algorithm for dysbetalipoproteinemia. J. Clin. Lipidol. 2020, 14, 431-437. [CrossRef] [PubMed] · DOI
- Boot, C.S.; Middling, E.; Allen, J.; Neely, R.D.G. Evaluation of the Non-HDL Cholesterol to Apolipoprotein B Ratio as a Screening Test for Dysbetalipoproteinemia. Clin Chem. 2019, 65, 313-320. [CrossRef] [PubMed] · DOI
- Bachorik, P.S.; Lovejoy, K.L.; Carroll, M.D.; Johnson, C.L. Apolipoprotein B and AI distributions in the United States, 1988-1991: Results of the National Health and Nutrition Examination Survey III (NHANES III). Clini. Chem. 1997, 43, 2364-2378. [CrossRef] · DOI
- Lau, S.E.; Paniagua, S.M.; Zarbafian, S.; Hoffman, U.; Long, M.T.; Hwang, S.J.; Courchesne, P.; Yao, C.; Ma, J.; Larson, M.G.; et al. Cardiovascular Biomarkers of Obesity and Overlap With Cardiometabolic Dysfunction. J. Am. Heart. Assoc. 2021, 10, e020215. [CrossRef] · DOI
- Sniderman, A.D.; Robinson, J.G. ApoB in clinical care: Pro and con. Atherosclerosis 2019, 282, 169-175. [CrossRef] [PubMed] · DOI
- Varghese, B.; Park, J.; Chew, E.; Sajja, A.; Brownstein, A.; Pallazola, V.A.; Sathiyakumar, V.; Jones, S.R.; Sniderman, A.D.; Martin, S.S. Importance of the triglyceride level in identifying patients with a Type III Hyperlipoproteinemia phenotype using the ApoB algorithm. J. Clin Lipidol. 2021, 15, 104-115. [CrossRef] · DOI · Paper page
- Hegele, R.A.; Boren, J.; Ginsberg, H.N.; Arca, M.; Averna, M.; Binder, C.J.; Calabresi, L.; Chapman, M.J.; Cuchel, M.; von Eckardstein, A.; et al. Rare dyslipidaemias, from phenotype to genotype to management: A European Atherosclerosis Society task force consensus statement. Lancet Diabetes Endocrinol. 2020, 8, 50-67. [CrossRef] · DOI · Paper page
- Meshkov, A.N.; Ershova, A.I.; Kiseleva, A.V.; Shalnova, S.A.; Drapkina, O.M.; Boytsov, S.A. The prevalence of heterozygous familial hypercholesterolemia in selected regions of the Russian Federation: The FH-ESSE-RF study. J. Pers. Med. 2021, 11, 464. [CrossRef] · DOI
- Toft-Nielsen, F.; Emanuelsson, F.; Benn, M. Familial Hypercholesterolemia Prevalence Among Ethnicities-Systematic Review and Meta-Analysis. Front. Genet. 2022, 13, 840797. [CrossRef] · DOI
- Mach, F.; Baigent, C.; Catapano, A.L.; Koskinas, K.C.; Casula, M.; Badimon, L.; Chapman, M.J.; De Backer, G.G.; Delgado, V.; Ference, B.A.; et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: Lipid modification to reduce cardiovascular risk: The Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS). Eur. Heart. J. 2020, 41, 111-188. [CrossRef] · DOI · Paper page
- Tokgozoglu, L.; Kayikcioglu, M. Familial hypercholesterolemia: Global burden and approaches. Curr. Cardiol. Rep. 2021, 23, 151. [CrossRef] · DOI
- Feussner, G.; Albanese, M.; Mann, W.A.; Valencia, A.; Schuster, H. Apolipoprotein E2 (Arg-136 → Cys), a variant of apolipoprotein E associated with late-onset dominance of type III hyperlipoproteinaemia. Eur. J. Clin. Invest. 1996, 26, 13-23. [CrossRef] · DOI · Paper page
- Boytsov, S.A.; Drapkina, O.M.; Shlyakhto, E.V.; Konradi, A.O.; Balanova, Y.A.; Zhernakova, Y.V.; Metelskaya, V.A.; Oshchepkova, E.V.; Rotar, O.P.; Shalnova, S.A. Epidemiology of cardiovascular diseases and their risk factors in regions of Russian Federation (ESSE-RF) study. Ten years later. Cardiovasc. Ther. Prev. 2021, 20, 3007. [CrossRef] · DOI
- Ramensky, V.E.; Ershova, A.I.; Zaicenoka, M.; Kiseleva, A.V.; Zharikova, A.A.; Vyatkin, Y.V.; Sotnikova, E.A.; Efimova, I.A.; Divashuk, M.G.; Kurilova, O.V.; et al. Targeted Sequencing of 242 Clinically Important Genes in the Russian Population from the Ivanovo Region. Front. Genet. 2021, 12, 709419. [CrossRef] [PubMed] · DOI
- Baratloo, A.; Hosseini, M.; Negida, A.; El Ashal, G. Part 1: Simple Definition and Calculation of Accuracy, Sensitivity and Specificity. Emerg (Tehran) 2015, 3, 48-49. [PubMed]
- Van der Auwera, G.A.; O'Connor, B.D. Genomics in the Cloud: Using Docker, GATK, and WDL in Terra; O'Reilly Media: Sebastopol, CA, USA, 2020.
- Amberger, J.S.; Bocchini, C.A.; Schiettecatte, F.; Scott, A.F.; Hamosh, A. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res. 2015, 43, 89-98. [CrossRef] [PubMed] · DOI · Paper page
- Karczewski, K.J.; Francioli, L.C.; Tiao, G.; Cummings, B.B.; Alfoldi, J.; Wang, Q.; Collins, R.L.; Laricchia, K.M.; Ganna, A.; Birnbaum, D.P.; et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 2020, 581, 434-443. [CrossRef] [PubMed] · DOI · Paper page
- Landrum, M.J.; Lee, J.M.; Benson, M.; Brown, G.; Chao, C.; Chitipiralla, S.; Gu, B.; Hart, J.; Hoffman, D.; Hoover, J.; et al. ClinVar: Public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 2016, 44, 862-868. [CrossRef] · DOI · Paper page
- Stenson, P.D.; Mort, M.; Ball, E.V.; Chapman, M.; Evans, K.; Azevedo, L.; Hayden, M.; Heywood, S.; Millar, D.S.; Phillips, A.D.; et al. The Human Gene Mutation Database (HGMD®): Optimizing its use in a clinical diagnostic or research setting. Hum. Genet. 2020, 139, 1197-1207. [CrossRef] · DOI
- Fokkema, I.F.; Kroon, M.; López Hernández, J.A.; Asscheman, D.; Lugtenburg, I.; Hoogenboom, J.; den Dunnen, J.T. The LOVD3 platform: Efficient genome-wide sharing of genetic variants. Eur. J. Hum. Genet. 2021, 29, 1796-1803. [CrossRef] · DOI
- Sherry, S.T.; Ward, M.H.; Kholodov, M.; Baker, J.; Phan, L.; Smigielski, E.M.; Sirotkin, K. dbSNP: The NCBI database of genetic variation. Nucleic Acids Res. 2001, 29, 308-311. [CrossRef] [PubMed] · DOI · Paper page
- Richards, S.; Aziz, N.; Bale, S.; Bick, D.; Das, S.; Gastier-Foster, J.; Grody, W.W.; Hegde, M.; Lyon, E.; Spector, E.; et al. Standards and guidelines for 321 the interpretation of sequence variants: A joint consensus recommendation of the American 322 College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 2015, 17, 405-423. [CrossRef] [PubMed] · DOI · Paper page
- Van den Maagdenberg, A.M.; Weng, W.; de Bruijn, I.H.; de Knijff, P.; Funke, H.; Smelt, A.H.; Gevers Leuven, J.A.; van't Hooft, F.M.; Assmann, G.; Hofker, M.H.; et al. Characterization of five new mutants in the carboxyl-terminal domain of human apolipoprotein E: No cosegregation with severe hyperlipidemia. Am. J. Hum. Genet. 1993, 52, 937-946. [PubMed]
Cited by
Sorted by citations
Blokhina, A. V., Ershova, A. I., Kiseleva, A. V., Sotnikova, E. A., Zharikova, A. A., Zaicenoka, M., Vyatkin, Y. V., Ramensky, V. E., Kutsenko, V. A., Garbuzova, E. V., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252312651 · Cited by 8 · see citing works
Self-citation
- Authors
- Blokhina, A. V., Ershova, A. I., Kiseleva, A. V., Sotnikova, E. A., Zharikova, A. A., Zaicenoka, M., Vyatkin, Y. V., Ramensky, V. E., Kutsenko, V. A., Shalnova, S. A., Meshkov, A. N., & Drapkina, O. M.
- Affiliations
- Ministry of Health of the Russian Federation (RU)
- Lomonosov Moscow State University (RU)
- Moscow Institute of Physics and Technology (RU)
- Novosibirsk State University (RU)
- Pirogov Russian National Research Medical University (RU)
- ORCID
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2023-06-02
- Volume
- 24
- Issue
- 17
- Pages
- 13159-13159
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC10487848
- OpenAlex
- W4386141455
- Cited by
- 16
- References
- 0
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 6
- FWCI
- 3.14
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- International Journal of Molecular Sciences (publishedVersion, cc-by)
- Preprints.org (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipid metabolism and disorders
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- familial dysbetalipoproteinemia, diagnostic criteria, prevalence, apolipoprotein B, triglycerides, genetic lipid disorders, atherogenic dyslipidemia, Russia
- MeSH terms
- Apolipoproteins B, Humans, Hyperlipoproteinemia Type III, Pilot Projects, Russia, Triglycerides, Prevalence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review