The Increasing Importance of Gene-Based Analyses


In recent years, genome and exome sequencing studies have implicated a plethora of new disease genes with rare causal variants. Here, I review 150 exome sequencing studies that claim to have discovered that a disease can be caused by different rare variants in the same gene, and I determine whether their methods followed the current best-practice guidelines in the interpretation of their data. Specifically, I assess whether studies appropriately assess controls for rare variants throughout the entire gene or implicated region as opposed to only investigating the specific rare variants identified in the cases, and I assess whether studies present sufficient co-segregation data for statistically significant linkage. I find that the proportion of studies performing gene-based analyses has increased with time, but that even in 2015 fewer than 40% of the reviewed studies used this method, and only 10% presented statistically significant co-segregation data. Furthermore, I find that the genes reported in these papers are explaining a decreasing proportion of cases as the field moves past most of the low-hanging fruit, with 50% of the genes from studies in 2014 and 2015 having variants in fewer than 5% of cases. As more studies focus on genes explaining relatively few cases, the importance of performing appropriate gene-based analyses is increasing. It is becoming increasingly important for journal editors and reviewers to require stringent gene-based evidence to avoid an avalanche of misleading disease gene discovery papers.


Vyšlo v časopise: The Increasing Importance of Gene-Based Analyses. PLoS Genet 12(4): e32767. doi:10.1371/journal.pgen.1005852
Kategorie: Review
prolekare.web.journal.doi_sk: 10.1371/journal.pgen.1005852

Souhrn

In recent years, genome and exome sequencing studies have implicated a plethora of new disease genes with rare causal variants. Here, I review 150 exome sequencing studies that claim to have discovered that a disease can be caused by different rare variants in the same gene, and I determine whether their methods followed the current best-practice guidelines in the interpretation of their data. Specifically, I assess whether studies appropriately assess controls for rare variants throughout the entire gene or implicated region as opposed to only investigating the specific rare variants identified in the cases, and I assess whether studies present sufficient co-segregation data for statistically significant linkage. I find that the proportion of studies performing gene-based analyses has increased with time, but that even in 2015 fewer than 40% of the reviewed studies used this method, and only 10% presented statistically significant co-segregation data. Furthermore, I find that the genes reported in these papers are explaining a decreasing proportion of cases as the field moves past most of the low-hanging fruit, with 50% of the genes from studies in 2014 and 2015 having variants in fewer than 5% of cases. As more studies focus on genes explaining relatively few cases, the importance of performing appropriate gene-based analyses is increasing. It is becoming increasingly important for journal editors and reviewers to require stringent gene-based evidence to avoid an avalanche of misleading disease gene discovery papers.


Zdroje

1. MacArthur DG, Manolio TA, Dimmock DP, Rehm HL, Shendure J, Abecasis GR, et al. Guidelines for investigating causality of sequence variants in human disease. Nature. 2014;508(7497):469–476. doi: 10.1038/nature13127 24759409; PubMed Central PMCID: PMC4180223.

2. Goldstein DB, Allen A, Keebler J, Margulies EH, Petrou S, Petrovski S, et al. Sequencing studies in human genetics: design and interpretation. Nature reviews. 2013;14(7):460–470. doi: 10.1038/nrg3455 23752795; PubMed Central PMCID: PMC4117319.

3. Lander E, Kruglyak L. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet. 1995;11(3):241–247. doi: 10.1038/ng1195-241 7581446.

4. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature reviews. 2008;9(5):356–369. doi: 10.1038/nrg2344 18398418.

5. Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ, et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature. 2012;485(7397):237–241. doi: 10.1038/nature10945 22495306; PubMed Central PMCID: PMC3667984.

6. Epi KC, Epilepsy Phenome/Genome P, Allen AS, Berkovic SF, Cossette P, Delanty N, et al. De novo mutations in epileptic encephalopathies. Nature. 2013;501(7466):217–221. doi: 10.1038/nature12439 23934111; PubMed Central PMCID: PMC3773011.

7. O'Roak BJ, Deriziotis P, Lee C, Vives L, Schwartz JJ, Girirajan S, et al. Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations. Nat Genet. 2011;43(6):585–589. doi: 10.1038/ng.835 21572417; PubMed Central PMCID: PMC3115696.

8. Cirulli ET, Lasseigne BN, Petrovski S, Sapp PC, Dion PA, Leblond CS, et al. Exome sequencing in amyotrophic lateral sclerosis identifies risk genes and pathways. Science. 2015;347(6229):1436–1441. doi: 10.1126/science.aaa3650 25700176; PubMed Central PMCID: PMC4437632.

9. Do R, Stitziel NO, Won HH, Jorgensen AB, Duga S, Angelica Merlini P, et al. Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. Nature. 2015;518(7537):102–106. doi: 10.1038/nature13917 25487149; PubMed Central PMCID: PMC4319990.

10. Kunishima S, Okuno Y, Yoshida K, Shiraishi Y, Sanada M, Muramatsu H, et al. ACTN1 mutations cause congenital macrothrombocytopenia. Am J Hum Genet. 2013;92(3):431–438. doi: 10.1016/j.ajhg.2013.01.015 23434115; PubMed Central PMCID: PMC3591851.

11. Cruchaga C, Karch CM, Jin SC, Benitez BA, Cai Y, Guerreiro R, et al. Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease. Nature. 2014;505(7484):550–554. doi: 10.1038/nature12825 24336208; PubMed Central PMCID: PMC4050701.

12. Ionita-Laza I, Xu B, Makarov V, Buxbaum JD, Roos JL, Gogos JA, et al. Scan statistic-based analysis of exome sequencing data identifies FAN1 at 15q13.3 as a susceptibility gene for schizophrenia and autism. Proc Natl Acad Sci U S A. 2014;111(1):343–348. doi: 10.1073/pnas.1309475110 24344280; PubMed Central PMCID: PMC3890869.

13. Lee S, Emond MJ, Bamshad MJ, Barnes KC, Rieder MJ, Nickerson DA, et al. Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies. Am J Hum Genet. 2012;91(2):224–237. doi: 10.1016/j.ajhg.2012.06.007 22863193; PubMed Central PMCID: PMC3415556.

14. Sung YJ, Korthauer KD, Swartz MD, Engelman CD. Methods for collapsing multiple rare variants in whole-genome sequence data. Genetic epidemiology. 2014;38 Suppl 1:S13–20. doi: 10.1002/gepi.21820 25112183; PubMed Central PMCID: PMC4558905.

15. Lee S, Abecasis GR, Boehnke M, Lin X. Rare-variant association analysis: study designs and statistical tests. Am J Hum Genet. 2014;95(1):5–23. doi: 10.1016/j.ajhg.2014.06.009 24995866; PubMed Central PMCID: PMC4085641.

16. Leslie EJ, Standley J, Compton J, Bale S, Schutte BC, Murray JC. Comparative analysis of IRF6 variants in families with Van der Woude syndrome and popliteal pterygium syndrome using public whole-exome databases. Genet Med. 2013;15(5):338–344. doi: 10.1038/gim.2012.141 23154523; PubMed Central PMCID: PMC3723330.

17. Zankl A, Duncan EL, Leo PJ, Clark GR, Glazov EA, Addor MC, et al. Multicentric carpotarsal osteolysis is caused by mutations clustering in the amino-terminal transcriptional activation domain of MAFB. Am J Hum Genet. 2012;90(3):494–501. doi: 10.1016/j.ajhg.2012.01.003 22387013; PubMed Central PMCID: PMC3309183.

18. ExomeAggregationConsortium(ExAC). Cambridge, MA. http://exac.broadinstitute.org.

19. Wooderchak-Donahue WL, McDonald J, O'Fallon B, Upton PD, Li W, Roman BL, et al. BMP9 mutations cause a vascular-anomaly syndrome with phenotypic overlap with hereditary hemorrhagic telangiectasia. Am J Hum Genet. 2013;93(3):530–537. doi: 10.1016/j.ajhg.2013.07.004 23972370; PubMed Central PMCID: PMC3769931.

20. Gbadegesin RA, Hall G, Adeyemo A, Hanke N, Tossidou I, Burchette J, et al. Mutations in the gene that encodes the F-actin binding protein anillin cause FSGS. Journal of the American Society of Nephrology: JASN. 2014;25(9):1991–2002. doi: 10.1681/ASN.2013090976 24676636; PubMed Central PMCID: PMC4147982.

21. Klein CJ, Botuyan MV, Wu Y, Ward CJ, Nicholson GA, Hammans S, et al. Mutations in DNMT1 cause hereditary sensory neuropathy with dementia and hearing loss. Nat Genet. 2011;43(6):595–600. doi: 10.1038/ng.830 21532572; PubMed Central PMCID: PMC3102765.

22. Simpson MA, Irving MD, Asilmaz E, Gray MJ, Dafou D, Elmslie FV, et al. Mutations in NOTCH2 cause Hajdu-Cheney syndrome, a disorder of severe and progressive bone loss. Nat Genet. 2011;43(4):303–305. doi: 10.1038/ng.779 21378985.

23. Isidor B, Lindenbaum P, Pichon O, Bezieau S, Dina C, Jacquemont S, et al. Truncating mutations in the last exon of NOTCH2 cause a rare skeletal disorder with osteoporosis. Nat Genet. 2011;43(4):306–308. doi: 10.1038/ng.778 21378989.

24. Ng SB, Bigham AW, Buckingham KJ, Hannibal MC, McMillin MJ, Gildersleeve HI, et al. Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome. Nat Genet. 2010;42(9):790–793. doi: 10.1038/ng.646 20711175; PubMed Central PMCID: PMC2930028.

25. Ng SB, Buckingham KJ, Lee C, Bigham AW, Tabor HK, Dent KM, et al. Exome sequencing identifies the cause of a mendelian disorder. Nat Genet. 2010;42(1):30–35. doi: 10.1038/ng.499 19915526; PubMed Central PMCID: PMC2847889.

26. Bedell VM, Westcot SE, Ekker SC. Lessons from morpholino-based screening in zebrafish. Briefings in functional genomics. 2011;10(4):181–188. doi: 10.1093/bfgp/elr021 21746693; PubMed Central PMCID: PMC3144740.

27. Eisen JS, Smith JC. Controlling morpholino experiments: don't stop making antisense. Development. 2008;135(10):1735–1743. doi: 10.1242/dev.001115 18403413.

28. Kalueff AV, Murphy DL. The importance of cognitive phenotypes in experimental modeling of animal anxiety and depression. Neural plasticity. 2007;2007:52087. doi: 10.1155/2007/52087 18288249; PubMed Central PMCID: PMC2233771.

29. Jucker M. The benefits and limitations of animal models for translational research in neurodegenerative diseases. Nature medicine. 2010;16(11):1210–1214. doi: 10.1038/nm.2224 21052075.

30. Neale BM, Sham PC. The future of association studies: gene-based analysis and replication. Am J Hum Genet. 2004;75(3):353–362. doi: 10.1086/423901 15272419; PubMed Central PMCID: PMC1182015.

31. Willemsen MH, Vissers LE, Willemsen MA, van Bon BW, Kroes T, de Ligt J, et al. Mutations in DYNC1H1 cause severe intellectual disability with neuronal migration defects. Journal of medical genetics. 2012;49(3):179–183. doi: 10.1136/jmedgenet-2011-100542 22368300.

32. Sasaki M, Ohba C, Iai M, Hirabayashi S, Osaka H, Hiraide T, et al. Sporadic infantile-onset spinocerebellar ataxia caused by missense mutations of the inositol 1,4,5-triphosphate receptor type 1 gene. Journal of neurology. 2015;262(5):1278–1284. doi: 10.1007/s00415-015-7705-8 25794864.

33. Philippakis AA, Azzariti DR, Beltran S, Brookes AJ, Brownstein CA, Brudno M, et al. The Matchmaker Exchange: A Platform for Rare Disease Gene Discovery. Human mutation. 2015;36(10):915–921. doi: 10.1002/humu.22858 26295439.

34. Au PY, You J, Caluseriu O, Schwartzentruber J, Majewski J, Bernier FP, et al. GeneMatcher Aids in the Identification of a New Malformation Syndrome with Intellectual Disability, Unique Facial Dysmorphisms, and Skeletal and Connective Tissue Abnormalities Caused by De Novo Variants in HNRNPK. Human mutation. 2015;36(10):1009–1014. doi: 10.1002/humu.22837 26173930.

35. Codina-Sola M, Rodriguez-Santiago B, Homs A, Santoyo J, Rigau M, Aznar-Lain G, et al. Integrated analysis of whole-exome sequencing and transcriptome profiling in males with autism spectrum disorders. Molecular autism. 2015;6:21. doi: 10.1186/s13229-015-0017-0 25969726; PubMed Central PMCID: PMC4427998.

36. Andreoletti G, Ashton JJ, Coelho T, Willis C, Haggarty R, Gibson J, et al. Exome analysis of patients with concurrent pediatric inflammatory bowel disease and autoimmune disease. Inflammatory bowel diseases. 2015;21(6):1229–1236. doi: 10.1097/MIB.0000000000000381 25895113; PubMed Central PMCID: PMC4450895.

37. D'Alessandro LC, Al Turki S, Manickaraj AK, Manase D, Mulder BJ, Bergin L, et al. Exome sequencing identifies rare variants in multiple genes in atrioventricular septal defect. Genet Med. 2015. doi: 10.1038/gim.2015.60 25996639.

38. Chen MJ, Wei SY, Yang WS, Wu TT, Li HY, Ho HN, et al. Concurrent exome-targeted next-generation sequencing and single nucleotide polymorphism array to identify the causative genetic aberrations of isolated Mayer-Rokitansky-Kuster-Hauser syndrome. Hum Reprod. 2015;30(7):1732–1742. doi: 10.1093/humrep/dev095 25924657.

39. Mistry V, Bockett NA, Levine AP, Mirza MM, Hunt KA, Ciclitira PJ, et al. Exome sequencing of 75 individuals from multiply affected coeliac families and large scale resequencing follow up. PLoS ONE. 2015;10(1):e0116845. doi: 10.1371/journal.pone.0116845 25635822; PubMed Central PMCID: PMC4312029.

40. Futema M, Plagnol V, Li K, Whittall RA, Neil HA, Seed M, et al. Whole exome sequencing of familial hypercholesterolaemia patients negative for LDLR/APOB/PCSK9 mutations. Journal of medical genetics. 2014;51(8):537–544. doi: 10.1136/jmedgenet-2014-102405 24987033; PubMed Central PMCID: PMC4112429.

41. Goodloe AH, Evans JM, Middha S, Prasad A, Olson TM. Characterizing genetic variation of adrenergic signalling pathways in Takotsubo (stress) cardiomyopathy exomes. Eur J Heart Fail. 2014;16(9):942–949. doi: 10.1002/ejhf.145 25132214.

Štítky
Genetika Reprodukčná medicína
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