OBJECTIVES: Monozygotic twins with near-identical genotypes and discordance for complex diseases represent an exceptional resource to ascertain disease etiology. This strategy has been particularly effective with the availability of high-resolution complete individual genome sequencing. The challenge is using effective approaches to identify relevant differences that may cause or contribute toward disease discordance. PARTICIPANTS AND METHODS: This study carried out a VarScan2 bioinformatic analysis and a pathway analysis on whole-genome sequences from two sets of monozygotic twins. RESULTS: Variants were identified that were present in the affected twin, but not found in the unaffected twin. Such variations are expected to be de novo and originate during the independent development of the twins and may make them discordant for the disease. The genes and de novo variants identified in this experiment are compatible with their involvement in schizophrenia. Further analysis of the variants identified pathways including glutamate receptor signaling that have been implicated in this neurodevelopmental disease. CONCLUSION: The results support the polygenic nature of schizophrenia and the threshold model for its development. The results also show the effectiveness of VarScan2 to identify 'the needle in the hay stack' that may cause schizophrenia, specifically in the two patients. It offers a proof of principle for assessment of the genetic etiology of complex disorders where discordance of monozygotic twins is an established phenomenon.
OBJECTIVES: Monozygotic twins with near-identical genotypes and discordance for complex diseases represent an exceptional resource to ascertain disease etiology. This strategy has been particularly effective with the availability of high-resolution complete individual genome sequencing. The challenge is using effective approaches to identify relevant differences that may cause or contribute toward disease discordance. PARTICIPANTS AND METHODS: This study carried out a VarScan2 bioinformatic analysis and a pathway analysis on whole-genome sequences from two sets of monozygotic twins. RESULTS: Variants were identified that were present in the affected twin, but not found in the unaffected twin. Such variations are expected to be de novo and originate during the independent development of the twins and may make them discordant for the disease. The genes and de novo variants identified in this experiment are compatible with their involvement in schizophrenia. Further analysis of the variants identified pathways including glutamate receptor signaling that have been implicated in this neurodevelopmental disease. CONCLUSION: The results support the polygenic nature of schizophrenia and the threshold model for its development. The results also show the effectiveness of VarScan2 to identify 'the needle in the hay stack' that may cause schizophrenia, specifically in the two patients. It offers a proof of principle for assessment of the genetic etiology of complex disorders where discordance of monozygotic twins is an established phenomenon.
Authors: Derrick E Wood; James R White; Andrew Georgiadis; Beth Van Emburgh; Sonya Parpart-Li; Jason Mitchell; Valsamo Anagnostou; Noushin Niknafs; Rachel Karchin; Eniko Papp; Christine McCord; Peter LoVerso; David Riley; Luis A Diaz; Siân Jones; Mark Sausen; Victor E Velculescu; Samuel V Angiuoli Journal: Sci Transl Med Date: 2018-09-05 Impact factor: 17.956
Authors: Miller Huang; Jignesh Tailor; Qiqi Zhen; Aaron H Gillmor; Matthew L Miller; Holger Weishaupt; Justin Chen; Tina Zheng; Emily K Nash; Lauren K McHenry; Zhenyi An; Fubaiyang Ye; Yasuhiro Takashima; James Clarke; Harold Ayetey; Florence M G Cavalli; Betty Luu; Branden S Moriarity; Shirin Ilkhanizadeh; Lukas Chavez; Chunying Yu; Kathreena M Kurian; Thierry Magnaldo; Nicolas Sevenet; Philipp Koch; Steven M Pollard; Peter Dirks; Michael P Snyder; David A Largaespada; Yoon Jae Cho; Joanna J Phillips; Fredrik J Swartling; A Sorana Morrissy; Marcel Kool; Stefan M Pfister; Michael D Taylor; Austin Smith; William A Weiss Journal: Cell Stem Cell Date: 2019-06-13 Impact factor: 24.633
Authors: Wei Zhang; Taylor A Williams; Ankur S Bhagwath; Jared S Hiermann; Craig D Peacock; D Neil Watkins; Peiguo Ding; Jason Y Park; Elizabeth A Montgomery; Arlene A Forastiere; Chunfa Jie; Brandi L Cantarel; Thai H Pham; David H Wang Journal: Lab Invest Date: 2019-07-10 Impact factor: 5.662
Authors: Shirley Chu; Zachary L Skidmore; Jason Kunisaki; Jason R Walker; Malachi Griffith; Obi L Griffith; Jeffrey N Bryan Journal: PLoS One Date: 2021-02-08 Impact factor: 3.240