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Recurring exon deletions in the HP (haptoglobin) gene contribute to lower blood cholesterol levels

Nature Genetics volume 48, pages 359–366 (2016)Cite this article

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Abstract

One of the first protein polymorphisms identified in humans involves the abundant blood protein haptoglobin. Two exons of the HP gene (encoding haptoglobin) exhibit copy number variation that affects HP protein structure and multimerization. The evolutionary origins and medical relevance of this polymorphism have been uncertain. Here we show that this variation has likely arisen from many recurring deletions, more specifically, reversions of an ancient hominin-specific duplication of these exons. Although this polymorphism has been largely invisible to genome-wide genetic studies thus far, we describe a way to analyze it by imputation from SNP haplotypes and find among 22,288 individuals that these HP exonic deletions associate with reduced LDL and total cholesterol levels. We further show that these deletions, and a SNP that affects HP expression, appear to drive the strong association of cholesterol levels with SNPs near HP. Recurring exonic deletions in HP likely enhance human health by lowering cholesterol levels in the blood.

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Figure 1: A common CNV in the HP gene is responsible for distinct molecular phenotypes.
Figure 2: SNP haplotypes surrounding HP persist through the CNV region yet segregate with both structural forms of HP.
Figure 3: SNP haplotypes and sequence differences between HP subtypes inform structural history.
Figure 4: Lone HP1S structural alleles segregate on common HP2FS SNP haplotypes.
Figure 5: The HP2 allele associates with increased total cholesterol levels and increased LDL cholesterol levels.
Figure 6: The rs2000999[A] allele on the HP2 background is associated with a greater increase in total cholesterol and LDL cholesterol levels than the rs2000999[G] allele.
Figure 7: A model for the influence of HP genetic polymorphisms on total and LDL cholesterol levels.

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References

  1. Allison, A.C. & Rees, W.A. The binding of haemoglobin by plasma proteins (haptoglobins); its bearing on the renal threshold for haemoglobin and the aetiology of haemoglobinuria. BMJ 2, 1137–1143 (1957).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Langlois, M.R. & Delanghe, J.R. Biological and clinical significance of haptoglobin polymorphism in humans. Clin. Chem. 42, 1589–1600 (1996).

    CAS  PubMed  Google Scholar 

  3. Smithies, O. & Walker, N.F. Genetic control of some serum proteins in normal humans. Nature 176, 1265–1266 (1955).

    Article  CAS  PubMed  Google Scholar 

  4. Wejman, J.C., Hovsepian, D., Wall, J.S., Hainfeld, J.F. & Greer, J. Structure and assembly of haptoglobin polymers by electron microscopy. J. Mol. Biol. 174, 343–368 (1984).

    Article  CAS  PubMed  Google Scholar 

  5. Nielsen, M.J. & Moestrup, S.K. Receptor targeting of hemoglobin mediated by the haptoglobins: roles beyond heme scavenging. Blood 114, 764–771 (2009).

    Article  CAS  PubMed  Google Scholar 

  6. Melamed-Frank, M. et al. Structure-function analysis of the antioxidant properties of haptoglobin. Blood 98, 3693–3698 (2001).

    Article  CAS  PubMed  Google Scholar 

  7. Tripathi, A. et al. Identification of human zonulin, a physiological modulator of tight junctions, as prehaptoglobin-2. Proc. Natl. Acad. Sci. USA 106, 16799–16804 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Smithies, O., Connell, G.E. & Dixon, G.H. Inheritance of haptoglobin subtypes. Am. J. Hum. Genet. 14, 14–21 (1962).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Shindo, S. Haptoglobin subtyping with anti-haptoglobin α chain antibodies. Electrophoresis 11, 483–488 (1990).

    Article  CAS  PubMed  Google Scholar 

  10. Martosella, J. & Zolotarjova, N. Multi-component immunoaffinity subtraction and reversed-phase chromatography of human serum. Methods Mol. Biol. 425, 27–39 (2008).

    Article  CAS  PubMed  Google Scholar 

  11. Cahill, L.E. et al. Currently available versions of genome-wide association studies cannot be used to query the common haptoglobin copy number variant. J. Am. Coll. Cardiol. 62, 860–861 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Conrad, D.F. et al. Origins and functional impact of copy number variation in the human genome. Nature 464, 704–712 (2010).

    Article  CAS  PubMed  Google Scholar 

  13. 1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012).

  14. Levy, A.P. et al. Haptoglobin phenotype and prevalent coronary heart disease in the Framingham offspring cohort. Atherosclerosis 172, 361–365 (2004).

    Article  CAS  PubMed  Google Scholar 

  15. Koch, W. et al. Genotyping of the common haptoglobin Hp 1/2 polymorphism based on PCR. Clin. Chem. 48, 1377–1382 (2002).

    CAS  PubMed  Google Scholar 

  16. Soejima, M. & Koda, Y. TaqMan-based real-time PCR for genotyping common polymorphisms of haptoglobin (HP1 and HP2). Clin. Chem. 54, 1908–1913 (2008).

    Article  CAS  PubMed  Google Scholar 

  17. Zethelius, B. et al. Use of multiple biomarkers to improve the prediction of death from cardiovascular causes. N. Engl. J. Med. 358, 2107–2116 (2008).

    Article  CAS  PubMed  Google Scholar 

  18. Teslovich, T.M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Salvatore, A. et al. Haptoglobin binding to apolipoprotein A-I prevents damage from hydroxyl radicals on its stimulatory activity of the enzyme lecithin-cholesterol acyl-transferase. Biochemistry 46, 11158–11168 (2007).

    Article  CAS  PubMed  Google Scholar 

  20. Salvatore, A., Cigliano, L., Carlucci, A., Bucci, E.M. & Abrescia, P. Haptoglobin binds apolipoprotein E and influences cholesterol esterification in the cerebrospinal fluid. J. Neurochem. 110, 255–263 (2009).

    Article  CAS  PubMed  Google Scholar 

  21. Spagnuolo, M.S. et al. Analysis of the haptoglobin binding region on the apolipoprotein A-I–derived P2a peptide. J. Pept. Sci. 19, 220–226 (2013).

    Article  CAS  PubMed  Google Scholar 

  22. Cigliano, L., Pugliese, C.R., Spagnuolo, M.S., Palumbo, R. & Abrescia, P. Haptoglobin binds the antiatherogenic protein apolipoprotein E—impairment of apolipoprotein E stimulation of both lecithin:cholesterol acyltransferase activity and cholesterol uptake by hepatocytes. FEBS J. 276, 6158–6171 (2009).

    Article  CAS  PubMed  Google Scholar 

  23. Maeda, N., Yang, F., Barnett, D.R., Bowman, B.H. & Smithies, O. Duplication within the haptoglobin Hp2 gene. Nature 309, 131–135 (1984).

    Article  CAS  PubMed  Google Scholar 

  24. McEvoy, S.M. & Maeda, N. Complex events in the evolution of the haptoglobin gene cluster in primates. J. Biol. Chem. 263, 15740–15747 (1988).

    CAS  PubMed  Google Scholar 

  25. Hardwick, R.J. et al. Haptoglobin (HP) and haptoglobin-related protein (HPR) copy number variation, natural selection, and trypanosomiasis. Hum. Genet. 133, 69–83 (2014).

    Article  CAS  PubMed  Google Scholar 

  26. Hindson, B.J. et al. High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal. Chem. 83, 8604–8610 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).

  28. International HapMap Consortium. A haplotype map of the human genome. Nature 437, 1299–1320 (2005).

  29. Asakawa, J., Kodaira, M., Nakamura, N., Satoh, C. & Fujita, M. Chimerism in humans after intragenic recombination at the haptoglobin locus during early embryogenesis. Proc. Natl. Acad. Sci. USA 96, 10314–10319 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Rodriguez, S. et al. Molecular and population analysis of natural selection on the human haptoglobin duplication. Ann. Hum. Genet. 76, 352–362 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Prüfer, K. et al. The complete genome sequence of a Neanderthal from the Altai Mountains. Nature 505, 43–49 (2014).

    Article  PubMed  Google Scholar 

  32. Meyer, M. et al. A high-coverage genome sequence from an archaic Denisovan individual. Science 338, 222–226 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Gallego Llorente, M. et al. Ancient Ethiopian genome reveals extensive Eurasian admixture throughout the African continent. Science 350, 820–822 (2015).

    Article  CAS  PubMed  Google Scholar 

  34. Scally, A. & Durbin, R. Revising the human mutation rate: implications for understanding human evolution. Nat. Rev. Genet. 13, 745–753 (2012).

    Article  CAS  PubMed  Google Scholar 

  35. Browning, S.R. Missing data imputation and haplotype phase inference for genome-wide association studies. Hum. Genet. 124, 439–450 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2007).

    Article  CAS  PubMed  Google Scholar 

  37. Li, Y., Willer, C., Sanna, S. & Abecasis, G. Genotype imputation. Annu. Rev. Genomics Hum. Genet. 10, 387–406 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Ernst, J. & Kellis, M. Discovery and characterization of chromatin states for systematic annotation of the human genome. Nat. Biotechnol. 28, 817–825 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Froguel, P. et al. A genome-wide association study identifies rs2000999 as a strong genetic determinant of circulating haptoglobin levels. PLoS One 7, e32327 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Soejima, M. et al. Genetic factors associated with serum haptoglobin level in a Japanese population. Clin. Chim. Acta 433, 54–57 (2014).

    Article  CAS  PubMed  Google Scholar 

  42. Ishibashi, S., Herz, J., Maeda, N., Goldstein, J.L. & Brown, M.S. The two-receptor model of lipoprotein clearance: tests of the hypothesis in “knockout” mice lacking the low density lipoprotein receptor, apolipoprotein E, or both proteins. Proc. Natl. Acad. Sci. USA 91, 4431–4435 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Yang, Y., Cao, Z., Tian, L., Garvey, W.T. & Cheng, G. VPO1 mediates ApoE oxidation and impairs the clearance of plasma lipids. PLoS One 8, e57571 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Guthrie, P.A.I. et al. Complexity of a complex trait locus: HP, HPR, haemoglobin and cholesterol. Gene 499, 8–13 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Regan, J.F. et al. A rapid molecular approach for chromosomal phasing. PLoS One 10, e0118270 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Delaneau, O., Zagury, J.-F. & Marchini, J. Improved whole-chromosome phasing for disease and population genetic studies. Nat. Methods 10, 5–6 (2013).

    Article  CAS  PubMed  Google Scholar 

  49. Howie, B., Fuchsberger, C., Stephens, M., Marchini, J. & Abecasis, G.R. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat. Genet. 44, 955–959 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

    CAS  PubMed  Google Scholar 

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Acknowledgements

We thank C. Usher for comments on the manuscript and work on the figures. This work was supported by a grant from the National Human Genome Research Institute (R01HG006855 to S.A.M.). The Yerkes Center (grant P51OD011132) provided primate DNA samples. R.M.S. was supported by a US National Institutes of Health/National Heart, Lung, and Blood Institute K99 award (1K99HL122515-01A1) and an advanced postdoctoral fellowship award from the Juvenile Diabetes Research Foundation (JDRF 3-APF-2014-111-A-N). G.M.P. was supported by the National Heart, Lung, and Blood Institute of the US National Institutes of Health under award K01HL125751.

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Authors and Affiliations

  1. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA

    Linda M Boettger, Rany M Salem, Robert E Handsaker, Joel N Hirschhorn & Steven A McCarroll

  2. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    Linda M Boettger, Rany M Salem, Robert E Handsaker, Gina M Peloso, Sekar Kathiresan, Joel N Hirschhorn & Steven A McCarroll

  3. Division of Endocrinology, Boston Children's Hospital, Boston, Massachusetts, USA

    Rany M Salem & Joel N Hirschhorn

  4. Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts, USA.,

    Rany M Salem & Joel N Hirschhorn

  5. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA,

    Gina M Peloso & Sekar Kathiresan

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Contributions

L.M.B., S.A.M. and R.E.H. designed the experiments for understanding HP structural evolution. R.M.S., L.M.B. and G.M.P. performed imputation and association analyses of cholesterol cohorts. L.M.B. performed computational analyses of HapMap and 1000 Genomes Project data, constructed the imputation reference panels and performed all laboratory experiments. L.M.B. and S.A.M. wrote the manuscript. J.N.H. and S.K. provided advice on data analysis. All authors contributed to interpretations of data and to revisions of the manuscript.

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Correspondence to Steven A McCarroll.

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Integrated supplementary information

Supplementary Figure 1 SNPs on opposite sides of the CNV are routinely in high linkage disequilibrium.

The x axis indicates position on chromosome 16, while the y axis indicates the r2 correlation for linkage disequilibrium. The linkage disequilibrium value provided for each SNP is the maximum LD shared with a SNP on the opposite side of the CNV. The minor allele frequency for each SNP is indicated by color. (a) European populations (CEU, TSI, IBS). (b) African population (YRI).

Supplementary Figure 2 Sequence differences between human HP subtypes within the structurally variant region.

The x axis lists the base-pair position of each nucleotide variant as aligned to HP2FS-Left (hg19). The y axis indicates the HP subtype and HapMap or 1000 Genomes Project sample that was sequenced. Only polymorphic bases are shown. The lavender sequence indicates bases that result from paralogous gene conversion from HPR. The pink and green bases indicate alternate forms of the highly diverged region, while the white colored bases indicate other derived variants with respect to chimpanzee HP.

Supplementary Figure 3 Sequence differences between alleles, orthologs and paralogs in the HP structurally variant region.

An alignment of the structurally variant region for human structural haplotypes and other primates shows distinct polymorphic sections. The x axis lists the base-pair position of each nucleotide variant as aligned to HP2FS-Left (hg19). The homolog that provided the sequence is indicated on the y axis. Only the fixed differences between human HP subtypes are shown. The bases backed in white indicate mutations specific to human subtypes. The lavender region indicates bases that match human HPR. Human HP1F and HP2FS-Left have 30 derived bases (with respect to chimpanzee and bonobo HP) that match the human HPR gene. Bases in the highly diverged region are indicated in pink and green. The series of mutations that gave rise to the highly diverged region is unclear, as the great apes are also highly polymorphic in this region and multiple bases have potentially deep coalescence. Haptoglobin from the great apes was sequenced with the designed primers (Supplementary Table 14). Human HPR was provided by the hg19 reference sequence. Chimpanzee HPR and HPP are from previously released sequence (GenBank, M84462.1 and M84463.1). The following samples were provided by the Yerkes Center and Coriell Cell Repositories and were used to sequence HP in each respective great ape: PR00107 (gorilla), PR00251 (bonobo), NS03489 (chimpanzee) and NG06209 (orangutan).

Supplementary Figure 4 Assays designed to type HP variant boundaries.

(a) The coordinates for the boundaries of each sequence variant are given in hg19 coordinates. (b) Assays A–E were designed to the boundaries of HP variants. A 0 indicates that the assay sequence is absent and the haplotype will not amplify with the given assay, and a 1 indicates that the sequence is present and will produce amplicons.

Supplementary Figure 5 HP subtypes on different SNP haplotype backgrounds.

This figure is similar to Figure 1, but it includes subtype information in addition to the CNV. The vast majority of HP1F and HP1S alleles are on different SNP haplotype backgrounds. This plot displays the SNP haplotypes on either side of the CNV (10 kb on each side) segregating with HP1 and HP2. Each horizontal line represents an individual SNP haplotype. Note that the size of small clusters has been increased for visibility purposes, and the number of haplotypes contained in each cluster is indicated to the left of the plot. White represents the minor allele and gray indicates the major allele across all populations (CEU, IBS, TSI, YRI). YRI individuals are indicated with lavender bars to the left of the plot, while European populations (CEU, IBS, TSI) are indicated with dark purple bars to the left of the plot. Haplotypes were clustered with the k-means method using upstream SNP haplotypes. Similar SNP haplotypes carrying different structures are indicated with colored outlines (dark pink, light blue, green, gold).

Supplementary Figure 6 Model of HP structural evolution.

Our model of HP structural evolution is that a tandem duplication, paralogous gene conversion from HPR, and Form L and Form R of the highly diverged region were ancestral mutations that predate the deletion events that created the HP1S and HP1F structural alleles. However, it is possible that the ancestral duplication, gene conversion, and Form L and Form R could have arisen in an alternate order than is shown here. We interpret that the HP2SS structural allele arose relatively recently because it segregates solely on a homogeneous subset of the HP2FS-B SNP haplotype (Fig. 4 and Supplementary Fig. 5).

Supplementary Figure 7 HP1 alleles share derived nucleotides in the CNV region with HP2 alleles from the same SNP haplotype.

Nucleotide differences in the CNV region between HP1S alleles and HP2FS alleles on the same extended SNP haplotype background (as shown in Fig. 4). Derived variants are backed in white.

Supplementary Figure 8 A high-frequency recombinant haplotype increases LD between SNPs and HP2 structure in the YRI population.

The long-range SNP haplotype (100 kb) downstream of the CNV is shown. Minor alleles are shown in white, while major alleles are shown in gray. The minor alleles of SNPs with high LD to the CNV (r2 > 0.7) in the YRI population are colored in red. YRI haplotypes are indicated with lavender bars to the right of the plot. HP1S and HP1F SNP haplotypes are highly diverged locally around the CNV in both the European and YRI populations (also see Fig. 2). However, the YRI HP1S and HP1F haplotypes become nearly identical 27 kb downstream of the CNV (these haplotypes are indicated with stars to the right of the plot). This appears to be caused by a recombination event (interpreted location shown in green) on an HP1S haplotype. This recombination event allows HP1F and HP1S to be in high LD with the same alleles. Additionally, whereas this SNP haplotype is relatively common among European HP2FS alleles, it is very rare in YRI HP2FS alleles, allowing the LD between the CNV to be higher in the YRI population (haplotypes indicated with a black arrow).

Supplementary Figure 9 Association results for triglyceride and HDL cholesterol levels to HP structural forms and nearby SNPs.

(a) The association of HP structural forms and regional SNPs to triglyceride levels is not genome-wide significant with our combined cohort (HP2 P value = 2.24 × 10−3). (b) No association is observed between HP structural alleles and HDL cholesterol levels (HP2 P value = 0.57).

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Supplementary Figures 1–9, Supplementary Tables 1–15 and Supplementary Note. (PDF 3625 kb)

Supplementary Data Set

Reference panels for imputation of HP structural alleles. (ZIP 209 kb)

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Boettger, L., Salem, R., Handsaker, R. et al. Recurring exon deletions in the HP (haptoglobin) gene contribute to lower blood cholesterol levels. Nat Genet 48, 359–366 (2016). https://doi.org/10.1038/ng.3510

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