Single-gene diseases among complex neuropsychiatric disorders and genetic complexity in supposed single- gene neurodevelopmental diseases Atsushi Takata Department of Human Genetics, Yokohama City Univ. & RIKEN Center for Brain Science 04/17/19 PSTC Japan Safety Biomarker Conference@RIKEN IMS
Current status of biomarker studies for neuropsychiatric disorders There have been extensive efforts to identify biomarkers… However, this work has failed to deliver markers that can distinguish reliably between diagnoses and has similarly failed to identify disease subgroups. Currently, there are no biomarkers in routine clinical use. O'Donovan and Owen, Nature Medicine 2016 I think we need to rely on sths most robust. Genetic variation that never change since one’s birth (with very few exceptions) -> One of the most robust biomarkers
Genetic studies of neuropsychiatric disorders Common variants vs. Rare variants Genome-wide association study (GWAS) Ripke et al. Nature 2014 McDonald-McGinn et al. 2015 • • Only found in up to 1% of SCZ. >100 genome-wide significant • Increase the risk >20 times. (P<5x10 -8 ) schizophrenia (SCZ) loci • Allele frequency in the general identified. • population≈0 (extremely rare). Each variant increases the risk up • May have a certain diagnostic value. to 1.2 times. • • Usually arises as de novo . May have a limited diagnostic value.
De novo mutations (DNMs) and neuropsychiatric disorders Individually rare, Next generation sequencing has but collectively common enabled comprehensive analysis • 74 de novo SNVs (single nucleotide variants) per diploid genome on average. • 1 DNM per diploid exome (all protein coding exons) Veltman et al. Nature Reviews Genetics 2012 Bamshad et al. Nature Reviews in Genetics 2011 Epidemiological data indicate a role of DNMs in neuropsychiatric disorders • Paternal age correlates risk of autism spectrum disorder (ASD), SCZ etc. • Consistent prevalence despite the reduced reproduction fitness. Kong et al., Nature 2014
~2,000 quads (proband, unaffected sib and healthy parents) ~500 trios (proband and healthy parents) Iossifov et al., Nature 2014 Likely gene disruptive ( LGD : nonsense, splice site and frameshift; also referred to as loss-of-function [ LOF ]) DNMs are especially enriched in ASD cases when compared with unaffected siblings.
2,270 trios, 1,601 cases and 5,937 controls 22 autosomal genes with FDR<0.05 De Rubeis et al. Nature 2014
Integrative analyses of DNMs in ASD (Total N of trios = 4,244) Takata et al. Cell Reports 2018
Gene-based analysis of the combined DNM dataset 61 genes significantly enriched for damaging (LOF or deleterious missense) DNMs after multiple testing correction Takata et al. Cell Reports 2018
Comparison of the results with or without our new dataset Takata et al. Cell Reports 2018 An analysis of a few hundreds of new trios contributes to identification of ten new genes
Of these, ANKRD11 MED13L GABRB1 PPP2R5D DDX3X ->known NDD genes (but with limited evidence as ASD genes) The other genes, ATP2B2 GGNBP2 MCM6 AGO1 ATP1A3 -> co-expressed genes are significantly enriched for known ASD genes Takata et al. Cell Reports 2018
• Diagnostic single-gene rare variants can be identified in >1% of ASD. • Copy number variants and mutations in genes responsible for Mendelian disorders characterized with ASD and other symptoms (i.e. syndromic ASD) explain another >4%. • On the other hand, these rare variants explains a small proportion of liability. de la Torre-Ubieta et al., Nature Medicine 2016
DNMs in schizophrenia 1,043 ASD trios 1,021 SCZ trios 731 control trios Takata et al., Neuron 2016 2,541 SCZ trios 2,216 control trios Howrigan et al., bioRxiv 2018
Enrichment of LOF DNM in SETD1A (p = 2.4x10 −6 ), encoding H3K4 methyltransferase Takata et al., Neuron 2014 Singh et al., Nature Neuroscience 2016 The only gene that surpassed the exome-wide significance (0.05/20,000 = 2.5x10 -6 )
Not only for discovery of diagnostic variants -analysis of properties of genes hit by damaging DNMs in ASD Takata et al. Cell Reports 2018
Screening of compounds globally down-regulating DNM target genes With CMAP (Connectivity Map) data By DNENRICH (that considers gene sizes DNA topoisomerase inhibitors implicated in etc.) (Fromer et al., Nature 2014) ASD (King et al. Nature 2013) Most established maternal risk factor of ASD (Christensen et al. JAMA 2013) Takata et al. Cell Reports 2018
Screening of compounds globally up-regulating DNM target genes (in cell lines) GO enriched among the genes All of these are cardiac upregulated by cardiac glycosides glycosides , used for treatment of cardiac failure -> Previously unknown effect on regulation of gene transcription Takata et al. Cell Reports 2018
SNP-based genetic correlations between NDD (6,987 cases and 9,270 controls) against other traits. Common-variant risk was not significantly different between individuals with and without a known protein-coding diagnostic variant, which suggests that common variant risk affects patients both with and without a monogenic diagnosis. Niemi et al., Nature 2018
Enrichment of LOF DNM in SETD1A (p = 2.4x10 −6 ), encoding H3K4 methyltransferase Takata et al., Neuron 2014 Analysis of heterozygous Setd1a KO mice Mukai et al., bioRxiv 2019
Phenotypic abnormalities in Setd1a +/- mice Altered short-term synaptic plasticity (greater depression of fEPSP responses) Morphological changes of axons and spines Specific deficits in working memory (delayed non-match to sample T-maze task ) Mukai et al. bioRxiv 2019
Postnatal restoration of Setd1a expression Mukai et al. bioRxiv 2019
Possibly too simple working hypothesis H3K4me ↓ → Setd1A KO H3K4 demethylase Histone demethylase inhibitors There was compelling overlap between LSD1 and Setd1a bound regions (1,137/1,178) LSD1 = lysine-specific demethylase ≠ lysergic acid diethylamide Mukai et al. bioRxiv 2019
Summary • Single-gene diagnostic rare variants with a large effect size can be identified in genetically complex neuropsychiatric disorders such as ASD and SCZ. • On the other hand, comprehensive analysis of rare and common variants highlights that even among supposed single-gene NDD there is considerable genetic complexity. • While there is substantial genetic complexity, a simple intervention can reverse SCZ-related phenotypes in a mouse model of SCZ with Setd1a deficiency. https://gcn.com/articles/2016/04/07/simple-solutions.aspx
DEE URV paper Mitsuko Nakashima Rina Takahashi Hirotomo Saitsu Hiroko Ikeda Takeshi Mizuguchi Tokito Yamaguchi ASD DNM paper Satomi Mitsuhashi Kazuki Tsukamoto Noriko Miyake Ayumi Matsumoto Yukitoshi Takahashi Shinsaku Yoshitomi Yoshinori Tsurusaki Saoko Takeshita Nobuhiko Okamoto Taikan Oboshi Ryoko Fukai Jun Tohyama Hitoshi Osaka Katsumi Imai Satoko Miyatake Tomoko Saikusa Kazuyuki Nakamura Tomokazu Kimizu Eriko Koshimizu Toyojiro Matsuishi Jun Tohyama Yu Kobayashi Itaru Kushima Takumi Nakamura Kazuhiro Haginoya Masaya Kubota Takashi Okada Takashi Tsuboi Saoko Takeshita Hirofumi Kashii Mako Morikawa Tadafumi Kato Ichiro Kuki Shimpei Baba Yota Uno Toshifumi Suzuki Tohru Okanishi Mizue Iai Kanako Ishizuka Hirotomo Saitsu Tomohide Goto Ryutaro Kira Kazuhiko Nakamura Mitsuko Nakashima Masayuki Sasaki Munetsugu Hara Masatsugu Tsujii Takeshi Mizuguchi Yasunari Sakai Masayasu Ohta Takeo Yoshikawa Fumiaki Tanaka Noriko Miyake Yohane Miyata Tomoko Toyota Norio Mori Satoko Miyatake Rie Miyata Nobuhiko Okamoto Norio Ozaki Naomi Tsuchida Jun-ichi Takanashi Yoko Hiraki Naomichi Matsumoto Kazuhiro Iwama Jun Matsui Ryota Hashimoto Gaku Minase Kenji Yokochi Yuka Yasuda Setd1a KO mouse paper Futoshi Sekiguchi Masayuki Shimono Shinji Saitoh Jun Mukai Atsushi Fujita Masano Amamoto Kei Ohashi Enrico Cannavo Eri Imagawa Rumiko Takayama Yasunari Sakai Ziyi Sun Eriko Koshimizu Shinichi Hirabayashi Shouichi Ohga Gregg Crabtree Yuri Uchiyama Kaori Aiba Toshiro Hara Anastasia Diamantopoulou Kohei Hamanaka Hiroshi Matsumoto Mitsuhiro Kato Pratibha Thakur Chihiro Ohba Shin Nabatame Kazuyuki Nakamura Chia-Yuan Chang Toshiyuki Itai Takashi Shiihara Aiko Ito Yifei Cai Hiromi Aoi Mitsuhiro Kato Chizuru Seiwa Stavros Lomvardas Ken Saida Naomichi Matsumoto Emi Shirahata Bin Xu Tomohiro Sakaguchi on behalf of the DEEPEN Hitoshi Osaka Joseph A. Gogos Kouhei Den Consortium and many others including all study participants
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