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. 2021 Dec 3;3(1):100075.
doi: 10.1016/j.xhgg.2021.100075. eCollection 2022 Jan 13.

Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders

Michael A Levy  1 Haley McConkey  1 Jennifer Kerkhof  1 Mouna Barat-Houari  2 Sara Bargiacchi  3 Elisa Biamino  4 María Palomares Bralo  5 Gerarda Cappuccio  6   7 Andrea Ciolfi  8 Angus Clarke  9 Barbara R DuPont  10 Mariet W Elting  11 Laurence Faivre  12   13 Timothy Fee  10 Robin S Fletcher  10 Florian Cherik  14   15 Aidin Foroutan  16 Michael J Friez  10 Cristina Gervasini  17 Sadegheh Haghshenas  16 Benjamin A Hilton  10 Zandra Jenkins  18 Simranpreet Kaur  19 Suzanne Lewis  20 Raymond J Louie  10 Silvia Maitz  21 Donatella Milani  22 Angela T Morgan  23 Renske Oegema  24 Elsebet Østergaard  25   26 Nathalie Ruiz Pallares  2 Maria Piccione  27 Simone Pizzi  8 Astrid S Plomp  28 Cathryn Poulton  29 Jack Reilly  16 Raissa Relator  1 Rocio Rius  30   31 Stephen Robertson  18 Kathleen Rooney  1   16 Justine Rousseau  32 Gijs W E Santen  33 Fernando Santos-Simarro  5 Josephine Schijns  34 Gabriella Maria Squeo  35 Miya St John  23 Christel Thauvin-Robinet  12   13   36   37 Giovanna Traficante  3 Pleuntje J van der Sluijs  33 Samantha A Vergano  38   39 Niels Vos  40 Kellie K Walden  10 Dimitar Azmanov  41 Tugce Balci  42   43 Siddharth Banka  44   45 Jozef Gecz  46   47 Peter Henneman  28 Jennifer A Lee  10 Marcel M A M Mannens  28 Tony Roscioli  48   49   50   51 Victoria Siu  42   43 David J Amor  23 Gareth Baynam  29   29   52 Eric G Bend  53 Kym Boycott  54   55 Nicola Brunetti-Pierri  6   7 Philippe M Campeau  32 John Christodoulou  19 David Dyment  56 Natacha Esber  57 Jill A Fahrner  58 Mark D Fleming  59 David Genevieve  15 Kristin D Kerrnohan  54   60 Alisdair McNeill  61 Leonie A Menke  34 Giuseppe Merla  35   62 Paolo Prontera  63 Cheryl Rockman-Greenberg  64 Charles Schwartz  10 Steven A Skinner  10 Roger E Stevenson  10 Antonio Vitobello  12   36 Marco Tartaglia  8 Marielle Alders  28 Matthew L Tedder  10 Bekim Sadikovic  1   16
Affiliations

Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders

Michael A Levy et al. HGG Adv. .

Abstract

Overlapping clinical phenotypes and an expanding breadth and complexity of genomic associations are a growing challenge in the diagnosis and clinical management of Mendelian disorders. The functional consequences and clinical impacts of genomic variation may involve unique, disorder-specific, genomic DNA methylation episignatures. In this study, we describe 19 novel episignature disorders and compare the findings alongside 38 previously established episignatures for a total of 57 episignatures associated with 65 genetic syndromes. We demonstrate increasing resolution and specificity ranging from protein complex, gene, sub-gene, protein domain, and even single nucleotide-level Mendelian episignatures. We show the power of multiclass modeling to develop highly accurate and disease-specific diagnostic classifiers. This study significantly expands the number and spectrum of disorders with detectable DNA methylation episignatures, improves the clinical diagnostic capabilities through the resolution of unsolved cases and the reclassification of variants of unknown clinical significance, and provides further insight into the molecular etiology of Mendelian conditions.

Keywords: Clinical diagnostics; DNA methylation; Epigenetics; Episignatures; Neurodevelopmental disorders.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Methylation differences of probes used for episignatures Methylation differences between cases and controls for the microarray probes that make up each episignature for the newly identified and previously reported episignatures. Red lines indicate mean methylation for each episignature. Asterisk indicates new episignatures and/or those that have not previously been included in the multiclass classifier.
Figure 2
Figure 2
Gene region- or variant-specific sub-signatures (A) The last exon of ARID1A and ARID1B shown with the location of seven variants in the c.6200 region colored by whether they match the c.6200 episignature or not. (B and C) MDS (B) and hierarchical clustering (C) plots of the seven samples showing that the four central samples have a matching episignature, while the outer three cluster with controls. For hierarchical clustering plots, each row represents one microarray probe, and each column represents one sample. (D) Gene diagram of SMARCA4 (NM_001128849.1) showing the location of the three c.2656A>G variants in exon 19 (red arrowhead). The five horizontal gray bars indicate the locations of protein domains: QLQ, HSA, helicase ATP-binding, helicase C-terminal, and bromodomain. (E and F) MDS (E) and hierarchical clustering (F) showing that the three CSS4 samples with the above variant cluster separately from controls and from other BAFopathy samples. (G) Protein diagram of CREBBP/EP300 showing the location of protein domains (gray boxes) and intrinsically disordered (ID) domains (numbered). (H and I) MDS (H) and hierarchical clustering (I) showing the MKHK_ID4 samples clustering separately from controls and from other MKHK samples.
Figure 3
Figure 3
Identifying episignatures to distinguish between closely related syndromes Hierarchical clustering and MDS plots are shown for each episignature. For hierarchical clustering plots, each row represents one microarray probe, and each column represents one sample. (A and B) ARTHS probe selection using only ARTHS and control samples. (C and D) ARTHS probe selection when GTPTS and SBBYSS samples are included as controls. (E and F) The previously reported RSTS (RSTS1/RSTS2 combined) episignature. (G and H) The RSTS1 episignature generated by including RSTS2 samples as control. (I and J) the RSTS2 episignature generated by including RSTS1 samples as control.
Figure 4
Figure 4
Support vector machine-based classifiers for concurrent episignature detection (A) Each of the 19 new episignatures were evaluated using 4-fold cross-validation. For each fold, a different 25% of samples were used for testing (blue), and the remaining 75% of samples were used for training (gray). The case samples for each episignature are shown in red. The eight testing samples referenced in the text are labeled. (B) The final classifiers for all 57 episignatures. The case samples for each episignature are shown in red, and all other samples are in black. Non-case RSTS samples (for example, RSTS1 samples in the RSTS2 column) are in blue. Arrowheads indicate the two GADEVS samples with high BAFopathy scores.
Figure 5
Figure 5
Screening unresolved cases Samples with MVP scores greater than 0.5 were further assessed by unsupervised clustering plots. Hierarchical clustering and MDS plots are shown for each case. For hierarchical clustering plots, each row represents one microarray probe, and each column represents one sample. (A) Sample Unresolved_1, a previously unresolved case that matches the MKHK_ID4 episignature. (B) Sample Unresolved_2, a previously unresolved case that matches the LLS episignature. (C) Sample Unresolved_3, a previously unresolved case that matches the VCFS episignature.

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