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Family-based designs in the age of large-scale gene-association studies

Key Points

  • Either population-based or family-based designs can be used in gene-association studies. Population-based designs use unrelated individuals; family-based designs use probands and their relatives, typically either parents or siblings.

  • Genetic-association studies face the obstacles of population substructures and multiple testing.

  • Family-based designs are favoured because they are robust against confounding due to population substructures and test both linkage and association.

  • Case–control designs are preferred for the relative ease of data collection. They have modest power advantages, depending on the prevalence of the disease.

  • Family-based designs can be extended to incorporate pedigrees and complex phenotypes.

  • Screening tools are available for family-based designs that allow the multiple-testing problem, which is an important issue in whole-genome association studies, to be handled.

Abstract

Both population-based and family-based designs are commonly used in genetic association studies to locate genes that underlie complex diseases. The simplest version of the family-based design — the transmission disequilibrium test — is well known, but the numerous extensions that broaden its scope and power are less widely appreciated. Family-based designs have unique advantages over population-based designs, as they are robust against population admixture and stratification, allow both linkage and association to be tested for and offer a solution to the problem of model building. Furthermore, the fact that family-based designs contain both within- and between-family information has substantial benefits in terms of multiple-hypothesis testing, especially in the context of whole-genome association studies.

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Figure 1: Power comparison between case–control studies and family-based designs.

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References

  1. Risch, N. & Merikangas, K. The future of genetics studies of complex human diseases. Science 273, 1516–1517 (1996). Shows that genome-wide association scans based on trios have greater power than genome-wide linkage scans based on affected sib pairs.

    Article  CAS  PubMed  Google Scholar 

  2. Clayton, D. G. et al. Population structure, differential bias and genomic control in a large-scale, case–control association study. Nature Genet. 37, 1243–1246 (2005).

    Article  CAS  PubMed  Google Scholar 

  3. Freedman, M. L. et al. Assessing the impact of population stratification on genetic association studies. Nature Genet. 36, 388–393 (2004).

    Article  CAS  PubMed  Google Scholar 

  4. McGinnis, R. General equations for Pt, Ps, and the power of the TDT and the affected-sib-pair test. Am. J. Hum. Genet. 67, 1340–1347 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. McGinnis, R., Shifman, S. & Darvasi, A. Power and efficiency of the TDT and case–control design for association scans. Behav. Genet. 32, 135–144 (2002).

    Article  PubMed  Google Scholar 

  6. Zollner, S. et al. Evidence for extensive transmission distortion in the human genome. Am. J. Hum. Genet. 74, 62–72 (2004).

    Article  PubMed  Google Scholar 

  7. Ott, J. Statistical properties of the haplotype relative risk. Genet. Epidemiol. 6, 127–130. (1989) Demostrates the need for linkage and association under the alternative hypothesis for a family-based test.

    Article  CAS  PubMed  Google Scholar 

  8. Hirschhorn, J. N. & Daly, M. J. Genome-wide association studies for common diseases and complex traits. Nature Rev. Genet. 6, 95–108 (2005).

    Article  CAS  PubMed  Google Scholar 

  9. Lazzeroni, L. C. & Lange, K. A conditional inference framework for extending the transmission/disequilibrium test. Hum. Hered. 48, 67–81 (1998).

    Article  CAS  PubMed  Google Scholar 

  10. Rabinowitz, D. & Laird, N. A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information. Hum. Hered. 50, 211–223 (2000). Generalization of the TDT for general pedigrees, missing parents and arbitrary phenotypes using the approach of conditioning on the sufficient statistic.

    Article  CAS  PubMed  Google Scholar 

  11. Fulker, D. W. et al. Combined linkage and association sib-pair analysis for quantitative traits. Am. J. Hum. Genet. 64, 259–267 (1999). Forms the basis of the likelihood approaches for quantitative traits in family-based studies with correction for admixture.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cox, D. R. & Hinkley, D. V. Theoretical Statistics 18–23 (Chapman and Hall, London, 1974).

    Book  Google Scholar 

  13. Yu, J. et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genet. 38, 203–208 (2006).

    Article  CAS  PubMed  Google Scholar 

  14. Laird, N. et al. in Respiratory Genetics (eds Silverman, E. et al.) 27–46 (Hodder Arnold, Boston, 2005).

    Book  Google Scholar 

  15. Weinberg, C. R. Studying parents and grandparents to assess genetic contributions to early-onset disease. Am. J. Hum. Genet. 72, 438–447 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Martin, E. R., Kaplan, N. L. & Weir, B. S. Tests for linkage and association in nuclear families. Am. J. Hum. Genet. 61, 439–448 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Thompson, G. Mapping disease genes: family-based association studies. Am. J. Hum. Genet. 57, 487–498 (1995).

    Google Scholar 

  18. Schneiter, K., Laird, N. & Corcoran, C. Exact family-based association tests for biallelic data. Genet. Epidemiol. 29, 185–194 (2005).

    Article  PubMed  Google Scholar 

  19. Lake, S. L., Blacker, D. & Laird, N. M. Family-based tests of association in the presence of linkage. Am. J. Hum. Genet. 67, 1515–1525 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Curtis, D., Miller, M. B. & Sham, P. C. Combining the sibling disequilibrium test and transmission/disequilibrium test for multiallelic markers. Am. J. Hum. Genet. 64, 1785–1786 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Horvath, S. & Laird, N. M. A discordant-sibship test for disequilibrium and linkage: no need for parental data. Am. J. Hum. Genet. 63, 1886–1897 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Spielman, R. S. & Ewens, W. J. A sibship test for linkage in the presence of association: the sib transmission/disequilibrium test. Am. J. Hum. Genet. 62, 450–458 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Knapp, M. The transmission/disequilibrium test and parental-genotype reconstruction: the reconstruction-combined transmission/ disequilibrium test. Am. J. Hum. Genet. 64, 861–870 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Horvath, S. et al. Family-based tests for associating haplotypes with general phenotype data: application to asthma genetics. Genet. Epidemiol. 26, 61–69 (2004).

    Article  PubMed  Google Scholar 

  25. Dudbridge, F. Pedigree disequilibrium tests for multilocus haplotypes. Genet. Epidemiol. 25, 115–121 (2003).

    Article  PubMed  Google Scholar 

  26. Cordell, H. J., Barratt, B. J. & Clayton, D. G. Case/pseudocontrol analysis in genetic association studies: a unified framework for detection of genotype and haplotype associations, gene–gene and gene–environment interactions, and parent-of-origin effects. Genet. Epidemiol. 26, 167–185 (2004).

    Article  PubMed  Google Scholar 

  27. Purcell, S., Sham, P. & Daly, M. J. Parental phenotypes in family-based association analysis. Am. J. Hum. Genet. 76, 249–259 (2005).

    Article  CAS  PubMed  Google Scholar 

  28. Whittaker, J. C. & Lewis, C. M. Power comparisons of the transmission/disequilibrium test and sib-transmission/disequilibrium-test statistics. Am. J. Hum. Genet. 65, 578–580 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lange, C. & Laird, N. Analytical sample size and power calculations for a general class of family-based association tests: dichotomous traits. Am. J. Hum. Genet. 71, 575–584 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Whittaker, J. C. & Lewis, C. M. The effect of family structure on linkage tests using allelic association. Am. J. Hum. Genet. 63, 889–897 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Lange, C. & Laird, N. M. On a general class of conditional tests for family-based association studies in genetics: the asymptotic distribution, the conditional power, and optimality considerations. Genet. Epidemiol. 23, 165–180 (2002).

    Article  PubMed  Google Scholar 

  32. Abecasis, G. R., Cardon, L. R. & Cookson, W. O. A general test of association for quantitative traits in nuclear families. Am. J. Hum. Genet. 66, 279–292 (2000).

    Article  CAS  PubMed  Google Scholar 

  33. Gauderman, W. J. Candidate gene association analysis for a quantitative trait, using parent-offspring trios. Genet. Epidemiol. 25, 327–338 (2003).

    Article  PubMed  Google Scholar 

  34. Lunetta, K. L. et al. Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions. Am. J. Hum. Genet. 66, 605–614 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Lange, C. et al. A family-based association test for repeatedly measured quantitative traits adjusting for unknown environmental and/or polygenic effects. Stat. Appl. Genet. Mol. Biol. 3, 17 (2004).

    Article  Google Scholar 

  36. Lange, C., DeMeo, D. L. & Laird, N. M. Power and design considerations for a general class of family-based association tests: quantitative traits. Am. J. Hum. Genet. 71, 1330–1341 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Weiss, S. T. The origins of childhood asthma. Monaldi Arch. Chest Dis. 49, 154–158 (1994).

    CAS  PubMed  Google Scholar 

  38. Weiss, S. T. Epidemiology and heterogeneity of asthma. Ann. Allergy Asthma Immunol. 87 (1 Suppl. 1), 5–8 (2001).

    Article  CAS  PubMed  Google Scholar 

  39. Silverman, E. K. et al. Familial aggregation of severe, early-onset COPD: candidate gene approaches. Chest 117 (5 Suppl. 1), 273S–274S (2000).

    Article  CAS  PubMed  Google Scholar 

  40. Demeo, D. L. et al. The SERPINE2 gene is associated with chronic obstructive pulmonary disease. Am. J. Hum. Genet. 78, 253–264 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Celedon, J. C. et al. The transforming growth factor-β1 (TGFB1) gene is associated with chronic obstructive pulmonary disease (COPD). Hum. Mol. Genet. 13, 1649–1656 (2004).

    Article  CAS  PubMed  Google Scholar 

  42. Todd, R. Genetics of attention deficit/hyperactivity disorder: are we ready for molecular genetic studies? Am. J. Med. Genet. 96, 241–243 (2000).

    Article  CAS  PubMed  Google Scholar 

  43. Lange, C. et al. A multivariate family-based association test using generalized estimating equations: FBAT-GEE. Biostatistics 4, 195–206 (2003).

    Article  PubMed  Google Scholar 

  44. Mokliatchouk, O., Blacker, O. & Rabinowitz, D. Association tests for traits with variable age at onset. Hum. Hered. 51, 46–53 (2001).

    Article  CAS  PubMed  Google Scholar 

  45. Lange, C., Blacker, D. & Laird, N. M. Family-based association tests for survival and times-to-onset analysis. Stat. Med. 23, 179–189 (2004).

    Article  PubMed  Google Scholar 

  46. Jiang, H. et al. Family-based association test for time-to-onset data with time-dependent differences between the hazard functions. Genet. Epidemiol. 30, 124–132 (2005).

    Article  Google Scholar 

  47. Shih, M. C. & Whittemore, A. S. Tests for genetic association using family data. Genet. Epidemiol. 22, 128–145 (2002).

    Article  PubMed  Google Scholar 

  48. Lange, C. et al. Using the noninformative families in family-based association tests: a powerful new testing strategy. Am. J. Hum. Genet. 73, 801–811 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Lange, C. et al. PBAT: tools for family-based association studies. Am. J. Hum. Genet. 74, 367–369 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Van Steen, K. et al. Genomic screening and replication using the same data set in family-based association testing. Nature Genet. 37, 683–691 (2005). Demonstrates that the multi-testing problem can be handled at a genome-wide level in family-based association tests.

    Article  CAS  PubMed  Google Scholar 

  51. Lasky-Su, J. et al. Family-based association analysis of a statistically derived quantities trait for ADDO reveals an association in DRD4 with inattentive simony in AD individuals. Am. J. Med. Genet. B Neurophyschiatr. Genet. 138B, 57–58 (2005).

    Google Scholar 

  52. Thomas, D., Xie, R. & Gebregziabher, M. Two-stage sampling designs for gene association studies. Genet. Epidemiol. 27, 401–414 (2004).

    Article  PubMed  Google Scholar 

  53. Zaykin, D. V. & Zhivotovsky, L. A. Ranks of genuine associations in whole-genome scans. Genetics 171, 813–823 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Rosner, B. Fundamentals of Biostatistics 5th edn 527–530 (Duxbury, Boston MA,1995).

    Google Scholar 

  55. Hochberg, Y. A sharper Bonferroni procedure for multiple tests of significance. Biometrika 75, 800–802 (1988).

    Article  Google Scholar 

  56. Herbert, A. et al. A common genetic variant 10 kb upstream of INSIG2 is associated with adult and childhood obesity. Science (in the press).

  57. Gordon, D. et al. A transmission disequilibrium test for general pedigrees that is robust to the presence of random genotyping errors and any number of untyped parents. Eur. J. Hum. Genet. 12, 752–761 (2004).

    Article  CAS  PubMed  Google Scholar 

  58. Gordon, D. et al. A transmission/disequilibrium test that allows for genotyping errors in the analysis of single-nucleotide polymorphism data. Am. J. Hum. Genet. 69, 371–380 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Gordon, D. & Ott, J. Assessment and management of single nucleotide polymorphism genotype errors in genetic association analysis. Pac. Symp. Biocomput. 18–29 (2001).

  60. Spielman, R. S., McGinnis, R. E. & Ewens, W. J. Transmission test for linkage disequillibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am. J. Hum. Genet. 52, 506–516 (1993). Proposed the original idea of the TDT.

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Laird, N. M., Horvath, S. & Xu, X. Implementing a unified approach to family-based tests of association. Genet. Epidemiol. 19 (Suppl. 1), S36–S42 (2000).

    Article  PubMed  Google Scholar 

  62. Self, S. et al. On estimating HLA/disease association with application to a study of aplastic anemia. Biometrics 47, 53–61 (1991).

    Article  CAS  PubMed  Google Scholar 

  63. Cordell, H. J. & Clayton, D. G. A unified stepwise regression procedure for evaluating the relative effects of polymorphisms within a gene using case/control or family data: application to HLA in type 1 diabetes. Am. J. Hum. Genet. 70, 124–141 (2002).

    Article  CAS  PubMed  Google Scholar 

  64. Schaid, D. J. General score tests for associations of genetic markers with disease using cases and their parents. Genet. Epidemiol. 13, 423–449 (1996). Shows how the TDT can be derived as a score statistic from a multinomial likelihood model.

    Article  CAS  PubMed  Google Scholar 

  65. Clayton, D. A generalization of the transmission/disequilibrium test for uncertain-haplotype transmission. Am. J. Hum. Genet. 65, 1170–1177 (1999). The first haplotype-analysis paper to use a likelihood approach.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Whittemore, A. S. & Tu, I. P. Detection of disease genes by use of family data. I. Likelihood-based theory. Am. J. Hum. Genet. 66, 1328–1340 (2000). Generalized Schaid's-likelihood approach to handle missing parents, multiple offspring and incorporate founders into the test statistic.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Horvath, S., Xu, X. & Laird, N. M. The family based association test method: strategies for studying general genotype–phenotype associations. Euro. J. Hum. Gen. 9, 301–306 (2001).

    Article  CAS  Google Scholar 

  68. Weinberg, C. R., Wilcox, A. J. & Lie, R. T. A log-linear approach to case-parent-triad data: assessing effects of disease genes that act either directly or through maternal effects and that may be subject to parental imprinting. Am. J. Hum. Genet. 62, 969–978 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Weinberg, C. R. Allowing for missing parents in genetic studies of case-parent triads. Am. J. Hum. Genet. 64, 1186–1193 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Weinberg, C. R. Methods for detection of parent-of-origin effects in genetic studies of case-parents triads. Am. J. Hum. Genet. 65, 229–235 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Umbach, D. M. & Weinberg, C. R. The use of case-parent triads to study joint effects of genotype and exposure. Am. J. Hum. Genet. 66, 251–261 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Kistner, E. O. & Weinberg, C. R. Method for using complete and incomplete trios to identify genes related to a quantitative trait. Genet. Epidemiol. 27, 33–42 (2004).

    Article  PubMed  Google Scholar 

  73. Kistner, E. O. & Weinberg, C. R. A method for identifying genes related to a quantitative trait, incorporating multiple siblings and missing parents. Genet. Epidemiol. 29, 155–165 (2005).

    Article  PubMed  Google Scholar 

  74. Kistner, E. O., Infante-Rivard, C. & Weinberg, C. R. A method for using incomplete triads to test maternally mediated genetic effects and parent-of-origin effects in relation to a quantitative trait. Am. J. Epidemiol. 163, 255–261 (2006).

    Article  PubMed  Google Scholar 

  75. Witte, J. S., Gauderman, W. J. & Thomas, D. C. Asymptotic bias and efficiency in case–control studies of candidate genes and gene–environment interactions: basic family designs. Am. J. Epidemiol. 149, 693–705 (1999).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the National Institute of Mental Health and the National Heart, Lung and Blood Institute, USA. We would like to thank C. Garcia for with help with the preparation of this manuscript.

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Correspondence to Nan M. Laird.

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Glossary

Linkage analysis

A method for localizing genes that is based on the co-inheritance of genetic markers and phenotypes in families over several generations.

Association studies

A gene-discovery strategy that compares allele frequencies in cases and controls to assess the contribution of genetic variants to phenotypes in specific populations.

Candidate gene

A gene for which there is evidence, usually functional, for a possible role in a disease or trait of interest.

Power

The ability of a study to obtain a significant result if this result is true in the underlying population from which the study subjects were sampled.

Multiple-hypothesis testing

Many different statistical tests are used on the same sample; for example, many genetic markers might be tested against many different phenotypes. Failure to account for multiple testing inflates the study-wide type-1 error rate.

Population substructure

Characteristics of a population, such as admixture, population stratification and/or inbreeding, which might distort the distribution of the standard association statistics, leading to increased type-1 error and/or decreased power.

Genome-wide association studies

Studies designed to look for association between disease and a dense set of markers covering the entire genome.

Case–control study

An epidemiological study design in which cases with a defined condition and controls without this condition are sampled from the same population. Risk-factor information is compared between the two groups to investigate the potential role of these in the aetiology of the condition.

Case–cohort study

Similar to a case–control study, except both cases and controls are drawn from an existing cohort of subjects who are being followed to study a broad spectrum of diseases and risk factors.

Proband

In a family study, this is the individual who is first identified in the family as having the disease under study.

Odds ratio

The odds of exposure to the susceptible genetic variant in cases compared with controls. If the odds ratio is significantly greater than one, then the genetic variant is associated with the disease.

Monte Carlo

A method for obtaining a p-value for a test statistic by drawing repeated samples from the null distribution of the data, computing the p-value for the same statistic for each sample, and comparing the observed p-value to the distribution of p-values obtained from the samples.

Likelihood

A statistical model for analysing data that requires specifying a particular form for the distribution of the data.

Admixture

This occurs when two or more subpopulations inbreed, so that two randomly chosen individuals in the population might have different degrees of genetic heritage from the original subpopulations.

Population stratification

The presence in a population of distinct strata or groups that show limited inbreeding; they might have different disease rates and distinct allele-frequency distributions. Failure to control for the stratification can invalidate tests of association.

Linkage disequilibrium

(LD). This occurs when alleles at two different loci are associated in a population because of tight linkage.

Haplotype

A set of alleles at different loci that are present together on the same chromosome.

Phase

The arrangement of alleles at multiple loci on homologous chromosomes. For example, in a diploid individual with genotype Aa at one locus and genotype Bb at another locus, possible linkage phases are BA/ba or Ba/bA, where '/' separates the two homologous chromosomes.

Covariance

A measure of association between two variables that characterizes the tendency for the two variables to co-vary around their mean in a systematic way.

Informative families

Families that make a contribution to the FBAT test; that is, those with at least one heterozygote parent, or sibships with at least two distinct genotypes.

Nuisance parameters

Parameters that are not the primary focus of a statistical analysis, but for which misspecficiation might lead to biased results, for example, allele frequency in association tests.

Sufficient statistics

A data reduction function that retains all information about an unknown parameter; they are used to remove the dependence of a test on nuisance parameters that are unknown or difficult to model.

Confounding

A measure of the association between a disease and a risk factor is distorted because other variables, associated with both the disease and the risk factor, are not controlled for in the calculation of the measure of association.

Likelihood-ratio tests

A class of statistical tests obtained by comparing the likelihood statistic under the alternative hypothesis to the likelihood under the null hypothesis.

Score tests

A class of statistical tests that are derived from a likelihood model and are generally easier to compute than likelihood-ratio tests.

Identity-by-descent

(IBD). An allele shared by two related individuals is said to be identical-by-descent if the allele is inherited from the same common ancestor.

Permutation

An approach in which the actual data are randomized many times to generate a distribution of outcomes, so that the fraction of observations with values that are more extreme than the outcome that is observed with the real data reflects the statistical significance.

Outcome space

Set of all possible genotype configurations for a specific pedigree that are plausible under Mendelian transmissions, and consistent with the sufficient statistics for parental genotype.

Discordant sibs

A family design for testing association that uses a case and his/her unaffected sib.

Nested models

A sequence of statistical models, each specifying a different hypothesis, such that each model in the sequence contains one more factor than the preceeding model. Nested models are often used to test for the presence of interactions between two or more risk factors.

Multiplicative genetic model

A genetic model for penetrance functions that assumes the relative risk for disease given two alleles is the square of the relative risk for disease given only one allele.

Linear regression

A statistical method used to test and to describe the linear relationship between two or more variables.

Type-1 error

The probability that the null hypothesis is falsely rejected.

Intermediate phenotypes or endophenotypes

Measured biological variables intermediate between genotype and external phenotype that can indicate susceptibility to, or manifest as early signs of, a wide range of diseases or disorders.

Imputed

A statistical method for handling missing data which replaces the missing values by estimated values.

Bonferroni or Hochberg corrections

Statistical methods, proposed by Bonferroni and Hochberg, for controlling type-1 error (false positives) in the presence of multiple testing.

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Laird, N., Lange, C. Family-based designs in the age of large-scale gene-association studies. Nat Rev Genet 7, 385–394 (2006). https://doi.org/10.1038/nrg1839

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