What channelopathies present so early, and why? Or … why is there an age-dependent presentation for channelopathy diseases? James C. Perry MD Electrophysiology Adult Congenital Heart Program UC San Diego/Rady Children ’ s Hospital San Diego, California
Spoiler Alert! I cannot answer these questions
Disclosures • I have no formal genetics training or do lab-based genetic science • I was not clinically trained in the current era of genomics – thanks to Mark Keating et al, I’ve had to relearn and try to keep up Science. 1991 May 3;252(5006):704-6. Linkage of a cardiac arrhythmia, the long QT syndrome, and the Harvey ras-1 gene. Keating M, Atkinson D, Dunn C, Timothy K, Vincent GM, Leppert M • BUT!!! I’m old enough to see a big picture and ask questions • Best outcome – this topic prompts some discussion
Start of the Big Picture from the clinic: The first discussion of “what’s channelopathy”… I draw pictures
Parent response: after the first discussion of channelopathy… • “OK, I get it. But why doesn’t the bad stuff happen ALL THE TIME?” • “And why am I Meds fine with it, but my Pacemaker ICD child was not?” Restrictions
The basic question: Why aren’t these channelopathy mutations LETHAL , from BIRTH (or earlier) , ALL of the time?
Crude first hint?: Age-Dependent Clinical Disease Presentation One of the more common issues we deal with: WPW and SVT We also don’t know why this happens early, then later.
Another age dependent change: Hemoglobin…
LQT “events”: LQT Type vs Age ? Circulation Journal Vol.80, March 2016
Early age LQT: Genotype negative, phenotype positive NOW - Calmodulin mutations cause LQTS Boczek et al. Circ CV Genetics 2016
Age dependent “Events”: LQT 1 and 2 Gender vs Age LQT1 LQT2 Circulation Journal Vol.80, March 2016
Age-dependent “Events”: LQT 1 Gender, QTc, Mutation Location vs Age
Age-dependent “Events”: LQT 2 Gender, Mutation Location vs Age
Summary: Genotype, age onset Circulation Journal Vol.80, March 2016
Role of “Founder” mutations vs Non-Founder mutations (small population, less genetic variability) Same mutation, but shorter QT, less syncope, other inherited genetic Founder factors?
Fetal DOL 1 5 mo 7 yrs 8 yrs 13 yrs 14 mo 4 yrs Fetal AVB Heterotaxy** EKG: Long ST Tri atresia EKG: Long ST PS, hypo RV* Pre-op EKG DORV WES for FTT Ebstein, VSD** Pre-op EKG incidental PDA Stress EKG EKG with ASD, hypo arch CHD care Syncope, TdP IAA, DiGeorge arrhythmia Syncope, TdP PO TOF LQT2 LQT1 LQT1 LQT1 LQT1 LQT1 (+LQT2 VUS) LQT2 LQT2 LQT2 * Known positive family history; ** Positive cascade screening after LQTS diagnosis Ebrahim et al (submitted 2016)
LQT1 LQT2 LQT3 CALM TS BrS CPVT SVT Prenatal/NB 1 5 8 12 18 30 40+
Same mutation Not the same “disease” (from the patient’s perspective)
“So, what about my child?” “ Probability of event ” is not very patient-specific…
Incomplete Penetrance & Variable Expressivity • Penetrance – same mutation, do you manifest the disease • Expressivity – how severe are your clinical aspects of the disease • Incomplete penetrance is the general rule in channelopathies – “LQTS without a long QT”, – “what on Earth is Brugada Syndrome this week?” • Is there any evidence for age-dependent variability in penetrance and expressivity? – Longitudinal changes in individual QTc by age – Severity of events by age (faint vs TdP)
Are there age-dependent (“dynamic”) regulators of gene expression that affect channelopathies?
Where to look? other controls of gene expression • SNPs, which allele? • “second hit”; SNP or additional pathogenic mutation • Other common variants (e.g. NOS1AP and QT interval) • Environmental factors: epigenetics, ANS • Cardiac anatomy, Embryology • What of these other factors may be age- dependent?
“Two hits” Common variants that affect QT 2013
Based on clinical LQT data, Penetrance and Expressity change with Age therefore - Static vs Dynamic Genomics Webster. Can J Cardiol 2013
Epigenetic (dynamic) modifiers of gene expression 1 - DNA methylation – generally decreases gene transcription 2 - Histone acetylation – generally increases gene transcription 3 - Long non-coding RNAs – can decrease or increase transcription
Dynamic DNA Code 1- DNA methylation: “aging” o More a cell divides, the more opportunities for DNA methylation o One-way process, Stem cell to differentiated cell o Methyl groups added to DNA, 2 of 4 nucleotides can be methylated Cytosine and adenine (prokaryotes) In humans, at locations where cytosine followed by guanine (CpG) o Generally suppresses endogenous retroviral genes that are acquired over time o If in gene promoter region, DNA methylation decreases gene transcription o Generally, DNA methylation decreases with age o (“Horvath’s epigenetic clock”) o Between 5-10 years of age, environmental exposures change methylation
Dynamic DNA Code Genomic imprinting o 2 copies of almost all genes, one from each parent one gene out, other compensates o Small number of genes, one copy ON one copy OFF – “imprinting” o In utero exposure to malnutrition – long term risks of CV, DM, obesity, cancers o Not known if this affects pertinent CV-related genes in an age- dependent fashion
2 - Histones Age-dependent regulation: change of fetal to adult hemoglobin via chromatin looping due to histone acetylation Li, Cell 2006
3 - Long non-coding RNAs o Long noncoding RNAs (lncRNAs ) are ≥200 nt long, abundant class of RNAs that are transcribed in complex patterns from both intergenic and intronic regions of mammalian genome o Age-dependent expression of lnc RNAs found in brain development and aging o MicroRNAs have been implicated in virtually all areas of mammalian homeostatic gene regulation, to lower the expression of a shared target mRNA. o Disruption of miRNA function has been causally linked to a variety of cardiovascular diseases (CVDs) that rise with advancing age.
Dynamic DNA Expression Exogenous triggers – clinical arrhythmias Heat/fever Stress Electrolyte abnormalities Hypoxia
Exogenous triggers Different triggers by age: Young – adrenergic Older - secondary Different triggers by age and LQT subtype Sakaguchi et al. J CV EP 2008
Autonomic nervous system versus age • HR decreases with age • PR prolongs with age • Respiratory sinus arrhythmia starts around age 5- 10 years • Atrial and ventricular ectopy in newborns then not again until 7-8 years • Changes in HF (parasymp) and LF (symp/para) in spectral HR analysis with age and disease states
Cumulative effect Regulation of gene expression Triggers Ectopy DYNAMIC Fever Stress Hypoxia Autonomic changes Postural changes Pt AGE SNPs Epigenetics STATIC DNA methylation Patient with Physiology channelopathy Histone acetylation lnc RNAs Embryology
Why now??? Cumulative Developmental Arrhythmogenesis genetic anatomy & “environment” susceptibility physiology embryology ANS SUBSTRATE TRIGGERS “modifiers” X X X X X X “programmed response to cellular X epigenetics, dilation, “ON/OFF” changes” HR, ERP microbiome? ectopy X X X AGE X Threshold X X for an X X X X EVENT X X X X X X X X X
Patient and age-specific therapies? • If there’s risk, there’s “no risk” too – – No therapy and no restrictions for long stretches of time, by specific pt age? • Intervene by age depending on: – Specific mutation – Age-dependent Epigenetic modification – Target the modifier: methylation, acetylation, purposeful environmental manipulation – If late age brings about lower risk, then induce a more “mature” gene expression?
We have seemingly isolated facts about “risk” • QT type – LQT 1>2>3 – LQT1: Male>Female risk at all ages – LQT2: Female risk increases at puberty – CALM – under 1 year old presentation (f/u?) • QT duration: >500 always more risk • Mutation: C-loop/pore > non • Triggers – LQT1: exercise – LQT2: emotion/noise – LQT3: rest/sleep – Older pt: 2 ° factors: low K+, AVB, drugs
Sounds like time for a “big data” opportunity • Genomic Medicine Consortium: – Sanford Children's – Children's Hospital Los Angeles – Rady Children's Hospital, San Diego – Children's Hospital Colorado – Children's Hospitals and Clinics of Minnesota – Banner Children's Tucson • Need individual longitudinal data • Public access • Focus efforts on age-dependent epigenetics, microbiome (HMP)? • Build a test algorithm: current age, gender, mutation, epigenetic factors, age at presentation of prior untreated subjects, environmental exposures
we have a lot to learn…
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