The Tehran longitudinal family-based cardiometabolic cohort study sheds new light on dyslipidemia transmission patterns.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
27 Feb 2024
27 Feb 2024
Historique:
received:
01
07
2023
accepted:
01
02
2024
medline:
28
2
2024
pubmed:
28
2
2024
entrez:
27
2
2024
Statut:
epublish
Résumé
Dyslipidemia, as a metabolic risk factor, with the strongest and most heritable independent cause of cardiovascular diseases worldwide. We investigated the familial transmission patterns of dyslipidemia through a longitudinal family-based cohort, the Tehran Cardiometabolic Genetic Study (TCGS) in Iran. We enrolled 18,729 individuals (45% were males) aged > 18 years (mean: 38.15 (15.82)) and observed them over five 3-year follow-up periods. We evaluated the serum concentrations of total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the first measurement among longitudinal measures and the average measurements (AM) of the five periods. Heritability analysis was conducted using a mixed-effect framework with likelihood-based and Bayesian approaches. The periodic prevalence and heritability of dyslipidemia were estimated to be 65.7 and 42%, respectively. The likelihood of an individual having at least one dyslipidemic parent reveals an OR = 6.94 (CI 5.28-9.30) compared to those who do not have dyslipidemic parents. The most considerable intraclass correlation of family members was for the same-sex siblings, with ICC ~ 25.5%. For serum concentrations, heritability ranged from 33.64 to 60.95%. Taken together, these findings demonstrate that familial transmission of dyslipidemia in the Tehran population is strong, especially within the same-gender siblings. According to previous reports, the heritability of dyslipidemia in this population is considerably higher than the global average.
Identifiants
pubmed: 38413617
doi: 10.1038/s41598-024-53504-3
pii: 10.1038/s41598-024-53504-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
4739Informations de copyright
© 2024. The Author(s).
Références
Anderson, T. J. et al. 2012 update of the Canadian Cardiovascular Society guidelines for the diagnosis and treatment of dyslipidemia for the prevention of cardiovascular disease in the adult. Can. J. Cardiol. 29(2), 151–167 (2013).
doi: 10.1016/j.cjca.2012.11.032
pubmed: 23351925
Baghbani-Oskouei, A., Tohidi, M., Asgari, S., Ramezankhani, A., Azizi, F., & Hadaegh, F. Serum lipids during 20 years in the tehran lipid and glucose study: prevalence, trends and impact on non-communicable diseases. Int. J. Endocrinol. Metab. 16(4 Suppl) (2018)
Azizi, F. et al. Serum lipid levels in an Iranian population of children and adolescents: Tehran lipid and glucose study. Eur J Epidemiol. 17(3), 281–288 (2001).
doi: 10.1023/A:1017932212350
pubmed: 11680549
Azizi, F. et al. Determinants of serum HDL-C level in a Tehran urban population: The Tehran Lipid and Glucose Study. Nutr. Metab. Cardiovasc. Dis. 12(2), 80–89 (2002).
pubmed: 12189907
Yusuf, P. S. et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): Case-control study. Lancet. 364(9438), 937–952 (2004).
doi: 10.1016/S0140-6736(04)17018-9
pubmed: 15364185
Rice, T. K. Familial resemblance and heritability. Adv. Genet. 60, 35–49 (2008).
doi: 10.1016/S0065-2660(07)00402-6
pubmed: 18358315
Bayoumi, R. A. et al. Heritability of determinants of the metabolic syndrome among healthy Arabs of the Oman family study. Obesity (Silver Spring). 15(3), 551–556 (2007).
doi: 10.1038/oby.2007.555
pubmed: 17372303
Stirnadel, H. et al. Genetic and phenotypic architecture of metabolic syndrome-associated components in dyslipidemic and normolipidemic subjects: The GEMS Study. Atherosclerosis 197(2), 868–876 (2008).
doi: 10.1016/j.atherosclerosis.2007.07.038
pubmed: 17888929
Browning, S. R. & Browning, B. L. Identity-by-descent-based heritability analysis in the Northern Finland Birth Cohort. Hum. Genet. 132(2), 129–138 (2013).
doi: 10.1007/s00439-012-1230-y
pubmed: 23052944
Bellia, A. et al. “The Linosa Study”: epidemiological and heritability data of the metabolic syndrome in a Caucasian genetic isolate. Nutr. Metab. Cardiovasc. Dis. 19(7), 455–461 (2009).
doi: 10.1016/j.numecd.2008.11.002
pubmed: 19201175
Cadby, G. et al. Heritability of 596 lipid species and genetic correlation with cardiovascular traits in the Busselton Family Heart Study. J. Lipid. Res. 61(4), 537–545 (2020).
doi: 10.1194/jlr.RA119000594
pubmed: 32060071
pmcid: 7112151
Kaess, B. et al. The lipoprotein subfraction profile: Heritability and identification of quantitative trait loci. J. Lipid. Res. 49(4), 715–723 (2008).
doi: 10.1194/jlr.M700338-JLR200
pubmed: 18165655
van Dongen, J., Willemsen, G., Chen, W. M., de Geus, E. J. C. & Boomsma, D. I. Heritability of metabolic syndrome traits in a large population-based sample. J. Lipid. Res. 54(10), 2914–2923 (2013).
doi: 10.1194/jlr.P041673
pubmed: 23918046
pmcid: 3770104
Katzmarzyk, P. T., Pemsse, L., Rao, D. C. & Bouchard, C. Spousal resemblance and risk of 7-year increases in obesity and central adiposity in the Canadian population. Obes. Res. 7(6), 545–551 (1999).
doi: 10.1002/j.1550-8528.1999.tb00712.x
pubmed: 10574512
Stirnadel, H. et al. Genetic and phenotypic architecture of metabolic syndrome-associated components in dyslipidemic and normolipidemic subjects: the GEMS Study. Atherosclerosis. 197(2), 868–876 (2008).
doi: 10.1016/j.atherosclerosis.2007.07.038
pubmed: 17888929
Bossé, Y. et al. Heritability of LDL peak particle diameter in the Quebec Family Study. Genet. Epidemiol. 25(4), 375–381 (2003).
doi: 10.1002/gepi.10272
pubmed: 14639707
Pollin, T. I. et al. A genome-wide scan of serum lipid levels in the Old Order Amish. Atherosclerosis. 173(1), 89–96 (2004).
doi: 10.1016/j.atherosclerosis.2003.11.012
pubmed: 15177127
Kathiresan, S. et al. A genome-wide association study for blood lipid phenotypes in the Framingham Heart Study. BMC Med. Genet. 8(Suppl 1), S17 (2007).
doi: 10.1186/1471-2350-8-S1-S17
pubmed: 17903299
pmcid: 1995614
Kim, Y., Lee, Y., Lee, S., Kim, N. H., Lim, J., Kim, Y.J., et al. On the estimation of heritability with family-based and population-based samples. Biomed. Res. Int. 2015 (2015).
Zarkesh, M. et al. Heritability of the metabolic syndrome and its components in the Tehran Lipid and Glucose Study (TLGS). Genet. Res. (Camb). 94(6), 331–337 (2012).
doi: 10.1017/S001667231200050X
pubmed: 23374242
Akbarzadeh, M. et al. GWAS findings improved genomic prediction accuracy of lipid profile traits: Tehran Cardiometabolic Genetic Study. Sci. Rep. 11(1), 1–9 (2021).
doi: 10.1038/s41598-021-85203-8
Daneshpour, M.S., Akbarzadeh, M., Lanjanian, H., Sedaghati-Khayat, B., Guity, K., Masjoudi, S., et al. Cohort profile update: Tehran cardiometabolic genetic study. Eur. J. Epidemiol. 2023;1–13.
Daneshpour, M. S., Hedayati, M., Sedaghati-Khayat, B., Guity, K., Zarkesh, M., Akbarzadeh, M., et al. Genetic identification for non-communicable disease: Findings from 20 years of the Tehran Lipid and Glucose Study. Int. J. Endocrinol. Metab. 2018;16(4 Suppl).
Azizi, F. et al. Prevention of non-communicable disease in a population in nutrition transition: Tehran Lipid and Glucose Study phase II. Trials. 10, 5 (2009).
doi: 10.1186/1745-6215-10-5
pubmed: 19166627
pmcid: 2656492
Nordestgaard, B. G., Chapman, M. J., Humphries, S. E., Ginsberg, H. N., Masana, L., Descamps, O. S., et al. Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society. Eur Heart J. 2013;34(45).
Marks, D., Thorogood, M., Neil, H. A. W. & Humphries, S. E. A review on the diagnosis, natural history, and treatment of familial hypercholesterolaemia. Atherosclerosis. 168(1), 1–14 (2003).
doi: 10.1016/S0021-9150(02)00330-1
pubmed: 12732381
Risk of fatal coronary heart disease in familial hypercholesterolaemia. Scientific Steering Committee on behalf of the Simon Broome Register Group. BMJ 303(6807), 893 (1991).
Daneshpour, M. S., Akbarzadeh, M., Lanjanian, H., Sedaghati-khayat, B., Guity, K., Masjoudi, S., et al. Cohort profile update: Tehran Cardiometabolic Genetic Study, a path toward precision medicine. 2022 Nov 29 [cited 2022 Dec 12]; https://europepmc.org/article/ppr/ppr577953
Azizi, F., Ghanbarian, A., Momenan, A. A., Hadaegh, F., Mirmiran, P., Hedayati, M., et al. Prevention of non-communicable disease in a population in nutrition transition: Tehran Lipid and Glucose Study phase II. Trials. 10 (2009).
Daneshpour MS, Fallah MS, Sedaghati-Khayat B, Guity K, Khalili D, Hedayati M, et al. Rationale and design of a genetic study on cardiometabolic risk factors: Protocol for the tehran cardiometabolic genetic study (TCGS). JMIR Res. Protoc. 2017;6(2).
Bennett, R. L., French, K. S., Resta, R. G. & Doyle, D. L. Standardized human pedigree nomenclature: Update and assessment of the recommendations of the National Society of Genetic Counselors. J. Genet. Couns. 17(5), 424–433 (2008).
doi: 10.1007/s10897-008-9169-9
pubmed: 18792771
Kolifarhood, G. et al. Heritability of blood pressure traits in diverse populations: A systematic review and meta-analysis. J. Hum. Hypertens. 33(11), 775–785 (2019).
doi: 10.1038/s41371-019-0253-4
pubmed: 31551569
Elston, R. C. & Gray-McGuire, C. A review of the “statistical analysis for genetic epidemiology” (SAGE) software package. Hum. Genomics. 1(6), 456 (2004).
doi: 10.1186/1479-7364-1-6-456
pubmed: 15607000
pmcid: 3500199
Horvath, S. et al. Family-based tests for associating haplotypes with general phenotype data: Application to asthma genetics. Genet Epidemiol. 26(1), 61–69 (2004).
doi: 10.1002/gepi.10295
pubmed: 14691957
Genetic Pedigree Software - Progeny [Internet]. [cited 2022 Dec 7]. https://www.progenygenetics.com/
Chen, Y., Zhang, X., Pan, B., Jin, X., Yao, H., Chen, B., et al. A modified formula for calculating low-density lipoprotein cholesterol values. Lipids Health Dis. 9(1) (2010).
Peloso, G. M. et al. Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks. Am. J. Hum. Genet. 94(2), 223–232 (2014).
doi: 10.1016/j.ajhg.2014.01.009
pubmed: 24507774
pmcid: 3928662
Alberti, K. G. M. M., Zimmet, P. & Shaw, J. The metabolic syndrome—A new worldwide definition. Lancet 366(9491), 1059–1062 (2005).
doi: 10.1016/S0140-6736(05)67402-8
pubmed: 16182882
Alberti, K. G. M. M. et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 120(16), 1640–1645 (2009).
doi: 10.1161/CIRCULATIONAHA.109.192644
pubmed: 19805654
Grundy, S. M. et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 112(17), 2735–2752 (2005).
doi: 10.1161/CIRCULATIONAHA.105.169404
pubmed: 16157765
Sangsawang, T. & Sriwijitkamol, A. Type of dyslipidemia and achievement of the LDL-cholesterol goal in chronic kidney disease patients at the University Hospital. Vasc. Health Risk Manag. 11, 563 (2015).
pubmed: 26604773
pmcid: 4639517
McCaw, Z. R., Lane, J. M., Saxena, R., Redline, S. & Lin, X. Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies. Biometrics. 76(4), 1262–1272 (2020).
doi: 10.1111/biom.13214
pubmed: 31883270
pmcid: 8643141
Stata Bookstore: An Introduction to Survival Analysis Using Stata, Revised Third Edition. [cited 2022 Dec 7]. https://www.stata.com/bookstore/survival-analysis-stata-introduction/
de Campos, G., Vazquez, A. I., Fernando, R., Klimentidis, Y. C. & Sorensen, D. Prediction of complex human traits using the genomic best linear unbiased predictor. PLoS Genet. 9(7), e1003608. https://doi.org/10.1371/journal.pgen.1003608 (2013).
doi: 10.1371/journal.pgen.1003608
pubmed: 23874214
pmcid: 3708840
Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences 7(4), 457–472. https://doi.org/10.1214/ss/1177011136.full (1992).
doi: 10.1214/ss/1177011136.full
Traglia, M. et al. Heritability and demographic analyses in the large isolated population of val borbera suggest advantages in mapping complex traits genes. PLoS One. 4(10), e7554 (2009).
doi: 10.1371/journal.pone.0007554
pubmed: 19847309
pmcid: 2761731
Bucher, K. D. et al. Segregation analysis of low levels of high-density lipoprotein cholesterol in the collaborative Lipid Research Clinics Program Family Study. Am. J. Hum. Genet. 40(6), 489 (1987).
pubmed: 3591798
pmcid: 1684162
Paquette, M., Fantino, M., Bernard, S. & Baass, A. Paternal inheritance predicts earlier cardiovascular event onset in patients with familial hypercholesterolemia. Atherosclerosis. 329, 9–13 (2021).
doi: 10.1016/j.atherosclerosis.2021.06.006
pubmed: 34157652
Jee, S. H., Suh, I., Won, S. Y. & Kim, M. Familial correlation and heritability for cardiovascular risk factors. Yonsei Med. J. 43(2), 160–164 (2002).
doi: 10.3349/ymj.2002.43.2.160
pubmed: 11971209
Naseri, P., Khodakarim, S., Guity, K. & Daneshpour, M. S. Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors. Gene. 659, 118–122 (2018).
doi: 10.1016/j.gene.2018.03.033
pubmed: 29548861
Chien, K. L. et al. Familial aggregation of metabolic syndrome among the Chinese: Report from the Chin-Shan community family study. Diabetes Res. Clin. Pract. 76(3), 418–424 (2007).
doi: 10.1016/j.diabres.2006.09.026
pubmed: 17097184
Feng, Y., Zang, T., Xu, X. & Xu, X. Familial aggregation of metabolic syndrome and its components in a large Chinese population. Obesity. 16(1), 125–129. https://doi.org/10.1038/oby.2007.22 (2008).
doi: 10.1038/oby.2007.22
pubmed: 18223624
Goode, E. L., Cherny, S. S., Christian, J. C., Jarvik, G. P. & de Andrade, M. Heritability of longitudinal measures of body mass index and lipid and lipoprotein levels in aging twins. Twin. Res. Hum. Genet. 10(5), 703–711 (2007).
doi: 10.1375/twin.10.5.703
pubmed: 17903110
di Castelnuovo, A., Quacquaruccio, G., Donati, M. B., de Gaetano, G. & Iacoviello, L. Spousal concordance for major coronary risk factors: A systematic review and meta-analysis. Am. J. Epidemiol. 169(1), 1–8 (2009).
doi: 10.1093/aje/kwn234
pubmed: 18845552
Mehrjoo, Z. et al. Distinct genetic variation and heterogeneity of the Iranian population. PLoS Genet. 15(9), e1008385. https://doi.org/10.1371/journal.pgen.1008385 (2019).
doi: 10.1371/journal.pgen.1008385
pubmed: 31550250
pmcid: 6759149
Xia, C. et al. Pedigree- and SNP-associated genetics and recent environment are the major contributors to anthropometric and cardiometabolic trait variation. PLoS Genet. 12(2), e1005804. https://doi.org/10.1371/journal.pgen.1005804 (2016).
doi: 10.1371/journal.pgen.1005804
pubmed: 26836320
pmcid: 4737500