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Kalıtım Derecesinin Tahmini ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı

Year 2020, Volume: 10 Issue: 2, 252 - 257, 31.05.2020
https://doi.org/10.33631/duzcesbed.679732

Abstract

Popülasyon genetiği, popülasyonlardaki genlerin
davranışları hakkında kantitatif tahminler yapmak için büyük ölçüde
matematiksel modellemeye dayanmaktadır. Bu modeller Mendel’in klasik gen
kalıtım ilkelerine, bir popülasyondaki gen frekansını öngören Hardy-Weinberg
denge yasasına ve Darwin'in doğal seleksiyon teorisine dayanmaktadır. Son
yıllarda, insana ait özellik ve hastalıkların kalıtım derecelerinin (ℎ2) tahmini
ile ilgili genom çapında veriler kullanılarak yapılan çalışmalar oldukça
yaygındır. İkizlerin kullanıldığı çalışmalardan elde edilen sonuçların büyük
bir bölümü, insana ait karmaşık özelliklerin tümünün kalıtsal olduğunu
göstermiştir. Kalıtım derecesi, ya toplam genetik varyasyonun (geniş anlamda
kalıtım derecesi) ya da eklemeli genetik varyasyonun (dar anlamda kalıtım
derecesi) katkısı olarak ölçülür. Özelliklerin ve hastalıkların kalıtım
derecesini tahmin etmek için çeşitli yöntemler önerilmiştir. Bir özelliğin
kalıtım derecesi, bireyler arasındaki genetik çeşitlilikten kaynaklanan
fenotipik varyasyon oranını ifade eder. Karmaşık özelliklerin genetik temeli
hakkında önemli bilgiler sağlar ve bir fenotipin daha spesifik istatistiksel ve
moleküler genetik analizler için uygun bir hedef olup olmadığını gösterir.
Bununla birlikte, kalıtım derecesi bir fenotipin sabit bir özelliği değildir ve
genetik arka plan ile çevresel varyasyondaki popülasyona özgü farklılıklara
göre değişebilir. Bu çalışmanın amacı, kalıtım derecesini tahmin etmek için
yaygın olarak kullanılan üç farklı yöntemi tanıtmaktır.

Supporting Institution

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Project Number

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Thanks

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References

  • 1. Yuan A, He W, Qin G, Li Q. Statistical genetics and its applications in medical studies. Comput Math Method M. 2014; 2014: 712073. doi: 10.1155/2014/712073.
  • 2. Stanton-Geddes J, Yoder JB, Briskine R, Young ND, Tiffin P. Estimating heritability using genomic data. Methods Ecol Evol. 2013, 4(2): 1151–8.
  • 3. Vinkhuyzen AA, Wray NR, Yang J, Goddard ME, Visscher PM. Estimation and partition of heritability in human populations using whole-genome analysis methods. Annu Rev Genet. 2013; 47: 75-95.
  • 4. Croston R, Branch CL, Kozlovsky DY, Dukas R, Pravosudova VV. Heritability and the evolution of cognitive traits. Behav Ecol. 2015; 26 (6): 1447-59.
  • 5. Zaitlen N, Kraft P, Patterson N, Pasaniuc B, Bhatia G, Pollack S, Price AL. Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits. PLoS Genet. 2013; 9(5): e1003520.
  • 6. Rudra P, Shi WJ, Vestal B, Russell PH, Odell A, Dowell RD, et al. Model based heritability scores for high-throughput sequencing data. BMC Bioinformatics. 2017; 18: 143. https://doi.org/10.1186/s12859-017-1539-6.
  • 7. Kruijer W, Boer M, Malosetti M, Flood PJ, Engel B, Kooke R, et al. Marker-based estimation of heritability in immortal populations. Genetics. 2015; 199(2): 379-98.
  • 8. Burt CH, Simons RL. Pulling back the curtain on heritability studies: biosocial criminology in the postgenomic era. Criminology. 2014; 52(2): 223-62.
  • 9. Stansfield WD. Thoery and Problems of Genetics. 3rd ed. New York, USA: Schaum’s Outline Series, McGraw-Hill, Inc.; 1991. p. 222.
  • 10. Tenesa A, Haley CS. The heritability of human disease: estimation, uses and abuses. Nat Rev Genet. 2013; 14(2): 139-49.
  • 11. Weissbrod O, Flint J, Rosset S. Estimating SNP-based heritability and genetic correlation in case-control studies directly and with summary statistics. Am J Hum Genet. 2018; 103(1): 89-99.
  • 12. Bonnet A. Heritability estimation in case-control studies. Electron J Stat. 2018; 12(1): 1662-716.
  • 13. Ge T, Chen C-Y, Neale BM, Sabuncu MR, Smoller JW. Phenome-wide heritability analysis of the UK Biobank. PLoS Genet. 2017; 13(4): e1006711.
  • 14. Polubriaginof FCG, Vanguri R, Quinnies K, Belbin GM, Yahi A, Salmasian H, et al. Disease heritability inferred from familial relationships reported in medical records. Cell. 2018; 173(7): 1692-704.
  • 15. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, et al. Finding the missing heritability of complex diseases. Nature. 2009; 461(7265): 747-53.
  • 16. Speed D, Cai N, UCLEB Consortium, Johnson MR, Nejentsev S, Balding DJ. Reevaluation of SNP heritability in complex human traits. Nat Genet. 2017; 49(7): 986-92.
  • 17. Lee HS, Paik MC, Rundek T, Sacco RL, Dong C, Krischer JP. Heritability estimation using regression models for correlation. J Biom Biostat. 2011; 2(119): 1-17. doi: 10.4172/2155-6180.1000119.
  • 18. Kleunen M, Ritland K. Estimating heritabilities and genetic correlations with marker-based methods: an experimental test in Mimulus guttatus. J Hered. 2005; 96(4): 368-75.
  • 19. Falconer DS. Introduction to Quantitative Genetics. 2nd ed. Essex, England: The Pitman Press; 1981. p. 148-69.
  • 20. Friars GW, Smith PJ. Heritability, correlation and selection response estimates of some traits in fish populations. Atlantic Salmon Federation Technical Report. Canada: Atlantic Salmon Federation; 2010.
  • 21. Lopes MC, Andrew T, Carbonaro F, Spector TD, Hammond CJ. Estimating heritability and shared environmental effects for refractive error in twin and family studies. Invest Ophth Vis Sci. 2009; 50(1): 126-31.
  • 22. Sahu M, Prasuna JG. Twin studies: a unique epidemiological tool. Indian J Community Med. 2016; 41(3): 177-82.
  • 23. Wray NR, Visscher PM. Estimating trait heritability. Nature Education. 2008; 1(1): 1-16.
  • 24. Singh M, Ceccarelli S, Hamblin J. Estimation of heritability from varietal trials data. Theor Appl Genet. 1993; 86(4): 437-41.
  • 25. Heckerman D, Gurdasani D, Kadie C, Pomilla C, Carstensen T, Martin H, et al. Linear mixed model for heritability estimation that explicitly addresses environmental variation. PNAS. 2016; 113(27): 7377-82.
  • 26. Kim Y, Lee Y, Lee S, Kim NH, Lim J, Kim YJ, et al. On the estimation of heritability with family-based and population-based samples. Biomed Res Int. 2015; 2015: Article ID: 671349. https://doi.org/10.1155/2015/671349.
  • 27. Evans LM, Tahmasbi R, Jones M, Vrieze SI, Abecasis GR, Das S, et al. Narrow-sense heritability estimation of complex traits using identity-by-descent information. Heredity. 2018; 121(6): 616-30.

Estimation of Heritability and Inheritance of Some Human Traits and Diseases

Year 2020, Volume: 10 Issue: 2, 252 - 257, 31.05.2020
https://doi.org/10.33631/duzcesbed.679732

Abstract

Population genetics relies heavily on
mathematical modeling to make quantitative predictions about the behavior of
genes in populations. These models are based on Mendel's classical gene
inheritance principles, the Hardy-Weinberg balance law that predicts gene frequency
in a population, and Darwin's theory of natural selection. In recent years,
studies using genome-wide data on the prediction of human traits and disease
inheritance
(ℎ2) are quite
common. The majority of results from studies using twins have shown that all of
the human complex features are inherited. Heredity grade is measured as either
the contribution of total genetic variation (broad sense heredity) or additive
genetic variation (narrow sense heredity). Various methods have been proposed
to estimate the heritability of features and diseases. The heritability of a
feature refers to the rate of phenotypic variation resulting from genetic
variation among individuals. It provides important information about the
genetic basis of complex features and indicates whether a phenotype is a
suitable target for more specific statistical and molecular genetic analysis.
However, the degree of heredity is not a constant feature of a phenotype, and
may vary with population-specific differences in genetic background and
environmental variation. The aim of this study is to introduce three different
methods commonly used to estimate the degree of heredity. 

Project Number

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References

  • 1. Yuan A, He W, Qin G, Li Q. Statistical genetics and its applications in medical studies. Comput Math Method M. 2014; 2014: 712073. doi: 10.1155/2014/712073.
  • 2. Stanton-Geddes J, Yoder JB, Briskine R, Young ND, Tiffin P. Estimating heritability using genomic data. Methods Ecol Evol. 2013, 4(2): 1151–8.
  • 3. Vinkhuyzen AA, Wray NR, Yang J, Goddard ME, Visscher PM. Estimation and partition of heritability in human populations using whole-genome analysis methods. Annu Rev Genet. 2013; 47: 75-95.
  • 4. Croston R, Branch CL, Kozlovsky DY, Dukas R, Pravosudova VV. Heritability and the evolution of cognitive traits. Behav Ecol. 2015; 26 (6): 1447-59.
  • 5. Zaitlen N, Kraft P, Patterson N, Pasaniuc B, Bhatia G, Pollack S, Price AL. Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits. PLoS Genet. 2013; 9(5): e1003520.
  • 6. Rudra P, Shi WJ, Vestal B, Russell PH, Odell A, Dowell RD, et al. Model based heritability scores for high-throughput sequencing data. BMC Bioinformatics. 2017; 18: 143. https://doi.org/10.1186/s12859-017-1539-6.
  • 7. Kruijer W, Boer M, Malosetti M, Flood PJ, Engel B, Kooke R, et al. Marker-based estimation of heritability in immortal populations. Genetics. 2015; 199(2): 379-98.
  • 8. Burt CH, Simons RL. Pulling back the curtain on heritability studies: biosocial criminology in the postgenomic era. Criminology. 2014; 52(2): 223-62.
  • 9. Stansfield WD. Thoery and Problems of Genetics. 3rd ed. New York, USA: Schaum’s Outline Series, McGraw-Hill, Inc.; 1991. p. 222.
  • 10. Tenesa A, Haley CS. The heritability of human disease: estimation, uses and abuses. Nat Rev Genet. 2013; 14(2): 139-49.
  • 11. Weissbrod O, Flint J, Rosset S. Estimating SNP-based heritability and genetic correlation in case-control studies directly and with summary statistics. Am J Hum Genet. 2018; 103(1): 89-99.
  • 12. Bonnet A. Heritability estimation in case-control studies. Electron J Stat. 2018; 12(1): 1662-716.
  • 13. Ge T, Chen C-Y, Neale BM, Sabuncu MR, Smoller JW. Phenome-wide heritability analysis of the UK Biobank. PLoS Genet. 2017; 13(4): e1006711.
  • 14. Polubriaginof FCG, Vanguri R, Quinnies K, Belbin GM, Yahi A, Salmasian H, et al. Disease heritability inferred from familial relationships reported in medical records. Cell. 2018; 173(7): 1692-704.
  • 15. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, et al. Finding the missing heritability of complex diseases. Nature. 2009; 461(7265): 747-53.
  • 16. Speed D, Cai N, UCLEB Consortium, Johnson MR, Nejentsev S, Balding DJ. Reevaluation of SNP heritability in complex human traits. Nat Genet. 2017; 49(7): 986-92.
  • 17. Lee HS, Paik MC, Rundek T, Sacco RL, Dong C, Krischer JP. Heritability estimation using regression models for correlation. J Biom Biostat. 2011; 2(119): 1-17. doi: 10.4172/2155-6180.1000119.
  • 18. Kleunen M, Ritland K. Estimating heritabilities and genetic correlations with marker-based methods: an experimental test in Mimulus guttatus. J Hered. 2005; 96(4): 368-75.
  • 19. Falconer DS. Introduction to Quantitative Genetics. 2nd ed. Essex, England: The Pitman Press; 1981. p. 148-69.
  • 20. Friars GW, Smith PJ. Heritability, correlation and selection response estimates of some traits in fish populations. Atlantic Salmon Federation Technical Report. Canada: Atlantic Salmon Federation; 2010.
  • 21. Lopes MC, Andrew T, Carbonaro F, Spector TD, Hammond CJ. Estimating heritability and shared environmental effects for refractive error in twin and family studies. Invest Ophth Vis Sci. 2009; 50(1): 126-31.
  • 22. Sahu M, Prasuna JG. Twin studies: a unique epidemiological tool. Indian J Community Med. 2016; 41(3): 177-82.
  • 23. Wray NR, Visscher PM. Estimating trait heritability. Nature Education. 2008; 1(1): 1-16.
  • 24. Singh M, Ceccarelli S, Hamblin J. Estimation of heritability from varietal trials data. Theor Appl Genet. 1993; 86(4): 437-41.
  • 25. Heckerman D, Gurdasani D, Kadie C, Pomilla C, Carstensen T, Martin H, et al. Linear mixed model for heritability estimation that explicitly addresses environmental variation. PNAS. 2016; 113(27): 7377-82.
  • 26. Kim Y, Lee Y, Lee S, Kim NH, Lim J, Kim YJ, et al. On the estimation of heritability with family-based and population-based samples. Biomed Res Int. 2015; 2015: Article ID: 671349. https://doi.org/10.1155/2015/671349.
  • 27. Evans LM, Tahmasbi R, Jones M, Vrieze SI, Abecasis GR, Das S, et al. Narrow-sense heritability estimation of complex traits using identity-by-descent information. Heredity. 2018; 121(6): 616-30.
There are 27 citations in total.

Details

Primary Language Turkish
Subjects Health Care Administration
Journal Section Reviews
Authors

İsmet Doğan 0000-0001-9251-3564

Nurhan Dogan 0000-0001-7224-6091

Project Number -
Publication Date May 31, 2020
Submission Date January 24, 2020
Published in Issue Year 2020 Volume: 10 Issue: 2

Cite

APA Doğan, İ., & Dogan, N. (2020). Kalıtım Derecesinin Tahmini ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı. Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi, 10(2), 252-257. https://doi.org/10.33631/duzcesbed.679732
AMA Doğan İ, Dogan N. Kalıtım Derecesinin Tahmini ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı. DÜ Sağlık Bil Enst Derg. May 2020;10(2):252-257. doi:10.33631/duzcesbed.679732
Chicago Doğan, İsmet, and Nurhan Dogan. “Kalıtım Derecesinin Tahmini Ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı”. Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi 10, no. 2 (May 2020): 252-57. https://doi.org/10.33631/duzcesbed.679732.
EndNote Doğan İ, Dogan N (May 1, 2020) Kalıtım Derecesinin Tahmini ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı. Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi 10 2 252–257.
IEEE İ. Doğan and N. Dogan, “Kalıtım Derecesinin Tahmini ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı”, DÜ Sağlık Bil Enst Derg, vol. 10, no. 2, pp. 252–257, 2020, doi: 10.33631/duzcesbed.679732.
ISNAD Doğan, İsmet - Dogan, Nurhan. “Kalıtım Derecesinin Tahmini Ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı”. Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi 10/2 (May 2020), 252-257. https://doi.org/10.33631/duzcesbed.679732.
JAMA Doğan İ, Dogan N. Kalıtım Derecesinin Tahmini ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı. DÜ Sağlık Bil Enst Derg. 2020;10:252–257.
MLA Doğan, İsmet and Nurhan Dogan. “Kalıtım Derecesinin Tahmini Ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı”. Düzce Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi, vol. 10, no. 2, 2020, pp. 252-7, doi:10.33631/duzcesbed.679732.
Vancouver Doğan İ, Dogan N. Kalıtım Derecesinin Tahmini ve İnsan Hastalıkları İle Bazı Özelliklerinin Kalıtsallığı. DÜ Sağlık Bil Enst Derg. 2020;10(2):252-7.